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A frog’s story of surviving a fungal pandemic offers hope for other species

Evolving immunity to the Bd fungus and a reintroduction project saved a California frog. The key to rescuing other species might be in the frog’s genes.

Freeze-drying turned a woolly mammoth’s DNA into 3-D ‘chromoglass’

The last woolly mammoths offer new clues to why the species went extinct, more stories in genetics.

Child sacrifices at famed Maya site were all boys, many closely related

DNA analysis shows victims in one underground chamber at Chichén Itzá included twins, perhaps representing mythological figures.

Horses may have been domesticated twice. Only one attempt stuck

Genetic evidence suggests that the ancestors of domestic horses were bred for mobility about 4,200 years ago.

Scientists are fixing flawed forensics that can lead to wrongful convictions

People have been wrongly jailed for forensic failures. Scientists are working to improve police lineups, fingerprinting and even DNA analysis.

Thomas Cech’s ‘The Catalyst’ spotlights RNA and its superpowers

Nobel Prize-winning biochemist Thomas Cech’s new book is part ode to RNA and part detailed history of the scientists who’ve studied it.

50 years ago, chimeras gave a glimpse of gene editing’s future

Advances in gene editing technology have led to the first successful transplant of a pig kidney into a human.

The largest known genome belongs to a tiny fern

Though 'Tmesipteris oblanceolata' is just 15 centimeters long, its genome dwarfs humans’ by more than 50 times.

Here’s why some pigeons do backflips

Meet the scientist homing in on the genes involved in making parlor roller pigeons do backward somersaults.

A genetic parasite may explain why humans and other apes lack tails

Around 25 million years ago, a stretch of DNA inserted itself into an ancestral ape’s genome, an event that might have taken our tails away.

Ancient viruses helped speedy nerves evolve

A retrovirus embedded in the DNA of some vertebrates helps turn on production of a protein needed to insulate nerve cells, aiding speedy thoughts.

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A Freeze-Dried Woolly Mammoth Has Yielded the First Ever Fossilized Chromosomes

For the first time, researchers have reconstructed the 3D structure of ancient genetic material, in this case from a 52,000-year-old mammoth

Saima S. Iqbal

Out of Sight, ‘Dark Fungi’ Run the World from the Shadows

The land, water and air around us are chock-full of DNA from fungi that scientists can’t identify

Cody Cottier

Tiny Fern Has World’s Largest Genome

A small South Pacific fern boasts more than 50 times as many base pairs as the human genome

Max Kozlov, Nature magazine

Revolutionary Genetics Research Shows RNA May Rule Our Genome

Scientists have recently discovered thousands of active RNA molecules that can control the human body

Philip Ball

Stolen Bacterial Genes Helped Whiteflies to Become the Ultimate Pests

Rather than relying on bacteria, whiteflies cut out the middleman and acquired their own genes to process nitrogen

Rohini Subrahmanyam

How Sugar Gliders Got Their Wings

Several marsupial species, including sugar gliders, independently evolved a way to make membranes that allow them to glide through the air

Viviane Callier

Unraveling the Secrets of This Weird Beetle’s 48-Hour Clock

New research examines the molecular machinery behind a beetle’s strange biological cycle

Andrew Chapman

Forensic Genealogy Offers Families the Gift of Closure

The forensic scientist’s toolbox is growing thanks to creative methods that generate reliable leads, analyze evidence, identify suspects and solve cold cases

Nancy La Vigne

Ancient Malaria Genome from Roman Skeleton Hints at Disease’s History

Genetic information from ancient Roman remains is helping to reveal how malaria has moved and evolved alongside people

Tosin Thompson, Nature magazine

Rare Brown Panda Mystery Solved after 40 Years

Chinese researchers have found the gene responsible for the brown-and-white fur of a handful of giant pandas

Xiaoying You, Nature magazine

What Do You Mean, Bisexual People Are ‘Risk-Taking’? Why Genetic Studies about Sexuality Can Be Fraught

A recent study on risk-taking and bisexuality made assumptions that some experts don’t agree with.

Tulika Bose, Lauren Leffer, Timmy Broderick

How Humans Lost Their Tails

A newly discovered genetic mechanism helped eliminate the tails of human ancestors

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Collaboration and teamwork ensure that our genomic advances improve health for all humans., to accelerate genomics research, we support scientists at public and private institutions around the world..

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Spark scientific curiosity and engage a diverse community of learners., the more you know, the better decisions you can make about your health., about the national human genome research institute.

At NHGRI, we are focused on advances in genomics research. Building on our leadership role in the initial sequencing of the human genome, we collaborate with the world's scientific and medical communities to enhance genomic technologies that accelerate breakthroughs and improve lives. By empowering and expanding the field of genomics, we can benefit all of humankind.

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Masks Strongly Recommended but Not Required in Maryland, Starting Immediately

Due to the downward trend in respiratory viruses in Maryland, masking is no longer required but remains strongly recommended in Johns Hopkins Medicine clinical locations in Maryland. Read more .

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Department of Genetic Medicine

The human genome contains about 20,000 protein coding genes distributed over 23 pairs of chromosomes (22 pairs of autosomes and the sex chromosomes, X and Y). Our genes provide the code of life…..a blueprint for the processes that program every aspect of an individual’s development from a single fertilized egg at the initiation of life to the trillions of cells that make up an adult.  

Our genes also encode the mechanisms that maintain normal physiology in an ever-changing environment. The information within genes is determined by the linear sequence of four building blocks, G, A, T and C, which are called nucleotides. These components are arranged in long chain-like molecules that intertwine, forming a double helix that is about two meters in length. All of this is packaged into the nucleus of each of our cells, themselves thousands of times smaller than a raindrop.

Our genetic machinery is the product of more than a billion years of evolution. Understanding this marvelous feat of biology and how it functions in health and disease is a central goal for scientists in the Department of Genetic Medicine and requires a multi-faceted research program.

World Leaders in Genetics Research

Johns Hopkins scientists have long been leaders in medical genetics research. The field essentially began in the 1950s with renowned scientist Victor McKusick, who is considered the “father of medical genetics” and led the world in identifying thousands of inherited diseases and mapping the responsible genes to specific locations on our chromosomes. Legendary geneticist Barton Childs is best known for his quest to get physicians to think about disease in the context of genetics. Nobel laureates Daniel Nathans and Hamilton Smith discovered molecular scissors called restriction enzymes, which revolutionized genetic research by providing a way to map our genome and isolate genetic material and insert it into DNA. These techniques, used continuously by laboratories across the world since Nathan and Smith’s discoveries in the 1960s enabled molecular biology and was a precursor is to sequencing the human genome and to the recently identified, targeted gene-cutting tool, CRISPR/CAS9.

More on the history of the Department of Genetic Medicine

Moving Genetics Research Forward

With  innovations in genome sequencing over the last two decades, scientists have become very efficient at reading genetic material. Now, researchers are focusing on clinical applications of these advances including interpreting our genetic blueprints, relating these coded instructions to human disease and developing new ways to identify, treat and prevent disease.

The overarching goal of the Department of Genetic Medicine is to integrate genetics into all of medicine. In addition to genetic medicine scientists who study the fundamental links between our genes and disease, the Department has a robust clinical service which operates seven patient clinics along with providing inpatient and outpatient services.

Thus, the Department of Genetic Medicine provides a highly collaborative, innovative environment where scientists and physicians combine their knowledge to apply basic science discoveries to clinical care.

Research Areas

Faculty focus on areas that include:

• Discovering the genetic basis of human disease
• Research on the discovery and characterization of the genetic variants and genes responsible for a broad variety of rare disorders that arise from mutations or abnormalities in a single gene, or “Mendelian” disorders
• Enumerating and understanding combinations of genetic variants, or “the genetic architecture” that in aggregate determine individual risk for complex traits, such as cardiovascular disease, diabetes and neuropsychiatric disease 
• Developing animal models of human disease to further our understanding of how genetic variation interacts with environmental variable to produce disease and to explore new treatments for these disorders
• Uncovering the regulatory lexicon of the genome, the molecular mechanisms by which the activity of genes are turned on and off
• Exploring epigenetics, the interactions between our genes and the environment, and how disruptions in the “epigenome” contribute to health and disease
• Creating innovative new treatments and diagnostics for genetic disease
• Development and implementation of new genome-wide association analytical tools
• Research on autism spectrum disorders
• Understanding human aging and longevity
• Determining the effect of common and rare gene variants that contribute to cystic fibrosis
• Vaccine design
• Comparative and evolutionary genomics
• Molecular mechanisms of how the body regulates oxygen
• SARS-CoV2 research: Using genetics to understanding the severity, complications and risk factors for worse outcomes of COVID-19 illness

Research and Clinical Centers Collaborate

At the Department of Genetic Medicine, we take the power of research discoveries at Johns Hopkins and apply this knowledge to patients evaluated in our inpatient and outpatient clinics at The Johns Hopkins Hospital and its affiliates. As part of this effort, we have expanded the size and scope of the services offered by Johns Hopkins Genomics , (JHG) one of the world’s largest centers for DNA genotyping and sequencing. JHG is a collaborative effort between the Departments of Genetic Medicine and Pathology to provide a variety of DNA genotyping and sequencing services, both research and clinical, to the patients, physicians and scientists of Johns Hopkins Medicine.

The Department of Genetic Medicine also houses research centers with significant funding from the National Institutes of Health that provide services and resources for physicians and researchers at Johns Hopkins and around the world.

Thus, Department of Genetic Medicine researchers and clinicians, work to move human genetics and its multi-faceted and expanding applications to medicine forward by providing a collaborative and dynamic culture of innovative research and clinical care. 

Three Genetics Professors Receive Prestigious Awards, Funding Vital Areas of Research

Lars Steinmetz, PhD, professor of genetics, appointed new chair of the department of genetics Learn More

Polly Fordyce Receives 2024 President’s Award for Excellence Through Diversity. Learn More

Genetics Students Develop Critical Course on Genetics, Ethics, and Society Learn More

Amir Bahmani honored with prestigous Walter J. Gores Award for excellence in teaching. Learn more

Our bacteria are more personal than we thought, Stanford Medicine-led study shows Learn More

Researchers dial in on genetic culprit of disease Learn More

Global Health Equity Scholarship recipient Dylan Maghini conducts microbiome research with her team in South Africa. Learn more about her research

Snyder Lab and collaborators publish the first spatial map of the intestine at the single cell level. Learn More

Genetics department news.

Three Stanford Genetics Professors Win Prestigious Awards

Nicolas Altemose, PhD 

Altemose, an assistant professor in genetics, has been named a 2024 Pew Scholar in the Biomedical Sciences. The Pew Scholars program recognizes young investigators of promise in advancing human health and supports their research. Altemose will receive $300,000 over four years to investigate how specific proteins help maintain the function of centromeres, chromosomal structures that play a key role in cell division.

Ami Bhatt, MD, PhD

The professor of hematology and of genetics has been awarded the 2024 William Dameshek Award from the American Society of Hematology. The award is for researchers no older than 50 years who have made contributions leading to a new fundamental understanding of hematology. The society is recognizing Bhatt for pioneering the development and application of genomic approaches to studying the microbiome — work that has provided the basis for improving outcomes for many human diseases.

Rogelio Hernández-López, PhD

Hernández-López, an assistant professor of bioengineering and of genetics, has been named a 2024 Pew Scholar in the Biomedical Sciences. The Pew Scholars Program recognizes young investigators of outstanding promise in science relevant to the advancement of human health and supports their independent research. Hernández-López will receive $300,000 over four years for his research into novel approaches for designing synthetic protein receptors for engineering cellular communication. 

Lars Steinmetz, PhD, professor of genetics, appointed new chair of the department of genetics

Dr. Steinmetz, the Dieter Schwarz Foundation Endowed Professor, steps into this new role as an innovative and influential genetics researcher, a successful entrepreneur, a highly productive leader of laboratories here and in Europe, and with a proven ability to facilitate productive collaborations across sites and disciplines.    Learn More

Amir Bahmani, Ph.D. has received the  Walter J. Gores Award , which is Stanford University’s highest award for excellence in teaching. It recognizes faculty and teaching staff who have made special contributions to teaching in its broadest sense, including lecturing, tutoring, advising, and discussion leading.

Dr. Bahmani is a lecturer in computational biology and genetics and director of the  Deep Data Research Center  (DDRC). Bahmani is also recognized for co-founding the course  Cloud Computing for Biology and Healthcare  and developing the  Stanford Data Ocean  project, which integrates cutting-edge technology with education.   Learn More

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

Featured on the cover of April-May Cell Host & Microbe Journal , Xin Zhou, Ph.D. fellow researchers from Snyder Lab , and colleagues from multiple universities tracked the gut, mouth, nose and skin bacteria of 86 people for as long as six years to try to gauge what constitutes a healthy microbiome. 

“We found that when you get sick with something like a cold, you have this temporary change in the microbiome; it becomes very dysregulated,”  Xin Zhou, Ph.D.  said. “With diabetes, that signature is the same in many ways except that it is long-term rather than temporary.”   Learn More

Jesse Engreitz , PhD discusses genetics underlying coronary artery disease in an interview with SCOPE. A new study co-led by researchers at Stanford Medicine and others,  published Feb. 7 in  Nature , aims to address this challenge by proposing a solution that links disease-causing DNA variants to the deleterious processes they set in motion.  Learn More

Global Health Equity Scholarship recipient Dylan Maghini conducts microbiome research with her team in South Africa.

Dylan's research focuses on the intersection between the gut microbiome and human health in a large cohort of nearly two thousand women in four countries (Burkina Faso, Ghana, Kenya, and South Africa). 

This collaborative project between Stanford University and the University of the Witwatersrand seeks to measure microbiome composition in low- and middle-income populations, identify how the microbiome is shaped by environmental and lifestyle factors, and measure associations between the microbiome and pressing human health concerns in these populations.  The project represents one of the largest population-representative gut microbiome studies in LMIC settings to date,  and is an excellent example of collaborative, equitable, and community-engaged research.  Learn more

August 2023

First Spatial Maps at the Single-Cell Level

Michael Angelo, PhD and Michael Snyder, PhD worked with Sanjay Jain, PhD,  John Hickey, PhD and collaborators to "uncover how cellular interactions reveal new ways cells can communicate with each other".

By combining cellular imaging techniques, machine learning and other methods of molecular analyses, the teams are creating a comprehensive resource for researchers to better understand all human tissue. The data collected will be publicly available through HuBMAP, enabling researchers to study tissue-specific characteristics, understand disease mechanisms, and develop automated annotation tools that identify and characterize cells.  Learn More

December 2022

Professor Polly Fordyce is the recipient of the 2023 Eli Lilly Award in Biological Chemistry.

She is being recognized for her significant contributions to biological chemistry, especially her revolutionary work on applying high throughput biochemical techniques and analyses to investigate molecular recognition. Her novel strategies have dissected quantitative relationships that govern biological function.  The work has contributed fundamental new insights into genetic variation, enzyme kinetics and thermodynamics.

October 2022

Serena Sanulli is named NIH Director's New Innovator Award Recipient.

Dr. Sanulli's lab studies genome organization across length and time scales with the long-term goal to understand how cells leverage the diverse biophysical properties of chromatin to regulate genome functions. She is the recipient of the Independent Postdoctoral Fellow Award from the program for Breakthrough Biomedical Research, the McCormick and Gabilan Faculty Fellowship, and she was recently named a Searle Scholar.

Two Key Types of Genes Identified The human genome includes millions of "enhancer" sequences that turn genes on and off—but it has been unclear which enhancers can regulate which genes. A new study led by researchers from the Engreitz Lab finds that two types of genes respond differently to enhancers, and that these responses are controlled by specific sequences in gene promoters. Link to article: https://rdcu.be/cNZxa

2022 Winners of the FNIH Lurie Prize in Biomedical Sciences Provide Powerful Contributions to Our Understanding of the Aging Process

The Foundation for the National Institutes of Health (FNIH) has named Anne Brunet, Ph.D., and Andrew Dillin, Ph.D., co-winners of the 2022 Lurie Prize in Biomedical Sciences

Neighborhood matters

While the effects of regulatory sequences on gene expression have been widely studied, evidence for the importance of genomic context has been anecdotal. The Steinmetz lab has used the SCRaMbLE system of the yeast synthetic genome for a systematic study of transcript expression from multiple genomic contexts. Long-read sequencing of rearranged test genomes now revealed features of transcriptional context that predicts altered transcript isoform expression. 

https://www.science.org/doi/10.1126/science.abg0162

February 2022

“90 Seconds with Lisa Kim”: Genome sequencing sets Guinness World Record

A new ultra-rapid genome sequencing approach developed by Stanford Medicine scientists sets the first Guinness World Record for the fastest DNA sequencing technique, producing results for one study participant in just over five hours. See the video on StanfordMed TODAY.

January 2022

Sorting cells by intracellular features

Fluorescence-activated cell (FACS) sorting has revolutionized biomedical research, giving us the ability to isolate cells according to the expression of labeled proteins. So far, however, FACS has been blind to spatial processes such as protein localization. The Seinmetz lab, in collaboration with BD Biosciences, combined ultrafast microscopy and image analysis with a flow cytometric cell sorter to unlock spatial phenotypes for high-throughput sorting applications.

https://www.science.org/doi/10.1126/science.abj3013

Genome-wide enhancer maps link risk variants to disease genes

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease 1 . Many of the underlying causal variants may affect enhancers 2 , 3 , but we lack accurate maps of enhancers and their target genes to interpret such variants. Read more...

Image credit: Zayna Sheikh

Fitbit detecting oncoming sickness 

Dr. Michael Snyder discovered that among the millions of measurements they make every day, subtle variances in a Fitbit's data could be a predictor of an oncoming illness.

Read more...

Department of Genetics COVID-19 Research

Our scientists from the Department of Genetics have launched research projects as part of the global response to COVID-19. 

Stanford Medicine scientists hope to use data from wearable devices to predict illness, including COVID-19

Researchers from Stanford Medicine and their collaborators aim to predict the onset of viral infection through data provided by wearable technology. What they need now are participants.

Full Story...

September 2018

We are bombarded by thousands of diverse species and chemicals

We are all exposed to a vast and dynamic cloud of microbes, chemicals and particulates that, if visible, might make us look something like Pig-Pen from Peanuts.

Researchers can forecast risk of deadly vascular condition from genome sequence

A new approach that distills deluges of genetic data and patient health records has identified a set of telltale patterns that can predict a person’s risk for a common, and often fatal, cardiovascular disease, according to a new study from the Stanford University School of Medicine .

Diabetic-level glucose spikes seen in healthy people

A study out of Stanford in which blood sugar levels were continuously monitored reveals that even people who think they’re “healthy” should pay attention to what they eat.

New center sets out to stop disease before it starts

At the Precision Health and Integrated Diagnostics Center, scientists turn the norms of disease research on their head, searching not for treatments but for ways to prevent disease entirely.

It’s not often that world-class scientists band together to investigate disease with no intention of curing it. Yet upward of 55 scientists at Stanford’s Precision Health and Integrated Diagnostics Center are doing just that in a push to get researchers and physicians off their heels and onto their toes in the battle against disease..

CRISPR used to genetically edit coral

In a proof-of-principle study, Stanford scientists and their colleagues used the CRISPR-Cas9 gene-editing system to modify genes in coral, suggesting that the tool could one day aid conservation efforts.

Coral reefs on the precipice of collapse may get a conservation boost from the gene-editing tool known as CRISPR, according to researchers at the Stanford University School of Medicine and their collaborators.

January 2018

Weight flux alters molecular profile

Stanford scientists have found links between changes in a person’s weight and shifts in their microbiome, immune system and cardiovascular system.

A paper describing the work was published online Jan. 17 in Cell Systems . The lead authors are Stanford postdoctoral scholars Wenyu Zhou, PhD, and Hannes Röst, PhD ; staff scientist Kévin Contrepois, PhD; and former postdoctoral scholar Brian Piening, PhD . Senior authorship is shared by Michael Snyder , PhD, professor of genetics at Stanford; Tracey McLaughlin , MD, professor of medicine at Stanford; and George Weinstock , PhD, professor and director of microbial genomics at the Jackson Laboratory , an independent, nonprofit biomedical research institution.

October 2017

Study uncovers mutation that supercharges tumor-suppressor

Cancer researchers have long hailed p53, a tumor-suppressor protein, for its ability to keep unruly cells from forming tumors. But for such a highly studied protein, p53 has hidden its tactics well.

Now, researchers at the  Stanford University School of Medicine  have tapped into what makes p53 tick, delineating a clear pathway that shows how the protein mediates anti-tumor activity in pancreatic cancer. The team’s research also revealed something unexpected: A particular mutation in the p53 gene amplified the protein’s tumor-fighting capabilities, creating a “super tumor suppressor.”

Full story...

Tissue-specific gene expression uncovered, linked to disease

Understanding how a person’s DNA sequence affects gene expression in various tissues reveals the molecular mechanisms of disease. Stanford scientists involved in the National Institutes Health’s GTEx project have published some of their insights.

John Pringle and Anne Villeneuve elected to National Academy of Sciences  

Three Stanford researchers are among the 84 newly elected members of the National Academy of Sciences .

The new members from Stanford are Dominique Bergmann , PhD, professor of biology; John Pringle , PhD, professor of genetics; and Anne Villeneuve , PhD, professor of developmental biology and of genetics. Full story..

February 2017

$10.5 million awarded to researchers to work on dna encyclopedia.

Stanford’s William Greenleaf, Michael Bassik, Michael Snyder, Jonathan Pritchard and Michael Cherry have won grants to work on the federally funded Encyclopedia of DNA Elements. Full story..

January 2017

Wearable sensors can tell when you are getting sick

New research from Stanford shows that fitness monitors and other wearable biosensors can tell when an individual’s heart rate, skin temperature and other measures are abnormal, suggesting possible illness. Full story..

Interested in applying to the Ph.D. Program?

The Ph.D. program in the Department of Genetics provides opportunities for graduate study in all major areas of modern genetics, including identification and analysis of human disease genes, molecular evolution, gene therapy, statistical genetics, application of model organisms to problems in biology and medicine, and computational and experimental approaches to genome biology.

Learn more about the Genetics Ph.D. Program here .

Department Chair

"Driven by curiosity, our mission as a leader in genetics and genomics is to engineer state-of-the-art technologies to unravel genetic complexity and transform groundbreaking research into life-changing innovations.”

Lars Steinmetz, PhD Dieter Schwarz Foundation Endowed Professor and Chair, Department of Genetics. Co-director, Stanford Genome Technology Center (SGTC) 

Incoming & Outgoing Department Chairs

Lars Steinmetz, PhD, and Michael Snyder, PhD celebrate Sndyer's extraordinary 15 years and usher in a new era with Steinmetz at the helm. 

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An underlying theme in our Department is that genetics is not merely a set of tools but a coherent and fruitful way of thinking about biology and medicine. To this end, we emphasize a spectrum of approaches based on molecules, organisms, populations, and genomes.

We provide training through laboratory rotations, dissertation research, seminar series, didactic and interactive coursework, and an annual three-day retreat of nearly 200 students, faculty, postdoctoral fellows, and research staff.

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Open to the public: Take online courses in the Stanford Genetics and Genomics Certificate to gain fundamental knowledge and a 'big picture' understanding of the cutting-edge fields of genetics, genomics and personalized medicine.

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genes • gene editing • heredity• evolution • genetic variability • phenotypic variability • horizontal gene transfer • meiosis • recombination • epigenetics • DNA repair and replication • chromosome segregation • cell division • gene regulation • development • aging • pathogenesis • cancer • disease

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Eric S. Lander is interested in every aspect of the human genome and its application to medicine.

In immune cells, X marks the spot(s)

Unusual Labmates: Meet tardigrades, the crafters of nature’s ultimate survival kit

Gene silencing tool has a need for speed

“Vaults” within germ cells offer more than safekeeping

Taking RNAi from interesting science to impactful new treatments

Q&A: Pulin Li on recreating development in the lab

Evolution in Action Series: Birth of a species

Scientists develop a rapid gene-editing screen to find effects of cancer mutations

Genomics involves the study of genes, genetics, inheritance, molecular biology, biochemistry, biological statistics and incorporates the knowledge of advanced technology, computer science and mathematics.

Genetics and Gene Expression

Genetic change, genetics research and technology, feature articles, genetic inheritance, start and stop codons, what is the expanded genetic code, applications of the expanded genetic code, genetics of inflammatory bowel disease (ibd), genetic risk associated with social anxiety, von recklinghausen disease expressivity, what is genetic anticipation, genetic regulation of fingers and toes development, genotype versus phenotype, what is cytogenetics, the role of alternative splicing in disease, the importance of genetic counseling in healthcare and medicine, latest genetics news and research.

Mechanisms of tissue shape transformation revealed through fruit fly wing development

A key question that remains in biology and biophysics is how three-dimensional tissue shapes emerge during animal development.

AACR CEO Dr. Margaret Foti honored as 2024 Beacon Award recipient for leadership in oncology

The AIM-HI Accelerator Fund today announces Margaret Foti, PhD, MD (hc), Chief Executive Officer of the American Association for Cancer Research (AACR), is selected unanimously by the 2024 Blue Ribbon Selection Committee as the recipient of the 2024 Beacon Award for Women Leaders in Oncology, from a pool of outstanding global nominees.

Novel molecular signaling pathway found to play a crucial role in maintaining the skin barrier

Our skin–the body's largest organ–provides the first line of defense against infections and many other threats to our health.

Autism and ADHD linked to neighborhood conditions

Autistic youth who were born in underserved neighborhoods are more likely to have greater attention deficit hyperactivity disorder (ADHD) symptoms than those born in communities with more resources. This is one finding of a new study led by researchers at the UC Davis MIND Institute.

NIH awards $3.5M grant to study link between traumatic brain injury and Alzheimer's

A traumatic brain injury, or TBI, is caused by a contusion to the head that may result in injury to the brain.

Radiotherapy after surgery shown to prevent breast cancer recurrence for up to 10 years

Providing radiotherapy after surgery could prevent breast cancer from returning in the same place for up to 10 years, a long-term study suggests.

Nasal microbiome composition influences how well multi-resistant bugs can thrive in the nose

Whether dangerous staphylococci survive in the nose depends on what other bacteria are present - and how they obtain iron.

Social genomics: How friends' genes impact a person's mental health

Mom always said, "Choose your friends wisely." Now a study led by a Rutgers Health professor shows she was onto something: Their traits can rub off on you – especially ones that are in their genes.

Study advances understanding of complex neurological disorder

To effectively treat a disease or disorder, doctors must first know the root cause. Such is the case for developmental and epileptic encephalopathies (DEEs), whose root causes can be hugely complex and heterogeneous. Scientists at St. Jude Children's Research Hospital demonstrated the value of DNA methylation patterns for identifying the root cause of DEEs, showing specific gene methylation and genome-wide methylation "episignatures" can help identify the genes that cause DEE. The findings were published today in Nature Communications.

Study reveals distinct genetic risk factors for influenza and COVID-19

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The road ahead in genetics and genomics

Amy l. mcguire.

1 Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, TX USA

Stacey Gabriel

2 Broad Institute of MIT and Harvard, Cambridge, MA USA

Sarah A. Tishkoff

3 Department of Genetics, University of Pennsylvania, Philadelphia, PA USA

4 Department of Biology, University of Pennsylvania, Philadelphia, PA USA

Ambroise Wonkam

5 Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

6 Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa

Aravinda Chakravarti

7 Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY USA

Eileen E. M. Furlong

8 European Molecular Biology Laboratory, Genome Biology Department, Heidelberg, Germany

Barbara Treutlein

9 Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland

Alexander Meissner

10 Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany

11 Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA USA

12 Institute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany

Howard Y. Chang

13 Center for Personal Dynamic Regulomes, Howard Hughes Medical Institute, Stanford University, Stanford, CA USA

Núria López-Bigas

14 Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain

15 Research Program on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona, Spain

16 Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain

17 Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel

Jin-Soo Kim

18 Center for Genome Engineering, Institute for Basic Science, Daejon, Republic of Korea

In celebration of the 20th anniversary of Nature Reviews Genetics , we asked 12 leading researchers to reflect on the key challenges and opportunities faced by the field of genetics and genomics. Keeping their particular research area in mind, they take stock of the current state of play and emphasize the work that remains to be done over the next few years so that, ultimately, the benefits of genetic and genomic research can be felt by everyone.

To celebrate the first 20 years of Nature Reviews Genetics , we asked 12 leading scientists to reflect on the key challenges and opportunities faced by the field of genetics and genomics.

The contributors

Amy L. McGuire is the Leon Jaworski Professor of Biomedical Ethics and Director of the Center for Medical Ethics and Health Policy at Baylor College of Medicine. She has received numerous teaching awards at Baylor College of Medicine, was recognized by the Texas Executive Women as a Woman on the Move in 2016 and was invited to give a TedMed talk titled “There is No Genome for the Human Spirit” in 2014. In 2020, she was elected as a Hastings Center Fellow. Her research focuses on ethical and policy issues related to emerging technologies, with a particular focus on genomic research, personalized medicine and the clinical integration of novel neurotechnologies.

Stacey Gabriel is the Senior Director of the Genomics Platform at the Broad Institute since 2012 and has led platform development, execution and operation since its founding. She is Chair of Institute Scientists and serves on the institute’s executive leadership team. She is widely recognized as a leader in genomic technology and project execution. She has led the Broad’s contributions to numerous flagship projects in human genetics, including the International HapMap Project, the 1000 Genomes Project, The Cancer Genome Atlas, the National Heart, Lung, and Blood Institute’s Exome Sequencing Project and the TOPMed programme. She is Principal Investigator of the Broad’s All of Us (AoU) Genomics Center and serves on the AoU Program Steering Committee.

Sarah A. Tishkoff is the David and Lyn Silfen University Associate Professor in Genetics and Biology at the University of Pennsylvania, Philadelphia, USA, and holds appointments in the School of Medicine and the School of Arts and Sciences. She is a member of the US National Academy of Sciences and a recipient of an NIH Pioneer Award, a David and Lucile Packard Career Award, a Burroughs/Wellcome Fund Career Award and an American Society of Human Genetics Curt Stern Award. Her work focuses on genomic variation in Africa, human evolutionary history, the genetic basis of adaptation and phenotypic variation in Africa, and the genetic basis of susceptibility to infectious disease in Africa.

Ambroise Wonkam is Professor of Medical Genetics, Director of GeneMAP (Genetic Medicine of African Populations Research Centre) and Deputy Dean Research in the Faculty of Health Sciences, University of Cape Town, South Africa. He has successfully led numerous NIH- and Wellcome Trust-funded projects over the past decade to investigate clinical variability in sickle cell disease, hearing impairment genetics and the return of individual findings in genetic research in Africa. He won the competitive Clinical Genetics Society International Award for 2014 from the British Society of Genetic Medicine. He is president of the African Society of Human Genetics.

Aravinda Chakravarti is Director of the Center for Human Genetics and Genomics, the Muriel G. and George W. Singer Professor of Neuroscience and Physiology, and Professor of Medicine at New York University School of Medicine. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine and the Indian National Science Academy. He has been a key participant in the Human Genome Project, the International HapMap Project and the 1000 Genomes Project. His research attempts to understand the molecular basis of multifactorial disease. He was awarded the 2013 William Allan Award by the American Society of Human Genetics and the 2018 Chen Award by the Human Genome Organization.

Eileen E. M. Furlong is Head of the Genome Biology Department at the European Molecular Biology Laboratory (EMBL) and a member of the EMBL Directorate. She is an elected member of the European Molecular Biology Organization (EMBO) and the Academia Europaea, and a European Research Council (ERC) advanced investigator. Her group dissects fundamental principles of how the genome is regulated and how it drives cell fate decisions during embryonic development, including how developmental enhancers are organized and function within the 3D nucleus. Her work combines genetics, (single-cell) genomics, imaging and computational approaches to understand these processes. Her research has advanced the development of genomic methods for use in complex multicellular organisms.

Barbara Treutlein is Associate Professor of Quantitative Developmental Biology in the Department of Biosystems Science and Engineering of ETH Zurich in Basel, Switzerland. Her group uses and develops single-cell genomics approaches in combination with stem cell-based 2D and 3D culture systems to study how human organs develop and regenerate and how cell fate is regulated. For her work, Barbara has received multiple awards, including the Friedmund Neumann Prize of the Schering Foundation, the Dr. Susan Lim Award for Outstanding Young Investigator of the International Society of Stem Cell Research and the EMBO Young Investigator Award.

Alexander Meissner is a scientific member of the Max Planck Society and currently Managing Director of the Max Planck Institute (MPI) for Molecular Genetics in Berlin, Germany. He heads the Department of Genome Regulation and is a visiting scientist in the Department of Stem Cell and Regenerative Biology at Harvard University. Before his move to the MPI, he was a tenured professor at Harvard University and a senior associate member of the Broad Institute, where he co-directed the epigenomics programme. In 2018, he was elected as an EMBO member. His laboratory uses genomic tools to study developmental and disease biology with a particular focus on epigenetic regulation.

Howard Y. Chang is the Virginia and D. K. Ludwig Professor of Cancer Genomics at Stanford University and an investigator at the Howard Hughes Medical Institute. He is a physician–scientist who has focused on deciphering the hidden information in the non-coding genome. His laboratory is best known for studies of long non-coding RNAs in gene regulation and development of new epigenomic technologies. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine, and the American Academy of Arts and Sciences.

Núria López-Bigas is ICREA research Professor at the Institute for Research in Biomedicine and Associate Professor at the University Pompeu Fabra. She obtained an ERC Consolidator Grant in 2015 and was elected as an EMBO member in 2016. Her work has been recognized with the prestigious Banc de Sabadell Award for Research in Biomedicine, the Catalan National Award for Young Research Talent and the Career Development Award from the Human Frontier Science Program. Her research focuses on the identification of cancer driver mutations, genes and pathways across tumour types and in understanding the mutational processes that lead to the accumulation of mutations in cancer cells.

Eran Segal is Professor in the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, heading a multidisciplinary laboratory with extensive experience in machine learning, computational biology and analysis of heterogeneous high-throughput genomic data. His research focuses on the microbiome, nutrition and genetics, and their effect on health and disease and aims to develop personalized medicine based on big data from human cohorts. He has published more than 150 publications and received several awards and honours for his work, including the Overton and the Michael Bruno awards. He was recently elected as an EMBO member and as a member of the Israel Young Academy.

Jin-Soo Kim is Director of the Center for Genome Engineering in the Institute for Basic Science in Daejon, South Korea. He has received numerous awards, including the 2017 Asan Award in Medicine, the 2017 Yumin Award in Science and the 2019 Research Excellence Award (Federation of Asian and Oceanian Biochemists and Molecular Biologists). He was featured as one of ten Science Stars of East Asia in Nature ( 558 , 502–510 (2018)) and has been recognized as a highly cited researcher by Clarivate Analytics since 2018. His work focuses on developing tools for genome editing in biomedical research.

Making genomics truly equitable

Amy McGuire. For the field of genetics and genomics, the first decade of the twenty-first century was a time of rapid discovery, transformative technological development and plummeting costs. We moved from mapping the human genome, an international endeavour that took more than a decade and cost billions of dollars, to sequencing individual genomes for a mere fraction of the cost in a relatively short time.

During the subsequent decade, the field turned towards making sense of the vast amount of genomic information being generated and situating it in the context of one’s environment, lifestyle and other non-genetic factors. Much of the hype that characterized the previous decade was tempered as we were reminded of the exquisite complexity of human biology. A vision of medicine driven by genetically determined risk predictions was replaced with a vision of precision in which genetics, environment and lifestyle all converge to deliver the right treatment to the right patient at the right time 1 .

As we embark on the third decade of this century, we are now faced with the prospect of being able not only to more accurately predict disease risk and tailor existing treatments on the basis of genetic and non-genetic factors but also to potentially cure or even eliminate some diseases entirely with gene-editing technologies.

These advancements raise many ethical and policy issues, including concerns about privacy and discrimination, the right of access to research findings and direct-to-consumer genetic testing, and informed consent. Significant investment has been made to better understand the risks and benefits of clinical genomic testing, and there has been vigorous debate about the ethics of human gene editing, with many prominent scientists and bioethicists calling for a moratorium on human germline editing until it is proven to be safe and effective and there is broad societal consensus on its appropriate application 2 .

These are all important issues that we need to continue to explore, but as the technologies that have been developed and tested at warp speed over the past two decades begin to be integrated into routine clinical care, it is imperative that we also confront one of the most difficult and fundamental challenges in genomics, in medicine and in society — rectifying structural inequities and addressing factors that privilege some while disadvantaging others. The genomics of the future must be a genomics for all, regardless of ethnicity, geography or ability to pay.

This audacious goal of making genomics truly equitable requires multifaceted solutions. The disproportionate burden of illness and death among racial and ethnic minorities associated with the global COVID-19 pandemic 3 and recent protests against police brutality towards African American citizens 4 have strengthened the antiracism movement and amplified demands for racial equity.

To be part of this movement and effect change will require humility. We must actively listen and learn from each other, especially when it is uncomfortable and our own complicity may be implicated. It will require solidarity and a recognition that we are all connected through our common humanity. And it will require courage. It may seem like a platitude, but it is true that nothing will change unless actual change is made. If we continue to do things as they have always been done, we will end up where we have always been. It is time to step into the discomfort and dare to do something different.

So what can we do differently to make genomics more equitable? I propose three areas where we should focus attention to address this important question. First, we must ensure equitable representation in genomic research. Examining 2,511 studies involving nearly 35 million samples from the GWAS Catalog in 2016, Popejoy and Fullerton found that the vast majority (81%) come from individuals of European descent, with only 5% coming from non-Asian minority populations 5 . This has created an ‘information disparity’ that has an impact on the reliability of clinical genomic interpretation for under-represented minorities 6 . The US National Institutes of Health (NIH) has invested in efforts to increase diversity in genomic research, but to be successful these efforts must be accompanied by serious attention to earning the trust of disadvantaged and historically mistreated populations. This will require, at a minimum, more meaningful engagement, improved transparency, robust systems of accountability, and a commitment to creating opportunities that promote and support a genomics workforce that includes scientists and clinicians from under-represented populations.

It is insufficient to achieve diverse representation in genomic research; however, there must also be equitable access to the fruits of that research. An analysis of the US Centers for Disease Control and Prevention’s 2018 Behavioural Risk Factor Surveillance System found that non-elderly adults from self-identified racial or ethnic minority groups are significantly less likely to see a doctor because of cost than non-elderly white adults 7 . This finding reflects how the structure and financing of health care in the United States perpetuates inequities and contributes to the larger web of social injustice that is at the heart of the problem. Even when socio-economic factors are controlled for, racial disparities in access to genetic services persist 8 . Large-scale, sustained research is needed to better understand and actively address the multitude of factors that contribute to this, including issues related to structural racism, mistrust, implicit and explicit bias, a lack of knowledge of genetic testing, and concerns about misuse of genetic information.

Finally, and perhaps most daunting, we must strive to achieve more equitable outcomes from genomic medicine. Many racial and ethnic minorities disproportionately experience chronic disease and premature death compared with white individuals. Disparities also exist by gender, sexual orientation, age, disability status, socio-economic status and geographical location. Health outcomes are heavily influenced by social, economic and environmental factors. Thus, although providing more equitable access to genomic services and ensuring more equitable representation in genomic research are necessary first steps, they are not enough 9 . Genomics can only be part of the solution if it is integrated with broader social, economic and political efforts aimed at addressing disparities in health outcomes. For genomics to be truly equitable, it must operate within a just health-care system and a just society.

we must strive to achieve more equitable outcomes from genomic medicine

Genome sequencing at population scale

Stacey Gabriel. Twenty years ago, I finished a PhD project that involved laboriously sequencing one gene — a rather complicated one, RET — in a couple of hundred people to catalogue pathogenic variants for Hirschsprung disease. This work required designing primers on the basis of genome sequence data as they were gradually released, amplifying the gene exon by exon (all 20!), running sequencing gels and manually scoring sequence changes. The notion of sequencing the whole genome to catalogue sequence changes was something to wish for in our wildest dreams.

Thanks to great strides in technology and the hard work of geneticists, engineers, epidemiologists and clinicians, much progress has been made; huge numbers of genomes (and exomes) have been sequenced across the world. Disease gene-finding projects such as my graduate work are now done routinely, rather than one gene at a time, using whole-exome or whole-genome sequencing (WGS) in families and affected individuals, enabling the identification of genes and causative mutations in thousands of Mendelian diseases and some complex diseases.

But the real promise of genome sequencing lies in true population-scale sequencing, ultimately at the scale of tens of millions of individuals, whereby genome sequencing of unselected people enables the unbiased, comprehensive study of our genome and the variation therein. It provides a ‘lookup table’ to catalogue disease-causing and benign variants (our ‘allelic series’). The genome sequence should become part of the electronic health record; it is a stable, persistent source of information about a person akin to physical measurements such as weight or blood pressure, exposures such as smoking or alcohol use, and (in many ways better than) self-reported family history.

the real promise of genome sequencing lies in true population-scale sequencing, ultimately at the scale of tens of millions of individuals

What can we learn? What needs to be solved? Even fairly small numbers of genomes aggregated in a consistent and searchable form have enabled a new way to use and interpret genomic data, just in the past couple of years providing a glimpse at the future. Efforts such as gnomAD 10 are a start — this database contains data from more than 15,000 genomes and 125,0000 exomes. With this resource, the frequency of genetic variants within populations is readily available. A clinician interpreting the genome of a patient can ask whether a variant has been observed before. The data provide a starting point for assessing the functional impact of classes of genetic variation and the ability to ask questions about ‘missing’ genetic variation where there is constraint.

Coupled with clinical data, building up population-scale databases of genomic plus clinical information will fuel the application of better risk interpretation using polygenic risk scores (PRSs) 11 . More routine WGS will shorten the ‘diagnostic odyssey’, in which patients suffer through rounds of testing and parents are left uncertain about future reproductive planning. More efficient clinical trials might be built using genomic information. With existing genomic information on all individuals in a health system, trials could be designed in a way that selects individuals most likely to have an event. This enrichment could provide more promising, shorter, smaller and cheaper trial design.

These databases must also rapidly be built in such a way that is representative of the population, representing the actual racial and ethnic diversity, not just what was available as banked sample collections. These are well known to be predominantly European-descent samples and thus preclude application of risk prediction tools in non-white individuals and have limited the ability to find population-specific genetic associations, such as those that have been demonstrated in type 2 diabetes mellitus (T2DM) 12 .

We have to solve important issues — data sharing, privacy and getting the data to scale. Sharing genomic and clinical data is of key importance to drive forward discovery and our understanding of how to use these data in the health-care setting. To do this well and responsibly, trust must be built and maintained through adherence to the rights of privacy, protection and non-discrimination. Progress is being made through the creation of data platforms and the development of frameworks for data protection and sharing; for example, by the work of the Global Alliance for Genomics and Health (GA4GH).

Several large biobanks are already being established to launch population-scale efforts. The UK Biobank is a vanguard programme that contains genotype data, questionnaire-based health and physical measurements on 500,000 individuals and some linkage to their medical records. Other efforts such as the All of Us research programme have been launched with goals directed at true population-based representation, and biobanks that link genomic data to comprehensive medical records in specific health-care systems (for example, Geisinger) or in specific countries or regions (for example, Estonia and Iceland) are also under way.

A big piece of this puzzle is generating comprehensive genome sequence data in these programmes and far beyond. For this aim, large-scale, affordable sequencing is key. No problem, right? Is sequencing not always getting cheaper? The problem is that this assumption is no longer true. We have got to where we are today because for a long time, from 2008 to 2013, sequencing costs dropped exponentially. However, in recent years, the sequencing cost curve has flattened, as is apparent in publicly reported cost estimates provided by the US National Human Genome Research Institute 13 . The cost per megabase of sequence data has remained largely unchanged since around 2016, hovering around a list price of US$0.01 per megabase, which translates to a US$1,000 genome. Gone are the days of our field touting the impressive decrease of cost in comparison with Moore’s law, and this development is worrying.

Some discounting does happen at considerable volume, and whole genomes can be priced in the range of US$500 to US$700. However, large projects (more than 500,000 samples) sequenced at these prices are few and far between, and are generally dependent on pharmaceutical or biotech funding, which can bring with it restrictions on data sharing. It is my belief that a fivefold to sevenfold reduction in total costs is needed to unlock more sequencing at the population scale and, ultimately, for genome sequencing to be more widely applied in the health-care setting. At US$100 per genome, the cost represents less than 1% of the annual average health-care expenditure per person in the United States, and a genome sequence is a one-time investment that can be referenced again and again over the entire lifespan of a person. Getting that cost curve down will be important to inspire health-care systems to adopt genome sequencing routinely.

I see three main drivers that will get us to US$100 per genome: innovation, scale and competition.

• Innovation . Generating sequence data requires multiple components, and there are multiple areas ripe for innovation. Sample preparation can be improved through more efficient methods that decrease the labour required, or miniaturization can decrease the cost of the reagents used in library preparation. Developments to decrease data processing costs are also ripe for innovation. Recently, we showed that processing using optimized computing power lowered the time and cost of creating a sequence file by ~50% (S.G., unpublished observations). While decreases in the costs of sample preparation and data processing are important, they represent a small component of the total cost. Roughly 70% of the cost of sequencing a human genome is the sequencing reagent (flow cell) and the instrument. Appreciable cost decrease is made possible only by decreasing these marginal costs, as was demonstrated in the period from 2010 to 2014, when flow-cell densities doubled and sequencing cost dropped by an order of magnitude (US$100 per gigabase to US$10 per gigabase).
• Scale . One component of cost is the fixed cost borne by the sequencing centre or the sequencing vendor. With high scale, centres can become more efficient and offset costs such as the costs of personnel, equipment and facilities. Scale can also result in volume discounting of the reagents, although this process is tightly controlled and approached cautiously depending on overall market dynamics.
• Competition . Innovation and scale can only achieve so much. The cost of generating the data (the cost per gigabase) dominates and thus must come down considerably. The current market requires alternative options to drive this advance. Presently, the market for short-read sequencing is lacking viable, proven competition that would force flow-cell densities and machine yield to be increased and put pressures on volume discounting. While options for long-read sequencing exist and play a role in particular applications, such as de novo sequencing and structural variant resolution, they are at present far from cost competitive and, therefore, do not apply pressure to bring down the cost of routine WGS.

We need innovation, great economies of scale and/or real competition to come to play in the marketplace. When it comes to sequencing technology, particularly at a large scale, we cannot be complacent and work around the current barriers to realize small gains and one-off wins. This might involve specific types of investment beyond just financial ones; adopting and vetting new technology requires time, creativity, commitment and patience. It is a challenge for our community to take on now. In 5 years’ time, I hope we can look back at the era of the US$100 genome and progress towards real population-scale databases that fuel discovery, enriching our knowledge of the human allelic series and, importantly, the routine use of genomic data in the health-care setting.

A global view of human evolution

Sarah Tishkoff. The past 10 years saw an exponential increase in SNP array and high-coverage WGS data owing to innovations in genomic technologies. It is now possible to generate WGS data from tens of thousands of individuals (for example, GenomeAsia 100K 14 and NIH TOPMed 15 ). An increase in medical biobanks with access to electronic health records (for example, the UK Biobank 16 , the Million Veteran Project 17 and BioBank Japan 18 ) is enabling the mapping of hundreds of genetic associations with complex traits and diseases, as well as phenome-wide association studies 19 to map pleiotropic associations of phenotypes with genes. The genetic associations identified in these and other studies have been used to calculate PRSs for predicting complex phenotypes and risk of diseases.

Yet despite these advances, as of 2019, nearly 80% of individuals in genome-wide association studies (GWAS) were of European ancestries, ~10% were of East Asian ancestries, ~2% were of African ancestries, ~1.5% were of Hispanic ancestries and less than 1% were of other ancestries 20 . There is also a strong European bias in genomic reference databases, such as gnomAD and GTEx . These biases limit our knowledge of genetic risk factors for disease in ethnically diverse populations and could exacerbate health inequities 20 . Furthermore, PRSs that were estimated using European data do not accurately predict phenotypes and disease risk in non-European populations, performing worst in individuals with African ancestry 21 . The lack of transportability of PRSs across ethnic groups is likely due to differences in patterns of linkage disequilibrium and haplotype structure (resulting in different SNPs tagging causal variants), differences in allele frequencies, gene × gene effects and gene × environment effects. It is also possible that the genetic architecture of complex traits and diseases may differ across ethnic groups owing to different demographic histories and adaptation to diverse environments.

Although there have been initiatives to increase inclusion of ethnically diverse populations in human genomics research (for example, the NIH TOPMed 15 and H3Africa consortia), Indigenous populations remain under-represented. Great care must be taken to ensure that genomic research of minority and Indigenous populations is conducted in an ethical manner. This involves establishing partnerships with local research scientists, being sensitive to local customs and cultural concerns, obtaining both community and individual consent, and returning results to communities that participated when possible. In addition, there should be training and capacity building so that genomic research can be conducted locally, where feasible.

A particular area of focus in the future should be developing tools and resources that make genomic data and analyses accessible in low- and middle-income countries. We have to ensure that all people benefit from the genomics revolution and advances in precision medicine and gene editing. Thus, several of the biggest challenges in the next decade will be (1) to increase inclusion of ethnically diverse populations in human genomics research; (2) the generation of more diverse reference genomes using methods that generate long sequencing reads, and haplotype phasing, to account for the large amount of structural variation that likely exists within and between populations; (3) the training of a more diverse community of genomic research scientists; and (4) the development of better methods for accurately predicting phenotypes and genetic risk across ethnically diverse populations and for distinguishing gene × environment effects.

The inclusion of ethnically diverse populations, including Indigenous populations, is also critical for reconstructing human evolutionary history and understanding the genetic basis of adaptation to diverse environments and diets. While there have been a number of success stories for identifying genes of large effect that play a role in local adaptation (for example, lactose tolerance and sickle cell disease (SCD) associated with malaria resistance), identifying signatures of polygenic selection has been considerably more challenging 22 . Genomic signatures of polygenic adaptation are based on the ability to detect subtle shifts in allele frequencies at hundreds or thousands of loci with minor effect on the phenotype of a complex trait and to determine whether that shift is a result of demography or natural selection. A more daunting challenge arises from the same issues of portability of PRSs described earlier — variants associated with a complex trait may not tag well across ethnic groups and/or the genetic architecture of a trait may differ in different populations. Furthermore, it has recently been shown that uncorrected population stratification can result in a false signal of polygenic selection 23 . For example, several studies have identified signatures of polygenic adaptation for height across European populations (selection for increased height in northern Europeans and for decreased height in southern Europeans). However, it was recently shown that these results were influenced by population structure that could not be easily corrected using standard approaches, particularly for SNPs below genome-wide levels of significance 23 . When this analysis was repeated with variants identified in a more homogenous set of individuals of European ancestry from the UK Biobank, these signatures of polygenic adaptation were erased 23 . Thus, methods for detecting polygenic adaptation that are less biased by population structure and by population ascertainment bias will need to be developed in the future. These studies will also benefit from inclusion of more ethnically diverse populations in GWAS and identification of better tag SNPs as described earlier. A challenge of inclusion of minority populations in GWAS is that sample sizes are often small relative to majority populations. However, the high levels of genetic diversity and extremes of phenotypic diversity observed in some populations, particularly those from Africa, make them particularly informative for GWAS. For example, a GWAS of skin pigmentation in fewer than 1,600 Africans was informative for identifying novel genetic variants that affect skin colour, including a previously uncharacterized gene, MFSD12 (ref. 24 ). Thus, genomic studies in the future must make inclusion of minority populations a priority.

A challenge in both GWAS and selection scans has been the identification of causal genetic variants that directly have an impact on variable traits. Most of these variants are in non-coding regions of the genome. The development of high-throughput approaches, such as massively parallel luciferase expression assays to identify gene regulatory regions and high-throughput CRISPR screens in vitro and in vivo to identify functional variants influencing the trait of interest, will be useful 25 . There is also a need to better understand cell type-specific variation and gene regulation at the single-cell level, including response to stimuli such as immune, pharmacological and nutrient challenges, in ethnically diverse populations. However, these approaches are still limited by the need to have informative cell lines. This can be particularly challenging to obtain for Indigenous populations living in remote regions. Improvements in the differentiation of induced pluripotent stem cells (iPS cells) into assorted cell types and into organoids will be important for facilitating functional genomic studies. Establishment of iPS cells and organoids from diverse non-human primate species will also be informative for comparative genomic studies to identify the evolution of human-specific traits such as brain development and cognition. However, iPS cell-derived cells may not accurately reflect the impact of mutations acting on developmental phenotypes, which will require development of more efficient in vivo approaches in model organisms.

Perhaps the biggest revolution in the study of recent human evolutionary history has been the development of methods that make it feasible to sequence and/or obtain targeted genotypes from ancient DNA samples. The generation of high-coverage reference genomes for archaic hominid species such as Neanderthals and Denisovans, located in Eurasia, has made it feasible to identify archaic introgressed segments within the genomes of non-Africans. Some of these regions have been shown to play a role in adaptive traits such as adaptation to high altitude and immune response 26 . Furthermore, there has been an explosion of studies of ancient genetic variation in Europeans within the past 30,000 years that has demonstrated a much more complex model of the peopling of Europe, and the recent evolution of adaptive traits, than previously known from the archaeological record or from studies of modern populations 27 . The biggest challenge has been the inability to get high-quality ancient DNA from regions with a tropical climate, such as Africa and Asia. While there has been success in analysing DNA samples as old as 15,000 years in Africa, which has been informative for tracing recent migration and admixture events 28 , the lack of a more ancient African reference genome makes it very challenging to detect archaic introgression, which currently relies on statistical modelling approaches. Thus, the biggest challenge in the next 10 years will be the successful sequencing of ancient DNA more than 20,000 years old from all regions of the world, so that we may have a better understanding of the complex web of population histories from across the globe.

African genomics — the next frontier

Ambroise Wonkam. To fully meet the potential of global genetic medicine, research into African genomic variation is a scientific imperative, with equitable access being a major challenge to be addressed. Studying African genomic variation represents the next frontier of genetic medicine for three major reasons: ancestry, ecology and equity.

On the basis of a ‘pan-genome’ generated from 910 individuals of African descent, at least 300 million DNA variants (10%) are not found in the current human reference genome 29 , and 2–19% of the genome of ancestral Africans derives from poorly investigated archaic populations that diverged before the split of Neanderthals and modern humans 30 . Neanderthal genome contributions make up ~2% of the genome in present-day Europeans and are enriched for variations in genes involved in dermatological phenotypes, neuropsychiatric disorders and immunological functions 31 . Once technical challenges in sequencing poor-quality DNA have been overcome and approaches to investigate the genomic contribution of African archaic populations have been refined, it is likely that associations between variants in ancient African DNA and human traits or diseases will be found, providing insights that can benefit modern-day humans.

As a consequence of the 300,000–500,000 years of genomic history of modern humans in Africa, ancestral African populations are the most genetically diverse in the world. By contrast, there is an extreme genetic bottleneck, resulting in much less variation, in all non-African populations who evolved from the thousands of humans who migrated out of Africa approximately 70,000 years ago. Current PRSs, which aim to predict the risk for an individual of a specific disease on the basis of the genetic variants that individual harbours, exhibit a bias regarding usability and transferability across populations, as most PRSs do not account for multiple alleles that are either limited or of high frequency among Africans. A GWAS on the genetic susceptibility to T2DM identified a previously unreported African-specific significant locus, while showing transferability of 32 established T2DM loci 32 . In addition, nonsense mutations found commonly among Africans in PCSK9 , which are rare in Europeans 33 , are associated with a 40% reduction in plasma levels of low-density lipoprotein, supporting PCSK9 as a target for dyslipidaemia therapeutics. In the largest GWAS meta-analysis for 34 complex traits, conducted in 14,345 Africans, several loci had limited transferability among cohorts 34 , further illustrating that genomic variation is highest among Africans compared with other populations. As a consequence, linkage disequilibrium is lower in Africans, which improves fine mapping and identification of causative variants. Indeed, while only 2.4% of participants in large GWAS are African individuals, they account for 7% of all associations 35 . Moreover, whole-exome sequencing of nearly 1,000 African study participants of Xhosa ancestry with schizophrenia found very rare damaging mutations in multiple genes 36 , a finding that could be replicated in a Swedish cohort of 5,000 individuals. In comparison, results for the Xhosa cohort yielded larger effect sizes, which shows that for the same number of cases and controls, the greater genetic variation in African populations provides more power to detect genotype–phenotype relationships. Therefore, millions of African genomes must be sequenced, with genotyping and analysis tools optimized for their interrogation.

Greater availability of African genomes will improve our understanding of genomic variation and complex trait associations in all populations but will also support research into common monogenic diseases. The discovery of a single African origin of the SCD mutation, about 5,000–7,000 years ago, not only suggested recent migration and admixture events between Africans and Mediterranean and/or Middle Eastern populations but also enhanced our understanding of genetic variation in general as well as its potential impact on haemoglobinopathies 37 . For example, variants in the HBB -like gene cluster linked with high levels of fetal haemoglobin have been associated with less severe SCD; because the level of fetal haemoglobin is under genetic control, it is amenable to therapeutic manipulation by gene editing 38 . Moreover, knowledge of an individual’s genetic variants can have an impact on secondary prevention of and treatment strategies for SCD. For example, variants in APOL1 and HMOX1 and co-inheritance of α-thalassaemia are associated with kidney dysfunctions 39 ; stroke in SCD is associated with targeted genetic variants used in a Bayesian model; and overall SCD mortality has been associated with circulating transcriptomic profiles. It is estimated that 75% of the 305,800 babies with SCD born each year are born in Africa; SCD in Africa will serve as a model for understanding the impact of genetic variation on common monogenic traits and help to illustrate the multiple layers of genomic medicine implementation.

Greater availability of African genomes will improve our understanding of genomic variation and complex trait associations in all populations

Exploring African genomic diversity will also increase discovery of novel variants and genes for rare monogenic conditions. Indeed, allelic and locus heterogeneity display important differences in African individuals compared with other populations; for example, mutations in GJB2 account for nearly 50% of cases of congenital non-syndromic hearing impairment among Eurasians but are nearly non-existent in Africans, and there is evidence that novel variants in hearing impairment-associated genes are more likely to be found in Africans than in populations of European or Asian ancestries 40 . Higher fertility rate, consanguinity practices and regional genetic bottlenecks will improve novel gene discovery for monogenic diseases in Africa, as well as disease–gene pair curation, and will address existing challenges surrounding database biases and inference of variant deleteriousness, which have led to the misclassification of variants.

Differential population genomic variant frequencies are shaped by natural evolutionary selection as an adaptation to environmental pressures. The African continent follows a North–South axis, which is associated with variable climates and biodiversity, both motors of natural selection. This specific African ecology has shaped genetic variation accordingly, which can have a detrimental or positive impact on health. Obvious examples are variants that cause SCD but confer resistance to malaria 37 , APOL1 variants that are protective against trypanosomes (the parasites that cause sleeping sickness) 41 and variants of OSBPL10 and RXRA that protect against dengue fever 42 . Unfortunately, APOL1 variants also increase susceptibility to chronic kidney disease in populations of African ancestry 39 , 41 . A better understanding of the functional impact of genetic variants specific to African populations, particularly those that have been selected under environmental pressure, and the way they interact with each other is needed and will have a positive impact on genetic medicine practice. Moreover, immunogenetic studies among Africans will further our understanding of natural selection and responses to emerging infectious diseases, such as COVID-19.

The scientific imperative of genomic research of African populations is expected to enhance genetic medicine knowledge and practice in Africa but will face the challenges of overburdened and under-resourced public health-care systems, and often absent ethical, legal and social implication frameworks 43 , requiring international collaboration to be managed. Developing an African genomics workforce will be necessary to meet the major need for research across the lifespan for cohorts of millions of individuals with complex or monogenic diseases. Such endeavours can thrive on the foundation of recently established initiatives such as H3Africa. Indeed, equitable access for Africans is essential if African genomics is to reach its full potential as the next frontier of global genetic medicine.

Decoding multifactorial phenotypes

Aravinda Chakravarti. We live in a time of great technological progress in genomics and computing. And we live in a time when ‘genetics’ is a household word, with a public increasingly adept at understanding its relevance to their own lives. Not surprisingly, the study of genetics is being reinvented, rediscovered and reshaped, and we are beginning to understand the science of human heredity at a resolution that was impossible before.

The most significant genetics puzzle today, in my view, is the dissection of ‘family resemblance’ of complex phenotypes, both for intellectual (raison d'être of genetics) and practical (disease diagnosis and therapy) reasons. We have long known that family resemblance arises from shared alleles, declining as genetic relationship wanes, but the precise molecular components and composition of this resemblance are still poorly understood. At the turn of the twentieth century, the components were a matter of bitter and acrimonious debate 44 between the ‘Mendelians’ and the ‘Biometricians’, until the opposing views were reconciled by Ronald Fisher’s 1918 analysis 45 that complex inheritance could be explained through segregation of many genes, each individually Mendelian. In 1920, its publication delayed by World War I, this notion was elegantly demonstrated by the experimental studies of Altenburg and Muller using truncate wing , an “inconstant and modifiable character” 46 in Drosophila .

Fisher’s model assumed an infinite number of genes additively contributing to a trait, with common genetic variation at each component locus comprising two alleles that differ only slightly in their genetic effects 45 ; these genetic assumptions were quite contrary to what was then known 44 . Throughout the past century, this view matured, as segregation analyses of human phenotypes taught us that — beyond the effects of some major genes — most trait variation was polygenic, modulated by family-specific and random environmental factors 47 . Today, we have empirical evidence from GWAS, which use dense maps of genetic variants on hundreds of thousands of individuals measured for many traits and diseases, that the genetic architecture of most multifactorial traits is from common sequence variants with small allelic differences at thousands of sites across the genome 48 . This replacement of a pan-Mendelian view with a pan-polygenic view of traits is one of the most important contributions of genomics to genetics. Unfortunately, this mapping success has not clarified the number of genes involved, the identity of those genes or how those genes specify the phenotype. Indeed, some have concluded that many of the mapped GWAS loci are unrelated to the core biology of each phenotype 49 . Thus, for a deeper understanding, we need radically different approaches to understand complex trait biology in contrast to merely expanding GWAS in larger and larger samples.

for a deeper understanding, we need radically different approaches to understand complex trait biology

Yet, the most significant biology to emerge from GWAS is that most of the likely trait-causing variants fall outside coding sequences, in regulatory elements, most frequently enhancers 50 , 51 . This important finding has uncovered four new genetic puzzles. First, the non-coding regulatory machinery is vast; how much of this regulation is compromised, and how does it affect phenotypes? Second, regulatory changes affect RNA expression at many genes and protein expression at others; how does a cell ‘read’ these numerous changes as specific signals? Third, how is this coordinated expression response translated into cellular responses affecting phenotypes? Fourth, if specific environmental factors affect the same phenotype, which components do they dysregulate? In my opinion, we need to answer these questions for specific traits and diseases to truly understand their polygenic biology. Finally, these explanations must also answer the question of why some traits are decidedly Mendelian whereas others are not.

The questions of tomorrow will need to focus on four areas: the biology of enhancers and the transcription factors that bind them 51 ; the effect of genetic variation in enhancers 50 ; gene regulatory networks (GRNs) that regulate expression of multiple genes 52 ; and how GRN changes lead to specific cellular responses 53 . Despite many advances, the number of enhancers regulating expression of a specific gene remains unknown. How many enhancers are cell type specific versus ubiquitous? How many are constitutive rather than stage specific? And do they act additively or synergistically in gene expression? Additionally, which cognate transcription factors bind these enhancers, with what dynamics and how are they regulated 54 ? These details of a gene’s ‘enhancer code’ are critical for assessing its relative effect on a trait. Next, how does enhancer sequence variation affect a gene’s activity? Does such variation affect transcription factor binding only or its interaction with the promoter? Is the enhancer variant’s effect evident in all cellular states or only some? Is variation in only one enhancer sufficient to alter gene expression, or are multiple changes in multiple elements necessary?

Additional critical questions include which genes are involved in the core pathway underlying a trait, and how do we identify them 49 ? Elegant work has shown how genes are regulated within integrated modular GRNs, whereby one gene’s product is required in a subsequent step by another gene, with feedback interactions 52 . These GRNs comprise elements from the genome, transcriptome and proteome, with rate-limiting steps that require regulation. As our work on Hirschsprung disease has shown 50 , 53 , a GRN is composed of core genes, is the logic diagram of regulation of a major rate-limiting cellular step, is enriched in coding and enhancer disease variants with disease susceptibility scaling with increasing number of variants, and with disease resulting from effects on its rate-limiting gene product 53 . That is, the GRN integrates the expression of multiple genes. Finally, we need to understand how GRN changes alter cell properties and behaviour. I speculate that rate-limiting steps in GRNs are major regulators of broad cell properties, be they differentiation, migration, proliferation or apoptosis, the cellular integrator of GRN variation. Thus, genetic variation across the genome affects enhancers dysregulating many genes, but only when they dysregulate GRNs through rate-limiting steps do they affect cell and tissue biology 55 . This offers the promise of a mechanistic understanding of human polygenic disease.

The way forward for complex trait biology, including disease, is to shift our approach from reverse to forward genetics, using genome-wide approaches to cell type-specific gene perturbation. I believe we can construct cell-type GRNs en masse, inclusive of their enhancers, transcription factors and feedback or feedforward interactions, to then assay functionally defined variation in phenotypes. But, even this approach will be insufficient. We need to test our success by solving at least a few complex traits completely and demonstrating their veracity using a synthetic biology approach to recapitulate the phenotype in a model system; similarly to the field of chemistry, analysis has to be followed by de novo synthesis. Our genomic technologies are getting up to the task to enable this advance; as geneticists, are we?

Enhancers and embryonic development

Eileen Furlong. The work of my group sits at the interface of genome regulation and animal development, and there have been many exciting advances in both during the past decade. Developmental biology studies fundamental processes such as tissue and organ development and how complexity emerges through the combined action of cell communication, movement and mechanical forces. After the discovery that differentiated cells could be reprogrammed to a naive embryonic stem cell-like state, the past decade has witnessed an explosion in in vitro cellular reprogramming and differentiation studies. Organoids are a very exciting extension of this. The extent to which these fairly simple systems can self-organize and generate complexity 56 is one of the unexpected surprises of the past 5–10 years. The buzz around stem cells has also renewed interest in cellular plasticity in vivo and has uncovered an unexpected degree of transdifferentiation and dedifferentiation 57 . In the mouse heart, for example, cardiomyocytes dedifferentiate and proliferate to regenerate heart tissue when damaged within the first week after birth 58 .

Our understanding of the molecular changes that accompany differentiation has hugely advanced owing to the jump in scale, resolution and sensitivity of next-generation sequencing technologies over the past decade. This has led to a flood of studies in embryonic stem cells, iPS cells and embryos that revealed new concepts underlying genome regulation by measuring transcript diversity, transcription factor occupancy, chromatin accessibility and conformation, and chromatin, DNA and RNA modifications. The future challenge will be to connect this information to the physical characteristics of cells and how they form complex tissues. New technologies that solve many challenges of working with embryos will help, including CRISPR to engineer genomes, optogenetics to perturb proteins, lattice light-sheet and selective plane illumination microscopy to image processes in vivo, and low-input methods to overcome issues with scarce material. Particularly exciting to me are recent advances in single-cell genomics, which, although they are in their early days, will dramatically change the way we study embryogenesis. Many new insights have already emerged, including the discovery of unknown cell types and new developmental trajectories for well-established cell types. Even the concept of ‘cell identity’ has come into question.

Cell identities are largely driven by transcription factors, which act through cis -regulatory elements called ‘enhancers.’ One of the most exciting unsolved mysteries, in my opinion, is how enhancers relay information to their target genes. The textbook view of enhancers is of elements with exclusive function that regulate a specific target gene through direct promoter interactions, which occur sequentially if multiple enhancers are involved. However, emerging concepts in the past decade question many of these ‘dogmas’. Some enhancers have dual functions, whereas others may even regulate two genes. Enhancer–promoter communication is now viewed in the light of spatial genome organization, including topologically associating domains (TADs) and membraneless nuclear microcompartments (that is, hubs or condensates) 59 . Being present within the same TAD likely increases the frequency of enhancer–promoter interactions, but how a specific enhancer finds its correct promoter within a TAD, or when TADs are rearranged 60 , 61 , remains a mystery. Hubs or condensates are dynamic microcompartments 62 that contain high local concentrations of proteins, including transcription factors and the transcriptional machinery. One potential implication of condensates is that enhancers may not need to ‘directly’ touch a gene’s promoter to regulate transcription — rather, it may be sufficient to come in close proximity within the same condensate. Presumably, once proteins reach a critical concentration, transcription will be initiated. While this model fits a lot of emerging data, there are still many open questions. What is the required distance between an enhancer and a promoter to trigger transcription? Does this distance differ for different enhancers 63 depending on their transcription factor–DNA affinities? Do different chromatin environments 64 influence the process? At some loci, mutation of a single transcription factor-binding site in a single enhancer can have dramatic effects on gene expression and development. It is difficult to reconcile such cases with a shared condensate model, as other proteins bound to the enhancers and promoter should still phase separate. By contrast, there are many examples where mutation of a single transcription factor-binding site, or even an entire enhancer, has minimal impact on the expression of a gene. These observations suggest that there may be different types of loci, with requirements for different types of chromatin topologies and local nuclear environments, which will be important to tease apart in the coming years.

The genetic dissection of model loci in the 1990s and the first decade of the twenty-first century led to much of our understanding of how genes are regulated. The power of genomics in the past few decades has captured regulatory information for all genes genome-wide, providing more unbiased views of regulatory signatures, leading to new models of gene regulation. What is missing is empirical testing at a large scale. A major challenge is to move to more systematic in vivo functional dissection in organisms. CRISPR-based pooled screens have advanced the interrogation of genomic regions in cell culture systems. However, scaling functional assays in embryos remains a huge challenge. The task is enormous — even long-standing model organisms, such as Drosophila and mice, lack knockout strains for all protein-coding genes, and the number of regulatory elements is at least an order of magnitude higher. There has been little progress in developing scalable methods to quantify the contribution of a transcription factor’s input to an enhancer’s activity, and gene expression, in embryos. More systematic unbiased data will uncover more generalizable regulatory principles, increase our predictive abilities of gene regulation and developmental programmes, and enhance our understanding of the impact of genetic variation.

A major challenge is to move to more systematic in vivo functional dissection in organisms

Perhaps the most promising and exciting prospects in the coming years are to use single-cell genomics, imaging and the integration of the two to dissect the amazing complexity of embryonic development. Single-cell genomics can reveal information about developmental transitions in a way that was unfeasible before. When combined with temporal information, such data can reconstruct developmental trajectories 65 , 66 and identify the regulatory regions and transcription factors likely responsible for each transition 67 . The scale and unbiased nature of the data, profiling tens to hundreds of thousands of cells, provides much richer information than anyone envisaged just 5 years ago, bringing a new level of inference and causal modelling. The ability to measure single-cell parameters in situ (called ‘spatial omics’) will be transformative in the context of developing embryos to reveal the functional impact of spatial gradients, inductive signals and cell–cell interactions, and to move to digital 4D embryos. Combining these approaches with genetic perturbations holds promise to decode developmental programmes as they unfold. Will this bring us to a predictive understanding of the regulatory networks driving embryonic development during the next decade? ‘Simple’ model organisms are a fantastic test case to determine the types and scale of data required and to develop the computational framework to build predictive networks. The systematic functional dissection of gene regulation and true integration of single-cell genomics with single-cell imaging will bring many exciting advances in our understanding of the programmes driving embryonic development in the coming years.

Spatial multi-omics in single cells

Barbara Treutlein. Incredibly, the first single-cell transcriptome was sequenced just over a decade ago 68 ! Since this milestone, transcriptomes of millions of cells have been sequenced and analysed from diverse organisms, tissues and other cellular biosystems, and these maps of cell states are revolutionizing the life sciences. The technologies and associated computational methods have matured and been democratized to such an extent that nearly all laboratories can apply the approach to their particular system or question.

Of course, the transcriptome is not enough, and protocols have already been developed to measure chromatin accessibility, histone modifications, protein abundances, cell lineages and other features linked to genome activity in single cells 69 . Currently, many studies use dissociation-based single-cell genomics methods, where the spatial context is disrupted to facilitate the capture of single cells for downstream processing. Methods are improving to measure genomic features in situ 70 , as well as to computationally map features to spatial contexts 71 , 72 . The stage is set for the next phase of single-cell genomics, where spatial registration of multimodal genome activity across molecular, cellular and tissue or ecosystem scales will enable virtual reconstructions with extraordinary resolution and predictive capacity. These virtual maps will rely on multi-omic profiling of healthy and perturbed tissues and organisms, which presents major challenges and opportunities for innovation.

Cell throughput remains a challenge, and it is unclear what role dissociation-based single-cell sequencing protocols will play in the future. These protocols are fairly easy to implement, and laboratories around the world can execute projects with tens of thousands of cells analysed per experiment. However, there are scenarios in which measuring millions of cells per experiment would be desired, such as in perturbation screens. Combinatorial barcoding methods push cell-throughput boundaries 73 ; however, it is unclear how to scale full transcriptome sequencing economically to millions of cells using current sequencing technologies. ‘Compressed sensing’ modalities — whereby a limited, selected and/or random number of features are measured per cell, and high-dimensional feature levels are recovered through inference or similarity to a known reference — provide an interesting possibility to increasing cell throughput 74 .

Most single-cell transcriptome protocols are currently limited to priming the polyadenylation track present on all cellular mRNAs; however, this approach leads to biased sampling of highly expressed mRNAs. Clever innovations for random or targeted RNA enrichment could be a way to build up composite representations of cell states. Image-based in situ sequencing methods provide a means for increasing the number ofcells measured per experiment, as millions of cells can be imaged without a substantial increase in financial cost, although imaging time is a limiting factor. There remains a lot of room for experimental and computational optimizations to measure the transcriptome, random barcodes, DNA conformations and protein abundances from the micrometre scale to the centimetre scale spatially, and it will be interesting to see how methods for spatial registration advance over the next 5 years.

Currently, most high-throughput measurements are performed on cell suspensions or on intact tissues using one modality. That said, studies are emerging that measure several features from the same cell; for example, mRNA and chromatin accessibility 75 or mRNA and lineage 76 . To build virtual maps, independent measurements from different cells can be integrated with use of data integration tools 77 , although it can be difficult to align cell states across modalities in particular in developing systems. Therefore, the ultimate goal is to directly measure as many features as possible (for example, RNA, lineage, chromatin, proteins and DNA methylation) in the same cell 78 , ideally with spatial resolution. Furthermore, combining genetic and pharmacological perturbation screens with single-cell multi-omic measures will be informative to understand cell state landscapes and underlying regulatory networks for each cell type. The CRISPR–Cas field continues to develop creative tools for precise single-locus editing and other manipulations 79 , and incorporation of these toolkits with single-cell sequencing readouts will certainly bring new mechanistic insight.

Life forms are inherently dynamic, and each cell has a story to tell. Static measurements do not provide sufficient insight into the mechanisms that give rise to each cell state observed in a tissue. Computational approaches to stitch together independent measurements across time can be used to reconstruct potential histories; however, these are indirect inferences. Long-term live imaging in 2D cultures using confocal microscopy and in 3D tissues using light-sheet microscopy provides morphology, behaviour, location and, in some cases, molecular information on the history of a cell. Indeed, such long-term imaging experiments revealed that cell fates or states can be predicted from cell behaviour across many generations 80 . Cell tracking combined with end point single-cell genomics experiments can help to understand how cell states came to be; however, these experiments lack molecular resolution of the intermediates. There are strategies using CRISPR–Cas systems to capture highly prevalent RNAs inside cells at given times and insert these RNAs into DNA for storage and subsequent readout 81 . Together with live tracking and end-point single-cell genomics, such methods could provide unprecedented insight into cell histories.

My vision is that the emerging technologies described above can be applied to human 2D cell culture and 3D organoid biosystems to understand human development and disease mechanisms. My team and others are working to build virtual human organs that are based on high-throughput, multimodal single-cell genomics data. Organoid counterparts provide opportunities to perturb the system and understand lineage histories. Together, the next generation of single-cell genomics methods and human organoid technologies will provide unprecedented opportunities to develop new therapies for human disease.

the next generation of single-cell genomics methods and human organoid technologies will provide unprecedented opportunities

Unravelling the layers of the epigenome

Alexander Meissner. Around 1975, the idea that 5-methylcytosine could provide a mechanism to control gene expression gained traction, despite little knowledge of its genomic distribution or the associated enzymes 82 . With similarly limited genomic information or knowledge of the players involved, the histone code hypothesis was put forward in 2000 to explain how multiple different covalent modifications of chromatin may be coordinated to direct specific regulatory functions 83 . Tremendous progress has been made since, and the list of core epigenetic regulators that have been discovered and characterized seems largely complete 84 .

DNA sequencing has continued to dominate the past decade and contributed to an exponential growth of genome-wide maps of all layers of regulation. In the early days, individual CpG sites could be measured by restriction enzymes, whereas now we have generated probably well over a trillion cytosine methylation measurements. An equally astonishing number of genome-wide data sets have been collected for transcriptomes, histone modifications, transcription factor occupancy and DNA accessibility. Furthermore, the number of single-cell transcriptome and epigenome data sets continues to grow at an unprecedented pace.

On the basis of this overabundance of data across many normal and diseased cell states, for instance, we now clearly understand the non-random distribution of cytosine methylation across many different organisms. These maps have helped to refine our understanding of its relationship to gene expression, including the realization that only a few promoters are normally controlled via this modification, whereas gene bodies are actively targeted, and most dynamic changes occur at distal regulatory sites. Similar insights exist for many core histone modifications, and, in general, we have an improved appreciation of the epigenetic writers, readers and erasers involved. Over the past decade, we have seen substantially integrated and multilayered epigenomic analyses that provide a fairly comprehensive picture of epigenomic landscapes, including their dynamics across development and disease.

Additional innovation is now needed around data access and sharing. As noted, there is certainly no shortage of data, but to enable individual researchers to generate and verify hypotheses quickly improved tools are required to access and browse these data. Over the past decade, large coordinated projects such as ENCODE , the Roadmap Epigenomics Project and Blueprint Epigenome have initiated such efforts, but it remains a reality that data are not at everyone’s fingertips quite yet.

Moreover, despite decades of steady and recently accelerated progress, many important questions remain regarding the molecular coordination and developmental functions of these epigenetic modifications. For instance, cytosine methylation at gene bodies has been preserved for more than a billion years of evolution and yet its precise function is still under investigation. How and why did genomic methylation switch to a global mechanism in vertebrates compared with the selected methylation observed in invertebrates? What is the precise function of this modification in each of its regulatory contexts, and how are its ubiquitously acting enzymes recruited to specific sites in the genome? The latter is particularly timely given recent observations that enhancers, but also some repetitive elements, show ongoing recruitment of both de novo methylation and demethylation activity. Moreover, extraembryonic tissues show redirected activity that shares notable similarities with the long observed altered DNA methylation landscape found across most cancer types 85 . Lastly, it is abundantly clear that DNA methylation is essential for mammalian development; but despite us knowing this for nearly three decades, it is not clear how and why developing knockout embryos die. The specific developmental requirements are also largely true for many histone-modifying enzymes; however, it remains incompletely understood how exactly these modifications interact to support gene regulation.

A decade ago it seemed likely that we would answer questions such as these using newly gained sequencing power as a potent tool for generating hypotheses. However, for the most part, epigenomic analyses have expanded a highly valuable, but still largely descriptive, understanding of numerous epigenetic layers. So one may ask, what is different now and why should we expect to answer these questions in the coming years?

Technological innovation has always played a key role in biology, and some broadly applicable, recent breakthroughs will enable us to drive progress in the coming years. These include the transfer of the bacterial innate immunity CRISPR–Cas system as a universal genome-targeting tool 86 as well as for base editing, epigenome editing and various genome manipulations. Similarly, new fast-acting endogenous protein degradation systems have been developed that further enhance our ability to probe for precise function 87 . The past decade also saw major improvements in imaging technologies as well as cell and molecular biology, moving from the 2D space into the 3D space with both organoid cell culture models 88 and chromosome conformation capture approaches for exploring nuclear organization 89 .

Another major shift included the reappreciation that membraneless organelles are a widespread mechanism of cellular organization 90 . In particular, there have been many advances in our understanding of how condensates form and function, including for transcriptional regulation. Together with known properties of modified histones on DNA and the fact that many epigenetic regulators also contain intrinsically disordered regions, it is reasonable to assume that these physical properties will have a major impact on our understanding of chromatin. Importantly, changes in topology have been linked to disease 91 , and similar connections have been reported recently for condensates 92 . This will likely be an exciting area to follow in the coming years.

there have been many advances in our understanding of how condensates form and function, including for transcriptional regulation

Lastly, our research continues to be more and more reliant on multidisciplinary skills, with mathematics, physics, chemistry and computer science playing an ever-more central role in biology, which will require some rethinking in training and institutional organization to accomplish our goals. Going forward, we will need more functional integration, which in part due to the aforementioned selected discoveries is now very tractable. In particular, more refined perturbation of gene activity, which for many chromatin regulators should be separated into catalytic and regulatory functions, together with readouts at multiple levels of resolution will bring us closer to the insights needed. We recently exemplified this with a pipeline that explores epigenetic regulator mutant phenotypes at single-cell resolution 93 . From these studies, we may be able to understand how epigenetic regulators interact with the environment to influence or protect the organismal phenotype, connecting detailed molecular genetics to classical theories of epigenetic phenomena.

As we approach the 100-year anniversary of the detection of 5-methylcytosine in DNA 94 , it seems we can hope to declare at least for some layers of the epigenome that we fully understand the rules under which they operate. This may enable the exploration of more precise therapeutic interventions, for instance by redirecting chromatin modifiers rather than blocking their universal catalytic activities, which are shared between normal and diseased states. Of course, looking back at predictions made just 10 years ago 95 , one should expect many additional unforeseen advances that are just as difficult to predict now as they were back then.

Long non-coding RNAs: a time to build

Howard Chang. Long non-coding RNAs (lncRNAs) are the dominant transcriptional output of many eukaryotic genomes. Although studies over the past decade have revealed diverse mechanisms and disease implications for many lncRNAs, the vast majority of lncRNAs remain mysterious. The fundamental challenge is that we lack the knowledge to systematically transform lncRNA sequence into function. Progress in the next decade may come from a paradigm shift from ‘reading’ to ‘writing’ lncRNAs.

Gene regulation was once thought to be the exclusive province of proteins. Intense efforts for disease diagnosis and treatment focused almost entirely on protein-coding genes and their products, ignoring the vast majority of the genome. Even at the time of the completion of the Human Genome Project, only a handful of functional lncRNAs were known that silenced the expression of neighbouring genes. Thus, it was widely believed that the genome contained mostly ‘junk’, which sometimes made RNA as transcriptional noise.

The human genome is currently estimated to encode nearly 60,000 lncRNAs, ranging from several hundred to tens of thousands of bases, that apparently do not function by encoding proteins 96 . Studies over the past decade discovered that many lncRNAs act at the interface between chromatin modification machinery and the genome. Specific lncRNAs can act as guides, scaffolds or decoys to control the recruitment of specific chromatin modification enzymes or transcription factors to DNA or their dismissal from DNA 97 . lncRNAs can activate as well as silence genes, and these RNAs can target neighbouring genes as a function of local chromosomal folding (in cis ) or at a distance throughout the genome (in trans ). Detailed dissections of individual lncRNAs have revealed that lncRNAs are composed of modular RNA motifs that enable one lncRNA to connect proteins that read, write or erase specific chromatin marks. These findings have galvanized substantial excitement about lncRNAs; laboratories around the world are now investigating the roles of lncRNAs in diverse systems, ranging from control of flowering time in plants to mutations in human genetic disorders.

Nonetheless, the notable progress to date can be viewed as anecdotal — each lncRNA is its own story. When a new lncRNA sequence is recognized in a genome database or RNA profiling experiment, we are still in the dark about what may happen to the cell or organism (if anything) when the lncRNA is removed. Indeed, efforts to ‘read’ lncRNAs have been the dominant experimental strategy over the past two decades. Systematic efforts in the ENCODE, FANTOM and emerging cell atlas consortia have mapped the transcriptional landscape, transcript isoforms and, more recently, single-cell expression profiles of lncRNAs. These powerful data are now combined with genome-scale CRISPR-based methods to inactivate tens of thousands of lncRNAs, one at a time, to observe possible cell defects 98 , 99 . However, many challenges remain. Positive hits require further exploratory studies to define possible mechanisms of action, and we lack a principled strategy to combine lncRNA knockouts to address genetic redundancy and compensation.

A potentially fruitful and complementary direction is the pivot from ‘reading’ to ‘writing’ long RNA scripts. On the basis of the systematic dissection of RNA sequences and secondary structures in lncRNAs, we and others believe that the information in lncRNAs resembles that on a billboard (in which keywords and catchphrases are repeated) rather than a finely honed legal document (where every comma counts). Small units of RNA shapes are repeated within lncRNAs to build up the meaning in the lncRNA billboard, but these RNA shapes can be rearranged in different orders or locations without affecting meaning. These insights have allowed scientists to recognize lncRNA genes from different species that perform the same function even though the primary sequences bear little similarity 100 . Moreover, investigators were able to strip down lncRNAs to their essential ‘words’, composed of these key repeating shapes and one-tenth the size of the original lncRNA, which still functioned in vivo to control chromatin state over a whole chromosome 100 , 101 . Finally, it is now possible to successfully create synthetic lncRNAs. By adding RNA shapes to carefully chosen RNA templates, investigators are starting to create designer lncRNAs that can regulate chromatin in vivo 100 , suffice to partly rescue the physiological lncRNA gene knockout 102 , or target RNAs to specific cytotopic locations within the cell 103 , 104 .

The shift from reading to writing lncRNAs will challenge us on the technical front, leading to potential transformative technologies. Current technologies for massively parallel reporter gene assays are built on short sequence inserts. A plan to build tens of thousands of synthetic lncRNAs will require accurate long DNA or RNA synthesis. These designer sequences will need to be placed into the appropriate locations in the genome and controlled to have proper developmental expression, splicing pattern and RNA chemical modifications. Landmark studies using the XIST lncRNA, which normally silences the second X chromosome in female cells, to silence the ectopic chromosome 21 in Down syndrome cells highlight the biomedical promise of such an approach 105 .

As the field develops technologies for large-scale creation and testing of synthetic lncRNAs, we can rigorously test our understanding of the information content in the language of RNA sequences and shapes. The next decade promises to be an exciting time for building non-coding RNAs and to create entirely new tools to manipulate gene function for biology and medicine.

FAIR genomics to track tumorigenesis

Núria López-Bigas. Cancer research is one of the fields that has probably benefited the most from the technological and methodological advances of genomics. In the span of less than two decades, the field has witnessed an incredible boost in the generation of cancer genomic, epigenomic and transcriptomic data of patients’ tumours, both in bulk and more recently at the single-cell level. My dream as a cancer researcher is to have a full understanding of the path that cells follow towards tumorigenesis. Which events in the life of an individual, a tissue and a particular cell lead to the malignant transformation of some cells? Of course I do not expect to have a deterministic answer, as this is not a deterministic process. Instead we should aim for a quantitative or probabilistic understanding of the key events that drive tumorigenesis. We have solid epidemiological evidence showing that smoking increases the probability of lung cancer, exposure to the Sun raises the probability of developing melanoma and some anticancer treatments increase the probability of secondary neoplasms. But which specific mechanisms at the molecular and cellular levels influence these increases?

One first clear goal of cancer genomics is to catalogue all genes involved in tumorigenesis across different tissues. Although this is a daunting task, it is actually feasible 106 . By analysing the mutational patterns of genes across tumours, one can identify those with significant deviations from what is expected under neutrality, which indicates that these mutations provide a selective advantage in tumorigenesis and are thus driver mutations. We can imagine a future in which through the systematic analysis of millions of sequenced tumour genomes this catalogue or compendium moves closer and closer to completion. For this to happen, not only do we need genome sequencing to expand — this process is already in motion in research, clinical settings and the pharmaceutical industry — but more importantly the resulting data must be made FAIR (findable, accessible, interoperable and reusable) 107 . To this end, consortia and initiatives that promote, catalyse and facilitate the sharing of genomic data, such as the Beyond 1 Million Genomes consortium, the GA4GH or the cBioPortal for Cancer Genomics , are necessary.

Of note, cataloguing genes and mutations involved in cancer development, albeit a very important first step, is still far from the final goal of understanding how and under which conditions they drive tumorigenesis. Framing cancer development as a Darwinian evolutionary process helps me to navigate the path towards this final objective. As is true of any Darwinian process, its two key features are variation and selection. Thanks to the past 15 years of cancer genomics, we now have a much better grasp of the origin of somatic genetic variation between cells across different tissues. The study of the variability in the number, type and genomic distribution of mutations across tumours provides a window into the life history of cells across the somatic tissues of an individual 108 , 109 . In addition, recent studies sequencing the genome of healthy cells in different tissues 110 – 112 have shown that mutations accumulate in hundreds and thousands in our cells in normal conditions over time. These studies have also detected positive selection in some genes across healthy tissues. Hence, positive selection is a pervasive process that operates not only in tumorigenesis but also in healthy tissues, where it is a hallmark of somatic development of skin, oesophagus, blood and other tissues. Take, for example, clonal haematopoiesis: it results from a continuous Darwinian evolutionary process in which over time (with age) some haematopoietic cells harbouring mutations in certain blood development genes, such as DNMT3A and TET2 , outcompete other cells in the compartment 113 , 114 . This process is part of normal haematopoietic development. Problems arise only when this process gets out of control, leading to leukaemia in the case of blood, or a malignant tumour in solid tissues. Why is it only in rare cases that this ubiquitous interplay between variation and selection becomes uncontrollable and results in full-blown tumorigenesis? Which events, beside known tumorigenic mutations, drive this process?

we now have a much better grasp of the origin of somatic genetic variation between cells across different tissues

If we have learnt something in recent years, it is that virtually all tumours harbour driver mutations 115 – 117 , implying that driver genomic events are necessary. However, they are clearly not sufficient for tumorigenesis to occur. So, what are these other triggers of the tumorigenic process? What happens in the lung cells of a smoker or in the haematopoietic cells of a patient treated with chemotherapy that increases their chances to become malignant? Epigenetic modifications and changes in selective constraints, such as evolutionary bottlenecks, for example, at the time of chemotherapy, may be part of the answer.

For the near future, my dream is to see a further increase in FAIR cancer genomics data to help us disentangle the step-by-step game of variation and selection in our tissues that leads to tumorigenesis and likely other ageing-related diseases.

Integrating genomics into medicine

Eran Segal. The past 20 years in genomics have been extraordinary. We developed high-throughput sequencing and learned how to use it to efficiently sequence full genomes and measure gene expression and epigenetic marks at the genome-wide scale and even at the single-cell level 118 . Using these capabilities, we created unprecedented catalogues of novel genomes, functional DNA elements and non-coding RNAs from all kingdoms of life 119 . But — perhaps with the exception of cancer 120 and gene therapy for some monogenic diseases 121 — genomics has yet to deliver on its promise to have an impact on our everyday life. For example, drugs and diagnostics are still being developed in the traditional way, with screening assays to find lead compounds for targets typically arising from animal studies, without involving genomics in any of the steps. Moreover, when the global COVID-19 pandemic hit, the genome of the spreading severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was rapidly sequenced, but why some infected individuals exhibit severe disease and others do not remains unknown.

Indeed, our next challenge is to translate the incredible resources and technologies developed in genomics into an improved understanding of health and disease. This improved understanding should transform the field of medicine to use genomics in its transition to personalized medicine, which promises individualized treatment by targeting the right medication to the right person at the right time on the basis of that person’s unique profile. By continuing to focus on more and more measurements and the creation of more atlases and catalogues, we run the danger of drowning in ever-growing amounts of data and correlative findings. Walking down this path can lead to an endless endeavour, as bulk measurements can always be replaced with single-cell ones, or measures at higher temporal and spatial resolution, across more conditions and wider biological contexts.

Instead, we should use genomics to tackle big unanswered questions such as what causes the variation that we see across people in phenotypes, disease susceptibility and drug responses? What is the relative contribution of genetic, epigenetic, microbiome and environmental factors? How are their effects mediated, and what would be the effect of different interventions? Ultimately, we should strive to use genomics to generate actionable and personalized insights that lead to better health. We are now at an inflexion point in genomics that allows us for the first time to apply it to study human biology and realize these ambitious aims 122 .

At the cellular level, we can use iPS cells from patients to derive cellular models of multiple diseases and prioritize treatments based on measuring both their cellular and molecular response (for example, gene expression and epigenetics) to existing drugs and drug combinations. We can even use massively parallel assays to separately measure the effect of each of tens of thousands of rationally designed mutations, including patient-specific mutations, as we have done, for example, in testing the effect of all clinically identified mutations in TP53 on cellular function 123 . Measuring the molecular effects of directed mutations in genes encoding transcription factors and signalling molecules and in other genes can reveal the underlying pathways and regulatory networks of the disease studied and identify putative therapeutic targets. The application of such approaches to fields that are still poorly understood, such as neurodegenerative diseases, can be particularly impactful.

But we can be much more ambitious and directly profile large cohorts of human individuals using diverse ‘omics’ assays. As molecular changes typically precede clinical disease manifestations, longitudinal measurements coupled with clinical phenotyping have the potential of identifying novel disease diagnostics and therapeutic targets. Indeed, biobanks that track large samples of hundreds of thousands of individuals have recently emerged and are proving highly informative 124 . However, at the molecular level their focus has thus far been on genetics. Technological advances and cost reductions now allow us to obtain much deeper person-specific multi-omic profiles that include transcriptome, proteome, methylome, microbiome, immune system and metabolome measurements. Having these data on the same individual and at multiple time points can reveal which omic layer is more perturbed and informative for each disease and identify associations between molecular markers and disease.

The challenge in using such observational data from human cohorts is to identify which of the associations are causal. One way to address this is to wisely select the nature and type of the associations studied. For example, in working with microbiome data, we can move from analyses at the level of species composition to analyses at the level of SNPs in bacterial genes. Such associations are more specific and more likely to be causal, as in the case of a SNP in the dadH bacterial gene, which correlated with metabolism of the primary medication to treat Parkinson disease and the gut microbiota from patients 125 . Another approach is to use longitudinal measurements and separation of time to emulate target trials from observational data 126 . For example, we can select distinct subsets from the cohort that match on several known risk factors (for example, age or body mass index) but differ on a marker of interest (for example, expression of a gene or presence of an epigenetic mark), and compare future disease onset or progression in these two populations. Similarly, retrospective analysis of baseline multi-omic measurements from participants in randomized clinical trials may identify markers that distinguish responders from non-responders and be used for patient stratification or for identifying additional putative targets.

Ultimately, biomarkers identified from observational cohorts need to be tested in randomized clinical trials to establish causality and assess efficacy. In the case of microbial strains extracted from humans, we may be able to skip animal testing and go directly to human trials. In other cases, such as when human genes are being manipulated, we will need to start with cell culture assays and animal testing before performing clinical trials in humans. However, in all cases, tested omic targets should have already shown associations in human individuals, thus making them more likely to be relevant and succeed in trials, as is the case with drug targets for which genetic evidence links them to the disease 127 .

Beyond these scientific challenges, there is the challenge of engaging the public and diverse ethnic and socio-economic groups to participate in such large-scale multi-omic profiling endeavours even before we can present them with immediate benefits. We can start with incentives in the form of informational summary reports of the data measured and gradually move towards carefully and responsibly conveyed actionable insights as we learn more.

Overcoming the aforementioned challenges is not an easy task, but with the breathtaking advances that genomics has undergone in the past two decades, the time may be right to tackle them. Success can transform genomics from being applied mostly in research settings to having it become an integral and inseparable part of medicine.

CRISPR genome editing enters the clinic

Jin-Soo Kim. In the past several years, genome editing has come of age 128 , in particular because of the repurposing of CRISPR systems. Genomic DNA can be modified in a targeted manner in vivo or in vitro with high efficiency and precision, potentially enabling therapeutic genome editing for the treatment of both genetic and non-genetic diseases. All three types of programmable nucleases developed for genome editing, namely zinc-finger nucleases, transcription activator-like effector nucleases and CRISPR nucleases, are now under clinical investigation. In the next several years, we will be able to learn whether these genome-editing tools will be effective and safe enough to treat patients with an array of diseases, including HIV infection, leukaemia, blood disorders and hereditary blindness, heralding a new era in medicine.

If the history of the development of novel drugs or treatments such as gene therapy and monoclonal antibodies is any guide, the road to therapeutic genome editing is likely to be bumpy but ultimately worth travelling. Key questions related to medical applications of programmable nucleases concern their mode of delivery, specificity, on-target activity and immunogenicity. First, in vivo delivery (or direct delivery into patients) of genes or mRNAs encoding programmable nucleases or preassembled Cas9 ribonucleoproteins can be a challenge, given the large size of these nucleases. Ex vivo (or indirect) delivery is, in general, more efficient than in vivo delivery but is limited to cells from blood or bone marrow, which can be collected with ease, edited in vitro and transfused back into patients. Ongoing developments of nanoparticles and viral vectors are expected to enhance and expand in vivo genome editing in tissues or organs not readily accessible with current delivery systems, such as the brain.

Second, programmable nucleases, including CRISPR nucleases, can cause unwanted on-target and off-target mutations, which may contribute to oncogenesis. Several cell-based and cell-free methods have been developed to identify genome-wide CRISPR off-target sites in an unbiased manner 129 – 131 . But it remains a challenge to validate off-target activity at sites with low mutation frequencies (less than 0.1%) in a population of cells, owing to the intrinsic error rates of current sequencing technologies. Even at on-target sites, CRISPR–Cas9 can induce unexpected outcomes such as large deletions of chromosomal segments 132 . It will be important to understand the mechanisms behind the unusual on-target activity and to measure and reduce the frequencies of such events.

Last but not least, Cas9 and other programmable nucleases can be immunogenic, potentially causing undesired innate and adaptive immune responses. In this regard, it makes sense that initial clinical trials have focused on ex vivo delivery of Cas9 ribonucleoproteins into T cells or in vivo gene editing in the eye, an immunologically privileged organ. Cas9 epitope engineering or novel Cas9 orthologues derived from non-pathogenic bacteria may avoid some of the immune responses, offering therapeutic modalities for in vivo genome editing in tissues or organs with little or no immune privilege.

Base editing 133 , 134 and prime editing 135 are promising new approaches that may overcome some of the limitations of nuclease-mediated genome editing. Base editors and prime editors are composed of a Cas9 nickase, rather than the wild-type Cas9 nuclease, and a nucleobase deaminase and a reverse transcriptase, respectively. Because a nickase, unlike a nuclease, produces DNA single-strand breaks or nicks, but not double-strand breaks (DSBs), base editors and prime editors are unlikely to induce large deletions at on-target sites and chromosomal rearrangements resulting from non-homologous end joining (NHEJ) repair of concurrent on-target and off-target DSBs. Furthermore, when it comes to gene correction rather than gene disruption, these new types of gene editors are much more efficient and ‘cleaner’ than DSB-producing nucleases because they neither require donor template DNA nor rely on error-prone NHEJ; in human cells, DSBs are preferentially repaired by NHEJ, leading to small insertions or deletions (indels), rather than by homologous recombination involving donor DNA.

Base editors and prime editors are also well suited for germline editing and in utero editing (that is, gene editing in the fetus), which should be done with caution, in full consideration of ethical, legal and societal issues. In principle, CRISPR–Cas9 can be used for the correction of pathogenic mutations in human embryos; however, donor DNA is seldom used as a repair template in human embryos 136 . Recurrent or non-recurrent de novo mutations are responsible for the vast majority of genetic diseases. Cell-free fetal DNA in the maternal blood can be used to detect these de novo mutations in fetuses, which are absent in the parents. Some de novo mutations are manifested even before birth, leading to miscarriage, disability or early death after birth; it is often too late and inefficient to attempt gene editing in newborns. These mutations could be corrected in utero using base editors or prime editors without inducing unwanted indels and without relying on inefficient homologous recombination. Compared with germline editing or preimplantation genetic diagnosis, in utero editing, if proven safe and effective in the future, should be ethically more acceptable because it does not involve the creation or destruction of human embryos.

As promising and powerful as they are, current versions of base editors and prime editors can be further optimized and improved. For instance, Cas9 evolved in microorganisms as a nuclease rather than a nickase. Current Cas9 nickases used for base editing (D10A SpCas9 variant) and prime editing (H840A variant) can be engineered to increase their activities and specificities. In parallel, deaminase and reverse transcriptase moieties in base editors and prime editors, respectively, can be engineered or replaced with appropriate orthologues to increase the efficiency and scope of genome editing. It has been shown that base editors can cause both guide RNA-dependent and guide RNA-independent DNA or RNA off-target mutations, raising concerns for their applications in medicine. Prime editors may also cause unwanted on-target and off-target mutations, which must be carefully studied before moving on to therapeutic applications.

Biomedical researchers are now equipped with powerful tools for genome editing. I expect that these tools will be developed further and applied more broadly in both research and medicine in the coming years.

Acknowledgements

A.C. acknowledges that the ideas in his contribution were developed through studies on Hirschsprung disease and thanks the many trainees who have contributed to this work over the past 5 years. A.L.M. acknowledges A. Gutierrez, K. Kostick, G. Lazaro, M. Majumder, K. Munoz, S. Pereira, H. Smith and P. Zuk for feedback. A.M. thanks D. Hnisz, Z. D. Smith, J. Charlton and H. Kretzmer for feedback and the Max Planck Society for funding. A.W. is supported by NIH awards U54HG009790, U01HG009716, U01HG007459 and U24HL135600, and Wellcome Trust award H3A/18/001, and states that the funders had no role in study design, and analysis, decision to publish or preparation of the manuscript. B.T. acknowledges J. G. Camp for helpful discussions. E.E.M.F. is very grateful to A. Ephrussi, M. Mir, M. Perino, Y. Kherdjemil, T. Pollex and S. Secchia for useful comments. E. E. M. F is supported by European Research Council (Advanced Grant) agreement no. 787611 (DeCRyPT). E.S. is supported by grants from the European Research Council and the Israel Science Foundation. H.Y.C. is supported by NIH RM1-HG007735 and R35-CA209919. H.Y.C. is an investigator of the Howard Hughes Medical Institute. J.-S.K. is supported by the Institute for Basic Science (IBS-R021-D1). N.L-B. acknowledges funding from the European Research Council (Consolidator Grant 682398), the Spanish Ministry of Economy and Competitiveness (SAF2015-66084-R, European Regional Development Fund) and the Asociación Española Contra el Cáncer (GC16173697BIGA). S.A.T. is funded by NIH grants R35 GM134957-01 and NIAMS R01AR076241-01A1 and American Diabetes Association Pathway to Stop Diabetes grant #1-19-VSN-02.

Competing interests

H.Y.C. is a co-founder of Accent Therapeutics and Boundless Bio and an advisor of 10x Genomics, Arsenal Biosciences and Spring Discovery. J.-S.K. is a co-founder of and holds stock in ToolGen Inc. A.C., A.L.M., A.M., A.W., B.T., E.E.M.F., E.S., N.L.-B., S.G. and S.A.T. declare no competing interests.

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Related links

Beyond 1 Million Genomes : https://b1mg-project.eu/

Blueprint Epigenome : https://www.blueprint-epigenome.eu/

cBioPortal for Cancer Genomics : https://www.cbioportal.org/

ENCODE : https://www.encodeproject.org/

Global Alliance for Genomics and Health : https://www.ga4gh.org/

gnomAD : https://gnomad.broadinstitute.org/

GTEx : https://www.gtexportal.org/home/

GWAS Catalog : https://www.ebi.ac.uk/gwas

H3Africa : https://h3africa.org

Roadmap Epigenomics Project : http://www.roadmapepigenomics.org/

Contributor Information

Amy L. McGuire, Email: ude.mcb@eriugcma .

Stacey Gabriel, Email: gro.etutitsnidaorb@yecats .

Sarah A. Tishkoff, Email: ude.nnepu.enicidemnnep@ffokhsit .

Ambroise Wonkam, Email: [email protected] .

Aravinda Chakravarti, Email: [email protected] .

Eileen E. M. Furlong, Email: ed.lbme@gnolruf .

Barbara Treutlein, Email: [email protected] .

Alexander Meissner, Email: ed.gpm.neglom@renssiem .

Howard Y. Chang, Email: ude.drofnats@gnahcwoh .

Núria López-Bigas, Email: [email protected] .

Eran Segal, Email: [email protected] .

Jin-Soo Kim, Email: rk.ca.uns@10miksj .

Research Topics

The Center for Genetic Medicine’s faculty members represent 33 departments or programs across three Northwestern University schools and three Feinberg-affiliated healthcare institutions. Faculty use genetics and molecular genetic approaches to understand biological processes for a diverse range of practical and clinical applications.

Select a topic below to learn more and see a list of faculty associated with that type of research. For a full list of Center for Genetic Medicine members, visit our Members section .

  Animal Models of Human Disease

Using genetic approaches with model organisms to investigate cellular and physiological processes can lead to improved approaches for detection, prevention and treatment of human diseases.

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  Bioinformatics & Statistics

Bioinformatics, a discipline that unites biology, computer science, statistical methods, and information technology, helps researchers understand how genes or parts of genes relate to other genes, and how genes interact to form networks. These studies provide insight to normal cellular functions and how these functions are disturbed by disease. Statistics is central to genetic approaches, providing quantitative support for biological observations, and statistical genetics is heavily used by laboratories performing gene and trait mapping, sequencing and genotyping, epidemiology, population genetics and risk analysis.

  Cancer Genetics and Genomics

Cancer begins with genetic changes, or mutations, that disrupt normal regulation of cell proliferation, survival and death. Inherited genetic changes contribute to the most common cancers, like breast and colon cancer, and genetic testing can help identify risks for disease. Tumors also develop additional genetic changes, or somatic mutations, that promote cancer growth and tumor metastases. These genetic changes can be readily defined through DNA and RNA sequencing. Genetic changes within a tumor can be used to develop and guide treatment options.

  Cardiovascular Genetics

Cardiovascular disease is one of the leading causes of death in the US, and the risk of  cardiovascular disease is highly dependent inherited genetic changes. The most common forms of heart disease including heart failure, arrhythmias, and vascular disease are under heritable genetic changes. We work to identify and understand the functions of genes that affect the risk of developing cardiovascular disease, as well as to understand the function of genes involved in the normal and pathological development of the heart.

  Clinical and Therapeutics

Using genetic data identifies pathways for developing new therapies and applying existing therapies. DNA sequencing and epigenetic profiling of tumors helps define the precise defects responsible for cancer progression. We use genetic signals to validate pathways for therapy development.  We are using gene editing methods to correct genetic defects. These novel strategies are used to treat patients at Northwestern Memorial Hospital and the Ann & Robert H. Lurie Children's Hospital of Chicago.

  Development

The genomic blueprint of a single fertilized egg directs the formation of the entire organism. To understand the cellular processes that allow cells to create organs and whole animals from this blueprint, we use genetic approaches to investigate the development of model organisms and humans. Induced pluripotent stem cells can be readily generated from skin, blood or urine cells and used to mirror human developmental processes. These studies help us define how genes coordinate normal human development and the changes that occur in diseases, with the goal of improving detection, prevention and treatment of human disease.

  Epigenetics/Chromatin Structure/Gene Expression

Abnormal gene expression underlies many diseases, including cancer and cardiovascular diseases. We investigate how gene expression is regulated by chromatin structure and other regulators to understand abnormal gene expression in disease, and to learn how to manipulate gene expression for therapeutic purposes.

  Gene Editing/Gene Therapy

Gene editing tools like CRISPR/Cas can be used to directly alter the DNA code. This tool is being used to generate cell and animal models of human diseases and disease processes. Gene therapy is being used to treat human disease conditions.

  Genetic Counseling

As part of training in genetic counseling, each student completes a thesis project. These projects examine all aspects of genetic counseling ranging from family-based studies to mechanisms of genetic action. With the expansion of genetic testing, genetic counselors are now conducting research on outcomes, cost effectiveness, and quality improvement.

  Genetic Determinants of Cellular Biology

Genetic mutations ultimately change the functionality of the cells in which they are found. Mutations in genes encoding nuclear, cytoplasmic and extracellular matrix protein lead to many different human diseases, ranging from neurological and developmental disorders to cancer and heart disease. Using induced pluripotent stem cell and gene-editing technologies, it is now possible to generate and study nearly every human genetic disorder. Having cellular models of disease is necessary to develop new treatments.

  Immunology

Many immunological diseases, such as Rheumatoid arthritis, Lupus, scleroderma, and others have a genetic basis. We work to understand how genetic changes and misregulation contribute to immunological diseases, and use genetic approaches to investigate how the immune system functions.

  Infectious Disease/Microbiome

The susceptibility and/or pathological consequences of many infectious diseases have a genetic basis. We investigate how human genes interact with infectious diseases, and use genetic approaches to determine the interactions between pathogens and the host. Genetic tools, including deep sequencing, are most commonly used to define the microbiome as it undergoes adaptation and maladaptation to its host environment.

  Neuroscience

We work to understand how genes contribute to neurological diseases, and use genetic approaches to investigate how the nervous system functions. Epilepsy, movement disorders, and dementia are heritable and under genetic influence. Neuromuscular diseases including muscular dystrophies and myopathies arise from primary mutations and research in genetic correction is moving into human trials and drug approvals.

  Population Genetics/Epidemiology

Genetic data is increasingly available from large human populations and is advancing the population-level understanding of genetic risk. Northwestern participates in All-Of-US, which aims to build a cohort of one million citizens to expand genetic knowledge of human diseases. Race and ancestry have genetic determinants and genetic polymorphisms can help mark disease risks better than other markers of race/ancestry. We use epidemiology and population genetics to investigate the genetic basis of disease, and to assess how genetic diseases affect subgroups within broader populations.

  Reproduction

Research is examining how germ cells are specified. We study the broad range of biology required to transmit genetic information from one generation to another, and how to facilitate the process of reproduction when difficulties arise or to avoid passing on mutant genes.

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Study reveals previously unknown genetic causes of colorectal cancer

A pioneering study, led by UK universities, including the University of Oxford, The Institute of Cancer Research, London, the University of Manchester and the University of Leeds, has provided the most comprehensive analysis to date of the genetic makeup of colorectal cancer (CRC).

Cancers develop partly through genetic abnormalities within cells of the body. Colorectal cancer is a major cause of death worldwide, but we don’t yet have a full understanding of the genetic changes that cause it to grow. New research - published today in Nature - delivers an unprecedented view of the genetic landscape of CRC and its responses to treatment.

Utilising data from 2,023 bowel cancers from the 100,000 Genomes Project led by Genomics England and NHS England, the research team has identified new gene faults that lead to CRC. They’ve also uncovered new CRC cancer sub-groups (categories of cancer with specific genetic characteristics that affect how cancer behaves and responds to treatment). These findings offer profound insights into the disease's development and potential treatment strategies. Key Findings of the Study: • Identification of Over 250 Key Genes: The study has pinpointed more than 250 genes that play a crucial role in CRC, the great majority of which have not been previously linked to CRC or other cancers, expanding our understanding of how CRC develops. • New Sub-Groups of CRC: Four novel, common sub-groups of CRC have been discovered based on genetic features. In addition, several rare CRC sub-groups have been identified and characterised. These groups have different patient outcomes and may respond differently to therapy. • Genetic Mutation Causes: The research reveals a variety of genetic changes across different regions of the colorectum, highlighting differences in CRC causes between individuals. For example, a process has been found that is more active in younger CRC patients’ cancers; the cause is unknown, but might be linked to diet and smoking. • New Treatment Pathways: Many identified mutations could potentially be targeted with existing treatments currently used across other cancers. Commenting on the findings, co-lead researcher, Ian Tomlinson, Professor of Cancer Genetics at the University of Oxford , said: 'Our findings represent a significant advancement in understanding colorectal cancer. By better understanding the genetic changes in CRC, we can better predict patient outcomes and identify new treatment strategies, quite possibly including the use of anti-cancer drugs that are not currently used for CRC.' The research provides a vital resource for the scientific community and a promising foundation for future studies. The results from the study are available to other researchers, who are invited to build on the data by undertaking more focussed projects based on the CRC genome. Co-lead researcher, Professor Richard Houlston , Professor of Cancer Genomics at The Institute of Cancer Research, London, said: 'This research is a great insight into the biology of colorectal cancer, uncovering the clues as to how it develops, grows, and responds to treatments. I look forward to seeing future studies use these findings to develop tailored treatments for people with colorectal cancer, based on their genetics.'

Co-lead researcher, Professor David Wedge , Professor of Cancer Genomics and Data Science at the University of Manchester, said: 'This is the first really large study to come out of the 100,000 Genomes Project led by Genomics England and NHS England. In the coming months and years, I expect it to be followed by many more studies of different types of cancer as well as combined studies across all types of cancer, fuelled by the fantastic data resource provided by Genomics England.'

Dr Henry Wood , Lecturer in Translational Bioinformatics from Pathology in the University of Leeds’ School of Medicine, said: 'This study is the first to provide in-depth, whole-genome sequencing and characterisation of the microbiome - the community of bacteria and viruses that live in the gut - in a large number of cases of bowel cancer. This means that we are now in a position to investigate the importance of the microbiome in the development of these cancers, and whether we can change it to influence the tumour and improve patient outcomes.'

The paper, ' The genomic landscape of 2,023 colorectal cancers ', is published in Nature . 

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Rebecca Starble and Danielle Miyagishima win 2024 Carolyn Slayman Prize in Genetics for exceptional research and service

Rebecca starble and danielle miyagishima.

The Carolyn Slayman Prize in Genetics recognizes students for remarkable scientific achievements and exceptional contributions to the scientific community. The prize is named in honor of Dr. Carolyn Walch Slayman, Sterling Professor of Genetics. This year, the prize has been jointly awarded to Dr. Rebecca Starble and Dr. Danielle Miyagishima.

Starble conducted her PhD research in Andrew Xiao’s lab. Her graduate dissertation reports the discovery of an unexpected mechanism regulating therapeutic resistance in lung adenocarcinoma. Her work identifies a new chromatin factor regulating amplification of oncogenes, which promote cancer progression, and shows that depletion of the chromatin factor prevents therapeutic resistance. This work suggests new approaches for preventing therapeutic resistance in lung cancer.

Starble served on the Graduate Student Assembly and the Graduate and Professional Student Senate where she represented graduate students. One of Starble’s goals throughout her PhD was to help decrease systemic barriers within academia that prevent many students from even considering a scientific career.​ One of the most meaningful aspects of graduate school for Starble was having the opportunity to work with and learn from students in the New Haven Public School district through science and educational outreach organizations that she helped spearhead. “In particular, I really enjoyed helping to develop and run BioScience Club , a high school program that aims to teach experimental techniques that can be directly used in the STEM workforce through hands-on laboratory experiments. This program has not only reaffirmed the impact of early exposure to STEM, but it has also illuminated the importance of forming long-standing relationships with the community.”

Next, Starble will begin as a YSM Science Fellow in the Yale Pathology Department, where she aims to further elucidate the function and mechanisms of oncogene amplification in tumor evolution. She is particularly interested in uncovering novel factors that promote structural variation in tumorigenesis with the eventual goal of exploiting these factors therapeutically. Ultimately, she hopes to establish an independent research program in the field of cancer epigenetics, combining her passions for cancer biology research and mentorship.

Of her time in the Genetics department, Starble says “I have greatly enjoyed being part of such a collaborative and collegial department. I received so much valuable scientific feedback throughout my PhD from many members of the department that greatly propelled my project forward. The department is also very scientifically diverse, which has really helped me to think about science from different perspectives and learn about fields other than my own.”

The joint recipient of the prize, Miyagishima conducted her PhD research in Murat Günel’s lab. Her graduate dissertation provides a comprehensive cellular and molecular examination of meningiomas, tumors that grow from the membranes that surround the brain and spinal cord. Her work uncovers spatial compartmentalization within meningiomas, identifies predominant signaling pathways active in meningiomas, and reveals complex hormonal regulation within the tumor microenvironment. This comprehensive understanding of the tumor ecosystem suggests a systems-based therapeutic approach.

Miyagishima is the co-founder of the Yale Cushing Society, whose mission is to foster a direct educational and research interface between Yale undergraduates and medical students and neurosurgery residents and faculty, and she contributed to efforts to enhance opportunities for members of underrepresented communities to pursue careers in medicine. During the COVID-19 pandemic she worked to combat vaccine misinformation and to help increase access to vaccines to refugees and low-income communities. Miyagishima was also involved in the founding of the New Haven Global Shapers Hub , which aims to provide opportunities to work with changemakers around the world on a wide variety of impact areas.

Reflecting on her service, Miyagishima says “that nothing good happens without a great team and that science can take us far but getting society at large to buy-in is equally important. I hope to continue to contribute to making sure that scientific knowledge and advancements are accessible to as many people as possible.”

Danielle is currently finishing her MD as part of the Medical Scientist Training Program and preparing to apply to neurosurgery residency programs. As part of her preparation, she will do sub internships at Massachusetts General Hospital and New York Presbyterian-Weill Cornell Medical Campus this summer. Ultimately, Danielle hopes to emulate her mentors and become a neurosurgeon-scientist doing both basic and translational research.

Featured in this article

• Danielle Miyagishima
• Murat Gunel, MD, FACS, FAHA, FAANS Sterling Professor of Neurosurgery and Professor of Genetics and of Neuroscience; Chair, Neurosurgery; Physician-in-Chief, Neurosurgery, Yale New Haven Health System; Member, National Academy of Medicine; Co-Director, Yale Program on Neurogenetics
• Rebecca Starble Postdoctoral Associate
• Andrew Xiao, PhD Associate Professor of Genetics

Exploring The Life-Changing Promise Of Genetic Medicines In Blood Disorders

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Genetic medicines on the horizon have the potential to transform the hematology landscape.

The era of genetic medicines has ushered in novel and exciting ways of treating genetic diseases, one of which includes bringing to reality the promise of a one-time treatment by addressing the root cause.

This can be accomplished either by silencing defective genes, inserting working genes, or even editing harmful gene variants.

Building upon an expertise in genetics and disease biology, Regeneron has been developing a portfolio of innovative technologies to research investigational genetic medicines, including RNA interference, adeno-associated virus (AAV)-based gene delivery, and CRISPR mediated gene insertion.

Developing genetic medicines, however, takes more than technology. It’s about building trust with patient communities to help guide and optimize clinical trial designs, assessing which technologies may be appropriate for which diseases, and leveraging learnings from one clinical development program to inform others.

“It’s remarkable to see how the science has advanced to finally be able to tackle these hard-to-treat diseases,” says Gary Herman, Senior Vice President and co-head of Regeneron Genetic Medicines Clinical Development Unit. “Many of our development programs are potential ‘firsts,’ which can be incredibly exciting, but also highlights our important responsibility. We must be thoughtful at every step to build on the trust that a disease community has granted us.”

Addressing Unmet Medical Needs in Genetic Blood Disorders

Genetic blood disorders are caused by gene variants and defects that impact the production of normal blood proteins, 1,2 interfering with vital blood functions like oxygen circulation, 3 protection from infection, 4 and blood clotting. 2 Since many of these conditions are rare, there may be limited knowledge of disease parameters and real-world, day-to-day impact.

Integrating community voices—patients, caregivers, and advocates—into the clinical trial development process is, therefore, vital to successfully understanding these diseases. “We hold patient panels to truly assess what the unmet needs are and uncover what aspects of treatment would be most impactful for people living with these diseases and their families,” explains Herman.

Patient panels have shed light on some of the limitations of current treatments, which have largely focused on addressing disease symptoms with infusions of “working” blood proteins. However, these infusions must be continually administered over a person’s lifetime and have no impact on the root cause of the disease.

“There is a tremendous amount of medical need in blood disorders, and the field has been struggling for years to effectively address them,” explains Andres Sirulnik, Senior Vice President, Hematology Clinical Development Unit Head. “Many genetic blood diseases cannot be addressed with existing approaches like small-molecule or antibody therapies, and that’s where genetic medicines can make a difference.”

CRISPR Technology: Transforming Conventional Gene Replacement Therapy

CRISPR—short for “clustered regularly interspaced short palindromic repeats”—is a process used to precisely modify the DNA of living organisms, from cutting DNA to inserting genes in targeted locations in the genome. 5 Over the last 20 years, scientists have identified how CRISPR works and the molecular machinery that carries it out, leading to the ongoing development of this technology for gene editing in humans.

“For the rare genetic blood-clotting disease hemophilia—typically present at birth—the excessive bleeding endured by children with this disease can lead to progressive disability with pain syndromes and psychosocial impact, 6,7 ” said David Gutstein, Vice President, Global Program Head, Hematology, Regeneron. He continued, “CRISPR is helping to shape the next generation of potential gene therapies with the goal of more effectively addressing blood clotting defects early in life, so these children can have the highest chances of success. 8 ”

Gene therapies for hemophilia are delivered to the liver because key clotting factors necessary for normal blood function are made there. 9 As a person ages and the liver performs its many functions, liver cells divide, regenerate, and die in their normal life cycle. 9

Current gene therapies for hemophilia involve delivering a gene that encodes a functional clotting factor to liver cells. 9 However, as this gene is typically not inserted into the DNA itself, its expression can wane over time as cells divide during normal liver growth, ultimately diluting the treatment effect as the patient ages. 9

CRISPR technology is designed to insert the functional clotting factor gene into a specific location in the DNA of liver cells. 5 This potentially allows for long-term expression of functional clotting factors even during normal liver growth, which may support applicability to pediatric patients. 8 At Regeneron, a CRISPR-based gene insertion platform is being investigated in hemophilia B patients, with an early stage clinical trial planned to start this year.

From Science to Medicine in Blood Disorders

By advancing multiple technologies and matching them to the most appropriate diseases, Regeneron looks to unlock new approaches, potentially addressing conditions that were previously considered untreatable. As an example, another modality under investigation includes a combination approach which is being evaluated as a gene-silencing therapy for paroxysmal nocturnal hemoglobinuria (PNH), a devastating condition where the immune system attacks and destroys red blood cells. 10

“Our deep scientific inquiry really opens up the horizon of what we can accomplish,” Gutstein says, “and this relentless pursuit allows us to push the boundaries of scientific discovery in hematology and beyond.”

1. National Heart, Lung, and Blood Institute. Bleeding Disorders: Causes and Risk Factors. https://www.nhlbi.nih.gov/health/bleeding-disorders/causes .

2. Doherty TM, et al., Bleeding Disorders , in StatPearls . 2024, StatPearls Publishing Copyright © 2024, StatPearls Publishing LLC.: Treasure Island (FL).

3. MedlinePlus. Beta thalassemia. https://medlineplus.gov/genetics/condition/beta-thalassemia/ .

4. National Institute of Allergy and Infectious Diseases. Chronic Granulomatous Disease (CGD). https://www.niaid.nih.gov/diseases-conditions/chronic-granulomatous-disease-cgd .

5. Jiang F, et al. CRISPR-Cas9 Structures and Mechanisms . Annu Rev Biophys. 2017;46:505-529.

6. Bolous NS, et al. Gene Therapy and Hemophilia: Where Do We Go from Here?

J Blood Med. 2022;13:559-580.

7. De Pablo-Moreno JA, et al. Treatment of congenital coagulopathies, from biologic to biotechnological drugs: The relevance of gene editing (CRISPR/Cas) . Thromb Res. 2023;231:99-111.

8. Chen H, et al. Hemophilia A ameliorated in mice by CRISPR-based in vivo genome editing of human Factor VIII . Sci Rep. 2019;9(1):16838.

9. Pierce GF, et al. Deciphering conundrums of adeno-associated virus liver-directed gene therapy: focus on hemophilia . J Thromb Haemost. 2024;22(5):1263-1289.

10. Bektas M, et al. Paroxysmal nocturnal hemoglobinuria: role of the complement system, pathogenesis, and pathophysiology. J Manag Care Spec Pharm. 2020;26(12-b):S3-S8.

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UC Irvine-led team reveals how TREM2 genetic mutation affects late-onset Alzheimer’s

First-of-their-kind insights into brain effects could yield new targets for early intervention

Irvine, Calif., Aug. 6, 2024 — Researchers led by the University of California, Irvine have discovered how the TREM2 R47H genetic mutation causes certain brain areas to develop abnormal protein clumps, called beta-amyloid plaques, associated with late-onset Alzheimer’s disease. Leveraging single-cell Merfish spatial transcriptomics technology, the team was able to profile the effects of the mutation across multiple cortical and subcortical brain regions, offering first-of-their-kind insights at the single-cell level.

The study, recently published online in the journal Molecular Psychiatry , compared the brains of normal mice and special mouse models that undergo changes like those in humans with Alzheimer’s.

Findings revealed that the TREM2 mutation led to divergent patterns of beta-amyloid plaque accumulation in various parts of the brain involved in higher-level functions such as memory, reasoning and speech. It also affected certain cell types and their gene expression near the plaques.

“Alzheimer’s disease progresses differently in individuals with various genetic risk factors,” said principal investigator Xiangmin Xu, UC Irvine Chancellor’s Professor of anatomy and neurobiology and director of the campus’s Center for Neural Circuit Mapping. “By profiling known mutations, we can develop early, personalized treatments before cognitive decline begins.”

Team members analyzed 19 sections of mouse brains and more than 400,000 cells using a special technique called Merfish to see how they were affected by the Alzheimer’s-related mutations. They were able to examine the expression patterns of genes, providing insight into how they are regulated, contribute to cellular functions and respond to stimuli. Their analysis showed that disparate mutations, like TREM2 R47H, cause changes in the ways microglia and astrocyte cells react to inflammation, as well as how neurons communicate and support brain health.

“Early intervention is key to preventing severe cognitive decline. This is the first study to look at the entire brain at such a detailed level, enabling us to gain a deeper understanding of how the TREM2 R47H mutation impacts gene expression in specific cell types,” Xu said. “These insights can help develop targeted therapies that address these changes and can lead to early intervention strategies that help prevent or slow down the progression of Alzheimer’s disease.”

The team was led by Kevin G. Johnston, until recently a postdoctoral scholar, and associate researcher Zhiqun Tan from UC Irvine’s Department of Anatomy and Neurobiology. Other UC Irvine members included Kim Green, professor and vice chair, and graduate student Kristine Minh Tran from the Department of Neurobiology and Behavior; Grant Macgregor, professor of developmental and cell biology; Zhaoxia Yu, professor of statistics; and Bereket Berackey, biomedical engineering graduate student researcher. Eran A. Mukamel, associate professor of cognitive science, and Alon Gelber, M.D.-Ph.D. candidate, from UC San Diego also participated.

This work was supported by the National Institutes of Health under grants R01 AG082127, U01 AG076791, R01 AG067153, U54 AG054349 and RF 1 AG065675; and the National Institute on Deafness and Other Communication Disorders under grant T32 DC 010755.

UC Irvine’s Brilliant Future campaign: Publicly launched on Oct. 4, 2019, the Brilliant Future campaign aims to raise awareness and support for UC Irvine. By engaging 75,000 alumni and garnering $2 billion in philanthropic investment, UC Irvine seeks to reach new heights of excellence in student success, health and wellness, research and more. The School of Medicine plays a vital role in the success of the campaign. Learn more by visiting https://brilliantfuture.uci.edu/uci-school-of-medicine .

About the University of California, Irvine:  Founded in 1965, UC Irvine is a member of the prestigious Association of American Universities and is ranked among the nation’s top 10 public universities by  U.S. News & World Report . The campus has produced five Nobel laureates and is known for its academic achievement, premier research, innovation and anteater mascot. Led by Chancellor Howard Gillman, UC Irvine has more than 36,000 students and offers 224 degree programs. It’s located in one of the world’s safest and most economically vibrant communities and is Orange County’s second-largest employer, contributing $7 billion annually to the local economy and $8 billion statewide. For more on UC Irvine, visit  www.uci.edu .

Media access:  Radio programs/stations may, for a fee, use an on-campus studio with a Comrex IP audio codec to interview UC Irvine faculty and experts, subject to availability and university approval. For more UC Irvine news, visit  news.uci.edu . Additional resources for journalists may be found at  https://news.uci.edu/media-resources .

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Chiu DT , Hamlat EJ , Zhang J , Epel ES , Laraia BA. Essential Nutrients, Added Sugar Intake, and Epigenetic Age in Midlife Black and White Women : NIMHD Social Epigenomics Program . JAMA Netw Open. 2024;7(7):e2422749. doi:10.1001/jamanetworkopen.2024.22749

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Essential Nutrients, Added Sugar Intake, and Epigenetic Age in Midlife Black and White Women : NIMHD Social Epigenomics Program

• 1 Community Health Sciences Division, School of Public Health, University of California, Berkeley
• 2 Osher Center for Integrative Health, University of California, San Francisco
• 3 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
• 4 Department of Human Genetics, University of California, Los Angeles
• Original Investigation Sociodemographic and Lifestyle Factors and Epigenetic Aging in US Young Adults Kathleen Mullan Harris, PhD; Brandt Levitt, PhD; Lauren Gaydosh, PhD; Chantel Martin, PhD; Jess M. Meyer, PhD; Aura Ankita Mishra, PhD; Audrey L. Kelly, PhD; Allison E. Aiello, PhD JAMA Network Open
• Original Investigation Telehealth Parenting Program and Epigenetic Biomarkers in Children With Developmental Delay Sarah M. Merrill, PhD; Christina Hogan, MS; Anne K. Bozack, PhD; Andres Cardenas, PhD; Jonathan S. Comer, PhD; Daniel M. Bagner, PhD; April Highlander, PhD; Justin Parent, PhD JAMA Network Open
• Original Investigation Socioeconomic Status, Lifestyle, and DNA Methylation Age Alika K. Maunakea, PhD; Krit Phankitnirundorn, PhD; Rafael Peres, PhD; Christian Dye, PhD; Ruben Juarez, PhD; Catherine Walsh, PhD; Connor Slavens, BSc; S. Lani Park, PhD; Lynne R. Wilkens, DrPH; Loïc Le Marchand, MD, PhD JAMA Network Open
• Original Investigation Epigenetic Age Acceleration and Disparities in Posttraumatic Stress in Women Alicia K. Smith, PhD; Seyma Katrinli, PhD; Dawayland O. Cobb, MS; Evan G. Goff, BS; Michael Simmond, BS; Grace M. Christensen, PhD, MPH; Tyler Prusisz, BS; Sierra N. Garth, MPH; Meghan Brashear, MPH; Anke Hüls, PhD, MSc; Erika J. Wolf, PhD; Edward J. Trapido, ScD; Ariane L. Rung, PhD, MPH; Nicole R. Nugent, PhD; Edward S. Peters, DMD, SM, ScD JAMA Network Open
• Original Investigation Childhood Maltreatment and Longitudinal Epigenetic Aging Olivia D. Chang, MSW; Helen C. S. Meier, PhD; Kathryn Maguire-Jack, PhD; Pamela Davis-Kean, PhD; Colter Mitchell, PhD JAMA Network Open
• Original Investigation Familial Loss of a Loved One and Biological Aging Allison E. Aiello, PhD, MS; Aura Ankita Mishra, PhD; Chantel L. Martin, PhD; Brandt Levitt, PhD; Lauren Gaydosh, PhD; Daniel W. Belsky, PhD; Robert A. Hummer, PhD; Debra J. Umberson, PhD; Kathleen Mullan Harris, PhD JAMA Network Open
• Original Investigation Obesity and Early-Onset Breast Cancer in Black and White Women Sarabjeet Kour Sudan, PhD; Amod Sharma, PhD; Kunwar Somesh Vikramdeo, PhD; Wade Davis, BS; Sachin K. Deshmukh, PhD; Teja Poosarla, MD; Nicolette P. Holliday, MD; Pranitha Prodduturvar, MD; Cindy Nelson, BS; Karan P. Singh, PhD; Ajay P. Singh, PhD; Seema Singh, PhD JAMA Network Open
• Original Investigation Psychosocial Disadvantage During Childhood and Midlife Health Ryan L. Brown, PhD; Katie E. Alegria, PhD; Elissa Hamlat, PhD; A. Janet Tomiyama, PhD; Barbara Laraia, PhD; Eileen M. Crimmins, PhD; Terrie E. Moffitt, PhD; Elissa S. Epel, PhD JAMA Network Open
• Original Investigation Epigenetic Aging and Racialized, Economic, and Environmental Injustice Nancy Krieger, PhD; Christian Testa, BS; Jarvis T. Chen, ScD; Nykesha Johnson, MPH; Sarah Holmes Watkins, PhD; Matthew Suderman, PhD; Andrew J. Simpkin, PhD; Kate Tilling, BSc, MSc, PhD; Pamela D. Waterman, MPH; Brent A. Coull, PhD; Immaculata De Vivo, PhD; George Davey Smith, MA(Oxon), MD, BChir(Cantab), MSc(Lond); Ana V. Diez Roux, MD, PhD, MPH; Caroline Relton, PhD JAMA Network Open
• Original Investigation Prenatal Maternal Occupation and Child Epigenetic Age Acceleration Saher Daredia, MPH; Anne K. Bozack, PhD; Corinne A. Riddell, PhD; Robert Gunier, PhD; Kim G. Harley, PhD; Asa Bradman, PhD; Brenda Eskenazi, PhD; Nina Holland, PhD; Julianna Deardorff, PhD; Andres Cardenas, PhD JAMA Network Open
• Special Communication Advancing Health Disparities Science Through Social Epigenomics Research Arielle S. Gillman, PhD, MPH; Eliseo J. Pérez-Stable, MD; Rina Das, PhD JAMA Network Open

Question   Are dietary patterns, including essential nutrients and added sugar intakes, and scores of nutrient indices associated with epigenetic aging?

Findings   In this cross-sectional study of 342 Black and White women at midlife, higher added sugar intake was associated with older epigenetic age, whereas higher essential, pro-epigenetic nutrient intake and higher Alternate Mediterranean Diet (aMED) and Alternate Healthy Eating Index (AHEI)–2010 scores (reflecting dietary alignment with Mediterranean diet and chronic disease prevention guidelines, respectively) were associated with younger epigenetic age.

Meaning   The findings of this study suggest a tandem importance in both optimizing nutrient intake and reducing added sugar intake for epigenetic health.

Importance   Nutritive compounds play critical roles in DNA replication, maintenance, and repair, and also serve as antioxidant and anti-inflammatory agents. Sufficient dietary intakes support genomic stability and preserve health.

Objective   To investigate the associations of dietary patterns, including intakes of essential nutrients and added sugar, and diet quality scores of established and new nutrient indices with epigenetic age in a diverse cohort of Black and White women at midlife.

Design, Setting, and Participants   This cross-sectional study included analyses (2021-2023) of past women participants of the 1987-1997 National Heart, Lung, and Blood Institute Growth and Health Study (NGHS), which examined cardiovascular health in a community cohort of Black and White females aged between 9 and 19 years. Of these participants who were recruited between 2015 and 2019 from NGHS’s California site, 342 females had valid completed diet and epigenetic assessments. The data were analyzed from October 2021 to November 2023.

Exposure   Diet quality scores of established nutrient indices (Alternate Mediterranean Diet [aMED], Alternate Healthy Eating Index [AHEI]–2010); scores for a novel, a priori–developed Epigenetic Nutrient Index [ENI]; and mean added sugar intake amounts were derived from 3-day food records.

Main Outcomes and Measures   GrimAge2, a second-generation epigenetic clock marker, was calculated from salivary DNA. Hypotheses were formulated after data collection. Healthier diet indicators were hypothesized to be associated with younger epigenetic age.

Results   A total of 342 women composed the analytic sample (mean [SD] age, 39.2 [1.1] years; 171 [50.0%] Black and 171 [50.0%] White participants). In fully adjusted models, aMED (β, −0.41; 95% CI, −0.69 to −0.13), AHEI-2010 (β, −0.05; 95% CI, −0.08 to −0.01), and ENI (β, −0.17; 95% CI, −0.29 to −0.06) scores, and added sugar intake (β, 0.02; 95% CI, 0.01-0.04) were each significantly associated with GrimAge2 in expected directions. In combined analyses, the aforementioned results with GrimAge2 were preserved with the association estimates for aMED and added sugar intake retaining their statistical significance.

Conclusions and Relevance   In this cross-sectional study, independent associations were observed for both healthy diet and added sugar intake with epigenetic age. To our knowledge, these are among the first findings to demonstrate associations between added sugar intake and epigenetic aging using second-generation epigenetic clocks and one of the first to extend analyses to a diverse population of Black and White women at midlife. Promoting diets aligned with chronic disease prevention recommendations and replete with antioxidant or anti-inflammatory and pro-epigenetic health nutrients while emphasizing low added sugar consumption may support slower cellular aging relative to chronological age, although longitudinal analyses are needed.

Epigenetic clocks powerfully predict biological age independent of chronological age. These clocks reflect altered gene and protein expression patterns, particularly those resulting from differential DNA methylation (DNAm) at CpG (5′-C-phosphate-G-3′) sites. DNAm that accumulates over time is a testament to the toll social, behavioral, and environmental forces can have on the body. 1 - 3 These alterations often result in pathogenic processes (eg, genomic instability, systemic inflammation, and oxidative stress) characteristic of aging and chronic disease. 1 , 4 , 5 As such, myriad clocks reflecting epigenetic age have been developed for a range of age- or disease-related targets. 4 , 6 The GrimAge series contains second-generation markers of epigenetic aging that account for clinical and functional biomarkers, and is most notable for its robust associations with human mortality and morbidity risk, including time to death and comorbidity counts. 6 , 7 The recently developed version 2 of the GrimAge clock (hereafter, GrimAge2) improved on the first’s predictive abilities and confirmed its applicability for people at midlife and of different racial and ethnic backgrounds. 1 , 6

Epigenetic changes are modifiable and efforts to counter epigenetic alteration in humans have centered on lifestyle factors including diet, inspiring concepts of an “epigenetic diet” and “nutriepigenetics.” 8 , 9 So far, 2 epidemiological studies have found inverse associations between higher diet quality and slower epigenetic aging using clock measures related to mortality, including the first version of GrimAge. 7 , 10 In those studies, diet measures were reflective of healthy dietary patterns (eg, the Dietary Approaches to Stop Hypertension [DASH] diet, the Alternate Mediterranean Diet [aMED] score) emphasizing consumption of fruits, vegetables, whole grains, nuts and seeds, and legumes. 8 , 11 For example, the Mediterranean-style diet is largely plant-based with emphasis on extra virgin olive oil and seafood. This makes it replete with bioactive nutrients and phytotherapeutic compounds and low in highly processed, high fat, and nutrient-poor foods, a mixture hypothesized to be protective against low-grade chronic inflammation (“inflammaging”), oxidative stress, intracellular and extracellular waste accumulation, and disrupted intracellular signaling and protein-protein interactions. Thus, such a pattern is likely effective in preventing and reversing the epigenetic changes and pathogenic processes associated with aging, disease, and decline. 4 , 8 , 12 - 14

Dietary Reference Intakes (DRIs) are an established set of nutrient-specific reference values determined by experts that guide population intakes for adequacy and toxic effects. 15 Recent thinking, however, suggests that diets may not always adequately supply nutrients and other bioactives, particularly relative to the amounts necessary to fully condition gene expression or counteract epigenetic alterations to ensure optimal physiological metabolism. 8 Macronutrients and micronutrients play crucial roles in DNA replication, damage prevention, and repair, whereas nutrient deficiencies (and excesses) can cause genomic damage to the same degree as physical or chemical exposures. 16 Given that (1) progenome effects of some micronutrients have been observed at different and higher levels than the established DRIs and (2) determination of DRIs does not solely consider genomic stability (ie, lesser susceptibility to genomic alterations), experts have called for refining the DRIs to be better aligned for genomic health maintenance. 14 , 16 - 18 Diet quality inventories, such as those for Mediterranean-style diets, have not generally incorporated DRIs, although such considerations could clarify how food-based indices compare against requirements for related nutrients (eg, those with epigenetic properties) and refine epidemiological and intervention efforts. Accordingly, for this study, a novel nutrient index theoretically associated with epigenetic health was created and its associations with epigenetic aging were tested alongside established diet quality indices.

To date, nutriepigenetic work has mostly involved older White populations and focused on healthy dietary aspects. It is therefore important to examine the associations between nutrition and epigenetic aging in more diverse samples and to better understand what specific dietary aspects could be underlying the observed associations. Nutrients with established epigenetic action should be examined, especially considering intakes relative to amounts set forth in the DRIs and nutritional recommendations. Similarly, sugar is an established pro-inflammatory and oxidative agent that has been implicated in cancer as well as cardiometabolic diseases. 19 - 21 However, in diet quality indices often studied in the epigenetic context (eg, the aMED), sugar is noticeably unaccounted for, and it has also yet to be examined alone. Given the high consumption of sugar globally and the demographic variations within, 22 - 24 elucidating this association could motivate future dietary interventions and guidelines as well as health disparities research. This study sought to examine associations of diet with GrimAge2 in a midlife cohort comprising Black and White US women. The central hypothesis was that indicators of a healthier diet may be associated with decelerated epigenetic aging, and added sugar intake with accelerated aging.

This cross-sectional study used data from the original National Heart, Lung, and Blood Institute (NHLBI) Growth and Health Study (NGHS) (1987-1999) and its follow-up (2015-2019), which studied a cohort of Black and White females aged from 9 or 10 years into midlife (age 36-43 years), examining cardiometabolic health and related determinants. The participants were recruited based on biological female sex at age 9 or 10 years. The follow-up study re-recruited women from the California site. 25 , 26 Participants (and/or their parent[s] or guardian[s]) provided demographic data and completed online or paper surveys and new assessments. Participants received remuneration and provided informed consent. The institutional review board of the University of California, Berkeley, approved all study protocols. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline.

For inclusion in current analyses, the participants needed valid diet records and epigenetic data at midlife along with age and race and ethnicity information (participant self-reported); after excluding 5 women with epigenetic data quality issues, 342 individuals were included in the analytic sample. Complete case analyses were done. Among the 624 women who were followed up, the women composing the analytic sample were younger (39.2 years vs 39.9 years; P  < .001) and had greater body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) compared with women without complete diet and epigenetic data (32.5 vs 30.7; P  = .02) ( Table 1 ). No differences were otherwise observed.

Participants provided saliva samples used for DNAm analyses performed by the University of California, Los Angeles Neuroscience Genomics Core (UNGC) of the Semel Institute for Neuroscience and Human Behavior using the Infinium HumanMethylation450 BeadChip platform (Illumina, Inc). DNAm profiles were generated by Horvath’s online calculator, 27 which provided (1) estimates of epigenetic age based on GrimAge2 estimation methods; and (2) assessments of data quality (again, 5 observations did not pass quality checks). GrimAge2 uses Cox proportional hazards regression models that regress time to death (due to all-cause mortality) on DNAm-based surrogates of plasma proteins, a DNAm-based estimator of smoking pack-years, age, and female sex. It was updated from GrimAge, version 1 6 by including 2 new DNAm-based estimators of plasma proteins—high-sensitivity C-reactive protein (logCRP) and hemoglobin A 1c (log A 1c )—beyond the original 7. Linear transformation of results from these models allows GrimAge2 to be taken as an epigenetic age estimate (in years). Further information can be accessed from studies on DNA treatment and isolation and advanced analysis options for generating output files 28 or GrimAge2. 1

The participants were instructed by the NGHS study staff to self-complete a 3-day food record at follow-up for 3 nonconsecutive days. 29 Data were entered into and analyzed by the Nutrition Data System for Research (NDSR) software, version 2018 (University of Minnesota Nutrition Coordinating Center).

Mean nutrient and food intakes were calculated across valid food records for each woman based on the NDSR 2018 output. These values were used to calculate the scores of 2 overall diet quality nutrient indices (aMED and the Alternate Healthy Eating Index [AHEI]–2010) and a novel index (Epigenetic Nutrient Index [ENI]) score as described below. The aMED (Mediterranean-style diet) followed published scoring methodology 30 reflecting the degree of adherence to 9 components of an anti-inflammatory, antioxidant-rich diet. The AHEI-2010 was assessed following published scoring instructions 31 and reflects the degree of adherence to 11 dietary components associated with decreased risk for chronic disease.

This study developed a novel nutrient index (ENI) after the Mediterranean-style diet, but via a nutrient-based approach rather than a food-based one. Nutrient selection was done a priori based on antioxidant and/or anti-inflammatory capacities as well as roles in DNA maintenance and repair documented in the literature. 16 , 32 , 33 Scores can range from 0 to 24, with higher scores reflecting higher DRI adherence ( Table 2 ). 34 The internal consistency of the ENI was acceptable (Cronbach α = 0.79). The ENI also demonstrated convergent validity with r  = 0.51 ENI-aMED correlation as well as higher ENI scores in women from childhood households with higher annual incomes (13.9 vs 11.7, for ≥$40 000/y vs <$10 000/y, respectively) and parental educational attainment (14.7 vs 12.3, for ≥college graduate vs < high school graduate, respectively), corresponding to the literature. 36 Pearson correlations between the ENI and diet scores and added sugar intake were also calculated. The ENI score was moderately correlated with the AHEI-2010 score ( r  = 0.44) but not correlated with added sugar intake. The aMED and AHEI-2010 scores were highly correlated at r  = 0.73. Added sugar intake had moderate correlation with the AHEI-2010 score ( r  = −0.44) and low correlation with the aMED score ( r  = −0.28).

Added sugar intake was calculated as the mean across valid food records using NDSR output. The NDSR defines added sugar intake as the total sugar added to foods (eg, as syrups and sugars) during food preparation and commercial food processing. Monosaccharides and disaccharides naturally occurring in foods are not included. 35

To maximize internal validity and minimize confounding, several covariates were included. Age and sample batch were controlled for as well as naive CD8 and CD8pCD28nCD45Ran memory and effector T-cell counts, thus accounting for normal cell count variation. To control for baseline factors and their potential influence on diet and epigenetic age over time, the following parameters assessed at age 9 or 10 years (mostly parent or caregiver reported) were further adjusted for annual household income, highest parental educational attainment, number of parents in household, and number of siblings. Additionally, self-reported race (Black or White) as well as the current health and lifestyle factors of self-reported chronic conditions (yes to any of the following ever: cancer, diabetes [including gestational, prediabetes], hypertension, or hypercholesterolemia) or medication use (currently yes for any of the following conditions: diabetes, hypertension, hypercholesterolemia, or thyroid), BMI (measured), having ever smoked (yes or no), and mean daily total energy intake (as higher diet quality scores might result from higher energy intake) 37 were also included.

Descriptive analyses provided summary statistics. Linear regression models estimated unadjusted and adjusted cross-sectional associations between each of the 4 dietary exposures with GrimAge2. Per expert recommendations, unadjusted models controlled for women’s current age, sample batch, and both naive CD8 and CD8pCD28nCD45Ran memory and effector T-cell counts. Adjusted models controlled for those variables in addition to relevant sociodemographic and health behavior–related covariates already listed. To examine the association between healthy diet measures together with added sugar intake and GrimAge2, aMED, AHEI-2010, and ENI scores were each separately put into the same fully adjusted multivariable linear regression model. The threshold for statistical significance was 2-tailed (α = .05) and all statistical analyses were conducted from October 2021 to November 2023 with Stata15 SE, version 15.1 (StataCorp LLC).

The analytic sample of this study comprised 342 women (mean [SD] age at follow-up, 39.2 [1.1] years; 171 [50.0%] Black and 171 [50.0%] White participants; mean [SD] BMI, 32.5 [10.0]; 150 [43.9%] ever smokers; 164 [48.0%] ever diagnosed with a chronic condition; and 58 [17.0%] currently taking medication) ( Table 1 ). The participants were well distributed across socioeconomic status categories at baseline (9-10 years old). The participants presented with low to moderate levels of diet quality; the mean (SD) scores were 3.9 (1.9) (possible range, 0-9) on the anti-inflammatory, antioxidant Mediterranean-style pattern (aMED); 55.4 (14.7) (possible range, 0-110) on the AHEI-2010 for chronic disease risk; and 13.5 (5.0) (possible range, 0-24) on the ENI for intakes of epigenetic-relevant nutrients relative to DRIs. The participants also reported mean (SD) daily added sugar intake of 61.5 (44.6) g, although the score range was large (2.7-316.5 g).

Table 3 provides the overall unadjusted and adjusted associations between each dietary exposure of interest and GrimAge2 resulting from multivariable linear regression models. In both unadjusted and adjusted models, all dietary exposures were statistically and significantly associated with GrimAge2 in the hypothesized, anticipated direction. In adjusted models, the associations observed for each dietary exposure were slightly attenuated. Each unit increase in the scores was associated with year changes in GrimAge2, as follows: aMED (β, −0.41; 95% CI, −0.69 to −0.13), AHEI-2010 (β, −0.05; 95% CI, −0.08 to −0.01), and ENI (β, −0.17; 95% CI, −0.29 to −0.06), indicating that healthier diets were associated with decelerated epigenetic aging. Each gram increase in added sugar intake was associated with a 0.02 (95% CI, 0.01 to 0.04) increase in GrimAge2, reflecting accelerated epigenetic aging.

Table 4 illustrates the associations of healthy diet measures (aMED, AHEI-2010, and ENI scores) and added sugar intake with epigenetic aging and gives the adjusted results for each healthy diet measure and added sugar intake with GrimAge2 in the context of each other. In all instances, healthier diet measures and added sugar intake appeared to maintain their independent associations with GrimAge2 in the expected directions. Associations were statistically significant for added sugar intake in all models as well as for aMED scores; 95% CIs were more imprecise for AHEI-2010 and ENI scores.

The findings of this cross-sectional study are among the first, to our knowledge, to demonstrate the association of added sugar intake with an epigenetic clock. Further, to our knowledge, it is the first study to examine the associations of diet with GrimAge2 and extend the applicability of such results to a cohort of Black and White women at midlife. As hypothesized, measures of healthy dietary patterns (aMED, AHEI-2010 scores), and high intakes of nutrients theoretically related to epigenetics (ENI) were associated with younger epigenetic age, while a higher intake of added sugar was associated with older epigenetic age. Additionally, this study examined indicators of healthy and less healthy diets in the same model, allowing simultaneous evaluation of each in the presence of the other. Although the magnitudes of associations were diminished and some 95% CIs became wider, their statistical significance generally persisted, supporting the existence of independent epigenetic associations of both healthy and less healthy diet measures. This approach is informative, as dietary components are often examined singularly or in indices, which can lead to erroneous conclusions if key contextual dietary components are not accounted for or are obscured. From these findings, even in healthy dietary contexts, added sugar still has detrimental associations with epigenetic age. Similarly, despite higher added sugar intake, healthier dietary intakes appear to remain generally associated with younger epigenetic age.

The number of published nutriepigenetic studies, particularly on examining second-generation epigenetic clock markers, is still relatively small. However, the results of the present study are consistent with the literature. Two other studies 7 , 10 have examined GrimAge1-associated outcomes and found higher diet quality scores, including the DASH and aMED, were associated with slower epigenetic aging. However, those studies were limited to older (>50 years) and White populations, limiting their demographic generalizability. Analyses of epigenetic aging and added sugar intake are new, but findings are consistent with the larger body of epidemiological work that has drawn connections between added sugar intake and cardiometabolic disease, 19 , 20 perhaps suggesting a potential mechanism underlying such observations. Granted, point and 95% CI estimates for the added sugar–GrimAge2 associations were close to zero, suggesting a smaller role for added sugar compared with healthy dietary measures; however, more studies are needed. Nevertheless, their statistical significance was persistent.

Nutrient-based inventories can provide epidemiological contributions for genomic health studies. The idea of epigenetically critical nutrients is important for 2 reasons. First, it supports the notion that epigenetic nutrient intakes above DRI levels could boost epigenetic preservation and potentially motivate updates to nutritional guidelines, an outcome advocated for by nutriepigenetic experts. 16 - 18 In the novel ENI constructed for the present study, points were awarded based on comparisons of average daily intakes with: (1) estimated average requirements, or the requirement considered adequate for half of the healthy individuals in a population, and (2) recommended dietary allowances or adequate intakes, or where 97% to 98% or essentially all of a population’s healthy individuals’ requirements for a nutrient are met. 15 Future iterations could test varying ENI scoring parameters relative to DRIs for epigenetic benefit. Second, taking a nutrient approach suggests that any dietary pattern rich in vitamins, minerals, and other bioactives could be useful for preserving epigenetic health. This is helpful because dietary patterns are socioculturally influenced, but a nutrient focus rather than a focus on foods could help bridge cultures, class, and geography. 9 The Okinawan diet, for example, is nutritionally similar to the Mediterranean-style diet but more aligned to Asian tastes. 38 In general, the sociodemographic determinants of diet should not be discounted. Across the US population, for instance, it is known that overall diet quality is mediocre and relatively low while added sugar intake is considerably high, as also observed in the sample of the present study. However, specific nutrient intakes will vary based on the particulars of dietary patterns. 22 , 36 As dietetics and medicine progresses into the era of personalized nutrition and personalized medicine, the role of social factors including diet will be important to consider in epigenetic studies and could figure prominently in work on health disparities.

Strengths of this study are its inclusion of a diverse group of women as well as use of robust measures of diet and DNAm. It was also possible to control for several potential sociodemographic confounders.

This study also has limitations. As a cross-sectional study, it is not possible to infer causality without temporality, and therefore longitudinal studies are needed. Additionally, diet was self-reported via 3-day food records, which may lead to underestimates and overestimates of intakes depending on the nutrient. Therefore, augmenting dietary assessment with food frequency questionnaires and/or biomarkers could be helpful. 39 Also, other nutrients with pro-epigenetic properties were not included in the current ENI. Still, the Cronbach α for this first ENI version was acceptable at 0.79 and it demonstrated good convergent validity with customary socioeconomic and demographic characteristics. The tolerable upper intake levels of the DRIs were not considered in constructing the ENI. Future work should assess the prevalence of intakes beyond upper limits to assess whether toxicity could be a concern.

To our knowledge, the findings of this cross-sectional study are among the first to find associations between indicators of healthy diet as well as added sugar intake and second-generation epigenetic aging markers and one of the first to include a cohort of Black women. Higher diet quality and higher consumption of antioxidants or anti-inflammatory nutrients were associated with younger epigenetic age, whereas higher consumption of added sugar was associated with older epigenetic age. Promotion of healthy diets aligned with chronic disease prevention and decreased added sugar consumption may support slower cellular aging relative to chronological age, although longitudinal analyses are needed.

Accepted for Publication: April 29, 2024.

Published: July 29, 2024. doi:10.1001/jamanetworkopen.2024.22749

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Chiu DT et al. JAMA Network Open .

Corresponding Author: Dorothy T. Chiu, PhD, Osher Center for Integrative Health, University of California, San Francisco, 1545 Divisadero St, #301D, San Francisco, CA 94115 ( [email protected] ); Barbara A. Laraia, PhD, MPH, RD, Community Health Sciences Division, School of Public Health, University of California, Berkeley, 2121 Berkeley Way, Berkeley, CA 94720 ( [email protected] ).

Author Contributions: Drs Chiu and Laraia had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Epel and Laraia share co–senior authorship on this article.

Concept and design: Chiu, Hamlat, Epel, Laraia.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Chiu, Hamlat, Laraia.

Critical review of the manuscript for important intellectual content: Hamlat, Zhang, Epel, Laraia.

Statistical analysis: Chiu, Hamlat, Zhang.

Obtained funding: Epel, Laraia.

Administrative, technical, or material support: Chiu, Laraia.

Supervision: Epel, Laraia.

Conflict of Interest Disclosures: Dr Chiu reported receiving support from grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD); the National Heart, Lung, and Blood Institute (NHLBI); the National Institute on Aging (NIA); and the National Center for Complementary and Integrative Health (NCCIH) during the conduct of the study. Dr Hamlat reported receiving grants from the National Institutes of Health (NIH) during the conduct of the study. Dr Laraia reported receiving grants from NIH NICHD during the conduct of the study. No other disclosures were reported.

Funding/Support: The research reported in this publication was supported by grant R01HD073568 from the Eunice Kennedy Shriver NICHD (Drs Laraia and Epel, principal investigators [PIs]); grant R56HL141878 from the NHLBI; and grants R56AG059677 and R01AG059677 from the NIA (both for Drs Epel and Laraia, PIs). The participation of Dr Chiu was supported by the University of California, San Francisco Osher Center research training fellowship program under grant T32AT003997 from NCCIH.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See the Supplement .

Additional Contributions: We recognize the past and present NHLBI Growth and Health Study (NGHS) staff for their talents and dedication, without which the study and these analyses would not have been possible. We also thank the Nutrition Policy Institute for providing consultation and support with historical study data. Additionally, we express immense gratitude to Ake T. Lu, PhD, and Steve Horvath, PhD, now of Altos Labs, for their epigenetic clock expertise and consultation. Neither was financially compensated for their contributions beyond their usual salary. Of note, we thank the NGHS participants for their time and efforts over the years.

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Genomics articles from across Nature Portfolio

Genomics is the study of the full genetic complement of an organism (the genome). It employs recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble, and analyse the structure and function of genomes.

Toward learning a foundational representation of cells and genes

Inspired by the success of large-scale machine learning models in natural language, several groups are adapting these models for cellular data using massive single-cell datasets.

• Mohammad Lotfollahi

DNA strands show symmetry in damage tolerance but asymmetries in repair efficiency

The two strands of DNA, although chemically equivalent, are replicated and repaired asymmetrically. Insights into the persistence of DNA damage show how strand-specific interactions shape the genome-wide distribution of mutations, including the unexpected symmetry of mutations arising in the DNA strands during replication.

Achieving de novo scaffolding of chromosome-level haplotypes using Hi-C data

To overcome key challenges in scaffolding chromosome-level haplotypes with Hi-C data, we developed HapHiC, a Hi-C scaffolding tool that exhibits superior performance in handling haplotype-resolved assemblies without the need for reference genomes. We used HapHiC to construct the complex genome of triploid Miscanthus × giganteus .

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Non-redundant metagenome-assembled genomes of activated sludge reactors at different disturbances and scales

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Language models for biological research: a primer

This primer introduces the elements and best practices of adapting and using language models for biology.

• Elana Simon
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Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments

This Perspective discusses the methodologies, application and evaluation of interpretable machine learning (IML) approaches in computational biology, with particular focus on common pitfalls when using IML and how to avoid them.

• Valerie Chen

Exploring unsolved cases of lissencephaly spectrum: integrating exome and genome sequencing for higher diagnostic yield

• Shogo Furukawa
• Mitsuhiro Kato
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Extreme mitochondrial reduction in a novel group of free-living metamonads

Mitochondria are essential cellular components that are found in animals, plants, fungi, and protists. This study reports what is believed to be the first example of complete mitochondrial loss in a free-living organism, providing insights into the evolutionary plasticity of eukaryotic cells.

• Shelby K. Williams
• Jon Jerlström Hultqvist
• Andrew J. Roger

Genomic data provide insights into the classification of extant termites

Here, the authors produce an updated termite classification with genomic scale analyses, highlighting thirteen family-level lineages and resilience of their classification to future termite research.

• Simon Hellemans
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Unlocking the power of spatial omics with AI

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• Kyle Coleman
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Unlocking gene regulation with sequence-to-function models

By exploiting recent advances in modern artificial intelligence and large-scale functional genomic datasets, sequence-to-function models learn the relationship between genomic DNA and its multilayer gene regulatory functions. These models are poised to uncover mechanistic relationships across layers of cellular biology, which will transform our understanding of cis gene regulation and open new avenues for discovering disease mechanisms.

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Scientists are using consumer-genomics databases to link living people to ancestors from the recent and not-so-recent past. But the meaning of these connections isn’t always clear.

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Study finds omega-3 supplements reduce genetic risk of high total cholesterol, LDL and triglyceride levels

by University of Georgia

Fish oil supplements are a multi-billion dollar industry in the U.S. and abroad, with about 2 out of every 25 people popping the popular omega-3 pills.

And a new study from the University of Georgia published in The American Journal of Clinical Nutrition might encourage a new population to start looking into the supplements as well: people with a genetic predisposition to high cholesterol.

Using genetic data from more than 441,000 participants, the researchers calculated a score to predict the genetic likelihood of high levels of total cholesterol, high LDL cholesterol (which is often referred to as "bad" cholesterol), triglycerides and HDL cholesterol (or "good" cholesterol).

"Recent advances in genetic studies have allowed us to predict someone's genetic risk of high cholesterol," said Yitang Sun, a recent doctoral graduate from UGA's Department of Genetics. "But the current prediction has room for improvement because it does not consider individual differences in lifestyles, such as taking fish oil supplements."

The researchers found that participants who reported taking fish oil supplements have lower blood lipid levels than predicted, especially for total cholesterol, LDL cholesterol and triglycerides.

"Our study shows that considering lifestyles will improve genetic prediction," said Kaixiong Ye, corresponding author of the study and an assistant professor of genetics in UGA's Franklin College of Arts and Sciences. "Our findings also support that fish oil supplements may counteract the genetic predisposition to high cholesterol."

Fish oil counters effect of family history of high cholesterol

It's no secret that high cholesterol is bad for the body. Arteries start to harden, and the risk of heart attack or stroke increases.

While a healthy diet and exercise can help prevent it, the Centers for Disease Control and Prevention estimates that more than 86 million American adults—or about 1 in 4—have high cholesterol.

Millions more are at risk of developing high cholesterol due to a variety of factors including one they can't control: genetics.

For people whose families have a history of high cholesterol , the study's findings offer another possibility to help safeguard their health.

"Taking fish oil is associated with a shift toward a healthy lipid profile," Ye said.

The researchers also analyzed the effects of fish oil on HDL cholesterol and found the supplements are beneficial in raising the so-called "good" cholesterol.

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