rare diseases
A Rare Public Health Challenge
Posted on by Joni Rutter, Ph.D., National Center for Advancing Translational Sciences
Most public health challenges may seem obvious. The COVID-19 pandemic, for example, swept the globe and in some way touched the lives of everyone. But not all public health challenges are as readily apparent.
Rare diseases are a case in point. While individually each disease is rare, collectively rare diseases are common: More than 10,000 rare diseases affect nearly 400 million people worldwide. In the United States, the prevalence of rare diseases (over 30 million people) rivals or exceeds that of common diseases such as diabetes (37.3 million people), Alzheimer’s disease (6.5 million people), and heart failure (6.2 million people).
Shouldering the Burden of Rare Diseases
As with common diseases, the personal and economic burdens of rare diseases are immense. People who live with rare diseases often struggle for years before they receive an accurate diagnosis, with some remaining undiagnosed for a decade or longer. The diagnostic odyssey includes countless doctor visits, unnecessary tests and procedures, and wrong diagnoses. For people in rural and low-income communities, lack of access to care is an additional barrier to an accurate diagnosis. And a diagnosis often doesn’t lead to better health—only about 5 percent of rare diseases have U.S. Food and Drug Administration–approved treatments.
Collectively, the personal burdens of those with rare diseases impose a significant economic cost on the nation. When quantifying the health care expenses for people with rare diseases, we found that they have three to five times greater costs than those without rare diseases [1]. In the United States, the total direct medical costs for those with rare diseases is approximately $400 billion annually, a figure validated independently by the EveryLife Foundation for Rare Diseases. The EveryLife study also included indirect and non-medical costs, resulting in a higher total economic burden of nearly $1 trillion annually [2].
What’s even starker is that the true scope and impact of rare diseases actually may be greater because rare diseases aren’t easily visible in our health care system. Many of the diseases are too rare to have a code that identifies them in the electronic health record (EHR).
Speeding Up the Search for Solutions
Each and every day, NIH’s National Center for Advancing Translational Sciences (NCATS) works with patients, advocates, clinicians, and researchers to meet the public health challenge of rare diseases. Driving those conversations are three overarching goals to help people living with rare diseases get the high-quality care they need, faster:
1. Shorten the duration of the diagnostic odyssey by more than half. The diagnostic odyssey for someone with a rare disease takes on average seven years, and there are several ways we can speed the journey. For example, we are designing computational tools to detect rare genetic disorders from EHR data. This work is part of a broader research effort focused on using genetic analysis and machine learning to make it easier for health care providers to diagnose people with rare diseases correctly. Also, connecting patients more quickly with each other and the research community can hasten the search for answers. Check out the resources below to learn about rare diseases, find patient support organizations, and get involved in research efforts.
2. Develop treatments for more than one rare disease at a time. A key strategy is leveraging what rare diseases have in common. Some of our efforts build upon the fact that 80–85 percent of rare diseases are genetic. We can use this knowledge to develop genetic and molecular interventions for groups of rare diseases. Two programs—the Platform Vector Gene Therapy pilot project and the Bespoke Gene Therapy Consortium, which is part of the public-private Accelerating Medicines Partnership®—are streamlining the gene therapy development process. Their ultimate goal is to make gene therapies more accessible to many people with rare diseases. We also have joined in to advance the clinical application of genome editing for rare genetic diseases.
The NCATS-led Rare Diseases Clinical Research Network, which is supported across NIH, brings scientists together with rare disease organizations and patient advocacy groups to better understand common characteristics, which also might speed clinical research. With this in mind, we are adapting a clinical trial strategy used in cancer research to test a single therapy on multiple rare diseases.
3. Make it easier and more efficient for scientists to discover and develop treatments for rare diseases. NCATS develops ways for new treatments to reach people more quickly. Repurposing drugs, for example, is revealing already-approved drugs that may work for rare diseases. Programs such as Therapeutics for Rare and Neglected Diseases and Bridging Interventional Development Gaps move basic research discoveries in the lab closer to becoming new drugs. Ambitious initiatives, such as the Biomedical Data Translator, unite data from biomedical research, clinical trials, and EHRs to find treatments for rare diseases faster.
The COVID-19 pandemic showed us the power of working together to solve public health challenges. Let’s now come together to address the public health challenge of rare diseases. If you want to get involved, please join us at Rare Disease Day at NIH 2023 on February 28. You’ll hear personal stories, learn about the latest research, and discover helpful resources. I hope to see you there!
References:
[1] The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems. Tisdale A, Cutillo CM, Nathan R, Russo P, Laraway B, Haendel M, Nowak D, Hasche C, Chan CH, Griese E, Dawkins H, Shukla O, Pearce DA, Rutter JL, Pariser AR. Orphanet Journal of Rare Diseases. 2021 Oct 22; ;16(1):429.
[2] The national economic burden of rare disease in the United States in 2019. Yang G, Cintina I, Pariser A, Oehrlein E, Sullivan J, Kennedy A. Orphanet Journal of Rare Diseases. 2022 Apr 12;17(1):163.
Links:
Rare Disease Day at NIH 2023 (National Center for Advancing Translational Sciences/NIH)
Genetic and Rare Diseases Information Center (NCATS)
Toolkit for Patient-Focused Therapy Development (NCATS)
Rare Diseases Registry Program (NCATS)
Rare Diseases Research and Resources (NCATS)
Note: Dr. Lawrence Tabak, who performs the duties of the NIH Director, has asked the heads of NIH’s Institutes and Centers (ICs) to contribute occasional guest posts to the blog to highlight some of the interesting science that they support and conduct. This is the 23rd in the series of NIH IC guest posts that will run until a new permanent NIH director is in place.
Partnership to Expand Effective Gene Therapies for Rare Diseases
Posted on by Dr. Francis Collins
Rare diseases aren’t so rare. Collectively, up to 30 million Americans, many of them children, are born with one of the approximately 7,000 known rare diseases. Most of these millions of people also share a common genetic feature: their diseases are caused by an alteration in a single gene.
Many of these alterations could theoretically be targeted with therapies designed to correct or replace the faulty gene. But there have been significant obstacles in realizing this dream. The science of gene therapy has been making real progress, but pursuing promising approaches all the way to clinical trials and gaining approval from the U.S. Food and Drug Administration (FDA) is still very difficult. Another challenge is economic: for the rarest of these conditions (which is most of them), the market is so small that most companies have no financial incentive to pursue them.
To overcome these obstacles and provide hope for those with rare diseases, we need a new way of doing things. One way to do things differently—and more efficiently—is the recently launched Bespoke Gene Therapy Consortium (BGTC). It is a bold partnership of NIH, the FDA, 10 pharmaceutical companies, several non-profit organizations, and the Foundation for the National Institutes of Health [1]. Its aim: optimize the gene therapy development process and help fill the significant unmet medical needs of people with rare diseases.
The BGTC, which is also part of NIH’s Accelerating Medicines Partnership® (AMP®), will enable the easier, faster, and cheaper pursuit of “bespoke” gene therapies, meaning made for a particular customer or user. The goal of the Consortium is to reduce the cost of gene therapy protocols and increase the likelihood of success, making it more attractive for companies to invest in rare diseases and bring treatments to patients who desperately need them.
Fortunately, there is already some precedent. The BGTC effort builds on a pilot project led by NIH’s National Center for Advancing Translational Sciences (NCATS) known as Platform Vector Gene Therapy (PaVe-GT). This pilot project has helped to develop adeno-associated viruses (AAVs), which are small benign viruses engineered in the lab to carry a therapeutic gene. They are commonly used in gene therapy-related clinical trials of rare diseases.
Since the launch of PaVe-GT two years ago, the project has helped to introduce greater efficiency to gene therapy trials for rare disease. It’s also offered a way to get around the standard one-disease-at-a-time approach to therapeutic development that has stymied progress in treating rare conditions.
The BGTC will now continue to advance in-depth understanding of basic AAV biology and develop better gene therapies for rare and also common diseases. The consortium aims to develop a standard set of analytic tests to improve the production and functional assessment of AAVs and therapeutic genes. Such tests will be broadly applicable and will bring the needed manufacturing efficiency required for developing gene therapies for very rare conditions.
The BGTC also will work toward bringing therapies sooner to individuals in need. To start, BGTC-funded research will support four to six clinical trials, each focused on a distinct rare disease. While the details haven’t yet been decided, these diseases are expected to be rare, single-gene diseases that lack gene therapies or commercial programs in development, despite having substantial groundwork in place to enable the rapid initiation of preclinical and clinical studies.
Through these trials, the BGTC will chart a path from studies in animal models of disease to human clinical trials that cuts years off the development process. This will include exploring methods to streamline regulatory requirements and processes for FDA approval of safe and effective gene therapies, including developing standardized approaches to preclinical testing.
This work promises to be a significant investment in helping people with rare diseases. The NIH and private partners will contribute approximately $76 million over five years to support BGTC-funded projects. This includes about $39.5 million from the participating NIH institutes and centers, pending availability of funds. The NCATS, which is NIH’s lead for BGTC, is expected to contribute approximately $8 million over five years.
Today, only two rare inherited conditions have FDA-approved gene therapies. The hope is this investment will raise that number and ultimately reduce the many significant challenges, including health care costs, faced by families that have a loved one with a rare disease. In fact, a recent study found that health care costs for people with a rare disease are three to five times greater than those for people without a rare disease [2]. These families need help, and BGTC offers an encouraging new way forward for them.
References:
[1] NIH, FDA and 15 private organizations join forces to increase effective gene therapies for rare diseases. NIH news release, October 27, 2021.
[2] The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems. Tisdale, A., Cutillo, C.M., Nathan, R. et al. Orphanet J Rare Dis 16, 429 (2021).
Links:
FAQ About Rare Diseases (National Center for Advancing Translational Sciences/NIH)
Bespoke Gene Therapy Consortium (BGTC)
Platform Vector Gene Therapy (NCATS)
Accelerating Medicines Partnership® (AMP®) (NIH)
NIH Support: National Center for Advancing Translational Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Eye Institute; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Dental and Craniofacial Research; National Institute of Mental Health; National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; and NIH’s BRAIN Initiative.
Engineering a Better Way to Deliver Therapeutic Genes to Muscles
Posted on by Dr. Francis Collins
Amid all the progress toward ending the COVID-19 pandemic, it’s worth remembering that researchers here and around the world continue to make important advances in tackling many other serious health conditions. As an inspiring NIH-supported example, I’d like to share an advance on the use of gene therapy for treating genetic diseases that progressively degenerate muscle, such as Duchenne muscular dystrophy (DMD).
As published recently in the journal Cell, researchers have developed a promising approach to deliver therapeutic genes and gene editing tools to muscle more efficiently, thus requiring lower doses [1]. In animal studies, the new approach has targeted muscle far more effectively than existing strategies. It offers an exciting way forward to reduce unwanted side effects from off-target delivery, which has hampered the development of gene therapy for many conditions.
In boys born with DMD (it’s an X-linked disease and therefore affects males), skeletal and heart muscles progressively weaken due to mutations in a gene encoding a critical muscle protein called dystrophin. By age 10, most boys require a wheelchair. Sadly, their life expectancy remains less than 30 years.
The hope is gene therapies will one day treat or even cure DMD and allow people with the disease to live longer, high-quality lives. Unfortunately, the benign adeno-associated viruses (AAVs) traditionally used to deliver the healthy intact dystrophin gene into cells mostly end up in the liver—not in muscles. It’s also the case for gene therapy of many other muscle-wasting genetic diseases.
The heavy dose of viral vector to the liver is not without concern. Recently and tragically, there have been deaths in a high-dose AAV gene therapy trial for X-linked myotubular myopathy (XLMTM), a different disorder of skeletal muscle in which there may already be underlying liver disease, potentially increasing susceptibility to toxicity.
To correct this concerning routing error, researchers led by Mohammadsharif Tabebordbar in the lab of Pardis Sabeti, Broad Institute of MIT and Harvard and Harvard University, Cambridge, MA, have now assembled an optimized collection of AAVs. They have been refined to be about 10 times better at reaching muscle fibers than those now used in laboratory studies and clinical trials. In fact, researchers call them myotube AAVs, or MyoAAVs.
MyoAAVs can deliver therapeutic genes to muscle at much lower doses—up to 250 times lower than what’s needed with traditional AAVs. While this approach hasn’t yet been tried in people, animal studies show that MyoAAVs also largely avoid the liver, raising the prospect for more effective gene therapies without the risk of liver damage and other serious side effects.
In the Cell paper, the researchers demonstrate how they generated MyoAAVs, starting out with the commonly used AAV9. Their goal was to modify the outer protein shell, or capsid, to create an AAV that would be much better at specifically targeting muscle. To do so, they turned to their capsid engineering platform known as, appropriately enough, DELIVER. It’s short for Directed Evolution of AAV capsids Leveraging In Vivo Expression of transgene RNA.
Here’s how DELIVER works. The researchers generate millions of different AAV capsids by adding random strings of amino acids to the portion of the AAV9 capsid that binds to cells. They inject those modified AAVs into mice and then sequence the RNA from cells in muscle tissue throughout the body. The researchers want to identify AAVs that not only enter muscle cells but that also successfully deliver therapeutic genes into the nucleus to compensate for the damaged version of the gene.
This search delivered not just one AAV—it produced several related ones, all bearing a unique surface structure that enabled them specifically to target muscle cells. Then, in collaboration with Amy Wagers, Harvard University, Cambridge, MA, the team tested their MyoAAV toolset in animal studies.
The first cargo, however, wasn’t a gene. It was the gene-editing system CRISPR-Cas9. The team found the MyoAAVs correctly delivered the gene-editing system to muscle cells and also repaired dysfunctional copies of the dystrophin gene better than the CRISPR cargo carried by conventional AAVs. Importantly, the muscles of MyoAAV-treated animals also showed greater strength and function.
Next, the researchers teamed up with Alan Beggs, Boston Children’s Hospital, and found that MyoAAV was effective in treating mouse models of XLMTM. This is the very condition mentioned above, in which very high dose gene therapy with a current AAV vector has led to tragic outcomes. XLMTM mice normally die in 10 weeks. But, after receiving MyoAAV carrying a corrective gene, all six mice had a normal lifespan. By comparison, mice treated in the same way with traditional AAV lived only up to 21 weeks of age. What’s more, the researchers used MyoAAV at a dose 100 times lower than that currently used in clinical trials.
While further study is needed before this approach can be tested in people, MyoAAV was also used to successfully introduce therapeutic genes into human cells in the lab. This suggests that the early success in animals might hold up in people. The approach also has promise for developing AAVs with potential for targeting other organs, thereby possibly providing treatment for a wide range of genetic conditions.
The new findings are the result of a decade of work from Tabebordbar, the study’s first author. His tireless work is also personal. His father has a rare genetic muscle disease that has put him in a wheelchair. With this latest advance, the hope is that the next generation of promising gene therapies might soon make its way to the clinic to help Tabebordbar’s father and so many other people.
Reference:
[1] Directed evolution of a family of AAV capsid variants enabling potent muscle-directed gene delivery across species. Tabebordbar M, Lagerborg KA, Stanton A, King EM, Ye S, Tellez L, Krunnfusz A, Tavakoli S, Widrick JJ, Messemer KA, Troiano EC, Moghadaszadeh B, Peacker BL, Leacock KA, Horwitz N, Beggs AH, Wagers AJ, Sabeti PC. Cell. 2021 Sep 4:S0092-8674(21)01002-3.
Links:
Muscular Dystrophy Information Page (National Institute of Neurological Disorders and Stroke/NIH)
X-linked myotubular myopathy (Genetic and Rare Diseases Information Center/National Center for Advancing Translational Sciences/NIH)
Somatic Cell Genome Editing (Common Fund/NIH)
Mohammadsharif Tabebordbar (Broad Institute of MIT and Harvard and Harvard University, Cambridge, MA)
Sabeti Lab (Broad Institute of MIT and Harvard and Harvard University)
NIH Support: Eunice Kennedy Shriver National Institute of Child Health and Human Development; Common Fund
Seeing the Cytoskeleton in a Whole New Light
Posted on by Dr. Francis Collins
It’s been 25 years since researchers coaxed a bacterium to synthesize an unusual jellyfish protein that fluoresced bright green when irradiated with blue light. Within months, another group had also fused this small green fluorescent protein (GFP) to larger proteins to make their whereabouts inside the cell come to light—like never before.
To mark the anniversary of this Nobel Prize-winning work and show off the rainbow of color that is now being used to illuminate the inner workings of the cell, the American Society for Cell Biology (ASCB) recently held its Green Fluorescent Protein Image and Video Contest. Over the next few months, my blog will feature some of the most eye-catching entries—starting with this video that will remind those who grew up in the 1980s of those plasma balls that, when touched, light up with a simulated bolt of colorful lightning.
This video, which took third place in the ASCB contest, shows the cytoskeleton of a frequently studied human breast cancer cell line. The cytoskeleton is made from protein structures called microtubules, made visible by fluorescently tagging a protein called doublecortin (orange). Filaments of another protein called actin (purple) are seen here as the fine meshwork in the cell periphery.
The cytoskeleton plays an important role in giving cells shape and structure. But it also allows a cell to move and divide. Indeed, the motion in this video shows that the complex network of cytoskeletal components is constantly being organized and reorganized in ways that researchers are still working hard to understand.
Jeffrey van Haren, Erasmus University Medical Center, Rotterdam, the Netherlands, shot this video using the tools of fluorescence microscopy when he was a postdoctoral researcher in the NIH-funded lab of Torsten Wittman, University of California, San Francisco.
All good movies have unusual plot twists, and that’s truly the case here. Though the researchers are using a breast cancer cell line, their primary interest is in the doublecortin protein, which is normally found in association with microtubules in the developing brain. In fact, in people with mutations in the gene that encodes this protein, neurons fail to migrate properly during development. The resulting condition, called lissencephaly, leads to epilepsy, cognitive disability, and other neurological problems.
Cancer cells don’t usually express doublecortin. But, in some of their initial studies, the Wittman team thought it would be much easier to visualize and study doublecortin in the cancer cells. And so, the researchers tagged doublecortin with an orange fluorescent protein, engineered its expression in the breast cancer cells, and van Haren started taking pictures.
This movie and others helped lead to the intriguing discovery that doublecortin binds to microtubules in some places and not others [1]. It appears to do so based on the ability to recognize and bind to certain microtubule geometries. The researchers have since moved on to studies in cultured neurons.
This video is certainly a good example of the illuminating power of fluorescent proteins: enabling us to see cells and their cytoskeletons as incredibly dynamic, constantly moving entities. And, if you’d like to see much more where this came from, consider visiting van Haren’s Twitter gallery of microtubule videos here:
Reference:
[1] Doublecortin is excluded from growing microtubule ends and recognizes the GDP-microtubule lattice. Ettinger A, van Haren J, Ribeiro SA, Wittmann T. Curr Biol. 2016 Jun 20;26(12):1549-1555.
Links:
Lissencephaly Information Page (National Institute of Neurological Disorders and Stroke/NIH)
Wittman Lab (University of California, San Francisco)
Green Fluorescent Protein Image and Video Contest (American Society for Cell Biology, Bethesda, MD)
NIH Support: National Institute of General Medical Sciences
Whole-Genome Sequencing Plus AI Yields Same-Day Genetic Diagnoses
Posted on by Dr. Francis Collins
Back in April 2003, when the international Human Genome Project successfully completed the first reference sequence of the human DNA blueprint, we were thrilled to have achieved that feat in just 13 years. Sure, the U.S. contribution to that first human reference sequence cost an estimated $400 million, but we knew (or at least we hoped) that the costs would come down quickly, and the speed would accelerate. How far we’ve come since then! A new study shows that whole genome sequencing—combined with artificial intelligence (AI)—can now be used to diagnose genetic diseases in seriously ill babies in less than 24 hours.
Take a moment to absorb this. I would submit that there is no other technology in the history of planet Earth that has experienced this degree of progress in speed and affordability. And, at the same time, DNA sequence technology has achieved spectacularly high levels of accuracy. The time-honored adage that you can only get two out of three for “faster, better, and cheaper” has been broken—all three have been dramatically enhanced by the advances of the last 16 years.
Rapid diagnosis is critical for infants born with mysterious conditions because it enables them to receive potentially life-saving interventions as soon as possible after birth. In a study in Science Translational Medicine, NIH-funded researchers describe development of a highly automated, genome-sequencing pipeline that’s capable of routinely delivering a diagnosis to anxious parents and health-care professionals dramatically earlier than typically has been possible [1].
While the cost of rapid DNA sequencing continues to fall, challenges remain in utilizing this valuable tool to make quick diagnostic decisions. In most clinical settings, the wait for whole-genome sequencing results still runs more than two weeks. Attempts to obtain faster results also have been labor intensive, requiring dedicated teams of experts to sift through the data, one sample at a time.
In the new study, a research team led by Stephen Kingsmore, Rady Children’s Institute for Genomic Medicine, San Diego, CA, describes a streamlined approach that accelerates every step in the process, making it possible to obtain whole-genome test results in a median time of about 20 hours and with much less manual labor. They propose that the system could deliver answers for 30 patients per week using a single genome sequencing instrument.
Here’s how it works: Instead of manually preparing blood samples, his team used special microbeads to isolate DNA much more rapidly with very little labor. The approach reduced the time for sample preparation from 10 hours to less than three. Then, using a state-of-the-art DNA sequencer, they sequence those samples to obtain good quality whole genome data in just 15.5 hours.
The next potentially time-consuming challenge is making sense of all that data. To speed up the analysis, Kingsmore’s team took advantage of a machine-learning system called MOON. The automated platform sifts through all the data using artificial intelligence to search for potentially disease-causing variants.
The researchers paired MOON with a clinical language processing system, which allowed them to extract relevant information from the child’s electronic health records within seconds. Teaming that patient-specific information with data on more than 13,000 known genetic diseases in the scientific literature, the machine-learning system could pick out a likely disease-causing mutation out of 4.5 million potential variants in an impressive 5 minutes or less!
To put the system to the test, the researchers first evaluated its ability to reach a correct diagnosis in a sample of 101 children with 105 previously diagnosed genetic diseases. In nearly every case, the automated diagnosis matched the opinions reached previously via the more lengthy and laborious manual interpretation of experts.
Next, the researchers tested the automated system in assisting diagnosis of seven seriously ill infants in the intensive care unit, and three previously diagnosed infants. They showed that their automated system could reach a diagnosis in less than 20 hours. That’s compared to the fastest manual approach, which typically took about 48 hours. The automated system also required about 90 percent less manpower.
The system nailed a rapid diagnosis for 3 of 7 infants without returning any false-positive results. Those diagnoses were made with an average time savings of more than 22 hours. In each case, the early diagnosis immediately influenced the treatment those children received. That’s key given that, for young children suffering from serious and unexplained symptoms such as seizures, metabolic abnormalities, or immunodeficiencies, time is of the essence.
Of course, artificial intelligence may never replace doctors and other healthcare providers. Kingsmore notes that 106 years after the invention of the autopilot, two pilots are still required to fly a commercial aircraft. Likewise, health care decisions based on genome interpretation also will continue to require the expertise of skilled physicians.
Still, such a rapid automated system will prove incredibly useful. For instance, this system can provide immediate provisional diagnosis, allowing the experts to focus their attention on more difficult unsolved cases or other needs. It may also prove useful in re-evaluating the evidence in the many cases in which manual interpretation by experts fails to provide an answer.
The automated system may also be useful for periodically reanalyzing data in the many cases that remain unsolved. Keeping up with such reanalysis is a particular challenge considering that researchers continue to discover hundreds of disease-associated genes and thousands of variants each and every year. The hope is that in the years ahead, the combination of whole genome sequencing, artificial intelligence, and expert care will make all the difference in the lives of many more seriously ill babies and their families.
Reference:
[1] Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation. Clark MM, Hildreth A, Batalov S, Ding Y, Chowdhury S, Watkins K, Ellsworth K, Camp B, Kint CI, Yacoubian C, Farnaes L, Bainbridge MN, Beebe C, Braun JJA, Bray M, Carroll J, Cakici JA, Caylor SA, Clarke C, Creed MP, Friedman J, Frith A, Gain R, Gaughran M, George S, Gilmer S, Gleeson J, Gore J, Grunenwald H, Hovey RL, Janes ML, Lin K, McDonagh PD, McBride K, Mulrooney P, Nahas S, Oh D, Oriol A, Puckett L, Rady Z, Reese MG, Ryu J, Salz L, Sanford E, Stewart L, Sweeney N, Tokita M, Van Der Kraan L, White S, Wigby K, Williams B, Wong T, Wright MS, Yamada C, Schols P, Reynders J, Hall K, Dimmock D, Veeraraghavan N, Defay T, Kingsmore SF. Sci Transl Med. 2019 Apr 24;11(489).
Links:
DNA Sequencing Fact Sheet (National Human Genome Research Institute/NIH)
Genomics and Medicine (NHGRI/NIH)
Genetic and Rare Disease Information Center (National Center for Advancing Translational Sciences/NIH)
Stephen Kingsmore (Rady Children’s Institute for Genomic Medicine, San Diego, CA)
NIH Support: National Institute of Child Health and Human Development; National Human Genome Research Institute; National Center for Advancing Translational Sciences
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