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Whole-Genome Sequencing Plus AI Yields Same-Day Genetic Diagnoses

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Caption: Rapid whole-genome sequencing helped doctors diagnose Sebastiana Manuel with Ohtahara syndrome, a neurological condition that causes seizures. Her data are now being used as part of an effort to speed the diagnosis of other children born with unexplained illnesses. Credits: Getty Images (left); Jenny Siegwart (right).

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.


[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).


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

NASA Twins Study Reveals Health Effects of Space Flight

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Sending one identical twin into space while the other stays behind on Earth might sound like the plot of a sci-fi thriller. But it’s actually a setup for some truly fascinating scientific research!

As part of NASA’s landmark Twins Study, Scott Kelly became the first U.S. astronaut to spend nearly a year in “weightless” microgravity conditions aboard the International Space Station. Meanwhile, his identical twin, retired astronaut Mark Kelly, remained earthbound. Researchers put both men—who like all identical twins shared the same genetic makeup at birth—through the same battery of biomedical tests to gauge how the human body responds to life in space. The good news for the future of space travel is that the results indicated that health is “mostly sustained” during a prolonged stay in space.

Reporting in the journal Science, the Twins Study team, which included several NIH-funded researchers, detailed many thousands of differences between the Kelly twins at the molecular, cellular, and physiological levels during the 340-day observation period. However, most of Scott’s measures returned to near pre-flight levels within six months of rejoining Mark on Earth.

Over the past nearly 60 years, 559 people have flown in space. While weightless conditions are known to speed various processes associated with aging, few astronauts have remained in space for more than a few months at a time. With up to three year missions to the moon or Mars planned for the future, researchers want to get a better sense of how the human body will hold up under microgravity conditions for longer periods.

To get a more holistic answer, researchers collected a variety of biological samples from the Kelly twins before, during, and after Scott’s spaceflight. All told, more than 300 samples were collected over the course of 27 months.

Multiple labs around the country used state-of-the art tools to examine those samples in essentially every way they could think of doing. Those analyses offer a remarkably detailed view of changes in an astronaut’s biology and health while in space.

With so much data, there were lots of interesting findings to report, including many changes in the expression of Scott’s genes that weren’t observed in his twin. While most of these changes returned to preflight levels within six months of Scott’s return to Earth, about 7 percent of his genes continued to be expressed at different levels. These included some related to DNA repair and the immune system.

Despite those changes in immunity-related gene expression, his immune system appeared to remain fully functional. His body responded to the flu vaccine administered in space just as would be expected back home on Earth.

Scott also had some measurable changes in telomeres—complexes of specialized DNA sequences, RNA, and protein that protect the tips of our chromosomes. These generally shorten a bit each time cells divide. But during the time in space, the telomeres in Scott’s white blood cells measured out at somewhat greater length.

Potentially, this is because some of his stem cells, which are younger and haven’t gone through as many cell divisions, were being released into the blood. Back on Earth, his telomere lengths returned to an average length within six months of his return. Over the course of the study, the earthbound telomeres of his twin brother Mark remained stable.

Researchers also uncovered small but significant changes to Scott’s gut microbiome, the collection of microbes that play important roles in digestion and the immune system. More specifically, there was a shift in the ratio of two major groups of bacteria. Once back on Earth, his microbiome quickly shifted back to its original preflight state.

The data also provided some metabolic evidence suggesting that Scott’s mitochondria, the cellular powerhouses that supply the body with energy, weren’t functioning at full capacity in space. While further study is needed, the NIH-funded team led by Kumar Sharma, University of Texas Health Science Center, San Antonio, suggests that changes in the mitochondria might underlie changes often seen in space to the human cardiovascular system, kidneys, and eyes.

Of course, such a small, two-person study makes it hard to draw any general conclusions about human health in space. But the comparisons certainly help to point us in the right direction. They provide a framework for understanding how the human body responds on a molecular and cellular level to microgravity over time. They also may hold important lessons for understanding human health and precision medicine down here on Earth.

I look forward to future space missions and their contributions to biomedical research. I’m also happy to report, it will be a short wait.

Last year, I highlighted the Tissue Chips in Space Initiative. It’s a unique collaboration between NIH and NASA in which dozens of human tissue chips—tiny, 3D devices bioengineered to model different tissues and organs—will be sent to the International Space Station to study the accelerated aging that occurs in space.

The first tissue chips were sent to the International Space Station last December. And I’m pleased to report that more were aboard recently when the SpaceX Dragon cargo spacecraft made a resupply run to the International Space Station. On May 8, astronauts there successfully completed offloading miniaturized tissue chips of the lungs, bone marrow, and kidneys, enabling more truly unique science in low gravity that couldn’t be performed down here on Earth.


[1] The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight. Garrett-Bakelman FE, Darshi M, Green SJ, Gur RC, Lin L, Macias BR, et. al. Science. 2019 Apr 12;364(6436).


Twins Study (NASA)

Launches and Landings (NASA. Washington, D.C.)

Kumar Sharma (University of Texas Health Science Center, San Antonio)

Tissue Chips in Space (National Center for Advancing Translational Sciences/NIH)

NIH Support: National Institute on Aging; National Institute of Diabetes and Digestive and Kidney Diseases