Big Data Study Reveals Possible Subtypes of Type 2 Diabetes

Computational model

Caption: Computational model showing study participants with type 2 diabetes grouped into three subtypes, based on similarities in data contained in their electronic health records. Such information included age, gender (red/orange/yellow indicates females; blue/green, males), health history, and a range of routine laboratory and medical tests.
Credit: Dudley Lab, Icahn School of Medicine at Mount Sinai, New York

In recent years, there’s been a lot of talk about how “Big Data” stands to revolutionize biomedical research. Indeed, we’ve already gained many new insights into health and disease thanks to the power of new technologies to generate astonishing amounts of molecular data—DNA sequences, epigenetic marks, and metabolic signatures, to name a few. But what’s often overlooked is the value of combining all that with a more mundane type of Big Data: the vast trove of clinical information contained in electronic health records (EHRs).

In a recent study in Science Translational Medicine  [1], NIH-funded researchers demonstrated the tremendous potential of using EHRs, combined with genome-wide analysis, to learn more about a common, chronic disease—type 2 diabetes. Sifting through the EHR and genomic data of more than 11,000 volunteers, the researchers uncovered what appear to be three distinct subtypes of type 2 diabetes. Not only does this work have implications for efforts to reduce this leading cause of death and disability, it provides a sneak peek at the kind of discoveries that will be made possible by the new Precision Medicine Initiative’s national research cohort, which will enroll 1 million or more volunteers who agree to share their EHRs and genomic information.

Continue reading

Precision Medicine: Who Benefits from Aspirin to Prevent Colorectal Cancer?

Aspirin and DNA StethoscopeIn recent years, scientific evidence has begun to accumulate that indicates taking aspirin or other non-steroidal anti-inflammatory drugs (NSAIDs) on a daily basis may lower the risk of developing colorectal cancer. Now, a new study provides more precise information on who might benefit from this particular prevention strategy, as well as who might not.

Published in the journal JAMA, the latest work shows that, for the majority of people studied, regular use of aspirin or NSAIDs was associated with about a one-third lower risk of developing colorectal cancer. But the international research team, partly funded by NIH, also found that not all regular users of aspirin/NSAIDs reaped such benefits—about 9 percent experienced no reduction in colorectal cancer risk and 4 percent actually appeared to have an increased risk [1]. Was this just coincidence, or might there be a biological explanation?

Continue reading

Autism Architecture: Unrolling the Genetic Blueprint

An array of childrenWe know that a combination of genetic and environmental factors influence a child’s risk of autism spectrum disorder (ASD), which is a diverse group of developmental brain conditions that disrupt language, communication, and social interaction. Still, there remain a great many unknowns, including the crucial issues of what proportion of ASD risk is due to genes and what sorts of genes are involved. Answering such questions may hold the key to expanding our understanding of the disorder—and thereby to devising better ways to help the millions of Americans whose lives are touched by ASD [1].

Last year, I shared how NIH-funded researchers had identified rare, spontaneous genetic mutations that appear to play a role in causing ASD. Now, there’s additional news to report. In the largest study of its kind to date, an international team supported by NIH recently discovered that common, inherited genetic variants, acting in tandem with each other or with rarer variants, can also set the stage for ASD—accounting for nearly half of the risk for what’s called “strictly defined autism,” the full-blown manifestation of the disorder. And, when the effects of both rare and common genetic variants are tallied up, we can now trace about 50 to 60 percent of the risk of strictly defined autism to genetic factors.

Continue reading