International “Big Data” Study Offers Fresh Insights into T2D
Posted on by Dr. Francis Collins
It’s estimated that about 10 percent of the world’s population either has type 2 diabetes (T2D) or will develop the disease during their lives . Type 2 diabetes (formerly called “adult-onset”) happens when the body doesn’t produce or use insulin properly, causing glucose levels to rise. While diet and exercise are critical contributory factors to this potentially devastating disease, genetic factors are also important. In fact, over the last decade alone, studies have turned up more than 80 genetic regions that contribute to T2D risk, with much more still to be discovered.
Now, a major international effort, which includes work from my own NIH intramural research laboratory, has published new data that accelerate understanding of how a person’s genetic background contributes to T2D risk. The new study, reported in Nature and unprecedented in its investigative scale and scope, pulled together the largest-ever inventory of DNA sequence changes involved in T2D, and compared their distribution in people from around the world . This “Big Data” strategy has already yielded important new insights into the biology underlying the disease, some of which may yield novel approaches to diabetes treatment and prevention.
The study, led by Michael Boehnke at the University of Michigan, Ann Arbor, Mark McCarthy at the University of Oxford, England, and David Altshuler, until recently at the Broad Institute, Cambridge, MA, involved more than 300 scientists in 22 countries.
- Click to share on LinkedIn (Opens in new window)
- Click to share on Pinterest (Opens in new window)
- Click to share on Tumblr (Opens in new window)
- Click to share on Reddit (Opens in new window)
- Click to share on Telegram (Opens in new window)
- Click to share on WhatsApp (Opens in new window)
- Click to share on Skype (Opens in new window)
- Click to print (Opens in new window)
Tags: Accelerating Medicines Partnership, AMP, big data, common variants, diabetes, exome, exome sequencing, fatty liver disease, gene variants, genetic complexity, genetic risk, genetics, genomics, genotype, GoT2D Consortium, GWAS, international collaboration, rare mutations, T2D, T2D-GENES Consortium, TM6SF2, type 2 diabetes, whole genome sequencing