ScienceDaily (Mar. 15, 2012) Geneticist Michael Snyder, PhD, has almost no privacy. For more than two years, he and his lab members at the Stanford University School of Medicine pored over his body's most intimate secrets: the sequence of his DNA, the RNA and proteins produced by his cells, the metabolites and signaling molecules wafting through his blood. They spied on his immune system as it battled viral infections.

Finally, to his shock, they discovered that he was predisposed to type-2 diabetes and then watched his blood sugar shoot upward as he developed the condition during the study. It's the first eyewitness account -- viewed on a molecular level -- of the birth of a disease that affects millions of Americans. It's also an important milestone in the realization of the promise of truly personalized medicine, or tailoring health care to each individual's unique circumstances.

The researchers call the unprecedented analysis, which relies on collecting and analyzing billions of individual bits of data, an integrative Personal "Omics" Profile, or iPOP. The word "omics" indicates the study of a body of information, such as the genome (which is all DNA in a cell), or the proteome (which is all the proteins). Snyder's iPOP also included his metabolome (metabolites), his transcriptome (RNA transcripts) and autoantibody profiles, among other things.

The researchers say that Snyder's diabetes is but one of myriad problems the iPOP can identify and predict, and that such dynamic monitoring will soon become commonplace. "This is the first time that anyone has used such detailed information to proactively manage their own health," said Snyder. "It's a level of understanding of health at the molecular level that has never before been achieved."

The research was published in the March 16 issue of Cell. Snyder, who chairs the Department of Genetics, is the senior author. Postdoctoral scholars Rui Chen, PhD, George Mias, PhD, Jennifer Li-Pook-Than, PhD, and research associate Lihua Jiang, PhD, are co-first authors of the study, which involved a large team of investigators.

The study provides a glimpse into the future of medicine -- peppered with untold data-management hurdles and fraught with a degree of self-examination and awareness few of us have ever imagined. And, despite the challenges, the potential payoff is great.

"I was not aware of any type-2 diabetes in my family and had no significant risk factors," said Snyder, "but we learned through genomic sequencing that I have a genetic predisposition to the condition. Therefore, we measured my blood glucose levels and were able to watch them shoot up after a nasty viral infection during the course of the study."

As a result, he was able to immediately modify his diet and exercise to gradually bring his levels back into the normal range and prevent the ongoing tissue damage that would have occurred had the disease gone undiagnosed.

Snyder provided about 20 blood samples (about once every two months while healthy, and more frequently during periods of illness) for analysis over the course of the study. Each was analyzed with a variety of assays for tens of thousands of biological variables, generating a staggering amount of information.

The exercise was in stark contrast to the cursory workup most of us receive when we go to the doctor for our regular physical exam. "Currently, we routinely measure fewer than 20 variables in a standard laboratory blood test," said Snyder, who is also the Stanford W. Ascherman, MD, FACS, Professor in Genetics. "We could, and should, be measuring many, many thousands."

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Revolution in personalized medicine: First-ever integrative 'Omics' profile lets scientist discover, track his ...

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