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The Next Step in Medical Texts

The Next Step in Medical Texts

For 14-months, Michael Snyder, a molecular geneticist at Stanford University in Palo Alto, California analyzed his blood 20 times in order to record a wide sample of his biochemical data including his immune system, metabolism, and gene activity. Snyder, along with his team of 40 other researchers, recently presented the results of his detailed study, which they are now calling an integrative personal omics profile (iPOP).

While a typical doctor’s visit only gives the physician a brief overview of the body at one moment of time, iPOP provides the equivalent of an IMAX movie—an in-depth analysis that can chart the function of a human body over time.

The results of the test recorded 3.2 billion nucleotides of DNA in Snyder’s genome and more than 3 billion fluctuations in blood molecules like proteins, metabolites, microRNAs, cytokines, antibodies, glucose, and gene transcripts.

The study also led to a self-diagnosis. During his first draw, Snyder had a cold, and in a later test, he became infected with respiratory syncytial virus, which corresponded with a rise in his glucose levels. Snyder ended up being diagnosed with type 2 diabetes.

As a slender man with no history of diabetes in his family, this problem would probably have gone unnoticed had he undergone traditional medical testing. “The way we’re practicing medicine now seems woefully inadequate,” Snyder explains. “When you go to the doctor’s office and they do a blood test, they typically measure no more than 20 things. With the technology out there now, we feel you should be able to measure thousands if not tens of thousands and ultimately millions of things. That would be a much clearer picture of what’s going on.”

Experts in the medical field praise Snyder’s self-analysis as a landmark, and a huge leap forward in what many scientists believe will be the next step for medicine. Enthusiastic about his results, last summer Snyder co-founded Personalis—a company that aims to help clinicians make sense of genomic information. The company is currently located in Palo Alto, California.

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