Big Data Can Help Predict Personal Health Risks, Stanford Study Shows

Tracking genetic and molecular health data regularly can help physicians predict diseases.

Prof. Michael Snyder, PhD, professor and chair of genetics (Image credit: Steve Fisch via Stanford Medicine)

Tracking genetic and molecular health data regularly – rather than only when a health condition arises – can help physicians predict the onset of disease and provide insights into the development of highly personalized treatments, according to a study conducted by researchers at the Stanford University School of Medicine and their collaborators. Prof. Michael Snyder, who will be giving a keynote on predictive healthcare based on wearable data and AI at our upcoming WT | Wearable Technologies Conference in San Francisco on July 9-10, says the results of this study show there’s a need for fundamental change.

“I would argue that the way medicine is practiced is deeply flawed and could be significantly improved through longitudinal monitoring of one’s personal health baseline,” said Snyder, who holds the Stanford W. Ascherman, MD, FACS, Professorship in Genetics. “We generally study people when they’re sick, rarely when they’re healthy, and it means we don’t really know what ‘healthy’ looks like at an individual biochemical level.”

Related Combining Wearable Tech and AI Could Help Predict Onset of Diseases

For their study, the scientists followed a cohort of more than 100 people over several years, tracking the biology of what makes them what they are. Now, after collecting extensive data on the group’s genetic and molecular makeup, the researchers are piecing together a new understanding of what it means to be healthy and how deviations from an individual’s norm can flag early signs of disease, reports Stanford Medicine.

Image: Health.mil

More than 67 clinically actionable health discoveries were uncovered by the researchers over the course of the study. These ranged from high blood pressure, arrhythmias, cardiomyopathy and early stage cancer detection, among others. The study intertwined data from wearable technologies, genome sequencing and microbial and molecular profiling to establish a baseline of sorts for each participant. Every person’s broad swath of data painted a picture of their biological baseline, and as scientists tracked how that picture changed, they also kept tabs on any abnormalities that could signal the development of disease.

“What this paper really shows is that if doctors and scientists do more advanced profiling reasonably frequently, they’ll discover clinically actionable information for patient health at a broader scale than has ever been shown before,” Snyder said.

The study was published in the journal Nature Medicine.

WT | Wearable Technologies Conference in San Francisco on July 9-10

The most innovative wearables event will be back on July 9-10 in beautiful San Francisco at SEMICON West to celebrate the 34th edition of the WT | Wearable Technologies Conference Series. Topics include data analytics in professional sports, prevention, treatment and rehabilitation with wearables, the future of digital health, medication and adherence, smart patches, workflow optimization and workforce safety and much more – featuring international leaders and experts of the wearables industry´s biggest names including Abbott, Autodesk, Datwyler, Kopin, Maxim Integrated, Multek, NFLPA, Omron, SharkDreams, Qualcomm, and many more. Register now to be part of #WTUS19

Sam Draper
May 14, 2019

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