Study: How big data can inform personal health risks, precision treatment

Tracking genetic, molecular and daily health data on a regular basis — rather than only when a health issue arises — can help physicians predict the onset of disease and provide insights into the development of highly personalized treatments, according to a study published in Nature Medicine on May 8.

Researchers from the Stanford University School of Medicine tracked the health data of more than 100 people for up to eight years using wearable technologies, genome sequencing and molecular profiling. The scientists were thus able to assemble a "biological baseline" for each person.

Informed by this baseline, when an abnormality appeared, researchers could more easily identify issues like high blood pressure, arrhythmia, diabetes and early-stage cancer. Additionally, having access to such a wide swath of data about each person's biology aided in the development of precision treatment plans specifically for each individual.

"Right now, we're pretty much in the dark until we profile people, but this approach could provide us a much better view of people's norms, what it means to be healthy and what it means when people deviate from that," Michael Snyder, PhD, professor and chair of genetics at Stanford, said in a statement. "Ultimately, we want to shift the practice of medicine from treating people when they are ill to a focus on keeping them healthy by predicting disease risk and catching disease before it is symptomatic."

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