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Using big data to track a patient’s biology over time could unearth clinically actionable information, according to Stanford researchers who followed more than 100 relatively healthy individuals over several years, flagging disease before patients showed signs of illness. In a few instances, they identified life-threatening conditions in early stages. Researchers published their findings in Nature Medicine.
“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 the study’s lead author Michael Snyder, PhD, professor and chair of genetics at Stanford, in a statement. “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.”
Snyder and colleagues followed 109 healthy patients over a period of years, conducting quarterly clinical laboratory tests and multiomics assessments on the genome, immunome, transcriptome, proteome, metabolome, and gut microbiome to identify any shifts in health or abnormalities. Participants gave blood and stool samples and wore smartwatches and glucose monitors. The research team congregated this data to form a sophisticated picture of each patient’s biology, tracking some of the participants for as long as 8 years.
For most of the participants, the profiling unveiled previously undetected health issues. Overall, the research team identified 67 clinically actionable conditions, including diabetes, high blood pressure, arrhythmias, cardiomyopathy, and early stage cancers. Continuous monitoring of glucose and insulin levels flagged diabetes in nine participants, for instance. The team also found 13 disease-related conditions—including two cases of serious heart defects—through genetic sequencing.
Most of these health discoveries were either treatable or manageable although in some instances, the condition was fairly serious. One participant with an enlarged spleen was found to have lymphoma; two others had precancerous conditions. A half dozen participants discovered that they had arterial plaques, and 18 were found to have high blood pressure. Most of these discoveries would have gone unchecked under typical health screening, Snyder emphasized.
“We were able to catch a lot of these things before they were even symptomatic. And in most cases, it either led to folks being followed more carefully or to a medical intervention. For example, in the case of the individuals with plaques in their arteries, it led to an increase in their statins. So these findings really did change health management for many people,” he said. The majority of the participants ended up improving their diet and exercise regimens, based on their individual profiling results.
If conducted on a regular basis, advanced profiling could help improve health outcomes on a wide-scale basis, Snyder added.
His team plans to conduct follow-up studies to confirm preliminary findings on potential new biomarkers for cardiovascular and other diseases. “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,” he said.
Longitudinal monitoring could help improve people’s health on several fronts, observed Steven Steinhubl, MD, associate professor of genomic medicine at Scripps Research Translational Institute, La Jolla, California, in a related editorial. Integrating data from multiple types of omics over time for example “can provide the information needed for deeper mechanistic insights, which can drive future biomarker discovery and potential pharmaceutical breakthroughs,” he wrote.
For this type of approach to work outside clinical research, however, patients would have to see the value of it, Steinhubl offered. “Among other considerations, this would require that findings be returned to participants in an understandable and actionable manner, plus they would have to feel empowered to act upon these findings in order to realize the potential benefit,” he wrote.
“While involvement in the current study was found to influence the health behaviors of the majority of participants, it would be overly optimistic to assume the same would be the case in a broader, less motivated cohort,” he continued. Many of the study’s participants had actively sought studies of diabetes at Stanford.
Nevertheless, the findings do provide a glimpse of what might be possible with advanced profiling, Steinhubl acknowledged.