Longitudinal analysis of biomarker data from a personalized nutrition platform in healthy subjects

The trend toward personalized approaches to health and medicine has resulted in a need to collect high-dimensional datasets on individuals from a wide variety of populations, in order to generate customized intervention strategies. However, it is not always clear whether insights derived from studies in patient populations or in controlled trial settings are transferable to individuals in the general population. To address this issue, an observational analysis was conducted on blood biomarker data from 1033 generally healthy individuals who used an automated, web-based personalized nutrition and lifestyle platform. Using the resulting dataset, a correlation network was constructed to generate biological hypotheses that are relevant to researchers and, potentially, to users of personalized wellness tools. The correlation network revealed expected patterns, such as the established relationships between blood lipid levels, and novel insights, such as a connection between neutrophil and triglyceride concentrations that has been suggested as a relevant indicator of cardiovascular risk. Biomarker changes were assessed from baseline to follow-up, relative to platform use. Preliminary associations were found between the selection of specific nutrition and lifestyle interventions and biomarker outcomes. Across many biomarkers measured, there was a significant trend toward normalcy in participants whose biomarker values were out-of-range at baseline.