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, a longitudinal analysis was conducted on blood biomarker data from 1032 generally healthy individuals who used an automated, web-based personalized nutrition and lifestyle platform. The study had two main aims: to analyze correlations between biomarkers for biological insights, and to characterize the effectiveness of the platform in improving biomarker levels. First, a biomarker 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, as well as novel insights, such as a connection between neutrophil and triglyceride concentrations that has been suggested as a relevant indicator of cardiovascular risk. Next, biomarker changes during platform use were assessed, showing a trend toward normalcy for most biomarkers in those participants whose values were out of the clinically normal range at baseline. Finally, associations were found between the selection of specific interventions and corresponding biomarker changes, suggesting directions for future study.

Since next generation sequencing facilitated high-throughput and cost-efficient genomics analyses, the human gut metagenome has become an emerging frontier to explore toward precision nutrition. Significant progress has been made in identifying gut microbial features associated with a wide spectrum of human disease. However, other than a few microbiome-disease relationships, there is a dearth of confirmed causal inferences, particularly in generally healthy populations. The relatively high unexplained variability in microbiome compositions in this group warrants caution in applying this complex biomarker toward precision nutrition, as our understanding of what constitutes a healthy microbiome is still rudimentary. While gut microbiota harbor integrated environmental and host-specific information with the potential to facilitate personalized nutritional and lifestyle advice, these data cannot yet be confidently interpreted toward precise recommendations. Thus, nutritional advice for generally healthy individuals based on personal microbiome composition analysis may not yet be appropriate unless accompanied by established blood and physiological biomarkers.

Elevated blood concentration of low-density lipoprotein cholesterol (LDLc) is a primary risk factor for developing cardiovascular disease. Lifestyle interventions including an increase in dietary phytosterols as well as medications have proven effective in lowering LDLc. The primary objective of this randomized, placebo controlled, double blind, crossover study was to determine the impact of a new phytosterol emulsion for dietary supplements (1.5 g/day phytosterol equivalents) on LDLc concentrations. Thirty-two healthy adults were randomly assigned to receive placebo or treatment followed by a washout period, followed by placebo or treatment, each phase lasting one month. Secondary endpoints related to cardiovascular health were also assessed. Study management, including screening, recruitment, monitoring, compliance, and data collection, were done remotely (a siteless clinical trial) utilizing a novel virtual tool. Phytosterol supplementation significantly lowered LDLc concentrations by 10.2% (16.17 mg/dL or 0.419 mmol/L, p = 0.008 by paired t-test, p = 0.014 by Wilcoxon signed rank testing). No secondary biomarkers were found to change significantly. Supplementation with phytosterols in a new dietary supplement formulation efficiently and safely decreases LDLc within one month in a free-living setting.

Objectives A longitudinal analysis was conducted on blood biomarker data from 1032 generally healthy individuals who used an automated, web-based personalized nutrition and lifestyle platform. Methods Combining the power of automation with the concepts of biological and behavioral personalization, we developed an online platform to produce individually customized nutrition and lifestyle recommendations for healthy adults, based on a panel of serum biomarkers. The scalable nature of the platform has allowed us to generate longitudinal biomarker data on 1032 generally healthy adults Results Biomarker changes during platform use were assessed, showing a trend toward normalcy for most biomarkers in those participants whose values were out of the clinically normal range at baseline. Finally, associations were found between the selection of specific interventions and corresponding biomarker changes, suggesting directions for future study. Conclusions We have used a rich longitudinal dataset of clinical biomarkers to uncover novel biological relationships while validating known ones. Furthermore, we have demonstrated that the personalized health platform described here associates with improvements in health parameters and shows promise for the validation of biomarker-intervention associations in a “real world” setting. By tracking a variety of biomarkers in free-living individuals, this platform provides a novel resource for exploration and hypothesis generation. With the advent of personalized health platforms such as the one described here, new efforts should be devoted to understanding the efficacy of their individual components while incorporating the valuable insights of participants. Funding Sources The scientists who conducted this study are either employed by the sponsoring company or serve as advisors to it. Thus, there is no separation between investigative team and funder, which provided support in the form of salaries, and was involved in the study design, data collection and analysis, decision to publish, and preparation of the manuscript. Supporting Tables, Images and/or Graphs

between investigative team and funder, which provided support in the form of salaries, and was involved in the study design, data collection and analysis, decision to publish, and preparation of the manuscript. "