In order to explore opportunities for personalized and predictive health care, we collected serial clinical measurements, health surveys and multiomics profiles (genomics, proteomics, autoantibodies, metabolomics and gut microbiome) from 96 individuals. The participants underwent data-driven health coaching over a 16-month period with continuous digital monitoring of activity and sleep. Multiomics factor analysis resulted in an unsupervised, data-driven and integrated view of human health, revealing distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet and hormonal effects. The data revealed novel and previously uncovered associations between risk factors, molecular pathways, and quantitative lifestyle parameters. For example, ethinyl estradiol use had a distinct impact on metabolites, proteins and physiology. Multidimensional molecular and digital health signatures uncovered biological variability between people and quantitative effects of lifestyle changes, hence illustrating the value of the combined use of molecular and digital monitoring of human health.

中文翻译：

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生活方式改变期间的多组学和数字监测揭示了人类生物学和健康的独立方面

为了探索个性化和预测性保健的机会，我们收集了来自96位个体的系列临床测量，健康调查和多组学概况（基因组学，蛋白质组学，自身抗体，代谢组学和肠道微生物组）。参与者在16个月内接受了数据驱动的健康指导，并对活动和睡眠进行了连续数字监控。多元组学因素分析产生了无监督，以数据为驱动力的人类健康综合视图，揭示了与肥胖，糖尿病，肝功能，心血管疾病，炎症，免疫力，运动，饮食和激素作用有关的独特且独立的分子因素。数据揭示了危险因素，分子途径和定量生活方式参数之间的新颖且以前未发现的关联。例如，乙炔雌二醇的使用对代谢物，蛋白质和生理有显着影响。多维分子和数字健康特征揭示了人与人之间的生物变异性以及生活方式改变的定量影响，因此说明了分子和数字健康监测结合使用的价值。