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生活方式改变时的多组学和数字监测揭示了人类生物学和健康的独立维度。

Multiomics and digital monitoring during lifestyle changes reveal independent dimensions of human biology and health.

机构信息

Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki 00290, Finland; Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17165, Sweden.

Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki 00290, Finland; Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm 17165, Sweden.

出版信息

Cell Syst. 2022 Mar 16;13(3):241-255.e7. doi: 10.1016/j.cels.2021.11.001. Epub 2021 Dec 1.

DOI:10.1016/j.cels.2021.11.001
PMID:34856119
Abstract

We explored opportunities for personalized and predictive health care by collecting serial clinical measurements, health surveys, genomics, proteomics, autoantibodies, metabolomics, and gut microbiome data from 96 individuals who participated in a data-driven health coaching program over a 16-month period with continuous digital monitoring of activity and sleep. We generated a resource of >20,000 biological samples from this study and a compendium of >53 million primary data points for 558,032 distinct features. Multiomics factor analysis revealed distinct and independent molecular factors linked to obesity, diabetes, liver function, cardiovascular disease, inflammation, immunity, exercise, diet, and hormonal effects. For example, ethinyl estradiol, a common oral contraceptive, produced characteristic molecular and physiological effects, including increased levels of inflammation and impact on thyroid, cortisol levels, and pulse, that were distinct from other sources of variability observed in our study. In total, this work illustrates the value of combining deep molecular and digital monitoring of human health. A record of this paper's transparent peer review process is included in the supplemental information.

摘要

我们通过收集来自 96 名参与者的连续临床测量、健康调查、基因组学、蛋白质组学、自身抗体、代谢组学和肠道微生物组数据,探索了个性化和预测性医疗保健的机会。这些参与者在 16 个月的数据驱动健康教练计划中接受了连续的活动和睡眠数字化监测。我们从这项研究中生成了超过 20,000 个生物样本的资源,以及包含超过 5300 万个主要数据点的纲要,涵盖了 558,032 个独特特征。多组学因子分析揭示了与肥胖、糖尿病、肝功能、心血管疾病、炎症、免疫、运动、饮食和激素影响相关的独特且独立的分子因子。例如,一种常见的口服避孕药炔雌醇产生了特征性的分子和生理效应,包括炎症水平升高以及对甲状腺、皮质醇水平和脉搏的影响,这与我们研究中观察到的其他来源的可变性不同。总的来说,这项工作说明了结合人类健康的深度分子和数字监测的价值。本文的透明同行评审过程记录包含在补充信息中。

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