A longitudinal big data approach for precision health
A longitudinal big data approach for precision health
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DOI：
10.1038/s41591-019-0414-6
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发表时间：
2019-05-01
期刊：
影响因子：
82.9
通讯作者：
Snyder, Michael P.
中科院分区：
文献类型：
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作者：
Rose, Sophia Miryam Schussler-Fiorenza;Contrepois, Kevin;Snyder, Michael P.
精准健康依赖于在个人层面评估疾病风险、发现早期临床前状况和启动预防战略的能力。最近在组学和可穿戴监测方面的技术进步使深入分子和生理分析成为可能，并可能为精确健康提供重要工具。我们在前瞻性纵向队列（n = 109）中探讨了深度纵向分析的能力，以发现与健康相关的发现，确定临床相关的分子途径，并影响2型糖尿病风险的行为。该队列使用临床测量和新兴技术，包括基因组、免疫组、转录组、蛋白质组、代谢组、微生物组和可穿戴监测，对每季度收集的样本进行了综合个性化组学分析，持续时间长达8年（中位数为2.8年）。我们发现了超过67个临床可操作的健康发现，并确定了与代谢、心血管和肿瘤病理生理相关的多种分子途径。我们通过使用组学测量开发了胰岛素抵抗的预测模型，说明了它们替代繁琐测试的潜力。最后，研究参与导致大多数参与者实施饮食和运动的改变。总之，我们得出结论，深度纵向分析可以导致可操作的健康发现，并为精确健康提供相关信息。
Precision health relies on the ability to assess disease risk at an individual level, detect early preclinical conditions and initiate preventive strategies. Recent technological advances in omics and wearable monitoring enable deep molecular and physiological profiling and may provide important tools for precision health. We explored the ability of deep longitudinal profiling to make health-related discoveries, identify clinically relevant molecular pathways and affect behavior in a prospective longitudinal cohort (n = 109) enriched for risk of type 2 diabetes mellitus. The cohort underwent integrative personalized omics profiling from samples collected quarterly for up to 8 years (median, 2.8 years) using clinical measures and emerging technologies including genome, immunome, transcriptome, proteome, metabolome, microbiome and wearable monitoring. We discovered more than 67 clinically actionable health discoveries and identified multiple molecular pathways associated with metabolic, cardiovascular and oncologic pathophysiology. We developed prediction models for insulin resistance by using omics measurements, illustrating their potential to replace burdensome tests. Finally, study participation led the majority of participants to implement diet and exercise changes. Altogether, we conclude that deep longitudinal profiling can lead to actionable health discoveries and provide relevant information for precision health.