A Pilot Characterization of the Human Chronobiome

Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the noise attributable to the behavioral differences of free-living human volunteers. The majority (62%) of sensor readouts showed time-specific variability including the expected variation in blood pressure, heart rate, and cortisol. While variance in the multi-omics is dominated by inter-individual differences, temporal patterns are evident in the metabolome (5.4% in plasma, 5.6% in saliva) and in several genera of the oral microbiome. This demonstrates, despite a small sample size and limited sampling, the feasibility of characterizing at scale the human chronobiome in the wild. Such reference data at scale are a prerequisite to detect and mechanistically interpret discordant data derived from patients with temporal patterns of disease expression, to develop time-specific therapeutic strategies and to refine existing treatments.

生理功能、疾病表现与药物效应均随昼夜节律呈现动态变化。小鼠生物钟紊乱可引发心血管代谢、免疫及神经功能障碍；人类通过强制去同步化手段造成的昼夜节律错位，则会升高心血管疾病风险因子。本研究整合了远程传感器、生理学及多组学（multi-omics）分析数据，旨在评估在自由活动的人类志愿者的行为差异引入噪声干扰的情况下，检测时间依赖性信号——即昼夜节律组（chronobiome）——的可行性。研究结果显示，超过六成（62%）的传感器读数呈现昼夜特异性变异，包括血压、心率与皮质醇（cortisol）水平的预期波动。尽管多组学数据的变异主要由个体间差异主导，但血浆代谢组（metabolome，占变异的5.4%）、唾液代谢组（占变异的5.6%）以及部分口腔微生物组（oral microbiome）菌属中，仍存在显著的时间模式特征。本研究证实，即便样本量较小且采样有限，仍可在自然自由活动的人群中实现人类昼夜节律组的规模化表征。此类大规模参考数据集，是检测并从机制层面解读呈现疾病表现时间模式的患者所产生的异常数据、开发特异性时辰治疗策略，以及优化现有治疗方案的必要前提。