Li Yi, Ma Yanyun, Wang Kun, Zhang Menghan, Wang Yi, Liu Xiaoyu, Hao Meng, Yin Xianhong, Liang Meng, Zhang Hui, Wang Xiaofeng, Chen Xingdong, Zhang Yao, Duan Wenyuan, Kang Longli, Qiao Bin, Wang Jiucun, Jin Li
State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200438 China.
Institute for Six-Sector Economy, Fudan University, Shanghai, 200433 China.
Phenomics. 2021 Feb 22;1(1):3-14. doi: 10.1007/s43657-020-00005-8. eCollection 2021 Feb.
Altitude acclimatization is a human physiological process of adjusting to the decreased oxygen availability. Since several physiological processes are involved and their correlations are complicated, the analyses of single traits are insufficient in revealing the complex mechanism of high-altitude acclimatization. In this study, we examined these physiological responses as the composite phenotypes that are represented by a linear combination of physiological traits. We developed a strategy that combines both spectral clustering and partial least squares path modeling (PLSPM) to define composite phenotypes based on a cohort study of 883 Chinese Han males. In addition, we captured 14 composite phenotypes from 28 physiological traits of high-altitude acclimatization. Using these composite phenotypes, we applied k-means clustering to reveal hidden population physiological heterogeneity in high-altitude acclimatization. Furthermore, we employed multivariate linear regression to systematically model (Models 1 and 2) oxygen saturation (SpO) changes in high-altitude acclimatization and evaluated model fitness performance. Composite phenotypes based on Model 2 fit better than single trait-based Model 1 in all measurement indices. This new strategy of using composite phenotypes may be potentially employed as a general strategy for complex traits research such as genetic loci discovery and analyses of phenomics.
高原习服是人体适应氧气供应减少的生理过程。由于涉及多个生理过程且它们之间的相关性复杂，对单一性状的分析不足以揭示高原习服的复杂机制。在本研究中，我们将这些生理反应视为由生理性状线性组合表示的复合表型进行研究。我们开发了一种结合光谱聚类和偏最小二乘路径建模（PLSPM）的策略，基于对883名中国汉族男性的队列研究来定义复合表型。此外，我们从28个高原习服生理性状中获取了14个复合表型。利用这些复合表型，我们应用k均值聚类来揭示高原习服中隐藏的人群生理异质性。此外，我们采用多元线性回归对高原习服过程中的氧饱和度（SpO）变化进行系统建模（模型1和模型2）并评估模型拟合性能。在所有测量指标中，基于模型2的复合表型比基于单一性状的模型1拟合得更好。这种使用复合表型的新策略可能潜在地用作复杂性状研究的通用策略，如基因位点发现和表型组学分析。
