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Using composite phenotypes to reveal hidden physiological heterogeneity and model oxygen saturation variation of high altitude acclimatization in a Chinese Han longitudinal cohort

By Yi Li, Yi Wang, Menghan Zhang, Yanyun Ma, Kun Wang, Xiaoyu Liu, Meng Hao, Chang Sun, Xiaofeng Wang, Xingdong Chen, Yao Zhang, Wenyuan Duan, Longli Kang, Bin Qiao, Jiucun Wang, Li Jin

Posted 03 Jun 2018
bioRxiv DOI: 10.1101/336446

Altitude acclimatization is the physiological process of the human body adjusting to the decreased availability of oxygen. Since several physiological processes are involved and the relation among them is complicated, analyses of single-traits is insufficient in revealing the complex mechanism of high altitude acclimatization. In this study, we examined whether these physiological responses could be studied as composite phenotypes which are represented by a linear combination of physiological traits. We developed a strategy which 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. And 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 (Model 1 and Model 2) oxygen saturation (SpO2) changes in high altitude acclimatization and evaluated the model fitness performance. And composite phenotypes based Model 2 has better fitness than single-traits based Model 1 in all measurement indices. Therefore, this new strategy of defining and applying composite phenotypes can be considered as a general strategy of complex traits research, which may also shed light on genetic loci discovery and phenome analyses.

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