Using Composite Phenotypes to Reveal Hidden Physiological Heterogeneity in High-Altitude Acclimatization in a Chinese Han Longitudinal Cohort

Yi Li,Jiucun Wang,Xiaofeng Wang,Kun Wang,Longli Kang,Xingdong Chen,Meng Liang,Yanyun Ma,Yi Wang,Meng Hao,Hui Zhang,Xianhong Yin,Wenyuan Duan,Li Jin,Bin Qiao,Yao Zhang,Menghan Zhang,Xiaoyu Liu

doi:10.1007/s43657-020-00005-8

Abstract

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 (SpO2) 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.

Highlights

Altitude acclimatization is a human physiological process of adjusting to decreased oxygen availability (West et al 2012)
Since we are mainly concerned with changes in these phenotypes, the longitudinal data were transformed into change data (Fitzmaurice et al 2012) using M easurechronic-baseline = Measure chronic—Measurebaseline
We developed a data-driven strategy (Fig. 1) to extract composite phenotypes from multiple physiological phenotypes of high-altitude acclimatization in a large-scale Chinese Han longitudinal cohort

Summary

Introduction

Altitude acclimatization is a human physiological process of adjusting to decreased oxygen availability (West et al 2012). SpO2 rapidly decreased in lowlanders within 3 days of directly ascending to 4300 m, followed by a rise in altitude over weeks (West et al 2012; Muza et al 2010; Lundby et al 2004; Peng et al 2013). The variations in responses across individuals provide an opportunity to explore the mechanism of altitude acclimatization (West et al 2012; Peng et al 2013; Brown and Grocott 2013)

Methods

Results

Conclusion