Zhang Shixuan, Yang La, Duoji Zhuoma, Qiangba Danzeng, Hu Xiaoxi, Jiang Zeyu, Hou Dandan, Hu Zixin, Basang Zhuoma
High Altitude Health Science Research Centre of Tibet University, Tibet University, 10 East Zangda Road, Lhasa 850000, China.
State Key Laboratory of Genetic Engineering, School of Life Sciences & Human Phenome Institute, Fudan University, Shanghai 200438, China.
Int J Mol Sci. 2024 Nov 25;25(23):12652. doi: 10.3390/ijms252312652.
Repeated extreme environmental training (RET) enhances adaptability and induces lasting methylation modifications. We recruited 64 participants from a high-altitude region (4700 m), including 32 volunteers with repeated high-altitude exposure, reaching up to 8848 m and as many as 11 exposures. By analyzing 741,489 CpG loci and 39 phenotypes, we identified significant changes in 13 CpG loci (R > 0.8, ACC > 0.75) and 15 phenotypes correlated with increasing RET exposures. The phenotypic Bayesian causal network and phenotypic-CpG interaction networks showed greater robustness (node correlation) with more RET exposures, particularly in systolic blood pressure (SP), platelet count (PLT), and neutrophil count (NEUT). Six CpG sites were validated as significantly associated with hypoxia exposure using the GEO public da-taset (AltitudeOmics). Furthermore, dividing the participants into two groups based on the number of RET exposures ( = 9 and 4) revealed six CpG sites significantly corre-lated with PLT and red cell distribution width-standard deviation (RDW.SD). Our findings suggest that increased RET exposures strengthen the interactions between phenotypes and CpG sites, indicating that critical extreme adaptive states may alter methylation patterns, co-evolving with phenotypes such as PLT, RDW.SD, and NEUT.
重复极端环境训练(RET)可增强适应性并诱导持久的甲基化修饰。我们从高海拔地区(4700米)招募了64名参与者,其中包括32名有多次高海拔暴露经历的志愿者,其最高到达海拔8848米,暴露次数多达11次。通过分析741,489个CpG位点和39种表型,我们确定了13个CpG位点(R>0.8,ACC>0.75)和15种表型的显著变化,这些变化与RET暴露增加相关。表型贝叶斯因果网络和表型-CpG相互作用网络显示,随着RET暴露次数增加,其稳健性(节点相关性)更强,特别是在收缩压(SP)、血小板计数(PLT)和中性粒细胞计数(NEUT)方面。使用GEO公共数据集(AltitudeOmics)验证了6个CpG位点与低氧暴露显著相关。此外,根据RET暴露次数(9次和4次)将参与者分为两组,发现有六个CpG位点与PLT和红细胞分布宽度标准差(RDW.SD)显著相关。我们的研究结果表明,增加RET暴露会加强表型与CpG位点之间的相互作用,这表明关键的极端适应状态可能会改变甲基化模式,并与PLT、RDW.SD和NEUT等表型共同进化。