Cell ReportsBioinformaticsPeer-reviewed journal article
Multi-omics Reveals Immune Response and Metabolic Profiles during High-Altitude Mountaineering
Jianhua YiniD, Jingzhi LviD, Shichen YangiD, Yang WangiD, Zhuoli HuangiD, Xue Bing WangiD, Guixue HouiD, Wenwen ZhouiD, Ying LiuiD, Weikai WangiD, Xiumei LiniD, Yunting Huang, Yuhui ZhengiD, Chen Wei, Yue YuaniD, Yaling HuangiD, Chang LiuiD, Haoran TaoiD, Ruquan LiuiD, Yan Zhang, Guodan ZengiD, Feiyun Quan, Xinyue ZhuiD, Peng GaoiD, Jun XieiD, , Jian WangiD
Abstract
The physiological perturbations induced by high-altitude exposure in mountain climbers, manifesting as metabolic and immunologic deviations, have been previously reported but are not fully understood. In this study, we obtained longitudinal multi-omic profiles of blood samples for healthy mountain climbers during two mountaineering stages (acclimatization and extreme altitude mountaineering). Our integrative assay included metabolomics and lipidomics profiling of plasma coupled with single-cell transcriptomic analysis of 375,722 immune cells. Longitudinal analysis revealed dynamic immune response profiles, during the acclimatization period, characterized by the downregulation of inflammatory responses in monocytes and classical dendritic cells (cDCs) and an increase in the proportion of cytotoxic CD8+ T cells with enhanced immune effector processes. In contrast, during extreme altitude mountaineering, the activation of inflammatory responses and impairment of T cell effector function were observed, concomitant with an increased cellular response to hypoxia and oxidative stress pathways. Furthermore, we found upregulated glycolysis and antioxidant gene expression during extreme altitude mountaineering, which was primarily orchestrated by HIF1A and NFE2L2, while decreased expression of these genes was observed in dysregulated plasmacytoid dendritic cells (pDCs). Finally, high-resolution plasma metabolic analysis revealed significant alterations in the metabolism of climbers, involving enhanced glutamine and fatty acid metabolism.
- organism: human
- assay: bulk RNA-seq
- assay: metabolomics
- assay: proteomics
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- Citations
- 32
- FWCI
- 8.46
- Field percentile
- top 1%
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