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An association analysis between psychophysical characteristics and genome-wide gene expression changes in human adaptation to the extreme climate at the Antarctic Dome Argus

Molecular Psychiatry volume 20, pages 536–544 (2015)Cite this article

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Abstract

Genome-wide gene expression measurements have enabled comprehensive studies that integrate the changes of gene expression and phenotypic information to uncover their novel associations. Here we reported the association analysis between psychophysical phenotypes and genome-wide gene expression changes in human adaptation to one of the most extreme climates on Earth, the Antarctic Dome Argus. Dome A is the highest ice feature in Antarctica, and may be the coldest, driest and windiest location on earth. It is considered unapproachable due to its hostile environment. In 2007, a Chinese team of 17 male explorers made the expedition to Dome A for scientific investigation. Overall, 133 psychophysical phenotypes were recorded, and genome-wide gene expression profiles from the blood samples of the explorers were measured before their departure and upon their arrival at Dome A. We found that mood disturbances, including tension (anxiety), depression, anger and fatigue, had a strong, positive, linear relationship with the level of a male sex hormone, testosterone, using the Pearson correlation coefficient (PCC) analysis. We also demonstrated that significantly lowest-level Gene Ontology groups in changes of gene expression in blood cells with erythrocyte removal were consistent with the adaptation of the psychophysical characteristics. Interestingly, we discovered a list of genes that were strongly related to significant phenotypes using phenotype and gene expression PCC analysis. Importantly, among the 70 genes that were identified, most were significantly related to mood disturbances, where 42 genes have been reported in the literature mining, suggesting that the other 28 genes were likely novel genes involved in the mood disturbance mechanism. Taken together, our association analysis provides a reliable method to uncover novel genes and mechanisms related to phenotypes, although further studies are needed.

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Acknowledgements

We thank the 24th Chinese Antarctic inland expeditioners: Bo Sun, Bo Jin, XiaXing Xu, MingHu Ding, FuHai Wei, PengHui Cui, XiangBin Cui, JianXi Cao, Xiao Cheng, Xu Zhou, ZhenXi Zhu, XueFeng Wu, BingQuan Lei, Chen Liu, Hao Shen and ZhuangZhuo Chen for their participation and compliance to this strenuous protocol. We also thank the Chinese Arctic and Antarctic Administration and the Polar Research Institute of China for their full support of our work on site. This study could not have been completed without the dedicated support of the participants. We would like to thank Professor Liqun Luo for his critical reading of this manuscript. This work was also supported by the fund of Chinese Polar Environment Comprehensive Investigation & Assessment Programmes (NO. CHINARE 02-01), the Ministry of Science and Technology of China (2012CB518204 and 2009CB522105), Natural Science Foundation of China (30670783 and 61175002), the 2011 project of the Ministry of Education on Biotherapy, the Scientific Research Fund of the Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, and the 111 project (B08007). CJ is the Hsien Wu Professor of Biochemistry. DL acknowledges the support of the Science and Technology Commission of Shanghai Municipality (07pj14096). SD acknowledges the support of the Beijing Higher Education Young Elite Teacher Project (YETP1198).

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Author notes

  1. C Xu, X Ju, D Song and F Huang: These authors contributed equally to this work.

Authors and Affiliations

  1. United Laboratory of Polar Medical Sciences, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China

    C Xu, Q Wang, Y Xiong, Z Guo, X Chen, F Huang & C Jiang

  2. Department of Biochemistry and Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Tsinghua University, Beijing, China

    X Ju, F Huang, Z Zou, J Xu, Y Zhong & C Jiang

  3. School of Computer Science, Beijing Institute of Technology, Beijing, China

    D Song & L Jia

  4. Luzhou Medical School Affiliated Hospital of Traditional Chinese Medicine, Sichuan, China

    D Tang

  5. Department of Computer Science, Informatics Institute and C.S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA

    C Zhang, T Joshi & D Xu

  6. Center for Translational Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Beijing, China

    W Xu, K-F Xu & C Jiang

  7. Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Tsinghua University, Beijing, China

    Y Zhu, Y Peng & L Wang

  8. State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China

    X Zhang

  9. MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing, China

    R Jiang & T Jiang

  10. Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China

    D Li

  11. Department of Computer Science and Engineering, University of California, Riverside, CA, USA

    T Jiang

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  1. C Xu
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Correspondence to C Jiang.

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Xu, C., Ju, X., Song, D. et al. An association analysis between psychophysical characteristics and genome-wide gene expression changes in human adaptation to the extreme climate at the Antarctic Dome Argus. Mol Psychiatry 20, 536–544 (2015). https://doi.org/10.1038/mp.2014.72

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