Yuanqing Fu
Liang Yue
Geng-Dong Chen
Xue Cai
Menglei Shuai
Fengzhe Xu
Xiao Yi
Hao Chen
Yi Zhu
Mian-Li Xiao
Zengliang Jiang
Zelei Miao
Congmei Xiao
Bo Shen
Xiaomai Wu
Haihong Zhao
Wenhua Ling
Jun Wang
Yu-Ming Chen
Tiannan Guo
Ju-Sheng Zheng
a. College of Life Sciences, Zhejiang University, Hangzhou 310058, China;
b. Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, China;
c. Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, China;
d. Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou 310024, China;
e. Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, China;
f. Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510275, China;
g. Taizhou Hospital, Wenzhou Medical University, Linhai 325035, China;
h. CAS Key Laboratory for Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
Funds: and Westlake University Supercomputer Center for assistance in data storage and computation
and all the medical staff members who are on the front line fighting against COVID-19.
This study was supported by the National Natural Science Foundation of China (82073529, 81903316, 81773416, 81972492, 21904107, 81672086), Zhejiang Ten-thousand Talents Program (2019R52039), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), the 5010 Program for Clinical Researches (2007032) of the Sun Yat-sen University, Hangzhou Agriculture and Society Advancement Program (20190101A04), and Tencent foundation (2020). We thank all the participants for their collaboration as well as Dr. C.R. Palmer for his invaluable comments to this study
Received Date: 2021-01-20
Accepted Date:2021-04-15
Rev Recd Date:2021-04-05
Publish Date:2021-05-03
Abstract
Abstract
Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.Keywords: Gut microbiota,
Proinflammatory cytokines,
Proteomic biomarkers,
COVID-19,
Host infection response
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