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Regional variation limits applications of healthy gut microbiome reference ranges and disease modelsHe, Yan; Wu, Wei; Zheng, Hui-Min; Li, Pan; McDonald, Daniel; Sheng, Hua-Fang; Chen, Mu-Xuan; Chen, Zi-Hui; Ji, Gui-Yuan; Zheng, Zhong-Dai-Xi; Mujagond, Prabhakar; Chen, Xiao-Jiao; Rong, Zu-Hua; Chen, Peng; Lyu, Li-Yi; Wang, Xian; Wu, Chong-Bin; Yu, Nan; Xu, Yan-Jun; Yin, Jia; Raes, Jeroen; Knight, Rob; Ma, Wen-Jun; Zhou, Hong-Wei
Nature medicine, 10/2018, Volume: 24, Issue: 10Journal Article
Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression . Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis , colorectal cancer prescreening and therapeutic choices in melanoma . Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic and cardiovascular diseases . To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks.
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