Details

Autor(en) / Beteiligte

• He, 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

Titel

Regional variation limits applications of healthy gut microbiome reference ranges and disease models

Ist Teil von

• Nature medicine, 2018-10, Vol.24 (10), p.1532-1535

Ort / Verlag

New York: Nature Publishing Group US

Erscheinungsjahr

2018

Quelle

MEDLINE

Beschreibungen/Notizen

• Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression 1 – 3 . Diagnostic applications have been proposed for inflammatory bowel disease diagnosis and prognosis 4 , colorectal cancer prescreening 5 and therapeutic choices in melanoma 6 . Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic 7 and cardiovascular diseases 8 . 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. The definition of a 'healthy' microbiome is impacted by geographic regional variations.