TY - JOUR
T1 - Compositional and genetic alterations in Graves’ disease gut microbiome reveal specific diagnostic biomarkers
AU - Zhu, Qiyun
AU - Hou, Qiangchuan
AU - Huang, Shi
AU - Ou, Qianying
AU - Huo, Dongxue
AU - Vázquez-Baeza, Yoshiki
AU - Cen, Chaoping
AU - Cantu, Victor
AU - Estaki, Mehrbod
AU - Chang, Haibo
AU - Belda-Ferre, Pedro
AU - Kim, Ho Cheol
AU - Chen, Kaining
AU - Knight, Rob
AU - Zhang, Jiachao
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/11
Y1 - 2021/11
N2 - Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.
AB - Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.
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U2 - 10.1038/s41396-021-01016-7
DO - 10.1038/s41396-021-01016-7
M3 - Article
C2 - 34079079
AN - SCOPUS:85107305303
SN - 1751-7362
VL - 15
SP - 3399
EP - 3411
JO - ISME Journal
JF - ISME Journal
IS - 11
ER -