Microbial dysbiosis, characterized by an imbalanced microbial community structure and function, has been linked to hypertension. While prior research has primarily focused on differential abundances, our study highlights the role of non-differential microbes in hypertension. We propose that non-differential microbes contribute to hypertension through their ecological interactions, as defined by co-abundances (pairs of microbes exhibiting correlated abundance patterns). Using gut microbiome data from the Guangdong Gut Microbiome Project, which includes 2355 hypertensive and 4644 non-hypertensive participants across 14 regions, we identified replicable hypertension-related microbial interactions. Notably, most co-abundances involved non-differential microbes, which were found to correlate with both hypertension severity and hypertension-related microbial metabolic pathways. These findings emphasize the importance of microbial interactions in hypertension pathogenesis and propose a novel perspective for microbiome-based therapeutic strategies.
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http://dx.doi.org/10.1002/imt2.268 | DOI Listing |
Microbial dysbiosis, characterized by an imbalanced microbial community structure and function, has been linked to hypertension. While prior research has primarily focused on differential abundances, our study highlights the role of non-differential microbes in hypertension. We propose that non-differential microbes contribute to hypertension through their ecological interactions, as defined by co-abundances (pairs of microbes exhibiting correlated abundance patterns).
View Article and Find Full Text PDFGut Microbes
March 2024
Key Laboratory of Systems Biology, Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai, China.
In the development of Type 1 diabetes (T1D), there are critical states just before drastic changes, and identifying these pre-disease states may predict T1D or provide crucial early-warning signals. Unlike gene expression data, gut microbiome data can be collected noninvasively from stool samples. Gut microbiome sequencing data contain different levels of phylogenetic information that can be utilized to detect the tipping point or critical state in a reliable manner, thereby providing accurate and effective early-warning signals.
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