Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration.

Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration.
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DOI:
10.1038/s41564-022-01121-z
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发表时间:
2022-06
影响因子:
28.3
通讯作者:
--
中科院分区:
生物学1区
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--
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While gut microbiome and host gene regulation independently contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here we developed a machine learning-based framework to jointly analyse paired host transcriptomic (n = 208) and gut microbiome (n = 208) profiles from colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease and irritable bowel syndrome. We identified associations between gut microbes and host genes that depict shared as well as disease-specific patterns. We found that a common set of host genes and pathways implicated in gastrointestinal inflammation, gut barrier protection and energy metabolism are associated with disease-specific gut microbes. Additionally, we also found that mucosal gut microbes that have been implicated in all three diseases, such as Streptococcus, are associated with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes. Our framework can be applied to other diseases for the identification of host gene–microbiome associations that may influence disease outcomes. A machine learning framework for integrating multi-omic high-dimensional datasets identified disease-specific and shared host gene–microbiome associations across three gastrointestinal diseases.
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