Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis

Atherosclerosis (AS), a predominant contributor to global cardiovascular disease burden, exhibits complex interplay with gut microbiota dysbiosis. While the associations between microbial imbalance and AS pathogenesis are well-documented, the pathophysiological mechanisms governing microbe-host cros...

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Main Authors: Hongbo Shi, Meitao Wu, Xiaoliang Wu, Zhuoxin Liu, Shuo Jiang, Gen Li, Yetong Yang, Yanghe Fu, Qiuping Wang, Guangde Zhang, Liang Cheng
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Gut Microbes
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Online Access:https://www.tandfonline.com/doi/10.1080/19490976.2025.2542384
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author Hongbo Shi
Meitao Wu
Xiaoliang Wu
Zhuoxin Liu
Shuo Jiang
Gen Li
Yetong Yang
Yanghe Fu
Qiuping Wang
Guangde Zhang
Liang Cheng
author_facet Hongbo Shi
Meitao Wu
Xiaoliang Wu
Zhuoxin Liu
Shuo Jiang
Gen Li
Yetong Yang
Yanghe Fu
Qiuping Wang
Guangde Zhang
Liang Cheng
author_sort Hongbo Shi
collection DOAJ
description Atherosclerosis (AS), a predominant contributor to global cardiovascular disease burden, exhibits complex interplay with gut microbiota dysbiosis. While the associations between microbial imbalance and AS pathogenesis are well-documented, the pathophysiological mechanisms governing microbe-host crosstalk remain incompletely characterized. Current research limitations stem from methodological heterogeneity across studies and the absence of consensus regarding disease-specific microbial signatures. In this study, we conducted an integrated multi-omics analysis to characterize the functional signatures of gut microbiome in AS. We collected all public AS-related 6 microbiome datasets and 8 peripheral blood host transcriptomic datasets from across the world, comprising 456 metagenomic samples and 111 16S rRNA gene sequencing samples for microbial profiling, alongside 118 RNA-Seq samples and 302 microarray samples. We systematically characterized AS microbial taxa and computationally inferred the metabolic potential for the gut microbiome using metabolomic-related data. Metabolite-host gene interactions were further predicted based on the synergistic effects between microbiome and host transcriptome in AS. Five “microbe-metabolite-host gene” tripartite associations related to AS were identified involving 5 microbial genera (Actinomyces, Bacteroides, Eisenbergiella, Gemella, and Veillonella), 2 metabolites (Ethanol and H2O2), and 2 host genes (FANCD2 and GPX2), and the reliability of these associations was validated. Five microbial genera demonstrated robust diagnostic potential as noninvasive biomarkers, with 5-fold cross-validation, study-to-study transfer validation, and leave-one-study-out (LOSO) validation confirming good diagnostic performance. Additionally, the specificity of the biomarkers was validated against hypertension, inflammatory bowel disease (IBD), diabetes, and obesity cohorts. Our study unveiled the functional characteristics of gut microbiota interacting with AS host genes and highlighted the potential of gut microbiota as both diagnostic biomarkers and therapeutic targets for AS. However, the findings should be interpreted considering the inherent heterogeneity of the integrated datasets and the preliminary diagnostic value of the biomarkers.
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spelling doaj-art-ffb069433c3f40c0893c25f09d0f29ad2025-08-20T03:41:15ZengTaylor & Francis GroupGut Microbes1949-09761949-09842025-12-0117110.1080/19490976.2025.2542384Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosisHongbo Shi0Meitao Wu1Xiaoliang Wu2Zhuoxin Liu3Shuo Jiang4Gen Li5Yetong Yang6Yanghe Fu7Qiuping Wang8Guangde Zhang9Liang Cheng10College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaDepartment of Cardiology, Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, ChinaDepartment of Cardiology, Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, ChinaCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, ChinaAtherosclerosis (AS), a predominant contributor to global cardiovascular disease burden, exhibits complex interplay with gut microbiota dysbiosis. While the associations between microbial imbalance and AS pathogenesis are well-documented, the pathophysiological mechanisms governing microbe-host crosstalk remain incompletely characterized. Current research limitations stem from methodological heterogeneity across studies and the absence of consensus regarding disease-specific microbial signatures. In this study, we conducted an integrated multi-omics analysis to characterize the functional signatures of gut microbiome in AS. We collected all public AS-related 6 microbiome datasets and 8 peripheral blood host transcriptomic datasets from across the world, comprising 456 metagenomic samples and 111 16S rRNA gene sequencing samples for microbial profiling, alongside 118 RNA-Seq samples and 302 microarray samples. We systematically characterized AS microbial taxa and computationally inferred the metabolic potential for the gut microbiome using metabolomic-related data. Metabolite-host gene interactions were further predicted based on the synergistic effects between microbiome and host transcriptome in AS. Five “microbe-metabolite-host gene” tripartite associations related to AS were identified involving 5 microbial genera (Actinomyces, Bacteroides, Eisenbergiella, Gemella, and Veillonella), 2 metabolites (Ethanol and H2O2), and 2 host genes (FANCD2 and GPX2), and the reliability of these associations was validated. Five microbial genera demonstrated robust diagnostic potential as noninvasive biomarkers, with 5-fold cross-validation, study-to-study transfer validation, and leave-one-study-out (LOSO) validation confirming good diagnostic performance. Additionally, the specificity of the biomarkers was validated against hypertension, inflammatory bowel disease (IBD), diabetes, and obesity cohorts. Our study unveiled the functional characteristics of gut microbiota interacting with AS host genes and highlighted the potential of gut microbiota as both diagnostic biomarkers and therapeutic targets for AS. However, the findings should be interpreted considering the inherent heterogeneity of the integrated datasets and the preliminary diagnostic value of the biomarkers.https://www.tandfonline.com/doi/10.1080/19490976.2025.2542384Atherosclerosismulti-omicsgut microbiomehost transcriptomediagnostic biomarker
spellingShingle Hongbo Shi
Meitao Wu
Xiaoliang Wu
Zhuoxin Liu
Shuo Jiang
Gen Li
Yetong Yang
Yanghe Fu
Qiuping Wang
Guangde Zhang
Liang Cheng
Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
Gut Microbes
Atherosclerosis
multi-omics
gut microbiome
host transcriptome
diagnostic biomarker
title Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
title_full Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
title_fullStr Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
title_full_unstemmed Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
title_short Multi-omics integration reveals functional signatures of gut microbiome in atherosclerosis
title_sort multi omics integration reveals functional signatures of gut microbiome in atherosclerosis
topic Atherosclerosis
multi-omics
gut microbiome
host transcriptome
diagnostic biomarker
url https://www.tandfonline.com/doi/10.1080/19490976.2025.2542384
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