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Background <p>Gut microecology-targeted intervention shows significant potential in correcting metabolic imbalances associated with the global obesity epidemic. While the gut microbiome in obesity has been widely studied, prior work has largely examined individual microbial or metabolic dimensions in isolation. Thus, this study aims to systematically characterize obesity-associated gut microbial features through a multidimensional integrated analysis that jointly considers gut microbiome, bacteriophagenome, predicted metabolome, and body composition traits.</p> Results <p>Body composition parameters (body mass index [BMI], body fat rate [BFR], waist-to-hip ratio [WHR], muscle mass-to-body weight ratio [MM/BW], and basal metabolic rate-to-fat-free mass ratio [BMR/FFM]) along with species-level gut microbiota (SGBs), bacteriophages, gut metabolic modules (GMMs), and gut predicted metabolites (GPMs) were compared between obese adults (OB group, <i>n</i> = 36) and healthy adults (HE group, <i>n</i> = 36) to construct a multidimensional association network. The OB group showed significantly higher BMI, BFR, and WHR (<i>P</i> &lt; 0.05), while MM/BW and BMR/FFM were reduced (<i>P</i> &lt; 0.05). The omics analysis identified 21 key SGBs (including <i>Faecalibacillus intestinalis</i><i>, </i><i>Blautia_</i>A <i>wexlerae</i><i>, </i><i>Blautia_</i>A sp900066335<i>, Anaerostipes amylophilus</i><i>, </i><i>Anaerobutyricum hallii</i><i>, </i><i>Dorea formicigenerans</i>, etc.), two bacteriophages (Myoviridae, Inoviridae), 16 GMMs (including glycine degradation, methionine degradation I, aspartate degradation I, etc.), and 16 GPMs (including N-acetylspermidine, N-acetylhistidine, imidazole propionate, etc.) that were significantly altered in the OB group (<i>P</i> &lt; 0.05). Correlation network analysis revealed that these differential features were associated with body composition indicators through multi-level and distinct relationships (<i>P</i> &lt; 0.05, |r|≥ 0.4), suggesting their potential relevance as intervention targets.</p> Conclusion <p>This study provides hypothesis-generating insights into gut ecosystem-based alterations associated with obesity, and these distinctive gut-related features warrant validation as potential biomarkers in prospective studies.</p>

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Integrative profiling of gut microbiome, bacteriophagenome, and predicted metabolome in obese adults: novel insights into intervention targets

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Lu Li,
  • Huan Wang,
  • Yuan Gao,
  • Bei Zhang,
  • Yongfu Chen

摘要

Background

Gut microecology-targeted intervention shows significant potential in correcting metabolic imbalances associated with the global obesity epidemic. While the gut microbiome in obesity has been widely studied, prior work has largely examined individual microbial or metabolic dimensions in isolation. Thus, this study aims to systematically characterize obesity-associated gut microbial features through a multidimensional integrated analysis that jointly considers gut microbiome, bacteriophagenome, predicted metabolome, and body composition traits.

Results

Body composition parameters (body mass index [BMI], body fat rate [BFR], waist-to-hip ratio [WHR], muscle mass-to-body weight ratio [MM/BW], and basal metabolic rate-to-fat-free mass ratio [BMR/FFM]) along with species-level gut microbiota (SGBs), bacteriophages, gut metabolic modules (GMMs), and gut predicted metabolites (GPMs) were compared between obese adults (OB group, n = 36) and healthy adults (HE group, n = 36) to construct a multidimensional association network. The OB group showed significantly higher BMI, BFR, and WHR (P < 0.05), while MM/BW and BMR/FFM were reduced (P < 0.05). The omics analysis identified 21 key SGBs (including Faecalibacillus intestinalis, Blautia_A wexlerae, Blautia_A sp900066335, Anaerostipes amylophilus, Anaerobutyricum hallii, Dorea formicigenerans, etc.), two bacteriophages (Myoviridae, Inoviridae), 16 GMMs (including glycine degradation, methionine degradation I, aspartate degradation I, etc.), and 16 GPMs (including N-acetylspermidine, N-acetylhistidine, imidazole propionate, etc.) that were significantly altered in the OB group (P < 0.05). Correlation network analysis revealed that these differential features were associated with body composition indicators through multi-level and distinct relationships (P < 0.05, |r|≥ 0.4), suggesting their potential relevance as intervention targets.

Conclusion

This study provides hypothesis-generating insights into gut ecosystem-based alterations associated with obesity, and these distinctive gut-related features warrant validation as potential biomarkers in prospective studies.