Meta-analysis reveals obesity associated gut microbial alteration patterns and reproducible contributors of functional shift

ABSTRACT

The majority of cohort-specific studies associating gut microbiota with obesity are often contradictory; thus, the replicability of the signature remains questionable. Moreover, the species that drive obesity-associated functional shifts and their replicability remain unexplored. Thus, we aimed to address these questions by analyzing gut microbial metagenome sequencing data to develop an in-depth understanding of obese host-gut microbiota interactions using 3329 samples (Obese, n = 1494; Control, n = 1835) from 17 different countries, including both 16S rRNA gene and metagenomic sequence data. Fecal metagenomic data from diverse geographical locations were curated, profiled, and pooled using a machine learning-based approach to identify robust global signatures of obesity. Furthermore, gut microbial species and pathways were systematically integrated through the genomic content of the species to identify contributors to obesity-associated functional shifts. The community structure of the obese gut microbiome was evaluated, and a reproducible depletion of diversity was observed in the obese compared to the lean gut. From this, we infer that the loss of diversity in the obese gut is responsible for perturbations in the healthy microbial functional repertoire. We identified 25 highly predictive species and 37 pathway associations as signatures of obesity, which were validated with remarkably high accuracy (AUC, Species: 0.85, and pathway: 0.80) with an independent validation dataset. We observed a reduction in short-chain fatty acid (SCFA) producers (several Alistipes species, Odoribacter splanchnicus, etc.) and depletion of promoters of gut barrier integrity (Akkermansia muciniphila and Bifidobacterium longum) in obese guts. Our analysis underlines SCFAs and purine/pyrimidine biosynthesis, carbohydrate metabolism pathways in control individuals, and amino acid, enzyme cofactor, and peptidoglycan biosynthesis pathway enrichment in obese individuals. We also mapped the contributors to important obesity-associated functional shifts and observed that these are both dataset-specific and shared across the datasets. In summary, a comprehensive analysis of diverse datasets unveils species specifically contributing to functional shifts and consistent gut microbial patterns associated to obesity.

KEYWORDS:

• obesity
• gut microbial association
• meta-analysis
• machine learning
• functional contributors

Acknowledgments

This study was supported by a Start-up Research Grant (SRG/2019/000221) from the Science and Engineering Research Board (SERB), Government of India, to D.D.

D.C. extends his gratitude to the Council of Scientific and Industrial Research (CSIR), New Delhi, India for their financial support. Both authors acknowledge Mr. Ashis Roy for his valuable input in computational analyses.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Abbreviation

AUC, area under the receiver operating characteristic curve; BMI, body mass index; CSV, cross-study validation, CV, cross-validation; FDR, false discovery rate; F/B, Firmicutes/Bacteroidetes; LDA, linear discriminant analysis; LODO, leave-one-dataset-out; OTU, operational taxonomic unit; RF, random forest; ROC, receiver operator curves; SCFA, short-chain fatty acid, SMD, standardized mean difference; WGS, whole genome sequence.

Author contributions

D.C. collected the data, carried out the analyses according to the adopted pipeline, and wrote the manuscript. D.D. framed the research question, analyzed the data, supervised the work, and wrote the manuscript. All authors approved the final version of the manuscript.

Data availability statement

Data sharing is not applicable to this study, as no new data were created. However, the authors confirm that the data supporting the findings of this study are available within the article, its supplementary materials, and referenced publications from which the data were extracted.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2024.2304900