Gut Microbiota Signatures as Predictive Biomarkers for Metabolic and Gastrointestinal Diseases

Hafiza Ayesha Barkat; Bareera Masood; Aqsa Saif; Hasnain Jadoon; Tooba Kiyani; Sami Ullah

doi:10.70749/ijbr.v3i10.2536

Authors

Hafiza Ayesha Barkat Department of Zoology, Government College University, Lahore, Pakistan
Bareera Masood University of Veterinary and Animal Sciences, Lahore, Pakistan
Aqsa Saif University of Veterinary and Animal Sciences, Lahore, Pakistan
Hasnain Jadoon Department of Bioengineering, Dalian University of Technology, China
Tooba Kiyani Department of Biochemistry/Molecular Biology, Quaid-e-Azam University, Islamabad, Pakistan
Sami Ullah Department of Microbiology, Quaid-e-Azam University, Islamabad, Pakistan

DOI:

https://doi.org/10.70749/ijbr.v3i10.2536

Keywords:

Gut Microbiota, Metabolic Syndrome, Type 2 Diabetes Mellitus, Akkermansia Muciniphila

Abstract

Background: The association of gut microbiota changes to metabolic dysfunction is poorly characterized in South Asian populations, which limits the ability to develop meaningful diagnostic biomarkers. There is a significant gap in our understanding of population-level microbial signatures, especially in high-risk yet underrepresented populations (e.g. Pakistan, which has the highest prevalence of diabetes in the world) that face a mounting crisis of metabolic disease. Methods: This was a prospective, cross-sectional, observational study of 210 adults (70 with metabolic syndrome, 70 with type 2 diabetes mellitus [T2DM], and 70 healthy controls) at tertiary hospitals in Islamabad, Pakistan (October 2024 - March 2025). Participants were recruited via stratified cluster sampling and the study followed the STROBE reporting guidelines. Gut microbiota profiles were collected via fecal sample collection and characterized using 16S rRNA sequencing, targeting the V3-V4 region of the 16S gene. The primary outcome of this study was alpha diversity, as measured by the Shannon index. The secondary outcomes included the relative abundances of selected bacterial taxa (i.e. Firmicutes/Bacteroidetes [FB] ratio; Akkermansia muciniphila) and assessment of dietary impacts. Results: Overall, 210 participants enrolled in the study (completion rate of 84.7%; mean [SD] age 46.0 [11.4] years; male 58.6 %). Mean Shannon diversity was significantly lower in metabolic syndrome (4.21 [0.67]) and T2DM (4.06 [0.71]), compared to controls (4.75 [0.48]), with adjusted mean differences of −0.54 (95% confidence interval [CI], −0.78 to −0.30; p = 0.001) and −0.69 (95% CI, −0.93 to −0.45; p = 0.001), respectively. FB ratios were elevated (1.90 and 2.33 in metabolic syndrome and T2DM, respectively vs. 1.24 in controls) and A. muciniphila counts were lower (0.80 and 0.95 in metabolic syndrome and T2DM, respectively vs. 2.31 in controls). Shannon diversity was strongly correlated with HbA1c (Spearman -0.58, 95% CI -0.67 to -0.47) and CRP (-0.48, 95% CI -0.58 to -0.36). Conclusions: Alterations of gut microbiota composition, primarily reduced alpha diversity, elevated FB ratio, and reduced A. muciniphila, were associated with metabolic syndrome and T2DM in Pakistani adults. These population-specific microbial signatures demonstrated strong diagnostic evidence (AUC > 0.84), serving support for the ability to develop locally relevant and targeted panels of microbiota based biomarkers.

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