Multiomics profiling reveals signatures of dysmetabolism in urban populations in central India

Tanya M. Monaghan*, Rima N. Biswas, Rupam R. Nashine, Samidha S. Joshi, Benjamin H. Mullish, Anna M. Seekatz, Jesus Miguens Blanco, Julie A.K. McDonald, Julian R. Marchesi, Tung On Yau, Niki Christodoulou, Maria Hatziapostolou, Maja Pucic‐bakovic, Frano Vuckovic, Filip Klicek, Gordan Lauc, Ning Xue, Tania Dottorini, Shrikant Ambalkar, Ashish SatavChristos Polytarchou, Animesh Acharjee, Rajpal Singh Kashyap

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Background: Non‐communicable diseases (NCDs) have become a major cause of morbid-ity and mortality in India. Perturbation of host–microbiome interactions may be a key mechanism by which lifestyle‐related risk factors such as tobacco use, alcohol consumption, and physical inac-tivity may influence metabolic health. There is an urgent need to identify relevant dysmetabolic traits for predicting risk of metabolic disorders, such as diabetes, among susceptible Asian Indians where NCDs are a growing epidemic. Methods: Here, we report the first in‐depth phenotypic study in which we prospectively enrolled 218 adults from urban and rural areas of Central India and used multiomic profiling to identify relationships between microbial taxa and circulating biomarkers of cardiometabolic risk. Assays included fecal microbiota analysis by 16S ribosomal RNA gene am-plicon sequencing, quantification of serum short chain fatty acids by gas chromatography‐mass spectrometry, and multiplex assaying of serum diabetic proteins, cytokines, chemokines, and multi-isotype antibodies. Sera was also analysed for N‐glycans and immunoglobulin G Fc N‐glycopep-tides. Results: Multiple hallmarks of dysmetabolism were identified in urbanites and young over-weight adults, the majority of whom did not have a known diagnosis of diabetes. Association anal-yses revealed several host–microbe and metabolic associations. Conclusions: Host–microbe and metabolic interactions are differentially shaped by body weight and geographic status in Central Indians. Further exploration of these links may help create a molecular‐level map for estimating risk of developing metabolic disorders and designing early interventions.

Original languageEnglish
Article number1485
Issue number7
Early online date12 Jul 2021
Publication statusFirst published - 12 Jul 2021
Externally publishedYes


  • Diabetes mellitus
  • Dysmetabolism
  • Geography
  • Glycome
  • Host–microbe interactions
  • Multiomics


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