4.4 Article

Associations of network-derived metabolite clusters with prevalent type 2 diabetes among adults of Puerto Rican descent

Journal

BMJ OPEN DIABETES RESEARCH & CARE
Volume 9, Issue 1, Pages -

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/bmjdrc-2021-002298

Keywords

diabetes mellitus; type 2; epidemiology; metabolism

Funding

  1. National Institutes of Health (NIH) [2T32CA009001, 1K01DK107804-01A1, 1R01DK120560-01]

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In this study, network analysis was used to identify clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults. The results revealed several known and novel metabolite clusters that were significantly associated with T2D in the study cohorts. Meta-analysis showed consistent associations between specific metabolite clusters and prevalent T2D, highlighting the potential importance of these metabolic pathways in the development of the disease.
Introduction We investigated whether network analysis revealed clusters of coregulated metabolites associated with prevalent type 2 diabetes (T2D) among Puerto Rican adults. Research design and methods We used liquid chromatography-mass spectrometry to measure fasting plasma metabolites (>600) among participants aged 40-75 years in the Boston Puerto Rican Health Study (BPRHS; discovery) and San Juan Overweight Adult Longitudinal Study (SOALS; replication), with (n=357; n=77) and without (n=322; n=934) T2D, respectively. Among BPRHS participants, we used unsupervised partial correlation network-based methods to identify and calculate metabolite cluster scores. Logistic regression was used to assess cross-sectional associations between metabolite clusters and prevalent T2D at the baseline blood draw in the BPRHS, and significant associations were replicated in SOALS. Inverse-variance weighted random-effect meta-analysis was used to combine cohort-specific estimates. Results Six metabolite clusters were significantly associated with prevalent T2D in the BPRHS and replicated in SOALS (false discovery rate (FDR) <0.05). In a meta-analysis of the two cohorts, the OR and 95% CI (per 1 SD increase in cluster score) for prevalent T2D were as follows for clusters characterized primarily by glucose transport (0.21 (0.16 to 0.30); FDR <0.0001), sphingolipids (0.40 (0.29 to 0.53); FDR <0.0001), acyl cholines (0.35 (0.22 to 0.56); FDR <0.0001), sugar metabolism (2.28 (1.68 to 3.09); FDR <0.0001), branched-chain and aromatic amino acids (2.22 (1.60 to 3.08); FDR <0.0001), and fatty acid biosynthesis (1.54 (1.29 to 1.85); FDR <0.0001). Three additional clusters characterized by amino acid metabolism, cell membrane components, and aromatic amino acid metabolism displayed significant associations with prevalent T2D in the BPRHS, but these associations were not replicated in SOALS. Conclusions Among Puerto Rican adults, we identified several known and novel metabolite clusters that associated with prevalent T2D.

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