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Introduction & Objective: Lifestyle interventions are effective type 2 diabetes (T2D) prevention strategies, yet little is known about metabolic pathways associated with intervention response in at-risk individuals. The study's purpose was to characterize the baseline metabolome in adults at risk for T2D who responded to a 12-month lifestyle intervention randomized controlled trial with significantly reduced fasting blood glucose (FBG). Methods: This study analyzed de novo untargeted primary metabolome data from 113 plasma samples stored in a biorepository. The parent study recruited participants from San Diego and San Francisco communities between 2009-2012. Data were acquired via the West Coast Metabolomics Core Laboratory using validated liquid chromatography mass spectrometry methods and 15-25 internal standards. Metabolites were quantified by peak heights. Relative concentrations were compared between lifestyle intervention responders and non-responders using independent t-tests and then adjusted for multiple comparisons. Results: Six metabolites were significantly different (unadj p

Introduction: Metabolic syndrome (MetS) is a prominent risk factor for both cardiovascular disease (CVD) and type 2 diabetes (T2D). MicroRNAs (miRs) are small noncoding RNA molecules that target messenger RNAs to alter gene expression. Circulating miRs have been studied as potential clinically meaningful biomarkers of risk for MetS as they are readily measured from blood. Though associations among MetS components and social constructs of race, ethnicity, and gender have previously been established, grouping according to these constructs alone may conflate genetic ancestry with the environmental/behavioral effects of being characterized as a particular gender, race, or ethnicity. The purpose of this study was to identify differences in circulating miRs associated with demographic factors and MetS components to better illuminate the nuanced health impacts of race, ethnicity and gender. Methods: This was a secondary analysis of a subset of participants (N=1000) from the Diabetes Prevention Program (DPP). A custom Fireplex assay was used to quantify miRs from banked plasma collected at baseline. Correlations between miRs and metabolic syndrome components were assessed by Pearson’s correlation coefficient. Multivariable linear models adjusted for age and weight were used to analyze associations between gender, race, ethnicity, and miR expression. The Benjamini-Hochberg false discovery rate (FDR) method was applied. Results: The sample was 68% female, 19% Black, 15% Hispanic, and mean age was 52 ± 10 years. After adjusting for multiple comparisons (FDR

The Diabetes Prevention Program (DPP) randomized controlled trial demonstrated that metformin treatment reduced progression to type 2 diabetes (T2D) by 31% compared to placebo in adults with prediabetes. Circulating micro-ribonucleic acids (miRs) are promising biomarkers of T2D risk, but little is known about their associations with metformin regimens for T2D risk reduction. We compared the change in 24 circulating miRs from baseline to 2 years in a subset from DPP metformin intervention (n = 50) and placebo (n = 50) groups using Wilcoxon signed rank tests. Spearman correlations were used to evaluate associations between miR change and baseline clinical characteristics. Multiple linear regression was used to adjust for covariates. The sample was 73% female, 17% Black, 13% Hispanic, and 50 ± 11 years. Participants were obese, normotensive, prediabetic, and dyslipidemic. Change in 12 miR levels from baseline to 2 years was significantly different in the metformin group compared with placebo after adjusting for multiple comparisons: six (let-7c-5p, miR-151a-3p, miR-17-5p, miR-20b-5p, miR-29b-3p, and miR-93-5p) were significantly upregulated and six (miR-130b-3p, miR-22-3p, miR-222-3p, miR-320a-3p, miR-320c, miR-92a-3p) were significantly downregulated in the metformin group. These miRs help to explain how metformin is linked to T2D risk reduction, which may lead to novel biomarkers, therapeutics, and precision health strategies.