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Randomized Controlled Trial
. 2024 Sep 18:15:1419812.
doi: 10.3389/fendo.2024.1419812. eCollection 2024.

Longitudinal associations between microRNAs and weight in the diabetes prevention program

Elena Flowers  1   2 , Benjamin Stroebel  1 , Kimberly A Lewis  1 , Bradley E Aouizerat  3   4 , Meghana Gadgil  5 , Alka M Kanaya  5   6 , Li Zhang  6   7 , Xingyue Gong  1
Affiliations
Randomized Controlled Trial

Longitudinal associations between microRNAs and weight in the diabetes prevention program

Elena Flowers et al. Front Endocrinol (Lausanne). .

Erratum in

Abstract

Objective: Circulating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial.

Research design and methods: A subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years.

Results: In fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models.

Discussion: This study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.

Keywords: biomarker; diabetes; microRNA; prediabetes; weight loss.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Distribution of weight loss overall (A) and by trial arm (B-D). Within each red box, the bottom border represents the 25th percentile, the center line represents the 50th percentile, and the upper border represents the 75th percentile. The lowest point on the horizontal line represents the minimum value, and the highest point on the horizontal line represents the maximum value. Small black circles represent outliers.
Figure 2
Figure 2
Scatter plot for MiRs and weight. MiRs were z-score transformed to standardize units and scale from flow cytometry experiments. Lines are fitted based on observations. .
Figure 3
Figure 3
Forest plot for odds ratios for 3% weight loss.
See this image and copyright information in PMC

Update of

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