ArticleThe Journal of clinical endocrinology and metabolism2023
MicroRNAs Associated With Incident Diabetes in the Diabetes Prevention Program.
Article in The Journal of clinical endocrinology and metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- MicroRNAs Associated with Metformin Treatment in the Diabetes Prevention Program.International journal of molecular sciences · 2024Trial
- Longitudinal associations between microRNAs and weight in the diabetes prevention program.Frontiers in endocrinology · 2024Trial
- Co-expressed MicroRNAs Associated with An Elevated Psychometabolic Risk Phenotype in Women during Midlife.medRxiv : the preprint server for health sciences · 2026Article
- MicroRNAs modify relationships between hemoglobin A1c and race and ethnicity.Diabetes research and clinical practice · 2026Article
- Co-expressed microRNAs associated with elevated psychometabolic risk phenotype in women during midlife.Frontiers in endocrinology · 2026Article
- Considering microRNAs as measures of extrinsic domains of risk in the context of underlying genetic characteristics: type 2 diabetes as an exemplar.Frontiers in genetics · 2026Article
- Systematic validation of miR-503-5p abnormal expression in diabetic vascular complications: a meta-analysis and exploration of its targeted regulatory mechanism in retinopathy.Diabetology & metabolic syndrome · 2025Article
- Review of databases for experimentally validated human microRNA-mRNA interactions.Database : the journal of biological databases and curation · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
contextMicroRNAs (miRs) are short (ie, 18-26 nucleotide) regulatory elements of messenger RNA translation to amino acids.
objectiveThe purpose of this study was to assess whether miRs are predictive of incident type 2 diabetes (T2D) in the Diabetes Prevention Program (DPP) trial.
methodsThis was a secondary analysis (n = 1000) of a subset of the DPP cohort that leveraged banked biospecimens to measure miRs. We used random survival forest and Lasso methods to identify the optimal miR predictors and the Cox proportional hazards to model time to T2D overall and within intervention arms.
resultsWe identified 5 miRs (miR-144, miR-186, miR-203a, miR-205, miR-206) that constituted the optimal predictors of incident T2D after adjustment for covariates (hazard ratio [HR] 2.81, 95% CI 2.05, 3.87; P < .001). Predictive risk scores following cross-validation showed the HR for the highest quartile risk group compared with the lowest quartile risk group was 5.91 (95% CI 2.02, 17.3; P < .001). There was significant interaction between the intensive lifestyle (HR 3.60, 95% CI 2.50, 5.18; P < .001) and the metformin (HR 2.72; 95% CI 1.47, 5.00; P = .001) groups compared with placebo. Of the 5 miRs identified, 1 targets a gene with prior known associations with risk for T2D.
conclusionWe identified 5 miRs that are optimal predictors of incident T2D in the DPP cohort. Future directions include validation of this finding in an independent sample in order to determine whether this risk score may have potential clinical utility for risk stratification of individuals with prediabetes, and functional analysis of the potential genes and pathways targeted by the miRs that were included in the risk score.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.