Non-Coding RNAs in Prediabetes Beyond Glycemic Classification: Tissue Regulatory Networks, Progression Risk, and Intervention-Associated Dynamics

Prediabetes can be readily identified using established glycemic tests, but these measures provide limited information about underlying molecular heterogeneity, future progression to type 2 diabetes mellitus (T2DM), or molecular responses to preventive interventions. This narrative review evaluates whether non-coding RNAs (ncRNAs) may provide complementary information beyond glycemic classification. We integrate evidence on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), with brief consideration of emerging small ncRNA classes and epitranscriptomic regulation, emphasizing tissue-resolved regulatory crosstalk in skeletal muscle, liver, pancreatic β-cells, and adipose tissue while distinguishing direct human prediabetes evidence from mechanistic findings derived from related metabolic contexts. Circulating and extracellular-vesicle-associated ncRNAs are critically assessed according to diagnostic, prognostic, predictive, and pharmacodynamic functions. Particular attention is given to Diabetes Prevention Program analyses, in which baseline miRNA profiles were associated with incident T2DM and showed an exploratory treatment-by-biomarker interaction, while metformin exposure was associated with longitudinal changes in circulating miRNAs. Current evidence supports ncRNAs primarily as hypothesis-generating tools for mechanistic discovery and as candidate markers for progression risk and intervention-associated molecular dynamics, rather than replacements for established glycemic testing. Prospective validation is required to determine whether ncRNA profiling adds clinically meaningful information beyond conventional risk factors.

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Publication Details

Journal
Biomolecules
Published
2026-10-09
DOI
https://doi.org/10.3390/biom16101472
Primary Topic
MicroRNA in disease regulation
Type
article
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article

Non-Coding RNAs in Prediabetes Beyond Glycemic Classification: Tissue Regulatory Networks, Progression Risk, and Intervention-Associated Dynamics

Jae‐Hyung Park, Eun Yeong Ha, Zion Kim
Biomolecules
MicroRNA in disease regulation
article

Non-Coding RNAs in Prediabetes Beyond Glycemic Classification: Tissue Regulatory Networks, Progression Risk, and Intervention-Associated Dynamics

Jae‐Hyung Park, Eun Yeong Ha, Zion Kim
article en

Abstract

Prediabetes can be readily identified using established glycemic tests, but these measures provide limited information about underlying molecular heterogeneity, future progression to type 2 diabetes mellitus (T2DM), or molecular responses to preventive interventions. This narrative review evaluates whether non-coding RNAs (ncRNAs) may provide complementary information beyond glycemic classification. We integrate evidence on microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), with brief consideration of emerging small ncRNA classes and epitranscriptomic regulation, emphasizing tissue-resolved regulatory crosstalk in skeletal muscle, liver, pancreatic β-cells, and adipose tissue while distinguishing direct human prediabetes evidence from mechanistic findings derived from related metabolic contexts. Circulating and extracellular-vesicle-associated ncRNAs are critically assessed according to diagnostic, prognostic, predictive, and pharmacodynamic functions. Particular attention is given to Diabetes Prevention Program analyses, in which baseline miRNA profiles were associated with incident T2DM and showed an exploratory treatment-by-biomarker interaction, while metformin exposure was associated with longitudinal changes in circulating miRNAs. Current evidence supports ncRNAs primarily as hypothesis-generating tools for mechanistic discovery and as candidate markers for progression risk and intervention-associated molecular dynamics, rather than replacements for established glycemic testing. Prospective validation is required to determine whether ncRNA profiling adds clinically meaningful information beyond conventional risk factors.

BiomoleculesVol. 16(10)
Keimyung University (KR)
Openalex Percentile: Top 18%
MicroRNA in disease regulation
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