# Elucidating the Role of MicroRNAs in Regulating Insulin Signaling Pathways: Implications for the Pathophysiology and Treatment of Type 2 Diabetes

## TL;DR

This study explores how microRNA-375 (miR-375) influences insulin signaling in type 2 diabetes patients in Pakistan, suggesting it could help predict treatment outcomes and guide precision medicine.

## Contribution

The study identifies miR-375 as a novel biomarker for predicting treatment response and cardiovascular risk in type 2 diabetes.

## Key findings

- miR-375 levels are inversely correlated with HbA1c and positively with insulin sensitivity markers.
- Higher miR-375 expression is associated with better glycemic control and fewer comorbidities.
- miR-375 is a potential predictive biomarker for cardiovascular disease in type 2 diabetes patients.

## Abstract

Background

This retrospective cross-sectional analysis assessed the regulatory role of microRNA-375 (miR-375) in the insulin signaling pathway and its clinical relevance for the treatment of type 2 diabetes mellitus (T2DM) in a Pakistani cohort.

Methodology

The study analyzed data from 300 adult patients with clinically confirmed T2DM to identify associations between miR-375 expression levels, insulin signaling pathway-specific biomarkers, glycemic indices, and treatment response.

Results

The mean miR-375 levels were found to be inversely correlated with HbA1c (r = -0.31, p < 0.01) and positively correlated with both insulin receptor substrate 1 expression (r = 0.29, p < 0.01) and phosphoinositide 3-kinase activity (r = 0.25, p < 0.01), indicating a proportionately enhanced insulin sensitivity with increased miR-375 expression. The one-way analysis of variance revealed significant differences in the expression of glucose transporter type 4 (GLUT4) between the three therapy response groups, with improved therapy responders displaying higher GLUT4 levels (p = 0.012). Logistic regression models identified miR-375 (odds ratio (OR) = 0.71, p < 0.05) and Framingham Risk Score (OR = 1.46, p < 0.001) as microRNA and clinical predictors, respectively, for cardiovascular disease, indicating its promise as a potential predictive biomarker. Hierarchical k-means clustering identified distinct patient subtypes to identify a high-risk patient profile based on insulin signaling and treatment adherence behaviors. Cluster 1, with high miR-375 and insulin sensitivity indicators, was associated with superior glycemic management and fewer comorbidities among participants in the study.

Conclusions

The results support the incorporation of miR-375 profiling in clinical practice to improve therapeutic stratification for T2DM by providing successful treatment predictions to improve metabolic outcomes. This study builds upon earlier findings and initiates a deeper understanding of miRNA-mediated modulation of the pathophysiology associated with T2DM. miR-375 is highlighted as a candidate biomarker for precision medicine.