CROSS-SECTIONAL ANALYSIS OF MICRORNA EXPRESSION PATTERNS AND THEIR ASSOCIATION WITH EARLY DIAGNOSIS OF HUMAN DISEASES IN PAKISTAN

Abstract

Background: Circulating microRNAs (miRNAs) have emerged as potential non-invasive biomarkers for early disease detection due to their stability in plasma and regulatory roles in gene expression. In Pakistan, early diagnosis of chronic and malignant diseases remains challenging, necessitating the exploration of novel molecular markers to enhance timely clinical interventions.

Objective: This study aimed to evaluate the expression profiles of selected circulating microRNAs—miR-21, miR-155, miR-34a, miR-126, and miR-122—and assess their diagnostic potential as early biomarkers among patients with diverse early-stage diseases compared to healthy controls.

Methods: A cross-sectional study was conducted on 180 participants, including 120 patients with early-stage pathological conditions and 60 age- and sex-matched healthy controls. Plasma samples were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) for miRNA quantification. Statistical analyses included independent t-tests, Pearson’s correlation, and receiver operating characteristic (ROC) curve evaluation to determine diagnostic accuracy.

Results: Significant upregulation of miR-21 (3.8-fold), miR-155 (2.9-fold), and miR-34a (2.4-fold) was observed among patients (p < 0.001), while miR-126 and miR-122 were downregulated (2.6- and 2.1-fold reductions, respectively; p < 0.01). ROC analysis revealed the highest diagnostic accuracy for miR-21 (AUC = 0.92), followed by miR-155 (AUC = 0.88). Combined miRNA panels improved sensitivity (93.1%) and specificity (89.4%). Negative correlations were noted between miR-126 and serum cholesterol (r = −0.45, p < 0.05) and between miR-122 and fasting glucose (r = −0.52, p < 0.01).

Conclusion: The study demonstrated that specific circulating miRNAs, particularly miR-21 and miR-155, possess strong diagnostic potential for early disease detection. Their expression signatures could be integrated into population-based screening protocols, enhancing early diagnosis and management in resource-limited healthcare settings.