Identification Of Mir-103a/PLEKHA1 Pair As Candidate Biomarkers And Therapeutic Targets For Skin Aging By Bioinformatics Analysis

Abstract

Introduction: Skin aging is a deterioration in function and structure of the skin that occurs due to various factors. It is an intricate process involving several mechanisms. Identification of skin aging biomarkers is critical for early diagnosis and development of therapeutic targets.

Objectives: This study aims to identify gene molecular links related to skin aging using an in-silico approach.

Methods: The expression profiling by array and high throughput sequencing of GSE55299, GSE72264, GSE152251, GSE83922, GSE169382, and GSE240226 datasets were retrieved from the Gene Expression Omnibus (GEO). The data were integrated and analyzed to identify the differentially expressed microRNA (DEMs) and mRNA (DEGs) in skin aging. Fold changes (FCs) in the expression of individual genes were calculated with cut-off value of p ≤ 0.05 and FC ≥ 1.5. Data were processed to determine miRNA and mRNA hub which were then predicted using GeneCards and TargetScan.

Results: Eight genes and two miRNAs experienced alteration in expression in mRNA and miRNA data sets, respectively. In individuals with aging skin, miR-103a expression was downregulated and PLEKHA1 expression was upregulated, respectively. The intersection of DEMs and DEGs predicted targets resulted in one miRNA-mRNA pair related to skin aging, miR-103a / PLEKHA1. Additionally, bioinformatic analysis indicated that PLEKHA1 was a target of miR-103a.

Conclusions: This study uncovered miR-103a / PLEKHA1 pair potentially linked to the progression of skin aging, offering fresh insights into the molecular mechanisms underlying the condition, potential biomarker and therapeutic target.