Identification and validation of aging-related potential biomarkers for melasma via comprehensive transcriptome analysis

Abstract Background: Melasma is a pigmentary skin condition that affects appearance, while aging is an inevitable phenomenon in all higher organisms throughout their life cycle. However, the relationship of them remains unclear, further research is needed to identify potential aging-related genes (ARGs) associated with melasma. Methods: Melasma-related dataset was obtained from public database. Differential expression analysis, Maximum Clique Centrality (MCC) algorithm, and machine learning methods were utilized to select candidate biomarkers for melasma. Following these processes, receiver operating characteristic (ROC) and expression level analyses were integrated to identify biomarkers. Ultimately, the expression levels of biomarkers were validated through quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Western blotting analysis. Results: PTPN11, YWHAZ, FEN1, FOXO4, and TBP were identified as aging-related biomarkers in melasma. The area under ROC curve (AUC) value of these biomarkers was greater than 0.7, and except TBP had higher expression, remaining biomarkers had lower expression in melasma. Conclusively, experiments analysis demonstrated that FOXO4, PTPN11, and YWHAZ were down-regulated at mRNA and protein levels in the melasma group. Conclusion: In this study, 5 aging-related biomarkers-PTPN11, YWHAZ, FEN1, TBP and FOXO4-were identified in melasma, underscoring the potential of these biomarkers to provide theoretical insights for clinical applications for melasma patients.