Use of genetics in the prediction of success in male pattern hair loss therapy and mechanistic studies - Torres de Souza, Gustavo; Williams, Greg; Vicente Silva, Carolina Costa; Chiovatto, Caroline Brandão; Epstein, Gorana Kuka; Vila-Vecilla, Laura; Russo, Valentina (Frontiers in Pharmacology, 2026)
Male pattern hair loss, the clinical manifestation of androgenetic alopecia in men, is a highly prevalent chronic condition associated with significant psychosocial burden, yet current therapies show heterogeneous efficacy and tolerability between individuals. Over the past decade, genome wide association and sequencing studies have identified hundreds of susceptibility loci that converge on androgen signalling, WNT pathways, prostaglandin metabolism, extracellular matrix remodelling, vascular regulation, telomere biology, and cellular metabolism, indicating that male pattern hair loss is mechanistically tractable and strongly genetically determined. In parallel, pharmacogenetic work has linked variants in genes involved in minoxidil bioactivation, 5α-reductase isoenzyme activity, prostaglandin synthesis, collagen organisation, and vascular tone to differences in treatment response. In this narrative review, we integrate evidence from large genetic studies, targeted pharmacogenetic cohorts, transcriptomic and pathway analyses, and preclinical models to delineate how genetic architecture informs disease mechanisms and modulates the effects of established therapies such as topical and oral minoxidil, finasteride, dutasteride, and prostaglandin-directed approaches. We also discuss emerging targets, including IGF1R, WNT10A, PPARGC1A, and prolactin receptor signalling, and examine how RNA based androgen receptor silencing and stem-cell-derived regenerative strategies exploit these pathways. Together, these data support a shift from empirical prescribing towards genetically informed, mechanism anchored treatment algorithms for male pattern hair loss, in which pharmacogenetic markers, polygenic scores, and multi omic readouts are progressively incorporated into therapeutic decision making and the design of future clinical trials.