Utilising SNP Association Analysis as a Prospective Approach for Personalising Androgenetic Alopecia Treatment.

INTRODUCTION:Androgenetic alopecia (AGA) is a prevalent, multifactorial form of hair loss involving complex aetiological factors, such as altered androgen regulation and energy metabolism. Existing treatments offer limited success, thus highlighting the need for advanced, personalised therapeutic strategies. This study focuses on correlating the genetic mechanisms of AGA with molecular targets involved in the response to current treatment modalities. METHODS:An anonymised database including 26,607 patients was subjected to analysis. The dataset included information on patients' genotypes in 26 single nucleotide polymorphisms (SNPs), specifically, and diagnosed AGA grades, representing a broad range of ethnic backgrounds. RESULTS:In our sample, 64.6% of males and 35.4% of females were diagnosed with female pattern hair loss. This distribution aligns well with prior studies, thus validating the representativeness of our dataset. AGA grading was classified using the Hamilton-Norwood and Ludwig scales, although no association was found to the grade of the disease. SNP association analysis revealed eight SNPs, namely rs13283456 (PTGES2), rs523349 (SRD5A2), rs1800012 (COL1A1), rs4343 (ACE), rs10782665 (PTGFR), rs533116 (PTGDR2), rs12724719 (CRABP2) and rs545659 (PTGDR2), to be statistically significant with a p-value below 0.05. CONCLUSIONS:The study establishes a preliminary association between eight specific SNPs and AGA. These genetic markers offer insights into the variability of therapeutic responses, thus underlining the importance of personalised treatment approaches. Our findings show the potential for more targeted research to understand these SNPs' and further roles in AGA pathophysiology and in modulating treatment response.