A Genome-Wide Association Study Identifying Novel Genetic Markers of Response to Treatment with Interleukin-23 Inhibitors in Psoriasis

<b>Background/Objectives</b>: The advent of biologics targeting key inflammatory pathways has significantly advanced psoriasis treatment. Among them, the Interleukin-23 inhibitors Guselkumab and Risankizumab have demonstrated high efficacy and rapid clinical response in both clinical trials and real-world studies. However, up to 30% of patients fail to respond. This study aimed to identify pharmacogenetic markers associated with treatment response using a genome-wide association study (GWAS) and protein network-based approach. <b>Methods</b>: Fifty-three patients of Greek origin with moderate-to-severe plaque psoriasis were treated with Guselkumab or Risankizumab. Based on Psoriasis Area and Severity Index (PASI) improvement at 3 and 6 months, patients were categorized as responders or non-responders. Approximately 730,000 single-nucleotide polymorphisms (SNPs) were genotyped. After filtering, a GWAS was performed to identify variants associated with treatment response. Additionally, protein-protein interaction (PPI) network analysis was applied to the two Interleukin-23 subunits and SNPs within or near genes encoding Interleukin-23-interacting proteins to test for their association. <b>Results</b>: The GWAS identified two novel variants, rs73641950 and rs6627462, significantly associated with treatment response, with both surpassing the genome-wide significance threshold after Bonferroni correction. The PPI-based approach revealed rs13086445, located downstream of the Interleukin-12 subunit alpha (IL12A) gene, as another associated variant. All three SNPs lie in genomic regions with potential regulatory roles. <b>Conclusions</b>: This study identifies three novel genetic variants associated with response to Interleukin-23 inhibitors in psoriasis. These findings provide promising pharmacogenetic markers which, upon validation in larger, independent cohorts, will enable the translation of a patient's genotype into a response phenotype, thereby guiding clinical decisions and improving drug effectiveness.