Abstract
Hidradenitis suppurativa (HS) is a chronic autoinflammatory skin disorder with a complex genetic and molecular basis. To advance its characterization, we applied InterOmics, a novel bioinformatics pipeline integrating whole exome sequencing (WES) and RNA sequencing (RNA-seq), to saliva and skin biopsy samples from six HS patients. This approach enabled a comprehensive multiomics investigation, identifying disease-associated genetic variants and transcriptomic alterations. A key innovation of InterOmics is the Multiomics Variant Category, which classifies variants based on DNA and RNA data, capturing regulatory mechanisms such as allele-specific expression, RNA editing, nonsense-mediated decay, and gain-of-function mutations. Our findings highlight HLA gene variants and keratin-related mutations as potential contributors to HS pathogenesis. By bridging genomic and transcriptomic data, InterOmics enhances variant interpretation. This study underscores the power of multiomics-driven approaches in deciphering complex diseases, paving the way for precision medicine in HS.