Refining the Psoriatic Transcriptome: A High-Resolution Bioinformatic Analysis of Four Molecular Hallmarks in GSE13355 Using a Curated Probe-Selection Workflow

Background: Psoriasis is an immune-mediated inflammatory skin disease driven by complex transcriptomic alterations. Traditional secondary workflows frequently ignore alternative transcripts by averaging or discarding redundant microarray probes, which dilutes essential biological signals. Objective: To advance our foundational 2018 bioinformatic framework by performing a high-resolution transcriptomic analysis of four core molecular hallmarks in psoriasis - canonical TNF-α signaling, the IL-6 transduction core, the S100 calcium-binding family, and the EGFL8 pathway grid- using a refined probe-selection protocol. Methods: Public transcriptomic data from the NCBI GEO series GSE13355 (GPL570 platform), comprising paired lesional (PP) and non-lesional (PN) skin biopsies alongside healthy controls (NN), were analyzed using R-limma. Methodologically, cross-hybridizing _x_at probes were excluded, while unique _at and shared _s_at probes were retained to capture splice variants. Multiple probes targeting the same gene symbol were collapsed by selecting the single most informative probe based on the highest absolute t-statistic. Results: The S100 family displayed the highest magnitude of differential expression, led by the massive upregulation of alarmins S100A12 (logFC = 5.8263) and S100A9 (logFC = 5.8228). Within the TNF-α and IL-6 panels, NFKB1 (logFC = 0.5161) and STAT3 (logFC = 1.0926) were identified as dominant transcriptional nodes. Retaining _s_at probes proved essential to capture primary reactive signals for STAT3 and IKBKG. Furthermore, the EGFL8 grid revealed significant cell cycle acceleration via MAP2K1 and CDK1 induction. Conclusion: By refining microarray probe curation, this study successfully improves the data consistency of our original model, providing a precise, systems-level resolution of the molecular hallmarks sustaining psoriatic lesions.