Logistic regression analysis reveals SNP associations with biologic response in psoriasis, suggesting predictive biomarkers.
Biologics targeting tumor necrosis factor-α (TNFi), interleukin-12/23 (IL-12/23i), and interleukin-17 cytokine or receptor (IL-17i/IL-17Ri) have transformed psoriasis management. However, interindividual variation in response underscores the need for predictive biomarkers in guiding therapy selection. Patients treated with a biologic for psoriasis were genotyped for 67 single-nucleotide polymorphisms (SNPs) previously associated with response to biologics. Odds ratios (OR) with 95% confidence intervals (CI) for associations between SNPs and response to biologics were calculated using logistic regression models with an absolute Psoriasis Area and Severity Index (PASI) ≤2 after 3 months as treatment response. A p-value < 0.05 was considered statistically significant. In total, 373 patients with 574 treatment series were included. Twelve SNPs were associated with treatment response: four uniquely with response to TNF inhibitors (TNFi), two to IL-12/23i, and five to IL-17i/IL-17Ri, while one was associated with response to both TNFi and IL-17i/IL-17Ri. Notably, IRAK3 (rs11541076) and CD84 (rs6427528) were associated with response to TNFi (OR: 2.56 [95% CI: 1.22–5.37], p = 0.012 and OR: 0.53 [95% CI: 0.30–0.91], p = 0.023) and IL-17i/IL-17Ri (OR: 2.55 [95% CI: 0.70–9.22], p = 0.15), and OR: 0.50 [95% CI: 0.25–0.98], p = 0.045), with trends toward opposite associations for IL-12/23i (OR: 0.38 [95%CI: 0.08–1.72], p = 0.21 and OR: 1.64 [95%CI: 0.68–3.93], p = 0.26). This study replicates known genetic associations with biologic response in psoriasis. Variants in IRAK3 and CD84 show potential as stratification biomarkers, although they need confirmation in independent cohorts.
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Loft et al. (2025) studied this question.
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