# Biomarkers of Risankizumab Response

## Overview
What biomarkers correlate with response to risankizumab across plaque psoriasis, psoriatic arthritis, and Crohn's disease?

## Main Analysis
I'll search for biomarker studies across risankizumab's three main indications — plaque psoriasis, psoriatic arthritis, and Crohn's disease.

### Searches Conducted
1. Risankizumab transcriptomic genomic predictors clinical response
2. IL-23 inhibitor biomarkers pharmacodynamic skin gut inflammation
3. Risankizumab psoriatic arthritis biomarkers treatment response
4. Risankizumab Crohn's disease biomarkers fecal calprotectin CRP response prediction
5. Risankizumab biomarkers response predictors plaque psoriasis IL-23

### Biomarker Landscape
The biomarker landscape for risankizumab spans three broad categories — pharmacodynamic markers that change with treatment, baseline predictors of response, and drug-level markers — and there's meaningful heterogeneity across indications in what has actually been studied rigorously.

#### Plaque Psoriasis
Plaque psoriasis has the richest biomarker data. A head-to-head biopsy study by Visvanathan et al. in _JACI_ (2019, n=81) showed:
- Risankizumab produced rapid, sustained decreases in tissue markers of the IL-23/Th17 axis — including K16, Ki67, CD3, lipocalin-2, CD11c, β-defensin 2, and S100A7
- More strongly downregulated keratinocyte and monocyte gene signatures than ustekinumab at week 4, providing detailed molecular proof of on-target engagement.

On the predictive side, a transcriptomic study from Cantó et al. (_Int J Mol Sciences_, 2025) proposed:
- Skin expression of CXCL8, IL-6, and CXCL10, combined with plasma levels of CCL20, IL-6, and CXCL8, as candidate baseline predictors for anti-IL-23 response — though this involved only 18 patients requiring validation.

A small GWAS (n=53) identified three SNPs in regulatory regions near the IL-23 signaling network as candidate pharmacogenetic markers, though these have not been replicated.

##### Additional Insights
- A study of autoreactive T-cells found that dual reactivity to LL37 and ADAMTSL5 was associated with suboptimal PASI response.
- HLA-Cw06:02+ status predicted faster response at week 4, while obesity slowed early response.
- Two miRNA studies found circulating miR-146a and miR-155 decreased after one year, while baseline miR-200a-3p correlated with disease severity; however, the cohorts were small and exploratory.
- A multicenter study found that reduction in systemic inflammatory markers (NLR, SII, SIRI, CRP, ESR) tracked with treatment response, with faster responders showing more early normalization.

#### Psoriatic Arthritis
Psoriatic arthritis has a more limited dedicated biomarker dataset. The KEEPsAKE 2 biomarker substudy reported by Ravishankar et al. (_ARD_, 2023) profiled:
- 92 circulating proteins revealing a correlation of CCL20, IL-17A, IL-17C, IL-24, IL-6, S100A12, OSM, VEGF-A, CXCL1, and CSF-1 with disease activity.
- After treatment, IL-17A, IL-17C, IL-6, and β-defensin 2 (BD-2) were significantly reduced by week 4 and continued declining through week 24.

This suggests a domain-specific pharmacodynamic signature. A systematic review noted that higher baseline CRP generally predicted better clinical response in PsA, but the evidence predates risankizumab's approval.

#### Crohn's Disease
Crohn's disease has the most clinically actionable biomarker data focused on hs-CRP and fecal calprotectin (FCP). A post-hoc analysis found:
- Risankizumab achieved hs-CRP normalization (≤5 mg/L) in 49% of patients at week 12 versus 18% on placebo.
- FCP normalization (≤250 µg/g) in 26% versus 9%, with rates sustained through week 52.

### Final Insights
- Early CRP normalization at week 12 was identified as a strong predictor of week 52 remission.
- A phase 2b study showed risankizumab reduced various inflammatory markers.
- Trough levels indicated that patients achieving clinical and biological remission had higher risankizumab levels.
- Some cross-indication themes suggest IL-17A, IL-17C, IL-6, CCL20, and CRP consistently relate to treatment response across psoriasis and PsA.

### Conclusion
What remains genuinely absent is a validated predictive biomarker for any of the three indications with enough evidence to guide clinical decisions. The field has good pharmacodynamic markers but lags on prospectively validated predictors.

This is an initial search, and a more comprehensive review could surface unpublished trial sub-studies or translational work.