Soomro, M, Stadler, M, Dand, N et al. (60 more authors) (2022) Comparative Genetic Analysis of Psoriatic Arthritis and Psoriasis for the Discovery of Genetic Risk Factors and Risk Prediction Modeling. Arthritis and Rheumatology, 74 (9). pp. 1535-1543. ISSN 2326-5191
Abstract
Objectives
Psoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous-only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models.
Methods
Genome-wide meta-analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single-nucleotide polymorphism (SNP)–based heritability estimate (h2SNP) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation.
Results
We identified a novel genome-wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; P = 1.61 × 10−9), and key pathways that differentiate PsA from PsC, including NF-κB signaling (adjusted P = 1.4 × 10−45) and Wnt signaling (adjusted P = 9.5 × 10−58). The heritability of PsA in this cohort was found to be moderate (h2SNP = 0.63), which was similar to the heritability of PsC (h2SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data.
Conclusion
Key biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Institute of Rheumatology & Musculoskeletal Medicine (LIRMM) (Leeds) > Inflammatory Arthritis (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Sep 2022 13:35 |
Last Modified: | 27 Sep 2022 12:34 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1002/art.42154 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:191095 |