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银屑病关节炎与银屑病的比较遗传学分析:遗传风险因素的发现与风险预测模型构建。

Comparative Genetic Analysis of Psoriatic Arthritis and Psoriasis for the Discovery of Genetic Risk Factors and Risk Prediction Modeling.

机构信息

Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK.

King's College London, London, UK.

出版信息

Arthritis Rheumatol. 2022 Sep;74(9):1535-1543. doi: 10.1002/art.42154. Epub 2022 Aug 4.

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 (h ) 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 ), and key pathways that differentiate PsA from PsC, including NF-κB signaling (adjusted P = 1.4 × 10 ) and Wnt signaling (adjusted P = 9.5 × 10 ). The heritability of PsA in this cohort was found to be moderate (h  = 0.63), which was similar to the heritability of PsC (h  = 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.

摘要

目的

银屑病关节炎(PsA)具有很强的遗传成分,确定遗传风险因素可以帮助识别出约 30%的银屑病患者有发展为 PsA 的高风险。我们的目的是确定区分 PsA 与仅皮肤银屑病(PsC)的遗传风险因素和途径,并评估 PsA 风险预测模型的性能。

方法

分别对 5065 例 PsA 患者和 21286 例健康对照者、4340 例 PsA 患者和 6431 例 PsC 患者进行全基因组荟萃分析。使用基于单核苷酸多态性(SNP)的遗传力估计值(h )计算 PsA 的遗传力,并使用优先级指数软件识别区分 PsA 和 PsC 的生物途径。探索了先前发表的 PsA 风险预测模型的泛化能力,并利用外部验证开发了风险预测模型。

结果

我们在 22q11 染色体上发现了一个新的与 PsA 发病相关的全基因组显著易感位点(rs5754467;P = 1.61×10 ),以及区分 PsA 和 PsC 的关键途径,包括 NF-κB 信号(调整后的 P = 1.4×10 )和 Wnt 信号(调整后的 P = 9.5×10 )。该队列中 PsA 的遗传力被发现为中度(h  = 0.63),与 PsC 的遗传力(h  = 0.61)相似。我们观察到已发表的分类管道的性能一般(最大曲线下面积 0.61),使用当前数据得出的风险模型的性能也相似。

结论

确定了与 PsA 发展相关的关键生物学途径,但风险分类的研究表明,在现有数据集中的应用价值有限,这可能是因为本研究中纳入的许多 PsC 患者正在接受对 PsA 也有效的治疗。未来的 PsA 预测模型应在从初级保健中招募的 PsC 患者中进行测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acde/9539852/e4efdff8f48a/ART-74-1535-g002.jpg

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