Dataset Information

Evaluation of a Genetic Risk Score for Diagnosis of Psoriatic Arthritis.

ABSTRACT:

Background

Diagnosis of psoriatic arthritis (PsA) can be challenging, resulting in delays that contribute to irreversible joint damage, reduced quality of life, and increased mortality.

Objective

Use genetic markers to develop and evaluate a PsA genetic risk score (GRS) for its ability to discriminate between psoriasis (PsO) only and PsO with PsA among a psoriatic cohort with full genome-wide genotype data.

Methods

Genome-wide single-nucleotide polymorphism genotyping was performed on 724 psoriatic patients. A set of 11 candidate risk genes previously shown to be preferentially associated with PsO or PsA were selected. To evaluate the cumulative effects of these risk loci, a PsA GRS was developed using an unweighted risk allele count (cGRS) and a weighted (wGRS) approach. Additional analyses included only human leukocyte antigen (HLA) risk alleles.

Results

The discriminative power attributable to each GRS was evaluated by calculating the areas under the receiver operator characteristic curve (AUROC). The AUROC for the wGRS is 56.2% versus 54.1% for the cGRS, and the AUROC for the HLA-only wGRS model was 56.9% versus 55.7% for the HLA-only cGRS.

Conclusion

The AUROC of 56.9% for HLA-only wGRS indicates that this approach has the greatest power in discriminating PsA from PsO among these models. Given that an AUROC of 56.9% is quite modest, this study suggests that using a small number of well-validated genetic loci provides limited predictive power for PsA, and that future approaches may benefit from using a larger number of genetic loci.

SUBMITTER: Smith MP

PROVIDER: S-EPMC7252226 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Publications

Evaluation of a Genetic Risk Score for Diagnosis of Psoriatic Arthritis.

Smith Mary Patricia MP Ly Karen K Thibodeaux Quinn Q Beck Kristen K Yang Eric E Sanchez Isabelle I Nititham Joanne J Bhutani Tina T Liao Wilson W

Journal of psoriasis and psoriatic arthritis 20200304 2

<h4>Background</h4>Diagnosis of psoriatic arthritis (PsA) can be challenging, resulting in delays that contribute to irreversible joint damage, reduced quality of life, and increased mortality.<h4>Objective</h4>Use genetic markers to develop and evaluate a PsA genetic risk score (GRS) for its ability to discriminate between psoriasis (PsO) only and PsO with PsA among a psoriatic cohort with full genome-wide genotype data.<h4>Methods</h4>Genome-wide single-nucleotide polymorphism genotyping was p ...[more]

PMID: 32462110

Similar Datasets

Project description:IntroductionPsoriatic arthritis (PsA) is a chronic, inflammatory arthritis that affects an estimated 30% of patients with psoriasis. PsA is underdiagnosed in primary care and dermatology clinics due to a variety of reasons, including failure of healthcare providers to ask about symptoms, overlap of symptoms and signs with other rheumatologic conditions, and lack of a specific diagnostic test. A delay in PsA diagnosis and treatment, even as short as 6 months, can lead to decreased quality of life, increased joint damage, and worse long-term physical function. In this study, we sought to identify the clinical and genetic factors that help discriminate patients with PsA from those with cutaneous psoriasis only.MethodsWe analyzed a cohort of 974 psoriasis patients at an academic medical center, of whom 175 had confirmed PsA, and performed univariate, multivariate, and predictive modeling to determine factors associated with PsA.ResultsThe univariate analysis revealed significant positive associations of PsA with age, nail involvement, scalp involvement, skin fold involvement, elbow/knee involvement, psoriasis severity, plaque subtype, erythrodermic subtype, hypertension, type 2 diabetes, and coronary artery disease, and a significant negative association of PsA with the human leukocyte antigen (HLA)-C*06:02 allele. In the multivariate analysis, nail involvement, type 2 diabetes, and pustular psoriasis remained significantly associated with PsA, while HLA-C*06:02 positivity remained protective. There was a trend towards an association of PsA with older age, younger age of psoriasis onset, and skin fold involvement, while there was protective trend for smoking. A predictive model including both clinical and genetic factors showed reasonable discriminative ability between psoriasis and PsA, with an area under the curve of 0.87 for a receiver operating characteristic curve.ConclusionThis study identified a number of clinical and genetic features that could help stratify patients who are at higher risk for having PsA and for whom rheumatology referral may be beneficial.

Project description:ObjectivesPsoriatic 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.MethodsGenome-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 (h2 SNP ) 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.ResultsWe 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 (h2 SNP = 0.63), which was similar to the heritability of PsC (h2 SNP = 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.ConclusionKey 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.

Project description:BackgroundThe early detection of psoriatic arthritis (PSA) poses a challenge to rheumatologists, even when their diagnosis is aided by sonography. In order to facilitate early detection of PSA among patients with psoriasis (PSO), we retrospectively analyzed of the relationships between serological markers and comorbidities in 629 psoriatic patients, 102 of which had PSA, while the other 527 had PSO.ResultsSerological markers were found not to be useful in distinguishing between PSA and PSO (p > 0.05 for all comparisons). The prevalence rate of PSA among PSO patients was around 19.4%. Two components of metabolic syndrome-hyperlipidemia (2.94%) and gout (4.9%)-were significantly more prevalent in PSA patients than in PSO patients (p < 0.05). The odds ratio for PSA is 15.94 in patients with hyperlipidemia with a 95% confidence interval (CI) of 1.64-154.80; meanwhile, the odds ratio for PSA is 3.83 in patients with gout with a 95% CI of 1.19-12.31. Allergic rhinitis (5.88%) was more prevalent in PSA patients than in PSO patients (p < 0.01). The odds ratio was 8.17 in patients with allergic rhinitis with a 95% CI of 2.26-29.50. Plasma hs-miR-210-3p distinguishes PSA from PSO, and its levels can also be distinguished from PSA after treated with anti-TNFα biologics agents (both p < 0.05).ConclusionsNo clinical available serology markers, but hyperlipidemia, gout, axial spondylopathy (inflammatory back pain), or allergic rhinitis, could differentiate between psoriatic arthritis from psoriasis. Plasma hs-miR-210-3p and comorbidities may differentiate psoriatic arthritis from psoriasis. Key Points • Clinical manifestations and comorbidities are different between psoriatic arthritis and psoriasis only patients. • Traditional serology markers are similar between psoriatic arthritis and psoriasis-only patients. • Plasma hs-miR-210-3p distinguishes PSA from PSO, and its levels can also be distinguished from PSA after treated with anti-TNFα biologics agents in our study.

Dataset Information

Evaluation of a Genetic Risk Score for Diagnosis of Psoriatic Arthritis.

Background

Objective

Methods

Results

Conclusion

Publications

Evaluation of a Genetic Risk Score for Diagnosis of Psoriatic Arthritis.

Similar Datasets

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