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.
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.
Authors: D D Gladman; C T Schentag; B D M Tom; V Chandran; J Brockbank; C Rosen; V T Farewell Journal: Ann Rheum Dis Date: 2008-04-29 Impact factor: 19.103
Authors: Philip J Mease; Dafna D Gladman; Philip Helliwell; Majed M Khraishi; Joanne Fuiman; Eustratios Bananis; Daniel Alvarez Journal: J Am Acad Dermatol Date: 2014-06-25 Impact factor: 11.527
Authors: Mehreen Soomro; Michael Stadler; Nick Dand; James Bluett; Deepak Jadon; Farideh Jalali-Najafabadi; Michael Duckworth; Pauline Ho; Helena Marzo-Ortega; Philip S Helliwell; Anthony W Ryan; David Kane; Eleanor Korendowych; Michael A Simpson; Jonathan Packham; Ross McManus; Cem Gabay; Céline Lamacchia; Michael J Nissen; Matthew A Brown; Suzanne M M Verstappen; Tjeerd Van Staa; Jonathan N Barker; Catherine H Smith; Oliver FitzGerald; Neil McHugh; Richard B Warren; John Bowes; Anne Barton Journal: Arthritis Rheumatol Date: 2022-08-04 Impact factor: 15.483