The Efficacy of Genetic Testing for Early Detection of Psoriatic Arthritis in Patients with Psoriasis

Background: Improved understanding of the genetic architecture of psoriatic disease (PsD) and reduction in genotyping costs provide an opportunity to assess the application of genetic testing for psoriatic arthritis (PsA) diagnosis. The study aimed to assess the performance of a multi-marker genetic kit in classifying patients as PsD and PsA and to assess whether the performance has improved by combining genetic and clinical data.Methods: 328 patients with psoriasis and musculoskeletal symptoms (78 PsA and 250 psoriasis alone) who were referred to rheumatology for suspected PsA and 341 non-psoriatic controls were analyzed. A custom multi-SNP genetic assay, including 41 variants based on large scale association genome-wide association studies in PsA, was genotyped. Machine-learning methods were used to identify the optimal classification model by area under the receiver operating curve (AUC). Results: The performance of all three classifiers to distinguish PsD from non-psoriatic controls was moderate with similar AUC (range 0.64 to 0.69). Logistic regression had the highest AUC and showed moderate specificity (61.9%) and specificity (67.9%). The ability of the models to correctly classify PsA among all psoriasis patients was suboptimal with AUC ranging from 0.55 to 0.60 with low sensitivity (1.3% to 34.6%) and moderate to high specificity (69.2% to 99.6%). The combination of genetic and clinical data resulted in an improvement in the performance of the models (AUC 0.65 to 0.69), however, the information contributed by the genetic markers was only marginal. Conclusions: Genetic testing has marginal effect on correctly classifying PsA among psoriasis patients in clinical setting.