Combining Clinical, Genetic and Protein Markers Using Machine Learning Models Discriminates Psoriatic Arthritis Patients From Those With Psoriasis.

ABSTRACT:

Background

Psoriatic Arthritis (PsA), an immune mediated inflammatory arthritis, affects a quarter of patients with cutaneous psoriasis, usually after psoriasis onset. Early diagnosis of PsA is challenging. A biomarker-based diagnostic test may facilitate early diagnosis.

Objectives

We aimed to determine whether specific clinical features or genetic and protein markers, alone or in combination, can distinguish patients with PsA from those with psoriasis without PsA (PsC).

Methods

Patients with PsA and PsC were identified from a database of patients with psoriatic disease. Detailed demographic and clinical information were collected at time of assessment. Single-nucleotide polymorphisms (SNPs) of 19 "PsA weighted" genes were genotyped. Serum samples were used to assess

SUBMITTER: Ganatra D 

PROVIDER: S-EPMC12089127 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature