Classifying patients with psoriatic arthritis according to their disease activity status using serum metabolites and machine learning.

ABSTRACT:

Introduction

Psoriatic arthritis (PsA) is a heterogeneous inflammatory arthritis, affecting approximately a quarter of patients with psoriasis. Accurate assessment of disease activity is difficult. There are currently no clinically validated biomarkers to stratify PsA patients based on their disease activity, which is important for improving clinical management.

Objectives

To identify metabolites capable of classifying patients with PsA according to their disease activity.

Methods

An in-house solid-phase microextraction (SPME)-liquid chromatography-high resolution mass spectrometry (LC-HRMS) method for lipid analysis was used to analyze serum samples obtained from patients classified as having low (n = 134), moderate (n = 134) or high (n = 104) disease activity, based

SUBMITTER: Koussiouris J 

PROVIDER: S-EPMC10810020 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature