Machine learning identifies cytokine signatures of disease severity and autoantibody profiles in systemic lupus erythematosus - a pilot study.

ABSTRACT: Disrupted cytokine networks and autoantibodies play an important role in the pathogenesis of systemic lupus erythematosus. However, conflicting reports and non-reproducibility have hindered progress regarding the translational potential of cytokines in SLE. This study attempts to address the existing knowledge gap using multiplex cytokine assay and machine learning. 67 SLE patients fulfilling SLICC criteria were recruited after informed consent, and circulating cytokines were measured by multiplex cytokine assay kit. We observed a positive association between actual disease activity scores (SLEDAI) and predicted scores from a partial least squares regression (PLSR) analysis of multivariate cytokine response data, with MIP-1α having a strong contribution towards disease activity. Our analys

SUBMITTER: Pattanaik SS 

PROVIDER: S-EPMC11579361 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature