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Abstract

OBJECTIVE: Systemic lupus erythematosus (SLE) is a clinically and biologically heterogenous autoimmune disease. We aimed to investigate the plasma proteome of patients with active SLE to identify novel subgroups, or endotypes, of patients.

METHOD: Plasma was collected from patients with active SLE who were enrolled in the British Isles Lupus Assessment Group Biologics Registry (BILAG-BR). The plasma proteome was analysed using a data-independent acquisition method, Sequential Window Acquisition of All theoretical mass spectra mass spectrometry (SWATH-MS). Unsupervised, data-driven clustering algorithms were used to delineate groups of patients with a shared proteomic profile.

RESULTS: In 223 patients, six clusters were identified based on quantification of 581 proteins. Between the clusters, there were significant differences in age (p = 0.012) and ethnicity (p = 0.003). There was increased musculoskeletal disease activity in cluster 1 (C1), 19/27 (70.4%) (p = 0.002) and renal activity in cluster 6 (C6) 15/24 (62.5%) (p = 0.051). Anti-SSa/Ro was the only autoantibody that significantly differed between clusters (p = 0.017). C1 was associated with p21-activated kinases (PAK) and Phospholipase C (PLC) signalling. Within C1 there were two sub-clusters (C1A and C1B) defined by 49 proteins related to cytoskeletal protein binding. C2 and C6 demonstrated opposite Rho family GTPase and Rho GDI signalling. Three proteins (MZB1, SND1 and AGL) identified in C6 increased the classification of active renal disease although this did not reach statistical significance (p = 0.0617).

CONCLUSIONS: Unsupervised proteomic analysis identifies clusters of patients with active SLE, that are associated with clinical and serological features, which may facilitate biomarker discovery. The observed proteomic heterogeneity further supports the need for a personalised approach to treatment in SLE.

Original languageEnglish
Article number29
Number of pages17
JournalClinical Proteomics
Volume20
Issue number1
DOIs
Publication statusPublished - 29 Jul 2023

Bibliographical note

Funding:
The MASTERPLANS Consortium was funded by a grant from the Medical Research Council (MR/M01665X/1). BILAG BR has been funded by unrestricted educational donations from Roche, GSK and LUPUS UK. Professor Bruce is a National Institute for Health Research (NIHR) Emeritus Senior Investigator and is funded by the NIHR Manchester Biomedical Research Centre. Equipment used in the Stoller Biomarker Discovery Centre is funded by a donation received from the Stoller Charitable Trust and a research grant awarded by the Medical Research Council (MR/M008959/1). MRC/EPSRC Molecular Pathology Node provided additional financial support by a grant from the Medical Research Council and Engineering & Physical Sciences Research Council (MR/N00583X/1).

Availability of data and materials:
The datasets used during the current study may be available from the corresponding author on reasonable request providing anonymisation can be maintained.

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