Metabolomics and cardiovascular risk factors in autoimmune-mediated connective tissue diseases – an exploratory, hypothesis-generating study

BACKGROUND: Autoimmune connective tissue diseases (ACTD), including systemic lupus erythematosus (SLE), systemic sclerosis (SSc), Sjögren's disease (SD), and idiopathic inflammatory myopathies (IIM), are associated with markedly increased cardiovascular risk (CVR) that is insufficiently captured by conventional risk scores. Reliable biomarkers for CVR stratification in ACTD are lacking. This exploratory, hypothesis-generatig study aimed to investigate whether metabolomic alterations reflect CVR across ACTD subtypes. METHODS: In this cross-sectional, exploratory study, patients with SLE (n = 33), SSc (n = 18), SD (n = 16), and IIM (n = 9) were recruited from a tertiary rheumatology center. Serum metabolomic profiling was performed using ¹H-NMR spectroscopy. Associations between 113 quantified metabolites and clinical CVR parameters (including age, sex, body mass index, glucocorticoid use, Framingham score, hypertension, diabetes, lipid parameters, and lifestyle factors) were analyzed using non-parametric statistics with false discovery rate correction. Correlation analyses were conducted using Spearman coefficients. RESULTS: Metabolomic alterations varied substantially across ACTD subtypes and CVR factors. Lipid metabolites showed the strongest and most consistent associations with CVR parameters. The Framingham score correlated with 11 metabolites in SLE, 1 in SSc, 2 in SD, and 93 in IIM, predominantly involving lipid components. Diabetes mellitus was associated with extensive metabolomic changes, particularly in SSc (n = 62 metabolites), followed by SD (n = 20) and SLE (n = 5). In contrast, arterial hypertension showed minimal metabolomic differentiation across most ACTD, except in IIM. Body mass index correlated mainly with lipid metabolites in SSc, but not in SLE. Glucocorticoid therapy and dosage were strongly associated with alterations in lipid metabolism, especially in SLE and SSc. Across all entities, correlations with total cholesterol, LDL, and HDL were dominated by lipid metabolites. Associations with renal markers (UACR) were limited. CONCLUSIONS: ACTD are characterized by heterogeneous metabolomic signatures associated with cardiovascular risk factors. Larger, longitudinal studies are required to validate these findings and to determine their clinical utility in cardiovascular risk stratification in ACTD.