Woodridge, Laurel; (2024) Investigating multi-omics signatures to understand cardiovascular risk and atherosclerosis in systemic lupus erythematosus (SLE). Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Background: Cardiovascular disease (CVD) is a leading cause of mortality in SLE, a chronic autoimmune disease predominantly affecting women, through accelerated atherosclerosis. However, routine clinical measures underestimate CVD risk in SLE. Methods: A well-characterised cohort of CVD-free females were scanned for atherosclerotic plaques in the carotid and femoral arteries using vascular ultrasound. Molecular profiles of patients with (SLE-P) and without (SLE-NP) subclinical plaques were investigated using bioinformatic analysis and machine learning applied to multi-omics data: RNA-sequencing, proteomics, and metabolomics, with serum lipid profiles validated in two independent cohorts. Omics integration was conducted using several networks and factor analysis (MOFA). A pipeline to perform novel biomarker identification was developed using leading disease module enrichment algorithms (MONET, DIAMOnD). Results: A distinct subclinical atherosclerosis endotype was revealed in SLE. A 35-metabolite signature with clinical traits could accurately identify patients with subclinical plaque (0.92 receiver operating characteristic/ROC), which was validated in an external all-female cohort (ROC=0.79). Glycine concentration was diminished across a 5-year trajectory in SLE-P, which was used in a novel CVD-risk scoring system to stratify unscanned patients into distinct subgroups, alongside low and intermediate lipoproteins, and omega-6/omega-3 ratio concentrations. SLE-P patients’ transcriptomes were characterised by dampened inflammation, including a significantly lower interferon response, and overexpression of genes involved in purine metabolism and purinergic signalling. Dysregulated complement and apoptosis characterised SLE-P proteomes. A multi-omic signature was developed and examined for functional context using enriched disease modules, further implicating purine metabolism and cytokine signalling, with glutathione and lipid metabolism, endocytosis, and DNA repair. 50-novel biomarkers closely interacting with the SLE-P signature were associated with mitochondrial and complement function. Conclusions: Lipid dysregulation, dampened inflammation and complement dysfunction characterised molecular signatures associated with atherosclerosis in SLE that could be used to stratify patients by CVD risk.

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