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Subclinical Atherosclerosis Risk Can Be Predicted in Females with Systemic Lupus Erythematosus (SLE) Using Metabolomic Signatures
21 Pages Posted: 8 Feb 2024
More...Abstract
Background: Cardiovascular disease (CVD) is a leading cause of mortality in people with systemic lupus erythematosus (SLE) yet established clinical scores fail to predict CVD-risk accurately.
Methods: Patients with SLE (n=44, 100% female) were assessed for CVD-risk using established tools and scanned for carotid intima-media thickness (CIMT) and carotid/femoral atherosclerotic plaques using vascular ultrasound. A lipid-focused nuclear magnetic resonance metabolomic platform was used to assess serum metabolites (n≥250). Classification and regression ML models were applied to metabolomic data comparing patients with (SLE-P, n=18) and without (SLE-NP, n=26) subclinical atherosclerotic plaque. The SLE/atherosclerosis-specific metabolite signature was validated in independent adult SLE (n=98) and juvenile-onset SLE (n=36) cohorts grouped by subclinical atherosclerosis. A clinical score for CVD-risk prediction in SLE was developed and applied to assess CVD-risk in an unscanned adult SLE cohort (n=38).
Findings: Existing CVD-risk assessment tools categorised 44.9-100% of patients with subclinical atherosclerotic plaque and SLE as low CVD-risk. However, a distinct 35-metabolite/5-clinical trait signature correctly classified patients with subclinical plaque with high accuracy (area under curve-receiver operating characteristic AUC-ROC=0.92). This signature outperformed individual features and lipid profiles measured in routine care in the model for CVD-risk prediction. The SLE CVD-risk signature was validated in an independent cohort and correctly predicted plaque status with high accuracy (AUC-ROC=0.79). Finally, a novel score system was developed comprising glycine, medium-sized low-density lipoprotein, intermediate density lipoprotein cholesterol, omega-6/omega-3 ratio and age that could also predict CIMT progression in post-pubertal juvenile SLE (AUC-ROC 0.69/0.79 with and without age respectively). This scoring system was also used to assess CVD-risk in an additional unscanned adult SLE cohort, revealing distinct high and low risk subgroups.
Interpretation: This novel CVD-risk score could improve CVD-risk assessment in SLE across age compared to current methods and/or be used to screen patients to improve CVD management in SLE.
Funding: BBSRC London Interdisciplinary Biosciences PhD consortium (BB/M009513/1), National Institute for Health Research University College London Hospital Biomedical Research Centre (BRC531/III/IPT/101350) and the Rosetrees Trust. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Declaration of Interest: The authors declare no competing interests.
Ethical Approval: All patients provided informed written consent/assent according to the declaration of Helsinki. All patient information was anonymised or pseudo-anonymised in accordance with relevant data protection legislation (EU General Data Protection Regulation (https://www.eugdpr.org/) and UK Data Protection Bill, 2018). This study was approved by the London - City & East Research Ethics Committee of the NHS 15-LO-2065, LondonHarrow Research Ethics Committee (REC11/LO/0330) and by the Institutional Review Board of Laiko Hospital, Athens, Greece.
Keywords: Systemic lupus erythematosus, cardiovascular risk, metabolomics, atherosclerosis, machine learning
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