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Subclinical Atherosclerosis Risk Can Be Predicted in Female Patients With Systemic Lupus Erythematosus Using
Laurel Woodridge1, Maria G Tektonidou2, George A Robinson1
1Department of Ageing, Rheumatology and Regenerative Medicine, Division of Medicine University College of London London UK.
Insights
A new metabolite-based risk score accurately predicts atherosclerosis in women with systemic lupus erythematosus (SLE), outperforming traditional risk calculators. This tool can improve cardiovascular disease (CVD) risk assessment and management for SLE patients.
Area of Science:
- Cardiovascular Health
- Metabolomics
- Systemic Lupus Erythematosus (SLE) Research
Background:
- Cardiovascular disease (CVD) is a primary cause of mortality in women with systemic lupus erythematosus (SLE).
- Accelerated atherosclerosis in SLE patients is often undetected by current CVD risk scores.
- There is a need for improved CVD risk prediction in this vulnerable population.
Purpose of the Study:
- To develop and validate a novel, female-focused predictive atherosclerosis risk signature.
- To utilize serum metabolites and machine learning for enhanced risk prediction in SLE.
- To improve cardiovascular risk assessment and management strategies for women with SLE.
Main Methods:
- Serum metabolomics analysis was performed on female SLE patients.
- Machine learning pipelines were employed to identify predictive metabolite signatures.
- Developed signatures were validated in independent SLE cohorts using vascular ultrasound and plaque status.
- A refined 5-feature score was developed to predict subclinical plaque and progression.
Main Results:
- A 35-metabolite/5-clinical trait signature significantly outperformed existing CVD risk scores and routine lipid profiles.
- The validated atherosclerosis risk signature accurately predicted plaque status (AUC=0.79) and progression (AUC=0.79).
- A refined 5-feature score achieved high accuracy (AUC=0.84) in stratifying atherosclerosis risk and identified distinct risk subgroups.
Conclusions:
- The developed atherosclerosis risk score shows potential for improved CVD risk assessment in female SLE patients.
- This score could enhance clinical management strategies for cardiovascular health in SLE.
- Further validation in diverse cohorts is recommended to support broader clinical application.
Background:
Cardiovascular disease (CVD) is a leading cause of death in women with systemic lupus erythematosus (SLE) due to accelerated atherosclerosis that is not predicted by established CVD risk scores. This study aimed to develop, validate, and test a female-focused predictive atherosclerosis risk signature based on serum metabolites in patients with SLE.
Methods And Results:
Female patients with SLE were assessed for the presence (SLE-P; n=18) or absence (SLE-NP; n=26) of subclinical atherosclerosis using vascular ultrasound for carotid/femoral intima-media thickness. CVD risk was assessed using QRISK3 (which includes SLE diagnosis as a risk factor) and Framingham Risk Score. Serum metabolomics (n≥250) was performed and analyzed using machine learning pipelines. Despite having subclinical atherosclerosis, 44.8% to 100% of patients with SLE-P had low CVD risk according to QRISK3/Framlingham Risk Score scores. Using a lipid-focused metabolomic analysis, an improved atherosclerosis risk predictive signature was developed comprising 35 metabolites/5 clinical traits that classified patients with SLE-P and outperformed CVD risk assessment tools, lipid profiles measured in routine care, and clinical features alone. This "atherosclerosis risk signature" was validated in a second adult female SLE cohort (n=98) that predicted plaque status with moderate accuracy (area under the receiver operating characteristic curve, 0.79). The signature was then refined into a 5-feature subclinical plaque-predictive score that not only stratified the combined SLE-P/SLE-NP cohorts (n=142; area under the receiver operating characteristic curve, 0.84) but also predicted 3-year atherosclerosis progression in female postpubertal patients with juvenile-onset SLE (n=36; area under the receiver operating characteristic curve, 0.79). Finally, the 5-feature score identified distinct high and low subclinical atherosclerosis risk subgroups in a "real-world" setting of unscanned adult patients with SLE (n=38).
Conclusions:
This atherosclerosis risk score could improve CVD risk assessment/management in female patients with SLE across age. Validation in non-SLE and healthy cohorts could further substantiate these findings.
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