OA40 Predicting cardiovascular disease risk in children and adolescents with juvenile-onset systemic lupus erythematosus using the APPLE (Atherosclerosis Prevention in Paediatric Lupus Erythematosus) clinical trial cohort

Abstract Background/Aims The risk of developing cardiovascular disease (CVD) through atherosclerosis in juvenile-onset systemic lupus erythematosus (JSLE) patients is significantly increased. This study aimed to stratify and characterise JSLE patients at elevated CVD risk using patient/disease-relat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Rheumatology (Oxford, England) England), 2023-04, Vol.62 (Supplement_2)
Hauptverfasser: Peng, Junjie, Robinson, George A, Ardoin, Stacy P, Schanberg, Laura E, Jury, Elizabeth, Ciurtin, Coziana
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Abstract Background/Aims The risk of developing cardiovascular disease (CVD) through atherosclerosis in juvenile-onset systemic lupus erythematosus (JSLE) patients is significantly increased. This study aimed to stratify and characterise JSLE patients at elevated CVD risk using patient/disease-related factors and metabolomic data from patients recruited to the APPLE (Atherosclerosis Prevention in Paediatric Lupus Erythematosus) clinical trial, designed to assess atherosclerosis development. Methods Unsupervised hierarchical clustering was performed to stratify patients by arterial intima-media thickness (IMT) measurements at baseline (N = 151) and carotid (c)IMT progression over 36 months (placebo arm only, N = 60). Baseline metabolomic profiles (∼250 serum metabolites) were compared between clusters using conventional statistics, univariate logistic regression, sparse Partial Least-Squares Discriminant Analysis (sPLS-DA) and random forest classifier. An independent cohort (UCL-JSLE cohort, N = 89) with matching metabolomics, immunophenotyping and proteomics, was used to validate the discovered CVD risk-related signatures from the APPLE cohort. Results Baseline IMT stratification identified 3 clusters with high, intermediate, and low baseline IMT measurements and progression trajectories over 36 months, each having distinct racial/BMI/household education/income characteristics. Analysis of cIMT progression over 36 months identified 2 patient groups with high and low IMT progression. Unique metabolomic profiles differentiated high and low cIMT progression groups, with a good discriminatory ability (0.81 AUC in ROC analysis) using the top 6 metabolites (total cholesterol esters, total cholesterol, phospholipids in small LDL particles, total cholesterol in small LDL particles, free cholesterol in medium LDL particles, and total lipids in small LDL particles) selected from the analysis. cIMT progression over 36 months in the placebo group correlated positively with baseline disease activity (SLEDAI), damage score (SLICC), white blood cell count, serum complement C3, blood pressure (both systolic and diastolic) and BMI. Metabolomics signatures discovered from the APPLE cohort were applied to stratify JSLE patients in the validation cohort (UCL-JSLE), where 3 groups were identified with distinct metabolomics profiles indicating JSLE patients with high risk (N = 20), intermediate risk (N = 43) and low risk (N = 26) CVD-risk. Significant differences were observed
ISSN:1462-0324
1462-0332
DOI:10.1093/rheumatology/kead104.039