Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood

Abstract

Background: Cardiovascular diseases may originate in childhood. Biomarkers identifying individuals with increased risk for disease are needed to support early detection and to optimise prevention strategies. Methods: In this prospective study, by applying a machine learning to high throughput NMR-based metabolomics data, we identified circulating childhood metabolic predictors of adult cardiovascular disease risk (MetS score) in a cohort of 396 females, followed from childhood (mean age 11¢2 years) to early adulthood (mean age 18¢1 years). The results obtained from the discovery cohort were validated in a large longitudinal birth cohort of females and males followed from puberty to adulthood (n = 2664) and in four cross-sectional data sets (n = 6341). Findings: The identified childhood metabolic signature included three circulating biomarkers, glycoprotein acetyls (GlycA), large high-density lipoprotein phospholipids (L-HDL-PL), and the ratio of apolipoprotein B to apolipoprotein A-1 (ApoB/ApoA) that were associated with increased cardio-metabolic risk in early adulthood (AUC = 0¢641-0¢802, all p<0¢01). These associations were confirmed in all validation cohorts with similar effect estimates both in females (AUC = 0¢667-0¢905, all p<0¢01) and males (AUC = 0¢734-0¢889, all p<0¢01) as well as in elderly patients with and without type 2 diabetes (AUC = 0¢517-0¢700, all p<0¢01). We subsequently applied random intercept cross-lagged panel model analysis, which suggested bidirectional causal relationship between metabolic biomarkers and cardio-metabolic risk score from childhood to early adulthood. Interpretation: These results provide evidence for the utility of a circulating metabolomics panel to identify children and adolescents at risk for future cardiovascular disease, to whom preventive measures and followup could be indicated.

Percent body fat, but not body mass index, is associated with cardiometabolic risk factors in children and adolescents

“…Cardiometabolic diseases, such as Type 2 diabetes and cardiovascular diseases, are the main causes of mortality, disability, and significant economic burden in modern societies 1 . Although the clinical features of cardiometabolic diseases usually manifest in adulthood, its well‐recognized risk factors, including dyslipidemia, elevated blood pressure (BP), hyperglycemia, and obesity, may even originate in childhood and track into adulthood 2–4 . With economic development and lifestyle changes in recent decades, the population with cardiometabolic risk (CMR) has become more common and younger in China.…”

Metabolomics Defines Complex Patterns of Dyslipidaemia in Juvenile-SLE Patients Associated with Inflammation and Potential Cardiovascular Disease Risk

“…We also identified an increase in the ApoB:ApoA1 ratio exclusive to active patients; likely explained by increased ApoB-expressing small VLDL and decreased ApoA1-expressing small HDL in JSLE patients with more active disease. Importantly, this biomarker has been identified by previous studies to predict of CVD-risk in young people, including prospective studies showing that the expression of apolipoproteins in healthy children reflects subclinical atherosclerosis development [39] and cardiometabolic risk [40] in adulthood, and another study showing that the ApoB:ApoA1 ratio was associated with cardio-metabolic risk in a subset of JSLE patients [41]. Thus, a combination between early lipid biomarkers (such as those identified by our study), combined with traditional cardiovascular assessment tools (such as echocardiography), and measures of JSLE disease activity, could provide a more detailed analysis of CVD-risk in young patients for early clinical intervention.…”

Atherosclerosis Progression in the APPLE Trial Can Be Predicted in Young People With Juvenile‐Onset Systemic Lupus Erythematosus Using a Novel Lipid Metabolomic Signature

“…7 However, despite strong evidence of increased CVD risk in patients with JSLE, comorbidity-tailored recommendations or research directed toward stratifying and managing patients with JSLE based on CVD risk are limited. 8,9 Notably, a growing body of evidence, including data generated by our group, support that circulating biomarkers can predict CVD risk in healthy CYP 10,11 and CYP with JSLE. 12,13 Carotid intima-media thickness (CIMT) is a measure of atherosclerosis that can be used to predict CVD-related events from childhood into middle age 14 and improve the performance of traditional risk factors used for CVD risk classification.…”

“…However, despite strong evidence of increased CVD risk in patients with JSLE, comorbidity‐tailored recommendations or research directed toward stratifying and managing patients with JSLE based on CVD risk are limited 8,9 . Notably, a growing body of evidence, including data generated by our group, support that circulating biomarkers can predict CVD risk in healthy CYP 10,11 and CYP with JSLE 12,13 …”