Journal Article

Metabolic systems approaches update molecular insights of clinical phenotypes and cardiovascular risk in patients with homozygous familial hypercholesterolemia

Li, Fan, Jiang, Long, Wang, Yu, Sun, Haili, Du, Zhiyong, Yang, Ya, Du, Yunhui, Li, Linyi, Li, Jianping, Jiao, Xiaolu, Wang, Luya, Qin, Yanwen, Luo, Yan, Hu, Chaowei, Yu, Huahui

2023

Overview

Background Homozygous familial hypercholesterolemia (HoFH) is an orphan metabolic disease characterized by extremely elevated low-density lipoprotein cholesterol (LDL-C), xanthomas, aortic stenosis, and premature atherosclerotic cardiovascular disease (ASCVD). In addition to LDL-C, studies in experimental models and small clinical populations have suggested that other types of metabolic molecules might also be risk factors responsible for cardiovascular complications in HoFH, but definitive evidence from large-scale human studies is still lacking. Herein, we aimed to comprehensively characterize the metabolic features and risk factors of human HoFH by using metabolic systems strategies. Methods Two independent multi-center cohorts with a total of 868 individuals were included in the cross-sectional study. First, comprehensive serum metabolome/lipidome-wide analyses were employed to identify the metabolomic patterns for differentiating HoFH patients ( n  = 184) from heterozygous FH (HeFH, n  = 376) and non-FH ( n  = 100) subjects in the discovery cohort. Then, the metabolomic patterns were verified in the validation cohort with 48 HoFH patients, 110 HeFH patients, and 50 non-FH individuals. Subsequently, correlation/regression analyses were performed to investigate the associations of clinical/metabolic alterations with typical phenotypes of HoFH. In the prospective study, a total of 84 HoFH patients with available follow-up were enrolled from the discovery cohort. Targeted metabolomics, deep proteomics, and random forest approaches were performed to investigate the ASCVD-associated biomarkers in HoFH patients. Results Beyond LDL-C, various bioactive metabolites in multiple pathways were discovered and validated for differentiating HoFH from HoFH and non-FH. Our results demonstrated that the inflammation and oxidative stress-related metabolites in the pathways of arachidonic acid and lipoprotein(a) metabolism were independently associated with the prevalence of corneal arcus, xanthomas, and supravalvular/valvular aortic stenosis in HoFH patients. Our results also identified a small marker panel consisting of high-density lipoprotein cholesterol, lipoprotein(a), apolipoprotein A1, and eight proinflammatory and proatherogenic metabolites in the pathways of arachidonic acid, phospholipid, carnitine, and sphingolipid metabolism that exhibited significant performances on predicting first ASCVD events in HoFH patients. Conclusions Our findings demonstrate that human HoFH is associated with a variety of metabolic abnormalities and is more complex than previously known. Furthermore, this study provides additional metabolic alterations that hold promise as residual risk factors in HoFH population.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Abnormalities / Acids / Aorta / Aortic stenosis / Aortic valve stenosis / Apheresis / Apolipoproteins / Arachidonic acid / Arteriosclerosis / Atherosclerosis / Bioactive compounds / Biomarkers / Biomedicine / Cardiac patients / Cardiovascular diseases / Care and treatment / Carnitine / Cholesterol / Complications / Complications and side effects / Cornea / Corneal arcus / Density / Diagnosis / Genetic aspects / Genotype & phenotype / Health risks / Heart attacks / High density lipoprotein / Homozygous familial hypercholesterolemia / Hospitals / Hypercholesterolemia / Inflammation / Lipid metabolism / Lipids / Lipoprotein A / Lipoproteins / Liver transplants / Low density lipoprotein / Low density lipoproteins / Medical laboratories / Medical research / Medicine / Medicine & Public Health / Medicine, Experimental / Metabolic disorders / Metabolites / Metabolomics / Mutation / Oxidative stress / Performance prediction / Phenotype / Phenotypes / Phospholipids / Proteomics / Regression analysis / Research Article / Risk factors / Statins / Unsaturated fatty acids / Xanthoma / Xanthomas