Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias

Identification of multiple plasma lipids as diagnostic biomarkers of hypercholesterolemia and the underlying mechanisms based on pseudo-targeted lipidomics

RATIONALE

Hypercholesterolemia is an important risk factor for cardiovascular diseases and death. This study performed pseudo-targeted lipidomics to identify differentially expressed plasma lipids in hypercholesterolemia, to provide a scientific basis for the diagnosis and pathogenesis of hypercholesterolemia.

METHODS

Pseudo-targeted lipidomic analyses of plasma lipids from 20 patients with hypercholesterolemia and 20 normal control subjects were performed using liquid chromatography-mass spectrometry. Differentially expressed lipids were identified by principal component analysis and orthogonal partial least squares discriminant analysis. Receiver operating characteristic curves were used to identify differentially expressed lipids with high diagnostic value. The Kyoto Encyclopedia of Genes and Genomes pathway database was used to identify enriched metabolic pathways.

RESULTS

We identified 13 differentially expressed lipids in hypercholesterolemia using variable importance of projection > 1 and p < 0.05 as threshold parameters. The levels of eight sphingomyelins and cholesterol sulfate were higher and those of three triacylglycerols and lysophosphatidylcholine were reduced in hypercholesterolemia. Seven differentially expressed plasma lipids showed high diagnostic value for hypercholesterolemia. Functional enrichment analyses showed that pathways related to necroptosis, sphingolipid signaling, sphingolipid metabolism, and steroid hormone biosynthesis were enriched.

CONCLUSIONS

This pseudo-targeted lipidomics study demonstrated that multiple sphingomyelins and cholesterol sulfate were differentially expressed in the plasma of patients with hypercholesterolemia. We also identified seven plasma lipids, including six sphingomyelins and cholesterol sulfate, with high diagnostic value.

Traditional Therapeutics and Potential Epidrugs for CVD: Why Not Both?

Cardiovascular disease (CVD) is the leading cause of death worldwide. In addition to the high mortality rate, people suffering from CVD often endure difficulties with physical activities and productivity that significantly affect their quality of life. The high prevalence of debilitating risk factors such as obesity, type 2 diabetes mellitus, smoking, hypertension, and hyperlipidemia only predicts a bleak future. Current traditional CVD interventions offer temporary respite; however, they compound the severe economic strain of health-related expenditures. Furthermore, these therapeutics can be prescribed indefinitely. Recent advances in the field of epigenetics have generated new treatment options by confronting CVD at an epigenetic level. This involves modulating gene expression by altering the organization of our genome rather than altering the DNA sequence itself. Epigenetic changes are heritable, reversible, and influenced by environmental factors such as medications. As CVD is physiologically and pathologically diverse in nature, epigenetic interventions can offer a ray of hope to replace or be combined with traditional therapeutics to provide the prospect of addressing more than just the symptoms of CVD. This review discusses various risk factors contributing to CVD, perspectives of current traditional medications in practice, and a focus on potential epigenetic therapeutics to be used as alternatives.

Lipidomic analysis identified potential predictive biomarkers of statin response in subjects with Familial hypercholesterolemia

Familial hypercholesterolemia (FH) is a disorder of lipid metabolism that causes elevated low-density lipoprotein cholesterol (LDL-c) and increased premature atherosclerosis risk. Statins inhibit endogenous cholesterol biosynthesis, which reduces LDL-c plasma levels and prevent from cardiovascular events. This study aimed to explore the effects of statin treatment on serum lipidomic profile and to identify biomarkers of response in subjects with FH. Seventeen adult FH patients underwent a 6-week washout followed by 4-week treatment with atorvastatin (80 mg/day) or rosuvastatin (40 mg/day). LDL-c response was considered good (40-70 % reduction, n = 9) or poor (3-33 % reduction, n = 8). Serum lipidomic profile was analyzed by ultra-high-performance liquid chromatography combined with electrospray ionization tandem time-of-flight mass spectrometry, and data were analyzed using MetaboAnalyst v5.0. Lipidomic analysis identified 353 lipids grouped into 16 classes. Statin treatment reduced drastically 8 of 13 lipid classes, generating a characteristic lipidomic profile with a significant contribution of phosphatidylinositols (PI) 16:0/18:2, 18:0/18:1 and 18:0/18:2; and triacylglycerols (TAG) 18:2x2/18:3, 18:1/18:2/18:3, 16:1/18:2x2, 16:1/18:2/18:3 and 16:1/18:2/Arachidonic acid (p-adjusted <0.05). Biomarker analysis implemented in MetaboAnalyst subsequently identified PI 16:1/18:0, 16:0/18:2 and 18:0/18:2 as predictors of statin response with and receiver operating characteristic (ROC) areas under the curve of 0.98, 0.94 and 0.91, respectively. In conclusion, statins extensively modulate the overall serum lipid composition of FH individuals and these findings suggest that phosphatidyl-inositol molecules are potential predictive biomarkers of statin response.

Hypercholesterolemic Dysregulation of Calpain in Lymphatic Endothelial Cells Interferes With Regulatory T-Cell Stability and Trafficking

BACKGROUND

Although hypercholesterolemia reportedly counteracts lymphocyte trafficking across lymphatic vessels, the roles of lymphatic endothelial cells (LECs) in the lymphocyte regulations remain unclear. Previous studies showed that calpain-an intracellular modulatory protease-interferes with leukocyte dynamics in the blood microcirculation and is associated with hypercholesterolemic dysfunction in vascular endothelial cells.

METHODS

This study investigated whether the calpain systems in LECs associate with the LEC-lymphocyte interaction under hypercholesterolemia using gene-targeted mice.

RESULTS

Lipidomic analysis in hypercholesterolemic mice showed that several lysophospholipids, including lysophosphatidic acid, accumulated in the lymphatic environment. Lysophosphatidic acid enables the potentiation of calpain systems in cultured LECs, which limits their ability to stabilize regulatory T cells (Treg) without altering Th1/Th2 (T helper type1/2) subsets. This occurs via the proteolytic degradation of MEKK1 (mitogen-activated protein kinase kinase kinase 1) and the subsequent inhibition of TGF (transforming growth factor)-β1 production in LECs. Targeting calpain systems in LECs expanded Tregs in the blood circulation and reduced aortic atherosclerosis in hypercholesterolemic mice, concomitant with the reduction of proinflammatory macrophages in the lesions. Treg expansion in the blood circulation and atheroprotection in calpain-targeted mice was prevented by the administration of TGF-β type-I receptor inhibitor. Moreover, lysophosphatidic acid-induced calpain overactivation potentiated the IL (interleukin)-18/NF-κB (nuclear factor κB)/VCAM1 (vascular cell adhesion molecule 1) axis in LECs, thereby inhibiting lymphocyte mobility on the cells. Indeed, VCAM1 in LECs was upregulated in hypercholesterolemic mice and human cases of coronary artery disease. Neutralization of VCAM1 or targeting LEC calpain systems recovered afferent Treg transportation via lymphatic vessels in mice.

CONCLUSIONS

Calpain systems in LECs have a key role in controlling Treg stability and trafficking under hypercholesterolemia.

Lipidomics-Paving the Road towards Better Insight and Precision Medicine in Rare Metabolic Diseases

Even though the application of Next-Generation Sequencing (NGS) has significantly facilitated the identification of disease-associated mutations, the diagnostic rate of rare diseases is still below 50%. This causes a diagnostic odyssey and prevents specific treatment, as well as genetic counseling for further family planning. Increasing the diagnostic rate and reducing the time to diagnosis in children with unclear disease are crucial for a better patient outcome and improvement of quality of life. In many cases, NGS reveals variants of unknown significance (VUS) that need further investigations. The delineation of novel (lipid) biomarkers is not only crucial to prove the pathogenicity of VUS, but provides surrogate parameters for the monitoring of disease progression and therapeutic interventions. Lipids are essential organic compounds in living organisms, serving as building blocks for cellular membranes, energy storage and signaling molecules. Among other disorders, an imbalance in lipid homeostasis can lead to chronic inflammation, vascular dysfunction and neurodegenerative diseases. Therefore, analyzing lipids in biological samples provides great insight into the underlying functional role of lipids in healthy and disease statuses. The method of choice for lipid analysis and/or huge assemblies of lipids (=lipidome) is mass spectrometry due to its high sensitivity and specificity. Due to the inherent chemical complexity of the lipidome and the consequent challenges associated with analyzing it, progress in the field of lipidomics has lagged behind other omics disciplines. However, compared to the previous decade, the output of publications on lipidomics has increased more than 17-fold within the last decade and has, therefore, become one of the fastest-growing research fields. Combining multiple omics approaches will provide a unique and efficient tool for determining pathogenicity of VUS at the functional level, and thereby identifying rare, as well as novel, genetic disorders by molecular techniques and biochemical analyses.

Treatment of Dyslipidemia through Targeted Therapy of Gut Microbiota

Dyslipidemia is a multifaceted condition with various genetic and environmental factors contributing to its pathogenesis. Further, this condition represents an important risk factor for its related sequalae including cardiovascular diseases (CVD) such as coronary artery disease (CAD) and stroke. Emerging evidence has shown that gut microbiota and their metabolites can worsen or protect against the development of dyslipidemia. Although there are currently numerous treatment modalities available including lifestyle modification and pharmacologic interventions, there has been promising research on dyslipidemia that involves the benefits of modulating gut microbiota in treating alterations in lipid metabolism. In this review, we examine the relationship between gut microbiota and dyslipidemia, the impact of gut microbiota metabolites on the development of dyslipidemia, and the current research on dietary interventions, prebiotics, probiotics, synbiotics and microbiota transplant as therapeutic modalities in prevention of cardiovascular disease. Overall, understanding the mechanisms by which gut microbiota and their metabolites affect dyslipidemia progression will help develop more precise therapeutic targets to optimize lipid metabolism.

Multi-Omics Investigation into Acute Myocardial Infarction: An Integrative Method Revealing Interconnections amongst the Metabolome, Lipidome, Glycome, and Metallome

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. This work aims to investigate the translational potential of a multi-omics study (comprising metabolomics, lipidomics, glycomics, and metallomics) in revealing biomechanistic insights into AMI. Following the N-glycomics and metallomics studies performed by our group previously, untargeted metabolomic and lipidomic profiles were generated and analysed in this work via the use of a simultaneous metabolite/lipid extraction and liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis workflow. The workflow was applied to blood plasma samples from AMI cases (n = 101) and age-matched healthy controls (n = 66). The annotated metabolomic (number of features, n = 27) and lipidomic (n = 48) profiles, along with the glycomic (n = 37) and metallomic (n = 30) profiles of the same set of AMI and healthy samples were integrated and analysed. The integration method used here works by identifying a linear combination of maximally correlated features across the four omics datasets, via utilising both block-partial least squares-discriminant analysis (block-PLS-DA) based on sparse generalised canonical correlation analysis. Based on the multi-omics mapping of biomolecular interconnections, several postulations were derived. These include the potential roles of glycerophospholipids in N-glycan-modulated immunoregulatory effects, as well as the augmentation of the importance of Ca–ATPases in cardiovascular conditions, while also suggesting contributions of phosphatidylethanolamine in their functions. Moreover, it was shown that combining the four omics datasets synergistically enhanced the classifier performance in discriminating between AMI and healthy subjects. Fresh and intriguing insights into AMI, otherwise undetected via single-omics analysis, were revealed in this multi-omics study. Taken together, we provide evidence that a multi-omics strategy may synergistically reinforce and enhance our understanding of diseases.

Identification of molecular mechanisms underlying the therapeutic effects of Xintong granule in coronary artery disease by a network pharmacology and molecular docking approach

Coronary artery disease (CAD) is a cardiovascular disease characterized by atherosclerosis, angiogenesis, thrombogenesis, inflammation, etc. Xintong granule (XTG) is considered a practical therapeutic strategy in China for CAD. Although its therapeutic role in CAD has been reported, the molecular mechanisms of XTG in CAD have not yet been explored. A network pharmacology approach including drug-likeness (DL) evaluation, oral bioavailability (OB) prediction, protein-protein interaction (PPI) network construction and analysis, and Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses was used to predict the active ingredients, potential targets, and molecular mechanisms of XTG associated with the treatment of CAD. Molecular docking analysis was performed to investigate the interactions between the active compounds and the underlying targets. Fifty-one active ingredients of XTG and 294 CAD-related targets were screened for analysis. Gene Ontology enrichment analysis showed that the therapeutic targets of XTG in CAD are mainly involved in blood circulation and vascular regulation. KEGG pathway analysis indicated that XTG intervenes in CAD mainly through the regulation of fluid shear stress and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. Molecular docking analysis showed that each key active ingredient (quercetin, luteolin, kaempferol, stigmasterol, resveratrol, fisetin, gamma-sitosterol, and beta-sitosterol) of XTG can bind to the core targets of CAD (AKT1, JUN, RELA, MAPK8, NFKB1, EDN1, and NOS3). The present study revealed the CAD treatment-related active ingredients, underlying targets, and potential molecular mechanisms of XTG acting by regulating fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, and relaxin signaling pathway.

Lipidomic profiling analysis of human plasma from subjects with hypercholesterolemia to evaluate the intake of yellow yeast rice fermented by Aspergillus terreus DSMK01

Yellow yeast rice (YYR) is a Korean functional food fermented with Aspergillus terreus and contains monacolin K, a cholesterol-lowering ingredient. However, the effects of YYR on lipid metabolism alterations have not been reported until now. In this study, we performed a mass spectrometry-based lipidomic analysis of plasma samples from subjects (31 from the YYR group and 27 from the placebo group) with LDL-C higher than 130 mg dL^-1 to investigate the effects of the intake of YYR. Lipidomic profiling showed that the levels of sphingomyelin (SM) were significantly decreased in the YYR intake group compared with the placebo group. The SM level in the YYR intake group showed a significant association with the ApoB/ApoA1 ratio (p = 0.004, r = 0.503), an indicator of the effect of lipid-lowering therapy. This study suggests that global lipidomic profiling could be used to identify changes in lipid metabolism induced by YYR intake and provide information that these lipid changes are associated with improved hypercholesterolemia.

Clinical lipidomics – A community-driven roadmap to translate research into clinical applications

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Overview of current state of mass spectrometry based lipidomics.

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Highlighting ongoing efforts towards harmonization.

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Invitation to join international community.

Lipid metabolites, beyond triglycerides and cholesterol, have been shown to have vast potential for applications in clinical applications, with substantial societal and economical value. To successfully evolve from the current research-grade methods to assays suitable for routine clinical applications, a harmonization – if not standardization – of these mass spectrometry-based workflows is necessary. Input on clinical needs and technological capabilities must be obtained from all relevant stakeholders, including wet lab scientists, informaticians and data scientists, manufacturers, and medical professionals. In order to build bridges between this diverse group of professionals, the International Lipidomics Society and its Clinical Lipidomics Interest Group were created. This opinion article is intended to provide an overview of international efforts to tackle the issues of workflow harmonization, and to serve as an open invitation for others to join this growing community.

Mouse lipidomics reveals inherent flexibility of a mammalian lipidome

Lipidomics has become an indispensable method for the quantitative assessment of lipid metabolism in basic, clinical, and pharmaceutical research. It allows for the generation of information-dense datasets in a large variety of experimental setups and model organisms. Previous studies, mostly conducted in mice (Mus musculus), have shown a remarkable specificity of the lipid compositions of different cell types, tissues, and organs. However, a systematic analysis of the overall variation of the mouse lipidome is lacking. To fill this gap, in the present study, the effect of diet, sex, and genotype on the lipidomes of mouse tissues, organs, and bodily fluids has been investigated. Baseline quantitative lipidomes consisting of 796 individual lipid molecules belonging to 24 lipid classes are provided for 10 different sample types. Furthermore, the susceptibility of lipidomes to the tested parameters is assessed, providing insights into the organ-specific lipidomic plasticity and flexibility. This dataset provides a valuable resource for basic and pharmaceutical researchers working with murine models and complements existing proteomic and transcriptomic datasets. It will inform experimental design and facilitate interpretation of lipidomic datasets.

Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases

Background

Localized stress and cell death in chronic inflammatory diseases may release tissue-specific lipids into the circulation causing the blood plasma lipidome to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared.

Methods

Plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related vascular disease, including cardiovascular (CVD) and ischemic stroke (IS), and systemic lupus erythematosus (SLE), were screened by a top-down shotgun mass spectrometry-based analysis without liquid chromatographic separation and compared to each other and to age-matched controls. Lipid profiling of 596 lipids was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes were used to distinguish the two chronic inflammatory diseases from each other and from the controls.

Findings

Analysis of the lipidomes enabled separation of the studied chronic inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.94, Specificity: 0.88; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.93) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1; IS vs SLE - Sensitivity: 1, Specificity: 0.82). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls, and partially separated CVD severities, as classified into five clinical groups. Dysregulated lipids are partially but not fully counterbalanced by statin treatment.

Interpretation

Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes.

Funding

Full list of funding sources at the end of the manuscript.

Polygenic burden has broader impact on health, cognition, and socioeconomic outcomes than most rare and high-risk copy number variants

Copy number variants (CNVs) are associated with syndromic and severe neurological and psychiatric disorders (SNPDs), such as intellectual disability, epilepsy, schizophrenia, and bipolar disorder. Although considered high-impact, CNVs are also observed in the general population. This presents a diagnostic challenge in evaluating their clinical significance. To estimate the phenotypic differences between CNV carriers and non-carriers regarding general health and well-being, we compared the impact of SNPD-associated CNVs on health, cognition, and socioeconomic phenotypes to the impact of three genome-wide polygenic risk score (PRS) in two Finnish cohorts (FINRISK, n = 23,053 and NFBC1966, n = 4895). The focus was on CNV carriers and PRS extremes who do not have an SNPD diagnosis. We identified high-risk CNVs (DECIPHER CNVs, risk gene deletions, or large [>1 Mb] CNVs) in 744 study participants (2.66%), 36 (4.8%) of whom had a diagnosed SNPD. In the remaining 708 unaffected carriers, we observed lower educational attainment (EA; OR = 0.77 [95% CI 0.66-0.89]) and lower household income (OR = 0.77 [0.66-0.89]). Income-associated CNVs also lowered household income (OR = 0.50 [0.38-0.66]), and CNVs with medical consequences lowered subjective health (OR = 0.48 [0.32-0.72]). The impact of PRSs was broader. At the lowest extreme of PRS for EA, we observed lower EA (OR = 0.31 [0.26-0.37]), lower-income (OR = 0.66 [0.57-0.77]), lower subjective health (OR = 0.72 [0.61-0.83]), and increased mortality (Cox's HR = 1.55 [1.21-1.98]). PRS for intelligence had a similar impact, whereas PRS for schizophrenia did not affect these traits. We conclude that the majority of working-age individuals carrying high-risk CNVs without SNPD diagnosis have a modest impact on morbidity and mortality, as well as the limited impact on income and educational attainment, compared to individuals at the extreme end of common genetic variation. Our findings highlight that the contribution of traditional high-risk variants such as CNVs should be analyzed in a broader genetic context, rather than evaluated in isolation.

Statin Treatment in Specific Patient Groups: Role for Improved Cardiovascular Risk Markers

Ample evidence supports the use of statin therapy for secondary prevention in patients with a history of atherosclerotic cardiovascular disease (ASCVD), but evidence is wanting in the case of primary prevention, low-risk individuals, and elderly adults 65+. Statins are effective in lowering low-density lipoprotein (LDL), which has long been a target for treatment decisions. We discuss the weakening dependence between cholesterol levels and mortality as a function of age and highlight recent findings on lipoprotein subfractions and other superior markers of ASCVD risk. The efficacy of statins is compared for distinct subsets of patients based on age, diabetes, ASCVD, and coronary artery calcium (CAC) status. Most cardiovascular risk calculators heavily weight age and overestimate one's absolute risk of ASCVD, particularly in very old adults. Improvements in risk assessment enable the identification of specific patient populations that benefit most from statin treatment. Derisking is particularly important for adults over 75, in whom treatment benefits are reduced and adverse musculoskeletal effects are amplified. The CAC score stratifies the benefit effect size obtainable with statins, and forms of coenzyme Q are discussed for improving patient outcomes. Robust risk estimator tools and personalized, evidence-based approaches are needed to optimally reduce cardiovascular events and mortality rates through administration of cholesterol-lowering medications.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

Development of a nomogram that predicts the risk for coronary atherosclerotic heart disease

Studies seldom combine biological, behavioral and psychological factors to estimate coronary atherosclerotic heart disease (CHD) risk. Here, we evaluated the associations between these factors and CHD to develop a predictive nomogram to identify those at high risk of CHD. This case-control study included 4392 participants (1578 CHD cases and 2814 controls) in southeast China. Thirty-three biological, behavioral and psychological variables were evaluated. Following multivariate logistic regression analysis, which revealed eight risk factors associated with CHD, a predictive nomogram was developed based on a final model that included the three non-modifiable (sex, age and family history of CHD) and five modifiable (hypertension, hyperlipidemia, diabetes, recent experience of a major traumatic event, and anxiety) variables. The higher total nomogram score, the greater the CHD risk. Final model accuracy (as estimated from the area under the receiver operating characteristic curve) was 0.726 (95% confidence interval: 0.709-0.747). Validation analysis confirmed the high accuracy of the nomogram. High risk of CHD was associated with several biological, behavioral and psychological factors. We have thus developed an intuitive nomogram that could facilitate development of preliminary prevention strategies for CHD.

Prediction of Residual Risk by Ceramide-Phospholipid Score in Patients With Stable Coronary Heart Disease on Optimal Medical Therapy

Background

Identification of patients with stable coronary heart disease who are at significant residual risk could be helpful for targeted prevention. Our aim was to determine the prognostic value of the recently introduced ceramide‐ and phospholipid‐based risk score, the Cardiovascular Event Risk Test (CERT2), in patients with stable coronary heart disease on optimal medical therapy and to identify biological processes that contribute to the CERT2 score.

Methods and Results

Plasma samples (n=11 222) obtained from the STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) trial were analyzed using a tandem liquid chromatography‐mass spectrometry method. STABILITY was a trial in patients with stable coronary heart disease randomized to the lipoprotein‐associated phospholipase A2 inhibitor darapladib or placebo on optimized medical therapy at baseline, with a median follow‐up of 3.7 years. Hazard ratios per SD for the CERT2 risk score were 1.32 (95% CI, 1.25–1.39) for major adverse cardiovascular event, 1.47 (95% CI, 1.35–1.59) for cardiovascular death, 1.32 (95% CI, 1.16–1.49) for stroke, 1.23 (95% CI, 1.14–1.33) for myocardial infarction, and 1.56 (95% CI, 1.39–1.76) for hospitalization due to heart failure, when adjusted for traditional cardiovascular risk factors. CERT2 showed correlation (P<0.001, r>0.2) with inflammatory markers high‐sensitivity C‐reactive protein, interleukin 6, the heart failure marker N‐terminal pro‐B‐type natriuretic peptide, and low‐density lipoprotein cholesterol. After also adjusting for levels of other prognostic biomarkers, the CERT2 score was still independently related to the risk of cardiovascular death but not to nonfatal events.

Conclusions

The CERT2 risk score can detect residual risk in patients with stable coronary heart disease and is associated with biomarkers indicating inflammation, myocardial necrosis, myocardial dysfunction, renal dysfunction, and dyslipidemia.

REGISTRATION

URL: https://www.clini​caltr​ials.gov. Unique identifier: NCT00799903.

Genetic architecture of human plasma lipidome and its link to cardiovascular disease

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population-Ascertained Hyperlipidemias

Background

We asked whether, after excluding familial hypercholesterolemia, individuals with high low‐density lipoprotein cholesterol (LDL‐C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population‐based hyperlipidemias.

Methods and Results

We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first‐degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias (LDL‐C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta‐analysis of the hyperlipidemic families and the population cohort (high LDL‐C: hazard ratio, 1.74 [95% CI, 1.48–2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09–1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid‐lowering medication. In lipidomic profiling, high LDL‐C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P‐value range 0.038–2.3×10⁻⁵⁶). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population (LDL‐C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts).

Conclusions

Hyperlipidemias with family history conferred similar coronary artery disease risk as population‐based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL‐C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population‐ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.