What can human genetics teach us about the causes of cardiovascular disease?

Molecular Epidemiology of Heart Failure: Translational Challenges and Opportunities

Heart failure (HF) is the end-stage of all heart disease and arguably constitutes the greatest unmet therapeutic need in cardiovascular medicine today. Classic epidemiological studies have established clinical risk factors for HF, but the cause remains poorly understood in many cases. Biochemical analyses of small case-control series and animal models have described a plethora of molecular characteristics of HF, but a single unifying pathogenic theory is lacking. Heart failure appears to result not only from cardiac overload or injury but also from a complex interplay among genetic, neurohormonal, metabolic, inflammatory, and other biochemical factors acting on the heart. Recent development of robust, high-throughput tools in molecular biology provides opportunity for deep molecular characterization of population-representative cohorts and HF cases (molecular epidemiology), including genome sequencing, profiling of myocardial gene expression and chromatin modifications, plasma composition of proteins and metabolites, and microbiomes. The integration of such detailed information holds promise for improving understanding of HF pathophysiology in humans, identification of therapeutic targets, and definition of disease subgroups beyond the current classification based on ejection fraction which may benefit from improved individual tailoring of therapy. Challenges include: 1) the need for large cohorts with deep, uniform phenotyping; 2) access to the relevant tissues, ideally with repeated sampling to capture dynamic processes; and 3) analytical issues related to integration and analysis of complex datasets. International research consortia have formed to address these challenges and combine datasets, and cohorts with up to 1 million participants are being collected. This paper describes the molecular epidemiology of HF and provides an overview of methods and tissue types and examples of published and ongoing efforts to systematically evaluate molecular determinants of HF in human populations.

Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease

Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of Circulation with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.

Ceruloplasmin and atrial fibrillation: evidence of causality from a population-based Mendelian randomization study

OBJECTIVES

Inflammatory diseases and inflammatory markers secreted by the liver, including C-reactive protein (CRP) and ceruloplasmin, have been associated with incident atrial fibrillation (AF). Genetic studies have not supported a causal relationship between CRP and AF, but the relationship between ceruloplasmin and AF has not been studied. The purpose of this Mendelian randomization study was to explore whether genetic polymorphisms in the gene encoding ceruloplasmin are associated with elevated ceruloplasmin levels, and whether such genetic polymorphisms are also associated with the incidence of AF.

DESIGN

Genetic polymorphisms in the ceruloplasmin gene (CP) were genotyped in a population-based cohort study of men from southern Sweden (Malmö Preventive Project; n = 3900). Genetic polymorphisms associated with plasma ceruloplasmin concentration were also investigated for association with incident AF (n = 520) during a mean follow-up of 29 years in the same cohort. Findings were replicated in an independent case-control sample (The Malmö AF cohort; n = 2247 cases, 2208 controls).

RESULTS

A single nucleotide polymorphism (rs11708215, minor allele frequency 0.12) located in the CP gene promoter was strongly associated with increased levels of plasma ceruloplasmin (P = 9 × 10(-10) ) and with AF in both the discovery cohort [hazard ratio 1.24 per risk allele, 95% confidence interval (CI) 1.06-1.44, P = 0.006] and the replication cohort (odds ratio 1.13, 95% CI 1.02-1.26, P = 0.02).

CONCLUSIONS

Our findings indicate a causal role of ceruloplasmin in AF pathophysiology and suggest that ceruloplasmin might be a mediator in a specific inflammatory pathway that causally links inflammatory diseases and incidence of AF.

Mendelian randomization: application to cardiovascular disease

In the absence of an ethical, practical, and economical randomized trial, the epidemiologist is left to explore other methods in efforts to assert causality. An approach based on genotypic variation has the potential to mitigate against some of the problems found within conventional observational studies. Genetic variations associated with risk factors of interest at the population level can be used as proxy measures for these risk factors and to generate estimates of causal effect. The potential and the possible limitations of this approach within the cardiovascular field are presented in this review.

Genetic determinants of LDL, lipoprotein(a), triglyceride-rich lipoproteins and HDL: concordance and discordance with cardiovascular disease risk

PURPOSE OF REVIEW

To evaluate whether new and known genetic determinants of plasma levels of LDL cholesterol, lipoprotein(a), triglyceride-rich lipoproteins, and HDL cholesterol associate with the risk of cardiovascular disease expected from the effect on lipoprotein levels. Concordance or discordance of such genetic determinants with cardiovascular disease risk will either favor or disfavor that these lipoproteins are causally related to cardiovascular disease.

RECENT FINDINGS

Evidence for concordance or discordance with cardiovascular disease risk has come from Mendelian randomization studies, whereas indirect evidence also has emerged from genome-wide and candidate gene association studies. The major limitations of studies of genetic variation and concordance or discordance with cardiovascular disease are pleiotropic effects of the variants studied, and/or lack of sufficient statistical power of the majority of studies to firmly demonstrate a positive association, or even more difficult, to exclude an association.

SUMMARY

New and known genetic determinants of plasma levels of LDL cholesterol, lipoprotein(a), and triglyceride-rich lipoproteins are concordant with both the magnitude and direction of the expected risk of cardiovascular disease, whereas this is unclear for HDL cholesterol. The data are compatible with cardiovascular disease causality for the three former lipoprotein classes, but not for HDL cholesterol.