Enhanced linkage of a locus on chromosome 2 to premature coronary artery disease in the absence of hypercholesterolemia

Clinical utility of polygenic risk scores for coronary artery disease

Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.

Noncoding RNAs in Vascular Diseases

The advent of deep sequencing technologies led to the identification of a considerable amount of noncoding RNA transcripts, which are increasingly recognized for their functions in controlling cardiovascular diseases. MicroRNAs have already been studied for a decade, leading to the identification of several vasculoprotective and detrimental species, which might be considered for therapeutic targeting. Other noncoding RNAs such as circular RNAs, YRNAs, or long noncoding RNAs are currently gaining increasing attention, and first studies provide insights into their functions as mediators or antagonists of vascular diseases in vivo. The present review article will provide an overview of the different types of noncoding RNAs controlling the vasculature and focus on the developing field of long noncoding RNAs.

The long noncoding RNA CHROME regulates cholesterol homeostasis in primate

The human genome encodes thousands of long non-coding RNAs (lncRNAs), the majority of which are poorly conserved and uncharacterized. Here we identify a primate-specific lncRNA (CHROME), elevated in the plasma and atherosclerotic plaques of individuals with coronary artery disease, that regulates cellular and systemic cholesterol homeostasis. LncRNA CHROME expression is influenced by dietary and cellular cholesterol via the sterol-activated liver X receptor transcription factors, which control genes mediating responses to cholesterol overload. Using gain- and loss-of-function approaches, we show that CHROME promotes cholesterol efflux and HDL biogenesis by curbing the actions of a set of functionally related microRNAs that repress genes in those pathways. CHROME knockdown in human hepatocytes and macrophages increases levels of miR-27b, miR-33a, miR-33b and miR-128, thereby reducing expression of their overlapping target gene networks and associated biologic functions. In particular, cells lacking CHROME show reduced expression of ABCA1, which regulates cholesterol efflux and nascent HDL particle formation. Collectively, our findings identify CHROME as a central component of the non-coding RNA circuitry controlling cholesterol homeostasis in humans.

Nonhuman Primates and Translational Research-Cardiovascular Disease

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States. Human epidemiological studies provide challenges for understanding mechanisms that regulate initiation and progression of CVD due to variation in lifestyle, diet, and other environmental factors. Studies describing metabolic and physiologic aspects of CVD, and those investigating genetic and epigenetic mechanisms influencing CVD initiation and progression, have been conducted in multiple Old World nonhuman primate (NHP) species. Major advantages of NHPs as models for understanding CVD are their genetic, metabolic, and physiologic similarities with humans, and the ability to control diet, environment, and breeding. These NHP species are also genetically and phenotypically heterogeneous, providing opportunities to study gene by environment interactions that are not feasible in inbred animal models. Each Old World NHP species included in this review brings unique strengths as models to better understand human CVD. All develop CVD without genetic manipulation providing multiple models to discover genetic variants that influence CVD risk. In addition, as each of these NHP species age, their age-related comorbidities such as dyslipidemia and diabetes are accelerated proportionally 3 to 4 times faster than in humans.In this review, we discuss current CVD-related research in NHPs focusing on selected aspects of CVD for which nonprimate model organism studies have left gaps in our understanding of human disease. We include studies on current knowledge of genetics, epigenetics, calorie restriction, maternal calorie restriction and offspring health, maternal obesity and offspring health, nonalcoholic steatohepatitis and steatosis, Chagas disease, microbiome, stem cells, and prevention of CVD.

Design Considerations for Genetic Linkage and Association Studies

This chapter describes the main issues that genetic epidemiologists usually consider in the design of linkage and association studies. For linkage, we briefly consider the situation of rare highly penetrant alleles showing a disease pattern consistent with Mendelian inheritance investigated through parametric methods in large pedigrees, or with autozygosity mapping in inbred families, and we then turn our focus to the most common design, the affected sibling pair design that is of more relevance for common, complex diseases. Power and sample size calculations are provided as a function of the strength of the genetic effect being investigated. We also discuss the impact of other determinants of statistical power such as disease heterogeneity, pedigree and genotyping errors and the effect of the type and density of genetic markers. For association studies, we consider the popular case-control design for dichotomous phenotypes and we provide power and sample size calculations for one-stage and multistage designs. For candidate genes, guidelines are given on the prioritization of genetic variants, and for genome-wide association studies (GWAS) the issue of choosing an appropriate SNP array is discussed. A warning is issued regarding the danger of designing an underpowered replication study following an initial GWAS. The risk of finding spurious association due to population stratification, cryptic relatedness, and differential bias is underlined.

miRNA Targeting of Oxysterol-Binding Protein-Like 6 Regulates Cholesterol Trafficking and Efflux

OBJECTIVE

Cholesterol homeostasis is fundamental to human health and is, thus, tightly regulated. MicroRNAs exert potent effects on biological pathways, including cholesterol metabolism, by repressing genes with related functions. We reasoned that this mode of pathway regulation could be exploited to identify novel genes involved in cholesterol homeostasis.

APPROACH AND RESULTS

Here, we identify oxysterol-binding protein-like 6 (OSBPL6) as a novel target of 2 miRNA hubs regulating cholesterol homeostasis: miR-33 and miR-27b. Characterization of OSBPL6 revealed that it is transcriptionally regulated in macrophages and hepatocytes by liver X receptor and in response to cholesterol loading and in mice and nonhuman primates by Western diet feeding. OSBPL6 encodes the OSBPL-related protein 6 (ORP6), which contains dual membrane- and endoplasmic reticulum-targeting motifs. Subcellular localization studies showed that ORP6 is associated with the endolysosomal network and endoplasmic reticulum, suggesting a role for ORP6 in cholesterol trafficking between these compartments. Accordingly, knockdown of OSBPL6 results in aberrant clustering of endosomes and promotes the accumulation of free cholesterol in these structures, resulting in reduced cholesterol esterification at the endoplasmic reticulum. Conversely, ORP6 overexpression enhances cholesterol trafficking and efflux in macrophages and hepatocytes. Moreover, we show that hepatic expression of OSBPL6 is positively correlated with plasma levels of high-density lipoprotein cholesterol in a cohort of 200 healthy individuals, whereas its expression is reduced in human atherosclerotic plaques.

CONCLUSIONS

These studies identify ORP6 as a novel regulator of cholesterol trafficking that is part of the miR-33 and miR-27b target gene networks that contribute to the maintenance of cholesterol homeostasis.

Genomic determinants of triglyceride and cholesterol distribution into lipoprotein fractions in the rat

The plasma profile of major lipoprotein classes and its subdivision into particular fractions plays a crucial role in the pathogenesis of atherosclerosis and is a major predictor of coronary artery disease. Our aim was to identify genomic determinants of triglyceride and cholesterol distribution into lipoprotein fractions and lipoprotein particle sizes in the recombinant inbred rat set PXO, in which alleles of two rat models of the metabolic syndrome (SHR and PD inbred strains) segregate together with those from Brown Norway rat strain. Adult male rats of 15 PXO strains (n = 8–13/strain) and two progenitor strains SHR-Lx (n = 13) and BXH2/Cub (n = 18) were subjected to one-week of high-sucrose diet feeding. We performed association analyses of triglyceride (TG) and cholesterol (C) concentrations in 20 lipoprotein fractions and the size of major classes of lipoprotein particles utilizing 704 polymorphic microsatellite markers, the genome-wide significance was validated by 2,000 permutations per trait. Subsequent in silico focusing of the identified quantitative trait loci was completed using a map of over 20,000 single nucleotide polymorphisms. In most of the phenotypes we identified substantial gradient among the strains (e.g. VLDL-TG from 5.6 to 66.7 mg/dl). We have identified 14 loci (encompassing 1 to 65 genes) on rat chromosomes 3, 4, 7, 8, 11 and 12 showing suggestive or significant association to one or more of the studied traits. PXO strains carrying the SHR allele displayed significantly higher values of the linked traits except for LDL-TG and adiposity index. Cholesterol concentrations in large, medium and very small LDL particles were significantly associated to a haplotype block spanning part of a single gene, low density lipoprotein receptor-related protein 1B (Lrp1b). Using genome-wide association we have identified new genetic determinants of triglyceride and cholesterol distribution into lipoprotein fractions in the recombinant inbred panel of rat model strains.

ChIP-seq in steatohepatitis and normal liver tissue identifies candidate disease mechanisms related to progression to cancer

Background

Steatohepatitis occurs in alcoholic liver disease and may progress to liver cirrhosis and hepatocellular carcinoma. Its molecular pathogenesis is to a large degree unknown. Histone modifications play a key role in transcriptional regulations as marks for silencing and activation of gene expression and as marks for functional elements. Many transcription factors (TFs) are crucial for the control of the genes involved in metabolism, and abnormality in their function may lead to disease.

Methods

We performed ChIP-seq of the histone modifications H3K4me1, H3K4me3 and H3K27ac and a candidate transcription factor (USF1) in liver tissue from patients with steatohepatitis and normal livers and correlated results to mRNA-expression and genotypes.

Results

We found several regions that are differentially enriched for histone modifications between disease and normal tissue, and qRT-PCR results indicated that the expression of the tested genes strongly correlated with differential enrichment of histone modifications but is independent of USF1 enrichment. By gene ontology analysis of differentially modified genes we found many disease associated genes, some of which had previously been implicated in the etiology of steatohepatitis. Importantly, the genes associated to the strongest histone peaks in the patient were over-represented in cancer specific pathways suggesting that the tissue was on a path to develop to cancer, a common complication to the disease. We also found several novel SNPs and GWAS catalogue SNPs that are candidates to be functional and therefore needs further study.

Conclusion

In summary we find that analysis of chromatin features in tissue samples provides insight into disease mechanisms.

Design considerations for genetic linkage and association studies

This chapter describes the main issues that genetic epidemiologists usually consider in the design of linkage and association studies. For linkage, we briefly consider the situation of rare, highly penetrant alleles showing a disease pattern consistent with Mendelian inheritance investigated through parametric methods in large pedigrees or with autozygosity mapping in inbred families, and we then turn our focus to the most common design, affected sibling pairs, of more relevance for common, complex diseases. Theoretical and more practical power and sample size calculations are provided as a function of the strength of the genetic effect being investigated. We also discuss the impact of other determinants of statistical power such as disease heterogeneity, pedigree, and genotyping errors, as well as the effect of the type and density of genetic markers. Linkage studies should be as large as possible to have sufficient power in relation to the expected genetic effect size. Segregation analysis, a formal statistical technique to describe the underlying genetic susceptibility, may assist in the estimation of the relevant parameters to apply, for instance. However, segregation analyses estimate the total genetic component rather than a single-locus effect. Locus heterogeneity should be considered when power is estimated and at the analysis stage, i.e. assuming smaller locus effect than the total the genetic component from segregation studies. Disease heterogeneity should be minimised by considering subtypes if they are well defined or by otherwise collecting known sources of heterogeneity and adjusting for them as covariates; the power will depend upon the relationship between the disease subtype and the underlying genotypes. Ultimately, identifying susceptibility alleles of modest effects (e.g. RR≤1.5) requires a number of families that seem unfeasible in a single study. Meta-analysis and data pooling between different research groups can provide a sizeable study, but both approaches require even a higher level of vigilance about locus and disease heterogeneity when data come from different populations. All necessary steps should be taken to minimise pedigree and genotyping errors at the study design stage as they are, for the most part, due to human factors. A two-stage design is more cost-effective than one stage when using short tandem repeats (STRs). However, dense single-nucleotide polymorphism (SNP) arrays offer a more robust alternative, and due to their lower cost per unit, the total cost of studies using SNPs may in the future become comparable to that of studies using STRs in one or two stages. For association studies, we consider the popular case-control design for dichotomous phenotypes, and we provide power and sample size calculations for one-stage and multistage designs. For candidate genes, guidelines are given on the prioritisation of genetic variants, and for genome-wide association studies (GWAS), the issue of choosing an appropriate SNP array is discussed. A warning is issued regarding the danger of designing an underpowered replication study following an initial GWAS. The risk of finding spurious association due to population stratification, cryptic relatedness, and differential bias is underlined. GWAS have a high power to detect common variants of high or moderate effect. For weaker effects (e.g. relative risk<1.2), the power is greatly reduced, particularly for recessive loci. While sample sizes of 10,000 or 20,000 cases are not beyond reach for most common diseases, only meta-analyses and data pooling can allow attaining a study size of this magnitude for many other diseases. It is acknowledged that detecting the effects from rare alleles (i.e. frequency<5%) is not feasible in GWAS, and it is expected that novel methods and technology, such as next-generation resequencing, will fill this gap. At the current stage, the choice of which GWAS SNP array to use does not influence the power in populations of European ancestry. A multistage design reduces the study cost but has less power than the standard one-stage design. If one opts for a multistage design, the power can be improved by jointly analysing the data from different stages for the SNPs they share. The estimates of locus contribution to disease risk from genome-wide scans are often biased, and relying on them might result in an underpowered replication study. Population structure has so far caused less spurious associations than initially feared, thanks to systematic ethnicity matching and application of standard quality control measures. Differential bias could be a more serious threat and must be minimised by strictly controlling all the aspects of DNA acquisition, storage, and processing.

Cosegregation of aortic root atherosclerosis and intermediate lipid phenotypes on chromosomes 2 and 8 in an intercross of C57BL/6 and BALBc/ByJ low-density lipoprotein receptor-/- mice

OBJECTIVE

We sought to identify novel atherosclerosis-modifying loci and their potential functional links in a genome-wide approach using cosegregation analysis of atherosclerosis and related intermediate phenotypes in mice.

METHODS AND RESULTS

We carried out an F2 intercross between atherosclerosis-susceptible C57BL/6 mice and atherosclerosis-resistant BALB/cByJ mice on the low-density lipoprotein receptor(-/-) background to examine the genetic basis for their differences in atherosclerosis susceptibility. Atherosclerotic lesion size and a comprehensive panel of 61 atherosclerosis-related phenotypes, including plasma levels of lipids, cytokines, and chemokines were measured in 376 F2 mice. Quantitative trait locus mapping revealed a novel significant locus (logarithm of odds, 6.18) for atherosclerosis on proximal mouse chromosome (Chr) 2 (Ath39), which was associated with major variations in lesion size (14%). Plasma very-low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, lanosterol, and phytosterol levels cosegregated with atherosclerosis at this locus. Moreover, these lipid traits showed significant correlations with lesion size, suggesting that they share the same underlying genetic factor. We also describe a second male-specific locus on Chr 8 (Ath40) where atherosclerosis and lipids cosegregated.

CONCLUSIONS

Our study revealed new loci for atherosclerosis susceptibility on mouse Chr 2 and 8, which might exert their effects on lesion size via plasma lipid levels.

An evaluation of inflammatory gene polymorphisms in sibships discordant for premature coronary artery disease: the GRACE-IMMUNE study

BACKGROUND

Inflammatory cytokines play a crucial role in coronary artery disease (CAD). We investigated the association between 48 coding and three non-coding single nucleotide polymorphisms (SNPs) from 35 inflammatory genes and the development of CAD, using a large discordant sibship collection (2699 individuals in 891 families).

METHODS

Family-based association tests (FBAT) and conditional logistic regression (CLR) were applied to single SNPs and haplotypes and, in CLR, traditional risk factors of CAD were adjusted for.

RESULTS

An association was observed between CAD and a common three-locus haplotype in the interleukin one (IL-1) cluster with P = 0.006 in all CAD cases, P = 0.01 in myocardial infarction (MI) cases and P = 0.0002 in young onset CAD cases (<50 years). The estimated odds ratio (OR) per copy of this haplotype is 1.21 (95% confidence interval [95CI] = 1.04 - 1.40) for CAD; 1.30 (95CI = 1.09 - 1.56) for MI and 1.50 (95CI = 1.22 - 1.86) for young onset CAD. When sex, smoking, hypertension and hypercholesterolaemia were adjusted for, the haplotype effect remained nominally significant (P = 0.05) in young onset CAD cases, more so (P = 0.002) when hypercholesterolaemia was excluded. As many as 82% of individuals affected by CAD had hypercholesterolaemia compared to only 29% of those unaffected, making the two phenotypes difficult to separate.

CONCLUSION

Despite the multiple hypotheses tested, the robustness of family design to population confoundings and the consistency with previous findings increase the likelihood of true association. Further investigation using larger data sets is needed in order for this to be confirmed. See the related commentary by Keavney: http://www.biomedcentral.com/1741-7015/8/6.

Family based studies and genetic epidemiology: theory and practice

Family based studies have underpinned many successes in uncovering the causes of monogenic and oligogenic diseases. Now research is focussing on the identification and characterisation of genes underlying common diseases and it is widely accepted that these studies will require large population based samples. Population based family study designs have the potential to facilitate the analysis of the effects of both genes and environment. These types of studies integrate the population based approaches of classic epidemiology and the methods enabling the analysis of correlations between relatives sharing both genes and environment. The extent to which such studies are feasible will depend upon population- and disease-specific factors. To review this topic, a symposium was held to present and discuss the costs, requirements and advantages of population based family study designs. This article summarises the features of the meeting held at The University of Sheffield, August 2006.