Discovery and refinement of loci associated with lipid levels

Identification of Genetic Variants Linking Protein C and Lipoprotein Metabolism: The ARIC Study (Atherosclerosis Risk in Communities)

OBJECTIVE

Previous studies have identified common genetic variants in 4 chromosomal regions that together account for 14% to 15% of the variance in circulating levels of protein C. To further characterize the genetic architecture of protein C, we obtained denser coverage at some loci, extended investigation of protein C to low-frequency and rare variants, and searched for new associations in genes known to influence protein C.

APPROACH AND RESULTS

Genetic associations with protein C antigen level were evaluated in ≤10 778 European and 3190 black participants aged 45 to 64 years. Analyses included >26 million autosomal variants available after imputation to the 1000 Genomes reference panel along with additional low-frequency and rare variants directly genotyped using the Illumina ITMAT-Broad-CARe chip and Illumina HumanExome BeadChip. Genome-wide significant associations (P<5×10^-8) were found for common variants in the GCKR, PROC, BAZ1B, and PROCR-EDEM2 regions in whites and PROC and PROCR-EDEM2 regions in blacks, confirming earlier findings. In a novel finding, the low-density lipoprotein cholesterol-lowering allele of rs12740374, located in the CELSR2-PSRC1-SORT1 region, was associated with lower protein C level in both whites and blacks, reaching genome-wide significance in a meta-analysis combining results from both groups (P=1.4×10^-9). To further investigate a possible link between lipid metabolism and protein C level, we conducted Mendelian randomization analyses using 185 lipid-related genetic variants as instrumental variables. The results indicated that triglycerides, and possibly low-density lipoprotein cholesterol, influence protein C levels.

CONCLUSIONS

Discovery of variants influencing circulating protein C levels in the CELSR2-PSRC1-SORT1 region may indicate a novel genetic link between lipoprotein metabolism and hemostasis.

Intersections of post-transcriptional gene regulatory mechanisms with intermediary metabolism

Intermediary metabolism studies have typically concentrated on four major regulatory mechanisms-substrate availability, allosteric enzyme regulation, post-translational enzyme modification, and regulated enzyme synthesis. Although transcriptional control has been a big focus, it is becoming increasingly evident that many post-transcriptional events are deeply embedded within the core regulatory circuits of enzyme synthesis/breakdown that maintain metabolic homeostasis. The prominent post-transcriptional mechanisms affecting intermediary metabolism include alternative pre-mRNA processing, mRNA stability and translation control, and the more recently discovered regulation by noncoding RNAs. In this review, we discuss the latest advances in our understanding of these diverse mechanisms at the cell-, tissue- and organismal-level. We also highlight the dynamics, complexity and non-linear nature of their regulatory roles in metabolic decision making, and deliberate some of the outstanding questions and challenges in this rapidly expanding field.

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes

Background

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits.

Results

We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements “reverse regression” methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10⁻⁸), which has not been reported in previous large-scale GWAS of lipid traits.

Conclusions

The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Jointly determining significance levels of primary and replication studies by controlling the false discovery rate in two-stage genome-wide association studies

In genome-wide association studies, we normally discover associations between genetic variants and diseases/traits in primary studies, and validate the findings in replication studies. We consider the associations identified in both primary and replication studies as true findings. An important question under this two-stage setting is how to determine significance levels in both studies. In traditional methods, significance levels of the primary and replication studies are determined separately. We argue that the separate determination strategy reduces the power in the overall two-stage study. Therefore, we propose a novel method to determine significance levels jointly. Our method is a reanalysis method that needs summary statistics from both studies. We find the most powerful significance levels when controlling the false discovery rate in the two-stage study. To enjoy the power improvement from the joint determination method, we need to select single nucleotide polymorphisms for replication at a less stringent significance level. This is a common practice in studies designed for discovery purpose. We suggest this practice is also suitable in studies with validation purpose in order to identify more true findings. Simulation experiments show that our method can provide more power than traditional methods and that the false discovery rate is well-controlled. Empirical experiments on datasets of five diseases/traits demonstrate that our method can help identify more associations. The R-package is available at: http://bioinformatics.ust.hk/RFdr.html .

Comprehensive genotyping in dyslipidemia: mendelian dyslipidemias caused by rare variants and Mendelian randomization studies using common variants

Dyslipidemias, especially hyper-low-density lipoprotein cholesterolemia and hypertriglyceridemia, are important causal risk factors for coronary artery disease. Comprehensive genotyping using the 'next-generation sequencing' technique has facilitated the investigation of Mendelian dyslipidemias, in addition to Mendelian randomization studies using common genetic variants associated with plasma lipids and coronary artery disease. The beneficial effects of low-density lipoprotein cholesterol-lowering therapies on coronary artery disease have been verified by many randomized controlled trials over the years, and subsequent genetic studies have supported these findings. More recently, Mendelian randomization studies have preceded randomized controlled trials. When the on-target/off-target effects of rare variants and common variants exhibit the same direction, novel drugs targeting molecules identified by investigations of rare Mendelian lipid disorders could be promising. Such a strategy could aid in the search for drug discovery seeds other than those for dyslipidemias.

Association of the SPTLC3 rs364585 polymorphism and serum lipid profiles in two Chinese ethnic groups

BACKGROUND

Little is known about the association of the single nucleotide polymorphism (SNP) of rs364585 near serine palmitoyl-transferase long-chain base subunit 3 gene (SPTLC3) and serum lipid profiles. The present study was detected the association of the SPTLC3 rs364585 SNP and several environmental factors with serum lipid profiles in the Han and Jing populations.

METHODS

Genotyping of the SPTLC3 rs364585 SNP was performed in 824 unrelated individuals of Han and 783 participants of Jing by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing.

RESULTS

There was no significant difference in either genotypic or allelic frequencies between Han and Jing, or between males and females of the both ethnic groups. The levels of serum low-density lipoprotein cholesterol (LDL-C) and the ratio of apolipoprotein (Apo) A1 to ApoB in Han; and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and LDL-C in Jing were different between the A allele carriers and the A allele non-carriers (P < 0.05-0.001). Subgroup analysis according to sex showed that the levels of LDL-C in Han males; TC and LDL-C in Jing males; and HDL-C and LDL-C in Jing females were different between the A allele carriers and the A allele non-carriers (P < 0.05-0.001), the A allele carriers had higher LDL-C and TC levels, and lower HDL-C levels than the A allele non-carriers. Serum lipid traits were also associated with several environmental factors in the Han and Jing populations, or in males and females of the both ethnic groups.

CONCLUSIONS

The present study demonstrates the association between the SPTLC3 rs364585 SNP and serum TC, HDL-C and LDL-C levels in our study populations. These associations might have ethnic- and/or sex-specificity.

TRIAL REGISTRATION

Retrospectively registered.

DNA Methylation and High-Density Lipoprotein Functionality-Brief Report: The REGICOR Study (Registre Gironi del Cor)

OBJECTIVE

The function of high-density lipoproteins (HDLs) may better reflect their atheroprotective role, compared with HDL-cholesterol levels. The association between DNA methylation and HDL function has not yet been established.

APPROACH AND RESULTS

We designed an epigenome-wide association study including 645 individuals from the REGICOR study (Registre Gironi del Cor). We determined DNA methylation from peripheral blood cells using the HumanMethylation450 array. We analyzed HDL functionality by determining HDL cholesterol efflux capacity and HDL inflammatory index. We discovered 3 methylation sites located in HOXA3, PEX5, and PER3 related to cholesterol efflux capacity and 1 located in GABRR1 related to HDL inflammatory index. Using a candidate gene approach, we also found 2 methylation sites located in CMIP related to cholesterol efflux capacity.

CONCLUSIONS

We identified 6 potential loci associated with HDL functionality in HOXA3, PEX5, PER3, CMIP, and GABRR1. Additional studies are warranted to validate these findings in other populations.

Genome-Wide Association Study Reveals Four Loci for Lipid Ratios in the Korean Population and the Constitutional Subgroup

Circulating lipid ratios are considered predictors of cardiovascular risks and metabolic syndrome, which cause coronary heart diseases. One constitutional type of Korean medicine prone to weight accumulation, the Tae-Eum type, predisposes the consumers to metabolic syndrome, hypertension, diabetes mellitus, etc. Here, we aimed to identify genetic variants for lipid ratios using a genome-wide association study (GWAS) and followed replication analysis in Koreans and constitutional subgroups. GWASs in 5,292 individuals of the Korean Genome and Epidemiology Study and replication analyses in 2,567 subjects of the Korea medicine Data Center were performed to identify genetic variants associated with triglyceride (TG) to HDL cholesterol (HDLC), LDL cholesterol (LDLC) to HDLC, and non-HDLC to HDLC ratios. For subgroup analysis, a computer-based constitution analysis tool was used to categorize the constitutional types of the subjects. In the discovery stage, seven variants in four loci, three variants in three loci, and two variants in one locus were associated with the ratios of log-transformed TG:HDLC (log[TG]:HDLC), LDLC:HDLC, and non-HDLC:HDLC, respectively. The associations of the GWAS variants with lipid ratios were replicated in the validation stage: for the log[TG]:HDLC ratio, rs6589566 near APOA5 and rs4244457 and rs6586891 near LPL; for the LDLC:HDLC ratio, rs4420638 near APOC1 and rs17445774 near C2orf47; and for the non-HDLC:HDLC ratio, rs6589566 near APOA5. Five of these six variants are known to be associated with TG, LDLC, and/or HDLC, but rs17445774 was newly identified to be involved in lipid level changes in this study. Constitutional subgroup analysis revealed effects of variants associated with log[TG]:HDLC and non-HDLC:HDLC ratios in both the Tae-Eum and non-Tae-Eum types, whereas the effect of the LDLC:HDLC ratio-associated variants remained only in the Tae-Eum type. In conclusion, we identified three log[TG]:HDLC ratio-associated variants, two LDLC:HDLC ratio-associated variants, and one non-HDLC:HDLC-associated variant in Koreans and the constitutional subgroups.

Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance

Insulin resistance is a key mediator of obesity-related cardiometabolic disease, yet the mechanisms underlying this link remain obscure. Using an integrative genomic approach, we identify 53 genomic regions associated with insulin resistance phenotypes (higher fasting insulin levels adjusted for BMI, lower HDL cholesterol levels and higher triglyceride levels) and provide evidence that their link with higher cardiometabolic risk is underpinned by an association with lower adipose mass in peripheral compartments. Using these 53 loci, we show a polygenic contribution to familial partial lipodystrophy type 1, a severe form of insulin resistance, and highlight shared molecular mechanisms in common/mild and rare/severe insulin resistance. Population-level genetic analyses combined with experiments in cellular models implicate CCDC92, DNAH10 and L3MBTL3 as previously unrecognized molecules influencing adipocyte differentiation. Our findings support the notion that limited storage capacity of peripheral adipose tissue is an important etiological component in insulin-resistant cardiometabolic disease and highlight genes and mechanisms underpinning this link.

Spontaneously Hypertensive Rat Chromosome 2 with Mutant Connexin 50 Triggers Divergent Effects on Metabolic Syndrome Components

Metabolic syndrome is a frequent condition with multifactorial aetiology. Previous studies indicated the presence of genetic determinants of metabolic syndrome components on rat chromosome 2 (RNO2) and syntenic regions of the human genome. Our aim was to further explore these findings using novel rat models. We derived the BN-Dca and BN-Lx.Dca congenic strains by introgression of a limited RNO2 region from a spontaneously hypertensive rat strain carrying a mutation in the Gja8 gene (SHR-Dca, dominant cataract) into the genomic background of Brown Norway strain and congenic strain BN-Lx, respectively. We compared morphometric, metabolic and cytokine profiles of adult male BN-Lx, BN-Dca and BN-Lx.Dca rats. We performed in silico comparison of the DNA sequences throughout RNO2 differential segments captured in the new congenic strains. Both BN-Dca and BN-Lx.Dca showed lower total triacylglycerols and cholesterol concentrations compared to BN-Lx. Fasting insulin in BN-Dca was higher than in BN-Lx.Dca and BN-Lx. Concentrations of several proinflammatory cytokines were elevated in the BN-Dca strain, including IL-1α, IL-1β, IFN-γ and MCP-1. In silico analyses revealed over 740 DNA variants between BN-Lx and SHR genomes within the differential segment of the congenic strains. We derived new congenic models that prove that a limited genomic region of SHR-Dca RNO2 significantly affects lipid levels and insulin sensitivity in a divergent fashion.

Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

BACKGROUND

The link between DNA methylation, obesity, and adiposity-related diseases in the general population remains uncertain.

METHODS AND FINDINGS

We conducted an association study of body mass index (BMI) and differential methylation for over 400,000 CpGs assayed by microarray in whole-blood-derived DNA from 3,743 participants in the Framingham Heart Study and the Lothian Birth Cohorts, with independent replication in three external cohorts of 4,055 participants. We examined variations in whole blood gene expression and conducted Mendelian randomization analyses to investigate the functional and clinical relevance of the findings. We identified novel and previously reported BMI-related differential methylation at 83 CpGs that replicated across cohorts; BMI-related differential methylation was associated with concurrent changes in the expression of genes in lipid metabolism pathways. Genetic instrumental variable analysis of alterations in methylation at one of the 83 replicated CpGs, cg11024682 (intronic to sterol regulatory element binding transcription factor 1 [SREBF1]), demonstrated links to BMI, adiposity-related traits, and coronary artery disease. Independent genetic instruments for expression of SREBF1 supported the findings linking methylation to adiposity and cardiometabolic disease. Methylation at a substantial proportion (16 of 83) of the identified loci was found to be secondary to differences in BMI. However, the cross-sectional nature of the data limits definitive causal determination.

CONCLUSIONS

We present robust associations of BMI with differential DNA methylation at numerous loci in blood cells. BMI-related DNA methylation and gene expression provide mechanistic insights into the relationship between DNA methylation, obesity, and adiposity-related diseases.

Controlling the Rate of GWAS False Discoveries

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study.

Mendelian Randomization

Confounding and reverse causality have prevented us from drawing meaningful clinical interpretation even in well-powered observational studies. Confounding may be attributed to our inability to randomize the exposure variable in observational studies. Mendelian randomization (MR) is one approach to overcome confounding. It utilizes one or more genetic polymorphisms as a proxy for the exposure variable of interest. Polymorphisms are randomly distributed in a population, they are static throughout an individual's lifetime, and may thus help in inferring directionality in exposure-outcome associations. Genome-wide association studies (GWAS) or meta-analyses of GWAS are characterized by large sample sizes and the availability of many single nucleotide polymorphisms (SNPs), making GWAS-based MR an attractive approach. GWAS-based MR comes with specific challenges, including multiple causality. Despite shortcomings, it still remains one of the most powerful techniques for inferring causality.With MR still an evolving concept with complex statistical challenges, the literature is relatively scarce in terms of providing working examples incorporating real datasets. In this chapter, we provide a step-by-step guide for causal inference based on the principles of MR with a real dataset using both individual and summary data from unrelated individuals. We suggest best possible practices and give recommendations based on the current literature.

The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies

Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases 'type 2 diabetes, coronary artery disease, hypertension' and/or for the risk factors 'blood pressure, obesity, plasma lipid levels, insulin and glucose related traits'. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and 'depression' or 'depressive disorder' or 'depressive symptoms' or 'bipolar disorder' or 'lithium treatment response in bipolar disorder', or 'serotonin reuptake inhibitors treatment response in major depression'. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin or dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.

A multitrait GWAS sheds light on insulin resistance

A genome-wide study of fasting insulin, HDL cholesterol and triglycerides, designed to depict insulin resistance, identified 53 independent loci associated with a limited capacity to store fat in a healthy way. The increased power of this multitrait approach provides insights into an otherwise difficult-to-grasp phenotype.

Phenotypic Characterization of Genetically Lowered Human Lipoprotein(a) Levels

BACKGROUND

Genomic analyses have suggested that the LPA gene and its associated plasma biomarker, lipoprotein(a) (Lp[a]), represent a causal risk factor for coronary heart disease (CHD). As such, lowering Lp(a) levels has emerged as a therapeutic strategy. Beyond target identification, human genetics may contribute to the development of new therapies by defining the full spectrum of beneficial and adverse consequences and by developing a dose-response curve of target perturbation.

OBJECTIVES

The goal of this study was to establish the full phenotypic impact of LPA gene variation and to estimate a dose-response curve between genetically altered plasma Lp(a) and risk for CHD.

METHODS

We leveraged genetic variants at the LPA gene from 3 data sources: individual-level data from 112,338 participants in the U.K. Biobank; summary association results from large-scale genome-wide association studies; and LPA gene sequencing results from case subjects with CHD and control subjects free of CHD.

RESULTS

One SD genetically lowered Lp(a) level was associated with a 29% lower risk of CHD (odds ratio [OR]: 0.71; 95% confidence interval [CI]: 0.69 to 0.73), a 31% lower risk of peripheral vascular disease (OR: 0.69; 95% CI: 0.59 to 0.80), a 13% lower risk of stroke (OR: 0.87; 95% CI: 0.79 to 0.96), a 17% lower risk of heart failure (OR: 0.83; 95% CI: 0.73 to 0.94), and a 37% lower risk of aortic stenosis (OR: 0.63; 95% CI: 0.47 to 0.83). We observed no association with 31 other disorders, including type 2 diabetes and cancer. Variants that led to gain of LPA gene function increased the risk for CHD, whereas those that led to loss of gene function reduced the CHD risk.

CONCLUSIONS

Beyond CHD, genetically lowered Lp(a) levels are associated with a lower risk of peripheral vascular disease, stroke, heart failure, and aortic stenosis. As such, pharmacological lowering of plasma Lp(a) may influence a range of atherosclerosis-related diseases.

Liver Enzymes and Risk of Ischemic Heart Disease and Type 2 Diabetes Mellitus: A Mendelian Randomization Study

We used Mendelian randomization to estimate the causal effects of the liver enzymes, alanine aminotransferase (ALT), alkaline phosphatase (ALP) and gamma glutamyltransferase (GGT), on diabetes and cardiovascular disease, using genetic variants predicting these liver enzymes at genome wide significance applied to extensively genotyped case-control studies of diabetes (DIAGRAM) and coronary artery disease (CAD)/myocardial infarction (MI) (CARDIoGRAMplusC4D 1000 Genomes). Genetically higher ALT was associated with higher risk of diabetes, odds ratio (OR) 2.99 per 100% change in concentration (95% confidence interval (CI) 1.62 to 5.52) but ALP OR 0.92 (95% CI 0.71 to 1.19) and GGT OR 0.88 (95% CI 0.75 to 1.04) were not. Genetically predicted ALT, ALP and GGT were not clearly associated with CAD/MI (ALT OR 0.74, 95% CI 0.54 to 1.01, ALP OR 0.86, 95% CI 0.64 to 1.16 and GGT OR 1.08, 95% CI 0.97 to 1.19). We confirm observations of ALT increasing the risk of diabetes, but cannot exclude the possibility that higher ALT may protect against CAD/MI. We also cannot exclude the possibility that GGT increases the risk of CAD/MI and reduces the risk of diabetes. Informative explanations for these potentially contradictory associations should be sought.

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies.

Identification of the Functional Variant(s) that Explain the Low-Density Lipoprotein Receptor (LDLR) GWAS SNP rs6511720 Association with Lower LDL-C and Risk of CHD

Background

The Low-Density Lipoprotein Receptor (LDLR) SNP rs6511720 (G>T), located in intron-1 of the gene, has been identified in genome-wide association studies (GWAS) as being associated with lower plasma levels of LDL-C and a lower risk of coronary heart disease (CHD). Whether or not rs6511720 is itself functional or a marker for a functional variant elsewhere in the gene is not known.

Methods

The association of LDLR SNP rs6511720 with incidence of CHD and levels of LDL-C was determined by reference to CARDIoGRAM, C4D and Global lipids genetics consortium (GLGC) data. SNP annotation databases were used to identify possible SNP function and prioritization. Luciferase reporter assays in the liver cell line Huh7 were used to measure the effect of variant genotype on gene expression. Electrophoretic Mobility Shift Assays (EMSAs) were used to identify the Transcription Factors (TFs) involved in gene expression regulation.

Results

The phenotype-genotype analysis showed that the rs6511720 minor allele is associated with lower level of LDL-C [beta = -0.2209, p = 3.85 x10^-262], and lower risk of CHD [log (OR) = 0.1155, p = 1.04 x10^-7]. Rs6511720 is in complete linkage. Rs6511720 is in complete linkage disequilibrium (LD) with three intron-1 SNPs (rs141787760, rs60173709, rs57217136). Luciferase reporter assays in Huh7 cells showed that the rare alleles of both rs6511720 and rs57217136 caused a significant increase in LDLR expression compared to the common alleles (+29% and +24%, respectively). Multiplex Competitor-EMSAs (MC-EMSA) identified that the transcription factor serum response element (SRE) binds to rs6511720, while retinoic acid receptor (RAR) and signal transducer and activator of transcription 1 (STAT1) bind to rs57217136.

Conclusion

Both LDLR rs6511720 and rs57217136 are functional variants. Both these minor alleles create enhancer-binding protein sites for TFs and may contribute to increased LDLR expression, which is consequently associated with reduced LDL-C levels and 12% lower CHD risk.

Genetically decreased vitamin D and risk of Alzheimer disease

OBJECTIVE

To test whether genetically decreased vitamin D levels are associated with Alzheimer disease (AD) using mendelian randomization (MR), a method that minimizes bias due to confounding or reverse causation.

METHODS

We selected single nucleotide polymorphisms (SNPs) that are strongly associated with 25-hydroxyvitamin D (25OHD) levels (p < 5 × 10-8) from the Study of Underlying Genetic Determinants of Vitamin D and Highly Related Traits (SUNLIGHT) Consortium (N = 33,996) to act as instrumental variables for the MR study. We measured the effect of each of these SNPs on 25OHD levels in the Canadian Multicentre Osteoporosis Study (CaMos; N = 2,347) and obtained the corresponding effect estimates for each SNP on AD risk from the International Genomics of Alzheimer's Project (N = 17,008 AD cases and 37,154 controls). To produce MR estimates, we weighted the effect of each SNP on AD by its effect on 25OHD and meta-analyzed these estimates using a fixed-effects model to provide a summary effect estimate.

RESULTS

The SUNLIGHT Consortium identified 4 SNPs to be genome-wide significant for 25OHD, which described 2.44% of the variance in 25OHD in CaMos. All 4 SNPs map to genes within the vitamin D metabolic pathway. MR analyses demonstrated that a 1-SD decrease in natural log-transformed 25OHD increased AD risk by 25% (odds ratio 1.25, 95% confidence interval 1.03-1.51, p = 0.021). After sensitivity analysis in which we removed SNPs possibly influenced by pleiotropy and population stratification, the results were largely unchanged.

CONCLUSIONS

Our results provide evidence supporting 25OHD as a causal risk factor for AD. These findings provide further rationale to understand the effect of vitamin D supplementation on cognition and AD risk in randomized controlled trials.

Mendelian Randomization and Type 2 Diabetes

Type 2 diabetes (T2DM) is a common, complex disease that poses a substantial burden on individual and population health, but we have relatively limited understanding of its underlying pathophysiology. Observational studies have highlighted large numbers of risk factors for T2DM, some of which are modifiable through behavioural or pharmacological intervention. Determining which of these risk factors plays a causal role in the development of T2DM has been a challenge, but Mendelian randomisation (MR) studies are harnessing genetic data in population studies to offer new insights. Using evolving analytical methods, MR studies continue to address questions of causality related to T2DM, including exploring the roles of adiposity, blood lipids and inflammation. The causal roles of a number of important modifiable risk factors have been confirmed by MR studies, while the relevance of others has been called into question. As more MR studies are conducted, methods are developed and refined in order to make the most efficient and reliable use of available genetic and phenotypic data. In this review, the design and findings of some important MR studies related to T2DM are explored and their relevance for translation to clinical practice considered.

Birth weight and risk of ischemic heart disease: A Mendelian randomization study

Low birth weight is a risk factor for cardiovascular disease. However, the association could be confounded by many factors. We used Mendelian randomization to clarify the role of birth weight in ischemic heart disease (IHD) and lipids. We used all 7 single nucleotide polymorphisms (SNPs) independently contributing to birth weight at genome wide significance (p < 5 × 10⁻⁸) in separate sample instrumental variable analysis to estimate the effect of birth weight on IHD using the CARDIoGRAMplusC4D 1000 Genomes based GWAS case (n = 60,801)-control (n = 123,504) study and on lipids using GLGC (n = 188,577). Higher genetically predicted birth weight was associated with lower risk of IHD (odds ratio (OR) 0.96 per 100 grams, 95% confidence interval (CI) 0.93 to 0.99), but the association was not robust to sensitivity analyses excluding SNPs related to height or use of weighted median methods. Genetically predicted birth weight was not associated with low density lipoprotein cholesterol or triglycerides, but was associated with lower high density lipoprotein cholesterol (−0.014 standard deviation, 95% CI −0.027 to −0.0005) and the association was more robust to the sensitivity analyses. Our study does not show strong evidence for an effect of birth weight on IHD and lipids.

Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism

Autism spectrum disorder (ASD) involves substantial genetic contributions. These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood. Here, through post-mortem genome-wide transcriptome analysis of the largest cohort of samples analysed so far, to our knowledge, we interrogate the noncoding transcriptome, alternative splicing, and upstream molecular regulators to broaden our understanding of molecular convergence in ASD. Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes. Our data suggest that SOX5, a transcription factor involved in neuron fate specification, contributes to this reduction in regional differences. We further demonstrate that a genetically defined subtype of ASD, chromosome 15q11.2-13.1 duplication syndrome (dup15q), shares the core transcriptomic signature observed in idiopathic ASD. Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression. Our findings illustrate how diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.

Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10^-8; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.

Peripheral Blood Transcriptomic Signatures of Fasting Glucose and Insulin Concentrations

Genome-wide association studies (GWAS) have successfully identified genetic loci associated with glycemic traits. However, characterizing the functional significance of these loci has proven challenging. We sought to gain insights into the regulation of fasting insulin and fasting glucose through the use of gene expression microarray data from peripheral blood samples of participants without diabetes in the Framingham Heart Study (FHS) (n = 5,056), the Rotterdam Study (RS) (n = 723), and the InCHIANTI Study (Invecchiare in Chianti) (n = 595). Using a false discovery rate q <0.05, we identified three transcripts associated with fasting glucose and 433 transcripts associated with fasting insulin levels after adjusting for age, sex, technical covariates, and complete blood cell counts. Among the findings, circulating IGF2BP2 transcript levels were positively associated with fasting insulin in both the FHS and RS. Using 1000 Genomes-imputed genotype data, we identified 47,587 cis-expression quantitative trait loci (eQTL) and 6,695 trans-eQTL associated with the 433 significant insulin-associated transcripts. Of note, we identified a trans-eQTL (rs592423), where the A allele was associated with higher IGF2BP2 levels and with fasting insulin in an independent genetic meta-analysis comprised of 50,823 individuals. We conclude that integration of genomic and transcriptomic data implicate circulating IGF2BP2 mRNA levels associated with glucose and insulin homeostasis.

Variation in PCSK9 and HMGCR and Risk of Cardiovascular Disease and Diabetes

BACKGROUND

Pharmacologic inhibitors of proprotein convertase subtilisin-kexin type 9 (PCSK9) are being evaluated in clinical trials for the treatment of cardiovascular disease. The effect of lowering low-density lipoprotein (LDL) cholesterol levels by inhibiting PCSK9 on the risk of cardiovascular events or diabetes is unknown.

METHODS

We used genetic scores consisting of independently inherited variants in the genes encoding PCSK9 and 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR; the target of statins) as instruments to randomly assign 112,772 participants from 14 studies, with 14,120 cardiovascular events and 10,635 cases of diabetes, to groups according to the number of LDL cholesterol-lowering alleles that they had inherited. We compared the effects of lower LDL cholesterol levels that were mediated by variants in PCSK9, HMGCR, or both on the risk of cardiovascular events and the risk of diabetes.

RESULTS

Variants in PCSK9 and HMGCR were associated with nearly identical protective effects on the risk of cardiovascular events per decrease of 10 mg per deciliter (0.26 mmol per liter) in the LDL cholesterol level: odds ratio for cardiovascular events, 0.81 (95% confidence interval [CI], 0.74 to 0.89) for PCSK9 and 0.81 (95% CI, 0.72 to 0.90) for HMGCR. Variants in these two genes were also associated with very similar effects on the risk of diabetes: odds ratio for each 10 mg per deciliter decrease in LDL cholesterol, 1.11 (95% CI, 1.04 to 1.19) for PCSK9 and 1.13 (95% CI, 1.06 to 1.20) for HMGCR. The increased risk of diabetes was limited to persons with impaired fasting glucose levels for both scores and was lower in magnitude than the protective effect against cardiovascular events. When present together, PCSK9 and HMGCR variants had additive effects on the risk of both cardiovascular events and diabetes.

CONCLUSIONS

In this study, variants in PCSK9 had approximately the same effect as variants in HMGCR on the risk of cardiovascular events and diabetes per unit decrease in the LDL cholesterol level. The effects of these variants were independent and additive. (Funded by the Medical Research Council and the National Heart, Lung, and Blood Institute.).

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits.

Increasing insulin resistance accentuates the effect of triglyceride-associated loci on serum triglycerides during 5 years

Blood concentrations of triglycerides are influenced by genetic factors as well as a number of environmental factors, including adiposity and glucose homeostasis. The aim was to investigate the association between a serum triglyceride weighted genetic risk score (wGRS) and changes in fasting serum triglyceride level over 5 years and to test whether the effect of the wGRS was modified by 5 year changes of adiposity, insulin resistance, and lifestyle factors. A total of 3,474 nondiabetic individuals from the Danish Inter99 cohort participated in both the baseline and 5 year follow-up physical examinations and had information on the wGRS comprising 39 genetic variants. In a linear regression model adjusted for age, sex, and baseline serum triglyceride, the wGRS was associated with increased serum triglyceride levels over 5 years [per allele effect = 1.3% (1.0-1.6%); P = 1.0 × 10-17]. This triglyceride-increasing effect of the wGRS interacted with changes in insulin resistance (Pinteraction = 1.5 × 10-6). This interaction indicated that the effect of the wGRS was stronger in individuals who became more insulin resistant over 5 years. In conclusion, our findings suggest that increased genetic risk load is associated with a larger increase in fasting serum triglyceride levels in nondiabetic individuals during 5 years of follow-up. This effect of the wGRS is accentuated by increasing insulin resistance.

Association between PNPLA3 (rs738409), LYPLAL1 (rs12137855), PPP1R3B (rs4240624), GCKR (rs780094), and elevated transaminase levels in overweight/obese Mexican adults

There is scarce information about the link between specific single-nucleotide polymorphisms (SNPs) and risk of liver disease among Latinos, despite the disproportionate burden of disease among this population. Our aim was to investigate nine SNPs in or near the following genes: PNPLA3, LYPLAL1, PPP1R3B, GCKR, NCAN, IRS1, PPARG, and ADIPOR2 and examine their association with persistently elevated alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels in Mexican adults. Data and samples were collected from 741 participants in the Mexican Health Worker Cohort Study, in Cuernavaca, Mexico. We identified 207 cases who had persistently elevated levels of ALT or AST (≥40 U/L) and 534 controls with at least two consecutive normal ALT or AST results in a 6 month period, during 2004-2006 and 2011-2013. TaqMan assays were used to genotype the SNPs. The risk allele of PNPLA3 rs738409 was found to be associated with persistently elevated levels of ALT or AST, adjusting for age, sex, BMI, type 2 diabetes, and ancestry: (OR 2.28, 95 % CI 1.13, 4.58). A significant association was found between the LYPLAL1, PPP1R3B, and GCKR risk alleles and elevated ALT or AST levels among overweight/obese adults. These results suggest that among Mexicans, the PNPLA3 (rs738409), LYPLAL1 (rs12137855), PPP1R3B (rs4240624), and GCKR (rs780094) polymorphisms may be associated with a greater risk of chronic liver disease among overweight adults. This study is the first to examine these nine SNPs in a sample of adults in Mexico.

Truths and controversies concerning the role of miRNAs in atherosclerosis and lipid metabolism

PURPOSE OF REVIEW

Better tools are sorely needed for both the prevention and treatment of cardiovascular diseases, which account for more than one-third of the deaths in Western countries. MicroRNAs typically regulate the expression of several mRNAs involved in the same biological process. Therapeutic manipulation of miRNAs could restore the expression of multiple players within the same physiologic pathway, and ideally offer better curative outcomes than conventional approaches that target only one single player within the pathway. This review summarizes available studies on the prospective value of targeting miRNAs to prevent dyslipidemia and atherogenesis.

RECENT FINDINGS

Silencing the expression of miRNAs that target key genes involved in lipoprotein metabolism in vivo with antisense oligonucleotides results in the expected de-repression of target mRNAs in liver and atherosclerotic plaques. However, the consequences of long-term antimiRNA treatment on both circulating lipoproteins and athero-protection are yet to be established.

SUMMARY

A number of studies have demonstrated the efficacy of miRNA mimics and inhibitors as novel therapeutic tools for treating dyslipidemia and cardiovascular diseases. Nevertheless, concerns over unanticipated side-effects related to de-repression of additional targets should not be overlooked for miRNA-based therapies.

Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

BACKGROUND

In addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.

METHODS AND RESULTS

We performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p<1×10-4 from the 16 769 statin-treated participants in the first analysis stage were followed up in an independent group of 10 951 statin-treated individuals, providing a total sample size of 27 720 individuals. The only associations of genome-wide significance (p<5×10-8) were between minor alleles at the CETP locus and greater HDL-C response to statin treatment.

CONCLUSIONS

Based on results from this study that included a relatively large sample size, we suggest that CETP may be the only detectable locus with common genetic variants that influence HDL-C response to statins substantially in individuals of European descent. Although CETP is known to be associated with HDL-C, we provide evidence that this pharmacogenetic effect is independent of its association with baseline HDL-C levels.

Homocysteine-reducing B vitamins and ischemic heart disease: a separate-sample Mendelian randomization analysis

BACKGROUND/OBJECTIVES

Observationally, homocysteine is positively associated with ischemic heart disease (IHD) and unhealthy lipids; folate and vitamin B12, which reduce homocysteine, are associated with lower IHD risk and healthy lipids. Randomized controlled trials have shown no benefits of folate and vitamin B12 for IHD. To clarify the role of these potential targets of intervention in IHD we assessed how genetically determined homocysteine, folate and vitamin-B12-affected IHD and lipids.

SUBJECTS/METHODS

Separate-sample instrumental variable analysis with genetic instruments, that is, Mendelian randomization, was used to obtain unconfounded estimates (based on strongly related single-nucleotide polymorphisms (SNPs)) using CARDIoGRAMplusC4D, a large coronary artery disease/myocardial infarction (CAD/MI) case (n=64 374)-control (n=130 681) study with extensive genotyping, and the Global Lipids Genetics Consortium Results (n=196 475).

RESULTS

Homocysteine was unrelated to CAD/MI (odds ratio (OR) 1.07 per log-transformed s.d., 95% confidence interval (CI) 0.96 to 1.19) based on 14 SNPs, as was folate (OR 1.18 per s.d., 95% CI 0.80 to 1.75) based on rs153734, and vitamin B12 (OR 0.98 per log-transformed s.d., 95% CI 0.85 to 1.14) based on rs602662, rs9473555, rs526934 and rs11254363. Homocysteine and folate were not clearly associated with lipids, vitamin B12 was associated with higher inverse normal transformed low-density lipoprotein cholesterol (0.07, 95% CI 0.02 to 0.12) and triglycerides (0.05, 95% CI 0.004 to 0.09).

CONCLUSIONS

Our findings do not corroborate the observed positive association of homocysteine or negative associations of folate and vitamin B12 with CAD/MI. Vitamin B12 might be associated with an unfavorable lipid profile.

Meta-Analysis of Genome-Wide Association Studies for Abdominal Aortic Aneurysm Identifies Four New Disease-Specific Risk Loci

Supplemental Digital Content is available in the text.

Rationale:

Abdominal aortic aneurysm (AAA) is a complex disease with both genetic and environmental risk factors. Together, 6 previously identified risk loci only explain a small proportion of the heritability of AAA.

Objective:

To identify additional AAA risk loci using data from all available genome-wide association studies.

Methods and Results:

Through a meta-analysis of 6 genome-wide association study data sets and a validation study totaling 10 204 cases and 107 766 controls, we identified 4 new AAA risk loci: 1q32.3 (SMYD2), 13q12.11 (LINC00540), 20q13.12 (near PCIF1/MMP9/ZNF335), and 21q22.2 (ERG). In various database searches, we observed no new associations between the lead AAA single nucleotide polymorphisms and coronary artery disease, blood pressure, lipids, or diabetes mellitus. Network analyses identified ERG, IL6R, and LDLR as modifiers of MMP9, with a direct interaction between ERG and MMP9.

Conclusions:

The 4 new risk loci for AAA seem to be specific for AAA compared with other cardiovascular diseases and related traits suggesting that traditional cardiovascular risk factor management may only have limited value in preventing the progression of aneurysmal disease.

Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure

By jointly analyzing multiple variants within a gene, instead of one at a time, gene‐based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster‐specific effects in a quadratic sum of squares and cross‐products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well‐powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P‐value, variance‐component, and principal‐component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene‐specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome‐wide analysis. The cluster construction of the MLC test statistics helps reveal within‐gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations.

Plasma levels of the anti-coagulation protein C and the risk of ischaemic heart disease. A Mendelian randomisation study

Protein C is an environmentally modifiable anticoagulant, which protects against venous thrombosis, whether it also protects against ischaemic heart disease is unclear, based on observational studies and relatively small genetic studies. It was our study aim to clarify the role of protein C in ischaemic heart disease. The risk of coronary artery disease/myocardial infarction (CAD/MI) was assessed according to genetically predicted protein C in very large studies. Associations with lipids and diabetes were similarly assessed to rule out effects via traditional cardiovascular disease risk factors. Separate sample instrumental variable analysis with genetic instruments (Mendelian randomisation) was used to obtain an unconfounded estimate of the association of protein C (based on (rs867186 (PROCR), rs3746429 (EDEM2), rs7580658 (inter/PROC)) with CAD/MI in an extensively genotyped case (n=64374)-control (n=130681) study, CARDIoGRAMplusC4D. Associations with lipids and diabetes were similarly assessed using the Global Lipids Genetics Consortium Results (n=196,475) and the DIAbetes Genetics Replication And Meta-analysis case (n=34,380)-control (n=114,981) study. Genetically predicted protein C was negatively associated with CAD/MI, odds ratio (OR) 0.85 µg/ml, 95 % confidence interval 0.80 to 0.90, but had no such negative association with lipids or diabetes. Results were similar for the SNP rs867186 functionally relevant to protein C, and including additional potentially pleiotropic SNPs (rs1260326 (GCKR), rs17145713 (BAZ1B) and rs4321325 (CYP27C1)). In conclusion, protein C may protect against CAD/MI. Whether environmental or dietary items that raise protein C protect against ischaemic cardiovascular disease by that mechanism should be investigated.

The Changing Face of HDL and the Best Way to Measure It

BACKGROUND

HDL cholesterol (HDL-C) is a commonly used lipid biomarker for assessing cardiovascular health. While a central focus has been placed on the role of HDL in the reverse cholesterol transport (RCT) process, our appreciation for the other cardioprotective properties of HDL continues to expand with further investigation into the structure and function of HDL and its specific subfractions. The development of novel assays is empowering the research community to assess different aspects of HDL function, which at some point may evolve into new diagnostic tests.

CONTENT

This review discusses our current understanding of the formation and maturation of HDL particles via RCT, as well as the newly recognized roles of HDL outside RCT. The antioxidative, antiinflammatory, antiapoptotic, antithrombotic, antiinfective, and vasoprotective effects of HDL are all discussed, as are the related methodologies for assessing these different aspects of HDL function. We elaborate on the importance of protein and lipid composition of HDL in health and disease and highlight potential new diagnostic assays based on these parameters.

SUMMARY

Although multiple epidemiologic studies have confirmed that HDL-C is a strong negative risk marker for cardiovascular disease, several clinical and experimental studies have yielded inconsistent results on the direct role of HDL-C as an antiatherogenic factor. As of yet, our increased understanding of HDL biology has not been translated into successful new therapies, but will undoubtedly depend on the development of alternative ways for measuring HDL besides its cholesterol content.

Bayesian variable selection for post-analytic interrogation of susceptibility loci

Understanding the complex interplay among protein coding genes and regulatory elements requires rigorous interrogation with analytic tools designed for discerning the relative contributions of overlapping genomic regions. To this aim, we offer a novel application of Bayesian variable selection (BVS) for classifying genomic class level associations using existing large meta-analysis summary level resources. This approach is applied using the expectation maximization variable selection (EMVS) algorithm to typed and imputed SNPs across 502 protein coding genes (PCGs) and 220 long intergenic non-coding RNAs (lncRNAs) that overlap 45 known loci for coronary artery disease (CAD) using publicly available Global Lipids Gentics Consortium (GLGC) (Teslovich et al., 2010; Willer et al., 2013) meta-analysis summary statistics for low-density lipoprotein cholesterol (LDL-C). The analysis reveals 33 PCGs and three lncRNAs across 11 loci with >50% posterior probabilities for inclusion in an additive model of association. The findings are consistent with previous reports, while providing some new insight into the architecture of LDL-cholesterol to be investigated further. As genomic taxonomies continue to evolve, additional classes such as enhancer elements and splicing regions, can easily be layered into the proposed analysis framework. Moreover, application of this approach to alternative publicly available meta-analysis resources, or more generally as a post-analytic strategy to further interrogate regions that are identified through single point analysis, is straightforward. All coding examples are implemented in R version 3.2.1 and provided as supplemental material.

Genetic and Environmental Biomarkers Associated with Triglyceride Levels in Two Groups of Slovak Women

OBJECTIVE

This study analyzed the association between the MLXIPL gene polymorphism (rs3812316) and triglyceride (TG) levels and selected environmental biomarkers in Slovak women at risk for cardiovascular disease compared to a reference sample.

MATERIALS AND METHODS

The studied sample consisted of 200 women at cardiovascular risk (mean age 52.96 ± 6.01 years) and 244 healthy women (mean age 47.52 ± 5.34 years). Participants gave details of their health and lifestyle during their medical examination, and peripheral blood samples were used for biochemical analyses and DNA genotyping. A nested polymerase chain reaction-restriction fragment length polymorphism assay was used to detect the rs 3812316 SNP.

RESULTS

We determined that there were significantly different genotype distributions in two TG categories: (1) subjects with normal TG values had a significantly higher G allele frequency than those with elevated TG levels (χ² = 6.1556, df = 2, p = 0.046); and (2) the rare G allele frequency was 0.11 in the cardiovascular risk group and 0.15 in the reference group. Binary regression analysis showed that women with at least one G allele had a significantly lower relative risk of hypertriglyceridemia than women with the CC genotype (OR = 0.399, p = 0.022, 95% CI = 0.182-0.876).

CONCLUSION

This cross-sectional study suggests that MLXIPL rs3812316 genotypes may be associated with TG levels. However, further analysis is advisable because of study limitations.

Integrative mutation, haplotype and G × G interaction evidence connects ABGL4, LRP8 and PCSK9 genes to cardiometabolic risk

This study is expected to investigate the association of ATP/GTP binding protein-like 4 (AGBL4), LDL receptor related protein 8 (LRP8) and proprotein convertase subtilisin/kexin type 9 (PCSK9) gene single nucleotide variants (SNVs) with lipid metabolism in 2,552 individuals (Jing, 1,272 and Han, 1,280). We identified 12 mutations in this motif. The genotype and allele frequencies of these variants were different between the two populations. Multiple-locus linkage disequilibrium (LD) elucidated the detected sites are not statistically independent. Possible integrative haplotypes and gene-by-gene (G × G) interactions, comprising mutations of the AGBL4, LRP8 and PCSK9 associated with total cholesterol (TC, AGBL4 G-G-A, PCSK9 C-G-A-A and G-G-A-A-C-A-T-T-T-G-G-A), triglyceride (TG, AGBL4 G-G-A, LRP8 G-A-G-C-C, PCSK9 C-A-A-G, A-A-G-G-A-G-C-C-C-A-A-G and A-A-G-G-A-G-C-C-C-G-A-A), HDL cholesterol (HDL-C, AGBL4 A-A-G and A-A-G-A-A-G-T-C-C-A-A-G) and the apolipoprotein(Apo)A1/ApoB ratio (A1/B, PCSK9 C-A-A-G) in Jing minority. However, in the Hans, with TG (AGBL4 G-G-A, LRP8 G-A-G-C-C, PCSK9 C-A-A-G, A-A-G-G-A-G-C-C-C-A-A-G and A-A-G-G-A-G-C-C-C-G-A-A), HDL-C (LRP8 A-A-G-T-C), LDL-C (LRP8 A-A-G-T-C and A-A-G-A-A-G-T-C-C-A-A-G) and A1/B (LRP8 A-C-A-T-T and PCSK9 C-A-A-G). Association analysis based on haplotype clusters and G × G interactions probably increased power over single-locus tests especially for TG.

Habitual coffee consumption and risk of type 2 diabetes, ischemic heart disease, depression and Alzheimer's disease: a Mendelian randomization study

Observationally, coffee is inversely associated with type 2 diabetes mellitus (T2DM), depression and Alzheimer’s disease, but not ischemic heart disease (IHD). Coffee features as possibly protective in the 2015 Dietary Guidelines for Americans. Short-term trials suggest coffee has neutral effect on most glycemic traits, but raises lipids and adiponectin. To clarify we compared T2DM, depression, Alzheimer’s disease, and IHD and its risk factors by genetically predicted coffee consumption using two-sample Mendelian randomization applied to large extensively genotyped case-control and cross-sectional studies. Childhood cognition was used as a negative control outcome. Genetically predicted coffee consumption was not associated with T2DM (odds ratio (OR) 1.02, 95% confidence interval (CI) 0.76 to 1.36), depression (0.89, 95% CI 0.66 to 1.21), Alzheimer’s disease (1.17, 95% CI 0.96 to 1.43), IHD (0.96, 95% CI 0.80 to 1.14), lipids, glycemic traits, adiposity or adiponectin. Coffee was unrelated to childhood cognition. Consistent with observational studies, coffee was unrelated to IHD, and, as expected, childhood cognition. However, contrary to observational findings, coffee may not have beneficial effects on T2DM, depression or Alzheimer’s disease. These findings clarify the role of coffee with relevance to dietary guidelines and suggest interventions to prevent these complex chronic diseases should be sought elsewhere.

Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation

Longitudinal electronic health records on 99,785 Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort individuals provided 1,342,814 systolic and diastolic blood pressure measurements for a genome-wide association study on long-term average systolic, diastolic, and pulse pressure. We identified 39 novel among 75 significant loci (P≤5×10⁻⁸), most replicating in the combined International Consortium for Blood Pressure (ICBP, n=69,396) and UK Biobank (UKB, n=152,081) studies. Combining GERA with ICBP yielded 36 additional novel loci, most replicating in UKB. Combining all three studies (n=321,262) yielded 241 additional genome-wide significant loci, although for these no replication sample was available. All associated loci explained 2.9%/2.5%/3.1% of systolic/diastolic/pulse pressure variation in GERA non-Hispanic whites. Using multiple BP measurements in GERA doubled the variance explained. A normalized risk score was associated with time-to-onset of hypertension (hazards ratio=1.18, P=10⁻⁴⁴). Expression quantitative trait locus analysis of BP loci showed enrichment in aorta and tibial artery.

Liver microRNAs: potential mediators and biomarkers for metabolic and cardiovascular disease?

Recent discoveries have revealed that microRNAs (miRNAs) play a key role in the regulation of gene expression. In this review, we summarize the rapidly evolving knowledge about liver miRNAs (including miR-33, -33*, miR-223, -30c, -144, -148a, -24, -29, and -122) and their link to hepatic lipid metabolism, atherosclerosis and cardiovascular disease, non-alcoholic fatty liver disease, metabolic syndrome, and type-2 diabetes. With regards to its biomarker potential, the main focus is on miR-122 as the most abundant liver miRNA with exquisite tissue specificity. MiR-122 has been proposed to play a central role in the maintenance of lipid and glucose homeostasis and is consistently detectable in serum and plasma. This miRNA may therefore constitute a novel biomarker for cardiovascular and metabolic diseases.

A novel role for the Krüppel-like factor 14 on macrophage inflammatory response and atherosclerosis development

Genome-wide association studies have shown that Krüppel-like factor 14 (KLF14) is associated with both Type 2 diabetes mellitus and lipid metabolism. However, its role in chronic inflammatory responses and the pathogenesis of atherosclerosis remains unknown. The present study was designed to investigate both in vivo and in vitro the impact of KLF14 on chronic inflammatory responses and atherosclerosis. ApoE KO mice, a well-established animal model of atherosclerosis, had higher expressions of KLF14 in aorta tissues than that in C57BL/6 J mice when fed the high-fat diet (HFD) or standard chow diet. Adenovirus-mediated KLF14 knockdown markedly reduced the circulating levels of proinflammatory cytokines and the formation of atherosclerotic lesions in HFD-fed ApoE KO mice. In the in vitro study, KLF14 overexpression in the RAW264.7 macrophages significantly increased the expressions of inflammatory cytokines, total cholesterol (TC), cholesteryl ester (CE), and the ratio of CE to TC in the cells treated with acetylated low-density lipoproteins (AcLDL). Conversely, KLF14 knockdown remarkably attenuated AcLDL-induced increase in TC, CE, and the ratio of CE to TC as well as the expressions of inflammatory cytokines. Furthermore, up-regulation or down-regulation of KLF14 markedly elevated or inhibited the phosphorylation levels of p38 MAPK and ERK1/2 in AcLDL-stimulated RAW264.7 macrophages, respectively. Importantly, treatment with p38 MAPK or ERK1/2 inhibitor nullified the effects of KLF14 on inflammatory cytokine expressions in the cells. These data demonstrate an important role for KLF14 expression in atherosclerotic lesion formation.

TRIGLYCERIDES, ATHEROSCLEROSIS, AND CARDIOVASCULAR OUTCOME STUDIES: FOCUS ON OMEGA-3 FATTY ACIDS

OBJECTIVE

To provide an overview of the roles of triglycerides and triglyceride-lowering agents in atherosclerosis in the context of cardiovascular outcomes studies.

METHODS

We reviewed the published literature as well as ClinicalTrials.gov entries for ongoing studies.

RESULTS

Despite improved atherosclerotic cardiovascular disease (ASCVD) outcomes with statin therapy, residual risk remains. Epidemiologic data and recent genetic insights provide compelling evidence that triglycerides are in the causal pathway for the development of atherosclerosis, thereby renewing interest in targeting triglycerides to improve ASCVD outcomes. Fibrates, niacin, and omega-3 fatty acids (OM3FAs) are three classes of triglyceride-lowering drugs. Outcome studies with triglyceride-lowering agents have been inconsistent. With regard to OM3FAs, the JELIS study showed that eicosapentaenoic acid (EPA) significantly reduced major coronary events in statin-treated hypercholesterolemic patients. Regarding other agents, extended-release niacin and fenofibrate are no longer recommended as statin add-on therapy (by some guidelines, though not all) because of the lack of convincing evidence from outcome studies. Notably, subgroup analyses from the outcome studies have generated the hypothesis that triglyceride lowering may provide benefit in statin-treated patients with persistent hypertriglyceridemia. Two ongoing OM3FA outcome studies (REDUCE-IT and STRENGTH) are testing this hypothesis in high-risk, statin-treated patients with triglyceride levels of 200 to 500 mg/dL.

CONCLUSION

There is consistent evidence that triglycerides are in the causal pathway of atherosclerosis but inconsistent evidence from cardiovascular outcomes studies as to whether triglyceride-lowering agents reduce cardiovascular risk. Ongoing outcomes studies will determine the role of triglyceride lowering in statin-treated patients with high-dose prescription OM3FAs in terms of improved ASCVD outcomes.

ABBREVIATIONS

AACE = American Association of Clinical Endocrinologists ACCORD = Action to Control Cardiovascular Risk in Diabetes AIM-HIGH = Atherothrombosis Intervention in Metabolic Syndrome with Low HDL/High Triglycerides: Impact on Global Health Outcomes apo = apolipoprotein ASCEND = A Study of Cardiovascular Events in Diabetes ASCVD = atherosclerotic cardiovascular disease BIP = Bezafibrate Infarction Prevention CHD = coronary heart disease CI = confidence interval CV = cardiovascular CVD = cardiovascular disease DHA = docosahexaenoic acid DO-IT = Diet and Omega-3 Intervention Trial EPA = eicosapentaenoic acid FIELD = Fenofibrate Intervention and Event Lowering in Diabetes GISSI-HF = GISSI-Heart Failure HDL-C = high-density-lipoprotein cholesterol HPS2-THRIVE = Heart Protection Study 2-Treatment of HDL to Reduce the Incidence of Vascular Events HR = hazard ratio JELIS = Japan Eicosapentaenoic Acid Lipid Intervention Study LDL = low-density lipoprotein LDL-C = low-density-lipoprotein cholesterol MI = myocardial infarction OM3FAs = omega-3 fatty acids VITAL = Vitamin D and Omega-3 Trial.

Antisense oligonucleotides targeting apolipoprotein(a) in people with raised lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging trials

BACKGROUND

Elevated lipoprotein(a) (Lp[a]) is a highly prevalent (around 20% of people) genetic risk factor for cardiovascular disease and calcific aortic valve stenosis, but no approved specific therapy exists to substantially lower Lp(a) concentrations. We aimed to assess the efficacy, safety, and tolerability of two unique antisense oligonucleotides designed to lower Lp(a) concentrations.

METHODS

We did two randomised, double-blind, placebo-controlled trials. In a phase 2 trial (done in 13 study centres in Canada, the Netherlands, Germany, Denmark, and the UK), we assessed the effect of IONIS-APO(a)_Rx, an oligonucleotide targeting apolipoprotein(a). Participants with elevated Lp(a) concentrations (125-437 nmol/L in cohort A; ≥438 nmol/L in cohort B) were randomly assigned (in a 1:1 ratio in cohort A and in a 4:1 ratio in cohort B) with an interactive response system to escalating-dose subcutaneous IONIS-APO(a)_Rx (100 mg, 200 mg, and then 300 mg, once a week for 4 weeks each) or injections of saline placebo, once a week, for 12 weeks. Primary endpoints were mean percentage change in fasting plasma Lp(a) concentration at day 85 or 99 in the per-protocol population (participants who received more than six doses of study drug) and safety and tolerability in the safety population. In a phase 1/2a first-in-man trial, we assessed the effect of IONIS-APO(a)-L_Rx, a ligand-conjugated antisense oligonucleotide designed to be highly and selectively taken up by hepatocytes, at the BioPharma Services phase 1 unit (Toronto, ON, Canada). Healthy volunteers (Lp[a] ≥75 nmol/L) were randomly assigned to receive a single dose of 10-120 mg IONIS-APO(a)L_Rx subcutaneously in an ascending-dose design or placebo (in a 3:1 ratio; single-ascending-dose phase), or multiple doses of 10 mg, 20 mg, or 40 mg IONIS-APO(a)L_Rx subcutaneously in an ascending-dose design or placebo (in an 8:2 ratio) at day 1, 3, 5, 8, 15, and 22 (multiple-ascending-dose phase). Primary endpoints were mean percentage change in fasting plasma Lp(a) concentration, safety, and tolerability at day 30 in the single-ascending-dose phase and day 36 in the multiple-ascending-dose phase in participants who were randomised and received at least one dose of study drug. In both trials, the randomised allocation sequence was generated by Ionis Biometrics or external vendor with a permuted-block randomisation method. Participants, investigators, sponsor personnel, and clinical research organisation staff who analysed the data were all masked to the treatment assignments. Both trials are registered with ClinicalTrials.gov, numbers NCT02160899 and NCT02414594.

FINDINGS

From June 25, 2014, to Nov 18, 2015, we enrolled 64 participants to the phase 2 trial (51 in cohort A and 13 in cohort B). 35 were randomly assigned to IONIS-APO(a)_Rx and 29 to placebo. At day 85/99, participants assigned to IONIS-APO(a)_Rx had mean Lp(a) reductions of 66·8% (SD 20·6) in cohort A and 71·6% (13·0) in cohort B (both p<0·0001 vs pooled placebo). From April 15, 2015, to Jan 11, 2016, we enrolled 58 healthy volunteers to the phase 1/2a trial of IONIS-APO(a)-L_Rx. Of 28 participants in the single-ascending-dose phase, three were randomly assigned to 10 mg, three to 20 mg, three to 40 mg, six to 80 mg, six to 120 mg, and seven to placebo. Of 30 participants in the multiple-ascending-dose phase, eight were randomly assigned to 10 mg, eight to 20 mg, eight to 40 mg, and six to placebo. Significant dose-dependent reductions in mean Lp(a) concentrations were noted in all single-dose IONIS-APO(a)-L_Rx groups at day 30. In the multidose groups, IONIS-APO(a)-L_Rx resulted in mean reductions in Lp(a) of 66% (SD 21·8) in the 10 mg group, 80% (SD 13·7%) in the 20 mg group, and 92% (6·5) in the 40 mg group (p=0·0007 for all vs placebo) at day 36. Both antisense oligonucleotides were safe. There were two serious adverse events (myocardial infarctions) in the IONIS-APO(a)_Rx phase 2 trial, one in the IONIS-APO(a)_Rx and one in the placebo group, but neither were thought to be treatment related. 12% of injections with IONIS-APO(a)_Rx were associated with injection-site reactions. IONIS-APO(a)-L_Rx was associated with no injection-site reactions.

INTERPRETATION

IONIS-APO(a)-L_Rx is a novel, tolerable, potent therapy to reduce Lp(a) concentrations. IONIS-APO(a)-L_Rx might mitigate Lp(a)-mediated cardiovascular risk and is being developed for patients with elevated Lp(a) concentrations with existing cardiovascular disease or calcific aortic valve stenosis.

FUNDING

Ionis Pharmaceuticals.

Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems

BACKGROUND

Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies.

RESULTS

We developed Mergeomics, a computational pipeline consisting of independent modules that 1) leverage multi-omics association data to identify biological processes that are perturbed in disease, and 2) overlay the disease-associated processes onto molecular interaction networks to pinpoint hubs as potential key regulators. Unlike existing tools that are mostly dedicated to specific data type or settings, the Mergeomics pipeline accepts and integrates datasets across platforms, data types and species. We optimized and evaluated the performance of Mergeomics using simulation and multiple independent datasets, and benchmarked the results against alternative methods. We also demonstrate the versatility of Mergeomics in two case studies that include genome-wide, epigenome-wide and transcriptome-wide datasets from human and mouse studies of total cholesterol and fasting glucose. In both cases, the Mergeomics pipeline provided statistical and contextual evidence to prioritize further investigations in the wet lab. The software implementation of Mergeomics is freely available as a Bioconductor R package.

CONCLUSION

Mergeomics is a flexible and robust computational pipeline for multidimensional data integration. It outperforms existing tools, and is easily applicable to datasets from different studies, species and omics data types for the study of complex traits.

Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps

Large-scale whole-genome sequence data sets offer novel opportunities to identify genetic variation underlying human traits. Here we apply genotype imputation based on whole-genome sequence data from the UK10K and 1000 Genomes Project into 35,981 study participants of European ancestry, followed by association analysis with 20 quantitative cardiometabolic and hematological traits. We describe 17 new associations, including 6 rare (minor allele frequency (MAF) < 1%) or low-frequency (1% < MAF < 5%) variants with platelet count (PLT), red blood cell indices (MCH and MCV) and HDL cholesterol. Applying fine-mapping analysis to 233 known and new loci associated with the 20 traits, we resolve the associations of 59 loci to credible sets of 20 or fewer variants and describe trait enrichments within regions of predicted regulatory function. These findings improve understanding of the allelic architecture of risk factors for cardiometabolic and hematological diseases and provide additional functional insights with the identification of potentially novel biological targets.

Genetic support for the causal role of insulin in coronary heart disease

AIMS/HYPOTHESIS

Epidemiological studies have identified several traits associated with CHD, but few of these have been shown to be causal risk factors and thus suitable targets for treatment. Our aim was to evaluate the causal role of a large set of known CHD risk factors using single-nucleotide polymorphisms (SNPs) as instrumental variables.

METHODS

Based on published genome-wide association studies (GWASs), we estimated the associations between the established risk factors (blood lipids, obesity, glycaemic traits and BP) and CHD with two complementary approaches: (1) using summary statistics from GWASs to analyse the accordance of SNP effects on risk factors and on CHD; and (2) individual-level analysis where we constructed genetic risk scores (GRSs) in a large Finnish dataset (N = 26,554, CHD events n = 4016). We used a weighted regression-based method for summary-level data to evaluate the causality of risk factors. The associations between the GRSs and CHD in the Finnish dataset were evaluated with logistic and conditional logistic regression models.

RESULTS

The summary-level data analysis revealed causal effects between glycaemic traits (insulin and glucose) and CHD. The individual-level data analysis supported the causal role of insulin, but not of glucose, on CHD. The GRS for insulin was associated with CHD in the Finnish cohort (OR 1.06 per SD in GRS, 95% CI 1.02, 1.10, p = 0.002).

CONCLUSIONS/INTERPRETATION

These results support the causal role of insulin in the pathogenesis of CHD. Efficient treatment and prevention of insulin resistance is essential to prevent future CHD events.

Genetic Predisposition to an Impaired Metabolism of the Branched-Chain Amino Acids and Risk of Type 2 Diabetes: A Mendelian Randomisation Analysis

BACKGROUND

Higher circulating levels of the branched-chain amino acids (BCAAs; i.e., isoleucine, leucine, and valine) are strongly associated with higher type 2 diabetes risk, but it is not known whether this association is causal. We undertook large-scale human genetic analyses to address this question.

METHODS AND FINDINGS

Genome-wide studies of BCAA levels in 16,596 individuals revealed five genomic regions associated at genome-wide levels of significance (p < 5 × 10-8). The strongest signal was 21 kb upstream of the PPM1K gene (beta in standard deviations [SDs] of leucine per allele = 0.08, p = 3.9 × 10-25), encoding an activator of the mitochondrial branched-chain alpha-ketoacid dehydrogenase (BCKD) responsible for the rate-limiting step in BCAA catabolism. In another analysis, in up to 47,877 cases of type 2 diabetes and 267,694 controls, a genetically predicted difference of 1 SD in amino acid level was associated with an odds ratio for type 2 diabetes of 1.44 (95% CI 1.26-1.65, p = 9.5 × 10-8) for isoleucine, 1.85 (95% CI 1.41-2.42, p = 7.3 × 10-6) for leucine, and 1.54 (95% CI 1.28-1.84, p = 4.2 × 10-6) for valine. Estimates were highly consistent with those from prospective observational studies of the association between BCAA levels and incident type 2 diabetes in a meta-analysis of 1,992 cases and 4,319 non-cases. Metabolome-wide association analyses of BCAA-raising alleles revealed high specificity to the BCAA pathway and an accumulation of metabolites upstream of branched-chain alpha-ketoacid oxidation, consistent with reduced BCKD activity. Limitations of this study are that, while the association of genetic variants appeared highly specific, the possibility of pleiotropic associations cannot be entirely excluded. Similar to other complex phenotypes, genetic scores used in the study captured a limited proportion of the heritability in BCAA levels. Therefore, it is possible that only some of the mechanisms that increase BCAA levels or affect BCAA metabolism are implicated in type 2 diabetes.

CONCLUSIONS

Evidence from this large-scale human genetic and metabolomic study is consistent with a causal role of BCAA metabolism in the aetiology of type 2 diabetes.