Discovery and refinement of loci associated with lipid levels

Interactions of Lipid Genetic Risk Scores With Estimates of Metabolic Health in a Danish Population

Background—

There are several well-established lifestyle factors influencing dyslipidemia and currently; 157 genetic susceptibility loci have been reported to be associated with serum lipid levels at genome-wide statistical significance. However, the interplay between lifestyle risk factors and these susceptibility loci has not been fully elucidated. We tested whether genetic risk scores (GRS) of lipid-associated single nucleotide polymorphisms associate with fasting serum lipid traits and whether the effects are modulated by lifestyle factors or estimates of metabolic health.

Methods and Results—

The single nucleotide polymorphisms were genotyped in 2 Danish cohorts: inter99 (n=5961) for discovery analyses and Health2006 (n=2565) for replication. On the basis of published effect sizes of single nucleotide polymorphisms associated with circulating fasting levels of total cholesterol, low-density lipoprotein-cholesterol, high-density lipoprotein-cholesterol, or triglyceride, 4 weighted GRS were constructed. In a cross-sectional design, we investigated whether the effect of these weighted GRSs on lipid levels were modulated by diet, alcohol consumption, physical activity, and smoking or the individual metabolic health status as estimated from body mass index, waist circumference, and insulin resistance assessed using homeostasis model assessment of insulin resistance. All 4 lipid weighted GRSs associated strongly with their respective trait (from P =3.3×10 –69 to P =1.1×10 –123 ). We found interactions between the triglyceride weighted GRS and body mass index and waist circumference on fasting triglyceride levels in Inter99 and replicated these findings in Health2006 ( P interaction =9.8×10 –5 and 2.0×10 –5 , respectively, in combined analysis).

Conclusions—

Our findings suggest that individuals who are obese may be more susceptible to the cumulative genetic burden of triglyceride single nucleotide polymorphisms. Therefore, it is suggested that especially these genetically at-risk individuals may benefit more from targeted interventions aiming at obesity prevention.

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study

BACKGROUND

Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR).

METHODS AND FINDINGS

We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses.

CONCLUSIONS

Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.

The impact of low-frequency and rare variants on lipid levels

Using a genome-wide screen of 9.6 million genetic variants achieved through 1000 Genomes Project imputation in 62,166 samples, we identify association to lipid traits in 93 loci, including 79 previously identified loci with new lead SNPs and 10 new loci, 15 loci with a low-frequency lead SNP and 10 loci with a missense lead SNP, and 2 loci with an accumulation of rare variants. In six loci, SNPs with established function in lipid genetics (CELSR2, GCKR, LIPC and APOE) or candidate missense mutations with predicted damaging function (CD300LG and TM6SF2) explained the locus associations. The low-frequency variants increased the proportion of variance explained, particularly for low-density lipoprotein cholesterol and total cholesterol. Altogether, our results highlight the impact of low-frequency variants in complex traits and show that imputation offers a cost-effective alternative to resequencing.

Novel genes in LDL metabolism--a comprehensive overview

PURPOSE OF REVIEW

To summarize recent findings from genome-wide association studies (GWAS), whole-exome sequencing of patients with familial hypercholesterolemia and 'exome chip' studies pointing to novel genes in LDL metabolism.

RECENT FINDINGS

The genetic loci for ATP-binding cassette transporters G5 and G8, Niemann-Pick C1-Like protein 1, sortilin-1, ABO blood-group glycosyltransferases, myosin regulatory light chain-interacting protein and cholesterol 7α-hydroxylase have all consistently been associated with LDL cholesterol levels and/or coronary artery disease in GWAS. Whole-exome sequencing and 'exome chip' studies have additionally suggested several novel genes in LDL metabolism including insulin-induced gene 2, signal transducing adaptor family member 1, lysosomal acid lipase A, patatin-like phospholipase domain-containing protein 5 and transmembrane 6 superfamily member 2. Most of these findings still require independent replications and/or functional studies to confirm the exact role in LDL metabolism and the clinical implications for human health.

SUMMARY

GWAS, exome sequencing studies, and recently 'exome chip' studies have suggested several novel genes with effects on LDL cholesterol. Novel genes in LDL metabolism will improve our understanding of mechanisms in LDL metabolism, and may lead to the identification of new drug targets to reduce LDL cholesterol levels.

Associations of common SNPs in the SORT1, GCKR, LPL, APOA1, CETP, LDLR, APOE genes with lipid trait levels in an Algerian population sample

Genome-wide association studies have identified many lipid-associated loci primarily in European and Asian populations. In view of the differences between ethnic groups in terms of the frequency and impact of these variants, our objective was to evaluate the relationships between eight lipid-associated variants (considered individually and in combination) and fasting serum triglyceride, total cholesterol, HDL- and LDL-cholesterol levels in an Algerian population sample (ISOR study, n = 751). Three SNPs (in SORT1, CETP and GCKR) were individually associated with lipid level variations. Moreover, the risk allele scores for total cholesterol, triglyceride and LDL-C levels (encompassing between three and six SNPs) were associated with their corresponding lipid traits. Our study is the first to show that some of the lipid-associated loci in European populations are associated with lipid traits in Algerians. Although our results will have to be confirmed in other North African populations, this study contributes to a better understanding of genetic susceptibility to lipid traits in Algeria.

Suppressor of cytokine signaling 3 A+930-->G (rs4969168) polymorphism is associated with apolipoprotein A1 and low-density lipoprotein cholesterol

This study aimed to detect the association of the suppressor of cytokine signaling 3 gene (SOCS3) A+930-->G (rs4969168) single nucleotide polymorphism (SNP) and environmental factors with serum lipid levels in the Han and Mulao populations. Genotyping of the SOCS3 A+930-->G (rs4969168) SNP was performed in 752 of Han and 690 of Mulao participants using polymerase chain reaction and restriction fragment length polymorphism. The genotype and allele frequencies were significantly different between the Han and Mulao populations (GG, 57.71% vs. 51.16%, GA, 36.97% vs. 41.16%, AA, 5.32% vs. 7.68%, P = 0.023; G, 76.20% vs. 71.74%, A, 23.80% vs. 28.26%; P = 0.006; respectively). Serum apolipoprotein (Apo) A1 levels in Han were different among the genotypes (P < 0.05). Subgroup analyses showed that the levels of ApoA1 in Han females, and ApoA1 and low-density lipoprotein cholesterol (LDL-C) in Mulao males were different among the genotypes (P < 0.05). Serum lipid parameters were also associated with several environmental factors in both ethnic groups (P < 0.05-0.001). These findings suggest that there may be a racial/ethnic- and/or sex-specific association between the SOCS3 A+930-->G (rs4969168) SNP and serum lipid parameters in some populations.

Low density lipoprotein receptor related protein 1 and 6 gene variants and ischaemic stroke risk

BACKGROUND AND PURPOSE

Low density lipoprotein receptor related proteins (LRPs) 1 and 6 have been implicated in cerebral ischaemia. In addition, genetic variation in LRP1 and LRP6 has been linked with various factors that are related to risk of ischaemic stroke. The aim of this study was to examine the association of LRP1 and LRP6 gene variants with risk of ischaemic stroke as part of the Ischemic Stroke Genetics Study (ISGS).

METHODS

A Caucasian series (434 stroke patients, 319 controls) and an African American series (161 stroke patients, 116 controls) were included. Fourteen LRP6 variants and three LRP1 variants were genotyped and assessed for association with ischaemic stroke.

RESULTS

In the Caucasian series, significant associations with ischaemic stroke were observed for LRP6 rs2075241 [odds ratio (OR) 0.42, P = 0.023], rs2302685 (OR 0.44, P = 0.049), rs7975614 (OR 0.07, P = 0.017), rs10492120 (OR 0.62, P = 0.036) and rs10743980 (OR 0.66, P = 0.037). Risk of ischaemic stroke was significantly lower for carriers of any of these five protective LRP6 variants (24.0% of subjects) compared to non-carriers (OR 0.57, P = 0.003). The protective association for LRP6 rs2075241 was observed at a similar magnitude across ischaemic stroke subtypes, whilst the effects of rs23022685, rs10492120 and rs10743980 were most apparent for cardioembolic and large vessel stroke. In the African American series, LRP1 rs11172113 was associated with an increased risk of stroke (OR 1.89, P = 0.006).

CONCLUSIONS

The results of our preliminary study provide evidence that LRP6 and LRP1 variants may be associated with risk of ischaemic stroke. Validation in larger studies is warranted.

Triglyceride-Increasing Alleles Associated with Protection against Type-2 Diabetes

Elevated plasma triglyceride (TG) levels are an established risk factor for type-2 diabetes (T2D). However, recent studies have hinted at the possibility that genetic risk for TG may paradoxically protect against T2D. In this study, we examined the association of genetic risk for TG with incident T2D, and the interaction of baseline TG with TG genetic risk on incident T2D in 13,247 European-Americans (EA) and 3,238 African-Americans (AA) from three prospective cohort studies. A TG genetic risk score (GRS) was calculated based on 31 validated single nucleotide polymorphisms (SNPs). We considered several baseline covariates, including body- mass index (BMI) and lipid traits. Among EA and AA, we find, as expected, that baseline levels of TG are strongly positively associated with incident T2D (p<2 x 10-(10)). However, the TG GRS is negatively associated with T2D (p=0.013), upon adjusting for only race, in the full dataset. Upon additionally adjusting for age, sex, BMI, high-density lipoprotein cholesterol and TG, the TG GRS is significantly and negatively associated with T2D incidence (p=7.0 x 10(-8)), with similar trends among both EA and AA. No single SNP appears to be driving this association. We also find a significant statistical interaction of the TG GRS with TG (pi(nteraction) = 3.3 x 10-(4)), whereby the association of TG with incident T2D is strongest among those with low genetic risk for TG. Further research is needed to understand the likely pleiotropic mechanisms underlying these findings, and to clarify the causal relationship between T2D and TG.

Translational regulation shapes the molecular landscape of complex disease phenotypes

The extent of translational control of gene expression in mammalian tissues remains largely unknown. Here we perform genome-wide RNA sequencing and ribosome profiling in heart and liver tissues to investigate strain-specific translational regulation in the spontaneously hypertensive rat (SHR/Ola). For the most part, transcriptional variation is equally apparent at the translational level and there is limited evidence of translational buffering. Remarkably, we observe hundreds of strain-specific differences in translation, almost doubling the number of differentially expressed genes. The integration of genetic, transcriptional and translational data sets reveals distinct signatures in 3'UTR variation, RNA-binding protein motifs and miRNA expression associated with translational regulation of gene expression. We show that a large number of genes associated with heart and liver traits in human genome-wide association studies are primarily translationally regulated. Capturing interindividual differences in the translated genome will lead to new insights into the genes and regulatory pathways underlying disease phenotypes.

Human Enhancers Are Fragile and Prone to Deactivating Mutations

To explore the underlying mechanisms whereby noncoding variants affect transcriptional regulation, we identified nucleotides capable of disrupting binding of transcription factors and deactivating enhancers if mutated (dubbed candidate killer mutations or KMs) in HepG2 enhancers. On average, approximately 11% of enhancer positions are prone to KMs. A comparable number of enhancer positions are capable of creating de novo binding sites via a single-nucleotide mutation (dubbed candidate restoration mutations or RSs). Both KM and RS positions are evolutionarily conserved and tend to form clusters within an enhancer. We observed that KMs have the most deleterious effect on enhancer activity. In contrast, RSs have a smaller effect in increasing enhancer activity. Additionally, the KMs are strongly associated with liver-related Genome Wide Association Study traits compared with other HepG2 enhancer regions. By applying our framework to lymphoblastoid cell lines, we found that KMs underlie differential binding of transcription factors and differential local chromatin accessibility. The gene expression quantitative trait loci associated with the tissue-specific genes are strongly enriched in KM positions. In summary, we conclude that the KMs have the greatest impact on the level of gene expression and are likely to be the causal variants of tissue-specific gene expression and disease predisposition.

Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach

Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.

An Examination of the Relationship between Lipid Levels and Associated Genetic Markers across Racial/Ethnic Populations in the Multi-Ethnic Study of Atherosclerosis

Large genome-wide association studies have reported hundreds of genetic markers associated with lipid levels. However, the discovery and estimated effect of variants at these loci, derived from samples of exclusively European descent, may not generalize to the majority of the world populations. We examined the collective strength of association among these loci in a diverse set of U.S. populations from the Multi-Ethnic Study of Atherosclerosis. We constructed a genetic risk score for each lipid outcome based on previously identified lipid-associated genetic markers, and examined the relationship between the genetic risk scores and corresponding outcomes. We discover this relationship was often moderated by race/ethnicity. Our findings provide insight into the generalizability and predictive utility of large sample size meta-analyses results when leveraging data from a single population. We hope these findings will encourage researchers to investigate genetic susceptibility in more diverse populations and explore the source of such discrepancies. Until then, we caution clinicians, genetic counselors, and genetic testing consumers when interpreting genetic data on complex traits.

Mitochondrial GWA Analysis of Lipid Profile Identifies Genetic Variants to Be Associated with HDL Cholesterol and Triglyceride Levels

It has been suggested that mitochondrial dysfunction has an influence on lipid metabolism. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why cholesterol levels often are altered with age. To test the hypothesis whether mitochondrial variants are associated with lipid profile (total cholesterol, LDL, HDL, and triglycerides) we analyzed a total number of 978 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 2,815 individuals participating in the population-based KORA F4 study. To assess mtSNP association while taking the presence of heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Ten mtSNPs (mt3285, mt3336, mt5285, mt6591, mt6671, mt9163, mt13855, mt13958, mt14000, and mt14580) were significantly associated with HDL cholesterol and one mtSNP (mt15074) with triglycerides levels. These results highlight the importance of the mitochondrial genome among the factors that contribute to the regulation of lipid levels. Focusing on mitochondrial variants may lead to further insights regarding the underlying physiological mechanisms, or even to the development of innovative treatments. Since this is the first mitochondrial genome-wide association analysis (mtGWAS) for lipid profile, further analyses are needed to follow up on the present findings.

Enhanced meta-analysis and replication studies identify five new psoriasis susceptibility loci

Psoriasis is a chronic autoimmune disease with complex genetic architecture. Previous genome-wide association studies (GWAS) and a recent meta-analysis using Immunochip data have uncovered 36 susceptibility loci. Here, we extend our previous meta-analysis of European ancestry by refined genotype calling and imputation and by the addition of 5,033 cases and 5,707 controls. The combined analysis, consisting of over 15,000 cases and 27,000 controls, identifies five new psoriasis susceptibility loci at genome-wide significance (P<5 × 10(-8)). The newly identified signals include two that reside in intergenic regions (1q31.1 and 5p13.1) and three residing near PLCL2 (3p24.3), NFKBIZ (3q12.3) and CAMK2G (10q22.2). We further demonstrate that NFKBIZ is a TRAF3IP2-dependent target of IL-17 signalling in human skin keratinocytes, thereby functionally linking two strong candidate genes. These results further integrate the genetics and immunology of psoriasis, suggesting new avenues for functional analysis and improved therapies.

Age- and sex-specific causal effects of adiposity on cardiovascular risk factors

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.

Extracting research-quality phenotypes from electronic health records to support precision medicine

The convergence of two rapidly developing technologies - high-throughput genotyping and electronic health records (EHRs) - gives scientists an unprecedented opportunity to utilize routine healthcare data to accelerate genomic discovery. Institutions and healthcare systems have been building EHR-linked DNA biobanks to enable such a vision. However, the precise extraction of detailed disease and drug-response phenotype information hidden in EHRs is not an easy task. EHR-based studies have successfully replicated known associations, made new discoveries for diseases and drug response traits, rapidly contributed cases and controls to large meta-analyses, and demonstrated the potential of EHRs for broad-based phenome-wide association studies. In this review, we summarize the advantages and challenges of repurposing EHR data for genetic research. We also highlight recent notable studies and novel approaches to provide an overview of advanced EHR-based phenotyping.

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge.

The association between carbohydrate-rich foods and risk of cardiovascular disease is not modified by genetic susceptibility to dyslipidemia as determined by 80 validated variants

Background

It is still unclear whether carbohydrate consumption is associated with cardiovascular disease (CVD) risk. Genetic susceptibility might modify the associations between dietary intakes and disease risk.

Objectives

The aim was to examine the association between the consumption of carbohydrate-rich foods (vegetables, fruits and berries, juice, potatoes, whole grains, refined grains, cookies and cakes, sugar and sweets, and sugar-sweetened beverages) and the risk of incident ischemic CVD (iCVD; coronary events and ischemic stroke), and whether these associations differ depending on genetic susceptibility to dyslipidemia.

Methods

Among 26,445 individuals (44–74 years; 62% females) from the Malmö Diet and Cancer Study cohort, 2,921 experienced an iCVD event during a mean follow-up time of 14 years. At baseline, dietary data were collected using a modified diet history method, and clinical risk factors were measured in 4,535 subjects. We combined 80 validated genetic variants associated with triglycerides and HDL-C or LDL-C, into genetic risk scores and examined the interactions between dietary intakes and genetic risk scores on the incidence of iCVD.

Results

Subjects in the highest intake quintile for whole grains had a 13% (95% CI: 3–23%; p-trend: 0.002) lower risk for iCVD compared to the lowest quintile. A higher consumption of foods rich in added sugar (sugar and sweets, and sugar-sweetened beverages) had a significant cross-sectional association with higher triglyceride concentrations and lower HDL-C concentrations. A stronger positive association between a high consumption of sugar and sweets on iCVD risk was observed among those with low genetic risk score for triglycerides (p-interaction=0.05).

Conclusion

In this prospective cohort study that examined food sources of carbohydrates, individuals with a high consumption of whole grains had a decreased risk of iCVD. No convincing evidence of an interaction between genetic susceptibility for dyslipidemia, measured as genetic risk scores of dyslipidemia-associated variants, and the consumption of carbohydrate-rich foods on iCVD risk was observed.

Genetic analysis of ligation-induced neointima formation in an F2 intercross of C57BL/6 and FVB/N inbred mouse strains

Objective

Proliferation and migration of vascular smooth muscle cells (SMCs) are central for arterial diseases including atherosclerosis and restenosis. We hypothesized that the underlying mechanisms may be modeled by carotid ligation in mice. In FVB/N inbred mice, ligation leads to abundant neointima formation with proliferating media-derived SMCs, whereas in C57BL/6 mice hardly any neointima is formed. In the present study, we aimed to identify the chromosomal location of the causative gene variants in an F2 intercross between these two mouse strains.

Methods and Results

The neointimal cross-sectional area was significantly different between FVB/N, C57BL/6 and F1 female mice 4 weeks after ligation. Carotid artery ligation and a genome scan using 800 informative SNP markers were then performed in 157 female F2 mice. Using quantitative trait loci (QTL) analysis, we identified suggestive, but no genome-wide significant, QTLs on chromosomes 7 and 12 for neointimal cross-sectional area and on chromosome 14 for media area. Further analysis of the cross revealed 4 QTLs for plasma cholesterol, which combined explained 69% of the variation among F2 mice.

Conclusions

We identified suggestive QTLs for neointima and media area after carotid ligation in an intercross of FVB/N and C57BL/6 mice, but none that reached genome-wide significance indicating a complex genetic architecture of the traits. Genome-wide significant QTLs for total cholesterol levels were identified on chromosomes 1, 3, 9, and 12.

GREGOR: evaluating global enrichment of trait-associated variants in epigenomic features using a systematic, data-driven approach

MOTIVATION

The majority of variation identified by genome wide association studies falls in non-coding genomic regions and is hypothesized to impact regulatory elements that modulate gene expression. Here we present a statistically rigorous software tool GREGOR (Genomic Regulatory Elements and Gwas Overlap algoRithm) for evaluating enrichment of any set of genetic variants with any set of regulatory features. Using variants from five phenotypes, we describe a data-driven approach to determine the tissue and cell types most relevant to a trait of interest and to identify the subset of regulatory features likely impacted by these variants. Last, we experimentally evaluate six predicted functional variants at six lipid-associated loci and demonstrate significant evidence for allele-specific impact on expression levels. GREGOR systematically evaluates enrichment of genetic variation with the vast collection of regulatory data available to explore novel biological mechanisms of disease and guide us toward the functional variant at trait-associated loci.

AVAILABILITY AND IMPLEMENTATION

GREGOR, including source code, documentation, examples, and executables, is available at http://genome.sph.umich.edu/wiki/GREGOR.

CONTACT

cristen@umich.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genome-wide association studies of late-onset cardiovascular disease

Human genetics is a powerful tool for discovering causal mediators of human disease and physiology. Cardiovascular diseases with late onset in the lifecourse have historically not been considered genetic diseases, but in recent years the contribution of a heritable factor has been established. More importantly, over the last decade genome-wide association studies (GWASs) have identified many loci associated with late-onset cardiovascular diseases including coronary artery disease, carotid artery disease, ischemic stroke, aortic aneurysm, peripheral vascular disease, atrial fibrillation, valvular disease and correlates of vascular and myocardial function. Here we review findings from GWASs considered statistically robust with regard to multiple testing (p<5×10(-8)) for late-onset cardiovascular diseases and traits. Although for only a handful of the 92 genetic loci described here have the mechanisms underlying disease association been established, new and previously unsuspected pathways have been implicated for several conditions. Examples include a role for NO signaling in myocardial repolarization and sudden cardiac death and a role for the protein sortilin in lipid metabolism and coronary artery disease. Genetic loci with multiple trait associations have also provided novel biological insights. For example, of the 46 genetic loci associated with coronary artery disease, only 16 are also associated with conventional risk factors for cardiovascular disease whereas the remaining two thirds may reflect novel pathways. Much work remains to functionally characterize genetic loci and for clinical utility, but accruing insights into the biological basis of cardiovascular aging in human populations promise to point to novel therapeutic and preventive strategies. This article is part of a Special Issue entitled 'SI:CV Aging'.

Contribution of large region joint associations to complex traits genetics

A polygenic model of inheritance, whereby hundreds or thousands of weakly associated variants contribute to a trait’s heritability, has been proposed to underlie the genetic architecture of complex traits. However, relatively few genetic variants have been positively identified so far and they collectively explain only a small fraction of the predicted heritability. We hypothesized that joint association of multiple weakly associated variants over large chromosomal regions contributes to complex traits variance. Confirmation of such regional associations can help identify new loci and lead to a better understanding of known ones. To test this hypothesis, we first characterized the ability of commonly used genetic association models to identify large region joint associations. Through theoretical derivation and simulation, we showed that multivariate linear models where multiple SNPs are included as independent predictors have the most favorable association profile. Based on these results, we tested for large region association with height in 3,740 European participants from the Health and Retirement Study (HRS) study. Adjusting for SNPs with known association with height, we demonstrated clustering of weak associations (p = 2x10^-4) in regions extending up to 433.0 Kb from known height loci. The contribution of regional associations to phenotypic variance was estimated at 0.172 (95% CI 0.063-0.279; p < 0.001), which compared favorably to 0.129 explained by known height variants. Conversely, we showed that suggestively associated regions are enriched for known height loci. To extend our findings to other traits, we also tested BMI, HDLc and CRP for large region associations, with consistent results for CRP. Our results demonstrate the presence of large region joint associations and suggest these can be used to pinpoint weakly associated SNPs.

It is widely accepted that genetics influences a broad range of human traits and diseases, yet only a few genetic variants are known to determine these traits and their impact is modest. In this report, we made the hypothesis that combining information from a large number of genetic variants would help better explain how they together contribute to traits such as height. To do so, we first had to select a proper method to integrate large numbers of genetic variants in a single test, here named “large region joint association”. Next, we tested our method on height in 3,740 European participants from the Health and Retirement Study. We showed that the contribution of regional associations to variation in height was 17.2%, as compared to the 12.9% explained by known genetic determinants of height. In other words, the joint effect of multiple genetic variants integrated together contributed to a substantial fraction of the genetics of height. These results are significant because they can help identify new genes or genetic regions associated with human traits or diseases. Conversely, these results can be used to better understand genes that we already know are associated. Furthermore, our results provide insights on how traits are genetically determined.

Medical nutrition therapy is the essential cornerstone for effective treatment of "refractory" severe hypertriglyceridemia regardless of pharmaceutical treatment: Evidence from a Lipid Management Program

BACKGROUND

Patients with refractory severe hypertriglyceridemia are at risk of pancreatitis and cardiovascular disease. The role of individualized nutrition therapy in these patients independent of pharmaceutical treatment has not been documented.

OBJECTIVE

To document the effect of nutrition intervention on severe hypertriglyceridemia regardless of medication status or prior nutrition counseling.

METHODS

Outcomes of new patients with triglycerides ≥ 500 mg/dL presenting to a Lipid Management Program over a 6-year period were tracked. Patients received comprehensive laboratory assessment, nutrition assessment, and initiation of an individualized diet intervention before seeing the lipidologist. Clinical and behavioral outcomes were recorded.

RESULTS

In all, 168 patients (117 men; mean age, 49.03 ± 11.22 years; body mass index, 32.61 ± 5.85 kg/m(2); 110 (65.5%) on lipid-lowering medications) returned for assessment of nutrition intervention. Triglycerides were reduced from median (interquartile range) 961.5 (611.5-1785.3) to 493.0 (337-736.3) mg/dL (P < .0001 for log transformation of triglycerides). There was no difference in median percentage reduction in triglycerides after nutrition intervention between those not on lipid-lowering medication, on a fibric acid derivative, on other lipid-lowering medication, or on a combination of lipid-lowering medications (P = .376) in a median (interquartile range) of 5 (3-7) weeks. Effect was independent of prior nutrition counseling (P = .260). Reported percentage fat in the diet at second visit correlated with log-transformed triglycerides achieved, independent of initial triglycerides level (r = 0.290; P = .001).

CONCLUSIONS

Individualized nutrition therapy results in changes in eating behavior and reductions in triglyceride levels in patients with refractory severe hypertriglyceridemia independent of lipid-lowering medication(s) and prior nutrition counseling.

PCSK9 variation and association with blood pressure in African Americans: preliminary findings from the HyperGEN and REGARDS studies

Proprotein convertase subtilisin/kexin type 9 (encoded by PCSK9) plays a well-known role in the regulation of low-density lipoprotein (LDL) receptors, and an inhibitor of this enzyme is a promising new therapeutic for hyperlipidemia. Recently, animal and human studies also implicate PCSK9 genetic variation in the regulation of blood pressure. The goal of this study was to examine if common and rare polymorphisms in PCSK9 are associated with blood pressure in an African-American population at high risk for cardiovascular disease. Using genomic data assayed on the Affymetrix 6.0 array (n = 1199) and the Illumina HumanExome Beadchip (n = 1966) from the Hypertension Genetic Epidemiology Network (HyperGEN), we tested the association of PCSK9 polymorphisms with blood pressure. We used linear mixed models and the sequence kernel association test (SKAT) to assess the association of 31 common and 19 rare variants with blood pressure. The models were adjusted for age, sex, center, smoking status, principal components for ancestry and diabetes as fixed effects and family as a random effect. The results showed a marginally significant effect of two genome-wide association study (GWAS) single-nucleotide polymorphisms (SNPs) (rs12048828: β = 1.8, P = 0.05 and rs9730100: β = 1.0, P = 0.05) with diastolic blood pressure (DBP); however these results were not significant after correction for multiple testing. Rare variants were cumulatively associated with DBP (P = 0.04), an effect that was strengthened by restriction to non-synonymous or stop-gain SNPs (P = 0.02). While gene-based results for DBP did not replicate (P = 0.36), we found an association with SBP (P = 0.04) in the Reasons for Geographic And Racial Differences in Stroke study (REGARDS). The findings here suggest rare variants in PCSK9 may influence blood pressure among African Americans, laying the ground work for further validation studies.

Abundant genetic overlap between blood lipids and immune-mediated diseases indicates shared molecular genetic mechanisms

Epidemiological studies suggest a relationship between blood lipids and immune-mediated diseases, but the nature of these associations is not well understood. We used genome-wide association studies (GWAS) to investigate shared single nucleotide polymorphisms (SNPs) between blood lipids and immune-mediated diseases. We analyzed data from GWAS (n~200,000 individuals), applying new False Discovery Rate (FDR) methods, to investigate genetic overlap between blood lipid levels [triglycerides (TG), low density lipoproteins (LDL), high density lipoproteins (HDL)] and a selection of archetypal immune-mediated diseases (Crohn’s disease, ulcerative colitis, rheumatoid arthritis, type 1 diabetes, celiac disease, psoriasis and sarcoidosis). We found significant polygenic pleiotropy between the blood lipids and all the investigated immune-mediated diseases. We discovered several shared risk loci between the immune-mediated diseases and TG (n = 88), LDL (n = 87) and HDL (n = 52). Three-way analyses differentiated the pattern of pleiotropy among the immune-mediated diseases. The new pleiotropic loci increased the number of functional gene network nodes representing blood lipid loci by 40%. Pathway analyses implicated several novel shared mechanisms for immune pathogenesis and lipid biology, including glycosphingolipid synthesis (e.g. FUT2) and intestinal host-microbe interactions (e.g. ATG16L1). We demonstrate a shared genetic basis for blood lipids and immune-mediated diseases independent of environmental factors. Our findings provide novel mechanistic insights into dyslipidemia and immune-mediated diseases and may have implications for therapeutic trials involving lipid-lowering and anti-inflammatory agents.

ABO blood group in relation to plasma lipids and proprotein convertase subtilisin/kexin type 9

BACKGROUND AND AIMS

Proprotein convertase subtilisin/kexin type 9 (PCSK9), a newly-identified member that plays an essential role in cholesterol homeostasis and holds decent promise for hyperlipidemia and coronary artery disease (CAD) treatment. However, the determining factors of PCSK9 are not well-characterized. It is well established that ABO blood group is associated with cholesterol metabolism. Therefore, the relationship between ABO blood groups and plasma PCSK9 level was examined.

METHODS AND RESULTS

A group of 507 consecutive patients undergoing diagnostic or interventional coronary angiography were enrolled in this cross-sectional study. The baseline clinical characteristics were collected, and the plasma PCSK9 levels were determined using ELISA. As a result, subjects of non-O type had higher levels of total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), non high density lipoprotein cholesterol (NHDL-C), apolipoprotein B (apo B), and PCSK9 compared with that of O type (p < 0.05, all). PCSK9 levels were significantly and positively related to TC, LDL, NHDL-C, and apo B (r = 0.253, p < 0.001; r = 0.262, p < 0.001; r = 0.215, p < 0.001; r = 0.187, p < 0.001; respectively). Multivariable regression analysis revealed that ABO group was significantly and independently associated with PCSK9 level (β = 7.91, p = 0.009). Additionally, mediation analysis indicated that ≈8%-19% of the effect of ABO blood group on PCSK9 levels was mediated by TC, LDL-C or NHDL-C levels.

CONCLUSIONS

These data firstly suggested that the ABO blood group might be a significant determinant factor for plasma PCSK9 level. It is also possible that the observed association between PCSK9 and ABO blood group might be in part involved in their CAD susceptibility.

Gene-environment interaction in dyslipidemia

PURPOSE OF REVIEW

Recent genome-wide association studies have identified numerous common genetic variants associated with plasma lipid traits and have provided new insights into the regulation of lipoprotein metabolism including the identification of novel biological processes. These findings add to a body of existing data on dietary and environmental factors affecting plasma lipids. Here we explore how interactions between genetic risk factors and other phenotypes may explain some of the missing heritability of plasma lipid traits.

RECENT FINDINGS

Recent studies have identified true statistical interaction between several environmental and genetic risk factors and their effects on plasma lipid fractions. These include interactions between behaviors such as smoking or exercise as well as specific dietary nutrients and the effect size of specific genetic variants on plasma lipid traits risk and modifying effects of measures of adiposity on the cumulative impact of a number of common genetic variants on each of plasma triglycerides and HDL cholesterol.

SUMMARY

Interactions between genetic risk factors and clinical phenotypes may account for some of the unexplained heritability of plasma lipid traits. Recent studies provide biological insight into specific genetic associations and may aid in the identification of dyslipidemic patients for whom specific lifestyle interventions are likely to be most effective.

Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: a Mendelian randomisation analysis

BACKGROUND

To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation.

METHODS

We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453,411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746,171 total participants).

FINDINGS

For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0.22 SD (95% CI 0.18-0.25; 12.5%; p = 9.3 × 10(-33)), concentrations of interleukin 6 decreased by 0.02 SD (-0.04 to -0.01; -1.7%; p = 3.5 × 10(-3)), and concentrations of C-reactive protein decreased by 0.03 SD (-0.04 to -0.02; -3.4%; p = 7.7 × 10(-14)). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1.15 (1.08-1.22; p = 1.8 × 10(-6)) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1.03 (1.02-1.04; p = 3.9 × 10(-10)). Per-allele odds ratios were 0.97 (0.95-0.99; p = 9.9 × 10(-4)) for rheumatoid arthritis, 0.99 (0.97-1.01; p = 0.47) for type 2 diabetes, 1.00 (0.98-1.02; p = 0.92) for ischaemic stroke, and 1.08 (1.04-1.12; p = 1.8 × 10(-5)) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk.

INTERPRETATION

Human genetic data suggest that long-term dual IL-1α/β inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations.

Next-generation gene discovery for variants of large impact on lipid traits

PURPOSE OF REVIEW

Detection of high-impact variants on lipid traits is complicated by complex genetic architecture. Although genome-wide association studies (GWAS) successfully identified many novel genes associated with lipid traits, it was less successful in identifying variants with a large impact on the phenotype. This is not unexpected, as the more common variants detectable by GWAS typically have small effects. The availability of large familial datasets and sequence data has changed the paradigm for successful genomic discovery of the novel genes and pathogenic variants underlying lipid disorders.

RECENT FINDINGS

Novel loci with large effects have been successfully mapped in families, and next-generation sequencing allowed for the identification of the underlying lipid-associated variants of large effect size. The success of this strategy relies on the simplification of the underlying genetic variation by focusing on large single families segregating extreme lipid phenotypes.

SUMMARY

Rare, high-impact variants are expected to have large effects and be more relevant for medical and pharmaceutical applications. Family data have many advantages over population-based data because they allow for the efficient detection of high-impact variants with an exponentially smaller sample size and increased power for follow-up studies.

Identifying functional noncoding variants from genome-wide association studies for cardiovascular disease and related traits

PURPOSE OF REVIEW

Genome-wide association studies have identified many novel loci for cardiovascular disease and related traits. Attention is now shifting towards the analysis of these loci for causal variants, with a view to identify the novel mechanisms leading to disease.

RECENT FINDINGS

This review focuses on the approaches to identify causal, noncoding variants for coronary artery disease, lipid traits and other cardiovascular risk factors. Fine-mapping studies are discussed, along with the novel statistical approaches to produce 'credible sets'. The use of combining genome-wide association study datasets with experimental methods such as expression quantitative trait loci and allele-specific chromatin accessibility are explored, with recent examples discussed. Mapping long-range chromatin interactions and evolving genome-editing technologies such as clustered regularly interspaced short palindromic repeats combined with clustered regularly interspaced short palindromic repeats-associated (Cas9) nuclease promise to aid considerably the search for causal variants.

SUMMARY

Identification of causal variants for cardiovascular disease and related traits is still in the early stages, but with technologies evolving and increasingly relevant tissue samples undergoing analysis, there are favourable prospects that many new mechanisms for disease will be uncovered by the end of this decade.

Recent developments in genome and exome-wide analyses of plasma lipids

PURPOSE OF REVIEW

Genome-wide association scans (GWAS) have identified over 100 human loci associated with variation in lipids. The identification of novel genes and variants that affect lipid levels is made possible by next-generation sequencing, rare variant discovery and analytic advances. The current status of the genetic basis of lipid traits will be presented.

RECENT FINDINGS

Expansion of GWAS sample sizes for lipid traits has not substantially increased the proportion of trait variance explained by common genetic variants (less than 15% of trait variation captured). Although GWAS has discovered novel loci and pathways with putative biological function and impact on cardiovascular disease risk, discovery of the genes in these loci remains challenging. Exome sequencing promises to identify genes with protein-coding variants with a large impact on lipids, as shown for LDL-cholesterol levels associated with novel (PNPLA5) and known (LDLR, PCSK9, APOB) genes.

SUMMARY

Current results have increased our understanding of the genetic architecture of lipids, expanding the range of effect and frequency for variants identified for lipid traits. Identification of novel lipid-associated gene variants, even if small in effect or rare in the population, could provide important novel drug targets and biological pathways for dyslipidemia.

Genetic Variations in MicroRNA-Binding Sites Affect MicroRNA-Mediated Regulation of Several Genes Associated With Cardio-metabolic Phenotypes

BACKGROUND

Genome-wide association studies enabled us to discover a large number of variants and genomic loci contributing to cardiovascular and metabolic disorders. However, because the vast majority of the identified variants are thought to merely be proxies for other functional variants, the causal mechanisms remain to be elucidated. We hypothesized that the part of the functional variants involved in deregulating cardiometabolic genes is located in microRNA (miRNA)-binding sites.

METHODS AND RESULTS

Using the largest genome-wide association studies available on glycemic indices, lipid traits, anthropometric measures, blood pressure, coronary artery diseases, and type 2 diabetes mellitus, we identified 11,067 variants that are associated with cardiometabolic phenotypes. Of these, 230 variants are located within miRNA-binding sites in the 3'-untranslated region of 155 cardiometabolic genes. Thirty-seven of 230 variants were found to fulfill our predefined criteria for being functional in their genomic loci. Ten variants were subsequently selected for experimental validation based on genome-wide association studies results, expression quantitative trait loci (eQTL) analyses, and coexpression of their host genes and regulatory miRNAs in relevant tissues. Luciferase reporter assays revealed an allele-specific regulation of genes hosting the variants by miRNAs. These cotransfection experiments showed that rs174545 (FADS1:miR-181a-2), rs1059611 (LPL:miR-136), rs13702 (LPL:miR-410), rs1046875 (FN3KRP:miR-34a), rs7956 (MKRN2:miR-154), rs3217992 (CDKN2B:miR-138-2-3p), and rs11735092 (HSD17B13:miR-375) decrease or abrogate miRNA-dependent regulation of the genes. Conversely, 2 variants, rs6857 (PVRL2:miR-320e) and rs907091 (IKZF3:miR-326), were shown to enhance the activity of miRNAs on their host genes.

CONCLUSIONS

We provide evidence for a model in which polymorphisms in miRNA-binding sites can both positively and negatively affect miRNA-mediated regulation of cardiometabolic genes.

Association of genetic variants with dyslipidemia and chronic kidney disease in a longitudinal population-based genetic epidemiological study

We previously identified 9 genes and chromosomal region 3q28 as susceptibility loci for myocardial infarction, ischemic stroke, or chronic kidney disease (CKD) in Japanese individuals by genome-wide or candidate gene association studies. In the present study, we examined the association of 13 polymorphisms at these 10 loci with the prevalence of hypertriglyceridemia, hyper-low-density lipoprotein (LDL) cholesterolemia, hypo-high-density lipoprotein (HDL) cholesterolemia, or CKD in community-dwelling Japanese individuals. The study subjects comprised 6,027 individuals who were recruited to the Inabe Health and Longevity Study, a longitudinal genetic epidemiological study of atherosclerotic, cardiovascular and metabolic diseases. The subjects were recruited from individuals who visited the Health Care Center at Inabe General Hospital for an annual health checkup, and they were followed up each year (mean follow‑up period, 5 years). Longitudinal analysis with a generalized estimating equation and with adjustment for covariates revealed that rs6929846 of butyrophilin, subfamily 2, member A1 gene (BTN2A1) was significantly associated with the prevalence of hypertriglyceridemia (P=0.0001), hyper-LDL cholesterolemia (P=0.0004), and CKD (P=0.0007); rs2569512 of interleukin enhancer binding factor 3 (ILF3) was associated with hyper-LDL cholesterolemia (P=0.0029); and rs2074379 (P=0.0019) and rs2074388 (P=0.0029) of alpha-kinase 1 (ALPK1) were associated with CKD. Longitudinal analysis with a generalized linear mixed-effect model and with adjustment for covariates among all individuals revealed that rs6929846 of BTN2A1 was significantly associated with the serum concentrations of triglycerides (P=0.0011), LDL cholesterol (P=3.3 x 10(-5)), and creatinine (P=0.0006), as well as with the estimated glomerular filtration rate (eGFR) (P=0.0004); rs2569512 of ILF3 was shown to be associated with the serum concentration of LDL cholesterol (P=0.0221); and rs2074379 (P=0.0302) and rs2074388 (P=0.0336) of ALPK1 were shown to be associated with the serum concentration of creatinine. Similar analysis among individuals not taking any anti‑dyslipidemic medication revealed that rs6929846 of BTN2A1 was significantly associated with the serum concentrations of triglycerides (P=8.3 x 10‑5) and LDL cholesterol (P=0.0004), and that rs2569512 of ILF3 was associated with the serum concentration of LDL cholesterol (P=0.0010). BTN2A1 may thus be a susceptibility gene for hypertriglyceridemia, hyper‑LDL cholesterolemia and CKD in Japanese individuals.

Effect of naturally random allocation to lower low-density lipoprotein cholesterol on the risk of coronary heart disease mediated by polymorphisms in NPC1L1, HMGCR, or both: a 2 × 2 factorial Mendelian randomization study

BACKGROUND

Considerable uncertainty exists as to whether lowering low-density lipoprotein cholesterol (LDL-C) by inhibiting the Niemann-Pick C1-Like 1 (NPC1L1) receptor with ezetimibe, either alone or in combination with a 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibitor (statin), will reduce the risk of coronary heart disease (CHD).

OBJECTIVES

This study evaluated the effect of naturally random allocation to lower LDL-C mediated by polymorphisms in the NPC1L1 gene (target of ezetimibe), the HMGCR gene (target of statins), or both (target of combination therapy) on the risk of CHD.

METHODS

We constructed NPC1L1 and HMGCR genetic LDL-C scores to naturally randomize participants into 4 groups: reference, lower LDL-C mediated by NPC1L1 polymorphisms, lower LDL-C mediated by HMGCR polymorphisms, or lower LDL-C mediated by polymorphisms in both NPC1L1 and HMGCR. We compared the risk of CHD (fatal or nonfatal myocardial infarction) among each group using a 2 × 2 factorial mendelian randomization study design.

RESULTS

A total of 108,376 persons (10,464 CHD events) from 14 studies were included. There were no significant differences in baseline characteristics among the 4 groups, thus confirming that allocation was random. Compared to the reference group, the NPC1L1 group had 2.4 mg/dl lower LDL-C and 4.8% lower risk of CHD (odds ratio [OR]: 0.952, 95% confidence interval [CI]: 0.920 to 0.985); whereas the HMGCR group had 2.9 mg/dl lower LDL-C and a similar 5.3% lower risk of CHD (OR: 0.947, 95% CI: 0.909 to 0.986). The group with lower LDL-C mediated by both NPC1L1 and HMGCR polymorphisms had 5.8 mg/dl additively lower LDL-C and a 10.8% log-linearly additive lower risk of CHD (OR: 0.892, 95% CI: 0.854 to 0.932).

CONCLUSIONS

The effect of lower LDL-C on the risk of CHD mediated by polymorphisms in NPC1L1, HMGCR, or both is approximately the same per unit lower LDL-C and log-linearly proportional to the absolute exposure to lower LDL-C.

Genome of The Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10⁻⁴), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (β_LDL-C=0.135, β_TC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

Frequencies of rare variants fluctuate over populations, hampering gene discovery. Here the authors use a population-specific reference panel, the Genome of the Netherlands, to discover four novel loci involved in lipid metabolism, including an exonic variant in ABCA6.

Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors?

Clustering of obesity, coronary artery disease, and cardiovascular disease risk factors is observed in epidemiological studies and clinical settings. Twin and family studies have provided some supporting evidence for the clustering hypothesis. Loci nearest a lead single nucleotide polymorphism (SNP) showing genome-wide significant associations with coronary artery disease, body mass index, C-reactive protein, blood pressure, lipids, and type 2 diabetes mellitus were selected for pathway and network analyses. Eighty-seven autosomal regions (181 SNPs), mapping to 56 genes, were found to be pleiotropic. Most pleiotropic regions contained genes associated with coronary artery disease and plasma lipids, whereas some exhibited coaggregation between obesity and cardiovascular disease risk factors. We observed enrichment for liver X receptor (LXR)/retinoid X receptor (RXR) and farnesoid X receptor/RXR nuclear receptor signaling among pleiotropic genes and for signatures of coronary artery disease and hepatic steatosis. In the search for functionally interacting networks, we found that 43 pleiotropic genes were interacting in a network with an additional 24 linker genes. ENCODE (Encyclopedia of DNA Elements) data were queried for distribution of pleiotropic SNPs among regulatory elements and coding sequence variations. Of the 181 SNPs, 136 were annotated to ≥ 1 regulatory feature. An enrichment analysis found over-representation of enhancers and DNAse hypersensitive regions when compared against all SNPs of the 1000 Genomes pilot project. In summary, there are genomic regions exerting pleiotropic effects on cardiovascular disease risk factors, although only a few included obesity. Further studies are needed to resolve the clustering in terms of DNA variants, genes, pathways, and actionable targets.

IRF4, MC1R and TYR genes are risk factors for actinic keratosis independent of skin color

Actinic keratosis (AK) is a pre-malignant skin disease, highly prevalent in elderly Europeans. This study investigates genetic susceptibility to AK with a genome-wide association study (GWAS). A full body skin examination was performed in 3194 elderly individuals from the Rotterdam Study (RS) of exclusive north-western European origin (aged 51-99 years, 45% male). Physicians graded the number of AK into four severity levels: none (76%), 1-3 (14%), 4-9 (6%) and ≥10 (5%), and skin color was quantified using a spectrophotometer on sun-unexposed skin. A GWAS for AK severity was conducted, where promising signals at IRF4 and MC1R (P < 4.2 × 10(-7)) were successfully replicated in an additional cohort of 623 RS individuals (IRF4, rs12203592, Pcombined = 6.5 × 10(-13) and MC1R, rs139810560, Pcombined = 4.1 × 10(-9)). Further, in an analysis of ten additional well-known human pigmentation genes, TYR also showed significant association with AK (rs1393350, P = 5.3 × 10(-4)) after correction for multiple testing. Interestingly, the strength and significance of above-mentioned associations retained largely the same level after skin color adjustment. Overall, our data strongly suggest that IRF4, MC1R and TYR genes likely have pleiotropic effects, a combination of pigmentation and oncogenic functions, resulting in an increased risk of AK.