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Lack of genetic support for shared aetiology of Coronary Artery Disease and Late-onset Alzheimer's disease.
Epidemiological studies suggest a positive association between coronary artery disease (CAD) and late-onset Alzheimer's disease (LOAD). This large-scale genetic study brings together 'big data' resources to examine the causal impact of genetic determinants of CAD on risk of LOAD. A two-sample Mendelian randomization approach was adopted to estimate the causal effect of CAD on risk of LOAD using summary data from 60,801 CAD cases from CARDIoGRAMplusC4D and 17,008 LOAD cases from the IGAP Consortium. Additional analyses assessed the independent relevance of genetic associations at the APOE locus for both CAD and LOAD. Higher genetically determined risk of CAD was associated with a slightly higher risk of LOAD (Odds Ratio (OR) per log-odds unit of CAD [95% CI]: 1.07 [1.01-1.15]; p = 0.027). However, after exclusion of the APOE locus, the estimate of the causal effect of CAD for LOAD was attenuated and no longer significant (OR 0.94 [0.88-1.01]; p = 0.072). This Mendelian randomization study indicates that the APOE locus is the chief determinant of shared genetic architecture between CAD and LOAD, and suggests a lack of causal relevance of CAD for risk of LOAD after exclusion of APOE.
Genetically determined height and coronary artery disease.
BACKGROUND:The nature and underlying mechanisms of an inverse association between adult height and the risk of coronary artery disease (CAD) are unclear. METHODS:We used a genetic approach to investigate the association between height and CAD, using 180 height-associated genetic variants. We tested the association between a change in genetically determined height of 1 SD (6.5 cm) with the risk of CAD in 65,066 cases and 128,383 controls. Using individual-level genotype data from 18,249 persons, we also examined the risk of CAD associated with the presence of various numbers of height-associated alleles. To identify putative mechanisms, we analyzed whether genetically determined height was associated with known cardiovascular risk factors and performed a pathway analysis of the height-associated genes. RESULTS:We observed a relative increase of 13.5% (95% confidence interval [CI], 5.4 to 22.1; P<0.001) in the risk of CAD per 1-SD decrease in genetically determined height. There was a graded relationship between the presence of an increased number of height-raising variants and a reduced risk of CAD (odds ratio for height quartile 4 versus quartile 1, 0.74; 95% CI, 0.68 to 0.84; P<0.001). Of the 12 risk factors that we studied, we observed significant associations only with levels of low-density lipoprotein cholesterol and triglycerides (accounting for approximately 30% of the association). We identified several overlapping pathways involving genes associated with both development and atherosclerosis. CONCLUSIONS:There is a primary association between a genetically determined shorter height and an increased risk of CAD, a link that is partly explained by the association between shorter height and an adverse lipid profile. Shared biologic processes that determine achieved height and the development of atherosclerosis may explain some of the association. (Funded by the British Heart Foundation and others.).
A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease.
Genome-wide association studies have identified 11 common variants convincingly associated with coronary artery disease (CAD)¹⁻⁷, a modest number considering the apparent heritability of CAD⁸. All of these variants have been discovered in European populations. We report a meta-analysis of four large genome-wide association studies of CAD, with ∼575,000 genotyped SNPs in a discovery dataset comprising 15,420 individuals with CAD (cases) (8,424 Europeans and 6,996 South Asians) and 15,062 controls. There was little evidence for ancestry-specific associations, supporting the use of combined analyses. Replication in an independent sample of 21,408 cases and 19,185 controls identified five loci newly associated with CAD (P < 5 × 10⁻⁸ in the combined discovery and replication analysis): LIPA on 10q23, PDGFD on 11q22, ADAMTS7-MORF4L1 on 15q25, a gene rich locus on 7q22 and KIAA1462 on 10p11. The CAD-associated SNP in the PDGFD locus showed tissue-specific cis expression quantitative trait locus effects. These findings implicate new pathways for CAD susceptibility.
Low-frequency and common genetic variation in ischemic stroke: The METASTROKE collaboration.
OBJECTIVE:To investigate the influence of common and low-frequency genetic variants on the risk of ischemic stroke (all IS) and etiologic stroke subtypes. METHODS:We meta-analyzed 12 individual genome-wide association studies comprising 10,307 cases and 19,326 controls imputed to the 1000 Genomes (1 KG) phase I reference panel. We selected variants showing the highest degree of association (p < 1E-5) in the discovery phase for replication in Caucasian (13,435 cases and 29,269 controls) and South Asian (2,385 cases and 5,193 controls) samples followed by a transethnic meta-analysis. We further investigated the p value distribution for different bins of allele frequencies for all IS and stroke subtypes. RESULTS:We showed genome-wide significance for 4 loci: ABO for all IS, HDAC9 for large vessel disease (LVD), and both PITX2 and ZFHX3 for cardioembolic stroke (CE). We further refined the association peaks for ABO and PITX2. Analyzing different allele frequency bins, we showed significant enrichment in low-frequency variants (allele frequency <5%) for both LVD and small vessel disease, and an enrichment of higher frequency variants (allele frequency 10% and 30%) for CE (all p < 1E-5). CONCLUSIONS:Our findings suggest that the missing heritability in IS subtypes can in part be attributed to low-frequency and rare variants. Larger sample sizes are needed to identify the variants associated with all IS and stroke subtypes.
Meta analysis of candidate gene variants outside the LPA locus with Lp(a) plasma levels in 14,500 participants of six White European cohorts
Background: Both genome-wide association studies and candidate gene studies have reported that the major determinant of plasma levels of the Lipoprotein (a) [Lp(a)] reside within the LPA locus on chromosome 6. We have used data from the HumanCVD BeadChip to explore the contribution of other candidate genes determining Lp(a) levels. Methods: 48,032 single nucleotide polymorphisms (SNPs) from the Illumina HumanCVD BeadChip were genotyped in 5059 participants of the Whitehall II study (WHII) of randomly ascertained healthy men and women. SNPs showing association with Lp(a) levels of p<10 -4 outside the LPA locus were selected for replication in a total of an additional 9463 participants of five European based studies (EAS, EPIC-Norfolk, NPHSII, PROCARDIS, and SAPHIR). Results: In Whitehall II, apart from the LPA locus (where p values for several SNPs were <10 -30) there was significant association at four loci GALNT2, FABP1, PPARGC1A and TNFRSFF11A. However, a meta-analysis of the six studies did not confirm any of these findings. Conclusion: Results from this meta analysis of 14,522 participants revealed no candidate genes from the HumanCVD BeadChip outside the LPA locus to have an effect on Lp(a) levels. Further studies with genome-wide and denser SNP coverage are required to confirm or refute this finding. © 2011 Elsevier Ireland Ltd.
No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.
In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.
Identification of additional risk loci for stroke and small vessel disease: a meta-analysis of genome-wide association studies.
BACKGROUND:Genetic determinants of stroke, the leading neurological cause of death and disability, are poorly understood and have seldom been explored in the general population. Our aim was to identify additional loci for stroke by doing a meta-analysis of genome-wide association studies. METHODS:For the discovery sample, we did a genome-wide analysis of common genetic variants associated with incident stroke risk in 18 population-based cohorts comprising 84 961 participants, of whom 4348 had stroke. Stroke diagnosis was ascertained and validated by the study investigators. Mean age at stroke ranged from 45·8 years to 76·4 years, and data collection in the studies took place between 1948 and 2013. We did validation analyses for variants yielding a significant association (at p<5 × 10(-6)) with all-stroke, ischaemic stroke, cardioembolic ischaemic stroke, or non-cardioembolic ischaemic stroke in the largest available cross-sectional studies (70 804 participants, of whom 19 816 had stroke). Summary-level results of discovery and follow-up stages were combined using inverse-variance weighted fixed-effects meta-analysis, and in-silico lookups were done in stroke subtypes. For genome-wide significant findings (at p<5 × 10(-8)), we explored associations with additional cerebrovascular phenotypes and did functional experiments using conditional (inducible) deletion of the probable causal gene in mice. We also studied the expression of orthologs of this probable causal gene and its effects on cerebral vasculature in zebrafish mutants. FINDINGS:We replicated seven of eight known loci associated with risk for ischaemic stroke, and identified a novel locus at chromosome 6p25 (rs12204590, near FOXF2) associated with risk of all-stroke (odds ratio [OR] 1·08, 95% CI 1·05-1·12, p=1·48 × 10(-8); minor allele frequency 21%). The rs12204590 stroke risk allele was also associated with increased MRI-defined burden of white matter hyperintensity-a marker of cerebral small vessel disease-in stroke-free adults (n=21 079; p=0·0025). Consistently, young patients (aged 2-32 years) with segmental deletions of FOXF2 showed an extensive burden of white matter hyperintensity. Deletion of Foxf2 in adult mice resulted in cerebral infarction, reactive gliosis, and microhaemorrhage. The orthologs of FOXF2 in zebrafish (foxf2b and foxf2a) are expressed in brain pericytes and mutant foxf2b(-/-) cerebral vessels show decreased smooth muscle cell and pericyte coverage. INTERPRETATION:We identified common variants near FOXF2 that are associated with increased stroke susceptibility. Epidemiological and experimental data suggest that FOXF2 mediates this association, potentially via differentiation defects of cerebral vascular mural cells. Further expression studies in appropriate human tissues, and further functional experiments with long follow-up periods are needed to fully understand the underlying mechanisms. FUNDING:NIH, NINDS, NHMRC, CIHR, European national research institutions, Fondation Leducq.
Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation.
Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery.
Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.
Stroke has multiple etiologies, but the underlying genes and pathways are largely unknown. We conducted a multiancestry genome-wide-association meta-analysis in 521,612 individuals (67,162 cases and 454,450 controls) and discovered 22 new stroke risk loci, bringing the total to 32. We further found shared genetic variation with related vascular traits, including blood pressure, cardiac traits, and venous thromboembolism, at individual loci (n = 18), and using genetic risk scores and linkage-disequilibrium-score regression. Several loci exhibited distinct association and pleiotropy patterns for etiological stroke subtypes. Eleven new susceptibility loci indicate mechanisms not previously implicated in stroke pathophysiology, with prioritization of risk variants and genes accomplished through bioinformatics analyses using extensive functional datasets. Stroke risk loci were significantly enriched in drug targets for antithrombotic therapy.
Publisher Correction: Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Association between C reactive protein and coronary heart disease: mendelian randomisation analysis based on individual participant data.
To use genetic variants as unconfounded proxies of C reactive protein concentration to study its causal role in coronary heart disease. Mendelian randomisation meta-analysis of individual participant data from 47 epidemiological studies in 15 countries. 194418 participants, including 46557 patients with prevalent or incident coronary heart disease. Information was available on four CRP gene tagging single nucleotide polymorphisms (rs3093077, rs1205, rs1130864, rs1800947), concentration of C reactive protein, and levels of other risk factors. Risk ratios for coronary heart disease associated with genetically raised C reactive protein versus risk ratios with equivalent differences in C reactive protein concentration itself, adjusted for conventional risk factors and variability in risk factor levels within individuals. CRP variants were each associated with up to 30% per allele difference in concentration of C reactive protein (P<10(-34)) and were unrelated to other risk factors. Risk ratios for coronary heart disease per additional copy of an allele associated with raised C reactive protein were 0.93 (95% confidence interval 0.87 to 1.00) for rs3093077; 1.00 (0.98 to 1.02) for rs1205; 0.98 (0.96 to 1.00) for rs1130864; and 0.99 (0.94 to 1.03) for rs1800947. In a combined analysis, the risk ratio for coronary heart disease was 1.00 (0.90 to 1.13) per 1 SD higher genetically raised natural log (ln) concentration of C reactive protein. The genetic findings were discordant with the risk ratio observed for coronary heart disease of 1.33 (1.23 to 1.43) per 1 SD higher circulating ln concentration of C reactive protein in prospective studies (P=0.001 for difference). Human genetic data indicate that C reactive protein concentration itself is unlikely to be even a modest causal factor in coronary heart disease.
Genome-wide meta-analysis identifies 3 novel loci associated with stroke.
We conducted a European-only and transancestral genome-wide association meta-analysis in 72,147 stroke patients and 823,869 controls using data from UK Biobank (UKB) and the MEGASTROKE consortium. We identified an exonic polymorphism in NOS3 (rs1799983, p.Glu298Asp; p = 2.2E-8, odds ratio [OR] = 1.05, 95% confidence interval [CI] = 1.04-1.07) and variants in an intron of COL4A1 (rs9521634; p = 3.8E-8, OR = 1.04, 95% CI = 1.03-1.06) and near DYRK1A (rs720470; p = 6.1E-9, OR = 1.05, 95% CI = 1.03-1.07) at genome-wide significance for stroke. Effect sizes of known stroke loci were highly correlated between UKB and MEGASTROKE. Using Mendelian randomization, we further show that genetic variation in the nitric oxide synthase-nitric oxide pathway in part affects stroke risk via variation in blood pressure. Ann Neurol 2018;84:934-939.
Mendelian randomization with fine-mapped genetic data: Choosing from large numbers of correlated instrumental variables.
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences.
Pharmacogenomics of statin therapy: any new insights in efficacy or safety?
To examine the current evidence concerning the effects of genetic variation on statin-related low-density lipoprotein cholesterol reductions, clinical efficacy, and adverse events and the relevance for patient care.Recent years have seen the emergence of large-scale genetic experiments, including genome-wide association studies and candidate gene studies, exploring the impact of common genetic variation on patient response to statins. These studies have built on previous smaller scale evidence, providing improved statistical power and enhanced ability to explore the genome. Current evidence suggests that common genetic variants do not alter low-density lipoprotein cholesterol response by more than a few percent, or materially alter the effect of statin on vascular risk reduction, and therefore that patients benefit from statins independent of common genetic variation. However, knowledge of SLCO1B1 genotypes is believed to have clinical utility for predicting myopathy risk and ensuring that statins are prescribed as safely as possible. Furthermore, new hypothesis-generating studies, such as those associating GATM with myopathy risk, offer potential insights for the future.Common genetic variation does not appear to be an important determinant of statin response, with the exception of SLCO1B1 and risk of myopathy. Future studies will help to determine the impact of low-frequency and rare genetic variation on statin response.