scholarly journals GWAS of QRS Duration Identifies New Loci Specific to Hispanic/Latino Populations Swenson Hispanic/Latino QRS GWAS

2018 ◽  
Author(s):  
Brenton R. Swenson ◽  
Tin Louie ◽  
Henry J. Lin ◽  
Raú MéndezGiráldez ◽  
Jennifer E Below ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Integral Membrane Protein ◽  
Genome Wide Association Studies ◽  
Significance Threshold ◽  
Qrs Prolongation ◽  
Qrs Duration ◽  
Failure Prognosis

ABSTRACTBackgroundThe electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored.MethodsWe performed a GWAS of QRS duration among Hispanic/Latino ancestry populations (n=15,124) from four studies using 1000 Genomes imputed genotype data (adjusted for age, sex, global ancestry, clinical and study-specific covariates). Study-specific results were combined using fixed-effects, inverse variance-weighted meta-analysis.ResultsWe identified six loci associated with QRS (P<5×10−8), including two novel loci: MYOCD, a nuclear protein expressed in the heart, and SYT1, an integral membrane protein. The top association in the MYOCD locus, intronic SNP rs16946539, was found in Hispanics/Latinos with a minor allele frequency (MAF) of 0.04, but is monomorphic in European and African descent populations. The most significant QRS duration association was for intronic SNP rs3922344 (P= 8.56×10−26) in SCN5A/SCN10A. Three additional previously identified loci, CDKN1A, VTI1A, and HAND1, also exceeded the GWAS significance threshold among Hispanics/Latinos. A total of 27 of 32 previously identified QRS duration SNPs were shown to generalize in Hispanics/Latinos.ConclusionsOur QRS duration GWAS, the first in Hispanic/Latino populations, identified two new loci, underscoring the utility of extending large scale genomic studies to currently under-examined populations.

scholarly journals Understanding the genetic determinants of the brain with MOSTest

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Dennis van der Meer ◽  
Oleksandr Frei ◽  
Tobias Kaufmann ◽  
Alexey A. Shadrin ◽  
Anna Devor ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Computational Design ◽  
Brain Regions ◽  
Brain Morphology ◽  
Genome Wide Association Studies ◽  
Small Individual ◽  
Significance Threshold ◽  
Regional Brain ◽  
Genome Wide

Abstract Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects. This has proven challenging for genome-wide association studies (GWAS). Due to the distributed nature of genetic signal across brain regions, multivariate analysis of regional measures may enhance discovery of genetic variants. Current multivariate approaches to GWAS are ill-suited for complex, large-scale data of this kind. Here, we introduce the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable inference, and apply it to 171 regional brain morphology measures from 26,502 UK Biobank participants. At the conventional genome-wide significance threshold of α = 5 × 10−8, MOSTest identifies 347 genomic loci associated with regional brain morphology, more than any previous study, improving upon the discovery of established GWAS approaches more than threefold. Our findings implicate more than 5% of all protein-coding genes and provide evidence for gene sets involved in neuron development and differentiation.

scholarly journals Comment on ‘Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets’ by Lam et al.

2018 ◽  
Vol 21 (2) ◽  
pp. 84-88 ◽  
Author(s):  
W. David Hill
Keyword(s):  
Genetic Information ◽  
Drug Targets ◽  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Nootropic Drug ◽  
Genome Wide

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as ‘trait specific’ to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

scholarly journals Capturing SNP Association across the NK Receptor and HLA Gene Regions in Multiple Sclerosis by Targeted Penalised Regression Models

Genes ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 87
Author(s):  
Sean M. Burnard ◽  
Rodney A. Lea ◽  
Miles Benton ◽  
David Eccles ◽  
Daniel W. Kennedy ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Complex Traits ◽  
Multiple Testing ◽  
Large Scale ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Elastic Net ◽  
Genome Wide Association Studies ◽  
Multiple Testing Correction

Conventional genome-wide association studies (GWASs) of complex traits, such as Multiple Sclerosis (MS), are reliant on per-SNP p-values and are therefore heavily burdened by multiple testing correction. Thus, in order to detect more subtle alterations, ever increasing sample sizes are required, while ignoring potentially valuable information that is readily available in existing datasets. To overcome this, we used penalised regression incorporating elastic net with a stability selection method by iterative subsampling to detect the potential interaction of loci with MS risk. Through re-analysis of the ANZgene dataset (1617 cases and 1988 controls) and an IMSGC dataset as a replication cohort (1313 cases and 1458 controls), we identified new association signals for MS predisposition, including SNPs above and below conventional significance thresholds while targeting two natural killer receptor loci and the well-established HLA loci. For example, rs2844482 (98.1% iterations), otherwise ignored by conventional statistics (p = 0.673) in the same dataset, was independently strongly associated with MS in another GWAS that required more than 40 times the number of cases (~45 K). Further comparison of our hits to those present in a large-scale meta-analysis, confirmed that the majority of SNPs identified by the elastic net model reached conventional statistical GWAS thresholds (p < 5 × 10−8) in this much larger dataset. Moreover, we found that gene variants involved in oxidative stress, in addition to innate immunity, were associated with MS. Overall, this study highlights the benefit of using more advanced statistical methods to (re-)analyse subtle genetic variation among loci that have a biological basis for their contribution to disease risk.

Abstract 56: Fine-Mapping of Metabochip Lipid Regions in Global Populations Identifies Signals Unique to Hispanic Descent Populations and Refines Previously Identified Lipid Loci

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Niha Zubair ◽  
Mariaelisa Graff ◽  
Danyu Lin ◽  
Ani Manichaikul ◽  
Ida Chen ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Fixed Effects ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Ethnically Diverse ◽  
Lipid Lowering ◽  
Targeted Prevention ◽  
Genome Wide Association Studies ◽  
Functional Variants

INTRODUCTION: Genome wide association studies (GWAS) have identified over 150 loci associated with lipids traits. The majority of these GWAS were performed in European Americans (EA); no large-scale studies exist for Hispanic descent populations. Additionally, in many cases, the genetic architecture of these trait-influencing loci remains largely unknown. To address these gaps in knowledge, we performed one of the most ethnically diverse fine-mapping genetic studies on HDL-C, LDL-C, and triglycerides (TG) to-date. HYPOTHESIS: Here we aimed to identify variants with the strongest association at each locus, detect population-specific signals, and refine previously identified EA GWAS loci. METHODS: We used Metabochip data from African American (AA, ~21,000), Hispanic American (HA, ~20,000), Asian (AS, ~2,000), and Native American (NA, ~550) participants from the Population Architecture using Genomics and Epidemiology (PAGE) Study. We applied multiple linear regression models and assumed an additive mode of inheritance to test for association between genotypes and HDL-C, LDL-C, or log-transformed TG levels; lipid levels were corrected for lipid-lowering medication use. Model covariates included age, sex, and principal components of ancestry. We first conducted a meta-analysis within each ethnic group separately and then performed a combined trans-ethnic fixed effects meta-analysis. Significance was defined as p < 1 x 10 -6 ; equivalent to 0.05/ the mean number of variants at each Metabochip lipid locus. RESULTS: For HDL-C, 19 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, APOB, LIPC, STARD3, LIPG, and APOC1, have not been reported in EA. We identified a signal unique to HA at APOA5. In addition, we refined the set of candidate functional variants at PPP1R3B, LPL, and PLTP. For LDL-C, 16 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 5 of these loci, PCSK9, APOB, APOA5, CLIP2, and APOC1, have not been reported in EA. We identified a signal unique to HA at SLC22A1. In addition, we refined the set of candidate functional variants at TIMD4 and LDLR. For TG, 15 loci significantly associated in the trans-ethnic meta-analysis; the top signals at 3 of these loci, APOB, APOA5, and LIPC, have not been reported in EA. In addition, we refined the set of candidate functional variants at ANGPTL3, MLXIPL, PPP1R3B, and LPL. CONCLUSIONS: By taking advantage of the genetic architecture of ethnically diverse populations, we identified novel lipid-influencing variants in HA and refined the set of candidate functional variants at GWAS lipid loci. Anticipated conditional analyses will provide further insight into secondary and ethnic-specific signals. Our results can guide the creation of more informed risk models, which can then be used for targeted prevention efforts, especially for underrepresented populations.

Abstract 050: Meta-analysis of Genetic Associations in up to 339,224 Individuals Identify 66 New Loci for Bmi, Confirming a Neuronal Contribution to Body Weight Regulation and Implicating Several Novel Pathways

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Anne Justice ◽  
Kari North ◽  
Ruth Loos ◽  
Sailaja Vedantam ◽  
Felix Day ◽  
...  
Keyword(s):  
Risk Factors ◽  
Fixed Effects ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Genome Wide

Obesity is a rising global concern as it substantially contributes to cardiovascular disease (CVD) and CVD risk factors (e.g. insulin resistance, dyslipidemia, Type 2 Diabetes). BMI (body mass index) is an easily obtained measure of obesity, which is highly heritable, and often used as a proxy when searching for genetic risk factors. Previous analyses of genome-wide association studies (GWAS) in the GIANT (Genetic Investigation of ANthropometric Traits) Consortium identified 32 loci containing common variants associated with BMI in adults of European ancestry. To enhance discovery of common causal variants for BMI, GIANT has expanded to include 82 studies with GWAS data and 43 studies with Metabochip data in more ancestrally diverse populations including up to 339,224 individuals. We performed a meta-analysis of the study-specific summary statistics for the BMI associations, assuming an additive model and using a fixed-effects inverse variance method. SNPs in 97 loci reached genome-wide significance (P<10-8), of which 31 loci had previously been identified for BMI in European-descent samples. Of the 66 novel BMI loci, three had previously been identified for association with adiposity related traits in specific populations. Many of the 97 loci contain strong biological candidates, and multiple methods were employed to pinpoint the most likely candidate gene(s) within the main signal regions. In addition to manual curation, GRAIL, and MAGENTA, we also employed a newly developed, unbiased computational approach that integrates a variety of data types (i.e. tissue-specific gene expression data, phenotypic information from mouse knockout studies, etc.) to identify potentially causal genes and pathways. Consistent with previous findings, many of these BMI loci contain genes that have a potential neuronal role in regulating appetite (e.g. MC4R, POMC, GRID1, NAV1 ). Our analyses also highlight loci with genes in pathways that were previously less apparent, such as those related to glucose and insulin homeostasis ( TCF7L2 , GIPR ), lipid metabolism ( APOE -cluster, NPC1 , NR1H3 ), the immune system ( TLR4) , and others. Additionally, many of the newly associated variants are in high LD with previously identified SNPs associated with related phenotypes, including other CVD risk factors (e.g. SNPs nearby IRS1 associated with T2D, adiposity, HDL, TG, adiponectin levels, and CHD; and SNPs near NT5C2 associated with CHD and blood pressure variables). This large-scale meta-analysis has greatly increased the number of identified obesity-susceptibility loci and continues to contribute to our understanding of the complex biology of adiposity. Our results have highlighted overlapping GWAS signals and important pathways which connect BMI and other CVD risk factors supporting the importance of pleiotropic effects in the pathogenesis of common complex diseases.

scholarly journals Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: a genome–wide interaction study

2013 ◽  
Vol 20 (6) ◽  
pp. 875-887 ◽  
Author(s):  
Anja Rudolph ◽  
Rebecca Hein ◽  
Sara Lindström ◽  
Lars Beckmann ◽  
Sabine Behrens ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fixed Effects ◽  
Association Studies ◽  
Meta Analysis ◽  
Case Control ◽  
Genome Wide Association Studies ◽  
Genetic Modifiers ◽  
Genome Wide ◽  
A Genome ◽  
Increased Risk

Women using menopausal hormone therapy (MHT) are at increased risk of developing breast cancer (BC). To detect genetic modifiers of the association between current use of MHT and BC risk, we conducted a meta-analysis of four genome-wide case-only studies followed by replication in 11 case–control studies. We used a case-only design to assess interactions between single-nucleotide polymorphisms (SNPs) and current MHT use on risk of overall and lobular BC. The discovery stage included 2920 cases (541 lobular) from four genome-wide association studies. The top 1391 SNPs showing P values for interaction (Pint) <3.0×10−3 were selected for replication using pooled case–control data from 11 studies of the Breast Cancer Association Consortium, including 7689 cases (676 lobular) and 9266 controls. Fixed-effects meta-analysis was used to derive combined Pint. No SNP reached genome-wide significance in either the discovery or combined stage. We observed effect modification of current MHT use on overall BC risk by two SNPs on chr13 near POMP (combined Pint≤8.9×10−6), two SNPs in SLC25A21 (combined Pint≤4.8×10−5), and three SNPs in PLCG2 (combined Pint≤4.5×10−5). The association between lobular BC risk was potentially modified by one SNP in TMEFF2 (combined Pint≤2.7×10−5), one SNP in CD80 (combined Pint≤8.2×10−6), three SNPs on chr17 near TMEM132E (combined Pint≤2.2×10−6), and two SNPs on chr18 near SLC25A52 (combined Pint≤4.6×10−5). In conclusion, polymorphisms in genes related to solute transportation in mitochondria, transmembrane signaling, and immune cell activation are potentially modifying BC risk associated with current use of MHT. These findings warrant replication in independent studies.

scholarly journals Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis

2016 ◽  
Vol 17 (10) ◽  
pp. 1363-1373 ◽  
Author(s):  
Puya Gharahkhani ◽  
Rebecca C Fitzgerald ◽  
Thomas L Vaughan ◽  
Claire Palles ◽  
Ines Gockel ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Barrett’S Oesophagus ◽  
Oesophageal Adenocarcinoma ◽  
Genome Wide Association Studies ◽  
Barrett's Oesophagus ◽  
Genome Wide

scholarly journals Sex-specific gene and pathway modeling of inherited glioma risk

2017 ◽  
Author(s):  
Quinn T. Ostrom ◽  
Warren Coleman ◽  
William Huang ◽  
Joshua B. Rubin ◽  
Justin D. Lathia ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Cellular Aging ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Autosomal Snps ◽  
Significance Threshold ◽  
Risk Variants ◽  
Males And Females ◽  
Glioma Risk

ABSTRACTBackgroundGenome-wide association studies (GWAS) have identified 25 risk variants for glioma, which explain ~30% of heritable risk. Most glioma histologies occur with significantly higher incidence in males. A sex-stratified analysis ide7ntified sex-specific glioma risk variants, and further analyses using gene- and pathway-based approaches may further elucidate risk variation by sex.MethodsResults from the Glioma International Case-Control Study were used as a testing set, and results from three GWAS were combined via meta-analysis and used as a validation set. Using summary statistics for autosomal SNPs found to be nominally significant (p<0.01) in a previous meta-analysis and X chromosome SNPs with nominally significant association (p<0.01), three algorithms (Pascal, BimBam, and GATES) were used to generate gene-scores, and Pascal was used to generate pathway scores. Results were considered significant when p<3.3x10−6in ⅔ algorithms.Results25 genes within five regions and 19 genes within six regions reached the set significance threshold in at least 2/3 algorithms in males and females, respectively.EGFRandRTEL1-TNFRSF6Bwere significantly associated with all glioma and glioblastoma in males only, and a female-specific association inTERT, all of which remained nominally significant after conditioning on known risk loci. There were nominal associations with the Telomeres, Telomerase, Cellular Aging, and Immortality pathway in both males and females.ConclusionsThese results suggest that there may be biologically relevant significant differences by sex in genetic risk for glioma. Additional gene- and pathway-based analyses may further elucidate the biological processes through which this risk is conferred.

scholarly journals EnigmaVis: Online Interactive Visualization of Genome-Wide Association Studies of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium

2012 ◽  
Vol 15 (3) ◽  
pp. 414-418 ◽  
Author(s):  
Nic M. Novak ◽  
Jason L. Stein ◽  
Sarah E. Medland ◽  
Derrek P. Hibar ◽  
Paul M. Thompson ◽  
...  
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Intracranial Volume ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genome Wide ◽  
Neuroimaging Data ◽  
Neuroimaging Genetics

In an attempt to increase power to detect genetic associations with brain phenotypes derived from human neuroimaging data, we recently conducted a large-scale, genome-wide association meta-analysis of hippocampal, brain, and intracranial volume through the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium. Here, we present a freely available online interactive tool, EnigmaVis, which makes it easy to visualize the association results generated by the consortium alongside allele frequency, genes, and functional annotations. EnigmaVis runs natively within the web browser, and generates plots that show the level of association between brain phenotypes at user-specified genomic positions. Uniquely, EnigmaVis is dynamic; users can interact with elements on the plot in real time. This software will be useful when exploring the effect on brain structure of particular genetic variants influencing neuropsychiatric illness and cognitive function. Future projects of the consortium and updates to EnigmaVis will also be displayed on the site. EnigmaVis is freely available online at http://enigma.loni.ucla.edu/enigma-vis/

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