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.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

scholarly journals Large-scale meta-analysis across East Asian and European populations updated genetic architecture and variant-driven biology of rheumatoid arthritis, identifying 11 novel susceptibility loci

2020 ◽  
pp. annrheumdis-2020-219065
Author(s):  
Eunji Ha ◽  
Sang-Cheol Bae ◽  
Kwangwoo Kim
Keyword(s):  
Rheumatoid Arthritis ◽  
Transcription Factors ◽  
T Cell Activation ◽  
Fixed Effects ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Chromatin Interaction ◽  
Susceptibility Loci ◽  
European Populations

ObjectivesNearly 110 susceptibility loci for rheumatoid arthritis (RA) with modest effect sizes have been identified by population-based genetic association studies, suggesting a large number of undiscovered variants behind a highly polygenic genetic architecture of RA. Here, we performed the largest-ever trans-ancestral meta-analysis with the aim to identify new RA loci and to better understand RA biology underlying genetic associations.MethodsGenome-wide RA association summary statistics in three large case–control collections consisting of 311 292 individuals of Korean, Japanese and European populations were used in an inverse-variance-weighted fixed-effects meta-analysis. Several computational analyses using public omics resources were conducted to prioritise causal variants and genes, RA variant-implicating features (tissues, pathways and transcription factors) and potentially repurposable drugs for RA treatment.ResultsWe identified 11 new RA susceptibility loci that explained 6.9% and 1.8% of the single-nucleotide polymorphism-based heritability in East Asians and Europeans, respectively, and confirmed 71 known non-human leukocyte antigens (HLA) susceptibility loci, identifying 90 independent association signals. The RA variants were preferentially located in binding sites of various transcription factors and in cell type-specific transcription–activation histone marks that simultaneously highlighted the importance of CD4+ T-cell activation and the potential role of non-immune organs in RA pathogenesis. A total of 615 plausible effector genes, based on gene-based associations, expression-associated variants and chromatin interaction, included targets of drugs approved for RA treatments and potentially repurposable drugs approved for other indications.ConclusionOur findings provide useful insights regarding RA genetic aetiology and variant-driven RA pathogenesis.

Abstract 141: APOA1, CETP, and CILP2 Variants Modify the Lipid Response to Fenofibrate: Genetics of Lipid Lowering and Diet Network

2012 ◽  
Vol 32 (suppl_1) ◽  
Author(s):  
Stella Aslibekyan ◽  
Marguerite M Irvin ◽  
Alexis C Frazier-Wood ◽  
Robert J Straka ◽  
Ingrid B Borecki ◽  
...  
Keyword(s):  
Blood Lipids ◽  
Association Studies ◽  
Meta Analysis ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Lipid Lowering ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Lipid Response ◽  
Induced Changes

Introduction: Despite the widespread use of fibrates in treatment of dyslipidemia, the observed response is highly heterogeneous, suggesting a role for genetic determinants. Whether replicated variants associated with blood lipids identified by genome wide association studies (GWAS) are also associated with lipid response to fenofibrate is unknown. Objectives: To test if 95 genome-wide significant loci identified in a recent meta-analysis of blood lipids are associated with changes in high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, and triglycerides (TG) following 3 weeks of therapy with 160 mg of micronized fenofibrate. Methods: Using data from 861 European American Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) participants, we fit mixed linear models with baseline blood lipids and the post-to-pre fenofibrate treatment ratio of blood lipid levels as outcomes, the corresponding genetic markers from the published meta-analysis as predictors, and age, sex, pedigree, and ancestry as assessed by principal components as covariates. A Bonferroni correction was applied to adjust for multiple comparisons. Least square means were used to report the direction of fenofibrate-induced changes by genotype. Results: We observed statistically significant associations between rs964184 , a variant near the APOA1 gene, and baseline HDL-C (P<0.0001) and baseline TG (P<0.0001), as well as with diminished response to fenofibrate as evidenced by a smaller increase in HDL-C (P<0.0001) and a smaller decrease in TG (P=0.0001) per each copy of the variant allele. Additionally, we report suggestive associations of rs3764261 locus in the CETP gene and the rs10401969 locus in the CILP2 gene with decreased fenofibrate response as measured by changes in LDL-C (P=0.0003 and 0.02, respectively) and non-HDL-C (P=0.004 and 0.005, respectively). Conclusions: We have identified several novel biologically relevant loci associated with baseline blood lipids and fenofibrate-induced changes in blood lipids.

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 Discovery and prioritization of variants and genes for kidney function in >1.2 million individuals

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kira J. Stanzick ◽  
Yong Li ◽  
Pascal Schlosser ◽  
Mathias Gorski ◽  
Matthias Wuttke ◽  
...  
Keyword(s):  
Kidney Function ◽  
Fine Mapping ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Genome Wide ◽  
Credible Sets ◽  
Variance Explained

AbstractGenes underneath signals from genome-wide association studies (GWAS) for kidney function are promising targets for functional studies, but prioritizing variants and genes is challenging. By GWAS meta-analysis for creatinine-based estimated glomerular filtration rate (eGFR) from the Chronic Kidney Disease Genetics Consortium and UK Biobank (n = 1,201,909), we expand the number of eGFRcrea loci (424 loci, 201 novel; 9.8% eGFRcrea variance explained by 634 independent signal variants). Our increased sample size in fine-mapping (n = 1,004,040, European) more than doubles the number of signals with resolved fine-mapping (99% credible sets down to 1 variant for 44 signals, ≤5 variants for 138 signals). Cystatin-based eGFR and/or blood urea nitrogen association support 348 loci (n = 460,826 and 852,678, respectively). Our customizable tool for Gene PrioritiSation reveals 23 compelling genes including mechanistic insights and enables navigation through genes and variants likely relevant for kidney function in human to help select targets for experimental follow-up.

scholarly journals SparsePro: an efficient genome-wide fine-mapping method integrating summary statistics and functional annotations

2021 ◽  
Author(s):  
Wenmin Zhang ◽  
Hamed S Najafabadi ◽  
Yue Li
Keyword(s):  
Fine Mapping ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Association Studies ◽  
Computational Cost ◽  
Mapping Method ◽  
Genome Wide Association Studies ◽  
Functional Annotations ◽  
Genome Wide ◽  
Causal Variants

Identifying causal variants from genome-wide association studies (GWASs) is challenging due to widespread linkage disequilibrium (LD). Functional annotations of the genome may help prioritize variants that are biologically relevant and thus improve fine-mapping of GWAS results. However, classical fine-mapping methods have a high computational cost, particularly when the underlying genetic architecture and LD patterns are complex. Here, we propose a novel approach, SparsePro, to efficiently conduct functionally informed statistical fine-mapping. Our method enjoys two major innovations: First, by creating a sparse low-dimensional projection of the high-dimensional genotype, we enable a linear search of causal variants instead of an exponential search of causal configurations used in existing methods; Second, we adopt a probabilistic framework with a highly efficient variational expectation-maximization algorithm to integrate statistical associations and functional priors. We evaluate SparsePro through extensive simulations using resources from the UK Biobank. Compared to state-of-the-art methods, SparsePro achieved more accurate and well-calibrated posterior inference with greatly reduced computation time. We demonstrate the utility of SparsePro by investigating the genetic architecture of five functional biomarkers of vital organs. We identify potential causal variants contributing to the genetically encoded coordination mechanisms between vital organs and pinpoint target genes with potential pleiotropic effects. In summary, we have developed an efficient genome-wide fine-mapping method with the ability to integrate functional annotations. Our method may have wide utility in understanding the genetics of complex traits as well as in increasing the yield of functional follow-up studies of GWASs.

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.

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