A large Canadian cohort provides insights into the genetic architecture of human hair colour

AbstractHair colour is a polygenic phenotype that results from differences in the amount and ratio of melanins located in the hair bulb. Genome-wide association studies (GWAS) have identified many loci involved in the pigmentation pathway affecting hair colour. However, most of the associated loci overlap non-protein coding regions and many of the molecular mechanisms underlying pigmentation variation are still not understood. Here, we conduct GWAS meta-analyses of hair colour in a Canadian cohort of 12,741 individuals of European ancestry. By performing fine-mapping analyses we identify candidate causal variants in pigmentation loci associated with blonde, red and brown hair colour. Additionally, we observe colocalization of several GWAS hits with expression and methylation quantitative trait loci (QTLs) of cultured melanocytes. Finally, transcriptome-wide association studies (TWAS) further nominate the expression of EDNRB and CDK10 as significantly associated with hair colour. Our results provide insights on the mechanisms regulating pigmentation biology in humans.

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Multiethnic meta-analysis identifies new loci for pulmonary function

10.1101/196048 ◽

2017 ◽

Cited By ~ 1

Author(s):

Annah B. Wyss ◽

Tamar Sofer ◽

Mi Kyeong Lee ◽

Natalie Terzikhan ◽

Jennifer N. Nguyen ◽

...

Keyword(s):

Pulmonary Function ◽

Drug Targets ◽

Association Studies ◽

Meta Analysis ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Causal Variants ◽

Multiethnic Population ◽

Meta Analyses

AbstractNearly 100 loci have been identified for pulmonary function, almost exclusively in studies of European ancestry populations. We extend previous research by meta-analyzing genome-wide association studies of 1000 Genomes imputed variants in relation to pulmonary function in a multiethnic population of 90,715 individuals of European (N=60,552), African (N=8,429), Asian (N=9,959), and Hispanic/Latino (N=11,775) ethnicities. We identified over 50 novel loci at genome-wide significance in ancestry-specific and/or multiethnic meta-analyses. Recent fine mapping methods incorporating functional annotation, gene expression, and/or differences in linkage disequilibrium between ethnicities identified potential causal variants and genes at known and newly identified loci. Sixteen of the novel genes encode proteins with predicted or established drug targets, including KCNK2 and CDK12.

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The open targets post-GWAS analysis pipeline

Bioinformatics ◽

10.1093/bioinformatics/btaa020 ◽

2020 ◽

Vol 36 (9) ◽

pp. 2936-2937 ◽

Cited By ~ 4

Author(s):

Gareth Peat ◽

William Jones ◽

Michael Nuhn ◽

José Carlos Marugán ◽

William Newell ◽

...

Keyword(s):

Drug Targets ◽

Gene Expression Regulation ◽

Association Studies ◽

Genome Wide Association Studies ◽

Protein Coding ◽

Data Resource ◽

Coding Regions ◽

Genome Wide ◽

Causal Genes ◽

Interactive Data

Abstract Motivation Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. Results We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. Availability and implementation The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io.

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Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽

10.1161/circ.133.suppl_1.p260 ◽

2016 ◽

Vol 133 (suppl_1) ◽

Author(s):

James S Floyd ◽

Colleen Sitlani ◽

Christy L Avery ◽

Eric A Whitsel ◽

Leslie Lange ◽

...

Keyword(s):

Repeated Measures ◽

Qt Interval ◽

Association Studies ◽

Meta Analysis ◽

Small Sample ◽

Genome Wide Association ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

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Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR

Bioinformatics ◽

10.1093/bioinformatics/btaa568 ◽

2020 ◽

Vol 36 (18) ◽

pp. 4749-4756 ◽

Cited By ~ 2

Author(s):

Alexey A Shadrin ◽

Oleksandr Frei ◽

Olav B Smeland ◽

Francesco Bettella ◽

Kevin S O'Connell ◽

...

Keyword(s):

Functional Annotation ◽

Association Studies ◽

Effect Sizes ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Protein Coding ◽

Genome Wide ◽

Whole Exome ◽

Causal Variants ◽

Complex Human Traits

Abstract Motivation Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Results Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, <10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders. Availability and implementation The software is available at: https://github.com/precimed/mixer. Supplementary information Supplementary data are available at Bioinformatics online.

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Combined analysis of keratinocyte cancers identifies novel genome-wide loci

Human Molecular Genetics ◽

10.1093/hmg/ddz121 ◽

2019 ◽

Vol 28 (18) ◽

pp. 3148-3160 ◽

Cited By ~ 6

Author(s):

Upekha E Liyanage ◽

Matthew H Law ◽

Xikun Han ◽

Jiyuan An ◽

Jue-Sheng Ong ◽

...

Keyword(s):

Cell Carcinoma ◽

Association Studies ◽

Genetic Correlations ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Multiple Trait ◽

Total N ◽

Risk Variants ◽

Genome Wide ◽

Meta Analyses

Abstract The keratinocyte cancers (KC), basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common cancers in fair-skinned people. KC treatment represents the second highest cancer healthcare expenditure in Australia. Increasing our understanding of the genetic architecture of KC may provide new avenues for prevention and treatment. We first conducted a series of genome-wide association studies (GWAS) of KC across three European ancestry datasets from Australia, Europe and USA, and used linkage disequilibrium (LD) Score regression (LDSC) to estimate their pairwise genetic correlations. We employed a multiple-trait approach to map genes across the combined set of KC GWAS (total N = 47 742 cases, 634 413 controls). We also performed meta-analyses of BCC and SCC separately to identify trait specific loci. We found substantial genetic correlations (generally 0.5–1) between BCC and SCC suggesting overlapping genetic risk variants. The multiple trait combined KC GWAS identified 63 independent genome-wide significant loci, 29 of which were novel. Individual separate meta-analyses of BCC and SCC identified an additional 13 novel loci not found in the combined KC analysis. Three new loci were implicated using gene-based tests. New loci included common variants in BRCA2 (distinct to known rare high penetrance cancer risk variants), and in CTLA4, a target of immunotherapy in melanoma. We found shared and trait specific genetic contributions to BCC and SCC. Considering both, we identified a total of 79 independent risk loci, 45 of which are novel.

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Identifying Liver Cancer-Related Enhancer SNPs by Integrating GWAS and Histone Modification ChIP-seq Data

BioMed Research International ◽

10.1155/2016/2395341 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6 ◽

Cited By ~ 1

Author(s):

Tianjiao Zhang ◽

Yang Hu ◽

Xiaoliang Wu ◽

Rui Ma ◽

Qinghua Jiang ◽

...

Keyword(s):

Gene Expression ◽

Liver Cancer ◽

Histone Modification ◽

Association Studies ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Protein Coding ◽

Noncoding Regions ◽

Coding Regions ◽

Genome Wide

Many disease-related single nucleotide polymorphisms (SNPs) have been inferred from genome-wide association studies (GWAS) in recent years. Numerous studies have shown that some SNPs located in protein-coding regions are associated with numerous diseases by affecting gene expression. However, in noncoding regions, the mechanism of how SNPs contribute to disease susceptibility remains unclear. Enhancer elements are functional segments of DNA located in noncoding regions that play an important role in regulating gene expression. The SNPs located in enhancer elements may affect gene expression and lead to disease. We presented a method for identifying liver cancer-related enhancer SNPs through integrating GWAS and histone modification ChIP-seq data. We identified 22 liver cancer-related enhancer SNPs, 9 of which were regulatory SNPs involved in distal transcriptional regulation. The results highlight that these enhancer SNPs may play important roles in liver cancer.

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Shared Genetic Architecture between Asthma and Allergic Diseases: A Genome-Wide Cross Trait Analysis of 112,000 Individuals from UK Biobank

10.1101/133322 ◽

2017 ◽

Cited By ~ 3

Author(s):

Zhaozhong Zhu ◽

Phil H. Lee ◽

Mark D. Chaffin ◽

Wonil Chung ◽

Po-Ru Loh ◽

...

Keyword(s):

Molecular Mechanisms ◽

Association Studies ◽

Allergic Diseases ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Trait Analysis ◽

Genome Wide ◽

A Genome ◽

Shared Genetic

AbstractClinical and epidemiological data suggest that asthma and allergic diseases are associated. And may share a common genetic etiology. We analyzed genome-wide single-nucleotide polymorphism (SNP) data for asthma and allergic diseases in 35,783 cases and 76,768 controls of European ancestry from the UK Biobank. Two publicly available independent genome wide association studies (GWAS) were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (rg = 0.75, P = 6.84×10−62). Cross trait analysis identified 38 genome-wide significant loci, including novel loci such as D2HGDH and GAL2ST2. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance our understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.

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The Trans-Ancestral Genomic Architecture of Glycaemic Traits

10.1101/2020.07.23.217646 ◽

2020 ◽

Author(s):

Ji Chen ◽

Cassandra N. Spracklen ◽

Gaëlle Marenne ◽

Arushi Varshney ◽

Laura J Corbin ◽

...

Keyword(s):

Association Studies ◽

Glycated Haemoglobin ◽

European Ancestry ◽

Cardiometabolic Health ◽

Genomic Feature ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Credible Sets ◽

Meta Analyses ◽

Glycaemic Traits

AbstractGlycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P<5×10-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

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INFERNO - INFERring the molecular mechanisms of NOncoding genetic variants

10.1101/211599 ◽

2017 ◽

Cited By ~ 3

Author(s):

Alexandre Amlie-Wolf ◽

Mitchell Tang ◽

Elisabeth E. Mlynarski ◽

Pavel P. Kuksa ◽

Otto Valladares ◽

...

Keyword(s):

Genetic Variants ◽

Molecular Mechanisms ◽

Target Genes ◽

Association Studies ◽

Regulatory Elements ◽

Genome Wide Association Studies ◽

Cellular Processes ◽

Genome Wide ◽

Causal Variants ◽

Novel Method

AbstractThe majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, where they affect regulatory elements including transcriptional enhancers. We propose INFERNO (INFERring the molecular mechanisms of NOncoding genetic variants), a novel method which integrates hundreds of diverse functional genomics data sources with GWAS summary statistics to identify putatively causal noncoding variants underlying association signals. INFERNO comprehensively infers the relevant tissue contexts, target genes, and downstream biological processes affected by causal variants. We apply INFERNO to schizophrenia GWAS data, recapitulating known schizophrenia-associated genes including CACNA1C and discovering novel signals related to transmembrane cellular processes.

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Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations

10.1101/2020.01.14.905927 ◽

2020 ◽

Cited By ~ 2

Author(s):

Ying Wang ◽

Jing Guo ◽

Guiyan Ni ◽

Jian Yang ◽

Peter M. Visscher ◽

...

Keyword(s):

Complex Traits ◽

Association Studies ◽

African Ancestry ◽

Real Data ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Polygenic Scores ◽

Causal Variants ◽

The Uk

AbstractPolygenic scores (PGS) have been widely used to predict complex traits and risk of diseases using variants identified from genome-wide association studies (GWASs). To date, most GWASs have been conducted in populations of European ancestry, which limits the use of GWAS-derived PGS in non-European populations. Here, we develop a new theory to predict the relative accuracy (RA, relative to the accuracy in populations of the same ancestry as the discovery population) of PGS across ancestries. We used simulations and real data from the UK Biobank to evaluate our results. We found across various simulation scenarios that the RA of PGS based on trait-associated SNPs can be predicted accurately from modelling linkage disequilibrium (LD), minor allele frequencies (MAF), cross-population correlations of SNP effect sizes and heritability. Altogether, we find that LD and MAF differences between ancestries explain alone up to ~70% of the loss of RA using European-based PGS in African ancestry for traits like body mass index and height. Our results suggest that causal variants underlying common genetic variation identified in European ancestry GWASs are mostly shared across continents.

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