Combined analysis of keratinocyte cancers identifies novel genome-wide loci

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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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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The transferability of lipid loci across African, Asian and European cohorts

Nature Communications ◽

10.1038/s41467-019-12026-7 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 7

Author(s):

Karoline Kuchenbaecker ◽

◽

Nikita Telkar ◽

Theresa Reiker ◽

Robin G. Walters ◽

...

Keyword(s):

Association Studies ◽

Genetic Risk Score ◽

Genetic Correlations ◽

Serum Levels ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Genetic Determinants ◽

Gene Environment ◽

Genome Wide ◽

The Uk

Abstract Most genome-wide association studies are based on samples of European descent. We assess whether the genetic determinants of blood lipids, a major cardiovascular risk factor, are shared across populations. Genetic correlations for lipids between European-ancestry and Asian cohorts are not significantly different from 1. A genetic risk score based on LDL-cholesterol-associated loci has consistent effects on serum levels in samples from the UK, Uganda and Greece (r = 0.23–0.28, p < 1.9 × 10−14). Overall, there is evidence of reproducibility for ~75% of the major lipid loci from European discovery studies, except triglyceride loci in the Ugandan samples (10% of loci). Individual transferable loci are identified using trans-ethnic colocalization. Ten of fourteen loci not transferable to the Ugandan population have pleiotropic associations with BMI in Europeans; none of the transferable loci do. The non-transferable loci might affect lipids by modifying food intake in environments rich in certain nutrients, which suggests a potential role for gene-environment interactions.

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Pan-Cancer Study Detects Novel Genetic Risk Variants and Shared Genetic Basis in Two Large Cohorts

10.1101/635367 ◽

2019 ◽

Cited By ~ 3

Author(s):

Sara R. Rashkin ◽

Rebecca E. Graff ◽

Linda Kachuri ◽

Khanh K. Thai ◽

Stacey E. Alexeeff ◽

...

Keyword(s):

Genetic Basis ◽

Association Studies ◽

Large Population ◽

Regulatory Elements ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Risk Variants ◽

Genome Wide ◽

Pan Cancer ◽

Shared Genetic

AbstractDeciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. However, no studies have investigated pan-cancer pleiotropy within single, well-defined populations unselected for phenotype. We undertook novel genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (413,870 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detected 21 novel genome-wide significant risk variants. In addition, numerous cancer sites exhibited clear heritability. Investigations of pleiotropy identified 12 cancer pairs exhibiting either positive or negative genetic correlations and 43 pleiotropic loci. We identified 158 pleiotropic variants, many of which were enriched for regulatory elements and influenced cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

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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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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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Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

10.1101/2020.06.29.133702 ◽

2020 ◽

Cited By ~ 1

Author(s):

Daniel L. McCartney ◽

Josine L. Min ◽

Rebecca C. Richmond ◽

Ake T. Lu ◽

Maria K. Sobczyk ◽

...

Keyword(s):

Dna Methylation ◽

Association Studies ◽

Genetic Correlations ◽

Plasminogen Activator Inhibitor ◽

Lifestyle Factors ◽

Polygenic Risk Score ◽

Genome Wide Association Studies ◽

Plasminogen Activator Inhibitor 1 ◽

Genome Wide ◽

Meta Analyses

AbstractBiological ageing estimators derived from DNA methylation (DNAm) data are heritable and correlate with morbidity and mortality. Leveraging DNAm and SNP data from >41,000 individuals, we identify 137 genome-wide significant loci (113 novel) from meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We report strong genetic correlations with longevity and lifestyle factors such as smoking, education, and obesity. Significant associations are observed in polygenic risk score analysis and to a lesser extent in Mendelian randomization analyses. This study illuminates the genetic architecture underlying epigenetic ageing and its shared genetic contributions with lifestyle factors and longevity.

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Largest genome-wide association study for PTSD identifies genetic risk loci in European and African ancestries and implicates novel biological pathways

10.1101/458562 ◽

2018 ◽

Cited By ~ 6

Author(s):

Caroline M. Nievergelt ◽

Adam X. Maihofer ◽

Torsten Klengel ◽

Elizabeth G. Atkinson ◽

Chia-Yen Chen ◽

...

Keyword(s):

Genome Wide Association Study ◽

Association Studies ◽

Meta Analysis ◽

African Ancestry ◽

Genetic Correlations ◽

Genome Wide Association ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Post Traumatic Stress ◽

Genome Wide

AbstractPost-traumatic stress disorder (PTSD) is a common and debilitating disorder. The risk of PTSD following trauma is heritable, but robust common variants have yet to be identified by genome-wide association studies (GWAS). We have collected a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls. We first demonstrate significant genetic correlations across 60 PTSD cohorts to evaluate the comparability of these phenotypically heterogeneous studies. In this largest GWAS meta-analysis of PTSD to date we identify a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses. Follow-up analyses incorporated local ancestry and sex-specific effects, and functional studies. Along with other novel genes, a non-coding RNA (ncRNA) and a Parkinson’s Disease gene,PARK2, were associated with PTSD. Consistent with previous reports, SNP-based heritability estimates for PTSD range between 10-20%. Despite a significant shared liability between PTSD and major depressive disorder, we show evidence that some of our loci may be specific to PTSD. These results demonstrate the role of genetic variation contributing to the biology of differential risk for PTSD and the necessity of expanding GWAS beyond European ancestry.

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Genome-wide association study and multi-trait analysis of opioid use disorder identifies novel associations in 639,709 individuals of European and African ancestry

10.1101/2021.12.04.21267094 ◽

2021 ◽

Author(s):

Joseph D. Deak ◽

Hang Zhou ◽

Marco Galimberti ◽

Daniel Levey ◽

Frank R. Wendt ◽

...

Keyword(s):

Association Studies ◽

Meta Analysis ◽

Genetic Correlations ◽

Opioid Use Disorder ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Opioid Use ◽

Total N ◽

Trait Analysis ◽

Genome Wide

AbstractBackgroundDespite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci.MethodsWe performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program (MVP), Psychiatric Genomics Consortium (PGC), iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N=639,709 (Ncases=20,858) across ancestries. OUD cases were defined as having lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h2SNP) and genetic correlations (rg). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD).ResultsThe EUR meta-analysis identified three genome-wide significant (GWS; p≤5×10−8) lead SNPs—one at FURIN (rs11372849; p=9.54×10−10) and two OPRM1 variants (rs1799971, p=4.92×10−09 ; rs79704991, p=1.37×10−08; r2=0.02). Rs1799971 (p=4.91×10−08) and another OPRM1 variant (rs9478500; p=1.95×10−8; r2=0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg =0.82; p=1.14×10−47) and AUD (rg=0.77; p=6.36×10−78). The OUD-MTAG resulted in 18 GWS loci, all of which map to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes.ConclusionsWe identified multiple OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

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A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer

Scientific Reports ◽

10.1038/srep10442 ◽

2015 ◽

Vol 5 (1) ◽

Cited By ~ 74

Author(s):

Nada A. Al-Tassan ◽

Nicola Whiffin ◽

Fay J. Hosking ◽

Claire Palles ◽

Susan M. Farrington ◽

...

Keyword(s):

Colorectal Cancer ◽

Association Studies ◽

Meta Analysis ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Susceptibility Loci ◽

Risk Variants ◽

Non Coding Rna ◽

Genome Wide ◽

Long Non Coding Rna

Abstract Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10−8, odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10−8; OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10-8; OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.

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Genetics of Sleep and Insights into Its Relationship with Obesity

Annual Review of Nutrition ◽

10.1146/annurev-nutr-082018-124258 ◽

2021 ◽

Vol 41 (1) ◽

Author(s):

Hassan S. Dashti ◽

José M. Ordovás

Keyword(s):

Sleep Disorders ◽

Healthy Lifestyle ◽

Association Studies ◽

Genetic Correlations ◽

European Ancestry ◽

Annual Review ◽

Publication Date ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Polygenic Scores

Considerable recent advancements in elucidating the genetic architecture of sleep traits and sleep disorders may provide insight into the relationship between sleep and obesity. Despite the considerable involvement of the circadian clock in sleep and metabolism, few shared genes, including FTO, were implicated in genome-wide association studies (GWASs) of sleep and obesity. Polygenic scores composed of signals from GWASs of sleep traits show largely null associations with obesity, suggesting lead variants are unique to sleep. Modest genome-wide genetic correlations are observed between many sleep traits and obesity and are largest for snoring.Notably, U-shaped positive genetic correlations with body mass index (BMI) exist for both short and long sleep durations. Findings from Mendelian randomization suggest robust causal effects of insomnia on higher BMI and, conversely, of higher BMI on snoring and daytime sleepiness. Bidirectional effects between sleep duration and daytime napping with obesity may also exist. Limited gene-sleep interaction studies suggest that achieving favorable sleep, as part of a healthy lifestyle, may attenuate genetic predisposition to obesity, but whether these improvements produce clinically meaningful reductions in obesity risk remains unclear. Investigations of the genetic link between sleep and obesity for sleep disorders other than insomnia and in populations of non-European ancestry are currently limited. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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