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1. Human-Precision Medicine Interaction: Public Perceptions of Polygenic Risk Score for Genetic Health Prediction.

Author: Yuhao Sun, Albert Tenesa, and John Vines
Published: 2025
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2. Genetic and environmental contribution to phenotypic resemblance between Iranian couples: Tehran Cardiometabolic and Genetic Study (TCGS)

Author: Parisa Riahi, Amir Hossein Saeidian, Albert Tenesa, Carolyn T. Hogan, Michael March, Kamran Guity, Mahmoud Amiri Roudbar, Asieh Zahedi, Maryam Zarkesh, Farideh Neshati, Mehdi Hedayati, Fereidoun Azizi, Hakon Hakonarson, Maryam S. Daneshpour, and Mahdi Akbarzadeh
Subjects: Assortative mating, Polygenic risk scores, Genetic AM, GWAS, Spousal resemblance, TCGS, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: Objective: To provide an applied framework for assessing the genetic contribution to assortative mating (AM) using height as a model trait and disclose the trace of certain pieces of evidence of AM in the form of the shared environmental effects from long-term cohabitation on spouses’ anthropometric traits and lipid serum levels. Methods: 2315 genotyped couples were extracted from the Tehran Cardiometabolic Genetic Study (TCGS). Pearson correlation analysis was used to assess the relationship between spouses' height. The GCTA-GREML was used to assess the SNP-based heritability of individual and spousal heights with AM adjustments. We used a recent GWAS meta-analysis of ∼5.4M individuals of height to calculate polygenic risk scores (PRS) for spouses’ height. A subset of 1038 spouses out of 2315 couples were subsequently selected to enter the longitudinal resemblance, to be assessed in terms of their anthropometric traits and lipid serum levels in a 15-year follow-up. We conducted a Bayesian hierarchical meta-analysis for each time point to assess the validity of the increasing trend of the longitudinal association. Results: The correlation coefficient of height between spouses was estimated as r = 0.248. We found that a person's genotype determines 6.15 % of the variation in the spouse's height. Furthermore, correlation between PRS of individuals showed a statistical association between an individual’s genotype and their spouse’s genotype (R2 = 4 %) across 1,982 couples with only one genotyped spouse, achieving approximately half of the theoretical maximum accuracy. Long-term spousal resemblance revealed an increasing trend for correlation between husbands and wives in terms of their lipid serum level and obesity-related traits. Conclusion: Our findings support the AM hypothesis for height with a significant spousal correlation and show that selecting the spouse's height is genetically determined. Besides, we provide data showing that AM is predicted to result in a10 % increase in the heritability of height, which is related to the assortative nature of alleles in the population and not to the segregation of genetic variations. Finally, as one of the evolutionary consequences of AM, long-term spousal resemblance provided an increasing trend for correlation between spouses in terms of their lipid serum level and obesity-related traits.
Published: 2025
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3. The effect of family structure on the still-missing heritability and genomic prediction accuracy of type 2 diabetes

Author: Mahmoud Amiri Roudbar, Seyed Milad Vahedi, Jin Jin, Mina Jahangiri, Hossein Lanjanian, Danial Habibi, Sajedeh Masjoudi, Parisa Riahi, Sahand Tehrani Fateh, Farideh Neshati, Asiyeh Sadat Zahedi, Maryam Moazzam-Jazi, Leila Najd-Hassan-Bonab, Seyedeh Fatemeh Mousavi, Sara Asgarian, Maryam Zarkesh, Mohammad Reza Moghaddas, Albert Tenesa, Anoshirvan Kazemnejad, Hassan Vahidnezhad, Hakon Hakonarson, Fereidoun Azizi, Mehdi Hedayati, Maryam Sadat Daneshpour, and Mahdi Akbarzadeh
Subjects: Genome-wide association studies (GWAS), Heritability, Estimated risk values (ERV), Type 2 diabetes, Missing heritability, Medicine, Genetics, QH426-470
Abstract: Abstract This study aims to assess the effect of familial structures on the still-missing heritability estimate and prediction accuracy of Type 2 Diabetes (T2D) using pedigree estimated risk values (ERV) and genomic ERV. We used 11,818 individuals (T2D cases: 2,210) with genotype (649,932 SNPs) and pedigree information from the ongoing periodic cohort study of the Iranian population project. We considered three different familial structure scenarios, including (i) all families, (ii) all families with ≥ 1 generation, and (iii) families with ≥ 1 generation in which both case and control individuals are presented. Comprehensive simulation strategies were implemented to quantify the difference between estimates of $$\:{\text{h}}^{2}$$ and $$\:{\text{h}}_{\text{S}\text{N}\text{P}}^{2}$$ . A proportion of still-missing heritability in T2D could be explained by overestimation of pedigree-based heritability due to the presence of families with individuals having only one of the two disease statuses. Our research findings underscore the significance of including families with only case/control individuals in cohort studies. The presence of such family structures (as observed in scenarios i and ii) contributes to a more accurate estimation of disease heritability, addressing the underestimation that was previously overlooked in prior research. However, when predicting disease risk, the absence of these families (as seen in scenario iii) can yield the highest prediction accuracy and the strongest correlation with Polygenic Risk Scores. Our findings represent the first evidence of the important contribution of familial structure for heritability estimations and genomic prediction studies in T2D.
Published: 2024
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4. Mendelian randomization study of whole blood viscosity and cardiovascular diseases.

Author: Youngjune Bhak and Albert Tenesa
Subjects: Medicine, Science
Abstract: AimsAssociation between whole blood viscosity (WBV) and an increased risk of cardiovascular disease (CVD) has been reported. However, the causal relationship between WBV and CVD remains not thoroughly investigated. The aim of this study was to investigate the causal relation between WBV and CVD.MethodsTwo-sample Mendelian randomization (MR) was employed, with inverse variance weighting (IVW) as the primary method, to investigate the casual relationship between WBV and CVD. The calculated WBV and medical records of 378,210 individuals participating in the UK Biobank study were divided into halves and analyzed.ResultsThe means of calculated WBVs were 16.9 (standard deviation: 0.8) and 55.1 (standard deviation: 17.2) for high shear rate (HSR) and low shear rate (LSR), respectively. 37,859 (10.0%) major cardiovascular events (MACE) consisted of 23,894 (6.3%) cases of myocardial infarction (MI), 9,245 (2.4%) cases of ischemic stroke, 10,377 (2.7%) cases of revascularization, and 5,703 (1.5%) cases of coronary heart disease-related death. In the MR analysis, no evidence was found indicating a causal effect of WBV on MACE (IVW p-value for HSR = 0.81, IVW p-value for LSR = 0.47), MI (0.92, 0.83), ischemic stroke (0.52, 0.74), revascularization (0.71, 0.54), and coronary heart disease-related death (0.83, 0.70). The lack of sufficient evidence for causality persisted in other MR methods, including weighted median and MR-egger.ConclusionsThe Mendelian randomization analysis conducted in this study does not support a causal relationship between calculated WBV and CVD.
Published: 2024
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5. Fine-mapping of retinal vascular complexity loci identifies Notch regulation as a shared mechanism with myocardial infarction outcomes

Author: Ana Villaplana-Velasco, Marie Pigeyre, Justin Engelmann, Konrad Rawlik, Oriol Canela-Xandri, Claire Tochel, Frida Lona-Durazo, Muthu Rama Krishnan Mookiah, Alex Doney, Esteban J. Parra, Emanuele Trucco, Tom MacGillivray, Kristiina Rannikmae, Albert Tenesa, Erola Pairo-Castineira, and Miguel O. Bernabeu
Subjects: Biology (General), QH301-705.5
Abstract: Abstract There is increasing evidence that the complexity of the retinal vasculature measured as fractal dimension, Df, might offer earlier insights into the progression of coronary artery disease (CAD) before traditional biomarkers can be detected. This association could be partly explained by a common genetic basis; however, the genetic component of Df is poorly understood. We present a genome-wide association study (GWAS) of 38,000 individuals with white British ancestry from the UK Biobank aimed to comprehensively study the genetic component of Df and analyse its relationship with CAD. We replicated 5 Df loci and found 4 additional loci with suggestive significance (P
Published: 2023
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6. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Author: Ruidong Xiang, Lingzhao Fang, Shuli Liu, Iona M. Macleod, Zhiqian Liu, Edmond J. Breen, Yahui Gao, George E. Liu, Albert Tenesa, Brett A. Mason, Amanda J. Chamberlain, Naomi R. Wray, and Michael E. Goddard
Subjects: gene expression, RNA splicing, eQTL, sQTL, complex traits, heritability, Genetics, QH426-470, Internal medicine, RC31-1245
Abstract: Summary: Many quantitative trait loci (QTLs) are in non-coding regions. Therefore, QTLs are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription, so DNA variants changing gene expression (eVariants) or RNA splicing (sVariants) are expected to significantly affect phenotypes. We quantify the contribution of eVariants and sVariants detected from 16 tissues (n = 4,725) to 37 traits of ∼120,000 cattle (average magnitude of genetic correlation between traits = 0.13). Analyzed in Bayesian mixture models, averaged across 37 traits, cis and trans eVariants and sVariants detected from 16 tissues jointly explain 69.2% (SE = 0.5%) of heritability, 44% more than expected from the same number of random variants. This 69.2% includes an average of 24% from trans e-/sVariants (14% more than expected). Averaged across 56 lipidomic traits, multi-tissue cis and trans e-/sVariants also explain 71.5% (SE = 0.3%) of heritability, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.
Published: 2023
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7. The conservation of human functional variants and their effects across livestock species

Author: Rongrong Zhao, Andrea Talenti, Lingzhao Fang, Shuli Liu, George Liu, Neil P. Chue Hong, Albert Tenesa, Musa Hassan, and James G. D. Prendergast
Subjects: Biology (General), QH301-705.5
Abstract: An investigation of genetic variants that exist across human and livestock species supports the clear potential of livestock models in providing insights into the mechanisms driving human diseases and traits.
Published: 2022
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8. Comparative transcriptome in large-scale human and cattle populations

Author: Yuelin Yao, Shuli Liu, Charley Xia, Yahui Gao, Zhangyuan Pan, Oriol Canela-Xandri, Ava Khamseh, Konrad Rawlik, Sheng Wang, Bingjie Li, Yi Zhang, Erola Pairo-Castineira, Kenton D’Mellow, Xiujin Li, Ze Yan, Cong-jun Li, Ying Yu, Shengli Zhang, Li Ma, John B. Cole, Pablo J. Ross, Huaijun Zhou, Chris Haley, George E. Liu, Lingzhao Fang, and Albert Tenesa
Subjects: Comparative transcriptome, Gene co-expression, Heritability enrichment, Inter-individual variability, RNA-seq, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract: Abstract Background Cross-species comparison of transcriptomes is important for elucidating evolutionary molecular mechanisms underpinning phenotypic variation between and within species, yet to date it has been essentially limited to model organisms with relatively small sample sizes. Results Here, we systematically analyze and compare 10,830 and 4866 publicly available RNA-seq samples in humans and cattle, respectively, representing 20 common tissues. Focusing on 17,315 orthologous genes, we demonstrate that mean/median gene expression, inter-individual variation of expression, expression quantitative trait loci, and gene co-expression networks are generally conserved between humans and cattle. By examining large-scale genome-wide association studies for 46 human traits (average n = 327,973) and 45 cattle traits (average n = 24,635), we reveal that the heritability of complex traits in both species is significantly more enriched in transcriptionally conserved than diverged genes across tissues. Conclusions In summary, our study provides a comprehensive comparison of transcriptomes between humans and cattle, which might help decipher the genetic and evolutionary basis of complex traits in both species.
Published: 2022
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9. Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4

Author: Sarah Grosche, Ingo Marenholz, Jorge Esparza-Gordillo, Aleix Arnau-Soler, Erola Pairo-Castineira, Franz Rüschendorf, Tarunveer S. Ahluwalia, Catarina Almqvist, Andreas Arnold, Australian Asthma Genetics Consortium (AAGC), Hansjörg Baurecht, Hans Bisgaard, Klaus Bønnelykke, Sara J. Brown, Mariona Bustamante, John A. Curtin, Adnan Custovic, Shyamali C. Dharmage, Ana Esplugues, Mario Falchi, Dietmar Fernandez-Orth, Manuel A. R. Ferreira, Andre Franke, Sascha Gerdes, Christian Gieger, Hakon Hakonarson, Patrick G. Holt, Georg Homuth, Norbert Hubner, Pirro G. Hysi, Marjo-Riitta Jarvelin, Robert Karlsson, Gerard H. Koppelman, Susanne Lau, Manuel Lutz, Patrik K. E. Magnusson, Guy B. Marks, Martina Müller-Nurasyid, Markus M. Nöthen, Lavinia Paternoster, Craig E. Pennell, Annette Peters, Konrad Rawlik, Colin F. Robertson, Elke Rodriguez, Sylvain Sebert, Angela Simpson, Patrick M. A. Sleiman, Marie Standl, Dora Stölzl, Konstantin Strauch, Agnieszka Szwajda, Albert Tenesa, Philip J. Thompson, Vilhelmina Ullemar, Alessia Visconti, Judith M. Vonk, Carol A. Wang, Stephan Weidinger, Matthias Wielscher, Catherine L. Worth, Chen-Jian Xu, and Young-Ae Lee
Subjects: Science
Abstract: Genetic studies of eczema to date have mostly explored common genetic variation. Here, the authors perform a large meta-analysis for common and rare variants and discover 8 loci associated with eczema. Over 20% of the heritability of the condition is attributable to rare variants.
Published: 2021
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10. Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Author: Shuli Liu, Ying Yu, Shengli Zhang, John B. Cole, Albert Tenesa, Ting Wang, Tara G. McDaneld, Li Ma, George E. Liu, and Lingzhao Fang
Subjects: Comparative epigenomics, GWAS enrichment, Trait-relevant tissues, Human-cattle comparison, Biology (General), QH301-705.5
Abstract: Abstract Background Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle. Results We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle. Conclusion Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.
Published: 2020
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11. Physician-Confirmed and Administrative Definitions of Stroke in UK Biobank Reflect the Same Underlying Genetic Trait

Author: Kristiina Rannikmäe, Konrad Rawlik, Amy C. Ferguson, Nikos Avramidis, Muchen Jiang, Nicola Pirastu, Xia Shen, Emma Davidson, Rebecca Woodfield, Rainer Malik, Martin Dichgans, Albert Tenesa, and Cathie Sudlow
Subjects: stroke, genetic correlation, routinely collected health data, validation, accuracy, Neurology. Diseases of the nervous system, RC346-429
Abstract: BackgroundStroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation.MethodsWe compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants, we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci.ResultsThe stroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg.81-1) and each other (rg.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definition.ConclusionsStroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.
Published: 2022
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12. Functional annotation of the cattle genome through systematic discovery and characterization of chromatin states and butyrate-induced variations

Author: Lingzhao Fang, Shuli Liu, Mei Liu, Xiaolong Kang, Shudai Lin, Bingjie Li, Erin E. Connor, Ransom L. Baldwin, Albert Tenesa, Li Ma, George E. Liu, and Cong-jun Li
Subjects: Cattle genome, Functional annotation, Chromatin states, Butyrate, Rumen development, Biology (General), QH301-705.5
Abstract: Abstract Background The functional annotation of genomes, including chromatin accessibility and modifications, is important for understanding and effectively utilizing the increased amount of genome sequences reported. However, while such annotation has been well explored in a diverse set of tissues and cell types in human and model organisms, relatively little data are available for livestock genomes, hindering our understanding of complex trait variation, domestication, and adaptive evolution. Here, we present the first complete global landscape of regulatory elements in cattle and explore the dynamics of chromatin states in rumen epithelial cells induced by the rumen developmental regulator—butyrate. Results We established the first global map of regulatory elements (15 chromatin states) and defined their coordinated activities in cattle, through genome-wide profiling for six histone modifications, RNA polymerase II, CTCF-binding sites, DNA accessibility, DNA methylation, and transcriptome in rumen epithelial primary cells (REPC), rumen tissues, and Madin-Darby bovine kidney epithelial cells (MDBK). We demonstrated that each chromatin state exhibited specific enrichment for sequence ontology, transcription, methylation, trait-associated variants, gene expression-associated variants, selection signatures, and evolutionarily conserved elements, implying distinct biological functions. After butyrate treatments, we observed that the weak enhancers and flanking active transcriptional start sites (TSS) were the most dynamic chromatin states, occurred concomitantly with significant alterations in gene expression and DNA methylation, which was significantly associated with heifer conception rate and stature economic traits. Conclusion Our results demonstrate the crucial role of functional genome annotation for understanding genome regulation, complex trait variation, and adaptive evolution in livestock. Using butyrate to induce the dynamics of the epigenomic landscape, we were able to establish the correlation among nutritional elements, chromatin states, gene activities, and phenotypic outcomes.
Published: 2019
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13. Linking protein to phenotype with Mendelian Randomization detects 38 proteins with causal roles in human diseases and traits.

Author: Andrew D Bretherick, Oriol Canela-Xandri, Peter K Joshi, David W Clark, Konrad Rawlik, Thibaud S Boutin, Yanni Zeng, Carmen Amador, Pau Navarro, Igor Rudan, Alan F Wright, Harry Campbell, Veronique Vitart, Caroline Hayward, James F Wilson, Albert Tenesa, Chris P Ponting, J Kenneth Baillie, and Chris Haley
Subjects: Genetics, QH426-470
Abstract: To efficiently transform genetic associations into drug targets requires evidence that a particular gene, and its encoded protein, contribute causally to a disease. To achieve this, we employ a three-step proteome-by-phenome Mendelian Randomization (MR) approach. In step one, 154 protein quantitative trait loci (pQTLs) were identified and independently replicated. From these pQTLs, 64 replicated locally-acting variants were used as instrumental variables for proteome-by-phenome MR across 846 traits (step two). When its assumptions are met, proteome-by-phenome MR, is equivalent to simultaneously running many randomized controlled trials. Step 2 yielded 38 proteins that significantly predicted variation in traits and diseases in 509 instances. Step 3 revealed that amongst the 271 instances from GeneAtlas (UK Biobank), 77 showed little evidence of pleiotropy (HEIDI), and 92 evidence of colocalization (eCAVIAR). Results were wide ranging: including, for example, new evidence for a causal role of tyrosine-protein phosphatase non-receptor type substrate 1 (SHPS1; SIRPA) in schizophrenia, and a new finding that intestinal fatty acid binding protein (FABP2) abundance contributes to the pathogenesis of cardiovascular disease. We also demonstrated confirmatory evidence for the causal role of four further proteins (FGF5, IL6R, LPL, LTA) in cardiovascular disease risk.
Published: 2020
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14. Parent of origin genetic effects on methylation in humans are common and influence complex trait variation

Author: Yanni Zeng, Carmen Amador, Charley Xia, Riccardo Marioni, Duncan Sproul, Rosie M. Walker, Stewart W. Morris, Andrew Bretherick, Oriol Canela-Xandri, Thibaud S. Boutin, David W. Clark, Archie Campbell, Konrad Rawlik, Caroline Hayward, Reka Nagy, Albert Tenesa, David J. Porteous, James F. Wilson, Ian J. Deary, Kathryn L. Evans, Andrew M. McIntosh, Pau Navarro, and Chris S. Haley
Subjects: Science
Abstract: Parent-of-origin effects (POE) are observed when there are different effects from alleles inherited from the two parents on phenotypic measures. Here, Zeng et al. study POE on DNA methylation in 5,101 individuals and identify genetic variants that associate with methylation variation via POE and their potential phenotypic consequences.
Published: 2019
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15. Statistical and Functional Studies Identify Epistasis of Cardiovascular Risk Genomic Variants From Genome‐Wide Association Studies

Author: Yabo Li, Hyosuk Cho, Fan Wang, Oriol Canela‐Xandri, Chunyan Luo, Konrad Rawlik, Stephen Archacki, Chengqi Xu, Albert Tenesa, Qiuyun Chen, and Qing Kenneth Wang
Subjects: coronary artery disease, gene‐gene interactions, Genome‐wide Association Studies, long non‐coding RNA (lncRNA) ANRIL (CDKN2B‐AS1), TMEM106B, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Epistasis describes how gene‐gene interactions affect phenotypes, and could have a profound impact on human diseases such as coronary artery disease (CAD). The goal of this study was to identify gene‐gene interactions in CAD using an easily generalizable multi‐stage approach. Methods and Results Our forward genetic approach consists of multiple steps that combine statistical and functional approaches, and analyze information from global gene expression profiling, functional interactions, and genetic interactions to robustly identify gene‐gene interactions. Global gene expression profiling shows that knockdown of ANRIL (DQ485454) at 9p21.3 GWAS (genome‐wide association studies) CAD locus upregulates TMEM100 and TMEM106B. Functional studies indicate that the increased monocyte adhesion to endothelial cells and transendothelial migration of monocytes, 2 critical processes in the initiation of CAD, by ANRIL knockdown are reversed by knockdown of TMEM106B, but not of TMEM100. Furthermore, the decreased monocyte adhesion to endothelial cells and transendothelial migration of monocytes induced by ANRIL overexpression was reversed by overexpressing TMEM106B. TMEM106B expression was upregulated by >2‐fold in CAD coronary arteries. A significant association was found between variants in TMEM106B (but not in TMEM100) and CAD (P=1.9×10−8). Significant gene‐gene interaction was detected between ANRIL variant rs2383207 and TMEM106B variant rs3807865 (P=0.009). A similar approach also identifies significant interaction between rs6903956 in ADTRP and rs17465637 in MIA3 (P=0.005). Conclusions We demonstrate 2 pairs of epistatic interactions between GWAS loci for CAD and offer important insights into the genetic architecture and molecular mechanisms for the pathogenesis of CAD. Our strategy has broad applicability to the identification of epistasis in other human diseases.
Published: 2020
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16. Genome-wide study of hair colour in UK Biobank explains most of the SNP heritability

Author: Michael D. Morgan, Erola Pairo-Castineira, Konrad Rawlik, Oriol Canela-Xandri, Jonathan Rees, David Sims, Albert Tenesa, and Ian J. Jackson
Subjects: Science
Abstract: Natural hair colour in Europeans is a complex genetic trait. Here, the authors carry out a genome-wide association study using UK BioBank data, suggesting that in combination with pigmentation genes, variants with roles in hair texture and growth can affect hair colouration or our perception of it.
Published: 2018
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17. Schrödinger’s Cat in Simulations in Genome-wide Association Studies

Author: Mustafa Ismail Ozkaraca and Albert Tenesa
Abstract: Simulations are essential components for testing methods or assumptions in genome-wide association studies (GWAS). We show through theory and examples that markers can be both causal and non-causal simultaneously, resulting in a paradox, had simulation not being run properly. We developed a software (ParaPheSim – a paradoxical phenotype simulator) that allows users to create different traits whose genetic correlation is exactly 1 and yet they have no genetic overlap.
Published: 2023
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18. Reply to:Genotype by sex interactions in ankylosing spondylitis

Author: Elena Bernabeu, Konrad Rawlik, Oriol Canela-Xandri, Andrea Talenti, James Prendergast, and Albert Tenesa
Subjects: Genetics
Published: 2023
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19. Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

Author: J. Kenneth Baillie, Andrew Bretherick, Christopher S. Haley, Sara Clohisey, Alan Gray, Lucile P. A. Neyton, Jeffrey Barrett, Eli A. Stahl, Albert Tenesa, Robin Andersson, J. Ben Brown, Geoffrey J. Faulkner, Marina Lizio, Ulf Schaefer, Carsten O. Daub, Masayoshi Itoh, Naoto Kondo, Timo Lassmann, Jun Kawai, IIBDGC Consortium, Damian Mole, Vladimir B. Bajic, Peter Heutink, Michael Rehli, Hideya Kawaji, Albin Sandelin, Harukazu Suzuki, Jack Satsangi, Christine A. Wells, Nir Hacohen, Tom C. Freeman, Yoshihide Hayashizaki, Piero Carninci, Alistair R. R. Forrest, and David A. Hume
Published: 2018
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20. A compendium of genetic regulatory effects across pig tissues

Author: Lingzhao Fang, Jinyan Teng, Yahui Gao, Hongwei Yin, Zhonghao Bai, Shuli Liu, Haonan Zeng, Lijing Bai, Zexi Cai, Bingru Zhao, Xiujin Li, Zhiting Xu, Qing Lin, Zhangyuan Pan, Wenjing Yang, Xiaoshan Yu, Dailu Guan, Yali Hou, Brittney Keel, Gary Rohrer, Amanda Lindholm-Perry, William Oliver, Maria Ballester, Daniel Crespo-Piazuelo, Raquel Quintanilla, Oriol Canela-Xandri, Konrad Rawlik, Charley Xia, Yuelin Yao, Qianyi Zhao, Wenye Yao, Liu Yang, Houcheng Li, Huicong Zhang, Wang Liao, Tianshuo Chen, Peter Karlskov-Mortensen, Merete Fredholm, Marcel Amills, Alex Clop, Elisabetta Giuffra, Jun Wu, Xiaodian Cai, Shuqi Diao, Xiangchun Pan, Chen Wei, Jinghui Li, Hao Cheng, Sheng Wang, Guosheng Su, Goutam Sahana, Mogens Lund, Jack Dekkers, Luke Kramer, Christopher Tuggle, Ryan Corbett, Martien A.M. Groenen, Ole Madsen, Marta Gòdia, Dominique Rocha, Mathieu Charles, Cong-jun Li, Hubert Pausch, Xiaoxiang Hu, Laurent Frantz, Yonglun Luo, Lin Lin, Zhong-Yin Zhou, Zhe Zhang, Zitao Chen, Leilei Cui, Ruidong Xiang, Xia Shen, Pinghua Li, Ruihua Huang, Guoqing Tang, Mingzhou Li, Yunxiang Zhao, Guoqiang Yi, Zhonglin Tang, Jicai Jiang, Fuping Zhao, Xiaolong Yuan, Xiaohong Liu, Yaosheng Chen, Xuewen Xu, Shuhong Zhao, Pengju Zhao, Chris Haley, Huaijun Zhou, Qishan Wang, Yuchun Pan, Xiangdong Ding, Li Ma, Jiaqi Li, Pau Navarro, Qin Zhang, Bingjie Li, Albert Tenesa, Kui Li, and George Liu
Abstract: The Farm animal Genotype-Tissue Expression (FarmGTEx, https://www.farmgtex.org/) project has been established to develop a comprehensive public resource of genetic regulatory variants in domestic animal species, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biology discovery and exploitation in animal breeding and human biomedicine. Here we present results from the pilot phase of PigGTEx (http://piggtex.farmgtex.org/), where we processed 9,530 RNA-sequencing and 1,602 whole-genome sequencing samples from pigs. We build a pig genotype imputation panel, characterize the transcriptional landscape across over 100 tissues, and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We study interactions between genotype and breed/cell type, evaluate tissue specificity of regulatory effects, and elucidate the molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying about 80% of the genetic associations for 207 pig complex phenotypes, and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, corroborating the importance of pigs as a human biomedical model.
Published: 2022
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21. Frequency and phenotype associations of rare variants in 5 monogenic cerebral small vessel disease genes in 200,000 UK Biobank participants

Author: Amy Christina Ferguson, Sophie Thrippleton, David Henshall, Ed Whittaker, Bryan Conway, Malcolm MacLeod, Rainer Malik, Konrad Rawlik, Albert Tenesa, Cathie Sudlow, and Kristiina Rannikmae
Subjects: Neurology (clinical), Genetics (clinical)
Abstract: Background and ObjectivesBased on previous case reports and disease-based cohorts, a minority of patients with cerebral small vessel disease (cSVD) have a monogenic cause, with many also manifesting extracerebral phenotypes. We investigated the frequency, penetrance, and phenotype associations of putative pathogenic variants in cSVD genes in the UK Biobank (UKB), a large population-based study.MethodsWe used a systematic review of previous literature and ClinVar to identify putative pathogenic rare variants in CTSA, TREX1, HTRA1, and COL4A1/2. We mapped phenotypes previously attributed to these variants (phenotypes-of-interest) to disease coding systems used in the UKB's linked health data from UK hospital admissions, death records, and primary care. Among 199,313 exome-sequenced UKB participants, we assessed the following: the proportion of participants carrying ≥1 variant(s); phenotype-of-interest penetrance; and the association between variant carrier status and phenotypes-of-interest using a binary (any phenotype present/absent) and phenotype burden (linear score of the number of phenotypes a participant possessed) approach.ResultsAmong UKB participants, 0.5% had ≥1 variant(s) in studied genes. Using hospital admission and death records, 4%–20% of variant carriers per gene had an associated phenotype. This increased to 7%–55% when including primary care records. Only COL4A1 variant carrier status was significantly associated with having ≥1 phenotype-of-interest and a higher phenotype score (OR = 1.29, p = 0.006).DiscussionWhile putative pathogenic rare variants in monogenic cSVD genes occur in 1:200 people in the UKB population, only approximately half of variant carriers have a relevant disease phenotype recorded in their linked health data. We could not replicate most previously reported gene-phenotype associations, suggesting lower penetrance rates, overestimated pathogenicity, and/or limited statistical power.
Published: 2022
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22. Publisher Correction: Parent of origin genetic effects on methylation in humans are common and influence complex trait variation

Author: Yanni Zeng, Carmen Amador, Charley Xia, Riccardo Marioni, Duncan Sproul, Rosie M. Walker, Stewart W. Morris, Andrew Bretherick, Oriol Canela-Xandri, Thibaud S. Boutin, David W. Clark, Archie Campbell, Konrad Rawlik, Caroline Hayward, Reka Nagy, Albert Tenesa, David J. Porteous, James F. Wilson, Ian J. Deary, Kathryn L. Evans, Andrew M. McIntosh, Pau Navarro, and Chris S. Haley
Subjects: Science
Abstract: In the original version of this Article, the legend in the upper panel of Figure 2 incorrectly read ‘paternal imprinting’ and should have read ‘maternal imprinting’. This has been corrected in both the PDF and HTML versions of the Article.
Published: 2019
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23. Genetic score omics regression and multi-trait meta-analysis detect widespread cis-regulatory effects shaping bovine complex traits

Author: Albert Tenesa and George Liu
Abstract: To complete the genome-to-phenome map, transcriptome-wide association studies (TWAS) are performed to correlate genetically predicted gene expression with observed phenotypic measurements. However, the relatively small training population assayed with gene expression could limit the accuracy of TWAS. We propose Genetic Score Omics Regression (GSOR) correlating observed gene expression with genetically predicted phenotype, i.e., genetic score. The score, calculated using variants near genes with assayed expression, provides a powerful association test between cis-effects on gene expression and the trait. In simulated and real data, GSOR outperforms TWAS in detecting causal/informative genes. Applying GSOR to transcriptomes of 16 tissue (N∼5000) and 37 traits in ∼120,000 cattle, multi-trait meta-analyses of omics-associations (MTAO) found that, on average, each significant gene expression and splicing mediates cis-genetic effects on 8∼10 traits. Supported by Mendelian Randomisation, MTAO prioritised genes/splicing show increased evolutionary constraints. Many newly discovered genes/splicing regions underlie previously thought single-gene loci to influence multiple traits.
Published: 2022
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24. Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

Author: Li Ma, Albert Tenesa, Wentao Cai, Oriol Canela-Xandri, Curtis P. Van Tassell, Bingjie Li, Leeson J. Alexander, Tad S. Sonstegard, Paul M. VanRaden, Shengli Zhang, Shuli Liu, Benjamin D. Rosen, Steven G. Schroeder, Lingzhao Fang, George E. Liu, Congjun Li, Konrad Rawlik, Ying Yu, Yahui Gao, John B. Cole, and Jicai Jiang
Subjects: Resource, Cell type, Candidate gene, Somatic cell, Computational biology, Biology, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Immune system, Genetics, Animals, RNA-Seq, Gene, Genetics (clinical), 030304 developmental biology, Epigenomics, Genetic association, 0303 health sciences, Reproduction, DNA Methylation, Milk, Genes, Organ Specificity, Cattle, Female, 030217 neurology & neurosurgery
Abstract: By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.
Published: 2020
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25. Regional heritability advanced complex trait analysis for GPU and traditional parallel architectures.

Author: Luis Cebamanos, Alan Gray, I. Stewart, and Albert Tenesa
Published: 2014
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26. GWAS and meta-analysis identifies multiple new genetic mechanisms underlying severe Covid-19

Author: Charlotte Summers, Angel Carracedo, Lucija Klarić, Malcolm Gracie Semple, Albert Tenesa, Andy Law, Erola Pairo-Castineira, and John Kenneth Baillie
Abstract: Pulmonary inflammation drives critical illness in Covid-19, 1;2 creating a clinically homogeneous extreme phenotype, which we have previously shown to be highly efficient for discovery of genetic associations. 3;4 Despite the advanced stage of illness, we have found that immunomodulatory therapies have strong beneficial effects in this group. 1;5 Further genetic discoveries may identify additional therapeutic targets to modulate severe disease. 6 In this new data release from the GenOMICC (Genetics Of Mortality in Critical Care) study we include new microarray genotyping data from additional critically-ill cases in the UK and Brazil, together with cohorts of severe Covid-19 from the ISARIC4C 7 and SCOURGE 8 studies, and meta-analysis with previously-reported data. We find an additional 14 new genetic associations. Many are in potentially druggable targets, in inflammatory signalling (JAK1, PDE4A), monocyte-macrophage differentiation (CSF2), immunometabolism (SLC2A5, AK5), and host factors required for viral entry and replication (TMPRSS2, RAB2A). As with our previous work, these results provide tractable therapeutic targets for modulation of harmful host-mediated inflammation in Covid-19.
Published: 2022
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27. Expanded Analysis of Pigmentation Genetics in UK Biobank

Author: Erola Pairo-Castineira, Jaime Cornelissen, Konrad Rawlik, Oriol Canela-Xandri, Stacie K. Loftus, William J. Pavan, Kevin M. Brown, Albert Tenesa, and Ian J. Jackson
Subjects: integumentary system
Abstract: The genetics of pigmentation is an excellent model for understanding gene interactions in a trait almost entirely unaffected by environment. We have analysed pigmentation phenotypes in UK Biobank using DISSECT, a tool which enables genome-wide association studies (GWAS) whilst accounting for relatedness between individuals, and thus allows a much larger cohort to be studied. We have increased the number of candidate genes associated with red and blonde hair colour, basal skin colour and tanning response to UV radiation. As previously described, we find almost all red hair individuals have two variantMC1Ralleles; exome sequence data expands the number of associated coding variants. Rare red-headed individuals with only a singleMC1Rvariant are enriched for an associated eQTL at theASIPgene. We find that females are most likely to self-report red or blonde hair, paler skin and less tanning ability than men, and that variants atKITLG, MC1R, OCA2andIRF4show significant sex differences in effect. After taking sex into account, pigmentation phenotypes are not correlated with sex hormone levels, except for tanning ability, which shows a positive correlation with testosterone in men. Across the UK there is a correlation between place of birth and hair colour; red hair being more common in the north and west, whilst blonde hair is more common in the east. Combining GWAS with transcriptome data to generate a transcriptome wide association study identifies candidate genes whose expression in skin or melanocytes shows association with pigmentation phenotypes. A comparison of candidates associated with different pigmentation phenotypes finds that candidates for blonde hair, but not skin colour, are enriched for skin and hair genes suggesting that it may be hair shape and structure that impacts hair colour, rather than the melanocyte/keratinocyte interaction.
Published: 2022
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28. A multi-tissue atlas of regulatory variants in cattle: Cattle Genotype-Tissue Expression Atlas

Author: Shuli Liu, Yahui Gao, Oriol Canela-Xandri, Sheng Wang, Ying Yu, Wentao Cai, Bingjie Li, Erola Pairo-Castineira, Kenton D’Mellow, Konrad Rawlik, Charley Xia, Yuelin Yao, Xiujin Li, Ze Yan, Congjun Li, Benjamin D. Rosen, Curtis P. Van Tassell, Paul M. Vanraden, Shengli Zhang, Li Ma, John B. Cole, George E. Liu, Albert Tenesa, Lingzhao Fang
Published: 2022
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29. Improved Genetic Profiling of Anthropometric Traits Using a Big Data Approach.

Author: Oriol Canela-Xandri, Konrad Rawlik, John A Woolliams, and Albert Tenesa
Subjects: Medicine, Science
Abstract: Genome-wide association studies (GWAS) promised to translate their findings into clinically beneficial improvements of patient management by tailoring disease management to the individual through the prediction of disease risk. However, the ability to translate genetic findings from GWAS into predictive tools that are of clinical utility and which may inform clinical practice has, so far, been encouraging but limited. Here we propose to use a more powerful statistical approach, the use of which has traditionally been limited due to computational requirements and lack of sufficiently large individual level genotyped cohorts, but which improve the prediction of multiple medically relevant phenotypes using the same panel of SNPs. As a proof of principle, we used a shared panel of 319,038 common SNPs with MAF > 0.05 to train the prediction models in 114,264 unrelated White-British individuals for height and four obesity related traits (body mass index, basal metabolic rate, body fat percentage, and waist-to-hip ratio). We obtained prediction accuracies that ranged between 46% and 75% of the maximum achievable given the captured heritable component. For height, this represents an improvement in prediction accuracy of up to 68% (184% more phenotypic variance explained) over SNPs reported to be robustly associated with height in a previous GWAS meta-analysis of similar size. Across-population predictions in White non-British individuals were similar to those in White-British whilst those in Asian and Black individuals were informative but less accurate. We estimate that the genotyping of circa 500,000 unrelated individuals will yield predictions between 66% and 82% of the SNP-heritability captured by common variants in our array. Prediction accuracies did not improve when including rarer SNPs or when fitting multiple traits jointly in multivariate models.
Published: 2016
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30. Advanced Complex Trait Analysis.

Author: Alan Gray, I. Stewart, and Albert Tenesa
Published: 2012
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31. Frequency and phenotype associations of rare variants in five monogenic cerebral small vessel disease genes in 200,000 UK Biobank participants with whole exome sequencing data

Author: Albert Tenesa, Cathie Sudlow, Rainer Malik, Sophie Thrippleton, Amy C Ferguson, Bryan R. Conway, Kristiina Rannikmäe, Konrad Rawlik, Malcolm R. Macleod, Ed Whittaker, and David E. Henshall
Subjects: Genetics, education.field_of_study, HTRA1, Population, Disease, Biology, education, Biobank, Penetrance, Gene, Phenotype, Exome sequencing
Abstract: Based on previous case reports and disease-based cohorts, a minority of patients with cerebral small vessel disease (cSVD) have a monogenic cause, with many also manifesting extra-cerebral phenotypes. We investigated the frequency, penetrance, and phenotype associations of rare variants in cSVD genes in UK Biobank (UKB), a large population-based study.We used a systematic review of previous literature and ClinVar to identify putative pathogenic rare variants in CTSA, TREX1, HTRA1, COL4A1/2. We mapped phenotypes previously attributed to these variants (phenotypes-of-interest) to disease coding systems used in UKB’s linked health data from UK hospital admissions, death records and primary care. Among 199,313 exome-sequenced UKB participants, we assessed: the proportion of participants carrying ≥1 variant(s); phenotype-of-interest penetrance; and the association between variant carrier status and phenotypes-of-interest using a binary (any phenotype present/absent) and phenotype burden (linear score of the number of phenotypes a participant possessed) approach.Among UKB participants, 0.5% had ≥1 variant(s) in studied genes. Using hospital admission and death records, 4-20% of variant carriers per gene had an associated phenotype. This increased to 7-55% when including primary care records. Only COL4A1 variant carrier-status was significantly associated with having ≥1 phenotype-of-interest and a higher phenotype score (OR=1.29, p=0.006).While putative pathogenic rare variants in monogenic cSVD genes occur in 1:200 people in the UKB population, only around half of variant carriers have a relevant disease phenotype recorded in their linked health data. We could not replicate most previously reported gene-phenotype associations, suggesting lower penetrance rates, overestimated pathogenicity and/or limited statistical power.
Published: 2021
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32. Mapping the human genetic architecture of COVID-19: an update

Author: Massimo GIRARDIS, Andrea Antinori, Eunate Arana-Arri, Stefania Mantovani, Nadia Harerimana, Carlota Dobaño Lazaro, Elisa Arribas Rodríguez, Maria Teresa La Rovere, Albert Tenesa, Arianna Gabrieli, Elizabeth Atkinson, Chiara Fallerini, David Bernardo, Kai Kisand, Jahad Alghamdi, Alex Soriano, Vorasuk Shotelersuk, Aida Fiz López, Carlo Rivolta, Andrea Ganna, Elena Bargagli, Francesca Fava, and Maurizio Bussotti
Subjects: Vaccination, Disease susceptibility, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Evolutionary biology, Public health, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Pandemic, medicine, Genome-wide association study, Biology, Genetic architecture
Abstract: The Coronavirus Disease 2019 (COVID-19) pandemic continues to pose a major public health threat especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity we formed the COVID19 Host Genetics Initiative. Here we present GWAS meta-analysis of up to 125,584 cases and over 2.5 million controls across 60 studies from 25 countries, adding 11 new genome-wide significant loci compared to those previously identified. Genes in novel loci include SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.
Published: 2021
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33. Physician-confirmed and administrative definitions of stroke in UK Biobank reflect the same underlying genetic trait

Author: Catherine Sudlow, Nicola Pirastu, Xia Shen, Albert Tenesa, Avramidis N, Jiang M, Rainer Malik, Amy C Ferguson, Konrad Rawlik, Davidson E, Kristiina Rannikmäe, Woodfield R, and Martin Dichgans
Subjects: business.industry, Trait, Medicine, Genome-wide association study, Primary care, business, medicine.disease, Biobank, Stroke, Confidence interval, Death record, Demography, Genetic association
Abstract: BackgroundStroke in UK Biobank (UKB) is ascertained via linkages to coded administrative datasets and self-report. We studied the accuracy of these codes using genetic validation.MethodsWe compiled stroke-specific and broad cerebrovascular disease (CVD) code lists (Read V2/V3, ICD-9/-10) for medical settings (hospital, death record, primary care) and self-report. Among 408,210 UKB participants we identified all with a relevant code, creating 12 stroke definitions based on the code type and source. We performed genome-wide association studies (GWASs) for each definition, comparing summary results against the largest published stroke GWAS (MEGASTROKE), assessing genetic correlations, and replicating 32 stroke-associated loci.ResultsStroke case numbers identified varied widely from 3,976 (primary care stroke-specific codes) to 19,449 (all codes, all sources). All 12 UKB stroke definitions were significantly correlated with the MEGASTROKE summary GWAS results (rg 0.81-1) and each other (rg 0.4-1). However, Bonferroni-corrected confidence intervals were wide, suggesting limited precision of some results. Six previously reported stroke-associated loci were replicated using ≥1 UKB stroke definitions.ConclusionsStroke case numbers in UKB depend on the code source and type used, with a 5-fold difference in the maximum case-sample size. All stroke definitions are significantly genetically correlated with the largest stroke GWAS to date.
Published: 2021
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34. Modulation of genetic associations with serum urate levels by body-mass-index in humans.

Author: Jennifer E Huffman, Eva Albrecht, Alexander Teumer, Massimo Mangino, Karen Kapur, Toby Johnson, Zoltán Kutalik, Nicola Pirastu, Giorgio Pistis, Lorna M Lopez, Toomas Haller, Perttu Salo, Anuj Goel, Man Li, Toshiko Tanaka, Abbas Dehghan, Daniela Ruggiero, Giovanni Malerba, Albert V Smith, Ilja M Nolte, Laura Portas, Amanda Phipps-Green, Lora Boteva, Pau Navarro, Asa Johansson, Andrew A Hicks, Ozren Polasek, Tõnu Esko, John F Peden, Sarah E Harris, Federico Murgia, Sarah H Wild, Albert Tenesa, Adrienne Tin, Evelin Mihailov, Anne Grotevendt, Gauti K Gislason, Josef Coresh, Pio D'Adamo, Sheila Ulivi, Peter Vollenweider, Gerard Waeber, Susan Campbell, Ivana Kolcic, Krista Fisher, Margus Viigimaa, Jeffrey E Metter, Corrado Masciullo, Elisabetta Trabetti, Cristina Bombieri, Rossella Sorice, Angela Döring, Eva Reischl, Konstantin Strauch, Albert Hofman, Andre G Uitterlinden, Melanie Waldenberger, H-Erich Wichmann, Gail Davies, Alan J Gow, Nicola Dalbeth, Lisa Stamp, Johannes H Smit, Mirna Kirin, Ramaiah Nagaraja, Matthias Nauck, Claudia Schurmann, Kathrin Budde, Susan M Farrington, Evropi Theodoratou, Antti Jula, Veikko Salomaa, Cinzia Sala, Christian Hengstenberg, Michel Burnier, Reedik Mägi, Norman Klopp, Stefan Kloiber, Sabine Schipf, Samuli Ripatti, Stefano Cabras, Nicole Soranzo, Georg Homuth, Teresa Nutile, Patricia B Munroe, Nicholas Hastie, Harry Campbell, Igor Rudan, Claudia Cabrera, Chris Haley, Oscar H Franco, Tony R Merriman, Vilmundur Gudnason, Mario Pirastu, Brenda W Penninx, Harold Snieder, Andres Metspalu, Marina Ciullo, Peter P Pramstaller, Cornelia M van Duijn, Luigi Ferrucci, Giovanni Gambaro, Ian J Deary, Malcolm G Dunlop, James F Wilson, Paolo Gasparini, Ulf Gyllensten, Tim D Spector, Alan F Wright, Caroline Hayward, Hugh Watkins, Markus Perola, Murielle Bochud, W H Linda Kao, Mark Caulfield, Daniela Toniolo, Henry Völzke, Christian Gieger, Anna Köttgen, and Veronique Vitart
Subjects: Medicine, Science
Abstract: We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.
Published: 2015
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35. Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

Author: Fallerini, Chiara, Picchiotti, Nicola, Baldassarri, Margherita, Zguro, Kristina, Daga, Sergio, Fava, Francesca, Benetti, Elisa, Amitrano, Sara, Bruttini, Mirella, Palmieri, Maria, Croci, Susanna, Lista, Mirjam, Beligni, Giada, Valentino, Floriana, Meloni, Ilaria, Tanfoni, Marco, Minnai, Francesca, Colombo, Francesca, Cabri, Enrico, Fratelli, Maddalena, Gabbi, Chiara, Mantovani, Stefania, Frullanti, Elisa, Gori, Marco, Crawley, Francis P, Butler-Laporte, Guillaume, Richards, Brent, Zeberg, Hugo, Lipcsey, Miklos, Hultström, Michael, Ludwig, Kerstin U, Schulte, Eva C, Pairo-Castineira, Erola, Baillie, John Kenneth, Schmidt, Axel, Frithiof, Robert, Mari, Francesca, Renieri, Alessandra, Furini, Simone Simone Furini, Francesca, Montagnani, Mario, Tumbarello, Ilaria, Rancan, Massimiliano, Fabbiani, Barbara, Rossetti, Laura, Bergantini, Miriana, D'Alessandro, Paolo, Cameli, David, Bennett, Federico, Anedda, Simona, Marcantonio, Sabino, Scolletta, Federico, Franchi, Maria Antonietta Mazzei, Susanna, Guerrini, Edoardo, Conticini, Luca, Cantarini, Bruno, Frediani, Danilo, Tacconi, Chiara Spertilli Raffaelli, Marco, Feri, Alice, Donati, Raffaele, Scala, Luca, Guidelli, Genni, Spargi, Marta, Corridi, Cesira, Nencioni, Leonardo, Croci, Gian Piero Caldarelli, Maurizio, Spagnesi, Davide, Romani, Paolo, Piacentini, Maria, Bandini, Elena, Desanctis, Silvia, Cappelli, Anna, Canaccini, Agnese, Verzuri, Valentina, Anemoli, Manola, Pisani, Agostino, Ognibene, Alessandro, Pancrazzi, Maria, Lorubbio, Massimo, Vaghi, Antonella, D 'Arminio Monforte, Federica Gaia Miraglia, Mario, U Mondelli, Massimo, Girardis, Sophie, Venturelli, Stefano, Busani, Andrea, Cossarizza, Andrea, Antinori, Alessandra, Vergori, Arianna, Emiliozzi, Stefano, Rusconi, Matteo, Siano, Arianna, Gabrieli, Agostino, Riva, Daniela, Francisci, Elisabetta, Schiaroli, Francesco, Paciosi, Andrea, Tommasi, Pier Giorgio Scotton, Francesca, Andretta, Sandro, Panese, Stefano, Baratti, Renzo, Scaggiante, Francesca, Gatti, Saverio Giuseppe Parisi, Francesco, Castelli, Eugenia, Quiros-Roldan, Melania Degli Antoni, Isabella, Zanella, Matteo Della Monica, Carmelo, Piscopo, Mario, Capasso, Roberta, Russo, Immacolata, Andolfo, Achille, Iolascon, Giuseppe, Fiorentino, Massimo, Carella, Marco, Castori, Filippo, Aucella, Pamela, Raggi, Rita, Perna, Matteo, Bassetti, Antonio Di Biagio, Maurizio, Sanguinetti, Luca, Masucci, Alessandra, Guarnaccia, Serafina, Valente, Oreste De Vivo, Gabriella, Doddato, Rossella, Tita, Annarita, Giliberti, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Valentina, Perticaroli, Francesca, Ariani, Miriam Lucia Carriero, Laura Di Sarno, Diana, Alaverdian, Elena, Bargagli, Marco, Mandalà, Alessia, Giorli, Lorenzo, Salerni, Patrizia, Zucchi, Pierpaolo, Parravicini, Elisabetta, Menatti, Tullio, Trotta, Ferdinando, Giannattasio, Gabriella, Coiro, Fabio, Lena, Leonardo Gianluca Lacerenza, Domenico, A Coviello, Cristina, Mussini, Enrico, Martinelli, Sandro, Mancarella, Luisa, Tavecchia, Mary Ann Belli, Lia, Crotti, Gianfranco, Parati, Maurizio, Sanarico, Francesco, Raimondi, Filippo, Biscarini, Alessandra, Stella, Marco, Rizzi, Franco, Maggiolo, Diego, Ripamonti, Claudia, Suardi, Tiziana, Bachetti, Maria Teresa La Rovere, Simona, Sarzi-Braga, Maurizio, Bussotti, Katia, Capitani, Simona, Dei, Sabrina, Ravaglia, Rosangela, Artuso, Elena, Andreucci, Giulia, Gori, Angelica, Pagliazzi, Erika, Fiorentini, Antonio, Perrella, Francesco, Bianchi, Paola, Bergomi, Emanuele, Catena, Riccardo, Colombo, Sauro, Luchi, Giovanna, Morelli, Paola, Petrocelli, Sarah, Iacopini, Sara, Modica, Silvia, Baroni, Francesco Vladimiro Segala, Francesco, Menichetti, Marco, Falcone, Giusy, Tiseo, Chiara, Barbieri, Tommaso, Matucci, Grassi, Davide, Ferri, Claudio, Marinangeli, Franco, Brancati, Francesco, Antonella, Vincenti, Valentina, Borgo, Lombardi, Stefania, Mirco, Lenzi, Massimo Antonio Di Pietro, Francesca, Vichi, Benedetta, Romanin, Letizia, Attala, Cecilia, Costa, Andrea, Gabbuti, Menè, Roberto, Umberto, Zuccon, Lucia, Vietri, Stefano, Ceri, Pietro, Pinoli, Patrizia, Casprini, Giuseppe, Merla, Gabriella Maria Squeo, Marcello, Maffezzoni, Raffaele, Bruno, Marco, Vecchia, Marta, Colaneri, Serena, Ludovisi, Yanara, Marincevic-Zuniga, Jessica, Nordlund, Tomas, Luther, Anders, Larsson, Katja Hanslin Anna Gradin, Sarah, Galien, Sara Bulow Anderberg, Jacob, Rosén, Sten, Rubertsson, Hugo, Zeberg, Robert, Frithiof, Miklós, Lipcsey, Michael, Hultström, Sara Clohisey Peter Horby, Johnny, Millar, Julian, Knight, Hugh, Montgomery, David, Maslove, Lowell, Ling, Alistair, Nichol, Charlotte, Summers, Tim, Walsh, Charles, Hinds, Malcolm, G Semple, Peter J, M Openshaw, Manu, Shankar-Hari, Antonia, Ho, Danny, Mcauley, Chris, Ponting, Kathy, Rowan, J Kenneth Baillie, Fiona, Griffiths, Wilna, Oosthuyzen, Jen, Meikle, Paul, Finernan, James, Furniss, Ellie, Mcmaster, Andy, Law, Sara, Clohisey, Trevor, Paterson, Tony, Wackett, Ruth, Armstrong, Lee, Murphy, Angie, Fawkes, Richard, Clark, Audrey, Coutts, Lorna, Donnelly, Tammy, Gilchrist, Katarzyna, Hafezi, Louise, Macgillivray, Alan, Maclean, Sarah, Mccafferty, Kirstie, Morrice, Jane, Weaver, Ceilia, Boz, Ailsa, Golightly, Mari, Ward, Hanning, Mal, Helen, Szoor-McElhinney, Adam, Brown, Ross, Hendry, Andrew, Stenhouse, Louise, Cullum, Dawn, Law, Sarah, Law, Rachel, Law, Max Head Fourman, Maaike, Swets, Nicky, Day, Filip, Taneski, Esther, Duncan, Marie, Zechner, Nicholas, Parkinson, Erola, Pairo-Castineira, Lucija, Klaric, Andrew, D Bretherick, Konrad, Rawlik, Dorota, Pasko, Susan, Walker, Nick, Parkinson, Clark, D Russell, Anne, Richmond, Elvina, Gountouna, David, Harrison, Wang, Bo, Yang, Wu, Alison, Meynert, Athanasios, Kousathanas, Loukas, Moutsianas, Zhijian, Yang, Ranran, Zhai, Chenqing, Zheng, Graeme, Grimes, Jonathan, Millar, Barbara, Shih, Jian, Yang, Xia, Shen, Chris, P Ponting, Albert, Tenesa, Andrew, Law, Veronique, Vitart, James, F Wilson, Collier, D, Wood, S, Zak, A, Borra, C, Matharu, M, May, P, Alldis, Z, Mitchelmore, O, Bowles, R, Easthorpe, A, Bibi, F, Lancoma-Malcolm, I, Gurasashvili, J, Pheby, J, Shiel, J, Bolton, M, Patel, M, Taylor, M, Zongo, O, Ebano, P, Harding, P, Astin-Chamberlain, R, Choudhury, Y, Cox, A, Kallon, D, Burton, M, Hall, R, Blowes, S, Prime, Z, Biddle, J, Prysyazhna, O, Newman, T, Tierney, C, Kassam, J, Shankar-Hari, M, Ostermann, M, Campos, S, Bociek, A, Lim, R, Grau, N, O Jones, T, Whitton, C, Marotti, M, Arbane, G, Bonner, S, Hugill, K, Reid, J, Welters, I, Waugh, V, Williams, K, Shaw, D, J Fernandez Roman, M Lopez Martinez, Johnson, E, Waite, A, Johnson, B, Hamilton, O, Mulla, S, Mcphail, M, Smith, J, K Baillie, J, Barclay, L, Hope, D, Mcculloch, C, Mcquillan, L, Clark, S, Singleton, J, Priestley, K, Rea, N, Callaghan, M, Campbell, R, Andrew, G, Marshall, L, Mckechnie, S, Hutton, P, Bashyal, A, Davidson, N, Summers, C, Polgarova, P, Stroud, K, Pathan, N, Elston, K, Agrawal, S, Battle, C, Newey, L, Rees, T, Harford, R, Brinkworth, E, Williams, M, Murphy, C, White, I, Croft, M, Bandla, N, Gellamucho, M, Tomlinson, J, Turner, H, Davies, M, Quinn, A, Hussain, I, Thompson, C, Parker, H, Bradley, R, Griffiths, R, Scriven, J, Gill, J, Puxty, A, Cathcart, S, Salutous, D, Turner, L, Duffy, K, Puxty, K, Joseph, A, Herdman-Grant, R, Simms, R, Swain, A, Naranjo, A, Crowe, R, Sollesta, K, Loveridge, A, Baptista, D, Morino, E, Davey, M, Golden, D, Jones, J, J Moreno Cuesta, Haldeos, A, Bakthavatsalam, D, Vincent, R, Elhassan, M, Xavier, K, Ganesan, A, Purohit, D, Abdelrazik, M, Morgan, J, Akeroyd, L, Bano, S, Warren, D, Bromley, M, Sellick, K, Gurr, L, Wilkinson, B, Nagarajan, V, Szedlak, P, Cupitt, J, Stoddard, E, Benham, L, Preston, S, Slawson, N, Bradshaw, Z, Brown, J, Caswell, M, Smelling, Bamford, P, Faulkner, M, Cawley, K, Jeffrey, H, London, E, Sainsbury, H, Nagra, I, Nasir, F, Dunmore, Ce, Jones, R, Abraheem, A, Al-Moasseb, M, Girach, R, Brantwood, C, Alexander, P, Bradley-Potts, J, Allen, S, Felton, T, Manna, S, Farnell-Ward, S, Leaver, S, Queiroz, J, Maccacari, E, Dawson, D, C Castro Delgado, R Pepermans Saluzzio, Ezeobu, O, Ding, L, Sicat, C, Kanu, R, Durrant, G, Texeira, J, Harrison, A, Samakomva, T, Willis, H, Hopkins, B, Thrasyvoulou, L, Jackson, M, Zaki, A, Tibke, C, Bennett, S, Woodyatt, W, Kent, A, Goodwin, E, Brandwood, C, Clark, R, Smith, L, Rooney, K, Thomson, N, Rodden, N, Hughes, E, Mcglynn, D, Clark, C, Clark, P, Abel, L, Sundaram, R, Gemmell, L, Brett, M, Hornsby, J, Macgoey, P, Price, R, Digby, B, O'Neil, P, Mcconnell, P, Henderson, P, Henderson, S, Sim, M, Kennedy-Hay, S, Mcparland, C, Rooney, L, Baxter, N, Pogson, D, Rose, S, Daly, Z, Brimfield, L, K Phull, M, Hussain, M, Pogreban, T, Rosaroso, L, E Salciute, L Grauslyte, Brealey, D, Wraith, E, Maccallum, N, Bercades, G, Hass, I, Smyth, D, Reyes, A, Martir, G, D Clement, I, Webster, K, Hays, C, Gulati, A, Hodgson, L, Margarson, M, Gomez, R, Baird, Y, Thirlwall, Y, Folkes, L, Butler, A, Meadows, E, Moore, S, Raynard, D, Fox, H, Riddles, L, King, K, Kimber, S, Hobden, G, Mccarthy, A, Cannons, V, Balagosa, I, Chadbourn, I, Gardner, A, Horner, D, Mclaughlanv, D, Charles, B, Proudfoot, N, Marsden, T, L Mc Morrow, Blackledge, B, Pendlebury, J, Harvey, A, Apetri, E, Basikolo, C, Catlow, L, Doonan, R, Knowles, K, Lee, S, Lomas, D, Lyons, C, Perez, J, Poulaka, M, Slaughter, M, Slevin, K, Thomas, V, Walker, D, Harris, J, Drummond, A, Tully, R, Dearden, J, Philbin, J, Munt, S, Rishton, C, O'Connor, G, Mulcahy, M, Dobson, E, Cuttler, J, Edward, M, Rose, A, Sloan, B, Buckley, S, Brooke, H, Smithson, E, Charlesworth, R, Sandu, R, Thirumaran, M, Wagstaff, V, J Cebrian Suarez, Kaliappan, A, Vertue, M, Nicholson, A, Riches, J, Solesbury, A, Kittridge, L, Forsey, M, Maloney, G, Cole, J, Davies, R, Hill, H, Thomas, E, Williams, A, Duffin, D, Player, B, Radhakrishnan, J, Gibson, S, Lyle, A, Mcneela, F, Patel, B, Gummadi, M, Sloane, G, Dormand, N, Salmi, S, Farzad, Z, Cristiano, D, Liyanage, K, Thwaites, V, Varghese, M, Meredith, M, Mills, G, Willson, J, Harrington, K, Lenagh, B, Cawthron, K, Masuko, S, Raithatha, A, Bauchmuller, K, Ahmad, N, Barker, J, Jackson, Y, Kibutu, F, Bird, S, Watson, G, Martin, J, Bevan, E, C Wrey Brown, Trodd, D, English, K, Bell, G, Wilcox, L, Katary, A, Gopal, S, Lake, V, Harris, N, Metherell, S, Radford, E, Moore, F, Bancroft, H, Daglish, J, Sangombe, M, Carmody, M, Rhodes, J, Bellamy, M, Garg, A, Kuravi, A, Virgilio, E, Ranga, P, Butler, J, Botfield, L, Dexter, C, Fletcher, J, Shanmugasundaram, P, Hambrook, G, Burn, I, Manso, K, Thornton, D, Tebbutt, J, Penn, R, Hulme, J, Hussain, S, Maqsood, Z, Joseph, S, Colley, J, Hayes, A, Ahmed, C, Haque, R, Clamp, S, Kumar, R, Purewal, M, Baines, B, Frise, M, Jacques, N, Coles, H, Caterson, J, S Gurung Rai, Brunton, M, Tilney, E, Keating, L, Walden, A, Antcliffe, D, Gordon, A, Templeton, M, Rojo, R, Banach, D, S Sousa Arias, Fernandez, Z, Coghlan, P, Williams, D, Jardine, C, Bewley, J, Sweet, K, Grimmer, L, Johnson, R, Garland, Z, Gumbrill, B, Phillips, C, L Ortiz-Ruiz de Gordoa, Peasgood, E, Tridente, A, K Shuker, S Greer, Lynch, C, Pothecary, C, Roche, L, Deacon, B, Turner, K, Singh, J, G Sera Howe, Paul, P, Gill, M, Wynter, I, Ratnam, V, Shelton, S, Naisbitt, J, Melville, J, Baruah, R, Morrison, S, Mcgregor, A, Parris, V, Mpelembue, M, Srikaran, S, Dennis, C, Sukha, A, Verlande, M, Holding, K, Riches, K, Downes, C, Swan, C, Rostron, A, Roy, A, Woods, L, Cornell, S, Wakinshaw, F, Creagh-Brown, B, Blackman, H, Salberg, A, Smith, E, Donlon, S, Mtuwa, S, Michalak-Glinska, N, Stone, S, Beazley, C, Pristopan, V, Nikitas, N, Lankester, L, Wells, C, S Raj, A, Fletcher, K, Khade, R, Tsinaslanidis, G, Mcmahon, M, Fowler, S, Coventry, T, Stewart, R, Wren, L, Mwaura, E, Mew, L, Scaletta, D, Williams, F, Inweregbu, K, Lancaster, N, Cunningham, M, Daniels, A, Harrison, L, Hope, S, Jones, S, Crew, A, Wray, G, Matthews, J, Crawley, R, Carter, J, Birkinshaw, I, Ingham, J, Scott, Z, Howard, K, Joy, R, Roche, S, Clark, M, Purvis, S, Morrison, A, Strachan, D, Clements, S, Black, K, Parmar, C, Altabaibeh, A, Simpson, K, Mostoles, L, Gilbert, K, L, Ma, Alvaro, A, Thomas, M, Faulkner, B, Worner, R, Hayes, K, Gendall, E, Blakemore, H, Borislavova, B, Goff, E, Vuylsteke, A, Mwaura, L, Zamikula, J, Garner, L, Mitchell, A, Mepham, S, Cagova, L, Fofano, A, Holcombe, H, Praman, K, Szakmany, T, E Heron, A, Cherian, S, Cutler, S, Roynon-Reed, A, Randell, G, Convery, K, K Stammers, D Fottrell-Gould, Hudig, L, Keshet-Price, J, Peters, M, O'Neill, L, Ray, S, Belfield, H, Mchugh, T, Jones, G, Akinkugbe, O, Tomas, A, Abaleke, E, Beech, E, Meghari, H, Yussuf, S, Bamford, A, Hairsine, B, Dooks, E, Farquhar, F, Packham, S, Bates, H, Armstrong, L, Kaye, C, Allan, A, Medhora, J, Liew, J, Botello, A, Anderson, F, Cusack, R, Golding, H, Prager, K, Williams, T, Leggett, S, Golder, K, Male, M, Jones, O, Criste, K, Marani, M, Anumakonda, V, Amin, V, Karthik, K, Kausar, R, Anastasescu, E, Reid, K, Jacqui, M, Hormis, A, Walker, R, Duncan, T, Uriel, A, Ustianowski, A, T-Michael, H, Bruce, M, Connolly, K, Smith, K, Partridge, R, Griffin, D, Mcdonald, M, Muchenje, N, Martin, D, Filipe, H, Eastgate, C, Jackson, C, Gratrix, A, Foster, L, Martinson, V, Stones, E, Caroline, Abernathy, Parkinson, P, Reed, A, Prendergast, C, Rogers, P, Woodruff, M, Shokkar, R, Kaul, S, Barron, A, Collins, C, Beavis, S, Whileman, A, Dale, K, Hawes, J, Pritchard, K, Gascoyne, R, Stevenson, L, Jha, R, Lim, L, Krishnamurthy, V, Parker, R, Turner-Bone, I, Wilding, L, Reddy, A, Whiteley, S, Wilby, E, Howcroft, C, Aspinwall, A, Charlton, S, Ogg, B, Menzies, D, Pugh, R, Allan, E, Lean, R, Davies, F, Easton, J, Qiu, X, Kumar, S, Darlington, K, Houston, G, O'Brien, P, Geary, T, Allan, J, Meikle, A, Hughes, G, Balasubramaniam, M, Latham, S, Mckenna, E, Flanagan, R, Sathe, S, Davies, E, Chablani, M, Kirkby, A, Netherton, K, Archer, S, Yates, B, Ashbrook-Raby, C, Cole, S, Casey, M, Cabrelli, L, Chapman, S, Austin, P, Hutcheon, A, Whyte, C, Almaden-Boyle, C, Pattison, N, Cruz, C, Vochin, A, Kent, H, Thomas, A, Murdoch, S, David, B, Penacerrada, M, Lubimbi, G, Bastion, V, Wulandari, R, Valentine, J, Clarke, D, Serrano-Ruiz, A, Hierons, S, Ramos, L, Demetriou, C, Mitchard, S, White, K, White, N, Pitts, S, Branney, D, Frankham, J, Watters, M, Langton, H, Prout, R, Page, V, Varghes, T, Cowton, A, Kay, A, Potts, K, Birt, M, Kent, M, Wilkinson, A, Jude, E, Turner, V, Savill, H, Mccormick, J, Coulding, M, Siddiqui, S, Mercer, O, Rehman, H, Potla, D, Capps, N, Donaldson, D, Button, H, Martin, T, Hard, K, Agasou, A, Tonks, L, Arden, T, Boyle, P, Carnahan, M, Strickley, J, Adams, C, Childs, D, Rikunenko, R, Leigh, M, Breekes, M, Wilcox, R, Bowes, A, Tiveran, H, Hurford, F, Summers, J, Carter, A, Hussain, Y, Ting, L, Javaid, A, Motherwell, N, Moore, H, Millward, H, Jose, S, Schunki, N, Noakes, A, Clulow, C, Sadera, G, Jacob, R, Jones, C, Blunt, M, Coton, Z, Curgenven, H, S Mohamed Ally, Beaumont, K, Elsaadany, M, Fernandes, K, I Ali Mohamed Ali, Rangarajan, H, Sarathy, V, Selvanayagam, S, Vedage, D, White, M, Smith, M, Truman, N, Chukkambotla, S, Keith, S, Cockerill-Taylor, J, Ryan-Smith, J, Bolton, R, Springle, P, Dykes, J, Thomas, J, Khan, M, T Hijazi, M, Massey, E, Croston, G, Reschreiter, H, Camsooksai, J, Patch, S, Jenkins, S, Humphrey, C, Wadams, B, Bhatia, N, Msiska, M, Adanini, O, Attwood, B, Parsons, P, Tatham, K, Jhanji, S, Black, E, A Dela Rosa, Howle, R, Thomas, B, Bemand, T, Raobaikady, R, Saha, R, Staines, N, Daniel, A, Finn, J, Hutter, J, Doble, P, Shovelton, C, Pawley, C, Kannan, T, Hill, M, Combes, E, Monnery, S, Joefield, T, Popescu, M, Thankachen, M, Oblak, M, Little, J, Mcivor, S, Brady, A, Whittle, H, Prady, H, Chan, R, Ahmed, A, Morris, A, Gibson, C, Gordon, E, Keenan, S, Quinn, H, Benyon, S, Marriott, S, Zitter, L, Park, L, Baines, K, Lyons, M, Holland, M, Keenan, N, Young, M, Garrioch, S, Dawson, J, Tolson, M, Scholefield, B, R, Bi, Richardson, N, Schumacher, N, Cosier, T, Millen, G, Higham, A, Turki, S, Allen, L, Crisp, N, Hazleton, T, Knight, A, Deery, J, Price, C, Turney, S, Tilbey, S, Beranova, E, Wright, D, Georg, L, Twiss, S, Wadd, S, Postlethwaite, K, Gondo, P, Masunda, B, Kayani, A, Hadebe, B, Whiteside, J, Clarke, N, Donnison, P, Trim, F, Leadbitter, I, Butcher, D, O'Sullivan, S, Purewal, B, Bell, S, Rivers', V, O'Leary, R, Birch, J, Collins, E, Anderson, S, Hammerton, K, Andrews, E, Burns, K, Edmond, I, Todd, A, Donnachie, J, Turner, P, Prentice, L, Symon, L, Runciman, N, Auld, F, Halkes, M, Mercer, P, Thornton, L, Debreceni, G, Wilkins, J, Brown, A, Crickmore, V, Subramanian, G, Marshall, R, Jennings, C, Latif, M, Bunni, L, Spivey, M, Bean, S, Burt, K, Linnett, V, Ritzema, J, Sanderson, A, Mccormick, W, Bokhari, M, Kapoor, R, Loader, D, Ayers, A, Harrison, W, North, J, Belagodu, Z, Parasomthy, R, Olufuwa, O, Gherman, A, Fuller, B, Stuart, C, Kelsall, O, Davis, C, Wild, L, Wood, H, Thrush, J, Durie, A, Austin', K, Archer, K, Anderson, P, Vigurs, C, Thorpe, C, Knights, E, Boyle, N, Price, A, Kubisz-Pudelko, A, Wood, D, Lewis, A, Board, S, Pippard, L, Perry, J, Beesley, K, Rattray, A, Lee, E, Lennon, L, Douglas, K, Bell, D, Boyle, R, Glass, L, M Nauman Akhtar, Dent, K, Potoczna, D, Pearson, S, Horsley, E, Spencer, S, Mullan, D, Skinner, D, Gaylard, J, Ortiz-Ruizdegordoa, L, Barber, R, Hewitt, C, Hilldrith, A, Shepardson, S, Wills, M, Jackson-Lawrence, K, Gupta, A, Easthope, A, Timlick, E, Gorman, C, Otaha, I, Gales, A, Coetzee, S, Raj, M, Peiu, M, Quaid, S, Watson, E, Elliott, K, Mallinson, J, Chandler, B, Turnbull, A, Finch, C, Holl, C, Cooper, J, Evans, A, Khaliq, W, Collins, A, E Treus Gude, Love, N, L van Koutrik, Hunt, J, Kaye, D, Fisher, E, Brayne, A, Tuckey, V, Jackson, P, Parkin, J, Raith, E, Tariq, A, Houlden, H, Tucci, A, Hardy, J, Moncur, E, Highgate, J, Cowley, A, Mitra, A, Stead, R, Behan, T, Burnett, C, Newton, M, Heeney, E, Pollard, R, Hatton, J, Patel, A, Kasipandian, V, Allibone, S, M Genetu, R, Otahal, I, O'Brien, L, Omar, Z, Perkins, E, Davies, K, Tetla, D, Shelley, B, Irvine, V, Williams, S, Williams, P, Goodsell, J, Tutton, R, Bough, L, Winter-Goodwin, B, Kitson, R, Pinnell, J, Wilson, A, Nortcliffe, T, Wood, T, Home, M, Holdroyd, K, Robinson, M, Shaw, R, Greig, J, Brady, M, Haigh, A, Matupe, L, Usher, M, Mellor, S, Dale, S, Gledhill, L, Shaw, L, Turner, G, Kelly, D, Anwar, B, Riley, H, Sturgeon, H, Ali, A, Thomis, L, Melia, D, Dance, A, Hanson, K, Humphreys, S, Frost, I, Gopal, V, Godden, J, Holden, A, Swann, S, Smith, T, Clapham, M, Poultney, U, Harper, R, Rice, P, Reece-Anthony, R, Gurung, B, Moultrie, S, Odam, M, Mayer, A, Bellini, A, Pickard, A, Bryant, J, Roe, N, Sowter, J, Lang, K, Taylor, J, Barry, P, Hobrok, M, Tench, H, Wolf-Roberts, R, Mcguinness, H, Loosley, R, Hawcutt, D, Rad, L, O'Malley, L, Saunderson, P, Seddon, G, Anderson, T, Rogers, N, Ruddy, J, Harkins, M, Beith, C, Mcalpine, A, Ferguson, L, Grant, P, Macfadyen, S, Mclaughlin, M, Baird, T, Rundell, S, Welsh, B, Hamill, R, Fisher, F, Gregory, J, Axel, Schmidt, Kerstin, U Ludwig, Selina, Rolker, Markus, M Nöthen, Julia, Fazaal, Verena, Keitel, Björn, Jensen, Torsten, Feldt, Lisa, Knopp, Julia, Schröder, Carlo, Maj, Fabian, Brand, Marc, M Berger, Thorsten, Brenner, Anke, Hinney, Oliver, Witzke, Robert, Bals, Christian, Herr, Nicole, Ludwig, Jörn, Walter, Jochen, Schneider, Johanna, Erber, Christoph, D Spinner, Clemens, M Wendtner, Christof, Winter, Ulrike, Protzer, Nicolas, Casadei, Stephan, Ossowski, Olaf, H Riess, Eva, C Schulte, J Brent Richards, Guillaume, Butler-Laporte, Mirosław, Kwasniewski, Urszula, Korotko, Karolina, Chwialkowska, Magdalena, Niemira, Jerzy, Jaroszewicz, Barbara, Sobala-Szczygiel, Beata, Puzanowska, Anna, Parfieniuk-Kowerda, Diana, Martonik, Anna, Moniuszko-Malinowska, Sławomir, Pancewicz, Dorota, Zarębska-Michaluk, Krzysztof, Simon, Monika, Pazgan-Simon, Iwona, Mozer-Lisewska, Maciej, Bura, Agnieszka, Adamek, Krzysztof Tomasiewicz Małgorzata Pawłowska, Anna, Piekarska, Aleksandra, Berkan-Kawinska, Andrzej, Horban, Justyna, Kowalska, Regina, Podlasin, Piotr, Wasilewski, Arsalin, Azzadin, Miroslaw, Czuczwar, Slawomir, Czaban, Paweł, Olszewski, Jacek, Bogocz, Magdalena, Ochab, Anna, Kruk, Sandra, Uszok, Agnieszka, Bielska, Anna, Szałkowska, Justyna, Raczkowska, Gabriela, Sokołowska, Joanna, Chorostowska-Wynimko, Aleksandra, Jezela-Stanek, Adriana, Roży, Urszula, Lechowicz, Urszula, Polowianiuk, Kamil, Grubczak, Aleksandra, Starosz, Andrzej, Eljaszewicz, Wiktoria, Izdebska, Adam, Krętowski, Robert, Flisiak, Marcin Moniuszko Malak Abedalthagafi Manal Alaamery, Salam, Massadeh, Mohamed, Fawzy, Hadeel, Albardis, Nora, Aljawini, Moneera, Alsuwailm, Faisal, Almalki, Serghei, Mangul, Junghyun, Jung, Hamdi, Mbarek, Chadi, Saad, Yaser, Al-Sarraj, Wadha, Al-Muftah, Radja, Badji, Asma Al Thani, Said, I Ismail, HGI, WES/WGS Working Group Within the, Consortium, GenOMICC, Study, GEN-COVID Multicenter, Renieri, Alessandra [0000-0002-0846-9220], Apollo - University of Cambridge Repository, NIHR, Fallerini, C, Picchiotti, N, Baldassarri, M, Zguro, K, Daga, S, Fava, F, Benetti, E, Amitrano, S, Bruttini, M, Palmieri, M, Croci, S, Lista, M, Beligni, G, Valentino, F, Meloni, I, Tanfoni, M, Minnai, F, Colombo, F, Cabri, E, Fratelli, M, Gabbi, C, Mantovani, S, Frullanti, E, Gori, M, Crawley, F, Butler-Laporte, G, Richards, B, Zeberg, H, Lipcsey, M, Hultström, M, Ludwig, K, Schulte, E, Pairo-Castineira, E, Baillie, J, Schmidt, A, Frithiof, R, Mari, F, Renieri, A, Furini, S, and Crotti, L
Subjects: Male, Medicin och hälsovetenskap, Linkage disequilibrium, Medizin, severity, Genome-wide association study, Disease, WES/WGS Working Group Within the HGI, Logistic regression, Severity of Illness Index, Medical and Health Sciences, Whole Exome Sequencing, Cohort Studies, 0302 clinical medicine, Lasso (statistics), GEN-COVID Multicenter Study, Germany, 80 and over, Genetics (clinical), Exome sequencing, Original Investigation, Genetics & Heredity, Aged, 80 and over, 0303 health sciences, Adult, Aged, COVID-19, Female, Humans, Italy, Middle Aged, Polymorphism, Single Nucleotide, Quebec, SARS-CoV-2, Sweden, United Kingdom, Genetic Predisposition to Disease, Phenotype, Single Nucleotide, covid-19, 1104 Complementary and Alternative Medicine, GenOMICC Consortium, Human, coding variants, Computational biology, Biology, 03 medical and health sciences, Exome Sequencing, Genetics, Polymorphism, Gene, 030304 developmental biology, 0604 Genetics, 1114 Paediatrics and Reproductive Medicine, Cohort Studie, 030217 neurology & neurosurgery, Coding (social sciences)
Abstract: The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. Supplementary Information The online version contains supplementary material available at 10.1007/s00439-021-02397-7.
Published: 2021
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36. Sex differences in genetic architecture in the UK Biobank

Author: James Prendergast, Oriol Canela-Xandri, Albert Tenesa, Elena Bernabeu, Andrea Talenti, and Konrad Rawlik
Subjects: Functional role, Future studies, Mechanism (biology), Evolutionary biology, Genotype, Genetics, Biology, Genome, Biobank, Phenotype, Genetic architecture
Abstract: Males and females present differences in complex traits and in the risk of a wide array of diseases. Genotype by sex (GxS) interactions are thought to account for some of these differences. However, the extent and basis of GxS are poorly understood. In the present study, we provide insights into both the scope and the mechanism of GxS across the genome of about 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits. We also found that, in some cases, sex-agnostic analyses may be missing trait-associated loci and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the differences observed through sex-biased gene expression and gene-level analyses. Our results suggest the need to consider sex-aware analyses for future studies to shed light onto possible sex-specific molecular mechanisms.
Published: 2021
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37. Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals

Author: Martin I. Jones, Joseph D. Szustakowski, Giorgio Sirugo, Lukas Habegger, Adam J. Mansfield, Will Salerno, Joshua D. Backman, Athanasios Kousathanas, David J. Carey, Yi-Pin Lai, James F. Wilson, Alison M. Meynert, Anne E. Justice, Alexander H. Li, Jack A. Kosmicki, Anthony Marcketta, Sándor Szalma, Shane McCarthy, A. R. Shuldiner, A. Baras, Daniel J. Rader, Michael N. Cantor, Ashish Yadav, Manuel A. R. Ferreira, F. S. P. Kury, Konrad Rawlik, Loukas Moutsianas, Gonçalo R. Abecasis, Susan P. Walker, Xing Chen, Albert Tenesa, Paul Nioi, Adam E. Locke, Guillaume Butler-Laporte, E. N. Smith, Richard H Scott, Gundula Povysil, Joseph B. Leader, Lauren Gurski, Dorota Pasko, Marylyn D. Ritchie, A. Cordova-Palomera, Kyoko Watanabe, Colm O'Dushlaine, A. O'Neill, Tomoko Nakanishi, Erola Pairo-Castineira, Xiuwen Zheng, Emily Wong, Jeffrey G. Reid, Slavé Petrovski, Julie E. Horowitz, Anurag Verma, Justin W. Davis, Dylan Sun, Sahar Esmaeeli, Heiko Runz, Quanli Wang, John D. Overton, Shareef Khalid, Tooraj Mirshahi, Evan Maxwell, Mark J. Caulfield, Mark Lathrop, Olympe Chazara, Deepika Sharma, David Goldstein, Jonathan Marchini, Xiaodong Bai, Suganthi Balasubramanian, Krzysztof Kiryluk, Nilanjana Banerjee, Rouel Lanche, J. B. Richards, Hyun Min Kang, J. K. Baillie, Yunfeng Huang, Sean O'Keeffe, Erika Kvikstad, Margaret M. Parker, and Joelle Mbatchou
Subjects: Male, 0301 basic medicine, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Biology, 03 medical and health sciences, Current sample, 0302 clinical medicine, Data sequences, Report, Exome Sequencing, Genetics, Humans, Exome, Genetic Predisposition to Disease, 030212 general & internal medicine, Gene, Genetics (clinical), SARS-CoV-2, COVID-19, Prognosis, Hospitalization, 030104 developmental biology, Sample Size, Multiple comparisons problem, Susceptibility locus, Female, Interferons
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.
Published: 2021
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38. A common TMPRSS2 variant protects against severe COVID-19

Author: Alessia David, Isaric C Investigators, Wendy S. Barclay, Aurélie Cobat, Jean-Laurent Casanova, Erola Pairo-Castineira, Michael J.E. Sternberg, Nicholas J. Parkinson, Vanessa Sancho-Shimizu, Albert Tenesa, J Kenneth Baillie, Thomas P. Peacock, Tarun Khanna, and Laurent Abel
Subjects: education.field_of_study, Methionine, business.industry, Population, Autoantibody, TMPRSS2, Asymptomatic, Virus, Minor allele frequency, chemistry.chemical_compound, chemistry, Immunology, medicine, Reflux esophagitis, medicine.symptom, education, business
Abstract: SummaryInfection with SARS-CoV-2 has a wide range of clinical presentations, from asymptomatic to life-threatening. Old age is the strongest factor associated with increased COVID19-related mortality, followed by sex and pre-existing conditions. The importance of genetic and immunological factors on COVID19 outcome is also starting to emerge, as demonstrated by population studies and the discovery of damaging variants in genes controlling type I IFN immunity and of autoantibodies that neutralize type I IFNs. The human protein transmembrane protease serine type 2 (TMPRSS2) plays a key role in SARS-CoV-2 infection, as it is required to activate the virus’ spike protein, facilitating entry into target cells. We focused on the only common TMPRSS2 non-synonymous variant predicted to be damaging (rs12329760), which has a minor allele frequency of ∼25% in the population. In a large population of SARS-CoV-2 positive patients, we show that this variant is associated with a reduced likelihood of developing severe COVID19 (OR 0.87, 95%CI:0.79-0.97, p=0.01). This association was stronger in homozygous individuals when compared to the general population (OR 0.65, 95%CI:0.50-0.84, p=1.3×10−3). We demonstrate in vitro that this variant, which causes the amino acid substitution valine to methionine, impacts the catalytic activity of TMPRSS2 and is less able to support SARS-CoV-2 spike-mediated entry into cells.TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID19. Clinical trials are needed to confirm this.
Published: 2021
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39. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Author: Ruidong Xiang, Lingzhao Fang, Shuli Liu, Iona M. Macleod, Zhiqian Liu, Edmond J. Breen, Yahui Gao, George E. Liu, Albert Tenesa, CattleGTEx Consortium, Brett A Mason, Amanda J. Chamberlain, Naomi R. Wray, Michael E. Goddard
Published: 2021
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40. Model selection approach suggests causal association between 25-hydroxyvitamin D and colorectal cancer.

Author: Lina Zgaga, Felix Agakov, Evropi Theodoratou, Susan M Farrington, Albert Tenesa, Malcolm G Dunlop, Paul McKeigue, and Harry Campbell
Subjects: Medicine, Science
Abstract: Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC), but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders.Plasma 25-hydroxyvitamin D (25-OHD), genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls) and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions.Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model), and also for deviance information criteria (DIC) computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores.Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations.
Published: 2013
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41. Meta-analysis of mismatch repair polymorphisms within the cogent consortium for colorectal cancer susceptibility.

Author: Simone Picelli, Justo Lorenzo Bermejo, Jenny Chang-Claude, Michael Hoffmeister, Ceres Fernández-Rozadilla, Angel Carracedo, Antoni Castells, Sergi Castellví-Bel, Memebers of EPICOLON Consortium-Gastrointestinal Oncology Group of the Spanish Gastroenterological Association, Alessio Naccarati, Barbara Pardini, Ludmila Vodickova, Heiko Müller, Bente A Talseth-Palmer, Geoffrey Stibbard, Paolo Peterlongo, Carmela Nici, Silvia Veneroni, Li Li, Graham Casey, Albert Tenesa, Susan M Farrington, Ian Tomlinson, Victor Moreno, Tom van Wezel, Juul Wijnen, Malcolm Dunlop, Paolo Radice, Rodney J Scott, Pavel Vodicka, Clara Ruiz-Ponte, Hermann Brenner, Stephan Buch, Henry Völzke, Jochen Hampe, Clemens Schafmayer, and Annika Lindblom
Subjects: Medicine, Science
Abstract: In the last four years, Genome-Wide Association Studies (GWAS) have identified sixteen low-penetrance polymorphisms on fourteen different loci associated with colorectal cancer (CRC). Due to the low risks conferred by known common variants, most of the 35% broad-sense heritability estimated by twin studies remains unexplained. Recently our group performed a case-control study for eight Single Nucleotide Polymorphisms (SNPs) in 4 CRC genes. The present investigation is a follow-up of that study. We have genotyped six SNPs that showed a positive association and carried out a meta-analysis based on eight additional studies comprising in total more than 8000 cases and 6000 controls. The estimated recessive odds ratio for one of the SNPs, rs3219489 (MUTYH Q338H), decreased from 1.52 in the original Swedish study, to 1.18 in the Swedish replication, and to 1.08 in the initial meta-analysis. Since the corresponding summary probability value was 0.06, we decided to retrieve additional information for this polymorphism. The incorporation of six further studies resulted in around 13000 cases and 13000 controls. The newly updated OR was 1.03. The results from the present large, multicenter study illustrate the possibility of decreasing effect sizes with increasing samples sizes. Phenotypic heterogeneity, differential environmental exposures, and population specific linkage disequilibrium patterns may explain the observed difference of genetic effects between Sweden and the other investigated cohorts.
Published: 2013
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42. Complex variation in measures of general intelligence and cognitive change.

Author: Suzanne J Rowe, Amy Rowlatt, Gail Davies, Sarah E Harris, David J Porteous, David C Liewald, Geraldine McNeill, John M Starr, Ian J Deary, and Albert Tenesa
Subjects: Medicine, Science
Abstract: Combining information from multiple SNPs may capture a greater amount of genetic variation than from the sum of individual SNP effects and help identifying missing heritability. Regions may capture variation from multiple common variants of small effect, multiple rare variants or a combination of both. We describe regional heritability mapping of human cognition. Measures of crystallised (gc) and fluid intelligence (gf) in late adulthood (64-79 years) were available for 1806 individuals genotyped for 549,692 autosomal single nucleotide polymorphisms (SNPs). The same individuals were tested at age 11, enabling us the rare opportunity to measure cognitive change across most of their lifespan. 547,750 SNPs ranked by position are divided into 10, 908 overlapping regions of 101 SNPs to estimate the genetic variance each region explains, an approach that resembles classical linkage methods. We also estimate the genetic variation explained by individual autosomes and by SNPs within genes. Empirical significance thresholds are estimated separately for each trait from whole genome scans of 500 permutated data sets. The 5% significance threshold for the likelihood ratio test of a single region ranged from 17-17.5 for the three traits. This is the equivalent to nominal significance under the expectation of a chi-squared distribution (between 1 df and 0) of P
Published: 2013
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43. Evidence of horizontal indirect genetic effects in humans

Author: Oriol Canela-Xandri, Albert Tenesa, Charley Xia, and Konrad Rawlik
Subjects: Genetics, Mixed model, 0303 health sciences, Social Psychology, Experimental and Cognitive Psychology, Disease, Heritability, Biology, Mental health, Phenotype, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, Human disease, Genotype, Trait, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract: Indirect genetic effects, the effects of the genotype of one individual on the phenotype of other individuals, are environmental factors associated with human disease and complex trait variation that could help to expand our understanding of the environment linked to complex traits. Here, we study indirect genetic effects in 80,889 human couples of European ancestry for 105 complex traits. Using a linear mixed model approach, we estimate partner indirect heritability and find evidence of partner heritability on ~50% of the analysed traits. Follow-up analysis suggests that in at least ~25% of these traits, the partner heritability is consistent with the existence of indirect genetic effects including a wide variety of traits such as dietary traits, mental health and disease. This shows that the environment linked to complex traits is partially explained by the genotype of other individuals and motivates the need to find new ways of studying the environment.
Published: 2020
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44. A comprehensive catalogue of regulatory variants in the cattle transcriptome

Author: Shuli Liu, Yahui Gao, Oriol Canela-Xandri, Sheng Wang, Ying Yu, Wentao Cai, Bingjie Li, Ruidong Xiang, Amanda J. Chamberlain, Erola Pairo-Castineira, Kenton D’Mellow, Konrad Rawlik, Charley Xia, Yuelin Yao, Pau Navarro, Dominique Rocha, Xiujin Li, Ze Yan, Congjun Li, Benjamin D. Rosen, Curtis P. Van Tassell, Paul M. Vanraden, Shengli Zhang, Li Ma, John B. Cole, George E. Liu, Albert Tenesa, and Lingzhao Fang
Subjects: Transcriptome, Genetic gain, Research community, Gene expression, Alternative splicing, RNA, Computational biology, Biology
Abstract: Characterization of genetic regulatory variants acting on the transcriptome of livestock is essential for interpreting the molecular mechanisms underlying traits of economic value and for increasing the rate of genetic gain through artificial selection. Here, we build a cattle Genotype-Tissue Expression atlas (cattle GTEx, http://cgtex.roslin.ed.ac.uk/) as part of the pilot phase of Farm animal GTEx (FarmGTEx) project for the research community based on publicly available 11,642 RNA-Seq datasets. We describe the landscape of the transcriptome across over 100 tissues and report hundreds of thousands of genetic associations with gene expression and alternative splicing for 24 major tissues. We evaluate the tissue-sharing patterns of these genetic regulatory effects, and functionally annotate them using multi-omics data. Finally, we link gene expression in different tissues to 43 economically important traits using both transcriptome-wide association study (TWAS) and colocalization analyses to decipher the molecular regulatory mechanisms underpinning such agronomic traits in cattle.
Published: 2020
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45. A catalog of associations between rare coding variants and COVID-19 outcomes

Author: Anurag Verma, Anne E. Justice, Guillaume Butler-Laporte, E. N. Smith, Lukas Habegger, Joelle Mbatchou, Susan P. Walker, Albert Tenesa, Joseph D. Szustakowski, Konrad Rawlik, Dylan Sun, Loukas Moutsianas, Shane McCarthy, Richard H Scott, Aris Baras, Evan Maxwell, Aldo Cordova-Palomera, Tooraj Mirshahi, Dorota Pasko, David J. Carey, Sahar Esmaeli, Adam J. Mansfield, Quanli Wang, Jeffrey S. Reid, Nilanjana Banerjee, Joshua D. Backman, Athanasios Kousathanas, Ashish Yadav, Mark J. Caulfield, Alison M. Meynert, Rouel Lanche, Jack A. Kosmicki, James F. Wilson, J. Brent Richards, Heiko Runz, Gonçalo R. Abecasis, Adam E. Locke, Justin W. Davis, Mark Lathrop, Alan R. Shuldiner, Lauren Gurski, J Kenneth Baillie, Michael N. Cantor, David Goldstein, John D. Overton, Kyoko Watanabe, Amanda O'Neill, Yunfeng Huang, Jonathan Marchini, Xiaodong Bai, Krzysztof Kiryluk, Slavé Petrovski, Sean O'Keeffe, Erika Kvikstad, Anthony Marcketta, Margaret M. Parker, Giorgio Sirugo, Julie E. Horowitz, Emily Wong, Olympe Chazara, Paul Nioi, Manuel A. R. Ferreira, Sándor Szalma, Joseph B. Leader, Shareef Khalid, William J Salerno, Deepika Sharma, Tomoko Nakanishi, Marcus B. Jones, Gundula Povysil, Marylyn D. Ritchie, Colm O'Dushlaine, Xiuwen Zheng, Daniel J. Rader, Suganthi Balasubramanian, Hyun Min Kang, Yi-Pin Lai, Alexander H. Li, Xing Chen, and Erola Pairo-Castineira
Subjects: Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genome-wide association study, medicine.disease_cause, Biobank, Article, Genetic association analysis, Immunology, Multiple comparisons problem, Medicine, business, Gene, Coronavirus
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.
Published: 2020
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46. Genetic mechanisms of critical illness in Covid-19

Author: Lee Murphy, Chris P. Ponting, Xia Shen, Veronique Vitart, Seán Keating, Charles J. Hinds, Kathy Rowan, James F. Wilson, Mark J. Caulfield, Caroline Hayward, Alistair Nichol, Wilna Oosthuyzen, Hugh Montgomery, David M. Maslove, Manu Shankar-Hari, Barbara Shih, Konrad Rawlik, Julian C. Knight, J Kenneth Baillie, Nicola Wrobel, Graeme R. Grimes, Chris Haley, Peter J. M. Openshaw, Loukas Moutsianas, Charlotte Summers, Angie Fawkes, David J. Porteous, Susan P. Walker, Peter Horby, Fiona Griffiths, Clark D Russell, Sara Clohisey, Marie Zechner, Anne Richmond, Timothy S. Walsh, Alison M. Meynert, Chenqing Zheng, Albert Tenesa, Bo Wang, Andy Law, Daniel F. McAuley, Andrew D. Bretherick, Max Head Fourman, Elvina Gountouna, James J Furniss, Lucija Klaric, Erola Pairo-Castineira, Malcolm G Semple, Paul Klenerman, Nicholas J. Parkinson, Lance Turtle, Richard H Scott, Dorota Pasko, Zhijian Yang, Antonia Ho, Lowell Ling, and Ranran Zhai
Subjects: business.industry, Intensive care, Genetic variation, medicine, Population study, Locus (genetics), Genome-wide association study, Disease, Bioinformatics, medicine.disease, business, Gene, Comorbidity
Abstract: The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3GenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland.We identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 × 10−12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 × 10−8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 × 10−8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 × 10−30).We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19.Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.
Published: 2020
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47. SNP heritability: What are we estimating?

Author: John Woolliams, Konrad Rawlik, Albert Tenesa, and Oriol Canela-Xandri
Subjects: Mixed model, education.field_of_study, Restricted maximum likelihood, Population, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Econometrics, Inference, Estimator, Statistical model, Heritability, education, Genetic architecture, Mathematics
Abstract: The SNP heritability has become a central concept in the study of complex traits. Estimation of based on genomic variance components in a linear mixed model using restricted maximum likelihood has been widely adopted as the method of choice were individual level data are available. Empirical results have suggested that this approach is not robust if the population of interest departs from the assumed statistical model. Prolonged debate of the appropriate model choice has yielded a number of approaches to account for frequency- and linkage disequilibrium dependent genetic architectures. Here we analytically resolve the question of how these estimates relate to of the population from which samples are drawn. In particular, we show that the correct model for the purpose of inference about does not require knowledge of the true genetic architecture of a trait. More generally, our results provide a complete perspective of these class of estimators of , highlighting practical shortcomings of current practise. We illustrate our theoretical results using simulations and data from UK Biobank.
Published: 2020
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48. Sexual differences in genetic architecture in UK Biobank

Author: James Prendergast, Oriol Canela-Xandri, Elena Bernabeu, Albert Tenesa, Konrad Rawlik, and Andrea Talenti
Subjects: Sexual dimorphism, Genetic heterogeneity, Mechanism (biology), Evolutionary biology, Expression quantitative trait loci, Genome-wide association study, Heritability, Biology, Genetic architecture, Genetic association
Abstract: Sex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Gene by sex interactions (GxS) are thought to account for some of this sexual dimorphism. However, the extent and basis of these interactions are poorly understood.Here we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We also found that, in some cases, sex-agnostic GWAS efforts might be missing loci of interest, and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the dimorphism observed through sex-biased eQTL and gene-level analyses.This study marks a broad examination of the genetics of sexual dimorphism. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Our results suggest the need to consider sex-stratified analyses for future studies in order to shed light into possible sex-specific molecular mechanisms.
Published: 2020
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49. Sex differences in genetic architecture in the UK Biobank

Author: Elena, Bernabeu, Oriol, Canela-Xandri, Konrad, Rawlik, Andrea, Talenti, James, Prendergast, and Albert, Tenesa
Subjects: Male, Multifactorial Inheritance, Sex Characteristics, Quantitative Trait, Heritable, Sex Factors, Gene Expression Regulation, Genotype, Quantitative Trait Loci, Humans, Female, Polymorphism, Single Nucleotide, United Kingdom, Biological Specimen Banks
Abstract: Males and females present differences in complex traits and in the risk of a wide array of diseases. Genotype by sex (GxS) interactions are thought to account for some of these differences. However, the extent and basis of GxS are poorly understood. In the present study, we provide insights into both the scope and the mechanism of GxS across the genome of about 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits. We also found that, in some cases, sex-agnostic analyses may be missing trait-associated loci and looked into possible improvements in the prediction of high-level phenotypes. Finally, we studied the potential functional role of the differences observed through sex-biased gene expression and gene-level analyses. Our results suggest the need to consider sex-aware analyses for future studies to shed light onto possible sex-specific molecular mechanisms.
Published: 2020

50. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author: Matteo D’Antonio, Jennifer P. Nguyen, Timothy D. Arthur, Hiroko Matsui, Agnieszka D’Antonio-Chronowska, Kelly A. Frazer, Benjamin M. Neale, Mark Daly, Andrea Ganna, Christine Stevens, Gita A. Pathak, Shea J. Andrews, Masahiro Kanai, Mattia Cordioli, Juha Karjalainen, Renato Polimanti, Matti Pirinen, Nadia Harerimana, Kumar Veerapen, Brooke Wolford, Huy Nguyen, Matthew Solomonson, Rachel G. Liao, Karolina Chwialkowska, Amy Trankiem, Mary K. Balaconis, Caroline Hayward, Anne Richmond, Archie Campbell, Marcela Morris, Chloe Fawns-Ritchie, Joseph T. Glessner, Douglas M. Shaw, Xiao Chang, Hannah Polikowski, Petty E. Lauren, Hung-Hsin Chen, Zhu Wanying, Hakon Hakonarson, David J. Porteous, Jennifer Below, Kari North, Joseph B. McCormick, Paul R.H.J. Timmers, James F. Wilson, Albert Tenesa, Kenton D’Mellow, Shona M. Kerr, Mari E.K. Niemi, Lindokuhle Nkambul, Kathrin Aprile von Hohenstaufen, Ali Sobh, Madonna M. Eltoukhy, Amr M. Yassen, Mohamed A.F. Hegazy, Kamal Okasha, Mohammed A. Eid, Hanteera S. Moahmed, Doaa Shahin, Yasser M. El-Sherbiny, Tamer A. Elhadidy, Mohamed S. Abd Elghafar, Jehan J. El-Jawhari, Attia A.S. Mohamed, Marwa H. Elnagdy, Amr Samir, Mahmoud Abdel-Aziz, Walid T. Khafaga, Walaa M. El-Lawaty, Mohamed S. Torky, Mohamed R. El-shanshory, Chiara Batini, Paul H. Lee, Nick Shrine, Alexander T. Williams, Martin D. Tobin, Anna L. Guyatt, Catherine John, Richard J. Packer, Altaf Ali, Robert C. Free, Xueyang Wang, Louise V. Wain, Edward J. Hollox, Laura D. Venn, Catherine E. Bee, Emma L. Adams, Ahmadreza Niavarani, Bahareh Sharififard, Rasoul Aliannejad, Ali Amirsavadkouhi, Zeinab Naderpour, Hengameh Ansari Tadi, Afshar Etemadi Aleagha, Saeideh Ahmadi, Seyed Behrooz Mohseni Moghaddam, Alireza Adamsara, Morteza Saeedi, Hamed Abdollahi, Abdolmajid Hosseini, Pajaree Chariyavilaskul, Monpat Chamnanphon, Thitima B. Suttichet, Vorasuk Shotelersuk, Monnat Pongpanich, Chureerat Phokaew, Wanna Chetruengchai, Watsamon Jantarabenjakul, Opass Putchareon, Pattama Torvorapanit, Thanyawee Puthanakit, Pintip Suchartlikitwong, Nattiya Hirankarn, Voraphoj Nilaratanakul, Pimpayao Sodsai, Ben M. Brumpton, Kristian Hveem, Cristen Willer, Wei Zhou, Tormod Rogne, Erik Solligard, Bjørn Olav Åsvold, Malak Abedalthagafi, Manal Alaamery, Saleh Alqahtani, Dona Baraka, Fawz Al Harthi, Ebtehal Alsolm, Leen Abu Safieh, Albandary M. Alowayn, Fatimah Alqubaishi, Amal Al Mutairi, Serghei Mangul, Abdulraheem Alshareef, Mona Sawaji, Mansour Almutairi, Nora Aljawini, Nour Albesher, Yaseen M. Arabi, Ebrahim S. Mahmoud, Amin K. Khattab, Roaa T. Halawani, Ziab Z. Alahmadey, Jehad K. Albakri, Walaa A. Felemban, Bandar A. Suliman, Rana Hasanato, Laila Al-Awdah, Jahad Alghamdi, Deema AlZahrani, Sameera AlJohani, Hani Al-Afghani, May Alrashed, Nouf AlDhawi, Hadeel AlBardis, Sarah Alkwai, Moneera Alswailm, Faisal Almalki, Maha Albeladi, Iman Almohammed, Eman Barhoush, Anoud Albader, Salam Massadeh, Abdulaziz AlMalik, Sara Alotaibi, Bader Alghamdi, Junghyun Jung, Mohammad S. Fawzy, Yunsung Lee, Per Magnus, Lill-Iren S. Trogstad, Øyvind Helgeland, Jennifer R. Harris, Massimo Mangino, Tim D. Spector, Duncan Emma, Sandra P. Smieszek, Bartlomiej P. Przychodzen, Christos Polymeropoulos, Vasilios Polymeropoulos, Mihael H. Polymeropoulos, Israel Fernandez-Cadenas, Jordi Perez-Tur, Laia Llucià-Carol, Natalia Cullell, Elena Muiño, Jara Cárcel-Márquez, Marta L. DeDiego, Lara Lloret Iglesias, Anna M. Planas, Alex Soriano, Veronica Rico, Daiana Agüero, Josep L. Bedini, Francisco Lozano, Carlos Domingo, Veronica Robles, Francisca Ruiz-Jaén, Leonardo Márquez, Juan Gomez, Eliecer Coto, Guillermo M. Albaiceta, Marta García-Clemente, David Dalmau, Maria J. Arranz, Beatriz Dietl, Alex Serra-Llovich, Pere Soler, Roger Colobrán, Andrea Martín-Nalda, Alba Parra Martínez, David Bernardo, Silvia Rojo, Aida Fiz-López, Elisa Arribas, Paloma de la Cal-Sabater, Tomás Segura, Esther González-Villa, Gemma Serrano-Heras, Joan Martí-Fàbregas, Elena Jiménez-Xarrié, Alicia de Felipe Mimbrera, Jaime Masjuan, Sebastian García-Madrona, Anna Domínguez-Mayoral, Joan Montaner Villalonga, Paloma Menéndez-Valladares, Daniel I. Chasman, Julie E. Buring, Paul M. Ridker, Giulianini Franco, Howard D. Sesso, JoAnn E. Manson, Joseph R. Glessner, Carolina Medina-Gomez, Andre G. Uitterlinden, M. Arfan Ikram, Kati Kristiansson, Sami Koskelainen, Markus Perola, Kati Donner, Katja Kivinen, Aarno Palotie, Samuli Ripatti, Sanni Ruotsalainen, Mari Kaunisto, null FinnGen, Tomoko Nakanishi, Guillaume Butler-Laporte, Vincenzo Forgetta, David R. Morrison, Biswarup Ghosh, Laetitia Laurent, Alexandre Belisle, Danielle Henry, Tala Abdullah, Olumide Adeleye, Noor Mamlouk, Nofar Kimchi, Zaman Afrasiabi, Nardin Rezk Branka Vulesevic, Meriem Bouab, Charlotte Guzman, Louis Petitjean, Chris Tselios, Xiaoqing Xue, Erwin Schurr, Jonathan Afilalo, Marc Afilalo, Maureen Oliveira, Bluma Brenner, Pierre Lepage, Jiannis Ragoussis, Daniel Auld, Nathalie Brassard, Madeleine Durand, Michaël Chassé, Daniel E. Kaufmann, G. Mark Lathrop, Vincent Mooser, J. Brent Richards, Rui Li, Darin Adra, Souad Rahmouni, Michel Georges, Michel Moutschen, Benoit Misset, Gilles Darcis, Julien Guiot, Julien Guntz, Samira Azarzar, Stéphanie Gofflot, Yves Beguin, Sabine Claassen, Olivier Malaise, Pascale Huynen, Christelle Meuris, Marie Thys, Jessica Jacques, Philippe Léonard, Frederic Frippiat, Jean-Baptiste Giot, Anne-Sophie Sauvage, Christian Von Frenckell, Yasmine Belhaj, Bernard Lambermont, Sara Pigazzini, Lindokuhle Nkambule, Michelle Daya, Jonathan Shortt, Nicholas Rafaels, Stephen J. Wicks, Kristy Crooks, Kathleen C. Barnes, Christopher R. Gignoux, Sameer Chavan, Triin Laisk, Kristi Läll, Maarja Lepamets, Reedik Mägi, Tõnu Esko, Ene Reimann, Lili Milani, Helene Alavere, Kristjan Metsalu, Mairo Puusepp, Andres Metspalu, Paul Naaber, Edward Laane, Jaana Pesukova, Pärt Peterson, Kai Kisand, Jekaterina Tabri, Raili Allos, Kati Hensen, Joel Starkopf, Inge Ringmets, Anu Tamm, Anne Kallaste, Pierre-Yves Bochud, Carlo Rivolta, Stéphanie Bibert, Mathieu Quinodoz, Dhryata Kamdar, Noémie Boillat, Semira Gonseth Nussle, Werner Albrich, Noémie Suh, Dionysios Neofytos, Véronique Erard, Cathy Voide, null FHoGID, null RegCOVID, null P-PredictUs, null SeroCOVID, null CRiPSI, Rafael de Cid, Iván Galván-Femenía, Natalia Blay, Anna Carreras, Beatriz Cortés, Xavier Farré, Lauro Sumoy, Victor Moreno, Josep Maria Mercader, Marta Guindo-Martinez, David Torrents, Manolis Kogevinas, Judith Garcia-Aymerich, Gemma Castaño-Vinyals, Carlota Dobaño, Alessandra Renieri, Francesca Mari, Chiara Fallerini, Sergio Daga, Elisa Benetti, Margherita Baldassarri, Francesca Fava, Elisa Frullanti, Floriana Valentino, Gabriella Doddato, Annarita Giliberti, Rossella Tita, Sara Amitrano, Mirella Bruttini, Susanna Croci, Ilaria Meloni, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Giada Beligni, Andrea Tommasi, Laura Di Sarno, Maria Palmieri, Miriam Lucia Carriero, Diana Alaverdian, Stefano Busani, Raffaele Bruno, Marco Vecchia, Mary Ann Belli, Nicola Picchiotti, Maurizio Sanarico, Marco Gori, Simone Furini, Stefania Mantovani, Serena Ludovisi, Mario Umberto Mondelli, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Massimo Vaghi, Stefano Rusconi, Matteo Siano, Francesca Montagnani, Arianna Emiliozzi, Massimiliano Fabbiani, Barbara Rossetti, Elena Bargagli, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Maria Bandini, Gian Piero Caldarelli, Paolo Piacentini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Agostino Ognibene, Alessandro Pancrazzi, Maria Lorubbio, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Massimo Girardis, Sophie Venturelli, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Francesco Paciosi, Pier Giorgio Scotton, Francesca Andretta, Sandro Panese, Renzo Scaggiante, Francesca Gatti, Saverio Giuseppe Parisi, Stefano Baratti, Matteo Della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Giuseppe Merla, Gabriella Maria Squeo, Filippo Aucella, Pamela Raggi, Carmen Marciano, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Serafina Valente, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Domenico A. Coviello, Cristina Mussini, Enrico Martinelli, Sandro Mancarella, Luisa Tavecchia, Lia Crotti, Chiara Gabbi, Marco Rizzi, Franco Maggiolo, Diego Ripamonti, Tiziana Bachetti, Maria Teresa La Rovere, Simona Sarzi-Braga, Maurizio Bussotti, Stefano Ceri, Pietro Pinoli, Francesco Raimondi, Filippo Biscarini, Alessandra Stella, Kristina Zguro, Katia Capitani, Claudia Suardi, Simona Dei, Gianfranco Parati, Sabrina Ravaglia, Rosangela Artuso, Giordano Bottà, Paolo Di Domenico, Ilaria Rancan, Antonio Perrella Francesco Bianchi, Davide Romani, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Marco Tanfoni, Antonella Vincenti, Claudio Ferri, Davide Grassi, Gloria Pessina, Mario Tumbarello, Massimo Di Pietro, Ravaglia Sabrina, Sauro Luchi, Chiara Barbieri, Donatella Acquilini, Elena Andreucci, Francesco Vladimiro Segala, Giusy Tiseo, Marco Falcone, Mirjam Lista, Monica Poscente, Oreste De Vivo, Paola Petrocelli, Alessandra Guarnaccia, Silvia Baroni, Albert V. Smith, Andrew P. Boughton, Kevin W. Li, Jonathon LeFaive, Aubrey Annis, Anne E. Justice, Tooraj Mirshahi, Geetha Chittoor, Navya Shilpa Josyula, Jack A. Kosmicki, Manuel A.R. Ferreira, Joseph B. Leader, Dave J. Carey, Matthew C. Gass, Julie E. Horowitz, Michael N. Cantor, Ashish Yadav, Aris Baras, Goncalo R. Abecasis, David A. van Heel, Karen A. Hunt, Dan Mason, Qin Qin Huang, Sarah Finer, null Genes & Health Research Team, Bhavi Trivedi, Christopher J. Griffiths, Hilary C. Martin, John Wright, Richard C. Trembath, Nicole Soranzo, Jing Hua Zhao, Adam S. Butterworth, John Danesh, Emanuele Di Angelantonio, Lude Franke Marike Boezen, Patrick Deelen, Annique Claringbould, Esteban Lopera, Robert Warmerdam, Judith.M. Vonk, Irene van Blokland, Pauline Lanting, Anil P.S. Ori, Brooke Wolford Sebastian Zöllner, Jiongming Wang, Andrew Beck, Gina Peloso, Yuk-Lam Ho, Yan V. Sun, Jennifer E. Huffman, Christopher J. O’Donnell, Kelly Cho, Phil Tsao, J. Michael Gaziano, Michel (M.G.) Nivard, Eco (E.J.C.) de geus, Meike Bartels, Jouke Jan Hottenga, Scott T. Weiss, Elizabeth W. Karlson, Jordan W. Smoller, Robert C. Green, Yen-Chen Anne Feng, Josep Mercader, Shawn N. Murphy, James B. Meigs, Ann E. Woolley, Emma F. Perez, Daniel Rader, Anurag Verma, Marylyn D. Ritchie, Binglan Li, Shefali S. Verma, Anastasia Lucas, Yuki Bradford, Hugo Zeberg, Robert Frithiof, Michael Hultström, Miklos Lipcsey, Lindo Nkambul, Nicolas Tardif, Olav Rooyackers, Jonathan Grip, Tomislav Maricic, Konrad J. Karczewski, Elizabeth G. Atkinson, Kristin Tsuo, Nikolas Baya, Patrick Turley, Rahul Gupta, Shawneequa Callier, Raymond K. Walters, Duncan S. Palmer, Gopal Sarma, Nathan Cheng, Wenhan Lu, Sam Bryant, Claire Churchhouse, Caroline Cusick, Jacqueline I. Goldstein, Daniel King, Cotton Seed, Hilary Finucane, Alicia R. Martin, F. Kyle Satterstrom, Daniel J. Wilson, Jacob Armstrong, Justine K. Rudkin, Gavin Band, Sarah G. Earle, Shang-Kuan Lin, Nicolas Arning, Derrick W. Crook, David H. Wyllie, Anne Marie O’Connell, Chris C.A. Spencer, Nils Koelling, Mark J. Caulfield, Richard H. Scott, Tom Fowler, Loukas Moutsianas, Athanasios Kousathanas, Dorota Pasko, Susan Walker, Augusto Rendon, Alex Stuckey, Christopher A. Odhams, Daniel Rhodes, Georgia Chan, Prabhu Arumugam, Catherine A. Ball, Eurie L. Hong, Kristin Rand, Ahna Girshick, Harendra Guturu, Asher Haug Baltzell, Genevieve Roberts, Danny Park, Marie Coignet, Shannon McCurdy, Spencer Knight, Raghavendran Partha, Brooke Rhead, Miao Zhang, Nathan Berkowitz, Michael Gaddis, Keith Noto, Luong Ruiz, Milos Pavlovic, Laura G. Sloofman, Alexander W. Charney, Noam D. Beckmann, Eric E. Schadt, Daniel M. Jordan, Ryan C. Thompson, Kyle Gettler, Noura S. Abul-Husn, Steven Ascolillo, Joseph D. Buxbaum, Kumardeep Chaudhary, Judy H. Cho, Yuval Itan, Eimear E. Kenny, Gillian M. Belbin, Stuart C. Sealfon, Robert P. Sebra, Irene Salib, Brett L. Collins, Tess Levy, Bari Britvan, Katherine Keller, Lara Tang, Michael Peruggia, Liam L. Hiester, Kristi Niblo, Alexandra Aksentijevich, Alexander Labkowsky, Avromie Karp, Menachem Zlatopolsky, Michael Preuss, Ruth J.F. Loos, Girish N. Nadkarni, Ron Do, Clive Hoggart, Sam Choi, Slayton J. Underwood, Paul O’Reilly, Laura M. Huckins, Marissa Zyndorf, AII - Infectious diseases, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Neurology
Subjects: Medical Physiology, Gene Expression, Genome-wide association study, Genome, Severity of Illness Index, colocalization, Gene expression, Databases, Genetic, Ethnicity, 2.1 Biological and endogenous factors, GWAS, Aetiology, Biology (General), Lung, Genetics, Chromosome Mapping, Single Nucleotide, Organ Specificity, Biotechnology, Cell type, QH301-705.5, Quantitative Trait Loci, Single-nucleotide polymorphism, Biology, eQTL, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, Databases, Genetic, SNP, Humans, Genetic Predisposition to Disease, COVID-19 Host Genetics Initiative, Polymorphism, Gene, COVID-19, SARS-CoV-2, Gene Expression Profiling, Prevention, Human Genome, Computational Biology, Genetic Variation, Good Health and Well Being, Expression quantitative trait loci, Biochemistry and Cell Biology, Transcriptome, Genome-Wide Association Study
Abstract: Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types., Graphical abstract, D’Antonio et al. characterize associations between GWAS signals for COVID-19 disease and eQTLs in 69 human tissues to identify causal variants and their underlying molecular mechanisms. They show that diverse symptoms and disease severity of COVID-19 are associated with variants affecting gene expression in a wide variety of tissues.
Published: 2022
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