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Start Over Author "Brumpton, Ben M" Publisher escholarship, university of california
8 results on '"Brumpton, Ben M"'

1. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Author

Zhou, Wei, Kanai, Masahiro, Wu, Kuan-Han H, Rasheed, Humaira, Tsuo, Kristin, Hirbo, Jibril B, Wang, Ying, Bhattacharya, Arjun, Zhao, Huiling, Namba, Shinichi, Surakka, Ida, Wolford, Brooke N, Faro, Valeria Lo, Lopera-Maya, Esteban A, Läll, Kristi, Favé, Marie-Julie, Partanen, Juulia J, Chapman, Sinéad B, Karjalainen, Juha, Kurki, Mitja, Maasha, Mutaamba, Brumpton, Ben M, Chavan, Sameer, Chen, Tzu-Ting, Daya, Michelle, Ding, Yi, Feng, Yen-Chen A, Guare, Lindsay A, Gignoux, Christopher R, Graham, Sarah E, Hornsby, Whitney E, Ingold, Nathan, Ismail, Said I, Johnson, Ruth, Laisk, Triin, Lin, Kuang, Lv, Jun, Millwood, Iona Y, Moreno-Grau, Sonia, Nam, Kisung, Palta, Priit, Pandit, Anita, Preuss, Michael H, Saad, Chadi, Setia-Verma, Shefali, Thorsteinsdottir, Unnur, Uzunovic, Jasmina, Verma, Anurag, Zawistowski, Matthew, Zhong, Xue, Afifi, Nahla, Al-Dabhani, Kawthar M, Thani, Asma Al, Bradford, Yuki, Campbell, Archie, Crooks, Kristy, de Bock, Geertruida H, Damrauer, Scott M, Douville, Nicholas J, Finer, Sarah, Fritsche, Lars G, Fthenou, Eleni, Gonzalez-Arroyo, Gilberto, Griffiths, Christopher J, Guo, Yu, Hunt, Karen A, Ioannidis, Alexander, Jansonius, Nomdo M, Konuma, Takahiro, Lee, Ming Ta Michael, Lopez-Pineda, Arturo, Matsuda, Yuta, Marioni, Riccardo E, Moatamed, Babak, Nava-Aguilar, Marco A, Numakura, Kensuke, Patil, Snehal, Rafaels, Nicholas, Richmond, Anne, Rojas-Muñoz, Agustin, Shortt, Jonathan A, Straub, Peter, Tao, Ran, Vanderwerff, Brett, Vernekar, Manvi, Veturi, Yogasudha, Barnes, Kathleen C, Boezen, Marike, Chen, Zhengming, Chen, Chia-Yen, Cho, Judy, Smith, George Davey, Finucane, Hilary K, Franke, Lude, Gamazon, Eric R, Ganna, Andrea, Gaunt, Tom R, Ge, Tian, Huang, Hailiang, and Huffman, Jennifer

Subjects
Human Genome, Genetics, Biotechnology, Generic health relevance, Good Health and Well Being, Biobank of the Americas, Biobank Japan Project, BioMe, BioVU, CanPath - Ontario Health Study, China Kadoorie Biobank Collaborative Group, Colorado Center for Personalized Medicine, deCODE Genetics, Estonian Biobank, FinnGen, Generation Scotland, Genes & Health Research Team, LifeLines, Mass General Brigham Biobank, Michigan Genomics Initiative, National Biobank of Korea, Penn Medicine BioBank, Qatar Biobank, QSkin Sun and Health Study, Taiwan Biobank, HUNT Study, UCLA ATLAS Community Health Initiative, Uganda Genome Resource, UK Biobank, GWAS, ancestry diversity, biobank, genetic association studies, meta-analysis, phenotype harmonization
Abstract

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Published
2022

2. A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

Author

Ramdas, Shweta, Judd, Jonathan, Graham, Sarah E, Kanoni, Stavroula, Wang, Yuxuan, Surakka, Ida, Wenz, Brandon, Clarke, Shoa L, Chesi, Alessandra, Wells, Andrew, Bhatti, Konain Fatima, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Zajac, Greg JM, Wu, Kuan-Han H, Ntalla, Ioanna, Hui, Qin, Klarin, Derek, Hilliard, Austin T, Wang, Zeyuan, Xue, Chao, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Hwang, Mi Yeong, Han, Sohee, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Havulinna, Aki S, Veturi, Yogasudha, Pacheco, Jennifer Allen, Rosenthal, Elisabeth A, Lingren, Todd, Feng, QiPing, Kullo, Iftikhar J, Narita, Akira, Takayama, Jun, Martin, Hilary C, Hunt, Karen A, Trivedi, Bhavi, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Rasheed, Asif, Hindy, George, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Choudhury, Ananyo, Sengupta, Dhriti, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Bjerregaard, Anne A, Yao, Jie, Manichaikul, Ani, Lee, Wen-Jane, Hsiung, Chao Agnes, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, and Sabater-Lleal, Maria

Subjects
Human Genome, Biotechnology, Genetics, 2.1 Biological and endogenous factors, Aetiology, Chromatin, Genome-Wide Association Study, Genomics, Humans, Lipids, Polymorphism, Single Nucleotide, Million Veterans Program, Global Lipids Genetics Consortium, complex traits, fine-mapping, functional genomics, lipid biology, post-GWAS, regulatory mechanism, variant prioritization, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Published
2022

3. Multi‐phenotype analyses of hemostatic traits with cardiovascular events reveal novel genetic associations

Author

Temprano‐Sagrera, Gerard, Sitlani, Colleen M, Bone, William P, Martin‐Bornez, Miguel, Voight, Benjamin F, Morrison, Alanna C, Damrauer, Scott M, de Vries, Paul S, Smith, Nicholas L, Sabater‐Lleal, Maria, Dehghan, Abbas, Heath, Adam S, Reiner, Alex P, Johnson, Andrew, Richmond, Anne, Peters, Annette, van Hylckama Vlieg, Astrid, McKnight, Barbara, Psaty, Bruce M, Hayward, Caroline, Ward‐Caviness, Cavin, O’Donnell, Christopher, Chasman, Daniel, Strachan, David P, Tregouet, David A, Mook‐Kanamori, Dennis, Gill, Dipender, Thibord, Florian, Asselbergs, Folkert W, Leebeek, Frank WG, Rosendaal, Frits R, Davies, Gail, Homuth, Georg, Temprano, Gerard, Campbell, Harry, Taylor, Herman A, Bressler, Jan, Huffman, Jennifer E, Rotter, Jerome I, Yao, Jie, Wilson, James F, Bis, Joshua C, Hahn, Julie M, Desch, Karl C, Wiggins, Kerri L, Raffield, Laura M, Bielak, Lawrence F, Yanek, Lisa R, Kleber, Marcus E, Mueller, Martina, Kavousi, Maryam, Mangino, Massimo, Liu, Melissa, Brown, Michael R, Conomos, Matthew P, Jhun, Min‐A, Chen, Ming‐Huei, de Maat, Moniek PM, Pankratz, Nathan, Peyser, Patricia A, Elliot, Paul, Wei, Peng, Wild, Philipp S, Morange, Pierre E, van der Harst, Pim, Yang, Qiong, Le, Ngoc‐Quynh, Marioni, Riccardo, Li, Ruifang, Cox, Simon R, Trompet, Stella, Felix, Stephan B, Völker, Uwe, Tang, Weihong, Koenig, Wolfgang, Jukema, J Wouter, Guo, Xiuqing, Lindstrom, Sara, Wang, Lu, Smith, Erin N, Gordon, William, de Andrade, Mariza, Brody, Jennifer A, Pattee, Jack W, Haessler, Jeffrey, Brumpton, Ben M, Chasman, Daniel I, Suchon, Pierre, Turman, Constance, Germain, Marine, MacDonald, James, and Braekkan, Sigrid K

Subjects
Genetics, Biotechnology, Human Genome, Atherosclerosis, Prevention, Cardiovascular, Hematology, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular Diseases, Factor XI, Genetic Predisposition to Disease, Genome-Wide Association Study, Hemostasis, Hemostatics, Humans, Phenotype, Polymorphism, Single Nucleotide, Tissue Plasminogen Activator, blood coagulation, cardiovascular diseases, genetic pleiotropy, genome-wide association study, hemostasis, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

BackgroundMulti-phenotype analysis of genetically correlated phenotypes can increase the statistical power to detect loci associated with multiple traits, leading to the discovery of novel loci. This is the first study to date to comprehensively analyze the shared genetic effects within different hemostatic traits, and between these and their associated disease outcomes.ObjectivesTo discover novel genetic associations by combining summary data of correlated hemostatic traits and disease events.MethodsSummary statistics from genome wide-association studies (GWAS) from seven hemostatic traits (factor VII [FVII], factor VIII [FVIII], von Willebrand factor [VWF] factor XI [FXI], fibrinogen, tissue plasminogen activator [tPA], plasminogen activator inhibitor 1 [PAI-1]) and three major cardiovascular (CV) events (venous thromboembolism [VTE], coronary artery disease [CAD], ischemic stroke [IS]), were combined in 27 multi-trait combinations using metaUSAT. Genetic correlations between phenotypes were calculated using Linkage Disequilibrium Score Regression (LDSC). Newly associated loci were investigated for colocalization. We considered a significance threshold of 1.85 × 10-9 obtained after applying Bonferroni correction for the number of multi-trait combinations performed (n = 27).ResultsAcross the 27 multi-trait analyses, we found 4 novel pleiotropic loci (XXYLT1, KNG1, SUGP1/MAU2, TBL2/MLXIPL) that were not significant in the original individual datasets, were not described in previous GWAS for the individual traits, and that presented a common associated variant between the studied phenotypes.ConclusionsThe discovery of four novel loci contributes to the understanding of the relationship between hemostasis and CV events and elucidate common genetic factors between these traits.

Published
2022

4. The power of genetic diversity in genome-wide association studies of lipids

Author

Graham, Sarah E, Clarke, Shoa L, Wu, Kuan-Han H, Kanoni, Stavroula, Zajac, Greg JM, Ramdas, Shweta, Surakka, Ida, Ntalla, Ioanna, Vedantam, Sailaja, Winkler, Thomas W, Locke, Adam E, Marouli, Eirini, Hwang, Mi Yeong, Han, Sohee, Narita, Akira, Choudhury, Ananyo, Bentley, Amy R, Ekoru, Kenneth, Verma, Anurag, Trivedi, Bhavi, Martin, Hilary C, Hunt, Karen A, Hui, Qin, Klarin, Derek, Zhu, Xiang, Thorleifsson, Gudmar, Helgadottir, Anna, Gudbjartsson, Daniel F, Holm, Hilma, Olafsson, Isleifur, Akiyama, Masato, Sakaue, Saori, Terao, Chikashi, Kanai, Masahiro, Zhou, Wei, Brumpton, Ben M, Rasheed, Humaira, Ruotsalainen, Sanni E, Havulinna, Aki S, Veturi, Yogasudha, Feng, QiPing, Rosenthal, Elisabeth A, Lingren, Todd, Pacheco, Jennifer Allen, Pendergrass, Sarah A, Haessler, Jeffrey, Giulianini, Franco, Bradford, Yuki, Miller, Jason E, Campbell, Archie, Lin, Kuang, Millwood, Iona Y, Hindy, George, Rasheed, Asif, Faul, Jessica D, Zhao, Wei, Weir, David R, Turman, Constance, Huang, Hongyan, Graff, Mariaelisa, Mahajan, Anubha, Brown, Michael R, Zhang, Weihua, Yu, Ketian, Schmidt, Ellen M, Pandit, Anita, Gustafsson, Stefan, Yin, Xianyong, Luan, Jian’an, Zhao, Jing-Hua, Matsuda, Fumihiko, Jang, Hye-Mi, Yoon, Kyungheon, Medina-Gomez, Carolina, Pitsillides, Achilleas, Hottenga, Jouke Jan, Willemsen, Gonneke, Wood, Andrew R, Ji, Yingji, Gao, Zishan, Haworth, Simon, Mitchell, Ruth E, Chai, Jin Fang, Aadahl, Mette, Yao, Jie, Manichaikul, Ani, Warren, Helen R, Ramirez, Julia, Bork-Jensen, Jette, Kårhus, Line L, Goel, Anuj, Sabater-Lleal, Maria, Noordam, Raymond, Sidore, Carlo, Fiorillo, Edoardo, McDaid, Aaron F, Marques-Vidal, Pedro, Wielscher, Matthias, Trompet, Stella, and Sattar, Naveed

Subjects
Heart Disease, Prevention, Human Genome, Genetics, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Cardiovascular Diseases, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Population Groups, VA Million Veteran Program, Global Lipids Genetics Consortium*, General Science & Technology
Abstract

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

Published
2021

5. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author

Mullins, Niamh, Forstner, Andreas J, O’Connell, Kevin S, Coombes, Brandon, Coleman, Jonathan RI, Qiao, Zhen, Als, Thomas D, Bigdeli, Tim B, Børte, Sigrid, Bryois, Julien, Charney, Alexander W, Drange, Ole Kristian, Gandal, Michael J, Hagenaars, Saskia P, Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M, Sloofman, Laura G, Steinberg, Stacy, Trubetskoy, Vassily, Winsvold, Bendik S, Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Agerbo, Esben, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bækvad-Hansen, Marie, Bass, Nicholas, Bauer, Michael, Beins, Eva C, Bergen, Sarah E, Birner, Armin, Bøcker Pedersen, Carsten, Bøen, Erlend, Boks, Marco P, Bosch, Rosa, Brum, Murielle, Brumpton, Ben M, Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Clarke, Toni-Kim, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M, Dale, Anders M, Dalkner, Nina, David, Friederike S, Degenhardt, Franziska, Djurovic, Srdjan, Dobbyn, Amanda L, Douzenis, Athanassios, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Ferrier, I Nicol, Fiorentino, Alessia, Foroud, Tatiana M, Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B, Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Giørtz Pedersen, Marianne, Gizer, Ian R, Gordon, Scott D, Gordon-Smith, Katherine, Greenwood, Tiffany A, Grove, Jakob, Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hoffmann, Per, Holmans, Peter A, Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S, and Kalman, Janos L

Subjects
Biological Sciences, Genetics, Biotechnology, Serious Mental Illness, Human Genome, Bipolar Disorder, Neurosciences, Brain Disorders, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Good Health and Well Being, Case-Control Studies, Chromosomes, Human, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Major Histocompatibility Complex, Multifactorial Inheritance, Phenotype, Quantitative Trait Loci, Risk Factors, HUNT All-In Psychiatry, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Published
2021

6. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors

Author

Bakker, Mark K, van der Spek, Rick AA, van Rheenen, Wouter, Morel, Sandrine, Bourcier, Romain, Hostettler, Isabel C, Alg, Varinder S, van Eijk, Kristel R, Koido, Masaru, Akiyama, Masato, Terao, Chikashi, Matsuda, Koichi, Walters, Robin G, Lin, Kuang, Li, Liming, Millwood, Iona Y, Chen, Zhengming, Rouleau, Guy A, Zhou, Sirui, Rannikmäe, Kristiina, Sudlow, Cathie LM, Houlden, Henry, van den Berg, Leonard H, Dina, Christian, Naggara, Olivier, Gentric, Jean-Christophe, Shotar, Eimad, Eugène, François, Desal, Hubert, Winsvold, Bendik S, Børte, Sigrid, Johnsen, Marianne Bakke, Brumpton, Ben M, Sandvei, Marie Søfteland, Willer, Cristen J, Hveem, Kristian, Zwart, John-Anker, Verschuren, WM Monique, Friedrich, Christoph M, Hirsch, Sven, Schilling, Sabine, Dauvillier, Jérôme, Martin, Olivier, Jones, Gregory T, Bown, Matthew J, Ko, Nerissa U, Kim, Helen, Coleman, Jonathan RI, Breen, Gerome, Zaroff, Jonathan G, Klijn, Catharina JM, Malik, Rainer, Dichgans, Martin, Sargurupremraj, Muralidharan, Tatlisumak, Turgut, Amouyel, Philippe, Debette, Stéphanie, Rinkel, Gabriel JE, Worrall, Bradford B, Pera, Joanna, Slowik, Agnieszka, Gaál-Paavola, Emília I, Niemelä, Mika, Jääskeläinen, Juha E, von Und Zu Fraunberg, Mikael, Lindgren, Antti, Broderick, Joseph P, Werring, David J, Woo, Daniel, Redon, Richard, Bijlenga, Philippe, Kamatani, Yoichiro, Veldink, Jan H, and Ruigrok, Ynte M

Subjects
Genetics, Brain Disorders, Human Genome, Clinical Research, Prevention, Stroke, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Asian People, Blood Pressure, Case-Control Studies, Endothelial Cells, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypertension, Intracranial Aneurysm, Polymorphism, Single Nucleotide, Risk Factors, Smoking, Subarachnoid Hemorrhage, White People, HUNT All-In Stroke, China Kadoorie Biobank Collaborative Group, BioBank Japan Project Consortium, ICAN Study Group, CADISP Group, Genetics and Observational Subarachnoid Haemorrhage (GOSH) Study investigators, International Stroke Genetics Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Rupture of an intracranial aneurysm leads to subarachnoid hemorrhage, a severe type of stroke. To discover new risk loci and the genetic architecture of intracranial aneurysms, we performed a cross-ancestry, genome-wide association study in 10,754 cases and 306,882 controls of European and East Asian ancestry. We discovered 17 risk loci, 11 of which are new. We reveal a polygenic architecture and explain over half of the disease heritability. We show a high genetic correlation between ruptured and unruptured intracranial aneurysms. We also find a suggestive role for endothelial cells by using gene mapping and heritability enrichment. Drug-target enrichment shows pleiotropy between intracranial aneurysms and antiepileptic and sex hormone drugs, providing insights into intracranial aneurysm pathophysiology. Finally, genetic risks for smoking and high blood pressure, the two main clinical risk factors, play important roles in intracranial aneurysm risk, and drive most of the genetic correlation between intracranial aneurysms and other cerebrovascular traits.

Published
2020

7. Age-of-onset information helps identify 76 genetic variants associated with allergic disease.

Author

Ferreira, Manuel AR, Vonk, Judith M, Baurecht, Hansjörg, Marenholz, Ingo, Tian, Chao, Hoffman, Joshua D, Helmer, Quinta, Tillander, Annika, Ullemar, Vilhelmina, Lu, Yi, Grosche, Sarah, Rüschendorf, Franz, Granell, Raquel, Brumpton, Ben M, Fritsche, Lars G, Bhatta, Laxmi, Gabrielsen, Maiken E, Nielsen, Jonas B, Zhou, Wei, Hveem, Kristian, Langhammer, Arnulf, Holmen, Oddgeir L, Løset, Mari, Abecasis, Gonçalo R, Willer, Cristen J, Emami, Nima C, Cavazos, Taylor B, Witte, John S, Szwajda, Agnieszka, 23andMe Research Team, collaborators of the SHARE study, Hinds, David A, Hübner, Norbert, Weidinger, Stephan, Magnusson, Patrik Ke, Jorgenson, Eric, Karlsson, Robert, Paternoster, Lavinia, Boomsma, Dorret I, Almqvist, Catarina, Lee, Young-Ae, and Koppelman, Gerard H

Subjects
23andMe Research Team, collaborators of the SHARE study, Humans, Asthma, Eczema, Age of Onset, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Middle Aged, Child, Female, Rhinitis, Allergic, Seasonal, Male, Genome-Wide Association Study, Genetic Loci, Polymorphism, Single Nucleotide, Rhinitis, Allergic, Seasonal, Developmental Biology, Genetics
Abstract

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P

Published
2020

8. Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology

Author

Ferreira, Manuel A, Vonk, Judith M, Baurecht, Hansjörg, Marenholz, Ingo, Tian, Chao, Hoffman, Joshua D, Helmer, Quinta, Tillander, Annika, Ullemar, Vilhelmina, van Dongen, Jenny, Lu, Yi, Rüschendorf, Franz, Esparza-Gordillo, Jorge, Medway, Chris W, Mountjoy, Edward, Burrows, Kimberley, Hummel, Oliver, Grosche, Sarah, Brumpton, Ben M, Witte, John S, Hottenga, Jouke-Jan, Willemsen, Gonneke, Zheng, Jie, Rodríguez, Elke, Hotze, Melanie, Franke, Andre, Revez, Joana A, Beesley, Jonathan, Matheson, Melanie C, Dharmage, Shyamali C, Bain, Lisa M, Fritsche, Lars G, Gabrielsen, Maiken E, Balliu, Brunilda, Nielsen, Jonas B, Zhou, Wei, Hveem, Kristian, Langhammer, Arnulf, Holmen, Oddgeir L, Løset, Mari, Abecasis, Gonçalo R, Willer, Cristen J, Arnold, Andreas, Homuth, Georg, Schmidt, Carsten O, Thompson, Philip J, Martin, Nicholas G, Duffy, David L, Novak, Natalija, Schulz, Holger, Karrasch, Stefan, Gieger, Christian, Strauch, Konstantin, Melles, Ronald B, Hinds, David A, Hübner, Norbert, Weidinger, Stephan, Magnusson, Patrik KE, Jansen, Rick, Jorgenson, Eric, Lee, Young-Ae, Boomsma, Dorret I, Almqvist, Catarina, Karlsson, Robert, Koppelman, Gerard H, and Paternoster, Lavinia

Subjects
Biological Sciences, Genetics, Emerging Infectious Diseases, Lung, Prevention, Asthma, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Eczema, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hypersensitivity, Phenotype, Polymorphism, Single Nucleotide, Rhinitis, Allergic, Seasonal, Risk Factors, 23andMe Research Team, AAGC collaborators, BIOS consortium, LifeLines Cohort Study, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Asthma, hay fever (or allergic rhinitis) and eczema (or atopic dermatitis) often coexist in the same individuals, partly because of a shared genetic origin. To identify shared risk variants, we performed a genome-wide association study (GWAS; n = 360,838) of a broad allergic disease phenotype that considers the presence of any one of these three diseases. We identified 136 independent risk variants (P < 3 × 10-8), including 73 not previously reported, which implicate 132 nearby genes in allergic disease pathophysiology. Disease-specific effects were detected for only six variants, confirming that most represent shared risk factors. Tissue-specific heritability and biological process enrichment analyses suggest that shared risk variants influence lymphocyte-mediated immunity. Six target genes provide an opportunity for drug repositioning, while for 36 genes CpG methylation was found to influence transcription independently of genetic effects. Asthma, hay fever and eczema partly coexist because they share many genetic risk variants that dysregulate the expression of immune-related genes.

Published
2017

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