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Your search keyword '"Mangino, Massimo"' showing total 45 results
Start Over Author "Mangino, Massimo" Publisher escholarship, university of california
45 results on '"Mangino, Massimo"'

1. Understanding the genetic complexity of puberty timing across the allele frequency spectrum.

Author

Kentistou, Katherine, Kaisinger, Lena, Stankovic, Stasa, Vaudel, Marc, Mendes de Oliveira, Edson, Messina, Andrea, Walters, Robin, Liu, Xiaoxi, Busch, Alexander, Helgason, Hannes, Thompson, Deborah, Santoni, Federico, Petricek, Konstantin, Zouaghi, Yassine, Huang-Doran, Isabel, Gudbjartsson, Daniel, Bratland, Eirik, Lin, Kuang, Gardner, Eugene, Zhao, Yajie, Jia, Raina, Terao, Chikashi, Riggan, Marjorie, Bolla, Manjeet, Yazdanpanah, Mojgan, Yazdanpanah, Nahid, Bradfield, Jonathan, Broer, Linda, Campbell, Archie, Chasman, Daniel, Cousminer, Diana, Franceschini, Nora, Franke, Lude, Girotto, Giorgia, He, Chunyan, Järvelin, Marjo-Riitta, Joshi, Peter, Kamatani, Yoichiro, Karlsson, Robert, Luan, Jianan, Lunetta, Kathryn, Mägi, Reedik, Mangino, Massimo, Medland, Sarah, Meisinger, Christa, Noordam, Raymond, Nutile, Teresa, Concas, Maria, Polašek, Ozren, Porcu, Eleonora, Ring, Susan, Sala, Cinzia, Smith, Albert, Tanaka, Toshiko, van der Most, Peter, Vitart, Veronique, Wang, Carol, Willemsen, Gonneke, Zygmunt, Marek, Ahearn, Thomas, Andrulis, Irene, Anton-Culver, Hoda, Antoniou, Antonis, Auer, Paul, Barnes, Catriona, Beckmann, Matthias, Berrington de Gonzalez, Amy, Bogdanova, Natalia, Bojesen, Stig, Brenner, Hermann, Buring, Julie, Canzian, Federico, Chang-Claude, Jenny, Couch, Fergus, Cox, Angela, Crisponi, Laura, Czene, Kamila, Daly, Mary, Demerath, Ellen, Dennis, Joe, Devilee, Peter, De Vivo, Immaculata, Dörk, Thilo, Dunning, Alison, Dwek, Miriam, Eriksson, Johan, Fasching, Peter, Fernandez-Rhodes, Lindsay, Ferreli, Liana, Fletcher, Olivia, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José, González-Neira, Anna, Grallert, Harald, Guénel, Pascal, Haiman, Christopher, Hall, Per, Hamann, Ute, and Hakonarson, Hakon

Subjects
Humans, Female, Menarche, Puberty, Gene Frequency, Animals, Multifactorial Inheritance, Mice, Genome-Wide Association Study, Adolescent, Puberty, Precocious, Polymorphism, Single Nucleotide, Receptors, G-Protein-Coupled, Puberty, Delayed, Child
Abstract

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease.

Published
2024

2. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

Author

Rahmioglu, Nilufer, Mortlock, Sally, Ghiasi, Marzieh, Møller, Peter L, Stefansdottir, Lilja, Galarneau, Geneviève, Turman, Constance, Danning, Rebecca, Law, Matthew H, Sapkota, Yadav, Christofidou, Paraskevi, Skarp, Sini, Giri, Ayush, Banasik, Karina, Krassowski, Michal, Lepamets, Maarja, Marciniak, Błażej, Nõukas, Margit, Perro, Danielle, Sliz, Eeva, Sobalska-Kwapis, Marta, Thorleifsson, Gudmar, Topbas-Selcuki, Nura F, Vitonis, Allison, Westergaard, David, Arnadottir, Ragnheidur, Burgdorf, Kristoffer S, Campbell, Archie, Cheuk, Cecilia SK, Clementi, Caterina, Cook, James, De Vivo, Immaculata, DiVasta, Amy, Dorien, O, Donoghue, Jacqueline F, Edwards, Todd, Fontanillas, Pierre, Fung, Jenny N, Geirsson, Reynir T, Girling, Jane E, Harkki, Paivi, Harris, Holly R, Healey, Martin, Heikinheimo, Oskari, Holdsworth-Carson, Sarah, Hostettler, Isabel C, Houlden, Henry, Houshdaran, Sahar, Irwin, Juan C, Jarvelin, Marjo-Riitta, Kamatani, Yoichiro, Kennedy, Stephen H, Kepka, Ewa, Kettunen, Johannes, Kubo, Michiaki, Kulig, Bartosz, Kurra, Venla, Laivuori, Hannele, Laufer, Marc R, Lindgren, Cecilia M, MacGregor, Stuart, Mangino, Massimo, Martin, Nicholas G, Matalliotaki, Charoula, Matalliotakis, Michail, Murray, Alison D, Ndungu, Anne, Nezhat, Camran, Olsen, Catherine M, Opoku-Anane, Jessica, Padmanabhan, Sandosh, Paranjpe, Manish, Peters, Maire, Polak, Grzegorz, Porteous, David J, Rabban, Joseph, Rexrode, Kathyrn M, Romanowicz, Hanna, Saare, Merli, Saavalainen, Liisu, Schork, Andrew J, Sen, Sushmita, Shafrir, Amy L, Siewierska-Górska, Anna, Słomka, Marcin, Smith, Blair H, Smolarz, Beata, Szaflik, Tomasz, Szyłło, Krzysztof, Takahashi, Atsushi, Terry, Kathryn L, Tomassetti, Carla, Treloar, Susan A, Vanhie, Arne, Vincent, Katy, Vo, Kim C, Werring, David J, Zeggini, Eleftheria, Zervou, Maria I, and Adachi, Sosuke

Subjects
Biological Sciences, Genetics, Contraception/Reproduction, Clinical Research, Endometriosis, Prevention, Pain Research, Chronic Pain, Infertility, 2.1 Biological and endogenous factors, Aetiology, Female, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, Pain, Comorbidity, DBDS Genomic Consortium, FinnGen Study, FinnGen Endometriosis Taskforce, Celmatix Research Team, 23andMe Research Team, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

Published
2023

3. Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.

Author

Wang, Zhe, Emmerich, Andrew, Pillon, Nicolas, Moore, Tim, Hemerich, Daiane, Cornelis, Marilyn, Mazzaferro, Eugenia, Broos, Siacia, Ahluwalia, Tarunveer, Bartz, Traci, Bentley, Amy, Bielak, Lawrence, Chong, Mike, Chu, Audrey, Berry, Diane, Dorajoo, Rajkumar, Dueker, Nicole, Kasbohm, Elisa, Feenstra, Bjarke, Feitosa, Mary, Gieger, Christian, Graff, Mariaelisa, Hall, Leanne, Haller, Toomas, Hartwig, Fernando, Hillis, David, Huikari, Ville, Heard-Costa, Nancy, Holzapfel, Christina, Jackson, Anne, Johansson, Åsa, Jørgensen, Anja, Kaakinen, Marika, Karlsson, Robert, Kerr, Kathleen, Kim, Boram, Koolhaas, Chantal, Kutalik, Zoltan, Lagou, Vasiliki, Lind, Penelope, Lorentzon, Mattias, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Metzendorf, Christoph, Monroe, Kristine, Pacolet, Alexander, Pérusse, Louis, Pool, Rene, Richmond, Rebecca, Rivera, Natalia, Robiou-du-Pont, Sebastien, Schraut, Katharina, Schulz, Christina-Alexandra, Stringham, Heather, Tanaka, Toshiko, Teumer, Alexander, Turman, Constance, van der Most, Peter, Vanmunster, Mathias, van Rooij, Frank, van Vliet-Ostaptchouk, Jana, Zhang, Xiaoshuai, Zhao, Jing-Hua, Zhao, Wei, Balkhiyarova, Zhanna, Balslev-Harder, Marie, Baumeister, Sebastian, Beilby, John, Blangero, John, Boomsma, Dorret, Brage, Soren, Braund, Peter, Brody, Jennifer, Bruinenberg, Marcel, Ekelund, Ulf, Liu, Ching-Ti, Cole, John, Collins, Francis, Cupples, L, Esko, Tõnu, Enroth, Stefan, Faul, Jessica, Fernandez-Rhodes, Lindsay, Fohner, Alison, Franco, Oscar, Galesloot, Tessel, Gordon, Scott, Grarup, Niels, Hartman, Catharina, Heiss, Gerardo, Hui, Jennie, Illig, Thomas, Jago, Russell, James, Alan, Joshi, Peter, Jung, Taeyeong, Kähönen, Mika, Kilpeläinen, Tuomas, Koh, Woon-Puay, and Kolcic, Ivana

Subjects
Actinin, Cross-Sectional Studies, Exercise, Genome-Wide Association Study, Humans, Leisure Activities, Sedentary Behavior
Abstract

Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.

Published
2022

4. 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

5. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects

Author

Howe, Laurence J, Nivard, Michel G, Morris, Tim T, Hansen, Ailin F, Rasheed, Humaira, Cho, Yoonsu, Chittoor, Geetha, Ahlskog, Rafael, Lind, Penelope A, Palviainen, Teemu, van der Zee, Matthijs D, Cheesman, Rosa, Mangino, Massimo, Wang, Yunzhang, Li, Shuai, Klaric, Lucija, Ratliff, Scott M, Bielak, Lawrence F, Nygaard, Marianne, Giannelis, Alexandros, Willoughby, Emily A, Reynolds, Chandra A, Balbona, Jared V, Andreassen, Ole A, Ask, Helga, Baras, Aris, Bauer, Christopher R, Boomsma, Dorret I, Campbell, Archie, Campbell, Harry, Chen, Zhengming, Christofidou, Paraskevi, Corfield, Elizabeth, Dahm, Christina C, Dokuru, Deepika R, Evans, Luke M, de Geus, Eco JC, Giddaluru, Sudheer, Gordon, Scott D, Harden, K Paige, Hill, W David, Hughes, Amanda, Kerr, Shona M, Kim, Yongkang, Kweon, Hyeokmoon, Latvala, Antti, Lawlor, Deborah A, Li, Liming, Lin, Kuang, Magnus, Per, Magnusson, Patrik KE, Mallard, Travis T, Martikainen, Pekka, Mills, Melinda C, Njølstad, Pål Rasmus, Overton, John D, Pedersen, Nancy L, Porteous, David J, Reid, Jeffrey, Silventoinen, Karri, Southey, Melissa C, Stoltenberg, Camilla, Tucker-Drob, Elliot M, Wright, Margaret J, Hewitt, John K, Keller, Matthew C, Stallings, Michael C, Lee, James J, Christensen, Kaare, Kardia, Sharon LR, Peyser, Patricia A, Smith, Jennifer A, Wilson, James F, Hopper, John L, Hägg, Sara, Spector, Tim D, Pingault, Jean-Baptiste, Plomin, Robert, Havdahl, Alexandra, Bartels, Meike, Martin, Nicholas G, Oskarsson, Sven, Justice, Anne E, Millwood, Iona Y, Hveem, Kristian, Naess, Øyvind, Willer, Cristen J, Åsvold, Bjørn Olav, Koellinger, Philipp D, Kaprio, Jaakko, Medland, Sarah E, Walters, Robin G, Benjamin, Daniel J, Turley, Patrick, Evans, David M, Davey Smith, George, Hayward, Caroline, Brumpton, Ben, Hemani, Gibran, and Davies, Neil M

Subjects
Human Genome, Genetics, Pediatric, 2.1 Biological and endogenous factors, Aetiology, Mental health, Generic health relevance, Genome-Wide Association Study, Humans, Mendelian Randomization Analysis, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Social Science Genetic Association Consortium, Within Family Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.

Published
2022

6. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

McCartney, Daniel L, Min, Josine L, Richmond, Rebecca C, Lu, Ake T, Sobczyk, Maria K, Davies, Gail, Broer, Linda, Guo, Xiuqing, Jeong, Ayoung, Jung, Jeesun, Kasela, Silva, Katrinli, Seyma, Kuo, Pei-Lun, Matias-Garcia, Pamela R, Mishra, Pashupati P, Nygaard, Marianne, Palviainen, Teemu, Patki, Amit, Raffield, Laura M, Ratliff, Scott M, Richardson, Tom G, Robinson, Oliver, Soerensen, Mette, Sun, Dianjianyi, Tsai, Pei-Chien, van der Zee, Matthijs D, Walker, Rosie M, Wang, Xiaochuan, Wang, Yunzhang, Xia, Rui, Xu, Zongli, Yao, Jie, Zhao, Wei, Correa, Adolfo, Boerwinkle, Eric, Dugué, Pierre-Antoine, Durda, Peter, Elliott, Hannah R, Gieger, Christian, de Geus, Eco JC, Harris, Sarah E, Hemani, Gibran, Imboden, Medea, Kähönen, Mika, Kardia, Sharon LR, Kresovich, Jacob K, Li, Shengxu, Lunetta, Kathryn L, Mangino, Massimo, Mason, Dan, McIntosh, Andrew M, Mengel-From, Jonas, Moore, Ann Zenobia, Murabito, Joanne M, Ollikainen, Miina, Pankow, James S, Pedersen, Nancy L, Peters, Annette, Polidoro, Silvia, Porteous, David J, Raitakari, Olli, Rich, Stephen S, Sandler, Dale P, Sillanpää, Elina, Smith, Alicia K, Southey, Melissa C, Strauch, Konstantin, Tiwari, Hemant, Tanaka, Toshiko, Tillin, Therese, Uitterlinden, Andre G, Van Den Berg, David J, van Dongen, Jenny, Wilson, James G, Wright, John, Yet, Idil, Arnett, Donna, Bandinelli, Stefania, Bell, Jordana T, Binder, Alexandra M, Boomsma, Dorret I, Chen, Wei, Christensen, Kaare, Conneely, Karen N, Elliott, Paul, Ferrucci, Luigi, Fornage, Myriam, Hägg, Sara, Hayward, Caroline, Irvin, Marguerite, Kaprio, Jaakko, Lawlor, Deborah A, Lehtimäki, Terho, Lohoff, Falk W, Milani, Lili, Milne, Roger L, Probst-Hensch, Nicole, Reiner, Alex P, Ritz, Beate, and Rotter, Jerome I

Subjects
Prevention, Nutrition, Aging, Human Genome, Genetics, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adiposity, Biomarkers, C-Reactive Protein, CpG Islands, DNA Methylation, Educational Status, Epigenesis, Genetic, Genetic Loci, Genetic Markers, Genome, Human, Genome-Wide Association Study, Granulocytes, Humans, Immunity, Innate, Lipid Metabolism, Multifactorial Inheritance, Plasminogen Activator Inhibitor 1, DNA methylation, GWAS, Epigenetic clock, Genetics of DNA Methylation Consortium, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundBiological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.ResultsLeveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.ConclusionThis study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021

7. Genome-wide association study identifies 48 common genetic variants associated with handedness

Author

Cuellar-Partida, Gabriel, Tung, Joyce Y, Eriksson, Nicholas, Albrecht, Eva, Aliev, Fazil, Andreassen, Ole A, Barroso, Inês, Beckmann, Jacques S, Boks, Marco P, Boomsma, Dorret I, Boyd, Heather A, Breteler, Monique MB, Campbell, Harry, Chasman, Daniel I, Cherkas, Lynn F, Davies, Gail, de Geus, Eco JC, Deary, Ian J, Deloukas, Panos, Dick, Danielle M, Duffy, David L, Eriksson, Johan G, Esko, Tõnu, Feenstra, Bjarke, Geller, Frank, Gieger, Christian, Giegling, Ina, Gordon, Scott D, Han, Jiali, Hansen, Thomas F, Hartmann, Annette M, Hayward, Caroline, Heikkilä, Kauko, Hicks, Andrew A, Hirschhorn, Joel N, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Liang-Dar, Ikram, M Arfan, Kaprio, Jaakko, Kemp, John P, Khaw, Kay-Tee, Klopp, Norman, Konte, Bettina, Kutalik, Zoltan, Lahti, Jari, Li, Xin, Loos, Ruth JF, Luciano, Michelle, Magnusson, Sigurdur H, Mangino, Massimo, Marques-Vidal, Pedro, Martin, Nicholas G, McArdle, Wendy L, McCarthy, Mark I, Medina-Gomez, Carolina, Melbye, Mads, Melville, Scott A, Metspalu, Andres, Milani, Lili, Mooser, Vincent, Nelis, Mari, Nyholt, Dale R, O’Connell, Kevin S, Ophoff, Roel A, Palmer, Cameron, Palotie, Aarno, Palviainen, Teemu, Pare, Guillaume, Paternoster, Lavinia, Peltonen, Leena, Penninx, Brenda WJH, Polasek, Ozren, Pramstaller, Peter P, Prokopenko, Inga, Raikkonen, Katri, Ripatti, Samuli, Rivadeneira, Fernando, Rudan, Igor, Rujescu, Dan, Smit, Johannes H, Smith, George Davey, Smoller, Jordan W, Soranzo, Nicole, Spector, Tim D, Pourcain, Beate St, Starr, John M, Stefánsson, Hreinn, Steinberg, Stacy, Teder-Laving, Maris, Thorleifsson, Gudmar, Stefánsson, Kári, Timpson, Nicholas J, Uitterlinden, André G, van Duijn, Cornelia M, van Rooij, Frank JA, Vink, Jaqueline M, Vollenweider, Peter, Vuoksimaa, Eero, and Waeber, Gérard

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Human Genome, Mental Health, Brain Disorders, Neurosciences, Schizophrenia, Genetics, 2.1 Biological and endogenous factors, Aetiology, Mental health, Adult, Aged, Female, Functional Laterality, Gene Frequency, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Sex Factors, Biomedical and clinical sciences, Health sciences
Abstract

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P

Published
2021

8. Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity

Author

Yaghootkar, Hanieh, Zhang, Yiying, Spracklen, Cassandra N, Karaderi, Tugce, Huang, Lam Opal, Bradfield, Jonathan, Schurmann, Claudia, Fine, Rebecca S, Preuss, Michael H, Kutalik, Zoltan, Wittemans, Laura BL, Lu, Yingchang, Metz, Sophia, Willems, Sara M, Li-Gao, Ruifang, Grarup, Niels, Wang, Shuai, Molnos, Sophie, Sandoval-Zárate, América A, Nalls, Mike A, Lange, Leslie A, Haesser, Jeffrey, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Feitosa, Mary F, Sitlani, Colleen M, Venturini, Cristina, Mahajan, Anubha, Kacprowski, Tim, Wang, Carol A, Chasman, Daniel I, Amin, Najaf, Broer, Linda, Robertson, Neil, Young, Kristin L, Allison, Matthew, Auer, Paul L, Blüher, Matthias, Borja, Judith B, Bork-Jensen, Jette, Carrasquilla, Germán D, Christofidou, Paraskevi, Demirkan, Ayse, Doege, Claudia A, Garcia, Melissa E, Graff, Mariaelisa, Guo, Kaiying, Hakonarson, Hakon, Hong, Jaeyoung, Ida Chen, Yii-Der, Jackson, Rebecca, Jakupović, Hermina, Jousilahti, Pekka, Justice, Anne E, Kähönen, Mika, Kizer, Jorge R, Kriebel, Jennifer, LeDuc, Charles A, Li, Jin, Lind, Lars, Luan, Jian'an, Mackey, David A, Mangino, Massimo, Männistö, Satu, Martin Carli, Jayne F, Medina-Gomez, Carolina, Mook-Kanamori, Dennis O, Morris, Andrew P, de Mutsert, Renée, Nauck, Matthias, Prokic, Ivana, Pennell, Craig E, Pradhan, Arund D, Psaty, Bruce M, Raitakari, Olli T, Scott, Robert A, Skaaby, Tea, Strauch, Konstantin, Taylor, Kent D, Teumer, Alexander, Uitterlinden, Andre G, Wu, Ying, Yao, Jie, Walker, Mark, North, Kari E, Kovacs, Peter, Ikram, M Arfan, van Duijn, Cornelia M, Ridker, Paul M, Lye, Stephen, Homuth, Georg, Ingelsson, Erik, Spector, Tim D, McKnight, Barbara, Province, Michael A, Lehtimäki, Terho, Adair, Linda S, Rotter, Jerome I, Reiner, Alexander P, and Wilson, James G

Subjects
Genetics, Nutrition, Prevention, Obesity, Aetiology, 2.1 Biological and endogenous factors, Oral and gastrointestinal, Metabolic and endocrine, Cardiovascular, Stroke, Cancer, Adiposity, Gene Expression Regulation, Developmental, Genetic Variation, Genotype, Humans, Leptin, Models, Molecular, Protein Conformation, Racial Groups, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

Leptin influences food intake by informing the brain about the status of body fat stores. Rare LEP mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in LEP, ZNF800, KLHL31, and ACTL9, and one intergenic variant near KLF14. The missense variant Val94Met (rs17151919) in LEP was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry (P = 2 × 10-16, n = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.

Published
2020

9. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

Author

Ntalla, Ioanna, Weng, Lu-Chen, Cartwright, James H, Hall, Amelia Weber, Sveinbjornsson, Gardar, Tucker, Nathan R, Choi, Seung Hoan, Chaffin, Mark D, Roselli, Carolina, Barnes, Michael R, Mifsud, Borbala, Warren, Helen R, Hayward, Caroline, Marten, Jonathan, Cranley, James J, Concas, Maria Pina, Gasparini, Paolo, Boutin, Thibaud, Kolcic, Ivana, Polasek, Ozren, Rudan, Igor, Araujo, Nathalia M, Lima-Costa, Maria Fernanda, Ribeiro, Antonio Luiz P, Souza, Renan P, Tarazona-Santos, Eduardo, Giedraitis, Vilmantas, Ingelsson, Erik, Mahajan, Anubha, Morris, Andrew P, Del Greco M, Fabiola, Foco, Luisa, Gögele, Martin, Hicks, Andrew A, Cook, James P, Lind, Lars, Lindgren, Cecilia M, Sundström, Johan, Nelson, Christopher P, Riaz, Muhammad B, Samani, Nilesh J, Sinagra, Gianfranco, Ulivi, Sheila, Kähönen, Mika, Mishra, Pashupati P, Mononen, Nina, Nikus, Kjell, Caulfield, Mark J, Dominiczak, Anna, Padmanabhan, Sandosh, Montasser, May E, O'Connell, Jeff R, Ryan, Kathleen, Shuldiner, Alan R, Aeschbacher, Stefanie, Conen, David, Risch, Lorenz, Thériault, Sébastien, Hutri-Kähönen, Nina, Lehtimäki, Terho, Lyytikäinen, Leo-Pekka, Raitakari, Olli T, Barnes, Catriona LK, Campbell, Harry, Joshi, Peter K, Wilson, James F, Isaacs, Aaron, Kors, Jan A, van Duijn, Cornelia M, Huang, Paul L, Gudnason, Vilmundur, Harris, Tamara B, Launer, Lenore J, Smith, Albert V, Bottinger, Erwin P, Loos, Ruth JF, Nadkarni, Girish N, Preuss, Michael H, Correa, Adolfo, Mei, Hao, Wilson, James, Meitinger, Thomas, Müller-Nurasyid, Martina, Peters, Annette, Waldenberger, Melanie, Mangino, Massimo, Spector, Timothy D, Rienstra, Michiel, van de Vegte, Yordi J, van der Harst, Pim, Verweij, Niek, Kääb, Stefan, Schramm, Katharina, Sinner, Moritz F, Strauch, Konstantin, Cutler, Michael J, Fatkin, Diane, London, Barry, Olesen, Morten, and Roden, Dan M

Subjects
Humans, Cardiovascular Diseases, Genetic Predisposition to Disease, Electrocardiography, Gene Expression, Multifactorial Inheritance, Quantitative Trait Loci, Female, Male, Arrhythmias, Cardiac, Genetic Variation, Genome-Wide Association Study, Genetic Loci, Endophenotypes, Arrhythmias, Cardiac
Abstract

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Published
2020

10. New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders

Author

Evangelou, Evangelos, Gao, He, Chu, Congying, Ntritsos, Georgios, Blakeley, Paul, Butts, Andrew R, Pazoki, Raha, Suzuki, Hideaki, Koskeridis, Fotios, Yiorkas, Andrianos M, Karaman, Ibrahim, Elliott, Joshua, Luo, Qiang, Aeschbacher, Stefanie, Bartz, Traci M, Baumeister, Sebastian E, Braund, Peter S, Brown, Michael R, Brody, Jennifer A, Clarke, Toni-Kim, Dimou, Niki, Faul, Jessica D, Homuth, Georg, Jackson, Anne U, Kentistou, Katherine A, Joshi, Peter K, Lemaitre, Rozenn N, Lind, Penelope A, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Milaneschi, Yuri, Nelson, Christopher P, Nolte, Ilja M, Perälä, Mia-Maria, Polasek, Ozren, Porteous, David, Ratliff, Scott M, Smith, Jennifer A, Stančáková, Alena, Teumer, Alexander, Tuominen, Samuli, Thériault, Sébastien, Vangipurapu, Jagadish, Whitfield, John B, Wood, Alexis, Yao, Jie, Yu, Bing, Zhao, Wei, Arking, Dan E, Auvinen, Juha, Liu, Chunyu, Männikkö, Minna, Risch, Lorenz, Rotter, Jerome I, Snieder, Harold, Veijola, Juha, Blakemore, Alexandra I, Boehnke, Michael, Campbell, Harry, Conen, David, Eriksson, Johan G, Grabe, Hans J, Guo, Xiuqing, van der Harst, Pim, Hartman, Catharina A, Hayward, Caroline, Heath, Andrew C, Jarvelin, Marjo-Riitta, Kähönen, Mika, Kardia, Sharon LR, Kühne, Michael, Kuusisto, Johanna, Laakso, Markku, Lahti, Jari, Lehtimäki, Terho, McIntosh, Andrew M, Mohlke, Karen L, Morrison, Alanna C, Martin, Nicholas G, Oldehinkel, Albertine J, Penninx, Brenda WJH, Psaty, Bruce M, Raitakari, Olli T, Rudan, Igor, Samani, Nilesh J, Scott, Laura J, Spector, Tim D, Verweij, Niek, Weir, David R, Wilson, James F, Levy, Daniel, Tzoulaki, Ioanna, Bell, Jimmy D, Matthews, Paul M, Rothenfluh, Adrian, Desrivières, Sylvane, Schumann, Gunter, and Elliott, Paul

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Epidemiology, Health Sciences, Psychology, Pharmacology and Pharmaceutical Sciences, Biotechnology, Substance Misuse, Brain Disorders, Mental Health, Neurosciences, Serious Mental Illness, Alcoholism, Alcohol Use and Health, Schizophrenia, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Mental health, Stroke, Cancer, Oral and gastrointestinal, Good Health and Well Being, Adult, Aged, Alcohol Drinking, Alcoholism, Brain, Female, Genes, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Mental Disorders, Middle Aged, Neuroimaging, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Biomedical and clinical sciences, Health sciences
Abstract

Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d-1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.

Published
2019

11. Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology

Author

Spracklen, Cassandra N, Karaderi, Tugce, Yaghootkar, Hanieh, Schurmann, Claudia, Fine, Rebecca S, Kutalik, Zoltan, Preuss, Michael H, Lu, Yingchang, Wittemans, Laura BL, Adair, Linda S, Allison, Matthew, Amin, Najaf, Auer, Paul L, Bartz, Traci M, Blüher, Matthias, Boehnke, Michael, Borja, Judith B, Bork-Jensen, Jette, Broer, Linda, Chasman, Daniel I, Chen, Yii-Der Ida, Chirstofidou, Paraskevi, Demirkan, Ayse, van Duijn, Cornelia M, Feitosa, Mary F, Garcia, Melissa E, Graff, Mariaelisa, Grallert, Harald, Grarup, Niels, Guo, Xiuqing, Haesser, Jeffrey, Hansen, Torben, Harris, Tamara B, Highland, Heather M, Hong, Jaeyoung, Ikram, M Arfan, Ingelsson, Erik, Jackson, Rebecca, Jousilahti, Pekka, Kähönen, Mika, Kizer, Jorge R, Kovacs, Peter, Kriebel, Jennifer, Laakso, Markku, Lange, Leslie A, Lehtimäki, Terho, Li, Jin, Li-Gao, Ruifang, Lind, Lars, Luan, Jian'an, Lyytikäinen, Leo-Pekka, MacGregor, Stuart, Mackey, David A, Mahajan, Anubha, Mangino, Massimo, Männistö, Satu, McCarthy, Mark I, McKnight, Barbara, Medina-Gomez, Carolina, Meigs, James B, Molnos, Sophie, Mook-Kanamori, Dennis, Morris, Andrew P, de Mutsert, Renee, Nalls, Mike A, Nedeljkovic, Ivana, North, Kari E, Pennell, Craig E, Pradhan, Aruna D, Province, Michael A, Raitakari, Olli T, Raulerson, Chelsea K, Reiner, Alex P, Ridker, Paul M, Ripatti, Samuli, Roberston, Neil, Rotter, Jerome I, Salomaa, Veikko, Sandoval-Zárate, America A, Sitlani, Colleen M, Spector, Tim D, Strauch, Konstantin, Stumvoll, Michael, Taylor, Kent D, Thuesen, Betina, Tönjes, Anke, Uitterlinden, Andre G, Venturini, Cristina, Walker, Mark, Wang, Carol A, Wang, Shuai, Wareham, Nicholas J, Willems, Sara M, Willems van Dijk, Ko, Wilson, James G, Wu, Ying, Yao, Jie, Young, Kristin L, Langenberg, Claudia, and Frayling, Timothy M

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Nutrition, Obesity, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Cardiovascular, Adiponectin, Adipose Tissue, Adolescent, Adult, Black or African American, Aged, Aged, 80 and over, Exome, Female, Genetic Predisposition to Disease, Hispanic or Latino, Humans, Lipids, Male, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Young Adult, adiponectin, cardio metabolic traits, exome, genetics, genome-wide association study, lipids, obesity, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.

Published
2019

12. Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders

Author

Ligthart, Symen, Vaez, Ahmad, Võsa, Urmo, Stathopoulou, Maria G, de Vries, Paul S, Prins, Bram P, Van der Most, Peter J, Tanaka, Toshiko, Naderi, Elnaz, Rose, Lynda M, Wu, Ying, Karlsson, Robert, Barbalic, Maja, Lin, Honghuang, Pool, René, Zhu, Gu, Macé, Aurélien, Sidore, Carlo, Trompet, Stella, Mangino, Massimo, Sabater-Lleal, Maria, Kemp, John P, Abbasi, Ali, Kacprowski, Tim, Verweij, Niek, Smith, Albert V, Huang, Tao, Marzi, Carola, Feitosa, Mary F, Lohman, Kurt K, Kleber, Marcus E, Milaneschi, Yuri, Mueller, Christian, Huq, Mahmudul, Vlachopoulou, Efthymia, Lyytikäinen, Leo-Pekka, Oldmeadow, Christopher, Deelen, Joris, Perola, Markus, Zhao, Jing Hua, Feenstra, Bjarke, Amini, Marzyeh, Lahti, Jari, Schraut, Katharina E, Fornage, Myriam, Suktitipat, Bhoom, Chen, Wei-Min, Li, Xiaohui, Nutile, Teresa, Malerba, Giovanni, Luan, Jian’an, Bak, Tom, Schork, Nicholas, Del Greco M., Fabiola, Thiering, Elisabeth, Mahajan, Anubha, Marioni, Riccardo E, Mihailov, Evelin, Eriksson, Johan, Ozel, Ayse Bilge, Zhang, Weihua, Nethander, Maria, Cheng, Yu-Ching, Aslibekyan, Stella, Ang, Wei, Gandin, Ilaria, Yengo, Loïc, Portas, Laura, Kooperberg, Charles, Hofer, Edith, Rajan, Kumar B, Schurmann, Claudia, Hollander, Wouter den, Ahluwalia, Tarunveer Singh, Zhao, Jing, Draisma, Harmen HM, Ford, Ian, Timpson, Nicholas, Teumer, Alexander, Huang, Hongyan, Wahl, Simone, Liu, YongMei, Huang, Jie, Uh, Hae-Won, Geller, Frank, Joshi, Peter K, Yanek, Lisa R, Trabetti, Elisabetta, Lehne, Benjamin, Vozzi, Diego, Verbanck, Marie, Biino, Ginevra, Saba, Yasaman, Meulenbelt, Ingrid, O’Connell, Jeff R, Laakso, Markku, Giulianini, Franco, Magnusson, Patrik KE, Ballantyne, Christie M, and Hottenga, Jouke Jan

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Prevention, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Biomarkers, Bipolar Disorder, Body Mass Index, C-Reactive Protein, Child, Female, Genetic Loci, Genome-Wide Association Study, Humans, Inflammation, Liver, Male, Mendelian Randomization Analysis, Metabolic Networks and Pathways, Middle Aged, Schizophrenia, Young Adult, LifeLines Cohort Study, CHARGE Inflammation Working Group, C-reactive protein, DEPICT, Mendelian randomization, coronary artery disease, genome-wide association study, inflammation, inflammatory disorders, schizophrenia, system biology, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10-8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.

Published
2018

13. GWAS of epigenetic aging rates in blood reveals a critical role for TERT.

Author

Lu, Ake T, Xue, Luting, Salfati, Elias L, Chen, Brian H, Ferrucci, Luigi, Levy, Daniel, Joehanes, Roby, Murabito, Joanne M, Kiel, Douglas P, Tsai, Pei-Chien, Yet, Idil, Bell, Jordana T, Mangino, Massimo, Tanaka, Toshiko, McRae, Allan F, Marioni, Riccardo E, Visscher, Peter M, Wray, Naomi R, Deary, Ian J, Levine, Morgan E, Quach, Austin, Assimes, Themistocles, Tsao, Philip S, Absher, Devin, Stewart, James D, Li, Yun, Reiner, Alex P, Hou, Lifang, Baccarelli, Andrea A, Whitsel, Eric A, Aviv, Abraham, Cardona, Alexia, Day, Felix R, Wareham, Nicholas J, Perry, John RB, Ong, Ken K, Raj, Kenneth, Lunetta, Kathryn L, and Horvath, Steve

Subjects
Leukocytes, Cells, Cultured, Telomere, Fibroblasts, Humans, Telomerase, DNA Methylation, Epigenesis, Genetic, CpG Islands, Aging, Menopause, Menarche, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Female, Male, Genome-Wide Association Study, Young Adult, Mendelian Randomization Analysis, Cells, Cultured, Epigenesis, Genetic, and over
Abstract

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9907 individuals, we find gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in three loci associated with extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggests causal influences of menarche and menopause on IEAA and lipoproteins on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) paradoxically confer higher IEAA (P

Published
2018

14. ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals

Author

Bihlmeyer, Nathan A, Brody, Jennifer A, Smith, Albert Vernon, Warren, Helen R, Lin, Honghuang, Isaacs, Aaron, Liu, Ching-Ti, Marten, Jonathan, Radmanesh, Farid, Hall, Leanne M, Grarup, Niels, Mei, Hao, Müller-Nurasyid, Martina, Huffman, Jennifer E, Verweij, Niek, Guo, Xiuqing, Yao, Jie, Li-Gao, Ruifang, van den Berg, Marten, Weiss, Stefan, Prins, Bram P, van Setten, Jessica, Haessler, Jeffrey, Lyytikäinen, Leo-Pekka, Li, Man, Alonso, Alvaro, Soliman, Elsayed Z, Bis, Joshua C, Austin, Tom, Chen, Yii-Der Ida, Psaty, Bruce M, Harrris, Tamara B, Launer, Lenore J, Padmanabhan, Sandosh, Dominiczak, Anna, Huang, Paul L, Xie, Zhijun, Ellinor, Patrick T, Kors, Jan A, Campbell, Archie, Murray, Alison D, Nelson, Christopher P, Tobin, Martin D, Bork-Jensen, Jette, Hansen, Torben, Pedersen, Oluf, Linneberg, Allan, Sinner, Moritz F, Peters, Annette, Waldenberger, Melanie, Meitinger, Thomas, Perz, Siegfried, Kolcic, Ivana, Rudan, Igor, de Boer, Rudolf A, van der Meer, Peter, Lin, Henry J, Taylor, Kent D, de Mutsert, Renée, Trompet, Stella, Jukema, J Wouter, Maan, Arie C, Stricker, Bruno HC, Rivadeneira, Fernando, Uitterlinden, André, Völker, Uwe, Homuth, Georg, Völzke, Henry, Felix, Stephan B, Mangino, Massimo, Spector, Timothy D, Bots, Michiel L, Perez, Marco, Raitakari, Olli T, Kähönen, Mika, Mononen, Nina, Gudnason, Vilmundur, Munroe, Patricia B, Lubitz, Steven A, van Duijn, Cornelia M, Newton-Cheh, Christopher H, Hayward, Caroline, Rosand, Jonathan, Samani, Nilesh J, Kanters, Jørgen K, Wilson, James G, Kääb, Stefan, Polasek, Ozren, van der Harst, Pim, Heckbert, Susan R, Rotter, Jerome I, Mook-Kanamori, Dennis O, Eijgelsheim, Mark, Dörr, Marcus, Jamshidi, Yalda, Asselbergs, Folkert W, Kooperberg, Charles, Lehtimäki, Terho, Arking, Dan E, and Sotoodehnia, Nona

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease, Prevention, Genetics, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Antiporters, DNA-Binding Proteins, Electrocardiography, Exome, Genome-Wide Association Study, Humans, Long QT Syndrome, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Receptors, Calcium-Sensing, Transcription Factors, arrhythmias, cardiac, death, sudden, cardiac, genetics, genome, humans, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract

BackgroundQT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.Methods and resultsWe performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.ConclusionsOur analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest.

Published
2018

15. Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness.

Author

Willems, Sara M, Wright, Daniel J, Day, Felix R, Trajanoska, Katerina, Joshi, Peter K, Morris, John A, Matteini, Amy M, Garton, Fleur C, Grarup, Niels, Oskolkov, Nikolay, Thalamuthu, Anbupalam, Mangino, Massimo, Liu, Jun, Demirkan, Ayse, Lek, Monkol, Xu, Liwen, Wang, Guan, Oldmeadow, Christopher, Gaulton, Kyle J, Lotta, Luca A, Miyamoto-Mikami, Eri, Rivas, Manuel A, White, Tom, Loh, Po-Ru, Aadahl, Mette, Amin, Najaf, Attia, John R, Austin, Krista, Benyamin, Beben, Brage, Søren, Cheng, Yu-Ching, Cięszczyk, Paweł, Derave, Wim, Eriksson, Karl-Fredrik, Eynon, Nir, Linneberg, Allan, Lucia, Alejandro, Massidda, Myosotis, Mitchell, Braxton D, Miyachi, Motohiko, Murakami, Haruka, Padmanabhan, Sandosh, Pandey, Ashutosh, Papadimitriou, Ioannis, Rajpal, Deepak K, Sale, Craig, Schnurr, Theresia M, Sessa, Francesco, Shrine, Nick, Tobin, Martin D, Varley, Ian, Wain, Louise V, Wray, Naomi R, Lindgren, Cecilia M, MacArthur, Daniel G, Waterworth, Dawn M, McCarthy, Mark I, Pedersen, Oluf, Khaw, Kay-Tee, Kiel, Douglas P, GEFOS Any-Type of Fracture Consortium, Pitsiladis, Yannis, Fuku, Noriyuki, Franks, Paul W, North, Kathryn N, van Duijn, Cornelia M, Mather, Karen A, Hansen, Torben, Hansson, Ola, Spector, Tim, Murabito, Joanne M, Richards, J Brent, Rivadeneira, Fernando, Langenberg, Claudia, Perry, John RB, Wareham, Nick J, and Scott, Robert A

Subjects
GEFOS Any-Type of Fracture Consortium, Hand, Humans, Actins, Transforming Growth Factor alpha, Membrane Proteins, Neoplasm Proteins, Nuclear Proteins, Repressor Proteins, Hand Strength, Cohort Studies, Genetics, Population, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Genetic Loci, United Kingdom, Prevention, Genetics, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Musculoskeletal
Abstract

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P

Published
2017

16. A Low-Frequency Inactivating Akt2 Variant Enriched in the Finnish Population is Associated With Fasting Insulin Levels and Type 2 Diabetes Risk.

Author

Manning, Alisa, Highland, Heather M, Gasser, Jessica, Sim, Xueling, Tukiainen, Taru, Fontanillas, Pierre, Grarup, Niels, Rivas, Manuel A, Mahajan, Anubha, Locke, Adam E, Cingolani, Pablo, Pers, Tune H, Viñuela, Ana, Brown, Andrew A, Wu, Ying, Flannick, Jason, Fuchsberger, Christian, Gamazon, Eric R, Gaulton, Kyle J, Im, Hae Kyung, Teslovich, Tanya M, Blackwell, Thomas W, Bork-Jensen, Jette, Burtt, Noël P, Chen, Yuhui, Green, Todd, Hartl, Christopher, Kang, Hyun Min, Kumar, Ashish, Ladenvall, Claes, Ma, Clement, Moutsianas, Loukas, Pearson, Richard D, Perry, John RB, Rayner, N William, Robertson, Neil R, Scott, Laura J, van de Bunt, Martijn, Eriksson, Johan G, Jula, Antti, Koskinen, Seppo, Lehtimäki, Terho, Palotie, Aarno, Raitakari, Olli T, Jacobs, Suzanne BR, Wessel, Jennifer, Chu, Audrey Y, Scott, Robert A, Goodarzi, Mark O, Blancher, Christine, Buck, Gemma, Buck, David, Chines, Peter S, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Trakalo, Joseph, Banks, Eric, Carey, Jason, Carneiro, Mauricio O, DePristo, Mark, Farjoun, Yossi, Fennell, Timothy, Goldstein, Jacqueline I, Grant, George, Hrabé de Angelis, Martin, Maguire, Jared, Neale, Benjamin M, Poplin, Ryan, Purcell, Shaun, Schwarzmayr, Thomas, Shakir, Khalid, Smith, Joshua D, Strom, Tim M, Wieland, Thomas, Lindstrom, Jaana, Brandslund, Ivan, Christensen, Cramer, Surdulescu, Gabriela L, Lakka, Timo A, Doney, Alex SF, Nilsson, Peter, Wareham, Nicholas J, Langenberg, Claudia, Varga, Tibor V, Franks, Paul W, Rolandsson, Olov, Rosengren, Anders H, and Farook, Vidya S

Subjects
Genetics, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Black or African American, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Fasting, Finland, Gene Frequency, Genetic Predisposition to Disease, Genotype, Hispanic or Latino, Humans, Insulin, Insulin Resistance, Odds Ratio, Proto-Oncogene Proteins c-akt, White People, Medical and Health Sciences, Endocrinology & Metabolism
Abstract

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Published
2017

17. Discovery of novel heart rate-associated loci using the Exome Chip

Author

van den Berg, Marten E, Warren, Helen R, Cabrera, Claudia P, Verweij, Niek, Mifsud, Borbala, Haessler, Jeffrey, Bihlmeyer, Nathan A, Fu, Yi-Ping, Weiss, Stefan, Lin, Henry J, Grarup, Niels, Li-Gao, Ruifang, Pistis, Giorgio, Shah, Nabi, Brody, Jennifer A, Müller-Nurasyid, Martina, Lin, Honghuang, Mei, Hao, Smith, Albert V, Lyytikäinen, Leo-Pekka, Hall, Leanne M, van Setten, Jessica, Trompet, Stella, Prins, Bram P, Isaacs, Aaron, Radmanesh, Farid, Marten, Jonathan, Entwistle, Aiman, Kors, Jan A, Silva, Claudia T, Alonso, Alvaro, Bis, Joshua C, de Boer, Rudolf, de Haan, Hugoline G, de Mutsert, Renée, Dedoussis, George, Dominiczak, Anna F, Doney, Alex SF, Ellinor, Patrick T, Eppinga, Ruben N, Felix, Stephan B, Guo, Xiuqing, Hagemeijer, Yanick, Hansen, Torben, Harris, Tamara B, Heckbert, Susan R, Huang, Paul L, Hwang, Shih-Jen, Kähönen, Mika, Kanters, Jørgen K, Kolcic, Ivana, Launer, Lenore J, Li, Man, Yao, Jie, Linneberg, Allan, Liu, Simin, Macfarlane, Peter W, Mangino, Massimo, Morris, Andrew D, Mulas, Antonella, Murray, Alison D, Nelson, Christopher P, Orrú, Marco, Padmanabhan, Sandosh, Peters, Annette, Porteous, David J, Poulter, Neil, Psaty, Bruce M, Qi, Lihong, Raitakari, Olli T, Rivadeneira, Fernando, Roselli, Carolina, Rudan, Igor, Sattar, Naveed, Sever, Peter, Sinner, Moritz F, Soliman, Elsayed Z, Spector, Timothy D, Stanton, Alice V, Stirrups, Kathleen E, Taylor, Kent D, Tobin, Martin D, Uitterlinden, André, Vaartjes, Ilonca, Hoes, Arno W, van der Meer, Peter, Völker, Uwe, Waldenberger, Melanie, Xie, Zhijun, Zoledziewska, Magdalena, Tinker, Andrew, Polasek, Ozren, Rosand, Jonathan, Jamshidi, Yalda, van Duijn, Cornelia M, Zeggini, Eleftheria, Jukema, J Wouter, Asselbergs, Folkert W, Samani, Nilesh J, and Lehtimäki, Terho

Subjects
Biological Sciences, Genetics, Human Genome, Biotechnology, Heart Disease, Prevention, Cardiovascular, Stem Cell Research, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Adult, Alleles, Exome, Female, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Heart Rate, Humans, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Risk Factors, White People, Medical and Health Sciences, Genetics & Heredity
Abstract

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies.

Published
2017

18. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Author

Day, Felix R, Thompson, Deborah J, Helgason, Hannes, Chasman, Daniel I, Finucane, Hilary, Sulem, Patrick, Ruth, Katherine S, Whalen, Sean, Sarkar, Abhishek K, Albrecht, Eva, Altmaier, Elisabeth, Amini, Marzyeh, Barbieri, Caterina M, Boutin, Thibaud, Campbell, Archie, Demerath, Ellen, Giri, Ayush, He, Chunyan, Hottenga, Jouke J, Karlsson, Robert, Kolcic, Ivana, Loh, Po-Ru, Lunetta, Kathryn L, Mangino, Massimo, Marco, Brumat, McMahon, George, Medland, Sarah E, Nolte, Ilja M, Noordam, Raymond, Nutile, Teresa, Paternoster, Lavinia, Perjakova, Natalia, Porcu, Eleonora, Rose, Lynda M, Schraut, Katharina E, Segrè, Ayellet V, Smith, Albert V, Stolk, Lisette, Teumer, Alexander, Andrulis, Irene L, Bandinelli, Stefania, Beckmann, Matthias W, Benitez, Javier, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Brand, Judith S, Brauch, Hiltrud, Brenner, Hermann, Broer, Linda, Brüning, Thomas, Buring, Julie E, Campbell, Harry, Catamo, Eulalia, Chanock, Stephen, Chenevix-Trench, Georgia, Corre, Tanguy, Couch, Fergus J, Cousminer, Diana L, Cox, Angela, Crisponi, Laura, Czene, Kamila, Davey Smith, George, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Dennis, Joe, Devilee, Peter, Dos-Santos-Silva, Isabel, Dunning, Alison M, Eriksson, Johan G, Fasching, Peter A, Fernández-Rhodes, Lindsay, Ferrucci, Luigi, Flesch-Janys, Dieter, Franke, Lude, Gabrielson, Marike, Gandin, Ilaria, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Guénel, Pascal, Hall, Per, Hallberg, Emily, Hamann, Ute, Harris, Tamara B, Hartman, Catharina A, Heiss, Gerardo, Hooning, Maartje J, Hopper, John L, Hu, Frank, Hunter, David J, Ikram, M Arfan, Im, Hae Kyung, Järvelin, Marjo-Riitta, Joshi, Peter K, Karasik, David, and Kellis, Manolis

Subjects
LifeLines Cohort Study, InterAct Consortium, kConFab/AOCS Investigators, Endometrial Cancer Association Consortium, Ovarian Cancer Association Consortium, PRACTICAL consortium, Humans, Neoplasms, Genetic Predisposition to Disease, Ubiquitin-Protein Ligases, Intercellular Signaling Peptides and Proteins, Calcium-Binding Proteins, Ribonucleoproteins, Membrane Proteins, Body Mass Index, Risk Factors, Age Factors, Genomic Imprinting, Puberty, Menarche, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Databases, Genetic, Adolescent, Female, Male, Genome-Wide Association Study, Aging, Breast Cancer, Biotechnology, Cancer, Human Genome, Genetics, Prostate Cancer, Urologic Diseases, 2.1 Biological and endogenous factors, Aetiology, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10-8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

Published
2017

19. Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study

Author

Haycock, Philip C, Burgess, Stephen, Nounu, Aayah, Zheng, Jie, Okoli, George N, Bowden, Jack, Wade, Kaitlin Hazel, Timpson, Nicholas J, Evans, David M, Willeit, Peter, Aviv, Abraham, Gaunt, Tom R, Hemani, Gibran, Mangino, Massimo, Ellis, Hayley Patricia, Kurian, Kathreena M, Pooley, Karen A, Eeles, Rosalind A, Lee, Jeffrey E, Fang, Shenying, Chen, Wei V, Law, Matthew H, Bowdler, Lisa M, Iles, Mark M, Yang, Qiong, Worrall, Bradford B, Markus, Hugh Stephen, Hung, Rayjean J, Amos, Chris I, Spurdle, Amanda B, Thompson, Deborah J, O’Mara, Tracy A, Wolpin, Brian, Amundadottir, Laufey, Stolzenberg-Solomon, Rachael, Trichopoulou, Antonia, Onland-Moret, N Charlotte, Lund, Eiliv, Duell, Eric J, Canzian, Federico, Severi, Gianluca, Overvad, Kim, Gunter, Marc J, Tumino, Rosario, Svenson, Ulrika, van Rij, Andre, Baas, Annette F, Bown, Matthew J, Samani, Nilesh J, van t’Hof, Femke NG, Tromp, Gerard, Jones, Gregory T, Kuivaniemi, Helena, Elmore, James R, Johansson, Mattias, Mckay, James, Scelo, Ghislaine, Carreras-Torres, Robert, Gaborieau, Valerie, Brennan, Paul, Bracci, Paige M, Neale, Rachel E, Olson, Sara H, Gallinger, Steven, Li, Donghui, Petersen, Gloria M, Risch, Harvey A, Klein, Alison P, Han, Jiali, Abnet, Christian C, Freedman, Neal D, Taylor, Philip R, Maris, John M, Aben, Katja K, Kiemeney, Lambertus A, Vermeulen, Sita H, Wiencke, John K, Walsh, Kyle M, Wrensch, Margaret, Rice, Terri, Turnbull, Clare, Litchfield, Kevin, Paternoster, Lavinia, Standl, Marie, Abecasis, Gonçalo R, SanGiovanni, John Paul, Li, Yong, Mijatovic, Vladan, Sapkota, Yadav, Low, Siew-Kee, Zondervan, Krina T, Montgomery, Grant W, Nyholt, Dale R, van Heel, David A, Hunt, Karen, Arking, Dan E, Ashar, Foram N, Sotoodehnia, Nona, Woo, Daniel, and Rosand, Jonathan

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Clinical Research, Cancer, Prevention, Genetics, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Aged, 80 and over, Cardiovascular Diseases, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Germ-Line Mutation, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Neoplasms, Polymorphism, Single Nucleotide, Risk Assessment, Telomere, Telomere Homeostasis, Telomeres Mendelian Randomization Collaboration, Public Health and Health Services, Oncology and carcinogenesis
Abstract

ImportanceThe causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.ObjectiveTo conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.Data sourcesGenomewide association studies (GWAS) published up to January 15, 2015.Study selectionGWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.Data extraction and synthesisSummary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.Main outcomes and measuresOdds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.ResultsSummary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).Conclusions and relevanceIt is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Published
2017

20. Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study.

Author

Telomeres Mendelian Randomization Collaboration, Haycock, Philip C, Burgess, Stephen, Nounu, Aayah, Zheng, Jie, Okoli, George N, Bowden, Jack, Wade, Kaitlin Hazel, Timpson, Nicholas J, Evans, David M, Willeit, Peter, Aviv, Abraham, Gaunt, Tom R, Hemani, Gibran, Mangino, Massimo, Ellis, Hayley Patricia, Kurian, Kathreena M, Pooley, Karen A, Eeles, Rosalind A, Lee, Jeffrey E, Fang, Shenying, Chen, Wei V, Law, Matthew H, Bowdler, Lisa M, Iles, Mark M, Yang, Qiong, Worrall, Bradford B, Markus, Hugh Stephen, Hung, Rayjean J, Amos, Chris I, Spurdle, Amanda B, Thompson, Deborah J, O'Mara, Tracy A, Wolpin, Brian, Amundadottir, Laufey, Stolzenberg-Solomon, Rachael, Trichopoulou, Antonia, Onland-Moret, N Charlotte, Lund, Eiliv, Duell, Eric J, Canzian, Federico, Severi, Gianluca, Overvad, Kim, Gunter, Marc J, Tumino, Rosario, Svenson, Ulrika, van Rij, Andre, Baas, Annette F, Bown, Matthew J, Samani, Nilesh J, van t'Hof, Femke NG, Tromp, Gerard, Jones, Gregory T, Kuivaniemi, Helena, Elmore, James R, Johansson, Mattias, Mckay, James, Scelo, Ghislaine, Carreras-Torres, Robert, Gaborieau, Valerie, Brennan, Paul, Bracci, Paige M, Neale, Rachel E, Olson, Sara H, Gallinger, Steven, Li, Donghui, Petersen, Gloria M, Risch, Harvey A, Klein, Alison P, Han, Jiali, Abnet, Christian C, Freedman, Neal D, Taylor, Philip R, Maris, John M, Aben, Katja K, Kiemeney, Lambertus A, Vermeulen, Sita H, Wiencke, John K, Walsh, Kyle M, Wrensch, Margaret, Rice, Terri, Turnbull, Clare, Litchfield, Kevin, Paternoster, Lavinia, Standl, Marie, Abecasis, Gonçalo R, SanGiovanni, John Paul, Li, Yong, Mijatovic, Vladan, Sapkota, Yadav, Low, Siew-Kee, Zondervan, Krina T, Montgomery, Grant W, Nyholt, Dale R, van Heel, David A, Hunt, Karen, Arking, Dan E, Ashar, Foram N, Sotoodehnia, Nona, and Woo, Daniel

Subjects
Telomeres Mendelian Randomization Collaboration, Telomere, Humans, Neoplasms, Cardiovascular Diseases, Genetic Predisposition to Disease, Risk Assessment, Germ-Line Mutation, Polymorphism, Single Nucleotide, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genome-Wide Association Study, Mendelian Randomization Analysis, Telomere Homeostasis, Polymorphism, Single Nucleotide, and over, Prevention, Clinical Research, Cancer, Genetics, Rare Diseases, 2.1 Biological and endogenous factors, Oncology and Carcinogenesis, Public Health and Health Services
Abstract

ImportanceThe causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain owing to the susceptibility of observational studies to confounding and reverse causation.ObjectiveTo conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases.Data sourcesGenomewide association studies (GWAS) published up to January 15, 2015.Study selectionGWAS of noncommunicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of preexisting diseases. Of 163 GWAS of noncommunicable diseases identified, summary data from 103 were available.Data extraction and synthesisSummary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population.Main outcomes and measuresOdds ratios (ORs) and 95% confidence intervals (CIs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation.ResultsSummary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420 081 cases (median cases, 2526 per disease) and 1 093 105 controls (median, 6789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations (ORs [95% CIs] per 1-SD change in genetically increased telomere length) were observed for glioma, 5.27 (3.15-8.81); serous low-malignant-potential ovarian cancer, 4.35 (2.39-7.94); lung adenocarcinoma, 3.19 (2.40-4.22); neuroblastoma, 2.98 (1.92-4.62); bladder cancer, 2.19 (1.32-3.66); melanoma, 1.87 (1.55-2.26); testicular cancer, 1.76 (1.02-3.04); kidney cancer, 1.55 (1.08-2.23); and endometrial cancer, 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division. There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic, and other non-neoplastic diseases, except for coronary heart disease (OR, 0.78 [95% CI, 0.67-0.90]), abdominal aortic aneurysm (OR, 0.63 [95% CI, 0.49-0.81]), celiac disease (OR, 0.42 [95% CI, 0.28-0.61]) and interstitial lung disease (OR, 0.09 [95% CI, 0.05-0.15]).Conclusions and relevanceIt is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.

Published
2017

21. Comparison of HapMap and 1000 Genomes Reference Panels in a Large-Scale Genome-Wide Association Study

Author

de Vries, Paul S, Sabater-Lleal, Maria, Chasman, Daniel I, Trompet, Stella, Ahluwalia, Tarunveer S, Teumer, Alexander, Kleber, Marcus E, Chen, Ming-Huei, Wang, Jie Jin, Attia, John R, Marioni, Riccardo E, Steri, Maristella, Weng, Lu-Chen, Pool, Rene, Grossmann, Vera, Brody, Jennifer A, Venturini, Cristina, Tanaka, Toshiko, Rose, Lynda M, Oldmeadow, Christopher, Mazur, Johanna, Basu, Saonli, Frånberg, Mattias, Yang, Qiong, Ligthart, Symen, Hottenga, Jouke J, Rumley, Ann, Mulas, Antonella, de Craen, Anton JM, Grotevendt, Anne, Taylor, Kent D, Delgado, Graciela E, Kifley, Annette, Lopez, Lorna M, Berentzen, Tina L, Mangino, Massimo, Bandinelli, Stefania, Morrison, Alanna C, Hamsten, Anders, Tofler, Geoffrey, de Maat, Moniek PM, Draisma, Harmen HM, Lowe, Gordon D, Zoledziewska, Magdalena, Sattar, Naveed, Lackner, Karl J, Völker, Uwe, McKnight, Barbara, Huang, Jie, Holliday, Elizabeth G, McEvoy, Mark A, Starr, John M, Hysi, Pirro G, Hernandez, Dena G, Guan, Weihua, Rivadeneira, Fernando, McArdle, Wendy L, Slagboom, P Eline, Zeller, Tanja, Psaty, Bruce M, Uitterlinden, André G, de Geus, Eco JC, Stott, David J, Binder, Harald, Hofman, Albert, Franco, Oscar H, Rotter, Jerome I, Ferrucci, Luigi, Spector, Tim D, Deary, Ian J, März, Winfried, Greinacher, Andreas, Wild, Philipp S, Cucca, Francesco, Boomsma, Dorret I, Watkins, Hugh, Tang, Weihong, Ridker, Paul M, Jukema, Jan W, Scott, Rodney J, Mitchell, Paul, Hansen, Torben, O'Donnell, Christopher J, Smith, Nicholas L, Strachan, David P, and Dehghan, Abbas

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Genome-Wide Association Study, HapMap Project, Humans, General Science & Technology
Abstract

An increasing number of genome-wide association (GWA) studies are now using the higher resolution 1000 Genomes Project reference panel (1000G) for imputation, with the expectation that 1000G imputation will lead to the discovery of additional associated loci when compared to HapMap imputation. In order to assess the improvement of 1000G over HapMap imputation in identifying associated loci, we compared the results of GWA studies of circulating fibrinogen based on the two reference panels. Using both HapMap and 1000G imputation we performed a meta-analysis of 22 studies comprising the same 91,953 individuals. We identified six additional signals using 1000G imputation, while 29 loci were associated using both HapMap and 1000G imputation. One locus identified using HapMap imputation was not significant using 1000G imputation. The genome-wide significance threshold of 5×10-8 is based on the number of independent statistical tests using HapMap imputation, and 1000G imputation may lead to further independent tests that should be corrected for. When using a stricter Bonferroni correction for the 1000G GWA study (P-value < 2.5×10-8), the number of loci significant only using HapMap imputation increased to 4 while the number of loci significant only using 1000G decreased to 5. In conclusion, 1000G imputation enabled the identification of 20% more loci than HapMap imputation, although the advantage of 1000G imputation became less clear when a stricter Bonferroni correction was used. More generally, our results provide insights that are applicable to the implementation of other dense reference panels that are under development.

Published
2017

22. KLB is associated with alcohol drinking, and its gene product β-Klotho is necessary for FGF21 regulation of alcohol preference

Author

Schumann, Gunter, Liu, Chunyu, O'Reilly, Paul, Gao, He, Song, Parkyong, Xu, Bing, Ruggeri, Barbara, Amin, Najaf, Jia, Tianye, Preis, Sarah, Segura Lepe, Marcelo, Akira, Shizuo, Barbieri, Caterina, Baumeister, Sebastian, Cauchi, Stephane, Clarke, Toni-Kim, Enroth, Stefan, Fischer, Krista, Hällfors, Jenni, Harris, Sarah E, Hieber, Saskia, Hofer, Edith, Hottenga, Jouke-Jan, Johansson, Åsa, Joshi, Peter K, Kaartinen, Niina, Laitinen, Jaana, Lemaitre, Rozenn, Loukola, Anu, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Mangino, Massimo, Manichaikul, Ani, Mbarek, Hamdi, Milaneschi, Yuri, Moayyeri, Alireza, Mukamal, Kenneth, Nelson, Christopher, Nettleton, Jennifer, Partinen, Eemil, Rawal, Rajesh, Robino, Antonietta, Rose, Lynda, Sala, Cinzia, Satoh, Takashi, Schmidt, Reinhold, Schraut, Katharina, Scott, Robert, Smith, Albert Vernon, Starr, John M, Teumer, Alexander, Trompet, Stella, Uitterlinden, André G, Venturini, Cristina, Vergnaud, Anne-Claire, Verweij, Niek, Vitart, Veronique, Vuckovic, Dragana, Wedenoja, Juho, Yengo, Loic, Yu, Bing, Zhang, Weihua, Zhao, Jing Hua, Boomsma, Dorret I, Chambers, John, Chasman, Daniel I, Daniela, Toniolo, de Geus, Eco, Deary, Ian, Eriksson, Johan G, Esko, Tõnu, Eulenburg, Volker, Franco, Oscar H, Froguel, Philippe, Gieger, Christian, Grabe, Hans J, Gudnason, Vilmundur, Gyllensten, Ulf, Harris, Tamara B, Hartikainen, Anna-Liisa, Heath, Andrew C, Hocking, Lynne, Hofman, Albert, Huth, Cornelia, Jarvelin, Marjo-Riitta, Jukema, J Wouter, Kaprio, Jaakko, Kooner, Jaspal S, Kutalik, Zoltan, Lahti, Jari, Langenberg, Claudia, Lehtimäki, Terho, Liu, Yongmei, Madden, Pamela AF, Martin, Nicholas, Morrison, Alanna, Penninx, Brenda, Pirastu, Nicola, Psaty, Bruce, and Raitakari, Olli

Subjects
Underage Drinking, Genetics, Alcoholism, Alcohol Use and Health, Neurosciences, Substance Misuse, Pediatric, Underpinning research, 1.1 Normal biological development and functioning, Stroke, Cardiovascular, Cancer, Oral and gastrointestinal, Good Health and Well Being, Alcohol Drinking, Animals, Behavior, Animal, Brain, Emotions, Female, Fibroblast Growth Factors, Genome-Wide Association Study, Humans, Klotho Proteins, Liver, Male, Membrane Proteins, Mice, Mice, 129 Strain, Mice, Inbred C57BL, Mice, Knockout, Polymorphism, Single Nucleotide, alcohol consumption, human, beta-Klotho, FGF21, mouse model, β-Klotho
Abstract

Excessive alcohol consumption is a major public health problem worldwide. Although drinking habits are known to be inherited, few genes have been identified that are robustly linked to alcohol drinking. We conducted a genome-wide association metaanalysis and replication study among >105,000 individuals of European ancestry and identified β-Klotho (KLB) as a locus associated with alcohol consumption (rs11940694; P = 9.2 × 10-12). β-Klotho is an obligate coreceptor for the hormone FGF21, which is secreted from the liver and implicated in macronutrient preference in humans. We show that brain-specific β-Klotho KO mice have an increased alcohol preference and that FGF21 inhibits alcohol drinking by acting on the brain. These data suggest that a liver-brain endocrine axis may play an important role in the regulation of alcohol drinking behavior and provide a unique pharmacologic target for reducing alcohol consumption.

Published
2016

23. Heritable components of the human fecal microbiome are associated with visceral fat

Author

Beaumont, Michelle, Goodrich, Julia K, Jackson, Matthew A, Yet, Idil, Davenport, Emily R, Vieira-Silva, Sara, Debelius, Justine, Pallister, Tess, Mangino, Massimo, Raes, Jeroen, Knight, Rob, Clark, Andrew G, Ley, Ruth E, Spector, Tim D, and Bell, Jordana T

Subjects
Human Genome, Aging, Genetics, Clinical Research, Obesity, Nutrition, Prevention, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Oral and gastrointestinal, Metabolic and endocrine, Cancer, Stroke, Fecal microbiome, Visceral fat, Heritability, Genetic association, Twins, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

BackgroundVariation in the human fecal microbiota has previously been associated with body mass index (BMI). Although obesity is a global health burden, the accumulation of abdominal visceral fat is the specific cardio-metabolic disease risk factor. Here, we explore links between the fecal microbiota and abdominal adiposity using body composition as measured by dual-energy X-ray absorptiometry in a large sample of twins from the TwinsUK cohort, comparing fecal 16S rRNA diversity profiles with six adiposity measures.ResultsWe profile six adiposity measures in 3666 twins and estimate their heritability, finding novel evidence for strong genetic effects underlying visceral fat and android/gynoid ratio. We confirm the association of lower diversity of the fecal microbiome with obesity and adiposity measures, and then compare the association between fecal microbial composition and the adiposity phenotypes in a discovery subsample of twins. We identify associations between the relative abundances of fecal microbial operational taxonomic units (OTUs) and abdominal adiposity measures. Most of these results involve visceral fat associations, with the strongest associations between visceral fat and Oscillospira members. Using BMI as a surrogate phenotype, we pursue replication in independent samples from three population-based cohorts including American Gut, Flemish Gut Flora Project and the extended TwinsUK cohort. Meta-analyses across the replication samples indicate that 8 OTUs replicate at a stringent threshold across all cohorts, while 49 OTUs achieve nominal significance in at least one replication sample. Heritability analysis of the adiposity-associated microbial OTUs prompted us to assess host genetic-microbe interactions at obesity-associated human candidate loci. We observe significant associations of adiposity-OTU abundances with host genetic variants in the FHIT, TDRG1 and ELAVL4 genes, suggesting a potential role for host genes to mediate the link between the fecal microbiome and obesity.ConclusionsOur results provide novel insights into the role of the fecal microbiota in cardio-metabolic disease with clear potential for prevention and novel therapies.

Published
2016

24. GWAS analysis of handgrip and lower body strength in older adults in the CHARGE consortium.

Author

Matteini, Amy M, Tanaka, Toshiko, Karasik, David, Atzmon, Gil, Chou, Wen-Chi, Eicher, John D, Johnson, Andrew D, Arnold, Alice M, Callisaya, Michele L, Davies, Gail, Evans, Daniel S, Holtfreter, Birte, Lohman, Kurt, Lunetta, Kathryn L, Mangino, Massimo, Smith, Albert V, Smith, Jennifer A, Teumer, Alexander, Yu, Lei, Arking, Dan E, Buchman, Aron S, Chibinik, Lori B, De Jager, Philip L, Evans, Denis A, Faul, Jessica D, Garcia, Melissa E, Gillham-Nasenya, Irina, Gudnason, Vilmundur, Hofman, Albert, Hsu, Yi-Hsiang, Ittermann, Till, Lahousse, Lies, Liewald, David C, Liu, Yongmei, Lopez, Lorna, Rivadeneira, Fernando, Rotter, Jerome I, Siggeirsdottir, Kristin, Starr, John M, Thomson, Russell, Tranah, Gregory J, Uitterlinden, André G, Völker, Uwe, Völzke, Henry, Weir, David R, Yaffe, Kristine, Zhao, Wei, Zhuang, Wei Vivian, Zmuda, Joseph M, Bennett, David A, Cummings, Steven R, Deary, Ian J, Ferrucci, Luigi, Harris, Tamara B, Kardia, Sharon LR, Kocher, Thomas, Kritchevsky, Stephen B, Psaty, Bruce M, Seshadri, Sudha, Spector, Timothy D, Srikanth, Velandai K, Windham, B Gwen, Zillikens, M Carola, Newman, Anne B, Walston, Jeremy D, Kiel, Douglas P, and Murabito, Joanne M

Subjects
Humans, Hand Strength, Cohort Studies, Reproducibility of Results, Chromatin Immunoprecipitation, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Adult, Aged, Muscle Strength, Genome-Wide Association Study, Molecular Sequence Annotation, SNP, aging, genomewide association, meta-analysis, muscle strength, older adults, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Developmental Biology, Medical and Health Sciences, Biological Sciences
Abstract

Decline in muscle strength with aging is an important predictor of health trajectory in the elderly. Several factors, including genetics, are proposed contributors to variability in muscle strength. To identify genetic contributors to muscle strength, a meta-analysis of genomewide association studies of handgrip was conducted. Grip strength was measured using a handheld dynamometer in 27 581 individuals of European descent over 65 years of age from 14 cohort studies. Genomewide association analysis was conducted on ~2.7 million imputed and genotyped variants (SNPs). Replication of the most significant findings was conducted using data from 6393 individuals from three cohorts. GWAS of lower body strength was also characterized in a subset of cohorts. Two genomewide significant (P-value< 5 × 10(-8) ) and 39 suggestive (P-value< 5 × 10(-5) ) associations were observed from meta-analysis of the discovery cohorts. After meta-analysis with replication cohorts, genomewide significant association was observed for rs752045 on chromosome 8 (β = 0.47, SE = 0.08, P-value = 5.20 × 10(-10) ). This SNP is mapped to an intergenic region and is located within an accessible chromatin region (DNase hypersensitivity site) in skeletal muscle myotubes differentiated from the human skeletal muscle myoblasts cell line. This locus alters a binding motif of the CCAAT/enhancer-binding protein-β (CEBPB) that is implicated in muscle repair mechanisms. GWAS of lower body strength did not yield significant results. A common genetic variant in a chromosomal region that regulates myotube differentiation and muscle repair may contribute to variability in grip strength in the elderly. Further studies are needed to uncover the mechanisms that link this genetic variant with muscle strength.

Published
2016

25. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, Aysu, Beauchamp, Jonathan P, Fontana, Mark Alan, Lee, James J, Pers, Tune H, Rietveld, Cornelius A, Turley, Patrick, Chen, Guo-Bo, Emilsson, Valur, Meddens, S Fleur W, Oskarsson, Sven, Pickrell, Joseph K, Thom, Kevin, Timshel, Pascal, de Vlaming, Ronald, Abdellaoui, Abdel, Ahluwalia, Tarunveer S, Bacelis, Jonas, Baumbach, Clemens, Bjornsdottir, Gyda, Brandsma, Johannes H, Pina Concas, Maria, Derringer, Jaime, Furlotte, Nicholas A, Galesloot, Tessel E, Girotto, Giorgia, Gupta, Richa, Hall, Leanne M, Harris, Sarah E, Hofer, Edith, Horikoshi, Momoko, Huffman, Jennifer E, Kaasik, Kadri, Kalafati, Ioanna P, Karlsson, Robert, Kong, Augustine, Lahti, Jari, Lee, Sven J van der, deLeeuw, Christiaan, Lind, Penelope A, Lindgren, Karl-Oskar, Liu, Tian, Mangino, Massimo, Marten, Jonathan, Mihailov, Evelin, Miller, Michael B, van der Most, Peter J, Oldmeadow, Christopher, Payton, Antony, Pervjakova, Natalia, Peyrot, Wouter J, Qian, Yong, Raitakari, Olli, Rueedi, Rico, Salvi, Erika, Schmidt, Börge, Schraut, Katharina E, Shi, Jianxin, Smith, Albert V, Poot, Raymond A, St Pourcain, Beate, Teumer, Alexander, Thorleifsson, Gudmar, Verweij, Niek, Vuckovic, Dragana, Wellmann, Juergen, Westra, Harm-Jan, Yang, Jingyun, Zhao, Wei, Zhu, Zhihong, Alizadeh, Behrooz Z, Amin, Najaf, Bakshi, Andrew, Baumeister, Sebastian E, Biino, Ginevra, Bønnelykke, Klaus, Boyle, Patricia A, Campbell, Harry, Cappuccio, Francesco P, Davies, Gail, De Neve, Jan-Emmanuel, Deloukas, Panos, Demuth, Ilja, Ding, Jun, Eibich, Peter, Eisele, Lewin, Eklund, Niina, Evans, David M, Faul, Jessica D, Feitosa, Mary F, Forstner, Andreas J, Gandin, Ilaria, Gunnarsson, Bjarni, Halldórsson, Bjarni V, Harris, Tamara B, Heath, Andrew C, Hocking, Lynne J, Holliday, Elizabeth G, Homuth, Georg, and Horan, Michael A

Subjects
Biological Sciences, Genetics, Epidemiology, Health Sciences, Statistics, Mathematical Sciences, Human Genome, Clinical Research, Alzheimer Disease, Bipolar Disorder, Brain, Cognition, Computational Biology, Educational Status, Fetus, Gene Expression Regulation, Gene-Environment Interaction, Genome-Wide Association Study, Humans, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Schizophrenia, United Kingdom, LifeLines Cohort Study, General Science & Technology
Abstract

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Published
2016

26. Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Author

Kilpeläinen, Tuomas O, Carli, Jayne F Martin, Skowronski, Alicja A, Sun, Qi, Kriebel, Jennifer, Feitosa, Mary F, Hedman, Åsa K, Drong, Alexander W, Hayes, James E, Zhao, Jinghua, Pers, Tune H, Schick, Ursula, Grarup, Niels, Kutalik, Zoltán, Trompet, Stella, Mangino, Massimo, Kristiansson, Kati, Beekman, Marian, Lyytikäinen, Leo-Pekka, Eriksson, Joel, Henneman, Peter, Lahti, Jari, Tanaka, Toshiko, Luan, Jian'an, Del Greco M, Fabiola, Pasko, Dorota, Renström, Frida, Willems, Sara M, Mahajan, Anubha, Rose, Lynda M, Guo, Xiuqing, Liu, Yongmei, Kleber, Marcus E, Pérusse, Louis, Gaunt, Tom, Ahluwalia, Tarunveer S, Ju Sung, Yun, Ramos, Yolande F, Amin, Najaf, Amuzu, Antoinette, Barroso, Inês, Bellis, Claire, Blangero, John, Buckley, Brendan M, Böhringer, Stefan, I Chen, Yii-Der, de Craen, Anton JN, Crosslin, David R, Dale, Caroline E, Dastani, Zari, Day, Felix R, Deelen, Joris, Delgado, Graciela E, Demirkan, Ayse, Finucane, Francis M, Ford, Ian, Garcia, Melissa E, Gieger, Christian, Gustafsson, Stefan, Hallmans, Göran, Hankinson, Susan E, Havulinna, Aki S, Herder, Christian, Hernandez, Dena, Hicks, Andrew A, Hunter, David J, Illig, Thomas, Ingelsson, Erik, Ioan-Facsinay, Andreea, Jansson, John-Olov, Jenny, Nancy S, Jørgensen, Marit E, Jørgensen, Torben, Karlsson, Magnus, Koenig, Wolfgang, Kraft, Peter, Kwekkeboom, Joanneke, Laatikainen, Tiina, Ladwig, Karl-Heinz, LeDuc, Charles A, Lowe, Gordon, Lu, Yingchang, Marques-Vidal, Pedro, Meisinger, Christa, Menni, Cristina, Morris, Andrew P, Myers, Richard H, Männistö, Satu, Nalls, Mike A, Paternoster, Lavinia, Peters, Annette, Pradhan, Aruna D, Rankinen, Tuomo, Rasmussen-Torvik, Laura J, Rathmann, Wolfgang, Rice, Treva K, Brent Richards, J, Ridker, Paul M, Sattar, Naveed, and Savage, David B

Subjects
Adipose Tissue, Animals, Mice, Leptin, RNA, Messenger, Tissue Culture Techniques, Gene Expression Regulation, Male, Genome-Wide Association Study, Gene Knockdown Techniques, RNA, Messenger
Abstract

Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P

Published
2016

27. A meta-analysis of 120 246 individuals identifies 18 new loci for fibrinogen concentration

Author

de Vries, Paul S, Chasman, Daniel I, Sabater-Lleal, Maria, Chen, Ming-Huei, Huffman, Jennifer E, Steri, Maristella, Tang, Weihong, Teumer, Alexander, Marioni, Riccardo E, Grossmann, Vera, Hottenga, Jouke J, Trompet, Stella, Müller-Nurasyid, Martina, Zhao, Jing Hua, Brody, Jennifer A, Kleber, Marcus E, Guo, Xiuqing, Wang, Jie Jin, Auer, Paul L, Attia, John R, Yanek, Lisa R, Ahluwalia, Tarunveer S, Lahti, Jari, Venturini, Cristina, Tanaka, Toshiko, Bielak, Lawrence F, Joshi, Peter K, Rocanin-Arjo, Ares, Kolcic, Ivana, Navarro, Pau, Rose, Lynda M, Oldmeadow, Christopher, Riess, Helene, Mazur, Johanna, Basu, Saonli, Goel, Anuj, Yang, Qiong, Ghanbari, Mohsen, Willemsen, Gonneke, Rumley, Ann, Fiorillo, Edoardo, de Craen, Anton JM, Grotevendt, Anne, Scott, Robert, Taylor, Kent D, Delgado, Graciela E, Yao, Jie, Kifley, Annette, Kooperberg, Charles, Qayyum, Rehan, Lopez, Lorna M, Berentzen, Tina L, Räikkönen, Katri, Mangino, Massimo, Bandinelli, Stefania, Peyser, Patricia A, Wild, Sarah, Trégouët, David-Alexandre, Wright, Alan F, Marten, Jonathan, Zemunik, Tatijana, Morrison, Alanna C, Sennblad, Bengt, Tofler, Geoffrey, de Maat, Moniek PM, de Geus, Eco JC, Lowe, Gordon D, Zoledziewska, Magdalena, Sattar, Naveed, Binder, Harald, Völker, Uwe, Waldenberger, Melanie, Khaw, Kay-Tee, Mcknight, Barbara, Huang, Jie, Jenny, Nancy S, Holliday, Elizabeth G, Qi, Lihong, Mcevoy, Mark G, Becker, Diane M, Starr, John M, Sarin, Antti-Pekka, Hysi, Pirro G, Hernandez, Dena G, Jhun, Min A, Campbell, Harry, Hamsten, Anders, Rivadeneira, Fernando, Mcardle, Wendy L, Slagboom, P Eline, Zeller, Tanja, Koenig, Wolfgang, Psaty, Bruce M, Haritunians, Talin, Liu, Jingmin, Palotie, Aarno, Uitterlinden, André G, Stott, David J, Hofman, Albert, and Franco, Oscar H

Subjects
Biological Sciences, Genetics, Human Genome, Adult, Aged, Aged, 80 and over, Female, Fibrinogen, Genetic Loci, Genome-Wide Association Study, Humans, INDEL Mutation, Male, Middle Aged, Polymorphism, Single Nucleotide, White People, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies have previously identified 23 genetic loci associated with circulating fibrinogen concentration. These studies used HapMap imputation and did not examine the X-chromosome. 1000 Genomes imputation provides better coverage of uncommon variants, and includes indels. We conducted a genome-wide association analysis of 34 studies imputed to the 1000 Genomes Project reference panel and including ∼120 000 participants of European ancestry (95 806 participants with data on the X-chromosome). Approximately 10.7 million single-nucleotide polymorphisms and 1.2 million indels were examined. We identified 41 genome-wide significant fibrinogen loci; of which, 18 were newly identified. There were no genome-wide significant signals on the X-chromosome. The lead variants of five significant loci were indels. We further identified six additional independent signals, including three rare variants, at two previously characterized loci: FGB and IRF1. Together the 41 loci explain 3% of the variance in plasma fibrinogen concentration.

Published
2016

28. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair.

Author

Day, Felix R, Ruth, Katherine S, Thompson, Deborah J, Lunetta, Kathryn L, Pervjakova, Natalia, Chasman, Daniel I, Stolk, Lisette, Finucane, Hilary K, Sulem, Patrick, Bulik-Sullivan, Brendan, Esko, Tõnu, Johnson, Andrew D, Elks, Cathy E, Franceschini, Nora, He, Chunyan, Altmaier, Elisabeth, Brody, Jennifer A, Franke, Lude L, Huffman, Jennifer E, Keller, Margaux F, McArdle, Patrick F, Nutile, Teresa, Porcu, Eleonora, Robino, Antonietta, Rose, Lynda M, Schick, Ursula M, Smith, Jennifer A, Teumer, Alexander, Traglia, Michela, Vuckovic, Dragana, Yao, Jie, Zhao, Wei, Albrecht, Eva, Amin, Najaf, Corre, Tanguy, Hottenga, Jouke-Jan, Mangino, Massimo, Smith, Albert V, Tanaka, Toshiko, Abecasis, Goncalo, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Arndt, Volker, Arnold, Alice M, Barbieri, Caterina, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bernstein, Leslie, Bielinski, Suzette J, Blomqvist, Carl, Boerwinkle, Eric, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Borresen-Dale, Anne-Lise, Boutin, Thibaud S, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Burwinkel, Barbara, Campbell, Archie, Campbell, Harry, Chanock, Stephen J, Chapman, J Ross, Chen, Yii-Der Ida, Chenevix-Trench, Georgia, Couch, Fergus J, Coviello, Andrea D, Cox, Angela, Czene, Kamila, Darabi, Hatef, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Devilee, Peter, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dunning, Alison M, Eicher, John D, Fasching, Peter A, Faul, Jessica D, Figueroa, Jonine, Flesch-Janys, Dieter, Gandin, Ilaria, Garcia, Melissa E, García-Closas, Montserrat, Giles, Graham G, Girotto, Giorgia G, Goldberg, Mark S, González-Neira, Anna, Goodarzi, Mark O, Grove, Megan L, Gudbjartsson, Daniel F, Guénel, Pascal, Guo, Xiuqing, Haiman, Christopher A, Hall, Per, and Hamann, Ute

Subjects
PRACTICAL consortium, kConFab Investigators, AOCS Investigators, Generation Scotland, EPIC-InterAct Consortium, LifeLines Cohort Study, Hypothalamus, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, Genomics, Age Factors, Signal Transduction, DNA Repair, Aging, Reproduction, Menopause, Genotype, Phenotype, Models, Genetic, Adult, Middle Aged, Female, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Models, Genetic, Developmental Biology, Medical and Health Sciences, Biological Sciences
Abstract

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Published
2015

29. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author

Winkler, Thomas W, Justice, Anne E, Graff, Mariaelisa, Barata, Llilda, Feitosa, Mary F, Chu, Su, Czajkowski, Jacek, Esko, Tõnu, Fall, Tove, Kilpeläinen, Tuomas O, Lu, Yingchang, Mägi, Reedik, Mihailov, Evelin, Pers, Tune H, Rüeger, Sina, Teumer, Alexander, Ehret, Georg B, Ferreira, Teresa, Heard-Costa, Nancy L, Karjalainen, Juha, Lagou, Vasiliki, Mahajan, Anubha, Neinast, Michael D, Prokopenko, Inga, Simino, Jeannette, Teslovich, Tanya M, Jansen, Rick, Westra, Harm-Jan, White, Charles C, Absher, Devin, Ahluwalia, Tarunveer S, Ahmad, Shafqat, Albrecht, Eva, Alves, Alexessander Couto, Bragg-Gresham, Jennifer L, de Craen, Anton JM, Bis, Joshua C, Bonnefond, Amélie, Boucher, Gabrielle, Cadby, Gemma, Cheng, Yu-Ching, Chiang, Charleston WK, Delgado, Graciela, Demirkan, Ayse, Dueker, Nicole, Eklund, Niina, Eiriksdottir, Gudny, Eriksson, Joel, Feenstra, Bjarke, Fischer, Krista, Frau, Francesca, Galesloot, Tessel E, Geller, Frank, Goel, Anuj, Gorski, Mathias, Grammer, Tanja B, Gustafsson, Stefan, Haitjema, Saskia, Hottenga, Jouke-Jan, Huffman, Jennifer E, Jackson, Anne U, Jacobs, Kevin B, Johansson, Åsa, Kaakinen, Marika, Kleber, Marcus E, Lahti, Jari, Mateo Leach, Irene, Lehne, Benjamin, Liu, Youfang, Lo, Ken Sin, Lorentzon, Mattias, Luan, Jian'an, Madden, Pamela AF, Mangino, Massimo, McKnight, Barbara, Medina-Gomez, Carolina, Monda, Keri L, Montasser, May E, Müller, Gabriele, Müller-Nurasyid, Martina, Nolte, Ilja M, Panoutsopoulou, Kalliope, Pascoe, Laura, Paternoster, Lavinia, Rayner, Nigel W, Renström, Frida, Rizzi, Federica, Rose, Lynda M, Ryan, Kathy A, Salo, Perttu, Sanna, Serena, Scharnagl, Hubert, Shi, Jianxin, Smith, Albert Vernon, Southam, Lorraine, Stančáková, Alena, Steinthorsdottir, Valgerdur, Strawbridge, Rona J, Sung, Yun Ju, and Tachmazidou, Ioanna

Subjects
CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Humans, Genetic Predisposition to Disease, Body Mass Index, Body Size, Waist-Hip Ratio, Chromosome Mapping, Age Factors, Sex Characteristics, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Developmental Biology, Genetics
Abstract

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR

Published
2015

30. Directional dominance on stature and cognition in diverse human populations

Author

Joshi, Peter K, Esko, Tonu, Mattsson, Hannele, Eklund, Niina, Gandin, Ilaria, Nutile, Teresa, Jackson, Anne U, Schurmann, Claudia, Smith, Albert V, Zhang, Weihua, Okada, Yukinori, Stančáková, Alena, Faul, Jessica D, Zhao, Wei, Bartz, Traci M, Concas, Maria Pina, Franceschini, Nora, Enroth, Stefan, Vitart, Veronique, Trompet, Stella, Guo, Xiuqing, Chasman, Daniel I, O'Connel, Jeffrey R, Corre, Tanguy, Nongmaithem, Suraj S, Chen, Yuning, Mangino, Massimo, Ruggiero, Daniela, Traglia, Michela, Farmaki, Aliki-Eleni, Kacprowski, Tim, Bjonnes, Andrew, van der Spek, Ashley, Wu, Ying, Giri, Anil K, Yanek, Lisa R, Wang, Lihua, Hofer, Edith, Rietveld, Cornelius A, McLeod, Olga, Cornelis, Marilyn C, Pattaro, Cristian, Verweij, Niek, Baumbach, Clemens, Abdellaoui, Abdel, Warren, Helen R, Vuckovic, Dragana, Mei, Hao, Bouchard, Claude, Perry, John RB, Cappellani, Stefania, Mirza, Saira S, Benton, Miles C, Broeckel, Ulrich, Medland, Sarah E, Lind, Penelope A, Malerba, Giovanni, Drong, Alexander, Yengo, Loic, Bielak, Lawrence F, Zhi, Degui, van der Most, Peter J, Shriner, Daniel, Mägi, Reedik, Hemani, Gibran, Karaderi, Tugce, Wang, Zhaoming, Liu, Tian, Demuth, Ilja, Zhao, Jing Hua, Meng, Weihua, Lataniotis, Lazaros, van der Laan, Sander W, Bradfield, Jonathan P, Wood, Andrew R, Bonnefond, Amelie, Ahluwalia, Tarunveer S, Hall, Leanne M, Salvi, Erika, Yazar, Seyhan, Carstensen, Lisbeth, de Haan, Hugoline G, Abney, Mark, Afzal, Uzma, Allison, Matthew A, Amin, Najaf, Asselbergs, Folkert W, Bakker, Stephan JL, Barr, R Graham, Baumeister, Sebastian E, Benjamin, Daniel J, Bergmann, Sven, Boerwinkle, Eric, Bottinger, Erwin P, Campbell, Archie, Chakravarti, Aravinda, Chan, Yingleong, Chanock, Stephen J, Chen, Constance, and Chen, Y-D Ida

Subjects
Biological Sciences, Genetics, Clinical Research, Human Genome, Biological Evolution, Blood Pressure, Body Height, Cholesterol, LDL, Cognition, Cohort Studies, Educational Status, Female, Forced Expiratory Volume, Genome, Human, Homozygote, Humans, Lung Volume Measurements, Male, Phenotype, General Science & Technology
Abstract

Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Published
2015

31. New genetic loci link adipose and insulin biology to body fat distribution

Author

Shungin, Dmitry, Winkler, Thomas W, Croteau-Chonka, Damien C, Ferreira, Teresa, Locke, Adam E, Mägi, Reedik, Strawbridge, Rona J, Pers, Tune H, Fischer, Krista, Justice, Anne E, Workalemahu, Tsegaselassie, Wu, Joseph MW, Buchkovich, Martin L, Heard-Costa, Nancy L, Roman, Tamara S, Drong, Alexander W, Song, Ci, Gustafsson, Stefan, Day, Felix R, Esko, Tonu, Fall, Tove, Kutalik, Zoltán, Luan, Jian’an, Randall, Joshua C, Scherag, André, Vedantam, Sailaja, Wood, Andrew R, Chen, Jin, Fehrmann, Rudolf, Karjalainen, Juha, Kahali, Bratati, Liu, Ching-Ti, Schmidt, Ellen M, Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bragg-Gresham, Jennifer L, Buyske, Steven, Demirkan, Ayse, Ehret, Georg B, Feitosa, Mary F, Goel, Anuj, Jackson, Anne U, Johnson, Toby, Kleber, Marcus E, Kristiansson, Kati, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J, Prokopenko, Inga, Stančáková, Alena, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Van Vliet-Ostaptchouk, Jana V, Yengo, Loïc, Zhang, Weihua, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Böhringer, Stefan, Bonnet, Fabrice, Böttcher, Yvonne, Bruinenberg, Marcel, Carba, Delia B, Caspersen, Ida H, Clarke, Robert, Warwick Daw, E, Deelen, Joris, Deelman, Ewa, Delgado, Graciela, Doney, Alex SF, Eklund, Niina, Erdos, Michael R, Estrada, Karol, Eury, Elodie, Friedrich, Nele, Garcia, Melissa E, Giedraitis, Vilmantas, Gigante, Bruna, Go, Alan S, Golay, Alain, Grallert, Harald, Grammer, Tanja B, Gräßler, Jürgen, Grewal, Jagvir, Groves, Christopher J, Haller, Toomas, and Hallmans, Goran

Subjects
Genetics, Human Genome, Diabetes, Obesity, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Cardiovascular, Stroke, Adipocytes, Adipogenesis, Adipose Tissue, Age Factors, Body Fat Distribution, Body Mass Index, Epigenesis, Genetic, Europe, Female, Genome, Human, Genome-Wide Association Study, Humans, Insulin, Insulin Resistance, Male, Models, Biological, Neovascularization, Physiologic, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Racial Groups, Sex Characteristics, Transcription, Genetic, Waist-Hip Ratio, ADIPOGen Consortium, CARDIOGRAMplusC4D Consortium, CKDGen Consortium, GEFOS Consortium, GENIE Consortium, GLGC, ICBP, International Endogene Consortium, LifeLines Cohort Study, MAGIC Investigators, MuTHER Consortium, PAGE Consortium, ReproGen Consortium, General Science & Technology
Abstract

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P

Published
2015

32. Genetic studies of body mass index yield new insights for obesity biology

Author

Locke, Adam E, Kahali, Bratati, Berndt, Sonja I, Justice, Anne E, Pers, Tune H, Day, Felix R, Powell, Corey, Vedantam, Sailaja, Buchkovich, Martin L, Yang, Jian, Croteau-Chonka, Damien C, Esko, Tonu, Fall, Tove, Ferreira, Teresa, Gustafsson, Stefan, Kutalik, Zoltán, Luan, Jian’an, Mägi, Reedik, Randall, Joshua C, Winkler, Thomas W, Wood, Andrew R, Workalemahu, Tsegaselassie, Faul, Jessica D, Smith, Jennifer A, Hua Zhao, Jing, Zhao, Wei, Chen, Jin, Fehrmann, Rudolf, Hedman, Åsa K, Karjalainen, Juha, Schmidt, Ellen M, Absher, Devin, Amin, Najaf, Anderson, Denise, Beekman, Marian, Bolton, Jennifer L, Bragg-Gresham, Jennifer L, Buyske, Steven, Demirkan, Ayse, Deng, Guohong, Ehret, Georg B, Feenstra, Bjarke, Feitosa, Mary F, Fischer, Krista, Goel, Anuj, Gong, Jian, Jackson, Anne U, Kanoni, Stavroula, Kleber, Marcus E, Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Mangino, Massimo, Mateo Leach, Irene, Medina-Gomez, Carolina, Medland, Sarah E, Nalls, Michael A, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Peters, Marjolein J, Prokopenko, Inga, Shungin, Dmitry, Stančáková, Alena, Strawbridge, Rona J, Ju Sung, Yun, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W, van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V, Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Isaacs, Aaron, Albrecht, Eva, Ärnlöv, Johan, Arscott, Gillian M, Attwood, Antony P, Bandinelli, Stefania, Barrett, Amy, Bas, Isabelita N, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blagieva, Roza, Blüher, Matthias, Böhringer, Stefan, Bonnycastle, Lori L, Böttcher, Yvonne, Boyd, Heather A, Bruinenberg, Marcel, Caspersen, Ida H, Ida Chen, Yii-Der, Clarke, Robert, Warwick Daw, E, de Craen, Anton JM, Delgado, Graciela, and Dimitriou, Maria

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Nutrition, Obesity, Prevention, Aetiology, 2.1 Biological and endogenous factors, Stroke, Cardiovascular, Metabolic and endocrine, Oral and gastrointestinal, Cancer, Adipogenesis, Adiposity, Age Factors, Body Mass Index, Energy Metabolism, Europe, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Glutamic Acid, Humans, Insulin, Insulin Secretion, Male, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Racial Groups, Synapses, LifeLines Cohort Study, ADIPOGen Consortium, AGEN-BMI Working Group, CARDIOGRAMplusC4D Consortium, CKDGen Consortium, GLGC, ICBP, MAGIC Investigators, MuTHER Consortium, MIGen Consortium, PAGE Consortium, ReproGen Consortium, GENIE Consortium, International Endogene Consortium, General Science & Technology
Abstract

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Published
2015

33. Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

Author

Mahajan, Anubha, Sim, Xueling, Ng, Hui Jin, Manning, Alisa, Rivas, Manuel A, Highland, Heather M, Locke, Adam E, Grarup, Niels, Im, Hae Kyung, Cingolani, Pablo, Flannick, Jason, Fontanillas, Pierre, Fuchsberger, Christian, Gaulton, Kyle J, Teslovich, Tanya M, Rayner, N William, Robertson, Neil R, Beer, Nicola L, Rundle, Jana K, Bork-Jensen, Jette, Ladenvall, Claes, Blancher, Christine, Buck, David, Buck, Gemma, Burtt, Noël P, Gabriel, Stacey, Gjesing, Anette P, Groves, Christopher J, Hollensted, Mette, Huyghe, Jeroen R, Jackson, Anne U, Jun, Goo, Justesen, Johanne Marie, Mangino, Massimo, Murphy, Jacquelyn, Neville, Matt, Onofrio, Robert, Small, Kerrin S, Stringham, Heather M, Syvänen, Ann-Christine, Trakalo, Joseph, Abecasis, Goncalo, Bell, Graeme I, Blangero, John, Cox, Nancy J, Duggirala, Ravindranath, Hanis, Craig L, Seielstad, Mark, Wilson, James G, Christensen, Cramer, Brandslund, Ivan, Rauramaa, Rainer, Surdulescu, Gabriela L, Doney, Alex SF, Lannfelt, Lars, Linneberg, Allan, Isomaa, Bo, Tuomi, Tiinamaija, Jørgensen, Marit E, Jørgensen, Torben, Kuusisto, Johanna, Uusitupa, Matti, Salomaa, Veikko, Spector, Timothy D, Morris, Andrew D, Palmer, Colin NA, Collins, Francis S, Mohlke, Karen L, Bergman, Richard N, Ingelsson, Erik, Lind, Lars, Tuomilehto, Jaakko, Hansen, Torben, Watanabe, Richard M, Prokopenko, Inga, Dupuis, Josee, Karpe, Fredrik, Groop, Leif, Laakso, Markku, Pedersen, Oluf, Florez, Jose C, Morris, Andrew P, Altshuler, David, Meigs, James B, Boehnke, Michael, McCarthy, Mark I, Lindgren, Cecilia M, Gloyn, Anna L, and T2D-GENES consortium and GoT2D consortium

Subjects
T2D-GENES consortium and GoT2D consortium, Humans, Diabetes Mellitus, Type 2, Insulin, Glucose-6-Phosphatase, Blood Glucose, Receptors, Glucagon, Glycemic Index, Gene Frequency, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Exome, Glucagon-Like Peptide-1 Receptor, Diabetes Mellitus, Type 2, Receptors, Glucagon, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P

Published
2015

34. Defining the role of common variation in the genomic and biological architecture of adult human height

Author

Wood, Andrew R, Esko, Tonu, Yang, Jian, Vedantam, Sailaja, Pers, Tune H, Gustafsson, Stefan, Chu, Audrey Y, Estrada, Karol, Luan, Jian'an, Kutalik, Zoltán, Amin, Najaf, Buchkovich, Martin L, Croteau-Chonka, Damien C, Day, Felix R, Duan, Yanan, Fall, Tove, Fehrmann, Rudolf, Ferreira, Teresa, Jackson, Anne U, Karjalainen, Juha, Lo, Ken Sin, Locke, Adam E, Mägi, Reedik, Mihailov, Evelin, Porcu, Eleonora, Randall, Joshua C, Scherag, André, Vinkhuyzen, Anna AE, Westra, Harm-Jan, Winkler, Thomas W, Workalemahu, Tsegaselassie, Zhao, Jing Hua, Absher, Devin, Albrecht, Eva, Anderson, Denise, Baron, Jeffrey, Beekman, Marian, Demirkan, Ayse, Ehret, Georg B, Feenstra, Bjarke, Feitosa, Mary F, Fischer, Krista, Fraser, Ross M, Goel, Anuj, Gong, Jian, Justice, Anne E, Kanoni, Stavroula, Kleber, Marcus E, Kristiansson, Kati, Lim, Unhee, Lotay, Vaneet, Lui, Julian C, Mangino, Massimo, Leach, Irene Mateo, Medina-Gomez, Carolina, Nalls, Michael A, Nyholt, Dale R, Palmer, Cameron D, Pasko, Dorota, Pechlivanis, Sonali, Prokopenko, Inga, Ried, Janina S, Ripke, Stephan, Shungin, Dmitry, Stancáková, Alena, Strawbridge, Rona J, Sung, Yun Ju, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, van der Laan, Sander W, van Setten, Jessica, Van Vliet-Ostaptchouk, Jana V, Wang, Zhaoming, Yengo, Loïc, Zhang, Weihua, Afzal, Uzma, Ärnlöv, Johan, Arscott, Gillian M, Bandinelli, Stefania, Barrett, Amy, Bellis, Claire, Bennett, Amanda J, Berne, Christian, Blüher, Matthias, Bolton, Jennifer L, Böttcher, Yvonne, Boyd, Heather A, Bruinenberg, Marcel, Buckley, Brendan M, Buyske, Steven, Caspersen, Ida H, Chines, Peter S, Clarke, Robert, Claudi-Boehm, Simone, Cooper, Matthew, Daw, E Warwick, De Jong, Pim A, Deelen, Joris, and Delgado, Graciela

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Adult, Analysis of Variance, Body Height, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, White People, Electronic Medical Records and Genomics (eMEMERGEGE) Consortium, MIGen Consortium, PAGEGE Consortium, LifeLines Cohort Study, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Published
2014

35. Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche

Author

Perry, John RB, Day, Felix, Elks, Cathy E, Sulem, Patrick, Thompson, Deborah J, Ferreira, Teresa, He, Chunyan, Chasman, Daniel I, Esko, Tõnu, Thorleifsson, Gudmar, Albrecht, Eva, Ang, Wei Q, Corre, Tanguy, Cousminer, Diana L, Feenstra, Bjarke, Franceschini, Nora, Ganna, Andrea, Johnson, Andrew D, Kjellqvist, Sanela, Lunetta, Kathryn L, McMahon, George, Nolte, Ilja M, Paternoster, Lavinia, Porcu, Eleonora, Smith, Albert V, Stolk, Lisette, Teumer, Alexander, Tšernikova, Natalia, Tikkanen, Emmi, Ulivi, Sheila, Wagner, Erin K, Amin, Najaf, Bierut, Laura J, Byrne, Enda M, Hottenga, Jouke-Jan, Koller, Daniel L, Mangino, Massimo, Pers, Tune H, Yerges-Armstrong, Laura M, Hua Zhao, Jing, Andrulis, Irene L, Anton-Culver, Hoda, Atsma, Femke, Bandinelli, Stefania, Beckmann, Matthias W, Benitez, Javier, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Brauch, Hiltrud, Brenner, Hermann, Buring, Julie E, Chang-Claude, Jenny, Chanock, Stephen, Chen, Jinhui, Chenevix-Trench, Georgia, Collée, J Margriet, Couch, Fergus J, Couper, David, Coviello, Andrea D, Cox, Angela, Czene, Kamila, D’adamo, Adamo Pio, Davey Smith, George, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Devilee, Peter, Dieffenbach, Aida K, Dunning, Alison M, Eiriksdottir, Gudny, Eriksson, Johan G, Fasching, Peter A, Ferrucci, Luigi, Flesch-Janys, Dieter, Flyger, Henrik, Foroud, Tatiana, Franke, Lude, Garcia, Melissa E, García-Closas, Montserrat, Geller, Frank, de Geus, Eco EJ, Giles, Graham G, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Guénel, Pascal, Guo, Suiqun, Hall, Per, Hamann, Ute, Haring, Robin, Hartman, Catharina A, Heath, Andrew C, Hofman, Albert, Hooning, Maartje J, Hopper, John L, Hu, Frank B, Hunter, David J, Karasik, David, and Kiel, Douglas P

Subjects
Paediatrics, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Contraception/Reproduction, Pediatric, Biotechnology, Human Genome, Clinical Research, Adolescent, Age Factors, Alleles, Body Mass Index, Breast Neoplasms, Calcium-Binding Proteins, Cardiovascular Diseases, Child, Diabetes Mellitus, Type 2, Europe, Female, Genetic Loci, Genome-Wide Association Study, Genomic Imprinting, Humans, Hypothalamo-Hypophyseal System, Intercellular Signaling Peptides and Proteins, Male, Membrane Proteins, Menarche, Obesity, Ovary, Parents, Polymorphism, Single Nucleotide, Potassium Channels, Tandem Pore Domain, Proteins, Quantitative Trait Loci, Receptors, GABA-B, Receptors, Retinoic Acid, Ribonucleoproteins, Ubiquitin-Protein Ligases, Australian Ovarian Cancer Study, GENICA Network, kConFab, LifeLines Cohort Study, InterAct Consortium, Early Growth Genetics (EGG) Consortium, General Science & Technology
Abstract

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P

Published
2014

36. Low copy number of the salivary amylase gene predisposes to obesity

Author

Falchi, Mario, El-Sayed Moustafa, Julia Sarah, Takousis, Petros, Pesce, Francesco, Bonnefond, Amélie, Andersson-Assarsson, Johanna C, Sudmant, Peter H, Dorajoo, Rajkumar, Al-Shafai, Mashael Nedham, Bottolo, Leonardo, Ozdemir, Erdal, So, Hon-Cheong, Davies, Robert W, Patrice, Alexandre, Dent, Robert, Mangino, Massimo, Hysi, Pirro G, Dechaume, Aurélie, Huyvaert, Marlène, Skinner, Jane, Pigeyre, Marie, Caiazzo, Robert, Raverdy, Violeta, Vaillant, Emmanuel, Field, Sarah, Balkau, Beverley, Marre, Michel, Visvikis-Siest, Sophie, Weill, Jacques, Poulain-Godefroy, Odile, Jacobson, Peter, Sjostrom, Lars, Hammond, Christopher J, Deloukas, Panos, Sham, Pak Chung, McPherson, Ruth, Lee, Jeannette, Tai, E Shyong, Sladek, Robert, Carlsson, Lena MS, Walley, Andrew, Eichler, Evan E, Pattou, Francois, Spector, Timothy D, and Froguel, Philippe

Subjects
Biological Sciences, Genetics, Cancer, Body Mass Index, Carbohydrate Metabolism, Gene Dosage, Genetic Predisposition to Disease, Genomics, Humans, Microarray Analysis, Obesity, Odds Ratio, Salivary alpha-Amylases, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Common multi-allelic copy number variants (CNVs) appear enriched for phenotypic associations compared to their biallelic counterparts. Here we investigated the influence of gene dosage effects on adiposity through a CNV association study of gene expression levels in adipose tissue. We identified significant association of a multi-allelic CNV encompassing the salivary amylase gene (AMY1) with body mass index (BMI) and obesity, and we replicated this finding in 6,200 subjects. Increased AMY1 copy number was positively associated with both amylase gene expression (P = 2.31 × 10(-14)) and serum enzyme levels (P < 2.20 × 10(-16)), whereas reduced AMY1 copy number was associated with increased BMI (change in BMI per estimated copy = -0.15 (0.02) kg/m(2); P = 6.93 × 10(-10)) and obesity risk (odds ratio (OR) per estimated copy = 1.19, 95% confidence interval (CI) = 1.13-1.26; P = 1.46 × 10(-10)). The OR value of 1.19 per copy of AMY1 translates into about an eightfold difference in risk of obesity between subjects in the top (copy number > 9) and bottom (copy number < 4) 10% of the copy number distribution. Our study provides a first genetic link between carbohydrate metabolism and BMI and demonstrates the power of integrated genomic approaches beyond genome-wide association studies.

Published
2014

37. Discovery and refinement of loci associated with lipid levels

Author

Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayse, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tonu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkila, Kauko, Hyppoenen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Asa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikainen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Mueller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Ines, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Doering, Angela, Elliott, Paul, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Goran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, Khaw, Kay-Tee, and Kim, Eric

Subjects
Cardiovascular, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Asian People, Black People, Cholesterol, HDL, Cholesterol, LDL, Coronary Artery Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Lipids, Triglycerides, White People, Global Lipids Genetics Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Published
2013

38. Common variants associated with plasma triglycerides and risk for coronary artery disease

Author

Do, Ron, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Gao, Chi, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, and Khaw, Kay-Tee

Subjects
Heart Disease - Coronary Heart Disease, Atherosclerosis, Prevention, Heart Disease, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Biological Transport, Cholesterol, HDL, Cholesterol, LDL, Coronary Artery Disease, Humans, Polymorphism, Single Nucleotide, Risk Factors, Triglycerides, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Published
2013

39. A genome-wide association study of early menopause and the combined impact of identified variants

Author

Perry, John RB, Corre, Tanguy, Esko, Tõnu, Chasman, Daniel I, Fischer, Krista, Franceschini, Nora, He, Chunyan, Kutalik, Zoltan, Mangino, Massimo, Rose, Lynda M, Smith, Albert Vernon, Stolk, Lisette, Sulem, Patrick, Weedon, Michael N, Zhuang, Wei V, Arnold, Alice, Ashworth, Alan, Bergmann, Sven, Buring, Julie E, Burri, Andrea, Chen, Constance, Cornelis, Marilyn C, Couper, David J, Goodarzi, Mark O, Gudnason, Vilmundur, Harris, Tamara, Hofman, Albert, Jones, Michael, Kraft, Peter, Launer, Lenore, Laven, Joop SE, Li, Guo, McKnight, Barbara, Masciullo, Corrado, Milani, Lili, Orr, Nicholas, Psaty, Bruce M, Ridker, Paul M, Rivadeneira, Fernando, Sala, Cinzia, Salumets, Andres, Schoemaker, Minouk, Traglia, Michela, Waeber, Gérard, Chanock, Stephen J, Demerath, Ellen W, Garcia, Melissa, Hankinson, Susan E, Hu, Frank B, Hunter, David J, Lunetta, Kathryn L, Metspalu, Andres, Montgomery, Grant W, Murabito, Joanne M, Newman, Anne B, Ong, Ken K, Spector, Tim D, Stefansson, Kari, Swerdlow, Anthony J, Thorsteinsdottir, Unnur, Van Dam, Rob M, Uitterlinden, André G, Visser, Jenny A, Vollenweider, Peter, Toniolo, Daniela, and Murray, Anna

Subjects
Biotechnology, Contraception/Reproduction, Infertility, Genetics, Human Genome, Aging, Estrogen, Prevention, Aetiology, 2.1 Biological and endogenous factors, Reproductive health and childbirth, Good Health and Well Being, Case-Control Studies, Female, Gene Frequency, Genome-Wide Association Study, Humans, Menopause, Premature, Polymorphism, Single Nucleotide, Primary Ovarian Insufficiency, Quantitative Trait Loci, Risk, ReproGen Consortium, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.

Published
2013

40. Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans.

Author

Mangino, Massimo, Hwang, Shih-Jen, Spector, Timothy, Hunt, Steven, Kimura, Masayuki, Fitzpatrick, Annette, Christiansen, Lene, Petersen, Inge, Elbers, Clara, Harris, Tamara, Chen, Wei, Srinivasan, Sathanur, Kark, Jeremy, Benetos, Athanase, El Shamieh, Said, Visvikis-Siest, Sophie, Christensen, Kaare, Berenson, Gerald, Valdes, Ana, Viñuela, Ana, Garcia, Melissa, Arnett, Donna, Broeckel, Ulrich, Province, Michael, Pankow, James, Kammerer, Candace, Liu, Yongmei, Nalls, Michael, Tishkoff, Sarah, Thomas, Fridtjof, Psaty, Bruce, Bis, Joshua, Taylor, Kent, Smith, Erin, Schork, Nicholas, Levy, Daniel, Aviv, Abraham, Ziv, Elad, and Rotter, Jerome

Subjects
Genome-Wide Association Study, Humans, Kruppel-Like Transcription Factors, Telomere, Telomere Homeostasis, Telomere-Binding Proteins
Abstract

Leukocyte telomere length (LTL) is associated with a number of common age-related diseases and is a heritable trait. Previous genome-wide association studies (GWASs) identified two loci on chromosomes 3q26.2 (TERC) and 10q24.33 (OBFC1) that are associated with the inter-individual LTL variation. We performed a meta-analysis of 9190 individuals from six independent GWAS and validated our findings in 2226 individuals from four additional studies. We confirmed previously reported associations with OBFC1 (rs9419958 P = 9.1 × 10(-11)) and with the telomerase RNA component TERC (rs1317082, P = 1.1 × 10(-8)). We also identified two novel genomic regions associated with LTL variation that map near a conserved telomere maintenance complex component 1 (CTC1; rs3027234, P = 3.6 × 10(-8)) on chromosome17p13.1 and zinc finger protein 676 (ZNF676; rs412658, P = 3.3 × 10(-8)) on 19p12. The minor allele of rs3027234 was associated with both shorter LTL and lower expression of CTC1. Our findings are consistent with the recent observations that point mutations in CTC1 cause short telomeres in both Arabidopsis and humans affected by a rare Mendelian syndrome. Overall, our results provide novel insights into the genetic architecture of inter-individual LTL variation in the general population.

Published
2012

41. A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation

Author

Coviello, Andrea D, Haring, Robin, Wellons, Melissa, Vaidya, Dhananjay, Lehtimäki, Terho, Keildson, Sarah, Lunetta, Kathryn L, He, Chunyan, Fornage, Myriam, Lagou, Vasiliki, Mangino, Massimo, Onland-Moret, N Charlotte, Chen, Brian, Eriksson, Joel, Garcia, Melissa, Liu, Yong Mei, Koster, Annemarie, Lohman, Kurt, Lyytikäinen, Leo-Pekka, Petersen, Ann-Kristin, Prescott, Jennifer, Stolk, Lisette, Vandenput, Liesbeth, Wood, Andrew R, Zhuang, Wei Vivian, Ruokonen, Aimo, Hartikainen, Anna-Liisa, Pouta, Anneli, Bandinelli, Stefania, Biffar, Reiner, Brabant, Georg, Cox, David G, Chen, Yuhui, Cummings, Steven, Ferrucci, Luigi, Gunter, Marc J, Hankinson, Susan E, Martikainen, Hannu, Hofman, Albert, Homuth, Georg, Illig, Thomas, Jansson, John-Olov, Johnson, Andrew D, Karasik, David, Karlsson, Magnus, Kettunen, Johannes, Kiel, Douglas P, Kraft, Peter, Liu, Jingmin, Ljunggren, Östen, Lorentzon, Mattias, Maggio, Marcello, Markus, Marcello RP, Mellström, Dan, Miljkovic, Iva, Mirel, Daniel, Nelson, Sarah, Papunen, Laure Morin, Peeters, Petra HM, Prokopenko, Inga, Raffel, Leslie, Reincke, Martin, Reiner, Alex P, Rexrode, Kathryn, Rivadeneira, Fernando, Schwartz, Stephen M, Siscovick, David, Soranzo, Nicole, Stöckl, Doris, Tworoger, Shelley, Uitterlinden, André G, van Gils, Carla H, Vasan, Ramachandran S, Wichmann, H-Erich, Zhai, Guangju, Bhasin, Shalender, Bidlingmaier, Martin, Chanock, Stephen J, De Vivo, Immaculata, Harris, Tamara B, Hunter, David J, Kähönen, Mika, Liu, Simin, Ouyang, Pamela, Spector, Tim D, van der Schouw, Yvonne T, Viikari, Jorma, Wallaschofski, Henri, McCarthy, Mark I, Frayling, Timothy M, Murray, Anna, Franks, Steve, Järvelin, Marjo-Riitta, de Jong, Frank H, Raitakari, Olli, Teumer, Alexander, Ohlsson, Claes, Murabito, Joanne M, and Perry, John RB

Subjects
Biological Sciences, Genetics, Breast Cancer, Aging, Estrogen, Cancer Genomics, Urologic Diseases, Cancer, Prostate Cancer, Human Genome, Women's Health, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Alleles, Female, Genetic Heterogeneity, Genome-Wide Association Study, Gonadal Steroid Hormones, Humans, Male, Metabolic Networks and Pathways, Polymorphism, Single Nucleotide, Sex Characteristics, Sex Hormone-Binding Globulin, Developmental Biology
Abstract

Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8 × 10(-106)), PRMT6 (rs17496332, 1p13.3, p = 1.4 × 10(-11)), GCKR (rs780093, 2p23.3, p = 2.2 × 10(-16)), ZBTB10 (rs440837, 8q21.13, p = 3.4 × 10(-09)), JMJD1C (rs7910927, 10q21.3, p = 6.1 × 10(-35)), SLCO1B1 (rs4149056, 12p12.1, p = 1.9 × 10(-08)), NR2F2 (rs8023580, 15q26.2, p = 8.3 × 10(-12)), ZNF652 (rs2411984, 17q21.32, p = 3.5 × 10(-14)), TDGF3 (rs1573036, Xq22.3, p = 4.1 × 10(-14)), LHCGR (rs10454142, 2p16.3, p = 1.3 × 10(-07)), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7 × 10(-08)), and UGT2B15 (rs293428, 4q13.2, p = 5.5 × 10(-06)). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5 × 10(-08), women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ~15.6% and ~8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.

Published
2012

42. A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol.

Author

Surakka, Ida, Isaacs, Aaron, Karssen, Lennart C, Laurila, Pirkka-Pekka P, Middelberg, Rita PS, Tikkanen, Emmi, Ried, Janina S, Lamina, Claudia, Mangino, Massimo, Igl, Wilmar, Hottenga, Jouke-Jan, Lagou, Vasiliki, van der Harst, Pim, Mateo Leach, Irene, Esko, Tõnu, Kutalik, Zoltán, Wainwright, Nicholas W, Struchalin, Maksim V, Sarin, Antti-Pekka, Kangas, Antti J, Viikari, Jorma S, Perola, Markus, Rantanen, Taina, Petersen, Ann-Kristin, Soininen, Pasi, Johansson, Asa, Soranzo, Nicole, Heath, Andrew C, Papamarkou, Theodore, Prokopenko, Inga, Tönjes, Anke, Kronenberg, Florian, Döring, Angela, Rivadeneira, Fernando, Montgomery, Grant W, Whitfield, John B, Kähönen, Mika, Lehtimäki, Terho, Freimer, Nelson B, Willemsen, Gonneke, de Geus, Eco JC, Palotie, Aarno, Sandhu, Manj S, Waterworth, Dawn M, Metspalu, Andres, Stumvoll, Michael, Uitterlinden, André G, Jula, Antti, Navis, Gerjan, Wijmenga, Cisca, Wolffenbuttel, Bruce HR, Taskinen, Marja-Riitta, Ala-Korpela, Mika, Kaprio, Jaakko, Kyvik, Kirsten O, Boomsma, Dorret I, Pedersen, Nancy L, Gyllensten, Ulf, Wilson, James F, Rudan, Igor, Campbell, Harry, Pramstaller, Peter P, Spector, Tim D, Witteman, Jacqueline CM, Eriksson, Johan G, Salomaa, Veikko, Oostra, Ben A, Raitakari, Olli T, Wichmann, H-Erich, Gieger, Christian, Järvelin, Marjo-Riitta, Martin, Nicholas G, Hofman, Albert, McCarthy, Mark I, Peltonen, Leena, van Duijn, Cornelia M, Aulchenko, Yurii S, Ripatti, Samuli, and ENGAGE Consortium

Subjects
ENGAGE Consortium, Adipose Tissue, Chromosomes, Human, Pair 4, Humans, Cholesterol, Lipids, Triglycerides, Lipoproteins, Cadherins, Waist-Hip Ratio, Risk Factors, Chromosome Mapping, Genotype, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, European Continental Ancestry Group, Body Fat Distribution, Genome-Wide Association Study, Chromosomes, Human, Pair 4, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Published
2011

43. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index

Author

Speliotes, Elizabeth K, Willer, Cristen J, Berndt, Sonja I, Monda, Keri L, Thorleifsson, Gudmar, Jackson, Anne U, Allen, Hana Lango, Lindgren, Cecilia M, Luan, Jian'an, Mägi, Reedik, Randall, Joshua C, Vedantam, Sailaja, Winkler, Thomas W, Qi, Lu, Workalemahu, Tsegaselassie, Heid, Iris M, Steinthorsdottir, Valgerdur, Stringham, Heather M, Weedon, Michael N, Wheeler, Eleanor, Wood, Andrew R, Ferreira, Teresa, Weyant, Robert J, Segrè, Ayellet V, Estrada, Karol, Liang, Liming, Nemesh, James, Park, Ju-Hyun, Gustafsson, Stefan, Kilpeläinen, Tuomas O, Yang, Jian, Bouatia-Naji, Nabila, Esko, Tõnu, Feitosa, Mary F, Kutalik, Zoltán, Mangino, Massimo, Raychaudhuri, Soumya, Scherag, Andre, Smith, Albert Vernon, Welch, Ryan, Zhao, Jing Hua, Aben, Katja K, Absher, Devin M, Amin, Najaf, Dixon, Anna L, Fisher, Eva, Glazer, Nicole L, Goddard, Michael E, Heard-Costa, Nancy L, Hoesel, Volker, Hottenga, Jouke-Jan, Johansson, Åsa, Johnson, Toby, Ketkar, Shamika, Lamina, Claudia, Li, Shengxu, Moffatt, Miriam F, Myers, Richard H, Narisu, Narisu, Perry, John RB, Peters, Marjolein J, Preuss, Michael, Ripatti, Samuli, Rivadeneira, Fernando, Sandholt, Camilla, Scott, Laura J, Timpson, Nicholas J, Tyrer, Jonathan P, van Wingerden, Sophie, Watanabe, Richard M, White, Charles C, Wiklund, Fredrik, Barlassina, Christina, Chasman, Daniel I, Cooper, Matthew N, Jansson, John-Olov, Lawrence, Robert W, Pellikka, Niina, Prokopenko, Inga, Shi, Jianxin, Thiering, Elisabeth, Alavere, Helene, Alibrandi, Maria TS, Almgren, Peter, Arnold, Alice M, Aspelund, Thor, Atwood, Larry D, Balkau, Beverley, Balmforth, Anthony J, Bennett, Amanda J, Ben-Shlomo, Yoav, Bergman, Richard N, Bergmann, Sven, Biebermann, Heike, Blakemore, Alexandra IF, Boes, Tanja, Bonnycastle, Lori L, Bornstein, Stefan R, Brown, Morris J, and Buchanan, Thomas A

Subjects
Biological Sciences, Genetics, Prevention, Human Genome, Body Height, Body Mass Index, Body Size, Body Weight, Chromosome Mapping, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Obesity, Polymorphism, Single Nucleotide, White People, MAGIC, Procardis Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Published
2010

44. Hundreds of variants clustered in genomic loci and biological pathways affect human height

Author

Lango Allen, Hana, Estrada, Karol, Lettre, Guillaume, Berndt, Sonja I, Weedon, Michael N, Rivadeneira, Fernando, Willer, Cristen J, Jackson, Anne U, Vedantam, Sailaja, Raychaudhuri, Soumya, Ferreira, Teresa, Wood, Andrew R, Weyant, Robert J, Segrè, Ayellet V, Speliotes, Elizabeth K, Wheeler, Eleanor, Soranzo, Nicole, Park, Ju-Hyun, Yang, Jian, Gudbjartsson, Daniel, Heard-Costa, Nancy L, Randall, Joshua C, Qi, Lu, Vernon Smith, Albert, Mägi, Reedik, Pastinen, Tomi, Liang, Liming, Heid, Iris M, Luan, Jian’an, Thorleifsson, Gudmar, Winkler, Thomas W, Goddard, Michael E, Sin Lo, Ken, Palmer, Cameron, Workalemahu, Tsegaselassie, Aulchenko, Yurii S, Johansson, Åsa, Carola Zillikens, M, Feitosa, Mary F, Esko, Tõnu, Johnson, Toby, Ketkar, Shamika, Kraft, Peter, Mangino, Massimo, Prokopenko, Inga, Absher, Devin, Albrecht, Eva, Ernst, Florian, Glazer, Nicole L, Hayward, Caroline, Hottenga, Jouke-Jan, Jacobs, Kevin B, Knowles, Joshua W, Kutalik, Zoltán, Monda, Keri L, Polasek, Ozren, Preuss, Michael, Rayner, Nigel W, Robertson, Neil R, Steinthorsdottir, Valgerdur, Tyrer, Jonathan P, Voight, Benjamin F, Wiklund, Fredrik, Xu, Jianfeng, Hua Zhao, Jing, Nyholt, Dale R, Pellikka, Niina, Perola, Markus, Perry, John RB, Surakka, Ida, Tammesoo, Mari-Liis, Altmaier, Elizabeth L, Amin, Najaf, Aspelund, Thor, Bhangale, Tushar, Boucher, Gabrielle, Chasman, Daniel I, Chen, Constance, Coin, Lachlan, Cooper, Matthew N, Dixon, Anna L, Gibson, Quince, Grundberg, Elin, Hao, Ke, Juhani Junttila, M, Kaplan, Lee M, Kettunen, Johannes, König, Inke R, Kwan, Tony, Lawrence, Robert W, Levinson, Douglas F, Lorentzon, Mattias, McKnight, Barbara, Morris, Andrew P, Müller, Martina, Suh Ngwa, Julius, Purcell, Shaun, Rafelt, Suzanne, Salem, Rany M, and Salvi, Erika

Subjects
Biological Sciences, Genetics, Health Sciences, Mathematical Sciences, Statistics, Human Genome, Clinical Research, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Body Height, Chromosomes, Human, Pair 3, Genetic Loci, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Metabolic Networks and Pathways, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, General Science & Technology
Abstract

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P

Published
2010

45. A common variant in the telomerase RNA component is associated with short telomere length.

Author

Njajou, Omer T, Blackburn, Elizabeth H, Pawlikowska, Ludmila, Mangino, Massimo, Damcott, Coleen M, Kwok, Pui-Yan, Spector, Timothy D, Newman, Anne B, Harris, Tamara B, Cummings, Steven R, Cawthon, Richard M, Shuldiner, Alan R, Valdes, Ana M, and Hsueh, Wen-Chi

Subjects
Telomere, Humans, Osteoporosis, Telomerase, RNA, Cohort Studies, Body Composition, Aging, Twins, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, European Continental Ancestry Group, Female, Male, Genetic Variation, Young Adult, Polymorphism, Single Nucleotide, and over, General Science & Technology
Abstract

BackgroundTelomeres shorten as cells divide. This shortening is compensated by the enzyme telomerase. We evaluated the effect of common variants in the telomerase RNA component (TERC) gene on telomere length (TL) in the population-based Health Aging and Body Composition (Health ABC) Study and in two replication samples (the TwinsUK Study and the Amish Family Osteoporosis Study, AFOS).MethodologyFive variants were identified in the TERC region by sequence analysis and only one SNP was common (rs2293607, G/A). The frequency of the G allele was 0.26 and 0.07 in white and black, respectively. Testing for association between TL and rs2293607 was performed using linear regression models or variance component analysis conditioning on relatedness among subjects.ResultsThe adjusted mean TL was significantly shorter in 665 white carriers of the G allele compared to 887 non-carriers from the Health ABC Study (4.69±0.05 kbp vs. 4.86±0.04 kbp, measured by quantitative PCR, p = 0.005). This association was replicated in another white sample from the TwinsUK Study (6.90±0.03 kbp in 301 carriers compared to 7.06±0.03 kbp in 395 non-carriers, measured by Southern blots, p = 0.009). A similar pattern of association was observed in whites from the family-based AFOS and blacks from the Health ABC cohort, although not statistically significant, possibly due to the lower allele frequency in these populations. Combined analysis using 2,953 white subjects from 3 studies showed a significant association between TL and rs2293607 (β = -0.19±0.04 kbp, p = 0.001).ConclusionOur study shows a significant association between a common variant in TERC and TL in humans, suggesting that TERC may play a role in telomere homeostasis.

Published
2010

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