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1. Genome-wide associations for birth weight and correlations with adult disease

Author

Horikoshi, Momoko, Beaumont, Robin N, Day, Felix R, Warrington, Nicole M, Kooijman, Marjolein N, Fernandez-Tajes, Juan, Feenstra, Bjarke, van Zuydam, Natalie R, Gaulton, Kyle J, Grarup, Niels, Bradfield, Jonathan P, Strachan, David P, Li-Gao, Ruifang, Ahluwalia, Tarunveer S, Kreiner, Eskil, Rueedi, Rico, Lyytikäinen, Leo-Pekka, Cousminer, Diana L, Wu, Ying, Thiering, Elisabeth, Wang, Carol A, Have, Christian T, Hottenga, Jouke-Jan, Vilor-Tejedor, Natalia, Joshi, Peter K, Boh, Eileen Tai Hui, Ntalla, Ioanna, Pitkänen, Niina, Mahajan, Anubha, van Leeuwen, Elisabeth M, Joro, Raimo, Lagou, Vasiliki, Nodzenski, Michael, Diver, Louise A, Zondervan, Krina T, Bustamante, Mariona, Marques-Vidal, Pedro, Mercader, Josep M, Bennett, Amanda J, Rahmioglu, Nilufer, Nyholt, Dale R, Ma, Ronald Ching Wan, Tam, Claudia Ha Ting, Tam, Wing Hung, CHARGE Consortium Hematology Working Group, Ganesh, Santhi K, van Rooij, Frank Ja, Jones, Samuel E, Loh, Po-Ru, Ruth, Katherine S, Tuke, Marcus A, Tyrrell, Jessica, Wood, Andrew R, Yaghootkar, Hanieh, Scholtens, Denise M, Paternoster, Lavinia, Prokopenko, Inga, Kovacs, Peter, Atalay, Mustafa, Willems, Sara M, Panoutsopoulou, Kalliope, Wang, Xu, Carstensen, Lisbeth, Geller, Frank, Schraut, Katharina E, Murcia, Mario, van Beijsterveldt, Catharina Em, Willemsen, Gonneke, Appel, Emil VR, Fonvig, Cilius E, Trier, Caecilie, Tiesler, Carla Mt, Standl, Marie, Kutalik, Zoltán, Bonas-Guarch, Sílvia, Hougaard, David M, Sánchez, Friman, Torrents, David, Waage, Johannes, Hollegaard, Mads V, de Haan, Hugoline G, Rosendaal, Frits R, Medina-Gomez, Carolina, Ring, Susan M, Hemani, Gibran, McMahon, George, Robertson, Neil R, Groves, Christopher J, Langenberg, Claudia, Luan, Jian'an, Scott, Robert A, Zhao, Jing Hua, Mentch, Frank D, MacKenzie, Scott M, Reynolds, Rebecca M, Early Growth Genetics (EGG) Consortium, Lowe, William L, Tönjes, Anke, Stumvoll, Michael, and Lindi, Virpi

Subjects
Adult, Male, Aging, Genotype, General Science & Technology, Datasets as Topic, Blood Pressure, Coronary Artery Disease, Low Birth Weight and Health of the Newborn, CHARGE Consortium Hematology Working Group, Cohort Studies, Genomic Imprinting, Fetus, Early Growth Genetics (EGG) Consortium, Preterm, Clinical Research, Infant Mortality, Diabetes Mellitus, Genetics, Humans, Birth Weight, Insulin, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Obesity, Aetiology, Nutrition, Pediatric, Anthropometry, Prevention, Human Genome, Genetic Variation, Perinatal Period - Conditions Originating in Perinatal Period, Chromatin Assembly and Disassembly, Glucose, Phenotype, Genetic Loci, Female, Type 2, Glycogen, Signal Transduction, Genome-Wide Association Study
Abstract

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P

Published
2016

2. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Author

Warrington, Nicole M, Beaumont, Robin N, Horikoshi, Momoko, Day, Felix R, Helgeland, Øyvind, Laurin, Charles, Bacelis, Jonas, Peng, Shouneng, Hao, Ke, Feenstra, Bjarke, Wood, Andrew R, Mahajan, Anubha, Tyrrell, Jessica, Robertson, Neil R, Rayner, N William, Qiao, Zhen, Moen, Gunn-Helen, Vaudel, Marc, Marsit, Carmen J, Chen, Jia, Nodzenski, Michael, Schnurr, Theresia M, Zafarmand, Mohammad H, Bradfield, Jonathan P, Grarup, Niels, Kooijman, Marjolein N, Li-Gao, Ruifang, Geller, Frank, Ahluwalia, Tarunveer S, Paternoster, Lavinia, Rueedi, Rico, Huikari, Ville, Hottenga, Jouke-Jan, Lyytikäinen, Leo-Pekka, Cavadino, Alana, Metrustry, Sarah, Cousminer, Diana L, Wu, Ying, Thiering, Elisabeth, Wang, Carol A, Have, Christian T, Vilor-Tejedor, Natalia, Joshi, Peter K, Painter, Jodie N, Ntalla, Ioanna, Myhre, Ronny, Pitkänen, Niina, Van Leeuwen, Elisabeth M, Joro, Raimo, Lagou, Vasiliki, Richmond, Rebecca C, Espinosa, Ana, Barton, Sheila J, Inskip, Hazel M, Holloway, John W, Santa-Marina, Loreto, Estivill, Xavier, Ang, Wei, Marsh, Julie A, Reichetzeder, Christoph, Marullo, Letizia, Hocher, Berthold, Lunetta, Kathryn L, Murabito, Joanne M, Relton, Caroline L, Kogevinas, Manolis, Chatzi, Leda, Allard, Catherine, Bouchard, Luigi, Hivert, Marie-France, Zhang, Ge, Muglia, Louis J, Heikkinen, Jani, EGG Consortium, Morgen, Camilla S, Van Kampen, Antoine HC, Van Schaik, Barbera DC, Mentch, Frank D, Langenberg, Claudia, Luan, Jian'an, Scott, Robert A, Zhao, Jing Hua, Hemani, Gibran, Ring, Susan M, Bennett, Amanda J, Gaulton, Kyle J, Fernandez-Tajes, Juan, Van Zuydam, Natalie R, Medina-Gomez, Carolina, De Haan, Hugoline G, Rosendaal, Frits R, Kutalik, Zoltán, Marques-Vidal, Pedro, Das, Shikta, Willemsen, Gonneke, Mbarek, Hamdi, Müller-Nurasyid, Martina, Standl, Marie, Appel, Emil VR, Fonvig, Cilius E, Trier, Caecilie, Van Beijsterveldt, Catharina EM, Murcia, Mario, Bustamante, Mariona, Bonas-Guarch, Sílvia, Hougaard, David M, Mercader, Josep M, Linneberg, Allan, Schraut, Katharina E, Lind, Penelope A, Medland, Sarah E, Shields, Beverley M, Knight, Bridget A, Chai, Jin-Fang, Panoutsopoulou, Kalliope, Bartels, Meike, Sánchez, Friman, Stokholm, Jakob, Torrents, David, Vinding, Rebecca K, Willems, Sara M, Atalay, Mustafa, Chawes, Bo L, Kovacs, Peter, Prokopenko, Inga, Tuke, Marcus A, Yaghootkar, Hanieh, Ruth, Katherine S, Jones, Samuel E, Loh, Po-Ru, Murray, Anna, Weedon, Michael N, Tönjes, Anke, Stumvoll, Michael, Michaelsen, Kim F, Eloranta, Aino-Maija, Lakka, Timo A, Van Duijn, Cornelia M, Kiess, Wieland, Körner, Antje, Niinikoski, Harri, Pahkala, Katja, Raitakari, Olli T, Jacobsson, Bo, Zeggini, Eleftheria, Dedoussis, George V, Teo, Yik-Ying, Saw, Seang-Mei, Montgomery, Grant W, Campbell, Harry, Wilson, James F, Vrijkotte, Tanja GM, Vrijheid, Martine, De Geus, Eco JCN, Hayes, M Geoffrey, Kadarmideen, Haja N, Holm, Jens-Christian, Beilin, Lawrence J, Pennell, Craig E, Heinrich, Joachim, Adair, Linda S, Borja, Judith B, Mohlke, Karen L, Eriksson, Johan G, Widén, Elisabeth E, Hattersley, Andrew T, Spector, Tim D, Kähönen, Mika, Viikari, Jorma S, Lehtimäki, Terho, Boomsma, Dorret I, Sebert, Sylvain, Vollenweider, Peter, Sørensen, Thorkild IA, Bisgaard, Hans, Bønnelykke, Klaus, Murray, Jeffrey C, Melbye, Mads, Nohr, Ellen A, Mook-Kanamori, Dennis O, Rivadeneira, Fernando, Hofman, Albert, Felix, Janine F, Jaddoe, Vincent WV, Hansen, Torben, Pisinger, Charlotta, Vaag, Allan A, Pedersen, Oluf, Uitterlinden, André G, Järvelin, Marjo-Riitta, Power, Christine, Hyppönen, Elina, Scholtens, Denise M, Lowe, William L, Davey Smith, George, Timpson, Nicholas J, Morris, Andrew P, Wareham, Nicholas J, Hakonarson, Hakon, Grant, Struan FA, Frayling, Timothy M, Lawlor, Debbie A, Njølstad, Pål R, Johansson, Stefan, Ong, Ken K, McCarthy, Mark I, Perry, John RB, Evans, David M, and Freathy, Rachel M

Subjects
Adult, Male, Heart Diseases, Models, Genetic, Infant, Newborn, Blood Pressure, Polymorphism, Single Nucleotide, Body Height, 3. Good health, Fetal Development, Diabetes Mellitus, Type 2, Metabolic Diseases, Pregnancy, Risk Factors, Birth Weight, Humans, Female, Genetic Predisposition to Disease, Maternal Inheritance, Maternal-Fetal Exchange, Genome-Wide Association Study
Abstract

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

3. Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes

Author

Bonàs-Guarch, Sílvia, Guindo-Martínez, Marta, Miguel-Escalada, Irene, Grarup, Niels, Sebastian, David, Rodriguez-Fos, Elias, Sánchez, Friman, Planas-Fèlix, Mercè, Cortes-Sánchez, Paula, González, Santi, Timshel, Pascal, Pers, Tune H, Morgan, Claire C, Moran, Ignasi, Atla, Goutham, González, Juan R, Puiggros, Montserrat, Martí, Jonathan, Andersson, Ehm A, Díaz, Carlos, Badia, Rosa M, Udler, Miriam, Leong, Aaron, Kaur, Varindepal, Flannick, Jason, Jørgensen, Torben, Linneberg, Allan, Jørgensen, Marit E, Witte, Daniel R, Christensen, Cramer, Brandslund, Ivan, Appel, Emil V, Scott, Robert A, Luan, Jian'an, Langenberg, Claudia, Wareham, Nicholas J, Pedersen, Oluf, Zorzano, Antonio, Florez, Jose C, Hansen, Torben, Ferrer, Jorge, Mercader, Josep Maria, and Torrents, David

Subjects
Male, Chromosomes, Human, X, Genotype, Models, Genetic, Risk Factors, Humans, Gene Regulatory Networks, Genetic Predisposition to Disease, Insulin Resistance, Polymorphism, Single Nucleotide, Alleles, 3. Good health, Genome-Wide Association Study
Abstract

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches.

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