Artigo Acesso aberto Revisado por pares

The CODATwins Project: The Cohort Description of Collaborative Project of Development of Anthropometrical Measures in Twins to Study Macro-Environmental Variation in Genetic and Environmental Effects on Anthropometric Traits

2015; Cambridge University Press; Volume: 18; Issue: 4 Linguagem: Inglês

10.1017/thg.2015.29

ISSN

1839-2628

Autores

Karri Silventoinen, Aline Jelenkovic, Reijo Sund, Chika Honda, Sari Aaltonen, Yoshie Yokoyama, Ádám Domonkos Tárnoki, Dávid László Tárnoki, Feng Ning, Fuling Ji, Zengchang Pang, Juan R. Ordoñana, Juan F. Sánchez-Romera, Lucía Colodro‐Conde, S. Alexandra Burt, Kelly L. Klump, Sarah E. Medland, Grant W. Montgomery, Christian Kandler, Tom A. McAdams, Thalia C. Eley, Alice M. Gregory, Kimberly J. Saudino, Lise Dubois, Michel Boivin, Claire M. A. Haworth, Robert Plomin, Sevgi Yurt Öncel, Fazil Alıev, Maria Antonietta Stazi, Corrado Fagnani, Cristina D’Ippolito, Jeffrey M. Craig, Richard Saffery, Sisira Siribaddana, Matthew Hotopf, Athula Sumathipala, Timothy D. Spector, Massimo Mangino, Geneviève Lachance, Margaret Gatz, David A. Butler, Gombojav Bayasgalan, Narandalai Danshiitsoodol, Duarte Freitas, José Maia, K. Paige Harden, Elliot M. Tucker‐Drob, Kaare Christensen, Axel Skytthe, Kirsten Ohm Kyvik, Chang-Hee Hong, Young-Sook Chong, Cathérine Derom, Robert Vlietinck, Ruth J. F. Loos, Wendy Cozen, Amie E. Hwang, Thomas M. Mack, Mingguang He, Xiaohu Ding, Billy Chang, Judy L. Silberg, Lindon J. Eaves, Hermine H. Maes, Tessa L. Cutler, John L. Hopper, Kelly Aujard, Patrik K. E. Magnusson, Nancy L. Pedersen, Anna K. Dahl Aslan, Yun‐Mi Song, Sarah Yang, Kayoung Lee, Laura A. Baker, Catherine Tuvblad, Morten Bjerregaard-Andersen, Henning Beck‐Nielsen, Morten Sodemann, Kauko Heikkilä, Qihua Tan, Dongfeng Zhang, Gary E. Swan, Ruth E. Krasnow, Kerry L. Jang, Ariel Knafo‐Noam, David Mankuta, Lior Abramson, Paul Lichtenstein, Robert F. Krueger, Matt McGue, Shandell Pahlen, Per Tynelius, Glen E. Duncan, Dedra Buchwald, Robin P. Corley, Brooke M. Huibregtse, Tracy L. Nelson, Keith E. Whitfield, Carol E. Franz, William S. Kremen, Michael J. Lyons, Syuichi Ooki, Ingunn Brandt, Thomas Sevenius Nilsen, Fujio Inui, Mikio Watanabe, Meike Bartels, C.E.M. van Beijsterveldt, Jane Wardle, Clare Llewellyn, Abigail Fisher, Esther Rebato, Nicholas G. Martin, Yoshinori Iwatani, Kazuo Hayakawa, Finn Rasmussen, Joohon Sung, Jennifer R. Harris, Gonneke Willemsen, Andreas Busjahn, Jack Goldberg, Dorret I. Boomsma, Yoon-Mi Hur, Thorkild I. A. Sørensen, Jaakko Kaprio,

Tópico(s)

Genetics and Physical Performance

Resumo

For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m 2 ) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.

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