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22 results on '"Min, Jin"'

1. Heritability and genomics of gene expression in peripheral blood

Author

Wright, Fred A, Sullivan, Patrick F, Brooks, Andrew I, Zou, Fei, Sun, Wei, Xia, Kai, Madar, Vered, Jansen, Rick, Chung, Wonil, Zhou, Yi-Hui, Abdellaoui, Abdel, Batista, Sandra, Butler, Casey, Chen, Guanhua, Chen, Ting-Huei, D'Ambrosio, David, Gallins, Paul, Ha, Min Jin, Hottenga, Jouke Jan, Huang, Shunping, Kattenberg, Mathijs, Kochar, Jaspreet, Middeldorp, Christel M, Qu, Ani, Shabalin, Andrey, Tischfield, Jay, Todd, Laura, Tzeng, Jung-Ying, van Grootheest, Gerard, Vink, Jacqueline M, Wang, Qi, Wang, Wei, Wang, Weibo, Willemsen, Gonneke, Smit, Johannes H, de Geus, Eco J, Yin, Zhaoyu, Penninx, Brenda WJH, and Boomsma, Dorret I

Subjects
Biotechnology, Human Genome, Genetics, Blood, Gene Expression Profiling, Gene Expression Regulation, Genotype, Humans, Inheritance Patterns, Likelihood Functions, Netherlands, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTLs) in peripheral blood. The most highly heritable genes (∼777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function or ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic identity-by-descent sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which we further examined in a replication set of 1,895 unrelated subjects. A large number of non-redundant local eQTLs (6,756) met replication criteria, whereas a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide a new resource toward understanding the genetic control of transcription.

Published
2014

2. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marilyn C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex SF, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Groop, Leif C, Groves, Christopher J, Grundberg, Elin, Guiducci, Candace, Hamsten, Anders, Han, Bok-Ghee, Hara, Kazuo, and Hassanali, Neelam

Subjects
Biological Sciences, Genetics, Human Genome, Diabetes, Metabolic and endocrine, Alleles, Asian People, Case-Control Studies, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Genome-Wide Association Study, Hispanic or Latino, Humans, Polymorphism, Single Nucleotide, Risk Factors, White People, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Published
2014

3. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

Author

DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Mahajan, Anubha, Go, Min Jin, Zhang, Weihua, Below, Jennifer E, Gaulton, Kyle J, Ferreira, Teresa, Horikoshi, Momoko, Johnson, Andrew D, Ng, Maggie CY, Prokopenko, Inga, Saleheen, Danish, Wang, Xu, Zeggini, Eleftheria, Abecasis, Goncalo R, Adair, Linda S, Almgren, Peter, Atalay, Mustafa, Aung, Tin, Baldassarre, Damiano, Balkau, Beverley, Bao, Yuqian, Barnett, Anthony H, Barroso, Ines, Basit, Abdul, Been, Latonya F, Beilby, John, Bell, Graeme I, Benediktsson, Rafn, Bergman, Richard N, Boehm, Bernhard O, Boerwinkle, Eric, Bonnycastle, Lori L, Burtt, Noël, Cai, Qiuyin, Campbell, Harry, Carey, Jason, Cauchi, Stephane, Caulfield, Mark, Chan, Juliana CN, Chang, Li-Ching, Chang, Tien-Jyun, Chang, Yi-Cheng, Charpentier, Guillaume, Chen, Chien-Hsiun, Chen, Han, Chen, Yuan-Tsong, Chia, Kee-Seng, Chidambaram, Manickam, Chines, Peter S, Cho, Nam H, Cho, Young Min, Chuang, Lee-Ming, Collins, Francis S, Cornelis, Marylin C, Couper, David J, Crenshaw, Andrew T, van Dam, Rob M, Danesh, John, Das, Debashish, de Faire, Ulf, Dedoussis, George, Deloukas, Panos, Dimas, Antigone S, Dina, Christian, Doney, Alex S, Donnelly, Peter J, Dorkhan, Mozhgan, van Duijn, Cornelia, Dupuis, Josée, Edkins, Sarah, Elliott, Paul, Emilsson, Valur, Erbel, Raimund, Eriksson, Johan G, Escobedo, Jorge, Esko, Tonu, Eury, Elodie, Florez, Jose C, Fontanillas, Pierre, Forouhi, Nita G, Forsen, Tom, Fox, Caroline, Fraser, Ross M, Frayling, Timothy M, Froguel, Philippe, Frossard, Philippe, Gao, Yutang, Gertow, Karl, Gieger, Christian, Gigante, Bruna, Grallert, Harald, Grant, George B, Grrop, Leif C, and Groves, Chrisropher J

Subjects
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, South Asian Type 2 Diabetes (SAT2D) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Factors, Case-Control Studies, Polymorphism, Single Nucleotide, Alleles, Asian Continental Ancestry Group, European Continental Ancestry Group, Hispanic Americans, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Polymorphism, Single Nucleotide, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Published
2014

4. Meta-analysis identifies multiple loci associated with kidney function–related traits in east Asian populations

Author

Okada, Yukinori, Sim, Xueling, Go, Min Jin, Wu, Jer-Yuarn, Gu, Dongfeng, Takeuchi, Fumihiko, Takahashi, Atsushi, Maeda, Shiro, Tsunoda, Tatsuhiko, Chen, Peng, Lim, Su-Chi, Wong, Tien-Yin, Liu, Jianjun, Young, Terri L, Aung, Tin, Seielstad, Mark, Teo, Yik-Ying, Kim, Young Jin, Lee, Jong-Young, Han, Bok-Ghee, Kang, Daehee, Chen, Chien-Hsiun, Tsai, Fuu-Jen, Chang, Li-Ching, Fann, S-J Cathy, Mei, Hao, Rao, Dabeeru C, Hixson, James E, Chen, Shufeng, Katsuya, Tomohiro, Isono, Masato, Ogihara, Toshio, Chambers, John C, Zhang, Weihua, Kooner, Jaspal S, Albrecht, Eva, Yamamoto, Kazuhiko, Kubo, Michiaki, Nakamura, Yusuke, Kamatani, Naoyuki, Kato, Norihiro, He, Jiang, Chen, Yuan-Tsong, Cho, Yoon Shin, Tai, E-Shyong, and Tanaka, Toshihiro

Subjects
Biological Sciences, Genetics, Kidney Disease, Human Genome, Renal and urogenital, Asian People, Blood Urea Nitrogen, Cohort Studies, Creatinine, Genetic Predisposition to Disease, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, Kidney, Polymorphism, Single Nucleotide, Renal Insufficiency, Chronic, Uric Acid, KidneyGen Consortium, CKDGen Consortium, GUGC consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Chronic kidney disease (CKD), impairment of kidney function, is a serious public health problem, and the assessment of genetic factors influencing kidney function has substantial clinical relevance. Here, we report a meta-analysis of genome-wide association studies for kidney function-related traits, including 71,149 east Asian individuals from 18 studies in 11 population-, hospital- or family-based cohorts, conducted as part of the Asian Genetic Epidemiology Network (AGEN). Our meta-analysis identified 17 loci newly associated with kidney function-related traits, including the concentrations of blood urea nitrogen, uric acid and serum creatinine and estimated glomerular filtration rate based on serum creatinine levels (eGFRcrea) (P < 5.0 × 10(-8)). We further examined these loci with in silico replication in individuals of European ancestry from the KidneyGen, CKDGen and GUGC consortia, including a combined total of ∼110,347 individuals. We identify pleiotropic associations among these loci with kidney function-related traits and risk of CKD. These findings provide new insights into the genetics of kidney function.

Published
2012

5. Genome sequencing reveals evidence of adaptive variation in the genus Zea

Author

Lu Chen, Jingyun Luo, Minliang Jin, Ning Yang, Xiangguo Liu, Yong Peng, Wenqiang Li, Alyssa Phillips, Brenda Cameron, Julio S. Bernal, Rubén Rellán-Álvarez, Ruairidh J. H. Sawers, Qing Liu, Yuejia Yin, Xinnan Ye, Jiali Yan, Qinghua Zhang, Xiaoting Zhang, Shenshen Wu, Songtao Gui, Wenjie Wei, Yuebin Wang, Yun Luo, Chenglin Jiang, Min Deng, Min Jin, Liumei Jian, Yanhui Yu, Maolin Zhang, Xiaohong Yang, Matthew B. Hufford, Alisdair R. Fernie, Marilyn L. Warburton, Jeffrey Ross-Ibarra, and Jianbing Yan

Subjects
Plant Breeding, Base Sequence, Genetics, Genetic Variation, Zea mays, Adaptation, Physiological, Alleles
Abstract

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.

Published
2022

6. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

Tazeen H. Jafar, Lars Lind, Peter Almgren, Wendy Winckler, Eitaro Nakashima, Young Min Cho, Annette Peters, Rona J. Strawbridge, Ananda R. Wickremasinghe, Katharine R. Owen, Lee-Ming Chuang, Tien-Jyun Chang, Graeme I. Bell, James B. Meigs, Bill Musk, Timo A. Lakka, Elin Grundberg, Wei Lu, Sarah Edkins, George Dedoussis, Weiping Jia, Danish Saleheen, Suthesh Sivapalaratnam, Maria Samuel, Tien Yin Wong, Lu Qi, Pierre Fontanillas, Momoko Horikoshi, Jirong Long, Abdul Basit, Anubha Mahajan, Andrew T. Hattersley, Markus M. Nöthen, Denis Rybin, Inger Njølstad, S. Krithika, Miguel Cruz, Delilah Zabaneh, Leena Peltonen, Jasmina Kravic, Sangsoo Kim, David Couper, Lori L. Bonnycastle, Heather M. Stringham, Yi-Cheng Chang, Paul Elliott, Eric J.G. Sijbrands, Nita G. Forouhi, Alena Stančáková, Ghazala Mirza, Robert W. Lawrence, Ruth J. F. Loos, Norman Klopp, Shiro Maeda, Martina Müller-Nurasyid, Jer-Yuarn Wu, Jianjun Liu, Kee Seng Chia, Elodie Eury, Loukianos S. Rallidis, Timothy M. Frayling, Ken Yamamoto, David Altshuler, Gunnar Sigurosson, Harald Grallert, Jackie F. Price, Barbara Thorand, Jouko Saramies, Malene M. Kristensen, Sonali Pechlivanis, Inês Barroso, Jong-Young Lee, Melissa Parkin, Josée Dupuis, Stéphane Lobbens, Jesús Kumate, Elena Tremoli, Sudhir Kowlessur, Xueling Sim, Norihiro Kato, Philippe Froguel, Kathleen Stirrups, Eero Lindholm, Alex S. F. Doney, Andres Metspalu, Yu-Tang Gao, Roman Wennauer, Xiao-Ou Shu, Marilyn C. Cornelis, Veikko Salomaa, Nanette R. Lee, Johanna Kuusisto, Caroline S. Fox, Man Li, James Scott, Wing-Yee So, Andrew R. Wood, Inga Prokopenko, Oddgeir L. Holmen, Tin Aung, Ryoichi Takayanagi, Chen Suo, Hara Kazuo, Carl G. P. Platou, Ann M. Kelly, Teresa Ferreira, Karl-Heinz Jöckel, Wei-Yen Lim, James F. Wilson, Tom Forsén, Qi Sun, Valur Emilsson, Gonçalo R. Abecasis, Fan Zhang, Timo Saaristo, Harry Campbell, Ying Wu, Mark Seielstad, Wei Zheng, Han Chen, Stavroula Kanoni, Yuqian Bao, Jose C. Florez, Wan Ting Tay, Ronald C. WMa, Gerald Steinbach, Min Jin Go, Rong Zhang, Junbin Liang, Vasiliki Lagou, Leif Groop, Emil Rehnberg, Nabi Shah, Weihua Zhang, Yun Li, Bengt Sennblad, Olle Melander, Nancy L. Pedersen, Muhammed Islam, Jaakko Tuomilehto, Young Jin Kim, Richard N. Bergman, Juliana C.N. Chan, Eleftheria Zeggini, Andrew D. Johnson, Kees Hovingh, Joban Sehmi, Rainer Rauramaa, Satu Männistö, Reedik Mägi, Samuel Liju, Mingyu Yang, Ayellet V. Segrè, Noël P. Burtt, Mozhgan Dorkhan, Beverley Balkau, Neelam Hassanali, Hyun Min Kang, Fabrizio Veglia, Eeva Korpi-Hyövälti, Loic Yengo, Elizabeth J. Rossin, Angela Silveira, Maggie C.Y. Ng, Yuan-Tsong Chen, Anders Hamsten, David R. Matthews, Mark J. Caulfield, Emmi Tikkanen, Tanya M. Teslovich, John R. B. Perry, Karen L. Mohlke, Sarah E. Hunt, Soo Heon Kwak, Jorge Escobedo, Christopher J. Groves, Ulf de Faire, Jeremy B M Jowett, Gudmar Thorleifsson, Michael Roden, Evelin Mihailov, Viswanathan Mohan, Craig L. Hanis, Thomas WMühleisen, Congrong Wang, Sonia Shah, Kyle J. Gaulton, Jaspal S. Kooner, Jiro Nakamura, Mustafa Atalay, Linda S. Adair, S Wiltshire, Tõnu Esko, Anna Jonsson, Antigone S. Dimas, Karin Leander, Li Ching Chang, George B. Grant, Bo Isomaa, Anne U. Jackson, Claudia Langenberg, Kristian Hveem, Yoon Shin Cho, Astradur B. Hreidarsson, Xu Wang, Keizo Ohnaka, Alexandra C. Nica, Simon D. Rees, Pau Navarro, Sekar Kathiresan, Rob M. van Dam, Zafar I. Hydrie, Bok Ghee Han, Francis S. Collins, Fuu Jen Tsai, Unnur Thorsteinsdottir, Ross M. Fraser, Caroline Hayward, Cornelia M. van Duijn, Samuli Ripatti, Mieke D. Trip, Hyung Lae Kim, Rafn Benediktsson, Candace Guiducci, Bruna Gigante, Kyong Soo Park, Wen Hong L. Kao, Tom Wilsgaard, Leena Kinnunen, John Danesh, Alan James, Alan R. Shuldiner, Mitsuhiro Yokota, Jen Mai Lee, Kari Stefansson, Erik Ingelsson, Colin N. A. Palmer, David J. Hunter, Paul Zimmet, Manickam Chidambaram, Sirkka Keinänen-Kiukaanniemi, Laura J. Scott, Susanne Moebus, Benjamin F. Voight, Wolfgang Rathmann, Hassan Khan, Thomas Illig, Prasad Katulanda, Christian Gieger, Andrew D. Morris, Yik Ying Teo, Andrew P. Morris, Venkatesan Radha, N. William Rayner, Johan G. Eriksson, Christian Dina, Igor Rudan, Sailaja Vedantam, Cheng Hu, James S. Pankow, Ann-Christine Syvänen, Karl Gertow, Valeriya Lyssenko, Guillaume Charpentier, Albert Hofman, Chiea Chuen Khor, Joseph Trakalo, Peter Kraft, Takashi Kadowaki, Qiuyin Cai, John C. Chambers, André G. Uitterlinden, Simon C. Potter, Nicholas J. Wareham, Soumya Raychaudhuri, Jian'an Luan, Tiinamaija Tuomi, Anthony H. Barnett, Juha Saltevo, Robert A. Scott, Valgerdur Steinthorsdottir, Peng Keat Ng, Mark I. McCarthy, Åsa K. Hedman, Kerrin S. Small, Julia Meyer, Frank B. Hu, Cecilia M. Lindgren, Jennifer E. Below, Nancy J. Cox, Jennie Hui, Andrew Crenshaw, Latonya F. Been, Nam H. Cho, Janani Pinidiyapathirage, A. Samad Shera, Bernhard OBoehm, Jason Carey, Augustine Kong, Twee Hee Ong, Philippe M. Frossard, Donald W. Bowden, Toshimasa Yamauchi, Steve E. Humphries, Cordelia Langford, Xinzhong Li, Hiroshi Ikegami, Stéphane Cauchi, Ching-Ti Liu, Michael Boehnke, Peter M. Nilsson, Debashish Das, John Beilby, Robin Young, Christian Herder, Asif Rasheed, Neil Robertson, Raimund Erbel, Fumihiko Takeuchi, Markku Laakso, Esteban J. Parra, Panos Deloukas, Eric Boerwinkle, Adan Valladares-Salgado, Chien-Hsiun Chen, Kay-Tee Khaw, Damiano Baldassarre, Ashok Kumar, E. Shyong Tai, Peter S. Chines, Dharambir KSanghera, Peter Donnelly, [ 1 ] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England [ 2 ] Natl Inst Hlth, Ctr Genome Sci, Gangoe Myeon, Yeonje Ri, South Korea [ 3 ] Univ London Imperial Coll Sci Technol & Med, London, England [ 4 ] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA [ 5 ] Univ Oxford, Oxford Ctr Diabet Endocrinol & Metab, Oxford OX1 2JD, England [ 6 ] NHLBI, Framingham Heart Study, Framingham, MA USA [ 7 ] Wake Forest Sch Med, Ctr Genom & Personalized Med Res, Winston Salem, NC USA [ 8 ] Wake Forest Sch Med, Ctr Diabet Res, Winston Salem, NC USA [ 9 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, London, England [ 10 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Cambridge, England [ 11 ] Ctr Noncommunicable Dis Pakistan, Karachi, Pakistan [ 12 ] Natl Univ Singapore, Dept Epidemiol & Publ Hlth, Singapore 117548, Singapore [ 13 ] Wellcome Trust Sanger Inst, Cambridge, England [ 14 ] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA [ 15 ] Univ N Carolina, Dept Nutr, Chapel Hill, NC USA [ 16 ] Lund Univ, Scania Univ Hosp, Dept Clin Sci Malmo, Ctr Diabet, Malmo, Sweden [ 17 ] Univ Eastern Finland, Inst Biomed, Kuopio, Finland [ 18 ] Singapore Natl Eye Ctr, Singapore Eye Res Inst, Singapore, Singapore [ 19 ] Natl Univ Singapore, Dept Ophthalmol, Singapore 117548, Singapore [ 20 ] IRCCS, Ctr Cardiol Monzino, Milan, Italy [ 21 ] Univ Milan, Dept Pharmacol Sci, Milan, Italy [ 22 ] INSERM, Ctr Rech Epidemiol & Sante Populat CESP, U1018, Villejuif, France [ 23 ] Univ Paris 11, UMRS 1018, Villejuif, France [ 24 ] Shanghai Jiao Tong Univ, Affiliated Peoples Hosp 6, Dept Endocrinol & Metab, Shanghai Key Lab Diabet Mellitus,Shanghai Diabet, Shanghai 200030, Peoples R China [ 25 ] Univ Birmingham, Coll Med & Dent Sci, Birmingham, W Midlands, England [ 26 ] Heart England Natl Hlth Serv NHS Fdn Trust, Ctr Biomed Res, Birmingham, W Midlands, England [ 27 ] Univ Cambridge, Addenbrookes Hosp, Metab Res Labs, Inst Metab Sci, Cambridge CB2 2QQ, England [ 28 ] Addenbrookes Hosp, Inst Metab Sci, Cambridge Biomed Res Ctr, Natl Inst Hlth Res, Cambridge, England [ 29 ] Baqai Inst Diabetol & Endocrinol, Karachi, Pakistan [ 30 ] Univ Oklahoma, Hlth Sci Ctr, Coll Med, Dept Pediat,Sect Genet, Oklahoma City, OK 73190 USA [ 31 ] Sir Charles Gairdner Hosp, Busselton Populat Med Res Inst, Nedlands, WA 6009, Australia [ 32 ] Queen Elizabeth II Med Ctr, PathWest Lab Med Western Australia, Nedlands, WA, Australia [ 33 ] Univ Western Australia, Sch Pathol & Lab Med, Nedlands, WA 6009, Australia [ 34 ] Univ Chicago, Dept Med, Chicago, IL 60637 USA [ 35 ] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA [ 36 ] Univ Iceland, Fac Med, Reykjavik, Iceland [ 37 ] Landspitali Univ Hosp, Reykjavik, Iceland [ 38 ] Cedars Sinai Med Ctr, Diabet & Obes Res Inst, Los Angeles, CA 90048 USA [ 39 ] Univ Med Ctr Ulm, Div Endocrinol & Diabet, Dept Internal Med, Ulm, Germany [ 40 ] Nanyang Technol Univ, Lee Kong Chian LKC Sch Med, Singapore 639798, Singapore [ 41 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 42 ] Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA [ 43 ] NHGRI, NIH, Bethesda, MD 20892 USA [ 44 ] Broad Inst Harvard & Massachusetts Inst Technol M, Cambridge, MA USA [ 45 ] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Canc Ctr, Vanderbilt Epidemiol Ctr,Dept Med, Nashville, TN 37212 USA [ 46 ] Univ Edinburgh, Ctr Populat Hlth Sci, Edinburgh, Midlothian, Scotland [ 47 ] Univ Edinburgh, Western Gen Hosp, MRC, Inst Genet & Mol Med, Edinburgh, Midlothian, Scotland [ 48 ] CNRS, Unite Mixte Rech UMR 8199, Inst Biol, Lille, France [ 49 ] Univ Lille 2, Inst Pasteur, Lille, France [ 50 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, London, England [ 51 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, Barts & London Genome Ctr, London, England [ 52 ] Chinese Univ Hong Kong, Prince Wales Hosp, Dept Med & Therapeut, Hong Kong, Hong Kong, Peoples R China [ 53 ] Acad Sinica, Inst Biomed Sci, Taipei, Taiwan [ 54 ] Natl Taiwan Univ Hosp, Dept Internal Med, Taipei 100, Taiwan [ 55 ] Corbeil Essonnes Hosp, Endocrinol Diabetol Unit, Corbeil Essonnes, France [ 56 ] China Med Univ, Sch Chinese Med, Taichung, Taiwan [ 57 ] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA USA [ 58 ] Natl Univ Singapore, Ctr Mol Epidemiol, Singapore 117548, Singapore [ 59 ] Indian Council Med Res, Adv Ctr Genom Diabet, Madras Diabet Res Fdn, Dept Mol Genet, Madras, Tamil Nadu, India [ 60 ] Ajou Univ, Sch Med, Dept Prevent Med, Suwon 441749, South Korea [ 61 ] Seoul Natl Univ, Coll Med, Dept Internal Med, Seoul 151, South Korea [ 62 ] Natl Taiwan Univ, Sch Med, Grad Inst Clin Med, Taipei 10764, Taiwan [ 63 ] Harvard Univ, Sch Publ Hlth, Dept Nutr & Epidemiol, Boston, MA 02115 USA [ 64 ] Univ N Carolina, Dept Biostat, Collaborat Studies Coordinating Ctr, Chapel Hill, NC USA [ 65 ] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117548, Singapore [ 66 ] Ealing Hosp NHS Trust, Southall, Middx, England [ 67 ] Karolinska Inst, Inst Environm Med, Divis Cardiovasc Epidemiol, S-10401 Stockholm, Sweden [ 68 ] Harokopio Univ, Dept Dietet Nutr, Athens, Greece [ 69 ] Univ Geneva, Sch Med, Dept Genet Med & Dev, CH-1211 Geneva, Switzerland [ 70 ] Biomed Sci Res Ctr Alexander Fleming, Vari, Greece [ 71 ] INSERM, UMR 1087, Nantes, France [ 72 ] CNRS, UMR 6291, Nantes, France [ 73 ] Univ Nantes, Nantes, France [ 74 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Diabet Res Ctr, Dundee, Scotland [ 75 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Pharmacogen Ctr, Dundee, Scotland [ 76 ] Univ Oxford, Dept Stat, Oxford OX1 3TG, England [ 77 ] Erasmus Univ, Med Ctr, Dept Epidemiol, Rotterdam, Netherlands [ 78 ] Netherlands Consortium Healthy Ageing, Netherland Genom Initiat, Rotterdam, Netherlands [ 79 ] Ctr Med Syst Biol, Rotterdam, Netherlands [ 80 ] Univ London Imperial Coll Sci Technol & Med, MRC, Hlth Protect Agcy, Ctr Environm & Hlth, London, England [ 81 ] Iceland Heart Assoc, Kopavogur, Iceland [ 82 ] Univ Duisburg Essen, Univ Hosp Essen, West German Heart Ctr, Clin Cardiol, Essen, Germany [ 83 ] Natl Inst Hlth & Welf, Dept Chron Dis Prevent, Helsinki, Finland [ 84 ] Univ Helsinki, Dept Gen Practice & Primary Hlth Care, Helsinki, Finland [ 85 ] Univ Helsinki, Gen Hosp, Unit Gen Practice, Helsinki, Finland [ 86 ] Folkhalsan Res Ctr, Helsinki, Finland [ 87 ] Inst Mexicano Seguro Social, Hosp Gen Reg 1, Unidad Invest Epidemiol Clin, Mexico City, DF, Mexico [ 88 ] Univ Tartu, Estonian Genome Ctr, EE-50090 Tartu, Estonia [ 89 ] Univ Tartu, Inst Mol & Cell Biol, EE-50090 Tartu, Estonia [ 90 ] Broad Inst, Program Med & Populat Genet, Cambridge, MA USA [ 91 ] Childrens Hosp, Div Genet & Endocrinol, Boston, MA 02115 USA [ 92 ] Harvard Univ, Sch Med, Dept Med, Boston, MA USA [ 93 ] Massachusetts Gen Hosp, Ctr Human Genet Res, Boston, MA 02114 USA [ 94 ] Massachusetts Gen Hosp, Diabet Res Ctr, Diabet Unit, Boston, MA 02114 USA [ 95 ] Addenbrookes Hosp, Inst Metab Sci, MRC, Epidemiol Unit, Cambridge, England [ 96 ] Vaasa Hlth Care Ctr, Vaasa, Finland [ 97 ] Brigham & Womens Hosp, Div Endocrinol & Metab, Boston, MA 02115 USA [ 98 ] Harvard Univ, Sch Med, Boston, MA USA [ 99 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 100 ] Shanghai Canc Inst, Dept Epidemiol, Shanghai, Peoples R China [ 101 ] Karolinska Inst, Dept Med Solna, Atherosclerosis Res Unit, Stockholm, Sweden [ 102 ] Karolinska Univ, Hosp Solna, Ctr Mol Med, Stockholm, Sweden [ 103 ] Helmholtz Zentrum Muenchen, Inst Genet Epidemiol, Neuherberg, Germany [ 104 ] Helmholtz Zentrum Muenchen, Res Unit Mol Epidemiol, Neuherberg, Germany [ 105 ] Univ Munich, Clin Cooperat Grp Diabet, Munich, Germany [ 106 ] Helmholtz Zentrum Muenchen, Munich, Germany [ 107 ] Tech Univ Munich, Clin Cooperat Grp Nutrigen & Type Diabet 2, Munich, Germany [ 108 ] German Ctr Diabet Res DZD, Neuherberg, Germany [ 109 ] Kings Coll London, Dept Twin Res & Genet Epidemiol, London, England [ 110 ] Univ Tokyo, Grad Sch Med, Dept Diabet & Metab Dis, Tokyo, Japan [ 111 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 112 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Clin Diabetol, Dusseldorf, Germany [ 113 ] Norwegian Univ Sci & Technol, Dept Publ Hlth & Gen Practice, HUNT Res Ctr, Levanger, Norway [ 114 ] Univ Amsterdam, Acad Med Ctr, Dept Vasc Med, NL-1105 AZ Amsterdam, Netherlands [ 115 ] Brigham & Womens Hosp, Dept Med, Channing Lab, Boston, MA USA [ 116 ] Univ Western Australia, Sch Populat Hlth, Nedlands, WA 6009, Australia [ 117 ] UCL, Inst Cardiovasc Sci, London, England [ 118 ] Harvard Univ, Sch Publ Hlth, Program Mol & Genet Epidemiol, Boston, MA 02115 USA [ 119 ] Kinki Univ, Sch Med, Dept Diabet Endocrinol & Metab, Osaka 589, Japan [ 120 ] Hannover Med Sch, Hannover Unified Biobank, Hannover, Germany [ 121 ] Univ Uppsala Hosp, Dept Mol Sci, Mol Epidemiol & Sci Life Lab, Uppsala, Sweden [ 122 ] Aga Khan Univ, Dept Community Hlth Sci, Karachi, Pakistan [ 123 ] Dept Social Serv & Hlth Care, Pietarsaari, Finland [ 124 ] Aga Khan Univ, Dept Med, Karachi, Pakistan [ 125 ] Queen Elizabeth II Med Ctr, West Australian Sleep Disorders Res Inst, Dept Pulm Physiol & Sleep Med, Nedlands, WA, Australia [ 126 ] Univ Western Australia, Sch Med & Pharmacol, Nedlands, WA 6009, Australia [ 127 ] Univ Hosp Essen, Inst Med Informat Biometry & Epidemiol, Essen, Germany [ 128 ] Heart & Diabet Inst, Baker Int Diabet Inst IDI, Melbourne, Australia [ 129 ] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA [ 130 ] Massachusetts Gen Hosp, Cardiovasc Res Ctr, Boston, MA 02114 USA [ 131 ] Natl Ctr Global Hlth & Med, Res Inst, Shinjuku Ku, Tokyo, Japan [ 132 ] Univ Colombo, Dept Clin Med, Diabet Res Unit, Colombo, Sri Lanka [ 133 ] Univ Oulu, Inst Hlth Sci, Fac Med, Oulu, Finland [ 134 ] Oulu Univ Hosp, Unit Gen Practice, Oulu, Finland [ 135 ] Agcy Sci Technol & Res, Genome Inst Singapore, Singapore, Singapore [ 136 ] Ewha Womans Univ, Sch Med, Dept Biochem, Seoul, South Korea [ 137 ] Soongsil Univ, Sch Syst Biomed Sci, Seoul, South Korea [ 138 ] Natl Inst Hlth & Welf, Diabet Prevent Unit, Helsinki, Finland [ 139 ] deCODE Genet, Reykjavik, Iceland [ 140 ] South Ostrobothnia Cent Hosp, Seinajoki, Finland [ 141 ] Minist Hlth, Port Louis, Mauritius [ 142 ] Univ Toronto, Dept Anthropol, Mississauga, ON L5L 1C6, Canada [ 143 ] Fdn IMSS, Mexico City, DF, Mexico [ 144 ] Univ Eastern Finland, Dept Med, Kuopio, Finland [ 145 ] Kuopio Univ Hosp, SF-70210 Kuopio, Finland [ 146 ] Kuopio Res Inst Exercise Med, Kuopio, Finland [ 147 ] Univ Western Australia, Ctr Genet Epidemiol & Biostat, Nedlands, WA 6009, Australia [ 148 ] Univ San Carlos, Off Populat Studies Fdn Inc, Cebu, Philippines [ 149 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, Natl Heart & Lung Inst, London, England [ 150 ] Univ N Carolina, Dept Genet, Chapel Hill, NC USA [ 151 ] Univ N Carolina, Dept Biostat, Chapel Hill, NC USA [ 152 ] Beijing Genom Inst, Shenzhen, Peoples R China [ 153 ] Uppsala Univ, Akad Sjukhuset, Dept Med Sci, Uppsala, Sweden [ 154 ] Mt Sinai Sch Med, Charles R Bronfman Inst Personalized Med, New York, NY USA [ 155 ] Mt Sinai Sch Med, Child Hlth & Dev Inst, New York, NY USA [ 156 ] Mt Sinai Sch Med, Dept Prevent Med, New York, NY USA [ 157 ] Shanghai Inst Prevent Med, Shanghai, Peoples R China [ 158 ] Massachusetts Gen Hosp, Div Gen Med, Boston, MA 02114 USA [ 159 ] Dr Mohans Diabet Specialties Ctr, Madras, Tamil Nadu, India [ 160 ] Univ Bonn, Inst Human Genet, Bonn, Germany [ 161 ] Univ Bonn, Life & Brain Ctr, Dept Genom, Bonn, Germany [ 162 ] Univ Munich, Chair Genet Epidemiol, Inst Med Informat Biometry & Epidemiol, Munich, Germany [ 163 ] Univ Munich, Univ Hosp Grosshadern, Dept Med 1, Munich, Germany [ 164 ] Sir Charles Gairdner Hosp, Nedlands, WA 6009, Australia [ 165 ] Nagoya Univ, Grad Sch Med, Div Endocrinol & Diabet, Dept Internal Med, Nagoya, Aichi 4648601, Japan [ 166 ] Chubu Rosai Hosp, Dept Endocrinol & Diabet, Nagoya, Aichi, Japan [ 167 ] Univ Tromso, Fac Hlth Sci, Dept Community Med, Tromso, Norway [ 168 ] Kyushu Univ, Grad Sch Med Sci, Dept Geriatr Med, Higashi Ku, Fukuoka 812, Japan [ 169 ] Churchill Hosp, Hlth Res Biomed Res Ctr, Oxford Natl Inst, Oxford OX3 7LJ, England [ 170 ] Univ Minnesota, Div Epidemiol & Community Hlth, Minneapolis, MN USA [ 171 ] Seoul Natl Univ, Grad Sch Convergence Sci & Technol, Dept Mol Med & Biopharmaceut Sci, World Class Univ Program, Seoul, South Korea [ 172 ] Seoul Natl Univ, Coll Med, Seoul, South Korea [ 173 ] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden [ 174 ] Inst Mol Med Finland FIMM, Helsinki, Finland [ 175 ] Helmholtz Zentrum Muenchen, Inst Epidemiol 2, Neuherberg, Germany [ 176 ] Univ Kelaniya, Fac Med, Dept Publ Hlth, Ragama, Sri Lanka [ 177 ] Nord Trondelag Hlth Trust, Levanger Hosp, Dept Internal Med, Levanger, Norway [ 178 ] Univ Gen Hosp Attikon, Athens, Greece [ 179 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Biometr & Epidemiol, Dusseldorf, Germany [ 180 ] Kuopio Univ Hosp, Dept Clin Physiol & Nucl Med, SF-70210 Kuopio, Finland [ 181 ] Harvard Univ, Brigham & Womens Hosp, Sch Med, Div Rheumatol Immunol & Allergy, Boston, MA 02115 USA [ 182 ] Partners Ctr Personalized Genom Med, Boston, MA USA [ 183 ] Univ Dusseldorf, Dept Endocrinol & Diabetol, Dusseldorf, Germany [ 184 ] Univ Dusseldorf, Dept Metab Dis, Dusseldorf, Germany [ 185 ] Harvard Univ, Hlth Sci & Technol MD Program, Boston, MA 02115 USA [ 186 ] MIT, Boston, MA USA [ 187 ] Harvard Univ, Harvard Biol & Biomed Sci Program, Boston, MA 02115 USA [ 188 ] Boston Univ, Data Coordinating Ctr, Boston, MA 02215 USA [ 189 ] Finnish Diabet Assoc, Tampere, Finland [ 190 ] Pirkanmaa Hosp Dist, Tampere, Finland [ 191 ] Cent Finland Cent Hosp, Dept Med, Jyvaskyla, Finland [ 192 ] South Karelia Cent Hosp, Lappeenranta, Finland [ 193 ] UCL, Dept Genet Evolut & Environm, Genet Inst, London, England [ 194 ] Diabet Assoc Pakistan, Karachi, Pakistan [ 195 ] Univ Maryland, Sch Med, Div Endocrinol Diabet & Nutr, Baltimore, MD 21201 USA [ 196 ] Baltimore Vet Adm Med Ctr, Geriatr Res Educ & Clin Ctr, Baltimore, MD USA [ 197 ] Univ Maryland, Sch Med, Program Personalised & Genom Med, Baltimore, MD 21201 USA [ 198 ] Erasmus Univ, Med Ctr, Dept Internal Med, Rotterdam, Netherlands [ 199 ] Univ Ulm, Dept Clin Chem, D-89069 Ulm, Germany [ 200 ] Univ Ulm, Cent Lab, D-89069 Ulm, Germany [ 201 ] Uppsala Univ, Dept Med Sci, Uppsala, Sweden [ 202 ] Kyushu Univ, Grad Sch Med Sci, Dept Internal Med & Bioregulatory Sci, Higashi Ku, Fukuoka 812, Japan [ 203 ] Univ Helsinki, Helsinki Univ Hosp, Dept Med, Helsinki, Finland [ 204 ] Hosp Univ LaPaz IdiPAZ, Inst Invest Sanitaria, Madrid, Spain [ 205 ] Danube Univ Krems, Ctr Vasc Prevent, Krems, Austria [ 206 ] King Abdulaziz Univ, Diabet Res Grp, Jeddah 21413, Saudi Arabia [ 207 ] IMSS, Ctr Med Nacl Siglo 21, Hosp Especialidades, Unidad Invest Med Bioquim, Mexico City, DF, Mexico [ 208 ] Univ Penn, Perelman Sch Med, Dept Pharmacol, Philadelphia, PA 19104 USA [ 209 ] Univ Melbourne, Ctr Eye Res Australia, East Melbourne, Vic, Australia [ 210 ] Kyushu Univ, Med Inst Bioregulat, Res Ctr Genet Informat, Div Genome Anal,Higashi Ku, Fukuoka 812, Japan [ 211 ] Univ Lille 1, Math Lab, CNRS UMR 8524, MODAL Team,INRIA Lille Nord Europe, F-59655 Villeneuve Dascq, France [ 212 ] Aichi Gakuin Univ, Sch Dent, Dept Genome Sci, Nagoya, Aichi 464, Japan [ 213 ] Harvard Univ, Sch Med, Dept Genet, Boston, MA USA [ 214 ] Harvard Univ, Sch Med, Dept Mol Biol, Boston, MA USA [ 215 ] Massachusetts Gen Hosp, Diabet Unit, Boston, MA 02114 USA [ 216 ] Wake Forest Sch Med, Dept Biochem, Winston Salem, NC USA [ 217 ] Wake Forest Sch Med, Dept Internal Med, Winston Salem, NC USA [ 218 ] Hallym Univ, Dept Biomed Sci, Chunchon, Gangwon Do, South Korea [ 219 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 220 ] Imperial Coll Healthcare NHS Trust, London, England [ 221 ] Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA [ 222 ] Blood Syst Res Inst, San Francisco, CA USA [ 223 ] Natl Univ Singapore, Grad Sch Integrat Sci & Engn, Singapore 117548, Singapore [ 224 ] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117548, Singapore [ 225 ] Natl Univ Singapore, Dept Med, Singapore 117548, Singapore [ 226 ] Duke Natl Univ Singapore, Grad Sch Med, Singapore, Singapore [ 227 ] Univ Liverpool, Dept Biostat, Liverpool L69 3BX, Merseyside, England, Obstetrics & Gynecology, Radiology & Nuclear Medicine, Surgery, Epidemiology, Dermatology, Internal Medicine, Medical Microbiology & Infectious Diseases, Medical Research Council (MRC), National Institute for Health Research, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, and Cardiology

Subjects
CHROMATIN, endocrine system diseases, South Asian Type 2 Diabetes (SAT2D) Consortium, SCALE ASSOCIATION ANALYSIS, Medizin, LOCI, Genome-wide association study, VARIANTS, 0302 clinical medicine, Risk Factors, IMPUTATION, Glucose homeostasis, 11 Medical and Health Sciences, Genetics & Heredity, Genetics, 0303 health sciences, IDENTIFY, Hispanic or Latino, 3. Good health, MAP, POPULATIONS, Medical genetics, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Hispanic Americans, Life Sciences & Biomedicine, Asian Continental Ancestry Group, medicine.medical_specialty, European Continental Ancestry Group, TRANSETHNIC METAANALYSIS, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, White People, Sykursýki, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, Allele, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, Alleles, 030304 developmental biology, Genetic association, Science & Technology, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, 06 Biological Sciences, Arfgengi, Genetic architecture, INDIVIDUALS, Diabetes Mellitus, Type 2, Case-Control Studies, GLUCOSE-HOMEOSTASIS, ASSOCIATION ANALYSES, Imputation (genetics), Developmental Biology, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article click on the hyperlink at the bottom of the page To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry. Canadian Institutes of Health Research Medical Research Council UK G0601261 Mexico Convocatoria SSA/IMMS/ISSSTE-CONACYT 2012-2 clave 150352 IMSS R-2011-785-018 CONACYT Salud-2007-C01-71068 US National Institutes of Health DK062370 HG000376 DK085584 DK085545 DK073541 DK085501 Wellcome Trust WT098017 WT090532 WT090367 WT098381 WT081682 WT085475 info:eu-repo/grantAgreement/EC/FP7/201413

Published
2014

7. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

Author

Bok Ghee Han, Congrong Wang, Wing-Yee So, Ying Wu, Rong Zhang, Xueling Sim, Norihiro Kato, Eitaro Nakashima, Qiuyin Cai, Tien-Jyun Chang, Jiro Nakamura, Wei Lu, Mark Seielstad, Yu-Tang Gao, Juliana C.N. Chan, Fumihiko Takeuchi, Jer-Yuarn Wu, Lee-Ming Chuang, Young Min Cho, Hyung Lae Kim, Yik Ying Teo, Andrew P. Morris, Nam H. Cho, Daniel P.K. Ng, Rick Twee-Hee Ong, Cheng Hu, Kyong Soo Park, Sangsoo Kim, Shiro Maeda, Toshimasa Yamauchi, Fuu Jen Tsai, Yoon Shin Cho, Hiroshi Ikegami, Ronald C.W. Ma, Jirong Long, Ken Yamamoto, Yi-Cheng Chang, Xiao-Ou Shu, Karen L. Mohlke, Wei Zheng, Mitsuhiro Yokota, Soo Heon Kwak, Yuan-Tsong Chen, Chien Hsiun Chen, Linda S. Adair, Yun Li, Nanette R. Lee, Young-Jin Kim, Jeannette Lee, Li Ching Chang, Keizo Ohnaka, Ryoichi Takayanagi, Min Jin Go, Wan Ting Tay, Jianjun Liu, Tin Aung, Jong-Young Lee, Hara Kazuo, Yuqian Bao, Weiping Jia, Tien Yin Wong, E. Shyong Tai, Takashi Kadowaki, Mark I. McCarthy, Åsa K. Hedman, and Frank B. Hu

Subjects
Genetics, endocrine system, education.field_of_study, endocrine system diseases, PEPD, Population, Case-control study, Genome-wide association study, Type 2 diabetes, Biology, medicine.disease, Polymorphism (computer science), Diabetes mellitus, medicine, education, Genetic association
Abstract

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression, is known for its association with fasting glucose levels. The evidence of an association with T2D for PEPD and HNF4A has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D.

Published
2011

8. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians

Author

Masato Isono, Toshio Ogihara, Rick Twee-Hee Ong, Toru Nabika, Jiang He, Shotai Kobayashi, Min Jin Go, Sung Soo Kim, Xueling Sim, Norihiro Kato, Fumihiko Takeuchi, Mitsuhiro Yokota, Jong-Young Lee, Yasuharu Tabara, Xuegong Zhang, Dingliang Zhu, Mark Seielstad, Naoharu Iwai, Tien Yin Wong, Tin Aung, Wei Huang, Dongfeng Gu, Yun Ju Sung, Bok Ghee Han, Tomohiro Katsuya, Ryoichi Takayanagi, Xueya Zhou, Yuan-Tsong Chen, Tanika N. Kelly, Yoshihiro Kokubo, Li Ching Chang, Wan Ting Tay, Jer-Yuarn Wu, Yoon Shin Cho, Keizo Ohnaka, Cashell E. Jaquish, Young-Jin Kim, Jianjun Liu, Tetsuro Miki, Ken Yamamoto, E. Shyong Tai, Chien Hsiun Chen, Yik Ying Teo, Eitaro Nakashima, James E. Hixson, Takao Sugiyama, Yi Zhang, Yukio Yamori, and Jae Pil Jeon

Subjects
Genetics, Asia, Eastern, Systole, Hemodynamics, Blood Pressure, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, White People, Blood pressure, Asian People, Gene Frequency, Diastole, Polymorphism (computer science), Meta-analysis, Humans, cardiovascular diseases, Allele frequency, Genotyping, circulatory and respiratory physiology, Genome-Wide Association Study, Genetic association
Abstract

We conducted a meta-analysis of genome-wide association studies of systolic (SBP) and diastolic (DBP) blood pressure in 19,608 subjects of east Asian ancestry from the AGEN-BP consortium followed up with de novo genotyping (n = 10,518) and further replication (n = 20,247) in east Asian samples. We identified genome-wide significant (P < 5 × 10(-8)) associations with SBP or DBP, which included variants at four new loci (ST7L-CAPZA1, FIGN-GRB14, ENPEP and NPR3) and a newly discovered variant near TBX3. Among the five newly discovered variants, we obtained significant replication in the independent samples for all of these loci except NPR3. We also confirmed seven loci previously identified in populations of European descent. Moreover, at 12q24.13 near ALDH2, we observed strong association signals (P = 7.9 × 10(-31) and P = 1.3 × 10(-35) for SBP and DBP, respectively) with ethnic specificity. These findings provide new insights into blood pressure regulation and potential targets for intervention.

Published
2011

9. Meta-analysis identifies common variants associated with body mass index in east Asians

Author

Jong-Young Lee, Yasuharu Tabara, Tin Aung, Mei Hao, Yong-Bing Xiang, Li Ching Chang, Xueling Sim, Norihiro Kato, Fuu Jen Tsai, Yoon Shin Cho, Qiuyin Cai, Gary K. Chen, Tatsuhiko Tsunoda, Yanling Hu, Tien Yin Wong, Dingliang Zhu, Fumihiko Takeuchi, Dongfeng Gu, Mark Seielstad, Chun Li, Mitsuhiro Yokota, Naoharu Iwai, Yi Zhang, Brian E. Henderson, Yukinori Okada, Yusuke Nakamura, Christopher A. Haiman, Lu Qi, Wanqing Wen, Min Jin Go, Shiro Maeda, E. Shyong Tai, Loic Le Marchand, Frank B. Hu, Seang-Mei Saw, Xiao-Ou Shu, Yu Tang Gao, Wei Lu, Aihua Tan, Ken Yamamoto, Zengnan Mo, Jianjun Liu, Chien Hsiun Chen, Bok Ghee Han, Michiaki Kubo, Jiajun Shi, Wei Zheng, Naoyuki Kamatani, Toshihiro Tanaka, Rick Twee-Hee Ong, Jiang He, Jirong Long, Daniel P.K. Ng, Huai-Dong Song, Jianfeng Xu, Cathy S.J. Fann, Yoshihiro Kokubo, Jer-Yuarn Wu, Jun Liang, Mei Hsin Su, Ryan J. Delahanty, Rajkumar Dorajoo, and Tetsuro Miki

Subjects
Genotype, Quantitative Trait Loci, 030209 endocrinology & metabolism, Genome-wide association study, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, Body Mass Index, 03 medical and health sciences, 0302 clinical medicine, Asian People, Polymorphism (computer science), Genetics, medicine, Humans, Genetic Predisposition to Disease, Obesity, CDKAL1, 030304 developmental biology, Genetic association, 2. Zero hunger, 0303 health sciences, Asia, Eastern, medicine.disease, Body mass index, Genome-Wide Association Study
Abstract

Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We performed a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 east Asians, which was followed by in silico and de novo replication studies in 37,691 and 17,642 additional east Asians, respectively. We identified ten BMI-associated loci at genome-wide significance (P < 5.0 × 10(-8)), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR-QPCTL, ADCY3-DNAJC27, BDNF and MAP2K5) and three novel loci in or near the CDKAL1, PCSK1 and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a newly identified signal near PAX6, all of which were associated with BMI with P < 5.0 × 10(-7). Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations.

Published
2011

10. Large-scale genome-wide association studies in East Asians identify new genetic loci influencing metabolic traits

Author

Eun Jung Hong, Ji Hyun Kim, Taesung Park, Bok Ghee Han, Naoyuki Kamatani, Joo Yeon Hwang, Chang Bum Hong, Hyung Lae Kim, Yun Kyoung Kim, Nam H. Cho, Cheng Hu, Rong Zhang, Ji Hee Oh, Atsushi Takahashi, Young-Jin Kim, Haesook Min, Koichi Matsuda, Min Jin Go, Yoon Shin Cho, Jong-Young Lee, Yukinori Okada, Ji-Young Lee, Nam Hee Kim, Daehee Kang, Kuchan Kimm, Bermseok Oh, Soeui Kim, Toshihiro Tanaka, Yeonjung Kim, Weiping Jia, Dong Joon Kim, Chol Shin, and Michiaki Kubo

Subjects
Adult, Blood Glucose, Linkage disequilibrium, China, Genotyping Techniques, Quantitative Trait Loci, Genome-wide association study, Quantitative trait locus, Biology, Genome, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Cohort Studies, Asian People, Japan, Polymorphism (computer science), Republic of Korea, Genetics, Humans, Genetic Predisposition to Disease, Aged, Genome, Human, Cholesterol, HDL, Case-control study, Cholesterol, LDL, Fasting, Middle Aged, Biobank, Phenotype, Gene Expression Regulation, Case-Control Studies, Genome-Wide Association Study
Abstract

To identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery meta-analysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall meta-analysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study.

Published
2010

11. Common variants at CDKAL1 and KLF9 are associated with body mass index in east Asian populations

Author

Atsushi Takahashi, Kazuhiko Yamamoto, Rajkumar Dorajoo, Yusuke Nakamura, Naoya Hosono, Min Jin Go, Tatsuhiko Tsunoda, Norihiro Kato, Naoyuki Kamatani, Toshihiro Tanaka, Michiaki Kubo, Yukinori Okada, Shiro Maeda, Hiroko Ohmiya, Wanqing Wen, Qi Lu, Wei Zheng, Jer-Yuarn Wu, and Natsuhiko Kumasaka

Subjects
Genotype, Kruppel-Like Transcription Factors, Locus (genetics), Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, Body Mass Index, Asian People, Genetic variation, Genetics, medicine, SNP, Humans, Obesity, CDKAL1, tRNA Methyltransferases, Asia, Eastern, Genetic Variation, Cyclin-Dependent Kinase 5, medicine.disease, TRNA Methyltransferases, Chromosomes, Human, Pair 6, Chromosomes, Human, Pair 9, Body mass index, Genome-Wide Association Study
Abstract

Obesity is a disorder with a complex genetic etiology, and its epidemic is a worldwide problem. Although multiple genetic loci associated with body mass index, the most common measure of obesity, have been identified in European populations, few studies have focused on Asian populations. Here we report a genome-wide association study and replication studies with 62,245 east Asian subjects, which identified two new body mass index-associated loci in the CDKAL1 locus at 6p22 (rs2206734, P = 1.4 × 10(-11)) and the KLF9 locus at 9q21 (rs11142387, P = 1.3 × 10(-9)), as well as several previously reported loci (the SEC16B, BDNF, FTO, MC4R and GIPR loci, P < 5.0 × 10(-8)). We subsequently performed gene-gene interaction analyses and identified an interaction (P = 2.0 × 10(-8)) between a SNP in the KLF9 locus (rs11142387) and one in the MSTN (also known as GDF8) locus at 2q32 (rs13034723). These findings should provide useful insights into the etiology of obesity.

Published
2010

12. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits

Author

Jong-Young Lee, Seung Hun Cha, Nam H. Cho, Young-Jin Kim, Dong Joon Kim, Dankyu Yoon, Yoon Shin Cho, Taesung Park, Bok Ghee Han, Ji Wan Park, Man Suk Park, Jun Woo Kim, Bermseok Oh, Hye Ree Han, Hye Yoon Jang, Miey Park, Jee Yeon Heo, Eunyoung Cho, Mark I. McCarthy, Lon R. Cardon, Haesook Min, Jong Koo Lee, Jong Eun Lee, Hyung Lae Kim, Ji Hee Oh, Geraldine M. Clarke, Younjhin Ahn, Jong-Keuk Lee, Chol Shin, Min Jin Go, Hyo Jeong Ban, and Mi-Hee Lee

Subjects
Adult, Genotype, Population, Quantitative Trait Loci, Population genetics, Genome-wide association study, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Body Mass Index, Cohort Studies, Asian People, Bone Density, Genetics, Humans, Genetic Predisposition to Disease, education, Gene, Aged, education.field_of_study, Genome, Human, Waist-Hip Ratio, Chromosome, Middle Aged, Human genome, Genome-Wide Association Study
Abstract

To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 x 10(-9)) and 6q22 (rs12110693, P = 1.6 x 10(-9)), with the latter approximately 400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 x 10(-7)). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 x 10(-12)) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 x 10(-11)), tibia (P = 1.6 x 10(-6)) and heel (P = 1.9 x 10(-10)). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 x 10(-3), P = 1.4 x 10(-7) and P = 6.0 x 10(-4), respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways.

Published
2009

13. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians

Author

Kato, Norihiro, primary, Takeuchi, Fumihiko, additional, Tabara, Yasuharu, additional, Kelly, Tanika N, additional, Go, Min Jin, additional, Sim, Xueling, additional, Tay, Wan Ting, additional, Chen, Chien-Hsiun, additional, Zhang, Yi, additional, Yamamoto, Ken, additional, Katsuya, Tomohiro, additional, Yokota, Mitsuhiro, additional, Kim, Young Jin, additional, Ong, Rick Twee Hee, additional, Nabika, Toru, additional, Gu, Dongfeng, additional, Chang, Li-ching, additional, Kokubo, Yoshihiro, additional, Huang, Wei, additional, Ohnaka, Keizo, additional, Yamori, Yukio, additional, Nakashima, Eitaro, additional, Jaquish, Cashell E, additional, Lee, Jong-Young, additional, Seielstad, Mark, additional, Isono, Masato, additional, Hixson, James E, additional, Chen, Yuan-Tsong, additional, Miki, Tetsuro, additional, Zhou, Xueya, additional, Sugiyama, Takao, additional, Jeon, Jae-Pil, additional, Liu, Jian Jun, additional, Takayanagi, Ryoichi, additional, Kim, Sung Soo, additional, Aung, Tin, additional, Sung, Yun Ju, additional, Zhang, Xuegong, additional, Wong, Tien Yin, additional, Han, Bok-Ghee, additional, Kobayashi, Shotai, additional, Ogihara, Toshio, additional, Zhu, Dingliang, additional, Iwai, Naoharu, additional, Wu, Jer-Yuarn, additional, Teo, Yik Ying, additional, Tai, E Shyong, additional, Cho, Yoon Shin, additional, and He, Jiang, additional

Published
2011
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14. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits

Author

Cho, Yoon Shin, primary, Go, Min Jin, additional, Kim, Young Jin, additional, Heo, Jee Yeon, additional, Oh, Ji Hee, additional, Ban, Hyo-Jeong, additional, Yoon, Dankyu, additional, Lee, Mi Hee, additional, Kim, Dong-Joon, additional, Park, Miey, additional, Cha, Seung-Hun, additional, Kim, Jun-Woo, additional, Han, Bok-Ghee, additional, Min, Haesook, additional, Ahn, Younjhin, additional, Park, Man Suk, additional, Han, Hye Ree, additional, Jang, Hye-Yoon, additional, Cho, Eun Young, additional, Lee, Jong-Eun, additional, Cho, Nam H, additional, Shin, Chol, additional, Park, Taesung, additional, Park, Ji Wan, additional, Lee, Jong-Keuk, additional, Cardon, Lon, additional, Clarke, Geraldine, additional, McCarthy, Mark I, additional, Lee, Jong-Young, additional, Lee, Jong-Koo, additional, Oh, Bermseok, additional, and Kim, Hyung-Lae, additional

Published
2009
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15. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders.

Author

den Hoed, Marcel, Eijgelsheim, Mark, Esko, Tõnu, Brundel, Bianca J J M, Peal, David S, Evans, David M, Nolte, Ilja M, Segrè, Ayellet V, Holm, Hilma, Handsaker, Robert E, Westra, Harm-Jan, Johnson, Toby, Isaacs, Aaron, Yang, Jian, Lundby, Alicia, Zhao, Jing Hua, Kim, Young Jin, Go, Min Jin, Almgren, Peter, and Bochud, Murielle

Subjects
HEART beat, CARDIOVASCULAR diseases, DANIO, DROSOPHILA melanogaster
Abstract

Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets. [ABSTRACT FROM AUTHOR]

Published
2013
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16. Meta-analysis identifies common variants associated with body mass index in east Asians.

Author

Wen, Wanqing, Cho, Yoon-Shin, Zheng, Wei, Dorajoo, Rajkumar, Kato, Norihiro, Qi, Lu, Chen, Chien-Hsiun, Delahanty, Ryan J, Okada, Yukinori, Tabara, Yasuharu, Gu, Dongfeng, Zhu, Dingliang, Haiman, Christopher A, Mo, Zengnan, Gao, Yu-Tang, Saw, Seang-Mei, Go, Min-Jin, Takeuchi, Fumihiko, Chang, Li-Ching, and Kokubo, Yoshihiro

Subjects
LOCUS (Genetics), BODY mass index, GENOMES, META-analysis
Abstract

Multiple genetic loci associated with obesity or body mass index (BMI) have been identified through genome-wide association studies conducted predominantly in populations of European ancestry. We performed a meta-analysis of associations between BMI and approximately 2.4 million SNPs in 27,715 east Asians, which was followed by in silico and de novo replication studies in 37,691 and 17,642 additional east Asians, respectively. We identified ten BMI-associated loci at genome-wide significance (P < 5.0 × 10?8), including seven previously identified loci (FTO, SEC16B, MC4R, GIPR-QPCTL, ADCY3-DNAJC27, BDNF and MAP2K5) and three novel loci in or near the CDKAL1, PCSK1 and GP2 genes. Three additional loci nearly reached the genome-wide significance threshold, including two previously identified loci in the GNPDA2 and TFAP2B genes and a newly identified signal near PAX6, all of which were associated with BMI with P < 5.0 × 10?7. Findings from this study may shed light on new pathways involved in obesity and demonstrate the value of conducting genetic studies in non-European populations. [ABSTRACT FROM AUTHOR]

Published
2012
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17. Common variants at CDKAL1 and KLF9 are associated with body mass index in east Asian populations.

Author

Okada, Yukinori, Kubo, Michiaki, Ohmiya, Hiroko, Takahashi, Atsushi, Kumasaka, Natsuhiko, Hosono, Naoya, Maeda, Shiro, Wen, Wanqing, Dorajoo, Rajkumar, Go, Min Jin, Zheng, Wei, Kato, Norihiro, Wu, Jer-Yuarn, Lu, Qi, Tsunoda, Tatsuhiko, Yamamoto, Kazuhiko, Nakamura, Yusuke, Kamatani, Naoyuki, and Tanaka, Toshihiro

Subjects
OBESITY, BODY mass index, DNA replication, LOCUS (Genetics), ETIOLOGY of diseases
Abstract

Obesity is a disorder with a complex genetic etiology, and its epidemic is a worldwide problem. Although multiple genetic loci associated with body mass index, the most common measure of obesity, have been identified in European populations, few studies have focused on Asian populations. Here we report a genome-wide association study and replication studies with 62,245 east Asian subjects, which identified two new body mass index-associated loci in the CDKAL1 locus at 6p22 (rs2206734, P = 1.4 × 10?11) and the KLF9 locus at 9q21 (rs11142387, P = 1.3 × 10?9), as well as several previously reported loci (the SEC16B, BDNF, FTO, MC4R and GIPR loci, P < 5.0 × 10?8). We subsequently performed gene-gene interaction analyses and identified an interaction (P = 2.0 × 10?8) between a SNP in the KLF9 locus (rs11142387) and one in the MSTN (also known as GDF8) locus at 2q32 (rs13034723). These findings should provide useful insights into the etiology of obesity. [ABSTRACT FROM AUTHOR]

Published
2012
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18. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians.

Author

Cho, Yoon Shin, Chen, Chien-Hsiun, Hu, Cheng, Long, Jirong, Hee Ong, Rick Twee, Sim, Xueling, Takeuchi, Fumihiko, Wu, Ying, Go, Min Jin, Yamauchi, Toshimasa, Chang, Yi-Cheng, Kwak, Soo Heon, Ma, Ronald C W, Yamamoto, Ken, Adair, Linda S, Aung, Tin, Cai, Qiuyin, Chang, Li-Ching, Chen, Yuan-Tsong, and Gao, Yutang

Subjects
GENETICS of type 2 diabetes, LOCUS (Genetics), META-analysis, EAST Asians, CHROMOSOME replication, PANCREATIC beta cells, GENE expression, DISEASES
Abstract

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression, is known for its association with fasting glucose levels. The evidence of an association with T2D for PEPD and HNF4A has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D. [ABSTRACT FROM AUTHOR]

Published
2012
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19. Large-scale genome-wide association studies in east Asians identify new genetic loci influencing metabolic traits.

Author

Kim, Young Jin, Go, Min Jin, Hu, Cheng, Hong, Chang Bum, Kim, Yun Kyoung, Lee, Ji Young, Hwang, Joo-Yeon, Oh, Ji Hee, Kim, Dong-Joon, Kim, Nam Hee, Kim, Soeui, Hong, Eun Jung, Kim, Ji-Hyun, Min, Haesook, Kim, Yeonjung, Zhang, Rong, Jia, Weiping, Okada, Yukinori, Takahashi, Atsushi, and Kubo, Michiaki

Subjects
*META-analysis, *GENOMICS, *LOCUS (Genetics), *LIPOPROTEINS, *BLOOD plasma
Abstract

To identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery meta-analysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall meta-analysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study. [ABSTRACT FROM AUTHOR]

Published
2011
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20. A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits.

Author

Yoon Shin Cho, Min Jin Go, Young Jin Kim, Jee Yeon Heo, Ji Hee Oh, Hyo-Jeong Ban, Dankyu Yoon, Mi Hee Lee, Dong-Joon Kim, Miey Park, Seung-Hun Cha, Jun-Woo Kim, Bok-Ghee Han, Haesook Min, Younjhin Ahn, Man Suk Park, Hye Ree Han, Hye-Yoon Jang, Eun Young Cho, and Jong-Eun Lee

Subjects
*GENOMICS, *GENOMES, *CHROMOSOMES, *GENE mapping, *GENETIC research
Abstract

To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 × 10−9) and 6q22 (rs12110693, P = 1.6 × 10−9), with the latter ∼400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 × 10−7). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 × 10−12) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 × 10−11), tibia (P = 1.6 × 10−6) and heel (P = 1.9 × 10−10). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 × 10−3, P = 1.4 × 10−7 and P = 6.0 × 10−4, respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways. [ABSTRACT FROM AUTHOR]

Published
2009
Full Text
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21. Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation.

Author

Kato N, Loh M, Takeuchi F, Verweij N, Wang X, Zhang W, Kelly TN, Saleheen D, Lehne B, Leach IM, Drong AW, Abbott J, Wahl S, Tan ST, Scott WR, Campanella G, Chadeau-Hyam M, Afzal U, Ahluwalia TS, Bonder MJ, Chen P, Dehghan A, Edwards TL, Esko T, Go MJ, Harris SE, Hartiala J, Kasela S, Kasturiratne A, Khor CC, Kleber ME, Li H, Yu Mok Z, Nakatochi M, Sapari NS, Saxena R, Stewart AFR, Stolk L, Tabara Y, Teh AL, Wu Y, Wu JY, Zhang Y, Aits I, Da Silva Couto Alves A, Das S, Dorajoo R, Hopewell JC, Kim YK, Koivula RW, Luan J, Lyytikäinen LP, Nguyen QN, Pereira MA, Postmus I, Raitakari OT, Scannell Bryan M, Scott RA, Sorice R, Tragante V, Traglia M, White J, Yamamoto K, Zhang Y, Adair LS, Ahmed A, Akiyama K, Asif R, Aung T, Barroso I, Bjonnes A, Braun TR, Cai H, Chang LC, Chen CH, Cheng CY, Chong YS, Collins R, Courtney R, Davies G, Delgado G, Do LD, Doevendans PA, Gansevoort RT, Gao YT, Grammer TB, Grarup N, Grewal J, Gu D, Wander GS, Hartikainen AL, Hazen SL, He J, Heng CK, Hixson JE, Hofman A, Hsu C, Huang W, Husemoen LLN, Hwang JY, Ichihara S, Igase M, Isono M, Justesen JM, Katsuya T, Kibriya MG, Kim YJ, Kishimoto M, Koh WP, Kohara K, Kumari M, Kwek K, Lee NR, Lee J, Liao J, Lieb W, Liewald DCM, Matsubara T, Matsushita Y, Meitinger T, Mihailov E, Milani L, Mills R, Mononen N, Müller-Nurasyid M, Nabika T, Nakashima E, Ng HK, Nikus K, Nutile T, Ohkubo T, Ohnaka K, Parish S, Paternoster L, Peng H, Peters A, Pham ST, Pinidiyapathirage MJ, Rahman M, Rakugi H, Rolandsson O, Ann Rozario M, Ruggiero D, Sala CF, Sarju R, Shimokawa K, Snieder H, Sparsø T, Spiering W, Starr JM, Stott DJ, Stram DO, Sugiyama T, Szymczak S, Tang WHW, Tong L, Trompet S, Turjanmaa V, Ueshima H, Uitterlinden AG, Umemura S, Vaarasmaki M, van Dam RM, van Gilst WH, van Veldhuisen DJ, Viikari JS, Waldenberger M, Wang Y, Wang A, Wilson R, Wong TY, Xiang YB, Yamaguchi S, Ye X, Young RD, Young TL, Yuan JM, Zhou X, Asselbergs FW, Ciullo M, Clarke R, Deloukas P, Franke A, Franks PW, Franks S, Friedlander Y, Gross MD, Guo Z, Hansen T, Jarvelin MR, Jørgensen T, Jukema JW, Kähönen M, Kajio H, Kivimaki M, Lee JY, Lehtimäki T, Linneberg A, Miki T, Pedersen O, Samani NJ, Sørensen TIA, Takayanagi R, Toniolo D, Ahsan H, Allayee H, Chen YT, Danesh J, Deary IJ, Franco OH, Franke L, Heijman BT, Holbrook JD, Isaacs A, Kim BJ, Lin X, Liu J, März W, Metspalu A, Mohlke KL, Sanghera DK, Shu XO, van Meurs JBJ, Vithana E, Wickremasinghe AR, Wijmenga C, Wolffenbuttel BHW, Yokota M, Zheng W, Zhu D, Vineis P, Kyrtopoulos SA, Kleinjans JCS, McCarthy MI, Soong R, Gieger C, Scott J, Teo YY, He J, Elliott P, Tai ES, van der Harst P, Kooner JS, and Chambers JC

Subjects
Adult, Aged, Aged, 80 and over, Asian People genetics, Cardiovascular Diseases blood, Cardiovascular Diseases ethnology, Cardiovascular Diseases genetics, Female, Genetic Predisposition to Disease ethnology, Genetic Predisposition to Disease genetics, Genetic Variation, Genotype, Humans, Male, Middle Aged, Natriuretic Peptide, Brain blood, Peptide Fragments blood, Polymorphism, Single Nucleotide, Regression Analysis, Risk Factors, White People genetics, Blood Pressure genetics, DNA Methylation, Genetic Loci genetics, Genome-Wide Association Study methods
Abstract

We carried out a trans-ancestry genome-wide association and replication study of blood pressure phenotypes among up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 new loci to be associated with blood pressure (P = 3.9 × 10(-11) to 5.0 × 10(-21)). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that, at some of the loci identified, DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 new loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7 and TBX2) function. The new and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, and cardiovascular and all-cause mortality (P = 0.04 to 8.6 × 10(-6)). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.

Published
2015
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22. Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians.

Author

Cho YS, Chen CH, Hu C, Long J, Ong RT, Sim X, Takeuchi F, Wu Y, Go MJ, Yamauchi T, Chang YC, Kwak SH, Ma RC, Yamamoto K, Adair LS, Aung T, Cai Q, Chang LC, Chen YT, Gao Y, Hu FB, Kim HL, Kim S, Kim YJ, Lee JJ, Lee NR, Li Y, Liu JJ, Lu W, Nakamura J, Nakashima E, Ng DP, Tay WT, Tsai FJ, Wong TY, Yokota M, Zheng W, Zhang R, Wang C, So WY, Ohnaka K, Ikegami H, Hara K, Cho YM, Cho NH, Chang TJ, Bao Y, Hedman ÅK, Morris AP, McCarthy MI, Takayanagi R, Park KS, Jia W, Chuang LM, Chan JC, Maeda S, Kadowaki T, Lee JY, Wu JY, Teo YY, Tai ES, Shu XO, Mohlke KL, Kato N, Han BG, and Seielstad M

Subjects
Adult, Blood Glucose, Case-Control Studies, Chromosome Mapping, Asia, Eastern, Humans, Polymorphism, Single Nucleotide, Asian People genetics, Diabetes Mellitus, Type 2 genetics, Genetic Predisposition to Disease, Genome-Wide Association Study
Abstract

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression, is known for its association with fasting glucose levels. The evidence of an association with T2D for PEPD and HNF4A has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D.

Published
2011
Full Text
View/download PDF

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