IDEAS home Printed from https://ideas.repec.org/a/plo/pgen00/1001363.html
   My bibliography  Save this article

Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia

Author

Listed:
  • Xueling Sim
  • Rick Twee-Hee Ong
  • Chen Suo
  • Wan-Ting Tay
  • Jianjun Liu
  • Daniel Peng-Keat Ng
  • Michael Boehnke
  • Kee-Seng Chia
  • Tien-Yin Wong
  • Mark Seielstad
  • Yik-Ying Teo
  • E-Shyong Tai

Abstract

Recent large genome-wide association studies (GWAS) have identified multiple loci which harbor genetic variants associated with type 2 diabetes mellitus (T2D), many of which encode proteins not previously suspected to be involved in the pathogenesis of T2D. Most GWAS for T2D have focused on populations of European descent, and GWAS conducted in other populations with different ancestry offer a unique opportunity to study the genetic architecture of T2D. We performed genome-wide association scans for T2D in 3,955 Chinese (2,010 cases, 1,945 controls), 2,034 Malays (794 cases, 1,240 controls), and 2,146 Asian Indians (977 cases, 1,169 controls). In addition to the search for novel variants implicated in T2D, these multi-ethnic cohorts serve to assess the transferability and relevance of the previous findings from European descent populations in the three major ethnic populations of Asia, comprising half of the world's population. Of the SNPs associated with T2D in previous GWAS, only variants at CDKAL1 and HHEX/IDE/KIF11 showed the strongest association with T2D in the meta-analysis including all three ethnic groups. However, consistent direction of effect was observed for many of the other SNPs in our study and in those carried out in European populations. Close examination of the associations at both the CDKAL1 and HHEX/IDE/KIF11 loci provided some evidence of locus and allelic heterogeneity in relation to the associations with T2D. We also detected variation in linkage disequilibrium between populations for most of these loci that have been previously identified. These factors, combined with limited statistical power, may contribute to the failure to detect associations across populations of diverse ethnicity. These findings highlight the value of surveying across diverse racial/ethnic groups towards the fine-mapping efforts for the casual variants and also of the search for variants, which may be population-specific. Author Summary: Type 2 diabetes mellitus (T2D) is a chronic disease which can lead to complications such as heart disease, stroke, hypertension, blindness due to diabetic retinopathy, amputations from peripheral vascular diseases, and kidney disease from diabetic nephropathy. The increasing prevalence and complications of T2D are likely to increase the health and economic burden of individuals, families, health systems, and countries. Our study carried out in three major Asian ethnic groups (Chinese, Malays, and Indians) in Singapore suggests that the findings of studies carried out in populations of European ancestry (which represents most studies to date) may be relevant to populations in Asia. However, our study also raises the possibility that different genes, and within the genes different variants, may confer susceptibility to T2D in these populations. These findings are particularly relevant in Asia, where the greatest growth of T2D is expected in the coming years, and emphasize the importance of studying diverse populations when trying to localize the regions of the genome associated with T2D. In addition, we may need to consider novel methods for combining data across populations.

Suggested Citation

  • Xueling Sim & Rick Twee-Hee Ong & Chen Suo & Wan-Ting Tay & Jianjun Liu & Daniel Peng-Keat Ng & Michael Boehnke & Kee-Seng Chia & Tien-Yin Wong & Mark Seielstad & Yik-Ying Teo & E-Shyong Tai, 2011. "Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia," PLOS Genetics, Public Library of Science, vol. 7(4), pages 1-12, April.
  • Handle: RePEc:plo:pgen00:1001363
    DOI: 10.1371/journal.pgen.1001363
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1001363
    Download Restriction: no

    File URL: https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1001363&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pgen.1001363?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Robert Sladek & Ghislain Rocheleau & Johan Rung & Christian Dina & Lishuang Shen & David Serre & Philippe Boutin & Daniel Vincent & Alexandre Belisle & Samy Hadjadj & Beverley Balkau & Barbara Heude &, 2007. "A genome-wide association study identifies novel risk loci for type 2 diabetes," Nature, Nature, vol. 445(7130), pages 881-885, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yann C Klimentidis & Jin Zhou & Nathan E Wineinger, 2014. "Identification of Allelic Heterogeneity at Type-2 Diabetes Loci and Impact on Prediction," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-7, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ping Rao & Hao Wang & Honghong Fang & Qing Gao & Jie Zhang & Manshu Song & Yong Zhou & Youxin Wang & Wei Wang, 2016. "Association between IGF2BP2 Polymorphisms and Type 2 Diabetes Mellitus: A Case–Control Study and Meta-Analysis," IJERPH, MDPI, vol. 13(6), pages 1-13, June.
    2. Paul F O’Reilly & Clive J Hoggart & Yotsawat Pomyen & Federico C F Calboli & Paul Elliott & Marjo-Riitta Jarvelin & Lachlan J M Coin, 2012. "MultiPhen: Joint Model of Multiple Phenotypes Can Increase Discovery in GWAS," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-1, May.
    3. Sarah Meulebrouck & Judith Merrheim & Gurvan Queniat & Cyril Bourouh & Mehdi Derhourhi & Mathilde Boissel & Xiaoyan Yi & Alaa Badreddine & Raphaël Boutry & Audrey Leloire & Bénédicte Toussaint & Souhi, 2024. "Functional genetics reveals the contribution of delta opioid receptor to type 2 diabetes and beta-cell function," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    4. Jiajin Li & Brandon Jew & Lingyu Zhan & Sungoo Hwang & Giovanni Coppola & Nelson B Freimer & Jae Hoon Sul, 2019. "ForestQC: Quality control on genetic variants from next-generation sequencing data using random forest," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-30, December.
    5. Hongyan Mao & Qin Li & Shujun Gao, 2012. "Meta-Analysis of the Relationship between Common Type 2 Diabetes Risk Gene Variants with Gestational Diabetes Mellitus," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-7, September.
    6. Ren Matsuba & Minako Imamura & Yasushi Tanaka & Minoru Iwata & Hiroshi Hirose & Kohei Kaku & Hiroshi Maegawa & Hirotaka Watada & Kazuyuki Tobe & Atsunori Kashiwagi & Ryuzo Kawamori & Shiro Maeda, 2016. "Replication Study in a Japanese Population of Six Susceptibility Loci for Type 2 Diabetes Originally Identified by a Transethnic Meta-Analysis of Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-9, April.
    7. Nicholette D Palmer & Caitrin W McDonough & Pamela J Hicks & Bong H Roh & Maria R Wing & S Sandy An & Jessica M Hester & Jessica N Cooke & Meredith A Bostrom & Megan E Rudock & Matthew E Talbert & Jos, 2012. "A Genome-Wide Association Search for Type 2 Diabetes Genes in African Americans," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-14, January.
    8. Inga Prokopenko & Wenny Poon & Reedik Mägi & Rashmi Prasad B & S Albert Salehi & Peter Almgren & Peter Osmark & Nabila Bouatia-Naji & Nils Wierup & Tove Fall & Alena Stančáková & Adam Barker & Vasilik, 2014. "A Central Role for GRB10 in Regulation of Islet Function in Man," PLOS Genetics, Public Library of Science, vol. 10(4), pages 1-13, April.
    9. Trine Welløv Boesgaard & Anette Prior Gjesing & Niels Grarup & Jarno Rutanen & Per-Anders Jansson & Marta Letizia Hribal & Giorgio Sesti & Andreas Fritsche & Norbert Stefan & Harald Staiger & Hans Här, 2009. "Variant near ADAMTS9 Known to Associate with Type 2 Diabetes Is Related to Insulin Resistance in Offspring of Type 2 Diabetes Patients—EUGENE2 Study," PLOS ONE, Public Library of Science, vol. 4(9), pages 1-7, September.
    10. Artak Labadzhyan & Jinrui Cui & Miklós Péterfy & Xiuqing Guo & Yii-Der I Chen & Willa A Hsueh & Jerome I Rotter & Mark O Goodarzi, 2016. "Insulin Clearance Is Associated with Hepatic Lipase Activity and Lipid and Adiposity Traits in Mexican Americans," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-11, November.
    11. Ching-Yu Cheng & David Reich & Christopher A Haiman & Arti Tandon & Nick Patterson & Selvin Elizabeth & Ermeg L Akylbekova & Frederick L Brancati & Josef Coresh & Eric Boerwinkle & David Altshuler & H, 2012. "African Ancestry and Its Correlation to Type 2 Diabetes in African Americans: A Genetic Admixture Analysis in Three U.S. Population Cohorts," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-9, March.
    12. Pasi J Eskola & Susanna Lemmelä & Per Kjaer & Svetlana Solovieva & Minna Männikkö & Niels Tommerup & Allan Lind-Thomsen & Kirsti Husgafvel-Pursiainen & Kenneth M C Cheung & Danny Chan & Dino Samartzis, 2012. "Genetic Association Studies in Lumbar Disc Degeneration: A Systematic Review," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-10, November.
    13. Mengling Tang & Kun Chen & Fangxing Yang & Weiping Liu, 2014. "Exposure to Organochlorine Pollutants and Type 2 Diabetes: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-12, October.
    14. Sun, Yan V. & Jacobsen, Douglas M. & Turner, Stephen T. & Boerwinkle, Eric & Kardia, Sharon L.R., 2009. "Fast implementation of a scan statistic for identifying chromosomal patterns of genome wide association studies," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1794-1801, March.
    15. Florian Mittag & Michael Römer & Andreas Zell, 2015. "Influence of Feature Encoding and Choice of Classifier on Disease Risk Prediction in Genome-Wide Association Studies," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-18, August.
    16. Greve, Jane, 2008. "Obesity and labor market outcomes in Denmark," Economics & Human Biology, Elsevier, vol. 6(3), pages 350-362, December.
    17. John PA Ioannidis & Nikolaos A Patsopoulos & Evangelos Evangelou, 2007. "Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations," PLOS ONE, Public Library of Science, vol. 2(9), pages 1-7, September.
    18. Sato Yasunori & Laird Nan & Suganami Hideki & Hamada Chikuma & Niki Naoto & Yoshimura Isao & Yoshida Teruhiko, 2009. "Statistical Screening Method for Genetic Factors Influencing Susceptibility to Common Diseases in a Two-Stage Genome-Wide Association Study," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-23, November.
    19. Guang Guo, 2008. "Introduction to the Special Issue on Society and Genetics," Sociological Methods & Research, , vol. 37(2), pages 159-163, November.
    20. Peristera Paschou & Petros Drineas & Jamey Lewis & Caroline M Nievergelt & Deborah A Nickerson & Joshua D Smith & Paul M Ridker & Daniel I Chasman & Ronald M Krauss & Elad Ziv, 2008. "Tracing Sub-Structure in the European American Population with PCA-Informative Markers," PLOS Genetics, Public Library of Science, vol. 4(7), pages 1-13, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pgen00:1001363. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosgenetics (email available below). General contact details of provider: https://journals.plos.org/plosgenetics/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.