IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0070301.html
   My bibliography  Save this article

Genetic Associations with Diabetes: Meta-Analyses of 10 Candidate Polymorphisms

Author

Listed:
  • Linlin Tang
  • Lingyan Wang
  • Qi Liao
  • Qinwen Wang
  • Leiting Xu
  • Shizhong Bu
  • Yi Huang
  • Cheng Zhang
  • Huadan Ye
  • Xuting Xu
  • Qiong Liu
  • Meng Ye
  • Yifeng Mai
  • Shiwei Duan

Abstract

Aims: The goal of our study is to investigate the combined contribution of 10 genetic variants to diabetes susceptibility. Methods: Bibliographic databases were searched from 1970 to Dec 2012 for studies that reported on genetic association study of diabetes. After a comprehensive filtering procedure, 10 candidate gene variants with informative genotype information were collected for the current meta-anlayses. Using the REVMAN software, odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to evaluate the combined contribution of the selected genetic variants to diabetes. Results: A total of 37 articles among 37,033 cases and 54,716 controls were involved in the present meta-analyses of 10 genetic variants. Three variants were found to be significantly associated with type 1 diabetes (T1D): NLRP1 rs12150220 (OR = 0.71, 95% CI = 0.55–0.92, P = 0.01), IL2RA rs11594656 (OR = 0.86, 95% CI = 0.82–0.91, P

Suggested Citation

  • Linlin Tang & Lingyan Wang & Qi Liao & Qinwen Wang & Leiting Xu & Shizhong Bu & Yi Huang & Cheng Zhang & Huadan Ye & Xuting Xu & Qiong Liu & Meng Ye & Yifeng Mai & Shiwei Duan, 2013. "Genetic Associations with Diabetes: Meta-Analyses of 10 Candidate Polymorphisms," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-10, July.
  • Handle: RePEc:plo:pone00:0070301
    DOI: 10.1371/journal.pone.0070301
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0070301
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0070301&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0070301?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. Hakon Hakonarson & Struan F. A. Grant & Jonathan P. Bradfield & Luc Marchand & Cecilia E. Kim & Joseph T. Glessner & Rosemarie Grabs & Tracy Casalunovo & Shayne P. Taback & Edward C. Frackelton & Marg, 2007. "A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene," Nature, Nature, vol. 448(7153), pages 591-594, August.
    Full references (including those not matched with items on IDEAS)

    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. Joan Costa-Font & Cristina Vilaplana-Prieto, 2022. "Biased survival expectations and behaviours: Does domain specific information matter?," Journal of Risk and Uncertainty, Springer, vol. 65(3), pages 285-317, December.
    2. Anna L Mitchell & Anette Bøe Wolff & Katie MacArthur & Jolanta U Weaver & Bijay Vaidya & Sophie Bensing on behalf of The Swedish Addison Registry Study Group & Martina M Erichsen & Rebecca Darlay & Ey, 2015. "Linkage Analysis in Autoimmune Addison’s Disease: NFATC1 as a Potential Novel Susceptibility Locus," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-13, June.
    3. Pei Wang & Shunjie Chen & Sijia Yang, 2022. "Recent Advances on Penalized Regression Models for Biological Data," Mathematics, MDPI, vol. 10(19), pages 1-24, October.
    4. Diana Chang & Alon Keinan, 2014. "Principal Component Analysis Characterizes Shared Pathogenetics from Genome-Wide Association Studies," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-14, September.
    5. 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.
    6. Gabriel E Hoffman & Benjamin A Logsdon & Jason G Mezey, 2013. "PUMA: A Unified Framework for Penalized Multiple Regression Analysis of GWAS Data," PLOS Computational Biology, Public Library of Science, vol. 9(6), pages 1-19, June.
    7. Maggie C Y Ng & Daniel Shriner & Brian H Chen & Jiang Li & Wei-Min Chen & Xiuqing Guo & Jiankang Liu & Suzette J Bielinski & Lisa R Yanek & Michael A Nalls & Mary E Comeau & Laura J Rasmussen-Torvik &, 2014. "Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes," PLOS Genetics, Public Library of Science, vol. 10(8), pages 1-14, August.

    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:pone00:0070301. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.