IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v11y2012i2n10.html
   My bibliography  Save this article

Candidate Pathway Based Analysis for Cleft Lip with or without Cleft Palate

Author

Listed:
  • Zhang Tian-Xiao

    (Johns Hopkins University)

  • Beaty Terri H.

    (Johns Hopkins University)

  • Ruczinski Ingo

    (Johns Hopkins University)

Abstract

The objective of this research was to identify potential biological pathways associated with non-syndromic cleft lip with or without cleft palate (NSCL/P), and to explore the potential biological mechanisms underlying these associated pathways on risk of NSCL/P. This project was based on the dataset of a previously published genome-wide association (GWA) study on NSCL/P (Beaty et al. 2010). Case-parent trios used here originated from an international consortium (The Gene, Environment Association Studies consortium, GENEVA) formed in 2007. A total of 5,742 individuals from 1,908 CL/P case-parents trios (1,591 complete trios and 317 incomplete trios where one parent was missing) were collected and genotyped using the Illumina Human610-Quad array. Candidate pathways were selected using a list of 356 genes that may be related to oral clefts. In total, 42 candidate pathways, which included 1,564 genes and 40,208 SNPs were tested. Using a pathway-based analysis approach proposed by Wang et al (2007), we conducted a permutation-based test to assess the statistical significance of the nominal p-values of 42 candidate pathways. The analysis revealed several pathways yielding nominally significant p-values. However, controlling for the family wise error rate, none of these pathways could retain statistical significance. Nominal p-values of these pathways were concentrated at the lower tail of the distribution, with more than expected low p-values. A permutation based test for examining this type of distribution pattern yielded an overall p-value of 0.029. Thus, while this pathway-based analysis did not yield a clear significant result for any particular pathway, we conclude that one or more of the genes and pathways considered here likely do play a role in oral clefting.

Suggested Citation

  • Zhang Tian-Xiao & Beaty Terri H. & Ruczinski Ingo, 2012. "Candidate Pathway Based Analysis for Cleft Lip with or without Cleft Palate," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(2), pages 1-21, January.
  • Handle: RePEc:bpj:sagmbi:v:11:y:2012:i:2:n:10
    DOI: 10.2202/1544-6115.1717
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1717
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1544-6115.1717?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hariklia Eleftherohorinou & Victoria Wright & Clive Hoggart & Anna-Liisa Hartikainen & Marjo-Riitta Jarvelin & David Balding & Lachlan Coin & Michael Levin, 2009. "Pathway Analysis of GWAS Provides New Insights into Genetic Susceptibility to 3 Inflammatory Diseases," PLOS ONE, Public Library of Science, vol. 4(11), pages 1-11, November.
    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. Olga A Vsevolozhskaya & Min Shi & Fengjiao Hu & Dmitri V Zaykin, 2020. "DOT: Gene-set analysis by combining decorrelated association statistics," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-25, April.

    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. Ohad Manor & Eran Segal, 2013. "Predicting Disease Risk Using Bootstrap Ranking and Classification Algorithms," PLOS Computational Biology, Public Library of Science, vol. 9(8), pages 1-10, August.
    2. Ren-Hua Chung & Ying-Erh Chen, 2012. "A Two-Stage Random Forest-Based Pathway Analysis Method," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-6, May.
    3. Silver Matt & Montana Giovanni & Alzheimer's Disease Neuroimaging Initiative, 2012. "Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-43, January.
    4. Yvonne J K Edwards & Gary W Beecham & William K Scott & Sawsan Khuri & Guney Bademci & Demet Tekin & Eden R Martin & Zhijie Jiang & Deborah C Mash & Jarlath ffrench-Mullen & Margaret A Pericak-Vance &, 2011. "Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-11, February.
    5. Ayellet V Segrè & DIAGRAM Consortium & MAGIC investigators & Leif Groop & Vamsi K Mootha & Mark J Daly & David Altshuler, 2010. "Common Inherited Variation in Mitochondrial Genes Is Not Enriched for Associations with Type 2 Diabetes or Related Glycemic Traits," PLOS Genetics, Public Library of Science, vol. 6(8), pages 1-19, August.
    6. Nerea Bartolomé & Sergi Segarra & Marta Artieda & Olga Francino & Elisenda Sánchez & Magdalena Szczypiorska & Joaquim Casellas & Diego Tejedor & Joaquín Cerdeira & Antonio Martínez & Alfonso Velasco &, 2015. "A Genetic Predictive Model for Canine Hip Dysplasia: Integration of Genome Wide Association Study (GWAS) and Candidate Gene Approaches," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-13, April.

    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:bpj:sagmbi:v:11:y:2012:i:2:n:10. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.