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Association Signals Unveiled by a Comprehensive Gene Set Enrichment Analysis of Dental Caries Genome-Wide Association Studies

Overview of attention for article published in PLOS ONE, August 2013
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Title
Association Signals Unveiled by a Comprehensive Gene Set Enrichment Analysis of Dental Caries Genome-Wide Association Studies
Published in
PLOS ONE, August 2013
DOI 10.1371/journal.pone.0072653
Pubmed ID
Authors

Quan Wang, Peilin Jia, Karen T. Cuenco, Zhen Zeng, Eleanor Feingold, Mary L. Marazita, Lily Wang, Zhongming Zhao

Abstract

Gene set-based analysis of genome-wide association study (GWAS) data has recently emerged as a useful approach to examine the joint effects of multiple risk loci in complex human diseases or phenotypes. Dental caries is a common, chronic, and complex disease leading to a decrease in quality of life worldwide. In this study, we applied the approaches of gene set enrichment analysis to a major dental caries GWAS dataset, which consists of 537 cases and 605 controls. Using four complementary gene set analysis methods, we analyzed 1331 Gene Ontology (GO) terms collected from the Molecular Signatures Database (MSigDB). Setting false discovery rate (FDR) threshold as 0.05, we identified 13 significantly associated GO terms. Additionally, 17 terms were further included as marginally associated because they were top ranked by each method, although their FDR is higher than 0.05. In total, we identified 30 promising GO terms, including 'Sphingoid metabolic process,' 'Ubiquitin protein ligase activity,' 'Regulation of cytokine secretion,' and 'Ceramide metabolic process.' These GO terms encompass broad functions that potentially interact and contribute to the oral immune response related to caries development, which have not been reported in the standard single marker based analysis. Collectively, our gene set enrichment analysis provided complementary insights into the molecular mechanisms and polygenic interactions in dental caries, revealing promising association signals that could not be detected through single marker analysis of GWAS data.

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Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
United States 1 2%
Unknown 42 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 20%
Student > Ph. D. Student 7 16%
Student > Bachelor 4 9%
Professor 4 9%
Student > Master 2 4%
Other 4 9%
Unknown 15 33%
Readers by discipline Count As %
Medicine and Dentistry 16 36%
Agricultural and Biological Sciences 6 13%
Nursing and Health Professions 2 4%
Computer Science 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 3 7%
Unknown 15 33%