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CADgene: a comprehensive database for coronary artery disease genes

Hui Liu1, Wei Liu, Yifang Liao

  • 1Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology and Center for Human Genome Research, Huazhong University of Science and Technology, Wuhan 430074, China.

Nucleic Acids Research
|November 4, 2010
PubMed

Insights

Researchers created CADgene, a comprehensive database of coronary artery disease (CAD) genes. This resource integrates genetic evidence from over 1300 publications, aiding CAD gene research.

Area of Science:

  • Genetics
  • Bioinformatics
  • Cardiovascular Research

Background:

  • Coronary artery disease (CAD) is a leading global cause of mortality.
  • Understanding the genetic basis of CAD is crucial for developing effective treatments.
  • Extensive genetic data from numerous studies exist but are fragmented.

Purpose of the Study:

  • To develop CADgene, a centralized, comprehensive database for coronary artery disease (CAD) genes.
  • To integrate and organize vast amounts of genetic evidence related to CAD.
  • To provide a valuable resource for researchers investigating the genetic underpinnings of CAD.

Main Methods:

  • Manual extraction of CAD-related evidence from over 1300 publications.
  • Identification and curation of more than 300 candidate CAD genes.
  • Classification of genes into 12 functional categories based on their roles in CAD.
  • Detailed annotation of each gene, including study specifics (sample size, population, SNP, odds ratio, P-value), Gene Ontology, KEGG pathways, and protein-protein interactions.
  • Inclusion of cumulative data from 11 genome-wide association studies (GWAS) for CAD.
  • Development of a user-friendly web interface with search and browse functionalities.

Main Results:

  • CADgene successfully integrates genetic evidence for over 300 candidate CAD genes.
  • The database categorizes genes into 12 functional groups, offering insights into their roles in CAD.
  • Detailed annotations and cumulative GWAS data enhance the utility of the resource.
  • Tools for searching and identifying frequently studied genes are provided.

Conclusions:

  • CADgene serves as a comprehensive and valuable resource for researchers studying the genetic basis of coronary artery disease.
  • The database facilitates easier access to and integration of fragmented genetic data.
  • Improved understanding of CAD genetics through this resource can potentially lead to advancements in diagnosis and treatment.

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