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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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CardioGenBase: A Literature Based Multi-Omics Database for Major Cardiovascular Diseases.

Alexandar V1, Pradeep G Nayar2, R Murugesan1

  • 1Faculty of Allied Health Sciences, Chettinad Academy of Research and Education, Kelambakkam 603 103, Tamil Nadu, India.

Plos One
|December 2, 2015
PubMed
Summary
This summary is machine-generated.

CardioGenBase is a new online database that consolidates gene-disease associations for major cardiovascular diseases (CVDs). This resource aids researchers in understanding CVD genetic factors and developing new diagnostic and therapeutic strategies.

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Area of Science:

  • Genetics and Genomics
  • Cardiovascular Research
  • Bioinformatics

Background:

  • Cardiovascular diseases (CVDs) are a leading cause of global morbidity and mortality.
  • Genetic and epigenetic factors significantly contribute to CVD development.
  • Existing multi-omics data for CVDs lack comprehensive integration, hindering mechanistic understanding.

Purpose of the Study:

  • To develop a centralized, literature-based online database for cardiovascular disease (CVD) gene-disease associations.
  • To provide a comprehensive resource for understanding the genetic underpinnings of major CVDs.
  • To support advanced research in CVD pathophysiology and genetics.

Main Methods:

  • Developed CardioGenBase, a literature-based database, by extracting gene-disease associations from PubMed and MEDLINE.
  • Compiled data on approximately 1,500 cardiovascular disease genes from over 24,000 research articles.
  • Integrated diverse data types including gene-disease evidence, ontology, pathways, SNPs, protein interactions, and expression data.

Main Results:

  • CardioGenBase covers major cardiovascular diseases: cerebrovascular, coronary artery disease (CAD), hypertensive heart disease, inflammatory heart disease, ischemic heart disease, and rheumatic heart disease.
  • The database includes detailed information for ~1,500 CVD genes.
  • Includes integrated tools for gene-disease association and gene expression analysis, with visual aids.

Conclusions:

  • CardioGenBase is the first comprehensive database offering gene-disease associations for major cardiovascular diseases in a single portal.
  • It serves as a vital resource for genome-wide association studies, genetic, epigenetic, and pharmacological research in CVDs.
  • Facilitates novel methodologies for understanding CVD pathophysiology and advancing personalized medicine.