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Genome-wide Association Studies-GWAS

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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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Related Experiment Video

Updated: Mar 12, 2026

Electrophysiological Assessment of Murine Atria with High-Resolution Optical Mapping

Electrophysiological Assessment of Murine Atria with High-Resolution Optical Mapping

Published on: February 22, 2018

Gene-gene Interaction Analyses for Atrial Fibrillation.

Honghuang Lin^1,2, Martina Mueller-Nurasyid^3,4,5, Albert V Smith^6,7

¹National Heart Lung and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA.

Scientific Reports

|November 9, 2016

Summary

This study investigated gene-gene interactions in atrial fibrillation (AF) susceptibility. Despite a large discovery cohort, no significant gene-gene interactions were replicated, suggesting further research with larger sample sizes is needed for AF genetics.

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Last Updated: Mar 12, 2026

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

Area of Science:

Genetics
Cardiovascular Disease Research
Bioinformatics

Background:

Atrial fibrillation (AF) is a common, heritable heart rhythm disorder affecting millions globally.
Understanding the genetic basis of AF is crucial for developing targeted therapies.
Gene-gene interactions are hypothesized to play a role in AF susceptibility.

Purpose of the Study:

To investigate the impact of gene-gene interactions on atrial fibrillation susceptibility.
To identify specific genetic variants and their interactions contributing to AF risk.

Main Methods:

A large-scale genome-wide association study (GWAS) was conducted on 8,173 AF cases and 65,237 controls for discovery.
Putative interactions were examined between genome-wide single nucleotide polymorphisms (SNPs) and 17 known AF-related SNPs.
Top interactions were validated in an independent replication cohort of 2,363 AF cases and 114,746 controls.

Main Results:

One significant interaction between rs7164883 (HCN4 locus) and rs4980345 (SLC28A1 locus) was found in the discovery phase (OR=1.44, P=4.3×10⁻⁸).
Eight additional gene-gene interactions showed marginal significance (P < 5×10⁻⁷).
None of the top identified interactions were successfully replicated in the independent cohort.

Conclusions:

This study did not identify statistically significant gene-gene interactions associated with atrial fibrillation susceptibility.
Larger sample sizes and denser genotyping are recommended for future studies to detect complex genetic interactions in AF.