Overview

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.

GWAS does not require the identification of the target gene involved in the disease phenotype. It identifies the SNP associated with the disease and helps identify the individuals at risk. This method simplifies target gene identification, which is time-consuming and not accurate in many cases. GWAS was used to identify SNPs associated with an increased risk of myocardial infarction. GWAS has also identified SNPs associated with type 2 diabetes, Parkinson's disease, other heart disorders, obesity, Crohn's disease, and prostate cancer.

Procedure

Sometimes, SNPs within a haplotype block can aid in finding a gene responsible for certain diseases - like hemophilia. To track down such genes, researchers can conduct population studies.

For example, genome-wide association studies, or GWAS, are carried out to associate specific genetic variations with a disease.

In this approach, researchers use two large study groups: people with the disease of interest and a similar group of people without the disease.

DNA samples from each study participant are isolated and sequenced before the genomes are scanned for SNPs.

If certain SNPs appear more frequently in individuals with the disease as compared to the healthy individuals, then those SNPs are said to be associated with the disease.

While it is possible that these SNPs are causing the condition, it is more likely that they are part of a haplotype block that may contain the causal variant.