What is the Difference Between Candidate Gene and GWAS?

Candidate gene and genome-wide association studies (GWAS) are two different approaches used to investigate genetic associations with diseases or traits. Here are the main differences between the two:

1. Scope: Candidate gene studies focus on a relatively small number of genes, while GWAS investigate genetic variants across the entire genome.
2. Statistical Power: Candidate gene studies tend to have higher statistical power, which means they are more likely to detect genetic associations. However, they are not capable of discovering new genes or gene combinations. In contrast, GWAS can identify associations with genes regardless of whether their function was known before.
3. Bias: Candidate gene studies can be biased, as they are based on specific hypotheses about the genes being studied. GWAS, on the other hand, are unbiased and data-driven, addressing millions of common genetic variants and having well-accepted thresholds for multiple comparisons.
4. Limitations: One of the limitations of GWAS is its limited ability to detect low-frequency and rare variants. Candidate gene studies may use less stringent thresholds for statistical significance, which could lead to an excess of false-positive associations.
5. Future Roles: GWAS have increasingly become the preferred approach for studying genetic associations, but candidate gene studies can still be relevant when coupled with meticulous dissection of associated biological processes.

Comparative Table: Candidate Gene vs GWAS

Candidate gene and genome-wide association studies (GWAS) are two complementary approaches to uncovering genetic contributions to diseases or traits. Here is a table summarizing the differences between the two methods:

Both candidate gene and GWAS approaches help to understand the genetic basis of susceptibility to diseases. The candidate gene approach focuses on the genetic variation associated with a disease within a small number of pre-selected genes, while GWAS investigates the genetic variation associated with a disease within the entire genome without requiring prior knowledge or selection of specific genes.