A new study published in Nature Genetics has proposed a method to improve the discovery of risk genes for complex traits by adjusting for genetic confounders in transcriptome-wide association studies (TWAS).
Researchers have long been using expression quantitative trait loci (eQTL) data to identify candidate genes from genome-wide association studies. However, existing methods such as colocalization, TWAS, and Mendelian randomization-based methods have been found to suffer from a key problem. When assessing the role of a gene in a trait using its eQTLs, nearby variants and genetic components of other genes’ expression may be correlated with these eQTLs, potentially acting as confounders.
The new method, causal-TWAS (cTWAS), addresses this issue by incorporating ideas from statistical fine-mapping to adjust for all genetic confounders. The study conducted extensive simulations, demonstrating that cTWAS showed calibrated false discovery rates and successfully discovered new candidate genes for several common traits.
Genome-wide association studies have previously identified many loci associated with human traits. To understand the causal genes and molecular mechanisms behind these associations, researchers have turned to eQTL data. TWAS, in particular, has been widely used to identify candidate genes and their likely cell/tissue contexts, offering a valuable framework for gene discovery.
However, a central question in TWAS is whether the identified genes have causal effects on the phenotype. The study highlights scenarios where noncausal associations may arise due to linkage disequilibrium between eQTLs of noncausal and nearby causal genes, emphasizing the need to account for genetic confounders in TWAS.
The proposed cTWAS method provides a robust statistical framework for gene discovery, offering potential improvements in the identification of risk genes for complex traits. The study’s findings in Nature Genetics contribute to advancing our understanding of the genetic basis of complex traits and may have implications for future research in this field.
