Genome-wide association studies provide clues about the genetic mechanisms underlying a disease. Despite being a statistical method, only pointing us to genomic loci, we can generate hypotheses and functionally validate these.
Functional annotation using publicly available data available through the ENCODE project or GTeX consortium, can help us refine our hypotheses by determining the potential causal SNP and gene. Hence, many disease-genes identified through GWAS are now followed up as potential new drug targets.
However, often overlooked, GWAS can also be used to predict or explain adverse effects of new or well established drugs. The rationale is that a SNP altering the expression of a gene, may cause the same phenotype as a drug that targets the same gene, albeit the effect size may vary.
Hence, having linked a SNPs with a phenotype and for instance gene expression, we can predict adverse effects of drugs that alter the same gene or its pathway. In two recent papers, we compared drug targets to GWAS implicated genes.
We identified all genes reported to interact with cyclooxygenase 2 (Cox-2) inhibitors and glatiramer acetate (GA). Cox-2 inhibitors are used to treat chronic pain, whereas GA is a drug used to treat multiple sclerosis. Both drugs are reported to cause coronary artery disease.
To explain the mechanisms underlying the increased risk of CAD, we identified the genes reported to interact with the drugs and looked for overlaps with genes in CAD GWAS loci. Functional annotation of the risk SNPs allowed us to link the loci with the potential causal genes and also validate that the SNPs and the drug had the same direction of effect. We identified four genes likely to influence the risk of CAD under administration of Cox-2 inhibitors and one gene likely to influence CAD risk under GA treatment.
Overall, our results point to potential mechanisms that explain the increased risk of CAD under administration of Cox-2 inhibitors and GA. The novel approach also demonstrate how genetic studies can be used to explore the clinical relevance of drug pleiotropy.
Here are the links to both papers (OA).