Establishing Genetic Pleiotropy to Identify Common Pharmacological Agents for Common Diseases

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Background

Large scale genetic studies are transforming our biological understanding of many complex diseases. Large numbers of genetic loci have been found to associate with disease. Intriguingly, many of these loci, or nearby genetic regions, associate with more than one disease and thus appear to have pleiotropic effects. For example, the 8q24 region is associated with many different cancer types including breast, ovarian, endometrial, prostate and colorectal cancers. If drugs could be targeted against the genes (or the encoded proteins) that mediate these pleiotropic effects, multiple diseases could potentially be treated using the same therapeutic. Indeed, data has already shown that targeting proteins identified from genetic studies of disease has promise. For example, clinically approved drugs are more likely to target proteins related to genome-wide association study (GWAS) loci than other proteins and are even more likely to target proteins encoded by Mendelian genes.

However, for genetic findings to be clinically translated, major obstacles need to be overcome. These include:
1. Identification of the genes regulated by pleiotropic genetic loci is essential. In recent years it has become evident that the nearest gene to a GWAS locus is not necessarily its regulatory target as regulatory elements at GWAS locus often target distal genes.
2. Determination of the directionality of gene regulation at pleiotropic genetic regions. For multiple diseases to be treated with the same drug, the change in gene expression caused by the disease associated genetic variation must be in the same direction. Using the same drugs in diseases with discordant gene expression patterns may worsen patient outcomes.
3. Development of treatment strategies to target the identified pleiotropic genes or proteins. The easiest approach to develop treatment strategies against specific gene or protein targets is to reposition or repurpose existing drugs rather than developing new drugs. This could be especially beneficial in speeding up drug approval if the drug has already shown acceptable safety profiles in clinical trials.

Several advanced univariate and multivariate approaches such as Mendelian Randomization (MR) have been developed to dissect the pleiotropic effects of genetic variations. Functional genomic, epigenomic, transcriptome-wide association studies (TWAS) and other post-GWAS studies are expected to remove some of the obstacles described above, while pre-clinical studies are necessary to show drug efficacy in cellular and animal models before human trials are contemplated. In addition, emerging approaches, which do not just target specific genetic variations, but overlay information from pathway databases or biological networks are broadening our view on disease overlap. In such cases, a gene or multiple genes in a pathway might be considered to be pleiotropic if they affect more than one phenotype, regardless of whether the specific variants are shown to have pleiotropic effects.

These analytical and experimental approaches dissecting genetic pleiotropy will have future implications for genetic testing and personal genomics as well as drug re-positioning. The current Research Topic would thus cover the sub-analysis of the GWAS, and pathway based studies, advancing our knowledge in the area of genetic overlap across several diseases, by contributing to method development, new data or meta-analysis. This is a cross-disciplinary project involving the information from the discipline of genetics with a direct implication in pharmacology and thus is a unique and very timely concept in itself.

Keywords: GWAS, drug repositioning, pleiotropy, association studies

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