Biology subjects

Chopade, S.

Publications and source records attributed to Chopade, S..

3 recordsLinked to original sources

bioRxiv2020

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter its expression or function, as a tool to anticipate the effect of drug action on the same target. Here, we applied MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets were further prioritized using genetic co-localization, protein expression profiles from the Human Protein Atlas and, for targets with a licensed drug or an agent in clinical development, by sourcing data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with circulating blood lipids (HDL-C, LDL-C and triglycerides), we were able to robustly prioritize 30 targets that might elicit beneficial treatment effects in the prevention or treatment of CHD. The prioritized list included NPC1L1 and PCSK9, the targets of licensed drugs whose efficacy has been already proven in clinical trials. To conclude, we discuss how this approach can be generalized to other targets, disease biomarkers and clinical end-points to help prioritize and validate targets during the drug development process. One Sentence SummaryWe provide genetic support for lipid-modifying drug targets for coronary heart disease prevention using drug target Mendelian randomization and further prioritization based on clinical and biological evidence.

genetics↗

bioRxiv2019

Genetic drug target validation using Mendelian randomization

Mendelian randomisation analysis has emerged as an important tool to elucidate the causal relevance of a range of environmental and biological risk factors for human disease. However, inference on cause is undermined if the genetic variants used to instrument a risk factor of interest also associate with other traits that open alternative pathways to the disease (horizontal pleiotropy). We show how the no horizontal pleiotropy assumption in MR analysis is strengthened when proteins are the risk factors of interest. Proteins are the proximal effectors of biological processes encoded in the genome, and are becoming assayable on an-omics scale. Moreover, proteins are the targets of most medicines, so Mendelian randomization (MR) studies of drug targets are becoming a fundamental tool in drug development. To enable such studies we introduce a formal mathematical framework that contrasts MR analysis of proteins with that of risk factors located more distally in the causal chain from gene to disease. Finally, we illustrate key model decisions and introduce an analytical framework for maximizing power and elucidating the robustness of drug target MR analyses.

genetics↗

bioRxiv2017

Flipping the odds of drug development success through human genomics

Drug development depends on accurately identifying molecular targets that both play a causal role in a disease and are amenable to pharmacological action by small molecule drugs or bio-therapeutics, such as monoclonal antibodies.\n\nErrors in drug target specification contribute to the extremely high rates of drug development failure.\n\nIntegrating knowledge of genes that encode druggable targets with those that influence susceptibility to common disease has the potential to radically improve the probability of drug development success.

genomics↗