Date(s) - 28/01/2014
2:00 pm - 4:00 pm
Dr Vincent Plagnol
Title: The type of variants that cause Mendelian disorders and an overview of the strategies to discover them
Abstract: High throughput DNA sequencing technologies have revolutionised Mendelian disorder genetics. While the overall picture is a clear success story, the “success rate” is still far off 100%, and many cases remain unexplained. Here, I will present a large scale consortium type study of more than 2,000 exomes. I will describe what statistical and bioinformatics procedures can be used to identify disease genes in this cohort, including the analysis of expression data in appropriate tissues. A particular attention will be given to splice altering sites, owing to the difficulty in interpreting these variants. I will also discuss the role of copy number variants, and show that a substantial fraction of these Mendelian disorders (about 10%) can be attributed to this class of genetic variants. Lastly, I will present the future strategies that are being developed in order to map the remaining cases.
Dr John Whittaker
Title: Genetics in drug discovery
Abstract: Attrition is a major challenge in drug discovery and development with >90% of projects failing before clinical trials and >50% of the remainder failing in clinical development due to lack of efficacy. Therefore, selecting and validating the best targets is a key element in developing medicines. Often the human evidence supporting the chosen target in a disease context is limited. However, rapid progress in deciphering the genetic basis of disease, and associated pathways, offers an opportunity to transform this process and leads to a key question: what weight should be given to a genetic association in selecting targets and indications? To address this question we merged GWASdb, a database with over 100000 genetic associations corresponding to 1228 unique traits mapped to 603 Medical Subject Heading (MeSH) terms, with Informa Pipeline, a commercial database of >23000 drugs with known human targets (including >2400 marketed) with 915 unique indications mapped to 708 MeSH terms. We drew on linkage disequilibrium, eQTL data, ENCODE-related data, and location to map genetic variants to one or more genes.
We found that targets for marketed drugs are substantially enriched for genetic associations, suggesting that genetic evidence at the target increases the chance that a drug will reach the market. We also investigated the similarity between drug indication and genetically associated trait: as term similarity increases, so does the proportion of marketed drugs. We conclude that genetic associations should play an important role in making decisions about target selection and indications to be investigated in drug development.
Bookings are closed for this event.