Integrating GWAS, omics QTLs and gene networks to reveal drug target genes
For our next talk, in the BDI/CHG (gen)omics Seminar series, on 19th February, 4:00pm – 5:00pm at the Big Data Institute (BDI), we will be hearing from Dr Zoltán Kutalik, Statistical Geneticist and Associate Professor, Department of Computational Biology, University of Lausanne, Switzerland; Unisanté, University of Lausanne, Switzerland. We are delighted to host Dr Kutalik in what promises to be a great talk!

Date: 19 February
Time: 4:00pm – 5:00pm
Title: Integrating GWAS, omics QTLs and gene networks to reveal drug target genes
Location: Big Data Institute Seminar Room 0

Abstract: Drugs targeting genes linked to disease via evidence from human genetics have increased odds of approval. Approaches to prioritize such genes include genome-wide association studies (GWASs), rare variant burden tests in exome sequencing studies (Exome), or integration of a GWAS with expression/protein quantitative trait loci (eQTL/pQTL-GWAS). Here, we compare gene-prioritization approaches on 30 clinically relevant traits and benchmark their ability to recover drug targets. Across traits, prioritized genes were enriched for drug targets with odds ratios (ORs) of 2.17, 2.04, 1.81, and 1.31 for the GWAS, eQTL-GWAS, Exome, and pQTL-GWAS methods, respectively. Adjusting for differences in testable genes and sample sizes, GWAS outperforms e/pQTL-GWAS, but not the Exome approach. Furthermore, performance increased through gene network diffusion, although the node degree, being the best predictor (OR = 8.7), revealed strong bias in literature-curated networks. In conclusion, we systematically assessed strategies to prioritize drug target genes, highlighting the promises and pitfalls of current approaches.

Zoltán Kutalik, PhD is a statistical geneticist, associate professor at the University of Lausanne, heading the Statistical Genetics Group and honorary senior lecturer at the University of Exeter. His main research interest lies in developing statistical methods integrating various data modalities to better understand the genetic architecture of complex human diseases. He is a council member of the Swiss Institute of Bioinformatics (SIB), scientific programme committee member of the ESHG, EMGM, BC2, ISCB conferences and evaluation committee member of the Swiss National Science Foundation (SNSF). Zoltan is on the advisory board of the LongITools EU project, the CoLaus study, he is member of the science council of the Health 2030 Genome Center, an editorial board member of PLoS Genetics, Human Molecular Genetics, EJHG and ASHG. He won the Early Career Bioinformatician Award of the SIB, the Investigator-in-training award of the University of Lausanne and shared the Leenaards Prize. Five of his group members won the Lodewijk Sandkuijl Award of the ESHG in the past years. He published >200 peer-reviewed articles (>55,000 citations, h-index>100) in international scientific journals (incl. Nature, Nature Human Behavior, Nature Genetics and Nature Communications). His research has been financed by the SNSF, the SIB, the and the Leenaards Foundation.
Hybrid Option:
Please note that these meetings are closed meetings and only open to members of the University of Oxford. Please respect our speakers and do not share the link with anyone outside of the University. The aim of these seminars is to increase interaction between people working in Genomics across the University so we encourage in person attendance wherever possible. Everyone affiliated with the University is welcome to attend; we hope you can join us!

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Date: 19 February 2024, 16:00 (Monday, 6th week, Hilary 2024)
Venue: Big Data Institute, Old Road Campus OX3 7LF
Venue Details: Seminar Room 0
Speaker: Dr Zoltán Kutalik (University of Lausanne)
Organising department: Big Data Institute (NDPH)
Organisers: Nicola Whiffin (University of Oxford), Duncan Palmer (University of Oxford)
Organiser contact email address:
Part of: BDI/CHG Genomics Seminar Series
Booking required?: Not required
Cost: free
Audience: Members of the University only
Editor: Sumeeta Maheshwari