For our next talk, in the BDI/CHG (gen)omics Seminar series, on Tuesday 15 October, 9:30-10:30 am at the Big Data Institute (BDI), we will be hearing from Nikolas Baya, DTC in Genomic Medicine and Statistics student, Wellcome Centre for Human Genetics, University of Oxford. We’re delighted to host Nicolas in what promises to be a great talk!
Date: Tuesday 15 October
Time: 9:30-10:30 am, followed by refreshments in the atrium
Location: Big Data Institute Seminar Room 1
Title: Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution
Abstract
Overall adiposity and body fat distribution are heritable traits associated with altered risk of cardiometabolic disease and mortality. Performing rare variant (minor allele frequency<1%) association testing using exome-sequencing data from 402,375 participants in the UK Biobank (UKB) for nine overall and tissue-specific fat distribution traits, we identified 19 genes where putatively damaging rare variation associated with at least one trait (Bonferroni-adjusted P<1.58×10-7) and 52 additional genes at FDR≤1% (P≤4.37×10-5). These 71 genes exhibited higher (P=3.58×10-18) common variant prioritisation scores than genes not significantly enriched for rare putatively damaging variation, with evidence of monotonic allelic series (dose-response relationships) among ultra-rare variants (minor allele count≤10) in 22 genes. Five of the 71 genes have cognate protein UKB Olink data available; all five associated (P<3.80×10-6) with three or more analysed traits. Combining rare and common variation evidence, allelic series and proteomics, we selected 17 genes for CRISPR knockout in human white adipose tissue cell lines. In three previously uncharacterised target genes, knockout increased (two-sided t-test P<0.05) lipid accumulation, a cellular phenotype relevant for fat mass traits, compared to Cas9-empty negative controls: COL5A3 (fold change [FC]=1.72, P=0.0028), EXOC7 (FC=1.35, P=0.0096), and TRIP10 (FC=1.39, P=0.0157); furthermore, knockout of SLTM resulted in reduced lipid accumulation (FC=0.51, P=1.91×10-4). Integrating across population-based genetic and in vitro functional evidence, we highlight therapeutic avenues for altering obesity and body fat distribution by modulating lipid accumulation.
Note: Part of this talk will include a practice run of Nikolas’ ASHG talk.
Bio: Nik is a final-year DPhil in Genomic Medicine and Statistics at the University of Oxford, under the supervision of Prof Cecilia Lindgren and Prof Simon Myers. During his DPhil, he has studied the genetic basis of human adiposity using the UK Biobank. He’s also interested in outliers.
Affiliations
Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford
Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford
Department of Statistics, University of Oxford
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All members of the University are welcome to join, please let reception at BDI know you’re here for the seminar and sign-in. We hope you can join us!
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As a reminder, the gen)omics seminar series runs every other Tuesday morning and is intended to increase interaction between individuals working in genomics across Oxford. We encourage in-person attendance where possible. There is time for discussion over, tea, coffee and pastries after the talks.
Hybrid Option:
Please note that these meetings are closed meetings and only open to members of the University of Oxford to encourage sharing of new and unpublished data. 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.
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