Dr Gareth Hawkes @drghawkes.bsky.social

MRC Career Development Fellow, Lecturer in Health Data Science, University of Exeter. Academic in genetics, rare variants and complex traits

Reposted by Dr Gareth Hawkes
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Cedric Boeckx @cedricboeckx.bsky.social
2mo
Very nice work led @drghawkes.bsky.social,
showing convergence between rare and common genetic
associations, using whole-genome sequencing data to evaluate the
contribution of rare non-coding variants for commonly studied anthropometric traits 🧪🧬
www.nature.com/articles/s41467-026-69208-3
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Exeter rising-star @hiwwright.bsky.social leading the way in bridging population-scale WGS datasets for federated meta-conditioning across genetically-inferred ancestries. Haplotype effects are rife across the chromosomes: reference panels and LD matrices struggle with the rarest of variation!
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Interested in whole genomes, AI and functional validation? Sign up to hear more about our summer school in the sunny southwest U.K. @exeter.ac.uk in Sept 2026, in partnership with the U.K. Functional Genomics Initiative @uk-fgx.bsky.social and Google Deepmind @nihrexeterbrc.bsky.social
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Reposted by Dr Gareth Hawkes
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@loic-yengo.bsky.social
5mo
First time on Bsky and first big announcement!

I am excited to announce that our new study explaining the missing heritability of many phenotypes using WGS data from ~347,000 UK Biobank participants has just been published in @Nature.

Our manuscript is here: www.nature.com/articles/s41586-025-09720-6.
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Genomic superstar @chundru.bsky.social taking on fake-news genotypes in >900k individuals. He shows allele-level filtering is rarely suffifient, and makes the brave choice to properly tackle chrX!

We’ll be providing our filtered AoU WGS plink pgens for all registered users: watch this space
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Reposted by Dr Gareth Hawkes
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Tim Frayling @timfrayling.bsky.social
11mo
Already-risen Exeter star Gareth Hawkes @drghawkes.bsky.social following up with the latest master class in how to use WGS data, >1 billion variant based GWAS. They bypassed the WES era as didn't want to leave out 99% of the genome :-) #ESHG2025
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Come along today and see me and Harry begin to tackle the exponentially increasing population scale WGS data! #ESHG2025 #ESHG25
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Reposted by Dr Gareth Hawkes
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Kartik Chundru @chundru.bsky.social
11mo
I will be talking today in Space 3. The session starts at 10:30, my talk will be at 11:15
Come join if you are interested in de novo mutations, non-coding genome, rare disease, or just up for seeing @nickywhiffin.bsky.social talk about RNU4-2 saturation mutagenesis after me 😂
#ESHG2025
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Got a big showing of talented University of Exeter scientists with talks and posters at ESHG25 in Milan. Come along and find out more! @hls.exeter.ac.uk @exeter.ac.uk #ESHG25 @jamesfasham.bsky.social @jingzhan.bsky.social @ambermluckett.bsky.social @chundru.bsky.social @harrygreentkd.bsky.social
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Reposted by Dr Gareth Hawkes
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Jeff Spence @jeffspence.github.io
1y
A really nice paper by @drghawkes.bsky.social et al. argues that rare and common genetic associations converge on the same genes.

While this seems at odds with our recent work about how burden tests and GWAS prioritize different genes, our results agree (🧬🧪🧵 1/6)

www.biorxiv.org/content/10.1101/2025.02.24.639925v1
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Excited to be able to announce I’ll be starting a 5-year MRC Career Development Award fellowship next week on the 1st April at the University of Exeter! Lots of work to do on whole genomes, and I’m hoping to keep contributing my small piece!
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Last few days to apply! @exeter.ac.uk
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Reposted by Dr Gareth Hawkes
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Tim Frayling @timfrayling.bsky.social
1y
Interested in a PhD & have strong computational skills ? Study diabetes & heart disease using peta bytes of human genetic & medical record data. In a lovely central European location and as part of a cohort of Genomics and Digital Health students : lifesciencesphd.unige.ch/jobs
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Reposted by Dr Gareth Hawkes
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Cedric Boeckx @cedricboeckx.bsky.social
1y
Very interesting finding in this study led by @drghawkes.bsky.social: convergence between rare and common genetic associations. Implications for the genetic architecture of complex traits 🧪🧬
www.biorxiv.org/content/10.1101/2025.02.24.639925v1
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Reposted by Dr Gareth Hawkes
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Sasha Gusev @sashagusevposts.bsky.social
1y
We finally have some well-powered whole-genome heritability estimates, including a quasi-behavioral trait (BMI). For height, ~89% of the heritability estimated to reside in common variants. For BMI and WHR, ~100% estimated in common variants.

www.biorxiv.org/content/10.1101/2025.02.24.639925v1
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Reposted by Dr Gareth Hawkes
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Mike Inouye @mikeinouye.bsky.social
1y
Exeter doing some great stuff with biobank scale WGS at the moment!

Whole-genome sequencing analysis of anthropometric traits in 672,976 individuals reveals convergence between rare and common genetic associations www.biorxiv.org/content/10.1101/2025.02.24.639925v1
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Also want to specifically call out our rising-star Early Career Researcher (who isn't on bluesky/twitter!) Harry Wright, who nearly single-handedly conquered the All of Us data, in particular the WGS VDS format: more from him in the near future...

@anna123.bsky.social @timfrayling.bsky.social
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This was a really fun and exciting project to work on, and hopefully shows we're not near to exhausting population-scale WGS data. A great collaboration led by @mnweedon.bsky.social @drarwood.bsky.social and @carolinefwright.bsky.social , with @chundru.bsky.social and @rnbeaumont.bsky.social
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We next identify novel rare non-coding single variants not highlighted by imputation-based GWAS. For example, we identified two rare variants upstream of IGF2BP2 with large effects on WHRadjBMI, but notably different effects on adiposity traits
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We also identify another example of a gene-phenotype association only identified by aggregation of rare non-coding variants via WGS: 5-prime UTR variants in FGF18 were associated with up to 6cm difference in height, but we observed no coding association (possibly due to strong coding constraint)
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For height, given the common-variant saturation by Yengo et. al 2022, we further estimated heritability for ultra-rare variants (MAC>10), and found this co-localisation pattern holds, but find some remaining evidence of population stratification (or assortative mating etc) that we couldn't resolve
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We then assessed the heritability of rare variants (MAF>0.01%) using RHE-mc regression in UKB. We found a notable contribution for height (~11%), which almost entirely co-localised with common variants, but little to no evidence of rare-variant heritability for BMI and WHRadjBMI
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Based on our discovery-replication framework, 97% of our rare-variant findings co-localised with previously reported common variation.
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Really excited to share our next population-scale WGS work preprint. Here, we analyse three anthropometric traits in nearly 700,000 individuals (discovery UKB ~450K, replication AoU). We show, for these traits, that common and rare variant heritability is convergent

www.biorxiv.org/content/10.1101/2025.02.24.639925v1
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