Our association study in 653K individuals linking protein-coding genetic variants from @uk_biobank exomes & imputed genotypes in @FinnGen_FI to 744 disease endpoints. Brilliant work by @ben_b_sun 1/10 @GeneticsSociety #ASHG21
medrxiv.org/cgi/content/sh…
2/ GWAS have linked 1000s of genetic variants to disease, but datasets to resolve association signals to coding genes & higher impact rare/low frequency alleles are emerging only now, e.g. through sequencing @uk_biobank or leveraging bottlenecked populations like @FinnGen_FI
3/ We harmonized disease endpoints captured in both biobanks & conducted coding-wide association (CWAS) meta-analyses. This identified 975 replicating signals, most from missense alleles. 1/3 were novel, 145 had MAF<2%. This included "benign" variants in monogenic disease genes.
4/ Notably, not only sample size but also variant population enrichment substantially boosted association power - the more the rarer a variant. This supports more studies in bottlenecked populations like @FinnGen_FI & other ethnicities.
4/ Notably, not only sample size but also variant population enrichment substantially boosted association power - the more the rarer a variant. This supports more studies in bottlenecked populations like @FinnGen_FI & other ethnicities.
5/ We further tested our CWAS sentinel variants for association with 117 quantitative @uk_biobank biomarkers. This identified pleiotropic disease loci & in several cases generated hypotheses on the mechanisms linking variants to disease & underlying drug safety/efficacy signals.
6/ We are super excited to see the gap between Mendelian & complex disease narrowing. ~1/3 of sentinel variants were in genes linked to matching diseases in #ClinVar, yet only few annotated as pathogenic. We also report extended phenotypes for medically actionable ACMG3.0 genes.
7/ Our manuscript showcases numerous vignettes, with a special emphasis on Atrial Fibrillation. For instance, we use Clustered MR to relate AF variants to pulse rate & describe a FIN-enriched missense variant in PITX2 that likely enhances expression of disease-relevant AF genes.
8/ We are grateful for the wonderful @FinnGen_FI participants & collaboration partners, particularly @mitja_kurki @APalotie & @dalygene. Summary statistics from this amazing project are released bi-annually & can be explored in a public results browser r5.finngen.fi
9/ We also thank @uk_biobank who now released 300k exomes through their RAP. We @biogen have already shared insights from these amazing data on:
lifespan
doi.org/10.1101/2020.0…
lipids
doi.org/10.1101/2020.1…
depression
doi.org/10.1101/2021.0…
& shaped genebass.org
10/10 Finally this work wouldn’t have been possible without the stellar @ben_b_sun who just released another great study on the genetics of brain morphology @chrisdwhelan, @njahanshad & @PTenigma
Both studies will be presented @GeneticsSociety #ASHG21
biorxiv.org/cgi/content/sh…
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