Suyash Shringarpure (@suyashss) from @23andMeResearch presented a fantastic #raredisease study: "Novel genetic associations for rare diseases with GWAS and trans-ethnic analysis of self-reported medical data"
.@suyashss: It's well known that self-reported data works very well for common diseases, but what about rare diseases? The assumption is that it wouldn't work.
The other common assumption is that rare disease requires sequencing to find rare causal variants. #ASHG21
.@suyashss: They launched a survey to evaluate these two commonly held assumptions about genetics in #raredisease.
.@suyashss: To evaluate their self-reported data, they tested whether GWAS could re-discover known genetic associations with rare diseases (e.g., Huntington's disease, cystic fibrosis) and did, even with sample sizes as low as 41 cases (in Huntington's disease)! #ASHG21
.@suyashss: As an additional validation test, they compared effect sizes from their GWAS to published studies of these diseases (which themselves mostly have different cohort compositions) and effect sizes were very consistent. #ASHG21
.@suyashss: With these validation analyses completed, they looked for novel associations and found 5.
1 novel association for vestibular schwannoma near CDKN2A/CDKN2B locus.
.@suyashss: 3 novel associations for spontaneous pneumothorax. Through proximity and eQTLs point, these loci point to 3 genes: KY, POSTN, CFDP1 (all of which are linked to lung function)
.@suyashss: They attempted to replicate all 5 novel loci. 3 loci (1 in each trait) replicated, but all 5 have the same direction of effect in the replication data. Smaller sample size in replication data may have hurt the replication chances.
.@suyashss: These prior analyses were all done in individuals of European ancestries and excluded related individuals.
Using @weizhouw's SAIGE method, they found better p-values in a trans-ancestry analysis for 3 of their loci (these were the same 3 loci that replicated) #ASHG21
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Last in this #ASHG21 late breaking plenary session is Bailey Martin-Giacalone presenting on germline variants in cancer predisposition genes predict survival for children with rhabdomyosarcoma
#ASHG21 Martin-Giacalone: Want to look at germline (not somatic) variants associated with rhabdomyosarcoma (RMS ).
Exome-sequenced 615 RMS cases and 9963 adult controls.
#ASHG21 Martin-Giacalone: Examined 63 cancer predisposition genes. Found 7.3% RMS cases had variants (not sure what type??) compared to 1.5% of controls. TP53, NF1, HRAS had the largest excess.
Next up in the #ASHG21 late breaking plenary session is Elisa De Franco (@Elisa_EDF) presenting loss of primate-specific gene ZNF808.
#ASHG21@Elisa_EDF: studying mice can provide insights into human biology, but there are differences. Mice have 2 genes for insulin (Ins1, Ins2), humans have 1 (INS).
#ASHG21@Elisa_EDF: looked at 2877 neonatal diabetes patients from 111 countries and want Identify genes with pancreatic genesis.
Next up in the #ASHG21 plenary session is Jonathan Sebat (@sebatlab) covering WGS of #Autism combining common and rare variants.
#ASHG21@sebatlab: Found more de novo variants in cases than controls, rare inherited variants overtransmitted to cases, polygenic scores overtransmitted to cases. As such, all 3 categories are associated with #Autism risk.
#ASHG21@sebatlab: created rare variant and common variant risk scores and both were associated with #autism status.
Chen: When looking at largest constraint Z-scores (top Z-score was 4 on the figures)
- Super enhancers ~3x enriched
- ENCODE cCRE enhancers ~2.25x enriched
- FANTOM enhancers ~1.75x enriched
Next up is my @RegeneronDNA colleague, Julie Horowitz, presenting "Common and rare variant analysis of 21K psoriasis cases and 623K controls identifies novel, protective associations in several genes in the type 1 interferon #ASHG21
Horowitz: Previous GWAS of psoriasis have identified >60 loci, but no large scale sequencing of psoriasis has been performed to identify 1) very rare variants and 2) burden tests.
Horowitz: Leveraging data from >5 cohorts and 4 ancestries (EUR, AFR, SAS, AMR), they performed a trans-ancestry meta-analysis across a total of 21k cases and 623k controls.