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
Chen: known #GWAS associations enriched for constrained non-coding regions. Predictably, GWAS loci with external replication had the largest enrichment, followed by GWAS loci with internal replication.
Chen: Are enhancers linked to constrained genes also constrained (@jengreitz's @Nature enhancer paper comes into play here)? Yes.
More interestingly, are there unconstrained genes with constrained enhancers? #ASHG21
Chen: 40% of unconstrained genes are linked with a constrained enhancers.
Most of these "unconstrained" genes are small and underpowered for LoF intolerance. These "unconstrained" genes enriched for histone proteins as well as secreted proteins in cell signaling.
[this finding suggests that perhaps additional power might be gained if rare variants in enhancers are included in the burden tests - thought there's a lot of caveats here]
Chen: When examining 76k CNVs, they found those CNVs in severe developmental disorder patients were enriched in constrained noncoding regions
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.
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.
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.