#ASHG21 JS: Jonathan Sebat.
a phenotypic spectrum of autisim attributable to... [ too fast I missed it ]
#ASHG21 JS: combined 3 cohorts. Two WGS cohorts and the SPARK study. 11k families. 37,375 individuals. Called with GATK best practices. Imputed genotypes from SPARK combined with PLINK. Calculated polygenic scores.
#ASHG21 JS: autism enriched in de novo mutations, rare inherited variants, and increased PRS scores.
#ASHG21 JS: Effect sizes for rare and common variant risk scores very similar in general. A female protective effect seen for common and rare variants.
#ASHG21 JS: See the same effect for rare and common variant PRS. More genetic load in females than males in both cases and controls.
#ASHG21 JS: inverse variation of rare variant and common variant risk. [ that's interesting ]
#ASHG21 JS: consistent with a liability threshold that differs by sex. All genetic risk factors contribute of variation across the phenotypic spectrum [i.e. different features or behaviors of the autism spectrum ]
#ASHG21 JS: De novo mutations have a strong effect on motor function, but the polygenic scores don't.
#ASHG21 JS: Do not see a constant male biased effect across phenotypes. Male biased effect on social communication. Other factors show some female bias. The parental age effect shows sex bias.
#ASHG21 JS: genetic basis of parental age is multifactorial. paternal bias of de novo mutation. maternal bias of PRS both rare and common with maternal age.
#ASHG21 JS: Look at 114 GWAS genes and 115 genes implicated by rare variant exome sets. But sets are enriched in fetal brain (cortex esp) categories. Most dramatic for the rare variant (rare, larger effect) genes.
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#ASHG21 BMG: Bailey Martin-Giacalone.
Germline variants in cancer predisposition genes predict survival for children with rhabdomyosarcoma (RMS)
#ASHG21 BMG: RMS most common soft tissue cancer of childhood. Usually two subtypes. alveolar RMS (ARMS) ~80% have a PAX3/7-FOX01 fusion. Embryonal RMS (ERMS) have heterogeneous somatic mutation landscape.
#ASHG21 BMG: risk factors for survival include histology, primary site, fusion status, metastasis, age at diagnosis. tumor size. ERMS cases have better outcome. In fusion negative RMS with TP53 mutation have worse survival.
#ASHG21 RB: Richard Border.
Widespread evidence of systematic bias in estimates of genetic correlation due to assortative mating.
[ I think this is the preprint. Don't hold me to it. ] biorxiv.org/content/10.110…
#ASHG21 RB: interested in characterizing what extent two traits share similarity across traits.
#ASHG21 RB: Can compute the polygenic scores for each trait and see how they compare. Or correlation of effect correlations. Many ways to look at genetic correlations.
#ASHG21 MO: Meritxell Oliva.
Genetic regulation of DNA methylation across tissues reveals thousands of molecular links to complex traits.
#ASHG21 MO: GTEx looks at gene expression, regulation, and its relationship to genetic variation. The v8 set has eQTL data. 15,201 RNA-Seq samples from 838 post-mortem donors. 49 tissues.
#ASHG21 MO: A mQTLs are variants associated with DNA methylation. GWAS-QTL colocalization can help prioritize the causal genes at a GWAS locus.