#ASHG21 WL: Interested in pleiotropy. Look at variant-level pleiotropy. 349k vars. 5.4k with > 1 phenotype. 152 associated with > 20 phenotypes.
#ASHG21 WL: Gene-level pleiotropy. 650 genes associated > 1 phenotype. 24 associated with > 10 phenotypes. Example SLC39A8.
#ASHG21 WL: Looked at ICD diseases lumped into 14 domains (by ICD chapter). Diseases within each domain tend to have stronger correlation than between domains.
#ASHG21 WL: Examples LDLR and ADH1B. LDLR associated with hypercholesterolemia. ADH1B associated with drinking behaviors.
#ASHG21 WL: Look at allelic series - variants with different functional impacts may have different levels and strength of pleiotropy.
#ASHG21 WL: Tested 17.9k genes. 35 show allelic series. 8 show pLoF associated with ICD diseases, but missense with traits look blood parameters
#ASHG21 WL: How to quantify pleiotropy? Many associations are across phenotypes, but may be due to correlation. New method to quantify pleiotropic structure in the presence of known phenotypic correlation
#ASHG21 WL: Test for allelic heterogeniety. assumes all variants are independent, no in LD. Null correlated with some constant. Alternative not correlated.
#ASHG21 WL: Currently limited to quantitative phenotypes. Prefilters for MAF < 0.01% [ hmm ]. Remove ultrarare with allele count < 9. 1,117 continuous phenotypes. 211 unique phenotypes. 3.504 unique pairs of phenotypes tested.
#ASHG21 WL: Example of gene ALB related to albumin and total blood calcium. ALB variants associated with both traits. Effect sizes of missense variants not correlated. But effect sizes of pLoF are for the gene (effect on blood albumin and blood calcium).
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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 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 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.