Liability threshold modeling of case–control status and family history of disease increases association power

Hujoel, Margaux L.A.; Gazal, Steven; Loh, Po−Ru; Patterson, Nick; Price, Alkes L.

doi:10.1038/s41588-020-0613-6

Cited by 80 publications

(116 citation statements)

References 38 publications

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“…Conceptually, this is similar to multipoint linkage analysis performed with pedigrees that include deceased members. It is also related to familial imputations (also called in silico genealogy-based genotyping) 11,12 and association by proxy 13,14 where genotypes of relatives are used to associate with phenotypes of un-genotyped probands. Even though our general framework can also incorporate association by proxy, e.g.…”

Section: Discussionmentioning

confidence: 99%

Family Analysis with Mendelian Imputations

Kong

Benónísdóttir

Young

2020

Preprint

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AbstractGenotype-phenotype associations can be results of direct effects, genetic nurturing effects and population stratification confounding. Genotypes from parents and siblings of the proband can be used to statistically disentangle these effects. To maximize power, a comprehensive framework for utilizing various combinations of parents’ and siblings’ genotypes is introduced. Central to the approach is mendelian imputation, a method that utilizes identity by descent (IBD) information to non-linearly impute genotypes into untyped relatives using genotypes of typed individuals. Applying the method to UK Biobank probands with at least one parent or sibling genotyped, for an educational attainment (EA) polygenic score that has an R2 of 5.7% with EA, its predictive power based on direct genetic effect alone is demonstrated to be only about 1.4%. For women, the EA polygenic score has a bigger estimated direct effect on age-at-first-birth than EA itself.

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Section: Discussionmentioning

confidence: 99%

Family Analysis with Mendelian Imputations

Kong

Benónísdóttir

Young

2020

Preprint

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“…We curated GWAS results of 38 independent complex traits and diseases ( Abbott et al ., 2018; De- montis et al, 2019; Watson et al ., 2019; Hujoel et al, 2020 ; de Lange et al, 2017 ; Nalls et al, 2019 ; Okada et al, 2014 ; Pardiñas et al, 2018 ; Mahajan et al, 2018 ; Yu et al, 2019; Jin et al, 2016 ) with the standard of independence described by Finucane et al ( 2015 ) (Supplementary Table 1 and 4). We used the Ensembl GRCh37 annotated autosomal protein-coding genes as the universal gene set.…”

Section: Methodsmentioning

confidence: 99%

Natural selections on both amino acid sequences and expression levels are determinants of ohnolog retention

Liu

2021

Preprint

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The mechanism of ohnolog retention is a subject of concern in evolutionary biology. Natural selections on coding sequences and gene dosages have been proposed to be determinants of ohnolog retention. However, the relationship between the two models is not widely accepted, and the role of regulatory sequences on ohnolog retention has long been neglected. In this study, based on a model of complex traits' genetic architecture, we compared the natural selection's strength on corresponding sequences between ohnologs and non-ohnologs by comparing complex traits' heritability enrichments. We showed that complex traits' regulatory sequences' heritability enrichments (p=1.1e-5 in 5 kb flanking regions) and expression-mediated heritability enrichments (p=2.1e-5) of ohnologs were significantly higher than non-ohnologs. Then, we deduced that regulatory sequences of ohnologs were under substantial natural selection, which was also a determent of ohnolog retention. Meanwhile, we showed that in coding sequences, the complex traits' heritability enrichments of ohnologs were significantly higher than of non-ohnologs (p=9.9e-5), supporting the ohnolog retention model of natural selection on coding sequences. We also showed that complex traits' causal gene expression effect sizes of ohnologs were significantly larger than of non-ohnologs (p=8.8e-6), supporting the ohnolog retention model of natural selection on gene dosages. In conclusion, we provide the first unified framework to show that both amino acid sequences and expression levels of ohnologs are under substantial selection, which may end the long-standing debate on ohnolog retention models.

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“…Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits. Nature Genetics, 50 9 The liability threshold model The liability threshold model (LTM) is a classic model in quantitative genetics [1,2,3], and is also commonly used to analyze modern data (e.g., [4,5,6,7,8,9,10,11]). The LTM assumes that a disease has an underlying "liability", which is normally distributed in the population, and is the sum of two components: genetic and non-genetic (the environment).…”

Section: Methodsmentioning

confidence: 99%

“…The liability threshold model (LTM) is a classic model in quantitative genetics (Dempster and Lerner, 1950; Falconer, 1965; Lynch and Walsh, 1998), and is also commonly used to analyze modern data (e.g., (Wray and Goddard, 2010; So et al, 2011; Lee et al, 2011, 2012; Do et al, 2012; Hayeck et al, 2017; Weissbrod et al, 2018; Hujoel et al, 2020)). The LTM assumes that a disease has an underlying “liability”, which is normally distributed in the population, and is the sum of two components: genetic and non-genetic (the environment).…”

Section: Methodsmentioning

confidence: 99%

Utility of polygenic embryo screening for disease depends on the selection strategy

Lencz

Backenroth

Green

et al. 2020

Preprint

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As of 2019, polygenic risk scores have been utilized to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. In this short report, we demonstrate that a strong determinant of the potential utility of such screening is the selection strategy employed, a factor that has not been previously studied. Minimal risk reduction is expected if only extremely high-scoring embryos are excluded, whereas risk reductions are substantially greater if the lowest-scoring embryo (for a given disease) is selected. We systematically examined the relative contributions of the variance explained by the score, the number of embryos, the disease prevalence, and the parental scores on the utility of screening. We discuss the results in the context of relative vs absolute risk, as well as the potential ethical concerns raised by such procedures.

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Liability threshold modeling of case–control status and family history of disease increases association power

Cited by 80 publications

References 38 publications

Family Analysis with Mendelian Imputations

Family Analysis with Mendelian Imputations

Natural selections on both amino acid sequences and expression levels are determinants of ohnolog retention

Utility of polygenic embryo screening for disease depends on the selection strategy

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