Biology subjects

Benonisdottir, S.

Publications and source records attributed to Benonisdottir, S..

4 recordsLinked to original sources

bioRxiv2022

The Genetics of Participation: Method and Analysis

Participation in a genetic study likely has a genetic component. Identifying such component is difficult as we cannot compare genetic information of participants with non-participants directly, the latter being unavailable. Here, we show that alleles that are more common in participants than non-participants would be further enriched in genetic segments shared by two related participants. Genome-wide analysis was performed by comparing allele frequencies in shared and not-shared genetic segments of first-degree relative pairs of the UK Biobank. A polygenic score constructed from that analysis, in non-overlapping samples, is associated with educational attainment (P = 2.1 x 10-52), body mass index (P = 1.5 x 10-19), and participation in a dietary study (P = 6.9 x 10-21). Further analysis shows that inclination to participate is a behavioural trait in its own right, and not simply a consequence of other established phenotypes. Understanding the basis of this trait is important for data analyses and the design of future surveys, genetic or otherwise.

genetics↗

bioRxiv2020

Family Analysis with Mendelian Imputations

Genotype-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.

genetics↗

bioRxiv2020

Mendelian imputation of parental genotypes for genome-wide estimation of direct and indirect genetic effects

Associations between genotype and phenotype derive from four sources: direct genetic effects, indirect genetic effects from relatives, population stratification, and correlations with other variants affecting the phenotype through assortative mating. Genome-wide association studies (GWAS) of unrelated individuals have limited ability to distinguish the different sources of genotype-phenotype association, confusing interpretation of results and potentially leading to bias when those results are applied – in genetic prediction of traits, for example. With genetic data on families, the randomisation of genetic material during meiosis can be used to distinguish direct genetic effects from other sources of genotype-phenotype association. Genetic data on siblings is the most common form of genetic data on close relatives. We develop a method that takes advantage of identity-by-descent sharing between siblings to impute missing parental genotypes. Compared to no imputation, this increases the effective sample size for estimation of direct genetic effects and indirect parental effects by up to one third and one half respectively. We develop a related method for imputing missing parental genotypes when a parent-offspring pair is observed. We provide the imputation methods in a software package, SNIPar (single nucleotide imputation of parents), that also estimates genome-wide direct and indirect effects of SNPs. We apply this to a sample of 45,826 White British individuals in the UK Biobank who have at least one genotyped first degree relative. We estimate direct and indirect genetic effects for ∼5 million genome-wide SNPs for five traits. We estimate the correlation between direct genetic effects and effects estimated by standard GWAS to be 0.61 (S.E. 0.09) for years of education, 0.68 (S.E. 0.10) for neuroticism, 0.72 (S.E. 0.09) for smoking initiation, 0.87 (S.E. 0.04) for BMI, and 0.96 (S.E. 0.01) for height. These results suggest that GWAS based on unrelated individuals provides an inaccurate picture of direct genetic effects for certain human traits.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genetics↗

bioRxiv2017

The nature of nurture: effects of parental genotypes

Sequence variants in the parental genomes that are not transmitted to a child/proband are often ignored in genetic studies. Here we show that non-transmitted alleles can impact a child through their effects on the parents and other relatives, a phenomenon we call genetic nurture. Using results from a meta-analysis of educational attainment, the polygenic score computed for the non-transmitted alleles of 21,637 probands with at least one parent genotyped has an estimated effect on the educational attainment of the proband that is 29.9% (P = 1.6x10-14) of that of the transmitted polygenic score. Genetic nurturing effects of this polygenic score extend to other traits. Paternal and maternal polygenic scores have similar effects on educational attainment, but mothers contribute more than fathers to nutrition/heath related traits.\n\nOne Sentence SummaryNurture has a genetic component, i.e. alleles in the parents affect the parents phenotypes and through that influence the outcomes of the child.

genetics↗