Using the phenotype differences model to identify genetic effects in samples of partially genotyped sibling pairs DOI Creative Commons
Sam Trejo, Klint Kanopka

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(49)

Published: Nov. 26, 2024

The identification of causal relationships between specific genes and social, behavioral, health outcomes is challenging due to environmental confounding from population stratification dynastic genetic effects. Existing methods eliminate leverage random variation resulting recombination require within-family dyadic data (i.e., parent–child and/or sibling pairs), meaning they can only be applied in relatively small selected samples. We introduce the phenotype differences model provide derivations showing that it—under plausible assumptions—provides consistent (and, certain cases, unbiased) estimates effects using just a single individual’s genotype. Then, leveraging distinct samples fully partially genotyped pairs Wisconsin Longitudinal Study, we use polygenic indices phenotypic for 24 different traits empirically validate model. Finally, utilize test 40 on lifespan. After 10% false discovery rate correction, find three traits—body mass index, self-rated health, chronic obstructive pulmonary disease—have statistically significant effect an

Language: Английский

Genetic basis of partner choice DOI Creative Commons

Qinwen Zheng,

Sjoerd van Alten, Torkild Hovde Lyngstad

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Abstract Previous genetic studies of human assortative mating have primarily focused on searching for its genomic footprint but revealed limited insights into biological and social mechanisms. Combining from the economics marriage market with advanced tools in statistical genetics, we perform first genome-wide association study (GWAS) a latent index partner choice. Using 206,617 individuals four global cohorts, uncover phenotypic characteristics processes underlying mating. We identify broadly robust component choice between sexes several countries correlates. also provide solutions to reduce mating-driven biases complex traits by conditioning GWAS summary statistics associations index.

Language: Английский

Citations

1
Genetic Predictors of Cognitive Decline and Labor Market Exit  DOI
Esben Agerbo,

Anne Katrine Borgbjerg,

Nabanita Datta Gupta

et al.

SSRN Electronic Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Genetic Predictors of Cognitive Decline and Labor Market Exit DOI

Anne Katrine Borgbjerg,

Esben Agerbo, Nabanita Datta Gupta

et al.

SSRN Electronic Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Family-based genome-wide association study designs for increased power and robustness DOI Creative Commons
Junming Guan, Tammy Tan,

Seyed Moeen Nehzati

et al.

Nature Genetics, Journal Year: 2025, Volume and Issue: unknown

Published: March 10, 2025

Abstract Family-based genome-wide association studies (FGWASs) use random, within-family genetic variation to remove confounding from estimates of direct effects (DGEs). Here we introduce a ‘unified estimator’ that includes individuals without genotyped relatives, unifying standard and FGWAS while increasing power for DGE estimation. We also ‘robust is not biased in structured and/or admixed populations. In an analysis 19 phenotypes the UK Biobank, unified estimator White British subsample robust (applied ancestry restrictions) increased effective sample size DGEs by 46.9% 106.5% 10.3% 21.0%, respectively, compared using differences between siblings. Polygenic predictors derived demonstrated superior out-of-sample prediction ability other family-based methods. implemented methods software package snipar efficient linear mixed model accounts relatedness sibling shared environment.

Language: Английский

Citations

0
The differential effects of common and rare genetic variants on cognitive performance across development DOI Creative Commons
Daniel Malawsky, Mahmoud Koko,

Petr Danacek

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 4, 2024

Abstract Common and rare genetic variants that impact adult cognitive performance also contribute to risk of neurodevelopmental conditions involving deficits in children. However, their influence on across early life remains poorly understood. Here, we investigate the contribution common genome-wide exonic variation childhood adolescence primarily using Avon Longitudinal Study Parents Children (n=6,495 unrelated children). We show effect associated with educational attainment increases as children age. Conversely, negative deleterious attenuates Using trio analyses, these age-related trends are driven by direct effects individual who carries variants. further find increasing stronger individuals at upper end phenotype distribution, whereas attenuating those lower end. Concordant results were observed Millenium Cohort (5,920 children) UK Biobank (101,232 adults). The broadly comparable magnitude other factors such parental attainment, maternal illness preterm birth. birth attenuate age, does not. Furthermore, relative various differ depending whether one considers phenotypic variance entire population or poor outcomes. Our findings may help explain apparent incomplete penetrance damaging conditions. More generally, they importance studying dynamic influences course differential distribution.

Language: Английский

Citations

1
Using the phenotype differences model to identify genetic effects in samples of partially genotyped sibling pairs DOI Creative Commons
Sam Trejo, Klint Kanopka

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(49)

Published: Nov. 26, 2024

The identification of causal relationships between specific genes and social, behavioral, health outcomes is challenging due to environmental confounding from population stratification dynastic genetic effects. Existing methods eliminate leverage random variation resulting recombination require within-family dyadic data (i.e., parent–child and/or sibling pairs), meaning they can only be applied in relatively small selected samples. We introduce the phenotype differences model provide derivations showing that it—under plausible assumptions—provides consistent (and, certain cases, unbiased) estimates effects using just a single individual’s genotype. Then, leveraging distinct samples fully partially genotyped pairs Wisconsin Longitudinal Study, we use polygenic indices phenotypic for 24 different traits empirically validate model. Finally, utilize test 40 on lifespan. After 10% false discovery rate correction, find three traits—body mass index, self-rated health, chronic obstructive pulmonary disease—have statistically significant effect an

Language: Английский

Citations

0