Variance Components Models for Analysis of Big Family Data of Health Outcomes in the Lifelines Cohort Study.
Twin Res Hum Genet
; 22(1): 4-13, 2019 02.
Article
en En
| MEDLINE
| ID: mdl-30944055
Large multigenerational cohort studies offer powerful ways to study the hereditary effects on various health outcomes. However, accounting for complex kinship relations in big data structures can be methodologically challenging. The traditional kinship model is computationally infeasible when considering thousands of individuals. In this article, we propose a computationally efficient alternative that employs fractional relatedness of family members through a series of founding members. The primary goal of this study is to investigate whether the effect of determinants on health outcome variables differs with and without accounting for family structure. We compare a fixed-effects model without familial effects with several variance components models that account for heritability and shared environment structure. Our secondary goal is to apply the fractional relatedness model in a realistic setting. Lifelines is a three-generation cohort study investigating the biological, behavioral, and environmental determinants of healthy aging. We analyzed a sample of 89,353 participants from 32,452 reconstructed families. Our primary conclusion is that the effect of determinants on health outcome variables does not differ with and without accounting for family structure. However, accounting for family structure through fractional relatedness allows for estimating heritability in a computationally efficient way, showing some interesting differences between physical and mental quality of life heritability. We have shown through simulations that the proposed fractional relatedness model performs better than the standard kinship model, not only in terms of computational time and convenience of fitting using standard functions in R, but also in terms of bias of heritability estimates and coverage.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Envejecimiento
/
Familia
/
Bases de Datos Genéticas
/
Interacción Gen-Ambiente
/
Macrodatos
/
Modelos Genéticos
Tipo de estudio:
Etiology_studies
/
Observational_studies
/
Prognostic_studies
Aspecto:
Patient_preference
Límite:
Female
/
Humans
/
Male
Idioma:
En
Revista:
Twin Res Hum Genet
Asunto de la revista:
GENETICA MEDICA
Año:
2019
Tipo del documento:
Article
País de afiliación:
Países Bajos
Pais de publicación:
Reino Unido