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Sökning: id:"swepub:oai:gup.ub.gu.se/289415" > Data Integration Me...

Data Integration Methods for Phenotype Harmonization in Multi-Cohort Genome-Wide Association Studies With Behavioral Outcomes

Luningham, J. M. (författare)
Department of Psychology, University of Notre Dame, Notre Dame IN, United States; School of Public Health, Georgia State University, Atlanta GA, United States
McArtor, D. B. (författare)
Department of Psychology, University of Notre Dame, Notre Dame IN, United States
Hendriks, A. M. (författare)
Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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van Beijsterveldt, C. E. M. (författare)
Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
Lichtenstein, P. (författare)
Karolinska Institutet,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
Lundström, Sebastian (författare)
Gothenburg University,Göteborgs universitet,Gillbergcentrum,Gillberg Neuropsychiatry Centre,Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
Larsson, Henrik, 1975- (författare)
Örebro universitet,Institutionen för medicinska vetenskaper,Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden.;Orebro Univ, Sch Med Sci, Orebro, Sweden.
Bartels, M. (författare)
Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
Boomsma, D. I. (författare)
Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
Lubke, G. H. (författare)
Department of Psychology, University of Notre Dame, Notre Dame IN, United States
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 (creator_code:org_t)
2019-12-10
2019
Engelska.
Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 10
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Parallel meta-analysis is a popular approach for increasing the power to detect genetic effects in genome-wide association studies across multiple cohorts. Consortia studying the genetics of behavioral phenotypes are oftentimes faced with systematic differences in phenotype measurement across cohorts, introducing heterogeneity into the meta-analysis and reducing statistical power. This study investigated integrative data analysis (IDA) as an approach for jointly modeling the phenotype across multiple datasets. We put forth a bi-factor integration model (BFIM) that provides a single common phenotype score and accounts for sources of study-specific variability in the phenotype. In order to capitalize on this modeling strategy, a phenotype reference panel was utilized as a supplemental sample with complete data on all behavioral measures. A simulation study showed that a mega-analysis of genetic variant effects in a BFIM were more powerful than meta-analysis of genetic effects on a cohort-specific sum score of items. Saving the factor scores from the BFIM and using those as the outcome in meta-analysis was also more powerful than the sum score in most simulation conditions, but a small degree of bias was introduced by this approach. The reference panel was necessary to realize these power gains. An empirical demonstration used the BFIM to harmonize aggression scores in 9-year old children across the Netherlands Twin Register and the Child and Adolescent Twin Study in Sweden, providing a template for application of the BFIM to a range of different phenotypes. A supplemental data collection in the Netherlands Twin Register served as a reference panel for phenotype modeling across both cohorts. Our results indicate that model-based harmonization for the study of complex traits is a useful step within genetic consortia.

Ämnesord

NATURVETENSKAP  -- Biologi -- Genetik (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Genetics (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Medicinsk genetik (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Medical Genetics (hsv//eng)

Nyckelord

phenotype harmonization
genome-wide association studies
latent
variable modeling
data integration
consortia
genetic analyses
longitudinal data
imputation
twin
netherlands
neuroticism
consortium
regression
bifactor
models
Genetics & Heredity
phenotype harmonization

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