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Data Integration Me...
Data Integration Methods for Phenotype Harmonization in Multi-Cohort Genome-Wide Association Studies With Behavioral Outcomes
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- 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
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- McArtor, D. B. (författare)
- Department of Psychology, University of Notre Dame, Notre Dame IN, United States
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- 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
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- Lichtenstein, P. (författare)
- Karolinska Institutet,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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- Lundström, Sebastian (författare)
- Gothenburg University,Göteborgs universitet,Gillbergcentrum,Gillberg Neuropsychiatry Centre,Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
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- 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.
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- 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
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- 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
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- 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.
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 10
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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
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas
- Av författaren/redakt...
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Luningham, J. M.
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McArtor, D. B.
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Hendriks, A. M.
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van Beijsterveld ...
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Lichtenstein, P.
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Lundström, Sebas ...
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visa fler...
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Larsson, Henrik, ...
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Bartels, M.
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Boomsma, D. I.
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Lubke, G. H.
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visa färre...
- Om ämnet
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- NATURVETENSKAP
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NATURVETENSKAP
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och Biologi
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och Genetik
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- MEDICIN OCH HÄLSOVETENSKAP
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MEDICIN OCH HÄLS ...
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och Medicinska och f ...
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och Medicinsk geneti ...
- Artiklar i publikationen
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Frontiers in Gen ...
- Av lärosätet
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Göteborgs universitet
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Karolinska Institutet
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Örebro universitet