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Borairi S, Deneault AA, Madigan S, Fearon P, Devereux C, Geer M, Jeyanayagam B, Martini J, Jenkins J. A meta-analytic examination of sensitive responsiveness as a mediator between depression in mothers and psychopathology in children. Attach Hum Dev 2024; 26:273-300. [PMID: 38860779 DOI: 10.1080/14616734.2024.2359689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 05/21/2024] [Indexed: 06/12/2024]
Abstract
The current meta-analysis examined the mediating role of sensitive-responsive parenting in the relationship between depression in mothers and internalizing and externalizing behavior in children. A systematic review of the path of maternal sensitive responsiveness to child psychopathology identified eligible studies. Meta-analytic structural equation modelling (MASEM) allowed for the systematic examination of the magnitude of the indirect effect across 68 studies (N = 15,579) for internalizing and 92 studies (N = 26,218) for externalizing psychopathology. The synthesized sample included predominantly White, English-speaking children (age range = 1 to 205 months; Mage = 66 months; 47% female) from Western, industrialized countries. The indirect pathway was small in magnitude and similar for externalizing (b = .02) and internalizing psychopathology (b = .01). Moderator analyses found that the indirect pathway for externalizing problems was stronger when mother-child interactions were observed during naturalistic and free-play tasks rather than structured tasks. Other tested moderators were not significant.
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Affiliation(s)
- Sahar Borairi
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
| | | | - Sheri Madigan
- Department of Psychology, University of Calgary, Calgary, Canada
| | - Pasco Fearon
- Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Chloe Devereux
- Department of Psychology, University of Calgary, Calgary, Canada
| | - Melissa Geer
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
| | | | - Julia Martini
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
| | - Jennifer Jenkins
- Department of Applied Psychology and Human Development, University of Toronto, Toronto, Canada
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Thorp JG, Campos AI, Grotzinger AD, Gerring ZF, An J, Ong JS, Wang W, Shringarpure S, Byrne EM, MacGregor S, Martin NG, Medland SE, Middeldorp CM, Derks EM. Symptom-level modelling unravels the shared genetic architecture of anxiety and depression. Nat Hum Behav 2021; 5:1432-1442. [PMID: 33859377 DOI: 10.1038/s41562-021-01094-9] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 03/01/2021] [Indexed: 02/02/2023]
Abstract
Depression and anxiety are highly prevalent and comorbid psychiatric traits that cause considerable burden worldwide. Here we use factor analysis and genomic structural equation modelling to investigate the genetic factor structure underlying 28 items assessing depression, anxiety and neuroticism, a closely related personality trait. Symptoms of depression and anxiety loaded on two distinct, although highly genetically correlated factors, and neuroticism items were partitioned between them. We used this factor structure to conduct genome-wide association analyses on latent factors of depressive symptoms (89 independent variants, 61 genomic loci) and anxiety symptoms (102 variants, 73 loci) in the UK Biobank. Of these associated variants, 72% and 78%, respectively, replicated in an independent cohort of approximately 1.9 million individuals with self-reported diagnosis of depression and anxiety. We use these results to characterize shared and trait-specific genetic associations. Our findings provide insight into the genetic architecture of depression and anxiety and comorbidity between them.
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Affiliation(s)
- Jackson G Thorp
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia.
| | - Adrian I Campos
- Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | - Zachary F Gerring
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jiyuan An
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Jue-Sheng Ong
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | | | | | - Enda M Byrne
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Christel M Middeldorp
- Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia
- Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Queensland, Australia
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Eske M Derks
- Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
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Maes HH. Notes on Three Decades of Methodology Workshops. Behav Genet 2021; 51:170-180. [PMID: 33585974 DOI: 10.1007/s10519-021-10049-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 01/27/2021] [Indexed: 01/20/2023]
Abstract
Since 1987, a group of behavior geneticists have been teaching an annual methodology workshop on how to use state-of-the-art methods to analyze genetically informative data. In the early years, the focus was on analyzing twin and family data, using information of their known genetic relatedness to infer the role of genetic and environmental factors on phenotypic variation. With the rapid evolution of genotyping and sequencing technology and availability of measured genetic data, new methods to detect genetic variants associated with human traits were developed and became the focus of workshop teaching in alternate years. Over the years, many of the methodological advances in the field of statistical genetics have been direct outgrowths of the workshop, as evidence by the software and methodological publications authored by workshop faculty. We provide data and demographics of workshop attendees and evaluate the impact of the methodology workshops on scientific output in the field by evaluating the number of papers applying specific statistical genetic methodologies authored by individuals who have attended workshops.
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Affiliation(s)
- Hermine H Maes
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980033, Richmond, VA, 23298-0033, USA. .,Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. .,Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA. .,Department of Kinesiology, Katholieke Universiteit Leuven, Leuven, Belgium.
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Wesseldijk LW, Fedko IO, Bartels M, Nivard MG, van Beijsterveldt CEM, Boomsma DI, Middeldorp CM. Psychopathology in 7-year-old children: Differences in maternal and paternal ratings and the genetic epidemiology. Am J Med Genet B Neuropsychiatr Genet 2017; 174:251-260. [PMID: 27774759 PMCID: PMC5413051 DOI: 10.1002/ajmg.b.32500] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Accepted: 09/20/2016] [Indexed: 11/11/2022]
Abstract
The assessment of children's psychopathology is often based on parental report. Earlier studies have suggested that rater bias can affect the estimates of genetic, shared environmental and unique environmental influences on differences between children. The availability of a large dataset of maternal as well as paternal ratings of psychopathology in 7-year old children enabled (i) the analysis of informant effects on these assessments, and (ii) to obtain more reliable estimates of the genetic and non-genetic effects. DSM-oriented measures of affective, anxiety, somatic, attention-deficit/hyperactivity, oppositional-defiant, conduct, and obsessive-compulsive problems were rated for 12,310 twin pairs from the Netherlands Twin Register by mothers (N = 12,085) and fathers (N = 8,516). The effects of genetic and non-genetic effects were estimated on the common and rater-specific variance. For all scales, mean scores on maternal ratings exceeded paternal ratings. Parents largely agreed on the ranking of their child's problems (r 0.60-0.75). The heritability was estimated over 55% for maternal and paternal ratings for all scales, except for conduct problems (44-46%). Unbiased shared environmental influences, i.e., on the common variance, were significant for affective (13%), oppositional (13%), and conduct problems (37%). In clinical settings, different cutoffs for (sub)clinical scores could be applied to paternal and maternal ratings of their child's psychopathology. Only for conduct problems, shared environmental and genetic influences explain an equal amount in differences between children. For the other scales, genetic factors explain the majority of the variance, especially for the common part that is free of rater bias. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Laura W. Wesseldijk
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands,EMGO+ Institute for Health and Care ResearchAmsterdamThe Netherlands
| | - Iryna O. Fedko
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands
| | - Meike Bartels
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands,EMGO+ Institute for Health and Care ResearchAmsterdamThe Netherlands,Neuroscience Campus AmsterdamAmsterdamThe Netherlands
| | - Michel G. Nivard
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands
| | | | - Dorret I. Boomsma
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands,EMGO+ Institute for Health and Care ResearchAmsterdamThe Netherlands,Neuroscience Campus AmsterdamAmsterdamThe Netherlands
| | - Christel M. Middeldorp
- Department of Biological PsychologyVU University AmsterdamAmsterdamThe Netherlands,Neuroscience Campus AmsterdamAmsterdamThe Netherlands,Department of Child and Adolescent PsychiatryGGZ inGeest/VU University Medical CenterAmsterdamThe Netherlands
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Keizer R, Lucassen N, Jaddoe V, Tiemeier H. A Prospective Study on Father Involvement and Toddlers' Behavioral and Emotional Problems: Are Sons and Daughters Differentially Affected? ACTA ACUST UNITED AC 2014. [DOI: 10.3149/fth.1201.38] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Franić S, Borsboom D, Dolan CV, Boomsma DI. The big five personality traits: psychological entities or statistical constructs? Behav Genet 2013; 44:591-604. [PMID: 24162101 DOI: 10.1007/s10519-013-9625-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2013] [Accepted: 10/14/2013] [Indexed: 11/25/2022]
Abstract
The present study employed multivariate genetic item-level analyses to examine the ontology and the genetic and environmental etiology of the Big Five personality dimensions, as measured by the NEO Five Factor Inventory (NEO-FFI) [Costa and McCrae, Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO-FFI) professional manual, 1992; Hoekstra et al., NEO personality questionnaires NEO-PI-R, NEO-FFI: manual, 1996]. Common and independent pathway model comparison was used to test whether the five personality dimensions fully mediate the genetic and environmental effects on the items, as would be expected under the realist interpretation of the Big Five. In addition, the dimensionalities of the latent genetic and environmental structures were examined. Item scores of a population-based sample of 7,900 adult twins (including 2,805 complete twin pairs; 1,528 MZ and 1,277 DZ) on the Dutch version of the NEO-FFI were analyzed. Although both the genetic and the environmental covariance components display a 5-factor structure, applications of common and independent pathway modeling showed that they do not comply with the collinearity constraints entailed in the common pathway model. Implications for the substantive interpretation of the Big Five are discussed.
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Affiliation(s)
- Sanja Franić
- Department of Biological Psychology, Faculty of Psychology and Education, VU University Amsterdam, Van der Boechorststraat 1, 1081 BT, Amsterdam, The Netherlands,
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