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Bruins S, van Bergen E, Masselink MW, Barzeva SA, Hartman CA, Otten R, Rommelse NNJ, Dolan CV, Boomsma DI. Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below-Average Intelligence? A Population-Based Twin Study. Behav Genet 2024; 54:278-289. [PMID: 38353893 PMCID: PMC11032279 DOI: 10.1007/s10519-023-10174-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 12/20/2023] [Indexed: 04/21/2024]
Abstract
There is a negative association between intelligence and psychopathology. We analyzed data on intelligence and psychopathology to assess this association in seven-year-old Dutch twin pairs (ranging from 616 to 14,150 depending on the phenotype) and estimated the degree to which genetic and environmental factors common to intelligence and psychopathology explain the association. Secondly, we examined whether genetic and environmental effects on psychopathology are moderated by intelligence. We found that intelligence, as assessed by psychometric IQ tests, correlated negatively with childhood psychopathology, as assessed by the DSM-oriented scales of the Child Behavior Check List (CBCL). The correlations ranged between - .09 and - .15 and were mainly explained by common genetic factors. Intelligence moderated genetic and environmental effects on anxiety and negative affect, but not those on ADHD, ODD, and autism. The heritability of anxiety and negative affect was greatest in individuals with below-average intelligence. We discuss mechanisms through which this effect could arise, and we end with some recommendations for future research.
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Affiliation(s)
- Susanne Bruins
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maurits W Masselink
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Stefania A Barzeva
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Roy Otten
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Nanda N J Rommelse
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Research and Development (AR&D) Research Institute, Amsterdam, The Netherlands
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2
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Hubers N, Hagenbeek FA, Pool R, Déjean S, Harms AC, Roetman PJ, van Beijsterveldt CEM, Fanos V, Ehli EA, Vermeiren RRJM, Bartels M, Hottenga JJ, Hankemeier T, van Dongen J, Boomsma DI. Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32955. [PMID: 37534875 DOI: 10.1002/ajmg.b.32955] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 06/13/2023] [Accepted: 07/11/2023] [Indexed: 08/04/2023]
Abstract
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
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Affiliation(s)
- Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Sébastien Déjean
- Toulouse Mathematics Institute, UMR 5219, University of Toulouse, CNRS, Toulouse, France
| | - Amy C Harms
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Peter J Roetman
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Vassilios Fanos
- Department of Surgical Sciences, University of Cagliari and Neonatal Intensive Care Unit, Cagliari, Italy
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, South Dakota, USA
| | - Robert R J M Vermeiren
- LUMC-Curium, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Leiden, the Netherlands
- Youz, Parnassia Group, the Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Thomas Hankemeier
- Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands
- The Netherlands Metabolomics Centre, Leiden, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
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3
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Kevenaar ST, van Bergen E, Oldehinkel AJ, Boomsma DI, Dolan CV. The relationship of school performance with self-control and grit is strongly genetic and weakly causal. NPJ SCIENCE OF LEARNING 2023; 8:53. [PMID: 38049407 PMCID: PMC10696063 DOI: 10.1038/s41539-023-00198-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 10/17/2023] [Indexed: 12/06/2023]
Abstract
The non-cognitive skills self-control and grit are often considered predictors of school performance, but whether this relationship is causal remains unclear. We investigated the causality of this association using a twin design. Specifically, we evaluated the direct impact of self-control and grit on school performance, while controlling for genetic or environmental influences common to all three traits (i.e., confounding). Teachers of 4891 Dutch 12-year-old twin pairs (of which 3837 were complete pairs) completed a survey about school performance (school grades), self-control (ASEBA self-control scale), and the perseverance aspect of grit. Our analysis aimed to determine the direct impact of self-control and grit on school performance, while simultaneously controlling for genetic or environmental confounding. Establishing the regression relationship corrected for confounding supports the interpretation of the regression relationship as causal. In all analyses, we corrected for sex, rater bias of the teachers, and parental socioeconomic status. Initially, in the standard regression, self-control, and grit explained 28.4% of the school performance variance. However, allowing for genetic confounding (due to genetic pleiotropy) revealed that most of this association could be attributed to genetic influences that the three traits share. In the presence of genetic pleiotropy, the phenotypic regression of school performance on self-control and grit accounted for only 4.4% (i.e., the effect size association with the causal hypothesis). In conclusion, self-control and grit predict school performance primarily due to genetic pleiotropy, with a much smaller causal effect (R2 = 4.4%). This suggests that interventions targeting self-control and grit alone may yield limited improvements in school performance.
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Affiliation(s)
- Sofieke T Kevenaar
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
| | - Albertine J Oldehinkel
- University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
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4
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Bizzarri D, Reinders MJT, Beekman M, Slagboom PE, van den Akker EB. Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health's 1H-NMR Metabolomics Platform. Metabolites 2023; 13:1181. [PMID: 38132863 PMCID: PMC10745109 DOI: 10.3390/metabo13121181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 11/07/2023] [Accepted: 11/17/2023] [Indexed: 12/23/2023] Open
Abstract
1H-NMR metabolomics data is increasingly used to track health and disease. Nightingale Health, a major supplier of 1H-NMR metabolomics, has recently updated the quantification strategy to further align with clinical standards. Such updates, however, might influence backward replicability, particularly affecting studies with repeated measures. Using data from BBMRI-NL consortium (~28,000 samples from 28 cohorts), we compared Nightingale data, originally released in 2014 and 2016, with a re-quantified version released in 2020, of which both versions were based on the same NMR spectra. Apart from two discontinued and twenty-three new analytes, we generally observe a high concordance between quantification versions with 73 out of 222 (33%) analytes showing a mean ρ > 0.9 across all cohorts. Conversely, five analytes consistently showed lower Spearman's correlations (ρ < 0.7) between versions, namely acetoacetate, LDL-L, saturated fatty acids, S-HDL-C, and sphingomyelins. Furthermore, previously trained multi-analyte scores, such as MetaboAge or MetaboHealth, might be particularly sensitive to platform changes. Whereas MetaboHealth replicated well, the MetaboAge score had to be retrained due to use of discontinued analytes. Notably, both scores in the re-quantified data recapitulated mortality associations observed previously. Concluding, we urge caution in utilizing different platform versions to avoid mixing analytes, having different units, or simply being discontinued.
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Affiliation(s)
- Daniele Bizzarri
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Leiden Computational Biology Center, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Delft Bioinformatics Lab., Department of Intelligent Systems, TU Delft, 2628 XE Delft, The Netherlands
| | - Marcel J. T. Reinders
- Leiden Computational Biology Center, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Delft Bioinformatics Lab., Department of Intelligent Systems, TU Delft, 2628 XE Delft, The Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
| | - P. Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Max Planck Institute for the Biology of Ageing, 50931 Cologne, Germany
| | - Erik B. van den Akker
- Molecular Epidemiology, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Leiden Computational Biology Center, Department of Biomedical Data Science, Leiden University Medical Center, 2333 ZC Leiden, The Netherlands
- Delft Bioinformatics Lab., Department of Intelligent Systems, TU Delft, 2628 XE Delft, The Netherlands
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5
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Beck JJ, Ahmed T, Finnicum CT, Zwinderman K, Ehli EA, Boomsma DI, Hottenga JJ. Genetic Ancestry Estimates within Dutch Family Units and Across Genotyping Arrays: Insights from Empirical Analysis Using Two Estimation Methods. Genes (Basel) 2023; 14:1497. [PMID: 37510400 PMCID: PMC10379078 DOI: 10.3390/genes14071497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/12/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023] Open
Abstract
Accurate inference of genetic ancestry is crucial for population-based association studies, accounting for population heterogeneity and structure. This study analyzes genome-wide SNP data from the Netherlands Twin Register to compare genetic ancestry estimates. The focus is on the comparison of ancestry estimates between family members and individuals genotyped on multiple arrays (Affymetrix 6.0, Affymetrix Axiom, and Illumina GSA). Two conventional methods, principal component analysis and ADMIXTURE, were implemented to estimate ancestry, each serving its specific purpose, rather than for direct comparison. The results reveal that as the degree of genetic relatedness decreases, the Euclidean distances of genetic ancestry estimates between family members significantly increase (empirical p < 0.001), regardless of the estimation method and genotyping array. Ancestry estimates among individuals genotyped on multiple arrays also show statistically significant differences (empirical p < 0.001). Additionally, this study investigates the relationship between the ancestry estimates of non-identical twin offspring with ancestrally diverse parents and those with ancestrally similar parents. The results indicate a statistically significant weak correlation between the variation in ancestry estimates among offspring and differences in ancestry estimates among parents (Spearman's rho: 0.07, p = 0.005). This study highlights the utility of current methods in inferring genetic ancestry, emphasizing the importance of reference population composition in determining ancestry estimates.
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Affiliation(s)
- Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Talitha Ahmed
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Casey T Finnicum
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Koos Zwinderman
- Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Academic Medical Center Amsterdam, 1105 AZ Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
| | - Dorret I Boomsma
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD 57105, USA
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
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6
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Bruins S, Hottenga JJ, Neale MC, Pool R, Boomsma DI, Dolan CV. Environment-by-PGS Interaction in the Classical Twin Design: An Application to Childhood Anxiety and Negative Affect. MULTIVARIATE BEHAVIORAL RESEARCH 2023:1-13. [PMID: 37439516 PMCID: PMC11157501 DOI: 10.1080/00273171.2023.2228763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/14/2023]
Abstract
One type of genotype-environment interaction occurs when genetic effects on a phenotype are moderated by an environment; or when environmental effects on a phenotype are moderated by genes. Here we outline these types of genotype-environment interaction models, and propose a test of genotype-environment interaction based on the classical twin design, which includes observed genetic variables (polygenic scores: PGSs) that account for part of the genetic variance of the phenotype. We introduce environment-by-PGS interaction and the results of a simulation study to address statistical power and parameter recovery. Next, we apply the model to empirical data on anxiety and negative affect in children. The power to detect environment-by-PGS interaction depends on the heritability of the phenotype, and the strength of the PGS. The simulation results indicate that under realistic conditions of sample size, heritability and strength of the interaction, the environment-by-PGS model is a viable approach to detect genotype-environment interaction. In 7-year-old children, we defined two PGS based on the largest genetic association studies for 2 traits that are genetically correlated to childhood anxiety and negative affect, namely major depression (MDD) and intelligence (IQ). We find that common environmental influences on negative affect are amplified for children with a lower IQ-PGS.
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Affiliation(s)
- Susanne Bruins
- Department of Biological Psychology, Vrije Universiteit
- Amsterdam Public Health research institute
| | | | - Michael C. Neale
- Department of Biological Psychology, Vrije Universiteit
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit
- Amsterdam Public Health research institute
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit
- Amsterdam Public Health research institute
- Amsterdam Reproduction and Development research institute
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7
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Kevenaar ST, Dolan CV, Boomsma DI, van Bergen E. Self-control and grit are associated with school performance mainly because of shared genetic effects. JCPP ADVANCES 2023; 3:e12159. [PMID: 37753153 PMCID: PMC10519738 DOI: 10.1002/jcv2.12159] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 03/06/2023] [Indexed: 09/28/2023] Open
Abstract
Background By combining the classical twin design with regression analysis, we investigated the role of two non-cognitive factors, self-control and grit, in the prediction of school performance. We did so at the phenotypic, genetic, and environmental level. Methods Teachers filled out a survey on the twins' school performance (school grades for reading, literacy, and math), self-control (ASEBA self-control scale), and grit (the perseverance aspect) for 4891 Dutch 12-years-old twin pairs (3837 pairs with data for both and 1054 pairs with data for one of the twins). We employed regression analyses to first assess the contributions of self-control and grit to school performance at the phenotypic level, and next at the genetic and environmental level, while correcting for rater (teacher) effects, parental SES, and sex. Results Higher SES was associated with better school performance, self-control, and grit. On average, girls had more self-control and grit than boys. Corrected for sex, SES, and teacher rater effects, genetic factors accounted for 74%, 69%, and 58% of the phenotypic variance of school performance, self-control, and grit, respectively. Phenotypically, self-control and grit explained 28.3% of the variance in school performance. We found that this phenotypic result largely reflected genetic influences. Conclusions Children who have better self-control and are grittier tend to do better in school. Individual differences in these three traits are not correlated because of shared environmental influences, but mainly because of shared genetic factors.
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Affiliation(s)
- Sofieke T. Kevenaar
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Research Institute LEARN!Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Conor V. Dolan
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
- Amsterdam Reproduction and Development Research InstituteAmsterdamThe Netherlands
| | - Elsje van Bergen
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Research Institute LEARN!Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
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8
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The heritability of vocal tract structures estimated from structural MRI in a large cohort of Dutch twins. Hum Genet 2022; 141:1905-1923. [PMID: 35831475 DOI: 10.1007/s00439-022-02469-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/18/2022] [Indexed: 11/04/2022]
Abstract
While language is expressed in multiple modalities, including sign, writing, or whistles, speech is arguably the most common. The human vocal tract is capable of producing the bewildering diversity of the 7000 or so currently spoken languages, but relatively little is known about its genetic bases, especially in what concerns normal variation. Here, we capitalize on five cohorts totaling 632 Dutch twins with structural magnetic resonance imaging (MRI) data. Two raters placed clearly defined (semi)landmarks on each MRI scan, from which we derived 146 measures capturing the dimensions and shape of various vocal tract structures, but also aspects of the head and face. We used Genetic Covariance Structure Modeling to estimate the additive genetic, common environmental or non-additive genetic, and unique environmental components, while controlling for various confounds and for any systematic differences between the two raters. We found high heritability, h2, for aspects of the skull and face, the mandible, the anteroposterior (horizontal) dimension of the vocal tract, and the position of the hyoid bone. These findings extend the existing literature, and open new perspectives for understanding the complex interplay between genetics, environment, and culture that shape our vocal tracts, and which may help explain cross-linguistic differences in phonetics and phonology.
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9
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Knigge A, Maas I, Stienstra K, de Zeeuw EL, Boomsma DI. Delayed tracking and inequality of opportunity: Gene-environment interactions in educational attainment. NPJ SCIENCE OF LEARNING 2022; 7:6. [PMID: 35508471 PMCID: PMC9068802 DOI: 10.1038/s41539-022-00122-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
There are concerns that ability tracking at a young age increases unequal opportunities for children of different socioeconomic background to develop their potential. To disentangle family influence and potential ability, we applied moderation models to twin data on secondary educational track level from the Netherlands Twin Register (N = 8847). Delaying tracking to a later age is associated with a lower shared environmental influence and a larger genetic influence on track level in adolescence. This is in line with the idea that delaying tracking improves equality of opportunity. Our results further suggest that this is mostly because delaying tracking reduces the indirect influence of family background on track level via the test performance of students. Importantly, delaying tracking improves the realization of genetic potential especially among students with low test scores, while it lowers shared environmental influence on track level for students of all test performance levels.
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Affiliation(s)
- Antonie Knigge
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands.
| | - Ineke Maas
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands
- Department of Sociology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Kim Stienstra
- Department of Sociology/ICS, Utrecht University, Utrecht, The Netherlands
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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10
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Rajula HSR, Manchia M, Agarwal K, Akingbuwa WA, Allegrini AG, Diemer E, Doering S, Haan E, Jami ES, Karhunen V, Leone M, Schellhas L, Thompson A, van den Berg SM, Bergen SE, Kuja-Halkola R, Hammerschlag AR, Järvelin MR, Leval A, Lichtenstein P, Lundstrom S, Mauri M, Munafò MR, Myers D, Plomin R, Rimfeld K, Tiemeier H, Ystrom E, Fanos V, Bartels M, Middeldorp CM. Overview of CAPICE-Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Skłodowska-Curie International Training Network. Eur Child Adolesc Psychiatry 2022; 31:829-839. [PMID: 33474652 PMCID: PMC9142454 DOI: 10.1007/s00787-020-01713-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 12/21/2020] [Indexed: 01/30/2023]
Abstract
The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).
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Affiliation(s)
- Hema Sekhar Reddy Rajula
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, Cagliari, Italy
| | - Mirko Manchia
- Section of Psychiatry, Department of Medical Science and Public Health, University of Cagliari, Cagliari, Italy.,Department of Pharmacology, Dalhousie University, Halifax, NS, Canada
| | - Kratika Agarwal
- Department of Learning, Data Analytics and Technology, University of Twente, Enschede, The Netherlands
| | - Wonuola A Akingbuwa
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Andrea G Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Elizabeth Diemer
- Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Sabrina Doering
- Centre for Ethics, Law and Mental Health (CELAM), Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | - Elis Haan
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Psychological Science, University of Bristol, Bristol, UK
| | - Eshim S Jami
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Marica Leone
- Janssen Pharmaceutical, Global Commercial Strategy Organization, Stockholm, Sweden.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Schellhas
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Psychological Science, University of Bristol, Bristol, UK
| | - Ashley Thompson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Stéphanie M van den Berg
- Department of Learning, Data Analytics and Technology, University of Twente, Enschede, The Netherlands
| | - Sarah E Bergen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anke R Hammerschlag
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.,Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Australia
| | - Marjo Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulun yliopisto, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.,Department of Life Sciences, College of Health and Life Sciences, Brunel University , London, UK
| | - Amy Leval
- Janssen Pharmaceutical, Global Commercial Strategy Organization, Stockholm, Sweden.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundstrom
- Centre for Ethics, Law and Mental Health (CELAM), Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | | | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Psychological Science, University of Bristol, Bristol, UK
| | - David Myers
- Janssen Pharmaceutical, Global Commercial Strategy Organization, Stockholm, Sweden
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Henning Tiemeier
- Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Eivind Ystrom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway.,Norwegian Institute of Public Health, Oslo, Norway.,Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, Cagliari, Italy
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Christel M Middeldorp
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. .,Child Health Research Centre, Level 6, Centre for Children's Health Research, University of Queensland, 62 Graham Street, South Brisbane, QLD, 4101, Australia. .,Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, Australia.
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11
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Teeuw J, Klein M, Mota NR, Brouwer RM, van ‘t Ent D, Al-Hassaan Z, Franke B, Boomsma DI, Hulshoff Pol HE. Multivariate Genetic Structure of Externalizing Behavior and Structural Brain Development in a Longitudinal Adolescent Twin Sample. Int J Mol Sci 2022; 23:ijms23063176. [PMID: 35328598 PMCID: PMC8949114 DOI: 10.3390/ijms23063176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/10/2022] [Accepted: 03/10/2022] [Indexed: 12/10/2022] Open
Abstract
Externalizing behavior in its more extreme form is often considered a problem to the individual, their families, teachers, and society as a whole. Several brain structures have been linked to externalizing behavior and such associations may arise if the (co)development of externalizing behavior and brain structures share the same genetic and/or environmental factor(s). We assessed externalizing behavior with the Child Behavior Checklist and Youth Self Report, and the brain volumes and white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) with magnetic resonance imaging in the BrainSCALE cohort, which consisted of twins and their older siblings from 112 families measured longitudinally at ages 10, 13, and 18 years for the twins. Genetic covariance modeling based on the classical twin design, extended to also include siblings of twins, showed that genes influence externalizing behavior and changes therein (h2 up to 88%). More pronounced externalizing behavior was associated with higher FA (observed correlation rph up to +0.20) and lower MD (rph up to −0.20), with sizeable genetic correlations (FA ra up to +0.42; MD ra up to −0.33). The cortical gray matter (CGM; rph up to −0.20) and cerebral white matter (CWM; rph up to +0.20) volume were phenotypically but not genetically associated with externalizing behavior. These results suggest a potential mediating role for global brain structures in the display of externalizing behavior during adolescence that are both partially explained by the influence of the same genetic factor.
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Affiliation(s)
- Jalmar Teeuw
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Correspondence: ; Tel.: +31-(088)-75-53-387
| | - Marieke Klein
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA;
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Nina Roth Mota
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
| | - Rachel M. Brouwer
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Dennis van ‘t Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
| | - Zyneb Al-Hassaan
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands; (N.R.M.); (B.F.)
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands; (D.v.‘t.E.); (D.I.B.)
- Amsterdam Public Health (APH) Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Hilleke E. Hulshoff Pol
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands; (R.M.B.); (Z.A.-H.); (H.E.H.P.)
- Department of Psychology, Utrecht University, 3584 CS Utrecht, The Netherlands
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12
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van Dongen J, Gordon SD, McRae AF, Odintsova VV, Mbarek H, Breeze CE, Sugden K, Lundgren S, Castillo-Fernandez JE, Hannon E, Moffitt TE, Hagenbeek FA, van Beijsterveldt CEM, Jan Hottenga J, Tsai PC, Min JL, Hemani G, Ehli EA, Paul F, Stern CD, Heijmans BT, Slagboom PE, Daxinger L, van der Maarel SM, de Geus EJC, Willemsen G, Montgomery GW, Reversade B, Ollikainen M, Kaprio J, Spector TD, Bell JT, Mill J, Caspi A, Martin NG, Boomsma DI. Identical twins carry a persistent epigenetic signature of early genome programming. Nat Commun 2021; 12:5618. [PMID: 34584077 PMCID: PMC8479069 DOI: 10.1038/s41467-021-25583-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 07/19/2021] [Indexed: 02/08/2023] Open
Abstract
Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.
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Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
| | - Scott D Gordon
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | | | - Karen Sugden
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | | | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Josine L Min
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, USA
| | - Franziska Paul
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
| | - Claudio D Stern
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Lucia Daxinger
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Bruno Reversade
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Medical Genetics Department, KOC University, School of Medicine, Istanbul, Turkey
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicholas G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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13
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Enck P, Goebel-Stengel M, Rieß O, Hübener-Schmid J, Kagan KO, Nieß AM, Tümmers H, Wiesing U, Zipfel S, Stengel A. [Twin research in Germany]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2021; 64:1298-1306. [PMID: 34524474 PMCID: PMC8441034 DOI: 10.1007/s00103-021-03400-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 07/23/2021] [Indexed: 12/16/2022]
Abstract
Nach dem Zweiten Weltkrieg wurden weltweit Zwillingskohorten aufgebaut, die inzwischen ca. 1,5 Mio. Zwillinge umfassen und zwischen 1950 und 2012 über 2748 Zwillingsstudien hervorgebracht haben. Diese Zahl steigt jedes Jahr um weitere 500 bis 1000. Die Unterrepräsentanz deutscher Zwillingsstudien in diesen Datenbanken lässt sich nicht allein durch den Missbrauch medizinischer Forschung im Nationalsozialismus erklären. Entwicklung und Ausbau großer Zwillingskohorten sind ethisch und datenschutzrechtlich eine Herausforderung. Zwillingskohorten ermöglichen jedoch die Langzeit- und Echtzeiterforschung vieler medizinischer Fragestellungen; und die Zwillingsstudien tragen auch nach der Entschlüsselung des Humangenoms erheblich zur Beantwortung der Frage nach Anlage oder Umwelt als mögliche Erkrankungsauslöser bei. Derzeit gibt es 2 deutsche Zwillingskohorten: die biomedizinische Kohorte HealthTwiSt mit ca. 1500 Zwillingspaaren und TwinLife, eine soziologisch-psychologische Kohorte mit ca. 4000 Zwillingspaaren. Daneben gibt es krankheitsspezifische Kohorten. 2016 startete das TwinHealth-Konsortium der Medizinischen Fakultät der Universität Tübingen mit dem Ziel, eine forschungsoffene und nachhaltige Zwillingsforschung am Standort Tübingen zur Bearbeitung unterschiedlicher Fragestellungen zu etablieren. Der Artikel bietet mithilfe einer systematischen Literaturrecherche und einer medizinhistorischen Betrachtung einen Überblick über die weltweite und nationale Entwicklung von Zwillingsstudien und -datenbanken der letzten 100 Jahre. Anhand der Tübinger TwinHealth-Initiative beleuchtet er den Aufbau eines Zwillingskollektivs und dessen juristische, ethische und Datenschutzaspekte.
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Affiliation(s)
- Paul Enck
- Innere Medizin VI, Psychosomatische Medizin und Psychotherapie, Universitätsklinikum Tübingen, Osianderstr. 5, 72076, Tübingen, Deutschland
| | - Miriam Goebel-Stengel
- Innere Medizin VI, Psychosomatische Medizin und Psychotherapie, Universitätsklinikum Tübingen, Osianderstr. 5, 72076, Tübingen, Deutschland. .,Klinik für Innere Medizin, Helios Klinik Rottweil, Rottweil, Deutschland.
| | - Olaf Rieß
- Institut für Medizinische Genetik und Angewandte Genomik, Universitätsklinikum Tübingen, Tübingen, Deutschland
| | - Jeannette Hübener-Schmid
- Institut für Medizinische Genetik und Angewandte Genomik, Universitätsklinikum Tübingen, Tübingen, Deutschland
| | - Karl Oliver Kagan
- Department für Frauengesundheit, Universitäts-Frauenklinik, Universitätsklinikum Tübingen, Tübingen, Deutschland
| | - Andreas Michael Nieß
- Innere Medizin V, Sportmedizin, Universitätsklinikum Tübingen, Tübingen, Deutschland
| | - Henning Tümmers
- Institut für Ethik und Geschichte der Medizin, Universität Tübingen, Tübingen, Deutschland
| | - Urban Wiesing
- Institut für Ethik und Geschichte der Medizin, Universität Tübingen, Tübingen, Deutschland
| | - Stephan Zipfel
- Innere Medizin VI, Psychosomatische Medizin und Psychotherapie, Universitätsklinikum Tübingen, Osianderstr. 5, 72076, Tübingen, Deutschland
| | - Andreas Stengel
- Innere Medizin VI, Psychosomatische Medizin und Psychotherapie, Universitätsklinikum Tübingen, Osianderstr. 5, 72076, Tübingen, Deutschland
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14
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Slob EMA, Brew BK, Vijverberg SJH, Dijs T, van Beijsterveldt CEM, Koppelman GH, Bartels M, Dolan CV, Larsson H, Lundström S, Lichtenstein P, Gong T, Maitland-van der Zee AH, Kraneveld AD, Almqvist C, Boomsma DI. Early-life antibiotic use and risk of attention-deficit hyperactivity disorder and autism spectrum disorder: results of a discordant twin study. Int J Epidemiol 2021; 50:475-484. [PMID: 33179025 PMCID: PMC8248483 DOI: 10.1093/ije/dyaa168] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/14/2020] [Indexed: 12/12/2022] Open
Abstract
Background Development of the gut-brain axis in early life may be disturbed by
antibiotic use. It has been hypothesized that this disturbance may
contribute to development of neurodevelopmental disorders, including autism
spectrum disorder and attention-deficit hyperactivity disorder. We aimed to
assess the association between antibiotic use in early life and the risk of
developing attention-deficit hyperactivity disorder or autism spectrum
disorder, while controlling for shared genetic and environmental factors in
a discordant twin design. Methods We conducted a cohort study in twins (7–12 years;
25 781 twins) from the Netherlands Twin Register (NTR) and a
replication study in the Childhood and Adolescent Twin Study in Sweden
(CATSS; 7946 9-year-old twins). Antibiotic use was recorded before age 2
years. Attention-deficit hyperactivity disorder and autism spectrum disorder
were parent-reported in the Netherlands Twin Register and register-based in
the Childhood and Adolescent Twin Study in Sweden. Results Early-life antibiotic use was associated with increased risk of
attention-deficit hyperactivity disorder development [pooled odds ratio (OR)
1.10, 95% confidence interval (CI) 1.02-1.17] and autism spectrum
disorder (pooled OR 1.15, 95% CI 1.06-1.25) in a case-control
design. When restricting to monozygotic twin pairs discordant for the
outcome, associations disappeared for both disorders in both cohorts
(attention-deficit hyperactivity disorder OR 0.90, 95% CI 0.48-1.69
and OR 0.80, 95% CI 0.37-1.76, and autism spectrum disorder OR 0.66,
95% CI 0.38-1.16 and OR 0.29, 95% CI 0.02-4.50,
respectively). Conclusions Our findings suggest that the association between early-life antibiotic use
and risk of attention-deficit hyperactivity and autism spectrum disorder may
be confounded by shared familial environment and genetics.
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Affiliation(s)
- Elise M A Slob
- Department of Respiratory Medicine, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands.,Department of Paediatric Pulmonology, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands
| | - Bronwyn K Brew
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,National Perinatal Epidemiology and Statistics Unit, Centre for Big Data Research in Health & Department of Women's and Children's Health, UNSW, Sydney, NSW, Australia
| | - Susanne J H Vijverberg
- Department of Respiratory Medicine, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands.,Department of Paediatric Pulmonology, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands
| | - Talitha Dijs
- Department of Respiratory Medicine, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands.,Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | | | - Gerard H Koppelman
- Department of Paediatric Pulmonology & Paediatric Allergology, Beatrix Children's Hospital, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma & COPD (GRIAC), University Medical Center Groningen, Groningen, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,School of Medical Sciences, Orebro University, Orebro, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Centre for Ethics Law and Mental Health (CELAM), Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anke H Maitland-van der Zee
- Department of Respiratory Medicine, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands.,Department of Paediatric Pulmonology, Amsterdam University Medical Centers, DE Amsterdam, The Netherlands
| | - Aletta D Kraneveld
- Division of Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.,Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Paediatric Allergy and Pulmonology Unit, Karolinska University Hospital, Stockholm, Sweden
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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15
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Beck JJ, Pool R, van de Weijer M, Chen X, Krapohl E, Gordon SD, Nygaard M, Debrabant B, Palviainen T, van der Zee MD, Baselmans B, Finnicum CT, Yi L, Lundström S, van Beijsterveldt T, Christiansen L, Heikkilä K, Kittelsrud J, Loukola A, Ollikainen M, Christensen K, Martin NG, Plomin R, Nivard M, Bartels M, Dolan C, Willemsen G, de Geus E, Almqvist C, Magnusson PKE, Mbarek H, Ehli EA, Boomsma DI, Hottenga JJ. Genetic Meta-Analysis of Twin Birth Weight Shows High Genetic Correlation with Singleton Birth Weight. Hum Mol Genet 2021; 30:1894-1905. [PMID: 33955455 PMCID: PMC8444448 DOI: 10.1093/hmg/ddab121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/19/2021] [Accepted: 04/20/2021] [Indexed: 01/09/2023] Open
Abstract
Birth weight (BW) is an important predictor of newborn survival and health and has associations with many adult health outcomes, including cardio-metabolic disorders, autoimmune diseases, and mental health. On average, twins have a lower BW than singletons as a result of a different pattern of fetal growth and shorter gestational duration. Therefore, investigations into the genetics of BW often exclude data from twins, leading to a reduction in sample size and remaining ambiguities concerning the genetic contribution to BW in twins. In this study, we carried out a genome-wide association meta-analysis of BW in 42 212 twin individuals and found a positive correlation of beta values (Pearson's r = 0.66, 95% confidence interval [CI]: 0.47-0.77) with 150 previously reported genome-wide significant variants for singleton BW. We identified strong positive genetic correlations between BW in twins and numerous anthropometric traits, most notably with BW in singletons (genetic correlation [rg] = 0.92, 95% CI: 0.66-1.18). Genetic correlations of BW in twins with a series of health-related traits closely resembled those previously observed for BW in singletons. Polygenic scores constructed from a genome-wide association study on BW in UK Biobank demonstrated strong predictive power in a target sample of Dutch twins and singletons. Together, our results indicate that a similar genetic architecture underlies BW in twins and singletons and that future genome-wide studies might benefit from including data from large twin registers.
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Affiliation(s)
- Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, United States of America
| | - René Pool
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Margot van de Weijer
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Xu Chen
- Department of Medical Epidemiology and Biostatististics, Karolinska Institutet, Stockholm, Sweden
| | - Eva Krapohl
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Scott D Gordon
- Genetic Epidemiology Laboratory, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Birgit Debrabant
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Teemu Palviainen
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Matthijs D van der Zee
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Bart Baselmans
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands.,Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Casey T Finnicum
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, United States of America
| | - Lu Yi
- Department of Medical Epidemiology and Biostatististics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Toos van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Lene Christiansen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kauko Heikkilä
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Julie Kittelsrud
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, United States of America
| | - Anu Loukola
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Miina Ollikainen
- University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Nicholas G Martin
- Genetic Epidemiology Laboratory, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Robert Plomin
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Michel Nivard
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor Dolan
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Eco de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatististics, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatististics, Karolinska Institutet, Stockholm, Sweden
| | - Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, United States of America
| | - Dorret I Boomsma
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, South Dakota, United States of America.,Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit, Amsterdam, The Netherlands
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16
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de Vries LP, van Beijsterveldt TCEM, Maes H, Colodro-Conde L, Bartels M. Genetic Influences on the Covariance and Genetic Correlations in a Bivariate Twin Model: An Application to Well-Being. Behav Genet 2021; 51:191-203. [PMID: 33582898 PMCID: PMC8093176 DOI: 10.1007/s10519-021-10046-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 01/21/2021] [Indexed: 01/07/2023]
Abstract
The distinction between genetic influences on the covariance (or bivariate heritability) and genetic correlations in bivariate twin models is often not well-understood or only one is reported while the results show distinctive information about the relation between traits. We applied bivariate twin models in a large sample of adolescent twins, to disentangle the association between well-being (WB) and four complex traits (optimism, anxious-depressed symptoms (AD), aggressive behaviour (AGG), and educational achievement (EA)). Optimism and AD showed respectively a strong positive and negative phenotypic correlation with WB, the negative correlation of WB and AGG is lower and the correlation with EA is nearly zero. All four traits showed a large genetic contribution to the covariance with well-being. The genetic correlations of well-being with optimism and AD are strong and smaller for AGG and EA. We used the results of the models to explain what information is retrieved based on the bivariate heritability versus the genetic correlations and the (clinical) implications.
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Affiliation(s)
- Lianne P de Vries
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, Netherlands.
| | - Toos C E M van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Hermine Maes
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Lucía Colodro-Conde
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QL, Australia
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, Netherlands
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17
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Boomsma DI, van Beijsterveldt TCEM, Odintsova VV, Neale MC, Dolan CV. Genetically Informed Regression Analysis: Application to Aggression Prediction by Inattention and Hyperactivity in Children and Adults. Behav Genet 2021; 51:250-263. [PMID: 33259025 PMCID: PMC8093158 DOI: 10.1007/s10519-020-10025-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 10/06/2020] [Indexed: 12/11/2022]
Abstract
We present a procedure to simultaneously fit a genetic covariance structure model and a regression model to multivariate data from mono- and dizygotic twin pairs to test for the prediction of a dependent trait by multiple correlated predictors. We applied the model to aggressive behavior as an outcome trait and investigated the prediction of aggression from inattention (InA) and hyperactivity (HA) in two age groups. Predictions were examined in twins with an average age of 10 years (11,345 pairs), and in adult twins with an average age of 30 years (7433 pairs). All phenotypes were assessed by the same, but age-appropriate, instruments in children and adults. Because of the different genetic architecture of aggression, InA and HA, a model was fitted to these data that specified additive and non-additive genetic factors (A and D) plus common and unique environmental (C and E) influences. Given appropriate identifying constraints, this ADCE model is identified in trivariate data. We obtained different results for the prediction of aggression in children, where HA was the more important predictor, and in adults, where InA was the more important predictor. In children, about 36% of the total aggression variance was explained by the genetic and environmental components of HA and InA. Most of this was explained by the genetic components of HA and InA, i.e., 29.7%, with 22.6% due to the genetic component of HA. In adults, about 21% of the aggression variance was explained. Most was this was again explained by the genetic components of InA and HA (16.2%), with 8.6% due to the genetic component of InA.
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Affiliation(s)
- Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands.
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development Research Institutes, Amsterdam, The Netherlands.
| | | | - Veronika V Odintsova
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development Research Institutes, Amsterdam, The Netherlands
| | - Michael C Neale
- Departments of Psychiatry and Human & Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, 1-156, P.O. Box 980126, Richmond, VA, 23298-0126, USA
| | - Conor V Dolan
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development Research Institutes, Amsterdam, The Netherlands
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18
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Whipp AM, Vuoksimaa E, Bolhuis K, de Zeeuw EL, Korhonen T, Mauri M, Pulkkinen L, Rimfeld K, Rose RJ, van Beijsterveldt C(TEM, Bartels M, Plomin R, Tiemeier H, Kaprio J, Boomsma DI. Teacher-rated aggression and co-occurring behaviors and emotional problems among schoolchildren in four population-based European cohorts. PLoS One 2021; 16:e0238667. [PMID: 33914742 PMCID: PMC8084195 DOI: 10.1371/journal.pone.0238667] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 03/31/2021] [Indexed: 11/18/2022] Open
Abstract
Aggressive behavior in school is an ongoing concern. The current focus is on specific manifestations such as bullying, but the behavior is broad and heterogenous. Children spend a substantial amount of time in school, but their behaviors in the school setting tend to be less well characterized than at home. Because aggression may index multiple behavioral problems, we used three validated instruments to assess means, correlations and gender differences of teacher-rated aggressive behavior with co-occurring externalizing/internalizing problems and social behavior in 39,936 schoolchildren aged 7-14 from 4 population-based cohorts from Finland, the Netherlands, and the UK. Correlations of aggressive behavior were high with all other externalizing problems (r: 0.47-0.80) and lower with internalizing problems (r: 0.02-0.39). A negative association was observed with prosocial behavior (r: -0.33 to -0.54). Mean levels of aggressive behavior differed significantly by gender. Despite the higher mean levels of aggressive behavior in boys, the correlations were notably similar for boys and girls (e.g., aggressive-hyperactivity correlations: 0.51-0.75 boys, 0.47-0.70 girls) and did not vary greatly with respect to age, instrument or cohort. Thus, teacher-rated aggressive behavior rarely occurs in isolation; boys and girls with problems of aggressive behavior likely require help with other behavioral and emotional problems. Important to note, higher aggressive behavior is not only associated with higher amounts of other externalizing and internalizing problems but also with lower levels of prosocial behavior.
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Affiliation(s)
- Alyce M. Whipp
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- * E-mail:
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Koen Bolhuis
- Department of Child and Adolescent Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Eveline L. de Zeeuw
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla, Jyvaskyla, Finland
| | - Kaili Rimfeld
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Richard J. Rose
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, United States of America
| | | | - Meike Bartels
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Robert Plomin
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - Henning Tiemeier
- Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Dorret I. Boomsma
- Department of Biological Psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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19
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Bos MM, Goulding NJ, Lee MA, Hofman A, Bot M, Pool R, Vijfhuizen LS, Zhang X, Li C, Mustafa R, Neville MJ, Li-Gao R, Trompet S, Beekman M, Biermasz NR, Boomsma DI, de Boer I, Christodoulides C, Dehghan A, van Dijk KW, Ford I, Ghanbari M, Heijmans BT, Ikram MA, Jukema JW, Mook-Kanamori DO, Karpe F, Luik AI, Lumey LH, van den Maagdenberg AMJM, Mooijaart SP, de Mutsert R, Penninx BWJH, Rensen PCN, Richmond RC, Rosendaal FR, Sattar N, Schoevers RA, Slagboom PE, Terwindt GM, Thesing CS, Wade KH, Wijsman CA, Willemsen G, Zwinderman AH, van Heemst D, Noordam R, Lawlor DA. Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses. BMC Med 2021; 19:69. [PMID: 33731105 PMCID: PMC7971964 DOI: 10.1186/s12916-021-01939-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Accepted: 02/11/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. METHODS We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. RESULTS We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (- 0.08 standard deviation (SD)[95% confidence interval (CI) - 0.12, - 0.03] in AMV and - 0.03SD [- 0.07, - 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (- 0.04SD [- 0.08, 0.00] in AMV and - 0.05SD [- 0.09, - 0.02] in MR), and lower phospholipids in very large HDL particles (- 0.04SD [- 0.08, 0.002] in AMV and - 0.05SD [- 0.08, - 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. CONCLUSIONS Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.
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Affiliation(s)
- Maxime M Bos
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Neil J Goulding
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew A Lee
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amy Hofman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Mariska Bot
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - René Pool
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lisanne S Vijfhuizen
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Xiang Zhang
- Department of Experimental Vascular Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Human and Animal Physiology, Wageningen University, Wageningen, The Netherlands
| | - Chihua Li
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA
| | - Rima Mustafa
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Matt J Neville
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford, UK
- Radcliffe Department of Medicine, Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, UK
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Nienke R Biermasz
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
| | - Dorret I Boomsma
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Irene de Boer
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Constantinos Christodoulides
- Radcliffe Department of Medicine, Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Ko Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Ian Ford
- Robertson Center for Biostatistics, University of Glasgow, Glasgow, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Fredrik Karpe
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Foundation Trust, Oxford, UK
- Radcliffe Department of Medicine, Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, UK
| | - Annemarie I Luik
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - L H Lumey
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Arn M J M van den Maagdenberg
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Simon P Mooijaart
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Brenda W J H Penninx
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Patrick C N Rensen
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Naveed Sattar
- BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, Glasgow, UK
| | - Robert A Schoevers
- Department of Psychiatry, Groningen, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Carisha S Thesing
- Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health research institute, Amsterdam, The Netherlands
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Carolien A Wijsman
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Gonneke Willemsen
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Aeilko H Zwinderman
- Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Diana van Heemst
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands
| | - Raymond Noordam
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands.
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
- NIHR Bristol Biomedical Research Centre, Bristol, UK.
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20
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Vuoksimaa E, Rose RJ, Pulkkinen L, Palviainen T, Rimfeld K, Lundström S, Bartels M, van Beijsterveldt C, Hendriks A, de Zeeuw EL, Plomin R, Lichtenstein P, Boomsma DI, Kaprio J. Higher aggression is related to poorer academic performance in compulsory education. J Child Psychol Psychiatry 2021; 62:327-338. [PMID: 32474928 DOI: 10.1111/jcpp.13273] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 04/30/2020] [Accepted: 05/04/2020] [Indexed: 12/27/2022]
Abstract
BACKGROUND To conduct a comprehensive assessment of the association between aggression and academic performance in compulsory education. METHOD We studied aggression and academic performance in over 27,000 individuals from four European twin cohorts participating in the ACTION consortium (Aggression in Children: Unraveling gene-environment interplay to inform Treatment and InterventiON strategies). Individual level data on aggression at ages 7-16 were assessed by three instruments (Achenbach System of Empirically Based Assessment, Multidimensional Peer Nomination Inventory, Strengths and Difficulties Questionnaire) including parental, teacher and self-reports. Academic performance was measured with teacher-rated grade point averages (ages 12-14) or standardized test scores (ages 12-16). Random effect meta-analytical correlations with academic performance were estimated for parental ratings (in all four cohorts) and self-ratings (in three cohorts). RESULTS All between-family analyses indicated significant negative aggression-academic performance associations with correlations ranging from -.06 to -.33. Results were similar across different ages, instruments and raters and either with teacher-rated grade point averages or standardized test scores as measures of academic performance. Meta-analytical r's were -.20 and -.23 for parental and self-ratings, respectively. In within-family analyses of all twin pairs, the negative aggression-academic performance associations were statistically significant in 14 out of 17 analyses (r = -.17 for parental- and r = -.16 for self-ratings). Separate analyses in monozygotic (r = -.07 for parental and self-ratings), same-sex dizygotic (r's = -.16 and -.17 for parental and self-ratings) and opposite-sex dizygotic (r's = -.21 and -.19 for parental and self-ratings) twin pairs suggested partial confounding by genetic effects. CONCLUSIONS There is a robust negative association between aggression and academic performance in compulsory education. Part of these associations were explained by shared genetic effects, but some evidence of a negative association between aggression and academic performance remained even in within-family analyses of monozygotic twin pairs.
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Affiliation(s)
- Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Richard J Rose
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Lea Pulkkinen
- Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kaili Rimfeld
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sebastian Lundström
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | | | - Anne Hendriks
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Robert Plomin
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
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21
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Harteveld LM, Nederend I, Ten Harkel ADJ, Schutte NM, de Rooij SR, Vrijkotte TGM, Oldenhof H, Popma A, Jansen LMC, Suurland J, Swaab H, de Geus EJC. Maturation of the Cardiac Autonomic Nervous System Activity in Children and Adolescents. J Am Heart Assoc 2021; 10:e017405. [PMID: 33525889 PMCID: PMC7955328 DOI: 10.1161/jaha.120.017405] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background Despite the increasing interest in cardiac autonomic nervous activity, the normal development is not fully understood. The main aim was to determine the maturation of different cardiac sympathetic‐(SNS) and parasympathetic nervous system (PNS) activity parameters in healthy patients aged 0.5 to 20 years. A second aim was to determine potential sex differences. Methods and Results Five studies covering the 0.5‐ to 20‐year age range provided impedance‐ and electrocardiography recordings from which heart rate, different PNS‐parameters (eg, respiratory sinus arrhythmia) and an SNS‐parameter (pre‐ejection period) were collected. Age trends were computed in the mean values across 12 age‐bins and in the age‐specific variances. Age was associated with changes in mean and variance of all parameters. PNS‐activity followed a cubic trend, with an exponential increase from infancy, a plateau phase during middle childhood, followed by a decrease to adolescence. SNS‐activity showed a more linear trend, with a gradual decrease from infancy to adolescence. Boys had higher SNS‐activity at ages 11 to 15 years, while PNS‐activity was higher at 5 and 11 to 12 years with the plateau level reached earlier in girls. Interindividual variation was high at all ages. Variance was reasonably stable for SNS‐ and the log‐transformed PNS‐parameters. Conclusions Cardiac PNS‐ and SNS‐activity in childhood follows different maturational trajectories. Whereas PNS‐activity shows a cubic trend with a plateau phase during middle childhood, SNS‐activity shows a linear decrease from 0.5 to 20 years. Despite the large samples used, clinical use of the sex‐specific centile and percentile normative values is modest in view of the large individual differences, even within narrow age bands.
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Affiliation(s)
- Lisette M Harteveld
- Department of Pediatric Cardiology Leiden University Medical Center Leiden The Netherlands
| | - Ineke Nederend
- Department of Pediatric Cardiology Leiden University Medical Center Leiden The Netherlands.,Department of Biological Psychology Faculty of Human Behavioral and Movement Sciences Vrije Universiteit AmsterdamAmsterdam Public Health Research Institute Amsterdam The Netherlands
| | - Arend D J Ten Harkel
- Department of Pediatric Cardiology Leiden University Medical Center Leiden The Netherlands
| | - Nienke M Schutte
- Department of Biological Psychology Faculty of Human Behavioral and Movement Sciences Vrije Universiteit AmsterdamAmsterdam Public Health Research Institute Amsterdam The Netherlands
| | - Susanne R de Rooij
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics Amsterdam University Medical CenterAcademic Medical Center Amsterdam The Netherlands.,Department of Public Health Amsterdam Public Health Research InstituteAmsterdam University Medical CenterUniversity of Amsterdam Amsterdam The Netherlands
| | - Tanja G M Vrijkotte
- Department of Public Health Amsterdam Public Health Research InstituteAmsterdam University Medical CenterUniversity of Amsterdam Amsterdam The Netherlands
| | - Helena Oldenhof
- Department of Child and Adolescent Psychiatry Amsterdam University Medical CenterVU University Medical Centre Amsterdam The Netherlands
| | - Arne Popma
- Department of Child and Adolescent Psychiatry Amsterdam University Medical CenterVU University Medical Centre Amsterdam The Netherlands
| | - Lucres M C Jansen
- Department of Child and Adolescent Psychiatry Amsterdam University Medical CenterVU University Medical Centre Amsterdam The Netherlands
| | - Jill Suurland
- Department of Clinical Child and Adolescent Studies and Leiden Institute for Brain and Cognition Leiden University Leiden The Netherlands
| | - Hanna Swaab
- Department of Clinical Child and Adolescent Studies and Leiden Institute for Brain and Cognition Leiden University Leiden The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology Faculty of Human Behavioral and Movement Sciences Vrije Universiteit AmsterdamAmsterdam Public Health Research Institute Amsterdam The Netherlands
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22
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Brouwer RM, Schutte J, Janssen R, Boomsma DI, Hulshoff Pol HE, Schnack HG. The Speed of Development of Adolescent Brain Age Depends on Sex and Is Genetically Determined. Cereb Cortex 2021; 31:1296-1306. [PMID: 33073292 PMCID: PMC8204942 DOI: 10.1093/cercor/bhaa296] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/18/2020] [Accepted: 09/10/2020] [Indexed: 11/20/2022] Open
Abstract
Children and adolescents show high variability in brain development. Brain age-the estimated biological age of an individual brain-can be used to index developmental stage. In a longitudinal sample of adolescents (age 9-23 years), including monozygotic and dizygotic twins and their siblings, structural magnetic resonance imaging scans (N = 673) at 3 time points were acquired. Using brain morphology data of different types and at different spatial scales, brain age predictors were trained and validated. Differences in brain age between males and females were assessed and the heritability of individual variation in brain age gaps was calculated. On average, females were ahead of males by at most 1 year, but similar aging patterns were found for both sexes. The difference between brain age and chronological age was heritable, as was the change in brain age gap over time. In conclusion, females and males show similar developmental ("aging") patterns but, on average, females pass through this development earlier. Reliable brain age predictors may be used to detect (extreme) deviations in developmental state of the brain early, possibly indicating aberrant development as a sign of risk of neurodevelopmental disorders.
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Affiliation(s)
- Rachel M Brouwer
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Jelle Schutte
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Ronald Janssen
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology and Netherlands Twin
Register, VU University Amsterdam, 1081 HV
Amsterdam, the Netherlands
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, University Medical Center Utrecht
Brain Center, Utrecht University, 3584 CX Utrecht, the Netherlands
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23
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Vermeulen MC, van der Heijden KB, Kocevska D, Treur JL, Huppertz C, van Beijsterveldt CE, Boomsma DI, Swaab H, Van Someren EJ, Bartels M. Associations of sleep with psychological problems and well-being in adolescence: causality or common genetic predispositions? J Child Psychol Psychiatry 2021; 62:28-39. [PMID: 32396669 PMCID: PMC7818180 DOI: 10.1111/jcpp.13238] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/18/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Whereas short and problematic sleep are associated with psychological problems in adolescence, causality remains to be elucidated. This study therefore utilized the discordant monozygotic cotwin design and cross-lagged models to investigate how short and problematic sleep affect psychological functioning. METHODS Adolescent twins (N = 12,803, 13-20 years, 42% male) completed questionnaires on sleep and psychological functioning repeatedly over a two-year interval. Monozygotic twin pairs were classified as concordant or discordant for sleep duration and trouble sleeping. Resulting subgroups were compared regarding internalizing problems, externalizing problems, and subjective well-being. RESULTS Cross-sectional analyses indicated associations of worse psychological functioning with both short sleep and problematic sleep, and cross-lagged models indicate bidirectional associations. Longitudinal analyses showed that an increase in sleep problems experienced selectively by one individual of an identical twin pair was accompanied by an increase of 52% in internalizing problem scores and 25% in externalizing problem scores. These changes were significantly different from the within-subject changes in cotwins with unchanged sleep quality (respectively, 3% increase and 5% decrease). Psychological functioning did, however, not worsen with decreasing sleep duration. CONCLUSIONS The findings suggest that sleep quality, rather than sleep duration, should be the primary target for prevention and intervention, with possible effect on psychological functioning in adolescents.
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Affiliation(s)
- Marije C.M. Vermeulen
- Department of Sleep and CognitionNetherlands Institute for Neurosciencean Institute of the Royal Netherlands Society for Arts and SciencesAmsterdamThe Netherlands,Department of Clinical Child and Adolescent StudiesInstitute of Education and Child StudiesLeiden UniversityLeidenThe Netherlands
| | - Kristiaan B. van der Heijden
- Department of Clinical Child and Adolescent StudiesInstitute of Education and Child StudiesLeiden UniversityLeidenThe Netherlands,Leiden Institute for Brain and CognitionLeiden UniversityLeidenThe Netherlands
| | - Desana Kocevska
- Department of Sleep and CognitionNetherlands Institute for Neurosciencean Institute of the Royal Netherlands Society for Arts and SciencesAmsterdamThe Netherlands,Department of Child and Adolescent PsychiatryErasmus Medical CenterRotterdamThe Netherlands
| | - Jorien L. Treur
- Department of Biological PsychologyNetherlands Twin RegisterVU University AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health Research InstituteAmsterdam UMCAmsterdamThe Netherlands,School of Experimental PsychologyUniversity of BristolBristolUK
| | - Charlotte Huppertz
- Department of Biological PsychologyNetherlands Twin RegisterVU University AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health Research InstituteAmsterdam UMCAmsterdamThe Netherlands,Department of Psychiatry, Psychotherapy and PsychosomaticsFaculty of MedicineRWTH Aachen UniversityAachenGermany
| | - Catharina E.M. van Beijsterveldt
- Department of Biological PsychologyNetherlands Twin RegisterVU University AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health Research InstituteAmsterdam UMCAmsterdamThe Netherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyNetherlands Twin RegisterVU University AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health Research InstituteAmsterdam UMCAmsterdamThe Netherlands,Amsterdam NeuroscienceAmsterdam UMCAmsterdamThe Netherlands
| | - Hanna Swaab
- Department of Clinical Child and Adolescent StudiesInstitute of Education and Child StudiesLeiden UniversityLeidenThe Netherlands,Leiden Institute for Brain and CognitionLeiden UniversityLeidenThe Netherlands
| | - Eus J.W. Van Someren
- Department of Sleep and CognitionNetherlands Institute for Neurosciencean Institute of the Royal Netherlands Society for Arts and SciencesAmsterdamThe Netherlands,Amsterdam NeuroscienceAmsterdam UMCAmsterdamThe Netherlands,Departments of Psychiatry and Integrative NeurophysiologyCenter for Neurogenomics and Cognitive Research (CNCR)Vrije Universiteit AmsterdamAmsterdam UMCAmsterdamThe Netherlands
| | - Meike Bartels
- Department of Biological PsychologyNetherlands Twin RegisterVU University AmsterdamAmsterdamThe Netherlands,Amsterdam Public Health Research InstituteAmsterdam UMCAmsterdamThe Netherlands
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24
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Odintsova VV, Rebattu V, Hagenbeek FA, Pool R, Beck JJ, Ehli EA, van Beijsterveldt CEM, Ligthart L, Willemsen G, de Geus EJC, Hottenga JJ, Boomsma DI, van Dongen J. Predicting Complex Traits and Exposures From Polygenic Scores and Blood and Buccal DNA Methylation Profiles. Front Psychiatry 2021; 12:688464. [PMID: 34393852 PMCID: PMC8357987 DOI: 10.3389/fpsyt.2021.688464] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/15/2021] [Indexed: 11/13/2022] Open
Abstract
We examined the performance of methylation scores (MS) and polygenic scores (PGS) for birth weight, BMI, prenatal maternal smoking exposure, and smoking status to assess the extent to which MS could predict these traits and exposures over and above the PGS in a multi-omics prediction model. MS may be seen as the epigenetic equivalent of PGS, but because of their dynamic nature and sensitivity of non-genetic exposures may add to complex trait prediction independently of PGS. MS and PGS were calculated based on genotype data and DNA-methylation data in blood samples from adults (Illumina 450 K; N = 2,431; mean age 35.6) and in buccal samples from children (Illumina EPIC; N = 1,128; mean age 9.6) from the Netherlands Twin Register. Weights to construct the scores were obtained from results of large epigenome-wide association studies (EWASs) based on whole blood or cord blood methylation data and genome-wide association studies (GWASs). In adults, MSs in blood predicted independently from PGSs, and outperformed PGSs for BMI, prenatal maternal smoking, and smoking status, but not for birth weight. The largest amount of variance explained by the multi-omics prediction model was for current vs. never smoking (54.6%) of which 54.4% was captured by the MS. The two predictors captured 16% of former vs. never smoking initiation variance (MS:15.5%, PGS: 0.5%), 17.7% of prenatal maternal smoking variance (MS:16.9%, PGS: 0.8%), 11.9% of BMI variance (MS: 6.4%, PGS 5.5%), and 1.9% of birth weight variance (MS: 0.4%, PGS: 1.5%). In children, MSs in buccal samples did not show independent predictive value. The largest amount of variance explained by the two predictors was for prenatal maternal smoking (2.6%), where the MSs contributed 1.5%. These results demonstrate that blood DNA MS in adults explain substantial variance in current smoking, large variance in former smoking, prenatal smoking, and BMI, but not in birth weight. Buccal cell DNA methylation scores have lower predictive value, which could be due to different tissues in the EWAS discovery studies and target sample, as well as to different ages. This study illustrates the value of combining polygenic scores with information from methylation data for complex traits and exposure prediction.
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Affiliation(s)
- Veronika V Odintsova
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Valerie Rebattu
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - René Pool
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, United States
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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25
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Hendriks AM, Ip HF, Nivard MG, Finkenauer C, Van Beijsterveldt CE, Bartels M, Boomsma DI. Content, diagnostic, correlational, and genetic similarities between common measures of childhood aggressive behaviors and related psychiatric traits. J Child Psychol Psychiatry 2020; 61:1328-1338. [PMID: 32080854 PMCID: PMC7754303 DOI: 10.1111/jcpp.13218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 12/19/2019] [Accepted: 01/03/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND Given the role of childhood aggressive behavior (AGG) in everyday child development, precise and accurate measurement is critical in clinical practice and research. This study aims to quantify agreement among widely used measures of childhood AGG regarding item content, clinical concordance, correlation, and underlying genetic construct. METHODS We analyzed data from 1254 Dutch twin pairs (age 8-10 years, 51.1% boys) from a general population sample for whom both parents completed the A-TAC, CBCL, and SDQ at the same occasion. RESULTS There was substantial variation in item content among AGG measures, ranging from .00 (i.e., mutually exclusive) to .50 (moderate agreement). Clinical concordance (i.e., do the same children score above a clinical threshold among AGG measures) was very weak to moderate with estimates ranging between .01 and .43 for mother-reports and between .12 and .42 for father-reports. Correlations among scales were weak to strong, ranging from .32 to .70 for mother-reports and from .32 to .64 for father-reports. We found weak to very strong genetic correlations among the measures, with estimates between .65 and .84 for mother-reports and between .30 and .87 for father-reports. CONCLUSIONS Our results demonstrated that degree of agreement between measures of AGG depends on the type (i.e., item content, clinical concordance, correlation, genetic correlation) of agreement considered. Because agreement was higher for correlations compared to clinical concordance (i.e., above or below a clinical cutoff), we propose the use of continuous scores to assess AGG, especially for combining data with different measures. Although item content can be different and agreement among observed measures may not be high, the genetic correlations indicate that the underlying genetic liability for childhood AGG is consistent across measures.
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Affiliation(s)
- Anne M. Hendriks
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Hill F. Ip
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Michel G. Nivard
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Catrin Finkenauer
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Department of Interdisciplinary Social Sciences: Youth StudiesUtrecht UniversityUtrechtThe Netherlands
| | | | - Meike Bartels
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Amsterdam Public Health Research InstituteAmsterdamThe Netherlands
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26
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Branje S, Geeraerts S, de Zeeuw EL, Oerlemans AM, Koopman-Verhoeff ME, Schulz S, Nelemans S, Meeus W, Hartman CA, Hillegers MHJ, Oldehinkel AJ, Boomsma DI. Intergenerational transmission: Theoretical and methodological issues and an introduction to four Dutch cohorts. Dev Cogn Neurosci 2020; 45:100835. [PMID: 32823179 PMCID: PMC7451818 DOI: 10.1016/j.dcn.2020.100835] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 06/27/2020] [Accepted: 08/04/2020] [Indexed: 01/09/2023] Open
Abstract
Behaviors, traits and characteristics are transmitted from parents to offspring because of complex genetic and non-genetic processes. We review genetic and non-genetic mechanisms of intergenerational transmission of psychopathology and parenting and focus on recent methodological advances in disentangling genetic and non-genetic factors. In light of this review, we propose that future studies on intergenerational transmission should aim to disentangle genetic and non-genetic transmission, take a long-term longitudinal perspective, and focus on paternal and maternal intergenerational transmission. We present four large longitudinal cohort studies within the Consortium on Individual Development, which together address many of these methodological challenges. These four cohort studies aim to examine the extent to which genetic and non-genetic transmission from the parental generation shapes parenting behavior and psychopathology in the next generation, as well as the extent to which self-regulation and social competence mediate this transmission. Conjointly, these four cohorts provide a comprehensive approach to the study of intergenerational transmission.
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Affiliation(s)
- Susan Branje
- Youth and Family, Department of Educational and Pedagogical Sciences, Utrecht University, Utrecht, the Netherlands.
| | - Sanne Geeraerts
- Youth and Family, Department of Educational and Pedagogical Sciences, Utrecht University, Utrecht, the Netherlands
| | - Eveline L de Zeeuw
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Anoek M Oerlemans
- Department of Psychiatry, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands
| | - M Elisabeth Koopman-Verhoeff
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Susanne Schulz
- Youth and Family, Department of Educational and Pedagogical Sciences, Utrecht University, Utrecht, the Netherlands
| | - Stefanie Nelemans
- Youth and Family, Department of Educational and Pedagogical Sciences, Utrecht University, Utrecht, the Netherlands
| | - Wim Meeus
- Youth and Family, Department of Educational and Pedagogical Sciences, Utrecht University, Utrecht, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands
| | - Manon H J Hillegers
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center Rotterdam-Sophia Children's Hospital, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
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27
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Luningham JM, Hendriks AM, Krapohl E, Ip HF, van Beijsterveldt CE, Lundström S, Vuoksimaa E, Korhonen T, Lichtenstein P, Plomin R, Pulkkinen L, Rose RJ, Kaprio J, Bartels M, Boomsma DI, Lubke GH. Harmonizing behavioral outcomes across studies, raters, and countries: application to the genetic analysis of aggression in the ACTION Consortium. J Child Psychol Psychiatry 2020; 61:807-817. [PMID: 31950512 PMCID: PMC7363537 DOI: 10.1111/jcpp.13188] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/25/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Aggression in children has genetic and environmental causes. Studies of aggression can pool existing datasets to include more complex models of social effects. Such analyses require large datasets with harmonized outcome measures. Here, we made use of a reference panel for phenotype data to harmonize multiple aggression measures in school-aged children to jointly analyze data from five large twin cohorts. METHODS Individual level aggression data on 86,559 children (42,468 twin pairs) were available in five European twin cohorts measured by different instruments. A phenotypic reference panel was collected which enabled a model-based phenotype harmonization approach. A bi-factor integration model in the integrative data analysis framework was developed to model aggression across studies while adjusting for rater, age, and sex. Finally, harmonized aggression scores were analyzed to estimate contributions of genes, environment, and social interaction to aggression. The large sample size allowed adequate power to test for sibling interaction effects, with unique dynamics permitted for opposite-sex twins. RESULTS The best-fitting model found a high level of overall heritability of aggression (~60%). Different heritability rates of aggression across sex were marginally significant, with heritability estimates in boys of ~64% and ~58% in girls. Sibling interaction effects were only significant in the opposite-sex twin pairs: the interaction effect of males on their female co-twin differed from the effect of females on their male co-twin. An aggressive female had a positive effect on male co-twin aggression, whereas more aggression in males had a negative influence on a female co-twin. CONCLUSIONS Opposite-sex twins displayed unique social dynamics of aggressive behaviors in a joint analysis of a large, multinational dataset. The integrative data analysis framework, applied in combination with a reference panel, has the potential to elucidate broad, generalizable results in the investigation of common psychological traits in children.
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Affiliation(s)
- Justin M. Luningham
- Department of Psychology, University of Notre Dame, Notre
Dame, IN;,Department of Population Health Sciences, School of Public
Health, Georgia State University, Atlanta, GA, USA
| | - Anne M. Hendriks
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Eva Krapohl
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Hill Fung Ip
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Catharina E.M. van Beijsterveldt
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, University of Gothenburg,
Gothenburg;,Centre for Ethics, Law and Mental Health (CELAM),
University of Gothenburg, Gothenburg, Sweden
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Stockholm, Sweden
| | - Robert Plomin
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla,
Jyvaskyla, Finland
| | - Richard J. Rose
- Department of Psychological and Brain Sciences, Indiana
University, Bloomington, IN, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland;,Department of Public Health, University of Helsinki,
Helsinki, Finland
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Gitta H. Lubke
- Department of Psychology, University of Notre Dame, Notre
Dame, IN
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28
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The (Broad-Sense) Genetic Correlations Among Four Measures of Inattention and Hyperactivity in 12 Year Olds. Behav Genet 2020; 50:273-288. [PMID: 32529491 PMCID: PMC7355270 DOI: 10.1007/s10519-020-10002-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Accepted: 05/28/2020] [Indexed: 10/26/2022]
Abstract
We estimated the genetic covariance matrix among four inattention (INATT) and four hyperactivity (HYP) measures in the classical twin design. Data on INATT and HYP symptom counts were obtained in mono- and dizygotic twin pairs (N = 1593) with an average age of 12.2 years (sd = .51). We analyzed maternal ratings of INATT and HYP based on the Conners' Parent Rating Scale (CPRS), the Strengths and Weaknesses of ADHD-symptoms and Normal-behavior (SWAN), and teacher ratings based on the Conners' Teacher rating scale (CTRS) and the ASEBA Teacher Rating Form (TRF). Broad-sense heritabilities, corrected for the main effects of sex and for random teacher rater effects, were large (ranging from .658 to .912). The results reveal pervasive and strong broad-sense genetic effects on INATT and HYP phenotypes with the phenotypic covariance among the phenotypes largely due to correlated genetic effects. Specifically between 79.9 and 99.9% of the phenotypic covariance among the HYP measures, and between 81.0 and 93.5% of the INATT measures are attributable to broad-sense genetic effects. Overall, the present results, pertaining to the broad-sense heritabilities and shared genetic effects, support the current genome-wide association meta-analytic approach to identifying pleiotropic genetic variants.
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29
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Slob EMA, Brew BK, Vijverberg SJH, Kats CJAR, Longo C, Pijnenburg MW, van Beijsterveldt TCEM, Dolan CV, Bartels M, Magnusson P, Lichtenstein P, Gong T, Koppelman GH, Almqvist C, Boomsma DI, Maitland-van der Zee AH. Early-life antibiotic use and risk of asthma and eczema: results of a discordant twin study. Eur Respir J 2020; 55:13993003.02021-2019. [PMID: 32139457 DOI: 10.1183/13993003.02021-2019] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 01/30/2020] [Indexed: 01/15/2023]
Abstract
RATIONALE Early-life antibiotic use has been associated with the development of atopic diseases, but the aetiology remains unclear. To elucidate the aetiology, we used a discordant twin design to control for genetic and environmental confounding. METHODS We conducted a retrospective cohort study in twins aged 3-10 years from the Netherlands Twin Register (NTR, n=35 365) and a replication study in twins aged 9 years from the Childhood and Adolescent Twin Study in Sweden (CATSS, n=7916). Antibiotic use was recorded at age 0-2 years. Doctor-diagnosed asthma and eczema were reported by parents when children were aged 3-12 years in both cohorts. Individuals were included in unmatched analyses and in co-twin control analyses with disease discordant twin pairs. RESULTS Early-life antibiotic use was associated with increased risk of asthma (NTR OR 1.34, 95% CI 1.28-1.41; CATSS OR 1.45, 95% CI 1.34-1.56) and eczema (NTR OR 1.08, 95% CI 1.03-1.13; CATSS OR 1.07, 95% CI 1.01-1.14) in unmatched analyses. Co-twin analyses in monozygotic and dizygotic twin pairs showed similar results for asthma (NTR OR 1.54, 95% CI 1.20-1.98; CATSS OR 2.00, 95% CI 1.28-3.13), but opposing results for eczema in the NTR (OR 0.99, 95% CI 0.80-1.25) and the CATSS (OR 1.67, 95% CI 1.12-2.49). The risk of asthma increased for antibiotics prescribed for respiratory infections (CATSS OR 1.45, 95% CI 1.34-1.56), but not for antibiotics commonly used for urinary tract/skin infections (CATSS OR 1.02, 95% CI 0.88-1.17). CONCLUSION Children exposed to early-life antibiotic use, particularly prescribed for respiratory infections, may be at higher risk of asthma. This risk can still be observed when correcting for genetic and environmental factors. Our results could not elucidate whether the relationship between early-life antibiotic use and eczema is confounded by familial and genetic factors.
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Affiliation(s)
- Elise M A Slob
- Dept of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Dept of Paediatric Pulmonology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Bronwyn K Brew
- Dept of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,National Perinatal Epidemiology and Statistics Unit, Centre for Big Data Research in Health and Dept of Women's and Children's Health, University of New South Wales, Sydney, Australia
| | - Susanne J H Vijverberg
- Dept of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Dept of Paediatric Pulmonology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Chantal J A R Kats
- Dept of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Cristina Longo
- Dept of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Mariëlle W Pijnenburg
- Dept of Paediatrics, Division of Respiratory Medicine and Allergology, ErasmusMC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Toos C E M van Beijsterveldt
- Netherlands Twin Register, Dept of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Conor V Dolan
- Netherlands Twin Register, Dept of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Meike Bartels
- Netherlands Twin Register, Dept of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Patrick Magnusson
- Dept of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Paul Lichtenstein
- Dept of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Tong Gong
- Dept of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Gerard H Koppelman
- Dept of Paediatric Pulmonology and Paediatric Allergology, Beatrix Children's Hospital, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.,Groningen Research Institute for Asthma and COPD (GRIAC), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Catarina Almqvist
- Dept of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Paediatric Allergy and Pulmonology Unit, Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Dorret I Boomsma
- Netherlands Twin Register, Dept of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anke H Maitland-van der Zee
- Dept of Respiratory Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.,Dept of Paediatric Pulmonology, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
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30
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Mbarek H, van Beijsterveldt CEM, Jan Hottenga J, Dolan CV, Boomsma DI, Willemsen G, Vink JM. Association Between rs1051730 and Smoking During Pregnancy in Dutch Women. Nicotine Tob Res 2020; 21:835-840. [PMID: 29228387 DOI: 10.1093/ntr/ntx267] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 12/05/2017] [Indexed: 01/09/2023]
Abstract
INTRODUCTION The common genetic variant (rs1051730) in the 15q24 nicotinic acetylcholine receptor gene cluster CHRNA5-CHRNA3-CHRNB4 was associated with smoking quantity and has been reported to be associated also with reduced ability to quit smoking in pregnant women but results were inconsistent in nonpregnant women. The aim of this study was to explore the association between rs1051730 and smoking cessation during pregnancy in a sample of Dutch women. METHODS Data on smoking during pregnancy were available from 1337 women, who ever smoked, registered at the Netherlands Twin Register (NTR). Logistic regression was used to assess evidence for the association of rs1051730 genotype on smoking during pregnancy. In a subsample of 561 women, we investigated the influence of partner's smoking. Educational attainment and year of birth were used as covariates in both analyses. RESULTS There was evidence for a significant association between having one or more T alleles of the rs1051730 polymorphism and the likelihood of smoking during pregnancy (p = .03, odds ratio = 1.28, 95% CI = 1.02 to 1.61). However, this association attenuated when adjusting for birth cohort and educational attainment (p = .37, odds ratio = 1.12, 95% CI = 0.87 to 1.43). In the subsample, smoking spouse was highly associated with smoking during pregnancy, even when educational attainment and birth cohort were included in the model. CONCLUSIONS Our results did not support a strong association between this genetic variant and smoking during pregnancy. However, a strong association was observed with the smoking behavior of the partner, regardless of the genotype of the women. IMPLICATIONS The present study emphasizes the importance of social influences like spousal smoking on the smoking behavior of pregnant women. Further research is needed to address the role of rs1051730 genetic variant in influencing smoking cessation and the interaction with important environmental factors like the smoking behavior of the partner.
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Affiliation(s)
- Hamdi Mbarek
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jacqueline M Vink
- Department of Biological Psychology, Amsterdam Public Health research institute, Vrije Universiteit, Amsterdam, The Netherlands.,Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
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31
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Brouwer SI, Stolk RP, Bartels M, van Beijsterveld TC, Boomsma DI, Corpeleijn E. Infant Motor Milestones and Childhood Overweight: Trends over Two Decades in A Large Twin Cohort. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E2366. [PMID: 32244434 PMCID: PMC7178093 DOI: 10.3390/ijerph17072366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 03/26/2020] [Accepted: 03/27/2020] [Indexed: 12/31/2022]
Abstract
BACKGROUND Poor motor skill competence may influence energy balance with childhood overweight as a result. Our aim was to investigate whether the age of motor milestone achievement has changed over the past decades and whether this change may contribute to the increasing trend observed in childhood overweight. METHODS Motor skill competence was assessed in children from the Young Netherlands Twin Register born between 1987 and 2007. Follow-up ranged from 4 up to 10 years. Weight and height were assessed at birth, 6 months, 14 months, and 2, 4, 7, and 10 years. RESULTS Babies born in later cohorts achieved their motor milestones 'crawling', 'standing', and 'walking unassisted' later compared to babies born in earlier cohorts (N = 18,514, p < 0.001). The prevalence of overweight at age 10 was higher in later cohorts (p = 0.033). The increase in overweight at age 10 was not explained by achieving motor milestones at a later age and this persisted after adjusting for gestational age, sex, and socioeconomic status. CONCLUSION Comparing children born in 1987 to those born in 2007, we conclude that children nowadays achieve their motor milestones at a later age. This does not however, explain the increasing trend in childhood overweight.
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Affiliation(s)
- Silvia I. Brouwer
- Institute of Sportstudies, Hanze University of Applied Sciences, Zernikeplein 17, 9747 AS Groningen, The Netherlands
- Department of Epidemilogy, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands; (R.P.S.); (E.C.)
| | - Ronald P. Stolk
- Department of Epidemilogy, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands; (R.P.S.); (E.C.)
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands; (M.B.); (T.C.E.M.v.B.); (D.I.B.)
| | - Toos C.E.M. van Beijsterveld
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands; (M.B.); (T.C.E.M.v.B.); (D.I.B.)
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Van der Boechorststraat 7, 1081 BT Amsterdam, The Netherlands; (M.B.); (T.C.E.M.v.B.); (D.I.B.)
| | - Eva Corpeleijn
- Department of Epidemilogy, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands; (R.P.S.); (E.C.)
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32
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Willems YE, de Zeeuw EL, van Beijsterveldt CEM, Boomsma DI, Bartels M, Finkenauer C. Out of Control: Examining the Association Between Family Conflict and Self-Control in Adolescence in a Genetically Sensitive Design. J Am Acad Child Adolesc Psychiatry 2020; 59:254-262. [PMID: 30877048 DOI: 10.1016/j.jaac.2019.02.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 02/08/2019] [Accepted: 03/05/2019] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Family conflict is associated with low self-control in adolescence. Thus far research about the direction of this association is inconclusive. In this study, we sort out whether this association reflects a causal effect or whether it is explained by a common underlying cause, including genetic factors. METHOD In twin data, we fitted a series of causal models, and compared models for the association of family conflict and self-control including reciprocal causation, unidirectional causation from family conflict to low self-control, unidirectional causation from low self-control to family conflict, and common genetic susceptibility. We included data from a large sample of twins aged 14 years (N = 9,173), all enrolled in the Netherlands Twin Register. RESULTS The results suggested a unidirectional pathway model in which family conflict leads to low self-control in adolescence, with genetic factors also playing a role in explaining the association. CONCLUSION Adolescents experiencing family conflict are at risk for showing hampered self-control capacities, with family conflict being a robust predictor of low self-control through common genetic factors but also through direct causal influences.
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Affiliation(s)
- Yayouk E Willems
- Vrije Universiteit Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, The Netherlands; Universiteit Utrecht, The Netherlands.
| | - Eveline L de Zeeuw
- Vrije Universiteit Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Vrije Universiteit Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Vrije Universiteit Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, The Netherlands; Neuroscience Campus Amsterdam, The Netherlands
| | - Meike Bartels
- Vrije Universiteit Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, The Netherlands; Neuroscience Campus Amsterdam, The Netherlands
| | - Catrin Finkenauer
- Vrije Universiteit Amsterdam, The Netherlands; Universiteit Utrecht, The Netherlands
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33
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Luningham JM, McArtor DB, Hendriks AM, van Beijsterveldt CEM, Lichtenstein P, Lundström S, Larsson H, Bartels M, Boomsma DI, Lubke GH. Data Integration Methods for Phenotype Harmonization in Multi-Cohort Genome-Wide Association Studies With Behavioral Outcomes. Front Genet 2020; 10:1227. [PMID: 31921287 PMCID: PMC6914843 DOI: 10.3389/fgene.2019.01227] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 11/05/2019] [Indexed: 01/03/2023] Open
Abstract
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.
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Affiliation(s)
- Justin M Luningham
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
| | - Daniel B McArtor
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
| | - Anne M Hendriks
- 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
| | - Catharina E M van Beijsterveldt
- 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
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Meike Bartels
- 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
| | - Dorret I Boomsma
- 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
| | - Gitta H Lubke
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
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34
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Hendriks AM, Finkenauer C, Nivard MG, Van Beijsterveldt CEM, Plomin RJ, Boomsma DI, Bartels M. Comparing the genetic architecture of childhood behavioral problems across socioeconomic strata in the Netherlands and the United Kingdom. Eur Child Adolesc Psychiatry 2020; 29:353-362. [PMID: 31154517 PMCID: PMC7056693 DOI: 10.1007/s00787-019-01357-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 05/23/2019] [Indexed: 11/12/2022]
Abstract
Socioeconomic status (SES) affects the development of childhood behavioral problems. It has been frequently observed that children from low SES background tend to show more behavioral problems. There also is some evidence that SES has a moderating effect on the causes of individual differences in childhood behavioral problems, with lower heritability estimates and a stronger contribution of environmental factors in low SES groups. The aim of the present study was to examine whether the genetic architecture of childhood behavioral problems suggests the presence of protective and/or harmful effects across socioeconomic strata, in two countries with different levels of socioeconomic disparity: the Netherlands and the United Kingdom. We analyzed data from 7-year-old twins from the Netherlands Twin Register (N = 24,112 twins) and the Twins Early Development Study (N = 19,644 twins). The results revealed a nonlinear moderation effect of SES on the contribution of genetic and environmental factors to individual differences in childhood behavioral problems. The heritability was higher, the contribution of the shared environment was lower, and the contribution of the nonshared environment was higher, for children from high SES families, compared to children from low or medium SES families. The pattern was similar for Dutch and UK families. We discuss the importance of these findings for prevention and intervention goals.
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Affiliation(s)
- A. M. Hendriks
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XAmsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - C. Finkenauer
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands ,grid.5477.10000000120346234Department of Interdisciplinary Social Sciences: Youth Studies, Utrecht University, Padualaan 14, 3584 CH Utrecht, the Netherlands
| | - M. G. Nivard
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands
| | - C. E. M. Van Beijsterveldt
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands
| | - R. J. Plomin
- grid.13097.3c0000 0001 2322 6764King’s College London, Social, Genetic and Developmental Psychiatry Centre, MRC Social, Institute of Psychiatry, Strand, London, WC2R 2LS UK
| | - D. I. Boomsma
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XAmsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - M. Bartels
- grid.12380.380000 0004 1754 9227Vrije Universiteit Amsterdam, Department of Biological Psychology, Netherlands Twin Register, van der Boechorststraat 7, 1081 BT Amsterdam, the Netherlands ,grid.16872.3a0000 0004 0435 165XAmsterdam Public Health Research Institute, Amsterdam, the Netherlands
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35
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Willems YE, Laceulle OM, Bartels M, Finkenauer C. Investigating the association between family connectedness and self-control in adolescence in a genetically sensitive design. Eur Child Adolesc Psychiatry 2020; 29:1683-1692. [PMID: 32025959 PMCID: PMC7641933 DOI: 10.1007/s00787-020-01485-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 01/27/2020] [Indexed: 11/26/2022]
Abstract
Family connectedness is key for the development of self-control in early and middle childhood. But is family connectedness still important during the transitional phase of adolescence, when adolescents demand more independence from their parents and rely more on their peers? The aim of the present study was to investigate the association between family connectedness and self-control, and whether it still holds in adolescence using a genetically sensitive design. Data were used from a large sample of twins aged 14 (N = 11,260) and aged 16 (N = 8175), all enrolled in the Netherlands Twin Register. We applied bivariate twin models and monozygotic twin difference models to investigate the association between family connectedness and self-control and to unravel to what extent genetic and environmental factors explain this association. The results showed that more family connectedness is significantly related to better self-control in adolescence, albeit with a small effect size. Twin analyses revealed that this association was mainly explained by common genetic factors and that the effects of environmental factors were small. The current findings confirm the role of family connectedness in adolescent self-control. Importantly, however, the results demonstrate that phenomena we see within families seem the product of parent and children sharing the same genes rather than being exclusively attributable to environmental processes.
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Affiliation(s)
- Yayouk E Willems
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Department of Interdisciplinary Social Science, Universiteit Utrecht, Utrecht, The Netherlands.
| | - Odilia M Laceulle
- Department of Developmental Psychology, Universiteit Utrecht, Utrecht, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - Catrin Finkenauer
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Boechorststraat 7-9, 1081 BT, Amsterdam, The Netherlands
- Department of Interdisciplinary Social Science, Universiteit Utrecht, Utrecht, The Netherlands
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36
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Odintsova VV, Hagenbeek FA, Suderman M, Caramaschi D, van Beijsterveldt CEM, Kallsen NA, Ehli EA, Davies GE, Sukhikh GT, Fanos V, Relton C, Bartels M, Boomsma DI, van Dongen J. DNA Methylation Signatures of Breastfeeding in Buccal Cells Collected in Mid-Childhood. Nutrients 2019; 11:E2804. [PMID: 31744183 PMCID: PMC6893543 DOI: 10.3390/nu11112804] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/12/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022] Open
Abstract
Breastfeeding has long-term benefits for children that may be mediated via the epigenome. This pathway has been hypothesized, but the number of empirical studies in humans is small and mostly done by using peripheral blood as the DNA source. We performed an epigenome-wide association study (EWAS) in buccal cells collected around age nine (mean = 9.5) from 1006 twins recruited by the Netherlands Twin Register (NTR). An age-stratified analysis examined if effects attenuate with age (median split at 10 years; n<10 = 517, mean age = 7.9; n>10 = 489, mean age = 11.2). We performed replication analyses in two independent cohorts from the NTR (buccal cells) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (peripheral blood), and we tested loci previously associated with breastfeeding in epigenetic studies. Genome-wide DNA methylation was assessed with the Illumina Infinium MethylationEPIC BeadChip (Illumina, San Diego, CA, USA) in the NTR and with the HumanMethylation450 Bead Chip in the ALSPAC. The duration of breastfeeding was dichotomized ('never' vs. 'ever'). In the total sample, no robustly associated epigenome-wide significant CpGs were identified (α = 6.34 × 10-8). In the sub-group of children younger than 10 years, four significant CpGs were associated with breastfeeding after adjusting for child and maternal characteristics. In children older than 10 years, methylation differences at these CpGs were smaller and non-significant. The findings did not replicate in the NTR sample (n = 98; mean age = 7.5 years), and no nearby sites were associated with breastfeeding in the ALSPAC study (n = 938; mean age = 7.4). Of the CpG sites previously reported in the literature, three were associated with breastfeeding in children younger than 10 years, thus showing that these CpGs are associated with breastfeeding in buccal and blood cells. Our study is the first to show that breastfeeding is associated with epigenetic variation in buccal cells in children. Further studies are needed to investigate if methylation differences at these loci are caused by breastfeeding or by other unmeasured confounders, as well as what mechanism drives changes in associations with age.
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Affiliation(s)
- Veronika V. Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
- Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow 101000, Russia
| | - Fiona A. Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | - Doretta Caramaschi
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | | | - Noah A. Kallsen
- Avera Institute for Human Genetics, Sioux Falls, SD 57101, USA
| | - Erik A. Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD 57101, USA
| | | | - Gennady T. Sukhikh
- Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow 101000, Russia
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, 09121 Cagliari, Italy
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
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Doering S, Lichtenstein P, Gillberg C, Middeldorp CM, Bartels M, Kuja-Halkola R, Lundström S. Anxiety at age 15 predicts psychiatric diagnoses and suicidal ideation in late adolescence and young adulthood: results from two longitudinal studies. BMC Psychiatry 2019; 19:363. [PMID: 31727035 PMCID: PMC6857289 DOI: 10.1186/s12888-019-2349-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 10/31/2019] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Anxiety disorders in adolescence have been associated with several psychiatric outcomes. We sought to describe the prospective relationship between various levels of adolescent anxiety and psychiatric diagnoses (anxiety-, bipolar/psychotic-, depressive-, and alcohol and drug misuse disorders) and suicidal ideation in early adulthood while adjusting for childhood attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and developmental coordination disorder (DCD). Furthermore, we aimed to estimate the proportion attributable to the various anxiety levels for the outcomes. METHODS We used a nation-wide population-based Swedish twin study comprising 14,106 fifteen-year-old twins born in Sweden between 1994 and 2002 and a replication sample consisting of 9211 Dutch twins, born between 1985 and 1999. Adolescent anxiety was measured with parental and self-report. Psychiatric diagnoses and suicidal ideation were retrieved from the Swedish National Patient Register and via self-report. RESULTS Adolescent anxiety, of various levels, predicted, in the Swedish National Patient Register, anxiety disorders: hazard ratio (HR) = 4.92 (CI 3.33-7.28); depressive disorders: HR = 4.79 (3.23-7.08), and any psychiatric outcome: HR = 3.40 (2.58-4.48), when adjusting for ADHD, ASD, and DCD. The results were replicated in the Dutch data. The proportion of psychiatric outcome attributable to adolescent anxiety over time (age 15-21) was 29% for any psychiatric outcome, 43-40% for anxiety disorders, and 39-38% for depressive disorders. CONCLUSION Anxiety in adolescence constitutes an important risk factor in the development of psychiatric outcomes, revealing unique predictions for the different levels of anxiety, and beyond the risk conferred by childhood ADHD, ASD, and DCD. Developmental trajectories leading into psychiatric outcomes should further empirically investigated.
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Affiliation(s)
- Sabrina Doering
- Centre for Ethics, Law and Mental Health, University of Gothenburg, Gothenburg, Sweden.
| | - Paul Lichtenstein
- 0000 0004 1937 0626grid.4714.6Department of Medical Epidemiology and Biostatics, Karolinska Institutet, Stockholm, Sweden
| | - Christopher Gillberg
- 0000 0000 9919 9582grid.8761.8Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | | | - Christel M. Middeldorp
- 0000 0004 1754 9227grid.12380.38Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands ,0000 0000 9320 7537grid.1003.2Child Health Research Centre, University of Queensland, Brisbane, Australia ,Child and Youth Mental Health Service, Children’s Health Queensland Hospital and Health Service, Brisbane, Australia
| | - Meike Bartels
- 0000 0004 1754 9227grid.12380.38Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands ,0000 0004 0435 165Xgrid.16872.3aAmsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Ralf Kuja-Halkola
- 0000 0004 1937 0626grid.4714.6Department of Medical Epidemiology and Biostatics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- 0000 0000 9919 9582grid.8761.8Centre for Ethics, Law and Mental Health, University of Gothenburg, Gothenburg, Sweden ,0000 0000 9919 9582grid.8761.8Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
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The Netherlands Twin Register: Longitudinal Research Based on Twin and Twin-Family Designs. Twin Res Hum Genet 2019; 22:623-636. [PMID: 31666148 DOI: 10.1017/thg.2019.93] [Citation(s) in RCA: 85] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The Netherlands Twin Register (NTR) is a national register in which twins, multiples and their parents, siblings, spouses and other family members participate. Here we describe the NTR resources that were created from more than 30 years of data collections; the development and maintenance of the newly developed database systems, and the possibilities these resources create for future research. Since the early 1980s, the NTR has enrolled around 120,000 twins and a roughly equal number of their relatives. The majority of twin families have participated in survey studies, and subsamples took part in biomaterial collection (e.g., DNA) and dedicated projects, for example, for neuropsychological, biomarker and behavioral traits. The recruitment into the NTR is all inclusive without any restrictions on enrollment. These resources - the longitudinal phenotyping, the extended pedigree structures and the multigeneration genotyping - allow for future twin-family research that will contribute to gene discovery, causality modeling, and studies of genetic and cultural inheritance.
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Veldkamp SAM, Boomsma DI, de Zeeuw EL, van Beijsterveldt CEM, Bartels M, Dolan CV, van Bergen E. Genetic and Environmental Influences on Different Forms of Bullying Perpetration, Bullying Victimization, and Their Co-occurrence. Behav Genet 2019; 49:432-443. [PMID: 31502010 PMCID: PMC6768918 DOI: 10.1007/s10519-019-09968-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2019] [Accepted: 08/16/2019] [Indexed: 02/01/2023]
Abstract
Bullying comes in different forms, yet most previous genetically-sensitive studies have not distinguished between them. Given the serious consequences and the high prevalence of bullying, it is remarkable that the aetiology of bullying and its different forms has been under-researched. We present the first study to investigate the genetic architecture of bullying perpetration, bullying victimization, and their co-occurrence for verbal, physical and relational bullying. Primary-school teachers rated 8215 twin children on bullying perpetration and bullying victimization. For each form of bullying, we investigated, through genetic structural equation modelling, the genetic and environmental influences on being a bully, a victim or both. 34% of the children were involved as bully, victim, or both. The correlation between being a bully and being a victim varied from 0.59 (relational) to 0.85 (physical). Heritability was ~ 70% for perpetration and ~ 65% for victimization, similar in girls and boys, yet both were somewhat lower for the relational form. Shared environmental influences were modest and more pronounced among girls. The correlation between being a bully and being a victim was explained mostly by genetic factors for verbal (~ 71%) and especially physical (~ 77%) and mostly by environmental factors for relational perpetration and victimization (~ 60%). Genes play a large role in explaining which children are at high risk of being a victim, bully, or both. For victimization this suggests an evocative gene-environment correlation: some children are at risk of being exposed to bullying, partly due to genetically influenced traits. So, genetic influences make some children more vulnerable to become a bully, victim or both.
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Affiliation(s)
- Sabine A M Veldkamp
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, van der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands. .,Amsterdam Public Health Research (APH), Amsterdam, The Netherlands.
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40
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Treur JL, Verweij KJH, Abdellaoui A, Fedko IO, de Zeeuw EL, Ehli EA, Davies GE, Hottenga JJ, Willemsen G, Boomsma DI, Vink JM. Testing Familial Transmission of Smoking With Two Different Research Designs. Nicotine Tob Res 2019; 20:836-842. [PMID: 28575460 DOI: 10.1093/ntr/ntx121] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Accepted: 05/26/2017] [Indexed: 01/10/2023]
Abstract
Introduction Classical twin studies show that smoking is heritable. To determine if shared family environment plays a role in addition to genetic factors, and if they interact (G×E), we use a children-of-twins design. In a second sample, we measure genetic influence with polygenic risk scores (PRS) and environmental influence with a question on exposure to smoking during childhood. Methods Data on smoking initiation were available for 723 children of 712 twins from the Netherlands Twin Register (64.9% female, median birth year 1985). Children were grouped in ascending order of risk, based on smoking status and zygosity of their twin-parent and his/her co-twin: never smoking twin-parent with a never smoking co-twin; never smoking twin-parent with a smoking dizygotic co-twin; never smoking twin-parent with a smoking monozygotic co-twin; and smoking twin-parent with a smoking or never smoking co-twin. For 4072 participants from the Netherlands Twin Register (67.3% female, median birth year 1973), PRS for smoking were computed and smoking initiation, smoking heaviness, and exposure to smoking during childhood were available. Results Patterns of smoking initiation in the four group children-of-twins design suggested shared familial influences in addition to genetic factors. PRS for ever smoking were associated with smoking initiation in all individuals. PRS for smoking heaviness were associated with smoking heaviness in individuals exposed to smoking during childhood, but not in non-exposed individuals. Conclusions Shared family environment influences smoking, over and above genetic factors. Genetic risk of smoking heaviness was only important for individuals exposed to smoking during childhood, versus those not exposed (G×E). Implications This study adds to the very few existing children-of-twins (CoT) studies on smoking and combines a CoT design with a second research design that utilizes polygenic risk scores and data on exposure to smoking during childhood. The results show that shared family environment affects smoking behavior over and above genetic factors. There was also evidence for gene-environment interaction (G×E) such that genetic risk of heavy versus light smoking was only important for individuals who were also exposed to (second-hand) smoking during childhood. Together, these findings give additional incentive to recommending parents not to expose their children to cigarette smoking.
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Affiliation(s)
- Jorien L Treur
- Radboud University Nijmegen, Behavioural Science Institute, the Netherlands
| | - Karin J H Verweij
- Radboud University Nijmegen, Behavioural Science Institute, the Netherlands.,Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Abdel Abdellaoui
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Iryna O Fedko
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Erik A Ehli
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands.,Avera Institute for Human Genetics, Sioux Falls, SD
| | - Gareth E Davies
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands.,Avera Institute for Human Genetics, Sioux Falls, SD
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Jacqueline M Vink
- Radboud University Nijmegen, Behavioural Science Institute, the Netherlands
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de Zeeuw EL, Kan KJ, van Beijsterveldt CEM, Mbarek H, Hottenga JJ, Davies GE, Neale MC, Dolan CV, Boomsma DI. The moderating role of SES on genetic differences in educational achievement in the Netherlands. NPJ SCIENCE OF LEARNING 2019; 4:13. [PMID: 31508241 PMCID: PMC6722095 DOI: 10.1038/s41539-019-0052-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 06/19/2019] [Indexed: 05/05/2023]
Abstract
Parental socioeconomic status (SES) is a strong predictor of children's educational achievement (EA), with an increasing effect throughout development. Inequality in educational outcomes between children from different SES backgrounds exists in all Western countries. It has been proposed that a cause of this inequality lies in the interplay between genetic effects and SES on EA, which might depend on society and the equality of the education system. This study adopted two approaches, a classical twin design and polygenic score (PGS) approach, to address the effect of parental SES on EA in a large sample of 12-year-old Dutch twin pairs (2479 MZ and 4450 DZ twin pairs with PGSs for educational attainment available in 2335 children) from the Netherlands Twin Register (NTR). The findings of this study indicated that average EA increased with increasing parental SES. The difference in EA between boys and girls became smaller in the higher SES groups. The classical twin design analyses based on genetic covariance structure modeling pointed to lower genetic, environmental, and thus phenotypic variation in EA at higher SES. Independent from a child's PGS, parental SES predicted EA. However, the strength of the association between PGS and EA did not depend on parental SES. In a within-family design, the twin with a higher PGS scored higher on EA than the co-twin, demonstrating that the effect of the PGS on EA was at least partly independent from parental SES. To conclude, EA depended on SES both directly and indirectly, and SES moderated the additive genetic and environmental components of EA. Adding information from PGS, in addition to parental SES, improved the prediction of children's EA.
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Affiliation(s)
- Eveline L. de Zeeuw
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VUmc, Amsterdam, the Netherlands
| | - Kees-Jan Kan
- College of Child Development and Education, University of Amsterdam, Amsterdam, the Netherlands
| | - Catharina E. M. van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VUmc, Amsterdam, the Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Qatar Genome Programme, Qatar Foundation, Doha, Qatar
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VUmc, Amsterdam, the Netherlands
| | - Gareth E. Davies
- Avera Institute for Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, SD USA
| | - Michael C. Neale
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
| | - Conor V. Dolan
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VUmc, Amsterdam, the Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, VUmc, Amsterdam, the Netherlands
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Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. Neuroimage 2019; 202:116073. [PMID: 31386921 DOI: 10.1016/j.neuroimage.2019.116073] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 06/27/2019] [Accepted: 08/02/2019] [Indexed: 12/11/2022] Open
Abstract
The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.
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Pre- and Perinatal Characteristics Associated with Apgar Scores in a Review and in a New Study of Dutch Twins. Twin Res Hum Genet 2019; 22:164-176. [PMID: 31198125 DOI: 10.1017/thg.2019.24] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
A literature review was carried out to identify pre and perinatal characteristics associated with variation in Apgar scores in population-based studies. The parameters identified in the literature search were included in the classical twin design study to estimate effects of pre and perinatal factors shared and nonshared by twins and to test for a contribution of genetic factors in 1- and 5-min Apgar scores in a large sample of Dutch monozygotic (MZ) and dizygotic (DZ) twins. The sample included MZ and DZ twins (N = 5181 pairs) recruited by the Netherlands Twin Register shortly after birth, with data on prenatal characteristics and Apgar scores at first and/or fifth minutes. The ordinal regression and structural equation modeling were used to analyze the effects of characteristics identified in the literature review and to estimate genetic and nongenetic variance components. The literature review identified 63 papers. Consistent with the review, we observed statistically significant effects of birth order, zygosity and gestational age (GA) for 1- and 5-min Apgar scores of both twins. Apgar scores are higher in first-born versus second-born twins and DZ first-born versus MZ first-born twins. Birth weight had an effect on the 5-min Apgar of the first born. Fetal presentation and mode of delivery had different effects on Apgar scores of first- and second-born twins. Parental characteristics and chorionicity did not have significant main effects on Apgar scores. The MZ twins' Apgar correlations equaled the DZ Apgar correlations. Our analyses suggest that individual differences in 1- and 5-min Apgar scores are attributable to shared and nonshared pre and perinatal factors, but not to genotypic factors of the newborns. The main predictors of Apgar scores are birth order, zygosity, GA, birth weight, mode of delivery and fetal presentation.
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Derks IPM, Bolhuis K, Yalcin Z, Gaillard R, Hillegers MHJ, Larsson H, Lundström S, Lichtenstein P, van Beijsterveldt CEM, Bartels M, Boomsma DI, Tiemeier H, Jansen PW. Testing Bidirectional Associations Between Childhood Aggression and BMI: Results from Three Cohorts. Obesity (Silver Spring) 2019; 27:822-829. [PMID: 30957987 PMCID: PMC6594099 DOI: 10.1002/oby.22419] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 12/21/2018] [Indexed: 01/01/2023]
Abstract
OBJECTIVE This study examined the prospective, potentially bidirectional association of aggressive behavior with BMI and body composition across childhood in three population-based cohorts. METHODS Repeated measures of aggression and BMI were available from the Generation R Study between ages 6 and 10 years (N = 3,974), the Netherlands Twin Register (NTR) between ages 7 and 10 years (N = 10,328), and the Swedish Twin Study of Child and Adolescent Development (TCHAD) between ages 9 and 14 years (N = 1,462). In all samples, aggression was assessed with the Child Behavior Checklist. Fat mass and fat-free mass were available in the Generation R Study. Associations were examined with cross-lagged modeling. RESULTS Aggressive behavior at baseline was associated with higher BMI at follow-up in the Generation R Study (β = 0.02, 95% CI: 0.00 to 0.04), in NTR (β = 0.04, 95% CI: 0.02 to 0.06), and in TCHAD (β = 0.03, 95% CI: -0.02 to 0.07). Aggressive behavior was prospectively associated with higher fat mass (β = 0.03, 95% CI: 0.01 to 0.05) but not fat-free mass. There was no evidence that BMI or body composition preceded aggressive behavior. CONCLUSIONS More aggressive behavior was prospectively associated with higher BMI and fat mass. This suggests that aggression contributes to the obesity problem, and future research should study whether these behavioral pathways to childhood obesity are modifiable.
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Affiliation(s)
- Ivonne P. M. Derks
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Generation R Study GroupErasmus Medical CenterRotterdamthe Netherlands
| | - Koen Bolhuis
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Generation R Study GroupErasmus Medical CenterRotterdamthe Netherlands
| | - Zeynep Yalcin
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
| | - Romy Gaillard
- Department of PediatricsErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Department of EpidemiologyErasmus Medical CenterRotterdamthe Netherlands
| | - Manon H. J. Hillegers
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Department of PsychiatryRudolf Magnus Brain Center, Utrecht University Medical CenterUtrechtthe Netherlands
| | - Henrik Larsson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstituteStockholmSweden
- School of Medical SciencesÖrebro UniversityÖrebroSweden
| | - Sebastian Lundström
- Center for Ethics, Law and Mental HealthUniversity of GothenborgGothenborgSweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and BiostatisticsKarolinska InstituteStockholmSweden
| | | | - Meike Bartels
- Department of Biological PsychologyVrije UniversityAmsterdamthe Netherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije UniversityAmsterdamthe Netherlands
| | - Henning Tiemeier
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Department of Social and Behavioral SciencesHarvard T. H. Chan School of Public Health, Harvard UniversityBostonMassachusettsUSA
| | - Pauline W. Jansen
- Department of Child & Adolescent Psychiatry/PsychologyErasmus Medical Center–Sophia Children's HospitalRotterdamthe Netherlands
- Department of Psychology, Education and Child StudiesErasmus University RotterdamRotterdamthe Netherlands
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Kochunov P, Patel B, Ganjgahi H, Donohue B, Ryan M, Hong EL, Chen X, Adhikari B, Jahanshad N, Thompson PM, Van't Ent D, den Braber A, de Geus EJC, Brouwer RM, Boomsma DI, Hulshoff Pol HE, de Zubicaray GI, McMahon KL, Martin NG, Wright MJ, Nichols TE. Homogenizing Estimates of Heritability Among SOLAR-Eclipse, OpenMx, APACE, and FPHI Software Packages in Neuroimaging Data. Front Neuroinform 2019; 13:16. [PMID: 30914942 PMCID: PMC6422938 DOI: 10.3389/fninf.2019.00016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 02/25/2019] [Indexed: 11/30/2022] Open
Abstract
Imaging genetic analyses use heritability calculations to measure the fraction of phenotypic variance attributable to additive genetic factors. We tested the agreement between heritability estimates provided by four methods that are used for heritability estimates in neuroimaging traits. SOLAR-Eclipse and OpenMx use iterative maximum likelihood estimation (MLE) methods. Accelerated Permutation inference for ACE (APACE) and fast permutation heritability inference (FPHI), employ fast, non-iterative approximation-based methods. We performed this evaluation in a simulated twin-sibling pedigree and phenotypes and in diffusion tensor imaging (DTI) data from three twin-sibling cohorts, the human connectome project (HCP), netherlands twin register (NTR) and BrainSCALE projects provided as a part of the enhancing neuro imaging genetics analysis (ENIGMA) consortium. We observed that heritability estimate may differ depending on the underlying method and dataset. The heritability estimates from the two MLE approaches provided excellent agreement in both simulated and imaging data. The heritability estimates for two approximation approaches showed reduced heritability estimates in datasets with deviations from data normality. We propose a data homogenization approach (implemented in solar-eclipse; www.solar-eclipse-genetics.org) to improve the convergence of heritability estimates across different methods. The homogenization steps include consistent regression of any nuisance covariates and enforcing normality on the trait data using inverse Gaussian transformation. Under these conditions, the heritability estimates for simulated and DTI phenotypes produced converging heritability estimates regardless of the method. Thus, using these simple suggestions may help new heritability studies to provide outcomes that are comparable regardless of software package.
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Affiliation(s)
- Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Binish Patel
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Habib Ganjgahi
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Brian Donohue
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Meghann Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Elliot L Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Xu Chen
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Bhim Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Paul M Thompson
- Imaging Genetics Center, Keck School of Medicine of USC, Marina del Rey, CA, United States
| | - Dennis Van't Ent
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Rachel M Brouwer
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Amsterdam, Netherlands
| | - Hilleke E Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
| | - Greig I de Zubicaray
- Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | | | - Margaret J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Thomas E Nichols
- Big Data Institute, University of Oxford, Oxford, United Kingdom
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Malanchini M, Smith-Woolley E, Ayorech Z, Rimfeld K, Krapohl E, Vuoksimaa E, Korhonen T, Bartels M, van Beijsterveldt TC, Rose RJ, Lundström S, Anckarsäter H, Kaprio J, Lichtenstein P, Boomsma DI, Plomin R. Aggressive behaviour in childhood and adolescence: the role of smoking during pregnancy, evidence from four twin cohorts in the EU-ACTION consortium. Psychol Med 2019; 49:646-654. [PMID: 29886849 PMCID: PMC6378412 DOI: 10.1017/s0033291718001344] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 03/14/2018] [Accepted: 04/24/2018] [Indexed: 01/19/2023]
Abstract
BACKGROUND Maternal smoking during pregnancy (MSDP) has been linked to offspring's externalizing problems. It has been argued that socio-demographic factors (e.g. maternal age and education), co-occurring environmental risk factors, or pleiotropic genetic effects may account for the association between MSDP and later outcomes. This study provides a comprehensive investigation of the association between MSDP and a single harmonized component of externalizing: aggressive behaviour, measured throughout childhood and adolescence. METHODS Data came from four prospective twin cohorts - Twins Early Development Study, Netherlands Twin Register, Childhood and Adolescent Twin Study of Sweden, and FinnTwin12 study - who collaborate in the EU-ACTION consortium. Data from 30 708 unrelated individuals were analysed. Based on item level data, a harmonized measure of aggression was created at ages 9-10; 12; 14-15 and 16-18. RESULTS MSDP predicted aggression in childhood and adolescence. A meta-analysis across the four samples found the independent effect of MSDP to be 0.4% (r = 0.066), this remained consistent when analyses were performed separately by sex. All other perinatal factors combined explained 1.1% of the variance in aggression across all ages and samples (r = 0.112). Paternal smoking and aggressive parenting strategies did not account for the MSDP-aggression association, consistent with the hypothesis of a small direct link between MSDP and aggression. CONCLUSIONS Perinatal factors, including MSDP, account for a small portion of the variance in aggression in childhood and adolescence. Later experiences may play a greater role in shaping adolescents' aggressive behaviour.
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Affiliation(s)
- Margherita Malanchini
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
- Department of Psychology, University of Texas at Austin, United States
| | - Emily Smith-Woolley
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
| | - Ziada Ayorech
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
| | - Kaili Rimfeld
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
| | - Eva Krapohl
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
| | - Eero Vuoksimaa
- Institute for Molecular Medicine FIMM, University of Helsinki, Finland
| | - Tellervo Korhonen
- Institute for Molecular Medicine FIMM, University of Helsinki, Finland
| | - Meike Bartels
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | | | - Richard J. Rose
- Department of Psychological and Brain Sciences, Indiana University, United States
| | - Sebastian Lundström
- Centre for Ethics, Law and Mental Health and the Gillberg Neuropsychiatry Centre, Gothenburg University, Sweden
| | - Henrik Anckarsäter
- Centre for Ethics, Law and Mental Health and the Gillberg Neuropsychiatry Centre, Gothenburg University, Sweden
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Dorret I. Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - Robert Plomin
- Social Genetic and Developmental Psychiatry Centre, King's College London, United Kingdom
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47
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Tracking of voluntary exercise behaviour over the lifespan. Int J Behav Nutr Phys Act 2019; 16:17. [PMID: 30717763 PMCID: PMC6360805 DOI: 10.1186/s12966-019-0779-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Accepted: 01/30/2019] [Indexed: 12/14/2022] Open
Abstract
Background The aim of many physical activity interventions is to develop life-long habits of regular exercise and sports activities in leisure time. Previous studies that assessed tracking (i.e. the stability of a trait over the lifespan) of leisure time exercise behaviour across various parts of the life span have treated it as a uniform construct by summing all types of leisure time exercise activities into a single summary score for the total volume of exercise. This study provides new insight by additionally determining tracking across leisure time exercise activities in six different domains: (1) team-based versus solitary activities, (2) competitive versus non-competitive activities, and (3) externally paced versus internally paced activities. We also assessed which of the domains of exercise activities best predicted total volume of exercise at follow-up. Methods A large dataset (N = 43,889) from the Netherlands Twin Register (NTR) was used to analyse the tracking of exercise behaviour over time. Using this dataset, we were able to examine tracking as a function of baseline age (8 to 80 years) and tracking duration (2 to 22-year follow-up), taking into account sex differences, using generalized estimating equations. Results Two-year tracking coefficients are moderate to high for total volume of exercise across ages at baseline, ranging from .38 to .77 with a median of .57. Tracking coefficients tend to decrease as the distance to follow-up increases, down to a median of .38 for the 22-year tracking coefficients. The patterns of tracking were largely domain-independent and were largely similar for solitary, competitive, non-competitive, externally and internally paced activities. With the exception of team-based activities, tracking was seen to increase as a function of baseline age. Cross-domain tracking did not favour any specific domain of exercise activity as the best predictor for total volume of exercise behaviour and this was true at all baseline ages. Conclusion We conclude that exercise behaviour is moderately to highly stable across the life span. In particular in adulthood, where the tracking of exercise mimics that of a classical behavioural trait like personality. This stability reinforces existing evidence that exercise habits are hard to change, but at the same time suggests that successful intervention leading to the adoption of exercise habits will tend to last. Electronic supplementary material The online version of this article (10.1186/s12966-019-0779-4) contains supplementary material, which is available to authorized users.
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48
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Baselmans BML, Jansen R, Ip HF, van Dongen J, Abdellaoui A, van de Weijer MP, Bao Y, Smart M, Kumari M, Willemsen G, Hottenga JJ, Boomsma DI, de Geus EJC, Nivard MG, Bartels M. Multivariate genome-wide analyses of the well-being spectrum. Nat Genet 2019; 51:445-451. [PMID: 30643256 DOI: 10.1038/s41588-018-0320-8] [Citation(s) in RCA: 166] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2018] [Accepted: 11/27/2018] [Indexed: 12/21/2022]
Abstract
We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the added value of our multivariate methods relative to univariate GWAMA. We applied the novel methods to life satisfaction, positive affect, neuroticism, and depressive symptoms, collectively referred to as the well-being spectrum (Nobs = 2,370,390), and found 304 significant independent signals. Our multivariate approaches resulted in a 26% increase in the number of independent signals relative to the four univariate GWAMAs and in an ~57% increase in the predictive power of polygenic risk scores. Supporting transcriptome- and methylome-wide analyses (TWAS and MWAS, respectively) uncovered an additional 17 and 75 independent loci, respectively. Bioinformatic analyses, based on gene expression in brain tissues and cells, showed that genes differentially expressed in the subiculum and GABAergic interneurons are enriched in their effect on the well-being spectrum.
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Affiliation(s)
- Bart M L Baselmans
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Hill F Ip
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Abdel Abdellaoui
- Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.,Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Margot P van de Weijer
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Yanchun Bao
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Melissa Smart
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | | | | | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. .,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. .,Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands. .,Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands.
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49
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Vandenbosch MMLJZ, van 't Ent D, Boomsma DI, Anokhin AP, Smit DJA. EEG-based age-prediction models as stable and heritable indicators of brain maturational level in children and adolescents. Hum Brain Mapp 2019; 40:1919-1926. [PMID: 30609125 DOI: 10.1002/hbm.24501] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 12/06/2018] [Accepted: 12/09/2018] [Indexed: 12/31/2022] Open
Abstract
The human brain shows remarkable development of functional brain activity from childhood to adolescence. Here, we investigated whether electroencephalogram (EEG) recordings are suitable for predicting the age of children and adolescents. Moreover, we investigated whether overestimation or underestimation of age was stable over longer time periods, as stable prediction error can be interpreted as reflecting individual brain maturational level. Finally, we established whether the age-prediction error was genetically determined. Then, 3 min eyes-closed resting-state EEG data from the longitudinal EEG studies of Netherlands Twin Register (NTR; n = 836) and Washington University in St. Louis (n = 702) were used at ages 5, 7, 12, 14, 16, and 18. Longitudinal data were available within childhood (5-7 years) and adolescence (16-18 years). We calculated power in 1 Hz wide bins (1-24 Hz). Random forest (RF) regression and relevance vector machine with sixfold cross-validation were applied. The best mean absolute prediction error was obtained with RF (1.22 years). Classification of childhood versus puberty/adolescence reached over 94% accuracy. Prediction errors were moderately to highly stable over periods of 1.5-2.1 years (0.53 < r < 0.74) and signifcantly affected by genetic factors (heritability between 42 and 79%). Our results show that age prediction from low-cost EEG recordings is comparable in accuracy to those obtained with magnetic resonance imaging. Children and adolescents showed stable overestimation or underestimation of their age, which means that some participants have stable brain activity patterns that reflect those of an older or younger age, and could therefore reflect individual brain maturational level. This prediction error is heritable, suggesting that genes underlie maturational level of functional brain activity. We propose that age prediction based on EEG recordings can be used for tracking neurodevelopment in typically developing children, in preterm children, and in children with neurodevelopmental disorders.
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Affiliation(s)
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Andrey P Anokhin
- Washington University School of Medicine, Department of Psychiatry, St. Louis, Missouri
| | - Dirk J A Smit
- Department of Psychiatry, Amsterdam Universitair Medisch Centrum, Amsterdam Neuroscience, Amsterdam, The Netherlands
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50
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van Bergen E, Snowling MJ, de Zeeuw EL, van Beijsterveldt CEM, Dolan CV, Boomsma DI. Why do children read more? The influence of reading ability on voluntary reading practices. J Child Psychol Psychiatry 2018; 59:1205-1214. [PMID: 29635740 DOI: 10.1111/jcpp.12910] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/12/2018] [Indexed: 11/25/2022]
Abstract
BACKGROUND This study investigates the causal relationships between reading and print exposure and investigates whether the amount children read outside school determines how well they read, or vice versa. Previous findings from behavioural studies suggest that reading predicts print exposure. Here, we use twin-data and apply the behaviour-genetic approach of direction of causality modelling, suggested by Heath et al. (), to investigate the causal relationships between these two traits. METHOD Partial data were available for a large sample of twin children (N = 11,559) and 262 siblings, all enrolled in the Netherlands Twin Register. Children were assessed around 7.5 years of age. Mothers completed questionnaires reporting children's time spent on reading activities and reading ability. Additional information on reading ability was available through teacher ratings and performance on national reading tests. For siblings reading test, results were available. RESULTS The reading ability of the twins was comparable to that of the siblings and national norms, showing that twin findings can be generalized to the population. A measurement model was specified with two latent variables, Reading Ability and Print Exposure, which correlated .41. Heritability analyses showed that Reading Ability was highly heritable, while genetic and environmental influences were equally important for Print Exposure. We exploited the fact that the two constructs differ in genetic architecture and fitted direction of causality models. The results supported a causal relationship running from Reading Ability to Print Exposure. CONCLUSIONS How much and how well children read are moderately correlated. Individual differences in print exposure are less heritable than individual differences in reading ability. Importantly, the present results suggest that it is the children's reading ability that determines how much they choose to read, rather than vice versa.
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Affiliation(s)
- Elsje van Bergen
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Experimental Psychology, University of Oxford, Oxford, UK
| | - Margaret J Snowling
- Experimental Psychology, University of Oxford, Oxford, UK.,St. John's College, Oxford, UK
| | - Eveline L de Zeeuw
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Conor V Dolan
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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