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Zhou Q, Gidziela A, Allegrini AG, Cheesman R, Wertz J, Maxwell J, Plomin R, Rimfeld K, Malanchini M. Gene-environment correlation: the role of family environment in academic development. Mol Psychiatry 2024:10.1038/s41380-024-02716-0. [PMID: 39232197 DOI: 10.1038/s41380-024-02716-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 08/20/2024] [Accepted: 08/22/2024] [Indexed: 09/06/2024]
Abstract
Academic achievement is partly heritable and highly polygenic. However, genetic effects on academic achievement are not independent of environmental processes. We investigated whether aspects of the family environment mediated genetic effects on academic achievement across development. Our sample included 5151 children who participated in the Twins Early Development Study, as well as their parents and teachers. Data on academic achievement and family environments (parenting, home environments, and geocoded indices of neighbourhood characteristics) were available at ages 7, 9, 12 and 16. We computed educational attainment polygenic scores (PGS) and further separated genetic effects into cognitive and noncognitive PGS. Three core findings emerged. First, aspects of the family environment, but not the wider neighbourhood context, consistently mediated the PGS effects on achievement across development-accounting for up to 34.3% of the total effect. Family characteristics mattered beyond socio-economic status. Second, family environments were more robustly linked to noncognitive PGS effects on academic achievement than cognitive PGS effects. Third, when we investigated whether environmental mediation effects could also be observed when considering differences between siblings, adjusting for family fixed effects, we found that environmental mediation was nearly exclusively observed between families. This is consistent with the proposition that family environmental contexts contribute to academic development via passive gene-environment correlation processes or genetic nurture. Our results show how parents tend to shape environments that foster their children's academic development partly based on their own genetic disposition, particularly towards noncognitive skills, rather than responding to each child's genetic disposition.
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Affiliation(s)
- Quan Zhou
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.
| | - Agnieszka Gidziela
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Andrea G Allegrini
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Rosa Cheesman
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
| | - Jasmin Wertz
- School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Jessye Maxwell
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Robert Plomin
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Kaili Rimfeld
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychology, Royal Holloway, University of London, London, UK
| | - Margherita Malanchini
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK.
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
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2
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Burt CH. Polygenic Indices (a.k.a. Polygenic Scores) in Social Science: A Guide for Interpretation and Evaluation. SOCIOLOGICAL METHODOLOGY 2024; 54:300-350. [PMID: 39091537 PMCID: PMC11293310 DOI: 10.1177/00811750241236482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Polygenic indices (PGI)-the new recommended label for polygenic scores (PGS) in social science-are genetic summary scales often used to represent an individual's liability for a disease, trait, or behavior based on the additive effects of measured genetic variants. Enthusiasm for linking genetic data with social outcomes and the inclusion of premade PGIs in social science datasets have facilitated increased uptake of PGIs in social science research-a trend that will likely continue. Yet, most social scientists lack the expertise to interpret and evaluate PGIs in social science research. Here, we provide a primer on PGIs for social scientists focusing on key concepts, unique statistical genetic considerations, and best practices in calculation, estimation, reporting, and interpretation. We summarize our recommended best practices as a checklist to aid social scientists in evaluating and interpreting studies with PGIs. We conclude by discussing the similarities between PGIs and standard social science scales and unique interpretative considerations.
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3
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Austerberry C, Fearon P, Ronald A, Leve LD, Ganiban JM, Natsuaki MN, Shaw DS, Neiderhiser JM, Reiss D. Evocative effects on the early caregiving environment of genetic factors underlying the development of intellectual and academic ability. Child Dev 2024. [PMID: 39081003 DOI: 10.1111/cdev.14142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
This study examined gene-environment correlation (rGE) in intellectual and academic development in 561 U.S.-based adoptees (57% male; 56% non-Latinx White, 19% multiracial, 13% Black or African American, 11% Latinx) and their birth and adoptive parents between 2003 and 2017. Birth mother intellectual and academic performance predicted adoptive mother warmth at child age 6 (β = .14, p = .038) and 7 (β = .12, p = .040) but not 4.5 years, and adoptive father warmth at 7 (β = .18, p = .007) but not 4.5 or 6 years. These rGE effects were not mediated by children's language. Contrary to theory that rGE accounts for increasing heritability of intellectual ability, parenting did not mediate genetic effects on children's language or academic performance.
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Affiliation(s)
- Chloe Austerberry
- Centre for Family Research, University of Cambridge, Cambridge, UK
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Pasco Fearon
- Centre for Family Research, University of Cambridge, Cambridge, UK
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | | | - Leslie D Leve
- Prevention Science Institute, University of Oregon, Eugene, Oregon, USA
- Cambridge Public Health, University of Cambridge, Cambridge, United Kingdom of Great Britain and Northern Ireland
| | - Jody M Ganiban
- Department of Psychology, George Washington University, Washington, District of Columbia, USA
| | - Misaki N Natsuaki
- Department of Psychology, University of California, Riverside, California, USA
| | - Daniel S Shaw
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jenae M Neiderhiser
- Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - David Reiss
- Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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4
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Fabbri C, Lewis CM, Serretti A. Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110972. [PMID: 38367896 DOI: 10.1016/j.pnpbp.2024.110972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/15/2023] [Accepted: 02/14/2024] [Indexed: 02/19/2024]
Abstract
Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum. We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders. We included 33 k-380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3-5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01-0.02% variance explained to the corresponding additive model. PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.
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Affiliation(s)
- Chiara Fabbri
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Alessandro Serretti
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy; Department of Medicine and Surgery, Kore University of Enna, Enna, Italy
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5
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Pons VT, Claringbould A, Kamphuis P, Oldehinkel AJ, van Loo HM. Using parent-offspring pairs and trios to estimate indirect genetic effects in education. Genet Epidemiol 2024; 48:190-199. [PMID: 38472165 PMCID: PMC11343084 DOI: 10.1002/gepi.22554] [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: 05/04/2023] [Revised: 02/06/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
We investigated indirect genetic effects (IGEs), also known as genetic nurture, in education with a novel approach that uses phased data to include parent-offspring pairs in the transmitted/nontransmitted study design. This method increases the power to detect IGEs, enhances the generalizability of the findings, and allows for the study of effects by parent-of-origin. We validated and applied this method in a family-based subsample of adolescents and adults from the Lifelines Cohort Study in the Netherlands (N = 6147), using the latest genome-wide association study data on educational attainment to construct polygenic scores (PGS). Our results indicated that IGEs play a role in education outcomes in the Netherlands: we found significant associations of the nontransmitted PGS with secondary school level in youth between 13 and 24 years old as well as with education attainment and years of education in adults over 25 years old (β = 0.14, 0.17 and 0.26, respectively), with tentative evidence for larger maternal IGEs. In conclusion, we replicated previous findings and showed that including parent-offspring pairs in addition to trios in the transmitted/nontransmitted design can benefit future studies of parental IGEs in a wide range of outcomes.
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Affiliation(s)
- Victória Trindade Pons
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Annique Claringbould
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Structural & Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Priscilla Kamphuis
- Department of Hematology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Albertine J. Oldehinkel
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Hanna M. van Loo
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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6
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Frach L, Barkhuizen W, Allegrini AG, Ask H, Hannigan LJ, Corfield EC, Andreassen OA, Dudbridge F, Ystrom E, Havdahl A, Pingault JB. Examining intergenerational risk factors for conduct problems using polygenic scores in the Norwegian Mother, Father and Child Cohort Study. Mol Psychiatry 2024; 29:951-961. [PMID: 38225381 PMCID: PMC11176059 DOI: 10.1038/s41380-023-02383-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 12/07/2023] [Accepted: 12/13/2023] [Indexed: 01/17/2024]
Abstract
The aetiology of conduct problems involves a combination of genetic and environmental factors, many of which are inherently linked to parental characteristics given parents' central role in children's lives across development. It is important to disentangle to what extent links between parental heritable characteristics and children's behaviour are due to transmission of genetic risk or due to parental indirect genetic influences via the environment (i.e., genetic nurture). We used 31,290 genotyped mother-father-child trios from the Norwegian Mother, Father and Child Cohort Study (MoBa), testing genetic transmission and genetic nurture effects on conduct problems using 13 polygenic scores (PGS) spanning psychiatric conditions, substance use, education-related factors, and other risk factors. Maternal or self-reports of conduct problems at ages 8 and 14 years were available for up to 15,477 children. We found significant genetic transmission effects on conduct problems for 12 out of 13 PGS at age 8 years (strongest association: PGS for smoking, β = 0.07, 95% confidence interval = [0.05, 0.08]) and for 4 out of 13 PGS at age 14 years (strongest association: PGS for externalising problems, β = 0.08, 95% confidence interval = [0.05, 0.11]). Conversely, we did not find genetic nurture effects for conduct problems using our selection of PGS. Our findings provide evidence for genetic transmission in the association between parental characteristics and child conduct problems. Our results may also indicate that genetic nurture via traits indexed by our polygenic scores is of limited aetiological importance for conduct problems-though effects of small magnitude or effects via parental traits not captured by the included PGS remain a possibility.
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Affiliation(s)
- Leonard Frach
- Department of Clinical, Educational & Health Psychology, Division of Psychology & Language Sciences, Faculty of Brain Sciences, University College London, London, UK.
| | - Wikus Barkhuizen
- Department of Clinical, Educational & Health Psychology, Division of Psychology & Language Sciences, Faculty of Brain Sciences, University College London, London, UK
| | - Andrea G Allegrini
- Department of Clinical, Educational & Health Psychology, Division of Psychology & Language Sciences, Faculty of Brain Sciences, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Helga Ask
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Laurie J Hannigan
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Elizabeth C Corfield
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Frank Dudbridge
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, University of Leicester, Leicester, UK
| | - Eivind Ystrom
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Alexandra Havdahl
- Center for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Jean-Baptiste Pingault
- Department of Clinical, Educational & Health Psychology, Division of Psychology & Language Sciences, Faculty of Brain Sciences, University College London, London, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
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7
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Nivard MG, Belsky DW, Harden KP, Baier T, Andreassen OA, Ystrøm E, van Bergen E, Lyngstad TH. More than nature and nurture, indirect genetic effects on children's academic achievement are consequences of dynastic social processes. Nat Hum Behav 2024:10.1038/s41562-023-01796-2. [PMID: 38225408 DOI: 10.1038/s41562-023-01796-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 11/29/2023] [Indexed: 01/17/2024]
Abstract
Families transmit genes and environments across generations. When parents' genetics affect their children's environments, these two modes of inheritance can produce an 'indirect genetic effect'. Such indirect genetic effects may account for up to half of the estimated genetic variance in educational attainment. Here we tested if indirect genetic effects reflect within-nuclear-family transmission ('genetic nurture') or instead a multi-generational process of social stratification ('dynastic effects'). We analysed indirect genetic effects on children's academic achievement in their fifth to ninth years of schooling in N = 37,117 parent-offspring trios in the Norwegian Mother, Father, and Child Cohort Study (MoBa). We used pairs of genetically related families (parents were siblings, children were cousins; N = 10,913) to distinguish within-nuclear-family genetic-nurture effects from dynastic effects shared by cousins in different nuclear families. We found that indirect genetic effects on children's academic achievement cannot be explained by processes that operate exclusively within the nuclear family.
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Affiliation(s)
- Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Daniel W Belsky
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
- Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA
| | - K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, University of Texas at Austin, Austin, TX, USA
| | - Tina Baier
- Department of Sociology and Human Geography, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Eivind Ystrøm
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Torkild H Lyngstad
- Department of Sociology and Human Geography, University of Oslo, Oslo, Norway.
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8
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Kenkel W. Preeclampsia Argues Against an Ovulatory Shift in Female Mate Preferences. ARCHIVES OF SEXUAL BEHAVIOR 2023; 52:3171-3176. [PMID: 37672134 PMCID: PMC10842107 DOI: 10.1007/s10508-023-02691-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/16/2023] [Accepted: 08/17/2023] [Indexed: 09/07/2023]
Affiliation(s)
- Will Kenkel
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, 19716, USA.
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9
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Wolfram T, Morris D. Conventional twin studies overestimate the environmental differences between families relevant to educational attainment. NPJ SCIENCE OF LEARNING 2023; 8:24. [PMID: 37460608 PMCID: PMC10352382 DOI: 10.1038/s41539-023-00173-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 07/04/2023] [Indexed: 07/20/2023]
Abstract
Estimates of shared environmental influence on educational attainment (EA) using the Classical Twin Design (CTD) have been enlisted as genetically sensitive measures of unequal opportunity. However, key assumptions of the CTD appear violated for EA. In this study we compared CTD estimates of shared environmental influence on EA with estimates from a Nuclear Twin and Family Design (NTFD) in the same 982 German families. Our CTD model estimated shared environmental influence at 43%. After accounting for assortative mating, our best fitting NTFD model estimated shared environmental influence at 26%, disaggregating this into twin-specific shared environments (16%) and environmental influences shared by all siblings (10%). Only the sibling shared environment captures environmental influences that reliably differ between families, suggesting the CTD substantially overestimates between-family differences in educational opportunity. Moreover, parental education was found to have no environmental effect on offspring education once genetic influences were accounted for.
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Affiliation(s)
- Tobias Wolfram
- Department of Sociology, University of Bielefeld, Niedersachen, Germany.
- Department of Sociology, ENSAE/CREST, Paris, France.
| | - Damien Morris
- Social, Genetic & Developmental Psychiatry Centre, King's College London, London, United Kingdom
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10
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Tanksley PT, Brislin SJ, Wertz J, de Vlaming R, Courchesne-Krak NS, Mallard TT, Raffington LL, Linnér RK, Koellinger P, Palmer A, Sanchez-Roige A, Waldman I, Dick D, Moffitt TE, Caspi A, Harden KP. Do polygenic indices capture "direct" effects on child externalizing behavior? Within-family analyses in two longitudinal birth cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.31.23290802. [PMID: 37398155 PMCID: PMC10312898 DOI: 10.1101/2023.05.31.23290802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Behaviors and disorders characterized by difficulties with self-regulation, such as problematic substance use, antisocial behavior, and symptoms of attention-deficit/hyperactivity disorder (ADHD), incur high costs for individuals, families, and communities. These externalizing behaviors often appear early in the life course and can have far-reaching consequences. Researchers have long been interested in direct measurements of genetic risk for externalizing behaviors, which can be incorporated alongside other known risk factors to improve efforts at early identification and intervention. In a preregistered analysis drawing on data from the Environmental Risk (E-Risk) Longitudinal Twin Study (N = 862 twins) and the Millennium Cohort Study (MCS; N = 2,824 parent-child trios), two longitudinal cohorts from the UK, we leveraged molecular genetic data and within-family designs to test for genetic effects on externalizing behavior that are unbiased by the common sources of environmental confounding. Results are consistent with the conclusion that an externalizing polygenic index (PGI) captures causal effects of genetic variants on externalizing problems in children and adolescents, with an effect size that is comparable to those observed for other established risk factors in the research literature on externalizing behavior. Additionally, we find that polygenic associations vary across development (peaking from age 5-10 years), that parental genetics (assortment and parent-specific effects) and family-level covariates affect prediction little, and that sex differences in polygenic prediction are present but only detectable using within-family comparisons. Based on these findings, we believe that the PGI for externalizing behavior is a promising means for studying the development of disruptive behaviors across child development.
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Affiliation(s)
- Peter T Tanksley
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Sarah J Brislin
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Newark, NJ, USA
| | - Jasmin Wertz
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ronald de Vlaming
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | - Travis T Mallard
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Laurel L Raffington
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
- Max Planck Institute for Human Development, Berlin, Germany
| | | | - Philipp Koellinger
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Abraham Palmer
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Alexandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Irwin Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
| | - Danielle Dick
- Department of Psychiatry, Rutgers Robert Wood Johnson Medical School, Newark, NJ, USA
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for the Study of Population Health & Aging, Duke University Population Research Institute, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Department of Psychology, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for the Study of Population Health & Aging, Duke University Population Research Institute, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
- Department of Psychology, University of Oslo, Oslo, Norway
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - K Paige Harden
- Department of Psychology, The University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
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11
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McAdams TA, Cheesman R, Ahmadzadeh YI. Annual Research Review: Towards a deeper understanding of nature and nurture: combining family-based quasi-experimental methods with genomic data. J Child Psychol Psychiatry 2023; 64:693-707. [PMID: 36379220 PMCID: PMC10952916 DOI: 10.1111/jcpp.13720] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/06/2022] [Indexed: 11/17/2022]
Abstract
Distinguishing between the effects of nature and nurture constitutes a major research goal for those interested in understanding human development. It is known, for example, that many parent traits predict mental health outcomes in children, but the causal processes underlying such associations are often unclear. Family-based quasi-experimental designs such as sibling comparison, adoption and extended family studies have been used for decades to distinguish the genetic transmission of risk from the environmental effects family members potentially have on one another. Recently, these designs have been combined with genomic data, and this combination is fuelling a range of exciting methodological advances. In this review we explore these advances - highlighting the ways in which they have been applied to date and considering what they are likely to teach us in the coming years about the aetiology and intergenerational transmission of psychopathology.
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Affiliation(s)
- Tom A. McAdams
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
- PROMENTA Research Centre, Department of PsychologyUniversity of OsloOsloNorway
| | - Rosa Cheesman
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
- PROMENTA Research Centre, Department of PsychologyUniversity of OsloOsloNorway
| | - Yasmin I. Ahmadzadeh
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
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12
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Guimond FA, Brendgen M, Vitaro F, Dionne G, Boivin M. Teachers' behaviour and children's academic achievement: Evidence of gene-environment interactions. BRITISH JOURNAL OF EDUCATIONAL PSYCHOLOGY 2023; 93:167-182. [PMID: 36086861 DOI: 10.1111/bjep.12546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 08/17/2022] [Indexed: 12/01/2022]
Abstract
BACKGROUND Children's academic achievement is considerably influenced by genetic factors, which rarely operate independently of environmental influences such as teachers' behaviour. Praise and punitive discipline are commonly used management strategies by teachers. However, their effects on the genetic expression of children's academic achievement are still unclear. AIMS This study examined potential gene-environment interactions in the associations between children's estimated genetic disposition for academic achievement and teachers' use of praise and punitive discipline in predicting academic achievement. SAMPLE The participants were 165 twin pairs in sixth grade (M = 12.1 years). METHODS Teachers reported on children's academic achievement, as well as on their own behaviour. RESULTS Multilevel regression analyses showed significant interactions between children's estimated genetic disposition for academic achievement and teachers' use of praise and punitive discipline, respectively, in predicting academic achievement. These interactions indicated an enhancement process, suggesting that genetically advantaged children are those most likely to benefit from regular praise and infrequent punishments from their teacher. Moreover, genetically advantaged children were not more (nor less) likely to receive praise or punishments than other students. However, students from underprivileged backgrounds were less likely to receive praise from their teachers. CONCLUSIONS The results emphasize the importance of teachers' regular use of praise and infrequent punitive discipline to help genetically advantaged children reach their full potential. Future studies should investigate other protective factors of the school environment that might reduce the role of genetic influences that undermine disadvantaged youth's academic achievement.
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Affiliation(s)
| | - Mara Brendgen
- Department of Psychology, University of Quebec at Montreal, Montreal, Quebec, Canada.,Ste. Justine Hospital Research Centre, Montreal, Quebec, Canada
| | - Frank Vitaro
- Ste. Justine Hospital Research Centre, Montreal, Quebec, Canada.,School of Psycho-education, University of Montreal, Montreal, Quebec, Canada
| | - Ginette Dionne
- Department of Psychology, Laval University, Quebec City, Quebec, Canada
| | - Michel Boivin
- Department of Psychology, Laval University, Quebec City, Quebec, Canada
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13
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Abdellaoui A, Yengo L, Verweij KJH, Visscher PM. 15 years of GWAS discovery: Realizing the promise. Am J Hum Genet 2023; 110:179-194. [PMID: 36634672 PMCID: PMC9943775 DOI: 10.1016/j.ajhg.2022.12.011] [Citation(s) in RCA: 90] [Impact Index Per Article: 90.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
It has been 15 years since the advent of the genome-wide association study (GWAS) era. Here, we review how this experimental design has realized its promise by facilitating an impressive range of discoveries with remarkable impact on multiple fields, including population genetics, complex trait genetics, epidemiology, social science, and medicine. We predict that the emergence of large-scale biobanks will continue to expand to more diverse populations and capture more of the allele frequency spectrum through whole-genome sequencing, which will further improve our ability to investigate the causes and consequences of human genetic variation for complex traits and diseases.
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Affiliation(s)
- Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
| | - Loic Yengo
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Karin J H Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
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14
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Cheesman R, Ayorech Z, Eilertsen EM, Ystrom E. Why we need families in genomic research on developmental psychopathology. JCPP ADVANCES 2023. [DOI: 10.1002/jcv2.12138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Affiliation(s)
- Rosa Cheesman
- PROMENTA Research Center Department of Psychology University of Oslo Oslo Norway
| | - Ziada Ayorech
- PROMENTA Research Center Department of Psychology University of Oslo Oslo Norway
| | - Espen M. Eilertsen
- PROMENTA Research Center Department of Psychology University of Oslo Oslo Norway
- Centre for Fertility and Health Norwegian Institute of Public Health Oslo Norway
| | - Eivind Ystrom
- PROMENTA Research Center Department of Psychology University of Oslo Oslo Norway
- Department of Mental Disorders Norwegian Institute of Public Health Oslo Norway
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15
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Song J, Zou Y, Wu Y, Miao J, Yu Z, Fletcher JM, Lu Q. Decomposing heritability and genetic covariance by direct and indirect effect paths. PLoS Genet 2023; 19:e1010620. [PMID: 36689559 PMCID: PMC9894552 DOI: 10.1371/journal.pgen.1010620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 02/02/2023] [Accepted: 01/16/2023] [Indexed: 01/24/2023] Open
Abstract
Estimation of heritability and genetic covariance is crucial for quantifying and understanding complex trait genetic architecture and is employed in almost all recent genome-wide association studies (GWAS). However, many existing approaches for heritability estimation and almost all methods for estimating genetic correlation ignore the presence of indirect genetic effects, i.e., genotype-phenotype associations confounded by the parental genome and family environment, and may thus lead to incorrect interpretation especially for human sociobehavioral phenotypes. In this work, we introduce a statistical framework to decompose heritability and genetic covariance into multiple components representing direct and indirect effect paths. Applied to five traits in UK Biobank, we found substantial involvement of indirect genetic components in shared genetic architecture across traits. These results demonstrate the effectiveness of our approach and highlight the importance of accounting for indirect effects in variance component analysis of complex traits.
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Affiliation(s)
- Jie Song
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Yiqing Zou
- Department of Statistics, Stanford University, Stanford, CA, United States of America
| | - Yuchang Wu
- Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Wisconsin, United States of America
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Jiacheng Miao
- Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Wisconsin, United States of America
| | - Ze Yu
- Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Wisconsin, United States of America
| | - Jason M. Fletcher
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Sociology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Qiongshi Lu
- Department of Statistics, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Biostatistics and Medical Informatics, University of Wisconsin–Madison, Wisconsin, United States of America
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
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16
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Chen C, Lu Y, Lundström S, Larsson H, Lichtenstein P, Pettersson E. Associations between psychiatric polygenic risk scores and general and specific psychopathology symptoms in childhood and adolescence between and within dizygotic twin pairs. J Child Psychol Psychiatry 2022; 63:1513-1522. [PMID: 35292971 PMCID: PMC9790278 DOI: 10.1111/jcpp.13605] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/23/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND Although polygenic risk scores (PRS) predict psychiatric problems, these associations might be attributable to indirect pathways including population stratification, assortative mating, or dynastic effects (mediation via parental environments). The goal of this study was to examine whether PRS-psychiatric symptom associations were attributable to indirect versus direct pathways. METHODS The sample consisted of 3,907 dizygotic (DZ) twin pairs. In childhood, their parents rated them on 98 symptoms. In adolescence (n = 2,393 DZ pairs), both the parents and the twins rated themselves on 20 symptoms. We extracted one general and seven specific factors from the childhood data, and one general and three specific factors from the adolescent data. We then regressed each general factor model onto ten psychiatric PRS simultaneously. We first conducted the regressions between individuals (β) and then within DZ twin pairs (βw ), which controls for indirect pathways. RESULTS In childhood, the PRS for ADHD predicted general psychopathology (β = 0.09, 95% CI: [0.06, 0.12]; βw = 0.07 [0.01, 0.12]). Furthermore, the PRS for ADHD predicted specific inattention (β = 0.04 [0.00, 0.08]; βw = 0.09 [0.01, 0.17]) and specific hyperactivity (β = 0.07 [0.04, 0.11]; βw = 0.09 [0.01, 0.16]); the PRS for schizophrenia predicted specific learning (β = 0.08 [0.03, 0.13]; βw = 0.19 [0.08, 0.30]) and specific inattention problems (β = 0.05 [0.01, 0.09]; βw = 0.10 [0.02, 0.19]); and the PRS for neuroticism predicted specific anxiety (β = 0.06 [0.02, 0.10]; βw = 0.06 [0.00, 0.12]). Overall, the PRS-general factor associations were similar between individuals and within twin pairs, whereas the PRS-specific factors associations amplified by 84% within pairs. CONCLUSIONS This implies that PRS-psychiatric symptom associations did not appear attributable to indirect pathways such as population stratification, assortative mating, or mediation via parental environments. Rather, genetics appeared to directly influence symptomatology.
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Affiliation(s)
- Cen Chen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yi Lu
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sebastian Lundström
- Centre for Ethics, Law and Mental Health (CELAM)University of GothenburgGothenburgSweden
- Gillberg Neuropsychiatry CentreUniversity of GothenburgGothenburgSweden
| | - Henrik Larsson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- School of Medical SciencesÖrebro UniversityÖrebroSweden
| | - Paul Lichtenstein
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Erik Pettersson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
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17
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Educational Attainment Polygenic Scores: Examining Evidence for Gene-Environment Interplay with Adolescent Alcohol, Tobacco and Cannabis Use. Twin Res Hum Genet 2022; 25:187-195. [PMID: 36189823 DOI: 10.1017/thg.2022.33] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Genes associated with educational attainment may be related to or interact with adolescent alcohol, tobacco and cannabis use. Potential gene-environment interplay between educational attainment polygenic scores (EA-PGS) and adolescent alcohol, tobacco, and cannabis use was evaluated with a series of regression models fitted to data from a sample of 1871 adult Australian twins. All models controlled for age, age2, cohort, sex and genetic ancestry as fixed effects, and a genetic relatedness matrix was included as a random effect. Although there was no evidence that adolescent alcohol, tobacco or cannabis use interacted with EA-PGS to influence educational attainment, there was a significant, positive gene-environment correlation with adolescent alcohol use at all PGS thresholds (ps <.02). Higher EA-PGS were associated with an increased likelihood of using alcohol as an adolescent (ΔR2 ranged from 0.5% to 1.1%). The positive gene-environment correlation suggests a complex relationship between educational attainment and alcohol use that is due to common genetic factors.
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18
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Harden KP. On genetics and justice: A reply to Coop and Przeworski (). Evolution 2022; 76:2469-2474. [PMID: 35913435 PMCID: PMC10337657 DOI: 10.1111/evo.14589] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/05/2022] [Accepted: 04/20/2022] [Indexed: 01/22/2023]
Affiliation(s)
- Kathryn Paige Harden
- Department of Psychology, Population Research Center, University of Texas at Austin, Austin, Texas 78712
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19
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Demange PA, Hottenga JJ, Abdellaoui A, Eilertsen EM, Malanchini M, Domingue BW, Armstrong-Carter E, de Zeeuw EL, Rimfeld K, Boomsma DI, van Bergen E, Breen G, Nivard MG, Cheesman R. Estimating effects of parents' cognitive and non-cognitive skills on offspring education using polygenic scores. Nat Commun 2022; 13:4801. [PMID: 35999215 PMCID: PMC9399113 DOI: 10.1038/s41467-022-32003-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 07/12/2022] [Indexed: 12/12/2022] Open
Abstract
Understanding how parents' cognitive and non-cognitive skills influence offspring education is essential for educational, family and economic policy. We use genetics (GWAS-by-subtraction) to assess a latent, broad non-cognitive skills dimension. To index parental effects controlling for genetic transmission, we estimate indirect parental genetic effects of polygenic scores on childhood and adulthood educational outcomes, using siblings (N = 47,459), adoptees (N = 6407), and parent-offspring trios (N = 2534) in three UK and Dutch cohorts. We find that parental cognitive and non-cognitive skills affect offspring education through their environment: on average across cohorts and designs, indirect genetic effects explain 36-40% of population polygenic score associations. However, indirect genetic effects are lower for achievement in the Dutch cohort, and for the adoption design. We identify potential causes of higher sibling- and trio-based estimates: prenatal indirect genetic effects, population stratification, and assortative mating. Our phenotype-agnostic, genetically sensitive approach has established overall environmental effects of parents' skills, facilitating future mechanistic work.
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Affiliation(s)
- Perline A Demange
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Espen Moen Eilertsen
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Margherita Malanchini
- Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Benjamin W Domingue
- Graduate School of Education, Stanford University, Stanford, CA, USA
- Center for Population Health Sciences, Stanford University, Stanford, CA, USA
- Center for Education Policy Analysis, Stanford University, Stanford, CA, USA
| | - Emma Armstrong-Carter
- Graduate School of Education, Stanford University, Stanford, CA, USA
- Center for Education Policy Analysis, Stanford University, Stanford, CA, USA
| | - Eveline L de Zeeuw
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Kaili Rimfeld
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Department of Psychology, Royal Holloway University of London, London, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Elsje van Bergen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gerome Breen
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Michel G Nivard
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rosa Cheesman
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway.
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
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20
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Hwang LD, Moen GH, Evans DM. Using adopted individuals to partition indirect maternal genetic effects into prenatal and postnatal effects on offspring phenotypes. eLife 2022; 11:e73671. [PMID: 35822614 PMCID: PMC9323003 DOI: 10.7554/elife.73671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 07/11/2022] [Indexed: 11/13/2022] Open
Abstract
Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases.
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Affiliation(s)
- Liang-Dar Hwang
- Institute for Molecular Bioscience, The University of QueenslandBrisbaneAustralia
| | - Gunn-Helen Moen
- Institute for Molecular Bioscience, The University of QueenslandBrisbaneAustralia
- The University of Queensland Diamantina Institute, The University of QueenslandBrisbaneAustralia
- Institute for Clinical Medicine, Faculty of Medicine, University of OsloOsloNorway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and TechnologyTrondheimNorway
- Population Health Science, Bristol Medical School, University of BristolBristolUnited Kingdom
| | - David M Evans
- Institute for Molecular Bioscience, The University of QueenslandBrisbaneAustralia
- The University of Queensland Diamantina Institute, The University of QueenslandBrisbaneAustralia
- MRC Integrative Epidemiology Unit, University of BristolBristolUnited Kingdom
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21
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Howe LJ, Evans DM, Hemani G, Davey Smith G, Davies NM. Evaluating indirect genetic effects of siblings using singletons. PLoS Genet 2022; 18:e1010247. [PMID: 35797272 PMCID: PMC9262210 DOI: 10.1371/journal.pgen.1010247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 05/10/2022] [Indexed: 12/23/2022] Open
Abstract
Estimating effects of parental and sibling genotypes (indirect genetic effects) can provide insight into how the family environment influences phenotypic variation. There is growing molecular genetic evidence for effects of parental phenotypes on their offspring (e.g. parental educational attainment), but the extent to which siblings affect each other is currently unclear. Here we used data from samples of unrelated individuals, without (singletons) and with biological full-siblings (non-singletons), to investigate and estimate sibling effects. Indirect genetic effects of siblings increase (or decrease) the covariance between genetic variation and a phenotype. It follows that differences in genetic association estimates between singletons and non-singletons could indicate indirect genetic effects of siblings if there is no heterogeneity in other sources of genetic association between singletons and non-singletons. We used UK Biobank data to estimate polygenic score (PGS) associations for height, BMI and educational attainment in self-reported singletons (N = 50,143) and non-singletons (N = 328,549). The educational attainment PGS association estimate was 12% larger (95% C.I. 3%, 21%) in the non-singleton sample than in the singleton sample, but the height and BMI PGS associations were consistent. Birth order data suggested that the difference in educational attainment PGS associations was driven by individuals with older siblings rather than firstborns. The relationship between number of siblings and educational attainment PGS associations was non-linear; PGS associations were 24% smaller in individuals with 6 or more siblings compared to the rest of the sample (95% C.I. 11%, 38%). We estimate that a 1 SD increase in sibling educational attainment PGS corresponds to a 0.025 year increase in the index individual's years in schooling (95% C.I. 0.013, 0.036). Our results suggest that older siblings may influence the educational attainment of younger siblings, adding to the growing evidence that effects of the environment on phenotypic variation partially reflect social effects of germline genetic variation in relatives.
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Affiliation(s)
- Laurence J. Howe
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David M. Evans
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Neil M. Davies
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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22
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Burt CH. Challenging the utility of polygenic scores for social science: Environmental confounding, downward causation, and unknown biology. Behav Brain Sci 2022; 46:e207. [PMID: 35551690 PMCID: PMC9653522 DOI: 10.1017/s0140525x22001145] [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] [Indexed: 11/06/2022]
Abstract
The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as "genetic propensities" for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene-environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d'être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications.
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Affiliation(s)
- Callie H Burt
- Department of Criminal Justice & Criminology, Center for Research on Interpersonal Violence (CRIV), Georgia State University, Atlanta, GA, USA ; www.callieburt.org
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23
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Catts HW, Petscher Y. A Cumulative Risk and Resilience Model of Dyslexia. JOURNAL OF LEARNING DISABILITIES 2022; 55:171-184. [PMID: 34365842 DOI: 10.1177/00222194211037062] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Considerable attention and legislation are currently focused on developmental dyslexia. A major challenge to these efforts is how to define and operationalize dyslexia. In this article, we argue that rather than defining dyslexia on the basis of an underlying condition, dyslexia is best viewed as a label for an unexpected reading disability. This view fits well with a preventive approach in which risk for reading disability is identified and addressed prior to children experiencing reading failure. A risk-resilience model is introduced that proposes that dyslexia is due to the cumulative effects of risk and resilience factors. Evidence for the multifactorial causal basis of dyslexia is reviewed and potential factors that may offset this risk are considered. The implications of a cumulative risk and resilience model for early identification and intervention is discussed.
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24
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Nagpal S, Tandon R, Gibson G. Canalization of the Polygenic Risk for Common Diseases and Traits in the UK Biobank Cohort. Mol Biol Evol 2022; 39:6547257. [PMID: 35275999 PMCID: PMC9004416 DOI: 10.1093/molbev/msac053] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Since organisms develop and thrive in the face of constant perturbations due to environmental and genetic variation, species may evolve resilient genetic architectures. We sought evidence for this process, known as canalization, through a comparison of the prevalence of phenotypes as a function of the polygenic score (PGS) across environments in the UK Biobank cohort study. Contrasting seven diseases and three categorical phenotypes with respect to 151 exposures in 408,925 people, the deviation between the prevalence-risk curves was observed to increase monotonically with the PGS percentile in one-fifth of the comparisons, suggesting extensive PGS-by-Environment (PGS×E) interaction. After adjustment for the dependency of allelic effect sizes on increased prevalence in the perturbing environment, cases where polygenic influences are greater or lesser than expected are seen to be particularly pervasive for educational attainment, obesity, and metabolic condition type-2 diabetes. Inflammatory bowel disease analysis shows fewer interactions but confirms that smoking and some aspects of diet influence risk. Notably, body mass index has more evidence for decanalization (increased genetic influence at the extremes of polygenic risk), whereas the waist-to-hip ratio shows canalization, reflecting different evolutionary pressures on the architectures of these weight-related traits. An additional 10 % of comparisons showed evidence for an additive shift of prevalence independent of PGS between exposures. These results provide the first widespread evidence for canalization protecting against disease in humans and have implications for personalized medicine as well as understanding the evolution of complex traits. The findings can be explored through an R shiny app at https://canalization-gibsonlab.shinyapps.io/rshiny/.
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Affiliation(s)
- Sini Nagpal
- School of Biological Sciences, and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, USA
| | - Raghav Tandon
- Wallace H. Coulter Department of Biomedical Engineering, and Center for Machine Learning, Georgia Institute of Technology, Atlanta, GA, USA
| | - Greg Gibson
- School of Biological Sciences, and Center for Integrative Genomics, Georgia Institute of Technology, Atlanta, GA, USA
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25
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Simulated nonlinear genetic and environmental dynamics of complex traits. Dev Psychopathol 2022; 35:662-677. [PMID: 35236532 PMCID: PMC9440154 DOI: 10.1017/s0954579421001796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Genetic studies of complex traits often show disparities in estimated heritability depending on the method used, whether by genomic associations or twin and family studies. We present a simulation of individual genomes with dynamic environmental conditions to consider how linear and nonlinear effects, gene-by-environment interactions, and gene-by-environment correlations may work together to govern the long-term development of complex traits and affect estimates of heritability from common methods. Our simulation studies demonstrate that the genetic effects estimated by genome wide association studies in unrelated individuals are inadequate to characterize gene-by-environment interaction, while including related individuals in genome-wide complex trait analysis (GCTA) allows gene-by-environment interactions to be recovered in the heritability. These theoretical findings provide an explanation for the "missing heritability" problem and bridge the conceptual gap between the most common findings of GCTA and twin studies. Future studies may use the simulation model to test hypotheses about phenotypic complexity either in an exploratory way or by replicating well-established observations of specific phenotypes.
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Austerberry C, Fearon P, Ronald A, Leve LD, Ganiban JM, Natsuaki MN, Shaw DS, Neiderhiser JM, Reiss D. Early manifestations of intellectual performance: Evidence that genetic effects on later academic test performance are mediated through verbal performance in early childhood. Child Dev 2022; 93:e188-e206. [PMID: 34783370 PMCID: PMC10861934 DOI: 10.1111/cdev.13706] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Intellectual performance is highly heritable and robustly predicts lifelong health and success but the earliest manifestations of genetic effects on this asset are not well understood. This study examined whether early executive function (EF) or verbal performance mediate genetic influences on subsequent intellectual performance, in 561 U.S.-based adoptees (57% male) and their birth and adoptive parents (70% and 92% White, 13% and 4% African American, 7% and 2% Latinx, respectively), administered measures in 2003-2017. Genetic influences on children's academic performance at 7 years were mediated by verbal performance at 4.5 years (β = .22, 95% CI [0.08, 0.35], p = .002) and not via EF, indicating that verbal performance is an early manifestation of genetic propensity for intellectual performance.
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Affiliation(s)
- Chloe Austerberry
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Pasco Fearon
- Research Department of Clinical, Educational and Health Psychology, UCL, London, UK
| | - Angelica Ronald
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Leslie D. Leve
- Prevention Science Institute, University of Oregon, Eugene, Oregon, USA
| | - Jody M. Ganiban
- Department of Psychological and Brain Sciences, George Washington University, Washington, District of Columbia, USA
| | - Misaki N. Natsuaki
- Department of Psychology, University of California, Riverside, California, USA
| | - Daniel S. Shaw
- Department of Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jenae M. Neiderhiser
- Department of Psychology, The Pennsylvania State University, University Park, Pennsylvania, USA
| | - David Reiss
- Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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Baud A, McPeek S, Chen N, Hughes KA. Indirect Genetic Effects: A Cross-disciplinary Perspective on Empirical Studies. J Hered 2022; 113:1-15. [PMID: 34643239 PMCID: PMC8851665 DOI: 10.1093/jhered/esab059] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Indirect genetic effects (IGE) occur when an individual's phenotype is influenced by genetic variation in conspecifics. Opportunities for IGE are ubiquitous, and, when present, IGE have profound implications for behavioral, evolutionary, agricultural, and biomedical genetics. Despite their importance, the empirical study of IGE lags behind the development of theory. In large part, this lag can be attributed to the fact that measuring IGE, and deconvoluting them from the direct genetic effects of an individual's own genotype, is subject to many potential pitfalls. In this Perspective, we describe current challenges that empiricists across all disciplines will encounter in measuring and understanding IGE. Using ideas and examples spanning evolutionary, agricultural, and biomedical genetics, we also describe potential solutions to these challenges, focusing on opportunities provided by recent advances in genomic, monitoring, and phenotyping technologies. We hope that this cross-disciplinary assessment will advance the goal of understanding the pervasive effects of conspecific interactions in biology.
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Affiliation(s)
- Amelie Baud
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.,the Universitat Pompeu Fabra (UPF), Barcelona,Spain
| | - Sarah McPeek
- the Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | - Nancy Chen
- the Department of Biology, University of Rochester, Rochester, NY 14627,USA
| | - Kimberly A Hughes
- the Department of Biological Science, Florida State University, Tallahassee, FL 32303,USA
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Schizophrenia polygenic risk is associated with child mental health problems through early childhood adversity: evidence for a gene-environment correlation. Eur Child Adolesc Psychiatry 2022; 31:529-539. [PMID: 33635441 PMCID: PMC8940779 DOI: 10.1007/s00787-021-01727-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 01/16/2021] [Indexed: 12/22/2022]
Abstract
Previous studies have shown that schizophrenia polygenic risk predicts a multitude of mental health problems in the general population. Yet it is unclear by which mechanisms these associations arise. Here, we explored a possible gene-environment correlation in the association of schizophrenia polygenic risk with mental health problems via childhood adversity. This study was embedded in the population-based Generation R Study, including N = 1901 participants with genotyping for schizophrenia polygenic risk, maternal reporting of childhood adversity, and Child Behaviour Checklist measurement of mental health problems. Independent replication was attempted in the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 3641). Associations were analysed with Poisson regression and statistical mediation analysis. Higher burden of schizophrenia polygenic risk was associated with greater exposure to childhood adversity (P-value threshold < 0.5: Generation R Study, OR = 1.08, 95%CI 1.02-1.15, P = 0.01; ALSPAC, OR = 1.02, 95%CI 1.01-1.03, P < 0.01). Childhood adversities partly explained the relationship of schizophrenia polygenic risk with emotional, attention, and thought problems (proportion explained, range 5-23%). Direct effects of schizophrenia polygenic risk and adversity on mental health outcomes were also observed. In summary, genetic liability to schizophrenia increased the risk for mental health problems in the general paediatric population through childhood adversity. Although this finding could result from a mediated causal relationship between genotype and mental health, we argue that these observations most likely reflect a gene-environment correlation, i.e. adversities are a marker for the genetic risk that parents transmit to children. These and similar recent findings raise important conceptual questions about preventative interventions aimed at reducing childhood adversities.
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Deary IJ, Cox SR, Hill WD. Genetic variation, brain, and intelligence differences. Mol Psychiatry 2022; 27:335-353. [PMID: 33531661 PMCID: PMC8960418 DOI: 10.1038/s41380-021-01027-y] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 12/28/2020] [Accepted: 01/11/2021] [Indexed: 01/30/2023]
Abstract
Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are substantially stable across the life course, and are predictive of educational, social, and health outcomes. From this solid phenotypic foundation and importance for life, comes an interest in the environmental, social, and genetic aetiologies of intelligence, and in the foundations of intelligence differences in brain structure and functioning. Here, we summarise and critique the last 10 years or so of molecular genetic (DNA-based) research on intelligence, including the discovery of genetic loci associated with intelligence, DNA-based heritability, and intelligence's genetic correlations with other traits. We summarise new brain imaging-intelligence findings, including whole-brain associations and grey and white matter associations. We summarise regional brain imaging associations with intelligence and interpret these with respect to theoretical accounts. We address research that combines genetics and brain imaging in studying intelligence differences. There are new, though modest, associations in all these areas, and mechanistic accounts are lacking. We attempt to identify growing points that might contribute toward a more integrated 'systems biology' account of some of the between-individual differences in intelligence.
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Affiliation(s)
- Ian J. Deary
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - Simon R. Cox
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
| | - W. David Hill
- grid.4305.20000 0004 1936 7988Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
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30
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Dawes CT, Okbay A, Oskarsson S, Rustichini A. A polygenic score for educational attainment partially predicts voter turnout. Proc Natl Acad Sci U S A 2021; 118:e2022715118. [PMID: 34873032 PMCID: PMC8685665 DOI: 10.1073/pnas.2022715118] [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] [Accepted: 10/12/2021] [Indexed: 12/19/2022] Open
Abstract
Twin and adoption studies have shown that individual differences in political participation can be explained, in part, by genetic variation. However, these research designs cannot identify which genes are related to voting or the pathways through which they exert influence, and their conclusions rely on possibly restrictive assumptions. In this study, we use three different US samples and a Swedish sample to test whether genes that have been identified as associated with educational attainment, one of the strongest correlates of political participation, predict self-reported and validated voter turnout. We find that a polygenic score capturing individuals' genetic propensity to acquire education is significantly related to turnout. The strongest associations we observe are in second-order midterm elections in the United States and European Parliament elections in Sweden, which tend to be viewed as less important by voters, parties, and the media and thus present a more information-poor electoral environment for citizens to navigate. A within-family analysis suggests that individuals' education-linked genes directly affect their voting behavior, but, for second-order elections, it also reveals evidence of genetic nurture. Finally, a mediation analysis suggests that educational attainment and cognitive ability combine to account for between 41% and 63% of the relationship between the genetic propensity to acquire education and voter turnout.
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Affiliation(s)
- Christopher T Dawes
- Wilf Family Department of Politics, New York University, New York, NY 10012;
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, 1081HV Amsterdam, The Netherlands
| | - Sven Oskarsson
- Department of Government, Uppsala Universitet, 751 20 Uppsala, Sweden
| | - Aldo Rustichini
- Department of Economics, University of Minnesota, Minneapolis, MN 55455-0462
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Kondratyev NV, Alfimova MV, Golov AK, Golimbet VE. Bench Research Informed by GWAS Results. Cells 2021; 10:3184. [PMID: 34831407 PMCID: PMC8623533 DOI: 10.3390/cells10113184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.
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Affiliation(s)
| | | | - Arkadiy K. Golov
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
- Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vera E. Golimbet
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
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Friedman NP, Banich MT, Keller MC. Twin studies to GWAS: there and back again. Trends Cogn Sci 2021; 25:855-869. [PMID: 34312064 PMCID: PMC8446317 DOI: 10.1016/j.tics.2021.06.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 01/01/2023]
Abstract
The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.
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Affiliation(s)
- Naomi P Friedman
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309, USA.
| | - Marie T Banich
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO 80309, USA
| | - Matthew C Keller
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA; Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80309, USA
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Wang B, Baldwin JR, Schoeler T, Cheesman R, Barkhuizen W, Dudbridge F, Bann D, Morris TT, Pingault JB. Robust genetic nurture effects on education: A systematic review and meta-analysis based on 38,654 families across 8 cohorts. Am J Hum Genet 2021; 108:1780-1791. [PMID: 34416156 PMCID: PMC8456157 DOI: 10.1016/j.ajhg.2021.07.010] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/21/2021] [Indexed: 12/20/2022] Open
Abstract
Similarities between parents and offspring arise from nature and nurture. Beyond this simple dichotomy, recent genomic studies have uncovered "genetic nurture" effects, whereby parental genotypes influence offspring outcomes via environmental pathways rather than genetic transmission. Such genetic nurture effects also need to be accounted for to accurately estimate "direct" genetic effects (i.e., genetic effects on a trait originating in the offspring). Empirical studies have indicated that genetic nurture effects are particularly relevant to the intergenerational transmission of risk for child educational outcomes, which are, in turn, associated with major psychological and health milestones throughout the life course. These findings have yet to be systematically appraised across contexts. We conducted a systematic review and meta-analysis to quantify genetic nurture effects on educational outcomes. A total of 12 studies comprising 38,654 distinct parent(s)-offspring pairs or trios from 8 cohorts reported 22 estimates of genetic nurture effects. Genetic nurture effects on offspring's educational outcomes (βgenetic nurture = 0.08, 95% CI [0.07, 0.09]) were smaller than direct genetic effects (βdirect genetic = 0.17, 95% CI [0.13, 0.20]). Findings were largely consistent across studies. Genetic nurture effects originating from mothers and fathers were of similar magnitude, highlighting the need for a greater inclusion of fathers in educational research. Genetic nurture effects were largely explained by observed parental education and socioeconomic status, pointing to their role in environmental pathways shaping child educational outcomes. Findings provide consistent evidence that environmentally mediated parental genetic influences contribute to the intergenerational transmission of educational outcomes, in addition to effects due to genetic transmission.
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Affiliation(s)
- Biyao Wang
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK
| | - Jessie R Baldwin
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College, London SE5 8AF, UK
| | - Tabea Schoeler
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK
| | - Rosa Cheesman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College, London SE5 8AF, UK; PROMENTA Research Center, Department of Psychology, University of Oslo, 0373 Oslo, Norway
| | - Wikus Barkhuizen
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK
| | - Frank Dudbridge
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College London, London WC1H 0AL, UK
| | - Tim T Morris
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Jean-Baptiste Pingault
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP, UK; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College, London SE5 8AF, UK.
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Rea-Sandin G, Oro V, Strouse E, Clifford S, Wilson MN, Shaw DS, Lemery-Chalfant K. Educational attainment polygenic score predicts inhibitory control and academic skills in early and middle childhood. GENES, BRAIN, AND BEHAVIOR 2021; 20:e12762. [PMID: 34318993 PMCID: PMC8549462 DOI: 10.1111/gbb.12762] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 07/05/2021] [Accepted: 07/27/2021] [Indexed: 01/10/2023]
Abstract
Inhibitory control skills are important for academic outcomes across childhood, but it is unknown whether inhibitory control is implicated in the association between genetic variation and academic performance. This study examined the relationship between a GWAS-based (EduYears) polygenic score indexing educational attainment (EA PGS) and inhibitory control in early (Mage = 3.80 years) and middle childhood (Mage = 9.18 years), and whether inhibitory control in early childhood mediated the relation between EA PGS and academic skills. The sample comprised 731 low-income and racially/ethnically diverse children and their families from the longitudinal early steps multisite study. EA PGS predicted middle childhood inhibitory control (estimate = 0.09, SE = 0.05, p < 0.05) and academic skills (estimate = 0.18, SE = 0.05, p < 0.01) but did not predict early childhood inhibitory control (estimate = 0.08, SE = 0.05, p = 0.11); thus, mediation was not tested. Sensitivity analyses showed that effect sizes were similar across European and African American groups. This study suggests that inhibitory control could serve as a potential mechanism linking genetic differences to educational outcomes.
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35
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Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits. Nat Hum Behav 2021. [PMID: 33686200 DOI: 10.1038/s41562-021-01053-4.genetic] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES), and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N ~ 160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using genomic structural equation modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.
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36
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Marees AT, Smit DJ, Abdellaoui A, Nivard MG, van den Brink W, Denys D, Galama TJ, Verweij KJ, Derks EM. Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits. Nat Hum Behav 2021; 5:1065-1073. [PMID: 33686200 PMCID: PMC8376746 DOI: 10.1038/s41562-021-01053-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 01/13/2021] [Indexed: 01/31/2023]
Abstract
Epidemiological studies show high comorbidity between different mental health problems, indicating that individuals with a diagnosis of one disorder are more likely to develop other mental health problems. Genetic studies reveal substantial sharing of genetic factors across mental health traits. However, mental health is also genetically correlated with socio-economic status (SES), and it is therefore important to investigate and disentangle the genetic relationship between mental health and SES. We used summary statistics from large genome-wide association studies (average N ~ 160,000) to estimate the genetic overlap across nine psychiatric disorders and seven substance use traits and explored the genetic influence of three different indicators of SES. Using genomic structural equation modelling, we show significant changes in patterns of genetic correlations after partialling out SES-associated genetic variation. Our approach allows the separation of disease-specific genetic variation and genetic variation shared with SES, thereby improving our understanding of the genetic architecture of mental health.
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Affiliation(s)
- Andries T. Marees
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands,QIMR Berghofer, Translational Neurogenomics group, Brisbane, Queensland, Australia,Department of Economics, School of Business and Economics, VU University Amsterdam, Amsterdam, the Netherlands,Correspondence: Andries T. Marees () Eske M. Derks ()
| | - Dirk J.A. Smit
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Michel G. Nivard
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Wim van den Brink
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Damiaan Denys
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Titus J. Galama
- Department of Economics, School of Business and Economics, VU University Amsterdam, Amsterdam, the Netherlands,University of Southern California, Dornsife Center for Economic and Social Research (CESR), Los Angeles, CA, USA,Erasmus School of Economics, Erasmus University, Rotterdam, The Netherlands
| | - Karin J.H. Verweij
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Eske M. Derks
- QIMR Berghofer, Translational Neurogenomics group, Brisbane, Queensland, Australia,Correspondence: Andries T. Marees () Eske M. Derks ()
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37
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Wu Y, Zhong X, Lin Y, Zhao Z, Chen J, Zheng B, Li JJ, Fletcher JM, Lu Q. Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies. Proc Natl Acad Sci U S A 2021; 118:e2023184118. [PMID: 34131076 PMCID: PMC8237646 DOI: 10.1073/pnas.2023184118] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic, and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower body mass index, less-active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. A polygenic transmission disequilibrium test showed a significant overtransmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.
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Affiliation(s)
- Yuchang Wu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
| | - Xiaoyuan Zhong
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
| | - Yunong Lin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
| | - Zijie Zhao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706
| | - Jiawen Chen
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514
| | - Boyan Zheng
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Sociology, University of Wisconsin-Madison, Madison, WI 53706
| | - James J Li
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53706
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53706
| | - Jason M Fletcher
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Sociology, University of Wisconsin-Madison, Madison, WI 53706
- La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, WI 53706
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706;
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706
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38
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Dissecting polygenic signals from genome-wide association studies on human behaviour. Nat Hum Behav 2021; 5:686-694. [PMID: 33986517 DOI: 10.1038/s41562-021-01110-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 03/31/2021] [Indexed: 02/03/2023]
Abstract
Genome-wide association studies on human behavioural traits are producing large amounts of polygenic signals with significant predictive power and potentially useful biological clues. Behavioural traits are more distal and are less directly under biological control compared with physical characteristics, which makes the associated genetic effects harder to interpret. The results of genome-wide association studies for human behaviour are likely made up of a composite of signals from different sources. While sample sizes continue to increase, we outline additional steps that need to be taken to better delineate the origin of the increasingly stronger polygenic signals. In addition to genetic effects on the traits themselves, the major sources of polygenic signals are those that are associated with correlated traits, environmental effects and ascertainment bias. Advances in statistical approaches that disentangle polygenic effects from different traits as well as extending data collection to families and social circles with better geographical coverage will probably contribute to filling the gap of knowledge between genetic effects and behavioural outcomes.
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Leigh E, Chiu K, Clark DM. Is concentration an indirect link between social anxiety and educational achievement in adolescents? PLoS One 2021; 16:e0249952. [PMID: 33989297 PMCID: PMC8121284 DOI: 10.1371/journal.pone.0249952] [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: 09/04/2020] [Accepted: 03/29/2021] [Indexed: 01/05/2023] Open
Abstract
Social anxiety is associated with reduced educational achievement. Given that concentration is a predictor of educational achievement, and social anxiety symptoms are associated with reduced concentration in class, this prospective study examined the possibility that social anxiety may impair educational achievement through reduced classroom concentration. A sample of 509 participants (53.8% female; M age: 12.77 years [SD = 0.81]) recruited from secondary schools completed questionnaires assessing social anxiety symptoms, depressive symptoms, and concentration in class. Educational achievement was assessed by internal grades within schools. An indirect effect of social anxiety on later educational achievement via concentration was observed, over and above baseline achievement and depression symptoms; adolescents with higher levels of social anxiety tend to have more difficulties concentrating in class, which in turn is associated with poorer academic outcomes. Findings underscore the challenges socially anxious adolescents will face trying to learn in school, and the need for education providers and clinicians to consider the effect of social anxiety symptoms on concentration and learning.
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Affiliation(s)
- Eleanor Leigh
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
- * E-mail:
| | - Kenny Chiu
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - David M. Clark
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
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40
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Anderson EL, Saunders GRB, Willoughby EA, Iacono WG, McGue M. The role of the shared environment in college attainment: An adoption study. J Pers 2021; 89:580-593. [PMID: 33090471 PMCID: PMC10888505 DOI: 10.1111/jopy.12600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 10/06/2020] [Indexed: 11/29/2022]
Abstract
OBJECTIVE College attainment is one of the few phenotypes to have substantial variance accounted for by environmental factors shared by reared-together relatives. The shared environment is implicated by the consistently strong parent-to-offspring transmission of college attainment. The mechanisms underlying this relationship remain unclear. We use genetically informative methods with a longitudinal, adoption sample to identify possible environmental mechanisms underlying parent-offspring college transmission. METHOD Data were drawn from the Sibling Interaction and Behavior Study (SIBS), which includes 409 adoptive and 208 nonadoptive families, consisting of two offspring followed from adolescence into young adulthood and their rearing parents. Four domains of environmental mechanisms were examined: (a) skill enhancement; (b) academic support; (c) material advantage; and (d) supportive family environment. RESULTS Both shared environmental and genetic factors contributed to the parent-offspring transmission of college attainment. However, highly educated parents did not appear to be increasing their adopted offspring's attainment through skill development. The environmental factors that were associated with increased odds of offspring college attainment were mother's academic expectations and family income. CONCLUSIONS While complete mediation of the parent-offspring transmission of college attainment was not identified, the results shed light on some of the mechanisms associated with the common environment variance in the college attainment phenotype.
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Affiliation(s)
- Elise L Anderson
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | | | - Emily A Willoughby
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
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41
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Jami ES, Hammerschlag AR, Bartels M, Middeldorp CM. Parental characteristics and offspring mental health and related outcomes: a systematic review of genetically informative literature. Transl Psychiatry 2021; 11:197. [PMID: 33795643 PMCID: PMC8016911 DOI: 10.1038/s41398-021-01300-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 02/19/2021] [Accepted: 03/03/2021] [Indexed: 12/18/2022] Open
Abstract
Various parental characteristics, including psychiatric disorders and parenting behaviours, are associated with offspring mental health and related outcomes in observational studies. The application of genetically informative designs is crucial to disentangle the role of genetic and environmental factors (as well as gene-environment correlation) underlying these observations, as parents provide not only the rearing environment but also transmit 50% of their genes to their offspring. This article first provides an overview of behavioural genetics, matched-pair, and molecular genetics designs that can be applied to investigate parent-offspring associations, whilst modelling or accounting for genetic effects. We then present a systematic literature review of genetically informative studies investigating associations between parental characteristics and offspring mental health and related outcomes, published since 2014. The reviewed studies provide reliable evidence of genetic transmission of depression, criminal behaviour, educational attainment, and substance use. These results highlight that studies that do not use genetically informative designs are likely to misinterpret the mechanisms underlying these parent-offspring associations. After accounting for genetic effects, several parental characteristics, including parental psychiatric traits and parenting behaviours, were associated with offspring internalising problems, externalising problems, educational attainment, substance use, and personality through environmental pathways. Overall, genetically informative designs to study intergenerational transmission prove valuable for the understanding of individual differences in offspring mental health and related outcomes, and mechanisms of transmission within families.
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Affiliation(s)
- Eshim S Jami
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
- Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK.
| | - Anke R Hammerschlag
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, the Netherlands
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health Research Institute, Amsterdam University Medical Centres, Amsterdam, the Netherlands
| | - Christel M Middeldorp
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
- Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia
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Xia C, Canela-Xandri O, Rawlik K, Tenesa A. Evidence of horizontal indirect genetic effects in humans. Nat Hum Behav 2021; 5:399-406. [PMID: 33318663 DOI: 10.1038/s41562-020-00991-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Accepted: 09/29/2020] [Indexed: 02/06/2023]
Abstract
Indirect genetic effects, the effects of the genotype of one individual on the phenotype of other individuals, are environmental factors associated with human disease and complex trait variation that could help to expand our understanding of the environment linked to complex traits. Here, we study indirect genetic effects in 80,889 human couples of European ancestry for 105 complex traits. Using a linear mixed model approach, we estimate partner indirect heritability and find evidence of partner heritability on ~50% of the analysed traits. Follow-up analysis suggests that in at least ~25% of these traits, the partner heritability is consistent with the existence of indirect genetic effects including a wide variety of traits such as dietary traits, mental health and disease. This shows that the environment linked to complex traits is partially explained by the genotype of other individuals and motivates the need to find new ways of studying the environment.
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Affiliation(s)
- Charley Xia
- The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Oriol Canela-Xandri
- The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
- MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Konrad Rawlik
- The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Albert Tenesa
- The Roslin Institute, The Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
- MRC IGMM, Western General Hospital, University of Edinburgh, Edinburgh, UK.
- Usher Institute, Edinburgh bioQuarter, University of Edinburgh, Edinburgh, UK.
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Verhoef E, Shapland CY, Fisher SE, Dale PS, St Pourcain B. The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition. PLoS Genet 2021; 17:e1009144. [PMID: 33577555 PMCID: PMC7880480 DOI: 10.1371/journal.pgen.1009144] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/22/2020] [Indexed: 11/18/2022] Open
Abstract
Individual differences in early-life vocabulary measures are heritable and associated with subsequent reading and cognitive abilities, although the underlying mechanisms are little understood. Here, we (i) investigate the developmental genetic architecture of expressive and receptive vocabulary in early-life and (ii) assess timing of emerging genetic associations with mid-childhood verbal and non-verbal skills. We studied longitudinally assessed early-life vocabulary measures (15–38 months) and later-life verbal and non-verbal skills (7–8 years) in up to 6,524 unrelated children from the population-based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We dissected the phenotypic variance of rank-transformed scores into genetic and residual components by fitting multivariate structural equation models to genome-wide genetic-relationship matrices. Our findings show that the genetic architecture of early-life vocabulary involves multiple distinct genetic factors. Two of these genetic factors are developmentally stable and also contribute to genetic variation in mid-childhood skills: One genetic factor emerging with expressive vocabulary at 24 months (path coefficient: 0.32(SE = 0.06)) was also related to later-life reading (path coefficient: 0.25(SE = 0.12)) and verbal intelligence (path coefficient: 0.42(SE = 0.13)), explaining up to 17.9% of the phenotypic variation. A second, independent genetic factor emerging with receptive vocabulary at 38 months (path coefficient: 0.15(SE = 0.07)), was more generally linked to verbal and non-verbal cognitive abilities in mid-childhood (reading path coefficient: 0.57(SE = 0.07); verbal intelligence path coefficient: 0.60(0.10); performance intelligence path coefficient: 0.50(SE = 0.08)), accounting for up to 36.1% of the phenotypic variation and the majority of genetic variance in these later-life traits (≥66.4%). Thus, the genetic foundations of mid-childhood reading and cognitive abilities are diverse. They involve at least two independent genetic factors that emerge at different developmental stages during early language development and may implicate differences in cognitive processes that are already detectable during toddlerhood. Differences in the number of words young children produce (expressive vocabulary) and understand (receptive vocabulary) can be partially explained by common genetic variation, and are related to reading and cognitive abilities later in life. Here, we studied genetic influences underlying expressive and receptive vocabulary during early development (15–38 months) and their genetic relationship with mid-childhood reading and cognitive skills (7–8 years), based on longitudinal phenotype measures and genome-wide genetic data from up to 6,524 unrelated children. We showed that early-life vocabulary skills are influenced by multiple independent genetic factors, of which two also relate to mid-childhood skills, suggesting developmental stability. One genetic factor emerging with expressive vocabulary at 24 months was linked to subsequent verbal abilities, including vocabulary measures at 38 months, as well as mid-childhood reading and verbal intelligence performance. A second, independent genetic factor related to receptive vocabulary at 38 months contributed more generally to variation in mid-childhood reading, verbal and non-verbal intelligence. Thus, the genetic foundations of mid-childhood reading and cognitive abilities involve at least two independent genetic factors that emerge during early-life language development and may implicate differences in overarching cognitive mechanisms.
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Affiliation(s)
- Ellen Verhoef
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- International Max Planck Research School for Language Sciences, Nijmegen, The Netherlands
- * E-mail: (EV); (BSTP)
| | - Chin Yang Shapland
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Simon E. Fisher
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Philip S. Dale
- Speech & Hearing Sciences, University of New Mexico, Albuquerque, New Mexico, United States of America
| | - Beate St Pourcain
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- * E-mail: (EV); (BSTP)
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Stern AJ, Speidel L, Zaitlen NA, Nielsen R. Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies. Am J Hum Genet 2021; 108:219-239. [PMID: 33440170 PMCID: PMC7895848 DOI: 10.1016/j.ajhg.2020.12.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 12/07/2020] [Indexed: 12/17/2022] Open
Abstract
We present a full-likelihood method to infer polygenic adaptation from DNA sequence variation and GWAS summary statistics to quantify recent transient directional selection acting on a complex trait. Through simulations of polygenic trait architecture evolution and GWASs, we show the method substantially improves power over current methods. We examine the robustness of the method under stratification, uncertainty and bias in marginal effects, uncertainty in the causal SNPs, allelic heterogeneity, negative selection, and low GWAS sample size. The method can quantify selection acting on correlated traits, controlling for pleiotropy even among traits with strong genetic correlation (|rg|=80%) while retaining high power to attribute selection to the causal trait. When the causal trait is excluded from analysis, selection is attributed to its closest proxy. We discuss limitations of the method, cautioning against strongly causal interpretations of the results, and the possibility of undetectable gene-by-environment (GxE) interactions. We apply the method to 56 human polygenic traits, revealing signals of directional selection on pigmentation, life history, glycated hemoglobin (HbA1c), and other traits. We also conduct joint testing of 137 pairs of genetically correlated traits, revealing widespread correlated response acting on these traits (2.6-fold enrichment, p = 1.5 × 10-7). Signs of selection on some traits previously reported as adaptive (e.g., educational attainment and hair color) are largely attributable to correlated response (p = 2.9 × 10-6 and 1.7 × 10-4, respectively). Lastly, our joint test shows antagonistic selection has increased type 2 diabetes risk and decrease HbA1c (p = 1.5 × 10-5).
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Affiliation(s)
- Aaron J Stern
- Graduate Group in Computational Biology, UC Berkeley, Berkeley, CA 94703, USA.
| | - Leo Speidel
- Department of Statistics, University of Oxford, Oxford, UK
| | - Noah A Zaitlen
- David Geffen School of Medicine, UC Los Angeles, Los Angeles, CA 90095, USA
| | - Rasmus Nielsen
- Department of Integrative Biology, UC Berkeley, Berkeley, CA 94703, USA; Department of Statistics, UC Berkeley, Berkeley, CA 94703, USA
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45
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Bird KA. No support for the hereditarian hypothesis of the Black-White achievement gap using polygenic scores and tests for divergent selection. AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2021; 175:465-476. [PMID: 33529393 DOI: 10.1002/ajpa.24216] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Revised: 11/27/2020] [Accepted: 12/20/2020] [Indexed: 12/19/2022]
Abstract
OBJECTIVES Debate about the cause of IQ score gaps between Black and White populations has persisted within genetics, anthropology, and psychology. Recently, authors claimed polygenic scores provide evidence that a significant portion of differences in cognitive performance between Black and White populations are caused by genetic differences due to natural selection, the "hereditarian hypothesis." This study aims to show conceptual and methodological flaws of past studies supporting the hereditarian hypothesis. MATERIALS AND METHODS Polygenic scores for educational attainment were constructed for African and European samples of the 1000 Genomes Project. Evidence for selection was evaluated using an excess variance test. Education associated variants were further evaluated for signals of selection by testing for excess genetic differentiation (Fst ). Expected mean difference in IQ for populations was calculated under a neutral evolutionary scenario and contrasted to hereditarian claims. RESULTS Tests for selection using polygenic scores failed to find evidence of natural selection when the less biased within-family GWAS effect sizes were used. Tests for selection using Fst values did not find evidence of natural selection. Expected mean difference in IQ was substantially smaller than postulated by hereditarians, even under unrealistic assumptions that overestimate genetic contribution. CONCLUSION Given these results, hereditarian claims are not supported in the least. Cognitive performance does not appear to have been under diversifying selection in Europeans and Africans. In the absence of diversifying selection, the best case estimate for genetic contributions to group differences in cognitive performance is substantially smaller than hereditarians claim and is consistent with genetic differences contributing little to the Black-White gap.
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Affiliation(s)
- Kevin A Bird
- Department of Horticulture, Michigan State University, East Lansing, Michigan, USA.,Ecology, Evolutionary Biology and Behavior Program, Michigan State University, East Lansing, Michigan, USA
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46
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Incorporating Polygenic Risk Scores in the ACE Twin Model to Estimate A-C Covariance. Behav Genet 2021; 51:237-249. [PMID: 33523349 PMCID: PMC8093156 DOI: 10.1007/s10519-020-10035-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 12/05/2020] [Indexed: 12/18/2022]
Abstract
The assumption in the twin model that genotypic and environmental variables are uncorrelated is primarily made to ensure parameter identification, not because researchers necessarily think that these variables are uncorrelated. Although the biasing effects of such correlations are well understood, a method to estimate these parameters in the twin model would be useful. Here we explore the possibility of relaxing this assumption by adding polygenic scores to the (univariate) twin model. We demonstrate that this extension renders the additive genetic (A)—common environmental (C) covariance (σAC) identified. We study the statistical power to reject σAC = 0 in the ACE model and present the results of simulations.
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47
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Abstract
Behavior genetics studies how genetic differences among people contribute to differences in their psychology and behavior. Here, I describe how the conclusions and methods of behavior genetics have evolved in the postgenomic era in which the human genome can be directly measured. First, I revisit the first law of behavioral genetics stating that everything is heritable, and I describe results from large-scale meta-analyses of twin data and new methods for estimating heritability using measured DNA. Second, I describe new methods in statistical genetics, including genome-wide association studies and polygenic score analyses. Third, I describe the next generation of work on gene × environment interaction, with a particular focus on how genetic influences vary across sociopolitical contexts and exogenous environments. Genomic technology has ushered in a golden age of new tools to address enduring questions about how genes and environments combine to create unique human lives.
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Affiliation(s)
- K Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, Texas 78712, USA;
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48
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Hunjan AK, Cheesman R, Coleman JRI, Hübel C, Eley TC, Breen G. No Evidence for Passive Gene-Environment Correlation or the Influence of Genetic Risk for Psychiatric Disorders on Adult Body Composition via the Adoption Design. Behav Genet 2021; 51:58-67. [PMID: 33141367 PMCID: PMC7815612 DOI: 10.1007/s10519-020-10028-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 10/19/2020] [Indexed: 01/22/2023]
Abstract
The relationship between genetic and environmental risk is complex and for many traits, estimates of genetic effects may be inflated by passive gene-environment correlation. This arises because biological offspring inherit both their genotypes and rearing environment from their parents. We tested for passive gene-environment correlation in adult body composition traits using the 'natural experiment' of childhood adoption, which removes passive gene-environment correlation within families. Specifically, we compared 6165 adoptees with propensity score matched non-adoptees in the UK Biobank. We also tested whether passive gene-environment correlation inflates the association between psychiatric genetic risk and body composition. We found no evidence for inflation of heritability or polygenic scores in non-adoptees compared to adoptees for a range of body composition traits. Furthermore, polygenic risk scores for anorexia nervosa, attention-deficit/hyperactivity disorder and schizophrenia did not differ in their influence on body composition traits in adoptees and non-adoptees. These findings suggest that passive gene-environment correlation does not inflate genetic effects for body composition, or the influence of psychiatric disorder genetic risk on body composition. Our design does not look at passive gene-environment correlation in childhood, and does not test for 'pure' environmental effects or the effects of active and evocative gene-environment correlations, where child genetics directly influences home environment. However, these findings suggest that genetic influences identified for body composition in this adult sample are direct, and not confounded by the family environment provided by biological relatives.
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Affiliation(s)
- Avina K Hunjan
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Rosa Cheesman
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Jonathan R I Coleman
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Christopher Hübel
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
| | - Thalia C Eley
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Gerome Breen
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK.
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49
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Allegrini AG, Karhunen V, Coleman JRI, Selzam S, Rimfeld K, von Stumm S, Pingault JB, Plomin R. Multivariable G-E interplay in the prediction of educational achievement. PLoS Genet 2020; 16:e1009153. [PMID: 33201880 PMCID: PMC7721131 DOI: 10.1371/journal.pgen.1009153] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 12/07/2020] [Accepted: 09/15/2020] [Indexed: 12/21/2022] Open
Abstract
Polygenic scores are increasingly powerful predictors of educational achievement. It is unclear, however, how sets of polygenic scores, which partly capture environmental effects, perform jointly with sets of environmental measures, which are themselves heritable, in prediction models of educational achievement. Here, for the first time, we systematically investigate gene-environment correlation (rGE) and interaction (GxE) in the joint analysis of multiple genome-wide polygenic scores (GPS) and multiple environmental measures as they predict tested educational achievement (EA). We predict EA in a representative sample of 7,026 16-year-olds, with 20 GPS for psychiatric, cognitive and anthropometric traits, and 13 environments (including life events, home environment, and SES) measured earlier in life. Environmental and GPS predictors were modelled, separately and jointly, in penalized regression models with out-of-sample comparisons of prediction accuracy, considering the implications that their interplay had on model performance. Jointly modelling multiple GPS and environmental factors significantly improved prediction of EA, with cognitive-related GPS adding unique independent information beyond SES, home environment and life events. We found evidence for rGE underlying variation in EA (rGE = .38; 95% CIs = .30, .45). We estimated that 40% (95% CIs = 31%, 50%) of the polygenic scores effects on EA were mediated by environmental effects, and in turn that 18% (95% CIs = 12%, 25%) of environmental effects were accounted for by the polygenic model, indicating genetic confounding. Lastly, we did not find evidence that GxE effects significantly contributed to multivariable prediction. Our multivariable polygenic and environmental prediction model suggests widespread rGE and unsystematic GxE contributions to EA in adolescence. Our study investigates the complex interplay between genetic and environmental contributions underlying educational achievement (EA). Polygenic scores are becoming increasingly powerful predictors of EA. While emerging evidence indicates that polygenic scores are not pure measures of genetic predisposition, previous quantitative genetics findings indicate that measures of the environment are themselves heritable. In this regard it is unclear how such measures of individual predisposition jointly combine to predict EA. We investigate this question in a representative UK sample of 7,026 16-year-olds where we provide substantive results on gene-environment correlation and interaction underlying variation in EA. We show that polygenic score and environmental prediction models of EA overlap substantially. Polygenic scores effects on EA are partly accounted for by their correlation with environmental effects; similarly, environmental effects on EA are linked to polygenic scores effects. Nonetheless, jointly considering polygenic scores and measured environments significantly improves prediction of EA. We also find that, although correlation between polygenic scores and measured environments is substantial, interactions between them do not play a significant role in the prediction of EA. Our findings have relevance for genomic and environmental prediction models alike, as they show the way in which individuals’ genetic predispositions and environmental effects are intertwined. This suggests that both genetic and environmental effects must be taken into account in prediction models of complex behavioral traits such as EA.
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Affiliation(s)
- Andrea G. Allegrini
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
- * E-mail:
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, United Kingdom
| | - Jonathan R. I. Coleman
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
- NIHR Maudsley Biomedical Research Centre, King's College London, United Kingdom
| | - Saskia Selzam
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
| | - Kaili Rimfeld
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
| | | | - Jean-Baptiste Pingault
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
- Division of Psychology and Language Sciences, University College London, United Kingdom
| | - Robert Plomin
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, United Kingdom
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50
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LeWinn KZ, Bush NR, Batra A, Tylavsky F, Rehkopf D. Identification of Modifiable Social and Behavioral Factors Associated With Childhood Cognitive Performance. JAMA Pediatr 2020; 174:1063-1072. [PMID: 32955555 PMCID: PMC7506587 DOI: 10.1001/jamapediatrics.2020.2904] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
IMPORTANCE Inequities in social environments are likely associated with a large portion of racial disparities in childhood cognitive performance. Identification of the specific exposures associated with cognitive development is needed to inform prevention efforts. OBJECTIVE To identify modifiable factors associated with childhood cognitive performance. DESIGN, SETTING, AND PARTICIPANTS This longitudinal pregnancy cohort study included 1503 mother-child dyads who were enrolled in the University of Tennessee Health Science Center-Conditions Affecting Neurodevelopment and Learning in Early Life study between December 1, 2006, and July 31, 2011, and assessed annually until the children were aged 4 to 6 years. The analytic sample comprised 1055 mother-child dyads. A total of 155 prenatal, perinatal, and postnatal exposures were included to evaluate environment-wide associations. Participants comprised a community-based sample of pregnant women who were recruited between 16 weeks and 28 weeks of gestation from 4 hospitals in Shelby County, Tennessee. Women with high-risk pregnancies were excluded. Data were analyzed from June 1, 2018, to April 15, 2019. EXPOSURES Individual and neighborhood socioeconomic position, family structure, maternal mental health, nutrition, delivery complications, birth outcomes, and parenting behaviors. MAIN OUTCOMES AND MEASURES Child's full-scale IQ measured by the Stanford-Binet Intelligence Scales, Fifth Edition, at age 4 to 6 years. RESULTS Of 1055 children included in the analytic sample, 532 (50.4%) were female. Among mothers, the mean (SD) age was 26.0 (5.6) years; 676 mothers (64.1%) were Black, and 623 mothers (59.0%) had an educational level of high school or less. Twenty-four factors were retained in the least absolute shrinkage and selection operator regression analysis and full models adjusted for potential confounding. Associations were noted between child cognitive performance and parental education and breastfeeding; for each increase of 1.0 SD in exposure, positive associations were found with cognitive growth fostering from observed parent-child interactions (β = 1.12; 95% CI, 0.24-2.00) and maternal reading ability (β = 1.42; 95% CI, 0.16-2.68), and negative associations were found with parenting stress (β = -1.04; 95% CI, -1.86 to -0.21). A moderate increase in these beneficial exposures was associated with a notable improvement in estimated cognitive test scores using marginal means (0.5% of an SD). Black children experienced fewer beneficial cognitive performance exposures; in a model including all 24 exposures and covariates, no racial disparity was observed in cognitive performance (95% CIs for race included the null). CONCLUSIONS AND RELEVANCE The prospective analysis identified multiple beneficial and modifiable cognitive performance exposures that were associated with mean differences in cognitive performance by race. The findings from this observational study may help guide experimental studies focused on reducing racial disparities in childhood cognitive performance.
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Affiliation(s)
- Kaja Z. LeWinn
- Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco
| | - Nicole R. Bush
- Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco,Department of Pediatrics, Division of Developmental Medicine, University of California, San Francisco, San Francisco
| | - Akansha Batra
- University of California, San Francisco, San Francisco
| | - Frances Tylavsky
- Preventive Medicine, University of Tennessee Health Science Center, Memphis
| | - David Rehkopf
- Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, California
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