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Morris TT, von Hinke S, Pike L, Ingram NR, Davey Smith G, Munafò MR, Davies NM. Implications of the genomic revolution for education research and policy. BRITISH EDUCATIONAL RESEARCH JOURNAL 2024; 50:923-943. [PMID: 38974368 PMCID: PMC11225938 DOI: 10.1002/berj.3784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 03/04/2022] [Indexed: 07/09/2024]
Abstract
Research at the intersection of social science and genomics, 'sociogenomics', is transforming our understanding of the interplay between genomics, individual outcomes and society. It has interesting and maybe unexpected implications for education research and policy. Here we review the growing sociogenomics literature and discuss its implications for educational researchers and policymakers. We cover key concepts and methods in genomic research into educational outcomes, how genomic data can be used to investigate social or environmental effects, the methodological strengths and limitations of genomic data relative to other observational social data, the role of intergenerational transmission and potential policy implications. The increasing availability of genomic data in studies can produce a wealth of new evidence for education research. This may provide opportunities for disentangling the environmental and genomic factors that influence educational outcomes and identifying potential mechanisms for intervention.
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Affiliation(s)
- Tim T. Morris
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health SciencesBristol Medical SchoolUniversity of BristolOakfield GroveBarley HouseBristolUK
| | - Stephanie von Hinke
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- School of EconomicsUniversity of BristolUK
- Erasmus School of EconomicsErasmus University RotterdamRotterdamThe Netherlands
| | - Lindsey Pike
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health SciencesBristol Medical SchoolUniversity of BristolOakfield GroveBarley HouseBristolUK
| | | | - George Davey Smith
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health SciencesBristol Medical SchoolUniversity of BristolOakfield GroveBarley HouseBristolUK
| | - Marcus R. Munafò
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- School of Psychological ScienceUniversity of BristolBristolUK
| | - Neil M. Davies
- Medical Research Council Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health SciencesBristol Medical SchoolUniversity of BristolOakfield GroveBarley HouseBristolUK
- K.G. Jebsen Center for Genetic EpidemiologyDepartment of Public Health and NursingNorwegian University of Science and TechnologyTrondheimNorway
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2
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Golding MC. Teratogenesis and the epigenetic programming of congenital defects: Why paternal exposures matter. Birth Defects Res 2023; 115:1825-1834. [PMID: 37424262 PMCID: PMC10774456 DOI: 10.1002/bdr2.2215] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 06/16/2023] [Accepted: 06/23/2023] [Indexed: 07/11/2023]
Abstract
Until recently, clinicians and researchers did not realize paternal exposures could impact child developmental outcomes. Indeed, although there is growing recognition that sperm carry a large amount of non-genomic information and that paternal stressors influence the health of the next generation, toxicologists are only now beginning to explore the role paternal exposures have in dysgenesis and the incidence of congenital malformations. In this commentary, I will briefly summarize the few studies describing congenital malformations resulting from preconception paternal stressors, argue for the theoretical expansion of teratogenic perspectives into the male preconception period, and discuss some of the challenges in this newly emerging branch of toxicology. I argue that we must consider gametes the same as any other malleable precursor cell type and recognize that environmentally-induced epigenetic changes acquired during the formation of the sperm and oocyte hold equal teratogenic potential as exposures during early development. Here, I propose the term epiteratogen to reference agents acting outside of pregnancy that, through epigenetic mechanisms, induce congenital malformations. Understanding the interactions between the environment, the essential epigenetic processes intrinsic to spermatogenesis, and their cumulative influences on embryo patterning is essential to addressing a significant blind spot in the field of developmental toxicology.
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Affiliation(s)
- Michael C. Golding
- Department of Veterinary Physiology & Pharmacology, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, Texas, USA, 77843
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3
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Zoh RS, Yu X, Dawid P, Smith GD, French SJ, Allison DB. Causal models and causal modelling in obesity: foundations, methods and evidence. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220227. [PMID: 37661742 PMCID: PMC10475873 DOI: 10.1098/rstb.2022.0227] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 08/06/2023] [Indexed: 09/05/2023] Open
Abstract
Discussing causes in science, if we are to do so in a way that is sensible, begins at the root. All too often, we jump to discussing specific postulated causes but do not first consider what we mean by, for example, causes of obesity or how we discern whether something is a cause. In this paper, we address what we mean by a cause, discuss what might and might not constitute a reasonable causal model in the abstract, speculate about what the causal structure of obesity might be like overall and the types of things we should be looking for, and finally, delve into methods for evaluating postulated causes and estimating causal effects. We offer the view that different meanings of the concept of causal factors in obesity research are regularly being conflated, leading to confusion, unclear thinking and sometimes nonsense. We emphasize the idea of different kinds of studies for evaluating various aspects of causal effects and discuss experimental methods, assumptions and evaluations. We use analogies from other areas of research to express the plausibility that only inelegant solutions will be truly informative. Finally, we offer comments on some specific postulated causal factors. This article is part of a discussion meeting issue 'Causes of obesity: theories, conjectures and evidence (Part II)'.
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Affiliation(s)
- Roger S. Zoh
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, 47405-7000, USA
| | - Xiaoxin Yu
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, 47405-7000, USA
| | | | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Stephen J. French
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, 47405-7000, USA
| | - David B. Allison
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, IN, 47405-7000, USA
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4
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Pingault JB, Barkhuizen W, Wang B, Hannigan LJ, Eilertsen EM, Corfield E, Andreassen OA, Ask H, Tesli M, Askeland RB, Davey Smith G, Stoltenberg C, Davies NM, Reichborn-Kjennerud T, Ystrom E, Havdahl A. Genetic nurture versus genetic transmission of risk for ADHD traits in the Norwegian Mother, Father and Child Cohort Study. Mol Psychiatry 2023; 28:1731-1738. [PMID: 36385167 PMCID: PMC10208953 DOI: 10.1038/s41380-022-01863-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 10/26/2022] [Accepted: 10/28/2022] [Indexed: 11/17/2022]
Abstract
Identifying mechanisms underlying the intergenerational transmission of risk for attention-deficit/hyperactivity disorder (ADHD) traits can inform interventions and provide insights into the role of parents in shaping their children's outcomes. We investigated whether genetic transmission and genetic nurture (environmentally mediated effects) underlie associations between polygenic scores indexing parental risk and protective factors and their offspring's ADHD traits. This birth cohort study included 19,506 genotyped mother-father-offspring trios from the Norwegian Mother, Father and Child Cohort Study. Polygenic scores were calculated for parental factors previously associated with ADHD, including psychopathology, substance use, neuroticism, educational attainment, and cognitive performance. Mothers reported on their 8-year-old children's ADHD traits (n = 9,454 children) using the Parent/Teacher Rating Scale for Disruptive Behaviour Disorders. We found that associations between ADHD maternal and paternal polygenic scores and child ADHD traits decreased significantly when adjusting for the child polygenic score (pΔβ = 9.95 × 10-17 for maternal and pΔβ = 1.48 × 10-14 for paternal estimates), suggesting genetic transmission of ADHD risk. Similar patterns suggesting genetic transmission of risk were observed for smoking, educational attainment, and cognition. The maternal polygenic score for neuroticism remained associated with children's ADHD ratings even after adjusting for the child polygenic score, indicating genetic nurture. There was no robust evidence of genetic nurture for other parental factors. Our findings indicate that the intergenerational transmission of risk for ADHD traits is largely explained by the transmission of genetic variants from parents to offspring rather than by genetic nurture. Observational associations between parental factors and childhood ADHD outcomes should not be interpreted as evidence for predominantly environmentally mediated effects.
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Affiliation(s)
- Jean-Baptiste Pingault
- Division of Psychology and Language Sciences, University College London, London, United Kingdom
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College, London, United Kingdom
| | - Wikus Barkhuizen
- Division of Psychology and Language Sciences, University College London, London, United Kingdom.
| | - Biyao Wang
- Division of Psychology and Language Sciences, University College London, London, United Kingdom
| | - Laurie J Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - 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
| | - Elizabeth Corfield
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Martin Tesli
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ragna Bugge Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Camilla Stoltenberg
- Norwegian Institute of Public Health, Oslo, Norway
- University of Bergen, Bergen, Norway
| | - Neil M Davies
- MRC Integrative Epidemiology Unit (IEU), 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
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Eivind Ystrom
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
- School of Pharmacy, University of Oslo, Oslo, Norway
| | - Alexandra Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
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5
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Nigg JT. Considerations toward an epigenetic and common pathways theory of mental disorder. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2023; 132:297-313. [PMID: 37126061 PMCID: PMC10153068 DOI: 10.1037/abn0000748] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Psychopathology emerges from the dynamic interplay of physiological and mental processes and ecological context. It can be seen as a failure of recursive, homeostatic processes to achieve adaptive re-equilibrium. This general statement can be actualized with consideration of polygenic liability, early exposures, and multiunit (multi-"level") analysis of the psychological action and the associated physiological and neural operations, all in the context of the developmental exposome. This article begins by identifying key principles and clarifying key terms necessary to mental disorder theory. It then ventures a sketch of a model that highlights epigenetic dynamics and proposes a common pathways hypothesis toward psychopathology. An epigenetic perspective elevates the importance of developmental context and adaptive systems, particularly in early life, while opening the door to new mechanistic discovery. The key proposal is that a finite number of homeostatic biological and psychological mechanisms are shared across most risky environments (and possibly many genetic liabilities) for psychopathology. Perturbation of these mediating mechanisms leads to development of psychopathology. A focus on dynamic changes in these homeostatic mechanisms across multiple units of analysis and time points can render the problem of explaining psychopathology tractable. Key questions include the mapping of recursive processes over time, at adequate density, as mental disorders unfold across development. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University
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6
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Hatoum AS, Colbert SM, Johnson EC, Huggett SB, Deak JD, Pathak G, Jennings MV, Paul SE, Karcher NR, Hansen I, Baranger DA, Edwards A, Grotzinger A, Tucker-Drob EM, Kranzler HR, Davis LK, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg HJ, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. NATURE. MENTAL HEALTH 2023; 1:210-223. [PMID: 37250466 PMCID: PMC10217792 DOI: 10.1038/s44220-023-00034-y] [Citation(s) in RCA: 56] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 02/10/2023] [Indexed: 05/31/2023]
Abstract
Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.
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Affiliation(s)
- Alexander S. Hatoum
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
| | - Sarah M.C. Colbert
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
| | - Emma C. Johnson
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
| | | | - Joseph D. Deak
- Department of Psychiatry, Division of Human Genetics, Yale
School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven,
CT, USA
| | - Gita Pathak
- Department of Psychiatry, Division of Human Genetics, Yale
School of Medicine, New Haven, CT, USA
| | - Mariela V. Jennings
- UC San Diego School of Medicine, Department of Psychiatry,
San Diego, CA, USA
| | - Sarah E. Paul
- Department of Psychological & Brain Sciences,
Washington University in St. Louis
| | - Nicole R. Karcher
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
| | - Isabella Hansen
- Department of Psychological & Brain Sciences,
Washington University in St. Louis
| | - David A.A. Baranger
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
| | - Alexis Edwards
- Virginia Institute of Psychiatric and Behavioral Genetics,
Virginia Commonwealth University, Richmond, VA, USA
| | - Andrew Grotzinger
- University of Colorado-Boulder, Institute for Behavioral
Genetics, Boulder, CO, USA
| | | | - Elliot M. Tucker-Drob
- University of Texas at Austin, Department of Psychology and
Population Research Center, Austin, TX, USA
| | - Henry R. Kranzler
- Center for Studies of Addiction, Department of
Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia,
PA, USA
- VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
| | - Lea K. Davis
- Department of Medicine, Division of Genetic Medicine,
Vanderbilt University, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences,
Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt
University Medical Center, Nashville, TN, USA
| | - Sandra Sanchez-Roige
- UC San Diego School of Medicine, Department of Psychiatry,
San Diego, CA, USA
- Department of Medicine, Division of Genetic Medicine,
Vanderbilt University, Nashville, TN, USA
| | - Renato Polimanti
- Department of Psychiatry, Division of Human Genetics, Yale
School of Medicine, New Haven, CT, USA
- Veterans Affairs Connecticut Healthcare System, West Haven,
CT, USA
| | - Joel Gelernter
- Department of Psychiatry, Division of Human Genetics, Yale
School of Medicine, New Haven, CT, USA
- University of Texas at Austin, Department of Psychology and
Population Research Center, Austin, TX, USA
- Department of Genetics, Yale School of Medicine, New
Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New
Haven, CT, USA
| | - Howard J. Edenberg
- Department of Medical and Molecular Genetics, Indiana
University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, Indiana
University School of Medicine, Indianapolis, IN, USA
| | - Ryan Bogdan
- Department of Psychological & Brain Sciences,
Washington University in St. Louis
| | - Arpana Agrawal
- Washington University School of Medicine, Department of
Psychiatry, Saint Louis, USA
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7
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Martin J, Wray M, Agha SS, Lewis KJS, Anney RJL, O'Donovan MC, Thapar A, Langley K. Investigating Direct and Indirect Genetic Effects in Attention-Deficit/Hyperactivity Disorder Using Parent-Offspring Trios. Biol Psychiatry 2023; 93:37-44. [PMID: 35933166 PMCID: PMC10369485 DOI: 10.1016/j.biopsych.2022.06.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/06/2022] [Accepted: 06/06/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is highly heritable, but little is known about the relative effects of transmitted (i.e., direct) and nontransmitted (i.e., indirect) common variant risks. Using parent-offspring trios, we tested whether polygenic liability for neurodevelopmental and psychiatric disorders and lower cognitive ability is overtransmitted to ADHD probands. We also tested for indirect or genetic nurture effects by examining whether nontransmitted ADHD polygenic liability is elevated. Finally, we examined whether complete trios are representative of the clinical ADHD population. METHODS Polygenic risk scores (PRSs) for ADHD, anxiety, autism, bipolar disorder, depression, obsessive-compulsive disorder, schizophrenia, Tourette syndrome, and cognitive ability were calculated in UK control subjects (n = 5081), UK probands with ADHD (n = 857), their biological parents (n = 328 trios), and also a replication sample of 844 ADHD trios. RESULTS ADHD PRSs were overtransmitted and cognitive ability and obsessive-compulsive disorder PRSs were undertransmitted. These results were independently replicated. Overtransmission of polygenic liability was not observed for other disorders. Nontransmitted alleles were not enriched for ADHD liability compared with control subjects. Probands from incomplete trios had more hyperactive-impulsive and conduct disorder symptoms, lower IQ, and lower socioeconomic status than complete trios. PRS did not vary by trio status. CONCLUSIONS The results support direct transmission of polygenic liability for ADHD and cognitive ability from parents to offspring, but not for other neurodevelopmental/psychiatric disorders. They also suggest that nontransmitted neurodevelopmental/psychiatric parental alleles do not contribute indirectly to ADHD via genetic nurture. Furthermore, ascertainment of complete ADHD trios may be nonrandom, in terms of demographic and clinical factors.
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Affiliation(s)
- Joanna Martin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom; Wolfson Centre for Young People's Mental Health, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom.
| | - Matthew Wray
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Sharifah Shameem Agha
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom; Cwm Taf Morgannwg University Health Board, Wales, United Kingdom
| | - Katie J S Lewis
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Richard J L Anney
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Anita Thapar
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom; Wolfson Centre for Young People's Mental Health, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom
| | - Kate Langley
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom; School of Psychology, Cardiff University, Cardiff, United Kingdom
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8
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Sellers R, Riglin L, Harold GT, Thapar A. Using genetic designs to identify likely causal environmental contributions to psychopathology. Dev Psychopathol 2022; 34:1-13. [PMID: 36200346 DOI: 10.1017/s0954579422000906] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The multifactorial nature of psychopathology, whereby both genetic and environmental factors contribute risk, has long been established. In this paper, we provide an update on genetically informative designs that are utilized to disentangle genetic and environmental contributions to psychopathology. We provide a brief reminder of quantitative behavioral genetic research designs that have been used to identify potentially causal environmental processes, accounting for genetic contributions. We also provide an overview of recent molecular genetic approaches that utilize genome-wide association study data which are increasingly being applied to questions relevant to psychopathology research. While genetically informative designs typically have been applied to investigate the origins of psychopathology, we highlight how these approaches can also be used to elucidate potential causal environmental processes that contribute to developmental course and outcomes. We highlight the need to use genetically sensitive designs that align with intervention and prevention science efforts, by considering strengths-based environments to investigate how positive environments can mitigate risk and promote children's strengths.
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Affiliation(s)
- Ruth Sellers
- Brighton & Sussex Medical School, University of Sussex, Brighton, UK
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
| | - Gordon T Harold
- Faculty of Education, University of Cambridge, Cambridge, UK
- School of Medicine, Child and Adolescent Psychiatry Unit, University College Dublin, Dublin, Ireland
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Wolfson Centre for Young People's Mental Health, Cardiff University, Cardiff, UK
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9
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Pingault J, Allegrini AG, Odigie T, Frach L, Baldwin JR, Rijsdijk F, Dudbridge F. Research Review: How to interpret associations between polygenic scores, environmental risks, and phenotypes. J Child Psychol Psychiatry 2022; 63:1125-1139. [PMID: 35347715 PMCID: PMC9790749 DOI: 10.1111/jcpp.13607] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/23/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND Genetic influences are ubiquitous as virtually all phenotypes and most exposures typically classified as environmental have been found to be heritable. A polygenic score summarises the associations between millions of genetic variants and an outcome in a single value for each individual. Ever lowering costs have enabled the genotyping of many samples relevant to child psychology and psychiatry research, including cohort studies, leading to the proliferation of polygenic score studies. It is tempting to assume that associations detected between polygenic scores and phenotypes in those studies only reflect genetic effects. However, such associations can reflect many pathways (e.g. via environmental mediation) and biases. METHODS Here, we provide a comprehensive overview of the many reasons why associations between polygenic scores, environmental exposures, and phenotypes exist. We include formal representations of common analyses in polygenic score studies using structural equation modelling. We derive biases, provide illustrative empirical examples and, when possible, mention steps that can be taken to alleviate those biases. RESULTS Structural equation models and derivations show the many complexities arising from jointly modelling polygenic scores with environmental exposures and phenotypes. Counter-intuitive examples include that: (a) associations between polygenic scores and phenotypes may exist even in the absence of direct genetic effects; (b) associations between child polygenic scores and environmental exposures can exist in the absence of evocative/active gene-environment correlations; and (c) adjusting an exposure-outcome association for a polygenic score can increase rather than decrease bias. CONCLUSIONS Strikingly, using polygenic scores may, in some cases, lead to more bias than not using them. Appropriately conducting and interpreting polygenic score studies thus requires researchers in child psychology and psychiatry and beyond to be versed in both epidemiological and genetic methods or build on interdisciplinary collaborations.
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Affiliation(s)
- Jean‐Baptiste Pingault
- Division of Psychology and Language SciencesDepartment of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Andrea G. Allegrini
- Division of Psychology and Language SciencesDepartment of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Tracy Odigie
- Division of Psychology and Language SciencesDepartment of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Leonard Frach
- Division of Psychology and Language SciencesDepartment of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Jessie R. Baldwin
- Division of Psychology and Language SciencesDepartment of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Frühling Rijsdijk
- Faculty of Social SciencesAnton de Kom University of SurinameParamariboSuriname
| | - Frank Dudbridge
- Department of Health SciencesUniversity of LeicesterLeicesterUK
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10
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Havdahl A, Wootton RE, Leppert B, Riglin L, Ask H, Tesli M, Bugge Askeland R, Hannigan LJ, Corfield E, Øyen AS, Andreassen OA, Tilling K, Davey Smith G, Thapar A, Reichborn-Kjennerud T, Stergiakouli E. Associations Between Pregnancy-Related Predisposing Factors for Offspring Neurodevelopmental Conditions and Parental Genetic Liability to Attention-Deficit/Hyperactivity Disorder, Autism, and Schizophrenia: The Norwegian Mother, Father and Child Cohort Study (MoBa). JAMA Psychiatry 2022; 79:799-810. [PMID: 35793100 PMCID: PMC9260642 DOI: 10.1001/jamapsychiatry.2022.1728] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/10/2022] [Indexed: 02/02/2023]
Abstract
Importance Several maternal exposures during pregnancy are considered predisposing factors for offspring neurodevelopmental conditions. However, many of these exposures may be noncausal and biased by maternal genetic liability. Objective To assess whether pregnancy-related predisposing factors for offspring neurodevelopmental conditions are associated with maternal genetic liability for attention-deficit/hyperactivity disorder (ADHD), autism, and schizophrenia and to compare associations for maternal genetic liability with those for paternal genetic liability, which could indicate that paternal exposures are not suitable negative controls for maternal exposures. Design, Setting, and Participants The Norwegian Mother, Father and Child Cohort Study (MoBa) is a population-based pregnancy cohort that recruited parents from June 1999 to December 2008. Polygenic scores (PGS) for ADHD, autism, and schizophrenia were derived in mothers and fathers. The associations between maternal PGS and 37 pregnancy-related measures were estimated, and these results were compared with those from paternal PGS predicting paternal measures during the mother's pregnancy. Analysis took place between March 2021 and March 2022. Exposures PGS for ADHD, autism, and schizophrenia, calculated (using discovery effect size estimates and threshold of P < .05) from the largest available genome-wide association studies. Main Outcomes and Measures Self-reported pregnancy-related measures capturing lifestyle behaviors, metabolism, infectious and autoimmune diseases, other physical health conditions, and medication use. Results Data were available for up to 14 539 mothers (mean [SD] age, 30.00 [4.45] years) and 14 897 fathers (mean [SD] age, 32.46 [5.13] years) of European ancestry. Modest but robust associations were observed between specific pregnancy-related measures and maternal PGS, including ADHD PGS with asthma (odds ratio [OR], 1.15 [95% CI, 1.06-1.25]), smoking (OR, 1.26 [95% CI, 1.19-1.33]), prepregnancy body mass index (β, 0.25 [95% CI, 0.18-0.31]), pregnancy weight gain (β, 0.20 [95% CI, 0.10-0.30]), taking folate (OR, 0.92 [95% CI, 0.88-0.96]), and not taking supplements (OR, 1.09 [95% CI, 1.04-1.14]). Schizophrenia PGS was associated with coffee consumption (OR, 1.09 [95% CI, 1.05-1.12]), smoking (OR, 1.12 [95% CI, 1.06-1.19]), prepregnancy body mass index (β, -0.18 [95% CI, -0.25 to -0.11]), and pregnancy weight gain (β, 0.17 [95% CI, 0.07-0.27]). All 3 PGSs associated with symptoms of depression/anxiety (ADHD: OR, 1.15 [95% CI, 1.09-1.22]; autism: OR, 1.13 [95% CI, 1.06-1.19]; schizophrenia: OR, 1.13 [95% CI, 1.07-1.20]). Associations were largely consistent for maternal and paternal PGS, except ADHD PGS and smoking (fathers: OR, 1.13 [95% CI, 1.09-1.17]). Conclusions and Relevance In this study, genetic liability to neurodevelopmental conditions that is passed from mothers to children was associated with several pregnancy-related factors and may therefore confound associations between these pregnancy-related factors and offspring neurodevelopment that have previously been thought to be causal. It is crucial that future study designs account for genetic confounding to obtain valid causal inferences so that accurate advice can be given to pregnant individuals.
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Affiliation(s)
- Alexandra Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Robyn E. Wootton
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Beate Leppert
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Wolfson Centre for Young People’s Mental Health, Cardiff University, Cardiff, United Kingdom
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Martin Tesli
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ragna Bugge Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Laurie J. Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Elizabeth Corfield
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne-Siri Øyen
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kate Tilling
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Wolfson Centre for Young People’s Mental Health, Cardiff University, Cardiff, United Kingdom
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Evie Stergiakouli
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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11
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Michaëlsson M, Yuan S, Melhus H, Baron JA, Byberg L, Larsson SC, Michaëlsson K. The impact and causal directions for the associations between diagnosis of ADHD, socioeconomic status, and intelligence by use of a bi-directional two-sample Mendelian randomization design. BMC Med 2022; 20:106. [PMID: 35399077 PMCID: PMC8996513 DOI: 10.1186/s12916-022-02314-3] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 02/21/2022] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Previous studies have reported associations between attention-deficit/hyperactivity disorder (ADHD) and lower socioeconomic status and intelligence. We aimed to evaluate the causal directions and strengths for these associations by use of a bi-directional two-sample Mendelian randomization (MR) design. METHODS We used summary-level data from the largest available genome-wide association studies (GWAS) to identify genetic instruments for ADHD, intelligence, and markers of socioeconomic status including the Townsend deprivation index, household income, and educational attainment. Effect estimates from individual genetic variants were combined using inverse-variance weighted regression. RESULTS A genetically predicted one standard deviation (SD) increment in the Townsend deprivation index conferred an odds ratio (OR) of 5.29 (95% confidence interval (CI) 1.89-14.76) for an ADHD diagnosis (p<0.001). A genetically predicted one SD higher education level conferred an OR of 0.30 (95% CI 0.25-0.37) (p<0.001), and a genetically predicted one SD higher family income provided an OR of 0.35 (95% CI 0.25-0.49; p<0.001). The associations remained after adjustment for intelligence whereas the lower odds of an ADHD diagnosis with higher intelligence did not persist after adjustment for liability to greater educational attainment (adjusted OR 1.03, 95% CI 0.68-1.56; p=0.87). The MR analysis of the effect of ADHD on socioeconomic markers found that genetic liability to ADHD was statistically associated with each of them (p<0.001) but not intelligence. However, the average change in the socioeconomic markers per doubling of the prevalence of ADHD corresponded only to 0.05-0.06 SD changes. CONCLUSIONS Our results indicate that an ADHD diagnosis may be a direct and strong intelligence-independent consequence of socioeconomic related factors, whereas ADHD appears to lead only to modestly lowered socioeconomic status. Low intelligence seems not to be a major independent cause or consequence of ADHD.
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Affiliation(s)
| | - Shuai Yuan
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Håkan Melhus
- Department of Medical Sciences, Clinical Pharmacology, Uppsala University, Uppsala, Sweden
| | - John A Baron
- Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.,Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.,Department of Surgical Sciences, Unit of Medical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Liisa Byberg
- Department of Surgical Sciences, Unit of Medical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Susanna C Larsson
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Surgical Sciences, Unit of Medical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Karl Michaëlsson
- Department of Surgical Sciences, Unit of Medical Epidemiology, Uppsala University, Uppsala, Sweden.
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12
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Pingault JB, Richmond R, Davey Smith G. Causal Inference with Genetic Data: Past, Present, and Future. Cold Spring Harb Perspect Med 2022; 12:a041271. [PMID: 34580080 PMCID: PMC8886738 DOI: 10.1101/cshperspect.a041271] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
The set of methods discussed in this collection has emerged from the convergence of two scientific fields-genetics and causal inference. In this introduction, we discuss relevant aspects of each field and show how their convergence arises from the natural experiments that genetics offer. We present introductory concepts useful to readers unfamiliar with genetically informed methods for causal inference. We conclude that existing applications and foreseeable developments should ensure that we rapidly reap the rewards of this relatively new field, not only in terms of our understanding of human disease and development, but also in terms of tangible translational applications.
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Affiliation(s)
- Jean-Baptiste Pingault
- Division of Psychology and Language Sciences, University College London, London WC1H 0AP United Kingdom
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1TH, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1TH, United Kingdom
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13
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Abstract
In the last 40 years, there has been a huge increase in autism genetics research and a rapidly growing number of discoveries. We now know autism is one of the most highly heritable disorders with negligible shared environmental contributions. Recent discoveries also show that rare variants of large effect size as well as small effect common gene variants all contribute to autism risk. These discoveries challenge traditional diagnostic boundaries and highlight huge heterogeneity in autism. In this review, we consider some of the key findings that are shaping current understanding of autism and what these discoveries mean for clinicians.
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Affiliation(s)
- Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences and MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Hadyn Ellis Building, Cardiff, Maindy Road, Wales, CF24 4HQ, UK.
| | - Michael Rutter
- Social, Genetic and Developmental Psychiatry Centre, Kings College London, London, UK
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14
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Abstract
Causation has multiple distinct meanings in genetics. One reason for this is meaning slippage between two concepts of the gene: Mendelian and molecular. Another reason is that a variety of genetic methods address different kinds of causal relationships. Some genetic studies address causes of traits in individuals, which can only be assessed when single genes follow predictable inheritance patterns that reliably cause a trait. A second sense concerns the causes of trait differences within a population. Whereas some single genes can be said to cause population-level differences, most often these claims concern the effects of many genes. Polygenic traits can be understood using heritability estimates, which estimate the relative influences of genetic and environmental differences to trait differences within a population. Attempts to understand the molecular mechanisms underlying polygenic traits have been developed, although causal inference based on these results remains controversial. Genetic variation has also recently been leveraged as a randomizing factor to identify environmental causes of trait differences. This technique-Mendelian randomization-offers some solutions to traditional epidemiological challenges, although it is limited to the study of environments with known genetic influences.
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Affiliation(s)
- Kate E Lynch
- Department of Philosophy, The University of Sydney, Sydney, New South Wales 2006, Australia
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15
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Spry EA, Aarsman SR, Youssef GJ, Patton GC, Macdonald JA, Sanson A, Thomson K, Hutchinson DM, Letcher P, Olsson CA. Maternal and paternal depression and anxiety and offspring infant negative affectivity: A systematic review and meta-analysis. DEVELOPMENTAL REVIEW 2020. [DOI: 10.1016/j.dr.2020.100934] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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16
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Environmental risk factors, protective factors, and peripheral biomarkers for ADHD: an umbrella review. Lancet Psychiatry 2020; 7:955-970. [PMID: 33069318 DOI: 10.1016/s2215-0366(20)30312-6] [Citation(s) in RCA: 99] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 05/07/2020] [Accepted: 06/12/2020] [Indexed: 02/07/2023]
Abstract
BACKGROUND Many potential environmental risk factors, environmental protective factors, and peripheral biomarkers for ADHD have been investigated, but the consistency and magnitude of their effects are unclear. We aimed to systematically appraise the published evidence of association between potential risk factors, protective factors, or peripheral biomarkers, and ADHD. METHODS In this umbrella review of meta-analyses, we searched PubMed including MEDLINE, Embase, and the Cochrane Database of Systematic Reviews, from database inception to Oct 31, 2019, and screened the references of relevant articles. We included systematic reviews that provided meta-analyses of observational studies that examined associations of potential environmental risk factors, environmental protective factors, or peripheral biomarkers with diagnosis of ADHD. We included meta-analyses that used categorical ADHD diagnosis criteria according to DSM, hyperkinetic disorder according to ICD, or criteria that were less rigorous than DSM or ICD, such as self-report. We excluded articles that did not examine environmental risk factors, environmental protective factors, or peripheral biomarkers of ADHD; articles that did not include a meta-analysis; and articles that did not present enough data for re-analysis. We excluded non-human studies, primary studies, genetic studies, and conference abstracts. We calculated summary effect estimates (odds ratio [OR], relative risk [RR], weighted mean difference [WMD], Cohen's d, and Hedges' g), 95% CI, heterogeneity I2 statistic, 95% prediction interval, small study effects, and excess significance biases. We did analyses under credibility ceilings, and assessed the quality of the meta-analyses with AMSTAR 2 (A Measurement Tool to Assess Systematic Reviews 2). This study is registered with PROSPERO, number CRD42019145032. FINDINGS We identified 1839 articles, of which 35 were eligible for inclusion. These 35 articles yielded 63 meta-analyses encompassing 40 environmental risk factors and environmental protective factors (median cases 16 850, median population 91 954) and 23 peripheral biomarkers (median cases 175, median controls 187). Evidence of association was convincing (class I) for maternal pre-pregnancy obesity (OR 1·63, 95% CI 1·49 to 1·77), childhood eczema (1·31, 1·20 to 1·44), hypertensive disorders during pregnancy (1·29, 1·22 to 1·36), pre-eclampsia (1·28, 1·21 to 1·35), and maternal acetaminophen exposure during pregnancy (RR 1·25, 95% CI 1·17 to 1·34). Evidence of association was highly suggestive (class II) for maternal smoking during pregnancy (OR 1·6, 95% CI 1·45 to 1·76), childhood asthma (1·51, 1·4 to 1·63), maternal pre-pregnancy overweight (1·28, 1·21 to 1·35), and serum vitamin D (WMD -6·93, 95% CI -9·34 to -4·51). INTERPRETATION Maternal pre-pregnancy obesity and overweight; pre-eclampsia, hypertension, acetaminophen exposure, and smoking during pregnancy; and childhood atopic diseases were strongly associated with ADHD. Previous familial studies suggest that maternal pre-pregnancy obesity, overweight, and smoking during pregnancy are confounded by familial or genetic factors, and further high-quality studies are therefore required to establish causality. FUNDING None.
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