You are here

  • Home
  • Archive
  • Volume 12, Issue 2
  • Effects of prenatal nutrient supplementation and early life exposures on neurodevelopment at age 10: a randomised controlled trial - the COPSYCH study protocol

Article Text

Article menu

Download PDFPDF

Paediatrics
Protocol
Effects of prenatal nutrient supplementation and early life exposures on neurodevelopment at age 10: a randomised controlled trial - the COPSYCH study protocol
  1. Parisa Mohammadzadeh1,2,
  2. Julie Bøjstrup Rosenberg1,2,
  3. Rebecca Vinding2,
  4. Jens Richardt Møllegaard Jepsen1,
  5. Ulrich Lindberg3,
  6. Nilo Følsgaard2,
  7. Mikkel Erlang Sørensen1,
  8. Daban Sulaiman1,3,
  9. Niels Bilenberg4,5,
  10. Jayachandra Mitta Raghava1,3,
  11. Birgitte Fagerlund1,6,
  12. Mark Vestergaard3,
  13. Christos Pantelis1,7,
  14. Jakob Stokholm2,
  15. Bo Chawes2,
  16. Henrik Larsson3,8,
  17. Birte Yding Glenthøj1,8,
  18. Klaus Bønnelykke2,
  19. Bjørn H Ebdrup1,8,
  20. Hans Bisgaard2
  1. 1Center for Neuropsychiatric Schizophrenia Research (CNSR) & Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, University of Copenhagen, Glostrup, Denmark
  2. 2Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Gentofte, Denmark
  3. 3Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet Glostrup, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
  4. 4Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
  5. 5Department of Child and Adolescent Mental Health Odense, Mental Health Services in the Region of Southern Denmark, University of Southern Denmark, Odense, Denmark
  6. 6Department of Psychology, University of Copenhagen, Copenhagen, Denmark
  7. 7Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, Victoria, Australia
  8. 8Faculty of Health and Medical Sciences, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
  1. Correspondence to Dr Hans Bisgaard; bisgaard{at}copsac.com

Abstract

Introduction Nutrient deficiency and immune and inflammatory disturbances in early life may compromise neurodevelopment and be implicated in the aetiology of psychiatric disorders. However, current evidence is limited by its predominantly observational nature. COpenhagen Prospective Study on Neuro-PSYCHiatric Development (COPSYCH) is a research alliance between Copenhagen Prospective Studies on Asthma in Childhood (COPSAC) and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research with the overall aim to investigate effects of prenatal and early life exposures on neurodevelopment at 10 years. COPSYCH will investigate the impact of prenatal n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) and high-dose vitamin D supplementation on neurodevelopment reflected by brain development, neurocognition and psychopathology. Moreover, the neurodevelopmental impact of early life exposures such as infections, low grade inflammation and the gut microbiome will be scrutinised.

Methods and analysis COPSYCH is based on the prospective and ongoing COPSAC2010 birth cohort of 700 mother–child pairs. Randomised controlled trials of supplementation with n-3 LCPUFA and/or high-dose vitamin D or placebo in the third trimester were embedded in a factorial 2×2 design (ClinicalTrials.gov: NCT01233297 and NCT00856947). This unique cohort provides deep phenotyping data from 14 previous clinical follow-up visits and exposure assessments since birth. The ongoing 10-year visit is a 2-day visit. Day 1 includes a comprehensive neurocognitive examination, and assessment of psychopathological dimensions, and assessment of categorical psychopathology. Day 2 includes acquisition of brain structural, diffusion and functional sequences using 3 Tesla MRI. Study outcomes are neurocognitive, psychopathological and MRI measures.

Ethics and dissemination This study has been approved by the Danish National Committee on Health Research Ethics and The Danish Data Protection Agency. The study is conducted in accordance with the guiding principles of the Declaration of Helsinki. Parents gave written informed consent before enrolment.

  • child & adolescent psychiatry
  • paediatric radiology
  • paediatric infectious disease & immunisation
  • mental health
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2020-047706

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Strengths and limitations of this study

    • The Copenhagen Prospective Studies on Asthma in Childhood 2010 cohort consists of 700 children and is a randomised, placebo-controlled trial on effects of prenatal nutrient supplementation on prenatal n-3 long-chain polyunsaturated fatty acids and high-dose vitamin D supplementation on child development.

    • The COpenhagen Prospective Study on Neuro-PSYCHiatric Development (COPSYCH) study comprises an extensive 2-day 10-year clinical visit and focuses on brain development, neurocognition and psychopathology.

    • Deep phenotyping is available from the previous 14 clinical visits, and a limited selection of neurodevelopmental measures have been continuously assessed.

    • The randomised controlled trial design allows for unique, causal inferences on effects of prenatal nutrient supplementation on neurodevelopment at age 10.

    • The planned COPSYCH study would be strengthened by longitudinal neurodevelopmental data, thus future similar evaluations of the cohort will be applied for.

    Introduction

    Mounting evidence suggests that health and disease are programmed in early life, and that a wide range of prenatal and early life exposures affect brain development.1 Early life may therefore represent a window of opportunity for promoting a healthy neurodevelopment. Nevertheless, the evidence regarding early life exposures and their effects on neurodevelopment are limited by observational study designs. Neurodevelopmental disorders, for example, autism spectrum disorder, attention-deficit/hyperactivity disorder (ADHD) and intellectual disability are all highly heritable with complex, polygenetic contributions2–5 and have all been associated with brain structural and functional aberrations and neurocognitive impairment. Prenatal exposures in the form of supply of micronutrients, like folic acid, are shown to be pivotal to decrease risk of congenital neural tube defects, including anencephaly, spina bifida and encephalocele6.

    Our previous study on the Copenhagen Prospective Studies on Asthma in Childhood 2010(COPSAC2010) cohort showed that boys born to mother receiving n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) supplementation had improved motor development, improved global neurocognitive function at age 2½ years of age as assessed with the neurocognitive part of Bayley Scales of Infant and Toddler development, third edition7 and reduced functional impact of emotional and behavioural problems by age 6 years according to parents’ replies to the Strengths and Difficulties Questionnaire (SDQ).8–11 No effect on neurodevelopment in the first 6 years of life was observed in the offspring born to high-dose vitamin D3 supplemented mothers.12

    The risk for manifestation of psychiatric disorders later in life is associated with environmental insults, like maternal infections during pregnancy,13 14 infections during childhood and adolescence15–18 or ongoing inflammatory processes like asthma.19–22 Furthermore, emerging evidence has indicated that n-3 LCPUFA and vitamin D are important for brain development in particular maturation of cerebral white matter myelin and cognition.23–26

    The beneficial effects of maternal n-3 LCPUFA supplementation on neurocognitive development are not consistent in previous randomised controlled trials (RCTs), and the interpretation is complicated by methodological issues.27 Still, there is some evidence that n-3 LCPUFA supplement may reduce the prevalence rate of children with lower neurocognitive scores indicative of delayed neurocognitive development at 18 months of age.28 This may be hypothesised to be due to downregulation of the pro-inflammatory n-6 LCPUFA-derived eicosanoids rather than the more anti-inflammatory eicosanoids since n-3 LCPUFA and n-6 LCPUFA competes for the same enzymes.29 However, to the best of our knowledge, no RCT of prenatal supplementation with n-3 LCPUFA and high-dose vitamin D in pregnancy has examined the neurocognitive outcome in late childhood.

    The composition of the gut microbiome matures within the first years of life and the microbiome may have the ability to affect host inflammatory status at a time, when significant brain development takes place. Perturbation of the microbial and viral homeostasis during this critical period of development may affect the signalling pathways between gut and brain (immune, neural and endocrine pathways, the so-called ‘gut-brain axis’).30 Thus, the microbiome may be an intermediary player in the interaction between the host and its environment in the mechanisms that determine the transition from health to disease.31 32 In the human gut viruses are at least as abundant as bacteria. The viral community (virome) mostly target bacteria (bacteriophages) while only a fraction directly affect humans. Their role in disease development is poorly understood, but may be detrimental in the transition from health to disease in early life, either through manipulation of the bacterial community or through direct virome–host effects.33–35

    Most of the hypotheses regarding early risk factors are based on studies reporting associations between early life exposures and a later outcome, which could be confounded by other exposures and cannot infer causality.36 The factorial, randomised controlled design of the current study provide the unique opportunity to unravel causal effects of prenatal n-3 LCPUFA and vitamin D supplementation on neuropsychiatric and neurocognitive status as well as neuroimaging, all reflecting neurodevelopment at age 10. Furthermore, we have extensive information on a broad range of environmental exposures, which were collected through personal interviews with the families and when possible validated against register data, and assessed objectively and longitudinally, including repeated assessment of the airway and gut microbiome from birth throughout childhood.

    The main objective of COpenhagen Prospective Study on Neuro-PSYCHiatric Development (COPSYCH) is characterising the neurocognitive, psychopathological and brain structural and functional outcomes, and relating these to the n-3 LCPUFA and vitamin D interventions and early life exposures. Data are collected at a comprehensive, ongoing 2-day 10-year follow-up visit of the COPSAC2010 cohort. Comprehensive data on early exposures have been meticulously collected at previous follow-up visits of the COPSAC2010 cohort. The ambitious goal is to provide the basis for preventive interventions in prenatal or early life in order to improve neurocognitive development and prevent development of psychiatric disorders.

    Methods and analysis

    COPSYCH is a 5-year translational research alliance between COPSAC and Center for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) initiated in January 2019.

    First clinical examination took place on 11 February 2019. Expected end of clinical examinations is December 1st 2021, followed by data processing and analysis. The COPSAC2010 cohort and previous assessments are briefly summarised below and detailed previously.37

    Patient and public involvement

    Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.

    The COPSYCH 10-year visit

    The ongoing 10-year COPSYCH visit extends over 2 days. Day 1 is a 6–8 hour visit at the COPSAC research clinic. The first part consists of a neurocognitive assessment (table 1) and the second part is a neuropsychiatric assessment, where categorical and dimensional psychopathology is assessed using a diagnostic interview and parental and teacher questionnaire ratings (table 2).

    View this table:
    Table 1

    Neurocognitive test battery

    View this table:
    Table 2

    Psychopathological interviews and questionnaires

    Neurocognition

    The neurocognitive test battery is based on selected subtests from several neuropsychological tests. The Cambridge Neuropsychological Test Automated Battery (CANTAB)38 is a neuropsychological test battery developed from a neuroscience approach. The CANTAB battery has been validated for use between the ages 4–80 years39 and has been extensively used in, for example, lesion studies as well as neuropsychiatric and neurological populations. The CANTAB tests have been used in clinical cohorts of both children40 and adults with neurodevelopmental disorders including schizophrenia and ADHD, and healthy controls41. To assess specific neurocognitive functions across the selected neurocognitive domains from CANTAB, we have included the following: rapid visual information processing to assess sustained attention; reaction time task to assess both simple and five-choice reaction time and movement time; and paired associates learning to assess visual memory. Executive functions are assessed using the intra–extra dimensional set shifting task examining mental flexibility; the stockings of cambridge examining planning, and the spatial span and spatial working memory tasks, respectively, testing working memory span, and spatial working memory manipulation and strategy formation.

    Two subtests (vocabulary and matrices) from the Wechsler Intelligence Scale for Children, fourth edition (WISC-IV)42 are used to estimate intelligence; additionally other subtests are used to characterise verbal working memory (digit span and letter–number sequencing) and processing speed (coding and symbol search).40 42 From the Delis-Kaplan Executive Function System, trail making 2 is applied as an additional measure of processing speed, and the trail making 4 to measure flexibility/set shift.40 43 Moreover, selected subtests (Word Selective Reminding and Object Recall) from Test of Memory and Learning—Second Edition are used for evaluating verbal memory (2011).40 44 Fine motor dexterity is assessed with Grooved Pegboard and Reaction Time in CANTAB.45 46 The parent and teacher fill out Behaviour Rating Inventory of Executive Function, Second Edition (see table 1)47 measuring daily life executive functions in the home environment and school environment, respectively.

    All the neurocognitive tests are well validated, reliable and appropriate for this age group.39 41 48–50 The time for completing the full test battery is approximately 2 hours, but the duration is individualised with breaks when needed. Tests are administered in a fixed order.

    Categorical psychopathology

    The diagnostic interview Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL)48 is used to provide information on current and lifetime psychopathology. K-SADS-PL is a semi-structured clinical diagnostic interview containing the same questions for parents and children (except in the Autism Spectrum Supplement that contains extra questions for the parents only). According to the K-SADS-PL guidelines the interview is first completed with a parent/caregiver and afterwards with the child younger than 11 years of age. The K-SADS-PL consists of a general screening interview. If the threshold of a symptom has been reached in the general screening interview, K-SADS-PL contains additional questions in supplements, which target specific disorders. K-SADS-PL Schizophrenia Spectrum and Other Psychotic Disorders Supplement is applied whether or not any psychotic symptoms appear in the screening interview to detect possible psychotic-like experiences (PLE).51

    To obtain information on potential current and earlier use of psychotropic medicine, questions from the Schedules for Clinical Assessment in Neuropsychiatry52 are reworded to interview about prescribed psychotropic medication to the child (antidepressants, mood stabilisers, anxiolytics, hypnotics, antipsychotics, central stimulants).

    Children’s global assessment of functioning53 (included in K-SADS-PL), is used for assessment of the child’s global level of functioning.

    Research diagnoses are made according to both International Classification of Diseases 10th Revision(ICD-10)54 and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5).55 Diagnoses are based on information from all available sources (clinical observations during the neuropsychological testing and psychopathological assessments of each participating child). All K-SADS-PL interviews are video recorded. The videos are used for supervision and to reach consensus on diagnostics. Neurocognitive assessments and clinical interviews are supervised by a senior researcher, psychologist with specialty in child and adolescent psychiatry (JRMJ) and consensus diagnoses are made weekly (between JRMJ and at least two examiners). All diagnoses are furthermore re-evaluated at a monthly conference with a professor of child and adolescent psychiatry (NB). Additionally, cases with an inconclusive diagnosis are supervised by NB.

    Ratings of The Test Observation Form (TOF), the verbal subtest from WISC-IV (vocabulary) and Children’s Global Assessment Scale are also based on consensus rating with JRMJ. Inter-rater reliability will be estimated based on 10 K-SADS-PL screening interview videos recorded (by JRMJ) during the first half data collection period. Each 20th child that is not assigned a diagnosis will undergo re-evaluation with NB. The four interviewers have supervision on a weekly basis.

    Dimensional psychopathology

    In order to also quantify psychopathology, which may or may not meet the threshold for a psychiatric diagnosis, dimensional assessments of psychiatric symptoms and behavioural problems are undertaken on all children. For a detailed registration of inattentive and impulsive–hyperactive behaviours in different situations, the ADHD—Rating Scale (ADHD-RS) questionnaire is administered (filled out by parents and teachers, respectively).56 Similarly, the Social Responsiveness Scale—2 is used for parental ratings of the severity of autism spectrum disorder traits.57 58 In terms of dimensions of child and adolescent psychopathology, the parents report their evaluation in the Child Behaviour Checklist (CBCL)59 60; The teacher’s report form (TRF) is completed by the child’s teacher. In most aspects the TRF corresponds to the CBCL as most of its items have counterparts in the CBCL. SDQ is a multi-informant screening tool for emotional and behavioural problems in children and adolescents, answered by parents and teachers.61 TOF will be used to score severity of behavioural and emotional problems observed during the neurocognitive test session. It consists of 125 items, scored on a 4-point Likert scale. TOF is completed by the examiner immediately after the neurocognitive testing.62

    MRI (day 2)

    Day 2 is a 1-hour visit (table 2). MRI is a non-invasive medical scanning technique, which can acquire images of the brain without application of radioactive ligands or X-rays. MRI scans are acquired on a 3T Philips Achieva scanner (Philips Healthcare, Best, the Netherlands). Both brain structural and functional sequences are acquired (table 3). The total duration of MRI acquisition is 35 min, which including breaks effectively corresponds to 40–45 min of scan time.

    View this table:
    Table 3

    MRI sequences

    All children undergo a virtual MRI ‘practice scanning’ using a pair of three-dimensional (3D) goggles on examination day 1. In order to minimise movement and impatience, all children are given the opportunity to watch an animation movie while inside the MRI scanner, using a mirror and video projection. We extract head motion parameters using the Tracoline system, which is an advanced 3D stereo vision system to monitor and capture head movements using 3D surfaces from structured invisible infrared light, enabling markerless tracking of the subject’s head in a clinical MRI setup (https://tracinnovations.com/markerless-technology/). These motion parameters are used to retrospectively correct for scanner head motion.

    COPSAC2010 cohort

    COPSYCH is based on the COPSAC2010 cohort consisting of 700 mother–child pairs followed prospectively from pregnancy week 24.37 62 A population-based sample of 736 pregnant women were recruited during 2008–2010 and participated in a double blinded, randomised and placebo controlled study of fish oil, n-3 LCPUFA (2.4 g/day n-3 LCPUFA) and/or high-dose vitamin D (2400 IU/day) supplementation during the third trimester with the primary outcome of persistent wheeze/asthma until age 3, where the trials were unblinded (ClinicalTrials.gov: NCT00798226 and NCT00856947). Data validation and quality control followed the guidelines of Good Clinical Practice. Exclusion criteria were chronic cardiac, endocrinological, nephrological or lung disease other than asthma or a daily vitamin D intake above 600 IU.

    Neurodevelopmental outcomes were prespecified secondary outcomes specified in the primary study protocol (including milestones, language and The Bayley Scales of Infant and Toddler Development) The parents were informed that they participated in a cohort study lasting at least 3 years, and that we planned to follow the children forward if we succeeded in financing. The clinical visits after 3 years have been planned accordingly for the purpose of gaining as much knowledge in the prespecified fields as possible, and to replicate and continue further research of the previous findings

    The mothers and their children have been closely followed prospectively at the COPSAC research unit with 14 completed clinical visits scheduled from pregnancy week 24 until 8 years and with day-to-day diaries from birth capturing all symptoms related to airways, skin and infectious episodes the first 3 years between visits (figure 1). Retention rate for the previous visit at age 8 years was 92%.

    Figure 1
    Figure 1

    Overview of inflammation and infection markers in COPSAC2010 (mothers) - Modified from: http://copsac.com/home/copsac-cohorts/copsac2010-clinic/)

    The ongoing neurocognitive and psychopathological 10-year examinations are undertaken by trained medical doctors and experienced nurses, who will remain blinded to the intervention status of the children throughout the data collection and statistical analyses.

    Previous visits and examinations

    At all previous 14 clinical visits, the parents were interviewed about a variety of socioeconomic factors such as smoking during pregnancy, family size, household pets and so on. Furthermore, information has been collected on delivery mode, Apgar scores, maternal diet during pregnancy 4 weeks prior to randomisation, breastfeeding length, fatty acid composition of breast milk and introduction of solid foods. The child’s daily activity level and sleep patterns were also measured at 2 years and 10 years of age by accelerometry (wristband that measures daily physical activity, omnidirectional Actical accelerometer, Philips Respironics, Murrysville, Pennsylvania, USA).63

    Metabolomics

    Global metabolomics profiling of blood was done in the mothers at 24 weeks gestation and 1-week post partum and in the children at age 0.5, 1.5 and 6 years.64 Further, dry blood spot metabolomics profiling was done in the newborn child and urine metabolomics by age 1 month.65 These metabolomic assessments allow discovery of yet unknown mechanisms affecting aspects of neurodevelopment.

    Genetics

    Genomewide scan has been conducted on the cohort using the Illumina HumanOmniExpressExome-8 V1.2 BeadChip, including genetic variants of importance for n-3 LCPUFA and vitamin D levels and metabolism, which will be included in the analyses of the intervention. This data will allow us to analyse to which extent the effect of early exposures are modified by host genetics.

    Microbiome

    Longitudinal gut microbiome composition profiling has been performed in the cohort using 16S rRNA gene amplicon sequencing66 at 1 week, 1 month, 1 year, 4 and 6 years and metagenome at 1 year. These early samples together with samples collected at 8 and 10 years will allow us to characterise the microbial development until age 10 and how this may impact components of neurodevelopment.

    Inflammation in mothers and children

    We measured systemic inflammatory surrogate markers including high-sensitivity C-Reactive Protein (hs-CRP), interleukin (IL)-6, Tumor Necrosis Factor alpha (TNFα), IL-1β and CXC Chemokine Ligand 8 (CXCL-8). Furthermore we assessed a panel of immune mediators in the upper airways related to specific immune signalling pathways in unstimulated upper airway mucosal lining fluid at 1 month, 2 years and 6 years of age and at episodes with acute respiratory symptoms. Finally, at 18 months a deep immunological phenotyping was done with an extensive profiling of immune cell distribution and function including detailed phenotyping of 25 immune cell populations and 8 ligand simulations in freshly collected whole blood (figure 1).67

    Infections and prenatal information

    Mothers were interviewed regarding infectious symptoms and use of medication including all courses of antibiotics in pregnancy at the scheduled visits preintervention and post-intervention. The first 3 years of the child’s life the families kept diary cards monitoring signs of infection categorised as common cold, pneumonia, pharyngitis, otitis, fever, gastrointestinal infection and absence from daycare because of illness. The COPSAC physician validated the diary cards entries with the parents at each visit and interviewed them regarding other types of infections. Information was checked against hospital and medication prescription registries. After age 3, data on hospital admissions and information about prescribed medication were gathered at the scheduled visits. Diagnosed pre-eclampsia, gestational diabetes and pre-pregnancy weight were registered. These data allow

    Diagnosis of asthma, allergy and eczema

    Asthma/persistent wheeze was diagnosed according to a validated symptom-based quantitative algorithm (five episodes of troublesome lung symptoms, typical asthma symptoms, symptom relief when using inhaled short-acting B2-agonists and response to a 3-month trial of inhaled corticosteroid).68 69 Lung function was measured with whole-body plethysmography and spirometry, and bronchial responsiveness was evaluated by methacholine challenge.70 71

    Allergen specific IgE levels along with skin prick tests have been measured for the most common inhalant and food allergens and allergic rhinitis was diagnosed prospectively.72 73

    Eczema diagnosis was based on the Hanifin-Rajka criteria74 and the SCORing Atopic Dermatitis (SCORAD) index was used to measure severity during flares (severity scoring of atopic dermatitis)73 75–77 (figure 2).

    Figure 2
    Figure 2

    Overview of inflammation and infection markers in COPSAC2010 (children) - Modified from: http://copsac.com/home/copsac-cohorts/copsac2010-clinic/)

    Previous neurodevelopmental and cognitive assessments

    The children’s neurodevelopmental status78 has been examined throughout the years. Motor milestone achievements were continuously evaluated during the first years of life by the parents using a registration form based on the Denver Developmental Index,79 and WHO milestones.79 80 Language development was evaluated with MacArthur Bates Communicative Developmental Inventory at age 1 and 2 years.81 By the age of 2½ years global neurocognitive functioning was examined using the neurocognitive part of Bayley Scales of Infant and Toddler development, third edition.7 81 At age 3 years general neurodevelopment was assessed by the Ages and Stages Questionnaire.82 At ages 6 and 8 years, parents were asked to fill out a SDQ8–10 focusing on emotional and behavioural problems. Moreover, at age 8 years, parents were also asked to fill out the ADHD-RS56 83 which is a questionnaire merely focused on ADHD symptoms and oppositional defiant disorder symptoms (figure 3).

    Figure 3
    Figure 3

    Neurodevelopmental outcomes in COPSAC2010. ADHD-RS, Attention Deficit/Hyperactivity Disorder-Rating Scale; ASQ, Ages and Stages Questionnaire; COPSAC2010, Copenhagen Prospective Studies on Asthma in Childhood 2010; COPSYCH, COpenhagen Prospective Study on Neuro-PSYCHiatric Development; SDQ, Strengths and Difficulties Questionnaire.

    Power calculation

    At the last visit at 8 years, the retention rate was 92%, and we anticipate a similar participation rate at the 10-year visit. With a total sample size of N=644 and an alpha level of 0.05, t and a SD of 1.00, this study has a power of 80% to detect an effect size of 0.22 SD. Based on the SD of the psychopathological and global functioning raw scores reported in a large, recent Danish sample of population-based control children 7 years of age,40 the effect size of 0.22 SD is equivalent to 3.3 raw scores on the child behaviour checklist total problem scale, and 3.0 raw scores on the CGAS, respectively. We assume that the raw score distributions observed in these children with a mean age of 7.8 years are equivalent for 10-year-old children. Finally, this effect size is equivalent to 3.3 scores on the Processing Speed Index and the Working Memory Index using the published Danish WISC-IV norms.84

    Risks, side effects and potential benefits

    There are no known risks of simple MRI scanning. Discomfort during the actual scanning will be minimised with earplugs and hearing protectors.

    Children with psychiatric symptoms who have not been evaluated prior to the visit may likely benefit from the thorough COPSYCH evaluation. Early identification of mental challenges or detection of a psychiatric diagnosis is crucial in order to optimise, for example, the child’s schooling performance.85 Children who have psychiatric disorders are referred directly to child and adolescent mental health services (after the parents give their permission and consent).

    Main outcomes

    Neurocognition

    Neurocognitive functioning reflecting intelligence and the following seven neurocognitive domains: speed of processing, attention/vigilance, psychomotor speed, verbal memory, visual memory, executive functions and motor functioning (table 1).

    Categorical psychopathology

    Categorical psychopathology, that is, child and adolescent disorders according to ICD 1054 and DSM 5.55

    Dimensional psychopathology

    Dimensional psychopathology scores will be based on ratings in all psychopathological questionnaires (total scores and subscales scores (table 2) and on the number of mental and behavioural symptoms reported in the K-SADS-PL.48 Severity is thus reflected in a quantitative composite index of psychiatric symptoms which is the number of symptoms endorsed by a severity score of ‘three’ in the complete K-SADS-PL interview, that is, total number of symptoms at/over the threshold. Present symptoms will be counted separately from previous symptoms. Additionally, the number of symptoms within different subdomains will be calculated, for example, affective and anxiety disorders; neurodevelopmental and behavioural disorders. Counting symptoms does not interfere with the standard administration of the K-SADS-PL interview.

    Using this method we will quantify the symptom load of each child since a dimensional approach may be more sensitive than the categorical diagnostic approach in our context. A similar approach has been applied here where they use symptom composite measure from the K-SADS.86 The symptom count method will include all children irrespective of their diagnostic status.

    PLE

    We will examine if the children have experienced PLE.87 88 PLE will be measured by semi structured interviews using the K-SADS-PL-items on psychotic symptoms (Schizophrenia Spectrum and Other Psychotic Disorders Supplement), each symptom scored as ‘not present’ (1) ‘likely present’ (2) or ‘definitely present’ (3). A similar method was used in a previous Danish Copenhagen Child Cohort study (CCC2000).89 A score of 2 is reflective of a PLE. PLE will be consensus rated with a medical doctor (MR) with extensive experience from a prior similar study.89

    Brain structure and function

    Structural MRI measures of grey and white matter will be used to disentangle the putative link between early inflammation, psychosocial functioning, neurocognition and psychopathology. We will use conventional software packages to obtain measures of cortical thickness and surface area, curvature and volumes of specific grey matter brain structures (eg, FreeSurfer (http://surfer.nmr.mgh.harvard.edu/): Diffusion data we will used to assess white matter integrity using, for example, Tract-based Spatial Statistics (TBSS) (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS). Moreover we will use the functional data to assess cerebral blood flow and the spectroscopy data will provide novel data on cerebral lactate metabolism.90

    Ethics and dissemination

    This study is conducted in accordance with the guiding principles of the Declaration of Helsinki and was approved by the Local Ethics Committee: H-B-2008–093 and the Danish Data Protection Agency 2015-41-3696. All families will receive written information about the study prior to participation and both parents will give written informed consent before enrolment.

    Acquired data are stored in the secure Research Electronic Data Capture system provided by the Capital Region of Copenhagen. Direct electronic typing of as much data as possible is enforced, and double data entry by independent staff ensures validity of data.

    Perspectives

    This is the largest study of its kind, with a broad range of exposures, which were validated by personal interviews with the families. Identifying the possible linkage between neurocognitive impairments, psychopathology and early life exposures may become a game changer in future prevention of psychiatric disorders and neurocognitive impairments, for example, in terms of change of recommended guidelines of micronutrient and vitamin supplementation or other exposures during pregnancy. Knowledge delineating the mechanisms involved in linking early life exposure to aberrant neurodevelopment will potentially enable a more targeted therapeutic approach for the prevention or amelioration of structural and functional brain and neurocognitive developmental abnormalities, and the onset of psychopathology. Thereby, the results of this research may have direct, easily accessible and essential impact on children’s brain health.

    Positive, negative and inconclusive results will be presented at national and international conferences. Papers will be submitted to peer-reviewed journals.

    Ethics statements

    Patient consent for publication

    References

    1. ↵
      1. Marques AH,
      2. O'Connor TG,
      3. Roth C, et al
      . The influence of maternal prenatal and early childhood nutrition and maternal prenatal stress on offspring immune system development and neurodevelopmental disorders. Front Neurosci 2013;7:120. doi:10.3389/fnins.2013.00120pmid:http://www.ncbi.nlm.nih.gov/pubmed/23914151
      OpenUrlCrossRefPubMed
    2. ↵
      1. Cross-Disorder Group of the Psychiatric Genomics Consortium
      . Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 2013;381:1371–9.doi:10.1016/S0140-6736(12)62129-1pmid:http://www.ncbi.nlm.nih.gov/pubmed/23453885
      OpenUrlCrossRefPubMedWeb of Science
    3. ↵
      1. Shih RA,
      2. Belmonte PL,
      3. Zandi PP
      . A review of the evidence from family, twin and adoption studies for a genetic contribution to adult psychiatric disorders. Int Rev Psychiatry 2004;16:260–83.doi:10.1080/09540260400014401pmid:http://www.ncbi.nlm.nih.gov/pubmed/16194760
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Owen MJ,
      2. O'Donovan MC,
      3. Thapar A, et al
      . Neurodevelopmental hypothesis of schizophrenia. Br J Psychiatry 2011;198:173–5.doi:10.1192/bjp.bp.110.084384pmid:http://www.ncbi.nlm.nih.gov/pubmed/21357874
      OpenUrlAbstract/FREE Full Text
    5. ↵
      1. Craddock N,
      2. Owen MJ
      . The Kraepelinian dichotomy - going, going… but still not gone. Br J Psychiatry 2010;196:92–5.doi:10.1192/bjp.bp.109.073429pmid:20118450
      OpenUrlAbstract/FREE Full Text
    6. ↵
      1. De-Regil LM,
      2. Fernández-Gaxiola AC,
      3. Dowswell T, et al
      . Effects and safety of periconceptional folate supplementation for preventing birth defects. Cochrane Database Syst Rev 2010;10:CD007950. doi:10.1002/14651858.CD007950.pub2pmid:http://www.ncbi.nlm.nih.gov/pubmed/20927767
      OpenUrlPubMed
    7. ↵
      1. Hoskens J,
      2. Klingels K,
      3. Smits-Engelsman B
      . Validity and cross-cultural differences of the Bayley scales of infant and toddler development, third edition in typically developing infants. Early Hum Dev 2018;125:17–25.doi:10.1016/j.earlhumdev.2018.07.002pmid:http://www.ncbi.nlm.nih.gov/pubmed/30172781
      OpenUrlPubMed
    8. ↵
      1. Goodman R
      . Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry 2001;40:1337–45.doi:10.1097/00004583-200111000-00015pmid:http://www.ncbi.nlm.nih.gov/pubmed/11699809
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      1. Goodman R
      . The extended version of the strengths and difficulties questionnaire as a guide to child psychiatric caseness and consequent burden. J Child Psychol Psychiatry 1999;40:791–9.doi:10.1111/1469-7610.00494pmid:http://www.ncbi.nlm.nih.gov/pubmed/10433412
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      1. Obel C,
      2. Dalsgaard S,
      3. Stax H-P, et al
      . [Strengths and difficulties questionnaire (SDQ-Dan). A new instrument for psychopathologic screening of children aged 4-16 years]. Ugeskr Laeger 2003;165:462–5.pmid:12599845
      OpenUrlPubMed
    11. ↵
      1. Sass L,
      2. Bjarnadóttir E,
      3. Stokholm J, et al
      . Fish oil supplementation in pregnancy and neurodevelopment in Childhood-A randomized clinical trial. Child Dev 2021;92:1624–35.doi:10.1111/cdev.13541pmid:http://www.ncbi.nlm.nih.gov/pubmed/33506965
      OpenUrlPubMed
    12. ↵
      1. Sass L,
      2. Vinding RK,
      3. Stokholm J, et al
      . High-Dose vitamin D supplementation in pregnancy and neurodevelopment in childhood: a Prespecified secondary analysis of a randomized clinical trial. JAMA Netw Open 2020;3:e2026018. doi:10.1001/jamanetworkopen.2020.26018pmid:http://www.ncbi.nlm.nih.gov/pubmed/33289844
      OpenUrlPubMed
    13. ↵
      1. Khandaker GM,
      2. Zimbron J,
      3. Lewis G, et al
      . Prenatal maternal infection, neurodevelopment and adult schizophrenia: a systematic review of population-based studies. Psychol Med 2013;43:239–57.doi:10.1017/S0033291712000736pmid:http://www.ncbi.nlm.nih.gov/pubmed/22717193
      OpenUrlCrossRefPubMed
    14. ↵
      1. Brown AS
      . Epidemiologic studies of exposure to prenatal infection and risk of schizophrenia and autism. Dev Neurobiol 2012;72:1272–6.doi:10.1002/dneu.22024pmid:http://www.ncbi.nlm.nih.gov/pubmed/22488761
      OpenUrlCrossRefPubMed
    15. ↵
      1. Nielsen PR,
      2. Benros ME,
      3. Mortensen PB
      . Hospital contacts with infection and risk of schizophrenia: a population-based cohort study with linkage of Danish national registers. Schizophr Bull 2014;40:1526–32.doi:10.1093/schbul/sbt200pmid:http://www.ncbi.nlm.nih.gov/pubmed/24379444
      OpenUrlCrossRefPubMed
    16. ↵
      1. Köhler O,
      2. Petersen L,
      3. Mors O, et al
      . Infections and exposure to anti-infective agents and the risk of severe mental disorders: a nationwide study. Acta Psychiatr Scand 2017;135:97–105.doi:10.1111/acps.12671
      OpenUrl
    17. ↵
      1. Benros ME,
      2. Nielsen PR,
      3. Nordentoft M, et al
      . Autoimmune diseases and severe infections as risk factors for schizophrenia: a 30-year population-based register study. Am J Psychiatry 2011;168:1303–10.doi:10.1176/appi.ajp.2011.11030516
      OpenUrlCrossRefPubMedWeb of Science
    18. ↵
      1. Köhler-Forsberg O,
      2. Petersen L,
      3. Gasse C, et al
      . A nationwide study in Denmark of the association between treated infections and the subsequent risk of treated mental disorders in children and adolescents. JAMA Psychiatry 2019;76:271–9.doi:10.1001/jamapsychiatry.2018.3428pmid:http://www.ncbi.nlm.nih.gov/pubmed/30516814
      OpenUrlPubMed
    19. ↵
      1. Schans Jvander,
      2. Çiçek R,
      3. de Vries TW, et al
      . Association of atopic diseases and attention-deficit/hyperactivity disorder: a systematic review and meta-analyses. Neurosci Biobehav Rev 2017;74:139–48.doi:10.1016/j.neubiorev.2017.01.011pmid:http://www.ncbi.nlm.nih.gov/pubmed/28111269
      OpenUrlPubMed
    20. ↵
      1. Pedersen MS,
      2. Benros ME,
      3. Agerbo E, et al
      . Schizophrenia in patients with atopic disorders with particular emphasis on asthma: a Danish population-based study. Schizophr Res 2012;138:58–62.doi:10.1016/j.schres.2012.02.019
      OpenUrlCrossRefPubMed
    21. ↵
      1. Meyer U,
      2. Schwarz MJ,
      3. Müller N
      . Inflammatory processes in schizophrenia: a promising neuroimmunological target for the treatment of negative/cognitive symptoms and beyond. Pharmacol Ther 2011;132:96–110.doi:10.1016/j.pharmthera.2011.06.003pmid:http://www.ncbi.nlm.nih.gov/pubmed/21704074
      OpenUrlCrossRefPubMed
    22. ↵
      1. Kaas TH,
      2. Vinding RK,
      3. Stokholm J, et al
      . Association between childhood asthma and attention deficit hyperactivity or autism spectrum disorders: a systematic review with meta-analysis. Clin Exp Allergy 2021;51:228-252.doi:10.1111/cea.13750pmid:http://www.ncbi.nlm.nih.gov/pubmed/32997856
      OpenUrlPubMed
    23. ↵
      1. McNamara RK,
      2. Szeszko PR,
      3. Smesny S, et al
      . Polyunsaturated fatty acid biostatus, phospholipase A2 activity and brain white matter microstructure across adolescence. Neuroscience 2017;343:423–33.doi:10.1016/j.neuroscience.2016.12.007
      OpenUrlPubMed
    24. ↵
      1. McGrath JJ,
      2. Féron FP,
      3. Burne THJ, et al
      . Vitamin D3-implications for brain development. J Steroid Biochem Mol Biol 2004;89-90:557–60.doi:10.1016/j.jsbmb.2004.03.070pmid:http://www.ncbi.nlm.nih.gov/pubmed/15225838
      OpenUrlPubMed
    25. ↵
      1. Sable PS,
      2. Dangat KD,
      3. Joshi AA, et al
      . Maternal omega 3 fatty acid supplementation during pregnancy to a micronutrient-imbalanced diet protects postnatal reduction of brain neurotrophins in the rat offspring. Neuroscience 2012;217:46–55.doi:10.1016/j.neuroscience.2012.05.001
      OpenUrlCrossRefPubMedWeb of Science
    26. ↵
      1. Filley CM,
      2. Fields RD
      . White matter and cognition: making the connection. J Neurophysiol 2016;116:2093–104.doi:10.1152/jn.00221.2016pmid:http://www.ncbi.nlm.nih.gov/pubmed/27512019
      OpenUrlCrossRefPubMed
    27. ↵
      1. Gould JF,
      2. Smithers LG,
      3. Makrides M
      . The effect of maternal omega-3 (n-3) LCPUFA supplementation during pregnancy on early childhood cognitive and visual development: a systematic review and meta-analysis of randomized controlled trials. Am J Clin Nutr 2013;97:531–44.doi:10.3945/ajcn.112.045781
      OpenUrlAbstract/FREE Full Text
    28. ↵
      1. Makrides M,
      2. Gibson RA,
      3. McPhee AJ, et al
      . Effect of DHA supplementation during pregnancy on maternal depression and neurodevelopment of young children: a randomized controlled trial. JAMA 2010;304:1675–83.doi:10.1001/jama.2010.1507pmid:http://www.ncbi.nlm.nih.gov/pubmed/20959577
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      1. Salvig JD,
      2. Lamont RF
      . Evidence regarding an effect of marine n-3 fatty acids on preterm birth: a systematic review and meta-analysis. Acta Obstet Gynecol Scand 2011;90:825–38.doi:10.1111/j.1600-0412.2011.01171.x
      OpenUrlCrossRefPubMed
    30. ↵
      1. Cryan JF,
      2. O'Riordan KJ,
      3. Cowan CSM, et al
      . The microbiota-gut-brain axis. Physiol Rev 2019;99:1877–2013.doi:10.1152/physrev.00018.2018
      OpenUrlCrossRefPubMed
    31. ↵
      1. Proctor C,
      2. Thiennimitr P,
      3. Chattipakorn N, et al
      . Diet, gut microbiota and cognition. Metab Brain Dis 2017;32:1–17.doi:10.1007/s11011-016-9917-8pmid:http://www.ncbi.nlm.nih.gov/pubmed/27709426
      OpenUrlPubMed
    32. ↵
      1. Leyrolle Q,
      2. Decoeur F,
      3. Briere G, et al
      . Maternal dietary omega-3 deficiency worsens the deleterious effects of prenatal inflammation on the gut-brain axis in the offspring across lifetime. Neuropsychopharmacology 2021;46:579-602.doi:10.1038/s41386-020-00793-7pmid:http://www.ncbi.nlm.nih.gov/pubmed/32781459
      OpenUrlPubMed
    33. ↵
      1. Mirzaei MK,
      2. Maurice CF
      . Ménage à trois in the human gut: interactions between host, bacteria and phages. Nat Rev Microbiol 2017;15:397–408.doi:10.1038/nrmicro.2017.30
      OpenUrlCrossRef
    34. ↵
      1. Zhao G,
      2. Vatanen T,
      3. Droit L, et al
      . Intestinal virome changes precede autoimmunity in type I diabetes-susceptible children. Proc Natl Acad Sci U S A 2017;114:E6166–75.doi:10.1073/pnas.1706359114pmid:http://www.ncbi.nlm.nih.gov/pubmed/28696303
      OpenUrlAbstract/FREE Full Text
    35. ↵
      1. Hsu BB,
      2. Gibson TE,
      3. Yeliseyev V, et al
      . Dynamic modulation of the gut microbiota and metabolome by bacteriophages in a mouse model. Cell Host Microbe 2019;25:803–14.doi:10.1016/j.chom.2019.05.001
      OpenUrlCrossRefPubMed
    36. ↵
      1. Fedak KM,
      2. Bernal A,
      3. Capshaw ZA, et al
      . Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology. Emerg Themes Epidemiol 2015;12:14. doi:10.1186/s12982-015-0037-4pmid:http://www.ncbi.nlm.nih.gov/pubmed/26425136
      OpenUrlPubMed
    37. ↵
      1. Bisgaard H,
      2. Vissing NH,
      3. Carson CG, et al
      . Deep phenotyping of the unselected COPSAC2010 birth cohort study. Clin Exp Allergy 2013;43:1384–94.doi:10.1111/cea.12213pmid:http://www.ncbi.nlm.nih.gov/pubmed/24118234
      OpenUrlCrossRefPubMed
    38. ↵
      1. Sahakian BJ,
      2. Owen AM
      . Computerized assessment in neuropsychiatry using Cantab: discussion paper. J R Soc Med 1992;85:399–402.pmid:http://www.ncbi.nlm.nih.gov/pubmed/1629849
      OpenUrlCrossRefPubMedWeb of Science
    39. ↵
      1. De Luca CR,
      2. Wood SJ,
      3. Anderson V, et al
      . Normative data from the CANTAB. I: development of executive function over the lifespan. J Clin Exp Neuropsychol 2003;25:242–54.doi:10.1076/jcen.25.2.242.13639pmid:http://www.ncbi.nlm.nih.gov/pubmed/12754681
      OpenUrlCrossRefPubMedWeb of Science
    40. ↵
      1. Hemager N,
      2. Plessen KJ,
      3. Thorup A, et al
      . Assessment of neurocognitive functions in 7-year-old children at familial high risk for schizophrenia or bipolar disorder: the Danish high risk and resilience study via 7. JAMA Psychiatry 2018;75:844–52.doi:10.1001/jamapsychiatry.2018.1415pmid:http://www.ncbi.nlm.nih.gov/pubmed/29926086
      OpenUrlPubMed
    41. ↵
      1. Luciana M,
      2. Nelson CA
      . Assessment of neuropsychological function through use of the Cambridge neuropsychological testing automated battery: performance in 4- to 12-year-old children. Dev Neuropsychol 2002;22:595–624.doi:10.1207/S15326942DN2203_3pmid:http://www.ncbi.nlm.nih.gov/pubmed/12661972
      OpenUrlCrossRefPubMedWeb of Science
    42. ↵
      1. Wechsler D
      Antonio S, ed. Wechsler intelligence scale for children. 4th edn. TX: The Psychological Corporation, 2003.
    43. ↵
      1. Delis DC,
      2. Kaplan E,
      3. Kramer JH
      . Delis-Kaplan executive function system: D-KEFS, 2001: 144 p.
    44. ↵
      1. NJA GS
      , ed. TOMAL-2. encyclopedia of child behavior and development. Springer, 2011.
    45. ↵
      1. Merker B,
      2. Podell K
      . Grooved pegboard test. Encyclopedia of clinical neuropsychology 2011:1176–8.
    46. ↵
      1. Skogan AH,
      2. Oerbeck B,
      3. Christiansen C, et al
      . Updated developmental norms for fine motor functions as measured by finger tapping speed and the grooved Pegboard test. Dev Neuropsychol 2018;43:551–65.doi:10.1080/87565641.2018.1495724pmid:http://www.ncbi.nlm.nih.gov/pubmed/30156884
      OpenUrlCrossRefPubMed
    47. ↵
      1. Dodzik P
      . Behavior rating inventory of executive function. In: Gioia GA, Isquith PK, Guy SC, et al., eds. Journal of pediatric neuropsychology. Vol. 3. 2nd edn, 2017: 227–31.
      OpenUrl
    48. ↵
      1. Kaufman J,
      2. Birmaher B,
      3. Brent D, et al
      . Schedule for affective disorders and schizophrenia for school-age Children-Present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry 1997;36:980–8.doi:10.1097/00004583-199707000-00021pmid:http://www.ncbi.nlm.nih.gov/pubmed/9204677
      OpenUrlCrossRefPubMedWeb of Science
    49. ↵
      1. Thorup AAE,
      2. Jepsen JR,
      3. Ellersgaard DV, et al
      . The Danish high risk and resilience study--VIA 7--a cohort study of 520 7-year-old children born of parents diagnosed with either schizophrenia, bipolar disorder or neither of these two mental disorders. BMC Psychiatry 2015;15:233. doi:10.1186/s12888-015-0616-5pmid:http://www.ncbi.nlm.nih.gov/pubmed/26432691
      OpenUrlPubMed
    50. ↵
      1. Ellersgaard D,
      2. Jessica Plessen K,
      3. Richardt Jepsen J, et al
      . Psychopathology in 7-year-old children with familial high risk of developing schizophrenia spectrum psychosis or bipolar disorder - The Danish High Risk and Resilience Study - VIA 7, a population-based cohort study. World Psychiatry 2018;17:210–9.doi:10.1002/wps.20527pmid:http://www.ncbi.nlm.nih.gov/pubmed/29856544
      OpenUrlPubMed
    51. ↵
      1. Jeppesen P,
      2. Larsen JT,
      3. Clemmensen L, et al
      . The CCC2000 birth cohort study of register-based family history of mental disorders and psychotic experiences in offspring. Schizophr Bull 2015;41:1084–94.doi:10.1093/schbul/sbu167pmid:http://www.ncbi.nlm.nih.gov/pubmed/25452427
      OpenUrlCrossRefPubMed
    52. ↵
      1. Kaczkurkin AN,
      2. Park SS,
      3. Sotiras A, et al
      . Evidence for dissociable linkage of dimensions of psychopathology to brain structure in youths. Am J Psychiatry 2019;176:1000–9.doi:10.1176/appi.ajp.2019.18070835
      OpenUrlCrossRef
    53. ↵
      1. Shaffer D, et al
      . A children’s global assessment scale (CGAS). Arch Gen Psychiatry 1983;40:1228–31.doi:10.1001/archpsyc.1983.01790100074010
      OpenUrlCrossRefPubMedWeb of Science
    54. ↵
      1. World Health Organization
      . The ICD-10 classification of mental and behavioural disorders: diagnostic criteria for research. World Health Organization, 1993: 248.
    55. ↵
      1. American Psychiatric Association
      . Diagnostic and statistical manual of mental disorders (DSM-5®. American Psychiatric Pub, 2013: 991.
    56. ↵
      1. Makransky G,
      2. Bilenberg N
      . Psychometric properties of the parent and teacher ADHD rating scale (ADHD-RS): measurement invariance across gender, age, and informant. Assessment 2014;21:694–705.doi:10.1177/1073191114535242pmid:http://www.ncbi.nlm.nih.gov/pubmed/24852496
      OpenUrlCrossRefPubMed
    57. ↵
      1. Constantino JN,
      2. Gruber CP
      . Social responsiveness scale: SRS-2. CA: Western Psychological Services Torrance, 2012.
    58. ↵
      1. Constantino JN,
      2. Davis SA,
      3. Todd RD, et al
      . Validation of a brief quantitative measure of autistic traits: comparison of the social responsiveness scale with the autism diagnostic interview-revised. J Autism Dev Disord 2003;33:427–33.doi:10.1023/A:1025014929212
      OpenUrlCrossRefPubMedWeb of Science
    59. ↵
      1. Achenbach TM
      . Manual for the ASEBA school-age forms & profiles. BurlingtonRescorla LA: University of Vermont, Research Center for Children, Youth, & Families, 2001.
    60. ↵
      1. Bilenberg N
      . The child behavior checklist (CBCL) and related material: standardization and validation in Danish population based and clinically based samples. Acta Psychiatr Scand Suppl 1999;398:2–52.doi:10.1111/j.1600-0447.1999.tb10703.xpmid:http://www.ncbi.nlm.nih.gov/pubmed/10687023
      OpenUrlPubMed
    61. ↵
      1. Niclasen J,
      2. Teasdale TW,
      3. Andersen A-MN, et al
      . Psychometric properties of the Danish strength and difficulties questionnaire: the SDQ assessed for more than 70,000 raters in four different cohorts. PLoS One 2012;7:e32025. doi:10.1371/journal.pone.0032025pmid:http://www.ncbi.nlm.nih.gov/pubmed/22384129
      OpenUrlCrossRefPubMed
    62. ↵
      1. McConaughy SH ATM
      . Manual for the test observation form for ages 2-18. Burlington: University of Vermont, Center for Children, Youth, & Families, 2004.
    63. ↵
      1. Brasholt M,
      2. Chawes B,
      3. Kreiner-Møller E, et al
      . Objective assessment of levels and patterns of physical activity in preschool children. Pediatr Res 2013;74:333–8.doi:10.1038/pr.2013.99pmid:http://www.ncbi.nlm.nih.gov/pubmed/23770920
      OpenUrlPubMed
    64. ↵
      1. Rago D,
      2. Rasmussen MA,
      3. Lee-Sarwar KA, et al
      . Fish-Oil supplementation in pregnancy, child metabolomics and asthma risk. EBioMedicine 2019;46:399–410.doi:10.1016/j.ebiom.2019.07.057
      OpenUrl
    65. ↵
      1. Chawes BL,
      2. Giordano G,
      3. Pirillo P, et al
      . Neonatal urine metabolic profiling and development of childhood asthma. Metabolites 2019;9. doi:doi:10.3390/metabo9090185. [Epub ahead of print: 16 09 2019].doi:10.3390/metabo9090185pmid:http://www.ncbi.nlm.nih.gov/pubmed/31527391
      OpenUrlPubMed
    66. ↵
      1. Stokholm J,
      2. Blaser MJ,
      3. Thorsen J, et al
      . Maturation of the gut microbiome and risk of asthma in childhood. Nat Commun 2018;9:141. doi:10.1038/s41467-017-02573-2pmid:http://www.ncbi.nlm.nih.gov/pubmed/29321519
      OpenUrlCrossRefPubMed
    67. ↵
      1. Thysen AH,
      2. Waage J,
      3. Larsen JM, et al
      . Distinct immune phenotypes in infants developing asthma during childhood. Sci Transl Med 2020;12. doi:doi:10.1126/scitranslmed.aaw0258. [Epub ahead of print: 05 02 2020].doi:10.1126/scitranslmed.aaw0258pmid:http://www.ncbi.nlm.nih.gov/pubmed/32024797
      OpenUrlPubMed
    68. ↵
      1. Bisgaard H,
      2. Pipper CB,
      3. Bønnelykke K
      . Endotyping early childhood asthma by quantitative symptom assessment. J Allergy Clin Immunol 2011;127:1155–64.doi:10.1016/j.jaci.2011.02.007
      OpenUrlCrossRefPubMedWeb of Science
    69. ↵
      1. Bisgaard H,
      2. Hermansen MN,
      3. Buchvald F, et al
      . Childhood asthma after bacterial colonization of the airway in neonates. N Engl J Med 2007;357:1487–95.doi:10.1056/NEJMoa052632pmid:http://www.ncbi.nlm.nih.gov/pubmed/17928596
      OpenUrlCrossRefPubMedWeb of Science
    70. ↵
      1. Bisgaard H,
      2. Nielsen KG
      . Plethysmographic measurements of specific airway resistance in young children. Chest 2005;128:355–62.doi:10.1378/chest.128.1.355
      OpenUrlCrossRefPubMedWeb of Science
    71. ↵
      1. Arianto L,
      2. Hallas H,
      3. Stokholm J, et al
      . Multiple breath washout for diagnosing asthma and persistent wheeze in young children. Ann Am Thorac Soc 2019;16:599–605.doi:10.1513/AnnalsATS.201807-503OCpmid:http://www.ncbi.nlm.nih.gov/pubmed/30580555
      OpenUrlPubMed
    72. ↵
      1. Kreiner-Møller E,
      2. Chawes BLK,
      3. Caye-Thomasen P, et al
      . Allergic rhinitis is associated with otitis media with effusion: a birth cohort study. Clin Exp Allergy 2012;42:1615–20.doi:10.1111/j.1365-2222.2012.04038.xpmid:http://www.ncbi.nlm.nih.gov/pubmed/23106661
      OpenUrlCrossRefPubMed
    73. ↵
      1. Schoos A-MM,
      2. Chawes BL,
      3. Rasmussen MA, et al
      . Atopic endotype in childhood. J Allergy Clin Immunol 2016;137:844–51.doi:10.1016/j.jaci.2015.10.004pmid:http://www.ncbi.nlm.nih.gov/pubmed/26597163
      OpenUrlPubMed
    74. ↵
      1. Hanifin JM RG
      . Diagnostic features of atopic dermatitis. Acta Derm Venereol 1980;92:44–7.
      OpenUrl
    75. ↵
      Severity scoring of atopic dermatitis: the SCORAD index. consensus report of the European Task force on atopic dermatitis. Dermatology 1993;186:23–31.
      OpenUrlCrossRefPubMedWeb of Science
    76. ↵
      1. Bisgaard H,
      2. Halkjaer LB,
      3. Hinge R, et al
      . Risk analysis of early childhood eczema. J Allergy Clin Immunol 2009;123:1355–60.doi:10.1016/j.jaci.2009.03.046pmid:http://www.ncbi.nlm.nih.gov/pubmed/19501236
      OpenUrlCrossRefPubMedWeb of Science
    77. ↵
      1. Halkjaer LB,
      2. Loland L,
      3. Buchvald FF, et al
      . Development of atopic dermatitis during the first 3 years of life: the Copenhagen prospective study on asthma in childhood cohort study in high-risk children. Arch Dermatol 2006;142:561–6.doi:10.1001/archderm.142.5.561pmid:http://www.ncbi.nlm.nih.gov/pubmed/16702493
      OpenUrlCrossRefPubMedWeb of Science
    78. ↵
      1. Bjarnadóttir E,
      2. Stokholm J,
      3. Chawes B, et al
      . Determinants of neurodevelopment in early childhood - results from the Copenhagen prospective studies on asthma in childhood (COPSAC2010) mother-child cohort. Acta Paediatr 2019;108:1632–41.doi:10.1111/apa.14753pmid:http://www.ncbi.nlm.nih.gov/pubmed/30748036
      OpenUrlPubMed
    79. ↵
      1. Frankenburg WK,
      2. Dodds J,
      3. Archer P
      . The Denver II: a major revision and restandardization of the Denver developmental screening test. Pediatrics 1992;89:91–7.
      OpenUrlAbstract/FREE Full Text
    80. ↵
      1. WHO Multicentre Growth Reference Study Group
      . Who motor development study: windows of achievement for six gross motor development milestones. Acta Paediatr Suppl 2006;450:86–95.doi:10.1111/j.1651-2227.2006.tb02379.xpmid:http://www.ncbi.nlm.nih.gov/pubmed/16817682
      OpenUrlPubMed
    81. ↵
      1. Bleses D,
      2. Vach W,
      3. Slott M, et al
      . The Danish communicative developmental inventories: validity and main developmental trends. J Child Lang 2008;35:651–69.doi:10.1017/S0305000907008574
      OpenUrlCrossRefPubMedWeb of Science
    82. ↵
      1. Squires J,
      2. Bricker DD,
      3. Twombly E
      . Ages & Stages Questionnaires: A Parent-completed Child Monitoring System. Brookes Pub, 2009: 170.
    83. ↵
      1. Alexandre JL,
      2. Lange A-M,
      3. Bilenberg N, et al
      . The ADHD rating scale-IV preschool version: factor structure, reliability, validity, and standardisation in a Danish community sample. Res Dev Disabil 2018;78:125–35.doi:10.1016/j.ridd.2018.05.006pmid:http://www.ncbi.nlm.nih.gov/pubmed/29853334
      OpenUrlPubMed
    84. ↵
      1. Wechsler D
      . Wechsler intelligence scale for children. 4th edn. Pearson, 2010.
    85. ↵
      1. Dalsgaard S,
      2. McGrath J,
      3. Østergaard SD, et al
      . Association of mental disorder in childhood and adolescence with subsequent educational achievement. JAMA Psychiatry 2020;77:797.doi:10.1001/jamapsychiatry.2020.0217pmid:http://www.ncbi.nlm.nih.gov/pubmed/32211833
      OpenUrlPubMed
    86. ↵
      1. Burt KB,
      2. Van Dulmen MHM,
      3. Carlivati J, et al
      . Mediating links between maternal depression and offspring psychopathology: the importance of independent data. J Child Psychol Psychiatry 2005;46:490–9.doi:10.1111/j.1469-7610.2004.00367.xpmid:http://www.ncbi.nlm.nih.gov/pubmed/15845129
      OpenUrlCrossRefPubMedWeb of Science
    87. ↵
      1. Johns LC,
      2. van Os J
      . The continuity of psychotic experiences in the general population. Clin Psychol Rev 2001;21:1125–41.doi:10.1016/S0272-7358(01)00103-9
      OpenUrlCrossRefPubMedWeb of Science
    88. ↵
      1. Kelleher I,
      2. Connor D,
      3. Clarke MC, et al
      . Prevalence of psychotic symptoms in childhood and adolescence: a systematic review and meta-analysis of population-based studies. Psychol Med 2012;42:1857–63.doi:10.1017/S0033291711002960pmid:http://www.ncbi.nlm.nih.gov/pubmed/22225730
      OpenUrlCrossRefPubMed
    89. ↵
      1. Rimvall MK,
      2. van Os J,
      3. Rask CU, et al
      . Psychotic experiences from preadolescence to adolescence: when should we be worried about adolescent risk behaviors? Eur Child Adolesc Psychiatry 2020;29:1251-1264.doi:10.1007/s00787-019-01439-wpmid:http://www.ncbi.nlm.nih.gov/pubmed/31732797
      OpenUrlPubMed
    90. ↵
      1. Vestergaard MB,
      2. Jensen ML,
      3. Arngrim N, et al
      . Higher physiological vulnerability to hypoxic exposure with advancing age in the human brain. J Cereb Blood Flow Metab 2020;40:341–53.doi:10.1177/0271678X18818291pmid:http://www.ncbi.nlm.nih.gov/pubmed/30540217
      OpenUrlPubMed

    Footnotes

    • PM and JBR are joint first authors.

    • BHE and HB are joint senior authors.

    • Contributors HB was overall responsible for designing and conducting the COPSAC2010 cohort. HB is the sponsor and principal investigator of the study. HB, KB, BHE and BYG have conceived the idea and promoted the concept of the COPSYCH study with contributions from BC and JS. BF, JRMJ, NB and CP were involved in designing the cognitive and psychopathological part of the study. BHE, JMR, HL, MV and UL were involved in planning the MRI sequences and MRI data processing. MES, DS and NF were key personal in planning and conducting the study, including data handling. JBR and PM were the principal clinical investigators of the project. The manuscript was drafted by PM, JBR, RV, JRMJ and BHE. PM and JBR contributed equally to this paper and share first authorship. BHE and HB share senior authorship. All authors have contributed to the description of the study and have made critical revision of the manuscript. All authors have read and approved the final version of the manuscript.

    • Funding This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 946228)

    • Competing interests BHE is part of the Advisory Board of Eli Lilly Denmark A/S, JanssenCilag, Lundbeck Pharma A/S and Takeda Pharmaceutical Company; and has received lecture fees from Bristol Myers Squibb, Otsuka Pharma Scandinavia AB, Eli Lilly Company, Boehringer Ingelheim Danmark A/S and Lundbeck Pharma A/S.

    • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Author note PM and JBR are joint first authors.