Common Polygenic Variations for Psychiatric Disorders and Cognition in Relation to Brain Morphology in the General Pediatric Population (2023)

Section snippets

Study Population

Participants were drawn from the Generation R Study, an ongoing population-based cohort study of many domains of child development.20 As part of the cohort’s MRI study, 3,992 children were scanned from March 2013 through November 2015, corresponding to visits of the 9- to-11-year-old Generation R sample.21 Of these children, 3,937 had images that were reconstructed using FreeSurfer 6.0 ( One hundred thirty-one children were excluded due to the use of a

Sample Characteristics

A total of 1,139 children were included in the present study (561 girls [49.30%]), and the mean age was 10.16 years (SD 0.60, range 8.72–11.99).

Effects of PGS on Brain Morphology

Figure1 presents a summary of the associations between the PGS for psychiatric disorders and the PGS for cognition calculated at 6 priors and brain volumes. Full results for these associations are presented in TableS2, available online.

No significant associations were observed between PGSs for SCZ and BD and brain measurements.

Greater genetic


We examined whether polygenic susceptibility for psychiatric disorders and cognition was associated with brain morphology in children. We found a consistent pattern of results across priors, indicating that the polygenic risk for ADHD was negatively associated with caudate volume, with the finding of a prior of 0.01 surviving multiple testing correction. Polygenic susceptibility for intelligence and EA showed a positive relation with TBV that was consistent across all priors used, although

  • Polygenic risk score for five major psychiatric disorders associated with volume of distinct brain regions in the general population

    2023, Biological Psychology

    Risk genes and abnormal brain structural indices of psychiatric disorders have been extensively studied. However, whether genetic risk influences brain structure in the general population has been rarely studied. The current study enrolled 483 young Chinese adults, calculated their polygenic risk scores (PRS) for psychiatric disorders based on Psychiatric Genomics Consortium GWAS results, and examined the association between PRSs and brain volume. We found that PRSs were associated with the volume of many brain regions, with differences between PRS for different disorder, calculated at different threshold, and calculated using European or East Asian ancestry. Of them, the PRS for Major Depressive Disorder based on European ancestry was positively associated with right temporal gyrus; the PRS for schizophrenia based on East Asian ancestry was negatively associated with right precentral and postcentral gyrus; the PRS for schizophrenia based on European ancestry was positively associated with right superior temporal gyrus. All these brain regions are critical for corresponding disorders. However, no significant associations were found between PRS for Autism Spectrum Disorder / Bipolar Disorder and brain volume; and the association between PRS for Attention Deficit Hyperactivity Disorder at different thresholds and brain volume was inconsistent. These findings suggest distinct brain mechanisms underlying different psychiatric disorders.

  • Twin studies to GWAS: there and back again

    2021, Trends in Cognitive Sciences

    The field of human behavioral genetics has come full circle. It began by using twin/family studies to estimate the relative importance of genetic and environmental influences. As large-scale genotyping became cost-effective, genome-wide association studies (GWASs) yielded insights about the nature of genetic influences and new methods that use GWAS data to estimate heritability and genetic correlations invigorated the field. Yet these newer GWAS methods have not replaced twin/family studies. In this review, we discuss the strengths and weaknesses of the two approaches with respect to characterizing genetic and environmental influences, measurement of behavioral phenotypes, and evaluation of causal models, with a particular focus on cognitive neuroscience. This discussion highlights how twin/family studies and GWAS complement and mutually reinforce one another.

  • Systematic Review: How the Attention-Deficit/Hyperactivity Disorder Polygenic Risk Score Adds to Our Understanding of ADHD and Associated Traits

    2021, Journal of the American Academy of Child and Adolescent Psychiatry

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    To investigate, by systematically reviewing the literature, whether the attention-deficit/hyperactivity disorder (ADHD) polygenic risk score (PRS) associates with ADHD and related traits in independent clinical and population samples.

    PubMed, Embase and PsychoInfo were systematically searched, alongside study bibliographies. Quality assessments were conducted, and a best-evidence synthesis was applied. Studies were excluded when the predictor was not based on the latest ADHD genome-wide association study, when PRS was not based on genome-wide results, or when the study was a review. Initially, 197 studies were retrieved (February 22, 2020), and a second search (June 3, 2020) yielded a further 49 studies. From both searches, 57 studies were eligible, and 44 studies met inclusion criteria.

    Included studies were published in the last 3 years. Over 80% of the studies were rated excellent, based on a standardized quality assessment. Evidence of associations between ADHD PRS and the following categories was strong: ADHD, ADHD traits, brain structure, education, externalizing behaviors, neuropsychological constructs, physical health, and socioeconomic status. Evidence for associations with addiction, autism, and mental health were mixed and were, so far, inconclusive. Odds ratios for PRS associating with ADHD ranged from 1.22% to 1.76%; variance explained in dimensional assessments of ADHD traits was 0.7% to 3.3%.

    A new wave of high-quality research using the ADHD PRS has emerged. Eventually, symptoms may be partly identified based on PRS, but the current ADHD PRS is useful for research purposes only. This review shows that the ADHD PRS is robust and reliable, associating not only with ADHD but many outcomes and challenges known to be linked to ADHD.

  • Epigenetics in child psychiatry

    2021, Epigenetics in Psychiatry

    Most adult neuropsychiatric disorders begin in childhood, Genes remain constant throughout the lifespan, epigenetic factors are likely contributing to the onset and persistence of symptoms or the transition from one disorder to another from childhood to adulthood.

    Genetic and epigenetic factors conferring risk during brain development contribute to the development of neuropsychiatric disorders. Windows of vulnerability during various phases of neurodevelopment allow other factors such as hypoxia/ischemia, inflammation, toxins to also confer risk, at times using epigenetic mechanisms. These are explored in detail in ADHD, a common neurodevelopmental disorder.

    Recent technological advancements in single-cell RNA sequencing and cortically patterned organoids, generated from fetal fibroblasts-derived (hiPSC) that mimic the longitudinal development of embryonic and early human fetal cortical development, are increasing our understand of neuropathology and epigenetic mechanisms are being explored for treatments.

  • Development of a scale battery for rapid assessment of risk and resilience

    2020, Psychiatry Research

    It is critical to understand the factors that increase risk for development of psychiatric disorders as well as promote resilience against disorders. The current study describes the development of a brief tool for risk/resilience assessment that takes a broad perspective of “risk” and “resilience” to characterize the phenomena, and assesses multiple factors that span intrapersonal, interpersonal, and wide-ranging external contexts. We administered twelve scales (212 items) to a diverse population comprising help-seeking and community participants (N=298; 46% female) in the greater Philadelphia area. We used exploratory item-factor analysis to determine how items cluster across scales. After determining that a seven-factor solution was optimal, computerized adaptive testing (CAT) simulation was run to determine what would happen if the seven full-form factors were administered adaptively. These results were used to select items for short-form scales, producing seven final scales (items=47). Validity was assessed by relating short-form scores to demographics, clinical diagnoses, scales, and criteria; these relationships were also compared to the relationships found with the original scales. Almost all effects detected by the twelve original scales were detected by the substantially abbreviated short-forms. The abbreviated battery shows promise for rapid assessment of multiple risk and resilience parameters, a necessity in large-scale studies.

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  • Polygenic Risk Scores for Developmental Disorders, Neuromotor Functioning During Infancy, and Autistic Traits in Childhood

    2020, Biological Psychiatry

    Impaired neuromotor development is often one of the earliest observations in children with autism spectrum disorder (ASD). We investigated whether a genetic predisposition to developmental disorders was associated with nonoptimal neuromotor development during infancy and examined the genetic correlation between nonoptimal neuromotor development and autistic traits in the general population.

    In a population-based cohort in The Netherlands (2002–2006), we calculated polygenic risk scores (PRSs) for ASD and attention-deficit/hyperactivity disorder (ADHD) using genome-wide association study summary statistics. In 1921 children with genetic data, parents rated autistic traits at 6 years of age. Among them, 1174 children (61.1%) underwent neuromotor examinations (tone, responses, senses, and other observations) during infancy (9–20 weeks of age). We used linear regressions to examine associations of PRSs with neuromotor scores and autistic traits. We performed a bivariate genome-based restricted maximum likelihood analysis to explore whether genetic susceptibility underlies the association between neuromotor development and autistic traits.

    Higher PRSs for ASD were associated with less optimal overall infant neuromotor development, in particular low muscle tone. Higher PRSs for ADHD were associated with less optimal senses. PRSs for ASD and those for ADHD both were associated with autistic traits. The single nucleotide polymorphism–based heritability of overall motor development was 20% (SE= .21) and of autistic traits was 68% (SE= .26). The genetic correlation between overall motor development and autistic traits was .35 (SE= .21, p < .001).

    We found that genetic liabilities for ASD and ADHD covary with neuromotor development during infancy. Shared genetic liability might partly explain the association between nonoptimal neuromotor development during infancy and autistic traits in childhood.

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    Preserved white matter in unmedicated pediatric bipolar disorder

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    White matter (WM) abnormalities have been reported in bipolar disorder (BD) patients, as well as in their non-BD relatives, both children and adults. Although it is considered an emerging vulnerability marker for BD, there are no studies investigating WM alterations in pediatric unmedicated patients and young healthy offspring. In this study, we evaluated the presence of WM alterations in 18 pediatric, non medicated BD patients, as well as in 18 healthy offspring of BD type I parents and 20 healthy controls. 3T DT-MRI data were acquired and scans were processed with tract-based spatial statistics to provide measures of fractional anisotropy and diffusivity. We found no significant differences in WM microstructure between BD patients, healthy offspring and healthy controls. Previous studies that reported WM alterations investigated older subjects, either on medication (BD patients) or with psychiatric diagnoses other than BD (unaffected offspring). Our findings highlight the importance of the understanding of disease ontogeny and brain development dynamics in the search for early vulnerability markers for psychiatric disorders.

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    Polygenic risk for schizophrenia and associated brain structural changes: A systematic review

    Comprehensive Psychiatry, Volume 88, 2019, pp. 77-82

    Genome wide association studies (GWAS) of schizophrenia allow the generation of Polygenic Risk Scores (PRS). PRS can be used to determine the contribution to altered brain structures in this disorder, which have been well described. However, findings from studies using PRS to predict brain structural changes in schizophrenia have been inconsistent. We therefore performed a systematic review to determine the association between schizophrenia PRS and brain structure.

    Following PRISMA systematic review guidelines, databases were searched for literature using key search terms. Inclusion criteria for the discovery sample required case-control schizophrenia GWAS summary statistics from European populations. The target sample was required to be of European ancestry, and have brain structure and genotype information. Quality assessment of the publications was conducted using the Mixed Methods Appraisal Tool for quantitative non-randomised studies.

    A total of seven studies were found to be eligible for review. Five studies found no significant association and two studies found a significant association of schizophrenia PRS with total brain, reduced white matter volume, and globus pallidus volume. However, the latter studies were conducted using smaller discovery (ncases = 9394 ncontrols = 12,462) and target samples compared to the studies with substantially larger discovery (ncases = 33,636 ncontrols = 43,008) and target samples where no association was observed. Taken together, the results suggest that schizophrenia PRS are not significantly associated with brain structural changes in this disorder.

    The lack of significant association between schizophrenia PRS and brain structural changes may indicate that intermediate phenotypes other than brain structure should be the focus of future work. Alternatively, however, the lack of association found here may point to limitations of the current evidence-base, and so point to the need for future better powered studies.

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    Attention-Deficit/Hyperactivity Disorder Polygenic Risk Scores Predict Attention Problems in a Population-Based Sample of Children

    Journal of the American Academy of Child & Adolescent Psychiatry, Volume 53, Issue 10, 2014, pp. 1123-1129.e6

    Clinically, attention-deficit/hyperactivity disorder (ADHD) is characterized by hyperactivity, impulsivity, and inattention and is among the most common childhood disorders. These same traits that define ADHD are variable in the general population, and the clinical diagnosis may represent the extreme end of a continuous distribution of inattentive and hyperactive behaviors. This hypothesis can be tested by assessing the predictive value of polygenic risk scores derived from a discovery sample of ADHD patients in a target sample from the general population with continuous scores of inattention and hyperactivity. In addition, the genetic overlap between ADHD and continuous ADHD scores can be tested across rater and age.

    The Psychiatric Genomics Consortium has performed the largest genome-wide analysis (GWA) study of ADHD so far, including 5,621 clinical patients and13,589 controls. The effects sizes of single nucleotide polymorphisms (SNPs) estimated inthis meta-analysis were used to obtain individual polygenic risk scores in an independentpopulation-based cohort of 2,437 children from the Netherlands Twin Register. The variance explained in Attention Problems (AP) scale scores by the polygenic risk scores wasestimated bylinear mixed modeling.

    The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool- and school-aged children.

    These results indicate genetic overlap between a diagnosis of ADHD and AP scale scores across raters and age groups and provides evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.

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    Maternal thyroid function during pregnancy and child brain morphology: a time window-specific analysis of a prospective cohort

    The Lancet Diabetes & Endocrinology, Volume 7, Issue 8, 2019, pp. 629-637

    Adequate thyroid hormone availability during pregnancy is necessary for optimal fetal brain development. During the first 18–20 weeks of gestation, fetal thyroid hormone availability largely depends on the placental transfer of maternal thyroxine. Although various studies have shown that maternal thyroid dysfunction is associated with suboptimal child neurodevelopmental outcomes, the most vulnerable time window remains to be identified. The aim of this study is to examine the association of maternal thyroid function with child brain morphology and to study whether any association depends on the timing of thyroid assessment.

    This prospective cohort study was part of the Generation R Study in Rotterdam, Netherlands, with a prospective population-based birth cohort. Pregnant women living in Rotterdam with an expected delivery date between April 1, 2002, and Jan 1, 2006, were eligible. Other inclusion criteria were maternal serum thyroid-stimulating hormone (TSH) and free thyroxine (FT4) measurement in early or mid-pregnancy (≤18 weeks) and available brain MRI data for child at age 10 years. Exclusion criteria were pre-existing thyroid disorder, thyroid disorder treatment, twin pregnancy, in-vitro fertilisation-induced pregnancy, and suboptimal-quality MRI data or major incidental finding on MRI. The main outcome was the association between maternal TSH and FT4 concentrations with brain MRI outcomes of children. Regression analyses accounted for gestational age at blood sampling, maternal age, ethnicity, education level, smoking, thyroid peroxidase antibody positivity, child sex, age at MRI, and total intracranial volume. Effect modification by gestational age at blood sampling was also investigated.

    Between Dec 1, 2001, and June 30, 2005, 7069 women were enrolled during early or mid-pregnancy (≤18 weeks of gestation), of whom 5088 were not included because they did not have available data on maternal serum TSH or FT4 concentrations (n=1175), their child did not have brain MRI done (n=3377), or they met exclusion criteria (n=536). Thus, 1981 mother–child pairs were included in the study, with TSH and FT4 concentrations measured during pregnancy at a median of 13·1 weeks of gestation (IQR 12·1–14·5) and offspring brain morphology assessed by MRI at a median age of 9·9 years (9·7–10·2). Maternal TSH had an inverted U-shaped association with offspring total grey matter volume (p=0·007) and with cortical grey matter volume (p=0·022). The association of maternal TSH with child total grey matter volume (pinteraction=0·053) and cortical volume (pinteraction=0·086) differed by the duration of gestation. Analyses stratified for gestational age at blood sampling showed an inverted U-shaped association of maternal TSH with child total grey matter volume and cortical grey matter volume, which was most evident at 8 weeks gestation. After about 14 weeks of gestation, TSH was no longer associated with child brain morphology. Maternal FT4 concentrations were not associated with child total grey matter volume after adjusting for total intracranial volume (p=0·75).

    Here, we show that both low and high maternal thyroid function are associated with smaller child total grey matter and cortical volume. To the best of our knowledge, this study is the first to show that an association with a neurodevelopmental outcome is most evident when maternal thyroid function is measured early in pregnancy. These novel findings suggest that embryonic brain development is particularly vulnerable to altered maternal thyroid function.

    Netherlands Organisation for Health Research and Development and the Sophia Children's Hospital Foundation.

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1. NSHG-PM April 2021 Webinar: Polygenic Architecture of Mental Traits and Disorders
(Nordic Society Human Genetics & Precision Medicine)
2. Genes and Mental Illness: What's the Connection? - A Talk by Dr. Daniel Weinberger
(One Mind)
3. Barbara Franke - How to make sense of genetics for psychiatric disorders? (2013)
4. Daniel Geschwind | 2017 Allen Frontiers Symposium
(The Paul G. Allen Frontiers Group)
5. CARTA: Human Origins: Lessons from Autism Spectrum Disorders
(University of California Television (UCTV))
6. Andrew Grotzinger: Using Genomic SEM to Understand Psychiatric Comorbidity
(Center for Demography of Health and Aging)
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