A common neural signature between genetic and environmental risk for mental illness.

Not everyone is equally likely to experience mental illness. What is the contribution of an individual's genetic background and experiences of childhood adversity to that likelihood? And how do these risk factors interact at the level of the brain? This study explores these questions by investigating the relationship between genetic liability for mental illness, childhood adversity, and cortico-limbic connectivity in a large developmental sample drawn from the ABCD cohort (N = 6535). Canonical Correlation Analysis - a multivariate data-reduction technique - revealed two genetic dimensions of mental illness from the polygenic risk scores for ADHD, Anxiety, Depression, and Psychosis.

Charting structural brain asymmetry across the human lifespan.

Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years.

Attention-deficit/hyperactive disorder pre-adulthood and later adverse health outcomes: The 1987 Finnish birth cohort study.

Whereas attention-deficit/hyperactive disorder (ADHD) is correlated with later risk of depression, anxiety, and substance misuse, the relationship with other health endpoints is uncertain. In a full-nation birth cohort study, we used a phenotype-wide approach to explore the influence of an ADHD diagnosis in childhood/adolescence with later disease and injury. Comprising 53147 (25731 female) children born in a single year, the 1987 Finnish Birth Cohort was generated from linkage of routinely collected data.

Attention-deficit/hyperactive disorder pre-adulthood and later adverse health outcomes: The 1987 Finnish birth cohort study.

Whereas attention-deficit/hyperactive disorder (ADHD) is correlated with later risk of depression, anxiety, and substance misuse, the relationship with other health endpoints is uncertain. In a full-nation birth cohort study, we used a phenotype-wide approach to explore the influence of an ADHD diagnosis in childhood/adolescence with later disease and injury. Comprising 53147 (25731 female) children born in a single year, the 1987 Finnish Birth Cohort was generated from linkage of routinely collected data.

ComBatLS: A Location- and Scale-Preserving Method for Multi-Site Image Harmonization.

Recent study has leveraged massive datasets and advanced harmonization methods to construct normative models of neuroanatomical features and benchmark individuals' morphology. However, current harmonization tools do not preserve the effects of biological covariates including sex and age on features' variances; this failure may induce error in normative scores, particularly when such factors are distributed unequally across sites. Here, we introduce a new extension of the popular ComBat harmonization method, ComBatLS, that preserves biological variance in features' locations and scales.

Neurogenetic phenotypes of learning-dependent plasticity for improved perceptual decisions.

Genetics and experience are known to mold our cognitive development. Yet, the interactions between genetics and brain mechanisms that support learning and flexible behavior in the adult human brain remain largely unknown. Here, we test the link between brain-wide gene expression and macroscopic neuroimaging phenotypes of brain plasticity that support our ability to improve perceptual decisions with training.

Genome-wide association meta-analysis of age at onset of walking in over 70,000 infants of European ancestry.

Age at onset of walking is an important early childhood milestone which is used clinically and in public health screening. In this genome-wide association study meta-analysis of age at onset of walking (N = 70,560 European-ancestry infants), we identified 11 independent genome-wide significant loci. SNP-based heritability was 24.

Genomic and Developmental Models to Predict Cognitive and Adaptive Outcomes in Autistic Children.

Importance: Although early signs of autism are often observed between 18 and 36 months of age, there is considerable uncertainty regarding future development. Clinicians lack predictive tools to identify those who will later be diagnosed with co-occurring intellectual disability (ID).

Objective: To predict ID in children diagnosed with autism.

Breastfeeding Duration and Child Development.

Importance: Detecting and addressing potentially modifiable factors associated with healthy development is key to optimizing a child's potential. When investigating the outcomes of child development, it is important to account for disparities in feeding practices and avoid confounding bias.

Objectives: To estimate the independent association between breastfeeding and attainment of developmental milestones or neurodevelopmental conditions.

Polygenic scores for autism are associated with reduced neurite density in adults and children from the general population.

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4928).

Contribution of autosomal rare and de novo variants to sex differences in autism.

Autism is four times more prevalent in males than females. To study whether this reflects a difference in genetic predisposition attributed to autosomal rare variants, we evaluated sex differences in effect size of damaging protein-truncating and missense variants on autism predisposition in 47,061 autistic individuals using a liability model with differing thresholds. Given the sex differences in the rates of cognitive impairment among autistic individuals, we also compared effect sizes of rare variants between individuals with and without cognitive impairment or motor delay.

Examining the role of common variants in rare neurodevelopmental conditions.

Although rare neurodevelopmental conditions have a large Mendelian component, common genetic variants also contribute to risk. However, little is known about how this polygenic risk is distributed among patients with these conditions and their parents nor its interplay with rare variants. It is also unclear whether polygenic background affects risk directly through alleles transmitted from parents to children, or whether indirect genetic effects mediated through the family environment also play a role.

Integrating genomic variants and developmental milestones to predict cognitive and adaptive outcomes in autistic children.

Although the first signs of autism are often observed as early as 18-36 months of age, there is a broad uncertainty regarding future development, and clinicians lack predictive tools to identify those who will later be diagnosed with co-occurring intellectual disability (ID). Here, we developed predictive models of ID in autistic children (n=5,633 from three cohorts), integrating different classes of genetic variants alongside developmental milestones. The integrated model yielded an AUC ROC=0.

Child maltreatment as a transdiagnostic risk factor for the externalizing dimension: a Mendelian randomization study.

Observational studies suggest that child maltreatment increases the risk of externalizing spectrum disorders such as attention deficit hyperactivity disorder (ADHD), conduct disorder (CD), antisocial personality disorder (ASPD), and substance use disorder (SUD). Yet, only few of such associations have been investigated by approaches that provide strong evidence for causation, such as Mendelian Randomization (MR). Establishing causal inference is essential given the growing recognition of gene-environment correlations, which can confound observational research in the context of childhood maltreatment.

ComBatLS: A location- and scale-preserving method for multi-site image harmonization.

Recent work has leveraged massive datasets and advanced harmonization methods to construct normative models of neuroanatomical features and benchmark individuals' morphology. However, current harmonization tools do not preserve the effects of biological covariates including sex and age on features' variances; this failure may induce error in normative scores, particularly when such factors are distributed unequally across sites. Here, we introduce a new extension of the popular ComBat harmonization method, ComBatLS, that preserves biological variance in features' locations and scales.

Using Organoids to Model Sex Differences in the Human Brain.

Sex differences are widespread during neurodevelopment and play a role in neuropsychiatric conditions such as autism, which is more prevalent in males than females. In humans, males have been shown to have larger brain volumes than females with development of the hippocampus and amygdala showing prominent sex differences. Mechanistically, sex steroids and sex chromosomes drive these differences in brain development, which seem to peak during prenatal and pubertal stages.

Contribution of autosomal rare and variants to sex differences in autism.

Autism is four times more prevalent in males than females. To study whether this reflects a difference in genetic predisposition attributed to autosomal rare variants, we evaluated the sex differences in effect size of damaging protein-truncating and missense variants on autism predisposition in 47,061 autistic individuals, then compared effect sizes between individuals with and without cognitive impairment or motor delay. Although these variants mediated differential likelihood of autism with versus without motor or cognitive impairment, their effect sizes on the liability scale did not differ significantly by sex exome-wide or in genes sex-differentially expressed in the cortex.

Genetics of gambling disorder and related phenotypes: The potential uses of polygenic and multifactorial risk models to enable early detection and improve clinical outcomes.

Gambling Disorder (GD) is an impactful behavioural addiction for which there appear to be underpinning genetic contributors. Twin studies show significant GD heritability results and intergenerational transmission show high rates of transmission. Recent developments in polygenic and multifactorial risk prediction modelling provide promising opportunities to enable early identification and intervention for at risk individuals.

Childhood abuse neglect and risk for major psychiatric disorders.

Background: Childhood maltreatment (CM) is a strong risk factor for psychiatric disorders but serves in its current definitions as an umbrella for various fundamentally different childhood experiences. As first step toward a more refined analysis of the impact of CM, our objective is to revisit the relation of abuse and neglect, major subtypes of CM, with symptoms across disorders.

Methods: Three longitudinal studies of major depressive disorder (MDD, = 1240), bipolar disorder (BD, = 1339), and schizophrenia (SCZ, = 577), each including controls ( = 881), were analyzed.

The genetic relationships between brain structure and schizophrenia.

Genetic risks for schizophrenia are theoretically mediated by genetic effects on brain structure but it has been unclear which genes are associated with both schizophrenia and cortical phenotypes. We accessed genome-wide association studies (GWAS) of schizophrenia (N = 69,369 cases; 236,642 controls), and of three magnetic resonance imaging (MRI) metrics (surface area, cortical thickness, neurite density index) measured at 180 cortical areas (N = 36,843, UK Biobank). Using Hi-C-coupled MAGMA, 61 genes were significantly associated with both schizophrenia and one or more MRI metrics.

The molecular genetic landscape of human brain size variation.

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW.