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Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the "in vivo" quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6-18, n = 216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence. (Contains 3 figures and 4 tables.)

Competing Interests: Competing interests:: Lena Palaniyappan has received research support from the Monique H. Bourgeois Chair in Developmental Disorders; grants from the Graham Boeckh Foundation (Douglas Research Centre, McGill University) and the Canadian Institutes of Health Research; royalties from Oxford University Press and SPMM Course, UK; and speaker’s honoraria from Janssen Canada and Otsuka Canada. He reports a salary award from the Fonds de recherche du Québec-Santé. He is a member of the editorial board of the Canadian Journal of Psychiatry. He is the coeditor in chief of JPN; he had no role in editorial decision-making for this article. No other competing interests were declared.

Maternal smoking during pregnancy (MSDP) is considered a risk factor for ADHD. While the mechanisms underlying this association are not well understood, MSDP may impact the developing brain in ways that lead to ADHD. Here, we investigated the effect of prenatal smoking exposure on cortical brain structures in children with ADHD using two methods of assessing prenatal exposure: maternal recall and epigenetic typing. Exposure groups were defined according to: (1) maternal recall (+MSDP: n = 24; -MSDP: n = 85) and (2) epigenetic markers (EM) (+EM: n = 14 -EM: n = 21). CIVET-1.1.12 and RMINC were used to acquire cortical brain measurements and perform statistical analyses, respectively. The vertex with highest significance was tested for association with Continuous Performance Test (CPT) dimensions. While no differences of brain structures were identified between +MSDP and -MSDP, +EM children (n = 10) had significantly smaller surface area in the right orbitofrontal cortex (ROFc), middle temporal cortex (RTc) and parahippocampal gyrus (RPHg) (15% FDR) compared to -EM children (n = 20). Cortical surface area in the RPHg significantly correlated with CPT commission errors T-scores. This study suggests that molecular markers may better define exposure to environmental risks, as compared to human recall., Competing Interests: Declaration of competing interest Dr B. Chaumette has received research funding from the foundation Bettencourt Schueller, speaking fees from Janssen-Cilag, Lundbeck, and Eisai outside the submitted work. Dr N. Grizenko is a member of the advisory board of Purdue and Shire. Dr R. Joober is on the advisory boards and speakers’ bureaus of Pfizer, Janssen, Ortho, BMS, Sunovion, Otsuka, Lundbeck, Perdue and Myelin. He has received grant funding from them and from AstraZeneca and HLS. He has received honoraria from Janssen Canada, Shire, Lundbeck, Otsuka, Pfizer, and from Perdue for CME presentations and royalties for Henry Stewart talks. The other authors report no biomedical financial interests nor potential conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The rivers of Guadeloupe and Martinique (French West Indies) show high levels of chlordecone (CLD) contamination. This persistent molecule has a dramatic impact on both aquatic ecosystems and human health. In these rivers, epilithic biofilms are the main endogenous primary producers and represent a central food source for fish and crustaceans. Recently, their viscoelastic properties have been shown to be effective in bio-assessing pollution in tropical environments. As these properties are closely related to the biochemical composition of the biofilms, biochemical (fatty acids, pigments, extracellular polymeric substances (EPS) monosaccharides) and molecular markers (T-RFLP fingerprints of bacteria, archaea and eukaryotes) were investigated. Strong links between CLD pollution and both biofilm biochemistry and microbial community composition were found. In particular, high levels of CLD were linked with modified exo-polysaccharides corresponding to carbohydrates with enhanced adsorption and adhesion properties. The observed change probably resulted from a preferential interaction between CLD and sugars and/or a differential microbial secretion of EPS in response to the pollutant. These changes were expected to impact viscoelastic properties of epilithic biofilms highlighting the effect of CLD pollution on biofilm EPS matrix. They also suggested that microorganisms implement a CLD scavenging strategy, providing new insights on the role of EPS in the adaptation of microorganisms to CLD-polluted environments., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2022 Elsevier B.V. All rights reserved.)

In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1-3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)

Genomic copy number variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs > 50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of intelligence quotient when duplicated or deleted, respectively. Effect sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Background: Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction., Aims: Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician-patient interaction., Method: Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback., Results: All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician-patient interaction., Conclusions: The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician-patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.

Background: Although there is some evidence for a normalization of brain structure following exposure to ADHD medication, literature on the effects of duration and dose of continued use on the brain is scarce. Here, we investigated the association between cumulative exposure to medication (range 1 week to 4.69 years) and cortical structures and subcortical volumes in a clinical sample of children with ADHD taking medication (n = 109). To the best of our knowledge, this is the first structural MRI study investigating the effects of cumulative exposure to medication on subregional volumes in children treated for ADHD., Methods: Cumulative exposure to ADHD medication (CEM) was defined as the product of duration on medication (days) and dose (mg/day), yielding the area under the curve (total mg). Cortical thickness and surface area measurements (CIVET-1.1.12), and subcortical volumes in 51 regions (MAGeT-Brain) were analyzed using general linear modelling., Results: Significant effects of CEM were found in two subregions of the left hippocampus, the CA1 (df = 95; q = 0.003) and the strata radiatum/lacunosum/moleculare (df = 95; q = 0.003). Specifically, higher CEM was associated with smaller volumes within these subregions. No effects of medication exposure were detected on cortical thickness or surface area., Conclusions: Although this study is cross-sectional, the results found within this sample of children show that prolonged ADHD medication use at higher doses is significantly associated with smaller hippocampus volumes in specific subregions. More research is required to determine whether these results are reproduced in other samples of children of ADHD, and further, whether these are beneficial or off-target effects of the medication., (Copyright © 2021. Published by Elsevier Inc.)

Maternal antenatal depression strongly influences child mental health but with considerable inter-individual variation that is, in part, linked to genotype. The challenge is to effectively capture the genotypic influence. We outline a novel approach to describe genomic susceptibility to maternal antenatal depression focusing on child emotional/behavioral difficulties. Two cohorts provided measures of maternal depression, child genetic variation, and child mental health symptoms. We constructed a conventional polygenic risk score (PRS) for attention-deficit/hyperactivity disorder (ADHD) (PRSADHD) that significantly moderated the association between maternal antenatal depression and internalizing problems at 60 months (p = 2.94 × 10-4, R2 = .18). We then constructed an interaction PRS (xPRS) based on a subset of those single nucleotide polymorphisms from the PRSADHD that most accounted for the moderation of the association between maternal antenatal depression and child outcome. The interaction between maternal antenatal depression and this xPRS accounted for a larger proportion of the variance in child emotional/behavioral problems than models based on any PRSADHD (p = 5.50 × 10-9, R2 = .27), with similar findings in the replication cohort. The xPRS was significantly enriched for genes involved in neuronal development and synaptic function. Our study illustrates a novel approach to the study of genotypic moderation on the impact of maternal antenatal depression on child mental health and highlights the utility of the xPRS approach. These findings advance our understanding of individual differences in the developmental origins of mental health.

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one's occupation., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Background: Are cognitive and biological variables useful for predicting future behavioral outcomes?, Method: In two independent groups, we measured a set of cognitive (fluid and crystallized intelligence, working memory, and attention control) and biological (cortical thickness and cortical surface area) variables on two occasions separated by six months, to predict behavioral outcomes of interest (performance on an adaptive version of the n-back task) measured twelve and eighteen months later. We followed three stages: discovery, validation, and generalization. In the discovery stage, cognitive/biological variables and the behavioral outcome of interest were assessed in a group of individuals (in-sample). In the validation stage, the cognitive and biological variables were related with a parallel version of the behavioral outcome assessed several months later. In the generalization stage, the validation findings were tested in an independent group of individuals (out-of-sample)., Results: The key finding revealed that cortical surface area variations within the right dorsolateral prefrontal cortex predict the behavioral outcome of interest in both groups, whereas the cognitive variables failed to show reliable predictive validity., Conclusions: Individual differences in biological variables might predict future behavioral outcomes better than cognitive variables concurrently correlated with these behavioral outcomes.