Effect of early adversity and childhood internalizing symptoms on brain structure in young men

- Importance: Early adversity is an important risk factor that relates to internalizing symptoms and altered brain structure. - Objective: To assess the direct effects of early adversity and child internalizing symptoms (ie, depression, anxiety) on cortical gray matter (GM) volume, as well as the extent to which early adversity associates with variation in cortical GM volume indirectly via increased levels of internalizing symptoms. - Design, Setting, and Participants: A prospective investigation of associations between adversity within the first 6 years of life, internalizing symptoms during childhood and early adolescence, and altered brain structure in late adolescence (age, 18-21 years) was conducted in a community-based birth cohort in England (Avon Longitudinal Study of Parents and Children). Participants from the cohort included 494 mother-son pairs monitored since the mothers were pregnant (estimated date of delivery between April 1, 1991, and December 31, 1992). Data collection for the present study was conducted between April 1, 1991, and November 30, 2010; the neuroimaging data were collected between September 1, 2010, and November 30, 2012, and data analyses for the present study occurred between January 25, 2013, and February 15, 2015. Risk factors were adversity within the first 6 years of the child’s life (including prenatal exposure) and the child’s internalizing symptoms between age 7 and 13 years. - Exposures: Early childhood adversity. - Main Outcomes and Measures: The main outcome was GM volume of cortical regions previously associated with major depression measured through T1-weighted magnetic resonance images collected in late adolescence. - Results: Among 494 young men included in this analysis, early adversity was directly associated with lower GM volumes in the anterior cingulate cortex (β = −.18; P = .01) and higher GM volume in the precuneus (β = .18; P = .009). Childhood internalizing symptoms were associated with lower GM volume in the right superior frontal gyrus (β = −.20; P = .002). Early adversity was also associated with higher levels of internalizing symptoms (β = .37; P < .001), which, in turn, were associated with lower superior frontal gyrus volume (ie, an indirect effect) (β = −.08; 95% CI, −0.14 to −0.01; P = .02). - Conclusions and Relevance: Adversity early in life was associated with higher levels of internalizing symptoms as well as with altered brain structure. Early adversity was related to variation in brain structure both directly and via increased levels of internalizing symptoms. These findings may suggest that some of the structural variation often attributed to depression might be associated with early adversity in addition to the effect of depression

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes

Subcortical volumes across the lifespan: data from 18,605 healthy individuals aged 3-90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.Education and Child Studie

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging.

As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability

The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project

Background: Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) Consortium aims to clarify the role of genetic variation in brain abnormalities underlying schizophrenia. This article describes the GENUS Consortium sample collection. Methods: We identified existing samples collected for schizophrenia studies consisting of patients, controls, and/or individuals at familial high-risk (FHR) for schizophrenia. Samples had single nucleotide polymorphism (SNP) array data or genomic DNA, clinical and demographic data, and neuropsychological and/or brain magnetic resonance imaging (MRI) data. Data were subjected to quality control procedures at a central site. Results: Sixteen research groups contributed data from 5199 psychosis patients, 4877 controls, and 725 FHR individuals. All participants have relevant demographic data and all patients have relevant clinical data. The sex ratio is 56.5% male and 43.5% female. Significant differences exist between diagnostic groups for premorbid and current IQ (both p &lt;1×10-10). Data from a diversity of neuropsychological tests are available for 92% of participants, and 30% have structural MRI scans (half also have diffusion-weighted MRI scans). SNP data are available for 76% of participants. The ancestry composition is 70% European, 20% East Asian, 7% African, and 3% other. Conclusions: The Consortium is investigating the genetic contribution to brain phenotypes in a schizophrenia sample collection of &gt;. 10,000 participants. The breadth of data across clinical, genetic, neuropsychological, and MRI modalities provides an important opportunity for elucidating the genetic basis of neural processes underlying schizophrenia. © 2017 Elsevier B.V

Greater male than female variability in regional brain structure across the lifespan

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders

Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium.

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia

Preserving accuracy in GenBank

GenBank, the public repository for nucleotide and protein sequences, is a critical resource for molecular biology, evolutionary biology, and ecology. While some attention has been drawn to sequence errors, common annotation errors also reduce the value of this database. In fact, for organisms such as fungi, which are notoriously difficult to identify, up to 20% of DNA sequence records may have erroneous lineage designations in GenBank. Gene function annotation in protein sequence databases is similarly error-prone. Because identity and function of new sequences are often determined by bioinformatic analyses, both types of errors are propagated into new accessions, leading to long-term degradation of the quality of the database. Currently, primary sequence data are annotated by the authors of those data, and can only be reannotated by the same authors. This is inefficient and unsustainable over the long term as authors eventually leave the field. Although it is possible to link third-party databases to GenBank records, this is a short-term solution that has little guarantee of permanence. Similarly, the current third-party annotation option in GenBank (TPA) complicates rather than solves the problem by creating an identical record with a new annotation, while leaving the original record unflagged and unlinked to the new record. Since the origin of public zoological and botanical specimen collections, an open system of cumulative annotation has evolved, whereby the original name is retained, but additional opinion is directly appended and used for filing and retrieval. This was needed as new specimens and analyses allowed for reevaluation of older specimens and the original depositors became unavailable. The time has come for the public sequence database to incorporate a community-curated, cumulative annotation process that allows third parties to improve the annotations of sequences when warranted by published peer-reviewed analyses.Fil: Bidartondo, Martin I.. Imperial College London; Reino Unido. Royal Botanic Gardens; Reino UnidoFil: Bruns, Thomas D.. University of California at Berkeley; Estados UnidosFil: Blackwell, Meredith. Louisiana State University; Estados UnidosFil: Edwards, Ivan. University of Michigan; Estados UnidosFil: Taylor, Andy F. S.. Swedish University of Agricultural Sciences; SueciaFil: Bianchinotti, Maria Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur; ArgentinaFil: Padamsee, Mahajabeen. University of Minnesota; Estados UnidosFil: Callac, Philippe. Institut National de la Recherche Agronomique; FranciaFil: Lima, Nelson. Universidade do Minho; PortugalFil: White, Merlin M.. Boise State University; Estados UnidosFil: Barreau Daly, Camila. Centre National de la Recherche Scientifique; Francia. Institut National de la Recherche Agronomique; FranciaFil: Juncai, M. A.. Chinese Academy of Sciences; República de ChinaFil: Buyck, Bart. Museum National d'Histoire Naturelle; FranciaFil: Rabeler, Richard K.. University of Michigan; Estados UnidosFil: Liles, Mark R.. Auburn University; Estados UnidosFil: Estes, Dwayne. Austin Peay State University; Estados UnidosFil: Carter, Richard. Valdosta State University; Estados UnidosFil: Herr Jr., J. M.. University of South Carolina; Estados UnidosFil: Chandler, Gregory. University of North Carolina; Estados UnidosFil: Kerekes, Jennifer. University of California at Berkeley; Estados UnidosFil: Cruse Sanders, Jennifer. Salem College Herbarium; Estados UnidosFil: Galán Marquez, R.. Universidad de Alcalá; EspañaFil: Horak, Egon. Zurich Herbarium; SuizaFil: Fitzsimons, Michael. University of Chicago; Estados UnidosFil: Döering, Heidi. Royal Botanic Gardens; Reino UnidoFil: Yao, Su. China Center of Industrial Culture Collection; ChinaFil: Hynson, Nicole. University of California at Berkeley; Estados UnidosFil: Ryberg, Martin. University Goteborg; SueciaFil: Arnold, A. E.. University of Arizona; Estados UnidosFil: Hughes, Karen. University of Tennessee; Estados Unido