Total Cortical Surface Area Research Articles

Breastfeeding duration and brain-body development in 9-10-year-olds: modulating effect of socioeconomic levels.

To investigate relationships of breastfeeding duration with brain structure and adiposity markers in youth and how these relationships are modified by neighborhood socioeconomic environments (SEEs). This was a cross-sectional study of youth enrolled in the Adolescent Brain and Cognitive Development (ABCD) Study® (n = 7511). Mixed effects models examined associations of breastfeeding duration with global brain measures and adiposity markers, adjusting for sociodemographic, pre- and post-natal covariates. Stratified analysis was performed by area deprivation index (ADI) tertiles. Total cortical surface area (SA) (False Discovery Rate - FDR corrected P < 0.001), cortical (FDR corrected P < 0.001) and subcortical gray matter (GM) volume (FDR corrected P < 0.001) increased with increased breastfeeding duration. Body mass index (BMI) z-scores (FDR corrected P = 0.001), waist circumference (FDR corrected P = 0.002) and waist-to-height ratio (WHtR) (FDR corrected P = 0.001) decreased with increased breastfeeding duration. Breastfeeding duration was inversely associated with adiposity in youth from high- and medium- ADI neighborhoods, but positively associated with SA across ADI tertiles. In this cross-sectional study, longer breastfeeding duration was associated with lower adiposity indices, particularly in youth from lower SEEs and greater SA across SEE levels. Longer breastfeeding duration showed long-term associations with brain and body development for offspring. Building on previous findings that longer breastfeeding duration is associated with healthier weight gain, lower obesity risk, and brain white matter development in infancy, our results find longer breastfeeding duration to be associated with lower adiposity indices and greater cortical and subcortical gray matter volume, and cortical surface area during peri-adolescence. Children from lower socioeconomic environments (SEEs) demonstrated stronger negative associations of breastfeeding duration and adiposity indices, and children across SEEs showed positive relationships between breastfeeding duration and cortical surface area. Promoting breastfeeding, particularly among women from lower SEEs would confer long-term benefits to offspring.

Genetic evidence for the causal relationships between migraine, dementia, and longitudinal brain atrophy

BackgroundMigraine is a neurological disease with a significant genetic component and is characterized by recurrent and prolonged episodes of headache. Previous epidemiological studies have reported a higher risk of dementia in migraine patients. Neuroimaging studies have also shown structural brain atrophy in regions that are common to migraine and dementia. However, these studies are observational and cannot establish causality. The present study aims to explore the genetic causal relationship between migraine and dementia, as well as the mediation roles of brain structural changes in this association using Mendelian randomization (MR).MethodsWe collected the genome-wide association study (GWAS) summary statistics of migraine and its two subtypes, as well as four common types of dementia, including Alzheimer’s disease (AD), vascular dementia, frontotemporal dementia, and Lewy body dementia. In addition, we collected the GWAS summary statistics of seven longitudinal brain measures that characterize brain structural alterations with age. Using these GWAS, we performed Two-sample MR analyses to investigate the causal effects of migraine and its two subtypes on dementia and brain structural changes. To explore the possible mediation of brain structural changes between migraine and dementia, we conducted a two-step MR mediation analysis.ResultsThe MR analysis demonstrated a significant association between genetically predicted migraine and an increased risk of AD (OR = 1.097, 95% CI = [1.040, 1.158], p = 7.03 × 10− 4). Moreover, migraine significantly accelerated annual atrophy of the total cortical surface area (-65.588 cm2 per year, 95% CI = [-103.112, -28.064], p = 6.13 × 10− 4) and thalamic volume (-9.507 cm3 per year, 95% CI = [-15.512, -3.502], p = 1.91 × 10− 3). The migraine without aura (MO) subtype increased the risk of AD (OR = 1.091, 95% CI = [1.059, 1.123], p = 6.95 × 10− 9) and accelerated annual atrophy of the total cortical surface area (-31.401 cm2 per year, 95% CI = [-43.990, -18.811], p = 1.02 × 10− 6). The two-step MR mediation analysis revealed that thalamic atrophy partly mediated the causal effect of migraine on AD, accounting for 28.2% of the total effect.DiscussionThis comprehensive MR study provided genetic evidence for the causal effect of migraine on AD and identified longitudinal thalamic atrophy as a potential mediator in this association. These findings may inform brain intervention targets to prevent AD risk in migraine patients.

Association between cortical thickness or surface area and divergent thinking in patients with bipolar disorder.

Divergent thinking is a critical creative cognitive process. Its neural mechanisms have been well-studied through structural and functional imaging in healthy individuals but are less explored in patients with bipolar disorder (BD). Because of the traditional link between creativity and BD, this study investigated the structural correlates of divergent thinking in patients with BD through surface-based morphometry. Fifty-nine patients diagnosed with BD I or BD II (35.3 ± 8.5 years) and 56 age- and sex-matched controls (33.9 ± 7.4 years) were recruited. The participants underwent structural magnetic resonance imaging and an evaluation of divergent thinking by using the Chinese version of the Abbreviated Torrance Test for Adults (ATTA). FreeSurfer 7.0 was used to generate thickness and surface area maps for each participant. Brainwise regression of the association between cortical thickness or surface area and ATTA performance was conducted using general linear models. Divergent thinking performance did not differ significantly between the patients with BD and the healthy controls. In these patients, total ATTA score was negatively correlated with cortical thickness in the right middle frontal gyrus, right occipital, and left precuneus but positively correlated with the surface area of the right superior frontal gyrus. By contrast, total ATTA scores and cortical thickness or surface area were not significantly correlated among the controls. The findings indicate that divergent thinking involves cerebral structures for executive control, mental imagery, and visual processing in patients with BD, and the right prefrontal cortex might be the most crucial of these structures.

Investigation of causal relationships between cortical structure and osteoporosis using two-sample Mendelian randomization.

The mutual interaction between bone characteristics and brain had been reported previously, yet whether the cortical structure has any relevance to osteoporosis is questionable. Therefore, we applied a two-sample bidirectional Mendelian randomization analysis to investigate this relationship. We utilized the bone mineral density measurements of femoral neck (n = 32,735) and lumbar spine (n = 28,498) and data on osteoporosis (7300 cases and 358,014 controls). The global surficial area and thickness and 34 specific functional regions of 51,665 patients were screened by magnetic resonance imaging. For the primary estimate, we utilized the inverse-variance weighted method. The Mendelian randomization-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis were conducted to assess heterogeneity and pleiotropy. We observed suggestive associations between decreased thickness in the precentral region (OR = 0.034, P = 0.003) and increased chance of having osteoporosis. The results also revealed suggestive causality of decreased bone mineral density in femoral neck to declined total cortical surface area (β = 1400.230mm2, P = 0.003), as well as the vulnerability to osteoporosis and reduced thickness in the Parstriangularis region (β = -0.006mm, P = 0.002). Our study supports that the brain and skeleton exhibit bidirectional crosstalk, indicating the presence of a mutual brain-bone interaction.

Longitudinal mapping of the development of cortical thickness and surface area in rhesus macaques during the first three years

Studying dynamic spatiotemporal patterns of early brain development in macaque monkeys is critical for understanding the cortical organization and evolution in humans, given the phylogenetic closeness between humans and macaques. However, due to huge challenges in the analysis of early brain Magnetic Resonance Imaging (MRI) data typically with extremely low contrast and dynamic imaging appearances, our knowledge of the early macaque cortical development remains scarce. To fill this critical gap, this paper characterizes the early developmental patterns of cortical thickness and surface area in rhesus macaques by leveraging advanced computing tools tailored for early developing brains based on a densely sampled longitudinal dataset with 140 rhesus macaque MRI scans seamlessly covering from birth to 36 mo of age. The average cortical thickness exhibits an inverted U-shaped trajectory with peak thickness at around 4.3 mo of age, which is remarkably in line with the age of peak thickness at 14 mo in humans, considering the around 3:1 age ratio of human to macaque. The total cortical surface area in macaques increases monotonically but with relatively lower expansions than in humans. The spatial distributions of thicker and thinner regions are quite consistent during development, with gyri having a thicker cortex than sulci. By 4 mo of age, over 81% of cortical vertices have reached their peaks in thickness, except for the insula and medial temporal cortices, while most cortical vertices keep expanding in surface area, except for the occipital cortex. These findings provide important insights into early brain development and evolution in primates.

Brain folding increases in sharpness and complexity over third trimester-equivalent development

&#x0D; &#x0D; &#x0D; Background and Hypothesis:&#x0D; Gyrification, or convolution, of the cerebral cortex is a promising transdiagnostic marker for early neurodevelopment. Previous studies have related differences in sulcogyral shape to schizophrenia, bipolar disorder, and autism spectrum disorder, but the physical mechanisms underlying these differences remain poorly understood. The focus of this study was to explore decomposed curvature metrics, the principal curvatures, as physically meaningful quantitative biomarkers to track brain development. We hypothesize that the average sharpness and complexity of sulci and gyri, reflected by principal curvatures, increase throughout third trimester-equivalent development.&#x0D; Methods:&#x0D; Cortical surfaces generated from magnetic resonance imaging (MRI) were obtained from the developing Human Connectome Project. Global sharpness was calculated from the principal curvature of maximum magnitude, with average sharpness defined separately for gyral (positive) and sulcal (negative) curvatures. Global complexity of folds (eg., curviness along the length of a fold) was calculated from variance in the principal curvature with minimum magnitude. Trajectory of each summary metric was fit over time using polynomial regression.&#x0D; Results:&#x0D; Forty-three subjects were removed due to incomplete curvature analysis or missing subject information, such that 541 preterm and term-born infants were evaluated with scan age ranging from 27 to 45 weeks postmenstrual age (PMA). Across this developmental range, sharpness and complexity increased until a plateau around term-equivalent. Average sharpness of gyri was best correlated with age of scan (R2 = 0.877).&#x0D; Conclusion and Potential Impact:&#x0D; During the pre- and postnatal development period, total cortical surface area continues to increase after birth, but the overall sharpness and complexity of folding plateaus at ~37 weeks post-menstrual age. Exploring these physically meaningful curvature metrics can provide improved parameters for comparison to mechanistic models of brain folding.&#x0D; &#x0D; &#x0D;

Why weight? Analytic approaches for large-scale population neuroscience data

Population-based neuroimaging studies that feature complex sampling designs enable researchers to generalize their results more widely. However, several theoretical and analytical questions pose challenges to researchers interested in these data. The following is a resource for researchers interested in using population-based neuroimaging data. We provide an overview of sampling designs and describe the differences between traditional model-based analyses and survey-oriented design-based analyses. To elucidate key concepts, we leverage data from the Adolescent Brain Cognitive Development℠ Study (ABCD Study®), a population-based sample of 11,878 9–10-year-olds in the United States. Analyses revealed modest sociodemographic discrepancies between the target population of 9–10-year-olds in the U.S. and both the recruited ABCD sample and the analytic sample with usable structural and functional imaging data. In evaluating the associations between socioeconomic resources (i.e., constructs that are tightly linked to recruitment biases) and several metrics of brain development, we show that model-based approaches over-estimated the associations of household income and under-estimated the associations of caregiver education with total cortical volume and surface area. Comparable results were found in models predicting neural function during two fMRI task paradigms. We conclude with recommendations for ABCD Study® users and users of population-based neuroimaging cohorts more broadly.

Reduced cortical surface area globally and in reward-related cortex is associated with elevated depressive symptoms in preschoolers

BackgroundElevated depressive symptoms in early childhood strongly predict depression onset in youth. Nevertheless, little is known about the neural correlates of these symptoms, information that is key for understanding the early development of depression. As a result, the present study conducted a novel investigation of the association between cortical structure and depressive symptoms in preschoolers. MethodsForty-six preschool age children (Mage = 5.90, SD = 0.75), some (N = 15) at high risk for depression, participated in the study. Data included parent-report of child depressive symptoms and measures of child whole brain and regional cortical structure acquired via 3T MRI. ResultsAfter adjustment for maternal depression, socio-economic status, child age, child sex, and intracranial volume, reduced total cortical surface area and reduced surface area of the lateral orbitofrontal cortex were associated with elevated depressive symptoms. Cortical thickness was not associated with depressive symptoms. LimitationsThe present data are cross-sectional, limiting any causal interpretations. ConclusionsResults suggest that reduced cortical surface area, rather than thickness, is a neural correlate of depressive symptoms in preschoolers. Findings highlight the importance of surface area in reward processing regions (i.e., lateral orbitofrontal cortex) in particular. The present results provide novel insight into early emerging associations between brain structure and features of depression in young children and underscore early childhood as an important developmental period for understanding depression.

School Climate, Cortical Structure, and Socioemotional Functioning: Associations across Family Income Levels.

School climates are important for children's socioemotional development and may also serve as protective factors in the context of adversity. Nevertheless, little is known about the potential neural mechanisms of such associations, as there has been limited research concerning the relation between school climate and brain structure, particularly for brain regions relevant for mental health and socioemotional functioning. Moreover, it remains unclear whether the role of school climate differs depending on children's socioeconomic status. We addressed these questions in baseline data for 9- to 10-year-olds from the Adolescent Brain and Cognitive Development study (analytic sample for socioemotional outcomes, n = 8887), conducted at 21 sites across the United States. Cortical thickness, cortical surface area, and subcortical volume were derived from T1-weighted brain magnetic resonance imaging. School climate was measured by youth report, and socioemotional functioning was measured by both youth and parent report. A positive school climate and higher family income were associated with lower internalizing and externalizing symptoms, with no evidence of moderation. There were no associations between school climate and cortical thickness or subcortical volume, although family income was positively associated with hippocampal volume. For cortical surface area, however, there was both a positive association with family income and moderation: There was an interaction between school climate and income for total cortical surface area and locally in the lateral orbitofrontal cortex. In all cases, there was an unexpected negative association between school climate and cortical surface area in the lower-income group. Consequently, although the school climate appears to be related to better socioemotional function for all youth, findings suggest that the association between a positive school environment and brain structure only emerges in the context of socioeconomic stress and adversity. Longitudinal data are needed to understand the role of these neural differences in socioemotional functioning over time.

Brain Structure and Function Show Distinct Relations With Genetic Predispositions to Mental Health and Cognition

BackgroundMental health and cognitive achievement are partly heritable, highly polygenic, and associated with brain variations in structure and function. However, the underlying neural mechanisms remain unclear. MethodsWe investigated the association between genetic predispositions to various mental health and cognitive traits and a large set of structural and functional brain measures from the UK Biobank (N = 36,799). We also applied linkage disequilibrium score regression to estimate the genetic correlations between various traits and brain measures based on genome-wide data. To decompose the complex association patterns, we performed a multivariate partial least squares model of the genetic and imaging modalities. ResultsThe univariate analyses showed that certain traits were related to brain structure (significant genetic correlations with total cortical surface area from rg = −0.101 for smoking initiation to rg = 0.230 for cognitive ability), while other traits were related to brain function (significant genetic correlations with functional connectivity from rg = −0.161 for educational attainment to rg = 0.318 for schizophrenia). The multivariate analysis showed that genetic predispositions to attention-deficit/hyperactivity disorder, smoking initiation, and cognitive traits had stronger associations with brain structure than with brain function, whereas genetic predispositions to most other psychiatric disorders had stronger associations with brain function than with brain structure. ConclusionsThese results reveal that genetic predispositions to mental health and cognitive traits have distinct brain profiles.

Identification of individual subjects based on neuroanatomical measures obtained 7 years earlier.

We analysed a dataset comprising 118 subjects who were scanned three times (at baseline, 1‐year follow‐up, and 7‐year follow‐up) using structural magnetic resonance imaging (MRI) over the course of 7 years. We aimed to examine whether it is possible to identify individual subjects based on a restricted number of neuroanatomical features measured 7 years previously. We used FreeSurfer to compute 15 standard brain measures (total intracranial volume [ICV], total cortical thickness [CT], total cortical surface area [CA], cortical grey matter [CoGM], cerebral white matter [CeWM], cerebellar cortex [CBGM], cerebellar white matter [CBWM], subcortical volumes [thalamus, putamen, pallidum, caudatus, hippocampus, amygdala and accumbens] and brain stem volume). We used linear discriminant analysis (LDA), random forest machine learning (RF) and a newly developed rule‐based identification approach (RBIA) for the identification process. Using RBIA, different sets of neuroanatomical features (ranging from 2 to 14) obtained at baseline were combined by if–then rules and compared to the same set of neuroanatomical features derived from the 7‐year follow‐up measurement. We achieved excellent identification results with LDA, while the identification results for RF were very good but not perfect. The RBIA produced the best results, achieving perfect participant identification for some four‐feature sets. The identification results improved substantially when using larger feature sets, with 14 neuroanatomical features providing perfect identification. Thus, this study shows again that the human brain is highly individual in terms of neuroanatomical features. These results are discussed in the context of the current literature on brain plasticity and the scientific attempts to develop brain‐fingerprinting techniques.

Hallucinations and Brain Morphology Across Early Adolescence: A Longitudinal Neuroimaging Study

BackgroundPsychotic disorders have been widely associated with structural brain abnormalities. However, it is unclear whether brain structure predicts psychotic experiences in youth from the general population, owing to an overall paucity of studies and predominantly cross-sectional designs. Here, the authors investigated longitudinal associations between brain morphology and hallucinations from childhood to early adolescence. MethodsThis study was embedded in the population-based Generation R Study. Children underwent structural neuroimaging at age 10 years (N = 2042); a subsample received a second scan at age 14 years (n = 964). Hallucinations were assessed at ages 10 and 14 years and studied as a binary variable. Cross-lagged panel models and generalized linear mixed-effects models were fitted to examine longitudinal associations between brain morphology and hallucinations. ResultsSmaller total gray and white matter volumes and total cortical surface area at baseline were associated with a higher occurrence of hallucinations between ages 10 and 14 years. The regions associated with hallucinations were widespread, including the frontal, parietal, temporal, and occipital lobes, as well as the insula and cingulate cortex. Analyses of subcortical structures revealed that smaller baseline hippocampal volumes were longitudinally associated with hallucinations, although this association was no longer significant following adjustment for intracranial volume. No evidence for reverse temporality was observed (i.e., hallucinations predicting brain differences). ConclusionsThe findings from this longitudinal study suggest that global structural brain differences are associated with the development of hallucinations. These results extend findings from clinical populations and provide evidence for a neurodevelopmental vulnerability across the psychosis continuum.

Cytomegalovirus Infection Associated with Smaller Total Cortical Surface Area in Schizophrenia Spectrum Disorders.

ObjectivesCytomegalovirus (CMV) congenital infection and in immunodeficiency can have deleterious effects on human cortex. In immunocompetent adults, the putative association between CMV infection and cortical measures has not been explored. We hypothesized that CMV exposure is associated with smaller cortical surface area or cortical thinning mainly in patients with schizophrenia spectrum disorders.Study DesignWe included 67 adult patients with schizophrenia spectrum disorders and 262 adult healthy controls. We measured circulating CMV IgG antibody concentrations with solid-phase immunoassay techniques. We measured the total cortical surface area, regional cortical surface areas and the overall mean cortical thickness based on T1-weighted MRI scans processed in FreeSurfer v6.0.Study ResultsIn the whole sample analysis, we found a significant diagnostic group-by-CMV status interaction on the total surface area (P = .020). Among patients, CMV antibody positivity was significantly associated with smaller total surface area (P = .002, partial eta2 = 0.138) whereas no such association was found in healthy controls (P = .059). Post hoc analysis among patients showed that higher CMV antibody concentrations were also significantly associated with smaller total surface area (P = .038), and that CMV antibody positivity was significantly inversely associated with 14 left and 16 right regional surface areas mainly in the frontal and temporal lobes. CMV infection was not associated with the overall mean cortical thickness.ConclusionsThe results are indicative of a cortical surface area vulnerability to CMV infection in patients with schizophrenia spectrum disorders but not in healthy controls. CMV infection may contribute to the established cortical surface area aberrations in schizophrenia.

Cerebral cortex maldevelopment in syndromic craniosynostosis.

AimTo assess the relationship of surface area of the cerebral cortex to intracranial volume (ICV) in syndromic craniosynostosis.MethodRecords of 140 patients (64 males, 76 females; mean age 8y 6mo [SD 5y 6mo], range 1y 2mo–24y 2mo) with syndromic craniosynostosis were reviewed to include clinical and imaging data. Two hundred and three total magnetic resonance imaging (MRI) scans were evaluated in this study (148 patients with fibroblast growth factor receptor [FGFR], 19 patients with TWIST1, and 36 controls). MRIs were processed via FreeSurfer pipeline to determine total ICV and cortical surface area (CSA). Scaling coefficients were calculated from log‐transformed data via mixed regression to account for multiple measurements, sex, syndrome, and age. Educational outcomes were reported by syndrome.ResultsMean ICV was greater in patients with FGFR (1519cm3, SD 269cm3, p=0.016) than in patients with TWIST1 (1304cm3, SD 145cm3) or controls (1405cm3, SD 158cm3). CSA was related to ICV by a scaling law with an exponent of 0.68 (95% confidence interval [CI] 0.61–0.76) in patients with FGFR compared to 0.81 (95% CI 0.50–1.12) in patients with TWIST1 and 0.77 (95% CI 0.61–0.93) in controls. Lobar analysis revealed reduced scaling in the parietal (0.50, 95% CI 0.42–0.59) and occipital (0.67, 95% CI 0.54–0.80) lobes of patients with FGFR compared with controls. Modified learning environments were needed more often in patients with FGFR.InterpretationDespite adequate ICV in FGFR‐mediated craniosynostosis, CSA development is reduced, indicating maldevelopment, particularly in parietal and occipital lobes. Modified education is also more common in patients with FGFR.

Childhood Adversity and the Brain: Harnessing the Power of Neuroplasticity

In the current issue of Biological Psychiatry, Gehred et al. ( 1 Gehred M.Z. Knodt A.R. Ambler A. Bourassa K.J. Danese A. Elliott M.L. et al. Long-term neural embedding of childhood adversity in a population-representative birth cohort followed for 5 decades. Biol Psychiatry. 2021; 90: 182-193 Abstract Full Text Full Text PDF Scopus (6) Google Scholar ) showcase unique new data and a novel window on the long-term impact of childhood adversity on structural changes in the brain. This report uses data from a by now well-known birth cohort in Dunedin, New Zealand, creatively harnessed over many decades by Moffitt and Caspi. It is a testament to these scholars that they have continuously added to the measurement armamentarium of this project as new relevant measures and technologies have been developed. When the Dunedin study was first launched, neuroimaging did not exist. With the newly added neuroimaging measures along with the measurement of different aspects of development as the sample matured, this birth cohort offers a goldmine of rich data that have so effectively been explored over the years by Moffitt and Caspi and their colleagues. Gehred et al. ( 1 Gehred M.Z. Knodt A.R. Ambler A. Bourassa K.J. Danese A. Elliott M.L. et al. Long-term neural embedding of childhood adversity in a population-representative birth cohort followed for 5 decades. Biol Psychiatry. 2021; 90: 182-193 Abstract Full Text Full Text PDF Scopus (6) Google Scholar ) report that both prospectively ascertained and retrospective measures of childhood adversity were associated with smaller total cortical surface area, average cortical thickness, and smaller subcortical gray matter volume in a birth cohort of 861 participants. The imaging data were acquired when the participants were 45 years of age, with 94% of the original sample participating. Gehred et al. ( 1 Gehred M.Z. Knodt A.R. Ambler A. Bourassa K.J. Danese A. Elliott M.L. et al. Long-term neural embedding of childhood adversity in a population-representative birth cohort followed for 5 decades. Biol Psychiatry. 2021; 90: 182-193 Abstract Full Text Full Text PDF Scopus (6) Google Scholar ) also reported that associations with prospectively ascertained measures of adversity were consistently stronger than those with retrospectively reported adversity. Finally, the findings revealed widely distributed effects throughout the brain with virtually no regional specificity. SEE CORRESPONDING ARTICLE ON PAGE 182 SEE CORRESPONDING ARTICLE ON PAGE 182 Long-term Neural Embedding of Childhood Adversity in a Population-Representative Birth Cohort Followed for 5 DecadesBiological PsychiatryVol. 90Issue 3PreviewChildhood adversity has been previously associated with alterations in brain structure, but heterogeneous designs, methods, and measures have contributed to mixed results and have impeded progress in mapping the biological embedding of childhood adversity. We sought to identify long-term differences in structural brain integrity associated with childhood adversity. Full-Text PDF Open Access

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Positive Economic, Psychosocial, and Physiological Ecologies Predict Brain Structure and Cognitive Performance in 9-10-Year-Old Children.

While low socioeconomic status (SES) introduces risk for developmental outcomes among children, there are an array of proximal processes that determine the ecologies and thus the lived experiences of children. This study examined interrelations between 22 proximal measures in the economic, psychosocial, physiological, and perinatal ecologies of children, in association with brain structure and cognitive performance in a diverse sample of 8,158 9–10-year-old children from the Adolescent Brain Cognitive Development (ABCD) study. SES was measured by the income-to-needs ratio (INR), a measure used by federal poverty guidelines. Within the ABCD study, in what is one of the largest and most diverse cohorts of children studied in the United States, we replicate associations of low SES with lower total cortical surface area and worse cognitive performance. Associations between low SES (<200% INR) and measures of development showed the steepest increases with INR, with apparent increases still visible beyond the level of economic disadvantage in the range of 200–400% INR. Notably, we found three latent factors encompassing positive ecologies for children across the areas of economic, psychosocial, physiological, and perinatal well-being in association with better cognitive performance and the higher total cortical surface area beyond the effects of SES. Specifically, latent factors encompassing youth perceived social support and perinatal well-being were positive predictors of developmental measures for all children, regardless of SES. Further, we found a general latent factor that explained relationships between 20 of the proximal measures and encompassed a joint ecology of higher social and economic resources relative to low adversity across psychosocial, physiological, and perinatal domains. The association between the resource-to-adversity latent factor and cognitive performance was moderated by SES, such that for children in higher SES households, cognitive performance progressively increased with these latent factor scores, while for lower SES, cognitive performance increased only among children with the highest latent factor scores. Our findings suggest that both positive ecologies of increased access to resources and lower adversity are mutually critical for promoting better cognitive development in children from low SES households. Our findings inform future studies aiming to examine positive factors that influence healthier development in children.

Morphological changes of the cerebral cortex between children with isolated growth hormone deficiency and idiopathic short stature

The growth hormone (GH)-insulin-like growth factor-I (IGF-I) axis plays an important role in normal brain development, and GH deficiency inevitably affects the growth of the cerebral cortex. This study was designed to analyze morphological differences in gray matter volume, cortical surface area, and gray matter thickness between children with isolated growth hormone deficiency (IGHD) and children with idiopathic short stature (ISS). Twenty-four children with IGHD (mean age 9.42 years, peak GH < 5 μg/l) and 24 controls with ISS (mean age 9.21 years, peak GH > 10 μg/l) were included. High-resolution three-dimensional T1-weighted MRIs were acquired at participants’ first visit. Measurements of gray matter volume, cortical surface area and gray matter thickness were obtained using FreeSurfer. The total and regional differences between groups were statistically analyzed. Correlations between the FreeSurfer results and GH and IGF-I levels were also obtained. The gray matter volume, cortical surface area and gray matter thickness of the total brain and of the bilateral hemispheres of children with IGHD were significantly smaller than those of children with ISS (all P values < 0.05). All the measurements had similar cortical distributions between groups but varied across regions. Cortical regions with significant differences in the mean gray matter volume and surface area were mainly distributed around the bilateral central sulci and the lateral and basal parts of the temporal lobes (all P values < 0.05). There were negative correlations between gray matter volume, cortical surface area and GH levels, and the right hemispheric and total cortical surface area correlated significantly with GH levels (all P values < 0.05) in children with IGHD. There were significant positive correlations between gray matter volume, cortical surface area and IGF-I levels (all P values < 0.05) in both groups, except for in left hemispheric gray matter volume in children with ISS. Children with IGHD have significant morphological changes in the cerebral cortex, which were partially influenced by GH and IGF-I levels. These cortical changes may be related to deficits in their relatively slower development in intelligence, motor performance, and other functions.

Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment.

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.

Weak correlations between body height and several brain metrics in healthy elderly subjects.

The question whether body height is related to different brain size measures has recently gained renewed interest as some studies have reported that body height correlates with intelligence and several brain size measures. In this study, we re-evaluated this question by examining the relationship between body height and different brain size measures including intracranial volume, total brain volume, total cortical surface area, total cortical volume, volume of normal-appearing white matter, white matter hyperintensity, cortical surface area, cortical thickness, subcortical grey matter volume, cerebellar cortex and cerebellar white matter in a relatively large sample (n=216) of physically and cognitively healthy elderly subjects (mean age 71years, age range 65-85years). We identified small correlations (r=.11-.19) between body height and seven out of 10 brain metrics (total brain volume, cortical surface area, cortical volume, subcortical volume, normal-appearing white matter volume and cerebellar grey as well as white matter volumes) when controlling for sex and age. Based on these small relationships between body height and various brain size measures, we discuss the possible reasons and theoretical problems for these small relationships.