Genetic Influences on the Development of Cerebral Cortical Thickness During Childhood and Adolescence in a Dutch Longitudinal Twin Sample:The Brainscale Study

Previous studies have demonstrated that cortical thickness (CT) is under strong genetic control across the life span. However, little is known about genetic influences that cause changes in cortical thickness (ΔCT) during brain development. We obtained 482 longitudinal MRI scans at ages 9, 12, and 17 years from 215 twins and applied structural equation modeling to estimate genetic influences on (1) cortical thickness between regions and across time, and (2) changes in cortical thickness between ages. Although cortical thickness is largely mediated by the same genetic factor throughout late childhood and adolescence, we found evidence for influences of distinct genetic factors on regions across space and time. In addition, we found genetic influences for cortical thinning during adolescence that is mostly due to fluctuating influences from the same genetic factor, with evidence of local influences from a second emerging genetic factor. This fluctuating core genetic factor and emerging novel genetic factor might be implicated in the rapid cognitive and behavioral development during childhood and adolescence, and could potentially be targets for investigation into the manifestation of psychiatric disorders that have their origin in childhood and adolescence

Тенденції розвитку національної інноваційної системи в Україні

Проаналізовано національну інноваційну систему України. Розглянуто галузі промисловості України за ознаками інноваційної активності та досліджено темпи зростання показників, враховуючи індекс інфляції. Встановлено, що спад темпів зростання динаміки реалізованої продукції призводить до зменшення витрат на інноваційну діяльність.Дан анализ национальной инновационной системы Украины. Рассмотрены отрасли промышленности Украины по признакам инновационной активности и исследованы темпы роста показателей, учитывая индекс инфляции. Установлено, что спад темпов роста динамики реализованной продукции приводит к уменьшению затрат на инновационную деятельность.This article analyses national innovation system of Ukraine. Examined the industry of Ukraine based on innovative activity and investigated the growth indicators, taking into account inflation-index. It is established that the slowdown in the dynamics realized production leads to a decrease in the cost of innovation

Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes:findings from the ENIGMA Epigenetics Working Group

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions

Genetic influences on structural and functional brain maturation

Understanding typical brain development in children and adolescents is important because it provides a baseline for what is to be considered aberrant development. This knowledge can also be used to determine what parts of the brain is responsible for cognitive and behavioral development in adolescence and can inform on psychiatric disorders that have their onset in adolescence, such as schizophrenia. With a longitudinal twin study design, the genetic and environmental influences on brain and behavior, as well as their developmental changes, can be disentangled. In this thesis, I show that i) the thickness of the cerebral cortex and its rate of development during adolescence is largely under genetic control, with a new genetic factor marking the transition during adolescence; ii) functional connectivity in the adolescent brain is in part also determined by genes, along with several indications of influences from common environment, that remain largely stable over time. This suggests that the development of the structure of the brain is considerably influenced by genes, while the functioning of the brain is more flexible to adapt to the environment. Patients with schizophrenia experience accelerated aging. I looked at accelerated aging based on the structure of the brain and epigenetic modifications, and found iii) no clear evidence that these two aging processes are related despite that both are partially determined by genes implicated in schizophrenia. This suggests the possibility for two distinct aging processes affecting accelerated aging in patients with schizophrenia

Robust Automated White Matter Pathway Reconstruction for Large Studies

Automated probabilistic reconstruction of white matter pathways facilitates tractography in large studies. TRACULA (TRActs Constrained by UnderLying Anatomy) follows a Markov-chain Monte Carlo (MCMC) approach that is compute-intensive. TRACULA is available on our Neuroscience Gateway (NSG), a user-friendly environment for fully automated data processing on grid computing resources. Despite the robustness of TRACULA, our users and others have reported incidents of partially reconstructed tracts. Investigation revealed that in these situations the MCMC algorithm is caught in local minima. We developed a method that detects unsuccessful tract reconstructions and iteratively repeats the sampling procedure while maintaining the anatomical priors to reduce computation time. The anatomical priors are recomputed only after several unsuccessful iterations. Our method detects affected tract reconstructions by analyzing the dependency between samples produced by the MCMC algorithm. We extensively validated the original and the modified methods by performing five repeated reconstructions on a dataset of 74 HIV-positive patients and 47 healthy controls. Our method increased the rate of successful reconstruction in the two most prominently affected tracts (forceps major and minor) on average from 74% to 99%. In these tracts, no group difference in FA and MD was found, while a significant association with age could be confirme

Reliability modelling of resting-state functional connectivity

Resting-state functional magnetic resonance imaging (rs-fMRI) has an inherently low signal-to-noise ratio largely due to thermal and physiological noise that attenuates the functional connectivity (FC) estimates. Such attenuation limits the reliability of FC and may bias its association with other traits. Low reliability also limits heritability estimates. Classical test theory can be used to obtain a true correlation estimate free of random measurement error from parallel tests, such as split-half sessions of a rs-fMRI scan. We applied a measurement model to split-half FC estimates from the resting-state fMRI data of 1003 participants from the Human Connectome Project (HCP) to examine the benefit of reliability modelling of FC in association with traits from various domains. We evaluated the efficiency of the measurement model on extracting a stable and reliable component of FC and its association with several traits for various sample sizes and scan durations. In addition, we aimed to replicate our previous findings of increased heritability estimates when using a measurement model in a longitudinal adolescent twin cohort. The split-half measurement model improved test-retest reliability of FC on average with +0.33 points (from +0.49 to +0.82), improved strength of associations between FC and various traits on average 1.2-fold (range 1.09–1.35), and increased heritability estimates on average with +20% points (from 39% to 59%) for the full HCP dataset. On average, about half of the variance in split-session FC estimates was attributed to the stable and reliable component of FC. Shorter scan durations showed greater benefit of reliability modelling (up to 1.6-fold improvement), with an additional gain for smaller sample sizes (up to 1.8-fold improvement). Reliability modelling of FC based on a split-half using a measurement model can benefit genetic and behavioral studies by extracting a stable and reliable component of FC that is free from random measurement error and improves genetic and behavioral associations

Genetic influences on the development of cerebral cortical thickness during childhood and adolescence in a Dutch longitudinal twin sample : The brainscale study

Previous studies have demonstrated that cortical thickness (CT) is under strong genetic control across the life span. However, little is known about genetic influences that cause changes in cortical thickness (δCT) during brain development. We obtained 482 longitudinal MRI scans at ages 9, 12, and 17 years from 215 twins and applied structural equation modeling to estimate genetic influences on (1) cortical thickness between regions and across time, and (2) changes in cortical thickness between ages. Although cortical thickness is largely mediated by the same genetic factor throughout late childhood and adolescence, we found evidence for influences of distinct genetic factors on regions across space and time. In addition, we found genetic influences for cortical thinning during adolescence that is mostly due to fluctuating influences from the same genetic factor, with evidence of local influences from a second emerging genetic factor. This fluctuating core genetic factor and emerging novel genetic factor might be implicated in the rapid cognitive and behavioral development during childhood and adolescence, and could potentially be targets for investigation into the manifestation of psychiatric disorders that have their origin in childhood and adolescence

Age-related differences in autism: The case of white matter microstructure

Autism spectrum disorder (ASD) is typified as a brain connectivity disorder in which white matter abnormalities are already present early on in life. However, it is unknown if and to which extent these abnormalities are hard-wired in (older) adults with ASD and how this interacts with age-related white matter changes as observed in typical aging. The aim of this first cross-sectional study in mid- and late-aged adults with ASD was to characterize white matter microstructure and its relationship with age. We utilized diffusion tensor imaging with head motion control in 48 adults with ASD and 48 age-matched controls (30-74 years), who also completed a Flanker task. Intra-individual variability of reaction times (IIVRT) measures based on performance on the Flanker interference task were used to assess IIVRT-white matter microstructure associations. We observed primarily higher mean and radial diffusivity in white matter microstructure in ASD, particularly in long-range fibers, which persisted after taking head motion into account. Importantly, group-by-age interactions revealed higher age-related mean and radial diffusivity in ASD, in projection and association fiber tracts. Subtle dissociations were observed in IIVRT-white matter microstructure relations between groups, with the IIVRT-white matter association pattern in ASD resembling observations in cognitive aging. The observed white matter microstructure differences are lending support to the structural underconnectivity hypothesis in ASD. These reductions seem to have behavioral percussions given the atypical relationship with IIVRT. Taken together, the current results may indicate different age-related patterns of white matter microstructure in adults with ASD. Hum Brain Mapp 38:82-96, 2017. © 2016 Wiley Periodicals, In

Accelerated aging in the brain, epigenetic aging in blood, and polygenic risk for schizophrenia

Schizophrenia patients show signs of accelerated aging in cognitive and physiological domains. Both schizophrenia and accelerated aging, as measured by MRI brain images and epigenetic clocks, are correlated with increased mortality. However, the association between these aging measures have not yet been studied in schizophrenia patients. In schizophrenia patients and healthy subjects, accelerated aging was assessed in brain tissue using a longitudinal MRI (N = 715 scans; mean scan interval 3.4 year) and in blood using two epigenetic age clocks (N = 172). Differences (‘gaps’) between estimated ages and chronological ages were calculated, as well as the acceleration rate of brain aging. The correlations between these aging measures as well as with polygenic risk scores for schizophrenia (PRS; N = 394) were investigated. Brain aging and epigenetic aging were not significantly correlated. Polygenic risk for schizophrenia was significantly correlated with brain age gap, brain age acceleration rate, and negatively correlated with DNAmAge gap, but not with PhenoAge gap. However, after controlling for disease status and multiple comparisons correction, these effects were no longer significant. Our results imply that the (accelerated) aging observed in the brain and blood reflect distinct biological processes. Our findings will require replication in a larger cohort