49 research outputs found

    Using Multivariate Machine Learning Methods and Structural MRI to Classify Childhood Onset Schizophrenia and Healthy Controls

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    Introduction: Multivariate machine learning methods can be used to classify groups of schizophrenia patients and controls using structural magnetic resonance imaging (MRI). However, machine learning methods to date have not been extended beyond classification and contemporaneously applied in a meaningful way to clinical measures. We hypothesized that brain measures would classify groups, and that increased likelihood of being classified as a patient using regional brain measures would be positively related to illness severity, developmental delays, and genetic risk. Methods: Using 74 anatomic brain MRI sub regions and Random Forest (RF), a machine learning method, we classified 98 childhood onset schizophrenia (COS) patients and 99 age, sex, and ethnicity-matched healthy controls. We also used RF to estimate the probability of being classified as a schizophrenia patient based on MRI measures. We then explored relationships between brain-based probability of illness and symptoms, premorbid development, and presence of copy number variation (CNV) associated with schizophrenia. Results: Brain regions jointly classified COS and control groups with 73.7% accuracy. Greater brain-based probability of illness was associated with worse functioning (p = 0.0004) and fewer developmental delays (p = 0.02). Presence of CNV was associated with lower probability of being classified as schizophrenia (p = 0.001). The regions that were most important in classifying groups included left temporal lobes, bilateral dorsolateral prefrontal regions, and left medial parietal lobes. Conclusion: Schizophrenia and control groups can be well classified using RF and anatomic brain measures, and brain-based probability of illness has a positive relationship with illness severity and a negative relationship with developmental delays/problems and CNV-based risk

    Cortical thickness change in autism during early childhood

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    Structural magnetic resonance imaging (MRI) scans at high spatial resolution can detect potential foci of early brain dysmaturation in children with autism spectrum disorders (ASD). In addition, comparison between MRI and behavior measures over time can identify patterns of brain change accompanying specific outcomes. We report structural MRI data from two time points for a total of 84 scans in children with ASD and 30 scans in typical controls (mean age time one = 4.1 years, mean age at time two = 6.6 years). Surface-based cortical morphometry and linear mixed effects models were used to link changes in cortical anatomy to both diagnostic status and individual differences in changes in language and autism severity. Compared with controls, children with ASD showed accelerated gray matter volume gain with age, which was driven by a lack of typical age-related cortical thickness (CT) decrease within 10 cortical regions involved in language, social cognition, and behavioral control. Greater expressive communication gains with age in children with ASD were associated with greater CT gains in a set of right hemisphere homologues to dominant language cortices, potentially identifying a compensatory system for closer translational study. Hum Brain Mapp 37:2616-2629, 2016. © 2016 Wiley Periodicals, Inc

    Triangulating the sexually dimorphic brain through high-resolution neuroimaging of murine sex chromosome aneuploidies

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    Murine sex chromosome aneuploidies (SCAs) provide powerful models for charting sex chromosome influences on mammalian brain development. Here, building on prior work in X-monosomic (XO) mice, we use spatially non-biased high-resolution imaging to compare and contrast neuroanatomical alterations in XXY and XO mice relative to their wild-type XX and XY littermates. First, we show that carriage of a supernumerary X chromosome in XXY males (1) does not prevent normative volumetric masculinization of the bed nucleus of the stria terminalis (BNST) and medial amygdala, but (2) causes distributed anatomical alterations relative to XY males, which show a statistically unexpected tendency to be co-localized with and reciprocal to XO-XX differences in anatomy. These overlaps identify the lateral septum, BNST, ventral group thalamic nuclei and periaqueductal gray matter as regions with replicable sensitivity to X chromosome dose across two SCAs. We then harness anatomical variation across all four karyotype groups in our study--XO, XX, XY and XXY--to create an agnostic data-driven segmentation of the mouse brain into five distributed clusters which (1) recover fundamental properties of brain organization with high spatial precision, (2) define two previously uncharacterized systems of relative volume excess in females vs. males ("forebrain cholinergic" and "cerebelo-pontine-thalamo-cortical"), and (3) adopt stereotyped spatial motifs which delineate ordered gradients of sex chromosome and gonadal influences on volumetric brain development. Taken together, these data provide a new framework for the study of sexually dimorphic influences on brain development in health and disrupted brain development in SCA

    Cerebellum development during childhood and adolescence: A longitudinal morphometric MRI study

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    In addition to its well-established role in balance, coordination, and other motor skills, the cerebellum is increasingly recognized as a prominent contributor to a wide array of cognitive and emotional functions. Many of these capacities undergo dramatic changes during childhood and adolescence. However, accurate characterization of co-occurring anatomical changes has been hindered by lack of longitudinal data and methodologic challenges in quantifying subdivisions of the cerebellum. In this study we apply an innovative image analysis technique to quantify total cerebellar volume and 11 subdivisions (i.e. anterior, superior posterior, and inferior posterior lobes, corpus medullare, and three vermal regions) from anatomic brain MRI scans from 25 healthy females and 25 healthy males aged 5-24 years, each of whom was scanned at least three times at approximately 2-year intervals. Total cerebellum volume followed an inverted U shaped developmental trajectory peaking at age 11.8 years in females and 15.6 years in males. Cerebellar volume was 10% to 13% larger in males depending on the age of comparison and the sexual dimorphism remained significant after covarying for total brain volume. Subdivisions of the cerebellum had distinctive developmental trajectories with more phylogenetically recent regions maturing particularly late. The cerebellum's unique protracted developmental trajectories, sexual dimorphism, preferential vulnerability to environmental influences, and frequent implication in childhood onset disorders such as autism and ADHD make it a prime target for pediatric neuroimaging investigations

    Catechol-o-methyl transferase (COMT) val(158)met polymorphism and adolescent cortical development in patients with childhood-onset schizophrenia, their non-psychotic siblings, and healthy controls

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    Non-psychotic individuals at increased risk for schizophrenia show alterations in fronto-striatal dopamine signaling and cortical gray matter maturation reminiscent of those seen in schizophrenia. It remains unclear however if variations in dopamine signaling influence rates of structural cortical maturation in typically developing individuals, and whether such influences are disrupted in patients with schizophrenia and their non-psychotic siblings. We sought to address these issues by relating a functional Val→Met polymorphism within the gene encoding catechol-o-methyltransferase (COMT)—a key enzymatic regulator of cortical dopamine levels—to longitudinal structural neuroimaging measures of cortical gray matter thickness. We included a total of 792 magnetic resonance imaging brain scans, acquired between ages 9 and 22 years from patients with childhood-onset schizophrenia (COS), their non-psychotic full siblings, and matched healthy controls. Whereas greater Val allele dose (which confers enhanced dopamine catabolism and is proposed to aggravate cortical deficits in schizophrenia) accelerated adolescent cortical thinning in both schizophrenia probands and their siblings, it attenuated cortical thinning in healthy controls. This similarity between COS patients and their siblings was accompanied by differences between the two groups in the timing and spatial distribution of disrupted COMT influences on cortical maturation. Consequently, whereas greater Val “dose” conferred persistent dorsolateral prefrontal cortical deficits amongst affected probands by adulthood, cortical thickness differences associated with varying Val dose in non-psychotic siblings resolved over the age-range studied. These findings suggest that cortical abnormalities in pedigrees affected by schizophrenia may be contributed to by a disruption of dopaminergic infleunces on cortical maturation
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