MRI Neuroanatomy in Young Girls With Autism
ABSTRACT To test the hypothesis that young girls and boys with autism exhibit different profiles of neuroanatomical abnormality relative to each other and relative to typically developing children.
Structural magnetic resonance imaging was used to measure gray and white matter volumes (whole cerebrum, cerebral lobes, and cerebellum) and total brain volume in nine girls (ages 2.29-5.16) and 27 boys (ages 1.96-5.33) with autism and 14 girls (ages 2.17-5.71) and 13 boys (ages 1.72-5.50) with typical development. Structure size and the relationship between size and age were examined. Diagnostic and cognitive outcome data were obtained after the children reached 4 to 5 years of age.
Girls with autism exhibited nearly every size-related abnormality exhibited by boys with autism. Furthermore, additional sites of abnormality were observed in girls, including enlargement in temporal white and gray matter volumes and reduction in cerebellar gray matter volume. Significant correlations were observed between age and white matter volumes (e.g., cerebral white matter rs = 0.950) for the girls with autism, whereas no significant age-structure size relationships were observed for the boys with autism.
Results suggest sex differences in etiological factors and the biological time course of the disorder.
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ABSTRACT: The current state of biomedical science is such that both the number and sophistication of methods available to investigate the genetic determinants of disease is unprecedented. For example, the introduction of high-throughput technologies such as DNA microarrays, allow researchers to comprehensively assess the human genome for single nucleotide polymorphisms that confer genetic susceptibility. Indeed, while these, and other similarly sophisticated methods, have yielded notable findings with regard to identification of risk variants in diseases such as diabetes, obesity, and glaucoma, similar studies of neuropsychiatric diseases such as schizophrenia and bipolar disorder have been somewhat less successful in producing strong findings. The reasons why this is the case are numerous, but likely refl ect the very complex genetic architecture of neuropsychiatric conditions. In this chapter, we consider an approach to addressing this complexity that involves the use of what are termed ‘endophenotypes’ (or alternatively ‘intermediate phe-notypes’) in genetic studies of neuropsychiatric disorders. Endophenotypes are biological changes, such as brain structural differences, that are thought to represent underlying molecular, physiologic, or otherwise subclinical changes resulting directly from the genetic variations that mediate susceptibility to overt clinical disease. Furthermore, neuroimaging phenotypes are, for a variety of reasons, thought to represent good candidate endophenotypes for genetic association studies of neuropsychiatric disease. Like high-dimensional genome-wide data, however, these phenotyping technologies can produce hundreds to thousands of data points or more, when all neuroanatomic regions and tissue types of interest are considered. The question then becomes, how can two or more high-dimensional data types (i.e., in this case genomic and neuroimaging) be leveraged, integrated, and analyzed in order to make valid inferences about the genetic basis of neuropsychi-atric disease? We comment on the analytic issues that arise when trying to leverage both genome-wide genetic data and neuroimaging data (e.g., problems related to multiple comparisons and false positives, as well as small sample sizes), and discuss four general approaches, each with its own set of advantages and disadvantages, that can be used in the analysis of imag-ing-genetics data. Finally, we provide a brief review of some of the recent studies that combine imaging and genetics, but note that the field, as a whole, is still very much in its infancy. We also provide suggestions for future directions.
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ABSTRACT: Although the neurobiology of autism has been studied for more than two decades, the majority of these studies have examined brain structure 10, 20, or more years after the onset of clinical symptoms. The pathological biology that causes autism remains unknown, but its signature is likely to be most evident during the first years of life when clinical symptoms are emerging. This review highlights neurobiological findings during the first years of life and emphasizes early brain overgrowth as a key factor in the pathobiology of autism. We speculate that excess neuron numbers may be one possible cause of early brain overgrowth and produce defects in neural patterning and wiring, with exuberant local and short-distance cortical interactions impeding the function of large-scale, long-distance interactions between brain regions. Because large-scale networks underlie socio-emotional and communication functions, such alterations in brain architecture could relate to the early clinical manifestations of autism. As such, autism may additionally provide unique insight into genetic and developmental processes that shape early neural wiring patterns and make possible higher-order social, emotional, and communication functions.Neuron 11/2007; 56(2):399-413. DOI:10.1016/j.neuron.2007.10.016 · 15.98 Impact Factor
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ABSTRACT: Age-related volumetric differences in brain anatomy or volumetric brain analyses in many disorders are of interest. Delineating the normal anatomical cerebellar volume is of importance for both the anatomists and clinicians. In the present study, we aimed to evaluate the cerebellar volume using a stereological technique and to determine the possible volumetric asymmetry depending on age and gender. Volumetric asymmetry of cerebellar hemispheres was evaluated using stereological method on the magnetic resonance images (MRI) of healthy male and female subjects. Randomly selected individuals (27 males, 27 females) aged between 10-86 years who have normal brain MRI were enclosed in the study. All the subjects were right handed. The individuals were divided into three groups according to age as 18-34 (young), 35-60 (middle aged) and 60-84 (elder) and their MRI images were analyzed. The data set were analyzed by two factor repeated measure analysis. Although the cerebellum was smaller between young and middle aged groups and also middle aged and elder groups, there were no any statistically significant differences between compared groups' mean (P > 0.05). There were not statistically differences according to sex and age groups (P > 0.05). There was no cerebellar asymmetry between compared groups. The stereological evaluation of cerebellar asymmetry in humans correlate with both gender and age groups is of importance for both clinicians and anatomists. The technique is simple, reliable, unbiased and inexpensive.Surgical and Radiologic Anatomy 10/2008; 31(3):177-81. DOI:10.1007/s00276-008-0424-4 · 1.33 Impact Factor