1. {{Neurodevelopmental disorders: Whole-exome sequencing elucidates genetic architecture of autism spectrum disorder}}. {Nat Rev Neurol};2014 (Nov 18)
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2. Correia C, Oliveira G, Vicente AM. {{Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise}}. {PLoS One};2014;9(11):e112399.
Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical « noise » that warrant further analysis for causal variants.
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3. El-Ansary A, Al-Ayadhi L. {{GABAergic/glutamatergic imbalance relative to excessive neuroinflammation in autism spectrum disorders}}. {J Neuroinflammation};2014 (Nov 19);11(1):189.
BackgroundAutism spectrum disorder (ASD) is characterized by three core behavioral domains: social deficits, impaired communication, and repetitive behaviors. Glutamatergic/GABAergic imbalance has been found in various preclinical models of ASD. Additionally, autoimmunity immune dysfunction, and neuroinflammation are also considered as etiological mechanisms of this disorder. This study aimed to elucidate the relationship between glutamatergic/ GABAergic imbalance and neuroinflammation as two recently-discovered autism-related etiological mechanisms.MethodsTwenty autistic patients aged 3 to 15 years and 19 age- and gender-matched healthy controls were included in this study. The plasma levels of glutamate, GABA and glutamate/GABA ratio as markers of excitotoxicity together with TNF- inverted question mark, IL-6, IFN- inverted question mark and IFI16 as markers of neuroinflammation were determined in both groups.ResultsAutistic patients exhibited glutamate excitotoxicity based on a much higher glutamate concentration in the autistic patients than in the control subjects. Unexpectedly higher GABA and lower glutamate/GABA levels were recorded in autistic patients compared to control subjects. TNF- inverted question mark and IL-6 were significantly lower, whereas IFN- inverted question mark and IFI16 were remarkably higher in the autistic patients than in the control subjects.ConclusionMultiple regression analysis revealed associations between reduced GABA level, neuroinflammation and glutamate excitotoxicity. This study indicates that autism is a developmental synaptic disorder showing imbalance in GABAergic and glutamatergic synapses as a consequence of neuroinflammation.
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4. Fredo RJ, Kavitha G, Ramakrishnan S. {{ANALYSIS OF CORTICAL AND SUB-CORTICAL REGIONS IN AUTISTIC MR IMAGES USING LEVEL SET METHOD AND STRUCTURE TENSORS}}. {Biomed Sci Instrum};2014 (Apr 4);50:140-149.
Autism is a complex disease that causes micro structural changes in brain due to delayed growth. In this work, the cortical regions of brain are extracted from T1 -weighted magnetic resonance mid-sagittal view slices. The images are skull stripped using edge based Level Set (LS) which is regularized by a signed distance function. This skull stripping technique is validated with the Brain extraction tool (BET). The extracted cortical regions are then analyzed by calculating the structure tensor matrix from the gradient of the skull stripped images. The anisotropy index derived from the tensor matrix is correlated with the clinical features such as verbal, full scale and performance Intelligent Quotients (IQ). The results show that the level set method is able to extract the cortical brain boundaries correctly with distinct edges. The structure tensor features extracted from the skull stripped images discriminates the control and autistic images. Also, the anisotropy index is negatively correlated with the performance IQ values of autistic subjects.
5. Kim KC, Choi CS, Kim JW, Han SH, Cheong JH, Ryu JH, Shin CY. {{MeCP2 Modulates Sex Differences in the Postsynaptic Development of the Valproate Animal Model of Autism}}. {Mol Neurobiol};2014 (Nov 18)
Males are predominantly affected by autism spectrum disorders (ASD) with a prevalence ratio of 5:1. However, the underlying pathological mechanisms governing the male preponderance of ASD remain unclear. Recent studies suggested that epigenetic aberrations may cause synaptic dysfunctions, which might be related to the pathophysiology of ASD. In this study, we used rat offspring prenatally exposed to valproic acid (VPA) as an animal model of ASD. We found male-selective abnormalities in the kinetic profile of the excitatory glutamatergic synaptic protein expressions linked to N-methyl-D-aspartate receptor (NMDAR), alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) and metabotropic glutamate receptor 5 (mGluR5) pathways in the prefrontal cortex of the VPA-exposed offspring at postnatal weeks 1, 2, and 4. Furthermore, VPA exposure showed a male-specific attenuation of the methyl-CpG-binding protein 2 (MeCP2) expressions both in the prefrontal cortex of offspring and in the gender-isolated neural progenitor cells (NPCs). In the gender-isolated NPCs culture, higher concentration of VPA induced an increased glutamatergic synaptic development along with decreased MeCP2 expression in both genders suggesting the role of MeCP2 in the modulation of synaptic development. In the small interfering RNA (siRNA) knock-down study, 50 pmol of Mecp2 siRNA inhibited the MeCP2 expression in male- but not in female-derived NPCs with concomitant induction of postsynaptic proteins such as PSD95. Taken together, we suggest that the male-inclined reduction of MeCP2 expression is involved in the abnormal development of glutamatergic synapse and male preponderance in the VPA animal models of ASD.
