1. Brager DH, Akhavan AR, Johnston D. {{Impaired Dendritic Expression and fmr1(-) (/y) Plasticity of h-Channels in the Mouse Model of Fragile X Syndrome}}. {Cell Rep};2012 (Mar 29);1(3):225-233.
Despite extensive research into both synaptic and morphological changes, surprisingly little is known about dendritic function in fragile X syndrome (FXS). We found that the dendritic input resistance of CA1 neurons was significantly lower in fmr1(-) (/y) versus wild-type mice. Consistent with elevated dendritic I(h), voltage sag, rebound, and resonance frequency were significantly higher and temporal fmr1(-) (/y) summation was lower in the dendrites of mice. Dendritic expression of the h-channel subunit HCN1, but not HCN2, was higher in the CA1 region of fmr1(-) (/y) mice. Interestingly, whereas mGluR-mediated persistent decreases in I(h) occurred in both wild-type and fmr1(-) (/y) mice, persistent increases in I(h) that occurred after LTP induction in wild-type mice were absent in fmr1(-) (/y) mice. Thus, chronic upregulation of dendritic I(h) in conjunction with impairment of homeostatic h-channel plasticity represents a dendritic channelopathy in this model of mental retardation and may provide a mechanism for the cognitive impairment associated with FXS.
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2. Lewis WW, Sahin M, Scherrer B, Peters JM, Suarez RO, Vogel-Farley VK, Jeste SS, Gregas MC, Prabhu SP, Nelson CA, 3rd, Warfield SK. {{Impaired Language Pathways in Tuberous Sclerosis Complex Patients with Autism Spectrum Disorders}}. {Cereb Cortex};2012 (Jun 1)
The purpose of this study was to examine the relationship between language pathways and autism spectrum disorders (ASDs) in patients with tuberous sclerosis complex (TSC). An advanced diffusion-weighted magnetic resonance imaging (MRI) was performed on 42 patients with TSC and 42 age-matched controls. Using a validated automatic method, white matter language pathways were identified and microstructural characteristics were extracted, including fractional anisotropy (FA) and mean diffusivity (MD). Among 42 patients with TSC, 12 had ASD (29%). After controlling for age, TSC patients without ASD had a lower FA than controls in the arcuate fasciculus (AF); TSC patients with ASD had even a smaller FA, lower than the FA for those without ASD. Similarly, TSC patients without ASD had a greater MD than controls in the AF; TSC patients with ASD had even a higher MD, greater than the MD in those without ASD. It remains unclear why some patients with TSC develop ASD, while others have better language and socio-behavioral outcomes. Our results suggest that language pathway microstructure may serve as a marker of the risk of ASD in TSC patients. Impaired microstructure in language pathways of TSC patients may indicate the development of ASD, although prospective studies of language pathway development and ASD diagnosis in TSC remain essential.
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3. Robinson L, Spencer MD, Thomson LD, Stanfield AC, Owens DG, Hall J, Johnstone EC. {{Evaluation of a screening instrument for autism spectrum disorders in prisoners}}. {PloS one};2012;7(5):e36078.
There have been concerns that individuals with autism spectrum disorders (ASDs) are over-represented but not recognised in prison populations. A screening tool for ASDs in prisons has therefore been developed. AIMS: We aimed to evaluate this tool in Scottish prisoners by comparing scores with standard measures of autistic traits (Autism Quotient (AQ)), neurodevelopmental history (Asperger Syndrome (and High-Functioning Autism) Diagnostic Interview (ASDI)), and social cognition (Ekman 60 Faces test). METHODS: Prison officers across all 12 publicly-run closed prisons in Scotland assessed convicted prisoners using the screening tool. This sample included male and female prisoners and both adult and young offenders. Prisoners with high scores, along with an equal number of age and sex-matched controls, were invited to take part in interviews. Prisoners’ relatives were contacted to complete a neurodevelopmental assessment. RESULTS: 2458 prisoners were screened using the tool, and 4% scored above the cut-off. 126 prisoners were further assessed using standardised measures. 7 of those 126 assessed scored 32 or above (cut-off) on the AQ. 44 interviews were completed with prisoners’ relatives, no prisoner reached the cut-off score on the ASDI. Scores on the screening tool correlated significantly with AQ and ASDI scores, and not with the Ekman 60 Faces Test or IQ. Sensitivity was 28.6% and specificity 75.6%; AUC was 59.6%. CONCLUSIONS: Although this screening tool measures autistic traits in this population, sensitivity for scores of 32 or above on the AQ is poor. We consider that this limits its usefulness and do not recommend that the tool is routinely used to screen for ASDs in prisons.
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4. Wasilewska J, Kaczmarski M, Stasiak-Barmuta A, Tobolczyk J, Kowalewska E. {{Low serum IgA and increased expression of CD23 on B lymphocytes in peripheral blood in children with regressive autism aged 3-6 years old}}. {Arch Med Sci};2012 (May 9);8(2):324-331.
INTRODUCTION: Immune system dysfunction is considered to be one of many medical disorders found in children with autism. The primary objective of the study was to assess if blood tests reflecting humoral immunity (IgA, IgG, IgM, IgE) are useful in identifying children with regressive autism. The secondary objective was to evaluate a part of the cellular arm of immunity (CD4/CD25 Tregs, CD4/CD23 cells) in those children. MATERIAL AND METHODS: Using a clinical case-control design, the systemic levels of immunoglobulins and lymphocyte subpopulations analysed by flow cytometry were compared in children aged 3-6 years old with a new diagnosis of regressive autism (n = 24; mean age: 4.25 +/-1.70 years; male 23/24) and in sex- and age-matched healthy children (n = 24; aged 4.25 +/-2.20 years; male 23/24). RESULTS: The humoral immunity profile, described by three binary variables, IgA < 0.97 g/l, IgE > 36 IU/ml, and IgG > 6.3 g/l, with a sensitivity of 79% and a specificity of 83% (p < 0.0001), was able to identify children with autism. The highest risk of autism diagnosis was associated with IgA < 0.97g/l (OR – 23.0; p < 0.001). A higher number of CD19/CD23 was found in children diagnosed with autism than in the control group (36.82 +/-6.72% vs. 18.20 +/-3.95%; p < 0.02). No correlation between the number of CD23-positive cells and serum IgE levels was observed. CONCLUSIONS: A subtle shift of serum immunoglobulins consisting of low-normal IgA and B cell activation expressed by an increase of CD23-positive cells may characterize children with regressive autism aged 3-6 years old.