SHANK3 controls maturation of social reward circuits in the VTA.

Haploinsufficiency of SHANK3, encoding the synapse scaffolding protein SHANK3, leads to a highly penetrant form of autism spectrum disorder. How SHANK3 insufficiency affects specific neural circuits and how this is related to specific symptoms remains elusive. Here we used shRNA to model Shank3 insufficiency in the ventral tegmental area of mice. We identified dopamine (DA) and GABA cell-type-specific changes in excitatory synapse transmission that converge to reduce DA neuron activity and generate behavioral deficits, including impaired social preference. Administration of a positive allosteric modulator of the type 1 metabotropic glutamate receptors mGluR1 during the first postnatal week restored DA neuron excitatory synapse transmission and partially rescued the social preference defects, while optogenetic DA neuron stimulation was sufficient to enhance social preference. Collectively, these data reveal the contribution of impaired ventral tegmental area function to social behaviors and identify mGluR1 modulation during postnatal development as a potential treatment strategy

No preliminary evidence of differences in astrocyte density within the white matter of the dorsolateral prefrontal cortex in autism

Background: While evidence for white matter and astrocytic abnormalities exist in autism, a detailed investigation of astrocytes has not been conducted. Such an investigation is further warranted by an increasing role for neuroinflammation in autism pathogenesis, with astrocytes being key players in this process. We present the first study of astrocyte density and morphology within the white matter of the dorsolateral prefrontal cortex (DLPFC) in individuals with autism. Methods: DLPFC formalin-fixed sections containing white matter from individuals with autism (n = 8, age = 4-51 years) and age-matched controls (n = 7, age = 4-46 years) were immunostained for glial fibrillary acidic protein (GFAP). Density of astrocytes and other glia were estimated via the optical fractionator, astrocyte somal size estimated via the nucleator, and astrocyte process length via the spaceballs probe. Results: We found no evidence for alteration in astrocyte density within DLPFC white matter of individuals with autism versus controls, together with no differences in astrocyte somal size and process length. Conclusion: Our results suggest that astrocyte abnormalities within the white matter in the DLPFC in autism may be less pronounced than previously thought. However, astrocytic dysregulation may still exist in autism, even in the absence of gross morphological changes. Our lack of evidence for astrocyte abnormalities could have been confounded to an extent by having a small sample size and wide age range, with pathological features potentially restricted to early stages of autism. Nonetheless, future investigations would benefit from assessing functional markers of astrocytes in light of the underlying pathophysiology of autism

Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters

No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker

Neurexin-1 and Frontal Lobe White Matter: An Overlapping Intermediate Phenotype for Schizophrenia and Autism Spectrum Disorders

Background: Structural variation in the neurexin-1 (NRXN1) gene increases risk for both autism spectrum disorders (ASD) and schizophrenia. However, the manner in which NRXN1 gene variation may be related to brain morphology to confer risk for ASD or schizophrenia is unknown. Method/Principal Findings: 53 healthy individuals between 18–59 years of age were genotyped at 11 single nucleotide polymorphisms of the NRXN1 gene. All subjects received structural MRI scans, which were processed to determine cortical gray and white matter lobar volumes, and volumes of striatal and thalamic structures. Each subject’s sensorimotor function was also assessed. The general linear model was used to calculate the influence of genetic variation on neural and cognitive phenotypes. Finally, in silico analysis was conducted to assess potential functional relevance of any polymorphisms associated with brain measures. A polymorphism located in the 39 untranslated region of NRXN1 significantly influenced white matter volumes in whole brain and frontal lobes after correcting for total brain volume, age and multiple comparisons. Follow-up in silico analysis revealed that this SNP is a putative microRNA binding site that may be of functional significance in regulating NRXN1 expression. This variant also influenced sensorimotor performance, a neurocognitive function impaired in both ASD and schizophrenia. Conclusions: Our findings demonstrate that the NRXN1 gene, a vulnerability gene for SCZ and ASD, influences brai

Prevalence of co-occurring mental health diagnoses in the autism population: a systematic review and meta-analysis.

BACKGROUND: Co-occurring mental health or psychiatric conditions are common in autism, impairing quality of life. Reported prevalences of co-occurring mental health or psychiatric conditions in people with autism range widely. Improved prevalence estimates and identification of moderators are needed to enhance recognition and care, and to guide future research. METHODS: In this systematic review and meta-analysis, we searched MEDLINE, Embase, PsycINFO, Scopus, Web of Science, and grey literature for publications between Jan 1, 1993, and Feb 1, 2019, in English or French, that reported original research using an observational design on the prevalence of co-occurring mental health conditions in people with autism and reported confirmed clinical diagnoses of the co-occurring conditions and autism using DSM or ICD criteria. For co-occurring mental health conditions reported with at least 15 datapoints (studies), we assessed risk of bias and we determined pooled estimates of prevalence for different co-occurring conditions in autism using random-effects models, and descriptively compared these with prevalence estimates for the general population from the literature (post hoc). We investigated heterogeneity in prevalence estimates using random-effects meta-regression models. This systematic review is registered with PROSPERO, CRD42018103176. FINDINGS: Of 9746 unique studies identified, 432 were selected for full-text review. 100 studies were eligible for inclusion in our qualitative synthesis, of which 96 were included in our meta-analyses. 11 categories of co-occurring conditions were investigated, of which eight conditions were included in the meta-analyses and three were descriptively synthesised (ie, trauma and stressor-related disorders, substance-related and addictive disorders, and gender dysphoria). From our meta-analyses, we found overall pooled prevalence estimates of 28% (95% CI 25-32) for attention-deficit hyperactivity disorder; 20% (17-23) for anxiety disorders; 13% (9-17) for sleep-wake disorders; 12% (10-15) for disruptive, impulse-control, and conduct disorders; 11% (9-13) for depressive disorders; 9% (7-10) for obsessive-compulsive disorder; 5% (3-6) for bipolar disorders; and 4% (3-5) for schizophrenia spectrum disorders. Estimates in clinical sample-based studies were higher than in population-based and registry-based studies, and these estimates were mostly higher than those in the general population (post hoc). Age, gender, intellectual functioning, and country of study were associated with heterogeneity in prevalence estimates, yet remaining heterogeneity not explained was still substantial (all I2 >95%). INTERPRETATION: Co-occurring mental health conditions are more prevalent in the autism population than in the general population. Careful assessment of mental health is an essential component of care for all people on the autism spectrum and should be integrated into clinical practice. FUNDING: Academic Scholars Awards, Department of Psychiatry, University of Toronto; O'Brien Scholars Program, Slaight Family Child and Youth Mental Health Innovation Fund, and The Catherine and Maxwell Meighen Foundation via the Centre for Addiction and Mental Health Foundation