Genome-wide association study identifies 30 obsessive-compulsive disorder associated loci.

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.

Human archetypal pluripotent stem cells differentiate into trophoblast stem cells via endogenous BMP5/7 induction without transitioning through naive state.

Primary human trophoblast stem cells (TSCs) and TSCs derived from human pluripotent stem cells (hPSCs) can potentially model placental processes in vitro. Yet, the pluripotent states and factors involved in the differentiation of hPSCs to TSCs remain poorly understood. In this study, we demonstrate that the primed pluripotent state can generate TSCs by activating pathways such as Epidermal Growth Factor (EGF) and Wingless-related integration site (WNT), and by suppressing tumor growth factor beta (TGFß), histone deacetylases (HDAC), and Rho-associated protein kinase (ROCK) signaling pathways, all without the addition of exogenous Bone morphogenetic protein 4 (BMP4)-a condition we refer to as the TS condition. We characterized this process using temporal single-cell RNA sequencing to compare TS conditions with differentiation protocols involving BMP4 activation alone or BMP4 activation in conjunction with WNT inhibition. The TS condition consistently produced a stable, proliferative cell type that closely mimics first-trimester placental cytotrophoblasts, marked by the activation of endogenous retroviral genes and the absence of amnion expression. This was observed across multiple cell lines, including various primed induced pluripotent stem cell (iPSC) and embryonic stem cell (ESC) lines. Primed-derived TSCs can proliferate for over 30 passages and further specify into multinucleated syncytiotrophoblasts and extravillous trophoblast cells. Our research establishes that the differentiation of primed hPSCs to TSC under TS conditions triggers the induction of TMSB4X, BMP5/7, GATA3, and TFAP2A without progressing through a naive state. These findings propose that the primed hPSC state is part of a continuum of potency with the capacity to differentiate into TSCs through multiple routes.

Exploring the Acquisition of Social Communication Skills in Children with Autism: Preliminary Findings from Applied Behavior Analysis (ABA), Parent Training, and Video Modeling.

Social communication skills, especially eye contact and joint attention, are frequently impaired in autism spectrum disorder (ASD) and predict functional outcomes. Applied behavior analysis is one of the most common evidence-based treatments for ASD, but it is not accessible to most families in low- and middle-income countries (LMICs) as it is an expensive and intensive treatment and needs to be delivered by highly specialized professionals. Parental training has emerged as an effective alternative. This is an exploratory study to assess a parental intervention group via video modeling to acquire eye contact and joint attention. Four graded measures of eye contact and joint attention (full physical prompt, partial physical prompt, gestural prompt, and independent) were assessed in 34 children with ASD and intellectual disability (ID). There was a progressive reduction in the level of prompting required over time to acquire eye contact and joint attention, as well as a positive correlation between the time of exposure to the intervention and the acquisition of abilities. This kind of parent training using video modeling to teach eye contact and joint attention skills to children with ASD and ID is a low-cost intervention that can be applied in low-resource settings.

Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal.

BACKGROUND: Autism Spectrum Disorder (ASD) diagnosis can be aided by approaches based on eye-tracking signals. Recently, the feasibility of building Visual Attention Models (VAMs) from features extracted from visual stimuli and their use for classifying cases and controls has been demonstrated using Neural Networks and Support Vector Machines. The present work has three aims: 1) to evaluate whether the trained classifier from the previous study was generalist enough to classify new samples with a new stimulus; 2) to replicate the previously approach to train a new classifier with a new dataset; 3) to evaluate the performance of classifiers obtained by a new classification algorithm (Random Forest) using the previous and the current datasets. METHODS: The previously approach was replicated with a new stimulus and new sample, 44 from the Typical Development group and 33 from the ASD group. After the replication, Random Forest classifier was tested to substitute Neural Networks algorithm. RESULTS: The test with the trained classifier reached an AUC of 0.56, suggesting that the trained classifier requires retraining of the VAMs when changing the stimulus. The replication results reached an AUC of 0.71, indicating the potential of generalization of the approach for aiding ASD diagnosis, as long as the stimulus is similar to the originally proposed. The results achieved with Random Forest were superior to those achieved with the original approach, with an average AUC of 0.95 for the previous dataset and 0.74 for the new dataset. CONCLUSION: In summary, the results of the replication experiment were satisfactory, which suggests the robustness of the approach and the VAM-based approaches feasibility to aid in ASD diagnosis. The proposed method change improved the classification performance. Some limitations are discussed and additional studies are encouraged to test other conditions and scenarios.

Computer aided diagnosis of neurodevelopmental disorders and genetic syndromes based on facial images - A systematic literature review.

Neurodevelopment disorders can result in facial dysmorphisms. Therefore, the analysis of facial images using image processing and machine learning techniques can help construct systems for diagnosing genetic syndromes and neurodevelopmental disorders. The systems offer faster and cost-effective alternatives for genotyping tests, particularly when dealing with large-scale applications. However, there are still challenges to overcome to ensure the accuracy and reliability of computer-aided diagnosis systems. This article presents a systematic review of such initiatives, including 55 articles. The main aspects used to develop these diagnostic systems were discussed, namely datasets - availability, type of image, size, ethnicities and syndromes - types of facial features, techniques used for normalization, dimensionality reduction and classification, deep learning, as well as a discussion related to the main gaps, challenges and opportunities.

Gene expression alterations in the postmortem hippocampus from older patients with bipolar disorder - A hypothesis generating study.

Bipolar disorder (BD) presents with a progressive course in a subset of patients. However, our knowledge of molecular changes in older BD is limited. In this study, we examined gene expression changes in the hippocampus of BD from the Biobank of Aging Studies to identify genes of interest that warrant further exploration. RNA was extracted from the hippocampus from 11 subjects with BD and 11 age and sex-matched controls. Gene expression data was generated using the SurePrint G3 Human Gene Expression v3 microarray. Rank feature selection was performed to identify a subset of features that can optimally differentiate BD and controls. Genes ranked in the top 0.1% with log2 fold change >1.2 were identified as genes of interest. Average age of the subjects was 64 years old; duration of disease was 21 years and 82% were female. Twenty-five genes were identified, of which all but one was downregulated in BD. Of these, CNTNAP4, MAP4, SLC4A1, COBL, and NEURL4 had been associated with BD and other psychiatric conditions in previous studies. We believe our findings have identified promising targets to inform future studies aiming to understand the pathophysiology of BD in later life.

Assessment of vulnerability dimensions considering Family History and environmental interplay in Autism Spectrum Disorder.

BACKGROUND: Despite previous studies have recently shown Autism Spectrum Disorders (ASD) as having a strong genetics background, over a minimum environmental background, no study up to date has investigated the interplay between genetics and environment. METHODS: We have collected data regarding Family History (FH) and Environmental Factors (EF) from 2,141 individuals with ASD and their caretakers throughout Brazil, based on an online questionnaire. Most of the ASD individuals were males (81%) and the average age was 02 years minimum for males and females, and the maximum age was 41 years for males and 54 for females. People from all states in Brazil have answered the questionnaire. Genetic inheritance was obtained based on the declared FH of Psychiatric and Neurological diagnosis. As for EF, exposure to risk factors during pregnancy was considered, like infections, diabetes, drugs/chemicals exposure, socioeconomic, and psychological factors. Respondents were invited to answer the questionnaire in lectures given throughout Brazil, and by the social networks of the NGO "The Tooth Fairy Project". A Multiple Correspondence Analysis (MCA) was conducted to search vulnerability dimensions, and a Cluster Analysis was conducted to classify and identify the subgroups. RESULTS: Regarding EF, social and psychological exposures contributed to the first two dimensions. Concerning FH, the first dimension represented psychiatric FH, while the second represented neurological FH. When analyzed together, EF and FH contributed to two new dimensions: 1. psychiatric FH, and 2. a psychosocial component. Using Cluster Analysis, it was not possible to isolate subgroups by genetic vulnerability or environmental exposure. Instead, a gradient of psychiatric FH with similar contributions of EF was observed. CONCLUSION: In this study, it was not possible to isolate groups of patients that correspond to only one component, but rather a continuum with different compositions of genetic and environmental interplay.

CRISIS AFAR: an international collaborative study of the impact of the COVID-19 pandemic on mental health and service access in youth with autism and neurodevelopmental conditions.

BACKGROUND: Heterogeneous mental health outcomes during the COVID-19 pandemic are documented in the general population. Such heterogeneity has not been systematically assessed in youth with autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDD). To identify distinct patterns of the pandemic impact and their predictors in ASD/NDD youth, we focused on pandemic-related changes in symptoms and access to services. METHODS: Using a naturalistic observational design, we assessed parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) Adapted For Autism and Related neurodevelopmental conditions (AFAR). Cross-sectional AFAR data were aggregated across 14 European and North American sites yielding a clinically well-characterized sample of N = 1275 individuals with ASD/NDD (age = 11.0 ± 3.6 years; n females = 277). To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups. RESULTS: Clustering revealed four subgroups. One subgroup-broad symptom worsening only (20%)-included youth with worsening across a range of symptoms but with service disruptions similar to the average of the aggregate sample. The other three subgroups were, relatively, clinically stable but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Distinct combinations of a set of pre-pandemic services, pandemic environment (e.g., COVID-19 new cases, restrictions), experiences (e.g., COVID-19 Worries), and age predicted each outcome subgroup. LIMITATIONS: Notable limitations of the study are its cross-sectional nature and focus on the first six months of the pandemic. CONCLUSIONS: Concomitantly assessing variation in changes of symptoms and service access during the first phase of the pandemic revealed differential outcome profiles in ASD/NDD youth. Subgroups were characterized by distinct prediction patterns across a set of pre- and pandemic-related experiences/contexts. Results may inform recovery efforts and preparedness in future crises; they also underscore the critical value of international data-sharing and collaborations to address the needs of those most vulnerable in times of crisis.

1H NMR Metabolomics and Lipidomics To Monitor Positive Responses in Children with Autism Spectrum Disorder Following a Guided Parental Intervention: A Pilot Study.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that is characterized by patients displaying at least two out of the classical symptoms, such as impaired social communication, impaired interactions, and restricted repetitive behavior. Early parent-mediated interventions, such as video modeling for parental training, were demonstrated to be a successful low-cost way to deliver care for children with ASD. Nuclear magnetic resonance (NMR)-based metabolomics/lipidomics has been successfully employed in several mental disorder studies. Metabolomics and lipidomics of 37 ASD patients (children, aged 3-8 years), who were divided into two groups, one control group with no parental-training intervention (N = 18) and the other in which the parents were trained by a video modeling intervention (ASD parental training, N = 19), were analyzed by proton NMR spectroscopy. Patients in the ASD parental-training group sera were seen to have increased glucose, myo-inositol, malonate, proline, phenylalanine, and gangliosides in their blood serum, while cholesterol, choline, and lipids were decreased, compared to the control group, who received no parental-training. Taken together, we demonstrated here significant changes in serum metabolites and lipids in ASD children, previously demonstrated to show clinical positive effects following a parental training intervention based on video modeling, delivered over 22 weeks. We demonstrate the value of applying metabolomics and lipidomics to identify potential biomarkers for clinical interventions follow-up in ASD.

Maternal distress, DNA methylation, and fetal programing of stress physiology in Brazilian mother-infant pairs.

Maternal prenatal psychosocial stress is associated with adverse hypothalamic-pituitary-adrenal axis (HPAA) function among infants. Although the biological mechanisms influencing this process remain unknown, altered DNA methylation is considered to be one potential mechanism. We investigated associations between maternal prenatal psychological distress, infant salivary DNA methylation, and stress physiology at 12 months. Mother's distress was measured via depression and anxiety in early and late pregnancy in a cohort of 80 pregnant adolescents. Maternal hair cortisol was collected during pregnancy. Saliva samples were collected from infants at 12 months to quantify DNA methylation of three stress-related genes (FKBP5, NR3C1, OXTR) (n = 62) and diurnal cortisol (n = 29). Multivariable linear regression was used to test for associations between prenatal psychological distress, and infant DNA methylation and cortisol. Hair cortisol concentrations in late pregnancy were negatively associated with two sites of FKBP5 (site 1: B = -22.33, p = .003; site 2: B = -15.60, p = .012). Infants of mothers with elevated anxiety symptoms in late pregnancy had lower levels of OXTR2 CpG2 methylation (B = -2.17, p = .03) and higher evening salivary cortisol (B = 0.41, p = .03). Furthermore, OXTR2 methylation was inversely associated with evening cortisol (B = -0.14, p-value ≤ .001). Our results are, to our knowledge, the first evidence that the methylation of the oxytocin receptor may contribute to the regulation of HPAA during infancy.

Gestational age acceleration is associated with epigenetic biomarkers of prenatal physiologic stress exposure.

BACKGROUND: Physiological maternal stress response, such as imbalance in the glucocorticoid pathway and immune system seems to be mediated by DNA methylation (DNAm) and might translate intrauterine stress exposures into phenotypic changes in a sex-specific manner. DNAm in specific sites can also predict newborn gestational age and gestational age acceleration (GAA). GAA occurs when the predicted biological age is higher than the chronological age. In adults, poor health outcomes related to this deviance are well documented and raise questions for the interpretation and prediction in early stages of life. Boys seem to be more vulnerable to intrauterine stress exposure than girls; however, the mechanisms of adaptive sex-specific responses are still unclear. We hypothesize that intrauterine stress exposure is associated with GAA and could be different in boys and girls if inflammatory or glucocorticoid pathways exposure is considered. RESULTS: Using the Western Region Birth Cohort (ROC-São Paulo, Brazil) (n = 83), we calculated DNAm age and GAA from cord blood samples. Two epigenetic risk scores were calculated as an indirect proxy for low-grade inflammation (i-ePGS) and for glucocorticoid exposure (GES). Multivariate linear regression models were applied to investigate associations of GAA with prenatal exposures. The i-ePGS and GES were included in different models with the same co-variates considering sex interactions. The first multivariate model investigating inflammatory exposure (adj. R2 = 0.31, p = < 0.001) showed that GAA was positively associated with i-ePGS (CI, 0.26-113.87, p = 0.049) and negative pregnancy-related feelings (CI, 0.04-0.48 p = 0.019). No sex interaction was observed. The second model investigating glucocorticoid exposure (adj. R2 = 0.32, p = < 0.001) showed that the higher was the GAA was associated with a lower the lower was the GES in girls (CI, 0.04-2.55, p = 0.044). In both models, maternal self-reported mental disorder was negatively associated with GAA. CONCLUSION: Prenatal epigenetic score of exposure to low-grade inflammatory was a predictor of GAA for both sexes. Glucocorticoid epigenetic score seems to be more important to GAA in girls. This study supports the evidence of sex-specificity in stress response, suggesting the glucocorticoid as a possible pathway adopted by girls to accelerate the maturation in an adverse condition.

Sex differences in gene regulatory networks during mid-gestational brain development.

Neurodevelopmental disorders differ considerably between males and females, and fetal brain development is one of the most critical periods to determine risk for these disorders. Transcriptomic studies comparing male and female fetal brain have demonstrated that the highest difference in gene expression occurs in sex chromosomes, but several autossomal genes also demonstrate a slight difference that has not been yet explored. In order to investigate biological pathways underlying fetal brain sex differences, we applied medicine network principles using integrative methods such as co-expression networks (CEMiTool) and regulatory networks (netZoo). The pattern of gene expression from genes in the same pathway tend to reflect biologically relevant phenomena. In this study, network analysis of fetal brain expression reveals regulatory differences between males and females. Integrating two different bioinformatics tools, our results suggest that biological processes such as cell cycle, cell differentiation, energy metabolism and extracellular matrix organization are consistently sex-biased. MSET analysis demonstrates that these differences are relevant to neurodevelopmental disorders, including autism.

MicroRNA target prediction tools for animals: Where we are at and where we are going to - A systematic review.

MicroRNAs (miRNAs) are non-coding RNAs containing 19-26 nucleotides, and they directly regulate the translation of mRNAs by binding to them. MiRNAs participate in various physiological processes and are associated with the development of diseases, such as cancer. Therefore, understanding miRNAs regulation on targets is crucial for understanding the mechanisms of diseases and for obtaining a more suitable treatment. In animals, the base complementarity between miRNAs and the mRNA is imperfect, hindering the prediction of these targets. Thus, over the past 15 years, several computational tools have emerged for the prediction of miRNA targets in animals, generally with a focus on human expression data. Taking into account the wide range of prediction tools, a systematic review is presented here to analyze and classify these methods and features to enable the most appropriate choice according to the needs of each researcher. In this study, only articles whose methods met the inclusion and exclusion criteria established in the protocol were considered. The search was performed in November 2020, in two search engines PubMed and VHL Regional Portal. Among the initial 5315 journals found in the two searches, 78 articles were accepted, comprising 49 different tools analyzed and grouped by features and method similarities. As we limited our criteria to animals, all tools found in our search were suitable for human studies. The results demonstrated the evolution of prediction tools, including the most used features, such as alignment and thermodynamics, the methods used, as well as performance issues. It is possible to conclude that the currently available miRNA target prediction tools and methods can be aggregated with new features or other methods to improve accuracy.

DNA methylation mediates a randomized controlled trial home-visiting intervention during pregnancy and the Bayley infant's cognitive scores at 12 months of age.

The crosstalk between maternal stress exposure and fetal development may be mediated by epigenetic mechanisms, including DNA methylation (DNAm). To address this matter, we collect 32 cord blood samples from low-income Brazilian pregnant adolescents participants of a pilot randomized clinical intervention study (ClinicalTrials.gov, Identifier: NCT02807818). We hypothesized that the association between the intervention and infant neurodevelopmental outcomes at 12 months of age would be mediated by DNAm. First, we searched genome methylation differences between cases and controls using different approaches, as well as differences in age acceleration (AA), represented by the difference of methylation age and birth age. According to an adjusted p-value ≤ 0.05 we identified 3090 differentially methylated positions- CpG sites (DMPs), 21 differentially methylated regions (DMRs) and one comethylated module weakly preserved between groups. The intervention group presented a smaller AA compared to the control group (p = 0.025). A logistic regression controlled by sex and with gestational age indicated a coefficient of -0.35 towards intervention group (p = 0.016) considering AA. A higher cognitive domain score from Bayley III scale was observed in the intervention group at 12 months of age. Then, we performed a potential causal mediation analysis selecting only DMPs highly associated with the cognitive domain (adj. R2 > 0.4), DMRs and CpGs of hub genes from the weakly preserved comethylated module and epigenetic clock as raw values. DMPs in STXBP6, and PF4 DMR, mediated the association between the maternal intervention and the cognitive domain at 12 months of age. In conclusion, DNAm in different sites and regions mediated the association between intervention and cognitive outcome.

Antipsychotics preserve telomere length in peripheral blood mononuclear cells after acute oxidative stress injury.

Antipsychotics may prolong or retain telomere length, affect mitochondrial function, and then affect the metabolism of nerve cells. To validate the hypothesis that antipsychotics can prolong telomere length after oxidative stress injury, leukocytes from healthy volunteers were extracted using Ficoll-Histopaque density gradient. The mononuclear cells layer was resuspended in cell culture medium. Oxidative stress was induced with hydrogen peroxide in cultured leukocytes. Four days later, leukocytes were treated with aripiprazole, haloperidol or clozapine for 7 days. Real-time PCR revealed that treatments with aripiprazole and haloperidol increased the telomere length by 23% and 20% in peripheral blood mononuclear cells after acute oxidative stress injury. These results suggest that haloperidol and aripiprazole can reduce the damage to telomeres induced by oxidative stress. The experiment procedure was approved by the Ethics Committee of Faculty of Medicine of the University of São Paulo (FMUSP/CAAE approval No. 52622616.8.0000.0065).

ADHD and autism symptoms in youth: a network analysis.

BACKGROUND: Previous research investigating the overlap between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (henceforth, autism) symptoms in population samples have relied on latent variable modeling in which averaged scores representing dimensions were derived from observed symptoms. There are no studies evaluating how ADHD and autism symptoms interact at the level of individual symptom items. METHODS: We aimed to address this gap by performing a network analysis on data from a school survey of children aged 6-17 years old (N = 7,405). ADHD and autism symptoms were measured via parent-report on the Swanson, Nolan, Pelham-IV questionnaire and the Childhood Autism Spectrum test, respectively. RESULTS: A relatively low interconnectivity between ADHD and autism symptoms was found with only 10.06% of possible connections (edges) between one ADHD and one autism symptoms different than zero. Associations between ADHD and autism symptoms were significantly weaker than those between two symptoms pertaining to the same construct. Select ADHD symptoms, particularly those presenting in social contexts (e.g. 'talks excessively', 'does not wait turn'), showed moderate-to-strong associations with autism symptoms, but some were considered redundant to autism symptoms. CONCLUSIONS: The present findings indicate that individual ADHD and autism symptoms are largely segregated in accordance with diagnostic boundaries corresponding to these conditions in children and adolescents from the community. These findings could improve our clinical conceptualization of ADHD and autism and guide advancements in diagnosis and treatment.

Increased levels of TAR DNA-binding protein 43 in the hippocampus of subjects with bipolar disorder: a postmortem study.

Bipolar disorder shares symptoms and pathological pathways with other neurodegenerative diseases, including frontotemporal dementia (FTD). Since TAR DNA-binding protein 43 (TDP-43) is a neuropathological marker of frontotemporal dementia and it is involved in synaptic transmission, we explored the role of TDP-43 as a molecular feature of bipolar disorder (BD). Homogenates were acquired from frozen hippocampus of postmortem brains of bipolar disorder subjects. TDP-43 levels were quantified using an ELISA-sandwich method and compared between the postmortem brains of bipolar disorder subjects and age-matched control group. We found higher levels of TDP-43 protein in the hippocampus of BD (n = 15) subjects, when compared to controls (n = 15). We did not find associations of TDP-43 with age at death, postmortem interval, or age of disease onset. Our results suggest that protein TDP-43 may be potentially implicated in behavioral abnormalities seen in BD. Further investigation is needed to validate these findings and to examine the role of this protein during the disease course and mood states.

Sex differences in gene regulatory networks during mid-gestational brain development

Neurodevelopmental disorders differ considerably between males and females, and fetal brain development is one of the most critical periods to determine risk for these disorders. Transcriptomic studies comparing male and female fetal brain have demonstrated that the highest difference in gene expression occurs in sex chromosomes, but several autossomal genes also demonstrate a slight difference that has not been yet explored. In order to investigate biological pathways underlying fetal brain sex differences, we applied medicine network principles using integrative methods such as co-expression networks (CEMiTool) and regulatory networks (netZoo). The pattern of gene expression from genes in the same pathway tend to reflect biologically relevant phenomena. In this study, network analysis of fetal brain expression reveals regulatory differences between males and females. Integrating two different bioinformatics tools, our results suggest that biological processes such as cell cycle, cell differentiation, energy metabolism and extracellular matrix organization are consistently sex-biased. MSET analysis demonstrates that these differences are relevant to neurodevelopmental disorders, including autism.

Corrigendum: Neuronal-Glial Interaction in a Triple-Transgenic Mouse Model of Alzheimer's Disease: Gene Ontology and Lithium Pathways.

[This corrects the article DOI: 10.3389/fnins.2020.579984.].

Involvement of the habenula in the pathophysiology of autism spectrum disorder.

The habenula is a small epithalamic structure with widespread connections to multiple cortical, subcortical and brainstem regions. It has been identified as the central structure modulating the reward value of social interactions, behavioral adaptation, sensory integration and circadian rhythm. Autism spectrum disorder (ASD) is characterized by social communication deficits, restricted interests, repetitive behaviors, and is frequently associated with altered sensory perception and mood and sleep disorders. The habenula is implicated in all these behaviors and results of preclinical studies suggest a possible involvement of the habenula in the pathophysiology of this disorder. Using anatomical magnetic resonance imaging and automated segmentation we show that the habenula is significantly enlarged in ASD subjects compared to controls across the entire age range studied (6-30 years). No differences were observed between sexes. Furthermore, support-vector machine modeling classified ASD with 85% accuracy (model using habenula volume, age and sex) and 64% accuracy in cross validation. The Social Responsiveness Scale (SRS) significantly differed between groups, however, it was not related to individual habenula volume. The present study is the first to provide evidence in human subjects of an involvement of the habenula in the pathophysiology of ASD.