1. Antaki D, Guevara J, Maihofer AX, Klein M, Gujral M, Grove J, Carey CE, Hong O, Arranz MJ, Hervas A, Corsello C, Vaux KK, Muotri AR, Iakoucheva LM, Courchesne E, Pierce K, Gleeson JG, Robinson EB, Nievergelt CM, Sebat J. Publisher Correction: A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex. Nat Genet;2022 (Jun 29)

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2. Brefort E, Saint-Georges-Chaumet Y, Cohen D, Saint-Georges C. Two-year follow-up of 90 children with autism spectrum disorder receiving intensive developmental play therapy (3i method). BMC Pediatr;2022 (Jun 28);22(1):373.

BACKGROUND: The Intensive, Interactive, and Individual (3i) intervention approach aims to decrease the severity of autism spectrum disorder (ASD) using intensive developmental play therapy (3i). We performed a retrospective study of 90 children who were enrolled for 2 years in the 3i approach to assess changes and predictors of changes in ASD severity at follow-up (FU). METHODS: The ASD severity of all patients (N = 119) who began 3i intervention between 2013 and 2018 was systematically measured using the childhood autism rating scale (CARS) and autism diagnosis interview-revised (ADI-R). Among them, 90 patients (mean age 5.6 ± 3.7 years) had a second assessment at the 2 year FU. CARS and ADI-R scores after 2 years of 3i intervention were compared to baseline scores using paired student’s t-tests. We used multiple linear regression models to assess the weight of baseline variables (e.g., age, oral language, sex, treatment intensity) on changes at the 2 year FU. RESULTS: Mean CARS and ADI-R subscores (interaction, communication, repetitive behaviour) decreased significantly by 20, 41, 27.5 and 25%, respectively (effect sizes: d > 0.8). Moreover, 55 and 46.7% of participants switched to a lower category of ASD severity based on the CARS scale and ADI-R interview, respectively. Multiple linear models showed that (i) a higher treatment intensity (more than 30 h per week) was significantly associated with a greater decrease (improvement) in the ADI-R interaction score; (ii) patients categorized as verbal subjects at baseline were associated with a better outcome, as ascertained by the CARS, ADI-R interaction and ADI-R communication scores; and (iii) older patients were significantly associated with a greater decrease in the ADI-R interaction score. However, we found no impact of sex, severity of ASD or comorbidities at baseline. CONCLUSION: This study performed on 90 children suggests that 3i therapy may allow for a significant reduction in ASD severity with improvements in interaction, communication, and repetitive behaviours. A study using a control group is required to assess the efficacy of 3i play therapy compared to other interventions.

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3. Camilleri LJ, Maras K, Brosnan M. Correction: The impact of using digitally-mediated social stories on the perceived competence and attitudes of parents and practitioners supporting children with autism. PLoS One;2022;17(6):e0270948.

[This corrects the article DOI: 10.1371/journal.pone.0262598.].

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4. Chehbani F, Tomaiuolo P, Picinelli C, Baccarin M, Castronovo P, Scattoni ML, Gaddour N, Persico AM. Yield of array-CGH analysis in Tunisian children with autism spectrum disorder. Mol Genet Genomic Med;2022 (Jun 27):e1939.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic underpinnings. Microarray-based comparative genomic hybridization (aCGH) technology has been proposed as a first-level test in the genetic diagnosis of ASD and of neurodevelopmental disorders in general. METHODS: We performed aCGH on 98 Tunisian children (83 boys and 15 girls) diagnosed with ASD according to DSM-IV criteria. RESULTS: « Pathogenic » or « likely pathogenic » copy number variants (CNVs) were detected in 11 (11.2%) patients, CNVs of « uncertain clinical significance » in 26 (26.5%), « likely benign » or « benign » CNVs were found in 37 (37.8%) and 24 (24.5%) patients, respectively. Gene set enrichment analysis involving genes spanning rare « pathogenic, » « likely pathogenic, » or « uncertain clinical significance » CNVs, as well as SFARI database « autism genes » in common CNVs, detected eight neuronal Gene Ontology classes among the top 10 most significant, including synapse, neuron differentiation, synaptic signaling, neurogenesis, and others. Similar results were obtained performing g: Profiler analysis. Neither transcriptional regulation nor immune pathways reached significance. CONCLUSIONS: aCGH confirms its sizable diagnostic yield in a novel sample of autistic children from North Africa. Recruitment of additional families is under way, to verify whether genetic contributions to ASD in the Tunisian population, differently from other ethnic groups, may involve primarily neuronal genes, more than transcriptional regulation and immune-related pathways.

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5. Chen M, Dutt AS, Nair R. Systematic review of reviews on Activities of Daily Living measures for children with developmental disabilities. Heliyon;2022 (Jun);8(6):e09698.

BACKGROUND: There seems to be a lack of consensus on the concept and domains of Activities of Daily Living (ADL) measured among children and adolescents with developmental disabilities (DD), despite a significant number of existing measures of ADL and associated constructs, and two prevailing theoretical frameworks (i.e., the cognitive-social-practical framework, and the activity-and-participation framework). AIMS: This systematic review (SR) aims to identify articles that systematically reviewed measures of ADL for children and adolescents aged 7-18 years with DD to evaluate the quality of included articles, and describe the measures and domains identified. METHODS: and Procedures: Searches were conducted in PubMed®, Academic Search Complete® (EBSCOhost), Education Source Search® (EBSCOhost), ERIC® (EBSCOhost), and PsychInfo® (EBSCOhost). 14,931 articles were identified, and two researchers completed title screening, abstract screening, and full-text screening, with disagreements resolved. Out of these 14,931 articles, fourteen were included, which resulted in a total of 163 ADL measures. Out of the 163 ADL measures, forty-eight met the criteria and were included for analysis. PRISMA and COSMIN checklists were used to appraise the methodological quality of the included articles. OUTCOMES AND RESULTS: Results indicated that most of the 14 systematic review articles did not provide information on instrument development and content validity of their included measures. Analysis of the identified 48 measures of ADL and its associated constructs revealed heterogeneity in domains covered, although there were seven domains that were most often included. CONCLUSIONS AND IMPLICATIONS: Implications in terms of practice, research, and policy are further discussed.

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6. Dafflon J, P FDC, Váša F, Monti RP, Bzdok D, Hellyer PJ, Turkheimer F, Smallwood J, Jones E, Leech R. A guided multiverse study of neuroimaging analyses. Nat Commun;2022 (Jun 29);13(1):3758.

For most neuroimaging questions the range of possible analytic choices makes it unclear how to evaluate conclusions from any single analytic method. One possible way to address this issue is to evaluate all possible analyses using a multiverse approach, however, this can be computationally challenging and sequential analyses on the same data can compromise predictive power. Here, we establish how active learning on a low-dimensional space capturing the inter-relationships between pipelines can efficiently approximate the full spectrum of analyses. This approach balances the benefits of a multiverse analysis without incurring the cost on computational and predictive power. We illustrate this approach with two functional MRI datasets (predicting brain age and autism diagnosis) demonstrating how a multiverse of analyses can be efficiently navigated and mapped out using active learning. Furthermore, our presented approach not only identifies the subset of analysis techniques that are best able to predict age or classify individuals with autism spectrum disorder and healthy controls, but it also allows the relationships between analyses to be quantified.

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7. Dai YG, Carter AS. Characterizing Accommodations by Parents of Young Children with Autism: A Mixed Methods Analysis. J Autism Dev Disord;2022 (Jun 28)

Symptoms of autism influence families’ participation in daily activities, but few studies have broadly explored the types of accommodations caregivers make to their family’s routines after their child is diagnosed with autism. The current study used a mixed-methods approach to characterize the rate and types of accommodations made by 171 families and the child and family characteristics that predicted accommodations. Most families (91%) endorsed making accommodations in the past year. Lower income, older child age, marginalized racial/ethnic identity, and higher levels of child problem behavior predicted accommodations in a greater number of domains. Thematic analysis illuminated the types of accommodations caregivers made and their motivation for making these lifestyle adjustments. Findings have important implications for parent-mediated interventions and policy.

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8. Dellapiazza F, Michelon C, Picot MC, Baghdadli A. Early risk factors for anxiety disorders in children with autism spectrum disorders: results from the ELENA Cohort. Sci Rep;2022 (Jun 28);12(1):10914.

Anxiety in children with autism spectrum disorder (ASD) negatively affects their social interactions, and quality of life. It is necessary to identify early risk factors for anxiety to tailor prevention and interventions. We aimed to examine the clinical level of anxiety in children with ASD from 5 to 10 years of age and identify potential early risk factors 3 years earlier. Participants were ASD children included in ELENA, a French prospective cohort. In this study, we used the collection of data at Time 1-T1 (at baseline) and Time 2-T2 (3 years after T1). Two groups were identified at T2 according to the threshold for anxiety on the CBCL: ASD-only group and ASD + anxiety group. Our results showed that half of the children in our sample had a clinical level of anxiety at T2. Regression analysis showed that greater ASD severity and lower sensory processing difficulties predicted lower anxiety, whereas higher levels of restricted and repetitive behaviours tended to predict higher levels of anxiety. The high prevalence of clinical-level anxiety in our sample suggests the need for specific assessment and targeted treatment of anxiety on a routine basis.

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9. Kalinowska M, van der Lei MB, Kitiashvili M, Mamcarz M, Oliveira MM, Longo F, Klann E. Deletion of Fmr1 in parvalbumin-expressing neurons results in dysregulated translation and selective behavioral deficits associated with fragile X syndrome. Mol Autism;2022 (Jun 29);13(1):29.

BACKGROUND: Fragile X syndrome (FXS), the most common genetic cause of autism spectrum disorder and intellectual disability, is caused by the lack of fragile X mental retardation protein (FMRP) expression. FMRP is an mRNA binding protein with functions in mRNA transport, localization, and translational control. In Fmr1 knockout mice, dysregulated translation has been linked to pathophysiology, including abnormal synaptic function and dendritic morphology, and autistic-like behavioral phenotypes. The role of FMRP in morphology and function of excitatory neurons has been well studied in mice lacking Fmr1, but the impact of Fmr1 deletion on inhibitory neurons remains less characterized. Moreover, the contribution of FMRP in different cell types to FXS pathophysiology is not well defined. We sought to characterize whether FMRP loss in parvalbumin or somatostatin-expressing neurons results in FXS-like deficits in mice. METHODS: We used Cre-lox recombinase technology to generate two lines of conditional knockout mice lacking FMRP in either parvalbumin or somatostatin-expressing cells and carried out a battery of behavioral tests to assess motor function, anxiety, repetitive, stereotypic, social behaviors, and learning and memory. In addition, we used fluorescent non-canonical amino acid tagging along with immunostaining to determine whether de novo protein synthesis is dysregulated in parvalbumin or somatostatin-expressing neurons. RESULTS: De novo protein synthesis was elevated in hippocampal parvalbumin and somatostatin-expressing inhibitory neurons in Fmr1 knockout mice. Cell type-specific deletion of Fmr1 in parvalbumin-expressing neurons resulted in anxiety-like behavior, impaired social behavior, and dysregulated de novo protein synthesis. In contrast, deletion of Fmr1 in somatostatin-expressing neurons did not result in behavioral abnormalities and did not significantly impact de novo protein synthesis. This is the first report of how loss of FMRP in two specific subtypes of inhibitory neurons is associated with distinct FXS-like abnormalities. LIMITATIONS: The mouse models we generated are limited by whole body knockout of FMRP in parvalbumin or somatostatin-expressing cells and further studies are needed to establish a causal relationship between cellular deficits and FXS-like behaviors. CONCLUSIONS: Our findings indicate a cell type-specific role for FMRP in parvalbumin-expressing neurons in regulating distinct behavioral features associated with FXS.

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10. Klila H, Giuliani F. [Autism and attachment difficulties in adulthood : Overlap of symptoms]. Rev Med Suisse;2022 (Jun 29);18(788):1330-1333.

This article explores the overlap of symptoms between autism and attachment difficulties in adulthood. Clinicians express difficulties in differentiating between these conditions contributing to misdiagnosis. Distinguishing autism spectrum behaviors from behaviors relating to disorganized attachment can be challenging. Urgency is added by the fact that the number of cases is increasing in the diagnosis of autism spectrum disorder (ASD). It is becoming increasingly recognized that ASD shares phenotypic similarities with other traditionally distinct developmental conditions. This article aims enhance the clinicians’ critical reasoning regarding the patient’s behavior to distinguish if its autism or attachment-related behavior disorders. For us, the clearest differentiation factor seemed to be the nature of the behavior.

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11. Melo C, Ribeiro TP, Prior C, Gesta C, Martins V, Oliveira G, Temudo T. Motor stereotypies in autism spectrum disorder: Clinical randomized study and classification proposal. Autism;2022 (Jun 28):13623613221105479.

Motor stereotypies are one of the most frequent features in children with a diagnosis of autism spectrum disorder. They may disrupt children’s functioning and development and be a potential source of stress for families. Several factors, including sex, age, cognitive ability, and severity of autism spectrum disorder, may influence the presence and intensity of stereotypies. The present study aimed to identify the prevalence of motor stereotypies in a group of children with autism spectrum disorder. In addition, it sought to investigate whether sex, age, cognitive ability, verbal language, neurological comorbidities, and severity of autism spectrum disorder were associated with an increased probability and higher number, duration, and variability of stereotypies. A total of 134 participants aged 2.3-17.6 years underwent a clinical protocol with standardized video-recorded sessions. Stereotypies were identified and classified by two independent evaluators. The prevalence of stereotypies was 56.7%, and a total of 1198 motor stereotypies were captured. Children who were younger, nonverbal, and had higher severity of autism spectrum disorder had an increased probability of presenting stereotypies. Being nonverbal or having higher severity of autism spectrum disorder was also associated with presenting a higher number of stereotypies. Children with developmental delay, intellectual disability, or epilepsy displayed longer stereotypies, and children with developmental delay or intellectual disability additionally presented more diverse stereotypies. As part of the study, the authors present a clinical classification model, a glossary, and video samples of motor stereotypies. The findings of this study suggest that children who are younger, nonverbal, have lower cognitive ability, and have higher severity of autism spectrum disorder may have a higher burden of stereotypies. Earlier intervention and monitoring of these children have the potential to improve their long-term outcomes.

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12. Pino MC, Donne IL, Vagnetti R, Tiberti S, Valenti M, Mazza M. Using the Griffiths Mental Development Scales to Evaluate a Developmental Profile of Children with Autism Spectrum Disorder and Their Symptomatologic Severity. Child Psychiatry Hum Dev;2022 (Jun 28)

Early diagnosis is crucial for Autism spectrum disorder (ASD) and is achieved through a screening of developmental indicators to recognise children who are at risk of autism. One of the most widely used instruments in clinical practice for assessing child development is the Griffiths Mental Development Scale (GMDS). We sought (a) to assess longitudinally whether children diagnosed with ASD, with a mean age of 33.50 months (SD 7.69 months), show a developmental delay of abilities measured by the GMDS over time and (b) to analyse which skills of the GMDS could be associate to the symptomatologic severity of ASD. Our results showed lower scores of General Quotient and all sub-quotients of GMDS from first (T0) to second assessment (T1), except for the Performance sub-quotient. Three sub-quotients (Personal-Social, Hearing and Language and Practical Reasoning) also associate symptom severity at the time when the diagnosis of ASD is made.

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13. Préfontaine I, Lanovaz MJ, Rivard M. Brief Report: Machine Learning for Estimating Prognosis of Children with Autism Receiving Early Behavioral Intervention-A Proof of Concept. J Autism Dev Disord;2022 (Jun 28)

Although early behavioral intervention is considered as empirically-supported for children with autism, estimating treatment prognosis is a challenge for practitioners. One potential solution is to use machine learning to guide the prediction of the response to intervention. Thus, our study compared five machine algorithms in estimating treatment prognosis on two outcomes (i.e., adaptive functioning and autistic symptoms) in children with autism receiving early behavioral intervention in a community setting. Each machine learning algorithm produced better predictions than random sampling on both outcomes. Those results indicate that machine learning is a promising approach to estimating prognosis in children with autism, but studies comparing these predictions with those produced by qualified practitioners remain necessary.

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14. Rao S, Baranova A, Yao Y, Wang J, Zhang F. Genetic Relationships between Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, and Intelligence. Neuropsychobiology;2022 (Jun 28):1-13.

INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear. METHODS: The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants across the three traits. RESULTS: Our results showed that intelligence has a positive and negative genetic correlation with ASD and ADHD, respectively, including three hub genomic regions showing correlated genetic effects across the three traits. Polygenic overlap analysis indicated that all the risk variants contributing to ADHD are overlapped with half of those for intelligence, and the majority of the shared variants have opposite effect directions between them. The majority of risk variants (80%) of ASD are overlapped with almost all the risk variants of intelligence (97%). Notably, some ASD/intelligence overlapping variants displayed opposing effects on these two conditions. MR analysis showed that the genetic liability to higher intelligence was associated with an increased risk for ASD (OR = 1.12) and a decreased risk for ADHD (OR = 0.78). Cross-trait meta-analyses identified 170 pleiotropic genomic loci across the three traits, including 12 novel loci. Functional analyses of the novel genes support their potential involvement in neurodevelopment. CONCLUSION: Our results suggest that ADHD is associated with inheriting a reduced set of low-intelligence alleles, whereas ASD results from incongruous effects from a mixture of high-intelligence and low-intelligence contributing alleles summed up with additional, ASD-specific risk variants not associated with intelligence.

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15. Solmi M, Song M, Yon DK, Lee SW, Fombonne E, Kim MS, Park S, Lee MH, Hwang J, Keller R, Koyanagi A, Jacob L, Dragioti E, Smith L, Correll CU, Fusar-Poli P, Croatto G, Carvalho AF, Oh JW, Lee S, Gosling CJ, Cheon KA, Mavridis D, Chu CS, Liang CS, Radua J, Boyer L, Fond G, Shin JI, Cortese S. Incidence, prevalence, and global burden of autism spectrum disorder from 1990 to 2019 across 204 countries. Mol Psychiatry;2022 (Jun 29)

Autism spectrum disorder (ASD) substantially contributes to the burden of mental disorders. Improved awareness and changes in diagnostic criteria of ASD may have influenced the diagnostic rates of ASD. However, while data on trends in diagnostic rates in some individual countries have been published, updated estimates of diagnostic rate trends and ASD-related disability at the global level are lacking. Here, we used the Global Burden of Diseases, Injuries, and Risk Factors Study data to address this gap, focusing on changes in prevalence, incidence, and disability-adjusted life years (DALYs) of ASD across the world. From 1990 to 2019, overall age-standardized estimates remained stable globally. Both prevalence and DALYs increased in countries with high socio-demographic index (SDI). However, the age-standardized incidence decreased in some low SDI countries, indicating a need to improve awareness. The male/female ratio decreased between 1990 and 2019, possibly accounted for by increasing clinical attention to ASD in females. Our results suggest that ASD detection in low SDI countries is suboptimal, and that ASD prevention/treatment in countries with high SDI should be improved, considering the increasing prevalence of the disorder. Additionally, growing attention is being paid to ASD diagnosis in females, who might have been left behind by ASD epidemiologic and clinical research previously. ASD burden estimates are underestimated as GBD does not account for mortality in ASD.

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16. Wong ASK, Burns S, Woodruff E. Examining the impact of social stressor stimuli in eliciting physiological reactivity in children and adolescents with autism spectrum disorder: a systematic review and meta-analysis protocol. BMJ Open;2022 (Jun 29);12(6):e060048.

INTRODUCTION: Stress is not experienced the same by everyone. Some individuals, such as individuals with autism spectrum disorder (ASD), are at risk of heightened sensitivity to stress responses. ASD is a neurodevelopmental disorder commonly characterised by deficits in social communication and social interaction. Among different stressor stimuli, social stressors are particularly worth our attention due to the social and communication challenges inherent in ASD. This study aims to systematically evaluate different social stressor stimuli in eliciting physiological reactivity in ASD, focusing on the children and adolescent population. METHODS AND ANALYSIS: We designed a study protocol for this study and submitted it to PROSPERO for systematic review registration. Any studies with children and adolescents with ASD between the ages of 0 and 18 in clinical and community settings will be included. All types of social stressor interventions will be included. The outcome of interest will include studies with physiological activity of the participants being measured, for example, measures related to autonomic functioning, electrodermal functioning and cortisol level. The primary literature sources will be across four electronic databases: MEDLINE, Embase, PsycInfo and CINAHL in August 2021. The second source of literature will be across grey literature, including ProQuest Dissertations & Theses Global and across clinical trial registries in August 2021. Hand searching of references will be performed on the reference lists of all included studies. Two volunteers pursuing postgraduate-level studies will independently search and screen potential studies for eligibility. Finally, all references considered by hand searching will be reviewed by two researchers. The methodological quality of the research will be assessed by adopting the quality assessment used by a previous study. The assessment consists of four primary categories: descriptive validity, internal validity, external validity and statistical conclusion validity. ETHICS AND DISSEMINATION: No ethical approval is required for this study. Results will be disseminated through conferences and publications in relevant peer-reviewed journals. PROSPERO REGISTRATION NUMBER: CRD42021244039.

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17. Xu Y, Wang Y, Xu J, Song Y, Liu B, Xiong Z. Leveraging Existing 16SrRNA Microbial Data to Define a Composite Biomarker for Autism Spectrum Disorder. Microbiol Spectr;2022 (Jun 28):e0033122.

Cumulative studies have utilized high-throughput sequencing of the 16SrRNA gene to characterize the composition and structure of the microbiota in autism spectrum disorder (ASD). However, they do not always obtain consistent results; thus, conducting cross-study comparisons is necessary. This study sought to analyze the alteration of fecal microbiota and the diagnostic capabilities of gut microbiota biomarkers in individuals with ASD using the existing 16SrRNA microbial data and explore heterogeneity among studies. The raw sequence and metadata from 10 studies, including 1,019 samples, were reanalyzed. Results showed no significant difference in alpha diversity of fecal microbiota between ASD and the control group. However, a significant difference in the composition structure of fecal microbiota was observed. Given the large differences in sample selection and technical differences, the separation of fecal microbiota between ASD and controls was not observed. Subgroup analysis was performed on the basis of different country of origin, hypervariable regions, and sequencing platforms, and the dominant genera in ASD and healthy control groups were determined by linear discriminant analysis (LDA) of the effect size (LEfSe) algorithm and Wilcoxon rank-sum test. Machine learning analyses were carried out to determine the diagnostic capabilities of potential microbial biomarkers. A total of 12 genera were identified to distinguish ASD from control, and the AUC of the training set and verification set was 0.757 and 0.761, respectively. Despite cohort heterogeneity, gut microbial dysbiosis of ASD has been proven to be a widespread phenomenon. Therefore, fecal microbial markers are of great significance in diagnosing ASD diseases and possible candidates for further mechanistic study of the role of intestinal microbiota in ASD. IMPORTANCE This study provides an updated analysis to characterize the gut microbiota in ASD using 16SrRNA gene high-throughput sequencing data from 10 publicly available studies. Our analysis suggests an association between the fecal microbiota and ASD. Sample selection and technical differences between studies may interfere with the species composition analysis of the ASD group and control group. By summarizing the results of 16SrRNA gene sequencing from multiple fecal samples, we can provide evidence to support the use of microbial biomarkers to diagnose the occurrence of ASD. Our study provides a new perspective for further revealing the correlation between gut microbiota and ASD from the perspective of 16SrRNA sequencing in larger samples.

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18. Yang XY, Wang YY, Zhou YP, He J, Mei MJ, Zhang MN, Wang B, Zhou WJ, Luo MH, Wang QH, Li ZY, Xu Y, Lu Q, Zou LP. Postnatal Cytomegalovirus Infection May Increase the Susceptibility of Tuberous Sclerosis Complex to Autism Spectrum Disorders. Microbiol Spectr;2022 (Jun 29);10(3):e0186421.

Autism spectrum disorder (ASD), a highly hereditary and heterogeneous neurodevelopmental disorder, is influenced by genetic and environmental factors. Tuberous sclerosis complex (TSC) is a common syndrome associated with ASD. Cytomegalovirus (CMV) infection is an environmental risk factor for ASD. The similarities in pathological and mechanistic pathways of TSC and CMV intrigued us to investigate whether CMV and TSC interacted in ASD’s occurrence. We detected CMV IgG seroprevalence of 308 TSC patients from our prospective cohort (September 2011 to March 2021) and 93 healthy children by magnetic particle indirect chemiluminescence immunoassay. A total of 206 TSC patients enrolled were divided into ASD and non-ASD groups, and the relationship between ASD and CMV seroprevalence was analyzed. Nested PCR and Western blot were used to detect CMV DNAs and proteins in cortical malformations of seven TSC patients with and without ASD. No difference was found in CMV seroprevalence between TSC patients and healthy children (74.0% versus 72.0%, P = 0.704). Univariate analysis showed the seroprevalence in TSC patients with ASD was higher than that in TSC patients without ASD (89.2% versus 75.1%, P = 0.063), and multifactorial analysis showed that CMV seroprevalence was a risk factor for ASD in TSC patients (OR = 3.976, 95% CI = 1.093 to 14.454). Moreover, CMV was more likely to be detected in the cortical malformations in TSC patients with ASD but not in those without ASD. The findings demonstrated that CMV may increase the susceptibility of TSC to ASD. IMPORTANCE CMV is an environmental risk factor for ASD, but its role in syndromic autism with known genetic etiology has been rarely studied. The pathogenesis of ASD is related to the interaction between environmental and genetic factors. This study demonstrated that CMV can contribute to the occurrence of ASD related to TSC, a common genetic syndrome associated with ASD. Our findings provided support for the theory of gene-environment interaction (G × E) in pathogenesis of ASD and a new perspective for the prevention and therapy for TSC related ASD.

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19. Zhong C, Shah R, Rando J, Park B, Girardi T, Walker CK, Croen LA, Fallin MD, Hertz-Picciotto I, Lee BK, Schmidt RJ, Volk HE, Newschaffer CJ, Salafia CM, Lyall K. Placental morphology in association with autism-related traits in the EARLI study. BMC Pregnancy Childbirth;2022 (Jun 28);22(1):525.

BACKGROUND: In prior work we observed differences in morphology features in placentas from an autism-enriched cohort as compared to those from a general population sample. Here we sought to examine whether these differences associate with ASD-related outcomes in the child. METHODS: Participants (n = 101) were drawn from the Early Autism Risk Longitudinal Investigation (EARLI), a cohort following younger siblings of children with autism spectrum disorder (ASD). ASD-related outcomes, including the Social Responsiveness Scale (SRS), Mullen Scales of Early Learning (MSEL) Early Learning Composite, and ASD diagnosis, were assessed at age 3. Crude and adjusted linear regression was used to examine associations between placental morphological features (parametrized continuously and in quartiles) and SRS and MSEL scores; comparisons by ASD case status were explored as secondary analyses due to the small number of cases (n = 20). RESULTS: In adjusted analyses, we observed a modest positive association between umbilical cord eccentricity, defined as the ratio of the maximum:minimum radius from the cord insertion point, and SRS scores (Beta = 1.68, 95%CI = 0.45, 2.9). Positive associations were also suggested between placental maximum thickness and cord centrality and SRS scores, though these were estimated with little precision. Associations between other placental morphological features and outcomes were not observed. CONCLUSIONS: Our analyses suggested a potential association between umbilical cord features and ASD-related traits, of interest as non-central cord insertion may reflect reduced placenta efficiency. Future studies with larger sample sizes are needed to further examine these and other placental features in association with ASD-related outcomes.

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