1. Chellappa SL. Neuroaffirming services for autistic people. The lancet Psychiatry. 2023.

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2. Costa-Cordella S, Soto-Icaza P, Borgeaud K, Grasso-Cladera A, Malberg NT. Towards a comprehensive approach to mentalization-based treatment for children with autism: integrating attachment, neurosciences, and mentalizing. Frontiers in psychiatry. 2023; 14: 1259432.

Autism spectrum disorder (ASD) is diagnosed based on socio-communicative difficulties, which are believed to result from deficits in mentalizing, mainly evidenced by alterations in recognizing and responding to the mental states of others. In recent years, efforts have been made to develop mentalization-based treatment (MBT) models for this population. These models focus on enhancing individuals’ ability to understand and reflect on their own mental states, as well as those of others. However, MBT approaches for people with ASD are limited by their existing theoretical background, which lacks a strong foundation grounded in neuroscience-based evidence properly integrated with attachment, and mentalizing. These are crucial aspects for understanding psychological processes in autism, and as such, they play a pivotal role in shaping the development of tailored and effective therapeutic strategies for this specific population. In this paper we review evidence related to the neurobiological, interpersonal, and psychological dimensions of autism and their implications for mentalizing processes. We also review previous mentalization-based frameworks on the psychosis continuum to provide a comprehensive understanding of attachment, neurobiology, and mentalization domains in therapeutic approaches for autism. After presenting a synthesis of the literature, we offer a set of clinical strategies for the work with children with autism. Finally, we provide recommendations to advance the field towards more robust models that can serve as a basis for evidence-based therapeutic strategies.

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3. Deng L, He WZ, Zhang QL, Wei L, Dai Y, Liu YQ, Chen ZL, Ren T, Zhang LL, Gong JB, Li F. Caregiver-child interaction as an effective tool for identifying autism spectrum disorder: evidence from EEG analysis. Child and adolescent psychiatry and mental health. 2023; 17(1): 138.

BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that affects individuals across their lifespan. Early diagnosis and intervention are crucial for improving outcomes. However, current diagnostic methods are often time-consuming, and costly, making them inaccessible to many families. In the current study, we aim to test caregiver-child interaction as a potential tool for screening children with ASD in clinic. METHODS: We enrolled 85 preschool children (Mean age: 4.90 ± 0.65 years, 70.6% male), including ASD children with or without developmental delay (DD), and typical development (TD) children, along with their caregivers. ASD core symptoms were evaluated by Childhood Autism Rating Scale (CARS) and Autism Diagnostic Observation Schedule-Calibrated Severity Scores (ADOS-CSS). Behavioral indicators were derived from video encoding of caregiver-child interaction, including social involvement of children (SIC), interaction time (IT), response of children to social cues (RSC), time for caregiver initiated social interactions (GIS) and time for children initiated social interactions (CIS)). Power spectral density (PSD) values were calculated by EEG signals simultaneously recorded. Partial Pearson correlation analysis was used in both ASD groups to investigate the correlation among behavioral indicators scores and ASD symptom severity and PSD values. Receiver operating characteristic (ROC) analysis was used to describe the discrimination accuracy of behavioral indicators. RESULTS: Compared to TD group, both ASD groups demonstrated significant lower scores of SIC, IT, RSC, CIS (all p values < 0.05), and significant higher time for GIS (all p values < 0.01). SIC scores negatively correlated with CARS (p = 0.006) and ADOS-CSS (p = 0.023) in the ASD with DD group. Compared to TD group, PSD values elevated in ASD groups (all p values < 0.05), and was associated with SIC (theta band: p = 0.005; alpha band: p = 0.003) but not IQ levels. SIC was effective in identifying both ASD groups (sensitivity/specificity: ASD children with DD, 76.5%/66.7%; ASD children without DD, 82.6%/82.2%). CONCLUSION: Our results verified the behavioral paradigm of caregiver-child interaction as an efficient tool for early ASD screening.

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4. Fang Y, Cui Y, Yin Z, Hou M, Guo P, Wang H, Liu N, Cai C, Wang M. Comprehensive systematic review and meta-analysis of the association between common genetic variants and autism spectrum disorder. Gene. 2023; 887: 147723.

BACKGROUND: Autism spectrum disorder (ASD) is neurodevelopmental disorder characterized by stereotyped behavior and deficits in communication and social interactions. To date, numerous studies have investigated the associations between genetic variants and ASD risk. However, the results of these published studies lack a clear consensus. In the present study, we performed a systematic review on the association between genetic variants and ASD risk. Meanwhile, we conducted a meta-analysis on available data to identify the association between the single nucleotide polymorphisms (SNPs) of candidate genes and ASD risk. METHODS: We systematically searched public databases including English and Chinese from their inception to August 1, 2022. Two independent reviewers extracted data and assessed study quality. Odds ratio and 95 % confidence interval were used as effect indexes to evaluate the association between the SNPs of candidate genes and the risk of ASD. Heterogeneity was explored through subgroup, sensitivity, and meta-regression analyses. Publication bias was assessed by using Egger’s and Begg’s tests for funnel plot asymmetry. In addition, TSA analysis were performed to confirm the study findings. RESULTS: We summarized 84 SNPs of 32 candidate genes from 81 articles included in the study. Subsequently, we analyzed 16 SNPs of eight genes by calculating pooled ORs, and identified eight significant SNPs of contactin associated protein 2 (CNTNAP2), methylentetrahydrofolate reductase (MTHFR), oxytocin receptor (OXTR), and vitamin D receptor (VDR). Results showed that seven SNPs, including the CNTNAP2 rs2710102 (homozygote, heterozygote, dominant and allelic models) and rs7794745 (heterozygote and dominant models), MTHFR C677T (homozygote, heterozygote, dominant, recessive and allelic models) and A1298C (dominant and allelic models), OXTR rs2254298 (homozygote and recessive models), VDR rs731236 (homozygote, dominant, recessive and allelic models) and rs2228570 (homozygote and recessive models), were showed to be correlated with an increased ASD risk. By contrast, the VDR rs7975232 was correlated with a decreased the risk of ASD under the homozygote and allelic models. CONCLUSION: Our study summarized research evidence on the genetic variants of ASD and provides a broad and detailed overview of ASD risk genes. The C677T and A1298C polymorphisms of MTHFR, rs2710102 and rs7794745 polymorphisms of CNTNAP2, rs2254298 polymorphism of OXTR, and rs731236 and rs2228570 polymorphisms of VDR were genetic risk factors. The rs7975232 polymorphism of VDR was a genetic protective factor for ASD. Our study provides novel clues to clinicians and healthcare decision-makers to predict ASD susceptibility.

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5. Franco FO, Oliveira JS, Portolese J, Sumiya FM, Silva AF, Machado-Lima A, Nunes FLS, Brentani H. Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal. BMC medical informatics and decision making. 2023; 23(1): 285.

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.

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6. Grissom A, Finke E, Zane E. Verbal fluency and autism: Reframing current data through the lens of monotropism. Autism research : official journal of the International Society for Autism Research. 2023.

The purpose of this study was to reexamine research that used verbal fluency tasks to reinforce assumed deficits in word knowledge and retrieval in the autistic population. We identified seventeen articles that compared the performance of autistic and non-autistic people on verbal fluency measures and provided an interpretation of the observed performance. In this narrative review, we summarize many components of these studies, including a comprehensive account of how authors framed their research findings. Overall, results of the studies showed variation both between and within groups in terms of total number of correct words, how many subsequent words fell into subcategories, and how frequently participants switched between subcategories. Despite wide variation in findings across studies, authors consistently interpreted results as revealing or reinforcing autistic deficits. To contrast the deficit narrative, we offer an alternative interpretation of findings by considering how they could provide support for the autistic-led theory of monotropism. This alternative interpretation accounts for the inconsistencies in findings between studies, since wide individual variation in performance is an expected feature of the monotropic theory. We use our review as an exercise in reframing a body of literature from a neurodiversity-affirming perspective. We propose this as a case example and model for how autism research and clinical practice can move away from the consistent narrative of autism deficits that has pervaded our field for decades. Accordingly, we offer suggestions for future research and clinical practice.

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7. Jang H, Chen J, Iakoucheva LM, Nussinov R. Cancer and Autism: How PTEN Mutations Degrade Function at the Membrane and Isoform Expression in the Human Brain. Journal of molecular biology. 2023; 435(24): 168354.

Mutations causing loss of PTEN lipid phosphatase activity can promote cancer, benign tumors (PHTS), and neurodevelopmental disorders (NDDs). Exactly how they preferentially trigger distinct phenotypic outcomes has been puzzling. Here, we demonstrate that PTEN mutations differentially allosterically bias P loop dynamics and its connection to the catalytic site, affecting catalytic activity. NDD-related mutations are likely to sample conformations of the functional wild-type state, while sampled conformations for the strong, cancer-related driver mutation hotspots favor catalysis-primed conformations, suggesting that NDD mutations are likely to be weaker, and our large-scale simulations show why. Prenatal PTEN isoform expression data suggest exons 5 and 7, which harbor NDD mutations, as cancer-risk carriers. Since cancer requires more than a single mutation, our conformational and genomic analysis helps discover how same protein mutations can foster different clinical manifestations, articulates a role for co-occurring background latent driver mutations, and uncovers relationships of splicing isoform expression to life expectancy.

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8. Kaneko S, Hirano Y, Matsuzawa D, Oiji A, Tanaka K. [The Relationship between the Autistic Traits and Everyday Memory Processing in Adults with Autism Spectrum Disorder and Healthy Adults]. Brain and nerve = Shinkei kenkyu no shinpo. 2023; 75(12): 1361-6.

We investigated the association between everyday memory and autistic traits in adults with autism spectrum disorder (ASD, n=22) and healthy adults (n=20) by using the Rivermead Behavioral Memory Test (RBMT). A generalized linear model (GLM) was used to explore the relationships between the subjects’ performance on the RBMT as the objective variable and the composite score of the Autism Spectrum Quotient (AQ) as the explanatory variable. Multiple models were created with the AQ subscales (‘Social skills,’ ‘Attention-shifting,’ ‘Attention to details,’ ‘Communication,’ ‘Imagination’), age, gender, the full-scale intelligence quotient (FSIQ), the Patient Health Questionnaire-9 (PHQ-9), and the General Anxiety Disorder-7 (GAD-7) scale added as the moderator variables. The GLM revealed that the AQ subscale ‘Social skills’ significantly predicted the RBMT-total scores with age, gender, and psychological measures scores as the moderator variables (Model 4: B=0.752, 95%CI: 0.191 to 1.313, p<0.01). Also, The GLM revealed that the AQ subscale 'Communication', in addition to 'Social skills', significantly predicted the RBMT- 'Prospective memory' (Model 4: B=0.298, 95%CI: 0.19 to 0.578, p<0.05). These results indicate an influence of social skills on everyday memory functioning, highlighting the weakness of memory processing in everyday life situations among individuals with ASD.

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9. Kim JH, Hong J, Choi H, Kang HG, Yoon S, Hwang JY, Park YR, Cheon KA. Development of Deep Ensembles to Screen for Autism and Symptom Severity Using Retinal Photographs. JAMA network open. 2023; 6(12): e2347692.

IMPORTANCE: Screening for autism spectrum disorder (ASD) is constrained by limited resources, particularly trained professionals to conduct evaluations. Individuals with ASD have structural retinal changes that potentially reflect brain alterations, including visual pathway abnormalities through embryonic and anatomic connections. Whether deep learning algorithms can aid in objective screening for ASD and symptom severity using retinal photographs is unknown. OBJECTIVE: To develop deep ensemble models to differentiate between retinal photographs of individuals with ASD vs typical development (TD) and between individuals with severe ASD vs mild to moderate ASD. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study was conducted at a single tertiary-care hospital (Severance Hospital, Yonsei University College of Medicine) in Seoul, Republic of Korea. Retinal photographs of individuals with ASD were prospectively collected between April and October 2022, and those of age- and sex-matched individuals with TD were retrospectively collected between December 2007 and February 2023. Deep ensembles of 5 models were built with 10-fold cross-validation using the pretrained ResNeXt-50 (32×4d) network. Score-weighted visual explanations for convolutional neural networks, with a progressive erasing technique, were used for model visualization and quantitative validation. Data analysis was performed between December 2022 and October 2023. EXPOSURES: Autism Diagnostic Observation Schedule-Second Edition calibrated severity scores (cutoff of 8) and Social Responsiveness Scale-Second Edition T scores (cutoff of 76) were used to assess symptom severity. MAIN OUTCOMES AND MEASURES: The main outcomes were participant-level area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. The 95% CI was estimated through the bootstrapping method with 1000 resamples. RESULTS: This study included 1890 eyes of 958 participants. The ASD and TD groups each included 479 participants (945 eyes), had a mean (SD) age of 7.8 (3.2) years, and comprised mostly boys (392 [81.8%]). For ASD screening, the models had a mean AUROC, sensitivity, and specificity of 1.00 (95% CI, 1.00-1.00) on the test set. These models retained a mean AUROC of 1.00 using only 10% of the image containing the optic disc. For symptom severity screening, the models had a mean AUROC of 0.74 (95% CI, 0.67-0.80), sensitivity of 0.58 (95% CI, 0.49-0.66), and specificity of 0.74 (95% CI, 0.67-0.82) on the test set. CONCLUSIONS AND RELEVANCE: These findings suggest that retinal photographs may be a viable objective screening tool for ASD and possibly for symptom severity. Retinal photograph use may speed the ASD screening process, which may help improve accessibility to specialized child psychiatry assessments currently strained by limited resources.

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10. Kramer JM, Beasley JB, Caoili A, Kalb L, Urquilla MP, Klein AE, Poncelet J, Black S, Tessler RC. Development and content validity of the Person Experiences Interview Survey (PEIS): a measure of the mental health services experiences of people with developmental disabilities. Frontiers in psychiatry. 2023; 14: 1271210.

PURPOSE: People with developmental disabilities and mental health service experiences have a right to be included in healthcare decisions, including the evaluation of their mental health services and providers. However, few self-report measures address this need. This study aimed to fill this gap by developing and evaluating the content validity, including comprehension, relevance, and comprehensiveness, of the Person Experiences Interview Survey (PEIS) with people with developmental disabilities and mental health experiences. METHODS: The research team established a measurement framework based on the Family Experiences Interview Survey (FEIS), resulting in 21 PEIS items that were written in collaboration with young adults with developmental disabilities and mental health service experiences. Comprehension, relevance, and comprehensiveness were evaluated through cognitive interviews with people with developmental disabilities and mental health service experiences (respondents; n = 9) ages 23-49 years. Comprehensiveness and relevance were also evaluated in focus groups with family caregivers (n = 9) and mental health providers (n = 10) who serve this population. Two researchers independently coded open-ended responses to the PEIS for comprehension. A content validity index (CVI), indicating relevance, was calculated for each participant group for each item, and comprehensiveness was rated for item sets. RESULTS: Fifteen of the 21 items met the criteria of ≥80% comprehension, with 89-100% of responses containing all or some intended information. All items met the CVI ≥80% criterion in at least two of the three groups. In all item sets, between 1 and 4 family members or providers felt one question was missing. Respondents used the response scale in a manner that corresponded with their open-ended descriptions, and family caregivers and providers had positive feedback about the response scale’s visual cues and number of choices. Using these findings, four items were removed and six items were revised, resulting in a 17-item measure. CONCLUSION: This study presents a novel and promising measure, the Person Experiences Interview Survey (PEIS). It also demonstrates that the employment of accessible methods allows people with developmental disabilities to meaningfully evaluate mental health services and providers. The PEIS shows great promise for application in the field by engaging those directly involved in the evaluation of mental health services and providers.

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11. Maleki M, Noorimotlagh Z, Mirzaee SA, Jaafarzadeh N, Martinez SS, Rahim F, Kaffashian M. An updated systematic review on the maternal exposure to environmental pesticides and involved mechanisms of autism spectrum disorder (ASD) progression risk in children. Reviews on environmental health. 2023; 38(4): 727-40.

Autism spectrum disorder (ASD) increased dramatically over the past 25 years because of genetic and environmental factors. This systematic review (SR) aimed to determine the association between maternal exposure during pregnancy to environmental pesticides and other associations with the risk of ASD progression in children. PubMed (MEDLINE), Scopus (Elsevier) and the Institute for Scientific Information (ISI) Web of Science were searched using appropriate keywords up to March 2021. Twenty-four studies met the inclusion/exclusion criteria and were selected. Most studies reported that ASD increases the risk of offspring after prenatal exposure to environmental pesticides in pregnant mother’s residences, against offspring of women from the same region without this exposure. The main potential mechanisms inducing ASD progressions are ROS and prostaglandin E2 synthesis, AChE inhibition, voltage-gated sodium channel disruption, and GABA inhibition. According to the included studies, the highest rates of ASD diagnosis increased relative to organophosphates, and the application of the most common pesticides near residences might enhance the prevalence of ASD.

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12. McManus B, Kana R, Rajpari I, Holm HB, Stavrinos D. Risky driving behavior among individuals with Autism, ADHD, and typically developing persons. Accident; analysis and prevention. 2023; 195: 107367.

INTRODUCTION: Many individuals with Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) often experience difficulty with driving, including difficulty with obtaining a driver’s license as well as driving safely and efficiently. Such difficulties negatively impact their ability to function independently and participate in daily activities that require driving. ASD and ADHD commonly occur co-morbidly and share many overlapping clinical features. Few studies have directly compared the nature of difficulties in driving safety outcomes between ASD and ADHD. The overarching goal of the current study was to characterize and compare self-reported driving behavior among young autistic drivers, ADHD drivers, and typically developing (TD) drivers. METHOD: Fifty-four participants (14 ASD, 20 ADHD, 20 TD); ages 16-30) completed the Autism Spectrum Quotient and ADHD Adult Rating scale as a method of screening of symptoms. All three groups then completed the Driving Behavior Questionnaire (DBQ), which measured self-reported driving violations, driving errors, and overall risky driving behavior. The three groups of ASD, ADHD, and TD individuals were then compared regarding symptomology and driving behavior differences. RESULTS: One-way ANOVAs indicated group differences in DBQ total scores and DBQ errors. Drivers with ADHD reported significantly greater overall risky driving behaviors and driving errors compared to ASD and TD drivers. There were no significant differences between ASD and TD drivers in reported risky driving behaviors and errors. Linear regressions indicated that among all drivers, self-reported ADHD symptoms were significantly associated with higher levels of self-reported overall risky driving and driving errors, regardless of diagnostic group. DISCUSSION: Risky driving and driving errors may be more closely related to symptoms that are characteristic of ADHD. This has implications for individuals with ADHD and autistic individuals who often show or report higher rates of ADHD symptoms. Future studies should compare driving skills of ASD and ADHD drivers using objective measures of driving performance, such as driving simulators or on-road tests.

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13. Neo WS, Foti D, Keehn B, Kelleher B. Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis. Translational psychiatry. 2023; 13(1): 389.

Narrative reviews have described various resting-state EEG power differences in autism across all five canonical frequency bands, with increased power for low and high frequencies and reduced power for middle frequencies. However, these differences have yet to be quantified using effect sizes and probed robustly for consistency, which are critical next steps for clinical translation. Following PRISMA guidelines, we conducted a systematic review of published and gray literature on resting-state EEG power in autism. We performed 10 meta-analyses to synthesize and quantify differences in absolute and relative resting-state delta, theta, alpha, beta, and gamma EEG power in autism. We also conducted moderator analyses to determine whether demographic characteristics, methodological details, and risk-of-bias indicators might account for heterogeneous study effect sizes. Our literature search and study selection processes yielded 41 studies involving 1,246 autistic and 1,455 neurotypical individuals. Meta-analytic models of 135 effect sizes demonstrated that autistic individuals exhibited reduced relative alpha (g = -0.35) and increased gamma (absolute: g = 0.37, relative: g = 1.06) power, but similar delta (absolute: g = 0.06, relative: g = 0.10), theta (absolute: g = -0.03, relative: g = -0.15), absolute alpha (g = -0.17), and beta (absolute: g = 0.01, relative: g = 0.08) power. Substantial heterogeneity in effect sizes was observed across all absolute (I(2): 36.1-81.9%) and relative (I(2): 64.6-84.4%) frequency bands. Moderator analyses revealed that age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not moderate study effect sizes. In contrast, resting-state paradigm type (eyes-closed versus eyes-open) moderated absolute beta, relative delta, and relative alpha power effect sizes, and resting-state recording duration moderated relative alpha power effect sizes. These findings support further investigation of resting-state alpha and gamma power as potential biomarkers for autism.

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14. Neubauer J, Kaiser A, Hohmann S. [Gut Microbiota and Autism Spectrum Disorders: An Overview of Correlations and Potential Implications for Therapeutic Interventions]. Zeitschrift fur Kinder- und Jugendpsychiatrie und Psychotherapie. 2023.

Gut Microbiota and Autism Spectrum Disorders: An Overview of Correlations and Potential Implications for Therapeutic Interventions Abstract: At the beginning of research on microbiota, researchers focused mainly on the role of microbiota dysbiosis in the development of gastrointestinal diseases. However, over the last years, researchers have also identified correlations with other physical processes and neuropsychiatric diseases such as autism spectrum disorder. These correlations are believed to be at least partly mediated through the brain-gut-microbiome axis. An altered composition of microbiota in patients with autism spectrum disorder was detected compared to healthy controls. Today, the discussion centers around a possible systemic impact of the metabolites of some microbiota or microbiota-induced chronic inflammatory processes on the brain (mediated through the brain-gut-microbiome axis) as an underlying mechanism. Still, the specific underlying mechanisms remain largely unknown, so conclusions on therapeutic implications are difficult to determine. Here, we describe some promising approaches to improving autistic behavior through dietary changes, the use of prebiotics and probiotics, stool transplantation from healthy controls, and restricted absorbance of certain metabolites. We need further clinical studies of high quality to fully understand the pathophysiology of autism spectrum disorder and to improve diagnostic and therapeutic strategies.

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15. Stone LE, Kelly MP, Alexander M, Brandel M, Lam SK, Ravindra VM. Rett Syndrome-Associated Scoliosis: Analysis of National Trends and Treatment Patterns of a Rare Indication for Posterior Instrumented Fusion. Spine. 2023; 48(24): E409-e16.

STUDY DESIGN: Retrospective database cohort study. OBJECTIVE: To evaluate U.S. treatment trends and inpatient outcomes for children undergoing posterior spinal fusion (PSF) for Rett syndrome (RTT)-associated scoliosis (RAS). SUMMARY OF BACKGROUND DATA: RTT is a rare, sporadic neurodevelopmental disorder presenting in childhood with developmental regression, ataxia, and seizures. RAS occurs in 50% to 80% of cases of RTT, but little is known about the case volume and perioperative experience for children undergoing PSF. MATERIALS AND METHODS: Using the International Classification of Diseases Ninth and 10th revision codes in the national Kids’ Inpatient Database, we identified children with RTT who underwent PSF from 2000 to 2019. Annual case volumes were analyzed. Clinical characteristics and outcomes were compared with those of a cohort of patients with neuromuscular scoliosis (NMS). RESULTS: Among 220 patients with RAS, 216 (98.2%) were females (mean age at surgery: 12.3±3.3 yr). Surgical case incidence steadily increased over 19 years, with more RAS admissions in the South (31.4%). Overall, patients with RAS demonstrated a higher mean Elixhauser Comorbidity Index score (2 vs . 1, P < 0.001) and had more perioperative complications (41.4% vs . 18%, P < 0.001) than patients with NMS. RTT diagnosis independently predicted higher odds of any complications (odds ratio: 1.98, P < 0.001) and increased length of stay (odds ratio: 1.18, P = 0.009) for admissions for PSF. CONCLUSIONS: Surgical treatment for RAS is rare but increased over a 19-year period. Cases appear to be clustering by region, with the highest proportion in the South. The higher Elixhauser Comorbidity Index in RAS patients predicted higher costs, longer hospital stays, more complications (particularly respiratory), and more nonroutine discharge disposition than in other patients with NMS. RTT was independently associated with higher odds of complications and longer length of stay. Because RAS cases appear to be increasing in number, future studies should emphasize methods to reduce morbidity and investigate deformity-specific metrics to help better understand this population.

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16. van der Miesen AIR, Shi SY, Lei HC, Ngan CL, VanderLaan DP, Wong WI. Gender diversity in a Chinese community sample and its associations with autism traits. Autism research : official journal of the International Society for Autism Research. 2023.

Emerging evidence suggests that gender dysphoria or gender diversity (GD) intersects frequently with autism spectrum disorder or autism traits. However, the magnitude and interpretation of this link continue to be debated. Most child studies on this topic were performed in clinical populations, and little is known about the generalizability of this co-occurrence to the broader community, especially to non-Western samples. Also, little is known about whether specific subdomains of autism are more strongly associated with GD. Therefore, we investigated GD and its association with autism traits in a Chinese community sample of 4-12-year-olds (N = 379; 51% birth-assigned girls). Parents provided information about GD characteristics using the standardized Gender Identity Questionnaire for Children and autism traits using the Chinese version of the Autism-Spectrum Quotient-Children. In addition, broader behavioral and emotional challenges were measured by the Behavior Problem Index (BPI) to account for psychological challenges other than autism traits. In this community sample of Chinese children, increased GD was associated with increased autism traits, even after accounting for the BPI. Of the four subscales, the Imagination and Patterns subscales in birth-assigned girls and the Imagination subscale in birth-assigned boys were especially associated with GD. These findings indicate that the association between GD and autism traits generalizes to a nonclinical, non-Western sample. Clinicians and researchers working with clinical as well as community children should thus pay attention to the co-occurrence of GD and autism traits, in and outside the West.

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17. Wang C, Chen W, Jiang Y, Xiao X, Zou Q, Liang J, Zhao Y, Wang Q, Yuan T, Guo R, Liu X, Liu Z. A synbiotic formulation of Lactobacillus reuteri and inulin alleviates ASD-like behaviors in a mouse model: the mediating role of the gut-brain axis. Food & function. 2023.

Autism Spectrum Disorder (ASD), a complex neurodevelopmental disorder marked by social communication deficits and repetitive behaviors, may see symptom amelioration through gut microbiota modulation. This study investigates the effects of a synbiotic – specifically a probiotic amplified by prebiotic supplementation – on ASD-like mouse model’s social deficiencies. This model was established via valproic acid injection into pregnant females. Post-weaning, male progeny received daily synbiotic treatment, a combination of Lactobacillus reuteri (L. reuteri) and inulin, for four weeks. Results indicated that the synbiotic rectified social impairments and attenuated inflammatory cytokine expressions in the brain. Moreover, synbiotic intervention protected gut barrier integrity and altered the gut microbiota composition, enhancing the butyrate-producing Bifidobacterium abundance. The synbiotic elevated metabolites such as butyrate and 3-hydroxybutyric acid (3-HB), alongside upregulated genes associated with 3-HB synthesis in the colon and liver, and brain receptors. Conclusively, the synbiotic combination of L. reuteri and inulin mitigated ASD-related social impairments, partially via their regulatory effect on the gut-brain axis.

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18. Wiggins LD, Overwyk K, Daniels J, Barger B, Crain H, Grzadzinski R, Moody E, Reynolds A, Reyes N, Rosenberg C, Rosenberg S, Pazol K. Risk factors and clinical correlates of sensory dysfunction in preschool children with and without autism spectrum disorder. Autism research : official journal of the International Society for Autism Research. 2023.

Sensory dysfunction is a common feature of autism spectrum disorder (ASD). The objectives of this analysis were to examine risk factors and clinical correlates of sensory dysfunction in preschool children with and without ASD. Children aged 2-5 years were enrolled in a multi-site case-control study. Data were collected in eight areas across the United States in three phases. Caregivers completed an interview with questions on assisted delivery, maternal alcohol use, maternal anxiety during pregnancy, pregnancy weight gain, neonatal jaundice, preterm birth, and child sensory diagnosis given by a healthcare provider. Caregivers also completed an interview and questionnaires on sensory symptoms and clinical correlates of sensory dysfunction in their child. There were 2059 children classified as ASD, 3139 as other developmental delay or disability (DD), and 3249 as population comparison (POP). Caregivers reported significantly more sensory diagnoses and sensory symptoms in children classified as ASD than DD or POP (23.7%, 8.6%, and 0.8%, respectively, for a sensory diagnosis and up to 78.7% [ASD] vs. 49.6% [DD] for sensory symptoms). Maternal anxiety during pregnancy and neonatal jaundice were significantly associated with a sensory diagnosis and certain sensory symptoms in children with ASD and DD. Children’s anxiety, attention deficits/hyperactivity, and sleep problems were significantly albeit subtly correlated with both a sensory diagnosis and sensory symptoms in children with ASD and DD. These findings support sensory dysfunction as a distinguishing symptom of ASD in preschool children and identify risk factors and clinical correlates to inform screening and treatment efforts in those with atypical development.

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19. Xu FX, Wang XT, Cai XY, Liu JY, Guo JW, Yang F, Chen W, Schonewille M, De Zeeuw C, Zhou L, Shen Y. Purkinje-cell-specific MeCP2 deficiency leads to motor deficits and autistic-like behavior due to aberrations in PTP1B-TrkB-SK signaling. Cell reports. 2023; 42(12): 113559.

Patients with Rett syndrome suffer from a loss-of-function mutation of the Mecp2 gene, which results in various symptoms including autistic traits and motor deficits. Deletion of Mecp2 in the brain mimics part of these symptoms, but the specific function of methyl-CpG-binding protein 2 (MeCP2) in the cerebellum remains to be elucidated. Here, we demonstrate that Mecp2 deletion in Purkinje cells (PCs) reduces their intrinsic excitability through a signaling pathway comprising the small-conductance calcium-activated potassium channel PTP1B and TrkB, the receptor of brain-derived neurotrophic factor. Aberration of this cascade, in turn, leads to autistic-like behaviors as well as reduced vestibulocerebellar motor learning. Interestingly, increasing activity of TrkB in PCs is sufficient to rescue PC dysfunction and abnormal motor and non-motor behaviors caused by Mecp2 deficiency. Our findings highlight how PC dysfunction may contribute to Rett syndrome, providing insight into the underlying mechanism and paving the way for rational therapeutic designs.

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20. Yang J, Xu X, Sun M, Ruan Y, Sun C, Li W, Gao X. Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data. Cerebral cortex (New York, NY : 1991). 2023.

Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial correlation, or causality. Such an approach fails in discovering the potential complementary topology information of FCNs at different connection patterns, resulting in lower diagnostic performance. Consequently, toward an accurate autism spectrum disorder diagnosis, a straightforward ambition is to combine the multiple connectivity patterns for the diagnosis of neurological disorders. To this end, we conduct functional magnetic resonance imaging data to construct multiple brain networks with different connectivity patterns and employ kernel combination techniques to fuse information from different brain connectivity patterns for autism diagnosis. To verify the effectiveness of our approach, we assess the performance of the proposed method on the Autism Brain Imaging Data Exchange dataset for diagnosing autism spectrum disorder. The experimental findings demonstrate that our method achieves precise autism spectrum disorder diagnosis with exceptional accuracy (91.30%), sensitivity (91.48%), and specificity (91.11%).

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