1. Aggarwal S. Interdisciplinary, team-based approach for effective care of self-injury in individuals with intellectual and developmental disabilities. Evid Based Nurs. 2025.

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2. Dilshad A, Khan MH, Sai Sujana C, Ahsan A, Mehta F, Meshram Y, Singh PK, Verma A, Singh AK, Akbar A. The relationship between autism spectrum disorder and screen time in children: a literature review. Ann Med Surg (Lond). 2025; 87(7): 4184-93.

BACKGROUND: Autism spectrum disorder (ASD) affects millions of children globally, significantly impacting their quality of life. Understanding factors that contribute to symptoms, is essential for improving outcomes. This review aims to explore the relationship between screen time and ASD and provide insights for targeted interventions. METHODS: PubMed, Web of Science, and Google Scholar were searched for studies on the link between screen time and ASD symptoms. RESULTS: The findings suggest a possible link between excessive screen time and increased ASD symptoms, including social withdrawal and communication challenges. Some studies propose a bidirectional relationship, where children with this disorder may prefer more screen time due to social isolation. CONCLUSION: Although there is evidence suggesting a link between screen time and ASD, the relationship remains unclear; further research is needed to better understand these connections and develop effective interventions for children with this disorder.

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3. Liu DF, Zhang YC, Li JD. [Circadian rhythm disturbances and neurodevelopmental disorders]. Sheng Li Xue Bao. 2025; 77(4): 678-88.

Neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and intellectual developmental disorder (IDD), are highly prevalent and lack effective treatments, posing significant health challenges. These disorders are frequently comorbid with disruptions in sleep rhythms, and sleep-related indicators are often used to assess disease severity and treatment efficacy. Recent evidence has highlighted the crucial roles of circadian rhythm disturbances and circadian clock gene mutations in the pathogenesis of NDDs. This review focuses on the mechanisms by which circadian rhythm disruptions and circadian clock gene mutations contribute to cognitive, behavioral, and emotional disorders associated with NDDs, particularly through the dysregulation of dopamine system. Additionally, we discussed the potential of targeting the circadian system as novel therapeutic strategies for the treatment of NDDs.

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4. Sariyanidi E, Yankowitz L, Schultz RT, Herrington JD, Tunc B, Cohn J. Beyond FACS: Data-driven Facial Expression Dictionaries, with Application to Predicting Autism. Proc Int Conf Autom Face Gesture Recognit. 2025; 2025.

The Facial Action Coding System (FACS) has been used by numerous studies to investigate the links between facial behavior and mental health. The laborious and costly process of FACS coding has motivated the development of machine learning frameworks for Action Unit (AU) detection. Despite intense efforts spanning three decades, the detection accuracy for many AUs is considered to be below the threshold needed for behavioral research. Also, many AUs are excluded altogether, making it impossible to fulfill the ultimate goal of FACS-the representation of any facial expression in its entirety. This paper considers an alternative approach. Instead of creating automated tools that mimic FACS experts, we propose to use a new coding system that mimics the key properties of FACS. Specifically, we construct a data-driven coding system called the Facial Basis, which contains units that correspond to localized and interpretable 3D facial movements, and overcomes three structural limitations of automated FACS coding. First, the proposed method is completely unsupervised, bypassing costly, laborious and variable manual annotation. Second, Facial Basis reconstructs all observable movement, rather than relying on a limited repertoire of recognizable movements (as in automated FACS). Finally, the Facial Basis units are additive, whereas AUs may fail detection when they appear in a non-additive combination. The proposed method outperforms the most frequently used AU detector in predicting autism diagnosis from in-person and remote conversations, highlighting the importance of encoding facial behavior comprehensively. To our knowledge, Facial Basis is the first alternative to FACS for deconstructing facial expressions in videos into localized movements. We provide an open source implementation of the method at github.com/sariyanidi/FacialBasis.

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5. Simoncic V, Wenger R, Monnier M, Michelon C, Peries M, Hough I, Klook I, Lepeule J, Mortamais M, Baghdadli A. Perinatal Air Pollution Exposure and Autism spectrum disorder Severity: The Intertwined Roles of Green Space, Grey Space and Healthcare Accessibility – A Cohort Study. Environ Res. 2025: 122577.

INTRODUCTION: Autism spectrum disorder (ASD) is influenced by environmental, genetic, and socio-economic factors. While air pollution exposure during development has been linked to ASD outcomes, the roles of green spaces, grey spaces, and healthcare accessibility in this relationship remain understudied. This research examines how these factors during the first 1000 days (from conception to the first two years of life), moderate the association between air pollution and ASD severity in children from the ELENA cohort (« Etude Longitudinale chez l’Enfant avec Autisme »). METHODS: Data from 237 children with ASD were analyzed. Perinatal exposure to particulate matter (PM(10) and PM(2.5)) was estimated using a validated model, with green spaces quantified using the normalized difference vegetation index (NDVI) and grey spaces through impervious surface coverage. Healthcare accessibility was measured as the distance to autism resource centers (CRA) from residential addresses. ASD severity was assessed using the total score of the Social Responsiveness Scale. Linear regression models within structural equation modeling estimated the effects of air pollution, green spaces, grey spaces, and healthcare accessibility on ASD severity. RESULTS: Higher PM exposures were paradoxically associated with lower ASD severity. However, grey spaces significantly moderated this association, with greater impervious surface coverage attenuating the negative association. Healthcare accessibility was crucial: when considering center proximity, pollution was no longer associated with ASD severity. CONCLUSIONS: These findings highlight the critical role of healthcare accessibility and environmental factors in shaping the relationship between air pollution and ASD severity. Integrating geographic and environmental contexts is crucial when evaluating the environmental determinants of ASD outcomes.

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6. Srivarathan A, Bradford A, Shearkhani S, Heimlich L, Jefferson S, Miller KE, Smith K, Haskell H, Giardina TD. Bridging diagnostic safety and mental health: a systematic review highlighting inequities in autism spectrum disorder diagnosis. BMJ Qual Saf. 2025.

INTRODUCTION: There is increased recognition that diagnostic errors disproportionately affect marginalised and underserved patient populations in the USA. However, evidence on diagnostic inequities in mental disorders is sparse and not well integrated into the overall diagnostic safety literature. OBJECTIVE: We systematically reviewed and narratively synthesised evidence on inequities in diagnosis of mental disorders, guided by the Diagnostic Process Framework developed by The National Academies of Sciences, Engineering, and Medicine. METHODS: We conducted a systematic review and a narrative synthesis. Medline, Embase, PsycInfo and CINAHL were searched for studies published between 2015 and 2024. Studies were eligible if they reported on inequities in the diagnosis of mental disorders and applied a quantitative, qualitative or mixed-methods design. Studies had to be peer reviewed, US based and published in English. The Mixed-Methods Appraisal Tool was used for quality appraisal. Data were analysed with a descriptive intent, and inequities were mapped into the diagnostic process. RESULTS: 20 studies of varying methodological quality were included. Though not the initial focus, autism spectrum disorder (ASD) emerged as the most studied mental disorder (n=17). Of the diagnostic errors identified, most fell into the category of delayed diagnosis. 11 factors emerged as contributors to diagnostic inequities. Limited health literacy among patients and caregivers was the leading cause of diagnostic error in symptom recognition. Insurance coverage issues delayed patient engagement with the healthcare system. Provider bias during clinical history-taking and interviewing was seen as a key cause of delays and misdiagnoses. Within diagnostic testing and interpretation, culturally inequivalent assessment measures might cause misdiagnosis and delayed diagnosis for Black/African American and Hispanic/Latino patients. The use of medical jargon and lack of qualified language interpreters during communicating the diagnosis were associated with diagnostic errors impacting patients with limited health literacy and low English language proficiency. CONCLUSIONS: Diagnostic inequities in ASD and other mental disorders persist across US patient populations. Multiple factors such as parental health literacy, provider bias and limited access interact and impact the diagnostic process. Addressing these interconnected barriers is essential to ensure timely, accurate and equitable care. PROSPERO REGISTRATION NUMBER: CRD42024581271.

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7. Victoria S, Roper C. Autism spectrum disorder-like behaviors in developing zebrafish exposed to particulate matter. Neurotoxicol Teratol. 2025: 107548.

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders that can impact communication and social behaviors. Evidence suggests that the causes of ASD are likely a combination of genetic and environmental factors, such as air pollution. Particulate matter (PM) is the solid and liquid portion of air pollution that can vary in size and has been associated with many health impacts, including cardiorespiratory impacts, and has more recently been found to be associated with the prevalence of ASD. However, little is known about the phenotypic presentations of this association between PM and ASD, therefore, the zebrafish (Danio rerio) model was employed to study behaviors often associated with ASD as a result of PM exposure. Zebrafish larvae were exposed for a total of 5 days to PM standard reference material (SRM1649b) and a commonly used home remedy, melatonin, beginning at 6 h post-fertilization and various behavioral assays were performed on subsequent days for a total of 13 days. Observed and quantified behaviors were compared to a positive control, valproic acid (VPA). Generally, PM exposure did not elicit behavior resembling that of VPA exposure and the interactions between PM and VPA did not induce additive or synergistic behavioral patterns, as expected. Melatonin supplementation did not ameliorate most of the observed behavioral impacts of PM or VPA exposure. These results have prompted additional questions about the phenotypic presentations of ASD as a result of PM exposure and contribute to growing knowledge about disease-environment interactions.

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8. Wang W, Lin Q, Liu L, Mai H, Tang H, Xu K. Knockdown of CDKN1A Suppresses the IL-17 Pathway to Inhibit Oxidative Stress and Alleviate Autism Spectrum Disorder. J Biochem Mol Toxicol. 2025; 39(9): e70466.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impaired social interaction, communication deficits, and repetitive behaviors. However, the underlying molecular mechanisms remain elusive. This study aims to investigate the role of cyclin-dependent kinase inhibitor 1 A (CDKN1A) in ASD. This study integrated multi-omics bioinformatics analysis to identify differentially expressed genes (DEGs) related to oxidative stress in ASD. Hub genes were screened using machine learning models. In vivo, an ASD rat model was established by maternal lipopolysaccharide (LPS) injection. Behavioral tests (open field, three-chamber social, morris water maze) were performed. Histopathology change was observed by hematoxylin-eosin staining. In vitro, LPS-stimulated BV2 microglia were treated with IL-17A for feedback experiments. Enzyme-linked immunosorbent assay was carried out to measure inflammatory factors and oxidative stress indicators. Western blot was used to detect protein expression. Bioinformatics analysis revealed 30 DEGs, with CDKN1A emerging as a prominent hub gene associated with oxidative stress. ASD model rats exhibited behavioral deficits, neuroinflammation, and hippocampal neurodegeneration. CDKN1A knockdown significantly attenuated these phenotypes, improving social interaction, reducing anxiety-like behaviors, and enhancing spatial learning and memory. Moreover, IL-17 pathway was screened as downstream pathway of CDKN1A. CDKN1A silencing suppressed LPS-induced apoptosis, inflammation, and oxidative stress in BV2 microglial cells, which was weakened by IL-17A. CDKN1A drives ASD pathogenesis via IL-17 pathway activation. Its suppression mitigates neuroinflammation, oxidative stress, and behavioral impairments, establishing CDKN1A as a novel therapeutic target for ASD. Trial Registration: Clinical trial number: Not applicable.

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9. Zhang J, Li YX, Huang Q, Yuan Y, Chen JY, Yang FW, Yang L, Liu LY, Yu YC. Bcl11a deficiency in cerebellar Purkinje cells causes ataxia and autistic-like behavior by altering Vav3. Mol Psychiatry. 2025.

BCL11A encodes a transcription factor essential for brain development, with pathogenic variants causing intellectual disability, autism spectrum disorder (ASD), microcephaly, hypotonia, and behavioral abnormalities. While clinical studies have identified cerebellar pathology in patients with BCL11A variants, the specific roles of this gene in cerebellar function and its relationship to clinical symptoms remain unclear. In this study, we demonstrate that Bcl11a is predominantly expressed in Purkinje cells (PCs) of both the developing and adult mouse cerebellum. Conditional deletion of Bcl11a in PCs leads to impaired PC survival, disrupts dendritic morphology, reduces spine density, and results in ataxia, motor learning deficits, and autistic-like behaviors. Electrophysiological analyses reveal that Bcl11a-deficient PCs exhibit decreased frequency and regularity of spontaneous firing and reduced excitatory synaptic inputs from both parallel and climbing fibers, while maintaining normal intrinsic excitability and inhibitory synaptic inputs. Moreover, we identify Vav3 (guanosine nucleotide exchange factor 3) as a downstream target of Bcl11a in PCs and demonstrate that Vav3 overexpression partially rescues both PC dysfunction and abnormal motor and social behaviors in Bcl11a-deficient mice. Together, these findings establish Bcl11a’s critical role in PC function and provide mechanistic insight into how BCL11A mutations contribute to cerebellar dysfunction in psychiatric disorders such as ASD.

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10. Zhang L, Wang JH. The utilization of non-human primates in the investigation of autism spectrum disorder. Brain Res. 2025: 149900.

Autism spectrum disorder (ASD), a prevalent neurodevelopmental condition characterized by social communication deficits and repetitive behaviors, presents significant therapeutic challenges due to its multifactorial etiology, clinical heterogeneity, and frequent comorbidities. To address these complexities, animal models have become indispensable tools for unraveling ASD pathogenesis and evaluating potential interventions. This review synthesizes recent advances across three pivotal research domains – neuroimaging biomarkers, metabolic dysregulation, and etiological mechanisms while providing a critical evaluation of animal models, including rodent and non-human primate (NHP) paradigms developed through pharmacological induction, spontaneous mutations, and CRISPR-based gene editing. Although rodent models have substantially advanced our understanding of ASD-linked genetic pathways and neural circuitry, their limited capacity to model higher-order social cognition underscores the need for evolutionarily proximate systems. Non-human primates (NHPs), with their neuroanatomical homology to humans and complex socio-cognitive behaviors, offer unparalleled advantages for recapitulating core ASD phenotypes. Current evidence demonstrates that NHP models faithfully replicate hallmark behavioral manifestations while elucidating aberrant neural network dynamics and synaptic plasticity underlying these traits. Key challenges in the field include standardizing model validation protocols, addressing sex-specific phenotypic variability, and integrating multi-omics approaches for biomarker discovery and circuit-level analysis, finally evaluating the efficiency of NHP models in therapeutic translation.

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