Search Results (233)

Background/Objectives: Autism spectrum disorder (ASD) has been extensively studied through neuroimaging, primarily focusing on grey matter and more in children than in adults. Studies in children and adolescents fail to capture changes that may dampen with age, thus leaving only changes specific to ASD. While grey matter has been the primary focus, white matter (WM) may be more specific in identifying the particular biological signature of the neurodiversity of ASD. Diffusion tensor imaging (DTI) is the more appropriate tool to investigate WM in ASD. Despite being introduced in 1994, its application to ASD research began in 2001. Studies employing DTI identify altered fractional anisotropy (FA), mean diffusivity, and radial diffusivity (RD) in individuals with ASD compared to typically developing (TD) individuals. Methods: We systematically reviewed literature on 21 May 2025 on PubMed using the following strategy: (“autism spectrum”[ti] OR autistic[ti] OR ASD[ti] OR “high-functioning autism” OR Asperger*[ti] OR Rett*[ti]) AND (DTI[ti] OR “diffusion tensor”[ti] OR multimodal[ti] OR “white matter”[ti] OR tractograph*[ti]). Our search yielded 239 results, of which 26 were adult human studies and eligible. Results: Analysing the evidence, we obtained regionally diverse WM alterations in adult ASD, specifically in FA, MD, RD, axial diffusivity and kurtosis, neurite density, and orientation dispersion index, compared to TD individuals, mostly in frontal and interhemispheric tracts, association fibres, and subcortical projection pathways. These alterations were less prominent than those of children and adolescents, indicating that individuals with ASD may improve during brain maturation. Conclusions: Our findings suggest that white matter alterations in adults with ASD are regionally diverse but generally less pronounced than in younger populations. This may indicate a potential improvement or adaptation of brain structure during maturation. Further research is needed to clarify the neurobiological mechanisms underlying these changes and their implications for clinical outcomes. Full article

Background: Autism spectrum disorder (ASD) is characterised by atypical behavioural and cognitive diversity, yet the neural underpinnings linking brain activity and individual presentations remain poorly understood. In this study, we investigated the relationship between resting-state functional magnetic resonance imaging (fMRI) signal complexity and intelligence (full-scale intelligence quotient (FIQ); verbal intelligence quotient (VIQ); and performance intelligence quotient (PIQ)) in male adults with ASD (n = 14) and matched neurotypical controls (n = 15). Methods: We used three complexity-based metrics: Hurst exponent (H), fuzzy approximate entropy (fApEn), and fuzzy sample entropy (fSampEn) to characterise resting-state fMRI signal dynamics, and correlated these measures with standardised intelligence scores. Results: Using a whole-brain measure, ASD participants showed significant negative correlations between PIQ and both fApEn and fSampEn, suggesting that increased neural irregularity may relate to reduced cognitive–perceptual performance in autistic individuals. No significant associations between entropy (fApEn and fSampEn) and PIQ were found in the control group. Group differences in brain–behaviour associations were confirmed through formal interaction testing using Fisher’s r-to-z transformation, which showed significantly stronger correlations in the ASD group. Complementary regression analyses with interaction terms further demonstrated that the entropy (fApEn and fSampEn) and PIQ relationship was significantly moderated by group, reinforcing evidence for autism-specific neural mechanisms underlying cognitive function. Conclusions: These findings provide insight into how cognitive functions in autism may not only reflect deficits but also an alternative neural strategy, suggesting that distinct temporal patterns may be associated with intelligence in ASD. These preliminary findings could inform clinical practice and influence health and social care policies, particularly in autism diagnosis and personalised support planning. Full article

Background/Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental disorder distinguished by an extensive range of symptoms, including reduced social interaction, communication difficulties and tiresome behaviors. Early detection of ASD is important because it allows for timely intervention, which significantly improves developmental, behavioral, and communicative outcomes in children. However, traditional diagnostic procedures for identifying autism spectrum disorder (ASD) typically involve lengthy clinical examinations, which can be both time-consuming and costly. This research proposes leveraging automated machine learning (AUTOML) to streamline the diagnostic process and enhance its accuracy. Methods: In this study, by collecting data from various rehabilitation centers across Pakistan, we applied a specific AUTOML tool known as Tree-based Pipeline Optimization Tool (TPOT) for ASD detection. Notably, this study marks one of the initial explorations into utilizing AUTOML for ASD detection. The experimentations indicate that the TPOT provided the best pipeline for the dataset, which was verified using a manual machine learning method. Results: The study contributes to the field of ASD diagnosis by using AUTOML to determine the likelihood of ASD in children at prompt stages of evolution. The study also provides an evaluation of precision, recall, and F1-score metrics to confirm the correctness of the diagnosis. The propose TPOT-based AUTOML framework attained an overall accuracy 78%, with a precision of 83%, a recall of 90%, and an F1-score of 86% for the autistic class. Conclusions: In summary, this research offers an encouraging approach to improve the detection of autism spectrum disorders (ASD) in children, which could lead to better results for affected individuals and their families. Full article

Autistic traits—such as social communication deficits, cognitive rigidity, and repetitive behaviors—are increasingly recognized in individuals with schizophrenia, particularly in early-onset cases and subtypes with predominant negative symptoms. This overlap has prompted investigations into shared pathophysiological mechanisms. One emerging area of focus is the role of neuroinflammation in schizophrenia, which may contribute to the manifestation of autistic features. Immunological research indicates the presence of chronic low-grade inflammation, microglial activation, and disruption of the blood–brain barrier in schizophrenia. In particular, an imbalance in T-helper (Th) cell responses—specifically a shift toward Th2 dominance or concurrent Th1/Th2 activation—may lead to dysregulated cytokine production and disturbances in neural function. These findings highlight the importance of exploring immunological pathways as a basis for specific symptom profiles. Additionally, current efforts aim to identify reliable inflammatory biomarkers in schizophrenia that could support diagnosis, predict disease course, and guide treatment. Evaluating neuroinflammatory markers in patients with autistic features may provide novel insight into schizophrenia subtypes and help tailor immunomodulatory therapies. This review explores the expression of autistic traits in schizophrenia and examines the role of neuroinflammation and Th1/Th2 imbalance as potential mechanisms and biomarkers. Full article

Motor deficits, including atypical gait, are common in individuals with autism spectrum disorder (ASD), although the precise nature and cause of this co-occurrence is unclear. Because walking is a natural activity and gait timing is a metric that is relatively accessible to measurement, we explored whether autistic gait could be described solely in terms of the timing of gait parameters. The aim was to establish whether temporal analysis, including machine learning models, could be used as a group classifier between ASD and typically developing (TD) individuals. Thus, we performed a high-resolution temporal analysis of gait on two age-matched groups of male participants: one group with high-functioning ASD and a comparison TD group (each N = 16, age range 7 to 35 years). The primary data were collected using a VICON^® 3D motion analysis system. Significant increased temporal variability of all gait parameters tested was observed for the ASD group compared to the TD group (p < 0.001). Further machine learning analysis showed that the temporal variability of gait could be used as a group classifier for ASD. Of the twelve models tested, the best-fitting model type was random forest. The temporal analysis of gait with machine learning algorithms may be useful as a future ASD diagnostic aid. Full article

Background: Between 40 and 70% of the population with autism have been found to suffer from functional gastrointestinal disorders (FGIDs). The emergence of FGIDs is related to lower quality of life and greater medical resources, somatization and emotional instability. There is a paucity of research available that examines gastrointestinal symptoms and sensory responses in individuals with autism in different countries and cultures. The aim of the present study is to compare the possible differences between gastrointestinal symptoms and sensory reactivity between two samples of individuals with autism from Spain and Colombia. Methods. Differences in gastrointestinal symptoms and sensory response were analysed between individuals with autism from Spain (n = 65; mean age = 8.91, SD = 4.02) and Colombia (n = 62; mean age = 10.16, SD = 5.31). Results. No differences were found as a function of age, sex and autism severity between Spanish and Colombian participants. More severe functional nausea and vomiting was reported by the Colombian sample when compared with the Spanish sample (p < 0.00, d = 0.42). Similarly, greater sensory reactivity emerged in Colombian individuals with autism relative to Spanish individuals with autism. Conclusions. Due to methodological limitations, sample size and other factors that could not be analysed in this research, it is not possible to draw conclusions about the influences of cultural or biological factors on gastrointestinal symptomatology and sensory reactivity among both autistic populations. This work could encourage more rigorous cross-cultural research in the future. Full article

Propranolol, a nonselective beta-adrenergic antagonist, has shown potential for improving anxiety in autistic individuals. Heart rate variability (HRV), a noninvasive cardiac marker of autonomic nervous system functioning, may help identify individuals most likely to benefit from propranolol. Objectives: Determine if baseline resting HRV and other cardiac measures predict the response to propranolol for anxiety and core autism symptomology in autistic children and young adults. Methods: Sixty-two autistic individuals (ages 7–24) participated in a two-phase (i.e., a 12-week randomized controlled trial and a 12-week open-label extension) trial of propranolol. Baseline (i.e., resting state, prior to treatment) HRV and other cardiac measures were obtained from an electrocardiogram. Clinical global impression for anxiety symptoms and overall behavioral treatment impact were assessed after the 12-week trial period. Group-level (i.e., all participants) and responder groups (i.e., strong, minimal, and non-responders to propranolol) were analyzed for treatment effects. Results: HRV variables predicted group-level anxiety response to propranolol, particularly for strong responders. Also, lower baseline values of parasympathetic HRV indices were significantly correlated with greater behavioral improvement after treatment with propranolol. Last, several baseline cardiac variables were associated with improvement in multiple behavioral domains after treatment with propranolol. Conclusions: HRV may be a potential biomarker for predicting reduced anxiety and behavioral symptoms in response to propranolol in autistic children and young adults. Identifying autonomic profiles associated with positive treatment outcomes could guide future personalized interventions in autism. The results presented herein should be regarded as preliminary until the findings are replicated in future clinical trials. Full article

Many studies have recognized that individual variability shapes user experience in virtual reality (VR), yet little is known about how these differences influence objective cognitive engagement and performance outcomes. This study investigates how cognitive factors (IQ, age) and technological familiarity (tech enthusiasm, tech fluency, first-time VR experience) influence EEG-derived cognitive responses (alpha and theta activity) and task performance (trial duration) during VR interactions. Sixteen autistic and sixteen neurotypical participants engaged with various VR interactions while their neural activity was recorded using a Muse S EEG. Correlational analyses showed distinct group-specific patterns: higher IQ correlated with elevated average alpha and theta power in autistic participants, while tech fluency significantly influenced performance outcomes only in neurotypical group. Prior VR experience correlated with better performance in the neurotypical group but slower adaptation in the autistic group. These results highlight the role of individual variability in shaping VR engagement and underscore the importance of personalized design approaches. This work provides foundational insights toward advancing inclusive, user-centered VR systems. Full article

Deciduous teeth accumulate toxic metals until fully mineralized, making them a stable biological matrix for assessing chronic exposure during fetal and early postnatal life. Their metal content is influenced by environmental factors (e.g., industrial areas, mining sites) and individual factors (e.g., maternal diet, early nutrition, passive smoking). The aim of this study was to evaluate the toxic metal content in deciduous teeth and to identify factors contributing to its accumulation, as well as possible health implications. A systematic review was conducted in accordance with the PRISMA guidelines and following the PICO framework. Quality assessment was assessed using the Joanna Briggs Institute (JBI) checklist for quasi-experimental studies. The literature search was carried out in the PubMed, Scopus, and Web of Science databases using the following keywords: deciduous, milk, primary, decidua, teeth, dentition, heavy metal, toxic metals. A total of 134 articles were initially identified, with 95 remaining after duplicate removal. After screening, 75 articles were excluded: 71 did not meet the inclusion criteria, 3 were not available in English, and 1 lacked full-text access. Ultimately, 20 studies were included in the review. Toxic metal concentrations were determined using various analytical techniques, mainly inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectrometry (AAS). Higher levels of metals, especially lead, were observed in the teeth of children residing in industrial areas, near mines, or in regions affected by armed conflict. Although two out of five studies indicated a possible link between fathers’ smoking habits and elevated lead concentrations, no definitive relationship was established between secondhand smoke exposure and the levels of lead and cadmium found in dental tissue. Similarly, no definitive relationship was identified between mercury and lead content and the prevalence of autism. However, lower manganese levels were associated with the presence of autistic traits, weaker verbal performance, and reduced memory capacity. In conclusion, deciduous teeth represent a valuable biological material for assessing chronic prenatal and early postnatal exposure to toxic metals, which may serve as a starting point for further research into diseases of unknown etiology, such as autism, and in the future may have clinical significance in their prevention and treatment. And it is also important for monitoring environmental pollution levels. Full article

Although prosodic differences in autistic individuals have been widely documented, little is known about their ability to perceive and interpret specific prosodic features, such as contrastive pitch accent—a prosodic signal that places emphasis and helps listeners distinguish between competing referents in discourse. This study addresses that gap by investigating the extent to which autistic children can (1) perceive contrastive pitch accent (i.e., discriminate contrastive pitch accent differences in speech); (2) interpret contrastive pitch accent (i.e., use prosodic cues to guide real-time language comprehension); and (3) the extent to which their ability to interpret contrastive pitch accent is associated with broader language and social communication skills, including receptive prosody, pragmatic language, social communication, and autism severity. Twenty-four autistic children and 24 neurotypical children aged 8 to 14 completed an AX same–different task and a visual-world paradigm task to assess their ability to perceive and interpret contrastive pitch accent. Autistic children demonstrated the ability to perceive and interpret contrastive pitch accent, as evidenced by comparable discrimination ability to neurotypical peers on the AX task and real-time revision of visual attention based on prosodic cues in the visual-world paradigm. However, autistic children showed significantly slower reaction time during the AX task, and a subgroup of autistic children with language impairment showed significantly slower processing of contrastive pitch accent during the visual-world paradigm task. Additionally, speed of contrastive pitch accent processing was significantly associated with pragmatic language skills and autism symptom severity in autistic children. Overall, these findings suggest that while autistic children as a group are able to discriminate prosodic forms and interpret the pragmatic function of contrastive pitch accent during spoken language comprehension, differences in prosody processing in autistic children may be reflected not in accuracy, but in speed of processing measures and in specific subgroups defined by language ability. Full article

Using an inductive computational approach, our present data exploration sought to use machine learning methodology to define and identify patterns and gain insight into autism-related discussions on Reddit across three different categories of subreddits: (a) individuals who self-identify as autistic, (b) parents of individuals on the autism spectrum, and (c) behavior therapists. By doing so, we sought to review authentic autism-related discussions and identify important topics that emerged across these three demographic groups, including insights related to assessing and treating challenging behavior. Following basic and advanced preprocessing, our extraction resulted in 57 subreddits and 46,914 comments from autism spectrum subreddit members, 46 subreddits and 27,838 comments from parent subreddit members, and six subreddits with 3163 comments from behavior therapist subreddit members. Subsequent network analyses revealed interesting patterns of discussion within and across subreddit groups that may be used to inform support and resources, practice considerations, and future directions for research. Full article

Background/Objectives: Orthorexia Nervosa (ON), a condition marked by an obsessive focus on eating healthily, has drawn increasing clinical attention due to its rigid dietary patterns and social impairment. Borderline Personality Disorder (BPD), characterized by emotional dysregulation, impulsivity, and unstable interpersonal relationships, frequently co-occurs with eating disorders. Recent research suggests that autistic traits—such as cognitive rigidity and restricted interests—may underlie both ON and BPD, especially in female populations. This study aimed to assess the prevalence of orthorexic tendencies in patients with BPD compared to healthy controls (HCs) and to explore their associations with autistic traits and disordered eating behaviors. Methods: This study involved 73 BPD patients and 52 HCs. Participants completed the Adult Autism Subthreshold (AdAS) Spectrum, Eating Disorder Inventory-2 (EDI-2), and the ORTO-15 questionnaire. Results: BPD patients scored significantly higher than HCs on AdAS Spectrum and EDI-2, and significantly lower on ORTO-15, indicating more pronounced autistic traits, disordered eating behavior, and orthorexic tendencies. A greater proportion of BPD individuals reported clinically relevant ON symptoms according to the ORTO-15 threshold. Orthorexic symptoms were significantly correlated with most EDI-2 and all AdAS Spectrum domains. Regression analysis revealed that autistic traits, but not feeding and eating disorder symptoms, significantly predicted orthorexic tendencies. Conclusions: Orthorexic tendencies are more prevalent in individuals with BPD and are significantly associated with autistic traits. These findings suggest that ON may represent a manifestation of the autism spectrum, particularly in individuals with BPD, and support a reconceptualization of ON within a neurodevelopmental framework. Recommendation: Future research is needed in order to clarify the temporal and causal relationships among autistic traits, BPD symptomatology, and the emergence of orthorexic behaviors. Full article

Background/Objectives: Diagnosing ASD in adults presents unique challenges, and there are currently no specific biomarkers for this condition. Most existing studies on the gut microbiota in ASD are conducted in children; however, the composition of the gut microbiota in children differs significantly from that of adults. This study aimed to study the gut microbiota of young adults with high-functioning ASD. Methods: Using metagenomic sequencing, we evaluated the gut microbiota in 45 adults with high-functioning ASD and 45 matched healthy controls. Results: Adjusting for sociodemographic information, dietary habits, and clinical data, we observed a distinct microbiota profile of adults with ASD in comparison to controls, with the intensity of autistic traits strongly correlating to microbial diversity (correlation coefficient = −0.351, p-value < 0.001). Despite a similar dietary pattern, the ASD group exhibited more gastrointestinal symptoms than the healthy controls. An internally validated machine-learning predictive model that combines the Autism Spectrum Quotient questionnaire score of individuals with their microbial features could achieve an area under the receiver operating characteristic curve (AUC) of 0.955 in diagnosing ASD in adults. Conclusions: This study evaluates the gut microbiota in adult ASD and highlights its potential as a non-invasive biomarker to enhance the diagnosis of ASD in this population group. Full article

Background/Objectives: Autistic individuals with eating disorders (ED) face socio-emotional, sensory, and communication difficulties that influence engagement and treatment outcomes. We examined how the PEACE Pathway—an autism-informed approach to ED treatment—addresses these challenges through tailored adaptations in clinical care. Methods: A qualitative multiple case studies design was employed, drawing data from clinical documentation, stakeholder feedback, and service evaluations. Results: We identified eight core domains essential for implementation: pathway knowledge, assessment and planning, psychological interventions, sensory management, nutritional care, lived-experience feedback, family/community engagement, and staff training. These domains informed the development of the PEACE Self-Assessment Checklist to support the wider adoption of the pathway. Conclusions: The PEACE Pathway offers a structured approach to adapting ED treatment for autistic individuals. The checklist provides practical guidance for implementing autism-friendly adaptions. Full article

Proper nutrition is a critical component in supporting the overall health and development of individuals with autism spectrum disorder (ASD) who experience eating difficulties associated with their autistic traits. Evidence regarding the prevalence, origins, and consequences of eating issues related to ASD is largely derived from studies on autistic children, while information pertaining to adults remains scarce. It is therefore essential to critically review existing research focusing on autistic adults to draw robust conclusions and identify clear research gaps. A computer-aided search in PubMed, Science Direct, Scopus, and Web of Science databases spanning the years 2013–2024 using the search terms covering ASD/Autism, Adult, Nutrition/Nutritional Status, and Diet yielded 43 full-text articles. In our literature review, we explored three critical aspects of nutrition in adults with ASD: their food preferences and sensory processing patterns, studies on nutritional status, and whether dietary and nutritional interventions have improved their adherence to healthier diets. Autistic adults appear to select food based on sensory perceptions. This selection pattern can affect their nutritional status, with a tendency toward overweight and nutritional deficiencies. The most promising intervention strategies incorporate sensory adaptation and structured meal planning. Further research should apply rigorous methodologies that account for this population’s specific characteristics. Full article