Journal of Autism and Developmental Disorders

BackgroundAutism spectrum disorder (ASD) is frequently associated with speech and language difficulties, yet empirical data from Central Asian countries remain scarce. This study examined the association between a diagnosis of childhood autism (ICD-10: F84.0) and the presence of speech development difficulties in a clinical sample from Tajikistan MethodA retrospective cross-sectional study was conducted using clinical records of 85 patients (36 with F84.0; 49 with other psychiatric diagnoses) at the Insight Mental Health Center in Dushanbe, Tajikistan (December 2025-January 2026). Speech difficulties were identified through systematic review of clinical notes. Between-group comparisons were performed using Pearsons {chi}2 test, odds ratios (OR), relative risk (RR), and effect size measures ({varphi} coefficient, Cohens h). ResultsSpeech difficulties were present in 72.2% of the autism group versus 36.7% of the comparison group. The association was statistically significant ({chi}2 = 10.47, p <.01). Children with autism had substantially higher odds of speech difficulties (OR = 4.48, 95% CI [1.76, 11.38]), with a large effect size (Cohens h = 0.73). ConclusionsAutism diagnosis was significantly associated with elevated rates of speech difficulties in this Tajik clinical sample. Practical implicationsThese findings support the systematic inclusion of speech-language assessment and intervention within autism care protocols, particularly in Central Asian healthcare settings where such integration remains limited. HighlightsO_LISpeech difficulties were identified in 72.2% of children with autism (F84.0) in a Tajik clinical sample. C_LIO_LIChildren with autism were 4.5 times more likely to present with speech difficulties than those with other diagnoses (OR = 4.48, 95% CI [1.76, 11.38]). C_LIO_LIThe most prevalent speech pattern was complete absence of expressive speech (nonverbal presentation). C_LIO_LIFindings support the integration of speech-language assessment into standard autism care protocols in Central Asia. C_LIO_LIThis is one of the first empirical reports on autism and speech profiles from Tajikistan. C_LI

Genetic counselling outcome measures are increasingly adapted for diverse clinical contexts. While the Genetic Counselling Outcome Scale (GCOS-24) is available in Swedish, no autism-specific version has been developed. Therefore, we adapted the Swedish GCOS-24 using the English version of the modified GCOS-24 (mGCSOS-24) to create a Swedish autism-specific mGCOS-24. Thereafter, we evaluated both the Swedish autism mGCOS-24 and the Swedish general GCOS-24 using Rasch analysis to assess their psychometric properties. Both instruments exhibited structural challenges, including multidimensionality, disordered thresholds, local item dependence, and invariance issues. For the Swedish autism mGCOS-24, we were able to identify subscales with acceptable measurement properties. However, applying the same structure to the Swedish general GCOS-24 did not resolve its broader limitations. This study introduces the first Swedish autism-specific mGCOS-24 and represents the first Rasch-based evaluation of any GCOS-24 or mGCOS-24 in Swedish. Our findings highlight important opportunities for measure refinement but also indicate that new or more substantially adapted tools may be needed to capture outcomes of genetic counselling in autistic populations.

AimAutistic children have a high but varied prevalence of internalizing and externalizing problems. This study aimed to identify the subtypes of internalizing and externalizing problems among autistic preschool children in Japan, examine their temporal stability, and investigate differences in participation in daily life and family outcomes across these subtypes. MethodsA prospective cohort study was conducted with 275 caregivers of autistic children aged 51-75 months. Internalizing and externalizing problems were assessed using the Strengths and Difficulties Questionnaire. ResultsLatent transition analysis identified five subtypes: Low-symptom, High-emotional, Externalizing, Comorbid, and Peer-difficulty groups. Membership in the High-emotional and Externalizing groups was relatively stable over time, whereas the Peer-difficulty group showed frequent transitions to subtypes with higher levels of internalizing or externalizing problems. Significant differences in participation in daily life and family outcomes were observed across subtypes, but these patterns were inconsistent with a simple gradient of symptom levels. ConclusionsThe novel findings that the temporal stability of subtype membership varied and that differences in participation in daily life and family outcomes were observed across the subtypes suggest that the heterogeneity of internalizing and externalizing problems may be associated with variations in childrens participation in daily life and family outcomes over time. Plain Language SummaryAutistic preschool children often experience emotional and behavioral difficulties, but the way these difficulties manifest varies widely across individuals. This study aimed to identify the patterns of these difficulties, examine how they change over time, and investigate how participation in daily life and family outcomes differ across autistic preschool children. We conducted a study with 275 caregivers of autistic children aged 4-6 years in Japan. From caregiver reports of childrens emotional and behavioral difficulties, five distinct patterns were identified: a group with mainly emotional difficulties, a group with mainly behavioral difficulties, a group with both types of difficulties, a group with relatively low levels of difficulties, and a group characterized primarily by peer-related difficulties. Our findings suggest that different patterns of emotional and behavioral difficulties are associated with differences in childrens participation in daily life and family outcomes. These differences could not be explained simply by the overall severity of difficulties but rather reflect distinct patterns based on the type of difficulty. The results indicate that autistic children face diverse difficulties that change over time.

PurposeNavigational ability develops throughout childhood alongside the maturation of brain regions supporting egocentric and allocentric processing. In Autism Spectrum Disorder (ASD), atypical hippocampal development may impact flexible spatial memory; however, findings on navigational ability in autistic children remain inconsistent. This study aimed to compare both objective and perceived navigation ability in children with ASD and typically developing (TD) peers. MethodTwenty-six children with high-functioning ASD and twenty-five age- and gender-matched TD children (M_age = 12.04 years, SD = 1.64) completed a battery of navigational tasks from the Spatial Performance Assessment for Cognitive Evaluation (SPACE), including Path Integration, Egocentric Pointing, Mapping, Associative Memory, and Perspective Taking. Perceived navigation ability was assessed using the Santa Barbara Sense of Direction (SBSOD) scale. ResultsNo significant group differences were observed across any objective navigation tasks. However, children with ASD reported significantly lower perceived navigation ability compared to TD peers. ConclusionThese findings suggest a dissociation between perceived and actual navigational ability in ASD. By early adolescence, objective navigation performance appears intact, potentially reflecting sufficient maturation of underlying neural systems or the presence of compensatory mechanisms. The results underscore the importance of incorporating objective, task-based measures when assessing cognitive abilities in autistic populations.

Because both monothetic and polythetic diagnostic classification approaches focus on the presence of individual symptom(s) to identify individuals in a clinical population, they may be diagnostically sensitive clinical markers of multidimensional disorders such as developmental language disorder (DLD). DLD researchers have also used likelihood ratios (LHs) to identify possible diagnostic clinical markers of DLD, however the diagnostic sensitivity of LHs varies markedly across studies. A recent multidimensional computational elastic-net regression examined a total of 71 measures of spoken language and cognitive processing from a cohort of 223 children ages 7;0 to 11;0 with and without DLD (DLD = 110; typically developing (TD) controls = 113). All 200 iterations of the model had high discriminative power (87% - 88%) in positively identifying and distinguishing the DLD participants across all thresholds. Notably, the models identified a sparse DLD-specific deficit profile which only included nine of the 71 measures. In this study, we ask if the individual LHs for each of these nine measures are equally sensitive in identifying and discriminating the children with DLD from TD controls or if diagnostic markers of multidimensional disorders such as DLD can only be identified based on computational modeling approaches. The LHs for each of the nine measures were in the moderately high ranged (3.25 - 10). However, at the the highest LH cut points for each measure, there was little to no overlap in the children each measure identified as having DLD. Follow up analysis revealed that the elastic net model-derived predictive scores for each participant were significantly correlated with the participants language ability. The model also identified a subgroup of TD participants as having the same DLD-deficit profile as the DLD participants. This subgroup were younger, predominantly male participants whose standardized language assessment scores were lower as compared to the larger TD cohort. Taken together, the results from this study show that, because multidimensional modeling approaches such as elastic net regression leverage the variability in the deficit profiles across individual members of a diagnostic group and the unique contributions of each of the behavioral features of the phenotype, they may be an effective tool in deriving diagnostically specific deficit profiles for phenotypically complex, multicausal, multidimensional, neurodevelopmental disorders such as DLD. The results also demonstrate the robustness of the derived DLD-specific deficit profile in identifying individuals with "mild" or subclinical DLD, demonstrating the potential utility of this approach in both clinical and research arenas. What this paper adds.O_ST_ABSWhat is already known on this subject.C_ST_ABSThe identification of diagnostic markers for DLD has been a challenge for both clinicians and researchers across multiple decades. Monothetic classification markers such as non-word repetition, optional infinitive, or syntax dependencies have been explored, as well as polythetic classification approaches where a list of diagnostic symptoms is used together. However, each assumes different criteria and symptoms that should be included as diagnostic markers of DLD. What this study adds.Our study assessed the feasibility and effectiveness of monothetic vs. polythetic classification approaches for identifying DLD. Since our prior work, which used elastic net logistic regression computational modeling with strong discriminatory power, consistently selected nine key features as the DLD-deficit profile, in this effort, we calculated each of the nine features likelihood ratios to examine each measures ability to identify children with DLD. The monothetic approach failed to identify a consistent set of children with DLD, and the polythetic classification approach also did not identify participants who were shown to have mild DLD by the elastic net modeling approach. Instead, our analysis showed that a computational modeling approach, such as elastic net regression, that included small but important input from multiple cognitive and linguistic aspects of children, could better capture multifaceted information about the disorder, better account for individual variability, and consistently identify most participants with DLD. Clinical implications of this study.Elastic net logistic regression identifies a small subset of important features for distinguishing DLD and can assign a probability of DLD presence for each participant. Instead of the polythetic and monothetic approaches commonly used in the field, our study shows that integrating advanced computational modeling, such as elastic net regression, with clinician judgment can better refine assessment processes and address prior and ongoing inconsistencies in the DLD literature and diagnostic practices.

Atypical social functioning is a core feature of autism, yet findings remain fragmented across components and development. We aimed to systematically integrate this literature and characterize the organization, development, and moderators of social functioning in autism. We conducted a systematic review and meta-analysis of behavioral studies published between January 1990 and August 2025, identified through PubMed, Web of Science, and prior reviews, including studies with clinically diagnosed autistic individuals and neurotypical controls. A qualitative synthesis and two complementary quantitative meta-analyses were performed, with risk of bias evaluated through study-level characteristics. A total of 2,622 studies (94,114 autistic and 172,847 neurotypical individuals across 32 countries) were included, covering 22 social components that clustered into five domains. Overall group differences were substantial (Hedges g = -0.744, 95% CI [-0.797, -0.690]). Differences emerged earliest in motivation-based processes ([~]6 months), followed by motor, emotion, and inference domains, and showed age-related divergence alongside improvement in some skills. Cross-domain analyses revealed stronger interdependencies in autism and an organizational pattern most consistent with serial relationships among domains. These findings should be interpreted in light of methodological heterogeneity, underpowered samples, and uneven cultural representation. Together, the results provide an integrative framework for understanding the organization and development of social functioning in autism, with implications for precision subtyping, developmentally timed interventions, and neurodiversity-informed research and policy. This study was pre-registered (PROSPERO: CRD42024566141).

Background: Adult autism services research is hampered by a lack of accessible self-reported outcome measures. The AASPIRE Outcomes Project used a community-based participatory research (CBPR) approach to create and test the AASPIRE Measurement Toolkit, a set of accessible survey instruments for use in real-world settings. The core toolkit contains 12 characteristics modules and 19 outcome measures, each with self-reported and caregiver-reported versions. Methods: In a prior phase of the project, we collaboratively adapted, revised, or co-created all instruments. We used our CBPR-nested Delphi process, our collaborative adaptation/creation process, and cognitive interviews to ensure accessibility and content validity. We then conducted a longitudinal survey to validate the 19 outcome measures in a pragmatic sample of 870 autistic adults from two healthcare systems, two disability service systems, and the larger autistic community in the United States. Participants completed surveys at 3 time points over 12-18 months. A 15% random subset completed an additional retest survey 2 weeks after the second time point. We assessed 1) accessibility using completion rates and perceived ease of use; 2) internal consistency using Cronbach's alphas and omegas; 3) convergent validity using Pearson's correlations; 4) two-week test-retest reliability using interclass correlation coefficients; and 5) six-month responsiveness to change by comparing self-perceived change with change in scores. Results: Over 90% of participants reported the survey items were easy to understand; over 90% of participants who started the survey completed all applicable sections at each time point; and participants answered 99% of items on each instrument. The outcome measures and their pre-determined subscales demonstrated strong accessibility, content validity, internal consistency reliability, test-retest reliability, convergent and discriminant validity, and responsiveness to change. Conclusion: The AASPIRE Measurement Toolkit is accessible and includes 19 outcome measures with strong initial psychometric properties. We will report in-depth assessments of construct and structural validity separately for each measure. All instruments are available for free and can help clinicians, service providers, advocacy organizations, and researchers assess the effectiveness of interventions and follow changes in outcomes over time.

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition with multifactorial etiology, resulting from complex interactions between genetic susceptibility and environmental exposures. Although numerous studies have identified individual perinatal risk factors for ASD, most have examined these exposures in isolation, limiting understanding of how perinatal complications cluster and jointly influence neurodevelopment. Evidence from Latin America also remains scarce. This study aimed to identify multivariate perinatal risk patterns associated with ASD in a Chilean population, addressing gaps in regional representation and methodological approaches. We conducted a population-based analysis of mothers of children with and without ASD in Chile. A broad set of medical and psychosocial perinatal variables was jointly analyzed using multiple correspondence analysis (MCA) to characterize interrelated risk structures. MCA revealed a clear separation between ASD and non-ASD groups along the first dimension, suggesting that ASD diagnosis is embedded within structured perinatal patterns rather than isolated exposures. MCA-derived, stepwise, and LASSO-penalized logistic regression models were then compared. The most parsimonious model identified maternal vaginal bleeding during pregnancy, prenatal maternal stress or anxiety, and negative pregnancy intention or perception as the strongest factors jointly associated with increased odds of ASD, with a dose-response pattern observed for maternal stress. An unexpected inverse association with neonatal cyanosis may reflect enhanced medical surveillance and warrants cautious interpretation. These findings underscore the importance of integrated perinatal care addressing both obstetric and maternal mental health, and demonstrate the value of multivariate approaches for elucidating complex developmental risk pathways.

ObjectiveTo characterize the familial patterns of misophonia and other commonly co-occurring neuropsychiatric conditions. MethodsWe examined cross-sectional survey responses from 101 probands with misophonia and their biological parents enrolled in a genetics study. ResultsProbands had a mean age of 24.6 {+/-} 11.6 years (8-64 years), were predominantly female (88%), and had high rates of co-occurring neuropsychiatric conditions, including anxiety (70%), depression (38%), ADHD (31%), and OCD (25%). Among probands, 39% had a first-degree relative with misophonia, and 48% had at least one any-degree relative with misophonia. In addition, many probands had at least one first-degree relative with anxiety (65%), depression (57%), ADHD (40%), OCD (20%), and autism (13%). Comparing rates of neuropsychiatric conditions reported by parents, mothers had significantly higher rates of misophonia (29% maternal vs. 9% paternal, p = 0.001) and anxiety (44% maternal vs. 26% paternal, p = 0.02) than fathers. ConclusionThese findings provide new insight into the familial patterns of misophonia and co-occurring neuropsychiatric conditions. Future research on underlying genetic and environmental factors is needed to shed light on the observed shared predispositions for misophonia and other neuropsychiatric conditions in families.

RationaleNeurodevelopmental disorders (NDDs) are characterised by significant challenges in communication, social interaction, and adaptive function, often impacting quality of life. Previous studies support genetic influences on the communication abilities of individuals with NDD, but were either limited to single genetic conditions or to small cohorts with a limited selection of communication measures. MethodsWe analysed caregiver-reported communication abilities in 79,518 individuals with NDD from the Simons Searchlight and SPARK registries: 4,439 with a CNV-based or monogenic NDD and 75,079 with autism spectrum disorder (ASD) without a known genetic cause (idiopathic ASD) as controls. For analysis, we a priori selected 10 communication-related measures based on their availability in the study cohorts, coverage of distinct communication aspects, and their frequent use in neurodevelopmental phenotyping, yielding 177,328 data points across all study cohorts. The individuals in the Searchlight registry were divided into a Discovery cohort (the 15 most prevalent genetic NDD conditions) and a Confirmation cohort (all other genetic NDD conditions). A second Confirmation cohort was generated using all individuals with genetic ASD forms from the SPARK registry. We then tested each of the three case cohorts and each genetic condition represented in the Discovery cohort against the ASD control cohort. Developmental trajectories were assessed through testing of participants grouped by age at evaluation. ResultsMeasure-level analyses demonstrated significant associations between genetic status and communication abilities, differences in communication abilities between classes of genetic variants (monogenic vs. CNV-based NDDs), and variability between specific genetic NDD conditions. CNV-based NDDs showed milder communication impairment, outperforming idiopathic ASD controls in 9/10 communication measures, whereas monogenic NDD conditions had more pervasive impairments, especially in verbal communication. Although impaired in verbal communication, five monogenic NDD conditions showed at least suggestive strengths in nonverbal and social communication relative to idiopathic ASD controls (CSNK2A1, CTNNB1, SETBP1, MED13L, and PPP2R5D), specifically in using gestures. Developmental trajectory analyses revealed STXBP1 as the gene group at highest risk of developmental stagnation in communication abilities. ConclusionsThese findings underscore the potential of precision speech-language pathology (SLP) approaches tailored to the specific verbal and nonverbal communication strengths and weaknesses of genetic groups. We also provide evidence for measurable improvements and declines in communication abilities with age at the group level, highlighting the need for developmentally informed care. By integrating genetic insights into clinical practice, precision SLP approaches may enhance communication outcomes and developmental progress and improve quality of life for individuals with genetic NDDs.

Neuroligin-3 (NLGN3) was first identified as a risk gene associated with autism spectrum disorder (ASD). The initial variant, p.R451C, associating NLGN3 with ASD has been heavily investigated, yet little is known about the functional consequences of other NLGN3 variants. Furthermore, while most of the identified variants are present in males with maternally inherited variants from unaffected mothers, several de novo variants were observed in females, suggesting a possible functional difference between de novo and maternally inherited variants. To address the functional consequences of NLGN3 variants in vivo, we generated transgenic Drosophila models corresponding to one de novo variant (p.R175W) identified in one female proband, and two maternally inherited variants (p.R451C and p.R597W) identified in male probands. In Drosophila, loss of the fly homolog, Nlg3, altered sleep patterns, synaptic architecture, and vesicle dynamics, which were rescued by the expression of the human NLGN3Ref allele. When comparing the variants, the de novo p.R175W variant and the maternally inherited p.R451C variant altered synapse morphology and sleep patterns, with minimal effects on vesicle dynamics, and the p.R597W variant altered sleep and vesicle dynamics with minimal impact on synapse morphology. Using overexpression models, human NLGN3Ref altered sleep patterns and synaptic morphology. Moreover, the p.R175W variant exacerbated sleep phenotypes, and the p.R175W and p.R451C variants exacerbated synapse morphology phenotypes. Together, our findings suggest that de novo NLGN3 variants identified in females are likely gain-of-function, while maternally inherited variants have mixed loss-and gain-of-function effects. Moreover, the location of the variants may contribute to the distinct functional differences we observed. Some NLGN3 variants disrupt synaptic development, while other variants alter synaptic function, suggesting that NLGN3 variants have differential effects. These functional differences may provide insight into the heterogeneity of individuals with ASD. Author SummaryAutism spectrum disorder (ASD) is a common neurodevelopmental disorder. Mutations in the Neuroligin-3 (NLGN3) gene are associated with ASD but very few of these mutations have been characterized in animal models. Most of these mutations affect male individuals who maternally inherited their genetic mutation; however, more rarely female individuals may present with a genetic mutation that was not identified in either of the parents. Here, we utilized the fruit fly model to investigate how three different mutations, one mutation identified in a female and two mutations identified in males, affect the flys behavior and synapse development. We identified altered sleep patterns in some of our mutants which is consistent with sleep disturbances being highly comorbid with ASD. Additionally, we identified alterations in synapse development and function which is consistent with the role of NLGN3 in synapse formation and maturation. Together, our findings support that NLGN3 is important for regulating the synapse and mutations in this gene can alter its function. However, different mutations can have differential effects. This demonstrates the need to assess multiple variants simultaneously because each variant may have distinct functional significances.

The causes of severe neuropsychiatric deteriorations among patients with previously stable autism spectrum disorder (ASD) are poorly understood and present substantial challenges for care. We aimed to characterize the prevalence of autoimmune and inflammatory conditions and markers, as well as musculoskeletal findings, among youth with ASD experiencing a suspected post-infectious neuropsychiatric deterioration. The Stanford Immune Behavioral Health (IBH) Clinic is a specialty program for youth with neuropsychiatric deteriorations that are suspected to be post-infectious (non-psychosocial). We report findings for 43 consecutive patients with ASD (70% male [30 of 43]) evaluated in the IBH Clinic. The average (SD) age at clinical presentation was 12.0 (4.0) years. Juvenile arthritis was diagnosed in 15 patients (35%), predominantly enthesitis-related arthritis (ERA) and psoriatic arthritis (PsA). Seven patients had ultrasonographic evidence of joint effusions and/or synovitis without meeting juvenile idiopathic arthritis (JIA) criteria. Autoimmune conditions other than arthritis were observed in 9 patients (21%). The mean (SD) age at arthritis and other autoimmune condition diagnoses were 16.2 (5.5) and 12.7 (4.9) years, respectively. We observe markers of immune activation during neuropsychiatric deteriorations in over half of patients (60% [26 of 43]), including markers of autoimmunity (33% [12 of 36]), complement activation (41% [13 of 32]), immune dysregulation/inflammation (11% [4 of 37]), and vasculopathy (30% [13 of 43]). One-third (37% [16 of 43]) demonstrated two or more markers. These data underscore the importance of targeted immune evaluation--including musculoskeletal imaging and inflammatory marker screening--in ASD patients who have had a suspected post-infectious behavioral regression. Lay SummaryIn this cohort study of 43 patients with autism spectrum disorder (ASD) and suspected post-infectious deteriorations, more than half had laboratory markers of immune activation (using a limited panel), one-third had joint inflammation (confirmed by ultrasound), and additional autoimmune conditions were observed in 21%. From this, we conclude that patients with ASD who experience a suspected post-infectious neuropsychiatric deterioration may have underlying inflammation which may contribute to neuropsychiatric and behavioral regressions, highlighting the importance of immunologic and rheumatologic evaluation in clinical assessment.

Background Phonemic awareness deficits are a core feature of Specific Learning Disorder-Reading (SLD-R). How task- and language-specific factors influence these deficits in alphasyllabary languages may help clarify the cognitive mechanisms underlying reading impairment in SLD-R. Methods Thirty children with a DSM-5 diagnosis of SLD-R (mean age 11.4 years) and 29 age-matched typically developing children were given phoneme blending (words and pseudowords) and segmentation tasks in Malayalam. The effects of age and consonant clusters on task performance were evaluated. Results Children with SLD-R performed significantly worse than controls across most phonemic awareness tasks, with the largest deficits observed in pseudoword blending and word blending, and smaller deficits in segmentation. No significant difference was observed for initial phoneme deletion. In typically developing children, age showed strong positive correlations with phonemic performance across most tasks, whereas the SLD-R group showed weak or absent correlations, except in word blending and initial phoneme deletion. Consonant clusters significantly affected performance in both groups, with SLD-R showing more severe deficits. Conclusions Phonemic awareness deficits observed in SLD-R in alphasyllabary languages like Malayalam are more prominent in tasks where lexical support is absent, like pseudoword blending. These deficits vary across task types and linguistic complexity. Phonemic awareness improves with age in typically developing children, while improvement is uneven in children with SLD-R. The findings suggest that phonemic awareness deficits are a core feature of SLD-R across languages, but their manifestation is shaped by orthographic and linguistic characteristics of the writing system.

Objective: Autistic individuals may face elevated risk for PTSD, yet the degree to which this risk differs by sex remains unknown. We examined the association between autism and incident PTSD, characterized sex differences in risk, identified high-risk subgroups, and described post-diagnosis clinical trajectories. Method: We conducted a population-based matched cohort study using Swedish national registers. Individuals born 1990 through 2010 were followed from age 6 years through December 31, 2017. Autistic individuals (N=42,862) were matched 1:10 to controls (N=412,251) on sex and birth year. Cox proportional hazards regression estimated hazard ratios (HRs) for incident PTSD. Among those who developed PTSD, we compared care utilization, hospitalization rates, and persistence of care contacts. Results: During mean follow-up of 5.1 years, 401 autistic individuals (0.9%) and 903 controls (0.2%) developed PTSD (incidence rates: 18.3 vs 4.2 per 10,000 person-years). Autism was associated with 4.4-fold increased PTSD risk (HR=4.37; 95% CI, 3.93-4.86). Risk was higher among females (HR=4.79) than males (HR=3.39; P interaction=.006). Among autistic individuals, comorbid ADHD conferred additional risk (HR=1.38; 95% CI, 1.14-1.68). Ten-year cumulative incidence reached 6.0% among autistic females with ADHD. Autistic individuals with PTSD had higher care utilization (mean visits: 5.0 vs 3.9; P<.001), more psychiatric hospitalizations (27.9% vs 19.8%; P=.002), and more persistent courses (24.8% vs 12.3% with contacts in all 3 post-diagnosis years; P=.001). Conclusion: Autism is associated with substantially elevated PTSD risk, particularly among females with comorbid ADHD. When PTSD occurs, autistic individuals experience more severe and persistent clinical courses, supporting targeted screening and sustained follow-up.

Adult ADHD is increasingly recognized across the lifespan, yet the psychometric equivalence of the Adult ADHD Self-Report Scale (ASRS) remains unverified for older populations. This study examined age-related Differential Item Functioning (DIF) in 600 adults (n = 100 per decade, ages 20-80) who completed the 18-item ASRS. Using a bi-factor Graded Response Model, we extracted latent ADHD trait scores ({omega}H = .895) and assessed DIF via ordinal logistic regression with adaptive age modeling. Five of 18 items exhibited significant uniform DIF. At equivalent latent severity, older adults were less likely to endorse hyperactivity symptoms in Part A (fidgeting, feeling "driven by a motor") but more likely to endorse specific symptoms in Part B (careless mistakes, misplacing items, interrupting). From ages 20 to 80, expected Part A scores decreased by 1.36 points (~0.27 per decade), while Part B scores increased by 1.15 points (~0.23 per decade). These findings indicate a phenotypic redistribution of ADHD symptoms as individuals age. Because the 6-item Part A screener serves as the primary clinical gatekeeper, its concentration of negative DIF suggests standard screening practice may systematically underestimate ADHD severity in older adults. We recommend using the full 18-item ASRS when screening older populations and suggest that developing age-adjusted norms would improve diagnostic accuracy.

BackgroundAutistic individuals experience higher rates of sleep problems throughout their lives, and there is considerable heterogeneity in manifestations of these issues that remains unexplained. Here, we examine associations over time of heterogenous sleep trajectories with autism diagnosis, and behavioural and genetic factors related to autism. MethodWe used data from the Avon Longitudinal Study of Parents and Children (N=13,886, autistic n=150). The primary outcome was parent and self-reported night-time sleep duration, measured on 10 occasions (between 0.5y and 15.5y). The independent variables were autism diagnosis, autism polygenic score (PGS) and four parent-reported autistic traits: repetitive behaviour, social communication, speech coherence, and sociability. Latent class growth analysis was conducted to identify heterogenous classes of sleep trajectories, and these trajectory classes were regressed onto the independent variables. ResultsFour night-time sleep duration trajectory subclasses were identified; shorter (n=512, 4.1%), longer (n=1654, 13.1%), intermediate-shorter (n=3630, 28.8%), and intermediate-longer (used as the reference class; n=6825, 54.1%). An autism diagnosis was associated with a shorter or intermediate-shorter sleep duration trajectory, compared to the reference class. Similarly, higher scores in domains of repetitive behaviour, speech coherence and social communication were associated with shorter sleep duration trajectories. The autism PGS and sociability were not associated with any sleep trajectories compared to the intermediate-longer sleep trajectory (reference group). ConclusionAn autism diagnosis and specific autistic traits were associated with poorer long-term sleep outcomes across childhood and adolescence, highlighting the need for early, sustained sleep interventions, and the potential of trait-specific mechanisms for sleep problems. HighlightsO_LIFour distinct night-time sleep duration trajectories were identified across development C_LIO_LIAutism diagnosis predicted shorter and intermediate-shorter sleep trajectories C_LIO_LISpecific (but not all) autistic traits were linked to shorter sleep trajectories C_LIO_LIAutism PGS did not predict sleep duration trajectories C_LI

Background Diagnosis and treatment monitoring of attention-deficit/hyperactivity disorder (ADHD) largely rely on subjective assessments, highlighting the need for objective markers. Voice features and speech embeddings represent promising candidates for such markers, as they may capture alterations in speech production relevant to ADHD. However, it remains unclear which speech features are most informative for distinguishing ADHD and monitoring treatment effects, and which speech tasks most reliably elicit such differences. Methods Twenty-seven children with ADHD and 27 age-matched neurotypical controls completed six speech tasks across two study visits. Children with ADHD were unmedicated at baseline (first visit) and were assessed under prescribed methylphenidate treatment at follow-up, whereas controls underwent repeated assessment without intervention. Established acoustic voice features (eGeMAPS) and high-dimensional speech embeddings (WavLm, Whisper) were extracted and analysed using linear mixed models to examine baseline group differences and group-by-time interaction effects reflecting medication-associated change patterns. Results At baseline, children with ADHD differed significantly from controls in frequency, spectral, and temporal voice features, characterized by lower and more variable pitch, altered spectral properties, and reduced rhythmic stability. Group-by-time interaction effects indicated medication-associated modulation in the ADHD group, including reduced loudness variability and increased precision of vowel articulation at follow-up, changes not observed in controls. Speech embeddings revealed additional baseline and interaction effects beyond established acoustic features. Free speech tasks, particularly picture description, yielded the most robust and consistent effects. Conclusion Children with ADHD differed from neurotypical controls in vocal features at baseline and showed distinct longitudinal change patterns consistent with medication-related change. These findings support further investigation of speech-based measures as candidate digital phenotypes and potential digital biomarkers in ADHD, with picture description emerging as a particularly promising task for future clinical assessment protocols.

Background: Sibling-matched designs control for shared familial confounding but remain vulnerable to non-shared confounders. Bi-directional sensitivity analyses, which stratify families by whether the older or younger sibling was exposed, are commonly used to assess carryover effects. We aimed to demonstrate how this methodological approach can introduce severe confounding by parity. Methods: We conducted simulations motivated by a recent epidemiological study. The true causal effect of a hypothetical exposure (prenatal acetaminophen) on neurodevelopmental outcomes was set to strictly null. To introduce parity-related confounding, baseline exposure and outcome probabilities were varied slightly by birth order. We compared conditional logistic regression effect estimates from total sibling models against bi-directional stratified models. Results: In the total simulated sibling cohort, models yielded the true null effect (odds ratio = 1.00) when adjusting for parity. However, the bi-directional analyses exhibited divergent artifactual signals. Because parity is perfectly collinear with exposure in these stratified subsets, it cannot be adjusted for. For example, when the older sibling was exposed, the odds ratio for autism spectrum disorder was 1.68; when the younger was exposed, the odds ratio was 0.60. Conclusions: Divergent estimates in bi-directional sibling analyses can be a predictable artifact of parity confounding rather than evidence of carryover effects or invalidating unmeasured bias. Overall sibling models adjusting for parity may remain robust despite divergent stratified sensitivity results.

BackgroundThe influence of genetic and environmental factors, especially during early development, is critical in the pathogenesis of autism. Maternal autoantibodies that recognize specific fetal brain proteins can be strong predictors of autism risk. These antibodies cross the placenta and bind to their target antigens, which play critical roles in neurodevelopment, thereby increasing autism risk. This etiologically defined subtype is now referred to as Maternal Autoantibody-Related Autism (MARA). The newly developed MAR-AutismTM test is an indirect multi-ELISA assay designed to detect specific combinations of these maternal antibodies, which strongly predicts increased autism risk. ObjectiveTranslation of the indirect ELISA assays for the eight relevant antibodies (LDH-A, LDH-B, GDA, STIP1, CRMP1, CRMP2, NSE and YBOX) from an academic laboratory to a clinical development laboratory for optimization and determination of the analytical performance of the individual antibody assays. MethodsFeasibility assays were transferred from the academic laboratory and their performance confirmed prior to optimization of all steps from target protein production to preliminary threshold determination. Validation to rigorous standards was conducted. The ELISAs are qualitative assays using an internal continuous response and a cutoff to define positivity and negativity for each analyte. Analytical performance metrics of linearity, sensitivity, specificity, precision, and stability were determined by standard testing methodologies. ResultsThe optimized ELISAs all performed at acceptable standards for analytical performance. All of the assays except one were demonstrated to be linear upon dilution with buffer and with non-reactive plasma, however, recovery was overestimated with buffer diluent. The precision profile results demonstrated that the Lower Limit of Quantification (LOQ) was greater than the Limit of Detection (LOD) and below the preliminary thresholds determined from a general population cohort distribution. Precision studies showed coefficients of variation less than 15% with two minor exceptions. Common interfering substances, apart from whole human IgG, did not affect assay performance. The microtiter assay plates were stable for at least 6 months without significant drift. ConclusionOverall, the individual antibody assays demonstrated high sensitivity, specificity, and robustness sufficient to enable extension to clinical validation. These assays enable evaluation of specific antibody combinations that were previously reported to strongly and specifically correlate with autism risk, particularly in settings of suspected diagnosis or in families with an older sibling with a confirmed autism diagnosis.

BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a common heritable neurodevelopmental disorder, affecting [~]7 million children (11.4%) in the U.S. However, ADHDs underlying genetic architecture remains largely unknown. Transcriptome-wide association studies (TWAS), which integrate expression quantitative trait loci (eQTL) and GWAS summary data, can identify differentially expressed risk genes underlying complex phenotypes. Here we conduct a TWAS of ADHD using expression data from multiple brain tissues to improve understanding of the complex genetic architecture underlying this psychopathology. MethodsWe applied the TWAS framework OTTERS to train multiple gene expression imputation models using cis-eQTL summary statistics from MetaBrain for three brain regions: cortex (n=2,683), basal ganglia (n=208), and cerebellum (n=492), and GWAS summary statistics from the most recent meta-analysis of ADHD (n=225,534; case fraction =0.17). We further conducted fine-mapping, colocalization analysis, and functional enrichment analysis. ResultsWe identified 29 significant TWAS risk genes for ADHD (11 in cortex, 4 in basal ganglia, and 14 in cerebellum). Six genes appear novel for ADHD (MPL, C1orf210, MDFIC, NKX2-2, FAM183A, HIGD1A) while four genes were previously implicated in autism spectrum disorder (XRN2, KIZ, NKX2-4, NKX2-2). Pathway analysis indicated cortex and basal ganglia were enriched for neurodevelopmental pathways and regulation of cell development, and the protein-protein interaction network was statistically significant (p=1.12E-04). ConclusionThis multi-tissue TWAS refines the genetic architecture of ADHD by identifying genes whose genetically regulated expression is associated with risk, including six candidates not previously linked to ADHD. Together, these findings provide novel insights for potential targets in translational research and drug discovery.