Enhanced motor noise in an autism subtype with poor motor skills.

BACKGROUND: Motor difficulties are common in many, but not all, autistic individuals. These difficulties can co-occur with other problems, such as delays in language, intellectual, and adaptive functioning. Biological mechanisms underpinning such difficulties are less well understood. Poor motor skills tend to be more common in individuals carrying highly penetrant rare genetic mutations. Such mechanisms may have downstream consequences of altering neurophysiological excitation-inhibition balance and lead to enhanced behavioral motor noise. METHODS: This study combined publicly available and in-house datasets of autistic (n = 156), typically-developing (TD, n = 149), and developmental coordination disorder (DCD, n = 23) children (age 3-16 years). Autism motor subtypes were identified based on patterns of motor abilities measured from the Movement Assessment Battery for Children 2nd edition. Stability-based relative clustering validation was used to identify autism motor subtypes and evaluate generalization accuracy in held-out data. Autism motor subtypes were tested for differences in motor noise, operationalized as the degree of dissimilarity between repeated motor kinematic trajectories recorded during a simple reach-to-drop task. RESULTS: Relatively 'high' (n = 87) versus 'low' (n = 69) autism motor subtypes could be detected and which generalize with 89% accuracy in held-out data. The relatively 'low' subtype was lower in general intellectual ability and older at age of independent walking, but did not differ in age at first words or autistic traits or symptomatology. Motor noise was considerably higher in the 'low' subtype compared to 'high' (Cohen's d = 0.77) or TD children (Cohen's d = 0.85), but similar between autism 'high' and TD children (Cohen's d = 0.08). Enhanced motor noise in the 'low' subtype was also most pronounced during the feedforward phase of reaching actions. LIMITATIONS: The sample size of this work is limited. Future work in larger samples along with independent replication is important. Motor noise was measured only on one specific motor task. Thus, a more comprehensive assessment of motor noise on many other motor tasks is needed. CONCLUSIONS: Autism can be split into at least two discrete motor subtypes that are characterized by differing levels of motor noise. This suggests that autism motor subtypes may be underpinned by different biological mechanisms.

Predictive Measures in Child Language Development: The Role of Familial History and Early Expressive Vocabulary.

PURPOSE: Prediction of developmental language disorder in children under 3 years of age is challenging. Among early risk factors, research has focused on having a positive familial history (FH+) for language or literacy problems and on late language emergence, that is, late-talker (LT) status. The interaction between these two risk factors and their cumulative effect is still debated. Here, we (a) investigate the effect of FH+ on 24-month language development, (b) test for cumulative effects of FH+ status and early language delay on 36-month language outcomes, and (c) disentangle the direct and indirect effects of familial history (FH) on the language outcome. METHOD: One hundred eighty-five Italian children were followed up longitudinally between 24 and 36 months of age (64 FH+ and 121 FH-) through parental questionnaires and direct child assessment. RESULTS: At the age of 24 months, the FH+ group showed worse expressive vocabulary and higher prevalence of LT. At the age of 36 months, main effects of LT and FH were identified on lexical and phonological performances, respectively. Interestingly, significant interaction effects were identified on expressive vocabulary and phonological processing. Path analysis highlights that FH had a direct effect on later measures of phonology, whereas its effect on 36-month lexical abilities was indirect, via measures of expressive vocabulary at 24 months. CONCLUSIONS: The study suggests specific predictive roles of FH and LT status on language development. Interestingly, FH+ seems to represent an additive risk for LT children. The use of cumulative risk measures is confirmed as a powerful approach to identify those children with the highest probability of developing persistent language difficulties. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.26790580.

Pupillary responses for social versus non-social stimuli in autism: A systematic review and meta-analysis.

Pupillometry has gained attention as a valuable tool for assessing autonomic nervous system activity and studying phasic changes in pupil size to comprehend underlying neurocognitive mechanisms. However, knowledge regarding pupillary responses to social processing in autism is limited. We conducted a systematic review and meta-analysis, examining research studies on pupil size changes that compare social and non-social stimuli in autism. Electronic searches were performed for articles up to September 2023 and relevant studies were evaluated following PRISMA guidelines. Out of 284 articles screened, 14 studies were eligible for systematic review. The results indicated that non-autistic individuals showed larger pupil size for social compared to non-social stimuli (g = 0.54; 95 % CI [0.25, 0.82]), whereas autistic individuals seemed to exhibit no differences between the two conditions. However, high heterogeneity was observed between studies in autistic populations, compromising interpretability. Despite such limitations, pupillary responses may constitute an objective physiological marker of social processing in autism. This review emphasizes the need for further investigations into pupillary responses in autism across different life stages.

Comparing remote versus in-person assessment of learning skills in children with specific learning disabilities.

Background: Interactive telemedicine applications have been progressively introduced in the assessment of cognitive and literacy skills. However, there is still a lack of research focusing on the validity of this methodology for the neuropsychological assessment of children with Specific Learning Disorder (SLD). Methods: Seventy-nine children including 40 typically developing children (18 males, age 11.5 ± 1.06) and 39 children with SLD (24 males, age 12.3 ± 1.28) were recruited. Each participant underwent the same neuropsychological battery assessing reading accuracy, speed, and comprehension, writing, numerical processing, computation, and semantic numerical sense, twice (once during an in-person session (I) and once during a remote (R) home-based videoconference session). Four groups were subsequently defined based on the administration order. Repeated-measure-ANOVAs with assessment type (R vs. I testing) as within-subject factor and diagnosis (SLD vs. TR) and administration order (R-I vs. I-R) as between-subject factors, and between-group t-tests comparing the two assessment types within each time of administration, were run. Results: No differences emerged between I and R assessments of reading accuracy and speed, numerical processing, and computation; on the contrary, potential biases against R assessment emerged when evaluating skills in writing, reading comprehension, and semantic numerical sense. However, regardless of the assessment type, the scores obtained with I and R assessments within the same administration time point overlapped. Discussion: These results partially support the validity and reliability of the assessment of children's learning skills via a remote home-based videoconferencing system. Implementing telemedicine as an assessment tool may increase timely access to primary health care and to support research activity.

Exploring the impact of parents' face-mask wearing on dyadic interactions in infants at higher likelihood for autism compared with general population.

Since the COVID-19 pandemic, both the public and researchers have raised questions regarding the potential impact of protective face-mask wearing on infants' development. Nevertheless, limited research has tested infants' response to protective face-mask wearing adults in real-life interactions and in neurodiverse populations. In addition, scarce attention was given to changes in interactive behavior of adults wearing a protective face-mask. The aims of the current study were (1) to examine differences in 12-month-old infants' behavioral response to an interactive parent wearing a protective face-mask during face-to-face interaction, (2) to investigate potential differences in infants at higher likelihood for autism (HL-ASD) as compared with general population (GP) counterparts, and (3) to explore significant differences in parents' behaviors while wearing or not wearing a protective face-mask. A total of 50 mother-infant dyads, consisting of 20 HL-ASD infants (siblings of individuals with autism) and 30 GP infants, participated in a 6-min face-to-face interaction. The interaction was videotaped through teleconferencing and comprised three 2-min episodes: (a) no mask, (b) mask, and (c) post-mask. Infants' emotionality and gaze direction, as well as mothers' vocal production and touching behaviors, were coded micro-analytically. Globally, GP infants exhibited more positive emotionality compared with their HL-ASD counterparts. Infants' negative emotionality and gaze avoidance did not differ statistically across episodes. Both groups of infants displayed a significant increase in looking time toward the caregiver during the mask episode. No statistically significant differences emerged in mothers' behaviors. These findings suggest that the use of protective face-masks might not negatively affect core dimensions of caregiver-infant interactions in GP and HL-ASD 12-month-old infants.

Predicting Response to Neuropsychological Intervention in Developmental Dyslexia: A Retrospective Study.

Identifying the patients who are likely to be non-responders to a certain treatment may allow clinicians to provide alternative strategies and avoid frustration and unrealistic expectations for the patients and their families. A retrospective study on 145 children treated with visual hemisphere-specific stimulation examined the specific profiles (reading, writing, metaphonology, memory, callosal functions) of non-responders, and identified predictors of response to intervention (reading, reading and writing) through linear regression models. The effects of additional variables such as rapid automatized naming (RAN) and Visual Search were investigated in a subsample of 48 participants. Subgroups related to gender and dyslexia subtype were considered in the analyses. The results highlight an Intervention Differential Effect (IDE) not depending on regression to the mean and mathematical coupling effects. The characteristics of non-responders for reading seem to correspond children with mild reading and severe writing impairments; non-responders for reading and writing are those with impaired callosal transfer. Predictors of overall response to intervention were pre-test reading and writing scores; phoneme blending, accuracy in visual search and speed in rapid automatized naming contributed to explaining response variance. Specific predictors for female vs. male participants and dyslexia subtypes were identified.

Use of Machine Learning Models to Differentiate Neurodevelopment Conditions Through Digitally Collected Data: Cross-Sectional Questionnaire Study.

BACKGROUND: Diagnosis of child and adolescent psychopathologies involves a multifaceted approach, integrating clinical observations, behavioral assessments, medical history, cognitive testing, and familial context information. Digital technologies, especially internet-based platforms for administering caregiver-rated questionnaires, are increasingly used in this field, particularly during the screening phase. The ascent of digital platforms for data collection has propelled advanced psychopathology classification methods such as supervised machine learning (ML) into the forefront of both research and clinical environments. This shift, recently called psycho-informatics, has been facilitated by gradually incorporating computational devices into clinical workflows. However, an actual integration between telemedicine and the ML approach has yet to be fulfilled. OBJECTIVE: Under these premises, exploring the potential of ML applications for analyzing digitally collected data may have significant implications for supporting the clinical practice of diagnosing early psychopathology. The purpose of this study was, therefore, to exploit ML models for the classification of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) using internet-based parent-reported socio-anamnestic data, aiming at obtaining accurate predictive models for new help-seeking families. METHODS: In this retrospective, single-center observational study, socio-anamnestic data were collected from 1688 children and adolescents referred for suspected neurodevelopmental conditions. The data included sociodemographic, clinical, environmental, and developmental factors, collected remotely through the first Italian internet-based screening tool for neurodevelopmental disorders, the Medea Information and Clinical Assessment On-Line (MedicalBIT). Random forest (RF), decision tree, and logistic regression models were developed and evaluated using classification accuracy, sensitivity, specificity, and importance of independent variables. RESULTS: The RF model demonstrated robust accuracy, achieving 84% (95% CI 82-85; P<.001) for ADHD and 86% (95% CI 84-87; P<.001) for ASD classifications. Sensitivities were also high, with 93% for ADHD and 95% for ASD. In contrast, the DT and LR models exhibited lower accuracy (DT 74%, 95% CI 71-77; P<.001 for ADHD; DT 79%, 95% CI 77-82; P<.001 for ASD; LR 61%, 95% CI 57-64; P<.001 for ADHD; LR 63%, 95% CI 60-67; P<.001 for ASD) and sensitivities (DT: 82% for ADHD and 88% for ASD; LR: 62% for ADHD and 68% for ASD). The independent variables considered for classification differed in importance between the 2 models, reflecting the distinct characteristics of the 3 ML approaches. CONCLUSIONS: This study highlights the potential of ML models, particularly RF, in enhancing the diagnostic process of child and adolescent psychopathology. Altogether, the current findings underscore the significance of leveraging digital platforms and computational techniques in the diagnostic process. While interpretability remains crucial, the developed approach might provide valuable screening tools for clinicians, highlighting the significance of embedding computational techniques in the diagnostic process.

Visual statistical learning in preverbal infants at a higher likelihood of autism and its association with later social communication skills.

Visual statistical Learning (SL) allows infants to extract the statistical relationships embedded in a sequence of elements. SL plays a crucial role in language and communication competencies and has been found to be impacted in Autism Spectrum Disorder (ASD). This study aims to investigate visual SL in infants at higher likelihood of developing ASD (HL-ASD) and its predictive value on autistic-related traits at 24-36 months. At 6 months of age, SL was tested using a visual habituation task in HL-ASD and neurotypical (NT) infants. All infants were habituated to a visual sequence of shapes containing statistically predictable patterns. In the test phase, infants viewed the statistically structured, familiar sequence in alternation with a novel sequence that did not contain any statistical information. HL-ASD infants were then evaluated at 24-36 months to investigate the associations between visual SL and ASD-related traits. Our results showed that NT infants were able to learn the statistical structure embedded in the visual sequences, while HL-ASD infants showed different learning patterns. A regression analysis revealed that SL ability in 6-month-old HL-ASD infants was related to social communication and interaction abilities at 24-36 months of age. These findings indicate that early differences in learning visual statistical patterns might contribute to later social communication skills.

Psychosocial resources and psychopathology among persons with neuromuscular disorders during the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic substantially affected the lives of persons with inherited neuromuscular disorders (INMD), causing disruption in clinical and support services. While several studies have investigated mental health, distress and psychosocial resources in the general population during the pandemic, little is known about the experience of persons with INMD. METHODS: This study was aimed to fill this gap by jointly investigating both psychopathological symptoms and psychosocial resources - specifically, resilience and perceived social support - among persons with INMD during the pandemic, taking into account demographic and clinical factors. Between April and December 2020, 59 participants with INMD (aged 15-59, 71.2% M) completed a questionnaire collecting demographic and clinical data, the Multidimensional Scale of Perceived Social Support, the Resilience Scale for Adults, and the Achenbach System of Empirically Based Assessment. RESULTS: Overall, participants showed good levels of resilience and perceived social support. A minority of participants reported clinically relevant psychopathological symptoms, 28.81% for anxiety and depression. Most psychopathological symptoms were negatively correlated with resilience (-0.347 < r < - .420), but not significantly associated with social support. Consistent with previous studies, regression analyses highlighted that participants with Duchenne muscular dystrophy were more prone to report anxious and depressive symptoms (B = 1.748, p = .028, OR = 5.744), and participants with myotonic dystrophy, attention problems (B = 2.339, p = .006, OR = 10.376). Resilience emerged as a potential predictor of lower anxious-depressive symptoms (B=-1.264, p = .012, OR = 0.283). CONCLUSIONS: The findings suggest the importance to investigate psychosocial resources in addition to psychopathology among persons with INMD, and to design interventions supporting resilience as a protective factor for mental health promotion.

Action video games normalise the phonemic awareness in pre-readers at risk for developmental dyslexia.

Action video-games (AVGs) could improve reading efficiency, enhancing not only visual attention but also phonological processing. Here we tested the AVG effects upon three consolidated language-based predictors of reading development in a sample of 79 pre-readers at-risk and 41 non-at-risk for developmental dyslexia. At-risk children were impaired in either phonemic awareness (i.e., phoneme discrimination task), phonological working memory (i.e., pseudoword repetition task) or rapid automatized naming (i.e., RAN of colours task). At-risk children were assigned to different groups by using an unequal allocation randomization: (1) AVG (n = 43), (2) Serious Non-Action Video Game (n = 11), (3) treatment-as-usual (i.e., speech therapy, n = 11), and (4) waiting list (n = 14). Pre- and post-training comparisons show that only phonemic awareness has a significantly higher improvement in the AVG group compared to the waiting list, the non-AVG, and the treatment-as-usual groups, as well as the combined active groups (n = 22). This cross-modal plastic change: (i) leads to a recovery in phonemic awareness when compared to the not-at-risk pre-readers; (ii) is present in more than 80% of AVG at-risk pre-readers, and; (iii) is maintained at a 6-months follow-up. The present findings indicate that this specific multisensory attentional training positively affects how phonemic awareness develops in pre-readers at risk for developmental dyslexia, paving the way for innovative prevention programs.

Rules generalization in children with dyslexia.

BACKGROUND: Rule learning (RL) is the ability to extract and generalize higher-order repetition-based structures. Children with Developmental Dyslexia (DD) often report difficulties in learning complex regularities in sequential stimuli, which might be due to the complexity of the rule to be learned. Learning high-order repetition-based rules represents a building block for the development of language skills. AIMS: This study investigates the ability to extract and generalize simple, repetition-based visual rules (e.g., ABA) in 8-11-year-old children without (TD) and with a diagnosis of Development Dyslexia (DD) and its relationship with language and reading skills. METHOD: Using a forced-choice paradigm, children were first exposed to a visual sequence containing a repetition-based rule (e.g., ABA) and were then asked to recognize familiar and novel rules generated by new visual elements. Standardized language and reading tests were also administered to both groups. RESULTS: The accuracy in recognizing rules was above chance for both groups, even though DD children were less accurate than TD children, suggesting a less efficient RL mechanism in the DD group. Moreover, visual RL was positively correlated with both language and reading skills. CONCLUSION: These results further confirm the crucial role of RL in the acquisition of linguistic skills and mastering reading abilities.

The challenge of remote treatment in neuropsychological intervention for reading and spelling in dyslexia: A prospective observational cohort study.

Telemedicine approaches have proved to be valuable solutions for the delivery of treatment for many health-related issues, and crucial during the pandemics. Nonetheless, the efficacy of such Web-based practices in developmental dyslexia needs to be thoroughly evaluated. To this aim, the effects of a multi-componential program for neuropsychological intervention in dyslexia delivered as an outpatient program were compared with those obtained with a remotely delivered, Web-based treatment, based on the same methodological principles and delivered with the same duration and intensity. The treatment-related changes obtained with a combination of visual hemisphere-specific stimulation and training of visual-spatial attention through action video games, were compared to those obtained through remote treatment via the Tachidino Web-based platform. Both treatments had a duration of 4 weeks. The same battery of reading and phonemic awareness tests was delivered in presence, before and after treatment, as well as at 6-months follow-up. User satisfaction was assessed through parents and user questionnaires. Both treatments were significantly and similarly effective in improving reading speed, reading accuracy, and writing accuracy. No reduction in the effects was observed after treatment discontinuation. The Web-based treatment may thus offer a valid alternative to in-person intervention, optimizing the flexibility, capillary diffusion and cost-effectiveness of intervention.

Prolonged neural encoding of visual information in autism.

Autism spectrum disorder (ASD) is associated with a hyper-focused visual attentional style, impacting higher-order social and affective domains. The understanding of such peculiarity can benefit from the use of multivariate pattern analysis (MVPA) of high-resolution electroencephalography (EEG) data, which has proved to be a powerful technique to investigate the hidden neural dynamics orchestrating sensory and cognitive processes. Here, we recorded EEG in typically developing (TD) children and in children with ASD during a visuo-spatial attentional task where attention was exogenously captured by a small (zoom-in) or large (zoom-out) cue in the visual field before the appearance of a target at different eccentricities. MVPA was performed both in the cue-locked period, to reveal potential differences in the modulation of the attentional focus, and in the target-locked period, to reveal potential cascade effects on stimulus processing. Cue-locked MVPA revealed that while in the TD group the pattern of neural activity contained information about the cue mainly before the target appearance, the ASD group showed a temporally sustained and topographically diffuse significant decoding of the cue neural response even after the target onset, suggesting a delayed extinction of cue-related neural activity. Crucially, this delayed extinction positively correlated with behavioral measures of attentional hyperfocusing. Results of target-locked MVPA were coherent with a hyper-focused attentional profile, highlighting an earlier and stronger decoding of target neural responses in small cue trials in the ASD group. The present findings document a spatially and temporally overrepresented encoding of visual information in ASD, which can constitute one of the main reasons behind their peculiar cognitive style.

Exploring telediagnostic procedures in child neuropsychiatry: addressing ADHD diagnosis and autism symptoms through supervised machine learning.

Recently, there has been an increase in telemedicine applied to child neuropsychiatry, such as the use of online platforms to collect remotely case histories and demographic and behavioral information. In the present proof-of-concept study, we aimed to understand to what extent information parents and teachers provide through online questionnaires overlaps with clinicians' diagnostic conclusions on attention-deficit/hyperactivity disorder (ADHD). Moreover, we intended to explore a possible role that autism spectrum disorders (ASD) symptoms played in this process. We examined parent- and teacher-rated questionnaires collected remotely and an on-site evaluation of intelligence quotients from 342 subjects (18% females), aged 3-16 years, and referred for suspected ADHD. An easily interpretable machine learning model-decision tree (DT)-was built to simulate the clinical process of classifying ADHD/non-ADHD based on collected data. Then, we tested the DT model's predictive accuracy through a cross-validation approach. The DT classifier's performance was compared with those that other machine learning models achieved, such as random forest and support vector machines. Differences in ASD symptoms in the DT-identified classes were tested to address their role in performing a diagnostic error using the DT model. The DT identified the decision rules clinicians adopt to classify an ADHD diagnosis with an 82% accuracy rate. Regarding the cross-validation experiment, our DT model reached a predictive accuracy of 74% that was similar to those of other classification algorithms. The caregiver-reported ADHD core symptom severity proved the most discriminative information for clinicians during the diagnostic decision process. However, ASD symptoms were a confounding factor when ADHD severity had to be established. Telehealth procedures proved effective in obtaining an automated output regarding a diagnostic risk, reducing the time delay between symptom detection and diagnosis. However, this should not be considered an alternative to on-site procedures but rather as automated support for clinical practice, enabling clinicians to allocate further resources to the most complex cases.

Autism spectrum disorder prevalence in Italy: a nationwide study promoted by the Ministry of Health.

BACKGROUND: This nationwide study aimed to estimate Autism Spectrum Disorder (ASD) prevalence in 7-9-year-old Italian children. Promoted by Italy's Ministry of Health and coordinated by the National Observatory for Autism at the National Institute of Health, it covered schools in northern (Lecco and Monza-Brianza), central (Rome and its province), and southern (Palermo and its province) regions from February 24, 2016, to February 23, 2018, using a multi-stage approach defined by the European Union's ASD network. METHODS: Phase one identified ASD-diagnosed children in mainstream schools through local Ministry of Education (MoE) disability registries. Phase two had a subset of schools screen 7-9-year-olds using the Social Communication Questionnaire-Life version (SCQ-L). Those with SCQ-L scores of 15 + underwent clinical consultation for ASD symptoms, cognitive abilities, and life skills. To counter potential false negatives, 20% scoring 11-14 were randomly assessed via Autism Diagnostic Interview-Revised (ADI-R). RESULTS: MoE data revealed 9.8 per 1000 certified ASD children in the north, 12.2 in the central, and 10.3 in the south. In phase two, 35,823 SCQ-L questionnaires were distributed across 198 schools (northern: 11,190 in 49 schools, central: 13,628 in 87 schools, southern: 11,005 in 62 schools). Of SCQ-L respondents, 2.4% (n = 390) scored above the 15 cutoff. Among these, 100 had ASD diagnoses, and 50 had other diagnoses. Among 115 families assessed, 16.5% (n = 19) received ASD diagnoses. CONCLUSIONS: The estimated prevalence of ASD in Italy was 13.4 (11.3-16.0) per 1,000 children aged 7-9 years, with a male-to-female ratio of 4.4:1. It will guide national policies in enhancing services tailored to the specific needs of autistic children.

Exposure to environmental pollutants and attention-deficit/hyperactivity disorder: an overview of systematic reviews and meta-analyses.

Although heritability estimates suggest a role for genetic components, environmental risk factors have been described as relevant in the etiology of attention deficit/hyperactivity disorder (ADHD). Several studies have investigated the role of toxicological pollution, i.e., air pollution, heavy metals, POPs, and phthalates. Clear evidence for association of ADHD and environmental factors has not been provided yet. To answer this, we have assessed all available systematic reviews and meta-analyses that focused on the association between pollutant exposure and either ADHD diagnosis or symptoms. More than 1800 studies were screened of which 14 found eligible. We found evidence of a significant role for some pollutants, in particular heavy metals and phthalates, in the increased risk of developing ADHD symptoms. However, at the current stage, data from existing literature also do not allow to weight the role of the different environmental pollutants. We also offer a critical examination of the reviews/meta-analyses and provide indications for future studies in this field. PROSPERO registration: CRD42022341496.

Differentiating early sensory profiles in toddlers at elevated likelihood of autism and association with later clinical outcome and diagnosis.

LAY ABSTRACT: Early sensory responsiveness may produce cascading effects on later development, but the relation between sensory profiles and autistic diagnosis remains unclear. In a longitudinal sample of toddlers at elevated likelihood for autism, we aimed to characterize sensory subgroups and their association with clinical outcomes later on. Three sensory subgroups were described and early sensory sensitivity plays a significant role in later development and diagnosis. This study supported the importance of examining different levels of sensory patterns to dissect the phenotypic heterogeneity in sensory processing. As sensory differences are associated with later developmental outcomes, these results may be critical when designing intervention needs and support for children at increased likelihood for neurodevelopmental disorders.

Intergenerational longitudinal associations between parental reading/musical traits, infants' auditory processing, and later phonological awareness skills.

The intergenerational transmission of language/reading skills has been demonstrated by evidence reporting that parental literacy abilities contribute to the prediction of their offspring's language and reading skills. According to the "Intergenerational Multiple Deficit Model," literacy abilities of both parents are viewed as indicators of offspring's liability for literacy difficulties, since parents provide offspring with genetic and environmental endowment. Recently, studies focusing on the heritability of musical traits reached similar conclusions. The "Musical Abilities, Pleiotropy, Language, and Environment (MAPLE)" framework proposed that language/reading and musical traits share a common genetic architecture, and such shared components have an influence on the heritable neural underpinnings of basic-level skills underlying musical and language traits. Here, we investigate the intergenerational transmission of parental musical and language-related (reading) abilities on their offspring's neural response to a basic auditory stimulation (neural intermediate phenotype) and later phonological awareness skills, including in this complex association pattern the mediating effect of home environment. One-hundred and seventy-six families were involved in this study. Through self-report questionnaires we assessed parental reading abilities and musicality, as well as home literacy and musical environment. Offspring were involved in a longitudinal study: auditory processing was measured at 6 months of age by means of a Rapid Auditory Processing electrophysiological paradigm, and phonological awareness was assessed behaviorally at 5 years of age. Results reveal significant correlations between parents' reading skills and musical traits. Intergenerational associations were investigated through mediation analyses using structural equation modeling. For reading traits, the results revealed that paternal reading was indirectly associated with children's phonological awareness skills via their electrophysiological MisMatch Response at 6 months, while maternal reading was directly associated with children's phonological awareness. For musical traits, we found again that paternal musicality, rather than maternal characteristics, was associated with children's phonological phenotypes: in this case, the association was mediated by musical environment. These results provide some insight about the intergenerational pathways linking parental reading and musical traits, neural underpinnings of infants' auditory processing and later phonological awareness skills. Besides shedding light on possible intergenerational transmission mechanisms, this study may open up new perspectives for early intervention based on environmental enrichment.

A multimodal approach can identify specific motor profiles in autism and attention-deficit/hyperactivity disorder.

It is still unclear whether and to what extent the motor difficulties are specific to autism. This study aimed to determine whether a multimodal assessment of motor skills could accurately discriminate autistic children from attention-deficit/hyperactivity disorder (ADHD) and typically developing (TD) peers. Seventy-five children, aged 7-13, equally divided into three groups, were assessed with the developmental coordination disorder questionnaire (DCDQ), the movement assessment battery for children 2 (MABC2), the sensorimotor subtests of NEPSY-II, and the kinematic analysis of a reach-to-drop task. Principal component analysis (PCA) on DCDQ subscales revealed one factor-Caregiver Report-, whereas MABC2/NEPSY-II scores identified three factors-namely, Object Interception and Balance, Motor Imitation, and Fine-Motor Skills-. Lastly, PCA on kinematic variables identified four factors: PC1, loaded by the parameters of velocity and acceleration throughout the task, PC2 and PC3 involved the temporal parameters of the two submovements, and PC4 accounted for the wrist inclination at ball drop. When comparing autistic and TD children, Caregiver Report and Motor Imitation factors predicted membership with 87.2% of accuracy. In the model comparing ADHD and TD groups, Caregiver Report and Fine-Motor Skills predicted membership with an accuracy of 73.5%. In the last model, the Object Interception and Balance factor differentiated autistic children from ADHD with an accuracy of 73.5%. In line with our previous findings, kinematics did not differentiate school-aged autistic children from ADHD and TD peers. The present findings show that specific motor profiles in autism and ADHD can be isolated with a multimodal investigation of motor skills.

Celiac disease in autism spectrum disorder: data from an Italian child cohort.

BACKGROUND: In recent decades some studies described the frequent co-occurrence of celiac disease autoimmunity and overt celiac disease in patients with autism. Therefore, it was suggested that celiac disease could play a possible role in the etiopathogenesis of autism spectrum disorder. However, several other studies have not confirmed this association. The aim of the present study was to elucidate the potential association between autism spectrum disorder and celiac disease. METHODS: We prospectively collected data from an Italian cohort of 223 children at the time of their clinical diagnosis of autism spectrum disorder in the 2019-2020 period. A serological celiac disease screening was performed and data were available for 196 patients; male (M):female (F) ratio = 4.4:1; median age = 3.6 years; age range = 1.6-12.8 years. Full-blown celiac disease was established according to the diagnostic algorithm of the European Society of Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) 2012 or 2019 guidelines. Fisher's exact test was used to compare the celiac disease seroprevalence and prevalence in our autism spectrum disorder cohort and in the Italian healthy pediatric population studied by Gatti et al. to highlight the possible differences between the two groups. RESULTS: A not statistically significant difference between the celiac disease seroprevalence in our autism spectrum disorder cohort (4.08%) and Gatti's Italian healthy group (2.22%) was found, p = 0.0810; OR = 1.871. A similar result emerged for overt celiac disease prevalences (2.24% versus 1.58%, respectively), p = 0.2862; OR = 1.431. CONCLUSIONS: Our data validates a weakness of association between autism spectrum disorder and celiac disease. On the basis of our results, a regular screening for CD in patients with ASD is not recommended to a greater extent than in the general population.