1. Bettencourt C, Garret-Gloanec N, Pellerin H, Péré P, Bertamini G, Squillante M, Roos-Weil F, Ferrand L, Pernel AS, Apter G, Chetouani M, Cortese S, Cohen D. Promoting emotional and behavioral interventions in ASD treatment: Evidence from EPIGRAM, A naturalistic, prospective and longitudinal study. Res Dev Disabil;2024 (Mar 2);147:104688.

BACKGROUND: Prognostic factors from naturalistic treatment studies of children with Autism Spectrum Disorder (ASD) remain largely unknown. We aimed to identify baseline and treatment-related prognostic predictors at 1-year follow-up after Integrative Care Practices (ICPs). METHODS: Eighty-nine preschool children with severe ASD were given ICP combining nine therapeutic workshops based on children’s needs. Participants were assessed at baseline and during 12 months follow-up with the Psycho-educational Profile-3-R, Children Autism Rating Scale, Parental Global Impression, and the Autistic Behaviors Scale. We assessed prognostic predictors using multivariable regression models and explored treatment ingredients influencing outcome using Classification and Regression Trees (CART). RESULTS: Multivariable models showed that being a child from first generation immigrant parents predicted increased maladaptive behaviors, whereas play activities had an opposite effect; severity of ASD symptoms and impaired cognitive functions predicted worse autism severity at follow-up; and lower play activities predicted worse parent impression. Regarding treatment effects, more emotion/behavioral interventions predicted better outcomes, and more communication interventions predicted lower autism severity, whereas more education and cognitive interventions had an opposite effect. CART confirmed that more hours of intervention in the emotion/behavioral domain helped classifying cases with better outcomes. More parental support was associated with decreased maladaptive behaviors. Sensorimotor and education interventions also significantly contributed to classifying cases according to outcomes but defined subgroups with opposite prognosis. CONCLUSION: Children who exhibited the best prognosis following ICPs had less autism severity, better cognition, and non-immigrant parents at baseline. Emotion/behavior interventions appeared key across all outcomes and should be promoted.

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2. Chen Y, Xue Y, Jia L, Yang M, Huang G, Xie J. Causal effects of gut microbiota on autism spectrum disorder: A two-sample mendelian randomization study. Medicine (Baltimore);2024 (Mar 1);103(9):e37284.

There is increasing evidence that alterations in gut microbiota (GM) composition are associated with autism spectrum disorder (ASD), but no reliable causal relationship has been established. Therefore, a 2-sample Mendelian randomization (MR) study was conducted to reveal a potential causal relationship between GM and ASD. Instrumental variables for 211 GM taxa were obtained from genome-wide association studies (GWAS) and Mendelian randomization studies to estimate their impact on ASD risk in the iPSYCH-PGC GWAS dataset (18,382 ASD cases and 27,969 controls). Inverse variance weighted (IVW) is the primary method for causality analysis, and several sensitivity analyses validate MR results. Among 211 GM taxa, IVW results confirmed that Tenericutes (P value = .0369), Mollicutes (P value = .0369), Negativicutes (P value = .0374), Bifidobacteriales (P value = .0389), Selenomonadales (P value = .0374), Bifidobacteriaceae (P value = .0389), Family XIII (P value = .0149), Prevotella7 (P value = .0215), Ruminococcaceae NK4A214 group (P value = .0205) were potential protective factors for ASD. Eisenbergiella (P value = .0159) was a possible risk factor for ASD. No evidence of heterogeneous, pleiotropic, or outlier single-nucleotide polymorphism was detected. Additionally, further sensitivity analysis verified the robustness of the above results. We confirm a potential causal relationship between certain gut microbes and ASD, providing new insights into how gut microbes mediate ASD. The association between them needs to be further explored and will provide new ideas for the prevention and treatment of ASD.

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3. Chetcuti L, Varcin KJ, Boutrus M, Smith J, Bent CA, Whitehouse AJO, Hudry K. Feasibility of a 2-minute eye-tracking protocol to support the early identification of autism. Sci Rep;2024 (Mar 1);14(1):5117.

We tested the potential for Gazefinder eye-tracking to support early autism identification, including feasible use with infants, and preliminary concurrent validity of trial-level gaze data against clinical assessment scores. We embedded the ~ 2-min ‘Scene 1S4’ protocol within a comprehensive clinical assessment for 54 consecutively-referred, clinically-indicated infants (prematurity-corrected age 9-14 months). Alongside % tracking rate as a broad indicator of feasible assessment/data capture, we report infant gaze data to pre-specified regions of interest (ROI) across four trial types and associations with scores on established clinical/behavioural tools. Most infants tolerated Gazefinder eye-tracking well, returning high overall % tracking rate. As a group, infants directed more gaze towards social vs. non-social (or more vs. less socially-salient) ROIs within trials. Behavioural autism features were correlated with increased gaze towards non-social/geometry (vs. social/people) scenes. No associations were found for gaze directed to ROIs within other stimulus types. Notably, there were no associations between developmental/cognitive ability or adaptive behaviour with gaze towards any ROI. Gazefinder assessment seems highly feasible with clinically-indicated infants, and the people vs. geometry stimuli show concurrent predictive validity for behavioural autism features. Aggregating data across the ~ 2-min autism identification protocol might plausibly offer greater utility than stimulus-level analysis alone.

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4. Griffin JW, Webb SJ, Keehn B, Dawson G, McPartland JC. Autistic Individuals Do Not Alter Visual Processing Strategy During Encoding Versus Recognition of Faces: A Hidden Markov Modeling Approach. J Autism Dev Disord;2024 (Mar 2)

PURPOSE: Visual face recognition-the ability to encode, discriminate, and recognize the faces of others-is fundamentally supported by eye movements and is a common source of difficulty for autistic individuals. We aimed to evaluate how visual processing strategies (i.e., eye movement patterns) directly support encoding and recognition of faces in autistic and neurotypical (NT) individuals. METHODS: We used a hidden Markov modeling approach to evaluate the spatiotemporal dynamics of eye movements in autistic (n = 15) and neurotypical (NT) adolescents (n = 17) during a face identity recognition task. RESULTS: We discovered distinct eye movement patterns among all participants, which included a focused and exploratory strategy. When evaluating change in visual processing strategy across encoding and recognition phases, autistic individuals did not shift their eye movement patterns like their NT peers, who shifted to a more exploratory visual processing strategy during recognition. CONCLUSION: These findings suggest that autistic individuals do not modulate their visual processing strategy across encoding and recognition of faces, which may be an indicator of less efficient face processing.

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5. Kirby AV, Conner CM, Mazefsky CA. Are autistic females at greater risk of suicide? A call for clarity to advance suicide prevention for the whole community. Autism Res;2024 (Mar 1)

Understanding suicide risk is critical for supporting prevention. A growing body of evidence shows autistic people are at greater risk for multiple suicide-related outcomes than non-autistic people. This commentary is in response to an observed pattern of miscommunication in scientific and community spaces about autistic females having higher risk of suicide. However, it is not always clear who they are being compared with in these statements. To address this confusion, we summarize the current population-based evidence on autistic suicide risk, highlighting findings related to sex similarities and differences, which actually indicates comparable rates of suicide death among autistic males and females, and mixed findings related to sex differences in risk of other suicidal behaviors. We call for greater clarity in suicide risk communication moving forward focused on outcomes, measurement, sampling methods, and comparison groups to reflect accurate conclusions about existing evidence. Further research is needed about the full range of suicide-related outcomes for autistic people, including a greater understanding of sex differences as well as potential gender differences to include transgender and nonbinary autistic people. However, studies of sex and gender differences should not overshadow the compelling need for efforts to understand and address the elevated risk of suicidal thoughts, behaviors, and death among autistic people across sex and gender boundaries.

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6. Lebeda D, Fierenz A, Werfel L, Rosin-Arbesfeld R, Hofhuis J, Thoms S. Systematic and quantitative analysis of stop codon readthrough in Rett syndrome nonsense mutations. J Mol Med (Berl);2024 (Mar 2)

Rett syndrome (RTT) is a neurodevelopmental disorder resulting from genetic mutations in the methyl CpG binding protein 2 (MeCP2) gene. Specifically, around 35% of RTT patients harbor premature termination codons (PTCs) within the MeCP2 gene due to nonsense mutations. A promising therapeutic avenue for these individuals involves the use of aminoglycosides, which stimulate translational readthrough (TR) by causing stop codons to be interpreted as sense codons. However, the effectiveness of this treatment depends on several factors, including the type of stop codon and the surrounding nucleotides, collectively referred to as the stop codon context (SCC). Here, we develop a high-content reporter system to precisely measure TR efficiency at different SCCs, assess the recovery of the full-length MeCP2 protein, and evaluate its subcellular localization. We have conducted a comprehensive investigation into the intricate relationship between SCC characteristics and TR induction, examining a total of 14 pathogenic MeCP2 nonsense mutations with the aim to advance the prospects of personalized therapy for individuals with RTT. Our results demonstrate that TR induction can successfully restore full-length MeCP2 protein, albeit to varying degrees, contingent upon the SCC and the specific position of the PTC within the MeCP2 mRNA. TR induction can lead to the re-establishment of nuclear localization of MeCP2, indicating the potential restoration of protein functionality. In summary, our findings underscore the significance of SCC-specific approaches in the development of tailored therapies for RTT. By unraveling the relationship between SCC and TR therapy, we pave the way for personalized, individualized treatment strategies that hold promise for improving the lives of individuals affected by this debilitating neurodevelopmental disorder. KEY MESSAGES: The efficiency of readthrough induction at MeCP2 premature termination codons strongly depends on the stop codon context. The position of the premature termination codon on the transcript influences the readthrough inducibility. A new high-content dual reporter assay facilitates the measurement and prediction of readthrough efficiency of specific nucleotide stop contexts. Readthrough induction results in the recovery of full-length MeCP2 and its re-localization to the nucleus. MeCP2 requires only one of its annotated nuclear localization signals.

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7. Minissi ME, Altozano A, Marín-Morales J, Chicchi Giglioli IA, Mantovani F, Alcañiz M. Biosignal comparison for autism assessment using machine learning models and virtual reality. Comput Biol Med;2024 (Feb 24);171:108194.

Clinical assessment procedures encounter challenges in terms of objectivity because they rely on subjective data. Computational psychiatry proposes overcoming this limitation by introducing biosignal-based assessments able to detect clinical biomarkers, while virtual reality (VR) can offer ecological settings for measurement. Autism spectrum disorder (ASD) is a neurodevelopmental disorder where many biosignals have been tested to improve assessment procedures. However, in ASD research there is a lack of studies systematically comparing biosignals for the automatic classification of ASD when recorded simultaneously in ecological settings, and comparisons among previous studies are challenging due to methodological inconsistencies. In this study, we examined a VR screening tool consisting of four virtual scenes, and we compared machine learning models based on implicit (motor skills and eye movements) and explicit (behavioral responses) biosignals. Machine learning models were developed for each biosignal within the virtual scenes and then combined into a final model per biosignal. A linear support vector classifier with recursive feature elimination was used and tested using nested cross-validation. The final model based on motor skills exhibited the highest robustness in identifying ASD, achieving an AUC of 0.89 (SD = 0.08). The best behavioral model showed an AUC of 0.80, while further research is needed for the eye-movement models due to limitations with the eye-tracking glasses. These findings highlight the potential of motor skills in enhancing objectivity and reliability in the early assessment of ASD compared to other biosignals.

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8. Nakhaee S, Amirabadizadeh A, Farnia V, Azadi NA, Mansouri B, Radmehr F. Correction: Association between Biological Lead Concentrations and Autism Spectrum Disorder (ASD) in Children: A Systematic Review and Meta-Analysis. Biol Trace Elem Res;2024 (Mar 2)

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9. Radhoe TA, Agelink van Rentergem JA, Torenvliet C, Groenman AP, van der Putten WJ, Geurts HM. The clinical relevance of subgroups of autistic adults: Stability and predictive value. Autism Res;2024 (Mar 1)

Autism in adulthood is characterized by heterogeneity, complicating the provision of tailored support. In previous work, we aimed to capture this heterogeneity by determining subgroups of autistic adults that differed in clinical outcomes: cognitive failures, psychological difficulties, and quality of life (QoL). Two subgroups were identified: a « Feelings of Low Grip » subgroup characterized by experiencing a lower sense of mastery and a higher susceptibility to difficulties in daily life, and a « Feelings of High Grip » subgroup characterized by a higher sense of mastery and lower susceptibility to difficulties in daily life. The current pre-registered study involves a longitudinal extension to determine (a) stability and (b) predictive value of the previously identified two subgroups. Subgroups were identified using community detection based on 14 self-report measures related to demographic, psychological, and lifestyle characteristics in two samples (aged 31-86 years) that were analyzed separately: Sample 1 (N(Autism)  = 80) measured 5 years after baseline and Sample 2 (N(Autism)  = 241, N(Comparison)  = 211) measured 2 years after baseline. The stability over time was assessed based on (a) the number of subgroups, (b) subgroup profiles, and (c) subgroup membership. Predictive validity was assessed for cognitive failures, psychological difficulties, and QoL. Results indicated that autistic and non-autistic adults formed distinct subgroups. Within both autism samples, the two previously identified autism subgroups were replicated at follow-up. Subgroup profiles were similar for >50% of the variables at two-year follow-up, and 21% at five-year follow-up. Moreover, ≥76% remained in the same subgroup at two-year follow-up, and ≥ 57% after 5 years. Subgroup membership was predictive of external clinical outcomes up to 5 years. Thus, this study demonstrated the stability and predictive value of the autism subgroups, especially for the two-year follow-up. A further focus on their clinical utility might increase the aptness of support, and may provide more insight into the aging process when being autistic.

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10. Schiltz HK, Williams ZJ, Zheng S, Kaplan-Kahn EA, Morton HE, Rosenau KA, Nicolaidis C, Sturm A, Lord C. Measurement matters: A commentary on the state of the science on patient reported outcome measures (PROMs) in autism research. Autism Res;2024 (Mar 1)

High quality science relies upon psychometrically valid and reliable measurement, yet very few Patient Reported Outcome Measures (PROMs) have been developed or thoroughly validated for use with autistic individuals. The present commentary summarizes the current state of autism PROM science, based on discussion at the Special Interest Group (SIG) at the 2022 International Society for Autism Research (INSAR) Annual Meeting and collective expertise of the authors. First, we identify current issues in autism PROM research including content and construct operationalization, informant-structure, measure accessibility, and measure validation and generalization. We then enumerate barriers to conducting and disseminating this research, such as a lack of guidance, concerns regarding funding and time, lack of accessible training and professionals with psychometric skills, difficulties collecting large representative samples, and challenges with dissemination. Lastly, we offer future priorities and resources to improve PROMs in autism research including a need to continue to evaluate and develop PROMs for autistic people using robust methods, to prioritize diverse and representative samples, to expand the breadth of psychometric properties and techniques, and to consider developing field specific guidelines. We remain extremely optimistic about the future directions of this area of autism research. This work is well positioned to have an immense, positive impact on our scientific understanding of autism and the everyday lives of autistic people and their families.

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11. Schmitt I, Evert BO, Sharma A, Khazneh H, Murgatroyd C, Wüllner U. The Alpha-Synuclein Gene (SNCA) is a Genomic Target of Methyl-CpG Binding Protein 2 (MeCP2)-Implications for Parkinson’s Disease and Rett Syndrome. Mol Neurobiol;2024 (Mar 2)

Mounting evidence suggests a prominent role for alpha-synuclein (a-syn) in neuronal cell function. Alterations in the levels of cellular a-syn have been hypothesized to play a critical role in the development of Parkinson’s disease (PD); however, mechanisms that control expression of the gene for a-syn (SNCA) in cis and trans as well as turnover of a-syn are not well understood. We analyzed whether methyl-CpG binding protein 2 (MeCP2), a protein that specifically binds methylated DNA, thus regulating transcription, binds at predicted binding sites in intron 1 of the SNCA gene and regulates a-syn protein expression. Chromatin immunoprecipitation (ChIP) and electrophoretic mobility-shift assays (EMSA) were used to confirm binding of MeCP2 to regulatory regions of SNCA. Site-specific methylation and introduction of localized mutations by CRISPR/Cas9 were used to investigate the binding properties of MeCP2 in human SK-N-SH neuroblastoma cells. The significance of MeCP2 for SNCA regulation was further investigated by overexpressing MeCP2 and mutated variants of MeCP2 in MeCP2 knockout cells. We found that methylation-dependent binding of MeCP2 at a restricted region of intron 1 of SNCA had a significant impact on the production of a-syn. A single nucleotide substitution near to CpG1 strongly increased the binding of MeCP2 to intron 1 of SNCA and decreased a-syn protein expression by 60%. In contrast, deletion of a single nucleotide closed to CpG2 led to reduced binding of MeCP2 and significantly increased a-syn levels. In accordance, knockout of MeCP2 in SK-N-SH cells resulted in a significant increase in a-syn production, demonstrating that SNCA is a genomic target for MeCP2 regulation. In addition, the expression of two mutated MeCP2 variants found in Rett syndrome (RTT) showed a loss of their ability to reduce a-syn expression. This study demonstrates that methylation of CpGs and binding of MeCP2 to intron 1 of the SNCA gene plays an important role in the control of a-syn expression. In addition, the changes in SNCA regulation found by expression of MeCP2 variants carrying mutations found in RTT patients may be of importance for the elucidation of a new molecular pathway in RTT, a rare neurological disorder caused by mutations in MECP2.

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12. Shea L, Cooper D, Wilson AB, Hyatt J, Msipa D, Hofvander B, Øverland S, da Silva WC, Mogavero M, Green D, Wall N, Lerner M, Stahmer A, Hooven K, Bornman J, Robinson K, Burke J. A response to and caution of « Language is a critical mediator of autistic experiences within the criminal justice system ». Autism Res;2024 (Mar 1)

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13. Wang Y, Long H, Bo T, Zheng J. Residual graph transformer for autism spectrum disorder prediction. Comput Methods Programs Biomed;2024 (Feb 19);247:108065.

Brain functional connectivity (FC) based on resting-state functional magnetic resonance imaging (rs-fMRI) has been in vogue to predict Autism Spectrum Disorder (ASD), which is a neuropsychiatric disease up the plight of locating latent biomarkers for clinical diagnosis. Albeit massive endeavors have been made, most studies are fed up with several chronic issues, such as the intractability of harnessing the interaction flourishing within brain regions, the astriction of representation due to vanishing gradient within deeper network architecture, and the poor interpretability leading to unpersuasive diagnosis. To ameliorate these issues, a FC-learned Residual Graph Transformer Network, namely RGTNet, is proposed. Specifically, we design a Graph Encoder to extract temporal-related features with long-range dependencies, from which interpretable FC matrices would be modeled. Besides, the residual trick is introduced to deepen the GCN architecture, thereby learning the higher-level information. Moreover, a novel Graph Sparse Fitting followed by weighted aggregation is proposed to ease dimensionality explosion. Empirically, the results on two types of ABIDE data sets demonstrate the meliority of RGTNet. Notably, the achieved ACC metric reaches 73.4%, overwhelming most competitors with merely 70.9% on the AAL atlas using a five-fold cross-validation policy. Moreover, the investigated biomarkers concord closely with the authoritative medical knowledge, paving a viable way for ASD-clinical diagnosis. Our code is available at https://github.com/CodeGoat24/RGTNet.

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14. Yu ACL, McAllister R, Mularoni N, To CKS. Brief Report: Atypical Temporal Sensitivity in Coarticulation in Autism: Evidence from Sibilant-Vowel Interaction in Cantonese. J Autism Dev Disord;2024 (Mar 2)

PURPOSE: Atypicalities in the prosodic aspects of speech are commonly considered in clinical assessments of autism. While there is an increasing number of studies using objective measures to assess prosodic deficits, such studies have primarily focused on the intonational and rhythmic aspects of prosody. Little is known about prosodic deficits that are reflected at the segmental level, despite the strong connection between prosody and segmental realization. This study examines the nature of sibilant-vowel coarticulation among male adult native speakers of Cantonese with autism and those without. METHODS: Fifteen Cantonese-speaking autistic (ASD) adults (mean age = 25 years) and 23 neuro-typical (NT) adults (mean age = 20 years) participated. Each participant read aloud 42 syllables with a sibilant onset in carrier phrase. Spectral means and variance, skewness and kurtosis were measured, and regressed by vocalic rounding (rounded vs. unrounded), cohort (ASD vs. NT), sibilant duration, and articulation rate. RESULTS: While neurotypical participants exhibit sibilant-vowel coarticulation that are sensitive to variation in sibilant duration, autistic participants show no sensitivity to segmental temporal changes. CONCLUSION: These findings point to the potential for atypicalities in prosody-segment interaction as an important characteristic of autistic speech.

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