1. Bartholomay KL, Jordan TL, Foland-Ross LC, Kendall N, Lightbody AA, Reiss AL. Alterations in cortical and subcortical neuroanatomy and associations with behavior in females with fragile X syndrome. Dev Med Child Neurol;2024 (Sep 15)

AIM: To address substantial gaps in the literature on neuroanatomical variations in females with fragile X syndrome (FXS). METHOD: Surface-based modeling techniques were applied to the magnetic resonance imaging of 45 females with FXS (mean age = 10 years 9 months, range 6 years-16 years 4 months, SD = 2 years 9 months) and 33 age-matched and developmentally matched females without FXS to elucidate differences in cortical gray matter volume, surface area, and thickness. Gray matter volumes in subcortical regions were examined to ascertain differences in subcortical volume. RESULTS: In females with FXS, cortical volume was greater bilaterally in the occipital pole and smaller in the right postcentral gyrus. Seven regions demonstrated lower surface area in participants with FXS, while cortical thickness was significantly greater over the posterior and medial surfaces in the group with FXS. Subcortical region of interest analyses demonstrated greater volume in the caudate nucleus, globus pallidus, and nucleus accumbens in the group with FXS. Global gray matter volume, pial thickness, and surface area were associated with behavioral outcomes in the group with FXS but not in the comparison group. INTERPRETATION: Females with FXS demonstrated unique cortical and subcortical gray matter anatomy relative to a matched comparison group. These findings may be relevant to the pathogenesis of the FXS behavioral phenotype and provide insights into behavioral interventions targeted to this population.

Lien vers le texte intégral (Open Access ou abonnement)

2. Brogna C, Moro M, Pane M. Management of anesthesia in children with autism spectrum disorders. Minerva Anestesiol;2024 (Sep);90(9):719-721.

Lien vers le texte intégral (Open Access ou abonnement)

3. Cusano J, Graham Holmes L, Caplan R, Rothman EF. Prevalence and Correlates of Dating Violence Victimization Among a U.S.-Based Sample of Autistic Youth. J Interpers Violence;2024 (Sep 15):8862605241275997.

Dating violence victimization is a pervasive public health problem that affects individuals of all age groups, but it holds particular significance during adolescence due to the potential long-term consequences on an individual’s physical and psychological well-being, and potential influence on the health of adult relationships. Although there is now ample research on the topic of adolescent dating violence prevalence, risk factors, and consequences, to our knowledge, only four studies have assessed dating violence victimization among autistic youth. The current study was designed to investigate the prevalence of, and risk markers for, dating violence victimization among autistic youth. Specifically, the study had two aims: (a) to estimate the prevalence of dating violence victimization among autistic youth in a U.S.-based sample and (b) to identify correlates of dating violence for autistic youth, which include sociodemographic, mental health, and alcohol-related variables. We found that among participants who were in a romantic relationship in the past year, autistic participants were not any less likely to experience dating violence victimization compared to their non-autistic counterparts (40.7% for autistic youth vs. 38.0% for non-autistic youth). In addition, findings from the current study demonstrate the significant relationships between dating violence victimization and consequences of alcohol use, loneliness, and anxiety among autistic youth. Existing studies, in addition to the results of the current study, suggest the need for tailored dating violence prevention, support, and intervention to support the overall well-being of autistic youth.

Lien vers le texte intégral (Open Access ou abonnement)

4. Dias C. Characterizing the female brain in fragile X syndrome. Dev Med Child Neurol;2024 (Sep 15)

Lien vers le texte intégral (Open Access ou abonnement)

5. Kameya M, Hirosawa T, Soma D, Yoshimura Y, An KM, Iwasaki S, Tanaka S, Yaoi K, Sano M, Miyagishi Y, Kikuchi M. Relationships between peak alpha frequency, age, and autistic traits in young children with and without autism spectrum disorder. Front Psychiatry;2024;15:1419815.

BACKGROUND: Atypical peak alpha frequency (PAF) has been reported in children with autism spectrum disorder (ASD); however, the relationships between PAF, age, and autistic traits remain unclear. This study was conducted to investigate and compare the resting-state PAF of young children with ASD and their typically developing (TD) peers using magnetoencephalography (MEG). METHODS: Nineteen children with ASD and 24 TD children, aged 5-7 years, underwent MEG under resting-state conditions. The PAFs in ten brain regions were calculated, and the associations between these findings, age, and autistic traits, measured using the Social Responsiveness Scale (SRS), were examined. RESULTS: There were no significant differences in PAF between the children with ASD and the TD children. However, a unique positive association between age and PAF in the cingulate region was observed in the ASD group, suggesting the potential importance of the cingulate regions as a neurophysiological mechanism underlying distinct developmental trajectory of ASD. Furthermore, a higher PAF in the right temporal region was associated with higher SRS scores in TD children, highlighting the potential role of alpha oscillations in social information processing. CONCLUSIONS: This study emphasizes the importance of regional specificity and developmental factors when investigating neurophysiological markers of ASD. The distinct age-related PAF patterns in the cingulate regions of children with ASD and the association between right temporal PAF and autistic traits in TD children provide novel insights into the neurobiological underpinnings of ASD. These findings pave the way for future research on the functional implications of these neurophysiological patterns and their potential as biomarkers of ASD across the lifespan.

Lien vers le texte intégral (Open Access ou abonnement)

6. Katirai A. Autism and emotion recognition technologies in the workplace. Autism;2024 (Sep 16):13623613241279704.

Technologies using artificial intelligence to recognize people’s emotional states are increasingly being developed under the name of emotional recognition technologies. Emotion recognition technologies claim to identify people’s emotional states based on data, like facial expressions. This is despite research providing counterevidence that emotion recognition technologies are founded on bad science and that it is not possible to correctly identify people’s emotions in this way. The use of emotion recognition technologies is widespread, and they can be harmful when they are used in the workplace, especially for autistic workers. Although previous research has shown that the origins of emotion recognition technologies relied on autistic people, there has been little research on the impact of emotion recognition technologies on autistic people when it is used in the workplace. Through a review of recent academic studies, this article looks at the development and implementation processes of emotion recognition technologies to show how autistic people in particular may be disadvantaged or harmed by the development and use of the technologies. This article closes with a call for more research on autistic people’s perception of the technologies and their impact, with involvement from diverse participants.

Lien vers le texte intégral (Open Access ou abonnement)

7. Linke AC, Chen B, Olson L, Cordova M, Wilkinson M, Wang T, Herrera M, Salmina M, Rios A, Mahmalji J, Do T, Vu J, Budman M, Walker A, Fishman I. Altered development of the Hurst Exponent in medial prefrontal cortex in preschoolers with autism. Biol Psychiatry Cogn Neurosci Neuroimaging;2024 (Sep 16)

BACKGROUND: Atypical balance of excitation (E) and inhibition (I) in the brain is thought to contribute to the emergence and symptomatology of autism spectrum disorders (ASD). E/I ratio can be estimated from resting state functional magnetic resonance imaging (fMRI) using the Hurst Exponent (H). A recent study reported decreased ventromedial prefrontal cortex (vmPFC) H in male adults with ASD. Part of the default mode network (DMN), vmPFC plays an important role in emotion regulation, decision making, and social cognition. It frequently shows altered function and connectivity in autistic individuals. METHODS: The current study presents the first fMRI evidence of altered early development of vmPFC H and its link to DMN functional connectivity (FC) and emotional control in toddlers and preschoolers with ASD. 83 children (n=45 ASD), ages 1½ – 5 years, underwent natural sleep fMRI as part of a longitudinal study. RESULTS: In a cross-sectional analysis, vmPFC H decreased with age in children with ASD, reflecting increasing E/I ratio, but not in typically developing children. This effect remained significant when controlling for gestational age at birth, socioeconomic status, or ethnicity. The same pattern was also observed in a subset of children with longitudinal fMRI data acquired two years apart on average. Lower vmPFC H was further associated with reduced FC within the DMN as well as with higher emotional control deficits (though only significant transdiagnostically). CONCLUSIONS: These results suggest an early onset of E/I imbalances in vmPFC in ASD with likely consequences for the maturation of the DMN.

Lien vers le texte intégral (Open Access ou abonnement)

8. Love C, Sominsky L, O’Hely M, Berk M, Vuillermin P, Dawson SL. Prenatal environmental risk factors for autism spectrum disorder and their potential mechanisms. BMC Med;2024 (Sep 16);22(1):393.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is globally increasing in prevalence. The rise of ASD can be partially attributed to diagnostic expansion and advocacy efforts; however, the interplay between genetic predisposition and modern environmental exposures is likely driving a true increase in incidence. A range of evidence indicates that prenatal exposures are critical. Infection during pregnancy, gestational diabetes, and maternal obesity are established risk factors for ASD. Emerging areas of research include the effects of maternal use of selective serotonin reuptake inhibitors, antibiotics, and exposure to toxicants during pregnancy on brain development and subsequent ASD. The underlying pathways of these risk factors remain uncertain, with varying levels of evidence implicating immune dysregulation, mitochondrial dysfunction, oxidative stress, gut microbiome alterations, and hormonal disruptions. This narrative review assesses the evidence of contributing prenatal environmental factors for ASD and associated mechanisms as potential targets for novel prevention strategies.

Lien vers le texte intégral (Open Access ou abonnement)

9. Murphy D, Walker F, Broyd J. Do autism and psychopathy co-occur? A systematic review and clinical discussion. Crim Behav Ment Health;2024 (Sep 16)

BACKGROUND: Although the prevalence is unknown, psychopathy can be a possible co-occurring condition associated with autism especially among forensic populations. However, the relationship between these two conditions remains poorly understood. AIMS: To carry out a systematic review of the available literature exploring the relationship between autism and psychopathy. METHODS: A systematic literature review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using terms for autism and psychopathy to search the literature databases Scopus, Pubmed, Web of Science, ASSIA, APA Psych Info, Medline and EMBASE from 1980 to March 2024. For inclusion, we required that a recognised measure of autism and psychopathy or associated features of the latter had been used. RESULTS: Of the 4230 potential articles identified, 37 met the selection criteria. Insufficient and inconsistent methodologies for data pooling meant that a narrative analysis was used. Although there is some overlap, four broad themes emerged relating to (1) assessment and frequency of co-occurrence, (2) behavioural and neurophysiological expressions of empathy, (3) behavioural contagion effects, mirroring, mimicry and other linking mechanisms and (4) emotional face perception and theory of mind characteristics. Within these areas there are some specific differences between the two conditions. However, the research to date examining the relationship between autism and psychopathy has mostly been with children and males, carried out with non-clinical non-forensic populations, as well as using self-report measures and parental ratings. Prior research has also largely focused on looking for differences between these conditions rather than co-occurrence. CONCLUSION: This review outlines a case for considering autism and psychopathy as distinct, but potentially co-occurring conditions and highlights the need for more research into how the two conditions interact with clinical populations. There also appears to be a need for guidelines on when and how to assess psychopathy with autistic individuals and a better understanding of the therapeutic needs and factors influencing the long-term outcomes of autistic individuals who may also present with co-occurring psychopathy.

Lien vers le texte intégral (Open Access ou abonnement)

10. Schendel D, Ejlskov L, Overgaard M, Jinwala Z, Kim V, Parner E, Kalkbrenner AE, Ladd Acosta C, Fallin MD, Xie S, Mortensen PB, Lee BK. 3-generation family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions associated with autism: An open-source catalog of findings. Autism Res;2024 (Sep 16)

The relatively few conditions and family member types (e.g., sibling, parent) considered in investigations of family health history in autism spectrum disorder (ASD, or autism) limits understanding of the role of family history in autism etiology. For more comprehensive understanding and hypothesis-generation, we produced an open-source catalog of autism associations with family histories of mental, neurologic, cardiometabolic, birth defect, asthma, allergy, and autoimmune conditions. All live births in Denmark, 1980-2012, of Denmark-born parents (1,697,231 births), and their 3-generation family members were followed through April 10, 2017 for each of 90 diagnoses (including autism), emigration or death. Adjusted hazard ratios (aHR) were estimated via Cox regression for each diagnosis-family member type combination, adjusting for birth year, sex, birth weight, gestational age, parental ages at birth, and number of family member types of index person; aHRs also calculated for sex-specific co-occurrence of each disorder. We obtained 6462 individual family history aHRS across autism overall (26,840 autistic persons; 1.6% of births), by sex, and considering intellectual disability (ID); and 350 individual co-occurrence aHRS. Results are cataloged in interactive heat maps and down-loadable data files: https://ncrr-au.shinyapps.io/asd-riskatlas/ and interactive graphic summaries: https://public.tableau.com/app/profile/diana.schendel/viz/ASDPlots_16918786403110/e-Figure5. While primarily for reference material or use in other studies (e.g., meta-analyses), results revealed considerable breadth and variation in magnitude of familial health history associations with autism by type of condition, family member type, sex of the family member, side of the family, sex of the index person, and ID status, indicative of diverse genetic, familial, and nongenetic autism etiologic pathways. Careful attention to sources of autism likelihood in family health history, aided by our open data resource, may accelerate understanding of factors underlying neurodiversity.

Lien vers le texte intégral (Open Access ou abonnement)

11. Shiota Y, Nishiyama T, Yokoyama S, Yoshimura Y, Hasegawa C, Tanaka S, Iwasaki S, Kikuchi M. Association of genetic variants with autism spectrum disorder in Japanese children revealed by targeted sequencing. Front Genet;2024;15:1352480.

INTRODUCTION: Autism spectrum disorders (ASD) represent a heterogeneous group of neurodevelopmental disorders with strong genetic predispositions. Although an increasing number of genetic variants have been implicated in the pathogenesis of ASD, little is known about the relationship between ASD-associated genetic variants and individual ASD traits. Therefore, we aimed to investigate these relationships. METHODS: Here, we report a case-control association study of 32 Japanese children with ASD (mainly with high-functioning autism [HFA]) and 36 with typical development (TD). We explored previously established ASD-associated genes using a next-generation sequencing panel and determined the association between Social Responsiveness Scale (SRS) T-scores and intelligence quotient (IQ) scores. RESULTS: In the genotype-phenotype analyses, 40 variants of five genes (SCN1A, SHANK3, DYRK1A, CADPS, and SCN2A) were associated with ASD/TD phenotypes. In particular, 10 SCN1A variants passed permutation filtering (false discovery rate <0.05). In the quantitative association analyses, 49 variants of 12 genes (CHD8, SCN1A, SLC6A1, KMT5B, CNTNAP2, KCNQ3, SCN2A, ARID1B, SHANK3, DYRK1A, FOXP1, and GRIN2B) and 50 variants of 10 genes (DYRK1A, SCN2A, SLC6A1, ARID1B, CNTNAP2, SHANK3, FOXP1, PTEN, SCN1A, and CHD8) were associated with SRS T- and IQ-scores, respectively. CONCLUSION: Our data suggest that these identified variants are essential for the genetic architecture of HFA.

Lien vers le texte intégral (Open Access ou abonnement)

12. Tonizzi I, Usai MC. Cognitive correlates of math abilities in autism spectrum disorder. PLoS One;2024;19(9):e0310525.

The purpose of the current study was to investigate the contribution of different cognitive processes to specific math abilities in students with autism spectrum disorder (ASD) and typically developing (TD) students. The study involved a group of students with ASD without intellectual disabilities (n = 26) and a group with TD students (n = 52). The two groups aged from six to 20 years old and were matched for age, sex ratio and visuospatial reasoning. To assess math abilities, four math tasks were administered: arithmetic facts, mental calculation, mathematical inferences and math problem solving. Concerning cognitive processes, participants were tested on vocabulary, verbal working memory, visuospatial working memory, response inhibition and interference control. The group with ASD showed lower scores on all specific math measures than the TD group; cognitive processes differently contributed to diverse math abilities, and vocabulary and verbal working memory were stronger associated to specific math abilities in the group with ASD than in the TD group. The current results suggest that students with ASD had lower math abilities that are generalized to different math tasks. Implications for research and clinical assessment and intervention were discussed.

Lien vers le texte intégral (Open Access ou abonnement)

13. Xia JN, Wang YM, Li M, Chen LP. Fragile X-associated tremor/ataxia syndrome: A case report. Asian J Surg;2024 (Sep 14)

Lien vers le texte intégral (Open Access ou abonnement)

14. Xu X, Li Y, Ding N, Zang Y, Sun S, Shen G, Song X. Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods. Psychiatry Res Neuroimaging;2024 (Sep 16);345:111901.

RATIONALE AND OBJECTIVES: To explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features. METHODS: A total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients. RESULTS: Compared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively. CONCLUSION: Automatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.

Lien vers le texte intégral (Open Access ou abonnement)