Sex/gender differences in neurology and psychiatry: Autism

Differently different?: A commentary on the emerging social cognitive neuroscience of female autism

Autism is a neurodevelopmental condition, behaviourally identified, which is generally characterised by social communication differences, and restrictive and repetitive patterns of behaviour and interests. It has long been claimed that it is more common in males. This observed preponderance of males in autistic populations has served as a focussing framework in all spheres of autism-related issues, from recognition and diagnosis through to theoretical models and research agendas. One related issue is the near total absence of females in key research areas. For example, this paper reports a review of over 120 brain-imaging studies of social brain processes in autism that reveals that nearly 70% only included male participants or minimal numbers (just one or two) of females. Authors of such studies very rarely report that their cohorts are virtually female-free and discuss their findings as though applicable to all autistic individuals. The absence of females can be linked to exclusionary consequences of autism diagnostic procedures, which have mainly been developed on male-only cohorts. There is clear evidence that disproportionately large numbers of females do not meet diagnostic criteria and are then excluded from ongoing autism research. Another issue is a long-standing assumption that the female autism phenotype is broadly equivalent to that of the male autism phenotype. Thus, models derived from male-based studies could be applicable to females. However, it is now emerging that certain patterns of social behaviour may be very different in females. This includes a specific type of social behaviour called camouflaging or masking, linked to attempts to disguise autistic characteristics. With respect to research in the field of sex/gender cognitive neuroscience, there is emerging evidence of female differences in patterns of connectivity and/or activation in the social brain that are at odds with those reported in previous, male-only studies. Decades of research have excluded or overlooked females on the autistic spectrum, resulting in the construction of inaccurate and misleading cognitive neuroscience models, and missed opportunities to explore the brain bases of this highly complex condition. A note of warning needs to be sounded about inferences drawn from past research, but if future research addresses this problem of male bias, then a deeper understanding of autism as a whole, as well as in previously overlooked females, will start to emerge.

Risk factors for developmental quotients in ASD children: A cross-sectional study

Objective

To analyze the risk factors for developmental quotients (DQs) of children with autism spectrum disorder (ASD) and to better understand the effects of screen time on neurodevelopment in children with ASD.

Methods

We retrospectively analyzed the data of 382 children with ASD, including demographic profiles; socioeconomic status; score on the Chinese parent–child interaction scale (CPCIS); screen time questionnaire; ASD symptom rating scales, including the Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Autism Diagnostic Observation Schedule Second Edition (ADOS-2); and DQs using Griffiths Development Scales–Chinese Edition. Univariate analysis was carried out to analyze the factors related to the DQs of children with ASD, and then the linear regression model was used to identify the independent influencing factors of the DQs of children with ASD.

Results

Vitamin D (β = 0.180, p = 0.002), age (β = −0.283, p = 0.000) and CARS score (β = −0.347, p = 0.000) are risk factors related to DQ of locomotor in children with ASD. Vitamin D (β = 0.108, p = 0.034), CARS score (β =  −0.503, p = 0.000), ADOS-2 severity score (β =  −0.109, p = 0.045) and CPCIS score (β = 0.198, p = 0.000) are risk factors related to DQ of personal social skill in children with ASD. Vitamin D (β = 0.130, p = 0.018), CARS score (β =  −0.469, p = 0.000), and CPCIS score (β = 0.133, p = 0.022) are risk factors related to DQ of hearing-speech in children with ASD. Vitamin D (β = 0.163, p = 0.003) and CARS score (β =  −0.471, p = 0.000) are risk factors related to DQ of eye-hand coordination in children with ASD. Age (β =  −0.140, p = 0.020), CARS score (β =  −0.342, p = 0.000), ADOS-2 severity score (β = −0.133, p = 0.034) and CPCIS score (β = 0.193, p = 0.002) are risk factors related to DQ of performance in children with ASD. Vitamin D (β = 0.801, p = 0.000) and CPCIS score (β = 0.394, p = 0.019) are risk factors related to DQ of practical reasoning in children with ASD.

Conclusion

Vitamin D status, the severity of autistic symptoms and parent-child interaction are risk factors for developmental quotients in children with ASD. Screen exposure time is negatively associated with DQs in children with ASD but is not an independent risk factor for DQs.

Recent Developments in Autism Genetic Research: A Scientometric Review from 2018 to 2022

Genetic research in Autism Spectrum Disorder (ASD) has progressed tremendously in recent decades. Dozens of genetic loci and hundreds of alterations in the genetic sequence, expression, epigenetic transformation, and interactions with other physiological and environmental systems have been found to increase the likelihood of developing ASD. There is therefore a need to represent this wide-ranging yet voluminous body of literature in a systematic manner so that this information can be synthesised and understood at a macro level. Therefore, this study made use of scientometric methods, particularly document co-citation analysis (DCA), to systematically review literature on ASD genetic research from 2018 to 2022. A total of 14,818 articles were extracted from Scopus and analyzed with CiteSpace. An optimized DCA analysis revealed that recent literature on ASD genetic research can be broadly organised into 12 major clusters representing various sub-topics. These clusters are briefly described in the manuscript and potential applications of this study are discussed.

Women seeking an autism diagnosis in Australia: A qualitative exploration of factors that help and hinder

LAY ABSTRACT

An autism diagnosis can have a big impact on women and make it possible to access support. This study explored women's experiences of being diagnosed with autism as an adult in Australia, to try to understand what was helpful (facilitators) and unhelpful (barriers) for them during this process. We interviewed 10 autistic women who had been diagnosed in the last 5 years. Framework analysis was used to understand the data. We wanted to understand barriers and facilitators relating to the individual participants, the professionals they saw and the system they went through for their diagnostic assessment. Women reported that being able to recognise they were autistic, being motivated, preparing for the assessment, having social support and unmasking to be themselves were helpful during the diagnostic process. They reported that having a knowledgeable diagnostician who made accommodations for their needs assisted them during the assessment process. When providers dismissed the participants when they first raised the possibility they were autistic, it delayed them in seeking an assessment. At the system level, the women in this study found some aspects of the healthcare system difficult to navigate, particularly costs and long waitlists. Some found the assessment tools used were not well suited to them. The experiences of the women in this study highlight improvements that could be made to accessing an adulthood autism diagnosis in Australia. These include improving provider knowledge of the varied presentation of autism and the development of resources to help autistic women prepare for their diagnostic assessment.

Deep learning identifies robust gender differences in functional brain organization and their dissociable links to clinical symptoms in autism

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous disorder that affects nearly 1 in 189 females and 1 in 42 males. However, the neurobiological basis of gender differences in ASD is poorly understood, as most studies have neglected females and used methods ill-suited to capture such differences.

AIMS

To identify robust functional brain organisation markers that distinguish between females and males with ASD and predict symptom severity.

METHOD

We leveraged multiple neuroimaging cohorts (ASD n = 773) and developed a novel spatiotemporal deep neural network (stDNN), which uses spatiotemporal convolution on functional magnetic resonance imaging data to distinguish between groups.

RESULTS

stDNN achieved consistently high classification accuracy in distinguishing between females and males with ASD. Notably, stDNN trained to distinguish between females and males with ASD could not distinguish between neurotypical females and males, suggesting that there are gender differences in the functional brain organisation in ASD that differ from normative gender differences. Brain features associated with motor, language and visuospatial attentional systems reliably distinguished between females and males with ASD. Crucially, these results were observed in a large multisite cohort and replicated in a fully independent cohort. Furthermore, brain features associated with the motor network's primary motor cortex node predicted the severity of restricted/repetitive behaviours in females but not in males with ASD.

CONCLUSIONS

Our replicable findings reveal that the brains of females and males with ASD are functionally organised differently, contributing to their clinical symptoms in distinct ways. They inform the development of gender-specific diagnoses and treatment strategies for ASD, and ultimately advance precision psychiatry.

Autism spectrum disorder and air pollution: A systematic review and meta-analysis

Despite the widely-known effects of air pollution, pollutants exposure surrounding pregnancy and the risk for autism spectrum disorder (ASD) in newborns remains controversial. The purpose of our study was to carry out a systematic review and meta-analyses of the risk of ASD in newborns following air pollution exposure during the perinatal period (preconception to second year of life). The PubMed, Cochrane Library, Embase and ScienceDirect databases were searched for articles, published up to July 2020, with the keywords "air pollution" and "autism". Three models were used for each meta-analysis: a global model based on all risks listed in included articles, a pessimistic model based on less favorable data only, and an optimistic model based on the most favorable data only. 28 studies corresponding to a total of 758 997 newborns were included (47190 ASD and 703980 controls). Maternal exposure to all pollutants was associated with an increased risk of ASD in newborns by 3.9% using the global model and by 12.3% using the optimistic model, while the pessimistic model found no change. Each increase of 5 μg/m³ in particulate matter <2.5 μm (PM2.5) was associated with an increased risk of ASD in newborns, regardless of the model used (global +7%, pessimistic +5%, optimistic +15%). This risk increased during preconception (global +17%), during pregnancy (global +5%, and optimistic +16%), and during the postnatal period (global +11% and optimistic +16%). Evidence levels were poor for other pollutants (PM10, NOx, O3, metals, solvents, styrene, PAHs, pesticides). PM2.5 was associated with a greater risk than PM10 (coefficient 0.20, 95CI -0.02 to 0.42), NOx (0.29, 0.08 to 0.50) or solvents (0.24, 0.04 to 0.44). All models revealed that exposure to pollutants, notably PM2.5 during pregnancy, was associated with an increased risk of ASD in newborns. Pregnancy and postnatal periods seem to be the most at-risk periods.