Altered structural brain asymmetry in autism spectrum disorder (ASD) has been reported. However, findings have been inconsistent, likely due to limited sample sizes. Here we investigated 1,774 individuals with ASD and 1,809 controls, from 54 independent data sets of the ENIGMA consortium. ASD was significantly associated with alterations of cortical thickness asymmetry in mostly medial frontal, orbitofrontal, cingulate and inferior temporal areas, and also with asymmetry of orbitofrontal surface area. These differences generally involved reduced asymmetry in individuals with ASD compared to controls. Furthermore, putamen volume asymmetry was significantly increased in ASD. The largest case-control effect size was Cohen’sd = −0.13, for asymmetry of superior frontal cortical thickness. Most effects did not depend on age, sex, IQ, severity or medication use. Altered lateralized neurodevelopment may therefore be a feature of ASD, affecting widespread brain regions with diverse functions. Large-scale analysis was necessary to quantify subtle alterations of brain structural asymmetry in ASD.

The male preponderance in autism prevalence has brought together the disparate topics of sex/gender and autism research. Two directions of neuroimaging studies on the relationships between sex/gender and autism may inform male‐specific risk mechanisms and female‐specific protective mechanisms of autism. First, we review how sex/gender moderates autism‐related brain changes and how this informs general models of autism etiology. Better‐powered human neuroimaging studies suggest that the brain characteristics of autism are qualitatively, rather than simply quantitatively, different between males and females. However, age and comorbidities might substantially moderate the pattern of differences. Second, we review how the relationship between autism‐related brain changes (separately in males and females) and normative brain sex/gender differences informs specific etiological–developmental mechanisms. Both human and animal studies converge to indicate that the brain characteristics of autism are partly associated with normative brain sex/gender differences, suggesting convergence or overlap between the mechanisms leading to and modifying the development of autism and the mechanisms underlying sex differentiation and/or gender socialization. Future animal work needs to investigate sex differences in rodent mutants modeling autism‐relevant genes and environmental exposures. Future human work needs to address the substantial phenotypic and etiological heterogeneity of autism and to focus on longitudinal neuroimaging studies (from early development) on the developmental trajectories of sex/gender‐differential neural characteristics of autism. Combining animal and human work links up the causal chain from etiological factors, brain and physical development, to phenotypes. These together help delineate the different roles of sex and gender in relation to risk vs. protective mechanisms.

Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach. A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics. Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion. There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

Atypical lateralization of language-related functions has been repeatedly found in individuals with autism spectrum conditions (ASC). Few studies have, however, investigated deviations from typically occurring asymmetry of other lateralized cognitive and behavioural domains. Motor deficits are among the earliest and most prominent symptoms in individuals with ASC and precede core social and communicative symptoms. Here, we investigate whether motor circuit connectivity is (1) atypically lateralized in children with ASC and (2) whether this relates to core autistic symptoms and motor performance. Participants comprised 44 right-handed high-functioning children with autism (36 males, 8 females) and 80 typically developing control children (58 males, 22 females) matched on age, sex and performance IQ. We examined lateralization of functional motor circuit connectivity based on homotopic seeds derived from peak activations during a finger tapping paradigm. Motor performance was assessed using the Physical and Neurological Examination for Subtle Signs (PANESS). Children with ASC showed rightward lateralization in mean motor circuit connectivity compared to typically developing children, and this was associated with poorer performance on all three PANESS measures. Our findings reveal that atypical lateralization in ASC is not restricted to language functions but is also present in circuits subserving motor functions and may underlie motor deficits in children with ASC. Future studies should investigate whether this is an age-invariant finding extending to adolescents and adults and whether these asymmetries relate to atypical lateralization in the language domain.

Pattern classification and stratification approaches have increasingly been used in research on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation towards clinical applicability. Here, we present an extensive scoping literature review on those two approaches. We screened a total of 635 studies, of which 57 pattern classification and 19 stratification studies were included. We observed large variance across pattern classification studies in terms of predictive performance from about 60% to 98% accuracy, which is among other factors likely linked to sampling bias, different validation procedures across studies, the heterogeneity of ASD and differences in data quality. Stratification studies were less prevalent with only two studies reporting replications and just a few showing external validation. While some identified strata based on cognition and intelligence reappear across studies, biology as a stratification marker is clearly underexplored. In summary, mapping biological differences at the level of the individual with ASD is a major challenge for the field now. Conceptualizing those mappings and individual trajectories that lead to the diagnosis of ASD, will become a major challenge in the near future.