Amber N. V. Ruigrok

A meta-analysis of sex differences in human brain structure

Highlights • This is the first meta-analysis of sex differences in the typical human brain.• Regional sex differences overlap with areas implicated in psychiatric conditions.• The amygdala, hippocampus, planum temporale and insula display sex differences.• On average, males have larger brain volumes than females.• Most articles providing sex differences in volume are in the ‘mature’ category.

A Behavioral Comparison of Male and Female Adults with High Functioning Autism Spectrum Conditions

Autism spectrum conditions (ASC) affect more males than females in the general population. However, within ASC it is unclear if there are phenotypic sex differences. Testing for similarities and differences between the sexes is important not only for clinical assessment but also has implications for theories of typical sex differences and of autism. Using cognitive and behavioral measures, we investigated similarities and differences between the sexes in age- and IQ-matched adults with ASC (high-functioning autism or Asperger syndrome). Of the 83 (45 males and 38 females) participants, 62 (33 males and 29 females) met Autism Diagnostic Interview-Revised (ADI-R) cut-off criteria for autism in childhood and were included in all subsequent analyses. The severity of childhood core autism symptoms did not differ between the sexes. Males and females also did not differ in self-reported empathy, systemizing, anxiety, depression, and obsessive-compulsive traits/symptoms or mentalizing performance. However, adult females with ASC showed more lifetime sensory symptoms (p = 0.036), fewer current socio-communication difficulties (p = 0.001), and more self-reported autistic traits (p = 0.012) than males. In addition, females with ASC who also had developmental language delay had lower current performance IQ than those without developmental language delay (p<0.001), a pattern not seen in males. The absence of typical sex differences in empathizing-systemizing profiles within the autism spectrum confirms a prediction from the extreme male brain theory. Behavioral sex differences within ASC may also reflect different developmental mechanisms between males and females with ASC. We discuss the importance of the superficially better socio-communication ability in adult females with ASC in terms of why females with ASC may more often go under-recognized, and receive their diagnosis later, than males.

Biological sex affects the neurobiology of autism

In autism, heterogeneity is the rule rather than the exception. One obvious source of heterogeneity is biological sex. Since autism was first recognized, males with autism have disproportionately skewed research. Females with autism have thus been relatively overlooked, and have generally been assumed to have the same underlying neurobiology as males with autism. Growing evidence, however, suggests that this is an oversimplification that risks obscuring the biological base of autism. This study seeks to answer two questions about how autism is modulated by biological sex at the level of the brain: (i) is the neuroanatomy of autism different in males and females? and (ii) does the neuroanatomy of autism fit predictions from the ‘extreme male brain’ theory of autism, in males and/or in females? Neuroanatomical features derived from voxel-based morphometry were compared in a sample of equal-sized high-functioning male and female adults with and without autism (n = 120, n = 30/group). The first question was investigated using a 2 × 2 factorial design, and by spatial overlap analyses of the neuroanatomy of autism in males and females. The second question was tested through spatial overlap analyses of specific patterns predicted by the extreme male brain theory. We found that the neuroanatomy of autism differed between adult males and females, evidenced by minimal spatial overlap (not different from that occurred under random condition) in both grey and white matter, and substantially large white matter regions showing significant sex × diagnosis interactions in the 2 × 2 factorial design. These suggest that autism manifests differently by biological sex. Furthermore, atypical brain areas in females with autism substantially and non-randomly (P < 0.001) overlapped with areas that were sexually dimorphic in neurotypical controls, in both grey and white matter, suggesting neural ‘masculinization’. This was not seen in males with autism. How differences in neuroanatomy relate to the similarities in cognition between males and females with autism remains to be understood. Future research should stratify by biological sex to reduce heterogeneity and to provide greater insight into the neurobiology of autism.

Cognition in males and females with autism: similarities and differences.

The male bias in autism spectrum conditions (ASC) has led to females with ASC being under-researched. This lack of attention to females could hide variability due to sex that may explain some of the heterogeneity within ASC. In this study we investigate four key cognitive domains (mentalizing and emotion perception, executive function, perceptual attention to detail, and motor function) in ASC, to test for similarities and differences between males and females with and without ASC (n = 128 adults; n = 32 per group). In the mentalizing and facial emotion perception domain, males and females with ASC showed similar deficits compared to neurotypical controls. However, in attention to detail and dexterity involving executive function, although males with ASC showed poorer performance relative to neurotypical males, females with ASC performed comparably to neurotypical females. We conclude that performance in the social-cognitive domain is equally impaired in male and female adults with ASC. However, in specific non-social cognitive domains, performance within ASC depends on sex. This suggests that in specific domains, cognitive profiles in ASC are modulated by sex.

Quantifying and exploring camouflaging in men and women with autism

Autobiographical descriptions and clinician observations suggest that some individuals with autism, particularly females, ‘camouflage’ their social communication difficulties, which may require considerable cognitive effort and lead to increased stress, anxiety and depression. Using data from 60 age- and IQ-matched men and women with autism (without intellectual disability), we operationalized camouflaging in adults with autism for the first time as the quantitative discrepancy between the person’s ‘external’ behavioural presentation in social–interpersonal contexts (measured by the Autism Diagnostic Observation Schedule) and the person’s ‘internal’ status (dispositional traits measured by the Autism Spectrum Quotient and social cognitive capability measured by the ‘Reading the Mind in the Eyes’ Test). We found that the operationalized camouflaging measure was not significantly correlated with age or IQ. On average, women with autism had higher camouflaging scores than men with autism (Cohen’s d = 0.98), with substantial variability in both groups. Greater camouflaging was associated with more depressive symptoms in men and better signal-detection sensitivity in women with autism. The neuroanatomical association with camouflaging score was largely sex/gender-dependent and significant only in women: from reverse inference, the most correlated cognitive terms were about emotion and memory. The underlying constructs, measurement, mechanisms, consequences and heterogeneity of camouflaging in autism warrant further investigation.

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Functional magnetic resonance imaging (fMRI) research is routinely criticized for being statistically underpowered due to characteristically small sample sizes and much larger sample sizes are being increasingly recommended. Additionally, various sources of artifact inherent in fMRI data can have detrimental impact on effect size estimates and statistical power. Here we show how specific removal of non-BOLD artifacts can improve effect size estimation and statistical power in task-fMRI contexts, with particular application to the social-cognitive domain of mentalizing/theory of mind. Non-BOLD variability identification and removal is achieved in a biophysical and statistically principled manner by combining multi-echo fMRI acquisition and independent components analysis (ME-ICA). Without smoothing, group-level effect size estimates on two different mentalizing tasks were enhanced by ME-ICA at a median rate of 24% in regions canonically associated with mentalizing, while much more substantial boosts (40–149%) were observed in non-canonical cerebellar areas. Effect size boosting occurs via reduction of non-BOLD noise at the subject-level and consequent reductions in between-subject variance at the group-level. Smoothing can attenuate ME-ICA-related effect size improvements in certain circumstances. Power simulations demonstrate that ME-ICA-related effect size enhancements enable much higher-powered studies at traditional sample sizes. Cerebellar effects observed after applying ME-ICA may be unobservable with conventional imaging at traditional sample sizes. Thus, ME-ICA allows for principled design-agnostic non-BOLD artifact removal that can substantially improve effect size estimates and statistical power in task-fMRI contexts. ME-ICA could mitigate some issues regarding statistical power in fMRI studies and enable novel discovery of aspects of brain organization that are currently under-appreciated and not well understood.

The EU-AIMS Longitudinal European Autism Project (LEAP): Design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders

BackgroundThe tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD.MethodsLEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability.ResultsHere, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some ‘lessons learnt’. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted).ConclusionWe expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.

Imaging sex/gender and autism in the brain: Etiological implications.

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.

Association Between the Probability of Autism Spectrum Disorder and Normative Sex-Related Phenotypic Diversity in Brain Structure

Importance Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive. Objectives To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD. Design, Setting, and Participants This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016. Main Outcomes and Measures Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals. Results Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; &khgr;21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals). Conclusions and Relevance These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual’s risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.

In Vivo Evidence of Reduced Integrity of the Gray–White Matter Boundary in Autism Spectrum Disorder

Abstract Atypical cortical organization and reduced integrity of the gray‐white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray‐white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray‐white matter interface, which indicates a less distinct gray‐white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well‐defined gray‐white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies.