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

Age-atypical brain functional networks in autism spectrum disorder: a normative modeling approach

BACKGROUND

Despite extensive research into the neural basis of autism spectrum disorder (ASD), the presence of substantial biological and clinical heterogeneity among diagnosed individuals remains a major barrier. Commonly used case‒control designs assume homogeneity among subjects, which limits their ability to identify biological heterogeneity, while normative modeling pinpoints deviations from typical functional network development at individual level.

METHODS

Using a world-wide multi-site database known as Autism Brain Imaging Data Exchange, we analyzed individuals with ASD and typically developed (TD) controls (total n = 1218) aged 5-40 years, generating individualized whole-brain network functional connectivity (FC) maps of age-related atypicality in ASD. We then used local polynomial regression to estimate a networkwise normative model of development and explored correlations between ASD symptoms and brain networks.

RESULTS

We identified a subset exhibiting highly atypical individual-level FC, exceeding 2 standard deviation from the normative value. We also identified clinically relevant networks (mainly default mode network) at cohort level, since the outlier rates decreased with age in TD participants, but increased in those with autism. Moreover, deviations were linked to severity of repetitive behaviors and social communication symptoms.

CONCLUSIONS

Individuals with ASD exhibit distinct, highly individualized trajectories of brain functional network development. In addition, distinct developmental trajectories were observed among ASD and TD individuals, suggesting that it may be challenging to identify true differences in network characteristics by comparing young children with ASD to their TD peers. This study enhances understanding of the biological heterogeneity of the disorder and can inform precision medicine.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear.

METHODS

We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD.

RESULTS

Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD.

CONCLUSIONS

These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders.

TRIAL REGISTRATION

PROSPERO CRD42022370620. Registered on November 9, 2022.

Characterizing individual differences in children and adolescents with autism spectrum disorder: a descriptive study

Introduction

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by a higher prevalence in male than in female participants. Recent studies have hypothesized the presence of different phenotypes in male and female participants with ASD. The present study aims to assess possible sex differences in cognitive and adaptive functioning, symptomatology of ASD, and psychopathological comorbidities in a large sample of children and adolescents with ASD.

Methods

The study included a total of 2,146 children and adolescents diagnosed with ASD, comprising 1785 boys (mean age 7.12 ± 3.69 years) and 361 girls (mean age 6.25 ± 3.30 years). The age of the participants ranged from 1.35 to 19.05 years (mean age 9.98 ± 3.64). The study sought to include all children and adolescents diagnosed with Autism or ASD.

Results

Present results showed that girls with ASD had lower IQs than boys but similar adaptive functioning. The severity of symptoms of ASD was greater in boys than in girls, as were scores on psychopathological measures. With increasing age, boys with ASD showed greater impairment in social communication skills than girls and increased psychopathological comorbidities. Older girls showed fewer restricted and repetitive behaviors.

Discussion

Exploring phenotypic differences in children and adolescents with ASD fosters an understanding of subtle diagnostic facets that may go unrecognized, allowing for increasingly individualized and tailored interventions.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Background

Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods

Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions

These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Intellectual disabilities moderate sex/gender differences in autism spectrum disorder: a systematic review and meta-analysis

BACKGROUND

Girls/women with autism spectrum disorder (ASD) are suggested to exhibit different symptom profiles than boys/men with ASD. Accumulating evidence suggests that intellectual disability (ID) may affect sex/gender differences in ASD. However, a systematic review and meta-analysis on this topic is missing.

METHODS

Two databases (MEDLINE and PsycINFO) were used to search for studies reporting sex/gender differences (girls/women versus boys/men) in social communication and interaction, restrictive and repetitive behaviour and interests (RRBIs), sensory processing, and linguistic and motor abilities in ASD. The final sample consisted of 79 studies. The meta-analysis was performed with Review Manager using a random-effects model. Participants with ASD without and with ID were analysed as separate subgroups, and the effects in these two subgroups were also compared with each other.

RESULTS

Girls/women with ASD without ID displayed fewer RRBIs, more sensory symptoms and less problems in linguistic abilities than their boys/men counterparts. In contrast, girls/women with ASD with ID displayed more social difficulties and RRBIs, poorer linguistic abilities and more motor problems than boys/men with ASD with ID. Comparisons of groups of participants with ASD without ID versus participants with ASD with ID confirmed differences in sex/gender effects on social difficulties, sensory processing, linguistic abilities and motor abilities.

CONCLUSIONS

Our results clearly suggest that the female phenotype of ASD is moderated by ID. Among individuals with ASD with ID, girls/women seem to be more severely affected than boys/men, whereas among individuals with ASD without ID, girls/women with ASD may have less symptoms than boys/men. Such phenotypic differences could be a potential cause of underrecognition of girls/women with ASD, and it is also possible that observed phenotypic differences may reflect underdiagnosing of girls/women with ASD.

Sex-specific genetic association between psychiatric disorders and cognition, behavior and brain imaging in children and adults

Although there are pronounced sex differences for psychiatric disorders, relatively little has been published on the heterogeneity of sex-specific genetic effects for these traits until very recently for adults. Much less is known about children because most psychiatric disorders will not manifest until later in life and existing studies for children on psychiatric traits such as cognitive functions are underpowered. We used results from publicly available genome-wide association studies for six psychiatric disorders and individual-level data from the Adolescent Brain Cognitive Development (ABCD) study and the UK Biobank (UKB) study to evaluate the associations between the predicted polygenic risk scores (PRS) of these six disorders and observed cognitive functions, behavioral and brain imaging traits. We further investigated the mediation effects of the brain structure and function, which showed heterogeneity between males and females on the correlation between genetic risk of schizophrenia and fluid intelligence. There was significant heterogeneity in genetic associations between the cognitive traits and psychiatric disorders between sexes. Specifically, the PRSs of schizophrenia of boys showed stronger correlation with eight of the ten cognitive functions in the ABCD data set; whereas the PRSs of autism of females showed a stronger correlation with fluid intelligence in the UKB data set. Besides cognitive traits, we also found significant sexual heterogeneity in genetic associations between psychiatric disorders and behavior and brain imaging. These results demonstrate the underlying early etiology of psychiatric disease and reveal a shared and unique genetic basis between the disorders and cognition traits involved in brain functions between the sexes.

Sex Differences in Autism Spectrum Disorder: Diagnostic, Neurobiological, and Behavioral Features

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a worldwide prevalence of about 1%, characterized by impairments in social interaction, communication, repetitive patterns of behaviors, and can be associated with hyper- or hypo-reactivity of sensory stimulation and cognitive disability. ASD comorbid features include internalizing and externalizing symptoms such as anxiety, depression, hyperactivity, and attention problems. The precise etiology of ASD is still unknown and it is undoubted that the disorder is linked to some extent to both genetic and environmental factors. It is also well-documented and known that one of the most striking and consistent finding in ASD is the higher prevalence in males compared to females, with around 70% of ASD cases described being males. The present review looked into the most significant studies that attempted to investigate differences in ASD males and females thus trying to shade some light on the peculiar characteristics of this prevalence in terms of diagnosis, imaging, major autistic-like behavior and sex-dependent uniqueness. The study also discussed sex differences found in animal models of ASD, to provide a possible explanation of the neurological mechanisms underpinning the different presentation of autistic symptoms in males and females.

Dissecting the heterogeneous subcortical brain volume of autism spectrum disorder using community detection

Structural brain alterations in autism spectrum disorder (ASD) are heterogeneous, with limited effect sizes overall. In this study, we aimed to identify subgroups in ASD, based on neuroanatomical profiles; we hypothesized that the effect sizes for case/control differences would be increased in the newly defined subgroups. Analyzing a large data set from the ENIGMA-ASD working group (n = 2661), we applied exploratory factor analysis (EFA) to seven subcortical volumes of individuals with and without ASD to uncover the underlying organization of subcortical structures. Based on earlier findings and data availability, we focused on three age groups: boys (<=14 years), male adolescents (15-22 years), and adult men (> = 22 years). The resulting factor scores were used in a community detection (CD) analysis to cluster participants into subgroups. Three factors were found in each subsample; the factor structure in adult men differed from that in boys and male adolescents. From these factors, CD uncovered four distinct communities in boys and three communities in adolescents and adult men, irrespective of ASD diagnosis. The effect sizes for case/control comparisons were more pronounced than in the combined sample, for some communities. A significant group difference in ADOS scores between communities was observed in boys and male adolescents with ASD. We succeeded in stratifying participants into more homogeneous subgroups based on subcortical brain volumes. This stratification enhanced our ability to observe case/control differences in subcortical brain volumes in ASD, and may help to explain the heterogeneity of previous findings in ASD. LAY SUMMARY: Structural brain alterations in ASD are heterogeneous, with overall limited effect sizes. Here we aimed to identify subgroups in ASD based on neuroimaging measures. We tested whether the effect sizes for case/control differences would be increased in the newly defined subgroups. Based on neuroanatomical profiles, we succeeded in stratifying our participants into more homogeneous subgroups. The effect sizes of case/control differences were more pronounced in some subgroups than those in the whole sample.

Association Between Abnormal Fetal Head Growth and Autism Spectrum Disorder

OBJECTIVE

Despite evidence for the prenatal onset of abnormal head growth in children with autism spectrum disorder (ASD), studies on fetal ultrasound data in ASD are limited and controversial.

METHOD

We conducted a longitudinal matched case-sibling-control study on prenatal ultrasound biometric measures of children with ASD, and 2 control groups: (1) their own typically developed sibling (TDS) and (2) typically developed population (TDP). The cohort comprised 528 children (72.7% male), 174 with ASD, 178 TDS, and 176 TDP.

RESULTS

During the second trimester, ASD and TDS fetuses had significantly smaller biparietal diameter (BPD) than TDP fetuses (adjusted odds ratio for the z score of BPD [aOR_zBPD] = 0.685, 95% CI = 0.527-0.890, and aOR_zBPD = 0.587, 95% CI = 0.459-0.751, respectively). However, these differences became statistically indistinguishable in the third trimester. Interestingly, head biometric measures varied by sex, with male fetuses having larger heads than female fetuses within and across groups. A linear mixed-effect model assessing the effects of sex and group assignment on fetal longitudinal head growth indicated faster BPD growth in TDS versus both ASD and TDP in male fetuses (β = 0.084 and β = 0.100 respectively; p < .001) but not in female fetuses, suggesting an ASD-sex interaction in head growth during gestation. Finally, fetal head growth showed conflicting correlations with ASD severity in male and female children across different gestation periods, thus further supporting the sex effect on the association between fetal head growth and ASD.

CONCLUSION

Our findings suggest that abnormal fetal head growth is a familial trait of ASD, which is modulated by sex and is associated with the severity of the disorder. Thus, it could serve as an early biomarker for ASD.

Beyond sex differences and a male-female continuum: Mosaic brains in a multidimensional space

In the last two decades, the 60 years old view that in utero exposure to testosterone irreversibly masculinizes the brain of males away from a default female form has been replaced by a complex scenario according to which sex affects the brains of both females and males via multiple mechanisms, which are susceptible to internal and external factors. These observations led to the "mosaic" hypothesis-the expectation that the degree of "maleness"/"femaleness" of different features within a single brain would not be internally consistent. Following a short review of the animal studies providing the basis of the mosaic hypothesis, I describe three studies conducted in humans that assessed internal consistency in regional volume, cortical thickness, and connectivity as revealed by magnetic resonance imaging (MRI); in neuronal numbers in the postmortem hypothalamus; and in changes in regional volume and cortical thickness (assessed with MRI) following exposure to extreme real-life stress. The conclusion from these studies, that human brains are largely composed of unique mosaics of female-typical and male-typical features, was supported by recent findings that the brain "types" typical of women are also typical of men, and vice versa. Lastly, I discuss criticism of the mosaic hypothesis and suggest replacing the framework of a male-female continuum with thinking about mosaic brains residing in a multidimensional space.

Autism spectrum disorder: An examination of sex differences in neuropsychological and self-report measures of executive and non-executive cognitive function

LAY ABSTRACT

Research comparing females and males with a diagnosis of autism suggests that there are sex differences in some characteristics such as behaviour regulation. One area not studied in detail is whether females and males with autism perform differently in tests of cognitive ability. The results of previous research are quite mixed. One explanation may be that some research comparing females and males with autism did not include a neurotypical control group for comparison. As a result, it is not clear whether the sex differences in cognitive ability observed in people with autism are similar to differences between neurotypical males and females. To better understand whether there are unique differences between males and females with autism, it is important to also compare them with neurotypical males and females. In our research, we included a neurotypical group and compared males and females with and without a diagnosis of autism. We found that the sex differences in autism are similar to what we observe in males and females without autism. Our study showed that compared with males, females (with and without autism) do better in assessments of processing speed, cognitive flexibility, verbal learning and memory and semantic fluency. Our results suggest that although females show different cognitive performance to males, these sex differences were not specific to the group with a diagnosis of autism.

S-Palmitoylation of Synaptic Proteins as a Novel Mechanism Underlying Sex-Dependent Differences in Neuronal Plasticity

Although sex differences in the brain are prevalent, the knowledge about mechanisms underlying sex-related effects on normal and pathological brain functioning is rather poor. It is known that female and male brains differ in size and connectivity. Moreover, those differences are related to neuronal morphology, synaptic plasticity, and molecular signaling pathways. Among different processes assuring proper synapse functions are posttranslational modifications, and among them, S-palmitoylation (S-PALM) emerges as a crucial mechanism regulating synaptic integrity. Protein S-PALM is governed by a family of palmitoyl acyltransferases, also known as DHHC proteins. Here we focused on the sex-related functional importance of DHHC7 acyltransferase because of its S-PALM action over different synaptic proteins as well as sex steroid receptors. Using the mass spectrometry-based PANIMoni method, we identified sex-dependent differences in the S-PALM of synaptic proteins potentially involved in the regulation of membrane excitability and synaptic transmission as well as in the signaling of proteins involved in the structural plasticity of dendritic spines. To determine a mechanistic source for obtained sex-dependent changes in protein S-PALM, we analyzed synaptoneurosomes isolated from DHHC7-/- (DHHC7KO) female and male mice. Our data showed sex-dependent action of DHHC7 acyltransferase. Furthermore, we revealed that different S-PALM proteins control the same biological processes in male and female synapses.

Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findings

Females with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical cohorts. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in "protection." When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain "masculinization" and "feminization" across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.

Testing the extreme male brain hypothesis: Is autism spectrum disorder associated with a more male-typical brain?

Autism spectrum disorder (ASD) is more common in males than females and has been linked to male-typical behavior. Accordingly, the "Extreme Male Brain" hypothesis suggests that ASD is associated with an exaggeratedly male-typical brain. To test this hypothesis, we derived a data-driven measure of individual differences along a male-female dimension based on sex differences in subcortical brain shape (i.e., brain maleness) by training our algorithm on two population samples (Queensland Twin IMaging study and Human Connectome Project; combined N = 2153). We then applied this algorithm to two clinical datasets (Autism Brain Imaging Data Exchange I and II; ASD N = 1060; neurotypical controls N = 1166) to obtain a brain maleness score for each individual, representing maleness of their brain on a male-female continuum. Consistent with the Extreme Male Brain hypothesis, we found a higher mean brain maleness score in the ASD group than in controls (d = 0.20 [0.12-0.29]), parallel to higher scores for control males than control females (d = 1.17 [1.05-1.29]). Further, brain maleness was positively associated with autistic symptoms. We tested the possibility this finding was driven by the ASD group's larger brains than controls (d = 0.17 [0.08-0.25]), given that males had larger brains than females (d = 0.96 [0.84-1.07]). Indeed, after adjusting for differences in brain size, the brain maleness difference between the ASD group and controls disappeared, and no association with autistic symptoms remained (after controlling for multiple comparisons), suggesting greater maleness of the autistic brain is driven by brain size. Brain maleness may be influenced by the same factors that influence brain size. LAY SUMMARY: A popular theory proposes that individuals with autistic spectrum disorder (ASD) have an "extreme male brain", but this has not been subject to rigorous, direct tests. We developed a measure of individual differences along a male-female dimension and then derived this measure for 1060 individuals with ASD and 1166 neurotypical controls. Individuals with ASD had slightly more male-type brains. However, this difference is accounted for by males and individuals with ASD having relatively larger brains than females and controls, respectively.

Alterations of Regional Homogeneity in Preschool Boys With Autism Spectrum Disorders

Objectives

The study was aimed at investigating the alterations of local spontaneous brain activity in preschool boys with autism spectrum disorders (ASD).

Methods

Based on regional homogeneity (ReHo), the acquired resting state functional magnetic resonance imaging (fMRI) data sets, which included 86 boys with ASD and 54 typically developing (TD) boys, were used to detect regional brain activity. Pearson correlation analysis was used to study the relationship between abnormal ReHo value and the Childhood Autism Rating Scale (CARS), Autism Behavior Checklist (ABC), developmental quotient, and age.

Results

In the ASD group, we found increased ReHo in the right calcarine as well as decreased ReHo in the opercular part of the left inferior frontal gyrus, the left middle temporal gyrus, the left angular gyrus, and the right medial orbital frontal cortex (p < 0.05, false discovery rate correction). We did not find a correlation between the results of brain regions and the CARS, ABC, and age.

Conclusions

Our study found spontaneous activity changes in multiple brain regions, especially the visual and language-related areas of ASD, that may help to further understand the clinical characteristics of boys with ASD.

Quantitative and Qualitative Sex Modulations in the Brain Anatomy of Autism

BACKGROUND

Sex-based neurobiological heterogeneity in autism is poorly understood. Research is disproportionately biased to males, leading to an unwarranted presumption that autism neurobiology is the same across sexes. Previous neuroimaging studies using amalgamated multicenter datasets to increase autistic female samples are characterized by large statistical noise.

METHODS

We used a better-powered dataset of 1183 scans of 839 individuals-299 (467 scans) autistic males, 74 (102 scans) autistic females, 240 (334 scans) control males, and 226 (280 scans) control females-to test two whole-brain models of overall/global sex modulations on autism neuroanatomy, by summary measures computed across the brain: the local magnitude model, in which the same brain regions/circuitries are involved across sexes but effect sizes are larger in females, indicating quantitative sex modulation; and spatial dissimilarity model, in which the neuroanatomy differs spatially between sexes, indicating qualitative sex modulation. The male and female autism groups were matched on age, IQ, and autism symptoms. Autism brain features were defined by comparisons with same-sex control individuals.

RESULTS

Across five metrics (cortical thickness, surface area, volume, mean absolute curvature, and subcortical volume), we found no evidence supporting the local magnitude model. We found indicators supporting the spatial dissimilarity model on cortical mean absolute curvature and subcortical volume, but not on other metrics.

CONCLUSIONS

The overall/global autism neuroanatomy in females and males does not simply differ quantitatively in the same brain regions/circuitries. They may differ qualitatively in spatial involvement in cortical curvature and subcortical volume. The neuroanatomy of autism may be partly sex specific. Sex stratification to inform autism preclinical/clinical research is needed to identify sex-informed neurodevelopmental targets.

Beyond the binary: Rethinking sex and the brain

The paper reviews the relations between sex and brain in light of the binary conceptualization of these relations and the challenges posed to it by the 'mosaic' hypothesis. Recent formulations of the binary framework range from arguing that the typical male brain is different from the typical female brain to claiming that brains are typically male or female because brain structure can be used to predict the sex category (female/male) of the brain's owner. These formulations are challenged by evidence that sex effects on the brain may be opposite under different conditions, that human brains are comprised of mosaics of female-typical and male-typical features, and that sex category explains only a small part of the variability in human brain structure. These findings led to a new, non-binary, framework, according to which mosaic brains reside in a multi-dimensional space that cannot meaningfully be reduced to a male-female continuum or to a binary variable. This framework may also apply to sex-related variables and has implications for research.

Sex-related patterns of intrinsic functional connectivity in children and adolescents with autism spectrum disorders

LAY SUMMARY

We investigated whether children and adolescents with autism spectrum disorders show sex-specific patterns of brain function (using functional magnetic resonance imaging) that are well documented in typically developing males and females. We found, unexpectedly, that boys and girls with autism do not differ in their brain functional connectivity, whereas typically developing boys and girls showed differences in a brain network involved in thinking about self and others (the default mode network). Results suggest that autism may be characterized by a lack of brain sex differentiation.

A Longitudinal Study of Local Gyrification Index in Young Boys With Autism Spectrum Disorder

Local gyrification index (LGI), a metric quantifying cortical folding, was evaluated in 105 boys with autism spectrum disorder (ASD) and 49 typically developing (TD) boys at 3 and 5 years-of-age. At 3 years-of-age, boys with ASD had reduced gyrification in the fusiform gyrus compared with TD boys. A longitudinal evaluation from 3 to 5 years revealed that while TD boys had stable/decreasing LGI, boys with ASD had increasing LGI in right inferior temporal gyrus, right inferior frontal gyrus, right inferior parietal lobule, and stable LGI in left lingual gyrus. LGI was also examined in a previously defined neurophenotype of boys with ASD and disproportionate megalencephaly. At 3 years-of-age, this subgroup exhibited increased LGI in right dorsomedial prefrontal cortex, cingulate cortex, and paracentral cortex, and left cingulate cortex and superior frontal gyrus relative to TD boys and increased LGI in right paracentral lobule and parahippocampal gyrus, and left precentral gyrus compared with boys with ASD and normal brain size. In summary, this study identified alterations in the pattern and development of LGI during early childhood in ASD. Distinct patterns of alterations in subgroups of boys with ASD suggests that multiple neurophenotypes exist and boys with ASD and disproportionate megalencephaly should be evaluated separately.

Biological sex classification with structural MRI data shows increased misclassification in transgender women

Transgender individuals (TIs) show brain-structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of N = 1753 cisgender (CG) healthy participants were used to train (N = 1402) and validate (20% holdout N = 351) a support-vector machine classifying the biological sex. As a second validation, we classified N = 1104 patients with depression. A third validation was performed using the matched CG sample of the transgender women (TW) application sample. Subsequently, the classifier was applied to N = 26 TW. Finally, we compared brain volumes of CG-men, women, and TW-pre/post treatment cross-sex hormone treatment (CHT) in a univariate analysis controlling for sexual orientation, age, and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR-male = 56.0%). The TPR did not differ between CG-individuals with (TPR-male = 86.9%) and without depression (TPR-male = 88.5%). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain-structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain-structural alterations leading to a different pattern of brain structure than CG-individuals.

Androgens During Infancy, Childhood, and Adolescence: Physiology and Use in Clinical Practice

We provide an in-depth review of the role of androgens in male maturation and development, from the fetal stage through adolescence into emerging adulthood, and discuss the treatment of disorders of androgen production throughout these time periods. Testosterone, the primary androgen produced by males, has both anabolic and androgenic effects. Androgen exposure induces virilization and anabolic body composition changes during fetal development, influences growth and virilization during infancy, and stimulates development of secondary sexual characteristics, growth acceleration, bone mass accrual, and alterations of body composition during puberty. Disorders of androgen production may be subdivided into hypo- or hypergonadotropic hypogonadism. Hypogonadotropic hypogonadism may be either congenital or acquired (resulting from cranial radiation, trauma, or less common causes). Hypergonadotropic hypogonadism occurs in males with Klinefelter syndrome and may occur in response to pelvic radiation, certain chemotherapeutic agents, and less common causes. These disorders all require testosterone replacement therapy during pubertal maturation and many require lifelong replacement. Androgen (or gonadotropin) therapy is clearly beneficial in those with persistent hypogonadism and self-limited delayed puberty and is now widely used in transgender male adolescents. With more widespread use and newer formulations approved for adults, data from long-term randomized placebo-controlled trials are needed to enable pediatricians to identify the optimal age of initiation, route of administration, and dosing frequency to address the unique needs of their patients.

Sex Differences Along the Autism Continuum: A Twin Study of Brain Structure

Females might possess protective mechanisms regarding autism spectrum disorder (ASD) and require a higher detrimental load, including structural brain alterations, before developing clinically relevant levels of autistic traits. This study examines sex differences in structural brain morphology in autism and autistic traits using a within-twin pair approach. Twin design inherently controls for shared confounders and enables the study of gene-independent neuroanatomical variation. N = 148 twins (62 females) from 49 monozygotic and 25 dizygotic same-sex pairs were included. Participants were distributed along the whole continuum of autism including twin pairs discordant and concordant for clinical ASD. Regional brain volume, surface area, and cortical thickness were computed. Within-twin pair increases in autistic traits were related to decreases in cortical volume and surface area of temporal and frontal regions specifically in female twin pairs, in particular regions involved in social communication, while only two regions were associated with autistic traits in males. The same pattern was detected in the monozygotic twin pairs only. Thus, non-shared environmental factors seem to impact female more than male cerebral architecture associated with autistic traits. Our results are in line with the hypothesis of a female protective effect in autism and highlights the need to study ASD in females separately from males.

Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder

Significant heterogeneity across aetiologies, neurobiology and clinical phenotypes have been observed in individuals with autism spectrum disorder (ASD). Neuroimaging-based neuroanatomical studies of ASD have often reported inconsistent findings which may, in part, be attributable to an insufficient understanding of the relationship between factors influencing clinical heterogeneity and their relationship to brain anatomy. To this end, we performed a large-scale examination of cortical morphometry in ASD, with a specific focus on the impact of three potential sources of heterogeneity: sex, age and full-scale intelligence (FIQ). To examine these potentially subtle relationships, we amassed a large multi-site dataset that was carefully quality controlled (yielding a final sample of 1327 from the initial dataset of 3145 magnetic resonance images; 491 individuals with ASD). Using a meta-analytic technique to account for inter-site differences, we identified greater cortical thickness in individuals with ASD relative to controls, in regions previously implicated in ASD, including the superior temporal gyrus and inferior frontal sulcus. Greater cortical thickness was observed in sex specific regions; further, cortical thickness differences were observed to be greater in younger individuals and in those with lower FIQ, and to be related to overall clinical severity. This work serves as an important step towards parsing factors that influence neuroanatomical heterogeneity in ASD and is a potential step towards establishing individual-specific biomarkers.

A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms

Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One of the difficulties in investigating differences between the sexes in autism is the small sample sizes of available imaging datasets with mixed sex. Thus, the majority of the investigations have involved male samples, with females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal differences in regional brain structure between individuals with autism and typically developing participants. A four-class classification problem (sex and condition) is specified, with theoretical restrictions based on the evaluation of a novel upper bound in the resubstitution estimate. These conditions were imposed on the classifier complexity and feature space dimension to assure generalizable results from the training set to test samples. Accuracies above [Formula: see text] on gray and white matter tissues estimated from voxel-based morphometry (VBM) features are obtained in a sample of equal-sized high-functioning male and female adults with and without autism ([Formula: see text], [Formula: see text]/group). The proposed learning machine revealed how autism is modulated by biological sex using a low-dimensional feature space extracted from VBM. In addition, a spatial overlap analysis on reference maps partially corroborated predictions of the “extreme male brain” theory of autism, in sexual dimorphic areas.

Beyond a Binary Classification of Sex: An Examination of Brain Sex Differentiation, Psychopathology, and Genotype

OBJECTIVE

Sex differences in the brain are traditionally treated as binary. We present new evidence that a continuous measure of sex differentiation of the brain can explain sex differences in psychopathology. The degree of sex-differentiated brain features (ie, features that are more common in one sex) may predispose individuals toward sex-biased psychopathology and may also be influenced by the genome. We hypothesized that individuals with a female-biased differentiation score would have greater female-biased psychopathology (internalizing symptoms, such as anxiety and depression), whereas individuals with a male-biased differentiation score would have greater male-biased psychopathology (externalizing symptoms, such as disruptive behaviors).

METHOD

Using the Philadelphia Neurodevelopmental Cohort database acquired from database of Genotypes and Phenotypes, we calculated the sex differentiation measure, a continuous data-driven calculation of each individual's degree of sex-differentiating features extracted from multimodal brain imaging data (magnetic resonance imaging [MRI] /diffusion MRI) from the imaged participants (n = 866, 407 female and 459 male).

RESULTS

In male individuals, higher differentiation scores were correlated with higher levels of externalizing symptoms (r = 0.119, p = .016). The differentiation measure reached genome-wide association study significance (p < 5∗10^-8) in male individuals with single nucleotide polymorphisms Chromsome5:rs111161632:RASGEF1C and Chromosome19:rs75918199:GEMIN7, and in female individuals with Chromosome2:rs78372132:PARD3B and Chromosome15:rs73442006:HCN4.

CONCLUSION

The sex differentiation measure provides an initial topography of quantifying male and female brain features. This demonstration that the sex of the human brain can be conceptualized on a continuum has implications for both the presentation of psychopathology and the relation of the brain with genetic variants that may be associated with brain differentiation.

Opposite Expression Patterns of Spry3 and p75NTR in Cerebellar Vermis Suggest a Male-Specific Mechanism of Autism Pathogenesis

Autism is a genetically complex neurobehavioral disorder with a population prevalence of more than 1%. Cerebellar abnormalities, including Purkinje cell deficits in the vermis, are consistently reported, and rodent models of cerebellar dysfunction exhibit features analogous to human autism. We previously analyzed the regulation and expression of the pseudoautosomal region 2 gene SPRY3, which is adjacent to X chromosome-linked TMLHE, a known autism susceptibility gene. SPRY3 is a regulator of branching morphogenesis and is strongly expressed in Purkinje cells. We previously showed that mouse Spry3 is not expressed in cerebellar vermis lobules VI-VII and X, regions which exhibit significant Purkinje cell loss or abnormalities in autism. However, these lobules have relatively high expression of p75NTR, which encodes a neurotrophin receptor implicated in autism. We propose a mechanism whereby inappropriate SPRY3 expression in these lobules could interact with TrkB and p75NTR signaling pathways resulting in Purkinje cell pathology. We report preliminary characterization of X and Y chromosome-linked regulatory sequences upstream of SPRY3, which are polymorphic in the general population. We suggest that an OREG-annotated region on chromosome Yq12 ∼60 kb from SPRY3 acts as a silencer of Y-linked SPRY3 expression. Deletion of a β-satellite repeat, or alterations in chromatin structure in this region due to trans-acting factors, could affect the proposed silencing function, leading to reactivation and inappropriate expression of Y-linked SPRY3. This proposed male-specific mechanism could contribute to the male bias in autism prevalence.

Extreme male developmental trajectories of homotopic brain connectivity in autism

It has been proposed that autism spectrum disorder (ASD) may be characterized by an extreme male brain (EMB) pattern of brain development. Here, we performed the first investigation of how age-related changes in functional brain connectivity may be expressed differently in females and males with ASD. We analyzed resting-state functional magnetic resonance imaging data of 107 typically developing (TD) females, 114 TD males, 104 females, and 115 males with ASD (6-26 years) from the autism brain imaging data exchange repository. We explored how interhemispheric homotopic connectivity and its maturational curvatures change across groups. Differences between ASD and TD and between females and males with ASD were observed for the rate of changes in connectivity in the absence of overall differences in connectivity. The largest portion of variance in age-related changes in connectivity was described through similarities between TD males, ASD males, and ASD females, in contrast to TD females. We found that shape of developmental curvature is associated with symptomatology in both males and females with ASD. We demonstrated that females and males with ASD tended to follow the male pattern of developmental changes in interhemispheric connectivity, supporting the EMB theory of ASD.

Empathy in Females With Autism Spectrum Disorder

Objective: Despite the fact that autism spectrum disorder (ASD) is a common psychiatric diagnosis, knowledge about the special behavioral and neurobiological female phenotype is still scarce. The present study aimed to investigate neural correlates of empathy for physical and social pain and to assess the impact of egocentric perspective taking on social pain empathy in complex social situations in women and girls with ASD. Methods: Nine female individuals with high functioning ASD were compared to nine matched peers without ASD during two functional magnetic resonance imaging (fMRI) experiments, examining empathy for physical and social pain using well-established paradigms. Participants viewed multiple pictorial stimuli depicting a social target in either physically painful or socially unpleasant situations. In the social situations, the participant either shared the social target's knowledge about the inappropriateness of the situation (observed social target is aware about the embarrassment of the situation; e.g., tripping in public) or not (observed social target is unaware about the embarrassment of the situation; e.g., open zipper). Results: Females with ASD did not rate the physical pain stimuli differently from non-clinical controls. Social pain situations, however, posed a greater challenge to females with ASD: For non-shared knowledge situations, females with ASD rated the social target's embarrassment as more intense. Thus, compared to non-clinical controls, females with ASD had a stronger egocentric perspective of the situation rather than sharing the social target's perspective. On the neural systems level, both groups showed activation of areas of the so-called empathy network that was attenuated in females with ASD during empathy for physical and social pain with a particular reduction in insula activation. Conclusion: Females with high functioning ASD are able to share another person's physical or social pain on the neural systems level. However, hypoactivation of the anterior insula in contrast to individuals without ASD suggests that they are less able to rely on their shared representations of emotions along with difficulties to take over a person's perspective and to make a clear distinction between their own and someone else's experience of embarrassment.

Gender Identity in Autism: Sex Differences in Social Affiliation with Gender Groups

High rates of gender variance have been reported in autistic people, with higher variance in autistic females than males. The social component of gender identity may be affected, with autistic females experiencing lower identification with and feeling less positively about their gender groups than controls. We measured gender identification, gender self-esteem, and aspects of gender expression (masculinity and femininity) in autistic natal males and females, and controls (N = 486). We found that autistic people had lower gender identification and gender self-esteem than controls, and autistic natal females had lower gender identification than autistic natal males and natal female controls. In conclusion, autistic people, particularly natal females, had lower social identification with and more negative feelings about a gender group.

Support Vector Machines, Multidimensional Scaling and Magnetic Resonance Imaging Reveal Structural Brain Abnormalities Associated With the Interaction Between Autism Spectrum Disorder and Sex

Despite substantial efforts, it remains difficult to identify reliable neuroanatomic biomarkers of autism spectrum disorder (ASD) based on magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Studies which use standard statistical methods to approach this task have been hampered by numerous challenges, many of which are innate to the mathematical formulation and assumptions of general linear models (GLM). Although the potential of alternative approaches such as machine learning (ML) to identify robust neuroanatomic correlates of psychiatric disease has long been acknowledged, few studies have attempted to evaluate the abilities of ML to identify structural brain abnormalities associated with ASD. Here we use a sample of 110 ASD patients and 83 typically developing (TD) volunteers (95 females) to assess the suitability of support vector machines (SVMs, a robust type of ML) as an alternative to standard statistical inference for identifying structural brain features which can reliably distinguish ASD patients from TD subjects of either sex, thereby facilitating the study of the interaction between ASD diagnosis and sex. We find that SVMs can perform these tasks with high accuracy and that the neuroanatomic correlates of ASD identified using SVMs overlap substantially with those found using conventional statistical methods. Our results confirm and establish SVMs as powerful ML tools for the study of ASD-related structural brain abnormalities. Additionally, they provide novel insights into the volumetric, morphometric, and connectomic correlates of this epidemiologically significant disorder.

Developmental changes of cortical white-gray contrast as predictors of autism diagnosis and severity

Recent studies suggest that both cortical gray and white-matter microstructural characteristics are distinct for subjects with autism. There is a lack of evidence regarding how these characteristics change in a developmental context. We analysed a longitudinal/cross-sectional dataset of 402 magnetic resonance imaging (MRI) scans (171 subjects with autism and 231 with typical development) from the Autism Brain Imaging Data Exchange, cohorts I-II (ABIDE-I-II). In the longitudinal sample, we computed the rate of change in the white-gray contrast, a measure which has been related to age and cognitive performance, at the boundary of the cerebral cortex. Then, we devised an analogous metric for the cross-sectional sample of the ABIDE dataset to measure age-related differences in cortical contrast. Further, we developed a probabilistic model to predict the diagnostic group in the longitudinal sample of the cortical contrast change data, using results obtained from the cross-sectional sample. In both subsets, we observed a similar overall pattern of greater decrease within the autistic population in intensity contrast for most cortical regions (81%), with occasional increases, mostly in primary sensory regions. This pattern correlated well with raw and calibrated behavioural scores. The prediction results show 76% accuracy for the whole-cortex diagnostic prediction and 86% accuracy in prediction using the motor system alone. Our results support a contrast change analysis strategy that appears sensitive in predicting diagnostic outcome and symptom severity in autism spectrum disorder, and is readily extensible to other MRI-based studies of neurodevelopmental cohorts.

Analysis of Human Brain Structure Reveals that the Brain "Types" Typical of Males Are Also Typical of Females, and Vice Versa

Findings of average differences between females and males in the structure of specific brain regions are often interpreted as indicating that the typical male brain is different from the typical female brain. An alternative interpretation is that the brain types typical of females are also typical of males, and sex differences exist only in the frequency of rare brain types. Here we contrasted the two hypotheses by analyzing the structure of 2176 human brains using three analytical approaches. An anomaly detection analysis showed that brains from females are almost as likely to be classified as “normal male brains,” as brains from males are, and vice versa. Unsupervised clustering algorithms revealed that common brain “types” are similarly common in females and in males and that a male and a female are almost as likely to have the same brain “type” as two females or two males are. Large sex differences were found only in the frequency of some rare brain “types.” Last, supervised clustering algorithms revealed that the brain “type(s)” typical of one sex category in one sample could be typical of the other sex category in another sample. The present findings demonstrate that even when similarity and difference are defined mathematically, ignoring biological or functional relevance, sex category (i.e., whether one is female or male), is not a major predictor of the variability of human brain structure. Rather, the brain types typical of females are also typical of males, and vice versa, and large sex differences are found only in the prevalence of some rare brain types. We discuss the implications of these findings to studies of the structure and function of the human brain.

Mouse MRI shows brain areas relatively larger in males emerge before those larger in females

Sex differences exist in behaviors, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. Here, we use manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulate findings on canonically dimorphic areas, demonstrating MEMRI’s ability to study neuroanatomical sex differences. We discover, upon whole-brain volume correction, that neuroanatomical regions larger in males develop earlier than those larger in females. Groups of areas with shared sexually dimorphic developmental trajectories reflect behavioral and functional networks, and expression of genes involved with sex processes. Also, post-pubertal neuroanatomy is highly individualized, and individualization occurs earlier in males. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders.

Sex differences occur in various aspects of neurodevelopment. Here the authors use manganese-enhanced MRI at nine different postnatal stages to detail the development of structural sex differences in the mouse brain.

Cortical and Subcortical Brain Morphometry Differences Between Patients With Autism Spectrum Disorder and Healthy Individuals Across the Lifespan: Results From the ENIGMA ASD Working Group

OBJECTIVE

Neuroimaging studies show structural differences in both cortical and subcortical brain regions in children and adults with autism spectrum disorder (ASD) compared with healthy subjects. Findings are inconsistent, however, and it is unclear how differences develop across the lifespan. The authors investigated brain morphometry differences between individuals with ASD and healthy subjects, cross-sectionally across the lifespan, in a large multinational sample from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) ASD working group.

METHOD

The sample comprised 1,571 patients with ASD and 1,651 healthy control subjects (age range, 2-64 years) from 49 participating sites. MRI scans were preprocessed at individual sites with a harmonized protocol based on a validated automated-segmentation software program. Mega-analyses were used to test for case-control differences in subcortical volumes, cortical thickness, and surface area. Development of brain morphometry over the lifespan was modeled using a fractional polynomial approach.

RESULTS

The case-control mega-analysis demonstrated that ASD was associated with smaller subcortical volumes of the pallidum, putamen, amygdala, and nucleus accumbens (effect sizes [Cohen's d], 0.13 to -0.13), as well as increased cortical thickness in the frontal cortex and decreased thickness in the temporal cortex (effect sizes, -0.21 to 0.20). Analyses of age effects indicate that the development of cortical thickness is altered in ASD, with the largest differences occurring around adolescence. No age-by-ASD interactions were observed in the subcortical partitions.

CONCLUSIONS

The ENIGMA ASD working group provides the largest study of brain morphometry differences in ASD to date, using a well-established, validated, publicly available analysis pipeline. ASD patients showed altered morphometry in the cognitive and affective parts of the striatum, frontal cortex, and temporal cortex. Complex developmental trajectories were observed for the different regions, with a developmental peak around adolescence. These findings suggest an interplay in the abnormal development of the striatal, frontal, and temporal regions in ASD across the lifespan.

Sex Differences in Autism Spectrum Disorder: a Review

PURPOSE OF REVIEW

Neurodevelopmental disorders disproportionately affect males. The mechanisms underlying male vulnerability or female protection are not known and remain understudied. Determining the processes involved is crucial to understanding the etiology and advancing treatment of neurodevelopmental disorders. Here, we review current findings and theories that contribute to male preponderance of neurodevelopmental disorders, with a focus on autism.

RECENT FINDINGS

Recent work on the biological basis of the male preponderance of autism and other neurodevelopmental disorders includes discussion of a higher genetic burden in females and sex-specific gene mutations or epigenetic changes that differentially confer risk to males or protection to females. Other mechanisms discussed are sex chromosome and sex hormone involvement. Specifically, fetal testosterone is involved in many aspects of development and may interact with neurotransmitter, neuropeptide, or immune pathways to contribute to male vulnerability. Finally, the possibilities of female underdiagnosis and a multi-hit hypothesis are discussed. This review highlights current theories of male bias in developmental disorders. Topics include environmental, genetic, and epigenetic mechanisms; theories of sex chromosomes, hormones, neuroendocrine, and immune function; underdiagnosis of females; and a multi-hit hypothesis.

Resting-state brain activity in Chinese boys with low functioning autism spectrum disorder

BACKGROUND

This study aimed to explore the resting-state fMRI changes in Chinese boys with low functioning autism spectrum disorder (LFASD) and the correlation with clinical symptoms.

METHODS

The current study acquired resting-state fMRI data from 15 Chinese boys with LFASD and 15 typically developing (TD) boys to examine the local brain activity using the regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) indexes; the researchers also examined these measures and their possible relationships with clinical symptoms using the autism behavior checklist.

RESULTS

Results indicated that boys with LFASD exhibited increased ReHo in the right precuneus and inferior parietal gyrus (IPG), increased ALFF in right middle temporal gyrus, angular gyrus and IPG. However, no correlation was found between the ALFF/ReHo score and clinical symptoms in the LFASD group.

CONCLUSIONS

Some of the brain regions had ReHo/ALFF values that were higher in the boys with LFASD than the TD group and these differentiated brain areas in boys with LFASD were all on the right cerebrum, which supported 'atypical rightward asymmetry' in boys with LFASD.

Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction and communication, as well as repetitive and restrictive behaviours. The etiological and phenotypic complexity of ASD has so far hindered the development of clinically useful biomarkers for the condition. Neuroimaging studies have been valuable in establishing a biological basis for ASD. Increasingly, neuroimaging has been combined with 'machine learning'-based pattern classification methods to make individual diagnostic predictions. Moving forward, the hope is that these techniques may not only facilitate the diagnostic process but may also aid in fractionating the ASD phenotype into more biologically homogeneous sub-groups, with defined pathophysiology, predictable outcomes and/or responses to targeted treatments and/or interventions. This review chapter will first introduce 'machine learning' and pattern recognition methods in general, with a focus on their application to diagnostic classification. It will highlight why such approaches to biomarker discovery may have advantages over more conventional analytical methods. Magnetic resonance imaging (MRI) findings of atypical brain structure, function and connectivity in ASD will be briefly reviewed before we describe how pattern recognition has been applied to generate predictive models for ASD. Last, we will discuss some limitations and pitfalls of pattern recognition analyses in ASD and consider how the field can advance beyond the prediction of binary outcomes.

Abnormal functional activation and maturation of ventromedial prefrontal cortex and cerebellum during temporal discounting in autism spectrum disorder

People with autism spectrum disorder (ASD) have poor decision-making and temporal foresight. This may adversely impact on their everyday life, mental health, and productivity. However, the neural substrates underlying poor choice behavior in people with ASD, or its' neurofunctional development from childhood to adulthood, are unknown. Despite evidence of atypical structural brain development in ASD, investigation of functional brain maturation in people with ASD is lacking. This cross-sectional developmental fMRI study investigated the neural substrates underlying performance on a temporal discounting (TD) task in 38 healthy (11-35 years old) male adolescents and adults with ASD and 40 age, sex, and IQ-matched typically developing healthy controls. Most importantly, we assessed group differences in the neurofunctional maturation of TD across childhood and adulthood. Males with ASD had significantly poorer task performance and significantly lower brain activation in typical regions that mediate TD for delayed choices, in predominantly right hemispheric regions of ventrolateral/dorsolateral prefrontal cortices, ventromedial prefrontal cortex, striatolimbic regions, and cerebellum. Importantly, differential activation in ventromedial frontal cortex and cerebellum was associated with abnormal functional brain maturation; controls, in contrast to people with ASD, showed progressively increasing activation with increasing age in these regions; which furthermore was associated with performance measures and clinical ASD measures (stereotyped/restricted interests). Findings provide first cross-sectional evidence that reduced activation of TD mediating brain regions in people with ASD during TD is associated with abnormal functional brain development in these regions between childhood and adulthood, and this is related to poor task performance and clinical measures of ASD. Hum Brain Mapp 38:5343-5355, 2017. © 2017 Wiley Periodicals, Inc.

Hippocampus and amygdala radiomic biomarkers for the study of autism spectrum disorder

Background

Emerging evidence suggests the presence of neuroanatomical abnormalities in subjects with autism spectrum disorder (ASD). Identifying anatomical correlates could thus prove useful for the automated diagnosis of ASD. Radiomic analyses based on MRI texture features have shown a great potential for characterizing differences occurring from tissue heterogeneity, and for identifying abnormalities related to these differences. However, only a limited number of studies have investigated the link between image texture and ASD. This paper proposes the study of texture features based on grey level co-occurrence matrix (GLCM) as a means for characterizing differences between ASD and development control (DC) subjects. Our study uses 64 T1-weighted MRI scans acquired from two groups of subjects: 28 typical age range subjects 4–15 years old (14 ASD and 14 DC, age-matched), and 36 non-typical age range subjects 10–24 years old (20 ASD and 16 DC). GLCM matrices are computed from manually labeled hippocampus and amygdala regions, and then encoded as texture features by applying 11 standard Haralick quantifier functions. Significance tests are performed to identify texture differences between ASD and DC subjects. An analysis using SVM and random forest classifiers is then carried out to find the most discriminative features, and use these features for classifying ASD from DC subjects.

Results

Preliminary results show that all 11 features derived from the hippocampus (typical and non-typical age) and 4 features extracted from the amygdala (non-typical age) have significantly different distributions in ASD subjects compared to DC subjects, with a significance of p < 0.05 following Holm–Bonferroni correction. Features derived from hippocampal regions also demonstrate high discriminative power for differentiating between ASD and DC subjects, with classifier accuracy of 67.85%, sensitivity of 62.50%, specificity of 71.42%, and the area under the ROC curve (AUC) of 76.80% for age-matched subjects with typical age range.

Conclusions

Results demonstrate the potential of hippocampal texture features as a biomarker for the diagnosis and characterization of ASD.