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Autism symptom severity change was evaluated during early childhood in 125 children diagnosed with autism spectrum disorder (ASD). Children were assessed at approximately 3 and 6 years of age for autism symptom severity, IQ and adaptive functioning. Each child was assigned a change score, representing the difference between ADOS Calibrated Severity Scores (CSS) at the two ages. A Decreased Severity Group (28.8%) decreased by 2 or more points; a Stable Severity Group (54.4%) changed by 1 point or less; and an Increased Severity Group (16.8%) increased by 2 or more points. Girls tended to decrease in severity more than boys and increase in severity less than boys. There was no clear relationship between intervention history and membership in the groups.

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2–100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.

Brain development occurs rapidly during the first few years of life involving region-specific changes in both gray matter and white matter. Due to the inherent difficulties in acquiring magnetic resonance imaging data in young children, little is known about the properties of white matter in typically developing toddlers. In the context of an ongoing study of young children with autism spectrum disorder, we collected diffusion-weighted imaging data during natural nocturnal sleep in a sample of young (mean age=35months) typically developing male and female (n=41 and 25, respectively) children. Axial diffusivity, radial diffusivity, mean diffusivity and fractional anisotropy were measured at 99 points along the length of 18 major brain tracts. Influences of hemisphere, age, sex, and handedness were examined. We find that diffusion properties vary significantly along the length of the majority of tracks. We also identify hemispheric and sex differences in diffusion properties in several tracts. Finally, we find the relationship between age and diffusion parameters changes along the tract length illustrating variability in age-related white-matter development at the tract level. •We used white-matter tractography in children between 2 and 5years of age.•We examined 4 diffusion parameters at 99 locations along 18 major tracts.•Diffusion parameters varied between hemispheres and along the length of most tracts.•Sexual dimorphisms were found in several tracts.•The relationship between age and diffusion parameters varied along tract length.

Background We extended our study of trajectories of intellectual development of autistic individuals in early (mean age 3 years; T1), and middle childhood (mean age 5 years, 7 months; T2) into later middle childhood/preadolescence (mean age 11 years, 6 months; T3) in the longitudinal Autism Phenome Project cohort. Participants included 373 autistic children (115 females). Methods Multivariate latent class growth analysis was used to identify distinct IQ trajectory subgroups. Baseline and developmental course group differences and predictors of trajectory membership were assessed using linear mixed effects models for repeated measures with pairwise testing, multinomial logistic regression models, and sensitivity analyses. Results We isolated three IQ trajectory groups between T1 and T3 for autistic youth that were similar to those found in our prior work. These included a group with persistent intellectual disability (ID; 45%), a group with substantial increases in IQ (CHG; 39%), and a group with persistently average or above IQs (P‐High; 16%). By T3, the groups did not differ in ADOS‐2 calibrated severity scores (CSS), and there were no group differences between Vineland (VABS) communication scores in CHG and P‐High. T1‐T3 externalizing behaviors declined significantly for CHG, however, there were no significant T3 group differences between internalizing or externalizing symptoms. T1 correlates for CHG and P‐High versus ID group membership included higher VABS communication and lower ADOS‐2 CSS. A T1 to T2 increase in VABS communication scores and a decline in externalizing predicted CHG versus ID group membership, while T1 to T2 improvement in VABS communication and reduction in ADOS‐2 CSS predicted P‐High versus ID group membership. Conclusions Autistic youth exhibit consistent IQ developmental trajectories from early childhood through preadolescence. Factors associated with trajectory group membership may provide clues about prognosis, and the need for treatments that improve adaptive communication and externalizing symptoms. Three IQ trajectories between early childhood and preadolescence were isolated for autistic youth. One showed persistent intellectual disability (ID), one showed persistent higher intellectual ability, and one demonstrated increasing intellectual development with IQ scores rising at least 1 standard deviations. Repetitive behaviors and externalizing behaviors declined for this group with increasing IQs, who together with the persistently high group showed greater symptoms of internalizing. The group with persistent ID showed the most impaired communication and social adaptive functioning, and an NVIQ that was significantly greater than VIQ in early childhood.

Keywords: biomarker, intellectual disability, autism, Down syndrom, Sturge-Weber syndrome, neurodevelopment

Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2–13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

Autism is a heterogeneous disorder with multiple behavioral and biological phenotypes. Accelerated brain growth during early childhood is a well-established biological feature of autism. Onset pattern, i.e., early onset or regressive, is an intensely studied behavioral phenotype of autism. There is currently little known, however, about whether, or how, onset status maps onto the abnormal brain growth. We examined the relationship between total brain volume and onset status in a large sample of 2- to 4-y-old boys and girls with autism spectrum disorder (ASD) [n = 53, no regression (nREG); n = 61, regression (REG)] and a comparison group of age-matched typically developing controls (n = 66). We also examined retrospective head circumference measurements from birth through 18 mo of age. We found that abnormal brain enlargement was most commonly found in boys with regressive autism. Brain size in boys without regression did not differ from controls. Retrospective head circumference measurements indicate that head circumference in boys with regressive autism is normal at birth but diverges from the other groups around 4–6 mo of age. There were no differences in brain size in girls with autism (n = 22, ASD; n = 24, controls). These results suggest that there may be distinct neural phenotypes associated with different onsets of autism. For boys with regressive autism, divergence in brain size occurs well before loss of skills is commonly reported. Thus, rapid head growth may be a risk factor for regressive autism.

The structure of large-scale intrinsic connectivity networks is atypical in adolescents diagnosed with autism spectrum disorder (ASD or autism). However, the degree to which alterations occur in younger children, and whether these differences vary by sex, is unknown. We utilized structural magnetic resonance imaging (MRI) data from a sex- and age- matched sample of 122 autistic and 122 typically developing (TD) children (2–4 years old) to investigate differences in underlying network structure in preschool-aged autistic children within three large scale intrinsic connectivity networks implicated in ASD: the Socioemotional Salience, Executive Control, and Default Mode Networks. Utilizing structural covariance MRI (scMRI), we report network-level differences in autistic versus TD children, and further report preliminary findings of sex-dependent differences within network topology.

One of the most universally accepted facts about autism is that it is heterogenous. Individuals diagnosed with autism spectrum disorder have a wide range of behavioral presentations and a variety of co-occurring medical and mental health conditions. The identification of more homogenous subgroups is likely to lead to a better understanding of etiologies as well as more targeted interventions and treatments. In 2006, we initiated the UC Davis MIND Institute Autism Phenome Project (APP) with the overarching goal of identifying clinically meaningful subtypes of autism. This ongoing longitudinal multidisciplinary study now includes over 400 children and involves comprehensive medical, behavioral, and neuroimaging assessments from early childhood through adolescence (2 to 19 years of age). We have employed several strategies to identify sub-populations within autistic individuals: subgrouping by neural, biological, behavioral or clinical characteristics as well as by developmental trajectories. In this Mini Review, we summarize findings to date from the APP cohort and describe progress made towards identifying meaningful subgroups of autism.

Background The core symptoms of autism spectrum disorder (ASD) are widely theorized to result from altered brain connectivity. Diffusion-weighted magnetic resonance imaging (DWI) has been a versatile method for investigating underlying microstructural properties of white matter (WM) in ASD. Despite phenotypic and etiological heterogeneity, DWI studies in majority male samples of older children, adolescents, and adults with ASD have largely reported findings of decreased fractional anisotropy (FA) across several commissural, projection, and association fiber tracts. However, studies in preschool-aged children (i.e., < 30–40 months) suggest individuals with ASD have increased measures of WM FA earlier in development. Methods We analyzed 127 individuals with ASD (85♂, 42♀) and 54 typically developing (TD) controls (42♂, 26♀), aged 25.1–49.6 months. Voxel-wise effects of ASD diagnosis, sex, age, and their interaction on DWI measures of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were investigated using tract-based spatial statistics (TBSS) while controlling mean absolute and relative motion. Results Compared to TD controls, males and females with ASD had significantly increased measures of FA in eight clusters (threshold-free cluster enhancement p < 0.05) that incorporated several WM tracts including regions of the genu, body, and splenium of the corpus callosum, inferior frontal-occipital fasciculi, inferior and superior longitudinal fasciculi, middle and superior cerebellar peduncles, and corticospinal tract. A diagnosis by sex interaction was observed in measures of AD across six significant clusters incorporating areas of the body, genu, and splenium of the corpus collosum. In these tracts, females with ASD showed increased AD compared to TD females, while males with ASD showed decreased AD compared to TD males. Conclusions The current findings support growing evidence that preschool-aged children with ASD have atypical measures of WM microstructure that appear to differ in directionality from alterations observed in older individuals with the condition. To our knowledge, this study represents the largest sample of preschool-aged females with ASD to be evaluated using DWI. Microstructural differences associated with ASD largely overlapped between sexes. However, differential relationships of AD measures indicate that sex likely modulates ASD neuroanatomical phenotypes. Further longitudinal study is needed to confirm and quantify the developmental relationship of WM structure in ASD.