Cross-sectional and longitudinal neuroanatomical profiles of distinct clinical (adaptive) outcomes in autism.

Individuals with autism spectrum disorder (henceforth referred to as autism) display significant variation in clinical outcome. For instance, across age, some individuals' adaptive skills naturally improve or remain stable, while others' decrease. To pave the way for 'precision-medicine' approaches, it is crucial to identify the cross-sectional and, given the developmental nature of autism, longitudinal neurobiological (including neuroanatomical and linked genetic) correlates of this variation. We conducted a longitudinal follow-up study of 333 individuals (161 autistic and 172 neurotypical individuals, aged 6-30 years), with two assessment time points separated by ~12-24 months. We collected behavioural (Vineland Adaptive Behaviour Scale-II, VABS-II) and neuroanatomical (structural magnetic resonance imaging) data. Autistic participants were grouped into clinically meaningful "Increasers", "No-changers", and "Decreasers" in adaptive behaviour (based on VABS-II scores). We compared each clinical subgroup's neuroanatomy (surface area and cortical thickness at T1, ∆T (intra-individual change) and T2) to that of the neurotypicals. Next, we explored the neuroanatomical differences' potential genomic associates using the Allen Human Brain Atlas. Clinical subgroups had distinct neuroanatomical profiles in surface area and cortical thickness at baseline, neuroanatomical development, and follow-up. These profiles were enriched for genes previously associated with autism and for genes previously linked to neurobiological pathways implicated in autism (e.g. excitation-inhibition systems). Our findings suggest that distinct clinical outcomes (i.e. intra-individual change in clinical profiles) linked to autism core symptoms are associated with atypical cross-sectional and longitudinal, i.e. developmental, neurobiological profiles. If validated, our findings may advance the development of interventions, e.g. targeting mechanisms linked to relatively poorer outcomes.

Examining volumetric gradients based on the frustum surface ratio in the brain in autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is accompanied by neurodevelopmental differences in regional cortical volume (CV), and a potential layer-specific pathology. Conventional measures of CV, however, do not indicate how volume is distributed across cortical layers. In a sample of 92 typically developing (TD) controls and 92 adult individuals with ASD (aged 18-52 years), we examined volumetric gradients by quantifying the degree to which CV is weighted from the pial to the white surface of the brain. Overall, the spatial distribution of Frustum Surface Ratio (FSR) followed the gyral and sulcal pattern of the cortex and approximated a bimodal Gaussian distribution caused by a linear mixture of vertices on gyri and sulci. Measures of FSR were highly correlated with vertex-wise estimates of mean curvature, sulcal depth, and pial surface area, although none of these features explained more than 76% variability in FSR on their own. Moreover, in ASD, we observed a pattern of predominant increases in the degree of FSR relative to TD controls, with an atypical neurodevelopmental trajectory. Our findings suggest a more outward-weighted gradient of CV in ASD, which may indicate a larger contribution of supragranular layers to regional differences in CV.

Atypical measures of diffusion at the gray-white matter boundary in autism spectrum disorder in adulthood.

Autism spectrum disorder (ASD) is a highly complex neurodevelopmental condition that is accompanied by neuroanatomical differences on the macroscopic and microscopic level. Findings from histological, genetic, and more recently in vivo neuroimaging studies converge in suggesting that neuroanatomical abnormalities, specifically around the gray-white matter (GWM) boundary, represent a crucial feature of ASD. However, no research has yet characterized the GWM boundary in ASD based on measures of diffusion. Here, we registered diffusion tensor imaging data to the structural T1-weighted images of 92 adults with ASD and 92 matched neurotypical controls in order to examine between-group differences and group-by-sex interactions in fractional anisotropy and mean diffusivity sampled at the GWM boundary, and at different sampling depths within the superficial white and into the gray matter. As hypothesized, we observed atypical diffusion at and around the GWM boundary in ASD, with between-group differences and group-by-sex interactions depending on tissue class and sampling depth. Furthermore, we identified that altered diffusion at the GWM boundary partially (i.e., ~50%) overlapped with atypical gray-white matter tissue contrast in ASD. Our study thus replicates and extends previous work highlighting the GWM boundary as a crucial target of neuropathology in ASD, and guides future work elucidating etiological mechanisms.

Patterns of Cortical Folding Associated with Autistic Symptoms in Carriers and Noncarriers of the 22q11.2 Microdeletion.

22q11.2 deletion syndrome (22q11.2DS) is a genetic condition accompanied by a range of psychiatric manifestations, including autism spectrum disorder (ASD). It remains unknown, however, whether these symptoms are mediated by the same or distinct neural mechanisms as in idiopathic ASD. Here, we examined differences in lGI associated with ASD in 50 individuals with 22q11.2DS (n = 25 with ASD, n = 25 without ASD) and 81 individuals without 22q11.2DS (n = 40 with ASD, n = 41 typically developing controls). We initially utilized a factorial design to identify the set of brain regions where lGI is associated with the main effect of 22q11.2DS, ASD, and with the 22q11.2DS-by-ASD interaction term. Subsequently, we employed canonical correlation analysis (CCA) to compare the multivariate association between variability in lGI and the complex clinical phenotype of ASD between 22q11.2DS carriers and noncarriers. Across approaches, we established that even though there is a high degree of clinical similarity across groups, the associated patterns of lGI significantly differed between carriers and noncarriers of the 22q11.2 microdeletion. Our results suggest that ASD symptomatology recruits different neuroanatomical underpinnings across disorders and that 22q11.2DS individuals with ASD represent a neuroanatomically distinct subgroup that differs from 22q11.2DS individuals without ASD and from individuals with idiopathic ASD.

Down syndrome is accompanied by significantly reduced cortical grey-white matter tissue contrast.

Increased cortical thickness (CT) has been reported in Down syndrome (DS) during childhood and adolescence, but it remains unclear, which components of the neural architecture underpin these increases and if CT remains altered in adults. Among other factors, differences in CT measures could be driven by reduced tissue contrast between grey and white matter (GWC), which has been reported in neurodegenerative disorders, such as Alzheimer's disease. Using structural magnetic resonance imaging, we therefore examined differences in CT and GWC in 26 adults with DS, and 23 controls, to (1) examine between-group differences in CT in adulthood, (2) establish whether DS is associated with significant reductions in GWC, and (3) determine the influence of GWC variability on between-group differences in CT. As hypothesized, we observed that DS was accompanied by wide-spread increases in CT, and significantly reduced GWC in several large clusters distributed across the cortex. Out of all vertices with a significant between-group difference in CT, 38.50% also displayed a significant reduction in GWC. This percentage of overlap was also statistically significant and extremely unlikely to be obtained by chance (p = .0002). Differences in GWC thus seem to explain some, although not all, of the differences in CT observed in DS. In addition, our study is the first to extend previous in vivo reports of altered CT in DS during childhood and adolescence to older adults, implying that the regional pattern of neuroanatomical differences associated with DS remains stable across the lifespan.

The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings.

BACKGROUND: Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings. METHODS: We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings. RESULTS: In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD-but not for ADHD-related genes. LIMITATIONS: Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting. CONCLUSION: Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.

Neurobiological Correlates of Change in Adaptive Behavior in Autism.

OBJECTIVE: Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that is associated with significant difficulties in adaptive behavior and variation in clinical outcomes across the life span. Some individuals with ASD improve, whereas others may not change significantly, or regress. Hence, the development of "personalized medicine" approaches is essential. However, this requires an understanding of the biological processes underpinning differences in clinical outcome, at both the individual and subgroup levels, across the lifespan. METHODS: The authors conducted a longitudinal follow-up study of 483 individuals (204 with ASD and 279 neurotypical individuals, ages 6-30 years), with assessment time points separated by ∼12-24 months. Data collected included behavioral data (Vineland Adaptive Behavior Scale-II), neuroanatomical data (structural MRI), and genetic data (DNA). Individuals with ASD were grouped into clinically meaningful "increasers," "no-changers," and "decreasers" in adaptive behavior. First, the authors compared neuroanatomy between outcome groups. Next, they examined whether deviations from the neurotypical neuroanatomical profile were associated with outcome at the individual level. Finally, they explored the observed neuroanatomical differences' potential genetic underpinnings. RESULTS: Outcome groups differed in neuroanatomical features (cortical volume and thickness, surface area), including in "social brain" regions previously implicated in ASD. Also, deviations of neuroanatomical features from the neurotypical profile predicted outcome at the individual level. Moreover, neuroanatomical differences were associated with genetic processes relevant to neuroanatomical phenotypes (e.g., synaptic development). CONCLUSIONS: This study demonstrates, for the first time, that variation in clinical (adaptive) outcome is associated with both group- and individual-level variation in anatomy of brain regions enriched for genes relevant to ASD. This may facilitate the move toward better targeted/precision medicine approaches.

Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder.

OBJECTIVE: Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions. METHODS: The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features. RESULTS: In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission. CONCLUSIONS: The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Longitudinal Changes in Cortical Thickness in Adolescents with Autism Spectrum Disorder and Their Association with Restricted and Repetitive Behaviors.

The neuroanatomy of autism spectrum disorder (ASD) shows highly heterogeneous developmental trajectories across individuals. Mapping atypical brain development onto clinical phenotypes, and establishing their molecular underpinnings, is therefore crucial for patient stratification and subtyping. In this longitudinal study we examined intra- and inter-individual differences in the developmental trajectory of cortical thickness (CT) in childhood and adolescence, and their genomic underpinnings, in 33 individuals with ASD and 37 typically developing controls (aged 11-18 years). Moreover, we aimed to link regional atypical CT development to intra-individual variations in restricted and repetitive behavior (RRB) over a two-year time period. Individuals with ASD showed significantly reduced cortical thinning in several of the brain regions functionally related to wider autism symptoms and traits (e.g., fronto-temporal and cingulate cortices). The spatial patterns of the neuroanatomical differences in CT were enriched for genes known to be associated with ASD at a genetic and transcriptomic level. Further, intra-individual differences in CT correlated with within-subject variability in the severity of RRBs. Our findings represent an important step towards characterizing the neuroanatomical underpinnings of ASD across development based upon measures of CT. Moreover, our findings provide important novel insights into the link between microscopic and macroscopic pathology in ASD, as well as their relationship with different clinical ASD phenotypes.

Neuroanatomical underpinnings of autism symptomatology in carriers and non-carriers of the 22q11.2 microdeletion.

BACKGROUND: A crucial step to understanding the mechanistic underpinnings of autism spectrum disorder (ASD), is to examine if the biological underpinnings of ASD in genetic high-risk conditions, like 22q11.2 deletion syndrome (22q11.2DS), are similar to those in idiopathic illness. This study aimed to examine if ASD symptomatology in 22q11.2DS is underpinned by the same-or distinct-neural systems that mediate these symptoms in non-deletion carriers. METHODS: We examined vertex-wise estimates of cortical volume (CV), surface area (SA), and cortical thickness across 131 individuals between 6 and 25 years of age including (1) 50 individuals with 22q11.2DS, out of which n = 25 had a diagnosis of ASD, (2) 40 non-carriers of the microdeletion with a diagnosis of ASD (i.e., idiopathic ASD), and (3) 41 typically developing (TD) controls. We employed a 2-by-2 factorial design to identify neuroanatomical variability associated with the main effects of 22q11.2DS and ASD, as well as their interaction. Further, using canonical correlation analysis (CCA), we compared neuroanatomical variability associated with the complex (i.e., multivariate) clinical phenotype of ASD between 22q11.2 deletion carriers and non-carriers. RESULTS: The set of brain regions associated with the main effect of 22q11.2DS was distinct from the neuroanatomical underpinnings of the main effect of ASD. Moreover, significant 22q11.2DS-by-ASD interactions were observed for CV and SA in the dorsolateral prefrontal cortex, precentral gyrus, and posterior cingulate cortex, suggesting that the neuroanatomy of ASD is significantly modulated by 22q11.2DS (p < 0.01). We further established that the multivariate patterns of neuroanatomical variability associated with differences in symptom profiles significantly differed between 22q11.2 deletion carriers and non-carriers. LIMITATIONS: We employed a multicenter design to overcome single-site recruitment limitations; however, FreeSurfer-derived measures of surface anatomy have been shown to be highly reliable across scanner platforms and field strengths. Further, we controlled for gender to address the differing distribution between idiopathic ASD individuals and the other groups. Nonetheless, the gender distribution in our sample reflects that of the respective populations, adding to the generalizability of our results. Last, we included individuals with a relatively wide age range (i.e., 6-25 years). CONCLUSIONS: Our findings indicate that neuroanatomical correlates of ASD symptomatology in carriers of the 22q11.2 microdeletion diverge from those in idiopathic ASD.

The effect of age on vertex-based measures of the grey-white matter tissue contrast in autism spectrum disorder.

Background: Histological evidence suggests that autism spectrum disorder (ASD) is accompanied by a reduced integrity of the grey-white matter boundary. This has also recently been confirmed by a structural neuroimaging study in vivo reporting significantly reduced grey-white matter tissue contrast (GWC) in adult individuals (18-42 years of age) with ASD relative to typically developing (TD) controls. However, it remains unknown whether the neuroanatomical differences in ASD at the grey-white matter boundary are stable across development or are age-dependent. Methods: Here, we examined differences in the neurodevelopmental trajectories of GWC in a cross-sectional sample of 77 male ASD individuals and 76 typically developing (TD) controls across childhood and early adulthood (from 7 to 25 years). Results: Using nested model comparisons, we first established that the developmental trajectory of GWC is complex in many regions across the cortex and includes linear and non-linear effects of age. Second, while ASD individuals have significantly reduced GWC overall, these differences are age-dependent and are most prominent during childhood (< 15 years). Conclusions: Taken together, our findings suggest that differences in GWC in ASD are unlikely to reflect atypical grey matter cytoarchitecture alone, but may also represent other aspects of the cortical architecture such as age-dependent variability in myelin integrity.

Visual event-related potentials to biological motion stimuli in autism spectrum disorders.

Atypical visual processing of biological motion contributes to social impairments in autism spectrum disorders (ASD). However, the exact temporal sequence of deficits of cortical biological motion processing in ASD has not been studied to date. We used 64-channel electroencephalography to study event-related potentials associated with human motion perception in 17 children and adolescents with ASD and 21 typical controls. A spatio-temporal source analysis was performed to assess the brain structures involved in these processes. We expected altered activity already during early stimulus processing and reduced activity during subsequent biological motion specific processes in ASD. In response to both, random and biological motion, the P100 amplitude was decreased suggesting unspecific deficits in visual processing, and the occipito-temporal N200 showed atypical lateralization in ASD suggesting altered hemispheric specialization. A slow positive deflection after 400 ms, reflecting top-down processes, and human motion-specific dipole activation differed slightly between groups, with reduced and more diffuse activation in the ASD-group. The latter could be an indicator of a disrupted neuronal network for biological motion processing in ADS. Furthermore, early visual processing (P100) seems to be correlated to biological motion-specific activation. This emphasizes the relevance of early sensory processing for higher order processing deficits in ASD.