Regional and cellular organization of the autism-associated protein UBE3A/E6AP and its antisense transcript in the brain of the developing rhesus monkey.

Angelman syndrome (AS) is a neurogenetic disorder caused by mutations or deletions in the maternally-inherited UBE3A allele, leading to a loss of UBE3A protein expression in neurons. The paternally-inherited UBE3A allele is epigenetically silenced in neurons during development by a noncoding transcript (UBE3A-ATS). The absence of neuronal UBE3A results in severe neurological symptoms, including speech and language impairments, intellectual disability, and seizures. While no cure exists, therapies aiming to restore UBE3A function-either by gene addition or by targeting UBE3A-ATS-are under development. Progress in developing these treatments relies heavily on inferences drawn from mouse studies about the function of UBE3A in the human brain. To aid translational efforts and to gain an understanding of UBE3A and UBE3A-ATS biology with greater relevance to human neurodevelopmental contexts, we investigated UBE3A and UBE3A-ATS expression in the developing brain of the rhesus macaque, a species that exhibits complex social behaviors, resembling aspects of human behavior to a greater degree than mice. Combining immunohistochemistry and in situ hybridization, we mapped UBE3A and UBE3A-ATS regional and cellular expression in normal prenatal, neonatal, and adolescent rhesus macaque brains. We show that key hallmarks of UBE3A biology, well-known in rodents, are also present in macaques, and suggest paternal UBE3A silencing in neurons-but not glial cells-in the macaque brain, with onset between gestational day 48 and 100. These findings support proposals that early-life, perhaps even prenatal, intervention is optimal for overcoming the maternal allele loss of UBE3A linked to AS.

Sex differences in trajectories of cortical development in autistic children from 2-13 years of age.

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 Severity and its Relationship to Disability.

Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken by The Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments. Lay Summary: The severity of a person's autism is currently defined based on the severity of their core autism symptoms: impaired social-communication and the presence of restricted or repetitive patterns of behaviors and interests. But autistic people often face additional challenges such as intellectual disability, epilepsy, and anxiety disorder, that considerably impact their everyday life, wellbeing, and the need for support. A more complete view of autism severity, one that includes core symptoms as well as additional challenges, could help identify meaningful sub-groups of autistic individuals and could be useful in clinical care. Appeared originally in Autism Res 2023; 16:685-696.

The analysis of H.M.'s brain: A brief review of status and plans for future studies and tissue archive.

The famous amnesic patient Henry Molaison (H.M.) died on December 2, 2008. After extensive in situ magnetic resonance imaging in Boston, his brain was removed at autopsy and transported to the University of California San Diego. There the brain was prepared for frozen sectioning and cut into 2401, 70 µm coronal slices. While preliminary analyses of the brain sections have been reported, a comprehensive microscopic neuroanatomical analysis of the state of H.M.'s brain at the time of his death has not yet been published. The brain tissue and slides were subsequently moved to the University of California Davis and the slides digitized at high resolution. Initial stages of producing a website for the public viewing of the images were also carried out. Recently, the slides, digital images, and tissue have been transferred to Boston University for permanent archiving. A new steering committee has been established and plans are in place for completion of a freely accessible H.M. website. Research publications on the microscopic anatomy and neuropathology of H.M.'s brain at the time of his death are also planned. We write this commentary to provide the hippocampus and memory neuroscience communities with a brief summary of what has transpired following H.M.'s death and outline plans for future publications and a tissue archive.

Metabolomic biomarkers in autism: identification of complex dysregulations of cellular bioenergetics.

Autism Spectrum Disorder (ASD or autism) is a phenotypically and etiologically heterogeneous condition. Identifying biomarkers of clinically significant metabolic subtypes of autism could improve understanding of its underlying pathophysiology and potentially lead to more targeted interventions. We hypothesized that the application of metabolite-based biomarker techniques using decision thresholds derived from quantitative measurements could identify autism-associated subpopulations. Metabolomic profiling was carried out in a case-control study of 499 autistic and 209 typically developing (TYP) children, ages 18-48 months, enrolled in the Children's Autism Metabolome Project (CAMP; ClinicalTrials.gov Identifier: NCT02548442). Fifty-four metabolites, associated with amino acid, organic acid, acylcarnitine and purine metabolism as well as microbiome-associated metabolites, were quantified using liquid chromatography-tandem mass spectrometry. Using quantitative thresholds, the concentrations of 4 metabolites and 149 ratios of metabolites were identified as biomarkers, each identifying subpopulations of 4.5-11% of the CAMP autistic population. A subset of 42 biomarkers could identify CAMP autistic individuals with 72% sensitivity and 90% specificity. Many participants were identified by several metabolic biomarkers. Using hierarchical clustering, 30 clusters of biomarkers were created based on participants' biomarker profiles. Metabolic changes associated with the clusters suggest that altered regulation of cellular metabolism, especially of mitochondrial bioenergetics, were common metabolic phenotypes in this cohort of autistic participants. Autism severity and cognitive and developmental impairment were associated with increased lactate, many lactate containing ratios, and the number of biomarker clusters a participant displayed. These studies provide evidence that metabolic phenotyping is feasible and that defined autistic subgroups can lead to enhanced understanding of the underlying pathophysiology and potentially suggest pathways for targeted metabolic treatments.

Changes in the severity of autism symptom domains are related to mental health challenges during middle childhood.

LAY ABSTRACT: For many autistic children, the severity of their autism symptoms changes during middle childhood. We studied whether these changes are associated with the emergence of other mental health challenges such as anxiety and attention-deficit hyperactivity disorder. Children who had increased social-communication challenges had more anxiety and attention-deficit hyperactivity disorder symptoms and disruptive behavior problems than other children. Children who decreased their restricted and repetitive behaviors, on the contrary, had more anxiety. We discuss why these changes in autism symptoms may lead to increases in other mental health concerns.

IQ trajectories in autistic children through preadolescence.

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 with repeated measures with pairwise testing, multinomial logistic regression models, and sensitivity analyses. Results: We isolated three IQ trajectories 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 at T3, 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.

Structural plasticity in the entorhinal and perirhinal cortices following hippocampal lesions in rhesus monkeys.

Immature neurons expressing the Bcl2 protein are present in various regions of the mammalian brain, including the amygdala and the entorhinal and perirhinal cortices. Their functional role is unknown but we have previously shown that neonatal and adult hippocampal lesions increase their differentiation in the monkey amygdala. Here, we assessed whether hippocampal lesions similarly affect immature neurons in the entorhinal and perirhinal cortices. Since Bcl2-positive cells were found mainly in areas Eo, Er, and Elr of the entorhinal cortex and in layer II of the perirhinal cortex, we also used Nissl-stained sections to determine the number and soma size of immature and mature neurons in layer III of area Er and layer II of area 36 of the perirhinal cortex. We found different structural changes in these regions following hippocampal lesions, which were influenced by the time of the lesion. In neonate-lesioned monkeys, the number of immature neurons in the entorhinal and perirhinal cortices was generally higher than in controls. The number of mature neurons was also higher in layer III of area Er of neonate-lesioned monkeys but no differences were found in layer II of area 36. In adult-lesioned monkeys, the number of immature neurons in the entorhinal cortex was lower than in controls but did not differ from controls in the perirhinal cortex. The number of mature neurons in layer III of area Er did not differ from controls, but the number of small, mature neurons in layer II of area 36 was lower than in controls. In sum, hippocampal lesions impacted populations of mature and immature neurons in discrete regions and layers of the entorhinal and perirhinal cortices, which are interconnected with the amygdala and provide major cortical inputs to the hippocampus. These structural changes may contribute to some functional recovery following hippocampal injury in an age-dependent manner.

Translational Neuroscience Approaches to Understanding Autism.

While autism spectrum disorder affects nearly 2% of children in the United States, little is known with certainty concerning the etiologies and brain systems involved. This is due, in part, to the substantial heterogeneity in the presentation of the core symptoms of autism as well as the great number of co-occurring conditions that are common in autistic individuals. Understanding the neurobiology of autism is further hampered by the limited availability of postmortem brain tissue to determine the cellular and molecular alterations that take place in the autistic brain. Animal models therefore provide great translational value in helping to define the neural systems that constitute the social brain and mediate repetitive behaviors or interests. If they are based on genetic or environmental factors that contribute to autism, organisms from flies to nonhuman primates may serve as models of the neural structure or function of the autistic brain. Ultimately, successful models can also be employed to test the safety and effectiveness of potential therapeutics. This is an overview of the major animal species that are currently used as models of autism, including an appraisal of the advantages and limitations of each.

Autism severity and its relationship to disability.

Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken byThe Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments.

Patterns of sensory processing in young children with autism: Differences in autism characteristics, adaptive skills, and attentional problems.

LAY ABSTRACT: Research has found differences in responding to various sensory stimuli among autistic individuals, which are associated with social and adaptive skills. However, our understanding of sensory profiles in autism has been complicated due to the variable presentation of sensory symptoms. One way to better understand variability in sensory symptoms is to use advanced statistical approaches, such as latent profile analysis, that allow for the identification of more similar sensory classes in otherwise variable groups. We used the Short Sensory Profile to identify homogeneous classes of sensory reactivity in autistic children based on both severity and modality and examined whether sensory classes differed in terms of autism characteristics, adaptive skills, and attention-deficit/hyperactivity disorder symptoms. Based on the pattern of both severity and modality, four sensory classes emerged and were named Moderate/Mixed (35.5%; probable-to-definite differences in all modalities except in movement sensitivity and low energy/weakness), Severe/Mixed (8.5%; definite sensory differences in all modalities except in low energy/weakness), Moderate/Broad (14.6%; probable-to-definite differences in all modalities), and Low/Mixed (41.1%; typical scores in most modalities with probable differences in taste/smell sensitivity, under-responsive/seeks sensation, and auditory filtering). The Severe/Mixed class exhibited greater problems in a variety of areas such as social, adaptive, and attention-deficit/hyperactivity disorder symptoms, whereas the Low/Mixed class showed overall fewer problems. This may provide insight for clinicians and researchers aiming to understand whether autistic children who exhibit distinct sensory patterns are more or less likely to also experience social, adaptive, and/or attention/behavior-related difficulties.

Default mode and fronto-parietal network associations with IQ development across childhood in autism.

BACKGROUND: Intellectual disability affects approximately one third of individuals with autism spectrum disorder (autism). Yet, a major unresolved neurobiological question is what differentiates autistic individuals with and without intellectual disability. Intelligence quotients (IQs) are highly variable during childhood. We previously identified three subgroups of autistic children with different trajectories of intellectual development from early (2-3½ years) to middle childhood (9-12 years): (a) persistently high: individuals whose IQs remained in the normal range; (b) persistently low: individuals whose IQs remained in the range of intellectual disability (IQ < 70); and (c) changers: individuals whose IQs began in the range of intellectual disability but increased to the normal IQ range. The frontoparietal (FPN) and default mode (DMN) networks have established links to intellectual functioning. Here, we tested whether brain regions within the FPN and DMN differed volumetrically between these IQ trajectory groups in early childhood. METHODS: We conducted multivariate distance matrix regression to examine the brain regions within the FPN (11 regions x 2 hemispheres) and the DMN (12 regions x 2 hemispheres) in 48 persistently high (18 female), 108 persistently low (32 female), and 109 changers (39 female) using structural MRI acquired at baseline. FPN and DMN regions were defined using networks identified in Smith et al. (Proc Natl Acad Sci U S A 106:13040-5, 2009). IQ trajectory groups were defined by IQ measurements from up to three time points spanning early to middle childhood (mean age time 1: 3.2 years; time 2: 5.4 years; time 3: 11.3 years). RESULTS: The changers group exhibited volumetric differences in the DMN compared to both the persistently low and persistently high groups at time 1. However, the persistently high group did not differ from the persistently low group, suggesting that DMN structure may be an early predictor for change in IQ trajectory. In contrast, the persistently high group exhibited differences in the FPN compared to both the persistently low and changers groups, suggesting differences related more to concurrent IQ and the absence of intellectual disability. CONCLUSIONS: Within autism, volumetric differences of brain regions within the DMN in early childhood may differentiate individuals with persistently low IQ from those with low IQ that improves through childhood. Structural differences in brain networks between these three IQ-based subgroups highlight distinct neural underpinnings of these autism sub-phenotypes.

Altered Development of Amygdala-Connected Brain Regions in Males and Females with Autism.

Altered amygdala development is implicated in the neurobiology of autism, but little is known about the coordinated development of the brain regions directly connected with the amygdala. Here we investigated the volumetric development of an amygdala-connected network, defined as the set of brain regions with monosynaptic connections with the amygdala, in autism from early to middle childhood. A total of 950 longitudinal structural MRI scans were acquired from 282 children (93 female) with autism and 128 children with typical development (61 female) at up to four time points (mean ages: 39, 52, 64, and 137 months, respectively). Volumes from 32 amygdala-connected brain regions were examined using mixed effects multivariate distance matrix regression. The Social Responsiveness Scale-2 was administered to assess degree of autistic traits and social impairments. The amygdala-connected network exhibited persistent diagnostic differences (p values ≤ 0.03) that increased over time (p values ≤ 0.02). These differences were most prominent in autistics with more impacted social functioning at baseline. This pattern was not observed across regions without monosynaptic amygdala connection. We observed qualitative sex differences. In males, the bilateral subgenual anterior cingulate cortices were most affected, while in females the left fusiform and superior temporal gyri were most affected. In conclusion, (1) autism is associated with widespread alterations to the development of brain regions connected with the amygdala, which were associated with autistic social behaviors; and (2) autistic males and females exhibited different patterns of alterations, adding to a growing body of evidence of sex differences in the neurobiology of autism.SIGNIFICANCE STATEMENT Global patterns of development across brain regions with monosynaptic connection to the amygdala differentiate autism from typical development, and are modulated by social functioning in early childhood. Alterations to brain regions within the amygdala-connected network differed in males and females with autism. Results also indicate larger volumetric differences in regions having monosynaptic connection with the amygdala than in regions without monosynaptic connection.

Sex-dependent structure of socioemotional salience, executive control, and default mode networks in preschool-aged children with 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.

Association of Amygdala Development With Different Forms of Anxiety in Autism Spectrum Disorder.

BACKGROUND: The amygdala is widely implicated in both anxiety and autism spectrum disorder. However, no studies have investigated the relationship between co-occurring anxiety and longitudinal amygdala development in autism. Here, the authors characterize amygdala development across childhood in autistic children with and without traditional DSM forms of anxiety and anxieties distinctly related to autism. METHODS: Longitudinal magnetic resonance imaging scans were acquired at up to four time points for 71 autistic and 55 typically developing (TD) children (∼2.5-12 years, 411 time points). Traditional DSM anxiety and anxieties distinctly related to autism were assessed at study time 4 (∼8-12 years) using a diagnostic interview tailored to autism: the Anxiety Disorders Interview Schedule-IV with the Autism Spectrum Addendum. Mixed-effects models were used to test group differences at study time 1 (3.18 years) and time 4 (11.36 years) and developmental differences (age-by-group interactions) in right and left amygdala volume between autistic children with and without DSM or autism-distinct anxieties and TD children. RESULTS: Autistic children with DSM anxiety had significantly larger right amygdala volumes than TD children at both study time 1 (5.10% increase) and time 4 (6.11% increase). Autistic children with autism-distinct anxieties had significantly slower right amygdala growth than TD, autism-no anxiety, and autism-DSM anxiety groups and smaller right amygdala volumes at time 4 than the autism-no anxiety (-8.13% decrease) and autism-DSM anxiety (-12.05% decrease) groups. CONCLUSIONS: Disparate amygdala volumes and developmental trajectories between DSM and autism-distinct forms of anxiety suggest different biological underpinnings for these common, co-occurring conditions in autism.

Social housing status impacts rhesus monkeys' affective responding in classic threat processing tasks.

Individuals' social contexts are broadly recognized to impact both their psychology and neurobiology. These effects are observed in people and in nonhuman animals who are the subjects for comparative and translational science. The social contexts in which monkeys are reared have long been recognized to have significant impacts on affective processing. Yet, the social contexts in which monkeys live as adults are often ignored and could have important consequences for interpreting findings, particularly those related to biopsychiatry and behavioral neuroscience studies. The extant nonhuman primate neuropsychological literature has historically tested individually-housed monkeys, creating a critical need to understand how social context might impact the outcomes of such experiments. We evaluated affective responding in adult rhesus monkeys living in four different social contexts using two classic threat processing tasks-a test of responsivity to objects and a test of responsivity to an unfamiliar human. These tasks have been commonly used in behavioral neuroscience for decades. Relative to monkeys with full access to a social partner, individually-housed monkeys had blunted reactivity to threat and monkeys who had limited contact with their partner were more reactive to some threatening stimuli. These results indicate that monkeys' social housing contexts impact affective reactivity and point to the potential need to reconsider inferences drawn from prior studies in which the impacts of social context have not been considered.