Diffusion Tensor Imaging Provides Evidence of Possible Axonal Overconnectivity in Frontal Lobes in Autism Spectrum Disorder Toddlers.

BACKGROUND: Theories of brain abnormality in autism spectrum disorder (ASD) have focused on underconnectivity as an explanation for social, language, and behavioral deficits but are based mainly on studies of older autistic children and adults. METHODS: In 94 ASD and typical toddlers ages 1 to 4 years, we examined the microstructure (indexed by fractional anisotropy) and volume of axon pathways using in vivo diffusion tensor imaging of fronto-frontal, fronto-temporal, fronto-striatal, and fronto-amygdala axon pathways, as well as posterior contrast tracts. Differences between ASD and typical toddlers in the nature of the relationship of age to these measures were tested. RESULTS: Frontal tracts in ASD toddlers displayed abnormal age-related changes with greater fractional anisotropy and volume than normal at younger ages but an overall slower than typical apparent rate of continued development across the span of years. Posterior cortical contrast tracts had few significant abnormalities. CONCLUSIONS: Frontal fiber tracts displayed deviant early development and age-related changes that could underlie impaired brain functioning and impact social and communication behaviors in ASD.

Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers.

Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi-tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment.

Different functional neural substrates for good and poor language outcome in autism.

Autism (ASD) is vastly heterogeneous, particularly in early language development. While ASD language trajectories in the first years of life are highly unstable, by early childhood these trajectories stabilize and are predictive of longer-term outcome. Early neural substrates that predict/precede such outcomes are largely unknown, but could have considerable translational and clinical impact. Pre-diagnosis fMRI response to speech in ASD toddlers with relatively good language outcome was highly similar to non-ASD comparison groups and robustly recruited language-sensitive superior temporal cortices. In contrast, language-sensitive superior temporal cortices were hypoactive in ASD toddlers with poor language outcome. Brain-behavioral relationships were atypically reversed in ASD, and a multimodal combination of pre-diagnostic clinical behavioral measures and speech-related fMRI response showed the most promise as an ASD prognosis classifier. Thus, before ASD diagnoses and outcome become clinically clear, distinct functional neuroimaging phenotypes are already present that can shed insight on an ASD toddler's later outcome. VIDEO ABSTRACT.

Prediction of autism by translation and immune/inflammation coexpressed genes in toddlers from pediatric community practices.

IMPORTANCE: The identification of genomic signatures that aid early identification of individuals at risk for autism spectrum disorder (ASD) in the toddler period remains a major challenge because of the genetic and phenotypic heterogeneity of the disorder. Generally, ASD is not diagnosed before the fourth to fifth birthday. OBJECTIVE: To apply a functional genomic approach to identify a biologically relevant signature with promising performance in the diagnostic classification of infants and toddlers with ASD. DESIGN, SETTING, AND PARTICIPANTS: Proof-of-principle study of leukocyte RNA expression levels from 2 independent cohorts of children aged 1 to 4 years (142 discovery participants and 73 replication participants) using Illumina microarrays. Coexpression analysis of differentially expressed genes between Discovery ASD and control toddlers were used to define gene modules and eigengenes used in a diagnostic classification analysis. Independent validation of the classifier performance was tested on the replication cohort. Pathway enrichment and protein-protein interaction analyses were used to confirm biological relevance of the functional networks in the classifier. Participant recruitment occurred in general pediatric clinics and community settings. Male infants and toddlers (age range, 1-4 years) were enrolled in the study. Recruitment criteria followed the 1-Year Well-Baby Check-Up Approach. Diagnostic judgment followed DSM-IV-TR and Autism Diagnostic Observation Schedule criteria for autism. Participants with ASD were compared with control groups composed of typically developing toddlers as well as toddlers with global developmental or language delay. MAIN OUTCOMES AND MEASURES: Logistic regression and receiver operating characteristic curve analysis were used in a classification test to establish the accuracy, specificity, and sensitivity of the module-based classifier. RESULTS: Our signature of differentially coexpressed genes was enriched in translation and immune/inflammation functions and produced 83% accuracy. In an independent test with approximately half of the sample and a different microarray, the diagnostic classification of ASD vs control samples was 75% accurate. Consistent with its ASD specificity, our signature did not distinguish toddlers with global developmental or language delay from typically developing toddlers (62% accuracy). CONCLUSIONS AND RELEVANCE: This proof-of-principle study demonstrated that genomic biomarkers with very good sensitivity and specificity for boys with ASD in general pediatric settings can be identified. It also showed that a blood-based clinical test for at-risk male infants and toddlers could be refined and routinely implemented in pediatric diagnostic settings.

Neuron number and size in prefrontal cortex of children with autism.

CONTEXT: Autism often involves early brain overgrowth, including the prefrontal cortex (PFC). Although prefrontal abnormality has been theorized to underlie some autistic symptoms, the cellular defects that cause abnormal overgrowth remain unknown. OBJECTIVE: To investigate whether early brain overgrowth in children with autism involves excess neuron numbers in the PFC. DESIGN, SETTING, AND CASES: Postmortem prefrontal tissue from 7 autistic and 6 control male children aged 2 to 16 years was examined by expert anatomists who were blinded to diagnostic status. Number and size of neurons were quantified using stereological methods within the dorsolateral (DL-PFC) and mesial (M-PFC) subdivisions of the PFC. Cases were from the eastern and southeastern United States and died between 2000 and 2006. MAIN OUTCOME MEASURES: Mean neuron number and size in the DL-PFC and M-PFC were compared between autistic and control postmortem cases. Correlations of neuron number with deviation in brain weight from normative values for age were also performed. RESULTS: Children with autism had 67% more neurons in the PFC (mean, 1.94 billion; 95% CI, 1.57-2.31) compared with control children (1.16 billion; 95% CI, 0.90-1.42; P = .002), including 79% more in DL-PFC (1.57 billion; 95% CI, 1.20-1.94 in autism cases vs 0.88 billion; 95% CI, 0.66-1.10 in controls; P = .003) and 29% more in M-PFC (0.36 billion; 95% CI, 0.33-0.40 in autism cases vs 0.28 billion; 95% CI, 0.23-0.34 in controls; P = .009). Brain weight in the autistic cases differed from normative mean weight for age by a mean of 17.6% (95% CI, 10.2%-25.0%; P = .001), while brains in controls differed by a mean of 0.2% (95% CI, -8.7% to 9.1%; P = .96). Plots of counts by weight showed autistic children had both greater total prefrontal neuron counts and brain weight for age than control children. CONCLUSION: In this small preliminary study, brain overgrowth in males with autism involved an abnormal excess number of neurons in the PFC.