Contributions to auditory system conduction velocity: insights with multi-modal neuroimaging and machine learning in children with ASD and XYY syndrome.

Introduction: The M50 electrophysiological auditory evoked response time can be measured at the superior temporal gyrus with magnetoencephalography (MEG) and its latency is related to the conduction velocity of auditory input passing from ear to auditory cortex. In children with autism spectrum disorder (ASD) and certain genetic disorders such as XYY syndrome, the auditory M50 latency has been observed to be elongated (slowed). Methods: The goal of this study is to use neuroimaging (diffusion MR and GABA MRS) measures to predict auditory conduction velocity in typically developing (TD) children and children with autism ASD and XYY syndrome. Results: Non-linear TD support vector regression modeling methods accounted for considerably more M50 latency variance than linear models, likely due to the non-linear dependence on neuroimaging factors such as GABA MRS. While SVR models accounted for ~80% of the M50 latency variance in TD and the genetically homogenous XYY syndrome, a similar approach only accounted for ~20% of the M50 latency variance in ASD, implicating the insufficiency of diffusion MR, GABA MRS, and age factors alone. Biologically based stratification of ASD was performed by assessing the conformance of the ASD population to the TD SVR model and identifying a sub-population of children with unexpectedly long M50 latency. Discussion: Multimodal integration of neuroimaging data can help build a mechanistic understanding of brain connectivity. The unexplained M50 latency variance in ASD motivates future hypothesis generation and testing of other contributing biological factors.

Magnetoencephalography Studies of the Envelope Following Response During Amplitude-Modulated Sweeps: Diminished Phase Synchrony in Autism Spectrum Disorder.

Prevailing theories of the neural basis of at least a subset of individuals with autism spectrum disorder (ASD) include an imbalance of excitatory and inhibitory neurotransmission. These circuitry imbalances are commonly probed in adults using auditory steady-state responses (ASSR, driven at 40 Hz) to elicit coherent electrophysiological responses (EEG/MEG) from intact circuitry. Challenges to the ASSR methodology occur during development, where the optimal ASSR driving frequency may be unknown. An alternative approach (more agnostic to driving frequency) is the amplitude-modulated (AM) sweep in which the amplitude of a tone (with carrier frequency 500 Hz) is modulated as a sweep from 10 to 100 Hz over the course of ∼15 s. Phase synchrony of evoked responses, measured via intra-trial coherence, is recorded (by EEG or MEG) as a function of frequency. We applied such AM sweep stimuli bilaterally to 40 typically developing and 80 children with ASD, aged 6-18 years. Diagnoses were confirmed by DSM-5 criteria as well as autism diagnostic observation schedule (ADOS) observational assessment. Stimuli were presented binaurally during MEG recording and consisted of 20 AM swept stimuli (500 Hz carrier; sweep 10-100 Hz up and down) with a duration of ∼30 s each. Peak intra-trial coherence values and peak response frequencies of source modeled responses (auditory cortex) were examined. First, the phase synchrony or inter-trial coherence (ITC) of the ASSR is diminished in ASD; second, hemispheric bias in the ASSR, observed in typical development (TD), is maintained in ASD, and third, that the frequency at which the peak response is obtained varies on an individual basis, in part dependent on age, and with altered developmental trajectories in ASD vs. TD. Finally, there appears an association between auditory steady-state phase synchrony (taken as a proxy of neuronal circuitry integrity) and clinical assessment of language ability/impairment. We concluded that (1) the AM sweep stimulus provides a mechanism for probing ASSR in an unbiased fashion, during developmental maturation of peak response frequency, (2) peak frequencies vary, in part due to developmental age, and importantly, (3) ITC at this peak frequency is diminished in ASD, with the degree of ITC disturbance related to clinically assessed language impairment.

A Multimodal Study of the Contributions of Conduction Velocity to the Auditory Evoked Neuromagnetic Response: Anomalies in Autism Spectrum Disorder.

This multimodal imaging study used magnetoencephalography, diffusion magnetic resonance imaging (MRI), and gamma-aminobutyric acid (GABA) magnetic resonance spectroscopy (MRS) to identify and contrast the multiple physiological mechanisms associated with auditory processing efficiency in typically developing (TD) children and children with autism spectrum disorder (ASD). Efficient transmission of auditory input between the ear and auditory cortex is necessary for rapid encoding of auditory sensory information. It was hypothesized that the M50 auditory evoked response latency would be modulated by white matter microstructure (indexed by diffusion MRI) and by tonic inhibition (indexed by GABA MRS). Participants were 77 children diagnosed with ASD and 40 TD controls aged 7-17 years. A model of M50 latency with auditory radiation fractional anisotropy and age as independent variables was able to predict 52% of M50 latency variance in TD children, but only 12% of variance in ASD. The ASD group exhibited altered patterns of M50 latency modulation characterized by both higher variance and deviation from the expected structure-function relationship established with the TD group. The TD M50 latency model was used to identify a subpopulation of ASD who are significant "outliers" to the TD model. The ASD outlier group exhibited unexpectedly long M50 latencies in conjunction with significantly lower GABA levels. These findings indicate the dependence of electrophysiologic sensory response latency on underlying microstructure (white matter) and neurochemistry (synaptic activity). This study demonstrates the use of biologically based measures to stratify ASD according to their brain-level "building blocks" as an alternative to their behavioral phenotype. LAY SUMMARY: Children with ASD often have a slower brain response when hearing sounds. This study used multiple brain imaging techniques to examine the structural and neurochemical factors which control the brain's response time to auditory tones in children with ASD and TD children. The relationship between brain imaging measures and brain response time was also used to identify ASD subgroups. Autism Res 2020, 13: 1730-1745. © 2020 International Society for Autism Research and Wiley Periodicals LLC.

Developmental-Behavioral Pediatricians' Diagnosis and Coding of Overweight and Obesity in Children with Autism Spectrum Disorder.

OBJECTIVE: The prevalence of obesity in autism spectrum disorder (ASD) is high, and managing obesity in children with ASD can be challenging. The study's objective was to examine developmental-behavioral pediatricians' (DBPs) coding practices for overweight/obesity in children with ASD and patient characteristics associated with coding. METHODS: We analyzed the clinical data on children with ASD with at least 1 visit at one of 3 developmental-behavioral pediatrics network sites between January 2010 and December 2011. Weight status was calculated using body mass index z-scores. For children meeting the criteria for overweight/obesity, we assessed the frequency of weight-related ICD-9 diagnosis codes at DBP visits, used multivariable logistic regression to determine characteristics associated with the presence of these codes, and examined the prevalence of weight-related codes relative to other diagnosis codes. RESULTS: The sample included 4542 children, ages 2 to 19 years. 15.5% of children met the criteria for overweight, 14.7% for obesity, and 6.3% for severe obesity. Of children meeting the criteria for overweight/obesity/severe obesity, 7.5% had a weight-related code documented at their visits. Children with obesity or severe obesity and older children had higher odds of having a weight-related code. Compared with not being on medications, atypical antipsychotics use was significantly associated with increased odds of having a weight-related code. Of 3802 unique ICD-9 diagnosis codes documented at any visit during the study period, only 4% were related to weight. CONCLUSION: Few children meeting the criteria for overweight/obesity had documented weight-related codes. Weight-related coding was more likely for children with obesity, who were older, and those taking atypical antipsychotics.

Evaluating motor cortical oscillations and age-related change in autism spectrum disorder.

Autism spectrum disorder (ASD) is primarily characterized by impairments in social communication and the appearance of repetitive behaviors with restricted interests. Increasingly, evidence also points to a general deficit of motor tone and coordination in children and adults with ASD; yet the neural basis of motor functional impairment in ASD remains poorly characterized. In this study, we used magnetoencephalography (MEG) to (1) assess potential group differences between typically developing (TD) and ASD participants in motor cortical oscillatory activity observed on a simple button-press task and (2) to do so over a sufficiently broad age-range so as to capture age-dependent changes associated with development. Event-related desynchronization was evaluated in Mu (8-13 Hz) and Beta (15-30 Hz) frequency bands (Mu-ERD, Beta-ERD). In addition, post-movement Beta rebound (PMBR), and movement-related gamma (60-90 Hz) synchrony (MRGS) were also assessed in a cohort of 123 participants (63 typically developing (TD) and 59 with ASD) ranging in age from 8 to 24.9 years. We observed significant age-dependent linear trends in Beta-ERD and MRGS power with age for both TD and ASD groups; which did not differ significantly between groups. However, for PMBR, in addition to a significant effect of age, we also observed a significant reduction in PMBR power in the ASD group (p < 0.05). Post-hoc tests showed that this omnibus group difference was driven by the older cohort of children >13.2 years (p < 0.001) and this group difference was not observed when assessing PMBR activity for the younger PMBR groups (ages 8-13.2 years; p = 0.48). Moreover, for the older ASD cohort, hierarchical regression showed a significant relationship between PMBR activity and clinical scores of ASD severity (Social Responsiveness Scale (SRS T scores)), after regressing out the effect of age (p < 0.05). Our results show substantial age-dependent changes in motor cortical oscillations (Beta-ERD and MRGS) occur for both TD and ASD children and diverge only for PMBR, and most significantly for older adolescents and adults with ASD. While the functional significance of PMBR and reduced PMBR signaling remains to be fully elucidated, these results underscore the importance of considering age as a factor when assessing motor cortical oscillations and group differences in children with ASD.

Factors Associated with Developmental Behavioral Pediatricians Prescribing Psychotropic Medication to Children with Autism Spectrum Disorder: A Study of Three DBPNet Sites.

OBJECTIVE: Psychotropic medications are frequently prescribed to children with autism spectrum disorder (ASD), but little is known about the prescribing practices of developmental-behavioral pediatricians (DBPs). Our objective was to determine whether clinical site, age, insurance, or comorbidities influenced DBPs prescribing psychotropic medication for children with ASD. METHODS: A retrospective analysis was performed using electronic health record data of all patients with ASD seen at 3 academic developmental-behavioral pediatrics (DBP) clinical programs from January 2010 to December 2011. Data included age, diagnoses, primary insurance, and medications prescribed. Factors associated with prescribing psychotropic medication were examined using generalized estimating equations. RESULTS: Sites varied in the frequency with which they prescribed psychotropic medication for children with ASD (site 1: 33.1%, site 2: 49.3%, site 3: 4.0%; p < .001). We found that the following factors predicted prescribing of psychotropic medications: comorbidities (odds ratio [OR]: 2.87; 95% confidence interval [CI], 2.58-3.18), age, and primary insurance. However, the impact of insurance depended on age. For 3- to 5-year-old children, those on Medicaid were more likely to be prescribed psychotropic medications than those with private insurance (OR: 1.65; 95% CI, 1.29-2.12). This was particularly true for alpha-2-adrenergic agonists (OR: 2.48; 95% CI, 1.56-3.92) and atypical antipsychotics (OR: 2.57; 95% CI, 1.46-4.55). CONCLUSION: There are large variations in prescribing psychotropic medication to children with ASD at 3 academic DBP programs. Further research is needed to understand factors that contribute to higher use of psychotropic medication in young children with Medicaid.