Shared atypical brain anatomy and intrinsic functional architecture in male youth with autism spectrum disorder and their unaffected brothers

Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research

Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.

Altered intrinsic brain activity and connectivity in unaffected parents of individuals with autism spectrum disorder: a resting-state fMRI study

Objectives: Autism spectrum disorder (ASD) is a juvenile onset neurodevelopmental disorder with social impairment and stereotyped behavior as the main symptoms. Unaffected relatives may also exhibit similar ASD features due to genetic factors. Although previous studies have demonstrated atypical brain morphological features as well as task-state brain function abnormalities in unaffected parents with ASD children, it remains unclear the pattern of brain function in the resting state.

Methods: A total of 42 unaffected parents of ASD children (pASD) and 39 age-, sex-, and handedness-matched controls were enrolled. Multiple resting-state fMRI (rsfMRI) analyzing methods were applied, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC), to reveal the functional abnormalities of unaffected parents in ASD-related brain regions. Spearman Rho correlation analysis between imaging metric values and the severity of ASD traits were evaluated as well.

Results: ALFF, ReHo, and DC methods all revealed abnormal brain regions in the pASD group, such as the left medial orbitofrontal cortex (mOFC) and rectal gyrus (ROI-1), bilateral supplementary motor area (ROI-2), right caudate nucleus head and right amygdala/para-hippocampal gyrus (ROI-3). FC decreasing was observed between ROI-1 and right anterior cingulate cortex (ACC), ROI-2, and bilateral precuneus. FC enhancing was observed between ROI-3 and right anterior cerebellar lobe, left medial temporal gyrus, left superior temporal gyrus, left medial frontal gyrus, left precentral gyrus, right postcentral gyrus in pASD. In addition, ALFF values in ROI-1, DC values in ROI-3 were positively correlated with AQ scores in pASD (ρ₁ = 0.298, P₁ = 0.007; ρ₂ = 0.220, P₂ = 0.040), while FC values between ROI-1 and right ACC were negatively correlated with AQ scores (ρ₃ = −0.334, P₃ = 0.002).

Conclusion: rsfMRI metrics could be used as biomarkers to reveal the underlying neurobiological feature of ASD for unaffected parents.

Validation of the Chinese Version of the Autism Diagnostic Interview-Revised in Autism Spectrum Disorder

BACKGROUND

The Autism Diagnostic Interview-Revised (ADI-R) is an essential semi-structured diagnostic tool for autism spectrum disorder (ASD). This study aims to validate the Chinese version of the ADI-R in Taiwan.

METHODS

The Chinese version of the ADI-R was translated and back-translated by professional translators and was approved by the original authors. A group of child psychiatrists and psychologists corrected medical terminology for the final version. Then, a total of 74 participants with ASD (male, 59, 79.73%) and 33 control participants without ASD (male, 16, 48.48%) were recruited. All participants were between 3 years 4 months to 41 years old (mean: 14.63 ± 7.93 years). Exploratory factor analysis (EFA) was used to measure the factor structure.

RESULTS

Cronbach's α showed good to excellent internal consistency (0.78-0.98) over the three core symptom domains of the Chinese version of the ADI-R. Pearson's correlation analysis revealed very high test-retest reliability (Pearson's correlation coefficients ranging from 0.95 to 0.99). EFA supported three categories of factors. For correct diagnosis of ASD, the Chinese version of the ADI-R had high sensitivity (97.30%), specificity (100%), positive predictive value (PPV) (100%), and negative predictive value (NPV) (94.29%). All domains also showed excellent area under the curves (0.991-1), sensitivity (94.59-98.65%), specificity (96.97-100%), Youden index (94.59-98.65%), PPV (97.78-100%), NPV (89.19-100%), positive likelihood ratio (32.55-33.00%) and negative likelihood ratio (0.00-0.05) after statistical examination.

CONCLUSION

The Chinese version of the ADI-R is a reliable and valid diagnostic tool for the diagnosis of ASD in Clinical settings in Taiwan.

Comparative meta-analyses of brain structural and functional abnormalities during cognitive control in attention-deficit/hyperactivity disorder and autism spectrum disorder

BACKGROUND

People with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have abnormalities in frontal, temporal, parietal and striato-thalamic networks. It is unclear to what extent these abnormalities are distinctive or shared. This comparative meta-analysis aimed to identify the most consistent disorder-differentiating and shared structural and functional abnormalities.

METHODS

Systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies of cognitive control comparing people with ASD or ADHD with typically developing controls. Regional gray matter volume (GMV) and fMRI abnormalities during cognitive control were compared in the overall sample and in age-, sex- and IQ-matched subgroups with seed-based d mapping meta-analytic methods.

RESULTS

Eighty-six independent VBM (1533 ADHD and 1295 controls; 1445 ASD and 1477 controls) and 60 fMRI datasets (1001 ADHD and 1004 controls; 335 ASD and 353 controls) were identified. The VBM meta-analyses revealed ADHD-differentiating decreased ventromedial orbitofrontal (z = 2.22, p < 0.0001) but ASD-differentiating increased bilateral temporal and right dorsolateral prefrontal GMV (zs ⩾ 1.64, ps ⩽ 0.002). The fMRI meta-analyses of cognitive control revealed ASD-differentiating medial prefrontal underactivation but overactivation in bilateral ventrolateral prefrontal cortices and precuneus (zs ⩾ 1.04, ps ⩽ 0.003). During motor response inhibition specifically, ADHD relative to ASD showed right inferior fronto-striatal underactivation (zs ⩾ 1.14, ps ⩽ 0.003) but shared right anterior insula underactivation.

CONCLUSIONS

People with ADHD and ASD have mostly distinct structural abnormalities, with enlarged fronto-temporal GMV in ASD and reduced orbitofrontal GMV in ADHD; and mostly distinct functional abnormalities, which were more pronounced in ASD.

A Deep Learning Approach for Missing Data Imputation of Rating Scales Assessing Attention-Deficit Hyperactivity Disorder

A variety of tools and methods have been used to measure behavioral symptoms of attention-deficit/hyperactivity disorder (ADHD). Missing data is a major concern in ADHD behavioral studies. This study used a deep learning method to impute missing data in ADHD rating scales and evaluated the ability of the imputed dataset (i.e., the imputed data replacing the original missing values) to distinguish youths with ADHD from youths without ADHD. The data were collected from 1220 youths, 799 of whom had an ADHD diagnosis, and 421 were typically developing (TD) youths without ADHD, recruited in Northern Taiwan. Participants were assessed using the Conners' Continuous Performance Test, the Chinese versions of the Conners' rating scale-revised: short form for parent and teacher reports, and the Swanson, Nolan, and Pelham, version IV scale for parent and teacher reports. We used deep learning, with information from the original complete dataset (referred to as the reference dataset), to perform missing data imputation and generate an imputation order according to the imputed accuracy of each question. We evaluated the effectiveness of imputation using support vector machine to classify the ADHD and TD groups in the imputed dataset. The imputed dataset can classify ADHD vs. TD up to 89% accuracy, which did not differ from the classification accuracy (89%) using the reference dataset. Most of the behaviors related to oppositional behaviors rated by teachers and hyperactivity/impulsivity rated by both parents and teachers showed high discriminatory accuracy to distinguish ADHD from non-ADHD. Our findings support a deep learning solution for missing data imputation without introducing bias to the data.

Aggression in BALB/cJ mice is differentially predicted by the volumes of anterior and midcingulate cortex

Anterior cingulate cortex (ACC) and midcingulate cortex (MCC) have been implicated in the regulation of aggressive behaviour. For instance, patients with conduct disorder (CD) show increased levels of aggression accompanied by changes in ACC and MCC volume. However, accounts of ACC/MCC changes in CD patients have been conflicting, likely due to the heterogeneity of the studied populations. Here, we address these discrepancies by studying volumetric changes of ACC/MCC in the BALB/cJ mouse, a model of aggression, compared to an age- and gender-matched control group of BALB/cByJ mice. We quantified aggression in BALB/cJ and BALB/cByJ mice using the resident-intruder test, and related this to volumetric measures of ACC/MCC based on Nissl-stained coronal brain slices of the same animals. We demonstrate that BALB/cJ behave consistently more aggressively (shorter attack latencies, more frequent attacks, anti-social biting) than the control group, while at the same time showing an increased volume of ACC and a decreased volume of MCC. Differences in ACC and MCC volume jointly predicted a high amount of variance in aggressive behaviour, while regression with only one predictor had a poor fit. This suggests that, beyond their individual contributions, the relationship between ACC and MCC plays an important role in regulating aggressive behaviour. Finally, we show the importance of switching from the classical rodent anatomical definition of ACC as cingulate area 2 and 1 to a definition that includes the MCC and is directly homologous to higher mammalian species: clear behaviour-related differences in ACC/MCC anatomy were only observed using the homologous definition.

Gradient of Parvalbumin- and Somatostatin-Expressing Interneurons Across Cingulate Cortex Is Differentially Linked to Aggression and Sociability in BALB/cJ Mice

Successfully navigating social interactions requires the precise and balanced integration of social and environmental cues. When such flexible information integration fails, maladaptive behavioral patterns arise, including excessive aggression, empathy deficits, and social withdrawal, as seen in disorders such as conduct disorder and autism spectrum disorder. One of the main hubs for the context-dependent regulation of behavior is cingulate cortex, specifically anterior cingulate cortex (ACC) and midcingulate cortex (MCC). While volumetric abnormalities of ACC and MCC have been demonstrated in patients, little is known about the exact structural changes responsible for the dysregulation of behaviors such as aggression and social withdrawal. Here, we demonstrate that the distribution of parvalbumin (PV) and somatostatin (SOM) interneurons across ACC and MCC differentially predicts aggression and social withdrawal in BALB/cJ mice. BALB/cJ mice were phenotyped for their social behavior (three-chamber task) and aggression (resident-intruder task) compared to control (BALB/cByJ) mice. In line with previous studies, BALB/cJ mice behaved more aggressively than controls. The three-chamber task revealed two sub-groups of highly-sociable versus less-sociable BALB/cJ mice. Highly-sociable BALB/cJ mice were as aggressive as the less-sociable group-in fact, they committed more acts of socially acceptable aggression (threats and harmless bites). PV and SOM immunostaining revealed that a lack of specificity in the distribution of SOM and PV interneurons across cingulate cortex coincided with social withdrawal: both control mice and highly-sociable BALB/cJ mice showed a differential distribution of PV and SOM interneurons across the sub-areas of cingulate cortex, while for less-sociable BALB/cJ mice, the distributions were near-flat. In contrast, both highly-sociable and less-sociable BALB/cJ mice had a decreased concentration of PV interneurons in MCC compared to controls, which was therefore linked to aggressive behavior. Together, these results suggest that the dynamic balance of excitatory and inhibitory activity across ACC and MCC shapes both social and aggressive behavior.

Altered frontal aslant tracts as a heritable neural basis of social communication deficits in autism spectrum disorder: A sibling study using tract-based automatic analysis

Investigating social behaviors and brain structural alterations in unaffected siblings of individuals with autism spectrum disorder (ASD) may help identify intermediate phenotypes of social communication deficits in ASD. This study hypothesized that such intermediate phenotypes could be identified in white matter tracts of the social communication model that exhibited reduced tract integrity and associations with social communication deficits. Boys with ASD (N = 30), unaffected male siblings (N = 27), and typically developing (TD) boys (N = 30) underwent clinical evaluation and MRI scanning. Group differences in generalized fractional anisotropy (GFA) values, a white matter integrity index derived from diffusion MRI data, and the relationships of GFA with the Social Responsiveness Scale (SRS) scores and the Child Behavior Checklist (CBCL/4-18) scores were investigated. Significant differences were found in the GFA values of the frontal aslant tract (FAT) among the three groups, with the decreasing order of GFA from TD to siblings to ASD. The GFA values of the FAT were associated with the social communication scores (on the SRS) in the sibling group, and those of the superior longitudinal fasciculus III were associated with the social problems scores (on the CBCL/4-18) in the boys with ASD. Due to the altered tract integrity and association with social communication deficits in the unaffected siblings of individuals with ASD, the FAT might be a heritable neural basis for social communication deficits of ASD. Autism Res 2019, 12: 225-238 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is a group of highly heritable disorders with social communication deficits as one of the core symptoms. This study aimed to identify a neural trait of social communication deficits in individuals with ASD. We investigated brain structural alterations and their associations with social communication scores in unaffected siblings of individuals with ASD. The siblings' frontal aslant tract was found to be impaired, and this tract showed a significant association with the social communication scores. Our findings support that the frontal aslant tract might be a potential neural trait of social communication deficits in ASD.

School Functions in Unaffected Siblings of Youths with Autism Spectrum Disorders

This study investigated school functioning among unaffected siblings of youths with autistic spectrum disorder (ASD) and identified the correlates for school maladjustment. We recruited 66 youths with a clinical diagnosis of ASD, aged 8-19, their unaffected siblings and 132 typically developing controls (TD). We found that ASD youths had poorer school functions than unaffected siblings and TD. Unaffected siblings had poorer attitude toward schoolwork and more severe behavioral problems at school than TD. Several associated factors for different scholastic functional domains (i.e., academic performance, attitude toward school work, social interactions, behavioral problems) in the siblings included IQ, autistic traits, inattention/oppositional symptoms, sibling relationships, etc. Our findings suggest the need of assessing school functions in unaffected siblings of ASD.

TRIAL REGISTRATION

Clinical trial registration identifier: NCT01582256.