Predictive value of morphological features in patients with autism versus normal controls

Application of pseudocontinuous arterial spin labeling perfusion imaging in children with autism spectrum disorders

Introduction

Pseudocontinuous Arterial Spin Labeling (pCASL) perfusion imaging allows non-invasive quantification of regional cerebral blood flow (CBF) as part of a multimodal magnetic resonance imaging (MRI) protocol. This study aimed to compare regional CBF in autism spectrum disorders (ASD) individuals with their age-matched typically developing (TD) children using pCASL perfusion imaging.

Materials and methods

This cross-sectional study enrolled 17 individuals with ASD and 13 TD children. All participants underwent pCASL examination on a 3.0 T MRI scanner. Children in two groups were assessed for clinical characteristics and developmental profiles using Autism Behavior Checklist (ABC) and Gesell development diagnosis scale (GDDS), respectively. We compared CBF in different cerebral regions of ASD and TD children. We also assessed the association between CBF and clinical characteristics/developmental profile.

Results

Compared with TD children, individuals with ASD demonstrated a reduction in CBF in the left frontal lobe, the bilateral parietal lobes, and the bilateral temporal lobes. Within the ASD group, CBF was significantly higher in the right parietal lobe than in the left side. Correlation analysis of behavior characteristics and CBF in different regions showed a positive correlation between body and object domain scores on the ABC and CBF of the bilateral occipital lobes, and separately, between language domain scores and CBF of the left frontal lobe. The score of the social and self-help domain was negatively correlated with the CBF of the left frontal lobe, the left parietal lobe, and the left temporal lobe.

Conclusion

Cerebral blood flow was found to be negatively correlated with scores in the social and self-help domain, and positively correlated with those in the body and object domain, indicating that CBF values are a potential MRI-based biomarker of disease severity in ASD patients. The findings may provide novel insight into the pathophysiological mechanisms of ASD.

The Role of Structure MRI in Diagnosing Autism

This study proposes a Computer-Aided Diagnostic (CAD) system to diagnose subjects with autism spectrum disorder (ASD). The CAD system identifies morphological anomalies within the brain regions of ASD subjects. Cortical features are scored according to their contribution in diagnosing a subject to be ASD or typically developed (TD) based on a trained machine-learning (ML) model. This approach opens the hope for developing a new CAD system for early personalized diagnosis of ASD. We propose a framework to extract the cerebral cortex from structural MRI as well as identifying the altered areas in the cerebral cortex. This framework consists of the following five main steps: (i) extraction of cerebral cortex from structural MRI; (ii) cortical parcellation to a standard atlas; (iii) identifying ASD associated cortical markers; (iv) adjusting feature values according to sex and age; (v) building tailored neuro-atlases to identify ASD; and (vi) artificial neural networks (NN) are trained to classify ASD. The system is tested on the Autism Brain Imaging Data Exchange (ABIDE I) sites achieving an average balanced accuracy score of 97±2%. This paper demonstrates the ability to develop an objective CAD system using structure MRI and tailored neuro-atlases describing specific developmental patterns of the brain in autism.

Deep Learning Approach for Screening Autism Spectrum Disorder in Children with Facial Images and Analysis of Ethnoracial Factors in Model Development and Application

Autism spectrum disorder (ASD) is a developmental disability that can cause significant social, communication, and behavioral challenges. Early intervention for children with ASD can help to improve their intellectual ability and reduces autistic symptoms. Multiple clinical researches have suggested that facial phenotypic differences exist between ASD children and typically developing (TD) children. In this research, we propose a practical ASD screening solution using facial images through applying VGG16 transfer learning-based deep learning to a unique ASD dataset of clinically diagnosed children that we collected. Our model produced a 95% classification accuracy and 0.95 F1-score. The only other reported study using facial images to detect ASD was based on the Kaggle ASD Facial Image Dataset, which is an internet search-produced, low-quality, and low-fidelity dataset. Our results support the clinical findings of facial feature differences between children with ASD and TD children. The high F1-score achieved indicates that it is viable to use deep learning models to screen children with ASD. We concluded that the racial and ethnic-related factors in deep-learning based ASD screening with facial images are critical to solution viability and accuracy.

Brief Report: Facial Asymmetry and Autistic-Like Traits in the General Population

Atypical facial morphology, particularly increased facial asymmetry, has been identified in some individuals with Autism Spectrum Conditions (ASC). Many cognitive, behavioural and biological features associated with ASC also occur on a continuum in the general population. The aim of the present study was to examine subthreshold levels of autistic traits and facial morphology in non-autistic individuals. Facial asymmetry was measured using three-dimensional facial photogrammetry, and the Autism-spectrum Quotient was used to measure autistic-like traits in a community-ascertained sample of young adults (n = 289). After accounting for covariates, there were no significant associations observed between autistic-like traits and facial asymmetry, suggesting that any potential facial morphology differences linked to ASC may be limited to the clinical condition.

Actionable and incidental neuroradiological findings in twins with neurodevelopmental disorders

While previous research has investigated neuroradiological findings in autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD), the entire range of neurodevelopmental disorders (NDDs) has not yet been well-studied using magnetic resonance imaging (MRI). Considering the overlap among NDDs and simultaneous development of the brain and face, guided by molecular signaling, we examined the relationship of actionable and incidental (non-actionable) MRI findings and NDD diagnoses together with facial morphological variants and genetic copy number variants (CNVs). A cross-sectional study was conducted with a twin cohort 8–36 years of age (57% monozygotic, 40% dizygotic), including 372 subjects (46% with NDDs; 47% female) imaged by MRI, 280 with data for facial morphological variants, and 183 for CNVs. Fifty-one percent of participants had MRI findings. Males had a statistically significantly higher percentage of MRI findings (57.7%) compared with females (43.8%, p = 0.03). Twin zygosity was not statistically significantly correlated with incidence or severity of specific MRI findings. No statistically significant association was found between MRI findings and any NDD diagnosis or facial morphological variants; however, MRI findings were statistically significantly associated with the number of CNVs (OR 1.20, 95% CI 1.00–1.44, p = 0.05, adjusted OR for sex 1.24, 95% CI 1.03–1.50, p = 0.02). When combining the presence of MRI findings, facial morphological variants, and CNVs, statistically significant relationships were found with ASD and ADHD diagnoses (p = 0.0006 and p = 0.002, respectively). The results of this study demonstrate that the ability to identify NDDs from combined radiology, morphology, and CNV assessments may be possible. Additionally, twins do not appear to be at increased risk for neuroradiological variants.

Identification of Essential, Equivocal and Complex Autism by the Autism Dysmorphology Measure: An Observational Study

The Autism Dysmorphology Measure is designed for non-expert clinicians. It uses an algorithm to assess 12 body regions and categorizes Autism on the number of dysmorphic regions identified; Essential (≤ 3), Equivocal (4-5) or Complex (≥ 6). We evaluated 200 Indian children with Autism (mean age 3.7 years) in a hospital-based cross-sectional study and compared inter-group profiles. We found 31% Essential, 49% Equivocal and 20% Complex Autism. On comparing results with existing literature, it appeared that genetic ancestry and age significantly influenced dysmorphism and hence categorization. No significant differences were observed between complex and essential autism in epilepsy, severity of autism or development, as reported earlier. These shortcomings make the present tool unsuitable for use in young Indian children with Autism.

Clinical versus automated assessments of morphological variants in twins with and without neurodevelopmental disorders

Physical examinations are recommended as part of a comprehensive evaluation for individuals with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder. These examinations should include assessment for morphological variants. Previous studies have shown an increase in morphological variants in individuals with NDDs, particularly ASD, and that these variants may be present in greater amounts in individuals with genetic alterations. Unfortunately, assessment for morphological variants can be subjective and time-consuming, and require a high degree of clinical expertise. Therefore, objective, automated methods of morphological assessment are desirable. This study compared the use of Face2Gene, an automated tool to explore facial morphological variants, to clinical consensus assessment, using a cohort of N = 290 twins enriched for NDDs (n = 135 with NDD diagnoses). Agreement between automated and clinical assessments were satisfactory to complete (78.3-100%). In our twin sample, individuals with NDDs did not have greater numbers of facial morphological variants when compared to those with typical development, nor when controlling for shared genetic and environmental factors within twin pairs. Common facial morphological variants in those with and without NDDs were similar and included thick upper lip vermilion, abnormality of the nasal tip, long face, and upslanted palpebral fissure. We conclude that although facial morphological variants can be assessed reliably in NDDs with automated tools like Face2Gene, clinical utility is limited when just exploring the facial region. Therefore, currently, automated assessments may best complement, rather than replace, in-person clinical assessments.

Increased facial asymmetry in autism spectrum conditions is associated with symptom presentation

A key research priority in the study of autism spectrum conditions (ASC) is the discovery of biological markers that may help to identify and elucidate etiologically distinct subgroups. One physical marker that has received increasing research attention is facial structure. Although there remains little consensus in the field, findings relating to greater facial asymmetry (FA) in ASC exhibit some consistency. As there is growing recognition of the importance of replicatory studies in ASC research, the aim of this study was to investigate the replicability of increased FA in autistic children compared to nonautistic peers. Using three-dimensional photogrammetry, this study examined FA in 84 autistic children, 110 typically developing children with no family history of the condition, and 49 full siblings of autistic children. In support of previous literature, significantly greater depth-wise FA was identified in autistic children relative to the two comparison groups. As a further investigation, increased lateral FA in autistic children was found to be associated with greater severity of ASC symptoms on the Autism Diagnostic Observation Schedule, second edition, specifically related to repetitive and restrictive behaviors. These outcomes provide an important and independent replication of increased FA in ASC, as well as a novel contribution to the field. Having confirmed the direction and areas of increased FA in ASC, these findings could motivate a search for potential underlying brain dysmorphogenesis. Autism Res 2019, 12: 1774-1783. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study looked at the amount of facial asymmetry (FA) in autistic children compared to typically developing children and children who have siblings with autism. The study found that autistic children, compared to the other two groups, had greater FA, and that increased FA was related to greater severity of autistic symptoms. The face and brain grow together during the earliest stages of development, and so findings of facial differences in autism might inform future studies of early brain differences associated with the condition.

Heritable genotype contrast mining reveals novel gene associations specific to autism subgroups

Though the genetic etiology of autism is complex, our understanding can be improved by identifying genes and gene-gene interactions that contribute to the development of specific autism subtypes. Identifying such gene groupings will allow individuals to be diagnosed and treated according to their precise characteristics. To this end, we developed a method to associate gene combinations with groups with shared autism traits, targeting genetic elements that distinguish patient populations with opposing phenotypes. Our computational method prioritizes genetic variants for genome-wide association, then utilizes Frequent Pattern Mining to highlight potential interactions between variants. We introduce a novel genotype assessment metric, the Unique Inherited Combination support, which accounts for inheritance patterns observed in the nuclear family while estimating the impact of genetic variation on phenotype manifestation at the individual level. High-contrast variant combinations are tested for significant subgroup associations. We apply this method by contrasting autism subgroups defined by severe or mild manifestations of a phenotype. Significant associations connected 286 genes to the subgroups, including 193 novel autism candidates. 71 pairs of genes have joint associations with subgroups, presenting opportunities to investigate interacting functions. This study analyzed 12 autism subgroups, but our informatics method can explore other meaningful divisions of autism patients, and can further be applied to reveal precise genetic associations within other phenotypically heterogeneous disorders, such as Alzheimer's disease.

Investigating facial phenotype in autism spectrum conditions: The importance of a hypothesis driven approach

Atypical facial characteristics have been observed in many disorders associated with developmental disability. While autism spectrum conditions (ASC) have not previously been thought to be associated with a distinct facial phenotype, an emerging research literature is casting doubt on this assumption. The identification of differences in the facial phenotype of individuals with ASC may contribute to efforts to promote early identification of the condition and help elucidate etiological pathways. With the aim of identifying facial phenotypes associated with ASC, this commentary evaluated facial features purported to distinguish ASC from typical development. Although there is little consensus across the reviewed studies for the majority of facial characteristics described, preliminary evidence suggests increased facial asymmetry may be more common in ASC. There is also evidence to suggest that there are morphologically distinct subgroups within ASC that correspond with different cognitive and behavioral symptomatology. However, in light of the various inconsistencies in the reported literature, and based on an accumulating understanding of etiological pathways proposed to be associated with ASC, we propose an alternative paradigm for investigating facial phenotypes in ASC. A series of studies are outlined to demonstrate the promise of a research program that has taken a hypothesis-driven approach to examine facial phenotypes associated with increased exposure to prenatal testosterone and to ASC. Autism Res 2017, 10: 1910-1918. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

This commentary reviewed studies that found differences in the facial features of individuals with autism spectrum conditions (ASC) compared to typically developing individuals. While there is little agreement between studies, there is some support for asymmetrical facial features associated with ASC, and preliminary evidence that particular facial features relate to specific patterns of cognitive and behavioral symptoms. However, in light of inconsistencies between studies and based on accumulating understanding of etiological pathways, we propose an alternative approach to investigating facial differences in ASC.

Reduced Hemispheric Asymmetry of White Matter Microstructure in Autism Spectrum Disorder

OBJECTIVE

Many past studies have suggested atypical functional and anatomical hemispheric asymmetries in autism spectrum disorder (ASD). However, almost all of these have examined only language-related asymmetries. Here, we conduct a comprehensive investigation of microstructural asymmetries across a large number of fiber tracts in ASD.

METHOD

We used diffusion tensor imaging for a comprehensive investigation of anatomical white matter asymmetries across the entire white matter skeleton, using tract-based spatial statistics in 41 children and adolescents with ASD and a matched group of 44 typically developing (TD) participants.

RESULTS

We found significant asymmetries in the TD group, being rightward for fractional anisotropy and leftward for mean diffusivity (with concordant asymmetries for radial and axial diffusivity). These asymmetries were significantly reduced in the group with ASD: in whole brain analysis for fractional anisotropy, and in a region where several major association and projection tracts travel in close proximity within occipital white matter for mean diffusivity, axial diffusivity, and radial diffusivity. No correlations between global white matter asymmetry and age or socio-communicative abilities were detected.

CONCLUSION

Our findings in TD children and adolescents can be interpreted as reflecting different processing modes (more integrative in the right and more specialized in the left hemisphere). These asymmetries and the "division of labor" between hemispheres implied by them appear to be diminished in autism spectrum disorder.

The mane effect in the horse (Equus ferus caballus): Right mane dominance enhanced in mares but not associated with left and right manoeuvres in a reining competition

A human physical asymmetry is the near 90% clockwise occipitoparietal scalp hair-whorl direction in Europeans, an incidence that approximates the left lateralization of speech and right-handedness. Hair-whorl direction is also asymmetric in horses, Equus ferus caballus and placement is proposed to be related to temperament and lateralized skill in equitation manoeuvres. We describe a hair-whorl asymmetry in the horse, mane direction. Of 526, 3-year-old American Quarter horses, 69% of horses had mane directed to the right and 31% had mane directed to the left. The bias was larger in females, with 74% of females vs. 65% of males having mane directed to the right. Mane direction was unrelated to coat colour. The behavioural significance of mane asymmetry was investigated using judges' scores from a reining competition requiring symmetrical maneuvers of spin, circle and roll-back to either the left or to the right. There was no relation between mane asymmetry and overall reining performance and no relation between mane direction and scores for left or right manoeuvres. The results are discussed in relation to the significance of morphological asymmetries, neural function and the influence of planar cell polarity genes, such as Frizzled, that influence epidermal hair cell patterning.

A quarter century of progress on the early detection and treatment of autism spectrum disorder

The last 25 years have witnessed tremendous changes in our ability to detect autism very early in life and provide interventions that can significantly influence children's outcomes. It was once questioned whether autism could be recognized before children had developed language and symbolic play skills; now changes in early behaviors, as well as structural brain changes, have been documented in infants 6-12 months of age who later develop autism. Advances in brain imaging and genetics offer the possibility of detecting autism before the syndrome is fully manifest, thereby reducing or preventing symptoms from developing. Whereas the primary mode of behavioral intervention a few decades ago relied on operant conditioning, recent approaches integrate the methods of applied behavioral analysis within a developmental, relationship-focused intervention model that are implemented by both parents and clinicians. These interventions have been found to have positive effects on children's developmental trajectory, as measured by both behavioral and neurophysiological assessments. Future approaches will likely combine both behavioral and pharmacological treatments for children who have less robust responses to behavioral interventions. There has been a paradigm shift in the way that autism is viewed, evolving from a lifelong condition with a very poor prognosis to one in which significant gains and neuroplasticity is expected, especially when the condition is detected early and appropriate interventions are provided. The grand challenge for the future is to bridge the tremendous gap between research and the implementation of evidence-based practices in the broader community, both in the United States and worldwide. Significant disparities in access to appropriate health care for children with autism exist that urgently require advocacy and more resources.