Similar white matter aberrations in children with autism and their unaffected siblings: a diffusion tensor imaging study using tract-based spatial statistics

A Twin Study of Altered White Matter Heritability in Youth With Autism Spectrum Disorder

OBJECTIVE

White matter alterations are frequently reported in autism spectrum disorder (ASD), yet the etiology is currently unknown. The objective of this investigation was to examine, for the first time, the impact of genetic and environmental factors on white matter microstructure in twins with ASD compared to control twins without ASD.

METHOD

Diffusion-weighted MRIs were obtained from same-sex twin pairs (6-15 years of age) in which at least 1 twin was diagnosed with ASD or neither twin exhibited a history of neurological or psychiatric disorders. Fractional anisotropy (FA) and mean diffusivity (MD) were examined across different white matter tracts in the brain, and statistical and twin modeling were completed to assess the proportion of variation associated with additive genetic (A) and common/shared (C) or unique (E) environmental factors. We also developed a novel Twin-Pair Difference Score analysis method that produces quantitative estimates of the genetic and environmental contributions to shared covariance between different brain and behavioral traits.

RESULTS

Good-quality data were available from 84 twin pairs, 50 ASD pairs (32 concordant for ASD [16 monozygotic; 16 dizygotic], 16 discordant for ASD [3 monozygotic; 13 dizygotic], and 2 pairs in which 1 twin had ASD and the other exhibited some subthreshold symptoms [1 monozygotic; 1 dizygotic]) and 34 control pairs (20 monozygotic; 14 dizygotic). Average FA and MD across the brain, respectively, were primarily genetically mediated in both control twins (A = 0.80, 95% CI [0.57, 1.02]; A = 0.80 [0.55, 1.04]) and twins concordant for having ASD (A = 0.71 [0.33, 1.09]; A = 0.84 [0.32,1.36]). However, there were also significant tract-specific differences between groups. For instance, genetic effects on commissural fibers were primarily associated with differences in general cognitive abilities and perhaps some diagnostic differences for ASD because Twin-Pair Difference-Score analysis indicated that genetic factors may have contributed to ∼40% to 50% of the covariation between IQ scores and FA of the corpus callosum. Conversely, the increased impact of environmental factors on some projection and association fibers were primarily associated with differences in symptom severity in twins with ASD; for example, our analyses suggested that unique environmental factors may have contributed to ∼10% to 20% of the covariation between autism-related symptom severity and FA of the cerebellar peduncles and external capsule.

CONCLUSION

White matter alterations in youth with ASD are associated with both genetic contributions and potentially increased vulnerability or responsivity to environmental influences.

DIVERSITY & INCLUSION STATEMENT

We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. One or more of the authors of this paper self-identifies as living with a disability. The author list of this paper includes contributors from the location and/or community where the research was conducted and they participated in the data collection, design, analysis, and/or interpretation of the work.

Tract- and gray matter- based spatial statistics show white matter and gray matter microstructural differences in autistic males

Background

Autism spectrum disorder (ASD) is a neurodevelopmental condition commonly studied in the context of early childhood. As ASD is a life-long condition, understanding the characteristics of brain microstructure from adolescence into adulthood and associations to clinical features is critical for improving outcomes across the lifespan. In the current work, we utilized Tract Based Spatial Statistics (TBSS) and Gray Matter Based Spatial Statistics (GBSS) to examine the white matter (WM) and gray matter (GM) microstructure in neurotypical (NT) and autistic males.

Methods

Multi-shell diffusion MRI was acquired from 78 autistic and 81 NT males (12-to-46-years) and fit to the DTI and NODDI diffusion models. TBSS and GBSS were performed to analyze WM and GM microstructure, respectively. General linear models were used to investigate group and age-related group differences. Within the ASD group, relationships between WM and GM microstructure and measures of autistic symptoms were investigated.

Results

All dMRI measures were significantly associated with age across WM and GM. Significant group differences were observed across WM and GM. No significant age-by-group interactions were detected. Within the ASD group, positive relationships with WM microstructure were observed with ADOS-2 Calibrated Severity Scores.

Conclusion

Using TBSS and GBSS our findings provide new insights into group differences of WM and GM microstructure in autistic males from adolescence into adulthood. Detection of microstructural differences across the lifespan as well as their relationship to the level of autistic symptoms will deepen to our understanding of brain-behavior relationships of ASD and may aid in the improvement of intervention options for autistic adults.

Reduced brain connectivity along the autism spectrum controlled for familial confounding by co-twin design

Previous studies on brain connectivity correlates of autism have often focused on selective connections and yielded inconsistent results. By applying global fiber tracking and utilizing a within-twin pair design, we aimed to contribute to a more unbiased picture of white matter connectivity in association with clinical autism and autistic traits. Eighty-seven twin pairs (n = 174; 55% monozygotic; 24 with clinical autism) underwent diffusion tensor imaging. Linear regressions assessed within-twin pair associations between structural brain connectivity of anatomically defined brain regions and both clinical autism and autistic traits. These were explicitly adjusted for IQ, other neurodevelopmental/psychiatric conditions and multiple testing, and implicitly for biological sex, age, and all genetic and environmental factors shared by twins. Both clinical autism and autistic traits were associated with reductions in structural connectivity. Twins fulfilling diagnostic criteria for clinical autism had decreased brainstem-cuneus connectivity compared to their co-twins without clinical autism. Further, twins with higher autistic traits had decreased connectivity of the left hippocampus with the left fusiform and parahippocampal areas. These associations were also significant in dizygotic twins alone. Reduced brainstem-cuneus connectivity might point towards alterations in low-level visual processing in clinical autism while higher autistic traits seemed to be more associated with reduced connectivity in networks involving the hippocampus and the fusiform gyrus, crucial especially for processing of faces and other (higher order) visual processing. The observed associations were likely influenced by both genes and environment.

Association of Sex With Neurobehavioral Markers of Executive Function in 2-Year-Olds at High and Low Likelihood of Autism

Importance

Children with autism and their siblings exhibit executive function (EF) deficits early in development, but associations between EF and biological sex or early brain alterations in this population are largely unexplored.

Objective

To investigate the interaction of sex, autism likelihood group, and structural magnetic resonance imaging alterations on EF in 2-year-old children at high familial likelihood (HL) and low familial likelihood (LL) of autism, based on having an older sibling with autism or no family history of autism in first-degree relatives.

Design, Setting, and Participants

This prospective cohort study assessed 165 toddlers at HL (n = 110) and LL (n = 55) of autism at 4 university-based research centers. Data were collected from January 1, 2007, to December 31, 2013, and analyzed between August 2021 and June 2022 as part of the Infant Brain Imaging Study.

Main Outcomes and Measures

Direct assessments of EF and acquired structural magnetic resonance imaging were performed to determine frontal lobe, parietal lobe, and total cerebral brain volume.

Results

A total of 165 toddlers (mean [SD] age, 24.61 [0.95] months; 90 [54%] male, 137 [83%] White) at HL for autism (n = 110; 17 diagnosed with ASD) and LL for autism (n = 55) were studied. The toddlers at HL for autism scored lower than the toddlers at LL for autism on EF tests regardless of sex (mean [SE] B = -8.77 [4.21]; 95% CI, -17.09 to -0.45; η2p = 0.03). With the exclusion of toddlers with autism, no group (HL vs LL) difference in EF was found in boys (mean [SE] difference, -7.18 [4.26]; 95% CI, 1.24-15.59), but EF was lower in HL girls than LL girls (mean [SE] difference, -9.75 [4.34]; 95% CI, -18.32 to -1.18). Brain-behavior associations were examined, controlling for overall cerebral volume and developmental level. Sex differences in EF-frontal (B [SE] = 16.51 [7.43]; 95% CI, 1.36-31.67; η2p = 0.14) and EF-parietal (B [SE] = 17.68 [6.99]; 95% CI, 3.43-31.94; η2p = 0.17) associations were found in the LL group but not the HL group (EF-frontal: B [SE] = -1.36 [3.87]; 95% CI, -9.07 to 6.35; η2p = 0.00; EF-parietal: B [SE] = -2.81 [4.09]; 95% CI, -10.96 to 5.34; η2p = 0.01). Autism likelihood group differences in EF-frontal (B [SE] = -9.93 [4.88]; 95% CI, -19.73 to -0.12; η2p = 0.08) and EF-parietal (B [SE] = -15.44 [5.18]; 95% CI, -25.86 to -5.02; η2p = 0.16) associations were found in girls not boys (EF-frontal: B [SE] = 6.51 [5.88]; 95% CI, -5.26 to 18.27; η2p = 0.02; EF-parietal: B [SE] = 4.18 [5.48]; 95% CI, -6.78 to 15.15; η2p = 0.01).

Conclusions and Relevance

This cohort study of toddlers at HL and LL of autism suggests that there is an association between sex and EF and that brain-behavior associations in EF may be altered in children at HL of autism. Furthermore, EF deficits may aggregate in families, particularly in girls.

A critical role of brain network architecture in a continuum model of autism spectrum disorders spanning from healthy individuals with genetic liability to individuals with ASD

Studies have shown cortical alterations in individuals with autism spectrum disorders (ASD) as well as in individuals with high polygenic risk for ASD. An important addition to the study of altered cortical anatomy is the investigation of the underlying brain network architecture that may reveal brain-wide mechanisms in ASD and in polygenic risk for ASD. Such an approach has been proven useful in other psychiatric disorders by revealing that brain network architecture shapes (to an extent) the disorder-related cortical alterations. This study uses data from a clinical dataset-560 male subjects (266 individuals with ASD and 294 healthy individuals, CTL, mean age at 17.2 years) from the Autism Brain Imaging Data Exchange database, and data of 391 healthy individuals (207 males, mean age at 12.1 years) from the Pediatric Imaging, Neurocognition and Genetics database. ASD-related cortical alterations (group difference, ASD-CTL, in cortical thickness) and cortical correlates of polygenic risk for ASD were assessed, and then statistically compared with structural connectome-based network measures (such as hubs) using spin permutation tests. Next, we investigated whether polygenic risk for ASD could be predicted by network architecture by building machine-learning based prediction models, and whether the top predictors of the model were identified as disease epicenters of ASD. We observed that ASD-related cortical alterations as well as cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. We also observed that age progression of ASD-related cortical alterations and cortical correlates of polygenic risk for ASD implicated cortical hubs more strongly than non-hub regions. Further investigation revealed that structural connectomes predicted polygenic risk for ASD (r = 0.30, p < 0.0001), and two brain regions (the left inferior parietal and left suparmarginal) with top predictive connections were identified as disease epicenters of ASD. Our study highlights a critical role of network architecture in a continuum model of ASD spanning from healthy individuals with genetic risk to individuals with ASD. Our study also highlights the strength of investigating polygenic risk scores in addition to multi-modal neuroimaging measures to better understand the interplay between genetic risk and brain alterations associated with ASD.

The relationship between alexithymia, interoception, and neural functional connectivity during facial expression processing in autism spectrum disorder

Neural processing differences of emotional facial expressions, while common in autism spectrum disorder (ASD), may be related to co-occurring alexithymia and interoceptive processing differences rather than autism per se. Here, we investigate relationships between alexithymia, interoceptive awareness of emotions, and functional connectivity during observation of facial expressions in youth (aged 8-17) with ASD (n = 28) compared to typically developing peers (TD; n = 37). Behaviorally, we found no significant differences between ASD and TD groups in interoceptive awareness of emotions, though alexithymia severity was significantly higher in the ASD group. In the ASD group, increased alexithymia was significantly correlated with lower interoceptive sensation felt during emotion. Using psycho-physiological interaction (PPI) analysis, the ASD group showed higher functional connectivity between the left ventral anterior insula and the left lateral prefrontal cortex than the TD group when viewing facial expressions. Further, alexithymia was associated with reduced left anterior insula-right precuneus connectivity and reduced right dorsal anterior insula-left ventral anterior insula connectivity when viewing facial expressions. In the ASD group, the degree of interoceptive sensation felt during emotion was positively correlated with left ventral anterior insula-right IFG connectivity when viewing facial expressions. However, across all participants, neither alexithymia nor interoceptive awareness of emotions predicted connectivity between emotion-related brain regions when viewing emotional facial expressions. To summarize, we found that in ASD compared to TD: 1) there is stronger connectivity between the insula and lateral prefrontal cortex; and 2) differences in interhemispheric and within left hemisphere connectivity between the insula and other emotion-related brain regions are related to individual differences in interoceptive processing and alexithymia. These results highlight complex relationships between alexithymia, interoception, and brain processing in ASD.

Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study

BACKGROUND

Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence.

METHODS

Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes.

RESULTS

Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone.

CONCLUSIONS

Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.

Near-infrared spectroscopy in child and adolescent neurodevelopmental disorders

Near-infrared spectroscopy (NIRS) is a noninvasive optical technique that uses the near-infrared spectrum for functional neuroimaging by measuring oxygenation and hemodynamic changes in the cerebral cortex. The advantages of NIRS include its portability and ease of application, which allows for testing with the subject in natural positions, such as sitting or standing. Since 1994, NIRS has been increasingly used to conduct functional activation studies on different psychiatric disorders, most prominently schizophrenia, depression, bipolar disorder, and neurodevelopmental disorders. However, limited information on its use among child and adolescent patients is available. We herein review recent findings obtained using NIRS measurements of the brain during cognitive tasks in neurodevelopmental disorders, such as autism spectrum disorder, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, and Tourette's disorder. This will facilitate evaluations of the causation and treatment of prefrontal cortex dysfunctions.

Translating neuroimaging changes to neuro-endophenotypes of autistic spectrum disorder: a narrative review

Background

Autism-spectrum disorder is a neurodevelopmental disorder with heterogeneity in etiopathogenesis and clinical presentation. Neuroanatomical and neurophysiological abnormalities may represent neural endophenotypes for autism spectrum disorders which may help identify subgroups of patients seemingly similar in clinical presentation yet different in their pathophysiological underpinnings. Furthermore, a thorough understanding of the pathophysiology of disease can pave the way to effective treatments, prevention, and prognostic predictions. The aim of this review is to identify the predominant neural endophenotypes in autism-spectrum disorder. The evidence was researched at the following electronic databases: Pubmed, PsycINFO, Scopus, Web of Science, and EMBASE.

Results

Enlarged brain, especially frontotemporal cortices have been consistently reported by structural neuroimaging, whereas functional neuroimaging has revealed frontotemporal dysconnectivity.

Conclusions

Regrettably, many of these findings have not been consistent. Therefore, translating these findings into neural endophenotype is by far an attempt in its budding stage. The structural and functional neuroimaging changes may represent neural endophenotypes unique to autism-spectrum disorder. Despite inconsistent results, a clinically meaningful finding may require combined efforts of autism-spectrum-disorder researchers focused on different aspects of basic, genetic, neuroimaging, and clinical research.

Differences in white matter segments in autistic males, non-autistic siblings, and non-autistic participants: An intermediate phenotype approach

LAY ABSTRACT

White matter is the neural pathway that connects neurons in different brain regions. Although research has shown white matter differences between autistic and non-autistic people, little is known about the properties of white matter in non-autistic siblings. In addition, past studies often focused on the whole neural tracts; it is unclear where differences exist in specific segments of the tracts. This study identified neural segments that differed between autistic people, their non-autistic siblings, and the age- and non-autistic people. We found altered segments within the tracts connected to anterior brain regions corresponding to several higher cognitive functions (e.g. executive functions) in autistic people and non-autistic siblings. Segments connecting to regions for social cognition and Theory of Mind were altered only in autistic people, explaining a large portion of autistic traits and may serve as neuroimaging markers. Segments within the tracts associated with fewer autistic traits or connecting brain regions for diverse highly integrated functions showed compensatory increases in the microstructural properties in non-autistic siblings. Our findings suggest that differential white matter segments that are shared between autistic people and non-autistic siblings may serve as potential "intermediate phenotypes"-biological or neuropsychological characteristics in the causal link between genetics and symptoms-of autism. These findings shed light on a promising neuroimaging model to refine the intermediate phenotype of autism which may facilitate further identification of the genetic and biological bases of autism. Future research exploring links between compensatory segments and neurocognitive strengths in non-autistic siblings may help understand brain adaptation to autism.

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

BACKGROUND

Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.

White matter disruptions related to inattention and autism spectrum symptoms in tuberous sclerosis complex

Tuberous sclerosis complex is a rare genetic multisystem condition that is associated with a high prevalence of neurodevelopmental disorders such as autism and attention-deficit/hyperactivity disorder. The underlying neural mechanisms of the emergence of these symptom domains in tuberous sclerosis complex remain unclear. Here, we use fixel-based analysis of diffusion-weighted imaging, which allows for the differentiation between multiple fibre populations within a voxel, to compare white matter properties in 16 participants with tuberous sclerosis complex (aged 11-19) and 12 age and sex matched control participants. We further tested associations between white matter alterations and autism and inattention symptoms as well as cognitive ability in participants with tuberous sclerosis complex. Compared to controls, participants with tuberous sclerosis complex showed reduced fibre density cross-section (FDC) in the dorsal branch of right superior longitudinal fasciculus and bilateral inferior longitudinal fasciculus, reduced fibre density (FD) in bilateral tapetum, and reduced fibre cross-section (FC) in the ventral branch of right superior longitudinal fasciculus. In participants with tuberous sclerosis complex, the extent of FDC reductions in right superior longitudinal fasciculus was significantly associated with autism traits (social communication difficulties and restricted, repetitive behaviours), whereas FDC reductions in right inferior longitudinal fasciculus were associated with inattention. The observed white matter alterations were unrelated to cognitive ability. Our findings shed light on the fibre-specific biophysical properties of white matter alterations in tuberous sclerosis complex and suggest that these regional changes are selectively associated with the severity of neurodevelopmental symptoms.

Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD

The neurodevelopmental model of schizophrenia is supported by multi-level impairments shared among schizophrenia and neurodevelopmental disorders. Despite schizophrenia and typical neurodevelopmental disorders, i.e., autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), as disorders of brain dysconnectivity, no study has ever elucidated whether whole-brain white matter (WM) tracts integrity alterations overlap or diverge between these three disorders. Moreover, whether the linked dimensions of cognition and brain metrics per the Research Domain Criteria framework cut across diagnostic boundaries remains unknown. We aimed to map deviations from normative ranges of whole-brain major WM tracts for individual patients to investigate the similarity and differences among schizophrenia (281 patients subgrouped into the first-episode, subchronic and chronic phases), ASD (175 patients), and ADHD (279 patients). Sex-specific WM tract normative development was modeled from diffusion spectrum imaging of 626 typically developing controls (5-40 years). There were three significant findings. First, the patterns of deviation and idiosyncrasy of WM tracts were similar between schizophrenia and ADHD alongside ASD, particularly at the earlier stages of schizophrenia relative to chronic stages. Second, using the WM deviation patterns as features, schizophrenia cannot be separated from neurodevelopmental disorders in the unsupervised machine learning algorithm. Lastly, the canonical correlation analysis showed schizophrenia, ADHD, and ASD shared linked cognitive dimensions driven by WM deviations. Together, our results provide new insights into the neurodevelopmental facet of schizophrenia and its brain basis. Individual's WM deviations may contribute to diverse arrays of cognitive function along a continuum with phenotypic expressions from typical neurodevelopmental disorders to schizophrenia.

The Role of Diffusion Tensor MR Imaging (DTI) of the Brain in Diagnosing Autism Spectrum Disorder: Promising Results

Autism spectrum disorder (ASD) is a combination of developmental anomalies that causes social and behavioral impairments, affecting around 2% of US children. Common symptoms include difficulties in communications, interactions, and behavioral disabilities. The onset of symptoms can start in early childhood, yet repeated visits to a pediatric specialist are needed before reaching a diagnosis. Still, this diagnosis is usually subjective, and scores can vary from one specialist to another. Previous literature suggests differences in brain development, environmental, and/or genetic factors play a role in developing autism, yet scientists still do not know exactly the pathology of this disorder. Currently, the gold standard diagnosis of ASD is a set of diagnostic evaluations, such as the Autism Diagnostic Observation Schedule (ADOS) or Autism Diagnostic Interview-Revised (ADI-R) report. These gold standard diagnostic instruments are an intensive, lengthy, and subjective process that involves a set of behavioral and communications tests and clinical history information conducted by a team of qualified clinicians. Emerging advancements in neuroimaging and machine learning techniques can provide a fast and objective alternative to conventional repetitive observational assessments. This paper provides a thorough study of implementing feature engineering tools to find discriminant insights from brain imaging of white matter connectivity and using a machine learning framework for an accurate classification of autistic individuals. This work highlights important findings of impacted brain areas that contribute to an autism diagnosis and presents promising accuracy results. We verified our proposed framework on a large publicly available DTI dataset of 225 subjects from the Autism Brain Imaging Data Exchange-II (ABIDE-II) initiative, achieving a high global balanced accuracy over the 5 sites of up to 99% with 5-fold cross validation. The data used was slightly unbalanced, including 125 autistic subjects and 100 typically developed (TD) ones. The achieved balanced accuracy of the proposed technique is the highest in the literature, which elucidates the importance of feature engineering steps involved in extracting useful knowledge and the promising potentials of adopting neuroimaging for the diagnosis of autism.

Whole Brain White Matter Tract Deviation and Idiosyncrasy From Normative Development in Autism and ADHD and Unaffected Siblings Link With Dimensions of Psychopathology and Cognition

OBJECTIVE

The heterogeneity of autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) preclude definitive identification of neurobiomarkers and biological risks. High clinical overlap suggests multifaceted circuit-level alterations across diagnoses, which remains elusive. This study investigated whether individuals with ADHD or ASD and their unaffected siblings constitute a spectrum of neurodevelopmental conditions in terms of white matter etiology.

METHODS

Sex-specific white matter tract normative development was modeled from diffusion MRI of 626 typically developing control subjects (ages 5-40 years; 376 of them male). Individualized metrics estimating white matter tract deviation from the age norm were derived for 279 probands with ADHD, 175 probands with ASD, and their unaffected siblings (ADHD, N=121; ASD, N=72).

RESULTS

ASD and ADHD shared diffuse white matter tract deviations in the commissure and association tracts (rho=0.54; p<0.001), while prefrontal corpus callosum deviated more remarkably in ASD (effect size=-0.36; p<0.001). Highly correlated deviance patterns between probands and unaffected siblings were found in both ASD (rho=0.69; p<0.001) and ADHD (rho=0.51; p<0.001), but only unaffected sisters of ASD probands showed a potential endophenotype in long-range association fibers and projection fibers connecting prefrontal regions. ADHD and ASD shared significant white matter tract idiosyncrasy (rho=0.55; p<0.001), particularly in tracts connecting prefrontal regions, not identified in either sibling group. Canonical correlation analysis identified multiple dimensions of psychopathology/cognition across categorical entities; autistic, visual memory, intelligence/planning/inhibition, nonverbal-intelligence/attention, working memory/attention, and set-shifting/response-variability were associated with distinct sets of white matter tract deviations.

CONCLUSIONS

When conceptualizing neurodevelopmental disorders as white matter tract deviations from normative patterns, ASD and ADHD are more alike than different. The modest white matter tract alterations in siblings suggest potential endophenotypes in these at-risk populations. This study further delineates brain-driven dimensions of psychopathology/cognition, which may help clarify within-diagnosis heterogeneity and high between-diagnosis co-occurrence.

Reduced Inter-hemispheric Resting State Functional Connectivity and Its Association With Social Deficits in Autism

Autism spectrum disorder (ASD) is an early onset developmental disorder which persists throughout life and is increasing in prevalence over the last few decades. Given its early onset and variable cognitive and emotional functional impairments, it is generally challenging to assess ASD individuals using task-based behavioral and functional MRI paradigms. Consequently, resting state functional MRI (rs-fMRI) has become a key approach for examining ASD-associated neural alterations and revealed functional alterations in large-scale brain networks relative to typically developing (TD) individuals, particularly those involved in social-cognitive and affective processes. Recent progress suggests that alterations in inter-hemispheric resting state functional connectivity (rsFC) between regions in the 2 brain hemispheres, particularly homotopic ones, may be of great importance. Here we have reviewed neuroimaging studies examining inter-hemispheric rsFC abnormities in ASD and its associations with symptom severity. As an index of inter-hemispheric functional connectivity, we have additionally reviewed previous studies on corpus callosum (CC) volumetric and fiber changes in ASD. There are converging findings on reduced inter-hemispheric (including homotopic) rsFC in large-scale brain networks particularly in posterior hubs of the default mode network, reduced volumes in the anterior and posterior CC, and on decreased FA and increased MD or RD across CC subregions. Associations between the strength of inter-hemispheric rsFC and social impairments in ASD together with their classification performance in distinguishing ASD subjects from TD controls across ages suggest that the strength of inter-hemispheric rsFC may be a more promising biomarker for assisting in ASD diagnosis than abnormalities in either brain wide rsFC or brain structure.

Role of Oligodendrocytes and Myelin in the Pathophysiology of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is an early neurodevelopmental disorder that involves deficits in interpersonal communication, social interaction, and repetitive behaviors. Although ASD pathophysiology is still uncertain, alterations in the abnormal development of the frontal lobe, limbic areas, and putamen generate an imbalance between inhibition and excitation of neuronal activity. Interestingly, recent findings suggest that a disruption in neuronal connectivity is associated with neural alterations in white matter production and myelination in diverse brain regions of patients with ASD. This review is aimed to summarize the most recent evidence that supports the notion that abnormalities in the oligodendrocyte generation and axonal myelination in specific brain regions are involved in the pathophysiology of ASD. Fundamental molecular mediators of these pathological processes are also examined. Determining the role of alterations in oligodendrogenesis and myelination is a fundamental step to understand the pathophysiology of ASD and identify possible therapeutic targets.

How Do Children with Autism Spectrum Disorder Encode and Reproduce Visuospatial Stimuli?: Investigation into Visuospatial Processing Abilities and Styles

OBJECTIVE

The purpose of this study was to examine the visuospatial processing abilities of children with autism spectrum disorder (ASD) using the Rey Osterrieth Complex Figure (ROCF).

METHODS

One-hundred thirty-four children with ASD [mean age (MA)=113.56 months], 150 siblings of children with ASD (MA= 111.67 months), and 55 typically developing (TD) children (MA=109.02 months) were included in this study. During their one-time visit, participants completed the ROCF, various autism diagnostic assessments, and the Korean-Leiter International Performance ScaleRevised. Repeated-measures Analysis of Covariance (ANCOVA) and post-hoc Tukey-Kramer comparisons were computed to compare the ROCF scores. Partial correlations and multiple regressions were computed to examine the association between ROCF scores and the severity of autistic symptoms, as measured by the Autism Diagnostic Interview-Revised (ADI-R) among children with ASD.

RESULTS

There were significant main effects of the analysis group in Structural and Incidental Accuracy, Error, and Style. More siblings than TD children drew in a part-oriented way, but the performance of the sibling group was comparable or superior to that of the TD group in all parameters. Social Interaction scores of children with ASD were significantly associated with Organization scores in Copy condition. Whether or not a child drew in the Part-Oriented style significantly predicted his/her repetitive and restricted behavior scores.

CONCLUSION

The findings add to the evidence for altered visuospatial processing patterns of ASD as a potential inherent and genetic trait and suggest that this particular cognitive style should not be considered as a deficit. Educational and theoretical implications are discussed.

Grey-Matter Thickness of the Left But Not the Right Primary Visual Area Correlates with Autism Traits in Typically Developing Adults

We examined whether functional and structural variability in the primary visual area (V1) correlated with autism traits. Twenty-nine participants (16 males; M_Age = 26.4 years, SD_Age = 4.0 years) completed the autism-spectrum quotient (AQ) questionnaire prior to a magnetic resonance imaging session. The total AQ scores was used to assess the degree of self-reported autism traits. The average functional activation in V1 to visual stimulation and its average grey-matter thickness were calculated. There were no correlations between functional activation in V1 and autism traits. Conversely, grey-matter thickness of the left but not the right V1 correlated with autism traits. We conclude that structural changes in the left V1 could be a marker for the presence of autism traits.

Differences in White Matter Microstructure Among Children With Developmental Coordination Disorder

IMPORTANCE

Developmental coordination disorder (DCD) is a motor impairment that significantly interferes with activities of daily living. Little is known about the cause of DCD and how it develops, making it difficult to understand why children with DCD struggle in learning motor skills and to determine the best intervention to optimize function.

OBJECTIVE

To characterize white matter differences using diffusion tensor imaging in children with and without DCD.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study collected diffusion tensor imaging data at BC Children's Hospital Research Institute in Vancouver, British Columbia, Canada, from September 2014 to January 2017. Using a sample of convenience, children with DCD and children without DCD aged 8 to 12 years underwent magnetic resonance imaging. Data analysis was conducted from January 2017 to January 2020.

MAIN OUTCOMES AND MEASURES

The main outcome measures were diffusion parameters, including fractional anisotropy and mean, axial, and radial diffusivity, which are thought to provide an indirect measure of white matter microstructure. Tract-based spatial statistics, a voxelwise statistical analysis of diffusion parameters, were conducted using a 2-group comparison design matrix with age and attention as covariates.

RESULTS

Thirty children without DCD (mean [SD] age, 9.9 [1.4] years; 21 [70%] boys) and 31 children with DCD (mean [SD] age, 10.1 [1.2] years; 26 [84%] boys) were included in the study. Compared with children without DCD, children with DCD were characterized by significantly lower fractional anisotropy and axial diffusivity in regions of white matter pathways associated with motor and sensorimotor processing, including the corticospinal tract (fractional anisotropy: mean [SD], 0.54 [0.03] vs 0.51 [0.03]; P < .001; axial diffusivity: mean [SD], 0.13 [0.98] vs 0.12 [0.46]; P = .01), posterior thalamic radiation at the retrolenticular part of the internal capsule (axial diffusivity: mean [SD], 0.14 [0.57] vs 0.14 [0.44]; P = .01), and cerebellar pathways (eg, superior cerebellar peduncle, fractional anisotropy: mean [SD], 0.49 [0.05] vs 0.46 [0.03]; P = .03; axial diffusivity: mean [SD], 0.14 [0.66] vs 0.14 [0.63]; P = .009). There were no significant differences in mean diffusivity and radial diffusivity between children with and without DCD.

CONCLUSIONS AND RELEVANCE

These findings suggest that children with DCD show significant brain differences in motor and sensorimotor white matter pathways compared with children without DCD. The pattern of diffusion parameters in children with DCD suggests that axonal development may be disrupted in this neurodevelopmental disorder.

Reduced White Matter Integrity and Deficits in Neuropsychological Functioning in Adults With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full-scale-IQ-matched healthy volunteers. Tract-based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (P = 0.022) and the right cingulum (P = 0.008). All neuropsychological measures were worse in the ASD group, but none of the measures significantly correlated with reduced FA in either tract in the adults with ASD or in the healthy volunteers. Together, this indicates that the tracts that are the most impacted in autism may not be (at least directly) responsible for the behavioral deficits in ASD. Autism Res 2020, 13: 702-714. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: White matter tracts are the data cables in the brain that efficiently transfer information, and damage to these tracts could be the cause for the abnormal behaviors that are associated with autism. We found that two long-range tracts (the anterior thalamic radiation and the cingulum) were both impaired in autism but were not directly related to the impairments in behavior. This suggests that the abnormal tracts and behavior are the effects of another underlying mechanism.

Anomalies in uncinate fasciculus development and social defects in preschoolers with autism spectrum disorder

BACKGROUND

Individuals with autism spectrum disorder (ASD) have social interaction deficits and difficulties in emotional regulation. The neural substrates for these socio-affective deficits are not yet clear, but one potential candidate is maldevelopment of the uncinate fasciculus (UF), a white matter tract thought to be involved in socio-affective processing. However, the developmental trajectory of the UF in young children with social interaction deficits has not been examined. The present study was designed to describe the developmental growth trajectory of the UF and the relationships between UF development and social deficits in ASD.

METHODS

Eigenvalues of the UF were measured by diffusion tensor imaging (DTI)-based tractography in 37 children with ASD and 27 matched 2-3-year-old subjects with developmental delay (DD) at baseline (time 1) and at 2-year follow-up (time 2). Growth rates of the UF were compared between groups and associations with social deficit scores according to the Autism Diagnostic Interview-Revised (ADI-R) analyzed by Pearson's correlations.

RESULTS

At time 1, axial diffusivity (AD) of the left UF was significantly larger in the ASD group than the DD group. At time 2, left UF fractional anisotropy (FA) was significantly higher and radial diffusivity (RD) significantly lower in the ASD group than the DD group. The rate of UF growth during this 2-year interval was faster in children with ASD than DD. Significant negative correlations were found between the rise in ADI-R social deficit measures and both right UF RD and left UF mean diffusivity (MD).

CONCLUSIONS

Young children with ASD demonstrate UF overgrowth during the 2-year development period between 2 and 3 and 4-5 years of age, and this white matter abnormality is directly associated with the progression of social deficits.

TRIAL REGISTRATION

World Health Organization class I registered international clinical trial platform, ChiCTR-ROC-17012877.

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity.

Methods

The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6–25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.

Results

Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = − 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity.

Limitations

This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable.

Conclusions

Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Widespread White Matter Aberrations Are Associated with Phonemic Verbal Fluency Impairment in Chronic Traumatic Brain Injury

Microstructural white matter (WM) disruption and resulting abnormal structural connectivity form a potential underlying pathology in traumatic brain injury (TBI). Herein, to determine the potential mechanism of cognitive deterioration in TBI, we examined the association of damage to specific WM tracts with cognitive function in TBI patients. We recruited 18 individuals with mild-to-moderate/severe TBI in the chronic phase and 17 age-matched controls. We determined the pattern of WM aberrations in TBI using tract-based spatial statistics (TBSS) and then examined the relationship between cognitive impairment and WM damage using the threshold-free cluster enhancement correction in TBSS. TBSS analysis showed that TBI patients exhibited WM aberrations in a wide range of brain regions. In the majority of these regions, lower fractional anisotropy (FA) largely overlapped with increased radial diffusivity, but not with axial diffusivity. Further, voxel-wise correction in TBSS demonstrated that higher FA values were associated with better performance in the phonemic verbal fluency task (VFT) in widespread WM regions, but not with the semantic VFT. Despite variation in the magnitude and location of brain injury between individual cases, chronic TBI patients exhibited widespread WM aberrations. We confirmed the findings of previous studies that WM integrity is lower across the spectrum of TBI severity in chronic subjects compared to controls. Further, phonemic VFT may be a more sensitive cognitive measure of executive dysfunction associated with WM aberrations in TBI compared with semantic VFT.

Widespread Disrupted White Matter Microstructure in Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) are characterised by impaired social communication and restricted repetitive behaviours. Researchers posit that these core features may be underpinned by disrupted structural connectivity. A tract based spatial statistical analysis of diffusion MRI data was performed to investigate white matter organisation (an indication of structural connectivity) in a well-defined cohort of 45 ASD and 45 age and IQ matched control participants. Aberrant structural connectivity characterised by reduced fractional anisotropy was observed in several fiber pathways in ASD relative to controls. Disrupted white matter organisation was associated with social deficits and restricted repetitive behaviours in ASD. Abnormal structural connectivity is apparent in ASD and may be linked to the core behavioural features of the disorder.

Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder

AIM

Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps.

METHODS

We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings.

RESULTS

A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest.

CONCLUSION

This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

White matter endophenotypes and correlates for the clinical diagnosis of autism spectrum disorder

Since prior diffusion tensor imaging (DTI) studies reported no significant differences in white matter organizations between individuals with autism spectrum disorder (ASD) and their unaffected siblings, the neural correlates for developing a clinical diagnosis among people with endophenotypes remain undetermined. We obtained DTI data from a total of 60 participants consisting of 30 people with endophenotypes and 30 people without. We first followed a conventional approach by comparing individuals with ASD and their unaffected siblings. Using region-of-interest approach, we then performed bootstrapping to examine whether the differences in white matter organizations between individuals with ASD and their unaffected siblings were substantially large, considering the distribution of differences between typically developing (TD) siblings. Conventional approaches revealed no significant differences in white matter organizations between individuals with ASD and their unaffected siblings. Bootstrapping revealed a significantly large difference in axial diffusivity in the left stria terminalis between individuals with ASD and their unaffected siblings after accounting for the distribution of differences in axial diffusivity among TD siblings (99.998 percentile). The results remained significant after controlling for multiple comparisons with Bonferroni method. We assumed that one aspect of this tract was associated with the development of a clinical diagnosis.

Diffusion Tensor Imaging And Tractography In Autistic, Dysphasic, And Healthy Control Children

BACKGROUND

Diffusion tensor imaging (DTI) is a powerful tool for investigating brain anatomical connectivity. The aim of our study was to compare brain connectivity among children with autism spectrum disorders (ASD), developmental dysphasia (DD), and healthy controls (HC) in the following tracts: the arcuate fasciculus (AF), inferior frontal occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and uncinate fasciculus (UF).

METHODS

Our sample consisted of 113 children with a mean age 8.7±2.2 years (77 boys, 36 girls), divided into three subgroups: ASD (n=39), DD (n=36), and HC (n=38). The International Classification of Diseases, 10th ed. was used to make clinical diagnoses. DTI images were collected using a 1.5 T Phillips Achieva MR imaging system.

RESULTS

Detailed analyses of fractional anisotropy (FA) revealed significant differences among the ASD, DD, and HC groups in the left AF (p=0.014) and right AF (p=0.001), the left IFOF (p<0.001) and right IFOF (p<0.001), the left ILF (p<0.001) and right ILF (p<0.001), but not in the UF. Post-hoc analyses revealed three patterns of FA differences among the groups: (1) in the right AF, right IFOF, and right ILF, FA was significantly lower in the ASD group compared to the DD and HC groups; however, there was no difference in FA between DD and HC; (2) in the left AF and left IFOF, FA was significantly lower in the ASD than in the HC group, but there were no differences between DD vs HC nor DD vs ASD; and (3) in the left ILF, no difference in FA was seen between ASD and DD, but FA in both was significantly lower than in the HC.

CONCLUSION

Microstructural white matter properties differed between ASD vs DD and HC subjects. The tract where FA impairment in ASD and DD subjects was the most similar was the left ILF.

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.

From bedside to bench and back: Translating ASD models

Autism spectrum disorders (ASD) represent a heterogeneous group of disorders defined by deficits in social interaction/communication and restricted interests, behaviors, or activities. Models of ASD, developed based on clinical data and observations, are used in basic science, the "bench," to better understand the pathophysiology of ASD and provide therapeutic options for patients in the clinic, the "bedside." Translational medicine creates a bridge between the bench and bedside that allows for clinical and basic science discoveries to challenge one another to improve the opportunities to bring novel therapies to patients. From the clinical side, biomarker work is expanding our understanding of possible mechanisms of ASD through measures of behavior, genetics, imaging modalities, and serum markers. These biomarkers could help to subclassify patients with ASD in order to better target treatments to a more homogeneous groups of patients most likely to respond to a candidate therapy. In turn, basic science has been responding to developments in clinical evaluation by improving bench models to mechanistically and phenotypically recapitulate the ASD phenotypes observed in clinic. While genetic models are identifying novel therapeutics targets at the bench, the clinical efforts are making progress by defining better outcome measures that are most representative of meaningful patient responses. In this review, we discuss some of these challenges in translational research in ASD and strategies for the bench and bedside to bridge the gap to achieve better benefits to patients.

Preliminary mapping of the structural effects of age in pediatric bipolar disorder with multimodal MR imaging

This study investigates multimodal structural MR imaging biomarkers of development trajectories in pediatric bipolar disorder. T1-weighted and diffusion-weighted MR imaging was conducted to investigate cross-sectional group differences with age between typically developing controls (N = 26) and youths diagnosed with bipolar disorder (N = 26). Region-based analysis was used to examine cortical thickness of gray matter and diffusion tensor parameters in superficial white matter, and tractography-based analysis was used to examine deep white matter fiber bundles. Patients and controls showed significantly different maturation trajectories across brain areas; however, the magnitude of differences varied by region. The rate of cortical thinning with age was greater in patients than controls in the left frontal pole. While controls showed increasing fractional anisotropy (FA) and axial diffusivity (AD) with age, patients showed an opposite trend of decreasing FA and AD with age in fronto-temporal-striatal regions located in both superficial and deep white matter. The findings support fronto-temporal-striatal alterations in the developmental trajectories of youths diagnosed with bipolar disorder, and further, show the value of multimodal computational techniques in the assessment of neuropsychiatric disorders. These preliminary results warrant further investigation into longitudinal changes and the effects of treatment in the brain areas identified in this study.

Impaired White Matter Integrity and Social Cognition in High-Function Autism: Diffusion Tensor Imaging Study

OBJECTIVE

It is known that many of the cognitive and social deficits associated with autism can arise from abnormal functional connectivity between brain networks. This aberrant functional connectivity in autism spectrum disorders (ASD) can be explained by impaired integrity of white matter tracts that link distant regions of the networks.

METHODS

We investigated white matter in 9 children with high-function autism (HFA) compared to 13 typically developing controls using diffusion tensor imaging (DTI). The aim of this research is to provide supporting evidence for abnormalities in neural connectivity as an underlying pathophysiology of the main characteristics of ASD.

RESULTS

We found impairment of neural connectivity, mainly in association fiber tracts as evidenced by decreased fractional anisotropy (FA), the index of white matter integrity, of these tracts. Among them, inferior fronto-occipital fasciculus (IFOF) had a significant relationship with ADI-R score. The inferior longitudinal fasciculus (ILF) and superior longitudinal fasciculus (SLF) also showed decreased FA. Decreased FA of ILF and SLF had negative correlations with scores of social interaction.

CONCLUSION

These findings suggest that widespread abnormalities in association fiber tracts may contribute to both core and associated symptoms of ASD.

Correlation of reduced social communicational and interactional skills with regional grey matter volumes in schizophrenia patients

OBJECTIVE

Recent studies have detected similarities between autism spectrum disorder and schizophrenia. We investigated structural abnormalities associated with autistic-like traits in patients with schizophrenia by voxel-based morphometry.

METHODS

Patients with schizophrenia and healthy subjects were evaluated by the adult version of the social responsiveness scale (SRS-A), which is sensitive to autistic traits and symptoms even under subthreshold conditions, and magnetic resonance imaging.

RESULTS

There were significant decreases in the anterior cingulate cortex, bilateral hippocampi, cerebellums, and right insula of patients with schizophrenia, compared with healthy subjects. We found significant negative correlations of the social communication and interaction (SCI) score, a subscale of SRS-A, with grey matter volume in the left posterior superior temporal region of schizophrenia patients. When subscales of SCI were examined separately in schizophrenic patients, negative correlations were observed between the social cognition score and the volumes of the left posterior superior temporal region, and between social motivation and the posterior cingulate cortex.

CONCLUSION

We found significant negative correlation between the SCI score and the grey matter volume in the left posterior superior temporal region of schizophrenia patients. This area was the region affected in previous studies of autistic spectrum disorders. Further, this area was associated with the theory of mind. Schizophrenia patients not necessarily show the impairment of SCI, nor this correlated region was not always the point with schizophrenia-specific change. However, we reveal the relationship between the left posterior superior temporal gyrus and the severity of the SCI in schizophrenia by using with SRS-A.

The effect of feature image on sensitivity of the statistical analysis in the pipeline of a tractography atlas-based analysis

Tractography atlas-based analysis (TABS) is a new diffusion tensor image (DTI) statistical analysis method for detecting and understanding voxel-wise white matter properties along a fiber tract. An important requisite for accurate and sensitive TABS is the availability of a deformation field that is able to register DTI in native space to standard space. Here, three different feature images including the fractional anisotropy (FA) image, T1 weighted image, and the maximum eigenvalue of the Hessian of the FA (hFA) image were used to calculate the deformation fields between individual space and population space. Our results showed that when the FA image was a feature image, the tensor template had the highest consistency with each subject for scalar and vector information. Additionally, to demonstrate the sensitivity and specificity of the TABS method with different feature images, we detected a gender difference along the corpus callosum. A significant difference between the male and female group in diffusion measurement appeared predominantly in the right corpus callosum only when FA was the feature image. Our results demonstrated that the FA image as a feature image was more accurate with respect to the underlying tensor information and had more accurate analysis results with the TABS method.

Altered white-matter integrity in unaffected siblings of probands with autism spectrum disorders

Despite the evidence of altered white-matter tract property in individuals with autism spectrum disorder (ASD), little is known about their unaffected siblings. This study aimed to investigate white-matter integrity in unaffected siblings of ASD probands. Thirty-nine unaffected siblings (mean age 15.6 ± 6.0 years; 27 males, 69.2%) and 39 typically developing controls (TDC) (14.2 ± 5.6 years; 26 males, 66.7%) were assessed with diffusion spectrum images and neuropsychological tests. Using the tract-based automatic analysis and the threshold-free cluster weighted (TFCW) scores, we searched for the segments among 76 tracts with the largest difference over the entire brain compared to TDC. Tract integrity was quantified by calculating the mean generalized fractional anisotropy (mGFA) values of the segments with the largest difference in TFCW scores. Unaffected siblings showed reduced mGFA in the bilateral frontal aslant tracts, the right superior longitudinal fasciculus 2 (SLF2), the frontostriatal tracts from the right dorsolateral and left ventrolateral prefrontal cortices, the thalamic radiations of the left ventral and the right dorsal thalamus, the callosal fibers of the splenium, and the increased mGFA of the callosal fibers of the precuneus and the left inferior longitudinal fasciculus. Among these, reduced right SLF2 mGFA was associated with social awareness deficits; impaired frontostriatal tract was associated with internalizing problems, while right frontal aslant tract integrity was associated with visual memory deficits. In conclusion, unaffected siblings showed the aberrant integrity of several white-matter tracts, which were correlated with clinical symptoms and neurocognitive dysfunction. The altered tract integrity could be further examined in the probands with ASD. Hum Brain Mapp 38:6053-6067, 2017. © 2017 Wiley Periodicals, Inc.

The Default Mode Network in Autism

Autism spectrum disorder (ASD) is characterized by deficits in social communication and interaction. Since its discovery as a major functional brain system, the default mode network (DMN) has been implicated in a number of psychiatric disorders, including ASD. Here we review converging multimodal evidence for DMN dysfunction in the context of specific components of social cognitive dysfunction in ASD: 'self-referential processing' - the ability to process social information relative to oneself and 'theory of mind' or 'mentalizing' - the ability to infer the mental states such as beliefs, intentions, and emotions of others. We show that altered functional and structural organization of the DMN, and its atypical developmental trajectory, are prominent neurobiological features of ASD. We integrate findings on atypical cytoarchitectonic organization and imbalance in excitatory-inhibitory circuits, which alter local and global brain signaling, to scrutinize putative mechanisms underlying DMN dysfunction in ASD. Our synthesis of the extant literature suggests that aberrancies in key nodes of the DMN and their dynamic functional interactions contribute to atypical integration of information about the self in relation to 'other', as well as impairments in the ability to flexibly attend to socially relevant stimuli. We conclude by highlighting open questions for future research.

Neural processing of biological motion in autism: An investigation of brain activity and effective connectivity

The superior temporal sulcus (STS) forms a key region for social information processing and disruptions of its function have been associated with socio-communicative impairments characteristic of autism spectrum disorders (ASD). Task-based fMRI was applied in 15 adults with ASD and 15 matched typical-controls (TC) to explore differences in activity and effective connectivity of STS while discriminating either 'intact' versus 'scrambled' biological motion point light displays (explicit processing) or responding to a color-change while the 'intact' versus 'scrambled' nature of the stimulus was irrelevant for the task (implicit processing). STS responded stronger to 'intact' than 'scrambled' stimuli in both groups, indicating that the basic encoding of 'biological' versus 'non-biological' motion seems to be intact in ASD. Only in the TC-group however, explicit attention to the biological motion content induced an augmentation of STS-activity, which was not observed in the ASD-group. Overall, these findings suggest an inadequacy to recruit STS upon task demand in ASD, rather than a generalized alteration in STS neural processing. The importance of attention orienting for recruiting relevant neural resources was further underlined by the observation that connectivity between STS and medial prefrontal cortex (mPFC), a key region in attention regulation, effectively modulated STS-recruitment in the ASD-group.

White matter microstructure in children with autistic traits

Autism spectrum disorder (ASD) is thought to arise from aberrant development of connections in the brain. Previous studies have identified differences in white matter microstructure in children with ASD, offering support to such hypotheses. While ASD is thought to represent the severe end of a spectrum of traits, there are no studies evaluating white matter microstructure in relation to autistic traits in children from the general population. In a population-based sample of 604 6-to-10 year-old children, we assessed the relation between a continuous measure of autistic traits and white matter microstructure, using both probabilistic tractography and Tract-Based Spatial Statistics (TBSS). Using the TBSS approach, a cluster in the left superior longitudinal fasciculus (SLF) was identified where autistic traits negatively associated with fractional anisotropy (FA). In addition, two clusters of lower axial diffusion were identified; one in the corpus callosum and another in the corticospinal tract. Part of the findings remained when excluding children with ASD and were paralleled with similar, trend-level differences in 19 children with ASD, compared to matched controls. This study showed localized associations between autistic traits on a continuum and white matter microstructure, which could indicate a continuum of the neurobiology along the spectrum of autistic symptoms.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.

Neuroimaging-Based Phenotyping of the Autism Spectrum

Recent advances in neuroimaging have offered a rich array of structural and functional markers to probe the organization of regional and large-scale brain networks. The current chapter provides a brief introduction into these techniques and overviews their contribution to the understanding of autism spectrum disorder (ASD), a neurodevelopmental condition associated with atypical social cognition, language function, and repetitive behaviors/interests. While it is generally recognized that ASD relates to structural and functional network anomalies, the extent and overall pattern of reported findings have been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD (e.g., 'early brain overgrowth hypothesis', 'amygdala theory', 'disconnectivity hypothesis'), none of these frameworks has been without controversy. Methodological sources of inconsistent results may include differences in subject inclusion criteria, variability in image processing, and analysis methodology. However, inconsistencies may also relate to high heterogeneity across the autism spectrum itself. It, therefore, remains to be investigated whether a consistent imaging phenotype that adequately describes the entire autism spectrum can, in fact, be established. On the other hand, as previous findings clearly emphasize the value of neuroimaging in identifying atypical brain morphology, function, and connectivity, they ultimately support its high potential to identify biologically and clinically relevant endophenotypes.

White matter structure in the uncinate fasciculus: Implications for socio-affective deficits in Autism Spectrum Disorder

Individuals with Autism Spectrum Disorder (ASD) have social and communication deficits and difficulties regulating emotions. The brain bases of these socio-affective deficits are not yet clear, but one candidate is structural connectivity in the left uncinate fasciculus, which connects limbic temporal and frontal areas thought to be involved in socio-affective processing. In this study, we assessed white matter structure in the left and right uncinate fasciculus in 18 high-functioning individuals with ASD and 18 group-matched typically developing (TD) controls using Diffusion Tensor Imaging. To test specificity of the associations, we also examined the association between both uncinate fasciculi and restricted and repetitive behaviors. Compared to TD individuals, individuals with ASD had significantly lower fractional anisotropy (FA) in the left and right uncinate. Group status significantly moderated the association between left uncinate and socio-affective deficits, indicating that within the ASD group, FA was associated with socio-affective deficits: Individuals with ASD with lower FA in the left uncinate had significantly more social and emotion regulation deficits. There was no association with restricted and repetitive behaviors. This study provides evidence that the left uncinate may play a critical role in socio-affective skills in individuals with ASD.

Sleep Spindle Characteristics in Children with Neurodevelopmental Disorders and Their Relation to Cognition

Empirical evidence indicates that sleep spindles facilitate neuroplasticity and “off-line” processing during sleep, which supports learning, memory consolidation, and intellectual performance. Children with neurodevelopmental disorders (NDDs) exhibit characteristics that may increase both the risk for and vulnerability to abnormal spindle generation. Despite the high prevalence of sleep problems and cognitive deficits in children with NDD, only a few studies have examined the putative association between spindle characteristics and cognitive function. This paper reviews the literature regarding sleep spindle characteristics in children with NDD and their relation to cognition in light of what is known in typically developing children and based on the available evidence regarding children with NDD. We integrate available data, identify gaps in understanding, and recommend future research directions. Collectively, studies are limited by small sample sizes, heterogeneous populations with multiple comorbidities, and nonstandardized methods for collecting and analyzing findings. These limitations notwithstanding, the evidence suggests that future studies should examine associations between sleep spindle characteristics and cognitive function in children with and without NDD, and preliminary findings raise the intriguing question of whether enhancement or manipulation of sleep spindles could improve sleep-dependent memory and other aspects of cognitive function in this population.

Frontal networks in adults with autism spectrum disorder

It has been postulated that autism spectrum disorder is underpinned by an 'atypical connectivity' involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a 'whole brain' non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate--predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these results suggest that autism spectrum disorder is a condition linked to aberrant developmental trajectories of the frontal networks that persist in adult life.

Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder

White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.