Disrupted focal white matter integrity in autism spectrum disorder: A voxel-based meta-analysis of diffusion tensor imaging studies

Intrinsic disruption of white matter microarchitecture in major depressive disorder: A voxel-based meta analysis of diffusion tensor imaging

BACKGROUND

Major depressive disorder (MDD) is a prevalent and disabling mood disorder, thought to be linked with brain white matter (WM) alterations. Prior diffusion tensor imaging (DTI) studies have reported inconsistent changes in fractional anisotropy (FA) across different brain regions in MDD patients. However, none of these studies utilized raw t-map data for WM meta-analysis in MDD. Our study aims to address this gap by conducting a whole-brain-based meta-analysis of FA in MDD using Seed-based d mapping via permutation of subject images (SDM-PSI), combining reported peak coordinates and raw statistical parametric maps.

OBJECTIVES

Following PRISMA guidelines, we performed a systematic search and meta-analysis to compare FA in MDD patients with healthy controls (HC). Our goal was to identify WM abnormalities in MDD, using SDM, which could shed light on the disorder's pathogenesis.

RESULTS

The meta-analysis included 39 studies with 3696 participants (2094 with MDD, 1602HC). It revealed that MDD patients, in comparison to HC, have lower FA in the corpus callosum (CC) and anterior thalamic projections (ATP). Subgroup analyses indicated that the CC is a more stable pathogenic factor in MDD. Meta-regression analyses showed no linear correlation between the mean age, percentage of female patients, duration of depression, and FA abnormalities. This suggests that WM impairments in interhemispheric connections and anterior thalamocortical circuits are significant in the pathogenesis of MDD.

Comparison of resting-state brain activity between insomnia and generalized anxiety disorder: A coordinate-based meta-analysis

Patients with insomnia disorder (ID) usually experience a greater burden of comorbid anxiety symptoms. However, the neural mechanism under the mutual relationship between ID and anxiety remains largely unclear. The meta-analysis aimed to explore the concordance and distinction of regional brain functional activity in patients with ID and those with generalized anxiety disorder (GAD) using coordinate-based activation likelihood estimation approach. Studies using resting-state regional homogeneity, amplitude of low-frequency fluctuations (ALFF), or fractional ALFF in patients with ID or GAD were included by searching multiple databases up to May 24, 2024. Using meta-analytic approach, 21 studies of ID vs. healthy controls (HC) and 16 studies of GAD vs. HC were included to illuminate the common and distinct patterns between the two disorders. Results showed that ID and GAD shared increased brain activities in the left posterior cingulate cortex and left precuneus, as well as decreased brain activity in the left medial prefrontal cortex. Additionally, compared with ID, GAD showed greater increased activities in the left superior frontal gyrus. Our study reveals both common and different activation patterns between ID and GAD, which may provide novel insights for understanding the neural basis of the two disorders and enlighten the possibility of the development of more targeted treatment strategies for ID and GAD.

Transcallosal white matter and cortical gray matter variations in autistic adults ages 30-73 years: A bi-tensor free water imaging approach

Background: Autism spectrum disorder (ASD) has long been recognized as a lifelong condition, but brain aging studies in autistic adults aged >30 years are limited. Free water, a novel brain imaging marker derived from diffusion MRI (dMRI), has shown promise in differentiating typical and pathological aging and monitoring brain degeneration. We aimed to examine free water and free water corrected dMRI measures to assess white and gray matter microstructure and their associations with age in autistic adults. Methods: Forty-three autistic adults ages 30-73 years and 43 age, sex, and IQ matched neurotypical controls participated in this cross-sectional study. We quantified fractional anisotropy (FA), free water, and free water-corrected FA (fwcFA) across 32 transcallosal white matter tracts and 94 gray matter areas in autistic adults and neurotypical controls. Follow-up analyses assessed age effect on dMRI metrics of the whole brain for both groups and the relationship between dMRI metrics and clinical measures of ASD in regions that significantly differentiated autistic adults from controls. Results: We found globally elevated free water in 24 transcallosal tracts in autistic adults. We identified negligible differences in dMRI metrics in gray matter between the two groups. Age-associated FA reductions and free water increases were featured in neurotypical controls; however, this brain aging profile was largely absent in autistic adults. Additionally, greater autism quotient (AQ) total raw score was associated with increased free water in the inferior frontal gyrus pars orbitalis and lateral orbital gyrus in autistic adults. Limitations: All autistic adults were cognitively capable individuals, minimizing the generalizability of the research findings across the spectrum. This study also involved a cross-sectional design, which limited inferences about the longitudinal microstructural changes of white and gray matter in ASD. Conclusions: We identified differential microstructural configurations between white and gray matter in autistic adults and that autistic individuals present more heterogeneous brain aging profiles compared to controls. Our clinical correlation analysis offered new evidence that elevated free water in some localized white matter tracts may critically contribute to autistic traits in ASD. Our findings underscored the importance of quantifying free water in dMRI studies of ASD.

Pervasive alterations of intra-axonal volume and network organization in young children with a 16p11.2 deletion

Reciprocal Copy Number Variants (CNVs) at the 16p11.2 locus confer high risk for autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDDs). Morphometric MRI studies have revealed large and pervasive volumetric alterations in carriers of a 16p11.2 deletion. However, the specific neuroanatomical mechanisms underlying such alterations, as well as their developmental trajectory, are still poorly understood. Here we explored differences in microstructural brain connectivity between 24 children carrying a 16p11.2 deletion and 66 typically developing (TD) children between 2 and 8 years of age. We found a large pervasive increase of intra-axonal volume widespread over a high number of white matter tracts. Such microstructural alterations in 16p11.2 deletion children were already present at an early age, and led to significant changes in the global efficiency and integration of brain networks mainly associated to language, motricity and socio-emotional behavior, although the widespread pattern made it unlikely to represent direct functional correlates. Our results shed light on the neuroanatomical basis of the previously reported increase of white matter volume, and align well with analogous evidence of altered axonal diameter and synaptic function in 16p11.2 mice models. We provide evidence of a prevalent mechanistic deviation from typical maturation of brain structural connectivity associated with a specific biological risk to develop ASD. Future work is warranted to determine how this deviation contributes to the emergence of symptoms observed in young children diagnosed with ASD and other NDDs.

White and Gray Matter Abnormalities in Young Adult Females with Dependent Personality Disorder: A Diffusion-Tensor Imaging and Voxel-Based Morphometry Study

We applied diffusion-tensor imaging (DTI) including measurements of fractional anisotropy (FA), a parameter of neuronal fiber integrity, mean diffusivity (MD), a parameter of brain tissue integrity, as well as voxel-based morphometry (VBM), a measure of gray and white matter volume, to provide a basis to improve our understanding of the neurobiological basis of dependent personality disorder (DPD). DTI was performed on young girls with DPD (N = 17) and young female healthy controls (N = 17). Tract-based spatial statistics (TBSS) were used to examine microstructural characteristics. Gray matter volume differences between the two groups were investigated using voxel-based morphometry (VBM). The Pearson correlation analysis was utilized to examine the relationship between distinct brain areas of white matter and gray matter and the Dy score on the MMPI. The DPD had significantly higher fractional anisotropy (FA) values than the HC group in the right retrolenticular part of the internal capsule, right external capsule, the corpus callosum, right posterior thalamic radiation (include optic radiation), right cerebral peduncle (p < 0.05), which was strongly positively correlated with the Dy score of MMPI. The volume of gray matter in the right postcentral gyrus and left cuneus in DPD was significantly increased (p < 0.05), which was strongly positively correlated with the Dy score of MMPI (r1,2= 0.467,0.353; p1,2 = 0.005,0.04). Our results provide new insights into the changes in the brain structure in DPD, which suggests that alterations in the brain structure might implicate the pathophysiology of DPD. Possible visual and somatosensory association with motor nerve circuits in DPD.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

Poor response to methylphenidate is associated with a smaller dorsal attentive network in adult Attention-Deficit/Hyperactivity Disorder (ADHD)

Stimulants, such as methylphenidate (MPH), are effective in treating attention-deficit/hyperactivity disorder (ADHD), but there is individual variability in response, especially in adults. To improve outcomes, we need to understand the factors associated with adult treatment response. This longitudinal study investigated whether pre-treatment anatomy of the fronto-striatal and fronto-parietal attentional networks was associated with MPH treatment response. 60 adults with ADHD underwent diffusion brain imaging before starting MPH treatment, and response was measured at two months. We tested the association between brain anatomy and treatment response by using regression-based approaches; and compared the identified anatomical characteristics with those of 20 matched neurotypical controls in secondary analyses. Finally, we explored whether combining anatomical with clinical and neuropsychological data through machine learning provided a more comprehensive profile of factors associated with treatment response. At a group level, a smaller left dorsal superior longitudinal fasciculus (SLF I), a tract responsible for the voluntary control of attention, was associated with a significantly lower probability of being responders to two-month MPH-treatment. The association between the volume of the left SLF I and treatment response was driven by improvement on both inattentive and hyperactive/impulsive symptoms. Only non-responders significantly differed from controls in this tract metric. Finally, our machine learning approach identified clinico-neuropsychological factors associated with treatment response, such as higher cognitive performance and symptom severity at baseline. These novel findings add to our understanding of the pathophysiological mechanisms underlying response to MPH, pointing to the dorsal attentive network as playing a key role.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

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.

The shared white matter developmental trajectory anomalies of attention-deficit/hyperactivity disorder and autism spectrum disorders: A meta-analysis of diffusion tensor imaging studies

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) show common brain area abnormalities, which may contribute to the high shared co-occurrence symptoms and comorbidity of the two disorders. However, neuroanatomic anomalies in neurodevelopmental disorders may change over the course of development, and the developmental variation of these two disorders is unclear. Our study conducted a systematic literature search of PubMed, Web of Science, and EMBASE databases to identify disorder-shared abnormalities of white matter (WM) from childhood to adulthood in ADHD and ASD. 28 ADHD and 23 ASD datasets were included in this meta-analysis and were analysed by AES-SDM to detect differences in fractional anisotropy in patients compared to typically developing individuals. Our main findings reveal the variable WM developmental trajectories in ADHD and ASD respectively, and the two disorders showed overlapping corpus callosum tract abnormalities in their development from children to adults. Furthermore, the overlapping abnormalities of the corpus callosum tract increased with age, which may be related to their gradually increasing shared symptoms and comorbidity in these two disorders.

A brain structural connectivity biomarker for autism spectrum disorder diagnosis in early childhood

Background

Autism spectrum disorder (ASD) is associated with altered brain development, but it is unclear which specific structural changes may serve as potential diagnostic markers, particularly in young children at the age when symptoms become fully established. Furthermore, such brain markers need to meet the requirements of precision medicine and be accurate in aiding diagnosis at an individual rather than only a group level.

Objective

This study aimed to identify and model brain-wide differences in structural connectivity using diffusion tensor imaging (DTI) in young ASD and typically developing (TD) children.

Methods

A discovery cohort including 93 ASD and 26 TD children and two independent validation cohorts including 12 ASD and 9 TD children from three different cities in China were included. Brain-wide (294 regions) structural connectivity was measured using DTI (fractional anisotropy, FA) together with symptom severity and cognitive development. A connection matrix was constructed for each child for comparisons between ASD and TD groups. Pattern classification was performed on the discovery dataset and the resulting model was tested on the two independent validation datasets.

Results

Thirty-three structural connections showed increased FA in ASD compared to TD children and associated with both autistic symptom severity and impaired general cognitive development. The majority (29/33) involved the frontal lobe and comprised five different networks with functional relevance to default mode, motor control, social recognition, language and reward. Overall, classification achieved very high accuracy of 96.77% in the discovery dataset, and 91.67% and 88.89% in the two independent validation datasets.

Conclusions

Identified structural connectivity differences primarily involving the frontal cortex can very accurately distinguish novel individual ASD from TD children and may therefore represent a robust early brain biomarker which can address the requirements of precision medicine.

Translational Neuroscience Approaches to Understanding Autism

While autism spectrum disorder affects nearly 2% of children in the United States, little is known with certainty concerning the etiologies and brain systems involved. This is due, in part, to the substantial heterogeneity in the presentation of the core symptoms of autism as well as the great number of co-occurring conditions that are common in autistic individuals. Understanding the neurobiology of autism is further hampered by the limited availability of postmortem brain tissue to determine the cellular and molecular alterations that take place in the autistic brain. Animal models therefore provide great translational value in helping to define the neural systems that constitute the social brain and mediate repetitive behaviors or interests. If they are based on genetic or environmental factors that contribute to autism, organisms from flies to nonhuman primates may serve as models of the neural structure or function of the autistic brain. Ultimately, successful models can also be employed to test the safety and effectiveness of potential therapeutics. This is an overview of the major animal species that are currently used as models of autism, including an appraisal of the advantages and limitations of each.

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.

White matter microstructural abnormalities and gray matter volume alterations in obsessive-compulsive disorder: A coordinate-based meta-analysis

OBJECTIVE

A comprehensive meta-analysis using correlated coordinate data to explore abnormalities in white matter (WM) microarchitecture and changes in gray matter volume (GMV) in patients with obsessive-compulsive disorder (OCD).

METHODS

We reviewed 23 reported studies of diffusion tensor imaging (DTI) in OCD patients. The differences in WM fractional anisotropy (FA) between OCD patients and healthy controls (HCs) were investigated using tract-based spatial statistics (TBSS) and voxel-based analysis (VBA), respectively, and the results of the two methods were compared. In addition, we will explore changes in OCD GMV by analyzing studies (n = 21) using the voxel-based morphometry (VBM) approach and comparing the difference between adults and adolescents.

RESULTS

In the pooled meta-analysis, WM study results presented that compared with HCs, OCD patients had higher FA in right lenticular nucleus (putamen), and lower FA in corpus callosum (CC), left insula, right cerebellum (hemispheric lobule), right gyrus rectal and left inferior parietal gyri. However, in subgroup analysis, there was a significant difference in FA changes between TBSS and VBA in OCD patients compared with HCs. In addition, we found that the GMV of OCD patients was significantly increased in left striatum and left precentral gyrus, and significantly decreased in right inferior frontal gyrus triangular part, right superior temporal gyrus and right hippocampus. Compared with adolescents, adult patients have increased GMV in left lenticular nucleus putamen.

CONCLUSION

The meta-analysis showed that OCD patients had abnormal WM microarchitecture and altered GMV. These changes may be closely related to the pathophysiological mechanism of the disease.

Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.

Specific tractography differences in autism compared to developmental coordination disorder

About 85% of children with autism spectrum disorder (ASD) experience comorbid motor impairments, making it unclear whether white matter abnormalities previously found in ASD are related to social communication deficits, the hallmark of ASD, or instead related to comorbid motor impairment. Here we aim to understand specific white matter signatures of ASD beyond those related to comorbid motor impairment by comparing youth (aged 8-18) with ASD (n = 22), developmental coordination disorder (DCD; n = 16), and typically developing youth (TD; n = 22). Diffusion weighted imaging was collected and quantitative anisotropy, radial diffusivity, mean diffusivity, and axial diffusivity were compared between the three groups and correlated with social and motor measures. Compared to DCD and TD groups, diffusivity differences were found in the ASD group in the mid-cingulum longitudinal and u-fibers, the corpus callosum forceps minor/anterior commissure, and the left middle cerebellar peduncle. Compared to the TD group, the ASD group had diffusivity differences in the right inferior frontal occipital/extreme capsule and genu of the corpus callosum. These diffusion differences correlated with emotional deficits and/or autism severity. By contrast, children with DCD showed unique abnormality in the left cortico-spinal and cortico-pontine tracts.Trial Registration All data are available on the National Institute of Mental Health Data Archive: https://nda.nih.gov/edit_collection.html?id=2254 .

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.

Neuroanatomical correlates of autism spectrum disorders: A meta-analysis of structural magnetic resonance imaging (MRI) studies

Autism spectrum disorders (ASD) are neurodevelopmental disorders correlated to various neuroanatomical modifications. We aimed to identify neuroanatomical changes assessed in magnetic resonance imaging (MRI) studies of autism spectrum disorder (ASD) through Activation Likelihood Estimate (ALE) meta-analysis. We included 19 peer-reviewed magnetic resonance imaging (MRI) studies that analyzed cortical volume in patients with ASD compared to healthy control subjects (HCs). The between-group analyses comparing subjects with ASD to HCs showed a volumetric reduction of a large cluster in the right brain, including the uncus/amygdala, parahippocampal gyrus, and entorhinal cortex, and putamen. The anomalies are primarily found in the right hemisphere, involved in social cognitive function, particularly impaired in ASD. These results correlate with several clinical aspects of ASD. These volumetric alterations can be considered a major correlate of disease in the context of multifactorial etiology. Further studies on brain lateralization in ASD are needed, considering the clinical phenotype variability of these disorders.

Altered topological properties of white matter structural network in adults with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a complex developmental disability and is currently viewed as a disorder of brain connectivity in which white matter abnormalities. However, the majority of the research to date has focused on children with ASD. Understanding the topological organization of the white matter structural network in adults may help uncover the nature of ASD pathology in adulthood.

METHOD

This study investigated the topological properties of white matter structural network using diffusion tensor imaging and graph theory analysis in a sample of 32 adults with ASD compared to 35 matched typically developing (TD) controls. Group differences in global and nodal topological metrics were compared. The relationships between the altered network metrics and the severity of clinical symptoms were calculated.

RESULTS

Compared to TD controls, ASD patients exhibited decreased small-worldness and increased global efficiency. In addition, the reduced nodal efficiency and increased nodal degree were found in the frontal (e.g., the inferior frontal gyrus) and parietal (e.g., postcentral gyrus) regions. Furthermore, the altered topological metrics (e.g., increased global efficiency and reduced nodal efficiency) were correlated with the severity of ASD symptoms.

CONCLUSION

These results indicated that the complicatedly topological organization of the white matter structural network was abnormal and may play an essential role in the underlying pathological mechanism of ASD in adults.

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.

Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder

BACKGROUND

Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management.

METHODS

We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively.

RESULTS

Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants.

CONCLUSIONS

Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.

White matter microstructural and morphometric alterations in autism: implications for intellectual capabilities

Background

Neuroimage literature of autism spectrum disorder (ASD) has a moderate-to-high risk of bias, partially because those combined with intellectual impairment (II) and/or minimally verbal (MV) status are generally ignored. We aimed to provide more comprehensive insights into white matter alterations of ASD, inclusive of individuals with II (ASD-II-Only) or MV expression (ASD-MV).

Methods

Sixty-five participants with ASD (ASD-Whole; 16.6 ± 5.9 years; comprising 34 intellectually able youth, ASD-IA, and 31 intellectually impaired youth, ASD-II, including 24 ASD-II-Only plus 7 ASD-MV) and 38 demographic-matched typically developing controls (TDC; 17.3 ± 5.6 years) were scanned in accelerated diffusion-weighted MRI. Fixel-based analysis was undertaken to investigate the categorical differences in fiber density (FD), fiber cross section (FC), and a combined index (FDC), and brain symptom/cognition associations.

Results

ASD-Whole had reduced FD in the anterior and posterior corpus callosum and left cerebellum Crus I, and smaller FDC in right cerebellum Crus II, compared to TDC. ASD-IA, relative to TDC, had no significant discrepancies, while ASD-II showed almost identical alterations to those from ASD-Whole vs. TDC. ASD-II-Only had greater FD/FDC in the isthmus splenium of callosum than ASD-MV. Autistic severity negatively correlated with FC in right Crus I. Nonverbal full-scale IQ positively correlated with FC/FDC in cerebellum VI. FD/FDC of the right dorsolateral prefrontal cortex showed a diagnosis-by-executive function interaction.

Limitations

We could not preclude the potential effects of age and sex from the ASD cohort, although statistical tests suggested that these factors were not influential. Our results could be confounded by variable psychiatric comorbidities and psychotropic medication uses in our ASD participants recruited from outpatient clinics, which is nevertheless closer to a real-world presentation of ASD. The outcomes related to ASD-MV were considered preliminaries due to the small sample size within this subgroup. Finally, our study design did not include intellectual impairment-only participants without ASD to disentangle the mixture of autistic and intellectual symptoms.

Conclusions

ASD-associated white matter alterations appear driven by individuals with II and potentially further by MV. Results suggest that changes in the corpus callosum and cerebellum are key for psychopathology and cognition associated with ASD. Our work highlights an essential to include understudied subpopulations on the spectrum in research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00499-1.

Identify aberrant white matter microstructure in ASD, ADHD and other neurodevelopmental disorders: A meta-analysis of diffusion tensor imaging studies

BACKGROUND

Neurodevelopmental disorders (NDDs) usually present overlapping symptoms. Abnormal white matter (WM) microstructure has been found in these disorders. Identification of common and unique neural abnormalities across NDDs could provide further insight into the underlying pathophysiological mechanisms.

METHODS

We performed a voxel-based meta-analysis of whole-brain diffusion tensor imaging (DTI) studies in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and other NDDs. A systematic literature search was conducted through March 2020 to identify studies that compared measures of WM microstructure between patients with NDDs and neurotypical controls. Peak voxel coordinates were meta-analyzed via anisotropic effect size-signed differential mapping (AES-SDM) as well as activation likelihood estimation (ALE).

RESULTS

Our final sample included a total of 4137 subjects from 66 studies across five NDDs. Fractional anisotropy (FA) reductions were found in the splenium of the CC in ADHD, and the genu and splenium of CC in ASD. And mean diffusivity (MD) increases were shown in posterior thalamic radiation in ASD. No consistent abnormalities were detected in specific learning disorder, motor disorder or communication disorder. Significant differences between child/adolescent and adult patients were found within the CC across NDDs, reflective of aberrant neurodevelopmental processes in NDDs.

CONCLUSIONS

The current study demonstrated atypical WM patterns in ASD, ADHD and other NDDs. Microstructural abnormalities in the splenium of the CC were possibly shared among ASD and ADHD.

A callosal biomarker of behavioral intervention outcomes for autism spectrum disorder? A case-control feasibility study with diffusion tensor imaging

Tentative results from feasibility analyses are critical for planning future randomized control trials (RCTs) in the emerging field of neural biomarkers of behavioral interventions. The current feasibility study used MRI-derived diffusion imaging data to investigate whether it would be possible to identify neural biomarkers of a behavioral intervention among people diagnosed with autism spectrum disorder (ASD). The corpus callosum has been linked to cognitive processing and callosal abnormalities have been previously found in people diagnosed with ASD. We used a case-control design to evaluate the association between the type of intervention people diagnosed with ASD had previously received and their current white matter integrity in the corpus callosum. Twenty-six children and adolescents with ASD, with and without a history of parent-managed behavioral intervention, underwent an MRI scan with a diffusion data acquisition sequence. We conducted tract-based spatial statistics and a region of interest analysis. The fractional anisotropy values (believed to indicate white matter integrity) in the posterior corpus callosum was significantly different across cases (exposed to parent-managed behavioral intervention) and controls (not exposed to parent-managed behavioral intervention). The effect was modulated by the intensity of the behavioral intervention according to a dose-response relationship. The current feasibility case-control study provides the basis for estimating the statistical power required for future RCTs in this field. In addition, the study demonstrated the effectiveness of purposely-developed motion control protocols and helped to identify regions of interest candidates. Potential clinical applications of diffusion tensor imaging in the evaluation of treatment outcomes in ASD are discussed.

Looking Back at the Next 40 Years of ASD Neuroscience Research

During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.

Cingulo-opercular and Cingulo-parietal Brain Networks Functional Connectivity in Pre-adolescents: Multiplicative Effects of Race, Ethnicity, and Parental Education

Introduction

A growing body of research has shown a diminished association between socioeconomic status (SES) indicators and a wide range of neuroimaging indicators for racial and ethnic minorities compared to majority groups. However, less is known about these effects for resting-state functional connectivity between various brain networks.

Purpose

This study investigated racial and ethnic variation in the correlation between parental education and resting-state functional connectivity between the cingulo-opercular (CO) and cingulo-parietal (CP) networks in children.

Methods

This cross-sectional study used data from the Adolescent Brain Cognitive Development (ABCD) study; we analyzed the resting-state functional Magnetic Resonance Imaging (rsfMRI) data of 8,464 American pre-adolescents between the ages of 9 and 10. The main outcome measured was resting-state functional connectivity between the CO and CP networks calculated using rsfMRI. The independent variable was parental education, which was treated as a nominal variable. Age, sex, and family marital status were the study covariates. Race and ethnicity were the moderators. Mixed-effects regression models were used for data analysis, with and without interaction terms between parental education and race and ethnicity.

Results

Higher parental education was associated with higher resting-state functional connectivity between the CO and CP networks. Race and ethnicity both showed statistically significant interactions with parental education on children's resting-state functional connectivity between CO and CP networks, suggesting that the correlation between parental education and the resting-state functional connectivity was significantly weaker for Black and Hispanic pre-adolescents compared to White and non-Hispanic pre-adolescents.

Conclusions

In line with the Minorities' Diminished Returns theory, the association between parental education and pre-adolescents resting-state functional connectivity between CO and CP networks may be weaker in Black and Hispanic children than in White and non-Hispanic children. The weaker link between parental education and brain functional connectivity for Blacks and Hispanics than for Whites and non-Hispanics may reflect racism, racialization, and social stratification that collectively minimize the returns of SES indicators, such as parental education for non-Whites, who become others in the US.

Overconnectivity of the right Heschl's and inferior temporal gyrus correlates with symptom severity in preschoolers with autism spectrum disorder

Previous studies have reported varying findings regarding the association of brain connectivity in autism spectrum disorder (ASD) with overconnectivity, underconnectivity, or both. Despite the emerging understanding that ASD is a developmental disconnection syndrome, very little is known about structural brain networks in preschool‐aged children with low‐functioning ASD. We aimed to investigate the structural brain connectivity of low‐functioning ASD using diffusion magnetic resonance imaging and graph theory to examine alterations in different brain network topologies and identify any correlations with the clinical severity of ASD in preschool‐aged children. Fifty‐two preschool‐aged children (28 with ASD and 24 with typical development) were included in the analysis. Graph‐based network analysis was performed to examine the global and local structural brain networks. Nodal network measures exhibited increased nodal strength in the right Heschl's gyrus, which was positively associated with all autistic clinical symptoms (Autism Diagnostic Observation Schedule and Childhood Autism Rating Scale [CARS]). The nodal strength of the right inferior temporal gyrus showed a moderate correlation with the CARS score. Using network‐based statistics, we identified a subnetwork with increased connections encompassing the right Heschl's gyrus and the right inferior temporal gyrus in preschool‐aged children with ASD. The asymmetric value in the inferior temporal gyrus exhibited right dominance of nodal strength in children with ASD compared to that in typically developing children. Our findings support the theory of aberrant brain growth and overconnectivity as the underlying mechanism of ASD and provides new insights into potential regional biomarkers that can detect low‐functioning ASD in preschool‐aged children.

Machine learning with neuroimaging data to identify autism spectrum disorder: a systematic review and meta-analysis

PURPOSE

Autism Spectrum Disorder (ASD) is diagnosed through observation or interview assessments, which is time-consuming, subjective, and with questionable validity and reliability. Thus, we aimed to evaluate the role of machine learning (ML) with neuroimaging data to provide a reliable classification of ASD.

METHODS

A systematic search of PubMed, Scopus, and Embase was conducted to identify relevant publications. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess the studies' quality. A bivariate random-effects model meta-analysis was employed to evaluate the pooled sensitivity, the pooled specificity, and the diagnostic performance through the hierarchical summary receiver operating characteristic (HSROC) curve of ML with neuroimaging data in classifying ASD. Meta-regression was also performed.

RESULTS

Forty-four studies (5697 ASD and 6013 typically developing individuals [TD] in total) were included in the quantitative analysis. The pooled sensitivity for differentiating ASD from TD individuals was 86.25 95% confidence interval [CI] (81.24, 90.08), while the pooled specificity was 83.31 95% CI (78.12, 87.48) with a combined area under the HSROC (AUC) of 0.889. Higgins I² (> 90%) and Cochran's Q (p < 0.0001) suggest a high degree of heterogeneity. In the bivariate model meta-regression, a higher pooled specificity was observed in studies not using a brain atlas (90.91 95% CI [80.67, 96.00], p = 0.032). In addition, a greater pooled sensitivity was seen in studies recruiting both males and females (89.04 95% CI [83.84, 92.72], p = 0.021), and combining imaging modalities (94.12 95% [85.43, 97.76], p = 0.036).

CONCLUSION

ML with neuroimaging data is an exciting prospect in detecting individuals with ASD but further studies are required to improve its reliability for usage in clinical practice.

The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project design and methodologies: a dimensional approach to understanding neurobiological and genetic aetiology

Background

ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters.

Methods

The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics.

Conclusion

The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00457-3.

Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder

Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.

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.

Impact of Machine Learning Pipeline Choices in Autism Prediction From Functional Connectivity Data

Autism Spectrum Disorder (ASD) is a largely prevalent neurodevelopmental condition with a big social and economical impact affecting the entire life of families. There is an intense search for biomarkers that can be assessed as early as possible in order to initiate treatment and preparation of the family to deal with the challenges imposed by the condition. Brain imaging biomarkers have special interest. Specifically, functional connectivity data extracted from resting state functional magnetic resonance imaging (rs-fMRI) should allow to detect brain connectivity alterations. Machine learning pipelines encompass the estimation of the functional connectivity matrix from brain parcellations, feature extraction, and building classification models for ASD prediction. The works reported in the literature are very heterogeneous from the computational and methodological point of view. In this paper, we carry out a comprehensive computational exploration of the impact of the choices involved while building these machine learning pipelines. Specifically, we consider six brain parcellation definitions, five methods for functional connectivity matrix construction, six feature extraction/selection approaches, and nine classifier building algorithms. We report the prediction performance sensitivity to each of these choices, as well as the best results that are comparable with the state of the art.

Emerging behavioral and neuroimaging biomarkers for early and accurate characterization of autism spectrum disorders: a systematic review

The possibility of early treatment and a better outcome is the direct product of early identification and characterization of any pathological condition. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairment in social communication, restricted, and repetitive patterns of behavior. In recent times, various tools and methods have been developed for the early identification and characterization of ASD features as early as 6 months of age. Thorough and exhaustive research has been done to identify biomarkers in ASD using noninvasive neuroimaging and various molecular methods. By employing advanced assessment tools such as MRI and behavioral assessment methods for accurate characterization of the ASD features and may facilitate pre-emptive interventional and targeted therapy programs. However, the application of advanced quantitative MRI methods is still confined to investigational/laboratory settings, and the clinical implication of these imaging methods in personalized medicine is still in infancy. Longitudinal research studies in neurodevelopmental disorders are the need of the hour for accurate characterization of brain-behavioral changes that could be monitored over a period of time. These findings would be more reliable and consistent with translating into the clinics. This review article aims to focus on the recent advancement of early biomarkers for the characterization of ASD features at a younger age using behavioral and quantitative MRI methods.

Microstructural white matter abnormalities in obsessive-compulsive disorder: A coordinate-based meta-analysis of diffusion tensor imaging studies

BACKGROUND

There are no conclusive diffusion tensor imaging (DTI) findings on obsessive-compulsive disorder (OCD) for now. We conducted a comprehensive meta-analysis of DTI studies to identify white matter (WM) microarchitecture changes in OCD, and also to compare the results differences between the two most frequently used methods (voxel-based analysis, VBA versus tract-based spatial statistics, TBSS) for DTI data.

METHODS

A systematic search was performed on relevant studies that reported fractional anisotropy (FA) alterations between patients with OCD and healthy controls (HC). Seed-based d mapping (SDM) was applied to analyze microstructural WM abnormalities in OCD patients. Subgroup meta-analysis was subsequently performed to explore methodological differences between VBA and TBSS approaches.

RESULTS

A total of 30 studies (with 31 datasets) that comprised 855 patients and 875 HC were identified. OCD patients exhibited significantly decreased FA in the right cerebellar hemispheric lobule, corpus callosum (CC), left superior frontal gyrus (orbital part), right gyrus rectus, left superior longitudinal fasciculus and right lenticular nucleus in the pooled meta-analysis. The VBA subgroup showed lower FA in several brain regions while the TBSS subgroup only exhibited significant FA reductions in the CC.

CONCLUSION

According to the pooled meta-analysis, OCD patients presented microstructural abnormalities in distributed WM tracts. However, heterogeneous results were found between VBA and TBSS studies.

Air Pollution-Related Brain Metal Dyshomeostasis as a Potential Risk Factor for Neurodevelopmental Disorders and Neurodegenerative Diseases

Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. Excess brain exposure to either essential or non-essential elements can result in brain dyshomeostasis, which has been implicated in both neurodevelopmental disorders (NDDs; autism spectrum disorder, schizophrenia, and attention deficit hyperactivity disorder) and neurodegenerative diseases (NDGDs; Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis). This review summarizes the current understanding of the extent to which the inhalational or intranasal instillation of metals reproduces in vivo the shared features of NDDs and NDGDs, including enlarged lateral ventricles, alterations in myelination, glutamatergic dysfunction, neuronal cell death, inflammation, microglial activation, oxidative stress, mitochondrial dysfunction, altered social behaviors, cognitive dysfunction, and impulsivity. Although evidence is limited to date, neuronal cell death, oxidative stress, and mitochondrial dysfunction are reproduced by numerous metals. Understanding the specific contribution of metals/trace elements to this neurotoxicity can guide the development of more realistic animal exposure models of human AP exposure and consequently lead to a more meaningful approach to mechanistic studies, potential intervention strategies, and regulatory requirements.

Elevated serum neurofilament light chain in children autism spectrum disorder: A case control study

OBJECTIVE

We aimed to assess serum neurofilament light chain (sNfL) levels in autism spectrum disorder (ASD) and to investigate whether they are related to the severity of disease.

METHODS

The cohorts consisted of 166 children aged 3-8 (83 children diagnosed with ASD and 83 children with typically-developing). sNfL were analyzed using Single Molecule Array (Simoa) technology. ASD symptom severity was assessed according to the Chinese version of the Childhood Autism Rating Scale (CARS) score.

RESULTS

The mean age of those included ASD was 5.1 years (standard deviations [S.D.]: 1.7) and 78.3 % were boys. The mean (SD) sNfL concentrations were significantly (P < 0.001) higher in ASD than in TP children (10.2[5.0] pg/mL and 7.1[3.2]pg/mL). For each 1 pg/mL increase of sNfL, the risk of ASD would increase by 19 % (with the OR _unadjusted of 1.19 [95 % CI 1.10-1.29], P < 0.001) and 11 % (with the OR _adjusted of 1.11 [1.03-1.23], P < 0.001), respectively. sNfL concentrations in children with severe ASD were higher than in those children with mild-to-moderate ASD (12.4[5.1] pg/mL vs. 8.3[4.2]pg/mL; P < 0.001). Among ASD cases, each 1 pg/mL increase of sNfL is associated with 20 % higher unadjusted or 11 % higher adjusted odds, respectively, of severe (vs. mild-to-moderate) ASD.

CONCLUSIONS

The data showed that sNfL was elevated in ASD and related to symptom severity, suggesting that sNfL may play a role in ASD progression.

Reduced White Matter Fiber Density in Autism Spectrum Disorder

Differences in brain networks and underlying white matter abnormalities have been suggested to underlie symptoms of autism spectrum disorder (ASD). However, robustly characterizing microstructural white matter differences has been challenging. In the present study, we applied an analytic technique that calculates structural metrics specific to differently-oriented fiber bundles within a voxel, termed "fixels". Fixel-based analyses were used to compare diffusion-weighted magnetic resonance imaging data from 25 individuals with ASD (mean age = 16.8 years) and 27 typically developing age-matched controls (mean age = 16.9 years). Group comparisons of fiber density (FD) and bundle morphology were run on a fixel-wise, tract-wise, and global white matter (GWM) basis. We found that individuals with ASD had reduced FD, suggestive of decreased axonal count, in several major white matter tracts, including the corpus callosum (CC), bilateral inferior frontal-occipital fasciculus, right arcuate fasciculus, and right uncinate fasciculus, as well as a GWM reduction. Secondary analyses assessed associations with social impairment in participants with ASD, and showed that lower FD in the splenium of the CC was associated with greater social impairment. Our findings suggest that reduced FD could be the primary microstructural white matter abnormality in ASD.

White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

A diffusion-weighted imaging tract-based spatial statistics study of autism spectrum disorder in preschool-aged children

BACKGROUND

The core symptoms of autism spectrum disorder (ASD) are widely theorized to result from altered brain connectivity. Diffusion-weighted magnetic resonance imaging (DWI) has been a versatile method for investigating underlying microstructural properties of white matter (WM) in ASD. Despite phenotypic and etiological heterogeneity, DWI studies in majority male samples of older children, adolescents, and adults with ASD have largely reported findings of decreased fractional anisotropy (FA) across several commissural, projection, and association fiber tracts. However, studies in preschool-aged children (i.e., < 30-40 months) suggest individuals with ASD have increased measures of WM FA earlier in development.

METHODS

We analyzed 127 individuals with ASD (85♂, 42♀) and 54 typically developing (TD) controls (42♂, 26♀), aged 25.1-49.6 months. Voxel-wise effects of ASD diagnosis, sex, age, and their interaction on DWI measures of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were investigated using tract-based spatial statistics (TBSS) while controlling mean absolute and relative motion.

RESULTS

Compared to TD controls, males and females with ASD had significantly increased measures of FA in eight clusters (threshold-free cluster enhancement p < 0.05) that incorporated several WM tracts including regions of the genu, body, and splenium of the corpus callosum, inferior frontal-occipital fasciculi, inferior and superior longitudinal fasciculi, middle and superior cerebellar peduncles, and corticospinal tract. A diagnosis by sex interaction was observed in measures of AD across six significant clusters incorporating areas of the body, genu, and splenium of the corpus collosum. In these tracts, females with ASD showed increased AD compared to TD females, while males with ASD showed decreased AD compared to TD males.

CONCLUSIONS

The current findings support growing evidence that preschool-aged children with ASD have atypical measures of WM microstructure that appear to differ in directionality from alterations observed in older individuals with the condition. To our knowledge, this study represents the largest sample of preschool-aged females with ASD to be evaluated using DWI. Microstructural differences associated with ASD largely overlapped between sexes. However, differential relationships of AD measures indicate that sex likely modulates ASD neuroanatomical phenotypes. Further longitudinal study is needed to confirm and quantify the developmental relationship of WM structure in ASD.

Anorexia nervosa and diffusion weighted imaging: An open methodological question raised by a systematic review and a fractional anisotropy anatomical likelihood estimation meta-analysis

BACKGROUND

Anorexia nervosa (AN) is characterized by white matter abnormalities in neuroimaging studies. Fractional anisotropy (FA) is a diffusion tensor imaging (DTI) index that is considered an instrument for the evaluation of white matter alterations. However, the literature has recently pointed out the role of the partial volume effect (PVE) as a confounding factor for the identification of juxtaposed tissues. Our goal was to review the DTI literature in AN and evaluate possible confounding factors linked to the reported results.

METHOD

A systematic review of the literature was conducted to identify Diffusion Tensor Imaging studies of individuals with AN and, subsequently, an anatomical likelihood estimation (ALE) meta-analysis was performed on studies published before March 18, 2019.

RESULTS

Twenty-four studies (AN = 517, controls = 542) were included in the qualitative systematic review of the literature. Ten published studies underwent the ALE-analysis (AN = 210, controls = 229), plus data from an unpublished cohort (AN = 38, controls = 38). Two clusters of decreased FA were identified, namely in the left corona radiata, and in the left thalamus. Only one article took the PVE correction analysis into account.

CONCLUSIONS

The alterations identified must be considered within the limits of a possible methodological bias regarding PVE and free water and re-analysis of the data may be recommended. The preliminary data showed that the alteration of white matter pathways between the limbic structures and brain cortex may be linked to the processing of somatosensory information that could play a key role in the psychopathology of the disorder.

Altered Neural Connectivity in Females, But Not Males with Autism: Preliminary Evidence for the Female Protective Effect from a Quality-Controlled Diffusion Tensor Imaging Study

Previous studies using diffusion tensor imaging (DTI) to investigate white matter (WM) structural connectivity have suggested widespread, although inconsistent WM alterations in autism spectrum disorder (ASD), such as greater reductions in fractional anisotropy (FA). However, findings may lack generalizability because: (a) most have focused solely on the ASD male brain phenotype, and not sex‐differences in WM integrity; (b) many lack stringent and transparent data quality control such as controlling for head motion in analysis. This study addressed both issues by using Tract‐Based Spatial Statistics (TBSS) to separately compare WM differences in 81 ASD (56 male, 25 female; 4–21 years old) and 39 typically developing (TD; 23 males, 16 females; 5–18 years old) children and young people, carefully group‐matched on sex, age, cognitive abilities, and head motion. ASD males and females were also matched on autism symptom severity. Two independent‐raters completed a multistep scan quality assurance to remove images that were significantly distorted by motion artifacts before analysis. ASD females exhibited significant widespread reductions in FA compared to TD females, suggesting altered WM integrity. In contrast, no significant localized or widespread WM differences were found between ASD and TD males. This study highlights the importance of data quality control in DTI, and outlines important sex‐differences in WM alterations in ASD females. Future studies can explore the extent to which neural structural differences might underlie sex‐differences in ASD behavioral phenotype, and guide clinical interventions to be tailored toward the unique needs of ASD females and males. Autism Res 2019, 12: 1472–1483. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.

Lay Summary

Previous Diffusion Tensor Imaging (DTI) studies have found atypical brain structural connectivity in males with autism, although findings are inconclusive in females with autism. To investigate potential sex‐differences, we studied males and females with and without autism who showed a similar level of head movement during their brain scan. We found that females with autism had widespread atypical neural connectivity than females without autism, although not in males, highlighting sex‐differences.

White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models

Prior neuroimaging studies have reported white matter network underconnectivity as a potential mechanism for autism spectrum disorder (ASD). In this study, we examined the structural connectome of children with ASD using edge density imaging (EDI), and then applied machine-learning algorithms to identify children with ASD based on tract-based connectivity metrics. Boys aged 8-12 years were included: 14 with ASD and 33 typically developing children. The edge density (ED) maps were computed from probabilistic streamline tractography applied to high angular resolution diffusion imaging. Tract-based spatial statistics was used for voxel-wise comparison and coregistration of ED maps in addition to conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD). Tract-based average DTI/connectome metrics were calculated and used as input for different machine-learning models: naïve Bayes, random forest, support vector machines (SVMs), and neural networks. For these models, cross-validation was performed with stratified random sampling ( × 1,000 permutations). The average accuracy among validation samples was calculated. In voxel-wise analysis, the body and splenium of corpus callosum, bilateral superior and posterior corona radiata, and left superior longitudinal fasciculus showed significantly lower ED in children with ASD; whereas, we could not find significant difference in FA, MD, and RD maps between the two study groups. Overall, machine-learning models using tract-based ED metrics had better performance in identification of children with ASD compared with those using FA, MD, and RD. The EDI-based random forest models had greater average accuracy (75.3%), specificity (97.0%), and positive predictive value (81.5%), whereas EDI-based polynomial SVM had greater sensitivity (51.4%) and negative predictive values (77.7%). In conclusion, we found reduced density of connectome edges in the posterior white matter tracts of children with ASD, and demonstrated the feasibility of connectome-based machine-learning algorithms in identification of children with ASD.

Elevated protein concentrations in newborn blood and the risks of autism spectrum disorder, and of social impairment, at age 10 years among infants born before the 28th week of gestation

Among the 1 of 10 children who are born preterm annually in the United States, 6% are born before the third trimester. Among children who survive birth before the 28th week of gestation, the risks of autism spectrum disorder (ASD) and non-autistic social impairment are severalfold higher than in the general population. We examined the relationship between top quartile inflammation-related protein concentrations among children born extremely preterm and ASD or, separately, a high score on the Social Responsiveness Scale (SRS total score ≥65) among those who did not meet ASD criteria, using information only from the subset of children whose DAS-II verbal or non-verbal IQ was ≥70, who were assessed for ASD, and who had proteins measured in blood collected on ≥2 days (N = 763). ASD (N = 36) assessed at age 10 years is associated with recurrent top quartile concentrations of inflammation-related proteins during the first post-natal month (e.g., SAA odds ratio (OR); 95% confidence interval (CI): 2.5; 1.2-5.3) and IL-6 (OR; 95% CI: 2.6; 1.03-6.4)). Top quartile concentrations of neurotrophic proteins appear to moderate the increased risk of ASD associated with repeated top quartile concentrations of inflammation-related proteins. High (top quartile) concentrations of SAA are associated with elevated risk of ASD (2.8; 1.2-6.7) when Ang-1 concentrations are below the top quartile, but not when Ang-1 concentrations are high (1.3; 0.3-5.8). Similarly, high concentrations of TNF-α are associated with heightened risk of SRS-defined social impairment (N = 130) (2.0; 1.1-3.8) when ANG-1 concentrations are not high, but not when ANG-1 concentrations are elevated (0.5; 0.1-4.2).