Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes

Chen, Heng; Uddin, Lucina Q.; Guo, Xiaonan; Wang, Jia; Wang, Runshi; Wang, Xiaomin; Duan, Xujun; Chen, Huafu

doi:10.1002/hbm.24400

Cited by 56 publications

(62 citation statements)

References 46 publications

(55 reference statements)

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“…Although semi-metric edges were largely increased in number, semi-metric backbones of autism showed more variation (i.e., a reduced number of edges represented) in their spatial distribution than that of the TD group. This inconsistency in location of the shortest indirect functional connections is in agreement with the evidence of a general increase in heterogeneity of imaging measures in autism (Chen et al, 2018;Jeste & Geschwind, 2014). The higher SMP across a wide range of spatial scales that was observed in autistic adults closely coincides with previous findings in autistic adolescents .…”

Section: Discussionsupporting

confidence: 89%

Enhancement of indirect functional connections with shortest path length in the adult autistic brain

Guo¹,

Simas

Lai

et al. 2019

Human Brain Mapping

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Autism is a neurodevelopmental condition characterized by atypical brain functional organization. Here we investigated the intrinsic indirect (semi‐metric) connectivity of the functional connectome associated with autism. Resting‐state functional magnetic resonance imaging scans were acquired from 65 neurotypical adults (33 males/32 females) and 61 autistic adults (30 males/31 females). From functional connectivity networks, semi‐metric percentages (SMPs) were calculated to assess the proportion of indirect shortest functional pathways at global, hemisphere, network, and node levels. Group comparisons were then conducted to ascertain differences between autism and neurotypical control groups. Finally, the strength and length of edges were examined to explore the patterns of semi‐metric connections associated with autism. Compared with neurotypical controls, autistic adults displayed significantly higher SMP at all spatial scales, similar to prior observations in adolescents. Differences were primarily in weaker, longer‐distance edges in the majority between networks. However, no significant diagnosis‐by‐sex interaction effects were observed on global SMP. These findings suggest increased indirect functional connectivity in the autistic brain is persistent from adolescence to adulthood and is indicative of reduced functional network integration.

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Section: Discussionsupporting

confidence: 89%

Enhancement of indirect functional connections with shortest path length in the adult autistic brain

Guo¹,

Simas

Lai

et al. 2019

Human Brain Mapping

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“…Additionally, we examined high‐motion frame percentage of each subject to reduce unwanted effects from head motion artifacts on functional connectivity analyses (Power, Barnes, Snyder, Schlaggar, & Petersen, ). Time points with FD > 0.5 mm with preceding one and subsequent two time points obtained in realignment were labeled as high‐motion frames (Chen et al, ). Subjects with less than 50% high‐motion frames were included in the following analyses (Chen et al, ; Guo et al, ).…”

Section: Methodsmentioning

confidence: 99%

Altered inter‐ and intrahemispheric functional connectivity dynamics in autistic children

Guo

Duan

Chen

et al. 2019

Human Brain Mapping

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Emerging evidence has associated autism spectrum disorder (ASD) with static functional connectivity abnormalities between multiple brain regions. However, the temporal dynamics of intra-and interhemispheric functional connectivity patterns remain unknown in ASD. Resting-state functional magnetic resonance imaging data were analyzed for 105 ASD and 102 demographically matched typically developing control (TC) children (age range: 7-12 years) available from the Autism Brain Imaging Data Exchange database. Whole-brain functional connectivity was decomposed into ipsilateral and contralateral functional connectivity, and sliding-window analysis was utilized to capture the intra-and interhemispheric dynamic functional connectivity density (dFCD) patterns. The temporal variability of the functional connectivity dynamics was further quantified using the standard deviation (SD) of intra-and interhemispheric dFCD across time. Finally, a support vector regression model was constructed to assess the relationship between abnormal dFCD variance and autism symptom severity. Both intra-and interhemispheric comparisons showed increased dFCD variability in the anterior cingulate cortex/medial prefrontal cortex and decreased variability in the fusiform gyrus/inferior temporal gyrus in autistic children compared with TC children. Autistic children additionally showed lower intrahemispheric dFCD variability in sensorimotor regions including the precentral/postcentral gyrus. Moreover, aberrant temporal variability of the contralateral dFCD predicted the severity of social communication impairments in autistic children.These findings demonstrate altered temporal dynamics of the intra-and interhemispheric functional connectivity in brain regions incorporating social brain network of ASD, and highlight the potential role of abnormal interhemispheric communication dynamics in neural substrates underlying impaired social processing in ASD. K E Y W O R D Sautism spectrum disorder, dynamic functional connectivity, interhemisphere, intrahemisphere, resting-state functional magnetic resonance imaging

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“…The present ASD neurosubtyping literature is in its infancy with a total of 12 studies in humans, 92% published since 2018 (60)(61)(62)(63)(64)(65)(66)(67)(68)(69)(70)(71). Studies vary in methodology (FIGURE 1, TABLE 1).…”

Section: Data-driven Asd Neurosubtypingmentioning

confidence: 99%

“…Therefore, high dimensionality can become toxic (88). To date, only two ASD neurosubtyping studies quantitatively addressed this challenge, one via principal component analysis (PCA; 61) in EEG data, another via non-negative matrix factorization (62).…”

Section: Featuresmentioning

confidence: 99%

“…i) Clustering partitions the data into a number of clusters such that the samples in each cluster are more similar to one another than to those in others. Reflecting its widespread popularity and relative computational ease, three ASD neurosubtyping studies (60,62,63) have used k-means clustering -a centroid-based approach that iteratively assigns individual data points based on their 'closeness' to the centroid of each cluster. Others (61,64,65) have used variants of hierarchical clustering that generate cluster trees using heuristic data splitting or merging (FIGURE S2A).…”

Section: Algorithmsmentioning

confidence: 99%

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Towards Neurosubtypes in Autism

Hong¹,

Vogelstein²,

Gozzi³

et al. 2019

Preprint

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There is a general consensus that substantial heterogeneity underlies the neurobiology in autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular-, cellular-, and system-level domains is a prerequisite for identifying biomarkers and developing more targeted therapeutic strategies in ASD. Advances in neuroimaging approaches to characterizing atypical brain patterns have recently motivated their application as viable tools to delineate more homogenous ASD subgroups at the level of brain structure and function -i.e., neurosubtyping. This review assesses and critically discusses the current datadriven neurosubtyping in ASD. It breaks this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithm and validation approaches. For each step, we appraise the current literature in terms of progress, as well as remaining challenges and potential solutions. Convergence across findings is discussed and biological implications are highlighted. Although preliminary and with limited methodological overlap, results from this literature illustrate the feasibility of neurosubtyping. Across studies, there is general agreement that distinct neurosubtypes exist, but the exact number and their definitions vary depending on the specific features and approach utilized in a given study. Results also suggest the utility of subtypes in predicting symptom severity and diagnostic labels above and beyond group-average comparison designs. This review concludes with a discussion of future avenues towards a comprehensive understanding of the mechanisms underlying ASD heterogeneity.

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Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes

Cited by 56 publications

References 46 publications

Enhancement of indirect functional connections with shortest path length in the adult autistic brain

Enhancement of indirect functional connections with shortest path length in the adult autistic brain

Altered inter‐ and intrahemispheric functional connectivity dynamics in autistic children

Towards Neurosubtypes in Autism

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