Network-specific sex differentiation of intrinsic brain function in males with autism

Floris, Dorothea L.; Lai, Meng‐Chuan; Nath, Tanmay; Milham, Michael P.; Martino, Adriana Di

doi:10.1186/s13229-018-0192-x

Cited by 55 publications

(58 citation statements)

References 73 publications

(119 reference statements)

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“…Finally, along with factor-specific RSFC signatures, all three factors shared atypical RSFC involving the default network. This is consistent with the larger RSFC ASD literature that have consistently reported structural, and functional ASD-related abnormalities involving the default network (68)(69)(70). The directionality of the abnormal default network RSFC varied by factor, e.g., factor 2 exhibited hyper-connectivity within the default network, while factor 1 and 3 exhibited hypo-connectivity ( Figure 2B).…”

Section: Discussionsupporting

confidence: 87%

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study

Tang

Sun

Floris

et al. 2019

Preprint

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word count: 250 Main text word count (excluding references and figure captions): 3991 Number of figures: 5 Number of tables: 1 Number of supplemental files: 1 Abstract Background: Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach.Methods: A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of ASD individuals into multiple abnormal RSFC patterns, i.e., categorical subtypes henceforth referred to as "factors". Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 ASD individuals (age 5.2-57 years) from two multisite repositories. Posthoc analyses associated factors with symptoms and demographics.Results: Analyses yielded three factors with dissociable whole-brain hypo/hyper RSFC patterns.Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default network, but the directionality (hypo/hyper RSFC) differed across factors. Factor 1 was associated with core ASD symptoms, while factor 2 was associated with comorbid symptoms. Older males preferentially expressed factor 3. Factors were robust across multiple control analyses and not associated with IQ, nor head motion. Conclusions:There exist at least three ASD factors with dissociable patterns of whole-brain RSFC, behaviors and demographics. Heterogeneous default network hypo/hyper RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms -a less appreciated domain of heterogeneity in ASD. These factors are co-expressed in ASD individuals with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

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Section: Discussionsupporting

confidence: 87%

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study

Tang

Sun

Floris

et al. 2019

Preprint

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“…ABIDE is a data sharing initiative wherein researchers across laboratories shared resting‐state data from TD and ASD participants for the flexible use by other researchers, “allow[ing] for replication, secondary analyses and discovery efforts” (Di Martino et al, ). This flexibility has allowed a proliferation of research on functional connectivity in ASD, and the data has been used in various ways, including considering each site separately (Hahamy, Behrmann, & Malach, ; Pua, Malpas, Bowden, & Seal, ) or using multisite aggregation (Abraham et al, ; Floris, Lai, Nath, Milham, & Di Martino, ; King et al, ). Both of these approaches are widely employed, and while greater statistical power can be achieved from aggregation, examining multiple individual sites can be used to evaluate replicability.…”

Section: Introductionmentioning

confidence: 99%

“…Martino et al, 2014). This flexibility has allowed a proliferation of research on functional connectivity in ASD, and the data has been used in various ways, including considering each site separately (Hahamy, Behrmann, & Malach, 2015;Pua, Malpas, Bowden, & Seal, 2018) or using multisite aggregation (Abraham et al, 2017;Floris, Lai, Nath, Milham, & Di Martino, 2018;King et al, 2019) resting-state fcMRI studies of ASD. We searched the PubMed database using keywords consisted of "resting*," "autism," and "fMRI," or combining "resting*," "autism," and "connectivity," published from the beginning of 2013 until June 2019 (inclusive of the time when ABIDE data has been available).…”

mentioning

confidence: 99%

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Byrge

Kennedy

2020

Human Brain Mapping

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A rapidly growing number of studies on autism spectrum disorder (ASD) have used resting‐state fMRI to identify alterations of functional connectivity, with the hope of identifying clinical biomarkers or underlying neural mechanisms. However, results have been largely inconsistent across studies, and there remains a pressing need to determine the primary factors influencing replicability. Here, we used resting‐state fMRI data from the Autism Brain Imaging Data Exchange to investigate two potential factors: denoising strategy and data site (which differ in terms of sample, data acquisition, etc.). We examined the similarity of both group‐averaged functional connectomes and group‐level differences (ASD vs. control) across 33 denoising pipelines and four independently‐acquired datasets. The group‐averaged connectomes were highly consistent across pipelines (r = 0.92 ± 0.06) and sites (r = 0.88 ± 0.02). However, the group differences, while still consistent within site across pipelines (r = 0.76 ± 0.12), were highly inconsistent across sites regardless of choice of denoising strategies (r = 0.07 ± 0.04), suggesting lack of replication may be strongly influenced by site and/or cohort differences. Across‐site similarity remained low even when considering the data at a large‐scale network level or when considering only the most significant edges. We further show through an extensive literature survey that the parameters chosen in the current study (i.e., sample size, age range, preprocessing methods) are quite representative of the published literature. These results highlight the importance of examining replicability in future studies of ASD, and, more generally, call for extra caution when interpreting alterations in functional connectivity across groups of individuals.

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“…ABIDE is a data sharing initiative wherein researchers across laboratories shared resting-state data from TD and ASD participants for the flexible use by other researchers, "allow[ing] for replication, secondary analyses and discovery efforts" (Di Martino et al, 2014). This flexibility has allowed a proliferation of research on functional connectivity in ASD, and the data has been used in various ways, including considering each site separately (Hahamy, Behrmann, & Malach, 2015;Pua, Malpas, Bowden, & Seal, 2018) or using multi-site aggregation (Abraham et al, 2017;Floris, Lai, Nath, Milham, & Di Martino, 2018;King et al, 2019). Both of these approaches are widely employed, and while greater statistical power can be achieved from aggregation, examining multiple individual sites can be used to evaluate replicability.…”

Section: Introductionmentioning

confidence: 99%

Non-replication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Byrge

Kennedy

2019

Preprint

View full text Add to dashboard Cite

A rapidly growing number of studies on autism spectrum disorder (ASD) have used restingstate fMRI to identify alterations of functional connectivity, with the hope of identifying clinical biomarkers or underlying neural mechanisms. However, results have been largely inconsistent across studies, and there is therefore a pressing need to determine the primary factors influencing replicability. Here, we used resting-state fMRI data from the Autism Brain Imaging Data Exchange to investigate two potential factors: denoising strategy and data site (which differ in terms of sample, data acquisition, etc.). We examined the similarity of both group-average functional connectomes and group-level differences (ASD vs. control) across 33 denoising pipelines and four independently-acquired datasets. The group-average connectomes were highly consistent across pipelines (r = 0.92±0.06) and sites (r = 0.88±0.02). However, the group differences, while still consistent within site across pipelines (r = 0.76±0.12), were highly inconsistent across sites regardless of choice of denoising strategies (r = 0.07±0.04), suggesting lack of replication may be strongly influenced by site and/or cohort differences. Across-site similarity remained low even when considering the data at a large-scale network level or when considering only the most significant edges. We further show through an extensive literature survey that the parameters chosen in the current study (i.e., sample size, age range, preprocessing methods) are quite representative of the published literature. These results highlight the importance of examining replicability in future studies of ASD, and, more generally, call for extra caution when interpreting alterations in functional connectivity across groups of individuals.

show abstract

Network-specific sex differentiation of intrinsic brain function in males with autism

Cited by 55 publications

References 73 publications

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study

Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

Non-replication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies

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