Network over‐connectivity differentiates autism spectrum disorder from other developmental disorders in toddlers: A diffusion MRI study

Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnorm...

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Published inHuman brain mapping Vol. 38; no. 5; pp. 2333 - 2344
Main Authors Conti, E., Mitra, J., Calderoni, S., Pannek, K., Shen, K. K., Pagnozzi, A., Rose, S., Mazzotti, S., Scelfo, D., Tosetti, M., Muratori, F., Cioni, G., Guzzetta, A.
Format Journal Article
LanguageEnglish
Published United States John Wiley & Sons, Inc 01.05.2017
John Wiley and Sons Inc
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Abstract Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other‐DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other‐DD including intellectual disability and language disorder) according to DSM‐IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (DNUM) and the tract‐averaged fractional anisotropy (DFA) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other‐DD groups. The network differences resulted in an over‐connectivity pattern (i.e., higher DNUM and DFA values) in the ASD group with a significance of P < 0.05. No contra‐comparison results were found. The over‐connectivity pattern in ASD occurred in networks primarily involving the fronto‐temporal nodes, known to be crucial for social‐skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network‐based diffusion study comparing toddlers with ASD and those with other‐DD. Results indicate the detection of different connectivity patterns in ASD and other‐DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333–2344, 2017. © 2017 Wiley Periodicals, Inc.
AbstractList Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other-DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other-DD including intellectual disability and language disorder) according to DSM-IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (D sub(NUM)) and the tract-averaged fractional anisotropy (D sub(FA)) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other-DD groups. The network differences resulted in an over-connectivity pattern (i.e., higher D sub(NUM) and D sub(FA) values) in the ASD group with a significance of P<0.05. No contra-comparison results were found. The over-connectivity pattern in ASD occurred in networks primarily involving the fronto-temporal nodes, known to be crucial for social-skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network-based diffusion study comparing toddlers with ASD and those with other-DD. Results indicate the detection of different connectivity patterns in ASD and other-DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333-2344, 2017. copyright 2017 Wiley Periodicals, Inc.
Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other-DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other-DD including intellectual disability and language disorder) according to DSM-IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (DNUM) and the tract-averaged fractional anisotropy (DFA) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other-DD groups. The network differences resulted in an over-connectivity pattern (i.e., higher DNUM and DFA values) in the ASD group with a significance of P<0.05. No contra-comparison results were found. The over-connectivity pattern in ASD occurred in networks primarily involving the fronto-temporal nodes, known to be crucial for social-skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network-based diffusion study comparing toddlers with ASD and those with other-DD. Results indicate the detection of different connectivity patterns in ASD and other-DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333-2344, 2017. © 2017 Wiley Periodicals, Inc.
Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other-DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other-DD including intellectual disability and language disorder) according to DSM-IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (D ) and the tract-averaged fractional anisotropy (D ) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other-DD groups. The network differences resulted in an over-connectivity pattern (i.e., higher D and D values) in the ASD group with a significance of P < 0.05. No contra-comparison results were found. The over-connectivity pattern in ASD occurred in networks primarily involving the fronto-temporal nodes, known to be crucial for social-skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network-based diffusion study comparing toddlers with ASD and those with other-DD. Results indicate the detection of different connectivity patterns in ASD and other-DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333-2344, 2017. © 2017 Wiley Periodicals, Inc.
Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity. However, most of these studies compare ASD and typically developing subjects, thus providing little information on the specificity of the abnormalities detected in comparison with other developmental disorders (other‐DD). We recruited subjects aged below 36 months who received a clinical diagnosis of Neurodevelopmental Disorder (32 ASD and 16 other‐DD including intellectual disability and language disorder) according to DSM‐IV TR. Structural and diffusion MRI were acquired to perform whole brain probabilistic and anatomically constrained tractography. Network connectivity matrices were built encoding the number of streamlines (D NUM ) and the tract‐averaged fractional anisotropy (D FA ) values connecting each pair of cortical and subcortical regions. Network Based Statistics (NBS) was finally applied on the connectivity matrices to evaluate the network differences between the ASD and other‐DD groups. The network differences resulted in an over‐connectivity pattern (i.e., higher D NUM and D FA values) in the ASD group with a significance of P  < 0.05. No contra‐comparison results were found. The over‐connectivity pattern in ASD occurred in networks primarily involving the fronto‐temporal nodes, known to be crucial for social‐skill development and basal ganglia, related to restricted and repetitive behaviours in ASD. To our knowledge, this is the first network‐based diffusion study comparing toddlers with ASD and those with other‐DD. Results indicate the detection of different connectivity patterns in ASD and other‐DD at an age when clinical differential diagnosis is often challenging. Hum Brain Mapp 38:2333–2344, 2017 . © 2017 Wiley Periodicals, Inc.
Author Scelfo, D.
Guzzetta, A.
Calderoni, S.
Mitra, J.
Tosetti, M.
Rose, S.
Mazzotti, S.
Shen, K. K.
Pannek, K.
Muratori, F.
Conti, E.
Pagnozzi, A.
Cioni, G.
AuthorAffiliation 1 Department of Developmental Neuroscience Stella Maris Scientific Institute Pisa Italy
2 Department of Clinical and Experimental Medicine University of Pisa Pisa Italy
3 The Australian eHealth Research Centre CSIRO Brisbane Queensland Australia
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Issue 5
Keywords brain connectivity
toddlers
autism spectrum disorders
overconnectivity
developmental disorders
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2014; 63
2011; 17
2012; 169
2012; 13
2012; 12
2005b; 15
2014; 23
2007; 35
2009; 48
2016; 79
2007; 37
2010; 23
2012; 72
2010; 20
1998; 17
2000
2010; 119
2013; 57
2009; 50
2015; 136
2015; 42
2011b; 306
2011; 66
2008; 20
2003; 126
2009; 19
2014; 8
2001; 13
2012; 22
2008; 152
2014; 53
2012; 62
2007; 17
2015; 6
2009; 61
2006; 10
2016; 10
2008
2011; 32
2008; 11
2016; 125
2012; 36
2015; 9
2009; 1262
2009; 1265
2014; 44
2001; 20
2012b; 63
2005a; 23
2016; 7
2009; 30
2003; 229
2004; 51
2015; 62
2015; 234
2000; 30
2011; 41
2005; 6
2013; 251
2013
2012; 48
2013; 170
2012; 6
2014; 221
2014; 73
2012; 42
2010; 50
2014; 76
2009; 39
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Snippet Advanced connectivity studies in toddlers with Autism Spectrum Disorder (ASD) are increasing and consistently reporting a disruption of brain connectivity....
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SourceType Open Access Repository
Aggregation Database
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StartPage 2333
SubjectTerms Anisotropy
Autism Spectrum Disorder - diagnostic imaging
autism spectrum disorders
Brain - diagnostic imaging
Brain - physiopathology
brain connectivity
Child, Preschool
developmental disorders
Diagnostic and Statistical Manual of Mental Disorders
Diffusion Magnetic Resonance Imaging - methods
Electroencephalography
Female
Humans
Image Processing, Computer-Assisted
Infant
Intellectual Disability - etiology
Language Disorders - etiology
Male
Neural Pathways - diagnostic imaging
Neurodevelopmental Disorders - complications
Neurodevelopmental Disorders - diagnostic imaging
overconnectivity
Prospective Studies
Statistics as Topic
toddlers
Title Network over‐connectivity differentiates autism spectrum disorder from other developmental disorders in toddlers: A diffusion MRI study
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fhbm.23520
https://www.ncbi.nlm.nih.gov/pubmed/28094463
https://www.proquest.com/docview/1885186149
https://www.proquest.com/docview/1861562114
https://www.proquest.com/docview/1891874722
https://pubmed.ncbi.nlm.nih.gov/PMC6866938
Volume 38
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