scholarly journals Transdiagnostic Profiles of Behaviour and Communication Relate to Academic and Socio-emotional Functioning and Neural White Matter Organisation

Author(s):  
Silvana Mareva ◽  
Danyal Akarca ◽  
Joni Holmes ◽  

Behavioural and language difficulties co-occur in multiple neurodevelopmental conditions. Our understanding of these problems has arguably been slowed by an overreliance on case-control designs, which limit the conclusions we can draw because they fail to capture the overlap across different neurodevelopmental disorders and the heterogeneity within them. In this study, we recruited a large transdiagnostic cohort of children with complex diagnosed and undiagnosed needs (N = 805) to identify distinct subgroups of children with common profiles of behavioural and language strengths and difficulties. We then investigated whether and how these data-driven groupings could be distinguished from a comparison sample (N = 158) on academic, socio-emotional, and neural white matter characteristics. We identified three distinct subgroups of children, each with different levels of difficulties in structural language, pragmatic communication, and hot and cool executive functions. All three subgroups struggled with academic and socio-emotional skills relative to the comparison sample, potentially representing three alternative but related developmental pathways to difficulties in these areas. The children with the weakest language skills had the most widespread difficulties with learning, whereas those with more pronounced difficulties with hot executive skills experienced the most severe difficulties within the socio-emotional domain. Each data-driven subgroup could be distinguished from the comparison sample based on both shared and subgroup-unique patterns of neural white matter organisation. These findings advance our understanding of commonly co-morbid behavioural and language problems and their relationship to behavioural outcomes and neurobiological substrates.

2021 ◽  
pp. jnnp-2020-323541
Author(s):  
Jessica L Panman ◽  
Vikram Venkatraghavan ◽  
Emma L van der Ende ◽  
Rebecca M E Steketee ◽  
Lize C Jiskoot ◽  
...  

ObjectiveProgranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way.MethodsWe included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes.ResultsLanguage functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA.ConclusionDegeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.


2017 ◽  
Author(s):  
Dag Alnæs ◽  
Tobias Kaufmann ◽  
Nhat Trung Doan ◽  
Aldo Córdova-Palomera ◽  
Yunpeng Wang ◽  
...  

AbstractA healthy transition from adolescence to adulthood relies on a continuous individual adaptation to a dynamic environment. Here, we employed data driven multivariate approaches to derive both general cognitive and psychopathology factors as well as brain phenotypes in children and adolescents in the publicly available PNC sample. We identified a distinct brain white matter pattern which proved central for prediction of heritable cognition and psychopathology scores, highlighting the importance of fronto-temporal connections for intellectual and mental development.


2018 ◽  
Author(s):  
Kendra E. Hinton ◽  
Benjamin B. Lahey ◽  
Victoria Villalta-Gil ◽  
Francisco A. C. Meyer ◽  
Leah L. Burgess ◽  
...  

AbstractIncreasing data indicate that prevalent forms of psychopathology can be organized into second-order dimensions based on their correlations, including a general factor of psychopathology that explains the common variance among all disorders and specific second-order externalizing and internalizing factors. Despite this organization, and high levels of comorbidity between diagnoses, most existing studies on the neural correlates of psychopathology employ case-control designs that treat diagnoses as independent categories. Thus, for instance, although perturbations in white matter microstructure have been identified across a range of disorders, the majority of such studies have used case-control designs, leaving it unclear whether observed relations reflect disorder specific characteristics, or transdiagnostic patterns. Using a representative community twin sample of 410 young adults, we tested the hypothesis that some relations between white matter microstructure properties in major tracts are related to second-order factors of psychopathology. We examined fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). White matter correlates of all second-order factors were identified after controlling for multiple tests, including the general factor (FA in the body of the corpus callosum), specific internalizing (AD in the fornix), and specific externalizing (AD in the splenium of the corpus callosum, sagittal stratum, anterior corona radiata, and internal capsule). These findings suggest that features of white matter within specific tracts are associated with broad transdiagnostic dimensions of psychopathology rather than being restricted to individual diagnostic categories.


2021 ◽  
Vol 17 (S1) ◽  
Author(s):  
Hanyi Chen ◽  
Eric de Silva ◽  
Carole H Sudre ◽  
Jo Barnes ◽  
Alexandra L. Young ◽  
...  

2019 ◽  
Vol 15 ◽  
pp. P1300-P1301
Author(s):  
Qiuting Wen ◽  
Shannon L. Risacher ◽  
Sourajit Mitra Mustafi ◽  
Jaroslaw Harezlak ◽  
Linhui Xie ◽  
...  

2019 ◽  
Vol 15 (7) ◽  
pp. P144-P145
Author(s):  
Qiuting Wen ◽  
Shannon L. Risacher ◽  
Sourajit Mitra Mustafi ◽  
Jaroslaw Harezlak ◽  
Linhui Xie ◽  
...  

2017 ◽  
Author(s):  
Matthew Walton ◽  
Deborah Dewey ◽  
Catherine Lebel

AbstractBrain alterations are associated with reading and language difficulties in older children, but little research has investigated relationships between early language skills and brain white matter structure during the preschool period. We studied 68 children aged 3.0-5.6 years who underwent diffusion tensor imaging and participated in assessments of Phonological Processing and Speeded Naming. Tract-based spatial statistics and tractography revealed relationships between Phonological Processing and fractional anisotropy and mean diffusivity in bilateral ventral white matter pathways, the corpus callosum, and corticospinal tracts. The relationships observed in left ventral pathways are consistent with studies in older children, and demonstrate that structural markers for language difficulties are apparent as young as 3 years of age. Our findings in right hemisphere areas that are not as commonly found in adult studies suggest that young children rely on a widespread network for language processing that becomes more specialized with age.


Author(s):  
Grace R. Jacobs ◽  
Aristotle N. Voineskos ◽  
Colin Hawco ◽  
Laura Stefanik ◽  
Natalie J. Forde ◽  
...  

AbstractAutism spectrum disorder (ASD), obsessive-compulsive disorder (OCD) and attention-deficit/hyperactivity disorder (ADHD) are clinically and biologically heterogeneous neurodevelopmental disorders (NDDs). The objective of the present study was to integrate brain imaging and behavioral measures to identify new brain-behavior subgroups cutting across these disorders. A subset of the data from the Province of Ontario Neurodevelopmental Disorder (POND) Network including participants with different NDDs (aged 6-16 years) that underwent cross-sectional T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scanning on the same 3T scanner, and behavioral/cognitive assessments was used. Similarity Network Fusion was applied to integrate cortical thickness, subcortical volume, white matter fractional anisotropy (FA), and behavioral measures in 176 children with ASD, ADHD or OCD with complete data that passed quality control. Normalized mutual information (NMI) was used to determine top contributing model features. Bootstrapping, out-of-model outcome measures and supervised machine learning were each used to examine stability and evaluate the new groups. Cortical thickness in socio-emotional and attention/executive networks and inattention symptoms comprised the top ten features driving participant similarity and differences between four transdiagnostic groups. Subcortical volumes (pallidum, nucleus accumbens, thalamus) were also different among groups, although white matter FA showed limited differences. Features driving participant similarity remained stable across resampling, and the new groups showed significantly different scores on everyday adaptive functioning. Our findings open the possibility of studying new data-driven groups that represent children with NDDs more similar to each other than others within their own diagnostic group. Such new groups can be evaluated longitudinally for prognostic utility and could be stratified for clinical trials targeted toward each group’s unique brain and behavioral profiles.


2020 ◽  
Author(s):  
R. Austin Benn ◽  
Rogier B. Mars ◽  
Ting Xu ◽  
Luis Rodríguez-Esparragoza ◽  
Paula Montesinos ◽  
...  

AbstractThe characterization and definition of homology in the cerebral cortex needed for a species to be adopted as a translational model in neuroscience is a unique challenge given the diverse array of cortical morphology present in the mammalian lineage. Using the domestic pig as an example, we provide a roadmap of how leveraging Magnetic Resonance Imaging of the brain and data-driven tractography can overcome these obstacles and facilitate cortical alignment between distantly related species. In doing so, we created a full platform of neuroimaging tools to be used in the pig, including volumetric and surface templates, a structural white matter atlas, and the establishment of a common connectivity space to facilitate pig-human cortical alignment. Releasing our data and code and our pig-human cortical alignment, we permit researchers already working with the pig to accentuate the clinical relevance and translational capacity of their work. By sharing the intermediate outputs and scripts used to construct our pig-human cortical alignment, we also provide a roadmap to expand the current repertoire of animal models used in neuroscience.


2020 ◽  
Vol 16 (S5) ◽  
Author(s):  
Mohamad Habes ◽  
Aristeidis Sotiras ◽  
Guray Erus ◽  
Jon B. Toledo ◽  
Deborah Janowitz ◽  
...  

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