Predicting pragmatic language abilities from brain structural MRI in preschool children with ASD by NBS-Predict.

Pragmatics plays a crucial role in effectively conveying messages across various social communication contexts. This aspect is frequently highlighted in the challenges experienced by children diagnosed with autism spectrum disorder (ASD). Notably, there remains a paucity of research investigating ho...

Descripción completa

Detalles Bibliográficos
Publicado en:European Child & Adolescent Psychiatry Vol. 34; no. 12; pp. 3779 - 3791
Autores principales: Qian, Lu, Ding, Ning, Fang, Hui, Xiao, Ting, Sun, Bei, Gao, HuiYun, Ke, XiaoYan
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Dec2025
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190506454&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 190506454
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        10188827
        EJ3
      jtl: European Child & Adolescent Psychiatry
      issn: 10188827
      maglogo: N
    pubinfo:
      dt: Dec2025
      vid: 34
      iid: 12
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        190506454
        185830861
        190506454
        190506454
        10.1007/s00787-025-02775-w
        190506454
      ppf: 3779
      ppct: 12
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: Predicting pragmatic language abilities from brain structural MRI in preschool children with ASD by NBS-Predict.
      aug:
        au:
          Qian, Lu
          Ding, Ning
          Fang, Hui
          Xiao, Ting
          Sun, Bei
          Gao, HuiYun
          Ke, XiaoYan
        affil: https://ror.org/01wcx2305 Child Mental Health Research Center, Nanjing Brain Hospital Affiliated of Nanjing Medical University, Nanjing Guangzhou Road 264#, 210029, Nanjing, China
      sug:
        subj:
          Brain Anatomy and Histology
          Magnetic Resonance Imaging
          Autism Spectrum Disorder Diagnosis
          Diagnosis, Neurologic
          White Matter Pathology
          Machine Learning
          Prediction Models
          Human
          Male
          Female
          Child, Preschool
          Child
          China
          Case Control Studies
          Discriminant Analysis
          Sensitivity and Specificity
          Linear Regression
          Pearson's Correlation Coefficient
          Funding Source
          Scales
          Child, Preschool: 2-5 years
          Child: 6-12 years
          Male
          Female
      ab: Pragmatics plays a crucial role in effectively conveying messages across various social communication contexts. This aspect is frequently highlighted in the challenges experienced by children diagnosed with autism spectrum disorder (ASD). Notably, there remains a paucity of research investigating how the structural connectome (SC) predicts pragmatic language abilities within this population. Using diffusion tensor imaging (DTI) and deterministic tractography, we constructed the whole-brain white matter structural network (WMSN) in a cohort comprising 92 children with ASD and 52 typically developing (TD) preschoolers, matched for age and gender. We employed network-based statistic (NBS)-Predict, a novel methodology that integrates machine learning (ML) with NBS, to identify dysconnected subnetworks associated with ASD, and then to predict pragmatic language abilities based on the SC derived from the whole-brain WMSN in the ASD group. Initially, NBS-Predict identified a subnetwork characterized by 42 reduced connections across 37 brain regions (p = 0.01), achieving a highest classification accuracy of 79.4% (95% CI: 0.791 ~ 0.796). The dysconnected regions were predominantly localized within the brain's frontotemporal and subcortical areas, with the right superior medial frontal gyrus (SFGmed.R) emerging as the region exhibiting the most extensive disconnection. Moreover, NBS-Predict demonstrated that the optimal correlation coefficient between the predicted pragmatic language scores and the actual measured scores was 0.220 (95% CI: 0.174 ~ 0.265). This analysis revealed a significant association between the pragmatic language abilities of the ASD cohort and the white matter connections linking the SFGmed.R with the bilateral anterior cingulate gyrus (ACG). In summary, our findings suggest that the subnetworks displaying the most significant abnormal connections were concentrated in the frontotemporal and subcortical regions among the ASD group. Furthermore, the observed abnormalities in the white matter connection pathways between the SFGmed.R and ACG may underlie the neurobiological basis for pragmatic language deficits in preschool children with ASD.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N