Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Indra Kraft - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Jan Schreiber - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Riccardo Cafiero - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Riccardo Metere - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Gesa Schaadt - , Max Planck Institute for Human Cognitive and Brain Sciences, Humboldt University of Berlin (Author)
  • Jens Brauer - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Nicole E. Neef - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Bent Müller - , Fraunhofer Institute for Cell Therapy and Immunology (Author)
  • Holger Kirsten - , Fraunhofer Institute for Cell Therapy and Immunology, Leipzig University (Author)
  • Arndt Wilcke - , Fraunhofer Institute for Cell Therapy and Immunology (Author)
  • Johannes Boltze - , Fraunhofer Institute for Cell Therapy and Immunology, University of Lübeck (Author)
  • Angela D. Friederici - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)
  • Michael A. Skeide - , Max Planck Institute for Human Cognitive and Brain Sciences (Author)

Abstract

Background Recent studies suggest that neurobiological anomalies are already detectable in pre-school children with a family history of developmental dyslexia (DD). However, there is a lack of longitudinal studies showing a direct link between those differences at a preliterate age and the subsequent literacy difficulties seen in school. It is also not clear whether the prediction of DD in pre-school children can be significantly improved when considering neurobiological predictors, compared to models based on behavioral literacy precursors only. Methods We recruited 53 pre-reading children either with (N=25) or without a family risk of DD (N=28). Quantitative T1 MNI data and literacy precursor abilities were assessed at kindergarten age. A subsample of 35 children was tested for literacy skills either one or two years later, that is, either in first or second grade. Results The group comparison of quantitative T1 measures revealed significantly higher T1 intensities in the left anterior arcuate fascicle (AF), suggesting reduced myelin concentration in preliterate children at risk of DD. A logistic regression showed that DD can be predicted significantly better (p=.024) when neuroanatomical differences between groups are used as predictors (80%) compared to a model based on behavioral predictors only (63%). The Wald statistic confirmed that the T1 intensity of the left AF is a statistically significant predictor of DD (p<.05). Conclusions Our longitudinal results provide evidence for the hypothesis that neuroanatomical anomalies in children with a family risk of DD are related to subsequent problems in acquiring literacy. Particularly, solid white matter organization in the left anterior arcuate fascicle seems to play a pivotal role.

Details

Original languageEnglish
Pages (from-to)378-386
Number of pages9
JournalNeuroImage
Volume143
Publication statusPublished - 1 Dec 2016
Peer-reviewedYes
Externally publishedYes

External IDs

PubMed 27608602
ORCID /0009-0004-4533-5880/work/150882781

Keywords

ASJC Scopus subject areas

Keywords

  • Arcuate fascicle, Cortical thickness, Developmental dyslexia, Diffusion-weighted imaging, Quantitative T1, Reading