Data-driven Cognitive Clusters in Persistent Developmental Dyslexia

Abstract

Developmental dyslexia is a neurodevelopmental condition characterized by persistent reading difficulties despite adequate intelligence and educational opportunities. The cognitive underpinnings of dyslexia remain incompletely understood. Although multiple causal pathways have been proposed, there is a gap in studies that can reliably identify dyslexia subtypes based on comprehensive evaluations that go beyond measures of reading and phonology. We employed one of the largest detailed samples of children with developmental dyslexia resistant to intervention, consisting of 147 extensively phenotyped school-age children aged 7-14 years who were recruited from specialized schools for students with learning differences. We implemented data-driven analyses leveraging a comprehensive neuropsychological assessment to delineate cognitive subdomains and characterize the heterogeneity in the sample. Hierarchical clustering of 24 cognitive measures aided in constructing a framework to subsequently interpret emerging clusters. Four clusters emerged, predominantly associated with: Processing Speed & Executive Function, Visuospatial & Mathematical Reasoning, Phonological Manipulation, and Verbal Short-term Memory & Word Retrieval. Subsequent latent profile analysis identified two distinct dyslexia profiles: one characterized by marked difficulties in executive functioning and processing speed, and another displaying impairments primarily in verbal short-term memory and word retrieval relative to the other profile. Importantly, both profiles exhibited comparable severity of persistent reading difficulties despite their divergent cognitive profiles. These findings show that phenotypically similar reading impairments can arise from distinct underlying cognitive factors, emphasizing the role of comprehensive neuropsychological evaluation in developing tailored interventions for affected children.