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Updated: Jan 8, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
Gene-Environment Interplay in Reading Performance
Amaia Carrión-Castillo1,2, Manuel Carreiras1,2,3, Marie Lallier1,2
1Basque Center on Cognition, Brain, and Language (BCBL), Donostia-San Sebastian, Spain.
None:
Genetic factors are known to play a role in shaping reading abilities and their underlying cognitive processes. However, understanding how genetic and environmental factors interact to influence reading outcomes remains largely unknown. By evaluating the interplay between genetic and environmental influences on reading performance, this study aims to provide insights into the complex mechanisms underlying reading abilities. To this aim, we leveraged the Adolescent Brain Cognitive Development dataset, considering socioeconomic indicators including household income and parental education, along with linguistic characteristics such as bilingualism and the child's first language (L1). We operationalized genetic influences as polygenic scores (PGS), which aggregate genetic risk across multiple loci associated with reading-relevant traits (word reading, dyslexia, cognitive performance, and educational attainment). First, we establish the individual associations between selected environmental and genetic predictors for reading, observing that all except L1 are significant predictors of reading, with a similar range of variance explained by the two types of predictors. Next, we confirm an additive effect, as the PGS remain significant after adjustment for the environmental effects, although the effects of PGSEducationalAttainment and PGSCognitivePerformance are attenuated, confirming a partial gene-environment correlation. This is further supported by analyzing direct and genetic effects in a subset of siblings. Next, potential interactions between the PGS and these environmental variables are considered. Finally, we evaluate the combined contribution of the four PGS through a multiPGS analysis, which improves the predictive power of the individual PGS analyses, explaining up to 10% of variance in reading performance (adjusted R2). Sensitivity analyses with other cognitive outcomes (vocabulary and fluid intelligence) reveal that the observed pattern is specific to reading. Our study highlights the important and interrelated roles of both environmental and genetic factors in shaping reading abilities.
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