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Brain structure, phenotypic and genetic correlates of reading performance
Amaia Carrión-Castillo1, Pedro M Paz-Alonso2,3, Manuel Carreiras4,5,6
1Basque Center on Cognition, Brain and Language (BCBL), Donostia-San Sebastián, Spain. a.carrion@bcbl.eu.
Nature Human Behaviour
|April 10, 2023
Summary
Reading ability is linked to brain structure and partly influenced by genetics. This study explored the connection between brain metrics, reading skills, and genetic factors in children.
Area of Science:
- Neuroscience
- Genetics
- Developmental Psychology
Background:
- Reading is a complex cognitive skill relying on specialized brain networks.
- Understanding the interplay between brain structure, genetics, and reading ability is crucial for identifying learning differences.
Purpose of the Study:
- To investigate the correlation between brain structural measures and reading performance in children.
- To determine if genetic variants mediate the relationship between brain structure and reading ability.
Main Methods:
- Utilized the Adolescent Brain Cognitive Development dataset (n=9,013) comprising 9-10-year-olds.
- Analyzed 150 measures of cortical surface area (CSA) and thickness.
- Examined associations between brain structure metrics and reading performance, with a focus on genetic mediation.
Main Results:
- Reading performance was associated with nine measures of brain structure, including key regions within the reading network.
- Genetic factors partially mediated the relationship between reading performance and CSA for the entire left hemisphere and the left superior temporal gyrus.
- Reading is a polygenic skill influenced by a distributed network, with partial heritability.
Conclusions:
- Brain structure, particularly cortical surface area in specific left-hemisphere regions, is associated with reading performance.
- Genetic factors play a role in mediating the relationship between brain structure and reading ability, highlighting a complex gene-brain-reading interplay.
- Reading is a complex, partly heritable skill supported by a distributed neural network.
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