Biological networks associated with reading ability

Biological networks associated with reading ability

First Author: Hope Lancaster -- Arizona State University
Additional authors/chairs: 
Jing Li
Keywords: Behavior Genetics, Dyslexia, Reading Ability
Abstract / Summary: 

Purpose: This project explored the genetic associations with and corresponding biological networks for reading (dis)ability in the Avon Longitudinal Study of Parents and Children (ASLPAC) to better understand the etiology of reading (dis)ability.

Methods: We used genetic and longitudinal reading data from the ALSPAC database (n = 8,071). We utilized two complimentary designs, case-control and quantitative, for completing the genetic analyses. For the case-control design, children were labeled reading disorder (n = 1,215) or typical reader (n = 6,856). For the quantitative design, we created a weighted reading ability composite (n = 3,933) score using confirmatory factor analysis. We performed genome-wide association to screen the genetic data for the top 100 significant variants. We used lasso regression to identify the most informative variants, which were mapped to genes. We utilized pathway and network analysis to understand how the relevant genes interacted.

Results: Lasso regression identified several informative variants which mapped to known genes (e.g., DCDC2, KIAA0319, FOXP2) and novel genes (e.g., RAPGEF2, RELN, SUCLA2) for the two phenotypes. Neuron migration was associated with all phenotypes, suggesting that this network is key to supporting reading development. Dendrite regulation networks and large scale structural networks were overrepresented in the case-control design.

Discussion: Our findings provide initial evidence that biological networks work together in guiding brain development in children to support reading. Our results demonstrate that a composite score for reading is a possible alternative method to representing reading (dis)ability in genetic studies. We will discuss implications for future research. We are currently validating our results in an additional database.