In the United States, one-in-five school aged children are diagnosed with a learning disorder. Learning disabilities encompass several commonly co-occurring neurodevelopmental disorders that contribute to a persistent struggle to read, write, spell, compute math, and/or focus, impeding their success in school, access to post-secondary education, and employment opportunities. The etiology of learning disabilities is a product of complex genetic and environmental factors but the genetic and biological mechanisms underlying them are poorly understood. Twin studies report substantial genetic overlap across reading, language, math, and attentional abilities, suggesting that shared genetic factors contribute to the high prevalence of co-occurring learning disabilities. However, twin studies report the net effect of genetic influence, but cannot specify what individual genetic factors contribute to the observed overlap. Therefore, the goal of this proposal is to identify shared genetic factors that contribute to variation across reading, language, math, attention, and brain structures using a multivariate approach.
Aim 1 will identify genetic factors that contribute to the co-occurrence of language-based learning disabilities in a multi-generational family using a multivariate linkage approach.
Aim 2 will identify common genetic factors shared between correlated cognitive traits associated with reading, language, math, and attentional abilities in a population cohort using a multivariate genome-wide association study.
Aim 3 will evaluate the genetic overlap between structural neuroanatomical traits and cognitive traits associated with reading, language, math, and attention abilities. Completion of these Aims will highlight shared genetic and biological mechanisms that contribute to the etiology of learning disabilities and can serve as targets for further functional analyses. Furthermore, these findings would contribute to the future development of diagnostic tools to identify children at risk for learning disabilities, allowing them access to critical behavioral interventions and additional resources sooner. Dr. Truong received her Ph.D. in Behavioral Neuroscience and is currently a postdoctoral fellow in the Department of Pediatrics at the Yale School of Medicine. The career development plan outlines a comprehensive strategy for acquiring the technical, conceptual, and professional skills required to complete the proposed studies and launch an independent research career. It will focus on gaining 1) computational skills to handle large datasets through coursework at Yale, 2) expertise in advanced statistical genetic methods and modeling of different data types (genetic, neuroimaging, and cognitive), 3) processing and analyzing neuroimaging data; and 4) leadership, lab management, communication skills, and grant writing. The training plan, together with her background in behavioral neuroscience, genetics, and psychology, will place her among a select group of scientists with the skills and breadth of knowledge to effectively pursue interdisciplinary work on learning disabilities to uncover the complex relationships across genes, brain, and behavior.
The proposed research will integrate genetic, neuroanatomical, and cognitive data to elucidate potential molecular and biological mechanisms that underlie the etiology of learning disorders and their co-occurrence. This project will identify future targets for functional analysis. In the long term, findings will inform the future development of diagnostic tools to identify children at risk for different learning disorders and determine effective early intervention strategies.
