B3109 - Predictive genomic classifiers for the risk assessment of common learning disabilities in children - 29/05/2018

B number: 
B3109
Principal applicant name: 
Emmanuel Labourier | Cognitive Genetics (USA)
Co-applicants: 
Dr. Dennis Wylie
Title of project: 
Predictive genomic classifiers for the risk assessment of common learning disabilities in children
Proposal summary: 

Learning disabilities are common disorders characterized by unexpected difficulty with a specific mode of learning in the context of adequate intelligence and academic opportunity. The high prevalence of these disorders in the general population represents a costly burden to the educational system and affected individual are often at risk for long-term adverse psychological and socioeconomic outcomes. Intervention programs work, but are more effective when tailored to individuals and administered earlier in life. The pre-symptomatic detection of individual who are at risk of developing learning disabilities, and who are more likely to benefit from early intervention, is therefore an important diagnostic opportunity with major economic and societal implications. The objective of this project is to evaluate the diagnostic performance and predictive value of genetic variants associated with learning disabilities in the ALSPAC cohort.

Impact of research: 
This research has the potential to improve the pre-symptomatic diagnosis of children at risk of developing learning disabilities and who may benefit from early intervention strategies
Date proposal received: 
Friday, 4 May, 2018
Keywords: 
Clinical research/clinical practice, Cognitive impairment, Learning difficulty, Speech/language problem, Computer simulations/modelling/algorithms, Cognition - cognitive function, Communication (including non-verbal), Genomics, Speech and language