Evaluating resilience to inherited genetic risk variants in infants

Emma Meaburn (primary)
Centre for Brain and Cognitive Development
Birkbeck
Michael Simpson (secondary)
Division of Genetics and Molecular Medicine
King's College London

Abstract

Rapid progress has been made in identifying rare and common ‘polygenic’ genetic variants for neurodevelopmental disorders, which can have incomplete or variable penetrance. Whilst these studies provide insights into putative molecular networks affected, the phenotypes examined are almost universally based on behavioral symptoms manifested by children and adults. At present, there exists a ‘black hole’ in our ability to build mechanistic models of the effect of genetic variation on early brain development, and the mechanisms by which apparently unaffected carriers functionally compensate for increased genetic risk.

The proposed project will utilize detailed neurocognitive and behavioral measures on ~150 infants at-risk of neurodevelopmental disorders to test the hypothesis that clinically unaffected individuals at high genetic risk show atypical cognitive and/or behavioral development. It will also examine whether candidate protective factors can ameliorate the effects of high genetic risk.


References

1. Spain SL, Pedroso I, Kadeva N, Miller MB, Iacono WG, McGue M, Stergiakouli E, Smith GD, Putallaz M, Lubinski D, Meaburn EL, Plomin R, Simpson MA. A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence (2015) Mol Psychiatry.

2. Plomin & Simpson. The future of genomics for developmentalists (2013). Dev Psychopathol 25(4 Pt 2):1263-78.

3. Jones et al Developmental pathways to autism: A review of prospective studies of infants at risk. (2013). Neuroscience and Biobehavioural Reviews.

4. Lossifov et al. De Novo gene disruptions in children on the autism spectrum. (2012) Neuron 74:285-299.

5. Robinson, E. B. et al. Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nat. Genet. 48, 552–555 (2016).


BBSRC Area
Genes, development and STEM* approaches to biology
Area of Biology
DevelopmentGenetics
Techniques & Approaches
BioinformaticsGeneticsMathematics / StatisticsSimulation / Modelling