B3933 - Understanding Genetic Risk for Externalizing across Development and in Conjunction with the Environment - 17/12/2021

B number: 
Principal applicant name: 
Danielle Dick | Virginia Commonwealth University (United States)
Dr. Holly Poore, Maia Choi, Erin Gallert, Dr. Fazil Aliev, Dr. Sarah Brislin, Morgan Driver, Rebecca Smith, Nate Thomas, Dr. Amy Adkins, Emily Balcke
Title of project: 
Understanding Genetic Risk for Externalizing across Development and in Conjunction with the Environment
Proposal summary: 

Externalizing refers to a constellation of behaviors characterized by under-controlled or impulsive action and antagonism and which manifests in multiple psychiatric disorders (e.g., ADHD, substance use disorders) as well as personality, temperament, and behavioral traits. Twin and molecular genetic studies indicate that externalizing phenotypes are highly heritable and that multiple externalizing phenotypes are influenced by the same genetic factors. This project aims to characterize genetic risk for externalizing in longitudinal samples to better understand the spectrum of phenotypes associated with identified genetic variants, across development, across sex, and in conjunction with the environment.

Impact of research: 
Results from this project will further the goal of genomics research to enhance risk prediction of phenotypes associated with high disease burden and suffering. By taking genetic findings from GWAS into longitudinal, developmental studies like ALSPAC, we will be able to map the pathways by which genetic risk manifests across development, highlighting the early behavioral manifestations of risk, and studying how various individual characteristics and environments moderate the risk across developmental periods. The original externalizing GWAS, from which our polygenic scores were derived, was published in Nature Neuroscience (full citation below) and we anticipate that our follow-up analyses further characterizing risk will also be of high impact. Karlsson Linnér, R., Mallard, T.T., Barr, P.B. et al. Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction. Nat Neurosci 24, 1367–1376 (2021). https://doi.org/10.1038/s41593-021-00908-3
Date proposal received: 
Thursday, 9 December, 2021
Date proposal approved: 
Friday, 17 December, 2021
Social Science, Addiction - e.g. alcohol, illicit drugs, smoking, gambling, etc., Behaviour - e.g. antisocial behaviour, risk behaviour, etc., Mental health, GWAS, Statistical methods, Genetic epidemiology, Genetics, Genomics, Psychology - personality, Social science, Statistical methods