Gene variants associated with antisocial behaviour: a latent variable approach. (3rd July 2013)

• Record Type: Journal Article
• Authors: Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.
• Is Part Of: Journal of child psychology and psychiatry and allied disciplines. Volume 54:Number 10(2013:Oct.)
• Page Start: 1074
• Page End: 1085
• Publication Date: 2013-07-03
• Subjects: Antisocial behaviour -- latent variable analysis -- shared variance -- co‐action of gene variants; Child psychology -- Periodicals; Child psychiatry -- Periodicals; 155.4
• DOI: 10.1111/jcpp.12109
• Languages: English
• ISSNs: 0021-9630

Abstract

Abstract : Objective: The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods: Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15‐year follow‐up of a randomized trial of a prenatal and infancy nurse‐home visitation programme in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Results: Eight single‐nucleotide polymorphisms (SNPs) from eight genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all eight genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid and cholinergic signalling as well as stress response pathways in mediating susceptibility to antisocial behaviour. Conclusions: This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential 'co‐action' of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the aetiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a 'shared' variance across genetic risk alleles associated with complex neuropsychiatric dimensional phenotypes using relatively small numbers of well‐characterized research participants.