Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse. (6th March 2013)

• Record Type: Journal Article
• Authors: Costello, E. Jane; Eaves, Lindon; Sullivan, Patrick; Kennedy, Martin; Conway, Kevin; Adkins, Daniel E.; Angold, A.; Clark, Shaunna L.; Erkanli, Alaattin; McClay, Joseph L.; Copeland, William; Maes, Hermine H.; Liu, Youfang; Patkar, Ashwin A.; Silberg, Judy; van den Oord, Edwin
• Is Part Of: Twin research and human genetics. Volume 16:Number 2(2013)
• Page Start: 505
• Page End: 515
• Publication Date: 2013-03-06
• Subjects: genomewide association study, -- environment, -- development, -- multi-site; Twins -- Periodicals; Multiple birth -- Periodicals; 618.25
• DOI: 10.1017/thg.2013.6
• Languages: English
• ISSNs: 1832-4274

Abstract

Abstract : The importance of including developmental and environmental measures in genetic studies of human pathology is widely acknowledged, but few empirical studies have been published. Barriers include the need for longitudinal studies that cover relevant developmental stages and for samples large enough to deal with the challenge of testing gene–environment–development interaction. A solution to some of these problems is to bring together existing data sets that have the necessary characteristics. As part of the National Institute on Drug Abuse-funded Gene-Environment-Development Initiative, our goal is to identify exactly which genes, which environments, and which developmental transitions together predict the development of drug use and misuse. Four data sets were used of which common characteristics include (1) general population samples, including males and females; (2) repeated measures across adolescence and young adulthood; (3) assessment of nicotine, alcohol, and cannabis use and addiction; (4) measures of family and environmental risk; and (5) consent for genotyping DNA from blood or saliva. After quality controls, 2, 962 individuals provided over 15, 000 total observations. In the first gene–environment analyses, of alcohol misuse and stressful life events, some significant gene–environment and gene–development effects were identified. We conclude that in some circumstances, already collected data sets can be combined for gene–environment and gene–development analyses. This greatly reduces the cost and time needed for this type of research. However, care must be taken to ensure careful matching across studies and variables.