Literature DB >> 23461817

Genes, environments, and developmental research: methods for a multi-site study of early substance abuse.

E Jane Costello1, Lindon Eaves, Patrick Sullivan, Martin Kennedy, Kevin Conway, Daniel E Adkins, A Angold, Shaunna L Clark, Alaattin Erkanli, Joseph L McClay, William Copeland, Hermine H Maes, Youfang Liu, Ashwin A Patkar, Judy Silberg, Edwin van den Oord.   

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.

Entities:  

Mesh:

Year:  2013        PMID: 23461817      PMCID: PMC3609892          DOI: 10.1017/thg.2013.6

Source DB:  PubMed          Journal:  Twin Res Hum Genet        ISSN: 1832-4274            Impact factor:   1.587


  55 in total

1.  KEGG: kyoto encyclopedia of genes and genomes.

Authors:  M Kanehisa; S Goto
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Sample size determination for studies of gene-environment interaction.

Authors:  J A Luan; M Y Wong; N E Day; N J Wareham
Journal:  Int J Epidemiol       Date:  2001-10       Impact factor: 7.196

3.  Association studies in psychiatric genetics: what are we doing?

Authors:  E J C G van den Oord
Journal:  Mol Psychiatry       Date:  2002       Impact factor: 15.992

4.  The future of association studies: gene-based analysis and replication.

Authors:  Benjamin M Neale; Pak C Sham
Journal:  Am J Hum Genet       Date:  2004-07-22       Impact factor: 11.025

5.  Controlling the proportion of false positives in multiple dependent tests.

Authors:  R L Fernando; D Nettleton; B R Southey; J C M Dekkers; M F Rothschild; M Soller
Journal:  Genetics       Date:  2004-01       Impact factor: 4.562

6.  Genome-wide meta-analyses identify multiple loci associated with smoking behavior.

Authors: 
Journal:  Nat Genet       Date:  2010-04-25       Impact factor: 38.330

7.  The Great Smoky Mountains Study of Youth. Goals, design, methods, and the prevalence of DSM-III-R disorders.

Authors:  E J Costello; A Angold; B J Burns; D K Stangl; D L Tweed; A Erkanli; C M Worthman
Journal:  Arch Gen Psychiatry       Date:  1996-12

8.  Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples.

Authors:  Andrew M Smith; Lawrence E Heisler; Robert P St Onge; Eveline Farias-Hesson; Iain M Wallace; John Bodeau; Adam N Harris; Kathleen M Perry; Guri Giaever; Nader Pourmand; Corey Nislow
Journal:  Nucleic Acids Res       Date:  2010-05-11       Impact factor: 16.971

9.  Alcohol consumption indices of genetic risk for alcohol dependence.

Authors:  Julia D Grant; Arpana Agrawal; Kathleen K Bucholz; Pamela A F Madden; Michele L Pergadia; Elliot C Nelson; Michael T Lynskey; Richard D Todd; Alexandre A Todorov; Narelle K Hansell; John B Whitfield; Nicholas G Martin; Andrew C Heath
Journal:  Biol Psychiatry       Date:  2009-07-03       Impact factor: 13.382

Review 10.  Strategy for investigating interactions between measured genes and measured environments.

Authors:  Terrie E Moffitt; Avshalom Caspi; Michael Rutter
Journal:  Arch Gen Psychiatry       Date:  2005-05
View more
  6 in total

1.  PROSPER Intervention Effects on Adolescents' Alcohol Misuse Vary by GABRA2 Genotype and Age.

Authors:  Michael A Russell; Gabriel L Schlomer; H Harrington Cleveland; Mark E Feinberg; Mark T Greenberg; Richard L Spoth; Cleve Redmond; David J Vandenbergh
Journal:  Prev Sci       Date:  2018-01

Review 2.  The Great Smoky Mountains Study: developmental epidemiology in the southeastern United States.

Authors:  E Jane Costello; William Copeland; Adrian Angold
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2016-03-24       Impact factor: 4.328

3.  Time-varying Effects of GABRG1 and Maladaptive Peer Behavior on Externalizing Behavior from Childhood to Adulthood: Testing Gene × Environment × Development Effects.

Authors:  Elisa M Trucco; Songshan Yang; James J Yang; Robert A Zucker; Runze Li; Anne Buu
Journal:  J Youth Adolesc       Date:  2019-11-30

Review 4.  Gene-environment interactions in severe mental illness.

Authors:  Rudolf Uher
Journal:  Front Psychiatry       Date:  2014-05-15       Impact factor: 4.157

5.  Microsatellite polymorphisms associated with human behavioural and psychological phenotypes including a gene-environment interaction.

Authors:  Andrew T M Bagshaw; L John Horwood; David M Fergusson; Neil J Gemmell; Martin A Kennedy
Journal:  BMC Med Genet       Date:  2017-02-03       Impact factor: 2.103

6.  Genome-wide DNA methylation analysis of heavy cannabis exposure in a New Zealand longitudinal cohort.

Authors:  Amy J Osborne; John F Pearson; Alexandra J Noble; Neil J Gemmell; L John Horwood; Joseph M Boden; Miles C Benton; Donia P Macartney-Coxson; Martin A Kennedy
Journal:  Transl Psychiatry       Date:  2020-04-22       Impact factor: 6.222

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.