Skip to main content Accessibility help

Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse

  • E. Jane Costello (a1), Lindon Eaves (a2), Patrick Sullivan (a3), Martin Kennedy (a4), Kevin Conway (a5), Daniel E. Adkins (a6), A. Angold (a1), Shaunna L. Clark (a6), Alaattin Erkanli (a1), Joseph L. McClay (a6), William Copeland (a1), Hermine H. Maes (a2), Youfang Liu (a7), Ashwin A. Patkar (a1), Judy Silberg (a2) and Edwin van den Oord (a2)...


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.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse
      Available formats

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse
      Available formats

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse
      Available formats


Corresponding author

Address for correspondence: Professor E. J. Costello, Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Suite 22, Brightleaf Square, 905 West Main Street, Durham, NC 27701, USA. E-mail:


Hide All
Ackermann, K. H., Adams, N., Adler, C., Ahammed, Z., Ahmad, S., Allgower, C., . . . Zubarev, A. N. (2001). Elliptic flow in Au + Au collisions at square root(S)NN = 130 GeV. Physical Review Letters, 86, 402407.
Adkins, D. E., Daw, J. K., McClay, J. L., & van den Oord, E. J. C. G. (2012). The influence of five monoamine genes on trajectories of depressive symptoms across adolescence and young adulthood. Development and Psychopathology, 24, 267285.
Agrawal, A. N., Freedman, D., Cheng, Y. C., Lin, P., Shaffer, J. R., Sun, Q., . . . GENEVA Consortium. (2012). Measuring alcohol consumption for genomic meta-analyses of alcohol intake: Opportunities and challenges. American Journal of Clinical Nutrition, 95, 539547.
Agrawal, A. J., Grant, D., Littlefield, A., Waldron, M., Pergadia, M. L., Lynskey, M. T., . . . Heath, A. C. (2009). Developing a quantitative measure of alcohol consumption for genomic studies on prospective cohorts. Journal of Studies on Alcohol and Drugs, 70, 157168.
American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed., DSM-IV). Washington, DC: APA.
Anastasi, A. (1950). The concept of validity in the interpretation of test scores. Journal of Psychology and Educational Measures, 10, 6778.
Angold, A., Erkanli, A., Farmer, E. M., Fairbank, J. A., Burns, B. J., Keeler, G., & Costello, E. J. (2002). Psychiatric disorder, impairment, and service use in rural African American and White youth. Archives of General Psychiatry, 59, 893901.
Bath, P. A., Deeg, D., & Poppelaars, J. (2010). The harmonisation of longitudinal data: A case study using data from cohort studies in The Netherlands and the United Kingdom. Ageing & Society, 30, 14191437.
Beecham, G. W., Martin, E. R., Li, Y.-J., Slifer, M. A., Gilbert, J. R., Haines, J. L., & Pericak-Vance, M. A. (2009). Genome-wide association study implicates a chromosome 12 risk locus for late-onset Alzheimer disease. American Journal of Human Genetics, 84, 3643.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B, 57, 289300.
Black, M. A. (2004). A note on the adaptive control of false discovery rates. J. R. Statist. Soc. B, 66 (2), 297304.
Bookman, E. B., McAllister, K., Gillanders, E., Wanke, K., Balshaw, D., Rutter, J., . . . Birnbaum, L. S., for the NIH G × E Interplay Workshop participants. (2011). Gene-environment interplay in common complex diseases: Forging an integrative model-recommendations from an NIH workshop. Genetic Epidemiology, doi:10.1002/gepi.20571 (Epub ahead of print).
Borden, K. A., Brown, R. T., Jenkins, P., & Clingerman, S. R. (1987). Achievement attributions and depressive symptoms in attention deficit disordered and normal children. Journal of School Psychology, 25, 399404.
Casey, B. J., Glatt, C. E., Tottenham, N., Soliman, F., Bath, K., Amso, D., . . . Lee, F. S. (2009). Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development. Neuroscience, 164, 108120.
Chiang, M. C., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Hickie, I., Toga, A. W., . . . Thompson, P. M. (2011). Genetics of white matter development: A DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage, 54, 23082317.
Cole, S. W., Arevalo, J. M., Manu, K., Telzer, E. H., Kiang, L., Bower, J. E., . . . Fuligni, A. J. (2011). Antagonistic pleiotropy at the human IL6 promoter confers genetic resilience to the pro-inflammatory effects of adverse social conditions in adolescence. Developmental Psychology, 47, 11731180.
Copeland, W., Gottfredson, N., Adkins, D. E., Angold, A., Clark, S. L., Erkanli, A., . . . Costello, E. J. (2012). Stressful life events and alcohol use: A longitudinal G×E GWAS meta-analysis. Manuscript submitted for publication.
Cornelis, M. C., Agrawal, A., Cole, J. W., Hansel, N. N., Barnes, K. C., Beaty, T. H., . . . GENEVA Consortium. (2010). The Gene, Environment Association Studies consortium (GENEVA): Maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions. Genetic Epidemiology, 34, 364372.
Costello, E. J., Angold, A., Burns, B. J., Stangl, D. K., Tweed, D. L., Erkanli, A., & Worthman, C. M. (1996). The Great Smoky Mountains Study of Youth: Goals, designs, methods, and the prevalence of DSM-III-R disorders. Archives of General Psychiatry, 53, 11291136.
Costello, E., Farmer, E., Angold, A., Burns, B. J., & Erkanli, A. (1997). Psychiatric disorders among American Indian and White youth in Appalachia: The Great Smoky Mountains Study. American Journal of Public Health, 87, 827832.
Derringer, J., Krueger, R. F., McGue, M., & Iacono, W. G. (2008). Genetic and environmental contributions to the diversity of substances used in adolescent twins: a longitudinal study of age and sex effects. Addiction, 103, 17441751.
Di Chiara, G., & Imperato, A. (1988). Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freely moving rats. Proceedings of the National Academy of Sciences USA, 85, 52745278.
Dick, D. M. (2011). Developmental changes in genetic influences on alcohol use and dependence. Child Development Perspectives, 5, 223230.
Dunlap, W. P., Cortina, J. M., Vaslow, J. B., & Burke, M. J. (1996). Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods, 1, 170177.
Edenberg, H. J. (2007). The genetics of alcohol metabolism: Role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Research & Health, 30, 513.
Fergusson, D., & Horwood, L. (2001). The Christchurch health and development study: Review of findings on child and adolescent mental health. Australian and New Zealand Journal of Psychiatry, 35, 287296.
Fernando, R., Nettleton, D., Southey, B. R., Dekkers, J. C. M., Rothschild, M. F., & Soller, M. (2004). Controlling the proportion of false positives in multiple dependent tests. Genetics, 166, 611619.
Fortier, I., Doiron, D., Little, J., Ferretti, V., L'Heureux, F., Stolk, R. P., . . . International Harmonization Initiative. (2011). Is rigorous retrospective harmonization possible? Application of the DataSHaPER approach across 53 large studies. International Journal of Epidemiology, 40, 13141328.
Gnirke, A., Melnikov, A., Maguire, J., Rogov, P., LeProust, E. M., Brockman, W., . . . Nusbaum, C. (2009). Solution hybrid selection with ultra-long oligonucleotides for massively parallel-targeted sequencing. Nature Biotechnology, 27, 182189.
Grant, J. D., Agrawal, A., Bucholz, K. K., Madden, P. A. F., Pergadia, M. L., . . . Heath, A. C. (2009). Alcohol consumption indices of genetic risk for alcohol dependence. Biological Psychiatry, 66, 795800.
International Schizophrenia Consortium. (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748752.
Kanehisa, M., & Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28, 2730.
Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., & Tanabe, M. (2011). KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research, 40, D109D114.
Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter promoter variant (5-HTTLPR), stress, and depression meta-analysis revisited: Evidence of genetic moderation. Archives of General Psychiatry, 68, 444454.
Khoury, M. J., & Wacholder, S. (2009). Invited commentary: From genome-wide association studies to gene-environment-wide interaction studies – Challenges and opportunities. American Journal of Epidemiology, 169, 227230; discussion 234–225.
Korn, E., Troendle, J., McShane, L. M., & Simon, R. (2004). Controlling the number of false discoveries: Application to high-dimensional genomic data. Journal of Statistical Planning and Inference, 124, 379398.
Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C., Zody, M. C., Baldwin, J., . . . International Human Genome Sequencing Consortium. (2001). Initial sequencing and analysis of the human genome. Nature, 409, 860921.
Lee, P. H., O'Dushlaine, C., Thomas, B., & Purcell, S. M. (2012). INRICH: Interval-based enrichment analysis for genome-wide association studies. Bioinformatics, 28, 17971799.
Le Merrer, J., Becker, J. A., Befort, K., & Kieffer, B. L. (2009). Reward processing by the opioid system in the brain. Physiological Reviews, 89, 13791412.
Lei, S.-F., Yang, T.-L., Tan, L.-J., Chen, X.-D., Guo, Y., Guo, Y.-F., . . . Deng, H.-W. (2009). Genome-wide association scan for stature in Chinese: evidence for ethnic specific loci. Human Genetics, 125 (1), 19.
Lenroot, R. K., & Giedd, J. N. (2011). Annual research review: Developmental considerations of gene by environment interactions. Journal of Child Psychology and Psychiatry, 52, 429441.
Liu, J., Zhang, Z., Bando, M., Itoh, T., Deardorff, M. A., Clark, D., . . . Krantz, I. D. (2009). Transcriptional dysregulation in NIPBL and cohesin mutant human cells. PLoS Biol, 7 (5): e1000119. doi:10.1371/journal.pbio.1000119
Liu, J. Z., McRae, A. F., Nyholt, D. R., Medland, S. E., Wray, N. R., Brown, K. M., . . . Macgregor, S. (2010a). A versatile gene-based test for genome-wide association studies. The American Journal of Human Genetics, 87, 139145.
Liu, J. Z., Tozzi, F., Waterworth, D. M., Pillai, S. G., Muglia, P., Middleton, L., . . . Marchini, J. (2010b). Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nature Genetics, 42, 436440.
Luan, J. A., Wong, M. Y., Day, N. E., & Wareham, N. J. (2001). Sample size determination for studies of gene-environment interaction. International Journal of Epidemiology, 30, 1035.
Mailman, M. D., Feolo, M., Jin, Y., Kimura, M., Tryka, K., Bagoutdinov, R., . . . Sherry, S. T. (2007). The NCBI dbGaP database of genotypes and phenotypes. Nature Genetics, 39, 11811186.
McKernan, K. J., Peckham, H. E., Costa, G. L., McLaughlin, S. F., Fu, Y., Tsung, E. F., . . . Blanchard, A. P. (2009). Sequence and structural variation in a human genome uncovered by short-read, massively parallel ligation sequencing using two-base encoding. Genome Research, 19, 15271541.
Moffitt, T. E., Caspi, A., & Rutter, M. (2005). Strategy for investigating interactions between measured genes and measured environments. Archives of General Psychiatry, 62, 473481.
Neale, B. M., & Sham, P. C. (2004). The future of association studies: Gene-based analysis and replication. American Journal of Human Genetics, 75, 353362.
Ng, S. B., Turner, E. H., Robertson, P. D., Flygare, S. D., Bigham, A. W., Lee, C, . . . Shendure, J. (2009). Targeted capture and massively parallel sequencing of 12 human exomes. Nature, 461, 272276.
Pagan, J. L., Rose, R. J., Viken, R. J., Pulkkinen, L., Kaprio, J., & Dick, D. M. (2006). Genetic and environmental influences on stages of alcohol use across adolescence and into young adulthood. Behavior Genetics, 36, 483497.
Price, A. L., Butler, J., Patterson, N., Capelli, C., Pascali, V. L., Scarnicci, F., . . . Hirschhorn, J. N. (2008). Discerning the ancestry of European Americans in genetic association studies. PLoS Genetics, 4, e236.
Purcell, S. M., Wray, N. R., Stone, J. L., Visscher, P. M., O'Donovan, M. C., Sullivan, P. F., . . . International Schizophrenia Consortium (2009). Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 460, 748752.
Rose, R. J., & Dick, D. M. (2010). Commentary on Agrawal et al. (2010): Social environments modulate alcohol use. Addiction, 105, 18541855.
Sabatti, C., Service, S., & Freimer, N. (2003). False discovery rate in linkage and association genome screens for complex disorders. Genetics, 164, 829833.
Schumann, G., Coin, L. J., Lourdusamy, A., Charoen, P., Berger, K. H., Stacey, D., . . . Ellioty, P. (2011). Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption. Proceedings of the National Academy of Sciences, USA, 108, 71197124.
Simonoff, E., Pickles, A., Meyer, J. M., Silberg, J. L., Maes, H. H., Loeber, R., . . . Eaves, L. J. (1997). The Virginia Twin Study of adolescent behavioral development: Influences of age, sex and impairment on rates of disorder. Archives of General Psychiatry, 54, 801808.
Smith, A. M., Heisler, L. E., St Onge, R. P., Farias-Hesson, E., Wallace, I. M., Bodeau, J., . . . Nislow, C. (2010). Highly multiplexed barcode sequencing: An efficient method for parallel analysis of pooled samples. Nucleic Acids Research, 38, e142.
Solinas, M., Yasar, S., & Goldberg, S. R. (2007). Endocannabinoid system involvement in brain reward processes related to drug abuse. Pharmacological Research, 56, 393405.
Spatola, C. A., Scaini, S., Pesenti-Gritti, P., Medland, S. E., Moruzzi, S., Ogliari, A., . . . Battaglia, M. (2011). Gene–environment interactions in panic disorder and CO2 sensitivity: Effects of events occurring early in life. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 156B, 7988.
Storey, J. (2003). The positive false discovery rate: A Bayesian interpretation and the q-value. Annals of Statistics, 31, 20132035.
Sullivan, P. F., Eaves, L. J., Kendler, K. S., & Neale, M. C. (2001). Genetic case-control association studies in neuropsychiatry. Archives of General Psychiatry, 58, 10151024.
Sung, M., AErkanli, A., Angold, A., & Costello, E. J. (2004). Effects of age at first substance use and psychiatric comorbidity on the development of substance use disorders. Drug and Alcohol Dependence, 75, 287299.
Tarter, R. E., & Vanyukov, M. (1994). Alcoholism: A developmental disorder. Journal of Consulting and Clinical Psychology, 62 (6), 10961107.
Thomas, D. (2010). Gene–environment-wide association studies: Emerging approaches. Nature Reviews Genetics, 11, 259272.
Thorgeirsson, T. E., Gudbjartsson, D. F., Surakka, I., Vink, J. M., Amin, N., Geller, F., . . . Stefansson, K. (2010). Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior. Nature Genetics, 42, 448453.
Tsai, C. A., Hsueh, H. M., & Chen, J. J. (2003). Estimation of false discovery rates in multiple testing: Application to gene microarray data. Biometrics, 59, 10711081.
van den Oord, E. J. (2002). Association studies in psychiatric genetics: What are we doing? Molecular Psychiatry, 7, 827828.
van den Oord, E. J., & Sullivan, P. (2003). False discoveries and models for gene discovery. Trends in Genetics, 19, 537542.
van Ijzendoorn, M. H., Bakermans-Kranenburg, M. J., Belsky, J., Beach, S., Brody, G., Dodge, K. A., . . . Scott, S. (2011). Gene-by-environment experiments: A new approach to finding the missing heritability. Nature Reviews Genetics, 12, 881.
Wang, K., Li, M., & Bucan, M. (2007). Pathway-based approaches for analysis of genomewide association studies. The American Journal of Human Genetics, 81, 12781283.
Wong, M. Y., Day, N. E., Luan, J. A., Chan, K. P., & Wareham, N. J. (2003). The detection of gene–environment interaction for continuous traits: Should we deal with measurement error by bigger studies or better measurement? International Journal of Epidemiology, 32, 51.
Wong, M. Y., Day, N. E., Luan, J. A., & Wareham, N. J. (2004). Estimation of magnitude in gene–environment interactions in the presence of measurement error. Statistics in Medicine, 23, 987998.


Related content

Powered by UNSILO

Genes, Environments, and Developmental Research: Methods for a Multi-Site Study of Early Substance Abuse

  • E. Jane Costello (a1), Lindon Eaves (a2), Patrick Sullivan (a3), Martin Kennedy (a4), Kevin Conway (a5), Daniel E. Adkins (a6), A. Angold (a1), Shaunna L. Clark (a6), Alaattin Erkanli (a1), Joseph L. McClay (a6), William Copeland (a1), Hermine H. Maes (a2), Youfang Liu (a7), Ashwin A. Patkar (a1), Judy Silberg (a2) and Edwin van den Oord (a2)...


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.