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Associations between alcohol dehydrogenase genes and alcohol use across early and middle adolescence: Moderation × Preventive intervention

Published online by Cambridge University Press:  23 May 2017

H. Harrington Cleveland ,
Gabriel L. Schlomer ,
David J. Vandenbergh ,
Pedro S. A. Wolf ,
Mark E. Feinberg ,
Mark T. Greenberg ,
Richard L. Spoth  and
Cleve Redmond
H. Harrington Cleveland*
Affiliation:
Pennsylvania State University
Gabriel L. Schlomer
Affiliation:
Pennsylvania State University
David J. Vandenbergh
Affiliation:
Pennsylvania State University
Pedro S. A. Wolf
Affiliation:
Pennsylvania State University
Mark E. Feinberg
Affiliation:
Pennsylvania State University
Mark T. Greenberg
Affiliation:
Pennsylvania State University
Richard L. Spoth
Affiliation:
Iowa State University
Cleve Redmond
Affiliation:
Iowa State University
*
Address correspondence and reprint requests to: H. Harrington Cleveland, Department of Human Development and Family Studies, Pennsylvania State University, 315 East Human Development Building, University Park, PA 16802; E-mail: [email protected].
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Abstract

Data from the in-school sample of the PROSPER preventive intervention dissemination trial were used to investigate associations between alcohol dehydrogenase genes and alcohol use across adolescence, and whether substance misuse interventions in the 6th and 7th grades (targeting parenting, family functioning, social norms, youth decision making, and peer group affiliations) modified associations between these genes and adolescent use. Primary analyses were run on a sample of 1,885 individuals and included three steps. First, we estimated unconditional growth curve models with separate slopes for alcohol use from 6th to 9th grade and from 9th to 12th grade, as well as the intercept at Grade 9. Second, we used intervention condition and three alcohol dehydrogenase genes, 1B (ADH1B), 1C (ADH1C), and 4 (ADH4) to predict variance in slopes and intercept. Third, we examined whether genetic influences on model slopes and intercepts were moderated by intervention condition. The results indicated that the increase in alcohol use was greater in early adolescence than in middle adolescence; two of the genes, ADH1B and ADH1C, significantly predicted early adolescent slope and Grade 9 intercept, and associations between ADH1C and both early adolescent slope and intercept were significantly different across control and intervention conditions.

Type
Regular Articles
Information
Development and Psychopathology , Volume 30 , Issue 1 , February 2018 , pp. 297 - 313
Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

We thank Dr. Deborah Grove, Kerry Hair, and Ashley Price of the Penn State Genomics Core Facility for DNA purification and genotyping and Lee Carpenter and Amanda Griffin for their assistance in preparing the document. Work on this paper was supported by the National Institute on Drug Abuse (Grants DA030389 and DA013709).

References

Agrawal, A., Balasubramanian, S., Smith, E., Madden, P., Bucholz, K., Heath, A., & Linskey, M. T. (2010). Peer substance involvement modifies genetic influences on regular substance involvement in young women. Addiction, 105, 1844–1853.Google Scholar
Albert, D., Belsky, D., Crowley, D. M., Latendresse, S. J., Aliev, F., Riley, B., … Dodge, K. (2015). Can genetics predict response to complex behavioral interventions? Evidence from a genetic analysis of the Fast Track randomized control trial. Journal of Policy Analysis and Management, 34, 497–518.CrossRefGoogle ScholarPubMed
Ali, M. A., Way, M. J., Marks, M., Guerrini, I., Thomson, A. D., Strang, J., … Morgan, M. Y. (2015). Phenotypic heterogeneity in study populations may significantly confound the results of genetic association studies on alcohol dependence. Psychiatric Genetics, 25, 234–240.Google Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2015). The hidden efficacy of interventions: Gene × Environment experiments from a differential susceptibility perspective. Annual Review of Psychology, 66, 381–409.Google Scholar
Bakermans-Kranenberg, M. J., van IJzendoorn, M. H., Pijlman, F. T. A., Mesman, J., & Juffer, F. (2008). Experimental evidence for differential susceptibility: Dopamine D4 receptor polymorphism (DRD4 VNTR) moderates intervention effects on toddlers’ externalizing behavior in a randomized controlled trial. Developmental Psychology, 44, 293–300.Google Scholar
Belsky, D. W., Moffitt, T. E., Baker, T., Biddle, A. H., Evans, J. P., Harintno, H., … Caspi, A. (2013). Polygenic risk and the developmental progression to heavy, persistent smoking and nicotine dependence: Evidence from a 4-decade longitudinal study. JAMA Psychiatry, 70, 534–542.Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience and dysregulation: Phenotypic plasticity and human development. Development and Psychopathology, 25, 1243–1261.Google Scholar
Belsky, J., & van IJzendoorn, M. H. (2015). What works for whom? Genetic moderation of intervention efficacy. Development and Psychopathology, 27, 1–6. doi:10.1017/S0954579414001254.Google Scholar
Berrettini, W. H., & Doyle, G. A. (2012). The CHRNA5-A3-B4 gene cluster in nicotine addiction. Molecular Psychiatry, 17, 856–866.CrossRefGoogle ScholarPubMed
Biernacka, J. M., Geske, J. R., Schneekloth, T. D., Frye, M. A., Cunningham, J. M., Choi, D. S., … Karpyak, V. M. (2013). Replication of genome wide association studies of alcohol dependence: Support for association with variation in ADH1C. PLOS ONE, 8, e58798. doi:10.1371/journal.pone.0058798 Google Scholar
Birley, A. J., Whitfield, J. B., Neale, M. C., Duffy, D. L., Heath, A. C., Boomsma, D. I., & Martin, N. G. (2005). Genetic time-series analysis identifies a major QTL for in vivo alcohol metabolism not predicted by in vitro studies of structural protein polymorphism at the ADH1B or ADH1C loci. Behavioral Genetics, 35, 509–524.Google Scholar
Botvin, G. J. (2000). Preventing adolescent drug abuse through life skills training: Theory, methods, and effectiveness. In Hansen, W. B., Giles, S. M., & Fearnow-Kenney, M. D. (Eds.), Improving prevention effectiveness (pp. 225–257). Greensboro, NC: Tanglewood Research.Google Scholar
Brody, G. H., Beach, S. R. H., Philibert, R. A., Chen, Y., & Murry, V. M. (2009). Prevention effects moderate the association of 5-HTTLPR and youth risk behavior initiation: Gene × Environment hypotheses tested via a randomized prevention design. Child Development, 80, 645–661.Google Scholar
Centers for Disease Control and Prevention. (1991). Alcohol-related traffic fatalities among youth and young adults: United States, 1982–1989. Morbidity and Mortality Weekly Report, 40, 178–179, 185–187.Google Scholar
Chang, C. C., Chow, C. C., Tellier, L. C. A. M., Vattikuit, S., Purcell, S. M., & Lee, J. J. (2015). Second generation PLINK: Rising to the challenge of larger and richer datasets. GigaScience, 4, 1–16. doi:10.1186/s13742-015-0047-8 CrossRefGoogle Scholar
Clark, D. B., Parker, A. M., & Lynch, K. G. (1999). Psychopathogy and substance-related problems during early adolescence: A survival analysis. Journal of Clinical Child Psychology, 28, 333–341.Google Scholar
Cleveland, H. H., Griffin, A., Wolf, P. A., Wiebe, R. P., Schlomer, G. L., Feinberg, M., … Vandenbergh, D. J. (in press). Transactions between substance use intervention, the oxytocin receptor (OXTR) gene, and peer substance use predicting youth alcohol use. Prevention Science. doi:10.1007/s11121-017-0749-5 Google Scholar
Cleveland, H. H., Schlomer, G. L., Vandenbergh, D. J., Feinberg, M., Greenberg, M., Spoth, R. … Hair, K. L. (2015). The conditioning of intervention effects on early adolescent alcohol use by maternal involvement and dopamine receptor D4 (DRD4) and serotonin transporter linked polymorphic region (5-HTTLPR) genetic variants. Development and Psychopathology, 27, 51–67. doi:10.1017/s0954579414001291 Google Scholar
Cleveland, H. H., & Wiebe, R. (2008). Understanding the progression from adolescent marijuana use to young adult serious drug use: Gateway effect or developmental trajectory? Development and Psychopathology, 20, 615–632.Google Scholar
Cleveland, H. H., Schlomer, G. L., Vandenbergh, D. J., Feinberg, M., Greenberg, M., Spoth, R., … Hair, K. L. (2015). The conditioning of intervention effects on early adolescent alcohol use by maternal involvement and dopamine receptor D4 (DRD4) and serotonin transporter linked polymorphic region (5-HTTLPR) genetic variants. Development and Psychopathology, 27, 51–67. doi:10.1017/s0954579414001291 Google Scholar
Cleveland, H. H., Zheng, Y., Wiebe, R., & McGuire, J. (2015). Predicting the drinking of minority adolescents from their exposure to White schoolmates: Differences and similarities between Hispanic, Black, and Asian adolescents. Journal of Ethnicity in Substance Use, 14, 166–186. doi:10.1080/15332640.2014.973626 CrossRefGoogle Scholar
Dobkin, P. I., Tremblay, R. A., & Masse, L. C. (1995). Individual and peer characteristics in predicting boys’ early onset of substance abuse: A seven-year longitudinal study. Child Development, 28, 1198–1214 Google Scholar
Edenberg, H. J., & Foroud, T. (2014). Genetics of alcoholism in alcohol and the nervous system. In Sullivan, E. V. & Pfefferbaum, A. (Eds.), Handbook of clinical neurology (Vol. 125, 3rd series, pp. 561–571). New York: Elsevier.Google Scholar
Edenberg, H. J., Jerome, R. E., & Li, M. (1999). Polymorphism of the human alcohol dehydrogenase 4 (ADH4) promoter affects gene expression. Pharmacogenetics, 9, 25–30.CrossRefGoogle ScholarPubMed
Ellickson, P. L., McCaffrey, D. F., Ghosh-Dastidar, B., & Longshore, D. L. (2003). New inroads in preventing adolescent drug use: Results from a large-scale trial of Project ALERT in middle schools. American Journal of Public Health, 93, 1830–1836.CrossRefGoogle ScholarPubMed
Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology, 23, 7–28.CrossRefGoogle Scholar
Gottesman, I. I., & Gould, T. D. (2003). The endophenotype concept in psychiatry: Etymology and strategic intentions. American Journal of Psychiatry, 160, 636–645.Google Scholar
Grochans, E., Grzywacz, A., Małecka, I., Samochowiec, A., Karakiewicz, B., & Samochowiec, J. (2011). Research on associations between selected polymorphisms of genes DRD2, 5HTT, GRIK3, ADH4 and alcohol dependence syndrome. Psychiatria Polska (Warszawa) , 45, 325–335.Google ScholarPubMed
Guindalini, C., Scivoletto, S., Ferreira, R. G., Breen, G., Zilberman, M., Peluso, M. A., & Zatz, M. (2005). Association of genetic variants in alcohol dehydrogenase 4 with alcohol dependence in Brazilian patients. American Journal of Psychiatry, 162, 1005–1007.CrossRefGoogle ScholarPubMed
Halder, I., Shriver, M., Thomas, M., Fernandez, J. R., & Frudakis, T. (2008). A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: Utility and applications. Human Mutation, 29, 648–658.Google Scholar
Hawkins, J. D., Graham, J. W., Maguin, E., Abbott, R., Hill, K. G., & Catalano, R. F. (1997). Exploring the effects of age of alcohol use initiation and psychosocial risk factors on subsequent misuse. Journal of Studies on Alcohol, 58, 280–290.CrossRefGoogle Scholar
Hingson, R. W., & Zha, W. (2009). Age of drinking onset, alcohol use disorders, frequent heavy drinking, and unintentionally injuring oneself and others after drinking. Pediatrics, 123, 1477–1484. doi:10.1542/peds.2008-2176 Google Scholar
Hurley, T. D., Edenberg, H., & Li, T.-K. (2002). The pharmacogenomics of alcoholism. In Licinio, J. & Wong, M.-L. (Eds.), Pharmacogenomics: The search for individualized therapies. Weinheim, Germany: Wiley-VCH.Google Scholar
Jessor, R., & Jessor, S. L. (1977). Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press.Google Scholar
Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2006). Monitoring the future: National survey results on drug use, 1975–2005: Vol. 1. Secondary school students. Bethesda, MD: National Institute on Drug Abuse.Google Scholar
Keyes, M. A., Iacono, W. G., & McGue, M. (2007). Early onset problem behavior, young adult psychopathology, and contextual risk. Twin Research and Human Genetics, 10, 45–53.Google Scholar
Kuo, P. H., Kalsi, G., Prescott, C. A., Hodgkinson, C. A., Goldman, D., van den Oord, E. J., … Riley, B. P. (2008). Association of ADH and ALDH genes with alcohol dependence in the Irish Affected Sib Pair Study of alcohol dependence (IASPSAD) sample. Alcohol Clinical & Experimental Research, 32, 785–795.Google Scholar
Kuryatov, A., Berrettini, W., & Lindstrom, J. (2001). Acetylcholine receptor (AChR) α5 subunit variant associated with risk for nicotine dependence and lung cancer reduces (α4β2)2α5 AChR function. Molecular Pharmacology, 79, 119–125.Google Scholar
Li, M., & Edenberg, H. J. (2009). Function of cis-acting elements in human alcohol dehydrogenase 4 (ADH4) promoter and role of C/EBP proteins in gene expression. DNA and Cell Biology, 17, 387–397.Google Scholar
Lo, C. C. (2000). Timing of drinking initiation: A trend study predicting drug use among high school. Journal of Drug Issues, 30, 525–554.Google Scholar
Luo, X., Kranzler, H. R., Zuo, L., Lappalainen, J., Yang, B. Z., & Gelernter, J. (2006). ADH4 gene variation is associated with alcohol dependence and drug dependence in European Americans: Results from HWD tests and case-control association studies. Neuropsychopharmacology, 31, 1085–1095.Google Scholar
Luo, X., Kranzler, H. R., Zuo, L., Wang, S., Schork, N. J., & Gelernter, J. (2007). Multiple ADH genes modulate risk for drug dependence in both African- and European-Americans. Human Molecular Genetics, 16, 380–390.Google Scholar
Luo, X., Kranzler, H. R., Zuo, L., Yang, B. Z., Lappalainen, J., & Gelernter, J. (2005). ADH4 gene variation is associated with alcohol and drug dependence: Results from family controlled and population-structured association studies. Pharmacogenetics and Genomics, 15, 755–768.Google Scholar
Macgregor, S., Lind, P. A., Bucholz, K. K., Hansell, N. K., Madden, P. A., Richter, M. M., … Whitfield, J. B. (2009). Associations of ADH and ALDH2 gene variation with self-report alcohol reactions, consumption and dependence: An integrated analysis. Human Molecular Genetics, 18, 580–593. doi:10.1093/hmg/ddn372 Google Scholar
McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114, 376–390.Google Scholar
McGue, M., Iacono, W. G., Legrand, L. N., & Elkins, I. (2001). Origins and consequences of age at first drink: II. Familial risk and heritability. Alcohol Clinical and Experimental Research, 25, 1166–1173.Google Scholar
McNeal, R. B. Jr., Hansen, W. B., Harrington, N. G., & Giles, S. M. (2004). How All Stars works: An examination of program effects on mediating variables. Health Education & Behavior, 31, 165–178.Google Scholar
Meyers, J. L., & Dick, D. M. (2010). Genetic and environmental risk factors for adolescent-onset substance use disorders. Child Adolescent Psychiatric Clinics North America, 19, 465–477.Google Scholar
Muthén, L. K., & Muthén, B. O. (1998–2015). Mplus user's guide (7th ed.). Los Angeles: Author.Google Scholar
Nikolova, Y. S., Ferrell, R. E., Manuck, S. B., & Hariri, A. R. (2011). Multilocus genetic profile for dopamine signaling predicts ventral striatum reactivity. Neuropsychopharmacology, 36, 1940–1947.Google Scholar
Olfson, E., Edenberg, H. J., Nurnberger, J. Jr., Agrawal, A., Bucholz, K. K., Almasy, L. A., … Bierut, L. J. (2014). An ADH1B variant and peer drinking in progression to adolescent drinking milestones: Evidence of a gene-by-environment interaction. Alcohol Clinical and Experimental Research, 38, 2541–2549. doi:10.1111/acer.12524 Google Scholar
Osier, M. V., Pakstis, A. J., Soodyall, H., Comas, D., Goldman, D., Odunsi, A., … Kidd, K. K. (2002). A global perspective on genetic variation at the ADH genes reveals unusual patterns of linkage disequilibrium and diversity. American Journal of Human Genetics, 71, 84–99.Google Scholar
Parker, D. A., Levin, B. M., & Harford, T. C. (1996). Effects of early drinking and an antisocial orientation on the alcohol use of young Russians. Alcohol Clinical and Experimental Research, 20, 1179–1183.CrossRefGoogle Scholar
Pikanen, T., Lyyra, A. L., & Pulkkinen, L (2005). Age of onset of drinking and the use of alcohol in adulthood: A follow-up study from age 8–42 for females and males. Addiction, 100, 652–661.Google Scholar
Preuss, U. W., Ridinger, M., Rujescu, D., Samochowiec, J., Fehr, C., Wurst, F. M., … Zill, P. (2011). Association of ADH4 genetic variants with alcohol dependence risk and related phenotypes: Results from a larger multicenter association study. Addiction Biology, 16, 323–333.Google Scholar
Purcell, S. M., & Chang, C. C. (2015). PLINK 1.9. Retrieved from https://www.cog-genomics.org/plink2 Google Scholar
Rose, R. J., Dick, D. M., Viken, R. J., Pulkkinen, L., & Kapio, J (2001) Drinking or abstaining at age 14: A genetic epidemiological study. Alcohol: Clinical and Experimental Research, 25, 1594–1604.Google Scholar
Saccone, S. F., Hinrichs, A. L., Saccone, N. L., Chase, G. A., Konvicka, K., Madden, P. A., … Bierut, L. J. (2007). Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs. Human Molecular Genetics, 16, 36–49.Google Scholar
Salvatore, J. E., & Dick, D. M. (2015). Gene-environment interplay: Where we are, where we are going. Journal of Marriage and Family, 77, 344–350. doi:10.1111/jomf.12164 Google Scholar
Sampson, H. H., Maxell, C. O., & Doyle, T. F. (1989). The relation of initial alcohol experiences to current alcohol consumption. Journal of Studies on Alcohol, 50, 254–260.Google Scholar
Sartor, C. E., Lynskey, M. T., Bucholz, K. K., Madden, P. A. F., Martin, N. G., & Heath, A. C. (2009). Timing of first alcohol use and alcohol dependence: Evidence of common genetic influences. Addiction, 104, 1512–1518.Google Scholar
SAS Institute. (2012). SAS/STAT 9.4 users guide: Survey data analysis. Cary, NC: Author.Google Scholar
Schlomer, G. L., Bauman, S., & Card, N. A. (2010). Best practices for missing data management in counseling psychology. Journal of Counseling Psychology, 57, 1–10. doi:10.1037/a0018082 Google Scholar
Schlomer, G. L., Cleveland, H. H., Vandenbergh, D. J., Fosco, G. M., & Feinberg, M. E. (2015). Looking forward in candidate gene research: Concerns and suggestions. Journal of Marriage and Family, 77, 351–354. doi:10.1111/jomf.12165 Google Scholar
Schlomer, G. L., Fosco, G. M., Cleveland, H. H., Vandenbergh, D. J., & Feinberg, M. E. (2015). Interparental relationship sensitivity leads to adolescent internalizing problems: Different genotypes, different pathways. Journal of Marriage and Family, 77, 329–343. doi:10.1111/jomf.12168 CrossRefGoogle ScholarPubMed
Schulenberg, L. E., & Maggs, J. L. (2002). A developmental perspective on alcohol use and heaving drinking during adolescence and the transition to young adulthood. Journal of Studies on Alcohol, 14, 54–70.Google Scholar
Spear, L. P. (2015). Adolescent alcohol exposure: Are there separable vulnerable periods within adolescence? Physiology & Behavior, 148, 122–130. doi:10.1016/j.physbeh.2015.01.027 Google Scholar
Spoth, R., Greenberg, M., Bierman, K., & Redmond, C. (2004). PROSPER community-university partnership model for public education systems: Capacity-building for evidence-based, competence-building prevention. Prevention Science, 5, 31–39.Google Scholar
Spoth, R., Guyll, M., Lillehoj, C. J., Redmond, C., & Greenberg, M. (2007). PROSPER study of evidence-based intervention implementation quality by community-university partnerships. Journal of Community Psychology, 35, 981–999. doi:10.1002/jcop.20207 Google Scholar
Spoth, R., Redmond, C., Clair, S., Shin, C., Greenberg, M., & Feinberg, M. (2011). Preventing substance misuse through community-university partnerships: Randomized controlled trial outcomes 4½ years past baseline. American Journal of Preventive Medicine, 40, 440–447.Google Scholar
Stueve, A., & O'Donnell, L. N. (2005). Early alcohol initiation and subsequent sexual and alcohol risk behaviors among urban youths. American Journal of Public Health, 95, 887–893.Google Scholar
Substance Abuse and Mental Health Services Administration. (2006). Results from the 2005 National Survey on Drug Use and Health: National findings (Office of Applied Studies, NSDUH Series H-30, DHHS Publication No. SMA 06-4194). Rockville, MD: Author.Google Scholar
Tolstrup, J. S., Nordestgaard, B. G., Rasmussen, S., Tybjaerg-Hansen, A., & Grønbaek, M. (2008). Alcoholism and alcohol drinking habits predicted from alcohol dehydrogenase genes. Pharmacogenomics Journal, 8, 220–207.Google Scholar
Treutlein, J., Cichon, S., Ridinger, M., Wodarz, N., Soyka, M., Zill, P., … Rietschel, M. (2009). Genome-wide association study of alcohol dependence. Archives of General Psychiatry, 66, 773–784. doi:10.1001/archgenpsychiatry.2009.83 Google Scholar
Tsukahara, M., & Yoshida, A. (1989). Chromosomal assignment of the alcohol dehydrogenase cluster locus to human chromosome 4q21-23 by in situ hybridization. Genomics, 4, 218–220.Google Scholar
Vandenbergh, D. J., Schlomer, G. L., Cleveland, H. H., Schink, A. E., Feinberg, M. E., Neiderhiser, J. M., … Redmond, C. (2016). An adolescent drug use intervention blocks the effect of CHRNA5 genotype on smoking in high school. Nicotine & Tobacco Research, 18, 212–220. doi:10.1093/ntr/ntv095 Google Scholar
Wall, T. L., Luczak, S. E., Orlowska, D., & Pandika, D. (2013). Differential metabolism of alcohol as an intermediate phenotype of risk for alcohol use disorders: Alcohol and aldehyde dehydrogenase variants. In MacKillop, J. & Munafò, M. R. (Eds.), Genetic influences on addiction: An intermediate phenotype approach (pp. 41–63). Cambridge, MA: MIT Press.Google Scholar
Wang, J. C., Kapoor, M., & Goate, A. M. (2012). The genetics of substance dependence. Annual Review of Genomics and Human Genetics, 13, 241–261. doi:10.1146/annurev-genom-090711-163844 Google Scholar
Way, M., McQuillin, A., Saini, J., Ruparelia, K., Lydall, G. J., Guerrini, I., … Gurling, H. M. (2015). Genetic variants in or near ADH1B and ADH1C affect susceptibility to alcohol dependence in a British and Irish population. Addiction Biology, 20, 594–604.Google Scholar
Werner, M. J., Walker, L. S., & Greee, J. W. (1994). Longitudinal evaluation of a screening measure for problem drinking among female college freshman. Archives of Pediatrics and Adolescent Medicine, 148, 1331–1337.Google Scholar
Widaman, K. F., Helm, J. L., Castro-Schilo, L., Pluess, M., Stallings, M. C., & Belsky, J. (2012). Distinguishing ordinal and disordinal interactions. Psychological Methods, 17, 615–622.Google Scholar
Windle, M. (2004). Suicidal behaviors and alcohol use among adolescents: A developmental psychopathology perspective. Alcohol Clinical and Experimental Research, 28(Suppl.), 29S–37S.Google Scholar
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011). GCTA: A tool for genome-wide complex trait analysis. American Journal of Human Genetics, 88, 76–82.Google Scholar
Ystrom, E., Kenneth, S., Kendler, K. S., & Reichborn-Kjennerud, T. (2014). Early age of alcohol initiation is not the cause of alcohol use disorders in adulthood, but is a major indicator of genetic risk: A population-based twin study. Addiction, 109, 1824–1832.Google Scholar
Zucker, R. A. (2006). Alcohol use and the alcohol use disorders: A developmental-biopsychological systems formulation covering the life course. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental psychopathology: Vol. 3. Risk, disorder and adaptation (2nd ed., pp. 620–656). Hoboken, NJ: Wiley.Google Scholar
Zucker, R. A., Donovan, J. E., Masten, A. S., Mattson, M. E., & Moss, H. (2008). Early developmental processes and the continuity of risk for underage drinking and problem drinking. Pediatrics, 121(Suppl. 4), S252–S272.Google Scholar