Annals of Behavioral Medicine

, Volume 40, Issue 1, pp 77–88

Evaluation of a Brief Web-Based Genetic Feedback Intervention for Reducing Alcohol-Related Health Risks Associated with ALDH2

  • Christian S. Hendershot
  • Jacqueline M. Otto
  • Susan E. Collins
  • Tiebing Liang
  • Tamara L. Wall
Original Article

Abstract

There is increasing interest in health interventions that incorporate genetic risk information. Although genetic feedback has been evaluated as an adjunct to smoking cessation interventions, its efficacy for reducing alcohol-related risks is unknown. The purpose of this study was to evaluate the feasibility, acceptability, and efficacy of a web-based alcohol intervention incorporating genetic feedback and risk information specific to ALDH2 genotype. The ALDH2*2 variant is associated with partial protection against alcohol dependence but confers significantly increased risk for alcohol-related cancers as a function of alcohol exposure. Two hundred Asian-American young adults were randomly assigned to receive web-based personalized genetic feedback or attention-control feedback. Genetic feedback included health risk information specific to alcohol-related cancer or alcohol dependence, depending on genotype. Outcomes included postintervention drinking behavior and theoretical correlates of behavior change. Genetic feedback and risk information resulted in significant reductions in 30-day drinking frequency and quantity among participants with the ALDH2*1/*2 genotype. Genetic feedback was rated highly by participants and also showed some effects on theoretical correlates of behavior change. Results provide initial evidence of the feasibility, acceptability, and brief efficacy of web-based genetic feedback for reducing alcohol-related health risks associated with ALDH2 genotype.

Keywords

Alcohol use Aldehyde dehydrogenase Intervention Personalized feedback Genetic feedback Internet 

References

  1. 1.
    Bell J. Predicting disease using genomics. Nature. 2004; 429: 453–456.CrossRefPubMedGoogle Scholar
  2. 2.
    Guttmacher AE, Collins FS. Realizing the promise of genomics in biomedical research. JAMA. 2005; 294: 1399–1402.CrossRefPubMedGoogle Scholar
  3. 3.
    The Wellcome Trust Case Control Consortium. Genome-wide association study of 14, 000 cases of seven common diseases and 3, 000 shared controls. Nature. 2007; 447: 661–678.CrossRefGoogle Scholar
  4. 4.
    Kraft P, Hunter DJ. Genetic risk prediction: Are we there yet? N Engl J Med. 2009; 360: 1701–1703.CrossRefPubMedGoogle Scholar
  5. 5.
    Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk to disease from genome-wide association studies. Genome Res. 2007; 17: 1520–1528.CrossRefPubMedGoogle Scholar
  6. 6.
    Wray NR, Goddard ME, Visscher PM. Prediction of individual genetic risk of complex disease. Curr Opin Genet Dev. 2008; 18: 257–263.CrossRefPubMedGoogle Scholar
  7. 7.
    Lango H, Palmer CNA, Morris AD, et al. Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk. Diabetes. 2008; 57: 3129–3135.CrossRefPubMedGoogle Scholar
  8. 8.
    Lyssenko V, Jonsson A, Almgren P, et al. Clinical risk factors, DNA variants, and the development of type 2 diabetes. N Engl J Med. 2008; 359: 2220–2232.CrossRefPubMedGoogle Scholar
  9. 9.
    van Hoek M, Dehghan A, Wittentan JCM, et al. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: A population-dased study. Diabetes. 2008; 57: 3122–3128.CrossRefPubMedGoogle Scholar
  10. 10.
    Henrikson NB, Bowen D, Burke W. Does genomic risk information motivate people to change their behavior? Genome Med. 2009; 1: 37.CrossRefPubMedGoogle Scholar
  11. 11.
    Lerman C, Croyle RT, Tercyak KP, Hamann H. Genetic testing: Psychological aspects and implications. J Consult Clin Psychol. 2002; 70: 784–797.CrossRefPubMedGoogle Scholar
  12. 12.
    Janssens AC, van Duijn CM. Genome-based prediction of common diseases: Methodological considerations for future research. Genome Med. 2009; 1: 20.CrossRefPubMedGoogle Scholar
  13. 13.
    Benhamou S, Lee WJ, Alexandrie AK, et al. Meta- and pooled analyses of the effects of glutathione S-transferase M1 polymorphisms and smoking on lung cancer risk. Carcinogenesis. 2002; 23: 1343–1350.CrossRefPubMedGoogle Scholar
  14. 14.
    Carlsten C, Sagoo GS, Frodsham AJ, Burke W, Higgins JPT. Glutathione S-transferase M1 (GSTM1) polymorphisms and lung cancer: A literature-based systematic HuGE review and meta-analysis. Am J Epidemiol. 2008; 167: 759–774.CrossRefPubMedGoogle Scholar
  15. 15.
    McBride CM, Bepler G, Lipkus IM, et al. Incorporating genetic susceptibility feedback into a smoking cessation program for African-American smokers with low income. Cancer Epidemiol Biomarkers Prev. 2002; 11: 521–528.PubMedGoogle Scholar
  16. 16.
    Sanderson SC, Humphries SE, Hubbart C, Hughes E, Jarvis MJ, Wardle J. Psychological and behavioural impact of genetic testing smokers for lung cancer risk: A phase II exploratory trial. J Health Psychol. 2008; 13: 481–494.CrossRefPubMedGoogle Scholar
  17. 17.
    Sanderson SC, O'Neill SC, White DB, et al. Responses to online GSTM1 genetic test results among smokers related to patients with lung cancer: A pilot study. Cancer Epidemiol Biomarkers Prev. 2009; 18: 1953–1961.CrossRefPubMedGoogle Scholar
  18. 18.
    Lerman C, Gold K, Audrain J, et al. Incorporating biomarkers of exposure and genetic susceptibility into smoking cessation treatment: Effects on smoking-related cognitions, emotions, and behavior change. Health Psychol. 1997; 16: 87–99.CrossRefPubMedGoogle Scholar
  19. 19.
    Audrain J, Boyd NR, Roth J, Main D, Caporaso NE, Lerman C. Genetic susceptibility testing in smoking-cessation treatment: One-year outcomes of a randomized trial. Addict Behav. 1997; 22: 741–751.CrossRefPubMedGoogle Scholar
  20. 20.
    Ito H, Matsuo K, Wakai K, et al. An intervention study of smoking cessation with feedback on genetic cancer susceptibility in Japan. Prev Med. 2006; 42: 102–108.CrossRefPubMedGoogle Scholar
  21. 21.
    Carpenter MJ, Strange C, Jones Y, et al. Does genetic testing result in behavioral health change? Changes in smoking behavior following testing for alpha-1 antitrypsin deficiency. Ann Behav Med. 2007; 33: 22–28.CrossRefPubMedGoogle Scholar
  22. 22.
    Rehm J, Mathers C, Popova S, Thavorncharoensap M, Teerawattananon Y, Patra J. Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders. Lancet. 2009; 373: 2223–2233.CrossRefPubMedGoogle Scholar
  23. 23.
    Baan R, Straif K, Grosse Y, et al. Carcinogenicity of alcoholic beverages. Lancet Oncol. 2007; 8: 292–293.CrossRefPubMedGoogle Scholar
  24. 24.
    Lachenmeier DW, Kanteres F, Rehm J. Carcinogenicity of acetaldehyde in alcoholic beverages: Risk assessment outside ethanol metabolism. Addiction. 2009; 104: 533–550.CrossRefPubMedGoogle Scholar
  25. 25.
    Edenberg HJ. The genetics of alcohol metabolism—role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Res Health. 2007; 30: 5–13.PubMedGoogle Scholar
  26. 26.
    Chen YJ, Chen C, Wu DC, et al. Interactive effects of lifetime alcohol consumption and alcohol and aldehyde dehydrogenase polymorphisms on esophageal cancer risks. Int J Cancer. 2006; 119: 2827–2831.CrossRefPubMedGoogle Scholar
  27. 27.
    Hiyama T, Yoshihara M, Tanaka S, Chayama K. Genetic polymorphisms and esophageal cancer risk. Int J Cancer. 2007; 121: 1643–1658.CrossRefPubMedGoogle Scholar
  28. 28.
    Peng GS, Yin SJ. Effect of the allelic variants of aldehyde dehydrogenase ALDH2*2 and alcohol dehydrogenase ADH1B*2 on blood acetaldehyde concentrations. Hum Genomics. 2009; 3: 121–127.PubMedGoogle Scholar
  29. 29.
    Luczak SE, Glatt SJ, Wall TL. Meta-analyses of ALDH2 and ADH1B with alcohol dependence in Asians. Psychol Bull. 2006; 132: 607–621.CrossRefPubMedGoogle Scholar
  30. 30.
    Yang CX, Matsuo K, Ito H, et al. Esophageal cancer risk by ALDH2 and ADH2 polymorphisms and alcohol consumption: Exploration of gene–environment and gene–gene interactions. Asian Pac J Cancer Prev. 2005; 6: 256–262.PubMedGoogle Scholar
  31. 31.
    Yokoyama A, Muramatsu T, Ohmori T, et al. Alcohol-related cancers and aldehyde dehydrogenase-2 in Japanese alcoholics. Carcinogenesis. 1998; 19: 1383–1387.CrossRefPubMedGoogle Scholar
  32. 32.
    Yokoyama A, Muramatsu T, Omori T, et al. Alcohol and aldehyde dehydrogenase gene polymorphisms influence susceptibility to esophageal cancer in Japanese alcoholics. Alcohol Clin Exp Res. 1999; 23: 1705–1710.PubMedGoogle Scholar
  33. 33.
    Brooks PJ, Enoch MA, Goldman D, Li TK, Yokoyama A. The alcohol flushing response: An unrecognized risk factor for esophageal cancer from alcohol consumption. PLoS Med. 2009; 6(3): e1000050.CrossRefGoogle Scholar
  34. 34.
    Yokoyama T, Yokoyama A, Kato H, et al. Alcohol flushing, alcohol and aldehyde dehydrogenase genotypes, and risk for esophageal squamous cell carcinoma in Japanese men. Cancer Epidemiol Biomarkers Prev. 2003; 12: 1227–1233.PubMedGoogle Scholar
  35. 35.
    Lewis SJ, Smith GD. Alcohol, ALDH2, and esophageal cancer: A meta-analysis which illustrates the potentials and limitations of a Mendelian randomization approach. Cancer Epidemiol Biomarkers Prev. 2005; 14: 1967–1971.CrossRefPubMedGoogle Scholar
  36. 36.
    Collins SE, Carey KB, Sliwinski MJ. Mailed personalized normative feedback as a brief intervention for at-risk college drinkers. J Stud Alcohol. 2002; 63: 559–567.PubMedGoogle Scholar
  37. 37.
    Larimer ME, Lee CM, Kilmer JR, et al. Personalized mailed feedback for college drinking prevention: A randomized clinical trial. J Consult Clin Psychol. 2007; 75: 285–293.CrossRefPubMedGoogle Scholar
  38. 38.
    Miller WR, Rollnick S. Motivational interviewing: Preparing people for change. New York: Guilford; 2002.Google Scholar
  39. 39.
    Lewis MA, Neighbors C. Social norms approaches using descriptive drinking norms education: A review of the research on personalized normative feedback. J Am Coll Health. 2006; 54: 213–218.CrossRefPubMedGoogle Scholar
  40. 40.
    Cunningham JA, Wild TC, Cordingley J, van Mierlo T, Humphreys K. A randomized controlled trial of an internet-based intervention for alcohol abusers. Addiction. 2009; 104: 2023–2032.CrossRefPubMedGoogle Scholar
  41. 41.
    Neighbors C, Lee CM, Lewis MA, Fossos N, Walter T. Internet-based personalized feedback to reduce 21st-birthday drinking: A randomized controlled trial of an event-specific prevention intervention. J Consult Clin Psychol. 2009; 77: 51–63.CrossRefPubMedGoogle Scholar
  42. 42.
    Hendershot CS, Collins SE, George WH, et al. Associations of ALDH2 and ADH1B genotypes with alcohol-related phenotypes in Asian young adults. Alcohol Clin Exp Res. 2009; 33: 839–847.CrossRefPubMedGoogle Scholar
  43. 43.
    Wright AJ, French DP, Weinman J, Marteau TM. Can genetic risk information enhance motivation for smoking cessation? An analogue study. Health Psychol. 2006; 25: 740–752.CrossRefPubMedGoogle Scholar
  44. 44.
    Gooding HC, Organista K, Burack J, Biesecker BB. Genetic susceptibility testing from a stress and coping perspective. Soc Sci Med. 2006; 62: 1880–1890.CrossRefPubMedGoogle Scholar
  45. 45.
    Jones BT, Corbin W, Fromme K. A review of expectancy theory and alcohol consumption. Addiction. 2001; 96: 57–72.CrossRefPubMedGoogle Scholar
  46. 46.
    Collins RL, Parks GA, Marlatt GA. Social determinants of alcohol-consumption: The effects of social-interaction and model status on the self-administration of alcohol. J Consult Clin Psychol. 1985; 53: 189–200.CrossRefPubMedGoogle Scholar
  47. 47.
    LaBrie JW, Quinlan T, Schiffman JE, Earleywine ME. Performance of alcohol and safer sex change rulers compared with readiness to change questionnaires. Psychol Addict Behav. 2005; 19: 112–115.CrossRefPubMedGoogle Scholar
  48. 48.
    Fromme K, Stroot EA, Kaplan D. Comprehensive effects of alcohol: Development and psychometric assessment of a new expectancy questionnaire. Psychol Assess. 1993; 5: 19–26.CrossRefGoogle Scholar
  49. 49.
    Truett GE, Heeger P, Mynatt RL, Truett AA, Walker JA, Warman ML. Preparation of PCR-quality mouse genomic DNA with hot sodium hydroxide and tris (HotSHOT). Biotechniques. 2000; 29: 52.PubMedGoogle Scholar
  50. 50.
    Newcombe RG. Confidence intervals for an effect size measure based on the Mann–Whitney statistic. Part 1: General issues and tail-area-based methods. Stat Med. 2005; 25: 543–557.CrossRefGoogle Scholar
  51. 51.
    Newcombe RG. Confidence intervals for an effect size measure based on the Mann–Whitney statistic. Part 2: Asymptotic methods and evaluation. Stat Med. 2005; 25: 559–573.CrossRefGoogle Scholar
  52. 52.
    Marteau TM, Weinman J. Self-regulation and the behavioural response to DNA risk information: A theoretical analysis and framework for future research. Soc Sci Med. 2006; 62: 1360–1368.CrossRefPubMedGoogle Scholar
  53. 53.
    Cameron LD, Sherman KA, Marteau TM, Brown PM. Impact of genetic risk information and type of disease on perceived risk, anticipated affect, and expected consequences of genetic tests. Health Psychol. 2009; 28: 307–316.CrossRefPubMedGoogle Scholar
  54. 54.
    McBride CM, Alford SH, Reid RJ, Larson EB, Baxevanis AD, Brody LC. Characteristics of users of online personalized genomic risk assessments: Implications for physician–patient interactions. Genet Med. 2009; 11: 582–587.CrossRefPubMedGoogle Scholar
  55. 55.
    Chao S, Roberts JS, Marteau TM, Silliman R, Cupples LA, Green RC. Health behavior changes after genetic risk assessment for Alzheimer disease: The REVEAL Study. Alzheimer Dis Assoc Disord. 2008; 22: 94–97.CrossRefPubMedGoogle Scholar

Copyright information

© The Society of Behavioral Medicine 2010

Authors and Affiliations

  • Christian S. Hendershot
    • 1
    • 2
  • Jacqueline M. Otto
    • 3
  • Susan E. Collins
    • 4
  • Tiebing Liang
    • 5
  • Tamara L. Wall
    • 6
    • 7
    • 8
  1. 1.The Mind Research NetworkAlbuquerqueUSA
  2. 2.Center on Alcoholism, Substance Abuse and Addictions (CASAA)University of New MexicoAlbuquerqueUSA
  3. 3.Department of PsychologyUniversity of WashingtonSeattleUSA
  4. 4.Department of Psychiatry and Behavioral SciencesUniversity of WashingtonSeattleUSA
  5. 5.Indiana University School of MedicineIndianapolisUSA
  6. 6.Department of PsychiatryUniversity of California, San DiegoLa JollaUSA
  7. 7.Psychology ServiceVeterans Affairs San Diego Healthcare SystemSan DiegoUSA
  8. 8.Veterans Medical Research FoundationSan DiegoUSA

Personalised recommendations