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Lai D, Zhang M, Abreu M, Schwantes-An TH, Chan G, Dick DM, Kamarajan C, Kuang W, Nurnberger JI, Plawecki MH, Rice J, Schuckit M, Porjesz B, Liu Y, Foroud T. Alcohol Use Disorder Polygenic Score Compared With Family History and ADH1B. JAMA Netw Open 2024; 7:e2452705. [PMID: 39786404 PMCID: PMC11686414 DOI: 10.1001/jamanetworkopen.2024.52705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2024] [Accepted: 10/31/2024] [Indexed: 01/12/2025] Open
Abstract
Importance Identification of individuals at high risk of alcohol use disorder (AUD) and subsequent application of prevention and intervention programs has been reported to decrease the incidence of AUD. The polygenic score (PGS), which measures an individual's genetic liability to a disease, can potentially be used to evaluate AUD risk. Objective To assess the estimability and generalizability of the PGS, compared with family history and ADH1B, in evaluating the risk of AUD among populations of European ancestry. Design, Setting, and Participants This genetic association study was conducted between October 1, 2023, and May 21, 2024. A 2-stage design was used. First, the pruning and thresholding method was used to calculate PGSs in the screening stage. Second, the estimability and generalizability of the best PGS was determined using 2 independent samples in the testing stage. Three cohorts ascertained to study AUD were used in the screening stage: the Collaborative Study on the Genetics of Alcoholism (COGA), the Study of Addiction: Genetics and Environment (SAGE), and the Australian Twin-Family Study of Alcohol Use Disorder (OZALC). The All of Us Research Program (AOU), which comprises participants with diverse backgrounds and conditions, and the Indiana Biobank (IB), consisting of Indiana University Health system patients, were used to test the best PGS. For the COGA, SAGE, and OZALC cohorts, cases with AUD were determined using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) or Fifth Edition (DSM-5) criteria; controls did not meet any criteria or did not have any other substance use disorders. For the AOU and IB cohorts, cases with AUD were identified using International Classification of Diseases, Ninth Revision (ICD-9) or International Classification of Diseases, Tenth Revision (ICD-10) codes; controls were aged 21 years or older and did not have AUD. Exposure The PGS was calculated using single-nucleotide variants with concordant effects in 3 large-scale genome-wide association studies of AUD-related phenotypes. Main Outcomes and Measures The main outcome was AUD determined with DSM-IV or DSM-5 criteria and ICD-9 or ICD-10 codes. Generalized linear mixed models and logistic regression models were used to analyze related and unrelated samples, respectively. Results The COGA, SAGE, and OZALC cohorts included a total of 8799 samples (6323 cases and 2476 controls; 50.6% were men). The AOU cohort had a total of 116 064 samples (5660 cases and 110 404 controls; 60.4% were women). The IB cohort had 6373 samples (936 cases and 5437 controls; 54.9% were women). The 5% of samples with the highest PGS in the AOU and IB cohorts were approximately 2 times more likely to develop AUD (odds ratio [OR], 1.96 [95% CI, 1.78-2.16]; P = 4.10 × 10-43; and OR, 2.07 [95% CI, 1.59-2.71]; P = 9.15 × 10-8, respectively) compared with the remaining 95% of samples; these ORs were comparable to family history of AUD. For the 5% of samples with the lowest PGS in the AOU and IB cohorts, the risk of AUD development was approximately half (OR, 0.53 [95% CI, 0.45-0.62]; P = 6.98 × 10-15; and OR, 0.57 [95% CI, 0.39-0.84]; P = 4.88 × 10-3) compared with the remaining 95% of samples; these ORs were comparable to the protective effect of ADH1B. PGS had similar estimabilities in male and female individuals. Conclusions and Relevance In this study of AUD risk among populations of European ancestry, PGSs were calculated using concordant single-nucleotide variants and the best PGS was tested in targeted datasets. The findings suggest that the PGS may potentially be used to evaluate AUD risk. More datasets with similar AUD prevalence as in general populations are needed to further test the generalizability of PGS.
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Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Michael Zhang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Marco Abreu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Tae-Hwi Schwantes-An
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington
- Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City
| | - Danielle M. Dick
- Department of Psychiatry, Robert Wood Johnson Medical School, Rutgers University, Piscataway, New Jersey
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, SUNY Downstate Health Science University, New York, New York
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, SUNY Downstate Health Science University, New York, New York
| | - John I. Nurnberger
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
| | - Martin H. Plawecki
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis
| | - John Rice
- Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri
| | - Marc Schuckit
- Department of Psychiatry, University of California San Diego Medical School, San Diego
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, SUNY Downstate Health Science University, New York, New York
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis
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Conlin WE, Hoffman M, Steinley D, Vergés A, Sher KJ. Predictors of symptom course in alcohol use disorder. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2023; 47:2288-2300. [PMID: 38151783 PMCID: PMC10935605 DOI: 10.1111/acer.15201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 09/14/2023] [Accepted: 09/21/2023] [Indexed: 12/29/2023]
Abstract
BACKGROUND Symptoms often play an important role in the scientific inquiry of psychological disorders and have been theorized to play a functional role in the disorders themselves. However, little is known about the course of specific symptoms and individual differences in course. Understanding the course of specific symptoms and factors influencing symptom course can inform psychological theory and future research on course and treatment. METHODS The current study examined alcohol use disorder (AUD) criteria to explore how etiologically relevant covariates differentially affected the course of individual criteria. The study examined 34,653 participants from Wave 1 (2001-2002) and Wave 2 (2003-2004) of the National Epidemiological Survey on Alcohol and Related Conditions (NESARC), to analyze the extent to which AUD symptom course is predicted by alcohol consumption patterns, family history of alcoholism, the presence of internalizing and externalizing disorders, and race. RESULTS The course of all AUD criteria was significantly influenced by these predictors, with the magnitude of the influence varying across different criteria and different aspects of the course (i.e., onset, persistence, recurrence). The strength of the relationship is partially related to the theoretical proximity of a given covariate to AUD symptomatology, with heavy drinking being the strongest and family history of AUD being the weakest. The course of all criteria was strongly associated with the prevalence of the criterion in the overall sample. CONCLUSIONS The course of AUD criteria is heterogeneous, appearing to be influenced by conceptually proximal predictors, the prevalence of the criterion, and perhaps an underlying common factor. Diagnostic accuracy may be improved by including a criterion related to alcohol consumption. Future work should include exploring the interchangeability of criteria and alternative operationalization of them.
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Affiliation(s)
- William E. Conlin
- Department of Psychological Sciences, University of Missouri, Missouri, Columbia, USA
| | - Michaela Hoffman
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, South Carolina, Charleston, USA
| | - Douglas Steinley
- Department of Psychological Sciences, University of Missouri, Missouri, Columbia, USA
| | - Alvaro Vergés
- Universidad de los Andes, Escuela de Psicología, Las Condes, Chile
- Núcleo Milenio para Mejorar la Salud Mental de Adolescentes y Jóvenes, Michigan, Imhay, USA
| | - Kenneth J. Sher
- Department of Psychological Sciences, University of Missouri, Missouri, Columbia, USA
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Lai D, Johnson EC, Colbert S, Pandey G, Chan G, Bauer L, Francis MW, Hesselbrock V, Kamarajan C, Kramer J, Kuang W, Kuo S, Kuperman S, Liu Y, McCutcheon V, Pang Z, Plawecki MH, Schuckit M, Tischfield J, Wetherill L, Zang Y, Edenberg HJ, Porjesz B, Agrawal A, Foroud T. Evaluating risk for alcohol use disorder: Polygenic risk scores and family history. Alcohol Clin Exp Res 2022; 46:374-383. [PMID: 35267208 PMCID: PMC8928056 DOI: 10.1111/acer.14772] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/13/2021] [Accepted: 01/05/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Early identification of individuals at high risk for alcohol use disorder (AUD) coupled with prompt interventions could reduce the incidence of AUD. In this study, we investigated whether Polygenic Risk Scores (PRS) can be used to evaluate the risk for AUD and AUD severity (as measured by the number of DSM-5 AUD diagnostic criteria met) and compared their performance with a measure of family history of AUD. METHODS We studied individuals of European ancestry from the Collaborative Study on the Genetics of Alcoholism (COGA). DSM-5 diagnostic criteria were available for 7203 individuals, of whom 3451 met criteria for DSM-IV alcohol dependence or DSM-5 AUD and 1616 were alcohol-exposed controls aged ≥21 years with no history of AUD or drug dependence. Further, 4842 individuals had a positive first-degree family history of AUD (FH+), 2722 had an unknown family history (FH?), and 336 had a negative family history (FH-). PRS were derived from a meta-analysis of a genome-wide association study of AUD from the Million Veteran Program and scores from the problem subscale of the Alcohol Use Disorders Identification Test in the UK Biobank. We used mixed models to test the association between PRS and risk for AUD and AUD severity. RESULTS AUD cases had higher PRS than controls with PRS increasing as the number of DSM-5 diagnostic criteria increased (p-values ≤ 1.85E-05 ) in the full COGA sample, the FH+ subsample, and the FH? subsample. Individuals in the top decile of PRS had odds ratios (OR) for developing AUD of 1.96 (95% CI: 1.54 to 2.51, p-value = 7.57E-08 ) and 1.86 (95% CI: 1.35 to 2.56, p-value = 1.32E-04 ) in the full sample and the FH+ subsample, respectively. These values are comparable to previously reported ORs for a first-degree family history (1.91 to 2.38) estimated from national surveys. PRS were also significantly associated with the DSM-5 AUD diagnostic criterion count in the full sample, the FH+ subsample, and the FH? subsample (p-values ≤6.7E-11 ). PRS remained significantly associated with AUD and AUD severity after accounting for a family history of AUD (p-values ≤6.8E-10 ). CONCLUSIONS Both PRS and family history were associated with AUD and AUD severity, indicating that these risk measures assess distinct aspects of liability to AUD traits.
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Affiliation(s)
- Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Emma C. Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Sarah Colbert
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Gayathri Pandey
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY
| | - Grace Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT
- Department of Psychiatry, University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, IA
| | - Lance Bauer
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT
| | - Meredith W. Francis
- The Brown School of Social Work, Washington University School of Medicine, St. Louis, MO
| | - Victor Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT
| | - Chella Kamarajan
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY
| | - John Kramer
- Department of Psychiatry, University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, IA
| | - Weipeng Kuang
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY
| | - Sally Kuo
- Department of Psychology, Virginia Commonwealth University, Richmond, VA
| | - Samuel Kuperman
- Department of Psychiatry, University of Iowa Roy J and Lucille A Carver College of Medicine, Iowa City, IA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Vivia McCutcheon
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Zhiping Pang
- Department of Neuroscience and Cell Biology, Child Health Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ
| | - Martin H. Plawecki
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN
| | - Marc Schuckit
- Department of Psychiatry, University of California, San Diego Medical School, San Diego, CA
| | - Jay Tischfield
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
| | - Yong Zang
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN
| | - Howard J. Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN
| | - Bernice Porjesz
- Henri Begleiter Neurodynamics Lab, Department of Psychiatry, State University of New York, Downstate Medical Center, Brooklyn, NY
| | - Arpana Agrawal
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN
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Moska C, Goudriaan AE, Blanken P, van de Mheen D, Spijkerman R, Schellekens A, de Jonge J, Bary F, Vollebergh W, Hendriks V. Youth in transition: Study protocol of a prospective cohort study into the long-term course of addiction, mental health problems and social functioning in youth entering addiction treatment. BMC Psychiatry 2021; 21:605. [PMID: 34863131 PMCID: PMC8642918 DOI: 10.1186/s12888-021-03520-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 10/04/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Substance use disorders (SUDs) are prevalent in the general population, tend to follow a chronic course, are associated with many individual and social problems, and often have their onset in adolescence. However, the knowledge base from prospective population surveys and treatment-outcome studies on the course of SUD in adolescents is limited at best. The present study aims to fill this gap and focuses on a subgroup that is particularly at risk for chronicity: adolescents in addiction treatment. We will investigate the rate of persistent SUD and its predictors longitudinally from adolescence to young adulthood among youth with DSM-5 SUD from the start of their addiction treatment to 2 and 4 years following treatment-entry. In addition to SUD, we will investigate the course of comorbid mental disorders, social functioning, and quality of life and their association with SUD over time. METHODS/DESIGN In a naturalistic, multi-center prospective cohort design, we will include youths (n = 420), who consecutively enter addiction treatment at ten participating organizations in the Netherlands. Inclusion is prestratified by treatment organization, to ensure a nationally representative sample. Eligible youths are 16 to 22 years old and seek help for a primary DSM-5 cannabis, alcohol, cocaine or amphetamine use disorder. Assessments focus on lifetime and current substance use and SUD, non-SUD mental disorders, family history, life events, social functioning, treatment history, quality of life, chronic stress indicators (hair cortisol) and neuropsychological tests (computerized executive function tasks) and are conducted at baseline, end of treatment, and 2 and 4 years post-baseline. Baseline data and treatment data (type, intensity, duration) will be used to predict outcome - persistence of or desistance from SUD. DISCUSSION There are remarkably few prospective studies worldwide that investigated the course of SUD in adolescents in addiction treatment for longer than 1 year. We are confident that the Youth in Transition study will further our understanding of determinants and consequences of persistent SUD among high-risk adolescents during the critical transition from adolescence to young adulthood. TRIAL REGISTRATION The Netherlands National Trial Register Trial NL7928 . Date of registration January 17, 2019.
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Affiliation(s)
- Christina Moska
- grid.491465.bParnassia Addiction Research Centre (PARC, Brijder Addiction Treatment), Zoutkeetsingel 40, 2512 HN The Hague, the Netherlands ,grid.10419.3d0000000089452978Department of Child and Adolescent Psychiatry, LUMC Curium, Leiden University Medical Center, Leiden, the Netherlands
| | - Anna E. Goudriaan
- grid.7177.60000000084992262Department of Psychiatry, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands ,grid.491159.10000 0004 0493 7618Amsterdam Institute for Addiction Research, Arkin Mental Health Care, Amsterdam, the Netherlands
| | - Peter Blanken
- grid.491465.bParnassia Addiction Research Centre (PARC, Brijder Addiction Treatment), Zoutkeetsingel 40, 2512 HN The Hague, the Netherlands
| | - Dike van de Mheen
- grid.12295.3d0000 0001 0943 3265Department of Tranzo Scientific Center for Care and Wellbeing, Tilburg University, Tilburg, the Netherlands
| | - Renske Spijkerman
- grid.491465.bParnassia Addiction Research Centre (PARC, Brijder Addiction Treatment), Zoutkeetsingel 40, 2512 HN The Hague, the Netherlands
| | - Arnt Schellekens
- grid.10417.330000 0004 0444 9382Department of Psychiatry, Radboud University Medical Centre, Donders Institute for Brain, Cognition, and Behavior, Nijmegen, the Netherlands ,grid.491352.8Nijmegen Institute for Science Practitioners in Addiction (NISPA), Nijmegen, the Netherlands
| | - Jannet de Jonge
- grid.431204.00000 0001 0685 7679Research Group Urban Vitality, Faculty of Health, Amsterdam University of Applied Science, Amsterdam, the Netherlands
| | - Floris Bary
- Netherlands Network of Client Councils in Addiction Care ‘Het Zwarte Gat’, Hollands Kroon, The Netherlands
| | - Wilma Vollebergh
- grid.5477.10000000120346234Department of Interdisciplinary Social Science, Utrecht University, Utrecht, the Netherlands
| | - Vincent Hendriks
- grid.491465.bParnassia Addiction Research Centre (PARC, Brijder Addiction Treatment), Zoutkeetsingel 40, 2512 HN The Hague, the Netherlands ,grid.10419.3d0000000089452978Department of Child and Adolescent Psychiatry, LUMC Curium, Leiden University Medical Center, Leiden, the Netherlands
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Schuckit MA, Smith TL, Clarke DF. Cross-sectional and prospective associations of drinking characteristics with scores from the Self-Report of the Effects of Alcohol questionnaire and findings from alcohol challenges. Alcohol Clin Exp Res 2021; 45:2282-2293. [PMID: 34523737 PMCID: PMC8642305 DOI: 10.1111/acer.14710] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 08/13/2021] [Accepted: 09/03/2021] [Indexed: 01/24/2023]
Abstract
BACKGROUND Data from 2 generations of participants in the San Diego Prospective Study (SDPS) were used to compare cross-sectional and prospective relationships of 5 measures of the low level of response (low LR) to alcohol to 2 key alcohol-related outcomes. METHODS The analyses used data from 373 SDPS male probands and 158 male and female offspring of these individuals to evaluate relationships of 5 LR measures to the prior 5-year maximum drinks per occasion and the number of 11 DSM-IV alcohol use disorder (AUD) criteria experienced. Probands' LR measures included responses to alcohol challenges administered 15 years previously, and ratings for both generations included measures of the number of standard drinks during four periods: the first five times of drinking (SRE-5), the prior three drinking months (SRE-3), the period of heaviest drinking (SRE-H), and a total average across all time frames (SRE-T). Analyses included zero-order correlations, correlations using covariates, and hierarchical multiple regression analyses. RESULTS All 5 LR measures were correlated with aspects of maximum drinks and the number of AUD criteria, but the most robust results were seen for SRE-3 and maximum drinks. Correlations were less consistent for SRE-5, a measure more closely related to outcomes in the offspring. Hierarchical regression analyses supported most of these conclusions and showed that alcohol challenge-based LRs added significant information regarding maximum drinks even when evaluated with SRE values. The close correlation between SRE-H and SRE-T argues against the need for studies to include both measures. The patterns of results were similar irrespective of whether covariates were included. CONCLUSIONS There were significant correlations of maximum drinks and the number of AUD criteria with findings from prior alcohol challenges and all SRE scores. Challenges and SRE reports are related but not identical LR measures. All SRE scores, including SRE-5, offered useful information regarding subsequent drinking behavior.
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Affiliation(s)
- Marc A Schuckit
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Tom L Smith
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - Dennis F Clarke
- Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
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Schuckit MA, Clarke DF, Smith TL, Mendoza LA. Characteristics associated with denial of problem drinking among two generations of individuals with alcohol use disorders. Drug Alcohol Depend 2020; 217:108274. [PMID: 32956977 PMCID: PMC7736262 DOI: 10.1016/j.drugalcdep.2020.108274] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Denial of an overarching alcohol problem despite endorsement of specific alcohol-related difficulties may be central to development and continuation of alcohol use disorders (AUDs). However, there is limited information about which characteristics of drinkers and which drinking problems relate most closely to that denial. METHODS Using data from two generations of the San Diego Prospective Study (SDPS), we compared AUD subjects who considered themselves non-problematic drinkers (Group 1) with those with AUDs who acknowledged a general alcohol problem (Group 2). Comparisons included demography, alcohol-related patterns and problems, drug use, as well as impulsivity and sensation seeking. Variables were first evaluated as univariate characteristics after which significant group differences were entered in logistic regression analyses. RESULTS Sixty-seven percent of 94 AUD probands and 82 % of 176 AUD offspring reported themselves as light or moderate social drinkers despite averages of up to 12 maximum drinks per occasion and four DSM problems. Regression analyses indicated deniers evidenced less intense alcohol and drug-related problems and identified DSM-IV criterion items that they were most likely to deny. CONCLUSIONS A large majority of two generations of SDPS participants whose interviews indicated a current AUD did not characterize themselves as problem drinkers. Despite drinking amounts that far exceeded healthy limits and admitting to important life problems with alcohol, these individuals give misleading answers regarding their condition when asked general questions about drinking by health care deliverers. The authors offer suggestions regarding how to identify those drinkers in need of advice regarding dangers of their behaviors.
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