ArticleAddiction (Abingdon, England)2018
AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations.
Article in Addiction (Abingdon, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.
- Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review.Reviews in endocrine & metabolic disorders · 2022Pooled it
- Facilitating Screening and Brief Interventions in Primary Care: A Systematic Review and Meta-Analysis of the AUDIT as an Indicator of Alcohol Use Disorders.Alcoholism, clinical and experimental research · 2019Pooled it
- First-Recorded Alcohol Use Disorder Diagnosis as an Ascertainment Outcome: Implications for GLP-1 Target Trial Emulations.Pharmacoepidemiology and drug safety · 2026Article
- Evidence for sex differences in the impact of cytochrome P450 genotypes on early subjective effects of cannabis.Addictive behaviors · 2024Article
- Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program.Translational psychiatry · 2023Article
- Association Between Alcohol Use Disorder and Receipt of Direct-Acting Antiviral Hepatitis C Virus Treatment.JAMA network open · 2022Article
- Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2022Article
- A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation.Nature genetics · 2022Article
- Perspective on Beyond Statistical Significance: Finding Meaningful Effects.Complex psychiatry · 2021Article
- Remote delivery of alcohol and/or substance misuse interventions for adults: A systematic review protocol.PloS one · 2021Article
- Whole Genome Interpretation for a Family of Five.Frontiers in genetics · 2021Article
- The OATH Syndemic: opioids and other substances, aging, alcohol, tobacco, and HIV.Current opinion in HIV and AIDS · 2020Review
- Differentiating Types of Self-Reported Alcohol Abstinence.AIDS and behavior · 2020Article
- Survival Benefit of Liver Transplantation for Hepatocellular Carcinoma.Transplantation · 2020Article
- Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program.PloS one · 2020Article
- Using DNA methylation to validate an electronic medical record phenotype for smoking.Addiction biology · 2019Observational
- Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations.Nature communications · 2019Article
- Genetics of Alcoholism.Current psychiatry reports · 2019Review
Corrections and comments
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Authors and funding
15 authors at 5 institutions in 1 country.
Funding
Abstract
BACKGROUND AND
aimsLongitudinal electronic health record (EHR) data offer a large-scale, untapped source of phenotypical information on harmful alcohol use. Using established, alcohol-associated variants in the gene that encodes the enzyme alcohol dehydrogenase 1B (ADH1B) as criterion standards, we compared the individual and combined validity of three longitudinal EHR-based phenotypes of harmful alcohol use: Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) trajectories; mean age-adjusted AUDIT-C; and diagnoses of alcohol use disorder (AUD).
designWith longitudinal EHR data from the Million Veteran Program (MVP) linked to genetic data, we used two population-specific polymorphisms in ADH1B that are associated strongly with AUD in African Americans (AAs) and European Americans (EAs): rs2066702 (Arg369Cys, AAs) and rs1229984 (Arg48His, EAs) as criterion measures.
settingUnited States Department of Veterans Affairs Healthcare System.
participantsA total of 167 721 veterans (57 677 AAs and 110 044 EAs; 92% male, mean age = 63 years) took part in this study. Data were collected from 1 October 2007 to 1 May 2017. MEASUREMENTS: Using all AUDIT-C scores and AUD diagnostic codes recorded in the EHR, we calculated age-adjusted mean AUDIT-C values, longitudinal statistical trajectories of AUDIT-C scores and ICD-9/10 diagnostic groupings for AUD.
findingsA total of 19 793 AAs (34.3%) had one or two minor alleles at rs2066702 [minor allele frequency (MAF) = 0.190] and 6933 EAs (6.3%) had one or two minor alleles at rs1229984 (MAF = 0.032). In both populations, trajectories and age-adjusted mean AUDIT-C were correlated (r = 0.90) but, when considered separately, highest score (8+ versus 0) of age-adjusted mean AUDIT-C demonstrated a stronger association with the ADH1B variants [adjusted odds ratio (aOR) 0.54 in AAs and 0.37 in AAs] than did the highest trajectory (aOR 0.71 in AAs and 0.53 in EAs); combining AUDIT-C metrics did not improve discrimination. When age-adjusted mean AUDIT-C score and AUD diagnoses were considered together, age-adjusted mean AUDIT-C (8+ versus 0) was associated with lower odds of having the ADH1B minor allele than were AUD diagnostic codes: aOR = 0.59 versus 0.86 in AAs and 0.48 versus 0.68 in EAs. These independent associations combine to yield an even lower aOR of 0.51 for AAs and 0.33 for EAs.
conclusionsThe age-adjusted mean AUDIT-C score is associated more strongly with genetic polymorphisms of known risk for alcohol use disorder than are longitudinal trajectories of AUDIT-C or AUD diagnostic codes. AUD diagnostic codes modestly enhance this association.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.