AUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with <i>ADH1B</i> polymorphisms in two US populations

Justice, Amy C.; Smith, Ray; Tate, Janet P.; McGinnis, Kathleen A.; Becker, William C.; Lee, Kuang‐Yao; Lynch, Kevin G.; Sun, Ning; Concato, John; Fiellin, David A.; Zhao, Hongyu; Gelernter, Joel; Kranzler, Henry R.

doi:10.1111/add.14374

Cited by 24 publications

(25 citation statements)

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“…In the AA part of this sample (n=1,503), the AUDIT-C score was highly significantly associated with rs2066702, a missense (Arg369Cys) polymorphism of ADH1B , the minor allele of which is common in that population and has been associated with alcohol dependence 25 . We also examined AUDIT-C scores in 167,721 MVP participants (57,677 AAs and 110,044 EAs) 24 , comparing the association of AUDIT-C scores and AUD diagnoses with the frequency of the minor allele of rs2066702 in AAs and rs1229984 (Arg48His) in EAs. Both polymorphisms exert large effects on alcohol metabolism 39 and are among the genetic variants associated most consistently with alcohol-related traits in both AAs and EAs 8,12,18 .…”

Section: Methodsmentioning

confidence: 99%

“…As described previously 24 , we calculated the age-adjusted mean AUDIT-C value for each participant using age 50 as the reference point and down-weighting scores for individuals younger than 50 and up-weighting scores for individuals older than 50. There were 272,842 participants in the AUDIT-C analyses.…”

Section: Methodsmentioning

confidence: 99%

“…Such discoveries improve our understanding of the etiology and pathophysiology of complex diseases and their prevention and treatment. To that end, we used a common data source—longitudinal repeated measures of alcohol-related traits from the national Veterans Health Administration (VHA) EHR—to obtain the mean, age-adjusted AUDIT-C score and International Classification of Diseases (ICD) alcohol-related diagnosis codes over more than 11 years of care 24 . We then conducted a GWAS of each trait followed by downstream analysis of the findings in which we constructed polygenic risk scores (PRS) for both traits and showed that they were associated with alcohol-related disorders in two independent samples.…”

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confidence: 99%

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Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

Kranzler

Zhou

Kember

et al. 2019

Preprint

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SummaryAlthough alcohol consumption level and alcohol use disorder (AUD) diagnosis are both moderately heritable, their genetic risks and overlap are not well understood. We conducted genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores (reflecting alcohol consumption) and AUD diagnoses from electronic health records (EHRs) in a single, large multi-ancestry Million Veteran Program sample. Meta-analysis across population groups (N = 274,424) identified 18 genome-wide significant loci, 5 of which were associated with both traits and 13 with either AUDIT-C (N = 8) or AUD (N = 5). A significant genetic correlation between the traits reflects this overlap. However, downstream analyses revealed biologically meaningful points of divergence. Cell-type group partitioning heritability enrichment analyses indicated that central nervous system was the most significant cell type for AUDIT-C and the only significant cell type for AUD. Polygenic risk scores (PRS) for both traits were associated with alcohol-related disorders in two independent samples. Genetic correlations for 188 non-alcohol-related traits were significantly different for the two traits, as were the phenotypes associated with the traits’ polygenic risk scores. We conclude that EHR-derived, longitudinal, repeated measures of alcohol consumption level and AUD diagnosis can facilitate genetic discovery and help to elucidate the relationship between drinking level and AUD risk. Finally, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

Kranzler

Zhou

Kember

et al. 2019

Preprint

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“…; Justice et al . ), summary measures of repeated self‐reported smoking also demonstrate stronger associations than single, cross‐sectional reports that are often employed as phenotypes in large‐scale genetic studies (Sanchez‐Roige et al . ).…”

Section: Discussionmentioning

confidence: 99%

Using DNA methylation to validate an electronic medical record phenotype for smoking

et al. 2018

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A validated, scalable approach to characterizing (phenotyping) smoking status is needed to facilitate genetic discovery. Using established DNA methylation sites from blood samples as a criterion standard for smoking behavior, we compare three candidate electronic medical record (EMR) smoking metrics based on longitudinal EMR text notes. With data from the Veterans Aging Cohort Study (VACS), we employed a validated algorithm to translate each smoking-related text note into current, past or never categories. We compared three alternative summary characterizations of smoking: most recent, modal and trajectories using descriptive statistics and Spearman's correlation coefficients. Logistic regression and area under the curve analyses were used to compare the associations of these phenotypes with the DNA methylation sites, cg05575921 and cg03636183, which are known to have strong associations with current smoking. DNA methylation data were available from the VACS Biomarker Cohort (VACS-BC), a sub-study of VACS. We also considered whether the associations differed by the certainty of trajectory group assignment (<0.80/≥0.80). Among 140 152 VACS participants, EMR summary smoking phenotypes varied in frequency by the metric chosen: current from 33 to 53 percent; past from 16 to 24 percent and never from 24 to 33 percent. The association between the EMR smoking pairs was highest for modal and trajectories (rho = 0.89). Among 728 individuals in the VACS-BC, both DNA methylation sites were associated with all three EMR summary metrics (p < 0.001), but the strongest association with both methylation sites was observed for trajectories (p < 0.001). Longitudinal EMR smoking data support using a summary phenotype, the validity of which is enhanced when data are integrated into statistical trajectories.

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“…In an interesting twist on the usual approach, a study from the VA Million Veteran Program used the firmly established association of ADH1B (rs1229984 in European Americans, rs2066702 in African Americans 12 ) to examine how AUDIT-C and ICD codes perform as phenotypes for harmful alcohol use 18 . They determined that in the veteran population, high (≥8) age-adjusted AUDIT-C score correlated better than ICD diagnostic codes with the ADH1B variants.…”

Section: Recent Studiesmentioning

confidence: 99%

Genetics of Alcoholism

Edenberg

Gelernter

Agrawal

2019

Curr Psychiatry Rep

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Purpose of review:We review the search for genetic variants that affect the risk for alcohol dependence and alcohol consumption. Recent findings:Variations in genes affecting alcohol metabolism (ADH1B, ALDH2) are protective against both alcohol dependence and excessive consumption, but different variants are found in different populations. There are different patterns of risk variants for alcohol dependence vs. consumption. Variants for alcohol dependence, but not consumption, are associated with risk for other psychiatric illnesses.Summary: ADH1B and ALDH2 strongly affect both consumption and dependence. Variations in many other genes affect both consumption and dependence -or one or the other of these traits --but individual effect sizes are small. Evidence for other specific genes that affect dependenceis not yet strong. Most current knowledge derives from studies of European-ancestry populations, and large studies of carefully phenotyped subjects from different populations are needed to understand the genetic contributions to alcohol consumption and alcohol use disorders.

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AUDIT‐C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations

Abstract: The 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.

Cited by 24 publications

References 22 publications

Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

Using DNA methylation to validate an electronic medical record phenotype for smoking

Genetics of Alcoholism

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