Genome-wide association study of alcohol consumption and use disorder in 274,424 individuals from multiple populations

Identifying and Reducing Bias in Genome-Wide Association Studies of Alcohol-Related Traits.

Longitudinal 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). With 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. United States Department of Veterans Affairs Healthcare System. A total of 167 721 veterans (57 677 AAs and 110 044 EAs; 92% male, mean age=63years) took part in this study. Data were collected from 1 October 2007 to 1May 2017. 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. A 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. 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.

Studies show that racially and ethnically minoritized veterans have a higher prevalence of alcohol use disorder (AUD) than White veterans. The investigators examined whether the relationship between self-reported race and ethnicity and AUD diagnosis remains after adjusting for alcohol consumption, and if so, whether it varies by self-reported alcohol consumption. The sample included 700,012 Black, White, and Hispanic veterans enrolled in the Million Veteran Program. Alcohol consumption was defined as an individual's maximum score on the consumption subscale of the Alcohol Use Disorders Identification Test (AUDIT-C), a screen for unhealthy alcohol use. A diagnosis of AUD, the primary outcome, was defined by the presence of relevant ICD-9 or ICD-10 codes in electronic health records. Logistic regression with interactions was used to assess the association between race and ethnicity and AUD as a function of maximum AUDIT-C score. Black and Hispanic veterans were more likely than White veterans to have an AUD diagnosis despite similar levels of alcohol consumption. The difference was greatest between Black and White men; at all but the lowest and highest levels of alcohol consumption, Black men had 23%-109% greater odds of an AUD diagnosis. The findings were unchanged after adjustment for alcohol consumption, alcohol-related disorders, and other potential confounders. The large discrepancy in the prevalence of AUD across groups despite a similar distribution of alcohol consumption levels suggests that there is racial and ethnic bias, with Black and Hispanic veterans more likely than White veterans to receive an AUD diagnosis. Efforts are needed to reduce bias in the diagnostic process to address racialized differences in AUD diagnosis.

Focusing on Substance Use Disorders, Opioids, and Craving.

The degree to which alcohol use is associated with the risk of all-cause mortality and hepatic decompensation after hepatitis C (HCV) diagnosis, treatment, and cure remains unknown. We sought to address this question among patients achieving sustained virologic response (SVR) after direct-acting antiviral treatment in the largest HCV health system in the United States. We extracted data on alcohol use, HCV treatment, SVR, HIV co-infection, demographics, risk behaviours, hepatic decompensation, and mortality from all patients in the 1945 to 1965 VA Birth Cohort. Alcohol use categories were generated using responses to the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire and diagnostic codes for alcohol use disorder (AUD): abstinent without a history of AUD, abstinent with a history of AUD, current lower-risk consumption, current moderate-risk consumption, and current high-risk consumption with or without AUD. Cox proportional hazard models were used to examine associations between alcohol category and the risk of hepatic decompensation and all-cause mortality. Among 50,581 patients in the analytic cohort, compared to current drinkers exhibiting lower risk alcohol consumption (referent), current high-risk consumption with or without AUD was associated with increased risk of all-cause mortality (aHR: 1.40, 95% CI: 1.21-1.63) and hepatic decompensation (HR: 2.15, 95% CI: 1.60-2.89) as was abstinence with a history of AUD diagnosis (mortality aHR: 1.63, 95% CI: 1.41-1.89; hepatic decompensation aHR: 1.85, 95% CI: 1.36-2.51). AUD and high-risk alcohol consumption are associated with the risk of hepatic decompensation and all-cause mortality among Veterans who have achieved SVR, including those categorised as being currently abstinent. Interventions for alcohol consumption and use disorder among individuals treated for HCV infection may reduce morbidity and mortality in this population.

Topiramate is a medication that is widely prescribed to treat a variety of conditions, including alcohol use disorder (AUD). We used electronic health record (EHR) data to measure topiramate's effects on drinking in individuals differentiated by a history of AUD. Parallel-groups comparison of patients prescribed topiramate and a propensity score-matched comparison group. A large US integrated health-care system. Patients with Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) scores prior to and after a minimum of 180 days of topiramate prescription for any indication and a propensity score-matched group. The sample included 5918 patients with an electronic health record diagnosis of alcohol use disorder at any time (AUD-hx-pos) (1738 topiramate-exposed and 4180 controls) and 23 614 patients with no EHR diagnosis of AUD (AUD-hx-neg) (6324 topiramate-exposed and 17 290 controls). Regression analyses compared difference-in-difference (DiD) estimates, separately by AUD history. DiD estimates represent exposure-group (i.e. topiramate versus control) differences on the pre-post difference in AUDIT-C score. Effects of baseline AUDIT-C score and daily topiramate dosage were also tested. AUD-hx-neg patients who received topiramate had a greater reduction in AUDIT-C score (-0.11) than matched controls (-0.04). This yielded a DiD score of -0.07 [95% confidence interval (CI) = -0.11,-0.03; P = 0.002], with the greatest effect among AUD-hx-neg patients with a baseline AUDIT-C score of 4+ (DiD = -0.35, 95% CI = -0.49, -0.21; P < 0.0001) and those prescribed > 150 mg/day of the medication (DiD = -0.15, 95%CI = -0.23, -0.07; P < 0.001). Among individuals with no history of alcohol use disorder, topiramate appears to be associated with reduced drinking. This small effect is most evident among patients with higher baseline drinking levels and at a higher average daily topiramate dosage.

BACKGROUND:Alcohol use disorder (AUD) is highly prevalent in the U.S., affecting approximately 10.9% of adults, yet remains underdiagnosed and undertreated.OBJECTIVE:To estimate the rate of AUD underdiagnosis in clinical practice, identify individual characteristics associated with underdiagnosis, and assess whether receiving a diagnosis increases the likelihood of treatment.DESIGN:Retrospective cohort study.PARTICIPANTS:Adults aged ≥ 18 years who screened positive for unhealthy alcohol use using AUD Identification Test-Consumption (AUDIT-C) score (≥ 4 for men, ≥ 3 for women). This study used data from the All of Us Research Program, a national, population-based cohort to reflect the diverse U.S. population.MAIN MEASURES:AUD diagnoses were identified using ICD-9/10 codes. Treatment receipt was defined as either medication (disulfiram, acamprosate, or naltrexone prescriptions) or psychotherapy (identified via CPT-4 codes).KEY RESULTS:We identified 114,511 participants with unhealthy alcohol use (mean age = 50.4 years; 39.3% male). The overall AUD diagnosis rate was 10.1%, with rates of 6.8%, 21.5%, and 41.6% among participants with mild, moderate, and severe AUD risk, respectively. Factors associated with increased odds of receiving an AUD diagnosis were older age, male sex, non-Hispanic White, lower educational attainment and income, unemployment, unmarried status, public insurance coverage, and co-occurring substance use, mental health disorders, and alcohol-related medical conditions. The lifetime treatment rate was 2.55% for medication and 7.08% for psychotherapy. An AUD diagnosis was associated with increased odds of receiving medication (aOR = 10.68; 95% CI: 9.68–11.79) and psychotherapy (aOR = 1.57; 95% CI: 1.46–1.69).CONCLUSIONS:In this cohort of U.S. adults with unhealthy alcohol use, AUD was underdiagnosed across all risk level with females, racial/ethnic minorities, residence in economically deprived areas, and private insurance holders more likely to be undiagnosed. Given the strong association between diagnosis and treatment receipt, these diagnostic disparities are likely to contribute to inequities in care.

Excessive alcohol use is a leading cause of preventable death in the United States. Despite the availability of effective alcohol use disorder (AUD) treatments, usage remain low. This quality improvement project explored the use of direct-to-consumer (DTC) patient education across multiple US Department of Veterans Affairs (VA) facilities to increase AUD treatment. Patients with AUD or at high risk for AUD at 5 Veterans Integrated Service Network (VISN) 21 sites who were not receiving AUD pharmacotherapy were identified. Veterans were eligible for inclusion if they had an Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) score ≥ 6 with an AUD diagnosis, or ≥ 8 without diagnosis, and a scheduled appointment with primary care, mental health, or a substance use disorder (SUD) health care practitioner between October 1, 2023, and January 31, 2024. The final cohort was mailed education materials about 2 weeks prior to their appointment. A comparator group from the previous year was identified using propensity score matching, and findings were assessed using logistic regression. The outcomes were assessed within 30 days of the scheduled visit, with the primary outcome being the initiation of pharmacotherapy and the secondary outcome being the placement of a consultation for mental health or SUD services. DTC education was mailed to 1260 veterans. Primary and secondary outcomes did not find statistically significant differences between patients that received DTC education and the comparator group (P > .59). Although the results of this study were not statistically significant, this project initiated conversations at the VISN around AUD and available treatments. Future research should focus on addressing primary care involvement in AUD treatment, assessing different methods for delivering DTC education, and its potential long-term impact in the treatment of AUD.

Topiramate, which is increasingly being used to treat alcohol use disorder (AUD), is commonly associated with reduced serum bicarbonate concentrations. However, estimates of the prevalence and magnitude of this effect are from small samples and do not address whether topiramate's effects on acid-base balance differ in the presence of an AUD or by topiramate dosage. Veterans Health Administration electronic health record (EHR) data were used to identify patients with a minimum of 180 days of topiramate prescription for any indication and a propensity score-matched control group. We differentiated patients into two subgroups based on the presence of a diagnosis of AUD in the EHR. Baseline alcohol consumption was determined using Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) scores in the EHR. Analysis also included a three-level measure representing mean daily dosage. The topiramate-associated changes in serum bicarbonate concentration were estimated in difference-in-differences linear regression models. A serum bicarbonate concentration <17 mEq/L was considered to represent possible clinically significant metabolic acidosis. The cohort comprised 4287 topiramate-treated patients and 5992 propensity score-matched controls with a mean follow-up period of 417 days. The mean topiramate-associated reductions in serum bicarbonate concentration were <2mEq/L in the low (≤88.75), medium (>88.75 and ≤141.70), and high (>141.70) mg/day dosage tertiles, irrespective of AUD history. Concentrations <17 mEq/L occurred in 1.1% of topiramate-treated patients and 0.3% of controls and were not associated with alcohol consumption or an AUD diagnosis. The excess prevalence of metabolic acidosis associated with topiramate treatment does not differ with dosage, alcohol consumption, or the presence of an AUD. Baseline and periodic serum bicarbonate concentration measurements are recommended during topiramate therapy. Patients prescribed topiramate should be educated about the symptoms of metabolic acidosis and urged to report their occurrence promptly to a healthcare provider.

The Tobacco, Alcohol, Prescription Medication, and Other Substance (TAPS) tool is a screening and brief assessment instrument to identify unhealthy tobacco, alcohol, drug use, and prescription medication use in primary care patients. This secondary analysis compares the TAPS tool to the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) for alcohol screening. Adult primary care patients (1124 female, 874 male) completed the TAPS tool followed by AUDIT-C. Performance of each instrument was evaluated against a reference standard measure, the modified World Mental Health Composite International Diagnostic Interview, to identify problem use and alcohol use disorder (AUD). Area under the curve (AUC) appraised discrimination, and sensitivity and specificity were calculated for Youden optimal score thresholds. For identifying problem use: On the AUDIT-C, AUC was 0.90 (95% Confidence Interval: 0.86-0.92) for females and 0.91 (0.89-0.93) for males. Sensitivity and specificity for females were 0.89 (0.83-0.93) and 0.78 (0.75-0.80), respectively, and for males were 0.84 (0.79-0.88) and 0.82 (0.79-0.85). On the TAPS tool, AUC was 0.82 (0.79-0.86) for females and 0.81 (0.78-0.84) for males. Sensitivity and specificity for females were 0.78 (0.72-0.84) and 0.78 (0.75-0.81), respectively, and for males were 0.76 (0.71-0.81) and 0.76 (0.72-0.79). For AUD: On the AUDIT-C, AUC was 0.90 (0.88-0.93) for both females and males. Sensitivity and specificity for females were 0.83 (0.74-0.90) and 0.83 (0.80-0.85), respectively, while for males, they were 0.81 (0.74-0.87) and 0.84 (0.81-0.87). On the TAPS tool, AUC was 0.84 (0.80-0.89) for females and 0.82 (0.78-0.86) for males. Sensitivity and specificity for females were 0.73 (0.63-0.81) and 0.85 (0.83-0.88), respectively, while for males, they were 0.75 (0.68-0.81) and 0.84 (0.81-0.86). The AUDIT-C performed somewhat better than the TAPS tool for alcohol screening. However, the TAPS tool had an acceptable level of performance for alcohol screening and may be advantageous in practice settings seeking to identify alcohol and other substance use with a single instrument.

The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaire screens for harmful drinking using a 12-month timeframe. A score of 0 is assigned to individuals who report abstaining from alcohol in the past year. However, many middle-age individuals reporting current abstinence are former drinkers (FDs). Because FDs may be more genetically prone to harmful alcohol use than lifelong abstainers (LAs) and are often combined with LAs, we evaluated the impact of differentiating them on the identification of genetic association. The United Kingdom Biobank (UKBB) includes AUDIT-C and alcohol drinker status. 131 510 Europeans, including 5135 FDs. We compared three genome-wide association (GWAS) analyses to explore the effects of removing FDs: the full AUDIT-C data, AUDIT-C data without FDs, and data from a random sample numerically matched to the data without FDs. Because prior studies show a consistent association of the ADH1B polymorphism rs1229984 with both alcohol consumption and alcohol use disorder, we compared allele frequencies for rs1229984 stratified by AUDIT-C value and FD versus LA status. Additionally, we calculated polygenic risk scores (PRS) of related diseases. The rs1229984 allele frequencies among FDs were numerically comparable to those with high AUDIT-C scores and very different from those of LAs. Removing FDs from GWAS yielded a stronger association with rs1229984 (P value after removal: 1.9 × 10-70 vs 1.7 × 10-65 and 2.5 × 10-62 ), more statistically significant single nucleotide polymorphisms (SNPs) (after removal: 11 vs 9 and 8), and genomic loci (after removal: 11 vs 9 and 7). Additional independent SNPs were identified after removal of FDs: rs2817866 (PTGER3), rs7105867 (ANO3), and rs17601612 (DRD2). For PRS of alcohol use disorder and major depressive disorder, there are statistically significant differences between FDs and LAs. Differentiating between former drinkers and lifelong abstainers can improve Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) genome-wide association results.

Racial and Ethnic Biases and Psychiatric Misdiagnoses: Toward More Equitable Diagnosis and Treatment.

Background:Current understanding of associations between alcohol use and falls among people with HIV (PWH) is limited due to few and inconsistent studies. Given the prevalence of heavy episodic alcohol use reported among PWH, this remains an important question.Methods:Alcohol use was measured using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) and self-reported alcohol use treatment and/or diagnosis of alcohol use disorder (collectively AUD) among PWH at 8 CFAR Network of Integrated Clinical Systems (CNICS) sites from 2021–2024. Falls were self-reported using components of the Falls Risk for Older People in the Community questionnaire. Cross-sectional associations between alcohol use and falls were examined using relative risk models adjusted for age, sex, race/ethnicity, and geographic location.Results:Among 5,729 PWH, mean age was 55 years; 42% reported White and 41% reported Black/African American race/ethnicity; and 81% were male. Mean AUDIT-C score was 1.9 (range: 0–12); 27% reported heavy episodic drinking; 22% had AUD; and 22% reported falling in the past year. Reporting ≥1 fall in the past year was not associated with any measure of current alcohol use. AUD was associated with reporting ≥1 fall (prevalence ratio (PR)=1.54 (95%-CI: 1.39–1.70)) and number of falls (1-fall: PR=1.27 (95%-CI: 1.08–1.50); ≥2-falls: PR=1.84 (95%-CI: 1.58–2.15).Conclusion:Among PWH, 22% reported falling, which was associated with AUD, but not current alcohol use, suggesting that a mechanism other than acute intoxication could be responsible. Further longitudinal research is warranted to explore mechanisms for why AUD, but not current alcohol use, is associated with falls.

Background:Gabapentin and pregabalin have potential utility for treating alcohol use disorder (AUD), but their comparative effectiveness in reducing alcohol consumption in real-world settings is unknown. We compared changes in alcohol consumption associated with gabapentin or pregabalin treatment with those of matched unexposed comparators.Methods:We identified patients who were prescribed gabapentin or pregabalin for ≥60 days for any indication between 1 January 2009 and 30 June 2022 using electronic health records from the Veterans Aging Cohort Study (VACS-National). Alcohol consumption was measured using routinely-collected Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) questionnaires. We used propensity score matching to balance baseline characteristics between groups. Three comparisons were conducted: gabapentin vs. unexposed, pregabalin vs. unexposed, and pregabalin vs. gabapentin. Changes in AUDIT-C scores were estimated using multivariable difference-in-difference linear regression models. Analyses were stratified by baseline AUD diagnosis and AUDIT-C categories (lower-risk, at-risk, hazardous/binge).Results:We identified 592,957 gabapentin initiators, 14,923 pregabalin initiators, and 2,959,006 eligible unexposed comparators who were eligible for matching. Compared to unexposed individuals, patients who received gabapentin (DiD: 0.09, 95% CI 0.06, 0.11, p<0.0001) or pregabalin (DiD: 0.14, 95% CI 0.02, 0.26, p=0.0279) reported greater reductions in AUDIT-C scores. When compared head-to-head, pregabalin initiators reported greater reductions in AUDIT-C scores than gabapentin initiators with the largest difference observed among those with AUD (DiD: 0.86, 95% CI 1.22, 0.50, p<0.0001) and those who report baseline hazardous/binge drinking (DiD: 1.74, 95% CI 2.21, 1.27, p<0.0001).Discussion:In this large, nationwide cohort, treatment with gabapentin and pregabalin were associated with reductions in reported alcohol consumption, compared to matched unexposed comparators. Initiation of pregabalin was associated with greater reductions than with gabapentin, particularly among those with AUD and those with highest severity of alcohol use. Known safety concerns and risk of misuse should be considered when prescribing these medications. Randomized clinical trials directly comparing these medications are necessary to validate these findings.

Current medications for alcohol use disorder (AUD) have limited efficacy and utilization. Some clinical trials have shown efficacy for gabapentin among treatment-seeking individuals. The impact of gabapentin on alcohol consumption in a more general sample remains unknown. We identified patients prescribed gabapentin for ≥180 consecutive days for any clinical indication other than substance use treatment between 2009 and 2015 in the Veterans Aging Cohort Study. We propensity-score matched each gabapentin-exposed patient with up to 5 unexposed patients. Multivariable difference-in-difference (DiD) linear regression models estimated the differential change in Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) scores during follow-up between exposed and unexposed patients, by baseline level of alcohol consumption and daily gabapentin dose. Analyses were stratified by AUD history. Clinically meaningful changes were a priori considered a DiD ≥1 point. Among patients with AUD, AUDIT-C scores decreased 0.39 points (95% confidence interval [CI] 0.05, 0.73) more among exposed than unexposed patients (p<0.03). Potentially clinically meaningful differences were observed among those with AUD and exposed to ≥1,500 mg/d (DiD 0.77, 95% CI 0.15, 1.38, p<0.02). No statistically significant effects were found among patients with AUD at doses lower than 1,500mg/d or baseline AUDIT-C ≥4. Among patients without AUD, we found no overall difference in changes in AUDIT-C scores, nor in analyses stratified by baseline level of alcohol consumption. Patients exposed to doses of gabapentin consistent with those used in clinical trials, particularly those with AUD, experienced a greater decrease in AUDIT-C scores than matched unexposed patients.