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

Evidence for sex differences in the impact of cytochrome P450 genotypes on early subjective effects of cannabis

Early positive subjective effects of cannabis predict the development of cannabis use disorder (CUD). Genetic factors, such as the presence of cytochrome P450 genetic variants that are associated with reduced Δ9-tetrahydrocannabinol (THC) metabolism, may contribute to individual differences in subjective effects of cannabis. Young adults (N = 54) with CUD or a non-CUD substance use disorder (control) provided a blood sample for DNA analysis and self-reported their early (i.e., effects upon initial uses) and past-year positive and negative subjective cannabis effects. Participants were classified as slow metabolizers if they had at least one CYP2C9 or CYP3A4 allele associated with reduced activity. Though the CUD group and control group did not differ in terms of metabolizer status, slow metabolizer status was more prevalent among females in the CUD group than females in the control group. Slow metabolizers reported greater past year negative THC effects compared to normal metabolizers; however, slow metabolizer status did not predict early subjective cannabis effects (positive or negative) or past year positive effects. Post-hoc analyses suggested males who were slow metabolizers reported more negative early subjective effects of cannabis than female slow metabolizers. Other sex-by-genotype interactions were not significant. These initial findings suggest that genetic variation in CYP2C9 and CYP3A4 may have sex-specific associations with cannabis-related outcomes. Slow metabolizer genes may serve as a risk factor for CUD for females independent of subjective effects. Male slow metabolizers may instead be particularly susceptible to the negative subjective effects of cannabis.

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. Understanding the genetic architecture of this comorbidity could be improved by focusing on intermediate traits that show positive genetic correlation with the disorders. Thus, we aimed to characterize the shared vs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD) -beyond genetic correlation, and boost discovery for jointly-associated loci. Summary statistics for MOOD (a binary measure of the tendency to report frequent mood swings), AC (number of standard drinks over a typical consumption week) and AUD GWASs (Ns > 200,000) were analyzed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD. To do so, we used a newly established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly associated genomic loci, which were mapped to genes and biological functions. MOOD was highly polygenic (10.4k single nucleotide polymorphisms, SNPs, SD = 2k) compared to AC (4.9k SNPs, SD = 0.6k) and AUD (4.3k SNPs, SD = 2k). The polygenic overlap of MOOD and AC was twice that of MOOD and AUD (98% vs. 49%), with opposite genetic correlation (-0.2 vs. 0.23), as confirmed in independent samples. MOOD&AUD associated SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 jointly associated loci, fifteen were novel for MOOD, AC and AUD. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated partly shared biological underpinnings, yet, clearly distinct functional patterns between MOOD&AC and MOOD&AUD, suggesting new mechanisms for the comorbidity of AUD with mood disorders.

A systematic review and behaviour change technique analysis of remotely delivered alcohol and/or substance misuse interventions for adults

BACKGROUND

There has been a lack of systematic exploration of remotely delivered intervention content and their effectiveness for behaviour change outcomes. This review provides a synthesis of the behaviour change techniques (BCT) contained in remotely delivered alcohol and/or substance misuse approaches and their association with intervention promise.

METHODS

Searches in MEDLINE, Scopus, PsycINFO (ProQuest), and the Cochrane Library, included studies reporting remote interventions focusing on alcohol and/or substance misuse among adults, with a primary behaviour change outcome (e.g., alcohol levels consumed). Assessment of risk of bias, study promise, and BCT coding was conducted. Synthesis focussed on the association of BCTs with intervention effectiveness using promise ratios.

RESULTS

Studies targeted alcohol misuse (52 studies) or substance misuse (10 studies), with predominantly randomised controlled trial designs and asynchronous digital approaches. For alcohol misuse studies, 16 were very promising, 17 were quite promising, and 13 were not promising. Of the 36 eligible BCTs, 28 showed potential promise, with seven of these only appearing in very or quite promising studies. Particularly promising BCTs were 'Avoidance/reducing exposure to cues for behaviour', 'Pros and cons' and 'Self-monitoring of behaviour'. For substance misuse studies, three were very promising and six were quite promising, with all 12 BCTs showing potential promise.

CONCLUSIONS

This review showed remotely delivered alcohol and substance misuse interventions can be effective and highlighted a range of BCTs that showed promise for improving services. However, concerns with risk of bias and the potential of promise ratios to inflate effectiveness warrant caution in interpreting the evidence.

A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation

Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.

Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review

Non-alcoholic fatty liver disease (NAFLD) is one of the most important causes of chronic liver disease in the world, it has been found that cardiovascular and renal risks and diseases are also highly prevalent in adults with NAFLD. Diagnosis and treatment of NAFLD face many challenges, although the medical science has been very developed. Efficiency, accuracy and individualization are the main goals to be solved. Evaluation of the severity of NAFLD involves a variety of clinical parameters, how to optimize non-invasive evaluation methods is a necessary issue that needs to be discussed in this field. Artificial intelligence (AI) has become increasingly widespread in healthcare applications, and it has been also brought many new insights into better analyzing chronic liver disease, including NAFLD. This paper reviewed AI related researches in NAFLD field published recently, summarized diagnostic models based on electronic health record and lab test, ultrasound and radio imaging, and liver histopathological data, described the application of therapeutic models in personalized lifestyle guidance and the development of drugs for NAFLD. In addition, we also analyzed present AI models in distinguishing healthy VS NAFLD/NASH, and fibrosis VS non-fibrosis in the evaluation of NAFLD progression. We hope to provide alternative directions for the future research.

Remote delivery of alcohol and/or substance misuse interventions for adults: A systematic review protocol

INTRODUCTION

Alcohol and substance misuse are a public health priority. The World Health Organisation (WHO) estimates that harmful alcohol use accounts for 5.1% of the global burden of disease and that 35.6 million people worldwide are affected by substance misuse. The Coronavirus Disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has disrupted delivery of face-to-face alcohol and substance misuse interventions and has forced the development of alternative remote interventions or adaptation to existing ones. Although existing research on remote interventions suggests they might be as effective as face-to-face delivery, there has been a lack of systematic exploration of their content, the experience of service users, and their effectiveness for behavioural outcomes. This review will provide a narrative synthesis of the behaviour change techniques (BCT) contained in interventions for alcohol and/or substance misuse and their association with effectiveness.

METHODS AND ANALYSIS

Systematic searches will be conducted in MEDLINE, Scopus, PsycINFO (ProQuest), and the Cochrane Library. Included studies will be those reporting remote interventions focusing on alcohol and/or substance misuse among adults living in the community and which have a primary behaviour change outcome (i.e., alcohol levels consumed). Data extraction will be conducted by one author and moderated by a second, and risk of bias and behaviour change technique (BCT) coding will be conducted by two authors independently. A narrative synthesis will be undertaken focussing upon the association of BCTs with intervention effectiveness using promise ratios.

PATIENT AND PUBLIC INVOLVEMENT (PPI)

The Public Involvement in Research Group (PIRG), part of the NIHR-funded PHIRST, will be involved in refining the review questions, eligibility criteria, data synthesis and dissemination.

DISSEMINATION

Dissemination will be through an academic peer reviewed publication, alongside other outputs to be shared with non-academic policy, professional, and public audiences, including local authorities, service users and community organisations.

Whole Genome Interpretation for a Family of Five

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data.

Survival Benefit of Liver Transplantation for Hepatocellular Carcinoma

BACKGROUND

In the United States, nearly 30% of liver transplants (LT) are performed for hepatocellular carcinoma (HCC). Although overall long-term survival is highest with LT, there are limited data on the incremental survival benefit of LT versus other curative options (resection or ablation) due to shunting of patients towards LT.

METHODS

We performed a retrospective cohort study of patients aged 50-69 with cirrhosis and HCC in the Veterans Health Administration (population enriched with 3 curative treatments) from 2008 to 2016. The cohort was restricted to patients who received LT, resection, or ablation and a calculated model for end-stage liver disease score <15 at HCC diagnosis.

RESULTS

Among 2129 veterans in the analytic cohort, 658 (26.7%) received LT, 244 (11.5%) underwent resection, and 1317 (61.59%) received ablation. In multivariable models, patients who underwent resection (hazard ratio: 5.42; 95% confidence interval: 4.15-7.08) or ablation (hazard ratio: 5.50; 95% confidence interval: 4.51-6.71) had significantly increased hazards of death. However, in absolute terms, the incremental survival benefit of LT over resection or ablation was small, between 0.02 and 0.03 years at 1 year, 0.32-0.42 years at 3 years, and 1.04-1.24 years at 5 years follow-up. These results were consistent in sensitivity analyses accounting for possible immortal time bias, as well as a cohort restricted to early/intermediate stage HCC.

CONCLUSIONS

Although LT is associated with significantly increased survival compared to resection and ablation, the absolute incremental survival benefit is small over a 5-year time horizon. Optimal selection of patients for LT is critical for maximizing utilization of a scarce resource.

Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program

BACKGROUND & AIMS

Given ongoing challenges in non-invasive non-alcoholic liver disease (NAFLD) diagnosis, we sought to validate an ALT-based NAFLD phenotype using measures readily available in electronic health records (EHRs) and population-based studies by leveraging the clinical and genetic data in the Million Veteran Program (MVP), a multi-ethnic mega-biobank of US Veterans.

METHODS

MVP participants with alanine aminotransferases (ALT) >40 units/L for men and >30 units/L for women without other causes of liver disease were compared to controls with normal ALT. Genetic variants spanning eight NAFLD risk or ALT-associated loci (LYPLAL1, GCKR, HSD17B13, TRIB1, PPP1R3B, ERLIN1, TM6SF2, PNPLA3) were tested for NAFLD associations with sensitivity analyses adjusting for metabolic risk factors and alcohol consumption. A manual EHR review assessed performance characteristics of the NAFLD phenotype with imaging and biopsy data as gold standards. Genetic associations with advanced fibrosis were explored using FIB4, NAFLD Fibrosis Score and platelet counts.

RESULTS

Among 322,259 MVP participants, 19% met non-invasive criteria for NAFLD. Trans-ethnic meta-analysis replicated associations with previously reported genetic variants in all but LYPLAL1 and GCKR loci (P<6x10-3), without attenuation when adjusted for metabolic risk factors and alcohol consumption. At the previously reported LYPLAL1 locus, the established genetic variant did not appear to be associated with NAFLD, however the regional association plot showed a significant association with NAFLD 279kb downstream. In the EHR validation, the ALT-based NAFLD phenotype yielded a positive predictive value 0.89 and 0.84 for liver biopsy and abdominal imaging, respectively (inter-rater reliability (Cohen's kappa = 0.98)). HSD17B13 and PNPLA3 loci were associated with advanced fibrosis.

CONCLUSIONS

We validate a simple, non-invasive ALT-based NAFLD phenotype using EHR data by leveraging previously established NAFLD risk-associated genetic polymorphisms.

The OATH Syndemic: opioids and other substances, aging, alcohol, tobacco, and HIV

PURPOSE OF REVIEW

Persons living with HIV (PLWH) are aging, continue to use alcohol and other substances, and experience age-associated adverse effects. We explore a new syndemic: OATH (opioids and other substances, aging, alcohol, tobacco, and HIV).

RECENT FINDINGS

Frailty and falls are important problems that affect the health status of PLWH who continue to use alcohol and other substances. HIV, alcohol and other substance use, and aging each contributes to inflammaging. Multimorbidity and polypharmacy are also important pathways as alcohol and other substances interact with prescribed medications resulting in adverse-drug interactions leading to potentially serious consequences. Social conditions including racism, poverty, sex bias, stress, and stigma contribute to the existence and persistence of this syndemic.

SUMMARY

Substance use, HIV, and aging are linked in a new syndemic (OATH) that drives age-related outcomes such as frailty and falls. We need to expand our understanding of the 'healthcare team' so that we include social and political advocates who can support necessary structural change. Treatment of substance use should be better incorporated into the management of HIV, including a focus on potential medication/substance interactions. Finally, we need to explore treatment of frailty rather than individual manifestations of frailty (e.g., atherosclerosis, neurodegeneration).

Differentiating Types of Self-Reported Alcohol Abstinence

We contrast three types of abstinence: quit after alcohol associated problems (Q-AP), quit for other reasons (Q-OR), and lifetime abstainer (LTA). We summarized the characteristics of people living with HIV (PLWH), and matched uninfected individuals, by levels of alcohol use and types of abstinence. We then identified factors that differentiate abstinence and determined whether the association with an alcohol biomarker or a genetic polymorphism is improved by differentiating abstinence. Among abstainers, 34% of PLWH and 38% of uninfected were Q-AP; 53% and 53% were Q-OR; and 12% and 10% were LTA. Logistic regression models found smoking, alcohol, cocaine, and hepatitis C increased odds of Q-AP, whereas smoking and marijuana decreased odds of LTA. Differentiating types of abstinence improved association. Q-APs and LTAs can be readily differentiated by an alcohol biomarker and genetic polymorphism. Differentiating type of abstinence may enhance understanding of alcohol health effects.

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

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.

Facilitating Screening and Brief Interventions in Primary Care: A Systematic Review and Meta-Analysis of the AUDIT as an Indicator of Alcohol Use Disorders

Background

The Alcohol Use Disorders Identification Test (AUDIT) was developed for use in primary health care settings to identify hazardous and harmful patterns of alcohol consumption, and is often used to screen for alcohol use disorders (AUDs). This study examined the AUDIT as a screening tool for AUDs.

Methods

A systematic literature search was performed of electronic bibliographic databases (CINAHL, Embase, ERIC, MEDLINE, PsycINFO, Scopus, and Web of Science) without language or geographic restrictions for original quantitative studies published before September 1, 2018, that assess the AUDIT's ability to screen for AUDs. Random‐effects meta‐regression models were constructed by sex to assess the potential determinants of the AUDIT's specificity and sensitivity. From these models and ecological data from the Global Information System on Alcohol and Health, the true‐ and false‐positive and true‐ and false‐negative proportions were determined. The number of people needed to be screened to treat 1 individual with an AUD was estimated for all countries globally where AUD data exist, using a specificity of 0.95.

Results

A total of 36 studies met inclusion criteria for the meta‐regression. The AUDIT score cut‐point was significantly associated with sensitivity and specificity. Standard drink size was found to affect the sensitivity and specificity of the AUDIT for men, but not among women. The AUDIT performs less well in identifying women compared to men, and countries with a low prevalence of AUDs have higher false‐positive rates compared to countries with a higher AUD prevalence.

Conclusions

The AUDIT does not perform well as a screening tool for identifying individuals with an AUD, especially in countries and among populations with a low AUD prevalence (e.g., among women), and thus should not be used for this purpose.

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

Alcohol consumption level and alcohol use disorder (AUD) diagnosis are moderately heritable traits. We conduct genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores and AUD diagnoses in a multi-ancestry Million Veteran Program sample (N = 274,424). We identify 18 genome-wide significant loci: 5 associated with both traits, 8 associated with AUDIT-C only, and 5 associated with AUD diagnosis only. Polygenic Risk Scores (PRS) for both traits are associated with alcohol-related disorders in two independent samples. Although a significant genetic correlation reflects the overlap between the traits, genetic correlations for 188 non-alcohol-related traits differ significantly for the two traits, as do the phenotypes associated with the traits' PRS. Cell type group partitioning heritability enrichment analyses also differentiate the two traits. We conclude that, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.

Genetics of Alcoholism

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. 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 dependence is 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.

Longitudinal Drinking Patterns and Their Clinical Correlates in Million Veteran Program Participants

BACKGROUND

A variety of measures have been developed to screen for hazardous or harmful drinking. The Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) is one of the screening measures recommended by the U.S. Preventive Services Task Force. Annual administration of the AUDIT-C to all primary care patients is required by the U.S. Veterans Affairs Health System. The availability of data from the repeated administration of this instrument over time in a large patient population provides an opportunity to evaluate the utility of the AUDIT-C for identifying distinct drinking groups.

METHODS

Using data from the Million Veteran Program cohort, we modeled group-based drinking trajectories using 2,833,189 AUDIT-C scores from 495,178 Veterans across an average 6-year time period. We also calculated patients' age-adjusted mean AUDIT-C scores to compare to the drinking trajectories. Finally, we extracted data on selected clinical diagnoses from the electronic health record and assessed their associations with the drinking trajectories.

RESULTS

Of the trajectory models, the 4-group model demonstrated the best fit to the data. AUDIT-C trajectories were highly correlated with the age-adjusted mean AUDIT-C scores (rs = 0.94). Those with an alcohol use disorder diagnosis had 10 times the odds of being in the highest trajectory group (consistently hazardous/harmful) compared to the lowest drinking trajectory group (infrequent). Those with hepatitis C, posttraumatic stress disorder, liver cirrhosis, and delirium had 10, 7, 21, and 34%, respectively, higher odds of being classified in the highest drinking trajectory group versus the lowest drinking trajectory group.

CONCLUSIONS

Trajectories and age-adjusted mean scores are potentially useful approaches to optimize the information provided by the AUDIT-C. In contrast to trajectories, age-adjusted mean AUDIT-C scores also have clinical relevance for real-time identification of individuals for whom an intervention may be warranted.