Subtypes of alcohol use disorder in the general population: A latent class analysis

Cluster analysis of patients with alcohol use disorder featuring alexithymia, depression, and diverse drinking behavior

AIM

This study aimed to identify subgroups of alcohol use disorder (AUD) based on a multidimensional combination of alexithymia, depression, and diverse drinking behavior.

METHOD

We recruited 176 patients with AUD, which were initially divided into non-alexithymic (n = 130) and alexithymic (n = 46) groups using a cutoff score of 61 on the Toronto Alexithymia Scale (TAS-20). Subsequently, the profiles of the two groups were compared. Thereafter, a two-stage cluster analysis using hierarchical and K-means methods was performed with the Z-scores from the TAS-20, the Quick Inventory of Depressive Symptomatology Self-Report Japanese Version, the 12-item questionnaire for quantitative assessment of depressive mixed state, and the 20-item questionnaire for drinking behavior pattern.

RESULTS

In the first analysis, Alexithymic patients with AUD showed greater depressive symptoms and more pathological drinking behavior patterns than those without alexithymia. Cluster analysis featuring alexithymia, depression, and drinking behavior identified three subtypes: Cluster 1 (core AUD type) manifesting pathological drinking behavior highlighting automaticity; Cluster 2 (late-onset type) showing relatively late-onset alcohol use and fewer depressive symptoms or pathological drinking behavior; and Cluster 3 (alexithymic type) characterized by alexithymia, depression, and pathological drinking behavior featuring greater coping with negative affect.

CONCLUSION

The multidimensional model with alexithymia, depression, and diverse drinking behavior provided possible practical classification of AUD. The alexithymic subtype may require more caution, and additional support for negative affect may be necessary due to accompanying mood problems and various maladaptive drinking behaviors.

Machine Learning of Functional Connectivity to Biotype Alcohol and Nicotine Use Disorders

BACKGROUND

Magnetic resonance imaging provides noninvasive tools to investigate alcohol use disorder (AUD) and nicotine use disorder (NUD) and neural phenotypes for genetic studies. A data-driven transdiagnostic approach could provide a new perspective on the neurobiology of AUD and NUD.

METHODS

Using samples of individuals with AUD (n = 140), individuals with NUD (n = 249), and healthy control participants (n = 461) from the UK Biobank, we integrated clinical, neuroimaging, and genetic markers to identify biotypes of AUD and NUD. We partitioned participants with AUD and NUD based on resting-state functional connectivity (FC) features associated with clinical metrics. A multitask artificial neural network was trained to evaluate the cluster-defined biotypes and jointly infer AUD and NUD diagnoses.

RESULTS

Three biotypes-primary NUD, mixed NUD/AUD with depression and anxiety, and mixed AUD/NUD-were identified. Multitask classifiers incorporating biotype knowledge achieved higher area under the curve (AUD: 0.76, NUD: 0.74) than single-task classifiers without biotype differentiation (AUD: 0.61, NUD: 0.64). Cerebellar FC features were important in distinguishing the 3 biotypes. The biotype of mixed NUD/AUD with depression and anxiety demonstrated the largest number of FC features (n = 5), all related to the visual cortex, that significantly differed from healthy control participants and were validated in a replication sample (p < .05). A polymorphism in TNRC6A was associated with the mixed AUD/NUD biotype in both the discovery (p = 7.3 × 10-5) and replication (p = 4.2 × 10-2) sets.

CONCLUSIONS

Biotyping and multitask learning using FC features can characterize the clinical and genetic profiles of AUD and NUD and help identify cerebellar and visual circuit markers to differentiate the AUD/NUD group from the healthy control group. These markers support a new growing body of literature.

Prevalence and correlates of the misuse of z-drugs and benzodiazepines in the National Survey on Drug Use and Health

Background

Benzodiazepines and non-benzodiazepine hypnotics (z-drugs) are commonly prescribed for their anxiolytic and hypnotic properties, though they can also be misused. In studies examining the epidemiology of prescription drug misuse, these medication classes are commonly combined, rendering inadequate knowledge of their patterns of misuse. The objective of this study was to characterize the population prevalence, conditional dependence, and sociodemographic and clinical correlates of the misuse of benzodiazepines and z-drugs.

Methods

Data from the National Survey on Drug Use and Health from 2015 to 2019 were used to estimate population-level prevalence and characteristics of benzodiazepine and z-drug misuse. Groups were derived based on past-year misuse of benzodiazepines alone, z-drugs alone, or both drug types. Unadjusted regression analyses were used to compare groups on characteristics of interest.

Results

Exposure to benzodiazepines and/or z-drugs via prescription or misuse was common; however, only 2% of the population was estimated to have misused a benzodiazepine in the past year, and less than 0.5% misused z-drugs. People who misused only z-drugs were generally older, more likely to have health insurance, more educated, and had less severe psychiatric symptoms. This group was also more likely to report misuse to cope with sleep difficulty. Although concurrent substance use was highly prevalent in all groups, people who misused z-drugs alone generally reported less concurrent substance use than the other groups.

Conclusion

The misuse of z-drugs is less common than benzodiazepines, and people who misuse only z-drugs appear to generally have lower clinical severity. Nonetheless, a substantial subgroup of people exposed to z-drugs report concurrent, past-year use of other substances. Further research on z-drug misuse, including consideration of whether it should be grouped with other anxiolytic/hypnotic drugs, is needed.

Driven by need, shaped by access: Heterogeneity in patient profiles and patterns of service utilization in patients with alcohol use disorders

BACKGROUND

Patients with alcohol-use disorders (AUDs) are highly heterogenous and account for an increasing proportion of general medical hospital visits. However, many patients with AUDs do not present with severe medical or psychiatric needs requiring immediate attention. There may be a mismatch between some patients' needs and the available services, potentially driving re-admissions and re-encounters. The current study aims to identify subgroups of AUD patients and predict differences in patterns of healthcare service use (HSU) over time.

METHODS

Latent class analysis (LCA) was conducted using hospital data incorporating sociodemographic, health behavior, clinical, and service use variables to identify subtypes of AUD patients, then class membership was used to predict patterns of HSU.

RESULTS

Four classes were identified with the following characteristics: (1) Patients with acute medical injuries (30 %); (2) Patients with socioeconomic and psychiatric risk factors, (11 %); (3) Patients with chronic AUD with primarily non-psychiatric medical needs (18 %); and (4) Patients with primary AUDs with low medical-treatment complexity (40 %). Negative binomial models showed that Class 4 patients accounted for the highest frequency of service use, including significantly higher rates of emergency department reencounters at 30 days and 12 months.

CONCLUSIONS

The profile and patterns of HSU exhibited by patients in class 4 suggest that these patients have needs which are not currently being addressed in the emergency department. These have implications for how resources are allocated to meet the needs of patients with AUDs, including those who make frequent visits to the emergency department without high acuity medical needs.

Examining differential responses to the Take Care of Me trial: A latent class and moderation analysis

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Take Care of Me participants fell into three classes varying in risk.

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The low-risk class had the lowest pre-treatment symptom severity.

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The high-risk group had the highest symptom severity and executive dysfunction.

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Moderate risk individuals experienced the greatest benefits of the program.

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Future interventions may be tailored based on risk to maximize efficacy.

Given prevalent alcohol misuse-emotional comorbidities among young adults, we developed an internet-based integrated treatment called Take Care of Me. Although the treatment had an impact on several secondary outcomes, effects were not observed for the primary outcome. Therefore, the goal of the current study was to examine heterogeneity in treatment responses. The initial RCT randomized participants to either a treatment or psychoeducational control condition. We conducted an exploratory latent class analysis to distinguish individuals based on pre-treatment risk and then used moderated regressions to examine differential treatment responses based on class membership. We found evidence for three distinct groups. Most participants fell in the “low severity” group (n = 123), followed by the “moderate severity” group (n = 57) who had a higher likelihood of endorsing a previous mental health diagnosis and treatment and higher symptom severity than the low group. The “high severity” group (n = 42) endorsed a family history of alcoholism, and the highest symptom severity and executive dysfunction. Moderated regressions revealed significant class differences in treatment responses. In the treatment condition, high severity (relative to low) participants reported higher alcohol consumption and hazardous drinking and lower quality of life at follow-up, whereas moderate severity (relative to low) individuals had lower alcohol consumption at follow-up, and lower hazardous drinking at end-of-treatment. No class differences were found for participants in the control group. Higher risk individuals in the treatment condition had poorer responses to the program. Tailoring interventions to severity may be important to examine in future research.

A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD.

Alterations in white matter microstructure in alcohol and alcohol‐polydrug dependence: Associations with lifetime alcohol and nicotine exposure

Evidence suggests that alcohol dependence (AD) is associated with microstructural deficits in white matter, but the relationship with lifetime alcohol exposure and the impact of polydrug dependence is not well understood. Using diffusion tensor magnetic resonance (MR) imaging, we examined white matter microstructure in relation to alcohol and polydrug dependence using data from the Imperial College Cambridge Manchester (ICCAM) platform study. Tract‐based spatial statistics were used to examine fractional anisotropy (FA) in a cohort of abstinent AD participants, most of whom had a lifetime history of dependence to nicotine. A further subgroup also had a lifetime history of dependence to cocaine and/or opiates. Individuals with AD had lower FA throughout the corpus callosum, and negative associations with alcohol and nicotine exposure were found. A group‐by‐age interaction effect was found showing greater reductions with age in the alcohol‐dependent group within corpus callosum, overlapping with the group difference. We found no evidence of recovery with abstinence. A comparison of alcohol‐only‐ and alcohol‐polydrug‐dependent groups found no differences in FA. Overall, our findings show that AD is associated with lower FA and suggest that these alterations are primarily driven by lifetime alcohol consumption and cigarette smoking, showing no relationship with exposure to other substances such as cocaine, opiates or cannabis. Reductions in FA across the adult lifespan are more pronounced in AD and offer further support for the notion of accelerated ageing in relation to alcohol dependence. These findings highlight there may be lasting structural differences in white matter in alcohol dependence, despite continued abstinence.

An exploration of multivariate symptom clusters of cannabis use disorder in young adults

AIMS

Since the release of the DSM-V, CUD has been understood as a unidimensional construct. However, continued research has identified separate symptom clusters relating to consumption, loss of control, and withdrawal within substance use disorder criteria that may pose separate risk factors and functional difficulties. The current study aims to examine how symptom clusters commonly manifest in young adults that use cannabis using a latent class analysis (LCA) and explore how these clusters are related to co-occurring psychological constructs.

METHODS

1174 (aged 18-34) participants completed a battery of assessments on substance use and other psychological constructs. LCA was conducted on 17 symptoms corresponding with DSM-V CUD criteria. Multinomial regressions were used to examine class membership and commonly co-occurring psychopathology and psychological constructs.

RESULTS

LCA results identified a 'No problems' class, a 'Moderate consumption' class characterized by moderate probability of endorsing consumption items, a 'Consumption with Moderate Loss of Control' class, characterized by endorsing consumption and loss of control items but minimal endorsement of withdrawal items, a 'Consumption with Moderate Withdrawal' class characterized by moderate probability of endorsing all item types, and 'High Consumption, Loss of Control, Withdrawal' class characterized by high probability of endorsing all items. Multinomial regressions indicated some class differences in psychological constructs.

CONCLUSIONS

Symptom clusters differed in terms of CUD criteria, especially for those in our sample with moderate/severe problems. Findings suggest intervention efforts may benefit from treatment targeted at various presentations of CUD.

Identifying alcohol misuse biotypes from neural connectivity markers and concurrent genetic associations

Alcohol use behaviors are highly heterogeneous, posing significant challenges to etiologic research of alcohol use disorder (AUD). Magnetic resonance imaging (MRI) provides intermediate endophenotypes in characterizing problem alcohol use and assessing the genetic architecture of addictive behavior. We used connectivity features derived from resting state functional MRI to subtype alcohol misuse (AM) behavior. With a machine learning pipeline of feature selection, dimension reduction, clustering, and classification we identified three AM biotypes-mild, comorbid, and moderate AM biotypes (MIA, COA, and MOA)-from a Human Connectome Project (HCP) discovery sample (194 drinkers). The three groups and controls (397 non-drinkers) demonstrated significant differences in alcohol use frequency during the heaviest 12-month drinking period (MOA > MIA; COA > non-drinkers) and were distinguished by connectivity features involving the frontal, parietal, subcortical and default mode networks. Further, COA relative to MIA, MOA and controls endorsed significantly higher scores in antisocial personality. A genetic association study identified that an alcohol use and antisocial behavior related variant rs16930842 from LINC01414 was significantly associated with COA. Using a replication HCP sample (28 drinkers and 46 non-drinkers), we found that subtyping helped in classifying AM from controls (area under the curve or AUC = 0.70, P < 0.005) in comparison to classifiers without subtyping (AUC = 0.60, not significant) and successfully reproduced the genetic association. Together, the results suggest functional connectivities as important features in classifying AM subgroups and the utility of reducing the heterogeneity in connectivity features among AM subgroups in advancing the research of etiological neural markers of AUD.

Is lower severity alcohol use disorder qualitatively different than more severe manifestations? An evaluation of multivariate symptom clusters

BACKGROUND AND AIMS

Alcohol use disorder (AUD), since the release of DSM-V, is conceptualized and studied as a unidimensional construct. However, previous research has identified clusters of AUD symptoms related to excessive consumption/tolerance, loss of control/social dysfunction and withdrawal/craving that have shown differential genetic risks, personality associations and predictive ability. Although past 'variable-centered' (e.g. factor-analytic) studies have demonstrated the importance of these clusters, the current study aimed to examine how these clusters commonly manifest using a 'person-centered' approach (e.g. latent class).

DESIGN

Cross-sectional in-person assessment.

SETTING

Indiana, USA.

PARTICIPANTS

A convenience sample of 1390 young adults (mean age = 21.43, SD = 2.47) recruited for an over-representation of alcohol problems (65% with AUD).

MEASUREMENTS

Latent class analysis (LCA) was conducted on 23 criteria from the Semi-Structured Interview on the Genetics of Alcoholism (SSAGA) that align with DSM-V AUD symptoms. Identified latent classes were characterized using multinomial regressions to examine the association of class and measures of alcohol use, other externalizing psychopathology, internalizing problems and personality.

FINDINGS

LCA results identified a 'Low Problems' class (34% of sample), a 'Heavy Consumption' class (26%) characterized by high endorsement probabilities of essentially only consumption/tolerance symptoms, a 'Consumption and Loss of Control' class (31%) characterized by endorsing consumption/tolerance and loss of control/social dysfunction symptoms, and finally a 'Consumption, Loss of Control and Withdrawal' class (9%) characterized by high endorsement probabilities of all symptom clusters. Multinomial regression results indicated an increasing spectrum of severity in terms of psychological impairment.

CONCLUSIONS

AUD appears to manifest as different clusters of symptoms at different severity levels.

Externalizing personality characteristics define clinically relevant subgroups of alcohol use disorder

AIMS

Higher levels of externalizing characteristics, i.e. impulsivity, novelty seeking and aggression, could contribute to the development, progression and severity of alcohol use disorder (AUD). The present study aims to explore whether these externalizing characteristics together have a potential group-forming role in AUD using latent profile analysis (LPA).

METHODS

Externalizing characteristics of 102 AUD patients were analyzed using LPA to explore the group-forming role of externalizing symptoms; groups were compared in terms of demographic and alcohol-related variables, indices of psychopathological, depressive and anxiety symptom severity.

RESULTS

LPA revealed and supported a two-group model based on externalizing symptoms. The group with higher levels of externalizing symptoms showed significantly elevated levels of alcohol-related and anxio-depressive symptoms.

CONCLUSIONS

Externalizing characteristics converge and have a group-forming role in chronic AUD, and are associated with a more severe form of AUD. By making the diagnostic category less heterogeneous, these different subtypes within AUD may provide aid in tailoring treatments to patients' specific needs.

Epidemiology of comorbid hazardous alcohol use and insomnia in 19 185 women and men attending the population-based Tromsø Study 2015-2016

Background

Hazardous alcohol use is known to be comorbid with insomnia problems. The present study examined the prevalence of insomnia and if the odds of insomnia differed between women and men with a hazardous alcohol use.

Methods

Cross-sectional data from the seventh survey of the Norwegian population-based Tromsø Study 2015–2016 (participation 65%). The sample included 19 185 women and men 40–96 years. Hazardous alcohol use was defined by the Alcohol Use Disorder Identification Test (AUDIT) and insomnia by the Bergen Insomnia Scale. Covariates included socio-demographics, shift work, somatic conditions and mental distress defined by Hopkins Symptom Check List-10 (HSCL-10). Mental distress was also included as a moderator.

Results

Insomnia was more prevalent among participants with a hazardous alcohol use (24.1%) than without (18.9%), and participants who had hazardous alcohol use had higher odds of insomnia (odds ratio = 1.49, 95% CI = 1.20, 1.85). The association turned non-significant after adjustment for mental distress. Adding mental distress as a moderator variable revealed a higher odds of insomnia among hazardous alcohol users having no or low-to-medium levels of mental distress, but not among participants with high levels of mental distress.

Conclusion

Insomnia was more prevalent among women and men reporting hazardous alcohol use. When mental distress was treated as a moderator, hazardous alcohol use did not yield higher odds for insomnia among those with high levels of mental distress. This suggests that mental distress may play an important role in the association between hazardous alcohol use and insomnia. And that the impact of alcohol on insomnia may differ depending on the severity of mental distress.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13250-5.

Patterns and temporal change of psychopathological symptoms among inpatients with alcohol use disorder undergoing a twelve-step based treatment

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Psychopathological symptom profiles and trajectories were examined among AUD inpatients.

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Three quantitatively different subgroups were identified in terms of psychopathological symptoms.

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Classes were discriminated by different psychopathological symptom change trajectories.

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Subgroups with more severe psychopathological symptoms used alcohol in a more harmful way.

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Drinking of the more severely affected classes were more motivated by coping and conformity motives.

Background

Patients diagnosed with Alcohol Use Disorder (AUD) present an increased risk for experiencing severe internalizing and externalizing symptoms. Involvement in twelve-step based treatment programs, such as the Minnesota Model (MM), can contribute to improvement of an individual’s psychopathological symptom profile. The present study’s main objective was to examine profiles and change trajectories of psychopathological symptoms of AUD subgroups during an eight-week long period of MM treatment attendance.

Method

Inpatients with AUD (N = 303) who attended MM treatment programs participated in the present study. Latent Class Growth Analysis (LCGA) was used to evaluate the psychopathological symptom change trajectories assessed by using the Brief Symptom Inventory (BSI). Multiple comparisons and multinomial logistic regression were performed to validate the subgroups.

Results

Three subgroups were identified: low severity (48.5%), moderate severity (35.2%), and high severity (16.2%) symptomatic subgroups. The moderate severity class demonstrated the largest effect in terms of symptoms decrease. Higher severity classes showed significantly higher rates of harmful alcohol drinking and drinking motives.

Conclusions

The present study identified three severity-based subgroups which indicate that psychopathology sits on a spectrum of severity among AUD patients. The findings highlight the associations between AUD and internalizing symptoms, negative reinforcement drinking motives, and the symptomatic improvement that can occur among those participating in MM treatment programs.