Association of major depression with subtypes of nicotine dependence found among adult daily smokers: a latent class analysis

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.

Subtypes of smokers in a randomized controlled trial of a web-based smoking cessation program and their role in predicting intervention non-usage attrition: Implications for the development of tailored interventions

INTRODUCTION

Web-based smoking interventions hold potential for smoking cessation; however, many of them report low intervention usage (i.e., high levels of non-usage attrition). One strategy to counter this issue is to tailor such interventions to user subtypes if these can be identified and related to non-usage attrition outcomes. The aim of this study was two-fold: (1) to identify and describe a smoker typology in participants of a web-based smoking cessation program and (2) to explore subtypes of smokers who are at a higher risk for non-usage attrition (i.e., early dropout times).

METHODS

We conducted secondary analyses of data from a large randomized controlled trial (RCT) that investigated effects of a web-based Cognitive Bias Modification intervention in adult smokers. First, we conducted a two-step cluster analysis to identify subtypes of smokers based on participants' baseline characteristics (including demographics, psychological and smoking-related variables, N = 749). Next, we conducted a discrete-time survival analysis to investigate the predictive value of the subtypes on time until dropout.

RESULTS

We found three distinct clusters of smokers: Cluster 1 (25.2%, n = 189) was characterized by participants being relatively young, highly educated, unmarried, light-to-moderate smokers, poly-substance users, and relatively high scores on sensation seeking and impulsivity; Cluster 2 (41.0%, n = 307) was characterized by participants being older, with a relatively high socio-economic status (SES), moderate-to-heavy smokers and regular drinkers; Cluster 3 (33.8%, n = 253) contained mostly females of older age, and participants were further characterized by a relatively low SES, heavy smoking, and relatively high scores on hopelessness, anxiety sensitivity, impulsivity, depression, and alcohol use. Additionally, Cluster 1 was more likely to drop out at the early stage of the intervention compared to Cluster 2 (adjusted Hazard Ratio (HR _adjusted) = 1.51, 95% CI = [1.25, 1.83]) and Cluster 3 (HR _adjusted = 1.52, 95% CI = [1.25, 1.86]).

CONCLUSIONS

We identified three clusters of smokers that differed on a broad range of characteristics and on intervention non-usage attrition patterns. This highlights the heterogeneity of participants in a web-based smoking cessation program. Also, it supports the idea that such interventions could be tailored to these subtypes to prevent non-usage attrition. The subtypes of smokers identified in this study need to be replicated in the field of e-health outside the context of RCT; based on the smoker subtypes identified in this study, we provided suggestions for developing tailored web-based smoking cessation intervention programs in future research.

Depression symptom profiles and long-term response to cognitive behavioral therapy plus contingency management for smoking cessation

BACKGROUND

Depression is heterogeneous in nature and using diagnostic categories limits insight into understanding psychopathology and its impact on treatment efficacy. This secondary analysis sought to: 1) identify distinct subpopulations of cigarette users with depression, and 2) examine their response to cognitive-behavioral treatment (CBT) + contingency management (CM) for smoking cessation at one year.

METHOD

The sample comprised 238 (74 % females) adults who smoke receiving CBT only or CBT + CM. A latent class analysis was conducted on baseline depressive symptoms measured using the Beck Depression Inventory-II. Generalized estimating equations assessed the main and interactive effects of class, time, treatment, and sex on smoking abstinence.

RESULTS

Three distinct classes were identified: C1 (n= 76/238), characterized by mild depression, loss of energy, pessimism, and criticism, C2 (n= 100/238) presenting moderate severity and decreased appetite, and C3 (n= 62/238) showing severe depression, increased appetite, and feelings of punishment. There was a significant cluster × treatment interaction, which indicated additive effects of CM over CBT alone for Class 1 and 2. Persons in Class 1 and 2 were 3.60 [95 % CI: 1.62, 7.97] and 2.65 [95 % CI: 1.19, 5.91] times more likely to be abstinent if CBT + CM was delivered rather than CBT only. No differential sex effects were observed on treatment response according to cluster.

CONCLUSIONS

Profiling depression symptom subtypes of cigarette users may be more informative to improve CM treatment response than merely focusing on total scores.

Differentiation of 2 Obsessive-Compulsive Disorder Subgroups with Regard to Demographic and Phenomenological Characteristics Combining Multiple Correspondence and Latent Class Analysis

INTRODUCTION

Classic factor analysis of obsessive-compulsive disorder (OCD) dimensions and attempts to identify valid subgroups have not yet produced definitive conclusions.

OBJECTIVE AND METHODS

This study aims to examine possible homogeneous subgrouping of demographic and phenomenological characteristics in 134 treatment-seeking OCD patients. A combination of multiple correspondence analysis (MCA) and latent class analysis (LCA) was used.

RESULTS

MCA showed 2 distinct subgroups of OCD patients and LCA confirmed this result by a two-class solution. Both analyses demonstrated (a) a clear subgroup of female patients with washing compulsions, obsessions related to contamination, and late age of onset and (b) a subgroup comprised mostly of male patients with earlier onset of OCD, checking rituals, and doubts or aggressive obsessions. Mental, ordering, hoarding compulsions, religious, or sexual obsessions and images appeared exclusively in this subgroup.

CONCLUSIONS

Using 2 different analytic methods, we confirmed at least 2 subgroups in a clinical sample of Greek OCD patients. Future research combining dimensional and latent approaches could facilitate our understanding of the heterogeneous phenotype of OCD.

Work Stress and Depressive Symptoms in Fishermen With a Smoking Habit: A Mediator Role of Nicotine Dependence and Possible Moderator Role of Expressive Suppression and Cognitive Reappraisal

This study examined pathways of influence between work stress, depressive symptoms, nicotine dependence, expressive suppression, and cognitive reappraisal in fishermen with smoking habits in Qionghai, Hainan province, China (N = 1068). These fishermen responded to multiple assessments a week before leaving on a deep-sea fishing trip, including a Mental Stressor Investigation Questionnaire (MSIQ), the Center for Epidemiological Studies Depression Scale (CES-D), the Russell Reason for Smoking Questionnaire (RRSQ), and an Emotion Regulation Questionnaire (ERQ). Structural equation modeling (SEM) analyses of the collected data in Mplus 7 showed that work stress and nicotine dependence were independent predictors of depressive symptoms. The relationship between work stress and depressive symptoms was found to be partially mediated by nicotine dependence and be moderated by cognitive reappraisal. The evidence suggests it advantageous to examine the need of work stress, nicotine dependence, and cognitive reappraisal when attempting to understand depressive symptoms in fishermen with a smoking habit. These findings suggest that improving nicotine dependence through work stress management and training in cognitive reappraisal could be utilized as effective modalities for improving depressive symptoms.

Types of Smokers Who Seek Smoking Cessation Treatment According to Psychopathology

Psychopathology and psychological distress have been shown to be related to poor smoking cessation outcomes and abstinence maintenance. Thus, it is important to identify individuals with high levels of psychopathology before undergoing smoking cessation treatment in order to increase their likelihood of success.

OBJECTIVE

The primary aim of the present study was to analyze whether we could classify smokers by using self-reported measures of psychopathology. In addition, a secondary aim was to examine if there were significant differences among the groups of smokers regarding sociodemographic information, nicotine dependence, and cessation rates at the end of treatment and at 6- and 12-month follow-ups.

METHODS

Participants were 281 smokers seeking smoking cessation treatment. Participants were classified into different smoking groups by using a 2-step cluster analysis based on baseline scores on the Restructured Clinical (RC) scales of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF), Beck Depression Inventory-II (BDI-II), and State-Trait Anxiety Inventory (STAI).

RESULTS

Smokers were classified into 3 groups according to levels of psychopathology: Low (n = 158), Intermediate (n = 78), and High (n = 45). Smokers in the High Group were more likely to present higher levels of psychopathology and to continue smoking at the end of treatment when compared with the two other clusters. In addition, smokers classified in this group were more likely to be nicotine dependent and from a low social class.

CONCLUSIONS

A subgroup of smokers can be easily identified through self-report measures of psychopathology. Furthermore, these individuals were more likely to continue smoking at the end of treatment. This suggests that this group with high levels of psychopathology might benefit from future interventions that are more intensive or cessation treatments targeted to their specific characteristics.

Temporal sequencing of nicotine dependence and major depressive disorder: A U.S. national study

Major Depressive Disorder (MDD) and Nicotine dependence (ND) often co-occur. However, little attention has been given to the temporal order between the two disorders. We compared the sociodemographic and clinical characteristics of individuals whose onset of ND preceded (ND-prior) or followed the onset of MDD (MDD-prior). Binary logistic regression models were computed to compare ND-prior (n=546) and MDD-prior (n=801) individuals from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, n=43,093). We found that MDD-prior were more likely to have a history of suicide attempts and a family history of both depression and antisocial behavior, to have had psychiatric hospitalization, and to have an earlier age of onset of the first depressive episode; but a later age of onset for both daily smoking and ND. On average, MDD-prior individuals showed a significantly longer transition time from daily smoking to ND (15.6±0.6 vs. 6.9±0.4 years, P<0.001). In contrast, ND-prior subjects had a significantly greater proportion of withdrawal symptoms, and of lifetime alcohol use or alcohol use disorder. We conclude that the phenomenology and course of ND and MDD vary significantly, depending on which disorder had earlier onset.

Determining non-cigarette tobacco, alcohol, and substance use typologies across menthol and non-menthol smokers using latent class analysis

Background

Substance use and mental health are robustly associated with smoking and poor cessation outcomes, but not often examined in combination with menthol cigarette smoking, which is also associated with lower quit rates. This study identified classes of Black and White menthol and non-menthol cigarette smokers based on demographics, alcohol, drug, and other tobacco use behaviors.

Methods

Using screening data from two studies, latent class analysis (LCA) was conducted to classify n = 1177 menthol and non-menthol cigarette smokers on demographic characteristics, heavy smoking, alcohol and drug use, desire to quit smoking, other tobacco product use, and use of psychotropic medication.

Results

Three latent classes were identified that differentiated smokers on substance use, menthol cigarette smoking, and other tobacco use behavior. One class consisted primarily of young adults who used a wide array of other tobacco products, reported the highest prevalence of other drug use, and showed the lowest desire to quit smoking cigarettes in the next 6-months. Class 2 comprised primarily of Black male menthol smokers, all of whom used cigarillos in addition to cigarettes, and who displayed moderate drug use. The third class was categorized as primarily older cigarette smokers, who engaged in very little other tobacco use or drug use, but who were most likely to self-report being prescribed psychotropic medication.

Conclusions

LCA allowed for the identification of distinct classes of smokers based on factors related to poor cessation outcomes, including menthol use, that have not previously been examined in combination. Interventions should target specific groups of smokers, rather than take a “one size fits all” approach.

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Waves 1 and 2: review and summary of findings

PURPOSE

The NESARC, a "third-generation" psychiatric epidemiologic survey that integrated detailed measures of alcohol and drug use and problems has been the data source for over >850 publications. A comprehensive review of NESARC findings and their implications is lacking.

METHOD

NESARC was a survey of 43,093 participants that covered alcohol, drug and psychiatric disorders, risk factors, and consequences. Wave 1 of the NESARC was conducted in 2001-2002. Three years later, Wave 2 follow-up re-interviews were conducted with 34,653 of the original participants. Scopus and Pubmed were used to search for NESARC papers, which were sorted into topic areas and summarized.

RESULT

The most common disorders were alcohol and posttraumatic stress disorders, and major depression. Females had more internalizing disorders and males had more externalizing disorders, although the preponderance of males with alcohol disorders (the "gender gap") was less pronounced than it was in previous decades. A race/ethnic "paradox" (lower risk among disadvantaged minorities than whites) remains unexplained. Younger participants had higher risk for substance and personality disorders, but not unipolar depressive or anxiety disorders. Psychiatric comorbidity was extensive and often formed latent trans-diagnostic domains. Since 1991-1992, risk for marijuana and prescription drug disorders increased, while smoking decreased, although smoking decreases were less pronounced among those with comorbidity. A nexus of comorbidity, social support, and stress predicted transitions in diagnostic status between Waves 1 and 2. Childhood maltreatment predicted psychopathology. Alcohol and drug use disorders were seldom treated; attitudinal barriers (little perceived need, perceived alcoholism stigma, pessimism about efficacy) were more important in predicting non-treatment than financial barriers.

CONCLUSIONS

Understanding comorbidity and the effects of early stressors will require research incorporating biologic components, e.g., genetic variants and brain imaging. The lack of treatment for alcohol and drug disorders, predicted by attitudinal rather than financial variables, suggests an urgent need for public and professional education to reduce the stigma associated with these disorders and increase knowledge of treatment options.

Effect of variation in BDNF Val(66)Met polymorphism, smoking, and nicotine dependence on symptom severity of depressive and anxiety disorders

BACKGROUND

Smoking, especially nicotine dependence is associated with more severe symptoms of depression and anxiety disorders. However, the mechanisms underlying this association are unclear. We investigated the effect of brain-derived neurotrophic factor (BDNF) Val(66)Met polymorphism on the severity of depressive and anxiety symptoms in never-smokers, former smokers, non-dependent, and nicotine-dependent smokers with a current diagnosis of depression and/or anxiety.

METHODS

Patients with depressive or anxiety disorders and with available BDNF Val(66)Met polymorphism data (N=1271) were selected from Netherlands Study of Depression and Anxiety (NESDA). Dependent variables were severity of symptoms. Independent variables were smoking status and BDNF genotype. Age, sex, education, recent negative life events, alcohol use, body mass index, and physical activity were treated as covariates.

RESULTS

After controlling for covariates, nicotine-dependent smokers had more severe depressive symptoms than non-dependent smokers, former and never-smokers. The latter three groups did not differ in severity of depression. In Val(66)Val carriers, nicotine-dependent smokers had more severe symptoms of depression and anxiety than the other three groups, which were comparable in symptom severity. In Met(66) carriers, there were no group differences on severity of depression and anxiety. Nicotine dependence was the strongest predictor of severity of symptoms only in Val(66)Val carriers.

CONCLUSIONS

In patients with a current diagnosis of depression or anxiety, the relationship between nicotine dependence and symptom severity may be moderated by BDNF Val(66)Met. These results suggest that inherent genetic differences may be crucial for the worse behavioral outcome of nicotine, and that Val(66)Val carriers may benefit most in mental health from smoking cessation.

A population-based twin study of the genetic and environmental relationship of major depression, regular tobacco use and nicotine dependence

BACKGROUND

Numerous epidemiological studies have reported a positive association between major depression (MD) and regular tobacco use (RU) or nicotine dependence (ND). However, few have used a genetically informative design to assess whether these traits share a common genetic and/or environmental liability.

METHOD

We assessed MD, RU and ND in same-sex twins from the population-based Swedish Twin Registry. In males, we examined both cigarette use and snus (smokeless tobacco) use. We used structural equation modeling to examine the relationship between MD, RU, and ND given RU.

RESULTS

The results suggest modest correlations between MD and RU, and between MD and ND. In males, the liability shared between MD and RU is solely genetic for both cigarettes and snus, while MD and ND share both genetic and unique environmental influences. The continuation to ND given RU differed considerably between cigarette and snus users. In females, both MD-RU and MD-ND relationships are partially attributable to genetic and unique environmental correlations.

CONCLUSIONS

The relationship among MD, RU and ND is at least partially attributable to shared genetic and environmental risk factors. The genetic and environmental correlations between traits are modest. The nature of the shared liability differs by sex, and in males, by the type of tobacco product used. Differences between previous reports and results presented in the current study are suggestive of population differences in how MD and tobacco use inter-relate.

Subtypes of smokers who attend psychological treatment in order to stop smoking

The aim of this study is to identify subtypes of smokers who attended psychological treatment during the period 2006-2008 for smoking cessation from a sample of current smokers (N = 202) from Galicia, Spain. Eight instruments were used for data collection. Demographic variables, smoking variables, and psychopathological characteristics were clustered to establish typologies of smokers. A two-phase cluster analysis identified two subtypes of smokers (141 in Cluster 1 and 61 in Cluster 2). Those in Cluster 2 were younger, and had made an attempt to quit in the last year. They presented higher levels of nicotine dependence and psychopathology than those in Cluster 1. Differences in nicotine withdrawal syndrome, cigarette consumption at the end of the treatment, and adherence to the treatment were significant across the two clusters.

Latent class analysis of the Yale-Brown Obsessive-Compulsive Scale symptoms in obsessive-compulsive disorder

OBJECTIVE

Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous, and findings of underlying structure classification based on symptom grouping have been ambiguous to date. Variable-centered approaches, primarily factor analysis, have been used to identify homogeneous groups of symptoms; but person-centered latent methods have seen little use. This study was designed to uncover sets of homogeneous groupings within 1611 individuals with OCD based on symptoms.

METHOD

Latent class analysis models using 61 obsessive-compulsive symptoms collected from the Yale-Brown Obsessive-Compulsive Scale were fit. Relationships between latent class membership and treatment response, sex, symptom severity, and comorbid tic disorders were tested for relationship to class membership.

RESULTS

Latent class analysis models of best fit yielded 3 classes. Classes differed only in frequency of symptom endorsement. Classes with higher symptom endorsement were associated with earlier age of onset, being male, higher Yale-Brown Obsessive-Compulsive Scale symptom severity scores, and comorbid tic disorders. There were no differences in treatment response between classes.

CONCLUSIONS

These results provide support for the validity of a single underlying latent OCD construct, in addition to the distinct symptom factors identified previously via factor analyses.

Subtypes of sleep disturbance: associations among symptoms, comorbidities, treatment, and medical costs

Medical claims and survey data were used to evaluate patients with sleep disturbance lasting 1 year or more, and to identify subtypes of sleep disturbance using latent class analysis. Four subtypes were identified from the 1,374 patients. Subtypes differed on the number of sleep disturbance symptoms, presence of non-restorative sleep and comorbidities, degree of daytime impairment, and insomnia severity. The results from this study suggest that patient-reported symptoms of sleep disturbance, the frequency of symptoms, functional impairment, and comorbid conditions are important elements in distinguishing among groups of patients with varying degrees of sleep problems. These data provide evidence that the Insomnia Severity Index (ISI) varies accordingly with the frequency and resulting impairment of symptoms captured in the 4 clusters.

Differences in negative mood-induced smoking reinforcement due to distress tolerance, anxiety sensitivity, and depression history

RATIONALE

Negative mood increases smoking reinforcement and may do so to a greater degree in smokers vulnerable to negative mood dysregulation.

METHODS

Adult smokers (N = 71) without current depression were randomly assigned to one of two smoking conditions (nicotine or denic cigarettes, presented blind) maintained across all sessions. Subjects completed one neutral mood session and four negative mood induction sessions. Negative mood inductions included one each of the following: 1) overnight smoking abstinence, 2) challenging computer task, 3) public speech preparation, 4) watching negative mood slides. In each session, subjects took 4 puffs on their assigned cigarette, rated it for "liking" (reward), and then smoked those cigarettes ad libitum (reinforcement) during continued mood induction. Affect was assessed intermittently before and after smoking. Differences in responses were examined as functions of self-reported history of major depression and levels of distress tolerance and anxiety sensitivity.

RESULTS

Smoking reinforcement, but not reward or negative affect relief, was greater in all sessions in those with a history of depression and greater after overnight abstinence in those with lower distress tolerance. Reward and affect relief, but not reinforcement, were greater during speech preparation among those high in anxiety sensitivity.

CONCLUSIONS

Low distress tolerance may enhance acute smoking reinforcement due to abstinence, while depression history may broadly increase acute smoking reinforcement regardless of mood. Neither smoking reward nor affect help explain these individual differences in smoking reinforcement.