Prediction of alcohol use disorder using personality disorder traits: a twin study

Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features

Memory problems are common among older adults with a history of alcohol use disorder (AUD). Employing a machine learning framework, the current study investigates the use of multi-domain features to classify individuals with and without alcohol-induced memory problems. A group of 94 individuals (ages 50-81 years) with alcohol-induced memory problems (the memory group) were compared with a matched control group who did not have memory problems. The random forests model identified specific features from each domain that contributed to the classification of the memory group vs. the control group (AUC = 88.29%). Specifically, individuals from the memory group manifested a predominant pattern of hyperconnectivity across the default mode network regions except for some connections involving the anterior cingulate cortex, which were predominantly hypoconnected. Other significant contributing features were: (i) polygenic risk scores for AUD, (ii) alcohol consumption and related health consequences during the past five years, such as health problems, past negative experiences, withdrawal symptoms, and the largest number of drinks in a day during the past twelve months, and (iii) elevated neuroticism and increased harm avoidance, and fewer positive "uplift" life events. At the neural systems level, hyperconnectivity across the default mode network regions, including the connections across the hippocampal hub regions, in individuals with memory problems may indicate dysregulation in neural information processing. Overall, the study outlines the importance of utilizing multidomain features, consisting of resting-state brain connectivity data collected ~18 years ago, together with personality, life experiences, polygenic risk, and alcohol consumption and related consequences, to predict the alcohol-related memory problems that arise in later life.

Comparing Differences between Two Groups of Adolescents Hospitalized for Self-Harming Behaviors with and without Personality Disorders

Self-harm (non-suicidal self-injury (NSSI) and suicidal behavior (SB)) is frequent display during adolescence. Patients with personality disorders (PDs) frequently self-harm. However, few studies have focused on the role of PDs in self-harming adolescents. In this study, we collected 79 adolescents hospitalized due to self-harm (88.6% female; 78.5% Caucasian) and divided them into two groups, with or without a diagnosis of PD. The socio-demographic and psychological-clinical data were collected through a structured interview by clinicians. Univariate, subgroup, and multiple logistic regression analyses were performed. Univariate analysis showed that adolescents with a PD and self-harm had (1) an older age at hospitalization (p < 0.01); (2) experienced physical and sexual abuse (p = 0.05, and p < 0.01, respectively); (3) ADHD (p = 0.05); (4) a greater number of SA (p < 0.01); and (5) probability of being a major NSSI patient (>20 lifetime NSSI episodes) (p < 0.01). After multivariate stratified analysis, the results indicated that an older age, and particularly major NSSI status were predictors of PD diagnosis. Early identification and a better understanding of the characteristics of adolescent PDs can assist clinicians in intervening earlier and developing more rational treatment strategies to reduce the long-term effects of PDs.

Alcohol consumption and telomere length: Mendelian randomization clarifies alcohol's effects

Alcohol's impact on telomere length, a proposed marker of biological aging, is unclear. We performed the largest observational study to date (in n = 245,354 UK Biobank participants) and compared findings with Mendelian randomization (MR) estimates. Two-sample MR used data from 472,174 participants in a recent genome-wide association study (GWAS) of telomere length. Genetic variants were selected on the basis of associations with alcohol consumption (n = 941,280) and alcohol use disorder (AUD) (n = 57,564 cases). Non-linear MR employed UK Biobank individual data. MR analyses suggested a causal relationship between alcohol traits, more strongly for AUD, and telomere length. Higher genetically-predicted AUD (inverse variance-weighted (IVW) β = -0.06, 95% confidence interval (CI): -0.10 to -0.02, p = 0.001) was associated with shorter telomere length. There was a weaker association with genetically-predicted alcoholic drinks weekly (IVW β = -0.07, CI: -0.14 to -0.01, p = 0.03). Results were consistent across methods and independent from smoking. Non-linear analyses indicated a potential threshold relationship between alcohol and telomere length. Our findings indicate that alcohol consumption may shorten telomere length. There are implications for age-related diseases.

Caffeine consumption, toxicity, tolerance and withdrawal; shared genetic influences with normative personality and personality disorder traits

Our main aim was to estimate the extent of overlapping etiology between caffeine consumption and response and normative and pathological personality. Linear mixed-effects models were used to identify normative personality domains and personality disorder (PD) traits for inclusion in multivariate twin analyses together with individual caffeine related measures. Data were obtained from Norwegian adult twins in a face-to-face interview conducted in 1999-2004 as part of a population-based study of mental health and through self-report in 2010-2011 and 2015-2017. Personality disorder data was available for 2,793 twins, normative personality for 3,889 twins, and caffeine for 3,862 twins (mean age 43.0 years). Normative personality was assessed using the self-reported Big Five Inventory, PD traits were assessed by the Structured Interview for DSM-IV Personality, and caffeine consumption, toxicity, tolerance, and withdrawal were assessed through a self-report questionnaire developed at the Norwegian Institute of Public Health. Caffeine measures were found to be moderately heritable, h2 = 30.1%-45.0%. All normative personality domains and four PD traits, antisocial, borderline, dependent and paranoid, were significantly associated with at least one caffeine variable. A small proportion of variance in caffeine consumption was attributable to genetic factors shared with normative personality (1.3%) and personality disorders (11.4%). A modest proportion of variance in caffeine tolerance and toxicity was attributable to genetic factors shared with both normative personality (26.9%, 24.8%) and personality disorders (21.0%, 36.0%). The present study found caffeine consumption and response to be heritable and provides evidence that a small to-modest proportion of this genetic etiology is shared with both normative and pathological personality. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Risk and resilience for alcohol use disorder revealed in brain functional connectivity

A family history of alcoholism (FH) increases risk for alcohol use disorder (AUD), yet many at-risk individuals never develop alcohol use problems. FH is associated with intermediate levels of risk phenotypes, whereas distinct, compensatory brain changes likely promote resilience. Although several cognitive, behavioral, and personality factors have been associated with AUD, the relative contributions of these processes and their neural underpinnings to risk or resilience processes remains less clear. We examined whole-brain resting-state functional connectivity (FC) and behavioral metrics from 841 young adults from the Human Connectome Project, including healthy controls, individuals with AUD, and their unaffected siblings. First, we identified functional connections in which unaffected siblings were intermediate between controls and AUD, indicating AUD risk, and those in which siblings diverged, indicating resilience. Canonical correlations relating brain risk and resilience FC to behavioral patterns revealed AUD risk and resilience phenotypes. Risk phenotypes primarily implicated frontal-parietal networks corresponding with executive function, impulsivity, externalizing behaviors, and social-emotional intelligence. Conversely, resilience-related phenotypes were underpinned by networks of medial prefrontal, striatal, temporal, brainstem and cerebellar connectivity, which associated with high trait attention and low antisocial behavior. Additionally, we calculated "polyphenotypic" risk and resilience scores, to investigate how the relative load of risk and resilience phenotypes influenced the probability of an AUD diagnosis. Polyphenotypic scores predicted AUD in a dose-dependent manner. Moreover, resilience phenotypes interacted with risk phenotypes, reducing their effects. The hypothesis-generating results revealed interpretable AUD-related phenotypes and offer brain-informed targets for developing more effective interventions.

Sex differences in factors predicting post-treatment opioid use

BACKGROUND AND AIMS

Several reports have documented risk factors for opioid use following treatment discharge, yet few have assessed sex differences, and no study has assessed risk using contemporary machine learning approaches. The goal of the present paper was to inform treatments for opioid use disorder (OUD) by exploring individual factors for each sex that are most strongly associated with opioid use following treatment.

DESIGN

Secondary analysis of Global Appraisal of Individual Needs (GAIN) database with follow-ups at 3, 6 and 12 months post-OUD treatment discharge, exploring demographic, psychological and behavioral variables that predict post-treatment opioid use.

SETTING

One hundred and thity-seven treatment sites across the United States.

PARTICIPANTS

Adolescents (26.9%), young adults (40.8%) and adults (32.3%) in treatment for OUD. The sample (n = 1,126) was 54.9% male, 66.1% white, 20% Hispanic, 9.8% multi-race/ethnicity, 2.8% African American and 1.3% other.

MEASUREMENT

Primary outcome was latency to opioid use over 1 year following treatment admission.

RESULTS

For women, regularized Cox regression indicated that greater withdrawal symptoms [hazard ratio (HR) = 1.31], younger age (HR = 0.88), prior substance use disorder (SUD) treatment (HR = 1.11) and treatment resistance (HR = 1.11) presented the largest hazard for post-treatment opioid use, while a random survival forest identified and ranked substance use problems [variable importance (VI) = 0.007], criminal justice involvement (VI = 0.006), younger age (VI = 0.005) and greater withdrawal symptoms (VI = 0.004) as the greatest risk factors. For men, Cox regression indicated greater conduct disorder symptoms (HR = 1.34), younger age (HR = 0.76) and multiple SUDs (HR = 1.27) were most strongly associated with post-treatment opioid use, while a random survival forests ranked younger age (VI = 0.023), greater conduct disorder symptoms (VI = 0.010), having multiple substance use disorders (VI = 0.010) and criminal justice involvement (VI = 0.006) as the greatest risk factors.

CONCLUSION

Risk factors for relapse to opioid use following opioid use disorder treatment appear to be, for women, greater substance use problems and withdrawal symptoms and, for men, younger age and histories of conduct disorder and multiple substance use disorder.

Alcohol use disorders and ADHD

Despite a growing literature on the complex bidirectional relationship of ADHD and substance use, reviews specifically focusing on alcohol are scarce. ADHD and AUD show a significant genetic overlap, including genes involved in gluatamatergic and catecholaminergic neurotransmission. ADHD drives risky behavior and negative experiences throughout the lifespan that subsequently enhance a genetically increased risk for Alcohol Use Disorders (AUD). Impulsive decisions and a maladaptive reward system make individuals with ADHD vulnerable for alcohol use and up to 43 % develop an AUD; in adults with AUD, ADHD occurs in about 20 %, but is vastly under-recognized and under-treated. Thus, routine screening and treatment procedures need to be implemented in AUD treatment. Long-acting stimulants or non-stimulants can be used to treat ADHD in individuals with AUD. However, it is crucial to combine medical treatment for ADHD with pharmacotherapy and psychotherapy for AUD, and other comorbid disorders. Identification of individuals at risk for AUD, especially those with ADHD and conduct disorder or oppositional defiant disorder, is a key factor to prevent negative outcomes.

Antisocial Personality Disorder Among Patients in Treatment for Alcohol Use Disorder (AUD): Characteristics and Predictors of Early Relapse or Drop-Out

Background

Patients with alcohol use disorders (AUD) vary significantly in many clinically important characteristics making them a heterogenous group. AUD patients with comorbid antisocial personality disorder (ASPD) form an important sub-group, and studies indicate that these patients may have poorer treatment outcomes. Therefore, we aimed to investigate the characteristics of AUD inpatients with comorbid ASPD and identify predictors of early relapse or treatment drop-out in these patients.

Methods

In a longitudinal study of AUD patients (n = 113; 30 females; aged 27 to 72 years) in treatment at three residential rehabilitation clinics in Norway, we used interviews and self-report questionnaires to collect data on alcohol use, mental health, and trauma experience. In addition, we assessed biochemical parameters. The patients were followed up at 6 weeks to identify early relapse or drop-out.

Results

Prevalence of ASPD among AUD patients was 15%. AUD patients with comorbid ASPD were exclusively male, of younger age, and reported more childhood trauma, and adult attention-deficit-hyperactivity-disorder symptoms. They reported more hazardous drinking behavior and more often had dependence on substances in addition to alcohol. The presence of ASPD did not predict early relapse or drop-out. However, early relapse or drop-out in ASPD patients was associated with childhood and adult trauma, younger age of drinking debut, and higher baseline prolactin levels.

Conclusion

AUD patients with ASPD had different clinical characteristics to other AUD patients and they had specific predictors of early relapse or drop-out. Our findings indicate that the early relapse or drop-out among AUD patients with ASPD may be attributed to environmental and possibly biological vulnerability. However, further studies with larger sample size are warranted to confirm these preliminary associations.

Familial factors and the risk of borderline personality pathology: genetic and environmental transmission

BACKGROUND

Parental characteristics and practices predict borderline personality disorder (BPD) symptoms in children. However, it is difficult to disentangle whether these effects are genetically or environmentally mediated. The present study examines the contributions of genetic and environmental influences by comparing the effects of familial risk factors (i.e. parental psychopathology and borderline traits, maladaptive parenting, marital discord) on child BPD traits in genetically related (biological) and non-related (adoptive) families.

METHODS

Data are from 409 adoptive and 208 biological families who participated in the Siblings Interaction and Behavior Study (SIBS) and 580 twin families the Minnesota Twin Family Study (MTFS). Parent characteristics and practices included parental psychopathology (measured via structured clinical interviews), parental BPD traits, parenting behaviors, and marital discord. A series of multi-level regression models were estimated to examine the relationship of familial risk factors to child BPD traits and to test whether children's adoptive status moderated the association.

RESULTS

Symptom counts of parents' conduct disorder, adult antisocial behavior, nicotine, alcohol, and illicit drug dependence, and paternal BPD traits substantially predicted child BPD traits only in biological offspring, implying genetic transmission. Maternal BPD traits and both maternal and paternal conflict, lack of regard, and lack of involvement predicted offspring BPD traits regardless of the adoptive status, implying environmental transmission.

CONCLUSIONS

Parental externalizing psychopathology and father's BPD traits contribute genetic risk for offspring BPD traits, but mothers' BPD traits and parents' poor parenting constitute environmental risks for the development of these offspring traits.

What's old is new again: updated findings on personality disorders and substance use disorders

PURPOSE OF REVIEW

Personality disorders, mental disorders marked by long-term deviations from societal expectations that cause distress, and substance use and related disorders (SUDs), mental disorders marked by engaging with substances or behaviors that activate the brain's reward system to the point that normal activities are neglected, are common debilitating conditions. Personality disorders and SUDs are highly comorbid, potentially resistant to treatment, and their presence increases all-cause mortality, particularly when found together.

RECENT FINDINGS

The present review highlights the most notable findings on prevalence, comorbidity, biological and behavioral pathways between the disorders, impact on incarcerated people and treatment for the disorders.

SUMMARY

Personality disorders and SUDs are relatively common, highly comorbid, and increase the risk of all-cause mortality: particularly in those who have both conditions. Possible shared pathways between personality disorders and SUDs include emotional dysregulation, shared genes, and certain neurotransmitters. Personality disorders and SUDs are common in people who have been incarcerated, and this morbidity and comorbidity has been found throughout the world. Finally, comorbidity between personality disorders and SUDs greatly complicates treatment, with emerging treatment modalities such as mentalization-based treatment, schema modes, and attentional training showing potential, but lacking strong evidence of efficacy.

Exploring the association between problem drinking and language use on Facebook in young adults

Recent literature suggests that variations in both formal and content aspects of texts shared on social media tend to reflect user-level differences in demographic, psychosocial, and behavioral characteristics. In the present study, we examined associations between language use on Facebook and problematic alcohol use. We collected texts shared on Facebook by a sample of 296 adult social media users (66.9% females; mean age = 28.44 years (SD = 7.38)). Texts were mined using the closed-vocabulary approach based on the Linguistic Inquiry Word Count (LIWC) semantic dictionary, and an open-vocabulary approach performed via Latent Dirichlet Allocation (LDA). Then, we examined associations between emerging textual features and alcohol-drinking scores as assessed using the AUDIT-C questionnaire. As a final aim, we employed the Random Forest machine-learning algorithm to determine and compare the predictive accuracy of closed- and open-vocabulary features over users' AUDIT-C scores. We found use of words about family, school, and positive feelings and emotions to be negatively associated with alcohol use and problematic drinking, while words suggesting interest in sport events, politics and economics, nightlife, and use of coarse language were more frequent among problematic drinkers. Results coming from LIWC and LDA analyses were quite similar, but LDA added information that could not be retrieved only with LIWC analysis. Furthermore, open-vocabulary features outperformed closed-vocabulary features in terms of predictive power over participants’ AUDIT-C scores (r = .46 vs. r = .28, respectively). Emerging relationships between text features and offline behaviors may have important implications for alcohol screening purposes in the online environment.

Alcohol use disorders

Alcohol use disorders consist of disorders characterised by compulsive heavy alcohol use and loss of control over alcohol intake. Alcohol use disorders are some of the most prevalent mental disorders globally, especially in high-income and upper-middle-income countries; and are associated with high mortality and burden of disease, mainly due to medical consequences, such as liver cirrhosis or injury. Despite their high prevalence, alcohol use disorders are undertreated partly because of the high stigma associated with them, but also because of insufficient systematic screening in primary health care, although effective and cost-effective psychosocial and pharmacological interventions do exist. Primary health care should be responsible for most treatment, with routine screening for alcohol use, and the provision of a staggered treatment response, from brief advice to pharmacological treatment. Clinical interventions for these disorders should be embedded in a supportive environment, which can be bolstered by the creation of alcohol control policies aimed at reducing the overall level of consumption.

A biologically-informed polygenic score identifies endophenotypes and clinical conditions associated with the insulin receptor function on specific brain regions

BACKGROUND

Activation of brain insulin receptors modulates reward sensitivity, inhibitory control and memory. Variations in the functioning of this mechanism likely associate with individual differences in the risk for related mental disorders (attention deficit hyperactivity disorder or ADHD, addiction, dementia), in agreement with the high co-morbidity between insulin resistance and psychopathology. These neurobiological mechanisms can be explored using genetic studies. We propose a novel, biologically informed genetic score reflecting the mesocorticolimbic and hippocampal insulin receptor-related gene networks, and investigate if it predicts endophenotypes (impulsivity, cognitive ability) in community samples of children, and psychopathology (addiction, dementia) in adults.

METHODS

Lists of genes co-expressed with the insulin receptor in the mesocorticolimbic system or hippocampus were created. SNPs from these genes (post-clumping) were compiled in a polygenic score using the association betas described in a conventional GWAS (ADHD in the mesocorticolimbic score and Alzheimer in the hippocampal score). Across multiple samples (n = 4502), the biologically informed, mesocorticolimbic or hippocampal specific insulin receptor polygenic scores were calculated, and their ability to predict impulsivity, risk for addiction, cognitive performance and presence of Alzheimer's disease was investigated.

FINDINGS

The biologically-informed ePRS-IR score showed better prediction of child impulsivity and cognitive performance, as well as risk for addiction and Alzheimer's disease in comparison to conventional polygenic scores for ADHD, addiction and dementia.

INTERPRETATION

This novel, biologically-informed approach enables the use of genomic datasets to probe relevant biological processes involved in neural function and disorders. FUND: Toxic Stress Research network of the JPB Foundation, Jacobs Foundation (Switzerland), Sackler Foundation.

Resting state connectivity best predicts alcohol use severity in moderate to heavy alcohol users

BACKGROUND

In the United States, 13% of adults are estimated to have alcohol use disorder (AUD). Most studies examining the neurobiology of AUD treat individuals with this disorder as a homogeneous group; however, the theories of the neurocircuitry of AUD call for a quantitative and dimensional approach. Previous imaging studies find differences in brain structure, function, and resting-state connectivity in AUD, but few use a multimodal approach to understand the association between severity of alcohol use and the brain differences.

METHODS

Adults (ages 22-60) with problem drinking patterns (n = 59) completed a behavioral and neuroimaging protocol at the National Institutes of Health. Alcohol severity was quantified with the Alcohol Use Disorders Identification Test (AUDIT). In a 3 T MRI scanner, participants underwent a structural MRI as well as resting-state, monetary incentive delay, and face matching fMRI scans. Machine learning was applied and trained using the neural data from MRI scanning. The model was tested for generalizability in a validation sample (n = 24).

RESULTS

The resting state-connectivity features model best predicted AUD severity in the naïve sample, compared to task fMRI, structural MRI, combined MRI features, or demographic features. Network connectivity features between salience network, default mode network, executive control network, and sensory networks explained 33% of the variance associated with AUDIT in this model.

CONCLUSIONS

These findings indicate that the neural effects of AUD vary according to severity. Our results emphasize the utility of resting state fMRI as a neuroimaging biomarker for quantitative clinical evaluation of AUD.

Genetically Informative Mediation Modeling Applied to Stressors and Personality-Disorder Traits in Etiology of Alcohol Use Disorder

A statistical mediation model was developed within a twin design to investigate the etiology of alcohol use disorder (AUD). Unlike conventional statistical mediation models, this biometric mediation model can detect unobserved confounding. Using a sample of 1410 pairs of Norwegian twins, we investigated specific hypotheses that DSM-IV personality-disorder (PD) traits mediate effects of childhood stressful life events (SLEs) on AUD, and that adulthood SLEs mediate effects of PDs on AUD. Models including borderline PD traits indicated unobserved confounding in phenotypic path coefficients, whereas models including antisocial and impulsive traits did not. More than half of the observed effects of childhood SLEs on adulthood AUD were mediated by adulthood antisocial and impulsive traits. Effects of PD traits on AUD 5‒10 years later were direct rather than mediated by adulthood SLEs. The results and the general approach contribute to triangulation of developmental origins for complex behavioral disorders.