Associations between childhood trauma, neurodevelopment, alcohol use disorder (AUD), and posttraumatic stress disorder (PTSD) are understudied during adolescence.

Using 1652 participants (51.75% female, baseline Mage = 14.3) from the Collaborative Study of the Genetics of Alcoholism, we employed latent growth curve models to (1) examine associations of childhood physical, sexual, and non-assaultive trauma (CPAT, CSAT, and CNAT) with repeated measures of alpha band EEG coherence (EEGc), and (2) assess whether EEGc trajectories were associated with AUD and PTSD symptoms. Sex-specific models accommodated sex differences in trauma exposure, AUD prevalence, and neural development.

In females, CSAT was associated with higher mean levels of EEGc in left frontocentral (LFC, ß = 0.13, p = 0.01) and interhemispheric prefrontal (PFI, ß = 0.16, p < 0.01) regions, but diminished growth in LFC (ß = −0.07, p = 0.02) and PFI (ß = −0.07, p = 0.02). In males, CPAT was associated with lower mean levels (ß = −0.17, p = 0.01) and increased growth (ß = 0.11, p = 0.01) of LFC EEGc. Slope of LFC EEGc was inversely associated with AUD symptoms in females (ß = −1.81, p = 0.01). Intercept of right frontocentral and PFI EEGc were associated with AUD symptoms in males, but in opposite directions. Significant associations between EEGc and PTSD symptoms were also observed in trauma-exposed individuals.

Childhood assaultive trauma is associated with changes in frontal alpha EEGc and subsequent AUD and PTSD symptoms, though patterns differ by sex and trauma type. EEGc findings may inform emerging treatments for PTSD and AUD.

Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol use, and binge drinking (BD) in daily life, and identifies the most important predictors.

A total of 120 patients (BN: 50; AUD: 51; BN/AUD: 19) participated in an experience sampling study, where over a period of 12 months they reported on their eating and drinking behaviors as well as on several other emotional, behavioral, and contextual factors in daily life. The study had a burst-measurement design, where assessments occurred eight times a day on Thursdays, Fridays, and Saturdays in seven bursts of three weeks. Afterwards, person-specific and pooled models were fit with elastic net regularized regression and evaluated with cross-validation. From these models, the variables with the 10% highest estimates were identified.

The person-specific models had a median AUC of 0.61, 0.80, and 0.85 for BE, alcohol use, and BD respectively, while the pooled models had a median AUC of 0.70, 0.90, and 0.93. The most important predictors across the behaviors were craving and time of day. However, predictors concerning social context and affect differed among BE, alcohol use, and BD.

Pooled models outperformed person-specific models and the models for alcohol use and BD outperformed those for BE. Future studies should explore how the performance of these models can be improved and how they can be used to deliver interventions in daily life.

Problematic drinking frequently co-occurs with depression among young adults, but often remains unaddressed in depression treatment. Evidence is insufficient on whether digital alcohol interventions can be effective in this young comorbid population. In a randomized controlled trial, we examined the effectiveness of Beating the Booze (BtB), an add-on digital alcohol intervention to complement depression treatment for young adults.

Participants were randomized to BtB + depression treatment as usual (BTB + TAU, n = 81) or TAU (n = 82). The primary outcome was treatment response, a combined measure for alcohol and depression after 6-month follow-up. Secondary outcomes were number of weekly drinks (Timeline Follow-back) and depressive symptoms (Center for Epidemiologic Studies Depression scale). Treatment response was analyzed using generalized linear modeling and secondary outcomes using robust linear mixed modeling.

Low treatment response was found due to lower than expected depression remission rates. No statistically significant between-group effect was found for treatment response after 6-month follow-up (odds ratio 2.86, p = 0.089, 95% confidence interval [CI] 0.85–9.63). For our secondary outcomes, statistically significant larger reductions in weekly drinks were found in the intervention group after 3-month (B = −4.00, p = 0.009, 95% CI −6.97 to −1.02, d = 0.27) and 6-month follow-up (B = −3.20, p = 0.032, 95% CI −6.13 to −0.27, d = 0.23). We found no statistically significant between-group differences on depressive symptoms after 3-month (B = −0.57, p = 0.732, 95% CI −3.83 to 2.69) nor after 6-month follow-up (B = −0.44, p = 0.793, 95% CI −3.69 to 2.82).

The add-on digital alcohol intervention was effective in reducing alcohol use, but not in reducing depressive symptoms and treatment response among young adults with co-occurring depressive disorders and problematic alcohol use.

Pre-registered on October 29, 2019 in the Overview of Medical Research in the Netherlands (OMON), formerly the Dutch Trial Register(https://onderzoekmetmensen.nl/en/trial/49219).

Although the link between alcohol involvement and behavioral phenotypes (e.g. impulsivity, negative affect, executive function [EF]) is well-established, the directionality of these associations, specificity to stages of alcohol involvement, and extent of shared genetic liability remain unclear. We estimate longitudinal associations between transitions among alcohol milestones, behavioral phenotypes, and indices of genetic risk.

Data came from the Collaborative Study on the Genetics of Alcoholism (n = 3681; ages 11–36). Alcohol transitions (first: drink, intoxication, alcohol use disorder [AUD] symptom, AUD diagnosis), internalizing, and externalizing phenotypes came from the Semi-Structured Assessment for the Genetics of Alcoholism. EF was measured with the Tower of London and Visual Span Tasks. Polygenic scores (PGS) were computed for alcohol-related and behavioral phenotypes. Cox models estimated associations among PGS, behavior, and alcohol milestones.

Externalizing phenotypes (e.g. conduct disorder symptoms) were associated with future initiation and drinking problems (hazard ratio (HR)⩾1.16). Internalizing (e.g. social anxiety) was associated with hazards for progression from first drink to severe AUD (HR⩾1.55). Initiation and AUD were associated with increased hazards for later depressive symptoms and suicidal ideation (HR⩾1.38), and initiation was associated with increased hazards for future conduct symptoms (HR = 1.60). EF was not associated with alcohol transitions. Drinks per week PGS was linked with increased hazards for alcohol transitions (HR⩾1.06). Problematic alcohol use PGS increased hazards for suicidal ideation (HR = 1.20).

Behavioral markers of addiction vulnerability precede and follow alcohol transitions, highlighting dynamic, bidirectional relationships between behavior and emerging addiction.

Alcohol or drug (AOD) problems are a significant health burden in the UK population, and understanding pathways to remission is important.

To determine the UK population prevalence of overcoming an AOD problem and the prevalence and correlates of ‘assisted’ pathways to problem resolution.

Stage 1: a screening question was administered in a national telephone survey to provide (a) an estimate of the UK prevalence of AOD problem resolution; and (b) a demographic profile of those reporting problem resolution. Stage 2: social surveying organisation YouGov used the demographic data from stage 1 to guide the administration of the UK National Recovery Survey to a representative subsample from its online panel.

In stage 1 (n = 2061), 102 (5%) reported lifetime AOD problem resolution. In the weighted sample (n = 1373) who completed the survey in stage 2, 49.9% reported ‘assisted’ pathway use via formal treatment (35.0%), mutual help (29.7%) and/or recovery support services (22.6%). Use of an assisted pathway was strongly correlated with lifetime AOD diagnosis (adjusted odds ratio [AOR] = 9.54) and arrest in the past year (AOR = 7.88) and inversely correlated with absence of lifetime psychiatric diagnosis (AOR = 0.17). Those with cocaine (AOR = 2.44) or opioid problems (AOR = 3.21) were more likely to use assisted pathways compared with those with primary alcohol problems.

Nearly three million people have resolved an AOD problem in the UK. Findings challenge the therapeutic pessimism sometimes associated with these problems and suggest a need to learn from community-based self-change that can supplement and enhance existing treatment modalities.

The relationship between migraine and alcohol consumption is unclear. We assessed the association between chronic migraine and alcohol use disorder(AUD), relative to chronic disease controls, and in conjunction with common comorbidities.

We conducted a retrospective, observational study. The primary outcome was the odds ratio for AUD in patients with chronic migraine or with chronic migraine and additional comorbidities relative to controls.

A total of 3701 patients with chronic migraine, 4450 patients with low back pain, and 1780 patients with type 2 diabetes mellitus met inclusion criteria. Patients with chronic migraine had a lower risk of AUD relative to both controls of low back pain (OR 0.37; 95% CI: 0.29–0.47, p < 0.001) and type 2 diabetes mellitus (OR 0.39; 95% CI: 0.29–0.52, p < 0.001). Depression was associated with the largest OR for AUD in chronic migraine (OR 8.62; 95% CI: 4.99–14.88, p < 0.001), followed by post-traumatic stress disorder (OR 6.63; 95% CI: 4.13–10.64, p < 0.001) and anxiety (OR 3.58; 95% CI: 2.23–5.75, p < 0.001).

Patients with chronic migraine had a lower odds ratio of AUD relative to controls. But in patients with chronic migraine, those with comorbid depression, anxiety, or PTSD are at higher risk of AUD. When patients establish care, comorbid factors should be assessed and for those at higher risk, AUD should be screened for at every visit.

To determine whether genetic risk factors for major depression (MD) and alcohol use disorder (AUD) interact with a potent stressor – death of spouse, parent, and sibling – in predicting episodes of, respectively, MD and AUD.

MD and AUD registrations were assessed from national Swedish registries. In individuals born in Sweden 1960–1970, we identified 7586, 388 459, and 34 370 with the loss of, respectively, a spouse, parent, and sibling. We started following subjects at age 18 or the year 2002 with end of follow-up in 2018. We examined time to event – a registration for MD within 6 months or AUD within a year – on an additive scale, using the Nelson–Aalen estimator. Genetic risk was assessed by the Family Genetic Risk Score (FGRS).

In separate models controlling for the main effects of death of spouse, parent, and sibling, FGRS, and sex, significant interactions were seen in all analyses between genetic risk for MD and death of relative in prediction of subsequent MD registration. A similar pattern of results, albeit with weaker interaction effects, was seen for genetic risk for AUD and risk for AUD registration. Genetic risk for bipolar disorder (BD) and anxiety disorders (AD) also interacted with event exposure in predicting MD.

Genetic risk for both MD and AUD act in part by increasing the sensitivity of individuals to the pathogenic effects of environmental stressors. For prediction of MD, similar effects are also seen for genetic risk for AD and BD.

Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions.

To compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness.

Data were collected from individuals aged 18–26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown.

Mental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78–36.57) and 15.6% (95% CI 15.39–15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease.

Healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.

Social cognition impairments are a common feature of alcohol use disorders (AUD). However, it remains unclear whether these impairments are solely the consequence of chronic alcohol consumption or whether they could be a marker of vulnerability.

The present study implemented a family history approach to address this question for a key process of social cognition: theory of mind (ToM). Thirty healthy adults with a family history of AUD (FH+) and 30 healthy adults with a negative family history of AUD (FH−), matched for age, sex, and education level, underwent an fMRI cartoon-vignette paradigm assessing cognitive and affective ToM. Participants also completed questionnaires evaluating anxiety, depressive symptoms, childhood trauma, and alexithymia.

Results indicated that FH+ individuals differed from FH− individuals on affective but not cognitive ToM processing, at both the behavioral and neural levels. At the behavioral level, the FH+ group had lower response accuracy for affective ToM compared with the FH− group. At the neural level, the FH+ group had higher brain activations in the left insula and inferior frontal cortex during affective ToM processing. These activations remained significant when controlling for depressive symptoms, anxiety, and childhood trauma.

These findings highlight difficulties during affective ToM processing among first-degree relatives of AUD patients, supporting the idea that some of the impairments exhibited by these patients may already be present before the onset of AUD and may be considered a marker of vulnerability.

Response inhibition − or the ability to withhold a suboptimal response − relies on the efficacy of fronto-striatal networks, and is impaired in neuropsychiatric disorders including addiction. Cortical paired associative stimulation (cPAS) is a form of transcranial magnetic stimulation (TMS) which can strengthen neuronal connections via spike-timing-dependent plasticity mechanisms. Here, we used cPAS targeting the fronto-striatal inhibitory network to modulate performance on a response inhibition measure in chronic alcohol use.

Fifty-five participants (20 patients with a formal alcohol use disorder (AUD) diagnosis (26–74 years, 6[30%] females) and 20 matched healthy controls (HCs) (27–73 years, 6[30%] females) within a larger sample of 35 HCs (23–84 years, 11[31.4%] females) underwent two randomized sessions of cPAS 1-week apart: right inferior frontal cortex stimulation preceding right presupplementary motor area stimulation by either 4 ms (excitation condition) or 100 ms (control condition), and were subsequently administered the Stop Signal Task (SST) in both sessions.

HCs showed decreased stop signal reaction time in the excitation condition (t(19) = −3.01, p = 0.007, [CIs]:−35.6 to −6.42); this facilitatory effect was not observed for AUD (F(1,31) = 9.57, p = 0.004, CIs: −68.64 to −14.11). Individually, rates of SST improvement were substantially higher for healthy (72%) relative to AUD (13.6%) groups (OR: 2.33, p = 0.006, CIs:−3.34 to −0.55).

In line with previous findings, cPAS improved response inhibition in healthy adults by strengthening the fronto-striatal network through putative long-term potentiation-like plasticity mechanisms. Furthermore, we identified a possible marker of impaired cortical excitability, and, thus, diminished capacity for cPAS-induced neuroplasticity in AUD with direct implications to a disorder-relevant cognitive process.

To clarify, in a national sample, associations between risk for seven psychiatric and substance use disorders and five key transitions in Sweden's public educational system.

Swedish-born individuals (1972–1995, N = 1 997 910) were followed through 12-31-2018, at mean age 34.9. We predicted, from these educational transitions, risk for major depression (MD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), anorexia nervosa (AN), alcohol use disorder (AUD), and drug use disorder (DUD), assessed from Swedish national registers, by Cox regression, censoring individuals with onsets ⩽17. We also predicted risk from the deviation of grades from family-genetic expectations (deviation 1) and from changes in grades from ages 16 to 19 (deviation 2).

We observed four major risk patterns across transitions in our disorders: (i) MD and BD, (ii) OCD and SZ, (iii) AUD and DUD, and (iv) AN. Failing early educational transitions had the greatest impact on risk for OCD and SZ while for other disorders, not progressing from basic to upper high school had the largest effect. Completing vocational v. college-prep upper high school was strongly associated with risk for AUD and DUD, had little relation with MD, OCD, BD, and SZ risk, and was protective for AN. Deviation 1 predicted risk most strongly for SZ, AN, and MD. Deviation 2 predicted risk most strongly for SZ, AUD, and DUD.

The pattern of educational transitions and within family and within person development deviations are strongly and relatively specifically associated with future risk for seven psychiatric and substance-use disorders.

Prevalence of cognitive decline and dementia is rising globally, with more than 10 million new cases every year. These conditions cause a significant burden for individuals, their caregivers, and health care systems. As no causal treatment for dementia exists, prevention of cognitive decline is of utmost importance. Notably, alcohol is among the most significant modifiable risk factors for cognitive decline.

Longitudinal data across 15 years on 6,967 individuals of the Survey of Health, Ageing and Retirement in Europe were used to analyze the effect of alcohol consumption and further modifiable (i.e., smoking, depression, and educational obtainment) and non-modifiable risk factors (sex and age) on cognitive functioning (i.e., memory and verbal fluency). For this, a generalized estimating equation linear model was estimated for every cognitive test domain assessed.

Consistent results were revealed in all three regression models: A nonlinear association between alcohol consumption and cognitive decline was found—moderate alcohol intake was associated with overall better global cognitive function than low or elevated alcohol consumption or complete abstinence. Furthermore, female sex and higher educational obtainment were associated with better cognitive function, whereas higher age and depression were associated with a decline in cognitive functioning. No significant association was found for smoking.

Our data indicate that alcohol use is a relevant risk factor for cognitive decline in older adults. Furthermore, evidence-based therapeutic concepts to reduce alcohol consumption exist and should be of primary interest in prevention measures considering the aging European population.