This study investigated the risk of SARS-CoV-2 infection and severe COVID-19 outcomes among different mental health diagnoses and the role of sex in these associations.

Using electronic records from Catalonia, we identified adults receiving mental health care from 2017-2019 with diagnoses of non-affective psychosis (NAP), bipolar disorder (BD), depressive disorder (DEP), stress-related disorders, neurotic/somatoform disorders (NSD), and substance misuse (SUB) (exposed). The outcomes assessed were SARS-CoV-2 infection, COVID-19 hospitalization, and COVID-19-related death, compared to matched individuals without these mental disorders (unexposed). Adjusted logistic regression analyses were conducted.

785,378 adults were included (70.3% < 65 years old; 57.1% women). Compared to unexposed, those with NAP, BD, DEP, and SUB had a lower risk of SARS-CoV-2 infection, while those with NSD had an increased risk. Infected individuals with DEP, NSD, and SUB had a lower risk of hospitalization but a higher risk of COVID-19-related death. Higher COVID-19-related death was also observed in individuals with NAP and BD. Sex-stratified analysis revealed that women with NSD were especially vulnerable to infection, and women with DEP and NSD had a higher risk of COVID-19-related death.

These findings emphasize the need for tailored public health strategies to reduce excess mortality risk among individuals with certain mental disorders, while accounting for sex differences.

Tobacco use remains one of the most significant preventable public health problems globally and is increasingly concentrated among vulnerable groups, including those with trauma exposure or diagnosed with PTSD. The goal of this systematic review was to update and extend previous reviews. Of the 7224 publications that met the initial criteria, 267 were included in the review. Summary topic areas include conceptual frameworks for the relation between trauma or PTSD and tobacco use; associations between trauma exposure or PTSD and tobacco use; number and type of trauma exposures and tobacco use; PTSD symptoms and tobacco use; Treatment-related studies; and the examination of causal relations. Evidence continues to indicate that individuals exposed to trauma or diagnosed with PTSD are more likely to use tobacco products, more nicotine dependent and less likely to abstain from tobacco even when provided evidence-based treatments than individuals without trauma. The most commonly cited causal association proposed was use of tobacco for self-regulation of negative affect associated with trauma. A small proportion of the studies addressed causality and mechanisms of action. Future work should incorporate methodological approaches and measures from which we can draw causal conclusions and mechanisms to support the development of viable therapeutic targets.

As one of the leading causes of death and serious illnesses, tobacco smoking remains a significant issue in modern societies. Many individuals smoke during adolescence, a trend that has been exacerbated by the prevalence of vaping among young people. In this context, studying the behavioral effects induced by nicotine administration in male and female rats, during the adolescent period, assumes great importance because it can help to better understand the dynamics underlying tobacco use in the two sexes. For this purpose, we employed 4 groups of rats, 2 male and 2 female groups, chronically treated with saline or nicotine 3 mg/kg i.p. for 30 days, spanning from postnatal day 30 to postnatal day 60. Utilizing quantitative analyses and T-pattern detection and analysis, our findings revealed a complex and multifaceted behavioral reorganization in adolescent rats subjected to chronic nicotine administration. Specifically, we observed an increase of anxiety in males and a reduction in females. The distinctive structural changes, induced by chronic nicotine in both sexes, have significant implications, from a translational perspective, for studies on nicotine dependence disorders.

Psychiatric disorders are emerging as a serious public health hazard, influencing an increasing number of individuals worldwide. However, the effect of modifiable lifestyle factors on psychiatric disorders remains unclear.

Genome-wide association studies (GWAS) summary statistics were obtained mainly from Psychiatric Genomics Consortium and UK Biobank, with sample sizes varying between 10,000 and 1,200,000. The two-sample Mendelian randomization (MR) method was applied to investigate the causal associations between 45 lifestyle factors and 13 psychiatric disorders, and screen potential mediator proteins from 2992 candidate plasma proteins. We implemented a four-step framework with step-by-step screening incorporating two-step, univariable, and multivariable MR.

We found causal effects of strenuous sports or other exercise on Tourette's syndrome (OR [95%CI]: 0.0047 [5.24E-04-0.042]); lifelong smoking index on attention-deficit hyperactivity disorder (10.53 [6.96-15.93]), anxiety disorders (3.44 [1.95-6.05]), bipolar disorder (BD) (2.25 [1.64-3.09]), BD II (2.89 [1.81-4.62]), and major depressive disorder (MDD) (2.47 [1.90-3.20]); and educational years on anorexia nervosa (AN) (1.47 [1.22-1.76]), and MDD (0.74 [0.66-0.83]). Five proteins were found to have causal associations with psychiatric disorders, namely ADH1B, GHDC, STOM, CD226, and TP63. STOM, a membrane protein deficient in the erythrocytes of hereditary stomatocytosis patients, may mediate the effect of educational attainment on AN.

The mechanisms underlying the effects of lifestyle factors on psychiatric disorders require further investigation.

These findings could help assess the risk of psychiatric disorders based on lifestyle factors and also support lifestyle interventions as a prevention strategy for mental illness.

Despite the large public health toll of smoking, genetic studies of smoking cessation have been limited with few discoveries of risk or protective loci. We investigated common and rare variant associations with success in quitting smoking using a cohort from 8 randomized controlled trials involving 2231 participants and a total of 10,020 common and 24,147 rare variants. We identified 14 novel markers including 6 mapping to genes previously related to psychiatric and substance use disorders, 4 of which were protective (CYP2B6 (rs1175607105), HTR3B (rs1413172952; rs1204720503), rs80210037 on chr15), and 2 of which were associated with reduced cessation (PARP15 (rs2173763), SCL18A2 (rs363222)). The others mapped to areas associated with cancer including FOXP1 (rs1288980) and ZEB1 (rs7349). Network analysis identified significant canonical pathways for the serotonin receptor signaling pathway, nicotine and bupropion metabolism, and several related to tumor suppression. Two novel markers (rs6749438; rs6718083) on chr2 are flanked by genes associated with regulation of bodyweight. The identification of novel loci in this study can provide new targets of pharmacotherapy and inform efforts to develop personalized treatments based on genetic profiles.

Multimorbidity, defined as the presence of two or more long-term health conditions in an individual, is one of the most significant challenges facing health systems worldwide. This study aimed to identify determinants of classes of multimorbidity among older adults in Iran.

In a cross-sectional sample of older adults (aged ≥ 60 years) from the second stage of the Bushehr Elderly Health (BEH) program in southern Iran, latent class analysis (LCA) was used to identify patterns of multimorbidity. Multinomial logistic regression was conducted to investigate factors associated with each multimorbidity class, including age, gender, education, household income, physical activity, smoking status, and polypharmacy.

In 2,426 study participants (mean age 69 years, 52% female), the overall prevalence of multimorbidity was 80.2%. Among those with multimorbidity, 3 latent classes were identified. These comprised: class 1, individuals with a low burden of multisystem disease (56.9%); class 2, individuals with predominantly cardiovascular-metabolic disorders (25.8%) and class 3, individuals with predominantly cognitive and metabolic disorders (17.1%). Compared with men, women were more likely to belong to class 2 (odds ratio [OR] 1.96, 95% confidence interval [CI] 1.52-2.54) and class 3 (OR 4.52, 95% CI 3.22-6.35). Polypharmacy was associated with membership class 2 (OR 3.52, 95% CI: 2.65-4.68) and class 3 (OR 1.84, 95% CI 1.28-2.63). Smoking was associated with membership in class 3 (OR 1.44, 95% CI 1.01-2.08). Individuals with higher education levels (59%) and higher levels of physical activity (39%) were less likely to belong to class 3 (OR 0.41; 95% CI: 0.28-0.62) and to class 2 (OR 0.61; 95% CI: 0.38-0.97), respectively. Those at older age were less likely to belong to class 2 (OR 0.95).

A large proportion of older adults in Iran have multimorbidity. Female sex, polypharmacy, sedentary lifestyle, and poor education levels were associated with cardiovascular-metabolic multimorbidity and cognitive and metabolic multimorbidity. A greater understanding of the determinants of multimorbidity may lead to strategies to prevent its development.

Previous studies suggest an association between schizophrenia and stroke, but no studies have investigated stroke subtypes. We examined potential causal associations between schizophrenia and a range of atherosclerotic, embolic, and hemorrhagic stroke outcomes.

Two-sample Mendelian randomization analyses were conducted. The summary-level data (restricted to European ancestry) were obtained for schizophrenia and stroke: ischemic stroke, large-artery stroke, small-vessel stroke, cardioembolic stroke, and intracerebral hemorrhage. The associations between schizophrenia and each outcome were analyzed by an inverse variance weighting method primarily and Mendelian randomization Egger, weighted median, and weighted mode subsequently. The presence of pleiotropy was also tested by Cochran Q statistic, I2 index, and Mendelian randomization Egger intercept with scatter and funnel plots. We found associations between schizophrenia and cardioembolic stroke (odds ratio [OR], 1.070 [95% CI, 1.023-1.119]) and intracerebral hemorrhage (OR, 1.089 [95% CI, 1.005-1.180]) using inverse variance weighting. Little evidence of associations with the other stroke subtypes was found. Different Mendelian randomization methods corroborated the association with cardioembolic stroke but not intracerebral hemorrhage.

We have provided evidence of a potentially causal association between schizophrenia and cardioembolic stroke. Our findings suggest that cardiac evaluation should be considered for those with schizophrenia.

Previous studies have indicated that smoking is linked to an increased risk of developing schizophrenia, and that individuals with schizophrenia are more prone to engaging in antisocial behavior. However, the causal effects of smoking behaviors on antisocial behavior and the potential mediating role of schizophrenia remains largely unclear.

In the present study, using the summary data from genome wide association studies of smoking phenotypes (N = 323,386-805,431), schizophrenia (Ncases = 53,386, Ncontrols = 77,258), and antisocial behavior (N = 85,359), we assessed bidirectional causality between smoking phenotypes and schizophrenia by the Mendelian randomization (MR) approach. Using a two-step MR approach, we further examined whether causal effects of smoking phenotypes/schizophrenia on antisocial behavior were mediated by schizophrenia/smoking phenotypes.

The results showed that smoking initiation (SmkInit) and age of smoking initiation (AgeSmk) causally increase the risk of schizophrenia (SmkInit: OR = 2.06, 95% CI = 1.77-2.39, p = 4.36 × 10-21 ; AgeSmk: OR = 0.32, 95% CI = 0.16-0.62, p = 8.11 × 10-4 , Bonferroni corrected). However, there was no causal effect that liability to schizophrenia leads to smoking phenotypes. MR evidence also revealed causal influences of SmkInit and the amount smoked (CigDay) on antisocial behavior (SmkInit: OR = 1.28, 95% CI = 1.17-1.41, p = 2.53 × 10-7 ; CigDay: OR = 1.16, 95% CI = 1.06-1.27, p = 1.60 × 10-3 , Bonferroni corrected). Furthermore, the mediation analysis indicated that the relationship between SmkInit and antisocial behavior was partly mediated by schizophrenia (mediated proportion = 6.92%, 95% CI = 0.004-0.03, p = 9.66 × 10-3 ).

These results provide compelling evidence for taking smoking interventions as a prevention strategy for schizophrenia and its related antisocial behavior.

Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ.

We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association.

Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function.

We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

Patients with schizophrenia have a 15- to 20-year shorter life expectancy compared with the general population. The aim of this study was to explore these patients' perception of their physical health.

A patient reported outcomes measure (PROM) has been developed by patients with severe mental disease. This survey had to better capture undetected, under-rated and non-prioritized physical domains by traditional routine clinical scales that are important for people who live with mental health disease. These patients have tested the applicability of this PROM with peers with severe mental disease in medical, social and community-based centers from Hauts-de-France.

Two and a half years have been required to develop this PROM, to test its applicability to patients with severe mental disease and to analyze the results. The study process has been slowed by the sanitary context induced by the COVID-19 pandemic. Thirty-two questionnaires have been collected by the participants. Despite this low number of data, participants have been satisfied by the results and their experience. The results show that people with severe mental disease consider physical health as a major concern, notably pain and somatic diseases. External factors (such as accessibility to health care and medication) and internal factors (such as self-esteem, cognitive and negative symptoms, sleep, alimentation, and substance use) have been identified as barriers for physical health.

These results support the development of PROMs highlighting personal experience of people with severe mental disease. The data obtained thanks to these measures will allow to build programs to help them to cope with barriers for physical health.

This study explored the phenotypic association of mood disorders, including major depressive disorder (MDD) and bipolar disorder (BPD), with a range of substance involvement, including lifetime experience and age at initiation of tobacco, alcohol, and betel nut use. Additionally, we elucidated polygenic risk score (PRS) association.

In total, 132,615 community participants were recruited from the Taiwan Biobank. Genome-wide genotyping data were available for 106,806 unrelated individuals, and the PRS for MDD and BPD was calculated. The significance of mood disorders and PRSs associated with substance involvement were evaluated using a linear/logistic regression model with adjustment for potential confounders. Sex differences were assessed.

MDD and BPD were associated with regular alcohol consumption, drinking cessation, tobacco smoking, smoking cessation, betel nut chewing, and earlier onset of drinking. BPD was associated with an earlier onset of smoking. MDD PRS was associated with regular alcohol use (odds ratio [OR] per standard deviation increase in PRS = 1.03, p = 0.018), alcohol cessation (OR = 1.05, p = 0.03), regular tobacco use (OR = 1.08, p < 0.0001), and betel nut chewing (OR = 1.06, p < 0.0001), whereas BPD PRS was not associated with substance use. Phenotypic association strengths between MDD/BPD and regular drinking/smoking and the polygenic association between MDD PRS and regular smoking were larger in females than in males.

Retrospective self-reported MDD/BPD diagnoses and substance involvement.

Mood disorders were associated with a range of substance involvement. Shared genetic architecture contributed to the co-occurrence of MDD and substance involvement. These findings may help design prevention and cessation strategies for substance use.

Major depressive disorder (MDD) poses a significant social and economic burden worldwide. Identifying exposures, risk factors, and biological mechanisms that are causally connected to MDD can help build a scientific basis for disease prevention and development of novel therapeutic approaches.

In this systematic review, we assessed the evidence for causal relationships between putative causal risk factors and MDD from Mendelian randomization (MR) studies, following PRISMA. We assessed methodological quality based on key elements of the MR design: use of a full instrumental variable analysis and validation of the three key MR assumptions.

We included methodological details and results from 52 articles. A causal link between lifestyle, metabolic, inflammatory biomarkers, particular pathological states and MDD is supported by MR investigations, although results for each category varied substantially.

While this review shows how MR can offer useful information for examining prospective treatment targets and better understanding the pathophysiology of MDD, some methodological flaws in the existing literature limit reliability of results and probably underlie their heterogeneity. We highlight perspectives and recommendations for future works on MR in psychiatry.

It has been suggested that people with mental disorders have an elevated risk to acquire severe acute respiratory syndrome coronavirus 2 and to be disproportionally affected by coronavirus disease 19 (COVID-19) once infected. We aimed to analyse the COVID-19 infection rate, course and outcome, including mortality and long COVID, in people with anxiety, depressive, neurodevelopmental, schizophrenia spectrum and substance use disorders relative to control subjects without these disorders.

This study constitutes a preregistered systematic review and random-effects frequentist and Bayesian meta-analyses. Major databases were searched up until 27 June 2023.

Eighty-one original articles were included reporting 304 cross-sectional and prospective effect size estimates (median n per effect-size = 114837) regarding associations of interest. Infection risk was not significantly increased for any mental disorder that we investigated relative to samples of people without these disorders. The course of COVID-19, however, is relatively severe, and long COVID and COVID-19-related hospitalization are more likely in all patient samples that we investigated. The odds of dying from COVID-19 were high in people with most types of mental disorders, except for those with anxiety and neurodevelopmental disorders relative to non-patient samples (pooled ORs range, 1.26-2.57). Bayesian analyses confirmed the findings from the frequentist approach and complemented them with estimates of the strength of evidence.

Once infected, people with pre-existing mental disorders are at an elevated risk for a severe COVID-19 course and outcome, including long COVID and mortality, relative to people without pre-existing mental disorders, despite an infection risk not significantly increased.

Mental disorders, characterized as products of biopsychosocial interactions, have emerged as a leading contributor to the worldwide rise in overall morbidity and disability rates. Life's essentials can affect nearly every aspect of our lives, from physical to mental health. In this study, we try to identify the associations between life's essentials and mental disorders.

Three assumptions of Mendelian randomization (MR) were applied to obtain the genetic instruments associated with smoking, sleep, and body mass index (BMI) in genome-wide association studies. Then, we conducted univariable MR (UVMR) and multivariable MR (MVMR) two-sample analyses to estimate the causal effects of these life's essentials on two mental disorders namely, major depressive disorder (MDD) and bipolar disorder (BD). Additionally, multiple sensitivity analyses were performed to evaluate the reliability and stability of the study results.

In the MR analysis of the association of smoking, sleep, and BMI with MDD, we obtained 78, 39, and 302 genetic instruments, respectively. Smoking [odds ratio (OR), 1.03; 95% confidence interval (CI), 1.01-1.06; p = 0.004], sleep (OR, 1.04; 95% CI, 1.02-1.06; p < 0.001), and BMI (OR, 1.01; 95% CI, 1.01-1.02; p < 0.001) were all considered as risk factors for MDD and were independent of each other (smoking: OR, 1.03, 95% CI, 1.01-1.06, p = 0.008; sleep: OR, 1.03, 95% CI, 1.01-1.05, p = 0.001; and BMI: OR, 1.01, 95% CI, 1.01-1.02, p < 0.001). Additionally, 78, 38, and 297 genetic instruments were obtained in the MR analysis of smoking, sleep, and BMI with BD, respectively. Causal associations were observed between smoking (OR, 2.46; 95% CI, 1.17-5.15; p = 0.017), sleep (OR, 2.73; 95% CI, 1.52-4.92; p < 0.001), and BD, and smoking (OR, 2.43; 95% CI, 1.69-3.16; p = 0.018) might be a mediator in the causal effects of sleep on BD. Finally, there was no inconsistency between sensitivity and causality analysis, proving that our results are convincing.

The study results provide strong evidence that smoking, sleep, and BMI are causally related to MDD and BD, which need further research to clarify the underlying mechanism.

Prevalence of smoking in schizophrenia (SCZ) is larger than in general population. Genetic studies provided some evidence of a causal effect of smoking on SCZ. We aim to characterize the genetic susceptibility to SCZ affected by genetic susceptibility to smoking.

Multi-trait-based conditional and joint analysis was applied to the largest European SCZ genome-wide association studies (GWAS) to remove genetic effects on SCZ driven by smoking, estimated by generalized summary data-based Mendelian randomization. Enrichment analysis was performed to compare original v. conditional GWAS. Change in genetic correlation between SCZ and relevant traits after conditioning was assessed. Colocalization analysis was performed to identify specific loci confirming general findings.

Conditional analysis identified 19 new risk loci for SCZ and 42 lost loci whose association with SCZ may be partially driven by smoking. These results were strengthened by colocalization analysis. Enrichment analysis indicated a higher association of differentially expressed genes at prenatal brain stages after conditioning. Genetic correlation of SCZ with substance use and dependence, attention deficit-hyperactivity disorder, and several externalizing traits significantly changed after conditioning. Colocalization of association signal between SCZ and these traits was identified for some of the lost loci, such as CHRNA2, CUL3, and PCDH7.

Our approach led to identification of potential new SCZ loci, loci partially associated to SCZ through smoking, and a shared genetic susceptibility between SCZ and smoking behavior related to externalizing phenotypes. Application of this approach to other psychiatric disorders and substances may lead to a better understanding of the role of substances on mental health.

Depression has become a major health concern, particularly in developing countries. This disorder is highly prevalent among certain vulnerable populations, such as prisoners. In Peru, prisons are overcrowded, and the health of prisoners is neglected. Thus, this study aims to estimate the prevalence of depression diagnosed during incarceration in male inmates from all Peruvian prisons and assess its associated factors.

A cross-sectional study was conducted based on the secondary data analysis of the National Census of Prison Population 2016 in Peru. This study included records of prisoners who reported whether they were diagnosed with depression by a health-care professional after admission into the prisons. Descriptive, bivariate and multivariable analyses were performed.

Of the 63,312 prisoners included in this study, 1,007 reported an in-prison diagnosis of depression by a health-care professional, which represents a prevalence of 1.59%. Substance use disorder (adjusted prevalence ratio [aPR] 3.10; 95% confidence interval [CI]: 1.91-5.03), hypertension (aPR 7.20; 95% CI: 6.28-8.24) and previous discrimination (aPR 1.97; 95% CI: 1.62-2.40) were strongly associated with depression, even when adjusting for multiple confounders. Other directly associated variables were, for example, violence during childhood, infrequent visits in prison and diabetes.

The right of prisoners to adequate health care is being neglected in Peru. Mental health is a cornerstone of health quality. Acknowledging which factors are associated with depression in prison is important to implement strategies to improve the mental health of prisoners.

There has been a noticeable relative increase in psychiatric comorbidities among smokers as opposed to the general population. This is likely due to comparatively slower decrease in smoking prevalence among individuals with mental health conditions. This study aims to assess the prevalence trend of past or current mental health disorders in individuals seeking specialized smoking cessation assistance.

We conducted a retrospective single-centre observational study to assess the presence of mental disorders such as anxiety, depression, bipolar affective disorder, or schizophrenia in personal history of 6,546 smokers who sought treatment at the Centre for Treatment of Tobacco Dependence in Prague, Czech Republic between 2006 and 2019. The study examined the impact of gender, age, and the effect of successive years on the prevalence of the mental disorders using Poisson distribution regression.

In the studied cohort, 1,743 patients (26.6%) reported having one or more mental disorders. Compared to patients without a psychiatric disorder, they exhibited similar levels of carbon monoxide in expired air (mean 17 ppm, SD 11 ppm) and scored one point higher on the Fagerström Test of Cigarette Dependence. Among smokers with a mental disorder, women were more prevalent (62%) than men (38%). The prevalence of mental disorders increased on average by 4% every year, rising from 23% in 2006 to 35% in 2019.

Consistent with the observation that the prevalence of smoking among people with any mental disorder is higher and declining at a slower rate than in the general population, there is a steadily increasing percentage of these patients seeking specialized treatment over time. Professionals who offer tobacco dependence treatment should be aware of the upward trend in psychiatric disorders among smokers, as more intensive treatment may be needed. Similarly, psychiatric care should pay attention to smoking of their patients.

Identifying modifiable risk factors early on is essential to prevent major depressive disorder (MDD). This study systematically investigated the causal relationship between 19 modifiable risk factors and MDD. Single-nucleotide polymorphisms (SNPs) associated with 19 potentially modifiable risk factors were screened via the genome-wide association study (GWAS) enrolling individuals of European descent. Summary-level data for MDD (59,851 cases and 113,154 controls) were extracted from the UK Biobank. The inverse-variance-weighted (IVW) method was utilized as the primary analysis. Sensitivity analyses were performed using the MR-Egger method, the Maximum likelihood method, the MR-pleiotropy residual sum outlier (MR-PRESSO) method, and MR-robust adjusted profile score (MR-RAPS) method. MR-Egger regression, heterogeneity tests, pleiotropy tests, and leave-one-out tests were also performed to analyze sensitivity. The MR Steiger test was used to verify the directionality of the exposure to the outcome. Genetically predicted smoking initiation increased the risk of MDD (P = 6.00E-09), while smoking status: never and past tobacco smoking decreased the risk of MDD (all P < 0.01). In addition, education level was inversely associated with MDD risk (all P < 0.01). Genetically instrumented sleeplessness/insomnia, daytime naps, and nap during the day were positively related to the risk of MDD (all P < 0.01). Personal feelings, including guilt, hurt, tension, and worry too long after an embarrassing experience, had a suggestive increased risk for MDD (all P < 0.000). The remaining five modifiable risk factors were all causally associated with the risk of MDD, including neuroticism, neuroticism scores, body mass index (BMI), average total household income before tax, and types of physical activity in the last 4 weeks (all P < 0.01). All 19 potentially modifiable risk factors were causally associated with the risk of MDD. The main hypothesis of this MR study was that identifying and intervening in these 19 potentially modifiable risk factors could be beneficial to the prevention and treatment of MDD and further reduce mortality and economic burden.

Self-reported tiredness or low energy, often referred to as fatigue, has been linked to lifestyle factors, although data from randomized-controlled trials are lacking. We investigate whether modifiable lifestyle factors including smoking and alcohol intake related exposures (SAIEs) are causal factors for fatigue using Mendelian randomization (MR). A two-sample MR study was performed by using genome-wide association summary results from UK Biobank (UKBB), and each of the sample size is more than 100,000. We used the inverse variance weighted method, and sensitivity analyses (MR Egger, weighted median, penalized median estimators, and multivariable MR) to account for pleiotropy. The two-sample MR analyses showed inverse causal effect of never-smoking status and positive effect of current smoking status on the risk of fatigue. Similarly, genetically predicted alcoholic intake was positively associated with fatigue. The results were consistent across the different MR methods. Our Mendelian randomization analyses do support that the cessation of smoking and alcohol can decrease the risk of fatigue, and limit alcohol intake frequency can also reduce the risk.

Tobacco smoking is a risk factor for impaired brain function, but its causal effect on white matter brain aging remains unclear. This study aimed to measure the causal effect of tobacco smoking on white matter brain aging.

Mendelian randomization (MR) analysis using two non-overlapping data sets (with and without neuroimaging data) from UK Biobank (UKB). The group exposed to smoking and control group consisted of current smokers and never smokers, respectively. Our main method was generalized weighted linear regression with other methods also included as sensitivity analysis.

United Kingdom.

The study cohort included 23 624 subjects [10 665 males and 12 959 females with a mean age of 54.18 years, 95% confidence interval (CI) = 54.08, 54.28].

Genetic variants were selected as instrumental variables under the MR analysis assumptions: (1) associated with the exposure; (2) influenced outcome only via exposure; and (3) not associated with confounders. The exposure smoking status (current versus never smokers) was measured by questionnaires at the initial visit (2006-10). The other exposure, cigarettes per day (CPD), measured the average number of cigarettes smoked per day for current tobacco users over the life-time. The outcome was the 'brain age gap' (BAG), the difference between predicted brain age and chronological age, computed by training machine learning model on a non-overlapping set of never smokers.

The estimated BAG had a mean of 0.10 (95% CI = 0.06, 0.14) years. The MR analysis showed evidence of positive causal effect of smoking behaviors on BAG: the effect of smoking is 0.21 (in years, 95% CI = 6.5 × 10-3 , 0.41; P-value = 0.04), and the effect of CPD is 0.16 year/cigarette (UKB: 95% CI = 0.06, 0.26; P-value = 1.3 × 10-3 ; GSCAN: 95% CI = 0.02, 0.31; P-value = 0.03). The sensitivity analyses showed consistent results.

There appears to be a significant causal effect of smoking on the brain age gap, which suggests that smoking prevention can be an effective intervention for accelerated brain aging and the age-related decline in cognitive function.

People with high levels of intelligence are more aware of risk factors, therefore choosing a healthier lifestyle. This assumption seems reasonable, but is it true? Previous studies appear to agree and disagree. To cope with the uncertainty, we designed a mendelian randomization (MR) study to examine the causal effects of genetically proxied intelligence on alcohol-, smoking-, and physical activity (PA)-related behaviors. We obtained genome-wide association study (GWAS) datasets concerning these variables from separate studies or biobanks and used inverse-variance weighted (IVW) or MR-Egger estimator to evaluate the causal effects according to an MR protocol. The MR-Egger intercept test, MR-PRESSO, and funnel plots were employed for horizontal pleiotropy diagnosis. The Steiger test (with reliability test), Cochran's Q test, MR-PRESSO, and leave-one-out method were employed for sensitivity analysis. We found significant or potential effects of intelligence on alcohol dependence (OR = 0.749, p = 0.003), mental and behavioral disorders due to alcohol (OR = 0.814, p = 0.009), smoking (OR = 0.585, p = 0.005), and smoking cessation (OR = 1.334, p = 0.001). Meanwhile, we found significant or potential effects on walking duration (B = -0.066, p < 0.001), walking frequency (B = -0.055, p = 0.031), moderate PA frequency (B = -0.131, p < 0.001), and vigorous PA frequency (B = -0.070, p = 0.001), but all in a negative direction. In conclusion, our findings reinforce some existing knowledge, indicate the complexity of the health impacts of human intelligence, and underline the value of smoking and alcohol prevention in less intelligent populations. Given the existing limitations in this study, particularly the potential reverse causality in some estimations, re-examinations are warranted in future research.

Alcohol, tobacco and coffee are commonly used substances and use in adolescence has previously been linked to mood disorders. However, few large prospective studies have investigated adolescent use in relation to mental health outcomes in adulthood. The main aim of this study was to examine the prospective associations between alcohol use, cigarette smoking and coffee consumption at age 16 and subsequent mood disorders up to 33 years of age.

Data from The Northern Finland Birth Cohort 1986 Study were used and a total of 7660 participants (49.9% male) were included. Associations between alcohol use, cigarette smoking and coffee consumption at age 16 and later diagnoses of major depression and bipolar disorder were examined using multinomial logistic regression analyses.

Mean number of cigarettes/day (OR, 1.23 [95% CI 1.01-1.50]) and mean volume of alcohol consumption (OR, 1.22 [95% CI 1.01-1.47]), but not frequency of excessive drinking, in adolescence were associated with increased risk for subsequent bipolar disorder after adjustment for sex, parental psychiatric disorders, family structure, illicit substance use, and emotional and behavioral problems at age 16. An association between cigarette smoking and major depression attenuated to statistically non-significant when adjusted for emotional and behavioral problems. No associations were observed between adolescent coffee consumption and subsequent mood disorders.

This is the first study to report an association of adolescent cigarette smoking and subsequent bipolar disorder diagnosis providing grounds for further research and pointing to a place for preventive measures among adolescents.

Although several studies examined the association between e-cigarettes, substance use, and mental health conditions, there is limited research on whether COVID-19-related stress and health outcomes, mental health symptoms, and substance use differ by the frequency of e-cigarette use during the COVID-19 pandemic. We assessed the association of past 30-day frequent use of e-cigarettes with alcohol, cannabis, anxiety/depression, and COVID-19 impact.

We conducted a national online cross-sectional survey among a random sample of US adults aged 18 years or older (N = 5065) between 13 May 2021, and 9 January 2022. A multinomial logistic regression analysis was performed to assess the study aims.

Of the participants, 7.17% reported once to several times per month (OSTPM), 6.95% reported once to several times per week (OSTPW), and 6.57% reported every day to several times per day (ESTPD) use of e-cigarettes in the past month. Alcohol and cannabis use ESTPD and once to several times per week/month (OSTPW/M) were associated with a higher likelihood of e-cigarette use ESTPD and OSTPW/M, respectively. Anxiety/depression was associated with e-cigarette use ESTPD and OSTPW. Individuals who considered social distancing to be stressful were more likely to use e-cigarettes ESTPD and OSTPW/M compared to those that considered social distancing as not stressful.

Individuals who engaged in the frequent use of alcohol or cannabis, had depression/anxiety, and considered social distancing to be stressful were more likely to engage in frequent e-cigarette use. Improving efforts geared toward reducing the use of substances may help decrease the health risks associated with e-cigarette use.

Understanding mechanisms associated with depressed smokers is a relevant question given that tobacco use disorder with comorbid major depressive disorder (MDD) has worse outcomes. The beta-arrestin 1 (ARRB1) pathway is a suggested biomarker for major depressive disorder and is involved in both antidepressant mechanism of action and tobacco addiction. We aimed to assess the association between smoking and peripheral ARRB1 expression in participants who exhibited MDD with current major depressive episode (MDE).

61 participants who exhibited MDD with current MDE with a score above 17 on the Hamilton Depression Rating Scale (HDRS), and who were free from antidepressant drug treatment for at least one month before inclusion, were assessed for tobacco use and cigarettes/day. Peripheral ARRB1 expression was assessed by sandwich ELISA from peripheral blood mononuclear cells (PBMC).

In participants who exhibited MDD with current MDE, peripheral ARRB1 expression was lower in tobacco users (n = 20, mean (SD) 4.795 (1.04) ng/mg of total protein) compared to non-tobacco users (n = 41, mean (SD) 6.19 (1.56) ng/mg; FDR p-value= 0.0044). Higher daily tobacco consumption was associated with lower peripheral ARRB1 expression (r = -0.314; FDR p-value=0.037).

Tobacco consumption should be considered in studies of ARRB1 in participants who exhibit MDD. ARRB1 signaling is a new target of interest with a potential clinical implication for people with MDD and tobacco use disorder.

The effect of insomnia and sleep duration on risk of anxiety has been assessed based on traditional epidemiological studies. However, the inconsistent conclusions do not establish causal associations. This study aimed to explore the causal associations of insomnia, short sleep, and long sleep with anxiety.

We used summary statistics from three large-scale genome-wide association studies (GWAS) of European ancestry to perform a two-sample Mendelian randomization (MR) study. MR analyses were mainly conducted with the inverse-variance-weighted (IVW) method. To evaluate the robustness of our findings, we performed the weighted-median approach, the MR-Egger method, and the MR-robust adjusted profile score (MR-RAPS) method for sensitivity analyses.

There was a statistically significant association of genetically predicted insomnia with anxiety using the IVW method (OR = 1.36, 95% CI = 1.23-1.51, P < 0.001). Genetically predicted short sleep was potentially associated with anxiety using IVW method (OR = 1.67, 95% CI = 1.08-2.60, P = 0.022). However, sensitivity analyses did not find the causal association of short sleep with anxiety (all P > 0.053). We did not observe a statistically significant causal association of genetically predicted long sleep with anxiety (OR = 0.91, 95% CI = 0.48-1.74, P = 0.775).

We found strong evidence that insomnia but not short sleep and long sleep has a causal effect on anxiety. The characteristics of insomnia should be incorporated into anxiety prevention and intervention strategies, which have important public health significance.

Toxoplasmosis is a parasitic disease with worldwide prevalence. Despite the relatively similar effects of toxoplasmosis and smoking on alteration in neurotransmitters, especially dopamine, little is known about the relation of Toxoplasma gondii infection and addiction to cigarette smoking. Therefore, the main objective of this study was to assess the relationship between latent toxoplasmosis and smoking. Through a case-control study, 216 regular cigarette smokers and 324 nonsmoker age- and gender-matched subjects were evaluated for anti-T.gondii IgG antibodies with enzyme-linked immunosorbent assay (ELISA). During the sampling, a structured questionnaire was used to obtain the demographic information of participants and the risk factors of acquired Toxoplasma. The median ages of case and control groups were 51.04 ± 18.1 (22-97 years) and 51.03 ± 16.5 (21-89 years), respectively (p = 0.99). Anti-T.gondii IgG antibodies were detected in 44 (20.37%) cases and in 135 (41.67%) controls. There was a statistically significant difference for the positivity rate between the smokers and the control group (OR = 0.35; 95%CI: 0.19-0.65; and p = 0.001). The overall prevalence was 33.14%. This study indicated the inverse association between seropositivity to Toxoplasma infection and cigarette smoking. This relationship could be due to the changes that latent toxoplasmosis has on the neurotransmitters, especially dopamine, which needs more research.

The association between coronary artery disease (CAD) and posttraumatic stress disorder (PTSD) contributes to the high morbidity and mortality observed for these conditions. To understand the dynamics underlying PTSD-CAD comorbidity, we investigated large-scale genome-wide association (GWA) statistics from the Million Veteran Program (MVP), the UK Biobank (UKB), the Psychiatric Genomics Consortium, and the CARDIoGRAMplusC4D Consortium. We observed a genetic correlation of CAD with PTSD case-control and quantitative outcomes, ranging from 0.18 to 0.32. To investigate possible cause-effect relationships underlying these genetic correlations, we performed a two-sample Mendelian randomization (MR) analysis, observing a significant bidirectional relationship between CAD and PTSD symptom severity. Genetically-determined PCL-17 (PTSD 17-item Checklist) total score was associated with increased CAD risk (odds ratio = 1.04; 95% confidence interval, 95% CI = 1.01-1.06). Conversely, CAD genetic liability was associated with reduced PCL-17 total score (beta = -0.42; 95% CI = -0.04 to -0.81). Because of these opposite-direction associations, we conducted a pleiotropic meta-analysis to investigate loci with concordant vs. discordant effects on PCL-17 and CAD, observing that concordant-effect loci were enriched for molecular pathways related to platelet amyloid precursor protein (beta = 1.53, p = 2.97 × 10-7) and astrocyte activation regulation (beta = 1.51, p = 2.48 × 10-6) while discordant-effect loci were enriched for biological processes related to lipid metabolism (e.g., triglyceride-rich lipoprotein particle clearance, beta = 2.32, p = 1.61 × 10-10). To follow up these results, we leveraged MVP and UKB electronic health records (EHR) to assess longitudinal changes in the association between CAD and posttraumatic stress severity. This EHR-based analysis highlighted that earlier CAD diagnosis is associated with increased PCL-total score later in life, while lower PCL total score was associated with increased risk of a later CAD diagnosis (Mann-Kendall trend test: MVP tau = 0.932, p < 2 × 10-16; UKB tau = 0.376, p = 0.005). In conclusion, both our genetically-informed analyses and our EHR-based follow-up investigation highlighted a bidirectional relationship between PTSD and CAD where multiple pleiotropic mechanisms are likely to be involved.

This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan^® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the β values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.

Smoking is a well-established risk factor for chronic non-communicable diseases. However, the relationship between cigarette smoking and the risk of developing mental health conditions remains largely elusive. This study examined the relationship between cigarette smoking as well as smoking cessation and prevalent and incident symptoms of depression, anxiety, and sleep disturbance in the general population.

In a cohort of 15,010 individuals from the Gutenberg Health Study (aged 35-74 years at enrollment), prevalent (at baseline from 2007 to 2012) and incident symptoms (at follow-up from 2012 to 2017) of depression, anxiety, and sleep disturbance were determined by validated questionnaires and/or medical records. Smoking status, pack-years of smoking in current and former smokers, and years since quitting smoking in former smokers were assessed by a standardized computer-assisted interview.

In multivariable logistic regression models with comprehensive adjustment for covariates, smoking status was independently associated with prevalent and incident symptoms of depression (Patient Health Questionnaire-9 ≥ 10), whereas this association was weaker for anxiety (Generalized Anxiety Disorder Scale-2 ≥ 3) and sleep disturbance (Patient Health Questionnaire-9 > 1). Among current and former smokers, smoking ≥30 or ≥10 pack-years, respectively, yielded in general the highest effect estimates. Smoking cessation was weakly associated with the prevalence and incidence of all outcomes, here consistent associations were observed for prevalent symptoms of depression.

The observational nature of the study does not allow for causal inferences.

The results of the present study suggest that cigarette smoking is positively and that smoking cessation is negatively associated with symptoms of common mental health conditions, in particular of depression.

The causal association between cigarette smoking and several diseases remains equivocal. The purpose of this study was to appraise the causal role of smoking in a wide range of diseases by summarizing the evidence from Mendelian randomization (MR) studies.

MR studies on genetic liability to smoking initiation or lifetime smoking (composite of smoking initiation, heaviness, duration, and cessation) in relation to circulatory system, digestive system, nervous system, musculoskeletal system, endocrine, metabolic, and eye diseases, and neoplasms published until February 15, 2022, were identified in PubMed. De novo MR analyses were performed using summary statistics data from genome-wide association studies. Meta-analysis was applied to combine study-specific estimates.

Meta-analyses of findings of 29 published MR studies and 123 de novo MR analyses of 57 distinct primary outcomes showed that genetic liability to smoking (smoking initiation or lifetime smoking) was associated with increased risk of 13 circulatory system diseases, several digestive system diseases (including diverticular, gallstone, gastroesophageal reflux, and Crohn's disease, acute pancreatitis, and periodontitis), epilepsy, certain musculoskeletal system diseases (including fracture, osteoarthritis, and rheumatoid arthritis), endocrine (polycystic ovary syndrome), metabolic (type 2 diabetes) and eye diseases (including age-related macular degeneration and senile cataract) as well as cancers of the lung, head and neck, esophagus, pancreas, bladder, kidney, cervix, and ovaries, and myeloid leukemia. Smoking liability was associated with decreased risk of Parkinson's disease and prostate cancer.

This study found robust evidence that cigarette smoking causes a wide range of diseases.

This work was supported by research grants from the Swedish Cancer Society (Cancerfonden), the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council for Health, Working Life and Welfare (Forte, 2018-00123), and the Swedish Research Council (Vetenskapsrådet, 2019-00977). Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z) and the National Institute for Health Research Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.

Observational studies reported conflicting results regarding the association between circulating concentrations of nutrition-related factors and atrial fibrillation (AF). The aim of this study was to evaluate the potential causal effect of 8 circulating nutrition-related factors (vitamin B12, vitamin E, folate, retinol, β-carotene, iron, zinc, and copper) on AF risk using mendelian randomization (MR). Summary-level data for the nutrition-related factors and AF were obtained from genome-wide association studies conducted among individuals of European ancestry. The genome-wide association study on AF included 60,620 cases and 970,216 controls. A 2-sample MR design was applied for evaluating the causal association. In the primary MR analyses, the inverse variance-weighted method did not identify any causal effect of circulating concentrations of vitamin B12 [β = 0.000, standard error (SE) = 0.021, P = 0.994], vitamin E (β = 0.080, SE = 0.152, P = 0.600), retinol (β = 0.098, SE = 0.397, P = 0.806), folate (β = -0.006, SE = 0.052, P = 0.901), β-carotene (β = 0.014, SE = 0.025, P = 0.560), iron (β = -0.009, SE = 0.072, P = 0.905), zinc (β = 0.038, SE = 0.032, P = 0.239), and copper (β = -0.012, SE = 0.023, P = 0.589) on AF. The MR-Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analyses did not suggest the presence of pleiotropy. In addition, the lack of association remained in the leave-one-out analysis. This MR study indicates no causal association of circulating concentrations of vitamin B12, vitamin E, folate, retinol, β-carotene, iron, zinc, and copper with AF.

Tobacco Use Disorder (TUD) is a health problem of the first order in the world population, affecting a vulnerable population, such as people with other mental disorders, whose morbidity and mortality are increased as a result.

There is increasing attention on the association of socioeconomic status and individual behaviors (SES/IB) with mental health. However, the impacts of SES/IB on mental disorders are still unclear. To provide evidence for establishing feasible strategies on disease screening and prevention, we implemented Mendelian randomization (MR) design to appraise causality between SES/IB and mental disorders.

We conducted a two-sample MR study to assess the causal effects of SES and IB (dietary habits, habitual physical activity, smoking behaviors, drinking behaviors, sleeping behaviors, leisure sedentary behaviors, risky behaviors, and reproductive behaviors) on three mental disorders, including bipolar disorder, major depressive disorder and schizophrenia. A series of filtering steps were taken to select eligible genetic instruments robustly associated with each of the traits. Inverse variance weighted was used for primary analysis, with alternative MR methods including MR-Egger, weighted median, and weighted mode estimate. Complementary methods were further used to detect pleiotropic bias.

After Bonferroni correction and rigorous quality control, we identified that SES (educational attainment), smoking behaviors (smoking initiation, number of cigarettes per day), risky behaviors (adventurousness, number of sexual partners, automobile speeding propensity) and reproductive behavior (age at first birth) were causally associated with at least one of the mental disorders.

MR study provides robust evidence that SES/IB play broad impacts on mental disorders.

Much research has found that smoking is one of the major risk factors for a variety of physical diseases and mental disorders; however, few studies have been conducted on smoking in Egypt. Furthermore, to the researcher's best knowledge, no study in Egypt has compiled data on smoking prevalence, motives, and levels of nicotine dependency. In order to fill in this gap, the current study has attempted to summarize the situation and construct an accurate picture of smoking in Egypt.

This cross-sectional study included 2000 Egyptian adults in Fayoum through a multistage cluster sampling technique. For data collection, the Socioeconomic Status Scale was deployed. In addition, Depression, Anxiety, Stress Scale (DASS), the Modified Reasons for Smoking Scale (MRSS), and Fagerstrom Test for Nicotine Dependence (FTND) were used. Data analysis performed using SPSS version 22.0. For qualitative data, Chi-square test was used to determine statistical significance. Bivariate Pearson correlation was used to test for the association between quantitative variables.

Of the total sample of 2000 adults, 40.4% had anxiety and 24.3% had stress, and 19.5% showed severe to extremely severe level of depression. For MRSS, tension reduction or relaxation was found in 46.5% adults while 9.8% had high level of nicotine dependence. There was a statistically significant association between psychometric disorders, on one hand, and both smoking motivation and nicotine dependence, on the other (P < 0.001). The DASS score had a statistically significant correlation with age, smoking duration, nicotine dependence level, and MRSS subscales.

Smoking is linked to psychological symptoms and shows a moderate to high level of nicotine dependence, with a higher level of dependency, smoking pleasure, stress reduction/ relaxation, and hand-mouth movement as motives for smoking. Furthermore, there was a correlation between nicotine dependence, on one hand, and depression and stress on the other.

Peripheral arterial disease (PAD) is a prevalent and debilitating disease that can be effectively treated by surgical revascularization. However, Medicare-Medicaid dual-eligible patients experience worse long-term outcomes, notably higher rates of amputation and mortality, relative to other insurance groups. This study aims to investigate how insurance status may perpetuate health disparities in PAD outcomes.

The National Inpatient Sample was queried from 2000 to 2011 for patients ≥18 years with PAD who underwent surgical revascularization with hospitalization. Patients were stratified by insurance, and dual-eligibles were compared to Medicare-only, Medicaid-only, private insurance, and self-pay patients. Multivariable regression analysis was performed to assess the effect of dual-eligible status on postoperative outcomes such as inpatient mortality, complications, and favorable discharge (home or home with services).

A total of 771,790 hospitalizations were included in the analysis and stratified according to insurance type. Dual-eligible patients had the highest rates of major (32%) and extreme (11%) severity of illness and the highest rates of major (19%) and extreme (6%) risk of mortality among all insurance groups (p<0.001). Dual-eligibility status was independently associated with reduced odds of favorable discharge relative to all patients (p<0.001) and increased length of stay relative to Medicare-only (p=0.002) and private-payor groups (p<0.001). While dual-eligible patients had increased mortality odds relative to Medicaid-only and self-pay groups, they did not have significantly different odds of perioperative complications relative to all other insurance groups.

Medicare-Medicaid dual-eligible patients with PAD had more severe clinical presentations, a greater risk of extended hospitalizations, and a lower likelihood of being discharged home, relative to patients without dual-eligibility. Further studies are needed to examine the link between discharge disposition and disparities in health outcomes, as well as investigate interventions that effectively address the increased severity of PAD in dual-eligible patients.

Poor mental health has consistently been associated with substance use (smoking, alcohol drinking, cannabis use, and consumption of caffeinated drinks). To properly inform public health policy it is crucial to understand the mechanisms underlying these associations, and most importantly, whether or not they are causal.

In this pre-registered systematic review, we assessed the evidence for causal relationships between mental health and substance use from Mendelian randomization (MR) studies, following PRISMA. We rated the quality of included studies using a scoring system that incorporates important indices of quality, such as the quality of phenotype measurement, instrument strength, and use of sensitivity methods.

Sixty-three studies were included for qualitative synthesis. The final quality rating was '-' for 16 studies, '- +' for 37 studies, and '+'for 10 studies. There was robust evidence that higher educational attainment decreases smoking and that there is a bi-directional, increasing relationship between smoking and (symptoms of) mental disorders. Another robust finding was that higher educational attainment increases alcohol use frequency, but decreases binge-drinking and alcohol use problems, and that mental disorders causally lead to more alcohol drinking without evidence for the reverse.

The current MR literature increases our understanding of the relationship between mental health and substance use. Bi-directional causal relationships are indicated, especially for smoking, providing further incentive to strengthen public health efforts to decrease substance use. Future MR studies should make use of large(r) samples in combination with detailed phenotypes, a wide range of sensitivity methods, and triangulate with other research methods.

This study analyzed gene expression messenger RNA data, from cases with major depressive disorder (MDD) and controls, using supervised machine learning (ML). We built on the methodology of prior studies to obtain more generalizable/reproducible results. First, we obtained a classifier trained on gene expression data from the dorsolateral prefrontal cortex of post-mortem MDD cases (n = 126) and controls (n = 103). An average area-under-the-receiver-operating-characteristics-curve (AUC) from 10-fold cross-validation of 0.72 was noted, compared to an average AUC of 0.55 for a baseline classifier (p = .0048). The classifier achieved an AUC of 0.76 on a previously unused testing-set. We also performed external validation using DLPFC gene expression values from an independent cohort of matched MDD cases (n = 29) and controls (n = 29), obtained from Affymetrix microarray (vs. Illumina microarray for the original cohort) (AUC: 0.62). We highlighted gene sets differentially expressed in MDD that were enriched for genes identified by the ML algorithm. Next, we assessed the ML classification performance in blood-based microarray gene expression data from MDD cases (n = 1,581) and controls (n = 369). We observed a mean AUC of 0.64 on 10-fold cross-validation, which was significantly above baseline (p = .0020). Similar performance was observed on the testing-set (AUC: 0.61). Finally, we analyzed the classification performance in covariates subgroups. We identified an interesting interaction between smoking and recall performance in MDD case prediction (58% accurate predictions in cases who are smokers vs. 43% accurate predictions in cases who are non-smokers). Overall, our results suggest that ML in combination with gene expression data and covariates could further our understanding of the pathophysiology in MDD.