Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders,bipolar disorder and major depressive disorder: a systematic review and meta‐analysis

Metabolic syndrome (MetS) and its components are highly predictive of cardiovascular diseases. The primary aim of this systematic review and meta‐analysis was to assess the prevalence of MetS and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder, comparing subjects with different disorders and taking into account demographic variables and psychotropic medication use. The secondary aim was to compare the MetS prevalence in persons with any of the selected disorders versus matched general population controls. The pooled MetS prevalence in people with severe mental illness was 32.6% (95% CI: 30.8%‐34.4%; N = 198; n = 52,678). Relative risk meta‐analyses established that there was no significant difference in MetS prevalence in studies directly comparing schizophrenia versus bipolar disorder, and in those directly comparing bipolar disorder versus major depressive disorder. Only two studies directly compared people with schizophrenia and major depressive disorder, precluding meta‐analytic calculations. Older age and a higher body mass index were significant moderators in the final demographic regression model (z = ?3.6, p = 0.0003, r² = 0.19). People treated with all individual antipsychotic medications had a significantly (p<0.001) higher MetS risk compared to antipsychotic‐naïve participants. MetS risk was significantly higher with clozapine and olanzapine (except vs. clozapine) than other antipsychotics, and significantly lower with aripiprazole than other antipsychotics (except vs. amisulpride). Compared with matched general population controls, people with severe mental illness had a significantly increased risk for MetS (RR = 1.58; 95% CI: 1.35‐1.86; p<0.001) and all its components, except for hypertension (p = 0.07). These data suggest that the risk for MetS is similarly elevated in the diagnostic subgroups of severe mental illness. Routine screening and multidisciplinary management of medical and behavioral conditions is needed in these patients. Risks of individual antipsychotics should be considered when making treatment choices.     

Prevalence,incidence and mortality from cardiovascular disease in patients with pooled and specific severe mental illness: a large‐scale meta‐analysis of 3,211,768 patients and 113,383,368 controls

People with severe mental illness (SMI) – schizophrenia, bipolar disorder and major depressive disorder – appear at risk for cardiovascular disease (CVD), but a comprehensive meta‐analysis is lacking. We conducted a large‐scale meta‐analysis assessing the prevalence and incidence of CVD; coronary heart disease; stroke, transient ischemic attack or cerebrovascular disease; congestive heart failure; peripheral vascular disease; and CVD‐related death in SMI patients (N=3,211,768) versus controls (N=113,383,368) (92 studies). The pooled CVD prevalence in SMI patients (mean age 50 years) was 9.9% (95% CI: 7.4‐13.3). Adjusting for a median of seven confounders, patients had significantly higher odds of CVD versus controls in cross‐sectional studies (odds ratio, OR=1.53, 95% CI: 1.27‐1.83; 11 studies), and higher odds of coronary heart disease (OR=1.51, 95% CI: 1.47‐1.55) and cerebrovascular disease (OR=1.42, 95% CI: 1.21‐1.66). People with major depressive disorder were at increased risk for coronary heart disease, while those with schizophrenia were at increased risk for coronary heart disease, cerebrovascular disease and congestive heart failure. Cumulative CVD incidence in SMI patients was 3.6% (95% CI: 2.7‐5.3) during a median follow‐up of 8.4 years (range 1.8‐30.0). Adjusting for a median of six confounders, SMI patients had significantly higher CVD incidence than controls in longitudinal studies (hazard ratio, HR=1.78, 95% CI: 1.60‐1.98; 31 studies). The incidence was also higher for coronary heart disease (HR=1.54, 95% CI: 1.30‐1.82), cerebrovascular disease (HR=1.64, 95% CI: 1.26‐2.14), congestive heart failure (HR=2.10, 95% CI: 1.64‐2.70), and CVD‐related death (HR=1.85, 95% CI: 1.53‐2.24). People with major depressive disorder, bipolar disorder and schizophrenia were all at increased risk of CVD‐related death versus controls. CVD incidence increased with antipsychotic use (p=0.008), higher body mass index (p=0.008) and higher baseline CVD prevalence (p=0.03) in patients vs. controls. Moreover, CVD prevalence (p=0.007), but not CVD incidence (p=0.21), increased in more recently conducted studies. This large‐scale meta‐analysis confirms that SMI patients have significantly increased risk of CVD and CVD‐related mortality, and that elevated body mass index, antipsychotic use, and CVD screening and management require urgent clinical attention.     

Diabetes mellitus in people with schizophrenia,bipolar disorder and major depressive disorder: a systematic review and large scale meta‐analysis

Type 2 diabetes mellitus (T2DM) is highly predictive of cardiovascular diseases and can have particularly deleterious health impacts in people with severe mental illness (SMI), i.e. schizophrenia, bipolar disorder or major depressive disorder. This meta‐analysis aimed: a) to describe pooled frequencies of T2DM in people with SMI; b) to analyze the influence of demographic, illness and treatment variables as well as T2DM assessment methods; and c) to describe T2DM prevalence in studies directly comparing persons with each specific SMI diagnosis to general population samples. The trim and fill adjusted pooled T2DM prevalence among 438,245 people with SMI was 11.3% (95% CI: 10.0%‐12.6%). In antipsychotic‐naïve participants, the prevalence of T2DM was 2.9% (95% CI: 1.7%‐4.8%). There were no significant diagnostic subgroup differences. A comparative meta‐analysis established that multi‐episode persons with SMI (N=133,470) were significantly more likely to have T2DM than matched controls (N=5,622,664): relative risk, RR=1.85, 95% CI: 1.45‐2.37, p<0.001. The T2DM prevalence was consistently elevated in each of the three major diagnostic subgroups compared to matched controls. Higher T2DM prevalences were observed in women with SMI compared to men (RR=1.43, 95% CI: 1.20‐1.69, p<0.001). Multi‐episode (versus first‐episode) status was the only significant predictor for T2DM in a multivariable meta‐regression analysis (r²=0.52, p<0.001). The T2DM prevalence was higher in patients prescribed antipsychotics, except for aripriprazole and amisulpride. Routine screening and multidisciplinary management of T2DM is needed. T2DM risks of individual antipsychotic medications should be considered when making treatment choices.     

Life expectancy at birth for people with serious mental illness and other major disorders from a secondary mental health care case register in London

Objective

Despite improving healthcare, the gap in mortality between people with serious mental illness (SMI) and general population persists, especially for younger age groups. The electronic database from a large and comprehensive secondary mental healthcare provider in London was utilized to assess the impact of SMI diagnoses on life expectancy at birth.

Method

People who were diagnosed with SMI (schizophrenia, schizoaffective disorder, bipolar disorder), substance use disorder, and depressive episode/disorder before the end of 2009 and under active review by the South London and Maudsley NHS Foundation Trust (SLAM) in southeast London during 2007–09 comprised the sample, retrieved by the SLAM Case Register Interactive Search (CRIS) system. We estimated life expectancy at birth for people with SMI and each diagnosis, from national mortality returns between 2007–09, using a life table method.

Results

A total of 31,719 eligible people, aged 15 years or older, with SMI were analyzed. Among them, 1,370 died during 2007–09. Compared to national figures, all disorders were associated with substantially lower life expectancy: 8.0 to 14.6 life years lost for men and 9.8 to 17.5 life years lost for women. Highest reductions were found for men with schizophrenia (14.6 years lost) and women with schizoaffective disorders (17.5 years lost).

Conclusion

The impact of serious mental illness on life expectancy is marked and generally higher than similarly calculated impacts of well-recognised adverse exposures such as smoking, diabetes and obesity. Strategies to identify and prevent causes of premature death are urgently required.     

Recording of Severe Mental Illness in United Kingdom Primary Care, 2000–2010

Background

There is increasing emphasis on primary care services for individuals with severe mental illnesses (SMI), including schizophrenia, bipolar disorder, and other non-organic psychotic disorders. However we lack information on how many people receive these different diagnoses in primary care. Primary care databases offer an opportunity to explore the recording of new SMI diagnoses in representative general practices.

Methods

We used data from The UK Health Improvement Network (THIN) primary care database including longitudinal patient records for individuals aged over 16 years from 437 general practices. We determined the annual GP recorded rate of first diagnosis of SMI by age, gender, social deprivation and urbanicity between 2000 and 2010.

Results

We identified 10,520 individuals with a first record of schizophrenia, bipolar disorder or other non-organic psychosis among 4,164,794 patients. This corresponded to a rate of first diagnosis of 46.4 per 100,000 person years at risk (PYAR) (95% CI 45.4 to 47.4) in the 16–65 age group. The rate of first record of schizophrenia was 9.2 per 100,000 PYAR (95% CI 8.7 to 9.6) in this age group, bipolar disorder was 15.0 per 100,000 PYAR (95% CI 14.4 to 15.5) and other non-organic psychotic disorder was 22.3 per 100,000 PYAR (95% CI 21.6 to 23.0).

Conclusions

The rates of GP recorded SMI in primary care records were broadly comparable to incidence rates from previous epidemiological studies of SMI and show similar patterns by socio-demographic characteristics. However there were some differences by specific diagnoses. GPs may be recording rates that are higher than those used to commission services.     

Autistic-Like Traits in Adult Patients with Mood Disorders and Schizophrenia

Autism spectrum disorder often co-occurs with other psychiatric disorders. Although a high prevalence of autistic-like traits/symptoms has been identified in the pediatric psychiatric population of normal intelligence, there are no reports from adult psychiatric population. This study examined whether there is a greater prevalence of autistic-like traits/symptoms in patients with adult-onset psychiatric disorders such as major depressive disorder (MDD), bipolar disorder, or schizophrenia, and whether such an association is independent of symptom severity. The subjects were 290 adults of normal intelligence between 25 and 59 years of age (MDD, n=125; bipolar disorder, n=56; schizophrenia, n=44; healthy controls, n=65). Autistic-like traits/symptoms were measured using the Social Responsiveness Scale for Adults. Symptom severity was measured using the Positive and Negative Symptoms Scale, the Hamilton Depression Rating Scale, and/or the Young Mania Rating Scale. Almost half of the clinical subjects, except those with remitted MDD, exhibited autistic-like traits/symptoms at levels typical for sub-threshold or threshold autism spectrum disorder. Furthermore, the proportion of psychiatric patients that demonstrated high autistic-like traits/symptoms was significantly greater than that of healthy controls, and not different between that of remitted or unremitted subjects with bipolar disorder or schizophrenia. On the other hand, remitted subjects with MDD did not differ from healthy controls with regard to the prevalence or degree of high autistic-like traits/symptoms. A substantial proportion of adults with bipolar disorder and schizophrenia showed high autistic-like traits/symptoms independent of symptom severity, suggesting a shared pathophysiology among autism spectrum disorder and these psychiatric disorders. Conversely, autistic-like traits among subjects with MDD were associated with the depressive symptom severity. These findings suggest the importance of evaluating autistic-like traits/symptoms underlying adult-onset psychiatric disorders for the best-suited treatment. Further studies with a prospective design and larger samples are needed.     

Mortality among People with Severe Mental Disorders Who Reach Old Age: A Longitudinal Study of a Community-Representative Sample of 37892 Men

Background

Severe mental illnesses are leading causes of disability worldwide. Their prevalence declines with age, possibly due to premature death. It is unclear, however, if people with severe mental disorders who reach older age still have lower life expectancy compared with their peers and if their causes of death differ.

Methods and Findings

Cohort study of a community-representative sample of 37892 Australian men aged 65–85 years in 1996–1998. Follow up was censored on the 31st December 2010. Lifetime prevalence of schizophrenia spectrum, bipolar, depressive and alcohol-induced disorder was established through record linkage. A subsample of 12136 consented to a face-to-face assessment of sociodemographic, lifestyle and clinical variables. Information about causes of death was retrieved from the Australian Death Registry. The prevalence of schizophrenia spectrum, bipolar, depressive and alcohol-induced disorders was 1.2%, 0.3%, 2.5% and 1.8%. The mortality hazard for men with a severe mental disorder was 2.3 and their life expectancy was reduced by 3 years. Mortality rates increased with age, but the gap between men with and without severe mental disorders was not attenuated by age. Cardiovascular diseases and cancer were the most frequent causes of death. The excess mortality associated with severe mental disorders could not be explained by measured sociodemographic, lifestyle or clinical variables.

Conclusions

The excess mortality associated with severe mental disorders persists in later life, and the causes of death of younger and older people with severe mental disorders are similar. Hazardous lifestyle choices, suboptimal access to health care, poor compliance with treatments, and greater severity of medical comorbidities may all contribute to this increased mortality. Unlike young adults, most older people will visit their primary care physician at least once a year, offering health professionals an opportunity to intervene in order to minimise the harms associated with severe mental disorders.     

Relative Risk of Acute Myocardial Infarction in People with Schizophrenia and Bipolar Disorder: A Population-Based Cohort Study

Objective

Despite high mortality associated with serious mental illness, risk of acute myocardial infarction (AMI) remains unclear, especially for patients with bipolar disorder. The main objective was to investigate the relative risk of AMI associated with schizophrenia and bipolar disorders in a national sample.

Method

Using nationwide administrative data, an 11-year historic cohort study was assembled, comprised of cases aged 18 and above who had received a diagnosis of schizophrenia or bipolar disorder, compared to a random sample of all other adults excluding those with diagnoses of serious mental illness. Incident AMI as a primary diagnosis was ascertained. Hazard ratios stratified by age and gender were calculated and Cox regression models were used to adjust for other covariates.

Results

A total of 70,225 people with schizophrenia or bipolar disorder and 207,592 people without serious mental illness were compared. Hazard ratios in men adjusted for age, income and urbanization were 1.15 (95% CI 1.01~1.32) for schizophrenia and 1.37 (1.08~1.73)for bipolar disorder, and in women, 1.85 (1.58~2.18) and 1.88(1.47~2.41) respectively. Further adjustment for treated hypertension, diabetes and hyperlipidaemia attenuated the hazard ratio for men with schizophrenia but not the other comparison groups. Hazard ratios were significantly stronger in women than men and were stronger in younger compared to older age groups for both disorders; however, gender modification was only significant in people with schizophrenia, and age modification only significant in people with bipolar disorder.

Conclusions

In this large national sample, schizophrenia and bipolar disorder were associated with raised risk of AMI in women and in the younger age groups although showed differences in potential confounding and modifying factors.     

Mitochondrial Dysfunction and Psychiatric Disorders

Mitochondrial oxidative phosphorylation is the major ATP-producing pathway, which supplies more than 95% of the total energy requirement in the cells. Damage to the mitochondrial electron transport chain has been suggested to be an important factor in the pathogenesis of a range of psychiatric disorders. Tissues with high energy demands, such as the brain, contain a large number of mitochondria, being therefore more susceptible to reduction of the aerobic metabolism. Mitochondrial dysfunction results from alterations in biochemical cascade and the damage to the mitochondrial electron transport chain has been suggested to be an important factor in the pathogenesis of a range of neuropsychiatric disorders, such as bipolar disorder, depression and schizophrenia. Bipolar disorder is a prevalent psychiatric disorder characterized by alternating episodes of mania and depression. Recent studies have demonstrated that important enzymes involved in brain energy are altered in bipolar disorder patients and after amphetamine administration, an animal model of mania. Depressive disorders, including major depression, are serious and disabling. However, the exact pathophysiology of depression is not clearly understood. Several works have demonstrated that metabolism is impaired in some animal models of depression, induced by chronic stress, especially the activities of the complexes of mitochondrial respiratory chain. Schizophrenia is a devastating mental disorder characterized by disturbed thoughts and perception, alongside cognitive and emotional decline associated with a severe reduction in occupational and social functioning, and in coping abilities. Alterations of mitochondrial oxidative phosphorylation in schizophrenia have been reported in several brain regions and also in platelets. Abnormal mitochondrial morphology, size and density have all been reported in the brains of schizophrenic individuals. Considering that several studies link energy impairment to neuronal death, neurodegeneration and disease, this review article discusses energy impairment as a mechanism underlying the pathophysiology of some psychiatric disorders, like bipolar disorder, depression and schizophrenia.     

Effects of antipsychotics,antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia,depression and bipolar disorder

People with severe mental illness have a considerably shorter lifespan than the general population. This excess mortality is mainly due to physical illness. Next to mental illness‐related factors, unhealthy lifestyle, and disparities in health care access and utilization, psychotropic medications can contribute to the risk of physical morbidity and mortality. We systematically reviewed the effects of antipsychotics, antidepressants and mood stabilizers on physical health outcomes in people with schizophrenia, depression and bipolar disorder. Updating and expanding our prior systematic review published in this journal, we searched MEDLINE (November 2009 ‐ November 2014), combining the MeSH terms of major physical disease categories (and/or relevant diseases within these categories) with schizophrenia, major depressive disorder and bipolar disorder, and the three major psychotropic classes which received regulatory approval for these disorders, i.e., antipsychotics, antidepressants and mood stabilizers. We gave precedence to results from (systematic) reviews and meta‐analyses wherever possible. Antipsychotics, and to a more restricted degree antidepressants and mood stabilizers, are associated with an increased risk for several physical diseases, including obesity, dyslipidemia, diabetes mellitus, thyroid disorders, hyponatremia; cardiovascular, respiratory tract, gastrointestinal, haematological, musculoskeletal and renal diseases, as well as movement and seizure disorders. Higher dosages, polypharmacy, and treatment of vulnerable (e.g., old or young) individuals are associated with greater absolute (elderly) and relative (youth) risk for most of these physical diseases. To what degree medication‐specific and patient‐specific risk factors interact, and how adverse outcomes can be minimized, allowing patients to derive maximum benefits from these medications, requires adequate clinical attention and further research.     

Growth factors as clinical biomarkers of prognosis and diagnosis in psychiatric disorders

The psychiatric disorders are one of the most disabling illnesses in the world and represent a major problem for public health. These disorders are characterized by neuroanatomical or biochemical changes and it has been suggested that such changes may be due to inadequate neurodevelopment. Diverse alterations in the gene expression and/or serum level of specific growth factors have been implicated in the etiology, symptoms and progression of some psychiatric disorders. Herein, we summarize the latest information regarding the role of brain-derived neurotrophic factor (BDNF), epidermal growth factor (EGF), fibroblast growth factor (FGF), Insulin-like growth factor (IGF-1), neuroregulin-1 (NGR-1), erythropoietin (EPO), vascular growth factor (VEGF), transforming growth factor beta (TGF-β), nerve growth factor (NGF) and others cytokines in the pathogenesis of schizophrenia, depression, bipolar and anxiety disorders. Focusing on the role of these growth factors and their relationship with the main impairments (cognitive, emotional and social) of these pathologies. Some of these signaling molecules may be suitable biological markers for diagnosis and prognosis in cognitive, mood and social disabilities across different mental disorders.     

Social jetlag and depression status: Results obtained from the Netherlands Study of Depression and Anxiety

Social jetlag, the misalignment between the internal clock and the socially required timing of activities, is highly prevalent, especially in people with an evening chronotype and is hypothesized to be related to the link between the evening chronotype and major depressive disorder. Although social jetlag has been linked to depressive symptoms in non-clinical samples, it has never been studied in patients with major depressive disorder (MDD). This study is aimed to study social jetlag in patients with major depressive disorder and healthy controls, and to further examine the link between social jetlag and depressive symptomatology. Patients with a diagnosis of MDD (n = 1084) and healthy controls (n = 385), assessed in a clinical interview, were selected from the Netherlands Study of Depression and Anxiety. Social jetlag was derived from the Munich Chronotype Questionnaire, by calculating the absolute difference between the midsleep on free days and midsleep on work days. Depression severity was measured with the Inventory of Depressive Symptomatology. It was found that patients with MDD did not show more social jetlag compared to healthy controls, neither in a model without medication use (β = 0.06, 95% CI: ?0.03–0.15, p = 0.17) nor in a model where medication use is accounted for. There was no direct association between the amount of social jetlag and depressive symptoms, neither in the full sample, nor in the patient group or the healthy control group. This first study on social jetlag in a clinical sample showed no differences in social jetlag between patients with MDD and healthy controls.     

The future of psychopharmacology: a critical appraisal of ongoing phase 2/3 trials,and of some current trends aiming to de-risk trial programmes of novel agents

Despite considerable progress in pharmacotherapy over the past seven decades, many mental disorders remain insufficiently treated. This situation is in part due to the limited knowledge of the pathophysiology of these disorders and the lack of biological markers to stratify and individualize patient selection, but also to a still restricted number of mechanisms of action being targeted in monotherapy or combination/augmentation treatment, as well as to a variety of challenges threatening the successful development and testing of new drugs. In this paper, we first provide an overview of the most promising drugs with innovative mechanisms of action that are undergoing phase 2 or 3 testing for schizophrenia, bipolar disorder, major depressive disorder, anxiety and trauma-related disorders, substance use disorders, and dementia. Promising repurposing of established medications for new psychiatric indications, as well as variations in the modulation of dopamine, noradrenaline and serotonin receptor functioning, are also considered. We then critically discuss the clinical trial parameters that need to be considered in depth when developing and testing new pharmacological agents for the treatment of mental disorders. Hurdles and perils threatening success of new drug development and testing include inadequacy and imprecision of inclusion/exclusion criteria and ratings, sub-optimally suited clinical trial participants, multiple factors contributing to a large/increasing placebo effect, and problems with statistical analyses. This information should be considered in order to de-risk trial programmes of novel agents or known agents for novel psychiatric indications, increasing their chances of success.     

A Novel Relationship for Schizophrenia,Bipolar, and Major Depressive Disorder. Part 8: a Hint from Chromosome 8 High Density Association Screen

Convergent evidence from genetics, symptomatology, and psychopharmacology implies that there are intrinsic connections between schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD); for example, any two or even three of these disorders could co-exist in some families. A total of 48,753 single nucleotide polymorphisms (SNPs) on chromosome 8 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type I), 177 MDD patients, and 1000 controls. Associated SNP loci were comprehensively revealed, and outstanding susceptibility genes were identified including CSMD1, NRG1, PXDNL, SGCZ, and TMEM66. Unexpectedly, flanking genes for up to 95.9 % of the associated SNPs were replicated (P ≤ 9.9E?8) in the enlarged cohort of 986 SCZ patients. Considering convergent evidence, our results implicate that bipolar disorder and major depressive disorder might be subtypes of schizophrenia.     

Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia,Bipolar Disorder,and Major Depressive Disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.     

Predicting loneliness with polygenic scores of social,psychological and psychiatric traits

Loneliness is a heritable trait that accompanies multiple disorders. The association between loneliness and mental health indices may partly be due to inherited biological factors. We constructed polygenic scores for 27 traits related to behavior, cognition and mental health and tested their prediction for self‐reported loneliness in a population‐based sample of 8798 Dutch individuals. Polygenic scores for major depressive disorder (MDD), schizophrenia and bipolar disorder were significantly associated with loneliness. Of the Big Five personality dimensions, polygenic scores for neuroticism and conscientiousness also significantly predicted loneliness, as did the polygenic scores for subjective well‐being, tiredness and self‐rated health. When including all polygenic scores simultaneously into one model, only 2 major depression polygenic scores remained as significant predictors of loneliness. When controlling only for these 2 MDD polygenic scores, only neuroticism and schizophrenia remain significant. The total variation explained by all polygenic scores collectively was 1.7%. The association between the propensity to feel lonely and the susceptibility to psychiatric disorders thus pointed to a shared genetic etiology. The predictive power of polygenic scores will increase as the power of the genome‐wide association studies on which they are based increases and may lead to clinically useful polygenic scores that can inform on the genetic predisposition to loneliness and mental health.     

Relationships between substance abuse/dependence and psychiatric disorders based on polygenic scores

Genetic susceptibility to substance use disorders (SUDs) is partially shared between substances. Heritability of any substance dependence, estimated as 54%, is partly explained by additive effects of common variants. Comorbidity between SUDs and other psychiatric disorders is frequent. The present study aims to analyze the additive role of common variants in this comorbidity using polygenic scores (PGSs) based on genome‐wide association study discovery samples of schizophrenia (SCZ), bipolar disorder, attention‐deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder and anxiety disorders, available from large consortia. PGSs were calculated for 534 patients meeting DSM‐IV criteria for dependence of a substance and abuse/dependence of another substance between alcohol, tobacco, cannabis, cocaine, opiates, hypnotics, stimulants, hallucinogens and solvents; and 587 blood donors from the same population, Iberians from Galicia, as controls. Significance of the PGS and percentage of variance explained were calculated by logistic regression. Using discovery samples of similar size, significant associations with SUDs were detected for SCZ PGS. SCZ PGS explained more variance in SUDs than in most psychiatric disorders. Cross‐disorder PGS based on five psychiatric disorders was significant after adjustment for the effect of SCZ PGS. SCZ PGS was significantly higher in women than in men abusing alcohol. Our findings indicate that SUDs share genetic susceptibility with SCZ to a greater extent than with other psychiatric disorders, including externalizing disorders such as attention‐deficit/hyperactivity disorder. Women have lower probability to develop substance abuse/dependence than men at similar PGS probably because of a higher social pressure against excessive drug use in women.     

Sedentary behavior and physical activity levels in people with schizophrenia,bipolar disorder and major depressive disorder: a global systematic review and meta‐analysis

People with severe mental illness (schizophrenia, bipolar disorder or major depressive disorder) die up to 15 years prematurely due to chronic somatic comorbidities. Sedentary behavior and low physical activity are independent yet modifiable risk factors for cardiovascular disease and premature mortality in these people. A comprehensive meta‐analysis exploring these risk factors is lacking in this vulnerable population. We conducted a meta‐analysis investigating sedentary behavior and physical activity levels and their correlates in people with severe mental illness. Major electronic databases were searched from inception up to April 2017 for articles measuring sedentary behavior and/or physical activity with a self‐report questionnaire or an objective measure (e.g., accelerometer). Random effects meta‐analyses and meta‐regression analyses were conducted. Sixty‐nine studies were included (N=35,682; 39.5% male; mean age 43.0 years). People with severe mental illness spent on average 476.0 min per day (95% CI: 407.3‐545.4) being sedentary during waking hours, and were significantly more sedentary than age‐ and gender‐matched healthy controls (p=0.003). Their mean amount of moderate or vigorous physical activity was 38.4 min per day (95% CI: 32.0‐44.8), being significantly lower than that of healthy controls (p=0.002 for moderate activity, p<0.001 for vigorous activity). People with severe mental illness were significantly less likely than matched healthy controls to meet physical activity guidelines (odds ratio = 1.5; 95% CI: 1.1‐2.0, p<0.001, I²=95.8). Lower physical activity levels and non‐compliance with physical activity guidelines were associated with male gender, being single, unemployment, fewer years of education, higher body mass index, longer illness duration, antidepressant and antipsychotic medication use, lower cardiorespiratory fitness and a diagnosis of schizophrenia. People with bipolar disorder were the most physically active, yet spent most time being sedentary. Geographical differences were detected, and inpatients were more active than outpatients and those living in the community. Given the established health benefits of physical activity and its low levels in people with severe mental illness, future interventions specifically targeting the prevention of physical inactivity and sedentary behavior are warranted in this population.     

Temporal trends in associations between severe mental illness and risk of cardiovascular disease: A systematic review and meta-analysis

BackgroundSevere mental illness (SMI; schizophrenia, bipolar disorders (BDs), and other nonorganic psychoses) is associated with increased risk of cardiovascular disease (CVD) and CVD-related mortality. To date, no systematic review has investigated changes in population level CVD-related mortality over calendar time. It is unclear if this relationship has changed over time in higher-income countries with changing treatments.Methods and findingsTo address this gap, a systematic review was conducted, to assess the association between SMI and CVD including temporal change. Seven databases were searched (last: November 30, 2021) for cohort or case–control studies lasting ≥1 year, comparing frequency of CVD mortality or incidence in high-income countries between people with versus without SMI. No language restrictions were applied. Random effects meta-analyses were conducted to compute pooled hazard ratios (HRs) and rate ratios, pooled standardised mortality ratios (SMRs), pooled odds ratios (ORs), and pooled risk ratios (RRs) of CVD in those with versus without SMI. Temporal trends were explored by decade. Subgroup analyses by age, sex, setting, world region, and study quality (Newcastle–Ottawa scale (NOS) score) were conducted. The narrative synthesis included 108 studies, and the quantitative synthesis 59 mortality studies (with (≥1,841,356 cases and 29,321,409 controls) and 28 incidence studies (≥401,909 cases and 14,372,146 controls). The risk of CVD-related mortality for people with SMI was higher than controls across most comparisons, except for total CVD-related mortality for BD and cerebrovascular accident (CVA) for mixed SMI. Estimated risks were larger for schizophrenia than BD. Pooled results ranged from SMR = 1.55 (95% confidence interval (CI): 1.33 to 1.81, p < 0.001), for CVA in people with BD to HR/rate ratio = 2.40 (95% CI: 2.25 to 2.55, p < 0.001) for CVA in schizophrenia. For schizophrenia and BD, SMRs and pooled HRs/rate ratios for CHD and CVD mortality were larger in studies with outcomes occurring during the 1990s and 2000s than earlier decades (1980s: SMR = 1.14, 95% CI: 0.57 to 2.30, p = 0.71; 2000s: SMR = 2.59, 95% CI: 1.93 to 3.47, p < 0.001 for schizophrenia and CHD) and in studies including people with younger age. The incidence of CVA, CVD events, and heart failure in SMI was higher than controls. Estimated risks for schizophrenia ranged from HR/rate ratio 1.25 (95% CI: 1.04 to 1.51, p = 0.016) for total CVD events to rate ratio 3.82 (95% CI: 3.1 to 4.71, p < 0.001) for heart failure. Incidence of CHD was higher in BD versus controls. However, for schizophrenia, CHD was elevated in higher-quality studies only. The HR/rate ratios for CVA and CHD were larger in studies with outcomes occurring after the 1990s. Study limitations include the high risk of bias of some studies as they drew a comparison cohort from general population rates and the fact that it was difficult to exclude studies that had overlapping populations, although attempts were made to minimise this.ConclusionsIn this study, we found that SMI was associated with an approximate doubling in the rate ratio of CVD-related mortality, particularly since the 1990s, and in younger groups. SMI was also associated with increased incidence of CVA and CHD relative to control participants since the 1990s. More research is needed to clarify the association between SMI and CHD and ways to mitigate this risk.

Amanda Lambert and co-workers study associations between severe mental illness and cardiovascular disease outcomes over time.