Exploring shared genetic bases and causal relationships of schizophrenia and bipolar disorder with 28 cardiovascular and metabolic traits

Genome-Wide and Exome-Wide Association Study Identifies Genetic Underpinning of Comorbidity between Myocardial Infarction and Severe Mental Disorders

BACKGROUND

Myocardial Infarction (MI) and severe mental disorders (SMDs) are two types of highly prevalent and complex disorders and seem to have a relatively high possibility of mortality. However, the contributions of common and rare genetic variants to their comorbidity arestill unclear.

METHODS

We conducted a combined genome-wide association study (GWAS) and exome-wide association study (EWAS) approach.

RESULTS

Using gene-based and gene-set association analyses based on the results of GWAS, we found the common genetic underpinnings of nine genes (GIGYF2, KCNJ13, PCCB, STAG1, HLA-C, HLA-B, FURIN, FES, and SMG6) and nine pathways significantly shared between MI and SMDs. Through Mendelian randomization analysis, we found that twenty-seven genes were potential causal genes for SMDs and MI. Based on the exome sequencing data of MI and SMDs patients from the UK Biobank, we found that MUC2 was exome-wide significant in the two diseases. The gene-set analyses of the exome-wide association study indicated that pathways related to insulin processing androgen catabolic process and angiotensin receptor binding may be involved in the comorbidity between SMDs and MI. We also found that six candidate genes were reported to interact with known therapeutic drugs based on the drug-gene interaction information in DGIdb.

CONCLUSIONS

Altogether, this study revealed the overlap of common and rare genetic underpinning between SMDs and MI and may provide useful insights for their mechanism study and therapeutic investigations.

Type 2 diabetes mellitus is associated with manic morbidity in elderly patients with mood disorders

The association between mood disorders, especially bipolar disorder (BD), and metabolic disorders, is long known. However, to which extent metabolic disorders affect the course of mood disorders in late life is still open to inquiring. To assess the impact of type 2 diabetes mellitus (T2DM) on late-life mood disorders a retrospective chart review was performed. Elderly depressive patients (≥ 65 years) diagnosed with Major Depressive Disorder (N = 57) or BD (N = 43) and followed up for at least 18 months were included and subdivided according to the presence of T2DM comorbidity. Vascular encephalopathy (39.1% vs. 15.6%, P  = 0.021) and neurocognitive disorders (21.7% vs. 5.2%, P  = 0.028), were more frequently reported in patients with T2DM than in those without. Patients with T2DM showed a greater percentage of follow-up time in manic episodes (r = -0.23, P  = 0.020) and a higher rate of manic episode(s) during follow-up (21.7% vs. 5.2%, P  = 0.028) than those without. When restricting longitudinal analyses to patients with bipolar spectrum disorders, results were confirmed. In line with the well-known connection between BD and metabolic disorders, our data support an association between T2DM and unfavorable course of illness in the elderly with BD.

Polygenic risk for schizophrenia and bipolar disorder in relation to cardiovascular biomarkers

Individuals with schizophrenia and bipolar disorder are at an increased risk of cardiovascular disease (CVD), and a range of biomarkers related to CVD risk have been found to be abnormal in these patients. Common genetic factors are a putative underlying mechanism, alongside lifestyle factors and antipsychotic medication. However, the extent to which the altered CVD biomarkers are related to genetic factors involved in schizophrenia and bipolar disorder is unknown. In a sample including 699 patients with schizophrenia, 391 with bipolar disorder, and 822 healthy controls, we evaluated 8 CVD risk biomarkers, including BMI, and fasting plasma levels of CVD biomarkers from a subsample. Polygenic risk scores (PGRS) were obtained from genome-wide associations studies (GWAS) of schizophrenia and bipolar disorder from the Psychiatric Genomics Consortium. The CVD biomarkers were used as outcome variables in linear regression models including schizophrenia and bipolar disorder PGRS as predictors, age, sex, diagnostic category, batch and 10 principal components as covariates, controlling for multiple testing by Bonferroni correction for the number of independent tests. Bipolar disorder PGRS was significantly (p = 0.03) negatively associated with BMI after multiple testing correction, and schizophrenia PGRS was nominally negatively associated with BMI. There were no other significant associations between bipolar or schizophrenia PGRS, and other investigated CVD biomarkers. Despite a range of abnormal CVD risk biomarkers in psychotic disorders, we only found a significant negative association between bipolar disorder PGRS and BMI. This has previously been shown for schizophrenia PGRS and BMI, and warrants further exploration.

Multimorbidity in Severe Mental Illness as Part of the Neurodevelopmental Continuum: Physical Health-Related Endophenotypes of Schizophrenia-A Narrative Review

BACKGROUND

The majority of deaths in patients with schizophrenia and other severe mental illnesses (SMIs) are caused by natural causes, such as cardiovascular diseases (CVDs). The increased risk of CVD and other somatic diseases in SMIs cannot be fully explained by the contribution of traditional risk factors, behavioral risk factors, patients' lifestyle peculiarities, and the influence of antipsychotics. The present review has the following main objectives: (1) to aggregate evidence that neurodevelopmental disorders are the basis of SMIs; (2) to provide a review of studies that have addressed the shared genetic architecture of SMI and cardiovascular disease; and (3) to propose and substantiate the consideration of somatic diseases as independent endophenotypes of SMIs, which will make it possible to place the research of somatic diseases in SMIs within the framework of the concepts of the "neurodevelopmental continuum and gradient" and "endophenotype".

METHODS

A comprehensive literature search was performed on 1 July 2024. The search was performed using PubMed and Google Scholar databases up to June 2024.

RESULTS

The current literature reveals considerable overlap between the genetic susceptibility loci for SMIs and CVDs. We propose that somatic diseases observed in SMIs that have a shared genetic architecture with SMIs can be considered distinct physical health-related endophenotypes.

CONCLUSIONS

In this narrative review, the results of recent studies of CVDs in SMIs are summarized. Reframing schizophrenia as a multisystem disease should contribute to the activation of new research on somatic diseases in SMIs.

A network of transcriptomic signatures identifies novel comorbidity mechanisms between schizophrenia and somatic disorders

The clinical burden of mental illness, in particular schizophrenia and bipolar disorder, are driven by frequent chronic courses and increased mortality, as well as the risk for comorbid conditions such as cardiovascular disease and type 2 diabetes. Evidence suggests an overlap of molecular pathways between psychotic disorders and somatic comorbidities. In this study, we developed a computational framework to perform comorbidity modeling via an improved integrative unsupervised machine learning approach based on multi-rank non-negative matrix factorization (mrNMF). Using this procedure, we extracted molecular signatures potentially explaining shared comorbidity mechanisms. For this, 27 case-control microarray transcriptomic datasets across multiple tissues were collected, covering three main categories of conditions including psychotic disorders, cardiovascular diseases and type II diabetes. We addressed the limitation of normal NMF for parameter selection by introducing multi-rank ensembled NMF to identify signatures under various hierarchical levels simultaneously. Analysis of comorbidity signature pairs was performed to identify several potential mechanisms involving activation of inflammatory response auxiliarily interconnecting angiogenesis, oxidative response and GABAergic neuro-action. Overall, we proposed a general cross-cohorts computing workflow for investigating the comorbid pattern across multiple symptoms, applied it to the real-data comorbidity study on schizophrenia, and further discussed the potential for future application of the approach.

Alteration of DNA Methylation and Epigenetic Scores Associated With Features of Schizophrenia and Common Variant Genetic Risk

BACKGROUND

Unpacking molecular perturbations associated with features of schizophrenia is a critical step toward understanding phenotypic heterogeneity in this disorder. Recent epigenome-wide association studies have uncovered pervasive dysregulation of DNA methylation in schizophrenia; however, clinical features of the disorder that account for a large proportion of phenotypic variability are relatively underexplored.

METHODS

We comprehensively analyzed patterns of DNA methylation in a cohort of 381 individuals with schizophrenia from the deeply phenotyped Australian Schizophrenia Research Bank. Epigenetic changes were investigated in association with cognitive status, age of onset, treatment resistance, Global Assessment of Functioning scores, and common variant polygenic risk scores for schizophrenia. We subsequently explored alterations within genes previously associated with psychiatric illness, phenome-wide epigenetic covariance, and epigenetic scores.

RESULTS

Epigenome-wide association studies of the 5 primary traits identified 662 suggestively significant (p < 6.72 × 10-5) differentially methylated probes, with a further 432 revealed after controlling for schizophrenia polygenic risk on the remaining 4 traits. Interestingly, we uncovered many probes within genes associated with a variety of psychiatric conditions as well as significant epigenetic covariance with phenotypes and exposures including acute myocardial infarction, C-reactive protein, and lung cancer. Epigenetic scores for treatment-resistant schizophrenia strikingly exhibited association with clozapine administration, while epigenetic proxies of plasma protein expression, such as CCL17, MMP10, and PRG2, were associated with several features of schizophrenia.

CONCLUSIONS

Our findings collectively provide novel evidence suggesting that several features of schizophrenia are associated with alteration of DNA methylation, which may contribute to interindividual phenotypic variation in affected individuals.

Psychotic Disorders and the Risk of Type 2 Diabetes Mellitus, Atherosclerotic Cardiovascular Diseases, and All-Cause Mortality: A Population-Based Matched Cohort Study

BACKGRUOUND

The effects of psychotic disorders on cardiometabolic diseases and premature death need to be determined in Asian populations.

METHODS

In this population-based matched cohort study, the Korean National Health Insurance Service database (2002 to 2018) was used. The risk of type 2 diabetes mellitus (T2DM), acute myocardial infarction (AMI), ischemic stroke, composite of all cardiometabolic diseases, and all-cause death during follow-up was compared between individuals with psychotic disorders treated with antipsychotics (n=48,162) and 1:1 matched controls without psychiatric disorders among adults without cardiometabolic diseases before or within 3 months after baseline.

RESULTS

In this cohort, 53,683 composite cases of all cardiometabolic diseases (during median 7.38 years), 899 AMI, and 1,216 ischemic stroke cases (during median 14.14 years), 7,686 T2DM cases (during median 13.26 years), and 7,092 deaths (during median 14.23 years) occurred. The risk of all outcomes was higher in subjects with psychotic disorders than matched controls (adjusted hazard ratios [95% confidence intervals]: 1.522 [1.446 to 1.602] for T2DM; 1.455 [1.251 to 1.693] for AMI; 1.568 [1.373 to 1.790] for ischemic stroke; 1.595 [1.565 to 1.626] for composite of all cardiometabolic diseases; and 2.747 [2.599 to 2.904] for all-cause mortality) during follow-up. Similar patterns of associations were maintained in subgroup analyses but more prominent in younger individuals (P for interaction <0.0001) when categorized as those aged 18-39, 40-64, or ≥65 years.

CONCLUSION

Patients with psychotic disorders treated with antipsychotics were associated with increased risk of premature allcause mortality and cardiometabolic outcomes in an Asian population. This relationship was more pronounced in younger individuals, especially aged 18 to 39 years.

Association of clinical symptoms and cardiometabolic dysregulations in patients with schizophrenia spectrum disorders

BACKGROUND

Patients with schizophrenia spectrum disorders (SSD) have a shortened life expectancy related to cardiovascular diseases. We investigated the association of cognitive, positive, and negative symptoms with cardiometabolic dysregulations in SSD patients.

METHODS

Overall, 1,119 patients from the Genetic Risk and Outcome in Psychosis (GROUP) study were included. Cognitive function, positive and negative symptoms were assessed at baseline, 3-year, and 6-year. Cardiometabolic biomarkers were measured at 3-year follow-up. We used linear and multinomial logistic regression models to test the association between cardiometabolic biomarkers and clinical trajectories and performed mediation analyzes, while adjusting for clinical and demographic confounders.

RESULTS

Cognitive performance was inversely associated with increased body mass index (mean difference [β], βhigh = -1.24, 95% CI = -2.28 to 0.20, P = 0.02) and systolic blood pressure (βmild = 2.74, 95% CI = 0.11 to 5.37, P = 0.04). The severity of positive symptoms was associated with increased glycated hemoglobin (HbA1c) levels (βlow = -2.01, 95% CI = -3.21 to -0.82, P = 0.001). Increased diastolic blood pressure (ORhigh-decreased = 1.04, 95% CI = 1.01 to 1.08, P = 0.02; ORhigh-increased = 1.04, 95% CI = 1.00 to 1.08, P = 0.048) and decreased high-density lipoprotein (OR high-increased = 6.25, 95% CI = 1.81 to 21.59, P = 0.004) were associated with more severe negative symptoms. Increased HbA1c (ORmoderate = 1.05, 95% CI = 1.01 to 1.10, P = 0.024; ORhigh = 1.08, 95% CI = 1.02 to 1.14, P = 0.006) was associated with more severe positive symptoms. These associations were not mediated by antipsychotics.

CONCLUSIONS

We showed an association between cardiometabolic dysregulations and clinical and cognitive symptoms in SSD patients. The observed associations underscore the need for early identification of patients at risk of cardiometabolic outcomes.

Polygenic Risk Scores for Bipolar Disorder: Progress and Perspectives

Bipolar disorder (BD) is a common and highly heritable psychiatric disorder, the study of BD genetic characteristics can help with early prevention and individualized treatment. At the same time, BD is a highly heterogeneous polygenic genetic disorder with significant genetic overlap with other psychiatric disorders. In recent years, polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) data have been widely used in genetic studies of various complex diseases and can be used to explore the genetic susceptibility of diseases. This review discusses phenotypic associations and genetic correlations with other conditions of BD based on PRS, and provides ideas for genetic studies and prevention of BD.

Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors

OBJECTIVE

Schizophrenia is associated with increased risk of cardiovascular disease (CVD), although there is variation in risk among individuals. There are indications of shared genetic etiology between schizophrenia and CVD, but the nature of the overlap remains unclear. The aim of this study was to fill this gap in knowledge.

METHODS

Overlapping genetic architectures between schizophrenia and CVD risk factors were assessed by analyzing recent genome-wide association study (GWAS) results. The bivariate causal mixture model (MiXeR) was applied to estimate the number of shared variants and the conjunctional false discovery rate (conjFDR) approach was used to pinpoint specific shared loci.

RESULTS

Extensive genetic overlap was found between schizophrenia and CVD risk factors, particularly smoking initiation (N=8.6K variants) and body mass index (BMI) (N=8.1K variants). Several specific shared loci were detected between schizophrenia and BMI (N=304), waist-to-hip ratio (N=193), smoking initiation (N=293), systolic (N=294) and diastolic (N=259) blood pressure, type 2 diabetes (N=147), lipids (N=471), and coronary artery disease (N=35). The schizophrenia risk loci shared with smoking initiation had mainly concordant effect directions, and the risk loci shared with BMI had mainly opposite effect directions. The overlapping loci with lipids, blood pressure, waist-to-hip ratio, type 2 diabetes, and coronary artery disease had mixed effect directions. Functional analyses implicated mapped genes that are expressed in brain tissue and immune cells.

CONCLUSIONS

These findings indicate a genetic propensity to smoking and a reduced genetic risk of obesity among individuals with schizophrenia. The bidirectional effects of the shared loci with the other CVD risk factors may imply differences in genetic liability to CVD across schizophrenia subgroups, possibly underlying the variation in CVD comorbidity.

Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank

BACKGROUND

People with severe mental illness have a higher risk of cardiometabolic disease than the general population. Traditionally attributed to sociodemographic, behavioural factors and medication effects, recent genetic studies have provided evidence of shared biological mechanisms underlying mental illness and cardiometabolic disease. We aimed to determine whether signals in the DCC locus, implicated in psychiatric and cardiometabolic traits, were shared or distinct.

METHODS

In UK Biobank, we systematically assessed genetic variation in the DCC locus for association with metabolic, cardiovascular and psychiatric-related traits in unrelated "white British" participants (N = 402,837). Logistic or linear regression were applied assuming an additive genetic model and adjusting for age, sex, genotyping chip and population structure. Bonferroni correction for the number of independent variants was applied. Conditional analyses (including lead variants as covariates) and trans-ancestry analyses were used to investigate linkage disequilibrium between signals.

RESULTS

Significant associations were observed between DCC variants and smoking, anhedonia, body mass index (BMI), neuroticism and mood instability. Conditional analyses and linkage disequilibrium structure suggested signals for smoking and BMI were distinct from each other and the mood traits, whilst individual mood traits were inter-related in a complex manner.

LIMITATIONS

Restricting analyses in non-"white British" individuals to the phenotypes significant in the "white British" sample is not ideal, but the smaller samples sizes restricted the phenotypes possible to analyse.

CONCLUSIONS

Genetic variation in the DCC locus had distinct effects on BMI, smoking and mood traits, and therefore is unlikely to contribute to shared mechanisms underpinning mental and cardiometabolic traits.

Increased Metabolic Potential, Efficacy, and Safety of Emerging Treatments in Schizophrenia

Patients with schizophrenia experience a broad range of detrimental health outcomes resulting from illness severity, heterogeneity of disease, lifestyle behaviors, and adverse effects of antipsychotics. Because of these various factors, patients with schizophrenia have a much higher risk of cardiometabolic abnormalities than people without psychiatric illness. Although exposure to many antipsychotics increases cardiometabolic risk factors, mortality is higher in patients who are not treated versus those who are treated with antipsychotics. This indicates both direct and indirect benefits of adequately treated illness, as well as the need for beneficial medications that result in fewer cardiometabolic risk factors and comorbidities. The aim of the current narrative review was to outline the association between cardiometabolic dysfunction and schizophrenia, as well as discuss the confluence of factors that increase cardiometabolic risk in this patient population. An increased understanding of the pathophysiology of schizophrenia has guided discovery of novel treatments that do not directly target dopamine and that not only do not add, but may potentially minimize relevant cardiometabolic burden for these patients. Key discoveries that have advanced the understanding of the neural circuitry and pathophysiology of schizophrenia now provide possible pathways toward the development of new and effective treatments that may mitigate the risk of metabolic dysfunction in these patients. Novel targets and preclinical and clinical data on emerging treatments, such as glycine transport inhibitors, nicotinic and muscarinic receptor agonists, and trace amine-associated receptor-1 agonists, offer promise toward relevant therapeutic advancements. Numerous areas of investigation currently exist with the potential to considerably progress our knowledge and treatment of schizophrenia.

Associations of common genetic risk variants of the muscarinic acetylcholine receptor M2 with cardiac autonomic dysfunction in patients with schizophrenia

OBJECTIVES

Decreased vagal modulation, which has consistently been observed in schizophrenic patients, might contribute to increased cardiac mortality in schizophrenia. Previously, associations between CHRM2 (Cholinergic Receptor Muscarinic 2) and cardiac autonomic features have been reported. Here, we tested for possible associations between these polymorphisms and heart rate variability in patients with schizophrenia.

METHODS

A total of three single nucleotide polymorphisms (SNPs) in CHRM2 (rs73158705 A>G, rs8191992 T>A and rs2350782 T>C) that achieved significance (p < 5 * 10^-8) in genome-wide association studies for cardiac autonomic features were genotyped in 88 drug-naïve patients, 61 patients receiving antipsychotic medication and 144 healthy controls. Genotypes were analysed for associations with parameters of heart rate variability and complexity, in each diagnostic group.

RESULTS

We observed a significantly altered heart rate variability in unmedicated patients with identified genetic risk status in rs73158705 A>G, rs8191992 T>A and rs2350782 T>C as compared to genotype non-risk status. In patients receiving antipsychotic medication and healthy controls, these associations were not observed.

DISCUSSION

We report novel candidate genetic associations with cardiac autonomic dysfunction in schizophrenia, but larger cohorts are required for replication.

Association between brain similarity to severe mental illnesses and comorbid cerebral, physical, and cognitive impairments

Severe mental illnesses (SMIs) are often associated with compromised brain health, physical comorbidities, and cognitive deficits, but it is incompletely understood whether these comorbidities are intrinsic to SMI pathophysiology or secondary to having SMIs. We tested the hypothesis that cerebral, cardiometabolic, and cognitive impairments commonly observed in SMIs can be observed in non-psychiatric individuals with SMI-like brain patterns of deviation as seen on magnetic resonance imaging. 22,883 participants free of common neuropsychiatric conditions from the UK Biobank (age = 63.4 ± 7.5 years, range = 45-82 years, 50.9% female) were split into discovery and replication samples. The regional vulnerability index (RVI) was used to quantify each participant's respective brain similarity to meta-analytical patterns of schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder in gray matter thickness, subcortical gray matter volume, and white matter integrity. Cluster analysis revealed five clusters with distinct RVI profiles. Compared with a cluster with no RVI elevation, a cluster with RVI elevation across all SMIs and brain structures showed significantly higher volume of white matter hyperintensities (Cohen's d = 0.59, p_FDR < 10^-16), poorer cardiovascular (Cohen's d = 0.30, p_FDR < 10^-16) and metabolic (Cohen's d = 0.12, p_FDR = 1.3 × 10^-4) health, and slower speed of information processing (|Cohen's d| = 0.11-0.17, p_FDR = 1.6 × 10^-3-4.6 × 10^-8). This cluster also had significantly higher level of C-reactive protein and alcohol use (Cohen's d = 0.11 and 0.28, p_FDR = 4.1 × 10^-3 and 1.1 × 10^-11). Three other clusters with respective RVI elevation in gray matter thickness, subcortical gray matter volume, and white matter integrity showed intermediate level of white matter hyperintensities, cardiometabolic health, and alcohol use. Our results suggest that cerebral, physical, and cognitive impairments in SMIs may be partly intrinsic via shared pathophysiological pathways with SMI-related brain anatomical changes.

Genetic analysis of the PCSK9 locus in psychological, psychiatric, metabolic and cardiovascular traits in UK Biobank

The association between severe mental illness (SMI) and cardiovascular and metabolic disease (CMD) is poorly understood. PCSK9 is expressed in systems critical to both SMI and CMD and influences lipid homeostasis and brain function. We systematically investigated relationships between genetic variation within the PCSK9 locus and risk for both CMD and SMI. UK Biobank recruited ~500,000 volunteers and assessed a wide range of SMI and CMD phenotypes. We used genetic data from white British ancestry individuals of UK Biobank. Genetic association analyses were conducted in PLINK, with statistical significance defined by the number of independent SNPs. Conditional analyses and linkage disequilibrium assessed the independence of SNPs and the presence of multiple signals. Two genetic risk scores of lipid-lowering alleles were calculated and used as proxies for putative lipid-lowering effects of PCSK9. PCSK9 variants were associated with central adiposity, venous thrombosis embolism, systolic blood pressure, mood instability, and neuroticism (all p < 1.16 × 10-4). No secondary signals were identified. Conditional analyses and high linkage disequilibrium (r2 = 0.98) indicated that mood instability and central obesity may share a genetic signal. Genetic risk scores suggested that the lipid-lowering effects of PCSK9 may be causal for greater mood instability and higher neuroticism. This is the first study to implicate the PCSK9 locus in mood-disorder symptoms and related traits, as well as the shared pathology of SMI and CMD. PCSK9 effects on mood may occur via lipid-lowering mechanisms. Further work is needed to understand whether repurposing PCSK9-targeting therapies might improve SMI symptoms and prevent CMD.

Identification of genetic loci that overlap between schizophrenia and metabolic syndrome

Patients with schizophrenia (SCZ) frequently exhibit an elevated risk of metabolic syndrome (MetS), which may lead to a worse clinical outcome. Even though these two phenotypes are genetically linked, little is known about their shared genetic determinants. Here, we investigated whether SCZ and MetS share genetic risk factors. To examine the genetic overlap between the two disorders, we applied a comprehensive genetic overlap analysis by integrating GWAS data for SCZ (n = 320,404) and MetS (n = 291,107) at the genome, genetic variants, and gene levels. At the genome level, we observed polygenic overlap between SCZ and MetS by utilizing LDSC (r_g=-0.09, P = 1 × 10^-4) and GNOVA (rho=-0.04, P = 1.39 × 10^-8) analysis. At the SNP level, we performed conjunctional FDR (conjFDR) analysis to identify genetic variants simultaneously associated with two phenotypes. Based on conjFDR < 0.05, we identified 22 loci shared between SCZ and MetS. At the gene level, we further demonstrated that SCZ- and MetS-inferred gene expression overlapped across 49 GTEx tissues and highlighted the PCCB and KCTD13 genes as putative mediators of the genetic association. Overall, these findings shed novel light on the association between SCZ and MetS, and potentially enhance our knowledge of the high comorbidity and genetic processes that overlap between the two disorders.

Association of comorbid mental disorders with cardiovascular disease risk in patients with type 2 diabetes: A nationwide cohort study

OBJECTIVE

To examine the association between comorbid mental disorders and cardiovascular disease (CVD) risk among patients with type 2 diabetes.

METHOD

This retrospective cohort study was conducted using the claims data of 2,227,394 South Korean patients with type 2 diabetes. We analyzed the occurrence of CVD including myocardial infarction (MI) and ischemic stroke, CVD-specific mortality, and all-cause mortality according to comorbid mental disorders including depressive disorders, bipolar and related disorders, schizophrenia spectrum disorders, insomnia, and anxiety disorders.

RESULTS

Among the patients, 9.1% had a comorbid mental disorder. The adjusted hazard ratios (aHR) for MI, ischemic stroke, CVD-specific mortality, and all-cause mortality in patients with any mental disorder were 1.20 (95% CI, 1.17-1.24), 1.13 (95% CI, 1.11-1.16), 1.16 (95% CI, 1.12-1.20), and 1.21 (95% CI, 1.19-1.23), respectively. Each mental disorder increased the risk of all outcomes, particularly bipolar and related disorders and schizophrenia spectrum disorders.

CONCLUSION

Comorbid mental disorders increased the CVD risk in patients with type 2 diabetes, with significantly increased risks associated with schizophrenia spectrum disorders (aHR: 1.27 for MI and 1.50 for ischemic stroke) and bipolar and related disorders (aHR: 1.27 for MI and 1.45 for ischemic stroke).

Exploring Lead loci shared between schizophrenia and Cardiometabolic traits

Individuals with schizophrenia (SCZ) have, on average, a 10- to 20-year shorter expected life span than the rest of the population, primarily due to cardiovascular disease comorbidity. Genome-wide association studies (GWAS) have previously been used to separately identify common variants in SCZ and cardiometabolic traits. However, genetic variants jointly influencing both traits remain to be fully characterised. To assess overlaps (if any) between the genetic architecture of SCZ and cardiometabolic traits, we used conditional false discovery rate (FDR) and local genetic correlation statistical framework analyses. A conjunctional FDR was used to identify shared genetic traits between SCZ and cardiometabolic risk factors. We identified 144 genetic variants which were shared between SCZ and body mass index (BMI), and 15 variants shared between SCZ and triglycerides (TG). Furthermore, we discovered four novel single nucleotide polymorphisms (SNPs) (rs3865350, rs9860913, rs13307 and rs9614186) and four proximate genes (DERL2, SNX4, LY75 and EFCAB6) which were shared by SCZ and BMI. We observed that the novel genetic variant rs13307 and the most proximate gene LY75 exerted potential effects on SCZ and BMI comorbidity. Also, we observed a mixture of concordant and opposite direction associations with shared genetic variants. We demonstrated a moderate to high genetic overlap between SCZ and cardiometabolic traits associated with a pattern of bidirectional associations. Our data suggested a complex interplay between metabolism-related gene pathways in SCZ pathophysiology.

Cardiovascular disease risk in people with severe mental disorders: an update and call for action

PURPOSE OF REVIEW

Cardiovascular disease (CVD) is a major cause of premature death in people with severe mental disorders (SMDs). This review provides an update on the level of CVD mortality and morbidity, as well as the socioeconomic, psychosocial and genetic factors associated with the comorbidity, and offer directions for improved interventions to reduce CVD in SMDs.

RECENT FINDINGS

The level of CVD mortality and morbidity has sustained high in people with SMDs during the past decades, but the causal mechanism must be further elucidated. Psychosocial and socioeconomic challenges are frequent in SMDs as well as in CVD. Further, recent studies have revealed genetic variants jointly associated with SMDs, CVD risk and social factors. These findings highlight the need for more targeted interventions, prediction tools and psychosocial approaches to comorbid CVD in SMDs.

SUMMARY

The level of CVD comorbidity remains high in SMDs, indicating that most people with SMDs have not benefitted from recent medical advances. A complex interplay between genetic and social vulnerability to CVD, which differs across subgroups of patients, seems to be involved. Further research is required to meet the urgent need for earlier, more efficient intervention approaches and preventive strategies for comorbid CVD in SMD.

Inflammation subtypes in psychosis and their relationships with genetic risk for psychiatric and cardiometabolic disorders

Cardiometabolic disorders have known inflammatory implications, and peripheral measures of inflammation and cardiometabolic disorders are common in persons with psychotic disorders. Inflammatory signatures are also related to neurobiological and behavioral changes in psychosis. Relationships between systemic inflammation and cardiometabolic genetic risk in persons with psychosis have not been examined. Thirteen peripheral inflammatory markers and genome-wide genotyping were assessed in 122 participants (n ​= ​86 psychosis, n ​= ​36 healthy controls) of European ancestry. Cluster analyses of inflammatory markers classified higher and lower inflammation subgroups. Single-trait genetic risk scores (GRS) were constructed for each participant using previously reported GWAS summary statistics for the following traits: schizophrenia, bipolar disorder, major depressive disorder, coronary artery disease, type-2 diabetes, low-density lipoprotein, high-density lipoprotein, triglycerides, and waist-to-hip ratio. Genetic correlations across traits were quantified. Principal component (PC) analysis of the cardiometabolic GRSs generated six PC loadings used in regression models to examine associations with inflammation markers. Functional module discovery explored biological mechanisms of the inflammation association of cardiometabolic GRS genes. A subgroup of 38% persons with psychotic disorders was characterized with higher inflammation status. These higher inflammation individuals had lower BACS scores (p ​= ​0.038) compared to those with lower inflammation. The first PC of the cardiometabolic GRS matrix was related to higher inflammation status in persons with psychotic disorders (OR ​= ​2.037, p ​= ​0.001). Two of eight modules within the functional interaction network of cardiometabolic GRS genes were enriched for immune processes. Cardiometabolic genetic risk may predispose some individuals with psychosis to elevated inflammation which adversely impacts cognition associated with illness.

Genetics in psychiatry: Methods, clinical applications and future perspectives

Psychiatric disorders and related traits have a demonstrated genetic component, with heritability estimated by twin studies generally between 80% and 40%. Their pathogenesis is complex and multi-determined: environmental factors interact with a polygenic architecture, making difficult the development of models able to stratify patients or predict mental health outcomes. Despite this difficult challenge, relevant progress has been made in the field of psychiatric genetics in recent years. This review aims to present the main current methods in psychiatric genetics, their output, limitations, clinical applications, and possible future developments. Genome-wide association studies (GWASs) performed in increasingly large samples have led to the identification of replicated genetic loci associated with the risk of major psychiatric disorders, including schizophrenia and mood disorders. Statistical and biological approaches have been developed to improve our understanding of the etiopathogenetic mechanisms behind genome-wide significant associations, as well as for estimating the cumulative effect of risk variants at the individual level and the genetic overlap between different disorders, as pleiotropy is the rule rather than the exception. Clinical applications are available in the pharmacogenetics field. The main issues that remain to be addressed include improving ethnic diversity in genetic studies and the optimization of statistical power through methodological improvements, such as the definition of dimensional phenotypes with specific biological correlates and the integration of different types of omics data.

Novel disease associations with schizophrenia genetic risk revealed in ~400,000 UK Biobank participants

Schizophrenia is a serious mental disorder with considerable somatic and psychiatric morbidity. It is unclear whether comorbid health conditions predominantly arise due to shared genetic risk or consequent to having schizophrenia. To explore the contribution of genetic risk for schizophrenia, we analysed the effect of schizophrenia polygenic risk scores (PRS) on a broad range of health problems in 406 929 individuals with no schizophrenia diagnosis from the UK Biobank. Diagnoses were derived from linked health data including primary care, hospital inpatient records, and registers with information on cancer and deaths. Schizophrenia PRS were generated and tested for associations with general health conditions, 16 ICD10 main chapters, and 603 diseases using linear and logistic regressions. Higher schizophrenia PRS was significantly associated with poorer overall health ratings, more hospital inpatient diagnoses, and more unique illnesses. It was also significantly positively associated with 4 ICD10 chapters: mental disorders; respiratory diseases; digestive diseases; and pregnancy, childbirth and the puerperium, but negatively associated with musculoskeletal disorders. Thirty-one specific phenotypes were significantly associated with schizophrenia PRS, and the 19 novel findings include several musculoskeletal diseases, respiratory diseases, digestive diseases, varicose veins, pituitary hyperfunction, and other peripheral nerve disorders. These findings extend knowledge of the pleiotropic effect of genetic risk for schizophrenia and offer insight into how some conditions often comorbid with schizophrenia arise. Additional studies incorporating the genetic basis of hormone regulation and involvement of immune mechanisms in the pathophysiology of schizophrenia may further elucidate the biological mechanisms underlying schizophrenia and its comorbid conditions.

Insulinopathies of the brain? Genetic overlap between somatic insulin-related and neuropsychiatric disorders

The prevalence of somatic insulinopathies, like metabolic syndrome (MetS), obesity, and type 2 diabetes mellitus (T2DM), is higher in Alzheimer's disease (AD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD). Dysregulation of insulin signalling has been implicated in these neuropsychiatric disorders, and shared genetic factors might partly underlie this observed multimorbidity. We investigated the genetic overlap between AD, ASD, and OCD with MetS, obesity, and T2DM by estimating pairwise global genetic correlations using the summary statistics of the largest available genome-wide association studies for these phenotypes. Having tested these hypotheses, other potential brain "insulinopathies" were also explored by estimating the genetic relationship of six additional neuropsychiatric disorders with nine insulin-related diseases/traits. Stratified covariance analyses were then performed to investigate the contribution of insulin-related gene sets. Significant negative genetic correlations were found between OCD and MetS (rg = -0.315, p = 3.9 × 10-8), OCD and obesity (rg = -0.379, p = 3.4 × 10-5), and OCD and T2DM (rg = -0.172, p = 3 × 10-4). Significant genetic correlations with insulin-related phenotypes were also found for anorexia nervosa (AN), attention-deficit/hyperactivity disorder (ADHD), major depressive disorder, and schizophrenia (p < 6.17 × 10-4). Stratified analyses showed negative genetic covariances between AD, ASD, OCD, ADHD, AN, bipolar disorder, schizophrenia and somatic insulinopathies through gene sets related to insulin signalling and insulin receptor recycling, and positive genetic covariances between AN and T2DM, as well as ADHD and MetS through gene sets related to insulin processing/secretion (p < 2.06 × 10-4). Overall, our findings suggest the existence of two clusters of neuropsychiatric disorders, in which the genetics of insulin-related diseases/traits may exert divergent pleiotropic effects. These results represent a starting point for a new research line on "insulinopathies" of the brain.

Prenatal and Childhood Immuno-Metabolic Risk Factors for Adult Depression and Psychosis

Depression and psychosis have a developmental component to their origin. Epidemiologic evidence, which we synthesize in this nonsystematic review, suggests that early-life infection, inflammation, and metabolic alterations could play a role in the etiology of these psychiatric disorders. The risk of depression and psychosis is associated with prenatal maternal and childhood infections, which could be mediated by impaired neurodevelopment. Evidence suggests linear dose-response associations between elevated concentrations of circulating inflammatory markers in childhood, particularly the inflammatory cytokine interleukin 6, and the risk for depression and psychosis subsequently in early adulthood. Childhood inflammatory markers are also associated with persistence of depressive symptoms subsequently in adolescence and early adulthood. Developmental trajectories reflecting persistently high insulin levels during childhood and adolescence are associated with a higher risk of psychosis in adulthood, whereas increased adiposity during and after puberty is associated with the risk of depression. Together, these findings suggest that higher levels of infection, inflammation, and metabolic alterations commonly seen in people with depression and psychosis could be a cause for, rather than simply a consequence of, these disorders. Therefore, early-life immuno-metabolic alterations, as well as factors influencing these alterations such as adversity or maltreatment, could represent targets for prevention of these psychiatric disorders. Inflammation could also be an important treatment target for depression and psychosis. The field requires further research to examine sensitive periods when exposure to such immuno-metabolic alterations is most harmful. Interventional studies are also needed to test the potential usefulness of targeting early-life immuno-metabolic alterations for preventing adult depression and psychosis.

Ceramides: Shared Lipid Biomarkers of Cardiovascular Disease and Schizophrenia

INTRODUCTION

Schizophrenia, although a debilitating mental illness, greatly affects individuals' physical health as well. One of the leading somatic comorbidities associated with schizophrenia is cardiovascular disease, which has been estimated to be one of the leading causes of excess mortality in patients diagnosed with schizophrenia. Although the shared susceptibility to schizophrenia and cardiovascular disease is well established, the mechanisms linking these two disorders are not well understood. Genetic studies have hinted toward shared lipid metabolism abnormalities co-occurring in the two disorders, while lipid compounds have emerged as prognostic markers for cardiovascular disease. In particular, three ceramide species in the blood plasma, Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1), have been robustly linked to the latter disorder.

AIM

We aimed to assess the differences in abundances of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in the blood plasma of schizophrenia patients compared to healthy controls.

METHODS

We measured the abundances of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in a cohort of 82 patients with schizophrenia and 138 controls without a psychiatric diagnosis and validated the results using an independent cohort of 26 patients with schizophrenia, 55 control individuals, and 19 patients experiencing a first psychotic episode.

RESULTS

We found significant alterations for all three ceramide species Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) and a particularly strong difference in concentrations between psychiatric patients and controls for the ceramide species Cer(d18:1/18:0).

CONCLUSIONS

The alteration of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) levels in the blood plasma might be a manifestation of metabolic abnormalities common to both schizophrenia and cardiovascular disease.

Exploring the Relationship Between Schizophrenia and Cardiovascular Disease: A Genetic Correlation and Multivariable Mendelian Randomization Study

Individuals with schizophrenia have a reduced life-expectancy compared to the general population, largely due to an increased risk of cardiovascular disease (CVD). Clinical and epidemiological studies have been unable to unravel the nature of this relationship. We obtained summary-data of genome-wide-association studies of schizophrenia (N = 130 644), heart failure (N = 977 323), coronary artery disease (N = 332 477), systolic and diastolic blood pressure (N = 757 601), heart rate variability (N = 46 952), QT interval (N = 103 331), early repolarization and dilated cardiomyopathy ECG patterns (N = 63 700). We computed genetic correlations and conducted bi-directional Mendelian randomization (MR) to assess causality. With multivariable MR, we investigated whether causal effects were mediated by smoking, body mass index, physical activity, lipid levels, or type 2 diabetes. Genetic correlations between schizophrenia and CVD were close to zero (-0.02-0.04). There was evidence that liability to schizophrenia causally increases heart failure risk. This effect remained consistent with multivariable MR. There was also evidence that liability to schizophrenia increases early repolarization pattern, largely mediated by BMI and lipids. Finally, there was evidence that liability to schizophrenia increases heart rate variability, a direction of effect contrasting clinical studies. There was weak evidence that higher systolic blood pressure increases schizophrenia risk. Our finding that liability to schizophrenia increases heart failure is consistent with the notion that schizophrenia involves a systemic dysregulation of the body with detrimental effects on the heart. To decrease cardiovascular mortality among individuals with schizophrenia, priority should lie with optimal treatment in early stages of psychosis.

Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes

Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208-795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20-22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.

Associations and limited shared genetic aetiology between bipolar disorder and cardiometabolic traits in the UK Biobank

BACKGROUND

People with bipolar disorder (BPD) are more likely to die prematurely, which is partly attributed to comorbid cardiometabolic traits. Previous studies report cardiometabolic abnormalities in BPD, but their shared aetiology remains poorly understood. This study examined the phenotypic associations and shared genetic aetiology between BPD and various cardiometabolic traits.

METHODS

In a subset of the UK Biobank sample (N = 61 508) we investigated phenotypic associations between BPD (ncases = 4186) and cardiometabolic traits, represented by biomarkers, anthropometric traits and cardiometabolic diseases. To determine shared genetic aetiology in European ancestry, polygenic risk scores (PRS) and genetic correlations were calculated between BPD and cardiometabolic traits.

RESULTS

Several traits were significantly associated with increased risk for BPD, namely low total cholesterol, low high-density lipoprotein cholesterol, high triglycerides, high glycated haemoglobin, low systolic blood pressure, high body mass index, high waist-to-hip ratio; and stroke, coronary artery disease and type 2 diabetes diagnosis. BPD was associated with higher polygenic risk for triglycerides, waist-to-hip ratio, coronary artery disease and type 2 diabetes. Shared genetic aetiology persisted for coronary artery disease, when correcting PRS associations for cardiometabolic base phenotypes. Associations were not replicated using genetic correlations.

CONCLUSIONS

This large study identified increased phenotypic cardiometabolic abnormalities in BPD participants. It is found that the comorbidity of coronary artery disease may be based on shared genetic aetiology. These results motivate hypothesis-driven research to consider individual cardiometabolic traits rather than a composite metabolic syndrome when attempting to disentangle driving mechanisms of cardiometabolic abnormalities in BPD.

A common variation in HCN1 is associated with heart rate variability in schizophrenia

BACKGROUND

There is growing evidence for a shared genetic basis between schizophrenia risk and cardiovascular disease. Reduced efferent vagal activity, indexed by reduced heart rate variability (HRV), has been consistently described in patients with schizophrenia and may potentially contribute to the increased cardiovascular risk in these patients. In this study, we tested the hypothesis whether the established schizophrenia risk variant HCN1 rs16902086 (A > G) is associated with reduced HRV.

METHODS

We analyzed the risk status of HCN1 rs16902086 (AG/GG vs. AA genotype) in 83 unmedicated patients with schizophrenia and 96 healthy controls and investigated genotype-related impacts on various HRV parameters.

RESULTS

We observed significantly increased resting heart rates and a marked decrease of vagal modulation in our patient cohort. Strikingly, HCN1 rs16902086 (A > G) was associated with reduced HRV parameters in patients only. A trend towards more pronounced HRV deviations was observed in homozygous (GG) compared to heterozygous patients (AG).

CONCLUSION

We present first evidence for a genetic risk factor that is associated with decreased vagal modulation in unmedicated patients with schizophrenia. Moreover, our findings suggest that HCN1 might be involved in reduced vagal modulation and possibly in increased cardiac mortality in schizophrenia patients. Thus, our data indicate that reduced vagal modulation might be an endophenotype of schizophrenia.

The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

Understanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

The Role of Genetics in Bipolar Disorder

Bipolar disorder (BP) is a highly heritable disease, with heritability estimated between 60 and 85% by twin studies. The underlying genetic architecture was poorly understood for years since the available technology was limited to the candidate gene approach that did not allow to explore the contribution of multiple loci throughout the genome. BP is a complex disorder, which pathogenesis is influenced by a number of genetic variants, each with small effect size, and environmental exposures. Genome-wide association studies (GWAS) provided meaningful insights into the genetics of BP, including replicated genetic variants, and allowed the development of novel multi-marker methods for gene/pathway analysis and for estimating the genetic overlap between BP and other traits. However, the existing GWAS had also relevant limitations. Notably insufficient statistical power and lack of consideration of rare variants, which may be responsible for the relatively low heritability explained (~20% in the largest GWAS) compared to twin studies. The availability of data from large biobanks and automated phenotyping from electronic health records or digital phenotyping represent key steps for providing samples with adequate power for genetic analysis. Next-generation sequencing is becoming more and more feasible in terms of costs, leading to the rapid growth in the number of samples with whole-genome or whole-exome sequence data. These recent and unprecedented resources are of key importance for a more comprehensive understanding of the specific genetic factors involved in BP and their mechanistic action in determining disease onset and prognosis.

Lipid and Glycemic Profiles in Patients with Bipolar Disorder: Cholesterol Levels Are Reduced in Mania

Background and Objectives: Bipolar disorder (BD) is a severe mental condition with a lifetime prevalence estimated around 2% among the general population. Due to risk factors, etiological mechanisms, and the chronic use of psychotropic medications, people with BD are frequently affected by medical comorbidities, such as metabolic syndrome (MetS), associated with altered blood levels of glucose, cholesterol, and triglycerides. Moreover, the lipid concentration may be associated with the severity of psychiatric symptoms. Materials and Methods: Five hundred and forty-two in- and outpatients (418 affected by BD and 124 affected by schizophrenia) were recruited in two Italian university hospitals. A blood examination assessing the fasting glucose, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides was performed. Results: No significant differences were found in the lipid and glycemic profiles between patients with BD and schizophrenia. When considering only the BD sample, we found that patients experiencing a manic episode had significantly lower total cholesterol, HDL, and LDL than euthymic patients. Moreover, the total and LDL cholesterol levels were significantly lower in (hypo)manic than depressed patients. Mood episodes did not influence the triglyceride and glucose levels in our sample. Conclusions: Clinicians should pay attention to blood cholesterol levels in patients with BD, as differences in concentrations may predispose them to severe medical conditions and can be associated with the onset of mood episodes.

Exploring the Role of Contactins across Psychological, Psychiatric and Cardiometabolic Traits within UK Biobank

Individuals with severe mental illness have an increased risk of cardiometabolic diseases compared to the general population. Shared risk factors and medication effects explain part of this excess risk; however, there is growing evidence to suggest that shared biology (including genetic variation) is likely to contribute to comorbidity between mental and physical illness. Contactins are a family of genes involved in development of the nervous system and implicated, though genome-wide association studies, in a wide range of psychological, psychiatric and cardiometabolic conditions. Contactins are plausible candidates for shared pathology between mental and physical health. We used data from UK Biobank to systematically assess how genetic variation in contactin genes was associated with a wide range of psychological, psychiatric and cardiometabolic conditions. We also investigated whether associations for cardiometabolic and psychological traits represented the same or distinct signals and how the genetic variation might influence the measured traits. We identified: A novel genetic association between variation in CNTN1 and current smoking; two independent signals in CNTN4 for BMI; and demonstrated that associations between CNTN5 and neuroticism were distinct from those between CNTN5 and blood pressure/HbA1c. There was no evidence that the contactin genes contributed to shared aetiology between physical and mental illness.

Cardiovascular disease in patients with severe mental illness

Individuals diagnosed with schizophrenia or bipolar disorder have a life expectancy 15-20 years shorter than that in the general population. The rate of unnatural deaths, such as suicide and accidents, is high for these patients. Despite this increased proportion of unnatural deaths, physical conditions account for approximately 70% of deaths in patients with either schizophrenia or bipolar disorder, with cardiovascular disease contributing 17.4% and 22.0% to the reduction in overall life expectancy in men and women, respectively. Risk factors for cardiovascular disease, such as smoking, unhealthy diet and lack of exercise, are common in these patients, and lifestyle interventions have been shown to have small effects. Pharmacological interventions to reduce risk factors for cardiovascular disease have been proven to be effective. Treatment with antipsychotic drugs is associated with reduced mortality but also with an increased risk of weight gain, dyslipidaemia and diabetes mellitus. These patients have higher risks of both myocardial infarction and stroke but a lower risk of undergoing interventional procedures compared with the general population. Data indicate a negative attitude from clinicians working outside the mental health fields towards patients with severe mental illness. Education might be a possible method to decrease the negative attitudes towards these patients, thereby improving their rates of diagnosis and treatment.

Metabolic profile of methylazoxymethanol model of schizophrenia in rats and effects of three antipsychotics in long-acting formulation

Mortality in psychiatric patients with severe mental illnesses reaches a 2-3 times higher mortality rate compared to the general population, primarily due to somatic comorbidities. A high prevalence of cardiovascular morbidity can be attributed to the adverse metabolic effects of atypical antipsychotics (atypical APs), but also to metabolic dysregulation present in drug-naïve patients. The metabolic aspects of neurodevelopmental schizophrenia-like models are understudied. This study evaluated the metabolic phenotype of a methylazoxymethanol (MAM) schizophrenia-like model together with the metabolic effects of three APs [olanzapine (OLA), risperidone (RIS) and haloperidol (HAL)] administered via long-acting formulations for 8 weeks in female rats. Body weight, feed efficiency, serum lipid profile, gastrointestinal and adipose tissue-derived hormones (leptin, ghrelin, glucagon and glucagon-like peptide 1) were determined. The lipid profile was assessed in APs-naïve MAM and control cohorts of both sexes. Body weight was not altered by the MAM model, though cumulative food intake and feed efficiency was lowered in the MAM compared to CTR animals. The effect of the APs was also present; body weight gain was increased by OLA and RIS, while OLA induced lower weight gain in the MAM rats. Further, the MAM model showed lower abdominal adiposity, while OLA increased it. Serum lipid profile revealed MAM model-induced alterations in both sexes; total, HDL and LDL cholesterol levels were increased. The MAM model did not exert significant alterations in hormonal parameters except for elevation in leptin level. The results support intrinsic metabolic dysregulation in the MAM model in both sexes, but the MAM model did not manifest higher sensitivity to metabolic effects induced by antipsychotic treatment.

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes

Background

Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci. While well appreciated, almost all analyses of GWAS data consider reported disease phenotype values as is without accounting for potential misclassification.

Results

Here, we introduce Phenotype Latent variable Extraction of disease misdiagnosis (PheLEx), a GWAS analysis framework that learns and corrects misclassified phenotypes using structured genotype associations within a dataset. PheLEx consists of a hierarchical Bayesian latent variable model, where inference of differential misclassification is accomplished using filtered genotypes while implementing a full mixed model to account for population structure and genetic relatedness in study populations. Through simulations, we show that the PheLEx framework dramatically improves recovery of the correct disease state when considering realistic allele effect sizes compared to existing methodologies designed for Bayesian recovery of disease phenotypes. We also demonstrate the potential of PheLEx for extracting new potential loci from existing GWAS data by analyzing bipolar disorder and epilepsy phenotypes available from the UK Biobank. From the PheLEx analysis of these data, we identified new candidate disease loci not previously reported for these datasets that have value for supplemental hypothesis generation.

Conclusion

PheLEx shows promise in reanalyzing GWAS datasets to provide supplemental candidate loci that are ignored by traditional GWAS analysis methodologies.

Polygenic risk score for schizophrenia was not associated with glycemic level (HbA1c) in patients with non-affective psychosis: Genetic Risk and Outcome of Psychosis (GROUP) cohort study

INTRODUCTION

Type 2 diabetes (T2D) is a common comorbidity in patients with schizophrenia (SCZ). The underlying pathophysiologic mechanisms are yet to be fully elucidated, although it can be argued that shared genes, environmental factors or their interaction effect are involved. This study investigated the association between polygenic risk score of SCZ (PRS_SCZ) and glycated haemoglobin (HbA1c) while adjusting for polygenic risk score of T2D (PRS_T2D), and clinical and demographic covariables.

METHODS

Genotype, clinical and demographic data of 1129 patients with non-affective psychosis were extracted from Genetic Risk and Outcome of Psychosis (GROUP) cohort study. The glycated haemoglobin (HbA1c) was the outcome. PRS was calculated using standard methods. Univariable and multivariable linear regression analyses were applied to estimate associations. Additionally, sensitivity analysis based on multiple imputation was done. After correction for multiple testing, a two-sided p-value ≤.003 was considered to discover evidence for an association.

RESULTS

Of 1129 patients, 75.8% were male with median age of 29 years. The mean (standard deviation) HbA1c level was 35.1 (5.9) mmol/mol. There was no evidence for an association between high HbA1c level and increased PRS_SCZ (adjusted regression coefficient (aβ) = 0.69, standard error (SE) = 0.77, p-value = .37). On the other hand, there was evidence for an association between high HbA1c level and increased PRS_T2D (aβ = 0.93, SE = 0.32, p-value = .004), body mass index (aβ = 0.20, SE = 0.08, p-value = .01), diastolic blood pressure (aβ = 0.08, SE = 0.04, p-value = .03), late age of first psychosis onset (aβ = 0.19, SE = 0.05, p-value = .0004) and male gender (aβ = 1.58, SE = 0.81, p-value = .05). After multiple testing correction, there was evidence for an association between high HbA1c level and late age of first psychosis onset. Evidence for interaction effect between PRS_scz and antipsychotics was not observed. The multiple imputation-based sensitivity analysis provided consistent results with complete case analysis.

CONCLUSIONS

Glycemic dysregulation in patients with SCZ was not associated with PRS_SCZ. This suggests that the mechanisms of hyperglycemia or diabetes are at least partly independent from genetic predisposition to SCZ. Our findings show that the change in HbA1c level can be caused by at least in part due to PRS_T2D, late age of illness onset, male gender, and increased body mass index and diastolic blood pressure.

Integrated Analysis of Summary Statistics to Identify Pleiotropic Genes and Pathways for the Comorbidity of Schizophrenia and Cardiometabolic Disease

Genome-wide association studies (GWAS) have identified abundant risk loci associated with schizophrenia (SCZ), cardiometabolic disease (CMD) including body mass index, coronary artery diseases, type 2 diabetes, low- and high-density lipoprotein, total cholesterol, and triglycerides. Although recent studies have suggested that genetic risk shared between these disorders, the pleiotropic genes and biological pathways shared between them are still vague. Here we integrated comprehensive multi-dimensional data from GWAS, expression quantitative trait loci (eQTL), and gene set database to systematically identify potential pleiotropic genes and biological pathways shared between SCZ and CMD. By integrating the results from different approaches including FUMA, Sherlock, SMR, UTMOST, FOCUS, and DEPICT, we revealed 21 pleiotropic genes that are likely to be shared between SCZ and CMD. These genes include VRK2, SLC39A8, NT5C2, AMBRA1, ARL6IP4, OGFOD2, PITPNM2, CDK2AP1, C12orf65, ABCB9, SETD8, MPHOSPH9, FES, FURIN, INO80E, YPEL3, MAPK3, SREBF1, TOM1L2, GATAD2A, and TM6SF2. In addition, we also performed the gene-set enrichment analysis using the software of GSA-SNP2 and MAGMA with GWAS summary statistics and identified three biological pathways (MAPK-TRK signaling, growth hormone signaling, and regulation of insulin secretion signaling) shared between them. Our study provides insights into the pleiotropic genes and biological pathways underlying mechanisms for the comorbidity of SCZ and CMD. However, further genetic and functional studies are required to validate the role of these potential pleiotropic genes and pathways in the etiology of the comorbidity of SCZ and CMD, which should provide potential targets for future diagnostics and therapeutics.

Penetrance and Pleiotropy of Polygenic Risk Scores for Schizophrenia in 106,160 Patients Across Four Health Care Systems

OBJECTIVE

Individuals at high risk for schizophrenia may benefit from early intervention, but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts. The authors sought to test the utility of this approach in clinical settings and to evaluate the broader health consequences of high genetic risk for schizophrenia.

METHODS

The authors used electronic health records for 106,160 patients from four health care systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from summary statistics and tested for association with 1,359 disease categories, including schizophrenia and psychosis, in phenome-wide association studies. Effects were combined through meta-analysis across sites.

RESULTS

PRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS, 1.55; 95% CI=1.4, 1.7), and patients in the highest risk decile of the PRS distribution had up to 4.6-fold higher odds of schizophrenia compared with those in the bottom decile (95% CI=2.9, 7.3). PRSs were also positively associated with other phenotypes, including anxiety, mood, substance use, neurological, and personality disorders, as well as suicidal behavior, memory loss, and urinary syndromes; they were inversely related to obesity.

CONCLUSIONS

The study demonstrates that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in health care settings and has pleiotropic effects on related psychiatric disorders as well as other medical syndromes. The results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in health care systems.

Polygenic risk for schizophrenia, disordered eating behaviours and body mass index in adolescents

BACKGROUND

Recent studies suggest psychotic and eating disorders can be comorbid and could have shared genetic liability. However, this comorbidity has been overlooked in the epidemiological literature.AimsTo test whether polygenic risk scores (PRS) for schizophrenia are associated with disordered eating behaviours and body mass index (BMI) in the general population.

METHOD

Using data from the Avon Longitudinal Study of Parents and Children and random-effects logistic and linear regression models, we investigated the association between PRS for schizophrenia and self-reported disordered eating behaviours (binge eating, purging, fasting and excessive exercise) and BMI at 14, 16 and 18 years.

RESULTS

Of the 6920 children with available genetic data, 4473 (64.6%) and 5069 (73.3%) had at least one disordered eating and one BMI outcome measurement, respectively. An s.d. increase in PRS was associated with greater odds of having binge eating behaviours (odds ratio, 1.36; 95% CI 1.16-1.60) and lower BMI (coefficient, -0.03; 95% CI, -0.06 to -0.01).

CONCLUSIONS

Our findings suggest the presence of shared genetic risk between schizophrenia and binge eating behaviours. Intermediate phenotypes such as impaired social cognition and irritability, previously shown to be positively correlated in this sample with schizophrenia PRS, could represent risk factors for both phenotypes. Shared genetic liability between binge eating and schizophrenia could also explain higher rates of metabolic syndrome in individuals with schizophrenia, as binge eating could be a mediator of this association in drug-naïve individuals. The finding of an association between greater PRS and lower BMI, although consistent with existing epidemiological and genetic literature, requires further investigation.Declaration of interestNone.