Exploring the pathogenetic association between schizophrenia and type 2 diabetes mellitus diseases based on pathway analysis

The relationship between schizophrenia or schizoaffective disorder and type 1 diabetes mellitus: a scoping review of observational studies

OBJECTIVE

Both schizophrenia and type 1 diabetes mellitus (T1D) are known as immune-related disorders. We systematically reviewed observational studies to explore the relationship between schizophrenia or schizoaffective disorder and T1D.

METHODS

A preliminary search of articles was completed using the following databases: Airiti Library, CINAHL Complete (via EBSCOhost), OVID MEDLINE, Embase, and PubMed. Two researchers independently assessed each study's quality based on Joanna Briggs Institute (JBI). A narrative review summarized the potential relationship between the two diseases.

RESULTS

Eleven studies were included in the final analysis. Six observational studies investigated the risk of schizophrenia and schizoaffective disorder in patients with T1D. Two studies showed negative correlations, one showed no correlation, and three showed positive correlations. On the other hand, five studies reported the prevalence of T1D in patients with schizophrenia. Two of them showed positive associations, and three others showed no association. Although the majority of the included studies suggested a positive association between the two medical conditions, these studies were still too heterogeneous to draw consistent results.

CONCLUSION

We found conflicting results regarding the bidirectional relationship between schizophrenia or schizoaffective disorder and T1D. These may stem from differences in study design, sampling methods, or definition of diagnoses, which are essential aspects to consider in future research.

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.

Glucose dysregulation in antipsychotic-naive first-episode psychosis: in silico exploration of gene expression signatures

Antipsychotic (AP)-naive first-episode psychosis (FEP) patients display early dysglycemia, including insulin resistance and prediabetes. Metabolic dysregulation may therefore be intrinsic to psychosis spectrum disorders (PSDs), independent of the metabolic effects of APs. However, the potential biological pathways that overlap between PSDs and dysglycemic states remain to be identified. Using meta-analytic approaches of transcriptomic datasets, we investigated whether AP-naive FEP patients share overlapping gene expression signatures with non-psychiatrically ill early dysglycemia individuals. We meta-analyzed peripheral transcriptomic datasets of AP-naive FEP patients and non-psychiatrically ill early dysglycemia subjects to identify common gene expression signatures. Common signatures underwent pathway enrichment analysis and were then used to identify potential new pharmacological compounds via Integrative Library of Integrated Network-Based Cellular Signatures (iLINCS). Our search results yielded 5 AP-naive FEP studies and 4 early dysglycemia studies which met inclusion criteria. We discovered that AP-naive FEP and non-psychiatrically ill subjects exhibiting early dysglycemia shared 221 common signatures, which were enriched for pathways related to endoplasmic reticulum stress and abnormal brain energetics. Nine FDA-approved drugs were identified as potential drug treatments, of which the antidiabetic metformin, the first-line treatment for type 2 diabetes, has evidence to attenuate metabolic dysfunction in PSDs. Taken together, our findings support shared gene expression changes and biological pathways associating PSDs with dysglycemic disorders. These data suggest that the pathobiology of PSDs overlaps and potentially contributes to dysglycemia. Finally, we find that metformin may be a potential treatment for early metabolic dysfunction intrinsic to PSDs.

The Gordian knot of the immune-redox systems' interactions in psychosis

During the last decades the attempt to enlighten the pathobiological substrate of psychosis, from merely focusing on neurotransmitters, has expanded into new areas like the immune and redox systems. Indeed, the inflammatory hypothesis concerning psychosis etiopathology has exponentially grown with findings reflecting dysfunction/aberration of the immune/redox systems' effector components namely cytokines, chemokines, CRP, complement system, antibodies, pro-/anti-oxidants, oxidative stress byproducts just to name a few. Yet, we still lie far from comprehending the underlying cellular mechanisms, their causality directions, and the moderating/mediating parameters affecting these systems; let alone the inter-systemic (between immune and redox) interactions. Findings from preclinical studies on the stress field have provided evidence indicative of multifaceted interactions among the immune and redox components so tightly intertwined as a Gordian knot. Interestingly the literature concerning the interactions between these same systems in the context of psychosis appears minimal (if not absent) and ambiguous. This review attempts to draw a frame of the immune-redox systems' interactions starting from basic research on the stress field and expanding on clinical studies with cohorts with psychosis, hoping to instigate new avenues of research.

Association between polymorphism rs2421943 of the insulin-degrading enzyme and schizophrenia: Preliminary report

BACKGROUND

Insulin-degrading enzyme (IDE) is an important gene in studies of the pathophysiology of type 2 diabetes mellitus (T2DM). Recent studies have suggested a possible link between type 2 diabetes mellitus (T2DM) and the pathophysiology of schizophrenia (SZ). At the same time, significant changes in insulin-degrading enzyme (IDE) gene expression have been found in the brains of people with schizophrenia. These findings highlight the need to further investigate the role of IDE in schizophrenia pathogenesis.

METHODS

We enrolled 733 participants from the Czech Republic, including 383 patients with schizophrenia and 350 healthy controls. Our study focused on the single nucleotide polymorphism (SNP) rs2421943 in the IDE gene, which has previously been associated with the pathogenesis of Alzheimer's disease. The SNP was analyzed using the PCR-RFLP method.

RESULTS

The G allele of the rs2421943 polymorphism was found to significantly increase the risk of developing SZ (p < 0.01) when a gender-based analysis showed that both AG and GG genotypes were associated with a more than 1.55 times increased risk of SZ in females (p < 0.03) but not in males. Besides, we identified a potential binding site at the G allele locus for has-miR-7110-5p, providing a potential mechanism for the observed association.

CONCLUSION

Our results confirm the role of the IDE gene in schizophrenia pathogenesis and suggest that future research should investigate the relationship between miRNA and estrogen influence on IDE expression in schizophrenia pathogenesis.

The immune-stress/endocrine-redox-metabolic nature of psychosis' etiopathology; focus on the intersystemic pathways interactions

The evidence supporting the involvement of a number of systems in the neurobiological etiopathology of psychosis has recently grown exponentially. Indeed, the focus of research has changed from measuring solely neurotransmitters to estimating parameters from fields like immunity, stress/endocrine, redox, and metabolism. Yet, little is known regarding the exact role of each one of these fields on the formation of not only the brain neuropathological substrate in psychosis but also the associated general systemic pathology, in terms of causality directions. Research has shown deviations in the levels and/or function of basic effector molecules of the aforementioned fields namely cytokines, pro-/anti- oxidants, glucocorticoids, catecholamines, glucose, and lipids metabolites as well as kynurenines, in psychosis. Yet the evidence regarding their impact on neurotransmitters is minimal and the findings concerning these systems' interactions in the psychotic context are even more dispersed. The present review aims to draw holistically the frame of the hitherto known "players" in the field of psychosis' cellular pathobiology, with a particular focus on their in-between interactions.

Schizophrenia: a disorder of broken brain bioenergetics

A substantial and diverse body of literature suggests that the pathophysiology of schizophrenia is related to deficits of bioenergetic function. While antipsychotics are an effective therapy for the management of positive psychotic symptoms, they are not efficacious for the complete schizophrenia symptom profile, such as the negative and cognitive symptoms. In this review, we discuss the relationship between dysfunction of various metabolic pathways across different brain regions in relation to schizophrenia. We contend that several bioenergetic subprocesses are affected across the brain and such deficits are a core feature of the illness. We provide an overview of central perturbations of insulin signaling, glycolysis, pentose-phosphate pathway, tricarboxylic acid cycle, and oxidative phosphorylation in schizophrenia. Importantly, we discuss pharmacologic and nonpharmacologic interventions that target these pathways and how such interventions may be exploited to improve the symptoms of schizophrenia.

The Role of Ketogenic Metabolic Therapy on the Brain in Serious Mental Illness: A Review

In search of interventions targeting brain dysfunction and underlying cognitive impairment in schizophrenia, we look at the brain and beyond to the potential role of dysfunctional systemic metabolism on neural network instability and insulin resistance in serious mental illness. We note that disrupted insulin and cerebral glucose metabolism are seen even in medication-naïve first-episode schizophrenia, suggesting that people with schizophrenia are at risk for Type 2 diabetes and cardiovascular disease, resulting in a shortened life span. Although glucose is the brain's default fuel, ketones are a more efficient fuel for the brain. We highlight evidence that a ketogenic diet can improve both the metabolic and neural stability profiles. Specifically, a ketogenic diet improves mitochondrial metabolism, neurotransmitter function, oxidative stress/inflammation, while also increasing neural network stability and cognitive function. To reverse the neurodegenerative process, increasing the brain's access to ketone bodies may be needed. We describe evidence that metabolic, neuroprotective, and neurochemical benefits of a ketogenic diet potentially provide symptomatic relief to people with schizophrenia while also improving their cardiovascular or metabolic health. We review evidence for KD side effects and note that although high in fat it improves various cardiovascular and metabolic risk markers in overweight/obese individuals. We conclude by calling for controlled clinical trials to confirm or refute the findings from anecdotal and case reports to address the potential beneficial effects of the ketogenic diet in people with serious mental illness.

Evidence for Shared Genetic Aetiology Between Schizophrenia, Cardiometabolic, and Inflammation-Related Traits: Genetic Correlation and Colocalization Analyses

BACKGROUND

Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology.

METHODS

We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology.

RESULTS

We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (rg = -0.07; 95% C.I., -0.03,0.12; P = .002) and BMI (rg = -0.09; 95% C.I., -0.06, -0.12; P = 1.83 × 10-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways.

CONCLUSIONS

LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.

Low-Level Brain Somatic Mutations Are Implicated in Schizophrenia

BACKGROUND

Somatic mutations arising from the brain have recently emerged as significant contributors to neurodevelopmental disorders, including childhood intractable epilepsy and cortical malformations. However, whether brain somatic mutations are implicated in schizophrenia (SCZ) is not well established.

METHODS

We performed deep whole exome sequencing (average read depth > 550×) of matched dorsolateral prefrontal cortex and peripheral tissues from 27 patients with SCZ and 31 age-matched control individuals, followed by comprehensive and strict analysis of somatic mutations, including mutagenesis signature, substitution patterns, and involved pathways. In particular, we explored the impact of deleterious mutations in GRIN2B through primary neural culture.

RESULTS

We identified an average of 4.9 and 5.6 somatic mutations per exome per brain in patients with SCZ and control individuals, respectively. These mutations presented with average variant allele frequencies of 8.0% in patients with SCZ and 7.6% in control individuals. Although mutational profiles, such as the number and type of mutations, showed no significant difference between patients with SCZ and control individuals, somatic mutations in SCZ brains were significantly enriched for SCZ-related pathways, including dopamine receptor, glutamate receptor, and long-term potentiation pathways. Furthermore, we showed that brain somatic mutations in GRIN2B (encoding glutamate ionotropic NMDA receptor subunit 2B), which were found in two patients with SCZ, disrupted the location of GRIN2B across the surface of dendrites among primary cultured neurons.

CONCLUSIONS

Taken together, this study shows that brain somatic mutations are associated with the pathogenesis of SCZ.

Mechanisms Underlying the Comorbidity of Schizophrenia and Type 2 Diabetes Mellitus

The mortality rate of patients with schizophrenia is high, and life expectancy is shorter by 10 to 20 years. Metabolic abnormalities including type 2 diabetes mellitus (T2DM) are among the main reasons. The prevalence of T2DM in patients with schizophrenia may be epidemiologically frequent because antipsychotics induce weight gain as a side effect and the cognitive dysfunction of patients with schizophrenia relates to a disordered lifestyle, poor diet, and low socioeconomic status. Apart from these common risk factors and risk factors unique to schizophrenia, accumulating evidence suggests the existence of common susceptibility genes between schizophrenia and T2DM. Functional proteins translated from common genetic susceptibility genes are known to regulate neuronal development in the brain and insulin in the pancreas through several common cascades. In this review, we discuss common susceptibility genes, functional cascades, and the relationship between schizophrenia and T2DM. Many genetic and epidemiological studies have reliably associated the comorbidity of schizophrenia and T2DM, and it is probably safe to think that common cascades and mechanisms suspected from common genes' functions are related to the onset of both schizophrenia and T2DM. On the other hand, even when genetic analyses are performed on a relatively large number of comorbid patients, the results are sometimes inconsistent, and susceptibility genes may carry only a low or moderate risk. We anticipate future directions in this field.

Peripheral metabolic state and immune system in first-episode psychosis - A gene expression study with a prospective one-year follow-up

he excess availability of glucose and lipids can also have an impact on the dynamics of activation and regulation of peripheral immune cellsWe aimed at understanding the correlations between peripheral metabolic state and immune system during the first year in first-episode psychosis (FEP). Patients with FEP (n = 67) and matched controls (n = 38), aged 18-40 years, were met at baseline, 2 and 12 months. Fasting peripheral blood samples were collected. We applied the NanoString nCounter in-solution hybridization technology to determine gene expression levels of 178 candidate genes reflecting activation of the immune system. Serum triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL) cholesterol and insulin and plasma glucose (fP-Gluc) were measured. We applied Ingenuity Pathway Analysis (IPA) to visualize enrichment of genes to functional classes. Strength of positive or negative regulation of the disease and functional pathways was deduced from IPA activation Z-score at the three evaluation points. We correlated gene expression with plasma glucose, triglycerids and HDL and LDL, and used hierarchical clustering of the pairwise correlations to identify groups of genes with similar correlation patterns with metabolic markers. In patients, initially, genes associated with the innate immune system response pathways were upregulated, which decreased by 12 months. Furthermore, genes associated with apoptosis and T cell death were downregulated, and genes associated with lipid metabolism were increasingly downregulated by 12 months. The immune activation was thus an acute phase during illness onset. At baseline, after controlling for multiple testing, 31/178 genes correlated positively with fasting glucose levels, and 54/178 genes negatively with triglycerides in patients only. The gene clusters showed patterns of correlations with metabolic markers over time. The results suggest a functional link between peripheral immune system and metabolic state in FEP. Metabolic factors may have had an influence on the initial activation of the innate immune system. Future work is necessary to understand the role of metabolic state in the regulation of immune response in the early phases of psychosis.

NOGEA: A Network-oriented Gene Entropy Approach for Dissecting Disease Comorbidity and Drug Repositioning

Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes on the interactome network, which provides a new way for predicting drug-disease associations. Through this method, 11 old drugs were newly identified and predicted to be effective for treating pancreatic cancer and then validated by in vitro experiments. Collectively, the NOGEA was useful for identifying master genes that control disease initiation and co-occurrence, thus providing a valuable strategy for drug efficacy screening and repositioning. NOGEA codes are publicly available at https://github.com/guozihuaa/NOGEA.

The Association Between Metabolic Disturbance and Cognitive Impairments in Early-Stage Schizophrenia

Background: Cognitive impairment is one of the core symptoms of schizophrenia, which is considered to be significantly correlated to prognosis. In recent years, many studies have suggested that metabolic disorders could be related to a higher risk of cognitive defects in a general setting. However, there has been limited evidence on the association between metabolism and cognitive function in patients with early-stage schizophrenia.

Methods: In this study, we recruited 172 patients with early-stage schizophrenia. Relevant metabolic parameters were examined and cognitive function was evaluated by using the MATRICS Consensus Cognitive Battery (MCCB) to investigate the relationship between metabolic disorder and cognitive impairment.

Results: Generally, the prevalence of cognitive impairment among patients in our study was 84.7% (144/170), which was much higher than that in the general population. Compared with the general Chinese setting, the study population presented a higher proportion of metabolic disturbance. Patients who had metabolic disturbance showed no significant differences on cognitive function compared with the other patients. Correlation analysis showed that metabolic status was significantly correlated with cognitive function as assessed by the cognitive domain scores (p < 0.05), while such association was not found in further multiple regression analysis.

Conclusions: Therefore, there may be no association between metabolic disorder and cognitive impairment in patients with early-stage schizophrenia.

Trial Registration: Clinicaltrials.gov, NCT03451734. Registered March 2, 2018 (retrospectively registered).

Isoform-specific roles for AKT in affective behavior, spatial memory, and extinction related to psychiatric disorders

AKT is implicated in neurological disorders. AKT has three isoforms, AKT1/AKT2/AKT3, with brain cell type-specific expression that may differentially influence behavior. Therefore, we examined single Akt isoform, conditional brain-specific Akt1, and double Akt1/3 mutant mice in behaviors relevant to neuropsychiatric disorders. Because sex is a determinant of these disorders but poorly understood, sex was an experimental variable in our design. Our studies revealed AKT isoform- and sex-specific effects on anxiety, spatial and contextual memory, and fear extinction. In Akt1 mutant males, viral-mediated AKT1 restoration in the prefrontal cortex rescued extinction phenotypes. We identified a novel role for AKT2 and overlapping roles for AKT1 and AKT3 in long-term memory. Finally, we found that sex-specific behavior effects were not mediated by AKT expression or activation differences between sexes. These results highlight sex as a biological variable and isoform- or cell type-specific AKT signaling as potential targets for improving treatment of neuropsychiatric disorders.

Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses

Background

A typical task in bioinformatics consists of identifying which features are associated with a target outcome of interest and building a predictive model. Automated machine learning (AutoML) systems such as the Tree-based Pipeline Optimization Tool (TPOT) constitute an appealing approach to this end. However, in biomedical data, there are often baseline characteristics of the subjects in a study or batch effects that need to be adjusted for in order to better isolate the effects of the features of interest on the target. Thus, the ability to perform covariate adjustments becomes particularly important for applications of AutoML to biomedical big data analysis.

Results

We developed an approach to adjust for covariates affecting features and/or target in TPOT. Our approach is based on regressing out the covariates in a manner that avoids ‘leakage’ during the cross-validation training procedure. We describe applications of this approach to toxicogenomics and schizophrenia gene expression data sets. The TPOT extensions discussed in this work are available at https://github.com/EpistasisLab/tpot/tree/v0.11.1-resAdj.

Conclusions

In this work, we address an important need in the context of AutoML, which is particularly crucial for applications to bioinformatics and medical informatics, namely covariate adjustments. To this end we present a substantial extension of TPOT, a genetic programming based AutoML approach. We show the utility of this extension by applications to large toxicogenomics and differential gene expression data. The method is generally applicable in many other scenarios from the biomedical field.

A link among schizophrenia, diabetes, and asthma: Role of Ca2+/cAMP signaling

Asthma has been associated with an increased risk for developing schizophrenia. In addition, schizophrenia has been associated with an increased risk for developing type 2 diabetes mellitus, resulting in an elevated cardiovascular risk and in a limited life expectancy. It is well discussed that dysregulations related to Ca²⁺ signaling could link these diseases, in addition to cAMP signaling pathways. Thus, revealing this interplay among schizophrenia, diabetes, and asthma may provide novel insights into the pathogenesis of these diseases. Publications involving Ca²⁺ and cAMP signaling pathways, schizophrenia, diabetes, and asthma (alone or combined) were collected by searching PubMed and EMBASE. Both Ca²⁺ and cAMP signaling pathways (Ca²⁺/cAMP signaling) control the release of neurotransmitters and hormones, in addition to airway smooth muscle contractility, then dysregulations of these cellular processes may be involved in these diseases. Taking into consideration, the experience of our group in this field, this narrative review debated the involvement of Ca²⁺/cAMP signaling in this link among schizophrenia, diabetes, and asthma, including its pharmacological implications.

Phosphoinositide-3-kinase regulatory subunit 1 gene polymorphisms are associated with schizophrenia and bipolar disorder in the Han Chinese population

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share many genetic risk factors. This study aimed to investigate the association of phosphoinositide-3-kinase regulatory subunit1 (PIK3R1) gene rs3756668 and rs3730089 polymorphisms with SCZ and BD risks and determine the expression levels of PIK3R1. A total of 548 SCZ cases, 512 BD cases, and 598 healthy controls were included in this study. Single nucleotide polymorphisms (SNPs) were genotyped using the Sequenom MassARRAY platform, and quantitative reverse transcription polymerase chain reaction was conducted to examine the mRNA expression of PIK3R1. The genotypic distribution of rs3756668 in the BD group was significantly different from that in the healthy controls (P = 0.038). After adjustment for gender and age was made, rs3730089 was significantly associated with the risk of SCZ [AA/(AG + GG): OR = 2.25, P_adj = 0.040; AA/GG: OR = 2.27, P_adj = 0.038]. The SNP rs3756668 was associated with the susceptibility of BD (AA+GG/AG: OR = 0.73, P = 0.011) and the association remained after adjusting for gender and age. The mRNA level of PIK3R1 was significantly upregulated in patients with BD compared with that in the control group (P < 0.001). In terms of the diagnostic value of PIK3R1 for BD, the receiver operating characteristic curve analysis showed an area under the curve of 0.809 with 74.0% sensitivity and 73.9% specificity. PIK3R1 may be the shared susceptibility gene of SCZ and BD and may be a potential diagnostic biomarker for BD.

The Relative Risk of Developing Type 2 Diabetes Mellitus in Young Adults with Schizophrenia Treated with Different Atypical Antipsychotic

Background and aim: While the link between antipsychotic treatment and metabolic adverse events, including type 2 diabetes mellitus (T2DM) are clear in adults with schizophrenia, in young this association is not so well studied although the use of secondgeneration antipsychotics (SGA) is more and more frequent.

Material and methods: The local diabetes register was compared with the list of all registered young adults (18-35 years) with schizophrenia 2 years retrospective and 2 years prospective. Cumulative incidence, rate of incidence and relative risk was calculated knowing the number of persons in this age group within this region.

Results: Cumulative incidence for exposed group was 0.7% with a rate of incidence of 6.27 (95%CI: 4.1-10.5) per 1,000 patientyears, when in normal population was 0.2%, respectively 2.01 (95%CI: 0.72-3.79). This means a relative risk of 3.4736 (95%CI: 1.79-6.72), p=0.0002 and NNH=202 (95%CI: 134-404). Multivariate analysis showed that gender male (OR=1.83; 95%CI: 0.9-2.7; p=0.002) and olanzapine prescription (OR=4.76; 95%CI: 1.7-7.7; p=0.0001) were independent risk factors for T2DM.

Conclusions: The metabolic risk should be taken in account every time introducing or changing a SGA in young schizophrenic patient, balancing the benefits and negative metabolic effects (especially with olanzapine). Healthy nutrition and physical activities are necessary components of these patients lifestyle to avoid early onset of T2DM.

Pyrosequencing analysis of IRS1 methylation levels in schizophrenia with tardive dyskinesia

Tardive dyskinesia (TD) is a serious side effect of certain antipsychotic medications that are used to treat schizophrenia (SCZ) and other mental illnesses. The methylation status of the insulin receptor substrate 1 (IRS1) gene is reportedly associated with SCZ; however, no study, to the best of the authors' knowledge, has focused on the quantitative DNA methylation levels of the IRS1 gene using pyrosequencing in SCZ with or without TD. The present study aimed to quantify DNA methylation levels of 4 CpG sites in the IRS1 gene using a Chinese sample including SCZ patients with TD and without TD (NTD) and healthy controls (HCs). The general linear model (GLM) was used to detect DNA methylation levels among the 3 proposed groups (TD vs. NTD vs. HC). Mean DNA methylation levels of 4 CpG sites demonstrated normal distribution. Pearson's correlation analysis did not reveal any significant correlations between the DNA methylation levels of the 4 CpG sites and the severity of SCZ. GLM revealed significant differences between the 3 groups for CpG site 1 and the average of the 4 CpG sites (P=0.0001 and P=0.0126, respectively). Furthermore, the TD, NTD and TD + NTD groups demonstrated lower methylation levels in CpG site 1 (P=0.0003, P<0.0001 and P<0.0001, respectively) and the average of 4 CpG sites (P=0.0176, P=0.0063 and P=0.003, respectively) compared with the HC group. The results revealed that both NTD and TD patients had significantly decreased DNA methylation levels compared with healthy controls, which indicated a significant association between the DNA methylation levels of the IRS1 gene with SCZ and TD.

Second-Generation Antipsychotics and Dysregulation of Glucose Metabolism: Beyond Weight Gain

Second-generation antipsychotics (SGAs) are the cornerstone of treatment for schizophrenia because of their high clinical efficacy. However, SGA treatment is associated with severe metabolic alterations and body weight gain, which can increase the risk of type 2 diabetes and cardiovascular disease, and greatly accelerate mortality. Several underlying mechanisms have been proposed for antipsychotic-induced weight gain (AIWG), but some studies suggest that metabolic changes in insulin-sensitive tissues can be triggered before the onset of AIWG. In this review, we give an outlook on current research about the metabolic disturbances provoked by SGAs, with a particular focus on whole-body glucose homeostasis disturbances induced independently of AIWG, lipid dysregulation or adipose tissue disturbances. Specifically, we discuss the mechanistic insights gleamed from cellular and preclinical animal studies that have reported on the impact of SGAs on insulin signaling, endogenous glucose production, glucose uptake and insulin secretion in the liver, skeletal muscle and the endocrine pancreas. Finally, we discuss some of the genetic and epigenetic changes that might explain the different susceptibilities of SGA-treated patients to the metabolic side-effects of antipsychotics.

Impaired insulin signaling in unaffected siblings and patients with first-episode psychosis

Patients with psychotic disorders are at high risk for type 2 diabetes mellitus, and there is increasing evidence that patients display glucose metabolism abnormalities before significant antipsychotic medication exposure. In the present study, we examined insulin action by quantifying insulin sensitivity in first-episode psychosis (FEP) patients and unaffected siblings, compared to healthy individuals, using a physiological-based model and comprehensive assessment battery. Twenty-two unaffected siblings, 18 FEP patients, and 15 healthy unrelated controls were evaluated using a 2-h oral glucose tolerance test (OGTT), with 7 samples of plasma glucose and serum insulin concentration measurements. Insulin sensitivity was quantified using the oral minimal model method. Lipid, leptin, free fatty acids, and inflammatory marker levels were also measured. Anthropometric, nutrient, and activity assessments were conducted; total body composition and fat distribution were determined using whole-body dual-energy X-ray absorptiometry. Insulin sensitivity significantly differed among groups (F = 6.01 and 0.004), with patients and siblings showing lower insulin sensitivity, compared to controls (P = 0.006 and 0.002, respectively). Body mass index, visceral adipose tissue area (cm²), lipids, leptin, free fatty acids, inflammatory markers, and activity ratings were not significantly different among groups. There was a significant difference in nutrient intake with lower total kilocalories/kilogram body weight in patients, compared to siblings and controls. Overall, the findings suggest that familial abnormal glucose metabolism or a primary insulin signaling pathway abnormality is related to risk for psychosis, independent of disease expression and treatment effects. Future studies should examine underlying biological mechanisms of insulin signaling abnormalities in psychotic disorders.

Increased risk of type 2 diabetes among the siblings of patients with schizophrenia

BACKGROUND

Research suggests an association between metabolic disorders, such as type 2 diabetes mellitus (T2DM), and schizophrenia. However, the risk of metabolic disorders in the unaffected siblings of patients with schizophrenia remains unclear.

METHODS

Using the Taiwan National Health Insurance Research Database, 3135 unaffected siblings of schizophrenia probands and 12,540 age-/sex-matched control subjects were included and followed up to the end of 2011. Individuals who developed metabolic disorders during the follow-up period were identified.

RESULTS

The unaffected siblings of schizophrenia probands had a higher prevalence of T2DM (3.4% vs. 2.6%, p = 0.010) than the controls. Logistic regression analyses with the adjustment of demographic data revealed that the unaffected siblings of patients with schizophrenia were more likely to develop T2DM (odds ratio [OR]: 1.39, 95% confidence interval [CI]: 1.10-1.75) later in life compared with the control group. Moreover, only female siblings of schizophrenia probands had an increased risk of hypertension (OR: 1.47, 95% CI: 1.07-2.01) during the follow-up compared with the controls.DiscussionThe unaffected siblings, especially sisters, of schizophrenia probands had a higher prevalence of T2DM and hypertension compared with the controls. Our study revealed a familial link between schizophrenia and T2DM in a large sample. Additional studies are required to investigate the shared pathophysiology of schizophrenia and T2DM.

Brain insulin action in schizophrenia: Something borrowed and something new

Insulin signaling in the central nervous system is at the intersection of brain and body interactions, and represents a fundamental link between metabolic and cognitive disorders. Abnormalities in brain insulin action could underlie the development of comorbid schizophrenia and type 2 diabetes. Among its functions, central nervous system insulin is involved in regulation of striatal dopamine levels, peripheral glucose homeostasis, and feeding regulation. In this review, we discuss the role and importance of central nervous system insulin in schizophrenia and diabetes pathogenesis from a historical and mechanistic perspective. We describe central nervous system insulin sites and pathways of action, with special emphasis on glucose metabolism, cognitive functioning, inflammation, and food preferences. Finally, we suggest possible mechanisms that may explain the actions of central nervous system insulin in relation to schizophrenia and diabetes, focusing on glutamate and dopamine signaling, intracellular signal transduction pathways, and brain energetics. Understanding the interplay between central nervous system insulin and schizophrenia is essential to disentangling this comorbid relationship and may provide novel treatment approaches for both neuropsychiatric and metabolic dysfunction. This article is part of the issue entitled 'Special Issue on Antipsychotics'.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

Candidate gene prioritization for non-communicable diseases based on functional information: Case studies

Candidate gene prioritization for complex non-communicable diseases is essential to understanding the mechanism and developing better means for diagnosing and treating these diseases. Many methods have been developed to prioritize candidate genes in protein-protein interaction (PPI) networks. Integrating functional information/similarity into disease-related PPI networks could improve the performance of prioritization. In this study, a candidate gene prioritization method was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease PPI networks with weights for nodes and edges based on functional information. Here, three types of non-communicable diseases with pathobiological similarity, Type 2 diabetes (T2D), coronary artery disease (CAD) and dilated cardiomyopathy (DCM), were used as case studies. Literature review and pathway enrichment analysis of top-ranked genes demonstrated the effectiveness of our method. Better performance was achieved after comparing our method with other existing methods. Pathobiological similarity among these three diseases was further investigated for common top-ranked genes to reveal their pathogenesis.

Dysglycaemia, Inflammation and Psychosis: Findings From the UK ALSPAC Birth Cohort

BACKGROUND

Psychosis is associated with both dysglycaemia and low-grade inflammation, but population-based studies investigating the interplay between these factors are scarce.

AIMS

(1) To explore the direction of association between markers of dysglycaemia, inflammation and psychotic experiences (PEs); and (2) To explore whether dysglycaemia moderates and/or mediates the association between inflammation and PEs.

METHOD

Data from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were modeled using logistic and linear regression to examine cross-sectional and longitudinal associations between markers of dysglycaemia (ages 9 and 18), interleukin-6 (IL-6) (age 9), and PEs (ages 12 and 18). We tested for an interaction between dysglycaemia and IL-6 on risk of PEs at age 18, and tested whether dysglycaemia mediated the relationship between IL-6 and PEs.

RESULTS

Based on 2627 participants, at age 18, insulin resistance (IR) was associated with PEs (adjusted OR = 2.32; 95% CI, 1.37-3.97). IR was associated with IL-6 both cross-sectionally and longitudinally. Interaction analyses under a multiplicative model showed that IR moderated the association between IL-6 at age 9 and PEs at age 18 (adjusted OR for interaction term = 2.18; 95% C.I., 1.06-4.49). Mediation analysis did not support a model of IR mediating the relationship between IL-6 and PEs.

IMPLICATIONS

IR is associated with PEs in young people even before the onset of clinical psychosis. Metabolic alterations may interact with childhood inflammation to increase risk of PEs. The findings have implications for clinical practice and future research.

Schizophrenia in type 2 diabetes mellitus: Prevalence and clinical characteristics

BACKGROUND

This study investigated the prevalence and characteristics of schizophrenia in patients with type 2 diabetes mellitus (T2DM) in Taiwan.

METHODS

National Health Insurance claims data for patients with principal diagnoses of schizophrenia and T2DM were analysed.

RESULTS

Compared with patients with schizophrenia in the general population (GP), those with schizophrenia and T2DM were more likely to have higher Charlson comorbidity index (CCI) scores and multiple comorbidities, and were older. The prevalence of schizophrenia was significantly higher in patients with T2DM than in the GP from 2000 to 2010. In addition, during this period, the prevalence of schizophrenia in patients with T2DM increased from 0.64% to 0.85%; such an increase in the GP was also observed. A high prevalence of schizophrenia was observed in patients with T2DM aged less than 60 years old; those residing in eastern Taiwan; those with incomes of ≤NT$17,280, NT$17,281-NT$22,880, NT$22,881-NT$28,800, and NT$36,301-NT$45,800; and those with CCI > 2.

CONCLUSIONS

Our study found the prevalence of schizophrenia is higher in patients with T2DM than in the GP, particularly those with earlier ages less than 60 years old. Public health initiatives are necessary to prevent and treat schizophrenia in patients with T2DM, specifically for those with the aforementioned and premature death risk.

Shared Biological Pathways Between Alzheimer's Disease and Ischemic Stroke

Alzheimer's disease (AD) and ischemic stroke (IS) are an immense socioeconomic burden worldwide. There is a possibility that shared genetic factors lead to their links at epidemiological and pathophysiological levels. Although recent genome-wide association studies (GWAS) have provided profound insights into the genetics of AD and IS, no shared genetic variants have been identified to date. This prompted us to initiate this study, which sought to identify shared pathways linking AD and IS. We took advantage of large-scale GWAS summary data of AD (17,008 AD cases and 37,154 controls) and IS (10,307 cases and 19,326 controls) to conduct pathway analyses using genetic pathways from multiple well-studied databases, including GO, KEGG, PANTHER, Reactome, and Wikipathways. Collectively, we discovered that AD and IS shared 179 GO categories (56 biological processes, 95 cellular components, and 28 molecular functions); and the following pathways: six KEGG pathways; two PANTHER pathways; four Reactome pathways; and one in Wikipathways pathway. The more fine-grained GO terms were mainly summarized into different functional categories: transcriptional and post-transcriptional regulation, synapse, endocytic membrane traffic through the endosomal system, signaling transduction, immune process, multi-organism process, protein catabolic metabolism, and cell adhesion. The shared pathways were roughly classified into three categories: immune system; cancer (NSCLC and glioma); and signal transduction pathways involving the cadherin signaling pathway, Wnt signaling pathway, G-protein signaling and downstream signaling mediated by phosphoinositides (PIPs). The majority of these common pathways linked to both AD and IS were supported by convincing evidence from the literature. In conclusion, our findings contribute to a better understanding of common biological mechanisms underlying AD and IS and serve as a guide to direct future research.

Patterns of Multimorbidity in Middle-Aged and Older Adults: An Analysis of the UK Biobank Data

OBJECTIVE

To assess the prevalence, disease clusters, and patterns of multimorbidity using a novel 2-stage approach in middle-aged and older adults from the United Kingdom.

PATIENTS AND METHODS

Data on 36 chronic conditions from 502,643 participants aged 40 to 69 years with baseline measurements between March 13, 2006, and October 1, 2010, from the UK Biobank were extracted. We combined cluster analysis and association rule mining to assess patterns of multimorbidity overall and by age, sex, and ethnicity. A maximum of 3 clusters and 30 disease patterns were mined. Comparisons were made using lift as the main measure of association.

RESULTS

Ninety-five thousand seven hundred-ten participants (19%) had 2 or more chronic conditions. The first cluster included only myocardial infarction and angina (lift=13.3), indicating that the likelihood of co-occurrence of these conditions is 13 times higher than in isolation. The second cluster consisted of 26 conditions, including cardiovascular, musculoskeletal, respiratory, and neurodegenerative diseases. The strongest association was found between heart failure and atrial fibrillation (lift=23.6). Diabetes was at the center of this cluster with strong associations with heart failure, chronic kidney disease, liver failure, and stroke (lift>2). The third cluster contained 8 highly prevalent conditions, including cancer, hypertension, asthma, and depression, and the strongest association was observed between anxiety and depression (lift=5.0).

CONCLUSION

Conditions such as diabetes, hypertension, and asthma are the epicenter of disease clusters for multimorbidity. A more integrative multidisciplinary approach focusing on better management and prevention of these conditions may help prevent other conditions in the clusters.

Genetically determined schizophrenia is not associated with impaired glucose homeostasis

Here, we used data from large genome-wide association studies to test the presence of causal relationships, conducting a Mendelian randomization analysis; and shared molecular mechanisms, calculating the genetic correlation, among schizophrenia, type 2 diabetes (T2D), and impaired glucose homeostasis. Although our Mendelian randomization analysis was well-powered, no causal relationship was observed between schizophrenia and T2D, or traits related to glucose impaired homeostasis. Similarly, we did not observe any global genetic overlap among these traits. These findings indicate that there is no causal relationships or shared mechanisms between schizophrenia and impaired glucose homeostasis.

Cholesterol and triglyceride levels in first-episode psychosis: systematic review and meta-analysis

BackgroundThe extent of metabolic and lipid changes in first-episode psychosis (FEP) is unclear.AimsTo investigate whether individuals with FEP and no or minimal antipsychotic exposure show lipid and adipocytokine abnormalities compared with healthy controls.MethodWe conducted a meta-analysis of studies examining lipid and adipocytokine parameters in individuals with FEP and no or minimal antipsychotic exposure v. a healthy control group. Studies reported fasting total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and leptin levels.ResultsOf 2070 citations retrieved, 20 case-control studies met inclusion criteria including 1167 patients and 1184 controls. Total cholesterol and LDL cholesterol levels were significantly decreased in patients v. controls, corresponding to an absolute reduction of 0.26 mmol/L and 0.15 mmol/L respectively. Triglyceride levels were significantly increased in the patient group, corresponding to an absolute increase of 0.08 mmol/L. However, HDL cholesterol and leptin levels were not altered in patients v. controls.ConclusionsTotal and LDL cholesterol levels are reduced in FEP, indicating that hypercholesterolaemia in patients with chronic disorder is secondary and potentially modifiable. In contrast, triglycerides are elevated in FEP. Hypertriglyceridaemia is a feature of type 2 diabetes mellitus, therefore this finding adds to the evidence for glucose dysregulation in this cohort. These findings support early intervention targeting nutrition, physical activity and appropriate antipsychotic prescription.

Intrinsic and Antipsychotic Drug-Induced Metabolic Dysfunction in Schizophrenia

For decades, there have been observations demonstrating significant metabolic disturbances in people with schizophrenia including clinically relevant weight gain, hypertension, and disturbances in glucose and lipid homeostasis. Many of these findings pre-date the use of antipsychotic drugs (APDs) which on their own are also strongly associated with metabolic side effects. The combination of APD-induced metabolic changes and common adverse environmental factors associated with schizophrenia have made it difficult to determine the specific contributions of each to the overall metabolic picture. Data from drug-naïve patients, both from the pre-APD era and more recently, suggest that there may be an intrinsic metabolic risk associated with schizophrenia. Nevertheless, these findings remain controversial due to significant clinical variability in both psychiatric and metabolic symptoms throughout patients' disease courses. Here, we provide an extensive review of classic and more recent literature describing the metabolic phenotype associated with schizophrenia. We also suggest potential mechanistic links between signaling pathways associated with schizophrenia and metabolic dysfunction. We propose that, beyond its symptomatology in the central nervous system, schizophrenia is also characterized by pathophysiology in other organ systems directly related to metabolic control.

Connecting myelin-related and synaptic dysfunction in schizophrenia with SNP-rich gene expression hubs

Combining genome-wide mapping of SNP-rich regions in schizophrenics and gene expression data in all brain compartments across the human life span revealed that genes with promoters most frequently mutated in schizophrenia are expression hubs interacting with far more genes than the rest of the genome. We summed up the differentially methylated “expression neighbors” of genes that fall into one of 108 distinct schizophrenia-associated loci with high number of SNPs. Surprisingly, the number of expression neighbors of the genes in these loci were 35 times higher for the positively correlating genes (32 times higher for the negatively correlating ones) than for the rest of the ~16000 genes. While the genes in the 108 loci have little known impact in schizophrenia, we identified many more known schizophrenia-related important genes with a high degree of connectedness (e.g. MOBP, SYNGR1 and DGCR6), validating our approach. Both the most connected positive and negative hubs affected synapse-related genes the most, supporting the synaptic origin of schizophrenia. At least half of the top genes in both the correlating and anti-correlating categories are cancer-related, including oncogenes (RRAS and ALDOA), providing further insight into the observed inverse relationship between the two diseases.

Impaired Glucose Homeostasis in First-Episode Schizophrenia: A Systematic Review and Meta-analysis

IMPORTANCE

Schizophrenia is associated with an increased risk of type 2 diabetes. However, it is not clear whether schizophrenia confers an inherent risk for glucose dysregulation in the absence of the effects of chronic illness and long-term treatment.

OBJECTIVE

To conduct a meta-analysis examining whether individuals with first-episode schizophrenia already exhibit alterations in glucose homeostasis compared with controls.

DATA SOURCES

The EMBASE, MEDLINE, and PsycINFO databases were systematically searched for studies examining measures of glucose homeostasis in antipsychotic-naive individuals with first-episode schizophrenia compared with individuals serving as controls.

STUDY SELECTION

Case-control studies reporting on fasting plasma glucose levels, plasma glucose levels after an oral glucose tolerance test, fasting plasma insulin levels, insulin resistance, and hemoglobin A1c (HbA1c) levels in first-episode antipsychotic-naive individuals with first-episode schizophrenia compared with healthy individuals serving as controls. Two independent investigators selected the studies.

DATA EXTRACTION

Two independent investigators extracted study-level data for a random-effects meta-analysis. Standardized mean differences in fasting plasma glucose levels, plasma glucose levels after an oral glucose tolerance test, fasting plasma insulin levels, insulin resistance, and HbA1c levels were calculated. Sensitivity analyses examining the effect of body mass index, diet and exercise, race/ethnicity, and minimal (≤2 weeks) antipsychotic exposure were performed.

DATA SYNTHESIS

Of 3660 citations retrieved, 16 case-control studies comprising 15 samples met inclusion criteria. The overall sample included 731 patients and 614 controls. Fasting plasma glucose levels (Hedges g = 0.20; 95% CI, 0.02 to 0.38; P = .03), plasma glucose levels after an oral glucose tolerance test (Hedges g = 0.61; 95% CI, 0.16 to 1.05; P = .007), fasting plasma insulin levels (Hedges g = 0.41; 95% CI, 0.09 to 0.72; P = .01), and insulin resistance (homeostatic model assessment of insulin resistance) (Hedges g = 0.35; 95% CI, 0.14 to 0.55; P = .001) were all significantly elevated in patients compared with controls. However, HbA1c levels (Hedges g = -0.08; CI, -0.34 to 0.18; P = .55) were not altered in patients compared with controls.

CONCLUSIONS AND RELEVANCE

These findings show that glucose homeostasis is altered from illness onset in schizophrenia, indicating that patients are at increased risk of diabetes as a result. This finding has implications for the monitoring and treatment choice for patients with schizophrenia.

Meta-analysis of glucose tolerance, insulin, and insulin resistance in antipsychotic-naïve patients with nonaffective psychosis

BACKGROUND

Some studies have suggested that antipsychotic-naïve patients with nonaffective psychosis (NAP) have glucose intolerance.

AIMS

To conduct a systematic review and meta-analysis of fasting glucose (FG), two hour values in the oral glucose tolerance test (2HG), fasting insulin concentration (INS), and insulin resistance (IR).

METHOD

We identified possibly relevant studies, then selected studies, following usual guidelines, with two authors reviewing the manuscripts. We required studies to include subjects with nonaffective psychosis and control subjects.

RESULTS

There were 911 patients and 870 control subjects in the analysis of FG; their average ages were respectively 28.7 and 29.5years. Significant differences were found for all four variables, with effect size estimates ranging from 0.21 to 0.58.

CONCLUSIONS

As a group, at the time of first clinical contact for psychosis, people with NAP have a slight increase in FG, which most of them maintain in the normal range despite a small increase in IR by secreting additional INS. When faced with a physiological challenge such as a glucose tolerance test or antipsychotics, they are no longer able to maintain a normal glucose concentration.

Metabolic pathways in the periphery and brain: Contribution to mental disorders?

The association between mental disorders and diabetes has a long history. Recent large-scale, well-controlled epidemiological studies confirmed a link between diabetes and psychiatric illnesses. The scope of this review is to summarize our current understanding of this relationship from a molecular perspective. We first discuss the potential contribution of diabetes-associated metabolic impairments to the etiology of mental conditions. Then, we focus on possible shared molecular risk factors and mechanisms. Simple comorbidity, shared susceptibility loci, and common pathophysiological processes in diabetes and mental illnesses have changed our traditional way of thinking about mental illness. We conclude that schizophrenia and affective disorders are not limited to an imbalance in dopaminergic and serotoninergic neurotransmission in the brain. They are also systemic disorders that can be considered, to some extent, as metabolic disorders.

Common dysregulated pathways in obese adipose tissue and atherosclerosis

Background

The metabolic syndrome is becoming increasingly prevalent in the general population that is at simultaneous risk for both type 2 diabetes and cardiovascular disease. The critical pathogenic mechanisms underlying these diseases are obesity-driven insulin resistance and atherosclerosis, respectively. To obtain a better understanding of molecular mechanisms involved in pathogenesis of the metabolic syndrome as a basis for future treatment strategies, studies considering both inherent risks, namely metabolic and cardiovascular, are needed. Hence, the aim of this study was to identify pathways commonly dysregulated in obese adipose tissue and atherosclerotic plaques.

Methods

We carried out a gene set enrichment analysis utilizing data from two microarray experiments with obese white adipose tissue and atherosclerotic aortae as well as respective controls using a combined insulin resistance-atherosclerosis mouse model.

Results

We identified 22 dysregulated pathways common to both tissues with p values below 0.05, and selected inflammatory response and oxidative phosphorylation pathways from the Hallmark gene set to conduct a deeper evaluation at the single gene level. This analysis provided evidence of a vast overlap in gene expression alterations in obese adipose tissue and atherosclerosis with Il7r, C3ar1, Tlr1, Rgs1 and Semad4d being the highest ranked genes for the inflammatory response pathway and Maob, Bckdha, Aldh6a1, Echs1 and Cox8a for the oxidative phosphorylation pathway.

Conclusions

In conclusion, this study provides extensive evidence for common pathogenic pathways underlying obesity-driven insulin resistance and atherogenesis which could provide a basis for the development of novel strategies to simultaneously prevent type 2 diabetes and cardiovascular disease in patients with metabolic syndrome.

Electronic supplementary material

The online version of this article (doi:10.1186/s12933-016-0441-2) contains supplementary material, which is available to authorized users.

Common familial risk factors for schizophrenia and diabetes mellitus

OBJECTIVE

The co-occurrence of type 2 diabetes and psychosis is an important form of medical comorbidity within individuals, but no large-scale study has evaluated comorbidity within families. The aim of this study was to determine whether there is evidence for familial comorbidity between type 2 diabetes and psychosis.

METHOD

Data were analysed from an observational study of a nationally representative sample of 1642 people with psychosis who were in contact with psychiatric services at the time of survey (The 2010 Australian National Survey of Psychosis). Participants were aged 18-64 years and met World Health Organization's International Classification of Diseases, 10th Revision diagnostic criteria for a psychotic disorder (857 with schizophrenia, 319 with bipolar disorder with psychotic features, 293 with schizoaffective disorder, 81 with depressive psychosis and 92 with delusional disorder or other non-organic psychoses). Logistic regression was used to estimate the association between a family history of diabetes and a family history of schizophrenia.

RESULTS

A positive family history of diabetes was associated with a positive family history of schizophrenia in those with a psychotic disorder (odds ratio = 1.35, p = 0.01, adjusted for age and gender). The association was different in those with an affective versus non-affective psychosis (odds ratio = 0.613, p = 0.019, adjusted for age and gender) and was significant only in those with a non-affective psychosis, specifically schizophrenia (odds ratio = 1.58, p = 0.005, adjusted for age and sex). Adjustment for demographic factors in those with schizophrenia slightly strengthened the association (odds ratio = 1.74, p = 0.001, adjusted for age, gender, diagnosis, ethnicity, education, employment, income and marital status).

CONCLUSION

Elevated risk for type 2 diabetes in people with schizophrenia is not simply a consequence of antipsychotic medication; type 2 diabetes and schizophrenia share familial risk factors.

Evaluation of genetic association of neurodevelopment and neuroimmunological genes with antipsychotic treatment response in schizophrenia in Indian populations

Neurodevelopmental and neuroimmunological genes critically regulate antipsychotic treatment outcome. We report genetic associations of antipsychotic response in 742 schizophrenia patients from Indian populations of Indo‐European and Dravidian ancestry, segregated by disease severity. Meta‐analysis comparing the two populations identified CCL2 [rs4795893: OR (95% CI) = 1.79 (1.27–2.52), P = 7.62 × 10⁻⁴; rs4586: OR (95% CI) = 1.74 (1.24–2.43), P = 1.13 × 10⁻³] and GRIA4 [rs2513265: OR (95% CI) = 0.53 (0.36–0.78), P = 1.44 × 10⁻³] in low severity group; and, ADCY2 [rs1544938: OR (95% CI) = 0.36 (0.19–0.65), P = 7.68 × 10⁻⁴] and NRG1 [rs13250975, OR (95% CI) = 0.42 (0.23–0.79), P = 6.81 × 10⁻³; rs17716295, OR (95% CI) = 1.78 (1.15–2.75), P = 8.71 × 10⁻³] in high severity group, with incomplete response toward antipsychotics. To our knowledge, this is the first study to identify genetic polymorphisms associated with the efficacy of antipsychotic treatment of schizophrenia patients from two major India populations.

Genetic underpinnings of left superior temporal gyrus thickness in patients with schizophrenia

OBJECTIVES

Schizophrenia is a highly disabling psychiatric disorder with a heterogeneous phenotypic appearance. We aimed to further the understanding of some of the underlying genetics of schizophrenia, using left superior temporal gyrus (STG) grey matter thickness reduction as an endophenoptype in a genome-wide association (GWA) study.

METHODS

Structural magnetic resonance imaging (MRI) and genetic data of the Mind Clinical Imaging Consortium (MCIC) study of schizophrenia were used to analyse the interaction effects between 1,067,955 single nucleotide polymorphisms (SNPs) and disease status on left STG thickness in 126 healthy controls and 113 patients with schizophrenia. We next used a pathway approach to detect underlying pathophysiological pathways that may be related to schizophrenia.

RESULTS

No SNP by diagnosis interaction effect reached genome-wide significance (5 × 10-8) in our GWA study, but 10 SNPs reached P-values less than 10-6. The most prominent pathways included those involved in insulin, calcium, PI3K-Akt and MAPK signalling.

CONCLUSIONS

Our strongest findings in the GWA study and pathway analysis point towards an involvement of glucose metabolism in left STG thickness reduction in patients with schizophrenia only. These results are in line with recently published studies, which showed an increased prevalence of psychosis among patients with metabolic syndrome-related illnesses including diabetes.

MicroRNA Profiling of Neurons Generated Using Induced Pluripotent Stem Cells Derived from Patients with Schizophrenia and Schizoaffective Disorder, and 22q11.2 Del

We are using induced pluripotent stem cell (iPSC) technology to study neuropsychiatric disorders associated with 22q11.2 microdeletions (del), the most common known schizophrenia (SZ)-associated genetic factor. Several genes in the region have been implicated; a promising candidate is DGCR8, which codes for a protein involved in microRNA (miRNA) biogenesis. We carried out miRNA expression profiling (miRNA-seq) on neurons generated from iPSCs derived from controls and SZ patients with 22q11.2 del. Using thresholds of p<0.01 for nominal significance and 1.5-fold differences in expression, 45 differentially expressed miRNAs were detected (13 lower in SZ and 32 higher). Of these, 6 were significantly down-regulated in patients after correcting for genome wide significance (FDR<0.05), including 4 miRNAs that map to the 22q11.2 del region. In addition, a nominally significant increase in the expression of several miRNAs was found in the 22q11.2 neurons that were previously found to be differentially expressed in autopsy samples and peripheral blood in SZ and autism spectrum disorders (e.g., miR-34, miR-4449, miR-146b-3p, and miR-23a-5p). Pathway and function analysis of predicted mRNA targets of the differentially expressed miRNAs showed enrichment for genes involved in neurological disease and psychological disorders for both up and down regulated miRNAs. Our findings suggest that: i. neurons with 22q11.2 del recapitulate the miRNA expression patterns expected of 22q11.2 haploinsufficiency, ii. differentially expressed miRNAs previously identified using autopsy samples and peripheral cells, both of which have significant methodological problems, are indeed disrupted in neuropsychiatric disorders and likely have an underlying genetic basis.

Increased cardiometabolic dysfunction in first-degree relatives of patients with psychotic disorders

INTRODUCTION

Elevated prevalence of comorbid cardio-vascular and metabolic dysfunction (CMD) is consistently reported in patients with severe psychotic disorders such as schizophrenia (SZ), schizoaffective (SZA) and bipolar disorder (BP-P). Since both psychosis and CMD are substantively heritable in nature, we attempted to investigate the occurrence of CMD disorders in first-degree relatives of probands with psychosis.

METHODS

Our sample included 861 probands with a diagnosis of SZ (n=354), SZA (n=212) and BP-P (n=295), 776 first-degree relatives of probands and 416 healthy controls. Logistic regression was used to compare prevalence of any CMD disorders (diabetes, hypertension, hyperlipidemia or coronary artery disease) across groups. Post hoc tests of independence checked for CMD prevalence across psychosis diagnosis (SZ, SZA and BP-P), both in relatives of probands and within probands themselves.

RESULTS

After controlling for potential confounders, first-degree relatives with (p<0.001) and without (p=0.03) Axis I non-psychotic or Axis- II cluster disorders were at a significant risk for CMD compared to controls. No significant difference (p=0.42) was observed in prevalence of CMD between relatives of SZ, SZA and BP-P, or between psychosis diagnoses for probands (p=0.25).

DISCUSSION

Prevalence of CMD was increased in the first-degree relatives of psychosis subjects. This finding suggests the possibility of overlapping genetic contributions to CMD and psychosis. Increased somatic disease burden in relatives of psychotic disorder probands points to need for early detection and preventive efforts in this population.

Diabetes mellitus and severe mental illness: mechanisms and clinical implications

The prevalence of diabetes mellitus is twofold to threefold higher in people with severe mental illness (SMI) than in the general population, with diabetes mellitus affecting ∼12% of people receiving antipsychotics. The consequences of diabetes mellitus are more severe and frequent in people with SMI than in those without these conditions, with increased rates of microvascular and macrovascular complications, acute metabolic dysregulation and deaths related to diabetes mellitus. Multiple complex mechanisms underlie the association between diabetes mellitus and SMI; these mechanisms include genetic, environmental and disease-specific factors, and treatment-specific factors. Although antipsychotics are the mainstay of treatment in SMI, a causative link, albeit of uncertain magnitude, seems to exist between antipsychotics and diabetes mellitus. The principles of managing diabetes mellitus in people with SMI are similar to those for the general population and should follow currently established treatment algorithms. Lifestyle interventions are needed to reduce incident diabetes mellitus. In addition, improved uptake of opportunities to screen for this disease will reduce the high prevalence of undiagnosed diabetes mellitus. Currently, people with SMI receive poorer treatment for diabetes mellitus than the general population. Thus, health-care professionals in primary care, diabetes mellitus services and mental health teams have a responsibility to ensure that patients with SMI are not disadvantaged.

Correlation between DNA methylation and gene expression in the brains of patients with bipolar disorder and schizophrenia

OBJECTIVES

Aberrant DNA methylation and gene expression have been reported in postmortem brain tissues of psychotic patients, but until now there has been no systematic evaluation of synergistic changes in methylation and expression on a genome-wide scale in brain tissue.

METHODS

In this study, genome-wide methylation and expression analyses were performed on cerebellum samples from 39 patients with schizophrenia, 36 patients with bipolar disorder, and 43 unaffected controls, to screen for a correlation between gene expression and CpG methylation.

RESULTS

Out of 71,753 CpG gene pairs (CGPs) tested across the genome, 204 were found to significantly correlate with gene expression after correction for multiple testing [p < 0.05, false discovery rate (FDR) q < 0.05]. The correlated CGPs were tested for disease-associated expression and methylation by comparing psychotic patients with bipolar disorder and schizophrenia to healthy controls. Four of the identified CGPs were found to significantly correlate with the differential expression and methylation of genes encoding phosphoinositide-3-kinase, regulatory subunit 1 (PIK3R1), butyrophilin, subfamily 3, member A3 (BTN3A3), nescient helix-loop-helix 1 (NHLH1), and solute carrier family 16, member 7 (SLC16A7) in psychotic patients (p < 0.05, FDR q < 0.2). Additional expression and methylation datasets were used to validate the relationship between DNA methylation, gene expression, and neuropsychiatric diseases.

CONCLUSIONS

These results suggest that the identified differentially expressed genes with an aberrant methylation pattern may represent novel candidate factors in the etiology and pathology of neuropsychiatric disorders.

Genetic liability for schizophrenia predicts risk of immune disorders

BACKGROUND

Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between schizophrenia and three immune disorders and to compare with the overlap between schizophrenia and two disorders not primarily characterized by immune dysregulation: bipolar disorder and type 2 diabetes.

METHODS

We performed a polygenic risk score analysis using results from the schizophrenia Psychiatric GWAS consortium (PGC) (8922 cases and 9528 controls) and five Wellcome Trust Case Control Consortium (WTCCC) case samples as target cases: bipolar disorder (n=1998), type 1 diabetes (n=2000), Crohn's diseases (n=2005), rheumatoid arthritis (n=1999), and type 2 diabetes (n=1999). The WTCCC British Birth Cohort and National Blood Service samples (n=3004) were used as target controls. Additionally, we tested whether schizophrenia polygenic risk scores significantly differed between patients with immune disorder, bipolar disorder, and type 2 diabetes respectively.

RESULTS

Polygenic risk scores for schizophrenia significantly predicted disease status in all three immune disorder samples (Nagelkerke-R(2) 1.1%-1.3%; p<0.05). The polygenic risk of schizophrenia in patients with immune disorders was significantly lower than in patients with bipolar disorder (Nagelkerke-R(2) 6.0%; p<0.05), but higher than in type 2 diabetes patients (Nagelkerke-R(2) 0.5%; p<0.05).

CONCLUSIONS

Our results suggest that genetic factors are shared between schizophrenia and immune disorders. This contributes to an accumulating body of evidence that immune processes may play a role in the etiology of schizophrenia.

Pathway-based analysis tools for complex diseases: a review

Genetic studies are traditionally based on single-gene analysis. The use of these analyses can pose tremendous challenges for elucidating complicated genetic interplays involved in complex human diseases. Modern pathway-based analysis provides a technique, which allows a comprehensive understanding of the molecular mechanisms underlying complex diseases. Extensive studies utilizing the methods and applications for pathway-based analysis have significantly advanced our capacity to explore large-scale omics data, which has rapidly accumulated in biomedical fields. This article is a comprehensive review of the pathway-based analysis methods—the powerful methods with the potential to uncover the biological depths of the complex diseases. The general concepts and procedures for the pathway-based analysis methods are introduced and then, a comprehensive review of the major approaches for this analysis is presented. In addition, a list of available pathway-based analysis software and databases is provided. Finally, future directions and challenges for the methodological development and applications of pathway-based analysis techniques are discussed. This review will provide a useful guide to dissect complex diseases.