Association of the ADRA1A gene and the severity of metabolic abnormalities in patients with schizophrenia

Network Pharmacology and Data Mining Approach Reveal the Medication Rule of Traditional Chinese Medicine in the Treatment of Premenstrual Syndrome/Premenstrual Dysphoric Disorder

Premenstrual syndrome (PMS) is a common disorder that affects women of reproductive age. It is characterized by periodic mental and somatic symptoms such as irritability, depression, and breast pain during the luteal phase. Premenstrual dysphoric disorder (PMDD) is the most severe form of PMS. In recent years, the incidence of PMS/PMDD has been increasing year after year. However, due to the complex symptoms and ambiguous classification of PMS/PMDD, the limitations of present treatments, such as their poor efficacy rate, have become increasingly apparent. With its unique benefits such as syndrome differentiation and high cure rate, traditional Chinese medicine (TCM) has sparked new diagnosing and treating of PMS/PMDD. This study uses data mining methods, and statistical analysis revealed that Xiaoyao San and Chaihu Shugan San were the commonly used TCM to treat PMS/PMDD. A detailed investigation of regularly used single herbs revealed that most TCM is used as cold herbs that penetrate the liver meridian, with predominant bitter, sweet, and pungent flavors. The network pharmacology method analyzes the interactions between diseases, targets, and herbs. Meanwhile, the deep action targets and molecular mechanisms of 10 commonly used herbs for the treatment of PMS/PMDD are studied, revealing that it involves several ingredients, many targets, and different pathways. This interaction provides insight into the mechanism of action of TCM in the synergistic treatment of PMS/PMDD. It is now clear that we can begin treating PMS/PMDD with TCM using the target and mechanism revealed by the abovementioned findings in the future. This serves as an essential reference for future research and clinical application of TCM in the treatment of PMS/PMDD.

A Review of Switching Strategies for Patients with Schizophrenia Comorbid with Metabolic Syndrome or Metabolic Abnormalities

Metabolic syndrome (MetS) in patients with schizophrenia occurs 2-3 times more frequently than in the general population. Antipsychotic medication is a primary risk factor for patients with MetS. In particular, the widely used second-generation antipsychotics can affect glucose and lipid metabolism and can induce insulin resistance and other metabolic abnormalities through various receptors. Notably, the metabolic risks of various antipsychotics may differ because of their different pharmacological affinity to MetS-related receptors. Several previous studies have shown that switching from high to low metabolic risk antipsychotics may improve patients' metabolic parameters. The current review aims to discuss the strategies for switching antipsychotic medications and the impact on metabolic abnormalities in patients with schizophrenia.

Metabolic syndrome in psychiatry: advances in understanding and management

Metabolic syndrome comprises a number of cardiovascular risk factors that increase morbidity and mortality. The increase in incidence of the syndrome among psychiatric patients has been unanimously demonstrated in recent studies and it has become one of the greatest challenges in psychiatric practice. Besides the use of psychotropic drugs, factors such as genetic polymorphisms, inflammation, endocrinopathies and unhealthy lifestyle contribute to the association between metabolic syndrome and a number of psychiatric disorders. In this article, we review the current diagnostic criteria for metabolic syndrome and propose clinically useful guidelines for psychiatrists to identify and monitor patients who may have the syndrome. We also outline the relationship between metabolic syndrome and individual psychiatric disorders, and discuss advances in pharmacological treatment for the syndrome, such as metformin.

LEARNING OBJECTIVES

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The Role of Norepinephrine and Its α-Adrenergic Receptors in the Pathophysiology and Treatment of Major Depressive Disorder and Schizophrenia: A Systematic Review

Norepinephrine (NE) is recognized as having a key role in the pathophysiology of major depressive disorder (MDD) and schizophrenia, although its distinct actions via α-adrenergic receptors (α-ARs) are not well defined. We performed a systematic review examining the roles of NE and α-ARs in MDD and schizophrenia. PubMed and ProQuest database searches were performed to identify English language papers published between 2008 and 2015. In total, 2,427 publications (PubMed, n = 669; ProQuest, n = 1,758) were identified. Duplicates, articles deemed not relevant, case studies, reviews, meta-analyses, preclinical reports, or articles on non-target indications were excluded. To limit the review to the most recent data representative of the literature, the review further focused on publications from 2010 to 2015, which were screened independently by all authors. A total of 16 research reports were identified: six clinical trial reports, six genetic studies, two biomarker studies, and two receptor studies. Overall, the studies provided indirect evidence that α-AR activity may play an important role in aberrant regulation of cognition, arousal, and valence systems associated with MDD and schizophrenia. Characterization of the NE pathway in patients may provide clinicians with information for more personalized therapy of these heterogeneous diseases. Current clinical studies do not provide direct evidence to support the role of NE α-ARs in the pathophysiology of MDD and schizophrenia and in the treatment response of patients with these diseases, in particular with relation to specific valence systems. Clinical studies that attempt to define associations between specific receptor binding profiles of psychotropics and particular clinical outcomes are needed.

From Molecules to the Clinic: Linking Schizophrenia and Metabolic Syndrome through Sphingolipids Metabolism

Metabolic syndrome (MS) is a prevalent and severe comorbidity observed in schizophrenia (SZ). The exact nature of this association is controversial and very often accredited to the effects of psychotropic medications and disease-induced life-style modifications, such as inactive lifestyle, poor dietary choices, and smoking. However, drug therapy and disease-induced lifestyle factors are likely not the only factors contributing to the observed converging nature of these conditions, since an increased prevalence of MS is also observed in first episode and drug-naïve psychosis populations. MS and SZ share common intrinsic susceptibility factors and etiopathogenic mechanisms, which may change the way we approach clinical management of SZ patients. Among the most relevant common pathogenic pathways of SZ and MS are alterations in the sphingolipids (SLs) metabolism and SLs homeostasis. SLs have important structural functions as they participate in the formation of membrane “lipid rafts.” SLs also play physiological roles in cell differentiation, proliferation, and inflammatory processes, which might be part of MS/SZ common pathophysiological processes. In this article we review a plausible mechanism to explain the link between MS and SZ through a disruption in SL homeostasis. Additionally, we provide insights on how this hypothesis can lead to the developing of new diagnostic/therapeutic technologies for SZ patients.

Evidence for contribution of common genetic variants within chromosome 8p21.2-8p21.1 to restricted and repetitive behaviors in autism spectrum disorders

BACKGROUND

Restricted and Repetitive Behaviors (RRB), one of the core symptom categories for Autism Spectrum Disorders (ASD), comprises heterogeneous groups of behaviors. Previous research indicates that there are two or more factors (subcategories) within the RRB domain. In an effort to identify common variants associated with RRB, we have carried out a genome-wide association study (GWAS) using the Autism Genetic Resource Exchange (AGRE) dataset (n = 1,335, all ASD probands of European ancestry) for each identified RRB subcategory, while allowing for comparisons of associated single nucleotide polymorphisms (SNPs) with associated SNPs in the same set of probands analyzed using all the RRB subcategories as phenotypes in a multivariate linear mixed model. The top ranked SNPs were then explored in an independent dataset.

RESULTS

Using principal component analysis of item scores obtained from Autism Diagnostic Interview-Revised (ADI-R), two distinct subcategories within Restricted and Repetitive Behaviors were identified: Repetitive Sensory Motor (RSM) and Insistence on Sameness (IS). Quantitative RSM and IS scores were subsequently used as phenotypes in a GWAS using the AGRE ASD cohort. Although no associated SNPs with genome-wide significance (P < 5.0E-08) were detected when RSM or IS were analyzed independently, three SNPs approached genome-wide significance when RSM and IS were considered together using multivariate association analysis. These included the top IS-associated SNP, rs62503729 (P-value = 6.48E-08), which is located within chromosome 8p21.2-8p21.1, a locus previously linked to schizophrenia. Notably, all of the most significantly associated SNPs are located in close proximity to STMN4 and PTK2B, genes previously shown to function in neuron development. In addition, several of the top-ranked SNPs showed correlations with STMN4 mRNA expression in adult CEU (Caucasian and European descent) human prefrontal cortex. However, the association signals within chromosome 8p21.2-8p21.1 failed to replicate in an independent sample of 2,588 ASD probands; the insufficient sample size and between-study heterogeneity are possible explanations for the non-replication.

CONCLUSIONS

Our analysis indicates that RRB in ASD can be represented by two distinct subcategories: RSM and IS. Subsequent univariate and multivariate genome-wide association studies of these RRB subcategories enabled the detection of associated SNPs at 8p21.2-8p21.1. Although these results did not replicate in an independent ASD dataset, genomic features of this region and pathway analysis suggest that common variants in 8p21.2-8p21.1 may contribute to RRB, particularly IS. Together, these observations warrant future studies to elucidate the possible contributions of common variants in 8p21.2-8p21.1 to the etiology of RSM and IS in ASD.

Circulating 'lncRNA OTTHUMT00000387022' from monocytes as a novel biomarker for coronary artery disease

AIMS

Long non-coding RNAs (lncRNAs) have been found to be involved in the pathogenesis of coronary artery disease (CAD). However, it remains to be established whether or not circulating lncRNAs can serve as biomarkers of CAD.

METHODS AND RESULTS

Using a microarray-based lncRNA expression profiling, we found 86 lncRNAs that were differentially expressed in circulating peripheral blood monocytes and plasma from 15 CAD patients and 15 control subjects. After choosing a consistent criterion (average normalized intensity ≥7 with significance <0.005) and confirmed by quantitative PCR, only three lncRNAs (CoroMarker, BAT5, and IL21R-AS1) remained as candidate CAD biomarkers. Using the analysis of area under the curve (AUC) of the receiver-operating characteristic in another pilot group and another larger cohort, CoroMarker was found to be the best candidate biomarker for CAD with an AUC of 0.920 and 95% confidence interval of 0.892-0.947. CoroMarker was independent from known CAD risk factors and other cardiovascular diseases. In a prospective study, we found that the sensitivity and specificity of CoroMarker were 76 and 92.5%, respectively. Functional enrichment analysis showed CoroMarker to be clustered with genes positively associated with signal transduction, transmembrane transport, synaptic transmission, and innate immunity and negatively associated with inflammation. These findings were validated in THP-1 cells; CoroMarker siRNA treatment decreased the concentrations of proinflammatory cytokines [interleukin (IL)-1β, IL-6, and tumour necrosis factor α] in the culture medium.

CONCLUSION

The present study suggests that CoroMarker is a novel and specific biomarker of CAD.

A systematic review of genetic variants associated with metabolic syndrome in patients with schizophrenia

Metabolic syndrome (MetS) is a cluster of factors that increases the risk of cardiovascular disease (CVD), one of the leading causes of mortality in patients with schizophrenia. Incidence rates of MetS are significantly higher in patients with schizophrenia compared to the general population. Several factors contribute to this high comorbidity. This systematic review focuses on genetic factors and interrogates data from association studies of genes implicated in the development of MetS in patients with schizophrenia. We aimed to identify variants that potentially contribute to the high comorbidity between these disorders. PubMed, Web of Science and Scopus databases were accessed and a systematic review of published studies was conducted. Several genes showed strong evidence for an association with MetS in patients with schizophrenia, including the fat mass and obesity associated gene (FTO), leptin and leptin receptor genes (LEP, LEPR), methylenetetrahydrofolate reductase (MTHFR) gene and the serotonin receptor 2C gene (HTR2C). Genetic association studies in complex disorders are convoluted by the multifactorial nature of these disorders, further complicating investigations of comorbidity. Recommendations for future studies include assessment of larger samples, inclusion of healthy controls, longitudinal rather than cross-sectional study designs, detailed capturing of data on confounding variables for both disorders and verification of significant findings in other populations. In future, big genomic datasets may allow for the calculation of polygenic risk scores in risk prediction of MetS in patients with schizophrenia. This could ultimately facilitate early, precise, and patient-specific pharmacological and non-pharmacological interventions to minimise CVD associated morbidity and mortality.

Pharmacogenomics in psychiatry: the relevance of receptor and transporter polymorphisms

The treatment of severe mental illness, and of psychiatric disorders in general, is limited in its efficacy and tolerability. There appear to be substantial interindividual differences in response to psychiatric drug treatments that are generally far greater than the differences between individual drugs; likewise, the occurrence of adverse effects also varies profoundly between individuals. These differences are thought to reflect, at least in part, genetic variability. The action of psychiatric drugs primarily involves effects on synaptic neurotransmission; the genes for neurotransmitter receptors and transporters have provided strong candidates in pharmacogenetic research in psychiatry. This paper reviews some aspects of the pharmacogenetics of neurotransmitter receptors and transporters in the treatment of psychiatric disorders. A focus on serotonin, catecholamines and amino acid transmitter systems reflects the direction of research efforts, while relevant results from some genome-wide association studies are also presented. There are many inconsistencies, particularly between candidate gene and genome-wide association studies. However, some consistency is seen in candidate gene studies supporting established pharmacological mechanisms of antipsychotic and antidepressant response with associations of functional genetic polymorphisms in, respectively, the dopamine D2 receptor and serotonin transporter and receptors. More recently identified effects of genes related to amino acid neurotransmission on the outcome of treatment of schizophrenia, bipolar illness or depression reflect the growing understanding of the roles of glutamate and γ-aminobutyric acid dysfunction in severe mental illness. A complete understanding of psychiatric pharmacogenomics will also need to take into account epigenetic factors, such as DNA methylation, that influence individual responses to drugs.

Association of ADRA2A and MTHFR gene polymorphisms with weight loss following antipsychotic switching to aripiprazole or ziprasidone

OBJECTIVES

Various genetic polymorphisms have been reported to be associated with antipsychotic-induced weight gain. In this study, we aimed to determine whether risk polymorphisms in 12 candidate genes are associated with reduction in body mass index (BMI) of patients following switching of antipsychotics to aripiprazole or ziprasidone.

METHODS

We recruited 115 schizophrenia patients with metabolic abnormalities and who have been on at least 1 year treatment with other antipsychotics; they were then switched to either aripiprazole or ziprasidone. They were genotyped, and their BMI monitored for 6 months.

RESULTS

Significant associations with reduction in BMI at 6 months following switching were found in two of these genes: with rs1800544 of the ADRA2A gene (CC + CG [-0.32 ± 1.41 kg/m²] vs GG [-1.04 ± 1.63 kg/m²], p = 0.013) and with rs1801131 of the MTHFR gene (AA [-0.36 ± 1.53] vs AC + CC [-1.07 ± 1.53], p = 0.015).

CONCLUSION

The study data indicated that carriage of the ADRA2A rs1800544 GG genotype and the MTHFR rs1801131 C allele are associated with BMI reduction in this population following switching of antipsychotics to aripiprazole and ziprasidone.

A meta-analysis of cardio-metabolic abnormalities in drug naïve, first-episode and multi-episode patients with schizophrenia versus general population controls

A meta-analysis was conducted to explore the risk for cardio-metabolic abnormalities in drug naïve, first-episode and multi-episode patients with schizophrenia and age- and gender- or cohort-matched general population controls. Our literature search generated 203 relevant studies, of which 136 were included. The final dataset comprised 185,606 unique patients with schizophrenia, and 28 studies provided data for age- and gender-matched or cohort-matched general population controls (n=3,898,739). We found that multi-episode patients with schizophrenia were at increased risk for abdominal obesity (OR=4.43; CI=2.52-7.82; p<0.001), hypertension (OR=1.36; CI=1.21-1.53; p<0.001), low high-density lipoprotein cholesterol (OR=2.35; CI=1.78-3.10; p<0.001), hypertriglyceridemia (OR=2.73; CI=1.95-3.83; p<0.001), metabolic syndrome (OR=2.35; CI=1.68-3.29; p<0.001), and diabetes (OR=1.99; CI=1.55-2.54; p<0.001), compared to controls. Multi-episode patients with schizophrenia were also at increased risk, compared to first-episode (p<0.001) and drug-naïve (p<0.001) patients, for the above abnormalities, with the exception of hypertension and diabetes. Our data provide further evidence supporting WPA recommendations on screening, follow-up, health education and lifestyle changes in people with schizophrenia.

Metabolic syndrome in schizophrenia

To review the data with respect to prevalence of metabolic syndrome (MetS) and its correlates in schizophrenia. For this review, electronic search engines PUBMED, Sciencedirect, and Google Scholar were used. Available data suggests that most of the studies have been of cross-sectional design. Prevalence rates of MetS have varied from 11% to 69% in medicated patients, and 4-26% in drug naive patients in cross-sectional evaluations. Longitudinal studies have shown the prevalence rates to range from 0% to 14% at the baseline in drug naive patients, which increase to as high as 52.4% by 3 months of antipsychotic medication treatment. The prevalence rates of MetS in patients with schizophrenia are much higher than that seen in general population or healthy controls. Though there is no causal association with any demographic or clinical variables, the risk increases with increase in age. Among antipsychotics, there seems to be an association between MetS and atypical antipsychotics like clozapine and olanzapine. Therefore, the psychiatrists should be more vigilant regarding the presence of MetS in these high risk groups. Research on biological correlates of MetS in schizophrenia is still in its primitive stage, however, these is some evidence to suggest an association of MetS with adiponectin levels, hematological indices, methylenetetrahydrofolate reductase (MTHFR) and Alpha-1A adrenergic receptor (ADRA1A) gene. These areas hold promise, and targeting these with appropriate interventions may help us to prevent the occurrence of MetS in patients with schizophrenia in future.

The prevalence and mechanisms of metabolic syndrome in schizophrenia: a review

Metabolic syndrome (MetS), a constellation of central obesity, hypertension, dyslipidaemia and glucose intolerance, is highly prevalent in individuals with schizophrenia and conveys significant cardiovascular risk and mortality. Associated risk factors are female sex, some ethnic groups, advanced age, long duration of illness, smoking and exposure to antipsychotic agents. The prevalence of MetS varies across countries and psychiatric populations, and its development can be very rapid. Regular monitoring of all features of MetS is the cornerstone of its early detection and management. Future research needs to focus more on genetic determinants of MetS in the context of schizophrenic illness. This review aims to update the reader with the latest knowledge about the prevalence of MetS in schizophrenia and what might be the underlying pathophysiological mechanisms.