Electrocardiographic abnormalities and psychotropic polypharmacy in schizophrenia and schizoaffective disorders.

BACKGROUND: Sudden cardiac death (SCD) is a significant cause for increased mortality in people with schizophrenia and schizoaffective disorders. Cardiac arrhythmia is one cause of SCD. Electrocardiographic (ECG) abnormalities predictive of arrhythmias are associated with antipsychotic drug use. METHOD: This chart audit examined the types and frequency of ECG abnormalities (ECG-Abs) in 169 patients with schizophrenia and schizoaffective disorder in a long-stay inpatient unit. We examined the association of ECG-Abs with demographic details and psychotropic drug prescription using chi-square test, Fisher's Exact test, independent two-sample t-test, Pearson's correlation, and one-way ANOVA. RESULTS: Eighty-eight patients (52.1%) recorded at least one ECG-Ab, and 20.7% had two or more ECG-Abs. The use of multiple antipsychotics, with or without other psychotropic drugs, did not associate significantly with the presence or number of ECG-Abs. CONCLUSION: A significant proportion of patients with schizophrenia and schizoaffective disorder have ECG-Abs other than prolonged QTc interval, which can predispose them to cardiac arrhythmias. The abnormalities were not limited to patients on psychotropic polypharmacy. ECG evaluation is indicated for all patients and should consider various electrical abnormalities to identify arrhythmia risk.

Association of Schizophrenia Risk With Disordered Niacin Metabolism in an Indian Genome-wide Association Study.

Importance: Genome-wide association studies (GWASs) in European populations have identified more than 100 schizophrenia-associated loci. A schizophrenia GWAS in a unique Indian population offers novel findings. Objective: To discover and functionally evaluate genetic loci for schizophrenia in a GWAS of a unique Indian population. Design, Setting, and Participants: This GWAS included a sample of affected individuals, family members, and unrelated cases and controls. Three thousand ninety-two individuals were recruited and diagnostically ascertained via medical records, hospitals, clinics, and clinical networks in Chennai and surrounding regions. Affected participants fulfilled DSM-IV diagnostic criteria for schizophrenia. Unrelated control participants had no personal or family history of psychotic disorder. Recruitment, genotyping, and analysis occurred in consecutive phases beginning January 1, 2001. Recruitment was completed on February 28, 2018, and genotyping and analysis are ongoing. Main Outcomes and Measures: Associations of single-nucleotide polymorphisms and gene expression with schizophrenia. Results: The study population included 1321 participants with schizophrenia, 885 family controls, and 886 unrelated controls. Among participants with schizophrenia, mean (SD) age was 39.1 (11.4) years, and 52.7% were male. This sample demonstrated uniform ethnicity, a degree of inbreeding, and negligible rates of substance abuse. A novel genome-wide significant association was observed between schizophrenia and a chromosome 8q24.3 locus (rs10866912, allele A; odds ratio [OR], 1.27 [95% CI, 1.17-1.38]; P = 4.35 × 10-8) that attracted support in the schizophrenia Psychiatric Genomics Consortium 2 data (rs10866912, allele A; OR, 1.04 [95% CI, 1.02-1.06]; P = 7.56 × 10-4). This locus has undergone natural selection, with the risk allele A declining in frequency from India (approximately 72%) to Europe (approximately 43%). rs10866912 directly modifies the abundance of the nicotinate phosphoribosyltransferase gene (NAPRT1) transcript in brain cortex (normalized effect size, 0.79; 95% CI, 0.6-1.0; P = 5.8 × 10-13). NAPRT1 encodes a key enzyme for niacin metabolism. In Indian lymphoblastoid cell lines, (risk) allele A of rs10866912 was associated with NAPRT1 downregulation (AA: 0.74, n = 21; CC: 1.56, n = 17; P = .004). Preliminary zebrafish data further suggest that partial loss of function of NAPRT1 leads to abnormal brain development. Conclusions and Relevance: Bioinformatic analyses and cellular and zebrafish gene expression studies implicate NAPRT1 as a novel susceptibility gene. Given this gene's role in niacin metabolism and the evidence for niacin deficiency provoking schizophrenialike symptoms in neuropsychiatric diseases such as pellagra and Hartnup disease, these results suggest that the rs10866912 genotype and niacin status may have implications for schizophrenia susceptibility and treatment.

Body mass index as a screening test for metabolic syndrome in schizophrenia and schizoaffective disorders.

OBJECTIVE: The aim of this paper was to identify a simple screening measure for detecting metabolic syndrome (MetS) in people with schizophrenia and schizoaffective disorders. METHOD: A total of 202 patients with chronic schizophrenia and schizoaffective disorders on antipsychotic medications were assessed for MetS using the criteria defined by the International Diabetes Federation. Receiver operating characteristic (ROC) analysis was applied using body mass index (BMI) as the test variable for diagnosis of MetS. RESULTS: The prevalence of MetS was 69.3%. Logistic regression analysis identified BMI and gender as significant predictors of MetS. ROC analysis identified BMI >28.7 as the criterion value with highest accuracy in terms of specificity and sensitivity. The likelihood ratios were robust at this cut-off score. The area under the curve was 0.75. CONCLUSION: BMI is a quick and easy measure, and can be used as a screening test for MetS in any clinical or community setting.

Obesity and metabolic syndrome in a psychiatric rehabilitation service.

OBJECTIVE: People with schizophrenia and bipolar disorders suffer from increased rates of obesity and metabolic syndrome. Metabolic disorders add to the burden of disease and affect treatment and rehabilitation outcomes. This study aimed to study the prevalence of obesity and metabolic syndrome in people with chronic psychotic disorders in a psychiatric rehabilitation setting. METHOD: All patients in the psychiatry rehabilitation program were assessed for obesity and metabolic syndrome using the definition of International Diabetes Federation (2005) was conducted as part of clinical protocol recently introduced into practice. RESULTS: A total of 221 patients were assessed. The prevalence of obesity was 59% and metabolic syndrome 68%. Metabolic syndrome was more frequent in patients receiving polypharmacy with multiple antipsychotics and mood stabilisers. Rates of nontreatment for metabolic disorders ranged from 30% to 88%. CONCLUSIONS: The rates of obesity and metabolic syndrome in patients with chronic severe mental disorders on antipsychotic drug treatment were 2 to 3 times that in the general population. A majority of them were untreated. Detection, monitoring and appropriate treatment of obesity and metabolic disorders should be a component of an assertive care management program to reduce morbidity and mortality and improve rehabilitation outcomes.