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.
Two single nucleotide polymorphisms of PDLIM5, rs7690296 and rs11097431, were genotyped using Mass-Array SNP genotyping by Sequenom technology in 244 bipolar disorder patients, 471 schizophrenia patients, and 601 control individuals who were Malay, Chinese, and Indian ethnic groups in the Malaysian population. A significant association was observed in allele frequency between the rs7690296 polymorphism and bipolar disorder in the Indian ethnic group [P=0.02, adjusted odds ratio (OR) 0.058, 95% confidence interval (CI) 0.36-0.93]. A significant association was also observed between the rs7690296 polymorphism and schizophrenia under the recessive model for both Malay (P=0.02, adjusted OR 1.86, 95% CI 1.12-3.10) and Indian (P=0.02, adjusted OR 1.92, 95% CI 1.10-3.37) ethnic groups. However, no association was detected between the rs11097431 polymorphism either with bipolar disorder or with schizophrenia. Therefore, it can be deduced that the nonsynonymous rs7690296 polymorphism could play an important role in the pathophysiology of both bipolar disorder and schizophrenia.
The occurrence of metabolic syndrome (MS) in schizophrenia patients receiving long-term antipsychotics (APs) contributes to their high mortality rate. We aimed to determine whether genetic polymorphisms of identified candidate genes are associated with MS in our study population.
Recent studies have shown that bipolar disorder (BPD) and schizophrenia (SZ) share some common genetic risk factors. This study aimed to examine the association between candidate single nucleotide polymorphisms (SNPs) identified from genome-wide association studies (GWAS) and risk of BPD and SZ. A total of 715 patients (244 BPD and 471 SZ) and 593 controls were genotyped using the Sequenom MassARRAY platform. We showed a positive association between LMAN2L (rs6746896) and risk of both BPD and SZ in a pooled population (P-value=0.001 and 0.009, respectively). Following stratification by ethnicity, variants of the ANK3 gene (rs1938516 and rs10994336) were found to be associated with BPD in Malays (P-value=0.001 and 0.006, respectively). Furthermore, an association exists between another variant of LMAN2L (rs2271893) and SZ in the Malay and Indian ethnic groups (P-value=0.003 and 0.002, respectively). Gene-gene interaction analysis revealed a significant interaction between the ANK3 and LMAN2L genes (empirical P=0.0107). Significant differences were shown between patients and controls for two haplotype frequencies of LMAN2L: GA (P=0.015 and P=0.010, for BPD and SZ, respectively) and GG (P=0.013 for BPD). Our study showed a significant association between LMAN2L and risk of both BPD and SZ.
An early warning system for dengue is meant to predict outbreaks and prevent dengue cases by aiding timely decision making and deployment of interventions. However, only a system which is accepted and utilised by the public would be sustainable in the long run. This study aimed to explore the perception and attitude of the Malaysian public towards a dengue early warning system. The sample consisted of 847 individuals who were 18 years and above and living/working in the Petaling District, an area adjacent to Kuala Lumpur, Malaysia. A questionnaire consisting of personal information and three sub-measures of; i) perception, ii) attitude towards dengue early warning and iii) response towards early warning; was distributed to participants. We found that most of the respondents know about dengue fever (97.1%) and its association with climate factors (90.6%). Most of them wanted to help reduce the number of dengue cases in their area (91.5%). A small percentage of the respondents admitted that they were not willing to be involved in public activities, and 64% of them admitted that they did not check dengue situations or hotspots around their area regularly. Despite the high awareness on the relationship between climate and dengue, about 45% of respondents do not know or are not sure how this can be used to predict dengue. Respondents would like to know more about how climate data can be used to predict a dengue outbreak (92.7%). Providing more information on how climate can influence dengue cases would increase public acceptability and improve response towards climate-based warning system. The most preferred way of communicating early warning was through the television (66.4%). This study shows that the public in Petaling District considers it necessary to have a dengue warning system to be necessary, but more education is required.