Pharmaco-genetic analysis of CYP1A1 and RGS4 variants and its impact on response to olanzapine and risperidone in Indian schizophrenic cohort.

OBJECTIVES: Genetic variations contribute significantly to inter-individual responses to drugs and side effects. Pharmacogenomics has the potential to be utilized as a tool in disorders like schizophrenia with a high degree of genetic inheritance, although data on pharmacogenomics of schizophrenia are limited. Olanzapine and risperidone are the frequently used anti-psychotic drugs used in clinics. Studies have observed the variability in the response of both drugs in schizophrenic individuals. Considering the pharmacogenomics importance of both drugs, we aim to examine the cytochrome P 4501A1 (CYP1A1) and regulator of G-protein signaling 4 (RGS4) variants and their metabolizing status in 94 schizophrenic individuals of Indian descent. METHODS: The present study is retrospective observational study. The metabolizing status of schizophrenic individuals was examined using Axiom Precision Medicine Diversity Array (PMDA) and the data were analyzed with the help of SNP Axiom Analysis Suite v5.1 (Affymetrix). The pharmacogenomics annotation was performed using PharmGKB. RESULTS: Genotype and allele frequencies were observed. The results reveal the high frequency of poor metabolizers of olanzapine and risperidone in the studied cohort. In lieu of the high distribution of poor metabolizers, we compare observed allele frequencies with global populations' data to understand the variability of the genetic pool attained by Indian schizophrenic individuals. CONCLUSIONS: Interestingly, the Indian schizophrenic cohort forms a different cluster compared to global populations, suggesting that pharmacogenomics testing might play an important role in clinical decision making for schizophrenia drug management.

New Jersey COVID-19 municipal dataset.

Although data about COVID-19 cases and deaths in the United States are readily available at the county-level, datasets on smaller geographic areas are limited. County-level data have been used to identify geospatial patterns of COVID-19 spread and, in conjunction with sociodemographic variables, have helped identify population health disparities concerning COVID-19 in the US. Municipality-level data are essential for advancing more targeted and nuanced understanding of geographic-based risk and resilience associated with COVID-19. We created a dataset that tracks COVID-19 cases and deaths by municipalities in the state of New Jersey (NJ), US, from April 22, 2020 to December 31, 2020. Data were drawn primarily from official county and municipality websites. The dataset is a spreadsheet containing cumulative case counts and case rates in each municipaly on three target dates, representing the peak of the first wave, the summer trough after the first wave, and the outbreak of the second wave in NJ. This dataset is valuable for four main reasons. First, the dataset is unique, because New Jersey's Health Department does not release COVID-19 data for the 77% (433/565) of municipalities with populations smaller than 20,000 individuals. Second, especially when combined with other data sources, such as publicly available sociodemographic data, this dataset can be used to advance epidemiological research on geographic differences in COVID-19, as well as to inform decision-making concerning the allocation of resources in response to the pandemic (e.g., strategies for targeted vaccine outreach campaigns). Third, county-level data mask important variations across municipalities, so municipality-level data permit a more nuanced exploration of health disparities related to local demographics, socioeconomic conditions, and access to resources and services. New Jersey is a good state to explore these patterns, because it is the most densely-populated and racially/ethnically diverse state in the US. Fourth, New Jersey was one of the few locations in the US with a high prevalence of COVID-19 during the first wave of the pandemic in the US. Thus, this dataset permits exploration of whether sociodemographic variables predicted COVID-19 differently as time progressed. To summarize, this unique municipality-level dataset in a diverse state with high COVID-19 cases is valuable for scholars and policy analysts to explore social and environmental factors related to the prevalence and transmission of COVID-19 in the US.

A comprehensive mobile application tool for disease surveillance, workforce management and supply chain management for Malaria Elimination Demonstration Project.

BACKGROUND: Health care technologies are now offering accountability, quality, robustness, and accuracy in disease surveillance and health care delivery programmes. With the advent of mobile hand-held devices, these technologies have become more accessible and adaptable for use by field staff working in remote areas. The Malaria Elimination Demonstration Project started collection of data and conduct of routine operations using paper-based reporting systems. Observing the need for a robust and quality digital mobile application, a comprehensive mobile application tool was developed that allowed the project to conduct disease surveillance, workforce management and supply chain management. METHODS: In June 2017, the project conceptualized a comprehensive mobile application tool in the local language (Hindi) for disease surveillance, human resources management, and supply chain management. The tool is also available in English. Solution for Community Health-workers (SOCH) mobile app is an android native application developed using android SDK and web-based tool using MVC.net framework. Construction of the application started in November 2017 and rolled out its pilot in April 2018, followed by pan-district roll out in July 2018. The application uses self-validation tools to ensure high level of data quality and integrity. RESULTS: The software is available in android based hand-held devices and web-screens with built-in data analytical capabilities. Using SOCH, the project has now successfully digitized its routine surveillance, attendance, tour plans, supply chain management components. The project has documented a reduction in 91% indigenous cases in the district, 60% improvement in stock accountability, and 99.6% accuracy in data collected through the mobile application. CONCLUSION: SOCH is an excellent and user-friendly tool, which can be customized for any public health management programme. The system ensures accountability and data robustness, which is needed for malaria elimination efforts throughout the country. The mobile application can be adapted for English or any other Indian or international language for use for malaria or any other disease surveillance and control programme. Another expansion feature of this mobile application is incorporation of indicators for Indoor Residual Spraying (IRS), Long-Lasting Insecticidal Nets (LLINs), and minor engineering by the residents of community under surveillance. The authors believe that it would be highly desirable and appropriate for an international organization, such as the World Health Organization (WHO), to conduct an independent comparison of all available mobile e-surveillance tools, so that a high-performing and globally suitable system can be selected for use in malaria elimination programmes. The Foundation of Disease Elimination and Controlof India has decided to make the SOCH mobile application available to anyone who would like to use it for disease surveillance and health care programmes.

Is obesity a risk to depression? A cross-sectional study.

BACKGROUND: Depression and obesity are disorders of stress with a dose dependent relationship between the both. The adverse health and social consequences are significant, when depression and obesity co-exist. This study aimed to examine the prevalence of depression among overweight and obese patients in a large station of Armed Forces and associate other risk factors of depression. METHODS: This cross sectional descriptive study was conducted in the general OPD of large Station medicare centre (SMC) on overweight and obese personnel. Data was collected by self-administered Patient Health Questionnaire (PHQ-9) to assess the risk for depression over a period of one month. RESULTS: In this study, out of 106 individuals, 71 (67%) were overweight and 35 (33%) were obese, as per WHO criteria. Of the individuals assessed, 13 (12%) individuals were found to have risk of moderate depression, 58 (54%) for mild depression and 35 (33%) individuals had no risk for clinically significant depression. The likelihood of depression was most strongly associated with BMI followed by age, status of living with family and habit of drinking alcohol. CONCLUSION: Obesity and depressive disorders are common comorbidities with overlapping pathophysiology whose co-existence leads to exponential adverse health outcomes. The outcome of depression and obesity is to be managed comprehensively by psychological counseling and life style modification.

Influence of early adversity on cortisol reactivity, SLC6A4 methylation and externalizing behavior in children of alcoholics.

BACKGROUND: Children of parents with alcoholism face considerable stress, and often have externalizing behaviors. Early adversity is known to affect DNA methylation and the functioning of the HPA axis. We investigated the association of early adversity with cortisol reactivity, 5HTTLPR genotype, site specific DNA methylation in the SLC6A4 gene and externalizing behavior in children of alcoholics (COA), and a matched sample of control children. METHODS: We examined children of alcoholics (N = 50) and age matched control children (N = 50) for exposure to early adversity (both prenatal and postnatal), assessed their salivary cortisol reactivity and evaluated their levels of emotional and behavioral difficulty in terms of externalizing and internalizing behavior. Site-specific DNA methylation at a previously characterized SLC6A4 region was determined in salivary DNA using pyrosequencing. The 5HTTLPR region of the SLC6A4 gene was also genotyped. RESULTS: COA had significantly higher experience of early adversity than control children. Cortisol reactivity was reduced in COA, and negatively correlated with early adversity. Both early adversity and cortisol reactivity correlated with externalizing behavior. SLC6A4 methylation was higher in COA, and correlated with early adversity. SLC6A4 genotype did not show association with any of the variables. CONCLUSION: Our study provides further evidence that early adversity is associated with blunted cortisol reactivity, increased site-specific CpG DNA methylation at the SLC6A4 gene, and high externalizing behavior.

Association of educational stress with depression, anxiety, and substance use among medical and engineering undergraduates in India.

BACKGROUND: Students pursuing higher education are subject to high stress levels which could be associated with dysfunctional coping. Maladaptive coping is known to be operative in manifesting as psychopathology as depression, anxiety, suicidal ideation, and substance abuse. This study aimed to elaborate the psychological morbidity among professional undergraduates in general and medical students in particular, its evolution over the years and its psychosocial correlates. METHODOLOGY: The study examined medical students (n = 202) and age-matched engineering students (n = 145) belonging to the first and final year for psychological stress and coping, educational stress, domestic and professional concerns, depression, anxiety, and substance abuse. Psychometric scales along with demographic questionnaire were used to assess and quantify stress and psychological morbidity. RESULTS: Medical students had higher levels of stress (psychological and education related) and higher psychological morbidity (depression and anxiety). Stress scores correlated positively with depression and anxiety scores and negatively with substance use score. Psychological stress other than educational stress was noted to be predictors of alcohol use in the sample. CONCLUSION: Our study elucidates that medical students face higher levels of psychological and education-related stressors and have higher levels of psychological morbidity than students from engineering colleges. Psychoactive substances are used as a form of self-medication to alleviate stress.