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1.
Front Mol Neurosci ; 16: 1268827, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38178910

RESUMO

Copy number variants (CNVs) are among the main genetic factors identified in schizophrenia (SZ) through genome-scale studies conducted mostly in Caucasian populations. However, to date, there have been no genome-scale CNV reports on patients from India. To address this shortcoming, we generated, for the first time, genome-scale CNV data for 168 SZ patients and 168 controls from South India. In total, 63 different CNVs were identified in 56 patients and 46 controls with a significantly higher proportion of medium-sized deletions (100 kb-1 Mb) after multiple testing (FDR = 2.7E-4) in patients. Of these, 13 CNVs were previously reported; however, when searched against GWAS, transcriptome, exome, and DNA methylation studies, another 17 CNVs with candidate genes were identified. Of the total 30 CNVs, 28 were present in 38 patients and 12 in 27 controls, indicating a significantly higher representation in the former (p = 1.87E-5). Only 4q35.1-q35.2 duplications were significant (p = 0.020) and observed in 11 controls and 2 patients. Among the others that are not significant, a few examples of patient-specific and previously reported CNVs include deletions of 11q14.1 (DLG2), 22q11.21, and 14q21.1 (LRFN5). 16p13.3 deletion (RBFOX1), 3p14.2 duplication (CADPS), and 7p11.2 duplication (CCT6A) were some of the novel CNVs containing candidate genes. However, these observations need to be replicated in a larger sample size. In conclusion, this report constitutes an important foundation for future CNV studies in a relatively unexplored population. In addition, the data indicate that there are advantages in using an integrated approach for better identification of candidate CNVs for SZ and other mental health disorders.

2.
Indian J Psychiatry ; 65(12): 1275-1281, 2023 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-38298867

RESUMO

Background: Existing psychiatric epidemiological studies from Tamil Nadu with methodological limitations and variations had under-reported the prevalence of mental morbidity. Robust data from a representative population-based epidemiological study are not readily available to guide mental health programs in Tamil Nadu. Aim: This study aimed to estimate the prevalence, correlates, and treatment gap of mental morbidity in the state of Tamil Nadu using data from National Mental Health Survey (NMHS) of India, 2015-2016. Materials and Methods: NMHS in Tamil Nadu was conducted in 60 clusters of 4 districts (Trichy, Tirunelveli, Thoothukudi, and Namakkal) using a door-to-door survey and multistage sampling proportionate to rural, urban nonmetro, and urban metro population. Mini-International Neuropsychiatric Interview (M.I.N.I version 6) and Fagerstrom nicotine dependence scale were administered on a representative adult (aged ≥18 years) sample to assess the mental morbidity. Prevalence and 95% confidence intervals (CIs) were estimated after weighing the sample for survey design. Results: A total of 3059 adults from 1069 households were interviewed. The overall weighted prevalence of lifetime and current mental morbidity was 19.3% (95% CI: 19.0%-19.6%) and 11.8% (95% CI: 11.6%-12.0%) respectively. Participants who were men (largely contributed by substance-use disorders), aged 40-49 years, from rural areas, and from lower income quintile had higher prevalence of mental morbidity. The treatment gap was 94.2% for any mental health problem. Common mental disorders (depression, anxiety, and substance-use) accounted for most of the morbidity. Conclusion: The burden and treatment gap for mental health morbidity is high in Tamil Nadu. The findings call for urgent policy level and systemic action to strengthen mental health program in Tamil Nadu.

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