Integrative ceRNA network analysis identifies unique and shared molecular signatures in Bipolar Disorder and Schizophrenia.

Bipolar Disorder (BPD) and Schizophrenia (SCZ) are complex psychiatric disorders with shared symptomatology and genetic risk factors. Understanding the molecular mechanisms underlying these disorders is crucial for refining diagnostic criteria and guiding targeted treatments. In this study, publicly available RNA-seq data from post-mortem samples of the basal ganglia's striatum were analyzed using an integrative computational approach to identify differentially expressed (DE) transcripts associated with SCZ and BPD. The analysis aimed to reveal both shared and distinct genes and long non-coding RNAs (lncRNAs) and to construct competitive endogenous RNA (ceRNA) networks within the striatum. Furthermore, the functional implications of these identified transcripts are explored, alongside their presence in established databases such as BipEx and SCHEMA. A significant outcome of our analysis was the identification of 21 DEmRNAs and 1 DElncRNA shared between BPD and SCZ across the Caudate, Putamen, and Nucleus Accumbens. Another noteworthy finding was the identification of Hub nodes within the ceRNA networks that were linked to major psychosis. Particularly, MED19, HNRNPC, MAGED4B, KDM5A, GOLGA7, CHASERR, hsa-miR-4778-3p, hsa-miR-4739, and hsa-miR-4685-5p emerged as potential biomarkers. These findings shed light on the common and unique molecular signatures underlying BPD and SCZ, offering significant potential for the advancement of diagnostic and therapeutic strategies tailored to these psychiatric disorders.

District-level differences in the distribution of mental and substance use disorders in Assam.

Background: The lifetime prevalence of mental morbidity in Assam is estimated at 8% (NMHS 2015-16). Understanding the distribution patterns of different types of mental disorders among persons with mental morbidity in different districts would facilitate evidence-driven district mental health programming in Assam. Given the varied socio-geopolitical situation across districts in Assam, significant variations in the distribution of mental disorders are expected. Aims: To assess interdistrict differentials in common mental disorders (CMDs), severe mental disorders (SMDs), socioeconomic impact, healthcare utilization, and mental disability across three districts sampled in NMHS in Assam. Materials and Methods: This cross-sectional study used stratified random cluster sampling to identify and study eligible adult participants in Dibrugarh, Barpeta, and Cachar districts. Standardized scales and validated questionnaires were used to assess mental morbidity, disability, socioeconomic impact, and healthcare utilization. The distribution of different mental disorders among persons with mental disorders and their interdistrict differentials were tested using the Chi-square test of significance. Results: Among persons with mental morbidity, the most common disorder was CMDs (79%). The proportional distribution of CMDs among persons with mental morbidity was significantly higher in the Dibrugarh district (79%), whereas the distribution of SMDs was higher in the Cachar district (55%). The distribution of alcohol use disorder was the highest in the Dibrugarh district (71.6%). Significant differences in disability and healthcare utilization were observed between the districts. Conclusions: NMHS 2015-16 Assam indicates significant differentials in the distribution of CMDs and SMDs, healthcare utilization, and associated disability between the three districts. The differentials necessitate further research to understand socio-ethnocultural, religious, geopolitical, and other factors influencing the distribution. These differences need to be accounted for during the implementation of mental health programs in the state.