Disaster mental health is based on the principles of ‘preventive medicine’ This principle has necessitated a paradigm shift from relief centered post-disaster management to a holistic, multi-dimensional integrated community approach of health promotion, disaster prevention, preparedness and mitigation. This has ignited the paradigm shift from curative to preventive aspects of disaster management. This can be understood on the basis of six ‘R’s such as Readiness (Preparedness), Response (Immediate action), Relief (Sustained rescue work), Rehabilitation (Long term remedial measures using community resources), Recovery (Returning to normalcy) and Resilience (Fostering). Prevalence of mental health problems in disaster affected population is found to be higher by two to three times than that of the general population. Along with the diagnosable mental disorders, affected community also harbours large number of sub-syndromal symptoms. Majority of the acute phase reactions and disorders are self-limiting, whereas long-term phase disorders require assistance from mental health professionals. Role of psychotropic medication is very limited in preventing mental health morbidity. The role of cognitive behaviour therapy (CBT) in mitigating the mental health morbidity appears to be promising. Role of Psychological First Aid (PFA) and debriefing is not well-established. Disaster management is a continuous and integrated cyclical process of planning, organising, coordinating and implementing measures to prevent and to manage disaster effectively. Thus, now it is time to integrate public health principles into disaster mental health.

BackgroundThere is emerging evidence that there are shared genetic, environmental and developmental risk factors in psychiatry, that cut across traditional diagnostic boundaries. With this background, the Discovery biology of neuropsychiatric syndromes (DBNS) proposes to recruit patients from five different syndromes (schizophrenia, bipolar disorder, obsessive compulsive disorder, Alzheimer’s dementia and substance use disorders), identify those with multiple affected relatives, and invite these families to participate in this study. The families will be assessed: 1) To compare neuro-endophenotype measures between patients, first degree relatives (FDR) and healthy controls., 2) To identify cellular phenotypes which differentiate the groups., 3) To examine the longitudinal course of neuro-endophenotype measures., 4) To identify measures which correlate with outcome, and 5) To create a unified digital database and biorepository.MethodsThe identification of the index participants will occur at well-established specialty clinics. The selected individuals will have a strong family history (with at least another affected FDR) of mental illness. We will also recruit healthy controls without family history of such illness. All recruited individuals (N = 4500) will undergo brief clinical assessments and a blood sample will be drawn for isolation of DNA and peripheral blood mononuclear cells (PBMCs). From among this set, a subset of 1500 individuals (300 families and 300 controls) will be assessed on several additional assessments [detailed clinical assessments, endophenotype measures (neuroimaging- structural and functional, neuropsychology, psychophysics-electroencephalography, functional near infrared spectroscopy, eye movement tracking)], with the intention of conducting repeated measurements every alternate year. PBMCs from this set will be used to generate lymphoblastoid cell lines, and a subset of these would be converted to induced pluripotent stem cell lines and also undergo whole exome sequencing.DiscussionWe hope to identify unique and overlapping brain endophenotypes for major psychiatric syndromes. In a proportion of subjects, we expect these neuro-endophenotypes to progress over time and to predict treatment outcome. Similarly, cellular assays could differentiate cell lines derived from such groups. The repository of biomaterials as well as digital datasets of clinical parameters, will serve as a valuable resource for the broader scientific community who wish to address research questions in the area.

Lithium is an effective, well-established treatment for bipolar disorder (BD). However, the mechanisms of its action, and reasons for variations in clinical response, are unclear. We used neural precursor cells (NPCs) and lymphoblastoid cell lines (LCLs), from BD patients characterized for clinical response to lithium (using the “Alda scale” and “NIMH Retrospective Life chart method”), to interrogate cellular phenotypes related to both disease and clinical lithium response. NPCs from two biologically related BD patients who differed in their clinical response to lithium were compared with healthy controls. RNA-Seq and analysis, mitochondrial membrane potential (MMP), cell viability, and cell proliferation parameters were assessed, with and without in vitro lithium. These parameters were also examined in LCLs from 25 BD patients (16 lithium responders and 9 non-responders), and 12 controls. MMP was lower in both NPCs and LCLs from BD; but it was reversed with in vitro lithium only in LCLs, and this was unrelated to clinical lithium response. The higher cell proliferation observed in BD was unaffected by in vitro lithium. Cell death was greater in BD. However, LCLs from clinical lithium responders could be rescued by addition of in vitro lithium. In vitro lithium also enhanced BCL2 and GSK3B expression in these cells. Our findings indicate cellular phenotypes related to the disease (MMP, cell proliferation) in both NPCs and LCLs; and those related to clinical lithium response (cell viability, BCL2/GSK3B expression) in LCLs.

Aim:In a resource-poor country such as India, telepsychiatry could be an economical method to expand health-care services. This study was planned to compare the costing and feasibility of three different service delivery models. The end user was a state-funded long-stay Rehabilitation Center (RC) for the homeless.Methodology:Model A comprised patients going to a tertiary care center for clinical care, Model B was community outreach service, and Model C comprised telepsychiatry services. The costing included expenses incurred by the health system to complete a single consultation for a patient on an outpatient basis. It specifically excluded the cost borne by the care-receiver. No patients were interviewed for the study.Results:The RC had 736 inmates, of which 341 had mental illness of very long duration. On comparing the costing, Model A costed 6047.5 INR (100$), Model B costed 577.1 INR (9.1$), and Model C costed 137.2 INR (2.2$). Model C was found fifty times more economical when compared to Model A and four times more economical when compared to Model B.Conclusion:Telepsychiatry services connecting tertiary center and a primary health-care center have potential to be an economical model of service delivery compared to other traditional ones. This resource needs to be tapped in a better fashion to reach the unreached.

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