Clinical characteristics and structural changes in MRI: importance for the outcome of depression in the elderly

• Grant number: 14/05467-7
• Support type: Scholarships in Brazil - Post-Doctorate
• Effective date (Start): October 01, 2014
• Effective date (End): January 31, 2019
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal researcher: Geraldo Busatto Filho
• Grantee: Salma Rose Imanari Ribeiz Nery
• Home Institution: Instituto de Psiquiatria Doutor Antonio Carlos Pacheco e Silva (IPq). Hospital das Clínicas da Faculdade de Medicina da USP (HCFMUSP). Secretaria da Saúde (São Paulo - Estado). São Paulo , SP, Brazil
• Associated research grant: 12/50010-0 - Prevention and Treatment of Depression in Older People: A Population-Based Study, AP.TEM

Abstract

Depression is among the major mental disorders in the elderly, and according to the World Health Association (WHO), depression is currently among the top ten causes of burden of disease worldwide, and in 2030 will be the leading cause of burden of disease. The successful treatment of depression is one of the most effective ways to reduce impairment in general, prevent morbidity and improve quality of life in a depressed elderly patient. In general, around 30% of the elderly treated in the community or primary care will reach remission of the depressive symptoms. To better understand the pathophysiology of depression in the elderly and to improve medical care of depression in old age, a study that investigates predictors of treatment response is urgently needed. The main objective of the present study is to investigate predictive factors of response to pharmacological treatment of depression (age at onset of depression, psychopathological characteristics, medical comorbidity, cognitive profile, genetic and structural brain changes). This study is a hybrid design, in which we initially used a case-control comparison (120 patients with major depression and 100 elderly controls), followed by a prospective follow-up of elderly depressed patients (n = 120) underwent a clinical naturalistic. Patients will be treated according to a pharmacological algorithm for depression in the elderly for 18 months. Personality traits, neuropsychological tests, genetic polymorphisms and structural changes on MRI scans will be evaluated. In conclusion, we aim to identify which factors may predict a better response to pharmacological treatment of elderly depressed, resulting in more effective treatment of depression in this age group. Moreover, the effectiveness of the use of this algorithm in this sample of old age patients with depression will be evaluated. (AU)