Neuroimaging, genomics, transcriptomics and epigenomics: dealing with big data toward an integrative model of mental disorders

Abstract

Mental disorders (MD) such as schizophrenia, bipolar disorder, major depressive disorder, and substance use disorders are among the largest sources of medical disability in the world, surpassing both cardiovascular disease and cancer. Together, they have an enormous impact on public health, representing 39% of the years lived with disability and a reduction of life expectancy of more than 15 years. The picture is even more dramatic in Brazil where neuropsychiatric disorders are responsible for 19% of the total burden of diseases, and the relative morbidity associated with MD is increasing, as a consequence of the improvement in general health indicators and longevity. A vast amount of research over the last twenty years converged into the perspective that MD are diseases of brain circuits. MD are complex, multifactorial genetic/epigenetic disorders, associated with brain changes that occur throughout neurodevelopment, under environmental influence Psychiatry needs to follow general medicine and focus on diagnosis, prevention and treatment strategies. However several challenges have to be tackled to reach prevention of MD among them limited biological knowledge and poor effectiveness of the available prevention and treatments strategies. In the last decades, the psychiatry area has gained important tools and methods, such as genetics and neuroimaging approaches, to help understanding the pathogenesis and progression of mental diseases and these methods have produced a huge volume of data, given their complexity. In this context, we highlight the present project as a multidisciplinary combining research in computer science, neuroimaging and genetics/epigenetics and as multistage project, since we will analyze data from patients in different stages of mental disorders. Here will use the Bioinformatics, which is an integration of computational science, statistics and mathematics to analyze and interpret biological data, in order to develop pipelines, algorithms and methods for solving biological problems of psychiatry. Our main goal is to develop tools and techniques regarding processing and storage of information of genomes and imaging from psychiatry patients in a way that other researchers can use, and this pipelines might be reproduced in a simple manner by other stakeholders. (AU)