ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders.

Roman Ivanov,Alexandra Klimenko,Evgeny Zavarzin,Sergey Lashin,Yury G Matushkin,Fedor Kazantsev,Alexander Savostyanov,Natalya Milakhina

doi:10.3390/jpm12010053

Abstract

In this study, we collected and systemized diverse information related to depressive and anxiety disorders as the first step on the way to investigate the associations between molecular genetics, electrophysiological, behavioral, and psychological characteristics of people. Keeping that in mind, we developed an internet resource including a database and tools for primary presentation of the collected data of genetic factors, the results of electroencephalography (EEG) tests, and psychological questionnaires. The sample of our study was 1010 people from different regions of Russia. We created the integrated ICBrainDB database that enables users to easily access, download, and further process information about individual behavioral characteristics and psychophysiological responses along with inherited trait data. The data obtained can be useful in training neural networks and in machine learning construction processes in Big Data analysis. We believe that the existence of such a resource will play an important role in the further search for associations of genetic factors and EEG markers of depression.

Highlights

Depression and anxiety are among the most common mental health disorders in a modern society
Despite the long history of elaboration of methods for diagnostic and treatment of depression, modern psychology and medicine face the challenge of identifying the genetic factors associated with this pathology [1]
The database provides a comprehensive access to depersonalized data on each individual, including genetic traits, fMRI, and psychological questionnaire summaries data via REST API

Summary

Introduction

Depression and anxiety are among the most common mental health disorders in a modern society. Depressive disorders significantly reduce the quality of life, damage health, and are even life-threatening due to an increased risk of suicide. Despite the long history of elaboration of methods for diagnostic and treatment of depression, modern psychology and medicine face the challenge of identifying the genetic factors associated with this pathology [1]. Finding the genetic predisposition of psychological disorders is complicated due to the fact that the most of them are complex disorders associated with many various genes and environmental factors that influence dynamics of depression. In addition to genetic studies of the causes of depression, there has been an increasing accumulation of data on the neural basis of integrative brain activity and its pathology in depression, by using of electroencephalography (EEG)

Methods

Results

Conclusion