Models for diagnosing schizophrenia and depression using genetic data
Date Issued
March 11, 2021
Type
Μεταπτυχιακή Διπλωματική Εργασία
Abstract
In many countries, schizophrenia, schizoaffective, bipolar and other mental disorders have been consistently overdiagnosed and affective disorders underdiagnosed, particularly among vulnerable and lower socioeconomic groups. The general causes of such misdiagnoses include overreliance on the classic thought disorder symptoms as pathognomonic of schizophrenia or other psychoses and, for affective disorders, lack of clearly characterized boundaries between normal and abnormal behaviors and failure to realize that patients with affective illness can manifest cognitive symptoms. In addition to the above factors, misdiagnosis among some specific social groups results from such factors as cultural differences in language and mannerisms, difficulties in relating between patients and therapists, and other myths related to mental and affective disorders.
In the modern era, due to the recent findings and correlations, scientists have significantly advanced the understanding of the genetic architecture of schizophrenia. In this work, a genetic analysis in three mental conditions (schizophrenia, schizoaffective disorder, depression) will be conducted while the developed models for diagnosing schizophrenia, schizoaffective disorder, and bipolar disorder using genetic data setting will set the example on how this knowledge may be translated into advances that will improve diagnosis and patient health control.
Subjects