THE GENETIC OVERLAP BETWEEN NEUROPSYCHIATRIC DISORDERS: A META-ANALYSIS OF NEXT GENERATION SEQUENCING DATA

Neurodegenerative and neuropsychiatric disorders (NDD-NPDs) are multifactorial, polygenic and complex behavioral phenotypes caused by brain abnormalities. Most genetic studies have focused on understanding the genetic component of specific brain diseases. Several brain diseases also show similar clinical and pathological symptoms. In recen years, multiple studies have used next generation sequencing (NGS) technologies such as RNA sequencing (RNA-Seq) to investigate molecular signature of brain diseases. However, many studies have only focused on a particular disease and limited brain regions. By using the data from a broad range of cortical regions from multiple brain diseases, we will be able to dig deeper into the molecular basis of neurological diseases. The main aim of this thesis was to examine the transcriptome-wide characterization of cortical brain regions across neurological disorders. We focused our research efforts on highlighting cross-disease shared molecular signatures, and exploring co-expression networks and cell-type-specific patterns for NDD-NPDs. By processing and analyzing RNA-Seq data using a set of computational tools and statistical tests, we performed transcriptomic profiling of brain samples from eight groups of patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), Progressive Supranuclear Palsy (PSP), Pathological Aging (PA), Autism Spectrum Disorder (ASD), Schizophrenia (SZ), Major Depressive Disorder (MDD), and Bipolar Disorder (BP)-in comparison with 2,078 brain samples from matched control subjects. In this thesis, we provide a transcriptomic framework to understand the molecular architecture of NPDs and NDDs through their shared- and specific gene expression in the brain.