Data Analysis of Genetic Variability in Alzheimer’s Affected Brains

Abstract

Alzheimer's disease (AD) has been widely recognized as the most common cause of dementia. Alzheimer's disease is a terminal neurological disorder that primarily affects the elderly and causes gradual memory loss and neurodegeneration. The National Institute on Aging-Association Alzheimer's (NIA-AA) analyzed and illustrated Alzheimer's disease (AD) as cognitive damage in 2011. AD steadily erodes a person's ability to learn, think, and communicate. According to Alzheimer's Disease International (ADI), over 50 million individuals worldwide were living with AD in 2019, and with approximately 10 million new cases every year, this figure is expected to rise to 82 million by 2030 and 152 million by 2050. There are two forms of Alzheimer's disease: early-onset Alzheimer's disease and late-onset Alzheimer's disease (LOAD). AD manifests itself as early-onset Alzheimer's disease between the ages of 30 and 60. This is a rarer form of Alzheimer's disease, affecting only 10% of all AD patients. Amyloid precursor proteins (APP) on chromosome 21, Presenilin (PSEN 1) on chromosome 14, and PSEN 2 on chromosome 1 are markers for early-onset AD. Late-onset Alzheimer's disease is more common and begins around the age of 60. No one gene causes LOAD, however, the presence of apolipoprotein E (APOE) on chromosome 19 raises the risk. We will be studying gene expression data from 22 Alzheimer's patients and 9 controls. The differences and similarities between the various severities of this condition will be examined, as 7 of the 22 participants have incipient Alzheimer's disease, 8 have intermediate Alzheimer's disease, and 7 have severe Alzheimer's disease. Using the Orange software, we will be able to evaluate the data using principal component analysis (PCA). We will utilize the RStudio software to create a volcano plot for the data points that we have accumulated.