Presentations

Abstract

Introduction: A mutation in mitochondrial DNA (mtDNA) that is strongly associated with Alzheimer's disease (AD) has been discovered by the Castora lab. This T9861C mutation changes a phenylalanine into a leucine at amino acid position 219 of cytochrome c oxidase subunit 3, resulting in a significant reduction of cytochrome oxidase activity. Effects of this mutation on gene expression in AD brains have previously been studied using PCR array analysis and more recently using RNA bulk sequencing. The genes included in the array analysis focused on mitochondrial function and ATP production while the RNA bulk sequencing analysis included all cellular RNA species. In this study, we compared all data from both analysis methods to better understand the effects of the mutation on gene expression in AD brains and to identify potential therapeutic targets for AD and AD+ patients.

Methods: Qiagen Ingenuity Pathway Analysis (IPA) software was used to analyze the data for each gene as three expression log ratios: AD brains/control brains, AD+ brains/control brains, and AD+ brains/AD brains. These ratios were run through an IPA core analysis filtered to only include genes whose expression log ratios were between -2.0 to 2.0 in the comparisons. IPA connected the PCR Array and RNA Bulk datasets to findings from literature stored in IPA's knowledge base and identified relationships, pathways, mechanisms, and functions relevant to each dataset. The two analyses were compared. Regulator effects were grown to connect with other molecules, and the downstream and upstream effects of activating and inhibiting molecules were observed using the molecule activity predictor (MAP). We created a pathway using regulators and molecules, in the datasets, directly related to AD and used MAP to identify potential therapeutic targets.

Results: Our IPA analysis identified the top canonical pathways related to the genes in the datasets, the most expressed regulators in the datasets, the top diseases and functions affected by the expression of the genes in the dataset, and the downstream and upstream effects of the changing expression of genes in the dataset. The RNA bulk sequencing analysis provided more data, resulting in IPA returning more canonical pathways; regulators, regulator effects; diseases and functions related to the genes in the datasets. However, these results were less statistically significant than those returned by the PCR array analysis. Another difference between the datasets was that the AD/Control ratio was the most statistically significant between the three for PCR array analysis while AD+/Control was the most statistically significant for RNA bulk sequencing analysis.

Conclusion: The difference in the amount of data and statistical significance provided by the RNA bulk sequencing analysis and the PCR array analysis provides evidence that the focused number of genes in the PCR array analysis results in greater statistical significance while sacrificing breadth. Through exploring the relationships between and manipulating the expression of regulators, molecules, and diseases retrieved from IPA's database for the two datasets, we identified activating brain derived neurotrophic factor (BDNF) as the most effective therapeutic approach for inhibiting Alzheimer's disease. BDNF will be added to a mathematical model to evaluate and optimize the therapeutic potential of activating BDNF to significantly inhibit AD in patients, including those possessing the T9861C mtDNA mutation.