Evaluation of the Common Molecular Basis in Alzheimer's and Parkinson's Diseases

• Published in: International journal of molecular sciences Vol. 20; no. 15; p. 3730
• Main Authors: Rana, Pratip, Franco, Edian F, Rao, Yug, Syed, Khajamoinuddin, Barh, Debmalya, Azevedo, Vasco, Ramos, Rommel T J, Ghosh, Preetam
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30-07-2019; MDPI
• Subjects: Alzheimer Disease - genetics; Alzheimer's disease; Biomarkers; Cerebrospinal fluid; Disease; Gene expression; gene regulatory network; Gene Regulatory Networks; Genes; Genetic Predisposition to Disease; genetics; Genome-wide association studies; Genomes; Genomics; HLA-DRB5 Chains - genetics; Humans; Immune system; Inflammation; Metabolism; MicroRNAs - genetics; MicroRNAs - metabolism; miRNA; miRNAs; Mutation; Nervous system; Neurodegeneration; Oxidative stress; Parkinson Disease - genetics; Parkinson’s disease; Pathology; Patients; Population; Prefrontal cortex; Proteins; Regulators; Review; Risk analysis; Risk factors; Similarity; Sirtuin 1 - genetics; Transcriptomics; genetics; Alzheimer’s disease; miRNAs; gene regulatory network; Parkinson’s disease
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms20153730

Alzheimer's disease (AD) and Parkinson's disease (PD) are the most common neurodegenerative disorders related to aging. Though several risk factors are shared between these two diseases, the exact relationship between them is still unknown. In this paper, we analyzed how these two diseases relate to each other from the genomic, epigenomic, and transcriptomic viewpoints. Using an extensive literature mining, we first accumulated the list of genes from major genome-wide association (GWAS) studies. Based on these GWAS studies, we observed that only one gene (
) was shared between AD and PD. A subsequent literature search identified a few other genes involved in these two diseases, among which SIRT1 seemed to be the most prominent one. While we listed all the miRNAs that have been previously reported for AD and PD separately, we found only 15 different miRNAs that were reported in both diseases. In order to get better insights, we predicted the gene co-expression network for both AD and PD using network analysis algorithms applied to two GEO datasets. The network analysis revealed six clusters of genes related to AD and four clusters of genes related to PD; however, there was very low functional similarity between these clusters, pointing to insignificant similarity between AD and PD even at the level of affected biological processes. Finally, we postulated the putative epigenetic regulator modules that are common to AD and PD.