Obstructive Sleep Apnea and Dementia-Common Gene Associations through Network-Based Identification of Common Driver Genes

Authors

Hyun-Hwan Jeong
Arvind Chandrakantan
Adam C Adler

Publication Date

4-9-2021

Journal

Genes

DOI

10.3390/genes12040542

PMID

33918603

PMCID

PMC8069301

PubMedCentral® Posted Date

4-9-2021

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Biomarkers, Computational Biology, Databases, Genetic, Dementia, Gene Expression Regulation, Humans, Polymorphism, Single Nucleotide, Sleep Apnea, Obstructive, Systems Biology, Obstructive Sleep Apnea, driver genes, Alzheimer’s disease

Abstract

BACKGROUND: Obstructive Sleep Apnea (OSA) occurs in 7% of the adult population. The relationship between neurodegenerative diseases such as dementia and sleep disorders have long attracted clinical attention; however, no comprehensive data exists elucidating common gene expression between the two diseases. The objective of this study was to (1) demonstrate the practicability and feasibility of utilizing a systems biology approach called network-based identification of common driver genes (NICD) to identify common genomic features between two associated diseases and (2) utilize this approach to identify genes associated with both OSA and dementia.

METHODS: This study utilized 2 public databases (PCNet, DisGeNET) and a permutation assay in order to identify common genes between two co-morbid but mutually exclusive diseases. These genes were then linked to their mechanistic pathways through Enrichr, producing a list of genes that were common between the two different diseases.

RESULTS: 42 common genes were identified between OSA and dementia which were primarily linked to the G-coupled protein receptor (GPCR) and olfactory pathways. No single nucleotide polymorphisms (SNPs) were identified.

CONCLUSIONS: This study demonstrates the viability of using publicly available databases and permutation assays along with canonical pathway linkage to identify common gene drivers as potential mechanistic targets for comorbid diseases.

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