Computational identification of key genes that may regulate gene expression reprogramming in Alzheimer’s patients

Autoři: Judith A. Potashkin aff001;  Virginie Bottero aff001;  Jose A. Santiago aff002;  James P. Quinn aff003
Působiště autorů: The Cellular and Molecular Pharmacology Department, The Chicago Medical School, Rosalind Franklin University of Medicine and Science, North Chicago, IL, United States of America aff001;  NeuroHub Analytics, LLC, Chicago, IL, United States of America aff002;  Q Regulating Systems, LLC, Gurnee, IL, United States of America aff003
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0222921


The dementia epidemic is likely to expand worldwide as the aging population continues to grow. A better understanding of the molecular mechanisms that lead to dementia is expected to reveal potentially modifiable risk factors that could contribute to the development of prevention strategies. Alzheimer’s disease is the most prevalent form of dementia. Currently we only partially understand some of the pathophysiological mechanisms that lead to development of the disease in aging individuals. In this study, Switch Miner software was used to identify key switch genes in the brain whose expression may lead to the development of Alzheimer’s disease. The results indicate that switch genes are enriched in pathways involved in the proteasome, oxidative phosphorylation, Parkinson’s disease, Huntington’s disease, Alzheimer’s disease and metabolism in the hippocampus and posterior cingulate cortex. Network analysis identified the krupel like factor 9 (KLF9), potassium channel tetramerization domain 2 (KCTD2), Sp1 transcription factor (SP1) and chromodomain helicase DNA binding protein 1 (CHD1) as key transcriptional regulators of switch genes in the brain of AD patients. These transcriptions factors have been implicated in conditions associated with Alzheimer’s disease, including diabetes, glucocorticoid signaling, stroke, and sleep disorders. The specific pathways affected reveal potential modifiable risk factors by lifestyle changes.

Klíčová slova:

Alzheimer's disease – Gene expression – Gene mapping – Microarrays – Network analysis – Non-coding RNA – Swimming – Transcription factors


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