Skip to main content

ORIGINAL RESEARCH article

Front. Genet.
Sec. Statistical Genetics and Methodology
Volume 15 - 2024 | doi: 10.3389/fgene.2024.1518471
This article is part of the Research Topic Expanding Insights Into Structure, Function, and Disorder of Genome by the Power of Artificial Intelligence in Bioinformatics View all articles

Dual disease co-expression analysis reveals potential roles of estrogen-related genes in postmenopausal osteoporosis and Parkinson's disease

Provisionally accepted
Dong Yu Dong Yu 1,2*Jian Kang Jian Kang 2Chengguo Ju Chengguo Ju 2Qingyan Wang Qingyan Wang 2Ye Qiao Ye Qiao 1,2Long Qiao Long Qiao 1,2Dongxiang Yang Dongxiang Yang 2
  • 1 Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China
  • 2 Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China

The final, formatted version of the article will be published soon.

    The deficiency of estrogen correlates with a range of diseases, notably Postmenopausal osteoporosis (PMO) and Parkinson's disease (PD). There is a possibility that PMO and PD may share underlying molecular mechanisms that are pivotal in their development and progression. The objective of this study was to identify critical genes and potential mechanisms associated with PMO by examining co-expressed genes linked to PD. Initially, pertinent data concerning PMO and PD were obtained from the GWAS database, followed by conducting a Bayesian colocalization analysis. Subsequently, co-expressed genes from the PMO dataset (GSE35956) and the PD dataset (GSE20164) were identified and cross-referenced with estrogen-related genes (ERGs). Differentially expressed genes (DEGs) among PMO, PD, and ERGs were subjected to an array of bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses, in addition to protein-protein interaction (PPI) network analysis. The study also involved constructing TF-gene interactions, TF-microRNA coregulatory networks, interactions of hub genes with diseases, and validation through quantitative reverse transcription polymerase chain reaction (qRT-PCR). The colocalization analysis uncovered shared genetic variants between PD and osteoporosis, with a posterior probability of colocalization (PPH4) measured at 0.967. Notably, rs3796661 was recognized as a shared genetic variant. A total of 11 genes were classified as DEGs across PMO, PD, and ERGs. Five principal KEGG pathways were identified, which include the p53 signaling pathway, TGFbeta signaling pathway, cell cycle, FoxO signaling pathway, and cellular senescence. Additionally, three hub genes-WT1, CCNB1, and SMAD7-were selected from the PPI network utilizing Cytoscape software. These three hub genes, which possess significant diagnostic value for PMO and PD, were further validated using GEO datasets. Interactions between transcription factors and genes, as well as between microRNAs and hub genes, were established. Ultimately, the expression trends of the identified hub genes were confirmed through qRT-PCR validation. This study is anticipated to offer innovative approaches for identifying potential biomarkers and important therapeutic targets for both PMO and PD.

    Keywords: Postmenopausal osteoporosis, Parkinson Disease, Differentially expressed genes, estrogen, Common gene

    Received: 28 Oct 2024; Accepted: 16 Dec 2024.

    Copyright: © 2024 Yu, Kang, Ju, Wang, Qiao, Qiao and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Dong Yu, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.