Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/111727
PIRA download icon_1.1View/Download Full Text
Title: Decoding the genetic comorbidity network of alzheimer's disease
Authors: Zhang, X
Li, D
Ye, S
Liu, S
Ma, S
Li, M
Peng, Q
Hu, L
Shang, X 
He, M 
Zhang, L
Issue Date: 2024
Source: BioData mining, 2024, v. 17, 40
Abstract: Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. Graphical Abstract: Study pipeline.
Publisher: BioMed Central Ltd.
Journal: BioData mining 
EISSN: 1756-0381
DOI: 10.1186/s13040-024-00394-w
Rights: © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Zhang, X., Li, D., Ye, S. et al. Decoding the genetic comorbidity network of Alzheimer's disease. BioData Mining 17, 40 (2024) is available at https://doi.org/10.1186/s13040-024-00394-w.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
s13040-024-00394-w.pdf2.99 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

1
Citations as of Apr 14, 2025

Downloads

2
Citations as of Apr 14, 2025

SCOPUSTM   
Citations

1
Citations as of Dec 19, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.