Identification of significant biomarkers for predicting the risk of bipolar disorder with arteriosclerosis based on integrative bioinformatics and machine learning

Identification of significant biomarkers for predicting the risk of bipolar disorder with arteriosclerosis based on integrative bioinformatics and machine learning

IntroductionIncreasing evidence has indicated a connection between bipolar disorder (BD) and arteriosclerosis (AS), yet the specific molecular mechanisms remain unclear. This study aims to investigate the hub genes and molecular pathways for BD with AS.MethodsBD-related dataset GSE12649 were downloa...

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Bibliographic Details
Main Authors: Xiabing Zheng, Xiaozhe Zhang, Yaqi Zhang, Cai Chen, Erni Ji
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-09-01
Series:Frontiers in Psychiatry
Subjects:
bipolar disorder
arteriosclerosis
bioinformatics
hub genes
CX3CR1
ST6GAL1
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1392437/full

Internet

https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1392437/full

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