<i>FOXO3</i> as a potential diagnostic biomarker for autophagy in rheumatoid arthritis: A bioinformatics study

This study aimed to identify genes associated with autophagy and potential diagnostic biomarkers by comparing the gene expression profiles of synovial tissues in patients with rheumatoid arthritis (RA) and healthy individuals, aiming to offer new insights for clinical treatment strategies. We used publicly available datasets to analyze differentially expressed genes (DEGs) between the synovial tissue of RA patients and healthy individuals. Then, we intersected these DEGs with autophagy-related genes to identify autophagy genes in the synovial tissue of RA patients. We further analyzed the biological processes and functions of these genes. Furthermore, we used machine learning to identify characteristic autophagy genes in RA synovial tissue. Finally, we examined the differential expression of these characteristic genes in the blood of RA patients using an external dataset. Our study identified <i>FOXO3</i> as a potential biomarker for diagnosing RA. <i>FOXO3</i> gene expression was downregulated in both the synovial tissue and blood of RA patients, suggesting its involvement in multiple biological processes such as local inflammation, oxidative stress, metabolic processes, and immune responses. Our findings suggest that <i>FOXO3</i> may be a novel biomarker for the clinical diagnosis of RA and may play a crucial role in the pathogenesis of RA. The study provides new insights into the molecular mechanisms of RA and potential new therapeutic targets.

Authors

Institutions

Publication Details

Journal
Autoimmunity
Published
2024-11-05
DOI
https://doi.org/10.1080/08916934.2024.2423759
Citations
2
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.57

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FOXO3 as a potential diagnostic biomarker for autophagy in rheumatoid arthritis: A bioinformatics study

Fanyu Meng, Qian Deng, Mengyuan Zhu, W. Zeng et al.
2 citations
Autoimmunity
Cancer-related molecular mechanisms research
0.57
article

FOXO3 as a potential diagnostic biomarker for autophagy in rheumatoid arthritis: A bioinformatics study

Fanyu Meng, Qian Deng, Mengyuan Zhu, W. Zeng, Weitian Yan, Jiangyun Peng, Zining Peng, Nian Liu
article en
2 citations

Abstract

This study aimed to identify genes associated with autophagy and potential diagnostic biomarkers by comparing the gene expression profiles of synovial tissues in patients with rheumatoid arthritis (RA) and healthy individuals, aiming to offer new insights for clinical treatment strategies. We used publicly available datasets to analyze differentially expressed genes (DEGs) between the synovial tissue of RA patients and healthy individuals. Then, we intersected these DEGs with autophagy-related genes to identify autophagy genes in the synovial tissue of RA patients. We further analyzed the biological processes and functions of these genes. Furthermore, we used machine learning to identify characteristic autophagy genes in RA synovial tissue. Finally, we examined the differential expression of these characteristic genes in the blood of RA patients using an external dataset. Our study identified <i>FOXO3</i> as a potential biomarker for diagnosing RA. <i>FOXO3</i> gene expression was downregulated in both the synovial tissue and blood of RA patients, suggesting its involvement in multiple biological processes such as local inflammation, oxidative stress, metabolic processes, and immune responses. Our findings suggest that <i>FOXO3</i> may be a novel biomarker for the clinical diagnosis of RA and may play a crucial role in the pathogenesis of RA. The study provides new insights into the molecular mechanisms of RA and potential new therapeutic targets.

AutoimmunityVol. 57(1)
Yunnan University (CN), Yunnan University of Traditional Chinese Medicine (CN)
National Natural Science Foundation of China
Zero hunger
Openalex Percentile: Top 30%
Cancer-related molecular mechanisms research
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.