AUTHOR=Xin Peicheng , Li Ming , Dong Jing , Zhu Hongbo , Li Jie 

TITLE=Bioinformatics gene analysis of potential biomarkers and therapeutic targets of osteoarthritis associated myelodysplastic syndrome

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1040438

DOI=10.3389/fgene.2022.1040438

ISSN=1664-8021

ABSTRACT=Objective: Osteoarthritis (OA) and myelodysplastic syndrome (MDS) are diseases caused by the same immune disorder with unclear etiology and many similarities in clinical manifestations; however, the specific mechanisms between OA and MDS are unclear.
Methods: The expression profile microarrays of OA and MDS were searched in the GEO database, the intersection of their differential genes was taken, Venn diagrams were constructed to find common pathogenic genes, bioinformatics analysis signaling pathway analysis was performed on the obtained genes, and PPI networks were constructed to find hub genes in order to establish diagnostic models for each disease and explore the immune infiltration of hub genes.
Results: 52 co-pathogenic genes were screened for association with immune regulation, immune response, and inflammation. The mean area under the receiver operating characteristic (ROC) for all 10 genes used for co-causal diagnosis ranged from 0.71-0.81. Immune cell infiltration analysis in the MDS subgroup showed that the relative numbers of Macrophages M1, B cells memory, and T cells CD4 memory resting in the MDS group were significantly different from the normal group, however, in the OA subgroup the relative numbers of Mast cells resting in the OA subgroup was significantly different from the normal group.
Conclusion: There are common pathogenic genes in OA and MDS, which in turn mediate differential alterations in related signaling pathways and immune cells, affecting the high prevalence of OA and MDS and the two disease phenomena.