AUTHOR=Jiang Wen , Wang Xiaochuan , Tao Dongxia , Zhao Xin TITLE=Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning JOURNAL=Frontiers in Immunology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2023.1183115 DOI=10.3389/fimmu.2023.1183115 ISSN=1664-3224 ABSTRACT=Introduction

Depression is the most common comorbidity of rheumatoid arthritis (RA). In particular, major depressive disorder (MDD) and rheumatoid arthritis share highly overlapping mental and physical manifestations, such as depressed mood, sleep disturbance, fatigue, pain, and worthlessness. This overlap and indistinguishability often lead to the misattribution of physical and mental symptoms of RA patients to depression, and even, the depressive symptoms of MDD patients are ignored when receiving RA treatment. This has serious consequences, since the development of objective diagnostic tools to distinguish psychiatric symptoms from similar symptoms caused by physical diseases is urgent.

Methods

Bioinformatics analysis and machine learning.

Results

The common genetic characteristics of rheumatoid arthritis and major depressive disorder are EAF1, SDCBP and RNF19B.

Discussion

We discovered a connection between RA and MDD through immune infiltration studies: monocyte infiltration. Futhermore, we explored the correlation between the expression of the 3 marker genes and immune cell infiltration using the TIMER 2.0 database. This may help to explain the potential molecular mechanism by which RA and MDD increase the morbidity of each other.