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Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning

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...

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Autores principales: Jiang, Wen, Wang, Xiaochuan, Tao, Dongxia, Zhao, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320004/
https://www.ncbi.nlm.nih.gov/pubmed/37415981
http://dx.doi.org/10.3389/fimmu.2023.1183115
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author Jiang, Wen
Wang, Xiaochuan
Tao, Dongxia
Zhao, Xin
author_facet Jiang, Wen
Wang, Xiaochuan
Tao, Dongxia
Zhao, Xin
author_sort Jiang, Wen
collection PubMed
description 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.
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spelling pubmed-103200042023-07-06 Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning Jiang, Wen Wang, Xiaochuan Tao, Dongxia Zhao, Xin Front Immunol Immunology 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. Frontiers Media S.A. 2023-06-21 /pmc/articles/PMC10320004/ /pubmed/37415981 http://dx.doi.org/10.3389/fimmu.2023.1183115 Text en Copyright © 2023 Jiang, Wang, Tao and Zhao https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Jiang, Wen
Wang, Xiaochuan
Tao, Dongxia
Zhao, Xin
Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title_full Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title_fullStr Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title_full_unstemmed Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title_short Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
title_sort identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10320004/
https://www.ncbi.nlm.nih.gov/pubmed/37415981
http://dx.doi.org/10.3389/fimmu.2023.1183115
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