Relevant Characteristics Analysis Using Natural Language Processing and Machine Learning Based on Phenotypes and T-Cell Subsets in Systemic Lupus Erythematosus Patients With Anxiety

Gu, Xianfeng; Jin, Y.; Fu, Ting; Zhang, Xiaoming; Li, Teng; Yang, Ying; Li, Rong; Zhou, Wei; Guo, Jia; Zhao, Rui; Li, Jingjing; Dong, Chen; Gu, Zhifeng

doi:10.3389/fpsyt.2021.793505

Cited by 6 publications

(3 citation statements)

References 47 publications

(54 reference statements)

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“…CD27 is a member of the TNF receptor superfamily, which is involved in regulating T cells, B cells, and immunoglobulins to mediate the inflammatory response. It has been reported that CD27 may lead to anxiety or depression in patients with systemic lupus erythematosus by regulating T cells ( Gu et al, 2021 ). As a receptor of interleukin-7 (IL-7), IL7R plays a key role in immune cell development and immune system homeostasis.…”

Section: Discussionmentioning

confidence: 99%

Identification of key genes in late-onset major depressive disorder through a co-expression network module

Yao

Sun

2022

Front. Genet.

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Late-onset major depressive disorder (LOD) increases the risk of disability and suicide in elderly patients. However, the complex pathological mechanism of LOD still remains unclear. We selected 10 LOD patients and 12 healthy control samples from the GSE76826 dataset for statistical analysis. Under the screening criteria, 811 differentially expressed genes (DEGs) were screened. We obtained a total of two most clinically significant modules through the weighted gene co-expression network analysis (WGCNA). Functional analysis of the genes in the most clinically significant modules was performed to explore the potential mechanism of LOD, followed by protein–protein interaction (PPI) analysis and hub gene identification in the core area of the PPI network. Furthermore, we identified immune infiltrating cells using the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm between healthy subjects and LOD patients with the GSE98793 dataset. Next, six hub genes (CD27, IL7R, CXCL1, CCR7, IGLL5, and CD79A) were obtained by intersecting hub genes with DEGs, followed by verifying the diagnostic accuracy with the receiver operating characteristic curve (ROC). In addition, we constructed the least absolute shrinkage and selection operator (LASSO) regression model for hub gene cross-validation. Finally, we found that CD27 and IGLL5 were good diagnostic indicators of LOD, and CD27 may be the key gene of immune function change in LOD. In conclusion, our research shows that the changes in the immune function may be an important mechanism in the development of LOD, which can provide some guidance for the related research of LOD in the future.

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Section: Discussionmentioning

confidence: 99%

Identification of key genes in late-onset major depressive disorder through a co-expression network module

Yao

Sun

2022

Front. Genet.

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“…Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease characterized by the abnormal activation of T and B lymphocytes with decreased quality of life [1,2]. SLE affects multiple organs and systems and is especially associated with neuropsychiatric problems.…”

Section: Introductionmentioning

confidence: 99%

“…2 = 0.641. Abbreviations: ASC: plasma B cell; PBMC: peripheral blood mononuclear c MAIT: mucosal-associated invariant T cell; TEMRA: effector memory CD45RA+ T cells; Th: hel T cells.…”

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confidence: 99%

SVM-Based Model Combining Patients’ Reported Outcomes and Lymphocyte Phenotypes of Depression in Systemic Lupus Erythematosus

et al. 2023

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Background: The incidence of depression in patients with systemic lupus erythematosus (SLE) is high and leads to a lower quality of life than that in undepressed SLE patients and healthy individuals. The causes of SLE depression are still unclear. Methods: A total of 94 SLE patients were involved in this study. A series of questionnaires (Hospital Depression Scale, Social Support Rate Scale and so on) were applied. Flow cytometry was used to test the different stages and types of T cells and B cells in peripheral blood mononuclear cells. Univariate and multivariate analyses were conducted to explore the key contributors to depression in SLE. Support Vector Machine (SVM) learning was applied to form the prediction model. Results: Depressed SLE patients showed lower objective support, severer fatigue, worse sleep quality and higher percentages of ASC%PBMC, ASC%CD19+, MAIT, TEM%Th, TEMRA%Th, CD45RA+CD27-Th, TEMRA%CD8 than non-depressed patients. A learning-based SVM model combining objective and patient-reported variables showed that fatigue, objective support, ASC%CD19+, TEM%Th and TEMRA%CD8 were the main contributing factors to depression in SLE. With the SVM model, the weight of TEM%Th was 0.17, which is the highest among objective variables, and the weight of fatigue was 0.137, which was the highest among variables of patients’ reported outcomes. Conclusions: Both patient-reported factors and immunological factors could be involved in the occurrence and development of depression in SLE. Scientists can explore the mechanism of depression in SLE or other psychological diseases from the above perspective.

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CD4+ T-cell subsets are associated with chronic stress effects in newly diagnosed anxiety disorders

Dai,

Li,

Cao

et al. 2024

Neurobiology of Stress

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Relevant Characteristics Analysis Using Natural Language Processing and Machine Learning Based on Phenotypes and T-Cell Subsets in Systemic Lupus Erythematosus Patients With Anxiety

Cited by 6 publications

References 47 publications

Identification of key genes in late-onset major depressive disorder through a co-expression network module

Identification of key genes in late-onset major depressive disorder through a co-expression network module

SVM-Based Model Combining Patients’ Reported Outcomes and Lymphocyte Phenotypes of Depression in Systemic Lupus Erythematosus

CD4+ T-cell subsets are associated with chronic stress effects in newly diagnosed anxiety disorders

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