Xiao-Yi Jia

Dr. Xiao-Yi Jia

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 September 2023 in Phytomedicine
Verified
Journal Article
Closed access
SCSimeng Chen
Simeng Chen
JWJin Wang
Jin Wang
JWJiayu Wang
Jiayu Wang
XJXiao-Yi Jia
Xiao-Yi Jia
ZXZihua Xuan
Zihua Xuan
WSWenrui Su
Wenrui Su

1 November 2014 in International Immunopharmacology
Verified
Journal Article
Closed access
XJXiao-Yi Jia
Xiao-Yi Jia
YCYan Chang
Yan Chang
XSXiao-Jing Sun
Xiao-Jing Sun
XDXing Dai
Xing Dai
WWWei Wei
Wei Wei

1 January 2014 in International Immunopharmacology
Verified
Journal Article
Closed access
XJXiao-Yi Jia
Xiao-Yi Jia
YCYan Chang
Yan Chang
XSXiao-Jing Sun
Xiao-Jing Sun
HWHua-Xun Wu
Hua-Xun Wu
CWChun Wang
Chun Wang
WWWei Wei
Wei Wei

15 June 2024 in International Immunopharmacology
Verified
Journal Article
Closed access
ZQZhifang Qin
Zhifang Qin
RTRan Tang
Ran Tang
JLJuan Liang
Juan Liang
XJXiao-Yi Jia
Xiao-Yi Jia

18 August 2022 in Frontiers in Immunology
Verified
Journal Article
Open access
XMXiang-Wen Meng
Xiang-Wen Meng
ZCZhi-Luo Cheng
Zhi-Luo Cheng
ZLZhi-Yuan Lu
Zhi-Yuan Lu
YTYa-Nan Tan
Ya-Nan Tan
XJXiao-Yi Jia
Xiao-Yi Jia
MZMin Zhang
Min Zhang
Background: Systemic lupus erythematosus (SLE) is an autoimmune disease that involves multiple organs. However, the current SLE-related biomarkers still lack sufficient sensitivity, specificity and predictive power for clinical application. Thus, it is significant to explore new immune-related biomarkers for SLE diagnosis and development.Methods: We obtained seven SLE gene expression profile microarrays (GSE121239/11907/81622/65391/100163/45291/49454) from the GEO database. First, differentially expressed genes (DEGs) were screened using GEO2R, and SLE biomarkers were screened by performing WGCNA, Random Forest, SVM-REF, correlation with SLEDAI and differential gene analysis. Receiver operating characteristic curves (ROCs) and AUC values were used to determine the clinical value. The expression level of the biomarker was verified by RT‒qPCR. Subsequently, functional enrichment analysis was utilized to identify biomarker-associated pathways. ssGSEA, CIBERSORT, xCell and ImmuCellAI algorithms were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Finally, the transcriptional regulatory network of the biomarker was constructed, and the corresponding therapeutic drugs were predicted.Results: Multiple algorithms were screened together for a unique marker gene, MX2, and expression analysis of multiple datasets revealed that MX2 was highly expressed in SLE compared to the normal group (all P < 0.05), with the same trend validated by RT‒qPCR (P = 0.026). Functional enrichment analysis identified the main pathway of MX2 promotion in SLE as the NOD-like receptor signaling pathway (NES=2.492, P < 0.001, etc.). Immuno-infiltration analysis showed that MX2 was closely associated with neutrophils, and single-cell and transcriptomic data revealed that MX2 was specifically expressed in neutrophils. The NOD-like receptor signaling pathway was also remarkably correlated with neutrophils (r >0.3, P < 0.001, etc.). Most of the MX2-related interacting proteins were associated with SLE, and potential transcription factors of MX2 and its related genes were also significantly associated with the immune response.Conclusion: Our study found that MX2 can serve as an immune-related biomarker for predicting the diagnosis and disease activity of SLE. It activates the NOD-like receptor signaling pathway and promotes neutrophil infiltration to aggravate SLE.

13 July 2022 in Inflammopharmacology
Verified
Journal Article
Closed access
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JWJin Wang
Jin Wang
SCSimeng Chen
Simeng Chen
MLMin Liu
Min Liu
MZMin Zhang
Min Zhang
XJXiao-Yi Jia
Xiao-Yi Jia