Xueqi Wang

Dr. Xueqi Wang

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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15 April 2024 in International Immunopharmacology
Verified
Journal Article
Closed access
YLYan Li
Yan Li
XWXueqi Wang
Xueqi Wang
QZQidong Zhang
Qidong Zhang
DTDongli Tian
Dongli Tian
YBYu Bai
Yu Bai
ZDZongli Diao
Zongli Diao

1 September 2024 in Diabetes, Metabolic Syndrome and Obesity
Verified
Journal Article
Open access
PDF file
YGYiming Guan
Yiming Guan
XYXiayan Yin
Xiayan Yin
LWLiyan Wang
Liyan Wang
ZDZongli Diao
Zongli Diao
HHHongdong Huang
Hongdong Huang
XWXueqi Wang
Xueqi Wang
Background: Diabetic nephropathy (DN) is a severe complication of diabetes influenced by arginine methylation. This study aimed to elucidate the role of protein arginine methylation-related genes (PRMT-RGs) in DN and identify potential biomarkers. Methods: Differentially expressed genes in two GEO datasets (GSE30122 and GSE104954) were integrated with 9 PRMT-RGs. Candidate genes were identified using WGCNA and differential expression analysis, then screened using support vector machine-recursive feature elimination and least absolute shrinkage and selection operator. Biomarkers were defined as genes with consistent differential expression across both datasets. Regulatory networks were constructed using the miRNet and Network Analyst databases. Gene set enrichment analysis was performed to identify the signaling pathways in which the biomarkers were enriched in DN. Different immune cells in DN were identified using immune infiltration analysis. Meanwhile, drug prediction and molecular docking identified potential DN therapies. Finally, qRT-PCR and immunohistochemistry validated two biomarkers in STZ-induced DN mice and DN patients. Results: Two biomarkers (FAM98A and FAM13B) of DN were identified in this study. The molecular regulatory network revealed that FAM98A and FAM13B were co-regulated by 6 microRNAs and 1 transcription factor and were enriched in signaling pathways. Immune infiltration and correlation analyses revealed that FAM98A and FAM13B were involved in developing DN along with PRMT-RGs and immune cells. The expression levels of Fam98a and Fam13b were significantly upregulated in the kidneys of DN mice revealed by qRT-PCR analysis. The expression levels of FAM98A were significantly upregulated in the kidneys of DN patients revealed by immunohistochemistry staining. Molecular docking showed that estradiol and rotenone exerted potential therapeutic effects on DN by targeting FAM98A. Conclusion: Comprehensive bioinformatics analysis revealed that FAM98A and FAM13B were potential DN biomarkers correlated with PRMT-RGs and immune cells. This study provided useful insights for elucidating the molecular mechanisms and developing targeted therapy for DN.