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通过生物信息学和免疫组织化学确定IFI44作为狼疮性肾炎的关键生物标志物。

Determining IFI44 as a key lupus nephritis's biomarker through bioinformatics and immunohistochemistry.

作者信息

Tan Yue, Wang Xueyao, Zhang Deyou, Wang Jiahui, Wang Shuxian, Yu Jinyu, Wu Hao

机构信息

Department of Nephrology, The First Hospital of Jilin University, Changchun, China.

Department of Critical Care Medicine, The First Hospital of Jilin University, Changchun, China.

出版信息

Ren Fail. 2025 Dec;47(1):2479575. doi: 10.1080/0886022X.2025.2479575. Epub 2025 Mar 18.

Abstract

BACKGROUND

Lupus nephritis (LN) emerges as a severe complication of systemic lupus erythematosus (SLE), significantly affecting patient survival. Despite improvements in treatment reducing LN's morbidity and mortality, existing therapies remain suboptimal, emphasizing the necessity for early detection to improve patient outcomes.

METHODS

This study employs bioinformatics and machine learning to identify and validate potential LN biomarkers using immunohistochemistry (IHC). It explores the relationship between these biomarkers and the clinical and pathological characteristics of LN, assessing their prognostic significance. The research provides deeper mechanistic insights by employing Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, the study characterizes the immune profiles of LN patients through the CIBERSORT algorithm, focusing on the role of interferon-inducible protein 44 (IFI44) as a key biomarker.

RESULTS

IFI44 shows elevated expression in LN-affected kidneys, compared to healthy controls. The levels of IFI44 positively correlate with serum creatinine and the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and inversely with serum complement C3 and initial estimated glomerular filtration rate (eGFR).

CONCLUSION

IFI44 is identified as a promising biomarker for LN, offering potential to refine the assessment of disease progression and predict clinical outcomes. This facilitates the development of more personalized treatment strategies for LN patients.

摘要

背景

狼疮性肾炎(LN)是系统性红斑狼疮(SLE)的一种严重并发症,显著影响患者的生存率。尽管治疗方法的改进降低了LN的发病率和死亡率,但现有疗法仍不尽人意,这凸显了早期检测以改善患者预后的必要性。

方法

本研究采用生物信息学和机器学习方法,通过免疫组织化学(IHC)识别和验证潜在的LN生物标志物。它探讨了这些生物标志物与LN临床和病理特征之间的关系,评估它们的预后意义。该研究通过基因集富集分析(GSEA)、基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析提供了更深入的机制见解。此外,该研究通过CIBERSORT算法对LN患者的免疫谱进行了表征,重点关注干扰素诱导蛋白44(IFI44)作为关键生物标志物的作用。

结果

与健康对照相比,IFI44在受LN影响的肾脏中表达升高。IFI44水平与血清肌酐和系统性红斑狼疮疾病活动指数(SLEDAI)呈正相关,与血清补体C3和初始估计肾小球滤过率(eGFR)呈负相关。

结论

IFI44被确定为LN的一个有前景的生物标志物,有望改善疾病进展评估并预测临床结果。这有助于为LN患者制定更个性化的治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ea8/11921169/7b65ed0a82af/IRNF_A_2479575_F0001_C.jpg

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