基于血清外泌体蛋白组学筛选非创伤性股骨头坏死塌陷的潜在生物标志物

徐西林; 王刚; 康伯源; 刘博; 张铮; 姜益常

doi:10.16766/j.cnki.issn.1674-4152.003993

基于血清外泌体蛋白组学筛选非创伤性股骨头坏死塌陷的潜在生物标志物

doi: 10.16766/j.cnki.issn.1674-4152.003993

徐西林^{1, 2},
王刚³,
康伯源¹,
刘博¹,
张铮⁴,
姜益常^5, ,

1.
黑龙江中医药大学附属第三医院骨一科，黑龙江哈尔滨 150030
2.
黑龙江中医药大学附属第二医院骨科，黑龙江哈尔滨 150001
3.
黑龙江中医药大学研究生院，黑龙江哈尔滨 150040
4.
哈尔滨医科大学附属第一医院骨二科，黑龙江哈尔滨 150006
5.
黑龙江中医药大学附属第一医院骨三科，黑龙江哈尔滨 150040

基金项目:

国家自然科学基金项目 8237153419

黑龙江省重点研发计划项目 GZ20210136

黑龙江省重点研发计划项目 GA21C006

国家中医药管理局青年岐黄学者支持项目国中医药人教发〔2020〕7号

黑龙江省中医药科研项目 ZHY2023-099

详细信息

通讯作者:
姜益常，E-mail: jiangyichan2008@126.com

中图分类号: R681.8
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- 文章访问数: 7
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出版历程
- 收稿日期: 2024-11-22
- 网络出版日期: 2025-08-14

Prediction of collapse in non-traumatic osteonecrosis of the femoral head based on serum exosome proteomics

XU Xilin^{1, 2},
WANG Gang³,
KANG Boyuan¹,
LIU Bo¹,
ZHANG Zheng⁴,
JIANG Yichang^{5
, ,}

1.
Department of Orthopaedics, the Third Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang 150030, China

摘要

摘要: 目的利用生物信息学和机器学习方法，揭示非创伤性股骨头坏死(NONFH)进展中的分子机制及塌陷相关潜在标志物。方法选取黑龙江中医药大学附属第二医院2022年3月—2023年5月收治的非创伤性股骨头坏死患者20例，收集早期组(11例，ARCOⅠ期)和塌陷组(9例，ARCO Ⅲc~Ⅳ期)患者的外周血，并分离纯化外泌体。使用透射电镜、粒径分析仪和Western blotting对外泌体的表征进行鉴定；使用液相质谱分析技术(LC-MS/MS)检测血清外泌体蛋白，通过生物信息学联合SVM-RFE算法和LASSO回归模型筛选NONFH塌陷相关标志物。最后，对塌陷蛋白与免疫细胞进行相关性分析。结果 (1) 塌陷组的高密度脂蛋白胆固醇水平为(1.52±0.36)mmol/L，相较于早期组高密度脂蛋白胆固醇水平[(1.13±0.31)mmol/L]，差异有统计学意义(t=2.587, P=0.019)，而年龄、胆固醇、低密度脂蛋白胆固醇、碱性磷酸酶和甘油三酯水平差异均无统计学意义(P>0.05)；(2)SAA1、C4A和RPS8的AUC分别为0.66、0.89和0.84，具有良好的预测性能，为潜在的NONFH塌陷蛋白。(3)相关性分析提示C4A、SAA1、RPS8可能通过调节多种免疫细胞参与NONFH的发病过程。结论 C4A、SAA1、RPS8可作为NONFH塌陷发生的预测指标，并且可能通过调节多种免疫细胞参与NONFH的进展, 为未来NONFH的早期干预和临床治疗提供了新视角。
- 非创伤性股骨头坏死 /
- 外泌体 /
- 蛋白组学 /
- 生物信息学 /
- 机器学习 /
- 免疫浸润
Abstract: Objective This study aimed to elucidate the molecular mechanisms underlying the progression of non-traumatic osteonecrosis of the femoral head (NONFH) and to identify potential biomarkers associated with femoral head collapse using bioinformatics and machine learning approaches. Methods Peripheral blood samples were collected from early-stage (n=11, ARCO Ⅰ stage) and collapsed-stage (n=9, ARCO Ⅲc-Ⅳ stage) NONFH patients treated at the Second Affiliated Hospital of Heilongjiang University of Chinese Medicine between March 2022 and May 2023. Exosomes were isolated and purified from serum and characterized using transmission electron microscopy, nanoparticle tracking analysis, and Western blotting. Serum exosomal proteins were identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Biomarkers associated with NONFH collapse were screened using bioinformatics, support vector machine-recursive feature elimination (SVM-RFE) algorithm, and least absolute shrinkage and selection operator (LASSO) regression model. Correlation analysis was performed between collapse-associated proteins and immune cells. Results (1) The cholesterol level in the collapsed-stage group [(1.52±0.36) mmol/L] was significantly higher than that in the early-stage group [(1.13±0.31) mmol/L, t=2.587, P=0.019]. However, no significant differences were observed in age, total cholesterol, low-density lipoprotein cholesterol, alkaline phosphatase, or triglyceride levels (P>0.05). (2) The area under the curve (AUC) values for the candidate biomarkers SAA1, C4A, and RPS8 were 0.66, 0.89, and 0.84, respectively, demonstrating good predictive potential. (3) Correlation analysis indicated that C4A, SAA1, and RPS8 might be involved in NONFH pathogenesis by regulating various immune cells. Conclusion C4A, SAA1, and RPS8 can serve as predictive biomarkers for predicting femoral head collapse in NONFH and may contribute to disease progression through immune cell modulation. These findings provide new insights into early intervention and clinical treatment strategies for NONFH.
- Non-traumatic osteonecrosis of the femoral head /
- Exosomes /
- Proteomics /
- Bioinformatics /
- Machine learning /
- Immune infiltration

HTML全文

图 1 外泌体表征鉴定

Figure 1. Characterization and identification of exosomes

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图 2 DEPs的蛋白互作网络图

Figure 2. Protein interaction network diagram of DEPs

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图 3 C4A、SAA1、RPS8在塌陷组中的表达及诊断价值

Figure 3. Expression and diagnostic value of C4A, SAA1, and RPS8 in the collapse group

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图 4 塌陷标记物与免疫细胞相关性热图

Figure 4. Heat map of correlation between collapse markers and immune cells

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表 1 早期组和塌陷组一般临床资料比较

Table 1. Comparison of general clinical data between early group and collapsed group

组别	例数	年龄 (x±s，岁)	性别 (男/女，例)	胆固醇 (x±s，mmol/L)	低密度脂蛋白胆固醇(x±s，mmol/L)	高密度脂蛋白胆固醇(x±s，mmol/L)	碱性磷酸酶 (x±s，U/L)	甘油三酯 [M(P₂₅, P₇₅)，mmol/L]
早期组	11	53.09±8.68	10/1	4.60±1.55	2.78±1.32	1.13±0.31	76.63±16.27	1.81(0.70, 3.06)
塌陷组	9	48.44±11.34	6/3	5.17±0.76	2.93±0.59	1.52±0.36	78.22±12.07	2.80(1.28, 3.85)
统计量		1.039^a		1.074^a	0.344^a	2.587^a	0.284^a	-0.570^c
P值		0.312	0.285^b	0.300	0.736	0.019	0.780	0.569
注：^a为t值，^c为Z值，^b为采用Fisher精确检验。

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