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小鼠血清蛋白谱分析:鉴定凝血因子XIIIa作为肌肉萎缩症的潜在生物标志物。

Serum protein profiling in mice: identification of Factor XIIIa as a potential biomarker for muscular dystrophy.

作者信息

Alagaratnam Sharmini, Mertens Bart J A, Dalebout Johannes C, Deelder André M, van Ommen Gert-Jan B, den Dunnen Johan T, 't Hoen Peter A C

机构信息

Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.

出版信息

Proteomics. 2008 Apr;8(8):1552-63. doi: 10.1002/pmic.200700857.

Abstract

Protein profiling in blood serum by fractionation and MS analysis has been applied in mice to assess its applicability as a fast, economical alternative to current DNA and RNA analyses for diagnosis of neuromuscular disorders. Mass spectra of peptides and proteins were generated using serum from dystrophin-deficient mdx and control mice by WCX ClinProt bead fractionation, followed by MALDI-MS. Double cross-validatory linear discriminant and logistic regression data analysis methods were compared with a new Bayesian logistic regression method. These were evaluated on their ability to discriminate between healthy and dystrophic samples, and to identify the discriminatory peaks in the mass spectra. All three approaches classified the spectra with comparable misclassification rates (between 18.4 and 20.6%), with much overlap between the differential peaks identified between the methods. The differential peak pattern from the Bayesian method was sparser and easier to interpret than from the other two methods, without compromising classifying strength. One of the two main differentiating peaks at m/z 3908 was identified as an N-terminal peptide of coagulation Factor XIIIa, previously identified in human serum. This work underlines the translational aspect of serum protein profiling in mice and supports a further study with serum from patients with neuromuscular disorders.

摘要

通过分级分离和质谱分析对血清中的蛋白质进行谱分析已应用于小鼠,以评估其作为一种快速、经济的替代方法用于诊断神经肌肉疾病的适用性,可替代当前的DNA和RNA分析。使用来自肌营养不良蛋白缺陷的mdx小鼠和对照小鼠的血清,通过WCX ClinProt磁珠分级分离,然后进行基质辅助激光解吸电离质谱(MALDI-MS),生成肽和蛋白质的质谱图。将双交叉验证线性判别和逻辑回归数据分析方法与一种新的贝叶斯逻辑回归方法进行了比较。对这些方法区分健康样本和营养不良样本的能力以及识别质谱图中鉴别峰的能力进行了评估。所有三种方法对光谱的分类错误率相当(在18.4%至20.6%之间),不同方法识别出的差异峰之间有很大重叠。与其他两种方法相比,贝叶斯方法的差异峰模式更稀疏且更易于解释,同时不影响分类强度。质荷比(m/z)为3908的两个主要区分峰之一被鉴定为凝血因子XIIIa的N端肽,此前已在人血清中鉴定出该肽。这项工作强调了小鼠血清蛋白质谱分析的转化意义,并支持对神经肌肉疾病患者的血清进行进一步研究。

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