MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain

BMC Musculoskeletal Disorders

Wei-Juan Ma²  Shi-Xun Wu³  Tuan-Mao Guo³  Ren-qi Jiang¹  Yin-gang Zhang³ 

[1] Department of Sports Injury, Hong-Hui Hospital, Xi’an Jiaotong University College of Medicine, Xi’an 710054, China;Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi’an Jiaotong University, Xi’an 710061, China;Department of Orthopedics, First Affiliated Hospital of Medical College of Xi’an Jiaotong University, Xi’an 710061, China

关键词: Biomarker;    Serum profiling;    MALDI-TOF-MS;    Lumbar disc herniation;    Dicogenic low back pain;    Chronic low back pain;   

Others  :  1125597
DOI  :  10.1186/1471-2474-15-193

 received in 2014-05-06, accepted in 2014-05-30,  发布年份 2014

【 摘 要 】

Background

The identification of the cause of chronic low back pain (CLBP) represents a great challenge to orthopedists due to the controversy over the diagnosis of discogenic low back pain (DLBP) and the existence of a number of cases of CLBP of unknown origin. This study aimed to develop diagnostic models to distinguish DLBP from other forms of CLBP and to identify serum biomarkers for DLBP.

Methods

Serum samples were collected from patients with DLBP, chronic lumbar disc herniation (LDH), or CLBP of unknown origin, and healthy controls (N), and randomly divided into a training set (n = 30) and a blind test set (n = 30). Matrix-assisted laser desorption ionization time-of-flight mass spectrometry was performed for protein profiling of these samples. After the discriminative ability of two most significantly differential peaks from each two groups was assessed using scatter plots, classification models were developed using differential peptide peaks to evaluate their diagnostic accuracy. The identity of peptides corresponding to three representative differential peaks was analyzed.

Results

The fewest statistically significant differential peaks were identified between DLBP and CLBP (3), followed by CLBP vs. N (5), DLBP vs. N (9), LDH vs. CLBP (20), DLBP vs. LDH (23), and LDH vs. N (43). The discriminative ability of two most significantly differential peaks was poor in classifying DLBP vs. CLBP but good in classifying DLBP vs. LDH. The accuracy of models for classification of DLBP vs. CLBP was not very high in the blind test (forecasting ability, 67.24%; sensitivity, 70%), although a higher accuracy was observed for classification of DLBP vs. LDH and LDH vs. N (forecasting abilities, ~90%; sensitivities, >90%). A further investigation of three representative differential peaks led to the identification of two peaks as peptides of complement C3, and one peak as a human fibrinogen peptide.

Conclusions

Our findings benefit not only the diagnosis of CLBP but also the understanding of the differences between different forms of DLBP. The ability to distinguish between different causes of CLBP and the identification of serum biomarkers may be of great value to diagnose different causes of DLBP and predict treatment efficacy.

【 授权许可】

   
2014 Zhang et al.; licensee BioMed Central Ltd.

【 图 表 】

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