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

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 diagnost...

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Autores principales: Zhang, Yin-gang, Jiang, Ren-qi, Guo, Tuan-Mao, Wu, Shi-Xun, Ma, Wei-Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061098/
https://www.ncbi.nlm.nih.gov/pubmed/24889399
http://dx.doi.org/10.1186/1471-2474-15-193
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author Zhang, Yin-gang
Jiang, Ren-qi
Guo, Tuan-Mao
Wu, Shi-Xun
Ma, Wei-Juan
author_facet Zhang, Yin-gang
Jiang, Ren-qi
Guo, Tuan-Mao
Wu, Shi-Xun
Ma, Wei-Juan
author_sort Zhang, Yin-gang
collection PubMed
description 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.
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spelling pubmed-40610982014-06-18 MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain Zhang, Yin-gang Jiang, Ren-qi Guo, Tuan-Mao Wu, Shi-Xun Ma, Wei-Juan BMC Musculoskelet Disord Research Article 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. BioMed Central 2014-06-02 /pmc/articles/PMC4061098/ /pubmed/24889399 http://dx.doi.org/10.1186/1471-2474-15-193 Text en Copyright © 2014 Zhang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Yin-gang
Jiang, Ren-qi
Guo, Tuan-Mao
Wu, Shi-Xun
Ma, Wei-Juan
MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title_full MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title_fullStr MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title_full_unstemmed MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title_short MALDI-TOF-MS serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
title_sort maldi-tof-ms serum protein profiling for developing diagnostic models and identifying serum markers for discogenic low back pain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4061098/
https://www.ncbi.nlm.nih.gov/pubmed/24889399
http://dx.doi.org/10.1186/1471-2474-15-193
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