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Classification of Traditional Chinese Medicine Syndromes in Patients with Chronic Hepatitis B by SELDI-Based ProteinChip Analysis.

Song YN, Zhang H, Guan Y, Peng JH, Lu YY, Hu YY, Su SB - Evid Based Complement Alternat Med (2012)

Bottom Line: Based on SELDI ProteinChip data, healthy controls and CHB patients or excess and deficiency syndromes in CHB patients were obviously differentiated by orthogonal partial least square (OPLS) analysis.Moreover, the area under the receiver operating characteristic (ROC) curve was 0.887 for classifying excess and nonexcess syndrome, and 0.700 for classifying deficiency and nondeficiency syndrome, respectively.Therefore, the present study provided the possibility of TCM syndrome classification in CHB patients using a universally acceptable scientific approach.

View Article: PubMed Central - PubMed

Affiliation: Research Center for Traditional Chinese Medicine Complexity System, Shanghai University of Traditional Chinese Medicine,1200 Cailun Road, Pudong, Shanghai 201203, China.

ABSTRACT
Traditional Chinese medicine (TCM) syndrome, also called ZHENG, is the basis concept of TCM theory. It plays an important role in TCM practice. There are excess and deficiency syndromes in TCM syndrome. They are the common syndromes in chronic hepatitis B (CHB) patients. Here we aim to explore serum protein profiles and potential biomarkers for classification of TCM syndromes in CHB patients. 24 healthy controls and two cohorts of CHB patients of excess syndrome (n = 25) or deficiency syndrome (n = 19) were involved in this study. Protein profiles were obtained by surface-enhanced laser desorption ionization time-flight mass spectrometry (SELDI-TOF/MS) and multiple analyses were performed. Based on SELDI ProteinChip data, healthy controls and CHB patients or excess and deficiency syndromes in CHB patients were obviously differentiated by orthogonal partial least square (OPLS) analysis. Two significant serum proteins (m/z 4187 and m/z 5032) for classifying excess and deficiency syndromes were found. Moreover, the area under the receiver operating characteristic (ROC) curve was 0.887 for classifying excess and nonexcess syndrome, and 0.700 for classifying deficiency and nondeficiency syndrome, respectively. Therefore, the present study provided the possibility of TCM syndrome classification in CHB patients using a universally acceptable scientific approach.

No MeSH data available.


Related in: MedlinePlus

ROC curve for classification of two different TCM syndromes in CHB patients. It was generated combining the peak values of m/z 4187 and m/z 5032. (a) ROC curve for classification of excess syndrome and non-excess syndrome. AUC (area under the curve) = 0.887. (b) ROC curve for classification of deficiency syndrome and nondeficiency syndrome. AUC = 0.700.
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fig5: ROC curve for classification of two different TCM syndromes in CHB patients. It was generated combining the peak values of m/z 4187 and m/z 5032. (a) ROC curve for classification of excess syndrome and non-excess syndrome. AUC (area under the curve) = 0.887. (b) ROC curve for classification of deficiency syndrome and nondeficiency syndrome. AUC = 0.700.

Mentions: To determine the sensitivity and specificity of serum protein potential biomarkers and the usefulness of protein peak quantifications as classification of different TCM syndromes, ROC analysis was conducted. To increase the performance of the classification, the most efficient peak combination was determined using regression analysis. Control group and deficiency syndrome group were put together and defined as the nonexcess syndrome group, so ROC analysis was carried out for discriminating excess syndrome with nonexcess syndrome. The area under the ROC curve for the combination of m/z 4187 and m/z 5032 was 0.887 (Figure 5(a)). In the same way, Control group and excess syndrome group were put together and defined as the nondeficiency syndrome group, and then ROC analysis was performed to discriminate excess syndrome with nonexcess syndrome. The area under the ROC curve was 0.700 (Figure 5(b)). It was suggested that the quantification of these variables by SELDI-TOF/MS was useful to classify excess and deficiency syndromes (Figure 5).


Classification of Traditional Chinese Medicine Syndromes in Patients with Chronic Hepatitis B by SELDI-Based ProteinChip Analysis.

Song YN, Zhang H, Guan Y, Peng JH, Lu YY, Hu YY, Su SB - Evid Based Complement Alternat Med (2012)

ROC curve for classification of two different TCM syndromes in CHB patients. It was generated combining the peak values of m/z 4187 and m/z 5032. (a) ROC curve for classification of excess syndrome and non-excess syndrome. AUC (area under the curve) = 0.887. (b) ROC curve for classification of deficiency syndrome and nondeficiency syndrome. AUC = 0.700.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369440&req=5

fig5: ROC curve for classification of two different TCM syndromes in CHB patients. It was generated combining the peak values of m/z 4187 and m/z 5032. (a) ROC curve for classification of excess syndrome and non-excess syndrome. AUC (area under the curve) = 0.887. (b) ROC curve for classification of deficiency syndrome and nondeficiency syndrome. AUC = 0.700.
Mentions: To determine the sensitivity and specificity of serum protein potential biomarkers and the usefulness of protein peak quantifications as classification of different TCM syndromes, ROC analysis was conducted. To increase the performance of the classification, the most efficient peak combination was determined using regression analysis. Control group and deficiency syndrome group were put together and defined as the nonexcess syndrome group, so ROC analysis was carried out for discriminating excess syndrome with nonexcess syndrome. The area under the ROC curve for the combination of m/z 4187 and m/z 5032 was 0.887 (Figure 5(a)). In the same way, Control group and excess syndrome group were put together and defined as the nondeficiency syndrome group, and then ROC analysis was performed to discriminate excess syndrome with nonexcess syndrome. The area under the ROC curve was 0.700 (Figure 5(b)). It was suggested that the quantification of these variables by SELDI-TOF/MS was useful to classify excess and deficiency syndromes (Figure 5).

Bottom Line: Based on SELDI ProteinChip data, healthy controls and CHB patients or excess and deficiency syndromes in CHB patients were obviously differentiated by orthogonal partial least square (OPLS) analysis.Moreover, the area under the receiver operating characteristic (ROC) curve was 0.887 for classifying excess and nonexcess syndrome, and 0.700 for classifying deficiency and nondeficiency syndrome, respectively.Therefore, the present study provided the possibility of TCM syndrome classification in CHB patients using a universally acceptable scientific approach.

View Article: PubMed Central - PubMed

Affiliation: Research Center for Traditional Chinese Medicine Complexity System, Shanghai University of Traditional Chinese Medicine,1200 Cailun Road, Pudong, Shanghai 201203, China.

ABSTRACT
Traditional Chinese medicine (TCM) syndrome, also called ZHENG, is the basis concept of TCM theory. It plays an important role in TCM practice. There are excess and deficiency syndromes in TCM syndrome. They are the common syndromes in chronic hepatitis B (CHB) patients. Here we aim to explore serum protein profiles and potential biomarkers for classification of TCM syndromes in CHB patients. 24 healthy controls and two cohorts of CHB patients of excess syndrome (n = 25) or deficiency syndrome (n = 19) were involved in this study. Protein profiles were obtained by surface-enhanced laser desorption ionization time-flight mass spectrometry (SELDI-TOF/MS) and multiple analyses were performed. Based on SELDI ProteinChip data, healthy controls and CHB patients or excess and deficiency syndromes in CHB patients were obviously differentiated by orthogonal partial least square (OPLS) analysis. Two significant serum proteins (m/z 4187 and m/z 5032) for classifying excess and deficiency syndromes were found. Moreover, the area under the receiver operating characteristic (ROC) curve was 0.887 for classifying excess and nonexcess syndrome, and 0.700 for classifying deficiency and nondeficiency syndrome, respectively. Therefore, the present study provided the possibility of TCM syndrome classification in CHB patients using a universally acceptable scientific approach.

No MeSH data available.


Related in: MedlinePlus