Additional file 2: of Microarray expression profile analysis of mRNAs and long non-coding RNAs in pulmonary tuberculosis with different traditional Chinese medicine syndromes

Sample data for TB PYD, HFYD, and DQY patients and healthy controls. (DOCX 15 kb

Additional file 1: of Microarray expression profile analysis of mRNAs and long non-coding RNAs in pulmonary tuberculosis with different traditional Chinese medicine syndromes

Clinical data for TB cases with PYD, HFYD and DQY syndromes and normal reference ranges. P values between TB cases with PYD, HFYD and DQY syndromes and the normal reference range were determined by one-sample t-test after taking the logarithm and comparison to the median. *P < 0.05. **P < 0.01. *** P < 0.001 (DOCX 17 kb

Serum amyloid A, protein Z, and C4b-binding protein β chain as new potential biomarkers for pulmonary tuberculosis

<div><p>The aim of this study was to discover novel biomarkers for pulmonary tuberculosis (TB). Differentially expressed proteins in the serum of patients with TB were screened and identified by iTRAQ-two dimensional liquid chromatography tandem mass spectrometry analysis. A total of 79 abnormal proteins were discovered in patients with TB compared with healthy controls. Of these, significant differences were observed in 47 abnormally expressed proteins between patients with TB or pneumonia and chronic obstructive pulmonary disease (COPD). Patients with TB (n = 136) exhibited significantly higher levels of serum amyloid A (SAA), vitamin K-dependent protein Z (PROZ), and C4b-binding protein β chain (C4BPB) than those in healthy controls (n = 66) (<i>P</i><0.0001 for each) albeit significantly lower levels compared with those in patients with pneumonia (n = 72) (<i>P</i><0.0001 for each) or COPD (n = 72) (<i>P</i><0.0001, <i>P</i><0.0001, <i>P</i> = 0.0016, respectively). After 6 months of treatment, the levels of SAA and PROZ were significantly increased (<i>P</i> = 0.022, <i>P</i><0.0001, respectively), whereas the level of C4BPB was significantly decreased (<i>P</i> = 0.0038) in treated TB cases (n = 72). Clinical analysis showed that there were significant differences in blood clotting and lipid indices in patients with TB compared with healthy controls, patients with pneumonia or COPD, and treated TB cases (<i>P</i><0.05). Correlation analysis revealed significant correlations between PROZ and INR (rs = 0.414, <i>P</i> = 0.044), and between C4BPB and FIB (rs = 0.617, <i>P</i> = 0.0002) in patients with TB. Receiver operating characteristic curve analysis revealed that the area under the curve value of the diagnostic model combining SAA, PROZ, and C4BPB to discriminate the TB group from the healthy control, pneumonia, COPD, and cured TB groups was 0.972, 0.928, 0.957, and 0.969, respectively. Together, these results suggested that SAA, PROZ, and C4BPB may serve as new potential biomarkers for TB. Our study may thus provide experimental data for the differential diagnosis of TB.</p></div

Correlation analysis of differentially expressed proteins and clinical coagulation indices.

<p>Correlation analysis of differentially expressed proteins and clinical coagulation indices.</p

Flowchart of the experimental design.

<p>Differentially expressed proteins were identified and quantified by applying iTRAQ-2DLC-MS/MS technology and by ELISA.</p

Serum proteins levels in the healthy controls, patients with TB, and treated TB cases.

<p>(A) SAA. (B) PROZ. (C) C4BPB. TB: pulmonary tuberculosis. <i>P</i> value <0.05 indicates statistical significance using the Mann-Whitney U test. *<i>P</i> < 0.05, **<i>P</i> < 0.01, ***<i>P</i> < 0.001.</p

Bioinformatics analysis of differentially expressed proteins.

<p>(A) Biological process (GO analysis). (B) Molecular function (GO analysis). (C) Cellular component (GO analysis). (D) KEGG analysis. (E) Functional network of differentially expressed proteins. ECM: extracellular matrix; MAPK: Mitogen-activated protein kinase; PPAR: peroxisome proliferator activated receptor.</p

Clinical data of patients with TB, healthy controls, patients with pneumonia or COPD, and treated TB cases.

<p>Clinical data of patients with TB, healthy controls, patients with pneumonia or COPD, and treated TB cases.</p

Receiver operating characteristics of SAA, PROZ, and C4BPB in distinguishing patients with TB from healthy controls, patients with pneumonia or COPD, and treated TB cases individually and as a panel.

<p>Receiver operating characteristics of SAA, PROZ, and C4BPB in distinguishing patients with TB from healthy controls, patients with pneumonia or COPD, and treated TB cases individually and as a panel.</p

Decision trees in the diagnostic model for TB generated by Biomarker Patterns Software.

<p>Serum proteins SAA, PROZ, and C4BPB were incorporated to establish a decision tree using Biomarker Patterns Software. The diagnostic model shows the sample distribution and tree structure of the set. (A) Diagnostic model for patients with TB and healthy controls. (B) Diagnostic model for patients with TB or pneumonia. (C) Diagnostic model for patients with TB or COPD. (D) Diagnostic model for patients with TB and treated TB cases.</p