Three dominant clusters of the 1446 differentially expressed transcripts are associated with distinct biological pathways.

<p>Each of the three dominant clusters of transcripts is associated with different study groups in the Training Set. The top transcript cluster is over-abundant in the pneumonia and cancer patients and significantly associated with IPA pathways relating to inflammation (Fisher’s exact with Benjamini Hochberg FDR = 0.05). The middle transcript cluster is over-abundant in the TB and sarcoidosis patients and significantly associated with IFN signalling and other immune response IPA pathways (Fisher’s exact with Benjamini Hochberg FDR = 0.05). The bottom transcript cluster is under-abundant in all the patients and significantly associated with T and B cell IPA pathways (Fisher’s exact Benjamini Hochberg FDR = 0.05).</p

Modular analysis shows similar pathways associated with TB and sarcoidosis, differing from pneumonia and cancer.

<p>(A) Gene expression levels of all transcripts that were significantly detected compared to background hybridisation (15212 transcripts, <i>p</i><0.01) were compared in the Training Set between each patient group: TB, active sarcoidosis, non-active sarcoidosis, pneumonia, lung cancer, to the healthy controls. Each module corresponds to a set of co-regulated genes that were assigned biological functions by unbiased literature profiling. A red dot indicates significant over-abundance of transcripts and a blue dot indicates significant under-abundance (p<0.05). The colour intensity correlates with the percentage of genes in that module that are significantly differentially expressed. The modular analysis can also be represented in graphical form as shown in (B)–(E), including both the Training and Test Set samples. The mean, SEM and <i>p-</i>values are displayed (ANOVA with Tukey’s multiple comparison test). (B) The percentage of genes significantly overexpressed in the 3 IFN modules for each disease. (C) The fold change of the expression of the genes present in the IFN modules compared to the controls. (D) The percentage of genes significantly overexpressed in the 5 inflammation modules for each disease. (E) The fold change of the expression of the genes present in the inflammation modules compared to the controls.</p

Class prediction of 100 Agilent transcripts from the Maertzdorf et al study.

<p>Class prediction was performed using support vector machines (SVM). The 100 Agilent transcripts from the Maertzdorf <i>et al</i> study translated to 76 recognised genes using the DAVID gene converter. The SVM model was built in the Training Set and run in the Test and Validation Sets.</p

Class prediction of 50 genes from the Koth et al study.

<p>Class prediction was performed using support vector machines (SVM). The 50 genes from the Koth <i>et al</i> study were used to build the last SVM model in the Training Set and run in the Test and Validation Sets.</p

Summary of participant numbers in each cohort.

<p>Summary of participant numbers in each cohort.</p

Pulmonary granulomatous diseases display similar transcriptional signatures that are distinct from pneumonia and lung cancer.

<p>1446-transcripts were differentially expressed in the whole blood of the Training Set healthy controls, pulmonary TB patients, pulmonary sarcoidosis patients, pneumonia patients and lung cancer patients. The clustering of the 1446-transcripts were tested in an independent cohort from which they were not derived from, the Test Set. The heatmap shows the transcripts and Test Set patients’ profiles as organised by the unbiased algorithm of unsupervised hierarchical clustering. A dotted line is added to the heatmap to help visualisation of the main clusters generated by the clustering algorithm. Transcript intensity values are normalised to the median of all transcripts. Red transcripts are relatively over-abundant and blue transcripts under-abundant. The coloured bar at the bottom of the heatmap indicates to which group the profile belongs.</p

144 transcripts.

<p>The 144 transcripts are differentially expressed genes between the TB and active sarcoidosis profiles in the Training Set (significance analysis of microarray <i>q</i><0.05, fold change ≥1.5). FC = Fold change TB versus active sarcoidosis. Exp. = Regulation of expression.</p

IFN-inducible gene expression is most abundant in the neutrophils in both TB and sarcoidosis.

<p>The expression of IFN-inducible genes were measured in purified leucocyte populations from whole blood. (A) Heatmap shows the expression of IFN-inducible transcripts, from the Berry et al 2010 study, for each disease group normalised to the controls for that cell type. (B) The mean expression fold change in the TB samples of the same IFN-inducible transcripts. (C) The mean expression fold change in the sarcoidosis samples of the same IFN-inducible transcripts. (D) The mean expression fold change in the TB samples of all the genes present in the three IFN modules compared to the controls. (E) The mean expression fold change in the sarcoidosis samples of all the genes present in the three IFN modules compared to the controls. Graphs show mean and SEM.</p