Figures and data
Baseline characteristics of TBM, PTB, and healthy controls
Association between baseline clinical characteristics with TBM mortality
Objectives and cohorts flow
TBM: TB meningitis, HIV: human immunodeficiency virus, PTB: pulmonary TB, HC; healthy controls
Blood transcriptomic profiles of four cohorts: healthy controls (n=30), PTB (n=295), HIV-negative TBM (n=207) and HIV-positive TBM (n=74)
(A) Principle component analysis (PCA) of whole transcriptomic profile of HC, PTB PTB and TBM with and without HIV. Each symbol represents one individual with color coding differents. The x-axis represents principle component (PC) 1, while y-axis represents PC2. (B-G) Enrichment scores of known innate immunity pathways associated with TBM pathogenesis. st of these pathway were depicted in additional file 1, table S5. Pathway enrichment scores were calculated using single sample GSEA algorithm (ssGSEA) (Barbie DA, et al 2009). ot represents one participant. The box presents median, 25th to 75th percentile and the whiskers present the minimum to the maximum points in the data.
Blood transcriptomic profiles of three-month mortality at baseline in all TBM and TBM stratified by HIV status
Volcano plot showed differential expression (DE) genes by fold change (FC) between death and survival in all TBM (A), HIV-negative (B) and HIV-positive TBM (C). Each dot represents one gene. The x-axis represents log2 FC. The y-axis showed –log10 FDR of genes. DE genes were colored with red indicating up-regulated, blue indicating down-regulated genes which having fold discovery rate (FDR) <0.05 and absolute FC > 1.5.
Blood transcriptional modules associated with mortality in TBM
(A) Associations between WGCNA modules with two clinical phenotypes TBM disease severity (MRC grade) and three-month mortality in discovery and validation cohorts, and their sociated biological processes. The heatmap showed the association between principle component 1 (PC1) of each module and the phenotypes, particularly Spearman correlation r for RC grade and hazard ratio per increase 1/10 unit of PC1 (HR) for mortality. The HRs were estimated using a Cox regression model adjusted for age, HIV status and dexamethasone eatment. False discovery rate (FDR) corrected based on Benjamini & Yekutieli procedure, with significant level denoted as * < .05, ** < .01 and *** <.001. Gradient colors were used to the cell with green indicating negative r or HR < 1, red color indicating positive r or HR > 1. The order of modules was based on hierarchical clustering using Pearson correlation stance for module eigengene. On the left, biological processes, corresponding to modules, were identified using Gene Ontology and KEGG database. (B) Validation of the association tween WGCNA modules and mortality in discovery and validation cohorts. X-axis represents –log10 FDR in discovery cohort and Y-axis represents –log10 FDR in validation cohort. Red sh lines indicate FDR = 0.05 as the threshold for statistically significant in both cohorts. Five modules (blue, brown, red, black and cyan) with FDR < 0.05 were validated.
Biological processes, pathways and hub genes of validated modules associated with mortality
(A-D) showed biological processes and pathways identified in four mortality associated modules: blue, brown, red and black module, by over representation analysis (ORA). Bar plots w the top representative GO biological processes or KEGG pathways. The bars indicates biological processes or pathways having ORA FDR < 0.05 and size corresponding to fold ichment calculated as the ratio of gene number of pathway in the input list divided by the ratio of gene number of the pathway in reference. (E-H) showed gene co-expression works and hub genes of blue, brown, red and black module, respectively. Each node represents one gene. Each edge represents the link between two genes. Hub genes were shown bigger nodes and bold text. The gradient color of node corresponds to its HR to mortality, with red indicating HR > 1, and blue HR < 1.
Gene expression of representative hub genes in healthy controls (n=30), PTB (n=295), HIV-negative TBM (n=207) and HIV-positive TBM (n=74)
Each dot represents gene expression from one participant. (A, B) expression of FCAR and MCEMP1 hub genes from the blue module. (C, D) expression of NELL2 and TRABD2A genes from the brown modules. (E, F) expression of PLCG1 and NLRC3 hub genes from the red module. (G, H) expression of CD247 and MATK hub genes from the black ule. The box presents median, 25th to 75th percentile and the whiskers present the minimum to the maximum points in the data. Comparisons were made between dead with survival (blue) or between HIV-negative and HIV-positive TBM by Wilcoxon rank sum test with p-values displayed as significance level above the boxes and the ontal bars (* < .05, ** < .01, *** <.001).
Relationship between known pathways associated with TBM pathogenesis and mortality
Enrichment scores of known immune pathways associated with TBM pathogenesis. Gene list of these pathway were depicted in additional file 1, table S5. Pathway enrichment scores were calculated using single sample GSEA algorithm (ssGSEA) (Barbie DA, et al 2009). Each dot represents one participant. The box presents median, 25th to 75th percentile and the whiskers present the minimum to the maximum points in the data. The comparisons were made between survival and death using Wilcoxon rank sum test. Only significant results are presented with * < .05, ** < .01, *** <.001.
Consensus transcriptional modules associated with TBM mortality stratified by HIV-infection
A) Associations between 16 consensus WGCNA modules with two clinical phenotypes TBM severity (MRC grade) and mortality in HIV-negative (n=207) and HIV-positive (n=74) TBM participants, and their associated BP Gene ontology or KEEG database. The heatmap showed the association between modules and the phenotypes, with Spearman correlation r for MRC grade and hazard ratio per increase 1 unit of PC1 of module (HR) for mortality in HIV-positive and HIV-negative cohorts. The consensus sub-panel presented associations of the consensus modules and clinical phenotypes with same trend detected in both HIV cohorts, otherwise were annotated with missing (NA) values. False discovery ate (FDR) corrected using Benjamini & Yekutieli procedure, with significant level denoted as * < .05, ** < .01 and *** <.001. Gradient colors were used to fill the cell with green ndicating negative r or HR < 1, red color indicating positive r or HR > 1. The order of modules was based on hierarchical clustering using Pearson correlation distance for module eigengene. It is noted that these consensus modules were not identical to the identified modules in the primary analysis in Figure 1. (B-C) Functional enrichment analysis of HIV-positive pathway (blue module) and HIV-negative pathway (yellow module), respectively. (D-E) Gene co-expression network of blue and yellow modules. Each node represents one gene. Each edge represents the link between two genes. Hub genes were shown by bigger nodes with bold text. The gradient color of node corresponds to its HR to mortality, with red indicating HR>1, and blue HR<1.
Enrichment score of immunity pathways in healthy controls (n=30), PTB (n=295), HIV-negative TBM (n=207) and HIV-positive TBM (n=74)
Pathway enrichment scores were calculated using single sample GSEA algorithm (ssGSEA) (Barbie DA, et al 2009). Each dot represents one participant. (A-C) showed box-plots cting enrichment scores of the innate immunity pathways from the blue module. (E-H) enrichment scores of the adaptive immunity pathways from the red and brown ules. (D) normalized expression of TNF. Gene list of these pathway were depicted in additional file 1, table S5. The box presents median, 25th to 75th percentile and the kers present the minimum to the maximum points in the data. Comparisons were made between dead (red) with survival (blue) or between HIV-negative and HIV-positive by Wilcoxon rank sum test with p-values displayed as significance level above the boxes and the horizontal bars, respectively (* < .05, ** < .01, *** <.001).
