Fig 1.
A. Schematic of sample processing for library preparation of whole blood for AIH cohort. B. Heat map displaying gene counts (variance stabilizing transformation, see DESeq2) of the top 1000 genes with highest variance amongst samples. Samples are clustered on the x-axis and protein coding genes are clustered on the y-axis using a Ward D2 method. Relevant metadata included patient status, steroid exposure, and fibrosis groups to classify samples. C. PCA plot of variance stabilizing transformed gene counts colored by sex of patient sample. D. Volcano plot of differential gene expression in DESeq2, showing genes with P < 0.05 and log fold change > 1 in red, and genes with only log fold change > 1 in blue, and genes with only P < 0.05 in grey.
Table 1.
Clinical cohort of AIH patients and healthy controls.
Table 2.
Random forest results with increasing standard deviation multiplicative factor separating AIH patients and healthy controls.
Fig 2.
A. Top ten most significant canonical pathways related to differential gene expression of AIH patients compared to healthy controls. B. kmer-based phylogenetic analysis performed with the IDSeq platform shows relationships between four assembled pegivirus genomes from the GRACE cohort and their closest related publicly available pegivirus NCBI reference genomes, with patient metadata annotated.
Table 3.
A. Top 10 activated upstream regulators identified by pathway analysis for treatment-naïve patients compared to healthy controls.
B. Top 10 inhibited upstream regulators identified by pathway analysis for treatment-naïve patients compared to healthy volunteers.
Fig 3.
A. WGCNA module trait graph, with patient metadata on the x-axis and generated gene modules on the y-axis. B. Interconnectivity plot for gene module 9 identified by WGCNA. C. Heatmap displaying gene counts (variance stabilizing transformation, see DESeq2) of the top 12 hub genes identified from interconnectivity metrics as described in Methods. Samples are clustered on the x-axis using a Ward D2 method and color annotated with cirrhosis status and treatment at sample collection.
Fig 4.
A. CIBERSORT data deconvoluting absolute CD8+ T-cell counts from bulk RNA-seq, with significant differences in counts between healthy patients and those with a partial response to treatment and between those with a complete compared to a partial response to treatment. B. CIBERSORT data deconvoluting absolute CD8+ T-cell counts from bulk RNA-seq, removing steroid patients and showing a significant difference between those with a complete compared to a partial response to treatment.