Gene expression profiling in PBMCs for acute rejection in lung transplant recipients reveals myeloid responses

Abstract

The acute rejection (AR) diagnosis depends on transbronchial biopsy, which is semi-invasive and not easily performed. Our study used the Nanostring gene expression technology on PBMCs obtained from lung transplant recipients (LTRs) to search for biomarkers. We identified distinct differential gene profiles between patients with stable status (STA) and AR. Subsequently, we independently evaluated monocyte compositions in PBMCs using flow cytometry and assessed the levels of 7 chemokines in serum using Luminex. The 48 top differentially expressed genes (DEGs) were identified, utilizing a criterion of at least a 1.5-fold change between two groups, with a false discovery rate (FDR) p-Adj < 0.05. Of these 48 genes, the top 10 genes with the highest fold changes and significant p-values were selected for qPCR validation. CD68, ANXA1, ITGB, and IFI30 can be confirmed among the validated genes. A significantly lower percentage of CD14 + CD16- classical monocytes was observed in AR than in STA patients, which aligns with downregulated DEGs. Many of the DEGs were related to monocytes-macrophages and chemokines. Although these results still need to be confirmed in larger cohorts, they suggest that gene profiling of PBMC can help to identify markers related to AR in LTRs.

Keywords: NanoString; acute rejection; gene expression; lung transplantation; monocytes.

Figure 1

Flow chart of participants enrolled for nanostring gene expression.

Figure 2

Differential expression genes. (A) Principal Component Analysis (PCA) comparing the expression profiles of 770 genes in the AR (green dots) and STA (red dots) groups. (B) The volcano plot displays transcripts that are upregulated (green dots) and downregulated (pink dots) genes with a false discovery rate (FDR) adjusted p-value ≤0.05 and a log2 fold change >1.5 in the AR group compared to the STA group (STA used as the baseline). (C) Heatmap illustrating the 48 differential expression of genes distinguishing the AR (green) and STA (red) groups. The p-value was calculated by independent t-test between PC1 and PC2 using R software. (D) KEGG pathway descriptors. The orange column represents the numeric -log10 p-value, blue column represents the percentage of involved genes of all 48 differential expression genes. The pathways were selected by adjusted p-value <0.05 of KEGG pathways evaluated in DAVID Bioinformatics Resources system.

Figure 3

Validation of differential expressed genes. Validation of differential expression genes of CD68, ANXA1, ITGB, IFI30, LTBR, CCR1, FKBP1A, MYD88, TNFRSF1A, TNFRSF1B by quantitative PCR in the same patients set for Nanostring gene expression. Differences between the two groups were tested using the Mann–Whitney U test.

Figure 4

Analysis of chemokines in serum. An independent validation of extended Chemokines (CXCL1, CXCL6, CXCL8, CXCL10, CXCL16, CX3CL1, and CCL2) using Luminex for Comparing AR and STA Patients.

Figure 5

An independent validation of monocytes in PBMCs. Validation of CD14 + CD16− classical monocytes, CD14 + CD16 + intermediate monocytes, and CD14 + CD16− classical monocytes by flow cytometry comparing AR and STA patients.