Background/Purpose:

Lupus is an autoimmune disease characterized by a type I interferon signature thought to be initiated by granulocyte NETosis. The granulocyte population in the periphery of lupus patients contains abnormal LDGs (low-density granulocytes) that are correlated with SLEDAI and anti-dsDNA antibodies. The current experiments were carried out to identify LDGs quantitatively by their genomic signature in peripheral and tissue datasets from lupus patients.

Methods:

Publicly available microarray or RNASeq gene expression profiles from lupus patients were identified in GEO, including those obtained from from neutrophils, whole blood (WB), PBMC and skin, synovium, and kidney. The raw data were downloaded, normalized, curated and assessed for differentially expressed (DE) genes. Correlation with clinical or histologic features was carried out by WGCNA and variation in pathway activity was determined in individual samples and groups of samples by Gene Set Variation Analysis (GSVA). Curated STRING-based protein-protein interaction analysis was carried out using MCODE in Cytoscape. Functional categories were defined using the BIG-C clustering algorithm.

Results:

Analysis of control or lupus neutrophil RNA expression datasets as well as lupus LDGs resulted in three WGCNA modules that are consistent across patient samples. Specifically, modules were identified that were positively correlated with LDGs but negatively correlated with lupus and normal neutrophils (or vice-versa). Two WGCNA modules were identified in the LDG to neutrophil comparison that were positively correlated (A,334 genes; B, 92 genes). “A” contains genes related to platelet activation and adhesion. “B” contains genes classic for neutrophils and granulocytes. One module was negatively correlated (C, 82 genes) and contains genes related to nuclear transport and translational machinery. The most informative module was “B”. 41/92 of “B” genes have been described to characterize neutrophils/granulocytes (M2.2)¹. 30/92 genes fall under the Neutrophil Granulation GO term and 13 of the 30 genes described by the Neutrophil Granulation GO term are contained in M2.2. An end goal of this analysis was to identify a group of genes that could be used to query whole blood, PBMC and tissue datasets for the presence of neutrophils and LDGs. WGCNA modules for whole blood and PBMC were compared to the LDG modules described above and GSVA was utilized to examine the consistency across patients. Module B containing LDG genes was found in 3/3 PBMC and 3/3 WB datasets by three measurements (gene overlap LDG module to PBMC or WB module, eigengene correlation with module “B” and eigengene correlation with clinical traits).

Assessing correlation of the log₂ fold change of DE genes in the WGCNA “B” module with the test sets (PBMCs or WB) gives an r range of 0.6-0.8 (p value < 0.05) regardless of disease activity. Genes within modules “A” and “C” were not significantly correlated. This observation was not found for lupus-affected tissues.

Conclusion:

These results indicate that a discrete LDG module can be identified in the periphery of lupus patients. However, the contribution of these cells to tissue pathology is uncertain.

« Back to 2017 ACR/ARHP Annual Meeting

ACR Meeting Abstracts - https://acrabstracts.org/abstract/a-module-of-genes-describing-low-density-granulocytes-can-be-identified-and-followed-in-the-periphery-of-lupus-patients/