Abnormal Neutrophil Transcriptional Signature May Predict Newly Diagnosed Latent Autoimmune Diabetes in Adults of South China

Abstract

Objective: Latent autoimmune diabetes in adults (LADA) is an autoimmune diabetes characterized by slowly progressive of β-cell function deterioration. Our previous finding demonstrated that neutrophil numbers and migration abilities display distinct levels in different types of diabetes, including LADA, whereas its pathological alterations in the development of LADA remain unknown. We aimed to investigate the changes in transcriptional levels of peripheral neutrophils in newly diagnosed LADA.

Methods: Peripheral blood neutrophils were isolated from newly diagnosed LADA patients (n = 5) and age-and sex-matched healthy controls (n = 5). The Transcriptomic signature was determined by RNA sequencing (RNA-seq). Differentially expressed genes (DEG) were screened, followed by analyzing downstream Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Real-time polymerase chain reaction (qPCR) was applied for validation in LADA patients (n = 9) and age-and sex-matched healthy controls (n = 18), including sequencing samples.

Results: Compared with controls, 4105 DEG were screened in LADA patients, including 2661 upregulated and 1444 downregulated DEG. In GO analysis, DEG are mainly involved in leukocyte degranulation, myeloid cell differentiation, and immune response-regulating signaling. The top enriched KEGG pathways included cytokine-cytokine receptor interaction, adhesion molecule signaling, nuclear factor-κB (NF-κB) signaling and Th17 cell differentiation. Consistent with RNA-seq results, SELL, ITGA4, ITGAM, NCF4, ARHGAP3, and CLDN15 are upregulated in neutrophils by qPCR.

Conclusion: The present study results provided a profile of DEG in the newly diagnosed LADA of south China. Our study reveals an abnormality in neutrophil disposition at the transcriptional level in LADA. Several essential genes may be involved in of LADA's pathological process, which may be useful to guide prediction for LADA and further investigation into the pathogenesis for this disease.

Keywords: RNA-seq; data mining; latent autoimmune diabetes in adults; neutrophils; transcriptome; type 2 diabetes mellitus.