UBE2D1 and COX7C as Potential Biomarkers of Diabetes-Related Sepsis

Abstract

Patients with diabetes are physiologically frail and more likely to suffer from infections and even life-threatening sepsis. This study aimed to identify and verify potential biomarkers of diabetes-related sepsis (DRS). Datasets GSE7014, GSE57065, and GSE95233 from the Gene Expression Omnibus were used to explore diabetes- and sepsis-related differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) and functional analyses were performed to explore potential functions and pathways associated with sepsis and diabetes. Weighted gene co-expression network analysis (WGCNA) was performed to identify diabetes- and sepsis-related modules. Functional enrichment analysis was performed to determine the characteristics and pathways of key modules. Intersecting DEGs that were also present in key modules were considered as common DEGs. Protein-protein interaction (PPI) network and key genes were analyzed to screen hub genes involved in DRS development. A mouse C57 BL/6J-DRS model and a neural network prediction model were constructed to verify the relationship between hub genes and DRS. In total, 7457 diabetes-related DEGs and 2606 sepsis-related DEGs were identified. GSEA indicated that gene datasets associated with diabetes and sepsis were mainly enriched in metabolic processes linked to inflammatory responses and reactive oxygen species, respectively. WGCNA indicated that grey60 and brown modules were diabetes- and sepsis-related key modules, respectively. Functional analysis showed that grey60 module genes were mainly enriched in cell morphogenesis, heart development, and the PI3K-Akt signaling pathway, whereas genes from the brown module were mainly enriched in organelle inner membrane, mitochondrion organization, and oxidative phosphorylation. UBE2D1, IDH1, DLD, ATP5C1, COX6C, and COX7C were identified as hub genes in the PPI network. Animal DRS and neural network prediction models indicated that the expression levels of UBE2D1 and COX7C in DRS models and samples were higher than control mice. UBE2D1 and COX7C were identified as potential biomarkers of DRS. These findings may help develop treatment strategies for DRS.

Gene expression profile and presentation of novel gene variants of <i>COX7B</i> and <i>COX7C</i> in a cohort of patients with chronic myeloid leukemia

“…This is in concordance with another study, which reported that COX7C is associated with venous thromboembolism via its ability to inhibit miR-200a-5p [26]. Moreover, a recent study presented COX7C as a biomarker for sepsis-related diabetes mellitus [27]. There is not much more reported on the relationship between COX7C and cancer pathogenesis suggesting importance of future studies to explore the implications of COX7C upregulation in CML.…”

Latent disease similarities and therapeutic repurposing possibilities uncovered by multi-modal generative topic modeling of human diseases

“…UBE2D1, a CKD candidate, is inferred as a potential biomarker for diabetes-related sepsis by a machine-learning pipeline using public databases ( Wang et al , 2022 ). Diabetes is a known risk factor for CKD ( Shahbazian and Rezaii, 2013 ), hence, further supporting the candidacy of UBE2D1 for a CKD target as deduced herein.…”

Latent disease similarities and therapeutic repurposing possibilities uncovered by multi-modal generative topic modeling of human diseases

“…UBE2D1, a CKD candidate predicted to function outside the known CKD pathways (Figure 8, Tables S31&S32), is inferred as a potential biomarker for diabetes-related sepsis by a machine-learning pipeline using public databases (Wang et al, 2022). Diabetes is a known risk factor for CKD (Shahbazian and Rezaii, 2013), hence, further supporting the candidacy of UBE2D1 for a CKD target as deduced herein.…”