Diabetic kidney disease: m6A modification as a marker of disease progression and subtype classification

This paper aims to investigate m6A modification during DKD progression. We evaluated m6A regulators expression in peripheral blood mononuclear cells, whole kidney tissue, glomerular, and tubulointerstitial samples. CIBERSORT and single-sample gene set enrichment analysis analyzed glomerular immune characteristics. Logistic-LASSO regression were used to develop the m6A regulators model that can identify early DKD. Consensus clustering algorithms were used to classify DKD in glomerular samples into m6A modified subtypes based on the expression of m6A regulators. Gene set variation analysis algorithm was used to evaluate the functional pathway enrichment of m6A modified subtypes. Weighted gene co-expression network analysis and protein-protein interaction networks identified m6A modified subtype marker genes. The Nephroseq V5 tool was used to evaluate the correlation between m6A modified subtypes marker genes and renal function. DKD patients' m6A regulators expression differed from the control group in various tissue types. DKD stages have various immune characteristics. The m6A regulators model with YTHDC1, METTL3, and ALKBH5 better identified early DKD. DKD was divided into two subtypes based on the expression of 26 m6A regulators. Subtype 1 was enriched in myogenesis, collagen components, and cytokine receptor interaction, while subtype 2 was enriched in protein secretion, proliferation, apoptosis, and various signaling pathways (e.g., TGFβ signaling pathway, PI3K/AKT/mTOR pathway, and etc.). Finally, AXIN1 and GOLGA4 were identified as possible biomarkers associated with glomerular filtration rate. From the viewpoint of m6A modification, the immune characteristics and molecular mechanisms of DKD at various stages are different, and targeted treatment would improve efficacy.