Identifying myoglobin as a mediator of diabetic kidney disease: a machine learning-based cross-sectional study.

In view of the alarming increase in the burden of diabetes mellitus (DM) today, a rising number of patients with diabetic kidney disease (DKD) is forecasted. Current DKD predictive models often lack reliable biomarkers and perform poorly. In this regard, serum myoglobin (Mb) identified by machine learning (ML) may become a potential DKD indicator. We aimed to elucidate the significance of serum Mb in the pathogenesis of DKD. Electronic health record data from a total of 728 hospitalized patients with DM (286 DKD vs. 442 non-DKD) were used. We developed DKD ML models incorporating serum Mb and metabolic syndrome (MetS) components (insulin resistance and ß-cell function, glucose, lipid) while using SHapley Additive exPlanation (SHAP) to interpret features. Restricted cubic spline (RCS) models were applied to evaluate the relationship between serum Mb and DKD. Serum Mb-mediated renal function impairment induced by MetS components was verified by causal mediation effect analysis. The area under the receiver operating characteristic curve of the DKD machine learning models incorporating serum Mb and MetS components reached 0.85. Feature importance analysis and SHAP showed that serum Mb and MetS components were important features. Further RCS models of DKD showed that the odds ratio was greater than 1 when serum Mb was > 80. Serum Mb showed a significant indirect effect in renal function impairment when using MetS components such as HOMA-IR, HGI and HDL-C/TC as a reason. Moderately elevated serum Mb is associated with the risk of DKD. Serum Mb may mediate MetS component-caused renal function impairment.

AKT/PACS2 Participates in Renal Vascular Hyperpermeability by Regulating Endothelial Fatty Acid Oxidation in Diabetic Mice.

Diabetes is a chronic metabolic disorder that can cause many microvascular and macrovascular complications, including diabetic nephropathy. Endothelial cells exhibit phenotypic and metabolic diversity and are affected by metabolic disorders. Whether changes in endothelial cell metabolism affect vascular endothelial function in diabetic nephropathy remains unclear. In diabetic mice, increased renal microvascular permeability and fibrosis, as well as increased MAMs and PACS2 in renal endothelial cells, were observed. Mice lacking PACS2 improved vascular leakage and glomerulosclerosis under high fat diet. In vitro, PACS2 expression, VE-cadherin internalization, fibronectin production, and Smad-2 phosphorylation increased in HUVECs treated with high glucose and palmitic acid (HGHF). Pharmacological inhibition of AKT significantly reduced HGHF-induced upregulation of PACS2 and p-Smad2 expression. Blocking fatty acid ß-oxidation (FAO) ameliorated the impaired barrier function mediated by HGHF. Further studies observed that HGHF induced decreased FAO, CPT1α expression, ATP production, and NADPH/NADP+ ratio in endothelial cells. However, these changes in fatty acid metabolism were rescued by silencing PACS2. In conclusion, PACS2 participates in renal vascular hyperpermeability and glomerulosclerosis by regulating the FAO of diabetic mice. Targeting PACS2 is potential new strategy for the treatment of diabetic nephropathy.