Risk Factors for Albuminuria in Normotensive Older Adults with Type 2 Diabetes Mellitus and Normal Renal Function: A Cross-Sectional Study

Serum JKAP reflects Th2 and Th17 cell levels, and diabetic nephropathy risk and severity in diabetes mellitus patients

Objective: This study aimed to explore the potency of serum JKAP for estimating diabetic nephropathy risk in diabetes mellitus (DM) patients. Methods: Serum JKAP was detected in 212 DM patients. According to urinary albumin-to-creatinine ratio, DM patients were divided into normoalbuminuria, microalbuminuria and macroalbuminuria groups. Results: JKAP declined in the macroalbuminuria group versus normoalbuminuria group (p < 0.001). In DM patients, JKAP inversely correlated with Th17 cells (p < 0.001) but positively related to Th2 cells (p = 0.003). After adjustment, JKAP independently estimated lower risks of albuminuria (microalbuminuria + macroalbuminuria; odds ratio = 0.966, p < 0.001) and macroalbuminuria (odds ratio = 0.948; p = 0.002). Conclusion: Serum JKAP reflects increased Th2 cells, decreased Th17 cells, and lower diabetic nephropathy risk and severity in DM patients.

High levels of serum C-peptide are associated with a decreased risk for incident renal progression in patients with type 2 diabetes: a retrospective cohort study

INTRODUCTION

C-peptide has been reported to provide renoprotective effects. This study aims to explore the relationship between C-peptide and progression of renal function in patients with type 2 diabetes mellitus (T2DM).

RESEARCH DESIGN AND METHODS

We retrospectively collected clinical data from 854 T2DM patients over a median follow-up of 5 years. Renal events included an annual decline in estimated glomerular filtration rate (eGFR), a rapid kidney function decline and a renal composite endpoint. A linear mixed-effects model and Cox regression analysis were used to investigate the effect of C-peptide on renal events, and a subgroup analysis was performed after stratification by risk factors.

RESULTS

The highest-level C-peptide group had a smaller annual eGFR decline compared with those in the group with the lowest level (p<0.05). Higher levels of 2 h postprandial C-peptide (2hPCP) (adjusted HR 0.53; 95% CI 0.31 to 0.92), difference between 2 h postprandial and fasting C-peptide (ΔCP) (adjusted HR 0.39; 95% CI 0.22 to 0.69), and 2 h postprandial C-peptide-to-glucose ratio (PCGR) (adjusted HR 0.44; 95% CI 0.24 to 0.82) were independently related to a decreased risk for the renal composite endpoint. 2hPCP <2.92 ng/mL, ΔCP <1.86 ng/mL, and PCGR <1.11 significantly increased the risk of progression in kidney function (adjusted HRs <0.50, p<0.05) among T2DM patients with male sex, an age of <65 years old, a disease course of <10 years, an glycosylated hemoglobin value of ≥7%, or a history of hypertension.

CONCLUSIONS

Higher levels of 2hPCP, ΔCP and PCGR could protect T2DM patients from renal progression, especially in the aforementioned population with diabetes.

Integrative analyses of biomarkers and pathways for diabetic nephropathy

Background: Diabetic nephropathy (DN) is a widespread diabetic complication and a major cause of terminal kidney disease. There is no doubt that DN is a chronic disease that imposes substantial health and economic burdens on the world's populations. By now, several important and exciting advances have been made in research on etiopathogenesis. Therefore, the genetic mechanisms underlying these effects remain unknown. Methods: The GSE30122, GSE30528, and GSE30529 microarray datasets were downloaded from the Gene Expression Omnibus database (GEO). Analyses of differentially expressed genes (DEGs), enrichment of gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed. Protein-protein interaction (PPI) network construction was completed by the STRING database. Hub genes were identified by Cytoscape software, and common hub genes were identified by taking intersection sets. The diagnostic value of common hub genes was then predicted in the GSE30529 and GSE30528 datasets. Further analysis was carried out on the modules to identify transcription factors and miRNA networks. As well, a comparative toxicogenomics database was used to assess interactions between potential key genes and diseases associated upstream of DN. Results: Samples from 19 DNs and 50 normal controls were identified in the GSE30122 dataset. 86 upregulated genes and 34 downregulated genes (a total of 120 DEGs). GO analysis showed significant enrichment in humoral immune response, protein activation cascade, complement activation, extracellular matrix, glycosaminoglycan binding, and antigen binding. KEGG analysis showed significant enrichment in complement and coagulation cascades, phagosomes, the Rap1 signaling pathway, the PI3K-Akt signaling pathway, and infection. GSEA was mainly enriched in the TYROBP causal network, the inflammatory response pathway, chemokine receptor binding, the interferon signaling pathway, ECM receptor interaction, and the integrin 1 pathway. Meanwhile, mRNA-miRNA and mRNA-TF networks were constructed for common hub genes. Nine pivotal genes were identified by taking the intersection. After validating the expression differences and diagnostic values of the GSE30528 and GSE30529 datasets, eight pivotal genes (TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8) were finally identified as having diagnostic values. Conclusion: Pathway enrichment analysis scores provide insight into the genetic phenotype and may propose molecular mechanisms of DN. The target genes TYROBP, ITGB2, CD53, IL10RA, LAPTM5, CD48, C1QA, and IRF8 are promising new targets for DN. SPI1, HIF1A, STAT1, KLF5, RUNX1, MBD1, SP1, and WT1 may be involved in the regulatory mechanisms of DN development. Our study may provide a potential biomarker or therapeutic locus for the study of DN.

Newly established LC-MS/MS method for measurement of plasma BH4 as a predictive biomarker for kidney injury in diabetes

OBJECTIVE

The clinical research on BH4 is limited because of the difficulties on its measurement. In this study, we used our own established LC-MS/MS method to examine the plasma BH4 levels in diabetes to determine whether it could be used as a biomarker for the prediction of kidney injury in those patients.

METHODS

Hospitalized diabetes patients in Renmin Hospital of Wuhan University from Jan to Aug 2021 were recruited. To assess the association between plasma BH4 with ACR or eGFR in diabetes, a total of 142 patients with type 2 diabetes (T2DM) were enrolled. They were divided into three groups by albuminuria levels: normoalbuminuria (n = 68), microalbuminuria (n = 48), and macroalbuminuria (n = 26) according to ACR; or into two groups by eGFR: eGFR≥90 or eGFR<90 ml/min for correlation and logistic regression analysis. Plasma BH4 level was measured by LC-MS/MS along with other biochemical indices.

RESULTS

Plasma BH4 concentrations were decreased as ACR progressed. BH4 (r = -0.55, P < 0.001) and 2h C-Peptide (CP-2h) (r = -0.248, P = 0.003) levels were negatively correlated with ACR. Moreover, multivariable logistic regression analysis showed BH4 concentrations (B = -0.468, P < 0.001) and CP-2h (B = -0.257, P = 0.028) were independently associated with ACR progression. ROC curve showed that BH4 level has a predictive value on ACR (95%CI 0.686-0.841, sensitivity 69.1%, specificity 73%). Moreover, in diabetes patients with eGFR≥90 ml/min, plasma BH4 level (P = 0.008) is higher than those in diabetes with eGFR<90 ml/min and BH4 was remained independently associated with eGFR after multivariable logistic regression analysis (B = -0.193, P = 0.048).

CONCLUSION

Our established LC-MS/MS method could be used on human plasma BH4 measurements and our data suggested that BH4 level can be used as a biomarker for kidney injury in diabetes indicated by its association with ACR progression and early renal function decline.