Diabetic Kidney Disease Back in Focus: Management Field Guide for Health Care Professionals in the 21st Century

Gut microbiota profiling reflects the renal dysfunction and psychological distress in patients with diabetic kidney disease

Background

The gut microbiota plays a pivotal role in the development of diabetes and kidney disease. However, it is not clear how the intestinal microecological imbalance is involved in the context of diabetic kidney disease (DKD), the leading cause of renal failure.

Objectives

To elucidate the gut microbial signatures associated with DKD progression towards end-stage renal disease (ESRD) and explore whether they could reflect renal dysfunction and psychological distress.

Methods

A cross-sectional study was conducted to explore the gut microbial signatures of 29 DKD non-ESRD patients and 19 DKD ESRD patients compared to 20 healthy controls. Differential analysis was performed to detect distinct gut microbial alterations in diversities and taxon abundance of DKD with and without ESRD. Renal dysfunction was estimated by urea, creatinine, and estimated glomerular filtration rate. Psychological distress was assessed using the Self-Rating Anxiety Scale, Self-Rating Depression Scale, Hamilton Anxiety Rating Scale, and Hamilton Depression Rating Scale.

Results

Alpha diversity indexes were reduced in DKD patients, particularly those with ESRD. Beta diversity analysis revealed that the gut microbial compositions of DKD patients were different with healthy individuals whereas similar compositions were observed in DKD patients. Taxon differential analysis showed that when compared with the controls, DKD patients exhibit distinct microbial profiles including reduced abundances of butyrate-produced, anti-inflammatory bacteria Faecalibacterium, Lachnospira, Roseburia Lachnoclostridium, and increased abundances of pro-inflammatory bacteria Collinsella, Streptococcus etc. These distinctive genera presented consistent associations with renal dysfunction, as well as psychological distress, especially in DKD patients.

Conclusions

DKD patients, especially those who have progressed to ESRD, exhibit unique characteristics in their gut microbiota that are associated with both renal dysfunction and psychological distress. The gut microbiota may be a significant factor in the deterioration of DKD and its eventual progression to ESRD.

Association of different domains of physical activity with diabetic kidney disease: a population-based study

Background

The aim of this cross-sectional study was to elucidate the associations between various domains of physical activity, such as occupation-related (OPA), transportation-related (TPA), leisure-time (LTPA) and overall physical activity (PA), and diabetic kidney disease.

Methods

Our study encompassed 2,633 participants, drawn from the cross-sectional surveys of the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018, and employed survey-weighted logistic regression, generalized linear regression, and restricted cubic spline (RCS) analyses to ascertain the relationship between different domains of physical activity and diabetic kidney disease.

Results

After controlling for all confounders, multivariate logistic regression analyses revealed a lack of correlation between the various domains of physical activity and the prevalence of diabetic kidney disease. Multiple generalized linear regression analyses showed that durations of PA (β = 0.05, 95% CI, 0.01-0.09, P = 0.012) and TPA (β = 0.32, 95% CI, 0.10-0.55, P = 0.006) were positively associated with eGFR levels; and LTPA durations were inversely associated with UACR levels (β = -5.97, 95% CI, -10.50 - -1.44, P = 0.011). The RCS curves demonstrated a nonlinear relationship between PA, OPA, and eGFR, as well as a nonlinear correlation between PA and ACR. Subgroup and sensitivity analyses largely aligned with the outcomes of the multivariate generalized linear regression, underscoring the robustness of our findings.

Conclusion

Our population-based study explored the association between different domains of physical activity and diabetic kidney disease. Contrary to our expectations, we found no significant association between the duration of physical activity across all domains and the prevalence of diabetic nephropathy. Nonetheless, renal function markers, including eGFR and UACR, exhibited significant correlations with the duration of total physical activity (TPA) and leisure-time physical activity (LTPA), respectively, among diabetic patients. Interestingly, our findings suggest that diabetic patients engage in physical activity to preserve renal function, ensuring moderate exercise durations not exceeding 35 hours per week.

Unraveling DDIT4 in the VDR-mTOR pathway: a novel target for drug discovery in diabetic kidney disease

Introduction

Diabetic kidney disease (DKD) necessitates innovative therapeutic strategies. This study delves into the role of DNA damage-inducing transcription factor 4 (DDIT4) within the VDR-mTOR pathway, aiming to identify a novel target for DKD drug discovery.

Methods

Transcriptome data from the Gene Expression Omnibus Database were analyzed to assess the expression of mTOR and VDR expression in human renal tissues. Clinical samples from DKD patients and minimal change disease (MCD) controls were examined, and a DKD animal model using 20-week-old db/db mice was established. DDIT4 plasmid transfection was employed to modulate the VDR-mTOR pathway, with its components evaluated using immunohistochemistry, real-time quantitative PCR (qRT-PCR), Western blotting, and enzyme-linked immunosorbent assay (ELISA).

Results

Changes in the expression of the VDR-mTOR pathway were observed in both DKD patients and the animal model. Overexpression of DDIT4 increased VDR expression and decreased levels of mTOR, p70s6k, and 4E-BP1. Furthermore, DDIT4 treatment regulated autophagy by upregulating LC3I expression and downregulating LC3II expression. Notably, DDIT4 alleviated oxidative stress by reducing the levels of lipid peroxidation product MDA, while simultaneously increasing the levels of superoxide dismutase (SOD) and glutathione (GSH), underscoring the role of DDIT4 in the pathological process of DKD and its potential as a therapeutic target.

Conclusion

Unraveling DDIT4's involvement in the VDR-mTOR pathway provides insights for innovative DKD drug discovery, emphasizing its potential as a therapeutic target for future interventions.

Prescription of guideline-directed medical therapies in patients with diabetes and chronic kidney disease from the CURE-CKD Registry, 2019-2020

AIM

Guideline-directed medical therapy (GDMT) is designed to improve clinical outcomes. The study aim was to assess GDMT prescribing rates and prescribing-persistence predictors in patients with diabetes and chronic kidney disease (CKD) from the Center for Kidney Disease Research, Education, and Hope Registry.

MATERIALS AND METHODS

Data were obtained from adults ≥18 years old with diabetes and CKD between 1 January 2019 and 31 December 2020 (N = 39 158). Baseline and persistent (≥90 days) prescriptions for GDMT, including angiotensin converting enzyme (ACE) inhibitor/angiotensin receptor blocker (ARB), sodium-glucose cotransporter-2 (SGLT2) inhibitor and glucagon-like peptide 1 (GLP-1) receptor agonist were assessed.

RESULTS

The population age (mean ± SD) was 70 ± 14 years, and 49.6% (n = 19 415) were women. Baseline estimated glomerular filtration rate (2021 CKD-Epidemiology Collaboration creatinine equation) was 57.5 ± 23.0 ml/min/1.73 m2 and urine albumin/creatinine 57.5 mg/g (31.7-158.2; median, interquartile range). Baseline and ≥90-day persistent prescribing rates, respectively, were 70.7% and 40.4% for ACE inhibitor/ARB, 6.0% and 5.0% for SGLT2 inhibitors, and 6.8% and 6.3% for GLP-1 receptor agonist (all p < .001). Patients lacking primary commercial health insurance coverage were less likely to be prescribed an ACE inhibitor/ARB [odds ratio (OR) = 0.89; 95% confidence interval (CI) 0.84-0.95; p < .001], SGLT2 inhibitor (OR 0.72; 95% CI 0.64-0.81; p < .001) or GLP-1 receptor agonist (OR 0.89; 95% CI 0.80-0.98; p = .02). GDMT prescribing rates were lower at Providence than UCLA Health.

CONCLUSIONS

Prescribing for GDMT was suboptimal and waned quickly in patients with diabetes and CKD. Type of primary health insurance coverage and health system were associated with GDMT prescribing.

Osteopontin as a Biomarker in Chronic Kidney Disease

Osteopontin (OPN) is a ubiquitously expressed protein with a wide range of physiological functions, including roles in bone mineralization, immune regulation, and wound healing. OPN has been implicated in the pathogenesis of several forms of chronic kidney disease (CKD) where it promotes inflammation and fibrosis and regulates calcium and phosphate metabolism. OPN expression is increased in the kidneys, blood, and urine of patients with CKD, particularly in those with diabetic kidney disease and glomerulonephritis. The full-length OPN protein is cleaved by various proteases, including thrombin, matrix metalloproteinase (MMP)-3, MMP-7, cathepsin-D, and plasmin, producing N-terminal OPN (ntOPN), which may have more detrimental effects in CKD. Studies suggest that OPN may serve as a biomarker in CKD, and while more research is needed to fully evaluate and validate OPN and ntOPN as CKD biomarkers, the available evidence suggests that they are promising candidates for further investigation. Targeting OPN may be a potential treatment strategy. Several studies show that inhibition of OPN expression or activity can attenuate kidney injury and improve kidney function. In addition to its effects on kidney function, OPN has been linked to cardiovascular disease, which is a major cause of morbidity and mortality in patients with CKD.

Still finding ways to augment the existing management of acute and chronic kidney diseases with targeted gene and cell therapies: Opportunities and hurdles

The rising global incidence of acute and chronic kidney diseases has increased the demand for renal replacement therapy. This issue, compounded with the limited availability of viable kidneys for transplantation, has propelled the search for alternative strategies to address the growing health and economic burdens associated with these conditions. In the search for such alternatives, significant efforts have been devised to augment the current and primarily supportive management of renal injury with novel regenerative strategies. For example, gene- and cell-based approaches that utilize recombinant peptides/proteins, gene, cell, organoid, and RNAi technologies have shown promising outcomes primarily in experimental models. Supporting research has also been conducted to improve our understanding of the critical aspects that facilitate the development of efficient gene- and cell-based techniques that the complex structure of the kidney has traditionally limited. This manuscript is intended to communicate efforts that have driven the development of such therapies by identifying the vectors and delivery routes needed to drive exogenous transgene incorporation that may support the treatment of acute and chronic kidney diseases.

Identification and validation of immune and oxidative stress-related diagnostic markers for diabetic nephropathy by WGCNA and machine learning

Background

Diabetic nephropathy (DN) is the primary cause of end-stage renal disease, but existing therapeutics are limited. Therefore, novel molecular pathways that contribute to DN therapy and diagnostics are urgently needed.

Methods

Based on the Gene Expression Omnibus (GEO) database and Limma R package, we identified differentially expressed genes of DN and downloaded oxidative stress-related genes based on the Genecard database. Then, immune and oxidative stress-related hub genes were screened by combined WGCNA, machine learning, and protein-protein interaction (PPI) networks and validated by external validation sets. We conducted ROC analysis to assess the diagnostic efficacy of hub genes. The correlation of hub genes with clinical characteristics was analyzed by the Nephroseq v5 database. To understand the cellular clustering of hub genes in DN, we performed single nucleus RNA sequencing through the KIT database.

Results

Ultimately, we screened three hub genes, namely CD36, ITGB2, and SLC1A3, which were all up-regulated. According to ROC analysis, all three demonstrated excellent diagnostic efficacy. Correlation analysis revealed that the expression of hub genes was significantly correlated with the deterioration of renal function, and the results of single nucleus RNA sequencing showed that hub genes were mainly clustered in endothelial cells and leukocyte clusters.

Conclusion

By combining three machine learning algorithms with WGCNA analysis, this research identified three hub genes that could serve as novel targets for the diagnosis and therapy of DN.