Clinical implications and guidelines for CKD in type 2 diabetes

An Investigation of the Correlation Between Retinal Nerve Fiber Layer Thickness with Blood Biochemical Indices and Cognitive Dysfunction in Patients with Type 2 Diabetes Mellitus

Objective

The study aimed to explore the correlation between retinal nerve fiber layer thickness (RNFLT) with blood biochemical indicators and cognitive dysfunction in patients with type 2 diabetes mellitus (T2DM) and the possible mechanism, thereby providing more theoretical basis for the occurrence and prevention of diabetes related complications.

Methods

Eighty T2DM patients treated in our hospital from March 2022 to September 2022 were selected as the study subjects, and the clinical data of the patients were retrospectively analyzed. All patients underwent fundus fluorescein angiography (FFA) to analyze the changes in retinal blood vessels. Patients who met the inclusion criteria were divided as the diabetic retinopathy (DR) group (n=46) and simple diabetes group (n=34). The RNFLT, blood biochemical indexes and changes in cognitive functions of the patients were detected. The correlation between RNFLT with blood biochemical indexes and cognitive dysfunction was analyzed.

Results

Compared with the simple diabetes group, patients in the DR group had much lower mean, nasal, inferior and superior thicknesses (P<0.01). There existed no significant difference in blood pressure, body mass index (BMI), blood lipids (triglycerides, cholesterol, low-density lipoprotein, high-density lipoprotein) between the two groups (P>0.05). Compared with the simple diabetes group, patients in the DR group had much higher fasting blood glucose (FBG), hemoglobin A1c (HbA1c), fasting insulin (FINS), insulin resistance (HOMA-IR) index, apolipoprotein B (ApoB)/apolipoprotein A1 (ApoA1) (P<0.001). Besides, the DR group had sharply lower scores on the Mini-Mental State Examination (MMSE) scale and higher levels of the Trail Making Test-A (TMT-A) and TMT-B (P<0.001). Spearman correlation analysis confirmed that the mean RNFLT was negatively correlated with the levels of FBG, HbA1c, HOMA-IR index, TMT-A and TMT-B (P<0.05), positively correlated with the score of mini-mental state examination (MMSE) (P<0.05), and was no significant correlation with FINS and ApoB/ApoA1 (P>0.05).

Conclusion

DR patients had significantly reduced RNFLT, elevated levels of blood glucose related indicators, and cognitive dysfunction. There existed a correlation between RNFLT and FBG, HbA1c, HOMA-IR index, TMT-A, TMT-B and MMSE.

Comprehensive analysis of cuproptosis-related ceRNA network and immune infiltration in diabetic kidney disease

Background

Diabetic kidney disease (DKD) is the primary contributor to renal failure and poses a severe threat to human health. Accumulating studies demonstrated that competing endogenous RNA (ceRNA) network is involved in cuproptosis and DKD progression. However, the role of cuproptosis-associated ceRNA network and immune infiltration in DKD remains largely unclear. This study aimed to investigate the cuproptosis-related ceRNA regulation network and immune infiltration in DKD.

Methods

The rat model of DKD was induced by combining the nephrectomy of the left kidney, high-fat diet, and streptozotocin. Differentially expressed genes (DEGs), miRNAs (DEMs), and lncRNAs (DELs) between normal and DKD rats were obtained. DEGs were intersected with cuproptosis-related genes (CRGs) to obtain DE-CRGs. LncRNAs and miRNAs were predicted based on the DE-CRGs, and they were intersected with DEMs and DELs, respectively. Subsequently, a cuproptosis-associated lncRNA-miRNA-mRNA network was established in DKD. In addition, the relative proportion of 22 infiltrating immune cell types in each sample was calculated, and the relationship between hub DE-CRGs and immune cells was explored.

Results

In total, there were 429 DEGs, 22 DEMs, and 48 DELs between CON and MOD groups. Then, 73 DE-CRGs were obtained, which were significantly enriched in 22 pathways, such as MAPK signaling pathway, IL-17 signaling pathway, and TNF signaling pathway. In addition, a core cuproptosis-related ceRNA network that included one lncRNA (USR0000B2476D), one miRNA (miR-34a-3p), and eight mRNAs (Mmp9, Pik3c3, Prom1, Snta1, Slc51b, Ntrk3, Snca, Egf) was established. In addition, 18 hub DE-CRGs were obtained. CIBERSORT algorithms showed that resting dendritic cells and resting NK cells were more infiltrated whereas regulatory T cells were less infiltrated in DKD rats than in normal rats. Spearman's correlation analysis revealed that hub DE-CRGs showed significant positive or negative correlations with naive B cells, regulatory T cells, resting NK cells, M0 macrophages, resting dendritic cells, and resting mast cells.

Conclusion

A ceRNA network was comprehensively constructed, and 18 hub DE-CRGs were obtained, which will provide novel insights into the pathologic mechanism elucidation and targeted therapy development of DKD.

Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomics

BACKGROUND

Chronic Kidney Disease (CKD) and Metabolic dysfunction-associated steatohepatitis (MASH) are metabolic fibroinflammatory diseases. Combining single-cell (scRNAseq) and spatial transcriptomics (ST) could give unprecedented molecular disease understanding at single-cell resolution. A more comprehensive analysis of the cell-specific ligand-receptor (L-R) interactions could provide pivotal information about signaling pathways in CKD and MASH. To achieve this, we created an integrative analysis framework in CKD and MASH from two available human cohorts.

RESULTS

The analytical framework identified L-R pairs involved in cellular crosstalk in CKD and MASH. Interactions between cell types identified using scRNAseq data were validated by checking the spatial co-presence using the ST data and the co-expression of the communicating targets. Multiple L-R protein pairs identified are known key players in CKD and MASH, while others are novel potential targets previously observed only in animal models.

CONCLUSION

Our study highlights the importance of integrating different modalities of transcriptomic data for a better understanding of the molecular mechanisms. The combination of single-cell resolution from scRNAseq data, combined with tissue slide investigations and visualization of cell-cell interactions obtained through ST, paves the way for the identification of future potential therapeutic targets and developing effective therapies.

Comparing the effects of empagliflozin and liraglutide on lipid metabolism and intestinal microflora in diabetic mice

Background and Objectives

Recent studies have shown that the imbalance of intestinal flora is related to the occurrence and progression of diabetic nephropathy (DN) and can affect lipid metabolism. Sodium-dependent glucose transporters 2 (SGLT2) inhibitor and glucagon-like peptide-1 (GLP-1) receptor agonist are commonly used hypoglycemic drugs and have excellent renal safety. The purpose of this study was to compare the protective effects of empagliflozin and liraglutide on kidneys, lipid metabolism, and intestinal microbiota in diabetic mice.

Methods

We established a mouse model of type two diabetes by feeding rats a high-fat diet (HFD) followed by an intraperitoneal injection of STZ. The mice were randomly divided into groups: normal control (NC), diabetic model (DM), liraglutide treatment (LirT), empagliflozin treatment (EmpT), and liraglutide combined with empagliflozin treatment (Emp&LirT) groups. Blood glucose, lipids, creatinine, and uric acid, as well as urinary nitrogen and albumin levels were measured. The renal tissues were subjected to HE, PAS and Masson's staining. These parameters were used to evaluate renal function and histopathological changes in mice. Mice feces were also collected for 16sRNA sequencing to analyze the composition of the intestinal flora.

Results

All the indexes related to renal function were significantly improved after treatment with drugs. With respect to lipid metabolism, both drugs significantly decreased the serum triglyceride levels in diabetic mice, but the effect of liraglutide on reducing serum cholesterol was better than that of empagliflozin. However, empagliflozin had a better effect on the reduction of low-density lipoproteins (LDL). The two drugs had different effects on intestinal flora. At the phylum level, empagliflozin significantly reduced the ratio of Firmicutes to Bacteroidota, but no effect was seen with liraglutide. At the genus level, both of them decreased the number of Helicobacter and increased the number of Lactobacillus. Empagliflozin also significantly increased the abundance of Muribaculaceae, Muribaculum, Olsenella, and Odoribacter, while liraglutide significantly increased that of Ruminococcus.

Conclusion

Liraglutide and empagliflozin were both able to improve diabetes-related renal injury. However, the ability of empagliflozin to reduce LDL was better compared to liraglutide. In addition, their effects on the intestine bacterial flora were significantly different.

Effects of Zhuang medicine compound Xiancao Granule on diabetic kidney disease: A multi-omics analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Diabetic kidney disease (DKD) poses a severe threat to human health. Compound Xiancao Granule (CXCG), a classic Zhuang medicinal formula, is reported as highly effective in treating DKD. However, the mechanisms underlying the action of CXCG in DKD remain unclear.

AIM OF THE STUDY

This study aimed to investigate the mechanisms of action of CXCG against DKD using multi-omics analysis, including 16s rRNA sequencing, metabolomics, and transcriptomics.

MATERIALS AND METHODS

The chemical compounds of CXCG were identified using ultra-high- performance liquid chromatography quadrupole/electrostatic field orbital trap high-resolution mass spectrometry analysis. A rat model of DKD was established by combining nephrectomy of the left kidney, high-fat diet, and streptozotocin. The therapeutic effects of CXCG on DKD were assessed based on body weight, blood glucose level, renal function, inflammatory cytokine levels, and histological staining. Subsequently, 16s rRNA sequencing, liquid chromatography-tandem mass spectrometry untargeted metabolomic profiling, and RNA sequencing analysis were used to investigate the mechanisms of action of CXCG in DKD. Spearman's correlation analysis was performed to elucidate the correlations between efficacy indicators, gut microbiota, metabolites, and inflammation-related genes.

RESULTS

A total of 118 compounds were identified in CXCG. CXCG significantly ameliorated glucose metabolism disorders, improved renal function, attenuated inflammation, and delayed renal pathological changes in DKD rats. CXCG modulated gut microbiota dysbiosis, including Alloprevotella, Oscillibacter, Anaeroplasma, Anaerotruncus, and Faecalibacterium. In addition, metabolic disruption in DKD rats was regulated by CXCG, which is involved in the metabolism of carbohydrates and amino acids. Transcriptome analysis showed that CXCG affected DKD mainly by regulating inflammation-related genes and pathways, such as the PI3K/Akt and MAPK signaling pathways. Furthermore, there were significant correlations between efficacy indicators, gut microbiota, metabolites, and genes.

CONCLUSION

This multi-omics association study provides novel insights into the effects of CXCG on DKD by remodeling the gut microbiota structure and restoring the metabolic homeostasis through the regulation of carbohydrate metabolism, amino acid metabolism, and inflammation-related pathways, highlighting a potential therapeutic strategy for DKD.

The Renal Composite Benefit of Sodium Glucose Co-Transporter 2 Inhibitors Should Ideally Be Assessed Based on a Standardised Definition: A Meta-Analysis of Randomised Controlled Trials

(1) Background: Chronic kidney disease (CKD) is extremely common against the backdrop of type 2 diabetes (T2D), accounting for nearly 30-40% of cases. The conventional management strategy relie predominantly on metabolic control and the renin-angiotensin-aldosterone system (RAAS) blockage. In the last decade, sodium glucose cotransporter 2 inhibitors (SGLT-2is) have emerged as the leading molecules preventing the development of, as well as retarding, the progression to CKD. Although the evidence in support of SGLT-2is is overwhelming, the definition of renal composite outcome in the trials varied considerably. The aim of the present meta-analysis was to explore the robustness of the renal composite benefits using a uniform definition. (2) Methods: A web-based search was conducted using the Cochrane Library to identify the relevant articles for meta-analysis. RStudio (1 July 2022, Build 554) software was used to conduct the meta-analysis. Hazard ratio (HR) was the effect size used to estimate the renal composite benefit, and prediction interval was used to detect heterogeneity. In view of the differing baseline characteristic of the trials as well as different molecules used, a random effects model was used. (3) Results: There were 12 trials including 78,781 patients, identified using the search strategy, and a five-point Cochrane risk-of-bias was used to assess quality of the publications. In the overall estimation (irrespective of the definition used for the renal composite) the HR was 0.68 (95% CI 0.60-0.76, prediction interval: 0.48-0.95) in favour of SGLT-2is, devoid of heterogeneity. While using a uniform definition of eGFR ≥ 40%decline, ESKD, or renal death, the HR was 0.64 (95% CI 0.53-0.78); using eGFR ≥ 50%decline, ESKD, or renal death the HR was 0.75 (95% CI 0.59-0.97); and with doubling of serum creatinine, renal replacement therapy, or renal death, the HR was 0.67 (95% CI 0.55-0.83) in favour of SGLT-2is. However, significant heterogeneity was encountered with all these three definitions. (4) Conclusion: There is a need to analyse the renal outcomes using a uniform definition in future trials. The presence of heterogeneity might disappear with the pooling of larger number of trials. However, if heterogeneity persists, we need to identify other clinical or laboratory attributes (in addition to SGLT-2is) responsible for the positive renal outcomes.