The Specific Alteration of Gut Microbiota in Diabetic Kidney Diseases—A Systematic Review and Meta-Analysis

Impact of gut microbiota in chronic kidney disease: natural polyphenols as beneficial regulators

Chronic kidney disease (CKD) poses a severe health risk with high morbidity and mortality, profoundly affecting patient quality of life and survival. Despite advancements in research, the pathophysiology of CKD remains incompletely understood. Growing evidence links CKD with shifts in gut microbiota function and composition. Natural compounds, particularly polyphenols, have shown promise in CKD treatment due to their antioxidant and anti-inflammatory properties and their ability to modulate gut microbiota. This review discusses recent progress in uncovering the connections between gut microbiota and CKD, including microbiota changes across different kidney diseases. We also examine metabolite alterations,such as trimethylamine-N-oxide, tryptophan derivatives, branched-chain amino acids, short-chain fatty acids, and bile acids,which contribute to CKD progression. Further, we outline the mechanisms through which polyphenols exert therapeutic effects on CKD, focusing on signaling pathways like nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK), mammalian target of rapamycin (mTOR), NOD-like receptor thermal protein domain associated protein 3 (NLRP3), phosphatidylin-ositol-3-kinase (PI3K)/protein kinase B (Akt), and toll like receptors (TLR), as well as their impact on gut microbiota. Lastly, we consider how dietary polyphenols could be harnessed as bioactive drugs to slow CKD progression. Future research should prioritize multi-omics approaches to identify patients who would benefit from polyphenolic interventions, enabling personalized treatment strategies to enhance therapeutic efficacy.

Construction of a metabolic-immune model for predicting the risk of diabetic nephropathy and study of gut microbiota

AIMS

This study conducts a comprehensive analysis of the relative impact of risk factors for diabetic nephropathy (DN) during disease progression, with a particular emphasis on the role of gut microbiota. We developed multiple predictive models trying to enhance the early identification of high-risk patients in clinical practice.

MATERIALS AND METHODS

We collected data from type 2 diabetes mellitus patients, categorizing them by renal function for comparison. Logistic regression identified risk factors for DN, and we developed nomogram and random forest risk prediction models. Finally, we analyzed the correlations among these factors.

RESULTS

Compared to patients with diabetes alone, those with DN have a longer disease duration, characterized by abdominal obesity, hypertension, chronic inflammation, activation of the complement system, and declining renal function, along with a significant reduction in Bifidobacterium and Enterobacterium. Patients with macroalbuminuria exhibit a higher male prevalence, as well as elevated blood pressure and lipid levels, and poorer renal function. Increased waist-to-hip ratio, systolic blood pressure, urea, neutrophil-to-lymphocyte ratio, and complement C3, along with decreased Enterobacterium and albumin, have been identified as significant risk factors for DN. The nomogram model developed based on these findings demonstrates good predictive capacity. And the establishment of the random forest model further underscores the importance of the aforementioned indicators. Additionally, significant correlations were observed among obesity, inflammation, blood pressure, lipid levels, and gut microbiota.

CONCLUSIONS

Dysbiosis, metabolic disorders, and chronic inflammation play key roles in the progression of DN and may serve as new targets for future prevention and treatment strategies.

Association of the gut microbiome with diabetic nephropathy and the mediated effect of metabolites: friend or enemy?

OBJECTIVE

The effects of gut microbiome and its metabolites on diabetic nephropathy (DN) have been inadequately elucidated. The aim of this study is to assess the causal effect of gut microbiome on DN and the mediated effect of metabolites by a two-step Mendelian randomization (MR).

METHODS

Datasets of gut microbiome, metabolites, and DN were acquired in genome-wide association studies and screened for single nucleotide polymorphisms according to the underlying assumptions of MR. Subsequently, inverse variance weighted was used as the primary method for MR analysis to assess the causal effect of gut microbiome on DN and the mediated effect of metabolites. Finally, MR-Egger intercept, Cochran's Q test, and leave-one-out sensitivity analysis were used to assess the horizontal pleiotropy, heterogeneity, and robustness of the results, respectively.

RESULTS

The MR analysis demonstrated that Parabacteroides merdae increased the genetic susceptibility to DN by reducing acetylcarnitine (C2) to propionylcarnitine (C3) ratio (mediated proportion 8.95%, mediated effect 0.024) and alpha-ketobutyrate to 3-methyl-2-oxovalerate ratio (mediated proportion 19.90%, mediated effect 0.053). MR Egger showed that these results lack horizontal pleiotropy (p ≥ 0.05). Cochran's Q and sensitivity analysis suggested these results had no heterogeneity (p ≥ 0.05) and were robust.

CONCLUSION

Our findings revealed the pathway by which Parabacteroides merdae increased the genetic susceptibility to DN by regulating acetylcarnitine (C2) to propionylcarnitine (C3) ratio and alpha-ketobutyrate to 3-methyl-2-oxovalerate ratio. It provides new genetic insights for understanding the pathogenesis of DN and related drug research.

Urobiome of patients with diabetic kidney disease in different stages is revealed by 2bRAD-M

BACKGROUND

Knowledge of the urinary microbiome (urobiome) in diabetic kidney disease (DKD) remains limited. The most commonly used 16S rRNA sequencing technique can only provide bacterial identification at the genus level. As a novel technique, 2bRAD sequencing for microbiome (2bRAD-M) can be used to identify the low-biomass microbiome at the species level. In this study, we used 2bRAD-M to compare the urobiome composition of patients with DKD at different stages with healthy individuals and those with type 2 diabetes mellitus (T2DM), with the expectation that we would find discriminative species correlated with DKD.

METHOD

Healthy controls, patients with DKD with microalbuminuria (DKD1 group) or macroalbuminuria (DKD2 group), and patients with T2DM were recruited (n = 20 for each group). The first-morning urine was collected for 2bRAD-M testing. The albumin-to-creatinine ratio (ACR) was also measured with urine samples. Serum samples were collected for detecting clinical indicators. The microbial diversity and composition based on abundance were calculated. Differential bacteria for different groups were identified. Besides, the correlation between discriminative bacteria and clinical indices was also analyzed.

RESULTS

Urobiome diversity was significantly reduced in the DKD groups. In the DKD1 group, was the dominant genus, followed by Pseudomonas_E, whereas in the DKD2 group, Pseudomonas_E became the dominant genus and Escherichia was notably reduced. Both Bifidobacterium and Streptococcus, which were the top genera in the control group, were substantially decreased in the DKD groups. The discriminative species for DKD1 included Escherichia coli and Acinetobacter johnsonii, while for DKD2, Pseudomonas_E oleovorans, Enterococcus faecalis, and Morganella morganii were identified. Pseudomonas_E, Enterococcus and Morganella showed a strong correlation with renal function indicators and urinary protein levels.

CONCLUSION

The urobiome diversity and composition in patients with DKD were markedly different from those in healthy individuals and T2DM patients. These findings provide valuable insights into the onset and progression of DKD, driven by changes in the urinary bacterial community structure.

The gut microbiome as a potential therapeutic target in IgA nephropathy

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis and a leading cause of kidney failure, with limited treatment options available. The pathophysiology of IgAN remains unclear; however, recent studies suggest that genetic, epigenetic and environmental factors play significant roles. There is also strong evidence linking the gut microbiome to the development of IgAN. In this review, we will examine the relationship between the microbiome and the pathogenesis of IgAN, as well as its potential as a target for future therapeutic interventions.

Gut microbiota may mediate the causality of statins on diabetic nephropathy: a mediation Mendelian randomization study

BACKGROUND

Increasing evidence indicates that statins may increase the risk of developing diabetic nephropathy (DN). As the gut-kidney axis concept gains traction, it remains unclear whether statins contribute to the onset and progression of DN by modulating gut microbiota.

OBJECTIVE

To investigate the association between statins and DN and the proportion of this association mediated through gut microbiota.

METHOD

This study utilized a two-sample Mendelian randomization (MR) approach and a cross-sectional observational design to investigate the causal relationships among statins, 473 gut microbiota, and DN. Furthermore, mediation MR analysis was employed to explore the potential mediating effects of gut microbiota in the statins-DN relationship.

RESULTS

HMGCR inhibitors were causally linked to the increased incidence of DN (odds ratio [OR]: 0.732, 95% confidence interval [CI] 0.647, 0.828, PFDR = 0.000004). Supporting results from a cross-sectional study based on the Medical Information Marketplace in Intensive Care (MIMIC-IV) database also indicated this association (OR: 0.74, 95% CI: 0.61, 0.91, P = 0.004). Among the 473 identified gut microbiota species, 13 (PFDR < 0.05) were causally associated with DN. The mediation MR analysis revealed that 10 gut microbiota mediated the relationship between statins and DN, acting as either protective or risk factors (P < 0.05). In addition, HMGCR and related proteins may be involved in lipid metabolism, insulin resistance, and AMPK signaling pathway.

CONCLUSION

Statins may become a risk factor for DN by increasing or decreasing the abundance of specific gut microbiota. These specific gut bacteria have the potential to become a new indicator for guiding the clinical use of statins in diabetic patients.

Phenylethanol Glycosides from Cistanche tubulosa Modulate the Gut Microbiota and Cecal Metabolites to Ameliorate Diabetic Nephropathy Induced by Streptozotocin Combined with High-Fat Diet in Rats

Diabetic nephropathy (DN) is a prevalent complication and serious microvascular of diabetes mellitus. After previous studies, we found that phenylethanol glycosides (CPhGs) derived from Cistanche tubulosa (Schenk) Wight exerts antidiabetic and renoprotective effects. However, the effects of CPhGs on DN remain incompletely understood. The study aimed to examine the effects of CPhGs on DN in rats and explore the underlying mechanism involved. A DN rat model was established by streptozotocin (STZ) combined with a high-fat diet. Reagent kits were used to assess the extent to which CPhGs ameliorate hyperglycemia, insulin resistance (IR), renal dysfunction, kidney oxidative stress, and peripheral inflammation. Histology and immunohistochemical staining were used to detect the changes in renal tissue structure and the expression levels of α-smooth muscle actin (α-SMA) and collagen I. Furthermore, we analyzed the cecal contents of DN rats to investigate the effect of CPhGs on gut microbiota by using 16S rRNA sequencing and broad-spectrum metabolite profiling. The results showed that CPhGs demonstrated a range of advantageous outcomes in DN, encompassing the enhancement of kidney function and alleviation of hyperglycemia, IR, renal injury, oxidative stress, and peripheral inflammatory reactions. In addition, CPhGs regulated the abundance of the [Eubacterium]_coprostanoligenes_group, Oscillospiraceae_UCG-005, etc. to modulate the gut microbiota. CPhGs significantly upregulated the content of vitamin B6 and tyrosyl-tryptophan and downregulated histamine, L-methionine, etc. In summary, the therapeutic efficacy of CPhGs on DN rats may be achieved by modulating the gut microbiota and cecal metabolites to restore the metabolic disorders of vitamin B6, histidine, etc.

Decrease in Escherichia-Shigella in the gut microbiota of ESKD patients undergoing maintenance hemodialysis

BACKGROUND

Gut dysbiosis is thought to be involved in the pathogenesis and progression of chronic kidney disease and end-stage kidney disease (ESKD). However, differences in the composition and function of gut microbiota in hemodialysis patients are not consistently concluded.

METHODS

A total of 20 patients receiving maintenance hemodialysis (MHD) treatment at the Blood Purification Center of Bethune International Peace Hospital from March 2021 to December 2022 were included based on the inclusion criteria. Additionally, 20 healthy volunteers matched for age, gender, and body mass index were recruited from the Health Examination Center as the healthy control (HC) group. The structure of the gut microbiota community in the study subjects was analyzed using second-generation high-throughput sequencing technology based on 16S rRNA and amplicon sequence variants (ASV) analysis.

RESULTS

There were significant differences in gut microbial communities between the two groups. At the genus level, significant differences were found in 19 genera. Among them, Escherichia-Shigella, Lachnospira, Parasutterella, [Ruminococcus]-torques-group, Butyricicoccus, and Streptococcus were significantly decreased, while Phascolarctobacterium, Ruminococcaceae-UBA1819, Erysipelotrichaceae-UCG-003, Flavonifractor, and Erysipelatoclostridium were significantly increased in MHD patients. In particular, the abnormal decrease in the abundance of p-Proteobacteria.c-Gammaproteobacteria.o-Enterobacterales.f-Enterobacteriaceae.g-Escherichia-Shigella might be a significant characteristic of gut microbiota in MHD patients.

CONCLUSION

The decreased abundance of Escherichia-Shigella is a signature gut microbiota alteration in patients with ESKD undergoing MHD, and Escherichia-Shigella may represent a key bacterial group warranting exploration in the field of hemodialysis. The dysbiosis of gut microbiota holds promise as a therapeutic target and biomarker for the diagnosis and treatment of MHD.

Gut-X axis

Recent advances in understanding the modulatory functions of gut and gut microbiota on human diseases facilitated our focused attention on the contribution of the gut to the pathophysiological alterations of many extraintestinal organs, including the liver, heart, brain, lungs, kidneys, bone, skin, reproductive, and endocrine systems. In this review, we applied the "gut-X axis" concept to describe the linkages between the gut and other organs and discussed the latest findings related to the "gut-X axis," including the underlying modulatory mechanisms and potential clinical intervention strategies.

Causal Relationships Between Gut Microbiota, Metabolites, and Diabetic Nephropathy: Insights from a Two-Sample Mendelian Randomization Analysis

Background

 Previous studies have established a correlation between gut microbiota, metabolites, and diabetic nephropathy (DN). However, the inherent limitations of observational studies, including reverse causality and confounding factors, made this relationship uncertain.

Methods

In this study, we compiled summary statistics from a genome-wide association study (GWAS) conducted on gut microbiota, metabolites, and DN. We employed a two-sample Mendelian randomization (MR) approach, utilizing inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode methods.

Results

 We detected the protective nature of genetically predicted representatives from the family Bacteroidaceae (OR: 0.716, 95% CI: 0.516-0.995, p = 0.046), family Victivallaceae (OR: 0.871, 95% CI: 0.772-0.982, p = 0.026), genus Bacteroides (OR: 0.716, 95% CI: 0.516-0.995, p = 0.046), genus Coprococcus 2 (OR: 0.745, 95% CI: 0.576-0.963, p = 0.025), and genus Lactococcus (OR: 0.851, 95% CI: 0.730-0.992, p = 0.039) against the development of DN. Conversely, we identified a positive correlation between the incidence of DN and entities, such as Phylum Bacteroidetes (OR: 1.427, 95% CI: 1.085-1.875, p = 0.011), class Bacteroidia (OR: 1.304, 95% CI: 1.036-1.641,p = 0.024), order Bacteroidales (OR: 1.304, 95% CI: 1.035-1.641, p = 0.028), genus Catenibacterium (OR: 1.312, 95% CI: 1.079-1.594, p = 0.006), genus Lachnoclostridium (OR: 1.434, 95% CI: 1.129-1.821, p = 0.003), and genus Parasutterella (OR: 1.270, 95% CI: 1.070-1.510, p = 0.006). In our analysis, none of the gut metabolites demonstrated a causal relationship with DN.

Conclusion

 Our results substantiated the potential causal association between specific gut microbiota and DN. Therefore, our study offers novel insight into the mechanisms underlying DN. This finding provides a theoretical foundation for the future development of targeted strategies for the prevention and treatment of DN.

Traditional Chinese medicine improved diabetic kidney disease through targeting gut microbiota

CONTEXT

Diabetic kidney disease (DKD) affects nearly 40% of diabetic patients, often leading to end-stage renal disease that requires renal replacement therapies, such as dialysis and transplantation. The gut microbiota, an integral aspect of human evolution, plays a crucial role in this condition. Traditional Chinese medicine (TCM) has shown promising outcomes in ameliorating DKD by addressing the gut microbiota.

OBJECTIVE

This review elucidates the modifications in gut microbiota observed in DKD and explores the impact of TCM interventions on correcting microbial dysregulation.

METHODS

We searched relevant articles from databases including Web of Science, PubMed, ScienceDirect, Wiley, and Springer Nature. The following keywords were used: diabetic kidney disease, diabetic nephropathy, gut microbiota, natural product, TCM, Chinese herbal medicine, and Chinese medicinal herbs. Rigorous criteria were applied to identify high-quality studies on TCM interventions against DKD.

RESULTS

Dysregulation of the gut microbiota, including Lactobacillus, Streptococcus, and Clostridium, has been observed in individuals with DKD. Key indicators of microbial dysregulation include increased uremic solutes and decreased short-chain fatty acids. Various TCM therapies, such as formulas, tablets, granules, capsules, and decoctions, exhibit unique advantages in regulating the disordered microbiota to treat DKD.

CONCLUSION

This review highlights the importance of targeting the gut-kidney axis to regulate microbial disorders, their metabolites, and associated signaling pathways in DKD. The Qing-Re-Xiao-Zheng formula, the Shenyan Kangfu tablet, the Huangkui capsule, and the Bekhogainsam decoction are potential candidates to address the gut-kidney axis. TCM interventions offer a significant therapeutic approach by targeting microbial dysregulation in patients with DKD.

Genetic Evidence for the Causal Relationship Between Gut Microbiota and Diabetic Kidney Disease: A Bidirectional, Two-Sample Mendelian Randomisation Study

Aims: According to the gut-kidney axis theory, gut microbiota (GM) has bidirectional crosstalk with the development of diabetic kidney disease (DKD). However, empirical results have been inconsistent, and the causal associations remain unclear. This study was aimed at exploring the causal relationship between GM and DKD as well as the glomerular filtration rate (GFR) and urinary albumin-to-creatinine ratio (UACR). Materials and Methods: Two-sample Mendelian randomisation (MR) analysis was performed with inverse-variance weighting as the primary method, together with four additional modes (MR-Egger regression, simple mode, weighted mode, and weighted median). We utilised summary-level genome-wide association study statistics from public databases for this MR analysis. Genetic associations with DKD were downloaded from the IEU Open GWAS project or CKDGen consortium, and associations with GM (196 taxa from five levels) were downloaded from the MiBioGen repository. Results: In forward MR analysis, we identified 13 taxa associated with DKD, most of which were duplicated in Type 2 diabetes with renal complications but not in Type 1 diabetes. We observed a causal association between genetic signature contributing to the relative abundance of Erysipelotrichaceae UCG003 and that for both DKD and GFR. Similarly, host genetic signature defining the abundance of Ruminococcaceae UCG014 was found to be simultaneously associated with DKD and UACR. In reverse MR analysis, the abundance of 14 other GM taxa was affected by DKD, including the phylum Proteobacteria, which remained significant after false discovery rate correction. Sensitivity analyses revealed no evidence of outliers, heterogeneity, or horizontal pleiotropy. Conclusion: Our findings provide compelling causal genetic evidence for the bidirectional crosstalk between specific GM taxa and DKD development, contributing valuable insights for a comprehensive understanding of the pathological mechanisms of DKD and highlighting the possibility of prevention and management of DKD by targeting GM.

Association between gut microbiota and diabetic nephropathy: a two-sample mendelian randomization study

BACKGROUND

Observational studies have demonstrated the alterations of gut microbiota composition in diabetic nephropathy (DN), however, the correlation between gut microbiota and DN remains unclear.

METHODS

A two-sample Mendelian randomization (MR) analysis was designed to estimate the association between gut microbiota and DN. The summary statistics of gut microbiota from phylum level to genus level were obtained from a large-scale, genome-wide association study involving 18,340 individuals, and the data at the species level was derived from the study of TwinsUK Registry, including 1126 twin pairs. The summary statistics of DN were originated from the latest release data of FinnGen (R7, 299623 participants). The MR estimation was calculated using inverse variance weighted, weighted median, MR-Egger regression, and MR-PRESSO. Heterogeneity was assessed using Cochrane's Q test.

RESULTS

Inverse variance weighted results indicated that the order Bacteroidetes and its corresponding class and phylum [odds ratio (OR), 1.58; 95% confidence interval (CI), 1.15-2.17], the family Verrucomicrobiaceae and its corresponding class and order (OR, 1.46; 95% CI, 1.14-1.87), the genera Akkermansia (OR, 1.46; 95% CI, 1.14-1.87) and Catenibacterium (OR, 1.33; 95% CI, 1.07-1.66) might be associated with a higher risk of DN; whereas the genera Coprococcus2 (OR, 0.68; 95% CI, 0.51-0.91) and Eubacterium_coprostanoligenes_group (OR, 0.69; 95% CI, 0.52-0.92) might play protective roles in DN.

CONCLUSIONS

This MR study suggested that several gut bacteria were potentially associated with DN, further studies are required to validate these findings.

Gut Microbiota and Neonatal Acute Kidney Injury

OBJECTIVE

 To characterize the relationship between gut microbiota and neonatal acute kidney injury biomarkers based on the gut-kidney axis.

STUDY DESIGN

 The Pubmed database was primarily searched to include relevant literature on gut microbiota and neonatal acute kidney injury biomarkers, which was subsequently organized and analyzed and a manuscript was written.

RESULTS

 Gut microbiota was associated with neonatal acute kidney injury biomarkers. These biomarkers included TIMP-2, IGFBP-7, VEGF, calbindin, GST, B2MG, ghrelin, and clusterin.

CONCLUSION

 The gut microbiota is strongly associated with neonatal acute kidney injury biomarkers, and controlling the gut microbiota may be a potential target for ameliorating neonatal acute kidney injury.

KEY POINTS

· There is a bidirectional association between gut microbiota and AKI.. · Gut microbiota is closely associated with biomarkers of nAKI.. · Manipulation of gut microbiota may improve nAKI..

Intestinal flora and bile acid interactions impact the progression of diabetic kidney disease

In recent years, with the rapid development of omics technologies, researchers have shown that interactions between the intestinal flora and bile acids are closely related to the progression of diabetic kidney disease (DKD). By regulating bile acid metabolism and receptor expression, the intestinal flora affects host metabolism, impacts the immune system, and exacerbates kidney injury in DKD patients. To explore interactions among the gut flora, bile acids and DKD, as well as the related mechanisms, in depth, in this paper, we review the existing literature on correlations among the gut flora, bile acids and DKD. This review also summarizes the efficacy of bile acids and their receptors as well as traditional Chinese medicines in the treatment of DKD and highlights the unique advantages of bile acid receptors in DKD treatment. This paper is expected to reveal a new and important potential strategy for the clinical treatment of DKD.

The mineralocorticoid receptor in diabetic kidney disease

Diabetes mellitus is one of the leading causes of chronic kidney disease and its progression to end-stage kidney disease (ESKD). Diabetic kidney disease (DKD) is characterized by glomerular hypertrophy, hyperfiltration, inflammation, and the onset of albuminuria, together with a progressive reduction in glomerular filtration rate. This progression is further accompanied by tubulointerstitial inflammation and fibrosis. Factors such as genetic predisposition, epigenetic modifications, metabolic derangements, hemodynamic alterations, inflammation, and inappropriate renin-angiotensin-aldosterone system (RAAS) activity contribute to the onset and progression of DKD. In this context, decades of work have focused on glycemic and blood pressure reduction strategies, especially targeting the RAAS to slow disease progression. Although much of the work has focused on targeting angiotensin II, emerging data support that the mineralocorticoid receptor (MR) is integral in the development and progression of DKD. Molecular mechanisms linked to the underlying pathophysiological changes derived from MR activation include vascular endothelial and epithelial cell responses to oxidative stress and inflammation. These responses lead to alterations in the microcirculatory environment, the abnormal release of extracellular vesicles, gut dysbiosis, epithelial-mesenchymal transition, and kidney fibrosis. Herein, we present recent experimental and clinical evidence on the MR in DKD onset and progress along with new MR-based strategies for the treatment and prevention of DKD.

Exendin-4-enriched exosomes from hUCMSCs alleviate diabetic nephropathy via gut microbiota and immune modulation

Introduction

Diabetic nephropathy (DN) presents a significant therapeutic challenge, compounded by complex pathophysiological mechanisms. Recent studies suggest Exendin-4 (Ex-4) as a potential ameliorative agent for DN, albeit with unclear mechanisms. This research investigates the effects and underlying mechanisms of Ex-4-enriched exosomes derived from human umbilical cord mesenchymal stem cells (hUCMSCs) on DN, focusing on their renoprotective properties and interactions with gut microbiota.

Method

Exosomes from hUCMSCs (hUCMSCs-Exo) were loaded with Ex-4 via electroporation. A streptozotocin (STZ) -induced DN mouse model was employed to assess the therapeutic impact of these engineered exosomes. The study further explored immune cell dynamics, mainly CD4+ regulatory T (Treg) cells, using bioinformatics, flow cytometry, and the influence of gut microbiota through antibiotic treatment and specific bacterial reintroduction.

Results

Treatment with hUCMSCs-Exo@Ex-4 significantly improved key DN markers, including blood glucose and proteinuria, alleviating kidney damage. A notable decrease in natural Treg cell infiltration in DN was observed, while Ex-4-loaded exosomes promoted CD4+ Treg cell induction. The therapeutic benefits of hUCMSCs-Exo@Ex-4 were diminished upon CD4+ Treg cell depletion, underscoring their role in this context. Notably, CD4+ Treg cell induction correlated with the presence of Prevotella species, and disruption of gut microbiota adversely affected these cells and the therapeutic efficacy of the treatment. However, the reintroduction of Prevotella strains counteracted these adverse effects.

Discussion

This study elucidates a novel therapeutic mechanism of Ex-4-loaded hUCMSCs exosomes in DN, highlighting the induction of CD4+ Treg cells mediated by specific gut microbiota components. These findings underscore the potential of leveraging gut microbiota and immune cell interplay in developing effective DN treatments.

Guild-level signature of gut microbiome for diabetic kidney disease

Current microbiome signatures for chronic diseases such as diabetic kidney disease (DKD) are mainly based on low-resolution taxa such as genus or phyla and are often inconsistent among studies. In microbial ecosystems, bacterial functions are strain specific, and taxonomically different bacteria tend to form co-abundance functional groups called guilds. Here, we identified guild-level signatures for DKD by performing in-depth metagenomic sequencing and conducting genome-centric and guild-based analysis on fecal samples from 116 DKD patients and 91 healthy subjects. Redundancy analysis on 1,543 high-quality metagenome-assembled genomes (HQMAGs) identified 54 HQMAGs that were differentially distributed among the young healthy control group, elderly healthy control group, early-stage DKD patients (EDG), and late-stage DKD patients (LDG). Co-abundance network analysis classified the 54 HQMAGs into two guilds. Compared to guild 2, guild 1 contained more short-chain fatty acid biosynthesis genes and fewer genes encoding uremic toxin indole biosynthesis, antibiotic resistance, and virulence factors. Guild indices, derived from the total abundance of guild members and their diversity, delineated DKD patients from healthy subjects and between different severities of DKD. Age-adjusted partial Spearman correlation analysis showed that the guild indices were correlated with DKD disease progression and with risk indicators of poor prognosis. We further validated that the random forest classification model established with the 54 HQMAGs was also applicable for classifying patients with end-stage renal disease and healthy subjects in an independent data set. Therefore, this genome-level, guild-based microbial analysis strategy may identify DKD patients with different severity at an earlier stage to guide clinical interventions.

IMPORTANCE

Traditionally, microbiome research has been constrained by the reliance on taxonomic classifications that may not reflect the functional dynamics or the ecological interactions within microbial communities. By transcending these limitations with a genome-centric and guild-based analysis, our study sheds light on the intricate and specific interactions between microbial strains and diabetic kidney disease (DKD). We have unveiled two distinct microbial guilds with opposite influences on host health, which may redefine our understanding of microbial contributions to disease progression. The implications of our findings extend beyond mere association, providing potential pathways for intervention and opening new avenues for patient stratification in clinical settings. This work paves the way for a paradigm shift in microbiome research in DKD and potentially other chronic kidney diseases, from a focus on taxonomy to a more nuanced view of microbial ecology and function that is more closely aligned with clinical outcomes.

Association between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

Background

To clarify the causal relationship between gut microbiota and diabetic nephropathy (DN), we employed Mendelian randomization (MR). Despite a strong correlation observed, establishing causality is still unclear. By utilizing MR, we aimed to investigate this relationship further and shed light on the potential causal effect of gut microbiota on DN.

Methods

Genetic instrumental variables for gut microbiota were obtained from a GWAS with 18340 participants. DN summary statistics (1032 cases, 451248 controls) were sourced from a separate GWAS. The primary analysis used the inverse-variance weighted (IVW) method. Reverse MR analysis was conducted to explore reverse causation. Rigorous sensitivity analyses were performed to ensure the resilience and reliability of the study's findings.

Results

We found two bacterial traits associated with an increased risk of DN: genus LachnospiraceaeUCG008 (OR: 1.4210; 95% CI: 1.0450, 1.9322; p = 0.0250) and genus Terrisporobacter (OR: 1.9716; 95% CI: 1.2040, 3.2285; p = 0.0070). Additionally, phylum Proteobacteria (OR: 0.4394; 95% CI: 0.2721, 0.7096; p = 0.0008) and genus Dialister (OR: 0.4841; 95% CI: 0.3171, 0.7390; p = 0.0008) were protective against DN. Sensitivity analyses consistently supported these results. In the reverse MR analysis, no statistically significant associations were observed between DN and these four bacterial traits.

Conclusions

Our analyses confirmed a potential causal relationship between certain gut microbiota taxa and the risk of DN. However, additional studies are required to elucidate the underlying mechanisms through which gut microbiota influences the development of DN.

A multi-omics approach to investigate characteristics of gut microbiota and metabolites in hypertension and diabetic nephropathy SPF rat models

Background

Imbalance in intestinal microbiota caused by microbial species and proportions or metabolites derived from microbes are associated with hypertension, as well as diabetic nephropathy. However, the involvement of the intestinal microbiota and metabolites in hypertension and diabetic nephropathy comorbidities (HDN) remains to be elucidated.

Methods

We investigated the effects of intestinal microbiota on HDN in a rat model and determined the abundance of the intestinal microbiota using 16S rRNA sequencing. Changes in fecal and serum metabolites were analyzed using ultra-high-performance liquid chromatography-mass spectrometry.

Results

The results showed abundance of Proteobacteria and Verrucomicrobia was substantially higher, whereas that of Bacteroidetes was significant lower in the HDN group than in the sham group. Akkermansia, Bacteroides, Blautia, Turicibacter, Lactobacillus, Romboutsia, and Fusicatenibacter were the most abundant, and Prevotella, Lachnospiraceae_NK4A136_group, and Prevotella_9 were the least abundant in the HDN group. Further analysis with bile acid metabolites in serum showed that Blautia was negatively correlated with taurochenodeoxycholic acid, taurocholic acid, positively correlated with cholic acid and glycocholic acid in serum.

Conclusions

These findings suggest that the gut microbiota and metabolites in feces and serum substantially differed between the HDN and sham groups. The F/B ratio was higher in the HDN group than in the sham group. Blautia is potentially associated with HDN that correlated with differentially expressed bile acid metabolites, which might regulate the pathogenesis of HDN via the microorganism-gut-metabolite axis.

Causal effect of gut microbiota and diabetic nephropathy: a Mendelian randomization study

BACKGROUND

The interaction of dysbiosis of gut microbiota (GM) with diabetic nephropathy (DN) drew our attention and a better understanding of GM on DN might provide potential therapeutic approaches. However, the exact causal effect of GM on DN remains unknown.

METHODS

We applied two-sample Mendelian Randomization (MR) analysis, including inverse variance weighted (IVW), MR-Egger methods, etc., to screen the significant bacterial taxa based on the GWAS data. Sensitivity analysis was conducted to assess the robustness of MR results. To identify the most critical factor on DN, Mendelian randomization-Bayesian model averaging (MR-BMA) method was utilized. Then, whether the reverse causality existed was verified by reverse MR analysis. Finally, transcriptome MR analysis was performed to investigate the possible mechanism of GM on DN.

RESULTS

At locus-wide significance levels, the results of IVW suggested that order Bacteroidales (odds ratio (OR) = 1.412, 95% confidence interval (CI): 1.025-1.945, P = 0.035), genus Akkermansia (OR = 1.449, 95% CI: 1.120-1.875, P = 0.005), genus Coprococcus 1 (OR = 1.328, 95% CI: 1.066-1.793, P = 0.015), genus Marvinbryantia (OR = 1.353, 95% CI: 1.037-1.777, P = 0.030) and genus Parasutterella (OR = 1.276, 95% CI: 1.022-1.593, P = 0.032) were risk factors for DN. Reversely, genus Eubacterium ventriosum (OR = 0.756, 95% CI: 0.594-0.963, P = 0.023), genus Ruminococcus gauvreauii (OR = 0.663, 95% CI: 0.506-0.870, P = 0.003) and genus Erysipelotrichaceae (UCG003) (OR = 0.801, 95% CI: 0.644-0.997, P = 0.047) were negatively associated with the risk of DN. Among these taxa, genus Ruminococcus gauvreauii played a crucial role in DN. No significant heterogeneity or pleiotropy in the MR result was found. Mapped genes (FDR < 0.05) related to GM had causal effects on DN, while FCGR2B and VNN2 might be potential therapeutic targets.

CONCLUSIONS

This work provided new evidence for the causal effect of GM on DN occurrence and potential biomarkers for DN. The significant bacterial taxa in our study provided new insights for the 'gut-kidney' axis, as well as unconventional prevention and treatment strategies for DN.

Specific Alternation of Gut Microbiota and the Role of Ruminococcus gnavus in the Development of Diabetic Nephropathy

In this study, we aim to investigate the precise alterations in the gut microbiota during the onset and advancement of diabetic nephropathy (DN) and examine the impact of Ruminococcus gnavus (R. gnavus) on DN. Eight-week-old male KK-Ay mice were administered antibiotic cocktails for a duration of two weeks, followed by oral administration of R. gnavus for an additional eight weeks. Our study revealed significant changes in the gut microbiota during both the initiation and progression of DN. Specifically, we observed a notable increase in the abundance of Clostridia at the class level, higher levels of Lachnospirales and Oscillospirales at the order level, and a marked decrease in Clostridia_UCG-014 in DN group. Additionally, there was a significant increase in the abundance of Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae at the family level. Moreover, oral administration of R. gnavus effectively aggravated kidney pathology in DN mice, accompanied by elevated levels of urea nitrogen (UN), creatinine (Cr), and urine protein. Furthermore, R. gnavus administration resulted in down-regulation of tight junction proteins such as Claudin-1, Occludin, and ZO-1, as well as increased levels of uremic toxins in urine and serum samples. Additionally, our study demonstrated that orally administered R. gnavus up-regulated the expression of inflammatory factors, including nucleotide-binding oligomerization domain-like receptor pyrin domain-containing protein 3 (NLRP3) and Interleukin (IL)-6. These changes indicated the involvement of the gut-kidney axis in DN, and R. gnavus may worsen diabetic nephropathy by affecting uremic toxin levels and promoting inflammation in DN.

Association between gut microbiota and diabetic nephropathy: a mendelian randomization study

Background

The correlation between diabetic nephropathy (DN) and gut microbiota (GM) has been suggested in numerous animal experiments and cross-sectional studies. However, a causal association between GM and DN has not been ascertained.

Methods

This research adopted MR analysis to evaluate the causal link between GM and DN derived from data acquired through publicly available genome-wide association studies (GWAS). The study utilized the inverse variance weighted (IVW) approach to assess causal association between GM and DN. Four additional methods including MR-Egger, weighted median, weighted mode, and simple mode were employed to ensure comprehensive analysis and robust results. The Cochran's Q test and the MR-Egger method were conducted to identify heterogeneity and horizontal pleiotropy, respectively. The leave-one-out approach was utilized to evaluate the stability of MR results. Finally, a reverse MR was performed to identify the reverse causal association between GM and DN.

Results

According to IVW analysis, Class Verrucomicrobiae (p = 0.003), Order Verrucomicrobiales (p = 0.003), Family Verrucomicrobiaceae (p = 0.003), Genus Akkermansia (p = 0.003), Genus Catenibacterium (p = 0.031), Genus Coprococcus 1 (p = 0.022), Genus Eubacterium hallii group (p = 0.018), and Genus Marvinbryantia (p = 0.023) were associated with a higher risk of DN. On the contrary, Class Actinobacteria (p = 0.037), Group Eubacterium ventriosum group (p = 0.030), Group Ruminococcus gauvreauii group (p = 0.048), Order Lactobacillales (p = 0.045), Phylum Proteobacteria (p = 0.017) were associated with a lower risk of DN. The sensitivity analysis did not identify any substantial pleiotropy or heterogeneity in the outcomes. We found causal effects of DN on 11 GM species in the reverse MR analysis. Notably, Phylum Proteobacteria and DN are mutually causalities.

Conclusion

This study identified the causal association between GM and DN with MR analysis, which may enhance the understanding of the intestinal-renal axis and provide novel potential targets for early non-invasive diagnosis and treatment of DN.

Integrated 16S rRNA sequencing and metabolomic analysis reveals the potential protective mechanism of Germacrone on diabetic nephropathy in mice

Diabetic nephropathy (DN) is a severe complication of diabetes and the leading cause of end-stage renal disease and death. Germacrone (Ger) possesses anti-inflammatory, antioxidant and anti-DN properties. However, it is unclear whether the improvement in kidney damage caused by Ger in DN mice is related to abnormal compositions and metabolites of the gut microbiota. This study generates a mouse model of DN to explore the potent therapeutic ability and mechanism of Ger in renal function by 16S rRNA sequencing and untargeted fecal metabolomics. Although there is no significant change in microbiota diversity, the structure of the gut microbiota in the DN group is quite different. Serratia_marcescens and Lactobacillus_iners are elevated in the model group but significantly decreased after Ger intervention ( P<0.05). Under the treatment of Ger, no significant differences in the diversity and richness of the gut microbiota are observed. An imbalance in the intestinal flora leads to the dysregulation of metabolites, and non-targeted metabolomics data indicate high expression of stearic acid in the DN group, and oleic acid could serve as a potential marker of the therapeutic role of Ger in the DN model. Overall, Ger improves kidney injury in diabetic mice, in part potentially by reducing the abundance of Serratia_marcescens and Lactobacillus_iners, as well as regulating the associated increase in metabolites such as oleic acid, lithocholic acid and the decrease in stearic acid. Our research expands the understanding of the relationship between the gut microbiota and metabolites in Ger-treated DN. This contributes to the usage of natural products as a therapeutic approach for the treatment of DN via microbiota regulation.

Causal relationship between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

Objective

Emerging evidence has provided compelling evidence linking gut microbiota (GM) and diabetic nephropathy (DN) via the "gut-kidney" axis. But the causal relationship between them hasn't been clarified yet. We perform a Two-Sample Mendelian randomization (MR) analysis to reveal the causal connection with GM and the development of DN, type 1 diabetes nephropathy (T1DN), type 2 diabetes nephropathy (T2DN), type 1 diabetes mellitus (T1DM), and type 2 diabetes mellitus (T2DM).

Methods

We used summary data from MiBioGen on 211 GM taxa in 18340 participants. Generalized MR analysis methods were conducted to estimate their causality on risk of DN, T1DN, T2DN, T1DM and T2DM from FinnGen. To ensure the reliability of the findings, a comprehensive set of sensitivity analyses were conducted to confirm the resilience and consistency of the results.

Results

It was showed that Class Verrucomicrobiae [odds ratio (OR) =1.5651, 95%CI:1.1810-2.0742,PFDR=0.0018], Order Verrucomicrobiales (OR=1.5651, 95%CI: 1.1810-2.0742, PFDR=0.0018) and Family Verrucomicrobiaceae (OR=1.3956, 95%CI:1.0336-1.8844, PFDR=0.0296) had significant risk of DN. Our analysis found significant associations between GM and T2DN, including Class Verrucomimicrobiae (OR=1.8227, 95% CI: 1.2414-2.6763, PFDR=0.0139), Order Verrucomimicrobiae (OR=1.5651, 95% CI: 1.8227-2.6764, PFDR=0.0024), Rhodospirillales (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0026), and Family Verrucomicroniaceae (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0083). The Eubacteriumprotogenes (OR=0.4076, 95% CI: 0.2415-0.6882, PFDR=0.0021) exhibited a protection against T1DN. Sensitivity analyses confirmed that there was no significant heterogeneity and pleiotropy.

Conclusions

At the gene prediction level, we identified the specific GM that is causally linked to DN in both T1DM and T2DM patients. Moreover, we identified distinct microbial changes in T1DN that differed from those seen in T2DN, offering valuable insights into GM signatures associated with subtype of nephropathy.

Clinical metabolomics characteristics of diabetic kidney disease: A meta-analysis of 1875 cases with diabetic kidney disease and 4503 controls

AIMS

Diabetic Kidney Disease (DKD), one of the major complications of diabetes, is also a major cause of end-stage renal disease. Metabolomics can provide a unique metabolic profile of the disease and thus predict or diagnose the development of the disease. Therefore, this study summarises a more comprehensive set of clinical biomarkers related to DKD to identify functional metabolites significantly associated with the development of DKD and reveal their driving mechanisms for DKD.

MATERIALS AND METHODS

We searched PubMed, Embase, the Cochrane Library and Web of Science databases through October 2022. A meta-analysis was conducted on untargeted or targeted metabolomics research data based on the strategy of standardized mean differences and the process of ratio of means as the effect size, respectively. We compared the changes in metabolite levels between the DKD patients and the controls and explored the source of heterogeneity through subgroup analyses, sensitivity analysis and meta-regression analysis.

RESULTS

The 34 clinical-based metabolomics studies clarified the differential metabolites between DKD and controls, containing 4503 control subjects and 1875 patients with DKD. The results showed that a total of 60 common differential metabolites were found in both meta-analyses, of which 5 metabolites (p < 0.05) were identified as essential metabolites. Compared with the control group, metabolites glycine, aconitic acid, glycolic acid and uracil decreased significantly in DKD patients; cysteine was significantly higher. This indicates that amino acid metabolism, lipid metabolism and pyrimidine metabolism in DKD patients are disordered.

CONCLUSIONS

We have identified 5 metabolites and metabolic pathways related to DKD which can serve as biomarkers or targets for disease prevention and drug therapy.

Intestinal microbiota and metabolome perturbations in ischemic and idiopathic dilated cardiomyopathy

BACKGROUND

Various clinical similarities are present in ischemic (ICM) and idiopathic dilated cardiomyopathy (IDCM), leading to ambiguity on some occasions. Previous studies have reported that intestinal microbiota appeared dysbiosis in ICM, whether implicating in the IDCM remains unclear. The aim of this study was to assess the alterations in intestinal microbiota and fecal metabolites in ICM and IDCM.

METHODS

ICM (n = 20), IDCM (n = 22), and healthy controls (HC, n = 20) were enrolled in this study. Stool samples were collected for 16S rRNA gene sequencing and gas chromatography-mass spectrometry (GC-MS) analysis.

RESULTS

Both ICM and IDCM exhibited reduced alpha diversity and altered microbial community structure compared to HC. At the genus level, nine taxa including Blautia, [Ruminococcus]_torques_group, Christensenellaceae_R-7_group, UCG-002, Corynebacterium, Oceanobacillus, Gracilibacillus, Klebsiella and Citrobacter was specific to ICM, whereas one taxa Alistipes uniquely altered in IDCM. Likewise, these changes were accompanied by significant metabolic differences. Further differential analysis displayed that 18 and 14 specific metabolites uniquely changed in ICM and IDCM, respectively. The heatmap was generated to display the association between genera and metabolites. Receiver operating characteristic curve (ROC) analysis confirmed the predictive value of the distinct microbial-metabolite features in disease status. The results showed that microbial (area under curve, AUC = 0.95) and metabolic signatures (AUC = 0.84) were effective in discriminating ICM from HC. Based on the specific microbial and metabolic features, the patients with IDCM could be separated from HC with an AUC of 0.80 and 0.87, respectively. Furthermore, the gut microbial genus (AUC = 0.88) and metabolite model (AUC = 0.89) were comparable in predicting IDCM from ICM. Especially, the combination of fecal microbial-metabolic features improved the ability to differentiate IDCM from ICM with an AUC of 0.96.

CONCLUSION

Our findings highlighted the alterations of gut microbiota and metabolites in different types of cardiomyopathies, providing insights into the pathophysiological mechanisms of myocardial diseases. Moreover, multi-omics analysis of fecal samples holds promise as a non-invasive tool for distinguishing disease status.

Composition of gut microbiota and non-alcoholic fatty liver disease: A systematic review and meta-analysis

The present systematic review and meta-analysis aimed to summarize the associations between gut microbiota composition and non-alcoholic fatty liver disease. To compare the differences between individuals with or without NAFLD, the standardized mean difference and 95% confidence interval were computed for each α-diversity index and relative abundance of gut microbes. The β-diversity indices were summarized in a qualitative manner. A total of 54 studies with 8894 participants were included. Overall, patients with NAFLD had moderate reduction in α-diversity indices including Shannon (SMD = -0.36, 95% CI = [-0.53, -0.19], p < 0.001) and Chao 1 (SMD = -0.42, 95% CI = [-0.68, -0.17], p = 0.001), but no significant differences were found for Simpson, observed species, phylogenetic diversity, richness, abundance-based coverage estimator, and evenness (p ranged from 0.081 to 0.953). Over 75% of the included studies reported significant differences in β-diversity. Although there was substantial interstudy heterogeneity, especially for analyses at the phylum, class, and family levels, the majority of the included studies showed alterations in the depletion of anti-inflammatory microbes (i.e., Ruminococcaceae and Coprococcus) and the enrichment of proinflammatory microbes (i.e., Fusobacterium and Escherichia) in patients with NAFLD. Perturbations in gut microbiota were associated with NAFLD, commonly reflected by a reduction in beneficial species and an increase in the pathogenic species.

Enhanced trimethylamine metabolism and gut dysbiosis in type 2 diabetes mellitus with microalbumin

Background

Abnormal gut microbiota and blood trimethylamine-N-oxide (TMAO) metabolome have been reported in patients with type 2 diabetes mellitus (T2DM) and advanced diabetic nephropathy. This study aimed to investigate the gut microbiota profiles and a group of targeted urine metabolic characteristics in T2DM patients with or without microalbuminuria, to determine the correlation between the gut microbiota composition, trimethylamine (TMA) metabolism, and the clinical features during progression of diabetic kidney disease (DKD).

Methods

This study included 26 T2DM patients with microalbuminuria (Micro), 26 T2DM patients with normoalbuminuria (Normo), and 15 healthy controls (HC). Urine and Fecal samples were detected using ultra performance liquid chromatography tandem mass spectrometry and 16S ribosomal DNA gene sequencing, respectively.

Results

The TMAO/TMA ratio decreased gradually during the HC-Normo-Micro transition. The levels of TMA, choline and betaine were significantly different between the HC group and the T2DM patients belonging to both Normo and Micro groups. At the operational taxonomic unit (OTU) level, the gut microflora diversity was significantly reduced in the Micro groups compared to the HC groups and the Normo groups. Taxonomic analyses revealed significant consumption in the relative abundances of eight bacterial genera and significant enrichment of two bacterial genera during the HC-Normo-Micro transition. Furthermore, the relative abundances of six bacterial genera, namely, Ruminococcus_1, [Eubacterium]_ruminantium_group, Roseburia, Faecalibacterium, Fusicatenibacter and Coprococcus_3 exhibited significant differences, and were associated with elevated urinary albumin creatinine ratio (UACR), TMAO/TMA, TMA and its precursors in the Micro group compared with the other groups.

Conclusion

The imbalance of gut microbiota has occurred in patients with early-stage DKD, and the consumption of short-chain fatty acid-producing bacteria were associated with the accumulation of TMA and UACR.

The Dose-Response Effect of Fluoride Exposure on the Gut Microbiome and Its Functional Pathways in Rats

Metabolic activities within the gut microbiome are intimately linked to human health and disease, especially within the context of environmental exposure and its potential ramifications. Perturbations within this microbiome, termed "gut microbiome perturbations", have emerged as plausible intermediaries in the onset or exacerbation of diseases following environmental chemical exposures, with fluoride being a compound of particular concern. Despite the well-documented adverse impacts of excessive fluoride on various human physiological systems-ranging from skeletal to neurological-the nuanced dynamics between fluoride exposure, the gut microbiome, and the resulting dose-response relationship remains a scientific enigma. Leveraging the precision of 16S rRNA high-throughput sequencing, this study meticulously examines the ramifications of diverse fluoride concentrations on the gut microbiome's composition and functional capabilities within Wistar rats. Our findings indicate a profound shift in the intestinal microbial composition following fluoride exposure, marked by a dose-dependent modulation in the abundance of key genera, including Pelagibacterium, Bilophila, Turicibacter, and Roseburia. Moreover, discernible alterations were observed in critical functional and metabolic pathways of the microbiome, such as D-lyxose ketol-isomerase and DNA polymerase III subunit gamma/tau, underscoring the broad-reaching implications of fluoride exposure. Intriguingly, correlation analyses elucidated strong associations between specific bacterial co-abundance groups (CAGs) and these shifted metabolic pathways. In essence, fluoride exposure not only perturbs the compositional equilibrium of the gut microbiota but also instigates profound shifts in its metabolic landscape. These intricate alterations may provide a mechanistic foundation for understanding fluoride's potential toxicological effects mediated via gut microbiome modulation.

The potential mechanism of gut microbiota-microbial metabolites-mitochondrial axis in progression of diabetic kidney disease

Diabetic kidney disease (DKD), has become the main cause of end-stage renal disease (ESRD) worldwide. Lately, it has been shown that the onset and advancement of DKD are linked to imbalances of gut microbiota and the abnormal generation of microbial metabolites. Similarly, a body of recent evidence revealed that biological alterations of mitochondria ranging from mitochondrial dysfunction and morphology can also exert significant effects on the occurrence of DKD. Based on the prevailing theory of endosymbiosis, it is believed that human mitochondria originated from microorganisms and share comparable biological characteristics with the microbiota found in the gut. Recent research has shown a strong correlation between the gut microbiome and mitochondrial function in the occurrence and development of metabolic disorders. The gut microbiome's metabolites may play a vital role in this communication. However, the relationship between the gut microbiome and mitochondrial function in the development of DKD is not yet fully understood, and the role of microbial metabolites is still unclear. Recent studies are highlighted in this review to examine the possible mechanism of the gut microbiota-microbial metabolites-mitochondrial axis in the progression of DKD and the new therapeutic approaches for preventing or reducing DKD based on this biological axis in the future.

Clinical Perspectives of Gut Microbiota in Patients with Chronic Kidney Disease and End-Stage Kidney Disease: Where Do We Stand?

The gut microbiota (GM) plays a vital role in human health, with increasing evidence linking its imbalance to chronic kidney disease and end-stage kidney disease. Although the exact methods underlying kidney-GM crosstalk are not fully understood, interventions targeting GM were made and lay in three aspects: diagnostic, predictive, and therapeutic interventions. While these interventions show promising results in reducing uremic toxins and inflammation, challenges remain in the form of patient-specific GM variability, potential side effects, and safety concerns. Our understanding of GMs role in kidney disease is still evolving, necessitating further research to elucidate the causal relationship and mechanistic interactions. Personalized interventions focusing on specific GM signatures could enhance patient outcomes. However, comprehensive clinical trials are needed to validate these approaches' safety, efficacy, and feasibility.

The roles of gut microbiota and its metabolites in diabetic nephropathy

Diabetic nephropathy (DN) is a severe microvascular complication of diabetes, which increases the risk of renal failure and causes a high global disease burden. Due to the lack of sustainable treatment, DN has become the primary cause of end-stage renal disease worldwide. Gut microbiota and its metabolites exert critical regulatory functions in maintaining host health and are associated with many pathogenesis of aging-related chronic diseases. Currently, the theory gut-kidney axis has opened a novel angle to understand the relationship between gut microbiota and multiple kidney diseases. In recent years, accumulating evidence has revealed that the gut microbiota and their metabolites play an essential role in the pathophysiologic processes of DN through the gut-kidney axis. In this review, we summarize the current investigations of gut microbiota and microbial metabolites involvement in the progression of DN, and further discuss the potential gut microbiota-targeted therapeutic approaches for DN.

The Effects of Specific Gut Microbiota and Metabolites on IgA Nephropathy-Based on Mendelian Randomization and Clinical Validation

BACKGROUND

Although recent research suggests that alterations in gut microbiota and metabolites play a critical role in the pathophysiology of immunoglobulin A nephropathy (IgAN), the causal relationship between specific intestinal flora and metabolites and the risk of IgAN remains unclear.

METHOD

This study employed Mendelian randomization (MR) to investigate the causal association between gut microbiota and IgAN. To explore potential associations between gut microbiota and various outcomes, four MR methods were applied: inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. If the results of the four methods are inconclusive, we prefer the IVW as the primary outcome. Additionally, MR-Egger, MR-PRESSO-Global, and Cochrane's Q tests were used to detect heterogeneity and pleiotropy. The stability of MR findings was assessed using the leave-one-out approach, and the strength of the causal relationship between exposure and outcome was tested using Bonferroni correction. Additional clinical samples were utilized to validate the results of Mendelian randomization, and the outcomes were visualized through an ROC curve, confusion matrix, and correlation analysis.

RESULT

This study examined a total of 15 metabolites and 211 microorganisms. Among them, eight bacteria and one metabolite were found to be associated with the risk of IgAN (p < 0.05). The Bonferroni-corrected test reveals that only Class. Actinobacteria (OR: 1.20, 95% CI: 1.07-1.36, p = 0.0029) have a significant causal relationship with IgAN. According to Cochrane's Q test, there is no substantial heterogeneity across different single-nucleotide polymorphisms (p > 0.05). Furthermore, MR-Egger and MR-PRESSO-Global tests (p > 0.05) showed no evidence of pleiotropy. No reverse causal association was found between the risk of IgAN and microbiota or metabolites (p > 0.05). Clinical specimens demonstrated the effectiveness and accuracy of Actinobacteria in distinguishing IgAN patients from those with other glomerular diseases (AUC = 0.9, 95% CI: 0.78-1.00). Additionally, our correlation analysis revealed a potential association between Actinobacteria abundance and increased albuminuria (r = 0.85) and poorer prognosis in IgAN patients (p = 0.01).

CONCLUSION

Through MR analysis, we established a causal link between Actinobacteria and the incidence of IgAN. Moreover, clinical validation using fecal samples indicated that Actinobacteria might be associated with the onset and poorer prognosis of IgAN. This finding could provide valuable biomarkers for early, noninvasive detection of the disease and potential therapeutic targets in IgAN.

Abelmoschus Manihot ameliorates the levels of circulating metabolites in diabetic nephropathy by modulating gut microbiota in non-obese diabetes mice

Huangkui capsule (HKC), a traditional Chinese medicine, has been used for medication of kidney diseases, including diabetic nephropathy (DN). The current study aimed to evaluate the effects of HKC in the modulation of gut microbiota and the amelioration of metabolite levels by using non-obese diabetes (NOD) mice with DN. The microbiota from three parts of intestines (duodenum, ileum and colon) in NOD mice with and without HKC treatment were analysed using 16S rDNA sequencing techniques. Untargeted metabolomics in plasma of NOD mice were analysed with liquid mass spectrometry. Results showed that HKC administration ameliorated DN in NOD mice and the flora in duodenum were more sensitive to HKC intervention, while the flora in colon had more effects on metabolism. The bacterial genera such as Faecalitalea and Muribaculum significantly increased and negatively correlated with most of the altered metabolites after HKC treatment, while Phyllobacterium, Weissella and Akkermansia showed an opposite trend. The plasma metabolites, mainly including amino acids and fatty acids such as methionine sulfoxide, BCAAs and cis-7-Hexadecenoic acid, exhibited a distinct return to normal after HKC treatment. The current study thereby provides experimental evidence suggesting that HKC may modulate gut microbiota and subsequently ameliorate the metabolite levels in DN.

Gut microbiota and its metabolites - molecular mechanisms and management strategies in diabetic kidney disease

Diabetic kidney disease (DKD) is one of the major microvascular complications of diabetes mellitus and is also one of the serious risk factors in cardiovascular events, end-stage renal disease, and mortality. DKD is associated with the diversified, compositional, and functional alterations of gut microbiota. The interaction between gut microbiota and host is mainly achieved through metabolites, which are small molecules produced by microbial metabolism from exogenous dietary substrates and endogenous host compounds. The gut microbiota plays a critical role in the pathogenesis of DKD by producing multitudinous metabolites. Nevertheless, detailed mechanisms of gut microbiota and its metabolites involved in the occurrence and development of DKD have not been completely elucidated. This review summarizes the specific classes of gut microbiota-derived metabolites, aims to explore the molecular mechanisms of gut microbiota in DKD pathophysiology and progression, recognizes biomarkers for the screening, diagnosis, and prognosis of DKD, as well as provides novel therapeutic strategies for DKD.

Association of the gut microbiome with kidney function and damage in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

BACKGROUND

The gut microbiome is altered in chronic kidney disease (CKD), potentially contributing to CKD progression and co-morbidities, but population-based studies of the gut microbiome across a wide range of kidney function and damage are lacking.

METHODS

In the Hispanic Community Health Study/Study of Latinos, gut microbiome was assessed by shotgun sequencing of stool (n = 2,438; 292 with suspected CKD). We examined cross-sectional associations of estimated glomerular filtration rate (eGFR), urinary albumin:creatinine (UAC) ratio, and CKD with gut microbiome features. Kidney trait-related microbiome features were interrogated for correlation with serum metabolites (n = 700), and associations of microbiome-related serum metabolites with kidney trait progression were examined in a prospective analysis (n = 3,635).

RESULTS

Higher eGFR was associated with overall gut microbiome composition, greater abundance of species from Prevotella, Faecalibacterium, Roseburia, and Eubacterium, and microbial functions related to synthesis of long-chain fatty acids and carbamoyl-phosphate. Higher UAC ratio and CKD were related to lower gut microbiome diversity and altered overall microbiome composition only in participants without diabetes. Microbiome features related to better kidney health were associated with many serum metabolites (e.g., higher indolepropionate, beta-cryptoxanthin; lower imidazole propionate, deoxycholic acids, p-cresol glucuronide). Imidazole propionate, deoxycholic acid metabolites, and p-cresol glucuronide were associated with prospective reductions in eGFR and/or increases in UAC ratio over ~6 y.

CONCLUSIONS

Kidney function is a significant correlate of the gut microbiome, while the relationship of kidney damage with the gut microbiome depends on diabetes status. Gut microbiome metabolites may contribute to CKD progression.

The role and mechanism of the gut microbiota in the development and treatment of diabetic kidney disease

Diabetic kidney disease (DKD) is a common complication in patients with diabetes mellitus (DM). Increasing evidence suggested that the gut microbiota participates in the progression of DKD, which is involved in insulin resistance, renin-angiotensin system (RAS) activation, oxidative stress, inflammation and immunity. Gut microbiota-targeted therapies including dietary fiber, supplementation with probiotics or prebiotics, fecal microbiota transplantation and diabetic agents that modulate the gut microbiota, such as metformin, glucagon-like peptide-1 (GLP-1) receptor agonists, dipeptidyl peptidase-4 (DPP-4) inhibitors, and sodium-glucose transporter-2 (SGLT-2) inhibitors. In this review, we summarize the most important findings about the role of the gut microbiota in the pathogenesis of DKD and the application of gut microbiota-targeted therapies.

Sacubitril/Valsartan contributes to improving the diabetic kidney disease and regulating the gut microbiota in mice

Background

Diabetic kidney disease (DKD), as a serious microvascular complication of diabetes, has limted treatment options. It is reported that the Sacubitril/Valsartan (Sac/Val) can improve kidney function, and the disordered gut microbiota and part of its metabolites are related to the development of DKD. Therefore, we aim to explore whether the effect of Sac/Val on DKD is associated with the gut microbiota and related plasma metabolic profiles.

Methods

Male C57BL/6J mice were randomly divided into 3 groups: Con group (n = 5), DKD group (n = 6), and Sac/Val group (n = 6) . Sac/Val group was treated with Sac/Val solution. The intervention was given once every 2 days for 6 weeks. We measured the blood glucose and urine protein level of mice at different times. We then collected samples at the end of experiment for the 16s rRNA gene sequencing analysis and the untargeted plasma metabonomic analysis.

Results

We found that the plasma creatinine concentration of DKD-group mice was significantly higher than that of Con-group mice, whereas it was reduced after the Sac/Val treatment. Compared with DKD mice, Sac/Val treatment could decrease the expression of indicators related to EndMT and renal fibrosis like vimentin, collagen IV and fibronectin in kidney. According to the criteria of LDA ≥ 2.5 and p<0.05, LefSe analysis of gut microbiota identified 13 biomarkers in Con group, and 33 biomarkers in DKD group, mainly including Prevotella, Escherichia_Shigella and Christensenellaceae_R_7_group, etc. For the Sac/Val group, there were 21 biomarkers, such as Bacteroides, Rikenellaceae_RC9_gut_group, Parabacteroides, Lactobacillus, etc. Plasma metabolomics analysis identified a total of 648 metabolites, and 167 important differential metabolites were screened among groups. KEGG pathway of tryptophan metabolism: M and bile secretion: OS had the highest significance of enrichment.

Conclusions

Sac/Val improves the renal function of DKD mice by inhibiting renal fibrosis. This drug can also regulate gut microbiota in DKD mice.

Specific alterations of gut microbiota in diabetic microvascular complications: A systematic review and meta-analysis

BACKGROUND

The role of gut microbiota in diabetes mellitus (DM) and its complications has been widely accepted. However, the alternation of gut microbiota in diabetic microvascular complications (DC) remains to be determined.

METHODS

Publications (till August 20th, 2022) on gut microbiota in patients with DC were retrieved from PubMed, Web of Science, Embase and Cochrane. Review Manager 5.3 was performed to estimate the standardized mean difference (SMD) and 95% confidence interval (CI) and calculate alpha diversity indices and the relative abundance of gut microbiota between patients in DC v.s. DM and DC v.s. healthy controls (HC).

RESULTS

We included 13 studies assessing 329 patients with DC, 232 DM patients without DC, and 241 HC. Compared to DM, patients with DC shared a significantly lower Simpson index (SMD = -0.59, 95% CI [-0.82, -0.36], p < 0.00001), but a higher ACE index (SMD = 0.42, 95% CI[0.11, 0.74], p = 0.009). Compared to HC, DC patients held a lower ACE index (SMD = -0.61, 95% CI[-1.20, -0.02], p = 0.04). The relative abundances of phylum Proteobacteria (SMD = 0.03, 95% CI[0.01, 0.04], p = 0.003, v.s. HC) and genus Klebsiella (SMD = 0.00, 95% CI[0.00, 0.00], p < 0.00001, v.s. HC) were enriched, accompanying with depleted abundances of phylum Firmicutes (SMD = -0.06, 95% CI[-0.11, -0.01], p = 0.02, v.s. HC), genera Bifidobacterium (SMD = -0.01, 95% CI[-0.02,-0.01], p < 0.0001, v.s. DM), Faecalibacterium (SMD = -0.01, 95% CI[-0.02, -0.00], p = 0.009, v.s. DM; SMD = -0.02, 95% CI[-0.02, -0.01], p < 0.00001, v.s. HC) and Lactobacillus (SMD = 0.00, 95% CI[-0.00, -0.00], p < 0.00001, v.s. HC) in DC.

CONCLUSIONS

Gut microbiota perturbations with the depletion of alpha diversity and certain short-chain fatty acids (SCFAs)-producing bacteria were associated with the pathology of DC. Therefore, gut microbiota might serve as a promising approach for the diagnosis and treatment of DC. Further investigations are required to study the mechanisms by which gut dysbiosis acts on the onset and progression of DC.

Ginsenoside Compound K Ameliorates Development of Diabetic Kidney Disease through Inhibiting TLR4 Activation Induced by Microbially Produced Imidazole Propionate

Diabetic kidney disease (DKD) is a common and devastating complication in diabetic patients, which is recognized as a large and growing problem leading to end-stage kidney disease. As dietary-mediated therapies are gradually becoming more acceptable to patients with DKD, we planned to find active compounds on preventing DKD progression from dietary material. The present paper reports the renoprotective properties and underlying mechanisms of ginsenoside compound K (CK), a major metabolite in serum after oral administration of ginseng. CK supplementation for 16 weeks could improve urine microalbumin, the ratio of urinary albumin/creatinine and renal morphological abnormal changes in db/db mice. In addition, CK supplementation reshaped the gut microbiota by decreasing the contents of Bacteroides and Paraprevotella and increasing the contents of Lactobacillu and Akkermansia at the genus level, as well as reduced histidine-derived microbial metabolite imidazole propionate (IMP) in the serum. We first found that IMP played a significant role in the progression of DKD through activating toll-like receptor 4 (TLR4). We also confirmed CK supplementation can down-regulate IMP-induced protein expression of the TLR4 signaling pathway in vivo and in vitro. This study suggests that dietary CK could offer a better health benefit in the early intervention of DKD. From a nutrition perspective, CK or dietary material containing CK can possibly be developed as new adjuvant therapy products for DKD.

To do one and to get more: Part I. Diabetes and bone

Type 2 diabetes mellitus (T2DM), is a chronic metabolic disease, characterized by the presence of hyperglycemia and insulin resistance. The key treatment strategies for T2DM include modification of lifestyle, medications, and continuous glucose monitoring. DM patients often have DM-associated morbidities and comorbidities; however, disorders of musculoskeletal system are often neglected, compared to other major systems in DM patients. Based on sharing similar pathophysiology of DM and osteoporosis, it is supposed that the use of antidiabetic agents (ADAs) may not only provide the lowering glucose level effect and the maintenance of the sugar homeostasis to directly delay the tissue damage secondary to hyperglycemia but also offer the benefits, such as the prevention of developing osteoporosis and fractures. Based on the current review, evidence shows the positive correlation between DM and osteoporosis or fracture, but the effectiveness of using ADA in the prevention of osteoporosis and subsequent reduction of fracture seems to be inconclusive. Although the benefits of ADA on bone health are uncertain, the potential value of "To do one and to get more" therapeutic strategy should be always persuaded. At least, one of the key treatment strategies as an establishment of healthy lifestyle may work, because it improves the status of insulin resistance and subsequently helps DM control, prevents the DM-related micro- and macrovascular injury, and possibly strengthens the general performance of musculoskeletal system. With stronger musculoskeletal system support, the risk of "fall" may be decreased, because it is associated with fracture. Although the ADA available in the market does not satisfy the policy of "To do one and to get more" yet, we are looking forward to seeing the continuously advanced technology of drug development on diabetic control, and hope to see their extra-sugar-lowering effects.

A systematic review and meta-analysis of gut microbiota in diabetic kidney disease: Comparisons with diabetes mellitus, non-diabetic kidney disease, and healthy individuals

BACKGROUND

Gut microbiota has been reported to play an important role in diabetic kidney disease (DKD), however, the alterations of gut bacteria have not been determined.

METHODS

Studies comparing the differences of gut microbiome between patients with DKD and non-DKD individuals using high-throughput sequencing technology, were systematically searched and reviewed. Outcomes were set as gut bacterial diversity, microbial composition, and correlation with clinical parameters of DKD. Qualitative data were summarized and compared through a funnel R script, and quantitative data were estimated by meta-analysis.

RESULTS

A total of 15 studies and 1640 participants were included, the comparisons were conducted between DKD, diabetes mellitus (DM), non-diabetic kidney disease (NDKD), and healthy controls. There were no significant differences of α-diversity between DKD and DM, and between DKD and NDKD, however, significant lower microbial richness was found in DKD compared to healthy controls. Different bacterial compositions were found between DKD and non-DKD subjects. The phylum Actinobacteria were found to be enriched in DKD compared to healthy controls. At the genus level, we found the enrichment of Hungatella, Bilophila, and Escherichia in DKD compared to DM, patients with DKD showed lower abundances of Faecalibacterium compared to those with NDKD. The genera Butyricicoccus, Faecalibacterium, and Lachnospira were depleted in DKD compared to healthy controls, whereas Hungatella, Escherichia, and lactobacillus were significantly enriched. The genus Ruminococcus torques group was demonstrated to be inversely correlated with estimated glomerular filtration rate of DKD.

CONCLUSIONS

Gut bacterial alterations was demonstrated in DKD, characterized by the enrichment of the genera Hungatella and Escherichia, and the depletion of butyrate-producing bacteria, which might be associated with the occurrence and development of DKD. Further studies are still needed to validate these findings, due to substantial heterogeneity.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42022340870.