Genetic evidence supporting the causal role of gut microbiota in chronic kidney disease and chronic systemic inflammation in CKD: a bilateral two-sample Mendelian randomization study

Association between the aggregate index of systemic inflammation and CKD: evidence from NHANES 1999-2018

Purpose

We aimed to investigate the potential association between the aggregate index of systemic inflammation (AISI) and chronic kidney disease (CKD).

Patients and methods

This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. CKD was defined as either an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or the presence of albuminuria, defined as a urine albumin-to-creatinine ratio (ACR) of 30 mg/g or higher. Low eGFR is an eGFR of less than 60 mL/min/1.73 m2. Multivariate regression analysis, smoothed curve fitting, and subgroup analyses were conducted to investigate the relationship between the Inflammatory status index (AISI) and CKD. The receiver operating characteristic (ROC) curve analysis was used to evaluate its ability to identify CKD and low eGFR. The AISI was transformed using the natural logarithm (Ln) for statistical analysis.

Results

Of the 50,768 recruits, 49.86% were male. The prevalence of CKD and low eGFR was 20.31% and 8.57%, respectively. Ln-AISI was positively associated with CKD (OR = 1.24; 95% CI: 1.19, 1.28) and low eGFR (OR = 1.17; 95% CI:1.11, 1.24). Smooth curve fitting revealed a positive association between AISI and CKD and low eGFR. Subgroup analysis and interaction tests indicated that stratifications did not significantly alter the association between AISI and CKD and low eGFR. Threshold effect analysis indicated that this relationship became more pronounced when Ln-AISI exceeded 5.2 (AISI > 181.27). The ROC analysis showed that AISI had better discrimination and accuracy for identifying CKD and low eGFR compared to other inflammatory indicators [lymphocyte count (LYM), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and the product of platelet count and neutrophil count (PPN)].

Conclusion

AISI was significantly and positively correlated with the prevalence of CKD, and this relationship was more potent when AISI was greater than 181.27. Compared with other inflammatory indicators, AISI was more effective in identifying CKD.

Investigating the role of gut microbiota in diabetic nephropathy through plasma proteome mediated analysis

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease and poses significant threats to individuals with diabetes. The concept of gut-kidney axis has gained increasing attention in recent years and the in the occurrence and development of DN, alterations in the gut microbiota also plays a crucial and indispensable role. However, the specific causal relationships between various gut microbial communities and DN, as well as the underlying molecular mechanisms, remains unclear. This study utilized data from genome-wide association studies. After screening for qualified instrumental variables, mendelian randomization causal analyses were performed by inverse variance weighting, MR-Egger, weighted median, weighted mode and MR-RAPS methods. Additionally, sensitivity analyses such as heterogeneity, multiplicity, and the direction of the causal effect were carried out to ensure that the results were robust. After identifying significant gut microbiota, protein-proteomics mediation analysis was conducted on potential 3282 plasma proteins to determine those with mediating effects. Finally, Reactome enrichment analysis was performed to ascertain metabolic or signaling pathways with mediating effects. Mendelian randomization analysis indicated associations between 21 gut microbiota and DN. After adjusting significance levels, Catenibacterium and Parasutterella were found to have causal effects on the onset of DN. Subsequently, we identified 22 plasma proteins with mediating effects, along with 27 metabolic or signaling pathways including activated propionic acid metabolism. Increased in the abundance of Catenibacterium and Parasutterella intestinal bacteria are causative factors for DN. More importantly, the underlying mechanism by which the increased abundance of Catenibacterium and Parasutterella intestinal bacteria lead to DN were revealed, providing a blueprint for the involvement of gut-kidney axis in the pathogenesis of DN and paving the way for future studies.

Total alkaloids of Aconitum carmichaelii Debx alleviate cisplatin-induced acute renal injury by inhibiting inflammation and oxidative stress related to gut microbiota metabolism

BACKGROUND

Cisplatin-induced acute kidney injury (AKI) is a complex and serious clinical issue, representing a major cause of hospital-acquired AKI. Alkaloids are the main active constituents of Aconitum carmichaelii Debx, which exhibit protective effects in several kidney disease models and against other acute organ injuries. However, its activity and mechanism of action in AKI treatment remain unclear.

PURPOSE

This study aimed to elucidate the effect of Aconitum carmichaelii Debx (ACA) in a model of cisplain-induced AKI and comprehensively investigate its underlying mechanisms.

METHODS

The major alkaloids in ACA were analyzed using high-performance liquid chromatography. Blood urea nitrogen (BUN) and serum creatine levels were measured using automated biochemical instruments. 16S rRNA sequencing, short-chain fatty acid (SCFA) analysis, fecal microbiota transplantation (FMT), non-targeted metabolomics, and transcriptomics were performed to systematically identify prospective biomarkers after ACA treatment. Anti-inflammatory and anti-oxidative stress activities were monitored using ELISA and western blotting.

RESULTS

Four main compounds (fuziline, neoline, talatisamine, and songorine) were identified in ACA. ACA significantly alleviated cisplatin-induced AKI by reducing (BUN) and serum creatine levels and improving histopathological scores. Moreover, ACA balanced cisplatin-mediated confoundments in microbial composition and function, including decreasing the levels of Escherichia-Shigella, Clostridium, and Ruminococcus, as well as increasing Ligilactobacillus, Anaerotruncus, Bacteroides and Desulfovibrio levels, accompanied by uremic toxin reduction, and augmenting serum SCFAs. The FMT experiments further confirmed that ACA exerts anti-AKI effects by affecting gut microbiota. A multi-omics study has shown that ACA regulates glutathione and tryptophan metabolism and mediates pathways that trigger inflammatory responses. Finally, ACA reduced serum levels of inflammatory factors (IL-1β, IL-6, and TNF-α), restored enzymes of the antioxidative system (SOD and CAT) and GSH values, and decreased monoester diterpene alkaloid levels in the kidney by inhibiting the expression of NF-κB pathway-related proteins and increasing Nrf2/HO-1 pathway-related protein expression.

CONCLUSION

ACA protects against cisplatin-induced AKI through its anti-inflammatory and antioxidant functions, which may be associated with the restoration of gut microbiota metabolism. ACA is a potential drug for AKI and other forms of organ damage related to the disruption of the gut microbiota.

Effect of konjac glucomannan on gut microbiota from hyperuricemia subjects in vitro: fermentation characteristics and inhibitory xanthine oxidase activity

Background

The disorder of uric acid metabolism is closely associated with gut microbiota and short-chain fatty acids (SCFAs) dysregulation, but the biological mechanism is unclear, limiting the development of uric acid-lowering active polysaccharides. Konjac glucomannan (KGM) could attenuate metabolic disturbance of uric acid and modulate the gut microbiota. However, the relationship between uric acid metabolism and gut microbiota is still unknown.

Methods

In this study, The fecal samples were provided by healthy volunteers and hyperuricemia (HUA) patients. Fecal samples from healthy volunteers was regarded as the NOR group. Similarly, 10% HUA fecal suspension was named as the HUA group. Then, fecal supernatant was inoculated into a growth basal medium containing glucose or KGM, and healthy fecal samples were designated as the NOR-GLU and NOR-KGM groups, while HUA fecal samples were designated as the HUA-GLU and HUA-KGM groups. All samples were cultured in an anaerobic bag system. After fermentation for 24 h, the samples were collected for further analysis of composition of intestinal microbiota, SCFAs concentration and XOD enzyme activity.

Results

The results showed that KGM could be utilized and degraded by the gut microbiota from HUA subjects, and it could modulate the composition and structure of their HUA gut microbiota to more closely resemble that of a healthy group. In addition, KGM showed a superior modulated effect on HUA gut microbiota by increasing Megasphaera, Faecalibacterium, Lachnoclostridium, Lachnospiraceae, Anaerostipes, and Ruminococcus levels and decreasing Butyricicoccus, Eisenbergiella, and Enterococcus levels. Furthermore, the fermentation solution of KGM showed an inhibitory effect on xanthine oxidase (XOD) enzyme activity, which might be due to metabolites such as SCFAs.

Conclusion

In conclusion, the effect of KGM on hyperuricemia subjects was investigated based on the gut microbiota in vitro. In the present study. It was found that KGM could be metabolized into SCFAs by HUA gut microbiota. Furthermore, KGM could modulate the structure of HUA gut microbiota. At the genus level, KGM could decrease the relative abundances of Butyricicoccus, Eisenbergiella, and Enterococcus, while Lachnoclostridium and Lachnospiraceae in HUA gut microbiota were significantly increased by the addition of KGM. The metabolites of gut microbiota, such as SCFAs, might be responsible for the inhibition of XOD activity. Thus, KGM exhibited a superior probiotic function on the HUA gut microbiota, which is expected as a promising candidate for remodeling the HUA gut microbiota.

Is the enteric nervous system a lost piece of the gut-kidney axis puzzle linked to chronic kidney disease?

The enteric nervous system (ENS) regulates numerous functional and immunological attributes of the gastrointestinal tract. Alterations in ENS cell function have been linked to intestinal outcomes in various metabolic, intestinal, and neurological disorders. Chronic kidney disease (CKD) is associated with a challenging intestinal environment due to gut dysbiosis, which further affects patient quality of life. Although the gut-related repercussions of CKD have been thoroughly investigated, the involvement of the ENS in this puzzle remains unclear. ENS cell dysfunction, such as glial reactivity and alterations in cholinergic signaling in the small intestine and colon, in CKD are associated with a wide range of intestinal pathways and responses in affected patients. This review discusses how the ENS is affected in CKD and how it is involved in gut-related outcomes, including intestinal permeability, inflammation, oxidative stress, and dysmotility.

Association of methyl donor nutrients dietary intake and sleep disorders in the elderly revealed by the intestinal microbiome

Currently, sleep disorders (SD) in the elderly are gaining prominence globally and are becoming a significant public health concern. Methyl donor nutrients (MDNs), such as vitamin B6, vitamin B12, folate, and choline, have been reported to have the potential to improve sleep disorders. Moreover, MDNs help to maintain gut flora homeostasis, and are closely associated with the development of SD. Nevertheless, there has been a lack of comprehensive human studies examining the association between MDNs intake and SD. In our study, we comprehensively evaluated the association between MDNs intake and SD in the elderly and used 16S rRNA gene sequencing to explore the underlying mechanism. We found that the SD group (n = 91) had a lower methyl-donor nutritional quality index (MNQI) and a trend toward lower intake compared to the control group (n = 147). Based on the intestinal microbiome, the beta diversity of the intestinal flora was higher in the high methyl-donor nutritional quality (HQ) group compared to the low methyl-donor nutritional quality (LQ) group, and it was lower in the SD group compared to the control group. This suggests that MDNs may regulate sleep by modulating the abundance distribution of the microbiota. Subsequently, we performed correlation analyses between the relative abundance of the microbiota, MDNs intake, and the Pittsburgh Sleep Quality Index (PSQI), identifying five genera with potential regulatory roles. The KEGG pathway analysis indicated that energy metabolism and one-carbon metabolism might be the pathways through which MDNs modulate sleep. This study offers dietary guidance strategies for managing SD in the elderly and provides insights for targeted microbiota intervention.

Causal associations of gut microbiota and pulmonary tuberculosis: a two-sample Mendelian randomization study

Background

The prevalence of pulmonary tuberculosis (PTB) as an infectious disease continues to contribute significantly to global mortality. According to recent studies, the gut microbiota of PTB patients and healthy controls (HCs) show significant disparities. However, the causal relationship between them has yet to be elucidated.

Methods

We conducted a study using Mendelian Randomization (MR) to explore the potential causal link between gut microbiota and pulmonary tuberculosis (PTB). The summary statistics of the gut microbiota were acquired from the MiBioGen consortium, while data on PTB were sourced from pheweb.jp. A range of statistical methodologies were employed to evaluate causality, encompassing inverse variance weighting (IVW), MR-Egger, weighted median (WM), weighted model, and simple model. We utilized instrumental variables (IVs) that have a direct causal relationship with PTB to annotate SNPs, aiming to discover the genes harboring these genetic variants and uncover potential associations between host genes and the microbiome in patients with PTB.

Results

Among the 196 bacterial traits in the gut microbiome, we have identified a total of three microbiomes that exhibit a significant association with PTB. The occurrence of Dorea (P = 0.0458, FDR-adjusted P = 0.0458) and Parasutterella (P = 0.0056, FDR-adjusted P = 0.0168) was linked to an elevated risk of PTB, while the presence of Lachnoclostridium (P = 0.0347, FDR-adjusted P = 0.0520) demonstrated a protective effect against PTB. Our reverse Two-Sample Mendelian Randomization (TSMR) analysis did not yield any evidence supporting the hypothesis of reverse causality from PTB to alterations in the intestinal flora.

Conclusion

We have established a connection between the gut microbiota and PTB through gene prediction analysis, supporting the use of gut microecological therapy in managing PTB and paving the way for further understanding of how gut microbiota contributes to PTB's development.

The causal relationship between the gut microbiota and acute pancreatitis: A 2-sample Mendelian randomization study

Several observational studies have reported a correlation between the gut microbiota (GM) and the risk of acute pancreatitis (AP). However, the causal relationship between them remains uncertain. We conducted a 2-sample Mendelian randomization (MR) study using pooled data from genome-wide association studies of 211 taxa (131 genera, 35 families, 20 orders, 16 classes, and 9 phyla) and AP patients. We evaluated the causal relationship between the GM and AP using methods such as inverse-variance weighting, MR-Egger, weighted medians, simple mode, and weighted mode. Cochran Q test, MR-Egger regression intercept analysis, and MR-PRESSO were used to examine the heterogeneity, multipotency, and outlier values of the variables, respectively. The reverse causal relationship between AP and the GM was assessed with reverse MR. In total, 5 gut microbial taxa were significantly associated with AP. The inverse-variance weighting results indicated that Acidaminococcaceae (odds ratio [OR]: 0.81, 95% confidence interval [CI]: 0.66-1.00, P = .045) and Ruminococcaceae UCG004 (OR: 0.85, 95% CI: 0.72-0.99, P = .040) were protective factors against the occurrence of AP. Coprococcus 3 (OR: 1.32, 95% CI: 1.03-1.70, P = .030), Eisenbergiella (OR: 1.13, 95% CI: 1.00-1.28, P = .043), and the Eubacterium fissicatena group (OR: 1.18, 95% CI: 1.05-1.33, P = .006) were risk factors for the development of AP. A comprehensive sensitivity analysis proved our results to be reliable. Reverse MR analysis did not indicate any causal relationship between AP and the GM. This study revealed a complex causal relationship between 5 GM taxa and AP, providing new insights into the diagnostic and therapeutic potential of the GM in AP patients.

Causal relationship between gut microbiota and chronic renal failure: a two-sample Mendelian randomization study

Background

Observational studies and some experimental investigations have indicated that gut microbiota are closely associated with the incidence and progression of chronic renal failure. However, the causal relationship between gut microbiota and chronic renal failure remains unclear. The present study employs a two-sample Mendelian randomization approach to infer the causal relationship between gut microbiota and chronic renal failure at the genetic level. This research aims to determine whether there is a causal effect of gut microbiota on the risk of chronic renal failure, aiming to provide new evidence to support targeted gut therapy for the treatment of chronic renal failure.

Methods

Employing genome-wide association study (GWAS) data from the public MiBioGen and IEU OpenGWAS platform, a two-sample Mendelian randomization analysis was conducted. The causal relationship between gut microbiota and chronic renal failure was inferred using five different methods: Inverse Variance Weighted, MR-Egger, Weighted Median, Simple Mode, and Weighted Mode. The study incorporated sensitivity analyses that encompassed evaluations for pleiotropy and heterogeneity. Subsequently, the results of the Mendelian randomization analysis underwent a stringent correction for multiple testing, employing the False Discovery Rate method to enhance the validity of our findings.

Results

According to the results from the Inverse Variance Weighted method, seven bacterial genera show a significant association with the outcome variable chronic renal failure. Of these, Ruminococcus (gauvreauii group) (OR = 0.82, 95% CI = 0.71-0.94, p = 0.004) may act as a protective factor against chronic renal failure, while the genera Escherichia-Shigella (OR = 1.22, 95% CI = 1.08-1.38, p = 0.001), Lactococcus (OR = 1.1, 95% CI = 1.02-1.19, p = 0.013), Odoribacter (OR = 1.23, 95% CI = 1.03-1.49, p = 0.026), Enterorhabdus (OR = 1.14, 95% CI = 1.00-1.29, p = 0.047), Eubacterium (eligens group) (OR = 1.18, 95% CI = 1.02-1.37, p = 0.024), and Howardella (OR = 1.18, 95% CI = 1.09-1.28, p < 0.001) may be risk factors for chronic renal failure. However, after correction for multiple comparisons using False Discovery Rate, only the associations with Escherichia-Shigella and Howardella remain significant, indicating that the other genera have suggestive associations. Sensitivity analyses did not reveal any pleiotropy or heterogeneity.

Conclusion

Our two-sample Mendelian randomization study suggests that the genera Escherichia-Shigella and Howardella are risk factors for chronic renal failure, and they may serve as potential targets for future therapeutic interventions. However, the exact mechanisms of action are not yet clear, necessitating further research to elucidate their precise roles fully.

Two-sample Mendelian randomization analysis of 91 circulating inflammatory protein levels and amyotrophic lateral sclerosis

Introduction

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease with poorly understood pathophysiology. Recent studies have highlighted systemic inflammation, especially the role of circulating inflammatory proteins, in ALS.

Methods

This study investigates the potential causal link between these proteins and ALS. We employed a two-sample Mendelian Randomization(MR) approach, analyzing data from large-scale genome-wide association studies to explore the relationship between 91 circulating inflammatory proteins and ALS. This included various MR methods like MR Egger, weighted median, and inverse-variance weighted, complemented by sensitivity analyses for robust results.

Results

Significant associations were observed between levels of inflammatory proteins, including Adenosine Deaminase, Interleukin-17C, Oncostatin-M, Leukemia Inhibitory Factor Receptor, and Osteoprotegerin, and ALS risk. Consistencies were noted across different P-value thresholds. Bidirectional MR suggested that ALS risk might influence levels of certain inflammatory proteins.

Discussion

Our findings, via MR analysis, indicate a potential causal relationship between circulating inflammatory proteins and ALS. This sheds new light on ALS pathophysiology and suggests possible therapeutic targets. Further research is required to confirm these results and understand the specific roles of these proteins in ALS.

Genetic evidence strengthens the bidirectional connection between gut microbiota and Shigella infection: insights from a two-sample Mendelian randomization study

Background

In recent investigations, substantial strides have been made in the precise modulation of the gut microbiota to prevent and treat a myriad of diseases. Simultaneously, the pressing issue of widespread antibiotic resistance and multidrug resistance resulting from Shigella infections demands urgent attention. Several studies suggest that the antagonistic influence of the gut microbiota could serve as a novel avenue for impeding the colonization of pathogenic microorganisms or treating Shigella infections. However, conventional research methodologies encounter inherent challenges in identifying antagonistic microbial agents against Shigella, necessitating a comprehensive and in-depth analysis of the causal relationship between Shigella infections and the gut microbiota.

Materials and methods

Utilizing the aggregated summary statistics from Genome-Wide Association Studies (GWAS), we conducted Mendelian Randomization (MR) analyses encompassing 18,340 participants to explore the interplay between the gut microbiota and Shigella infections. This investigation also involved 83 cases of Shigella infection patients and 336,396 control subjects. In the positive strand of our findings, we initially performed a preliminary analysis using the Inverse Variance Weighting (IVW) method. Subsequently, we undertook sensitivity analyses to assess the robustness of the results, addressing confounding factors' influence. This involved employing the Leave-One-Out method and scrutinizing funnel plots to ensure the reliability of the MR analysis outcomes. Conclusively, a reverse MR analysis was carried out, employing the Wald ratio method due to the exposure of individual Single Nucleotide Polymorphisms (SNPs). This was undertaken to explore the plausible associations between Shigella infections and genetically predicted compositions of the gut microbiota.

Results

In this study, we employed 2,818 SNPs associated with 211 species of gut microbiota as instrumental variables (IVs). Through IVW analysis, our positive MR findings revealed a significant negative correlation between the occurrence of Shigella infections and the phylum Tenericutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), class Mollicutes (OR: 0.18, 95% CI: 0.04-0.74, p = 0.02), genus Intestinimonas (OR: 0.16, 95% CI: 0.04-0.63, p = 0.01), genus Gordonibacter (OR: 0.39, 95% CI: 0.16-0.93, p = 0.03), and genus Butyrivibrio (OR: 0.44, 95% CI: 0.23-0.87, p = 0.02). Conversely, a positive correlation was observed between the occurrence of Shigella infections and genus Sutterella (OR: 10.16, 95% CI: 1.87-55.13, p = 0.01) and genus Alistipes (OR: 12.24, 95% CI: 1.71-87.34, p = 0.01). In sensitivity analyses, utilizing MR-Egger regression analysis and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) detection, all outcomes demonstrated robust stability. Simultaneously, in the reverse MR analysis, Shigella infections resulted in an upregulation of four bacterial genera and a downregulation of three bacterial genera.

Conclusion

In summation, the MR analysis outcomes corroborate the presence of bidirectional causal relationships between the gut microbiota and Shigella infections. This study not only unveils novel perspectives for the prevention and treatment of Shigella infections but also furnishes fresh insights into the mechanistic underpinnings of how the gut microbiota contributes to the pathogenesis of Shigella infections. Consequently, the established dual causal association holds promise for advancing our understanding and addressing the complexities inherent in the interplay between the gut microbiota and Shigella infections, thereby paving the way for innovative therapeutic interventions and preventive strategies in the realm of Shigella-related diseases.