Causal effects of gut microbiota on the risk of chronic kidney disease: a Mendelian randomization study

Poricoic Acid A Protects Against High-Salt-Diet Induced Renal Fibrosis by Modulating Gut Microbiota and SCFA Metabolism

The gut microbiota serves a critical role in the development of chronic kidney disease (CKD). High salt intake has been known to cause hypertension and CKD, however, it is still unclear whether it also affects gut microbiota in CKD mice. This article first studied the salutary effects of poricoic acid A (PAA), a natural triterpenoid from Poria cocos, on high salt diet-induced CKD in kunming mice. It was demonstrated that the administration of PAA by oral gavage (20 mg/kg·bw) could decrease the kidney index and urinary protein levels, prevent the kidney tubule dilated and renal fibrosis, and activated the expression of adenosine monophosphate-activated protein kinase (AMPK) in kidney. In addition, 16 S rRNA-based microbiota analysis indicated that PAA ameliorated intestinal microbiota dysbiosis caused by high-salt-diet and particularly enhanced the abundances of beneficial microbiota, such as Lactobacillus and Akkermansia, followed by a significant increase in the levels of short-chain fatty acids (SCFAs). Meanwhile, PAA improved intestinal barrier damage and increased the expression of intestinal tight junction protein. In summary, these experiments demonstrated that PAA enhances the growth of probiotics while decreasing the abundance of endotoxin-producing bacteria. This dual action contributes to the amelioration of intestinal mucosal barrier dysfunction and mitigates the impact of a high-salt diet on renal interstitial fibrosis in mice.

Characterization of gut microbiota and metabolites in renal transplant recipients during COVID-19 and prediction of one-year allograft function

BACKGROUND

The gut-lung-kidney axis is pivotal in immune-related kidney diseases, with gut dysbiosis potentially exacerbating the severity of Coronavirus disease 2019 (COVID-19) in recipients of kidney transplant. This study aimed to characterize the gut microbiome and metabolome in renal transplant recipients with COVID-19 pneumonia over a one-year follow-up period.

METHODS

A total of 30 renal transplant recipients were enrolled, comprising 17 with COVID-19 pneumonia, six with mild COVID-19, and seven without COVID-19. Fecal samples were collected at the onset of infection for gut microbiome and metabolome analysis. Generalized Estimating Equations (GEE) model and Latent Class Growth Mixed Model (LCGMM) were employed to dissect the relationships among clinical characteristics, laboratory tests, and gut microbiota and metabolites.

RESULTS

Four microbial phyla (Deferribacteres, TM7, Fusobacteria, and Gemmatimonadetes) and 13 genera were significantly enriched across three recipients groups, correlating with baseline inflammatory response and allograft function. Additionally, 52 differentially expressed metabolites were identified, with seven significantly correlating with eight altered microbiota genera. LCGMM revealed two distinct classes of recipients, with those suffering from COVID-19 pneumonia exhibiting significantly elevated serum creatinine (Scr) trajectories over the one-year period. GEE further identified 12 genera and 181 metabolites closely associated with these trajectories; a multivariable model incorporating gut metabolites of 1-Caffeoylquinic Acid and PMK was found to effectively predict one-year allograft function.

CONCLUSIONS

Our study indicates a possible interaction between the composition of the gut microbiota and metabolites community and COVID-19 in renal transplant recipients, particularly in relation to disease severity and the prediction of one-year allograft function.

The association between the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio and delirium in ischemic stroke patients

Background

Delirium is a severe neuropsychiatric symptom following acute ischemic stroke (IS) and is associated with poor outcomes. Systemic inflammation and immune dysregulation are believed to contribute to the pathophysiology of delirium. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) are widely recognized as convenient and reliable biomarkers of systemic inflammation. However, their association with delirium after IS remains unclear.

Methods

In this study, we identified IS patients requiring ICU admission from the Medical Information Mart for Intensive Care (MIMIC)-IV database. We employed multivariable logistic regression and restricted cubic splines (RCS) to assess the association between the NLR, PLR, and LMR and delirium. Two-sample Mendelian randomization (MR) analysis was performed to further explore their causal relationship at the genetic level.

Results

A total of 1,436 patients with IS were included in this study, of whom 214 (14.9%) had delirium. In the multivariate logistic regression analysis, after adjustment for confounders, the patients in the highest quartile of the NLR (odds ratio [OR] 2.080, 95% confidence interval [CI], 1.282-3.375) and LMR (OR 0.503, 95% CI 0.317-0.798) and the patients in the second quartile of the PLR (OR 1.574, 95% CI 1.019-2.431) were significantly associated with delirium. The RCS function showed a progressive increase in the risk of delirium with higher NLR and PLR and lower LMR. In the MR analysis, only the PLR was negatively associated with the risk of delirium.

Conclusion

The observational studies found significant associations between the NLR, PLR, and LMR and delirium. However, the MR analysis only demonstrated a potential protective causal relationship between the PLR and delirium. Further prospective studies are needed to validate their association and to elucidate the underlying mechanisms.

Mendelian Randomization Studies: Opening a New Window in the Study of Metabolic Diseases and Chronic Kidney Disease

It is widely recognized that a strong correlation exists between metabolic diseases and chronic kidney disease (CKD). Based on bibliometric statistics, the overall number of Mendelian randomization (MR) analysis in relation to metabolic diseases and CKD has increased since 2005. In recent years, this topic has emerged as a significant area of research interest. In clinical studies, RCTs are often limited due to the intricate causal interplay between metabolic diseases and CKD, which makes it difficult to ascertain the precise etiology of these conditions definitively. In MR studies, genetic variation is incorporated as an instrumental variable (IV). They elucidate the possible causal relationships between associated risk factors and disease risks by including individual innate genetic markers. It is widely believed that MR avoids confounding and can reverse effects to the greatest extent possible. As an increasingly popular technology in the medical field, MR studies have become a popular technology in causal relationships investigation, particularly in epidemiological etiology studies. At present, MR has been widely used for the investigation of medical etiologies, drug development, and decision-making in public health. The article aims to offer insights into the causal relationship between metabolic diseases and CKD, as well as strategies for prevention and treatment, through a summary of MR-related research on these conditions.

Causal role of the pyrimidine deoxyribonucleoside degradation superpathway mediation in Guillain-Barré Syndrome via the HVEM on CD4 + and CD8 + T cells

Immune system regulation is a key indicator of the gut microbiota (GM) influencing disease development. The causal role of the GM in Guillain-Barré syndrome (GBS) and whether it can be mediated by immune cells is unknown. Genome-wide association study (GWAS) summary statistics for the GM were obtained from the Dutch Microbiota Project (n = 7,738) and the FINRISK 2002 (FR02) cohort (n = 5,959). Inverse variance weighting method (IVW) were used as the main method to evaluate the causal relationship between GM and GBS. Subsequently, the mediating effects of 731 immune traits were evaluated. Additionally, we also executed the Bayesian Weighting algorithm for verification. Mendelian randomization (MR) analysis determined the protective effect of the pyrimidine deoxyribonucleoside degradation superpathway on GBS (IVW: P = 0.0019, OR = 0.4508). It is worth noting that in the causal effects of pyrimidine deoxyribonucleoside degradation superpathway on GBS, the mediated proportions of herpesvirus entry mediator (HVEM) ( HVEM on CM CD4 + , HVEM on naive CD4 + , HVEM on CD45RA - CD4 + , HVEM on CM CD8br) in the T cell maturation stage on GBS were -0.0398, -0.0452, -0.0414, -0.0425, accounting for 5.00%, 5.67%, 5.19% and 5.34% of the total effect. 11 types of intestinal bacteria might be involved in the pyrimidine deoxyriboside degradation superpathway, including Staphylococcus A fleurettii, AR31,CAG-274 sp000432155, Photobacterium, Acetobacteraceae, Dysgonomonadaceae, NK4A144,Leptospirae, CAG-81 sp000435795, Leptospirales and CAG-873 sp001701165. This study suggests that there is a causal relationship between pyrimidine deoxyribonucleoside degradation superpathway and GBS, which may be mediated by HVEM on CD4 + and CD8 + T cells. As a bidirectional molecular switch, HVEM plays an important role in T cell regulation. 11 intestinal flora were found to be involved in pyrimidine deoxyribonucleoside degradation superpathway, and their changes may be related to the occurrence of GBS. However, extensive research is still warranted before microbiome sequencing can be used for prevention and targeted treatment of GBS.

Exploring the potential link between gut microbiota and chronic kidney disease in causality: A 2-sample Mendelian randomization study

Increasing evidence indicates a significant correlation between gut microbiota (GM) and susceptibility to chronic kidney disease (CKD). However, causal relationship presence remains uncertain. Mendelian randomization (MR) was applied to evaluate potential causal relation from GM to CKD. Genomic association analysis aggregates publicly online databases, utilizing Genome-Wide Association Study (GWAS) database focused on GM and CKD. For examination of potential causal connection from GM to CKD, a 2-way, 2-sample Mendelian randomization (MR) method was applied. Sensitivity analyses were utilized to scrutinize for heterogeneity, horizontal pleiotropy, MR outcomes resilience. Result from inverse variance weighting (IVW) method revealed that 10 microbiotas such as Porphyromonadaceae (OR = 1.351, 95% CI: 1.114-1.638, P = .002), Dorea (OR = 1.236, 95% CI: 1.040-1.468, P = .016), Ruminococcus torques group (OR = 1.290, 95% CI: 1.035-1.608, P = .024) are potential CKD risk factors. Five microbiotas, including the Prevotellaceae (OR = 0.814, 95% CI: 0.719-0.922, P = .001) are potential CKD protective factors. Sensitivity analyses reveal no horizontal pleiotropy or heterogeneity. Additionally, reverse MR results unveiled potential relation between CKD and disorders in 3 microbiotas, including Senegalimassilia. According to the investigation, MR method was employed to delve into reciprocal causal connection from GM to CKD. Our findings identified 15 types of GM causally linked to CKD, as well as CKD demonstrating causal associations with 3 types of GM. Further exploration of these associated GM types is hopeful to raise novel insights, for CKD preventing and early monitoring.

Causal Relationship Between Sjögren's Syndrome and Gut Microbiota: A Two-Sample Mendelian Randomization Study

Background: Gut microbiota have been previously reported to be related to a variety of immune diseases. However, the causal connection between Sjögren's syndrome (SS) and gut microbiota has yet to be clarified. Methods: We employed a two-sample Mendelian randomization (MR) analysis to evaluate the causal connection between gut microbiota and SS, utilizing summary statistics from genome-wide association studies (GWASs) obtained from the MiBioGen and FinnGen consortia. The inverse variance weighted (IVW) approach represents the primary method of Mendelian randomization (MR) analysis. Sensitivity analysis was used to eliminate instrumental variables heterogeneity and horizontal pleiotropy. In addition, we performed an analysis using independent GWAS summary statistics for SS from the European Bioinformatics Institute (EBI) dataset for further verify our results. Results: IVW results demonstrated that the phylum Lentisphaerae (OR = 0.79, 95% CI: 0.63-0.99, p = 0.037), class Deltaproteobacteria (OR = 0.67, 95% CI: 0.47-0.96, p = 0.030), family Porphyromonadaceae (OR = 0.60, 95% CI: 0.38-0.94, p = 0.026), genus Eubacterium coprostanoligenes group (OR = 0.61, 95% CI: 0.4-0.93, p = 0.021), genus Blautia (OR = 0.62, 95% CI: 0.43-0.90, p = 0.012), genus Butyricicoccus (OR = 0.61, 95% CI: 0.42-0.90, p = 0.012), genus Escherichia.Shigella (OR = 0.7, 95% CI: 0.49-0.99, p = 0.045) and genus Subdoligranulum (OR = 0.61, 95% CI: 0.44-0.86, p = 0.005) exhibited protective effects on SS. Relevant heterogeneity of horizontal pleiotropy or instrumental variables was not detected. Furthermore, repeating our results with an independent cohort provided by the EBI dataset, only the genus Eubacterium coprostanoligenes group remained significantly associated with the protective effect on SS (OR = 0.41, 95% CI: 0.18-0.91, p = 0.029). Two-step MR analysis further revealed that genus Eubacterium coprostanoligenes group exerts its protective effect by reducing CXCL6 levels in SS (OR, 0.87; 95% CI = 0.76-0.99, p = 0.033). Conclusions: Our study using two-sample MR analysis identified a causal association between multiple genera and SS. A two-step MR result calculated that genus Eubacterium coprostanoligenes group mediated its protective effect by reducing CXCL6 levels in SS. However, the datasets available from the MiBioGen and FinnGen consortia do not provide sufficient information or comprehensive demographic data for subgroup analyses. Additional validation using various omics technologies is necessary to comprehend the development of SS in the intricate interplay between genes and the environment over a period of time.

Causal role of immune cells in diabetic nephropathy: a bidirectional Mendelian randomization study

Background

Diabetic nephropathy (DN) stands as a pervasive chronic renal disease worldwide, emerging as the leading cause of renal failure in end-stage renal disease. Our objective is to pinpoint potential immune biomarkers and evaluate the causal effects of prospective therapeutic targets in the context of DN.

Methods

We employed Mendelian randomization (MR) analysis to examine the causal associations between 731 immune cell signatures and the risk of DN. Various analytical methods, including inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode, were employed for the analysis. The primary analytical approach utilized was the inverse-variance weighted (IVW) method. To ensure the reliability of our findings, we conducted comprehensive sensitivity analyses to assess the robustness, heterogeneity, and presence of horizontal pleiotropy in the results. Statistical powers were also calculated. Ultimately, a reverse Mendelian randomization (MR) analysis was conducted to assess the potential for reverse causation.

Results

After Benjamini & Hochberg (BH) correction, four immunophenotypes were identified to be significantly associated with DN risk: HLA DR on Dendritic Cell (OR=1.4460, 95% CI = 1.2904~1.6205, P=2.18×10-10, P.adjusted= 1.6×10-7), HLA DR on CD14+ CD16- monocyte (OR=1.2396, 95% CI=1.1315~1.3580, P=3.93×10-6, P.adjusted = 0.00143). HLA DR on CD14+ monocyte (OR=1.2411, 95% CI=1.12957~1.3637, P=6.97×10-6, P.adjusted=0.0016), HLA DR on plasmacytoid Dendritic Cell (OR=1.2733, 95% CI= 1.1273~1.4382, P= 0.0001, P.adjusted = 0.0183). Significant heterogeneity of instrumental variables was found in the four exposures, and significant horizontal pleiotropy was only found in HLA DR on Dendritic Cell. The bidirectional effects between the immune cells and DN were not supported.

Conclusion

Our research illustrated the intimate association between immune cells and DN, which may contribute to a deeper understanding of the intricate mechanisms underlying DN and aid in the identification of novel intervention target pathways.

Causal relationship between gut microbiota and male erectile dysfunction: a Mendelian randomization analysis

Background

Several observational studies have reported an association between gut microbiota and male erectile dysfunction (ED). However, it remains unclear whether there is a causal relationship between gut microbiota and male ED. Thus, we aimed to investigate the potential causal relationship between gut microbiota and male ED through Mendelian randomization (MR) analysis.

Objective

To assess the causal relationship between gut microbiota and male ED, we performed a two-sample MR analysis.

Methods

We obtained gut microbiota genome-wide association studies (GWAS) data from the MiBioGen consortium and publicly available GWAS data on male ED from the OPEN GWAS database. Subsequently, we performed a two-sample MR analysis to evaluate the causal relationship between gut microbiota and male ED. Finally, we performed sensitivity analysis, including Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO, and leave-one-out analysis, to assess the level of heterogeneity and horizontal pleiotropy in the results.

Results

Our MR analysis revealed a negative causal relationship between the genus Ruminococcaceae UCG013 and male ED (OR = 0.761, 95% CI 0.626-0.926), while the family Lachnospiraceae, genus Lachnospiraceae NC2004 group, genus Oscillibacter, and genus Tyzzerella3 may be associated with an increased risk of male ED, with the highest risk observed for family Lachnospiraceae (OR = 1.264, 95% CI 1.063-1.504). Furthermore, sensitivity analysis confirmed the reliability of our positive findings.

Conclusion

Our MR analysis revealed a causal relationship between gut microbiota and male ED. This may contribute to a better understanding of the potential applications of gut microbiota in the occurrence and treatment of male ED.

Causal relationships between gut microbiome and obstructive sleep apnea: a bi-directional Mendelian randomization

Background

Previous studies have identified a clinical association between gut microbiota and Obstructive sleep apnea (OSA), but the potential causal relationship between the two has not been determined. Therefore, we aim to utilize Mendelian randomization (MR) to investigate the potential causal effects of gut microbiota on OSA and the impact of OSA on altering the composition of gut microbiota.

Methods

Bi-directional MR and replicated validation were utilized. Summary-level genetic data of gut microbiota were derived from the MiBioGen consortium and the Dutch Microbiome Project (DMP). Summary statistics of OSA were drawn from FinnGen Consortium and Million Veteran Program (MVP). Inverse-variance-weighted (IVW), weighted median, MR-Egger, Simple Mode, and Weighted Mode methods were used to evaluate the potential causal link between gut microbiota and OSA.

Results

We identified potential causal associations between 23 gut microbiota and OSA. Among them, genus Eubacterium xylanophilum group (OR = 0.86; p = 0.00013), Bifidobacterium longum (OR = 0.90; p = 0.0090), Parabacteroides merdae (OR = 0.85; p = 0.00016) retained a strong negative association with OSA after the Bonferroni correction. Reverse MR analyses indicated that OSA was associated with 20 gut microbiota, among them, a strong inverse association between OSA and genus Anaerostipes (beta = -0.35; p = 0.00032) was identified after Bonferroni correction.

Conclusion

Our study implicates the potential bi-directional causal effects of the gut microbiota on OSA, potentially providing new insights into the prevention and treatment of OSA through specific gut microbiota.

Causal effects of gut microbiota on risk of overactive bladder symptoms: a two-sample Mendelian randomization study

Background

Clinical observations indicate a correlation between the gut microbiota and overactive bladder (OAB) symptoms. Nevertheless, the causal relationship and mechanisms between gut microbiota and OAB symptoms remain elusive.

Methods

Two-sample Mendelian randomization (MR) analyses were performed to assess the association between gut microbiota and OAB symptoms, including urinary incontinence (UI). Data were obtained from the MiBioGen International Consortium genome-wide association studies (GWAS) dataset and the IEU GWAS database. The inverse variance weighted method was used as the primary approach in the MR analysis, with the weighted median, MR-Egger, and weighted mode methods as supplementary approaches. Sensitivity analyses were employed to assess potential violations of the MR assumptions.

Results

Our analysis identified seven gut bacterial taxa with a causal relationship to OAB and nine gut bacterial taxa associated with UI. Genera Eubacteriumfissicatenumgroup, LachnospiraceaeNK4A136group, and Romboutsia were identified as protective factors against OAB, while genera Barnesiella, FamilyXIIIAD3011group, Odoribacter, and RuminococcaceaeUCG005 were associated with an increased risk of OAB. A higher abundance of the genus Coprococcus3, order Burkholderiales, and phylum Verrucomicrobia predicted a lower risk of UI. Conversely, the class Mollicutes, genus Ruminococcus gauvreauii group, order Mollicutes RF9, and phylum Firmicutes and Tenericutes were positively correlated with UI risk. The sensitivity analysis excluded the influence of potential heterogeneity and horizontal pleiotropy.

Conclusion

This study revealed a causal relationship between gut microbiota and OAB symptoms, providing new insights and a theoretical foundation to identify biomarkers and therapeutic targets for patients with OAB symptoms.

Association between gut microbiota and adrenal disease: a two-sample Mendelian randomized study

Background

Some observational studies and clinical experiments suggest a close association between gut microbiota and metabolic diseases. However, the causal effects of gut microbiota on adrenal diseases, including Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism, remain unclear.

Methods

This study conducted a two-sample Mendelian randomization analysis using summary statistics data of gut microbiota from a large-scale genome-wide association study conducted by the MiBioGen Consortium. Summary statistics data for the three adrenal diseases were obtained from the FinnGen study. The study employed Inverse variance weighting, MR-Egger, and MR-PRESSO methods to assess the causal relationship between gut microbiota and these three adrenal diseases. Additionally, a reverse Mendelian randomization analysis was performed for bacteria found to have a causal relationship with these three adrenal diseases in the forward Mendelian randomization analysis. Cochran's Q statistic was used to test for heterogeneity of instrumental variables.

Results

The IVW test results demonstrate that class Deltaproteobacteria, Family Desulfovibrionaceae, and Order Desulfovibrionales exhibit protective effects against adrenocortical insufficiency. Conversely, Family Porphyromonadaceae, Genus Lachnoclostridium, and Order MollicutesRF9 are associated with an increased risk of adrenocortical insufficiency. Additionally, Family Acidaminococcaceae confers a certain level of protection against Cushing syndrome. In contrast, Class Methanobacteria, Family Lactobacillaceae, Family Methanobacteriaceae, Genus. Lactobacillus and Order Methanobacteriales are protective against Hyperaldosteronism. Conversely, Genus Parasutterella, Genus Peptococcus, and Genus Veillonella are identified as risk factors for Hyperaldosteronism.

Conclusions

This two-sample Mendelian randomization analysis revealed a causal relationship between microbial taxa such as Deltaproteobacteria and Desulfovibrionaceae and Adrenocortical insufficiency, Cushing syndrome, and Hyperaldosteronism. These findings offer new avenues for comprehending the development of adrenal diseases mediated by gut microbiota.

The causal relationship between gut microbiota and diabetic neuropathy: a bi-directional two-sample Mendelian randomization study

Background

Many studies suggest a strong correlation between gut microbiota (GM) and diabetic neuropathy (DN). However, the precise causal relationship between GM and DN has yet to be fully elucidated. Hence, a bi-directional Mendelian randomization (MR) analysis was used to examine the association between GM and DN.

Methods

Widely known genome-wide association study (GWAS) of GM was collected from the MiBio Gen project. Summary-level datasets for DN were taken from the FinnGen project. Inverse variance weighted approach was used for evaluating the causal relationship between GM and DN. Subsequently, pleiotropy and heterogeneity tests were performed to verify the reliability of the data. Furthermore, a bidirectional two-sample MR analysis was done to investigate the directionality of the causal relationships. Gene Ontology analysis was conducted to identify the associations that could indicate biological functions.

Results

We identified potential causal associations between GM and DN (p< 0.05 in all three MR methods). Among them, we found increased levels of Christensenellaceae R-7 (Odds ratio, OR= 1.52; 95% confidence interval, CI = 1.03-2.23; p = 0.03), Ruminococcaceae UCG013 (OR =1.35; 95% CI = 1.00-1.85; p = 0.04), and Eggerthella groups (OR = 1.27; 95% CI = 1.05-1.55; p = 0.01), which may be associated with a higher risk of DN, while increased levels of Peptococcaceae (OR = 0.69; 95% CI = 0.54-0.90; p< 0.01) and Eubacterium coprostanoligenes groups (OR = 0.68; 95% CI = 0.49-0.93; p = 0.01) could be associated with a lower risk. Gene Ontology pathway analysis revealed enrichment of genes regulated by the associated single-nucleotide polymorphisms (SNPs) in the apical plasma membrane, glycosyltransferase activity, hexosyltransferase activity and membrane raft. Reverse MR analyses indicated that DN was associated with five microbial taxa in all three MR methods.

Conclusion

The results of our study validate the possible causative relationship between GM and DN. This discovery gives new perspectives into the mechanism on how GM influences DN, and establishes a theoretical foundation for future investigations into targeted preventive measures.

Causal effects of gut microbiota on the risk of osteomyelitis: a Mendelian randomization study

Background

Osteomyelitis is characterized by an inflammatory process initiated by microorganisms, leading to infection and subsequent degradation of bone tissue. Several studies have indicated a potential link between gut microbiota and the occurrence of osteomyelitis. Utilizing the benefits of Mendelian randomization, which mitigates issues of confounding and reverse causation, we employed this approach to ascertain the presence of a causal connection between gut microbiota and osteomyelitis. Additionally, we aimed to pinpoint gut microbiota that could potentially exert substantial influence.

Methods

We performed a rigorous screening of single nucleotide polymorphisms in GWAS summary statistics for gut microbiota and osteomyelitis. The 2,542 instrumental variables obtained after screening were subjected to MR analyses, including inverse variance weighting, weighted median, weighted mode, MR-Egger, and Mendelian randomization pleiotropy residual sum and outlier test. We then validated the reliability of the results by performing sensitivity analyses on the MR of 196 well-defined gut microbiota.

Result

We established a causal relationship between gut microbiota and osteomyelitis through MR analysis. Additionally, we identified a taxon of significant importance and six taxons with nominal significance. Specifically, the family Bacteroidales S24.7 group exhibited an association with a diminished risk of osteomyelitis development. Conversely, the class Bacilli, class Bacteroidia, order Bacteroidales, order Lactobacillales, family Streptococcaceae, and genus Coprococcus3 displayed an increased risk of developing osteomyelitis. The MR outcomes for these seven taxa remained stable throughout a series of sensitivity analyses.

Conclusion

This study demonstrated a causal relationship between gut microbiota and osteomyelitis by Mendelian randomization. We hope that this study will provide a new direction for the treatment of osteomyelitis, which has a paucity of therapeutic options.

Association of gut microbiota with cerebral cortical thickness: A Mendelian randomization study

BACKGROUND

The causal relationship between gut microbiota and cerebral cortex development remains unclear. We aimed to scrutinize the plausible causal impact of gut microbiota on cortical thickness via Mendelian randomization (MR) study.

METHODS

Genome-wide association study (GWAS) data for 196 gut microbiota phenotypes (N = 18,340) were obtained as exposures, and GWAS data for cortical thickness-related traits (N = 51,665) were selected as outcomes. Inverse variance weighted was used as the main estimate method. A series of sensitivity analyses was used to test the robustness of the estimates including Cochran's Q test, MR-Egger intercept analysis, Steiger filtering, scatter plot funnel plot and leave-one-out analysis.

RESULTS

Genetic prediction of high Bacillales (β = 0.005, P = 0.032) and Lactobacillales (β = 0.010, P = 0.012) abundance was associated with a potential increase in global cortical thickness. For specific functional brain subdivisions, genetically predicted order Lactobacillales would potentially increase the thickness of the fusiform (β = 0.014, P = 0.016) and supramarginal (β = 0.017, P = 0.003). Meanwhile, order Bacillales would increase the thickness of fusiform (β = 0.007, P = 0.039), insula (β = 0.011, P = 0.003), rostralanteriorcingulate (β = 0.014, P = 0.002) and supramarginal (β = 0.006, P = 0.043). No significant estimates of heterogeneity or pleiotropy were found.

CONCLUSIONS

Through MR studies, we discovered genetic prediction of the Lactobacillales and Bacillales orders potentially linked to cortical thickness, affirming gut microbiota may enhance brain structure. Genetically predicted supramarginal and fusiform may be potential targets.

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.

Exploring causality in the association between gut microbiota and irritable bowel syndrome risk: a large Mendelian randomization study

BACKGROUND

In the past, some observational studies have highlighted the correlation between gut microbiota and irritable bowel syndrome (IBS). However, it is still unknown if the composition of gut microbiota shows a causal effect on the risk of IBS.

AIM

To conduct Mendelian randomization (MR) analysis of the samples to study the probable causal relationship between the gut microbiota, their taxonomic groups, and the risk of IBS.

MATERIALS AND METHODS

In this study, the summarized data regarding 211 gut microbiota and their IBS genome-wide association studies (GWAS) were collected from public databases. The causal estimates were determined using five MR techniques, where Inverse Variance Weighted (IVW) regression was employed as the major MR technique. Herein, MR-PRESSO and MR-Egger intercept tests were conducted to prevent horizontal pleiotropy. Cochran's Q test was used to evaluate heterogeneity using the IVW and MR-Egger techniques.

RESULTS

IVW results showed that gut microbes, belonging to Class Gammaproteobacteria (P = 0.04; OR = 1.45), Family XIII (P = 0.03; OR = 1.34), Family Prevotellaceae (P = 0.003; OR =1.24), and Lachnospiraceae UCG004 (P = 0.049; OR = 1.19) increased the risk of IBS, while Alcaligenaceae (P = 0.03; OR = 0.83, 95% CI: 0.69-0.98) and Coprobacter (P = 0.02; OR = 0.86, 95% CI: 0.76-0.98) decreased the risk of IBS.

CONCLUSIONS

This study presented novel insights that highlighted the causal relationship between gut microbiota and IBS, and offered new treatment strategies for preventing or treating IBS.

Association of NAFLD/NASH, and MAFLD/MASLD with chronic kidney disease: an updated narrative review

Chronic kidney disease (CKD) and nonalcoholic fatty liver disease (NAFLD), metabolic dysfunction-associated fatty liver disease (MAFLD) and metabolic dysfunction-associated steatotic liver disease (MASLD) account for substantial financial burden worldwide. These alarming features call for enhanced efforts to prevent and manage the development and progression of CKD. Accumulating evidence supporting a causal role of NAFLD/MAFLD/MASLD-in CKD opens new horizons to achieve this aim. Recent epidemiological studies and meta-analyses exploring the association of NAFLD/MAFLD/MASLD with CKD and the characteristics of NAFLD/MAFLD/MASLD associated with the odds of incident CKD are discussed. The involved pathomechanisms, including the common soil hypothesis, genetics, gut dysbiosis, and portal hypertension, are examined in detail. Finally, lifestyle changes (diet and physical exercise), direct manipulation of gut microbiota, and drug approaches involving statins, renin-angiotensin-aldosterone system inhibitors, GLP-1 Receptor Agonists, Sodium-glucose cotransporter-2, pemafibrate, and vonafexor are examined within the context of prevention and management of CKD among those with NAFLD/MAFLD/MASLD. The evolving NAFLD/MAFLD/MASLD nomenclature may generate confusion among practicing clinicians and investigators. However, comparative studies investigating the pros and contra of different nomenclatures may identify the most useful definitions among NAFLD/MAFLD/MASLD and strategies to identify, prevent, and halt the onset and progression of CKD.

Integration of Urinary Peptidome and Fecal Microbiome to Explore Patient Clustering in Chronic Kidney Disease

Millions of people worldwide currently suffer from chronic kidney disease (CKD), requiring kidney replacement therapy at the end stage. Endeavors to better understand CKD pathophysiology from an omics perspective have revealed major molecular players in several sample sources. Focusing on non-invasive sources, gut microbial communities appear to be disturbed in CKD, while numerous human urinary peptides are also dysregulated. Nevertheless, studies often focus on isolated omics techniques, thus potentially missing the complementary pathophysiological information that multidisciplinary approaches could provide. To this end, human urinary peptidome was analyzed and integrated with clinical and fecal microbiome (16S sequencing) data collected from 110 Non-CKD or CKD individuals (Early, Moderate, or Advanced CKD stage) that were not undergoing dialysis. Participants were visualized in a three-dimensional space using different combinations of clinical and molecular data. The most impactful clinical variables to discriminate patient groups in the reduced dataspace were, among others, serum urea, haemoglobin, total blood protein, urinary albumin, urinary erythrocytes, blood pressure, cholesterol measures, body mass index, Bristol stool score, and smoking; relevant variables were also microbial taxa, including Roseburia, Butyricicoccus, Flavonifractor, Burkholderiales, Holdemania, Synergistaceae, Enterorhabdus, and Senegalimassilia; urinary peptidome fragments were predominantly derived from proteins of collagen origin; among the non-collagen parental proteins were FXYD2, MGP, FGA, APOA1, and CD99. The urinary peptidome appeared to capture substantial variation in the CKD context. Integrating clinical and molecular data contributed to an improved cohort separation compared to clinical data alone, indicating, once again, the added value of this combined information in clinical practice.

Causal associations between human gut microbiota and hemorrhoidal disease: A two-sample Mendelian randomization study

Hemorrhoidal disease (HEM) is a common condition affecting a significant proportion of the population. However, the causal relationship between the gut microbiota and hemorrhoids remains unclear. In this study, we employed a Mendelian randomization (MR) approach to investigate the potential associations between them. In this study, the exposure factor was determined by selecting summary statistics data from a large-scale gut microbiome whole-genome association study conducted by the MiBioGen Consortium, which involved a sample size of 18,340 individuals. The disease outcome data consisted of 218,920 cases of HEM and 725,213 controls of European ancestry obtained from the European Bioinformatics Institute dataset. Two-sample MR analyses were performed to assess the causalities between gut microbiota and hemorrhoids using various methods, including inverse-variance weighting, MR-Egger regression, MR Pleiotropy Residual Sum and Outlier (MR-PRESSO), simple mode, and weighted median. Reverse MR analyses were performed to examine reverse causal association. Our findings suggest phylum Cyanobacteria (OR = 0.947, 95% CI: 0.915-0.980, P = 2.10 × 10 - 3), genus Phascolarctobacterium (OR = 0.960, 95% CI: 0.924-0.997, P = .034) and family FamilyXI (OR = 0.974, 95% CI: 0.952-0.997, P = .027) have potentially protective causal effects on the risk of HEM, while genus Ruminococcaceae_UCG_002 (OR = 1.036, 95% CI: 1.001-1.071, P = .042), family Peptostreptococcaceae (OR = 1.042, 95% CI: 1.004-1.082, P = .029), genus Oscillospira (OR = 1.048, 95% CI: 1.005-1.091, P = .026), family Alcaligenaceae (OR = 1.048, 95% CI: 1.005-1.091, P = .036) and order Burkholderiales (OR = 1.074, 95% CI: 1.020-1.130, P = 6.50 × 10-3) have opposite effect. However, there was a reverse causal relationship between HEM and genus Oscillospira (OR = 1.140, 95% CI: 1.002-1.295, P = .046) This is the first MR study to explore the causalities between specific gut microbiota taxa and hemorrhoidal disease, which may offer valuable insights for future clinical interventions for hemorrhoidal disease.

The causal relationship between gut microbiota and biliary tract cancer: comprehensive bidirectional Mendelian randomization analysis

Background

Growing evidence has shown that gut microbiome composition is associated with Biliary tract cancer (BTC), but the causality remains unknown. This study aimed to explore the causal relationship between gut microbiota and BTC, conduct an appraisal of the gut microbiome's utility in facilitating the early diagnosis of BTC.

Methods

We acquired the summary data for Genome-wide Association Studies (GWAS) pertaining to BTC (418 cases and 159,201 controls) from the Biobank Japan (BBJ) database. Additionally, the GWAS summary data relevant to gut microbiota (N = 18,340) were sourced from the MiBioGen consortium. The primary methodology employed for the analysis consisted of Inverse Variance Weighting (IVW). Evaluations for sensitivity were carried out through the utilization of multiple statistical techniques, encompassing Cochrane's Q test, the MR-Egger intercept evaluation, the global test of MR-PRESSO, and a leave-one-out methodological analysis. Ultimately, a reverse Mendelian Randomization analysis was conducted to assess the potential for reciprocal causality.

Results

The outcomes derived from IVW substantiated that the presence of Family Streptococcaceae (OR = 0.44, P = 0.034), Family Veillonellaceae (OR = 0.46, P = 0.018), and Genus Dorea (OR = 0.29, P = 0.041) exerted a protective influence against BTC. Conversely, Class Lentisphaeria (OR = 2.21, P = 0.017), Genus Lachnospiraceae FCS020 Group (OR = 2.30, P = 0.013), and Order Victivallales (OR = 2.21, P = 0.017) were associated with an adverse impact. To assess any reverse causal effect, we used BTC as the exposure and the gut microbiota as the outcome, and this analysis revealed associations between BTC and five different types of gut microbiota. The sensitivity analysis disclosed an absence of empirical indicators for either heterogeneity or pleiotropy.

Conclusion

This investigation represents the inaugural identification of indicative data supporting either beneficial or detrimental causal relationships between gut microbiota and the risk of BTC, as determined through the utilization of MR methodologies. These outcomes could hold significance for the formulation of individualized therapeutic strategies aimed at BTC prevention and survival enhancement.

Causal association of gut microbiota on spondyloarthritis and its subtypes: a Mendelian randomization analysis

Background

Despite establishing an association between gut microbiota and spondyloarthritis (SpA) subtypes, the causal relationship between them remains unclear.

Methods

Gut microbiota data were obtained from the MiBioGen collaboration, and SpA genome-wide association study (GWAS) summary data were obtained from the FinnGen collaboration. We conducted a two-sample Mendelian randomization (MR) analysis using the inverse-variance-weighted method supplemented with four additional MR methods (MR-Egger, weighted median, simple mode, and weighted mode). Pleiotropy and heterogeneity were also assessed. Reverse MR analysis was used to detect reverse causal relationships.

Results

We identified 23 causal links between specific gut microbiota taxa and SpA levels. Of these, 22 displayed nominal causal associations, and only one demonstrated a robust causal connection. Actinobacteria id.419 increased the risk of ankylosing spondylitis (AS) (odds ratio (OR) = 1.86 (95% confidence interval (CI): 1.29-2.69); p = 8.63E-04). The family Rikenellaceae id.967 was associated with a reduced risk of both AS (OR = 0.66 (95% CI: 0.47-0.93); p = 1.81E-02) and psoriatic arthritis (OR = 0.70 (95% CI: 0.50-0.97); p = 3.00E-02). Bacillales id.1674 increased the risk of AS (OR = 1.23 (95% CI: 1.00-1.51); p = 4.94E-02) and decreased the risk of enteropathic arthritis (OR = 0.56 (95% CI: 0.35-0.88); p = 1.14E-02). Directional pleiotropy, or heterogeneity, was not observed. No reverse causal associations were observed between the diseases and the gut microbiota.

Conclusion

Our MR analysis suggested a genetic-level causal relationship between specific gut microbiota and SpA, providing insights into the underlying mechanisms behind SpA development mediated by gut microbiota.

Gut microbiota and risk of endocarditis: a bidirectional Mendelian randomization study

Background

The associations between gut microbiota and cardiovascular disease have been reported in previous studies. However, the relationship between gut microbiota and endocarditis remains unclear.

Methods

A bidirectional Mendelian randomization (MR) study was performed to detect the association between gut microbiota and endocarditis. Inverse variance weighted (IVW) method was considered the main result. Simultaneously, heterogeneity and pleiotropy tests were conducted.

Results

Our study suggests that family Victivallaceae (p = 0.020), genus Eubacterium fissicatena group (p = 0.047), genus Escherichia Shigella (p = 0.024), genus Peptococcus (p = 0.028) and genus Sellimonas (p = 0.005) play protective roles in endocarditis. Two microbial taxa, including genus Blautia (p = 0.006) and genus Ruminococcus2 (p = 0.024) increase the risk of endocarditis. At the same time, endocarditis has a negative effect on genus Eubacterium fissicatena group (p = 0.048). Besides, no heterogeneity or pleiotropy was found in this study.

Conclusion

Our study emphasized the certain role of specific gut microbiota in patients with endocarditis and clarified the negative effect of endocarditis on gut microbiota.

Microbiota during pregnancy and early life: role in maternal-neonatal outcomes based on human evidence

Here, we explored the vast potential of microbiome-based interventions in preventing and managing non-communicable diseases including obesity, diabetes, allergies, celiac disease, inflammatory bowel diseases, malnutrition, and cardiovascular diseases across different life stages. We discuss the intricate relationship between microbiome and non-communicable diseases, emphasizing on the "window of opportunity" for microbe-host interactions during the first years after birth. Specific biotics and also live biotherapeutics including fecal microbiota transplantation emerge as pivotal tools for precision medicine, acknowledging the "one size doesn't' fit all" aspect. Challenges in implementation underscore the need for advanced technologies, scientific transparency, and public engagement. Future perspectives advocate for understanding maternal-neonatal microbiome, exploring the maternal exposome and delving into human milk's role in the establishment and restoration of the infant microbiome and its influence over health and disease. An integrated scientific approach, employing multi-omics and accounting for inter-individual variance in microbiome composition and function appears central to unleash the full potential of early-life microbiome interventions in revolutionizing healthcare.

Association between gut microbiota and seven gastrointestinal diseases: A Mendelian randomized study

BACKGROUND

Observational research has shed light on the ability of gut microbes to influence the onset and progression of gastrointestinal diseases. The causal relationships between specific gut microbiomes and various gastrointestinal conditions, however, remain unknown.

METHODS

We investigated the relationship between gut microbiota and seven specific gastrointestinal disorders using a robust two-sample Mendelian randomization (MR) approach. The inverse variance-weighted (IVW) method was used as the primary analysis tool in our study. Furthermore, we conducted multiple sensitivity analyses to strengthen the robustness of our findings and ensure the reliability of the IVW method.

RESULTS

Our research has discovered significant links between the composition of gut microbiota and a variety of gastrointestinal ailments. We found compelling links between 13 gut microbiota and fatty liver, four gut microbiota and cirrhosis, eight gut microbiota and hepatocellular carcinoma, four gut microbiota and cholelithiasis, 12 gut microbiota and acute pancreatitis, eight gut microbiota and chronic pancreatitis, and 11 gut microbiota and pancreatic cancer. These findings shed light on the intricate relationship between gut microbes and the emergence of these specific gastrointestinal conditions.

CONCLUSIONS

The findings of this extensive study not only validate the potential role of specific gut microbiota in gastrointestinal diseases, but also fill a critical gap in previous research. The discovery of these specific gut microbiota is a significant step forward because they may serve as novel and promising biomarkers for both the prevention and treatment of gastrointestinal conditions.

Prolonged Antibiotic Use in a Preclinical Model of Gulf War Chronic Multisymptom-Illness Causes Renal Fibrosis-like Pathology via Increased micro-RNA 21-Induced PTEN Inhibition That Is Correlated with Low Host Lachnospiraceae Abundance

Gulf War (GW) veterans show gastrointestinal disturbances and gut dysbiosis. Prolonged antibiotic treatments commonly employed in veterans, especially the use of fluoroquinolones and aminoglycosides, have also been associated with dysbiosis. This study investigates the effect of prolonged antibiotic exposure on risks of adverse renal pathology and its association with gut bacterial species abundance in underlying GWI and aims to uncover the molecular mechanisms leading to possible renal dysfunction with aging. Using a GWI mouse model, administration of a prolonged antibiotic regimen involving neomycin and enrofloxacin treatment for 5 months showed an exacerbated renal inflammation with increased NF-κB activation and pro-inflammatory cytokines levels. Involvement of the high mobility group 1 (HMGB1)-mediated receptor for advanced glycation end products (RAGE) activation triggered an inflammatory phenotype and increased transforming growth factor-β (TGF-β) production. Mechanistically, TGF-β- induced microRNA-21 upregulation in the renal tissue leads to decreased phosphatase and tensin homolog (PTEN) expression. The above event led to the activation of protein kinase-B (AKT) signaling, resulting in increased fibronectin production and fibrosis-like pathology. Importantly, the increased miR-21 was associated with low levels of Lachnospiraceae in the host gut which is also a key to heightened HMGB1-mediated inflammation. Overall, though correlative, the study highlights the complex interplay between GWI, host gut dysbiosis, prolonged antibiotics usage, and renal pathology via miR-21/PTEN/AKT signaling.

Unraveling the connections between gut microbiota, stress, and quality of life for holistic care in newly diagnosed breast cancer patients

There is little research about the stress, quality of life (QOL) and gut microbiota in newly diagnosed breast cancer patients. In this study addressing the dearth of research on stress, quality of life (QOL), and gut microbiota in newly diagnosed breast cancer patients, 82 individuals were prospectively observed. Utilizing the Functional Assessment of Chronic Illness Therapy (FACT)-Breast questionnaire to assess health-related quality of life (HRQOL) and the Distress Thermometer (DT) to gauge distress levels, the findings revealed a mean FACT-B score of 104.5, underscoring HRQOL's varied impact. Significantly, 53.7% reported moderate to severe distress, with a mean DT score of 4.43. Further exploration uncovered compelling links between distress levels, FACT-B domains, and microbial composition. Notably, Alcaligenaceae and Sutterella were more abundant in individuals with higher DT scores at the family and genus levels (p = 0.017), while Streptococcaceae at the family level and Streptococcus at the genus level were prevalent in those with lower DT scores (p = 0.028 and p = 0.023, respectively). This study illuminates the intricate interplay of stress, QOL, and gut microbiota in newly diagnosed breast cancer patients, offering valuable insights for potential interventions of biomarker or probiotics aimed at alleviating stress and enhancing QOL in this patient cohort.

Causal Associations Between Gut Microbiota and Psoriasis: A Mendelian Randomization Study

INTRODUCTION

Previous studies have proposed a possible gut-skin axis, and linked gut microbiota to psoriasis risks. However, there is heterogeneity in existing evidence. Observational research is prone to bias, and it is hard to determine causality. Therefore, this study aims to evaluate possible causal associations between gut microbiota (GM) and psoriasis.

METHODS

With published large-scale GWAS (genome-wide association study) summary datasets, two-sample Mendelian randomization (MR) was performed to sort out possible causal roles of GM in psoriasis and arthropathic psoriasis (PsA). The inverse variance weighted (IVW) method was taken as the primary evaluation of causal association. As complements to the IVW method, we also applied MR-Egger, weighted median. Sensitivity analyses were conducted using Cochrane's Q test, MR-Egger intercept test, MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlier) global test, and leave-one-out analysis.

RESULTS

By primary IVW analysis, we identified nominal protective roles of Bacteroidetes (odds ratio, OR 0.81, P = 0.033) and Prevotella9 (OR 0.87, P = 0.045) in psoriasis risks. Bacteroidia (OR 0.65, P = 0.03), Bacteroidales (OR 0.65, P = 0.03), and Ruminococcaceae UCG002 (OR 0.81, P = 0.038) are nominally associated with lower risks for PsA. On the other hand, Pasteurellales (OR 1.22, P = 0.033), Pasteurellaceae (OR 1.22, P = 0.033), Blautia (OR 1.46, P = 0.014), Methanobrevibacter (OR 1.27, P = 0.026), and Eubacterium fissicatena group (OR 1.21, P = 0.028) are nominal risk factors for PsA. Additionally, E. fissicatena group is a possible risk factor for psoriasis (OR 1.22, P = 0.00018). After false discovery rate (FDR) correction, E. fissicatena group remains a risk factor for psoriasis (PFDR = 0.03798).

CONCLUSION

We comprehensively evaluated possible causal associations of GM with psoriasis and arthropathic psoriasis, and identified several nominal associations. E. fissicatena group remains a risk factor for psoriasis after FDR correction. Our results offer promising therapeutic targets for psoriasis clinical management.

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.