Association between the gut microbiota and nonalcoholic fatty liver disease: A two-sample Mendelian randomization study

Exploring the mediating role of blood metabolites in the relationship between gut microbiota and gastric cancer risk: a Mendelian randomization study

Background

Prior studies have established correlations between gut microbiota (GM) dysbiosis, circulating metabolite alterations, and gastric cancer (GC) risk. However, the causal nature of these associations remains uncertain.

Methods

We utilized summary data from genome-wide association studies (GWAS) on GM (European, n=8,956), blood metabolites (European, n=120,241; East Asian, n=4,435), and GC (European, n=476,116; East Asian, n=167,122) to perform a bidirectional Mendelian randomization (MR) analysis, investigating the causal effects of GM and metabolites on GC risk. Additionally, we conducted mediation analysis (two-step MR) to identify potential metabolite mediators in the GM-GC relationship.

Results

We identified twelve negative and seven positive associations between specific GM taxa and GC risk. For blood metabolites, seven traits were found to be significantly associated with reduced GC risk in the European population, with these findings subsequently validated in the East Asian cohort. Three GM taxa showed potential causal associations with five metabolic traits: the Bacteroidia class and Bacteroidales order were positively correlated with five metabolites (all P < 0.013), while Bacteroides OTU97_27 exhibited a negative correlation with one metabolite (P = 0.007). Two-step MR analysis indicated that total lipids in intermediate-density lipoprotein (IDL), IDL particle concentration, phospholipids in medium low-density lipoprotein (LDL), phospholipids in small LDL, and free cholesterol in small LDL indirectly influenced the association between Bacteroidia class/Bacteroidales order and GC, with mediation proportions of 1.71% (P = 0.048), 1.69% (P = 0.048), 2.05% (P = 0.045), 1.85% (P = 0.048), and 1.99% (P = 0.045), respectively.

Conclusion

The present study provides suggestive evidence of a causal relationship between specific GM, blood metabolites, and GC risk, potentially offering new insights into GC etiology.

Causal relationships between gut microbiome and aplastic anemia: a Mendelian randomization analysis

BACKGROUND

Previous observational studies have hinted at a potential correlation between aplastic anemia (AA) and the gut microbiome. However, the precise nature of this bidirectional causal relationship remains uncertain.

METHODS

We conducted a bidirectional two-sample Mendelian randomization (MR) study to investigate the potential causal link between the gut microbiome and AA. Statistical analysis of the gut microbiome was based on data from an extensive meta-analysis (genome-wide association study) conducted by the MiBioGen Alliance, involving 18,340 samples. Summary statistical data for AA were obtained from the Integrative Epidemiology Unit database. Single -nucleotide polymorphisms (SNPs) were estimated and summarized using inverse variance weighted (IVW), MR Egger, and weighted median methods in the bidirectional MR analysis. Cochran's Q test, MR Egger intercept test, and sensitivity analysis were employed to assess SNP heterogeneity, horizontal pleiotropy, and stability.

RESULTS

The IVW analysis revealed a significant correlation between AA and 10 bacterial taxa. However, there is currently insufficient evidence to support a causal relationship between AA and the composition of gut microbiome.

CONCLUSION

This study suggests a causal connection between the prevalence of specific gut microbiome and AA. Further investigation into the interaction between particular bacterial communities and AA could enhance efforts in prevention, monitoring, and treatment of the condition.

Hepatic HKDC1 Deletion Alleviates Western Diet-Induced MASH in Mice

The global prevalence of Metabolic dysfunction-associated steatohepatitis (MASH) has been rising sharply, closely mirroring the increasing rates of obesity and metabolic syndrome. MASH exhibits a strong sexual dimorphism where females are affected with more severe forms after menopause. Hexokinase domain-containing protein 1 (HKDC1) has recently been recognized for its role in liver diseases, where its expression is minimal under normal conditions but significantly increases in response to metabolic stressors like obesity and liver injury. This selective upregulation suggests HKDC1's potential specialization in hepatic glucose and lipid dysregulation, linking it closely to the progression of MASLD and MASH. This study aims to clarify the role of HKDC1 in Western diet-induced MASH in female mice by examining its impact on hepatic glucose and lipid metabolism, offering insights into its potential as a therapeutic target and addressing the need for sex-specific research in liver disease. This study reveals that HKDC1 expression is elevated in obese women with MASH and correlates with liver pathology. In a mouse model, liver-specific HKDC1 knockout (HKDC1 LKO ) protected against Western diet-induced obesity, glucose intolerance, and MASH features, including steatosis, inflammation, and fibrosis. Transcriptomic analysis showed that HKDC1 deletion reduced pro-inflammatory and pro-fibrotic gene expression, while gut microbiome analysis indicated a shift toward MASH-protective bacteria. These findings suggest that HKDC1 may exacerbate MASH progression through its role in metabolic and inflammatory pathways, making it a potential therapeutic target.

Causal impact of gut microbiota on five liver diseases: insights from mendelian randomization and single-cell RNA sequencing

Background

Liver disease is among the top ten causes of death globally. With studies suggesting a link between gut microbiota (GM) and liver disease.

Method

We selected summary statistics data from the largest available whole-genome association study (n = 13,266) of GM by the MiBioGen consortium as the exposure, and obtained liver disease-related data from IEU Open GWAS and The NHGRI-EBI GWAS Catalog. A two-sample Mendelian Randomization (MR) analysis employing various methods, to establish the causal relationship between GM and five liver diseases. Meanwhile, single-cell RNA sequencing data were used to examine Prevotella-related genes expression under healthy and disease liver.

Results

The IVW analysis indicate a causal relationship between GM and liver diseases, with Prevotella exhibiting a protective effect in all five liver diseases: Alcoholic liver disease (OR:0.81,95% confidence interval:0.66-1.00,P IVW = 0.0494); Cirrhosis (OR: 0.85,95% confidence interval: 0.73-0.99,P IVW = 0.0397); Hepatic failure, not elsewhere classified (OR:0.60,95% confidence interval:0.37-0.95,P IVW = 0.0305); Benign neoplasm:Liver (OR:0.39,95% confidence interval:0.2-0.75,P IVW = 0.0046); Malignant neoplasm of liver, primary (OR:0.41, 95% confidence interval:0.18-0.93,P IVW = 0.0334). The single-cell results suggest differential expression of Prevotella-related genes between liver disease patients and healthy individuals.

Conclusion

Our MR results show a causal relationship between the GM and liver disease. Prevotella displays a notable protective effect. This finding may enhance the precision of GM-based therapies and offer new insights for clinical research.

Genetic prediction of blood metabolites mediating the relationship between gut microbiota and Alzheimer's disease: a Mendelian randomization study

Background

Observational studies have suggested an association between gut microbiota and Alzheimer's disease (AD); however, the causal relationship remains unclear, and the role of blood metabolites in this association remains elusive.

Purpose

To elucidate the causal relationship between gut microbiota and AD and to investigate whether blood metabolites serve as potential mediators.

Materials and methods

Univariable Mendelian randomization (UVMR) analysis was employed to assess the causal relationship between gut microbiota and AD, while multivariable MR (MVMR) was utilized to mitigate confounding factors. Subsequently, a two-step mediation MR approach was employed to explore the role of blood metabolites as potential mediators. We primarily utilized the inverse variance-weighted method to evaluate the causal relationship between exposure and outcome, and sensitivity analyses including Contamination mixture, Maximum-likelihood, Debiased inverse-variance weighted, MR-Egger, Bayesian Weighted Mendelian randomization, and MR pleiotropy residual sum and outlier were conducted to address pleiotropy.

Results

After adjustment for reverse causality and MVMR correction, class Actinobacteria (OR: 1.03, 95% CI: 1.01-1.06, p = 0.006), family Lactobacillaceae (OR: 1.03, 95% CI: 1.00-1.05, p = 0.017), genus Lachnoclostridium (OR: 1.03, 95% CI: 1.00-1.06, p = 0.019), genus Ruminiclostridium9 (OR: 0.97, 95% CI: 0.94-1.00, p = 0.027) and genus Ruminiclostridium6 (OR: 1.03, 95% CI: 1.01-1.05, p = 0.009) exhibited causal effects on AD. Moreover, 1-ribosyl-imidazoleacetate levels (-6.62%), Metabolonic lactone sulfate levels (2.90%), and Nonadecanoate (19:0) levels (-12.17%) mediated the total genetic predictive effects of class Actinobacteria on AD risk. Similarly, 2-stearoyl-GPE (18:0) levels (-9.87%), Octadecanedioylcarnitine (C18-DC) levels (4.44%), 1-(1-enyl-stearoyl)-2-oleoyl-GPE (p-18:0/18:1) levels (38.66%), and X-23639 levels (13.28%) respectively mediated the total genetic predictive effects of family Lactobacillaceae on AD risk. Furthermore, Hexadecanedioate (C16-DC) levels (5.45%) mediated the total genetic predictive effects of genus Ruminiclostridium 6 on AD risk; Indole-3-carboxylate levels (13.91%), X-13431 levels (7.08%), Alpha-ketoglutarate to succinate ratio (-13.91%), 3-phosphoglycerate to glycerate ratio (15.27%), and Succinate to proline ratio (-14.64%) respectively mediated the total genetic predictive effects of genus Ruminiclostridium 9 on AD risk.

Conclusion

Our mediation MR analysis provides genetic evidence suggesting the potential mediating role of blood metabolites in the causal relationship between gut microbiota and AD. Further large-scale randomized controlled trials are warranted to validate the role of blood metabolites in the specific mechanisms by which gut microbiota influence AD.

Causal effect between gut microbiota and metabolic syndrome in European population: a bidirectional mendelian randomization study

BACKGROUND

Observational studies have reported that gut microbiota composition is associated with metabolic syndrome. However, the causal effect of gut microbiota on metabolic syndrome has yet to be confirmed.

METHODS

We performed a bidirectional Mendelian randomization study to investigate the causal effect between gut microbiota and metabolic syndrome in European population. Summary statistics of gut microbiota were from the largest available genome-wide association study meta-analysis (n = 13,266) conducted by the MiBioGen consortium. The summary statistics of outcome were obtained from the most comprehensive genome-wide association studies of metabolic syndrome (n = 291,107). The inverse-variance weighted method was applied as the primary method, and the robustness of the results was assessed by a series of sensitivity analyses.

RESULTS

In the primary causal estimates, Actinobacteria (OR = 0.935, 95% CI = 0.878-0.996, P = 0.037), Bifidobacteriales (OR = 0.928, 95% CI = 0.868-0.992, P = 0.028), Bifidobacteriaceae (OR = 0.928, 95% CI = 0.868-0.992, P = 0.028), Desulfovibrio (OR = 0.920, 95% CI = 0.869-0.975, P = 0.005), and RuminococcaceaeUCG010 (OR = 0.882, 95% CI = 0.803-0.969, P = 0.009) may be associated with a lower risk of metabolic syndrome, while Lachnospiraceae (OR = 1.130, 95% CI = 1.016-1.257, P = 0.025), Veillonellaceae (OR = 1.055, 95% CI = 1.004-1.108, P = 0.034) and Olsenella (OR = 1.046, 95% CI = 1.009-1.085, P = 0.015) may be linked to a higher risk for metabolic syndrome. Reverse MR analysis demonstrated that abundance of RuminococcaceaeUCG010 (OR = 0.938, 95% CI = 0.886-0.994, P = 0.030) may be downregulated by metabolic syndrome. Sensitivity analyses indicated no heterogeneity or horizontal pleiotropy.

CONCLUSIONS

Our Mendelian randomization study provided causal relationship between specific gut microbiota and metabolic syndrome, which might provide new insights into the potential pathogenic mechanisms of gut microbiota in metabolic syndrome and the assignment of effective therapeutic strategies.

The Metabolic Impact of Nonalcoholic Fatty Liver Disease on Cognitive Dysfunction: A Comprehensive Clinical and Pathophysiological Review

Nonalcoholic fatty liver disease (NAFLD) exponentially affects the global healthcare burden, and it is currently gaining increasing interest in relation to its potential impact on central nervous system (CNS) diseases, especially concerning cognitive deterioration and dementias. Overall, scientific research nowadays extends to different levels, exploring NAFLD's putative proinflammatory mechanism of such dysmetabolic conditions, spreading out from the liver to a multisystemic involvement. The aim of this review is to analyze the most recent scientific literature on cognitive involvement in NAFLD, as well as understand its underlying potential background processes, i.e., neuroinflammation, the role of microbiota in the brain-liver-gut axis, hyperammonemia neurotoxicity, insulin resistance, free fatty acids, and vitamins.

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.

Impact of gut microbiota on nonalcoholic fatty liver disease: insights from a leave-one-out cross-validation study

Introduction

Enteric dysbacteriosis is strongly associated with nonalcoholic fatty liver disease (NAFLD). However, the underlying causal relationship remains unknown. Thus, the present study aimed to investigate the relationship between gut microbiota and NAFLD using Mendelian randomization (MR) and analyze the target genes potentially regulated by specific microbiota.

Methods

Bidirectional two-sample MR analysis was performed using inverse variance weighted (IVW) supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Data were pooled from gut microbiota and NAFLD association studies. The least absolute shrinkage, selection operator regression, and the Support Vector Machine algorithm were used to identify genes regulated by these intestinal flora in NAFLD. The liver expression of these genes was verified in methionine choline-deficient (MCD) diet-fed mice.

Results

IVW results confirmed a causal relationship between eight specific gut microbes and NAFLD. Notably, the order Actinomycetales, NB1n, the family Actinomycetaceae, Oxalobacteraceae and the genus Ruminococcaceae UCG005 were positively correlated, whereas Lactobacillaceae, the Christensenellaceae R7 group, and Intestinibacter were negatively correlated with NAFLD onset. In NAFLD, these eight bacteria regulated four genes: colony-stimulating factor 2 receptor β, fucosyltransferase 2, 17-beta-hydroxysteroid dehydrogenase 14, and microtubule affinity regulatory kinase 3 (MAPK3). All genes, except MARK3, were differentially expressed in the liver tissues of MCD diet-fed mice.

Discussion

The abundance of eight gut microbiota species and NAFLD progression displayed a causal relationship based on the expression of the four target genes. Our findings contributed to the advancement of intestinal microecology-based diagnostic technologies and targeted therapies for NAFLD.

Association between gut microbiota and NAFLD/NASH: a bidirectional two-sample Mendelian randomization study

Background

Recent studies have suggested a relationship between gut microbiota and non-alcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH). However, the nature and direction of this potential causal relationship are still unclear. This study used two-sample Mendelian randomization (MR) to clarify the potential causal links.

Methods

Summary-level Genome-Wide Association Studies (GWAS) statistical data for gut microbiota and NAFLD/NASH were obtained from MiBioGen and FinnGen respectively. The MR analyses were performed mainly using the inverse-variance weighted (IVW) method, with sensitivity analyses conducted to verify the robustness. Additionally, reverse MR analyses were performed to examine any potential reverse causal associations.

Results

Our analysis, primarily based on the IVW method, strongly supports the existence of causal relationships between four microbial taxa and NAFLD, and four taxa with NASH. Specifically, associations were observed between Enterobacteriales (P =0.04), Enterobacteriaceae (P =0.04), Lachnospiraceae UCG-004 (P =0.02), and Prevotella9 (P =0.04) and increased risk of NAFLD. Dorea (P =0.03) and Veillonella (P =0.04) could increase the risks of NASH while Oscillospira (P =0.04) and Ruminococcaceae UCG-013 (P=0.005) could decrease them. We also identified that NAFLD was found to potentially cause an increased abundance in Holdemania (P =0.007) and Ruminococcus2 (P =0.002). However, we found no evidence of reverse causation in the microbial taxa associations with NASH.

Conclusion

This study identified several specific gut microbiota that are causally related to NAFLD and NASH. Observations herein may provide promising theoretical groundwork for potential prevention and treatment strategies for NAFLD and its progression to NASH in future.