Large-scale association analyses identify host factors influencing human gut microbiome composition

Exploring the relationship between creatine supplementation and renal function: insights from Mendelian randomization analysis

BACKGROUND

Creatine supplementation is ubiquitously consumed by fitness enthusiasts due to its perceived advantages in enhancing athletic performance. Although there is an increasing concern within this demographic regarding its possible impact on renal function, there is still a lack of rigorous scientific investigations into this alleged association.

METHODS

Data were collected through an online survey on the participants' demographics, creatine usage and concerns related to renal function. The reliability and validity of the survey were assessed using SPSS software. A total of 1129 participants responded to the survey, and chi-square tests were utilized for data analysis. To explore the potential association between creatine levels (as the exposure) and renal function (as the outcome), we utilized open-access genetic databases, and Mendelian randomization (MR) techniques were used to confirm this correlation.

RESULTS

Chi-square analysis revealed no significant association between creatine usage and renal function among the participants. Our MR analysis further supported this finding, demonstrating no significant association between creatine levels and six indicators assessing renal function (IVW, all with p values exceeding 0.05). Similar p values were consistently observed across other MR methods, confirming the absence of a statistical correlation.

CONCLUSIONS

This MR study offers compelling evidence indicating that creatine levels are not statistically associated with renal function, suggesting the potential to alleviate concerns within the fitness community and emphasizing the significance of evidence-based decision-making when considering nutritional supplementation.

Causal effects between gut microbiota and endometriosis: a two-sample Mendelian randomisation study

BACKGROUND

Previous observational evidence has indicated the potential involvement of the gut microbiota (GM) in the development of endometriosis. However, the causal relationship of the association remains to be investigated.

METHOD

Genome-wide association study (GWAS) data of GM was obtained from the MiBioGen consortium, and GWAS for endometriosis data was from the FinnGen consortium. Initially, a two-sample Mendelian randomisation (MR) analysis was performed to identify specific bacteria associated with endometriosis. Inverse variance-weighted (IVW) was used as the main MR analysis to infer causal relationships. The other four popular MR methods including MR-Egger regression, weighted mode, weighted median, and simple mode were used for secondary confirmation. Subsequently, these selected bacteria were employed as exposure to investigate their causal effects on six sub-types of endometriosis. Furthermore, reverse MR analysis was implemented to evaluate the reverse causal effects. Cochran's Q statistics was used to test the heterogeneity of instrumental variables (IVs); MR-Egger regression was used to test horizontal pleiotropy; MR-PRESSO and leave-one-out sensitivity analysis were applied to find significant outliers.

RESULT

A total of 1131 single nucleotide polymorphisms (SNPs) were collected as IVs for 196 GM taxa with endometriosis as the outcome. We identified 12 causal relationships between endometriosis and GM taxa including 1 phylum, 3 families, 2 orders, and 6 genera (Rikenellaceae RC9 gut group, Eubacterium ruminantium group, Faecalibacterium, Peptococcus, Clostridium sensu stricto 1, and Ruminococcaceae UCG005). Utilizing the Bonferroni method, we identified phylum Cyanobacteria as the strongest associated GM taxa. Subsequently, 6 significant causal effects were uncovered between the 12 selected specific GM and 6 sub-types of endometriosis. Meanwhile, no reverse causal relationship was found. Further, no horizontal pleiotropy and no significant outliers were detected in the sensitive analysis.

CONCLUSIONS

This MR analysis revealed significant causal effects between GM and endometriosis and phylum Cyanobacteria had the strongest association.

Innovate therapeutic targets for autoimmune diseases: insights from proteome-wide mendelian randomization and Bayesian colocalization

BACKGROUND

Despite growing knowledge regarding the pathogenesis of autoimmune diseases (ADs) onset, the current treatment remains unsatisfactory. This study aimed to identify innovative therapeutic targets for ADs through various analytical approaches.

RESEARCH DESIGN AND METHODS

Utilizing Mendelian randomization, Bayesian co-localization, phenotype scanning, and protein-protein interaction network, we explored potential therapeutic targets for 14 ADs and externally validated our preliminary findings.

RESULTS

This study identified 12 circulating proteins as potential therapeutic targets for six ADs. Specifically, IL12B was judged to be a risk factor for ankylosing spondylitis (p = 1.61E - 07). TYMP (p = 6.28E - 06) was identified as a protective factor for ulcerative colitis. For Crohn's disease, ERAP2 (p = 4.47E - 14), HP (p = 2.08E - 05), and RSPO3 (p = 6.52E - 07), were identified as facilitators, whereas FLRT3 (p = 3.42E - 07) had a protective effect. In rheumatoid arthritis, SWAP70 (p = 3.26E - 10), SIGLEC6 (p = 2.47E - 05), ISG15 (p = 3.69E - 05), and FCRL3 (p = 1.10E - 10) were identified as risk factors. B4GALT1 (p = 6.59E - 05) was associated with a lower risk of Type 1 diabetes (T1D). Interestingly, CTSH was identified as a protective factor for narcolepsy (p = 1.58E - 09) but a risk factor for T1D (p = 7.36E - 11), respectively. External validation supported the associations of eight of these proteins with three ADs.

CONCLUSIONS

Our integrated study identified 12 potential therapeutic targets for ADs and provided novel insights into future drug development for ADs.

Evidence from mendelian randomization identifies several causal relationships between primary membranous nephropathy and gut microbiota

BACKGROUND

Research has showcased a correlation between disruptions in gut microbiota and primary membranous nephropathy (pMN), giving rise to the concept of the 'gut-kidney axis'. However, the precise relationship between gut microbiota and pMN remains elusive. Hence, this study endeavors to investigate whether a causal relationship exists between gut microbiota and pMN utilizing Mendelian randomization (MR) analysis.

METHODS

The primary method employed for MR analysis is the inverse variance weighting method, supplemented by MR-Egger and the weighted median method, to infer causality. This approach was validated within the pMN cohort across two distinct populations.

RESULTS

At the species level, the abundance of Bifidobacterium bifidum and Alistipes indistinctus was negatively correlated with the risk of pMN. Conversely, pMN was positively associated with Bacilli abundance at the class level, Lachnospiraceae abundance at the family level, and Dialister abundance at the genus level. Specifically, at the species level, pMN was positively correlated with the abundance of Ruminococcus lactaris, Dialister invisus, and Coprococcus_sp_ART55_1.

CONCLUSION

These findings lay the groundwork for future research exploring the interplay between pMN and the gut microbiota, with substantial implications for the prevention and treatment of pMN and its associated complications.

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

Numerous studies have revealed a correlation between the risk of developing diabetic nephropathy (DN) and the gut microbiota (GM) composition. However, it remains uncertain whether the GM composition causes DN. We aimed to explore any potential causal links between the GM composition and the risk of developing DN. A meta-analysis conducted by the MiBioGen consortium of the largest genome-wide association study (GWAS) provided aggregated data on the GM. DN data were obtained from the IEU database. The inverse-variance weighting (IVW) method was employed as the primary analytical approach. The IVW analysis indicated that genus Dialister (OR = 0.51, 95% CI: 0.34-0.77, p = 0.00118) was protective against DN. In addition, class Gammaproteobacteria (OR = 0.47, 95% CI: 0.27-0.83, p = 0.0096), class Lentisphaeria (OR =0.76, 95% CI: 0.68-0.99, p = 0.04), order Victivallales (OR = 0.76, 95% CI: 0.58-0.99, p = 0.04), and phylum Proteobacteria (OR = 0.53, 95% CI: 0.33-0.85, p = 0.00872) were negatively associated with the risk of developing DN. Genus LachnospiraceaeUCG008 (OR =1.45, 95% CI: 1.08-1.95, p = 0.01), order Bacteroidales (OR = 1.59, 95% CI: 1.02-2.49, p = 0.04), and genus Terrisporobacter (OR = 1.98, 95% CI: 1.14-3.45, p = 0.015) were positively associated with the risk of developing DN. In this study, we established a causal relationship between the genus Dialister and the risk of developing DN. Further trials are required to confirm the protective effects of probiotics on DN and to elucidate the precise protective mechanisms involving genus Dialister and DN.

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.

Genetic association between gut microbiome and blood pressure and blood cell count as mediator: A two-step Mendelian randomization analysis

BACKGROUND

Previous studies have established a genetic link between gut microbiota and hypertension, but whether blood cell count plays a mediating role in this remains unknown. This study aims to explore genetic associations and causal factors involving the gut microbiome, peripheral blood cell count, and blood pressure.

METHODS

We utilized summary statistics derived from genome-wide association studies to conduct a two-sample mediation Mendelian randomization analysis (https://gwas.mrcieu.ac.uk/). We applied inverse variance weighted (IVW) estimation method as the primary method, along with MR Egger, Weighted median, Simple mode and Weighted mode as complementary methods. To ensure the robustness of the results, several sensitivity analyses were conducted.

RESULTS

Genetic variants significantly associated with the microbiome, blood pressure, or peripheral blood cell counts were selected as instrumental variables. Fourteen microbial taxa were found to have suggestive associations with diastolic blood pressure (DBP), while fifteen microbial taxa showed suggestive associations with systolic blood pressure (SBP). Meanwhile, red blood cell count, lymphocyte count, and platelet count were identified to mediate the influence of the gut microbiome on blood pressure. Specifically, red cell count was identified to mediate the effects of the phylum Cyanobacteria on DBP (mediated proportion: 8.262 %). Lymphocyte count was found mediate the effects of the genus Subdoligranulum (mediated proportion: 2.642 %) and genus Collinsella (mediated proportion: 2.749 %) on SBP. Additionally, platelet count was found to mediate the relationship between the genus Eubacterium ventriosum group and SBP, explaining 3.421 % of the mediated proportion.

CONCLUSIONS

Our findings highlighted that gut microbiota may have causal influence on the blood pressure by modulating blood cell counts, which sheds new light on the pathogenesis and potential clinical interventions through the intricate axis of gut microbiome, blood cell counts, and blood pressure.

Gut microbiota causally impacts adrenal function: a two-sample mendelian randomization study

Some studies have reported that the gut microbiota can influence adrenal-related hormone levels. However, the causal effects of the gut microbiota on adrenal function remain unknown. Therefore, we employed a two-sample Mendelian randomization (MR) study to systematically investigate the impact of gut microbiota on the function of different regions of the adrenal gland. The summary statistics for gut microbiota and adrenal-related hormones used in the two-sample MR analysis were derived from publicly available genome-wide association studies (GWAS). In the MR analysis, inverse variance weighting (IVW) was used as the primary method, with MR-Egger, weighted median, and cML-MA serving as supplementary methods for causal inference. Sensitivity analyses such as the MR-Egger intercept test, Cochran's Q test, and leave-one-out analysis were used to assess pleiotropy and heterogeneity. We identified 27 causal relationships between 23 gut microbiota and adrenal function using the IVW method. Among these, Sellimonas enhanced the function of the adrenal cortex reticularis zone (beta = 0.008, 95% CI: 0.002-0.013, P = 0.0057). The cML-MA method supported our estimate (beta = 0.009, 95% CI: 0.004-0.013, P = 2 × 10- 4). Parasutterella, Sutterella, and Anaerofilum affect the functioning of different regions of the adrenal gland. Notably, pleiotropy was not observed. Our findings revealed that the gut microbiota is causally associated with adrenal function. This enhances our understanding of the gut-microbiota-brain axis and provides assistance in the early diagnosis and treatment of adrenal-related diseases in clinical practice.

Association of the gut microbiome and different phenotypes of COPD and asthma: a bidirectional Mendelian randomization study

Mounting evidence has revealed the association between gut microbiota and both chronic obstructive pulmonary disease (COPD) and asthma; however, the causal association between gut microbiota and specific disease phenotypes remains to be determined. This study employed bidirectional two-sample Mendelian randomization (MR) analyses to investigate the potential causal relationship between gut microbiota and these conditions. The research utilized genome-wide association study (GWAS) data from the MiBioGen consortium for gut microbiota and the integrative epidemiology unit (IEU) Open GWAS for these conditions. Four MR analysis methods were employed: the inverse variance weighted (IVW) test, MR-Egger, weighted median, and weighted mode methods. The IVW method results are considered the primary findings. Sensitivity analyses, including heterogeneity tests, horizontal pleiotropy analysis, and leave-one-out analysis, were used to enhance robustness. Our MR study identified eight gut microbiota taxa potentially associated with the risk of different types of COPD and asthma. These include two taxa for early-onset COPD: Streptococcaceae [odds ratio (OR) = 1.315, 95% confidence interval (CI) = 1.071-1.616, P = 0.009] and Holdemanella (OR = 1.199, 95% CI = 1.063-1.352, P = 0.003); three for later-onset COPD: Acidaminococcaceae (OR = 1.312, 95% CI = 1.098-1.567, P = 0.003), Holdemania (OR = 1.165, 95% CI = 1.039-1.305, P = 0.009), and Marvinbryantia (OR = 0.814, 95% CI = 0.697-0.951, P = 0.009); one for allergic asthma: Butyricimonas (OR = 0.794, 95% CI = 0.693-0.908, P = 0.001); and two for non-allergic asthma: Clostridia (OR = 1.255, 95% CI = 1.043-1.511, P = 0.016) and Clostridiales (OR = 1.256, 95% CI = 1.048-1.506, P = 0.014).IMPORTANCEIndividuals with diverse phenotypes of chronic obstructive pulmonary disease (COPD) and asthma exhibit different responses to the conventional "one treatment fits all" approach. Recent research has revealed the significant role of the gut-lung axis in both COPD and asthma. However, the specific impact of gut microbiota on different subtypes of these conditions remains poorly understood. Our study has identified eight gut microbiota that may be associated with the risk of different types of COPD and asthma. These findings provide evidence suggesting a potential causal relationship between gut microbiota and various phenotypes of COPD and asthma. This offers a new perspective on the origins of different disease phenotypes and points toward future exploration of phenotype-specific and personalized therapies.

Investigating the Causal Relationship Between Gut Microbiota and Allergic Conjunctivitis: A Two-Sample Mendelian Randomization Study

PURPOSE

To investigate the causal association between gut microbiota and allergic conjunctivitis.

METHODS

A two-sample Mendelian randomization (MR) analysis was performed using the summary statistics of gut microbiota (18,340) from MiBio-Gen consortium and allergic conjunctivitis data (n = 218,792) obtained from the IEU Open GWAS project. F-statistics and sensitivity analyses were used to address potential biases and ensure the reliability of our findings. Reverse MR analysis was conducted to assess the possible of reverse causal relationships.

RESULTS

The inverse variance weighted estimates revealed the protective potential of the phylum Euryarchaeota against allergic conjunctivitis (OR = 0.87, p = 6.17 × 10-4). On the other hand, the genus Christensenellaceae R.7 group (OR = 0.75, p = 2.89 × 10-3), family Peptostreptococcaceae (OR = 0.83, p = 6.22 × 10-3), genus Lachnospiraceae FCS020 group (OR = 0.82, p = 0.02) all showed a suggestive protective association with allergic conjunctivitis. Additionally, sensitivity analysis confirmed the robustness of the above associations. In the reverse MR analysis, no significant causal association was found between gut microbiota and allergic conjunctivitis.

CONCLUSION

This study has revealed a potential causal correlation between the phylum Euryarchaeota and allergic conjunctivitis, offering new insights to improve prevention and treatment of this condition.

Causal relationship between gut microbiota and childhood obesity: A Mendelian randomization study and case-control study

BACKGROUND

Gut microbiota and obesity are deeply interconnected. However, the causality in the relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between gut microbiota and childhood obesity.

METHODS

Genetic summary statistics for the gut microbiota were obtained from the MiBioGen consortium. Genome-wide association studies (GWAS) summary data for childhood obesity were obtained from North American, Australian, and European collaborative genome-wide meta-analyses. Mendelian randomization (MR) analyses were performed using the inverse variance weighting method. 16 children with obesity and 16 without obesity were included for clinical observation, and their weight, body mass index, blood lipid levels, and gut microbiology were assessed. Paired t-test was the primary method of data analysis, and statistical significance was set at P < 0.05.

RESULTS

MR identified 16 causal relationships between the gut microbiome and childhood obesity. In the case-control study, we found that five gut microorganisms differed between children with and without obesity, whereas three gut microorganisms changed after weight loss in children with obesity.

CONCLUSION

Our study provides new insights into the genetic mechanisms underlying gut microbiota and childhood obesity.

TRIAL REGISTRATION NUMBER

ChiCTR2300072179.

NAME OF REGISTRY

Change of intestinal flora and plasma metabolome in obese children and their weight loss intervention: a randomized controlled tria URL OF REGISTRY: https://www.chictr.org.cn/showproj.html.

DATE OF REGISTRATION

2023-06-06.

DATE OF ENROLMENT OF THE FIRST PARTICIPANT TO THE TRIAL

2023-06-07.

Dietary influences on urinary tract infections: unraveling the gut microbiota connection

This study employs Mendelian randomization to investigate the causal relationships between dietary factors, gut microbiota, and urinary tract infections (UTIs). Our analysis revealed statistically significant associations, including high alcohol intake, cheese, and oily fish consumption with UTI risk, as well as links between UTI risk and specific gut microbiota, such as Prevotellaceae, Butyrivibrio, Anaerotruncus, and Dorea. Additionally, we observed associations with inflammatory markers, including C-Reactive Protein and Interleukin-6. Although the observed effects of these dietary factors on UTI risk are minimal and may limit their clinical relevance, these findings can still hold significant implications at the population level in public health. This research offers novel insights into the interplay between diet, gut microbiota, and UTI risk, laying a foundation for future studies. Further research is warranted to validate these associations and to explore the underlying mechanisms and their broader impact on public health.

Causal Effects of Gut Microbiota and Metabolites on Chronic Obstructive Pulmonary Disease: A Bidirectional Two Sample Mendelian Randomization Study

Background

Recent evidence suggests that the gut microbiome and metabolites are intricately involved in Chronic Obstructive Pulmonary Disease (COPD) pathogenesis, yet the precise causal relationships remain unclear due to confounding factors and reverse causation. This study employs bidirectional two-sample Mendelian Randomization (MR) to clarify these connections.

Methods

Summary data from publicly available Genome-Wide Association Studies (GWAS) concerning the gut microbiome, metabolites, and COPD were compiled. The selection of genetic instrumental variables (Single Nucleotide Polymorphisms, or SNPs) for MR analysis was conducted meticulously, primarily utilizing the Inverse Variance Weighting (IVW) method, supplemented by MR-Egger regression and the Weighted Median (WM) approach. The evaluation of heterogeneity and horizontal pleiotropy was performed using Cochran's Q test, the MR-Egger intercept test, and the MR-PRESSO global test. Sensitivity analyses, including leave-one-out tests, were conducted to verify the robustness of our results. And the mediation effect of gut microbiota-mediated changes in metabolites on the causal relationship with COPD was analyzed.

Results

Our study identified nine significant gut microbiota taxa and thirteen known metabolites implicated in COPD pathogenesis. Moreover, associations between the onset of COPD and the abundance of five bacterial taxa, as well as the concentration of three known metabolites, were established. These findings consistently withstood sensitivity analyses, reinforcing their credibility. Additionally, our results revealed that gut microbiota contribute to the development of COPD by mediating changes in metabolites.

Conclusion

Our bidirectional Two-Sample Mendelian Randomization analysis has revealed reciprocal causal relationships between the abundance of gut microbiota and metabolite concentrations in the context of COPD. This research holds promise for identifying biomarkers for early COPD diagnosis and monitoring disease progression, thereby opening new pathways for prevention and treatment. Further investigation into the underlying mechanisms is essential to improve our understanding of COPD onset.

Dysbiosis of gut microbiota is associated with pathogenesis of peptic ulcer diseases through inflammatory proteins: A Mendelian randomization study

The gut microbiota and inflammatory proteins may affect the development of peptic ulcer disease. However, this association remains unclear. We analyzed genome-wide association study data of gut microbiota, inflammatory proteins, and peptic ulcer disease using Mendelian randomization with instrumental variables to assess causal relationships. Various statistical methods, including inverse variance weighting, Mendelian randomization Egger regression, and sensitivity analysis were employed to evaluate the data and calculate mediation ratios. Our findings reveal that the genus Butyriciccus plays a role in mitigating the adverse effects of gastric ulcers by 7.9%, primarily through reducing beta-negative growth factor levels. Additionally, the genus Lachnospiraceae UCG004 can significantly alleviate the negative outcomes of gastric ulcers and reduces hepatocyte growth factor and beta-reserve growth factor levels by 6.39% and 7.45%, respectively. This study highlights the independent and mediating effects of the gut microbiota and inflammatory proteins on peptic ulcers, offering insights on potential pathways and targets for future preventive interventions.

Gut microbiome and serum metabolome alterations associated with lactose intolerance (LI): a case‒control study and paired-sample study based on the American Gut Project (AGP)

Lactose intolerance (LI) is a prevalent condition characterized by gastrointestinal symptoms that arise following lactose consumption. Recent evidence suggests that the gut microbiome may influence lactose levels in the gut. However, there is limited understanding regarding the alterations in microbiota and metabolism between individuals with LI and non-LI. This study conducted a paired-sample investigation utilizing data from the American Gut Project (AGP) and performed metagenomic and untargeted metabolomic analyses in a Chinese cohort to explore the interaction between the gut microbiome and serum metabolites. In addition, fecal microbiota transplantation (FMT) experiments were conducted to further examine the impact of the LI-associated gut microbiome on inflammatory outcomes. We identified 14 microbial genera that significantly differed between LI and controls from AGP data. Using a machine learning approach, group separation was predicted based on seven species and nine metabolites in the Chinese cohort. Notably, increased levels of Escherichia coli in the LI group were negatively correlated with several metabolites, including PC (22:6/0:0), indole, and Lyso PC, while reduced levels of Faecalibacterium prausnitzii and Eubacterium rectale were positively correlated with indole and furazolidone. FMT-LI rats displayed visceral hypersensitivity and an altered gut microbiota composition compared to FMT-HC rats. Metagenomic and metabolomic analyses revealed an enrichment of MAPK signaling in LI, which was confirmed by FMT-LI rats showing higher expression of ERK and RAS, along with increased concentrations of proinflammatory cytokines. This study provides valuable insights into the disrupted microbial and metabolic traits associated with LI, emphasizing potential microbiome-based approaches for its prevention and treatment.

IMPORTANCE

Lactose intolerance (LI) is a prevalent condition characterized by gastrointestinal symptoms after lactose consumption due to a deficiency of lactase. There is limited understanding regarding the microbiota and metabolic alterations between individuals with LI and non-LI. This study represents the first exploration to investigate metagenomic and metabolomic signatures among subjects with lactose intolerance as far as our knowledge. We identified 14 microbial genera in the Western cohort and 7 microbial species, along with 9 circulating metabolites in the Chinese cohort, which significantly differed in LI patients. Metagenomic and metabolomic analyses revealed an enrichment of MAPK signaling in LI patients. This finding was confirmed by FMT-LI rats, exhibiting increased expression of ERK and RAS, along with higher concentrations of pro-inflammatory cytokines. Our study provides insights into the disrupted functional and metabolic traits of the gut microbiome in LI, highlighting potential microbiome-based approaches for preventing and treating LI.

Microbiome-metabolome analysis insight into the effects of high-salt diet on hemorheological functions in SD rats

The present study examined the effect of two dietary regimens with elevated salt concentrations (4% and 8% salt) on hemorheological functions of SD rats, and explored the underlying mechanisms mainly through microbiome-metabolome analysis. An 8% HSD substantially altered the hemorheological parameters, and compromised intestinal barrier integrity and reduced the short-chain fatty acid levels. The microbiome-metabolome analysis revealed that 49 genus-specific microorganisms and 156 metabolites showed a consistent trend after exposure to both 4% and 8% HSDs. Pathway analysis identified significant alterations in key metabolites within bile acid and arachidonic acid metabolism pathways. A two-sample Mendelian randomization (MR) analysis verified the link between high dietary salt intake and hemorheology. It also suggested that some key microbes and metabolites (such as Ruminococcaceae_UCG-005, Lachnospiraceae_NK4A136, Ruminiclostridium_6, and Ruminococcaceae_UCG-010, TXB-2, 11,12-diHETrE, glycochenodeoxycholate) may involve in abnormalities in blood rheology caused by high salt intake. Collectively, our findings underscored the adverse effects of high dietary salt on hemorheological functions and provide new insight into the underlying mechanism based on microbiome-metabolome analysis.

Gut microbiota and functional outcome after ischemic stroke: a Mendelian randomization study

Background

Previous studies have shown that gut microbiota dysbiosis could affect clinical prognosis through an unknown mechanism. However, the causal relationship between the gut microbiota and the functional outcome after ischemic stroke remains unclear. We aimed to investigate the causal association between the gut microbiota and the functional outcome after ischemic stroke using Mendelian randomization (MR).

Methods

Genetic instrumental variables associated with 211 bacterial traits were obtained from the MiBioGen consortium (N = 18,340). Data from genome-wide association studies (GWAS) for functional outcome after ischemic stroke were obtained from two phenotypes (i.e., overall stroke outcome and motor recovery). The inverse variance weighted method was used to estimate the causal association. Enrichment analysis was conducted based on the results of the MR analyses.

Results

The genetically predicted family Peptostreptococcaceae (OR = 0.63, 95% CI = 0.41-0.98, p = 0.038) and the genera LachnospiraceaeNK4A136 group (OR = 0.65, 95% CI = 0.43-1.00, p = 0.048), LachnospiraceaeUCG004 (OR = 0.54, 95% CI = 0.33-0.90, p = 0.017), and Odoribacter (OR = 0.40, 95% CI = 0.21-0.77, p = 0.006) presented a suggestive association with favorable functional outcome, while the genera Eubacterium oxidoreducens group (OR = 1.77, 95% CI = 1.11-2.84, p = 0.018) and RuminococcaceaeUCG005 (OR = 1.85, 95% CI = 1.15-2.96, p = 0.010) were associated with unfavorable functional outcome. The genetically predicted family Oxalobacteraceae (OR = 2.12, 95% CI = 1.10-4.11, p = 0.025) and the genus RuminococcaceaeUCG014 (OR = 4.17, 95% CI = 1.29-13.52, p = 0.017) showed a suggestive association with motor recovery, while the order Enterobacteriales (OR = 0.14, 95% CI = 0.02-0.87, p = 0.035) and the family Enterobacteriaceae (OR = 0.14, 95% CI = 0.02-0.87, p = 0.035) were associated with motor weakness. Enrichment analysis revealed that regulation of the synapse structure or activity may be involved in the effect of the gut microbiota on the functional outcome after ischemic stroke.

Conclusions

This study provides genetic support that the gut microbiota, especially those associated with short-chain fatty acids, could affect stroke prognosis by mediating synapse function. Our findings suggest that modifying the composition of the gut microbiota could improve the prognosis of ischemic stroke.

Dissecting causal relationships between gut microbiome, immune cells, and brain injury: A Mendelian randomization study

Increasing literature has affirmed that changes in the gut microbiome (GM) composition were linked to distinct brain injury (BI) through the gut-brain axis, but it is uncertain if such links reflect causality. Further, the immune cell changes mediating the impact of GM on BI are not completely understood. We made use of the summary statistics of 211 GM (MiBioGen consortium), 731 immune cells, and 2 different BIs (FinnGen consortium), namely traumatic BI (TBI) and focal BI (FBI), from the extensive genome-wide association studies to date. We executed bidirectional Mendelian randomization (MR) analyses to ascertain the causal relationships between the GM and BI, and 2-step MR to validate possible mediating immune cells. Additionally, thorough sensitivity analyses verified the heterogeneity, robustness, as well as horizontal pleiotropy of the results. Based on the results of inverse-variance weighted (IVW) and sensitivity analyses, in MR analyses, 5 specific GM taxa and 6 specific GM taxa were causally associated with FBI and TBI, respectively; 27 immunophenotypes and 39 immunophenotypes were causally associated with FBI and TBI, respectively. Remarkably, Anaerofilum, LachnospiraceaeNC2004group, RuminococcaceaeUCG004, CCR2 on myeloid dendritic cell (DC), CD123 on CD62L+ plasmacytoid DC, and CD123 on plasmacytoid DC were causally associated with TBI and FBI (all P < .040). However, our reverse MR did not indicate any influence of TBI and FBI on the specific GM. In mediation analysis, we found that the associations between Escherichia.Shigella and FBI were mediated by CD123 on CD62L + plasmacytoid DC in addition to CD123 on plasmacytoid DC, each accounting for 4.21% and 4.21%; the association between FamilyXIIIAD3011group and TBI was mediated by CCR2 on myeloid DC, with mediated proportions of 5.07%. No remarkable horizontal pleiotropy or heterogeneity of instrumental variables was detected. Our comprehensive MR analysis first provides insight into potential causal links between several specific GM taxa with FBI/TBI. Additionally, CD123 on plasmacytoid DC in conjunction with CCR2 on myeloid DC may function in gut microbiota-host crosstalk in FBI and TBI, correspondingly. Further studies are critical to unravel the underlying mechanisms of the links between GM and BI.

Unveiling genetic links between gut microbiota and asthma: a Mendelian randomization

Background

Multiple studies suggest a potential connection between the gut microbiome and asthma. Our objective is to use advanced genetic and metagenomic techniques to elucidate the causal relationships and underlying mechanisms between gut microbiota and asthma.

Methods

The study utilized comprehensive Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) analyses to examine the relationship between 119 gut microbiota genera and asthma, using publicly accessible genome-wide association studies (GWAS). The meta-analysis synthesized summary effect estimates obtained from LDSC, forward MR, and reverse MR. The MiBioGen collaboration, involving 18,340 individuals, identified genetic variations associated with gut bacteria. Asthma data were collected from the UK Biobank, FinnGen, and GERA, encompassing a total of 82,060 cases and 641,049 controls.

Results

LDSC analysis revealed significant negative genetic correlations between asthma and RuminococcaceaeUCG004 (Rg = -0.55, p = 7.66 × 10-5) and Subdoligranulum (Rg = -0.35, p = 3.61 × 10-4). Forward MR analysis suggested associations between Butyricicoccus (OR = 0.92, p = 0.01), Turicibacter (OR = 0.95, p = 0.025), Butyrivibrio (OR = 0.98, p = 0.047), and reduced asthma risk. Conversely, Coprococcus2 (OR = 1.10, p = 0.035) and Roseburia (OR = 1.07, p = 0.039) were associated with increased risk. Reverse MR analysis indicated significant associations between genetically predicted asthma and Eubacteriumxylanophilumgroup (Beta = -0.08, p = 9.25 × 10-7), LachnospiraceaeNK4A136group (Beta = -0.05, p = 1.26 × 10-4), and Eisenbergiella (Beta = 0.06, p = 0.015, Rg_P = 0.043).

Conclusion

The findings underscore significant genetic correlations and causal relationships between specific gut microbiota and asthma. These insights highlight the potential of gut microbiota as both markers and modulators of asthma risk, offering new avenues for targeted therapeutic strategies.

Investigating the causal link between gut microbiota and dry age-related macular degeneration: a bidirectional Mendelian randomization study

AIM

To assess the causal link between 211 gut microbiota (GM) taxa and dry age-related macular degeneration (dAMD) risk.

METHODS

Mendelian randomization using instrumental factors taken from a genome-wide association study (GWAS) were used. Inverse variance weighted (IVW) analysis and sensitivity analysis were performed on the FinnGen project, which included 5095 cases and 222 590 controls.

RESULTS

The IVW analysis showed substantial genus- and family-level relationships between GM taxa and dAMD risk. Specifically, the family Peptococcaceae (P=0.03), genus Bilophila (P=3.91×10-3), genus Faecalibacterium (P=6.55×10-3), and genus Roseburia (P=0.04) were linked to a higher risk of developing dAMD, while the genus Candidatus Soleaferrea (P=7.75×10-4), genus Desulfovibrio (P=0.04) and genus Eubacterium ventriosum group (P=0.04) exhibited a protective effect against dAMD. No significant causal relationships were observed at higher taxonomic levels. Additionally, in the reverse IVW analysis, no meaningful causal effects of the 7 GM taxa.

CONCLUSION

These findings give support for the gut-retina axis participation in dAMD and shed light on putative underlying processes. Investigations on the connection between GM and dAMD have not yet revealed the underlying mechanism.

Metabolic mediators: microbial-derived metabolites as key regulators of anti-tumor immunity, immunotherapy, and chemotherapy

The human microbiome has recently emerged as a focal point in cancer research, specifically in anti-tumor immunity, immunotherapy, and chemotherapy. This review explores microbial-derived metabolites, emphasizing their crucial roles in shaping fundamental aspects of cancer treatment. Metabolites such as short-chain fatty acids (SCFAs), Trimethylamine N-Oxide (TMAO), and Tryptophan Metabolites take the spotlight, underscoring their diverse origins and functions and their profound impact on the host immune system. The focus is on SCFAs' remarkable ability to modulate immune responses, reduce inflammation, and enhance anti-tumor immunity within the intricate tumor microenvironment (TME). The review critically evaluates TMAO, intricately tied to dietary choices and gut microbiota composition, assessing its implications for cancer susceptibility, progression, and immunosuppression. Additionally, the involvement of tryptophan and other amino acid metabolites in shaping immune responses is discussed, highlighting their influence on immune checkpoints, immunosuppression, and immunotherapy effectiveness. The examination extends to their dynamic interaction with chemotherapy, emphasizing the potential of microbial-derived metabolites to alter treatment protocols and optimize outcomes for cancer patients. A comprehensive understanding of their role in cancer therapy is attained by exploring their impacts on drug metabolism, therapeutic responses, and resistance development. In conclusion, this review underscores the pivotal contributions of microbial-derived metabolites in regulating anti-tumor immunity, immunotherapy responses, and chemotherapy outcomes. By illuminating the intricate interactions between these metabolites and cancer therapy, the article enhances our understanding of cancer biology, paving the way for the development of more effective treatment options in the ongoing battle against cancer.

The Causal Relationships Between Gut Microbiota, Brain Volume, and Intelligence: A Two-Step Mendelian Randomization Analysis

BACKGROUND

Growing evidence indicates that dynamic changes in gut microbiome can affect intelligence; however, whether these relationships are causal remains elusive. We aimed to disentangle the poorly understood causal relationship between gut microbiota and intelligence.

METHODS

We performed a 2-sample Mendelian randomization (MR) analysis using genetic variants from the largest available genome-wide association studies of gut microbiota (N = 18,340) and intelligence (N = 269,867). The inverse-variance weighted method was used to conduct the MR analyses complemented by a range of sensitivity analyses to validate the robustness of the results. Considering the close relationship between brain volume and intelligence, we applied 2-step MR to evaluate whether the identified effect was mediated by regulating brain volume (N = 47,316).

RESULTS

We found a risk effect of the genus Oxalobacter on intelligence (odds ratio = 0.968 change in intelligence per standard deviation increase in taxa; 95% CI, 0.952-0.985; p = 1.88 × 10-4) and a protective effect of the genus Fusicatenibacter on intelligence (odds ratio = 1.053; 95% CI, 1.024-1.082; p = 3.03 × 10-4). The 2-step MR analysis further showed that the effect of genus Fusicatenibacter on intelligence was partially mediated by regulating brain volume, with a mediated proportion of 33.6% (95% CI, 6.8%-60.4%; p = .014).

CONCLUSIONS

Our results provide causal evidence indicating the role of the microbiome in intelligence. Our findings may help reshape our understanding of the microbiota-gut-brain axis and development of novel intervention approaches for preventing cognitive impairment.

Dissecting the causal links between gut microbiome, immune traits and polyp using genetic evidence

Background

Previous research has demonstrated an association between gut microbiota and immune status with the development of several diseases. However, whether these factors contribute to polyps remains unclear. This study aims to use Mendelian randomization (MR) to investigate the causal relationship between gut microbiota and 4 types of polyps (nasal, gallbladder, colon, and gastric polyps), as well as to analyze the mediating role of immune traits.

Methods

This study utilized large-scale GWAS meta-analyses of gut microbiota (MiBioGen Consortium), 731 immune traits, and 4 types of polyps (one from the FinnGen Consortium and three from the NBDC Human Database). Univariate MR with the inverse variance weighted (IVW) estimation method was employed as the primary analytical approach. A two-step MR analysis was performed to identify potential mediating immune traits. Additionally, multivariable MR approach based on Bayesian model averaging (MR-BMA) was employed to further prioritize gut microbiota and immune traits associated with polyp development.

Results

Based on IVW method in univariate MR analysis, we identified 39 gut microbial taxa and 135 immune traits significantly causally associated with at least one type of polyp. For nasal polyps, 13 microbial taxa and 61 immune traits were causally associated. After false discovery rate (FDR) correction, CD3 on Central Memory CD8+ T cells and CD3 on CD4 regulatory T cells remained significant. MR-BMA identified 4 gut microbial taxa and 4 immune traits as high priority. For gallbladder polyps, 9 microbial taxa and 30 immune traits were causally associated. MR-BMA identified 8 microbial taxa and 6 immune traits as higher importance. For colon polyps, 6 microbial taxa and 21 immune traits were causally associated. MR-BMA identified 4 microbial taxa and 3 immune traits as higher importance. For gastric polyps, 12 microbial taxa and 33 immune traits were causally associated. Actinobacteria remained significant after FDR correction, and MR-BMA identified 7 gut microbial taxa and 6 immune traits as high priority. We identified 16 causal pathways with mediator directions consistent with the direction of gut microbiome-polyp association. Of these, 6 pathways were associated with the mechanism of nasal polyps, 1 with gallbladder polyps, 2 with colon polyps, and 7 with gastric polyps.

Conclusions

Our findings shed light on the causal relationships between gut microbiota, immune traits, and polyp development, underscoring the crucial roles of gut microbiota and immune status in polypogenesis. Furthermore, these findings suggest potential applications in polyp prevention, early screening, and the development of effective strategies to reduce polyp risk.

Uncovering a Causal Connection between Gut Microbiota and Six Thyroid Diseases: A Two-Sample Mendelian Randomization Study

BACKGROUND

Recent studies have established associations between the gut microbiota (GM) and thyroid diseases (TDs). However, their causal relationships remain elusive.

METHODS

To investigate this causality, we conducted a two-sample Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data from MiBioGen and FinnGen, with GM as the exposure and six TDs as outcomes.

RESULTS

We identified 32 microbial taxa linked to the risk of six TDs. The Clostridium innocuum group, Ruminiclostridium5, and Lachnoclostridium exhibited protective effects against nontoxic diffuse goiter (NDG). Conversely, an increased risk of NDG was associated with Ruminococcaceae UCG002, Alistipes, Methanobrevibacter, Marvinbryantia, and Ruminococcaceae UCG014. Bifidobacterium and Sutterella were protective against nontoxic multinodular goiter (NMG), while the Ruminococcus gauvreauii group and Rikenellaceae RC9 gut group heightened NMG risk. Protective effects against nontoxic single thyroid nodule (NSTN) were observed with Defluviitaleaceae UCG011, Ruminococcus1, and Ruminococcaceae UCG010, whereas increased risk was linked to Alistipes, the Ruminococcus gauvreauii group, and Lachnospiraceae UCG010. Ruminiclostridium9, Victivallis, and Butyricimonas offered protection against thyrotoxicosis with Graves' Disease (GD), while the Eubacterium rectale group, Desulfovibrio, Bifidobacterium, Collinsella, Oscillospira, and Catenibacterium were risk factors. For thyrotoxicosis with Plummer Disease (PD), protective taxa included Butyricimonas and Lachnospira, whereas Dorea, Eggerthella, Odoribacter, Lactobacillus, Intestinimonas, and Phascolarctobacterium increased risk. Lastly, Parasutterella was protective against thyrotoxicosis with toxic single thyroid nodule (TSTN), while increased risk was associated with Sutterella, Oscillibacter, and Clostridium sensu stricto1.

CONCLUSIONS

Our findings support a causal relationship between specific GM and TDs at the genetic level, laying the foundation for future research into potential mechanisms and the identification of novel therapeutic targets.

Causality investigation among gut microbiota, immune cells, and prostate diseases: a Mendelian randomization study

Background

The gut microbiota has been demonstrated to have a significant role in the pathogenesis and progression of a variety of diseases, including prostate cancer, prostatitis, and benign prostatic hyperplasia. Potential links between prostate diseases, immune cells and the gut microbiota have not been adequately investigated.

Methods

MR studies were conducted to estimate the effects of instrumental variables obtained from genome-wide association studies (GWASs) of 196 gut microbial taxa and 731 immune cells on the risk of prostate diseases. The primary method for analysing causal relationships was inverse variance-weighted (IVW) analysis, and the MR results were validated through various sensitivity analyses.

Results

MR analysis revealed that 28 gut microbiome taxa and 75 immune cell types were significantly associated with prostate diseases. Furthermore, reverse MR analysis did not support a causal relationship between prostate diseases and the intestinal microbiota or immune cells. Finally, the results of the mediation analysis indicated that Secreting Treg % CD4 Treg, Activated & resting Treg % CD4 Treg, and Mo MDSC AC inhibited the role of the class Mollicutes in reducing the risk of PCa. In prostatitis, CD8+ T cells on EM CD8br hinder the increased risk associated with the genus Eubacterium nodatum group. Interestingly, in BPH, CD28- CD25++CD8br AC and CD16-CD56 on HLA DR+ NK promoted the role of the genus Dorea in reducing the risk of BPH.

Conclusion

This study highlights the complex relationships among the gut microbiota, immune cells and prostate diseases. The involvement of the gut microbiota in regulating immune cells to impact prostate diseases could provide novel methods and concepts for its therapy and management.

Networks of human milk microbiota are associated with host genomics, childhood asthma, and allergic sensitization

The human milk microbiota (HMM) is thought to influence the long-term health of offspring. However, its role in asthma and atopy and the impact of host genomics on HMM composition remain unclear. Through the CHILD Cohort Study, we followed 885 pregnant mothers and their offspring from birth to 5 years and determined that HMM was associated with maternal genomics and prevalence of childhood asthma and allergic sensitization (atopy) among human milk-fed infants. Network analysis identified modules of correlated microbes in human milk that were associated with subsequent asthma and atopy in preschool-aged children. Moreover, reduced alpha-diversity and increased Lawsonella abundance in HMM were associated with increased prevalence of childhood atopy. Genome-wide association studies (GWASs) identified maternal genetic loci (e.g., ADAMTS8, NPR1, and COTL1) associated with HMM implicated with asthma and atopy, notably Lawsonella and alpha-diversity. Thus, our study elucidates the role of host genomics on the HMM and its potential impact on childhood asthma and atopy.

Causal relationships between gut microbiota and polycystic ovarian syndrome: A bidirectional Mendelian randomization study

INTRODUCTION

Previous studies have established a link between gut microbiota and polycystic ovary syndrome (PCOS), but little is known about their precise causal relationship. Therefore, this study aims to explore whether there are precise causal relationships between gut microbiota and PCOS.

MATERIAL AND METHODS

We performed a bidirectional two-sample Mendelian randomization (MR) analysis. Datasets were from the largest published meta-analysis on gut microbiota composition and the FinnGen cohort of the IEU Open Genome-Wide Association Study Project database. Inverse variance weighted (IVW), MR-Egger, constrained maximum likelihood-based Mendelian randomization, weighted median, weighted mode, and simple mode were used. Cochran's Q and MR-Egger intercept tests were employed to measure the heterogeneity.

RESULTS

A total of 211 gut microbiota taxa were identified in MR analysis. Nine taxa of bacteria, including Alphaproteobacteria (0.55, 0.30-0.99, p = 0.04), Bacilli (1.76, 1.07-2.91, p = 0.03), Bilophila (0.42, 0.23-0.77, p < 0.01), Blautia (0.16, 0.03-0.79, p = 0.02), Burkholderiales (2.37, 1.22-4.62, p = 0.01), Candidatus Soleaferrea (0.65, 0.43-0.98, p = 0.04), Cyanobacteria (0.51, 0.31-0.83, p = 0.01), Holdemania (0.53, 0.35-0.81, p < 0.01), and Lachnospiraceae (1.86, 1.04-3.35, p = 0.03), were found to be associated with PCOS in the above MR methods included at least IVW method. Cochran's Q statistics and MR-Egger intercept test suggested no significant heterogeneity. In addition, 69 taxa were shown significant for at least the IVW method in reverse MR analysis, of these, 25 had a positive correlation, and 37 had a negative correlation. Additionally, Alphaproteobacteria and Lachnospiraceae (0.95, 0.91-0.98, p < 0.01; 0.97, 0.94-0.99, p = 0.02, respectively) were shown a bidirected causally association with PCOS.

CONCLUSIONS

Our study provides evidence of the bidirectional causal association between gut microbiota and PCOS from a genetic perspective.

Causal roles of skin and gut microbiota in skin appendage disorders suggested by genetic study

Objectives

There is evidence from observational studies that human microbiota is linked to skin appendage Disorders (SADs). Nevertheless, the causal association between microbiota and SADs is yet to be fully clarified.

Methods

A comprehensive two-sample Mendelian randomization (MR) was first performed to determine the causal effect of skin and gut microbiota on SADs. A total of 294 skin taxa and 211 gut taxa based on phylum, class, order, family, genus, and ASV level information were identified. Summary data of SADs and eight subtypes (acne vulgaris, hidradenitis suppurativa, alopecia areata, rogenic alopecia, rosacea, rhinophyma, seborrhoeic dermatitis, and pilonidal cyst) were obtained from the FinnGen consortium. We performed bidirectional MR to determine whether the skin and gut microbiota are causally associated with multiple SADs. Furthermore, sensitivity analysis was conducted to examine horizontal pleiotropy and heterogeneity.

Results

A total of 65 and 161 causal relationships between genetic liability in the skin and gut microbiota with SADs were identified, respectively. Among these, we separately found 5 and 11 strong causal associations that passed Bonferroni correction in the skin and gut microbiota with SADs. Several skin bacteria, such as Staphylococcus, Streptococcus, and Propionibacterium, were considered associated with multiple SADs. As gut probiotics, Bifidobacteria and Lactobacilli were associated with a protective effect on SAD risk. There was no significant heterogeneity in instrumental variables or horizontal pleiotropy.

Conclusions

Our MR analysis unveiled bidirectional causal relationships between SADs and the gut and skin microbiota, and had the potential to offer novel perspectives on the mechanistic of microbiota-facilitated dermatosis.

Fine mapping-based multi-omics analysis interprets the gut-lung axis function of SGLT2 inhibitors

Background

Currently, Sodium-glucose cotransporter 2 (SGLT2) inhibitors demonstrate additional effects beyond glucose control on the gut microbiota and circulating metabolites. The gut microbiota and metabolites have been found to be useful in elucidating potential biological mechanisms of pulmonary diseases. Therefore, our study aims to investigate the effects of gut microbiota and metabolites mediating SGLT2 inhibition in 10 pulmonary diseases through Mendelian randomization (MR) research.

Methods

We conducted a two-sample, two-step MR study to assess the association between SGLT2 inhibition and 10 pulmonary diseases and to investigate the mediating effects of gut microbiota and metabolite. Gene-fine mapping and annotation of mediators by FUMA and Magma analyses were performed, and causal associations of mapped genes with diseases were assessed by muti-omics MR analyses. Possible side effects of SGLT2 inhibition were assessed by PheWAS analysis.

Results

SGLT2 inhibition was linked to a reduced risk of T2DM, Interstitial lung disease (ILD), Pneumoconiosis, Pulmonary tuberculosis, and Asthma(OR=0.457, 0.054, 0.002, 0.280, 0.706). The family Enterobacteriaceae and order Enterobacteriales were associated with SGLT2 inhibition and ILD(95% CI:0.079-0.138). The family Alcaligenaceae and X-12719 were linked to pneumoconiosis (95% CI: 0.042-0.120, 0.050-0.099). The genus Phascolarctobacterium was connected to pulmonary tuberculosis (95% CI: 0.236-0.703).The degree of unsaturation (Fatty Acids), ratio of docosahexaenoic acid to total fatty acids, and 4-androsten-3beta,17beta-diol disulfate 2, were associated with asthma(95% CI: 0.042-0.119, 0.039-0.101, 0.181-0.473). Furthermore, Fuma and Magma analyses identified target genes for the four diseases, and proteomic MR analysis revealed six overlapping target genes in asthma. PheWAS analysis also highlighted potential side effects of SGLT2 inhibition.

Conclusions

This comprehensive study strongly supports a multi-omics association between SGLT2 inhibition and reduced risk of interstitial lung disease, tuberculosis, pneumoconiosis, and asthma. Four identified gut microbiota, four metabolites, sixteen metabolic pathways, and six target genes appear to play a potential role in this association. The results of the comprehensive phenome-wide association analysis also identified the full effect of SGLT2 inhibitors.

Causal associations between gut microbiota, circulating inflammatory proteins, and epilepsy: a multivariable Mendelian randomization study

Background

Previous studies have suggested that gut microbiota (GM) may be involved in the pathogenesis of epilepsy through the microbiota-gut-brain axis (MGBA). However, the causal relationship between GM and different epilepsy subtypes and whether circulating inflammatory proteins act as mediators to participate in epileptogenesis through the MGBA remain unclear. Therefore, it is necessary to identify specific GM associated with epilepsy and its subtypes and explore their underlying inflammatory mechanisms for risk prediction, personalized treatment, and prognostic monitoring of epilepsy.

Methods

We hypothesized the existence of a pathway GM-inflammatory proteins-epilepsy. We found genetic variants strongly associated with GM, circulating inflammatory proteins, epilepsy and its subtypes, including generalized and partial seizures, from large-scale genome-wide association studies (GWAS) summary data and used Multivariate Mendelian Randomization to explore the causal relationship between the three and whether circulating inflammatory proteins play a mediating role in the pathway from GM to epilepsy, with inverse variance weighted (IVW) method as the primary statistical method, supplemented by four methods: MR-Egger, weighted median estimator (WME), Weighted mode and Simple mode.

Results

16 positive and three negative causal associations were found between the genetic liability of GM and epilepsy and its subtypes. There were nine positive and nine negative causal associations between inflammatory proteins and epilepsy and its subtypes. Furthermore, we found that C-X-C motif chemokine 11 (CXCL11) levels mediated the causal association between Genus Family XIII AD3011 group and epilepsy.

Conclusion

Our study highlights the possible causal role of specific GM and specific inflammatory proteins in the development of epilepsy and suggests that circulating inflammatory proteins may mediate epileptogenesis through the MGBA.

Gut microbiota and risk of ankylosing spondylitis

OBJECTIVE

Observational studies have established a connection between gut microbiota and ankylosing spondylitis (AS) risk; however, whether the observed associations are causal remains unclear. Therefore, we conducted a two-sample Mendelian randomization (MR) analysis to assess the potential causal associations of gut microbiota with AS risk.

METHODS

Instrumental variants of gut microbiota were obtained from the MiBioGen consortium (n = 18,340) and the Dutch Microbiome Project (n = 7738). The FinnGen consortium provided genetic association summary statistics for AS, encompassing 2860 cases and 270,964 controls. We used the inverse-variance weighted (IVW) method as the primary analysis, supplemented with the weighted median method, maximum likelihood-based method, MR pleiotropy residual sum and outlier test, and MR-Egger regression. In addition, we conducted a reverse MR analysis to assess the likelihood of reverse causality.

RESULTS

After the Bonferroni correction, species Bacteroides vulgatus remained statistically significantly associated with AS risk (odds ratio (OR) 1.55, 95% confidence interval (CI) 1.22-1.95, P = 2.55 × 10-4). Suggestive evidence of associations of eleven bacterial traits with AS risk was also observed (P < 0.05 by IVW). Among them, eight were associated with an elevated AS risk (OR 1.37, 95% CI 1.07-1.74, P = 0.011 for phylum Verrucomicrobia; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for class Verrucomicrobiae; OR 1.17, 95% CI 1.01-1.36, P = 0.035 for order Bacillales; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for order Verrucomicrobiales; OR 1.43, 95% CI 1.13-1.82, P = 0.003 for family Alcaligenaceae; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for family Verrucomicrobiaceae; OR 1.31, 95% CI 1.03-1.65, P = 0.026 for genus Akkermansia; OR 1.55, 95% CI 1.19-2.02, P = 0.001 for species Sutterella wadsworthensis). Three traits exhibited a negative association with AS risk (OR 0.68, 95% CI 0.53-0.88, P = 0.003 for genus Dialister; OR 0.84, 95% CI 0.72-0.97, P = 0.020 for genus Howardella; OR 0.75, 95% CI 0.59-0.97, P = 0.026 for genus Oscillospira). Consistent associations were observed when employing alternate MR methods. In the reverse MR, no statistically significant correlations were detected between AS and these bacterial traits.

CONCLUSION

Our results revealed the associations of several gut bacterial traits with AS risk, suggesting a potential causal role of gut microbiota in AS development. Nevertheless, additional research is required to clarify the mechanisms by which these bacteria influence AS risk. Key Points • The association of gut microbiota with AS risk in observational studies is unclear. • This MR analysis revealed associations of 12 gut bacterial traits with AS risk.

Purified fibers in chemically defined synthetic diets destabilize the gut microbiome of an omnivorous insect model

The macronutrient composition of a host's diet shapes its gut microbial community, with dietary fiber in particular escaping host digestion to serve as a potent carbon source for gut microbiota. Despite widespread recognition of fiber's importance to microbiome health, nutritional research often fails to differentiate hyper-processed fibers from cell-matrix derived intrinsic fibers, limiting our understanding of how individual polysaccharides influence the gut community. We use the American cockroach (Periplaneta americana) as a model system to dissect the response of complex gut microbial communities to diet modifications that are impossible to test in traditional host models. Here, we designed synthetic diets from lab-grade, purified ingredients to identify how the cockroach microbiome responds to six different carbohydrates (chitin, methylcellulose, microcrystalline cellulose, pectin, starch, xylan) in otherwise balanced diets. We show via 16S rRNA gene profiling that these synthetic diets reduce bacterial diversity and alter the phylogenetic composition of cockroach gut microbiota in a fiber-dependent manner, regardless of the vitamin and protein content of the diet. Comparisons with cockroaches fed whole-food diets reveal that synthetic diets induce blooms in common cockroach-associated taxa and subsequently fragment previously stable microbial correlation networks. Our research leverages an unconventional microbiome model system and customizable lab-grade artificial diets to shed light on how purified polysaccharides, as opposed to nutritionally complex intrinsic fibers, exert substantial influence over a normally stable gut community.

Causation between the gut microbiota and inguinal hernia: a two-sample double-sided Mendelian randomization study

Inguinal hernias are the most common type of enterocele and are frequently caused by defects in the abdominal wall muscles in the groin area. Numerous animal models and human studies have shown that the gut microbiota is associated with skeletal muscle aging and loss. However, the causation between the gut microbiota and inguinal hernia remains unclear. To reveal the causal association between the gut microbiota and inguinal hernia, we conducted a two-sample double-sided Mendelian randomization analysis. We used genome-wide association analysis (GWAS) summary statistics of the gut microbiota from the MiBioGen consortium and GWAS statistics of inguinal hernia from the FinnGen R10 database. The causation between the gut microbiota and inguinal hernia was explored through the inverse variance weighted (IVW) method, MR Egger regression method, weighted median method, weighted model method, and simple model method. Sensitivity analysis was used to test whether the Mendelian randomization analysis results were reliable. Reverse Mendelian randomization was used to conduct effect analysis and sensitivity analysis using the entire gut microbiota as the outcome. The IVW results indicated that Verrucomicrobia, Lactobacilliales, Clostridiaceae1, Butyricococcus, Categorybacter, Hungatella, Odoribacter, and Olsenella had a direct negative causation with the gut microbiota. The reverse Mendelian Randomization results showed that Eubacterium brachygroup, Eubacterium eligensgroup, Eubacterium xylanophilumgroup, Coprococcus3, Ruminococcus1, and Senegalimassilia were directly related to inguinal hernia. The bilateral sensitivity analysis revealed no heterogeneity or horizontal pleiotropy. The results confirmed that 8 bacterial traits had a negative causation with inguinal hernia. Reverse MR analysis revealed a positive correlation between inguinal hernia and 6 bacterial traits. Modulating the diversity and components of the gut microbiota is envisaged to contribute to improving the incidence and prognosis of inguinal hernia.

Exploring causal effects and potential mediating mechanisms of genetically linked environmental senses with intracerebral hemorrhage

The occurrence mechanism of intracerebral hemorrhage remains unclear. Several recent studies have highlighted the close relationship between environmental senses and intracerebral hemorrhage, but the mechanisms of causal mediation are inconclusive. We aimed to investigate the causal relationships and potential mechanisms between environmental senses and intracerebral hemorrhage. Multiple Mendelian randomization methods were used to identify a causal relationship between environmental senses and intracerebral hemorrhage. Gut microbiota and brain imaging phenotypes were used to find possible mediators. Enrichment and molecular interaction analyses were used to identify potential mediators and molecular targets. No causal relationship between temperature and visual perception with intracerebral hemorrhage was found, whereas long-term noise was identified as a risk factor for intracerebral hemorrhage (OR 2.95, 95% CI: 1.25 to 6.93, PIVW = 0.01). The gut microbiota belonging to the class Negativicutes and the order Selenomonadales and the brain image-derived phenotypes ICA100 node 54, edge 803, edge 1149, and edge 1323 played mediating roles. "Regulation of signaling and function in synaptic organization" is the primary biological pathway of noise-induced intracerebral hemorrhage, and ARHGAP22 may be the critical gene. This study emphasized the importance of environmental noise in the prevention, disease management, and underlying biological mechanisms of intracerebral hemorrhage.

No genetic causal association between human papillomavirus and lung cancer risk: a bidirectional two-sample Mendelian randomization analysis

INTRODUCTION

Several observational or retrospective studies have previously been conducted to explore the possible association between lung cancer and human papillomavirus (HPV) infection. However, there may be inconsistencies in the data and conclusions due to differences in study design and HPV testing methods. There are currently no studies that provide conclusive evidence to support the involvement of HPV in the occurrence and development of lung cancer. Therefore, the relationship between HPV and lung cancer remains controversial and uncertain. This study aimed to explore whether HPV infection is causally related to lung cancer risk by systematically performing a two-way Two-Sample Mendelian Randomization (TSMR) analysis.

METHODS

In the International Lung Cancer Consortium (ILCCO) genome-wide association study dataset, we included 11,348 lung cancer (LUCA) cases, including 3275 squamous cell carcinoma (LUSC) cases, 3442 adenocarcinoma (LUAD) cases, and 15,861 cases of control. Using genetic variants associated with the HPV E7 protein as instrumental variables, we summarized statistics associated with HPV infection in the MRC IEU OpenGWAS database, which included the HPV-16 E7 protein and the HPV-18 E7 protein. Two-sample Mendelian randomization (MR) results are expressed as odds ratios (OR) and 95% confidence intervals (CI).

RESULTS

Based on a comprehensive analysis of genome-wide association study (GWAS) data from public databases, we mainly used inverse-variance weighted (IVW) to estimate causal relationships, while using MR-Egger, weighted median, simple mode, and weighted mode, and other four methods as supplements. Two-sample MR Analysis revealed no causal relationship between exposure factors (HPV-16 E7 protein and HPV-18 E7 protein) and outcome factors (lung cancer (LUCA) and its subtypes squamous cell carcinoma (LUSC) and adenocarcinoma (LUAD)) in forward MR Analysis using the IVW approach.HPV-16 E7 protein and LUCA and its subtypes LUSC and LUAD by IVW method results: [OR] = 1.002; 95% [CI]: 0.961 - 1.045; p = 0.920; [OR] = 1.023; 95% [CI]: 0.966 - 1.084; p = 0.438; [OR] = 0.994; 95% [CI]: 0.927 - 1.066; p = 0.872); HPV-18 E7 protein and LUCA and its subtypes LUSC and LUAD by IVW method results: [OR] = 0.965; 95% [CI]: 0.914 - 1.019; p = 0.197; [OR] = 0.933; 95% [CI]: 0.834 - 1.043; p = 0.222; [OR] = 1.028; 95% [CI]: 0.945 - 1.118; p = 0.524. It was observed through reverse MR that LUCA and its subtypes LUSC and LUAD were used as exposure factors, and HPV infection (HPV-16 E7 protein and HPV-18 E7 protein) was used as the outcome factors, the results of the IVW method are also invalid.LUCA and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.036; 95% [CI]: 0.761 - 1.411; p = 0.82; [OR] = 1.318; 95% [CI]: 0.949 - 1.830; p = 0.099; LUSC and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.123; 95% [CI]0.847 - 1.489; p = 0.421; [OR] = 0.931; 95% [CI]: 0.660 - 1.313; p = 0.682; LUAD and HPV-16 E7 protein and HPV-18 E7 protein by IVW method results: [OR] = 1.182; 95% [CI] 0.983 - 1.421; p = 0.075; [OR] = 1.017; 95% [CI]: 0.817 - 1.267; p = 0.877.Our results indicate that there is no causal relationship between genetically predicted HPV infection and LUCA and its subtypes LUSC and LUAD. In addition, in the reverse MR analysis, we did not observe a significant causal relationship between LUCA and its subtypes LUSC and LUAD on HPV infection.

CONCLUSIONS

Our findings do not support a genetic association between HPV infection and lung cancer.

Causal Relationship Between Gut Microbiota and Chronic Obstructive Pulmonary Disease: A Bidirectional Two-Sample Mendelian Randomization Study

Background

The associations between gut microbiota and chronic obstructive pulmonary disease (COPD) have gained increasing attention and research interest among scholars. However, it remains unclear whether gut microbiota serves as a causal factor for COPD or if it is a consequence of the disease. Therefore, we investigated the causal relationship between COPD and gut microbiota, with intention of providing novel insights and references for clinical diagnosis and treatment.

Methods

Based on the genome-wide association study (GWAS) data, we employed MR-Egger regression, random-effects inverse variance-weighted (IVW) method, and weighted median method for bidirectional Mendelian randomization (MR) analysis. We conducted Cochran's Q test for heterogeneity assessment and performed multivariable analysis, sensitivity analysis, and heterogeneity testing to validate the reliability and stability of results.

Results

Utilizing MR analysis, mainly employing the IVW method, we detected a collective of 11 gut microbiota species that exhibited associations with COPD. Among them, Bacteroidia, family XIII, Clostridium innocuum group, Barnesiella, Collinsella, Lachnospiraceae NK4A136 group, Lachnospiraceae UCG004, Lachnospiraceae UCG010, and Bacteroidales were found to be protective factors for COPD. On the other hand, Holdemanella and Marvinbryantia were identified as risk factors for COPD. Individuals with elevated levels of Holdemanella exhibited a 1.141-fold higher risk of developing COPD compared to their healthy counterparts, and those with increased levels of Marvinbryantia had a 1.154-fold higher risk. Reverse MR analysis yielded no evidence indicating a causal relationship between gut microbiota and COPD occurrence.

Conclusion

Our study established a causal link between 11 specific gut microbiota species and COPD, offering novel insights and valuable references for targeted therapies in the clinical management of COPD. However, our results were mainly based on the analysis of database, and further clinical studies are needed to clarify the effects of gut microbiota on COPD and its specific protective mechanism.

The causal association between gut microbiota and postpartum depression: a two-sample Mendelian randomization study

Background

An escalating body of clinical trials and observational studies hints at a plausible link between gut flora and postpartum depression (PPD). The definitive causal dynamics between these two entities remain shrouded in ambiguity. Therefore, in this study, we employed the two-sample Mendelian randomization approach to ascertain the causal link between gut microbiota and PPD.

Methods

Summary-level GWAS data related to the human gut microbiota were obtained from the international consortium MiBioGen and the Dutch Microbiome Project (species). For PPD, GWAS data were derived from the FinnGen biobank, consisting 57,604 cases and 596,601 controls. The inverse variance weighted method (IVW) as the cornerstone of our analytical approach. Subsequent to this, a comprehensive suite of tests for pleiotropy and heterogeneity were conducted to ensure the reliability and robustness of our findings.

Results

We identified 12 bacterial taxa associated with the risk of PPD. Veillonellaceae, Ruminococcaceae UCG 011, Bifidobacterium adolescentis, Paraprevotella clara, Clostridium leptum, Eubacterium siraeum, Coprococcus catus exhibited an inversely associated with the risk of PPD. Alphaproteobacteria, Roseburia, FamilyXIIIAD3011group, Alistipes onderdonkii, Bilophila wadsworthia showed a positive correlation with the risk of PPD.

Limitations

The GWAS data derived from the MiBioGen consortium, DMP, and FinnGen consortium, may introduce selection bias. Moreover, the data primarily originates from European populations, hence extrapolating these results to diverse populations should be approached with caution. The etiological factors behind PPD remain enigmatic, alluding to the existence of potential undisclosed confounders.

Conclusion

Based on this MR analysis, we found a causal relationship between certain gut microbial communities and PPD. Future clinical studies can further explore the treatment of PPD through the combined use of microorganisms. This not only offers insights into the pathogenesis of PPD but also lays the foundation for utilizing gut microbiota as biotherapeutics in treating neurological disorders.

Mendelian randomization identifies causal associations between GWAS-associated bacteria and their metabolites and rheumatoid arthritis

Background

Accumulating evidence suggests that an imbalance of gut microbiota is commonly observed in patients with rheumatoid arthritis (RA). However, it remains unclear whether gut microbiota dysbiosis is a cause or consequence of RA, and the mechanisms by which gut dysbiosis contributes to RA have not been fully understood. This study aimed to investigate the causal relationship between gut microbiota and metabolites with RA.

Methods

A two-sample Mendelian randomization analysis was performed to estimate the causality of gut microbiota and metabolites on RA. A genome-wide association study (GWAS) of 211 gut microbiota and 217 metabolites was used as the exposure, whereas RA was treated as the outcome. Inverse variance weighted (IVW) was regarded as the primary approach for calculating causal estimates. MR Egger method, Weighted median method, Simple mode method, and weighted mode method were used for sensitive analysis. Metabolic pathway analysis was performed via the web-based Metaconflict 5.0. Additionally, an animal study was undertaken to evaluate the results inferred by Mendelian randomization.

Result

This study indicated that six gut microbiota taxa (RuminococcaceaeUCG013, Erysipelotrichia, Erysipelotrichaceae, Erysipelotrichales, Clostridia, and Veillonellaceae) were estimated to exert a positive impact on RA. Conversely, seven gut microbiota taxa (Oxalobacter, Cyanobacteria, RuminococcaceaeUCG002, LachnospiraceaeUCG010, Christensenellaceae, Oxalobacteraceae, Anaerostipes) were estimated to exert a negative impact on RA. Three metabolites, namely indole-3-propionate (IPA), glycine and sphingomyelin (SM 16:1), were found to be linked to lower RA risk, while five metabolites (argininosuccinate, CE 20_4, TAG 58_8, PC 40_6, and LPC 20_4) were linked to higher RA risk. Additionally, four metabolic pathways were identified by metabolic pathway analysis. The collagen-induced arthritis (CIA) rats exhibited a higher relative abundance of Class_Clostridia and a lower abundance of Genus_Lachnospiraceae (p < 0.05) than the healthy controls.

Conclusion

This study identified causal associations between specific gut microbiota, metabolites, and RA. These findings support the significant role of gut microbiota and metabolites in RA pathogenesis.

Gut microbiome and schizophrenia: insights from two-sample Mendelian randomization

Growing evidence suggests a potential link between the gut microbiome and schizophrenia. However, it is unclear whether the gut microbiome is causally associated with schizophrenia. We performed two-sample bidirectional Mendelian randomization to detect bidirectional causal relationships between gut microbiome and schizophrenia. Summary genome-wide association study (GWAS) datasets of the gut microbiome from the MiBioGen consortium (n = 18,340) and schizophrenia (n = 130,644) were utilized in our study. Then a cohort of sensitive analyses was followed to validate the robustness of MR results. We identified nine taxa that exerted positive causal effects on schizophrenia (OR: 1.08-1.16) and six taxa that conferred negative causal effects on schizophrenia (OR: 0.88-0.94). On the other hand, the reverse MR analysis showed that schizophrenia may increase the abundance of nine taxa (OR: 1.03-1.08) and reduce the abundance of two taxa (OR: 0.94). Our study unveiled mutual causal relationships between gut microbiome and schizophrenia. The findings may provide evidence for the treatment potential of gut microbiomes in schizophrenia.

Causal associations between gut microbiota and premature rupture of membranes: a two-sample Mendelian randomization study

Background

Previous study has indicated a potential link between gut microbiota and maternal pregnancy outcomes. However, the causal relationship between gut microbiota and premature rupture of membranes (PROM) remains a topic of ongoing debate.

Methods

A two-sample Mendelian Randomization (MR) study was used to investigate the relationship between gut microbiota and PROM. Genetic data on gut microbiota was obtained from the MiBioGen consortium's largest genome-wide association study (GWAS) (n=14,306). Genetic data on PROM (3011 cases and 104247 controls) were sourced from publicly available GWAS data from the Finnish National Biobank FinnGen consortium. Various methods including Inverse variance weighted (IVW), MR-Egger, simple mode, weighted median, and weighted mode were utilized to assess the causal relationship by calculating the odd ratio (OR) value and confidence interval (CI). Sensitivity analyses for quality control were performed using MR-Egger intercept tests, Cochran's Q tests, and leave-one-out analyses.

Results

The IVW method revealed that class Mollicutes (IVW, OR=0.773, 95%CI: 0.61-0.981, pval = 0.034), genus Marvinbryantia (IVW, OR=00.736, 95%CI: 0.555-0.977, pval = 0.034), genus Ruminooccaceae UCG003 (IVW, OR=0.734, 95%CI: 0.568-0.947, pval = 0.017) and phylum Tenericutes (IVW, OR=0.773, 95%CI: 0.566-1.067, pval = 0.034) were associated with a reduced risk of PROM, while genus Collinsella (IVW, OR=1.444, 95%CI: 1.028-2.026, pval = 0.034), genus Intestinibacter (IVW, OR=1.304, 95%CI: 1.047-1.623, pval = 0.018) and genus Turicibacter (IVW, OR=1.282, 95%CI: 1.02-1.611, pval = 0.033) increased the risk of PROM. Based on the other four supplementary methods, six gut microbiota may have a potential effect on PROM. Due to the presence of pleiotropy (pval=0.045), genus Lachnoclostridium should be ruled out. No evidence of horizontal pleiotropy or heterogeneity was found in other microbiota (pval >0.05).

Conclusions

In this study, we have discovered a causal relationship between the presence of specific probiotics and pathogens in the host and the risk of PROM. The identification of specific gut microbiota associated with PROM through MR studies offers a novel approach to diagnosing and treating this condition, thereby providing a new strategy for clinically preventing PROM.

Aging Modulates the Effect of Dietary Glycemic Index on Gut Microbiota Composition in Mice

BACKGROUND

Gut microbiome composition profoundly impacts host physiology and is modulated by several environmental factors, most prominently diet. The composition of gut microbiota changes over the lifespan, particularly during the earliest and latest stages. However, we know less about diet-aging interactions on the gut microbiome. We previously showed that diets with different glycemic indices, based on the ratio of rapidly digested amylopectin to slowly digested amylose, led to altered composition of gut microbiota in male C57BL/6J mice.

OBJECTIVES

Here, we examined the role of aging in influencing dietary effects on gut microbiota composition and aimed to identify gut bacterial taxa that respond to diet and aging.

METHODS

We studied 3 age groups of male C57BL/6J wild-type mice: young (4 mo), middle-aged (13.5 mo), and old (22 mo), all fed either high glycemic (HG) or low glycemic (LG) diets matched for caloric content and macronutrient composition. Fecal microbiome composition was determined by 16S rDNA metagenomic sequencing and was evaluated for changes in α- and β-diversity and bacterial taxa that change by age, diet, or both.

RESULTS

Young mice displayed lower α-diversity scores than middle-aged counterparts but exhibited more pronounced differences in β-diversity between diets. In contrast, old mice had slightly lower α-diversity scores than middle-aged mice, with significantly higher β-diversity distances. Within-group variance was lowest in young, LG-fed mice and highest in old, HG-fed mice. Differential abundance analysis revealed taxa associated with both aging and diet. Most differential taxa demonstrated significant interactions between diet and aging. Notably, several members of the Lachnospiraceae family increased with aging and HG diet, whereas taxa from the Bacteroides_H genus increased with the LG diet. Akkermansia muciniphila decreased with aging.

CONCLUSIONS

These findings illustrate the complex interplay between diet and aging in shaping the gut microbiota, potentially contributing to age-related disease.

Analysis of the causal relationship between gut microbiota and bone remodeling growth factor from the gene association

BACKGROUND

A growing body of evidence indicates a close association between the gut microbiota (GM) and the bone remodeling (BR) process, raising suspicions that the GM may actively participate in BR by modulating the levels of growth factors. However, the precise causal relationship between them remains unclear. Due to many confounding factors, many microorganisms related to BR growth factors have not been identified. We aimed to elucidate the causal relationship between the GM and BR growth factors.

METHODS

We evaluated the genome-wide association study (GWAS) summary statistics for GM and five common growth factors associated with BR: namely, bone morphogenetic proteins (BMP), transforming growth factors(TGF), insulin growth factors (IGFs), epidermal growth factors (EGFs), and fibroblast growth factors (FGF). The causal relationship between the GM and BR growth factors was studied by double-sample Mendelian randomized analysis. We used five Mendelian randomization (MR) methods, including inverse variance-weighted (IVW), MR-Egger, simple mode, weighted median, and weighted model methods.

RESULTS

Through MR analysis, a total of 56 bacterial genera were co-identified as associated with BMP, TGF, IGF, EGF, and FGF. Among them, eight genera were found to have a causal relationship with multiple growth factors: Marvinbryantia was causally associated with BMP-6 (P = 0.018, OR = 1.355) and TGF-β2 (P = 0.002, OR = 1.475); Lachnoclostridium, BMP-7 (P = 0.021, OR = 0.73) and IGF-1 (P = 0.046, OR = 0.804); Terrisporobacter, TGF-β (P = 0.02, OR = 1.726) and FGF-23 levels (P = 0.016, OR = 1.76); Ruminiclostridium5, TGF-β levels (P = 0.024, OR = 0.525) and FGFR-2 (P = 0.003, OR = 0.681); Erysipelatoclostridium, TGF-β2 (P = 0.001, OR = 0.739) and EGF and its receptor (EGFR) (P = 0.012, OR = 0.795); Eubacterium_brachy_group, FGFR-2 (P = 0.045, OR = 1.153) and EGF (P = 0.013, OR = 0.7); Prevotella9 with EGFR (P = 0.022, OR = 0.818) and FGFR-2 (P = 0.011, OR = 1.233) and Faecalibacterium with FGF-23 (P = 0.02, OR = 2.053) and IGF-1 (P = 0.005, OR = 0.843).

CONCLUSION

We confirmed the causal relationship between the GM and growth factors related to BR, which provides a new perspective for the study of BR, through targeted regulation of specific bacteria to prevent and treat diseases and growth factor-mediated BR disorders.

Gut Microbiome and colorectal cancer: discovery of bacterial changes with metagenomics application in Turkısh population

BACKGROUND

Colorectal cancer (CRC) is the 3rd most common cancer in the world and colonic carcinogenesis is a multifactorial disease that involves environmental and genetic factors. Gut microbiota plays a critical role in the regulation of intestinal homeostasis. Increasing evidence shows that the gut microbiome plays a role in CRC development and may be a biomarker for early diagnosis.

OBJECTIVE

This study aimed to determine the clinical prognostic significance of gut microbiota in CRC patients in the Turkish population by metagenomic analysis and to determine the microbial composition in tumor tissue biopsy samples.

METHODS

Tissue biopsies were taken from the participants with sterile forceps during colonoscopy and stored at -80 °C. Then, DNA isolation was performed from the tissue samples and the V3-V4 region of the 16 S rRNA gene was sequenced on the Illumina MiSeq platform. Quality control of the obtained sequence data was performed. Operational taxonomic units (OTUs) were classified according to the Greengenes database. Alpha diversity (Shannon index) and beta diversity (Bray-Curtis distance) analyses were performed. The most common bacterial species in CRC patients and healthy controls were determined and whether there were statistically significant differences between the groups was tested.

RESULTS

A total of 40 individuals, 13 CRC patients and 20 healthy control individuals were included in our metagenomic study. The mean age of the patients was 64.83 and BMI was 25.85. In CRC patients, the level of Bacteroidetes at the phylum taxonomy was significantly increased (p = 0.04), the level of Clostridia at the class taxonomy was increased (p = 0.23), and the level of Enterococcus at the genus taxonomy was significantly increased (p = 0.01). When CRC patients were compared with the control group, significant increases were detected in the species of Gemmiger formicilis (p = 0.15), Prevotella copri (p = 0.02) and Ruminococcus bromii (p = 0.001) at the species taxonomy.

CONCLUSIONS

Metagenomic analysis of intestinal microbiota composition in CRC patients provides important data for determining the treatment options for these patients. The results of this study suggest that it may be beneficial in terms of early diagnosis, poor prognosis and survival rates in CRC patients. In addition, this metagenomic study is the first study on the colon microbiome associated with CRC mucosa in the Turkish population.

Exploring causal effects of gut microbiota and metabolites on body fat percentage using two-sample Mendelian randomization

AIM

The relationship between the gut microbiota, metabolites and body fat percentage (BFP) remains unexplored. We systematically assessed the causal relationships between gut microbiota, metabolites and BFP using Mendelian randomization analysis.

MATERIALS AND METHODS

Single nucleotide polymorphisms associated with gut microbiota, blood metabolites and BFP were screened via a genome-wide association study enrolling individuals of European descent. Summary data from genome-wide association studies were extracted from the MiBioGen consortium and the UK Biobank. The inverse variance-weighted model was the primary method used to estimate these causal relationships. Sensitivity analyses were performed using pleiotropy, Mendelian randomization-Egger regression, heterogeneity tests and leave-one-out tests.

RESULTS

In the aspect of phyla, classes, orders, families and genera, we observed that o_Bifidobacteriales [β = -0.05; 95% confidence interval (CI): -0.07 to -0.03; false discovery rate (FDR) = 2.76 × 10-3], f_Bifidobacteriaceae (β = -0.05; 95% CI: -0.07 to -0.07; FDR = 2.76 × 10-3), p_Actinobacteria (β = -0.06; 95% CI: -0.09 to -0.03; FDR = 6.36 × 10-3), c_Actinobacteria (β = -0.05; 95% CI: -0.08 to -0.02; FDR = 1.06 × 10-2), g_Bifidobacterium (β = -0.05; 95% CI: -0.07 to -0.02; FDR = 1.85 × 10-2), g_Ruminiclostridium9 (β = -0.03; 95% CI: -0.06 to -0.01; FDR = 4.81 × 10-2) were negatively associated with BFP. G_Olsenella (β = 0.02; 95% CI: 0.01-0.03; FDR = 2.16 × 10-2) was positively associated with BFP. Among the gut microbiotas, f_Bifidobacteriales, o_Bifidobacteriales, c_Actinobacteria and p_Actinobacteria were shown to be significantly associated with BFP in the validated dataset. In the aspect of metabolites, we only observed that valine (β = 0.77; 95% CI: 0.5-1.04; FDR = 8.65 × 10-6) was associated with BFP.

CONCLUSIONS

Multiple gut microbiota and metabolites were strongly associated with an increased BFP. Further studies are required to elucidate the mechanisms underlying this putative causality. In addition, BFP, a key indicator of obesity, suggests that obesity-related interventions can be developed from gut microbiota and metabolite perspectives.

Causal effect of gut microbiota on the risk of prostatitis: a two-sample Mendelian randomization study

BACKGROUND

Recent studies demonstrated that chronic prostatitis (CP) is closely related to the gut microbiota (GM). Nevertheless, the causal relationship between GM and CP has not been fully elucidated. Therefore, the two-sample Mendelian randomization (MR) analysis was employed to investigate this association.

METHODS

The summary data of gut microbiota derived from a genome-wide association study (GWAS) involving 18,340 individuals in the MiBioGen study served as the exposure, and the corresponding summary statistics for CP risk, representing the outcome, were obtained from the FinnGen databases (R9). The causal effects between GM and CP were estimated using the inverse-variance weighted (IVW) method supplemented with MR-Egger, weighted median, weighted mode, and simple mode methods. Additionally, the false discovery rate (FDR) correction was performed to adjust results. The detection and quantification of heterogeneity and pleiotropy were accomplished through the MR pleiotropy residual sum and outlier method, Cochran's Q statistics, and MR-Egger regression.

RESULTS

The IVW estimates indicated that a total of 11 GM taxa were related to the risk of CP. Seven of them was correlated with an increased risk of CP, while the remained linked with a decreased risk of CP. However, only Methanobacteria (OR 0.86; 95% CI 0.74-0.99), Methanobacteriales (OR 0.86; 95% CI 0.74-0.99), NB1n (OR 1.16; 95% CI 1.16-1.34), Methanobacteriaceae (OR 0.86; 95% CI 0.74-0.99), Odoribactergenus Odoribacter (OR 1.43; 95% CI 1.05-1.94), and Sutterellagenus Sutterella (OR 1.33; 95% CI 1.01-1.76) still maintain significant association with CP after FDR correction. Consistent directional effects for all analyses were observed in the supplementary methods. Subsequently, sensitivity analyses indicated the absence of heterogeneity, directional pleiotropy, or outliers concerning the causal effect of specific gut microbiota on CP (p > 0.05).

CONCLUSION

Our study demonstrated a gut microbiota-prostate axis, offering crucial data supporting the promising use of the GM as a candidate target for CP prevention, diagnosis, and treatment. There is a necessity for randomized controlled trials to validate the protective effect of the linked GM against the risk of CP, and to further investigate the underlying mechanisms involved.

A comprehensive assessment of the association between common drugs and psychiatric disorders using Mendelian randomization and real-world pharmacovigilance database

BACKGROUND

Medications prescribed for chronic diseases can lead to short-term neuropsychiatric symptoms, but their long-term effects on brain structures and psychiatric conditions remain unclear.

METHODS

We comprehensively analyzed the FDA Adverse Event Reporting System database and conducted drug target Mendelian Randomization (MR) studies on six categories of common drugs, 477 brain imaging-derived phenotypes (IDPs) and eight psychiatric disorders. Genetic instruments were extracted from expression quantitative trait loci (eQTLs) in blood, brain, and other target tissues, protein quantitative trait loci (pQTLs) in blood, and genome-wide association studies (GWAS) of hemoglobin and cholesterol. Summary statistics for brain IDPs, psychiatric disorders, and gut microbiome were obtained from the BIG40, Psychiatric Genomics Consortium, and MiBioGen. A two-step MR and mediation analysis were employed to screen possible mediators of drug-IDP effects from 119 gut microbiota genera and identify their mediation proportions.

FINDINGS

Among 19 drug classes, six drugs were found to be associated with higher risks of psychiatric adverse events, while 11 drugs were associated with higher risks of gastrointestinal adverse events in the FAERS analysis. We identified ten drug-psychiatric disorder associations, 202 drug-IDP associations, 16 drug-microbiota associations, and four drug-microbiota-IDP causal links. For example, PPARG activation mediated HbA1c reduction caused a higher risk of bipolar disorder (BD) II. Genetically proxied GLP-1R agonists were significantly associated with an increase in the volume of the CA3-head of the right hippocampus and the area of the left precuneus cortex, both of which have been shown to correlate with cognition in previous studies.

INTERPRETATION

Common drugs may affect brain structure and risk of psychiatric disorder. Oral medications in particular may exert some of these effects by influencing gut microbiota. This study calls for greater attention to be paid to the neuropsychiatric adverse effects of drugs and encourages drug repurposing.

FUNDING

National Natural Science Foundation of China (grant No. 82330035, 82130043, 82172685, and 82001223), National Natural Science Foundation of Hunan Province (grant No. 2021SK1010), and the Science Foundation for Distinguished Young Scholars of Changsha (grant No. kq2209006).

Causal Relationship Between Gut Microbiota, Metabolites, and Sarcopenia: A Mendelian Randomization Study

BACKGROUND

Gut microbiota imbalance and sarcopenia are frequently observed in older adults. Gut microbiota and their metabolites are considered risk factors contributing to the heightened risk of sarcopenia, but whether these associations are causal remains unclear.

METHODS

We conducted linkage disequilibrium score regression and 2-sample Mendelian randomization (MR) methods with single-nucleotide polymorphisms sourced from large-scale genome-wide association studies as instrumental variables to examine the causal associations linking gut microbiota with their metabolites to the sarcopenia. Following the MR analysis, subsequent sensitivity analyses were conducted to reinforce the robustness and credibility of the obtained results.

RESULTS

MR analysis yielded compelling evidence demonstrating the correlation between genetically predicted gut microbiota and metabolites and the risk of sarcopenia. The abundance of Porphyromonadaceae, Rikenellaceae, Terrisporobacter, and Victivallis was found to be associated with walking pace. Our study also found suggestive associations of 12 intestinal bacteria with appendicular lean mass, and of Streptococcaceae, Intestinibacter, Paraprevotella, Ruminococcaceae UCG009, and Sutterella with grip strength. Specifically, we identified 21 gut microbiota-derived metabolites that may be associated with the risk of sarcopenia.

CONCLUSIONS

Utilizing a 2-sample MR approach, our study elucidates the causal interplay among gut microbiota, gut microbiota-derived metabolites, and the occurrence of sarcopenia. These findings suggest that gut microbiota and metabolites may represent a potential underlying risk factor for sarcopenia, and offer the promise of novel therapeutic focal points.

Association between gut microbiota and acute pancreatitis: a bidirectional Mendelian randomization study

BACKGROUND AND AIM

The dysbiosis of gut microbiota has been reported in acute pancreatitis. However, the direction and magnitude between host microbiota and pancreas remains to be established. This study investigated the association between gut microbiota and acute pancreatitis using Mendelian randomization (MR) methods.

METHODS

Summary statistics of gut microbiota abundance and acute pancreatitis were extracted from genome-wide association studies (GWAS). The two-sample bidirectional MR design was employed to assess genetic association between the microbiota and pancreatitis, followed by a comprehensive sensitivity analysis to verify the robustness of the results.

RESULTS

Seven microbiota taxa have been identified as significantly associated with the development of pancreatitis. Host genetic-driven order Bacteroidales and class Bacteroidia are associated with an increased risk of pancreatitis. The genera Coprococcus and Eubacterium fissicatena group also exhibit a positive effect on the development of pancreatitis, while the genera Prevotella, Ruminiclostridium, and Ruminococcaceae act as protective factors against pancreatitis. In contrast, acute pancreatitis was positively correlated with phylum Proteobacteria and genus Lachnospiraceae and negatively correlated with genus Holdemania.

CONCLUSIONS

The bidirectional relationship between gut microbiota and acute pancreatitis suggests a critical role for host-microbiota crosstalk in the development of the disease. Targeted modulation of specific gut microbiota enables the prevention and treatment of acute pancreatitis.

Predicting the potential deterioration of Barrett's esophagus based on gut microbiota: a Mendelian randomization analysis

Esophageal adenocarcinoma (EAC) is one of the most malignant tumors in the digestive system. To make thing worse, the scarcity of treatment options is disheartening. However, if detected early, there is a possibility of reversing the condition. Unfortunately, there is still a lack of relevant early screening methods. Considering that Barrett's esophagus (BE), a precursor lesion of EAC, has been confirmed as the only known precursor of EAC. Analyzing which BE cases will progress to EAC and understanding the processes and mechanisms involved is of great significance for early screening of such patients. Considering the significant alterations in the gut microbiota of patients with BE and its potential role in the progression to EAC, this study aims to analyze the relationship between BE, EAC, and GM to identify potential diagnostic biomarkers and therapeutic targets. This study utilized comprehensive statistical data on gut microbiota from a large-scale genome-wide association meta-analysis conducted by the MiBioGen consortium (n = 18,340). Subsequently, we selected a set of single nucleotide polymorphisms (SNPs) that fell below the genome-wide significance threshold (1 × 10-5) as instrumental variables. To investigate the causal relationship between gut microbiota and BE and EAC, we employed various MR analysis methods, including Inverse Variance Weighting (IVW), MR-Egger regression, weighted median (WM), and weighted mean. Additionally, we assessed the level of pleiotropy, heterogeneity, and stability of genetic variations through MR-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis. Furthermore, we conducted reverse MR analysis to identify the causal relationships between gut microbiota and BE and EAC. The results from the Inverse Variance-Weighted (IVW) analysis indicate that Alistipes (P = 4.86 × 10-2), Lactobacillus (P = 2.11 × 10-2), Prevotella 7 (P = 4.28 × 10-2), and RuminococcaceaeUCG004 (P = 4.34 × 10-2) are risk factors for Barrett's esophagus (BE), while Flavonifractor (P = 8.81 × 10-3) and RuminococcaceaeUCG004 (P = 4.99 × 10-2) are risk factors for esophageal adenocarcinoma (EAC). On the other hand, certain gut microbiota genera appear to have a protective effect against both BE and EAC. These include Eubacterium (nodatum group) (P = 4.51 × 10-2), Holdemania (P = 1.22 × 10-2), and Lactococcus (P = 3.39 × 10-2) in the BE cohort, as well as Eubacterium (hallii group) (P = 4.07 × 10-2) and Actinomyces (P = 3.62 × 10-3) in the EAC cohort. According to the results of reverse MR analysis, no significant causal effects of BE and EAC on gut microbiota were observed. Furthermore, no significant heterogeneity or pleiotropy was detected in the instrumental variables. We have established a causal relationship between the gut microbiota and BE and EAC. This study holds profound significance for screening BE patients who may be at risk of deterioration, as it can provide them with timely medical interventions to reverse the condition.