Gut microbiota as potential mediator linking dietary preferences and aging phenotypes.

Population ageing is a global phenomenon with significant implications for public health. Research has highlighted a relationship between gut microbiota, inflammatory cytokines, and ageing, yet the underlying causal mechanisms remain elusive. This study uses Mendelian randomization (MR) analysis to investigate causal relationships between gut microbiota, inflammatory cytokines, and ageing phenotypes. We leveraged the summary statistics of gut microbiota (n = 5959), circulating inflammatory cytokines (n = 8293), and three ageing phenotypes including telomere length (n = 472,174), facial ageing (n = 423,999), and frailty index (n = 175,226). We performed bidirectional MR analyses to explore the causal effects of gut microbiota and inflammatory cytokines on ageing, and mediation analyses to discover potential mediating gut microbiota and inflammatory cytokines. Our findings suggest that there are causal interactions between gut microbiota, inflammatory cytokines, and ageing. Notably, the abundance of GCA-900066575 sp900066385 appears to mediate the M-CSF pathway to facial ageing. The current MR study provides evidence supporting causal relationships between inflammatory cytokines and ageing and potential mediating gut microbiota, which are critical to advancing our understanding of the ageing process and developing effective interventions.

Studies have shown that carpal tunnel syndrome (CTS) is associated with inflammation and immunity. Additionally, recent research indicates that the gut microbiota can influence the development and progression of immune and inflammatory responses. We aim to investigate the causal impact of gut microbiota on CTS and identify potential immune cell mediators. We made use of the summary statistics of 412 gut microbiota (from 7738 individuals), 731 immune cells (from 3757 individuals), and CTS (FinnGen consortium), from the extensive genome-wide association studies to date. To determine the causal links between gut microbiota and CTS, we employed bidirectional Mendelian randomization (MR) analyses, Bayesian-weighted Mendelian randomization (BWMR) and further employed 2-step MR to confirm potential mediating roles of immune cells. Moreover, we conducted rigorous sensitivity analyses to assess the heterogeneity, robustness, and horizontal pleiotropy of our findings. Bidirectional MR analysis and BWMR revealed that 15 bacterial traits were significantly associated with CTS, while the reversed causal relationship was not existed. Moreover, the mediation analysis demonstrated that 4 immune cells mediated the causal relationships of 3 gut microbiota species on CTS: CD14 on CD33dim HLA-DR+ CD11b+ cells and CD39 on CD39+ secreting CD4 regulatory T cells mediated the effects of s_Bacteroides_salyersiae on CTS, with indirect effect sizes of -0.0035 and -0.0015, accounting for 10.44% and 4.41% of the total effect, respectively. CD25 on IgD+ CD24+ B cells mediated the effect of s_Paraprevotella_clara on CTS, with an effect size of 0.0018, corresponding to 4.10% of the total effect. Moreover, CD8 on CD28+ CD45RA- CD8+ T cells mediated the association between s_Bacteroides_massiliensis and CTS, with a mediating effect of -0.0096, representing 10.49% of the total effect. The risk of CTS has been linked causally to gut microbiota, with 4 distinct immunophenotypes acting as potential mediators in this relationship. The role of gut microbiota in modulating immune cells, thereby influencing CTS, may offer novel therapeutic strategies and management approaches.

Immune cells mediated the causal relationship between the gut microbiota and anxiety disorders: A Mendelian randomization study.

Background: Childhood obesity is characterized by metabolic dysregulation and unique gut microbiota profiles. Nevertheless, the comprehensive understanding of gut microbiota and metabolic dysregulation of childhood obesity remains unclear. Objectives: This study aimed to investigate the causal relationship of gut microbiota and childhood obesity and identify the blood metabolites as potential mediators. Methods: The exposure genome-wide association studies (GWAS) data were sourced from the GWAS Catalog, while the outcome GWAS data were obtained from the Early Growth Genetics (EGG) Consortium. The study used 473 types of gut microbiota, 233 types of blood metabolites, and childhood obesity from GWAS. We then performed two-sample Mendelian randomization (TSMR) and bidirectional Mendelian randomization (BDMR) analyses to explore the causal relationships between gut microbiota, blood metabolites, and childhood obesity. Additionally, we conducted multivariable Mendelian randomization (MVMR) and two-step Mendelian randomization (2SMR) to identify potential mediating blood metabolites in this process. Results: MR analysis identified 13 types of gut microbiota and 12 types of blood metabolites that were causally associated with childhood obesity. Furthermore, there was no strong evidence that genetically predicted childhood obesity had an effect on these gut microbiota and blood metabolites. Further, 2SMR analysis revealed that the association between K10 sp001941205 and childhood obesity was mediated by the Total cholesterol to total lipids ratio in medium VLDL, accounting for 2.53% (95%CI; 2.14%-2.92%) of the association. Similarly, the relationship between SM23-33 and childhood obesity was mediated by the Ratio of 22:6 docosahexaenoic acid to total fatty acids, which accounted for 4.07% (95%CI; 2.70%-5.44%) of the association. Conclusion: The present study is the first to investigate the causal relationships among 473 gut microbiota phenotypes, 233 blood metabolites, and childhood obesity through Mendelian randomization analysis, identifying 13 gut microbiota types with potential causal links to childhood obesity and suggesting that 2 blood metabolites may mediate these associations, thereby providing valuable insights for future intervention strategies aimed at addressing childhood obesity

Background and Purpose We investigated the causal relationships between the gut microbiota (GM), stroke, and potential metabolite mediators using Mendelian randomization (MR).Methods We leveraged the summary statistics of GM (n=18,340 in the MiBioGen consortium), blood metabolites (n=115,078 in the UK Biobank), and stroke (cases n=60,176 and controls n=1,310,725 in the Global Biobank Meta-Analysis Initiative) from the largest genome-wide association studies to date. We performed bidirectional MR analyses to explore the causal relationships between the GM and stroke, and two mediation analyses, two-step MR and multivariable MR, to discover potential mediating metabolites.Results Ten taxa were causally associated with stroke, and stroke led to changes in 27 taxa. In the two-step MR, Bifidobacteriales order, Bifidobacteriaceae family, Desulfovibrio genus, apolipoprotein A1 (ApoA1), phospholipids in high-density lipoprotein (HDL_PL), and the ratio of apolipoprotein B to ApoA1 (ApoB/ApoA1) were causally associated with stroke (all P<0.044). The causal associations between Bifidobacteriales order, Bifidobacteriaceae family and stroke were validated using the weighted median method in an independent cohort. The three GM taxa were all positively associated with ApoA1 and HDL_PL, whereas Desulfovibrio genus was negatively associated with ApoB/ApoA1 (all P<0.010). Additionally, the causal associations between the three GM taxa and ApoA1 remained significant after correcting for the false discovery rate (all q-values <0.027). Multivariable MR showed that the associations between Bifidobacteriales order, Bifidobacteriaceae family and stroke were mediated by ApoA1 and HDL_PL, each accounting for 6.5% (P=0.028) and 4.6% (P=0.033); the association between Desulfovibrio genus and stroke was mediated by ApoA1, HDL_PL, and ApoB/ApoA1, with mediated proportions of 7.6% (P=0.019), 4.2% (P=0.035), and 9.1% (P=0.013), respectively.Conclusion The current MR study provides evidence supporting the causal relationships between several specific GM taxa and stroke and potential mediating metabolites.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a multifactorial etiology, including genetic, immunological, and environmental factors, as well as alterations in the gut microbiome and plasma metabolites. The interplay between these factors is complex and not fully elucidated, particularly regarding the potential mediation of metabolites in the relationship between gut microbiota and UC. We performed a Mendelian randomization (MR) study to investigate the causal associations between gut microbiota, plasma metabolites, and UC. The study utilized a two-sample MR approach to discern causal relationships among these factors. Genetic variants from genome-wide association studies served as instrumental variables in the MR analyses, conducted using the "TwoSampleMR" package in R software. We adhered to the fundamental assumptions of MR analyses, ensuring the validity of our causal inferences. Additionally, we incorporated a mediation analysis to assess the potential mediating role of plasma metabolites in the relationship between gut microbiota and UC. Our current study found the substantial relationship between certain gut microbial taxa and the development of UC. Indeed, we have identified 6 microbial taxa, including Genus Dorea, Phylum Proteobacteria, Species Streptococcus parasanguinis, Species Ruminococcus obeum, Species Roseburia intestinalis, and Order Lactobacillales, which were found to be causally related to UC. Seventy-three metabolites and metabolite ratios of were also causally associated with UC, and a mediation analysis revealed that metabolites such as stearoylcarnitine, 3-hydroxyoctanoylcarnitine, 1-arachidonoyl-GPE (20:4n6), 3-(3-hydroxyphenyl)propionate sulfate, and thioproline mediated the effects of gut microbiota on UC and hence might play roles in disease pathogenesis. This microbiota-UC-specific MR study provides evidence for causal associations between specific gut microbiota and UC, potentially mediated through plasma metabolites. The findings give new perspectives on the causal nexus of the gut microbiota and plasma metabolites with UC, highlighting potential intervention targets for the disease. These findings call for confirmation in further research, together with investigation of the underlying mechanisms.

Urolithiasis is a multifactorial systemic metabolic disease influenced by genetic, environmental, and dietary factors. Although previous observational studies have established strong links between the gut microbiome, plasma metabolome, inflammatory proteome, and urolithiasis, may be influenced by various confounding factors. This study aims to elucidate the causal relationships between gut microbiota (GM) and urolithiasis, and to investigate whether plasma metabolites and inflammatory proteins mediate this interaction. We utilized publicly available dataset from genome-wide association studies (GWAS) to obtain data on GM, plasma metabolites, inflammatory proteins and urolithiasis. To elucidate the causal relationship between GM and urolithiasis, we conducted bidirectional Mendelian randomization (MR) analyses. Additionally, a two-step MR approach was applied to investigate whether GM contributes to the development of urolithiasis via plasma metabolites and inflammatory proteins, quantifying the mediation effect. Inverse variance weighting (IVW) was the primary method, with Bayesian weighted Mendelian randomization (BWMR), MR-Egger, and weighted median (WM) analyses used to ensure the robustness of our findings. Tests for horizontal pleiotropy and heterogeneity were conducted to confirm the reliability of the results. MR analyses identified causal relationships between seven GM taxa and six metabolic pathways with urolithiasis, while urolithiasis induced changes in 13 GM taxa and five metabolic pathways. Additionally, 43 plasma metabolites (27 identified, 8 unidentified, and 8 metabolite ratios) and six inflammatory proteins were identified as potential mediators in the GM-urolithiasis connection. Through two-step mediation analysis, 13 causal pathways were identified. After excluding metabolic pathways and unidentified metabolites, we determined that galactonate and LAP-TGF-β1 mediate the relationship between Bacteroides faecis, Alistipes finegoldii, and urolithiasis, with mediation proportions of 16.99% (P = 0.0371) and 9.61% (P = 0.0469), respectively. The present MR analysis provides evidence supporting causal relationships between specific GM taxa and urolithiasis, with plasma metabolites and inflammatory proteins emerging as potential mediators.

This study aims to determine the causal relationship between gut microbiota (GM) and Non-Suicidal Self-Injury (NSSI) using a two-sample Mendelian Randomization (MR) approach. By identifying Single Nucleotide Polymorphisms (SNPs) linked to both GM and NSSI, we explore bidirectional causal effects to uncover potential therapeutic pathways. A bidirectional MR analysis was conducted using GWAS data. SNPs associated with GM were used as instrumental variables (IVs) to assess the causal impact of GM on NSSI and vice versa. Forward MR analysis applied Inverse Variance Weighted (IVW) and MR-robust adjusted profile score (MR-RAPS) methods to address weak IVs. Sensitivity analyses, including MR-Egger regression, weighted median, and weighted mode methods, were employed to ensure robustness and minimize bias. Reverse MR analysis evaluated the influence of NSSI on GM. Additional tests, such as heterogeneity and leave-one-out analyses, were used for result validation. All analyses were performed using R software (v4.3.2) and the "TwoSampleMR" package. Our analysis identified significant associations between GM and NSSI. In the forward MR analysis, 38 GM taxa at the genus level were linked to NSSI, including Dorea (OR = 1.462, p = 0.023) and Escherichia Shigella (OR = 0.731, p = 0.035), which impacted hospital treatment needs. Notable taxa like Lachnospiraceae UCG001 (OR = 0.755, p = 0.012) and Paraprevotella (OR = 1.229, p = 0.022) were associated with self-injurious behavior. Reverse MR identified 10 significant associations, including Prevotella9 (p = 0.001) linked to inflammation and Faecalibacterium (p = 0.014) with protective effects. Sensitivity analyses confirmed the robustness of findings, with no pleiotropy or bias detected. This study establishes a complex relationship between GM and NSSI, revealing both risk-enhancing and protective associations. These findings suggest that GM may influence NSSI behaviors and could serve as a target for future therapeutic interventions. Further research is needed to explore underlying mechanisms and validate these results.

The gut microbiota and its metabolites exert a significant influence on COPD, yet the underlying mechanisms remain elusive. We aim to holistically evaluate the role and mechanisms of the gut microbiota and its metabolites in COPD through network pharmacology and Mendelian randomization approaches. Employing network pharmacology, we identified the gut microbiota and its metabolites' impact on COPD-related targets, elucidating the complex network mechanisms involving the gut microbiota, its metabolites, targets, and signaling pathways in relation to COPD. Further, promising gut microbiota metabolites and microbiota were pinpointed, with their causal relationships inferred through Mendelian randomization. A complex biological network was constructed, comprising 39 gut microbiota, 20 signaling pathways, 19 targets, and 23 metabolites associated with COPD. Phenylacetylglutamine emerged as a potentially promising metabolite for COPD treatment, with Mendelian randomization analysis revealing a causal relationship with COPD. This study illuminates the intricate associations between the gut microbiota, its metabolites, and COPD. Phenylacetylglutamine may represent a novel avenue for COPD treatment. These findings could aid in identifying individuals at high risk for COPD, offering insights into early prevention and treatment strategies.

Background: Preterm delivery (PTD) is characterized by inflammatory proteins and unique gut microbiota profiles. Nevertheless, the comprehensive understanding of gut microbiota and inflammatory proteins of PTD remains unclear. Objectives: This study aimed to investigate the causal relationship between gut microbiota and PTD and identify the inflammatory proteins as potential mediators. Methods: The exposure genome-wide association studies (GWAS) data were sourced from the GWAS Catalog, while the outcome GWAS data were obtained from the Early Growth Genetics (EGG) Consortium. The study used 473 types of gut microbiota, 91 types of inflammatory proteins, and PTD from GWAS. We then performed two-sample Mendelian randomization (TSMR) and bidirectional Mendelian randomization (BDMR) analyses to explore the causal relationships between gut microbiota, inflammatory proteins, and PTD. Additionally, we conducted two-step Mendelian randomization (2SMR) to identify potential mediating inflammatory proteins in this process. Results: MR analysis identified 26 types of gut microbiota and 6 types of inflammatory proteins that were causally associated with PTD. Furthermore, there was no strong evidence that genetically predicted PTD affected these gut microbiota and inflammatory proteins. Further, 2SMR analysis revealed that the association between Elusimicrobiaceae and PTD was mediated by the C-C motif chemokine 23 (CCL23), accounting for 5.09% (95%CI; 0.1%-18.7%) of the association. Similarly, the relationship between Thioalkalivibrionaceae and PTD was mediated by the Interleukin-20 receptor subunit alpha (IL-20RA), which accounted for 16.88% (95%CI; 12.77%-20.99%) of the association.

Sleep disorders and aging: Mendelian randomization analysis of epigenetic and frailty markers.

Studies have shown that the gut microbiota is associated with male infertility (MI). However, their causal relationship and potential mediators need more evidence to prove. We aimed to investigate the causal relationship between the gut microbiome and MI and the potential mediating role of inflammatory cytokines from a genetic perspective through a Mendelian randomization approach. This study used data from genome-wide association studies of gut microbes (Mibiogen, n = 18, 340), inflammatory cytokines (NFBC1966, FYPCRS, FINRISK 1997 and 2002, n=13, 365), and male infertility (Finngen, n=120, 706) to perform two-way Mendelian randomization (MR), mediated MR, and multivariate MR(MVMR) analyses. In this study, the inverse variance weighting method was used as the primary analysis method, and other methods were used as supplementary analysis methods. In the present study, two gut microbes and two inflammatory cytokines were found to have a potential causal relationship with MI. Of the two gut microorganisms causally associated with male infertility, Anaerotruncus increased the risk of male infertility (odds ratio = 1.81, 95% confidence interval = 1.18-2.77, P = 0.0062), and Bacteroides decreased the risk of male infertility (odds ratio = 0.57, 95% confidence interval = 0.33-0.96, P = 0.0363). In addition, of the two inflammatory cytokines identified, hepatocyte growth factor(HGF) reduced the risk of male infertility (odds ratio = 0.50, 95% confidence interval = 0.35-0.71, P = 0.0001), Monocyte chemotactic protein 3 (MCP-3) increased the risk of male infertility (odds ratio = 1.28, 95% confidence interval = 1.03-1.61, P = 0.0039). Mediated MR analysis showed that HGF mediated the causal effect of Bacteroides on MI (mediated percentage 38.9%). Multivariate MR analyses suggest that HGF may be one of the pathways through which Bacteroides affects MI, with other unexplored pathways. The present study suggests a causal relationship between specific gut microbiota, inflammatory cytokines, and MI. In addition, HGF may mediate the relationship between Bacteroides and MI.

Observational research findings have demonstrated correlations between diet and the process of aging. Nevertheless, there remains uncertainty regarding possible disruption caused by confounding variables. To elucidate the connections between diet and aging, we employed the Mendelian randomization analysis. The exposure factor was the daily diet, whereas accelerated aging was measured through telomere length, facial aging (FA), frailty index (FI), and senescence-associated secretory phenotypes (SASPs), representing the outcome factors. The primary analysis employed IVW analysis, with additional MR-Egger and Weighted Median analyses conducted to assess the reliability of the findings. Furthermore, we analyzed the heterogeneity and pleiotropy of the results. The results revealed that the consumption of salad/raw vegetables and oily fish exhibited a negative correlation with FA, whereas coffee intake showed a positive correlation with FA. On the other hand, the intake of cheese, oily fish, dried fruit, and cereal showed negative associations with FI. Additionally, coffee, alcohol, and pork intake were positively associated with FI. Lastly, the intake of bread exhibited a positively correlated with SASPs, while the intake of cheese and coffee showed a negative correlation with SASPs. Our study revealed that the consumption of cheese, vegetables, oily fish, dried fruit, bread, coffee, and alcohol was associated with the aging process. Interestingly, our findings suggest that coffee intake may accelerate aging, whereas intake of oily fish may delay the aging process. However, it is important to note that further well-designed prospective studies are required to validate our findings in the future.

Primary immune thrombocytopenia (ITP) is an immune-mediated hematologic disorder characterized by a reduction in platelet count, increasing the risk of bleeding. Recent studies have indicated a close association between alterations in gut microbiota and the development of ITP. However, the mechanisms by which gut microbiota influence the occurrence and progression of ITP through plasma metabolites remain poorly understood. Evidence suggests extensive interactions between gut microbiota and plasma metabolites, implying a potential role for gut microbiota in influencing ITP through alterations in plasma metabolites, which requires further investigation. In this study, summarized GWAS data (including 211 gut microbiota taxa, 1,400 plasma metabolites or ratios, and an ITP patient cohort) were retrieved from the MiBioGen and GWAS Catalog databases. Using a two-sample Mendelian randomization (MR) approach, we screened gut microbiota and plasma metabolites potentially causally related to ITP. We further identified plasma metabolites serving as mediators through which gut microbiota affect ITP and calculated the strength of the mediation effect. To ensure result stability, we primarily used the inverse variance weighted (IVW) method as the main judgment index. We also utilized MR Egger and inverse variance weighted methods to detect heterogeneity in the results, and employed MR-Egger and MR-PRESSO methods to assess the presence of pleiotropy. Though two-sample MR analysis, 8 gut microbiota taxa were found to have causal relationships with ITP. After excluding six plasma metabolites with pleiotropy, 39 plasma metabolites were found to be causally related to ITP (P < 0.05). Eleven plasma metabolites were identified as having causal relationships between gut microbiota and plasma metabolites. Finally, using the delta method, it was calculated that Sphingomyelin levels (8.0%, 95%CI: 0.9% to 11.5%, P = 0.047) and Glucose-to-mannose ratio (6.5%, 95%CI: 0.7% to 9.5%, P = 0.039) are intermediates for Intestinimonas influencing ITP, while Bilirubin (Z,Z) to etiocholanolone glucuronide ratio (5.6%, 95%CI: 4.7% to 6.9%, P = 0.043) is an intermediate for Senegalimassilia influencing ITP. Gut microbiota can influence the development of ITP through changes in plasma metabolites. Sphingomyelin levels, Glucose-to-mannose ratio, and Bilirubin (Z,Z) to etiocholanolone glucuronide ratio are newly discovered intermediates through which gut microbiota influence ITP, providing potential indicators and targets for clinical diagnosis and treatment. This study highlights the intricate relationship between gut microbiota and plasma metabolites in the context of ITP, suggesting new avenues for clinical diagnosis and treatment.

Background: Previous studies have indicated that the gut microbiome and plasma metabolites play key roles in autism spectrum disorder (ASD), but their causal relationships remain unclear. Linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) are powerful tools for assessing genetic causality. This study uses LDSC and MR to investigate the genetic links between the gut microbiome and ASD and explore the mediating role of plasma metabolites. Methods: To explore the genetic relationships between the gut microbiome, plasma metabolites, and ASD, we obtained summary statistics from large-scale genome-wide association studies (GWAS). Gut microbiome data came from a MiBioGen consortium meta-analysis (N = 18,340), ASD data from the Danish Psychiatric Central Research Register (DPCRR) (N = 18,382), and plasma metabolite data from the Canadian Longitudinal Study of Aging (CLSA) (N = 8299). We applied LDSC and bidirectional MR to analyze the genetic associations between the gut microbiome and ASD and plasma metabolites and ASD. Mediation MR was used to assess the mediating role of plasma metabolites in the gut microbiome-ASD relationship. Results: LDSC analysis revealed significant genetic correlations between the gut microbiota Lachnospiraceae NK4A136 group and Sellimonas with ASD. Moreover, bidirectional MR demonstrated causal effects of five gut microbial genera on ASD risk, as indicated by inverse variance weighted (IVW) methods. Similarly, we identified 49 plasma metabolites that exhibited genetic correlations with ASD, and 58 metabolites had causal effects on ASD in MR analysis. Mediation analysis revealed that specific bacteria, Ruminiclostridium5, reduce the occurrence of ASD through metabolites Delta-CEHC and Docosadioate (C22-DC). Furthermore, Ruminococcaceae UCG005 and Sutterella modulate ASD by inhibiting Serotonin and N-acetyl-L-glutamine, respectively. Conclusions: This study provides evidence of a causal relationship between the gut microbiome and ASD, with plasma metabolites acting as a potential mediator. Our findings offer new insights into the causal mechanisms linking the gut microbiome and ASD and provide a theoretical foundation for microbiome-based therapeutic strategies.