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Background In cancer patients receiving immune checkpoint inhibitors (ICIs), there is emerging evidence suggesting a correlation between gut microbiota and immune-related adverse events (irAEs). However, the exact roles of gut microbiota and the causal associations are yet to be clarified. Methods To investigate this, we first conducted a univariable bi-directional two-sample Mendelian randomization (MR) analysis. Instrumental variables (IVs) for gut microbiota were retrieved from the MiBioGen consortium (18,340 participants). GWAS summary data for irAEs were gathered from an ICIs-treated cohort with 1,751 cancer patients. Various MR analysis methods, including inverse variance weighted (IVW), MR PRESSO, maximum likelihood (ML), weighted median, weighted mode, and cML–MA–BIC, were used. Furthermore, multivariable MR (MVMR) analysis was performed to account for possible influencing instrumental variables. Results Our analysis identified fourteen gut bacterial taxa that were causally associated with irAEs. Notably, Lachnospiraceae was strongly associated with an increased risk of both high-grade and all-grade irAEs, even after accounting for the effect of BMI in the MVMR analysis. Akkermansia , Verrucomicrobiaceae , and Anaerostipes were found to exert protective roles in high-grade irAEs. However, Ruminiclostridium6 , Coprococcus3 , Collinsella , and Eubacterium (fissicatena group) were associated with a higher risk of developing high-grade irAEs. RuminococcaceaeUCG004 , and DefluviitaleaceaeUCG011 were protective against all-grade irAEs, whereas Porphyromonadaceae , Roseburia , Eubacterium (brachy group) , and Peptococcus were associated with an increased risk of all-grade irAEs. Conclusions Our analysis highlights a strong causal association between Lachnospiraceae and irAEs, along with some other gut microbial taxa. These findings provide potential modifiable targets for managing irAEs and warrant further investigation.

Background An increasing number of studies have focused on the association between Human papillomavirus (HPV) infection and systemic lupus erythematosus (SLE). However, current evidence is largely based on retrospective studies, which are susceptible to confounding factors and cannot establish causation. Methods A bidirectional two‐sample Mendelian randomization (MR) design was used to evaluate the causal relationship between HPV and SLE. Mononucleoside polymers (SNPS) with strong evidence for genome‐wide association studies (GWAS) were selected from the HPV exposure dataset and used as an instrumental variable (IV) for this study. For the MR Analysis results, the MR‐Egger intercept P test, MR‐Presso global test, CochranQ test and leave‐one test were used for sensitivity analysis. Results Based on the evidence of MR Analysis, this study finally determined that there was no causal association between HPV16 and HPV18 and SLE. Conclusions Possible regulation of HPV infection is not significantly associated with regulation of SLE. These findings provide new insights into the underlying mechanisms of HPV and SLE and need to be validated by further studies.

Background Several recent observational studies have reported that gut microbiota composition is associated with preeclampsia. However, the causal effect of gut microbiota on preeclampsia-eclampsia is unknown. Methods A two-sample Mendelian randomization study was performed using the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis ( n =13,266) conducted by the MiBioGen consortium. The summary statistics of preeclampsia-eclampsia were obtained from the FinnGen consortium R7 release data (5731 cases and 160,670 controls). Inverse variance weighted, maximum likelihood, MR-Egger, weighted median, weighted model, MR-PRESSO, and cML-MA were used to examine the causal association between gut microbiota and preeclampsia-eclampsia. Reverse Mendelian randomization analysis was performed on the bacteria that were found to be causally associated with preeclampsia-eclampsia in forward Mendelian randomization analysis. Cochran’s Q statistics were used to quantify the heterogeneity of instrumental variables. Results Inverse variance weighted estimates suggested that Bifidobacterium had a protective effect on preeclampsia-eclampsia (odds ratio = 0.76, 95% confidence interval: 0.64–0.89, P = 8.03 × 10 −4 ). In addition, Collinsella (odds ratio = 0.77, 95% confidence interval: 0.60–0.98, P = 0.03), Enterorhabdus (odds ratio = 0.76, 95% confidence interval: 0.62–0.93, P = 8.76 × 10 −3 ), Eubacterium (ventriosum group) (odds ratio = 0.76, 95% confidence interval: 0.63–0.91, P = 2.43 × 10 −3 ), Lachnospiraceae (NK4A136 group) (odds ratio = 0.77, 95% confidence interval: 0.65–0.92, P = 3.77 × 10 −3 ), and Tyzzerella 3 (odds ratio = 0.85, 95% confidence interval: 0.74–0.97, P = 0.01) presented a suggestive association with preeclampsia-eclampsia. According to the results of reverse MR analysis, no significant causal effect of preeclampsia-eclampsia was found on gut microbiota. No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. Conclusions This two-sample Mendelian randomization study found that Bifidobacterium was causally associated with preeclampsia-eclampsia. Further randomized controlled trials are needed to clarify the protective effect of probiotics on preeclampsia-eclampsia and their specific protective mechanisms.

Abstract Background Observational studies have shown a link between elevated body mass index (BMI) and the risk of polycystic ovary syndrome (PCOS). While Mendelian randomization (MR) studies in Europeans have suggested a causal role of increased BMI in PCOS, whether the same role is suggested in Asians has yet to be investigated. We used MR studies to infer causal effects using genetic data from East Asian populations. Methods and Findings We performed a 2-sample bidirectional MR analysis using summary statistics from genome-wide association studies (GWAS) of BMI (with up to 173 430 individuals) and PCOS (4386 cases and 8017 controls) in East Asian populations. Seventy-eight single nucleotide polymorphisms (SNPs) correlated with BMI were selected as genetic instrumental variables to estimate the causal effect of BMI on PCOS using the inverse-variance weighted (IVW) method. To test the reliability of the results, further sensitivity analyses included MR–Egger regression, weighted median estimates, and leave-one-out analysis. The IVW analysis indicated a significant association between high BMI and the risk of PCOS (odds ratio per standard deviation higher BMI, 2.208; 95% confidence interval 1.537 to 3.168, P = 1.77 × 10–5). In contrast, the genetic risk of PCOS had no significant effect on BMI. Conclusions The results of our bidirectional MR study showed that an increase in BMI causes PCOS, while PCOS does not cause an increased BMI. This study provides further genetic support for a link between BMI and PCOS. Further research is needed to interpret the potential mechanisms of this association.

Myopia, a major cause of irreversible visual impairment globally, is projected to affect about 25% of the world’s population by 2025. Myopia progresses through childhood and adolescence, necessitating frequent prescription updates. While genetic and environmental factors are well-established contributors to myopia, emerging evidence suggests a significant role of the gut microbiota (GM) in its development, mainly through metabolic interactions. This study utilized a Mendelian Randomization (MR) approach to investigate the causal relationships between GM, metabolites, and myopia and pathological myopia (PM) progression. Using genetic variants as instrumental variables, we analyzed data from extensive genome-wide association studies (GWAS) to assess the impacts of 473 GM taxa and 233 metabolites on myopia risks. Our MR analysis identified specific GM taxa and metabolites with significant causal relationship to myopia and PM. Notably, lipid metabolites were found to mediate the effects of GM on myopia, suggesting a biochemical pathway that could influence ocular development and myopia progression. We also observed significant mediation effects, indicating that specific metabolites might serve as therapeutic targets to modulate myopia progression. The findings highlight the potential of GM and metabolites as novel targets for preventing or managing myopia. This study underscores the importance of further research into the gut-metabolite-eye axis to develop targeted interventions for myopia based on modifying the GM through diet, probiotics, or other means. Future studies should aim to elucidate the specific metabolites involved and their roles in ocular health, potentially offering new avenues for treatment.

Background Alzheimer's disease (AD) and white‐matter structural connectivity have been linked in some observational studies, although it is unknown if this is a causal relationship. The purpose of this study was to examine the impact of various white‐matter structural connectivity on AD via a two‐sample multivariate Mendelian randomization (MR) approach. Methods The genome‐wide association study (GWAS) of Wainberg et al. provided the summary data on white‐matter structural connectivity, and Bellenguez et al.’s study provided the GWAS aggregated data for AD. MR methods included inverse variance weighted, Mendelian randomization Egger, simple mode, weighted median, and weighted mode. Heterogeneity, horizontal pleiotropy, and “leave‐one‐out” analysis guaranteed the robustness of causation. Finally, reverse MR analysis was conducted on the white‐matter structural connectivity that showed positive results in the forward MR analysis. Results Among 206 white‐matter structural connections, we identified 10 connections were strongly correlated with genetic susceptibility to AD. Right‐hemisphere limbic network to thalamus white‐matter structural connectivity and Right‐hemisphere salience_ventral attention network to accumbens white‐matter structural connectivity were positively correlated with the likelihood of AD, while the remaining 8 white‐matter structural connections were negatively related with AD. None of the above 10 white‐matter structural connections have a reverse causal relationship with AD. Conclusion Our MR study reveals a certain degree of association between white‐matter structural connectivity and AD, which may provide support for future diagnosis and treatment of AD. This study used a two‐sample bidirectional MR technique to evaluate the most recent summary GWAS data and revealed a causal relationship between white‐matter structural connectivity and AD, which is the first time that the relationship between these two has been investigated at the genetic level.

Observational studies suggest a link between depression and osteoporosis, but these may be subject to confounding and reverse causality. In this two-sample Mendelian randomization analysis, we included the large meta-analysis of genome-wide association studies for depression among 807,553 individuals (246,363 cases and 561,190 controls) of European descent, the large meta-analysis to identify genetic variants associated with femoral neck bone mineral density (FN-BMD), forearm BMD (FA-BMD) and lumbar spine BMD (LS-BMD) among 53,236 individuals of European ancestry, and the GWAS summary data of heel BMD (HE-BMD) and fracture among 426,824 individuals of European ancestry. The results revealed that genetic predisposition towards depression showed no causal effect on FA-BMD (beta-estimate: 0.091, 95% confidence interval [CI] − 0.088 to 0.269, SE:0.091, P value = 0.320), FN-BMD (beta-estimate: 0.066, 95% CI − 0.016 to 0.148, SE:0.042, P value = 0.113), LS-BMD (beta-estimate: 0.074, 95% CI − 0.029 to 0.177, SE:0.052, P value = 0.159), HE-BMD (beta-estimate: 0.009, 95% CI − 0.043 to 0.061, SE:0.027, P value = 0.727), or fracture (beta-estimate: 0.008, 95% CI − 0.071 to 0.087, SE:0.041, P value = 0.844). These results were also confirmed by multiple sensitivity analyses. Contrary to the findings of observational studies, our results do not reveal a causal role of depression in osteoporosis or fracture.

Background Gut microbiota (GM) comprises a vast and diverse community of microorganisms, and recent studies have highlighted the crucial regulatory roles of various GM and their secreted metabolites in pancreatic cancer (PC). However, the causal relationship between GM and PC has yet to be confirmed. Methods In the present study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal effect between GM and PC, with genome-wide association study (GWAS) from MiBioGen consortium as an exposure factor and PC GWAS data from FinnGen as an outcome factor. Inverse variance weighted (IVW) was used as the primary method for this study. Results At the genus level, we observed that Senegalimassilia (OR: 0.635, 95% CI : 0.403–0.998, P  = 0.049) exhibited a protective effect against PC, while Odoribacter (OR:1.899, 95% CI :1.157–3.116, P  = 0.011), Ruminiclostridium 9(OR:1.976,95% CI :1.128–3.461, P  = 0.017), Ruminococcaceae (UCG011)(OR:1.433, 95%CI:1.072–1.916, P  = 0.015), and Streptococcus(OR:1.712, 95%CI:1.071–1.736, P  = 0.025) were identified as causative factors for PC. Additionally, sensitivity analysis, Cochran’s Q test, the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and MR-Egger regression indicated no heterogeneity, horizontal pleiotropy, or reverse causality between GM and PC. Conclusions Our analysis establishes a causal effect between specific GM and PC, which may provide new insights into the potential pathogenic mechanisms of GM in PC and the assignment of effective therapeutic strategies.

[This corrects the article DOI: 10.3389/fimmu.2025.1582308.].

Background Growing evidence has shown that gut microbiome composition is associated with breast cancer (BC), but the causality remains unknown. We aimed to investigate the link between BC prognosis and the gut microbiome at various oestrogen receptor (ER) statuses. Methods We performed a genome-wide association study (GWAS) to analyse the gut microbiome of BC patients, the dataset for which was collected by the Breast Cancer Association Consortium (BCAC). The analysis was executed mainly via inverse variance weighting (IVW); the Mendelian randomization (MR) results were verified by heterogeneity tests, sensitivity analysis, and pleiotropy analysis. Results Our findings identified nine causal relationships between the gut microbiome and total BC cases, with ten and nine causal relationships between the gut microbiome and ER-negative (ER-) and ER-positive (ER+) BC, respectively. The family Ruminococcaceae and genus Parabacteroides were most apparent among the three categories. Moreover, the genus Desulfovibrio was expressed in ER- BC and total BC, whereas the genera Sellimonas , Adlercreutzia and Rikenellaceae appeared in the relationship between ER + BC and total BC. Conclusion Our MR inquiry confirmed that the gut microbiota is causally related to BC. This further explains the link between specific bacteria for prognosis of BC at different ER statuses. Considering that potential weak instrument bias impacts the findings and that the results are limited to European females due to data constraints, further validation is crucial.