Non-targeted metabolomics revealed novel links between serum metabolites and primary ovarian insufficiency: a Mendelian randomization study.

Primary ovarian insufficiency (POI) is a common clinical endocrine disorder with a high heterogeneity in both endocrine hormones and etiological phenotypes. However, the etiology of POI remains unclear. Herein, we unraveled the causality of genetically determined metabolites (GDMs) on POI through Mendelian randomization (MR) study with the overarching goal of disclosing underlying mechanisms. Genetic links with 486 metabolites were retrieved from GWAS data of 7824 European participants as exposures, while GWAS data concerning POI were utilized as the outcome. Via MR analysis, we selected inverse-variance weighted (IVW) method for primary analysis and several additional MR methods (MR-Egger, weighted median, and MR-PRESSO) for sensitivity analyses. MR-Egger intercept and Cochran's Q statistical analysis were conducted to assess potential heterogeneity and pleiotropy. In addition, genetic variations in the key target metabolite were scrutinized further. We conducted replication, meta-analysis, and linkage disequilibrium score regression (LDSC) to reinforce our findings. The MR Steiger test and reverse MR analysis were utilized to assess the robustness of genetic directionality. Furthermore, to deeply explore causality, we performed colocalization analysis and metabolic pathway analysis. Via IVW methods, our study identified 33 metabolites that might exert a causal effect on POI development. X-11437 showed a robustly significant relationship with POI in four MR analysis methods (P IVW=0.0119; P weighted-median =0.0145; PMR-Egger =0.0499; PMR-PRESSO =0.0248). Among the identified metabolites, N-acetylalanine emerged as the most significant in the primary MR analysis using IVW method, reinforcing its pivotal status as a serum biomarker indicative of an elevated POI risk with the most notable P-value (P IVW=0.0007; PMR-PRESSO =0.0022). Multiple analyses were implemented to further demonstrate the reliability and stability of our deduction of causality. Reverse MR analysis did not provide evidence for the causal effects of POI on 33 metabolites. Colocalization analysis revealed that some causal associations between metabolites and POI might be driven by shared genetic variants. By incorporating genomics with metabolomics, this study sought to offer a comprehensive analysis in causal impact of serum metabolome phenotypes on risks of POI with implications for underlying mechanisms, disease screening and prevention.

Chen S ，Zhou Z ，Zhou Z ，Liu Y ，Sun S ，Huang K ，Yang Q ，Guo Y ... -  《Frontiers in Endocrinology》

A metabolome-wide Mendelian randomization study prioritizes causal circulating metabolites for reproductive disorders including primary ovarian insufficiency, polycystic ovary syndrome, and abnormal spermatozoa.

Accumulating studies have highlighted the significant role of circulating metabolomics in the etiology of reproductive system disorders. However, the causal effects between genetically determined metabolites (GDMs) and reproductive diseases, including primary ovarian insufficiency (POI), polycystic ovary syndrome (PCOS), and abnormal spermatozoa (AS), still await thorough clarification. With the currently most comprehensive genome-wide association studies (GWAS) data of metabolomics, systematic two-sample Mendelian randomization (MR) analyses were conducted to disclose causal associations between 1,091 blood metabolites and 309 metabolite ratios with reproductive disorders. The inverse-variance weighted (IVW) method served as the primary analysis approach, and multiple effective MR methods were employed as complementary analyses including MR-Egger, weighted median, constrained maximum likelihood (cML-MA), contamination mixture method, robust adjusted profile score (MR-RAPS), and debiased inverse-variance weighted method. Heterogeneity and pleiotropy were assessed via MR-Egger intercept and Cochran's Q statistical analysis. Outliers were detected by Radial MR and MR-PRESSO methods. External replication and metabolic pathway analysis were also conducted. Potential causal associations of 63 GDMs with POI were unearthed, and five metabolites with strong causal links to POI were emphasized. Two metabolic pathways related to the pathogenesis of POI were pinpointed. Suggestive causal effects of 70 GDMs on PCOS were detected, among which 7 metabolites stood out for strong causality with elevated PCOS risk. Four metabolic pathways associated with PCOS mechanisms were recognized. For AS, 64 GDMs as potential predictive biomarkers were identified, particularly highlighting two metabolites for their strong causal connections with AS. Three pathways underneath the AS mechanism were identified. Multiple assessments were conducted to further confirm the reliability and robustness of our causal inferences. By extensively assessing the causal implications of circulating GDMs on reproductive system disorders, our study underscores the intricate and pivotal role of metabolomics in reproductive ill-health, laying a theoretical foundation for clinical strategies from metabolic insights.

Chen S ，Sun S ，Cai M ，Zhou Z ，Ma Y ，Zhou Z ，Wang F ，Liu J ，Song W ，Liu Y ，Huang K ，Yang Q ，Guo Y ... -  《Journal of Ovarian Research》

Causality of genetically determined metabolites on anxiety disorders: a two-sample Mendelian randomization study.

Xiao G ，He Q ，Liu L ，Zhang T ，Zhou M ，Li X ，Chen Y ，Chen Y ，Qin C ... -  《Journal of Translational Medicine》

Causal effects of genetically determined metabolites and metabolite ratios on esophageal diseases: a two-sample Mendelian randomization study.

Yang H ，Wang Y ，Zhao Y ，Cao L ，Chen C ，Yu W ... -  《BMC GASTROENTEROLOGY》

Association between gut microbiota and primary ovarian insufficiency: a bidirectional two-sample Mendelian randomization study.

Recent studies have indicated a potential correlation between intestinal bacteria and primary ovarian insufficiency (POI). However, the causal relationship between the gut microbiota (GM) and POI remains unclear. A bidirectional two-sample Mendelian randomization (MR) study was conducted to investigate the relationship between the GM and POI. Data on the GM were based on the MiBioGen consortium's summary statistics from the most comprehensive genome-wide association study meta-analysis to date (n=13,266), and POI data were obtained from the R8 release of the FinnGen consortium, containing a total of 424 cases and 181,796 controls. A variety of analytical methods, including inverse variance weighting, maximum likelihood, MR-Egger, weighted median, and constrained maximum likelihood and model averaging and Bayesian information criterion, were utilized to explore the connection between the GM and POI. The Cochran's Q statistics were used to evaluate the heterogeneity of instrumental variables. The MR-Egger and MR-pleiotropy residual sum and outlier (PRESSO) methods were used to identify the horizontal pleiotropy of instrumental variables. The MR Steiger test was used to evaluate the strength of causal relationships. A reverse MR study was performed to investigate the causal relationship between POI and the targeted GMs which were indicated to have a causal relationship with POI in the forward MR evaluation. The inverse variance weighted analysis indicated that Eubacterium (hallii group) (odds ratio [OR]=0.49, 95% confidence interval [CI]: 0.26-0.9, P=0.022) and Eubacterium (ventriosum group) (OR=0.51, 95% CI: 0.27-0.97, P=0.04) had protective effects on POI, and Intestinibacter (OR=1.82, 95% CI: 1.04-3.2, P=0.037) and Terrisporobacter (OR=2.47, 95% CI: 1.14-5.36, P=0.022) had detrimental effects on POI. Results of the reverse MR analysis indicated that POI had no significant influence on the four GMs. No significant heterogeneity or horizontal pleiotropy was observed in the performance of the instrumental variables. This bidirectional two-sample MR study revealed a causal link between Eubacterium (hallii group), Eubacterium (ventriosum group), Intestinibacter, and Terrisporobacter and POI. Additional clinical trials are needed to gain a clearer understanding of the beneficial or detrimental effects of the GMs on POI and their mechanisms of action.

Wang J ，Luo R ，Zhao X ，Xia D ，Liu Y ，Shen T ，Liang Y ... -  《Frontiers in Endocrinology》