Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study.

The occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective. Genome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis. The random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05). Only AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.

Su Y ，Hu Y ，Xu Y ，Yang M ，Wu F ，Peng Y ... -  《Frontiers in Endocrinology》

[Genetic Causation Analysis of Hyperandrogenemia Testing Indicators and Preeclampsia].

Some epidemiological studies have shown that pregnant women who develop preeclampsia (PE) have elevated levels of testosterone in their maternal plasma compared to women with normal blood pressure during pregnancy, revealing a potential association between hyperandrogenism in women and PE. To explore the causal relationship between hyperandrogenism and PE, this study selected total testosterone (TT), bioavailable testosterone (BIOT), and sex hormone binding globulin (SHBG) as exposure factors and PE and chronic hypertension with superimposed PE as disease outcomes. Two-sample Mendelian randomization (MR) analyses were used to genetically dissect the causal relationships between the three exposure factors (TT, BIOT, and SHBG) and the outcomes of PE and chronic hypertension with superimposed PE. Two independent genome-wide association study (GWAS) databases were used for the two-sample MR analysis. In the GWAS data of female participants from the UK Biobank cohort, single nucleotide polymorphisms (SNPs) associated with TT, BIOT, and SHBG were analyzed, involving 230454, 188507, and 188908 samples, respectively. GWAS data on PE and chronic hypertension with superimposed PE from the Finnish database were used to calculate SNP, involving 3556 PE cases and 114735 controls, as well as 38 cases of chronic hypertension with superimposed PE and 114735 controls. To meet the assumptions of instrumental relevance and independence in MR analysis, SNPs associated with exposure were identified at the genome-wide level (P<5.0×10-8), and those in linkage disequilibrium interference were excluded based on clustering thresholds of R 2<0.001 and an allele distance greater than 10000 kb. Known confounding factors, including previous PE, chronic kidney disease, chronic hypertension, diabetes, systemic lupus erythematosus, or antiphospholipid syndrome, were also identified and the relevant SNPs were removed. Finally, we extracted the outcome data based on the exposure-related SNPs in the outcome GWAS, integrating exposure and outcome data, and removing palindromic sequences. Five genetic causal analysis methods, including inverse variance-weighted method (IVW), MR-Egger regression, weighted median method, simple mode method, and weighted mode method, were used to infer causal relationships. In the IVW, it was assumed that the selected SNPs satisfied the three assumptions and provided the most ideal estimate of the effect. IVW was consequently used as the primary analysis method in this study. Considering the potential heterogeneity among the instrumental variables, random-effects IVW was used for MR analysis. The results were interpreted using odds ratios (OR) and the corresponding 95% confidence interval (CI) to explain the impact of exposure factors on PE and chronic hypertension with superimposed PE. If the CI did not include 1 and had a P value less than 0.05, the difference was considered statistically significant. Sensitivity analysis was conducted to assess heterogeneity and pleiotropy. Heterogeneity was examined using Cochran's Q test, and pleiotropy was assessed using MR-Egger intercept analysis. Additionally, leave-one-out analysis was conducted to examine whether individual SNPs were driving the causal associations. To further validate the findings, MR analyses were performed using the same methods and outcome variables, but with different exposure factors, including waist-to-hip ratio adjusted for BMI (WHRadjBMI) and 25-hydroxyvitamin D levels, with MR results for WHRadjBMI and PE serving as the positive controls and MR results for 25-hydroxyvitamin D levels and PE as the negative controls. According to the criteria for selecting genetic instrumental variables, 186, 127, and 262 SNPs were identified as genetic instrumental variables significantly associated with testosterone indicators TT, BIOT, and SHBG. MR analysis did not find a causal relationship between the TT, BIOT, and SHBG levels and the risk of developing PE and chronic hypertension with superimposed PE. The IVW method predicted that genetically predicted TT (OR [95% CI]=1.018 [0.897-1.156], P=0.78), BIOT (OR [95% CI]=1.11 [0.874-1.408], P=0.392), and SHBG (OR [95% CI]=0.855 [0.659-1.109], P=0.239) were not associated with PE. Similarly, genetically predicted TT (OR [95% CI]=1.222 [0.548-2.722], P=0.624), BIOT (OR [95% CI]=1.066 [0.242-4.695], P=0.933), and SHBG (OR [95% CI]=0.529 [0.119-2.343], P=0.402) were not significantly associated with chronic hypertension with superimposed PE. Additionally, MR analysis using the MR-Egger method, weighted median method, simple mode method, and weighted mode method yielded consistent results, indicating no significant causal relationship between elevated testosterone levels and PE or chronic hypertension with superimposed PE. Heterogeneity was observed for SHBG in the analysis with PE (Cochran's Q test, P=0.01), and pleiotropy was detected for BIOT in the analysis with PE (MR-Egger intercept analysis, P=0.014), suggesting that the instrumental variables did not affect PE through BIOT. Other instrumental variables did not show significant heterogeneity or pleiotropy. Leave-one-out analysis confirmed that the results of the MR analysis were not driven by individual instrumental variables. Consistent with previous MR studies, the results of the control MR analyses using WHRadjBMI and 25-hydroxyvitamin D levels supported the accuracy of the MR analysis approach and the methods used in this study. The MR analysis results suggest that current genetic evidence does not support a causal relationship between TT, BIOT, and SHBG levels and the development of PE and chronic hypertension with superimposed PE. This study suggests that elevated testosterone may be a risk factor for PE but not a direct cause.

Lin C ，Chen J ，Zhao X 《-》

The genetic causal relationship between type 2 diabetes, glycemic traits and venous thromboembolism, deep vein thrombosis, pulmonary embolism: a two-sample Mendelian randomization study.

To investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain. Genome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a "Leave one out" analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results. The random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827-0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503-0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412-0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235-0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the "Leave one out" analysis underscored that the MR analysis was not influenced by any single SNP. Our investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains.

Yang M ，Wan X ，Su Y ，Xu K ，Wen P ，Zhang B ，Liu L ，Yang Z ，Xu P ... -  《Thrombosis Journal》

No evidence of genetic causal association between sex hormone-related traits and systemic lupus erythematosus: A two-sample Mendelian randomization study.

Previous studies have demonstrated an association between sex hormone-related traits and systemic lupus erythematosus (SLE). However, because of the difficulties in determining sequential temporality, the causal association remains elusive. In this study, we used two-sample Mendelian randomization (MR) to explore the genetic causal associations between sex hormone-related traits and SLE. We used a two-sample MR to explore the causal association between sex hormone-related traits and SLE. The summarized data for sex hormone-related traits (including testosterone, estradiol (E2), sex hormone-binding globulin (SHBG), and bioavailable testosterone (BT)) originated from large genome-wide association studies (GWASs) of European descent. Aggregated data for SLE were derived from the FinnGen consortium (835 cases and 300,162 controls). Random-effects inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, weighted mode, and fixed-effects IVW methods were used for the MR analysis. Random-effects IVW was the primary method used to analyze the genetic causal association between sex hormone-related traits and SLE. Heterogeneity of the MR results was detected using the IVW Cochran's Q estimates. The pleiotropy of MR results was detected using MR-Egger regression and the MR pleiotropy residual sum and outlier (MR-PRESSO) test. Finally, leave-one-out analysis was performed to determine whether MR results were affected by a single single-nucleotide polymorphism (SNP). Random-effects IVW as the primary method showed that testosterone (odds ratio (OR), 0.87; 95% confidence interval (CI), 0.41-1.82; P = 0.705), E2 (OR, 0.95; 95% CI, 0.73-1.23; P = 0.693), SHBG (OR, 1.25; 95% CI, 0.74-2.13; P = 0.400), and BT (OR, 0.99; 95% CI, 0.67-1.47; P = 0.959) had no potential causal association with SLE. The MR-Egger, weighted median, simple mode, weighted mode, and fixed-effects IVW methods all indicated consistent results. The results of the MR-Egger regression showed that there was no pleiotropy in our MR analysis (P > 0.05). The IVW Cochran's Q estimates showed that the MR analysis results of E2, SHBG, and BT on SLE had no heterogeneity (P > 0.05), but testosterone and SLE had heterogeneity (P < 0.05). The leave-one-out analysis confirmed that a single SNP did not affect the MR results. Our MR analysis demonstrated that genetically predicted testosterone, E2, SHBG, and BT levels were not associated with SLE risk, but the roles of other non-genetic pathways cannot be ruled out. Key Points • This is the first MR study to explore the causal association of sex hormone-related traits with SLE. • No evidence to support causal associations between sex hormone-related traits and SLE. • Our MR analysis may provide novel insights into the causal association between sex hormone-related traits and SLE risk.

Yuan G ，Yang M ，Xie J ，Xu K ，Zhang F ... -  《-》

[A Mendelian randomization study on the relationship between insomnia and osteoporosis].

Liu HZ ，Fu XM ，Li XJ ，Wang YH ，Hu XD ，Xu HJ ，Wang AN ，Lyu ZH ，Dong S ，Pei Y ... -  《-》