Inverse-variance Weighted Method Research Articles

Rheumatoid arthritis increases the risk of heart failure: results from the cross-sectional study in the US population and mendelian randomization analysis in the European population

ObjectiveRheumatoid arthritis (RA) is a chronic systemic autoimmune disease. Among its various complications, heart failure (HF) has been recognized as the second leading cause of cardiovascular death in RA patients. The objective of this study was to investigate the relationship between RA and HF using epidemiological and genetic approachesMethodsThe study included 37,736 participants from the 1999-2020 National Health and Nutrition Examination Survey. Associations between RA and HF in the US population were assessed with weighted multivariate logistic regression analysis. A two-sample Mendelian randomization (MR) analysis was employed to establish the causal relationship between the two variables. The primary analysis method utilized was inverse variance weighting (IVW). Additionally, horizontal pleiotropy and heterogeneity were assessed to account for potential confounding factors. In cases where multiple independent datasets were accessible during MR analysis, we combined the findings through a meta-analytical approach.ResultsIn observational studies, the prevalence of HF in combination with RA reached 7.11% (95%CI 5.83 to 8.39). RA was positively associated with an increased prevalence of HF in the US population [odds ratio (OR):1.93, 95% confidence interval (CI):1.47-2.54, P < 0.0001]. In a MR analysis utilizing a meta-analytical approach to amalgamate the results of the IVW method, we identified a significant causal link between genetically predicted RA and a heightened risk of HF (OR = 1.083, 95% CI: 1.028-1.141; P = 0.003). However, this association was not deemed significant for seronegative RA (SRA) (OR = 1.028, 95% CI: 0.992-1.065; P = 0.126). These findings were consistent across sensitivity analyses and did not indicate any horizontal pleiotropy.ConclusionRA correlates with an elevated prevalence of HF within the US population. Furthermore, genetic evidence derived from European populations underscores a causal link between RA and the risk of HF. However this association was not significant in SRA.

Association between gut microbiota and anxiety disorders: a bidirectional two-sample mendelian randomization study.

There are many articles reporting that the component of intestinal microbiota implies a link to anxiety disorders (AD), and the brain-gut axis is also a hot topic in current research. However, the specific relevance between gut microbiota and AD is uncertain. We aimed to investigate causal relationship between gut microbiota and AD by using bidirectional Mendelian randomization (MR). Genetic instrumental variable (IV) for the gut microbiota were obtained from a genome-wide association study (GWAS) involving 18,340 participants. Summary data for AD were derived from the GWAS and included 158,565 cases and 300,995 controls. We applied the inverse variance weighted (IVW) method as the main analysis. Cochran's Q values was computed to evaluate the heterogeneity among IVs. Sensitivity analyses including intercept of MR-Egger method and MR-PRESSO analysis were used to test the horizontal pleiotropy. We discovered 9 potential connections between bacterial traits on genus level and AD. Utilizing the IVW method, we identified 5 bacterial genera that exhibited a direct correlation with the risk of AD: genus Eubacteriumbrachygroup, genus Coprococcus3, genus Enterorhabdus, genus Oxalobacter, genus Ruminiclostridium6. Additionally, we found 4 bacterial genera that exhibited a negative association with AD: genus Blautia, genus Butyricicoccus, genus Erysipelotrichaceae-UCG003 and genus Parasutterella. The associations were confirmed by the sensitivity analyses. Our study found a causal relation between parts of the gut microbiota and AD. Further randomized controlled trials are crucial to elucidate the positive effects of probiotics on AD and their particular protection systems.

Genetic associations between gut microbiota and allergic rhinitis: an LDSC and MR analysis

BackgroundSeveral studies have suggested a potential link between allergic rhinitis (AR) and gut microbiota. In response, we conducted a meta-analysis of Linkage Disequilibrium Score Regression (LDSC) and Mendelian randomization (MR) to detect their genetic associations.MethodsSummary statistics for 211 gut microbiota taxa were gathered from the MiBioGen study, while data for AR were sourced from the Pan-UKB, the FinnGen, and the Genetic Epidemiology Research on Aging (GERA). The genetic correlation between gut microbiota and AR was assessed using LDSC. The principal estimate of causality was determined using the Inverse-Variance Weighted (IVW) method. To assess the robustness of these findings, sensitivity analyses were conducted employing methods such as the weighted median, MR-Egger, and MR-PRESSO. The summary effect estimates of LDSC, forward MR and reverse MR were combined using meta-analysis for AR from different data resources.ResultsOur study indicated a significant genetic correlation between genus Sellimonas (Rg = −0.64, p = 3.64 × 10−5, Adjust_P = 3.64 × 10−5) and AR, and a suggestive genetic correlation between seven bacterial taxa and AR. Moreover, the forward MR analysis identified genus Gordonibacter, genus Coprococcus2, genus LachnospiraceaeUCG010, genus Methanobrevibacter, and family Victivallaceae as being suggestively associated with an increased risk of AR. The reverse MR analysis indicated that AR was suggestively linked to an increased risk for genus Coprococcus2 and genus RuminococcaceaeUCG011.ConclusionOur findings indicate a causal relationship between specific gut microbiomes and AR. This enhances our understanding of the gut microbiota’s contribution to the pathophysiology of AR and lays the groundwork for innovative approaches and theoretical models for future prevention and treatment strategies in this patient population.

Causal relationship between thyroid dysfunction and ovarian cancer: a two-sample Mendelian randomization study

PurposeObservational studies and clinical validation have suggested a link between thyroid dysfunction and an elevated ovarian cancer (OC) risk. However, whether this association indicates a cause-and-effect relationship remains uncertain. We aimed to investigate the plausible causal impact of thyroid dysfunction on OC through a Mendelian randomization (MR) study.MethodsGenome-wide association study (GWAS) data for thyrotropin (TSH), free thyroxine (FT4), hypothyroidism, and hyperthyroidism were obtained as exposures and those for OC (N = 199,741) were selected as outcomes. Inverse variance-weighted method was used as the main estimation method. A series of sensitivity analyses, including Cochran’s Q test, MR-Egger intercept analysis, forest plot scatter plot, and leave-one-out test, was conducted to assess the robustness of the estimates.ResultsGenetic prediction of hyperthyroidism was associated with a potential increase in OC risk (odds ratio = 1.094, 95% confidence interval: 1.029–1.164, p = 0.004). However, no evidence of causal effects of hypothyroidism, TSH, and FT4 on OC or reverse causality was detected. Sensitivity analyses demonstrated consistent and reliable results, with no significant estimates of heterogeneity or pleiotropy.ConclusionsThis study employed MR to establish a correlation between hyperthyroidism and OC risk. By genetically predicting OC risk in patients with hyperthyroidism, our research suggests new insights for early prevention and intervention of OC.

Genetically predicted major depression causally increases the risk of temporomandibular joint disorders

ObjectiveObservational studies have reported that mental disorders are comorbid with temporomandibular joint disorder (TMD). However, the causal relationship remains uncertain. To clarify the causal relationship between three common mental illnesses and TMD, we conduct this Mendelian Randomization (MR) study.MethodsThe large-scale genome-wide association studies data of major depression, bipolar disorder and schizophrenia were retrieved from the Psychiatric Genomics Consortium. The summary data of TMD was obtained from the Finn-Gen consortium, including 211,023 subjects of European descent (5,668 cases and 205,355 controls). The main approach utilized was inverse variance weighting (IVW) to evaluate the causal association between the three mental disorders and TMD. Five sensitivity analyses including MR-Egger, Maximum Likelihood, Weighted median, MR. RAPS and MR-PRESSO were used as supplements. We conducted heterogeneity tests and pleiotropic tests to ensure the robustness.ResultsAs shown by the IVW method, genetically determined major depression was associated with a 1.65-fold risk of TMD (95% CI = 1.10–2.47, p < 0.05). The direction and effect size remained consistent with sensitivity analyses. The odds ratios (ORs) were 1.51 (95% CI = 0.24–9.41, p > 0.05) for MR-Egger, 1.60 (95% CI = 0.98–2.61, p > 0.05) for Weighted median, 1.68 (95% CI = 1.19–2.38, p < 0.05) for Maximum likelihood, 1.56 (95% CI = 1.05–2.33, p < 0.05) for MR. RAPS, and 1.65 (95% CI = 1.10–2.47, p < 0.05) for MR-PRESSO, respectively. No pleiotropy was observed (both P for MR-Egger intercept and Global test >0.05). In addition, the IVW method identified no significant correlation between bipolar disorder, schizophrenia and TMD.ConclusionGenetic evidence supports a causal relationship between major depression and TMD, instead of bipolar disorder and schizophrenia. These findings emphasize the importance of assessing a patient’s depressive status in clinical settings.

The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis

BackgroundAssociations of liver function with the risk of gestational diabetes mellitus (GDM) remain unclear. This study aimed to examine the relationship and the potential causality between maternal liver biomarkers and the risk of subsequent GDM, as well as to evaluate the interaction between liver biomarkers and lipids on GDM risk.MethodsIn an ongoing Zhoushan Pregnant Women Cohort, pregnant women who finished the first prenatal follow-up record, underwent liver function tests in early pregnancy, and completed the GDM screening were included in this study. Logistic regression models were used to investigate the association, and the inverse-variance weighted method supplemented with other methods of two-sample Mendelian randomization (MR) analysis was applied to deduce the causality.ResultsAmong 9,148 pregnant women, 1,668 (18.2%) developed GDM. In general, the highest quartile of liver function index (LFI), including ALT, AST, GGT, ALP, and hepatic steatosis index, was significantly associated with an increased risk of GDM (OR ranging from 1.29 to 3.15), especially an elevated risk of abnormal postprandial blood glucose level. Moreover, the causal link between ALT and GDM was confirmed by the MR analysis (OR=1.28, 95%CI:1.05-1.54). A significant interaction between AST/ALT and TG on GDM risk was observed (Pinteraction = 0.026).ConclusionElevated levels of LFI in early pregnancy were remarkably associated with an increased risk of GDM in our prospective cohort. Besides, a positive causal link between ALT and GDM was suggested.

Causal Associations Between Gut Microbiota, Gut Microbiota-Derived Metabolites, and Alzheimer's Disease: A Multivariable Mendelian Randomization Study.

Multiple studies have demonstrated that the gut microbiome is closely related to the onset of Alzheimer's disease, but the causal relationship between the gut microbiome and AD, as well as potential mediating factors, have not been fully explored. Our aim is to validate the causal relationship between the gut microbiome and the onset of AD and determine the key mechanism by which the gut microbiome mediates AD through blood metabolites using Mendelian randomization (MR) analysis methods. We first conducted bidirectional and mediating MR analyses using gut microbiota, blood amino acid metabolites, and AD-related single nucleotide polymorphisms as research data. In the analysis process, the inverse variance-weighted average method was mainly used as the primary method, with other methods serving as supplementary evidence. Ultimately, we found that six types of gut bacteria and two blood amino acid metabolites have a causal effect on AD. Subsequent mediation analysis proved that decreased glutamine concentration mediates the negative causal effect of Holdemanella bacteria on AD (mediation ratio of 14.5%), and increased serum alanine concentration mediates the positive causal effect of Parabacteroide bacteria on AD (mediation ratio of 9.4%). Our study demonstrates the causality of Holdemanella and Parabacteroides bacteria in the onset of AD and suggests that the reduced glutamine and increased alanine serums concentration may be key nodes in mediating this effect.

Causal effects of BMI, waist circumference, and body fat percentage on the risk of bladder cancer: A Mendelian randomization study.

The causal role of body mass index (BMI) in bladder cancer (BC) by Mendelian randomization (MR) has not yet been reported. We evaluated the causal associations between the measures of obesity (BMI, waist circumference, and body fat percentage) and BC. We conducted a 2-sample MR analysis to assess the genetic effect of measures of obesity on BC. The BMI dataset (GWAS ID: ukb-b-2303) comprised 454,884 Europeans, and we identified 9,851,867 single nucleotide polymorphisms (SNPs). The waist circumference data (GWAS ID: ukb-b-9405) included 462,166 Europeans and 9,851,867 SNPs. The body fat percentage dataset (GWAS ID: ukb-a-264) contained data from 331,117 Europeans and 10,894,596 SNPs. For the outcome data, the GWAS ID was finn-b-C3_BLADDER, consisting of 1115 cases and 217,677 controls, with 16,380,466 SNPs. The inverse-variance weighted (IVW) model was used as the primary MR analysis. Cochran Q-statistic was used to identify heterogeneity between the SNPs. The MR-Egger and MR-PRESSO methods were employed to assess directional pleiotropy and outlier SNPs. We detected a decisive causal link between BMI and BC by the IVW analysis (odds ratio [OR] = 1.41, 95% confidence interval [CI]: 1.08-1.85, P = .011). The IVW analyses revealed a significant correlation between BC and waist circumference (OR = 1.55, 95% CI: 1.08-2.12, P = .016). However, the IVW method (OR = 1.49, 95% CI: 0.99-2.00, P = .05) did not report any statistical significance between body fat percentage and BC. We did not observe heterogeneity and directional pleiotropy in the 3 pairs of MR studies. The 2-sample MR analysis revealed a conceivable causal association between obesity (BMI, waist circumference) and BC.

Associations between varicose veins and heart failure: A genetic correlation and mendelian randomization study.

Varicose veins and heart failure (HF) are increasingly prevalent. Although numbers of observational studies have indicated that varicose veins might contribute to the risk of HF, the causal relationship between them remains unclear due to the uncontrolled confounding factors and reverse causation bias. Therefore, this study aimed to explore the potential causal relationship between varicose veins and HF. Based on publicly released genome-wide association studies (GWAS), gene correlation was assessed using linkage disequilibrium score (LDSC) regression, and we conducted a two-sample Mendelian randomization (TSMR) analysis to infer the causal relationship. We performed the Inverse variance weighted (IVW) method as the primary analysis, and used Weighted median, MR-Egger, weighted mode, simple mode, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods to detect and correct for horizontal pleiotropy. LDSC revealed there was a positive genetic correlation between varicose veins and HF (rg = 0.1726184, Se = 0.04511803, P = .0001). The results of the IVW method indicated that genetically predicted varicose veins were associated with an increased risk of HF (odds ratio (OR) = 1.03; 95% confidence interval (CI): 1.01-1.06; P = .009). Our findings illustrated the significant causal effect of varicose veins on HF, suggesting that people with varicose veins might have a higher risk of HF. The results provided a novel and important perspective into the development mechanism of HF.

Mendelian randomization analysis reveals causal relationships between circulating cell traits and renal disorders

PurposeThe aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders.MethodsWe applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05.ResultsOur results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10–2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13–1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06–1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08–1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined.ConclusionOur findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.

Causal effects and metabolites mediators between immune cell and risk of breast cancer: a Mendelian randomization study

Introduction: The incidence and mortality of female breast cancer remain high, and the immune microenvironment of breast cancer has undergone significant alterations. However, the impact of blood immune cell levels on the risk of breast cancer is not fully understood. Therefor this study aims to investigate the causal relationship between blood immune cell levels and the risk of breast cancer.Methods: A Mendelian randomization (MR) analysis was employed to assess the causal relationship between immune cells and the risk of breast cancer, as along with their potential mediating factors. Genetic statistics of metabolites breast cancer and immune cells were obtained from the GWAS Catalog, while the genome-wide association study (GWAS) statistics of breast cancer were extracted from the UK biobank. Two-sample MR analysis were performed using inverse-variance weighted (IVW) to ascertain the causal association between immune cells and the risk of breast cancer. Furthermore, 1,400 metabolites were analyzed for their mediating role between immune cells and the risk of breast cancer.Results: MR analysis through IVW method revealed that genetically predicted CD24+ CD27+ B cells were associated with a decreased risk of breast cancer (OR = 0.9978, 95% CI: 0.996–0.999, p = 0.001), while IgD- CD38+ B cells were linked to an increased risk of breast cancer (OR = 1.002, 95% CI: 1.001–1.004, p = 0.005). Additional CD14+ CD16+ monocytes were associated with an increased risk of breast cancer (OR = 1.000, 95% CI: 1.000–1.001, p = 0.005). Mediation analysis revealed a positive causal relationship between IgD- CD38+ B cells and Glycerate levels, with the latter also exhibiting a positive causal relationship with the risk of breast cancer (p < 0.05). Conversely, IgD- CD38+ B cells displayed a negative causal relationship with Succinoyltaurine levels, and the latter also demonstrated a negative causal relationship with the risk of breast cancer (p < 0.05).Conclusion: This MR study provides novel genetic evidence supporting a causal relationship between IgD- CD38+ B cells and the risk of BC. Moreover, it is identified that IgD- CD38+ B cells contribute to an increased risk of BC through both positive and negative mediation effects involving Glycerate and Succinoyltaurine.

Rheumatoid arthritis and the risk of chronic kidney diseases: a Mendelian randomization study

BackgroundThe extra-articular lesions of rheumatoid arthritis (RA) are reported to involve multiple organs and systems throughout the body, including the heart, kidneys, liver, and lungs. This study assessed the potential causal relationship between RA and the risk of chronic kidney diseases (CKDs) using the Mendelian randomization (MR) analysis.MethodIndependent genetic instruments related to RA and CKD or CKD subtypes at the genome-wide significant level were chosen from the publicly shared summary-level data of genome-wide association studies (GWAS). Then, we obtained some single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs), which are associated with RA in individuals of European origin, and had genome-wide statistical significance (p5 × 10−8). The inverse-variance weighted (IVW) method was the main analysis method in MR analysis. The other methods, such as weighted median, MR–Egger, simple mode, and weighted mode were used as supplementary sensitivity analyses. Furthermore, the levels of pleiotropy and heterogeneity were assessed using Cochran’s Q test and leave-one-out analysis. Furthermore, the relevant datasets were obtained from the Open GWAS database.ResultsUsing the IVW method, the main method in MR analysis, the results showed that genetically determined RA was associated with higher risks of CKD [odds ratio (OR): 1.22, 95% confidence interval (CI) 1.13–1.31; p < 0.001], glomerulonephritis (OR: 1.23, 95% CI 1.15–1.31; p < 0.000), amyloidosis (OR = 1.43, 95% CI 1.10–1.88, p < 0.001), and renal failure (OR = 1.18, 95% CI 1.00–1.38, p < 0.001). Then, using multiple MR methods, it was confirmed that the associations persisted in sensitivity analyses, and no pleiotropy was detected.ConclusionThe findings revealed a causal relationship between RA and CKD, including glomerulonephritis, amyloidosis, and renal failure. Therefore, RA patients should pay more attention to monitoring their kidney function, thus providing the opportunity for earlier intervention and lower the risk of progression to CKDs.

Genetic evidence strengthens the connection between gut microbiota and gingivitis: a two-sample Mendelian randomization study

IntroductionThe oral cavity and gut tract, being interconnected and rich in microbiota, may have a shared influence on gingivitis. However, the specific role of distinct gut microbiota taxa in gingivitis remains unexplored. Utilizing Mendelian Randomization (MR) as an ideal method for causal inference avoiding reverse causality and potential confounding factors, we conducted a comprehensive two-sample MR study to uncover the potential genetic causal impact of gut microbiota on gingivitis.MethodsInstrumental variables were chosen from single nucleotide polymorphisms (SNPs) strongly associated with 418 gut microbiota taxa, involving 14,306 individuals. Gingivitis, with 4,120 cases and 195,395 controls, served as the outcome. Causal effects were assessed using random-effect inverse variance-weighted, weighted median, and MR-Egger methods. For replication and meta-analysis, gingivitis data from IEU OpenGWAS were employed. Sensitivity analyses included Cochran’s Q tests, funnel plots, leave-one-out analyses, and MR-Egger intercept tests. This study aimed to assess the genetic correlation between the genetically predicted gut microbiota and gingivitis using linkage disequilibrium score regression (LDSC).ResultsThree gut microbiota taxa (class Actinobacteria id.419, family Defluviitaleaceae id.1924, genus Defluviitaleaceae UCG011 id.11287) are predicted to causally contribute to an increased risk of gingivitis (P< 0.05). Additionally, four gut microbiota taxa (class Actinobacteria id.419, genus Escherichia Shigella id.3504, genus Ruminococcaceae UCG002 id.11360) potentially exhibit inhibitory causal effects on the risk of gingivitis (P< 0.05). No significant evidence of heterogeneity or pleiotropy is detected. Our findings indicate a suggestive genetic correlation between class Actinobacteria id.419, class Bacteroidia id.912, family Defluviitaleaceae id.1924, genus Escherichia Shigella id.3504 and gingivitis.ConclusionOur study establishes the genetic causal effect of 418 gut microbiota taxa on gingivitis, offering insights for clinical interventions targeting gingivitis. Subsequent research endeavors are essential to corroborate the findings of our present study.

Genetic Prediction of Osteoporosis by Anti-Müllerian Hormone Levels and Reproductive Factors in Women: A Mendelian Randomization Study.

Previous observational studies have suggested that anti-Müllerian hormone (AMH) and reproductive factors are linked to reduced bone mineral density (BMD) and an increased risk of osteoporosis (OP) in women. However, related studies are limited, and these traditional observational studies may be subject to residual confounders and reverse causation, while also lacking a more comprehensive observation of various reproductive factors. Univariate and multivariate two-sample Mendelian randomization analyses were conducted to determine the causal associations of AMH levels and six reproductive factors with BMD and OP, using the random-effects inverse-variance weighted method. Heterogeneity was assessed using Cochran's Q-statistic, and sensitivity analyses were performed to identify causal correlations. Age at menarche (AAM) was negatively associated with total body BMD (TB-BMD) in females aged 45-60 and over 60years, as well as with heel bone mineral density (eBMD). Conversely, age at natural menopause (ANM) was positively associated with TB-BMD in the same age ranges and with eBMD. ANM was only causally associated with self-reported OP and showed no significant correlation with definitively diagnosed OP. Neither AMH level nor other reproductive factors were significantly associated with a genetic predisposition to BMD at any age and OP. Later AAM and earlier ANM are significantly genetically causally associated with decreased BMD but not with OP. AMH levels, length of menstrual cycle, age at first birth, age at last birth, and number of live births, in terms of genetic backgrounds, are not causally related to BMD or OP.

Application of two-sample Mendelian randomization method to assess the causal relationship between rheumatoid arthritis and osteoporotic fracture.

The association between rheumatoid arthritis (RA) and osteoporotic fracture has garnered considerable attention; however, the causal relationships between diseases remain uncertain. Therefore, this study employed Mendelian randomization (MR) analysis to investigate the causal effects of RA on osteoporotic fracture. The summary data for RA and osteoporotic fracture were extracted from the genome-wide association studies (GWAS) catalog and the Finn Biobank database. The database provides information about diseased and health control subjects. We searched the database for the following conditions: RA, osteoporosis (OP), and osteoporotic fractures. Entries were published by investigating centers, which had established definitions and diagnostic criteria. We downloaded and processed the data to obtain the single-nucleotide polymorphisms (SNPs) strongly associated with RA, OP, and osteoporotic fracture. RA genetic associations were obtained from the GWAS catalog, including 1961 cases and 454,387 controls. The osteoporosis of the GWAS catalog involved 991 cases and 455,357 controls, and the data of the Finn Biobank involved 8,017 cases and 391,037 controls. Genetic associations for osteoporotic fracture were taken from the Finn Biobank of 1822 cases and 311,210 controls. Independent SNPs that are significantly associated with meeting the criteria of p < 5 × 10-8, r2 < 0.001, and kb = 10,000 were selected for MR analysis. The inverse variance-weighted (IVW) method along with other MR methods was employed for analysis, while sensitivity analyses were conducted to assess reliability and stability. The results provided strong evidence that RA was causally and positively associated with osteoporosis from the GWAS catalog (OR = 1.16590; 95% CI: 1.04067-1.30619; p = 0.00811) and the Finn Biobank database (OR = 1.07314; 95% CI: 1.03455-1.11317; p = 0.00016). Moreover, a positive causal relationship was detected between RA and osteoporotic fracture (OR = 1.10132; 95% CI: 1.00506-1.20680; p = 0.03863). The results were robust according to sensitivity tests. This study showed positive causal relationships between RA and osteoporotic fracture. These results should be considered in further studies and public health measures on osteoporosis prevention strategies.

Obesity-Related Traits Mediate the Effects of Educational Attainment on the Risk of Varicose Veins, Venous Thromboembolism, and Phlebitis.

The extent to which educational attainment (EA) influences the risk of varicose veins (VVs), venous thromboembolism (VTE), and phlebitis occurrence, whether this pathway is mediated by obesity-related traits, and the proportion of their mediation is unknown. A Mendelian randomization (MR) design was used to genetically investigate the causal effects of EA on the risk of VV, VTE, and phlebitis and to assess the mediating effect of obesity-related traits. Causal effects were estimated using primarily the multiplicative random-effects inverse variance-weighted method. This was supplemented by Cochran's Q-statistic, MR-Egger regression, MR funnel plots, and leave-one-out test to evaluate the reliability of the results. For the individual mediation effect, the coefficient product method was mainly utilized to estimate. An increase in genetically predicted EA was associated with a lower risk of VV, VTE, and phlebitis, as well as lower body mass index, basal metabolic rate, hip circumference, and waist circumference. As genetically predicted body mass index, basal metabolic rate, hip circumference, and waist circumference increased, the risk of developing VV, VTE, and phlebitis increased, respectively. Body mass index, basal metabolic rate, hip circumference, and waist circumference were identified as mediators of the protective effects of EA on VV, VTE, and phlebitis. The findings support a causal relationship between higher EA and lower risk of VV, VTE, and phlebitis. Obesity-related traits play a significant mediating role in these pathways, and there are interactions between them, with hip circumference mediating these pathways relatively independently from the other three.

Mendelian randomization analysis does not reveal a causal association between migraine and Meniere's disease.

According to observational research, migraine may increase the risk of Meniere's disease (MD). The two have not, however, been proven to be causally related. Using Mendelian random (MR) analysis, we aimed to evaluate any potential causal relationship between migraine and MD. We extracted single-nucleotide polymorphisms (SNPs) from large-scale genome-wide association studies (GWAS) involving European individuals, focusing on migraine and MD. The main technique used to evaluate effect estimates was inverse-variance weighting (IVW). To assess heterogeneity and pleiotropy, sensitivity analyses were carried out using weighted median, MR-Egger, simple mode, weighted mode, and MR-PRESSO. There was no discernible causative link between genetic vulnerability to MD and migraine. The migraine dose not increase the prevalence of MD in the random-effects IVW method (OR = 0.551, P = 0.825). The extra weighted median analysis (OR = 0.674, P = 0.909), MR-Egger (OR = 0.068, P = 0.806), Simple mode (OR = 0.170, P = 0.737), and Weighted mode (OR = 0.219, P= 0.760) all showed largely consistent results. The MD dose not increase the prevalence of migraine in the random-effects IVW method (OR = 0.999, P = 0.020). The extra weighted median analysis (OR = 0.999, P = 0.909), MR-Egger (OR = 0.999, P = 0.806), Simple mode (OR = 0.999, P = 0.737), and Weighted mode (OR = 1.000, P = 0.760). This Mendelian randomization study provides casual evidence that migraine is not a risk factor for MD and MD is also not a risk factor for migraine.

Genetically predicted gut microbiota mediate the association between plasma lipidomics and primary sclerosing cholangitis

BackgroundPrimary sclerosing cholangitis (PSC) is a complex disease with pathogenic mechanisms that remain to be elucidated. Previous observational studies with small sample sizes have reported associations between PSC, dyslipidemia, and gut microbiota dysbiosis. However, the causality of these associations is uncertain, and there has been no systematic analysis to date.MethodsThe datasets comprise data on PSC, 179 lipid species, and 412 gut microbiota species. PSC data (n = 14,890) were sourced from the International PSC Study Group, while the dataset pertaining to plasma lipidomics originated from a study involving 7174 Finnish individuals. Data on gut microbiota species were derived from the Dutch Microbiome Project study, which conducted a genome-wide association study involving 7738 participants. Furthermore, we employed a two-step Mendelian randomization (MR) analysis to quantify the proportion of the effect of gut microbiota-mediated lipidomics on PSC.ResultsFollowing a rigorous screening process, our MR analysis revealed a causal relationship between higher levels of gene-predicted Phosphatidylcholine (O-16:1_18:1) (PC O-16:1_18:1) and an increased risk of developing PSC (inverse variance-weighted method, odds ratio (OR) 1.30, 95% confidence interval (CI) 1.03–1.63). There is insufficient evidence to suggest that gene-predicted PSC impacts the levels of PC O-16:1_18:1 (OR 1.01, 95% CI 0.98–1.05). When incorporating gut microbiota data into the analysis, we found that Eubacterium rectale-mediated genetic prediction explains 17.59% of the variance in PC O-16:1_18:1 levels.ConclusionOur study revealed a causal association between PC O-16:1_18:1 levels and PSC, with a minor portion of the effect mediated by Eubacterium rectale. This study aims to further explore the pathogenesis of PSC and identify promising therapeutic targets. For patients with PSC who lack effective treatment options, the results are encouraging.

Causal association between urine albumin-to-creatinine ratio and risk of colorectal cancer: Atwo-sample Mendelian randomization study.

Previous observational studies have investigated the association between urinary albumin excretion and the risk of colorectal cancer (CRC), but the results have been inconsistent. This study aimed to explore the causal association between urine albumin-to-creatinine ratio (ACR) and CRC risk through a two-sample Mendelian randomization (MR) analysis. The genome-wide association study (GWAS) data of ACR (n=382,500) and CRC (CRC: 6,509 cases and 287,137 controls) were obtained from the IEU OpenGWAS project website and the FinnGen database, respectively. The TwoSampleMR and MR-PRESSO R packages were used to search for and analyze genetic variations that served as instrumental variables for ACR. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using the inverse-variance weighted method, MR-Egger, and weighted median. Genetically predicted ACR was not associated with CRC risk (all P > 0.05). Further analysis based on the site of onset (colon or rectum) also did not show a significant association (all P > 0.05). MR-PRESSO, MR-Egger regression and leave-one-out sensitivity analysis all indicated that the current results were robust and reliable. These findings suggest that ACR does not affect CRC risk and may not be used as a marker of CRC risk in clinical practice. However, relevant studies especially in ethnically diverse populations are still needed to confirm the current findings.

Association between diabetes mellitus and primary biliary cholangitis: a two-sample Mendelian randomization study.

Previous observational studies have demonstrated a link between diabetes mellitus(DM) and primary biliary cholangitis (PBC). Nevertheless, since these relationships might be confused, whether there is any causal connection or in which direction it exists is unclear. Our investigation aimed to identify the causal associations between DM and PBC. We acquired genome-wide association study (GWAS) datasets for PBC, Type 1 diabetes(T1DM), and Type 2 diabetes(T2DM) from published GWASs. Inverse variance-weighted (IVW), MR-Egger, weighted median (WM), Simple mode, and weighted mode methods were used to determine the causal relationships between DM(T1DM or T2DM) and PBC. Sensitivity analyses were also carried out to ensure the results were robust. To determine the causal relationship between PBC and DM(T1DM or T2DM), we also used reverse MR analysis. T1DM was associated with a higher risk of PBC (OR 1.1525; 95% CI 1.0612-1.2517; p = 0.0007) in the IVW method, but no evidence of a causal effect T2DM on PBC was found (OR 0.9905; 95% CI 0.8446-1.1616; p = 0.9071) in IVW. Results of the reverse MR analysis suggested genetic susceptibility that PBC was associated with an increased risk of T1DM (IVW: OR 1.1991; 95% CI 1.12-1.2838; p = 1.81E-07), but no evidence of a causal effect PBC on T2DM was found (IVW: OR 1.0101; 95% CI 0.9892-1.0315; p = 0.3420). The current study indicated that T1DM increased the risk of developing PBC and vice versa. There was no proof of a causal connection between PBC probability and T2DM. Our results require confirmation through additional replication in larger populations.