Elucidating the role of blood metabolites on pancreatic cancer risk using two-sample Mendelian randomization analysis

Pancreatic ductal adenocarcinoma (PDAC) is an uncommon but highly fatal malignancy. Identifying causal metabolite biomarkers offers an opportunity to facilitate effective risk assessment strategies for PDAC. In this study, we performed a two-sample Mendelian randomization (MR) study to characterize the potential causal effects of metabolites in plasma on PDAC risk. Genetic instruments were determined for a total of 506 metabolites from one set of comprehensive genome-wide association studies (GWAS) involving 913 individuals of European ancestry from the INTERVAL/EPIC-Norfolk cohorts. Another set of genetic instruments was developed for 483 metabolites from an independent GWAS conducted with 8299 individuals of European ancestry from the Canadian Longitudinal Study on Aging (CLSA) cohort. We analyzed GWAS data of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), comprising 8275 PDAC cases and 6723 controls of European ancestry. The association of metabolites with PDAC risk was assessed using the inverse-variance weighted (IVW) method, and complemented with sensitivity analyses of MR-Egger and MR-PRESSO tests. Potential side effects of targeting the identified metabolites for PDAC intervention were further evaluated by a phenome-wide MR (Phe-MR) analysis. Forty-four unique metabolites were identified to be significantly associated with PDAC risk, of which four top-ranking metabolites (X: 12798, X: 11787, X: 11308 and X: 19141) showed replication evidence when using instruments developed from both two cohorts. Our results highlight novel blood metabolites related to PDAC risk, which may help prioritize metabolic features for PDAC mechanistic research and further evaluation of their potential role in PDAC risk assessment.

Investigation of causal relationships between cortical structure and osteoporosis using two-sample Mendelian randomization

The mutual interaction between bone characteristics and brain had been reported previously, yet whether the cortical structure has any relevance to osteoporosis is questionable. Therefore, we applied a two-sample bidirectional Mendelian randomization analysis to investigate this relationship. We utilized the bone mineral density measurements of femoral neck (n = 32,735) and lumbar spine (n = 28,498) and data on osteoporosis (7300 cases and 358,014 controls). The global surficial area and thickness and 34 specific functional regions of 51,665 patients were screened by magnetic resonance imaging. For the primary estimate, we utilized the inverse-variance weighted method. The Mendelian randomization-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis were conducted to assess heterogeneity and pleiotropy. We observed suggestive associations between decreased thickness in the precentral region (OR = 0.034, P = 0.003) and increased chance of having osteoporosis. The results also revealed suggestive causality of decreased bone mineral density in femoral neck to declined total cortical surface area (β = 1400.230 mm2, P = 0.003), as well as the vulnerability to osteoporosis and reduced thickness in the Parstriangularis region (β = -0.006 mm, P = 0.002). Our study supports that the brain and skeleton exhibit bidirectional crosstalk, indicating the presence of a mutual brain-bone interaction.

Mendelian randomization study highlights hypothyroidism as a causal determinant of alopecia areata

Background

Although observational studies have found an association between hypothyroidism and alopecia areata, the causality of this relationship remains unclear.

Objectives

This study aimed to investigate the genetic variants associated with hypothyroidism and their potential impact on the risk of developing alopecia areata.

Methods

genome-wide association study summary statistics for hypothyroidism (30,155 cases and 379,986 controls) and alopecia areata (289 cases and 211,139 controls) were obtained from the IEU OpenGwas project. The inverse variance-weighted method was used as the primary analysis method to evaluate the causality between hypothyroidism and alopecia areata, supplemented by the weighted median, MR-Egger, simple mode and weighted mode. Furthermore, the function of causal SNPs was evaluated by gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction networks.

Result

Utilizing two-sample Mendelian randomization analysis, we found that the single-nucleotide polymorphisms (SNPs) of hypothyroidism (OR = 1.40, 95% CI: 1.12-1.75, p = 3.03×10-3) significantly increased the risk of alopecia areata ( 289 cases and 211,139 controls ). KEGG pathway analysis showed that the candidate genes were mainly enriched in virion-herpesvirus, Th1 and Th2 cell differentiation, Th17 cell differentiation, T-cell receptor signaling pathway, PD-L1/PD-1 checkpoint pathway in cancer and Toll-like receptor signaling pathway. Protein-protein interaction networks results showed that CTLA4, STAT4, IL2RA, TYK2, IRF7, SH2B3, BACH2, TLR3, NOD2, and FLT3.

Conclusion

This study provided compelling genetic evidence supporting a causative association between hypothyroidism and alopecia areata, which could potentially inform the development of more efficacious treatment strategies for patients afflicted by alopecia areata.

Causal association between colorectal cancer and Alzheimer's disease: a bidirectional two-sample mendelian randomization study

Background: Colorectal cancer and Alzheimer's disease are both common life-threatening diseases in the elderly population. Some studies suggest a possible inverse relationship between colorectal cancer and Alzheimer's disease, but real-world research is subject to many biases. We hope to clarify the causal relationship between the two through a bidirectional two-sample Mendelian randomization study. Methods: In our study, we used genetic summary data from large-scale genome-wide association studies to investigate the relationship between colorectal cancer and Alzheimer's disease. Our primary analysis employed the inverse-variance weighted method and we also used complementary techniques, including MR-Egger, weighted median estimator, and Maximum likelihood. We applied simex adjustment to the MR-Egger results. We also utilized the MRlap package to detect potential sample overlap and its impact on the bias of the results. In addition, we performed several sensitivity and heterogeneity analyses, to ensure the reliability of our results. Results: The combined effect size results of the inverse-variance weighted method indicate that colorectal cancer may decrease the incidence of Alzheimer's disease, with an odds ratio (OR) of 0.846 (95% CI: 0.762-0.929). Similar results were observed using other methods such as MR-Egger, weighted median estimator, and Maximum likelihood. On the other hand, Alzheimer's disease may slightly increase the incidence of colorectal cancer, with an OR of 1.014 (95% CI: 1.001-1.027). However, the results of one subgroup were not significant, and the results from MRlap indicated that sample overlap introduced bias into the results. Therefore, the results of the reverse validation are not reliable. The F-statistic for all SNPs was greater than 20. Four SNPs related to the outcome were excluded using Phenoscanner website but the adjustment did not affect the overall direction of the results. The results of these statistics were further validated by MR-PRESSO, funnel plots, leave-one-out analyses, Cochran's Q, demonstrating the reliability of the findings. Conclusion: According to the findings of this Mendelian randomization study, there appears to be a causal association between colorectal cancer and Alzheimer's disease. These results could have important implications for clinical practice in terms of how colorectal cancer and Alzheimer's disease are treated. To better understand the relationship between these two diseases, more research and screening are needed in clinical settings.

Platelet-derived growth factor subunit-B mediating the effect of dickkopf-1 on acute myocardial infarction risk: a two-step Mendelian randomization study

Previous studies have indicated a potential connection between plasma levels of Dickkopf-1 (DKK1) and platelet-derived growth factor subunit-B (PDGF-B) with the development of atherosclerosis. However, the causal relationship between DKK1, PDGF-B, and the risk of acute myocardial infarction (AMI) is yet to be established. To address this research gap, we conducted Mendelian randomization (MR) and mediation analyses to investigate the potential mediating role of PDGF-B in the association between DKK1 and AMI risk. Summary statistics for DKK1 (n = 3,301) and PDGF-B (n = 21,758) were obtained from the GWAS meta-analyses conducted by Sun et al. and Folkersen et al., respectively. Data on AMI cases (n = 3,927) and controls (n = 333,272) were retrieved from the UK Biobank study. Our findings revealed that genetic predisposition to DKK1 (odds ratio [OR]: 1.00208; 95% confidence interval [CI]: 1.00056-1.00361; P = 0.0072) and PDGF-B (OR: 1.00358; 95% CI: 1.00136-1.00581; P = 0.0015) was associated with an increased risk of AMI. Additionally, genetic predisposition to DKK1 (OR: 1.38389; 95% CI: 1.07066-1.78875; P = 0.0131) was linked to higher PDGF-B levels. Furthermore, our MR mediation analysis revealed that PDGF-B partially mediated the association between DKK1 and AMI risk, with 55.8% of the effect of genetically predicted DKK1 being mediated through genetically predicted PDGF-B. These findings suggest that genetic predisposition to DKK1 is positively correlated with the risk of AMI, and that PDGF-B partially mediates this association. Therefore, DKK1 and PDGF-B may serve as promising targets for the prevention and treatment of AMI.

Association Between Endometritis and Endometrial Polyp: A Mendelian Randomization Study

Background

Endometrial polyps (EPs) are one of the most common intrauterine benign tumors, and are an important cause of uterine bleeding and female infertility. Previous studies have suggested that endometritis may contribute to the onset of EPs. This study aims to reveal the causal effect of endometritis on EPs by a two-sample Mendelian randomization (MR) study.

Methods

Utilizing summarized statistics from genome-wide association studies (GWAS) in the European population, we conducted a Mendelian randomization study. In order to select suitable instrumental variables (IVs) that were significantly related to the exposures, a number of quality control approaches were used. For endometritis, 2144 cases and 111,858 controls were included, while for EPs, 2252 cases and 460,758 controls. Utilizing the inverse variance weighted (IVW) as the primary analysis, the data were subjected to a two-sample MR analysis, and the weighted median (WM) technique and MR-Egger regression were carried out additionally. The sensitivity analysis revealed neither heterogeneity nor horizontal pleiotropy.

Results

Four independent single nucleotide polymorphisms (SNPs) from endometritis GWAS as IVs were selected. The IVW data did not agree to a causal association between endometritis and EPs (β=1.11e-04, standard error [SE] =4.88e-04, P = 0.82). Directional pleiotropy did not affect the outcome, according to the MR-Egger regression (intercept = 0.09, P = 0.10); Additionally, it showed no causation association between endometritis and EPs (β= -3.28e-03, SE = 3.54e-03, P = 0.45). Similar results were obtained using the weighted-median method (β=8.56e-05, SE=5.97e-04, P = 0.89). No proof of heterogeneity and horizontal pleiotropy between IV estimates was discovered.

Conclusion

In conclusion, by large scale genetic data, the results of this MR analysis provided suggestive evidence that the presence of endometritis is not associated with higher EPs risk.

Genetic evidence supporting the causal role of gut microbiota in chronic kidney disease and chronic systemic inflammation in CKD: a bilateral two-sample Mendelian randomization study

Background

The association of gut microbiota (GM) and chronic kidney disease (CKD), and the relevancy of GM and chronic systemic inflammation in CKD, were revealed on the basis of researches on gut-kidney axis in previous studies. However, their causal relationships are still unclear.

Objective

To uncover the causal relationships between GM and CKD, as well as all known GM from eligible statistics and chronic systemic inflammation in CKD, we performed two-sample Mendelian randomization (MR) analysis.

Materials and methods

We acquired the latest and most comprehensive summary statistics of genome-wide association study (GWAS) from the published materials of GWAS involving GM, CKD, estimated glomerular filtration rate (eGFR), c-reactive protein (CRP) and urine albumin creatine ratio (UACR). Subsequently, two-sample MR analysis using the inverse-variance weighted (IVW) method was used to determine the causality of exposure and outcome. Based on it, additional analysis and sensitivity analysis verified the significant results, and the possibility of reverse causality was also assessed by reverse MR analysis during this study.

Results

At the locus-wide significance threshold, IVW method and additional analysis suggested that the protective factors for CKD included family Lachnospiraceae (P=0.049), genus Eubacterium eligens group (P=0.002), genus Intestinimonas (P=0.009), genus Streptococcu (P=0.003) and order Desulfovibrionales (P=0.001). Simultaneously, results showed that genus LachnospiraceaeUCG010 (P=0.029) was a risk factor for CKD. Higher abundance of genus Desulfovibrio (P=0.048) was correlated with higher eGFR; higher abundance of genus Parasutterella (P=0.018) was correlated with higher UACR; higher abundance of class Negativicutes (P=0.003), genus Eisenbergiella (P=0.021), order Selenomonadales (P=0.003) were correlated with higher CRP levels; higher abundance of class Mollicutes (0.024), family Prevotellaceae (P=0.030), phylum Tenericutes (P=0.024) were correlated with lower levels of CRP. No significant pleiotropy or heterogeneity was found in the results of sensitivity analysis, and no significant causality was found in reverse MR analysis.

Conclusion

This study highlighted associations within gut-kidney axis, and the causal relationships between GM and CKD, as well as GM and chronic systemic inflammation in CKD were also revealed. Meanwhile, we expanded specific causal gut microbiota through comprehensive searches. With further studies for causal gut microbiota, they may have the potential to be new biomarkers for targeted prevention of CKD and chronic systemic inflammation in CKD.

Association between 23 drugs and Parkinson's disease: A two-sample Mendelian randomization study

BACKGROUND

Parkinson's disease (PD) is a common degenerative nervous system disease. At present, there are certain limitations in various treatment options aimed at preventing or delaying the progression of PD. Therefore, the exploration of new drugs for PD is beneficial. Mendelian randomization (MR) analysis can be used to explore the association between drugs and diseases. In this study, MR analysis was adopted to investigate the causal relationship between 23 drugs and PD. These drugs have been approved for the treatment of different diseases, such as salicylic acid and derivatives (collectively called salicylates, e.g., aspirin, used for fever and pain relief), antithrombotic agents (e.g., warfarin, aspirin, used for preventing thrombotic events).

METHODS

The GWAS data for the 23 drugs were obtained from the UK Biobank (UKB) project, while the GWAS data for PD were sourced from FinnGen. Single-Nucleotide Polymorphisms (SNPs) were selected as instrumental variables (IVs). We first performed a series of quality control steps (including MR-PRESSO) to select the appropriate SNPs. Two-sample MR analysis was performed using five different methods, including inverse variance weighting (IVW) with random-effects model, weighted median, MR-Egger, simple model, and weighted model. At the same time, sensitivity analysis was carried out using the MR-Egger and Cochran's Q test to ensure the authenticity and reliability of the results.

RESULTS

In MR-PRESSO, salicylates and antithrombotic agents showed statistically significant associations with PD, respectively. In the main MR analysis (IVW), there was a negative causal relationship between salicylates and PD (OR = 0.73, 95% CI = 0.54-0.98, p = .039). Similarly, there was a negative causal relationship between antithrombotic agents and PD (OR = 0.70, 95%CI = 0.52-0.96, p = .027). No statistically significant association was found between the remaining 21 drugs and PD.

CONCLUSION

This MR study demonstrated that salicylates and antithrombotic agents can reduce the risk of PD, thus providing a novel avenue for future drug exploration in PD.

Unveiling the intricate causal nexus between pancreatic cancer and peripheral metabolites through a comprehensive bidirectional two-sample Mendelian randomization analysis

Aim: Pancreatic cancer (PC) is a devastating malignancy characterized by its aggressive nature and poor prognosis. However, the relationship of PC with peripheral metabolites remains not fully investigated. The study aimed to explore the causal linkage between PC and peripheral metabolite profiles. Methods: Employing publicly accessible genome-wide association studies (GWAS) data, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis. The primary analysis employed the inverse-variance weighted (IVW) method. To address potential concerns about horizontal pleiotropy, we also employed supplementary methods such as maximum likelihood, weighted median, MR-Egger regression, and MR pleiotropy residual sum and outlier (MR-PRESSO). Results: We ascertained 20 genetically determined peripheral metabolites with causal linkages to PC while high-density lipoprotein (HDL) and very low-density lipoprotein (VLDL) particles accounted for the vast majority. Specifically, HDL particles exhibited an elevated PC risk while VLDL particles displayed an opposing pattern. The converse MR analysis underscored a notable alteration in 17 peripheral metabolites due to PC, including branch chain amino acids and derivatives of glycerophospholipid. Cross-referencing the bidirectional MR results revealed a reciprocal causation of PC and X-02269 which might form a self-perpetuating loop in PC development. Additionally, 1-arachidonoylglycerophosphocholine indicated a reduced PC risk and an increase under PC influence, possibly serving as a negative feedback regulator. Conclusion: Our findings suggest a complex interplay between pancreatic cancer and peripheral metabolites, with potential implications for understanding the etiology of pancreatic cancer and identifying novel early diagnosis and therapeutic targets. Moreover, X-02269 may hold a pivotal role in PC onset and progression.

The causal relationship between autoimmune diseases and osteoporosis: a study based on Mendelian randomization

Objective

The relationship between different autoimmune diseases and bone mineral density (BMD) and fractures has been reported in epidemiological studies. This study aimed to explore the causal relationship between autoimmune diseases and BMD, falls, and fractures using Mendelian randomization (MR).

Methods

The instrumental variables were selected from the aggregated statistical data of these diseases from the largest genome-wide association study in Europe. Specifically, 12 common autoimmune diseases were selected as exposure. Outcome variables included BMD, falls, and fractures. Multiple analysis methods were utilized to comprehensively evaluate the causal relationship between autoimmune diseases and BMD, falls, and fractures. Additionally, sensitivity analyses, including Cochran's Q test, MR-Egger intercept test, and one analysis, were conducted to verify the result's reliability.

Results

Strong evidence was provided in the results of the negatively association of ulcerative colitis (UC) with forearm BMD. UC also had a negatively association with the total body BMD, while inflammatory bowel disease (IBD) depicted a negatively association with the total body BMD at the age of 45-60 years. Horizontal pleiotropy or heterogeneity was not detected through sensitivity analysis, indicating that the causal estimation was reliable.

Conclusion

This study shows a negative causal relationship between UC and forearm and total body BMD, and between IBD and total body BMD at the age of 45-60 years. These results should be considered in future research and when public health measures and osteoporosis prevention strategies are formulated.

The causal relationship between multiple autoimmune diseases and nasal polyps

Background

Although previous sporadic studies have reported the associations between a few autoimmune diseases and nasal polyps, these studies have limitations such as conflicting results, small sample sizes, and low levels of evidence.

Methods

Several autoimmune diseases were selected as exposures while the nasal polyps were selected as outcomes. Bidirectional univariable Mendelian randomization and multivariable Mendelian randomization analyses were performed after rigorous screening of instrumental variables. Then mediation analyses were conducted to further investigate the underlying mechanisms.

Results

For the first time, we investigated the causal relationships between nine autoimmune diseases and nasal polyps in different genders and found: (1) there was a causal association between adult-onset Still's disease and nasal polyps; (2) sarcoidosis, ulcerative colitis, type 1 diabetes, and Crohn's disease had no significant associations with nasal polyps; (3) celiac disease showed a suggestive positive association with female nasal polyps, whereas juvenile arthritis and multiple sclerosis showed suggestive positive associations with male nasal polyps. By contrast, arthropathic psoriasis showed a suggestive negative association with nasal polyps. In addition to these nine diseases, previous controversial issues were further investigated: (1) there was a causal relationship between rheumatoid arthritis and nasal polyps, which was partially mediated by "BAFF-R for IgD+ B cells"; (2) ankylosing spondylitis showed suggestive positive associations with the female but not the male nasal polyps. Besides, we validated that there was no causal effect of autoimmune hyperthyroidism on nasal polyps.

Conclusion

Specific conclusions regarding the causal effects of multiple autoimmune diseases on nasal polyps are the same as above. By comparing results between different genders, we have initially observed the sex bimodality in the causal effects between autoimmune diseases and nasal polyps, with those on male nasal polyps being stronger than those on female nasal polyps. Our study lays a solid foundation for further research in the future, not only helping identify individuals susceptible to nasal polyps early but also improving our understanding of the immunopathogenesis of these heterogeneous diseases.

The causal associations between growth factors and constipation: a two-sample Mendelian randomization study

Introduction: Certain growth factors (GFs) are associated with constipation, but few studies has analyzed the causal associations between the two. Therefore, this study used two-sample Mendelian randomization (MR) to systematically analyze the causal associations between GF levels and constipation based on data from genome-wide association studies (GWAS). Methods: Both GF and constipation data were obtained from European populations. GFs, as an exposure variable, were obtained from a genetic map of the human plasma proteome containing 3,301 samples, another GWAS dataset on 90 circulating proteins containing 30,931 samples, and a GWAS dataset containing 3,788 samples. Constipation, as an outcome variable, was obtained from the FinnGen project containing 26,919 cases and 282,235 controls and another UK Biobank dataset containing 3,328 cases and 459,682 controls. Single-nucleotide polymorphisms strongly associated with GFs were regarded as instrumental variables. Inverse-variance weighting, MR-Egger regression, weight median, simple mode, and weight mode methods were used to determine genetic associations. Cochran's Q test, Egger intercept, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier tests were used to analyze sensitivity. Results: The IVW analysis based on FinnGen showed that NGFI-A-binding protein 2 and vascular endothelial growth factor receptor 2 were inversely associated with constipation, and that fibroblast growth factor 7 and transforming growth factor beta receptor II levels were positively associated with constipation. The IVW analysis based on UK Biobank showed that proheparin-binding epidermal growth factor, platelet-derived growth factor AA, and vascular endothelial growth factor₁₂₁ were inversely associated with constipation. Conclusion: This study showed that some GFs are genetically associated with the risk of constipation.

mGWAS-Explorer 2.0: Causal Analysis and Interpretation of Metabolite-Phenotype Associations

Metabolomics-based genome-wide association studies (mGWAS) are key to understanding the genetic regulations of metabolites in complex phenotypes. We previously developed mGWAS-Explorer 1.0 to link single-nucleotide polymorphisms (SNPs), metabolites, genes and phenotypes for hypothesis generation. It has become clear that identifying potential causal relationships between metabolites and phenotypes, as well as providing deep functional insights, are crucial for further downstream applications. Here, we introduce mGWAS-Explorer 2.0 to support the causal analysis between >4000 metabolites and various phenotypes. The results can be interpreted within the context of semantic triples and molecular quantitative trait loci (QTL) data. The underlying R package is released for reproducible analysis. Using two case studies, we demonstrate that mGWAS-Explorer 2.0 is able to detect potential causal relationships between arachidonic acid and Crohn's disease, as well as between glycine and coronary heart disease.

Observational and genetic evidence support a relationship between cardiac autonomic function and blood pressure

Background

It is unclear how cardiac autonomic function, as indicated by heart rate (HR), heart rate variability (HRV), HR increase during exercise, and HR recovery after exercise, is related to blood pressure (BP). We aimed to examine the observational and genetic evidence for a potential causal effect of these HR(V) traits on BP.

Methods

We performed multivariable adjusted linear regression using Lifelines and UK Biobank cohorts to investigate the relationship between HR(V) traits and BP. Linkage disequilibrium score regression was conducted to examine genetic correlations. We used two-sample Mendelian randomization (2SMR) to examine potential causal relations between HR(V) traits and BP.

Results

Observational analyses showed negative associations of all HR(V) traits with BP, except for HR, which was positively associated. Genetic correlations were directionally consistent with the observational associations, but most significant genetic correlations between HR(V) traits and BP were limited to diastolic blood pressure (DBP). 2SMR analyses suggested a potentially causal relationship between HR(V) traits and DBP but not systolic blood pressure (SBP). No reverse effect of BP on HR(V) traits was found. One standard deviation (SD) unit increase in HR was associated with a 1.82 mmHg elevation of DBP. In contrast, one ln(ms) unit increase of the root mean square of the successive differences (RMSSD) and corrected RMSSD (RMSSDc), decreased DBP by 1.79 and 1.83 mmHg, respectively. For HR increase and HR recovery at 50 s, every additional SD increase was associated with a lower DBP by 2.05 and 1.47 mmHg, respectively. Results of secondary analyses with pulse pressure as outcome were inconsistent between observational and 2SMR analyses, as well as between HR(V) traits, and therefore inconclusive.

Conclusion

Both observational and genetic evidence show strong associations between indices of cardiac autonomic function and DBP, suggesting that a larger relative contribution of the sympathetic versus the parasympathetic nervous system to cardiac function may cause elevated DBP.

Hypothyroidism and rheumatoid arthritis: a two-sample Mendelian randomization study

Background

Meta-analysis of genome-wide association studies (GWAS) data showed that the relationship between hypothyroidism and rheumatoid arthritis (RA) risk remains under debate. This study is conducted to test the causal relationship of hypothyroidism and RA.

Methods

A two-sample Mendelian randomization (TSMR) analysis was employed to estimate the causality of hypothyroidism and rheumatoid arthritis in European ancestry and Asian ancestry. Integrating the effects generated by TSMR, functional annotations and noncoding variant prediction framework were applied to analyze and interpret the functional instrument variants (IVs).

Results

The results of the inverse variance weighted method showed a strong significant causal relationship between hypothyroidism and risk of RA in European ancestry [odds ratio (OR) = 1.96; 95% confidence interval (CI) 1.49, 2.58; p < 0.001]. The outcomes of MR-Egger, weighted median, weighted mode, and simple mode also showed that hypothyroidism was significantly associated with increased risk of RA in European ancestry. The MR-PRESSO method also showed significant results [Outlier-corrected Causal Estimate = 0.70; standard error (SE) = 0.06; p < 0.001]. An independent dataset and an Asian ancestry dataset were applied to estimate and obtain the coincident results. Furthermore, we integrated the effect of variants in TSMR analysis, functional annotations, and prediction methods to pinpoint the single-nucleotide polymorphism (SNP) rs4409785 as one of the causal variants, which suggested that this variant could impact the binding of CTCF-cohesin and play a vital role in immune cells.

Conclusion

In this study, we prove that hypothyroidism is significantly causally associated with increased RA risk, which has not been shown in previous studies. Furthermore, we pinpoint the potential causal variants in RA.

C-Reactive Protein Levels and Risk of Cardiovascular Diseases: A Two-Sample Bidirectional Mendelian Randomization Study

Elevated C-reactive protein (CRP) levels are an indicator of inflammation, a major risk factor for cardiovascular disease (CVD). However, this potential association in observational studies remains inconclusive. We performed a two-sample bidirectional Mendelian randomization (MR) study using publicly available GWAS summary statistics to evaluate the relationship between CRP and CVD. Instrumental variables (IVs) were carefully selected, and multiple approaches were used to make robust conclusions. Horizontal pleiotropy and heterogeneity were evaluated using the MR-Egger intercept and Cochran's Q-test. The strength of the IVs was determined using F-statistics. The causal effect of CRP on the risk of hypertensive heart disease (HHD) was statistically significant, but we did not observe a significant causal relationship between CRP and the risk of myocardial infarction, coronary artery disease, heart failure, or atherosclerosis. Our primary analyses, after performing outlier correction using MR-PRESSO and the Multivariable MR method, revealed that IVs that increased CRP levels also increased the HHD risk. However, after excluding outlier IVs identified using PhenoScanner, the initial MR results were altered, but the sensitivity analyses remained congruent with the results from the primary analyses. We found no evidence of reverse causation between CVD and CRP. Our findings warrant updated MR studies to confirm the role of CRP as a clinical biomarker for HHD.

Causal relationships between birth weight, childhood obesity and age at menarche: A two-sample Mendelian randomization analysis

OBJECTIVES

Observational studies suggest birth weight and childhood obesity are closely associated with age at menarche. However, the relationships between them are currently inconsistent and it remains elusive whether such associations are causal. Therefore, the aim of the study was to investigate whether there existed causal relationships between birth weight, childhood obesity and age at menarche.

DESIGN, PATIENTS AND MEASUREMENTS

A two-sample Mendelian randomization (MR) study. The standard inverse variance weighted MR analyses were adopted to evaluate the causal effects of birth weight (n = 143,677), childhood body mass index (BMI) (n = 39,620) on age at menarche (n = 182,416) with summary statistics from large-scale genome-wide association studies (GWASs). Meanwhile, we validated our MR results with some sensitivity analyses including maximum likelihood, weighted-median and MR pleiotropy residual sum and outlier methods.

RESULTS

The present study showed that each one standard deviation (1-SD) lower birth weight was predicted to result in a 0.1479 years earlier of age at menarche (β = .1479, 95% confidence interval [CI] = 0.0422-0.2535; p = 0.0061). We also found that genetically predicted 1-SD increase in childhood BMI was causally associated with early age at menarche (β = -.3966, 95% CI = -0.5294 to -0.2639; p = 4.73E-09).

CONCLUSIONS

Our MR study suggests the causal effect of lower birth weight and higher childhood BMI on the increased risk of earlier menarche. It may be the opportune time to carry out weight control intervention in prenatal and early childhood development periods to prevent early menarche onset, thus decreasing the future adverse consequences.

Plasma homocysteine levels and risk of congestive heart failure or cardiomyopathy: A Mendelian randomization study

Background

Although observational studies have demonstrated associations between elevated plasma homocysteine levels and the risk of cardiovascular diseases, controversy remains.

Objective

This study investigated the causal association of plasma homocysteine levels with congestive heart failure and cardiomyopathy risk.

Methods

We performed a two-sample Mendelian randomization (MR) study of congestive heart failure (n = 218,792), cardiomyopathy (n = 159,811), and non-ischemic cardiomyopathy (n = 187,152). Genetic summary data on the association of single-nucleotide polymorphisms with homocysteine were extracted from the most extensive genome-wide association study of 44,147 individuals. MR analyses, including the random-effect inverse variance-weighted (IVW) meta-analysis, weighted median, simple median, maximum likelihood, penalized weighted median, MR-PRESSO, and MR-Egger regression, were used to estimate the associations between the selected single-nucleotide polymorphisms and congestive heart failure or cardiomyopathy.

Results

The MR analyses revealed no causal role of higher genetically predicted plasma homocysteine levels with congestive heart failure risk (random-effect IVW, odds ratio [OR] per standard deviation (SD) increase in homocysteine levels = 1.753, 95% confidence interval [CI] = 0.674-4.562, P = 0.250), cardiomyopathy (random-effect IVW, OR per SD increase in homocysteine levels = 0.805, 95% CI = 0.583 to 1.020, P = 0.189), or non-ischemic cardiomyopathy (random-effect IVW, OR per SD increase in homocysteine levels = 1.064, 95% CI = 0.927-1.222, P = 0.379). The results were consistent with other analytical methods and sensitivity analyses.

Conclusion

Genetically predicted homocysteine level was not associated with congestive heart failure or cardiomyopathy risk. It is unlikely that homocysteine-lowering therapy decreases the incidence or improves the outcomes of congestive heart failure and cardiomyopathy.

Fatty acids and risk of dilated cardiomyopathy: A two-sample Mendelian randomization study

Background

Previous observational studies have shown intimate associations between fatty acids (FAs) and dilated cardiomyopathy (DCM). However, due to the confounding factors and reverse causal association found in observational epidemiological studies, the etiological explanation is not credible.

Objective

To exclude possible confounding factors and reverse causal associations found in observational epidemiological studies, we used the two-sample Mendelian randomization (MR) analysis to verify the causal relationship between FAs and DCM risk.

Method

All data of 54 FAs were downloaded from the genome-wide association studies (GWAS) catalog, and the summary statistics of DCM were extracted from the HF Molecular Epidemiology for Therapeutic Targets Consortium GWAS. Two-sample MR analysis was conducted to evaluate the causal effect of FAs on DCM risk through several analytical methods, including MR-Egger, inverse variance weighting (IVW), maximum likelihood, weighted median estimator (WME), and the MR pleiotropy residual sum and outlier test (MRPRESSO). Directionality tests using MR-Steiger to assess the possibility of reverse causation.

Results

Our analysis identified two FAs, oleic acid and fatty acid (18:1)-OH, that may have a significant causal effect on DCM. MR analyses indicated that oleic acid was suggestively associated with a heightened risk of DCM (OR = 1.291, 95%CI: 1.044-1.595, P = 0.018). As a probable metabolite of oleic acid, fatty acid (18:1)-OH has a suggestive association with a lower risk of DCM (OR = 0.402, 95%CI: 0.167-0.966, P = 0.041). The results of the directionality test suggested that there was no reverse causality between exposure and outcome (P < 0.001). In contrast, the other 52 available FAs were discovered to have no significant causal relationships with DCM (P > 0.05).

Conclusion

Our findings propose that oleic acid and fatty acid (18:1)-OH may have causal relationships with DCM, indicating that the risk of DCM from oleic acid may be decreased by encouraging the conversion of oleic acid to fatty acid (18:1)-OH.

Causal effects for genetic variants of osteoprotegerin on the risk of acute myocardial infarction and coronary heart disease: A two-sample Mendelian randomization study

Although since the 1980s, the mortality of coronary heart disease(CHD) has obviously decreased due to the rise of coronary intervention, the mortality and disability of CHD were still high in some countries. Etiological studies of acute myocardial infarction(AMI) and CHD were extremely important. In this study, we used two-sample Mendelian randomization(TSMR) method to collect GWAS statistics of osteoprotegerin (OPG), AMI and CHD to reveal the causal relationship between OPG and these two diseases. In total, we identified 7 genetic variants associated with AMI and 7 genetic variants associated with CHD that were not found to be in linkage disequilibrium(LD; r ² < 0.001). Evidence of a positive effect of an OPG genetic susceptibility on AMI was discovered(IVW OR = 0.877; 95% CI = 0.787-0.977; p = 0.017; 7 SNPs) and CHD (IVW OR = 0.892; 95% CI = 0.803-0.991; p = 0.033; 7 SNPs). After removing the influence of rs1385492, we found that there was a correlation between OPG and AMI/CHD (AMI: weighted median OR = 0.818;95% CI = 0.724-0.950; p = 0.001; 6SNPs;CHD: weighted median OR = 0.842; 95% CI = 0.755-0.938; p = 1.893 × 10^-3; 6SNPs). The findings of our study indicated that OPG had a tight genetic causation association with MI or CHD. This genetic causal relationship presented us with fresh ideas for the etiology of AMI and CHD, which is an area of research that will continue in the future.

Dehydroepiandrosterone Sulfate and Colorectal Cancer Risk: A Mendelian Randomization Analysis

Colorectal cancer is the third most common and second most deadly type of cancer worldwide, with approximately 1.9 million cases and 0.9 million deaths worldwide in 2020. Previous studies have shown that estrogen and testosterone hormones are associated with colorectal cancer risk and mortality. However, the potential effect of their precursor, dehydroepiandrosterone sulfate (DHEAS), on colorectal cancer risk has not been investigated. Therefore, evaluating DHEAS's effect on colorectal cancer will expand our understanding of the hormonal contribution to colorectal cancer risk. In this study, we conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal effect of DHEAS on colorectal cancer. We obtained DHEAS and colorectal cancer genomewide association study (GWAS) summary statistics from the Leipzig Health Atlas and the GWAS catalog and conducted MR analyses using the TwoSampleMR R package. Our results suggest that higher DHEAS levels are causally associated with decreased colorectal cancer risk (odds ratio per unit increase in DHEAS levels z score = 0.70; 95% confidence interval [0.51, 0.96]), which is in line with previous observations in a case-control study of colon cancer. The outcome of this study will be beneficial in developing plasma DHEAS-based biomarkers in colorectal cancer. Further studies should be conducted to interpret the DHEAS-colorectal cancer association among different ancestries and populations.

The Causal Effects of Primary Biliary Cholangitis on Thyroid Dysfunction: A Two-Sample Mendelian Randomization Study

Background: Primary biliary cholangitis (PBC) is an autoimmune disease and is often accompanied by thyroid dysfunction. Understanding the potential causal relationship between PBC and thyroid dysfunction is helpful to explore the pathogenesis of PBC and to develop strategies for the prevention and treatment of PBC and its complications.

Methods: We used a two-sample Mendelian randomization (MR) method to estimate the potential causal effect of PBC on the risk of autoimmune thyroid disease (AITD), thyroid-stimulating hormone (TSH) and free thyroxine (FT4), hyperthyroidism, hypothyroidism, and thyroid cancer (TC) in the European population. We collected seven datasets of PBC and related traits to perform a series MR analysis and performed extensive sensitivity analyses to ensure the reliability of our results.

Results: Using a sensitivity analysis, we found that PBC was a risk factor for AITD, TSH, hypothyroidism, and TC with odds ratio (OR) of 1.002 (95% CI: 1.000–1.005, p = 0.042), 1.016 (95% CI: 1.006–1.027, p = 0.002), 1.068 (95% CI: 1.022–1.115, p = 0.003), and 1.106 (95% CI: 1.019–1.120, p = 0.042), respectively. Interestingly, using reverse-direction MR analysis, we also found that AITD had a significant potential causal association with PBC with an OR of 0.021 (p = 5.10E−4) and that the other two had no significant causal relation on PBC.

Conclusion: PBC causes thyroid dysfunction, specifically as AITD, mild hypothyroidism, and TC. The potential causal relationship between PBC and thyroid dysfunction provides a new direction for the etiology of PBC.

Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization

Multivariable Mendelian randomization (MVMR) is a form of instrumental variable analysis which estimates the direct effect of multiple exposures on an outcome using genetic variants as instruments. Mendelian randomization and MVMR are frequently conducted using two-sample summary data where the association of the genetic variants with the exposures and outcome are obtained from separate samples. If the genetic variants are only weakly associated with the exposures either individually or conditionally, given the other exposures in the model, then standard inverse variance weighting will yield biased estimates for the effect of each exposure. Here, we develop a two-sample conditional F-statistic to test whether the genetic variants strongly predict each exposure conditional on the other exposures included in a MVMR model. We show formally that this test is equivalent to the individual level data conditional F-statistic, indicating that conventional rule-of-thumb critical values of F> 10, can be used to test for weak instruments. We then demonstrate how reliable estimates of the causal effect of each exposure on the outcome can be obtained in the presence of weak instruments and pleiotropy, by repurposing a commonly used heterogeneity Q-statistic as an estimating equation. Furthermore, the minimized value of this Q-statistic yields an exact test for heterogeneity due to pleiotropy. We illustrate our methods with an application to estimate the causal effect of blood lipid fractions on age-related macular degeneration.

Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization

Multivariable Mendelian randomization (MVMR) is a form of instrumental variable analysis which estimates the direct effect of multiple exposures on an outcome using genetic variants as instruments. Mendelian randomization and MVMR are frequently conducted using two-sample summary data where the association of the genetic variants with the exposures and outcome are obtained from separate samples. If the genetic variants are only weakly associated with the exposures either individually or conditionally, given the other exposures in the model, then standard inverse variance weighting will yield biased estimates for the effect of each exposure. Here, we develop a two-sample conditional F-statistic to test whether the genetic variants strongly predict each exposure conditional on the other exposures included in a MVMR model. We show formally that this test is equivalent to the individual level data conditional F-statistic, indicating that conventional rule-of-thumb critical values of F > 10, can be used to test for weak instruments. We then demonstrate how reliable estimates of the causal effect of each exposure on the outcome can be obtained in the presence of weak instruments and pleiotropy, by repurposing a commonly used heterogeneity Q-statistic as an estimating equation. Furthermore, the minimized value of this Q-statistic yields an exact test for heterogeneity due to pleiotropy. We illustrate our methods with an application to estimate the causal effect of blood lipid fractions on age-related macular degeneration.

Instrumental Heterogeneity in Sex-Specific Two-Sample Mendelian Randomization: Empirical Results From the Relationship Between Anthropometric Traits and Breast/Prostate Cancer

Background

In two-sample Mendelian randomization (MR) studies, sex instrumental heterogeneity is an important problem needed to address carefully, which however is often overlooked and may lead to misleading causal inference.

Methods

We first employed cross-trait linkage disequilibrium score regression (LDSC), Pearson's correlation analysis, and the Cochran's Q test to examine sex genetic similarity and heterogeneity in instrumental variables (IVs) of exposures. Simulation was further performed to explore the influence of sex instrumental heterogeneity on causal effect estimation in sex-specific two-sample MR analyses. Furthermore, we chose breast/prostate cancer as outcome and four anthropometric traits as exposures as an illustrative example to illustrate the importance of taking sex heterogeneity of instruments into account in MR studies.

Results

The simulation definitively demonstrated that sex-combined IVs can lead to biased causal effect estimates in sex-specific two-sample MR studies. In our real applications, both LDSC and Pearson's correlation analyses showed high genetic correlation between sex-combined and sex-specific IVs of the four anthropometric traits, while nearly all the correlation coefficients were larger than zero but less than one. The Cochran's Q test also displayed sex heterogeneity for some instruments. When applying sex-specific instruments, significant discrepancies in the magnitude of estimated causal effects were detected for body mass index (BMI) on breast cancer (P = 1.63E-6), for hip circumference (HIP) on breast cancer (P = 1.25E-20), and for waist circumference (WC) on prostate cancer (P = 0.007) compared with those generated with sex-combined instruments.

Conclusion

Our study reveals that the sex instrumental heterogeneity has non-ignorable impact on sex-specific two-sample MR studies and the causal effects of anthropometric traits on breast/prostate cancer would be biased if sex-combined IVs are incorrectly employed.

The use of two-sample methods for Mendelian randomization analyses on single large datasets

BACKGROUND

With genome-wide association data for many exposures and outcomes now available from large biobanks, one-sample Mendelian randomization (MR) is increasingly used to investigate causal relationships. Many robust MR methods are available to address pleiotropy, but these assume independence between the gene-exposure and gene-outcome association estimates. Unlike in two-sample MR, in one-sample MR the two estimates are obtained from the same individuals, and the assumption of independence does not hold in the presence of confounding.

METHODS

With simulations mimicking a typical study in UK Biobank, we assessed the performance, in terms of bias and precision of the MR estimate, of the fixed-effect and (multiplicative) random-effects meta-analysis method, weighted median estimator, weighted mode estimator and MR-Egger regression, used in both one-sample and two-sample data. We considered scenarios differing by the: presence/absence of a true causal effect; amount of confounding; and presence and type of pleiotropy (none, balanced or directional).

RESULTS

Even in the presence of substantial correlation due to confounding, all two-sample methods used in one-sample MR performed similarly to when used in two-sample MR, except for MR-Egger which resulted in bias reflecting direction and magnitude of the confounding. Such bias was much reduced in the presence of very high variability in instrument strength across variants (IGX2 of 97%).

CONCLUSIONS

Two-sample MR methods can be safely used for one-sample MR performed within large biobanks, expect for MR-Egger. MR-Egger is not recommended for one-sample MR unless the correlation between the gene-exposure and gene-outcome estimates due to confounding can be kept low, or the variability in instrument strength is very high.

Mendelian randomization study of telomere length and bone mineral density

Purpose: Some epidemiological studies and animal studies have reported a relationship between leukocyte telomere length (LTL) and bone mineral density (BMD). However, the causality underlying the purported relationship has not been determined. Here we performed a two-sample MR analysis to test the causal link between telomere length and BMD.

Results: Our research suggested no causal link of LTL and BMD using IVW method. The weighted median, MR-Egger regression and MR.RAPS method yielded a similar pattern of effects. MR-Egger intercept test demonstrated our results were not influenced by pleiotropy. Heterogeneities among the genetic variants on heel estimated BMD and TB-BMD vanished after excluding rs6028466. “Leave-one-out” sensitivity analysis confirmed the stability of our results.

Conclusion: Our MR analysis did not support causal effect of telomere length on BMD.

Methods: We utilized 5 independent SNPs robustly associated with LTL as instrument variables. The outcome results were obtained from GWAS summary data of BMD. The two-sample MR analysis was conducted using IVW, weighted median, MR-Egger regression and MR.RAPS method. MR-Egger intercept test, Cochran’s Q test and I² statistics and “leave-one-out” sensitivity analysis were performed to evaluate the horizontal pleiotropy, heterogeneities and stability of these genetic variants on BMD.

AlzRiskMR database: an online database for the impact of exposure factors on Alzheimer's disease

In view of great difficulties in the pathogenesis analysis of Alzheimer's disease (AD) presently, profiling the modifiable risk factors is crucial for early detection and intervention of AD. However, the causal associations among them have yet to be identified, and the effective integration and application of these data also remain considerable challenges due to the lack of efficient collection and analysis procedures. To address this issue, we performed comprehensive analyses by two-sample Mendelian randomization (2SMR) and established the AlzRiskMR database (https://github.com/SDBMC/RiskFactors2AD). Four 2SMR analysis methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode, were used for the complementary calculation to test the reliability of the results. The database currently comprises 1870 sets of data of Genome-Wide Association Studies (GWAS) from the MR-Base and NHGRI-EBI GWAS Catalog database. AlzRiskMR database not only estimates causal associations between modifiable risk factors and AD but also offers a useful and timely resource for early intervention of AD development incidence.

An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings

BACKGROUND

Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilizing genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome.

METHODS AND RESULTS

We use simulations and theory to clarify the interpretation of estimated effects in a MVMR analysis under a range of underlying scenarios, where a secondary exposure acts variously as a confounder, a mediator, a pleiotropic pathway and a collider. We then describe how instrument strength and validity can be assessed for an MVMR analysis in the single-sample setting, and develop tests to assess these assumptions in the popular two-sample summary data setting. We illustrate our methods using data from UK Biobank to estimate the effect of education and cognitive ability on body mass index.

CONCLUSION

MVMR analysis consistently estimates the direct causal effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual- or summary-level data.