Two-sample Mendelian Randomization Research Articles

Investigating the causal association between serum uric acid levels and gastric cancer risk: a Mendelian randomization study

The causal link between serum uric acid (SUA) levels and gastric cancer susceptibility remains inadequately elucidated. This investigation employed a two-sample Mendelian randomization (MR) framework to assess the potential causative link between SUA concentrations and the propensity for developing gastric cancer. To further explore potential racial differences, this MR analysis was conducted on cohorts of both European and East Asian descent. Data from a large-scale GWAS in 343,836 Europeans and 92,615 East Asians were screened for 206 and 45 SNPs significantly linked to SUA levels, respectively, as genetic variants. Subsequently, four distinct MR methodologies were deployed to determine how SUA levels affected gastric cancer risk. Using the fixed-effects IVW approach, our analysis revealed no significant association between SUA levels and gastric cancer risk, with P-values exceeding the threshold of significance in both populations (European P = 0.778; East Asian P = 0.245). The findings were supported by three additional MR methods. The reliability of these results was substantiated by comprehensive sensitivity analyses. In summary, our data do not support a significant causal linkage between SUA levels and gastric cancer risk.

Genetical effects of sleep traits on postpartum depression: a bidirectional two-sample Mendelian randomization study

BackgroundPostpartum depression (PPD) is widely recognized as the most prevalent mental health crisis following childbirth and has been linked to sleep disturbances. However, the potential causal relationships between various sleep traits and PPD remain unclear. This study employs a bidirectional two-sample Mendelian randomization (MR) approach to investigate these associations.MethodsThe inverse-variance-weighted method was used to evaluate the causally linked sleep traits on postpartum depression. The weighted median, weighted mode, and MR-Egger were used to estimate the robustness of the inverse-variance-weighted method. The leave-one-out method estimated the sensitivity of the result. Cochran’s Q method was used for the heterogeneous test. The MR-Egger intercept and MR-PRESSO methods detected the horizontal pleiotropy.ResultsWe examined the genetic causal relationships between nine sleep traits and postpartum depression. Sleep apnea syndrome (OR: 1.122; 95%CI: 1.063–1.185; p = 0.000), sleeplessness/insomnia (OR: 1.465; 95%CI: 1.104–1.943; p = 0.008), and frequency of tiredness/lethargy in last 2 weeks (OR: 1.725; 95%CI: 1.345–2.213; p = 0.000) genetically predicted the increased risk of postpartum depression. The reverse Mendelian randomization analysis showed PPD caused sleeplessness/insomnia (β: 0.006; 95%CI: 0.001–0.010; p = 0.016) and frequency of tiredness/lethargy in last 2 weeks (β: 0.007; 95%CI: 0.002–0.011; p = 0.004). The remaining six sleep traits showed no significant association with PPD. There was no heterogeneity or horizontal pleiotropy.ConclusionsGenetic evidence reveals causal relationships between specific sleep traits and PPD, including sleep apnea syndrome, sleeplessness/insomnia, and tiredness. Whether certain sleep health indicators suggest a risk of postpartum depression or sleep issues that are caused by PPD, both may offer insights into the prevention and treatment of PPD.

The causal relationship between trace element status and upper gastrointestinal ulcers: a Mendelian randomization study.

This study aimed to investigate the bidirectional causal relationships between trace elements (such as zinc, magnesium, phosphate, and folate) and upper gastrointestinal ulcers (including gastric and duodenal ulcers). We utilized a two-sample Mendelian randomization (MR) analysis to achieve this. We conducted a two-sample MR analysis using summary-level data from genome-wide association studies (GWAS) obtained from public genomics repositories. We utilized a range of MR methods, including inverse-variance weighted (IVW), MR-Egger, and weighted median methods, and conducted a meta-analysis to synthesize results across different datasets. To ensure the robustness of our findings, we performed extensive sensitivity analyses, including pleiotropy assessment, heterogeneity tests, and leave-one-out analysis. Our findings are significant, indicating a positive causal relationship between increased zinc levels and the risk of gastric ulcers. Moreover, magnesium and folate appear to offer potential protective effects against gastroduodenal ulcers (p < 0.05). The meta-analysis further supports the causal relationship between zinc and gastric ulcers (p < 0.05), confirming zinc's significant causal impact on this condition. The study confirms a positive causal relationship between zinc and gastric ulcers and highlights the complexity of how trace elements regulate the progression of upper gastrointestinal ulcers. These results provide a scientific basis for dietary recommendations regarding trace element intake in clinical and public health practices. They also offer new insights into effective prevention and treatment strategies for gastric and duodenal ulcers.

Causal relationship between sarcopenia and rotator cuff tears: a Mendelian randomization study.

Sarcopenia and rotator cuff tears are common among elderly patients. However, the role of sarcopenia in the management of rotator cuff tears has been often overlooked. This study aimed to elucidate the effects of sarcopenia-related traits on rotator cuff tears. Two-sample Mendelian randomization (MR) analyses based on genome-wide association study data were used to evaluate the causal relationships among appendicular lean mass (ALM), usual walking pace, low hand grip strength, and rotator cuff tears. Multivariate Mendelian randomization (MVMR) analyses were used to evaluate the direct effects of each muscle trait on the causal relationship. Univariate MR analysis showed that ALM and usual walking pace were causally related to rotator cuff tears (odds ratio (OR) = 0.895; 95% confidence interval (CI), 0.758-0.966, P<0.001 and OR = 0.458, 95% CI, 0.276-0.762, P = 0.003, respectively), and there was no evidence of causality between low hand grip strength and rotator cuff tears (OR = 1.132, 95% CI, 0.913-1.404, P = 0.26). MVMR analysis confirmed the causal effects of ALM and walking pace on rotator cuff tears (OR = 0.918, 95% CI, 0.851-0.990, P = 0.03 and OR = 0.476, 95% CI, 0.304-0.746, P = 0.001, respectively). A causal genetic relationship exists between sarcopenia and rotator cuff tears. Sarcopenia-related traits including low muscle mass and physical function, increase the risk of rotator cuff tears. These findings provide new clinical insights and evidence-based medicine to optimize management of rotator cuff tears.

No genetic causality between appendectomy and gastrointestinal cancers: a Mendelian randomization study and meta-analysis in European population

The impact of appendectomy on the risk of gastrointestinal cancers remains unknown. We aimed to systematically estimate the causal relationship between appendectomy and gastrointestinal cancers in the European population using two-sample Mendelian randomization (TSMR) study methods and meta-analysis. As part of the discovery cohort analysis, we identified independent genetic variants strongly associated with appendectomy from the UK Biobank (50,105 cases) to serve as instrumental variables (IVs). Summary-level data for gastrointestinal cancers were obtained from the FinnGen study. As the replication cohort, IVs associated with appendectomy were extracted in the FinnGen study (28,601 cases). The data for gastrointestinal cancers were obtained from the UK Biobank. Finally, meta-analyses were conducted to evaluate the combined causal effects of the MR results. We found no causal relationship between appendectomy and gastrointestinal cancers in both the discovery and replication cohorts. Finally, the meta-analysis revealed no causal association between appendectomy and gastrointestinal cancers. Our findings suggest no causal relationship exists between appendectomy and gastrointestinal cancers in the European population. This genetic evidence supports the conclusion from other observational studies that appendectomy does not affect the risk of gastrointestinal cancers in the European population.

Exploring genetic links between blood metabolites and gout susceptibility.

Gout, a prevalent form of inflammatory arthritis, has a complex etiology where the causal relationship between metabolites and the disease remains underexplored. This study aims to elucidate the impact of genetically determined blood metabolites on gout. Employing a two-sample bidirectional Mendelian randomization analysis, we examined the association between 1400 blood metabolites and gout. Causal associations were determined using the inverse variance weighted (IVW) method with false discovery rate (FDR) correction. Sensitivity analyses encompassed weighted models, MR-Egger, weighted median, and MR-PRESSO approaches. MR-pleiotropy and Cochran's Q statistic were utilized to evaluate potential heterogeneity and pleiotropy. Additionally, metabolic pathway analyses were conducted to pinpoint relevant pathways. Of the initial 4 serum metabolites identified, 3 known metabolites-hexanoylglutamine levels, mannose content, and the phosphate to mannose ratio-were found to be causally associated with gout, along with 55 serum metabolites identified as potential predictors of gout (PIVW < 0.05). Furthermore, we discovered 3 metabolic pathways implicated in gouty attacks. Our findings, derived from Mendelian randomization, indicate that the identified metabolites and pathways may serve as biomarkers for clinical screening and prevention of gout. Additionally, they offer novel insights into the mechanisms of the disease and potential drug targets. Key points • Conducted a comprehensive Mendelian randomization study involving 1400 blood metabolites to explore their genetic impact on gout development and progression • Identified three key metabolites-hexanoylglutamine, mannose, and the phosphate-to-mannose ratio-with causal associations to gout, highlighting their potential use as biomarkers for early detection and risk stratification • Discovered 55 additional serum metabolites as potential predictors of gout, offering new insights into the pathophysiology of the disease and identifying high-risk individuals • Revealed three novel metabolic pathways involved in gout attacks, providing new therapeutic targets for precision medicine in gout treatment.

Association of lipid levels, adipokines and multiple myeloma: a two-sample multivariate Mendelian randomization study

Many observational studies and experiments have found a strong association between lipid levels and adipokines and multiple myeloma (MM), but the causal relationship between lipid levels, adipokines and MM remains to be determined. We performed a two-sample and multivariate MR analysis to investigate the causal relationship between lipid levels, adipokines and MM. Total cholesterol(TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) were used to represent lipid levels, and adiponectin, leptin, and resistin were used to represent adipokines. Genetic data for each index and MM were obtained from the Integrated Epidemiology Unit (IEU) Genome-Wide Association Study (GWAS) database, and two-sample MR analyses were performed, as well as multivariate MR analyses of adipokines for causality of MM using BMI as an adjusting factor. In the analyzed results, no significant causal association was found between adipokines, lipid levels and multiple myeloma, and after adjusting for BMI, an association between adipokines and MM was still not found. The results of this MR study do not support an association between genetically predicted adipokines, lipid levels, and risk of MM, but we cannot rule out the existence of a weak association. The mechanisms need to be further investigated.

Association between venous thromboembolism and atrial fibrillation: a Mendelian randomization study

BackgroundAlthough previous observational studies have shown an association between venous thromboembolism (VTE) and atrial fibrillation (AF), the underlying causal relationship between them remains uncertain.Methods and resultsThis two-sample bidirectional Mendelian randomization (MR) analysis was performed to investigate the causal relationship between VTE and AF. The VTE dataset were obtained from FinnGen, including 9,176 cases and 209,616 controls. Meanwhile a genome-wide association study (GWAS) of 60,620 individuals with AF and 970,216 control subjects identified genetic variations associated with AF. The principal MR analytic approach used in this study is the inverse-variance weighting (IVW) method. Furthermore, we performed complementary MR analyses, including the MR-Egger, Weighted median (WM), and Weighted Mode. MR pleiotropy residual sum was applied to identify pleiotropy. The MR analysis showed suggestive causal associations between VTE and the risk of AF (p = 0.0245, OR [95%CI]: 1.027 [1.003, 1.051]). The reverse MR analysis found that genetic susceptibility to AF was not significantly associated with VTE, as determined by the IVW method (p = 0.7773). The robustness of these findings was corroborated through MR sensitivity analyses.ConclusionsThere is a unidirectional causal relationship between VTE and AF, meaning that VTE is a causal risk factor for AF, whereas no effect of AF on VTE was identified.

Causal role of immune cells in muscle atrophy: mendelian randomization study

Immune system and inflammation had a great influence on the progression of muscle atrophy. However, the causal relationship with specific immune cell traits remained uncertain. The aim of this study was to elucidate the genetic influences on these associations, providing insights into the underlying mechanisms of muscle atrophy. A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between immune cell phenotypes and muscle atrophy. Data on immune cell phenotypes were obtained from a research cohort containing data on 731 immune cell phenotypes and data on muscle atrophy were sourced from a Finnish database. MR analysis was performed using the MR-Egger method, weighted median, inverse variance weighting, heterogeneity testing, sensitivity analysis, and multiplicity analysis, with results subjected to false discovery rate(FDR) correction. Additionally, the UK Biobank cohort was utilized as an external validation. A total of 31 immune phenotypes with causal relationships with muscle atrophy were identified, including various phenotypes of conventional dendritic cells, myeloid cells, T cells/B cells/natural killer cells, regulatory cells, and T cell maturation stages. Among them, 12 immune phenotypes were identified as exhibiting a positive causal relationship with muscle atrophy, while 19 immune phenotypes were demonstrated to have a negative causal association, highlighting the complex interactions between immune cells and muscle health. The results of the reverse MR analysis indicated that a negative correlation between muscle atrophy and CD28 on secreting Treg (OR = 0.9038, 95%CI:0.8308 ~ 0.9832, P = 0.0186). A significant positive correlation was revealed by external datasets between the CD25 on IgD + CD38- immune phenotype and the risk of muscle atrophy, which was consistent with the trend observed in the training group (OR = 1.1041, 95% CI: 1.1005–1.1076, P = 0.0263). No evidence of pleiotropy was observed, and the reliability of these findings was demonstrated by the leave-one-out analysis. The findings highlight significant correlations between certain immune cell features and muscle atrophy, providing potential targets for further investigation of immunological mechanisms and therapeutic interventions for this condition.

Exploring potential therapeutic targets for asthma: a proteome-wide Mendelian randomization analysis

BackgroundAsthma poses a significant global health challenge, characterized by high rates of morbidity and mortality. Despite available treatments, many severe asthma patients remain poorly managed, highlighting the need for novel therapeutic strategies. This study aims to identify potential drug targets for asthma by examining the influence of circulating plasma proteins on asthma risk.MethodsThis study employs summary-data-based Mendelian randomization (MR) and two-sample MR methods to investigate the association between 2940 plasma proteins from the UK Biobank study and asthma. The analysis includes discovery (FinnGen cohort) and replication (GERA cohort) phases, with Bayesian colocalization used to validate the relationships between proteins and asthma. Furthermore, protein–protein interaction and druggability assessments were conducted on high-evidence strength protein biomarkers, and candidate drug prediction and molecular docking were performed for proteins without targeted drugs. Given the complexity of asthma pathogenesis, the study also explores the relationships between plasma proteins and asthma-related endpoints (e.g., obesity-related asthma, infection-related asthma, childhood asthma) to identify potential therapeutic targets for different subtypes.ResultsIn the discovery cohort, 75 plasma proteins were associated with asthma, including IL1RAP, IL1RL1, IL6, CXCL5, and CXCL8. Additionally, 6 proteins (IL4R, LTB, CASP8, MAX, PCDH12, and SCLY) were validated through co-localization analysis and validation cohort. The assessment of drug targetability revealed potential drug targets for IL4R, CASP8, and SCLY, while candidate drugs were predicted for LTB and MAX proteins. MAX exhibited strong binding affinity with multiple small molecules indicating a highly stable interaction and significant druggability potential. Analysis of the 75 proteins with 9 asthma-related endpoints highlighted promising targets such as DOK2, ITGAM, CA1, BTN2A1, and GZMB.ConclusionThese findings elucidate the link between asthma, its related endpoints, and plasma proteins, advancing our understanding of molecular pathogenesis and treatment strategies. The discovery of potential therapeutic targets offers new insights into asthma drug target research.

Association between asthma and depression: results from the NHANES 2005-2018 and Mendelian randomization analysis.

Asthma is a common respiratory disease that is believed to be associated with mental disorders. This study aims to assess the correlation and causal relationship between asthma and depression by combining observational and Mendelian randomization (MR) approaches. We collected relevant data from the National Health and Nutrition Examination Survey (NHANES) and employed multivariable logistic regression to evaluate the correlation between asthma and depression. Additionally, a two-sample MR analysis was conducted using inverse variance-weighted (IVW) method, along with multiple sensitivity analyses. The observational study included a total of 23 648 participants, and the results showed that asthma patients had an increased risk of developing depression compared to non-asthma individuals (OR 1.26; 95% CI 1.04-1.57; P < 0.01). The IVW-MR results from two datasets indicated a potential causal relationship between asthma and depression (EBI dataset: OR 1.141; 95% CI 1.051-1.239; P = 0.01; UKB dataset: OR 1.009; 95% CI 1.005-1.013; P < 0.01). These findings suggest that asthma may be a risk factor for the onset of depression, increasing the risk of developing depression. There is a significant correlation and potential causal relationship between asthma and depression, with asthma being a risk factor for the onset of depression. These findings warrant further research for validation and exploration of preventive and therapeutic measures for depression in asthma patients. Key messages What is already known on this topic-There are some potential associations between asthma and depression based on observational studies, but the results of observational studies are often biased. This study aims to further explore the relationship between asthma and depression through a combination of observational studies and Mendelian randomization (MR) analysis. What this study adds-The observational study results from the National Health and Nutrition Examination Survey database and MR analysis are consistent, indicating that after adjusting for multiple covariates and confounding factors, asthma increases the risk of depression and is a risk factor for depression, with similar results obtained at the genetic level. How this study might affect research, practice or policy-Asthma patients not only need active medication treatment, but also need timely psychological attention, and psychological treatment is more important to a certain extent.

Genetically predicted plasma metabolites mediate the causal relationship between gut microbiota and primary immune thrombocytopenia (ITP).

Primary immune thrombocytopenia (ITP) is an immune-mediated hematologic disorder characterized by a reduction in platelet count, increasing the risk of bleeding. Recent studies have indicated a close association between alterations in gut microbiota and the development of ITP. However, the mechanisms by which gut microbiota influence the occurrence and progression of ITP through plasma metabolites remain poorly understood. Evidence suggests extensive interactions between gut microbiota and plasma metabolites, implying a potential role for gut microbiota in influencing ITP through alterations in plasma metabolites, which requires further investigation. In this study, summarized GWAS data (including 211 gut microbiota taxa, 1,400 plasma metabolites or ratios, and an ITP patient cohort) were retrieved from the MiBioGen and GWAS Catalog databases. Using a two-sample Mendelian randomization (MR) approach, we screened gut microbiota and plasma metabolites potentially causally related to ITP. We further identified plasma metabolites serving as mediators through which gut microbiota affect ITP and calculated the strength of the mediation effect. To ensure result stability, we primarily used the inverse variance weighted (IVW) method as the main judgment index. We also utilized MR Egger and inverse variance weighted methods to detect heterogeneity in the results, and employed MR-Egger and MR-PRESSO methods to assess the presence of pleiotropy. Though two-sample MR analysis, 8 gut microbiota taxa were found to have causal relationships with ITP. After excluding six plasma metabolites with pleiotropy, 39 plasma metabolites were found to be causally related to ITP (P < 0.05). Eleven plasma metabolites were identified as having causal relationships between gut microbiota and plasma metabolites. Finally, using the delta method, it was calculated that Sphingomyelin levels (8.0%, 95%CI: 0.9% to 11.5%, P = 0.047) and Glucose-to-mannose ratio (6.5%, 95%CI: 0.7% to 9.5%, P = 0.039) are intermediates for Intestinimonas influencing ITP, while Bilirubin (Z,Z) to etiocholanolone glucuronide ratio (5.6%, 95%CI: 4.7% to 6.9%, P = 0.043) is an intermediate for Senegalimassilia influencing ITP. Gut microbiota can influence the development of ITP through changes in plasma metabolites. Sphingomyelin levels, Glucose-to-mannose ratio, and Bilirubin (Z,Z) to etiocholanolone glucuronide ratio are newly discovered intermediates through which gut microbiota influence ITP, providing potential indicators and targets for clinical diagnosis and treatment. This study highlights the intricate relationship between gut microbiota and plasma metabolites in the context of ITP, suggesting new avenues for clinical diagnosis and treatment.

Type 2 diabetes prevention: genetic association analysis of dried fruit intake and disease risk.

Prior research has suggested an inverse correlation between dried fruit intake and type 2 diabetes mellitus (T2DM), yet the causal link remains uncertain. This study seeks to investigate the potential causal impact of dried fruit intake on T2DM, covering cases both with and without various complications, as well as glycaemic traits, using a two-sample Mendelian randomisation (MR) approach. Using MR analysis with genome-wide association study summary statistics, the primary analysis investigated the causal relationship between dried fruit intake and T2DM, both with and without complications, as well as glycaemic traits, employing the inverse variance weighted method. Supplementary analyses were conducted using MR-Egger and the weighted median method. Heterogeneity and intercept tests were utilised to evaluate the robustness of the study outcomes. The results show a significant association between dried fruit intake and T2DM without complications, as well as fasting insulin. Sensitivity analyses confirmed the robustness of the results and the independence from multicollinearity. However, no association was found between dried fruit intake and T2DM with various complications or other glycaemic traits. The significant association between dried fruit intake and T2DM without complications and fasting insulin persisted even after adjusting for BMI. This study offers genetic evidence endorsing the protective effects of dried fruit intake against T2DM, specifically for cases without complications, and in regulating fasting insulin. These findings suggest that dried fruit intake might serve as a primary preventive strategy for T2DM.

Mediating pathways between attention deficit hyperactivity disorder and type 2 diabetes mellitus: evidence from a two-step and multivariable Mendelian randomization study.

Type 2 diabetes (T2D) is a global health burden, more prevalent among individuals with attention deficit hyperactivity disorder (ADHD) compared to the general population. To extend the knowledge base on how ADHD links to T2D, this study aimed to estimate causal effects of ADHD on T2D and to explore mediating pathways. We applied a two-step, two-sample Mendelian randomization (MR) design, using single nucleotide polymorphisms to genetically predict ADHD and a range of potential mediators. First, a wide range of univariable MR methods was used to investigate associations between genetically predicted ADHD and T2D, and between ADHD and the purported mediators: body mass index (BMI), childhood obesity, childhood BMI, sedentary behaviour (daily hours of TV watching), blood pressure (systolic blood pressure, diastolic blood pressure), C-reactive protein and educational attainment (EA). A mixture-of-experts method was then applied to select the MR method most likely to return a reliable estimate. We used estimates derived from multivariable MR to estimate indirect effects of ADHD on T2D through mediators. Genetically predicted ADHD liability associated with 10% higher odds of T2D (OR: 1.10; 95% CI: 1.02, 1.18). From nine purported mediators studied, three showed significant individual mediation effects: EA (39.44% mediation; 95% CI: 29.00%, 49.73%), BMI (44.23% mediation; 95% CI: 34.34%, 52.03%) and TV watching (44.10% mediation; 95% CI: 30.76%, 57.80%). The combination of BMI and EA explained the largest mediating effect (53.31%, 95% CI: -1.99%, 110.38%) of the ADHD-T2D association. These findings suggest a potentially causal, positive relationship between ADHD liability and T2D, with mediation through higher BMI, more TV watching and lower EA. Intervention on these factors may thus have beneficial effects on T2D risk in individuals with ADHD.

Type 2 diabetes mediating the increased cardiovascular risk in patients with rheumatoid arthritis: a bidirectional mendelian randomisation approach

Abstract Background Patients with rheumatoid arthritis (RA) are at increased risk of developing coronary artery disease (CAD) as is evident from epidemiological studies. This however is not a causative association, as we have shown by two-sample mendelian randomisation (MR) in previous work. Mediators linking RA to cardiovascular phenotypes have yet to be identified. Purpose The present study seeks to determine whether type 2 diabetes (DM II) is such a mediator conferring the increased cardiovascular risk of patients with RA. Methods The associations between the phenotypes RA, CAD and DM II were tested for causality with two-sample MR using genetic instruments from genome-wide association studies (GWAS) in largely non-overlapping cohorts. For RA, genetic instruments were obtained from 14,361 cases and 43,923 controls of European ancestry in the dataset by Okada, comprised of 18 studies (1). For the trait DM II, the DIAbetes Genetics Replication and Meta-analysis (DIAGRAM) Consortium was used (2). This GWAS covered 120,000 SNPs from the Metabochip array in mixed European and Pakistani Population (34,840 cases and 114,981 controls). Genetic instruments for CAD were obtained from the CARDIoGRAMplusC4D consortium with 60,801 cases and 123,504 controls from 48 studies (3). Several MR regression methods such as MR Egger regression and inverse-variance weighted meta-analysis and sensitivity tests for pleiotropy and heterogeneity were performed for each exposure-outcome pair. Results Genetic predisposition to RA was not significantly associated with higher risk of CAD (OR = 1,02 [0,99-1,05]), see figure. In contrast, DM II was significantly, albeit weakly related as outcome to genetically determined manifestation of RA as exposure (OR = 1,04 [1,01-1,08]) and, conversely, genetic instruments of DM II conferred an increased risk of developing CAD ((OR = 1,11 [1,05-1,17]). Conclusions Despite the high prevalence of CAD among RA patients in observational studies, cardiovascular outcomes are not casually linked with RA. Instead, DM II could serve as a mediator, based on its significant associations with both RA and CAD in two-sample MR.

Serum circulating liver enzymes and human diseases

Abstract Background This study aimed to comprehensively investigate the observational and Mendelian randomization (MR) associations between liver enzymes (ALP, ALT, AST and GGT) with a wide spectrum of human diseases. Methods UK Biobank data was used for observational analysis. Cox proportional hazard models were used to quantify the observational associations between liver enzymes and risks of 1109 diseases, adjusted for covariates. A correction was applied to allow for multiple comparisons. Two-sample MR was performed to replicate the identified observational associations. We assessed the strength, consistency and pleiotropy of these MR associations. Results In 438571 participants with a median 12.4 years of follow-up, we found evidence linking liver enzymes and 654 diseases, 254 of which were further assessed in subsequent MR. In MR, 52 associations were replicated (10 for ALP, 14 for ALT, 10 for AST and 18 for GGT). Specifically, ALT was associated with liver conditions, diabetes, abnormal bleeding from the female genital tract, and prostate cancer. AST showed associations with prostate cancer, anxiety, diabetic neuropathy, and stroke. GGT was linked to hepatic and biliary conditions, coronary atherosclerosis, and pneumonia, while ALP displayed positive associations with vitamin D-calcium-parathyroid-bone conditions. Conclusions Elevated liver enzymes are risk factors for a wide range of hepatic and extrahepatic diseases, predominantly digestive, circulatory, metabolic/endocrine (including diabetes) diseases. Furthermore, the four liver enzymes demonstrated distinct patterns of disease associations. Key messages • Elevated liver enzymes are risk factors for a wide range of hepatic and extrahepatic diseases. • The four liver enzymes demonstrated distinct patterns of disease associations.

Relationship between Guillain-Barré syndrome and Cardiovascular disease: A bidirectional Mendelian randomization study.

Guillain-Barré syndrome (GBS) and cardiovascular diseases (CVDs) have been observed to have a potential association, with GBS potentially leading to cardiovascular complications. However, these observational studies may be influenced by confounding factors. This study aimed to assess the causal relationship between GBS and CVDs, including heart failure (HF), atrial fibrillation (AF), and coronary artery disease (CAD), using a two-sample bidirectional Mendelian randomization (MR) analysis. Datasets for GBS and CVDs were retrieved from the United Kingdom Biobank and analyzed using selected instrumental variables (IVs) related to genetic variations. Sensitivity tests, including heterogeneity and horizontal pleiotropy tests, were conducted to ensure the reliability of the selected IVs. The analysis results were then visualized to illustrate the causal relationships. The study identified genetic variants as IVs for both GBS and CVDs. MR analysis revealed a significant causal effect of GBS on the increased risk of HF (Inverse variance weighted [IVW], p<0.05), but no significant causal relationship was found between GBS and AF or CAD. Similarly, no causal effect of CVDs on the occurrence of GBS was observed. Sensitivity analyses indicated no significant heterogeneity or horizontal pleiotropy, supporting the robustness of the results. This bidirectional MR analysis suggests a causal relationship between GBS and an increased risk of HF but not with AF or CAD, nor was a reverse causal effect of CVDs on GBS observed. These findings underscore the importance of considering cardiovascular complications, particularly HF, in the clinical management of patients with GBS in European populations.

Proteogenomic analysis in population biobanks identifies new therapeutic targets across heart failure subtypes

Abstract Background Heart failure (HF) represents a multifactorial clinical syndrome with differential response to existing therapies across its subtypes. Proteogenomic analysis of genetic variants associated with changes in circulating protein level and risk of heart failure subtypes provides an opportunity for a systematic identification of proteins with subtype-specific causal effects as novel therapeutic targets. Purpose To identify proteins as potential therapeutic targets for specific heart failure subtypes by leveraging proteomics and genomics data in population biobanks. Methods We evaluated the causal effects of 2,773 proteins on 5 HF-related outcomes, including overall HF, non-ischaemic HF (ni-HF), ni-HF with reduced / preserved ejection fraction (ni-HFrEF / ni-HFpEF), and dilated cardiomyopathy (DCM). For each protein-phenotype pair, we performed a two-sample Mendelian randomisation (MR) analysis using protein-specific genetic association estimates derived from protein quantitative trait locus (pQTL) studies in 114,145 individuals from deCODE, UK Biobank, Fenland study, and SCALLOP consortium and genome-wide association studies (GWAS) of HF outcomes in 145,795 individuals by HERMES Consortium. We further prioritised candidate protein targets based on replication of results across datasets, model parameters, assays, and colocalization of causal genetic variants. Finally, we profiled the causal effects of identified proteins on 32 related cardiac traits and risk factors to explore potential mechanisms of actions and on-target side effects. Results We identified 493 proteins associated with at least one HF outcome at a false discovery rate (FDR) &amp;lt; 1% in the primary MR analysis. We further prioritised 44 proteins with concordant effect direction across datasets, model parameters, and assays or colocalization in at least one dataset. All 44 identified proteins showed cross association with at least one of 35 tested traits other than HF or cardiomyopathies at FDR &amp;lt;1%, including coronary artery disease (18 proteins), body mass index (11 proteins), type 2 diabetes (6 proteins), systolic / diastolic blood pressure (13 proteins), and chronic kidney disease (9 proteins). Conclusion We characterised the causal associations of 2,773 circulating proteins across HF-related outcomes and prioritised 44 proteins by integrating proteomics and genomics data in population biobanks. These findings extend our understanding of the molecular mechanism underlying different forms of HF and may inform the development of new therapeutic strategies.Study design

Causal association between visceral fat and coronary artery disease: a large-scale mendelian randomization analysis

Abstract Background While increased body mass index (BMI) is an established risk factor, the residual risk associated with visceral fat, remains a concern. We aimed to perform a Mendelian randomization to explore the causal relationship between visceral fat and the risk of coronary artery disease (CAD), aiming to address gaps left by observational studies that may be influenced by confounding factors and reverse causation. Methods Leveraging large-scale genome-wide association study (GWAS) databases, we identified single-nucleotide polymorphisms (SNPs) associated with visceral fat. These genetic instruments were analyzed to infer causal relationships with CAD outcomes, drawing data from the CARDIoGRAMplusC4D consortium for CAD, and additional databases for related cardiovascular conditions. We performed a Two-sample Mendelian Randomization (MR) to test the genetic association between the visceral obesity and Coronary Artery Disease (CAD). Results The analysis encompassed data from a combined cohort exceeding 500,000 participants, revealing a significant causal relationship between increased levels of visceral fat and the risk of CAD. The observed odds ratio (OR) for CAD per standard deviation (SD) increase in visceral fat was [OR, 1.48 ] ([95% CI, 1.33-1.64]; P&amp;lt;0.001), indicating a robust association which remains independent from BMI on mediation analysis. Notably, the study's methodology ensured minimal risk of pleiotropy, reinforcing the validity of the findings. Conclusions This Mendelian randomization study provides compelling evidence of a genetic causal link between visceral fat and coronary artery disease. The findings suggest that beyond BMI, visceral fat represents a significant, independent risk factor for CAD, underscoring the importance of considering comprehensive lipid management in cardiovascular risk reduction strategies. Further research is warranted to explore potential mechanisms and therapeutic targets associated with visceral fat in the context of cardiovascular disease.

The influence of remnant cholesterol on ischemic stroke and its subtypes

Abstract Background Established studies have firmly identified elevated low-density lipoprotein (LDL) as a key risk factor for stroke. Nevertheless, an emerging body of evidence suggests that residual stroke risk endures even with rigorous LDL control. Recent investigations propose a potential pivotal role of remnant cholesterol (RC) in this lingering risk. However, the causative relationship between RC and ischemic stroke, encompassing its subtypes, remains elusive. In this study, we employed a two-sample Mendelian Randomization (MR) analysis to delve into the causal association between RC and ischemic stroke, aiming to shed light on its various subtypes. Methods We sourced single nucleotide polymorphism (SNP) data associated with stroke and its subtypes from the MEGASTROKE consortium's comprehensive genome-wide association study (GWAS). SNPs relevant to RC were acquired from the MRC Integrative Epidemiology Unit (IEU) Open GWAS database. Our investigation involved the evaluation of the correlation between RC and ischemic stroke, encompassing 40,585 patients and 406,111 controls. Subtypes considered included large artery atherosclerosis (n=4,373), small artery occlusion (n=5,386), and cardioembolic stroke (n=7,193). A meticulous screening process was implemented to select instrumental variables (IVs) for RC, followed by five Mendelian Randomization (MR) analyses utilizing inverse-variance-weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods. Rigorous sensitivity analyses, along with assessments for heterogeneity and pleiotropy, were conducted to ensure the robustness and credibility of our study results. Results Our investigation unveiled a causal relationship between RC and large artery atherosclerosis-type ischemic stroke (IVW method, OR=1.267, 95% CI: 1.017-1.578, P=0.035). This association was further substantiated through rigorous sensitivity analyses, assessments for heterogeneity, and pleiotropy tests. In contrast, no evidence supported a causal link between RC and overall ischemic stroke (IVW method, OR=1.072, 95% CI: 0.986-1.164, P=0.102), small artery occlusion-type stroke (IVW method, OR=1.127, 95% CI: 0.939-1.353, P=0.198), and cardioembolic stroke (IVW method, OR=1.083, 95% CI: 0.931-1.259, P=0.301). Conclusions Our findings robustly establish a causal connection between elevated levels of RC and the occurrence of large artery strokes. This highlights the potential efficacy of reducing RC as a preventive strategy against large artery atherosclerosis. Nevertheless, it is crucial to note that such mitigation efforts may not necessarily result in a decreased risk associated with small artery occlusion and cardioembolic strokes.