Mendelian Randomization Analysis Research Articles

Brisk walking pace offsets venous thromboembolism risk equivalent to established monogenic mutations.

Mendelian mutations in F2 and F5 genes are known risk factors for venous thromboembolism (VTE). This study aimed to explore the association between walking pace and VTE, compare its risk with Mendelian mutations, and identify if blood biomarkers mediate this effect. We followed 445,261 UK Biobank participants free of VTE at baseline. Walking pace was self-reported, and carrier status for F2 and F5 gene mutations was determined by rs1799963 and rs6025 genotypes. We used a Cox proportional hazard model to estimate walking pace's effect on VTE risk, bidirectional Mendelian randomization (MR) analysis to assess causality, and mediation analysis to explore blood biomarkers. Over a median follow-up of 12.8 years, 11,155 incident VTE cases were identified. The 10-year incidence rates for brisk and slow walking paces were 1.32% and 3.90%, respectively. For F5 carriers, the rates were 1.70% (brisk pace) and 3.62% (slow pace). Brisk walking pace reduced VTE risk in F5 carriers (2.65%) compared to non-carriers with a slow pace (3.66%). MR analysis confirmed a causal relationship from walking pace to VTE risk. Mediation analysis revealed that serum albumin and cystatin C mediated 8.7% to 11.7% of the effect of brisk walking pace on VTE risk. A slow walking pace is causally associated with increased VTE risk. A brisk walking pace mitigates VTE risk, particularly in individuals with F5 gene mutations, and this effect is partially mediated by serum albumin and cystatin C.

Genetic overlap between major depressive disorder and obstructive sleep apnea

ObjectiveObservational studies have frequently shown a co-occurrence of psychiatric disorders and Obstructive sleep apnea (OSA), with major depressive disorder (MDD) being a prevalent psychiatric disorder. This study aims to investigate the genetic overlap between MDD and OSA to explore their underlying pathological mechanisms.MethodsLeveraging the extensive and recent GWAS for OSA and MDD, we conducted genetic correlation analyses utilizing Linkage disequilibrium score regression (LDSC), re-evaluated their pleiotropic Single-nucleotide polymorphisms (SNP) with Cross-Phenotype Association (CPASSOC) and Colocalization (COLOC), investigated the overlap at the gene level using physical annotations and Multi-marker Analysis of GenoMic Annotation (MAGMA), and finally employed Mendelian randomization (MR) to assess potential causal relationships between the two disorders.ResultsUpon our investigation, we established that MDD and OSA exhibit high heritability (h2MDD=0.02, h2OSA=0.04) alongside a significant genetic correlation (rg=0.31, P= 1.42E-23). Utilizing CPASSOC, we identified 397 pleiotropic SNPs, associable with 45 loci, two of which share common genetic fragments with a pleiotropic role. Furthermore, the MAGMA study uncovered a total of 154 pleiotropic genes capable of influencing multiple brain regions. Lastly, leveraging MR analysis, we concluded that MDD heightens the risk of developing OSA (P=3. 10E-04, OR (95%CI):1.28(1.12~ 1.47)).ConclusionIn summary, our study identified PCLO as a common gene between OSA and MDD and provided evidence that MDD causally contributes to the development of OSA. These insights enhance our understanding of the shared mechanisms underlying the comorbidity of these conditions.

Causal relationship between inflammatory cytokines and polycystic ovary syndrome: a bidirectional mendelian randomization study.

Polycystic ovary syndrome (PCOS) is defined as a chronic low-grade inflammatory reproductive endocrine disorder. PCOS can induce various metabolic disorders, which are associated with a state of mild and slow-acting inflammation. Nevertheless, the causal relationship between polycystic ovary syndrome and inflammatory factors is uncertain. The causality between inflammatory cytokines and PCOS was analyzed by bidirectional Mendelian randomization (MR) in this current probe. We performed an interactive MR study to assess the causal relationships between 91 inflammatory cytokines and PCOS using Genome Wide Association Study (GWAS) data. We underwent dual-sample MR analysis with inverse variance weights (IVW) as the predominant MR methodology with multiple validity and heterogeneity analyses. MR-Egger, weighted median, simple mode, weighted mode and MR-PRESSO were analyzed as multiple likelihood sensitivity analyses to enhance the final results.The results came out interleukin-1-alpha (IL-1A) levels (odds ratio [OR] = 1.051, 95% fiducial interval [95% CI] = 1.009-1.095, P = 0.02) and oncostatin-M (OSM) levels ( [OR] = 1.041, [95% CI] = 1.001-1.082, P = 0.04) were positively associated with the development of PCOS. Moreover, interleukin-7 (IL-7) levels ([OR] = 0.935, [95% CI] = 0.884-0.989, P = 0.02); interleukin-15 receptor subunit alpha (IL15RA) levels ([OR] = 0.959, [95% CI] = 0.929-0.99, P = 0.01); and C-X-C motif chemokine 11 (CXCL11) levels ([OR] = 0.959, [95% CI] = 0.922-0.996. P = 0.03) were strongly negatively associated with PCOS. However, we did not find any strong positive results in the reverse analysis, suggesting that although inflammatory factors contribute to the pathogenesis of PCOS, PCOS itself does not trigger inflammatory factor production.Our study provides genetic evidence for the connection between systemic inflammatory regulators and PCOS. Treatments targeting specific inflammatory factors may help to mitigate the risk of PCOS. The levels of five of the 91 inflammatory factors included in this study, namely, IL1A and OSM, were associated with PCOS. IL1A and OSM contribute to the progression of PCOS while IL-7, IL15RA, and CXCL11 levels are negatively correlated with the development of PCOS.

Causal association of gut microbes and blood metabolites with acne identified through systematic mendelian randomization

Acne is a prevalent inflammatory disease in dermatology, and its pathogenesis may be associated with inflammation, immunity, and other mechanisms. It commonly manifests in young individuals and frequently imposes a heavy economic, physical, and psychological burden on patients. Gut microbes and blood metabolites, as significant immune and inflammatory regulators in the body, have been hypothesized to form the “neurocutaneous axis.” Nonetheless, the precise causal relationships among the gut microbes, circulating blood metabolites, and acne development have yet to be elucidated. This study employed bidirectional two-sample Mendelian randomization (MR) to probe the causal impacts of 412 distinct gut microbes and 249 blood metabolites on acne. Single nucleotide polymorphisms (SNPs), which are closely associated with gut microbes and blood metabolites, were utilized as instrumental variables. This approach was taken to discern whether these elements serve as pathogenic or protective factors in relation to acne. Furthermore, a mediation analysis encompassing gut microbes, blood metabolites, and acne was conducted to explore potential correlations between gut microbes and blood metabolites, as well as their cumulative effects on acne. This was done to substantiate the notion of causality. Bidirectional two-sample MR analysis revealed 8 gut bacteria, 6 bacterial metabolic abundance pathways determined by birdshot, and 8 blood metabolites significantly associated with acne. The mediation MR analysis revealed 2 potential causal relationships, namely, Bifidobacterium-DHA-Acne and Bifidobacterium-Degree of Unsaturation-Acne. This study identified gut microbes and blood metabolites that are causally associated with acne. A potential causal relationship between gut microbes and blood metabolites was obtained via mediation analysis. These insights pave the way for the identification of new targets and the formulation of innovative approaches for the prevention and treatment of acne.

Mendelian Randomization Estimates the Effects of Plasma and Cerebrospinal Fluid Proteins on Intelligence, Fluid Intelligence Score, and Cognitive Performance.

Observational studies have revealed associations between levels of plasma and cerebrospinal fluid (CSF) proteins and cognition-related traits. However, these associations may be influenced by confounding factors inherent in observational research. This study aims to identify plasma and CSF proteins associated with intelligence, fluid intelligence score, and cognitive performance through the application of Mendelian randomization (MR). Proteomic quantitative trait locus (pQTL) data for plasma and CSF proteins were sourced from existing genome-wide association study (GWAS). Intelligence, fluid intelligence score, and cognitive performance GWAS summary statistics provided comprehensive data for two-sample MR analysis. Extensive sensitivity analyses, including Steiger testing, reverse MR analysis, and Bayesian co-localization, were conducted to validate associations and identify shared genetic variants. Phenotype scanning explored potential pleiotropic effects. MR analysis identified several proteins in plasma and CSF significantly associated with intelligence, fluid intelligence scores, and cognitive performance. For intelligence, negatively associated proteins in plasma include endoplasmic reticulum aminopeptidase 2 (ERAP2) and secretogranin III (SCG3), while positively associated proteins are myeloperoxidase (MPO), signal regulatory protein alpha (SIRPA), regulator of microtubule dynamics 1 (RMDN1), and endoplasmic reticulum lectin 1 (ERLEC1). In CSF, C1-esterase inhibitor and carboxypeptidase E (CBPE) both exhibited positive associations with intelligence. For fluid intelligence scores, negatively associated proteins in plasma are copine 1 (CPNE1) and SCG3, while positively associated proteins are nudix hydrolase 12 (NUDT12) and RMDN1.In CSF, Macrophage Stimulating Protein (MSP) demonstrated a significant negative impact. For cognitive performance, negatively associated proteins in plasma include ERAP2, tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1), and SCG3, while positively associated proteins are NUDT12, RMDN1, ERLEC1, and ectonucleotide pyrophosphatase/phosphodiesterase family member 5 (ENPP5). In CSF, C1-esterase inhibitor was positively associated, while MSP and soluble tyrosine kinase with immunoglobulin-like and EGF-like domains 1(sTie-1) showed a negative association. Bayesian co-localization analysis revealed significant genetic overlaps between SIRPA, RMDN1, and ERLEC1 in plasma with intelligence; NUDT12 and SCG3 in plasma with fluid intelligence scores; and TIE1, NUDT12, RMDN1, ERLEC1, and ENPP5 in plasma with cognitive performance. Additionally, significant co-localization was identified between C1-esterase inhibitor and CBPE in CSF with intelligence, as well as between C1-esterase inhibitor and sTie-1 in CSF with cognitive performance. Reverse causality analysis confirmed the causal direction from proteins to cognitive traits. This study identifies specific plasma and CSF proteins that significantly impact intelligence, fluid intelligence scores, and cognitive performance. These proteins could serve as biomarkers and targets for future research and therapeutic interventions aimed at sustaining cognitive abilities and reducing impairment risks.

Identifying causal relationships between 35 blood and urine biomarkers and urologic cancers: MR-meta combined with Bayesian colocalization Mendelian randomization analysis

BackgroundBlood and urine biomarkers have been associated with urologic tumors, but their causal relationship with urologic tumors is unclear.MethodsWe performed a bidirectional Mendelian randomization (MR) analysis of the association between 35 blood and urine biomarkers and urological tumors in our discovery cohort. A Bayesian weighting approach was used to validate the positive results identified in the discovery cohort, and steiger filtering analysis was used to distinguish causality from reverse causality. Bayesian colocalization analysis was used to analyze which single nucleotide polymorphisms (SNPs) specifically co-located between the positive blood and urine biomarkers and the disease phenotypes were driven, and MR-positive results from the discovery cohort and the validation cohort were combined using the MR-meta method.ResultsSeveral blood and urine biomarkers were found to be significantly and causally associated with urologic cancers. Notably, calcium (OR: 1.34, 95%CI 1.10–1.63, P = 0.0040) and sex hormone-binding globulin (SHBG) (OR: 0.81, 95%CI 0.70–0.95, P = 0.0092) were associated with bladder cancer; gamma glutamyl transferase (GGT) (OR: 0.91, 95%CI 0.83–0.99, P = 0.0209), lipoprotein A (Lp(a)) (OR: 1.12, 95%CI 1.01–1.24, P = 0.0399), and insulinlike growth factor 1 (IGF 1) (OR: 1.10, 95%CI 1.01–1.20, P = 0.0220) were linked to prostate cancer (PCa); non albumin protein (OR: 0.78, 95%CI 0.65–0.93, P = 0.0065) and total protein (OR: 0.80, 95%CI 0.64–0.99, P = 0.0380) were linked to renal cancer; and apolipoprotein A (Apo-A) (OR: 0.56, 95%CI 0.32–0.98, P = 0.0426) and urate (OR:1.89, 95%CI 1.03–3.47, P = 0.0399) were associated with renal pelvis cancer. These associations were validated in an independent cohort, with GGT, IGF 1, and Lp(a) being consistently linked to PCa.ConclusionThis study identified significant biomarkers associated with urological cancers in blood and urine. These include GGT, IGF 1, and Lp(a), which are strong biomarkers for PCa. In addition, the findings of this study provide evidence for a handful of risk and protective factors for the development of urologic cancers.

Genetic Association Between Blood Metabolites and Craniosynostosis: A Mendelian Randomization Study.

Craniosynostosis is a congenital disorder characterized by the premature fusion of cranial sutures, leading to abnormal skull development and potential neurodevelopmental complications. The role of metabolic influences in craniosynostosis remains underexplored. This study investigates the causal relationship between specific blood metabolites and the risk of craniosynostosis using a 2-sample Mendelian randomization (MR) approach. Genetic instruments were selected from a genome-wide association study on blood metabolites and craniosynostosis data from the FinnGen database. The MR analysis was conducted using inverse variance weighted regression as the primary method, with MR-Egger and weighted median methods as sensitivity analyses. Additional tests for pleiotropy and heterogeneity were performed to validate the robustness of the findings. The analysis identified significant associations between elevated levels of gamma-glutamylglycine [odds ratio (OR) = 2.379, 95% CI = 1.261-4.488, P = 0.007], N6-acetyllysine (OR = 2.731, 95% CI = 1.081-6.901, P = 0.034), phosphocholine (OR = 2.205, 95% CI = 1.226-3.658, P = 0.038) and glycine (OR = 2.118, 95% CI = 1.226-3.658, P = 0.007) with an increased risk of craniosynostosis. Conversely, higher levels of 3-hydroxy-2-methylpyridine sulfate (OR = 0.411, 95% CI = 0.1717-0.988, P = 0.047) and 5,6-dihydrothymine (OR = 0.293, 95% CI = 0.098-0.876, P = 0.028) were associated with reduced risk. Sensitivity analyses confirmed the robustness of these findings, with no significant evidence of pleiotropy or heterogeneity detected. This study provides evidence that specific blood metabolites may causally influence the risk of craniosynostosis, suggesting potential metabolic pathways that could be targeted for therapeutic intervention. These findings help to develop metabolite-based strategies for the prevention and treatment of craniosynostosis.

Causal Effects of Gut Microbiota on Gout and Hyperuricemia: Insights from Genome-Wide Mendelian Randomization, RNA-Sequencing, 16S rRNA Sequencing, and Metabolomes.

This study investigated the causal relationship between gut microbiota (GM), serum metabolome, and host transcriptome in the development of gout and hyperuricemia (HUA) using genome-wide association studies (GWAS) data and HUA mouse model experiments. &#160;Methods: Mendelian randomization (MR) analysis of GWAS summary statistics was performed using an inverse variance weighted (IVW) approach to determine predict the causal role of the gut microbiota on gout. The HUA mouse model was used to characterize changes in the gut microbiome, host metabolome, and host kidney transcriptome by integrating cecal 16S rRNA sequencing, untargeted serum metabolomics, and host mRNA sequencing.</p> &#160;Results: Our analysis demonstrated causal effects of seven gut microbiota taxa on gout, including genera of Ruminococcus, Odoribacter, and Bacteroides. Thirty-eight, immune cell traits were associated with gout. Dysbiosis of Dubosiella, Lactobacillus,Bacteroides, Alloprevotella, and Lachnospiraceae_NK4A136_group genera were associated with changes in the serum metabolites and kidney transcriptome of the HUA model mice. The changes in the gut microbiome of the HUA model mice correlated significantly with alterations in the levels of serum metabolites such as taurodeoxycholic acid, phenylacetylglycine, vanylglycol, methyl hexadecanoic acid, carnosol, 6-aminopenicillanic acid, sphinganine, p-hydroxyphenylacetic acid, pyridoxamine, and de-o-methylsterigmatocystin, and expression of kidney genes such as CNDP2, SELENOP, TTR, CAR3, SLC12A3, SCD1, PIGR, CD74, MFSD4B5, and NAPSA.</p> &#160;Conclusion: Our study demonstrated a causal relationship between GM, immune cells, and gout. HUA development involved alterations in the vitamin B6 metabolism because of gut microbiota dysbiosis that resulted in altered pyridoxamine and pyridoxal levels, dysregulated sphingolipid metabolism, and excessive inflammation.</p>.

Analyzing the causal role of blood cells in aging: a Mendelian randomization study.

Blood cells are crucial components of the human body, closely linked to the aging process. This study aims to explore the causal relationship between 91 blood cell phenotypes and aging through Mendelian randomization (MR) analysis. Exposure data from genome-wide association studies (GWAS) was extracted from the GWAS of blood cell perturbation phenotypes in 2,600 European individuals. Initial analysis utilized GWAS data related to aging from the GWAS Catalog database GCST90014288, with inverse-variance weighting as the primary method for causal analysis. Sensitivity analyses included Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. For significant associations, replication and meta-analysis were conducted using independent aging GWAS data from GCST90014300. Initial analysis revealed that environmental peroxide-impacted red blood cells and ciprofloxacin-impacted reticulocytes accelerated aging. Additionally, elevated neutrophil levels were found to accelerate aging, while LiCl-impacted neutrophils reduced aging risk. Replication and meta-analysis showed consistent results: ciprofloxacin-impacted reticulocytes and elevated neutrophil levels increased the risk of aging, while LiCl-impacted neutrophils reduced the risk. RBCs showed no significant impact on aging progression. Sensitivity analyses confirmed the robustness and reliability of these positive findings. Our study provides evidence of a causal relationship between three blood cell disturbance phenotypes and human aging.

The causal nexus between diverse smoking statuses, potential therapeutic targets, and NSCLC: insights from Mendelian randomization and mediation analysis

ObjectiveLung cancer, the most prevalent malignancy, is typically diagnosed at an advanced stage. Smoking is a pivotal risk factor for NSCLC, yet the impact of various smoking statuses on NSCLC remains unclear. Thus, this study aims to explore whether different smoking statuses can causally influence NSCLC through effects on predictive targets, offering a novel perspective for NSCLC treatment.MethodsEmploying dual-sample MR, MVMR, and TSMR approaches, we assessed the causal relationships between 13 distinct smoking statuses and NSCLC, using predicted potential therapeutic targets as mediators to further elucidate the causal interplay among them.ResultsAmong the 13 smoking statuses, current tobacco smoking, exposure to tobacco smoke outside the home, past tobacco smoking, and never smoked demonstrated causal relationships with NSCLC. MVMR analysis reveals that Current tobacco smoking is an independent risk factor for NSCLC. Utilizing NCAPD2, IL11RA, and MLC1 as mediators, IL11RA (22.2%) was found to potentially mediate the relationship between past tobacco smoking and NSCLC.ConclusionThis study, integrating bioinformatics and MR analysis, identified three potential predictive targets as mediators to investigate the causal relationships between different smoking statuses and NSCLC through potential therapeutic targets, providing new insights for the treatment and prevention of NSCLC.

Causal association between allergic diseases and celiac disease: a bidirectional two-sample and multivariable Mendelian-randomization study

Objective This study aimed to assess the causality of allergic diseases and celiac disease. Methods We collected summary-level data from publicly available genome-wide association studies to conduct our bidirectional two-sample and multivariable Mendelian randomization analysis. Furthermore, a series of sensitivity analyses were applied to validate our findings. Results In bidirectional two-sample MR analyses, we found a significant causal effect of atopic dermatitis (AD) on CD (Inverse-variance weighted (IVW): odds ratio [OR] = 1.302, 95% confidence interval [CI] = 1.152-1.471, P < 0.001). We also found a significant causal effect of allergic rhinitis (AR) on CD (IVW: OR = 4.181, 95% CI = 1.495-11.697, P = 0.006). However, the MR-Egger method indicated a different causal effect direction compared to the IVW and weighted median method. After Bonferroni correction, the result of asthma on CD is suggestive of a causal effect (IVW: OR = 1.186, 95% CI = 1.021-1.378, P = 0.026). No causal effects were found when CD was considered as an exposure variable. In MVMR analyses, after separately and jointly adjusting for the influence of smoking and BMI, the causal effect of AD on CD remained robust. Conclusions Our study suggests that AD is a risk factor for CD and it is considered suggestive of a causal relationship between asthma and CD. Further research is needed to explore the potential mechanisms underlying this causal effect.

Associations of human blood metabolome with optic neurodegenerative diseases: a bi-directionally systematic mendelian randomization study

BackgroundMetabolic disruptions were observed in patients with optic neurodegenerative diseases (OND). However, evidence for the causal association between metabolites and OND is limited.MethodsTwo-sample Mendelian randomization (MR). Summary data for 128 blood metabolites was selected from three genome-wide association study (GWASs) involving 147,827 participants of European descent. GWASs Data for glaucoma (20906 cases and 391275 controls) and age-related macular degeneration (AMD, 9721 cases and 381339 controls) came from FinnGen consortium. A bi-directional MR was conducted to assess causality, and a Mediation MR was further applied to explore the indirect effect, a phenome-wide MR analysis was then performed to identify possible side-effects of the therapies.ResultsAll the results underwent correction for multiple testing and rigorous sensitivity analyses. We identified N-acetyl glycine, serine, uridine were linked to an elevated risk of glaucoma. 1-arachidonic-glycerol-phosphate-ethanolamine, 4-acetamido butanoate, o-methylascorbate, saturated fatty acids, monounsaturated fatty acids, VLDL cholesterol, serum total cholesterol, X-11,529 were linked to reduced risk of glaucoma. There were 4 metabolites linked to a reduced risk of AMD, including tryptophan betaine, 4-androsten-3beta-17beta-diol disulfate, apolipoprotein B, VLDL cholesterol. We discovered IOP, AS, T2D as glaucoma risk factors, while BMI, AS, GCIPL as AMD factors. And 6 metabolites showed associations with risk factors in the same direction as their associations with glaucoma/AMD. Phenome-wide MR indicated that selected metabolites had protective/adverse effects on other diseases.ConclusionsBy integrating genomics and metabolomics, this study supports new insights into the intricate mechanisms, and helps prevent and screen glaucoma and AMD.

Lipid metabolism disorders and albuminuria risk: insights from National Health and Nutrition Examination Survey 2001–2018 and Mendelian randomization analyses

Background Previous studies have revealed an underlying connection between abnormal lipid metabolism and albuminuria. We aim to investigate the causal relationship between lipid metabolism disorders and the risk of albuminuria from both a population and genetic perspective. Methods A cross-sectional study was conducted by using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Multivariable-adjusted logistic regression, subgroup analysis, interaction tests and restricted cubic spline (RCS) were employed statistically. Mendelian randomization (MR) analysis was performed to validate the causal relationship between exposure and outcome to mitigate confounding factors and reverse causation interference. Results After adjusting for confounders, HDL levels (1.03-2.07 nmol/L) were associated with a reduced risk of albuminuria. In contrast, elevated cholesterol levels (>6.2 nmol/L) and triglyceride levels (>2.3 nmol/L) were associated with an increased risk of albuminuria. Serum triglyceride concentration emerged as a potential risk factor for albuminuria. In MR analysis, a reduced risk of albuminuria was associated with serum total HDL level (IVW: OR = 0.91, 95% CI = 0.86-0.97, p = 0.002). In contrast, cholesterol esters in medium VLDL (IVW: OR = 1.05, 95% CI = 1.00-1.10, p = 0.032), chylomicrons and extremely large VLDL (IVW: OR = 1.08, 95% CI = 1.03-1.14, p = 0.003), and triglycerides (IVW: OR = 1.14, 95% CI = 1.09-1.19, p < 0.001) were associated with an increased risk of albuminuria. Conclusion A causal relationship exists between serum lipid metabolism disorder and albuminuria risk. Further validation of additional blood lipid metabolism biomarkers is imperative for future studies.

Association between human blood metabolome and risk of myocarditis: a mendelian randomization study

Myocarditis is a common disease of the cardiovascular and immune systems, but the relationship between relevant blood metabolites and the risk of myocarditis has not been well-established. To identify potential biometabolic markers associated with myocarditis, we conducted a two-sample Mendelian randomization (MR) study. We performed preliminary MR analysis using the inverse variance weighted (IVW) method, supplemented by MR-Egger, weighted median, and weighted mode methods to adjust for false discovery rate (FDR). Confounders were screened using the GWAS Catalog website. Sensitivity analyses included Cochrane Q-test, Egger regression, Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO), scatterplots, funnel plots, and forest plots. For genetic and directional analysis, we employed co-localization analysis and the Steiger test. MR analysis was performed using the FinnGen database and meta-analysis was performed using the IEU database. MR analysis identified significant correlations for five metabolic biomarkers after FDR correction. These included four known metabolites: kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, and 5-acetylamino-6-formylamino-3-methyluracil, as well as one unknown metabolite, X-25,422. Among these, kynurenine (OR = 1.441, 95%CI = 1.089–1.906, p-value = 0.018) and 1-stearoyl-GPE (18:0) (OR = 1.263, 95%CI = 1.029–1.550, p-value = 0.029) were identified as risk factors for myocarditis, while deoxycarnitine (OR = 0.813, 95%CI = 0.676–0.979, p-value = 0.029), 5-acetylamino-6-formylamino-3-methyluracil (OR = 0.864, 95% CI = 0.775–0.962, p-value = 0.018), and X-25,422 (OR = 0.721, 95%CI = 0.587–0.886, p-value = 0.009) were found to be protective factors. No evidence of heterogeneity, horizontal pleiotropy, or sensitivity issues was observed, and no shared genetic factors between exposure and outcome were detected. The causality was in the correct direction. Meta-analysis further confirmed the causal relationship between the five metabolites and myocarditis. This study identifies a causal relationship between five circulating metabolites and myocarditis. Kynurenine, 1-stearoyl-GPE (18:0), deoxycarnitine, X-25,422, and 5-acetylamino-6-formylamino-3-methyluracil may serve as potential drug targets for myocarditis, providing a theoretical basis for the prevention, diagnosis, and treatment of the condition.

Causal Effects of Gastroesophageal Reflux on Chronic Rhinosinusitis: A Bidirectional Two-Sample Mendelian Randomization Study.

Observational studies have shown a bidirectional association between gastroesophageal reflux (GER) and chronic rhinosinusitis (CRS) or chronic rhinitis (CR), but it is not clear whether this association is causal. This study was to investigate the causality between GER and CRS or CR using bidirectional two-sample Mendelian randomization (MR) analysis. Using pooled data from large genome-wide association studies (GWAS), genetic loci independently associated with GER, CRS and CR in populations of European and American ancestry were selected as instrumental variables (IVs). The inverse variance weighted (IVW) method was used to analyse the random effects model of MR, and the odds ratio (OR) was used as the evaluation index to explore the bidirectional causality between GER and CRS or CR. Single nucleotide polymorphism (SNP) outliers were detected using MR-pleiotropy Residual Sum and Outliers (MR-PRESSO). The MR-Egger intercept test examined the horizontal pleiotropy of SNPs. The "leave-one-out" sensitivity analysis examined whether MR results were affected by a single SNP. The main results of IVW showed that GER increased the risk of CRS (OR = 1.3795, 95% CI = 1.188-1.603, p < 0.0500) and CR (OR = 1.3941, 95% CI = 1.1671-1.6652, p < 0.0500). The obtained SNPs as IVs for GER, CRS and CR had no significant horizontal pleiotropy, heterogeneity or bias. Regarding the reverse directions, no notable associations could be found. This MR analysis revealed that genetically predicted GER had a causal effect on an increased risk of CRS or CR, but not vice versa. These results have great implications for the management of CRS (especially for refractory CRS) or CR in clinical practice.

Skimmed milk intake reduces the risk of ER− breast cancer: a Mendelian randomization analysis

BackgroundIn prior observational investigations, it has been demonstrated that the consumption of milk is associated with the incidence of breast cancer (BC). Despite the existence of a two-sample Mendelian randomization (MR) that suggests a causal relationship between milk intake and breast cancer risk, the outcomes still lack a definitive conclusion. This ambiguity may be attributed to variables such as the variety of milk ingested, estrogen levels, the specific type of BC, and potential confounding factors. Therefore, our principal objective is to establish the causal association between the consumption of skimmed milk and full cream milk and the risk of different types of BC through the utilization of two-sample and two-step MR analyses.MethodsIn this study, we analyzed single nucleotide polymorphisms associated with skimmed and full-cream milk consumption in a cohort of 360,806 individuals from European populations through genome-wide association studies. We conducted a two-sample MR analysis using three different methods: inverse variance weighting (IVW) was used as the main analysis, and MR-Egger and Weighted median were used as supplementary analyses to IVW. We also performed sensitivity analysis, which included leave-one-out analysis, Cochran's Q test to detect heterogeneity, and MR-Egger intercept analysis to detect potential biases caused by pleiotropy. We used two-step MR analysis to evaluate potential mediators of associations.ResultsIn the two-sample MR analysis, IVW analysis suggests a potential inverse causal relationship between skimmed milk and BC [OR 0.34, 95% CI (0.12–1.00), P = 0.05]. Subgroup analysis revealed that skimmed milk reduces the risk of estrogen receptor-negative (ER−) breast cancer [OR 0.18, 95% CI (0.04–0.90), P = 0.04], but not estrogen receptor-positive (ER+) breast cancer [OR 0.42, 95% CI (0.15–1.22), P = 0.11]. MR Egger reached similar results, that is, skimmed milk reduces the risk of ER− breast cancer [OR 0.006, 95% CI (0.00–0.70), P = 0.04], but not BC [OR 0.16, 95% CI (0.01–4.66), P = 0.30] and ER+ breast cancer [OR 0.50, 95% CI (0.02–12.61), P = 0.65]. Additionally, we found no causal relationship between full cream milk and BC (P > 0.05). In two-step MR analysis, we found evidence for a mediating role of BMI in the relationship between skimmed milk intake and ER-breast cancer risk.ConclusionOur findings strengthen the evidence for a protective effect of skimmed milk consumption on ER-breast cancer risk. Further two-step MR analyses suggest that this protective effect may partly result from body mass index (BMI). There is no evidence that full cream milk consumption affects the risk of BC.

Genetic Evidence for GLP-1 and GIP Receptors as Targets for Treatment and Prevention of MASLD/MASH.

Glucagon-like peptide-1 receptor (GLP1R) agonists and glucose-dependent insulinotropic polypeptide receptor (GIPR) agonists may help treat metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). However, their definitive effects are still unclear. Our study aims to clarify this uncertainty. We utilised conventional Mendelian randomisation (MR) analysis to explore potential causal links between plasma GLP-1/GIP concentrations and MASLD and its related traits. Next, we conducted drug-target MR analysis using highly expressed tissue data to assess the effects of corresponding drug perturbation on these traits. Finally, mediation analysis was performed to ascertain whether the potential causal effect is direct or mediated by other MASLD-related traits. Circulating 2-h GLP-1 and GIP concentrations measured during an oral glucose tolerance test showed hepatoprotective effects on MASLD risk (ORGLP-1 = 0.168 [95% CI 0.033-0.839], p = 0.030; ORGIP = 0.331 [95% CI 0.222-0.494], p = 6.31 × 10-8). GLP1R expression in the blood had a minimal causal effect on MASLD risk, whereas GIPR expression significantly affected MASLD risk (OR = 0.671 [95% CI 0.531-0.849], p = 9.07 × 10-4). Expression levels of GLP1R or GIPR in the blood significantly influenced MASLD-related clinical traits. Mediation analysis revealed that GIPR expression protected against MASLD, even after adjusting for type 2 diabetes or body mass index. GLP-1/GIP receptor agonists offer promise in lowering MASLD/MASH risk. GIP receptor agonists can exert direct and indirect effects on MASLD mediated by weight reduction or glycemic control improvement.

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders

BackgroundGenome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders. MethodsThrough integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database. ResultsPWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10−7) and response to external stimulus (adjusted P = 4.13 × 10−7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10−2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB. ConclusionsOur findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

Phenotypic insights into genetic risk factors for immune-related adverse events in cancer immunotherapy

BackgroundImmune-related adverse events (irAEs) pose substantial challenges in the realm of cancer immunotherapy, frequently affecting treatment efficacy and patient safety. To address the urgent need for identifying risk factors associated with irAEs, we conducted a comprehensive phenotype-wide Mendelian randomization analysis (MR-PheWAS).MethodsUtilizing publicly accessible genome-wide association study (GWAS) data, this investigation evaluated the impact of over 5000 exposure variables on susceptibility to irAEs using univariate Mendelian randomization (MR). We categorized these correlations and further explored potential mechanisms by which associated traits might influence irAEs through multivariate MR.ResultsMR-PheWAS identified numerous risk factors for irAEs, encompassing both previously documented and novel associations. Specifically, we identified 105 traits with probable causal relationships to all-grade irAEs and 119 traits with suggestive associations. For high-grade irAEs, we categorized 122 traits as probably associated and 141 as suggestively associated. Notably, multivariate MR analyses uncovered intricate interactions, particularly highlighting how diabetes impacts all-grade irAEs through mediators such as body mass index and sex hormone-binding globulin.ConclusionsThis study has not only identified new risk factors for irAEs but also confirmed several well-established ones. Further investigation is crucial to validate and assess these identified risk factors within clinical trials. A mechanistic understanding of these causal factors is essential for improving the management and prevention of irAEs.

The causal relationship between anti-CD20 antibodies and endometrial cancer: a Mendelian randomization study

PurposeTo determine the effects of anti-B cell surface marker CD20 antibody on the occurrence and progression of endometrial cancer to provide insights into clinical treatment in the future.MethodsWe performed a two-sample Mendelian randomization analysis (MR) to analyze the causal relationship between EC and immune cell markers. The genome-wide association study (GWAS) data of MS4A1 single nucleotide polymorphism encoding gene of CD20 were collected, and a drug target MR analysis was performed to detect the causal relationship between anti-CD20 antibody and the risk of EC. The risk of follicular lymphoma was used as a positive control, and EC was used as the outcome.ResultsEC exerted an effect on 28 immunophenotypes, predominantly on CD20. CD20 in immunoglobulin D+ CD38− B cells, memory B cells, and unsw memory B cells increased after EC onset. In addition, we detected one immunophenotype that exerted a dangerous effect on EC, i.e., CD3/TD CD4+ (mature stage of the T cell group). Simultaneously, CD20 could be used as both a risk factor and a protective factor for EC (P > 0.05). Anti-CD20 antibodies significantly reduced the risk of follicular lymphoma, including two GWAS pooled datasets. In addition, anti-CD20 antibodies exerted a protective effect on EC in two GWAS pooled datasets (P > 0.05).ConclusionOur study confirms the close relationship between CD20 and EC. Anti-CD20 antibodies may exert a protective effect on EC and reduce the risk of EC morbidity, providing a reference for future clinical diagnosis and treatment. However, further clinical verification of our results is warranted.