Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects

Causal associations between circulating metabolites and chronic kidney disease: a Mendelian randomization study

BACKGROUND

Circulating metabolites have been associated with cross-sectional renal function in population-based research. Nevertheless, there is currently little proof to support the idea that metabolites either cause or prevent renal function. New treatment targets and ways to screen individuals with impaired renal function will be made possible via an in-depth analysis of the causal relationship between blood metabolites and renal function.

METHODS

We assessed the causal relationship between 452 serum metabolites and six renal phenotypes (CKD, rapid progression to CKD [CKDi25], rapid eGFR decline [CKD rapid3], dialysis, estimated glomerular filtration rate, and blood urea nitrogen) using univariate Mendelian randomization, primarily employing the inverse variance weighted method with robust sensitivity analyses. Heterogeneity and pleiotropy were examined via Cochrane's Q test and MR-Egger regression, and statistical significance was adjusted using Bonferroni correction. To assess potential adverse effects of metabolite modulation, we conducted a phenome-wide Mendelian randomization analysis, followed by multivariate Mendelian randomization to adjust for confounders.

RESULTS

We identified glycine and N-acetylornithine as potential causal mediators of CKD and renal dysfunction. Notably, lowering glycine levels may increase the risk of cholelithiasis and cholecystitis, while reducing N-acetylornithine could have unintended effects on tinnitus.

CONCLUSION

Glycine and N-acetylornithine represent promising therapeutic targets for CKD and renal function preservation, but their modulation requires careful risk-benefit assessment to avoid adverse effects.

Causal relationship between molecular markers of biological aging and orthopedic diseases: A two-sample bidirectional Mendelian randomization study

BACKGROUND

Studies indicate an association between biological aging and orthopedic diseases, but the causality remains unclear.

AIMS

This study aims to investigate the bidirectional causal relationship between molecular markers of biological aging age and orthopedic conditions.

METHODS

A two-sample Mendelian randomization (MR) analysis based on a genome-wide association study (GWAS) was conducted to explore these causal relationships. Analysis methods included inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. Sensitivity analyses involved Cochran's Q, MR-Egger, leave-one-out, and MR pleiotropy residual sum and outlier (MR-PRESSO) tests.

RESULTS

The forward MR analysis identified several causal relationships: granulocyte proportions influenced intervertebral disc degeneration (IVDD) (OR 0.2316, P = 0.0101) and low back pain (LBP) (OR 0.2624, P = 0.007); telomere length (TL) affected cervical spondylosis (C/S) (OR 0.8759, P = 0.0167) and IVDD (OR 0.9184, P = 0.023); fibroblast growth factor-23 (FGF-23) impacted frozen shoulder (FS) (OR 1.2424, P = 0.0316); and HannumAge influenced C/S (OR 0.9518, P = 0.0233). The reverse MR analysis found that FS influenced TL (OR 0.9582, P = 0.0002) and α-Klotho (OR 0.7592, P = 0.0256), while sciatica affected TL (OR 0.9344, P = 0.0055) and C/S impacted PhenoAge (OR 1.6583, P = 0.0131) after outlier exclusion. Cochran's Q indicated heterogeneity in certain analyses, and MR-Egger showed no horizontal pleiotropy in significant causal associations.

CONCLUSIONS

This study suggests a potential causal associations between molecular markers of biological aging and orthopedic diseases, suggesting avenues for future research into the underlying mechanisms.

Plasma proteins and herpes simplex virus infection: a proteome-wide Mendelian randomization study

Proteomics plays a pivotal role in clinical diagnostics and monitoring. We conducted proteome-wide Mendelian randomization (MR) study to estimate the causal association between plasma proteins and Herpes simplex virus (HSV) infection. Data for 2,923 plasma protein levels were obtained from a large-scale protein quantitative trait loci study involving 54,219 individuals, conducted by the UK Biobank Pharma Proteomics Project. HSV-associated SNPs were derived from the FinnGen study, which included a total of 400,098 subjects infected with HSV. MR analysis was performed to assess the links between protein levels and the risk of HSV infection. Furthermore, a Phenome-wide MR analysis was utilized to explore potential alternative indications or predict adverse drug events. Finally, we evaluated the impact of 1,949 plasma proteins on HSV infection, identifying 48 proteins that were negatively associated with HSV infection and 54 proteins that were positively associated. Genetically higher HLA-E levels were significantly associated with increased HSV infection risk (OR = 1.39, 95% CI: 1.17-1.65, P = 2.13 × 10-4, while ULBP2 showed a significant negative association with HSV infection risk (OR = 0.81, 95% CI: 0.73-0.90, P = 6.25 × 10-5) in the primary analysis. No significant heterogeneity or pleiotropy was observed in any of the results. Additionally, we found a suggestive association of Lymphotoxin-beta, SMOC1, MICB_MICA, ASGR1, and ANXA10 with HSV infection risk (P < 0.003). In Phenome-wide MR analysis, HLA-E was associated with 214 phenotypes (PFDR < 0.10) while ULBP2 did not show significant associations with any diseases after FDR adjustment. The comprehensive MR analysis established a causal link between multiple plasma proteins and HSV infection, emphasizing the roles of HLA-E and ULBP2. These results provide new insights into the biological mechanisms of HSV and support the potential for early intervention and treatment strategies, although further research is needed to validate these plasma protein biomarkers.

Mendelian randomization analysis revealed a gut microbiota-eye axis in acute anterior uveitis

BACKGROUND

Observational studies suggest that gut microbiome (GM) may contribute to acute anterior uveitis (AAU) development, but causality remains unclear. This study was conducted to test whether specific GM taxa were causally associated with AAU.

METHODS

The GM data were obtained from the DMP, which included 7738 individuals' faecal samples and an analysis of host genotype-taxa abundance associations. The AAU data were derived from the FinnGen Consortium (8624 cases and 473,095 controls). We primarily employed the inverse-variance weighted method, complemented by supplementary sensitivity analyses.

RESULTS

Higher abundance of Lachnospiraceae noname (OR = 0.86, 95% CI 0.81-0.91, P = 5.7 × 10-8), Alistipes finegoldii (OR = 0.87, 95% CI 0.78-0.96, P = 0.008), Erysipelotrichaceae (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), Erysipelotrichia (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), Erysipelotrichales (OR = 0.90, 95% CI 0.81-0.99, P = 0.037), and Bacteroides ovatus (OR = 0.93, 95% CI 0.87-1.00, P = 0.039) predicted a lower AAU risk. Conversely, higher abundance of Bifidobacterium catenulatum (OR = 1.06, 95% CI: 1.02-1.10, P = 0.005), Bacteroides coprocola (OR = 1.11, 95% CI: 1.02-1.21, P = 0.014), Parabacteroides unclassified (OR = 1.12, 95% CI 1.03-1.22, P = 0.010), and Prevotella (OR = 1.15, 95% CI: 1.01-1.29, P = 0.029) predicted a higher AAU risk. The results also showed a reverse causation from AAU to Bifidobacterium catenulatum (OR = 1.39, 95% CI: 1.03-1.86, P = 0.005).

CONCLUSION

This study suggests that specific GM is causally associated with AAU risk, warranting more mechanistic validation and clinical trials.

Prospective Investigation Unravels Plasma Proteomic Links to Dementia

Investigating plasma proteomic signatures of dementia offers insights into its pathology, aids biomarker discovery, supports disease monitoring, and informs drug development. Here, we analyzed data from 48,367 UK Biobank participants with proteomic profiling. Using Cox and generalized linear models, we examined the longitudinal associations between proteomic signatures and dementia-related phenotypes. Mendelian randomization analysis was employed to identify causal associations, and machine learning algorithms were applied to develop protein-based models for dementia prediction. We identified 74 proteins significantly associated with the risk of various types of dementia and cognitive functions after Bonferroni correction. Among these, strong associations were observed for growth/differentiation factor 15 (GDF15), glial fibrillary acidic protein (GFAP), and neurofilament light polypeptide (NEFL), across all types of dementia. Additionally, 15 proteins demonstrated significant associations with neuroimaging-defined dementia endophenotypes. Two-sample Mendelian randomization analyses further substantiated causal relationships between dementia-associated proteins and Alzheimer's disease, particularly involving GDF15, proto-oncogene tyrosine-protein kinase receptor Ret (RET), and GFAP. Moreover, we identified three protein modules associated with dementia, primarily linked to immune system processes, angiogenesis, and energy metabolism, providing insights into potential biological pathways underlying the disease. Furthermore, we proposed a ten-protein panel capable of forecasting dementia over a median follow-up period of 8.6 years, achieving an area under the curve (AUC) of 0.857 (95% confidence interval (CI), 0.837-0.876). Our results revealed dementia-associated plasma proteomic signatures, and their causal relationships, notably GDF15-RET signaling with Alzheimer's disease, and proposed a promising protein panel for high-risk dementia screening.

Exploring causal links in the gut-brain axis: a Mendelian randomization study of gut microbiota, metabolites, and cognition

The causal mediation effects of metabolites between gut microbiota and cognitive phenotypes remain unclear. Guided by the gut-brain axis mechanism, this study employed systematic Mendelian randomization (MR) to investigate these mediation pathways and their implications for functional food development. Univariate MR analysis was performed to estimate the causality of 211 gut microbial taxa (n = 18 340) and 452 serum metabolites (n = 7824) on general cognitive (n = 257 700), non-cognitive (n = 510 795), and specific cognitive phenotypes (n ≈ 2500) using genome-wide association study data. Inverse-variance weighted estimation was adopted as the primary method, with MR sensitivity analyses performed to complement the results. Metabolic pathway analysis was employed to enrich metabolic profiles, while two-step MR was used to screen mediation pathways. We revealed seven causal associations between microbiotas or metabolites and cognitive phenotypes (FDR < 0.05). Increased abundance of the order Clostridiales id.1863 was associated with better cognitive traits (OR = 1.14, 95%CI = 1.06-1.22, P = 2.06 × 10-4), while 1-linoleoylglycerophosphoethanolamine was also positively associated with cognitive traits (OR = 1.61, 95%CI = 1.33-1.95, P = 8.17 × 10-7). Seven significant metabolic pathways were enriched, including alpha-linolenic acid and linoleic acid metabolism, highlighting the potential role of omega-3 and omega-6 fatty acids in cognitive health. We further identified two significant mediation pathways linking the gut microbiota to cognitive phenotypes through metabolites. Notably, homostachydrine (39.1%) was found to mediate a proportion of the impact of the genus Turicibacter on emotion recognition (indirect effect: β = 0.105, 95%CI = 0.006-0.259, p = 2.60 × 10-2). This study provides evidence for causal relationships between gut microbiota, serum metabolites, and cognitive function, supporting the gut-brain axis mechanism. Our findings suggest potential targets for the development of functional food and personalized nutrition to improve cognitive health.

Investigating the link between genetic predictive factors of brain functional networks and two specific sleep disorders: Sleep apnoea and snoring

BACKGROUND

Sleep disorders are a widespread public health issue globally. Investigating the causal relationship between resting-state brain functional abnormalities and sleep disorders can provide scientific evidence for precision medicine interventions.

METHODS

We screened single nucleotide polymorphisms (SNPs) associated with rs-fMRI phenotype as instrumental variables Using bidirectional two-sample Mendelian randomization (MR), mediation MR, and multivariate MR based on Bayesian methods, the study tested the causal relationship between genetically predicted rs-fMRI and nine common sleep disorders.

RESULTS

The main inverse variance weighted (IVW) analysis identified four resting state functional magnetic resonance imaging (rs-fMRI) phenotypes that are causally associated with the risk of sleep disorders. For example, increased amplitude in nodes of the parietal, precuneus, occipital, temporal, and cerebellum regions, as well as the default mode network (DMN), central executive network (CEN) and attention network (AN) was associated with an increased risk of sleep apnoea. Enhanced neural activity in the calcarine or lingual and cerebellum regions and increased functional connectivity with the visual and subcortical-cerebellum networks was associated with a reduced risk of snoring. The mediation MR analysis shows that, body mass index (BMI) plays a significant mediating role in the risk of sleep apnoea by modulating the amplitude of nodes in the parietal, temporal, and cerebellum regions, as well as the connectivity changes in the DMN, CEN, and AN.

CONCLUSIONS

This study identified three rs-fMRI phenotypes linked to increased sleep apnoea risk and one associated with decreased snoring risk, providing an important target for the treatment of sleep disorders at the level of brain functional networks.

Causal relationship between schizophrenia and five types of dementia: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Although observational research indicates an association between schizophrenia and dementia, it is unclear whether the two are causally related. In order to examine the causal relationship between schizophrenia and five types of dementia (all-cause dementia, Alzheimer's disease, vascular dementia, frontotemporal dementia, and dementia with Lewy bodies), we performed a bidirectional two-sample Mendelian randomization analysis.

METHODS

In this study, pooled statistics of schizophrenia and dementia were obtained from the Large-scale genome-wide association study (GWAS) in individuals of European ancestry. Inverse variance weighted (IVW) was the primary statistical approach used in this Mendelian randomization, to further support our findings, we also used MR-Egger, weighted median, and cML-MA. We also used a number of sensitivity analyses to evaluate pleiotropy and heterogeneity.

RESULTS

In the study of the effect of schizophrenia on dementia, findings from the IVW analysis suggested that schizophrenia is associated with an increased risk of all-cause dementia (OR = 1.065, 95%CI: 1.027 ～ 1.104, P = 0.001, FDR-corrected P = 0.003), Alzheimer's disease (OR = 1.029, 95%CI: 1.003 ～ 1.054, P = 0.027, FDR-corrected P = 0.045), and vascular dementia (OR = 1.106, 95%CI: 1.023 ～ 1.197, P = 0.012, FDR-corrected P = 0.029). In the study of the effect of dementia on schizophrenia, no form of dementia assessed in this study was found to be a risk factor for schizophrenia.

CONCLUSION

Our findings suggest that schizophrenia may be a risk factor for all-cause dementia, Alzheimer's disease, and vascular dementia, but no dementia of any kind was found to be a risk factor for schizophrenia. Our study provides insights into the potential genetic relationship between schizophrenia and dementia.

DBI as a Novel Immunotherapeutic Candidate in Colorectal Cancer: Dissecting Genetic Risk and the Immune Landscape via GWAS, eQTL, and pQTL

Background: Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide. Identifying drug targets associated with CRC is crucial for developing targeted therapies. Methods: MR (IVW, Wald ratio, weighted median, and MR-Egger) and SMR analyses were used to screen candidate genes associated with CRC risk. Further validation was performed using The Cancer Genome Atlas (TCGA) to assess gene expression patterns and prognostic significance. Additionally, immune infiltration analysis was conducted to characterize the tumor immune microenvironment. Drug prediction was performed to explore potential therapeutic interventions. Results: Eight genes were identified associated with CRC. IGFBP3, CD72, SERPINH1, CHRDL2, LRP11, and SPARCL1 were linked to an increased risk of CRC, whereas DBI and HYAL1 were associated with a decreased risk of CRC. Notably, DBI exhibited a potentially favorable immune profile, negatively correlated with Tregs and MDSCs while positively associated with activated CD8+ and CD4+ T cells. Conclusions: Eight genes were identified as associated with CRC, among which DBI exhibited a potential protective role, correlating with improved patient survival, enhanced immune activation, and increased responsiveness to immunotherapy. The remaining proteins demonstrated diverse and complex functions within the tumor immune microenvironment, providing novel insights for the development of precision diagnostics and immunotherapeutic strategies.

The causal relationships between body composition and heart failure: A two-sample mendelian randomization study

The objective of this study was to assess the causal relationships between various body composition indicators, including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and specific measures of fat mass (right arm, right leg, trunk, and whole-body fat mass) and fat-free mass, and the risk of heart failure (HF) using a two-sample Mendelian randomization (MR) approach. We used genome-wide significant single nucleotide polymorphisms (SNPs) related to body composition from the UK Biobank, GIANT, and FinnGen as instrumental variables. To estimate causal associations, we applied multiple methods, including inverse variance weighted (IVW), IVW with multiplicative random effects (IVW_mre), MR-PRESSO, and maximum likelihood. The results demonstrated that each standard deviation (SD) increase in BMI (OR = 1.48; 95% CI: 1.37-1.60; P = 1.24E-23), WC (OR = 1.60; 95% CI: 1.45-1.77; P = 1.72E-20), and WHR (OR = 1.25; 95% CI: 1.01-1.54; P = 3.70E-02) was significantly associated with increased HF risk. Comparable associations were observed for fat mass in the right arm (OR = 1.42; P = 6.60E-17), right leg (OR = 1.57; P = 5.80E-18), trunk (OR = 1.31; P = 3.02E-11), and the whole body (OR = 1.34; P = 2.24E-12). Fat-free mass-both whole-body (OR = 1.34; P = 4.77E-10) and regional measurements (right arm, right leg, trunk)-also exhibited positive associations with HF risk. Leave-one-out analyses confirmed the stability of these findings and underscored the significance of multiple body composition indicators in HF risk assessment and prevention.

Analysis of gut microbiota and depression and anxiety: Mendelian randomization from three datasets

BACKGROUND

Emerging evidence supports gut microbiota's association with mental distress, particularly depression and anxiety, the microbiota-gut-brain axis was the believed to be the underlying mechanism. This study investigated the causal relationships between specific gut microbiota and depression and anxiety disorders using large-scale genome-wide association study (GWAS) data.

METHODS

A two-sample bidirectional Mendelian randomization (MR) analysis was conducted to explore the causal effects of 211 microbial taxa on depression and anxiety across three large GWAS databases: FinnGen, Pan-UKBB, and PGC. Sensitive analyses were followed to validate the robustness of results. Random-effect meta-analysis was further performed to enhance the statistical power.

RESULTS

The MR analysis revealed that the Bifidobacteriales (IVW: OR 0.90, 95 %CI 0.83 to 0.98) and Bifidobacteriaceae (IVW: OR 0.90, 95 %CI 0.83 to 0.98) had a protective effect against depression. Clostridiales (cML-MA: OR 0.88, 95 %CI 0.81 to 0.95) and Parasutterella (cML-MA: OR 0.75, 95 %CI 0.64 to 0.88) showed negative associations with depression. Increased abundance of Oxalobacteraceae (cML-MA: OR 1.78, 95 %CI 1.24 to 2.56), Deltaproteobacteria (cML-MA: OR 2.17, 95 %CI 1.38 to 3.40), and Desulfovibrionales (cML-MA: OR 2.22, 95 %CI 1.41 to 3.49) was associated with a higher risk of depression. For anxiety, protective effects were found for Actinobacteria (phylum: IVW: OR 0.83, 95 %CI 0.76 to 0.87; class: IVW: OR 0.84, 95 %CI 0.75 to 0.93), Bifidobacteriales (IVW: OR 0.80, 95 %CI 0.75 to 0.85), Bifidobacteriaceae (IVW: OR 0.80, 95 %CI 0.75 to 0.85) and Bifidobacterium [g] (IVW: OR 0.79, 95 %CI 0.74 to 0.84). Lactobacillaceae [f] (cML-MA: OR 1.18, 95 %CI 1.08 to 1.28), Clostridia [c] (cML-MA: OR 1.15, 95 %CI 0.1.06 to 1.26) and Clostridiales [o] (IVW: OR 1.15, 95 %CI 1.05 to 1.27) were associated with increased anxiety risk. Meta-analysis results indicated significant associations, particularly the protective effects of Actinobacteria (OR 0.90, 95 % CI, 0.83 to 0.98) and Clostridiaceae1 (OR 0.91, 95 % CI, 0.83 to 0.99) on depression and several taxa on anxiety. No significant instrumental variables for depression or anxiety on gut microbiota were identified.

CONCLUSIONS

Our findings highlight specific gut microbiota that are associated with depression and anxiety, underscoring the causal relationships between these intestinal microbes and psychiatric disorders. These results suggest potential strategies for mitigating disease symptoms and improving quality of life through microbiome-targeted therapies. Further studies, including randomized controlled trials and investigations into sex-specific effects, are essential to validate and expand upon these findings.

A latent outcome variable approach for Mendelian randomization using the stochastic expectation maximization algorithm

Mendelian randomization (MR) is a widely used tool to uncover causal relationships between exposures and outcomes. However, existing MR methods can suffer from inflated type I error rates and biased causal effects in the presence of invalid instruments. Our proposed method enhances MR analysis by augmenting latent phenotypes of the outcome, explicitly disentangling horizontal and vertical pleiotropy effects. This allows for explicit assessment of the exclusion restriction assumption and iteratively refines causal estimates through the expectation-maximization algorithm. This approach offers a unique and potentially more precise framework compared to existing MR methods. We rigorously evaluate our method against established MR approaches across diverse simulation scenarios, including balanced and directional pleiotropy, as well as violations of the Instrument Strength Independent of Direct Effect (InSIDE) assumption. Our findings consistently demonstrate superior performance of our method in terms of controlling type I error rates, bias, and robustness to genetic confounding, regardless of whether individual-level or summary data is used. Additionally, our method facilitates testing for directional horizontal pleiotropy and outperforms MR-Egger in this regard, while also effectively testing for violations of the InSIDE assumption. We apply our method to real data, demonstrating its effectiveness compared to traditional MR methods. This analysis reveals the causal effects of body mass index (BMI) on metabolic syndrome (MetS) and a composite MetS score calculated by the weighted sum of its component factors. While the causal relationship is consistent across most methods, our proposed method shows fewer violations of the exclusion restriction assumption, especially for MetS scores where horizontal pleiotropy persists and other methods suffer from inflation.

Revisiting the causal impact of lipid traits on metabolic dysfunction-associated fatty liver disease: Insights from a multidimensional plasma lipid profile

AIMS

Recent advancements in plasma lipidomes genome-wide association studies data have enhanced our understanding of lipid categories, significantly improving risk assessments for metabolic dysfunction-associated fatty liver disease (MAFLD) beyond traditional lipid biomarkers.

MATERIALS AND METHODS

This study utilized Mendelian randomization (MR) to assess the causal relationships between 179 lipid species across 13 subclasses and MAFLD, primarily using the Wald ratio and IVW methods. Corrections were made using false discovery rate (FDR), supplemented by Bayesian colocalization analysis.

RESULTS

Elevated levels of genetically predicted phosphatidylcholine (16:0_16:1) [ORWald ratio = 2.638, 95% CI 1.557-4.469, P = 3.11 × 10-4], phosphatidylcholine (16:1_18:0) (ORWald ratio = 2.644, 95% CI 1.559-4.486, P = 3.11 × 10-4), triacylglycerol (46:2) (ORWald ratio = 2.515, 95% CI 1.524-4.153, P = 3.11 × 10-4), and triacylglycerol (48:2) (ORIVW = 1.863, 95% CI 1.300-2.669, P = 6.95 × 10-4) were significantly associated with increased MAFLD risk, with rs1260326 within the GCKR gene playing a crucial role. Colocalization analysis indicated that in significant evidences, the posterior probability for hypothesis 4 was over 80%, identifying rs780093 as a shared causal variant. Additionally, 16 suggestive evidences were identified.

CONCLUSION

The study confirmed the significant role of specific lipid molecules in influencing MAFLD risk, providing new scientific bases and potential therapeutic targets for future treatment strategies.

Bayesian causal graphical model for joint Mendelian randomization analysis of multiple exposures and outcomes

Current Mendelian randomization (MR) methods do not reflect complex relationships among multiple exposures and outcomes as is typical for real-life applications. We introduce MrDAG, a Bayesian causal graphical model for summary-level MR analysis to detect dependency relations within the exposures, the outcomes, and between them to improve causal effects estimation. MrDAG combines three causal inference strategies. It uses genetic variation as instrumental variables to account for unobserved confounders. It performs structure learning to detect and orientate the direction of the dependencies within the exposures and the outcomes. Finally, interventional calculus is employed to derive principled causal effect estimates. In MrDAG the directionality of the causal effects between the exposures and the outcomes is assumed known, i.e., the exposures can only be potential causes of the outcomes, and no reverse causation is allowed. In the simulation study, MrDAG outperforms recently proposed one-outcome-at-a-time and multi-response multi-variable Bayesian MR methods as well as causal graphical models under the constraint on edges' orientation from the exposures to the outcomes. MrDAG was motivated to unravel how lifestyle and behavioral exposures impact mental health. It highlights first, education and second, smoking as effective points of intervention given their important downstream effects on mental health. It also enables the identification of a novel path between smoking and the genetic liability to schizophrenia and cognition, demonstrating the complex pathways toward mental health. These insights would have been impossible to delineate without modeling the paths between multiple exposures and outcomes at once.

Association between Plasma Metabolite Levels and Myopia: A 2-Sample Mendelian Randomization Study

Purpose

The role of plasma metabolites in myopia is still unclear, and previous studies are limited by various factors and were mostly observational. This study aims to investigate the causal relationship between plasma metabolites and myopia using 2-sample Mendelian randomization (MR).

Design

A 2-sample MR study.

Subjects and Participants

This study analyzed plasma metabolites consisting of 1091 metabolites and 309 metabolite ratios in 8299 individuals from the Canadian Longitudinal Study on Aging cohort. Summary statistics for myopia were obtained from the UK Biobank, encompassing 37 362 cases and 460 536 controls.

Methods

Causal effect estimates were primarily derived using the inverse variance weighting (IVW) method and the constrained maximum likelihood and model averaging-based MR method. Statistical significance for the MR effect estimate was defined as a false discovery rate (FDR) of <0.05. Additionally, we used the MR Steiger directionality test to examine whether exposure was directionally causal for the outcome. Furthermore, 4 supplementary methods were used for analysis: weighted median, MR-Egger, simple mode, and weighted mode.

Main Outcome Measures

Genetic causal association between plasma metabolites and myopia.

Results

The IVW analysis results indicated that elevated levels of 1-arachidonoyl-GPE (20:4n6) (P_FDR = 5.80E-06), linoleoyl-arachidonoyl glycerol (18:2/20:4)[1] (P_FDR = 2.24E-06), and linoleoyl-arachidonoyl-glycerol (18:2/20:4) [2](P_FDR = 0.0242) have a protective effect on myopia. Elevated levels of 4 plasma metabolite ratios, including the phosphate to linoleoyl-arachidonoyl-glycerol (18:2/20:4) [2] ratio (P_FDR = 0.0029), citrulline to dimethylarginine (SDMA + ADMA) ratio (P_FDR = 0.0207), oleoyl-linoleoyl-glycerol (18:1/18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2/20:4) [1] ratio (P_FDR = 0.0230), and retinol (vitamin A) to linoleoyl-arachidonoyl-glycerol (18:2/20:4) [2] ratio (P_FDR = 0.0230), were significantly associated with a higher risk of myopia.

Conclusions

This study provides evidence of a causal relationship between specific plasma metabolites and myopia, highlighting potential therapeutic targets and contributing to the understanding of myopia's etiology. Future research should include diverse populations to enhance the generalizability of these findings.

Financial Disclosures

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Omega-3 Fatty Acids as Protective Factors for Age-Related Macular Degeneration: Prospective Cohort and Mendelian Randomization Analyses

PURPOSE

Epidemiologic studies and clinical trials have reported inconsistent findings regarding omega-3 fatty acids' protective role in age-related macular degeneration (AMD). We investigated their association in a prospective cohort and examined causality using Mendelian randomization (MR) analyses.

DESIGN

Prospective cohort study and 2-sample MR analyses.

PARTICIPANTS

The cohort included 258 350 AMD-free individuals of European descent from the UK Biobank. Mendelian randomization analyses used genome-wide association study data on plasma omega-3 and docosahexaenoic acid (DHA) (UK Biobank, n = 115 006) and AMD (dry, wet, and any; FinnGen, n = 208 690-209 122).

METHODS

Cox regression assessed the association between plasma omega-3 and DHA levels and AMD incidence, adjusting for systemic covariates and AMD polygenetic risk score (PRS). Interaction effects of AMD genetic risk (PRS, complement factor H and age-related maculopathy susceptibility 2 genotypes), and plasma omega-3 and DHA levels were tested. For MR analyses, we used random-effect inverse-variance weighted model as primary, with 5 sensitivity models. Causality was considered significant if P < 0.05 in the primary model and at least 2 sensitivity models.

MAIN OUTCOME MEASURES

Risk of AMD.

RESULTS

Over 12.9 years, 5068 people (1.9%) demonstrated AMD. Higher plasma levels (in millimoles per liter) of omega-3 (hazard ratio [HR], 0.80; 95% confidence interval [CI], 0.72-0.95; P = 0.006) and DHA (HR, 0.65; 95% CI, 0.44-0.96; P = 0.029) were associated with lower risk of receiving an AMD diagnosis. Mendelian randomization showed genetic predisposition to higher plasma omega-3 levels reduced the risk of dry AMD (odds ratio [OR], 0.83; 95% CI, 0.73-0.96; P = 0.010), wet AMD (OR, 0.76; 95% CI, 0.65-0.88; P < 0.001), and any AMD (OR, 0.82; 95% CI, 0.74-0.92; P < 0.001). Similar results were found for plasma DHA levels (wet AMD:OR, 0.79; 95% CI, 0.65-0.96; P = 0.017; any AMD: OR, 0.84; 95% CI, 0.72-0.98; P = 0.030). No significant interaction was found between omega-3 and DHA levels and AMD genetic risk (all P > 0.05).

CONCLUSIONS

Both the prospective and MR analyses suggest omega-3 and DHA may protect against AMD, supporting the need for further clinical trials to test their effectiveness in AMD prevention and treatment.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Unveiling the immunological terrain of pancreatic ductal adenocarcinoma: strategies to prompt immunotherapy from Mendelian randomization

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is challenging to treat due to its immunosuppressive tumor microenvironment (TME) and resistance to immune checkpoint inhibitors. This study aims to discover new therapeutic targets and predictive biomarkers for PDAC.

METHODS

Using Mendelian randomization, we studied causal relationships between PDAC and an array of immune cell traits, bacterial traits, inflammatory factors, and blood metabolites. We employed large genome-wide association study datasets and the two-sample MR approach for the investigation.

RESULTS

Our results highlight suggestive evidence of associations between PDAC and distinct immune cell phenotypes, revealing nuanced alterations across monocytes, T-cells, B-cells, dendritic cells, and myeloid-derived suppressor cells. Our study provides a granular view of the PDAC-immune interface, identifying key immune cell traits and their associations with PDAC. For instance, our findings suggest a detrimental reduction in various monocyte traits, alongside a decrease in B-cell populations. Conversely, certain T-cell subsets showed increased associations, indicating potential targets for immunotherapeutic strategies. The bacterial trait associations, particularly with Collinsella and Ruminococcus torques, highlight the gut microbiome's influence on immune modulation and PDAC pathogenesis. Additionally, the traits concerning Interleukin-12 subunit beta levels and T-cell surface glycoprotein CD5 levels further indicate their function of this complex interaction.

CONCLUSIONS

This study enhances our understanding of PDAC's resistance to immunotherapies and highlights the potential of personalized immunotherapy and metabolic pathway modulation in PDAC treatment. Our findings provide supportive evidence for research and clinical translation.

Migraine and cardiovascular disease: A two-sample Mendelian randomization study

This study investigates the causal association between migraine and cardiovascular disease from a genetic perspective based on the Mendelian randomization analysis (MR) method. Single nucleotide polymorphism (SNPs) loci were used as genetic instrumental variables (IVs) to analyze potential causal relationships between exposure and outcome factors. The causal association between migraine and cardiovascular disease in terms of prevalence was assessed using inverse variance weighted as the primary MR method. Migraine is negatively associated with coronary artery disease (CAD) when migraine is the exposure and CAD is the outcome (OR = 0.0226, 95% CI = 0.0019-0.2639, P = .0024). CAD was negatively associated with migraine when CAD was the exposure and migraine was the outcome (OR = 0.9950, 95% CI = 0.9922-0.9978). No causal association between other cardiovascular diseases and migraine was found. This study demonstrates a negative causal relationship between CAD and migraine.

Immune cell phenotypes as causal factors in liver disease progression revealed by Mendelian randomization

Immune cells are central mediators of the immune response and play critical roles in the pathogenesis and progression of liver diseases. Understanding the specific contributions of immune cells to liver disease progression is essential for developing targeted therapeutic strategies. In this study, we employed a two-sample Mendelian randomization (MR) approach to explore potential causal relationships between peripheral immune cell phenotypes and liver diseases, using genetic instrumental variables from large-scale genome-wide association studies (GWAS). Applying the inverse variance weighted (IVW) methods, we identified that monocyte count(odds ratio (OR) 0.81; 95% confidence interval (CI) 0.74-0.90; P  =  5.95 × 10- 5, PFDR = 3.57 × 10- 4), CD3- lymphocyte/lymphocyte (OR 0.59, 95% CI 0.45-0.79; P  =  3.29 × 10- 4, PFDR = 5.92 × 10- 3) and SSC-A (Side Scatter Area) on Natural Killer (NK) cells (OR 0.89, 95% CI 0.82-0.95; P  =  1.37 × 10- 3, PFDR = 0.0396) acted as protective factors against alcoholic liver disease. Similarly, the trait HLA DR++ monocyte/monocyte was associated with a lower risk of autoimmune hepatitis (OR 0.56, 95% CI 0.41-0.79; P  =  7.42 × 10- 4, PFDR = 0.0475). Conversely, an elevated blood monocytic Myeloid-Derived Suppressor Cells (MDSCs) count was associated with a higher risk of chronic hepatitis (OR 1.23, 95% CI 1.11-1.37; P  =  1.13 × 10- 4, PFDR = 1.58 × 10- 3). Similarly, higher levels of HLA DR on CD14- CD16+ monocyte (OR 0.84, 95% CI 0.78-0.91; P  =  2.07 × 10- 5, PFDR = 1.32 × 10- 3) conferred lower risk for cirrhosis of liver. In hepatic failure, CD39+ resting CD4 regulatory T cell count (OR 0.85, 95% CI 0.79-0.92; P  =  1.70 × 10- 5, PFDR = 5.25 × 10- 3) played a protective role and CD28+ CD45RA- CD8dim T cell/CD8dim T cell (OR 1.14, 95% CI 1.06-1.22; P  =  2.63 × 10- 4, PFDR = 0.0406) exhibited a risk function. Our findings highlight key immune pathways in liver disease progression and underscore potential immunomodulatory targets for future therapeutic interventions. Further research is warranted to clarify the mechanistic underpinnings of these associations.

Pharmacovigilance study and genetic target prediction analysis of FDA adverse event reports (FAERS) for drug-induced sinusitis

BACKGROUND

Drug-induced sinusitis has been widely reported as an adverse drug reaction in recent years, yet the pharmacogenetic mechanisms and risk factors associated with sinusitis remain elusive.

OBJECTIVE

We aimed to identify the major drugs reported in the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) in relation to sinusitis and to analyze their pharmacogenetic mechanisms through drug target analysis.

METHODS

We conducted a review of the publicly available FAERS database from 2004 to the third quarter of 2023. We extracted genetic tools corresponding to each drug, utilized colocalization analysis, Mendelian randomization (MR) analysis, and cross-tissue drug target analysis to predict the impact of drug targets on sinusitis.

RESULTS

Following the validation of drug-related risks, a total of 13 medications were ultimately identified, including TNF inhibitors: pomalidomide (ROR: 14.77), certolizumab pegol(ROR: 8.21), etanercept (ROR: 7.961), lenalidomide (ROR: 6.998), adalimumab (ROR: 6.677), infliximab (ROR: 3.939); C4B-targeted drugs: human immunoglobulin G (ROR:3.846) and other risk drugs were commonly reported. Co-localization analysis and MR analysis suggests associations between TNF, C4B, and LTA and sinusitis.

CONCLUSION

We demonstrated the risk of sinusitis associated with 13 drugs, including pomalidomide, and the impact of TNF and C4B drugs on sinusitis, which provides guidance for the use of related drugs and the prevention of sinusitis.

Unbiased causal inference with Mendelian randomization and covariate-adjusted GWAS data

Mendelian randomization (MR) facilitates causal inference with observational data using publicly available genome-wide association study (GWAS) results. In a GWAS, one or more heritable covariates may be adjusted for to estimate the direct effects of SNPs on a focal trait or to improve statistical power, which may introduce collider bias in SNP-trait association estimates, thus affecting downstream MR analyses. Numerical studies suggested that using covariate-adjusted GWAS summary data might introduce bias in univariable Mendelian randomization (UVMR), which can be mitigated by multivariable Mendelian randomization (MVMR). However, it remains unclear and even mysterious why/how MVMR works; a rigorous theory is needed to explain and substantiate the above empirical observation. In this paper, we derive some analytical results when multiple covariates are adjusted for in the GWAS of exposure and/or the GWAS of outcome, thus supporting and explaining the empirical results. Our analytical results offer insights to how bias arises in UVMR and how it is avoided in MVMR, regardless of whether collider bias is present. We also consider applying UVMR or MVMR methods after collider-bias correction. We conducted extensive simulations to demonstrate that with covariate-adjusted GWAS summary data, MVMR had an advantage over UVMR by producing nearly unbiased causal estimates; however, in some situations it is advantageous to apply UVMR after bias correction. In real data analyses of the GWAS data with body mass index (BMI) being adjusted for metabolomic principal components, we examined the causal effect of BMI on blood pressure, confirming the above points.

Relationships among immune cells, metabolites, and non-small cell lung cancer: a mediation Mendelian randomization study

BACKGROUND

Immune cells and metabolites significantly impact organism health and disease processes. The interaction between non-small cell lung cancer (NSCLC) and metabolites and immune cells remains underexplored.

METHODS

To investigate the causal relationships between immune cells, metabolites, and NSCLC, we used Mendelian randomization (MR). The research design comprehensively embraced the direct correlation and the role that metabolites play as an intermediate in the interaction between NSCLC and immune cells.

RESULTS

MR analysis allowed us to finally identify one immune cell, there was a substantial causal connection between CD64 on CD14⁻CD16⁻ and NSCLC. Furthermore, we discovered four metabolites that showed strong causal links to NSCLC: 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) levels, phenyllactate (PLA) levels in elite athletes, the caffeine to paraxanthine ratio and 1-palmitoyl-2-arachidonoyl-GPC (16:0/20:4n6) levels. Finally, through a two-step MR mediation analysis, we found that CD64 on CD14⁻CD16⁻ mediated the occurrence of NSCLC via 1-palmitoleoyl-2-linolenoyl-GPC (16:1/18:3) levels and the caffeine to paraxanthine ratio, with mediation proportions of - 11.89% and 21.69%, respectively.

CONCLUSION

Our findings show the complicated link between immune cells, metabolites, and NSCLC. The discovered connections and mediating effects provide important insights.

A causal effects of neutrophil extracellular traps and its biomarkers on acute respiratory distress syndrome: a two-sample Mendelian randomization study

Previous studies have indicated an association between neutrophil extracellular traps (NETs) and acute respiratory distress syndrome (ARDS). This study aimed to investigate the potential causal effects of NETs and NETs-related biomarkers on ARDS or vice-versa. A two-sample Mendelian randomization (MR) utilizing genome-wide association studies (GWAS) data was employed to analyze the causality. The primary analysis was conducted using inverse-variance weighted (IVW) methods; weighted median, MR-Egger, and weighted model methods were used to validate the results. Horizontal pleiotropy and outlier detection were assessed via MR-Egger and MR pleiotropy residual sum and outlier (MR-PRESSO), respectively; Cochran's Q test evaluated heterogeneity, while Leave-one-out analyses were used to evaluate the presence of predominant instrumental variables (IVs). IVW method suggested causal associations between genetically predicted IL-13 and a higher risk of ARDS [OR (95%CI) = 1.52 (1.03-2.23), P = 0.047], while there was no causal effect of other factors on ARDS (all P > 0.05). Also, ARDS had no effect on NETs and NETs-related biomarkers (all P > 0.05). Cochran's Q confirmed no significant heterogeneity. MR-Egger regression ruled out horizontal pleiotropy's influence, and MR-PRESSO analysis identified no outliers, reinforcing the study's findings. This MR study established a causal relationship between IL-13 and ARDS, suggesting its potential role as a therapeutic target and biomarker of ARDS. Future work should delve into the underlying mechanisms and clinical applications.

Microbial Influences on Calcium-Phosphorus Homeostasis and Metabolic Bone Diseases: A Bidirectional Mendelian Randomisation Study on the Gut-Bone Axis

Observational studies have shown that the gut microbiota (GM) is associated with bone diseases, particularly calcium-phosphorus metabolic bone diseases, demonstrating the existence of a gut-bone axis. However, whether these associations are causal effects remains to be determined. This study employed bidirectional two-sample Mendelian randomisation (MR) using summary data from Genome-Wide Association Studies (GWAS) of 211 gut microbial taxa and six metabolic bone diseases (osteoporosis, Osteopenia, osteonecrosis, osteomyelitis, hypoparathyroidism and hyperparathyroidism) to explore causal relationships and their directionality. Comprehensive sensitivity analyses were conducted to ensure the robustness of the results, and a false discovery rate-corrected pFDR of < 0.05 was used as a threshold to support strong associations. Additionally, co-localisation analysis was conducted to consolidate the findings. We identified 35 causal relationships between GM and metabolic bone diseases, with 17 exhibiting positive and 18 negative correlations. Furthermore, reverse MR analysis indicated that osteomyelitis was associated with elevated abundance of two GMs (pFDR < 0.05, PP.H4 < 75%). No evidence of horizontal pleiotropy or heterogeneity was observed, and co-localisation analysis further strengthened the evidence for these causal relationships. The study underscores the critical role of GM in influencing bone health through the gut-bone axis, paving the way for future therapeutic interventions targeting the gut-bone axis and offering new directions for research in bone metabolism and diseases.

Effects of different types of milk consumption on type 2 diabetes and the mediating effect of AA: A Mendelian randomization study of East Asian populations

There is currently a lack of research examining the association between the consumption of different dairy products and type 2 diabetes (T2D) in East Asian populations. To address this gap, the present study employs Mendelian randomization to investigate the potential effects of 3 different types of milk consumption (including whole milk, semi-skim milk, and skim milk) on the risk of developing T2D. The results indicate that both whole milk and skim milk are associated with an increased risk of T2D (whole milk: odds ratio [OR] = 1.022, 95% CI: 1.001-1.044; skim milk: OR = 1.023, 95% CI: 1.007-1.039). Mediation analysis revealed that asparagine acts as a mediator between skim milk consumption and T2D, with a mediation effect of 0.003 (95% CI: 0.000 to 0.008), accounting for 14.269% of the total effect.

Risk of gastric cancer in autoimmune gastritis and pernicious anaemia: Insights from Mendelian randomization and multi‐omics analysis

Background

The newly onset debate surrounding the risk of gastric cancer (GC) in autoimmune gastritis (AIG) and pernicious anaemia has intensified. It is necessary to supplement higher level research evidences to settle this issue.

Methods

Two‐sample Mendelian randomization (MR) analysis using inverse variance weighted method was conducted to reveal the causal relationship between pernicious anaemia and GC. Because of the absence of available summary statistics for AIG at present, we used pernicious anaemia as a proxy exposure, as it was frequently used interchangeably. The multi‐omics characteristics of AIG and pernicious anaemia were further explored through proteome‐wide MR, colocalization, and transcriptome sequencing analysis.

Results

MR analysis found pernicious anaemia was causally associated with a higher risk of GC (odds ratio: 1.16, 95% confidence interval [1.03, 1.31], p = .018). Sensitivity analyses confirmed the stability of the results. The up‐regulation of genes involved in gastric dysplasia and carcinogenesis, including receptor activity‐modifying protein 3, fibroblast growth factor 3, transforming growth factor beta‐2 and tumour‐associated calcium signal transducer 2, suggested potential mechanisms underlying the risk of GC in AIG.

Conclusions

These results emphasized the independent link from AIG and pernicious anaemia to GC. Therefore, endoscopy follow‐up for GC screening in AIG is still appealed.

Severe traumatic brain injury and risk for osteoporosis: a Mendelian randomization study

BACKGROUND

The influence of nervous system activity on bone remodeling has been widely reported. Patients with traumatic brain injury (TBI) exhibit a high incidence of osteoporosis (OP). Nevertheless, the relationship between severe TBI (sTBI) and OP remains unclear. We performed Mendelian randomization (MR) analysis to assess the potential causal relationship between sTBI and OP.

METHODS

Data on exposure and outcomes were acquired from genome-wide association studies (GWAS). Data on OP was obtained from UK Biobank (5,266 cases of OP and 331,893 controls). Data on sTBI was obtained from FinnGen Consortium (6,687 cases and 370,590 controls). Single nucleotide polymorphisms (SNPs) that underwent strict screening were regarded as instrumental variables. We used the inverse variance weighted (IVW), constrained maximum likelihood and model averaging (CML-MA), MR-Egger, and weighted median methods for causal effect estimation. To test the reliability of the results, sensitivity analysis was performed using Cochran's Q, leave-one-out, MR-Egger intercept, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) tests.

RESULTS

The IVW analysis indicates that sTBI and OP have a suggestive association (odds ratio [OR] = 1.004, 95% confidence interval [CI] = 1.001,1.007; p = 0.002), and no heterogeneity (Q = 11.536, p = 0.241) or directional pleiotropy was observed (egger_intercept = 7.368 × 10- 5, p = 0.870). The robustness of the results was validated using a leave-one-out sensitivity test.

CONCLUSION

According to the MR analysis, sTBI and OP are likely suggestively related. This finding contributes to the prevention of OP in patients with sTBI and provides genetic evidence supporting the theory that the nervous system regulates bone remodeling.

Assessing causality between mitochondrial-associated proteins with musculoskeletal diseases: A Mendelian randomization study

Musculoskeletal diseases are the leading cause of disability-adjusted life years. Mitochondria, often referred to as the "powerhouses" of cells, are believed to play a role in regulating cellular metabolism and differentiation, potentially influencing the occurrence and progression of musculoskeletal diseases. However, the exact causal relationships remain to be defined. This study aimed to investigate the causal relationships between mitochondrial biological functions and musculoskeletal diseases (including osteoarthritis (OA), osteoporosis, rheumatoid arthritis (RA), and ankylosing spondylitis through Mendelian randomization (MR) analysis). We systematically summarized data related to mitochondrial functional proteins and musculoskeletal diseases from the IEU OpenGWAS and UK Biobank databases. We used single nucleotide polymorphisms significantly associated with musculoskeletal diseases as instrumental variables. The inverse variance weighting method performed the main MR analysis. We used Mendelian randomized residual sum of pleiotropy and outliers, MR-Egger regression, Cochran Q statistic, Rucker Q statistic, Radial-MR, weighted median, simple mode, weighted mode, and leave-one-out analysis methods as supplementary analyses. First, 14 positive mitochondrial functional proteins were screened out. After Bonferroni correction, COA3 and COX4I2 were found to be causally related to OA and act as protective factors. We identified a causal relationship between SLC25A18 and RA as a risk factor. This study provides genetic support and offers new evidence regarding the roles of COA3, COX4I2, and SLC25A18 in the pathophysiology of OA and RA. This study paves the way for a deeper understanding of the pathological mechanisms of musculoskeletal diseases and provides information for their prevention strategies and treatments.

Revealing the Causal Relationship Between Differential White Blood Cell Counts and Depression: A Bidirectional Two-Sample Mendelian Randomization Study

Background: The link between white blood cells (WBC) and depression has been studied, but the causal relationship remains unclear. This study aimed to elucidate the potential bidirectional causal links between six specific WBC count features and depression using a two-sample Mendelian randomization (MR) analysis, leveraging summary statistics from genome-wide association studies (GWAS). Method: The dataset on depression (N = 406,986) was sourced from the FinnGen database, while the dataset on WBC (N = 563,085) was obtained from a combined dataset of Blood Cell Consortium (BCX) and UK Biobank. The MR analyses employed include inverse variance weighted (IVW), MR-Egger, weighted median, contamination mixture method (conmix), and constrained maximum likelihood-based Mendelian randomization (cML-MA). A threshold p < 0.05 after false discovery rate (FDR) correction was set as the criterion for causality based on IVW. Results: Reverse MR analysis indicated a causal relationship where depression leads to an increase in overall WBC count (IVW beta = 0.031, p = 0.015, p FDR = 0.044) and specifically in basophil count (IVW beta = 0.038, p = 0.006, p FDR = 0.038), with a marginally significant impact on lymphocyte count (beta = 0.029, p = 0.036, p FDR = 0.071). Furthermore, forward MR analysis suggested a potential role of monocyte count in decreasing depression risk (p = 0.028), though this association did not retain statistical significance after FDR correction. Conclusion: These findings suggest that depression may causally influence the immune system by elevating overall WBC and basophil counts, with a marginally significant increase in lymphocyte levels. Conversely, higher monocyte count might confer some protection against depression, albeit with less statistial certainty. This study provides novel insights into the complex interplay between depression and immune function.

Effects of different types of milk consumption on Crohn's disease and the mediating effects of amino acids: A Mendelian randomization study

Dietary therapy is a common adjunctive treatment for Crohn's disease (CD). However, previous studies have presented conflicting views on whether dairy products should be included in dietary therapy. This controversy may be due to confounding factors. Thus, this study employed Mendelian randomization to investigate the effects of consumption of 6 different dairy products on CD. In addition, the mediating effects of 8 amino acids were explored. Three sensitivity analysis methods were employed to exclude horizontal pleiotropy and heterogeneity, ensuring the robustness of the conclusions. Ultimately, the study found that whole milk consumption can reduce the risk of CD (odds ratio = 0.504, 95% CI: 0.324-0.784). Mediation analysis demonstrated that serum isoleucine (mediation effect: -0.265, 95%CI: -0.533 to -0.068) and valine (mediation effect: -0.083, 95%CI: -0.198 to -0.002) are influenced by full-cream milk and modulate the onset of CD, with mediation effects accounting for 38.685% and 12.083%, respectively.

Genetically Predicted Frailty Index Is Associated With Increased Risk of Multiple Metabolic Diseases: 175 226 European Participants in a Mendelian Randomization Study

BACKGROUND

A relationship between frailty index (FI) and metabolic diseases (MDs) has been reported in previous observational studies. However, the causality between them remains unclear. This study aimed to examine the causal effect of FI on MDs.

METHODS

We performed a bidirectional two-sample Mendelian randomization (MR) study. A recent large-scale genome-wide association study (GWAS) provided available data associated with FI, and summary statistics on eight MDs were collected from the IEU OpenGWAS database. Inverse variance weighted (IVW) was used as the main analysis to estimate causal effects, together with MR pleiotropy residual sum and outlier (MR-PRESSO), MR-Egger, Cochran's Q test, pleiotropy test, leave-one-out method, and MR Steiger analysis were used in the sensitivity analyses.

RESULTS

Our MR study demonstrated for the first time that elevated FI was causally associated with an increased risk of MDs including obesity (odds ratio [OR] = 1.78; 95% confidence interval [CI]: 1.17-2.70; p = 0.0075), T2DM (OR = 1.67; 95% CI: 1.24-2.24; p = 6.95 × 10-4), gout (OR = 2.45; 95% CI: 1.29-4.64; p = 0.006), hypothyroidism (OR = 1.96; 95% CI: 1.47-2.60; p = 3.47 × 10-6), and HTN (OR = 2.17; 95% CI: 1.72-2.74; p = 5.25 × 10-11). However, no causal association was found between FI and osteoporosis, vitamin D deficiency, and hyperthyroidism.

CONCLUSIONS

Our findings support a causal relationship between FI and multiple MDs. This is crucial for the prevention of associated MDs in patients with frailty.

Association between sex steroid hormones and α-klotho: Results from the NHANES 2013-2016 and Mendelian randomization study

PURPOSE

This study aimed to explore the association and causal links between sex steroid hormones and the anti-aging protein α-Klotho, extending to investigate the mediation effects of potential mediators.

METHODS

Based on data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016, this study performed weighted multivariable-adjusted logistic regression to evaluate the association between sex steroid hormones and α-Klotho. Then, utilizing summary data from genome-wide association studies (GWAS), a bidirectional two-sample Mendelian randomization (MR) was conducted to assess the causal relationship between sex steroid hormones and α-Klotho. Finally, mediation analysis was conducted to delineate the influence of five identified potential mediators on the sex steroid hormones-α-Klotho association.

RESULTS

In men, significant positive correlations with α-Klotho were consistent across both unadjusted and fully adjusted models for total testosterone (TT), bio-available testosterone (Bio-T), estradiol (E2) and sex hormone-binding globulin (SHBG) (Model 3: TT: β = 3.54, 95 % CI: 1.63-5.44, P = 0.0003; Bio-T: β = 1.74, 95 % CI: 0.73-2.74, P = 0.0007; E2: β = 0.25, 95 % CI: 0.11-0.38, P = 0.0003; SHBG: β = 0.95, 95 % CI: 0.63-1.27, P < 0.0001); In premenopausal women, we detected a potential nonlinear relationship between TT levels and α-Klotho, with α-Klotho levels rising to a peak at a TT level of 72.2 ng/mL, after which they declined. Furthermore, results from MR analyses reaffirmed positive associations of TT and Bio-T with α-Klotho in men (TT: β = 3.54, 95 % CI: 1.63-5.44, P = 0.0003; Bio-T: β = 1.74, 95 % CI: 0.73-2.74, P = 0.0007). Finally, significant mediation effects were observed for uric acid (β = 0.27, 95 % CI: 0.15-0.67, P < 0.0001) and creatinine (β = 0.05, 95 % CI: 0.01-0.16, P = 0.0060), accounting for 26.7 % and 5.23 % of the total mediation effect, respectively.

CONCLUSION

In conclusion, our results demonstrate that both TT and Bio-T enhance the expression of α-Klotho in men. The positive association observed may be partly mediated by uric acid and creatinine.

Genetic colocalization of cathepsins H, D, and L1 with Alzheimer's disease: Implications for biomarker and therapeutic target discovery

BackgroundCathepsins, a family of lysosomal proteases, have been implicated in Alzheimer's disease (AD) pathogenesis through their involvement in amyloid-β protein precursor processing and neuroinflammation. However, the specific roles of different cathepsins in AD remain unclear.ObjectiveThis study aimed to investigate the genetic associations and potential causal relationships between cathepsins and AD, using Mendelian randomization (MR) to explore their roles as biomarkers and therapeutic targets.MethodsA two-sample MR analysis was conducted using genome-wide association study data for AD and cathepsins. Genetic variants associated with cathepsin expression were used as instrumental variables. Forward MR assessed the causal effect of cathepsins on AD, while reverse MR explored the impact of AD on cathepsin levels. Colocalization analysis was performed to identify shared genetic variants between cathepsins and AD.ResultsCathepsin H was significantly associated with an increased risk of AD (p = 0.0034, OR = 1.04), with consistent results across multiple MR methods. Colocalization analysis revealed a significant genetic overlap between Cathepsin L1 and AD (PP.H4 = 100%), suggesting a shared genetic basis.ConclusionsCathepsin H may be a potential risk factor for AD, while Cathepsin L1 shows promise as a therapeutic target and biomarker due to its genetic overlap with AD. Further research is needed to explore the mechanisms by which these cathepsins influence AD progression and to assess their therapeutic potential in diverse populations.

Causal Associations of Gut Microbiota Species With Lymphoma: A Two-Sample Mendelian Randomization Study

This study aims to focus on GM at species level, exploring the causal associations with different kinds of lymphoma to provide some information on potential intervention directions in lymphoma. Data of GM taxa were extracted from the genome-wide association study conducted by the MiBioGen and Dutch Microbiome Project (DMP), and those of lymphomas were obtained from the FinnGen consortium. Inverse variance weighted (IVW) method and Bonferroni multiple correction were utilized to assess the causal associations of GM species with different kinds of lymphoma. The effect size was expressed by odds ratios (ORs) with 95% confidence intervals (CIs). Reverse causal association analysis has also been performed. Additionally, scatter plots and leave-one-out test were conducted for sensitivity analysis. After correction, the IVW estimates suggested that elevated relative abundance of species Faecalibacterium_prausnitzii had a negatively causal association with increased odds of Hodgkin's lymphoma (HL) (OR = 0.584, 95% CI: 0.516-0.662). Relative abundance of species Gordonibacter_pamelaeae, Holdemania_filiformis, Sutterella_wadsworthensis and Coprococcus_sp_ART55_1 was negatively associated with follicular lymphoma (FL) odds, whereas that of species Bifidobacterium_catenulatum and Coprococcus_comes were positively associated with FL odds (all p < 0.05). Relative abundance of species Akkermansia_muciniphila and Coprococcus_sp_ART55_1 had a negatively causal association with non-follicular lymphoma (NFL) odds, respectively, while that of Bacteroides_uniformis had a positive one (all p < 0.05). Relative abundance of species Flavonifractor_plautii was negatively linked to diffuse large B-cell lymphoma (DLBCL) risk (OR = 0.471, 95% CI: 0.344-0.645). Relative abundance of species Eggerthella_unclassified was positively associated with T/NK cell lymphoma (TNK) risk while that of Ruminococcus_lactaris was negatively associated with TNK risk (all p < 0.05). Elevated relative abundance of Parabacteroides_unclassified was associated with higher risk of non-Hodgkin's lymphoma (NHL) (OR = 1.955, 95% CI: 1.654-2.312). The relative abundance of species Holdemania_filiformis was negatively associated with mantle cell lymphoma (MCL) risk (OR = 0.637, 95% CI: 0.544-0.746). The relative abundance of species Rothia_mucilaginosa and Lachnospiraceae_bacterium_3_1_46FAA had positively causal association with marginal zone lymphoma (MZL) risk, while that of species Alistipes_senegalensis had a negative one (all p < 0.05). This study identified 16 GM species that have potential causal associations with different kinds of lymphoma, which provided some new idea for further exploration on prevention and treatment targets in lymphoma.

The causal association between plasma caffeine and frailty: A two-sample mendelian randomization study

BACKGROUND

Frailty is one of the most common and challenging consequences of aging, which negatively affects older adults, their families, and society. Caffeine has been shown to be associated with a reduced risk of frailty by observational studies, yet its causal relationship with frailty remains to be tested using more robust methods.

AIMS

This study aimed to explore the causal association between plasma caffeine and frailty using a two-sample Mendelian Randomization (MR) analysis.

METHODS

Single nucleotide polymorphisms related to plasma caffeine concentrations were selected as instrumental variables. Data on the Frailty Index (FI) were sourced from the UK Biobank and TwinGen meta-analysis (n = 175,226), while data on the Fried Frailty Score (FFS) were obtained from the UK Biobank (n = 386,565). The causal association between plasma caffeine levels and frailty was tested using five MR methods, with the inverse-variance weighted method as the primary approach.

RESULTS

Our results consistently showed significantly negative associations between genetically predicted plasma caffeine with FI (β = -0.050, 95 % CI:0.077 to -0.023, P < 0.001) and FFS (β = -0.049, 95 % CI:0.064 to -0.034, P < 0.001). These results remained robust in further sensitivity analyses using a leave-one-out approach.

CONCLUSION

Our findings confirm a causal relationship between plasma caffeine and frailty and suggest that increasing plasma caffeine levels may help prevent and reduce the risk of frailty.

Exploring The Causal Relationship Between Lipid Profiles and Colorectal Cancer Through Mendelian Randomization: A Multidimensional Plasma Lipid Composition Perspective

Background: The causal relationship between blood lipids and colorectal cancer (CRC) risk has been preliminarily explored in previous Mendelian randomization (MR) studies, but these investigations were limited to conventional or partial metabolic lipid profiles. Recent advancements in genome-wide association studies of plasma lipidomics have expanded our understanding of lipid categories, underscoring the need to evaluate the causal associations between a broader range of lipid types and CRC risk to enhance risk assessment. Methods: This MR study utilized 179 lipid phenotypes across 13 lipid classes to investigate their causal associations with CRC risk. Genetic variants significantly associated with lipid traits at the genome-wide level (P<5×10-8) were used as instrumental variables for MR analysis. Initial analyses were conducted using a discovery dataset (n=321,040), followed by validation in an independent replication dataset (n=185,616). Meta-analysis was then employed to determine the strength of causal evidence. The inverse-variance weighted (IVW) method and Wald ratio were the primary MR approaches, complemented by up to nine methods for multidimensional validation. Sensitivity analyses included tests for pleiotropy, heterogeneity, Steiger directionality, and Bayesian colocalization analysis, among others. Results: After Bonferroni correction and rigorous validations, 9 significant causal associations were identified. Specifically, genetically predicted levels of sterol ester (27:1/20:5) (ORIVW = 1.214, 95% CI 1.119-1.317), phosphatidylcholine (20:4_0:0) (ORIVW = 1.147, 95% CI 1.077-1.222), phosphatidylcholine (16:0_22:4) (ORIVW = 1.312, 95% CI 1.170-1.472), phosphatidylcholine (16:0_22:5) (ORIVW =1.181, 95% CI 1.093-1.277), and phosphatidylcholine (18:0_20:5) (ORIVW = 1.198, 95% CI 1.104-1.300) were significantly associated with an increased risk of CRC. Conversely, levels of phosphatidylcholine (18:1_20:2) (ORIVW = 0.832, 95% CI 0.771-0.898), phosphatidylethanolamine (18:2_0:0) (ORIVW = 0.804, 95% CI 0.732-0.882), phosphatidylcholine (16:0_18:0) (ORWald ratio = 0.611, 95% CI 0.481-0.777), and phosphatidylcholine (O-18:1_18:2) (ORWald ratio = 0.723, 95% CI 0.620-0.840) were significantly associated with a decreased risk of CRC. Colocalization analysis revealed posterior probabilities for hypothesis 4 exceeding 90%, identifying rs174546 and rs28456 as shared causal variants. Additionally, 14 suggestive causal associations were observed. Conclusions: This study establishes a causal link between specific lipid species and CRC risk. These findings suggest new avenues for CRC prevention and treatment strategies.

SFRP2 mediates Epstein-Barr virus and bladder cancer risk: a Mendelian randomization study and colocalization analysis

Studies suggest a possible association between Epstein-Barr virus (EBV) infection and bladder cancer (BCa) risk, though this remains unclear. Secreted frizzled-related protein (sFRP) is also linked to BCa, with some DNA viruses potentially regulating its expression. This study used Mendelian randomization (MR) and colocalization analysis to explore the causal relationship between EBV infection, BCa risk, and the mediating role of sFRP. We first performed a two-sample MR study to assess the causal relationship between 5 EBV-related antibodies (AEB-IgG, EA-D, EBNA-1, VCA-p18, ZEBRA) and BCa using the Finnish Consortium's R11 dataset, validated with R10. Reverse MR analysis followed. For significant results, multivariable MR (MVMR) was applied to adjust for confounding risk factors. A two-step MR explored the potential mediating role of 3 sFRPs (sFRP1, sFRP2, sFRP3) between positive exposures and BCa. Colocalization analysis were conducted for positive exposures, mediators, and BCa, with multiple sensitivity analyses confirming the robustness of the results. The two-sample Mendelian randomization study found that EBNA-1 (OR = 1.15, 95% CI: 1.01-1.30; p = 0.039) and VCA-p18 (OR = 1.36, 95% CI: 1.13-1.64; p = 0.001) may increase BCa risk, with only VCA-p18 (P_fdr = 0.006) showing a significant effect after False Discovery Rate (FDR) correction. The Finnish Consortium R10 replication study yielded similar results, and reverse MR analysis did not suggest reverse causality. After MVMR adjusted for relevant confounders, VCA-p18 (OR = 1.40, 95% CI: 1.13-1.74; p = 0.002) still significantly increased BCa risk. Two-step MR identified sFRP2 as a mediator, with VCA-p18 down-regulating sFRP2 expression to elevate BCa risk. Colocalization analysis suggested a shared causal variant (nearby gene HLA-DQA1) between VCA-p18 and BCa (PPH4 = 65.44%). Multiple sensitivity analyses confirmed the robustness of the results. Our study suggests that EBV infection (VCA-p18 antibody) may increase the risk of BCa by lowering sFRP2 levels. Additionally, EBNA-1 antibodies may also contribute to an elevated risk of BCa. We hope these findings will provide new insights for future research on the association between EBV and BCa.

Multilayer analysis of ethnically diverse blood and urine biomarkers for breast cancer risk and prognosis

Breast cancer (BC) is one of the most common malignancies among women globally, characterized by complex pathogenesis involving various biomarkers present in blood and urine. To enhance understanding of the genetic associations between biomarkers and BC via multidimensional, cross ethnic investigations. Based on GWAS data of 35 blood and urine biomarkers from European populations, we adopted multiple analysis strategies including univariable Mendelian randomization (MR) analysis, reverse MR analysis, sensitivity analysis and multivariate MR to identify potential biomarkers associated with BC risk and survival. Our initial analysis included 122,977 BC and 105,974 controls of European ancestry. Building upon these findings, we conducted cross ethnic validation by applying the same analyses to East Asian populations using data from the IEU GWAS database, which included 5,552 BC and 89,731 controls. This step allowed us to investigate the universality and heterogeneity of our identified biomarkers across different ancestries. Subsequently, utilizing clinical laboratory detection data from multiple regions in China, we performed differential analyses and survival assessments on these potential biomarkers to evaluate their clinical relevance and utility. Notably, we leveraged Luzhou's clinical data to integrate HDL-C with conventional tumor markers (CEA, CA125, CA153) into a machine learning model, comparing its diagnostic efficacy against tumor marker combination. Our study validated associations of ALP, HDL-C, TG, SHBG, and IGF-1 with BC risk, reinforcing the reliability of these findings. Moreover, notable interethnic disparities emerged in the association between HDL-C and BC risk, where in HDL-C demonstrates a contrasting role: acting as a genetic protective agent against BC and suggesting promise as an auxiliary diagnostic marker in East Asian populations, yet inversely, it serves as a genetic dangerous predictor in European populations. Analyzing BC subtypes, we identified associations of HDL-C, TG, SHBG, and CRP with ER+BC, while ER-BC showed associations with GLU, urinary creatinine and microalbuminuria, underscoring subtype-specific genetic characteristics critical for personalized prevention and treatment strategies. Overall, this comprehensive study, by traversing the intricate landscape of genetic associations across ethnic boundaries and employing advanced analytical methodologies, not only uncovers the complex interplay between key biomarkers and BC susceptibility but also highlights the significance of ethnic-specific differences in the role of HDL-C. By enhancing the diagnostic power of a tailored biomarker panel through machine learning, this study contributes to the advancement of precision medicine in BC, offering strategies tailored to the unique genetic profiles and biomarker patterns across diverse populations.

Genetic evidence identifies a causal relationship between EBV infection and multiple myeloma risk

BACKGROUND

Previous observational studies have suggested a potential association between Epstein-Barr virus (EBV) infection and the development of multiple myeloma (MM), but this relationship is not clear. Therefore, we conducted a systematic Mendelian randomization (MR) analysis to investigate the causal relationship between EBV infection and the risk of MM, while exploring the possible mediating role of immune cells in this association.

METHODS

The study first conducted a two-sample MR analysis using the MM R11 dataset from the FinnGen Consortium to evaluate the causal relationship between five EBV infection-related antibodies (AEB-IgG, EA-D, EBNA-1, VCA-p18, and ZEBRA) and MM, with validation in the MM R10 dataset. A reverse MR analysis was then performed. For significant results, multivariable MR (MVMR) was used to adjust for the effects of confounding risk factors. Next, a two-step MR mediation analysis was applied to investigate the potential mediating role of 731 immune cell types between positive exposure and MM. Multiple sensitivity analyses were conducted to assess the robustness of the findings.

RESULTS

A two-sample MR study found that EBNA-1 antibodies (OR = 1.36, 95% CI: 1.06-1.73; P = 0.015) were associated with an increased risk of MM, with similar results observed in the FinnGen Consortium R10 replication study. Although the association did not remain statistically significant after false discovery rate (FDR) adjustment (P_fdr = 0.075), further adjustment for relevant confounders using multivariable MR (MVMR) demonstrated that EBNA-1 antibodies (OR = 1.33, 95% CI: 1.01-1.75; P = 0.041) were still significantly associated with an increased risk of MM. Reverse MR analysis indicated no causal effect of MM on EBV-related antibodies. A two-sample MR analysis involving 731 immune cell phenotypes identified 27 potential mediating cell types. Ultimately, two-step MR confirmed that HLA-DR on myeloid dendritic cells (HLA-DR⁺ mDC) serves as a mediating factor, with EBNA-1 antibodies downregulating HLA-DR⁺ mDC, thereby increasing MM risk. Multiple sensitivity analyses supported the robustness of these findings.

CONCLUSION

The findings of this study suggest that EBNA-1 antibodies may increase the risk of MM by downregulating HLA-DR⁺ mDC. This indicates that chronic EBV infection may contribute to an elevated risk of MM. We hope these results provide new insights for future research on the prevention and treatment of MM.

Genetically predicted inflammatory proteins mediate the association between gut microbiota and renal cell carcinoma

BACKGROUND

Studies have indicated a potential relationship between gut microbiota and renal cell carcinoma. However, the causal relationship between various types of gut microbiota and renal cell carcinoma, as well as the role of inflammatory protein as mediators, remains unclear.

METHODS

This study aimed to identify the relationship between gut microbiota, inflammatory protein, and renal cell cancer through a large-scale genome-wide association study (GWAS) utilizing pooled data. We employed Mendelian randomization (MR) to investigate the causal relationship among these variables. Inverse variance weighting (IVW) was utilized as the primary statistical method. Furthermore, we examined the mediating role of inflammatory protein in the pathway through which gut microbiota influences the development of renal cell cancer.

RESULTS

The analysis revealed 12 positive causal relationships and 15 negative causal relationships between the genetic liability of gut microbiota and renal cell cancer. Furthermore, there were three positive causal relationships and one negative causal relationship between inflammatory proteins and renal cell cancer. There were two axes of relationships in which gut microbiota promote the development of renal cell cancer. through inflammatory proteins acting as mediators.

CONCLUSIONS

Gut microbiota and inflammatory protein were causally related to renal cell cancer, and inflammatory protein were intermediary factors in the pathway between gut microbiota and renal cell cancer.

Insomnia and Female Reproductive Diseases: A Cross-Sectional and Mendelian Randomization Study

Background

Insomnia is increasingly emerging as a significant concern in public health, with a longstanding emphasis on its relationship with overall well-being. Nevertheless, few research has been devoted to investigating the relationship between insomnia and female reproductive health.

Methods

In our study, we conducted a Mendelian randomization (MR) study to estimate the causal relationship between insomnia and female reproductive diseases. A total of 268 independent genetic variants associated with insomnia at the genome-wide significance level (P < 5×10-8) were used as instrumental variables. Summary-level data were obtained from the UK Biobank and Finn Gen study, including ovarian cysts, polycystic ovarian syndrome (PCOS), endometriosis, premature ovarian insufficiency (POI), ovarian cancer (OC), uterine fibroids, endometrial cancer (EC) and female infertility. We performed logistic regression to assess the associations between insomnia and the risk of OC and EC by using data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014.

Results

Our research reveals that genetic liability to insomnia constitutes a risk factor for ovarian cysts (odds ratio [OR]: 1.44, 95% confidence interval [CI]: 1.21-1.72, P< 0.05), PCOS (OR: 1.67, 95% CI: 1.44-1.94, P< 0.05), and endometriosis (OR: 1.43, 95% CI: 1.16-1.76, P< 0.05). However, we found no statistically significant associations between insomnia and POI, OC, uterine fibroids, EC, or female infertility. Additionally, body mass index (BMI) was found to mediate about 10% of the effect of the insomnia on ovarian cysts and PCOS. Moreover, in cross-sectional study, insomnia was not associated with OC and EC.

Conclusion

Our study provides causal evidence that genetically predicted insomnia increases the risk of ovarian cysts, PCOS, and endometriosis. Accordingly, the potential significance of weight control and good sleep in keeping fit need to be emphasized.

Rheumatoid arthritis and risk of hearing impairment: A genetic correlation and bidirectional Mendelian randomization study

Prior research has indicated a connection between rheumatoid arthritis (RA) and hearing impairment (HI), although there is disagreement among researchers. An extensive assessment of the causal relationship between RA and HI was the aim of this Mendelian randomization (MR) study. We examined summary-level data from RA and HL genome-wide association studies using inverse variance weighted (IVW) analysis. We further supplemented the results with weighted median (WM), MR-Egger, MR-RAPS, and maximum likelihood techniques. We used sensitivity analyses to check the accuracy of the MR analysis results. Genetically, higher RA substantially increases the likelihood of HI (IVW: P = 8.78 × 10-03, odds ratio (OR) = 1.014, 95% confidence interval (CI): 1.003-1.024). Sensitivity analysis reveals a consistent direction of the association using the following methods: Bayesian MR (P = 8.72 × 10-03, OR = 1.014, 95% CI: 1.004-1.025), MR robust adjustment profile score (P = 2.31 × 10-02, OR = 1.013, 95% CI: 1.002-1.024), maximum likelihood method (P = 2.70 × 10-02, OR = 1.014, 95% CI: 0.996-1.026), WM (P = 1.35 × 10-01, OR = 1.012, 95% CI: 0.996-1.029), and MR-Egger (P = 1.41 × 10-01, OR = 1.011, 95% CI: 0.996-1.027). Despite not achieving statistical significance, the WM and MR-Egger approaches offered reliable guidance. Moreover, we replicated our results on other datasets and obtained similar results (IVW: P = 8.71 × 10-03, OR = 1.016, 95% CI: 1.004-1.028), indicating the validity of our results. Our study provides evidence linking RA to a higher risk of HI. In order to gain more insight into treatments that change the disease or prevent hearing loss, audiological testing is necessary for the diagnosis and follow-up of individuals with RA.

Causal role of plasma liposome in diabetic retinopathy: mendelian randomization (MR) study

BACKGROUND

Research indicates that there may be an association between plasma lipidome levels and the incidence of diabetic retinopathy (DR) in patients. However, the potential causality of this relationship is yet to be determined. To investigate this matter further, we employed a two-sample Mendelian randomization (MR) analysis to comprehensively assess the causality between lipidome levels and DR.

METHODS

Summary statistics for lipid levels and DR were obtained from the Genome-Wide Association Studies (GWAS) Catalog database and the FinnGen Consortium, respectively. We conducted a two-sample MR analysis, and statistical analysis were performed using the inverse variance weighted (IVW) with the addition of the MR-Egger, weighted median (WM), constrained maximum likelihood and model averaging (cML-MA) to test for causal associations between lipid levels and DR. Heterogeneity was checked using Cochran's Q statistic. The MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) global test and the MR-Egger regression were used to detect horizontal pleiotropy. The robustness of our findings was assessed using leave-one-out and funnel plots. To further assess the reliability of the results, linkage disequilibrium score regressions, colocalization analysis and reverse MR analysis were also performed.

RESULTS

Analysis of the pooled MR results and after correction for the false discovery rate (FDR) revealed that five lipid levels were associated with DR risk. Phosphatidylcholine (16:0_16:0) levels [OR = 0.869 (0.810 to 0.933), Pfdr = 0.006], phosphatidylcholine (16:0_20:2) levels [OR = 0.893 (0.834 to 0.956), Pfdr = 0.043] and phosphatidylethanolamine (18:0_20:4) levels [OR = 0.906 (0.863 to 0.951), Pfdr = 0.006] were protective against DR, whereas sphingomyelin (d36:1) levels [OR = 1.120 (1.061 to 1.183), Pfdr = 0.006], and sphingomyelin (d40:1) levels [OR = 1.081 (1.031 to 1.134), Pfdr = 0.043] were associated with a greater risk of DR. Further sensitivity analysis did not reveal heterogeneity or horizontal pleiotropy.

CONCLUSION

In summary, genetic evidence suggests a causal relationship between the levels of specific lipid levels and DR. These findings may provide valuable insights into the causal relationships between lipid levels and DR, potentially informing future prevention and treatment strategies.

Exploring the Relationship Between Sporadic Creutzfeldt-Jakob Disease and Gut Microbiota Through a Mendelian Randomization Study

Observational studies have shown gut microbiota changes in sporadic Creutzfeldt-Jakob disease patients, but the causal relationship remains unknown. We aimed to determine any causal links between gut microbiota and this prion disease. Using Mendelian randomization analysis, we examined the causal relationship between gut microbiota composition and sporadic Creutzfeldt-Jakob disease. Data on gut microbiota (N = 18,340) and disease cases (5208) were obtained. Various analysis methods were used, including inverse variance weighted, Mendelian randomization-Egger, weighted median, simple mode, and weighted mode. In addition, MR-PRESSO was used to evaluate horizontal pleiotropy and detect outliers. Pleiotropy and heterogeneity were assessed, and reverse analysis was conducted. Negative associations were found between sporadic Creutzfeldt-Jakob disease and family Defluviitaleaceae, family Ruminococcaceae, genus Butyricicoccus, genus Desulfovibrio, and genus Eubacterium nodatum. Genus Lachnospiraceae UCG010 showed a positive correlation. Reverse analysis indicated genetic associations between the disease and decreased levels of family Peptococcaceae, genus Faecalibacterium, and genus Phascolarctobacterium, as well as increased levels of genus Butyrivibrio. No pleiotropy, heterogeneity, outliers, or weak instrument bias were observed. This study revealed bidirectional causal effects between specific gut microbiota components and sporadic Creutzfeldt-Jakob disease. Certain components demonstrated inhibitory effects on disease pathogenesis, while others were positively associated with the disease. Modulating gut microbiota may provide new insights into prion disease therapies. Further research is needed to clarify mechanisms and explore treatments for sporadic Creutzfeldt-Jakob disease.

Genetically Predicted Vascular Proteins and Risk of Intracranial Aneurysms: A Mendelian Randomization Study

The relationship between vascular proteins (VPs) and intracranial aneurysms (IAs) has not been fully elucidated. We used Mendelian randomization (MR) analysis to explore the effect of VPs on IAs. Dataset of aneurysmal subarachnoid hemorrhage (aSAH) [5140 cases and 71,934 controls] and unruptured intracranial aneurysm (uIA) [2070 cases and 71,934 controls] were obtained from individuals of European ancestry. Univariate MR was used to explore the associations between 90 VPs and IAs. Then, we performed multivariate MR (MVMR) to further investigate the identified VP-to-IA estimates. Two-sample MR showed that TNFSF14 was inversely associated with aSAH (odds ratio [OR] = 0.831, 95% CI: 0.713-0.969, p = 0.018). IL-16 (OR = 1.218, 95% CI: 1.032-1.438, p = 0.020) and AgRP (OR = 1.394, 95% CI: 1.048-1.855, p = 0.023) were positively associated with aSAH. HBEGF (OR = 0.642, 95% CI: 0.461-0.894, p = 0.009), MCP-1 (OR = 1.537, 95% CI: 1.007-2.344, p = 0.046), and CX3CL1 (OR = 0.762, 95% CI: 0.581-0.999, 0.049 < p < 0.050) were associated with uIA risk. The MVMR showed that the TNFSF14-to-aSAH estimate remained statistically significant after adjustment for past tobacco smoking, alcohol consumption, systolic blood pressure and body mass index. Our study indicated that low serum TNFSF14 levels might be a potential risk factor for IA rupture. Five VPs (HBEGF, MCP-1, IL-6, CX3CL1, and AgRP) are associated with the risk of IAs (both uIA and aSAH).

Effect of different types of milk consumption on Gout and the mediating effect of branched chain amino acids (BCAAs): a Mendelian randomization study

Numerous studies have shown that dietary factors can reduce the risk of developing gout, while changes in serum amino acids also impact gout risk. However, current research lacks insights into how dairy products with varying fat content influence serum amino acids and gout risk, as well as the mediating effects of amino acids. This study employed Mendelian randomization (MR) to analyze the association between 3 milk consumption phenotypes with different fat contents and gout. We found that only whole milk was associated with a reduced risk of gout, whereas no association was observed with the other 2 milk types. Subsequent mediation analysis revealed that isoleucine played a mediating role, with a mediation effect of -0.198 (95% CI: -0.354 to -0.072), accounting for 66.32% of the total effect, and the mediation effect was significant (P = 0.006).

Genetic variation reveals the therapeutic potential of BRSK2 in idiopathic pulmonary fibrosis

BACKGROUND

Current research underscores the need to better understand the pathogenic mechanisms and treatment strategies for idiopathic pulmonary fibrosis (IPF). This study aimed to identify key targets involved in the progression of IPF.

METHODS

We employed Mendelian randomization (MR) with three genome-wide association studies and four quantitative trait loci datasets to identify key driver genes for IPF. Prioritized targets were evaluated for respiratory insufficiency and transplant-free survival. The therapeutic efficacy of the core gene was validated in cellular and animal models. Additionally, we conducted a comprehensive evaluation of therapeutic value, pathogenic mechanisms, and safety through phenome-wide association study (PheWAS), mediation analysis, transcriptomic analyses, shared causal variant exploration, DNA methylation MR, and protein interactions.

RESULTS

Multiple MR results revealed that BRSK2 has a significant pathogenic impact on IPF at both transcriptional and translational levels, with a lung tissue-specific association (OR = 1.596; CI, 1.300-1.961; Pval = 8.290 × 10 - 6). BRSK2 was associated with IPF progression driven by high-risk factors, with mediation effects ranging from 34.452 to 69.665%. Elevated BRSK2 expression in peripheral blood mononuclear cells correlated with reduced pulmonary function, while increased circulating BRSK2 levels suggested respiratory failure and shorter transplant-free survival in IPF patients. BRSK2 silencing attenuated lung fibrosis progression in cellular and animal models. Transcriptomic integration identified PSMB1, CTSD, and CTSH as significant downstream effectors of BRSK2, with PSMB1 showing robust shared causal variant support (PPH4 = 0.800). Colocalization analysis and phenotype scan deepened the pathogenic association of BRSK2 with IPF, while methylation MR analysis highlighted the critical role of epigenetic regulation in BRSK2-driven IPF pathogenesis. PheWAS revealed no significant drug-related toxicities for BRSK2, and its therapeutic potential was further underscored by protein interaction analyses.

CONCLUSIONS

BRSK2 is identified as a critical pathogenic factor in IPF, with strong potential as a therapeutic target. Future studies should focus on its translational implications and the development of targeted therapies to improve patient outcomes.

Association between serum iron status and gout: results from the NHANES and Mendelian randomization study

Aims. Previous observational studies have provided inconsistent evidence for the association between serum iron status and the risk of gout. Moreover, it remains uncertain whether the observed association is causal or due to confounding or reverse causality. This research aimed to investigate the association of serum iron status indicators with the risk of gout and to further examine the causal relationship by the Mendelian randomization (MR) method. Methods. We first conducted a cross-sectional study from the National Health and Nutrition Examination Survey 2017-2018, including a total of 4635 participants. The association of serum iron status indicators with gout risk was evaluated using a multivariable logistic regression model. Furthermore, a two-sample MR study using genetic data from large-scale genome-wide association studies of serum iron status indicators (246 139 individuals) and gout (discovery: 13 179 cases and 75 0634 controls; replication: 5292 cases and 368 788 controls; 2115 cases and 67 259 controls) was conducted to infer causality. Inverse-variance-weighting (IVW) was applied as the main method of MR analysis. A series of sensitivity analyses were used to evaluate the robustness of their relationship. Results. In the cross-sectional study, there was no significant relationship between serum iron status indicators and gout risk. However, IVW results showed that genetically predicted serum iron and transferrin saturation (TSAT) were significantly associated with the increased risk of gout in the discovery analysis [odds ratio (OR): 1.21; 95% confidence interval (CI): 1.10-1.32; P = 9.80 × 10-5 for serum iron and OR: 1.16; 95% CI: 1.08-1.25; P = 7.14 × 10-5 for TSAT]. The replication analysis provided similar results compared with the discovery analysis. Conclusion. Our study provides support for potential causal associations between serum iron and the altered risk of gout. Further investigations are warranted to elucidate the biological processes through which iron influences susceptibility to gout.

Immunological Insights into the Causal Link Between Arthritis, Osteoarthritis, and Frailty: An Integrated Analytical Study

Background: Previous observational studies have observed associations between rheumatoid arthritis (RA), knee osteoarthritis (KOA), hip osteoarthritis (HOA), and frailty, but the causal relationships remain unestablished. Objective: This study aimed to evaluate the causal relationships between RA, KOA, HOA, KneeHipOA, and frailty using Mendelian randomization (MR) and bioinformatics analysis. Methods: We performed two-sample MR to test for causality between RA, KOA, HOA, KneeHipOA, and frailty. Subsequently, we combined our results in a meta-analysis and conducted multiple sensitivity analyses (MR-Egger, weighted median, constrained maximum likelihood and model averaging (cML-MA), and Bayesian weighted MR (BWMR)). We further explored the role of circulating immune cells and the effects of RA and OA-related gene expression on frailty. Results: Genetically determined RA, KOA, HOA, and KneeHipOA were correlated with a higher risk of frailty. The results of multivariate MR analyses were consistent with those of two-sample MR. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes analysis indicated that RA and OA-related genes were primarily enriched in various immune responses. Our findings suggested that increases in monocyte cell AC, eosinophil cell AC, and neutrophil cell AC were associated with a higher risk of frailty. Conclusion: This research provides evidence supporting the associations between RA, KOA, HOA, KneeHipOA, and frailty. It also highlights the significant role of circulating immune cells in the development of frailty, indicating the importance of frailty management from an immunological perspective.

A semi-empirical Bayes approach for calibrating weak instrumental bias in sex-specific Mendelian randomization studies

Strong sex differences exist in sleep phenotypes and also cardiovascular diseases (CVDs). However, sex-specific causal effects of sleep phenotypes on CVD-related outcomes have not been thoroughly examined. Mendelian randomization (MR) analysis is a useful approach for estimating the causal effect of a risk factor on an outcome of interest when interventional studies are not available. We first conducted sex-specific genome-wide association studies (GWASs) for suboptimal-sleep phenotypes (insomnia, obstructive sleep apnea (OSA), short and long sleep durations, and excessive daytime sleepiness) utilizing the Million Veteran Program (MVP) dataset. We then developed a semi-empirical Bayesian framework that (i) calibrates variant-phenotype effect estimates by leveraging information across sex groups, and (ii) applies shrinkage sex-specific effect estimates in MR analysis, to alleviate weak instrumental bias when sex groups are analyzed in isolation. Simulation studies demonstrate that the causal effect estimates derived from our framework are substantially more efficient than those obtained through conventional methods. We estimated the causal effects of sleep phenotypes on CVD-related outcomes using sex-specific GWAS data from the MVP and All of Us. Significant sex differences in causal effects were observed, particularly between OSA and chronic kidney disease, as well as long sleep duration on several CVD-related outcomes. By applying shrinkage estimates for instrumental variable selection, we identified multiple sex-specific significant causal relationships between OSA and CVD-related phenotypes.