Assessing the causal association between human blood metabolites and the risk of epilepsy

Causal role of immune cells in major depressive disorder and bipolar disorder: Mendelian randomization (MR) study

BACKGROUND

Major depressive disorder (MDD) and bipolar disorder (BD) are prevalent psychiatric conditions linked to inflammatory processes. However, it is unclear whether associations of immune cells with these disorders are likely to be causal.

METHODS

We used two-sample Mendelian randomization (MR) approach to investigate the relationship between 731 immune cells and the risk of MDD and BD. Rigorous sensitivity analyses are conducted to assess the reliability, heterogeneity, and horizontal pleiotropy of the findings.

RESULTS

Genetically-predicted CD27 on IgD+ CD38- unswitched memory B cell (inverse variance weighting (IVW): odds ratio (OR) [95 %]: 1.017 [1.007 to 1.027], p = 0.001), CD27 on IgD+ CD24+ B cell (IVW: OR [95 %]: 1.021 [1.011 to 1.031], p = 4.821E-05) and other 12 immune cells were associated with increased risk of MDD in MR, while HLA DR++ monocyte %leukocyte (IVW: OR [95 %]: 0.973 [0.948 to 0.998], p = 0.038), CD4 on Central Memory CD4+ T cell (IVW: OR [95 %]: 0.979 [0.963 to 0.995], p = 0.011) and other 13 immune cells were associated with decreased risk of MDD in MR. Additionally, CD33+ HLA DR+ Absolute Count (IVW: OR [95 %]: 1.022[1.007 to 1.036], p = 0.007), CD28+ CD45RA- CD8+ T cell %T cell (IVW: OR [95 %]: 1.024 [1.008 to 1.041], p = 0.004) and other 18 immune cells were associated with increased risk of BD in MR, while CD62L on CD62L+ myeloid Dendritic Cell (IVW: OR [95 %]: 0.926 [0.871 to 0.985], p = 0.014), IgD- CD27- B cell %lymphocyte (IVW: OR [95 %]: 0.918 [0.880 to 0.956], p = 4.654E-05) and other 13 immune cells were associated with decreased risk of BD in MR.

CONCLUSIONS

This MR study provides robust evidence supporting a causal relationship between immune cells and the susceptibility to MDD and BD, offering valuable insights for future clinical investigations. Experimental studies are also required to further examine causality, mechanisms, and treatment potential for these immune cells for MDD and BD.

The causal relationship between human blood metabolites and risk of peripheral artery disease: a Mendelian randomization study

Background

Peripheral Artery Disease (PAD) is a common vascular disorder typically caused by atherosclerosis, leading to impaired blood supply to the lower extremities, resulting in pain, necrosis, and even amputation. Despite extensive research into the pathogenesis of PAD, many mysteries remain, particularly regarding its association with human blood metabolites.

Methods

To explore the causal relationship between 1,400 serum metabolites and PAD, a two-sample Mendelian randomization (MR) analysis was conducted. The Inverse Variance-Weighted (IVW) method was the primary technique used to estimate the causal impact of the metabolites on PAD. To enhance the analysis, several additional methods were employed: MR-Egger regression, weighted median, simple mode, and weighted mode. These methods provided a comprehensive evaluation beyond the primary IVW estimation. To ensure the validity of the MR findings, sensitivity analysis was performed. Furthermore, a bidirectional MR approach was applied to explore the possibility of a reverse causal effect between PAD and potential candidate metabolites.

Results

After rigorous selection, significant associations were found between 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) and X-17653 levels with PAD. 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) was positively associated with increased PAD risk (IVW OR = 1.13, 95% CI, 1.06-1.21; P < 0.001). X-17653 levels were associated with decreased PAD risk (IVW OR = 0.88, 95% CI, 0.83-0.94; P < 0.001). In the reverse direction, PAD was positively associated with increased 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) levels (IVW OR = 1.16, 95% CI, 1.01-1.34; P = 0.036). PAD was not associated with X-17653.

Conclusion

Among 1,400 blood metabolites, 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) and X-17653 are significantly associated with PAD risk. Importantly, in the reverse direction, PAD was found to be positively associated with increased levels of 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4). This highlights the bidirectional nature of the association and suggests a potential feedback mechanism between PAD and this specific lipid species. 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (p-18:0/20:4) may serve as potential biomarkers for PAD, aiding early diagnosis and providing novel avenues for personalized treatment and management. However, further validation and research are warranted despite the promising results.

Mendelian randomization identifies causal associations between GWAS-associated bacteria and their metabolites and rheumatoid arthritis

Background

Accumulating evidence suggests that an imbalance of gut microbiota is commonly observed in patients with rheumatoid arthritis (RA). However, it remains unclear whether gut microbiota dysbiosis is a cause or consequence of RA, and the mechanisms by which gut dysbiosis contributes to RA have not been fully understood. This study aimed to investigate the causal relationship between gut microbiota and metabolites with RA.

Methods

A two-sample Mendelian randomization analysis was performed to estimate the causality of gut microbiota and metabolites on RA. A genome-wide association study (GWAS) of 211 gut microbiota and 217 metabolites was used as the exposure, whereas RA was treated as the outcome. Inverse variance weighted (IVW) was regarded as the primary approach for calculating causal estimates. MR Egger method, Weighted median method, Simple mode method, and weighted mode method were used for sensitive analysis. Metabolic pathway analysis was performed via the web-based Metaconflict 5.0. Additionally, an animal study was undertaken to evaluate the results inferred by Mendelian randomization.

Result

This study indicated that six gut microbiota taxa (RuminococcaceaeUCG013, Erysipelotrichia, Erysipelotrichaceae, Erysipelotrichales, Clostridia, and Veillonellaceae) were estimated to exert a positive impact on RA. Conversely, seven gut microbiota taxa (Oxalobacter, Cyanobacteria, RuminococcaceaeUCG002, LachnospiraceaeUCG010, Christensenellaceae, Oxalobacteraceae, Anaerostipes) were estimated to exert a negative impact on RA. Three metabolites, namely indole-3-propionate (IPA), glycine and sphingomyelin (SM 16:1), were found to be linked to lower RA risk, while five metabolites (argininosuccinate, CE 20_4, TAG 58_8, PC 40_6, and LPC 20_4) were linked to higher RA risk. Additionally, four metabolic pathways were identified by metabolic pathway analysis. The collagen-induced arthritis (CIA) rats exhibited a higher relative abundance of Class_Clostridia and a lower abundance of Genus_Lachnospiraceae (p < 0.05) than the healthy controls.

Conclusion

This study identified causal associations between specific gut microbiota, metabolites, and RA. These findings support the significant role of gut microbiota and metabolites in RA pathogenesis.

Multidimensional plasma lipid composition and its causal association with type 2 diabetes mellitus: A Mendelian randomization study

BACKGROUND AND AIM

Recent research extends our knowledge of plasma lipid species, building on established links between serum lipid levels and Type 2 Diabetes Mellitus (T2DM) risk. Identifying the causal roles of these lipid species is key to improving T2DM risk assessment.

METHODS AND RESULTS

This study employs Mendelian randomization (MR) to investigate the causal relationship between 179 lipid species across 13 lipid categories and T2DM. Summary-level data were sourced from genome-wide association studies. The primary analytical methods included the inverse variance weighted (IVW) approach and the Wald ratio, complemented by a series of sensitivity analyses to ensure the robustness of results. The IVW analysis reveals a significant causal association between elevated levels of ceramide (d40:2) (OR = 1.071, 95% CI 1.034-1.109, P = 1.36 × 10-4), sphingomyelin (d38:1) (OR = 1.052, 95% CI 1.028-1.077, P = 1.80 × 10-5), and triacylglycerol (56:8) (OR = 1.174, 95% CI 1.108-1.243, P = 4.65 × 10-8), and an increased risk of T2DM. Conversely, Wald ratio analysis indicates that higher levels of phosphatidylcholine (O-16:1_16:0) (OR = 0.928, 95% CI 0.892-0.966, P = 2.37 × 10-4), phosphatidylcholine (O-16:1_20:4) (OR = 0.932, 95% CI 0.897-0.967, P = 2.37 × 10-4), and phosphatidylcholine (O-18:2_20:4) (OR = 0.872, 95% CI 0.812-0.935, P = 1.24 × 10-4) are significantly associated with a reduced risk of T2DM. Furthermore, suggestive causal evidence for 22 additional lipid species was identified.

CONCLUSIONS

This MR study establishes a causal relationship between specific lipid classes in modulating the risk of T2DM. It offers new insights for risk assessment and potential therapeutic targets in T2DM.

The causal effect of hot beverage temperature preference on esophageal cancer risk: a Mendelian randomization study

Background

Previous research has found a link between the temperature of food and beverages and the risk of esophageal cancer (EC). A causal relationship between the two has not been well established. Herein, we used Mendelian randomization (MR) analysis to assess the causal effect of temperature preference for hot beverages on EC risk.

Methods

Genome-wide association studies (GWAS) data for hot beverage temperature preference were obtained from the UK biobank. There were 457,873 European and 2,617 East Asian participants included. GWAS data for EC were obtained from the Integrative Epidemiology Unit (IEU) project database. Two datasets from the European population and two datasets from the East Asian population were included. Totally, 4,426 EC cases and 1,202,270 control subjects were included. The "TwoSampleMR" R package was used to conduct a two-sample MR analysis. A random-effect inverse variance weighted (IVW) was used as the main analytical method to estimate the causal effect, and various sensitivity analyses, including MR Egger, weighted median, simple mode, and weighted mode, were used to examine the potential violation of the second and third MR assumptions. Meta-analyses were performed to further confirm the results.

Results

Sixty-eight single nucleotide polymorphisms (SNPs) from the European population and 11 SNPs from the East Asian population were used for MR analysis. No significant causal effect was found between hot beverage temperature preference and EC risk in the European population {for the ieu-b-4960 dataset, inverse variance weighted odds ratio (ORIVW) =1.00 [95% confidence interval (CI): 0.99-1.00], P=0.54; for the ebi-a-GCST90018841 dataset, ORIVW =0.35 (95% CI: 0.10-1.29), P=0.12} or in the East Asian population [for the bbj-a-117 dataset, ORIVW =1.09 (95% CI: 0.80-1.48), P=0.59; for the ebi-a-GCST90018621 dataset, ORIVW =0.11 (95% CI: 0.82-1.50), P=0.49]. Meta-analyses of the European population datasets and the Asian population datasets showed consistent results.

Conclusions

The current MR analysis provides new genetic evidence for a null causal relationship between hot beverage temperature preference and EC, both in the European population and the East Asian population. Evidence to prevent EC by reducing the intake of hot beverages is insufficient.

Causal Association between Circulating Metabolites and Dementia: A Mendelian Randomization Study

The causal association of circulating metabolites with dementia remains uncertain. We assessed the causal association of circulating metabolites with dementia utilizing Mendelian randomization (MR) methods. We performed univariable MR analysis to evaluate the associations of 486 metabolites with dementia, Alzheimer's disease (AD), and vascular dementia (VaD) risk. For secondary validation, we replicated the analyses using an additional dataset with 123 metabolites. We observed 118 metabolites relevant to the risk of dementia, 59 of which were lipids, supporting the crucial role of lipids in dementia pathogenesis. After Bonferroni adjustment, we identified nine traits of HDL particles as potential causal mediators of dementia. Regarding dementia subtypes, protective effects were observed for epiandrosterone sulfate on AD (OR = 0.60, 95% CI: 0.48-0.75) and glycoproteins on VaD (OR = 0.89, 95% CI: 0.83-0.95). Bayesian model averaging MR (MR-BMA) analysis was further conducted to prioritize the predominant metabolites for dementia risk, which highlighted the mean diameter of HDL particles and the concentration of very large HDL particles as the predominant protective factors against dementia. Moreover, pathway analysis identified 17 significant and 2 shared metabolic pathways. These findings provide support for the identification of promising predictive biomarkers and therapeutic targets for dementia.

Exploring the impact of metabolites function on heart failure and coronary heart disease: insights from a Mendelian randomization (MR) study

BACKGROUND

Heart failure (HF) and coronary heart disease (CHD) are major causes of morbidity and mortality worldwide. While traditional risk factors such as hypertension, diabetes, and smoking have been extensively studied, the role of metabolite functions in the development of these cardiovascular conditions has been less explored. This study employed a Mendelian randomization (MR) approach to investigate the impact of metabolite functions on HF and CHD.

METHODS

To assess the causal impacts of specific metabolite risk factors on HF and CHD, this study utilized genetic variants associated with these factors as instrumental variables. Comprehensive genetic and phenotypic data from diverse cohorts, including genome-wide association studies (GWAS) and cardiovascular disease registries, were incorporated into the research.

RESULTS

Our results encompass 61 metabolic cell phenotypes, with ten providing strong evidence of the influence of metabolite functions on the occurrence of HF and CHD. We found that elevated levels of erucate (22:1n9), lower levels of α-tocopherol, an imbalanced citrulline-to-ornithine ratio, elevated γ-glutamyl glycine levels, and elevated 7-methylguanine levels independently increased the risk of these cardiovascular conditions. These findings were consistent across different populations and robust to sensitivity analyses.

CONCLUSION

This MR study provides valuable insights into the influence of metabolite functions on HF and CHD. However, further investigation is needed to fully understand the precise mechanisms by which these metabolite factors contribute to the onset of these conditions. Such research could pave the way for the development of targeted therapeutic strategies.

Genetic information supports a causal relationship between trace elements, inflammatory proteins, and COPD: evidence from a Mendelian randomization analysis

Objective

Dietary factors and nutritional status may be among the risk factors for Chronic Obstructive Pulmonary Disease (COPD). There exists a certain correlation between trace elements and COPD. Through Mendelian Randomization (MR) analysis, we investigated the causal relationships between trace elements, inflammatory proteins, and COPD.

Methods

We employed MR, multivariable MR (MVMR), and two-step MR (TSMR) approaches to assess the causal links between 15 trace elements and COPD, with 91 inflammatory proteins serving as mediators to further elucidate the tripartite causal relationships.

Results

Trace elements such as Folate (OR = 1.293, 95%CI 1.027-1.628; p = 0.029), Vitamin D (OR = 1.331, 95%CI 1.071-1.654; p = 0.010), Vitamin B12 (OR = 1.424, 95%CI 1.108-1.828; p = 0.006), and Iron (OR = 0.741, 95%CI 0.580-0.946; p = 0.016) demonstrated causal relationships with COPD. No causal relationship was observed in reverse MR. After adjusting for BMI, Folate (OR = 1.633, 95%CI 1.098-2.429; p = 0.015), Iron (OR = 0.507, 95%CI 0.31-0.778; p = 0.001), and Vitamin D (OR = 1.511, 95%CI 1.029-2.217; p = 0.034) were identified as independent risk factors for COPD, whereas Vitamin B12 (OR = 1.118, 95%CI 0.751-1.666; p = 0.581) was not. Mediation analysis indicated that CDCP1 (5.76%) may play a mediating role between Iron and COPD.

Conclusion

Trace elements such as Folate, Vitamin D, Vitamin B12, and Iron have causal relationships with COPD. After BMI adjustment, Folate, Vitamin D, and Iron emerge as independent risk factors. Furthermore, the inflammatory protein CDCP1 may partially mediate the causal relationship between Iron and COPD, offering a scientific basis for dietary recommendations that could benefit COPD patients. The supplementation of trace elements may be advantageous for individuals suffering from COPD.

The possible causal relationship between COVID-19 and imaging markers of cerebral small vessel disease: a Mendelian randomization study

OBJECTIVES

Observational studies have suggested that SARS-CoV-2 infection may increase the burden of cerebral small vessel disease (CSVD). This study aims to explore the causal correlation between COVID-19 and the imaging markers of CSVD using Mendelian randomization (MR) methods.

METHODS

Summary-level genome-wide association study (GWAS) statistics for COVID-19 susceptibility, hospitalization, and severity were utilized as proxies for exposure. Large-scale meta-analysis GWAS data on three neuroimaging markers of white matter hyperintensity, lacunar stroke, and brain microbleeds, were employed as outcomes. Our primary MR analysis employed the inverse variance weighted (IVW) approach, supplemented by MR-Egger, weighted median, and MR-PRESSO methods. We also conducted multivariable MR analysis to address confounding bias and validate the robustness of the established causal estimates. Comprehensive sensitivity analyses included Cochran's Q test, Egger-intercept analysis, MR-PRESSO, and leave-one-out analysis.

RESULTS

The MR analysis revealed a significant causal correlation between the severity of COVID-19 and an increased risk of lacunar stroke, as demonstrated by the IVW method (ORivw = 1.08, 95% CI: 1.03-1.16, pivw = 0.005, FDR = 0.047). Nevertheless, no causal correlations were observed between COVID-19 susceptibility or hospitalization and any CSVD imaging markers. The robustness and stability of these findings were further confirmed by multivariable MR analysis and comprehensive sensitivity analyses.

DISCUSSION

This study provides compelling evidence of a potential causal effect of severe COVID-19 on the incidence of lacunar stroke, which may bring fresh insights into the understanding of the comorbidity between COVID-19 and CSVD.

Causal association between cardiovascular proteins and membranous nephropathy: a bidirectional Mendelian randomization

PURPOSE

Multiple circulating proteins have been reported to participate in human diseases. However, the association between cardiovascular proteins and membranous nephropathy (MN) remained profoundly elusive.

METHODS

A bidirectional Mendelian randomization (MR) analysis was conducted to explore the causal correlation between ninety cardiovascular proteins and MN. Genome-wide association study (GWAS) data of cardiovascular proteins and MN were all from European research. Inverse variance weighted (IVW) was used as the main approach. Moreover, MR-Egger, weighted median, weighted mode, and simple mode were also performed. Cochrane's Q test, MR-Egger, and MR-PRESSO were conducted for sensitivity analysis.

RESULTS

According to IVW method, fatty acid-binding protein and thrombomodulin (TM) were identified as risk factors for MN, while a protective role was detected in tissue-type plasminogen activator. Additionally, MN was associated with an elevated level of macrophage colony-stimulating factor 1, stem cell factor, TM, and tissue factor. Reversely, MN was also correlated with a downregulated level of beta-nerve growth factor, Cathepsin D, hepatocyte growth factor, interleukin-6 receptor subunit alpha, macrophage colony-stimulating factor 1, and myeloperoxidase. In the sensitivity analysis, no significant pleiotropy and heterogeneity was detected.

CONCLUSION

This was the first study to reveal the causal association between cardiovascular proteins and MN. These specific cardiovascular proteins could be novel biomarkers for MN, and is helpful for timely identify the risk of other diseases that might result from MN. However, further clinical studies are needed to confirm our results.

Causal effects of genetically determined blood metabolites on asthma: a bidirectional Mendelian randomization study

OBJECTIVE

The observational association between blood metabolites and asthma has been extensively studied. However, it is still unclear whether this association is causal. In this study, we aimed to investigate the causal relationship between blood metabolites and asthma using a bidirectional Mendelian randomization (MR) analysis. Additionally, we aimed to explore the potential mechanisms underlying this relationship.

METHODS

The study design involved the use of genetic instruments as instrumental variables (IVs) to fulfill the assumptions of MR analysis. The data on 1,091 metabolites and 309 metabolite ratios were obtained from the Canadian Longitudinal Study on Aging (CLSA), while the data on asthma were obtained from the Integrative Epidemiology Unit (IEU) Open GWAS Project. Utilizing the inverse variance-weighted (IVW) method as the primary MR analysis approach, sensitivity tests were conducted to assess the reliability of the findings, which involved employing Cochran's Q and the MR-Egger intercept. Furthermore, Bayesian weighted MR was used to further test the robustness of the results. Additionally, pathway analysis was conducted to explore the metabolic explanations underlying asthma.

RESULT

In our study, a comprehensive MR Analysis identified 10 metabolites and 6 metabolite ratios significantly associated with the development of asthma (FDR < 0.05). The metabolites included glycerophosphocholines(GPCs), glycerophosphoethanolamines(GPEs), and an unknown metabolite. Of these, 1-arachidonoyl-GPC, 1-myristoyl-2-arachidonoyl-GPC, 1-palmitoyl-2-arachidonoyl-GPC, and 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC were associated with an increased risk of asthma, whereas 1,2-dilinoleoyl-GPC, 1-palmitoyl-2-linoleoyl-GPC, 1,2-dilinoleoyl-GPE, 1 - oleoyl - 2 - linoleoyl - GPE, 1-palmitoyl-2-linoleoyl-GPE, and X-21470 were found to have a protective effect. No heterogeneity and pleiotropy were observed in the significant metabolites (p > 0.05), and each metabolite exhibited a consistent effect direction across all five methods. BWMR analysis results confirmed the significance and direction of effects across exposures, except for Cholesterol to linoleoyl-arachidonoyl-glycerol ratio(p = 0.673). Pathway analysis suggests that glycerophospholipid metabolism may potentially be a mechanism underlying the development of asthma.

CONCLUSION

Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical asthma screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.

Causal impact of human blood metabolites and metabolic pathways on serum uric acid and gout: a mendelian randomization study

Objective

Hyperuricaemia and gout are common metabolic disorders. However, the causal relationships between blood metabolites and serum urate levels, as well as gout, remain unclear. A systematic evaluation of the causal connections between blood metabolites, hyperuricemia, and gout could enhance early screening and prevention of hyperuricemia and gout in clinical settings, providing novel insights and approaches for clinical treatment.

Methods

In this study, we employed a bidirectional two-sample Mendelian randomization analysis utilizing data from a genome-wide association study involving 7,286 participants, encompassing 486 blood metabolites. Serum urate and gout data were sourced from the Chronic Kidney Disease Genetics consortium, including 288,649 participants for serum urate and 9,819 African American and 753,994 European individuals for gout. Initially, LDSC methodology was applied to identify blood metabolites with a genetic relationship to serum urate and gout. Subsequently, inverse-variance weighting was employed as the primary analysis method, with a series of sensitivity and pleiotropy analyses conducted to assess the robustness of the results.

Results

Following LDSC, 133 blood metabolites exhibited a potential genetic relationship with serum urate and gout. In the primary Mendelian randomization analysis using inverse-variance weighting, 19 blood metabolites were recognized as potentially influencing serum urate levels and gout. Subsequently, the IVW p-values of potential metabolites were corrected using the false discovery rate method. We find leucine (IVW P FDR = 0.00004), N-acetylornithine (IVW P FDR = 0.0295), N1-methyl-3-pyridone-4-carboxamide (IVW P FDR = 0.0295), and succinyl carnitine (IVW P FDR = 0.00004) were identified as significant risk factors for elevated serum urate levels. Additionally, 1-oleoylglycerol (IVW P FDR = 0.0007) may lead to a substantial increase in the risk of gout. Succinyl carnitine exhibited acceptable weak heterogeneity, and the results for other blood metabolites remained robust after sensitivity, heterogeneity, and pleiotropy testing. We conducted an enrichment analysis on potential blood metabolites, followed by a metabolic pathway analysis revealing four pathways associated with serum urate levels.

Conclusion

The identified causal relationships between these metabolites and serum urate and gout offer a novel perspective, providing new mechanistic insights into serum urate levels and gout.

Effect of coffee, tea and alcohol intake on circulating inflammatory cytokines: a two sample-Mendelian randomization study

BACKGROUND

Despite the abundance of research examining the effects of coffee, tea, and alcohol on inflammatory diseases, there is a notable absence of conclusive evidence regarding their direct causal influence on circulating inflammatory cytokines. Previous studies have primarily concentrated on established cytokines, neglecting the potential impact of beverage consumption on lesser-studied but equally important cytokines.

METHODS

Information regarding the consumption of coffee, tea, and alcohol was collected from the UK Biobank, with sample sizes of 428,860, 447,485, and 462,346 individuals, respectively. Data on 41 inflammatory cytokines were obtained from summary statistics of 8293 healthy participants from Finnish cohorts.

RESULTS

The consumption of coffee was found to be potentially associated with decreased levels of Macrophage colony-stimulating factor (β = -0.57, 95% CI -1.06 ~ -0.08; p = 0.022) and Stem cell growth factor beta (β = -0.64, 95% CI -1.16 ~ -0.12; p = 0.016), as well as an increase in TNF-related apoptosis-inducing ligand (β = 0.43, 95% CI 0.06 ~ 0.8; p = 0.023) levels. Conversely, tea intake was potentially correlated with a reduction in Interleukin-8 (β = -0.45, 95% CI -0.9 ~ 0; p = 0.045) levels. Moreover, our results indicated an association between alcohol consumption and decreased levels of Regulated on Activation, Normal T Cell Expressed and Secreted (β = -0.24, 95% CI -0.48 ~ 0; p = 0.047), as well as an increase in Stem cell factor (β = 0.17, 95% CI 0.02 ~ 0.31; p = 0.023) and Stromal cell-derived factor-1 alpha (β = 0.20, 95% CI 0.04 ~ 0.36; p = 0.013).

CONCLUSION

Revealing the interactions between beverage consumption and various inflammatory cytokines may lead to the discovery of novel therapeutic targets, thereby facilitating dietary interventions to complement clinical disease treatments.

Immune-mediated inflammatory diseases and periodontal disease: a bidirectional two-sample mendelian randomization study

BACKGROUND

Previous observational studies have shown a bidirectional association between immune-mediated inflammatory disorders (IMID) and periodontal disease. However, evidence regarding the causal role of IMID and periodontal disease is still lacking. Therefore, we conducted a bidirectional two-sample Mendelian randomization (MR) study to uncover the potential genetic causal effects between IMID and periodontal disease.

METHODS

Bidirectional two-sample MR analysis was employed. Data for ten IMIDs were sourced from genome-wide association studies (GWAS) conducted by the FinnGen Consortium (range from 1023 to 36321 cases) and UK Biobank (UKB) (range from 150 to 17574 cases). Furthermore, GWAS data for periodontal disease were obtained from the FinnGen Consortium (87497 cases), UKB (458 cases), and Gene Lifestyle Interactions in Dental Endpoints (GLIDE) consortium (17,353 periodontitis cases). Subsequently, the causal relationships were analyzed by random effects inverse variance weighting, weighted median, and MR-Egger. Sensitivity analyses were performed using the Cochrane Q test, funnel plot, and Mr-Egger intercept test to ensure robustness. Eventually, replication analysis and meta-analysis across different databases were carried out.

RESULTS

Systemic lupus erythematosus (SLE) [IVW: OR = 1.079 (95% CI: 1.032-1.128) and P < 0.001], Sjogren syndrome [IVW: OR = 1.082 (95% CI: 1.012-1.157) and P = 0.022] and hypothyroidism [IVW: OR = 1.52 (95% CI: 1.13-2.04) and P = 0.005] may increase the risk of periodontal disease. In addition, periodontal disease may reduce the risk of SLE [IVW: OR = 0.8079 (95% CI: 0.6764-0.9650) and P = 0.019] and hyperthyroidism [IVW: OR = 5.59*10-9 (95% CI: 1.43*10-15-2.18*10-2) and P = 0.014]. Meta-analysis indicated a causal correlation between SLE and an increased risk of periodontal disease: [OR = 1.08 (95% CI: 1.03-1.13), P = 0.0009]. No significant evidence suggests bilateral causal relationships between other IMIDs and periodontal disease. No significant estimation of heterogeneity or pleiotropy is detected.

CONCLUSIONS

Our study has confirmed a genetic causal relationship between IMIDs and periodontal disease, thereby unveiling novel potential mechanisms underlying IMIDs and periodontal disease. This discovery is promising in fostering interdisciplinary collaboration between clinicians and stomatologists to facilitate appropriate and precise screening, prevention, and early treatment of IMIDs and periodontal disease.

Causal effect of immune cells on idiopathic pulmonary fibrosis: A mendelian randomization study

BACKGROUND

A key component of idiopathic pulmonary fibrosis (IPF) is the involvement of immune cells. However, the causal interaction between different immune cell signatures and IPF remain inconclusive.

OBJECTIVES

Based on publicly accessible data, our study utilized the Mendelian randomization (MR) approach to determine the causative relevance of complex immune cell phenotypes in IPF.

METHODS

We deployed a two-sample Mendelian randomization approach to evaluate the causal interaction between immune cell markers and IPF. All data regarding 731 immune signatures and IPF were acquired from two genome-wide association studies (GWAS) that are accessible to the public. The original study adopted the inverse variance weighted (IVW) method, followed by sensitivity analyses aimed at eliminating heterogeneity and pleiotropy. Additionally, Multivariate Mendelian randomization (MVMR) was utilized to identify the independent risk factors in our study.

RESULTS

The summary dataset for IPF was accessed from the Finnish Genetic Consortium R9, comprising 2018 patients and 373,064 controls. And the dataset for immune signatures was conducted in 3,757 Sardinian individuals. By conducting IVW and extensive sensitivity analyses, univariate Mendelian randomization (UVMR) identified one immunophenotype that remained causally associated with IPF after false discovery rate (FDR) correction: CD39 on CD39+ CD8+T cells (odd ratio [OR] = 0.850, 95 % confidence interval [CI] = 0.787-0.918, P = 3.68 × 10-5). The causal association with IPF was further validated using MVMR.

CONCLUSIONS

Based on rigorous MR analysis methods and FDR correction, our study demonstrated that CD39 on CD39+ CD8+T cells showed a protective effect against IPF, providing effective insights for preventing and diagnosing pulmonary fibrosis.

Causal association between blood metabolites and risk of hypertension: a Mendelian randomization study

Background

Previous studies have indicated a strong link between blood metabolites and hypertension, however the causality of metabolites and hypertension is unknown.

Methods

Two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between 486 blood metabolites and essential hypertension (EHT). Blood metabolite GWAS data was utilized as the exposure, with EHT GWAS data as the outcome. To further verify the results, another different source of EHT GWAS data was repeatedly analyzed. The major MR analytic approach used to determine causality was inverse variance weighted (IVW), with MR-Egger, Weighted Median, and MR-PRESSO models serving as supplements. We used the Cochran Q test to examine heterogeneity. Horizontal pleiotropy was examined using MR-Egger intercept and MR-PRESSO global test. The MR Steiger test confirmed the causal relationship between blood metabolites and EHT.

Results

In this study, nine blood metabolites associated with EHT were preliminarily identified by MR analysis, including four known metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid, creatine, hexadecanedioate) and five unknown metabolites. Then another source of EHT GWAS data was repeatedly analyzed for further verification, and two overlapped metabolites (N-acetylornithine, X-12510-2-aminooctanoic acid) were found. There was a negative correlation between N-acetylornithine and EHT (OR = 0.987, 95% CI = 0.980-0.993, P = 1.01 × 10-4), Cochran's Q test suggested there was no heterogeneity (Q = 31.7586, P = 0.1331), MR-Egger intercept and MR-PRESSO global test suggested there was no horizontal pleiotropy (P > 0.05), Leave-one-out analysis indicated that no single single-nucleotide polymorphism (SNP) had a significant effect on the results, and MR Steiger test confirmed that the direction of causality was correct (P < 0.001). There was a negative correlation between X-12510-2-aminooctanoic acid and EHT (OR = 0.982, 95% CI = 0.972-0.993, P = 0.0017), and there was no evidence of heterogeneity or pleiotropy in multiple sensitivity analyses.

Conclusion

The study discovered some blood metabolites causally linked to EHT, which might lead to new understandings of the pathophysiology of hypertension.

Role of inflammatory cytokine in mediating the effect of plasma lipidome on epilepsy: a mediation Mendelian randomization study

Background

Epilepsy is one of the most prevalent serious brain disorders globally, impacting over 70 million individuals. Observational studies have increasingly recognized the impact of plasma lipidome on epilepsy. However, establishing a direct causal link between plasma lipidome and epilepsy remains elusive due to inherent confounders and the complexities of reverse causality. This study aims to investigate the causal relationship between specific plasma lipidome and epilepsy, along with their intermediary mediators.

Methods

We conducted a two-sample Mendelian randomization (MR) and mediation MR analysis to evaluate the causal effects of 179 plasma lipidomes and epilepsy, with a focus on the inflammatory cytokine as a potential mediator based on the genome-wide association study. The primary methodological approach utilized inverse variance weighting, complemented by a range of other estimators. A set of sensitivity analyses, including Cochran's Q test, I 2 statistics, MR-Egger intercept test, MR-PRESSO global test and leave-one-out sensitivity analyses was performed to assess the robustness, heterogeneity and horizontal pleiotropy of results.

Results

Our findings revealed a positive correlation between Phosphatidylcholine (18:1_18:1) levels with epilepsy risk (OR = 1.105, 95% CI: 1.036-1.178, p = 0.002). Notably, our mediation MR results propose Tumor necrosis factor ligand superfamily member 12 levels (TNFSF12) as a mediator of the relationship between Phosphatidylcholine (18,1_18:1) levels and epilepsy risk, explaining a mediation proportion of 4.58% [mediation effect: (b = 0.00455, 95% CI: -0.00120-0.01030), Z = 1.552].

Conclusion

Our research confirms a genetic causal relationship between Phosphatidylcholine (18:1_18:1) levels and epilepsy, emphasizing the potential mediating role of TNFSF12 and provide valuable insights for future clinical investigations into epilepsy.

Dissecting causal relationships between immune cells, plasma metabolites, and COPD: a mediating Mendelian randomization study

Objective

This study employed Mendelian Randomization (MR) to investigate the causal relationships among immune cells, COPD, and potential metabolic mediators.

Methods

Utilizing summary data from genome-wide association studies, we analyzed 731 immune cell phenotypes, 1,400 plasma metabolites, and COPD. Bidirectional MR analysis was conducted to explore the causal links between immune cells and COPD, complemented by two-step mediation analysis and multivariable MR to identify potential mediating metabolites.

Results

Causal relationships were identified between 41 immune cell phenotypes and COPD, with 6 exhibiting reverse causality. Additionally, 21 metabolites were causally related to COPD. Through two-step MR and multivariable MR analyses, 8 cell phenotypes were found to have causal relationships with COPD mediated by 8 plasma metabolites (including one unidentified), with 1-methylnicotinamide levels showing the highest mediation proportion at 26.4%.

Conclusion

We have identified causal relationships between 8 immune cell phenotypes and COPD, mediated by 8 metabolites. These findings contribute to the screening of individuals at high risk for COPD and offer insights into early prevention and the precocious diagnosis of Pre-COPD.

Metabolome-Wide Mendelian Randomization Assessing the Causal Role of Serum and Cerebrospinal Metabolites in Traumatic Brain Injury

Previous studies have identified metabolites as biomarkers or potential therapeutic targets for traumatic brain injury (TBI). However, the causal association between them remains unknown. Therefore, we investigated the causal effect of serum metabolites and cerebrospinal fluid (CSF) metabolites on TBI susceptibility through Mendelian randomization (MR). Genetic variants related to metabolites and TBI were extracted from a corresponding genome-wide association study (GWAS). Causal effects were estimated through the inverse variance weighted approach, supplemented by a weighted median, weight mode, and the MR-Egger test. In addition, sensitivity analyses were further performed to evaluate the stability of the MR results, including the MR-Egger intercept, leave-one-out analysis, Cochrane's Q-test, and the MR-PRESSO global test. Metabolic pathway analysis was applied to uncover the underlying pathways of the significant metabolites in TBI. In blood metabolites, substances such as 4-acetaminophen sulfate and kynurenine showed positive links, whereas beta-hydroxyisovalerate and creatinine exhibited negative correlations. CSF metabolites such as N-formylanthranilic acid were positively related, while kynurenate showed negative associations. The metabolic pathway analysis highlighted the potential biological pathways involved in TBI. Of these 16 serum metabolites, 11 CSF metabolites and metabolic pathways may serve as useful circulating biomarkers in clinical screening and prevention, and may be candidate molecules for the exploration of mechanisms and drug targets.

Assessing the causal association between sleep apnea and the human gut microbiome composition: A two-sample Mendelian randomization study

Background

Studies have linked gut microbiota dysbiosis with sleep apnea; however, no causal relationship was found in human subjects. Finding new targets for the pathophysiology of sleep apnea might be made possible by systematically investigating the causal relationship between the human gut microbiota and sleep apnea.

Methods

A two-sample Mendelian randomization analysis was conducted. The human gut microbiome composition data, spanning five taxonomic levels, were acquired from a genome-wide association study that included 18,340 participants from 24 cohorts. Genome-wide association study data for sleep apnea were obtained from the Sleep Disorder Knowledge Portal for primary analysis and the FinnGen consortium for meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

Results

Using inverse-variance weighted analysis, eight microbial taxa were initially found to be substantially linked with the apnea-hypopnea index. Only three microbial taxa remained significant associations with sleep apnea when combined with the FinnGen consortium (the class Bacilli: B = 8.21%, 95% CI = 0.93%-15.49%; p = 0.03; the order Lactobacillales: B = 7.55%, 95% CI = 0.25%-4.85%; p = 0.04; the genus RuminococcaceaeUCG009: B = -21.63%, 95% CI = -41.47% to -1.80%; p = 0.03).

Conclusions

Sleep apnea may lead to gut dysbiosis as significant reductions in butyrate-producing bacteria and increases in lactate-producing bacteria. By integrating genomes and metabolism, the evidence that three microbiome species are causally linked to sleep apnea may offer a fresh perspective on the underlying mechanisms of the condition.

Association between biological aging and periodontitis using NHANES 2009-2014 and mendelian randomization

Aging is a recognized risk factor for periodontitis, while biological aging could provide more accurate insights into an individual's functional status. This study aimed to investigate the potential association between biological aging and periodontitis. Epidemiological data from 9803 participants in the 2009-2014 National Health and Nutrition Examination Survey were analyzed at a cross-sectional level to assess this link. Three biological ages [Klemera-Doubal method (KDM), PhenoAge, and homeostatic dysregulation (HD)] and two measures of accelerated biological aging (BioAgeAccel and PhenoAgeAccel) were set as primary exposure and were calculated. Logistic regression and restricted cubic spline regression were employed to examine the relationship between biological aging and periodontitis. Additionally, Mendelian randomization analysis was conducted to explore the causal connection between accelerated biological aging and periodontitis. After adjusting for age, gender, race, educational level, marital status, ratio of family income, and disease conditions, this study, found a significant association between subjects with older higher biological ages, accelerated biological aging, and periodontitis. Specifically, for a per year increase in the three biological ages (HD, KDM, and PhenoAge), the risk of periodontitis increases by 15%, 3%, and 4% respectively. Individuals who had positive BioAgeAccel or PhenoAgeAccel were 20% or 37% more likely to develop periodontitis compared with those who had negative BioAgeAccel or PhenoAgeAccel. Furthermore, a significant non-linear positive relationship was observed between the three biological ages, accelerated biological aging, and periodontitis. However, the Mendelian randomization analysis indicated no causal effect of accelerated biological aging on periodontitis. Our findings suggest that biological aging may contribute to the risk of periodontitis, highlighting the potential utility of preventive strategies targeting aging-related pathways in reducing periodontitis risk among older adults.

Exploration of the causal associations between circulating inflammatory proteins, immune cells, and neuromyelitis optica spectrum disorder: a bidirectional Mendelian randomization study and mediation analysis

Background

An increasing body of research has demonstrated a robust correlation between circulating inflammatory proteins and neuromyelitis optica spectrum disorders (NMOSD). However, whether this association is causal or whether immune cells act as mediators currently remains unclear.

Methods

We employed bidirectional two-sample Mendelian randomization (TSMR) analysis to examine the potential causal association between circulating inflammatory proteins, immune cells, and NMOSD using data from genome-wide association studies (GWAS). Five different methods for Mendelian randomization analyses were applied, with the inverse variance-weighted (IVW) method being the primary approach. Sensitivity analyses were further performed to assess the presence of horizontal pleiotropy and heterogeneity in the results. Finally, a two-step Mendelian randomization (MR) design was employed to examine the potential mediating effects of immune cells.

Results

A notable causal relationship was observed between three circulating inflammatory proteins (CSF-1, IL-24, and TNFRSF9) and genetically predicted NMOSD. Furthermore, two immune cell phenotypes, genetically predicted CD8 on naive CD8+ T cells, and Hematopoietic Stem Cell Absolute Count were negatively and positively associated with genetically predicted NMOSD, respectively, although they did not appear to function as mediators.

Conclusion

Circulating inflammatory proteins and immune cells are causally associated with NMOSD. Immune cells do not appear to mediate the pathway linking circulating inflammatory proteins to NMOSD.

An exploration of causal relationships between nine neurological diseases and the risk of breast cancer: a Mendelian randomization study

BACKGROUND

Some preceding researches have observed that certain neurological disorders, such as Alzheimer's disease and multiple sclerosis, may affect breast cancer risk. However, whether there are causal relationships between these neurological conditions and breast cancer is inconclusive. This study was designed to explore whether neurological disorders affected the risks of breast cancer overall and of the two subtypes (ER+ and ER-).

METHODS

In the course of this study, genome-wide association study (GWAS) data for nine neurological diseases (Alzheimer's disease, multiple sclerosis, Parkinson's disease, myasthenia gravis, generalized epilepsy, intracerebral haemorrhage, cerebral atherosclerosis, brain glioblastoma, and benign meningeal tumour) were collected from the Complex Trait Genetics lab and the MRC Integrative Epidemiology Unit, and single-nucleotide polymorphisms (SNPs) extensively associated with these neurological ailments had been recognized as instrumental variables (IVs). GWAS data on breast cancer were collected from the Breast Cancer Association Consortium (BCAC). Two-sample Mendelian randomization (MR) analyses as well as multivariable MR analyses were performed to determine whether these SNPs contributed to breast cancer risk. Additionally, the accuracy of the results was evaluated using the false discovery rate (FDR) multiple correction method. Both heterogeneity and pleiotropy were evaluated by analyzing sensitivities.

RESULTS

According to the results of two-sample MR analyses, Alzheimer's disease significantly reduced the risks of overall (OR 0.925, 95% CI [0.871-0.982], P = 0.011) and ER+ (OR 0.912, 95% CI [0.853-0.975], P = 0.007) breast cancer, but there was a negative result in ER- breast cancer. However, after multiple FDR corrections, the effect of Alzheimer's disease on overall breast cancer was not statistically significant. In contrast, multiple sclerosis significantly increased ER+ breast cancer risk (OR 1.007, 95% CI [1.003-1.011], P = 0.001). In addition, the multivariable MR analyses showed that Alzheimer's disease significantly reduced the risk of ER+ breast cancer (IVW: OR 0.929, 95% CI [0.864-0.999], P=0.047; MR-Egger: OR 0.916, 95% CI [0.846-0.992], P=0.031); however, multiple sclerosis significantly increased the risk of ER+ breast cancer (IVW: OR 1.008, 95% CI [1.003-1.012], P=4.35×10-4; MR-Egger: OR 1.008, 95% CI [1.003-1.012], P=5.96×10-4). There were no significant associations between the remainder of the neurological diseases and breast cancer.

CONCLUSIONS

This study found the trends towards a decreased risk of ER+ breast cancer in patients with Alzheimer's disease and an increased risk in patients with multiple sclerosis. However, due to the limitations of Mendelian randomization, we cannot determine whether there are definite causal relationships between neurological diseases and breast cancer risk. For conclusive evidences, more prospective randomized controlled trials will be needed in the future.

Examining the causal relationship between circulating immune cells and the susceptibility to osteomyelitis: A Mendelian randomization study

BACKGROUND

Osteomyelitis is considered as a deleterious inflammatory condition affecting the bone, primarily attributed to pathogenic infection. However, the underlying factors predisposing individuals to osteomyelitis remain incompletely elucidated. The immune system plays a multifaceted role in the progression of this condition, yet previous observational studies and randomized controlled trials investigating the association between circulating immune cell counts and osteomyelitis have been constrained. In order to address this knowledge gap, we conducted a Mendelian randomization (MR) analysis to evaluate the impact of diverse immune cell counts on the risk of developing osteomyelitis.

METHODS

In our study, we utilized single nucleotide polymorphisms (SNPs) that have been strongly linked to circulating immune cells or specific lymphocyte subtypes, as identified in large-scale genome-wide association studies (GWAS). These SNPs served as instrumental variables (IVs) for our MR analysis. We employed a more relaxed clumping threshold to conduct MR analysis on several related lymphocyte subtypes. To estimate causal effects, we utilized the Wald ratio, as well as the random-effects inverse variance weighted (IVW) and weighted median (WM) methods. To enhance the credibility of our results, we performed F-statistic calculations and a series of sensitivity analyses.

RESULTS

Our findings revealed a significant correlation between the absolute count of circulating lymphocytes and the risk of osteomyelitis [odds ratio(OR) 1.20；95 % confidence interval (CI), 1.08-1.32；P = 0.0005]. Furthermore, we identified a causal relationship between the absolute count of CD8+ T cells and susceptibility to osteomyelitis (OR 1.16; 95 % CI, 1.04-1.30; P = 0.0098). Importantly, these findings remained robust across a wide range of sensitivity analyses.

CONCLUSION

Through our MR analysis, we have provided evidence supporting a causal relationship between genetic predisposition to higher circulating immune cell counts and an increased risk of osteomyelitis. Specifically, our findings highlight the association between elevated CD8+ T cell counts and a heightened susceptibility to osteomyelitis. These results offer valuable insights for the future exploration of immunotherapy approaches in the management of osteomyelitis.

Association of genetically predicted 486 blood metabolites on the risk of Alzheimer's disease: a Mendelian randomization study

Background

Studies have reported that metabolic disturbance exhibits in patients with Alzheimer's disease (AD). Still, the presence of definitive evidence concerning the genetic effect of metabolites on AD risk remains insufficient. A systematic exploration of the genetic association between blood metabolites and AD would contribute to the identification of new targets for AD screening and prevention.

Methods

We conducted an exploratory two-sample Mendelian randomization (MR) study aiming to preliminarily identify the potential metabolites involved in AD development. A genome-wide association study (GWAS) involving 7,824 participants provided information on 486 human blood metabolites. Outcome information was obtained from a large-scale GWAS meta-analysis of AD, encompassing 21,982 cases and 41,944 controls of Europeans. The primary two-sample MR analysis utilized the inverse variance weighted (IVW) model while supplementary analyses used Weighted median (WM), MR Egger, Simple mode, and Weighted mode, followed by sensitivity analyses such as the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis. For the further identification of metabolites, replication and meta-analysis with FinnGen data, steiger test, linkage disequilibrium score regression, confounding analysis, and were conducted for further evaluation. Multivariable MR was performed to assess the direct effect of metabolites on AD. Besides, an extra replication analysis with EADB data was conducted for final evaluation of the most promising findings.

Results

After rigorous genetic variant selection, IVW, complementary analysis, sensitivity analysis, replication and meta-analysis with the FinnGen data, five metabolites (epiandrosterone sulfate, X-12680, pyruvate, docosapentaenoate, and 1-stearoylglycerophosphocholine) were identified as being genetically associated with AD. MVMR analysis disclosed that genetically predicted these four known metabolites can directly influence AD independently of other metabolites. Only epiandrosterone sulfate and X-12680 remained suggestive significant associations with AD after replication analysis with the EADB data.

Conclusion

By integrating genomics with metabonomics, this study furnishes evidence substantiating the genetic association of epiandrosterone sulfate and X-12680 with AD. These findings hold significance for the screening, prevention, and treatment strategies for AD.

Causality of genetically determined blood metabolites on irritable bowel syndrome: A Mendelian randomization study

BACKGROUND

Irritable bowel syndrome (IBS) is one of the most common functional bowel disorders and dysmetabolism plays an important role in the pathogenesis of disease. Nevertheless, there remains a lack of information regarding the causal relationship between circulating metabolites and IBS. A two-sample Mendelian randomization (MR) analysis was conducted in order to evaluate the causal relationship between genetically proxied 486 blood metabolites and IBS.

METHODS

A two-sample MR analysis was implemented to assess the causality of blood metabolites on IBS. The study utilized a genome-wide association study (GWAS) to examine 486 metabolites as the exposure variable while employing a GWAS study with 486,601 individuals of European descent as the outcome variable. The inverse-variance weighted (IVW) method was used to estimate the causal relationship of metabolites on IBS, while several methods were performed to eliminate the pleiotropy and heterogeneity. Another GWAS data was used for replication and meta-analysis. In addition, reverse MR and linkage disequilibrium score regression (LDSC) were employed for additional assessment. Multivariable MR analysis was conducted in order to evaluate the direct impact of metabolites on IBS.

RESULTS

Three known and two unknown metabolites were identified as being associated with the development of IBS. Higher levels of butyryl carnitine (OR(95%CI):1.10(1.02-1.18),p = 0.009) and tetradecanedioate (OR(95%CI):1.13(1.04-1.23),p = 0.003)increased susceptibility of IBS and higher levels of stearate(18:0)(OR(95%CI):0.72(0.58-0.89),p = 0.003) decreased susceptibility of IBS.

CONCLUSION

The metabolites implicated in the pathogenesis of IBS possess potential as biomarkers and hold promise for elucidating the underlying biological mechanisms of this condition.

Human blood metabolites and risk of sepsis: A Mendelian randomization investigation

BACKGROUND

Evidence supports the observational correlations between human blood metabolites and sepsis. However, whether these associations represent a causal relationship is unknown. In this study, we applied two-sample Mendelian randomization (MR) analyses to examine causality between genetically proxied 486 blood metabolites and sepsis risk.

METHODS

We used summary data from genome-wide association studies (GWAS) on 486 metabolites involving 7824 individuals as exposure and a sepsis GWAS including 11,643 cases and 474,841 controls as the outcome. The inverse-variance weighted (IVW) was the primary method to estimate the causal relationship between exposure and outcome, with MR-Egger and weighted median serving as supplements. Sensitivity analyses were implemented with Cochrane's Q test, MR-Egger intercept, MR-PRESSO and leave-one-out analysis. In addition, we performed replication MR, meta-analysis, Steiger test, linkage disequilibrium score (LDSC) regression and multivariable MR (MVMR) to thoroughly verify the causation.

RESULTS

We identified that genetically determined high levels of 1-oleoylglycerophosphoethanolamine (odds ratio (OR) = .52, 95% confidence interval (CI): .31-.87, p = .0122), alpha-glutamyltyrosine (OR = .75, 95% CI: .60-.93, p = .0102), heptanoate (7:0) (OR = .51, 95% CI: .33-.81, p = .0041) and saccharin (OR = .84, 95% CI: .74-.94, p = .0036) were causally associated with a lower risk of sepsis. MVMR analysis demonstrated the independent causal effect of these metabolites on sepsis.

CONCLUSIONS

These findings indicated that four blood metabolites have a protective impact on sepsis, thus providing novel perspectives into the metabolite-mediated development mechanism of sepsis by combining genomics and metabolomics.

Exploring the role of gut microbiota in migraine risk: a two-sample Mendelian randomization study

OBJECTIVES

The presence of intestinal flora in the gut has been linked to migraines in recent studies, but whether the association is causal or due to bias remains to be clarified. We aimed to explore whether there is a potential causal relationship between gut microbiota and migraine risk with this study.

MATERIALS AND METHODS

We conducted a two-sample Mendelian randomized analysis study to explore whether gut microbiota has a causal relationship with migraine using publicly available data from large-scale genome-wide association studies. The inverse variance weighting was used as the main method, and weighted median and MR-Egger were used as supplementary methods for causal inference. Sensitivity analyses, including leave-one-out analysis, Cochran Q test, and MR-Egger intercept test, were used to verify the robustness of the results.

RESULTS

After rigorous quality control of the results, we identified that genetic predisposition towards a higher abundance of genus.Lactobacillus was causally associated with higher of migraine (IVW OR = 1.10, 95% CI = 1.03 - 1.18, p = .004), whereas the higher abundance of family.Prvotellaceae predicted a decreased risk of migraine (IVW OR = 0.89, 95% CI = 0.80 - 0.98, p = .02). Sensitivity analyses indicated the results were not biased by pleiotropy.

CONCLUSION

According to our research, there is evidence showing that gut microbiota may be involved in migraine development, which suggested that a stool examination might be helpful to recognize those with a higher risk of migraine. Further mechanisms remained to be elucidated in future studies.

The relationship between human blood metabolites and preeclampsia-eclampsia: A Mendelian randomization study

Preeclampsia and eclampsia are serious complications of pregnancy, leading to high rates of maternal and neonatal mortality. During pregnancy, there are changes in relevant serum metabolites in women. However, it remains unclear if these serum metabolites contribute to the development of associated disorders during pregnancy. Therefore, we conducted a Mendelian randomization study to explore the causal relationship between serum metabolites and preeclampsia and eclampsia. We utilized the inverse variance weighted model as our primary analysis approach. We complemented this with sensitivity analyses, including the heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis, to ensure the robustness of our findings. Furthermore, we conducted linkage disequilibrium score regression, multivariable Mendelian randomization, and metabolic pathway analysis to further explore the genetic data. The Mendelian randomization analysis has identified γ-glutamylglutamine, inosine, and isoleucine 10 metabolites that are significantly associated with preeclampsia, and γ-glutamylglutamine and phenylacetate 8 metabolites that may potentially contribute to the development of eclampsia. Notably, γ-glutamylglutamine has been found to have a causal relationship with both preeclampsia and eclampsia. In the multivariable Mendelian randomization analysis, our research findings suggest that both isoleucine and X-14304-leucylalanine directly impact preeclampsia within the context of amino acids and peptides. Moreover, our observations reveal that carbohydrates can also have a direct effect on preeclampsia. Importantly, it should be emphasized that only 3-lactate in amino acids has been shown to have a direct influence on eclampsia. This research has the potential to enhance our understanding of the biological variances related to disease status, providing a foundation for future investigations.

Causal role of metabolites in non-small cell lung cancer: Mendelian randomization (MR) study

On a global scale, lung cancer(LC) is the most commonly occurring form of cancer. Nonetheless, the process of screening and detecting it in its early stages presents significant challenges. Earlier research endeavors have recognized metabolites as potentially reliable biomarkers for LC. However, the majority of these studies have been limited in scope, featuring inconsistencies in terms of the relationships and levels of association observed.Moreover, there has been a lack of consistency in the types of biological samples utilized in previous studies. Therefore, the main objective of our research was to explore the correlation between metabolites and Non-small cell lung cancer (NSCLC).Thorough two-sample Mendelian randomization (TSMR) analysis, we investigated potential cause-and-effect relationships between 1400 metabolites and the risk of NSCLC.The analysis of TSMR revealed a significant causal impact of 61 metabolites on NSCLC.To ensure the reliability and validity of our findings, we perform FDR correction for P-values by Benjaminiand Hochberg(BH) method, Our results indicate that Oleate/vaccenate (18:1) levels and Caffeine to paraxanthine ratio may be causally associated with an increased risk of NSCLC [Oleate/vaccenate(18:1)levels: OR = 1.171,95%CI: 1.085-1.265, FDR = 0.036; Caffeine to paraxanthine ratio: OR = 1.386, 95%CI:1.191-1.612,FDR = 0.032].

Causal relationship between dementia and delirium: Insights from a bidirectional two-sample Mendelian randomization analysis

BACKGROUND

Our previous study found dementia as a significant risk factor for delirium development in elderly patients with hip fracture. However, the causal relationship between dementia and delirium remains unclear.

METHODS

To assess the causal relationship between delirium and dementia, we conducted a bidirectional Mendelian randomization (MR) analysis. Inversevariance weighted (IVW), weighted median, MR Egger, weighted mode, and simple mode were employed to conduct the MR analysis. Heterogeneity was assessed using the Cochran Q statistic in MR-Egger and IVW methods. Horizontal pleiotropy was examined via the MR pleiotropy residual sum and outliers (MR-PRESSO) and MR-Egger intercept tests.

RESULTS

The forward MR analysis revealed a significant association between unclassified dementia (1.604 (1.326-1.941), p = 1.12 × 10-6), Alzheimer's disease (1.259 (1.128-1.405), p = 4.10 × 10-5), and dementia with Lewy bodies (1.121 (1.026-1.225), p = 0.011) with an increased risk of delirium. In the reverse MR analysis, delirium was also suggested to increase the risk of unclassified dementia (1.133 (1.066-1.204), p = 6.31 × 10-5) and vascular dementia (1.246 (1.075-1.444), p = 0.003). These significant results were further validated in the multivariable MR analysis. No evidence of heterogeneity or horizontal pleiotropy was observed (p > 0.05).

LIMITATIONS

(1) Limited to European populations. (2) Sample population overlap between delirium and dementia. (3) Not all dementia subtypes were causally associated with delirium.

CONCLUSIONS

This study provides genetic evidence supporting a causal relationship between dementia and delirium, indicating that dementia may influence the risk of delirium while delirium may also increase the risk of dementia.

Elucidating the relationship between metabolites and breast cancer: A Mendelian randomization study

The evidence about the causal roles of metabolites in breast cancer is lacking. This study conducted a systematic evaluation of the potential causal relationship between 1091 human blood metabolites, 309 metabolite ratios, and the likelihood of developing breast cancer and its subtype by employing a two-sample bidirectional Mendelian randomization (MR) approach Four metabolites, including tryptophan betaine (Odds Ratio [OR] = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.007), X-21312 (OR = 0.90, 95%CI = 0.86-0.94, Bonferroni-corrected P = 0.02), 3-bromo-5-chloro-2,6-dihydroxybenzoic acid (OR = 0.94, 95%CI = 0.91-0.96, Bonferroni-corrected P = 0.03) and X-18921 (OR = 0.96, 95%CI = 0.94-0.98, Bonferroni-corrected P = 0.04) were significantly associated with overall breast cancer using inverse-variance weighted (IVW) method. Tryptophan betaine was also significantly associated with estrogen receptor (ER)-positive breast cancer (OR = 1.08, 95%CI = 1.04-1.11, Bonferroni-corrected P = 0.03). X-23680 (OR = 1.10, 95%CI = 1.05-1.15, Bonferroni-corrected P = 0.04) and glycine to phosphate ratio (OR = 1.07, 95%CI = 1.04-1.10, Bonferroni-corrected P = 0.04) were associated with ER-negative breast cancer. Reverse MR analysis showed no significant associations between breast cancer and metabolites. This MR study indicated compelling evidence of a causal association between metabolites and the risk of breast cancer and its subtypes, underscoring the potential impact of metabolic interference on breast cancer risk and indicating the drug targets for breast cancer.

The Association Between SHBG and Osteoporosis: A NHANES Cross-Sectional Study and A Bidirectional Mendelian Randomization

This study aimed to examine the association between sex hormone-binding globulin (SHBG) and osteoporosis through a cross-sectional study and a two-sample bidirectional Mendelian randomization (MR). We used the National Health and Nutrition Examination Survey (NHANES) 2013-2014 and 2015-2016 data, with exposure as serum SHBG and outcome as osteoporosis and performed multivariate logistic regression to test the correlation between SHBG and osteoporosis. To determine the causal relationship between SHBG and osteoporosis, a two-sample bidirectional MR was employed. The genome-wide association study (GWAS) dataset for SHBG (n = 189,473) was obtained from the IEU database, and the GWAS dataset for osteoporosis (n = 212,778) was obtained from the FinnGen bioBank. The principal MR technique was inverse-variance weighting (IVW). In MR analyses, the MR-Egger intercept and Cochran Q test were used to detect multiple validity and horizontal heterogeneity. 1249 older adult participants (age ≥ 60) were involved in the cross-sectional study, including 113 osteoporosis cases. We identified a significant relationship between circulating SHBG concentration and osteoporosis risk [OR 3.963, 95% CI (2.095-7.495), P < 0.05]. Subgroup analysis indicated that SHBG was closely linked to the risk of osteoporosis in the female population [OR 1.008, 95% CI (1.002-1.013), P = 0.005] but not in males (P = 0.065). In addition, The IVW approach suggested a causal connection between SHBG and increased osteoporosis risk [OR 1.479, 95% CI (1.144-1.912), P = 0.003], and the MR-Egger intercept and the Cochran Q test validated the consistency of the MR results. Finally, the reverse MR analysis declined to identify a causal relation between SHBG and osteoporosis. Our research demonstrates a significant causal connection between circulating SHBG levels and increased osteoporosis risk. These results indicate that high SHBG may be associated with the risk of osteoporosis in postmenopausal women, but more research is needed.

Untargeted urine metabolomics and machine learning provide potential metabolic signatures in children with autism spectrum disorder

Background

Complementary to traditional biostatistics, the integration of untargeted urine metabolomic profiling with Machine Learning (ML) has the potential to unveil metabolic profiles crucial for understanding diseases. However, the application of this approach in autism remains underexplored. Our objective was to delve into the metabolic profiles of autism utilizing a comprehensive untargeted metabolomics platform coupled with ML.

Methods

Untargeted metabolomics quantification (UHPLC/Q-TOF-MS) was performed for urine analysis. Feature selection was conducted using Lasso regression, and logistic regression, support vector machine, random forest, and extreme gradient boosting were utilized for significance stratification. Pathway enrichment analysis was performed to identify metabolic pathways associated with autism.

Results

A total of 52 autistic children and 40 typically developing children were enrolled. Lasso regression identified ninety-two urinary metabolites that significantly differed between the two groups. Distinct metabolites, such as prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, were revealed to be associated with autism through the application of four different ML methods (p<0.05). The alterations observed in the phosphatidylinositol and inositol phosphate metabolism pathways were linked to the pathophysiology of autism (p<0.05).

Conclusion

Significant urinary metabolites, including prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, exhibit associations with autism. Additionally, the involvement of the phosphatidylinositol and inositol phosphate pathways suggests their potential role in the pathophysiology of autism.

Metabolic clues to aging: exploring the role of circulating metabolites in frailty, sarcopenia and vascular aging related traits and diseases

Background: Physical weakness and cardiovascular risk increase significantly with age, but the underlying biological mechanisms remain largely unknown. This study aims to reveal the causal effect of circulating metabolites on frailty, sarcopenia and vascular aging related traits and diseases through a two-sample Mendelian Randomization (MR) analysis. Methods: Exposures were 486 metabolites analyzed in a genome-wide association study (GWAS), while outcomes included frailty, sarcopenia, arterial stiffness, atherosclerosis, peripheral vascular disease (PAD) and aortic aneurysm. Primary causal estimates were calculated using the inverse-variance weighted (IVW) method. Methods including MR Egger, weighted median, Q-test, and leave-one-out analysis were used for the sensitive analysis. Results: A total of 125 suggestive causative associations between metabolites and outcomes were identified. Seven strong causal links were ultimately identified between six metabolites (kynurenine, pentadecanoate (15:0), 1-arachidonoylglycerophosphocholine, androsterone sulfate, glycine and mannose) and three diseases (sarcopenia, PAD and atherosclerosis). Besides, metabolic pathway analysis identified 13 significant metabolic pathways in 6 age-related diseases. Furthermore, the metabolite-gene interaction networks were constructed. Conclusion: Our research suggested new evidence of the relationship between identified metabolites and 6 age-related diseases, which may hold promise as valuable biomarkers.

The risk of common hypoglycemic and antihypertensive medications and COVID-19: A 2-sample Mendelian randomization study

BACKGROUND

It has been reported that diabetes and hypertension increase the adverse outcomes of coronavirus disease 2019 (COVID-19). Aside from the inherent factors of diabetes and hypertension, it remains unclear whether antidiabetic or antihypertensive medications contribute to the increased adverse outcomes of COVID-19. The effect of commonly used antidiabetic and antihypertensive medications on COVID-19 outcomes has been inconsistently concluded in existing observational studies. Conducting a systematic study on the causal relationship between these medications and COVID-19 would be beneficial in guiding their use during the COVID-19 pandemic.

METHODS

We employed the 2-sample Mendelian randomization approach to assess the causal relationship between 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and 3 commonly used antihypertensive medications (calcium channel blockers [CCB], ACE inhibitors, β-receptor blockers [BB]), and COVID-19 susceptibility, hospitalization, and severe outcomes. The genetic variations in the drug targets of the 5 antidiabetic medications and 3 antihypertensive medications were utilized as instrumental variables. European population-specific genome-wide association analysis (GWAS) data on COVID-19 from the Host Genetics Initiative meta-analyses were obtained, including COVID-19 susceptibility (n = 2597,856), COVID-19 hospitalization (n = 2095,324), and COVID-19 severity (n = 1086,211). The random-effects inverse variance-weighted estimation method was employed as the primary assessment technique, with various sensitivity analyses conducted to evaluate heterogeneity and pleiotropy.

RESULTS

There were no potential associations between the genetic variations in the drug targets of the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity (all P > .016).

CONCLUSION

The findings from this comprehensive Mendelian randomization analysis suggest that there may be no causal relationship between the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity.

The causal relationship between human blood metabolites and the risk of visceral obesity: a mendelian randomization analysis

BACKGROUND

We aimed to explore the causal relationship between blood metabolites and the risk of visceral obesity, as measured by visceral adipose tissue (VAT).

METHODS

Summary statistics for 486 blood metabolites and total, as well as sex-stratified, MRI-derived VAT measurements, adjusted for body mass index (BMI) and height, were collected from previous genome-wide association studies (GWAS). A two-sample Mendelian Randomization (MR) design was used. Comprehensive evaluation was further conducted, including sensitivity analysis, linkage disequilibrium score (LDSC) regression, Steiger test, and metabolic pathway analysis.

RESULTS

After multiple testing correction, arachidonate (20:4n6) has been implicated in VAT accumulation (β = 0.35, 95%CI:0.18-0.52, P < 0.001; FDR = 0.025). Additionally, several blood metabolites were identified as potentially having causal relationship (FDR < 0.10). Among them, lysine (β = 0.67, 95%CI: 0.28-1.06, P < 0.001; FDR = 0.074), proline (β = 0.30, 95%CI:0.13-0.48, P < 0.001; FDR = 0.082), valerate (β = 0.50, 95%CI:0.23-0.78, P < 0.001, FDR = 0.091) are associated with an increased risk of VAT accumulation. On the other hand, glycine (β=-0.21, 95%CI: -0.33-0.09), P < 0.001, FDR = 0.076) have a protective effect against VAT accumulation. Most blood metabolites showed consistent trends between different sexes. Multivariable MR analysis demonstrated the effect of genetically predicted arachidonate (20:4n6) and proline on VAT remained after accounting for BMI and glycated hemoglobin (HbA1c). There is no evidence of heterogeneity, pleiotropy, and reverse causality.

CONCLUSION

Our MR findings suggest that these metabolites may serve as biomarkers, as well as for future mechanistic exploration and drug target selection of visceral obesity.

Interaction between systemic iron parameters and left ventricular structure and function in the preserved ejection fraction population: a two-sample bidirectional Mendelian randomization study

BACKGROUND

Left ventricular (LV) remodeling and diastolic function in people with heart failure (HF) are correlated with iron status; however, the causality is uncertain. This Mendelian randomization (MR) study investigated the bidirectional causal relationship between systemic iron parameters and LV structure and function in a preserved ejection fraction population.

METHODS

Transferrin saturation (TSAT), total iron binding capacity (TIBC), and serum iron and ferritin levels were extracted as instrumental variables for iron parameters from meta-analyses of public genome-wide association studies. Individuals without myocardial infarction history, HF, or LV ejection fraction (LVEF) < 50% (n = 16,923) in the UK Biobank Cardiovascular Magnetic Resonance Imaging Study constituted the outcome dataset. The dataset included LV end-diastolic volume, LV end-systolic volume, LV mass (LVM), and LVM-to-end-diastolic volume ratio (LVMVR). We used a two-sample bidirectional MR study with inverse variance weighting (IVW) as the primary analysis method and estimation methods using different algorithms to improve the robustness of the results.

RESULTS

In the IVW analysis, one standard deviation (SD) increased in TSAT significantly correlated with decreased LVMVR (β = -0.1365; 95% confidence interval [CI]: -0.2092 to -0.0638; P = 0.0002) after Bonferroni adjustment. Conversely, no significant relationships were observed between other iron and LV parameters. After Bonferroni correction, reverse MR analysis showed that one SD increase in LVEF significantly correlated with decreased TSAT (β = -0.0699; 95% CI: -0.1087 to -0.0311; P = 0.0004). No heterogeneity or pleiotropic effects evidence was observed in the analysis.

CONCLUSIONS

We demonstrated a causal relationship between TSAT and LV remodeling and function in a preserved ejection fraction population.

Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent.

OBJECTIVE

We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure.

METHODS

MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis.

RESULTS

After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) =  - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology.

CONCLUSION

Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.

The causality between CD8+NKT cells and CD16-CD56 on NK cells with hepatocellular carcinoma: a Mendelian randomization study

BACKGROUND

Hepatocellular carcinoma (HCC), which is featured with high morbidity and mortality worldwide, is a primary malignant tumor of the liver. Recently, there is a wealth of supporting evidence revealing that NK cell-related immune traits are strongly associated with the development of HCC, but the causality between them has not been proven.

METHODS

Two-sample Mendelian randomization (MR) study was performed to probe the causal correlation between NK cell-related immune traits and HCC. Genetic variations in NK cell-related immune traits were extracted from recent genome-wide association studies (GWAS) of individuals with European blood lineage. HCC data were derived from the UK Biobank Consortium's GWAS summary count data, including a total of 372,184 female and male subjects, with 168 cases and 372,016 controls, all of whom are of European ancestry. Sensitivity analysis was mainly used for heterogeneity and pleiotropy testing.

RESULTS

Our research indicated the causality between NK cell-related immune traits and HCC. Importantly, CD8+NKT cells had protective causal effects on HCC (OR = 0.9996;95%CI,0.9993-0.9999; P = 0.0489). CD16-CD56 caused similar effects on NK cells (OR = 0.9997;95%CI,0.9996-0.9999; P = 0.0117) as CD8+NKT cells. Intercepts from Egger showed no pleiotropy and confounding factors. Furthermore, insufficient evidence was found to support the existence of heterogeneity by Cochran's Q test.

CONCLUSION

MR analysis suggested that low CD8+NKT cells and CD16-CD56 expression on NK cells were linked with a higher risk of HCC.

Causal relationship between human blood metabolites and risk of ischemic stroke: a Mendelian randomization study

Background: Ischemic stroke (IS) is a major cause of death and disability worldwide. Previous studies have reported associations between metabolic disorders and IS. However, evidence regarding the causal relationship between blood metabolites and IS lacking. Methods: A two-sample Mendelian randomization analysis (MR) was used to assess the causal relationship between 1,400 serum metabolites and IS. The inverse variance-weighted (IVW) method was employed to estimate the causal effect between exposure and outcome. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode approaches were employed as supplementary comprehensive evaluations of the causal effects between blood metabolites and IS. Tests for pleiotropy and heterogeneity were conducted. Results: After rigorous selection, 23 known and 5 unknown metabolites were identified to be associated with IS. Among the 23 known metabolites, 13 showed significant causal effects with IS based on 2 MR methods, including 5-acetylamino-6-formylamino-3-methyluracil, 1-ribosyl-imidazoleacetate, Behenoylcarnitine (C22), N-acetyltyrosine, and N-acetylputrescine to (N (1) + N (8))-acetate,these five metabolites were positively associated with increased IS risk. Xanthurenate, Glycosyl-N-tricosanoyl-sphingadienine, Orotate, Bilirubin (E,E), Bilirubin degradation product, C17H18N2O, Bilirubin (Z,Z) to androsterone glucuronide, Bilirubin (Z,Z) to etiocholanolone glucuronide, Biliverdin, and Uridine to pseudouridine ratio were associated with decreased IS risk. Conclusion: Among 1,400 blood metabolites, this study identified 23 known metabolites that are significantly associated with IS risk, with 13 being more prominent. The integration of genomics and metabolomics provides important insights for the screening and prevention of IS.

Evaluation of the causal effects of blood metabolites on irritable bowel syndrome: Mendelian randomization

BACKGROUND

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder characterized by abdominal pain, discomfort, and changes in bowel habits. The mechanism underlying IBS remains unclear, and little evidence exists for clarifying the causal relationship between blood metabolites and IBS.

METHODS

We conducted a Mendelian randomization (MR) study using two samples. Exposure data for 7824 Europeans were extracted from a genome-wide association study (GWAS) on metabolite levels. The IBS GWAS data from the GWAS database were used for the initial analysis. The primary analysis of causal relationships was conducted using inverse-variance weighting (IVW) with MR-Egger and weighted medians as supplementary analyses. Sensitivity analyses were performed using a combination of the Cochran's Q test, MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier, and leave-one-out analysis. For significant associations, replication and meta-analyses were performed using additional independent IBS case GWAS data released by the FinnGen Consortium R9. To identify the metabolites, score regression, confounding analysis, and reverse MR were performed to further assess the causal relationships between the metabolites.

RESULTS

After rigorous screening, we identified four known metabolites to be associated with IBS (stearate, odds ratio [OR]: 0.74, 95% confidence interval [CI]: 0.59-0.92; arginine, OR: 1.36, 95% CI: 1.07-1.74; 1-palmitoylglycerol, OR:1.49, 95% CI: 1.07-2.07; 1-palmitoylglycerophosphoinositol, OR: 0.84, 95% CI: 0.71-0.99).

CONCLUSIONS

MR analysis revealed a causal relationship between the four metabolites and IBS, providing preliminary evidence for the pathogenesis of IBS. Our results provide novel insights into the potential biomarkers of IBS.

Causal roles of immune cells in cardiovascular diseases: A Mendelian randomization (MR) study

Background

Despite being a major global cause of mortality, the exact underlying mechanisms of cardiovascular diseases (CVDs) remain uncertain. This study aimed to elucidate the possible pathological connection between circulating activated immune cell types and the advancement of CVD.

Methods

A two-sample Mendelian randomization analysis was performed on publicly available genetic databases to examine the potential causal relationships among 731 immune phenotypes and CVD risks. The study focused on four distinct immune signatures: relative cell counts (RC), absolute cell counts (AC), morphological parameters (MP), and median fluorescence intensities (MFI). A sensitivity analysis was performed to assess the findings' consistency, robustness, and potential pleiotropic effects.

Results

Significant associations between CVD and various immunophenotypes were observed in this study. Specifically, two phenotypes exhibited protective effects against CVD. The odds ratio (OR) for activated and secretory CD4+ regulatory T-cells (Tregs) was 0.757 [95% confidence interval (CI): 0.628-0.913; p = 0.004], whereas that for B-cell activating factor receptor on IgD-CD38+ memory B-cells was 0.654 (95% CI: 0.468-0.915; p = 0.013). Conversely, three major immunophenotypes were linked to heightened risks of CVD: CD80 on myeloid dendritic cells (OR: 1.181; 95% CI: 1.015-1.376; p = 0.032), the proportion of CD28+ CD45RA+ CD8+ T-cells in total T-cell population (OR: 1.064; 95% CI: 1.002-1.128; p = 0.041), and the proportion of CD28-CD45RA+ CD8+ T-cells in total T-cell population (OR: 1.005; 95% CI: 1.000-1.011; p = 0.045).

Conclusion

This study underscores significant correlations between specific immune phenotypes and the risks associated with CVD onset, thus providing valuable perspectives for forthcoming clinical inquiries.

Causal association of immune cells and polycystic ovarian syndrome: a Mendelian randomization study

Background

Polycystic ovarian syndrome (PCOS) is a common reproductive disorder that affects a considerable number of women worldwide. It is accompanied by irregular menstruation, hyperandrogenism, metabolic abnormalities, reproductive disorders and other clinical symptoms, which seriously endangers women's physical and mental health. The etiology and pathogenesis of PCOS are not completely clear, but it is hypothesized that immune system may play a key role in it. However, previous studies investigating the connection between immune cells and PCOS have produced conflicting results.

Methods

Mendelian randomization (MR) is a powerful study design that uses genetic variants as instrumental variables to enable examination of the causal effect of an exposure on an outcome in observational data. In this study, we utilized a comprehensive two-sample MR analysis to examine the causal link between 731 immune cells and PCOS. We employed complementary MR methods, such as the inverse-variance weighted (IVW) method, and conducted sensitivity analyses to evaluate the reliability of the outcomes.

Results

Four immunophenotypes were identified to be significantly associated with PCOS risk: Memory B cell AC (IVW: OR [95%]: 1.123[1.040 to 1.213], p = 0.003), CD39+ CD4+ %CD4+ (IVW: OR [95%]: 0.869[0.784 to 0.963], p = 0.008), CD20 on CD20- CD38-(IVW: OR [95%]:1.297[1.088 to 1.546], p = 0.004), and HLA DR on CD14- CD16+ monocyte (IVW: OR [95%]:1.225[1.074 to 1.397], p = 0.003). The results of the sensitivity analyses were consistent with the main findings.

Conclusions

Our MR analysis provides strong evidence supporting a causal association between immune cells and the susceptibility of PCOS. This discovery can assist in clinical decision-making regarding disease prognosis and treatment options, and also provides a new direction for drug development.

Evaluating the causal relationship between human blood metabolites and gastroesophageal reflux disease

BACKGROUND

Gastroesophageal reflux disease (GERD) affects approximately 13% of the global population. However, the pathogenesis of GERD has not been fully elucidated. The development of metabolomics as a branch of systems biology in recent years has opened up new avenues for the investigation of disease processes. As a powerful statistical tool, Mendelian randomization (MR) is widely used to explore the causal relationship between exposure and outcome.

AIM

To analyze of the relationship between 486 blood metabolites and GERD.

METHODS

Two-sample MR analysis was used to assess the causal relationship between blood metabolites and GERD. A genome-wide association study (GWAS) of 486 metabolites was the exposure, and two different GWAS datasets of GERD were used as endpoints for the base analysis and replication and meta-analysis. Bonferroni correction is used to determine causal correlation features (P < 1.03 × 10-4). The results were subjected to sensitivity analysis to assess heterogeneity and pleiotropy. Using the MR Steiger filtration method to detect whether there is a reverse causal relationship between metabolites and GERD. In addition, metabolic pathway analysis was conducted using the online database based MetaboAnalyst 5.0 software.

RESULTS

In MR analysis, four blood metabolites are negatively correlated with GERD: Levulinate (4-oxovalerate), stearate (18:0), adrenate (22:4n6) and p-acetamidophenylglucuronide. However, we also found a positive correlation between four blood metabolites and GERD: Kynurenine, 1-linoleoylglycerophosphoethanolamine, butyrylcarnitine and guanosine. And bonferroni correction showed that butyrylcarnitine (odd ratio 1.10, 95% confidence interval: 1.05-1.16, P = 7.71 × 10-5) was the most reliable causal metabolite. In addition, one significant pathways, the "glycerophospholipid metabolism" pathway, can be involved in the pathogenesis of GERD.

CONCLUSION

Our study found through the integration of genomics and metabolomics that butyrylcarnitine may be a potential biomarker for GERD, which will help further elucidate the pathogenesis of GERD and better guide its treatment. At the same time, this also contributes to early screening and prevention of GERD. However, the results of this study require further confirmation from both basic and clinical real-world studies.

Circulating Biomarkers and Risk of Hypertension: A Two-Sample Mendelian Randomisation Study

OBJECTIVE

This study systematically assessed circulating proteins to identify new serum biomarkers and risk of hypertension using Mendelian randomisation.

METHODS

The associations between 4,782 human circulating proteins and the risk of hypertension were evaluated using two-sample Mendelian randomisation. The FinnGen study demonstrated a link between genetic predisposition and hypertension in 85,438 cases and 223,663 controls.

RESULTS

Inverse variance weighted and sensitivity analysis revealed nine proteins in circulation that have a causative effect on hypertension. SMOC1 and TIE1 were determined to be causative factors in the decreased likelihood of developing hypertension, with odds ratios of 0.86 (95% CI 0.81-0.91; p=1.06e-06) and 0.96 (95% CI 0.94-0.98; p=9.39e-05), respectively. NDUFB4, ETHE1, POFUT2, TRIL, ADAM23, GXYLT1, OXT, TPST2, and TMCC3 showed a possible connection to hypertension.

CONCLUSIONS

This two-sample Mendelian randomisation study found that SMOC1 and TIE1 are causally linked to hypertension, making them a promising target for therapy.

Human blood metabolites and risk of severe COVID-19: A Mendelian randomization study

BACKGROUND

Evidence supports the observational associations of human blood metabolites with the risk of severe COVID-19. However, little is known about the potential pathological mechanisms and the analysis of blood metabolites may offer a better understanding of the underlying biological processes.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 486 blood metabolites and the risk of severe COVID-19. The inverse-variance weighted (IVW) model was used as the primary two-sample MR analysis method to estimate the causal relationship of the exposure on the outcome. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot.

RESULTS

Four hunderd and eighty six metabolites were included for MR analysis following rigorous genetic variants selection. After MR analyses and sensitivity analysis filtration, we found weak evidence of an association between 3-hydroxybutyrate (odds ratio [OR] = 1.21, 95% CI, 1.07-1.38, p = .0036) and the risk of severe COVID-19. A series of sensitivity analyses have been carried out to confirm the rigidity of the above results.

CONCLUSION

This study suggested a causal relationship between 3-hydroxybutyrate and the severity of COVID-19, thus providing novel insights into biomarkers and pathways for COVID-19 prevention and clinical interventions.

Causal relationship between blood metabolites and risk of five infections: a Mendelian randomization study

OBJECTIVE

Infectious diseases continue to pose a significant threat in the field of global public health, and our understanding of their metabolic pathogenesis remains limited. However, the advent of genome-wide association studies (GWAS) offers an unprecedented opportunity to unravel the relationship between metabolites and infections.

METHODS

Univariable and multivariable Mendelian randomization (MR) was commandeered to elucidate the causal relationship between blood metabolism and five high-frequency infection phenotypes: sepsis, pneumonia, upper respiratory tract infections (URTI), urinary tract infections (UTI), and skin and subcutaneous tissue infection (SSTI). GWAS data for infections were derived from UK Biobank and the FinnGen consortium. The primary analysis was conducted using the inverse variance weighted method on the UK Biobank data, along with a series of sensitivity analyses. Subsequently, replication and meta-analysis were performed on the FinnGen consortium data.

RESULTS

After primary analysis and a series of sensitivity analyses, 17 metabolites were identified from UK Biobank that have a causal relationship with five infections. Upon joint analysis with the FinGen cohort, 7 of these metabolites demonstrated consistent associations. Subsequently, we conducted a multivariable Mendelian randomization analysis to confirm the independent effects of these metabolites. Among known metabolites, genetically predicted 1-stearoylglycerol (1-SG) (odds ratio [OR] = 0.561, 95% confidence interval [CI]: 0.403-0.780, P < 0.001) and 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) (OR = 0.780, 95%CI: 0.689-0.883, P < 0.001) was causatively associated with a lower risk of sepsis, and genetically predicted phenylacetate (PA) (OR = 1.426, 95%CI: 1.152-1.765, P = 0.001) and cysteine (OR = 1.522, 95%CI: 1.170-1.980, P = 0.002) were associated with an increased risk of UTI. Ursodeoxycholate (UDCA) (OR = 0.906, 95%CI: 0.829-0.990, P = 0.029) is a protective factor against pneumonia. Two unknown metabolites, X-12407 (OR = 1.294, 95%CI: 1.131-1.481, P < 0.001), and X-12847 (OR = 1.344, 95%CI: 1.152-1.568, P < 0.001), were also identified as independent risk factors for sepsis.

CONCLUSIONS

In this MR study, we demonstrated a causal relationship between blood metabolites and the risk of developing sepsis, pneumonia, and UTI. However, there was no evidence of a causal connection between blood metabolites and the risk of URTI or SSTI, indicating a need for larger-scale studies to further investigate susceptibility to certain infection phenotypes.

GDF-15 (a biomarker for metformin) and the risk of COVID-19: A two-sample Mendelian randomization study

BACKGROUND

Regarding the impact of metformin on COVID-19, there are currently varying opinions from multiple studies. Growth differentiation factor 15 (GDF-15) is a biomarker of metformin use and dosage, and we used two-sample Mendelian randomization (MR) to assess the causal effect of GDF-15 (metformin) on COVID-19 susceptibility, hospitalization, and severe COVID-19, thereby guiding the selection of glucose-lowering agents for diabetic patients during the COVID-19 pandemic.

METHODS

Two sets of genetic tools were utilized for MR analysis, derived from publicly available genetic data. The first set was GDF-15 genome-wide association study (GWAS) data from a study with 5440 participants, while the second set was COVID-19 GWAS data from the Host Genetics Initiative (HGI) GWAS meta-analysis. The primary method used to assess causal effects was random effects inverse variance weighted estimation. Complementary methods included weighted median and MR-Egger analyses. Sensitivity analysis was performed using Cochran Q tests, MR-Egger intercept tests, MR-PRESSO, leave-one-out analyses, and funnel plots.

RESULTS

GDF-15 increased the risk of severe COVID-19 in patients (OR = 1.10, 95% CI 1.03-1.19; P = .006); there was no causal effect of GDF-15 on hospitalization for COVID-19 (OR = 1.02, 95% CI 0.96-1.07; P = .47) or susceptibility to COVID-19 in the general population (OR = 1.010, 95% CI 0.988-1.034; P = .354).

CONCLUSIONS

Our study supports the notion that GDF-15 increases the risk of severe COVID-19 in patients. However, there is no causal relationship between GDF-15 and hospitalization or susceptibility to COVID-19.

The causal effects of genetically determined human blood metabolites on the risk of atrial fibrillation

Background

Blood metabolites have been found related to atrial fibrillation (AF), but the causal role is still unclear. Mendel randomization (MR) can give information about the causality between blood metabolites and AF.

Methods

Two-sample MR analysis was used to evaluate the causality between 486 blood metabolites and AF. Firstly, the genome-wide association study (GWAS) data for AF (from Nielsen et al.) was analyzed and some metabolites were identified. Then another GWAS data for AF (from Roselli et al.) was repeatedly analyzed to verify the results. Inverse variance weighted method was mainly used to determine the causality, and MR-egger, Weighted Median, and MR-PRESSO models were used as supplements of MR. Cochran's Q test was used to assess heterogeneity. And MR-Egger intercept and MR-PRESSO global test were performed to measure pleiotropy.

Results

The study used Bonferroni's corrected P value (P < 1.03 × 10-4) as the significance threshold. After MR analysis and replication analysis, we found two overlapped metabolites. Among which tryptophan betaine was the most significant causal metabolite in both AF GWAS data (from Nielsen et al.) (odds ratio (OR) = 0.83, 95% confidence interval (CI) = 0.76-0.90, P = 9.37 × 10-6) and AF GWAS data (from Roselli et al.) (OR = 0.82, 95% CI = 0.76-0.88, P = 2.00 × 10-7), while uridine was nominally significant metabolites in both AF GWAS data (from Nielsen et al.) (OR = 0.58, 95% CI = 0.40-0.84, P = 0.004) and AF GWAS data (from Roselli et al.) (OR = 0.56, 95% CI = 0.35-0.88, P = 0.01). And the results of sensitivity analysis showed that none of them had obvious heterogeneity or pleiotropy.

Conclusion

The study identified several blood metabolites that were causally related to AF, which may provide new perspectives on the pathogenesis of AF.