Tea consumption and risk of lower respiratory tract infections: a two-sample mendelian randomization study

Bidirectional Mendelian Randomization of Causal Relationship between Inflammatory Cytokines and Different Pathological Types of Lung Cancer

Prior research has proposed a potential association between lung cancer and inflammatory cytokines, yet the specific causal relationship remains unclear, especially across various lung cancer pathologies. This study utilized bidirectional Mendelian randomization (MR) to explore these causal connections, unveiling novel insights. Our research revealed distinctive inflammatory cytokine profiles for each subtype of lung cancer and identified potential biomarkers that could refine diagnostic and therapeutic approaches. We applied two-sample Mendelian randomization, leveraging genetic variance data from three extensive genome-wide association studies (GWAS) focusing on different lung cancer types (lung adenocarcinoma: 1590 cases and 314,193 controls of healthy individuals of European descent; lung squamous cell carcinoma: 1510 cases and 314,193 controls of European ancestry; small cell lung cancer: 717 cases and 314,193 controls of European ancestry). A separate GWAS summary on inflammatory cytokines from 8,293 healthy participants was also included. The inverse variance weighting method was utilized to examine causal relationships, with robustness confirmed through multiple sensitivity analyses, including MR-Egger, weighted median, and MR-PRESSO. Our analysis revealed that elevated levels of IL_1RA were associated with an increased risk of lung adenocarcinoma (OR: 1.29, 95% CI: 1.02-1.64, p = 0.031), while higher MCP_1_MCAF levels correlated with a decreased risk of lung squamous cell carcinoma (OR: 0.77, 95% CI: 0.61-0.98, p = 0.031). Furthermore, IL_10, IL_13, and TRAIL levels were positively associated with lung squamous cell carcinoma risk (IL_10: OR: 1.27, 95% CI: 1.06-1.53, p = 0.012; IL_13: OR: 1.15, 95% CI: 1.06-1.53, p = 0.036; TRAIL: OR: 1.15, 95% CI: 1.06-1.53, p = 0.043). No association was found between inflammatory cytokine levels and small cell lung cancer development, whereas SDF_1A and B-NGF were linked to an increased risk of this cancer type (SDF_1A: OR: 1.13, 95% CI: 1.05-1.21, p = 0.001; B-NGF: OR: 1.13, 95% CI: 1.01-1.27, p = 0.029). No significant relationship was observed between the 41 circulating inflammatory cytokines and lung adenocarcinoma or squamous cell carcinoma development. Our findings indicate distinct associations between specific inflammatory cytokines and different types of lung cancer. Elevated IL_1RA levels are a risk marker for lung adenocarcinoma, whereas higher MCP_1_MCAF levels appear protective against lung squamous cell carcinoma. Conversely, elevated levels of IL_10, IL_13, and TRAIL are linked with an increased risk of lung squamous cell carcinoma. The relationships of SDF_1A and B-NGF with small-cell lung cancer highlight the complexity of inflammatory markers in cancer development. This study provides a nuanced understanding of the role of inflammatory cytokines in lung cancer, underscoring their potential in refining diagnosis and treatment strategies.

Iron, copper, zinc and magnesium on rheumatoid arthritis: a two-sample Mendelian randomization study

This study aimed to elucidate the causal genetic relationships between iron, copper, zinc, magnesium, and rheumatoid arthritis (RA). A two-sample Mendelian randomization (MR) analysis was conducted using the "TwoSampleMR" and "MendelianRandomization" packages in R. The random-effects inverse variance-weighted (IVW) method was used as the primary approach. We performed sensitivity analyses to test the reliability of the results. The random-effects IVW analysis revealed that there was no genetic causal relationship between iron (P = 0.429, odds ratio [OR] 95% confidence interval [CI] = 0.919 [0.746-1.133]), copper (P = 0.313, OR 95% CI = 0.973 [0.921-1.027]), zinc (P = 0.633, OR 95% CI = 0.978 [0.891-1.073]), or magnesium (P = 0.218, OR 95% CI = 0.792 [0.546-1.148]) and RA. Sensitivity analysis verified the reliability of the results. Therefore, there is no evidence to support a causal relationship between iron, copper, zinc, and magnesium intake at the genetic level and the development of RA.

Exploring causal correlations of inflammatory biomarkers in idiopathic normal-pressure hydrocephalus: insights from bidirectional Mendelian randomization analysis

Background and objective

Neuroinflammatory processes have been identified as playing a crucial role in the pathophysiology of various neurodegenerative diseases, including idiopathic normal-pressure hydrocephalus (iNPH). iNPH, defined as a common disease of cognitive impairment in older adults, poses major challenges for therapeutic interventions owing to the stringent methodological requirements of relevant studies, clinical heterogeneity, unclear etiology, and uncertain diagnostic criteria. This study aims to assess the relationship between circulating inflammatory biomarkers and iNPH risk using bidirectional two-sample Mendelian randomization (MR) combined with meta-analysis.

Methods

In our bidirectional MR study, genetic data from a genome-wide association study (GWAS) involving 1,456 iNPH cases and 409,726 controls of European ancestry were employed. Single-nucleotide polymorphisms (SNPs) associated with exposures served as instrumental variables for estimating the causal relationships between iNPH and 132 types of circulating inflammatory biomarkers from corresponding GWAS data. Causal associations were primarily examined using the inverse variance-weighted method, supplemented by MR-Egger, weighted median, simple mode, and weighted mode analyses. In the results, heterogeneity was assessed using the Cochran Q test. Horizontal pleiotropy was evaluated through the MR-Egger intercept test and the MR pleiotropy residual sum and outliers test. Sensitivity analysis was conducted through leave-one-out analysis. Reverse MR analyses were performed to mitigate bias from reverse causality. Meta-analyses of identical inflammatory biomarkers from both data sources strengthened the findings.

Results

Results indicated a genetically predicted association between Interleukin-16 (IL-16) [OR: 1.228, 95% CI: 1.049-1.439, p = 0.011], TNF-related apoptosis ligand (TRAIL) [OR: 1.111, 95% CI: 1.019-1.210, p = 0.017] and Urokinase-type plasminogen activator (uPA) [OR: 1.303, 95% CI: 1.025-1.658, p = 0.031] and the risk of iNPH. Additionally, changes in human Glial cell line-derived neurotrophic factor (hGDNF) [OR: 1.044, 95% CI: 1.006-1.084, p = 0.023], Matrix metalloproteinase-1 (MMP-1) [OR: 1.058, 95% CI: 1.020, 1.098, p = 0.003] and Interleukin-12p70 (IL-12p70) [OR: 0.897, 95% CI: 0.946-0.997, p = 0.037] levels were identified as possible consequences of iNPH.

Conclusion

Our MR study of inflammatory biomarkers and iNPH, indicated that IL-16, TRAIL, and uPA contribute to iNPH pathogenesis. Furthermore, iNPH may influence the expression of hGDNF, MMP-1, and IL-12p70. Therefore, targeting specific inflammatory biomarkers could be promising strategy for future iNPH treatment and prevention.

The association between fatty acids and atherosclerotic diseases: A mendelian randomization study

BACKGROUND

The current observational studies have disputed the relationship between various fatty acids and atherosclerotic diseases, and the causal relationship between the two is still unclear.

METHODS

In this study, we utilized the available genome-wide association studies (GWAS) summary data on fatty acids and atherosclerotic diseases from the IEU OpenGWAS project. After identifying the appropriate single nucleotide polymorphisms (SNPs) as instrumental variables, we employed the MR-PRESSO outlier test to remove extreme values. Subsequently, we conducted a two-sample mendelian randomization (MR) analysis and performed sensitivity analyses to ensure the reliability of the results.

RESULTS

The results of MR analysis suggest that ratio of saturated fatty acids to total fatty acids is positively correlated with the incidence rate of coronary heart disease (OR = 1.341, 95% CI = 1.016-1.769, P value = 0.038), monounsaturated fatty acid levels is negatively correlated with the incidence of stroke (OR = 0.800, 95% CI = 0.642-0.996, P value = 0.046), and docosahexaenoic acid levels is negatively correlated with the incidence of peripheral artery disease (OR = 0.747, 95% CI = 0.572-0.976, P value = 0.033). All results showed no heterogeneity or pleiotropy, but leave-one-out tests showed that the analysis results of some fatty acids were driven by a single SNP.

CONCLUSIONS

This study highlights the existence of causal relationships between fatty acids and atherosclerotic diseases at the genetic level. These findings provide valuable insights for potential prevention measures and therapeutic targets for the three atherosclerotic diseases.

The genetic causal relationship between type 2 diabetes, glycemic traits and venous thromboembolism, deep vein thrombosis, pulmonary embolism: a two-sample Mendelian randomization study

OBJECTIVE

To investigate the genetic underpinnings of the association between type 2 diabetes (T2D), glycemic indicators such as fasting glucose (FG), fasting insulin (FI), and glycated hemoglobin (GH), and venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), thereby contributing novel insights to the scholarly discourse within this domain.

METHODS

Genome-wide association study (GWAS) summary data pertaining to exposures (T2D, FG, FI, GH) and outcomes (VTE, DVT, PE) were acquired from the IEU Open GWAS database, encompassing participants of European descent, including both male and female individuals. Two-sample Mendelian randomization (MR) analyses were conducted utilizing the TwoSampleMR and MRPRESSO packages within the R programming environment. The primary analytical approach employed was the random-effects inverse variance weighted (IVW) method. Heterogeneity was assessed via Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger. Horizontal pleiotropy was evaluated using the intercept test of MR Egger and MR pleiotropy residual sum and outlier (MR-PRESSO) analysis, with the latter also employed for outlier detection. Additionally, a "Leave one out" analysis was conducted to ascertain the influence of individual single nucleotide polymorphisms (SNPs) on MR results.

RESULTS

The random-effects IVW analysis revealed a negative genetic causal association between T2D) and VTE (P = 0.008, Odds Ratio [OR] 95% confidence interval [CI] = 0.896 [0.827-0.972]), as well as between FG and VTE (P = 0.002, OR 95% CI = 0.655 [0.503-0.853]), GH and VTE (P = 0.010, OR 95% CI = 0.604 [0.412-0.884]), and GH and DVT (P = 0.002, OR 95% CI = 0.413 [0.235-0.725]). Conversely, the random-effects IVW analysis did not detect a genetic causal relationship between FI and VTE (P > 0.05), nor between T2D, FG, or FI and DVT (P > 0.05), or between T2D, FG, FI, or GH and PE (P > 0.05). Both the Cochran's Q statistic for MR-IVW and Rucker's Q statistic for MR-Egger indicated no significant heterogeneity (P > 0.05). Moreover, the intercept tests of MR Egger and MR-PRESSO suggested the absence of horizontal pleiotropy (P > 0.05). MR-PRESSO analysis identified no outliers, while the "Leave one out" analysis underscored that the MR analysis was not influenced by any single SNP.

CONCLUSION

Our investigation revealed that T2D, FG, and GH exhibit negative genetic causal relationships with VTE at the genetic level, while GH demonstrates a negative genetic causal relationship with DVT at the genetic level. These findings furnish genetic-level evidence warranting further examination of VTE, DVT, and PE, thereby making a contribution to the advancement of related research domains.

Proteome-wide Mendelian randomization identifies therapeutic targets for ankylosing spondylitis

Background

Ankylosing Spondylitis (AS) is a chronic inflammatory disorder which can lead to considerable pain and disability. Mendelian randomization (MR) has been extensively applied for repurposing licensed drugs and uncovering new therapeutic targets. Our objective is to pinpoint innovative therapeutic protein targets for AS and assess the potential adverse effects of druggable proteins.

Methods

We conducted a comprehensive proteome-wide MR study to assess the causal relationships between plasma proteins and the risk of AS. The plasma proteins were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) database, encompassing GWAS data for 2,940 plasma proteins. Additionally, GWAS data for AS were extracted from the R9 version of the Finnish database, including 2,860 patients and 270,964 controls. The colocalization analysis was executed to identify shared causal variants between plasma proteins and AS. Finally, we examined the potential adverse effects of druggable proteins for AS therapy by conducting a phenome-wide association study (PheWAS) utilizing the extensive Finnish database in version R9, encompassing 2,272 phenotypes categorized into 46 groups.

Results

The findings revealed a positive genetic association between the predicted plasma levels of six proteins and an elevated risk of AS, while two proteins exhibited an inverse association with AS risk (P fdr < 0.05). Among these eight plasma proteins, colocalization analysis identified AIF1, TNF, FKBPL, AGER, ALDH5A1, and ACOT13 as shared variation with AS(PPH3+PPH4>0.8), suggesting that they represent potential direct targets for AS intervention. Further phenotype-wide association studies have shown some potential side effects of these six targets (P fdr < 0.05).

Conclusion

Our investigation examined the causal connections between six plasma proteins and AS, providing a comprehensive understanding of potential therapeutic targets.

Green Tea Intake: A Protective Factor Against Postsurgical Hypothyroidism and Hypoparathyroidism

PURPOSE

Tea and coffee are the most commonly consumed types of drinks, identified with multiple health benefits. However, the association between tea and coffee intake and postsurgical hypothyroidism and hypoparathyroidism (PHypoTP) is still unclear. Therefore, the objective of this study is to explore the effect of tea and coffee intake on the risk of PHypoTP.

DESIGN

Two-sample Mendelian randomization (MR).

METHODS

The primary approach for MR estimates was the inverse-variance-weighted method. MR-Egger, MR Pleiotropy RESidual Sum and Outlier (PRESSO), weighted median, simple mode, and weighted mode were used to detect pleiotropy and heterogeneity.

FINDINGS

We found that green tea intake was causally associated with the decreased risk of PHypoTP (β = -0.019; 95% confidence interval: -0.038 to -0.001; P = .029). However, there was no significant association between coffee intake and the risk of PHypoTP. No heterogeneity or pleiotropy in these results was detected.

CONCLUSIONS

Our findings provide the genetic evidence supporting that green tea intake was a protective factor against PHypoTP. Accordingly, we may suggest that patients after thyroidectomy to add green tea into their habitual diet during nursing education.

The causal effect of oxidative stress on the risk of glaucoma

Glaucoma is a complex multifactorial disease. Oxidative stress has been implicated in its pathogenesis. However, establishing a causal relationship between oxidative stress and glaucoma is challenging due to confounding and reverse causality. In this study, we performed bidirectional two-sample Mendelian randomization (MR) analyses based on genetic instrumental variables as proxies for 11 biomarkers of oxidative stress injury to investigate the causal relationship between oxidative stress and glaucoma. Eight significant associations were identified. Increased circulating levels of catalase (OR = 0.915, 95 % CI: 0.848-0.987, P = 0.022), retinol (OR = 0.481, 95 % CI: 0.248-0.932, P = 0.044) and superoxide dismutase (OR = 0.779, 95 % CI: 0. 616-0.986, P = 0.038) are associated with a decreased risk of glaucoma, whereas an increased myeloperoxidase level (OR = 2.145, 95 % CI: 1.119-4.111, P = 0.029) is associated with an increased risk of glaucoma. Glaucoma was causally associated with lower levels of total bilirubin (OR = 0.961, 95 % CI: 0.927-0.997, P = 0.039), glutathione peroxidase (OR = 0. 934, 95 % CI: 0.890-0.981, P = 0.006), paraoxonase (OR = 0.883, 95 % CI: 0.810-0.963, P = 0.005) and albumin (OR = 0.988, 95 % CI: 0.978-0.998, P = 0.014). The bidirectional MR analysis revealed a causal relationship between oxidative stress and glaucoma. These findings provide a greater understanding of the underlying mechanisms of glaucomatous neurodegeneration and imply a potential therapeutic approach for glaucoma through targeting oxidative stress pathways.

Tea consumption and risk of lung diseases: a two‑sample Mendelian randomization study

BACKGROUND

Numerous studies have reported the association between tea intake and lung diseases. However, the probable relationship between tea consumption on lung diseases still remain controversial and it is unclear whether these findings are due to reverse causality or confounding factor.

METHODS

In order to systematically investigate the causal connection between tea intake on respiratory system disorders, we employed a two-sample Mendelian randomized (MR) study. Genetic instruments for tea intake were identified from a genome-wide association study (GWAS) involving 447,385 individuals. Data on lung diseases were collected from a variety of publicly available genome-wide association studies. The main method used for MR analysis is the inverse variance weighting (IVW) method. To ensure the accuracy of the findings, further sensitivity analysis was conducted.

RESULTS

The IVW method in our MR analysis revealed no evidence to support a causal relationship between tea intake and lung diseases (IPF: OR = 0.997, 95% CI = 0.994-1.000, p = 0.065; Lung cancer: OR = 1.003, 95% CI = 0.998-1.008, P = 0.261; COPD: OR = 1.001, 95% CI = 0.993-1.006, p = 0.552; acute bronchitis: OR = 0.919, 95% CI = 0.536-1.576, p = 0.759; tuberculosis: OR = 1.002, 95% CI = 0.998-1.008, p = 0.301; pneumonia: OR = 0.789, 95% CI = 0.583-1.068, p = 0.125). The reliability of the results was further demonstrated by four additional MR analysis techniques and additional sensitivity testing.

CONCLUSION

We found no evidence of a link between tea intake on lung diseases in our MR results based on genetic information.

Exploring causal correlations between inflammatory cytokines and ankylosing spondylitis: a bidirectional mendelian-randomization study

Background

The impact of inflammatory factors on the development of Ankylosing Spondylitis (AS) is widely recognized, but the exact causal relationship remains unclear.

Methods

The bidirectional mendelian-randomization study utilized genetic data from a genome-wide association study (GWAS) of 186 AS cases and 456,162 controls of European ancestry. Inflammatory cytokines were obtained from a GWAS summary of 8,293 healthy participants. Causal associations were primarily investigated using the inverse variance-weighted method, supplemented by MR Egger, weighted median and weighted mode analyses. Heterogeneity in the results was assessed using the Cochrane Q test. Horizontal pleiotropy was evaluated through the MR-Egger intercept test and the MR pleiotropy residual sum and outliers (MR-PRESSO) test. Sensitivity analysis was conducted through leave-one-out analysis.

Results

The results suggest a genetically predicted potential association between beta-nerve growth factor (βNGF), Interleukin-1-beta (IL-1β), and TNF-related apoptosis inducing ligand (TRAIL) with the risk of AS (OR: 2.17, 95% CI: 1.13-4.16; OR: 0.41, 95% CI: 0.18-0.95,; OR: 1.47, 95% CI: 1.02-2.13).Additionally, Interleukin-12p70 (IL-12p70), Interleukin-17 (IL-17), Interleukin-6 (IL-6), Interleukin-4 (IL-4), Stromal-cell-derived factor 1 alpha (SDF-1α), Macrophage inflammatory protein 1β (MIP1β), Monocyte chemoattractant protein-3 (MCP-3), Platelet-derived growth factor bb (PDGFbb), Granulocyte-colony stimulating factor (GCSF), Fibroblast growth factor basic (bFGF), TNF-related apoptosis inducing ligand (TRAIL), and Interferon-gamma (IFN -γ) are suggested as consequences of AS in genetically prediction.No evidence of horizontal pleiotropy or heterogeneity between the genetic variants was found (P>0.05), and a leave-one-out test confirmed the stability and robustness of this association.

Conclusion

These findings suggest that βNGF, IL-1β, and TRAIL may play a crucial role in the pathogenesis of AS. Additionally, AS may impact the expression of cytokines such as IL-12p70, IL-17, IL-6, IL-4, SDF-1α, MIP1β, MCP-3, PDGFbb,GCSF, bFGF,TRAIL,and IFN-γ. Further investigations are warranted to determine whether these biomarkers can be utilized for the prevention or treatment of AS.

No evidence of a causal relationship between ankylosing spondylitis and cardiovascular disease: a two-sample Mendelian randomization study

Objective

Observational studies have suggested an increased risk of cardiovascular disease in individuals with ankylosing spondylitis. However, these studies are prone to confounding factors and reverse causality. To address these limitations, we conducted a Mendelian randomization study to assess the causal relationship between AS and CVD.

Methods

The study population comprises 9,069 individuals with ankylosing spondylitis and 509,093 individuals with either of six common cardiovascular diseases and a related indicator. Causal analysis using summary effect estimates and inverse variance weighting were employed as the main methods.

Results

The CAUSE analysis showed no evidence of a causal relationship between AS and CVD. The odds ratios for total CVD, heart failure, myocardial infarction, valvular heart disease, ischemic heart disease, and venous thromboembolism, Arterial stiffness index, were as follows: OR, 1.01; 95% confidence interval, 0.96-1.05; P = 0.91; OR, 1.03; 95% CI, 0.99-1.08; P = 0.50; OR, 0.94; 95% CI, 0.86-1.03; P = 0.53; OR, 0.99; 95% CI, 0.94-1.04; P = 0.99; OR, 0.98; 95% CI, 0.91-1.04; P = 0.94; OR, 0.98; 95% CI, 0.91-1.04; P = 0.99; β, -0.0019; 95% CI, 0.97-1.01; P = 0.99. The IVW and weighted median methods also yielded consistent results, and no heterogeneity or pleiotropy was found. Likewise, a reverse Mendelian randomization analysis did not uncover a heritable causal relationship between AS and CVD.

Conclusion

This Mendelian randomization study does not support a causal relationship between AS and CVD. Further research is needed to confirm this association.

The causal relationship between COVID-19 and seventeen common digestive diseases: a two-sample, multivariable Mendelian randomization study

OBJECTIVES

In clinical practice, digestive symptoms such as nausea, vomiting are frequently observed in COVID-19 patients. However, the causal relationship between COVID-19 and digestive diseases remains unclear.

METHODS

We extracted single nucleotide polymorphisms associated with the severity of COVID-19 from summary data of genome-wide association studies. Summary statistics of common digestive diseases were primarily obtained from the UK Biobank study and the FinnGen study. Two-sample Mendelian randomization analyses were then conducted using the inverse variance-weighted (IVW), Mendelian randomization-Egger regression (MR Egger), weighted median estimation, weighted mode, and simple mode methods. IVW served as the primary analysis method, and Multivariable Mendelian randomization analysis was employed to explore the mediating effect of body mass index (BMI) and type 2 diabetes.

RESULTS

MR analysis showed that a causal association between SARS-CoV-2 infection (OR = 1.09, 95% CI 1.01-1.18, P = 0.03), severe COVID-19 (OR = 1.02, 95% CI 1.00-1.04, P = 0.02), and COVID-19 hospitalization (OR = 1.04, 95% CI 1.01-1.06, P = 0.01) with gastroesophageal reflux disease (GERD). Mediation analysis indicated that body mass index (BMI) served as the primary mediating variable in the causal relationship between SARS-CoV-2 infection and GERD, with BMI mediating 36% (95% CI 20-53%) of the effect.

CONCLUSIONS

We found a causal relationship between SARS-CoV-2 infection and gastroesophageal reflux disease. Furthermore, we found that the causal relationship between SARS-CoV-2 infection and GERD is mainly mediated by BMI.

Mendelian randomization analysis to analyze the genetic causality between different levels of obesity and different allergic diseases

BACKGROUND

The causal relationship between obesity and different allergic diseases remains controversial.

METHODS

The Two Sample MR package and Phenoscanner database were used to obtain and filter Genome-Wide Association Study (GWAS) data from the Open GWAS database. Mendelian randomization (MR) analysis was used to study the causal relationship between different levels of obesity and different allergic diseases. The data sets related to obesity and asthma were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened by the limma package. Cluster Profiler and GO plot packages were used for enrichment analysis to verify the results of MR analysis.

RESULTS

Two-sample MR analysis showed a causal relationship between obesity and childhood allergy (age < 16), allergic asthma and atopic dermatitis (P < 0.05). In addition, there was also a causal relationship between allergic asthma and obesity (P < 0.05), while there was no genetic causal relationship between obesity and allergic rhinitis, eczema, lactose intolerance and so on (P > 0.05). Subgroup analysis revealed a causal relationship between both class 1 and class 2 obesity and childhood allergy (age < 16) (P < 0.05). Obesity class 1 was associated with allergic asthma, while obesity class 3 was associated with atopic dermatitis (P < 0.05). Bioinformatics analysis shows that there were common DEGs between obesity and allergic asthma.

CONCLUSION

Obesity is a risk factor for childhood allergy (age < 16), allergic asthma and atopic dermatitis, while allergic asthma is also a risk factor for obesity. Class 1 and class 2 obesity are both causally associated with childhood allergy (age < 16). In addition, there is a causal relationship between milder obesity and allergic asthma, while heavier obesity is causally related to atopic dermatitis.

Genetically predicted ankylosing spondylitis is causally associated with psoriasis

Background

Previous observational studies have reported the striking association between ankylosing spondylitis (AS) and psoriasis, but the causal relationship between the two diseases remains unclear.

Methods

Two-sample Mendelian randomization (MR) analysis with methods of inverse-variance weighted, MR-Egger regression, weighted median, and weighted mode was conducted to evaluate the bidirectional causal associations between AS and psoriasis. Effective single-nucleotide polymorphisms (SNPs) from genome-wide association studies (GWAS) were selected as instrumental variables (IVs). Sensitivity analyses were also applied to verify whether heterogeneity and pleiotropy can bias the results.

Result

We found positive causal effects of genetically increased AS risk on psoriasis (IVW: OR = 1.009, 95% CI = 1.005-1.012, p = 8.07E-07). Comparable outcomes were acquired by MR-Egger regression, weighted median, and weighted mode approaches. Nevertheless, we did not find significant causal effects of psoriasis on AS (IVW: OR = 1.183, 95% CI = 0.137-10.199, p = 0.879). The sensitivity analyses showed that the horizontal pleiotropy was unlikely to skew the causality. The leave-one-out analysis demonstrated that no single SNP can drive the MR estimates. No evidence of heterogeneity was found between the selected IVs.

Conclusion

Our findings provide evidence that AS has positive causal effects on the risk of psoriasis in the European population.

No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study

Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic rule of "parental alleles are randomly assigned to offspring" and takes genetic variation as IVs to infer the causal association between exposure factors and study outcome in observational studies. Genome-wide association study (GWAS) summary data of AS were from the FinnGen consortium, and the gut microbiota (Bacteroides, Streptococcus, Proteobacteria, Lachnospiraceae) were from the MiBioGen consortium. The TwoSampleMR and MRPRESSO packages of the R were used to perform a two-sample MR study. Random-effects inverse variance weighted (IVW) was the main analysis method, and MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We examined heterogeneity and horizontal pleiotropy, and examined whether the analysis results were influenced by a single SNP. We applied radial variants of the IVW and MR-Egger model for the improved visualization of the causal estimate. We further examined the causal relationship between AS and gut microbiota, and the robustness of the analysis results. Finally, we performed maximum likelihood, penalized weighted median, and IVW (fixed effects) to further identify the potential causal association. Results: The random-effects IVW results showed that Bacteroides (p = 0.965, OR 95% confidence interval [CI] = 0.990 [0.621-1.579]), Streptococcus (p = 0.591, OR 95% CI = 1.120 [0.741-1.692]), Proteobacteria (p = 0.522, OR 95% CI = 1.160 [0.737-1.826]), and Lachnospiraceae (p = 0.717, OR 95% CI = 1.073 [0.732-1.574]) have no genetic causal relationship with AS. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. Conclusions: This study showed that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae, four common gut microbiotas associated with AS, had no causal relationship with AS at the genetic level. This study makes a positive contribution to the genetics of AS, but the insufficient number of gut microbiota included is a limitation.

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

OBJECTIVE

The occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.

METHODS

Genome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.

RESULTS

The random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).

CONCLUSION

Only AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.

No evidence of a genetic causal relationship between ankylosing spondylitis and iron homeostasis: A two-sample Mendelian randomization study

Background

Ankylosing spondylitis (AS) is an immune-mediated chronic inflammatory disease that leads to bone hyperplasia and spinal ankylosis. Iron homeostasis plays a very important role in the inflammatory response and is closely related to the pathogenesis of AS. This study aimed to use large-scale genome-wide association study (GWAS) summary data to study the genetic causal relationship between AS and iron homeostasis using Mendelian randomization (MR).

Methods

Genome-wide association study summary data of AS and iron homeostasis-related indicators were obtained from the FinnGen consortium and the DeCODE genetics database, respectively. We used four iron homeostasis-related indicators: ferritin, serum iron, total iron binding capacity (TIBC), and transferrin saturation (TSAT) for two-sample MR analyses to test for genetic causal association with AS using the "TwoSampleMR" package of the R software (version 4.1.2). The random-effects inverse variance weighted (IVW) method was the main analysis method used for MR. We examined the MR analysis results for heterogeneity, horizontal pleiotropy, and possible outliers. In addition, we confirmed the robustness of the MR analysis by testing whether the results were affected by a single SNP and whether they followed a normal distribution.

Results

The random-effects IVW results showed that ferritin [p = 0.225, OR 95% confidence interval (CI) = 0.836 (0.627-1.116)], serum iron [p = 0.714, OR 95% CI = 0.948 (0.714-1.260)], TIBC [p = 0.380, OR 95% CI = 0.917 (0.755-1.113)], and TSAT [p = 0.674, OR 95% CI = 0.942 (0.713-1.244)] have no genetic causal relationship with AS. We detected no heterogeneity，horizontal pleiotropy and possible outliers in our MR analysis (p > 0.05). In addition, our MR analysis results were not affected by a single SNP, and were normally distributed.

Conclusion

Our study did not detect a genetic causal relationship between AS and iron homeostasis. Nonetheless, this does not rule out a relationship between the two at other mechanistic levels.

Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis

This study aims to explore the genetic causal association between type 2 diabetes (T2D) and glycemic traits (fasting glucose [FG], fasting insulin [FI], and glycated hemoglobin [HbA1c]) on delirium using Mendelian randomization (MR). Genome-wide association studies (GWAS) summary data for T2D and glycemic traits were obtained from the IEU OpenGWAS database. GWAS summary data for delirium were obtained from the FinnGen Consortium. All the participants were of European ancestry. In addition, we used T2D, FG, FI, and HbA1c as exposures and delirium as outcomes. A random-effects variance-weighted model (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform MR analysis. In addition, MR-IVW and MR-Egger analyses were used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using MR-Egger regression and MR pleiotropy residual sum and outliers (MR-PRESSO). MR-PRESSO was also used to assess outlier single nucleotide polymorphisms (SNPs). The "leave one out" analysis was used to investigate whether the MR analysis results were influenced by a single SNP and evaluate the robustness of the results. In this study, we conducted a two-sample MR analysis, and there was no evidence of a genetic causal association between T2D and glycemic traits (T2D, FG, FI, and HbA1c) on delirium (all p > 0.05). The MR-IVW and MR-Egger tests showed no heterogeneity in our MR results (all p values >0.05). In addition, The MR-Egger and MR-PRESSO tests showed no horizontal pleiotropy in our MR results (all p > 0.05). The MR-PRESSO results also showed that there were no outliers during the MR analysis. In addition, the "leave one out" test did not find that the SNPs included in the analysis could affect the stability of the MR results. Therefore, our study did not support the causal effects of T2D and glycemic traits (FG, FI, and HbA1c) on delirium risk.