Inverse-variance Weighted Analysis Research Articles

Causal relationship between sleep traits and cognitive impairment: A Mendelian randomization study.

Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR). Using strict criteria, we selected genetic variants from European ancestry Genome-wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self-reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse-variance weighted (IVW) tests, MR-Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness. In the main IVW analysis, sleep duration (reaction time: β=-0.05, 95% CI -0.07 to -0.04, p=1.93×10-12 ), daytime sleepiness (average cortical thickness: β=-0.12, 95% CI -0.22 to -0.02, p=0.023), and daytime napping (fluid intelligence: β=-0.47, 95% CI -0.87 to -0.07, p=0.021; hippocampal volume in Alzheimer's disease: β=-0.99, 95% CI -1.64 to -0.35, p=0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined. Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns-particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors.

Causal effect of beta-blockers on the risk of lung cancer: a Mendelian randomization study.

It remains uncertain whether there is a causal association of the use of beta-blockers (BBs) on lung cancer risk. We used a two-sample Mendelian randomization (MR) approach to identify the causal association of BBs and lung cancer risk. Twenty-two BB-related single-nucleotide polymorphisms (SNPs) were obtained from the UK Biobank as the instrumental variables (IVs). Genetic summary data information of lung cancer was extracted from the International Lung Cancer Consortium, with a total of 11,348 cases and 15,861 controls. We adopted the inverse-variance weighted (IVW) approach to conduct the MR analyses. Egger-intercept analysis was further performed as sensitivity analysis for pleiotropy evaluation. Additionally, we investigated whether BBs could causally affect the risk of lung cancer through their pharmacological effects. The current IVW analysis suggested a decreased lung cancer risk in BB users [odds ratio (OR) =0.83; 95% confidence interval (CI): 0.73-0.95; P<0.01]. Results of Egger-intercept analysis demonstrated that no pleiotropy was found (P=0.94), which suggested the robustness of the causality. However, there was little evidence that pharmacological effects mediate the association between BBs and lung cancer. The current analysis suggested that BBs could decrease the risk of lung cancer but may be not via its pharmacological effects. Further research is in need for elucidating the underlying mechanisms.

Systemic lupus erythematosus Association between Osteomyelitis: A two-sample Mendelian randomization study in European population

BackgroundSystemic lupus erythematosus (SLE) has been correlated with osteomyelitis (OM), yet the underlying causal relationship remains poorly understood. This study aims to investigate the causal association between SLE and OM using Mendelian randomization (MR) analysis. MethodsGenetic instrumental variables (IVs) correlated with SLE were extracted from a comprehensive genome-wide association study (GWAS) summary database (5201 cases and 9066 controls). OM was considered a SLE phenotype, and summary data from the fast GWA data portal were utilized for the analysis. Eligible IVs were extracted following rigorous quality control measures (P < 5 × 10-8, LD r2>0.001, distance 1 Mb, and F > 10). MR analysis was conducted using the Inverse Variance Weighted (IVW), MR-Egger, and Weighted Median (WM) methods after excluding potential confounders. Cochran's Q was applied for heterogeneity test. Pleiotropy was evaluated through MR-Egger intercept, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method, and Leave-one-SNP-out analysis. ResultA total of 40 eligible IVs were included for MR analysis. IVW results demonstrated a positive causal association between SLE and OM (P = 0.049, OR = 1.167). Heterogeneity analysis reveal no significant heterogeneity in the IVW analysis (P = 0.5503). Pleiotropy tests, including MR-PRESSO global test and MR-Egger intercept, indicated no evidence of pleiotropy in our findings (P > 0.05). Additionally, the Leave-one-SNP-out analysis showed no substantial deviations when removing individual SNPs, thus supporting the robustness of our results. ConclusionThis study establishes a genetic causal relationship between SLE and OM, indicating an increased risk of developing OM in individuals with SLE. Therefore, proactive management of SLE is advised to mitigate the risk of developing OM.

Causal Relationships between Immune-Mediated Inflammatory Diseases and Hodgkin's Lymphoma: A Mendelian Randomization Study

Introduction: Immune-mediated inflammatory diseases (IMIDs) constitute a clinically heterogeneous group with a disruption of the immune system that provokes inflammation of any organ system on a chronic basis. Previous observational investigations have demonstrated an association between a person's or their family's medical background of IMIDs and a higher likelihood of developing Hodgkin's lymphoma (HL). Nevertheless, the exact causal connection between specific IMIDs and HL remains ambiguous. Therefore, the investigation aims to explore the causal effects between IMIDs and HL. Methods: A two-sample Mendelian randomization (TSMR) approach was employed in this study, using publicly available genome-wide association study summary statistics. The inverse variance weighted (IVW) method was the primary approach used for the Mendelian randomization (MR) analysis. Furthermore, supplementary statistical approaches such as MR-Egger, simple mode, weighted median, and MR-PRESSO were employed. In order to identify potential heterogeneity and pleiotropy, several tests were conducted, including Cochran's Q test, the MR-Egger regression test, and the MR-PRESSO test. Moreover, the leave-one-out method was implemented to examine the reliability of the MR results. Results: Based on the IVW analysis the findings revealed a positive causal link at risk for multiple sclerosis (MS) and HL [odds ratio (OR) = 1.281; 95% CI = 1.087-1.510, p = 0. 003] and a negative causal link at risk for type 1 diabetes (T1D) and HL (OR = 0.853; 95% CI = 0.776-0.937, p = 0.001). However, no significant causal relationship was found between the risk of HL and the other eight IMIDs, including inflammatory bowel diseases (OR = 1.034; 95%CI = 0.910-1.176, p = 0.606), systemic lupus erythematosus (OR = 1.041; 95%CI = 0.944-1.149, p = 0.422), Crohn's disease (OR = 0.952; 95%CI = 1.840-1.078, p = 0.436), ulcerative colitis (OR = 1.042; 95%CI = 0.874-1.242, p = 0.644), primary sclerosing cholangitis (OR = 1.061; 95%CI = 0.937-1.202, p = 0.349), primary biliary cirrhosis (OR = 1.046; 95%CI = 0.918-1.192, p = 0.495), psoriasis (OR = 0.989; 95%CI = 0.954-1.026, p = 0.565), celiac disease (OR = 1.198; 95%CI = 0.911-1.574, p = 0.195). Figure 1 displayed a detailed visual representation of the findings obtained in the study. No indication was made of any potential heterogeneity or horizontal pleiotropy. Besides, no outliers were discovered in the MR using MR-PRESSO. In addition, the leave-one-out analysis indicates that the MR estimates are not driven by any single SNP, suggesting that the observed associations are robust and reliable. Conclusions: The present investigation emphasizes an increased susceptibility of MS to the risk of HL and a potential protective effect of T1D against the risk of HL. In light of these findings, patients with MS receiving immunosuppressive therapy are highly suggested to undergo periodic physical evaluations and lymphoma surveillance. Further investigations are warranted to explore the potential mechanisms of MS and T1D on the development of HL.

Genetic Insights into the causal relationship between cannabis use and diabetic phenotypes: A genetic correlation and Mendelian randomization study

BackgroundPrevious studies have highlighted the association between cannabis use and diabetes and its complications; however, the causality remains ambiguous. MethodsUnivariate Mendelian randomization (MR), multivariate MR, mediation MR, and linkage disequilibrium score (LDSC) analysis to assess the causal relationship between cannabis use and 12 diabetic phenotypes. Summary statistics for lifetime cannabis use (N = 184,765) and cannabis use disorder (CUD) (N = 374,287) from genome-wide association studies. The primary method used was inverse-variance-weighted (IVW). A range of sensitivity analyses ensured the robustness of the results. ResultsLDSC analysis revealed a significant genetic correlation between CUD and T2DM, as well as between lifetime cannabis use and four diabetic phenotypes (P < 0.05). After correction by false discovery rate (FDR), the primary IVW analysis indicates that the genetically predicted CUD is positively associated with the risk of diabetic hypoglycemia (OR = 1.11, 95% CI 1.04–1.20, P = 0.003, PFDR = 0.04) and proliferative diabetic retinopathy (PDR) (OR = 1.12, 95% CI 1.04–1.19, P = 4.89×10−4, PFDR =0.01). Additionally, suggestive evidence links CUD with increased risks of diabetic nephropathy, type 1 diabetes mellitus (T1DM), diabetic retinopathy, and T1DM associated with diabetic ketoacidosis (P < 0.05 &PFDR > 0.05). No causal relationship was detected between lifetime cannabis use and diabetic phenotypes (P > 0.05 &PFDR > 0.05). Multivariable and mediation MR analyses revealed that glycated hemoglobin A1c partially mediates the causal effect of CUD on PDR and diabetic hypoglycemia. ConclusionThis MR study suggests that CUD may have a causal role in several diabetic disease phenotypes.

Relationship between Parkinson’s disease and cardio-cerebrovascular diseases: a Mendelian randomized study

Parkinson’s disease (PD) and cardio-cerebrovascular diseases are related, according to earlier studies, but these studies have some controversy. Our aim was to assess the impact of PD on cardiocerebrovascular diseases using a Mendelian randomization (MR) method. The data for PD were single nucleotide polymorphisms (SNPs) from a publicly available genome-wide association study (GWAS) dataset containing data on 482,730 individuals. And the outcome SNPs data is were derived from five different GWAS datasets. The basic method for MR analysis was the inverse variance weighted (IVW) approach. We use the weighted median method and the MR-Egger method to supplement the MR analysis conclusion. Finally, We used Cochran’s Q test to test heterogeneity, MR-PRESSO method and leave-one-out analysis method to perform sensitivity analysis. We used ratio ratios (OR) to assess the strength of the association between exposure and outcome, and 95% confidence intervals (CI) to show the reliability of the results. Our findings imply that PD is linked to a higher occurrence of coronary artery disease (CAD) (OR = 1.055, 95% CI 1.020–1.091, P = 0.001), stroke (OR = 1.039, 95% CI 1.007–1.072, P = 0.014). IVW analyses for stroke’s subgroups of ischemic stroke (IS) and 95% CI 1.007–1.072, P = 0.014). IVW analyses for stroke’s subgroups of ischemic stroke (IS) and cardioembolic stroke (CES) also yielded positive results, respectively (OR = 1.043, 95% CI 1.008–1.079, P = 0.013), (OR = 1.076, 95% CI 1.008–1.149, P = 0.026). There is no evidence of a relationship between PD and other cardio-cerebrovascular diseases. Additionally, sensitivity analysis revealed reliable outcomes. Our MR study analysis that PD is related with an elevated risk of CAD, stroke, IS, and CES.

Serum uric acid levels and risk of cardiovascular disease in type 2 diabetes: results from a cross-sectional study and Mendelian randomization analysis.

Serum uric acid (SUA) levels have been previously linked to a higher risk of cardiovascular disease (CVD) in individuals with type 2 diabetes (T2D) according to various observational studies. However, whether this association is causally linked or simply influenced by confounding factors is unclear. Therefore, this study utilized Mendelian randomization (MR) analysis to explore the causality between SUA levels and the risk of CVD in individuals with T2D. Our study cohort consisted of 5723 participants who were diagnosed with T2D in the National Health and Nutrition Examination Survey (NHANES) from 1999-2018. The study assessed the association between SUA levels and the risk of CVD using a multivariable logistic regression model. To further examine causality between SUA levels and CVD, a two-sample MR study was conducted utilizing genetic data from genome-wide association studies (GWAS) involving over 140,000 individuals. The main MR analysis employed the inverse-variance-weighted (IVW) method. Additionally, several sensitivity analyses were performed to evaluate the robustness and pleiotropy of the results. In the cross-sectional study, after multivariable adjustment, participants with SUA levels >6.7 mg/dL exhibited odds ratios (ORs) of 1.51 (95% CI: 1.01-2.26, p=0.049) for heart failure, 1.02 (95% CI: 0.69-1.50, p=0.937) for coronary heart disease, 1.36 (95% CI: 0.78-2.38, p=0.285) for angina, and 1.22 (95% CI: 0.80-1.85, p=0.355) for myocardial infarction when compared to participants with SUA levels ≤ 4.6 mg/dL. However, in the IVW analysis, no causality between SUA levels and the risk of heart failure was observed (OR = 1.03, 95% CI: 0.97-1.09, p = 0.293). The secondary analysis yielded similar results (OR = 1.05, 95% CI: 0.96-1.14, p = 0.299). The sensitivity analyses further supported our primary findings. Based on the MR study, we did not find supporting evidence for a causal association between SUA levels and the risk of heart failure.

Common autoimmune diseases and urticaria: the causal relationship from a bidirectional two-sample mendelian randomization study.

The immune response assumes a pivotal role in the underlying mechanisms of urticaria pathogenesis. The present study delves into an investigation of the genetic causal connections between urticaria and prevalent autoimmune afflictions, notably rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), ulcerative colitis (UC), and Crohn's disease (CD). A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationships involving four autoimmune diseases and urticaria. The genome-wide association study (GWAS) summary data of four autoimmune disease were sourced from the IEU OpenGWAS database. The GWAS summary data for urticaria were derived from the Finnish consortium dataset. The principal analytical approach employed in this study was the random-effects inverse variance weighted (IVW) method. Subsequently, a series of sensitivity analyses were performed, encompassing assessments of heterogeneity, horizontal pleiotropy, outliers, "Leave-one-out" analyses, and tests for adherence to the assumption of normal distribution. The random-effects IVW analysis indicate a positive genetic causal association between RA and urticaria (P < 0.001, OR 95% CI = 1.091 [1.051-1.133]). Conversely, SLE, UC, and CD do not exhibit a significant genetic causal relationship with urticaria. The reverse MR analysis reveals a positive genetic causal linkage between urticaria and SLE (P = 0.026, OR 95% CI = 1.289 [1.031-1.612]). However, the analysis demonstrates no substantial genetic causal relationship between urticaria and RA, UC, or CD. Importantly, the genetic causal assessment absence of heterogeneity, horizontal pleiotropy, and outliers. Furthermore, it remains unaffected by any individual single nucleotide polymorphism (SNP), demonstrating adherence to a normal distribution. This investigation establishing RA as a predisposing factor for urticaria. Moreover, urticaria as a plausible risk determinant for SLE. Heightened vigilance is recommended among RA patients to monitor the manifestation of urticaria within clinical settings. Similarly, individuals afflicted by urticaria should duly acknowledge the prospective susceptibility to SLE.

Relationship Between the Ovarian Cyst and Depression: A Two-Sample Mendelian Randomization Study.

Explore the causal relationship between the ovarian cyst and depression using a two-sample Mendelian randomization approach (MR). Based on data pooled from genome-wide association studies, genetic variants of the ovarian cyst and depression were selected as instrumental variables, as well as the Mendelian randomization analysis was conducted using inverse variance weighted (IVW) as the main analysis method and MR-Egger regression analysis, MR-PRESSO and other sensitivity analysis methods as supplements. The IVW analysis showed a direct causal association between ovarian cysts and depression (OR=1.040; 95% CI: 1.003, 1.078; p=0.031). Meantime, there was a causal effect of genetically predicted depression on ovarian cysts (OR=1.327.; 95% CI: 1.197, 1.470; p<0.001). Sensitivity analyses such as MR-Egger regression analysis and MR-PRESSO indicated that the IVW results were robust and reliable. This study suggested since ovarian cysts and female depression are mutually causal, the comorbidity of ovarian cysts and depression in women should be actively attended to and given appropriate prevention and treatment besides the diagnosis and treatment of depression or ovarian cysts.

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

ABSTRACT 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.

Causal associations of cytokines and growth factors with cholelithiasis: a bidirectional Mendelian randomization study.

It has been reported that patients with cholelithiasis may have changes in levels of cytokines and growth factors, while their causal relationships were still unclear. This study was a bidirectional Mendelian randomization (MR) study. Datasets of 41 circulation cytokines and growth factors and the data on cholelithiasis were obtained. Six steps of strict instrumental variable filtration were set, and inverse-variance weighted analysis, MR-Egger regression, and weighted median test were used to identify the causal relationships. Benjamini-Hochberg method was used to adjust the P-values. After adjustments of P-values, four cytokines and growth factors were still causally associated with cholelithiasis significantly: interleukin 2 receptor alpha (adjusted P: 4.59E-02), interleukin 8 (adjusted P: 1.09E-02), monocyte-specific chemokine 3 (adjusted P: 2.73E-04), and stem cell factor (adjusted P: 2.73E-04). In the reverse MR analysis, no significant causal relationship was detected after adjustment. Four cytokines and growth factors, including interleukin 2 receptor alpha, interleukin 8, monocyte-specific chemokine 3, and stem cell factor, were proven to relate to cholelithiasis causally and unidirectionally.

Association between gut microbiota and influenza: a bidirectional two-sample mendelian randomization study

BackgroundPrevious observational studies have indicated a correlation between the gut microbiota and influenza; however, the exact nature of the bidirectional causal connection remains uncertain.MethodA two-way, two-sample Mendelian randomization (MR) study was conducted to evaluate the possible causal connection between the gut microbiota and the two outcomes of influenza (pneumonia without influenza and influenza pneumonia). The statistical analysis of gut microbiota is derived from the information of the most extensive meta-analysis (GWAS) conducted by the MiBioGen Alliance, encompassing a sample size of 18,340.The summary statistical data for influenza (not pneumonia, n = 291,090) and influenza pneumonia (n = 342,499) are from GWAS data published by FinnGen consortium R8.Estimate and summarize Single-nucleotide polymorphisms (SNPs) using Inverse variance weighted (IVW), MR Egger, and Weighted median (WM) in bidirectional MR analysis. To assess the heterogeneity, horizontal pleiotropy, and stability of SNPs, we employed Cochran’s Q test, MR Egger intercept test, and sensitivity analysis.ResultThe IVW analysis indicated that there was a significant association between influenza infection and five bacterial taxa. Additionally, the abundance changes of seven gut microbiota were found to be causally related to influenza infection. In addition, seven bacterial taxa showed a significant association with the occurrence of influenza pneumonia. The findings from the WM analysis largely support the outcomes of IVW, however, the results of MR egger analysis do not align with IVW. Furthermore, there is no proof to substantiate the cause-and-effect relationship between influenza pneumonia and the composition of gut microbiota.ConclusionThis analysis demonstrates a possible bidirectional causal connection between the prevalence of particular gut microbiota and the occurrence of influenza infection. The presence of certain gut microbiota may potentially contribute to the development of pneumonia caused by influenza. Additional investigation into the interaction between particular bacterial communities and influenza can enhance efforts in preventing, monitoring, and treating influenza.

The causality between obstructive sleep apnea and ventricular structure and function: a bidirectional Mendelian randomization study.

Background: Multiple observational studies have discovered a substantial link between obstructive sleep apnea (OSA) and ventricular dysfunction. However, conventional observational studies are vulnerable to causal reversal and confounding, making it challenging to infer the causes of effects and their direction. Methods: With the help of a bidirectional, two-sample Mendelian randomization (MR) study, we assessed the potential causality between OSA and left and right ventricular (LV, RV) structure and function. We conducted our analysis utilizing summary data from genome-wide association studies of OSA (16,761 cases and 201,194 controls) in the FinnGen Study, as well as LV (36,041 participants) and RV (29,506 participants) in the UK Biobank cardiovascular magnetic resonance research. The inverse variance weighted (IVW) was selected as the main strategy, with the MR-Egger and weighted median methods serving as supplements. Other methods were employed as sensitivity analysis tools to look at heterogeneity and pleiotropy, including MR-Egger intercept, Cochran Q statistic, MR-PRESSO, and leave-one-out analysis. Results: In the primary IVW analysis, genetically predicted OSA was strongly causative on LV end-diastolic volume (β = 0.114, 95% CI = 0.034-0.194, p = 0.006) and LV stroke volume (β = 0.111, 95% CI = 0.031-0.191, p = 0.007), and genetically predicted LV ejection fraction was linked to an increased risk of OSA (OR = 1.161, 95% CI = 1.029-1.309, p = 0.015). However, there was no connection found between OSA and any RV parameters. Conclusion: Our genetic analysis raises a potential causative link between OSA and ventricular structure and function, which may improve the knowledge of OSA as a risk factor for cardiovascular disease by demonstrating a direct impact on cardiac structure and function.

Visceral and ectopic fat are more predictively associated with primary liver cancer than overall obesity from genetic sights: A Mendelian randomization study.

Several observational studies have reported an association between obesity and primary liver cancer (PLC), while the causality behind this association and the comparison of the risk effects of different obesity indicators on PLC remain unclear. In this study, we performed two-sample Mendelian randomization (MR) analyses to assess the associations of genetically determined liver fat, visceral adipose tissue (VAT), and body mass index (BMI) with the risk of PLC. The summary statistics of exposures were obtained from two genome-wide association studies (GWASs) based on the UK Biobank (UKB) imaging cohort and the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. GWAS summary statistics for PLC were obtained from FinnGen consortium R7 release data, including 304 PLC cases and 218 488 controls. Inverse-variance weighted (IVW) was used as the primary analysis, and a series of sensitivity analyses were performed to further verify the robustness of these findings. IVW analysis highlighted a significant association of genetically determined liver fat (OR per SD increase: 7.14; 95% CI: 5.10-9.99; P = 2.35E-30) and VAT (OR per SD increase: 5.70; 95% CI: 1.32-24.72; P = .020) with PLC but not of BMI with PLC. The findings were further confirmed by a series of MR methods. No evidence of horizontal pleiotropy between these associations existed. Our study suggested that genetically determined liver fat and VAT rather than BMI were associated with an increased risk of PLC, which suggested that visceral fat distribution is more predictive of the clinical risk of PLC than common in vitro measures.

Liver Iron Overload Drives COVID-19 Mortality: a Two-Sample Mendelian Randomization Study.

Iron overload has been associated with an increased risk of COVID-19 severity and mortality in observational studies, but it remains unclear whether these associations represent causal effects. We performed a two-sample Mendelian randomization (MR) to determine associations between genetic liability to iron overload and the risk of COVID-19 severity and mortality. From genome-wide association studies of European ancestry, single-nucleotide polymorphisms associated with liver iron (n = 32,858) and ferritin (n = 23,986) were selected as exposure instruments, and summary statistics of the hospitalization (n = 16,551) and mortality (n = 15,815) of COVID-19 were utilized as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis to estimate causal effects, and other alternative approaches as well as comprehensive sensitivity analysis were conducted for estimating the robustness of identified associations. Genetically predicted high liver iron levels were associated with an increased risk of COVID-19 mortality based on the results of IVW analysis (OR = 1.38, 95% CI: 1.05-1.82, P = 0.02). Likewise, sensitivity analyses showed consistent and robust results in general (all P > 0.05). A higher risk of COVID-19 hospitalization trend was also observed in patients with high liver iron levels without statistical significance. This study suggests that COVID-19 mortality might be partially driven by the iron accumulation in the liver, supporting the classification of iron overload as one of the independent death risk factors. Therefore, avoiding iron overload and maintaining normal iron levels may be a powerful measure to reduce COVID-19 mortality.

Susceptibility and severity of COVID-19 and risk of psychiatric disorders in European populations: a Mendelian randomization study.

Observational studies have suggested that COVID-19 increases the prevalence of psychiatric disorders, but the results of such studies are inconsistent. This study aims to investigate the association between COVID-19 and the risk of psychiatric disorders using Mendelian randomization (MR) analysis. We used summary statistics from COVID-19 Host Genetics Initiative genome-wide association study (GWAS) of COVID-19 involving 2,586,691 participants from European ancestry. Genetic variations of five psychiatric disorders including autism spectrum disorder (ASD) (N = 46,351), bipolar disorder (BID) (N = 51,710), major depressive disorder (MDD) (N = 480,359), anxiety disorder (N = 83,566), and schizophrenia (SCZ) (N = 77,096) were extracted from several GWAS of European ancestry. The inverse-variance weighted (IVW) method as the main MR analysis conducted. We further performed sensitivity analyzes and heterogeneity analyzes as validation of primary MR results. The IVW analysis found that COVID-19 hospitalization phenotype was the risk factor for BID (OR = 1.320, 95% CI = 1.106-1.576, p = 0.002) and SCZ (OR = 1.096, 95% CI = 1.031-1.164, p = 0.002). Moreover, we detected a significant positive genetic correlation between COVID-19 severity and two psychiatric traits, BID (OR = 1.139, 95% CI = 1.033-1.256, p = 0.008) and SCZ (OR = 1.043, 95% CI = 1.005-1.082, p = 0.024). There was no evidence supporting the causal relationship between COVID-19 susceptibility and psychiatric disorders. Our results found that the COVID-19 hospitalization phenotype and COVID-19 severity phenotype might be the potential risks of BID and SCZ in European populations. Therefore, patients infected with SARS-CoV-2 should have enhanced monitoring of their mental status.

Investigation of the causal relationship between osteocalcin and dementia: A Mendelian randomization study

ObjectiveBasic medical studies have reported an improved effect of osteocalcin on cognition. We explored the causal link between osteocalcin and dementia via the implementation of Mendelian randomization methodology. MethodsGenome-wide association studies were employed to identify single nucleotide polymorphisms (SNPs) showing significant correlations with osteocalcin. Subsequently, A two-sample Mendelian randomization analysis was conducted utilizing the inverse-variance-weighted (IVW) technique to assess the causal relationship between osteocalcin and various types of dementia, including Alzheimer's disease (AD), Parkinson's disease (PD), Lewy body dementia (LBD), and vascular dementia (VD). This approach aimed to minimize potential sources of confounding bias and provide more robust results. Multivariable MR (MVMR) analysis was conducted to adjust for potential genetic pleiotropy. ResultsThe study employed three SNPs, namely rs71631868, rs9271374, and rs116843408, as genetic tools to evaluate the causal association of osteocalcin with dementia. The IVW analysis indicated that osteocalcin may have a potential protective effect against AD with an odds ratio (OR) of 0.790 (95 % CI: 0.688–0.906; P < 0.001). However, no significant relationship was observed between osteocalcin and other types of dementia. Furthermore, the MVMR analysis indicated that the impact of osteocalcin on AD remained consistent even after adjusting for age-related macular degeneration and Type 2 diabetes with an OR of 0.856 (95 % CI: 0.744–0.985; P = 0.030). ConclusionsOur findings provide important insights into the role of osteocalcin in the pathogenesis of AD. Future research is required to clarify the underlying mechanisms and their clinical applications.

Causal effects of rheumatoid arthritis or ankylosing spondylitis on membranous nephropathy: a two-sample Mendelian randomization study.

Membranous nephropathy (MN) is the leading cause of adult-onset nephrotic syndrome, with primary MN of unclear cause accounting for 80% of cases. Retrospective clinical research reported that MN occurring in rheumatoid arthritis (RA) and ankylosing spondylitis (AS) patients was triggered by nephrotoxic drugs or of unknown cause. However, whether RA or AS itself increases the risk of developing MN is unknown. We conducted mendelian randomization (MR) analysis to evaluate the causal effects of RA or AS on MN using genome-wide association study (GWAS) statistics. The inverse variance weighted (IVW) method was the primary analysis, and several supplementary analyses and sensitivity analyses were performed to test the causal estimates. We obtained 30 valid instrumental variables (IVs) of RA and 16 valid IVs of AS from large-scale open-access GWASs. The genetically predicted RA significantly increased the risk of MN [IVW odds ratios (OR)=1.327, 95% confidence interval (CI)=(1.124, 1.565), P=8.051×10-4]. Three supplementary MR analyses provided the consistent positive causal effect of RA on MN (all P<0.05). No horizontal pleiotropy was detected by MR Egger intercept analysis (P=0.411). However, the genetically predicted AS had no causal effect on MN by IVW and supplementary analysis (all P>0.05). Genetically predicted RA could increase the risk of MN, but genetically predicted AS was not associated with MN. Screening for kidney involvement in RA patients should be noted, and active treatment of RA will reduce the public health burden of MN.

The non-causative role of abnormal serum uric acid in intervertebral disc degeneration: A Mendelian randomization study.

Intervertebral disc degeneration (IDD) is a common musculoskeletal disorder that contributes significantly to disability and healthcare costs. Serum urate concentration has been implicated in the development of various musculoskeletal conditions. While previous observational studies have suggested an association between the two conditions, it might confound the effect of serum urate concentrations on IDD. This Mendelian randomization (MR) study aimed to investigate the causal relationship between serum urate concentration and IDD. We performed a two-sample MR analysis using summary-level data from genome-wide association studies (GWAS) of serum urate concentration (n = 13 585 994 European ancestry) and IDD (n = 16 380 337 European ancestry). Single nucleotide polymorphisms (SNPs) significantly associated with serum urate concentration (p < 5 × 10-8) were selected as instrumental variables. The associations between genetically predicted serum urate concentration and IDD were estimated using the inverse-variance weighted (IVW) method, with sensitivity analyses employing the weighted median, MR-Egger, and MR-PRESSO approaches to assess the robustness of the findings. In the primary IVW analysis, genetically predicted serum urate concentration was unrelated associated with IDD (odds ratio [OR] = 1.00, 95% confidence interval (CI): 1.00-1.00, p = 0.17)). The results remained consistent across the sensitivity analyses, and no significant directional pleiotropy was detected (MR-Egger intercept: p = 0.15). This MR study provides evidence that there is no causal relationship between serum urate concentration and IDD. It suggests previous observational associations may be confounded. Serum urate levels are unlikely to be an important contributor to IDD.

Association between Gastric Cancer and 12 Autoimmune Diseases: A Mendelian Randomization Study.

Whether the positive associations of gastric cancer (GC) with autoimmune diseases are causal has always been controversial. This study aims to estimate the causal relationship between GC and 12 autoimmune diseases by means of Mendelian randomization (MR) analysis. After rigorous evaluation, potential candidate single nucleotide polymorphisms (SNPs) for GC and 12 autoimmune diseases were extracted from genome-wide association study (GWAS) datasets. We performed the MR analyses using the inverse variance weighted (IVW) method as the primary approach to the analysis. Three sensitivity analysis methods were added to assess the robustness of the results. In addition, heterogeneity was measured using Cochran's Q-value, and horizontal pleiotropy was assessed using MR-Egger regression and leave-one-out analysis. The IVW result, which is the main method of analysis, shows no evidence of a causal association between GC and any autoimmune disease. The results of IVW analysis show the relationship between rheumatoid arthritis (p = 0.1389), systemic lupus erythematosus (p = 0.1122), Crohn's disease (p = 0.1509), multiple sclerosis (p = 0.3944), primary sclerosing cholangitis (p = 0.9022), primary biliary cirrhosis (p = 0.7776), type 1 diabetes (p = 0.9595), ulcerative colitis (p = 0.5470), eczema (p = 0.3378), asthma (p = 0.7436), celiac disease (p = 0.4032), and psoriasis (p = 0.7622) and GC susceptibility. The same result was obtained with the weighted median and the MR-egger (p > 0.05). Our study did not find a genetic causal relationship between susceptibility to these autoimmune diseases and GC, which suggests that unmeasured confounders (e.g., inflammatory processes) or shared genetic architecture may be responsible for the reported epidemiologic associations. Further studies of ancestral diversity are warranted to validate such causal associations.