Objective Mendelian randomization (MR) was used to analyze the potential relationship between blood pressure and proliferative diabetic retinopathy (PDR). MethodsTwo-sample MR analysis was performed using summary statistics from genome-wide association studies. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were selected as the exposure, PDR as the outcome. The instrumental variable of SBP and DBP came from the publicly available data of the the UK Medical Research Council Comprehensive Epidemiology Unit and Neale Laboratory; the outcome data (8 681 cases in the case group, 204 208 cases in the control group, European population) are from the FinnGen database. Inverse variance weighting (IVW) and weighted median (WM) were used to analyze the potential relationships between SBP, DBP and PDR. ResultsMR analysis showed that IVW [SBP: odds ratio (OR)=1.36, 95% confidence interval (CI) 1.17-1.57, P=4.22E-05; DBP: OR=1.29, 95%CI 1.11-1.51, P=8.6E-04], WM (SBP: OR=1.33, 95%CI 1.07-1.66, P=0.009; DBP: OR=1.28, 95%CI=1.03-1.59, P=0.002). The results showed that elevated SBP and DBP increased the risk of PDR. ConclusionBlood pressure (SBP, DBP) change is positively correlated with the risk of PDR.
ObjectiveUsing the whole genome association study (GWAS) data, Mendel randomization (MR) method was used to find the causal relationship between oral flora and type 2 diabetes (T2D) and myocardial infarction (MI). MethodsGenetic association data of oral microbiota were selected from the Chinese 4D-SZ cohort GWAS dataset, and T2D and MI outcome data were obtained from a large-scale cohort study in BioBank Japan. Four methods, including inverse variance weighting (IVW), were used to analyze the causal relationship between exposure and outcomes. Sensitivity analysis was conducted on significant MR results to further validate the robustness of the results. ResultsThe results showed a total of 24 species of dorsal tongue flora and 13 species of salivary flora with a potential causal relationship with T2D. There were 12 species each of dorsal tongue and salivary flora with a potential causal relationship with MI. A total of 8 oral flora were found on the dorsum of the tongue and saliva that could affect both T2D and MI, namely Saccharimonadaceae, Treponemataceae, Prevotella, Haemophilus, Lachnoanaerobaculum, Campylobacter_A, Neisseria, and Streptococcus. ConclusionWe identified 8 oral flora causally associated with both T2D and MI, suggesting that T2D may play a role in promoting the progression of MI by affecting the above oral flora.
ObjectiveTo analyze the causal relationship between SARS-CoV-2 infection and retinal vascular obstruction by mendelian randomization (MR). MethodsA two-sample MR analysis utilizing summary statistics from genome-wide association studies (GWAS) in European populations was conducted. The GWAS data for SARS-CoV-2 infection comprised cases of common infection (2 597 856), hospitalized infection (2 095 324), and severe infection (1 086 211). Data on retinal vascular obstruction were obtained from the FinnGen database, which included 203 269 cases of retinal artery obstruction and 182 945 cases of retinal vein obstruction (RVO). Inverse variance weighting (IVW), random effects models, weighted median (WM), MR-Egger regression, simple models, and weighted models were used to analyze the bidirectional causal relationship between different SARS-CoV-2 infection phenotypes and retinal obstruction. The Q statistic was used to assess heterogeneity among single nucleotide polymorphisms (SNP), while MR-Presso was utilized to detect SNP outliers, and MR-Egger intercept tests were performed to evaluate horizontal pleiotropy. ResultsThe MR analysis, using IVW, random effects models, MR-Egger, WM, and weighted models, indicated no significant association between common SARS-CoV-2 infection, hospitalized infection, severe infection, and retinal vascular obstruction (P＞0.05). Additionally, retinal vascular obstruction did not show a significant association with the various SARS-CoV-2 infection phenotypes (P＞0.05). In the simple model, a significant association was found between severe SARS-CoV-2 infection and RVO (P＜0.05), as well as between RVO and common SARS-CoV-2 infection (P＜0.05). No heterogeneity was observed in the IVW and MR-Egger analyses (P＞0.05). The MR-Egger test provided no evidence of horizontal pleiotropy (P＞0.05), and MR-Presso detected no outlier SNP. ConclusionThe findings of this study do not support a causal relationship between SARS-CoV-2 infection and the occurrence of retinal vascular obstruction.
Objective To investigate the causal relationship between resistin and multiple myeloma (MM). Methods A two-sample Mendelian randomization analysis was conducted using genetic variants (SNPs) associated with resistin as instrumental variables and MM genome-wide association study (GWAS) data as the outcome event. Five analysis methods, including inverse-variance weighted (IVW), MR-Egger, weighted median, weighted model, and simple model were used to assess the causal impact of resistin on the risk of MM. Results None of the five analysis methods showed a causal relationship between resistin and multiple myeloma (P>0.05). Sensitivity analysis indicated consistent and robust results, with no evidence of horizontal pleiotropy, heterogeneity, outliers, or individual SNPs influencing the findings. Conclusion This Mendelian randomization study provides no support for a causal relationship between resistin and the risk of multiple myeloma.
ObjectiveThis study applied Mendelian randomization to explore the potential causal relationship between inflammatory factors and diabetic nephropathy. MethodsSummary-level data from genome-wide association studies of inflammatory factors and diabetic nephropathy were used, and inverse variance weighted analysis was used as the primary analytical method, complemented by results from weighted median, MR-Egger regression, simple model, and median model approaches. Sensitivity analysis was used to test the reliability of the MR analysis results. ResultsIn the inverse variance weighted method, stem cell factor (OR=1.28, 95%CI 1.04 to 1.58, P=0.020) and interferon-γ (OR=1.36, 95%CI 1.10 to 1.70, P=0.005) were positively correlated with diabetic nephropathy, and diabetic nephropathy was positively correlated with interferon-inducible protein 10 (OR=0.90, 95%CI 0.83 to 0.98, P=0.012) were negatively correlated with diabetic nephropathy. Sensitivity analysis showed that MR analysis was reliable. ConclusionStem cell factors and interferon-γ are associated with an increased risk of developing diabetic nephropathy, and diabetic nephropathy decreases the expression of interferon-inducible protein 10 in vivo. Our results demonstrate a potential causal relationship between inflammatory factors and the development of diabetic nephropathy. This finding is of clinical significance for the pre-diagnosis and treatment of diabetic nephropathy.
ObjectiveTo explore the causal association between venous thromboembolism (VTE) and cardiovascular disease (CVD) risks using a two-sample bidirectional Mendelian randomization (MR) study. MethodsThe single-nucleotide polymorphism (SNP) data associated with VTE and CVD from genome-wide association studies were obtained as instrumental variables. Inverse variance weighted (IVW) was used as the main MR method and other methods were used as supplementary methods. Cochran's Q test, the intercept term of MR-Egger, and MR-PRESSO were used to assess pleiotropy and heterogeneity to ensure the robustness of the results. ResultsThe IVW method suggested a causal association between VTE and atrial fibrillation (OR=1.033, 95%CI 1.009 to 1.058, P=0.008), but no association was identified between VTE and coronary artery disease (OR=0.994, 95%CI 0.974 to 1.023, P = 0.551), heart failure (OR=1.021, 95%CI 0.992 to 1.050, P=0.159) and myocardial infarction (OR=1.012, 95%CI 0.971 to 1.055, P=0.568). The results of Cochran's Q test showed that there was no heterogeneity in the MR analyses of VTE and CVD. The MR-Egger intercept analysis and the MR-PRESSO global testing did not detect potential horizontal pleiotropy, and the results were robust. Reverse MR analysis was used to verify the presence of reverse causal associations. The reverse MR analysis demonstrated that reverse causal associations between VTE and CVD were not evidenced. ConclusionThe results of the MR study demonstrated a causal association between VTE and atrial fibrillation, but not with coronary artery disease, heart failure or myocardial infarction.
Objective To analyze the causal relationship between cerebrospinal fluid (CSF) metabolites and tic disorder (TD) based on two-sample Mendelian randomization (MR). Methods CSF metabolites data from humans were downloaded from genome-wide association study databases, and CSF metabolites were selected as exposure factors. single nucleotide polymorphisms (SNPs) strongly associated with the exposure factors and independent of each other were selected as instrumental variables. The TD dataset from the Finngen database was downloaded, including 365 cases of TD and 411 816 controls. Analysis was conducted using inverse variance weighting, MR-Egger, weighted median, weighted mode, and simple mode. Sensitivity analysis was conducted using leave-one-out, and multiple-effects testing was conducted using MR-Egger and MR-PRESSO. Heterogeneity was detected using Cochran’s Q. Results A total of 9 CSF metabolites were found to have a causal relationship with the occurrence and development of TD (P<0.05), with a total of 394 SNPs included in the analysis. Inverse variance weighting results showed that N-acetylneuraminic acid [odds ratio (OR)=2.715, 95% confidence interval (CI) (1.102, 6.961), P=0.030], γ-glutamylglutamine [OR=1.402, 95%CI (1.053, 1.868), P=0.021], lysine [OR=2.816, 95%CI (1.084, 7.319), P=0.034] could increase the risk of TD. Cysteinylglycine disulfide [OR=0.437, 95%CI (0.216, 0.885), P=0.021], propionylcarnitine [OR=0.762, 95%CI (0.616, 0.941), P=0.012], pantothenate [OR=0.706, 95%CI (0.523, 0.952), P=0.023], gulareic acid [OR=0.758, 95%CI (0.579, 0.992), P=0.044], and cysteine-glycine [OR=0.799, 95%CI (0.684, 0.934), P=0.005] could reduce the risk of TD. The results of leave-one-out sensitivity analysis were stable, and no horizontal pleiotropy or heterogeneity was observed. Conclusions N-acetylneuraminic acid, γ-glutamylglutamine, and lysine can increase the risk of TD, but cysteinylglycine disulfide, propionylcarnitine, pantothenate, gulagic acid and cysteine-glycine can reduce the risk of TD. However, the mechanism of their effects on TD still needs to be further explored.
Objective To evaluate the potential causal relationship between asthma and the risk of gastroesophageal reflux disease (GERD) using a two-sample Mendelian randomization study. Methods A large sample of genome-wide association study was used to summarize the data, and the genetic loci [single nucleotide polymorphisms (SNPs)] closely related to asthma were selected as instrumental variables, and Mendelian randomization analysis was conducted by inverse variance weighting, weighted median and MR-Egger method, respectively. At the same time, the multi-effect of MR-Egger was detected and the sensitivity analysis was carried out by Leave-one-out method to ensure the robustness of the results. Results A total of 77 SNPs closely related to asthma were selected as instrumental variables. The results of inverse variance weighted analysis showed a significant positive correlation between asthma and the occurrence of gastroesophageal reflux disease [odds ratio (OR)=1.044, 95% confidence interval (CI) (1.006, 1.083), P=0.024]. Weighted median results showed similar causality [OR=1.075, 95%CI (1.021, 1.133), P=0.006]. The MR-Egger regression results showed that there was a positive correlation between asthma and GERD, but there was no statistical significance [OR=1.080, 95%CI (0.983, 1.187), P=0.115]. The heterogeneity test results showed that there was no heterogeneity in the causal relationship between asthma and GERD (P>0.05). The results of the horizontal pleiotropy test showed that there was no horizontal pleiotropy in SNPs (P>0.05). The results of the retention test showed that no SNPs with significant impact on the results were detected. Conclusion There is a positive causal relationship between asthma and GERD.
ObjectiveTo explore the potential causal relationship between 91 inflammatory factors and the risk of lung cancer (LC). MethodsBy extracting related data of inflammatory factors and LC and its subtypes from public databases of genome-wide association studies (GWAS), bidirectional, repeated, multivariable Mendelian randomization (MR) and subgroup MR methods were used for analysis. The inverse variance weighted method was mainly used for causal inference, and a series of sensitivity analyses were applied to verify the strength of the results. ResultsHigher levels of CD5, interleukin-18 (IL-18), and oncostatin-M (OSM) were causally associated with a lower risk of LC, while nerve growth factor-β (NGF-β) and S100 calcium-binding protein A12 (S100A12) were associated with an increased risk of LC. Subgroup MR analysis results showed that IL-18 had a causal relationship with a reduced risk of lung adenocarcinoma, while NGF-β and S100A12 had a causal relationship with an increased risk of lung adenocarcinoma; CD5 and OSM had a causal relationship with a reduced risk of lung squamous cell carcinoma; NGF-β had a causal relationship with an increased risk of small cell lung cancer. ConclusionFive inflammatory factors, including CD5, IL-18, OSM, NGF-β, and S100A12 have a causal correlation with the risk of LC, providing potential targets for early screening of LC patients and development of therapeutic drugs.
Objective To explore the correlation between physical activity, sleep and aging using a two-sample Mendelian randomization (MR) method. Methods The data through genome-wide association studies was summarized. The single nucleotide polymorphisms (SNPs) related to physical activity and sleep as instrumental variables was selected. The inverse variance weighting method was used for the main analyses, complemented by the weighted median method and MR Egger regression, and then sensitivity analyses were carried out in terms of multiplicity, heterogeneity and leave-one-out method. Finally, multivariate Mendelian methods were applied to eliminate confounders and find mediators. Results A total of two types of physical activity (strong physical activity, physical inactivity) and three sleep conditions (daytime naps, short sleep duration, adequate sleep duration) were found to have a causal relationship with frailty index (P<0.05), while physical inactivity was found to have a causal relationship with telomere length (P<0.05). A total of 167 SNPs were included in the analysis. Strong physical activity [correlation coefficient (β)=?1.26, 95% confidence interval (CI) (?1.60, ?0.96), P<0.0001], adequate sleep duration [β=?0.17, 95%CI (?0.26, ?0.09), P<0.001] were negatively correlated with the frailty index. Physical inactivity [β=1.47, 95%CI (0.85, 2.08), P<0.001], daytime naps [β=0.25, 95%CI (0.12, 0.39), P=0.0002], and short sleep duration [β=0.20, 95%CI (0.13, 0.27), P<0.0001] were positively associated with frailty index. Physical inactivity [β=?0.38, 95%CI (?0.69, ?0.07), P=0.02] was negatively correlated with telomere length. Percentage body fat, body fat mass, waist circumference, body weight and body mass index partially mediated 25.52%, 23.52%, 10.08%, 17.6% and 10.08% of the effect between daytime naps and frailty index, respectively. Conclusion There is a causal relationship between physical activity, sleep, and aging.
