In order to improve the efficiency and guarantee the quality of the research of cross-regional multi-center clinical trials, with the combination of WIN 2003 Server IIS, SQL Server 2005 database and ASP.Net programming techniques, the Pocock and Simon minimized randomization system model facing the network was put forward, and this system based on that model was developed. The two sides in this system can achieve cooperation process from screening subjects, random allocation and drug management to filling electronic case report form. Moreover, the customers of this system can also publish official documents, exchange information and take full use of other available assistant functions through the office automation platform.
Objective To analyze whether there is a causal association between psoriasis and Alzheimer disease (AD) by a two-sample two-way Mendelian randomization (MR) method. Methods In the forward study, the single nucleotide polymorphisms (SNPs) associated with psoriasis were obtained from the comprehensive statistical data of the genome-wide association study database as the instrumental variables, and AD as the outcome; in the reverse study, the SNPs associated with AD were taken as instrumental variables, and psoriasis as the outcome. Using two-sample two-way MR analysis, the odds ratio (OR) value and 95% confidence interval (CI) of regression models, namely inverse variance weighted (IVW) method, MR-Egger regression method, weighted median method, simple pattern method, and weighted pattern method, were used to evaluate the causal relationship between psoriasis and AD. Cochran’s Q test was used to assess the heterogeneity of genetic instrumental variables, MR-Egger intercept method was used to test the horizontal pleiotropy of the assessment, “leave-one-out” method was used to assess the sensitivity of a SNP to the effect of causality, and the symmetry of funnel plot was observed to assess bias. Results A total of 19 SNPs associated with psoriasis were included as instrumental variables in the forward study. The IVW analysis of the forward study showed that there was a causal correlation between psoriasis and AD [OR=1.032, 95%CI (1.014, 1.051), P<0.001], and MR-Egger regression method [OR=1.042, 95%CI (1.012, 1.073), P=0.013], weighted median [OR=1.048, 95%CI (1.023, 1.074), P<0.001], and weighted model [OR=1.046, 95%CI (1.020, 1.073), P=0.002] all supported this result. Heterogeneity test (IVW result: Q=13.752, P=0.745; MR-Egger regression result: Q=13.134, P=0.727), MR-Egger intercept method (Egger intercept=–0.004, P=0.442), the results of “leave-one-out” method and funnel plot showed that the results of MR analysis were reliable. A total of 127 AD-related SNPs were included as instrumental variables in the reverse study. In reverse research, there was no evidence to support the AD could increase the risk of psoriasis (P>0.05). Heterogeneity test (IVW result: Q=232.496, P<0.001; MR-Egger regression result: Q=232.119, P<0.001) suggested heterogeneity, but MR-Egger intercept method (Egger intercept=0.003, P=0.652), the results of “leave-one-out” method and funnel plot showed that the results of MR analysis were reliable. Conclusion There is a causal association between psoriasis and AD, and psoriasis may increase the risk of AD.
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.
ObjectiveTo analyze the causal relationship between obstructive sleep apnea (OSA) with its typical symptoms (daytime sleepiness and snoring) and cardiovascular diseases (hypertension, coronary heart disease, myocardial infarction, heart failure) by using Mendelian randomization. MethodsWe used the instrumental variables (IV) in the FINNGen database and the UK Biobank to perform two-sample Mendelian randomization (TSMR) analysis. The results of random-effects inverse variance weighting method (IVW) were the main results. MR-Egger method was used for pleiotropic analysis and sensitivity analysis was performed by the leave-one-out method to verify the reliability of the data. ResultsOSA could lead to hypertension (IVW β=0.043, 95%CI 0.012 to 0.074, P=0.006) and heart failure (IVW β=0.234, 95%CI 0.015 to 0.452, P=0.036). Daytime sleepiness also had a pathogenic effect on heart failure (IVW β=1.139, 95%CI 0.271 to 2.006, P=0.010). There was no causal association between OSA and CHD or MI, snoring and the four CVDs. There was no causal association between daytime sleepiness and hypertension, CHD or MI.ConclusionOSA and daytime sleepiness have pathogenic effects on hypertension and heart failure, with heart failure being the most affected.
Objective To explore the causal relationship between the Collagen VI (COL6) family proteins COL6A1, A2, and A3 and bronchiectasis using the Mendelian randomization (MR) method.MethodsThe primary analysis was conducted using MR combined with summary-data-based Mendelian randomization (SMR) analysis. COL6 family proteins were used as exposure data, and bronchiectasis was used as outcome data. Cis-protein quantitative trait locus (cis-pQTL) data were extracted for analysis, and the results were meta-analyzed. Subsequently, COL6A3-cis-pQTL data from the UK Biobank plasma proteome study were used for further validation. Colocalization analysis was also performed to further explore the association between COL6 proteins and bronchiectasis.Results MR and SMR results revealed a negative causal relationship between COL6A3 and bronchiectasis (p-MRmeta = 0.005, OR = 0.30; p-SMRmeta = 0.004, OR = 0.26). The validation phase also confirmed the negative causal relationship between COL6A3 and bronchiectasis (p-MRmeta = 0.000007, OR = 0.27; p-SMRmeta = 0.0003, OR = 0.29). Colocalization analysis supported the presence of a shared causal variant (rs972974) between COL6A3 and bronchiectasis (PP.H4 = 0.967/0.876).Conclusion There is an inverse causal relationship between COL6A3 and bronchiectasis. Low expression of COL6A3 increases the risk of developing bronchiectasis, making COL6A3 a potential biomarker and therapeutic target for drug development in bronchiectasis.
Mendelian randomization (MR) studies use genetic variants as instrumental variables to explore the effects of exposures on health outcomes. STROBE-MR (strengthening the reporting of observational studies in epidemiology using Mendelian randomization) assists authors in reporting their MR studies clearly and transparently, and helpfully to improve the quality of MR. This paper interpreted the STROBE-MR, aiming to help Chinese scholars better understand, disseminate, and apply it.
ObjectiveTo conduct a two-sample Mendelian randomization (MR) study to assess the bidirectional causal relationship between multiple sclerosis and inflammatory bowel disease. MethodsWe performed two-sample bidirectional MR analysis using publicly available genome-wide association study (GWAS) data. The primary analysis method used was the inverse variance weighted (IVW) method, with MR-Egger weighted median as a supplementary analysis. Sensitivity analyses were conducted. ResultsIVW, weighted median, and weighted mode all supported a causal relationship between multiple sclerosis and an increased risk of ulcerative colitis (OR=1.07, 95%CI 1.01 to 1.13, P=0.018), while no association was found between multiple sclerosis and Crohn's disease. Sensitivity analyses suggested that the study results were not affected by pleiotropy. ConclusionGenetic predisposition to multiple sclerosis is associated with an elevated risk of developing ulcerative colitis but not Crohn’s disease.
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.
ObjectiveTo investigate the potential causal relationship between four types of reproductive behaviors and rheumatoid arthritis (RA), with the goal of establishing a theoretical foundation for clinical prevention and treatment strategies. MethodsPooled gene-wide association study (GWAS) data were obtained from large publicly searchable databases. Four characteristics like menarche, menopause, the age of first pregnancy and the age of last pregnancy, which related to reproductive behavior were selected as the exposure factors and RA as the outcome factors. Single nucleotide polymorphisms (SNPs), which were strongly correlated with the phenotype of the exposure factors, were screened as the instrumental variables, and two-sample Mendelian randomization analyses were used to assess the potential causal relationship between the exposure and the disease. Results① The Mendelian randomization analysis utilizing the inverse variance weighted method on two distinct samples revealed a significant negative correlation between the age of first pregnancy and last pregnancy with the risk of RA (OR=0.91, 95%CI 0.85 to 0.98, P=0.011; OR=0.54, 95%CI 0.31 to 0.93, P=0.026). Conversely, no causal relationship was observed between menarche and menopause with RA. Sensitivity analysis confirmed the robustness of the causal relationship, while MR Egger intercept analysis did not identify any potential horizontal pleiotropy (Page of first gestation -RA=0.169, Page of last gestation -RA=0.283). ② Reverse Mendelian randomization analysis revealed a significant positive causal association between RA and the age of first pregnancy, while no causal relationship was observed with the age of last pregnancy (OR=1.07, 95%CI 1.02 to 1.11, P=0.001). ③ Multivariate Mendelian randomization analysis demonstrated that both the age of first pregnancy and last pregnancy in women were inversely associated with the risk of RA (OR=0.88, 95%CI 0.80 to 0.97, P=0.010; OR=0.68, 95%CI 0.48 to 0.97, P=0.033). ④ There existed a negative correlation between the age of pregnancy in women and the risk of developing RA, suggesting a potential protective effect. ConclusionPregnancy age may have a negative causal relationship with the risk of RA, while menarche and menopause have no causal relationship with RA.
ObjectiveA two-sample Mendelian randomization analysis was used to explore the causal associations between four basic body indices (basal metabolic rate, body fat percentage, BMI and hip circumference) and myasthenia gravis (MG). MethodsPooled gene-wide association study (GWAS) data were obtained from large publicly searchable databases, and four basic body indices were selected as the exposure factors and myasthenia gravis as the outcome factors, and single nucleotide polymorphisms (SNPs), which were strongly correlated with the phenotype of the exposure factors, were screened as the instrumental variables, and two-sample Mendelian randomization analyses were performed in order to assess the potential causal relationship between the exposure and the disease. ResultsInverse variance weighting (IVW) analysis showed that increased basal metabolic rate (OR=1.39, 95%CI 1.00 to 1.93, P=0.047), body fat percentage (OR=1.61, 95%CI 1.06 to 2.44, P=0.024), and hip circumference (OR=1.67, 95%CI 1.29 to 2.17, P<0.001) increased the risk of MG. But there was no significant causal relationship between BMI and MG. ConclusionBasal metabolic rate, body fat percentage and hip circumference have a positive causal relationship with MG, while BMI does not have a significant causal relationship with MG.