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 This study employs Mendelian randomization analysis to explore the causal relationship between dietary habits and systemic lupus erythematosus (SLE). MethodsWe obtained data from the MRC-IEU database on five dietary habits as instrumental variables for exposure "never eating dairy products" "never eating eggs or foods containing eggs" "never eating sugar or foods/drinks containing sugar" "never eating wheat products" and "I eat all of the above". Summary data related to SLE were retrieved from the MRC-IEU database for the discovery cohort (designated as MSLE) and from a Finnish database for the validation cohort (recorded as FSLE). Two-sample Mendelian randomization analyses were conducted using inverse variance weighting (IVW), MR-Egger, weighted median, Simple Mode, and Weighted Mode methods to investigate the causal relationship between dietary habits and SLE. The MR-Egger intercept test was performed to assess the presence of horizontal pleiotropy, while the leave-one-out method was employed to verify the stability of the results, with Cochran’s Q test and funnel plots used to evaluate heterogeneity. ResultsMendelian randomization analysis indicated that never eating wheat products increases the risk of developing SLE (IVW: P<0.05). In contrast, there was no significant causal relationship between the consumption of dairy products, eggs or foods containing eggs, or the consumption of all of the above with SLE (IVW: P>0.05). Additionally, there was no significant causal relationship between never sugar or foods/drinks containing sugar and MSLE (IVW: P=0.877), although a potential causal association with FSLE was suggested (IVW: P=0.016). The MR-Egger intercept test indicated no evidence of horizontal pleiotropy (P>0.05). ConclusionNever eating wheat products may be an independent risk factor for SLE. However, the causal relationship between never sugar or foods/drinks containing sugar and SLE remains indeterminate.
The severe acute respiratory syndrome coronavirus 2 is characterized by a long incubation period, strong infectivity and general susceptibility to the population. At present, there are no specific medicines that can treat coronavirus disease 2019. In order to increase the understanding of the molecular biology of severe acute respiratory syndrome coronavirus 2 and try to find effective treatments, we used SnapGene Viewer to analyze the genomic sequences of five strains of severe acute respiratory syndrome coronavirus 2 that published by National Genomics Data Center. The results showed that the genome length of this virus was about 29.8 kb and twelve open reading frames were predicted, and five nucleotide change sites were found in the open reading frames. In addition, we analyzed drugs used during the outbreak of severe acute respiratory syndrome, current drugs for the treatment of coronavirus disease 2019 and other possible drugs, to find some possible medicines with clinical treatment effects.
ObjectiveTo screen long non-coding RNAs (lncRNAs) relevant to programmed cell death (PCD) and construct a nomogram model predicting prognosis of hepatocellular carcinoma (HCC). MethodsThe HCC patients selected from The Cancer Genome Atlas (TCGA) were randomly divided into training set and validation set according to 1∶1 sampling. The lncRNAs relevant to PCD were screened by Pearson correlation analysis, and which associated with overall survival in the training set were screened by univariate Cox proportional hazards regression (abbreviation as “Cox regression”), and then multivariate Cox regression was further used to analyze the prognostic risk factors of HCC patients, and the risk score function model was constructed. According to the median risk score of HCC patients in the training set, the HCC patients in each set were assigned into a high-risk and low-risk, and then the Kaplan-Meier method was used to draw the overall survival curve, and the log-rank test was used to compare the survival between the HCC patients with high-risk and low-risk. At the same time, the area under receiver operating characteristic curve (AUC) was used to evaluate the value of the risk score function model in predicting the 1-, 3-, and 5-year overall survival rates of HCC patients in the training set, validation set, and integral set. Then the nomogram was constructed based on the risk score function model and factors validated in clinic, and its predictive ability for the prognosis of HCC patients was evaluated. ResultsA total of 374 patients with HCC were downloaded from the TCGA, of which 342 had complete clinicopathologic data, including 171 in the training set and 171 in the validation set. Finally, 8 lncRNAs genes relevant to prognosis (AC099850.3, LINC00942, AC040970.1, AC022613.1, AC009403.1, AL355974.2, AC015908.3, AC009283.1) were screened out, and the prognostic risk score function model was established as follows: prognostic risk score=exp1×β1+exp2×β2...+expi×βi (expi was the expression level of target lncRNA, βi was the coefficient of multivariate Cox regression analysis of target lncRNA). According to this prognostic risk score function model, the median risk score was 0.89 in the training set. The patients with low-risk and high-risk were 86 and 85, 86 and 85, 172 and 170 in the training set, validation set, and integral set, respectively. The overall survival curves of HCC patients with low-risk drawn by Kaplan-Meier method were better than those of the HCC patients with high-risk in the training set, validation set, and integral set (P<0.001). The AUCs of the prognostic risk score function model for predicting the 1-, 3-, and 5-year overall survival rates in the training set were 0.814, 0.768, and 0.811, respectively, in the validation set were 0.799, 0.684, and 0.748, respectively, and in the integral set were 0.807, 0.732, and 0.784, respectively. The multivariate Cox regression analysis showed that the prognostic risk score function model was a risk factor affecting the overall survival of patients with HCC [<0.89 points as a reference, RR=1.217, 95%CI (1.151, 1.286), P<0.001]. The AUC (95%CI) of the prognostic risk score function model for predicting the overall survival rate of HCC patients was 0.822 (0.796, 0.873). The AUCs of the nomogram constructed by the prognostic risk score function model in combination with clinicopathologic factors to predict the 1-, 3-, and 5-year overall survival rates were 0.843, 0.839, and 0.834. The calibration curves of the nomogram of 1-, 3-, and 5-year overall survival rates in the training set were close to ideal curve, suggesting that the predicted overall survival rate by the nomogram was more consistent with the actual overall survival rate. ConclusionThe prognostic risk score function model constructed by the lncRNAs relevant to PCD in this study may be a potential marker of prognosis of the patients with HCC, and the nomogram constructed by this model is more effective in predicting the prognosis (overall survival) of patients with HCC.
ObjectiveTo compare the function and action pathways of VEGFA, VEGFB and VEGFC in VEGF family of mouse eye.MethodsUsing the BXD mouse gene data in Genenetwork database as template to compare and study the similarities and differences of VEGFA, VEGFB and VEGFC molecular pathways or potential functions in the whole genome expression spectrum of BXD recombinant mouse inbred line population, with multiple analytical methods and statistical strategies were used, such as gene expression level, target genes comparison, top genes comparison associated to target genes, expression Quantitative Trait Loci (eQTL).ResultsMatrix comparison showed strong positive correlation between two probes of VEGFC (r=0.732, P＜0.01), weak correlation between VEGFA 1420909 and VEGFC 1440739, VEGFA 1451959 and VEGFC 1451803, VEGFC 1419417959 and VEGFC 1439766, VEGFC 1451803 and VEGFC 1439766 (P＜0.05); there was no correlation between VEGFA 1420909 and four other genes except VEGFC 1440739, VEGFA 1451959 and VEGFC 1440739, VEGFB 1451803 and VEGFA 1420909/VEGFC 1419417/VEGFC 1440739 (P ＞0.05). In the comparative analysis of the relevant Top50 genes of each VEGF gene, most of the genes in BXD mouse were not significantly correlated with VEGFA, VEGFB and VEGFC except for the weak association of individual related genes. The results of eQTL analysis showed that each probe of VEGF gene was located on different chromosomes.ConclusionsThe expression levels and positive and negative correlations of VEGFA, VEGFB and VEGFC were different in the VEGF family of mouse eye, suggesting that these genes may play their role through different pathways.
Objective To identify and isolate the variant gene associated with gastric adenocarcinoma and clone the fragment of variant gene.Methods By arbitrarily primer polymerase chain reaction (AP-PCR), DNA samples from 5 matched gastric adenocarcinoma and non-tumor gastric tissues were analysed. Results The produced AP-PCR profiles were different in each matched gastric adenocarcinoma and non-tumor gastric tissue. One differentiated amplified DNA fragments PW2.2 from a matched gastric adenocarcinoma were cloned. The result of Southern blot hybridization with PW2.2 as a probe showing that this fragment was also found in some other gastric adenocarcinoma samples. Conclusion AP-PCR fingerprinting assay can be used to identify and clone the variant genes associated with gastric adenocarcinoma.
To evaluate the differential expression profiles of the lncRNAs, miRNAs, mRNAs and ceRNAs, and their implication in the prognosis in clear cell renal cell carcinoma (CCRCC), the large sample genomics analysis technologies were used in this study. The RNA and miRNA sequencing data of CCRCC were obtained from The Cancer Genome Atlas (TCGA) database, and R software was used for gene expression analysis and survival analysis. Cytoscape software was used to construct the ceRNA network. The results showed that a total of 1 570 lncRNAs, 54 miRNAs, and 17 mRNAs were differentially expressed in CCRCC, and most of their expression levels were up-regulated (false discovery rate < 0.01 and absolute log fold change > 2). The ceRNA regulatory network showed the interaction between 89 differentially expressed lncRNAs and 9 differentially expressed miRNAs. Further survival analysis revealed that 38 lncRNAs (including COL18A1-AS1, TCL6, LINC00475, UCA1, WT1-AS, HOTTIP, PVT1, etc.) and 2 miRNAs (including miR-21 and miR-155) were correlated with the overall survival time of CCRCC (P < 0.05). Together, this study provided us several new evidences for the targeted therapy and prognosis assessment of CCRCC.
Hereditary retinal diseases (IRD) are a type of blinding eye disease with high genetic heterogeneity. In recent years, the rapid development of gene therapy technology has provided new possibilities for the treatment of IRD. Among them, recombinant adeno-associated virus (rAAV) has become the most concerned gene delivery vector at present due to its low immunogenicity, long-term stable transgenic expression and good retinal targeting. Raav-based gene replacement therapies have demonstrated good safety and efficacy in multiple clinical trials. For instance, the Luxturna? therapy for RPE65 gene mutation-related retinopathy has been successfully applied in clinical practice. However, the packaging capacity limitation of rAAV makes it difficult to deliver larger pathogenic genes, such as USH2A or ABCA4, etc. In addition, some IRD require precise gene modification rather than simple gene supplementation. To overcome these limitations, researchers are exploring a variety of strategies, including the splitting and delivery of biadeno-associated viral vectors, CRISPR/Cas9 gene editing technology, and the development of novel engineered capsids. Future research should focus on optimizing the safety and delivery efficiency of gene editing tools, establishing a more complete preclinical evaluation system, and further enhancing the tissue specificity of vectors. The breakthroughs in these technologies will promote the application of gene therapy in a wider range of IRD.
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.
ObjectiveTo explore whether there is a causal relationship between intestinal flora and esophageal cancer. MethodsSummary statistics of intestinal flora and esophageal cancer were obtained from the Genome-wide Association Studies (GWAS) database. Five methods, including inverse variance weighted (IVW), weighted median estimation, Mendelian randomization (MR)-Egger regression, single mode, and weighted mode, were used for analysis, with IVW as the main analysis method. Sensitivity analysis was used to evaluate the reliability of MR results. ResultsIn the IVW method, Oxalobacteraceae [OR=1.001, 95%CI (1.000, 1.002), P=0.023], Faecalibacterium [OR=1.001, 95%CI (1.000, 1.002), P=0.028], Senegalimassilia [OR=1.002, 95%CI (1.000, 1.003), P=0.006] and Veillonella [OR=1.001, 95%CI (1.000, 1.002), P=0.018] were positively correlated with esophageal cancer, while Burkholderiales [OR=0.999, 95%CI (0.998, 1.000), P=0.002], Eubacterium oxidoreducens [OR=0.998, 95%CI (0.997, 0.999), P=0.038], Romboutsia [OR=0.999, 95%CI (0.998, 1.000), P=0.048] and Turicibacter [OR=0.998, 95%CI (0.997, 0.999), P=0.013] were negatively correlated with esophageal cancer. Sensitivity analysis showed no evidence of heterogeneity, horizontal pleiotropy and reverse causality. ConclusionOxalobacteraceae, Faecalibacterium, Senegalimassilia and Veillonella increase the risk of esophageal cancer, while Burkholderiales, Eubacterium oxidoreducens, Romboutsia and Turicibacter decrease the risk of esophageal cancer. Further studies are needed to explore how these bacteria affect the progression of esophageal cancer.