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Objective To investigate the genetic risk factors of deep vein thrombosis(DVT)after trauma.Methods In a nested case-control study,50 patients with DVT after traumatic lower extremity fractures and 50 patients without DVT were recruited.The two groups were matched with gender,age and fracture sites.Preoperative venography was performed to diagnose DVT in trauma patients.Genome wide association study(GWAS)was used to investigate the genetic risk factors for preoperative DVT after traumatic lower ex-tremity fractures.Genomic DNA in leukocytes from blood sample was extracted and used for GWAS.Results GWAS was conducted based on 2 662 single nucleotide variants(SNV)which were dispersed in 144 interested genes.Ten genes were found to have signifi-cant association with trauma-related DVT,including cofactors of hemostasis mechanism,i.e.,THBD,F5,SERPIND1 and ITGA2,the factors related to vitamin K-dependent(VKD)carboxylation,i.e.,GGCX and CALU,and the members of cytochrome P450 family,i.e.,CYP1A1,CYP3A4,CYP2C19 and CYP2B6.Conclusion DVT after trauma might be regulated by the cofactors of hemostasis mechanism,the factors related to VKD carboxylation and the members of cytochrome P450 family.The results of our study may provide reference and inspiration for genetic susceptibility of preoperative DVT after trauma.
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【Objective】 To investigate the effects of emotions (subjective well-being, depressed effect, worry, and guilt) on cancer (colorectal cancer, hepatic cancer, thyroid cancer, lung cancer, and breast cancer). 【Methods】 Two-sample bi-directional Mendelian randomization (MR) method was adopted. All data were based on summary data from genome-wide association studies (GWAS). Inverse variance weighting (IVW) was used to generate the main results, and weighted median (WM) and MR-Egger methods were employed to calculate supplementary results. The outcome measure was odds ratio (OR), and sensitivity analysis was conducted. 【Results】 For depressed effect, a significant association with lung cancer (OR=1.005, 95% CI: 1.001-1.009, P=0.015) was found. For worry, a significant association with breast cancer (OR=1.199, 95% CI: 1.011-1.423, P=0.038) was observed. For guilt, a significant association with thyroid cancer (OR=2.083, 95% CI: 1.080-4.017, P=0.029) was identified. After removing all potentially pleiotropic SNPs detected by MR PRESSO, the association between worry and breast cancer showed no statistical difference (P=0.064), while the association between worry and colorectal cancer remained significant (OR=0.739, 95% CI: 0.571-0.956, P=0.021). No causal relationship was found between cancer and emotions. 【Conclusion】 There is a causal relationship between depression and increased lung cancer incidence, guilt and increased thyroid cancer incidence, as well as anxiety and decreased colorectal cancer incidence.
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【Objective】 To explore the causal relationship between education level and pancreatitis risk through Mendelian randomization. 【Methods】 A two-sample Mendelian randomization analysis was conducted using genome-wide association study (GWAS) summary data. The GWAS data for education level and pancreatitis were obtained from SSGAC database and the FinnGen database (version R9). Causal relationship between education level and pancreatitis was explored using the inverse variance weighted (IVW), MR-Egger, and weighted median methods. Heterogeneity and directional pleiotropy were evaluated using Cochran’s Q test and funnel plots. 【Results】 Totally 604 SNPs associated with education level were included. The results provided evidence that there was negative relationship between education level and pancreatitis risk. For acute pancreatitis, OR=0.52, 95% CI: 0.44-0.62, P=2.43×10-14 while for chronic pancreatitis, OR=0.51, 95% CI: 0.41-0.64, P=7.20×10-9. Results from MR-Egger and weighted median analyses obtained the same results. The results of sensitivity analysis indicated that this study did not violate the basic assumptions of Mendelian randomization. 【Conclusion】 There is a causal relationship between education level and the occurrence of pancreatitis. The educational level is negatively correlated with the risk of pancreatitis.
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【Objective】 A two-sample Mendelian randomization method was used to explore whether there is a causal relationship between the intake of alcohol, coffee, green tea and dairy products and the incidence of prostate cancer (PCa), in order to clarify the risk factors for the incidence of PCa and find a prevention pathway for PCa. 【Methods】 Data of alcohol, coffee, green tea, dairy products and prostate cancer were collected with genome-wide association study (GWAS).The causal relationship between their intake and the risk of PCa was analyzed with two-sample Mendelian randomization (2SMR).MR analysis was conducted with inverse-variance weighting (IVW).Sensitivity analysis was performed with weighted median, MR-Egger regression, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) tests. 【Results】 Coffee intake (OR: 0.994, 95%CI: 0.990-0.999, P=0.014) and green tea intake (OR: 0.999, 95%CI: 0.998-0.999, P=0.036) were negatively correlated with the risk of PCa.Alcohol intake (OR: 0.997, 95%CI: 0.990-1.004, P=0.392) and dairy intake (OR: 1.025, 95%CI: 0.983-1.069, P=0.256) were not associated with the risk of PCa.In weighted median, MR-Egger regression, and retention one method analyses, the results were robust without heterogeneity or pleiotropy. 【Conclusion】 There was a causal association between coffee intake and green tea intake and the onset of PCa, but no causal association between alcohol intake and dairy intake and PCa onset.
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BACKGROUND:Many clinical research observations have indicated a close association between rheumatoid arthritis and osteoporosis as well as bone mineral density(BMD).However,it remains unclear whether there is a causal genetic relationship between rheumatoid arthritis and the development of osteoporosis and alterations of BMD. OBJECTIVE:To assess the potential causal relationship between rheumatoid arthritis and osteoporosis as well as BMD using a two-sample Mendelian randomization approach,provide meaningful insights from a genetic perspective into the underlying mechanisms and offer a reference for early prevention of osteoporosis and improvement in the progression of the disease. METHODS:We conducted a study using data from publicly available genome-wide association studies databases to identify single nucleotide polymorphisms associated with rheumatoid arthritis as instrumental variables(P<5×10-8).The main outcomes of the study included osteoporosis and BMD at five different sites,including total body BMD,lumbar spine BMD,femoral neck BMD,heel BMD,and forearm BMD.The inverse variance-weighted method was used as the primary analysis method to evaluate causal effects.Weighted median,simple median,weighted mode and MR-Egger regression were used as supplementary analyses.Causal relationships between rheumatoid arthritis and the risk of osteoporosis and BMD were assessed using odds ratios(OR)and 95%confidence intervals(CI).Heterogeneity was assessed using Cochran's Q test and horizontal pleiotropy was evaluated using MR-Egger intercept tests. RESULTS AND CONCLUSION:The inverse variance-weighted analysis demonstrated a positive association between genetically predicted rheumatoid arthritis and osteoporosis(OR=1.123,95%CI:1.077-1.171;P=4.02×10-8).Heterogeneity test(P=0.388)indicated no significant heterogeneity among the single nucleotide polymorphisms.MR-Egger intercept(P=0.571)tests did not detect horizontal pleiotropy,and sensitivity analysis showed no evidence of bias in the study results.There was no causal relationship between rheumatoid arthritis and BMD at the five different sites.The total body BMD(OR=1.000,95%CI:0.988-1.012;P=0.925),lumbar spine BMD(OR=0.999,95%CI:0.982-1.016;P=0.937),femoral neck BMD(OR=1.001,95%CI:0.986-1.016;P=0.866),heel BMD(OR=0.996,95%CI:0.989-1.004;P=0.419),and forearm BMD(OR=1.063,95%CI:0.970-1.031;P=0.996)indicated no significant association.MR-Egger intercept analysis did not detect potential horizontal pleiotropy(total body BMD:P=0.253;lumbar spine BMD:P=0.638;femoral neck BMD:P=0.553;heel BMD:P=0.444;forearm BMD:P=0.079).Rheumatoid arthritis may contribute to the development of osteoporosis through the interaction between chronic inflammation and bone formation,resorption,and absorption.Additionally,the use of glucocorticoids and the presence of autoantibodies(such as anti-citrullinated protein antibody)in patients with rheumatoid arthritis showed associations with osteoporosis.Future research should focus on monitoring systemic inflammatory markers,standardized use of glucocorticoids,and regular screening for osteoporosis risk in patients with rheumatoid arthritis.
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BACKGROUND:Observational studies have suggested that statins may have a protective effect against osteoarthritis,including knee osteoarthritis and hip osteoarthritis.However,the association between statins and the risk of osteoarthritis remains unclear. OBJECTIVE:To investigate the association between statins and the risk of osteoarthritis through Mendelian randomization analysis using summary data from large-scale population-based genome-wide association studies(GWAS). METHODS:Firstly,single nucleotide polymorphism data related to statins were obtained from the latest 9th edition of the FinnGen database,while data of osteoarthritis,knee osteoarthritis and hip osteoarthritis were obtained from the IEU Open GWAS,UK Biobank,and ArcOGEN(Genetics of Osteoarthritis)databases,respectively.The inverse variance weighted method was used as the primary analysis approach to evaluate the causal effects.The weighted median method,simple median method,weighted mode-based method,and MR-Egger regression were used as supplementary analyses.The causal relationship between statins and the risk of osteoarthritis,knee osteoarthritis and hip osteoarthritis was assessed using odds ratios(OR)with 95%confidence intervals(CI).Sensitivity analyses were conducted to validate the reliability of the results,including the Cochran's Q test for heterogeneity and the MR-Egger-intercept test for horizontal pleiotropy,as well as leave-one-out analysis to identify potentially influential single nucleotide polymorphisms. RESULTS AND CONCLUSION:The inverse variance weighted analysis demonstrated a negative causal relationship between genetically predicted statins and the risk of osteoarthritis(OR=0.998,95%CI:0.996-0.999,P=0.01),knee osteoarthritis(OR=0.964,95%CI:0.940-0.989,P=0.005),and hip osteoarthritis(OR=0.928,95%CI:0.901-0.955,P=4.28×10-7).MR-Egger intercept analysis did not detect potential horizontal pleiotropy(osteoarthritis:P=0.658;knee osteoarthritis:P=0.600;hip osteoarthritis:P=0.141).The results of this study provide evidence that statins reduce the risks of osteoarthritis,knee osteoarthritis and hip osteoarthritis as described in observational studies.Further research is needed to explore the specific mechanisms of statin treatment for osteoarthritis.
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BACKGROUND:Osteonecrosis due to drugs is a serious adverse reaction occurring after the application of such drugs.Increasing evidence suggests that the gut microbiota composition is associated with osteonecrosis due to drugs.However,the causal relationship of the gut microbiota to osteonecrosis due to drugs is still unclear. OBJECTIVE:To evaluate the potential causal relationship between the gut microbiota and the risk of osteonecrosis due to drugs using the Mendelian randomization method. METHODS:A two-sample Mendelian randomization study was performed using the summary statistics of gut microbiota from the largest available genome-wide association study meta-analysis(n=13 266)conducted by the MiBioGen consortium as well as the summary statistics of osteonecrosis due to drugs obtained from the FinnGen consortium R9 release data(264 cases and 377 013 controls).Inverse variance weighted,MR-Egger,weighted median,weighted model and simple model were used to examine the causal association between gut microbiota and osteonecrosis due to drugs.Sensitivity analysis was used to test whether the results of the Mendelian randomization analysis were reliable.Reverse Mendelian randomization analysis was performed on all the bacteria as an outcome for effect analysis and sensitivity analysis. RESULTS AND CONCLUSION:Inverse variance weighted estimates suggested that Lentisphaerae(phylum),Lentisphaeria(class),Melainabacteria(class),Gastranaerophilales(order),Rhodospirillales(order),Victivallales(order)and Bifidobacterium(genus)had protective causal effects on osteonecrosis due to drugs.Methanobacteria(class),Bacillales(order),Methanobacteriaceae(family),Lachnospiraceae(family),Methanobacteriales(order),Holdemania(genus),Holdemania(UCG010 group)(genus),Odoribacter(genus)and Tyzzerella3(genus)had negative causal effects on osteonecrosis due to drugs.According to the results of reverse Mendelian randomization analysis,Clostridiaceae1(family),Peptostreptococcaceae(family),Streptococcaceae(family),Clostridiumsensustricto1(genus)and Streptococcus(genus)showed negative causal effects on osteonecrosis due to drugs.However,Eisenbergiella(genus)showed protective causal effects on osteonecrosis due to drugs.None of the bidirectional sensitivity analysis revealed heterogeneity or horizontal pleiotropy.When gut microbiota were used as exposure and osteonecrosis due to drugs as the outcome,Mendelian randomization analysis found that seven bacterial traits were positively correlated to osteonecrosis due to drugs,nine bacterial traits were negatively related to osteonecrosis due to drugs.When osteonecrosis due to drugs were used as exposure and gut microbiota as the outcome,reverse Mendelian randomization analysis found a negative correlated relationship with five bacterial traits and a positive causal relationship with one bacterial trait.By changing the diversity and composition of gut microbiota,it is expected to improve the incidence and prognosis of osteonecrosis due to drugs,providing new ideas for the study of orthopedic diseases.
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BACKGROUND:Observational studies have suggested that statin drugs may have a protective effect on bone density,making them a potential treatment option for osteoporosis. OBJECTIVE:To evaluate the causal relationship between drug target-mediated lipid phenotypes and bone mineral density(BMD)using Mendelian randomization methods. METHODS:We obtained single nucleotide polymorphismsrelated to statin drugs and BMD data from the IEU Open GWAS database.The primary analysis method was the inverse variance weighted method,and we also used weighted median,simple median,weighted mode,and MR-Egger regression.We usedβ values and 95%confidence intervals(CI)to assess the causal relationship between statin drugs and BMD.Additionally,we conducted sensitivity analyses to validate the results,assessed heterogeneity using Cochran's Q test,examined for horizontal pleiotropy using the MR-Egger intercept test,and performed leave-one-out analyses to determine if individual or multiplesingle nucleotide polymorphism influenced the results. RESULTS AND CONCLUSION:There was a significant association between the statin target of action,3-hydroxy-3-methyl glutaryl coenzyme A reductase-mediated low-density lipoprotein cholesterol,and heel bone BMD(β=-0.086,95%CI:-0.117 to-0.055,P=5.42×10-8)and whole-body BMD(β=-0.193,95%CI:-0.288 to-0.098,P=7.35×10-5).The findings of this study support the protective effect of statin drugs on BMD.These findings not only deepen our understanding of the relationship between cholesterol-related genes and bone health but also reveal potential therapeutic targets for improving BMD.
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BACKGROUND:Osteonecrosis is a common refractory disease in clinical practice,and observational studies have suggested that micronutrients may have a prognostic role in osteonecrosis.However,the specific causal association between micronutrients and osteonecrosis is not known. OBJECTIVE:To explore the causal association between micronutrients and osteonecrosis by Mendelian randomization using summary data from a large population-based genome-wide association study(GWAS)for clinical diagnosis and treatment. METHODS:The required exposure and outcome data(calcium,magnesium,iron,vitamin E,carotenoids,retinol&osteonecrosis)were extracted from the IEU OpenGWAS database,GWAS catalog database,and FinnGen database.Data were analyzed by bidirectional Mendelian randomization with inverse-variance weighted as the primary study method,and weighted median method,simple mode method,weighted mode method,and MR-Egger regression to complement the results.The reliability of the data was then verified through sensitivity analyses. RESULTS AND CONCLUSION:(1)The results found a positive correlation between serum iron concentration and osteonecrosis,while no correlation was found for other micronutrients.There was no reverse causality in all the data.(2)The results of sensitivity analysis showed a robust causality.(3)By Mendelian randomization method,this study provided evidence of causality between serum iron concentration and osteonecrosis,and understanding the causality of micronutrient elements on osteonecrosis can help in the clinical diagnosis and treatment of osteonecrosis,which is of great clinical significance.
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BACKGROUND:It has been found in recent observational studies that assessing localized fat mass is crucial in the evaluation of disc degeneration.Although obesity has been recognized as a risk factor for disc degeneration,the causal relationship between fat mass,which is a key factor in obesity,and intervertebral disc degeneration has been unclear in previous studies. OBJECTIVE:To investigate the causal risk factors of intervertebral disc degeneration associated with different distributions of fat mass,thereby enhancing the understanding of the pathogenesis of intervertebral disc degeneration and contributing to the development of preventive,therapeutic,and prognostic strategies. METHODS:Genetic markers associated with trunk and lower limb fat mass were extracted as instrumental variables from the publicly available IEU Open GWAS under the conditions of strong correlation and fulfillment of linkage disequilibrium.These markers were combined with the Mendelian randomization analysis to investigate the relationship between body fat and intervertebral disc degeneration.We used the latest version 9 database of FinnGen and assessed the results using several regression models,including inverse variance weighting,MR-Egger regression,simple mode,weighted mode,and weighted median estimator.We also assessed the heterogeneity of the genetic markers using Cochran's Q test,and multiplicity was assessed using the MR-Egger intercept test.Additionally,we used the leave-one-out method to determine the sensitivity of individual genetic markers to the causal effect of the exposure and outcome.The results were presented as odds ratios(OR)and 95%confidence intervals(CI). RESULTS AND CONCLUSION:The results from the inverse variance weighting method revealed that there was a positive causal relationship between trunk fat mass and the risk of developing intervertebral disc degeneration(OR=1.25,95%CI:1.15-1.35,P<0.001).Additionally,there was an inverse causal relationship between bilateral lower limb fat mass and the risk of developing intervertebral disc degeneration(OR=0.7,95%CI:0.63-0.78,P<0.001;OR=0.69,95%CI:0.62-0.76,P<0.001).Furthermore,the MR-Egger intercept analysis did not detect any potential horizontal pleiotropy.No bias single nucleotide polymorphisms were detected,while heterogeneity tests were present,and the leave-one-out sensitivity analysis suggested reliable results.The results above demonstrate a positive causal relationship between trunk fat mass and intervertebral disc degeneration.As trunk fat mass increases,the risk of intervertebral disc degeneration rises.With an increase in both lower limb fat mass,the risk of intervertebral disc degeneration decreases.Fat content and distribution affects the risk of developing intervertebral disc degeneration and should be given more attention.
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Objective@#To explore the bidirectional causal relationships between periodontitis and asthma using the two-sample Mendelian randomization (MR) method to provide a basis for exploring the etiology and formulating preventive and therapeutic measures of periodontitis and asthma.@*Methods@#We performed two-sample bidirectional Mendelian randomization analysis using publicly released European genome-wide association studies (GWAS) statistics for periodontitis (n = 34 615) and asthma (n = 408 422). The inverse variance weighted (IVW) method was employed as the main approach to estimate the bidirectional causal relationships between periodontitis and asthma. In addition, weighted median (WM), MR-Egger regression, maximum likelihood, and Mendelian randomization robust adjusted profile score (MR-RAPS) were used as supplementary analyses. Sensitivity analyses were conducted using Cochran's Q test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and leave-one-out analysis.@*Results@#A total of 12 and 43 single-nucleotide polymorphisms (SNPs) were included as instrumental variables for periodontitis and asthma, respectively. The results of IVW, WM, MR-Egger regression, maximum likelihood, and MR-RAPS showed that periodontitis was not causally related to the risk of asthma (IVW: OR: 1.003, 95% CI: 0.973-1.035, P = 0.828, WM: OR: 0.990, 95% CI: 0.951-1.031, P = 0.641; MR-Egger regression: OR: 0.988, 95% CI: 0.960-1.028, P = 0.573; maximum likelihood: OR: 1.003, 95% CI: 0.972-1.035, P = 0.834; MR-RAPS: OR: 1.002, 95% CI: 0.970-1.036, P = 0.890) among the European population, and no causal effect of asthma on periodontitis was found (IVW: OR: 1.021, 95% CI: 0.938-1.111, P = 0.633, WM: OR: 1.011, 95% CI: 0.894-1.142, P = 0.866; MR-Egger regression: OR: 1.042, 95% CI: 0.824-1.319, P = 0.731; maximum likelihood: OR: 1.021, 95% CI: 0.938-1.112, P = 0.631; MR-RAPS: OR: 1.017, 95% CI: 0.931-1.110, P = 0.713) among the European population. Cochran's Q test showed no heterogeneity among the included instrumental variables, MR-PRESSO test found no horizontal pleiotropy, and the leave-one-out method did not identify outlier SNPs.@*Conclusion@#The results of this study, based on European genetic data, do not support a bidirectional causal association between periodontitis and asthma in the European population.
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BackgroundMajor depressive disorder and insomnia often coexist, and the two may share a mechanism of pathogenesis and be affected by common underlying genes with strong pleiotropic effects. Previous genome-wide association studies (GWAS) mainly focused on single-gene morphological characters analysis, which impose limitations on showing possible pleiotropic effects. ObjectiveTo identify genetic loci related to insomnia and major depressive disorder, and to examine whether there are common genetic factors underlying both insomnia and depression. MethodsThe GWAS data for major depressive disorder originates from the Psychiatric Genomics Consortium (PGC), which comprises a total of 246 363 depressive cases and 561 190 controls. The insomnia GWAS data was downloaded from Sleep Disorder Knowledge Portal, involving 1 331 010 participants. Then the conditional false discovery rate (cFDR) and conjunction cFDR (ccFDR) were utilized to identify the genetic loci associated with major depressive disorder and insomnia, and pathway enrichment analysis was performed to examine the biological functions of these loci. ResultsA significant pleiotropic effect was detected between major depressive disorder and insomnia. By leveraging pleiotropic enrichment, 21 susceptibility loci (17 novel loci) for major depressive disorder and 38 susceptibility loci (28 novel loci) for insomnia were identified with the threshold of cFDR<0.01. A total of 16 pleiotropic loci (15 novel loci) related to both major depressive disorder and insomnia were identified with the threshold of ccFDR<0.05. pathway enrichment analysis indicated that the susceptibility loci were mainly enriched in synaptic transmission pathway, such as postsynaptic density (GO:0014069, P=4.91E-04, FDR=4.84E-03), asymmetric synapse (GO:0032279, P=5.09E-04, FDR=4.84E-03), and regulation of postsynaptic membrane neurotransmitter receptor levels (GO:0099072, P=5.11E-04, FDR=1.69E-02). ConclusionA significant pleiotropic enrichment is found between major depressive disorder and insomnia, and the comorbidity mechanism is related to synaptic transmission. [Funded by Tianjin Health Science and Technology Project (number, TJWJ2021QN065); Tianjin Key Medical Discipline (Specialty) Construction Project (number, TJYXZDXK-033A)]
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Objective@#To examine the association between leukocyte telomere length and cataract using bidirectional Mendelian randomization (MR) approach, so as to provide the basis for early diagnosis and prevention of cataracts.@*Methods@#Leukocyte telomere length data were collected through a meta analysis of genome-wide association studies (GWAS), including 78 952 participants, and the GWAS data of cataract were collected through the UK Biobank, including 8 890 cases and 454 120 controls. A bidirectional MR analysis was performed using the inverse-variance weighted (IVW) method, and single nucleotide polymorphisms (SNPs) which were associated with leukocyte telomere length were selected as instrumental variables. The heterogeneity was assessed using the Cochran's Q test, the horizontal pleiotropy was assessed using the MR-Egger regression and the outlier was verified with the leave-one-out and MR-PRESSO test.@*Results@#Forward MR analysis results showed that shortened leukocyte telomere length had an increased risk of cataract (OR=0.991, 95%CI: 0.990-0.997). Reverse MR analysis results showed no statistically significant association between leukocyte telomere length and cataract (P>0.05). Cochran's Q test detected no heterogeneity, and neither the MR-Egger regression nor the MR-PRESSO test revealed horizontal pleiotropy of instrumental variables (both P>0.05). Leave-one-out analysis showed robustness of the MR analysis results.@*Conclusion@#Shorter leukocyte telomere length might be associated with increased risk of cataract.
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Objective@#To evaluate the bidirectional association between periodontitis and Sjögren's syndrome using the Mendelian randomization (MR) method.@*Methods@#Genome-wide association study (GWAS) data of periodontitis (N = 45 563) and Sjögren's syndrome (N = 214 435) were selected to meet the requirements of the same ethnicity and different regions. Inverse variance-weighted (IVW), MR-Egger, and weighted median (WM) tests were used to evaluate the causal effect. Cochran's Q statistics, MR-Egger intercept, MR-PRESSO and leave-one-out analysis were used as sensitivity analyses to assess the stability and reliability of the results.@*Results@#After screening, the GWAS data of Sjögren's syndrome were based on the Finnish region, and the periodontitis GWAS data were based on the UK region, both of which originated from European ancestry. Using IVW (OR = 1.017, 95% CI = 0.956-1.082), MR-Egger (OR = 0.985, 95% CI= 0.956-1.082), and WM (OR =1.021, 95% CI = 0.948-1.099), no causal effect of Sjögren's syndrome on periodontitis was found using any of the three methods. Conversely, no causal effect of periodontitis on Sjögren's syndrome was found (IVW, OR = 1.024, 95% CI = 0.852-1.230; MR-Egger, OR = 0.978, 95% CI = 0.789-1.212; WM, OR = 1.024, 95% CI = 0.846-1.260). The sensitivity analyses indicated that the results were stable and reliable. Cochran's Q test and MR-PRESSO revealed that there was no significant heterogeneity among the instrumental variables, which included single nucleotide polymorphisms (SNPs). The intercept of MR-Egger regression indicated no pleiotropy in the included SNPs. No individual SNP was found that significantly affected the results using the leave-one-out method.@*Conclusion@#This study does not support a bidirectional causal effect between periodontitis and Sjögren's syndrome.
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In recent years, the research method of Mendelian randomization based on genome-wide association studies has been widely used for etiological exploration in the medical field, which can effectively overcome the confounding biases and interference of reverse causalities in traditional observational researches with its unique advantages of the distributive randomness and timing priority of genetic variants. This article reviews the method of Mendelian randomization and its application in liver cancer, in order to provide new ideas for the research on causal association in liver cancer.
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Eggplant is an important horticultural crop and one of the most widely grown vegetables in the Solanaceae family. Eggplant fruit-related agronomic traits are complex quantitative traits with low efficiency and long cycle time for traditional breeding selection. With the rapid development of high-throughput sequencing technology and bioinformatics tools, genome-wide association study (GWAS) has shown great application potential in analyzing the genetic rules of complex agronomic traits related to eggplant fruits. This paper first reviews the progress of genome-wide association analysis in eggplant fruit shape, fruit color and other fruit-related agronomic traits. Subsequently, aiming at the problem of missing heritability, which is common in the genetic studies of eggplant quantitative traits, this paper puts forward the development strategies of eggplant GWAS in the future based on the hot spots of application of four GWAS strategies in the research of agronomics traits related to eggplant fruits. Lastly, the application of GWAS strategy in the field of eggplant molecular breeding is expected to provide a theoretical basis and reference for the future use of GWAS to analyze the genetic basis of various eggplant fruit-related traits and to select fruit materials that meet consumer needs.
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Solanum melongena/genetics , Fruit/genetics , Genome-Wide Association Study , Plant Breeding , Agriculture , VegetablesABSTRACT
OBJECTIVES@#Intracerebral hemorrhage (ICH) has the highest mortality and disability rates among various subtypes of stroke. Previous studies have shown that the gut microbiome (GM) is closely related to the risk factors and pathological basis of ICH. This study aims to explore the causal effect of GM on ICH and the potential mechanisms.@*METHODS@#Genome wide association study (GWAS) data on GM and ICH were obtained from Microbiome Genome and International Stroke Genetics Consortium. Based on the GWAS data, we first performed Mendelian randomization (MR) analysis to evaluate the causal association between GM and ICH. Then, a conditional false discovery rate (cFDR) method was conducted to identify the pleiotropic variants.@*RESULTS@#MR analysis showed that Pasteurellales, Pasteurellaceae, and Haemophilus were negatively correlated with the risk of ICH, whileVerrucomicrobiae, Verrucomicrobiales, Verrucomicrobiaceae, Akkermansia, Holdemanella, and LachnospiraceaeUCG010 were positively correlated with ICH. By applying the cFDR method, 3 pleiotropic loci (rs331083, rs4315115, and rs12553325) were found to be associated with both GM and ICH.@*CONCLUSIONS@#There is a causal association and pleiotropic variants between GM and ICH.
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Humans , Genome-Wide Association Study , Gastrointestinal Microbiome/genetics , Genetic Predisposition to Disease , Cerebral Hemorrhage/genetics , StrokeABSTRACT
@#Abstract: Objective To understand the characteristics of mutations associated with resistance among 72 multidrug-resistant tuberculosis (MDR-TB) strains using whole genome sequencing (WGS) and to evaluate the performance of WGS for predicting MDR-TB drug resistance. Methods The clinical strains isolated from patients who visited the outpatient department of Tianjin Center for Tuberculosis Control from January to September in 2020 were collected. Identification tests using p-nitrobenzoic acid (PNB) medium were performed. Drug susceptibility tests (proportion method) on L-J medium were performed. After excluding duplicate strains, 72 MDR-TB strains were selected for WGS. Data were analyzed by using online databases and the phenotypic drug susceptibility test results were compared with resistance profiles predicted by WGS. Results All of 72 MDR-TB strains belonged to linage 2, and there was no significant difference in rate of pre-extensive drug-resistant tuberculosis (pre-XDR-TB) between modern type and ancestral type (χ2=0.287, P=0.592). A total of 81 mutation types were found from resistance-related genes for 12 anti-tuberculosis drugs, and the common mutation types in different drug-resistant strains were: streptomycin (SM): rpsL Lys43Arg; isoniazid (INH): katG Ser315Thr; rifampicin (RIF): rpoB Ser450Leu; ethambutol (EMB): embB Met306Val; ofloxacin (OFX), levofloxacin (LFX), moxifloxacin (MFX): gyrA Asp94Gly; kanamycin (KAM), capreomycin (CAP), amikacin (AMK): rrs 1401a>g; para-aminosalicylic acid (PAS): folC Ile43Thr. Nine mutation types were found in 9 prothionamide (PTO)-resistant strains, one type for each strain. The sensitivity and specificity of WGS for predicting resistance to different drugs were SM: 98.15% and 88.89%, INH: 90.28% and -, RIF: 98.62% and -, EMB: 79.49% and75.76%, OFX: 97.30% and 85.71%, KAM: 85.71% and 98.46%, PAS: 27.27% and 95.08%, PTO: 81.82% and 60.66%, CAP: 60.00% and 98.51%, LFX: 97.22% and 83.33%, MFX: 97.30% and 85.71%, AMK:100.00% and 100.00%, respectively. Conclusion WGS is a rapid and promising method which has high consistency with the phenotypic drug sensitivity test. Therefore, it has good application prospects in predicting drug resistance in MDR-TB.
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Advancements in high-throughput sequencing have yielded vast amounts of genomic data, which are studied using genome-wide association study (GWAS)/phenome-wide association study (PheWAS) methods to identify associations between the genotype and phenotype. The associated findings have contributed to pharmacogenomics and improved clinical decision support at the point of care in many healthcare systems. However, the accumulation of genomic data from sequencing and clinical data from electronic health records (EHRs) poses significant challenges for data scientists. Following the rise of artificial intelligence (AI) technology such as machine learning and deep learning, an increasing number of GWAS/PheWAS studies have successfully leveraged this technology to overcome the aforementioned challenges. In this review, we focus on the application of data science and AI technology in three areas, including risk prediction and identification of causal single-nucleotide polymorphisms, EHR-based phenotyping and CRISPR guide RNA design. Additionally, we highlight a few emerging AI technologies, such as transfer learning and multi-view learning, which will or have started to benefit genomic studies.
Subject(s)
Artificial Intelligence , Data Science , Genome-Wide Association Study , Genomics , TechnologyABSTRACT
Background: Vitiligo is a pigmentary skin disorder characterised by a chronic and progressive loss of melanocytes. Although several theories have been suggested to the pathogenesis of vitiligo, an autoimmune process leading to melanocyte destruction appears most likely. Human leukocyte antigen-G is a non-classic, major histocompatibility complex Class I molecule that plays an important role in the suppression of the immune response. Several recent studies have provided evidences that polymorphisms in the human leukocyte antigen-G gene might be related with autoimmune diseases. Objectives: The aim of this study was to decide whether exonic single nucleotide polymorphisms in human leukocyte antigen-G contribute to the risk of developing non-segmental vitiligo in the Korean population. Methods: To evaluate the associations between exonic single nucleotide polymorphisms (rs1630223 [Ala5Ala] and rs12722477 [Leu134Ile]) of human leukocyte antigen-G and vitiligo, 244 patients with vitiligo and 398 healthy controls were recruited. Genotyping was performed using Fluidigm 192.24 Dynamic Array with EP1 (Fluidigm Corp., CA). The SNP type assay (Fluidigm Corp., CA), which employs allele-specifically designed fluorescences (FAM or VIC) primers and a common reverse primer was applied and the data were analysed using the EP1 single nucleotide polymorphisms genotyping analysis software to obtain genotype calls. Results: Two exonic single nucleotide polymorphisms (rs1630223 and rs12722477) exhibited significant associations with susceptibility and remained a statistically significant association following Bonferroni correction. These two single nucleotide polymorphisms were located within a block of linkage disequilibrium. Haplotypes G-C and A-A comprising rs1630223 and rs12722477 demonstrated a significant association with non-segmental vitiligo. Limitations: The protein expression level of patients with vitiligo and controls was not studied and a replication study of the genetic association in an independent group was not managed. Conclusion: Our results suggest that exonic human leukocyte antigen-G polymorphisms (rs1630223 and rs12722477) are associated with the development of non-segmental vitiligo.