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Abstract The incidences of periodontitis and osteoporosis are rising worldwide. Observational studies have shown that periodontitis is associated with increased risk of osteoporosis. We performed a Mendelian randomization (MR) study to genetically investigate the causality of periodontitis on osteoporosis. We explored the causal effect of periodontitis on osteoporosis by MR analysis. A total of 9 single nucleotide polymorphisms (SNP) were related to periodontitis. The primary approach in this MR analysis was the inverse variance-weighted (IVW) method. Simple median, weighted median, and penalized weighted median were used to analyze sensitivity. The fixed-effect IVW model and random-effect IVW model showed no significant causal effect of genetically predicted periodontitis on the risk of osteoporosis (OR=1.032; 95%CI: 0.923-1.153; P=0.574; OR=1.032; 95%CI: 0.920-1.158; P=0.588, respectively). Similar results were observed in simple mode (OR=1.031; 95%CI: 0.780-1.361, P=0.835), weighted mode (OR=1.120; 95%CI: 0.944-1.328, P=0.229), simple median (OR=1.003; 95%CI: 0.839-1.197, P=0.977), weighted median (OR=1.078; 95%CI: 0.921-1.262, P=0.346), penalized weight median (OR 1.078; 95%CI: 0.919-1.264, P=0.351), and MR-Egger method (OR=1.360; 95%CI: 0.998-1.853, P=0.092). There was no heterogeneity in the IVW and MR-Egger analyses (Q=7.454, P=0.489 and Q=3.901, P=0.791, respectively). MR-Egger regression revealed no evidence of a pleiotropic influence through genetic variants (intercept: -0.004; P=0.101). The leave-one-out sensitivity analysis indicated no driven influence of any individual SNP on the association between periodontitis and osteoporosis. The Mendelian randomization analysis did not show a significant detrimental effect of periodontitis on the risk of osteoporosis.
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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:In recent years,epidemiological studies have shown that sleep patterns are risk factors for osteoarthritis,but the causal relationship between sleep characteristics and osteoarthritis remains unknown. OBJECTIVE:To investigate the causal relationship between seven sleep phenotypes and osteoarthritis,thereby providing a theoretical foundation for clinical prevention and intervention of osteoarthritis. METHODS:Seven sleep-related features,namely sleep duration,wake-up time,daytime napping,morning/evening preference,snoring,insomnia,and hypersomnia,were selected from published genome-wide association studies.Instrumental variables for these sleep-related features were extracted.Instrumental variables for knee osteoarthritis and hip osteoarthritis were obtained from publicly available genome-wide association studies.Causal relationships between sleep characteristics and outcome risks were evaluated using two-sample and multivariable Mendelian randomization analyses.The inverse variance weighted method was employed as the primary Mendelian randomization approach.Various methods,including weighted median,weighted mode,Mendelian randomization-Egger regression,Mendelian randomization pleiotropy-residual sum and outlier,were utilized to detect and correct for the presence of pleiotropy. RESULTS AND CONCLUSION:The results of the inverse variance-weighted method in the two-sample Mendelian randomization study revealed a detrimental causal association between the duration of sleep and the incidence risk of knee osteoarthritis[odds ratio(OR)=0.621,95%confidence interval(CI):0.470-0.822,P=0.001].Concurrently,insomnia displayed a positive causal connection with hip osteoarthritis risk(OR=2.016,95%CI:1.249-3.254,P=0.005).Sensitivity analysis affirmed the robustness of these causal relationships,and Mendelian randomization-Egger intercept analysis found no evidence of potential horizontal pleiotropy(knee osteoarthritis:P=0.468,hip osteoarthritis:P=0.551).Moreover,the results from the multivariable Mendelian randomization analysis showed that the causal association between insomnia and hip osteoarthritis lacked statistical significance(P=0.715).In contrast,sleep duration exhibited a direct negative causal relationship with the incidence risk of knee osteoarthritis(OR=0.526,95%CI:0.336-0.824,P=0.005).Reverse Mendelian randomization analysis indicated that knee osteoarthritis did not influence sleep duration(P=0.757).These findings indicate a negative correlation between sleep duration and incidence risk of knee osteoarthritis,suggesting that correcting insufficient sleep might mitigate the incidence risk of knee osteoarthritis.
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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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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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Sleep has attracted extensive attention due to its significance in health. However, its association with erectile dysfunction (ED) is insufficiently investigated. To investigate the potential causal links between sleep traits (insomnia, sleep duration, and chronotype) and ED, this study was performed. The single-nucleotide polymorphisms (SNPs) associated with insomnia, sleep duration, and chronotype were retrieved from previous genome-wide association studies (GWAS). A conventional two-sample Mendelian randomization (MR) was used to estimate the causal links between sleep traits and ED. The summary statistics of ED were from individuals of European ancestry (6175 cases vs 217 630 controls). As shown by the random effect inverse-variance-weighting (IVW) estimator, genetically predicted insomnia was causally associated with a 1.15-fold risk of ED (95% confidence interval: 1.07-1.23, P < 0.001). Sleep duration and morningness were not causally associated with ED, as indicated by the IVW (all P > 0.05). These findings were consistent with the results of sensitivity analyses. Based on genetic data, this study provides causal evidence that genetically predicted insomnia increases the risk of ED, whereas sleep duration and chronotype do not.
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Masculino , Humanos , Distúrbios do Início e da Manutenção do Sono/genética , Estudo de Associação Genômica Ampla , Disfunção Erétil/genética , Sono/genética , Fenótipo , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Prostate cancer is the second most common cancer in men worldwide. There are many occupational factors that have been suggested to cause prostate cancer. Our aim was to evaluate the evidence for causality by a literature review of occupational factors. We searched literature in Medline and SCOPUS from 1966 to June 30, 2015 to identify occupational risk factors for prostate cancer. The following risk factors were selected: farmers/agricultural workers, pesticides – whole group, and separately organophosphate and organochlorine pesticides, carbamates and triazines, cadmium, chromium, cutting fluids, acrylonitrile, rubber manufacturing, whole body vibration, shift work, flight personnel, ionizing radiation, and occupational physical activity. For each factor a literature search was performed and presented as meta-analysis of relative risk and heterogeneity (Q and I² index). A total of 168 original studies met the inclusion criteria with 90,688 prostate cancer cases. Significantly increased risks were observed for the following occupational exposures: pesticides (metaRR = 1.15, 95% confidence interval [CI] = 1.01–1.32; I² = 84%), and specifically group of organochlorine pesticides (meta relative risk [metaRR] = 1.08, 95% CI = 1.03–1.14; I² = 0%), chromium (metaRR = 1.19, 95% CI = 1.07–1.34; I² = 31%), shift work (metaRR = 1.25, 95% CI = 1.05–1.49; I² = 78%) and pilots (metaRR = 1.41, 95% CI = 1.02–1.94; I² = 63%) and occupational physical activity in cohort studies (metaRR = 0.87, 95% CI = 0.81–0.94; I² = 0%). The literature review supports a causal association for a few of the previously suggested factors.
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Humanos , Masculino , Acrilonitrila , Cádmio , Carbamatos , Cromo , Estudos de Coortes , Estudos Epidemiológicos , Atividade Motora , Exposição Ocupacional , Praguicidas , Características da População , Próstata , Neoplasias da Próstata , Radiação Ionizante , Fatores de Risco , Borracha , Triazinas , VibraçãoRESUMO
The purpose of this review is to discuss the debate concerning the interpretation of epidemiologic studies on particles and health effects. Study of the 1952 air pollution disaster in London established that very high levels of particulate-based smog can cause dramatic increases in daily mortality. However, recent epidemiologic studies have reported statistically significant health effects and mortality due to low levels of air pollution. The statistical significance does not prove causation in observational studies; therefore it is necessary to evaluate these associations. There are arguments for and against each of the numerous studies using Hill's criteria, however the body of accepted evidence supports the causal association. In particular, a high level of consistency in the estimated effect of PM10 has been observed across studies worldwide. The mechanism of the relationship between air pollution and health effects is not obvious. The mechanism of particle-induced injury may involve the production of an inflammatory response by the particulate. The harvesting and the threshold effect are also major concerns regarding the health effects of air pollution. However, current epidemiologic findings indicate that linear models lacking a threshold are appropriate for assessing the effect of particulate air pollution on daily mortality even at current levels.