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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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Objective To explore the causal association between gut microbes and non-alcoholic fatty liver disease(NAFLD)by Mendelian randomisation analysis.Methods Genetic instrumental variables for gut microbiota were identified from a gene-wide association study of 18 340 participants,and summary statistics for NAFLD were ob-tained from the FinnGen database,which provided data on 894 NAFLD cases and 217 898 controls using the IVW method as the primary analysis.In order to test the robustness of the results,MR-Egger method,WM method,Simple Mode method,Weighted Mode method were used for Mendelian randomisation analysis,and heterogeneity test,sensitivity analysis,and multiplicity analysis were performed.Results class Gammaproteobacteria IVW re-sults showed(OR=0.621,95％CI=0.412～0.934,P=0.022);family Enterobacteriaceae IVW results showed(OR=1.481,95％CI=1.069～2.053,P=0.018);genus Lachnospiraceae IVW results showed(OR=1.405,95％CI=1.036～1.904,P=0.029);genus Prevotella7 IVW results showed(OR=0.834,95％CI=0.714～0.974,P=0.021);genus Prevotella9 IVW results showed(OR=1.251,95％CI=1.025～1.527,P=0.027);order Desulfovibrionales IVW results showed(OR=0.714,95％CI=0.519～0.982,P=0.038);or-der Enterobacteriales IVW results showed(OR=1.481,95％CI=1.069～2.053,P=0.018).And there was no heterogeneity in the heterogeneity test,and the sensitivity analyses all showed robustness and no pleiotropy was found.Conclusion This study implicates class Gammaproteobacteria,family Enterobacteriaceae,genus Lachno-spiraceae,genus Prevotella7,genus Prevotella9,order Desulfovibrionales,order Enterobacteriales seven species of gut microorganisms have a causal relationship with NAFLD.
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Objective:To explore the robust relationship between insomnia and type 2 diabetes mellitus by two-sample Mendelian randomization analysis to overcome confounding factors and reverse causality in observational studies.Methods:We identified strong,independent single nucleotide polymorphisms(SNPs)of insomnia from the most up to date genome wide association studies(GWAS)within European ancestors and applied them as instrumental variable to GWAS of type 2 diabetes mellitus.After excluding SNPs that were significantly associated with smoking,physical activity,alcohol consumption,educational attainment,obesity,or type 2 diabetes mellitus,we assessed the impact of insomnia on type 2 diabetes mellitus using inverse variance weighting(IVW)method.Weighted median and MR-Egger regression analysis were also conducted to test the robustness of the association.We calculated the F statistic of the selected SNPs to test the applicability of instrumental variable and F statistic over than ten indicated that there was little possibility of bias of weak instrumental variables.We further examined the existence of pleiotropy by testing whether the intercept term in MR-Egger regression was significantly different from ze-ro.In addition,the leave-one-out method was used for sensitivity analysis to verify the stability and relia-bility of the results.Results:We selected 248 SNPs independently associated with insomnia at the genome-wide level(P＜5 ×10-8)as a preliminary candidate set of instrumental variables.After clum-ping based on the reference panel from 1000 Genome Project and removing the potential pleiotropic SNPs,a total of 167 SNPs associated with insomnia were included as final instrumental variables.The F statistic of this study was 39.74,which was in line with the relevance assumption of Mendelian randomi-zation.IVW method showed insomnia was associated with higher risk of type 2 diabetes mellitus that po-pulation with insomnia were 1.14 times more likely to develop type 2 diabetes mellitus than those without insomnia(95％CI:1.09-1.21,P＜0.001).The weighted median estimator(WME)method and MR-Egger regression showed similar causal effect of insomnia on type 2 diabetes mellitus.And MR-Egger re-gression also showed that the effect was less likely to be triggered by pleiotropy.Sensitivity analyses pro-duced directionally similar estimates.Conclusion:Insomnia is a risk factor of type 2 diabetes mellitus,which has positively effects on type 2 diabetes mellitus.Our study provides further rationale for indivi-duals at risk for diabetes to keep healthy lifestyle.
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Objective To investigate whether chemokine CCL2(also known as monocyte chemotactic protein 1 or MCP-1)has a causal relationship with lung cancer.Methods Genetic data of chemokine CCL2 and different pathological subtypes of lung cancer were extracted from genome-wide association studies(GWAS),and inverse-variance weighted(IVW)analysis was used as main analysis,while weighted median,simple model,MR-Egger regression,and weighted model were chosen as supplementary analyses.Sensitivity analyses were performed to verify the reliability of the data.Results The result of IVW analysis on chemokine CCL2 to lung adenocarcinoma was OR = 1.065,95%CI(0.919～1.234),P = 0.401.The result of IVW analysis on chemokine CCL2 to squamous cell lung carcinoma was OR = 1.059,95%CI(0.931～1.205),P = 0.381.The result of IVW analysis on chemokine CCL2 to small cell lung carcinoma was OR = 0.959,95%CI(0.760～1.208),P = 0.720.Conclusions There is no direct causal relationship between chemokine CCL2 and lung cancer.
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Objective To investigate assess the bidirectional causal relationship between ulcerative colitis(UC)and hypothyroidism using a two-sample Mendelian randomization(TSMR).Methods Single nucleotide polymorphism(SNP)data relevant to UC and hypothyroidism were retrieved from the Finnish Biobank and the IEU database,respectively.Independent SNPs strongly associated with UC were selected as instrumental variables.Causal associations between UC and hypothyroidism were evaluated using the inverse variance weighted(IVW)method,MR-Egger regression,and weighted median estimator.Additionally,MR-PRESSO was employed to assess the hori-zontal pleiotropy and outlier SNPs.Cochran's Q test and funnel plots were performed to evaluate the heterogeneity among the SNPs.A leave-one-out analysis was conducted to examine the influence of individual SNPs on causal assessments.Results Four instrumental variables strongly associated with UC were identified.The IVW method indicated a causal relationship between UC and hypothyroidism(OR = 0.975,95%CI:0.924～0.990,P = 0.011).Cochran's Q test yielded a Q statistic of 2.566 with a p-value of 0.463,suggesting no heterogeneity among the SNPs.Both MR-Egger(P = 0.523)and MR-PRESSO(P = 0.548)tests suggested the absence of horizontal pleiotropy.However,the results of the reverse TSMR did not support a reverse causal relationship.Conclusion The findings from the TSMR analysis reveal a negative causal relationship between UC and hypothyroidism.
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BACKGROUND:Osteoporosis is often accompanied by sarcopenia and an increased risk of fractures from falls.Recent studies have indicated a close relationship between lipid metabolism and sarcopenia.Abnormal lipid metabolism may directly impact muscle physiological function and metabolism. OBJECTIVE:To investigate the relationship between lipid metabolism and sarcopenia and evaluate their causal relationship using Mendelian randomization. METHODS:Mendelian randomization was used to explore the causal relationship between low-density lipoprotein cholesterol,high-density lipoprotein cholesterol,triglycerides,and muscle mass.Research data from genome-wide association studies were used and a sensitivity analysis was conducted to verify the reliability of the results.Approximate indicators of muscle mass,including trunk lean mass and appendicular lean mass,were used as outcome measures. RESULTS AND CONCLUSION:The study found a negative correlation of low-density lipoprotein cholesterol and triglycerides with muscle mass,while no correlation was observed between high-density lipoprotein cholesterol and muscle mass.The results of the sensitivity analysis indicated a robust causal relationship.Using Mendelian randomization,this study provides evidence of a causal relationship between low-density lipoprotein cholesterol and triglycerides and muscle mass.This finding deepens our understanding of the effects of lipids on sarcopenia and has important clinical implications for the prevention and treatment of sarcopenia and 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: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:Clinical evidences have suggested a correlation between metabolic factors and sarcopenia.Blood metabolites have been found as biological factors underlying the mechanisms of musculoskeletal disorders.However,the causal relationship between blood metabolites and sarcopenia is unclear. OBJECTIVE:To explore the causal relationship between blood metabolites and sarcopenia-related traits through a two-sample Mendelian randomization analysis and to analyze their metabolic pathways. METHODS:A dataset of 486 blood metabolites and sarcopenia-related traits was obtained from public databases.The inverse variance weighting,MR-Egger and weighted median methods were used to assess the causal relationship of blood metabolites with muscle mass and strength across genders.Sensitivity analyses,including heterogeneity and gene pleiotropy,were performed to explore the robustness of the results.Metabolic pathway analysis of potential causal relationships was performed using the Metaboanayst 5.0 tool. RESULTS AND CONCLUSION:A total of 124 metabolites and sarcopenia-related traits were observed to have potential causal relationships(P<0.05).Mannose and 1-arachidonoylglycerophosphocholine were significantly causally associated with an increased muscle mass in males(P<1.03×10-4).Pentadecanoate and glycine were significantly causally associated with decreased muscle mass and muscle strength in females,respectively(P<1.03×10-4).Metabolic pathway analysis identified eight metabolic pathways associated with altered levels of muscle mass and muscle strength in sarcopenia,including the"glyoxylate and dicarboxylate metabolism"and"Glycine,serine and threonine metabolism."The identified metabolites are considered as useful circulating metabolic biomarkers for screening and prevention of sarcopenia in clinical practice,serving as candidate molecules for future mechanistic exploration and drug target selection.
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BACKGROUND:Rheumatoid arthritis is a chronic systemic autoimmune disease.It is important to study the immunological changes involved in it for diagnosis and treatment. OBJECTIVE:To identify immune-related biomarkers associated with rheumatoid arthritis utilizing bioinformatics techniques and examine alterations in immune cell infiltration as well as the relationship between immune cells and biomarkers. METHODS:Differential expression analysis was used to identify the immune-related genes that were up-regulated in rheumatoid arthritis based on the GEO and Immport databases.Kyoto encyclopedia of genes and genomes(KEGG)and gene ontology(GO)enrichment analyses were used to investigate the possible function of these elevated genes.The immunological characteristic genes associated with rheumatoid arthritis were screened using least absolute shrinkage and selection operator(Lasso)and support vector machine recursive feature elimination(SVM-RFE).Independent datasets were used for difference validation,and the diagnostic performance was evaluated by plotting receiver operating characteristic curves for feature genes.Immune cell infiltration was used to analyze the differential profile of immune cells in rheumatoid arthritis and the correlation between the characterized genes and immune cells.In order to ascertain the causal relationship between monocytes and rheumatoid arthritis in immune cells,Mendelian randomization analysis was ultimately employed. RESULTS AND CONCLUSION:There were 39 upregulated differentially expressed genes in rheumatoid arthritis.The genes were primarily enriched in chemotaxis,cytokine activity,and immune receptor activity,according to GO enrichment analysis,while kEGG enrichment analysis revealed that the genes were considerably enriched in the tumor necrosis factor signaling pathway and peripheral leukocyte migration.Lasso and SVM-RFE identified five feature genes:CXCL13,SDC1,IGLC1,PLXNC1,and SLC29A3.Independent dataset validation of the feature genes found them to be similarly highly expressed in rheumatoid arthritis samples,with area under the curve values greater than 0.8 for all five feature genes in both datasets.Immune cell infiltration indicated that most immune cells,including natural killer cells and monocytes,exhibited increased levels of infiltration in rheumatoid arthritis samples.The correlation analysis revealed a significant positive correlation between memory B cells and immature B cells and these five feature genes.Correlation analysis showed that the five feature genes were positively correlated with memory B cells and immature B cells.The inverse variance weighting method revealed that monocytes were associated with the risk of developing rheumatoid arthritis.
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BACKGROUND:Numerous clinical studies have suggested a close relationship between obesity and osteoporosis,but whether there is a genetic causal effect between obesity and osteoporosis remains unclear. OBJECTIVE:To explore the association between obesity and osteoporosis using summary data from a large-scale genome-wide association study(GWAS)through Mendelian randomization analysis. METHODS:Obesity data were derived from summary statistics of the Genetic Investigation of Anthropometric Traits(GIANT)and the UK Biobank(UKBB).Osteoporosis data were obtained from the Genetic Factors for Osteoporosis(GeFOS)consortium,including two bone density phenotypes:total body bone mineral density(BMD)and heel BMD.The inverse variance-weighted method was the primary analysis,with the Mendelian randomization method based on Egger regression(MR-Egger)and weighted median method as supplementary approaches to calculate the causal association between genetic variations related to obesity and osteoporosis.Sensitivity analyses were conducted to validate the reliability of the results.Heterogeneity was assessed using Cochran's Q test.Horizontal pleiotropy was assessed through the MR-Egger intercept test.Leave-one-out analysis was performed to evaluate the potential influence of single nucleotide polymorphisms on the combined inverse variance-weighted estimates. RESULTS AND CONCLUSION:(1)Impact of obesity on osteoporosis:In addition to body mass index and forearm BMD,body mass index,waist-to-hip ratio,body mass index-adjusted waist-to-hip ratio,and whole-body body mass index,heel BMD,forearm BMD,lumbar spine BMD,and femoral neck BMD were causally related to each other.Further Meta-analysis revealed that obesity increased the risk of BMD(odds ratio=1.07,95%confidence interval:1.03-1.12,P<0.01).(2)Impact of osteoporosis on obesity:Apart from arm BMD and lumbar spine BMD as exposure factors showing causal relationships with obesity,other datasets indicated no causal effect between total body BMD,heel BMD,femoral neck BMD,and obesity.Additional meta-analysis demonstrated that BMD did not increase the risk of obesity(odds rate=0.99,95%confidence interval:0.98-1.01,P<0.01).There is a causal relationship between obesity and osteoporosis,suggesting that obesity may be a risk factor for osteoporosis.However,no causal association is found between osteoporosis and obesity.
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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: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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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:Multiple clinical observational studies have suggested a close relationship of serum trace elements and nutrients with osteonecrosis,but it remains unclear whether there is a genetic causal effect between serum trace elements and nutrients on osteonecrosis. OBJECTIVE:To investigate the causal effects of serum trace elements and nutrients on osteonecrosis using the Mendelian randomization approach. METHODS:The exposure factors of serum trace elements and vitamins with mononucleotide polymorphisms were obtained from the published UK Biobank database and publicly available databases of genome-wide association studies.The outcome event of osteonecrosis was derived from the FinnGen Biobank database.Mendelian randomization methods were employed to explore the causal relationship between seven trace elements and three nutrients with osteonecrosis.Causal inference was conducted using inverse variance weighting,MR-Egger,and weighted median methods.F-statistic was calculated to ensure the robustness of instrumental variables.Cochran's Q test and leave-one-out method were used for heterogeneity testing.MR-Egger regression and MR-PRESSO were employed for horizontal pleiotropy testing.PhenoScanner database was utilized to remove mononucleotide polymorphisms with horizontal pleiotropy to ensure the reliability of the results. RESULTS AND CONCLUSION:Causal relationships were found between serum selenium,phosphate,vitamin C,vitamin E,and osteonecrosis through Mendelian randomization analysis.Serum selenium,vitamin C,and vitamin E were found to have a protective effect on osteonecrosis,while excessive intake of phosphate increased the risk of osteonecrosis.No heterogeneity or horizontal pleiotropy was observed during the study,and Mendelian randomization statistical power(Power value>80%)indicated the reliability of the aforementioned four results.These findings have important clinical implications for the development of targeted preventive and therapeutic measures for osteonecrosis.
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BACKGROUND:Epidemiologic studies have shown a correlation between type 2 diabetes mellitus and bone mineral density,but the causal association between the two and whether it is age-related remains unknown. OBJECTIVE:To study the correlation between type 2 diabetes mellitus and whole body bone mineral density at unspecified age and at all ages based on the Mendelian randomization technique. METHODS:The genome-wide association study(GWAS)data of type 2 diabetes mellitus and bone mineral density at all ages were selected from the IEU GWAS database of the University of Bristol.The exposure data were single nucleotide polymorphisms with significant correlation with type 2 diabetes mellitus as instrumental variables,and bone mineral density at all ages was selected as the outcome variable.Two-sample Mendelian randomization analysis of type 2 diabetes mellitus and bone mineral density was performed using inverse variance weighted method,weighted median estimator,and MR-Egger regression.The βvalue was used to evaluate the causal relationship between type 2 diabetes mellitus and bone mineral density at all ages. RESULTS AND CONCLUSION:A total of 118 single nucleotide polymorphisms were extracted from the GWAS summary data as instrumental variables.The MR-Egger regression results showed that there was no horizontal pleiotropy,but there was heterogeneity.Therefore,this study was based on the inverse variance weighted results.Inverse variance weighted results showed that type 2 diabetes mellitus may be a potential protective factor for bone mineral density and is associated with age:age-unspecified bone mineral density[β=0.038,95%confidence interval(CI):1.01-1.07,P=0.002],bone mineral density over 60 years old(β=0.052,95%CI:1.01-1.09,P=0.027),bone mineral density between 45-60 years old(β=0.049,95%CI:1.01-1.09,P=0.009),bone mineral density between 30-45 years old(β=0.033,95%CI:0.99-1.07,P=0.127).bone mineral density of 15-30 years old(β=0.025,95%CI:0.95-1.10,P=0.506),bone mineral density of 0-15 years old(β=0.006,95%CI:0.96-1.04,P=0.716).Similar results were obtained from the MR-Egger regression and weighted median estimator analyses.These findings indicate that type 2 diabetes mellitus may be one of the protective factors of bone mineral density,and there is a correlation with age.
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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 analyze the causal relationship between obesity and central retinal artery occlusion(CRAO)based on body mass index(BMI),which is commonly used to measure obesity,and Mendelian randomization(MR)method.Methods Two-sample MR analysis was performed using summary statistics from genome-wide associa-tion studies.Exposed genetic tools were divided into the men group(n=60 586,SNP=2 736 876,European men)and women group(n=171 977,SNP=2 494 613,European women);CRAO was selected as the outcome.The instrumental variable for BMI came from the Integrative Epidemiology Unit(IEU)publicly available data;the outcome CRAO data came from the FinnGen database.Inverse variance weighting(IVW)and weighted median(WM)were used to analyze the poten-tial relationship between BMI and CRAO.Results IVW showed that the increased BMI level significantly increased the risk of CRAO in men[OR=4.57,95％CI:1.32-15.82,P=0.016]and the risk of CRAO in women[OR=3.48,95％CI:1.40-8.63,P=0.007].Meanwhile,the WM and MR-Egger analysis results supported the above conclusions.In addition,there was no heterogeneity or pleiotropy in the results of this study.Conclusion The increase in BMI is positively corre-lated with the occurrence of CRAO.This study provides an effective CRAO prevention strategy for asymptomatic patients with elevated BMI levels.
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Objective:To investigate the relationship between body mass index (BMI) and gestational hypertension using two-sample Mendelian randomization analysis.Methods:The summary level data for BMI and gestational hypertension were obtained from the genome-wide association study (the deadline for data inclusion was October 31, 2023). All data were analyzed by inverse variance weighting, MR-Egger regression, weighted median, simple model and weighted model methods. Cochrane Q test was used to evaluate heterogeneity, MR-Egger regression intercept test and funnel plot were used to assess horizontal pleiotropy. Results:Inverse variance weighting result under fixed effects and random effects models showed that the risk of gestational hypertension increased with the increase of BMI ( OR = 1.62 and 1.62, 95% CI 1.39 to 1.88 and 1.39 to 1.88, P<0.01). Sensitivity analysis results including MR-Egger regression, weighted median and weighted model methods showed that BMI increased the risk of gestational hypertension ( OR = 1.51, 1.56 and 1.71; 95% CI 1.01 to 2.26, 1.23 to 1.99 and 1.09 to 2.69; P<0.05 or <0.01). Although Cochrane Q test result showed evidence of heterogeneity ( P = 0.04), inverse variance weighting under a random model suggested that BMI increased the risk of gestational hypertension. Horizontal pleiotropy was not observed in the above analysis ( P = 0.73). Conclusions:Obesity may increase the risk of gestational hypertension. Pregnant women should pay attention to weight control to decrease the risk of gestational hypertension.