Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods ...Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.展开更多
Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the...Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the mutual influences between gut microbiota and insomnia.Methods We conducted Mendelian randomisation(MR)analysis using genome-wide association studies datasets on insomnia(N=386533),gut microbiota data from the MiBioGen alliance(N=18340)and the Dutch Microbiome Project(N=8208).The inverse variance weighted(IVW)technique was selected as the primary approach.Then,Cochrane’s Q,Mendelian randomization-Egger(MR-Egger)and MR Pleiotropy RESidual Sum and Outlier test(MRPRESSO)tests were used to detect heterogeneity and pleiotropy.The leave-one-out method was used to test the stability of the MR results.In addition,we performed the Steiger test to thoroughly verify the causation.Results According to IVW,our results showed that 14 gut bacterial taxa may contribute to the risks of insomnia(odds ratio(OR):1.01 to 1.04),while 8 gut bacterial taxa displayed a protective effect on this condition(OR:0.97 to 0.99).Conversely,reverse MR analysis showed that insomnia may causally decrease the abundance of 7 taxa(OR:0.21 to 0.57)and increase the abundance of 12 taxa(OR:1.65 to 4.43).Notably,the genus Odoribacter showed a significant positive causal relationship after conducting the Steiger test.Cochrane’s Q test indicated no significant heterogeneity between most singlenucleotide polymorphisms.In addition,no significant level of pleiotropy was found according to MR-Egger and MRPRESSO.Conclusions Our study highlighted the reciprocal relationships between gut microbiota and insomnia,which may provide new insights into the treatment and prevention of insomnia.展开更多
To the Editor:Lymphomas,classified as hematological malignancies(HMs),[1,2]continue to pose significant challenges to public health.Although gut microbiota is widely connected with lymphoma via several plausible mecha...To the Editor:Lymphomas,classified as hematological malignancies(HMs),[1,2]continue to pose significant challenges to public health.Although gut microbiota is widely connected with lymphoma via several plausible mechanisms,[1–4]the causality and directionality of this relationship are not fully understood.Therefore,a bidirectional multivariable Mendelian randomization(MR)study design was adopted to establish a robust causal relationship between gut microbiota and the development of lymphomas.展开更多
Hypertrophic cardiomyopathy(HCM)is a prevalent inherited cardiac condition,affecting approximately 1 in 500 in-dividuals.^(1)Recent research highlights immune cell involve-ment in HCM,with altered levels of various im...Hypertrophic cardiomyopathy(HCM)is a prevalent inherited cardiac condition,affecting approximately 1 in 500 in-dividuals.^(1)Recent research highlights immune cell involve-ment in HCM,with altered levels of various immune populations associated with the disease.^(2)However,whether these changes are causative or merely correlational is still uncertain.This study aims to investigate the causal effects of 731 immune cell types on HCM using comprehensive bidi-rectional Mendelian randomization(MR).展开更多
Objective:Mendelian randomization(MR)has been widely utilized for causal inference between diseases,and its implementation within the domain of traditional Chinese medicine(TCM)is considered feasible.Although previous...Objective:Mendelian randomization(MR)has been widely utilized for causal inference between diseases,and its implementation within the domain of traditional Chinese medicine(TCM)is considered feasible.Although previous clinical and epidemiological studies have demonstrated a close relationship between insomnia and depression,the inherent genetic factors underlying these associations are unclear.The aim of this study was to evaluate the causal relationship between depression and insomnia via bidirectional 2-sample MR and increase the understanding of the TCM theory of treating different diseases with the same method,particularly in the context of comorbid depression and insomnia.Methods:Genetic data related to depression and insomnia were extracted from published genome-wide association studies(GWAS)data sets.Single-nucleotide polymorphisms(SNPs)associated with depression and insomnia were used as instrumental variables to construct an“SNP-exposure-outcome”model.Bidirectional 2-sample MR analysis was conducted via inverse-variance weighted(IVW),weighted median,MR Egger regression,simple mode,and weighted mode methods.Furthermore,heterogeneity tests,pleiotropy analyses,and sensitivity analyses were performed.Results:The MR results revealed a causal relationship between depression and an increased risk of developing insomnia(IVW,OR=1.400,95%CI:1.246–1.573,P<0.001),and a causal relationship between insomnia and an increased risk of developing depression(IVW,OR=1.204,95%CI:1.144–1.266,P<0.001).Conclusions:There is a bidirectional causal relationship between depression and insomnia.These findings provide new theoretical support for the TCM approach of treating different diseases with the same method in the prevention and treatment of depression and insomnia and provide a scientific basis for the modernization of TCM.展开更多
Primary dysmenorrhea(PDM)is a common cyclic menstrual pain that significantly affects the quality of life for women.Several epidemiological studies have suggested a potential association between PDM and mental health ...Primary dysmenorrhea(PDM)is a common cyclic menstrual pain that significantly affects the quality of life for women.Several epidemiological studies have suggested a potential association between PDM and mental health traits,including stress,depression,and anxiety.However,there is a lack of systematic investigation into whether a causal relationship exists between PDM and mental health phenotypes compared to other physical phenotypes.In this study,we conducted a large-scale phenome study on a cohort of 7401 young female Chinese college students to explore the association between PDM and various physical and mental health phenotypes.Using a multi-phenotype correlation network model,we discovered that the correlation between the PDM phenotypes and mental health phenotypes was the most dominant among the complex inter-connections across different categories of phenotypes.Furthermore,employing a two-sample Mendelian randomiza-tion analysis,we systematically elucidated the genomic-level impact of PDM on the mental health traits of young women.Specifically,we identified an increased risk of depression and anxiety associated with PDM,potentially influenced by several Single-nucleotide polymorphism(SNP)variants such as ZMIZ1,DIO1,GRIK4 and RBFOX1.This study offers valuable insights into the genetic mechanism through which dysmenorrhea impacts mental health,which contributes to a better understanding of the comprehensive management of PDM and its associated psychological challenges.展开更多
Background:Prostate cancer(PCa)patients are at risk of developing second primary malignancies(SPMs),which can significantly shorten their survival.Understanding the risk of SPMs and associated factors is crucial to th...Background:Prostate cancer(PCa)patients are at risk of developing second primary malignancies(SPMs),which can significantly shorten their survival.Understanding the risk of SPMs and associated factors is crucial to the optimization of patient follow-up.Methods:This study focuses on PCa patients who were later diagnosed with SPMs using data from the Surveillance,Epidemiology,and End Results(SEER)database.Variables were carefully selected,and the data were analyzed using machine learning techniques combined with mul-tivariate Cox proportional hazards modeling.Subsequently,a nomogram was generated to predict the 1-,3-,and 5-year survival rates for SPMs patients.Additionally,a two-sample Mendelian randomization(TSMR)analysis was conducted to investigate the causal relationships between PCa and its top ten SPMs.Results:Among the variables,age,marital status,SPM site,M stage,American Joint Committee on Cancer(AJCC)stage,PCa surgery,and prostate-specific antigen(PSA)levels were identified as key prognostic factors through least absolute shrinkage and selection operator(LASSO)and backward stepwise regression.Based on these factors,a nomogram was developed to visually represent survival predictions,complemented by a web-based calculator for easy application.This nomogram,which serves as a supplement to traditional AJCC staging,demonstrated strong predictive power for 1-,3-,and 5-year survival,with area under the curve(AUC)values exceeding 0.85.Additionally,TSMR analysis revealed a causal link between PCa and urothelial carcinoma(UC).Conclusion:This study developed a nomogram for predicting survival in prostate cancer patients with secondary primary malignancies,enhancing prognosis accuracy.TSMR identified a causal link between PCa and UC.展开更多
Background and Aims:Accumulating evidence highlights the association between the gut microbiota and liver cirrhosis.However,the role of the gut microbiota in liver cirrhosis remains unclear.Methods:We first assessed t...Background and Aims:Accumulating evidence highlights the association between the gut microbiota and liver cirrhosis.However,the role of the gut microbiota in liver cirrhosis remains unclear.Methods:We first assessed the differences in the composition of the bacterial community between CCl4-induced liver cirrhosis and control mice using 16S rRNA sequencing.We then performed a two-sample Mendelian randomization(MR)analysis to reveal the underlying causal relationship between the gut microbiota and liver cirrhosis.Causal relationships were analyzed using primary inverse variance weighting(IVW)and other supplemental MR methods.Furthermore,fecal samples from liver cirrhosis patients and healthy controls were collected to validate the results of the MR analysis.Results:Analysis of 16S rRNA sequencing indicated significant differences in gut microbiota composition between the cirrhosis and control groups.IVW analyses suggested that Alphaproteobacteria,Bacillales,NB1n,Rhodospirillales,Dorea,Lachnospiraceae,and Rhodospirillaceae were positively correlated with the risk of liver cirrhosis,whereas Butyricicoccus,Hungatella,Marvinbryantia,and Lactobacillaceae displayed the opposite effects.However,the weighted median and MR-PRESSO estimates further showed that only Butyricicoccus and Marvinbryantia presented stable negative associations with liver cirrhosis.No significant heterogeneity or horizontal pleiotropy was observed in the sensitivity analysis.Furthermore,the result of 16S rRNA sequencing also showed that healthy controls had a higher relative abundance of Butyricicoccus and Marvinbryantia than liver cirrhosis patients.Conclusions:Our study provides new causal evidence for the link between gut microbiota and liver cirrhosis,which may contribute to the discovery of novel strategies to prevent liver cirrhosis.展开更多
基金supported by Natural Science Foundation of Shandong ProvinceChina[ZR2022MH115]the National Natural Science Foundation of China[81301479,82202593]。
文摘Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.
文摘Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the mutual influences between gut microbiota and insomnia.Methods We conducted Mendelian randomisation(MR)analysis using genome-wide association studies datasets on insomnia(N=386533),gut microbiota data from the MiBioGen alliance(N=18340)and the Dutch Microbiome Project(N=8208).The inverse variance weighted(IVW)technique was selected as the primary approach.Then,Cochrane’s Q,Mendelian randomization-Egger(MR-Egger)and MR Pleiotropy RESidual Sum and Outlier test(MRPRESSO)tests were used to detect heterogeneity and pleiotropy.The leave-one-out method was used to test the stability of the MR results.In addition,we performed the Steiger test to thoroughly verify the causation.Results According to IVW,our results showed that 14 gut bacterial taxa may contribute to the risks of insomnia(odds ratio(OR):1.01 to 1.04),while 8 gut bacterial taxa displayed a protective effect on this condition(OR:0.97 to 0.99).Conversely,reverse MR analysis showed that insomnia may causally decrease the abundance of 7 taxa(OR:0.21 to 0.57)and increase the abundance of 12 taxa(OR:1.65 to 4.43).Notably,the genus Odoribacter showed a significant positive causal relationship after conducting the Steiger test.Cochrane’s Q test indicated no significant heterogeneity between most singlenucleotide polymorphisms.In addition,no significant level of pleiotropy was found according to MR-Egger and MRPRESSO.Conclusions Our study highlighted the reciprocal relationships between gut microbiota and insomnia,which may provide new insights into the treatment and prevention of insomnia.
基金This work was supported by grants from the National Natural Science Foundation of China(No.82020108004)Chongqing Young and Middle-aged Medical High-end Talent Project(No.YXGD202467)Natural Science Foundation of Chongqing(No.CSTB2022NSCQ-MSX084).
文摘To the Editor:Lymphomas,classified as hematological malignancies(HMs),[1,2]continue to pose significant challenges to public health.Although gut microbiota is widely connected with lymphoma via several plausible mechanisms,[1–4]the causality and directionality of this relationship are not fully understood.Therefore,a bidirectional multivariable Mendelian randomization(MR)study design was adopted to establish a robust causal relationship between gut microbiota and the development of lymphomas.
基金supported by the Program for Youth Innovation in Future Medicine,Chongqing Medical University,Chongqing,China(No.W0168)the Natural Science Foundation of Chongqing,China(No.CSTB2022NSCQ-MSX0075)+1 种基金the Joint Project of Chongqing Health Commission and Science and Technology Bureau(China)(No.2025GDRC006)Chongqing Education Committee Grant(China)(No.KJQN202300480).
文摘Hypertrophic cardiomyopathy(HCM)is a prevalent inherited cardiac condition,affecting approximately 1 in 500 in-dividuals.^(1)Recent research highlights immune cell involve-ment in HCM,with altered levels of various immune populations associated with the disease.^(2)However,whether these changes are causative or merely correlational is still uncertain.This study aims to investigate the causal effects of 731 immune cell types on HCM using comprehensive bidi-rectional Mendelian randomization(MR).
基金supported by the China Academy of ChineseMedical Science(CACMS)Innovation Fund(No.CI2021A00603)the National Natural Science Foundation of China(No.82074299).
文摘Objective:Mendelian randomization(MR)has been widely utilized for causal inference between diseases,and its implementation within the domain of traditional Chinese medicine(TCM)is considered feasible.Although previous clinical and epidemiological studies have demonstrated a close relationship between insomnia and depression,the inherent genetic factors underlying these associations are unclear.The aim of this study was to evaluate the causal relationship between depression and insomnia via bidirectional 2-sample MR and increase the understanding of the TCM theory of treating different diseases with the same method,particularly in the context of comorbid depression and insomnia.Methods:Genetic data related to depression and insomnia were extracted from published genome-wide association studies(GWAS)data sets.Single-nucleotide polymorphisms(SNPs)associated with depression and insomnia were used as instrumental variables to construct an“SNP-exposure-outcome”model.Bidirectional 2-sample MR analysis was conducted via inverse-variance weighted(IVW),weighted median,MR Egger regression,simple mode,and weighted mode methods.Furthermore,heterogeneity tests,pleiotropy analyses,and sensitivity analyses were performed.Results:The MR results revealed a causal relationship between depression and an increased risk of developing insomnia(IVW,OR=1.400,95%CI:1.246–1.573,P<0.001),and a causal relationship between insomnia and an increased risk of developing depression(IVW,OR=1.204,95%CI:1.144–1.266,P<0.001).Conclusions:There is a bidirectional causal relationship between depression and insomnia.These findings provide new theoretical support for the TCM approach of treating different diseases with the same method in the prevention and treatment of depression and insomnia and provide a scientific basis for the modernization of TCM.
基金supported by the National Key R&D Program of China(2024YFA0916600)Shanghai Municipal Science and Technology Major Project,Natural Science Foundation of China(32070679,U1804284,32370724,82102669)+2 种基金Taishan Scholar Program of Shandong Province(tstp20240526)Natural Science Foundation of Shandong Province(ZR2019YQ14)the fundamental research funds for the central universities(23X010302406,YG2023QNB20,YG2021QN143).
文摘Primary dysmenorrhea(PDM)is a common cyclic menstrual pain that significantly affects the quality of life for women.Several epidemiological studies have suggested a potential association between PDM and mental health traits,including stress,depression,and anxiety.However,there is a lack of systematic investigation into whether a causal relationship exists between PDM and mental health phenotypes compared to other physical phenotypes.In this study,we conducted a large-scale phenome study on a cohort of 7401 young female Chinese college students to explore the association between PDM and various physical and mental health phenotypes.Using a multi-phenotype correlation network model,we discovered that the correlation between the PDM phenotypes and mental health phenotypes was the most dominant among the complex inter-connections across different categories of phenotypes.Furthermore,employing a two-sample Mendelian randomiza-tion analysis,we systematically elucidated the genomic-level impact of PDM on the mental health traits of young women.Specifically,we identified an increased risk of depression and anxiety associated with PDM,potentially influenced by several Single-nucleotide polymorphism(SNP)variants such as ZMIZ1,DIO1,GRIK4 and RBFOX1.This study offers valuable insights into the genetic mechanism through which dysmenorrhea impacts mental health,which contributes to a better understanding of the comprehensive management of PDM and its associated psychological challenges.
基金Student Innovation Capability Enhancement Program of Guangzhou Medical University,Grant/Award Numbers:2022 NO.67,2023 NO.7Special Funds for the Cultivation of Guangdong College Students'Scientific and Technological Innovation(“Climbing Program”Special Funds),Grant/Award Number:pdjh2023b0431。
文摘Background:Prostate cancer(PCa)patients are at risk of developing second primary malignancies(SPMs),which can significantly shorten their survival.Understanding the risk of SPMs and associated factors is crucial to the optimization of patient follow-up.Methods:This study focuses on PCa patients who were later diagnosed with SPMs using data from the Surveillance,Epidemiology,and End Results(SEER)database.Variables were carefully selected,and the data were analyzed using machine learning techniques combined with mul-tivariate Cox proportional hazards modeling.Subsequently,a nomogram was generated to predict the 1-,3-,and 5-year survival rates for SPMs patients.Additionally,a two-sample Mendelian randomization(TSMR)analysis was conducted to investigate the causal relationships between PCa and its top ten SPMs.Results:Among the variables,age,marital status,SPM site,M stage,American Joint Committee on Cancer(AJCC)stage,PCa surgery,and prostate-specific antigen(PSA)levels were identified as key prognostic factors through least absolute shrinkage and selection operator(LASSO)and backward stepwise regression.Based on these factors,a nomogram was developed to visually represent survival predictions,complemented by a web-based calculator for easy application.This nomogram,which serves as a supplement to traditional AJCC staging,demonstrated strong predictive power for 1-,3-,and 5-year survival,with area under the curve(AUC)values exceeding 0.85.Additionally,TSMR analysis revealed a causal link between PCa and urothelial carcinoma(UC).Conclusion:This study developed a nomogram for predicting survival in prostate cancer patients with secondary primary malignancies,enhancing prognosis accuracy.TSMR identified a causal link between PCa and UC.
基金supported by the Wuhan University Education&Development Foundation(2002330)the National Stem Cell Clinical Research Project of Chinathe Fundamental Research Funds for the Central Universities(2042022kf1115).
文摘Background and Aims:Accumulating evidence highlights the association between the gut microbiota and liver cirrhosis.However,the role of the gut microbiota in liver cirrhosis remains unclear.Methods:We first assessed the differences in the composition of the bacterial community between CCl4-induced liver cirrhosis and control mice using 16S rRNA sequencing.We then performed a two-sample Mendelian randomization(MR)analysis to reveal the underlying causal relationship between the gut microbiota and liver cirrhosis.Causal relationships were analyzed using primary inverse variance weighting(IVW)and other supplemental MR methods.Furthermore,fecal samples from liver cirrhosis patients and healthy controls were collected to validate the results of the MR analysis.Results:Analysis of 16S rRNA sequencing indicated significant differences in gut microbiota composition between the cirrhosis and control groups.IVW analyses suggested that Alphaproteobacteria,Bacillales,NB1n,Rhodospirillales,Dorea,Lachnospiraceae,and Rhodospirillaceae were positively correlated with the risk of liver cirrhosis,whereas Butyricicoccus,Hungatella,Marvinbryantia,and Lactobacillaceae displayed the opposite effects.However,the weighted median and MR-PRESSO estimates further showed that only Butyricicoccus and Marvinbryantia presented stable negative associations with liver cirrhosis.No significant heterogeneity or horizontal pleiotropy was observed in the sensitivity analysis.Furthermore,the result of 16S rRNA sequencing also showed that healthy controls had a higher relative abundance of Butyricicoccus and Marvinbryantia than liver cirrhosis patients.Conclusions:Our study provides new causal evidence for the link between gut microbiota and liver cirrhosis,which may contribute to the discovery of novel strategies to prevent liver cirrhosis.
