Objective To analyze the causal relationship between gut microbiota and tic disorder based on Mendelian randomization (MR). Methods A total of 196 known microbiota (9 phyla, 16 classes, 20 orders, 32 families, and 119 genera) in the human intestinal microbiota dataset downloaded from the MiBioGen database were selected as the exposure factors, and the dataset of tic disorder (finn-b-KRA_PSY_TIC) containing 172 patients and 218620 controls was downloaded from the genome-wide association study database as the outcome variable. Inverse variance weighted was used as the main analysis method, and the causal relationship between gut microbiota and tic disorder was evaluated using odds ratio (OR) and its 95% confidence interval (CI). Horizontal pleiotropy was tested by MR-Egger intercept and MR-PRESSO global test, heterogeneity was assessed by Cochran’s Q test, and sensitivity analysis was performed by leave-one-out method. Results Inverse variance weighted results showed that the Family Rhodospirillaceae [OR=0.398, 95%CI (0.191, 0.831), P=0.014], Order Rhodospirillales [OR=0.349, 95%CI (0.164, 0.743), P=0.006], and Parasutterella [OR=0.392, 95%CI (0.171, 0.898), P=0.027] had negative causal relationships with tic disorder. The Genus Lachnospira [OR=8.784, 95%CI (1.160, 66.496), P=0.035] and Candidatus Soleaferrea [OR=2.572, 95%CI (1.161, 5.695), P=0.020] had positive causal relationships with tic disorder. In addition, MR-Egger intercept and MR-PRESSO global test showed no horizontal pleiotropy, Cochran’s Q test showed no heterogeneity, and leave-one-out sensitivity analysis showed the results were stable. Conclusions A causal relationship exists between gut microbiota and tic disorder. The Family Rhodospirillaceae, Order Rhodospirillales, and Parasutterella are associated with a decreased risk of tic disorder, while the Genus Lachnospira and Candidatus Soleaverea can increase the risk of tic disorder.
ObjectiveThyroid nodules are an exceptionally common thyroid disorder. Past studies suggested a possible link between thyroid diseases and breast neoplasms. However, few studies have delved into the causal relationship between thyroid nodules and breast neoplasms. This study conducted a Mendelian randomization (MR) analysis to further investigate the causal relationship between them. MethodsThis study was conducted using data sourced from genome-wide association study (GWAS) summary datasets. The study focused on thyroid nodules, benign breast tumors, and malignant breast cancers as the research objects, and relevant single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs). The inverse-variance weighted (IVW) was primarily used to assess the causal relationship between thyroid nodules and breast neoplasms. Cochran’s Q test was employed to detect heterogeneity, while MR-Egger intercept and MR-PRESSO were used to test for pleiotropy. Sensitivity analysis was conducted using the leave-one-out method. ResultsThere was a significant causal relationship between thyroid nodules and malignant neoplasm of breast (OR=0.88, 95%CI 0.83 to 0.95, P<0.01), with no evidence of reverse causality between them (OR=1.01, 95%CI 0.99 to 1.03, P=0.16). No causal relationship was found between thyroid nodules and benign neoplasm of breast, as indicated by both forward MR analysis (OR=0.97, 95%CI 0.89 to 1.06, P=0.51) and reverse MR analysis (OR=0.97, 95%CI 0.92 to 1.04, P=0.40). Sensitivity analyses suggested that the study findings were accurate and reliable. ConclusionThe present study identifies thyroid nodules as a potential protective factor for malignant neoplasm of breast.
ObjectiveTo investigate the potential causal relationship between four types of reproductive behaviors and rheumatoid arthritis (RA), with the goal of establishing a theoretical foundation for clinical prevention and treatment strategies. MethodsPooled gene-wide association study (GWAS) data were obtained from large publicly searchable databases. Four characteristics like menarche, menopause, the age of first pregnancy and the age of last pregnancy, which related to reproductive behavior were selected as the exposure factors and RA as the outcome factors. Single nucleotide polymorphisms (SNPs), which were strongly correlated with the phenotype of the exposure factors, were screened as the instrumental variables, and two-sample Mendelian randomization analyses were used to assess the potential causal relationship between the exposure and the disease. Results① The Mendelian randomization analysis utilizing the inverse variance weighted method on two distinct samples revealed a significant negative correlation between the age of first pregnancy and last pregnancy with the risk of RA (OR=0.91, 95%CI 0.85 to 0.98, P=0.011; OR=0.54, 95%CI 0.31 to 0.93, P=0.026). Conversely, no causal relationship was observed between menarche and menopause with RA. Sensitivity analysis confirmed the robustness of the causal relationship, while MR Egger intercept analysis did not identify any potential horizontal pleiotropy (Page of first gestation -RA=0.169, Page of last gestation -RA=0.283). ② Reverse Mendelian randomization analysis revealed a significant positive causal association between RA and the age of first pregnancy, while no causal relationship was observed with the age of last pregnancy (OR=1.07, 95%CI 1.02 to 1.11, P=0.001). ③ Multivariate Mendelian randomization analysis demonstrated that both the age of first pregnancy and last pregnancy in women were inversely associated with the risk of RA (OR=0.88, 95%CI 0.80 to 0.97, P=0.010; OR=0.68, 95%CI 0.48 to 0.97, P=0.033). ④ There existed a negative correlation between the age of pregnancy in women and the risk of developing RA, suggesting a potential protective effect. ConclusionPregnancy age may have a negative causal relationship with the risk of RA, while menarche and menopause have no causal relationship with RA.
ObjectiveTo investigate whether there is a causal relationship between reproductive history (number of children, age at first birth) and the risk of hormone-related cancers (breast, endometrial, and ovarian) in women. MethodsUnivariate and multivariate Mendelian randomization (MR) methods were used to investigate the causal effects of the number of children (childlessness in infertile women and number of children ever born in fertile women) and age at first birth on three hormone-related cancers. The inverse variance weighting method was used for the primary analysis, and sensitivity analyses and reliability tests were used to ensure the reliability of the results. ResultsUnivariate MR showed that infertile women had a higher risk of breast cancer compared with fertile women (OR=1.07, 95%CI 1.05 to 1.09, P<0.001). Multivariate MR showed that among fertile women, after accounting for the effect of age at first birth, higher number of children ever born may be associated with lower risk of breast cancer (OR=0.61, 95%CI 0.43 to 0.85, P<0.01). Neither univariate nor multivariate MR found a causal relationship between age at first birth and hormone-related cancers, and no causal relationship was found between the number of children ever born and endometrial and ovarian cancers; sensitivity analyses and reliability tests demonstrated that the results were unlikely to be affected by heterogeneity and horizontal pleiotropy. ConclusionThe more children a normal woman has, the lower her risk of breast cancer. Infertile women face a higher risk of breast cancer.
Objective To investigate the causal relationship between 91 circulating inflammatory proteins and respiratory tract infection by bidirectional Mendelian randomization. Methods single nucleotide polymorphisms (SNPs) for 91 inflammatory circulating proteins were derived from GWAS data from a genome-wide association study of 14 824 subjects of European ancestry on the Olink Target platform, and SNPs for acute bronchitis, acute bronchiolitis, and acute laryngitis and tracheitis were derived from GWAS pooled data in the FinnGen database. Inverse variance weighting method was used as the main research method to conduct bidirectional Mendelian randomization analysis, and Cochran’ IVW Q test, MR-Egger regression method and one by one elimination method were used to conduct sensitivity tests to evaluate heterogeneity and horizontal pleiotropy. In order to reduce the incidence of Class I errors and improve the feasibility of the study, Bonferroni correction was performed.ResultsLevels of C hemokine C-X-C motif ligand 6 (CXCL6), matrix metalloproteinase-1 (MMP-1), hepatocyte growth factor (HGF), interleukin-10 (IL-10), chemokine C-X3-C motif ligand 1 (CX3CL1), and TNF-related activation-induced cytokine (TRANCE) were causally associated with acute bronchitis. MMP-1 level [OR: 1.239 0, 95%CI: 1.111 6-1.382 2, P<0.000 5] had a significant causal relationship with acute bronchitiss and played a promoting role. Levels of macrophage inflammatory protein-1α (MIP-1α), signaling lymphocyte activating molecules, and FMS-associated tyrosine kinase 3 ligand (FIt3L) were potentially causally associated with acute bronchiolitis. There was a potential causal relationship between C-X-C motif chemokine 5 (CXCL5), T cell surface glycoprotein CD6 subtype (CD6), fibroblast growth factor 19 (FGF-19), C-C motif chemokine 23 (CCL23), monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor ligand superfamily member 12 (TNFSF12) levels and acute laryngitis and tracheitis. In reverse Mendelian randomization analysis, there were no positive results between acute bronchitis, acute bronchiolitis and 91 inflammatory factors. Acute laryngitis and tracheitis [OR: 1.076 3,95%CI: 1.012 9-1.143 7, P=0.017 6] were potentially causally associated with FGF-19 levels. Conclusions MMP-1 level have a significant causal relationship with acute bronchitis. The levels of other inflammatory factors such as CXCL6, HGF, MIP-1 alpha, FIt3L, CXCL5, FGF-19 are potentially causally associated with respiratory tract infections. MMP-1 may be an important target for the prediction or treatment of acute bronchitis.
Objective To explore the causal relationship between the Collagen VI (COL6) family proteins COL6A1, A2, and A3 and bronchiectasis using the Mendelian randomization (MR) method.MethodsThe primary analysis was conducted using MR combined with summary-data-based Mendelian randomization (SMR) analysis. COL6 family proteins were used as exposure data, and bronchiectasis was used as outcome data. Cis-protein quantitative trait locus (cis-pQTL) data were extracted for analysis, and the results were meta-analyzed. Subsequently, COL6A3-cis-pQTL data from the UK Biobank plasma proteome study were used for further validation. Colocalization analysis was also performed to further explore the association between COL6 proteins and bronchiectasis.Results MR and SMR results revealed a negative causal relationship between COL6A3 and bronchiectasis (p-MRmeta = 0.005, OR = 0.30; p-SMRmeta = 0.004, OR = 0.26). The validation phase also confirmed the negative causal relationship between COL6A3 and bronchiectasis (p-MRmeta = 0.000007, OR = 0.27; p-SMRmeta = 0.0003, OR = 0.29). Colocalization analysis supported the presence of a shared causal variant (rs972974) between COL6A3 and bronchiectasis (PP.H4 = 0.967/0.876).Conclusion There is an inverse causal relationship between COL6A3 and bronchiectasis. Low expression of COL6A3 increases the risk of developing bronchiectasis, making COL6A3 a potential biomarker and therapeutic target for drug development in bronchiectasis.
Objective To explore the correlation between physical activity, sleep and aging using a two-sample Mendelian randomization (MR) method. Methods The data through genome-wide association studies was summarized. The single nucleotide polymorphisms (SNPs) related to physical activity and sleep as instrumental variables was selected. The inverse variance weighting method was used for the main analyses, complemented by the weighted median method and MR Egger regression, and then sensitivity analyses were carried out in terms of multiplicity, heterogeneity and leave-one-out method. Finally, multivariate Mendelian methods were applied to eliminate confounders and find mediators. Results A total of two types of physical activity (strong physical activity, physical inactivity) and three sleep conditions (daytime naps, short sleep duration, adequate sleep duration) were found to have a causal relationship with frailty index (P<0.05), while physical inactivity was found to have a causal relationship with telomere length (P<0.05). A total of 167 SNPs were included in the analysis. Strong physical activity [correlation coefficient (β)=?1.26, 95% confidence interval (CI) (?1.60, ?0.96), P<0.0001], adequate sleep duration [β=?0.17, 95%CI (?0.26, ?0.09), P<0.001] were negatively correlated with the frailty index. Physical inactivity [β=1.47, 95%CI (0.85, 2.08), P<0.001], daytime naps [β=0.25, 95%CI (0.12, 0.39), P=0.0002], and short sleep duration [β=0.20, 95%CI (0.13, 0.27), P<0.0001] were positively associated with frailty index. Physical inactivity [β=?0.38, 95%CI (?0.69, ?0.07), P=0.02] was negatively correlated with telomere length. Percentage body fat, body fat mass, waist circumference, body weight and body mass index partially mediated 25.52%, 23.52%, 10.08%, 17.6% and 10.08% of the effect between daytime naps and frailty index, respectively. Conclusion There is a causal relationship between physical activity, sleep, and aging.
Objective To explore the causal relationship between DNA copy number and the risk of Alzheimer disease (AD) using Mendelian randomization (MR) methods, as well as to investigate the potential mediating effects of immune cells. Methods The data related to 731 immune cell types, DNA copy number and AD from the Genome-Wide Association Study database were collected. A bidirectional MR analysis was conducted to explore the causal relationship between DNA copy number and AD, primarily using the inverse-variance weighted method and MR-Egger method. Additionally, a two-step mediation analysis was performed to identify potential mediating immune cells. Results A total of 134 single-nucleotide polymorphisms were included for bidirectional MR analysis. The MR methods results showed a negative causal relationship between DNA copy number and the risk of AD (P<0.05), while the reverse analysis showed no statistical significance. Sensitivity analysis confirmed the robustness of these results. The mediation analysis indicated that the immune cell phenotype (HVEM on CD45RA-CD4+) partially mediated the causal relationship between DNA copy numbers and the risk of AD, with a mediation effect proportion of 4.6%. Conclusion An increase in DNA copy numbers may reduce the risk of AD, and immune cells partially mediate this causal relationship.
Objective To analyze the causal relationship between educational attainment and the risk of systemic lupus erythematosus (SLE). Methods Based on the data from publicly available genome-wide association studies, we employed single nucleotide polymorphisms (SNPs) strongly associated with educational attainment as instrumental variables. Two-sample Mendelian randomization analysis was used to investigate the causal relationship between educational attainment and SLE. The primary analysis method used was the inverse variance weighted with multiplicative random effects. Validation methods included inverse variance weighted with fixed effects and MR-Egger methods. Additionally, sensitivity analysis was conducted using the leave-one-out approach. Results Finally, 433 SNPs were included. The inverse variance weighted with multiplicative random effects analysis indicated no causal effect of educational attainment on the risk of SLE [odds ratio =1.111, 95% confidence interval (0.813, 1.518), P=0.509]. Similarly, the other two methods did not find any evidence of a causal relationship (P>0.05); however, significant heterogeneity was observed. The MR-Egger regression analysis provided no evidence of horizontal pleiotropy among the included instrumental variables (P>0.05). The leave-one-out approach did not identify any individual SNP that had a significant impact on the overall effect estimate. ConclusionIn conclusion, this study does not support a causal effect of educational attainment on the risk of SLE.
ObjectiveTo explore the causal relationship between immune cells and heart failure (HF), and the mediating role of serum metabolites, in order to identify potential biomarkers and therapeutic targets. MethodsWe employed a two-sample Mendelian randomization (MR) analysis method based on genome-wide association study (GWAS) data, analyzing the direct and indirect effects of 731 types of immune cells and 1 400 metabolites on HF. We selected valid instrumental variables and conducted statistical analyses using R software. The primary analysis was performed using the inverse variance weighted method, supplemented by MR-Egger analysis and weighted median method. The stability of the results was assessed through tests such as Cochran’s Q test. ResultsOur research found a negative causal relationship between PD-L1 on CD14?CD16+ and HF. Sensitivity analysis supported this result. The reverse MR analysis did not find an effect of HF on PD-L1 on CD14?CD16+, indicating that PD-L1 on CD14?CD16+ may play a unidirectional role in reducing the risk of HF. Further mediation MR analysis showed that PD-L1 on CD14?CD16+ might influence the risk of HF onset by regulating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), with a mediation effect ratio of 6.7%. ConclusionPD-L1 on CD14?CD16+ may reduce the risk of HF by elevating the levels of sphingomyelin (d17:1/14:0, d16:1/15:0), which provides a new perspective for understanding the pathogenesis of HF.