Objective To explore the potential causal relationship between thyroid dysfunction and osteoporosis (OP) through bidirectional two-sample Mendelian randomization (MR) analysis to provide genetic evidence for the risk association between thyroid dysfunction and OP, and provide reference for early prevention and treatment of OP. Methods Causal relationships were estimated based on data from genome-wide association studies for hypothyroidism (n=410141), hyperthyroidism (n=460499), Hashimoto thyroiditis (n=395640), and OP (n=212778). The inverse variance weighted method was used as the main analysis method, and the other four methods were used as the supplementary analysis methods to evaluate the causal effect of thyroid dysfunction and OP. Results The results of inverse variance weighted method showed that hypothyroidism [odds ratio (OR)=1.097, 95% confidence interval (CI) (1.017, 1.183), P=0.017], hyperthyroidism [OR=1.089, 95%CI (1.000, 1.186), P=0.049] and Hashimoto thyroiditis [OR=1.190, 95%CI (1.054, 1.343), P=0.005] were positively correlated with the causal effect of OP. The results of reverse MR analysis did not support that OP would increase the risk of hypothyroidism, hyperthyroidism or Hashimoto thyroiditis (P>0.05). In the bidirectional MR analyses, there was no heterogeneity in Cochran Q detection, MR-Egger intercept test results showed that there was no horizontal pleotropy, and the leave-one-out method analysis results showed that the MR analysis results were reliable. Conclusion Hypothyroidism, hyperthyroidism, and Hashimoto thyroiditis increase the risk of OP, while OP is not found to increase the risk of thyroid dysfunction in reverse studies.
ObjectiveExploring the potential causal effects and directions of insulin resistance (IR) and chronic airway inflammatory diseases, including asthma and chronic obstructive pulmonary disease (COPD), through two sample Mendelian randomization (MR). MethodsA total of 53 validated single nucleotide polymorphisms (SNPs) associated with IR were selected as instrumental variables. The inverse variance-weighted (IVW) method was used to model the causal association, and sensitivity analyses through leave-one-out analysis and pleiotropy testing were conducted to assess the relationship between IR and asthma and COPD. ResultsMR analysis revealed no significant causal effect of IR on asthma (IVW: OR=1.067, 95%CI 0.871 to 1.306, P=0.531) or COPD (IVW: OR=0.906, 95%CI 0.686 to 1.196, P=0.557). The results were consistent across sensitivity analyses and multiple pleiotropy tests, with no evidence of horizontal pleiotropy detected. ConclusionNo causal association was found between IR and the development of asthma or COPD. The relationship between these conditions may be influenced indirectly through complex interactions between metabolic and inflammatory pathways affecting disease progression.
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 This study employs Mendelian randomization analysis to explore the causal relationship between dietary habits and systemic lupus erythematosus (SLE). MethodsWe obtained data from the MRC-IEU database on five dietary habits as instrumental variables for exposure "never eating dairy products" "never eating eggs or foods containing eggs" "never eating sugar or foods/drinks containing sugar" "never eating wheat products" and "I eat all of the above". Summary data related to SLE were retrieved from the MRC-IEU database for the discovery cohort (designated as MSLE) and from a Finnish database for the validation cohort (recorded as FSLE). Two-sample Mendelian randomization analyses were conducted using inverse variance weighting (IVW), MR-Egger, weighted median, Simple Mode, and Weighted Mode methods to investigate the causal relationship between dietary habits and SLE. The MR-Egger intercept test was performed to assess the presence of horizontal pleiotropy, while the leave-one-out method was employed to verify the stability of the results, with Cochran’s Q test and funnel plots used to evaluate heterogeneity. ResultsMendelian randomization analysis indicated that never eating wheat products increases the risk of developing SLE (IVW: P<0.05). In contrast, there was no significant causal relationship between the consumption of dairy products, eggs or foods containing eggs, or the consumption of all of the above with SLE (IVW: P>0.05). Additionally, there was no significant causal relationship between never sugar or foods/drinks containing sugar and MSLE (IVW: P=0.877), although a potential causal association with FSLE was suggested (IVW: P=0.016). The MR-Egger intercept test indicated no evidence of horizontal pleiotropy (P>0.05). ConclusionNever eating wheat products may be an independent risk factor for SLE. However, the causal relationship between never sugar or foods/drinks containing sugar and SLE remains indeterminate.
ObjectiveTo investigate the causal relationship between gut microbiota and cholelithiasis using a two-sample Mendelian randomization method. MethodsThe genome-wide association studies (GWAS) data of gut microbiota from the MiBioGen study and the GWAS data of cholelithiasis from the FinnGen Biobank were utilized. Genetic variants significantly associated with the relative abundance of gut microbiota were identified as instrumental variables (IVs) based on a specified threshold. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with results assessed based on the odds ratio (OR) and 95% confidence interval (CI). The robustness and reliability of the findings were ensured through quality control measures, including sensitivity analysis, assessment of heterogeneity, and evaluation for horizontal gene pleiotropy. ResultsClostridiumsensustricto1 [OR=1.160, 95%CI (1.023, 1.314), P=0.020], Coprococcus3 [OR=1.136, 95%CI (1.014, 1.272), P=0.028] and Peptococcus [OR=1.074, 95%CI (1.023, 1.128) , P=0.004] increased the risk of cholelithiasis. Bacilli [OR=0.897, 95%CI (0.818, 0.984), P=0.022], Family Ⅹ ⅢAD3011group [OR=0.908, 95%CI (0.830, 0.992), P=0.033] and Lactobacillales [OR=0.884, 95%CI (0.802, 0.974), P=0.013] were protective factors for cholelithiasis. ConclusionThe study has identified 6 kinds of specific gut microbiota that are causally linked to the development of cholelithiasis, providing new ideas for the diagnosis and treatment of cholelithiasis.
ObjectiveUsing the whole genome association study (GWAS) data, Mendel randomization (MR) method was used to find the causal relationship between oral flora and type 2 diabetes (T2D) and myocardial infarction (MI). MethodsGenetic association data of oral microbiota were selected from the Chinese 4D-SZ cohort GWAS dataset, and T2D and MI outcome data were obtained from a large-scale cohort study in BioBank Japan. Four methods, including inverse variance weighting (IVW), were used to analyze the causal relationship between exposure and outcomes. Sensitivity analysis was conducted on significant MR results to further validate the robustness of the results. ResultsThe results showed a total of 24 species of dorsal tongue flora and 13 species of salivary flora with a potential causal relationship with T2D. There were 12 species each of dorsal tongue and salivary flora with a potential causal relationship with MI. A total of 8 oral flora were found on the dorsum of the tongue and saliva that could affect both T2D and MI, namely Saccharimonadaceae, Treponemataceae, Prevotella, Haemophilus, Lachnoanaerobaculum, Campylobacter_A, Neisseria, and Streptococcus. ConclusionWe identified 8 oral flora causally associated with both T2D and MI, suggesting that T2D may play a role in promoting the progression of MI by affecting the above oral flora.
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 gut microbiota and urinary tract infections (UTI) using data from genome-wide association studies. Methods The gut microbiota data were sourced from the MiBioGen consortium, comprising genetic variables from 18 340 individuals. UTI data (ieu-b-5.65) were derived from the UK Biobank. Six methods including inverse variance weighted (IVW), Mendelian randomization (MR)-Egger, maximum likelihood, simple mode, weighted mode, and weighted median were employed for two-sample MR analysis on these datasets. Additionally, MR-PRESSO was used to detect and correct for heterogeneity and outliers in the analysis. Cochran’s Q test and leave-one-out analysis were applied to assess potential heterogeneity and multiple effects. Furthermore, reverse MR analysis was conducted to investigate causal relationships between UTI and gut microbiota. Results According to IVW method analysis results, bacterial genera Eggerthella (OR=1.08, 95%CI 1.01 to 1.16, P=0.034) and Ruminococcaceae (UCG005) (OR=1.10, 95%CI 1.01 to 1.20, P=0.022) were found to increase the risk of UTI, while Defluviitaleaceae (UCG011) (OR=0.90, 95%CI 0.82 to 0.99, P=0.022) appeared to decrease it. Reverse MR analysis did not reveal a significant effect of UTI on these three bacterial genera. Our study found no evidence of heterogeneity or pleiotropy based on the results of Cochran’s Q test, MR-Egger, and MR-PRESSO global test. Conclusion In this MR study, we demonstrate a causal association between Eggerthella, Ruminococcaceae, Defluvitalaceae and the risk of urinary tract infections.
ObjectiveThis study applied Mendelian randomization to explore the potential causal relationship between inflammatory factors and diabetic nephropathy. MethodsSummary-level data from genome-wide association studies of inflammatory factors and diabetic nephropathy were used, and inverse variance weighted analysis was used as the primary analytical method, complemented by results from weighted median, MR-Egger regression, simple model, and median model approaches. Sensitivity analysis was used to test the reliability of the MR analysis results. ResultsIn the inverse variance weighted method, stem cell factor (OR=1.28, 95%CI 1.04 to 1.58, P=0.020) and interferon-γ (OR=1.36, 95%CI 1.10 to 1.70, P=0.005) were positively correlated with diabetic nephropathy, and diabetic nephropathy was positively correlated with interferon-inducible protein 10 (OR=0.90, 95%CI 0.83 to 0.98, P=0.012) were negatively correlated with diabetic nephropathy. Sensitivity analysis showed that MR analysis was reliable. ConclusionStem cell factors and interferon-γ are associated with an increased risk of developing diabetic nephropathy, and diabetic nephropathy decreases the expression of interferon-inducible protein 10 in vivo. Our results demonstrate a potential causal relationship between inflammatory factors and the development of diabetic nephropathy. This finding is of clinical significance for the pre-diagnosis and treatment of diabetic nephropathy.
Objective To assess any potential associations between lung cancer and gut microbiota. Methods Mendelian randomization (MR) analysis was carried out by utilizing summary data from genome-wide association studies (GWAS) of the gut microbiota and lung cancer. The gut microbiota served as an exposure. Instrumental ariables (IVs) were identified from the GWAS of 18340 participants. The GWAS study of lung cancer from Europe served as an outcome, including 29 266 lung cancer patients and 56450 controls. We used the inverse-variance weighted (IVW) method as the primary analysis. Sensitivity analysis was used to test the reliability of MR analysis results. Results IVW results showed that Genus Parabacteroides (OR=1.258, 95%CI 1.034 to 1.531, P=0.022) and Phylum Bacteroidetes (OR=1.192, 95%CI 1.001 to 1.419, P=0.048) had a positive causal association with lung cancer, and there was a negative causal association between family Bifidobacteriaceae (OR=0.845, 95%CI 0.721 to 0.989, P=0.037) and order Bifidobacteriales (OR=0.865, 95%CI 0.721 to 0.989, P=0.037) with lung cancer. Sensitivity analysis showed no evidence of reverse causality, pleiotropy, and heterogeneity. Conclusion This study demonstrates that Genus Parabacteroides and Phylum Bacteroidetes are related to an increased risk of lung cancer, family Bifidobacteriaceae and order Bifidobacteriales can reduce the risk of lung cancer. Our thorough investigations provide evidence in favor of a potential causal relationship between a number of gut microbiota-taxa and lung cancer. To demonstrate how gut microbiota influences the development of lung cancer, further research is necessary.