Causal association between blood leukocyte counts and vascular dementia: a two-sample bidirectional Mendelian randomization study
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ABSTRACT:
SUBMITTER: Liu S
PROVIDER: S-EPMC11344047 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundAtrial fibrillation (AF) is an age-related disease, while telomeres play a central role in aging. But the relationship between AF and telomere length (LTL) is still controversial. This study aims to examine the potential causal association between AF and LTL by using Mendelian randomization (MR).MethodsBidirectional two-sample MR, expression and protein quantitative trait loci (eQTL and pQTL)-based MR were performed using genetic variants from United Kingdom Biobank, FinnGen, and a meta-analysis study, which comprised nearly 1 million participants in the Atrial Fibrillation Study and 470,000 participants in the Telomere Length Study. Apart from the inverse variance weighted (IVW) approach as the main MR analysis, complementary analysis approaches and sensitivity analysis were applied.ResultsThe forward MR revealed a significant causal estimate for the genetically predicted AF with LTL shortening [IVW: odds ratio (OR) = 0.989, p = 0.007; eQTL-IVW: OR = 0.988, p = 0.005; pQTL-IVW: OR = 0.975, p < 0.005]. But in the reverse MR analysis, genetically predicted LTL has no significant correlation with AF (IVW: OR = 0.995, p = 0.916; eQTL-IVW: OR = 0.999, p = 0.995; pQTL-IVW: OR = 1.055, p = 0.570). The FinnGen replication data yielded similar findings. Sensitivity analysis ensured the stability of the results.ConclusionThe presence of AF leads to LTL shortening rather than the other way around. Aggressive intervention for AF may delay the telomere attrition.
| S-EPMC9975167 | biostudies-literature
Project description:BackgroundNumerous observational studies have suggested that atrial fibrillation (AF) was associated with an increased risk of vascular dementia (VaD). However, the causal genetic relationships between AF and VaD remains unclear. To evaluate the effect of AF on VaD, we performed the Mendelian randomization (MR) analysis to investigate the causal genetic relationships between AF and VaD.MethodsThe bidirectional MR analysis was conducted to explore the causal relationships between exposure and disease. We applied a series of quality assessments to select significantly and independently single nucleotide polymorphisms (SNPs) from publicly available large-scale genome-wide association studies (GWAS) databases. Three methods [Inverse variance weighted method (IVW), MR-Egger method, and weighted median (WM)method] were used to derive MR estimates. In order to ensure reliable MR results, sensitivity analyses were performed to evaluate the horizontal pleiotropy and heterogeneity.ResultsOur MR analyses revealed no significant genetic relationships between AF and the risk of VaD (IVW: OR = 1.10, 95%CI = 0.95-1.28, P = 0.20). In the reverse direction analysis, there was no evidence to support a significant genetic relationship of VaD with AF risk (IVW: OR = 1.00, 95% CI = 0.99-1.01, P = 0.52). Consistent results were obtained using different MR methods. Sensitivity analyses suggested no significant horizontal pleiotropy and heterogeneity in the study.ConclusionThis MR analysis did not provide evidence to support the causal genetic relationships between AF on VaD risk and the causal effect of VaD on AF risk.
| S-EPMC10347408 | biostudies-literature
Project description:BackgroundTo explore the underlying causality between leukocyte telomere length (LTL) and four gastrointestinal diseases, we designed a two-sample bidirectional Mendelian randomization study.MethodsTwo-sample Mendelian randomization (MR) was used to explore genetic causality between LTL and four gastrointestinal diseases, including irritable bowel syndrome (IBS), gastroesophageal reflux disease (GERD), gastrointestinal ulcers disease (GUD), and nonalcoholic fatty liver disease (NAFLD). We utilized inverse-variance weighted (IVW) as the primary method for MR analysis. Supplementary analyses were conducted using methods such as MR-Egger regression, weighted-median, Maximum Likelihood (MaxLik), Robust adjusted profile score (MR-RAPS), Contamination mixture (ConMix), and MR-mix. Cochran's Q was calculated to check for heterogeneity. The MR-Egger regression and MR pleiotropy residual sum and outlier (MR-PRESSO) were detected for pleiotropy.ResultsThe IVW analysis suggests that there may be a potential causal relationship between LTL and two diseases (odds ratio (OR): 1.062; 95% confidence interval (CI): 1.003, 1.124; p = 0.038 for IBS and OR: 0.889; 95% CI: 0.798, 0.990; p = 0.032 for GERD). However, other methods do not entirely align with the results of the IVW analysis. In the reverse MR analysis, we did not find statistically significant associations between LTL and these four diseases.ConclusionThe current evidence does not definitively rule out a causal relationship between LTL and these four gastrointestinal diseases but suggests a potential association between LTL and IBS, or LTL and GERD. Exploring the relationship between gastrointestinal diseases and LTL may offer new insights into the onset, progression, and treatment of these diseases.
| S-EPMC10729385 | biostudies-literature
Project description:Background: Although observational studies have demonstrated that blood lipids were associated with systemic lupus erythematosus (SLE), the causality of this association remains elusive as traditional observational studies were prone to confounding and reverse causality biases. Here, this study attempted to reveal the potential causal link between SLE and the levels of four blood lipids (HDL cholesterol, LDL cholesterol, TG, and TC). Methods: Bidirectional two-sample Mendelian randomization (MR) was employed to explore the unconfounded causal associations between the four blood lipids and SLE. In addition, regression-based Multivariate MR (MVMR) to quantify the possible mediation effects of blood lipids on SLE. After a rigorous evaluation of the quality of studies, the single-nucleotide polymorphisms (SNPs) associated with the four blood lipids were selected from the Global Lipids Genetic Consortium (GLGC) consisted of 188,577 individuals of European ancestry, and the SNPs related to SLE were selected from a large-scale genome-wide association study (GWAS) database named IEU GWAS. Subsequently, MR analyses were conducted with inverse-variance weighted (IVW), weighted median, weighted mode, simple mode, and MR-Egger regression. Sensitivity analyses were performed to verify whether heterogeneity and pleiotropy led to bias in the MR results. Results: Bidirectional two-sample MR results demonstrated that there was no significant causal association between SLE and the four blood lipids (When setting SLE as outcome, HDL cholesterol and SLE, IVW OR: 1.32, 95% CI: 1.05∼1.66, p = 1.78E-02; LDL cholesterol and SLE, IVW OR: 1.26, 95% CI: 1.04∼1.53, p = 2.04E-02; TG and SLE, IVW OR: 1.04, 95% CI: 0.71∼1.51, p = 8.44E-01; TC and SLE, IVW OR: 1.07, 95% CI: 0.89∼1.29, p = 4.42E-01; When setting SLE as exposure, SLE and HDL cholesterol, IVW OR: 1.00, 95% CI: 0.99∼1.01, p = 9.51E-01; SLE and LDL cholesterol, IVW OR: 0.99, 95% CI: 0.98∼1.00, p = 3.14E-01; SLE and TG, IVW OR: 0.99, 95% CI: 0.98∼1.00, p = 1.30E-02; SLE and TC, IVW OR: 0.99, 95% CI: 0.98∼1.00, p = 1.56E-01). Our MVMR analysis also provided little evidence that genetically determined lipid traits were significantly associated with the risk of SLE (HDL cholesterol and SLE, p = 9.63E-02; LDL cholesterol and SLE, p = 9.63E-02; TG and SLE, p = 8.44E-01; TC and SLE, p = 4.42E-01). Conclusion: In conclusion, these data provide evidence that genetic changes in lipid traits are not significantly associated with SLE risk in the European population.
| S-EPMC9043646 | biostudies-literature
Project description:IntroductionPrevious observational studies have reported a positive correlation between obesity and susceptibility to hypothyroidism; however, there is limited evidence from alternative methodologies to establish a causal link.MethodsWe investigated the causal relationship between obesity and hypothyroidism using a two-sample bidirectional Mendelian randomization (MR) analysis. Single-nucleotide polymorphisms (SNPs) associated with obesity-related traits were extracted from a published genome-wide association study (GWAS) of European individuals. Summarized diagnostic data of hypothyroidism were obtained from the UK Biobank. Primary analyses were conducted using the inverse variance-weighted (IVW) method with a random-effects model as well as three complementary approaches. Sensitivity analyses were performed to ascertain the correlation between obesity and hypothyroidism.ResultsMR analyses of the IVW method and the analyses of hypothyroidism/myxedema indicated that body mass index (BMI) and waist circumference (WC) were significantly associated with higher odds and risk of hypothyroidism. Reverse MR analysis demonstrated that a genetic predisposition to hypothyroidism was associated with an increased risk of elevated BMI and WC, which was not observed between WC adjusted for BMI (WCadjBMI) and hypothyroidism.DiscussionOur current study indicates that obesity is a risk factor for hypothyroidism, suggesting that individuals with higher BMI/WC have an increased risk of developing hypothyroidism and indicating the importance of weight loss in reducing the risk of hypothyroidism.
| S-EPMC10801094 | biostudies-literature
Project description: Not available
| S-EPMC11020755 | biostudies-literature
Project description:BackgroundGrowing evidence from observational studies and clinical trials suggests that the gut microbiota is associated with tuberculosis (TB). However, it is unclear whether any causal relationship exists between them and whether causality is bidirectional.MethodsA bidirectional two-sample Mendelian randomization (MR) analysis was performed. The genome-wide association study (GWAS) summary statistics of gut microbiota were obtained from the MiBioGen consortium, while the GWAS summary statistics of TB and its specific phenotypes [respiratory tuberculosis (RTB) and extrapulmonary tuberculosis (EPTB)] were retrieved from the UK Biobank and the FinnGen consortium. And 195 bacterial taxa from phylum to genus were analyzed. Inverse variance weighted (IVW), MR-Egger regression, maximum likelihood (ML), weighted median, and weighted mode methods were applied to the MR analysis. The robustness of causal estimation was tested using the heterogeneity test, horizontal pleiotropy test, and leave-one-out method.ResultsIn the UK Biobank database, we found that 11 bacterial taxa had potential causal effects on TB. Three bacterial taxa genus.Akkermansia, family.Verrucomicrobiacea, order.Verrucomicrobiales were validated in the FinnGen database. Based on the results in the FinnGen database, the present study found significant differences in the characteristics of gut microbial distribution between RTB and EPTB. Four bacterial taxa genus.LachnospiraceaeUCG010, genus.Parabacteroides, genus.RuminococcaceaeUCG011, and order.Bacillales were common traits in relation to both RTB and TB, among which order.Bacillales showed a protective effect. Additionally, family.Bacteroidacea and genus.Bacteroides were identified as common traits in relation to both EPTB and TB, positively associating with a higher risk of EPTB. In reverse MR analysis, no causal association was identified. No significant heterogeneity of instrumental variables (IVs) or horizontal pleiotropy was found.ConclusionOur study supports a one-way causal relationship between gut microbiota and TB, with gut microbiota having a causal effect on TB. The identification of characteristic gut microbiota provides scientific insights for the potential application of the gut microbiota as a preventive, diagnostic, and therapeutic tool for TB.
| S-EPMC10765819 | biostudies-literature
Project description:BackgroundPrevious observational studies have reported that delirium has an association with an increased risk of Alzheimer's disease (AD), and that patients with AD have a higher risk of developing delirium. However, due to the limitations of observational study, it is challenging to confirm whether delirium has a causal effect on AD or reverse causation exists.MethodsA bidirectional two-sample Mendelian randomization (MR) was performed to investigate the relationship between delirium and AD. Summary statistics from genome-wide association studies of delirium and AD phenotypes were utilized. Inverse-variance weighted (IVW) method was used as the main analysis approach, and additional analyses were performed using MR Egger, weighted median, simple mode and weighted mode to ensure result accuracy. Heterogeneity and horizontal pleiotropy were assessed using Cochran's Q statistics and MR Egger intercept, separately.ResultsThe MR analyses showed that genetically predicted delirium was not associated with AD (IVW: odds ratio [OR] 0.98, 95% CI 0.91-1.05, P = 0.544; MR Egger: OR 0.98, 95% CI 0.83-1.15, P = 0.780; weighted median: OR 0.96, 95% CI 0.88-1.05, P = 0.323; simple mode: OR 0.91, 95% CI 0.80-1.04, P = 0.212; weighted mode: OR 0.93, 95% CI 0.83-1.05, P = 0.277). However, in the reverse direction, AD was associated with delirium (IVW: OR 1.32, 95% CI 1.13-1.54, P = 3.91E-04; MR Egger: OR 1.42, 95% CI 1.02-1.98, P = 5.60E-02; Weighted median: OR 1.39, 95% CI 1.18-1.63, P = 8.22E-05; Simple mode: OR 1.41, 95% CI 1.10-1.80, P = 1.41E-02; Weighted mode: OR 1.39, 95% CI 1.16-1.67, P = 3.23E-03).ConclusionBased on the results of our MR study, there is no bidirectional causality between delirium and AD, delirium is not associated with an increased risk of AD, while genetically predicted AD is a potential causal risk factor for delirium.
| S-EPMC10405368 | biostudies-literature
Project description:BackgroundThe relationship between Metabolic Syndrome (MetS) and ovarian dysfunction has been widely reported in observational studies, yet it remains not fully understood. This study employs genetic prediction methods and utilizes summary data from genome-wide association studies (GWAS) to investigate this causal link.MethodsWe employed a bidirectional two-sample Mendelian Randomization (MR) analysis utilizing MetS and ovarian dysfunction summary data from GWAS. Inverse variance weighted (IVW) was employed as the primary MR method, supplemented by Weighted Median, Weighted Mode, and MR-Egger methods. The robustness of the results was further assessed through sensitivity analyses including MR-Egger regression, MR-PRESSO, Cochran's Q, and leave-one-out test.ResultsOur MR analysis identified a causal relationship between genetically determined insulin resistance (OR = 0.26, 95% CI: 0.08-0.89, P = 0.03), waist circumference (OR = 2.14, 95% CI: 1.45-3.15, P < 0.001), BMI (OR = 2.1, 95% CI: 1.56-2.83, P < 0.001) and ovarian dysfunction. Conversely, reverse MR analysis confirmed causal effects of ovarian dysfunction on metabolic syndrome (OR = 0.98, 95% CI: 0.97-0.99, P < 0.001) and waist circumference (OR = 0.99, 95% CI: 0.98-0.99, P = 0.02). The results of MR-Egger regression test indicated that the whole analysis was not affected by horizontal pleiotropy. Additionally, the MR-PRESSO test identified outliers in SNPs, but after removal of outliers, results remained unchanged.ConclusionThis study reveals a bidirectional causal connection between metabolic syndrome and ovarian dysfunction via genetic prediction methods. These findings are crucial for advancing our understanding of the interactions between these conditions and developing strategies for prevention and treatment.
| S-EPMC11895234 | biostudies-literature
Project description: Not available
| S-EPMC11367819 | biostudies-literature