Associations between type 1 diabetes and pulmonary tuberculosis: a bidirectional mendelian randomization study
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SUBMITTER: Jiang Y
PROVIDER: S-EPMC10913601 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Type 2 diabetes mellitus (T2DM) is a common metabolic disease that can lead to a wide range of complications and impose a significant economic burden to society. Frailty is a disease associated with the accumulation of health deficits that may affect the quality of life of T2DM patients. This Mendelian randomization (MR) study explores the bidirectional causality between T2DM and frailty. All the data was available online at the IEU OpenGWAS project for this study, with the original data for T2DM coming from the pooled statistics of 468,298 participants in the UK biobank, and for frailty from the pooled summary statistics of a total of 175,226 participants in the UK biobank and Swedish TwinGene. The populations were all of European ancestry. Inverse variance weighting (IVW) was the main analytical method for assessing the causal effects of exposure and outcome, in addition, we also complemented weighted median and MR-Egger methods. Heterogeneity tests were performed with Cochran Q statistic and I2 statistic, and horizontal pleiotropy tests were detected through an intercept term in the MR-Egger regression model and MR-PRESSO. A sensitivity analysis was further performed with the leave-one-out method to estimate the impact of individual genetic variants on the overall outcomes. At the gene level, we identified 63 single nucleotide polymorphisms (SNPs) associated with T2DM and 14 SNPs associated with frailty for MR analysis. In the bidirectional MR analysis, the MR-Egger intercept and MR-PRESSO revealed no horizontal pleiotropy (P > .05), while significant heterogeneities were found by the heterogeneity test (P < .05). IVW results showed that frailty significantly increased the risk of T2DM (OR = 2.33, 95% confidence interval [CI] = 1.66-3.26, P < .001), and the similar result existed in the reverse MR analysis (OR = 1.04, 95% CI = 1.02-1.06, P < .001). A bidirectional causal relationship exists between T2DM and frailty, with intervention for either disease reducing the risk of the other.
| S-EPMC11903027 | biostudies-literature
Project description:BackgroundThe comorbidity rate between type 2 diabetes mellitus (T2DM) and pulmonary tuberculosis (PTB) is high and imposes enormous strains on healthcare systems. However, whether T2DM is causally associated with PTB is unknown owing to limited evidence from prospective studies. Consequently, the present study aimed to clarify the genetic causality between T2DM and PTB on the basis of Mendelian randomization (MR) analysis.MethodsGenetic variants for T2DM and PTB were obtained from the IEU OpenGWAS project. The inverse variance weighted method was used as the main statistical analysis method and was supplemented with MR-Egger, weighted median, simple mode, and weighted mode methods. Heterogeneity was analyzed using Cochran's Q statistic. Horizontal pleiotropy was assessed using the MR-PRESSO global test and MR-Egger regression. Robustness of the results was verified using the leave-one-out method.ResultsA total of 152 independent single-nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) to assess the genetic causality between T2DM and PTB. Patients with T2DM had a higher risk of PTB at the genetic level (odds ratio (OR) for MR-Egger was 1.550, OR for weighted median was 1.540, OR for inverse variance weighted was 1.191, OR for simple mode was 1.629, OR for weighted mode was 1.529). There was no horizontal pleiotropy or heterogeneity among IVs. The results were stable when removing the SNPs one by one.ConclusionsThis is the first comprehensive MR analysis that revealed the genetic causality between T2DM and PTB in the East Asian population. The study provides convincing evidence that individuals with T2DM have a higher risk of developing PTB at the genetic level. This offers a significant basis for joint management of concurrent T2DM and PTB in clinical practice.
| S-EPMC10636918 | biostudies-literature
Project description:ObjectiveObservational studies have suggested a potential association between constipation and several cancers. However, the causal relationship between constipation and cancer remains unclear. The purpose of this study is to explore the potential causal relationship between constipation and pan-cancer using Mendelian Randomization (MR) methods.MethodsWe performed a bidirectional MR analysis using publicly available summary data from Genome-Wide Association Studies (GWAS) statistics. The Inverse Variance Weighted (IVW) method was used as the main analysis method. We also used four MR methods: MR-Egger, Weighted Median, MR-PRESSO and MR.RAPS. Simultaneously, MR-Egger regression, Cochran's Q test and MR-PRESSO Global test were used to estimate the pleiotropy and heterogeneity of SNPs. In addition, we performed "leave-one-out" analyses" to avoid bias caused by horizontal pleiotropy of individual SNPs.ResultsMR analysis revealed a potential causal association between constipation and the risk of colorectal cancer (CRC) [IVW (OR= 1.0021 (1.0003, 1.0039), P= 0.0234)], lung cancer (LC) [IVW (OR=1.0955 (1.0134, 1.1843), P=0.0218)], Oral cavity and pharyngeal cancer (OPC) [IVW (OR=1.4068 (1.0070, 1.9652), P=0.0454)], and Pancreatic cancer (PC) [IVW (OR=1.5580 (1.0659, 2.2773), P=0.0221)]. In addition, we explored causal relationships between constipation and 12 other types of cancers, including gastric cancer, esophageal cancer, skin melanoma and so on. All five methods yielded no evidence of a causal association between constipation and the risk of these cancer types. In the reverse MR analysis, there was no evidence of a causal association between cancer and the risk of constipation for all five methods.ConclusionOur bidirectional MR study suggests a potential relationship between constipation and an increased risk of CRC, LC OPC and PC. The underlying mechanisms behind these associations will need to be explored in future experimental studies.
| S-EPMC11427234 | biostudies-literature
Project description:Liver dysfunction and type 2 diabetes (T2D) are consistently associated. However, it is currently unknown whether liver dysfunction contributes to, results from, or is merely correlated with T2D due to confounding. We used Mendelian randomization to investigate the presence and direction of any causal relation between liver function and T2D risk including up to 64,094 T2D case and 607,012 control subjects. Several biomarkers were used as proxies of liver function (i.e., alanine aminotransferase [ALT], aspartate aminotransferase [AST], alkaline phosphatase [ALP], and γ-glutamyl transferase [GGT]). Genetic variants strongly associated with each liver function marker were used to investigate the effect of liver function on T2D risk. In addition, genetic variants strongly associated with T2D risk and with fasting insulin were used to investigate the effect of predisposition to T2D and insulin resistance, respectively, on liver function. Genetically predicted higher circulating ALT and AST were related to increased risk of T2D. There was a modest negative association of genetically predicted ALP with T2D risk and no evidence of association between GGT and T2D risk. Genetic predisposition to higher fasting insulin, but not to T2D, was related to increased circulating ALT. Since circulating ALT and AST are markers of nonalcoholic fatty liver disease (NAFLD), these findings provide some support for insulin resistance resulting in NAFLD, which in turn increases T2D risk.
| S-EPMC7011195 | biostudies-literature
Project description:BackgroundThe presence of type 1 diabetes mellitus (T1DM) has been demonstrated to pose an increased risk for developing cardiovascular diseases (CVDs). However, the causal relationships between T1DM and CVDs remain unclear due to the uncontrolled confounding factors and reverse causation bias of the observational studies.MethodsSummary statistics of T1DM and seven CVDs from the largest available genome-wide association studies (GWAS) of European ancestry and FinnGen biobank were extracted for the primary MR analysis, and the analysis was replicated using UK biobank (UKBB) for validation. Three complementary methods: inverse variance weighted (IVW), weighted median, and MR-Egger were used for the MR estimates. The potential pleiotropic effects were assessed by MR-Egger intercept and MR-PRESSO global test. Additionally, multivariable MR (MVMR) analysis was performed to examine whether T1DM has independent effects on CVDs with adjustment of potential confounding factors. Moreover, a two-step MR approach was used to assess the potential mediating effects of these factors on the causal effects between T1DM and CVDs.ResultsCausal effects of T1DM on peripheral atherosclerosis (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.02-1.10; p = 0.002)] and coronary atherosclerosis (OR = 1.03, 95% CI: 1.01-1.05; p = 0.001) were found. The results were less likely to be biased by the horizontal pleiotropic effects (both p values of MR-Egger intercept and MR-PRESSO Global test > 0.05). In the following MVMR analysis, we found the causal effects of T1DM on peripheral atherosclerosis and coronary atherosclerosis remain significant after adjusting for a series of potential confounding factors. Moreover, we found that hypertension partly mediated the causal effects of T1DM on peripheral atherosclerosis (proportion of mediation effect in total effect: 11.47%, 95% CI: 3.23-19.71%) and coronary atherosclerosis (16.84%, 95% CI: 5.35-28.33%). We didn't find significant causal relationships between T1DM and other CVDs, including heart failure (HF), coronary artery disease (CAD), atrial fibrillation (AF), myocardial infarction (MI) and stroke. For the reverse MR from CVD to T1DM, no significant causal relationships were identified.ConclusionThis MR study provided evidence supporting the causal effect of T1DM on peripheral atherosclerosis and coronary atherosclerosis, with hypertension partly mediating this effect.
| S-EPMC10475187 | biostudies-literature
Project description:BackgroundPrevious epidemiological studies have reported associations between vitamin D and postpartum depression (PPD); however, the findings are inconsistent. This study employs bidirectional Mendelian Randomization (MR) to investigate the causal link between serum 25-hydroxyvitamin D [25(OH)D] levels and PPD. By utilizing genetic data from cohorts, this research aims to provide a more robust understanding of the potential relationship between vitamin D and PPD, addressing a critical gap in the current literature.MethodsA bidirectional MR analysis was conducted to investigate the genetic association between serum 25(OH)D and PPD using summary statistics extracted from GWAS datasets. The study included data from 15,668 patients with PPD and 376,755 healthy controls of European ancestry. The GWAS data for 25(OH)D were obtained from two studies within the UK Biobank, encompassing 496,946 and 79,366 participants. The primary analysis employed the inverse-variance weighted (IVW) method, while supplementary MR estimates were derived through the MR-Egger and weighted median (WME) methods. Furthermore, sensitivity analyses were implemented to ensure robustness and reliability, including Cochran's Q test, MR-PRESSO, MR-Egger intercept test, and the leave-one-out test.ResultsThe MR study revealed no substantial genetic correlation between serum 25(OH)D levels and PPD (OR = 1.065, 95%CI = 0.878-1.293, P = 0.522 for set A; OR = 0.978, 95 % CI = 0.669-1.430, P = 0.910 for set B). Additionally, in the reverse analysis, we did not observe a significant causal impact of PPD on serum 25(OH)D (OR = 1.001, 95%CI = 0.974-1.028, P = 0.951 for set A; OR = 1.011, 95%CI = 0.992-1.031, P = 0.261 for set B). The results obtained from MR-Egger and WME analyses concord with those derived from the IVW method. Conducting leave-one-out tests did not identify any single nucleotide polymorphism that might have influenced the MR results, confirming the robustness and reliability of the findings.ConclusionsThe results suggest the absence of a causal link between vitamin D concentrations and PPD. Inconsistent observations in previous observational studies may be attributed to residual confounding.
| S-EPMC11255668 | biostudies-literature
Project description:Background and aimsObservational studies showed that coronavirus disease (2019) (COVID-19) attacks universally and its most menacing progression uniquely endangers the elderly with cardiovascular disease (CVD). The causal association between COVID-19 infection or its severity and susceptibility of atrial fibrillation (AF) remains unknown.Methods and resultsThe bidirectional causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with not hospitalized COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and AF are determined by using two-sample Mendelian randomization (MR) analysis. Genetically predicted severe COVID-19 was not significantly associated with the risk of AF [odds ratio (OR), 1.037; 95% confidence interval (CI), 1.005-1.071; P = 0.023, q = 0.115]. In addition, genetically predicted AF was also not causally associated with severe COVID-19 (OR, 0.993; 95% CI, 0.888-1.111; P = 0.905, q = 0.905). There was no evidence to support the association between genetically determined COVID-19 and the risk of AF (OR, 1.111; 95% CI, 0.971-1.272; P = 0.127, q = 0.318), and vice versa (OR, 1.016; 95% CI, 0.976-1.058; P = 0.430, q = 0.851). Besides, no significant association was observed for hospitalized COVID-19 with AF. MR-Egger analysis indicated no evidence of directional pleiotropy.ConclusionOverall, this MR study provides no clear evidence that COVID-19 is causally associated with the risk of AF.
| S-EPMC8605875 | biostudies-literature
Project description:BackgroundEmerging evidence suggests bidirectional causal relationships between sleep disturbance and psychiatric disorders, but the underlying mechanisms remain unclear. Understanding the bidirectional causality between sleep traits and brain imaging-derived phenotypes (IDPs) will help elucidate the mechanisms. Although previous studies have identified a range of structural differences in the brains of individuals with sleep disorders, it is still uncertain whether grey matter (GM) volume alterations precede or rather follow from the development of sleep disorders.ResultsAfter Bonferroni correction, the forward MR analysis showed that insomnia complaint remained positively associated with the surface area (SA) of medial orbitofrontal cortex (β, 0.26; 95% CI, 0.15-0.37; P = 5.27 × 10-6). In the inverse MR analysis, higher global cortical SA predisposed individuals less prone to suffering insomnia complaint (OR, 0.89; 95%CI, 0.85-0.94; P = 1.51 × 10-5) and short sleep (≤ 6 h; OR, 0.98; 95%CI, 0.97-0.99; P = 1.51 × 10-5), while higher SA in posterior cingulate cortex resulted in a vulnerability to shorter sleep durations (β, - 0.09; 95%CI, - 0.13 to - 0.05; P = 1.21 × 10-5).ConclusionsSleep habits not only result from but also contribute to alterations in brain structure, which may shed light on the possible mechanisms linking sleep behaviours with neuropsychiatric disorders, and offer new strategies for prevention and intervention in psychiatric disorders and sleep disturbance.
| S-EPMC10544625 | biostudies-literature
Project description:IntroductionPrevious research has reported that the gut microbiota performs an essential role in sleep through the microbiome-gut-brain axis. However, the causal association between gut microbiota and sleep remains undetermined.MethodsWe performed a two-sample, bidirectional Mendelian randomization (MR) analysis using genome-wide association study summary data of gut microbiota and self-reported sleep traits from the MiBioGen consortium and UK Biobank to investigate causal relationships between 119 bacterial genera and seven sleep-associated traits. We calculated effect estimates by using the inverse-variance weighted (as the main method), maximum likelihood, simple model, weighted model, weighted median, and MR-Egger methods, whereas heterogeneity and pleiotropy were detected and measured by the MR pleiotropy residual sum and outlier method, Cochran's Q statistics, and MR-Egger regression.ResultsIn forward MR analysis, inverse-variance weighted estimates concluded that the genetic forecasts of relative abundance of 42 bacterial genera had causal effects on sleep-associated traits. In the reverse MR analysis, sleep-associated traits had a causal effect on 39 bacterial genera, 13 of which overlapped with the bacterial genera in the forward MR analysis.DiscussionIn conclusion, our research indicates that gut microbiota may be involved in the regulation of sleep, and conversely, changes in sleep-associated traits may also alter the abundance of gut microbiota. These findings suggest an underlying reciprocal causal association between gut microbiota and sleep.
| S-EPMC10461450 | biostudies-literature
Project description:Disruption of brain resting-state networks (RSNs) is known to be related to stroke exposure, but determining causality can be difficult in epidemiological studies. We used data on genetic variants associated with the levels of functional (FC) and structural connectivity (SC) within 7 RSNs identified from a genome-wide association study (GWAS) meta-analysis among 24,336 European ancestries. The data for stroke and its subtypes were obtained from the MEGASTROKE consortium, including up to 520,000 participants. We conducted a two-sample bidirectional Mendelian randomization (MR) study to investigate the causality relationship between FC and SC within 7 RSNs and stroke and its subtypes. The results showed that lower global mean FC and limbic network FC were associated with a higher risk of any ischemic stroke and small vessel stroke separately. Moreover, ventral attention network FC and default mode network SC have a positive causal relationship with the risk of small vessel stroke and large artery stroke, respectively. In the inverse MR analysis, any stroke and large artery stroke were causally related to dorsal attention network FC and somatomotor FC, respectively. The present study provides genetic support that levels of FC or SC within different RSNs have contrasting causal effects on stroke and its subtypes. Moreover, there is a combination of injury and compensatory physiological processes in brain RSNs following a stroke. Further studies are necessary to validate our results and explain the physiological mechanisms.
| S-EPMC10295514 | biostudies-literature