Dataset Information

No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study.

ABSTRACT:

Background

In epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases. However, it is still unclear whether the relationship is casual.

Methods

We employed a two-sample Mendelian randomization (MR) to clarify the causal effect of T2DM on high-frequency infectious diseases: sepsis, skin and soft tissue infections (SSTIs), urinary tract infections (UTIs), pneumonia, and genito-urinary infection (GUI) in pregnancy. And then, we analyzed the genome-wide association study (GWAS) meta-analysis of European-descent individuals and conducted T2DM-related single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) that were associated with genome-wide significance (p < 5 × 10^-8). MR estimates were obtained using the inverse variance-weighted (IVW), the MR-Egger regression, the simple mode (SM), weighted median, and weighted mode.

Results

The UK Biobank (UKB) cohort (n > 500,000) provided data for GWASs on infectious diseases. MR analysis showed little evidence of a causal relationship of T2DM with five mentioned infections' (sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy) susceptibility [odds ratio (OR) = 0.99999, p = 0.916; OR = 0.99986, p = 0.233; OR = 0.99973, p = 0.224; OR = 0.99997, p = 0.686; OR, 1.00002, p = 0.766]. Sensitivity analysis showed similar results, indicating the robustness of causality. There were no heterogeneity and pleiotropic bias.

Conclusion

T2DM would not be causally associated with high-frequency infectious diseases (including sepsis, SSTI, UTI, pneumonia, and GUI in pregnancy).

SUBMITTER: Wang H

PROVIDER: S-EPMC8435717 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study.

Wang Huachen H Guo Zheng Z Zheng Yulu Y Yu Chunyan C Hou Haifeng H Chen Bing B

Frontiers in genetics 20210830

<h4>Background</h4>In epidemiological studies, it has been proven that the occurrence of type 2 diabetes mellitus (T2DM) is related to an increased risk of infectious diseases. However, it is still unclear whether the relationship is casual.<h4>Methods</h4>We employed a two-sample Mendelian randomization (MR) to clarify the causal effect of T2DM on high-frequency infectious diseases: sepsis, skin and soft tissue infections (SSTIs), urinary tract infections (UTIs), pneumonia, and genito-urinary i ...[more]

PMID: 34527023

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Project description:BackgroundThe interplay between gut microbiome genera and inflammatory kidney-related diseases, such as nephrotic syndrome, glomerulonephritis, tubulo-interstitial nephritis, and chronic kidney disease, has been observed. However, the causal relationships between specific bacterial genera and these renal diseases have not been fully elucidated.ObjectiveTo investigate the potential causal links between different genera of the gut microbiome and the susceptibility to various renal conditions utilizing two-sample Mendelian randomization (MR) analyses.Materials and methodsGenome-wide association study (GWAS) summary statistics of gut microbiota and inflammatory kidney-related diseases were obtained from published GWASs. Two-sample MR analyses were conducted using methods including inverse-variance weighted (IVW), MR Egger, and others to identify potential causal links between gut microbial genera and renal conditions. Sensitivity analyses, including Cochran's Q test and the MR-PRESSO global test, were performed to validate the robustness of the results and detect horizontal pleiotropy. In addition, a reverse MR analysis was conducted to assess reverse causation possibilities.ResultsBy synthesizing insights from both primary and sensitivity analyses, this study unveiled critical associations of 12 bacterial genera with nephrotic syndrome, 7 bacterial genera with membranous nephropathy, 3 bacterial genera with glomerulonephritis, 4 bacterial genera with acute tubulo-interstitial nephritis, 6 bacterial genera with chronic tubulo-interstitial nephritis, and 7 bacterial genera with chronic kidney disease. Various genera were pinpointed as having either positive or negative causal relationships with these renal conditions, as evidenced by specific ranges of IVW-OR values (all P< 0.05). The congruence of the sensitivity analyses bolstered the primary findings, displaying no marked heterogeneity or horizontal pleiotropy. Notably, the reverse MR analysis with nephritis as the exposure did not reveal any causal relationships, thereby strengthening the resilience and validity of the primary associations.ConclusionThis study explored the causal associations between several gut microbial genera and the risk of several inflammatory kidney-related diseases, uncovering several associations between specific gut microbial genera and nephrotic syndrome, membranous nephropathy, glomerulonephritis, tubulo-interstitial nephritis, and chronic kidney disease. These findings enhance our understanding of the complex interplay between the gut microbiome and kidney diseases, and they will be beneficial for early diagnosis and subsequent treatment.

Project description:ObjectiveObservational studies have shown an association between systemic autoimmune disease (AD) and multiple malignancies. However, due to the difficulty indetermining the temporal nature of the order, their causal relationship remains elusive. Based on pooled data from a large population-wide genome-wide association study (GWAS), this study explores the genetic causality between systemic autoimmune disease and renal malignancy.MethodsWe took a series of quality control steps from a large-scale genome-wide association study to select single nucleotide polymorphisms (SNPs) associated with systemic autoimmune disease as instrumental variables(IVs) to analyze genetic causality with renal malignancies. Inverse variance weighting (IVW), MR- Egger, weighted median, simple model and weighted model were used for analysis. The results were mainly based on IVW (Random Effects), followed by sensitivity analysis. Inverse-Variance Weighted(IVW) and MR-Egger were used to test for heterogeneity. MR- Egger is also used for pleiotropic testing. A single SNP analysis was used to identify single nucleotide polymorphisms (SNPs) with potential impact. Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate causality, and sensitivity analysis was performed to evaluate pleiotropy and instrumental validity.ResultsAcute and subacute iridocylitis (P = 0.006, OR = 1.077), Ankylosing spondylitis (P = 0.002, OR = 1.051), and spondyloarthritis (P = 0.009, OR = 1.073) were positively associated with an increased risk of renal malignancy. Coxarthrosis (P = 0.008, OR = 0.483), Juvenile rheumatism (P = 0.011, OR = 0.897), and Systemic lupus erythematosus (P = 0.014, OR = 0.869) were negatively associated with an increased risk of renal malignancy. The results of sensitivity analysis were consistent without heterogeneity or pleiotropy.ConclusionOur study suggests a causal relationship between different systemic autoimmune diseases and renal malignancies. These findings prompt health care providers to take seriously the potential risk of systemic autoimmune disease and provide new insights into the genetics of kidney malignancies.

Project description:ObjectivePrior observational studies have reported that levels of sex hormones constitute a risk factor for the fracture. The aim of this study was to ascertain whether there is a causal relationship between the levels of sex hormones and the risk of fracture through Mendelian randomization (MR).MethodsSingle-nucleotide polymorphisms (SNPs) associated with two indicators of sex hormone levels, circulating sex hormone-binding globulin (SHBG) and bioavailable testosterone levels, as exposures were selected from a large genome-wide association study (GWAS) from UK Biobank. The summary statistics for 11 different types of fracture as outcomes from the FinnGen consortium. This study employed the two-sample MR approach. For the main analysis, the inverse-variance-weighted (IVW) method was utilized. To assess the heterogeneity of MR results, the IVW method and MR-Egger method were utilized. To evaluate potential pleiotropy, MR-Egger regression was conducted. Additionally, a leave-one-SNP-out test was performed to assess the robustness of MR results to the exclusion of any individual SNP.ResultsThe MR analyses demonstrated a conspicuous impact of SHBG on the risk of pathological fracture with osteoporosis (OP). We found that an increase of one standard deviation (SD) in SHBG correspondingly increased the risk of pathological fracture with OP [odds ratio (OR) 2.42, 95% confidence interval (CI), 1.52-3.85; p = 1.93 × 10-4 ]. The bioavailable testosterone showed the negative casual genetic associations with fractures of foot and forearm. An increase of one SD in the genetically predetermined bioavailable testosterone was associated with a reduction of 37% in the risk of fracture of foot (OR 0.63, 95% Cl 0.49 to 0.81; p = 3.37 × 10-4 ), as well as a 39% decrease in the risk of fracture of forearm (OR 0.61, 95% Cl 0.50 to 0.76; p = 5.40 × 10-6 ).ConclusionsOur study confirms that individuals experiencing elevated SHBG concentrations showed a major causal effect on pathological fracture with OP. High bioavailable testosterone levels play an important role in preventing the fractures of foot and forearm. Although increasing bioavailable testosterone and decreasing SHBG levels had no casual effect on most fractures in the general population, they are likely to have the most clinically relevant effect on certain fracture risk reduction.

Dataset Information

No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study.

Background

Methods

Results

Conclusion

Publications

No Casual Relationship Between T2DM and the Risk of Infectious Diseases: A Two-Sample Mendelian Randomization Study.

Similar Datasets

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