scholarly journals Mendelian randomization analysis of the association between human blood cell traits and uterine polyps

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shuliu Sun ◽  
Yan Liu ◽  
Lanlan Li ◽  
Minjie Jiao ◽  
Yufen Jiang ◽  
...  
Keyword(s):  
Human Blood ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Random Effect ◽  
Sensitivity Analyses ◽  
Endometrial Polyps ◽  
Inverse Variance ◽  
Weighted Median ◽  
The Uk ◽  
Uterine Polyps

AbstractHuman blood cells (HBCs) play essential roles in multiple biological processes but their roles in development of uterine polyps are unknown. Here we implemented a Mendelian randomization (MR) analysis to investigate the effects of 36 HBC traits on endometrial polyps (EPs) and cervical polyps (CPs). The random-effect inverse-variance weighted method was adopted as standard MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Genetic instruments of HBC traits was extracted from a large genome-wide association study of 173,480 individuals, while data for EPs and CPs were obtained from the UK Biobank. All samples were Europeans. Using genetic variants as instrumental variables, our study found that both eosinophil count (OR 0.85, 95% CI 0.79–0.93, P = 1.06 × 10−4) and eosinophil percentage of white cells (OR 0.84, 95% CI 0.77–0.91, P = 2.43 × 10−5) were associated with decreased risk of EPs. The results were robust in sensitivity analyses and no evidences of horizontal pleiotropy were observed. While we found no significant associations between HBC traits and CPs. Our findings suggested eosinophils might play important roles in the pathogenesis of EPs. Besides, out study provided novel insight into detecting uterine polyps biomarkers using genetic epidemiology approaches.

scholarly journals Carnitine and COVID-19 Susceptibility and Severity: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Chunyu Li ◽  
Ruwei Ou ◽  
Qianqian Wei ◽  
Huifang Shang
Keyword(s):  
Causal Relationship ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Carnitine Level ◽  
Standard Deviation Increase ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetically Determined

Background: Carnitine, a potential substitute or supplementation for dexamethasone, might protect against COVID-19 based on its molecular functions. However, the correlation between carnitine and COVID-19 has not been explored yet, and whether there exists causation is unknown.Methods: A two-sample Mendelian randomization (MR) analysis was conducted to explore the causal relationship between carnitine level and COVID-19. Significant single nucleotide polymorphisms from genome-wide association study on carnitine (N = 7,824) were utilized as exposure instruments, and summary statistics of the susceptibility (N = 1,467,264), severity (N = 714,592) and hospitalization (N = 1,887,658) of COVID-19 were utilized as the outcome. The causal relationship was evaluated by multiplicative random effects inverse variance weighted (IVW) method, and further verified by another three MR methods including MR Egger, weighted median, and weighted mode, as well as extensive sensitivity analyses.Results: Genetically determined one standard deviation increase in carnitine amount was associated with lower susceptibility (OR: 0.38, 95% CI: 0.19–0.74, P: 4.77E−03) of COVID-19. Carnitine amount was also associated with lower severity and hospitalization of COVID-19 using another three MR methods, though the association was not significant using the IVW method but showed the same direction of effect. The results were robust under all sensitivity analyses.Conclusions: A genetic predisposition to high carnitine levels might reduce the susceptibility and severity of COVID-19. These results provide better understandings on the role of carnitine in the COVID-19 pathogenesis, and facilitate novel therapeutic targets for COVID-19 in future clinical trials.

scholarly journals Periodontal disease increases the host susceptibility to COVID-19 and its severity: a Mendelian randomization study

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Yi Wang ◽  
Hui Deng ◽  
Yihuai Pan ◽  
Lijian Jin ◽  
Rongdang Hu ◽  
...  
Keyword(s):  
Periodontal Disease ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Host Susceptibility ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median ◽  
First Time

Abstract Background Emerging evidence shows that periodontal disease (PD) may increase the risk of Coronavirus disease 2019 (COVID-19) complications. Here, we undertook a two-sample Mendelian randomization (MR) study, and investigated for the first time the possible causal impact of PD on host susceptibility to COVID-19 and its severity. Methods Summary statistics of COVID-19 susceptibility and severity were retrieved from the COVID-19 Host Genetics Initiative and used as outcomes. Single nucleotide polymorphisms associated with PD in Genome-wide association study were included as exposure. Inverse-variance weighted (IVW) method was employed as the main approach to analyze the causal relationships between PD and COVID-19. Three additional methods were adopted, allowing the existence of horizontal pleiotropy, including MR-Egger regression, weighted median and weighted mode methods. Comprehensive sensitivity analyses were also conducted for estimating the robustness of the identified associations. Results The MR estimates showed that PD was significantly associated with significantly higher susceptibility to COVID-19 using IVW (OR = 1.024, P = 0.017, 95% CI 1.004–1.045) and weighted median method (OR = 1.029, P = 0.024, 95% CI 1.003–1.055). Furthermore, it revealed that PD was significantly linked to COVID-19 severity based on the comparison of hospitalization versus population controls (IVW, OR = 1.025, P = 0.039, 95% CI 1.001–1.049; weighted median, OR = 1.030, P = 0.027, 95% CI 1.003–1.058). No such association was observed in the cohort of highly severe cases confirmed versus those not hospitalized due to COVID-19. Conclusions We provide evidence on the possible causality of PD accounting for the susceptibility and severity of COVID-19, highlighting the importance of oral/periodontal healthcare for general wellbeing during the pandemic and beyond.

scholarly journals Causal Associations between Serum Urea and Cancer: A Mendelian Randomization Study

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 498
Author(s):  
Yandi Sun ◽  
Jingjia Li ◽  
Zihao Qu ◽  
Ze Yang ◽  
Xueyao Jia ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Serum Urea ◽  
Urea Level ◽  
Genome Wide ◽  
Inverse Variance ◽  
Weighted Median ◽  
First Time

Urea is largely derived from the urea cycle reactions through hepatic detoxification of free ammonia and cleared by urination, and the serum urea level is a crucial medical indicator for measuring the kidney function in patients with nephropathy; however, investigative revelations pointing to the serum urea level as a risk factor for cancer are very scarce, and relevant studies are restricted by potential biases. We aimed to explore the causal relationships of the serum urea level with cancer development by focusing on renal cell carcinoma (RCC) using the Mendelian randomization (MR) analyses. Summary estimates were collected from the inverse-variance weighted (IVW) method based on six single nucleotide polymorphisms (SNPs). The selected SNPs related to the serum urea were obtained from a large genome-wide association study (GWAS) of 13,312 European participants. The summary statistics of RCC were also available from public databases (IARC, n = 5219 cases, n = 8011 controls). Sensitivity analyses included the weighted median and MR-Egger methods. Serum urea was inversely associated with RCC in females (effect = 1.93; 95% CI: 1.24 to 3.01; p = 0.004) but exhibited null association with RCC in males, breast cancer (BRCA) in both genders and prostate cancer (PCa) in males. Similar conclusions were also drawn from the weighted median and MR-Egger. These findings reveal an intriguing link between serum urea and cancer risks for the very first time. Without ambiguity, the serum urea is causatively related to RCC specifically in females, although the mechanism(s) by which urea is involved in RCC development remains to be experimentally/clinically investigated. Our studies may well provide novel insights for RCC diagnosis, intervention and/or therapy.

scholarly journals Relationship of Soluble Interleukin-6 Receptors With Asthma: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Yoshihiko Raita ◽  
Zhaozhong Zhu ◽  
Carlos A. Camargo ◽  
Robert J. Freishtat ◽  
Debby Ngo ◽  
...  
Keyword(s):  
Interleukin 6 ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Study Data ◽  
Sensitivity Analyses ◽  
Receptor Level ◽  
Inverse Variance ◽  
Interleukin 6 Receptor ◽  
The Uk

Purpose: Emerging evidence suggests a potential role of interleukin-6 pathways—trans-signaling with soluble interleukin-6 receptors—in the asthma pathobiology. Despite the evidence for their associations with asthma, the causal role of soluble interleukin-6 receptors remains uncertain. We investigated the relations of soluble interleukin-6 receptors with asthma and its major phenotypes.Methods: We conducted a two-sample Mendelian randomization study. As genetic instruments, we selected 33 independent cis-acting variants strongly associated with the level of plasma soluble interleukin-6 receptor in the INTERVAL study. To investigate the association of variants with asthma and its phenotypes, we used genome-wide association study data from the UK Biobank. We combined variant-specific causal estimates by the inverse-variance weighted method for each outcome.Results: Genetically-instrumented soluble interleukin-6 receptor level was associated with a significantly higher risk of overall asthma (OR per one standard deviation increment in inverse-rank normalized soluble interleukin-6 receptor level, 1.02; 95%CI, 1.01–1.03; P = 0.004). Sensitivity analyses demonstrated consistent results and indicated no directional pleiotropy—e.g., MR-Egger (OR, 1.03; 95%CI, 1.01–1.05; P = 0.002; Pintercept =0.37). In the stratified analysis, the significant association persisted across asthma phenotypes—e.g., childhood asthma (OR, 1.05; 95%CI, 1.02–1.08; P < 0.001) and obese asthma (OR, 1.02; 95%CI 1.01–1.03; P = 0.007). Sensitivity analysis using 16 variants selected with different thresholds also demonstrated significant associations with overall asthma and its phenotypes.Conclusion: Genetically-instrumented soluble interleukin-6 receptor level was causally associated with modestly but significantly higher risks of asthma and its phenotypes. Our observations support further investigations into identifying specific endotypes in which interleukin-6 pathways may play major roles.

scholarly journals Using a Two-Sample Mendelian Randomization Method in Assessing the Causal Relationships Between Human Blood Metabolites and Heart Failure

2021 ◽  
Vol 8 ◽  
Author(s):  
Zixian Wang ◽  
Shiyu Chen ◽  
Qian Zhu ◽  
Yonglin Wu ◽  
Guifeng Xu ◽  
...  
Keyword(s):  
Heart Failure ◽  
Human Blood ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Blood Metabolites ◽  
Causal Relationships

Background: Heart failure (HF) is the main cause of morbidity and mortality worldwide, and metabolic dysfunction is an important factor related to HF pathogenesis and development. However, the causal effect of blood metabolites on HF remains unclear.Objectives: Our chief aim is to investigate the causal relationships between human blood metabolites and HF risk.Methods: We used an unbiased two-sample Mendelian randomization (MR) approach to assess the causal relationships between 486 human blood metabolites and HF risk. Exposure information was obtained from Sample 1, which is the largest metabolome-based genome-wide association study (mGWAS) data containing 7,824 Europeans. Outcome information was obtained from Sample 2, which is based on the results of a large-scale GWAS meta-analysis of HF and contains 47,309 cases and 930,014 controls of Europeans. The inverse variance weighted (IVW) model was used as the primary two-sample MR analysis method and followed the sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis.Results: We observed that 11 known metabolites were potentially related to the risk of HF after using the IVW method (P < 0.05). After adding another four MR models and performing sensitivity analyses, we found a 1-SD increase in the xenobiotics 4-vinylphenol sulfate was associated with ~22% higher risk of HF (OR [95%CI], 1.22 [1.07–1.38]).Conclusions: We revealed that the 4-vinylphenol sulfate may nominally increase the risk of HF by 22% after using a two-sample MR approach. Our findings may provide novel insights into the pathogenesis underlying HF and novel strategies for HF prevention.

scholarly journals Genetically Determined Levels of Serum Metabolites and Risk of Neuroticism: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Li Qian ◽  
Yajuan Fan ◽  
Fengjie Gao ◽  
Binbin Zhao ◽  
Bin Yan ◽  
...  
Keyword(s):  
Uric Acid ◽  
Lower Risk ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Strong Predictor ◽  
Causal Effects ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Inverse Variance

Abstract Background Neuroticism is a strong predictor for a variety of social and behavioral outcomes, but the etiology is still unknown. Our study aims to provide a comprehensive investigation of causal effects of serum metabolome phenotypes on risk of neuroticism using Mendelian randomization (MR) approaches. Methods Genetic associations with 486 metabolic traits were utilized as exposures, and data from a large genome-wide association study of neuroticism were selected as outcome. For MR analysis, we used the standard inverse-variance weighted (IVW) method for primary MR analysis and 3 additional MR methods (MR-Egger, weighted median, and MR pleiotropy residual sum and outlier) for sensitivity analyses. Results Our study identified 31 metabolites that might have causal effects on neuroticism. Of the 31 metabolites, uric acid and paraxanthine showed robustly significant association with neuroticism in all MR methods. Using single nucleotide polymorphisms as instrumental variables, a 1-SD increase in uric acid was associated with approximately 30% lower risk of neuroticism (OR: 0.77; 95% CI: 0.62–0.95; PIVW = 0.0145), whereas a 1-SD increase in paraxanthine was associated with a 7% higher risk of neuroticism (OR: 1.07; 95% CI: 1.01–1.12; PIVW = .0145). Discussion Our study suggested an increased level of uric acid was associated with lower risk of neuroticism, whereas paraxanthine showed the contrary effect. Our study provided novel insight by combining metabolomics with genomics to help understand the pathogenesis of neuroticism.

scholarly journals Causal relationships between genetically determined metabolites and human intelligence: A Mendelian randomization study

2020 ◽  
Author(s):  
Jian Yang ◽  
Binbin Zhao ◽  
Li Qian ◽  
Fengjie Gao ◽  
Yanjuan Fan ◽  
...  
Keyword(s):  
Complex Traits ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Human Intelligence ◽  
Causal Relationships ◽  
Biological Mechanisms ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetic And Environmental Factors ◽  
Genetically Determined

Abstract Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (P IVW = 9 · 25×10 -5 ). The causal relationship was robust when sensitivity analyses were applied (P MR-Egger = 0 · 0001, P Weighted median = 6 · 29×10 -6 , P MR-PRESSO = 0 · 0007), and no evidence of horizontal pleiotropy was observed. Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

scholarly journals Causal relationships between genetically determined metabolites and human intelligence: a Mendelian randomization study

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Jian Yang ◽  
Binbin Zhao ◽  
Li Qian ◽  
Fengjie Gao ◽  
Yanjuan Fan ◽  
...  
Keyword(s):  
Complex Traits ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Human Intelligence ◽  
Causal Relationships ◽  
Biological Mechanisms ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetic And Environmental Factors ◽  
Genetically Determined

AbstractIntelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (PIVW = 9.25 × 10–5). The causal relationship was robust when sensitivity analyses were applied (PMR-Egger = 0.0001, PWeighted median = 6.29 × 10–6, PMR-PRESSO = 0.0007), and repeated analysis yielded consistent result (PIVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

scholarly journals Elucidation of a Causal Relationship Between Platelet Count and Hypertension: A Bi-Directional Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Po-Chun Chiu ◽  
Amrita Chattopadhyay ◽  
Meng-Chun Wu ◽  
Tzu-Hung Hsiao ◽  
Ching-Heng Lin ◽  
...  
Keyword(s):  
Platelet Count ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Exact Nature ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Inverse Variance ◽  
Weighted Median

Hypertension has been reported as a major risk factor for diseases such as cardiovascular disease, and associations between platelet activation and risk for hypertension are well-established. However, the exact nature of causality between them remains unclear. In this study, a bi-directional Mendelian randomization (MR) analysis was conducted on 15,996 healthy Taiwanese individuals aged between 30 and 70 years from the Taiwan Biobank, recorded between 2008 and 2015. The inverse variance weighted (IVW) method was applied to determine the causal relationship between platelet count and hypertension with single nucleotide polymorphisms as instrumental variables (IVs). Furthermore, to check for pleiotropy and validity of the IVs, sensitivity analyses were performed using the MR-Egger, weighted median and simple median methods. This study provided evidence in support of a positive causal effect of platelet count on the risk of hypertension (odds ratio: 1.149, 95% confidence interval: 1.131–1.578, P < 0.05), using the weighted median method. A significant causal effect of platelet count on hypertension was observed using the IVW method. No pleiotropy was observed. The causal effect of hypertension on platelet count was found to be non-significant. Therefore, the findings from this study provide evidence that higher platelet count may have a significant causal effect on the elevated risk of hypertension for the general population of Taiwan.

scholarly journals Causal relationships between genetically determined metabolites and human intelligence: A Mendelian randomization study

2020 ◽  
Author(s):  
Jian Yang ◽  
Binbin Zhao ◽  
Li Qian ◽  
Fengjie Gao ◽  
Yanjuan Fan ◽  
...  
Keyword(s):  
Complex Traits ◽  
Mendelian Randomization ◽  
Sensitivity Analyses ◽  
Human Intelligence ◽  
Causal Relationships ◽  
Biological Mechanisms ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetic And Environmental Factors ◽  
Genetically Determined

Abstract Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (PIVW = 9·25 × 10− 5). The causal relationship was robust when sensitivity analyses were applied (PMR−Egger = 0·0001, PWeighted median = 6·29 × 10− 6, PMR−PRESSO = 0·0007), and no evidence of horizontal pleiotropy was observed. Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

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