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 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.

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 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 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 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 A Mendelian randomization analysis of the relationship between cardioembolic risk factors and ischemic stroke

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Danyang Tian ◽  
Linjing Zhang ◽  
Zhenhuang Zhuang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Mendelian Randomization ◽  
P Wave ◽  
Cardioembolic Stroke ◽  
Large Artery ◽  
Weighted Analysis ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetically Determined

AbstractObservational studies have shown that several risk factors are associated with cardioembolic stroke. However, whether such associations reflect causality remains unknown. We aimed to determine whether established and provisional cardioembolic risk factors are causally associated with cardioembolic stroke. Genetic instruments for atrial fibrillation (AF), myocardial infarction (MI), electrocardiogram (ECG) indices and N-terminal pro-brain natriuretic peptide (NT-pro BNP) were obtained from large genetic consortiums. Summarized data of ischemic stroke and its subtypes were extracted from the MEGASTROKE consortium. Causal estimates were calculated by applying inverse-variance weighted analysis, weighted median analysis, simple median analysis and Mendelian randomization (MR)-Egger regression. Genetically predicted AF was significantly associated with higher odds of ischemic stroke (odds ratio (OR): 1.20, 95% confidence intervals (CI): 1.16–1.24, P = 6.53 × 10–30) and cardioembolic stroke (OR: 1.95, 95% CI: 1.85–2.06, P = 8.81 × 10–125). Suggestive associations were found between genetically determined resting heart rate and higher odds of ischemic stroke (OR: 1.01, 95% CI: 1.00–1.02, P = 0.005), large-artery atherosclerotic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.026) and cardioembolic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.028). There was no causal association of P‐wave terminal force in the precordial lead V1 (PTFVI), P-wave duration (PWD), NT-pro BNP or PR interval with ischemic stroke or any subtype.

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 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 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 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.

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