scholarly journals Genetically Predicted Type 2 Diabetes Mellitus Liability, Glycated Hemoglobin and Cardiovascular Diseases: A Wide-Angled Mendelian Randomization Study

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1644
Author(s):  
Bowen Liu ◽  
Amy M. Mason ◽  
Luanluan Sun ◽  
Emanuele Di Angelantonio ◽  
Dipender Gill ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
General Population ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Disease Outcomes ◽  
Artery Disease ◽  
Diagnosed Diabetes

(1) Aim: To investigate the causal effects of T2DM liability and glycated haemoglobin (HbA1c) levels on various cardiovascular disease outcomes, both in the general population and in non-diabetic individuals specifically. (2) Methods: We selected 243 variants as genetic instruments for T2DM liability and 536 variants for HbA1c. Linear Mendelian randomization analyses were performed to estimate the associations of genetically-predicted T2DM liability and HbA1c with 12 cardiovascular disease outcomes in 367,703 unrelated UK Biobank participants of European ancestries. We performed secondary analyses in participants without diabetes (HbA1c < 6.5% with no diagnosed diabetes), and in participants without diabetes or pre-diabetes (HbA1c < 5.7% with no diagnosed diabetes). (3) Results: Genetically-predicted T2DM liability was positively associated (p < 0.004, 0.05/12) with peripheral vascular disease, aortic valve stenosis, coronary artery disease, heart failure, ischaemic stroke, and any stroke. Genetically-predicted HbA1c was positively associated with coronary artery disease and any stroke. Mendelian randomization estimates generally shifted towards the null when excluding diabetic and pre-diabetic participants from analyses. (4) Conclusions: This genetic evidence supports causal effects of T2DM liability and HbA1c on a range of cardiovascular diseases, suggesting that improving glycaemic control could reduce cardiovascular risk in a general population, with greatest benefit in individuals with diabetes.

scholarly journals Causal effects of serum levels of n-3 or n-6 polyunsaturated fatty acids on coronary artery disease: Mendelian randomization study

2020 ◽  
Author(s):  
Sehoon Park ◽  
Soojin Lee ◽  
Yaerim Kim ◽  
Yeonhee Lee ◽  
Min Woo Kang ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Fatty Acids ◽  
Linoleic Acid ◽  
Coronary Artery ◽  
Polyunsaturated Fatty Acids ◽  
Lower Risk ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Weighted Median ◽  
Artery Disease

AbstractBackgroundAdditional studies on the causal effects of 3-n and 6-n polyunsaturated fatty acids (PUFAs) on the risk of coronary artery disease (CAD) are warranted.MethodsThis Mendelian randomization (MR) study utilized a genetic instrument developed from previous genome-wide association studies for various serum 3-n and 6-n PUFA levels. First, we calculated the allele scores for genetic predisposition of PUFAs in individuals of European ancestry in the UK Biobank data (N=337,129). The allele score-based MR was obtained by regressing the allele scores to CAD risks. Second, summary-level MR was performed with the CARDIoGRAMplusC4D data for CAD (N=184,305). The inverse variance-weighted or Wald ratio method was the main analysis for the summary-level MR, and when multiple single nucleotide polymorphisms were utilized (e.g., linoleic acid), MR-Egger and weighted median methods were implemented as sensitivity analyses.ResultsHigher genetically predicted eicosapentaenoic acid and dihomo-gamma-linolenic acid levels were significantly associated with a lower risk of CAD both in the allele-score-based and summary-level MR analyses. Higher allele scores for linoleic acid level were significantly associated with lower CAD risks, and in the summary-level MR, the causal estimates by the MR-Egger and weighted median methods also indicated that higher linoleic acid levels cause a lower risk of CAD. Arachidonic acid was the 6-n PUFA that showed significant causal estimates for a higher risk of CAD. Higher docosapentaenoic acid and adrenic acid levels showed inconsistent findings in the MR analysis results.ConclusionsThis study supports the causal effects of certain 3-n and 6-n PUFA types on the risk of CAD.

Genetically rheumatoid arthrits and risk of comorbidities: a Mendelian randomization study

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Fokina ◽  
J Fill ◽  
G Klappacher
Keyword(s):  
Rheumatoid Arthritis ◽  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Funding Source ◽  
Artery Disease ◽  
Genetically Determined ◽  
Genetic Instruments

Abstract Background Ample observational evidence indicates that patients with rheumatoid arthritis (RA) are at increased risk of developing comorbid conditions, in particular cardiovascular disease. The pathogenesis of these comorbidities is still largely unknown. For effective preventive measures, it would however be important to discriminate between those that are causally linked with rheumatoid arthritis and those that are the results of concomitant treatments or other confounding factors. Purpose Our objective was to explore whether genetically determined manifestation of RA was associated with any comorbidities, in particular cardiovascular disease, by conducting a 2-sample Mendelian randomization (MR) study on publicly available summary statistics from genome-wide association study (GWAS) consortia. Methods Genetic instruments for RA were obtained from a GWAS of 14,361 autoantibody-positive individuals with RA and 43,923 controls of European descent (Okada et al. 2014). The CARDIoGRAMplusC4D consortium comprising 60,801 cases with coronary artery disease and 123,504 controls was used to evaluate the associations with cardiovascular outcomes applying inverse variance–weighted meta-analysis, weighted-median analysis, Mendelian randomization–Egger regression, and multivariable Mendelian randomization. Genetic instruments for RA were further tested for association with other etiologically related traits by using publicly available GWAS data. Results Genetic predisposition to RA was not associated with higher risk of coronary artery disease (beta coefficient [b] ± standard error [se] = 0.02±0.03; P=0.4913), and myocardial infarction (b ± se = 0.03±0.03; P=0.3338). In contrast, IgA nephropathy (b ± se = 0.47±0.18; P=0.0225) and triglyceride levels were significantly related as outcomes to genetically determined RA as exposure. Other significantly related outcomes were the manifestation of squamous cell lung cancer (b ± se = 0.17±0.08; P=0.0496), serous ovarian cancer (b ± se = 0.13±0.05; P=0.0202), and prostate cancer (b ± se = 0.06±0.02; P=0.0041). Conclusions Despite the high prevalence of coronary artery disease and myocardial infarction among RA patients in observational studies, cardiovascular outcomes were not significantly associated with RA by Mendelian randomization. This paradox might partly be explained by the traits such as IgA nephropathy and elevated triglyceride levels that could act as mediators for the increased cardiovascular risk by their causal link with genetically determined RA. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Medical University of Vienna, Austria

scholarly journals Relationship Between Blood Pressure and Incident Cardiovascular Disease

Hypertension ◽  
2021 ◽  
Author(s):  
Rainer Malik ◽  
Marios K. Georgakis ◽  
Marijana Vujkovic ◽  
Scott M. Damrauer ◽  
Paul Elliott ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diastolic Blood Pressure ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Hazard Ratio ◽  
European Ancestry ◽  
Artery Disease

Observational studies exploring whether there is a nonlinear effect of blood pressure on cardiovascular disease (CVD) risk are hindered by confounding. This limitation can be overcome by leveraging randomly allocated genetic variants in nonlinear Mendelian randomization analyses. Based on their association with blood pressure traits in a genome-wide association study of 299 024 European ancestry individuals, we selected 253 genetic variants to proxy the effect of modifying systolic and diastolic blood pressure. Considering the outcomes of incident coronary artery disease, stroke and the combined outcome of CVD, linear and nonlinear Mendelian randomization analyses were performed on 255 714 European ancestry participants without a history of CVD or antihypertensive medication use. There was no evidence favoring nonlinear relationships of genetically proxied systolic and diastolic blood pressure with the cardiovascular outcomes over linear relationships. For every 10-mm Hg increase in genetically proxied systolic blood pressure, risk of incident CVD increased by 49% (hazard ratio, 1.49 [95% CI, 1.38–1.61]), with similar estimates obtained for coronary artery disease (hazard ratio, 1.50 [95% CI, 1.38–1.63]) and stroke (hazard ratio, 1.44 [95% CI, 1.22–1.70]). Genetically proxied blood pressure had a similar relationship with CVD in men and women. These findings provide evidence to support that even for individuals who do not have elevated blood pressure, public health interventions achieving persistent blood pressure reduction will be of considerable benefit in the primary prevention of CVD.

scholarly journals The impact of growth differentiation factor 15 on the risk of cardiovascular disease: evidence from Mendelian randomization study

2020 ◽  
Author(s):  
Zhuo Wang ◽  
Fangkun Yang ◽  
Menghuai Ma ◽  
Qinyi Bao ◽  
Jinlian Shen ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Atrial Fibrillation ◽  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Cardioembolic Stroke ◽  
Growth Differentiation Factor 15 ◽  
Artery Disease

Abstract Background: Growth differentiation factor 15(GDF-15) concentration is apparently associated with cardiovascular disease, but whether there is a causal relationship has not been testified. Methods: We utilized Mendelian randomization to assess the function of GDF-15 in incidence of cardiovascular disease. The single-nucleotide polymorphism- GDF-15 association evaluations came from meta-analysis of genome-wide association study (GWAS). Besides inverse-variance weighted, MR-Egger test and weighted median method were applied to examine sensitivity. Results: Based on the instruments, GDF-15 level linked to the increasing risk of cardioembolic stroke (OR 1.09 per SD increase, 95% CI 1.01, 1.19) , atrial fibrillation (OR 1.03 per SD increase, 95% CI 1.0, 1.06), coronary artery disease (OR 0.94 per SD increase, 95% CI 0.89, 0.99) and myocardial infarction (OR 0.94 per SD increase, 95% CI 0.90, 0.98). However, the significant causal relationship between GDF-15 and the other cardiovascular diseases was not found in our study. Conclusions: The result suggested that GDF-15 was causally associated with the risk of cardioembolic stroke,atrial fibrillation, coronary artery disease and myocardial infarction, providing us conceivable strategies to alleviate the burden of cardiovascular disease.

scholarly journals The impact of growth differentiation factor 15 on the risk of cardiovascular disease: evidence from Mendelian randomization study

2020 ◽  
Author(s):  
Zhuo Wang ◽  
Fangkun Yang ◽  
Menghuai Ma ◽  
Qinyi Bao ◽  
Jinlian Shen ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Atrial Fibrillation ◽  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Cardioembolic Stroke ◽  
Growth Differentiation Factor 15 ◽  
Artery Disease

Abstract Background: Growth differentiation factor 15(GDF-15) concentration is apparently associated with cardiovascular disease, but whether there is a causal relationship has not been testified. Methods: We utilized Mendelian randomization to assess the function of GDF-15 in incidence of cardiovascular disease. The single-nucleotide polymorphism- GDF-15 association evaluations came from meta-analysis of genome-wide association study (GWAS). Besides inverse-variance weighted, MR-Egger test and weighted median method were applied to examine sensitivity. Results: Based on the instruments, GDF-15 level linked to the increasing risk of cardioembolic stroke (1.06, OR 1.09 per SD increase, 95% CI 1.01, 1.19) , atrial fibrillation (OR 1.03 per SD increase, 95% CI 1.0, 1.06), coronary artery disease (OR 0.94 per SD increase, 95% CI 0.89, 0.99) and myocardial infarction (OR 0.94 per SD increase, 95% CI 0.90, 0.98). However, the significant causal relationship between GDF-15 and the other cardiovascular diseases was not found in our study. Conclusions: The result suggested that GDF-15 was causally associated with the risk of cardioembolic stroke,atrial fibrillation, coronary artery disease and myocardial infarction, providing us conceivable strategies to alleviate the burden of cardiovascular disease.

scholarly journals Causal Effects of Serum Levels of n-3 or n-6 Polyunsaturated Fatty Acids on Coronary Artery Disease: Mendelian Randomization Study

Nutrients ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1490
Author(s):  
Sehoon Park ◽  
Soojin Lee ◽  
Yaerim Kim ◽  
Yeonhee Lee ◽  
Min Woo Kang ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Fatty Acids ◽  
Linoleic Acid ◽  
Coronary Artery ◽  
Polyunsaturated Fatty Acids ◽  
Lower Risk ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
European Ancestry ◽  
Artery Disease

We aimed to investigate the causal effects of n-3 and n-6 polyunsaturated fatty acids (PUFAs) on the risk of coronary artery disease (CAD) through Mendelian randomization (MR) analysis. This MR study utilized a genetic instrument developed from previous genome-wide association studies for various serum n-3 and n-6 PUFA levels. First, we calculated the allele scores for genetic predisposition of PUFAs in individuals of European ancestry in the UK Biobank data (N = 337,129). The allele score-based MR was obtained by regressing the allele scores to CAD risks. Second, summary-level MR was performed with the CARDIoGRAMplusC4D data for CAD (N = 184,305). Higher genetically predicted eicosapentaenoic acid and dihomo-gamma-linolenic acid levels were significantly associated with a lower risk of CAD both in the allele-score-based and summary-level MR analyses. Higher allele scores for linoleic acid level were significantly associated with lower CAD risks, and in the summary-level MR, the causal estimates by the pleiotropy-robust MR methods also indicated that higher linoleic acid levels cause a lower risk of CAD. Arachidonic acid showed significant causal estimates for a higher risk of CAD. This study supports the causal effects of certain n-3 and n-6 PUFA types on the risk of CAD.

scholarly journals Separating the direct effects of risk factors for atherosclerotic cardiovascular disease from those mediated by type 2 diabetes

2021 ◽  
Author(s):  
Venexia Walker ◽  
Marijana Vujkovic ◽  
Alice R Carter ◽  
Neil M Davies ◽  
Miriam Udler ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Atherosclerotic Cardiovascular Disease ◽  
Peripheral Artery ◽  
Artery Disease

Background: Type 2 diabetes and atherosclerotic cardiovascular disease share several risk factors. However, it is unclear whether the effect of these risk factors on liability to atherosclerotic cardiovascular disease is independent of their effect on liability to type 2 diabetes. Methods: We performed univariate Mendelian randomization to quantify the effects of continuous risk factors from the IEU OpenGWAS database on liability to three outcomes: type 2 diabetes, coronary artery disease, and peripheral artery disease, as well as the effects of liability to type 2 diabetes on the risk factors. We also performed two-step Mendelian randomization for mediation to estimate the mediating pathways between the risk factors, liability to type 2 diabetes, and liability to the atherosclerotic cardiovascular disease outcomes where possible. Results: We found evidence for 53 risk factors as causes of liability to coronary artery disease, including eight which were causes of liability to type 2 diabetes only and four which were consequences only. Except for fasting insulin and hip circumference, the direct and total effects from the two-step Mendelian randomization were similar. This suggests that the combination of these risk factors with liability to type 2 diabetes was unlikely to alter liability to coronary artery disease beyond their individual effects. We also found 13 risk factors that were causes of liability peripheral artery disease, including six which were causes of liability to type 2 diabetes only and four which were consequences only. Again, the direct and total effects were similar for these ten risk factors apart from fasting insulin. Conclusions: Most risk factors were likely to affect liability to atherosclerotic cardiovascular disease independently of their relationship with liability to type 2 diabetes. Control of modifiable risk factors therefore remains important for reducing atherosclerotic cardiovascular disease risk regardless of patient liability to type 2 diabetes.

Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Computational Models ◽  
Genetic Interaction ◽  
Association Studies ◽  
Genetic Interactions ◽  
Computational Techniques ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

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