Negative Effects of Age at Menarche on Risk of Cardiometabolic Diseases in Adulthood: A Mendelian Randomization Study

2019 ◽  
Vol 105 (2) ◽  
pp. 515-522 ◽  
Author(s):  
Min Cao ◽  
Bin Cui
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Age At Menarche ◽  
Model Assessment ◽  
Cardiometabolic Diseases ◽  
Genome Wide ◽  
Artery Disease

Abstract Context Observational studies have demonstrated that early menarche is associated with cardiometabolic diseases, but confounding factors make it difficult to infer causality. Objective We used Mendelian randomization (MR) to examine whether age at menarche (AAM) is causally associated with type 2 diabetes (T2D), coronary artery disease (CAD) and cardiometabolic traits. Design and Methods A 2-sample MR analysis was conducted using genome-wide association study (GWAS) summary statistics from the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) consortium (n = 159 208) for T2D and the Coronary Artery Disease Genome-wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CARDIoGRAMplusC4D) consortium (n = 184 305) for CAD. We used 122 instrumental variables (IVs) extracted from a published GWAS meta-analysis incorporating 182 416 women to determine the causal effect of AAM on cardiometabolic diseases, treating childhood and adult body mass index (BMI) as the confounders. Sensitivity analyses were also performed to detect the pleiotropy of the IVs. Results Employing the MR approach, we found that later AAM was associated with decreased risk of CAD (OR, 0.92 [95% CI, 0.88-0.96]; P = 2.06 × 10–4) in adults, as well as lower blood levels of log fasting insulin, log homeostatic model assessment of insulin resistance (HOMA-IR), log HOMA of β-cell function (HOMA-B), triglycerides, and diastolic blood pressure, but higher blood level of high-density lipoprotein. However, the associations were substantially attenuated after excluding BMI-related variants. MR analyses provide little evidence on the causal effect between AAM and T2D. Conclusions Our findings showed that AAM did not appear to have a causal effect on the risk of cardiometabolic diseases in adult life, as their associations observed in epidemiological studies might be largely mediated through excessive adiposity. We propose adiposity might be a primary target in future intervention strategy.

scholarly journals Desaturase Activity and the Risk of Type 2 Diabetes and Coronary Artery Disease: A Mendelian Randomization Study

Nutrients ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2261 ◽  
Author(s):  
Susanne Jäger ◽  
Rafael Cuadrat ◽  
Per Hoffmann ◽  
Clemens Wittenbecher ◽  
Matthias B. Schulze
Keyword(s):  
Type 2 Diabetes ◽  
Coronary Artery Disease ◽  
Fatty Acids ◽  
Coronary Artery ◽  
Cardiometabolic Risk ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Genome Wide ◽  
Artery Disease

Estimated Δ5-desaturase (D5D) and Δ6-desaturase (D6D) are key enzymes in metabolism of polyunsaturated fatty acids (PUFA) and have been associated with cardiometabolic risk; however, causality needs to be clarified. We applied two-sample Mendelian randomization (MR) approach using a representative sub-cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam Study and public data from DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) genome-wide association studies (GWAS). Furthermore, we addressed confounding by linkage disequilibrium (LD) as all instruments from FADS1 (encoding D5D) are in LD with FADS2 (encoding D6D) variants. Our univariable MRs revealed risk-increasing total effects of both, D6D and D5D on type 2 diabetes (T2DM) risk; and risk-increasing total effect of D6D on risk of coronary artery disease (CAD). The multivariable MR approach could not unambiguously allocate a direct causal effect to either of the individual desaturases. Our results suggest that D6D is causally linked to cardiometabolic risk, which is likely due to downstream production of fatty acids and products resulting from high D6D activity. For D5D, we found indication for causal effects on T2DM and CAD, which could, however, still be confounded by LD.

Associations of observational and genetically determined caffeine intake with coronary artery disease and diabetes

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
A Said ◽  
Y.J Van De Vegte ◽  
N Verweij ◽  
P Van Der Harst
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Cox Regression ◽  
Caffeine Intake ◽  
Uk Biobank ◽  
Genome Wide ◽  
Artery Disease ◽  
Genetically Determined

Abstract Background Caffeine is the most widely consumed psychostimulant and is associated with lower risk of coronary artery disease (CAD) and type 2 diabetes (T2D). However, whether these associations are causal remains unknown. Objectives This study aimed to identify genetic variants associated with caffeine intake, and to investigate possible causal links between genetically determined caffeine intake and CAD or T2D. Additionally, we aimed to replicate previous observational findings between caffeine intake and CAD or T2D. Methods Genome wide associated studies (GWAS) were performed on caffeine intake from coffee, tea or both in 407,072 UK Biobank participants. Identified variants were used in a two-sample Mendelian randomization (MR) approach to investigate evidence for causal links between caffeine intake and CAD in CARDIoGRAMplusC4D (60,801 cases; 123,504 controls) or T2D in DIAGRAM (26,676 cases; 132,532 controls). Observational associations were tested within UK Biobank using Cox regression analyses. Results Moderate observational caffeine intakes from coffee or tea were associated with lower risks of CAD or T2D compared to no or high intake, with the lowest risks at intakes of 120–180 mg/day from coffee for CAD (HR=0.77 [95% CI: 0.73–0.82; P<1e-16]), and 300–360 mg/day for T2D (HR=0.76 [95% CI: 0.67–0.86]; P=1.57e-5). GWAS identified 51 novel genetic loci associated with caffeine intake, enriched for central nervous system genes. In contrast to observational analyses, MR analyses in CARDIoGRAMplusC4D and DIAGRAM yielded no evidence for causal links between caffeine intake and the development of CAD or T2D. Conclusions MR analyses indicate caffeine intake might not protect against CAD or T2D, despite protective associations in observational analyses. Manhattan_plot_CaffeineIntake Funding Acknowledgement Type of funding source: None

scholarly journals Mendelian randomization analyses reveal mediating factors of the causal effect of height on coronary artery disease

2021 ◽  
Author(s):  
Daniel Hui ◽  
Christopher S. Thom ◽  
Kimberly Lorenz ◽  
Scott M. Damrauer ◽  
Themistocles L. Assimes ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Lung Function ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Multivariable Analysis ◽  
Inverse Correlation ◽  
Artery Disease ◽  
Cad Risk

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested evidence that this association may be causal. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized the largest set of genetic instruments for human stature to date, comprising >2,000 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 2.1x10-2). We observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest that height does not add meaningful clinical impact on CAD risk prediction beyond established risk factors.

Abstract 447: Deep Transcriptomic Analysis of Human Vascular Cells Identifies Risk Genes for Common Vascular Diseases

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Sylvia T Nurnberg ◽  
YoSon Park ◽  
Jordi Vaquero-Garcia ◽  
Milos Pjanic ◽  
Susanna Elwyn ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Genetic Susceptibility ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome ◽  
Allele Specific ◽  
Artery Disease ◽  
Shared Genetic

The most recent Genome-wide Association Study (GWAS) meta-analysis has reported a total of 58 genomic loci to be statistically significantly associated with genetic susceptibility to Coronary Artery Disease (CAD) (Consortium, 2015). Many of these loci also associate with other phenotypes, with the majority being lipid traits (Tada et al., 2014). But also hypertension, stroke (Dichgans et al., 2014) and migraine (Pickrell et al., 2016) appear to share genetic determinants with CAD. To functionally annotate the genomic loci harboring these association SNPs we sequenced the transcriptomes of 20 same donor human coronary artery endothelial (EC) and smooth muscle cell (SMC) lines. Deep RNA-Sequencing was used to assess Differential Gene Expression, Differential Splicing and Allele-Specific Expression. Focusing on GWAS loci for vascular phenotypes (CAD, stroke, migraine) we identified genes which display allele-specific differences in mRNA expression or splicing. We propose these genes as suitable targets for follow up studies. Consortium, C.A.D. (2015). A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nature genetics 47, 1121-1130. Tada, H., Won, H.H., Melander, O., Yang, J., Peloso, G.M., and Kathiresan, S. (2014). Multiple associated variants increase the heritability explained for plasma lipids and coronary artery disease. Circulation Cardiovascular genetics 7, 583-587. Dichgans, M., Malik, R., Konig, I.R., Rosand, J., Clarke, R., Gretarsdottir, S., Thorleifsson, G., Mitchell, B.D., Assimes, T.L., Levi, C., et al. (2014). Shared genetic susceptibility to ischemic stroke and coronary artery disease: a genome-wide analysis of common variants. Stroke; a journal of cerebral circulation 45, 24-36. Pickrell, J.K., Berisa, T., Liu, J.Z., Segurel, L., Tung, J.Y., and Hinds, D.A. (2016). Detection and interpretation of shared genetic influences on 42 human traits. Nature genetics 48, 709-717.

Rheumatoid Arthritis and Coronary Artery Disease: Genetic Analyses Do Not Support a Causal Relation

2016 ◽  
Vol 44 (1) ◽  
pp. 4-10 ◽  
Author(s):  
Henning Jansen ◽  
Christina Willenborg ◽  
Wolfgang Lieb ◽  
Lingyao Zeng ◽  
Paola Gloria Ferrario ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Inflammatory Diseases ◽  
Causal Relation ◽  
Meta Analysis ◽  
Density Lipoprotein ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Artery Disease

Objective.Inflammatory diseases, specifically rheumatoid arthritis (RA), are assumed to increase the risk of coronary artery disease (CAD). More recently, multiple single-nucleotide polymorphisms (SNP) associated with RA risk were identified. If causal mechanisms affecting risks of RA and CAD are overlapping, risk alleles for RA might also increase the risk of CAD.Methods.Sixty-one SNP associating with RA in genome-wide significant analyses were tested for association with CAD in CARDIoGRAM (Coronary ARtery DIsease Genome wide Replication and Meta-analysis), a metaanalysis including genome-wide association data (22,233 CAD cases, 64,762 controls). In parallel, a set of SNP being associated with low-density lipoprotein cholesterol (LDL-C) was tested as a positive control.Results.Twenty-nine RA-associated SNP displayed a directionality-consistent association with CAD (OR range 1.002–1.073), whereas 32 RA-associated SNP were not associated with CAD (OR range 0.96–0.99 per RA risk-increasing allele). The proportion (48%) of directionality-consistent associated SNP equaled the proportion expected by chance (50%, p = 0.09). Of only 5 RA-associated SNP showing p values for CAD < 0.05, 4 loci (C5orf30, IL-6R, PTPN22, and RAD51B) showed directionality-consistent effects on CAD, and 1 (rs10774624, locus SH2B3) reached study-wide significance (p = 7.29E-06). By contrast, and as a proof of concept, 46 (74%) out of 62 LDL-C–associated SNP displayed a directionality-consistent association with CAD, a proportion that was significantly different from 50% (p = 5.9E-05).Conclusion.We found no evidence that RA-associated SNP as a group are associated with CAD. Even though we were not able to study potential effects of all genetic variants individually, shared nongenetic factors may more plausibly explain the observed coincidence of the 2 conditions.

scholarly journals ADHD genetic liability and physical health outcomes - A two-sample Mendelian randomization study

2019 ◽  
Author(s):  
Beate Leppert ◽  
Lucy Riglin ◽  
Christina Dardani ◽  
Ajay Thapar ◽  
James R Staley ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Childhood Obesity ◽  
Health Outcomes ◽  
Physical Health ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Genetic Liability ◽  
Physical Health Outcomes ◽  
Artery Disease

AbstractObjectiveAttention-deficit/hyperactivity disorder (ADHD) has been associated with a broad range of physical health problems, including cardiometabolic, neurological and immunological conditions. Determining whether ADHD plays a causal role in these associations is of great importance for treatment and prevention but also because comorbid health problems further increase the serious social and economic impacts of ADHD on individuals and their families.MethodsWe used a two-sample Mendelian randomization (MR) approach to examine the causal relationships between genetic liability for ADHD and previously implicated physical health conditions. 11 genetic variants associated with ADHD were obtained from the latest summary statistics. Consistent effects obtained from IVW, weighted median and MR Egger methods were taken forward for sensitivity analysis, including bidirectional MR and multivariable MR (MVMR).ResultsWe found evidence of a causal effect of genetic liability for ADHD on childhood obesity (OR:1.29 (95% CI:1.02,1.63)) and coronary artery disease (CAD) (OR:1.11 (95% CI:1.03,1.19)) with consistent results across different MR approaches. There was further evidence for a bidirectional relationship between genetic liability for ADHD and childhood obesity. The effect of genetic liability for ADHD on CAD was independent of smoking heaviness but was attenuated when simultaneously controlling for childhood obesity. There was little evidence for a causal effect on other cardiometabolic, immunological, neurological disorders and lung cancer.ConclusionOur findings strengthen the argument for early treatment and support for children with ADHD and their families and especially promoting physical activity and providing them with dietary advice to reduce future risk for developing CAD.Key MessageEpidemiological studies have reported observational associations between ADHD and adult onset physical health outcomes.Mendelian Randomization can be used to assess causal associations for ADHD on health outcomes that would traditionally require long term follow-up and may suffer confoundingWe found that genetic liability for ADHD was associated with coronary artery disease and there was evidence for a bidirectional association between genetic liability for ADHD and childhood obesityMultivariable mendelian randomization suggests that the link between genetic liability and coronary artery disease might partially act through childhood obesity but was independent of smoking heavinessThere was little evidence of a causal of ADHD on other cardiometabolic and immunological diseases.

scholarly journals A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Qingyuan Zhao ◽  
Jingshu Wang ◽  
Zhen Miao ◽  
Nancy R Zhang ◽  
Sean Hennessy ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Particle Size ◽  
Coronary Artery ◽  
Protective Effect ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Particle Diameter ◽  
Lipoprotein Subfractions ◽  
Artery Disease

Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size.

scholarly journals MR-Clust: Clustering of genetic variants in Mendelian randomization with similar causal estimates

2019 ◽  
Author(s):  
Christopher N Foley ◽  
Paul D W Kirk ◽  
Stephen Burgess
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Risk Factor ◽  
Coronary Artery ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Causal Effect ◽  
Coronary Artery Disease Risk ◽  
Artery Disease

AbstractMotivationMendelian randomization is an epidemiological technique that uses genetic variants as instrumental variables to estimate the causal effect of a risk factor on an outcome. We consider a scenario in which causal estimates based on each variant in turn differ more strongly than expected by chance alone, but the variants can be divided into distinct clusters, such that all variants in the cluster have similar causal estimates. This scenario is likely to occur when there are several distinct causal mechanisms by which a risk factor influences an outcome with different magnitudes of causal effect. We have developed an algorithm MR-Clust that finds such clusters of variants, and so can identify variants that reflect distinct causal mechanisms. Two features of our clustering algorithm are that it accounts for uncertainty in the causal estimates, and it includes ‘null’ and ‘junk’ clusters, to provide protection against the detection of spurious clusters.ResultsOur algorithm correctly detected the number of clusters in a simulation analysis, outperforming the popular Mclust method. In an applied example considering the effect of blood pressure on coronary artery disease risk, the method detected four clusters of genetic variants. A hypothesis-free search suggested that variants in the cluster with a negative effect of blood pressure on coronary artery disease risk were more strongly related to trunk fat percentage and other adiposity measures than variants not in this cluster.Availability and ImplementationMR-Clust can be downloaded from https://github.com/cnfoley/[email protected] or [email protected] InformationSupplementary Material is included in the submission.

scholarly journals Enhancer Promoter Interactome and Mendelian Randomization Identify Network of Druggable Vascular Genes in Coronary Artery Disease

2021 ◽  
Author(s):  
Arnaud Chignon ◽  
Samuel Mathieu ◽  
Anne Rufiange ◽  
Deborah Argaud ◽  
Pierre Voisine ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Candidate Genes ◽  
Mendelian Randomization ◽  
Genome Mapping ◽  
Human Coronary Artery ◽  
Genome Wide ◽  
Cardinal Process ◽  
Artery Disease ◽  
Causal Candidate

Abstract Coronary artery disease (CAD) is a multifactorial disorder, which is partly heritable. Herein, we implemented a mapping of CAD-associated candidate genes by using genome-wide enhancer-promoter conformation (H3K27ac-HiChIP) and expression quantitative trait loci (eQTL). Enhancer-promoter anchor loops from human coronary artery smooth muscle cells (HCASMC) explained 22% of the heritability for CAD. 3D enhancer-promoter genome mapping of CAD-genes in HCASMC was enriched in vascular eQTL genes. By using colocalization and Mendelian randomization analyses, we identified 58 causal candidate vascular genes including some druggable targets (MAP3K11, CAMK1D, PDGFD, IPO9 and CETP). A network analysis of causal candidate genes was enriched in TGF beta and MAPK pathways. The pharmacologic inhibition of causal candidate gene MAP3K11 in vascular SMC reduced the expression of athero-relevant genes and lowered cell migration, a cardinal process in CAD. Genes connected to enhancers are enriched in vascular eQTL and druggable genes causally associated with CAD.

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