scholarly journals Clinical applicability of methylome sequencing in a pilot study of ischemic stroke individuals

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Mark Ziemann ◽  
KN Harikrishnan ◽  
Ishant Khurana ◽  
Antony Kaspi ◽  
Samuel T Keating ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Ischemic Stroke ◽  
Association Studies ◽  
Clinical Samples ◽  
Genome Wide Association Studies ◽  
Disease Etiology ◽  
Clinical Applicability ◽  
Genome Wide ◽  
Increased Risk

Abstract Despite recent progress in screening for genetic causes of cardiovascular disease using genome-wide association studies, identifying causative polymorphisms has not met initial expectations. This has led to interest in exploring the contribution of non-genetic factors in disease etiology. Elevated plasma homocysteine is an independent risk factor for cardiovascular disease but the mechanism for increased risk remains poorly understood. This study evaluates the clinical applicability of screening for genome-wide CpG methylation differences using methyl-CpG binding domain (MBD) protein-enriched genome sequencing (MBD-seq). Peripheral blood genomic DNA methylation in 8 Singaporean-Chinese ischemic stroke patients (4 male, 4 female) was profiled. Differential methylation of genes implicated in hyperhomocysteinemia was observed in males correlating with homocysteine; namely CBS (cystathionine-beta-synthase) and MTHFR (methylenetetrahydrofolate reductase). In females, hypomethylation of the LDLR (low density lipoprotein receptor) and CELSR1 (cadherin, EGF LAG seven-pass G-type receptor 1) genes were observed in the hypertensive group (2 normal and 2 hypertensive individuals). While the number of clinical samples analysed is small, the findings of this evaluation suggest that MBD-seq is a suitable and sufficiently sensitive technology to determine methylation variability. The results presented warrant an expanded case-control study to determine the pathophysiological implications of DNA methylation for hyper-homocysteinemia.

scholarly journals Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Tianxiao Huan ◽  
Roby Joehanes ◽  
Ci Song ◽  
Fen Peng ◽  
Yichen Guo ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Dna Methylation ◽  
Whole Blood ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Transcriptional Regulatory ◽  
Disease Associations ◽  
Independent Replication ◽  
Functional Mechanisms

Abstract Identifying methylation quantitative trait loci (meQTLs) and integrating them with disease-associated variants from genome-wide association studies (GWAS) may illuminate functional mechanisms underlying genetic variant-disease associations. Here, we perform GWAS of >415 thousand CpG methylation sites in whole blood from 4170 individuals and map 4.7 million cis- and 630 thousand trans-meQTL variants targeting >120 thousand CpGs. Independent replication is performed in 1347 participants from two studies. By linking cis-meQTL variants with GWAS results for cardiovascular disease (CVD) traits, we identify 92 putatively causal CpGs for CVD traits by Mendelian randomization analysis. Further integrating gene expression data reveals evidence of cis CpG-transcript pairs causally linked to CVD. In addition, we identify 22 trans-meQTL hotspots each targeting more than 30 CpGs and find that trans-meQTL hotspots appear to act in cis on expression of nearby transcriptional regulatory genes. Our findings provide a powerful meQTL resource and shed light on DNA methylation involvement in human diseases.

scholarly journals Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Biological Aging ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Biomarkers Of Aging ◽  
Genome Wide ◽  
Shared Genetic

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

scholarly journals Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization

2019 ◽  
Author(s):  
Daniel B. Rosoff ◽  
George Davey Smith ◽  
Nehal Mehta ◽  
Toni-Kim Clarke ◽  
Falk W. Lohoff
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Alcohol Use ◽  
Tobacco Use ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Cvd Risk ◽  
Increased Risk

ABSTRACTAlcohol and tobacco use, two major modifiable risk factors for cardiovascular disease (CVD), are often consumed together. Using large publicly available genome-wide association studies (results from > 940,000 participants), we conducted two-sample multivariable Mendelian randomization (MR) to simultaneously assess the independent effects of alcohol and tobacco use on CVD risk factors and events. We found genetic instruments associated with increased alcohol use, controlling for tobacco use, associated with increased high-density-lipoprotein-cholesterol (HDL-C), decreased triglycerides, but not with coronary heart disease (CHD), myocardial infarction (MI), nor stroke; and instruments for increased tobacco use, controlling for alcohol use, associated with decreased HDL-C, increased triglycerides, and increased risk of CHD and MI. Exploratory analysis found associations with HDL-C, LDL-C, and intermediate-density-lipoprotein metabolites. Consistency of results across complementary methods accommodating different MR assumptions strengthened causal inference, providing strong genetic evidence for the causal effects of modifiable lifestyle risk factors on CVD risk.

The Yin and Yang of High-density Lipoprotein and Atherosclerotic Cardiovascular Disease: Focusing on Functionality and Cholesterol Efflux to Reframe the HDL Hypothesis

2021 ◽  
Vol 28 ◽  
Author(s):  
Shiva Ganjali ◽  
Gerald F. Watts ◽  
Maciej Banach ◽  
Željko Reiner ◽  
Petr Nachtigal ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
High Density Lipoprotein ◽  
Cholesterol Efflux ◽  
Association Studies ◽  
Plasma Concentrations ◽  
Density Lipoprotein ◽  
High Density ◽  
Atherosclerotic Cardiovascular Disease ◽  
Genome Wide Association Studies ◽  
Increased Risk

Abstract: The inverse relationship between low plasma high-density lipoprotein cholesterol (HDL-C) concentrations and increased risk of Atherosclerotic Cardiovascular Disease (ASCVD) is well-known. However, plasma HDL-C concentrations are highly variable in subjects with ASCVD. In clinical outcome trials, pharmacotherapies that increase HDL-C concentrations are not associated with a reduction in ASCVD events. A causal relationship between HDL-C and ASCVD has also been questioned by Mendelian randomization studies and genome-wide association studies of genetic variants associated with plasma HDL-C concentrations. The U-shaped association between plasma HDL-C concentrations and mortality observed in several epidemiological studies implicates both low and very high plasma HDL-C concentrations in the etiology of ASCVD and non-ASCVD mortality. These data do not collectively support a causal association between HDL-C and ASCVD risk. Therefore, the hypothesis concerning the association between HDL and ASCVD has shifted from focus on plasma concentrations to the concept of functionality, in particular cellular cholesterol efflux and HDL holoparticle transport. In this review, we focus on these new concepts and provide a new framework for understanding and testing the role of HDL in ASCVD.

scholarly journals Genetics of Atrial Fibrillation in 2020

2020 ◽  
Vol 127 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Carolina Roselli ◽  
Michiel Rienstra ◽  
Patrick T. Ellinor
Keyword(s):  
Atrial Fibrillation ◽  
Complex Disease ◽  
Association Studies ◽  
Heart Rhythm ◽  
Genome Wide Association Studies ◽  
Future Directions ◽  
Genetics Research ◽  
Genome Wide ◽  
Increased Risk ◽  
Rhythm Disorder

Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.

scholarly journals Inference of causal relationships between sleep-related traits and 1,527 phenotypes using genetic data

SLEEP ◽  
2020 ◽  
Author(s):  
Luis M García-Marín ◽  
Adrián I Campos ◽  
Nicholas G Martin ◽  
Gabriel Cuéllar-Partida ◽  
Miguel E Rentería
Keyword(s):  
Sleep Duration ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Physical And Mental Health ◽  
Related Factors ◽  
Study Objective ◽  
Genome Wide ◽  
Increased Risk ◽  
Level Statistics

Abstract Study Objective Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data. Methods We used summary-level statistics from genome-wide association studies and the latent causal variable (LCV) method to screen the phenome and infer causal relationships between seven sleep-related traits (insomnia, daytime dozing, easiness of getting up in the morning, snoring, sleep duration, napping, and morningness) and 1,527 other phenotypes. Results We identify 84 inferred causal relationships. Among other findings, connective tissue disorders increase insomnia risk and reduce sleep duration; depression-related traits increase insomnia and daytime dozing; insomnia, napping and snoring are affected by obesity and cardiometabolic traits and diseases; and working with asbestos, thinner, or glues may increase insomnia risk, possibly through an increased risk of respiratory disease or socio-economic related factors. Conclusion Overall, our results indicate that changes in sleep variables are predominantly the consequence, rather than the cause, of other underlying phenotypes and diseases. These insights could inform the design of future epidemiological and interventional studies in sleep medicine and research.

scholarly journals A Review of the Hereditary Component of Triple Negative Breast Cancer: High- and Moderate-Penetrance Breast Cancer Genes, Low-Penetrance Loci, and the Role of Nontraditional Genetic Elements

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Darrell L. Ellsworth ◽  
Clesson E. Turner ◽  
Rachel E. Ellsworth
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Large Scale ◽  
Triple Negative ◽  
Association Studies ◽  
African Ancestry ◽  
Genome Wide Association Studies ◽  
Genetic Elements ◽  
Genome Wide ◽  
Increased Risk

Triple negative breast cancer (TNBC), representing 10-15% of breast tumors diagnosed each year, is a clinically defined subtype of breast cancer associated with poor prognosis. The higher incidence of TNBC in certain populations such as young women and/or women of African ancestry and a unique pathological phenotype shared between TNBC and BRCA1-deficient tumors suggest that TNBC may be inherited through germline mutations. In this article, we describe genes and genetic elements, beyond BRCA1 and BRCA2, which have been associated with increased risk of TNBC. Multigene panel testing has identified high- and moderate-penetrance cancer predisposition genes associated with increased risk for TNBC. Development of large-scale genome-wide SNP assays coupled with genome-wide association studies (GWAS) has led to the discovery of low-penetrance TNBC-associated loci. Next-generation sequencing has identified variants in noncoding RNAs, viral integration sites, and genes in underexplored regions of the human genome that may contribute to the genetic underpinnings of TNBC. Advances in our understanding of the genetics of TNBC are driving improvements in risk assessment and patient management.

scholarly journals Animal Models of GWAS-Identified Type 2 Diabetes Genes

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Gabriela da Silva Xavier ◽  
Elisa A. Bellomo ◽  
James A. McGinty ◽  
Paul M. French ◽  
Guy A. Rutter
Keyword(s):  
Type 2 Diabetes ◽  
Animal Models ◽  
Mouse Models ◽  
Human Genetics ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide ◽  
Increased Risk

More than 65loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D). Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notablyTCF7L2andZnT8/SLC30A8, have to date been examined in mouse models. We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.

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