scholarly journals The Complex Cardiac Atherosclerotic Disorder: The Elusive Role of Genetics and the New Consensus of Systems Biology Approach

2017 ◽  
Vol 2 ◽  
Author(s):  
George Louridas ◽  
Katerina Lourida
Keyword(s):  
Systems Biology ◽  
Association Studies ◽  
Methodological Approach ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Therapeutic Procedures ◽  
Clinical Consequences ◽  
Artery Disease ◽  
Atherosclerotic Process

<p>The present technological status of genetics and genomics or the genome-wide association studies (GWAS) are insufficient to explain complex diseases like atherosclerosis and coronary artery disease (CAD). It appears that the genetic risk variants of atherosclerosis are activated concurrently with functionally active specific environmental risk factors. With the systems biology methodological approach the atherosclerotic process and CAD are better explained and studied as a unified entity with significant clinical consequences.</p><p>Systems biology is an alternative approach for the study of atherosclerosis and CAD. With the systems biology approach the follow-up of the atherosclerotic process requires four conceptual areas of study: 1) the two potential directions, the bottom-up direction (functional composition from genes to phenotypes) and the top-down direction (functional decomposition from phenotypes to genes); 2) the four disciplines or levels of complexity: the genomic, the cellular, the modular and the model (clinical phenotype) level; 3) the concept of network construction; 4) the atherosclerotic plaque development and progression across all levels of complexity.</p><p>The systems biology methodology is holistic in conception. The proposed systems patterns are able to follow up the progressive nature of atherosclerosis and to explain the appearance of the clinical cardiovascular phenotypes. The phenotypes of CAD are integrated clinical wholes that determine through constrains and therapeutic procedures the behavior of the biological parts in the lower levels of complexity. This way of thinking is leading from genomics, through networks, to the mainstay of clinical cardiology. </p>

scholarly journals High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways

2019 ◽  
Vol 12 (3) ◽  
Author(s):  
Örjan Åkerborg ◽  
Rapolas Spalinskas ◽  
Sailendra Pradhananga ◽  
Anandashankar Anil ◽  
Pontus Höjer ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
High Resolution ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Expression Levels ◽  
Risk Variants ◽  
Genome Wide ◽  
Artery Disease

Background: Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease. Methods: In this study, we generated high-resolution genomic interaction maps (≈750 bases) in aortic endothelial, smooth muscle cells and THP-1 (human leukemia monocytic cell line) macrophages stimulated with lipopolysaccharide using Hi-C coupled with sequence capture targeting 25 429 features, including variants associated with coronary artery disease. We also sequenced their transcriptomes and mapped putative enhancers using chromatin immunoprecipitation with an antibody against H3K27Ac. Results: The regions interacting with promoters showed strong enrichment for enhancer elements and validated several previously known interactions and enhancers. We detected interactions for 727 risk variants obtained by genome-wide association studies and identified novel, as well as established genes and functions associated with cardiovascular diseases. We were able to assign potential target genes for additional 398 genome-wide association studies variants using haplotype information, thereby identifying additional relevant genes and functions. Importantly, we discovered that a subset of risk variants interact with multiple promoters and their expression levels were strongly correlated. Conclusions: In summary, we present a catalog of candidate genes regulated by coronary artery disease–related variants and think that it will be an invaluable resource to further the investigation of cardiovascular pathologies and disease.

scholarly journals Genetic Risk of Coronary Artery Disease, Features of Atherosclerosis, and Coronary Plaque Burden

2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Morten Krogh Christiansen ◽  
Louise Nissen ◽  
Simon Winther ◽  
Peter Loof Møller ◽  
Lars Frost ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Coronary Artery Calcium Score ◽  
Association Studies ◽  
Calcium Score ◽  
Plaque Burden ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Stenosis Severity ◽  
Artery Disease

Background Polygenic risk scores ( PRS s) based on risk variants from genome‐wide association studies predict coronary artery disease ( CAD ) risk. However, it is unknown whether the PRS is associated with specific CAD characteristics. Methods and Results We consecutively included 1645 patients with suspected stable CAD undergoing coronary computed tomography angiography. A multilocus PRS was calculated as the weighted sum of CAD risk variants. Plaques were evaluated using an 18‐segment model and characterized by stenosis severity and composition (soft [0%‐19% calcified], mixed‐soft [20%‐49% calcified], mixed‐calcified [50%‐79% calcified], or calcified [≥80% calcified]). Coronary artery calcium score and segment stenosis score were used to characterize plaque burden. For each standard deviation increase in the PRS , coronary artery calcium score increased by 78% ( P =4.1e‐26) and segment stenosis score increased by 16% ( P =2.4e‐29) in the fully adjusted model. The PRS was associated with a higher prevalence of obstructive plaques (odds ratio [ OR ] : 1.78, P =5.6e‐16), calcified ( OR : 1.69, P =6.5e‐17), mixed‐calcified ( OR : 1.67, P =7.3e‐9), mixed‐soft ( OR : 1.45, P =1.6e‐6), and soft plaques ( OR : 1.49, P =2.5e‐6), and a higher prevalence of plaque in each coronary vessel (all P <1.0e‐4). However, when analyzing data on a plaque level (3007 segments with plaque in 849 patients) the PRS was not associated with stenosis severity, plaque composition, or localization (all P >0.05). Conclusions Our results suggest that polygenic risk based on large genome‐wide association studies increases CAD risk through an increased burden of coronary atherosclerosis rather than promoting specific plaque features. Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifier: NCT 02264717.

scholarly journals The Parkinson’s Disease GWAS Locus Browser

2020 ◽  
Author(s):  
Francis P. Grenn ◽  
Jonggeol J. Kim ◽  
Mary B. Makarious ◽  
Hirotaka Iwaki ◽  
Anastasia Illarionova ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Large Scale ◽  
Association Studies ◽  
Age At Onset ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Risk Variants ◽  
Genome Wide

AbstractParkinson’s disease (PD) is a neurodegenerative disease with an often complex genetic component identifiable by genome-wide association studies (GWAS). The most recent large scale PD GWASes have identified more than 90 independent risk variants for PD risk and progression across 80 loci. One major challenge in current genomics is identifying the causal gene(s) and variant(s) from each GWAS locus. Here we present a GWAS locus browser application that combines data from multiple databases to aid in the prioritization of genes associated with PD GWAS loci. We included 92 independent genome-wide significant signals from multiple recent PD GWAS studies including the PD risk GWAS, age-at-onset GWAS and progression GWAS. We gathered data for all 2336 genes within 1Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Our aim is that the information contained in this browser (https://pdgenetics.shinyapps.io/GWASBrowser/) will assist the PD research community with the prioritization of genes for follow-up functional studies and as potential therapeutic targets.

Follow up of schizophrenia gwas based on cognitive performance, high density eeg, and structural brain imaging

2011 ◽  
Vol 26 (S2) ◽  
pp. 2083-2083
Author(s):  
G. Donohoe ◽  
E. Rose ◽  
D. Morris ◽  
A. Hargreaves ◽  
M. Gill ◽  
...  
Keyword(s):  
Cognitive Deficits ◽  
Association Studies ◽  
Structure And Function ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Brain Structure And Function ◽  
And Function ◽  
Healthy Participants

The advent of genome wide association studies have resulted in the identification of a number of novel genetic loci for schizophrenia and related disorders. Understanding the functional impact of these variants on brain structure and function is crucial to understand their role in disease pathology. We presents data based on our genetic and neuropsychological assessment of almost 700 patients and healthy participants for a number of these variants and replication of our findings in independent samples of almost 1500 cases and controls. Specifically, we will use this data to suggest that the risk associated with some genetics variants (e.g. NOS1) is being mediated by an influence on variation in intelligence and other cognitive phenotypes, while other risk variants (e.g. ZNF804A) delineate illness subtypes in which cognitive deficits are a less prominent feature.

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.

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 Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

Exome-Wide Pan-Cancer Analysis of Germline Variants in 8,719 Individuals Finds Little Evidence of Rare Variant Associations

2021 ◽  
pp. 1-10
Author(s):  
Zoe Guan ◽  
Ronglai Shen ◽  
Colin B. Begg
Keyword(s):  
Rare Variant ◽  
Rare Variants ◽  
Association Studies ◽  
The Cancer Genome Atlas ◽  
Considerable Proportion ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Risk Variants ◽  
Cancer Types ◽  
Pan Cancer

<b><i>Background:</i></b> Many cancer types show considerable heritability, and extensive research has been done to identify germline susceptibility variants. Linkage studies have discovered many rare high-risk variants, and genome-wide association studies (GWAS) have discovered many common low-risk variants. However, it is believed that a considerable proportion of the heritability of cancer remains unexplained by known susceptibility variants. The “rare variant hypothesis” proposes that much of the missing heritability lies in rare variants that cannot reliably be detected by linkage analysis or GWAS. Until recently, high sequencing costs have precluded extensive surveys of rare variants, but technological advances have now made it possible to analyze rare variants on a much greater scale. <b><i>Objectives:</i></b> In this study, we investigated associations between rare variants and 14 cancer types. <b><i>Methods:</i></b> We ran association tests using whole-exome sequencing data from The Cancer Genome Atlas (TCGA) and validated the findings using data from the Pan-Cancer Analysis of Whole Genomes Consortium (PCAWG). <b><i>Results:</i></b> We identified four significant associations in TCGA, only one of which was replicated in PCAWG (BRCA1 and ovarian cancer). <b><i>Conclusions:</i></b> Our results provide little evidence in favor of the rare variant hypothesis. Much larger sample sizes may be needed to detect undiscovered rare cancer variants.

scholarly journals Atrial fibrillation associated common risk variants in SYNE2 lead to lower expression of nesprin-2α1 and increased nuclear stiffness

2019 ◽  
Author(s):  
Nana Liu ◽  
Jeffrey Hsu ◽  
Gautam Mahajan ◽  
Han Sun ◽  
John Barnard ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Association Studies ◽  
Dominant Negative ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Gene Encoding ◽  
Enhancer Activity ◽  
Risk Alleles ◽  
Risk Variants ◽  
Lower Expression

ABSTRACTRationaleAtrial fibrillation (AF) genome-wide association studies (GWAS) identified significant associations for rs1152591 and linked variants in the SYNE2 gene encoding the nesprin-2 protein that connects the nuclear membrane with the cytoskeletonObjectiveDetermine the effects of the AF-associated rs1152591 and rs1152595, two linked intronic single nucleotide polymorphisms (SNPs), on SYNE2 expression and investigate the mechanisms for their association with AF.Methods and ResultsRNA sequencing of human left atrial appendage (LAA) tissues indicated that rs1152591 and rs1152595 were significantly associated with the expressions of SYNE2α1, a short mRNA isoform, without an effect on the expression of the full-length SYNE2 mRNA. SYNE2α1 mRNA uses an alternative transcription start site and encodes an N-terminal deleted 62 kDa nesprin-2α1 isoform, which can act as a dominant-negative on nuclear-cytoskeleton connectivity. Western blot and qPCR assays confirmed that AF risk alleles of both SNPs were associated with lower expression of nesprin-2α1 in human LAA tissues. Reporter gene transfections demonstrated that the risk vs. reference alleles of rs1152591 and rs1152595 had decreased enhancer activity. SYNE2 siRNA knockdown (KD) or nesprin-2α1 overexpression studies in human stem cell-derived induced cardiomyocytes (iCMs) resulted in ~12.5 % increases in the nuclear area compared to controls (p<0.001). Atomic force microscopy demonstrated that SYNE2 KD or nesprin-2α1 overexpression led to 57.5% or 33.2% decreases, respectively, in nuclear stiffness compared to controls (p< 0.0001).ConclusionsAF-associated SNPs rs1152591 and rs1152595 downregulate the expression of SYNE2α1, increasing nuclear-cytoskeletal connectivity and nuclear stiffness. The resulting increase in mechanical stress may play a role in the development of AF.

Characterizing a common CERS2 polymorphism in a mouse model of metabolic disease and in subjects from the Utah CAD Study

2021 ◽  
Author(s):  
Rebekah J Nicholson ◽  
Annelise M Poss ◽  
J Alan Maschek ◽  
James E Cox ◽  
Paul N Hopkins ◽  
...  
Keyword(s):  
Metabolic Disease ◽  
Coronary Artery Disease ◽  
Enzyme Activity ◽  
Coronary Artery ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Serum Samples ◽  
Artery Disease ◽  
Disease Study

Abstract Context Genome-wide association studies have identified associations between a common single nucleotide polymorphism (SNP, rs267738) in CERS2 – a gene that encodes a (dihydro)ceramide synthase involved in the biosynthesis of very-long chain sphingolipids (e.g. C20-C26) – and indices of metabolic dysfunction (e.g. impaired glucose homeostasis). However, the biological consequences of this mutation on enzyme activity and its causal roles in metabolic disease are unresolved. Objective The studies described herein aimed to characterize the effects of rs267738 on CERS2 enzyme activity, sphingolipid profiles, and metabolic outcomes. Design We performed in-depth lipidomic and metabolic characterization of a novel CRISPR knock-in mouse modeling the rs267738 variant. In parallel, we conducted mass spectrometry-based, targeted lipidomics on 567 serum samples collected through the Utah Coronary Artery Disease study, which included 185 patients harboring one (n = 163) or both (n = 22) rs267738 alleles. Results In-silico analysis of the amino acid substitution within CERS2 caused by the rs267738 mutation suggested that rs267738 is deleterious for enzyme function. Homozygous knock-in mice had reduced liver CERS2 activity and enhanced diet-induced glucose intolerance and hepatic steatosis. However, human serum sphingolipids and a ceramide-based CERT1 risk score of cardiovascular disease were not significantly affected by rs267738 allele count. Conclusions The rs267738 SNP leads to a partial loss-of-function of CERS2, which worsened metabolic parameters in knock-in mice. However, rs267738 was insufficient to effect changes in serum sphingolipid profiles in subjects from the Utah Coronary Artery Disease Study.

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