scholarly journals The SNP rs7865618 of 9p21.3 locus emerges as the most promising marker of coronary artery disease in the southern Indian population

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gorre Manjula ◽  
Rayabarapu Pranavchand ◽  
Irgam Kumuda ◽  
B. Sriteja Reddy ◽  
Battini Mohan Reddy
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Indian Population ◽  
Interaction Analysis ◽  
Association Studies ◽  
Specific Marker ◽  
Genome Wide Association Studies ◽  
Coronary Syndrome ◽  
Increased Risk ◽  
Artery Disease

AbstractDevelopment of coronary artery disease (CAD) is primarily due to the process of atherosclerosis, however the prognosis of CAD depends on pleiotropic effects of the genes located at 9p21.3 region. Genome wide association studies revealed association of variants in this region with CAD pathology. However, specific marker in predicting CAD development or progression is not yet identified. In the present study, 35 SNPs at 9p21.3 region, located in the cyclin dependent kinase inhibitor (CDKN2A/CDKN2B) genes, were genotyped among 350 CAD cases and 480 controls from the southern Indian population of Hyderabad using fluidigm nanofluidic SNP genotyping system and the data were analyzed using PLINK and R softwares. Of the 35 SNPs analysed, only one SNP, rs7865618, was found to be highly significantly associated with CAD, even after correction for multiple testing (p = 0.008). The AG and GG genotypes of this SNP conferred 3.08 and 1.93 folds increased risk for CAD respectively. In particular, this SNP was significantly associated with severe anatomic (triple vessel disease p = 0.023) and phenotypic (acute coronary syndrome p = 0.007) categories of CAD. Pair wise SNP interaction analysis between the SNPs of 9p21.3 and 11q23.3 regions revealed significantly increased risk of three SNPs of 11q23.3 region that were not associated individually, in conjunction with rs7865618 of 9p21.3.

Recent success in the discovery of coronary artery disease genes

2011 ◽  
Vol 89 (8) ◽  
pp. 609-615 ◽  
Author(s):  
Robert Roberts ◽  
Li Chen ◽  
George A. Wells ◽  
Alexandre F.R. Stewart
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Short Interval ◽  
Minimal Risk ◽  
Genome Wide Association Studies ◽  
Common Diseases ◽  
Multiple Genes ◽  
Increased Risk ◽  
Artery Disease

For more than 50 years, epidemiological studies have indicated that genetic predisposition accounts for approximately 50% of the susceptibility to coronary artery disease (CAD) and its sequelae, including myocardial infarction. Since common diseases such as CAD are caused by multiple genes, the age-old method of linkage analysis used to map monogenic Mendelian disorders in families unfortunately lacks the required sensitivity. The technology to identify genes predisposing individuals to CAD and other common diseases did not become available until 2005. This technology provided computerized arrays containing hundreds of thousands of DNA markers in the form of single-nucleotide polymorphisms (SNPs). This made it possible to pursue an unbiased approach referred to as genome-wide association studies. The first gene for CAD was simultaneously identified by 2 independent groups in 2007. In a very short interval, a total of 23 loci were mapped that were linked to increased risk for CAD. The results of these studies confirm that CAD is caused by multiple genes, each contributing minimal risk. The most exciting and novel findings are that these loci do not act through known risk factors for CAD and that the loci are more likely to be in DNA regions that regulate transcription rather than being in coding regions for protein.

scholarly journals Cis-epistasis at the LPA locus and risk of coronary artery disease

2019 ◽  
Author(s):  
Lingyao Zeng ◽  
Nazanin Mirza-Schreiber ◽  
Claudia Lamina ◽  
Stefan Coassin ◽  
Christopher P. Nelson ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Studies ◽  
Arterial Disease ◽  
Genome Wide Association Studies ◽  
Interaction Patterns ◽  
Cardiovascular Risks ◽  
Increased Risk ◽  
Artery Disease ◽  
Cad Risk

AbstractIdentification of epistasis affecting complex human traits has been challenging. Focusing on known coronary artery disease (CAD) risk loci, we explore pairwise statistical interactions between 8,068 SNPs from ten CAD genome-wide association studies (n=30,180). We discovered rs1800769 and rs9458001 in the vicinity of the LPA locus to interact in modulating CAD risk (P=1.75×10−13). Specific genotypes (e.g., rs1800769 CT) displayed either significantly decreased or increased risk for CAD in the context of genotypes of the respective other SNP (e.g., rs9458001 GG vs. AA). In the UK Biobank (n=450,112) significant interaction of this SNP pair was replicated for CAD (P=3.09×10−22), and was also found for aortic valve stenosis (P=6.95×10−7) and peripheral arterial disease (P=2.32×10−4). Identical interaction patterns affected circulating lipoprotein(a) (n=5,953; P=8.7×10−32) and hepatic apolipoprotein(a) (apo(a)) expression (n=522, P=2.6×10−11). We further interrogated potential biological implications of the variants and propose a mechanism explaining epistasis that ultimately may translate to substantial cardiovascular risks.

scholarly journals Association Between Genetic Variation in Blood Pressure and Increased Lifetime Risk of Peripheral Artery Disease

2021 ◽  
Author(s):  
Michael G. Levin ◽  
Derek Klarin ◽  
Venexia M. Walker ◽  
Dipender Gill ◽  
Julie Lynch ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Peripheral Artery Disease ◽  
Pulse Pressure ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Peripheral Artery ◽  
Increased Risk ◽  
Artery Disease

Objective: We aimed to estimate the effect of blood pressure (BP) traits and BP-lowering medications (via genetic proxies) on peripheral artery disease. Approach and Results: Genome-wide association studies summary statistics were obtained for BP, peripheral artery disease (PAD), and coronary artery disease. Causal effects of BP on PAD were estimated by 2-sample Mendelian randomization using a range of pleiotropy-robust methods. Increased systolic BP (SBP), diastolic BP, mean arterial pressure (MAP), and pulse pressure each significantly increased risk of PAD (SBP odds ratio [OR], 1.20 [1.16–1.25] per 10 mm Hg increase, P =1×10 −24 ; diastolic BP OR, 1.27 [1.18–1.35], P =4×10 − 11 ; MAP OR, 1.26 [1.19–1.33], P =6×10 − 16 ; pulse pressure OR, 1.31 [1.24–1.39], P =9×10 − 23 ). The effects of SBP, diastolic BP, and MAP were greater for coronary artery disease than PAD (SBP ratio of Ors, 1.06 [1.0–1.12], P = 0.04; MAP ratio of OR, 1.15 [1.06–1.26], P =8.6×10 − 4 ; diastolic BP ratio of OR, 1.21 [1.08–1.35], P =6.9×10 − 4 ). Considered jointly, both pulse pressure and MAP directly increased risk of PAD (pulse pressure OR, 1.26 [1.17–1.35], P =3×10 − 10 ; MAP OR, 1.14 [1.06–1.23], P =2×10 − 4 ). The effects of antihypertensive medications were estimated using genetic instruments. SBP-lowering via β-blocker (OR, 0.74 per 10 mm Hg decrease in SBP [95% CI, 0.65–0.84]; P =5×10 − 6 ), loop diuretic (OR, 0.66 [0.48–0.91], P =0.01), and thiazide diuretic (OR, 0.57 [0.41–0.79], P =6×10 − 4 ) associated variants were protective of PAD. Conclusions: Higher BP is likely to cause PAD. BP-lowering through β blockers, loop diuretics, and thiazide diuretics (as proxied by genetic variants) was associated with decreased risk of PAD. Future study is needed to clarify the specific mechanisms by which BP influences PAD.

scholarly journals Reply to Comment: Evaluation of the Association of Omentin 1 rs2274907 A > T and rs2274908 G > A Gene Polymorphisms with Coronary Artery Disease in Indian Population: A Case–Control Study

2020 ◽  
Vol 10 (4) ◽  
pp. 194
Author(s):  
Chandan K. Jha ◽  
Rashid Mir ◽  
Imadeldin Elfaki ◽  
Jamsheed Javid ◽  
Abdullatif Taha Babakr ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Gene Polymorphisms ◽  
Indian Population ◽  
Association Studies ◽  
Large Sample Size ◽  
South Indian Population ◽  
Genome Wide Association Studies ◽  
South Indian ◽  
Artery Disease

Coronary artery disease (CAD) is a major cause of death all over the world. CAD is caused by atherosclerosis which is induced by the interaction of genetic factors and environmental factors. Genome-wide association studies have revealed the association of certain gene polymorphisms with susceptibility to CAD. Omentin 1 is an adipokine secreted by the visceral adipose tissues and has been reported to have anti-inflammatory, cardioprotective, and enhances insulin sensitivity. In this study, we examined the role of omentin-1 common single nucleotide polymorphisms (SNPs) (rs2274907 A > T and rs2274908 G > A) in CAD. We conclude that the AT genotype and the T allele of the rs2274907 A > T is associated with Cad in the south Indian population. Our results indicated that the rs2274907 SNP may be associated with CAD in this population. This finding needs further validation in well-designed and large-sample size studies before being introduced in clinical settings.

scholarly journals Variant at 9p21 rs1333049 is associated with age of onset of coronary artery disease in a Western Indian population: a case control association study

2013 ◽  
Vol 95 (5) ◽  
pp. 138-145 ◽  
Author(s):  
APARNA A. BHANUSHALI ◽  
AASHISH CONTRACTOR ◽  
BIBHU R. DAS
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Indian Population ◽  
Risk Allele ◽  
Age Of Onset ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Age Group ◽  
Artery Disease ◽  
Cad Risk

SummaryThe 9p21 chromosomal region has been associated with coronary artery disease (CAD) in many genome wide association studies (GWAS). To date no information exists regarding the rs1333039 SNP which showed the strongest association in the WTCCC GWAS with CAD risk in the Indian population. The present study attempts to replicate the findings in the Indian population.Genotyping for rs1333049 was done in 229 cases and 151 controls by allele-specific real-time assay.A higher frequency of the risk allele rs1333049C was seen in cases (0·60) as compared with controls (0·49), which associated with CAD risk both in univariate (OR = 1·564, 95%CI = 1·154–2·119, P = 0·003) and multivariate analysis (OR = 2·460, 95%CI = 1·139–5·314, P = 0·022). Increased frequency of the risk allele was seen in younger individuals with CAD where 40% individuals in the age group 30–55 years had the CC genotype as compared with 29 and 24·5% in the age group 56–65 years and > 65 years, respectively (CC versus GG, P = 0·045). Higher incidence of the CC genotype was seen in MI patients, but missed significance when compared with controls (OR = 1·361, 95%CI = 0·954–1·942, P = 0·084).In conclusion, the rs1333049 variant is significantly associated with CAD risk and also with age of onset in the Western Indian population. However there are differences in the haplotype structure of this SNP with the neighbouring rs10757278 SNP, these differences emphasize the importance of genotyping all risk variants at this locus which could underlie the differences in risk susceptibility to CAD across populations.

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.

Reticulated Platelets: Changing Focus from Basics to Outcomes

2018 ◽  
Vol 118 (09) ◽  
pp. 1517-1527 ◽  
Author(s):  
Bashar Hannawi ◽  
Yousef Hannawi ◽  
Neal Kleiman
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Essential Role ◽  
State Of The Art ◽  
Specific Marker ◽  
Messenger Ribonucleic Acid ◽  
Coronary Syndrome ◽  
Reticulated Platelets ◽  
Artery Disease ◽  
Circulating Levels

AbstractPlatelets play an essential role in the pathophysiology of atherothrombosis. Reticulated platelets (RPs) are the youngest platelet population in the circulation; their presence is an indicator of platelet turnover. Circulating levels of RPs are increased in patients with coronary artery disease and stroke. Preliminary indications are that the proportion of circulating RP is associated with the likelihood of ischaemic events such as acute coronary syndrome and stroke. Plausible mechanisms include: (1) increased participation of these platelets in thrombosis due to messenger ribonucleic acid that may be translated to active proteins, (2) lack of exposure to anti-platelet drugs since they are newly released from the bone marrow or (3) their presence is a non-specific marker of inflammation. In this state-of-the-art review, we discuss the implication of RP in coronary artery disease and in hypo-responsiveness to the most commonly used anti-platelet drugs.

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.

scholarly journals Improved Detection of Potentially Pleiotropic Genes in Coronary Artery Disease and Chronic Kidney Disease Using GWAS Summary Statistics

2020 ◽  
Vol 11 ◽  
Author(s):  
Haimiao Chen ◽  
Ting Wang ◽  
Jinna Yang ◽  
Shuiping Huang ◽  
Ping Zeng
Keyword(s):  
Coronary Artery Disease ◽  
Chronic Kidney Disease ◽  
Coronary Artery ◽  
Kidney Disease ◽  
Association Studies ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genetic Determination ◽  
Artery Disease

The coexistence of coronary artery disease (CAD) and chronic kidney disease (CKD) implies overlapped genetic foundation. However, the common genetic determination between the two diseases remains largely unknown. Relying on summary statistics publicly available from large scale genome-wide association studies (n = 184,305 for CAD and n = 567,460 for CKD), we observed significant positive genetic correlation between CAD and CKD (rg = 0.173, p = 0.024) via the linkage disequilibrium score regression. Next, we implemented gene-based association analysis for each disease through MAGMA (Multi-marker Analysis of GenoMic Annotation) and detected 763 and 827 genes associated with CAD or CKD (FDR < 0.05). Among those 72 genes were shared between the two diseases. Furthermore, by integrating the overlapped genetic information between CAD and CKD, we implemented two pleiotropy-informed informatics approaches including cFDR (conditional false discovery rate) and GPA (Genetic analysis incorporating Pleiotropy and Annotation), and identified 169 and 504 shared genes (FDR < 0.05), of which 121 genes were simultaneously discovered by cFDR and GPA. Importantly, we found 11 potentially new pleiotropic genes related to both CAD and CKD (i.e., ARHGEF19, RSG1, NDST2, CAMK2G, VCL, LRP10, RBM23, USP10, WNT9B, GOSR2, and RPRML). Five of the newly identified pleiotropic genes were further repeated via an additional dataset CAD available from UK Biobank. Our functional enrichment analysis showed that those pleiotropic genes were enriched in diverse relevant pathway processes including quaternary ammonium group transmembrane transporter, dopamine transport. Overall, this study identifies common genetic architectures overlapped between CAD and CKD and will help to advance understanding of the molecular mechanisms underlying the comorbidity of the two diseases.

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