Association of ESR1 (rs2234693 and rs9340799), CETP (rs708272), MTHFR (rs1801133 and rs2274976) and MS (rs185087) polymorphisms with Coronary Artery Disease (CAD)

Raina, Jyotdeep Kour; Sharma, Minakashee; Panjaliya, Rakesh Kumar; Dogra, Vikas; Bakaya, Ashok; Kumar, Parvinder

doi:10.1186/s12872-020-01618-7

Cited by 20 publications

(23 citation statements)

References 49 publications

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“…The rare allele B2 is associated with a reduction in CETP activity, causing an elevation in HDL‐C 18–21 . This polymorphism was shown to relate to many disorders including CVD 22,23 . Li et al 24 and Kalantar et al 25 indicated that the association between CETP Taq1B polymorphism and HDL‐C concentrations became more clear when the role of diet was considered.…”

Section: Introductionmentioning

confidence: 99%

Interaction between CETP Taq1B polymorphism and HEI, DQI and DPI on metabolic biomarkers in patients with type 2 diabetes

Kalantar

Sotoudeh

Esmaeily

et al. 2021

J Human Nutrition Diet

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Background Type 2 diabetes mellitus (T2DM) is a multidimensional consequence of environmental and genetic factors. Cholesteryl ester transfer protein (CETP) Taq1B polymorphism has been reported as a main predictor of dyslipidaemia, comprising an important complication in persons with T2DM. However, diet could affect T2DM patients metabolic health. Methods We investigated the combination of gene–diet effects on some metabolic biomarkers. In our cross‐sectional study, blood samples of 220 patients were collected. Dietary indices (healthy eating index, dietary quality index and dietary phytochemical index) were obtained from a validated semi‐quantitative food frequency questionnaire. CETP Taq1B polymorphism was genotyped by a polymerase chain reaction‐restriction fragment polymorphism method. Data were analysed by analysis of covariance. Results The interaction between the CETP Taq1B polymorphism and dietary indices on low density lipoprotein/high density lipoprotein was significant (p < 0.001 both crude and adjusted models). In addition, the interaction between polymorphism and dietary quality index on total antioxidant capacity (p = 0.004 crude model, p = 0.005 after adjusting) and pentraxin 3 (p = 0.01 both crude and adjusted models) was significant. Also, the interaction between polymorphism and healthy eating index on waist circumference (p = 0.005 both crude and adjusted models) and dietary phytochemical index on interleukin‐18 (p = 0.03 crude model) was significant. Conclusions Our results indicated the effect of CETP Taq1B polymorphism on some inflammatory and anthropometrics markers (total antioxidant capacity, pentraxin 3, interleukin‐18, low density lipoprotein/high density lipoprotein and waist circumference) with high and low adherence to dietary incides.

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Section: Introductionmentioning

confidence: 99%

Interaction between CETP Taq1B polymorphism and HEI, DQI and DPI on metabolic biomarkers in patients with type 2 diabetes

Kalantar

Sotoudeh

Esmaeily

et al. 2021

J Human Nutrition Diet

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“…Endothelial dysfunction, oxidative stress and inflammation, which are the products of a multifactorial interplay between inherited and environmental risk factors, are established determinants of the atherosclerotic burden and CAD prognosis [ 4 , 28 ]. Large GWAS have been conducted in order to locate CAD-associated variants (SNPs) and decipher the underlying genetic fundament of the disease [ 6 , 29 – 35 ]. To date, a great number of susceptible multi-SNP loci have been identified with some of them reaching the stringent level of significance [ 6 , 32 , 34 , 36 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease—rationale and design of the GESS study

Vizirianakis

Chatzopoulou

Papazoglou

et al. 2021

BMC Cardiovasc Disord

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Background Coronary artery disease (CAD) remains one of the leading causes of mortality worldwide and is associated with multiple inherited and environmental risk factors. This study is designed to identify, design, and develop a panel of genetic markers that combined with clinical and angiographic information, will facilitate the creation of a personalized risk prediction algorithm (GEnetic Syntax Score—GESS). GESS score could be a reliable tool for predicting cardiovascular risk for future adverse events and for guiding therapeutic strategies. Methods GESS (ClinicalTrials.gov Identifier: NCT03150680) is a prospective, non-interventional clinical study designed to enroll 1080 consecutive patients with no prior history of coronary revascularization procedure, who undergo scheduled or emergency coronary angiography in AHEPA, University General Hospital of Thessaloniki. Next generation sequencing (NGS) technology will be used to genotype specific single-nucleotide polymorphisms (SNPs) across the genome of study participants, which were identified as clinically relevant to CAD after extensive bioinformatic analysis of literature-based SNPs. Enrichment analyses of Gene Ontology-Molecular Function, Reactome Pathways and Disease Ontology terms were also performed to identify the top 15 statistically significant terms and pathways. Furthermore, the SYNTAX score will be calculated for the assessment of CAD severity of all patients based on their angiographic findings. All patients will be followed-up for one-year, in order to record any major adverse cardiovascular events. Discussion A group of 228 SNPs was identified through bioinformatic and pharmacogenomic analysis to be involved in CAD through a wide range of pathways and was correlated with various laboratory and clinical parameters, along with the patients' response to clopidogrel and statin therapy. The annotation of these SNPs revealed 127 genes being affected by the presence of one or more SNPs. The first patient was enrolled in the study in February 2019 and enrollment is expected to be completed until June 2021. Hence, GESS is the first trial to date aspiring to develop a novel risk prediction algorithm, the GEnetic Syntax Score, able to identify patients at high risk for complex CAD based on their molecular signature profile and ultimately promote pharmacogenomics and precision medicine in routine clinical settings. Trial registration GESS trial registration: ClinicalTrials.gov Number: NCT03150680. Registered 12 May 2017- Prospectively registered, https://clinicaltrials.gov/ct2/show/NCT03150680.

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“…After completion of the sampling period i.e., 1 year, we found around 480 samples with 3 h each day at OPD. We also checked it on the pre-studied condition from our labs such as breast cancer which have a prevalence rate of 6% ( https://www.cancer.net/cancer-types/breast-cancer/statistics ), leukemia (9.5) 26 , 27 and Coronary artery diseases (CAD) (16%) 28 has found around 60 29 210 patients 30 and 400 subjects per year 31 respectively which is near to the calculated numbers by the model and also on congenital heart diseases (CHD) (8%) 32 and found 80 subjects per year (not published yet).…”

Section: Resultsmentioning

confidence: 99%

Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator

Sudershan

Mahajan

Panjaliya

et al. 2022

Sci Rep

Self Cite

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Looking at the population’s behavior by taking samples is quite uncertain due to its big and dynamic structure and unimaginable variability. All quantitative sampling approaches aim to draw a representative sample from the population so that the results of the studying samples can then be generalized back to the population. The probability of detecting a true effect of a study largely depends on the sample size and if taking small samples will give lowers statistical power, higher risk of missing a meaningful underlying difference. The probability of rejecting the null hypothesis i.e., finding significant difference using the sample largely depends upon the statistical power. There are a lot of online tools used for calculating the sample size, but none tell us about the availability of samples from single site in a fixed span. This study aims to provide an efficient calculation method for the availability of samples during a specific period of a research study which is an important question to be answered during the research study design. So, we have designed a spreadsheet-based sample availability calculator tool implemented in MS-Excel 2007.

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Association of ESR1 (rs2234693 and rs9340799), CETP (rs708272), MTHFR (rs1801133 and rs2274976) and MS (rs185087) polymorphisms with Coronary Artery Disease (CAD)

Cited by 20 publications

References 49 publications

Interaction between CETP Taq1B polymorphism and HEI, DQI and DPI on metabolic biomarkers in patients with type 2 diabetes

Interaction between CETP Taq1B polymorphism and HEI, DQI and DPI on metabolic biomarkers in patients with type 2 diabetes

The GEnetic Syntax Score: a genetic risk assessment implementation tool grading the complexity of coronary artery disease—rationale and design of the GESS study

Algorithm for sample availability prediction in a hospital-based epidemiological study spreadsheet-based sample availability calculator

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