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Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 64  |  Issue : 6  |  Page : 298-305

The risk stratification of coronary vascular disease as linked to homocysteine, its modulating genes, genetic polymorphisms, conventional predictors, and with antihypertensive medicaments


1 Department of Physiology, CMH Kharian Medical College, Kharian, Pakistan
2 Biochemistry Department, CMH Kharian Medical College, Kharian, Pakistan
3 Biochemistry Department, Mohiuddin Islamic Medical College, Azad Jammu and Kashmir, Pakistan
4 Department of Anesthesia, Major Shabeer Shareef THQ Level Hospital, Kunjah, Gujrat, Pakistan
5 Department of Physiology, Rawal Institute of Health Sciences, Rawalpindi, Pakistan

Date of Submission28-Jul-2021
Date of Decision17-Nov-2021
Date of Acceptance18-Nov-2021
Date of Web Publication27-Dec-2021

Correspondence Address:
Dr. Rizwan Masud
Department of Physiology, CMH Kharian Medical College, Postal Code: 50070, Kharian Cantt
Pakistan
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/cjp.cjp_71_21

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  Abstract 


Cardiovascular disease (CVD) have multifactorial nature, and owing to their disparate etiological roots, it is difficult to ascertain exact determinants of CVD. In the current study, primary objective was to determine association of single nucleotide polymorphisms (SNP) in folate pathway genes, homocysteine, antihypertensive medication, and of known risk factors in relation to CVD outcomes. The participants numbered 477 (controls, n = 201, ischemic heart disease patients, n = 95, and myocardial infarction cases, n = 181, respectively). SNPs that were queried for homocysteine pathway genes included, “methylene tetrahydrofolate reductase (MTHFR)” gene SNPs rs1801133 and rs1801131, “methyltransferase (MTR)” SNP rs1805087, “paraoxonase 1 (PON1)” SNP rs662, and angiotensin-converting enzyme (ACE) gene polymorphisms rs4646994. Medication data were collected through questionnaire, and serum-based parameters were analyzed through commercial kits. The analysis of variance and multiple comparison scrutiny revealed that age, gender, family history, cholesterol, creatinine, triglyceride, high density lipoproteins (HDL), homocysteine, beta-blocker, ACE inhibitors, MTHFR and PON1 SNPs related to coronary artery disease (CAD). On regression, rs662 SNPs and C-reactive protein had nonsignificant odds ratio, whereas age, gender, creatinine, and HDL were nonsignificant. Family history, cholesterol, homocysteine, beta blocker, and ACE inhibitors, homocysteine, rs1801133 and rs1801131 SNP maintained significance/significant odds for CAD. The current study indicates an intricate relationship between genetic variants, traditional factors, and drug usage in etiogenesis of arterial disease. Differences in SNPs, their modulated effects in consensus with medicinal usage may be related to ailment outcomes affecting coronary vasculature.

Keywords: Allele, coronary artery disease, homocysteine, methylene tetrahydrofolate reductase, single nucleotide polymorphism


How to cite this article:
Masud R, Anjum AF, Anwar MZ, Khan WU, Shahzad MA, Jawwad G. The risk stratification of coronary vascular disease as linked to homocysteine, its modulating genes, genetic polymorphisms, conventional predictors, and with antihypertensive medicaments. Chin J Physiol 2021;64:298-305

How to cite this URL:
Masud R, Anjum AF, Anwar MZ, Khan WU, Shahzad MA, Jawwad G. The risk stratification of coronary vascular disease as linked to homocysteine, its modulating genes, genetic polymorphisms, conventional predictors, and with antihypertensive medicaments. Chin J Physiol [serial online] 2021 [cited 2022 Aug 17];64:298-305. Available from: https://www.cjphysiology.org/text.asp?2021/64/6/298/333801




  Introduction Top


Coronary artery disease (CAD) is a major contributor and foremost constituent of cardiovascular diseases (CVD). The fatal outcomes related to vascular diseases and CAD remain high, and diseases of coronary vasculature are expected to continue as primary causes of mortality in the next decade.[1] CVD affects both the developed and developing nations, and that also with a considerable economic effect. Vascular disorders have complex etiology and the implied factors range from smoking to pollution, gender, age, genetic factors, as well as the proteins, amino acids, and lipids.[2] The well-characterized risk factors for CAD include old age, male gender, high blood pressure/blood sugar readings, elevated triglycerides/cholesterol levels, and smoking. All these factors implicate in unstable atherosclerotic plaques and ensuing high morbidity and mortality rates.[2],[3] Serum creatinine, higher body mass index (BMI), and positive family history of CAD have additional strong predisposition to the vascular disease outcomes.[4],[5] Literature exhibits novel risk factors as add-on predisposing factors for CVD outcomes. These newer factors for CAD include the amino acids, proteins, genes, and genetic polymorphisms.[5],[6]

Homocysteine, a sulfurated amino acid, and the folate pathways genes with the genetic polymorphisms have been implicated with higher risk of CAD. Over the past decades myriad of published work strongly implicates homocysteine levels with higher and independent risk of CAD, divination of disease, and with multiple vessel involvement in coronary vasculature.[5],[7],[8],[9],[10] Some of the CAD-related genes and polymorphisms in homocysteine pathway include methylene tetrahydrofolate reductase (MTHFR) gene with its C677T (rs1801133) and A1298C (rs1801131) polymorphisms; methyl tetrahydrofolate homocysteine methyltransferase (MTR) gene with A2756G (rs1805087) polymorphism; paraoxonase 1 (PON1) gene with A192G (rs662) polymorphism, and the angiotensin-converting enzyme (ACE) gene insertion/deletion (rs4646994) polymorphism, respectively. There is significant association between rs1801133 and rs1801131 single nucleotide polymorphisms (SNPs) in MTHFR and higher risk as well as early onset of CAD.[8],[11],[12] The rs662 SNP in PON1 has been additionally related to occurrence of CAD.[8],[11],[13] The rs4646994 allele in ACE gene in a similar fashion has been implicated with dyslipidemia, diabetes, and related higher risk of CAD in local as well as in other regions.[8],[11],[14],[15]

The medications used for the management of hypertension, dyslipidemia, and optimal cardiac function include statins, aspirin, beta-blockers, calcium channel blockers, ACE inhibitors, and angiotensin receptor blockers (ARB). There is huge interpatient inconsistency regarding medication efficacy and evidence suggests that these variances depend on the individual genotypes.[16],[17] There is an additional issue of drug compliance among patients as a major proportion of patients has a strong issue related to drug compliance.[18] In the current study we aim to elucidate the polymorphisms in folate pathway, and differences in medicinal usage as they relate to risk of CAD.


  Materials and Methods Top


Characteristics/basics of the study

The Institutional Review Board, Combined Military Hospital (CMH) Kharian Medical College (CKMC), Kharian Cantt. approved the study (Approval No. for study: CKMC Diary number 115, dated January 03, 2019). Approval for the study was obtained in January 2019. The written informed consent was attained from all participants for data usage and for sampling of the project. The controls, myocardial infarction (MI)/CAD cases, and ischemic heart disease (IHD) patients were engaged from the District Headquarter Hospital, from Benazir Bhutto Hospital, Rawalpindi, and from the CMH Kharian, respectively. Patients with renal diseases, cerebral vascular accidents, transient ischemic attacks, and cardiac failure were excluded from the current study. The number of participants added up to 477, 201 controls, 95 IHD patients, and 181 MI cases, respectively. For the calculation of sample size, the proportion data for CAD patients was evaluated for the Pakistani population, the margin of error was calculated by previous studies and by preliminary data obtained for current study. Confidence level was set at 95%. The margin of error was kept at average of 11%,[8],[19] and population proportion for CAD was considered at 29%.[20] (https://www.who.int/nmh/countries/pak_en.pdf) The website “Calculator.net” was used for generation of sample size and it was obtained at sixty-six samples per group. Sample size estimation was reworked through “benchmark 6 sigma” through putting in data for 95% confidence interval, mean values and standard deviation (SD), and the requisite sample size per group was acquired at sixty-three.

Presentation features of participants

The main presentation features for the participants have been stated elsewhere;[8] there was however some difference in patient selection for this study. IHD patients were not included in earlier study but these patients were inclusive in the current study. All participants were diagnosed hypertensive patients and were on various antihypertensives. The participants considered as controls were recruited from the hospital outpatient department and were all diagnosed hypertensive patients on various antihypertensive medications. None of the controls exhibited any sign of ischemic chest pain and their electrocardiography (ECG) recordings were unremarkable. They were on visits to their attending physicians as part of their routine checkups. The patients presented to the hospital emergency room (ER) within 3–4 h of acute symptoms. The majority of IHD and CAD participants, on presentation, had distinctive chest distress/pain (present for half to 1 h), nervousness/anxiety with some radiation of pain. The cardiology department was consulted for checkup of all the patients. The examination for lung edema and subsequently repeat ECG was performed and the cardiac enzymes were analyzed for suspected patients with normal ECG. Patients with chest ache, ischemic ECG findings, and within normal limit cardiac markers were categorized as IHD patients. Patients with elevated ST segment on repeat ECG (STEMI) or with non-significant ECG changes yet with positive cardiac markers (NSTEMI) were characterized as MI/CAD cases. On presentation, pulse, respiratory rate, systolic blood pressure (SBP mmHg), diastolic blood pressure (DBP mmHg) (recorded through mercury sphygmomanometer), and the temperature (°C) were recorded for all participants in the study. The vitals were recorded during sampling as well. Height (in meters) and weight (in kilograms) were documented for BMI (calculated by standardized formula).

Serum analysis and genetic analysis of collected samples

The MI cases were admitted and the IHD patients were retained in ER for the follow up and for the sampling purposes. Early morning (fasting) samples were obtained from all participants. For serum analysis, plain tubes were used for sample collection, and the serum was stored in − 20°C refrigerator till analysis of samples. The serum analyzed covariates included (a) homocysteine (μmol/L), (b) triglycerides (mg/dl), (c) cholesterol (mg/dl), (d) creatinine (mg/dl), (e) fasting blood sugar (FBS) (mg/dl), and (f) high density lipoproteins (mg/dl). Homocysteine analysis was performed through enzyme-linked immunosorbent assay (ELISA) and the kit was “EIA kit DRG International Inc., USA.” The commercial kits (AMP Diagnostics, AMEDA Labordiagnostik GmbH) were used for analyzing other factors. EDTA vacutainers were used for collecting blood samples for DNA extraction. DNA extraction was completed from peripheral leukocytes, and the extracted DNA samples were thereafter stored at 4°C. A questionnaire was used for data collection about drug usage, previously prescribed drugs and their usage by the patients. The questionnaire included family history of CAD/CHD, medication data for use of statins, aspirin, beta blockers, calcium channel blockers, diuretics, and ACE inhibitors, and about the persistence to the prescription.

Investigation of single nucleotide polymorphisms: Tetra primer amplification refractory mutation system-polymerase chain reaction; (restriction fragment length polymorphism analysis)

The detailed account of the primers, reaction products, and restriction fragment length polymorphism validation is stated in detail elsewhere.[11] Briefly, the Santa Cruz Genome Browser Database (University of California) site “genome.ucsc.edu/cgi-bin/hgGateway” was used for genomic sequencing of SNP, contiguous sequences, and associated specifics. The sequences were uploaded to http://cedar.genetics.soton.ac.uk, and primers were generated for study. Tetra primer amplification refractory mutation system-polymerase chain reaction requires two pairs of primers or specifically four primers for a single reaction; an outer pair and an inner pair of primers. The rs1801133, rs1801131 MTHFR SNPs, rs1805087 MTR SNP, and rs662 PON1 SNP, were committed to tetra primer sequence technique while only the outer primer pairs resolved the ACE gene insertion deletion polymorphism (rs4646994), respectively.

Statistical analysis

The entire data for current study were analyzed by employing two different statistical programs and two distinct software programs. Since homocysteine values were skewed, therefore homocysteine levels were log transmuted, and subsequent data computed with these log values. The analysis of variance (ANOVA), and multiple comparison “Tamhane” analysis was accomplished by IBM SPSS software–version 25.0. (IBM Corp. IBM SPSS Statistics for Windows, version 25.0. Armonk, NY, USA: IBM Corp. Released 2017). All studied factors were scrutinized through ANOVA, and the P < 0.05 was considered statistically significant. Subsequently, we performed regression analysis along-with computation of the odds ratios (OR) and 95% confidence intervals (95% CI) estimation for the data. Regression was done to validate ANOVA and to ascertain disease likelihood. Regression analysis was executed through R 4.0.2 statistical package environment (R Core Team 2020. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria).


  Results Top


Descriptive data

The data of age for the three groups (mean ± SD) was controls 63.80 ± 7.31, IHD 61.67 ± 9.26, and MI cases 65.44 ± 8.14. Females in the three groups were, controls n = 86 (42.8%), IHD n = 46 (48.4%), and MI cases n = 56 (30.9%), and males were controls n = 115 (57.2%), IHD n = 49 (51.6%), and MI cases n = 125 (69.1%) respectively. The values for the blood factors (mg/dl) were: serum cholesterol 178.85 ± 23.99, 182.27 ± 31.73, and 188.16 ± 37.44; serum creatinine 0.89 ± 0.34, 0.93 ± 0.35, and 1.10 ± 0.36; FBS levels 108.96 ± 35.08, 107.97 ± 30.73, and 117.11 ± 45.61; HDL levels were 55.64 ± 15.50, 59.46 ± 18.48, 50.45 ± 14.51; whereas serum total triglyceride levels were 115.71 ± 56.17, 109.44 ± 52.85, and 159.27 ± 84.75, in the control, IHD, and MI case groups, respectively. SBP and DBP reading in the three studied groups were 135.23 ± 13.98, 133.03 ± 17.88, 133.51 ± 17.48 (mmHg), and 80.37 ± 10.28, 80.85 ± 10.77, 80.03 ± 11.15 (mmHg), respectively. The serum homocysteine levels (log transformed values) in the control group were 1.17 ± 0.07 μmol/l, in IHD group were 1.19 ± 0.08 μmol/l, and in MI/CAD case group were 1.21 ± 0.09 μmol/l, respectively [Table 1].
Table 1: Characteristics of the participants/patients

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Analysis of variance/post hoc analysis

The ANOVA analysis revealed statistical significance for age, gender, family history, cholesterol, creatinine, triglyceride, HDL, homocysteine, beta blockers, ACE inhibitors, and the MTHFR and PON1 genes. For age, overall significance was P = 0.001 with significance in IHD versus MI case group. The overall significance for cholesterol was P = 0.015 with difference in control versus MI case group and for gender was P = 0.032 with differences significant in IHD versus MI and in control versus MI cases. For the family history of CAD, for creatinine, triglyceride and HDL levels, the overall significance was P < 0.001 with individual significances in IHD patients versus MI case and in control versus MI case groups, respectively. For homocysteine levels, inclusive significance was P < 0.001, with significance difference in control versus MI case category. For the use of beta-blockers and ACE inhibitors, the general significance was P = 0.019 and P < 0.001, for former group the significance was observed in control versus MI whereas in latter group the IHD versus MI cases group had significance as well. The MTHFR rs1801133 and rs1801131 SNPs had P = 0.032 and P < 0.001 with significance in control versus MI cases in former and in IHD versus MI and control versus MI cases in latter group. Finally, the rs662 PON1 SNP had P < 0.001 with significant differences in IHD patient versus MI and control versus MI groups on multiple comparison respectively [Table 2].
Table 2: The relationship of studied traits with coronary artery disease, based on ANOVA and post hoc multiple test

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  Results for the Regression Analysis Top


Following the regression analysis, age difference (P = 0.065), gender (P = 0.230), creatinine (P = 0.346), HDL (P = 0.614) and PON1 rs662 SNP (P = 0.010, OR = 0.766, 95% CI 0.692–0.848) could not maintain significance with CAD. Values for serum cholesterol levels were (P = 0.018, OR = 1.003, 95% CI: 1.000–1.005), for family history (P < 0.001, OR = 1.351, 95% CI 1.167–1.563), for triglycerides (P < 0.001 , OR = 1.002, 95% CI 1.001–1.003), for beta blocker usage (P = 0.029, OR = 1.176, 95% CI 1.017–1.359), and for ACE inhibitors were (P = 0.076, OR = 1.264, 95% CI 1.088–1.468). The strong relation of homocysteine with CAD remained significant after regression analysis as well (P < 0.001, OR = 2.335, 95% CI 1.416–3.772). The MTHFR SNPs rs1801133 (P < 0.001, OR = 1.270, 95% CI 1.115–1.445) and rs1801131 (P < 0.001, OR = 1.372, 95% CI 1.208–1.559), both maintained their statistical significance through ANOVA to regression [Table 3].
Table 3: The relationship of studied traits with coronary artery disease, based on regression analysis (associated odds ratios and 95% confidence intervals)

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The frequency distribution of rs1801133 and rs1801131 MTHFR SNPs, rs1805087 MTR SNP, and difference in use of beta blockers in the three study groups: controls, IHD patients, and CAD cases, are plotted in [Figure 1]. The differences in homocysteine, cholesterol, triglycerides, HDL, and creatinine levels, in the three studied groups are plotted in [Figure 2].
Figure 1: Graphic presentation (percentage frequency distribution) concerning allelic variations in the significant homocysteine pathway gene polymorphisms and the significant medicinal usage (amongst the controls, ischemic heart disease patients, and coronary artery disease cases); (a) differences in methylene tetrahydrofolate reductase single nucleotide polymorphisms rs1801133 amongst participants; (b) differences in methylene tetrahydrofolate reductase single nucleotide polymorphisms rs1801131 amongst participants; (c) differences in beta blocker usage amongst participants.

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Figure 2: Graphic presentation of the levels/values of blood parameters, with significant statistical annotations (amongst the controls, ischemic heart disease patients, and coronary artery disease cases); (a) differences in log homocysteine levels amongst participants; (b) differences in serum cholesterol readings amongst participants; (c) differences in serum triglyceride levels amongst participants; (d) differences in high density lipoproteins serum levels amongst participants, and (e) differences in serum creatinine levels amongst participants.

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  Discussion Top


CAD results in significant waning in health in addition to significant decline in the life expectancy. The ongoing research is focused on risk predictors for multigenic health problems, with emphasis on new “genetic” risk factors and on relationship with medication as a cause of vascular diseases. The acknowledged risk factors, and efforts to mitigate these risks can be of assistance to vascular disease patients and can reduce the number of CAD-related complications and deaths. The genetic (SNP) analysis, homocysteine estimation by ELISA based techniques, data on drug usage, and serum parameters analysis, followed by rigorous statistical analysis was carried out in the current study, and the results thereby implicate MTHFR gene SNPs, homocysteine, cholesterol, and difference in drug usage as compounding factors for the risk of CAD.

The high level of total cholesterol has been traditionally related to vascular disease outcomes and CAD incidence.[21] In the present study, cholesterol was significantly related to MI following ANOVA and following regression analysis. Age and family history of CAD have been strongly and positively linked with CAD previously, with family history warranting that CAD affects younger individuals in higher risk category.[22] In the present study, both age and family history of CAD had strong positive association with CAD and MI following ANOVA, however, following linear regression analysis age was non-significant (P = 0.065) while family history of CAD maintained its positive association with disease outcome.

A relatively novel recognized risk factor, homocysteine, has been intensely studied for CAD associated risk, with studies finding either strong or weak, and occasionally, no association with CAD. Hyperhomocysteinemia (elevated homocysteine level) is associated with early appearance of CAD, severe adverse outcomes, relatively high mortality, and involvement of vascular beds elsewhere.[5],[10] The present study exhibited strong predictive risk of elevated homocysteine levels with vascular disease (ANOVA analysis P < 0.001), exhibiting strong risk in IHD versus MI case and in controls versus MI cases, and in the subsequent regression analysis (P < 0.001, OR = 2.335). Homocysteine, therefore, appears as an independent risk factor for CAD in the present study as well.

The SNPs in folate pathway genes have mixed picture with CAD as far as the recent literature is concerned. The MTR gene SNP A2756G (rs1805087) and PON1 gene SNP A192G (rs662) have been inconsistently linked to CAD risk.[23],[24] The MTR gene polymorphism had no significance in the current study, while the PON1 SNP lost significance in regression analysis (OR = 0.766), despite strong association following ANOVA (P < 0.001). The ACE gene insertion deletion polymorphism (rs4646994), moreover, had no significant link to CAD in current study. The rs1801133 (C677T) and rs1801131 (A1298C) are strongly linked to CAD, and studies suggest that the mutant alleles carry an even stronger risk of CAD.[11],[25] Hyperhomocysteinemia and MTHFR SNPs have supplementary effect in CAD, and in vascular outcomes,[8],[11],[26] and both homocysteine and MTHFR SNP were strongly and significantly relevant in current study as well.

The present study furthermore focused on medications and the associated link to CAD. The various anti–hypertensive medications have attributable differences in risk of arterial diseases. Statin usage is well documented and is considered to lower the CAD risk as compared to aspirin,[27] whereas, other studies consider aspirin therapy to be highly effective as well.[28] In the current study, aspirin usage (P = 0.148) and statin usage (P = 0.785) were not significant following ANOVA, and subsequently following regression analysis. Beta-blocker usage is associated with “lower CAD-related mortality” if given early after suffering an infarction.[29] Beta antagonists and calcium channel antagonists are related to altered endothelial function and higher risk of CVD as per some studies.[30] In the present study, use of calcium channel blockers were nonsignificant in ANOVA and regression, but the beta antagonist usage was associated with CAD in ANOVA (P = 0.019), with difference in control versus MI group, and additionally beta-blockage attained significance with CAD following regression analysis. ACE inhibitors and ARB prescription is more focused in patients following an acute coronary disease, and are associated with lowered fatal outcome.[31] Patient adherence to ACE inhibitor/ARB compliance, before an acute attack is ambiguous. In the present study, ACE inhibitor usage was associated with CAD through ANOVA and through regression as well.

In management aspect for CAD, the compliance of drugs is another confounding factor. Although there are issues of drug compliance, still, strict adherence to anti-hypertensive medication is not only associated with better quality of life, with prevention of micro/macro-vascular complications, and with reduced healthcare-related disbursement on drugs and related services.[32] In an Asian cohort of hypertensive patients and in groups of acute coronary syndrome (ACS) and CAD patients, there was poor drug compliance, highlighting that the patients do not take prescribed medication regularly.[33],[34] Generally a great majority of patients take medicine only during/after disease complications.[35] The sporadic intake of medication predisposes to fluctuating blood pressure readings and flared up cardiovascular complication processes. Non–complaint patients are at an extremely increased risk as compared to complaint patients.[36] There were reports of patchy drug usage by the participants in the current study, and the presence/acute outcome of disease, despite administration of antihypertensive medications may be related to poor drug compliance.

Limitations of study

The comparatively restricted number of participants in study, the inclusion of patients from one segment of the province, and the use of hypertensive participants as controls are the limitations of the current study. In future studies, ailment-free controls, larger groups of participants, and diversified sampling cohorts may provide improved outcomes and may corroborate/validate the currently concluded results.


  Conclusion Top


The risk modulators for vascular disease outcome in this study included hyperhomocysteinemia, positive family history, cholesterol, triglyceride levels, beta-blocker, and ACE inhibitor usage, the rs1801133, and rs1801131 MTHFR SNPs. The collective effects of these all these factors may result in epistasis-based interactive role in coronary disease outcome.

Acknowledgments

The authors thanked Prof Dr IJ Kullo, Dr Keyue Ding, Dr Haider, and Dr Aleem for participants, samples, for the valued remarks, and for assistance in article script.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

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