Total impact of oxidative stress genes on cardiovascular events – 7-year follow-up study

doi:10.21203/rs.3.rs-1631060/v1

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Total impact of oxidative stress genes on cardiovascular events – 7-year follow-up study

https://doi.org/10.21203/rs.3.rs-1631060/v1

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published 23 Jan, 2023

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Cardiovascular (CV) events are the number one cause of lifetime disability and deaths worldwide. It is well known that traditional risk factors do not fully correlate with clinical outcomes; therefore, searching for other markers that would explain CV events occurrence seems essential. Of importance, one of the main factors at the origin of CV events is oxidative stress, causing inflammation and atherosclerotic plaque instability. Therefore the present study was conducted to evaluate eight carefully selected genetic polymorphisms related to oxidative stress as risk modifiers for CV events. A cohort of 1020 patients with coronary atherosclerosis was analysed in a 7-year follow-up observational study. The following endpoints were assessed: CV death, myocardial infarction (MI) and a combined endpoint of CV death/MI/stroke. Our results show that single polymorphisms are not significant cardiovascular disease risk factors, but genetic risk score (GRS), defined as the accumulation of our eight studied polymorphisms, was significantly associated with the three studied follow-up endpoints. In conclusion, when regarding CV events, GRS investigated here can become clinically meaningful and undoubtedly adds to the knowledge in stratifying the risk of CV events.

gene polymorphism

SNP

GRS

oxidative stress

cardiovascular disease

CV events

Despite increasingly intensive primary and secondary prevention, cardiovascular (CV) events continue to be the world's leading cause of death (Virani et al. 2020), typically occurring due to a sudden atherosclerotic plaque rupture in the presence of systemic inflammation (d’Alessandro et al. 2020)(Alfaddagh et al. 2020). Traditional risk factors do not fully correlate with clinical outcomes; therefore, searching for other markers that explain the different courses of cardiovascular disease (CVD), seems rational (Daiber et al. 2021)(Lechner et al. 2020)(Pavkova Goldbergova et al. 2017). As oxidative stress, identified as an increase of reactive oxygen species (ROS), leads to oxidative damage in cells and promotes inflammation, it may be perceived as an essential player in the disruption and thrombosis of atherosclerotic plaques(Sies 2015)(Kibel et al. 2020). Moreover, as clinical data suggest, CVD has a strong genetic component. Based on these two facts, we presumed that selected single nucleotide polymorphisms (SNPs) within genes encoding crucial enzymes of redox regulation and the accumulation of those SNPs could give new insights into the molecular basis of CVD(Katakami et al. 2014)(Augusciak-Duma et al. 2021).

In the present 7-year follow-up observation study, we used eight selected single nucleotide polymorphisms (SNPs) within genes encoding crucial enzymes of redox regulation and the accumulation of those variants defined as genetic risk score (GRS), under the assumption that they may impact CV events in a significant manner. Subsequent SNPs we brought to analysis include the following: PON1 c.575A>G, MPO c.-463G>A, SOD2 c.47T>C, GCLM c.-590C>T, NOS3 c.894G>T, NOS3 c.-786T>C, CYBA c.214C>T and CYBA c.-932A>G (Table 1). The eight SNPs and their GRS were assessed as the potential risk factors for CV death, nonfatal myocardial infarction (MI), and the combined end point of cardiovascular death, nonfatal MI or nonfatal cerebral stroke (CV death/MI/stroke).

Table 1

Baseline characteristics of the investigated SNPs (single nucleotide polymorphisms)

Enzyme	Gene	SNP	Ref.	Gene location	Phenotypic consequence of variant	rs
Paraoxonase1 (PON1)	PON1	*PON1* c.575 A>G	(Shunmoogam et al. 2018), (Deng et al. 2020)	7q21.3; Exon 6	¹⁹²Gln→Arg higher PON1 activity	rs662
Myeloperoxidase (MPO)	MPO	*MPO* c.-463 A>G	(Daugherty et al. 1994), (Ergen et al. 2011)	17q23.1; Promoter	Increased gene expression	rs2333227
Manganese superoxide dismutase (MnSOD)	SOD2	*SOD2* c.47C>T	(Bresciani et al. 2013), (Lian et al. 2019)	6q25.3; Exon 2	¹⁶Val→Ala	rs4880
γ-glutamyl-cysteine ligase (GCL)	GCLM	*GCLM* c.588 C>T	(Nakamura et al. 2002), (Franklin et al. 2009)	1p22.1; Promoter	Decreased glutathione production	rs41303970
Endothelial nitric oxide synthase (eNOS)	NOS3	*eNOS* c.894 G>T	(Aimo et al. 2019), (Oliveira-Paula et al. 2016), (Erbs et al. 2006)	7q36; Exon 7	²⁹⁸Glu→Asp; lower NO and higher lipid levels	rs1799983
Endothelial nitric oxide synthase (eNOS)	NOS3	*eNOS* c.-786 C>T		7q36; Promoter	Increased gene expression by 50%	rs2070744
NADPH oxidase (p22phox subunit)	CYBA	*CYBA* c.214 T>C	(Inoue et al. 1998), (San José et al. 2008), (Racis et al. 2020a)	16q24; Exon 4	⁷²His→Tyr; affected heme binding	rs4673
NADPH oxidase (p22phox subunit)	CYBA	*CYBA* c.-932 G>A		16q24; Promoter	Decreased gene expression	rs9932581

2.1. Study Population

Health-related data from 1905 patients referred for diagnostic coronary angiography to the First Department of Cardiology of the Medical University of Gdansk between 2003 and 2006 were used to compile a study population (Wirtwein et al. 2017)(Wirtwein et al. 2018). In this project, as in our previous publication (Racis et al. 2020b), the same group with coronary atherosclerosis confirmed in coronary angiography was enrolled, however, the final analysis was conducted on 1020 individuals since 79 patients lacked follow-up data; detailed inclusion and exclusion criteria are presented in Fig 1.

2.2. Follow-Up Study

The prospective data were obtained from the National Polish Health Service by means of the patients’ names and Polish residence identification numbers. All patients were observed from the date of coronary angiography until 31 December 2011. The data used to determine the evaluated end points were collected in a 7-year follow-up (mean, 96 months).

The end points, also defined as CV events, were as follows: (1) CV death, (2) nonfatal myocardial infarction (MI) and (3) a combined end point of CV death, nonfatal MI or nonfatal cerebral stroke (CV death/MI/stroke). The International Statistical Classification of Diseases and Related Health Problems defined the term CV death. The term MI was applied to non–ST-elevation MI and ST-elevation MI. MI and stroke diagnoses were performed according to the European Society of Cardiology and the European Stroke Organization guidelines, respectively.

2.3. Genetic Analyses

The analysis included eight SNPs: PON1 c.575A>G, MPO c.-463G>A, SOD2 c.47T>C, GCLM c.-590C>T, NOS3 c.894G>T, NOS3 c.-786T>C, CYBA c.214C>T and CYBA c.-932A>G; these SNPs constituted the same set of SNPs analysed in our previous study. Primers, probe sequences, concentrations of reagents, and genotyping conditions are listed in Table S1. The risk alleles were defined according to their potential to increase the extent of atherosclerosis, as presented in our previous publication (Racis et al. 2020b). After each SNP was investigated individually, the additive effect of the eight SNPs was analysed as a GRS that reflected the total impact of genetic variants.

To construct the GRS model the number of risk alleles of every patient was established (0: no risk allele; 1: one risk allele, 2: two risk alleles) and multiplied by eight (the number of SNPs). Although seventeen groups of patients could be created (from 0 [having no risk alleles] to 16 [having risk alleles exclusively]), only 12 groups were selected—from the group with one to the group with 12 risk alleles—because no patients had 0, 13, 14, 15 or 16 risk alleles present. Thus, patients were divided amongst the following groups: 1 (n = 16), 2 (n = 50), 3 (n = 113), 4 (n = 178), 5 (n = 185), 6 (n = 210), 7 (n = 134), 8 (n = 79), 9 (n = 40), 10 (n = 9), 11 (n = 5) and 12 (n = 1). Then, these 12 groups were merged into four GRS groups according to the number of patients: the first three groups (1, 2 and 3 [n = 179]); the last five groups (8-12 [n = 136]) and the middle groups in sets of two (4 and 5 [n = 363]; 6 and 7 [n = 344]). Ultimately, according to the analysis of the Kaplan-Meyer curves, which reflected the different behaviour of groups 1-3, based on the likelihood adaptive fusing model selection, the whole population was divided into two final groups—GRS < 4 (n = 179) and GRS ≥ 4 (n = 843), which were named the low GRS group and the high GRS group, respectively (Fig 2).

2.4. Statistical Analysis

Continuous variables were expressed as means ± standard deviations (SDs). Categorical (dichotomous) variables were expressed as frequencies (%). For all SNPs, the risk allele frequencies were calculated. Hazard ratios (HRs) and 95% CIs were determined for each event using multivariate Cox proportional hazards models, in which one key independent variable (risk allele, GRS) was adjusted for age and sex. The clinical characteristics of the patients were presented as means ± SDs and as medians for continuous variables (i.e., body mass index, triglyceride level) or percentages for categorical variables (i.e., smoking history, hypertension, diabetes). Smoking status was self-reported. Deviations from the Hardy-Weinberg equilibrium for the genotypes were assessed using a chi-square test. The chi-square tests compared the frequencies of categorical variables between groups, and the Wilcoxon test compared levels of continuous variables between groups. The follow-up events were presented using the Kaplan-Meier curves, and the odds ratio (OR) and the log-rank test assessed the differences in survival (cumulative incidence of events) among different groups. The model with two groups according to the number of risk alleles (GRS < 4 and GRS ≥ 4) was chosen after adaptive fusing based on the likelihood ratio method as the one with the highest log-likelihood (Sitko and Biecek 2017). An alpha value of 0.05 was considered significant. All statistical analyses were performed using R version 4.0.2 (https://www.R-project.org).

3.1. Baseline Characteristics

The characteristics of the entire population and of the two GRS subgroups are presented in Table 2. There were no statistically significant differences between the two GRS subgroups regarding the clinical characteristics and the prevalence of risk factors. All the SNPs were in Hardy-Weinberg equilibrium. During the median 7-year follow-up, 47 incidences of CV death, 82 cases of nonfatal MI and 36 cases of nonfatal cerebral stroke were reported. The prevalence of the combined end point (CV death/MI/stroke) was 162 cases.

Table 2

Baseline subject characteristics

Parameters	Total n=1020	GRS < 4 n=179	GRS ≥ 4 n=841	p. value
Age (years): mean ±SD	64.1 ±9.4	63.5 ±8.9	64.3 ±9.5	ns
Gender (male): n (%)	676 (66.0 %)	123 (69%)	553 (66%)	ns
BMI (kg/m²): mean ±SD	28.0 ±4.1	27.9 ±4.1	28.1 ±4.1	ns
Hypertension: n (%)	796 (81.1%)	143 (83%)	653 (81%)	ns
Diabetes: n (%)	243 (25.0%)	52 (30%)	191 (24%)	ns
HbA1c, mean ±SD	6.32 ±1.16	6.36 ±1.16	6.32 ±1.16	ns
Total cholesterol (mg/dL), mean ±SD	206.6 ±51.6	206.2 ±46.2	206.7 ±52.0	ns
LDL cholesterol (mg/dL), mean ±SD	123.3 ±43.8	125.0 ±43.1	122.9 ±43.9	ns
HDL cholesterol (mg/dL), mean ±SD	54.5 ±13.9	53.9 ±14.8	54.7 ±13.7	ns
Triglycerides (mg/dL), mean ±SD	146.5 ±92.7	142.2 ±64.9	147.4 ±97.9	ns
History of smoking: n (%)	632 (67.0%)	115 (69%)	517 (67%)	ns
CVD in family: n (%)	546 (54.0%)	85 (51%)	421 (55%)	ns

ns: non statistically significant; n: number of subjects included into analysis; SD: standard deviation; BMI: body mass index; LDL: low-density lipoprotein; HDL: high-density lipoprotein; CVD: cardiovascular disease;

3.2. Individual SNPs and CV Events

The relationship between individual SNP and the risk of CV events was evaluated. Cox proportional hazard regression analyses accounting for age, sex and genotype showed the clinical significance of the CYBA c.214C>T SNP, in which the T allele was protective against CV death (HR = 0.59; 95% CI: 0.37-0.94; log-rank p = 0.026). In case of analyses involving other SNPs, no statistically significant outcomes with follow-up end points were observed (Table 3).

Table 3

Hazard ratio of CV death, MI and CV death/MI/stroke regarding individual SNPs and GRS models.

		CV death			MI			CV death/MI/stroke
SNP	Risk allele	HR	95% CI	p-value	HR	95% CI	p-value	HR	95% CI	p-value
PON1 c.575 A>G	G	0.82	0.51-1.34	ns	1.06	0.75-1.51	ns	0.97	0.75-1.24	ns
MPO c.-463 A>G	A	1.14	0.67-1.93	ns	0.70	0.44-1.12	ns	0.93	0.69-1.26	ns
SOD2 c.47C>T	T	0.74	0.48-1.12	ns	1.16	0.85-1.58	ns	0.96	0.77-1.20	ns
GCLM c.588 C>T	T	0.68	0.42-1.10	ns	1.28	0.82-1.98	ns	0.95	0.72-1.25	ns
eNOS c.894 G>T	T	0.65	0.39-1.08	ns	0.88	0.62-1.25	ns	0.79	0.61-1.03	ns
eNOS c.-786 C>T	C	0.86	0.57-1.31	ns	0.79	0.57-1.09	ns	0.81	0.65-1.02	ns
CYBA c.214 T>C	T	0.59	0.37-0.94	0.026	0.84	0.60-1.16	ns	0.91	0.73-1.15	ns
CYBA c.-932 G>A	G	1.01	0.67-1.52	ns	0.93	0.68-1.27	ns	0.92	0.73-1.14	ns
GRS models
GRS^u		0.87	0.75-1.01	ns	0.91	0.81-1.02	ns	0.92	0.85-0.99	0.037
GRS^a		0.87	0.74-1.01	ns	0.91	0.81-1.02	ns	0.92	0.85-1.00	0.043
GRS ≥4^u		0.49	0.26-0.92	0.027	0.54	0.33-0.87	0.011	0.60	0.42-0.85	0.004
GRS ≥4^a		0.47	0.25-0.89	0.020	0.52	0.33-0.87	0.011	0.59	0.42-0.84	0.003

ns: non statistically significant; SNP: single nucleotide polymorphism; CV death: cardiovascular death; MI: myocardial infarction; HR: hazard ratio; 95%CI = 95% Confidence Interval; GRS: genetic risk score; Cox proportional hazard regression analyses: ^uunadjusted; ^aadjusted for age and sex;

3.3. GRS and CV Events

Among the patients with complete genetic data, the additive effect of eight SNPs on the studied follow-up end points were evaluated amongst patients in four GRS groups, depending on the number of risk alleles they carried: GRS 1-3 (n = 179), GRS 4-5 (n = 363), GRS 6-7 (n = 344) and GRS 8-12 (n = 136). The Kaplan-Meier curves depicting the cumulative probability of the follow-up end points revealed statistically significant differences in cumulative incidence of CV death/MI/stroke (log-rank p = 0.031) and trends regarding CV death and MI (log-rank p = 0.092 and p = 0.069, respectively) (Fig 3a, 4a, 5a). After implementation of adaptive fusing based on the likelihood ratio method, the Kaplan-Meier curves of two final groups depicting the cumulative probability of the follow-up end points revealed a significantly lower risk of CV death (log-rank p = 0.024), nonfatal MI (log-rank p = 0.0097) and CV death/MI/stroke (log-rank p = 0.0035) in the high GRS group compared with the low GRS group (Fig 3b, 4b, 5b).

Simultaneously, the Cox proportional hazard regression analyses revealed that the risk of CV death non-fatal MI and CV death/MI/stroke in the high GRS group was significantly lower than in the low GRS group (HR = 0.49 [95% CI: 0.26-0.92; p = 0.027]; 0.54 [95% CI: 0.33-0.87; p = 0.011]; and 0.60 [95% CI: 0.42-0.85; p = 0.004], respectively). The outcome stayed significant when adjusted for sex and age: (HR = 0.47 [95% CI: 0.25-0.89; p = 0.020]; 0.52 [95% CI: 0.33-0.87; p = 0.011]; and 0.59 [95% CI: 0.42-0.84; p = 0.003], respectively) (Table 3). Furthermore, the OR analyses showed that the risk of CV events was significantly lower in the high GRS group than in the low GRS group (CV death OR = 0.56 [95% CI: 0.36-0.85; p = 0.006]; MI OR = 0.48 [95% CI: 0.25-0.92; p = 0.024]; and CV death/MI/stroke OR = 0.54 [95% CI: 0.37-0.81; p = 0.002]).

Our study results indicate that only one SNP—CYBAc.214T—was associated with one end point (CV death/MI/stroke). However, GRS was significantly associated with all three follow-up end points. According to these results, having fewer than four risk alleles within the eight investigated SNPs, can be a risk factor for CV death, nonfatal MI and CVdeath/MI/stroke. Conversely, having four or more risk alleles within the eight investigated SNPs, can be a protective factor against CV death, nonfatal MI and CVdeath/MI/stroke.

Oxidative stress is one of the main factors at the origin of CV events, which are the number one cause of lifetime disabilities and deaths worldwide. In the study we investigated eight carefully chosen oxidative stress-related SNPs within genes encoding crucial enzymes of redox regulation and their additive effect on CV events occurrence. Our results show that GRS, defined as the total impact of eight investigated SNPs is significantly associated with three studied follow-up end points: CV death, nonfatal MI and CVdeath/MI/stroke. Thus, we can assume that the accumulation of oxidative stress-related SNPs can contribute to the pathophysiology of the atherosclerotic plaque by making it more unstable, which leads to acute manifestation of cardiovascular disease. Nevertheless, it must be highlighted that one unfavourable SNP may not be a significant risk factor, but the accumulation of several genetic variants related to oxidative stress might act as risk modifiers for CV events.

Interestingly, we previously published data that analysed the impact of the same eight oxidative stress-related SNPs presented as GRS on the extent of atherosclerosis detected in coronary angiography (Racis et al. 2020b). According to our previous results, the same GRS which makes CV events less frequent, was associated with more advanced coronary atherosclerosis. Thus, when interpreted together, both our studies showed the opposite trend: the genetic factors that favour atherosclerosis formation, simultaneously make CV events less frequent. What may appear conflicting, seems to be supported by clinical evidence - extensive atherosclerosis often does not result in an acute manifestation of cardiovascular disease. Conversely, individuals suffering from CV events often have not previously developed advanced atherosclerosis. Moreover, it seems to be in accordance with pathophysiological findings. Specifically, in 1985 it was determined that CV events are not usually the result of a slow-growing plaque that gradually affects the coronary artery lumen; rather, they are a result of a sudden plaque rupture, from a plaque that was unstable before the incident although the artery was not critically narrowed (Sies and Cadenas 1985).

Our study has some limitations. Although we associate our specific GRS with clinical outcomes, the conclusions about how it influences oxidative stress remain uninvestigated, as we did not perform any functional studies on those eight SNPs. Another limitation of our study is that the GRS is based on only eight specific oxidative stress-related SNPs. Although those SNPs were carefully selected based on their importance in redox state balance in terms of their functionality [31], future studies with a wider range of oxidative stress-related factors would be of interest.

According to our study, investigated eight oxidative stress-related polymorphisms: PON1 c.575A > G, MPO c.-463G > A, SOD2 c.47T > C, GCLM c.-590C > T, NOS3 c.894G > T, NOS3 c.-786T > C, CYBA c.214C > T and CYBA c.-932A > G, are significantly associated with CV events occurrence. As a conclusion, our findings may indicate better routes in the genetic approach to clinical management of acute manifestation of cardiovascular disease.

Funding

This research was funded by the National Science Centre, Poland (Grant no. 2012/07/N/NZ5/02161)

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

All authors contributed to the study design and manuscript preparation. Conceptualization: Milena Racis, Anna Stanisławska, Wojciech Sobiczewski and Andrzej Rynkiewicz; Data curation: Milena Racis, Wojciech Sobiczewski and Marcin Wirtwein; Formal analysis: Milena Racis, Anna Stanisławska, Michał Krzemiński and Marcin Gruchała; Funding acquisition: Milena Racis and Andrzej Rynkiewicz; Investigation: Milena Racis, Anna Stanisławska, Marcin Wirtwein and Andrzej Rynkiewicz; Methodology: Anna Stanisławska, Wojciech Sobiczewski and Marcin Wirtwein; Project administration: Milena Racis and Wojciech Sobiczewski; Resources: Wojciech Sobiczewski and Marcin Wirtwein; Software: Wojciech Sobiczewski and Marcin Wirtwein; Supervision, Anna Stanisławska, Wojciech Sobiczewski, Andrzej Rynkiewicz and Marcin Gruchała; Validation: Milena Racis and Anna Stanisławska; Visualization, Milena Racis and Michał Krzemiński; Writing – original draft: Milena Racis and Anna Stanisławska; Writing – review & editing: Wojciech Sobiczewski, Michał Krzemiński, Andrzej Rynkiewicz, Bartosz Wasąg, Miłosz Jaguszewski and Marcin Gruchała. All authors read and approved the final manuscript.

Ethics approval

Informed consent was given prior to the inclusion of subjects in the study and the study protocol was approved by the Ethics Committee of the Medical University of Gdansk (Ref No. NKBBN/486/2012 issued on 12 December 2012) and conformed to the ethical guidelines of the 1964 Declaration of Helsinki and its later amendments.

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Total impact of oxidative stress genes on cardiovascular events – 7-year follow-up study

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Abstract

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1. Introduction

2. Materials And Methods

3. Results

4. Discussion

5. Conclusions

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1