The rs46522 Polymorphism of the Ubiquitin-Conjugating Enzyme E2Z Gene Is Associated with Abnormal Metabolic Parameters in Patients with Myocardial Infarction: The Genetics of Atherosclerosis Disease Mexican Study

Abstract

The participation of ubiquitin-conjugating enzyme E2Z (UBE2Z) in atherosclerosis has been reported. We aimed to evaluate the association of the rs46522 polymorphism of the UBE2Z gene with myocardial infarction (MI) and other clinical and metabolic components in the Mexican population. A total of 2128 individuals (1023 patients with MI and 1105 healthy controls) were included. rs46522 was genotyped using the 5′ exonuclease TaqMan genotyping assay. A similar polymorphism distribution was observed between patients and healthy controls. The association between rs46522 polymorphism and cardiometabolic parameters was evaluated separately in the two groups. In the control group, rs46522 polymorphism was associated with increased risk of developing low-density lipoprotein cholesterol ≥130 mg/dL (odds ratio [OR] = 1.249, p _additive = 0.018; OR = 1.479, p _recessive = 0.015; OR = 1.589, p _{codominant 2} = 0.013). On the other hand, in MI patients, it was observed that rs46522 polymorphism was associated with an increased risk of developing high levels of alanine transaminase (OR = 1.297, p _heterozygote = 0.043) and aspartate transaminase (OR = 1.453, p _dominant = 0.009; OR = 1.592, p _heterozygote = 0.001; OR = 1.632, p _{codominant 1} = 0.001). Our results suggest that the UBE2Z gene rs46522 polymorphism is associated with abnormal metabolic parameters in Mexican patients with MI.

Introduction

Cardiovascular disease (CVD) is the leading cause of death worldwide. The prevalence of CVD remains high in both developing and industrialized countries. This could be due to the underlying pathophysiological mechanisms associated with development and progression of CVD.

Epidemiological studies have found a strong association between CVD and clinical, anthropometric, biochemical, lifestyle, inflammatory, and demographic factors. In addition, multiple physiological models have helped to predict and correlate the effects of such variables in the prevalence, morbidity, and mortality of the pathologies of the cardiovascular system (Tousoulis et al., 2011; Kessler et al., 2016; Johansson et al., 2017; Al-Shamsi et al., 2019; Gyldenkerne et al., 2019).

In the last decade, findings about genetic variability within individuals and populations have allowed to better understand the impact of certain polymorphisms on endothelial dysfunction, atherosclerosis, and the clinical components of CVD, including coronary artery disease (CAD), acute coronary syndrome (ACS), myocardial infarction (MI), carotid artery stenosis, stroke, and peripheral artery disease, among others (Ho et al., 2011; Arnett, 2016; Chen et al., 2018, 2019; Hong et al., 2018; Rodriguez-Perez et al., 2018a). Additionally, some genetic variants are implicated in several signaling pathways related to processes in vascular health (Perrot et al., 2017).

In this sense, the ubiquitin–proteasome system (UPS) participates in the degradation of dysfunctional proteins in eukaryotic cells. The UPS is implicated in several key regulatory processes such as cell cycle, apoptosis, and transcription. In addition, the UPS has been identified as an important molecular pathway associated with atherosclerosis, in particular regulating conditions of oxidative stress and the inflammatory process (Wilck and Ludwig, 2014). The ubiquitination of proteins comprises different steps involving enzymes of three different types: E1 (ubiquitin-activating enzyme), E2 (ubiquitin-conjugating enzyme), and E3 (ubiquitin ligase) (Willis et al., 2014; Leestemaker and Ovaa, 2017).

Specifically, ubiquitin-conjugating enzyme E2Z (UBE2Z) is a 354-residue-long atypical protein that plays an important role in preparing the ubiquitin for conjugation and binding to E3. Recently, the E3 has been described as a regulator of mitophagy, which impacts mitochondrial quality control for optimal cellular function during the ischemia–reperfusion process, and postinfarction recovery (Willis et al., 2014; Schelpe et al., 2016).

The UBE2Z gene is located on chromosome 17q21.32 and its genomic variants have been strongly linked with CVD. Specifically, the rs46522 polymorphism has been associated with CAD in Han Chinese (Lu et al., 2017), European (Schunkert et al., 2011), and Iranian (Bastami et al., 2015) populations and it has also been associated with dyslipidemia in the Japanese population (Abe et al., 2015). Nonetheless, there are no previous studies that analyze the association of this polymorphism in the Mexican Mestizo population. Thus, we aimed to analyze, within a well-characterized Mexican Mestizo cohort, the association of rs46522 polymorphism of the UBE2Z gene with MI and with clinical and metabolic parameters.

Materials and Methods

This is a case–control study nested in The Genetics of Atherosclerosis Disease (GEA) project, a research initiative designed to study the relationship of traditional cardiovascular risk factors and underlying genetic variables associated with CAD in a well-characterized Mexican cohort. The study was performed in compliance with the tenets of the Declaration of Helsinki and approved by the Ethical Review Board and Institutional Approval Number for Human Studies (INCICH, no. 15–915) at the “Instituto Nacional de Cardiología Ignacio Chavez” located in Mexico City. All participants signed an informed consent after receiving a verbal and written explanation.

Participant selection and variable assessment

This study involved 1023 patients with a past medical history of MI and 1105 healthy individuals as controls. Standardized questionnaires were used to obtain a detailed demographic, personal, and medical history, which included variables such as pharmacological treatment, frequency of physical activity, consumption of substances (i.e., tobacco and alcohol, etc.), and eating habits, as well as personal and family history of CVD and risk factors.

The selection of controls was rigorous; only apparently healthy subjects with no personal or family history of premature CAD were included. Likewise, participants with other conditions such as kidney and liver damage, cancer, thyroid problems, and congestive heart failure were excluded.

Patients with MI were diagnosed after presented symptoms and electrocardiogram consistent with heart ischemia. These patients also had high levels of creatine phosphokinase (normal value = 0.6–6.3 ng/mL). In compliance with our exclusion criteria, all subjects who had an acute cardiovascular event 3 months before the study were eliminated from the sample.

All participants had been previously evaluated through clinical, anthropometric, and biochemical measures, as well as through computed tomography of the chest and abdomen, as has been previously reported (Villarreal-Molina et al., 2012). Finally, to avoid population bias in our cohort, a panel of 265 ancestry informative markers (AIMs) was determined. The results of this analysis showed that there was no statistically significant difference between patients and controls, thus the population was ethnically matched (Posadas-Sanchez et al., 2017; Rodriguez-Perez et al., 2018b).

Genotype characterization

Genomic DNA was extracted from peripheral blood using the Lahiri and Nurnberger method (Lahiri and Nurnberger, 1991). DNA integrity was verified in 1% agarose gels stained with ethyl bromide. Then, DNA quantification was performed using an automated spectrophotometry equipment (NanoDrop, ND-1000 spectrophotometer), and aliquots of 10 ng/μL concentration were prepared. The rs46522 polymorphism (C/T) of the UBE2Z gene was genotyped using the 5′ exonuclease TaqMan genotyping assay on the ABI Prism 7900HT fast real-time PCR system (Thermo Fisher Scientific, Foster City, CA), with the assay C____587742_10. In addition, to validate the correct assignment of the three genotypes, we randomly chose and repeated 240 samples in another real-time PCR equipment (QuantStudio 12K Flex; Thermo Fisher Scientific) and the results agreed 100%.

Statistical analysis

Statistical analysis was performed with SPSS, version 24.0 (Chicago). After calculating the data distribution, means and standard deviations or medians and interquartile ranges (25–75) were reported. The comparison of numerical variables between patients and controls was performed using the Mann–Whitney U or Student's t test, as required. Categorical variables were presented as absolute values and frequencies and analyzed with a chi-square or Fisher's exact test. The Hardy–Weinberg equilibrium (HWE) was evaluated using the chi-square test.

Six inheritance models were assessed through multivariate logistic regression (codominant 1, codominant 2, dominant, recessive, heterozygote, and additive) (Rodriguez-Perez et al., 2018b). All inheritance models were adjusted for age, sex, body–mass index (BMI), homeostatic model of insulin resistance (HOMA-RI), visceral abdominal fat, fatty liver, and elevated alanine transaminase; associations were reported with the odds ratio (OR) and 95% confidence interval (CI). Finally, a logistic regression analysis was performed to assess the association of the rs46522 polymorphism with metabolic abnormalities under six inheritance models that were adjusted for age, sex, and BMI. A p-value of <0.05 was considered statistically significant.

Results

A total of 2128 individuals (1023 patients with MI and 1105 subject controls) were included in the study. Clinical, anthropometric, demographic, and biochemical characteristics are depicted in Tables 1 and 2 and Figure 1. In the group of patients with MI, there were more males than females and they were older than the controls. Diastolic and systolic blood pressure, waist circumference, BMI, visceral abdominal fat, alanine transaminase, aspartate transaminase, fasting glucose, triglycerides, and HOMA-IR were all higher in the group of patients with MI than in the control group. In addition, we observed a higher prevalence of metabolic syndrome, type 2 diabetes mellitus, obesity, hypertension, hypoadiponectinemia, hypoalphalipoproteinemia, abdominal obesity, current smoking, and hyperinsulinemia in patients with MI when compared with the control group.

FIG. 1.

Frequency of the metabolic and clinical characteristics of the analyzed population. *p ≤ 0.001, **p ≤ 0.01, and ***p = 0.096. ¥ For Lp (a), controls n = 654 and MI n = 686; ¥ for VAF, controls n = 1083 and MI n = 992. MI, myocardial infarction; VAF, visceral abdominal fat.

Table 1.

Clinical Characteristics of the Groups Studied

Characteristics	Control (n = 1105)	MI (n = 1023)	p^a
Sex (% male)	41.1	83.1	<0.001
Age (years)	51 ± 9	54 ± 8	<0.001
Diastolic blood pressure (mmHg)	71 (65–77)	72 (66–78)	0.013
Body–mass index (kg/m²)	27.9 (25.4–30.8)	28.2 (26.0–31.1)	0.006
Systolic blood pressure (mmHg)	112 (104–122)	116 (106–127)	<0.001
Waist circumference (cm)	94 ± 11	97 ± 10	<0.001
Subcutaneous abdominal fat (cm²)^b	286 (218–367)	244 (192–310)	<0.001
Visceral abdominal fat (cm²)^b	139 (104–179)	169 (130–216)	<0.001
Total abdominal fat (cm²)^b	432 (347–534)	424 (338–523)	0.206

Data are expressed as mean ± standard deviation or median (interquartile range).

Student's t-test or Mann–Whitney U test.

n = 1083 in controls and n = 992 in MI patients.

MI, myocardial infarction.

Table 2.

Metabolic Characteristics of the Subjects Studied

Characteristics	Control (n = 1105)	MI (n = 1023)	p^a
Glucose (mg/dL)	90 (84–97)	94 (87–118)	<0.001
Alanine transaminase (IU/L)	24 (18–34)	26 (19–36)	0.010
Aspartate transaminase (UI/L)	25 (21–30)	26 (22–31)	0.001
Adiponectin (μg/mL)	8.2 (5.1–13.0)	5.2 (3.2–8.0)	<0.001
Triglycerides (mg/dL)	145 (108–202)	162 (120–220)	<0.001
HOMA-RI	3.8 (2.6–5.5)	4.7 (3.3–7.2)	<0.001
Insulin (μUI/mL)	17 (12–23)	19 (14–26)	<0.001
C-LDL (mg/dL)	116 (95–134)	91 (69–116)	<0.001
Non-HDL cholesterol (mg/dL)	142 (121–164)	121 (93–151)	<0.001
HDL cholesterol (mg/dL)	45 (36–55)	37 (32–44)	<0.001
Total cholesterol (mg/dL)	190 (166–210)	161 (133–193)	<0.001
C-RPhs (mg/L)	1.5 (0.8–3.1)	1.2 (0.6–2.5)	<0.001

Data are expressed as median (interquartile range).

U from Mann–Whitney test.

C-RPhs, high-sensitivity C-reactive protein; HDL, high-density lipoprotein; HOMA-RI, homeostatic model of insulin resistance; C-LDL, low-density lipoprotein cholesterol.

Association of UBE2Z (rs46522) polymorphism with MI

The genotype frequencies of the rs46522 polymorphism were similar in MI patients and healthy controls (Table 3). All inheritance models were adjusted for age, sex, BMI, HOMA-RI, visceral abdominal fat, fatty liver, and alanine transaminase. Moreover, the genotype frequencies in both groups were in HWE.

Table 3.

Distribution of the UBE2Z rs46522 (C > T) Gene Polymorphism in the Study Groups

	n (genotype frequency)			MAF	Inheritance models	OR (95% CI)	p
	CC	CT	TT	T	Inheritance models	OR (95% CI)	p
Control subjects (n = 1105)	361 (0.327)	526 (0.476)	218 (0.197)	0.435	Additive	1.084 (0.937–1.253)	0.277
					Dominant	1.119 (0.900–1.392)	0.311
					Recessive	1.104 (0.850–1.433)	0.459
MI patients (n = 1023)	309 (0.302)	514 (0.502)	200 (0.196)	0.447	Heterozygote	1.039 (0.847–1.275)	0.711
					Codominant 1	1.101 (0.873–1.387)	0.416
					Codominant 2	1.169 (0.870–1.571)	0.301

The inheritance models were adjusted for age, sex, BMI, HOMA-RI, visceral abdominal fat, fatty liver, and alanine transaminase.

BMI, body–mass index; CI, confidence interval; MAF, minor allele frequency; OR, odds ratio.

Association of rs46522 with metabolic parameters

The association of the rs46522 UBE2Z polymorphism with different metabolic parameters was analyzed separately in healthy controls and MI patients. In the control group, under additive, recessive, and codominant 1 models, the rs46522 polymorphism was associated with low-density lipoprotein cholesterol (C-LDL) ≥130 mg/dL (OR = 1.249, p _additive = 0.018; OR = 1.479, p _recessive = 0.015; OR = 1.589, p _{codominant 2} = 0.013). On the other hand, in MI patients, under different inheritance models, the rs46522 polymorphism was associated with high levels of alanine transaminase (OR = 1.297, p _heterozygote = 0.043) and aspartate transaminase (OR = 1.453, p _dominant = 0.009; OR = 1.592, p _heterozygote = 0.001; OR = 1.632, p _{codominant 1} = 0.001). All inheritance models were adjusted for age, sex, and BMI. These data are depicted in Table 4.

Table 4.

Association of the UBE2Z rs46522 (C > T) Gene Polymorphism with Metabolic Abnormalities in Control Subjects and Myocardial Infarction Patients

	n (genotype frequency)			MAF	Inheritance models	OR (95% CI)	p
	CC	CT	TT	T	Inheritance models	OR (95% CI)	p
Control subjects
C-LDL ≥130 mg/dL					Additive	1.249 (1.040–1.500)	0.018^*
No (n = 777)	265 (0.341)	372 (0.479)	140 (0.180)	0.420	Dominant	1.249 (0.942–1.657)	0.122
Yes (n = 328)	96 (0.293)	154 (0.470)	78 (0.238)	0.472	Recessive	1.479 (1.078–2.030)	0.015^*
					Heterozygote	0.938 (0.723–1.218)	0.632
					Codominant 1	1.127 (0.833–1.523)	0.439
					Codominant 2	1.589 (1.102–2.291)	0.013^*
MI patients
Alanine transaminase increased level					Additive	1.001 (0.836–1.199)	0.990
No (n = 594)	187 (0.315)	282 (0.475)	125 (0.210)	0.448	Dominant	1.170 (0.888–1.541)	0.266
					Recessive	0.814 (0.590–1.121)	0.207
Yes (n = 442)	119 (0.282)	228 (0.540)	75 (0.178)	0.428	Heterozygote	1.297 (1.008–1.669)	0.043^*
					Codominant 1	1.269 (0.949–1.697)	0.109
					Codominant 2	0.945 (0.653–1.368)	0.765
Aspartate transaminase increased level					Additive	1.082 (0.903–1.296)	0.396
No (n = 618)	205 (0.332)	282 (0.456)	131 (0.212)	0.440	Dominant	1.453 (1.096–1.925)	0.009^*
					Recessive	0.799 (0.564–1.077)	0.131
Yes (n = 398)	101 (0.254)	228 (0.573)	69 (0.173)	0.460	Heterozygote	1.592 (1.234–2.053)	<0.001^*
					Codominant 1	1.632 (1.214–2.194)	0.001^*
					Codominant 2	1.065 (0.730–1.553)	0.743

The inheritance models were adjusted for age, sex, and BMI.

Values in bold p < 0.05.

MAF, minor allele frequency.

Discussion

In the present research, we evaluated the association of the rs46522 polymorphism of the UBE2Z gene with MI and with abnormal metabolic parameters. No association with MI was detected, which is similar to the results reported by Dechamethakun et al. (2014) in Japanese patients with atherosclerosis and the results reported by Huang et al. (2016) in southern Han Chinese patients with CAD. Previously, this polymorphism was identified as a novel susceptibility locus for CAD in genome-wide association studies (GWAS) (Schunkert et al., 2011; Guo et al., 2017).

Additionally, this polymorphism has been associated with CAD (Bastami et al., 2015), diabetes mellitus (Lu et al., 2017), dyslipidemia, and hypertriglyceridemia (Abe et al., 2015), which is opposite to our findings. Therefore, several points should be considered to explain the differences: (1) the studies by Bastami et al. and Lu et al. only included 300 controls and 390 patients with CAD, respectively; (2) the study by Lu et al. used the PCR-RFLP technique to determine the polymorphisms; (3) some of these studies included patients with CAD with other comorbidities such as diabetes; and (4) the studies were conducted in individuals with a different genetic background from Mexicans (Lisker et al., 1986, 1988, 1996; Juarez-Cedillo et al., 2008).

On the other hand, our study is the first report that showed the association of the UBE2Z genetic polymorphism (rs46522) with abnormal metabolic parameters in the group of healthy individuals—we found an association of this polymorphism with an increased risk of C-LDL ≥130 mg/dL, while in MI patients, the polymorphism was associated with other abnormal metabolic parameters, including elevated activity of alanine transaminase and aspartate transaminase. Nowadays, there are no studies of the UBE2Z genetic polymorphism (rs46522) that evaluate a possible genetic association of metabolic abnormalities with MI. More studies will be required in other populations to confirm these associations.

In silico analysis shows that the rs46522 polymorphism has an important regulatory function, it is linked to gene expression and probably affects binding of proteins and transcriptional factors such as RUNX3 and NFKB1 (Lonsdale et al., 2013). It is important to underline that multifactorial diseases such as MI involve complex interactions and pathways that include not just changes at the DNA sequence but also epigenetic marks and post-transcriptional modifications that could be affecting alternative splicing modifications (Rodriguez-Perez et al., 2016; Rodriguez-Perez et al., 2018a).

In this sense, RUNX3 has been involved in the maintenance of genomic stability by nontranscriptional and transcriptional mechanisms (Krishnan and Ito, 2017). NFKB1 participates in immune system regulation and recently one polymorphism of its gene (rs28362491) has been associated with increased risk of acute ACS (Jin et al., 2019).

Our work has important strengths: (1) we included a large cohort of MI patients and healthy controls; (2) individuals in the control group did not have coronary arterial calcium when evaluated by computed tomography, thus these individuals did not have subclinical atherosclerosis; and (3) AIMs were determined in patients and controls to avoid population bias.

Some study limitations should be considered: (1) the study used a cross-sectional design; (2) only one polymorphism was determined; and (3) the possible functional effect of the polymorphism was evaluated using informatic tools, therefore an experimental design is necessary to corroborate the true functional effect. Future studies will be necessary to include other UBE2Z gene polymorphisms and analyze the functional effect of these genetic variants to understand their effect on the physio-pathogenesis of MI.

Conclusion

In summary, our data suggest an association between the UBE2Z gene and some metabolic abnormalities in Mexican patients with MI, while the same rs46522 polymorphism is associated with other abnormal metabolic parameters in healthy controls. Additional studies in different populations are necessary to confirm these data and establish the true role of this polymorphism in metabolic processes.

Footnotes

Acknowledgments

The authors are grateful to the GEA study participants and “Instituto Nacional de Cardiología.” Additionally, some data presented were findings of Ruben Blachman obtained during his Master's degree program.

Disclosure Statement

The authors declare no conflicts of interest.

Funding Information

The present study was supported, in part, by the “Consejo Nacional de Ciencia y Tecnología” (CONACyT grant no. 233402).

References

Abe

, Tokoro

, Matsuoka

, Arai

, Noda

, Watanabe

, et al. (2015). Association of genetic variants with dyslipidemia. Mol Med Rep, 12, 5429–5436.

Al-Shamsi

, Regmi

, and Govender

R.D.

(2019). Incidence of cardiovascular disease and its associated risk factors in at-risk men and women in the United Arab Emirates: a 9-year retrospective cohort study. BMC Cardiovasc Disord, 19, 148.

Arnett

D.K.

(2016). Genetics of CVD in 2015: using genomic approaches to identify CVD-causing variants. Nat Rev Cardiol, 13, 72–74.

Bastami

, Ghaderian

S.M.

, Omrani

M.D.

, Mirfakhraie

, Nariman-Saleh-Fam

, Mansoori

, et al. (2015). Evaluating the association of common UBE2Z variants with coronary artery disease in an Iranian population. Cell Mol Biol (Noisy-le-grand), 61, 50–54.

Chen

, Wang

, Pang

, Cui

, Yan

, and Hawley

R.G.

(2019). Functional genetic variants of the GATA4 gene promoter in acute myocardial infarction. Mol Med Rep, 19, 2861–2868.

Chen

, Wang

, Gao

, Zhang

, Ma

, et al. (2018). Functional genetic variants in the SIRT5 gene promoter in acute myocardial infarction. Gene, 675, 233–239.

Dechamethakun

, Ikeda

, Arai

, Sato

, Sawabe

, and Muramatsu

(2014). Associations between the CDKN2A/B, ADTRP and PDGFD polymorphisms and the development of coronary atherosclerosis in Japanese patients. J Atheroscler Thromb, 21, 680–690.

Guo

, Wang

, Li

, Gao

, Arckacki

, Wang

I.Z.

, et al. (2017). Genome-wide linkage analysis of large multiple multigenerational families identifies novel genetic loci for coronary artery disease. Sci Rep, 7, 5472.

Gyldenkerne

, Olesen

K.K.W.

, Madsen

, Thim

, Jensen

L.O.

, Raungaard

, et al. (2019). Extent of coronary artery disease is associated with myocardial infarction and mortality in patients with diabetes mellitus. Clin Epidemiol, 11, 419–428.

10.

, Bhindi

, Ashley

E.A.

, and Figtree

G.A.

(2011). Genetic analysis in cardiovascular disease: a clinical perspective. Cardiol Rev, 19, 81–89.

11.

Hong

, Jiang

Y.F.

, Chen

, Zhang

N.N.

, Yang

H.J.

, Rui

, et al. (2018). Role of SH2B3 R262W gene polymorphism and risk of coronary heart disease: a PRISMA-compliant meta-analysis. Medicine (Baltimore), 97, e13436.

12.

Huang

E.W.

, Peng

L.Y.

, Zheng

J.X.

, Wang

, Tan

X.H.

, Yang

Z.Y.

, et al. (2016). Investigation of associations between ten polymorphisms and the risk of coronary artery disease in Southern Han Chinese. J Hum Genet, 61, 389–393.

13.

Jin

S.Y.

, Luo

J.Y.

, Li

X.M.

, Liu

, Ma

Y.T.

, Gao

X.M.

, et al. (2019). NFKB1 gene rs28362491 polymorphism is associated with the susceptibility of acute coronary syndrome. Biosci Rep, 39, BSR20182292.

14.

Johansson

, Rosengren

, Young

, and Jennings

(2017). Mortality and morbidity trends after the first year in survivors of acute myocardial infarction: a systematic review. BMC Cardiovasc Disord, 17, 53.

15.

Juarez-Cedillo

, Zuniga

, Acuna-Alonzo

, Perez-Hernandez

, Rodriguez-Perez

J.M.

, Barquera

, et al. (2008). Genetic admixture and diversity estimations in the Mexican Mestizo population from Mexico City using 15 STR polymorphic markers. Forensic Sci Int Genet, 2, e37–e39.

16.

Kessler

, Vilne

, and Schunkert

(2016). The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular disease. EMBO Mol Med, 8, 688–701.

17.

Krishnan

, and Ito

(2017). A regulatory role for RUNX1, RUNX3 in the maintenance of genomic integrity. Adv Exp Med Biol, 962, 491–510.

18.

Lahiri

D.K.

, and Nurnberger

J.I.

Jr . (1991). A rapid non-enzymatic method for the preparation of HMW DNA from blood for RFLP studies. Nucleic Acids Res, 19, 5444.

19.

Leestemaker

, and Ovaa

(2017). Tools to investigate the ubiquitin proteasome system. Drug Discov Today Technol, 26, 25–31.

20.

Lisker

, Perez-Briceno

, Granados

, and Babinsky

(1988). Gene frequencies and admixture estimates in the state of Puebla, Mexico. Am J Phys Anthropol, 76, 331–335.

21.

Lisker

, Perez-Briceno

, Granados

, Babinsky

, de Rubens

, Armendares

, et al. (1986). Gene frequencies and admixture estimates in a Mexico City population. Am J Phys Anthropol, 71, 203–207.

22.

Lisker

, Ramirez

, and Babinsky

(1996). Genetic structure of autochthonous populations of Meso-America: Mexico. Hum Biol, 68:395–404.

23.

Lonsdale

, Thomas

, Salvatore

, Phillips

, Lo

, Shad

, et al. (2013). The genotype-tissue (GTEx). Nat Genet, 45, 580–585.

24.

, Huang

, Ma

, Gu

, Zhang

, et al. (2017). Rs46522 in the ubiquitin-conjugating enzyme E2Z gene is associated with the risk of coronary artery disease in individuals of Chinese Han population with type 2 diabetes. J Diabetes Res, 2017, 4501794.

25.

Perrot

, Verbeek

, Sandhu

, Boekholdt

S.M.

, Hovingh

G.K.

, Wareham

N.J.

, et al. (2017). Ideal cardiovascular health influences cardiovascular disease risk associated with high lipoprotein(a) levels and genotype: the EPIC-Norfolk prospective population study. Atherosclerosis, 256, 47–52.

26.

Posadas-Sanchez

, Perez-Hernandez

, Rodriguez-Perez

J.M.

, Coral-Vazquez

R.M.

, Roque-Ramirez

, Llorente

, et al. (2017). Interleukin-27 polymorphisms are associated with premature coronary artery disease and metabolic parameters in the Mexican population: the genetics of atherosclerotic disease (GEA) Mexican study. Oncotarget, 8, 64459–64470.

27.

Rodriguez-Perez

J.M.

, Blachman-Braun

, Pomerantz

, Vargas-Alarcon

, Posadas-Sanchez

, and Perez-Hernandez

(2016). Possible role of intronic polymorphisms in the PHACTR1 gene on the development of cardiovascular disease. Med Hypotheses, 97, 64–70.

28.

Rodriguez-Perez

J.M.

, Posadas-Sanchez

, Blachman-Braun

, Vargas-Alarcon

, Posadas-Romero

, Garcia-Flores

, et al. (2018a). A haplotype of the phosphodiesterase 4D (PDE4D) gene is associated with myocardial infarction and with cardiometabolic parameters: the GEA study. EXCLI J, 17, 1182–1190.

29.

Rodriguez-Perez

J.M.

, Posadas-Sanchez

, Blachman-Braun

, Vargas-Alarcon

, Posadas-Romero

, Rodriguez-Cortes

A.A.

, et al. (2018b). HHIPL-1 (rs2895811) gene polymorphism is associated with cardiovascular risk factors and cardiometabolic parameters in Mexicans patients with myocardial infarction. Gene, 663, 34–40.

30.

Schelpe

, Monte

, Dewitte

, Sixma

T.K.

, and Rucktooa

(2016). Structure of UBE2Z enzyme provides functional insight into specificity in the FAT10 protein conjugation machinery. J Biol Chem, 291, 630–639.

31.

Schunkert

, Konig

I.R.

, Kathiresan

, Reilly

M.P.

, Assimes

T.L.

, Holm

, et al. (2011). Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet, 43, 333–338.

32.

Tousoulis

, Kampoli

A.M.

, Papageorgiou

, Androulakis

, Antoniades

, Toutouzas

, et al. (2011). Pathophysiology of atherosclerosis: the role of inflammation. Curr Pharma Des, 17, 4089–4110.

33.

Villarreal-Molina

, Posadas-Romero

, Romero-Hidalgo

, Antunez-Arguelles

, Bautista-Grande

, Vargas-Alarcon

, et al. (2012). The ABCA1 gene R230C variant is associated with decreased risk of premature coronary artery disease: the genetics of atherosclerotic disease (GEA) study. PLoS One, 7, e49285.

34.

Wilck

, and Ludwig

(2014). Targeting the ubiquitin-proteasome system in atherosclerosis: status quo, challenges, and perspectives. Antioxid Redox Signal, 21, 2344–2363.

35.

Willis

M.S.

, Bevilacqua

, Pulinilkunnil

, Kienesberger

, Tannu

, and Patterson

(2014). The role of ubiquitin ligases in cardiac disease. J Mol Cell Cardiol, 71, 43–53.