Acta Biochimica Polonica, Vol. 65, No 3/2018, 415–420, https://doi.org/10.18388/abp.2017_2344

Regular paper

Role of Apolipoprotein E gene polymorphism in the risk of familial hypercholesterolemia: a case-control study

Turky H. Almigbal1, Mohammed Ali Batais1, Rana M. Hasanato2, Fawaziah Khalaf Alharbi3, Imran Ali Khan4*, Khalid Khalaf Alharbi4

1Department of Family and Community Medicine, King Saud University, Riyadh, Saudi Arabia; 2Department of Pathology College of Medicine and University Hospitals, King Saud University, Riyadh, Kingdom of Saudi Arabia; 3Department of Biology Science, College of Science and Arts, Al-Qassim University, Al-Qassim, Saudi Arabia; 4Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, PO Box-10219, Riyadh-11433, Kingdom of Saudi Arabia

Familial Hypercholesterolemia (FH) is characterized by elevated cholesterol and based on biochemical, clinical, and genetic studies and FH disease, which was documented even with limited mutations. Earlier studies focused on Apolipoprotein E (ApoE) in variable diseases. The current study aimed to investigate the genetic association between FH disease and ApoE gene polymorphisms (rs429358 and rs7412) in the Saudi population. This case-control study was a hospital-based study performed in Saudi Arabia. Two hundred and four subjects in total were recruited and consisted of FH participants (n=104) and the controls (n=100). Common polymorphisms of ApoE gene (rs429358 and rs7412) were chosen and subjected to the genotyping using the TaqMan assay. Moreover, the ApoE risk allele E4 was proved significantly associated with FH cases when compared with controls (OR-2.24 (95%CI: 1.06-4.70); p=0.02). Lipid profile parameters were significantly associated (p<0.05); however, the ApoE alleles and lipid profiles were not correlated (p>0.05). In conclusion, the FH case-control study was associated with the E4 allele in the Saudi population. However, E4 allele was appeared as a reliable risk marker for lipid profiles, but not for ApoE alleles.

Key words: familial hypercholesterolemia, ApoE gene, TaqMan assay, Saudi population.

Received: 24 October, 2017; revised: 28 June, 2018; accepted: 02 July, 2018; available on-line: 15 September, 2018

*e-mail: imkhan@ksu.edu.sa

Abbreviations: ApoE, Apolipoprotein E; CAD, coronary artery disease; CI, confidence interval; CHD, coronary heart disease; CVD, cardiovascular disease; FH, Familial Hypercholesterolemia; HDL-C, high density lipoprotein cholesterol; HWE, Hardy-Weinberg equilibrium; LDL-C, low density lipoprotein cholesterol; TG, triglycerides; TC, total cholesterol VLDL, very low density lipoproteins; WES, whole-exome sequencing

INTRODUION

Familial Hypercholesterolemia (FH-OMIM#143890) is an autosomal dominant pattern of limited genetic complexity, along with premature atherosclerotic cardiovascular disease (CVD) (Chan et al., 2016; Paquette et al., 2018). The single pathogenic variant involved is related to LDLR (60–80%), APOB (1–5%), or PCSK9 gene (upto 3%), affecting one in three people (Maurera et al., 2016). Recent studies confirmed that the FH prevalence was not 1:500 but 1:250 (van Lennep, 2016). It causes high LDL-R level from birth, due to a family history of high cholesterol (Onorato & Sturm, 2016). FH was diagnosed for the first time 50 years ago, and gained attention due to its connection to atherosclerosis and coronary heart disease (CHD). The association between genetic polymorphisms and clinical diseases was recognized earlier. Functional mutational studies from the earlier reports in specific genes (LDLR, APOB, PCSK9, and LDLRAP1) proved useful in FH diagnosis (Radovica-Spalvina et al., 2015). Due to smoking FH patients, with high triglycerides (TG) level and low blood pressure within the recommended limits (Pajak et al., 2016). Molecular diagnostic techniques revealed the relation between FH and Apolipoprotein E (ApoE) gene (Awan et al., 2013; Carmena et al., 1993; Eto et al., 1996; Jensen, 2002; Utermann et al., 1979). The ApoE gene was recognized as a genetic marker for coronary artery disease (CAD). The function of ApoE in lipid metabolism with serum glycoprotein serves as a ligand for cell-surface receptors and very low density lipoproteins (VLDL) in the liver and in the control’s intestinal cholesterol absorption (Karahan et al., 2015; Yousuf & Iqbal, 2015). The ApoE gene was extensively studied in several diseases and it plays an important role in lipid metabolism (Megale et al., 2016). The ApoE allele e4 increases LDL-C levels and decreases ApoE plasma concentrations (Davignon et al., 1988). Three variable alleles (E2, E3 and E4) account for ApoE polymorphism that produces 6 genotypes: E2/E2, E3/E3, and E4/E4, which are homozygous, and E2/E3, E2/E4, and E3/E4, which are heterozygous (Afroze et al., 2016). These alleles are associated with rs429358 (Arg-130-Cyt) and rs7412 (Cys-163-Arg) polymorphisms that appear in the coding region of missense mutations of the ApoE gene. The combinations of these SNPs alleles results in the production of the following transcripts: Arg/Cys (referred to as isoform e3), Arg/Arg (isoform e4), Cys/Cys (isoform e2), and Cys/Arg (a rare isoform, seldom observed) (Alharbi et al., 2014). The studies on FH in relation to the genetic polymorphisms are limited and up to now no genetic study examined the FH in Saudi Arabia. Thus, the aim of the present research was to investigate the genetic association between FH cases and the ApoE gene polymorphisms (rs429358 and rs7412) in the Saudi population.

MATERIALS AND METHODS

Subjects. This case-control study was performed at King Khalid University Hospital (KKUH), Riyadh, a major city in Saudi Arabia. There were 104 FH cases recruited based on the diagnosis using the Dutch group classification criteria (Lye et al., 2013). Ethical approval for this study was obtained from the Institutional Review Board at King Saud University (E-2-829). Selection of the 100 control subjects was described previously (Alharbi et al., 2015).

Blood analysis. Each patient provided 5 ml of blood for biochemical and molecular analysis. A serum sample of 3 ml was used for the biochemical assays and 2 ml of the EDTA sample was used for the molecular analysis. The serum sample was used to obtain the lipid profile comprising of total cholesterol (TC), TG, high density lipoprotein-cholesterol (HDL-C) and low density lipoprotein-cholesterol (LDL-C). The assessment of the lipid profile was described in the earlier publication (Alharbi et al., 2013). DNA from peripheral leukocytes was isolated using Norgen DNA extraction kit (Thorold, Ontario, Canada). NanoDrop (Fisher Scientific, Waltham, MA, USA) was used to assess the quality of genomic DNA spectrophotometrically. TaqMan (Fisher Scientific, Waltham, MA, USA) assay genotyping as described (Alharbi et al., 2014).

Statistical analysis. The variables were compared between FH cases and healthy controls using the Student’ t-test. Anthropometric and lipid profile data were presented as mean ± S.D. for continuous variables. Categorical variables were compared using the chi-square test and presented as percentages. Goodness of fit test was exploited to calculate the Hardy-Weinberg equilibrium (HWE) in FH cases and healthy controls. Allele frequencies were calculated with gene counting. Univariate logistic regression analysis was used to compare the genotype and allele frequencies between the cases and controls and the results were presented as odds ratio (OR) and 95% confidence interval (CI) values. The Yates correction was also applied during the analysis of the genotyping. ANOVA was performed on the lipid profiles and allele frequencies. A p<0.05 was considered statistically significant. Altogether, the statistical analysis was performed using the statistical package for social sciences (SPSS-22, Chicago, IL, USA).

RESULTS

Overall, 204 subjects were included in this study, divided into 104 FH cases and 100 controls. Table 1 presents the anthropometric and biochemical characteristics of all the study participants and the results of the t-test. The mean age of FH cases and controls was 57.76±9.94 and 44.02±6.29 years, respectively. The BMI value of the FH cases equaled 27.1±1.91 kg/m2. However, comparison between FH and control cases included age, TC, TG, HDL-C and LDL-C, which were positively associated with statistical significance (p<0.05). Gender parameter did not show any gender association (p=0.58); one of the reasons could be unequal gender proportions in the studied groups i.e., 71.2% of males in FH cases and only 60% in controls.

In this case-control study, two specific SNPs (rs429358 and rs7412) of the ApoE gene were analyzed, in relation to them with FH in the Saudi population. HWE showed the association in the Saudi population. The genotype and allele distribution in FH cases and controls was presented in Table 2. The genotype frequencies in FH cases were as follows: E2/E2 – 0.96%, E2/E3 – 6.7%, E2/E4 – 1.9%, E3/E3 – 71.2%, E3/E4 – 17.3%, E4/E4 – 1.9% and for the controls: E2/E2 – 4%, E3/E3 – 85%, E3/E4 – 11%. In FH cases, the percentage of ε2, ε3, and ε4 alleles were 5.3%, 83.2%, and 11.5%, whereas in the controls it was only 2%, 92.5% and 5.5%, respectively. In control subjects, E2/E2, E2/E4 and E4/E4 did not appear at all (n=0). The E3/E4 genotypes was completely absent in the FH cases and controls (OR-0.40; (95% CI: 0.21–0.75) p=0.19) and E4/E4 (OR-4.90; [95% CI: 0.23–103.4) p=0.25). However, the e4 allele showed a positive association (OR-2.24; (95% CI: 1.06–4.70) p=0.02). The ANOVA on lipid profiles values (such as TC, TG, HDL-C and LDL-C) and allele frequencies did not show any association with FH (p>0.05 respectively). The statistical test results were presented in Table 3. However, for all four lipid profile parameters the levels were higher in the e2 allele bearers than in the case of alleles e3 and e4.

DISCUSSION

The presented study evaluated the relation between FH disease and the ApoE gene polymorphisms in the Saudi population. It revealed a nominal association i.e., association with the e4 allele (p=0.02). We did not find any genotype association, which may be due to the small sample size. Genetic susceptibility is thought to contribute to the pathogenesis of FH disease. However, FH prevalence in Saudi Arabia is still not well-documented, with too few studies focused on the subject (Al-Allaf et al., 2017; Al-Allaf et al., 2016; Al-Allaf et al., 2014; Al-Allaf et al., 2015; Alallaf et al., 2017; Alharbi et al., 2013; Alharbi et al., 2015; Nuglozeh, 2017). Moreover, FH disease may have a high prevalence may be due to connection with obesity (68%) and consanguineous marriages (~50–60%) in both the Saudi and Arab populations. In addition, the number of T2DM cases has been increasing (Alharbi et al., 2016), while FH disease is still underdiagnosed, but actively being evaluated. A previous study on 69 016 subjects from the Danish population revealed the prevalence of ~1 in 137 for diagnosed basing on the Dutch lipid clinic criteria, suggesting that FH is possibly underdiagnosed. The FH samples selected in this study has been selected through the Dutch group criteria, as only clinicians has diagnose FH disease (Benn et al., 2012).

Identification of SNPs in the DNA coding regions enables a better understanding of the pathophysiology of the diseases and may result in improved diagnosis, prevention and, treatment. Approximately, 90% of DNA sequence variants in humans are localized in coding regions (Khan et al., 2016). A significant progress regarding the detection of genetic diseases was documented (Risch & Merikangas, 1996). The techniques for sequencing of that complete exome are used to analyze the genetic variation in the affected patients with decreasing costs and increasing accuracy (Katsanis & Katsanis, 2013). The whole-exome sequencing (WES) technique identified the disease-causing marker and is a promising tool for understanding the molecular mechanisms of the diseases and for personalized treatment (Braenne et al., 2014). Earlier studies implemented exome sequencing in 125 FH-diagnosed patients in the UK population. The results did not reveal any novel genetic variants due to the selection of a limited number of genes. Exome sequencing analysis also failed to identify disease-related loci in both British and German population (Braenne et al., 2014; Futema et al., 2014). However, in the Saudi population, only specific genes were selected for the next-generation sequencing and a novel variant (c.2026delG, p. Gly676fs) identified in the LDLR gene in exon 14 (Al-Allaf et al., 2015). More number of studies have been published with the advanced technology in genotyping and detection of huge variant numbers in the human genome, which did not provide a better understanding of the disease mechanisms. Meta-analysis studies are defined as statistical procedures that integrates the results of several independent studies, thereby playing a central role in evidence-based medicine (Haidich, 2010; Salanti et al., 2005).

Meta-analysis of GWAS data can expand the associated data documented from earlier studies with assigned genotype data. However, the initial selection should be performed for the combinational results of GWAS and meta-analyses, along with genetic association with strong statistical support; at the same time, GWAS and meta-analyses showed convincing sizes effects are moderate in current platforms, as sample sizes can still explain the majority of large genetic risk for most common diseases (Zeggini & Ioannidis, 2009).

Meta-analysis studies on the ApoE gene in relation to multiple diseases revealed both were positive (Arati et al., 2016; Cao et al., 2014; Garatachea et al., 2015; Gatt et al., 2015; Han et al., 2013; Li et al., 2015; Liao et al., 2014; Lin et al., 2014; Meng et al., 2013; Rubino et al., 2013; Sun et al., 2015; Wang et al., 2014; Xu et al., 2014; Yin et al., 2012; Yin et al., 2013; Yin et al., 2014; Zhang et al., 2014a; Zhang et al., 2014b; Zhang et al., 2015), and negative associations (Agarwal & Tripathi, 2014; Gu et al., 2013; Liu et al., 2014; Miao et al., 2015; Stoumpos et al., 2013; Tian et al., 2014; Wang et al., 2013; Xu et al., 2015; Zhao et al., 2016; Zhu et al., 2016). Earlier reports in the nineties did not provide unequivocal conclusions regarding the relation of the ApoE gene and FH in different populations (Carmena et al., 1993; Friedlander & Leitersdorf, 1996; Utermann et al., 1979). However, recently, the positive, nominal, and negative associational studies for FH were reported (Aledo et al., 2015; Angarica et al., 2016; Drogari et al., 2014; Hiddink et al., 2015; Ho et al., 2015; Leduc et al., 2016; Saavedra et al., 2014; Sanchez Munoz-Torrero et al., 2014; Versmissen et al., 2015). The initial study on Saudi FH subjects and the ApoE gene correlated the risk with the E4 allele, which may be due to the low sample size. The E4 risk allele of ApoE gene was proved to be associated with TC (Fallaize et al., 2016). However, different studies based on NGS and exome sequencing did not show the diagnostic bio-marker with ApoE or other genes/SNPs (Al-Allaf et al., 2015; Angarica et al., 2016; Graham et al., 2017; Hinchcliffe et al., 2014; Nikkola et al., 2017; Radovica-Spalvina et al., 2015; Tada et al., 2016; Vandrovcova et al., 2013). The current study had specific limitations such as unequal genders proportion, low sample size, missing clinical data and family history.

However, the TaqMan assay genotyping performed in this study enable by passing the negative analysis and increased accuracy of the results.

Our results showed that the ε4 allele is associated with FH cases in the Saudi population. The ε4 allele proved an important and reliable marker and did not appear to have a significant association with lipid profiles. Future studies on FH should be implemented with large sample sizes, comprised of global ethnicities and confirm the relation between the FH and ApoE gene. Exome- and next-generation sequencing analysis should be performed to identify a reliable diagnostic marker linking FH disease with specific SNP/variations.

Conflict of Interest

All the authors declare no conflict of interest in relation to this manuscript.

Acknowledgements of Financial Support

This project was supported by the College of Medicine Research Centre, Deanship of Scientific Research, King Saud University, Riyadh, Saudi Arabia.

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