Association of Genetic Polymorphisms with Abdominal Aortic Aneurysm in the Processes of Apoptosis, Inflammation, and Cholesterol Metabolism
by
, , and
Nyityasmono Tri Nugroho
1,2,*,
Monika Herten
3,*
,
Giovanni F. Torsello
4,
Nani Osada
1,
Elena Marchiori
1,
Sonja Sielker
5 and
Giovanni B. Torsello
6 1
Department of Vascular and Endovascular Surgery, University Hospital Münster, 48149 Münster, Germany
2
Vascular and Endovascular Division, Department of Surgery, Cipto Mangunkusumo National Hospital, Faculty of Medicine, University of Indonesia, Jakarta 10430, Indonesia
3
Department of Trauma, Hand and Reconstructive Surgery, University Hospital Duisburg-Essen, 45147 Essen, Germany
4
Institute of Radiology, University of Göttingen, 37075 Göttingen, Germany
5
Research Unit Vascular Biology of Oral Structures (VABOS), Department of Cranio-Maxillofacial Surgery, University Hospital Münster, 48149 Münster, Germany
6
Institute for Vascular Research, St. Franziskus Hospital, 48145 Münster, Germany
*
Authors to whom correspondence should be addressed.
Medicina 2023, 59(10), 1844; https://doi.org/10.3390/medicina59101844
Submission received: 21 August 2023
/
Revised: 26 September 2023
/
Accepted: 14 October 2023
/
Published: 17 October 2023
(This article belongs to the Special Issue Medical Genetics in Cardiovascular Disease)
Abstract
:Background and Objectives: This study aims to identify the minor allele of the single nucleotide polymorphisms (SNPs) DAB2IP rs7025486, IL6R rs2228145, CDKN2BAS rs10757278, LPA rs3798220, LRP1 rs1466535, and SORT1 rs599839 in order to assess the risk of abdominal aortic aneurysm (AAA) formation and define the linkage among these SNPs. Materials and Methods: A case-control study with AAA patients (AAA group) and non-AAA controls (control group) was carried out in a study population. DNA was isolated from whole blood samples; the SNPs were amplified using PCR and sequenced. Results: In the AAA group of 148 patients, 87.2% of the patients were male, 64.2% had a history of smoking, and 18.2% had relatives with AAA. The mean ± SD of age, BMI, and aneurysmal diameter in the AAA group were 74.8 ± 8.3 years, 27.6 ± 4.6 kg/m2, and 56.2 ± 11.8 mm, respectively. In comparison with 50 non-AAA patients, there was a significantly elevated presence of the SNPs DAB2IP rs7025486[A], CDKN2BAS rs10757278[G], and SORT1 rs599839[G] in the AAA group (p-values 0.040, 0.024, 0.035, respectively), while LPA rs3798220[C] was significantly higher in the control group (p = 0.049). A haplotype investigation showed that the SNPs DAB2IP, CDKN2BAS, and IL6R rs2228145[C] were significantly elevated in the AAA group (p = 0.037, 0.037, and 0.046) with minor allele frequencies (MAF) of 25.5%, 10.6%, and 15.4%, respectively. Only DAB2IP and CDKN2BAS showed significantly higher occurrences of a mutation (p = 0.028 and 0.047). Except for LPA, all SNPs were associated with a large aortic diameter in AAA (p < 0.001). Linkage disequilibrium detection showed that LPA to DAB2IP, to IL6R, to CDKN2BAS, and to LRP1 rs1466535[T] had D’ values of 70.9%, 80.4%, 100%, and 100%, respectively. IL6R to LRP1 and to SORT1 had values for the coefficient of determination (r2) of 3.9% and 2.2%, respectively. Conclusions: In the investigated study population, the SNPs CDKN2BAS rs10757278, LPA rs3798220, SORT1 rs599839, DAB2IP rs7025486, and IL6R rs2228145 were associated with the development of abdominal aortic aneurysms. Individuals with risk factors for atherosclerosis and/or a family history of AAA should be evaluated using genetic analysis.
1. Introduction
Abdominal aortic aneurysm (AAA) is a degenerative disease with a prevalence from 3.9 to 7.7% in the USA and Europe [1]. It mainly occurs in the last decades of life and predominantly affects the male gender [2]. A ruptured AAA leads to a high mortality rate of up to 80% [3,4]. The risk of developing AAA increases with hypertension, dyslipidemia, and a history of smoking [5,6]. The impact of the risk factor “smoking” is expressed in a high odds ratio (OR) between smoking and non-smoking AAA patients of 2.3 to 13.72 [6]. Hereditary factors also play a role in the development of AAA with up to 20% of all AAA cases attributable to genetic predisposition [7,8]. The prevalence of familial AAA is from 13 to 25% and is found among siblings [7]. Various investigators have studied the polymorphisms of specific genes and encoded key molecules that are likely to be involved in AAA formation, such as structural proteins of the vessel wall, tissue-degrading enzymes and corresponding tissue inhibitors, immuno-modulatory molecules, and molecules involved in hemodynamic stress [4]. In meta-analyses of genome-wide association studies (GWAS) with distinct ethnicities and population genetic studies, different genes with single nucleotide polymorphisms (SNPs) have been reported to be associated with AAA [3,9,10]. The following six gene sequences and corresponding SNPs DAB2IP (rs7025486), IL6R (rs2228145), CDKN2BAS (rs10757278), LPA (rs3798220), LRP1 (rs1466535), and SORT1 (rs599839) have not yet been investigated in the study population, for which only a few studies have reported on other SNPs and their association with AAA [11].
The aim of our study is to identify the minor allele of the SNPs to assess the risk of AAA in a study population and define the linkage among these SNPs.
2. Materials and Methods
2.1. Study Population
This is a single-center case-control study of AAA patients and non-AAA controls in two referral centers for vascular and endovascular surgery between November 2016 and October 2019. All individuals provided their written informed consent to participate in this study. The study was conducted according to the Declaration of Helsinki and passed ethical clearance from the Ethics Commission of the Medical Council (Approval Number 2016-361-f-S).
The inclusion criteria were a confirmed diagnosis of degenerative AAA and patient age ≥18 years, with and without type II diabetes mellitus. The exclusion criteria were aortic dissection, connective tissue disorders, e.g., Ehlers-Danlos syndrome, Loeys-Dietz syndrome, or Marfan syndrome, and HIV/Hepatitis C infection. The control group consisted of patients ≥18 years who were previously not diagnosed with AAA.
Patients and controls were selected consecutively in the ambulatory setting. All relevant clinical information was collected from the patients’ histories and the medical record system.
2.2. Genotyping
Whole blood samples (8.5 mL) were collected from the patients and the controls using PAXgene Blood DNA Tubes (PreAnalytiX Qiagen, Hilden, Germany). DNA isolation was performed according to the protocol of the PAXgene Blood DNA Kit (Qiagen). Primers and the PCR protocol are listed in Supplementary Table S1. The PCR products were controlled using gel electrophoresis (Supplementary Figure S1). The detected gene sequences were purified using a PeqGOLD-Microspin Cycle-Pure Kit (VWR International, Darmstadt, Germany). The PCR products were sequenced using the Sanger method performed by GATC (Biotech-AG-Eurofins, Hamburg, Germany). The locations of the polymorphism loci of the SNPs were according to the dbSNP (NCBI). The polymorphism loci were evaluated using SNAPGene Viewer (GSL-Biotech-LLC, Chicago, IL, USA) and the software program Clustal-Omega (EMBL-EBI, Cambridge, UK).
2.3. Statistical Analysis
All statistical data and Forest plot diagrams were calculated using SPSS 27 (IBM, New York, USA). The nominal or ordinal parameters were presented as frequencies and percentages, and the numeric parameters were presented as mean ± SD (standard deviation). The categorical parameters were analyzed using the χ2 test and Fisher’s Exact test. Steady-state parameters were analyzed using the Mann–Whitney test or Wilcoxon test. A Student’s t-test was performed for comparison of the numeric data. Logistic regression univariate analysis was performed to calculate the OR (odds ratio) with 95% CI (confidence interval). The significance level was tested bilaterally with p-value < 0.05. Forest plot diagrams were used to summarize the OR of all six SNPs in this study using the lower and upper values of the 95% CI as limits.
Sample size estimation for genetic predisposition was performed using the software Power and Sample Size Calculation (Dept. of Biostatistics, Vanderbilt University, Nashville, TN, USA). To ensure homogeneity in the sex and age structure of the control group, recruitment of the controls was planned on the basis of the sex and age distribution in the AAA group.
The Hardy–Weinberg Equilibrium (HWE) describes a stationary state of the genetic variation (allele frequency) in a normal population from one generation to the next generation in the absence of other evolutionary changes, as opposed to the HWD—Hardy–Weinberg Disequilibrium. Deviations from HWE were tested using Pearson’s χ2 test, which evaluated the degree of difference between the observed genotype and allele frequencies and the frequencies that were expected if the HWE assumption held. Statistically significant test results suggest deviation from the HWE assumption.
Linkage Disequilibrium (LD) is the nonrandomized association of alleles at two or more loci. It is expressed as the basic linkage disequilibrium parameter, D, which is the difference between the observed and expected haplotype frequencies and is expressed as a percent. To avoid negative D in this study, we used D’ as the result of D/Dmax. A metric of LD is r2, which is equivalent to the Pearson correlation coefficient. r2 is calculated as a quotient of D2 and the product of frequencies and ranges from 0 to 1. TheLD was calculated using HaploView 4.2 (Broad-Institute, Cambridge, USA).
3. Results
3.1. Patient Characteristics
In total, 153 AAA patients and 54 controls were recruited. The rate of dropout samples was 3.3% (n = 5/153) in the AAA patients and 7.4% (n = 4/54) in the control group due to either insufficient DNA yield or detection of an HIV infection after blood analysis. The data of 148 AAA patients and 50 controls were evaluated. Patients with AAA were predominantly male, aged >65 years, and displayed significantly more comorbidities such as arterial hypertension, dyslipidemia, and a history of smoking compared to the controls (p < 0.001) (Table 1). Peripheral artery disease (PAD) was diagnosed in 25 AAA patients (16.9%).
A total of 103 AAA patients (69.6%) had a maximum aortic diameter ≥50 mm. The morphology was mostly fusiform (n = 111/148, 75%) and the aneurysms were located infrarenal (n = 95/148, 64.2%) (Supplementary Table S2).
Significant risk factors for a genotype mutation risk of AAA development (minor homozygotes and heterozygotes vs. major homozygotes) were investigated (Table 2). A higher occurrence of the SNP DAB2IP rs7025486[A] was detected in AAA patients with arterial hypertension (p < 0.001 with OR 3.295, 95% CI [1.704–6.374]) while a significantly higher occurrence of the SNP LRP1 rs1466535[T] was found in patients with a family history of AAA (p = 0.005; OR 3.275, 95% CI [1.390–7.717]) when compared to the control group. Obesity was significantly more often associated with AAA development for the genotype mutation of SORT1 rs599839[G] (p = 0.025, OR 2.419, 95% CI [1.101–5.314]). For LPA rs3798220[C] and IL6R rs2228145[C], there were no significant differences in the occurrence of genotype mutations between the AAA group and the controls.
3.2. Allele Frequencies, Haplotypes, and Mutations of the SNPs
3.2.1. Allele Frequencies
For the allele frequency analyses, both alleles of the gene were considered, resulting in 296 alleles for the AAA group and 100 alleles for the control group (Table 3, Figure 1).
The minor allele of the SNP DAB2IP rs7025486[A] was present in 17.6% (n = 52/296) of the alleles in the AAA group and in 9% (n = 9/100) of those in the control group. The overall OR between the two groups was 0.464, 95% CI [0.220–0.980], p = 0.040 with an OR < 1, indicating a decreased occurrence of the SNP DAB2IP rs7025486[A] in AAA development (protective exposure). Besides the SNP DAB2IP rs7025486[A], the SNPs CDKN2BAS rs10757278[G], LPA rs3798220[C], and SORT1 rs599839[G] also displayed significant differences in allele frequencies between the AAA and control groups. Here, the OR > 1 indicated the increased occurrence of these SNPs in AAA. The minor allele of CDKN2BAS rs10757278[G] was detected in 25% (n = 74) of male AAA patients and in 3.4% (n = 10) of female patients, with an OR for both sexes of 1.935, 95% CI [1.083–3.454], p = 0.024. The minor allele of LPA rs3798220[C] was displayed in 1.4% (n = 4) of the male AAA patients and was not detected in female AAA patients, but was detected in 3% (n = 3) of the female controls. The OR for both sexes was 3.842, 95% CI [1.011–14.600] in the AAA group with p = 0.049. The SNP SORT1 rs599839 showed a distribution of the minor allele [G] in 10.8% (n = 32) of the male and in 1.7% (n = 5) of the female AAA patients and was significantly higher than in the control group, p = 0.035. The OR for both sexes in the AAA group was 2.714, 95% CI [1.036–7.110]. The allele frequencies of LRP1 rs1466535 [T] and IL6R rs2228145[C] did not show significant differences between the AAA and the control groups for either sex (p = 0.918 and 0.159, respectively).
3.2.2. Haplotypes
Regarding zygosity, the similarities or differences between the individuals’ alleles, the set of DNA variations (polymorphisms) adjacent to one another at the same locus that tend to be inherited together (haplotypes), are presented in Table 4. For each SNP, the frequencies for major homozygote, heterozygote, and minor homozygote alleles are listed. In addition, the minor allele frequency (MAF) indicating the percent or fraction of the second most common allele for a given locus in a population is specified. The most frequent minor allele was detected in DAB2IP rs7025486[A] with a minor allele frequency (MAF) of 25.5% (p = 0.037). In the AAA group, this SNP had a frequency for major homozygote (GG), heterozygote (GA), and minor homozygote (AA) of 70.3% (n = 104), 24.3% (n = 36), and 5.4% (n = 8), respectively, for both sexes. The other two SNPs with significant differences in haplotypes were CDKN2BAS rs10757278[G] (p = 0.037; MAF = 10.6%) and IL6R rs2228145[C] (p = 0.046; MAF = 15.4%). The SNPs LRP1 rs1466535[T], LPA rs3798220[C], and SORT1 rs599839[G] showed no significant differences in haplotypes (p = 0.835, 0.146, and 0.203, respectively).
3.2.3. Mutations
The mutation occurrences in each genetic polymorphism revealed a higher occurrence of the SNP DAB2IP rs7025486[A] in the AAA group with 29.7% (n = 44) vs. 14% (n = 7) in the control group (p = 0.028) (Table 5). Also, the SNP CDKN2BAS rs10757278[G] showed a mutation in 43.9% (n = 65) of the AAA patients which was significantly higher than in the control group (28%, n = 14) (p = 0.047). For the SNPs LRP1 rs1466535[T], IL6R rs2228145[C], LPA rs3798220[C], and SORT1 rs599839[G], no significant differences in mutation occurrence were detected (p = 0.755, 0.073, 0.113, and 0.100, respectively).
In conclusion, the SNPs DAB2IP rs7025486[A] and CDKN2BAS rs10757278[G] were significantly different in all three investigated parameters: allele frequencies, haplotypes, and mutation occurrences, while no difference was detected for the SNP LRP rs1466535[T] (p = 0.918, 0.835, 0.755, respectively) (Table 3, Table 4 and Table 5).
Aneurysm sac size (>50 mm versus <50 mm) and morphology of AAA (saccular versus fusiform) revealed significant differences between the parameters in all SNPs, except for LPA rs3798220[C] (p = 0.180 and 0.401) (Table 6). With regard to the supra/juxtarenal vs. infrarenal AAA location, significant differences occurred only in the SNPs IL6R rs2228145[C], LPA rs3798220[C], and SORT1 rs599839[G] (p < 0.001, p < 0.001, and p = 0.005, respectively).
Regarding the Hardy–Weinberg Equilibrium (HWE), the four SNPs LRP1 rs1466535[T], CDKN2BAS rs10757278[G], IL6R rs2228145[C], and SORT1 rs599839[G] were in accordance with the HWE in the control group (p = 0.578, 0.119, 0.335, and 0.709, respectively) (Supplementary Table S3). In contrast to these, the SNPs DAB2IP rs7025486[A] and LPA rs3798220[C] were in accordance with the Hardy–Weinberg Disequilibrium (HWD) in the control group (p = 0.006 and 0.009, respectively).
3.3. Linkage Disequilibrium
Linkage disequilibrium (LD) describes the nonrandom association of alleles at two or more loci (Figure 2 and Supplementary Table S4). The SNPs LPA rs3798220[C] to DAB2IP rs7025486[A], to IL6R rs2228145[C], to CDKN2BAS rs10757278[G], and to LRP1 rs1466535[T] had D’ values of 0.709, 0.804, 1.00, and 1.00, respectively. Expressed as the correlation coefficient r2, the two highest r2 values occurred for IL6R rs2228145[C] to LRP1 rs1466535[T] and for IL6R rs2228145[C] to SORT1 rs599839[G] and reached 3.9% and 2.2%, respectively.
4. Discussion
The present study shows that the single nucleotide polymorphisms (SNPs) of the genes CDKN2BAS rs10757278, LPA rs3798220, SORT1 rs599839, DAB2IP rs7025486, and IL6R rs2228145 are associated with the development of abdominal aortic aneurysms (AAA) in a study population. To our knowledge, this is the first study to investigate polymorphisms in the selected SNP panel and to assess the Linkage Disequilibrium (LD) among them.
The SNPs in the processes of apoptosis and inflammation (CDKN2BAS rs10757278 +501A>G and IL6R rs2228145 +501A>C) and cholesterol metabolism (LPA rs3798220 +501T>C and SORT1 rs599839 +813A>G) represent risk factors for the development of AAA, while the SNP DAB2IP rs7025486 +501G>A has a protective effect. The SNP LRP1 rs1466535 +504C>T is not associated with AAA in the investigated population.
Polymorphisms of AAA have been investigated in different genome-wide association studies producing strong evidence that various SNPs are associated with AAA development [9,10]. Nevertheless, the pathway of these genetic polymorphisms in the development of AAA remains unclear.
The apoptotic process is critical in a physiological way and induced by tumor-suppressing genes [12,13]. DAB2IP plays a role in cell growth inhibition and correlates as a tumor-suppressing gene with the apoptotic process of the CDKN2BAS mechanism pathway. Histological images of the enlarged aortic wall have shown this apoptotic process [14,15]. The inactivation of tumor-suppressor genes could lead to an increased level of interleukin-6 receptor (IL6R) as demonstrated by Öner et al. [16,17]. Furthermore, IL6 as an inflammation mediator plays a role in the inflammatory process involved in the development of AAA [16,17]. Besides the tumor-suppressing genes, apoptosis, and inflammation theories, the development of AAA has a strong association with hypercholesterolemia [18]. Genetic polymorphisms of LRP1 (rs1466535), LPA (rs3798220), and SORT1 (rs599839) play a role in cholesterol metabolism [19,20,21]. This supports the theory that the development of AAA is associated with cholesterol metabolism in humans, although the exact pathway remains unclear.
4.1. Role of VSMC Apoptosis in Aneurysmal Formation–Potential Involvement of DAB2IP rs7025486[A], SORT1 rs599839[G], and CDKN2BAS rs10757278[G]
In aneurysmal formation, the apoptotic process is apparently due to vascular smooth muscle cell (VSMC) apoptosis which shows an over-expression of p53 in the aneurysmal aortic wall [22]. Both DAB2IP and CDKN2BAS use the p53 signaling pathway in the apoptotic process [23,24,25]. With reference to the histological images and the p53 signaling in VSMC, this might be a pathway via which DAB2IP and CDKN2BAS are involved in the development of AAA.
Recent studies demonstrated that DAB2IP rs7025486[A] and SORT1 rs599839[G] showed an association with AAA expansion rate [3]. In the present study, the allele frequencies of DAB2IP rs7025486[A] and SORT1 rs599839[G] were significantly higher in the AAA group than in the control group. Furthermore, the DAB2IP rs7025486[A] haplotypes and mutation occurrences displayed significant differences. Our findings are in line with another GWAS, which also found significant data for the [A] allele in DAB2IP rs7025486 [26]. DAB2IP is located on 9q33.1-q33.3 and acts as an apoptosis signal-regulating kinase 1-interacting protein. This GTP-ase-activating protein plays a role in mediating TNF-induced cell apoptosis and in cell cycle checkpoint regulation. The latter has an inhibitory effect on vascular smooth muscle cell (VSMC) proliferation via the pathway of JAK-STAT and on endothelial cell migration and angiogenesis [3]. The miR-182/SORT1 axis regulates vascular smooth muscle cell calcification in vitro and in vivo [27]. The present study also confirms that DAB2IP rs7025486[A] and SORT1 rs599839[G] are associated with a large diameter of the aneurysm sac.
Additionally, CDKN2BAS rs10757278 [G] showed significant differences in allele frequencies, haplotypes, and mutation occurrences and these findings match well with the meta-analysis results of 9p21 (CDKN2BAS) A/G and G/G [9,28]. The LD blocks for CDKN2BAS rs10757278[G] also had a strong D’ with LPA rs3798220[C] (D’ = 100%). This SNP is also significantly associated with metabolic syndrome (MetS) and hypercholesterolemia [29]. p53 signaling is involved in cholesterol metabolism via a process known as the ‘Hippo Pathway’ [30,31].
4.2. Involvement of Hypercholesterolemia in Aneurysmal Formation–Potential Roles of SORT1 rs599839 [G], LRP1 rs1466535 [T], and LPA rs3798220 [C]
SORT1, besides its function in VSMC calcification, and the genes LRP1 and LPA have a common pathway in cholesterol metabolism [19,25]. Lu et al. also reported that hypercholesterolemia was associated with the development of AAA [32]. A systematic review by Bradley et al. reported a significant association between the genetic polymorphism of SORT1 rs599839[G] and AAA [9]. The present results also revealed significant differences in this SNP in the [G] allele between the AAA and control groups (p = 0.035) and as a risk factor for AAA (p = 0.025) in obesity, but not in the haplotype nor in the mutation occurrence (p = 0.203 and 0.100). Of note, the SORT1 rs599839[G] allele was 2.714 times more likely to occur in the AAA group with a minor allele frequency (MAF) of 2.3%.
In our study, the genetic polymorphism of LRP1 rs1466535 [T] showed no significant differences in allele frequencies, haplotypes, and mutation occurrences but was associated with a family history of AAA (p = 0.005) and a large aortic diameter. In the present study, the SNP LPA rs3798220[C] showed significant differences in allele frequencies and in the location of AAA but not in the haplotypes nor the mutation occurrence. The present data support the theory that the SNPs LPA rs3798220[C] and SORT1 rs599839[G] but not LRP1 rs1466535 are associated with the development of AAA.
It has been reported that LPA rs3798220 plays a role in cholesterol metabolism, in which the JAK-STAT signaling pathway is crucial [20,33]. It can be assumed that CDKN2BAS rs10757278 and LPA rs3798220 stimulate the development of AAA via p53 signaling and the cholesterol pathway. Moreover, the coincidence in strong LD shows that these two SNPs are more closely linked.
Clarke et al. reported that LPA rs3798220 accounted for 36% of the low-density lipoprotein variations in systemic atherosclerosis [34]. Due to its correlation with this vascular disease, LPA is also implicated in coronary artery disease and PAD, as well as AAA [35,36]. Although the present study did not imply significant results for the LPA rs3798220[G] variant in haplotypes and mutation occurrences, this gene contributed in the linkage disequilibrium to a higher D’ value than the other genetic polymorphisms. The consequence of this is that the presence of LPA rs3798220 could interfere with the presence of the other SNPs, such as CDKN2BAS rs10757278, LRP1 rs1466535, IL6R rs2228145, and DAB2IP rs7025486.
4.3. Role of Inflammatory Mediators in Aneurysmal Formation–Potential Involvement of IL6R rs2228145[C] and LPA rs3798220[C]
The circulating level of IL6 as an inflammatory mediator was shown to correlate with the presence of AAA [37]. Previous studies showed that the SNP IL6R rs2228145[C] had significant differences in haplotypes AC and CC as demonstrated in the downstream effect of IL6R (STAT3) expression [16,25,37,38]. The present study showed significant differences in the incidence of these haplotypes of IL6R rs2228145 in the AAA group compared to the control group. It can be assumed that this association is closely related to the inflammation process in the apoptosis pathway in AAA development. Furthermore, according to the Linkage Disequilibrium blocks, this SNP had the highest value of r2 in correspondence with LRP1 rs1466535 and SORT1 rs599839.
4.4. Limitations of This Study
It was not possible to achieve homogeneity of the “sex and age” of the AAA and the control groups. In the control group, DAB2IP rs7025486 and LPA rs3798220 were in accordance with the Hardy–Weinberg Disequilibrium, instead of the Hardy–Weinberg Equilibrium.
5. Conclusions
Five SNPs’ variation in the selected panel, i.e., DAB2IP rs7025486[A], CDKN2BAS rs10757278[G], IL6R rs2228145[C], LPA rs3798220[C], and SORT1 rs599839[G], are associated with the development of AAA disease. The SNP LRP1 rs1466535[T], however, is not associated with AAA disease but is associated with a large aortic diameter in AAA. LPA rs3798220 is linked predominantly to the other investigated SNPs. This study could be used to inform the genetic screening of AAA patients and their families.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/medicina59101844/s1, (Figure S1: PCR Results in Electrophoresis Gel for all SNPs; Table S1: List of Primers; Table S2: AAA Patients’ Characteristics Defined by Sex; Table S3: Hardy–Weinberg (HW) Calculation; Table S4: Linkage Disequilibrium for Genetic Polymorphism).
Author Contributions
Conceptualization, N.T.N., M.H., N.O., S.S. and G.B.T.; methodology, N.T.N., M.H., N.O., S.S. and G.B.T.; validation, N.T.N., M.H., N.O. and G.F.T.; investigation, N.T.N., M.H., E.M. and S.S.; data curation, N.T.N., M.H., N.O., E.M., S.S. and G.F.T.; writing—original draft preparation, N.T.N., M.H., G.F.T. and N.O.; writing—review and editing, N.T.N., M.H., G.F.T., N.O., E.M., S.S. and G.B.T.; visualization, N.T.N., M.H. and G.F.T.; supervision, G.B.T.; project administration, N.T.N.; funding acquisition, N.T.N., M.H. and G.B.T. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported and funded by the Indonesian Endowment Fund for Education (LPDP) Ministry of Finance, Republic of Indonesia. The first author also received a full scholarship from the LPDP while preparing for a PhD degree during this study. We acknowledge support by the Open Access Publication Fund of the University of Duisburg-Essen, Germany.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Commission of the Medical Council Westfalen-Lippe and the University of Münster, Germany (protocol code 2016-361; approval date 2016-11-24).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data available on request from the authors.
Acknowledgments
We acknowledge Kaye Schreyer for editing the manuscript. We also thank Wojciech Makalowski from the Institute of Bioinformatics, Faculty of Medicine, University of Münster, Germany, for his support concerning data evaluation.
Conflicts of Interest
The authors declare no conflict of interest.
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Figure 1.
Forest plot of all SNPs.
Figure 2.
Linkage Disequilibrium (LD) blocks for all SNPs. (a) Number in the small square indicates the percentage of the D’ regarding two SNPs that crossed one another, with the color scheme being the alternate of D’/LOD (log of likelihood odds ratio) according to Haploview 4.2. White color indicates low D’–low LOD or low D’–high LOD (shades of grey indicate higher D’); shades of pink to red color indicate high D’–low LOD (darker pink to red or brown-red indicates higher D’); black indicates high D’–high LOD. Absence of number inside the small square indicates D’ = 100%. (b) Number in the small square indicates the r2 value in percentage, with color scheme of GOLD Heatmap. Shade color from yellowish to red indicates higher D’. See Supplementary Table S3 for detailed D’ and r2 values.
Figure 2.
Linkage Disequilibrium (LD) blocks for all SNPs. (a) Number in the small square indicates the percentage of the D’ regarding two SNPs that crossed one another, with the color scheme being the alternate of D’/LOD (log of likelihood odds ratio) according to Haploview 4.2. White color indicates low D’–low LOD or low D’–high LOD (shades of grey indicate higher D’); shades of pink to red color indicate high D’–low LOD (darker pink to red or brown-red indicates higher D’); black indicates high D’–high LOD. Absence of number inside the small square indicates D’ = 100%. (b) Number in the small square indicates the r2 value in percentage, with color scheme of GOLD Heatmap. Shade color from yellowish to red indicates higher D’. See Supplementary Table S3 for detailed D’ and r2 values.
Table 1.
Sample Characteristics Defined by Group.
| Parameter | AAAs, n = 148 n (%) | Controls, n = 50 n (%) | p-Value |
|---|---|---|---|
| Sex | <0.001 | ||
| Female | 19 (12.8) | 27 (54.0) | |
| Male | 129 (87.2) | 23 (46.0) | |
| Age, years | 74.8 ± 8.3 | 49.5 ± 13.2 | <0.001 |
| 19–35 | 0 (0) | 10 (20.0) | |
| 36–65 | 22 (14.9) | 36 (72.0) | |
| >65 | 126 (85.1) | 4 (8.0) | |
| Body Mass Index, kg/m2 | 27.6 ± 4.6 | 26.3 ± 5.7 | 0.097 |
| Body height in cm | 176.5 ± 7.8 | 177.5 ± 9.6 | 0.462 |
| Body weight in kg | 86.1 ± 15.0 | 83.5 ± 23.0 | 0.358 |
| Hypertension | 61 (41.2) | 10 (20) | 0.07 |
| Systolic in mmHg | 133.1 ± 20.0 | 122.6 ± 11.9 | 0.001 |
| Diastolic in mmHg | 75.9 ± 11.7 | 73.0 ± 10.6 | 0.12 |
| MAP | 94.9 ± 12.6 | 89.5 ± 9.7 | 0.177 |
| Dyslipidemia | 66 (44.6) | 5 (10.0) | <0.001 |
| Smoking history | 95 (64.2) | 11 (22) | <0.001 |
| Smoking in pack years | 34.9 ± 14.9 | 20.7 ± 13.7 | 0.003 |
| PAD | 25 (16.9) | 6 (12.0) | 0.411 |
| Relatives with AAA history | 27 (18.2) | 3 (6.0) | 0.139 |
| Parent–child relationship * | 15 (10.1) | 1 (2.0) | |
| Sibling relationship | 3 (2.0) | 1 (2.0) | |
| Twin | 5 (3.4) | 0 (0) | |
| Others | 4 (2.7) | 1 (2.0) | |
| Sex of relatives diagnosed with AAA | 0.539 | ||
| Male–male or female–female | 19 (12.8) | 2 (4.0) | |
| Male–female or female–male | 7 (4.7) | 1 (2.0) | |
| Both sexes to male/female | 1 (0.7) | 0 (0) | |
| Younger than sample | 7 (4.7) | 2 (4.0) | |
| Older than sample | 20 (13.5) | 1 (2.0) | |
* paternal relationship (n = 9/198, 4.5%) and maternal relationship (n = 7/198, 3.5%) in all samples (patients and controls). One sample in the control group was a paternal relationship. Abbreviations: MAP (mean arterial pressure); AAA (abdominal aortic aneurysm); PAD (peripheral arterial disease).
Table 2.
Genotype Mutation Risk for the Occurrence of AAA with Different Risk Factors.
| Variable | DAB2IP rs7025486 | LRP1 rs1466535 | ||
|---|---|---|---|---|
| OR [95% CI] | p-Value | OR [95% CI] | p-Value | |
| Age, years | 1.353 [0.679–2.698] | 0.389 | 1.026 [0.534–1.970] | 0.938 |
| Male sex | 1.874 [0.809–4.341] | 0.139 | 0.873 [0.424–1.796] | 0.711 |
| Smoking history | 1.661 [0.865–3.193] | 0.126 | 1.002 [0.539–1.863] | 0.995 |
| Family history of AAA | 2.146 [0.896–5.141] | 0.081 | 3.275 [1.390–7.717] | 0.005 |
| First-degree relatives | 2.300 [0.869–6.087] | 0.087 | 1.985 [0.753–5.230] | 0.159 |
| Obesity | 1.229 [0.586–2.581] | 0.585 | 0.665 [0.304–1.454] | 0.304 |
| Hypertension | 3.295 [1.704–6.374] | <0.001 | 1.365 [0.723–2.578] | 0.337 |
| Dyslipidemia | 0.967 [0.497–1.882] | 0.922 | 0.795 [0.413–1.533] | 0.494 |
| PAD | 1.218 [0.520–2.850] | 0.650 | 1.253 [0.548–2.861] | 0.593 |
| Statins | 0.967 [0.497–1.882] | 0.922 | 0.795 [0.413–1.533] | 0.494 |
| Aspirin | 0.813 [0.415–1.589] | 0.544 | 0.596 [0.305–1.166] | 0.129 |
| Clopidogrel | 3.133 [0.963–10.200] | 0.048 | 1.891 [0.574–6.227] | 0.288 |
| Warfarin | 1.020 [0.379–2.745] | 0.969 | 1.751 [0.711–4.313] | 0.219 |
| Variable | CDKN2BAS rs10757278 | IL6R rs2228145 | ||
| OR [95% CI] | p-Value | OR [95% CI] | p-Value | |
| Age, years | 1.344 [0.733–2.467] | 0.339 | 0.496 [0.228–1.078] | 0.073 |
| Male sex | 1.327 [0.668–2.639] | 0.419 | 0.482 [0.211–1.100] | 0.079 |
| Smoking history | 1.258 [0.710–2.230] | 0.431 | 0.490 [0.224–1.075] | 0.072 |
| Family history of AAA | 1.213 [0.520–2.829] | 0.654 | 0.432 [0.096–1.933] | 0.260 |
| First-degree relatives | 1.401 [0.542–3.621] | 0.484 | 0.609 [0.133–2.777] | 0.517 |
| Obesity | 0.611 [0.301–1.241] | 0.171 | 0.788 [0.301–2.058] | 0.626 |
| Hypertension | 1.063 [0.588–1.922] | 0.839 | 0.981 [0.440–2.185] | 0.962 |
| Dyslipidemia | 1.276 [0.707–2.302] | 0.419 | 0.981 [0.440–2.185] | 0.962 |
| PAD | 1.509 [0.698–3.260] | 0.293 | 0.768 [0.249–2.373] | 0.646 |
| Statins | 1.276 [0.707–2.302] | 0.419 | 0.981 [0.440–2.185] | 0.962 |
| Aspirin | 2.031 [1.126–3.665] | 0.018 | 0.931 [0.419–2.073] | 0.862 |
| Clopidogrel | 3.239 [0.941–11.151] | 0.051 | 0.473 [0.059–3.799] | 0.471 |
| Warfarin | 1.182 [0.491–2.844] | 0.709 | 0.788 [0.219–2.830] | 0.714 |
| Variable | LPA rs3798220 | SORT1 rs599839 | ||
| OR [95% CI] | p-Value | OR [95% CI] | p-Value | |
| Age, years | 0.298 [0.069–1.285] | 0.087 | 1.381 [0.620–3.075] | 0.428 |
| Male sex | 0.488 [0.112–2.123] | 0.329 | 1.572 [0.609–4.059] | 0.347 |
| Smoking history | 0.863 [0.210–3.551] | 0.838 | 1.847 [0.862–3.960] | 0.111 |
| Family history of AAA | 0.988 [0.116–8.386] | 0.991 | 1.568 [0.576–4.266] | 0.375 |
| First-degree relatives | 1.365 [0.159–11.729] | 0.561 | 2.387 [0.839–6.794] | 0.095 |
| Obesity | 2.114 [0.485–9.212] | 0.385 | 2.419 [1.101–5.314] | 0.025 |
| Hypertension | 0.245 [0.030–2.032] | 0.263 | 1.654 [0.789–3.466] | 0.180 |
| Dyslipidemia | 0.585 [0.115–2.976] | 0.714 | 1.906 [0.911–3.991] | 0.084 |
| PAD | 1.050 [1.015–1.087] | 0.362 | 0.650 [0.212–1.992] | 0.610 |
| Statins | 0.585 [0.115–2.976] | 0.513 | 1.906 [0.911–3.991] | 0.084 |
| Aspirin | 0.234 [0.028–1.942] | 0.145 | 1.175 [0.556–2.483] | 0.672 |
| Clopidogrel | 1.045 [1.014–1.077] | 0.463 | 0.927 [0.194–4.431] | 0.925 |
| Warfarin | 1.048 [1.014–1.082] | 0.600 | 0.978 [0.311–3.076] | 0.970 |
Table 3.
Allele Frequencies of Genetic Polymorphism.
| AAAs’ Allele n = 296 | Controls’ Allele n = 100 | OR | 95% CI | p-Value | |||||
|---|---|---|---|---|---|---|---|---|---|
| Allele | n | % | n | % | |||||
| DAB2IP rs7025486 + 501G>A | Male | G | 212 | 71.6 | 40 | 40.0 | |||
| A | 46 | 15.5 | 6 | 6.0 | 0.691 | 0.277–1.727 | 0.427 | ||
| Female | G | 32 | 10.8 | 51 | 51.0 | ||||
| A | 6 | 2.1 | 3 | 3.0 | 0.314 | 0.073–1.344 | 0.154 | ||
| Total | G | 244 | 82.4 | 91 | 91.0 | ||||
| A | 52 | 17.6 | 9 | 9.0 | 0.464 | 0.220–0.980 | 0.040 | ||
| LRP1 rs1466535 + 504C>T | Male | C | 219 | 74.0 | 36 | 36.0 | |||
| T | 39 | 13.2 | 10 | 10.0 | 0.641 | 0.294–1.397 | 0.260 | ||
| Female | C | 28 | 9.5 | 47 | 47.0 | ||||
| T | 10 | 3.4 | 7 | 7.0 | 2.398 | 0.820–7.014 | 0.104 | ||
| Total | C | 247 | 83.4 | 83 | 83.0 | ||||
| T | 49 | 16.6 | 17 | 17.0 | 0.969 | 0.529–1.774 | 0.918 | ||
| CDKN2BAS rs10757278 + 501A>G | Male | A | 184 | 62.2 | 38 | 38.0 | |||
| G | 74 | 25.0 | 8 | 8.0 | 1.910 | 0.851–4.289 | 0.112 | ||
| Female | A | 28 | 9.5 | 45 | 45.0 | ||||
| G | 10 | 3.4 | 9 | 9.0 | 1.786 | 0.646–4.935 | 0.260 | ||
| Total | A | 212 | 71.6 | 83 | 83.0 | ||||
| G | 84 | 28.4 | 17 | 17.0 | 1.935 | 1.083–3.454 | 0.024 | ||
| IL6R rs2228145 + 501A>C | Male | A | 240 | 81.1 | 41 | 41.0 | |||
| C | 18 | 6.1 | 5 | 5.0 | 0.615 | 0.216–1.748 | 0.358 | ||
| Female | A | 34 | 11.5 | 47 | 47.0 | ||||
| C | 4 | 1.4 | 7 | 7.0 | 0.790 | 0.214–2.914 | 0.723 | ||
| Total | A | 274 | 92.6 | 88 | 88.0 | ||||
| C | 22 | 7.4 | 12 | 12.0 | 0.589 | 0.280–1.238 | 0.159 | ||
| LPA rs3798220 + 501T>C | Male | T | 254 | 85.8 | 44 | 44.0 | |||
| C | 4 | 1.4 | 2 | 2.0 | 2.886 | 0.513–16.24 | 0.226 | ||
| Female | T | 38 | 12.8 | 51 | 51.0 | ||||
| C | 0 | 0.0 | 3 | 3.0 | 0.944 | 0.885–1.008 | 0.265 | ||
| Total | T | 292 | 98.6 | 95 | 95.0 | ||||
| C | 4 | 1.4 | 5 | 5.0 | 3.842 | 1.011–14.60 | 0.049 | ||
| SORT1 rs599839 + 813A>G | Male | A | 226 | 76.4 | 44 | 44.0 | |||
| G | 32 | 10.8 | 2 | 2.0 | 3.115 | 0.720–13.47 | 0.132 | ||
| Female | A | 33 | 11.1 | 51 | 51.0 | ||||
| G | 5 | 1.7 | 3 | 3.0 | 2.576 | 0.577–11.51 | 0.268 | ||
| Total | A | 259 | 87.5 | 95 | 95.0 | ||||
| G | 37 | 12.5 | 5 | 5.0 | 2.714 | 1.036–7.110 | 0.035 | ||
Table 4.
Haplotypes in Genetic Polymorphism.
| Haplotype n (%) | MAF * (%) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Major Homozygote | Heterozygote | Minor Homozygote | p-Value | ||||||
| AAAs | Controls | AAAs | Controls | AAAs | Controls | ||||
| DAB2IP rs7025486 + 501G>A | Male | 90 (69.8) | 19 (82.6) | 32 (24.8) | 2 (8.7) | 7 (5.4) | 2 (8.7) | ||
| Female | 14 (73.7) | 24 (88.9) | 4 (21.1) | 3 (11.1) | 1 (5.2) | 0 (0) | |||
| Total | 104 (70.3) | 43 (86.0) | 36 (24.3) | 5 (10.0) | 8 (5.4) | 2 (4.0) | 0.037 | 25.5 | |
| LRP1 rs1466535 + 504C>T | Male | 95 (73.6) | 15 (65.2) | 29 (22.5) | 6 (26.1) | 5 (3.9) | 2 (8,7) | ||
| Female | 12 (63.2) | 20 (74.1) | 4 (21.1) | 7 (25.9) | 3 (15.7) | 0 (0) | |||
| Total | 107 (72.3) | 35 (70.0) | 33 (22.3) | 13 (26.0) | 8 (5.4) | 2 (4.0) | 0.835 | 16.7 | |
| CDKN2BAS rs10757278 + 501A>G | Male | 72 (55.8) | 17 (73.9) | 40 (31.0) | 4 (17.4) | 17 (13.2) | 2 (8.7) | ||
| Female | 10 (52.6) | 19 (70.4) | 8 (42.1) | 7 (25.9) | 1 (5.3) | 1 (3.7) | |||
| Total | 82 (55.4) | 36 (72.0) | 48 (32.4) | 11 (22.0) | 18 (12.2) | 3 (6.0) | 0.037 | 10.6 | |
| IL6R rs2228145 + 501A>C | Male | 114 (88.4) | 18 (78.3) | 12 (9.3) | 5 (21.7) | 3 (2.3) | 0 (0) | ||
| Female | 15 (78.9) | 20 (74.1) | 4 (21.1) | 7 (25.9) | 0 (0) | 0 (0) | |||
| Total | 129 (87.2) | 38 (76.0) | 16 (10.8) | 12 (24.0) | 3 (2.0) | 0 (0) | 0.046 | 15.4 | |
| LPA rs3798220 + 501T>C | Male | 125 (96.9) | 22 (95.7) | 4 (3.1) | 0 (0) | 0 (0) | 1 (4.3) | ||
| Female | 19 (100.0) | 24 (88.9) | 0 (0) | 3 (11.1) | 0 (0) | 0 (0) | |||
| Total | 144 (97.3) | 46 (92.0) | 4 (2.7) | 3 (6.0) | 0 (0) | 1 (2.0) | 0.146 | 8.6 | |
| SORT1 rs599839 + 813A>G | Male | 102 (79.0) | 21 (91.3) | 22 (17.1) | 2 (8.7) | 5 (3.9) | 0 (0) | ||
| Female | 16 (84.2) | 24 (88.9) | 1 (5.3) | 3 (11.1) | 2 (10.5) | 0 (0) | |||
| Total | 118 (79.7) | 45 (90.0) | 23 (15.5) | 5 (10.0) | 7 (4.8) | 0 (0) | 0.203 | 2.3 | |
* MAF, minor allele frequency.
Table 5.
Mutation Occurrences in each Genetic Polymorphism.
| Mutation (n, %) | ||||||
|---|---|---|---|---|---|---|
| Occurred | Not Occurred | p-Value | ||||
| AAAs | Controls | AAAs | Controls | |||
| DAB2IP rs7025486 + 501G>A | Male | 39 (30.2) | 4 (17.4) | 90 (69.8) | 19 (82.6) | 0.314 |
| Female | 5 (26.3) | 3 (11.1) | 14 (73.7) | 24 (88.9) | 0.246 | |
| Total | 44 (29.7) | 7 (14.0) | 104 (70.4) | 43 (86.0) | 0.028 | |
| LRP1 rs1466535 + 504C>T | Male | 34 (26.4) | 8 (34.8) | 95 (73.6) | 15 (65.2) | 0.405 |
| Female | 7 (36.8) | 7 (25.9) | 12 (63.2) | 20 (74.1) | 0.428 | |
| Total | 41 (27.7) | 15 (30.0) | 107 (72.3) | 35 (70.0) | 0.755 | |
| CDKN2BAS rs10757278 + 501A>G | Male | 57 (44.2) | 6 (26.1) | 72 (55.8) | 17 (73.9) | 0.105 |
| Female | 8 (42.1) | 8 (29.6) | 11 (57.9) | 19 (70.4) | 0.382 | |
| Total | 65 (43.9) | 14 (28.0) | 83 (56.1) | 36 (72.0) | 0.047 | |
| IL6R rs2228145 + 501A>C | Male | 15 (11.6) | 5 (21.7) | 114 (88.4) | 18 (78.3) | 0.186 |
| Female | 4 (21.1) | 7 (25.9) | 15 (78.9) | 20 (74.1) | >0.995 | |
| Total | 19 (12.8) | 12 (24.0) | 129 (87.2) | 38 (76.0) | 0.073 | |
| LPA rs3798220 + 501T>C | Male | 4 (3.1) | 1 (4.3) | 125 (96.9) | 22 (95.7) | 0.565 |
| Female | 0 (0) | 3 (11.1) | 19 (100.0) | 24 (88.9) | 0.257 | |
| Total | 4 (2.7) | 4 (8.0) | 144 (97.3) | 46 (92.0) | 0.113 | |
| SORT1 rs599839 + 813A>G | Male | 27 (20.9) | 2 (8.7) | 102 (79.1) | 21 (91.3) | 0.250 |
| Female | 3 (15.8) | 3 (11.1) | 16 (84.2) | 24 (88.9) | 0.680 | |
| Total | 30 (20.3) | 5 (10.0) | 118 (79.7) | 45 (90.0) | 0.100 | |
Table 6.
Genotype Risk in Size of Aortic Diameter, AAA Morphology, and AAA Renally Referenced Location.
Table 6.
Genotype Risk in Size of Aortic Diameter, AAA Morphology, and AAA Renally Referenced Location.
| SNPs | Aneurysmal Sac Size | Morphology of AAA | ||||||
|---|---|---|---|---|---|---|---|---|
| Small (<50 mm) n (%) | Large (≥ 50 mm) n (%) | OR [95% CI] | p-Value * | Fusiform n (%) | Saccular n (%) | OR [95% CI] | p-Value * | |
| n = 45 | n = 103 | n = 111 | n = 19 | |||||
| DAB2IP rs7025486 | ||||||||
| GG | 34 (75.6) | 70 (68.0) | 1.457 | <0.001 | 77 (69.4) | 16 (84.2) | 2.35 | <0.001 |
| GA + AA | 11 (24.4) | 33 (32.0) | [0.66–3.23] | 34 (30.6) | 3 (15.8) | [0.64–8.62] | ||
| LRP1 rs1466535 | ||||||||
| CC | 35 (77.8) | 72 (69.9) | 1.507 | <0.001 | 81 (73.0) | 15 (78.9) | 1.389 | <0.001 |
| CT + TT | 10 (22.2) | 31 (30.1) | [0.66–3.42] | 30 (27.0) | 4 (21.1) | [0.43–4.52] | ||
| CDKN2BAS rs10757278 | ||||||||
| AA | 24 (53.3) | 59 (57.3) | 0.852 | <0.001 | 62 (55.9) | 10 (52.6) | 0.878 | <0.001 |
| AG + GG | 21 (46.7) | 44 (42.7) | [0.42–1.72] | 49 (44.1) | 9 (47.4) | [0.33–2.33] | ||
| IL6R rs2228145 | ||||||||
| AA | 41 (91.1) | 88 (85.4) | 1.747 | <0.001 | 96 (86.5) | 16 (84.2) | 0.833 | <0.001 |
| AC + CC | 4 (8.9) | 15 (14.6) | [0.55–5.59] | 15 (13.5) | 3 (15.8) | [0.22–3.21] | ||
| LPA rs3798220 | ||||||||
| TT | 45 (100) | 99 (96.1) | 0.961 | 0.180 | 107 (96.4) | 19 (100) | 0.964 | 0.401 |
| TC + CC | 0 (0) | 4 (3.9) | [0.92–1.00] | 4 (3.6) | 0 (0) | [0.93–1.00] | ||
| SORT1 rs599839 | ||||||||
| AA | 35 (77.8) | 83 (80.6) | 0.843 | <0.001 | 86 (77.5) | 16 (84.2) | 1.550 | <0.001 |
| AG + GG | 10 (22.2) | 20 (19.4) | [0.36–1.98] | 25 (22.5) | 3 (15.8) | [0.42–5.75] | ||
| SNPs | Location of AAA | |||||||
| Supra/Juxtarenal n (%) | Infrarenal n (%) | OR [95% CI] | p-Value * | |||||
| n = 53 | n = 95 | |||||||
| DAB2IP rs7025486 | ||||||||
| GG | 37 (69.8) | 67 (70.5) | 1.035 | 0.317 | ||||
| GA + AA | 16 (30.2) | 28 (29.5) | [0.50–2.15] | |||||
| LRP1 rs1466535 | ||||||||
| CC | 34 (64.2) | 73 (76.8) | 1.854 | 0.138 | ||||
| CT + TT | 19 (35.8) | 22 (23.2) | [0.89–3.87] | |||||
| CDKN2BAS rs10757278 | ||||||||
| AA | 28 (52.8) | 55 (57.9) | 1.228 | 0.118 | ||||
| AG + GG | 25 (47.2) | 40 (42.1) | [0.62–2.41] | |||||
| IL6R rs2228145 | ||||||||
| AA | 47 (88.7) | 82 (86.3) | 0.805 | <0.001 | ||||
| AC + CC | 6 (11.3) | 13 (13.7) | [0.29–2.26] | |||||
| LPA rs3798220 | ||||||||
| TT | 51 (96.2) | 93 (97.9) | 1.824 | <0.001 | ||||
| TC + CC | 2 (3.8) | 2 (2.1) | [0.25–13.33] | |||||
| SORT1 rs599839 | ||||||||
| AA | 43 (81.1) | 75 (78.9) | 0.872 | 0.005 | ||||
| AG + GG | 10 (18.9) | 20 (21.1) | [0.37–2.03] | |||||
* p-value indicates the Chi-square test between groups.
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Nugroho, N.T.; Herten, M.; Torsello, G.F.; Osada, N.; Marchiori, E.; Sielker, S.; Torsello, G.B. Association of Genetic Polymorphisms with Abdominal Aortic Aneurysm in the Processes of Apoptosis, Inflammation, and Cholesterol Metabolism. Medicina 2023, 59, 1844. https://doi.org/10.3390/medicina59101844
AMA Style
Nugroho NT, Herten M, Torsello GF, Osada N, Marchiori E, Sielker S, Torsello GB. Association of Genetic Polymorphisms with Abdominal Aortic Aneurysm in the Processes of Apoptosis, Inflammation, and Cholesterol Metabolism. Medicina. 2023; 59(10):1844. https://doi.org/10.3390/medicina59101844
Chicago/Turabian StyleNugroho, Nyityasmono Tri, Monika Herten, Giovanni F. Torsello, Nani Osada, Elena Marchiori, Sonja Sielker, and Giovanni B. Torsello. 2023. "Association of Genetic Polymorphisms with Abdominal Aortic Aneurysm in the Processes of Apoptosis, Inflammation, and Cholesterol Metabolism" Medicina 59, no. 10: 1844. https://doi.org/10.3390/medicina59101844
