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Association of LDLR Gene Polymorphism with the Risk of Cardiovascular Disease in End-Stage Kidney Disease Patients on Maintenance Hemodialysis
Corresponding author: Enas Ahmed Osman, Department of Clinical Chemistry, Theodor Bilharz Research Institute, Giza, Egypt. E-mail: inasosman@ymail.com
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Received: ,
Accepted: ,
How to cite this article: Osman EA, Shawky H, Abbas RM, Metwaly AA, Ibrahim AH, Khanany FM. Association of LDLR Gene Polymorphism with the Risk of Cardiovascular Disease in End-Stage Kidney Disease Patients on Maintenance Hemodialysis. Indian J Nephrol. doi: 10.25259/IJN_33_2024
Abstract
Background
The low-density lipoprotein receptor (LDLR) is essential for regulating intracellular cholesterol levels. Mutations in the LDLR gene can cause a increase in LDL cholesterol levels in the blood, elevating the vulnerability to cardiovascular disease (CVD). This study evaluated the correlation between the LDLR rs688 polymorphism and CVD risk in chronic kidney disease (CKD).
Materials and Methods
Polymorphism in this case-control study was genotyped using the TaqMan real-time polymerase chain reaction in a cohort of 100 CKD patients (Group I) and 100 healthy controls (Group II). We examined the LDLR rs688 allele and genotype distribution in 50 CKD cases with CVD and 50 cases without CVD.
Results
There was a significantly greater frequency of CT variant of LDL SNP rs688 in Group I than in Group II (p = 0.006). CT and TT genotypes were significantly higher in CKD patients with CVD, with odds ratios (ORs) (95% CI) of 4.3 (1.6–11.8, p = 0.004) and 7.6 (2.3–24.8, p = 0.001), respectively.
Conclusion
SNP rs688 C>T detection in the LDLR gene showed that CT and TT genotypes are associated with elevated CVD risk in CKD.
Keywords
LDLR
Rs688
Chronic kidney disease
Cardiovascular disease
SNP
Introduction
Cardiovascular disease (CVD) is a primary contributor to mortality in people with chronic kidney disease (CKD). Patients diagnosed with CKD who simultaneously suffer from CVD have a much higher likelihood of death in comparison to the overall population. Indeed, their mortality risk is 20 times higher.1 CKD affects around 10% of the population, totaling over 800 million individuals worldwide.2
The prevalence of CKD in Egypt has been calculated to be 483 individuals per million, as reported in the Egyptian Renal Registry.3 The increasing occurrence and prevalence of advanced CKD can be linked to factors such as aging, escalating rates of type II diabetes and hypertension, a low rate of identification, and treatment inertia.4 Dyslipidemia is one of numerous variables that contribute to atherosclerosis and CVD in the CKD population.5
Attachment and uptake of plasma LDL particles are carried out by LDLR, a cell surface glycoprotein essential for preserving cellular cholesterol homeostasis.6 Increased plasma LDL levels brought on by LDLR gene mutations can raise the risk of atherosclerosis and ischemic heart disease.
The genetic background is a significant component of CVD pathogenesis.7
The LDLR gene harbors many documented mutations that impact the promoter regions, splicing sites, and exons.8 A few of these variations have been linked to high cholesterol in families. The 45 kb long LDLR gene, which codes for LDLR proteins, is located on chromosome 19 (19p13) and contains 18 exons.6
In LDLR exon 12, there is a single nucleotide polymorphism (SNP) rs688 (accession number NC_000019.10:11116925: C: T) that has been associated with low-density lipoprotein cholesterol and the coronary artery disorder’s development.9 This SNP disrupts a splicing enhancer, which in turn causes alternative exon splicing that can alter the reading frame and the transcript of the gene.10
This study sought to determine whether CKD patients’ susceptibility to CVD was correlated with the LDLR rs688 polymorphism.
Materials and Methods
The case-control study was performed between July and December of 2022. The research groups consisted of a total of 200 participants. They were categorized into two distinct groups. Group I involved 100 CKD cases; they were enlisted from the dialysis department of Theodor Bilharz Research Institute.
The Kidney Disease Improving Global Outcomes (KDIGO) criteria were utilized to classify the CKD stages.11
Subgroup (a) included 50 patients with CVD. Cardiovascular disease was characterized as the existence of congestive cardiac failure, hypertrophy of the left ventricle, coronary heart disease, or myocardial infarction. Clinical signs of CVD were validated using suitable radiographic, biochemical, echocardiographic, and vascular diagnostic criteria.
Subgroup (b) included 50 CKD patients without CVD on regular hemodialysis treatment for more than 6 months and, confirmed by electrocardiogram (ECG) and echocardiography. All patients underwent a comprehensive evaluation, including a thorough medical history assessment, laboratory tests, and a physical checkup.
Group II consisted of 100 healthy individuals. They were randomly selected, primarily from Theodor Bilharz Hospital personnel and blood donors who had undergone health checks. All individuals exhibited a normal ECG and showed no clinical indications of CVD. There was no history of kidney disease in the control group.
Before enrolling, we measured serum creatinine levels for all participants in Group II. Individuals with a first-degree relative who had a family history of renal or cardiovascular illness were excluded from the research. The study obtained approval from the Institutional Review Board of Theodor Bilharz Research Institute (FWA 00010609) with a protocol serial number PT (710). All participants provided informed consent, adhering to the ethical guidelines of our hospital’’s ethics committee, the 1975 Helsinki Declaration, and its subsequent revisions.
Sample size estimation
As per the prior study via Buraczynska et al.,12 the frequencies of the rs688 genotypes CC among CKD CVD+ were 23% and 45% in normal control. At a power of 80% and a significance level of 5%, a minimum sample size of 160 individuals is required to detect the difference between groups, i.e., 80 participants in each group. To compensate for possible dropouts, 15% was added, and the total sample size was 184 participants (92 participants in each group). G*Power (Germany; version 3.1.9.2) was employed to determine the sample size.
Laboratory investigations
Four milliliters of venous blood were collected in a plain sterile vacutainer from all subjects used to determine serum creatinine, serum triglycerides, total cholesterol, HDL-C, and LDL-C. In addition, 2 mL of venous blood was collected in an EDTA vacutainer to determine LDLR rs688.
In the clinical chemistry department of TBRI Hospital, regular laboratory tests were analyzed using a (Beckman Coulter)1 AU 480 chemistry analyzer.
Analysis of SNPs
Serum preparation and DNA extraction
The ThermoFisher Sci GeneJET Whole Blood Genomic DNA Purification Mini Kit 2(Catalog number: K0781, supplied by Clinilab, Egypt) was used to extract DNA as directed by the kit instructions. Qubit fluorometric quantification assays were employed to measure the DNA concentration and its purity in the samples.
Genotyping assay
Amplification and real-time PCR with sequence-specific primers were utilized to detect LDLR rs688 in all the investigated subjects. (Applied Biosystems3) StepOne PCR equipment was utilized to assess the real-time PCR allelic discrimination tests generated from TaqMan® SNP Genotyping assays (Catalog number: 4371353, supplied by Clinilab, Egypt).13
The 40-fold SNP Genotyping Assay was diluted with 1×TE buffer to yield a 20× working stock. The mixture was then vortexed, centrifuged, and separated into aliquots holding 20 μl in microcentrifuge tubes. After that, it was kept for regular use at −20°C. As advised by Applied Biosystems, one negative control (NTC) was added to each plate, and the total volume of each component required for each experiment was computed. A 20 μl reaction mix was prepared for each well, comprising 10 μl of the TaqMan Universal PCR Master Mix (2×), 1.0 μl of the SNP Genotyping Assay’s 20× working stock, 4.0 μl of DNase-free water, and 5 μl of the extracted DNA. The cycling conditions were the AmpliTaq Gold enzyme activation for 10 minutes at 95°C, denature for 15 seconds at 95°C, and anneal/extend for 1 minute at 60°C.
Allelic discrimination plate read and analysis
An endpoint plate read was carried out after PCR amplification utilizing an Applied Biosystem Real-Time PCR. Plotting fluorescence (Rn) values depending on the signals from each well were conducted by the Sequence Detection System (SDS) software using the fluorescence measurements taken during the plate read. The displayed fluorescence signals indicated the presence of specific alleles in each sample. Subsequently, an allelic discrimination plate read document was generated and configured in the SDS program to discern the alleles present.
Statistical methods
We used SPSS statistical software (version 26). The normality of the data was evaluated using the Kolmogorov–Smirnov test. The mean and standard deviation (SD) were computed to synthesize the numerical data. At the same time, the qualitative data were represented by using frequencies and percentages. The correlation among qualitative data was evaluated using the chi-square test. The Mann–Whitney test was utilized to evaluate the numerical data of the two groups. When comparing more than two groups, the Kruskal–Wallis test was applied; for pairwise comparisons, a post-hoc test was utilized. The odds ratio (OR) and its correlated 95% confidence intervals (CI) were calculated using logistic regression to evaluate the degree of risk. By employing stepwise logistic regression, the multivariate analysis incorporated all pertinent variables that influence the risk of CVD. A p-value, or probability, less than or equal to 0.05 was considered to indicate statistical significance.
Results
Genotyping of the LDLR rs688 in the studied groups revealed a significantly higher CT variant in CKD patients than among the controls (p = 0.006) [Table 1].
| N | CKD (n = 100) | Control (n = 100) | OR | 95% CI | p-value | |
|---|---|---|---|---|---|---|
| CC | 82 | 33 (33%) | 49 (49%) | 1 | ||
| CT | 83 | 43 (43%) | 40 (40%) | 3.2 | 1.4–7.5 | 0.006 |
| TT | 35 | 24 (24%) | 11(11%) | 2.0 | 0.9–4.7 | 0.096 |
CKD cases with CVD were significantly older than CKD cases without CVD (55.4 ± 10.8 years versus 49.7 ± 12.1 years; p = 0.008). There was a significantly greater percentage of hypertension among CKD cases with CVD (p-value = 0.026). CKD: chronic kidney disease; OR: Odds ratio; CI: confidence interval, CC: cytosine/cytosine genotype, TT: thymine/thymine genotype, CT: cytosine/thymine genotype
CKD patients with CVD showed a significant increase in the average cholesterol, triglyceride, LDL (p-value < 0.001), and years of dialysis (p-value = 0.027); however, a significantly lower HDL in CKD patients with CVD (p-value < 0.001) was observed. Gender, creatinine level, and eGFR demonstrated no significant differences between CVD patients and patients without CVD (p-value = 0.398, 0.828, and 0.051, respectively) [Table 2]. There was a significant relationship between the CT and TT genotypes and the presence of CVD in CKD patients, with OR (95% CI) 4.3 (1.6–11.8), (p = 0.004), and 7.6 (2.3–24.8), (p = 0.001), consecutively [Table 3].
| Characteristics | Total (n = 100) | CKD with CVD (n = 50) | CKD without CVD- (n = 50) | p-value |
|---|---|---|---|---|
| Age (years) | 52.3 ± 11.7 | 55.4 ± 10.8 | 49.7 ± 12.1 | 0.008 |
| Gender (%) | ||||
| Female | 34 (34%) | 19 (38%) | 15 (30%) | |
| Male | 66 (66%) | 31 (62%) | 35 (70%) | 0.398 |
| Hypertension (%) | ||||
| No | 28 (28%) | 9 (18%) | 19 (38%) | |
| Yes | 72 (72%) | 41 (82%) | 31 (62%) | 0.026 |
| Systolic blood pressure (mmHg) | 137.8 ± 15.6 | 142 ± 17 | 133 ± 13 | <0.001 |
| Diastolic blood pressure (mmHg) | 85.6 ± 12.6 | 90 ± 13 | 81 ± 11 | <0.001 |
| Cholesterol (mg/dL) | 232.4 ± 48.4 | 271 ± 34 | 194 ± 24 | <0.001 |
| Triglyceride (mg/dL) | 229.1 ± 75.2 | 270 ± 72 | 188 ± 53 | <0.001 |
| HDL (mg/dL) | 35.9 ± 5.6 | 32 ± 4 | 40 ± 5 | <0.001 |
| LDL (mg/dL) | 150.7 ± 43.7 | 184.9 ± 31.4 | 116.5 ± 22 | <0.001 |
| Creatinine (mg/dL) | 7.2 ± 1.1 | 7.3 ± 1.2 | 7.1 ± 1 | 0.828 |
| eGFR (ml/min/1.73m2) | 7.7 ± 1.9 | 7.4 ± 1.7 | 8.1 ± 2.1 | 0.051 |
| Years on dialysis | 7.4 ± 3.9 | 8.1 ± 3.6 | 6.8 ± 4.1 | 0.027 |
CKD: chronic kidney disease; CVD: cardiovascular disease; HDL: high-density lipoprotein; LDL: low-density lipoprotein; eGFR: estimated glomerular filtration rate.
| N | CKD cases | OR | 95% CI | p-value | ||
|---|---|---|---|---|---|---|
| KD with CVD (n = 50) | CKD without CVD (n = 50) | |||||
| CC | 33 | 8 (16%) | 25 (50%) | 1 | ||
| CT | 43 | 25 (50%) | 18 (36%) | 4.3 | 1.6–11.8 | 0.004 |
| TT | 24 | 17 (34%) | 7 (14%) | 7.6 | 2.3–24.8 | 0.001 |
CKD: chronic kidney disease; OR: Odds ratio; CI: confidence interval, CC: cytosine/cytosine genotype, TT: thymine/thymine genotype, CT: cytosine/thymine genotype
A multivariate logistic regression analysis was conducted to determine the relationship between the rs688 T variation and the risk of CVD in cases with CKD. The independent factors affecting the increased risk of developing CVD were hypertension and the T allele in both CT and TT [Table 4].
| P-value | OR | 95% CI | ||
|---|---|---|---|---|
| Lower | Upper | |||
| Hypertension (yes vs > no) | 0.002 | 6.2 | 1.9 | 19.6 |
| LDLR SNP rs688 | ||||
| CT vs ≥ CC | <0.001 | 9.8 | 2.9 | 33.2 |
| TT vs ≥ CC | <0.001 | 8.7 | 2.6 | 29.8 |
LDLR: low density lipoprotein receptor; CKD: chronic kidney disease; CVD: Cardiovascular disease; OR: Odds ratio; CI: confidence interval; SNP: single nucleotide polymorphism.
The results revealed a significant difference between gene allele and cholesterol with an overall p-value of < 0.001. Upon pairwise comparisons, a significantly lower cholesterol level was observed in individuals with the CC genotype compared to those with CT and TT genotypes (adjusted p-values = 0.015 and <0.001, respectively).
A significant difference was observed between gene alleles and triglyceride levels, with an overall p-value < 0.001. Subsequent pairwise comparisons revealed a significantly higher triglyceride level in individuals with the TT genotype than those with CC and CT genotypes (adjusted p-values < 0.001 and 0.041, respectively).
Furthermore, a significant difference was identified between gene alleles and HDL levels, yielding an overall p-value of 0.001. Further pairwise comparison revealed a significantly lower level of HDL in individuals with the TT genotype compared to those with the CC genotype (adjusted p-value < 0.001).
Moreover, a significant difference was observed between gene alleles and LDL levels, with an overall p-value of 0.002. Upon pairwise comparisons, a significantly lower LDL level was noted in individuals with the CC genotype compared to those with CT and TT genotypes (adjusted p-values = 0.022 and 0.003, respectively).
There was a significantly higher proportion of hypertension in individuals with TT and CC genotypes compared to those with the CT genotype [Table 5].
| Characteristics | CC (n = 33) | CT (n = 43) | TT (n = 24) | p-value |
|---|---|---|---|---|
| Age | 51.2 ± 12.8 | 51.2 ± 11.8 | 57 ± 9.5 | 0.068 |
| Years of dialysis | 7.4 ± 4.5 | 7.3 ± 3.7 | 7.7 ± 3.4 | 0.705 |
| Systolic blood pressure | 138.8 ± 14.0 | 138.5 ± 18.2 | 135.2 ± 12.9 | 0.773 |
| Diastolic blood pressure | 85.3 ± 11.7 | 84.3 ± 14.5 | 88.5 ± 10.1 | 0.413 |
| eGFR | 8.3 ± 1.9 | 7.4 ± 1.6 | 7.4 ± 2.1 | 0.063 |
| Gender | ||||
| Female | 8 (24.2%) | 16 (37.2%) | 10 (41.7%) | 0.329 |
| Male | 25 (75.8%) | 27 (62.8%) | 14 (58.3%) | |
| Hypertension | ||||
| No | 4 (12.1%) | 21 (48.8%) | 3 (12.5%) | <0.001 |
| Yes | 29 (87.9%) | 22 (51.2%) | 21 (87.5%) | |
| Cholesterol | 207.2 ± 46.2 | 238.1 ± 42.1 | 256.8 ± 47.8 | <0.001 |
| Triglyceride | 196.6 ± 68.3 | 228.4 ± 68.7 | 274.8 ± 74.6 | <0.001 |
| HDL | 38.5 ± 5.2 | 35.4 ± 5.4 | 32.9 ± 5.1 | <0.001 |
| LDL | 129.3 ± 39.6 | 156.9 ± 39.4 | 168.8 ± 46.1 | 0.002 |
| Creatinine | 6.9 ± 1.2 | 7.3 ± 1.1 | 7.2 ± 1.2 | 0.497 |
HDL: high-density lipoprotein; LDL: low-density lipoprotein; eGFR: estimated glomerular filtration rate. Bold indicates significant values.
Discussion
CVD is one of the most common consequences of CKD,14 which suggests the existence of multiple risk factors related to kidney disease.15,16 These risk factors include chronic inflammation and elevated oxidative stress.7
Elevated serum cholesterol, LDL concentration, and dyslipidemia are among the various factors that contribute to atherosclerosis and CVD in individuals with CKD. In hemodialysis patients, CVD may be partially attributed to acquired LDL receptor deficiency. Extensive research has demonstrated that genetic variables, such as genetic predisposition has a significant role in the development of CVD.17
In the current study, genotyping of rs688 in the LDLR gene revealed a significantly higher frequency of rs688 genetic CT variant in CKD cases than in the controls.
We compared the distribution of rs688 genetic polymorphism in the LDLR gene between CKD patients with CVD and CKD cases without CVD. The CT and TT genotypes were significantly greater in the CKD patients with CVD, respectively suggesting that rs688 genetic polymorphism may exert its influence in a dominating manner. Moreover, the rs688 a functional SNP in the LDLR gene that affects the efficiency of exon splicing, and raises the proportion of LDLR transcripts lacking exon 12 or exons 11 and 12.18 Exon-12-deficient LDLR and exon-11- and 12-deficient LDLR, results in alterations in the LDLR gene’s reading frame and the appearance of premature stop codons in exons 13 and 14.10
Therefore, it is anticipated that the translation of these LDLR isoforms would generate proteins that include the LDL-binding domain encoded by exons 1–7 but do not have the transmembrane domain represented via exons 16–17.18 Consequently, this will lead to elevated levels of both whole and LDL cholesterol.19
Our study’s findings are consistent with a Polish study that included 500 people regarded as healthy controls and 800 patients with CKD. According to their findings, the CVD subgroup had considerably higher frequencies of the T allele and TT genotype, with OR (95% CI) 3.4 (2.71–4.26, p < 0.0001) and 13.2 (7.87–22.09, p < 0.0001), respectively.12
The LDLR rs688 TT genotype exhibited a robust association with an increased risk of CVD in Indian patients (OR = 3.0;95% CI = 1.43 × 6.2; p = 0.003). Similarly, the LDLR rs688 T allele demonstrated a significant association with a higher likelihood of CVD (OR = 0.74;95% CI = 1.57–0.97; p = 0.03) compared to the C allele. This study involved a cohort of 400 individuals from India. These results align with the outcomes of our investigation.10
A recent study has shown a correlation between LDLR gene variations and cardiovascular disease. This association was particularly pronounced among the rs688 TT genotype male carriers. The odds ratio for hyperlipidemia was significant in those with the TT genotype (OR = 0.5, CI: 0.29–0.907) but not in those with the CT or CC genotypes.5
There may be a connection between LDLR polymorphism and cardiovascular disease through mechanisms other than the lipoprotein metabolism cascade. The rs688 polymorphism in the LDLR gene appears to be one of the possible risk factors in the development of cardiovascular disease in people with CKD, even though a single polymorphism has little effect on prevalent illnesses.
The present investigation exhibits certain limitations. Originally, this study was conducted at a single center. In addition, specific comorbidities observed in CKD patients may be a confounding variable.
Conclusion
The detection of SNP rs688 C>Tin LDLR genes demonstrated a significant correlation between the CT and TT genotypes and the occurrence of cardiovascular disease in CKD cases. The potential utilization of this SNP as a predisposing genetic marker for CVD in CKD cases is suggested.
Conflicts of interest
There are no conflicts of interest.
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