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Original Article
161 (
6
); 727-737
doi:
10.25259/IJMR_905_2024

Relationship between vitamin D deficiency, vitamin D receptor gene variants, & the risk of coronary artery disease among South Indians: A case-control study

Department of Pathology & Faculty of Medicine, Sri Ramachandra Institute of Higher Education & Research, Chennai, Tamil Nadu, India
School of Allied Health Sciences, Sree Balaji Medical College and Hospital, Chennai, Tamil Nadu, India
Department of Cardiology, Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, India
Department of Pathology, Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, Karnataka, India
Department of Integrative Medical Research, PES University Institute of Medical Sciences and Research, Bengaluru, Karnataka, India
Department of Neurochemistry, National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, India

For correspondence: Dr S R Kalpana, Department of Pathology, Sri Jayadeva Institute of Cardiovascular Sciences & Research, Bengaluru 560 041, Karnataka, India e-mail: kalpanasr@gmail.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

Abstract

Background & objectives

Vitamin D deficiency (VDD) and variations in the vitamin D receptor (VDR) gene are implicated in the pathogenesis of coronary artery disease (CAD). This study investigated the association between VDD, VDR gene variants (ApaI, BsmI, FokI, and TaqI), and CAD risk among South Indians.

Methods

The case-control study was conducted in 250 CAD patients and 260 matched controls. Serum vitamin D levels were measured by ELISA. Genotyping for VDR ApaI (A>C, rs7975232), BsmI (A>G, rs1544410), FokI (T>C, rs2228570), and TaqI (C>T, rs731236) was performed using the polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) method.

Results

VDD was significantly higher among CAD patients (90%) than in controls (63%). Individuals with vitamin D levels <20 ng/ml were 5.7 times more likely to have CAD when compared to those with vitamin D levels ≥ 20 ng/ml (P<0.001, OR=5.74, 95% CI=2.92-11.30). No correlation was observed between vitamin D levels and CAD risk factors, systolic and diastolic blood pressure (r=-0.105, P=0.095, r=-0.049, P=0.437), and blood glucose (r=-0.067, P=0.304). A trend for negative correlation of vitamin D levels with cholesterol (r=-0.112, P=0.094) and triglyceride levels (r=-0.133, P=0.061) was observed. The VDR TaqI variant showed significant association with reduced CAD risk in the overall analysis (Model II, OR=0.60, 95% CI=0.39-0.90, P=0.016). The FokI variant was associated with an increased risk of CAD in males (Model III, OR=5.9, 95% CI=2.09-16.85, P=0.001). However, combined analysis of VDD and VDR gene variants indicated that neither FokI ‘ff’ (P=0.145) nor TaqI ‘tt’ (P=0.138) genotypes significantly altered CAD risk in vitamin D-deficient subjects.

Interpretation & conclusions

The findings of this study suggested that VDD was significantly higher among the CAD patients and increases the risk of CAD by 5.7-fold.This study revealed the differing roles of VDR gene variants in CAD susceptibility and the influence of gender and other covariates.

Keywords

Coronary artery disease
genetic association
Indian population
VDR variants
vitamin D receptor
vitamin D deficiency

Cardiovascular diseases (CVDs) have become one of the leading causes of mortality and morbidity in India, with coronary artery disease (CAD) accounting for 26.9 per cent of all medically certified deaths, with disorders of the circulatory system1. Indians are particularly susceptible to premature CAD, leading to acute myocardial infarction (AMI) at an earlier age compared to the Western population. CAD affects Indians a decade earlier in their most productive years of life. The complex interactions of both biological and social determinants are considered to be responsible for this higher burden in India2. Vitamin D deficiency (VDD) has been implicated as a major risk factor for CAD. A 60 per cent higher risk of heart disease was observed in patients with vitamin D levels below 15 ng/ml in the Framingham study3. Further, an increased cardiovascular risk with a hazard ratio of 1.5 in vitamin D-deficient individuals was reported in the Framingham offspring study4. These findings highlight the importance of considering VDD as a potential treatable cause of CAD.

VDD, as well as insufficiency, have been said to be a pandemic affecting 50 per cent of the population globally5. The prevalence of VDD in India is reported to range from 50-94 per cent by various studies on the Indian population over the last decade6, with only one study showing 34.5 per cent7. Vitamin D plays an essential role in the regulation of cell proliferation, differentiation, apoptosis, and modulation of immune response. It has been increasingly recognised that a deficiency in vitamin D levels increases the risk of chronic diseases like diabetes, hypertension, dyslipidaemia, cerebral or cardiovascular ailments, and chronic kidney disease. Studies have also found an association between VDD and the severity of CAD. Therefore, VDD is considered an independent risk factor for CAD.

The functioning of the active form of vitamin D is mediated through the vitamin D receptor (VDR), which is a ligand-dependent receptor. These receptors are found in cardiovascular cells, including cardiomyocytes, vascular smooth muscle cells, endothelial cells, immune cells, and also platelets8. The VDR gene, which encodes the VDR receptor, influences many regulatory genes that are of particular importance in CVD and directly modulates gene transcription. It has been suggested that VDR variants could be a better marker compared to traditional risk factors for earlier detection of CAD, which can aid in personalised treatment9.

There is a paucity of data on the association of hypovitaminosis D, VDR gene variants, and CAD risk in the Indian population. Existing studies often have small sample sizes, limiting their statistical power and generalisability. Therefore, we conducted this study to investigate the relationship between VDD, VDR variants (BsmI, ApaI, TaqI, and FokI), and CAD risk and severity in South Indian population.

Materials & Methods

This case-control study conducted between March 2020 and December 2021 was conducted by the department of Pathology, Sri Jayadeva Institute of Cardiovascular Sciences and Research (SJICR), Bengaluru, Karnataka, India, after obtaining clearance from the Institutional Medical Ethics Committee. Written informed consent for using samples for research was obtained from all the individuals before sampling. A detailed proforma with demographic variables and clinical details was used to document data for all study participants. Total 250 CAD patients who presented at SJICR, Bengaluru, were recruited in this study. Patients above 18 yr of age, with a clinical diagnosis of CAD with echocardiographic and ECG evidence, undergoing coronary angiography (CAG) were included in the study. The study population comprised both diabetic and non-diabetic patients. Terminally ill patients, those with hepatic/renal failures/malignancy, patients reactive to HIV, HBsAg, HCV & VDRL, and those on vitamin D or calcium supplements were excluded. The control group (n=260) was recruited from healthy volunteers who were attending to the hospital patients and blood donors during the study period. Individuals with any history of CVDs and those taking calcium or vitamin D supplements were excluded.

Sample collection and methodology

Venous blood (8 ml) was collected from the study participants in tubes containing EDTA and plain vials without an anticoagulant. The serum was separated from blood collected in plain vials and used for clinical biochemistry analysis, and a part of the serum sample was stored at -80°C for ELISA analysis. DNA was isolated from EDTA blood using the standard protocol and stored for molecular studies at -80°C.

Estimation of serum 25(OH) vitamin D [25(OH)D] levels

Serum 25(OH)D was measured by enzyme immunoassay (ELISA) using commercial kits (Cayman Chemical, MI, USA) and quality control materials provided by the manufacturer. The intra- and inter-assay coefficients of variation were 3.65 per cent and 4.8 per cent, respectively.

Multiplexing PCR genotyping of VDR variants - TaqI (C>T, rs731236), BsmI (A>G, rs1544410), FokI (T>C, rs2228570) and ApaI (A>C, rs7975232)

Genomic DNA from human peripheral blood samples was isolated using a QiAamp DNA isolation kit (Qiagen, Germany) and was quantified using NanoDrop 2000 (Thermo Fisher Scientific, MA, USA). PCR for VDR variants (Multiplex PCR I - TaqI and BsmI; Multiplex PCR II – FokI and ApaI) was carried out with 2U of Taq DNA Polymerase (Solis Biodyne, Tartu) and supplied buffer under the following conditions: 94° C for 6 min, followed by 35 cycles of 94°C for 30 sec, 60°C for 30 sec, and 72°C for 40 sec, followed by a 5 min final extension at 72°C. The fragments were then digested with restriction enzymes and resolved in 2.5 per cent agarose gels.

Statistical analysis

IBM SPSS statistics v.21 and GraphPad Prism v.9. (Chicago, IL, USA) were used for analysis. The sample size was calculated using OpenEpi (Open-Source Epidemiologic Statistics for Public Health, Version, available at www.OpenEpi.com ). Calculations were based on a two-sided confidence level of 95 per cent, a statistical power of 80 per cent, and an equal case-to-control ratio (1:1). The input parameters were obtained by combining the prevalence of VDD and VDR polymorphisms from a previous study10. The prevalence of VDD was 52 per cent in cases and 36 per cent in controls, and the minor allele frequencies (MAF) for VDR polymorphisms were: FokI (20.2% vs. 26.17%), BsmI (30% vs. 26.64%), ApaI (39.17% vs. 36.45%), and TaqI (56.67% vs. 59.81%). By applying a weighted prevalence approach, the estimated exposure prevalence in controls (P₀) was 36.88 per cent, and in cases (P₁) was 44.26 per cent. OpenEpi calculations estimated a minimum sample size per group of 692 (Kelsey), 691 (Fleiss), and 718 (Fleiss with continuity correction), a total of 1382–1436 participants. However, due to the feasibility of recruitment and other studies conducted with comparable sample sizes11,12, the sample size of 510 participants (250 cases, 260 controls) was determined to be adequate to retain statistical power. The differences in baseline characteristics, such as gender, hypertension, diabetes, smoking, and alcohol use, between patients and healthy controls were assessed using the chi-squared test. Age distribution was compared using the Mann-Whitney U test. The correlation analysis between vitamin D levels and CAD risk factors, including blood pressure, blood glucose, cholesterol, and triglyceride levels, was performed using the Spearman rank correlation coefficient (r). Genotypic frequencies of variants were tested for Hardy Weinberg Equilibrium (HWE) by chi-squared analysis. The frequency distribution of the alleles was compared between patient and control groups using the chi-squared test. Logistic regression analysis was used to analyse the association between VDR variants and CAD risk. Covariates included age, gender, the habit of smoking or drinking, and presence of diabetes mellitus and/or hypertension. Linkage disequilibrium (LD) analysis of VDR variants was conducted using Haploview 4.2 software available at www.broadinstitute.org/haploview/haploview . P<0.05 were considered statistically significant in all the analysis.

Results

Demographic and clinical characteristics of the study participants

A total of 250 CAD patients (206 males and 44 females) and 260 healthy controls (210 males and 50 females) were included in this study. The distribution of age between patients and control subjects was 47 (45-50) yr and 47 (40-52) yr (P=0.062), respectively. The demographic and clinical characteristics of the subjects have been presented in table I.

Table I. Demographic, clinical characteristics, and serum 25 (OH) D levels of the study participants
Parameters Controls Cases P value
n=260 n=250
Age in yr, median (IQR) 47 (45-50) 47 (40-52) 0.062
Sex, male/ female 210/50 206/44 0.649
Smokers, n (%) 24 (9.23) 143 (57.2) <0.001
Alcohol, n (%) 26 (10) 89 (35.6) <0.001
Hypertension, n (%) 45 (17.30) 113 (45.2) <0.001
Diabetes, n (%) 29 (11.15) 110 (44) <0.001
Vitamin D status
Serum 25 (OH)D, ng/ml, Mean ± SE 18.12 ±0.62 12.05±0.44 < 0.001
≥30 ng/ml, n % 31 (11.92) 10 (4.00) <0.001
20-30 ng/ml, n % 65 (24.50) 15 (6.00) < 0.001
< 20 ng/ml, n % 164 (63.07) 225 (90.00) < 0.001

n, the total number of subjects in each group; IQR, inter quartile range; SE, standard error; A P<0.05 is considered significant

Serum 25 (OH)D levels in patients and controls

The mean serum 25(OH)D levels were observed to be lower in patients (12.05±0.4 ng/ml) compared to controls (18.12±0.6 ng/ml). VDD (<20 ng/ml) was significantly more common in cases than in controls (P<0.001). Conversely, vitamin D sufficiency ≥30 ng/ml was more prevalent in controls compared to patients (11.92 vs. 4%; P<0.001) (Table I).

Partial correlation analysis

Partial correlation analysis was done to investigate the relationship between vitamin D levels and case-controls while adjusting for confounders such as age, gender, hypertension, diabetes, smoking, and alcohol intake. The unadjusted relationship between vitamin D levels and case-control status was significant (r= -0.304, P<0.001). After adjusting for confounders, the association was still statistically significant but slightly lower (r= -0.256, P<0.001). Among the confounding factors, hypertension (r = -0.102, P=0.015), diabetes (r= -0.087, P=0.045), and smoking (r = -0.092, P=0.035) were significantly negatively correlated with vitamin D levels (Table II).

Table II. Partial correlation analysis
Variable Vitamin D levels (Unadjusted r) P value (Unadjusted) Vitamin D levels (Adjusted r) P value (Adjusted)
Cases vs. Controls -0.304 <0.001 -0.256 <0.001
Age 0.048 0.278 0.035 0.41
Gender -0.031 0.485 -0.028 0.51
Hypertension -0.129 0.003 -0.102 0.015
Diabetes -0.119 0.007 -0.087 0.045
Smoking -0.107 0.016 -0.092 0.035
Alcohol -0.07 0.113 -0.065 0.15

r, Pearson correlation coefficient; A P<0.05 is considered significant

Impact of vitamin D levels on CAD risk

We then examined the relationship between vitamin D levels and the risk of CAD by calculating the odds ratio. Our analysis revealed a strong and significant association between low vitamin D levels and an increased risk of CAD, even after adjusting for hypertension, diabetes, smoking, and alcohol. Individuals with vitamin D levels <20 ng/ml are approximately 5.7 times more likely to have CAD compared to those with vitamin D levels ≥20 ng/ml (P<0.001, OR=5.74).

Correlation of vitamin D levels and CAD risk factors

Vitamin D plays a crucial role in regulating blood pressure and blood glucose levels, which are significant risk factors for CAD13. Hence, we did a correlation analysis of vitamin D levels and CAD risk factors (blood pressure and blood glucose) for cases and controls. However, our analysis did not reveal any significant correlation between vitamin D levels and either blood pressure or blood glucose levels in cases and controls (Fig. 1A-C for cases; Fig. 2A-C for controls).

The image presents three scatter plots (A, B, and C) showing the relationships between vitamin D levels (ng/ml) and CAD risk factors: Systolic blood pressure (Plot A), Diastolic blood pressure (Plot B), and Blood glucose levels (Plot C). The correlation coefficients (r) and P values for each relationship are provided. A P value <0.05 is considered significant.
Fig. 1.
The image presents three scatter plots (A, B, and C) showing the relationships between vitamin D levels (ng/ml) and CAD risk factors: Systolic blood pressure (Plot A), Diastolic blood pressure (Plot B), and Blood glucose levels (Plot C). The correlation coefficients (r) and P values for each relationship are provided. A P value <0.05 is considered significant.
The image presents six scatter plots (A to F) showing the relationship between vitamin D levels (ng/ml) and various blood lipid parameters: Total Cholesterol (Plot A), Triglycerides (Plot B), VLDL (Plot C), HDL (Plot D), LDL (Plot E), and the TC/HDL ratio (Plot F). The correlation coefficients (r) and P values for each relationship are provided. A P value <0.05 is considered significant.
Fig. 2.
The image presents six scatter plots (A to F) showing the relationship between vitamin D levels (ng/ml) and various blood lipid parameters: Total Cholesterol (Plot A), Triglycerides (Plot B), VLDL (Plot C), HDL (Plot D), LDL (Plot E), and the TC/HDL ratio (Plot F). The correlation coefficients (r) and P values for each relationship are provided. A P value <0.05 is considered significant.

Correlation analysis between vitamin D levels and blood lipid parameters

Vitamin D plays a significant role in lipid metabolism, influencing cholesterol synthesis and the levels of total cholesterol, LDL, and HDL. This relationship is crucial since elevated LDL cholesterol and triglycerides contribute to atherosclerosis, a major factor in CAD14. Hence, we did a correlation analysis. Plot ‘D’ (Fig. 1) shows a weak negative correlation between vitamin D levels and total cholesterol (r = -0.112, P=0.094), though this relationship is not statistically significant. Plot ‘E’ (Fig. 1) also showed a weak negative correlation between vitamin D levels and triglycerides (r = -0.133, P=0.061). Plot ‘F’ (Fig. 1) shows a near-zero correlation between vitamin D levels and HDL (r = 0.004, P=0.954). Similarly, plot ‘G’ (Fig. 1) shows a near-zero correlation between vitamin D levels and LDL (r = -0.001, P=0.984). The ‘H’ plot (Fig. 1) shows a weaker negative correlation between vitamin D levels and VLDL (r = -0.044, P=0.530). The ‘I’ plot (Fig. 1) shows a weak negative correlation between vitamin D levels and the TC/HDL ratio (r = -0.099, P=0.164). The correlation analysis of controls revealed no significant correlation between vitamin D levels and blood lipid parameters, including total cholesterol, triglycerides, HDL, LDL, VLDL, and the TC/HDL ratio. The correlation coefficients (r-values) for all parameters were close to zero, and the P values exceeded 0.05, indicating a lack of statistical significance (Fig. 2D-I).

Allelic frequency of VDR ApaI, FokI, TaqI, and BsmI variants

The distributions of all four VDR variants were examined for Hardy-Weinberg Equilibrium. No significant deviations were observed for ApaI (P=0.880), TaqI (P=0.102), and BsmI (P=0.175); however, FokI showed a deviation from HWE (P=0.045). Overall, the allelic frequency of ApaI, FokI, and BsmI genes was not significantly different in cases and controls. However, there was a significant difference in allelic distribution in the TaqI variant between cases and controls (P=0.005). Additionally, when the samples were analysed by gender, there was a significant difference in the distribution of the TaqI variant (P=0.008) and the FokI variant (P=0.043) in males compared to controls. The allele frequencies in the study groups have been shown in table III.

Table III. Allelic frequency of VDR ApaI, FokI, TaqI, and BsmI variants
Genotype Allelic frequency
P value OR 95% CI
Controls
Cases
VDR ApaI A a A a
Overall 306 (58.8) 214 (41.2) 294 (57.6) 226 (42.4) >0.999 1.02 0.78-1.28
0.99 0.77-1.28
Males 243 (57.8) 177 (42.2) 235 (53.2) 177 (46.7) 0.833 1.03 0.78-1.36
0.96 0.73-1.27
Females 63 (63.0) 37 (37.0) 59 (66.6) 29 (33.3) 0.646 0.83 0.45-1.52
1.19 0.65-2.18
VDR FokI F f F f
Overall, n (%) 400 (76.9) 120 (23.1) 367 (73.5) 133 (26.4) 0.217 1.20 0.90-1.60
0.82 0.62-1.10
Males, n (%) 331 (78.8) 89 (21.2) 299 (72.9) 113 (27.1) 0.043 1.40 1.02-1.93
0.71 0.51-0.97
Females, n (%) 69 (69.0) 31 (31.0) 59 (74.7) 29 (25.3) 0.25 0.65 0.34-1.25
1.52 0.72-2.93
VDR TaqI T t T t
Overall, n (%) 349 (67.1) 171 (32.8) 375 (75.0) 125 (25.0) 0.005 0.68 0.51-0.89
1.47 1.11-1.93
Males, n (%) 286 (68.0) 134 (32.0) 315 (76.4) 197 (23.6) 0.008 0.65 0.48-0.89
1.52 1.12-2.06
Females, n (%) 63 (63.0) 37 (37.0) 60 (68.1) 28 (31.9) 0.539 0.79 0.43-1.45
1.25 0.68-2.30
VDR BsmI B b B b
Overall, n (%) 306 (58.8) 214 (41.2) 278 (55.6) 222 (44.5) 0.311 1.14 0.89-1.46
0.87 0.68-1.12
Males, n (%) 249 (59.9) 171 (40.1) 224 (54.3) 188 (45.6) 0.161 1.22 0.92-1.60
0.81 0.62-1.07
Females, n (%) 57 (57.0) 43 (43.0) 54 (61.3) 34 (38.6) 0.556 0.83 0.46-1.49
1.19 0.66-2.14

n, Number of alleles; % percentage of allele frequency; ‘A’ represents the major allele frequency of the ApaI variant; ‘a’ represents the alternate allele frequency of the ApaI variant; ‘F’ represents the major allele frequency of the FokI variant; ‘f’ represents the alternate allele frequency of the FokI variant; ‘T’ represents the major allele frequency of the TaqI variant; ‘t’ represents the alternate allele frequency of the TaqI variant; ‘B’ represents the major allele frequency of the BsmI variant; ‘b’ represents the alternate allele frequency of the BsmI variant OR, odds ratio; CI, confidence interval; A P<0.05 is considered significant

Odds ratio as estimates of risk for CAD in carriers of the VDR gene variants

VDR TaqI variant

To estimate the odds ratios, we created three models with different levels of adjustments. ‘Model I’ was adjusted for age, ensuring the results accounted for differences in age. ‘Model II’ added adjustments for smoking and alcohol use, as these lifestyle factors can affect cardiovascular risk. ‘Model III’ included further adjustments for hypertension and diabetes, which are common conditions linked to heart disease. Our analysis revealed that, under the dominant inheritance model (Tt + tt vs. TT), the TaqI variant has a potential protective association (Model I, OR=0.62, 95% CI=0.43-0.88, P=0.008). This association remained significant even after adjusting the odds ratio for age, smoking, and alcohol (Model II, OR=0.60, 95% CI=0.39-0.90). However, upon additional adjustment for hypertension and diabetes, the associations abrogated (Model III, OR=0.69, 95% CI=0.43-1.09, P=0.119). Upon gender stratification, the protective association persisted significantly in males initially (Model I, OR=0.60, 95% CI=0.37-0.99, P=0.045); however, abrogated after adjusting for confounders. In females, the association persisted (Model II, OR=0.42, 95% CI=0.18-0.98, P=0.045), even after adjusting for age, smoking, and alcohol (Supplementary table).

Supplementary Table

VDR BsmI variant

There was no statistically significant difference observed in the distribution of alleles and genotypes of the BsmI gene variant between cases and controls, even when stratified according to gender (Supplementary table).

VDR ApaI variant

Logistic regression analysis did not indicate any association between the ApaI variant and CAD, even when stratified according to gender when analysed under various covariate adjustment models (Supplementary table).

VDR FokI variant

Overall logistic regression analysis did not reveal any significant association. However, in the recessive model of inheritance, the ‘f’ allele was significantly associated with CAD even after adjusting for the vascular risk factors (Model III, OR= 2.93, 95% CI=1.19-7.25, P= 0.019). Upon gender stratification, we found that the ‘f’ allele can significantly increase the risk of CAD in males by 5.9 folds (Model III, OR= 5.9, 95% CI= 2.09-16.8, P=0.001) even after adjusting the OR with confounders. In women, there was no significant association of the FokI gene variant with the risk for CAD (Supplementary table).

Impact of VDR gene variants (TaqI and FokI) in the context of VDD

To determine whether the protective and risk effects of TaqI and FokI variants persist in the background of VDD, the combined effects of VDD and FokI and TaqI were estimated as a measure of the odds ratio. The logistic regression analysis for the FokI variant showed that individuals with the ‘ff’ genotype did not have a significantly increased risk compared to those with the ‘FF’ or ‘Ff’ genotypes (OR= 0.51, 95% CI= 0.20-1.25, P=0.145). Similarly, the logistic regression analysis for the TaqI variant indicated that individuals with the ‘tt’ genotype did not have a significantly increased risk compared to those with the ‘TT’ or ‘Tt’ genotypes (OR=1.62, 95% CI=0.85-3.12, P=0.138). The results have been summarised in supplementary table.

Linkage disequilibrium analysis of VDR variants

The comparison of linkage disequilibrium (LD)patterns between cases and controls revealed a distinct difference in the genetic correlations among the four SNPs analysed (TaqI, BsmI, ApaI, and FokI) within a 34 kb genomic block. The case group demonstrated a higher LD between ApaI (rs7975232) and FokI (rs2228570), r2 = 92 and between BsmI (rs1544410) and ApaI, r2 = 87. Moderate LD is also observed between TaqI (rs731236) and ApaI (r2 = 47) and between TaqI and BsmI (r2 = 41). The deep red colour in the LD plot for cases underlines the strong linkage among certain SNP pairs, indicating the existence of a tightly linked haplotype in affected individuals (Fig. 3A). In contrast, the control group exhibited markedly lower LD values across most SNP pairs, with the strongest LD observed between ApaI and FokI (r2 = 54), which is reduced compared to the case group. The values of LD between other pairs, such as TaqI and BsmI or TaqI and ApaI, are minimal and between r2=1 to 4. The overall light intensity of the control LD plot reflects that the genetic correlations are relatively weak, which suggests a lack of closely linked haplotypes in non-affected individuals (Fig. 3B).

Linkage disequilibrium (LD) plot: ‘A’ represents the LD pattern observed in cases; ‘B’ represents LD pattern observed in controls. The deep red colour in the LD plot underlines the strong linkage, whereas the light intensity of the LD plot reflects the weak linkage.
Fig. 3.
Linkage disequilibrium (LD) plot: ‘A’ represents the LD pattern observed in cases; ‘B’ represents LD pattern observed in controls. The deep red colour in the LD plot underlines the strong linkage, whereas the light intensity of the LD plot reflects the weak linkage.

Discussion

This is a case-control study carried out on CAD patients in a tertiary cardiac centre in Southern India. We studied the prevalence and association between VDD and VDR gene variants with various risk factors for CAD and its severity.

Although both controls and cases had VDD in our study, the mean vitamin D level was significantly lower in patients. Also, 90 per cent of patients were deficient compared to 63 per cent of controls. We also found that VDD was associated with 5.7-fold increased risk of CAD. These findings suggest a strong association between VDD and CAD risk in our study group. In a meta-analysis of 44,717 participants across 65 studies from five South Asian countries, including India, Pakistan, Bangladesh, Nepal, and Sri Lanka, the prevalence of VDD was 67 per cent among Indians. The average level of vitamin D ranged from 4.7 to 32 ng/ml, with a weighted mean of 19.15 ng/ml15. The meta-analysis by Yan et al9, which included 13studies from China, Iran, Brazil, Egypt, Poland, Croatia, and Germany, concluded that low plasma vitamin D levels are associated with CAD9. A study from the Northern part of India on first incident acute myocardial infarction reported a higher prevalence of VDD and insufficiency and much lower mean values of vitamin D (98.3% of the cases had below normal values with a mean level of 6 ng/ml; 95.8% of controls had below normal values with a mean of 11.1 ng/ml). A 4.5-fold risk of myocardial infarction was also noted among individuals with severe (<10 ng/ml) VDD16. Collectively, these findings suggest that low vitamin D levels may be a significant risk factor for CAD, particularly in populations with a high prevalence of VDD. Our partial correlation analysis indicated that differences in vitamin D levels between cases and controls remain significant even after adjusting for key confounders, underscoring the potential role of vitamin D deficiency in CAD. Vitamin D plays a crucial role in regulating blood pressure and blood glucose levels, which are significant risk factors for CAD17,18. Our correlation analysis suggests that there are weak negative correlations between vitamin D levels and CAD risk factors, but none of these relationships are statistically significant. In a previous study from India, higher levels of vitamin D have been associated with lower incidences of CAD8, but our findings do not support a strong correlation between vitamin D levels and CAD risk factors. VDD can affect lipid profiles by influencing low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, and total cholesterol levels in CAD patients19,20. Additionally, VDD may impact blood sugar levels and the TC/HDL ratio21. Consistent with the previous findings our analysis revealed a trend for a negative correlation of vitamin D levels with cholesterol and triglyceride levels. However, other variables did not correlate. These findings suggest that maintaining adequate levels of vitamin D may have a positive impact on lipid profiles in CAD patients.

There are conflicting findings among various studies on VDR variants and their association with CAD22,23. In the present study, the allelic frequency of the TaqI variant was significantly different between cases and controls. Also, a significant difference was found in the allelic distribution of the FokI variant in males with VDD compared to controls. Under the dominant inheritance model (Tt + tt vs TT), the TaqI variant suggested a potential protective association with an odds ratio of 0.6. This association remained significant even after adjusting the odds ratio for age, smoking, and alcohol. Upon gender stratification, the protective association persisted significantly in both males and females, even after adjusting for age, smoking, and alcohol. These findings suggest that the protective association of the ‘t’ allele against CAD is consistent across genders and remains significant after controlling for potential confounders.

The presence of the ‘ff’ genotype of Fok I conferred a 5.9-fold risk of CAD in our cohort of males. In contrast, a previous study on 40 South Indian CAD subjects did not show any significant association of CAD with the FokI variant24. This discrepancy in the results may be due to differences in sample size, genetic heterogeneity within the population, or variations in environmental factors that were not accounted for in either study. Hence, it is important to consider other genetic variations that may contribute to the development of CAD. Also, a case-control study from China did not find any significant association of FokI (rs2228570) and BsmI (rs1544410) with CAD25.A recent meta-analysis9 evaluated thirteen studies using trial sequential analysis (TSA) for the association of four common VDR polymorphisms for CAD susceptibility. In their analysis, on stratification by race, the White people were found to have an increased CAD risk in BsmI (b’ allele), FokI (‘f’allele), and TaqI (t allele) polymorphisms and a protective association of ‘a’ allele of ApaI; Asians exhibited only 60 per cent risk in ‘ff’ genotype of FokI and no association with TaqI and BsmI polymorphisms9.The present study correlates with these findings except for TaqI polymorphism, which has shown a protective association in our study. A meta-analysis of 158 studies has reported an increased risk of CAD in patients with TaqI polymorphism and also suggested a possible protective role of FokI polymorphism26. Their observations are in total contrast to our study findings. Overall, our findings suggest that the VDR TaqI variant may play a role in reducing the risk of CAD, regardless of gender. However, the VDR FokI variant conferred a risk of CAD in our cohort of males. These findings indicate that genetic variations in the VDR gene may have differing effects on CAD risk based on gender.

Overall, the analysis of VDR gene variants revealed distinct associations with CAD under specific conditions. The TaqI variant demonstrated a potential protective effect under the dominant inheritance model, with the association remaining significant even after adjusting for age, smoking, and alcohol. Gender stratification showed that the protective effect persisted in both males and females, even after accounting for these covariates. In contrast, the BsmI variant showed no significant association with CAD, irrespective of gender or covariate adjustments. Similarly, the ApaI variant did not exhibit any association with CAD across various models of analysis, including gender stratification. On the other hand, the FokI variant displayed a significant association in the recessive model, where the ‘f’ allele notably increased the risk of CAD, particularly in males, with a marked 5.9-fold higher risk even after adjusting for vascular risk factors. This comparison highlights the differing roles of VDR gene variants in CAD susceptibility and the influence of gender and other covariates on these associations.

Then, we were interested in knowing whether TaqI and FokI variants maintain their protective and risk effects under the context of VDD. A measure of the odds ratio was calculated to assess the combined effects of VDD and VDR gene variants FokI and TaqI. We found that neither FokI ‘ff’ nor the TaqI ‘tt’ genotype significantly alters the risk in the context of VDD entirely. The lack of significance suggests that multiple factors likely contribute to the outcome. Firstly, there may be a threshold effect for vitamin D levels below which the impact of VDR gene variants becomes negligible. Secondly, if VDD is severe enough, the relative contribution of the VDR variants might be overshadowed by the overall deficiency. Biological systems often have compensatory mechanisms that can mitigate the effects of genetic variations. For example, individuals with ‘ff’ or ‘tt’ genotypes might have other compensatory pathways that help maintain some level of VDR activity or vitamin D metabolism.

The comparison of LD patterns between cases and controls revealed a distinct difference in the genetic correlations among the four SNPs analysed (TaqI, BsmI, ApaI, and FokI). These differences in LD patterns suggest that certain SNPs, particularly ApaI and FokI, may be associated with the cases. In contrast, the weaker LD in controls implies a more random distribution of alleles. The observed patterns warrant further investigation to explore the functional roles of these SNPs and their contribution to disease susceptibility.

Although our study focused on VDR variants, we recognise the importance of other genes involved in vitamin D metabolism, such as CYP27B1, which encodes the enzyme responsible for converting 25-hydroxyvitamin D into its active form, 1,25-dihydroxyvitamin D (calcitriol)27. Variants in CYP27B1 can lead to reduced activity of this enzyme, impairing the activation of vitamin D even when precursor levels are normal28. Loss-of-function mutations in CYP27B1 have been associated with conditions such as vitamin D-dependent rickets type 1 (VDDR1), characterised by bone deformities and growth retardation due to insufficient calcitriol levels29,30. Including the analysis of CYP27B1 variants in future studies could provide a more comprehensive understanding of vitamin D metabolism and its role in CAD, particularly when VDR function is normal but calcitriol synthesis may be disrupted.

Some limitations of this study were that it did not comprehensively account for environmental and dietary factors, such as diet, sun exposure, and lifestyle, which can significantly influence vitamin D levels and CAD risk. Furthermore, the role of other genetic factors in conjunction with VDR variants, which might provide a more comprehensive understanding of CAD development and progression were not explored.

In conclusion, while our study provides valuable insights into the association between VDR gene variants and CAD risk, more research is necessary to fully comprehend the underlying mechanisms and potential treatment options.

Financial support & sponsorship

Rajiv Gandhi University of Health Sciences, Bengaluru, Karnataka, India (RGUHS unique ID 19MED054 dt25/01/2020).

Conflicts of Interest

None.

Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation

The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.

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