ASSOCIATION OF THE APOLIPOPROTEIN A-I GENE POLYMORPHISMS WITH CARDIOVASCULAR DISEASE RISK FACTORS AND ATHEROGENIC INDICES IN PATIENTS FROM ASSAM, NORTHEAST INDIA
Bora K1,2,*, Pathak MS2, Borah P3, Hussain Md.I.3, Das D4
*Corresponding Author: : Dr. Kaustubh Bora, Regional Medical Research Centre, Northeast Region, Indian Council of Medical Research (ICMR), P.O. Box 105, Dibrugarh-786001, Assam, India. Tel: +91-943-557-2062. Fax: +91-364-253-8003. E-mail: kaustubhbora1@gmail.com
page: 59

MATERIALS AND METHODS

Study Subjects. Individuals undergoing health check-ups at the Guwahati Medical College and Hospital, Assam, India, were screened clinically and with the help of available investigation reports. Information on past medical history, drug history, dietary habits (vegetarian or non-vegetarian), and current smoking and alcohol use status was also obtained. We screened 649 individuals, from which 200 subjects (100 cases and 100 controls) of either sex, who were native to Assam, were finally selected for a case-control study on the basis of the following eligibility criteria. Subjects enrolled in the case group had decreased HDL-C dyslipidemia (defined as HDL-C levels <40.0 mg/ dL) [30]. Individuals with confounding conditions known to decrease the levels of HDL-C, such as diabetes mellitus/ hyperglycemia, liver diseases, thyroid disorders and other endocrinal disorders, acute infections and inflammatory conditions, using medications affecting serum lipids (such as β-blockers, statins, oral contraceptive pills, steroids, hormone replacement therapies, etc.) and pregnancy were excluded. In the control group, healthy subjects with normal values of HDL-C (≥40.0 mg/dL) were included. The other serum lipid fractions were also within the normal range (i.e., total cholesterol <200.0 mg/dL, TG <150.0 mg/dL, LDL-C <130.0 mg/dL, VLDL-C ≤30.0 mg/dL) [30]. The study was conducted as per the guidelines of the Declaration of Helsinki. It was approved by the Institutional Ethics Committee, Guwahati Medical College and Hospital, Assam, India. All subjects voluntarily provided written informed consent to participate prior to enrollment in the study. Some of the participants were selected from our previous studies [21,22]. Physical Measurements. The physical measurements performed in the subjects were: WC, BMI and BP. Waist circumference and BMI were used as indices of central and general obesity, respectively. They were measured according to World Health Organization guidelines [31]. Systolic and diastolic BP was measured as per Joint National Committee (JNC VII) guidelines [32]. Lipid Fractions and Atherogenic Indices. Measurements of TC, TG and HDL-C in fasting blood samples were done photometrically by homogenous enzymatic methods using dry chemistry reagent slides (Ortho-Clinical Diagnostics Inc., Rochester, NY, USA) in VITROS 5600 integrated system autoanalyzer (Ortho-Clinical Diagnostics Inc.). For quality control, these assays were validated using third-party control materials (Christian Medical College, Vellore, India and Bio-Rad Laboratories, Hercules, CA, USA). The LDL-C and VLDL-C were estimated indirectly using Friedewald’s formula [33]. Atherogenic indices were determined as follows: CRI-I = TC/HDL-C, CRI-II = LDLC/HDL-C, AIP = log10 (TG/HDL-C), AC = (TC – HDL-C)/ HDL-C and non-HDL-C = TC – HDL-C [34-36]. DNA Extraction and Genotyping. Genomic DNA extraction (by a rapid salting-out method) and genotyping for the G-75A and C+83T loci (by a PCR-RFLP method) were done from peripheral blood samples using the protocol described previously [21]. In brief, a 435 bp region at the 5’-end of the APOA1 gene that included the ‘-75’ and ‘+83’ loci was amplified using forward (5’-AGG GAC AGA GCT GAT CCT TGA ACT CTT AAG-3’) and reverse (5’-TTA GGG GAC ACC TAC CCG TCA GGA AGA GCA-3’) primers in 25 µL reaction mixture, followed by restriction digestion of the PCR product by MspI. The genotypes were inferred from the sizes of the restriction fragments analyzed in 12.0% polyacrylamide gel, as mentioned elsewhere [21]. Accordingly, for the G-75A site, the 66 and 114 bp fragments indicated a GG genotype; the 180 bp fragment indicated an AA genotype, and the 66, 114 and 180 bp fragments indicated a GA genotype. Likewise, for the C+83T site, the 46 and 209 bp fragments denoted a CC genotype, the 255 bp fragment denoted a TT genotype, and the 46, 209 and 255 bp fragments denoted a CT genotype. We performed a quality-check by repeating the PCRRFLP technique randomly in 20.0% of the samples ensuring that no differences were noted in the genotypes. Additional confirmation by direct sequencing (at SciGenom Pvt. Ltd., Cochin, Kerala, India) was done in 5.0% of the samples. All the genotypes detected for the two loci in the study were represented. Statistical Analyses. Descriptive statistics were performed in Excel spreadsheets (Microsoft Office 2003, Redmont, WA, USA). For continuous data, means with standard deviation (SD) were expressed. The categorical data were summarized as counts and percentages. The allelic and genotype frequencies for the two SNPs were calculated using POPGENE 2.0 software (Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, AB, Canada). Conformity to Hardy Weinberg equilibrium (HWE) was assessed by the goodness-of-fit χ2 and G-square tests. Diplotype frequencies were also determined. The statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS Inc., Chicago, IL, USA) version 11.5 software. The continuous data were verified for normality by the Kolmogorov-Smirnov test. The comparisons of allelic, genotype and diplotype frequencies between the case and the control groups were performed by the χ2 test (with Yate’s continuity correction, if required). The association of G-75A and C+83T poly-morphisms with decreased HDL-C was tested under different genetic models (dominant, recessive, additive and allelic). The crude association was first determined by calculating the unadjusted odds ratios (OR) with 95% confidence intervals (CI). Further, adjusted OR with 95% CI was calculated by multiple logistic regressions after adjusting for covariates such as gender, age, smoking, alcohol use, WC, BMI, TC and TG. The associations of the SNPs with other CVD risk factors (viz. concentrations of other lipid fractions, atherogenic indices, WC, BMI, systolic and diastolic BP) were examined by comparing their values (adjusted for covariates) across the detected genotypes using the analysis of covariance (ANCOVA) test. Comparisons were also performed across diplotypes. To quantify the significant relationships detected between the SNPs and CVD risk factors, the results were complemented by calculating the effect sizes (Cohen’s f) in G*POWER software (G*POWER 3.1.9.2; Düsseldorf, Germany). It provided an estimate of the magnitude of association that the SNPs had with the CVD risk factors. The effect sizes were interpreted as small (f = 0.1), medium (f = 0.25) and large (f = 0.4) effects as recommended by Cohen [37]. Further, power calculations were done to determine whether the statistical analysis and the results obtained therein were adequately powered. All calculations were two-tailed and a P value of less than 0.05 was considered as statistically significant.



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