Balkan Journal of Medical Genetics

RTN4 AND FBXL17 GENES ARE ASSOCIATED WITH CORONARY HEART DISEASE IN GENOME-WIDE ASSOCIATION ANALYSIS OF LITHUANIAN FAMILIES
Domarkienė I1,*, Pranculis A1, Germanas Š1, Jakaitienė A1, Vitkus D2, Dženkevičiūtė V3, Kučinskienė ZA2, Kučinskas V1
*Corresponding Author: Ingrida Domarkienė, Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariškių str. 2, 08661 Vilnius, Lithuania; Tel.: +370-52501788; E-mail: ingrida.domarkiene@ mf.vu.lt
page: 17

MATERIALS AND METHODS

All study protocols were approved by the Vilnius Regional Biomedical Research Ethics Committee (No. 158200-11-255-067LP2; 2010-11-05). Informed consent was obtained from all individuals who participated in the study. Individuals and Phenotype Definition. According to the Department of Statistics of Lithuania, in 2011, the total number of inhabitants was 3,030,200, and 17.3% of these were of non Lithuanian ethnicity. Considering the demographics and the fact that trios with CHD patients are generally rare, in total we collected 32 relevant families (trios of premature CHD patients and their parents) from different regions throughout Lithuania, i.e., 96 individuals in total. The patient group was represented by 31 males and only one female. Thus, conclusions from our study are suitable to extrapolate only for the male population. Patients were clinically examined at the Clinic of Cardiology and Angiology, Faculty of Medicine, Vilnius University, Vilnius, Lithuania. The patients’ clinical phenotype was evaluated after assessment of anthropometrical measurements, clinical and instrumental examination, and laboratory biochemical testing. Information about CHD risk factors, other diseases and treatment was obtained during the conventional anamnesis. Patient recruitment criteria was as follows: men aged 35-55, women aged 35-65; individuals who were experiencing acute coronary syndrome for the first time in their lives, who were hospitalized at an intensive cardiology unit for myocardial infarction (MI) with or without Q wave or unstable angina pectoris (confirmed by examination of common electrocardiographic and/or coronographic changes, assessment of cardio-specific markers); any previous or current evidence of significant atherosclerotic CHD (MI, percutaneous coronary angioplasty, coronary artery bypass graft or coronary angiography with hemo-dynamically significant stenosis). Anatomical vascular changes were confirmed by non invasive methods, evaluating the presence of the atherosclerotic plaques as well as examining the arterial stiffness and endothelial function. Patient exclusion criteria was as follows: diabetes treated with insulin, kidney function deficiency, III-IV functional class of heart deficiency, tumors (except skin basalioma), alcoholism and other social factors that may influence the study results. Metabolic syndrome was diagnosed by determining three or more criteria described in the NCEP ATP III program [5]: waist circumference in men >102 cm, in women >88 cm, triglycerides ≥1.7 mmol/L, high-density lipoprotein cholesterol (HDL-C) <1.0 in men and <1.2 in women, blood pressure ≥130/85 mm Hg, fasting glucose ≥5.6 mmol/L or type 2 diabetes. Evaluation of biochemical phenotype included inflammatory and metabolic markers, participating in the patho-genesis of atherosclerosis: C-reactive protein (CRP), Hb A1c, lipoprotein [Lp(a)], apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), ratio ApoB/ A1, lipids, oxidized low-density lipoprotein (oxLDL) homocysteine, interleukin-6 (IL-6), fasting glucose in plasma, potassium (K), sodium (Na), urea, creatinin. Genotyping. The DNA samples were extracted from the peripheral venous blood using phenol-chloroform DNA isolation or TECAN Freedom EVO® platform (TECAN Group Ltd., Männedorf, Switzerland) protocols. All DNA samples were genotyped according to the Illumina® provided protocols on Illumina HiScanSQ™ genetic analysis platform using an Illumina HumanOmni Express-12 v1.0 array comprised of ~770K SNP markers (Illumina Inc., San Diego, CA, USA). The primary genotyping results were visualized, inspected and prepared for further analysis by using the GenomeStudio software (Illumina Inc.). Subsequent data quality control, filtering and analysis were performed by using the PLINK v1.07 software [6] integrated in to the BC|Gene platform (Biocomputing Platforms Ltd., Espoo, Finland). Statistical Analysis. The transmission-disequilibrium test (TDT) was used to determine the association between SNPs and CHD phenotype using the McNemar test [7]. Single nucleotide polymorphisms included in the TDT analysis met the following criteria: 1) minor allele frequency (MAF) greater than 0.01 (MAF >0.01); 2) missingness rate smaller than 0.1 (GENO <0.1); 3) the p value (<0.0005) of the Hardy- Weinberg equilibrium test; also if the subjects’ missing genotype rate was lower than 0.05 (MIND <0.05). For the computation of the empirical power, the frequency of the informative transmission of disease alleles and the number of informative transmissions of marker alleles was used. The binomial distribution was used for the approximation of the TDT power [8]. The 106 random variables distributed according to the TDT statistics under alternative hypothesis were generated. Odds ratio (OR) with 95% confidence interval (CI 95%) was calculated for selected SNPs. The level of significance was set at a = 10–4. For multiple testing, the correction adaptive permutation procedure was used. Maximum number of permutations was 106. The statistical analysis was performed with the program R (v2.15.3) (R Foundation for Statistical Computing, Vienna, Austria).

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