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International Journal of Clinical and Experimental Pathology logoLink to International Journal of Clinical and Experimental Pathology
. 2015 Jun 1;8(6):7318–7331.

Association of two polymorphisms in the FADS1/FADS2 gene cluster and the risk of coronary artery disease and ischemic stroke

Qian Yang 1, Rui-Xing Yin 1, Xiao-Li Cao 1, Dong-Feng Wu 1, Wu-Xian Chen 1, Yi-Jiang Zhou 1
PMCID: PMC4525966  PMID: 26261632

Abstract

Little is known about the association of the FADS1/FADS2 SNPs and serum lipid levels and the risk of coronary artery disease (CAD) and ischemic stroke (IS) in the Chinese southern population. The present study aimed to determine such association in the Chinese southern population. A total of 1,669 unrelated subjects (CAD, 534; IS, 553; and healthy controls, 582) were recruited in the study. Genotypes of the FADS1 rs174546 SNP and the FADS2 rs174601 SNP were determined by the SNaPshot Multiplex Kit. The T allele and TT genotype frequencies of the two SNPs were predominant in our study population. The T alleles were associated with increased risk of CAD and IS. Correspondingly, the C alleles were associated with reduced risk of CAD and IS. Haplotype analyses showed that the haplotype of T-T (rs174546-rs174601) was associated with an increased risk for IS, and the haplotype of C-C (rs174546-rs174601) was associated with a reduced risk for CAD and IS. The two SNPs were likely to influence serum lipid levels. The T allele carriers of the two SNPs and rs174601 TT genotype were associated with decreased serum HDL-C and ApoAI levels in the patient groups and with an increased risk of CAD and IS. The present study suggests that the FADS1 rs174546 SNP and the FADS2 rs174601 SNP are associated with the risk of CAD and IS, and are likely to influence serum lipid levels. However, further functional studies are needed to clarify how the two SNPs actually affect serum lipid levels and the risk of CAD and IS.

Keywords: The FADS1/FADS2 gene cluster, single nucleotide polymorphism, ischemic stroke, coronary artery disease, lipids

Introduction

Both coronary artery disease (CAD) and ischemic stroke (IS) are the most prevalent geriatric diseases and the major determinant of mortality and morbidity worldwide [1-3]. As multifactorial diseases, both CAD and IS share common risk factors, including both lipid and nonlipid variables, such as metabolic factors, thrombogenic/hemostatic factors, and inflammatory markers [4]. These risk factors are involved in the initiation, progression and rupture of atherosclerotic plaque.

Long-chain polyunsaturated fatty acids (LC-PUFAs) are important components of cell membranes, serve as substrates for the synthesis of inflammatory eicosanoids (leukotrienes and prostaglandins), act as signaling molecules, and regulate gene expression [5]. LC-PUFAs composition of plasma and body tissues has been associated with numerous health outcomes including cardiovascular health, allergies, mental health, and cognitive development [6,7]. LC-PUFAs could reduce hepatic very low-density lipoprotein synthesis contributes to lower plasma triglycerides [8,9] and reduce plasma and urine levels of eicosanoids such as leukotriene E4 and alter several inflammatory pathways [10]. Additionally, in several trials, LC-PUFAs are commonly considered to have anti-thrombotic effects and improve endothelial function and health [11,12]. The roles of each of these molecular pathways could partly mediate protective effects of LC-PUFAs against cardiovascular disease.

Tissue LC-PUFAs levels are determined by both dietary intake and endogenous synthesis via the successive elongation and desaturation of dietary fatty acids precursors. Delta-5 desaturase (D5D) and delta-6 desaturase (D6D), the key enzymes required for the synthesis of LC-PUFAs [13], are respectively encoded by the FADS1 and FADS2 genes, which is clustered with family members at 11q12-q13.1. Many studies have reported associations between genetic variants in the FADS1/FADS2 gene cluster and LC-PUFAs levels [14]. Bokor et al. [14] indicated that the minor alleles of SNPs including rs174546 were associated with lower D5D desaturase activity. Stoffel et al. [15] found that Loss of FADS2 expression in the FADS2-null mouse, abolished the synthesis of LC-PUFAs. Thus, genetic variations in the FADS gene cluster correlated with a decrease of desaturase reaction products and an accumulation of substrates, which might have implications for cardiovascular disease [6,16-23]. Recently, several studies have showed strong associations between single nucleotide polymorphisms (SNPs) in the FADS1/FADS2 gene cluster and the risk of cardiovascular disease [6,16-23]. Other studies have also reported relationships between several FADS1/FADS2 variants and plasma lipid concentrations [21,22,24,25]. However, the mechanisms underlying these associations have not been clearly established. At present, the associations of the SNPs in the FADS1/FADS2 gene cluster with serum lipid levels and risk of cardiovascular disease have been more reported in the European populations, relatively little is known about such association in the Chinese populations, especially in Chinese south population. Considering the differences in genetic background and living habits among different population, and searching for novel pathway in lipid regulation and new therapeutic or preventive methods for cardiovascular disease, it is of great interest to evaluate these associations. Therefore, the aim of the present study was to investigate the possible association between the SNPs in the FADS1/FADS2 gene cluster and serum lipid levels, as well as the risk of CAD and IS in Chinese south population through the case-control study.

Materials and methods

Study population

A total of 1,087 unrelated patients with CAD (n = 534) and IS (n = 553) were recruited from hospitalized patients in the First Affiliated Hospital, Guangxi Medical University from September 2009 to October 2011. The diagnosis of CAD was based on typical clinical symptoms and electrocardiographic changes, as well as increases in the serum markers including creatinine kinase-MB and troponin T. Coronary angiography was performed in patients with CAD. The selected CAD patients were subject to significant coronary stenosis (≥ 50%) in at least either one of the three main coronary arteries or their major branches (branch diameter ≥ 2 mm). Additionally, angiographic severity of disease was defined as single or multi-vessel disease based on the number of involved artery (luminal narrowing ≥ 50%) in the three major coronary arteries [26,27]. The classification of IS was made according to the TOAST (Trial of Org 10172 in Acute Stroke Treatment) criteria [28]. The selected IS patients in the study included individuals who were eligible for one of the two subtypes of TOAST criteria: Large-artery atherosclerosis and Small-vessel occlusion. Subjects with a history of hematologic, neoplastic, renal, liver, thyroid, autoimmune diseases and type I diabetes mellitus were excluded. The selected IS patients who had a past history of CAD were excluded, while the selected CAD patients who had a past history of IS were excluded from the study.

A total of 582 healthy subjects matched by age, gender, and ethnic group (Han Chinese) were consecutively recruited from Physical Examination Center of the First Affiliated Hospital, Guangxi Medical University during the same period when CAD and IS patients were recruited. The controls were free of CAD and IS by questionnaires, history taking and clinical examination. All enrolled individuals were Han Chinese from Guangxi, the People’s Republic of China. A standard questionnaire was used to ascertain the general information and medical history for all participants. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital, Guangxi Medical University. Informed consent was obtained from all subjects after they received a full explanation of the study.

Biochemical measurements

Venous blood sample was drawn from all subjects after at least 12 hours of fasting. The levels of serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in samples were determined by enzymatic methods with commercially available kits. Serum apolipoprotein (Apo) AI and ApoB levels were detected by the immunoturbidimetric immunoassay. The normal values of serum TC, TG, HDL-C, LDL-C, ApoAI, ApoB levels, and the ratio of ApoAI to ApoB in our Clinical Science Experiment Center were 3.10-5.17, 0.56-1.70, 0.91-1.81, 2.70-3.20 mmol/L, 1.00-1.78, 0.63-1.14 g/L, and 1.00-2.50; respectively [29-31]. The individuals with TC > 5.17 mmol/L, and/or TG > 1.70 mmol/L were defined as hyperlipidemic [32]. Hypertension was diagnosed according to the criteria of 1999 World Health Organization International Society of Hypertension Guidelines for the management of hypertension [33]. Uncontrolled hypertension was defined as a systolic blood pressure of 140 mmHg or higher and a diastolic blood pressure of 90 mmHg or higher. The subjects with systolic blood pressure of only 140 mmHg or higher but a diastolic blood pressure of < 90 mmHg were diagnosed as isolated systolic hypertension. Normal weight, overweight and obesity were defined as a body mass index (BMI) < 24, 24-28, and > 28 kg/m2; respectively [34].

SNP selection and genotyping

The SNPs of rs174546 and rs174601 were selected as genetic markers. rs174561 (C/T) is located in 3’-untranslated regions (UTR) of FADS1 and rs174601 (C/T) is located in intron 1 of FADS2. The two SNPs were selected on the basis of the following assumptions: (1) Selected SNPs were established by Haploview (Broad Institute of MIT and Harvard, USA, version 4.2); (2) SNPs information was obtained from NCBI dbSNP Build 132 (http://www.Ncbi.nlm.nih.gov/SNP/); (3) SNPs were restricted to minor allele frequency (MAF) > 1%. (4) SNPs might be associated with the plasma lipids levels in a recent GWAS [24,25]; and (5) SNPs might be either functional or LD with other functional SNPs [35].

Genomic deoxyribonucleic acid (DNA) was extracted from leucocytes of venous blood using the phenol-chloroform method. The two SNPs (rs174546, rs174601) were determined using SNaPshot Multiplex Kit (Applied Biosystems Co., USA). The restriction enzymes for loci rs174546, rs174601 were SAP and EXO I (Promega, Epicentre), respectively. The sense and antisense primers were as follows: rs174546F: 5’-CAAACCCAACCCCCTCTGAGTA-3’, rs174546R: 5’-CCATTTTGTCCCTGCAGCTCACTA-3’; rs174601F: 5’-TTCTGGGGGTTCTTCAGCTGGT-3’, rs174601R: 5’-AGGGAAGGGACCTTGGATGATG-3’.

Statistical analyses

The statistical analyses were carried out using the statistical software package SPSS 21.0 (SPSS Inc., Chicago, Illinois). Quantitative variables were expressed as mean ± standard deviation (serum TG levels were presented as medians and interquartile ranges). Qualitative variables were expressed as percentages. Allele frequency was determined via direct counting, and the standard goodness-of-fit test was used to test the Handy-Weinberg equilibrium. A chi-square analysis was used to evaluate the difference in genotype distribution and sex ratio between the groups. The general characteristics between patients and controls were tested by the Student’s unpaired t-test. The association of genotypes and serum lipid parameters was tested by analysis of covariance (ANCOVA). Any variants associated with the serum lipid parameter at a value of P < 0.025 (corresponding to P < 0.05 after adjusting for two independent tests by the Bonferroni correction) were considered statistically significant. Unconditional logistic regression was used to assess the correlation between the risk of CAD and IS and genotypes. Age, gender, BMI, smoking and alcohol consumption were adjusted for the statistical analysis. Odds ratio (OR) and 95% confidence interval (CI) were calculated using unconditional logistic regression. Results were considered to be statistically significant if bilateral P-values were less than 0.05. The pattern of pair-wise LD between the selected SNPs was measured by D’ and r 2, and haplotype frequencies were calculated using the SHEsis software [36].

Results

Characteristics of the subjects

The clinical characteristics of the patients and healthy controls are shown in Table 1. The differences in age, gender, serum LDL-C and ApoB levels, and the percentages of subjects who smoked cigarettes were not significant between controls and CAD or IS patients (P > 0.05). Compared with the controls group, more patients in CAD or IS groups had type 2 diabetes mellitus (T2DM), hypertension and hyperlipidemia. The patient groups also had significant higher BMI, pulse pressure, serum TG, and lower levels of serum TC, HDL-C, ApoAI, the ApoAI/ApoB ratio (P < 0.05). In addition, compared with the control group, the IS patients had higher systolic blood pressure levels and lower percentage of subjects who consumed alcohol (P < 0.05), but there was no difference in diastolic blood pressure (P > 0.05). The CAD patients, in contrast, had lower levels of diastolic blood pressure (P < 0.05). There was no difference in systolic blood pressure (P > 0.05). In comparison with CAD patients, the IS patients had higher levels of blood pressure and HDL-C, and lower the percentages of subjects who suffered from T2DM (P < 0.05).

Table 1.

General characteristics and serum lipid levels between the controls and patients

Characteristic Controls(n = 582) patients P
CAD (n = 534) IS (n = 553) P 1 P2 P3
Male/female 418/164 403/131 399/154 0.095 0.477 0.214
Age, years 61.40 ± 10.54 61.93 ± 10.69 62.54 ± 12.11 0.405 0.090 0.374
Body mass index, kg/m2 22.28 ± 2.82 23.64 ± 4.10 24.71 ± 2.08 < 0.001 0.011 0.270
Systolic blood pressure, mmHg 130.45 ± 2.18 132.80 ± 23.11 147.71 ± 22.18 0.072 < 0.001 < 0.001
Diastolic blood pressure, mmHg 82.63 ± 13.43 79.05 ± 14.08 83.63 ± 13.43 < 0.001 0.144 < 0.001
Pulse pressure, mmHg 50.10 ± 14.87 53.65 ± 18.80 63.66 ± 18.49 < 0.001 < 0.001 < 0.001
Cigarette smoking, n (%) 248 (42.6) 240 (45.0) 231 (41.8) 0.469 0.810 0.299
Alcohol consumption, n (%) 259 (44.5) 211 (39.5) 203 (36.7) 0.101 0.008 0.349
Total cholesterol, mmol/L 4.93 ± 1.06 4.52 ± 1.23 4.52 ± 1.15 < 0.001 < 0.001 0.952
Triglyceride, mmol/L 1.00 (0.65) 1.36 (0.96) 1.36 (0.92) < 0.001 < 0.001 0.432
HDL-C, mmol/L 1.90 ± 0.49 1.14 ± 0.34 1.23 ± 0.40 < 0.001 < 0.001 < 0.001
LDL-C, mmol/L 2.76 ± 0.77 2.73 ± 1.00 2.68 ± 0.90 0.567 0.108 0.390
Apolipoprotein (Apo) AI, g/L 1.40 ± 0.27 1.00 ± 0.27 1.02 ± 0.22 < 0.001 < 0.001 0.288
ApoB, g/L 0.91 ± 0.21 0.91 ± 0.27 0.89 ± 0.25 0.726 0.325 0.242
ApoAI/ApoB 1.62 ± 0.48 1.27 ± 1.88 1.17 ± 0.61 < 0.001 < 0.001 0.233
Type 2 diabetes mellitus, n (%) 25 (4.3) 124 (23.2) 95 (17.2) < 0.001 < 0.001 0.013
Hypertension, n (%) 180 (30.9) 272 (50.9) 298 (53.9) < 0.001 < 0.001 0.330
Hyperlipidemia, n (%) 198 (34.0) 254 (47.6) 267 (48.3) < 0.001 < 0.001 0.813
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CAD, coronary artery disease; IS, ischemic stroke; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol. P 1: comparison of CAD and controls; P 2: comparison of IS and controls; P 3: comparison of CAD and IS.

Genotypic and allelic frequencies

The genotypic and allelic frequencies of FADS1 rs174546 and FADS2 rs174601 are presented in Table 2. The genotype distribution was concordant with the Hardy-Weinberg proportions in both patients and controls. For rs174546 SNP, the frequency of the T and C alleles was 67.7% and 32.3% in the controls, 71.7% and 28.3% in the CAD patients, and 72.2% and 27.8% in the IS patients respectively. The frequency of the TT, TC and CC genotypes was 45.5%, 44.2% and 10.3% in the controls, 53.0%, 37.4% and 9.6% in the CAD patients, and 53.3%, 37.8% and 8.9% in the IS patients respectively. For rs174601 SNP, the frequency of the T and C alleles was 67.9% and 32.1% in the controls, 72.8% and 27.2% in the CAD patients, and 74.1% and 25.9% in the IS patients respectively. The frequency of the TT, TC and CC genotypes was 46.1%, 43.6% and 10.3% in the controls, 54.7%, 36.3% and 9.0% in the CAD patients, and 56.0%, 36.0% and 8.0% in the IS patients respectively. The genotypic and allelic frequencies were different between the controls and CAD patients and between the controls and IS patients.

Table 2.

Genotypic and allelic frequencies and the risk of coronary artery disease (CAD) and ischemic stroke (IS)

Genotype or allele Controls (%) CAD (%) IS (%) CAD IS
N = 582 N = 534 N = 553 OR (95% CI) P OR (95% CI) P
rs174546
    CC 60 (10.3) 51 (9.6) 49 (8.9) 1 1
    CT 257 (44.2) 200 (37.4) 209 (37.8) 0.92 (0.58-1.47) 0.729 0.86 (0.54-1.37) 0.528
    TT 265 (45.5) 283 (53.0) 295 (53.3) 1.39 (0.88-2.21) 0.161 1.31 (0.83-2.06) 0.255
    P 0.041 0.031
    C 377 (32.3) 302 (28.3) 307 (27.8) 1 1
    T 787 (67.7) 766 (71.7) 799 (72.2) 1.30 (1.06-1.59) 0.010 1.29 (1.06-1.57) 0.011
    P 0.020 0.009
    HWE (P) 0.842 0.076 0.175
    TT 265 (45.5) 283 (53.0) 295 (53.3) 1 1
    CC + TC 317 (54.5) 251 (47.0) 258 (46.7) 0.57 (0.44-0.75) < 0.001 0.62 (0.48-0.80) < 0.001
    P 0.008 0.005
    CC 60 (10.3) 51 (9.6) 49 (8.9) 1 1
    TT + TC 522 (89.7) 483 (90.4) 504 (91.1) 1.12 (0.72-1.75) 0.603 1.08 (0.70-1.68) 0.730
    P 0.374 0.234
Rs174601
    CC 60 (10.3) 48 (9.0) 44 (8.0) 1 1
    CT 254 (43.6) 194 (36.3) 199 (36.0) 0.92 (0.57-1.48) 0.724 0.97 (0.60-1.56) 0.889
    TT 268 (46.1) 292 (54.7) 310 (56.0) 1.51 (0.95-2.40) 0.084 1.58 (0.99-2.53) 0.055
    P 0.015 0.003
    C 374 (32.1) 290 (27.2) 287 (25.9) 1 1
    T 790 (67.9) 778 (72.8) 819 (74.1) 1.38 (1.13-1.69) 0.002 1.42 (1.16-1.73) 0.001
    P 0.006 0.001
    HWE (P) 0.987 0.059 0.135
    TT 268 (46.0) 292 (54.7) 310 (56.1) 1 1
    CC + TC 314 (54.0) 242 (45.3) 243 (43.9) 0.54 (0.41-0.70) < 0.001 0.61 (0.48-0.79) < 0.001
    P 0.002 < 0.001
    CC 60 (10.3) 48 (9.0) 44 (8.0) 1 1
    TT + TC 522 (89.7) 486 (91.0) 509 (92.0) 1.23 (0.78-1.92) 0.372 1.27 (0.81-2.01) 0.291
    P 0.260 0.102
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HWE, Hardy-Weinberg equilibrium. CAD, coronary artery disease; IS, ischemic stroke.

FADS1/FADS2 SNPs and the risk of CAD and IS

For rs174546 SNP, the T allele was associated with an increased risk of CAD (adjusted Odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.06-1.59) and IS (adjusted OR = 1.29, 95% CI = 1.06-1.57) (Table 2). The CC/TC genotypes were also associated with a decreased risk of CAD (adjusted OR = 0.57, 95% CI = 0.44-0.75 for CC/TC vs. TT) and IS (adjusted OR = 0.62, 95% CI = 0.48-0.80 for CC/TC vs. TT). Similarly, for rs174601 SNP, the T allele was associated with an increased risk of CAD (adjusted OR = 1.38, 95% CI = 1.13-1.69) and IS (adjusted OR = 1.42, 95% CI = 1.16-1.73). The CC/TC genotypes were also associated with a decreased risk of CAD (adjusted OR = 0.54, 95% CI = 0.41-0.70 for CC/TC vs. TT) and IS (adjusted OR = 0.61, 95% CI = 0.48-0.79 for CC/TC vs. TT).

Haplotype and the risk of CAD and IS

The SNPs’ LD patterns were assessed by using both the D’ and r 2 values. The rs174546 SNP was in strong LD with rs174601 (D’ = 0.951; r 2 = 0.860). Hence, we performed haplotype analyses with the two SNPs to assess the associations of the SNPs with the risk of CAD and IS. Two common haplotypes (frequency > 3%) derived from the two SNPs accounted for above 90% haplotype variations. The frequency of C-C haplotype (rs174546-rs174601) was 31.8% in the controls, 24.6% in the CAD patients, and 25.8% in the IS patients. The frequency of T-T haplotype (rs174546-rs174601) was 67.3% in the controls, 69.2% in the CAD patients, and 72.1% in the IS patients. The haplotype of C-C was associated with a decreased risk for CAD and IS (adjusted OR = 0.72, 95% CI = 0.60-0.87 for CAD, and adjusted OR = 0.76, 95% CI = 0.63-0.91 for IS; respectively). In contrast, the haplotype of T-T was associated with an increased risk for IS (adjusted OR = 1.32, 95% CI = 1.10-1.59 for IS Table 3).

Table 3.

Haplotype and the risk of CAD and IS

Haplotype Haplotype frequency (%) CAD IS
Controls (n = 582) CAD (n = 534) IS (n = 553) OR (95% CI) P OR (95% CI) P
H1 CC 31.8 24.6 25.8 0.72 (0.60-0.87) 0.001 0.76 (0.63-0.91) 0.003
H2 TT 67.3 69.2 72.1 1.18 (0.98-1.41) 0.076 1.32 (1.10-1.59) 0.003
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Loci are arranged in the order rs174546, rs174601. Haplotype with frequency less than 3% was pooled and not analyzed. CAD, coronary artery disease; IS, ischemic stroke.

FADS1/FADS2 SNPs and the angiographic severity of CAD

As shown in Table 4, there were no significant effects of the rs174546 and rs174601 on angiographic severity of CAD in different genetic models (P > 0.05).

Table 4.

Effect of genotypes on angiographic severity of CAD

Genotype rs174546 rs174601
OR (95% CI) P OR (95% CI) P
CC 1 1
CT 0.99 (0.47-2.07) 0.972 1.19 (0.56-2.51) 0.658
TT 0.90 (0.44-1.84) 0.766 0.94 (0.46-1.93) 0.869
C 1 1
T 1.05 (0.71-1.54) 0.822 1.04 (0.63-1.17) 0.875
CC 1 1
CT + TT 0.92 (0.46-1.84) 0.809 1.17 (0.59-2.33) 0.653
TT 1 1
CC + TC 1.03 (0.69-1.53) 0.888 1.15 (0.77-1.71) 0.504
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CAD, coronary artery disease.

Related Risk Factors for CAD and IS

Multivariate logistic analysis showed that the incidence of CAD and IS positively correlated with BMI, diabetes, hypertension and hyperlipidemia and negatively correlated with alcohol consumption (Table 5).

Table 5.

The relative risk factors for CAD and IS

Relative Factors CAD IS
OR (95% CI) P OR (95% CI) P
Male 1 1
Female 0.78 (0.56-1.08) 0.130 0.87 (0.63-1.21) 0.415
Aged ≤ 60 year 1 1
Aged > 60 year 1.05 (0.81-1.37) 0.712 0.96 (0.74-1.25) 0.745
BMI ≤ 24 kg/m2 1 1
BMI > 24 kg/m2 2.45 (1.85-3.23) < 0.001 1.84 (1.39-2.44) < 0.001
Nonsmoking 1 1
Smoking 1.32 (0.99-1.77) 0.058 1.17 (0.88-1.56) 0.284
Nondrinking 1 1
Drinking 0.71 (0.54-0.94) 0.016 0.64 (0.48-0.86) 0.003
Normotensive 1 1
Hypertension 1.96 (1.50-2.56) < 0.001 2.38 (1.83-3.09) < 0.001
Normal blood lipids 1 1
Hyperlipidemia 1.57 (1.21-2.05) 0.001 2.38 (1.83-3.09) < 0.001
Non-diabetes 1 1
Diabetes 5.60 (3.51-8.94) < 0.001 3.26 (2.01-5.31) < 0.001
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CAD, coronary artery disease; IS, ischemic stroke.

FADS1/FADS2 SNPs and serum lipid levels

The serum lipid levels were different between genotypes in the CAD and IS patients, but not in the controls (Table 6). After correction for multiple testing, the subjects with rs174601 TT genotype had lower TC, HDL-C and ApoAI levels than the subjects with CC/TC genotypes in CAD patients (P < 0.025). Carrying T allele carriers of the rs174546 or rs174601 SNP had lower HDL-C and ApoAI levels than the non- carriers in IS patients (P < 0.025).

Table 6.

Effect of the genotypes on serum lipid levels

Genotype Controls TC (mmol/L) TG (mmol/L) HDL-C (mmol/L) LDL-C (mmol/L) ApoAI (g/L) ApoB (g/L) ApoAI/ApoB
rs174546
    CC 4.98 ± 0.14 1.06 (0.88) 1.85 ± 0.06 2.70 ± 0.10 1.41 ± 0.03 0.92 ± 0.03 1.56 ± 0.06
    CT 4.93 ± 0.07 0.99 (0.62) 1.93 ± 0.03 2.75 ± 0.05 1.40 ± 0.02 0.90 ± 0.01 1.62 ± 0.03
    TT 4.91 ± 0.06 1.01 (0.66) 1.89 ± 0.03 2.79 ± 0.05 1.39 ± 0.02 0.90 ± 0.01 1.64 ± 0.03
    P 0.898 0.727 0.490 0.593 0.860 0.713 0.520
    TT 4.91 ± 0.06 1.01 (0.66) 1.89 ± 0.03 2.79 ± 0.05 1.39 ± 0.02 0.90 ± 0.01 1.64 ± 0.03
    CC + TC 4.94 ± 0.06 0.99 (0.63) 1.91 ± 0.03 2.75 ± 0.04 1.41 ± 0.01 0.91 ± 0.01 1.61 ± 0.03
    P 0.699 0.474 0.465 0.456 0.463 0.814 0.504
    CC 4.98 ± 0.14 1.06 (0.88) 1.85 ± 0.06 2.70 ± 0.10 1.41 ± 0.03 0.92 ± 0.03 1.56 ± 0.06
    TT + TC 4.92 ± 0.05 1.00 (0.64) 1.90 ± 0.02 2.77 ± 0.03 1.40 ± 0.01 0.90 ± 0.01 1.63 ± 0.02
    P 0.680 0.910 0.423 0.397 0.801 0.490 0.320
rs174601
    CC 5.03 ± 0.14 1.06 (0.88) 1.88 ± 0.06 2.73 ± 0.10 1.42 ± 0.03 0.93 ± 0.03 1.57 ± 0.06
    CT 4.90 ± 0.07 0.99 (0.63) 1.92 ± 0.03 2.74 ± 0.05 1.40 ± 0.02 0.90 ± 0.01 1.62 ± 0.03
    TT 4.92 ± 0.06 1.01 (0.64) 1.89 ± 0.03 2.80 ± 0.05 1.39 ± 0.02 0.90 ± 0.01 1.64 ± 0.03
    P 0.549 0.768 0.669 0.628 0.737 0.567 0.561
    TT 4.92 ± 0.06 1.01 (0.64) 1.89 ± 0.03 2.80 ± 0.05 1.39 ± 0.02 0.90 ± 0.01 1.64 ± 0.03
    CC + TC 4.93 ± 0.06 0.99 (0.64) 1.91 ± 0.03 2.74 ± 0.04 1.40 ± 0.01 0.91 ± 0.01 1.61 ± 0.03
    P 0.884 0.500 0.486 0.335 0.603 0.819 0.427
    CC 5.03 ± 0.14 1.06 (0.88) 1.88 ± 0.06 2.73 ± 0.10 1.42 ± 0.03 0.93 ± 0.03 1.57 ± 0.06
    TT + TC 4.91 ± 0.05 1.00 (0.65) 1.90 ± 0.02 2.77 ± 0.03 1.40 ± 0.01 0.90 ± 0.01 1.63 ± 0.02
    P 0.401 0.612 0.842 0.700 0.448 0.360 0.402
CAD
rs174546
    CC 4.87 ± 0.17 1.53 (1.31) 1.14 ± 0.05 2.96 ± 0.14 0.99 ± 0.04 0.99 ± 0.04 1.04 ± 0.26
    CT 4.56 ± 0.08 1.33 (0.94) 1.18 ± 0.02 2.73 ± 0.07 1.02 ± 0.02 0.91 ± 0.02 1.09 ± 0.13
    TT 4.44 ± 0.07 1.35 (0.93) 1.12 ± 0.02 2.70 ± 0.06 1.00 ± 0.02 0.90 ± 0.02 1.37 ± 0.11
    P 0.046 0.371 0.079 0.213 0.711 0.091 0.381
    TT 4.44 ± 0.07 1.35 (0.93) 1.12 ± 0.02 2.70 ± 0.06 1.00 ± 0.02 0.90 ± 0.02 1.37 ± 0.11
    CC + TC 4.64 ± 0.08 1.38 (0.96) 1.17 ± 0.02 2.78 ± 0.06 1.01 ± 0.02 0.93 ± 0.02 1.17 ± 0.12
    P 0.052 0.485 0.033 0.358 0.650 0.203 0.202
    CC 4.87 ± 0.17 1.53 (1.31) 1.14 ± 0.05 2.96 ± 0.14 0.99 ± 0.04 0.99 ± 0.04 1.04 ± 0.26
    TT + TC 4.50 ± 0.05 1.35 (0.91) 1.14 ± 0.02 2.71 ± 0.05 1.01 ± 0.01 0.91 ± 0.01 1.30 ± 0.09
    P 0.034 0.169 0.972 0.085 0.624 0.034 0.338
rs174601
    CC 4.69 ± 0.18 1.47 (1.18) 1.15 ± 0.05 2.80 ± 0.14 0.99 ± 0.04 0.94 ± 0.04 1.08 ± 0.27
    CT 4.69 ± 0.09 1.34 (0.60) 1.20 ± 0.02 2.76 ± 0.07 1.05 ± 0.02 0.93 ± 0.02 1.22 ± 0.14
    TT 4.42 ± 0.07 1.36 (0.90) 1.10 ± 0.02 2.71 ± 0.06 0.99 ± 0.02 0.90 ± 0.02 1.35 ± 0.11
    P 0.054 0.657 0.012 0.774 0.027 0.287 0.575
    TT 4.42 ± 0.07 1.36 (0.90) 1.10 ± 0.02 2.71 ± 0.06 0.99 ± 0.02 0.90 ± 0.02 1.35 ± 0.11
    CC + TC 4.67 ± 0.08 1.37 (1.02) 1.19 ± 0.02 2.77 ± 0.06 1.04 ± 0.02 0.93 ± 0.02 1.20 ± 0.12
    P 0.017 0.516 0.005 0.509 0.021 0.124 0.345
    CC 4.69 ± 0.18 1.47 (1.18) 1.15 ± 0.05 2.80 ± 0.14 0.99 ± 0.04 0.94 ± 0.04 1.08 ± 0.27
    TT + TC 4.52 ± 0.05 1.36 (0.92) 1.14 ± 0.02 2.73 ± 0.05 1.01 ± 0.01 0.91 ± 0.01 1.30 ± 0.09
    P 0.353 0.405 0.889 0.625 0.631 0.381 0.446
IS
rs174546
    CC 4.42 ± 0.17 1.21 (0.87) 1.36 ± 0.06 2.54 ± 0.13 1.13 ± 0.03 0.88 ± 0.04 1.25 ± 0.09
    CT 4.50 ± 0.08 1.35 (0.95) 1.23 ± 0.03 2.69 ± 0.06 1.01 ± 0.02 0.89 ± 0.02 1.13 ± 0.04
    TT 4.57 ± 0.07 1.36 (0.93) 1.21 ± 0.02 2.71 ± 0.05 1.02 ± 0.02 0.90 ± 0.01 1.21 ± 0.04
    P 0.610 0.242 0.054 0.465 0.003 0.883 0.240
    TT 4.57 ± 0.07 1.36 (0.93) 1.21 ± 0.02 2.71 ± 0.05 1.02 ± 0.02 0.90 ± 0.01 1.21 ± 0.04
    CC + TC 4.48 ± 0.07 1.33 (0.91) 1.26 ± 0.03 2.66 ± 0.07 1.04 ± 0.01 0.89 ± 0.02 1.15 ± 0.04
    P 0.361 0.676 0.141 0.488 0.358 0.669 0.256
    CC 4.42 ± 0.17 1.21 (0.87) 1.36 ± 0.06 2.54 ± 0.13 1.13 ± 0.03 0.88 ± 0.04 1.25 ± 0.09
    TT + TC 4.54 ± 0.05 1.36 (0.92) 1.21 ± 0.02 2.70 ± 0.04 1.02 ± 0.01 0.90 ± 0.01 1.17 ± 0.03
    P 0.503 0.162 0.022 0.232 0.001 0.703 0.417
rs174601
    CC 4.39 ± 0.18 1.22 (0.88) 1.37 ± 0.06 2.50 ± 0.14 1.15 ± 0.03 0.87 ± 0.04 1.27 ± 0.09
    CT 4.51 ± 0.08 1.35 (0.97) 1.23 ± 0.03 2.70 ± 0.07 1.01 ± 0.02 0.89 ± 0.02 1.13 ± 0.04
    TT 4.56 ± 0.07 1.36 (0.92) 1.21 ± 0.02 2.71 ± 0.05 1.02 ± 0.01 0.90 ± 0.01 1.20 ± 0.03
    P 0.642 0.410 0.045 0.349 0.001 0.815 0.226
    TT 4.56 ± 0.07 1.36 (0.92) 1.21 ± 0.02 2.71 ± 0.05 1.02 ± 0.01 0.90 ± 0.01 1.20 ± 0.03
    CC + TC 4.49 ± 0.07 1.32 (0.93) 1.26 ± 0.03 2.66 ± 0.06 1.04 ± 0.01 0.89 ± 0.02 1.15 ± 0.04
    P 0.448 0.816 0.145 0.537 0.305 0.686 0.313
    CC 4.39 ± 0.18 1.22 (0.88) 1.37 ± 0.06 2.50 ± 0.14 1.15 ± 0.03 0.87 ± 0.04 1.27 ± 0.09
    TT + TC 4.54 ± 0.05 1.36 (0.92) 1.22 ± 0.02 2.70 ± 0.04 1.02 ± 0.01 0.90 ± 0.01 1.17 ± 0.03
    P 0.407 0.245 0.017 0.149 < 0.001 0.547 0.319
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TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; ApoAI, apolipoprotein AI; ApoB, apolipoprotein B. The value of triglyceride was presented as median (interquartile range) and used Nonparametric Test.

Discussion

Serum concentrations of TC, LDL-C, HDL-C, and TG are one of the most important risk factors for atherosclerosis related diseases and are targets for therapeutic intervention [37]. With the rapid progress in genome-wide association (GWA) studies, a number of novel lipid-related loci have been identified [24,25]. Several SNPs in the FADS1/FADS2 gene cluster have been reported to be associated with lipid metabolism, suggesting that altered desaturase activities may impact serum lipoprotein levels [14,21,24,25]. However, not all researches have consistent findings. In a meta-analysis, Teslovich et al. [24] reported that the T allele of rs174546 was associated with lower concentrations of HDL-C and LDL-C and higher TG concentrations in European ancestry. In the Doetinchem Cohort Study, Lu et al. [38] found that TC concentrations differed significantly according to the rs174546 genotype. The C allele of rs174546 was associated with higher TC. Additionally, Sone et al. [39] reported that the rs174546 TT genotype was found to be associated with lower LDL-C levels and a lower LDL-C/TC ratio, and the TT genotype reduced the risk of high LDL-C level in Japanese men aged 40-60. In the Chinese middle-east populations, Liu et al. [18] reported that the FADS1 rs174547 SNP, which was completed LD with rs174546 SNP, the subjects with CC/TC genotypes had significantly higher TG and lower HDL-C concentrations in individuals with average age of 40-50 years old than the subjects with TT genotype. Zhang et al. [40] also found that the T allele of rs174546 marginally associated with TG, with same effect direction to that in Europeans. In contrast, in the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, Bokor et al. [14] found that some FADS1/FADS2 variants, including the rs174546 SNP, were not associated with serum lipid and lipoprotein concentrations in European adolescents. In the present study, our study showed that no association was observed between the SNPs of rs174546 and rs174601 and serum lipid levels in controls. However, after correction for multiple testing, the subjects with rs174601 TT genotype had lower TC, HDL-C and ApoAI levels than the subjects with CC/TC genotypes in CAD patients. The subjects with the rs174546 or rs174601 T allele carriers had lower HDL-C and ApoAI levels than the subjects with non-carriers in IS patients, which inferred that the rs174546 SNP and the rs174601 SNP were likely to influence serum lipid levels. Carrying T allele carriers of the two SNPs and rs174601 TT genotype were associated with decreased serum HDL-C and ApoAI and with an increased risk of CAD and IS. Our results were partly consistent with previous studies. Reasons for these diverse findings remain unclear; one of the possible explanations was based on different genetic background. In our study, the T allele and TT genotype frequencies of the two SNPs were more predominant than the C allele and CC genotype frequencies, which somewhat differed with the data from the data of the International HapMap project: the C and T allele frequencies of rs174546 SNP were 65.9% and 34.1% in CEU (Utah residents with ancestry from northern and western Europe); 98.7% and 1.3% in YRI (Yoruba in Ibadan, Nigeria); 69.8% and 30.2% in JPT (Japanese in Tokyo, Japan); 67.3% and 32.7% in CHB (Han Chinese in Beijing, China); 45.9% and 54.1% in CAD (Chinese in Metropolitan Denver, Colorado). In the previous studies, the C allele frequencies of rs174546 SNP was predominant, which was inconsistent with our study. Another possible explanation was dietary intervention. Dietary habits may differ in different regions, especially dietary LC-PUFAs intake, which could confound the association between the SNPs in this gene cluster and serum lipid levels. In agreement with this hypothesis, AlSaleh et al. [41] recently observed that after the 1.8 g/day eicosapentaenoic acid (20: 5n-3, EPA) and docosahexaenoic acid (22: 6n-3, DHA), TG concentration decreased significantly more in rs174546 T allele carriers than in non-carriers. Thirdly, the participants, especially the individuals with CAD and IS, might have received statins therapies to influence the lipid metabolism. Therefore, the results might not truly reflect the situation of lipids in CAD and IS patients.

In the present study, we showed that the rs174546 and rs174601 T alleles were associated with a higher risk of CAD and IS, suggesting a positive association between the T allele of the two SNPs and CAD and IS. Multivariate analysis also showed that well-known risk factors, such as BMI, diabetes, hypertension and hyperlipidemia, were independently associated with CAD and IS. Additionally, the rs174546 and rs174601 C allele carriers had lower risk of CAD and IS than non-carriers. In our study, we found that the rs174546 SNP and the rs174601 SNP existed in strong LD. Haplotypes analyses suggested that the haplotype of T-T (rs174546-rs174601) was associated with an increased risk of IS. Meanwhile, the haplotype of C-C (rs174546-rs174601) was associated with a decreased risk of CAD and IS after adjusting for potential confounding factors. Previous studies showed that the rs174546 T allele is located within a microRNA target site and is associated with lower FADS1 mRNA levels in human liver [24]. What’s more, all haplotypes carrying rs174546 T allele were associated with lower arachidonic acid (ARA; C20: 4n-6) levels and lower D5D activity [14], suggesting that the rs174546 SNP might be either functional or in LD with other functional SNPs and influence FADS1/FADS2 transcript abundance. Recently published studies reported that the rs965867 SNP in the 5’ UTR of FADS2, recently demonstrated to be functional, was in strong LD with rs174546 SNP [14,24,33] and influenced FADS2 transcription [42]. The rs3834458 [T/del] in upstream region of FADS2, was also reported to be in strong LD with rs174546 SNP, had mostly associations with the level of the direct precursor of inflammatory eicosanoids [35]. The rs174547 SNP in intron region of FADS1 was in complete LD with rs174546 SNP, and had been found to associate with FADS1 transcript levels in the human liver [25]. These associated SNPs modulates expression of FADS1/FADS2 [25], which affect desaturase activity, as a result, leading to lower LC-PUFAs levels that might be prone to a proinflammatory response favoring atherosclerotic vascular damage [14,18]. However, the effects of SNPs in the FADS1/FADS2 gene cluster on risk of CAD and IS were an extremely complex process. In the Malmö Diet and Cancer (MDC) cohort study, Hellstrand et al. [43] have not observed any statistically significant association between rs174546 and risk of CAD and IS, but a borderline interaction was observed between the a-linolenic acid (ALA) (18: 3n-3)-to-linoleic acid (LA) (18: 2n-6) intake ratio and FADS1 genotype on CAD incidence. Likewise, they also observed a significant interaction between ALA and FADS1 genotype on IS incidence, suggesting the associated effects of SNPs in the FADS gene cluster on incident CAD and IS may be modified by dietary PUFAs intakes, and the health benefit of dietary PUFAs may depend on individual FADS1/FADS2 genotypes.

In the present study, we further investigated the association between the SNPs of rs174546 and rs174601 and angiographic severity of CAD. Consequently, we failed to found their relationship, which indicated that the pathogenic effects of this gene cluster were unlikely to be a major pathway for lower CAD and IS risk, but subtle effects cannot be excluded.

This study has two potential limitations. First, the drug information was not available in some participants, thus the effect of drugs or treatments could not be analyzed or excluded. The patient groups had lower levels of serum TC, HDL-C than the healthy controls, which was possibly related to taking cholesterol-lowering medications in the patient groups. Second, although we found that the two SNPs were associated with serum lipid levels and risk of CAD and IS, we did not explore an association between the two SNPs and the desaturase activities, which are important for the further functional evaluation.

In conclusion, The present study firstly report that the rs174601SNP is associated with risk of CAD and IS, and confirm that the T allele and TT genotype frequencies of the rs174546 SNP and rs174601 SNP are predominant in Chinese south population. The T allele, haplotype of T-T are associated with increased risk of CAD and IS. Correspondingly, carrying C allele, haplotype of C-C are associated with reduced risk of CAD and IS. The two SNPs are likely to influence serum lipid levels. Carrying T allele carriers and rs174601 TT genotype are associated with decreased serum HDL-C and ApoAI in the patients groups and with an increased risk of CAD and IS. Further functional investigations are needed to clarify whether the two SNPs are functional or not and how they actually affect the serum lipid levels and risk of CAD and IS.

Acknowledgements

This study was supported by the National Natural Science Foundation of China (No. 30960130), the Science Foundation of Guangxi Returned Oversea Scholars (No. 0991004) and the Innovation Project of Guangxi Graduate Education (No. YCBZ2013013).

Disclosure of conflict of interest

None.

References

  • 1.Ruff CT, Braunwald E. The evolving epidemiology of acute coronary syndromes. Nat Rev Cardiol. 2011;8:140–147. doi: 10.1038/nrcardio.2010.199. [DOI] [PubMed] [Google Scholar]
  • 2.Strong K, Mathers C, Bonita R. Preventing stroke: saving lives around the world. Lancet Neurol. 2007;6:182–187. doi: 10.1016/S1474-4422(07)70031-5. [DOI] [PubMed] [Google Scholar]
  • 3.Murray CJ, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud C, Ezzati M, Shibuya K, Salomon JA, Abdalla S, Aboyans V, Abraham J, Ackerman I, Aggarwal R, Ahn SY, Ali MK, Alvarado M, Anderson HR, Anderson LM, Andrews KG, Atkinson C, Baddour LM, Bahalim AN, Barker-Collo S, Barrero LH, Bartels DH, Basanez MG, Baxter A, Bell ML, Benjamin EJ, Bennett D, Bernabe E, Bhalla K, Bhandari B, Bikbov B, Bin Abdulhak A, Birbeck G, Black JA, Blencowe H, Blore JD, Blyth F, Bolliger I, Bonaventure A, Boufous S, Bourne R, Boussinesq M, Braithwaite T, Brayne C, Bridgett L, Brooker S, Brooks P, Brugha TS, Bryan-Hancock C, Bucello C, Buchbinder R, Buckle G, Budke CM, Burch M, Burney P, Burstein R, Calabria B, Campbell B, Canter CE, Carabin H, Carapetis J, Carmona L, Cella C, Charlson F, Chen H, Cheng AT, Chou D, Chugh SS, Coffeng LE, Colan SD, Colquhoun S, Colson KE, Condon J, Connor MD, Cooper LT, Corriere M, Cortinovis M, de Vaccaro KC, Couser W, Cowie BC, Criqui MH, Cross M, Dabhadkar KC, Dahiya M, Dahodwala N, Damsere-Derry J, Danaei G, Davis A, De Leo D, Degenhardt L, Dellavalle R, Delossantos A, Denenberg J, Derrett S, Des Jarlais DC, Dharmaratne SD, Dherani M, Diaz-Torne C, Dolk H, Dorsey ER, Driscoll T, Duber H, Ebel B, Edmond K, Elbaz A, Ali SE, Erskine H, Erwin PJ, Espindola P, Ewoigbokhan SE, Farzadfar F, Feigin V, Felson DT, Ferrari A, Ferri CP, Fevre EM, Finucane MM, Flaxman S, Flood L, Foreman K, Forouzanfar MH, Fowkes FG, Fransen M, Freeman MK, Gabbe BJ, Gabriel SE, Gakidou E, Ganatra HA, Garcia B, Gaspari F, Gillum RF, Gmel G, Gonzalez-Medina D, Gosselin R, Grainger R, Grant B, Groeger J, Guillemin F, Gunnell D, Gupta R, Haagsma J, Hagan H, Halasa YA, Hall W, Haring D, Haro JM, Harrison JE, Havmoeller R, Hay RJ, Higashi H, Hill C, Hoen B, Hoffman H, Hotez PJ, Hoy D, Huang JJ, Ibeanusi SE, Jacobsen KH, James SL, Jarvis D, Jasrasaria R, Jayaraman S, Johns N, Jonas JB, Karthikeyan G, Kassebaum N, Kawakami N, Keren A, Khoo JP, King CH, Knowlton LM, Kobusingye O, Koranteng A, Krishnamurthi R, Laden F, Lalloo R, Laslett LL, Lathlean T, Leasher JL, Lee YY, Leigh J, Levinson D, Lim SS, Limb E, Lin JK, Lipnick M, Lipshultz SE, Liu W, Loane M, Ohno SL, Lyons R, Mabweijano J, MacIntyre MF, Malekzadeh R, Mallinger L, Manivannan S, Marcenes W, March L, Margolis DJ, Marks GB, Marks R, Matsumori A, Matzopoulos R, Mayosi BM, McAnulty JH, McDermott MM, McGill N, McGrath J, Medina-Mora ME, Meltzer M, Mensah GA, Merriman TR, Meyer AC, Miglioli V, Miller M, Miller TR, Mitchell PB, Mock C, Mocumbi AO, Moffitt TE, Mokdad AA, Monasta L, Montico M, Moradi-Lakeh M, Moran A, Morawska L, Mori R, Murdoch ME, Mwaniki MK, Naidoo K, Nair MN, Naldi L, Narayan KM, Nelson PK, Nelson RG, Nevitt MC, Newton CR, Nolte S, Norman P, Norman R, O’Donnell M, O’Hanlon S, Olives C, Omer SB, Ortblad K, Osborne R, Ozgediz D, Page A, Pahari B, Pandian JD, Rivero AP, Patten SB, Pearce N, Padilla RP, Perez-Ruiz F, Perico N, Pesudovs K, Phillips D, Phillips MR, Pierce K, Pion S, Polanczyk GV, Polinder S, Pope CA 3rd, Popova S, Porrini E, Pourmalek F, Prince M, Pullan RL, Ramaiah KD, Ranganathan D, Razavi H, Regan M, Rehm JT, Rein DB, Remuzzi G, Richardson K, Rivara FP, Roberts T, Robinson C, De Leon FR, Ronfani L, Room R, Rosenfeld LC, Rushton L, Sacco RL, Saha S, Sampson U, Sanchez-Riera L, Sanman E, Schwebel DC, Scott JG, Segui-Gomez M, Shahraz S, Shepard DS, Shin H, Shivakoti R, Singh D, Singh GM, Singh JA, Singleton J, Sleet DA, Sliwa K, Smith E, Smith JL, Stapelberg NJ, Steer A, Steiner T, Stolk WA, Stovner LJ, Sudfeld C, Syed S, Tamburlini G, Tavakkoli M, Taylor HR, Taylor JA, Taylor WJ, Thomas B, Thomson WM, Thurston GD, Tleyjeh IM, Tonelli M, Towbin JA, Truelsen T, Tsilimbaris MK, Ubeda C, Undurraga EA, van der Werf MJ, van Os J, Vavilala MS, Venketasubramanian N, Wang M, Wang W, Watt K, Weatherall DJ, Weinstock MA, Weintraub R, Weisskopf MG, Weissman MM, White RA, Whiteford H, Wiebe N, Wiersma ST, Wilkinson JD, Williams HC, Williams SR, Witt E, Wolfe F, Woolf AD, Wulf S, Yeh PH, Zaidi AK, Zheng ZJ, Zonies D, Lopez AD, AlMazroa MA, Memish ZA. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2197–2223. doi: 10.1016/S0140-6736(12)61689-4. [DOI] [PubMed] [Google Scholar]
  • 4.Fruchart JC, Nierman MC, Stroes ES, Kastelein JJ, Duriez P. New risk factors for atherosclerosis and patient risk assessment. Circulation. 2004;109:III15–19. doi: 10.1161/01.CIR.0000131513.33892.5b. [DOI] [PubMed] [Google Scholar]
  • 5.Sampath H, Ntambi JM. Polyunsaturated fatty acid regulation of genes of lipid metabolism. Annu Rev Nutr. 2005;25:317–340. doi: 10.1146/annurev.nutr.25.051804.101917. [DOI] [PubMed] [Google Scholar]
  • 6.Glaser C, Lattka E, Rzehak P, Steer C, Koletzko B. Genetic variation in polyunsaturated fatty acid metabolism and its potential relevance for human development and health. Matern Child Nutr. 2011;7(Suppl 2):27–40. doi: 10.1111/j.1740-8709.2011.00319.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Mozaffarian D, Wu JH. Omega-3 fatty acids and cardiovascular disease: effects on risk factors, molecular pathways, and clinical events. J Am Coll Cardiol. 2011;58:2047–2067. doi: 10.1016/j.jacc.2011.06.063. [DOI] [PubMed] [Google Scholar]
  • 8.Harris WS, Bulchandani D. Why do omega-3 fatty acids lower serum triglycerides? Curr Opin Lipidol. 2006;17:387–393. doi: 10.1097/01.mol.0000236363.63840.16. [DOI] [PubMed] [Google Scholar]
  • 9.Hein GJ, Bernasconi AM, Montanaro MA, Pellon-Maison M, Finarelli G, Chicco A, Lombardo YB, Brenner RR. Nuclear receptors and hepatic lipidogenic enzyme response to a dyslipidemic sucrose-rich diet and its reversal by fish oil n-3 polyunsaturated fatty acids. Am J Physiol Endocrinol Metab. 2010;298:E429–439. doi: 10.1152/ajpendo.00513.2009. [DOI] [PubMed] [Google Scholar]
  • 10.Nakamura K, Kariyazono H, Komokata T, Hamada N, Sakata R, Yamada K. Influence of preoperative administration of omega-3 fatty acid-enriched supplement on inflammatory and immune responses in patients undergoing major surgery for cancer. Nutrition. 2005;21:639–649. doi: 10.1016/j.nut.2005.03.001. [DOI] [PubMed] [Google Scholar]
  • 11.Rizza S, Tesauro M, Cardillo C, Galli A, Iantorno M, Gigli F, Sbraccia P, Federici M, Quon MJ, Lauro D. Fish oil supplementation improves endothelial function in normoglycemic offspring of patients with type 2 diabetes. Atherosclerosis. 2009;206:569–574. doi: 10.1016/j.atherosclerosis.2009.03.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Haberka M, Mizia-Stec K, Mizia M, Janowska J, Gieszczyk K, Chmiel A, Zahorska-Markiewicz B, Gasior Z. N-3 polyunsaturated fatty acids early supplementation improves ultrasound indices of endothelial function, but not through NO inhibitors in patients with acute myocardial infarction: N-3 PUFA supplementation in acute myocardial infarction. Clin Nutr. 2011;30:79–85. doi: 10.1016/j.clnu.2010.07.011. [DOI] [PubMed] [Google Scholar]
  • 13.Nakamura MT, Nara TY. Structure, function, and dietary regulation of delta6, delta5, and delta9 desaturases. Annu Rev Nutr. 2004;24:345–376. doi: 10.1146/annurev.nutr.24.121803.063211. [DOI] [PubMed] [Google Scholar]
  • 14.Bokor S, Dumont J, Spinneker A, Gonzalez-Gross M, Nova E, Widhalm K, Moschonis G, Stehle P, Amouyel P, De Henauw S, Molnar D, Moreno LA, Meirhaeghe A, Dallongeville J. Single nucleotide polymorphisms in the FADS gene cluster are associated with delta-5 and delta-6 desaturase activities estimated by serum fatty acid ratios. J Lipid Res. 2010;51:2325–2333. doi: 10.1194/jlr.M006205. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Stoffel W, Holz B, Jenke B, Binczek E, Gunter RH, Kiss C, Karakesisoglou I, Thevis M, Weber AA, Arnhold S, Addicks K. Delta6-desaturase (FADS2) deficiency unveils the role of omega3- and omega6-polyunsaturated fatty acids. EMBO J. 2008;27:2281–2292. doi: 10.1038/emboj.2008.156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Lu Y, Vaarhorst A, Merry AH, Dolle ME, Hovenier R, Imholz S, Schouten LJ, Heijmans BT, Muller M, Slagboom PE, van den Brandt PA, Gorgels AP, Boer JM, Feskens EJ. Markers of endogenous desaturase activity and risk of coronary heart disease in the CAREMA cohort study. PLoS One. 2012;7:e41681. doi: 10.1371/journal.pone.0041681. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Malerba G, Schaeffer L, Xumerle L, Klopp N, Trabetti E, Biscuola M, Cavallari U, Galavotti R, Martinelli N, Guarini P, Girelli D, Olivieri O, Corrocher R, Heinrich J, Pignatti PF, Illig T. SNPs of the FADS gene cluster are associated with polyunsaturated fatty acids in a cohort of patients with cardiovascular disease. Lipids. 2008;43:289–299. doi: 10.1007/s11745-008-3158-5. [DOI] [PubMed] [Google Scholar]
  • 18.Liu SJ, Zhi H, Chen PZ, Chen W, Lu F, Ma GS, Dai JC, Shen C, Liu NF, Hu ZB, Wang H, Shen HB. Fatty acid desaturase 1 polymorphisms are associated with coronary heart disease in a Chinese population. Chin Med J (Engl) 2012;125:801–806. [PubMed] [Google Scholar]
  • 19.Qin L, Sun L, Ye L, Shi J, Zhou L, Yang J, Du B, Song Z, Yu Y, Xie L. A case-control study between the gene polymorphisms of polyunsaturated fatty acids metabolic rate-limiting enzymes and coronary artery disease in a Chinese Han population. Prostaglandins Leukot Essent Fatty Acids. 2011;85:329–333. doi: 10.1016/j.plefa.2011.08.007. [DOI] [PubMed] [Google Scholar]
  • 20.Martinelli N, Girelli D, Malerba G, Guarini P, Illig T, Trabetti E, Sandri M, Friso S, Pizzolo F, Schaeffer L, Heinrich J, Pignatti PF, Corrocher R, Olivieri O. FADS genotypes and desaturase activity estimated by the ratio of arachidonic acid to linoleic acid are associated with inflammation and coronary artery disease. Am J Clin Nutr. 2008;88:941–949. doi: 10.1093/ajcn/88.4.941. [DOI] [PubMed] [Google Scholar]
  • 21.Kwak JH, Paik JK, Kim OY, Jang Y, Lee SH, Ordovas JM, Lee JH. FADS gene polymorphisms in Koreans: association with omega6 polyunsaturated fatty acids in serum phospholipids, lipid peroxides and coronary artery disease. Atherosclerosis. 2011;214:94–100. doi: 10.1016/j.atherosclerosis.2010.10.004. [DOI] [PubMed] [Google Scholar]
  • 22.Harris WS, Poston WC, Haddock CK. Tissue n-3 and n-6 fatty acids and risk for coronary heart disease events. Atherosclerosis. 2007;193:1–10. doi: 10.1016/j.atherosclerosis.2007.03.018. [DOI] [PubMed] [Google Scholar]
  • 23.Li SW, Lin K, Ma P, Zhang ZL, Zhou YD, Lu SY, Zhou X, Liu SM. FADS gene polymorphisms confer the risk of coronary artery disease in a Chinese Han population through the altered desaturase activities: based on high-resolution melting analysis. PLoS One. 2013;8:e55869. doi: 10.1371/journal.pone.0055869. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee JY, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O’Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, Konig IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Janssens AC, Ingelsson E, Igl W, Kees Hovingh G, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Doring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor HA Jr, Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, Kathiresan S. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–713. doi: 10.1038/nature09270. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Kathiresan S, Willer CJ, Peloso GM, Demissie S, Musunuru K, Schadt EE, Kaplan L, Bennett D, Li Y, Tanaka T, Voight BF, Bonnycastle LL, Jackson AU, Crawford G, Surti A, Guiducci C, Burtt NP, Parish S, Clarke R, Zelenika D, Kubalanza KA, Morken MA, Scott LJ, Stringham HM, Galan P, Swift AJ, Kuusisto J, Bergman RN, Sundvall J, Laakso M, Ferrucci L, Scheet P, Sanna S, Uda M, Yang Q, Lunetta KL, Dupuis J, de Bakker PI, O’Donnell CJ, Chambers JC, Kooner JS, Hercberg S, Meneton P, Lakatta EG, Scuteri A, Schlessinger D, Tuomilehto J, Collins FS, Groop L, Altshuler D, Collins R, Lathrop GM, Melander O, Salomaa V, Peltonen L, Orho-Melander M, Ordovas JM, Boehnke M, Abecasis GR, Mohlke KL, Cupples LA. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet. 2009;41:56–65. doi: 10.1038/ng.291. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Chen Q, Reis SE, Kammerer CM, McNamara DM, Holubkov R, Sharaf BL, Sopko G, Pauly DF, Merz CN, Kamboh MI. Association between the severity of angiographic coronary artery disease and paraoxonase gene polymorphisms in the National Heart, Lung, and Blood Institute-sponsored Women’s Ischemia Syndrome Evaluation (WISE) study. Am J Hum Genet. 2003;72:13–22. doi: 10.1086/345312. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Xu Y, Wang W, Zhang L, Qi LP, Li LY, Chen LF, Fang Q, Dang AM, Yan XW. A polymorphism in the ABCG1 promoter is functionally associated with coronary artery disease in a Chinese Han population. Atherosclerosis. 2011;219:648–654. doi: 10.1016/j.atherosclerosis.2011.05.043. [DOI] [PubMed] [Google Scholar]
  • 28.Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J, Love BB, Gordon DL, Marsh EE 3rd. Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment. Stroke. 1993;24:35–41. doi: 10.1161/01.str.24.1.35. [DOI] [PubMed] [Google Scholar]
  • 29.Wu DF, Yin RX, Hu XJ, Aung LH, Cao XL, Miao L, Li Q, Yan TT, Wu JZ, Pan SL. Association of rs5888 SNP in the scavenger receptor class B type 1 gene and serum lipid levels. Lipids Health Dis. 2012;11:50. doi: 10.1186/1476-511X-11-50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Wu DF, Yin RX, Yan TT, Aung LH, Cao XL, Miao L, Li Q, Hu XJ, Wu JZ, Liu CW. The SCARB1 rs5888 SNP and serum lipid levels in the Guangxi Mulao and Han populations. Int J Med Sci. 2012;9:715–724. doi: 10.7150/ijms.4815. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Wu DF, Yin RX, Cao XL, Chen WX, Aung LH, Wang W, Huang KK, Huang P, Zeng XN, Wu J. Scavenger receptor class B type 1 gene rs5888 single nucleotide polymorphism and the risk of coronary artery disease and ischemic stroke: a case-control study. Int J Med Sci. 2013;10:1771–1777. doi: 10.7150/ijms.7044. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Huang KK, Yin RX, Zeng XN, Huang P, Lin QZ, Wu J, Guo T, Wang W, Yang DZ, Lin WX. Association of the rs7395662 SNP in the MADD-FOLH1 and several environmental factors with serum lipid levels in the Mulao and Han populations. Int J Med Sci. 2013;10:1537–1546. doi: 10.7150/ijms.6421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Chalmers J, MacMahon S, Mancia G, Whitworth J, Beilin L, Hansson L, Neal B, Rodgers A, Ni Mhurchu C, Clark T. 1999 World Health Organization-International Society of Hypertension Guidelines for the management of hypertension. Guidelines sub-committee of the World Health Organization. Clin Exp Hypertens. 1999;21:1009–1060. doi: 10.3109/10641969909061028. [DOI] [PubMed] [Google Scholar]
  • 34.Zhou BF. Effect of body mass index on all-cause mortality and incidence of cardiovascular diseases--report for meta-analysis of prospective studies open optimal cut-off points of body mass index in Chinese adults. Biomed Environ Sci. 2002;15:245–252. [PubMed] [Google Scholar]
  • 35.Schaeffer L, Gohlke H, Muller M, Heid IM, Palmer LJ, Kompauer I, Demmelmair H, Illig T, Koletzko B, Heinrich J. Common genetic variants of the FADS1 FADS2 gene cluster and their reconstructed haplotypes are associated with the fatty acid composition in phospholipids. Hum Mol Genet. 2006;15:1745–1756. doi: 10.1093/hmg/ddl117. [DOI] [PubMed] [Google Scholar]
  • 36.Shi YY, He L. SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res. 2005;15:97–98. doi: 10.1038/sj.cr.7290272. [DOI] [PubMed] [Google Scholar]
  • 37.Kathiresan S, Manning AK, Demissie S, D’Agostino RB, Surti A, Guiducci C, Gianniny L, Burtt NP, Melander O, Orho-Melander M, Arnett DK, Peloso GM, Ordovas JM, Cupples LA. A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study. BMC Med Genet. 2007;8(Suppl 1):S17. doi: 10.1186/1471-2350-8-S1-S17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Lu Y, Feskens EJ, Dolle ME, Imholz S, Verschuren WM, Muller M, Boer JM. Dietary n-3 and n-6 polyunsaturated fatty acid intake interacts with FADS1 genetic variation to affect total and HDL-cholesterol concentrations in the Doetinchem Cohort Study. Am J Clin Nutr. 2010;92:258–265. doi: 10.3945/ajcn.2009.29130. [DOI] [PubMed] [Google Scholar]
  • 39.Sone Y, Kido T, Ainuki T, Sonoda M, Ichi I, Kodama S, Sone H, Kondo K, Morita Y, Egawa S, Kawahara K, Otsuka Y, Fujiwara Y. Genetic variants of the fatty acid desaturase gene cluster are associated with plasma LDL cholesterol levels in Japanese males. J Nutr Sci Vitaminol (Tokyo) 2013;59:325–335. doi: 10.3177/jnsv.59.325. [DOI] [PubMed] [Google Scholar]
  • 40.Zhang Z, Tao L, Chen Z, Zhou D, Kan M, Zhang D, Li C, He L, Liu Y. Association of genetic loci with blood lipids in the Chinese population. PLoS One. 2011;6:e27305. doi: 10.1371/journal.pone.0027305. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.AlSaleh A, Maniou Z, Lewis FJ, Hall WL, Sanders TA, O’Dell SD. Genetic predisposition scores for dyslipidaemia influence plasma lipid concentrations at baseline, but not the changes after controlled intake of n-3 polyunsaturated fatty acids. Genes Nutr. 2014;9:412. doi: 10.1007/s12263-014-0412-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Lattka E, Eggers S, Moeller G, Heim K, Weber M, Mehta D, Prokisch H, Illig T, Adamski J. A common FADS2 promoter polymorphism increases promoter activity and facilitates binding of transcription factor ELK1. J Lipid Res. 2010;51:182–191. doi: 10.1194/jlr.M900289-JLR200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Hellstrand S, Ericson U, Gullberg B, Hedblad B, Orho-Melander M, Sonestedt E. Genetic variation in FADS1 has little effect on the association between dietary PUFA intake and cardiovascular disease. J Nutr. 2014;144:1356–1363. doi: 10.3945/jn.114.192708. [DOI] [PMC free article] [PubMed] [Google Scholar]

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