Literature DB >> 22911844

Markers of endogenous desaturase activity and risk of coronary heart disease in the CAREMA cohort study.

Yingchang Lu1, Anika Vaarhorst, Audrey H H Merry, Martijn E T Dollé, Robert Hovenier, Sandra Imholz, Leo J Schouten, Bastiaan T Heijmans, Michael Müller, P Eline Slagboom, Piet A van den Brandt, Anton P M Gorgels, Jolanda M A Boer, Edith J M Feskens.   

Abstract

BACKGROUND: Intakes of n-3 polyunsaturated fatty acids (PUFAs), especially EPA (C20:5n-3) and DHA (C22:6n-3), are known to prevent fatal coronary heart disease (CHD). The effects of n-6 PUFAs including arachidonic acid (C20:4n-6), however, remain unclear. δ-5 and δ-6 desaturases are rate-limiting enzymes for synthesizing long-chain n-3 and n-6 PUFAs. C20:4n-6 to C20:3n-6 and C18:3n-6 to C18:2n-6 ratios are markers of endogenous δ-5 and δ-6 desaturase activities, but have never been studied in relation to incident CHD. Therefore, the aim of this study was to investigate the relation between these ratios as well as genotypes of FADS1 rs174547 and CHD incidence.
METHODS: We applied a case-cohort design within the CAREMA cohort, a large prospective study among the general Dutch population followed up for a median of 12.1 years. Fatty acid profile in plasma cholesteryl esters and FADS1 genotype at baseline were measured in a random subcohort (n = 1323) and incident CHD cases (n = 537). Main outcome measures were hazard ratios (HRs) of incident CHD adjusted for major CHD risk factors.
RESULTS: The AA genotype of rs174547 was associated with increased plasma levels of C204n-6, C20:5n-3 and C22:6n-3 and increased δ-5 and δ-6 desaturase activities, but not with CHD risk. In multivariable adjusted models, high baseline δ-5 desaturase activity was associated with reduced CHD risk (P for trend = 0.02), especially among those carrying the high desaturase activity genotype (AA): HR (95% CI) = 0.35 (0.15-0.81) for comparing the extreme quintiles. High plasma DHA levels were also associated with reduced CHD risk.
CONCLUSION: In this prospective cohort study, we observed a reduced CHD risk with an increased C20:4n-6 to C20:3n-6 ratio, suggesting that δ-5 desaturase activity plays a role in CHD etiology. This should be investigated further in other independent studies.

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Year:  2012        PMID: 22911844      PMCID: PMC3402436          DOI: 10.1371/journal.pone.0041681

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Polyunsaturated fatty acids (PUFAs) are generally believed to reduce coronary heart disease (CHD) risk [1], [2], [3], [4]. Intakes of n-3 PUFAs, especially eicosapentaenoic acid (EPA, C205n-3) and docosahexaenoic acid (DHA, C22∶6n-3) present in fish oil, are confirmed to prevent fatal CHD and sudden cardiac death in both observational studies and large-scale randomized controlled trials (RCTs) [1], [3]. However, direct evidence for the preventive effect of n-3 PUFAs on non-fatal CHD was only recently observed in some, but not all, large-scale RCTs [5], [6], [7]. The replacement of saturated fatty acids by n-6 PUFAs protected against incident CHD in a recent meta-analysis including 8 RCTs [8]. As some of these RCTs also included n-3 PUFAs in addition to n-6 PUFAs [2], [8], the effects specific to n-6 PUFAs, however, remain unclear. The fatty acid profile of various biological tissues is often used as a biomarker of dietary fatty acid intake. Adipose tissue reflects the intake of past months to years, while erythrocyte membranes, and plasma or serum phospholipids or cholesteryl esters reflect the intake of several weeks [9], [10], [11]. However, the PUFA profile in biological tissues does not only reflect dietary intake, but is also strongly dependent on the endogenous metabolism of PUFAs [10], [12]. Therefore, PUFA biomarkers in biological tissues mirror the internal PUFA exposure that may be biologically more relevant. Several PUFAs can be endogenously synthesized by a series of alternate desaturation and elongation processes [12], [13]. The δ-5 desaturase and δ-6 desaturase are rate-limiting enzymes for synthesizing long-chain n-3 and n-6 PUFAs (Figure 1) [12], [14], [15], [16]. They are encoded by the FADS1 and FADS2 genes on chromosome 11 (11q12–13.1), respectively [12], [17]. Potential functional genetic variants in these genes have been identified including rs174547 [18], and confirmed in recent genome-wide association studies [19], [20], [21]. They have an impact on FADS1 mRNA abundance [22], [23], [24], [25], [26], and, as a result, on desaturase activity, plasma PUFA levels, and endogenous PUFA pools [18], [19], [20], [21], [26], [27], [28], [29]. Since it is impractical to directly assay the enzyme activities of δ-5 and δ-6 desaturase in humans [12], [14], [15], [29], especially in large-scale epidemiological studies, their activities have traditionally been estimated by using PUFA product-to-precursor ratios [11], [21], [27], [28].
Figure 1

Effect of genotypes of rs174547 on synthesis of PUFAs in the n-3 and n-6 pathways.

Measurements of n-3 and n-6 polyunsaturated fatty acid (PUFA) levels in plasma cholesteryl esters in the sub-cohort of CAREMA study (n = 1246, Table 2). The three bars in each of the smaller plots represent levels of fatty acids (%) in individuals who carry AA, AG and GG genotypes of rs174547, respectively.

Effect of genotypes of rs174547 on synthesis of PUFAs in the n-3 and n-6 pathways.

Measurements of n-3 and n-6 polyunsaturated fatty acid (PUFA) levels in plasma cholesteryl esters in the sub-cohort of CAREMA study (n = 1246, Table 2). The three bars in each of the smaller plots represent levels of fatty acids (%) in individuals who carry AA, AG and GG genotypes of rs174547, respectively.
Table 2

Association of rs174547 in FADS1 with baseline PUFAs in plasma cholesteryl esters and desaturase activities in the sub-cohort (n = 1246)1.

PUFA Rs174547 P value2
AA (545)AG (569)GG (132)
n-6 PUFA
C18∶2n-6 (%)44.30±0.272 44.88±0.2646.60±0.547.48×10−4
C18∶3n-6 (%)0.60±0.0090.48±0.0090.40±0.0196.87×10−28
C20∶3n-6 (%)0.42±0.0050.43±0.0050.44±0.0100.051
C20∶4n-6 (%)4.29±0.053.56±0.052.89±0.093.92×10−46
n-3 PUFA
C18∶3n-3 (%)0.40±0.0050.41±0.0050.45±0.0103.28×10−4
C18∶4n-3 (%)3 0.18±0.0070.18±0.0070.17±0.0140.708
C20∶5n-3 (%)0.56±0.010.46±0.010.40±0.038.71×10−8
C22∶6n-3 (%)0.34±0.0060.31±0.0060.30±0.0130.005
δ-54 10.65±0.098.59±0.096.86±0.196.40×10−85
δ-64 0.014±0.00020.011±0.00020.009±0.00052.51×10−27

77 subjects in the subcohort had missing values for rs174547. PUFAs: polyunsaturated fatty acids.

General linear models were used, and all values are mean ± SEM, adjusted for age and sex.

Only few subjects were successfully measured (AA = 161, AG = 185, and GG = 42).

δ-5 and δ-6 desaturase activities were assessed by the ratio of C20∶4n-6 to C20∶3n-6 and C18∶3n-6 to C18∶2n-6 in plasma cholesteryl esters, respectively.

Although few prospective cohort studies have investigated PUFA biomarkers in relation to the incidence of CHD [30], the relation with PUFA product-to-precursor ratios as markers of desaturase activities has, to the best of our knowledge, never been evaluated. In this prospective cohort study, we therefore aim to investigate whether C204n-6 to C203n-6 and C183n-6 to C182n-6 ratios, as respective markers of δ-5 and δ-6 desaturase activity, influence CHD risk.

Materials and Methods

Study Population

We conducted a case-cohort study within the Monitoring Project on Cardiovascular Disease Risk Factors 1987–1991 [31], one of the two monitoring studies that were included in the Cardiovascular Registry Maastricht (CAREMA) study. The CAREMA study was described in detail before [32], [33]. In total, 12,486 men and women, born between 1927 and 1967 and living in the Maastricht area, participated in the Monitoring Project on Cardiovascular Disease Risk Factors and had given informed consent to retrieve information from the municipal population registries and from the general practitioner and specialist. The Medical Ethics Committee of the Netherlands Organization for Applied Scientific Research (TNO) approved the study protocol and all participants signed an informed consent form.

Cardiological Follow-up

The cardiologic follow-up has been described before [32]. In brief, 97.6% of the CAREMA members could be found by linking the cohort to the hospital information system of University Hospital Maastricht (UHM). They were linked to the cardiology information system of the Department of Cardiology to obtain information about the occurrence of myocardial infarction (MI), unstable angina pectoris (UAP), coronary artery bypass grafting (CABG), or percutanous transluminal coronary angioplasty surgery (PTCA). For participants who died, the cause of death was obtained from Statistics Netherlands. In addition, the CAREMA cohort was linked to the hospital discharge registry of the UHM to increase the completeness of the cardiologic follow-up. Follow-up ended on 31 December 2003 with a median follow-up of 12.1 yrs (range: 0.0–16.9 yrs).

Subcohort and Incident CHD Selection for Case-cohort Design

For the present study, participants who were younger than 30 years at baseline (n = 2204), had a history of MI, UAP, CABG, or PTCA before baseline (n = 118), or were lost to follow-up (n = 2) were excluded. Thus, the eligible cohort consisted of 10,164 participants. All 620 participants who developed incident CHD during follow-up (315 MIs, 244 UAPs and 61 CHD deaths) were included in the case-cohort study. From the eligible cohort, 1483 participants were randomly drawn as a subcohort [34]. By randomly selecting a subcohort and using the specific statistics for this type of research design, the results are expected to be extrapolated to the entire cohort without the need of biomarker measurements in the entire cohort [11], [34], [35], [36].

Risk Factor Determination

At baseline, all participants filled in a questionnaire on life-style characteristics, medical history, and parental history of MI. During a medical examination, information was collected on blood pressure, height, and weight. In addition, non-fasting blood samples were collected using EDTA tubes. The blood was centrifuged for 10 minutes at 1000 rpm and fractioned into blood plasma, white blood cells and erythrocytes and subsequently stored at −20°C. Within three weeks, the plasma samples were transported to the Lipid Reference Laboratory of the University Hospital Dijkzigt (LRL) in Rotterdam where the total and HDL-cholesterol levels were determined using a CHOD-PAP method [37]. The LRL in Rotterdam is a permanent member of the International Cholesterol Reference Method Laboratory Network.

Fatty Acid Determination

Fatty acids from plasma cholesteryl esters were quantified by gas-liquid chromatography between 2010 and 2011 at the Department of Human Nutrition of Wageningen University. The case and non-case samples were evenly distributed among the different batches and the assay sequence within each batch was random. The solid-phase extraction method was used to separate the cholesteryl ester fraction from total plasma lipid extracts. Fatty acid methyl esters were prepared by incubating isolated cholesteryl esters with acidified methanol. Peak retention times and area percentages of total fatty acids were identified by using known cholesteryl ester standards (mixture of FAME components from Sigma (MO) and NuChek (MN)) and analyzed with the Agilent Technologies ChemStation software (Agilent, Amstelveen, The Netherlands). For certain fatty acids, the values were too low to be reliably detected in some subjects, and “0” was assigned to their values. Interassay coefficients of variance in fatty acids in plasma cholesteryl esters were 1.68% for C16∶0, 1.01% for C182n-6, 1.88% for C204n-6, and 5.02% for C22∶6n-3, respectively. Fatty acid product-to-precursor ratios were calculated, i.e. C204n-6 to C203n-6 to reflect δ-5 desaturase activity, and C183n-6 to C182n-6 to reflect δ-6 desaturase activity (Figure 1). The 20 subjects with a “0” value for C203n-6 were not included in the analyses for the C204n-6 to C203n-6 ratio, reflecting δ-5 desaturase activity. Information on plasma fatty acids was available on 1323 subcohort members and 537 CHD cases.

DNA Extraction and Genotyping

DNA was extracted from the white blood cell fraction (buffy coats), using a standard procedure [38]. The resulting DNA pellet was dissolved in TE buffer and DNA concentrations were determined using the Nanodrop ND1000 Spectrophotometer. The single nucleotide polymorphism (SNP) of rs174547 in the FADS1 gene was selected based on its association with blood cholesterol and triglyceride levels in a genome-wide association study [23]. This SNP is in high linkage disequilibrium (D′ = 1 and r 2≥0.8) with several other SNPs around the FADS1 and FADS2 gene region, which have an impact on mRNA abundance of FADS1 [22], [23], [24], [25], desaturase activity, plasma PUFA levels, and endogenous PUFA pools [18], [19], [20], [21], [26], [27], [28], [29]. Rs174547 was genotyped entirely independent of case and non-case status using the iPLEX Gold chemistry of Sequenom’s MassARRAY platform (San Diego, CA) at the Leiden University Medical Center. Sequenom’s MassARRAY® Assay Design 3.1 Software was used for SNP assay design, and Sequenom’s SpectroTyper 4.0 software was used to call genotypes automatically, followed by manual review. The total genotyping success rate was 93%. Among the subjects who were measured for plasma fatty acid levels, information on rs174547 genotype was available for 1246 subcohort members and 492 CHD cases. The genotype distribution was consistent with Hardy-Weinberg equilibrium expectations.

Statistical Analysis

Generalized linear models adjusted for age and sex were used to study the relations of rs174547 genotypes with PUFAs and PUFA ratios. Cox proportional hazards models adapted for the case-cohort design according to the Prentice’s method [35] were used to calculate hazard ratios (HRs) as measures for relative risk [36]. All the major predictors satisfied the proportional hazard assumption (data not shown). We estimated hazard ratios for quintiles of fatty acids (expressed as the percentage of total fatty acids present in the chromatogram) and ratios of C204n-6 to C203n-6 and C183n-6 to C182n-6 based on subcohort distributions, and the respective lowest quintile was used as reference. The base models included age and sex. Additional models were further adjusted for covariates from the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III) risk score based on the Framingham cohort (current smoking, systolic blood pressure, hypertensive medication use, total and HDL cholesterol levels) with the addition of a history of diabetes [39]. The models were also further adjusted for the total percentage of n-3 PUFAs or n-6 PUFAs in plasma cholesteryl esters where necessary. Additional covariates studied were parental history of MI, alcohol use and physical activity. The significance of a linear trend across quintiles of fatty acids and ratios of C204n-6 to C203n-6 and C183n-6 to C182n-6 was examined by including the exposure as a continuous variable in the model. Potential interactions between continuous ratios of C204n-6 to C203n-6 and C183n-6 to C182n-6 and dichotomized rs174547 genotype (homozygous major allele carriers vs. minor allele carriers) were tested by including interaction terms into the model. Statistical significance was considered to be met with a P value <0.05 and all testing was 2-sided. All statistical analyses were performed with SAS version 9.1 software (SAS Institute, Cary, NC).

Results

The general characteristics of the study population by subcohort-case status are shown in Table 1. As expected, cases were older, more frequently male, had higher blood pressure and total cholesterol levels, lower HDL cholesterol levels, smoked more often, and more often reported to have diabetes and a parental history of MI.
Table 1

Baseline characteristics of sub-cohort subjects and cases of incident coronary heart disease in the CAREMA cohort study1.

Subcohort (n = 1323)2 Cases (n = 537)Crude HR (95% CI)3 Adjusted HR (95% CI)4
Age (y)45.2±8.549.7±7.31.07 (1.06–1.09)1.05 (1.04–1.07)
Male sex608 (46.0%)392 (73.0%)3.34 (2.69–4.15)2.22 (1.66–2.99)
Total cholesterol (mmol/L)5.7±1.16.4±1.21.71 (1.56–1.87)1.42 (1.26–1.60)
HDL cholesterol (mmol/L)1.2±0.31.0±0.20.04 (0.03–0.06)0.09 (0.05–0.16)
Systolic blood pressure (mmHg)119.2±14.9128.0±16.91.03 (1.02–1.04)1.02 (1.01–1.03)
Hypertensive medication use67 (5.1%)58 (10.8%)2.34 (1.63–3.35)1.27 (0.79–2.05)
Diabetes mellitus13 (1.0%)20 (3.7%)5.33 (2.74–10.36)2.83 (1.39–5.78)
Current smoking551 (41.8%)304 (56.7%)1.81 (1.49–2.21)1.72 (1.33–2.22)
Parental history of MI452 (34.3%)228 (42.5%)1.40 (1.14–1.71)1.51 (1.16–1.95)

Data are expressed as mean ± SD or n (%) unless otherwise indicated. HDL: high-density lipoprotein; MI: myocardial infarction; and HR (95% CI): hazard ratio and 95% confidence interval.

Including 84 cases.

Hazard ratios were calculated per unit increase in total cholesterol, HDL cholesterol, and systolic blood pressure, and for the presence of the categorical traits.

All variables were added into one multivariable Cox proportional hazards model.

Data are expressed as mean ± SD or n (%) unless otherwise indicated. HDL: high-density lipoprotein; MI: myocardial infarction; and HR (95% CI): hazard ratio and 95% confidence interval. Including 84 cases. Hazard ratios were calculated per unit increase in total cholesterol, HDL cholesterol, and systolic blood pressure, and for the presence of the categorical traits. All variables were added into one multivariable Cox proportional hazards model. Carrying the minor G allele of rs174547 was associated with higher levels of substrates for desaturases (C182n-6, C203n-6, and C18∶3n-3) and lower levels of products from desaturases (C183n-6, C204n-6, C205n-3, and C22∶6n-3) in the plasma cholesteryl esters. Consequently, lower C204n-6 to C203n-6 and C183n-6 to C182n-6 ratios, as markers of δ-5 and δ-6 desaturase activity, respectively, were observed in carriers of the G allele as compared to those with the AA genotype (Table 2 and Figure 1). 77 subjects in the subcohort had missing values for rs174547. PUFAs: polyunsaturated fatty acids. General linear models were used, and all values are mean ± SEM, adjusted for age and sex. Only few subjects were successfully measured (AA = 161, AG = 185, and GG = 42). δ-5 and δ-6 desaturase activities were assessed by the ratio of C204n-6 to C203n-6 and C183n-6 to C182n-6 in plasma cholesteryl esters, respectively. A high baseline C204n-6 to C203n-6 ratio was associated with reduced CHD risk (Table 3). A 30% reduction in CHD risk was observed among the participants in the second, third, fourth and fifth quintile of C204n-6 to C203n-6 ratio compared with those in the first quintile after adjustment for age, sex, systolic blood pressure, hypertensive medication use, current smoking, diabetes, total cholesterol, and high-density lipoprotein cholesterol (P for trend = 0.02). Although the statistical interaction between rs174547 and δ-5 desaturase activity was not significant (P = 0.56), the protective effect of high δ-5 desaturase activity was mainly confined to subjects with the AA genotype (Table S1). In this group, the effect was stronger with a 65% risk reduction for the subjects in the fifth quintile compared with the first quintile (P for trend = 0.02). Rs174547 itself was not associated with CHD risk, the age- and sex-adjusted HR per G-allele being 0.99 (95% CI 0.84–1.16, Table S2).
Table 3

Association between baseline δ-5 and δ-6 desaturase activity and incident coronary heart disease (CHD).

Quintile of δ-5 desaturase activity1 P value for trend2
First (6.45)Second (7.93)Third (9.07)Fourth (10.32)Fifth (12.52)
Incident CHD, n155117949367
Model 13 10.70 (0.51–0.97)0.60 (0.42–0.83)0.60 (0.43–0.83)0.49 (0.34–0.70)<0.0001
Model 24 10.75 (0.54–1.06)0.66 (0.46–0.94)0.57 (0.39–0.82)0.51 (0.35–0.75)<0.0001
Model 35 10.68 (0.47–0.98)0.66 (0.45–0.96)0.69 (0.46–1.01)0.68 (0.45–1.02)0.0249
Model 46 10.71 (0.49–1.03)0.70 (0.48–1.04)0.74 (0.50–1.09)0.77 (0.50–1.18)0.1114
Quintile of δ-6 desaturase activity 1 P value for trend 2
First (0.0055) Second (0.0084) Third (0.0104) Fourth (0.0132) Fifth (0.019)
Incident CHD, n 92 99 93 122 131
Model 13 10.99 (0.69–1.42)0.87 (0.60–1.25)1.09 (0.76–1.55)1.03 (0.73–1.45)0.606
Model 24 11.03 (0.70–1.51)0.89 (0.61–1.31)1.07 (0.73–1.58)0.93 (0.63–1.36)0.627
Model 35 11.07 (0.71–1.63)0.86 (0.55–1.33)1.11 (0.73–1.69)0.96 (0.63–1.47)0.897

δ-5 and δ-6 desaturase activities were assessed by the ratio of C20∶4n-6 to C20∶3n-6 and the ratio of C18∶3n-6 to C18∶2n-6 in plasma cholesteryl esters, respectively and median ratios in each quintile are listed between brackets.

From models with desaturase activity included as a continuous variable.

Model 1 was adjusted for age and sex.

Model 2 was adjusted for age, sex, systolic blood pressure, hypertensive medication use, current smoking, and diabetes.

Model 3 was adjusted for all covariates in model 2, total cholesterol, and high-density lipoprotein cholesterol.

Model 4 was adjusted for all covariates in model 3 and percentages of C22∶6n-3 (DHA) in plasma cholesteryl esters.

δ-5 and δ-6 desaturase activities were assessed by the ratio of C204n-6 to C203n-6 and the ratio of C183n-6 to C182n-6 in plasma cholesteryl esters, respectively and median ratios in each quintile are listed between brackets. From models with desaturase activity included as a continuous variable. Model 1 was adjusted for age and sex. Model 2 was adjusted for age, sex, systolic blood pressure, hypertensive medication use, current smoking, and diabetes. Model 3 was adjusted for all covariates in model 2, total cholesterol, and high-density lipoprotein cholesterol. Model 4 was adjusted for all covariates in model 3 and percentages of C22∶6n-3 (DHA) in plasma cholesteryl esters. No association was observed between δ-6 desaturase activity and CHD risk (Table 3), also not after stratification by rs174547 genotype (data not shown). The results for the four n-6 PUFAs that determine δ-5 and δ-6 desaturase activity are shown in Table S3. No associations with CHD were observed for the C20 precursor (C203n-6) and product (C204n-6, arachidonic acid) of δ-5 desaturase (Figure 1), or for the C18 precursor (C182n-6, linoleic acid) and product (C183n-6) of δ-6 desaturase (Figure 1) after adjustment for age, sex, systolic blood pressure, hypertensive medication use, current smoking, diabetes, total cholesterol, and high-density lipoprotein cholesterol (P for trend >0.16). Regarding the n-3 PUFAs affected by desaturases, a significant inverse association was observed between C22∶6n-3 (DHA) and CHD risk. This association became stronger after adjustment for plasma total and HDL cholesterol levels, and the percentages of n-6 PUFA in plasma cholesteryl esters (P for trend = 0.027, Table S4). The proportion of plasma C205n-3 (EPA) was not associated with incident CHD (P for trend = 0.724, Table S4). No association was observed between C18∶3n-3 (α-linolenic acid) and CHD risk (data not shown). To explore whether there is any independent effect of C204n-6 to C203n-6 ratio on CHD beyond DHA, we additionally adjusted the models in Table 3 for percentages of DHA. The association between C204n-6 to C203n-6 ratio and CHD risk attenuated, but remained highly significant, especially among the AA carriers of rs174547 (HR:95% CI = 0.44∶0.19–1.04 for comparing the extreme quintiles, Table S1). Additional adjustment for parental history of MI, alcohol use or physical activity did not materially change any of the aforementioned associations (data not shown).

Discussion

In this prospective cohort study, we observed an inverse association between C204n-6 to C203n-6 ratio, as the marker of δ-5 desaturase activity, and incident CHD risk, but no association with C183n-6 to C182n-6 ratio, as the marker of δ-6 desaturase activity. This association was partly mediated by DHA. Furthermore we confirmed associations of rs174547 in the FADS1 gene with plasma PUFA levels and C204n-6 to C203n-6 ratio [18], [19], [20], [21], [27], [28]. Consistent with the established cardiovascular protective effects of n-3 PUFAs [1], [3], and especially tissue DHA [4], [30], high DHA in plasma cholesteryl esters was associated with a reduced CHD risk. However, no association was observed between arachidonic acid or other n-6 PUFAs related to δ-5 or δ-6 desaturase activity in plasma cholesteryl esters and CHD risk. Common genetic variants (including rs174547) in the FADS gene region have been associated with plasma lipid levels (total, LDL and HDL cholesterol, triglycerides, phospholipids and sphingolipids) [19], [21], [23], [40], [41], glycemic traits (fasting glucose and beta-cell function) [26], and resting heart rate [42] in recent genome-wide association studies. However, none of them have been associated with CHD risk directly [40], [43]. This was also the case in our relatively large prospective study. In contrast, when using the estimated δ-5 desaturase activity based on the fatty acid proportion in plasma cholesteryl esters, we found a significant inverse association with incident CHD. This seems contradictory, as a strong association between rs174547 genotypes and estimated δ-5 desaturase activities was observed. However, the reduced risk was already observed with relatively low δ-5 desaturase activities (the second quintile) and remained constant over the following quintiles. Therefore, the majority of the participants with the GG genotype of rs174547 might have sufficient δ-5 desaturase activity to protect them from CHD. This might explain why no association between rs174547 genotypes and CHD risk was found. Both rs174547 genotypes and C204n-6 to C203n-6 ratio reflect endogenous δ-5 desaturase activity, but from two different perspectives. The former can be regarded as the desaturase effect conferred by a single common genetic variant in the FADS1 gene [20], [26], [27], [28], [29], and the latter as an approximate estimation of full desaturase activity [21], [27], [28]. Their combination might provide the most accurate estimate of δ-5 desaturase activity. This might explain the stronger CHD risk reduction with high δ-5 desaturase activity in the subjects who inherited the AA genotype. The exact biological mechanisms that link δ-5 desaturase activity with CHD risk are still not well understood. Arachidonic acid, EPA, and DHA are currently considered to be potentially involved directly in the pathogenesis of CHD through thrombotic, inflammatory, arrhythmic and/or lipid regulatory pathways [1], [3], [12], [13], [44], [45], [46]. δ-5 Desaturase is the key enzyme synthesizing these PUFAs, while δ-6 desaturase is important at the beginning of the n-3 and n-6 PUFA synthetic pathways [14], [15]. Therefore, it is biologically plausible that CHD risk could be influenced by δ-5 desaturase activity, but not by δ-6 desaturase activity [12], [13] as was shown in our data. The non-significance of δ-6 desaturase activity on CHD risk is perhaps, also compatible with the reported normal viability and life span of δ-6 desaturase knockout mice [47]. Increased δ-5 desaturase activity might contribute to the intracellular increase of EPA and especially arachidonic acid levels [16]. In non-fish eating populations, arachidonic acid is the predominant tissue very-long-chain PUFA, reaching 80% of the total very-long-chain PUFA [30], [44]. Despite the potential pro-coagulant and pro-inflammatory effects of increased exposures to arachidonic acid and its derived eicosanoid metabolites [2], [13], [44], [45], [46], [48], [49], there is no evidence of increased CHD risk with ≈ 5–7 times habitual arachidonic acid intake based on short-term small-scale controlled feeding studies [2], [50], [51], [52], [53], [54]. Tissue arachidonic acid levels are generally not associated with CHD risk [30]. This was supported by our finding based on the fatty acid profile in plasma cholesteryl esters, which suggests that arachidonic acid does not mediate the observed association between C204n-6 to C203n-6 ratio, as the marker of δ-5 desaturase activity, and CHD risk. Increased δ-5 desaturase activity (C204n-6 to C203n-6 ratio) was associated with increased plasma levels of EPA and DHA. Our results showed that a possible protective effect of increased δ-5 desaturase activity on CHD may partly be mediated by increased endogenous exposure to DHA. The observation that increased DHA levels associated with increased δ-5 desaturase activity protect against CHD is consistent with the established cardiovascular protective effect of increased n-3 PUFA exposure (EPA and/or DHA) [1], [3]. Accumulating evidence from observational studies suggests that DHA might be more protective for CHD than EPA [4], [30], which is consistent with our findings. However, EPA and DHA are usually correlated with each other in tissues, and their potential effects cannot be easily discerned. More research on this issue is therefore warranted. In addition to blood triglyceride lowering and HDL cholesterol increasing effects of EPA and DHA, n-3 PUFAs have long been observed to have anti-thrombotic, anti-inflammatory, anti-arrhythmic, and blood pressure-lowering effects in humans even though the underlying mechanisms for these effects are incompletely understood [1], [3], [12], [13], [46]. Interestingly, the protective effects on fatal CHD and sudden cardiac death have been shown to level off with a modest intake of EPA and/or DHA (250 mg/day), and little additional benefit was observed with higher intakes [1]. This is also consistent with our results for C204n-6 to C203n-6 ratio as the marker of δ-5 desaturase activity. Nevertheless, there might be other unidentified pleiotropic cardiovascular protective effects of increased δ-5 desaturase activity. For example, these desaturases are also significantly expressed in immune cells [55], [56] that play important roles in atherosclerotic CHD progression. Our results should be interpreted in the context of several limitations. First, our analyses were based on a single baseline measurement of fatty acid levels in plasma cholesteryl esters that may not accurately reflect long-term fatty acid exposures. However, we did detect the established protective effect of DHA against CHD [1], [3], [4], [12], [13], [30]. Second, we estimated δ-5 and δ-6 desaturase activities based on n-6 PUFAs, while δ-5 and δ-6 desaturases are not only involved in n-6 PUFA conversion, but also in n-3 PUFA conversion. However, in comparison to n-6 PUFA conversion, the amount of n-3 PUFA conversion is relatively small [16], which should not have affected our results. Third, other potential unmeasured environmental or physiological factors could have confounded the observed associations. However, the relatively large magnitude of the protective effect of increased δ-5 desaturase activity relative to the effect of other risk factors for CHD makes confounding with other unknown risk factors unlikely. Finally, our models that included total and HDL cholesterol may have been over-adjusted, as these are probably intermediates in the metabolic pathway between desaturase and CHD risk (Note S1). In conclusion, in this prospective cohort study, we observed a reduced CHD risk with increased C204n-6 to C203n-6 ratio that was partly mediated by DHA. These results suggest that δ-5 desaturase activity plays a role in protecting us from CHD. Association between baseline δ-5 desaturase activity and incident coronary heart disease according to rs174547 genotypes. (DOCX) Click here for additional data file. Association of rs174547 with incident coronary heart disease (CHD) risk. (DOCX) Click here for additional data file. Association between baseline n-6 PUFA in plasma cholesteryl esters (precursors and products of δ5- or δ6-desaturase) and incident coronary heart disease (CHD). (DOCX) Click here for additional data file. Association of baseline C205n-3 (EPA) and C22∶6n-3 (DHA) in plasma cholesteryl esters with incident coronary heart disease (CHD). (DOCX) Click here for additional data file. Analysis of intermediate factors of coronary heart disease (CHD). (DOCX) Click here for additional data file.
  53 in total

1.  n-3 fatty acids and cardiovascular events after myocardial infarction.

Authors:  Daan Kromhout; Erik J Giltay; Johanna M Geleijnse
Journal:  N Engl J Med       Date:  2010-08-28       Impact factor: 91.245

2.  Genome-wide association analysis identifies multiple loci related to resting heart rate.

Authors:  Mark Eijgelsheim; Christopher Newton-Cheh; Nona Sotoodehnia; Paul I W de Bakker; Martina Müller; Alanna C Morrison; Albert V Smith; Aaron Isaacs; Serena Sanna; Marcus Dörr; Pau Navarro; Christian Fuchsberger; Ilja M Nolte; Eco J C de Geus; Karol Estrada; Shih-Jen Hwang; Joshua C Bis; Ina-Maria Rückert; Alvaro Alonso; Lenore J Launer; Jouke Jan Hottenga; Fernando Rivadeneira; Peter A Noseworthy; Kenneth M Rice; Siegfried Perz; Dan E Arking; Tim D Spector; Jan A Kors; Yurii S Aulchenko; Kirill V Tarasov; Georg Homuth; Sarah H Wild; Fabio Marroni; Christian Gieger; Carmilla M Licht; Ronald J Prineas; Albert Hofman; Jerome I Rotter; Andrew A Hicks; Florian Ernst; Samer S Najjar; Alan F Wright; Annette Peters; Ervin R Fox; Ben A Oostra; Heyo K Kroemer; David Couper; Henry Völzke; Harry Campbell; Thomas Meitinger; Manuela Uda; Jacqueline C M Witteman; Bruce M Psaty; H-Erich Wichmann; Tamara B Harris; Stefan Kääb; David S Siscovick; Yalda Jamshidi; André G Uitterlinden; Aaron R Folsom; Martin G Larson; James F Wilson; Brenda W Penninx; Harold Snieder; Peter P Pramstaller; Cornelia M van Duijn; Edward G Lakatta; Stephan B Felix; Vilmundur Gudnason; Arne Pfeufer; Susan R Heckbert; Bruno H Ch Stricker; Eric Boerwinkle; Christopher J O'Donnell
Journal:  Hum Mol Genet       Date:  2010-07-16       Impact factor: 6.150

3.  The American Heart Association advisory on n-6 fatty acids: evidence based or biased evidence?

Authors:  Philip C Calder
Journal:  Br J Nutr       Date:  2010-12       Impact factor: 3.718

4.  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.

Authors:  Yingchang Lu; Edith Jm Feskens; Martijn Et Dollé; Sandra Imholz; Wm Monique Verschuren; Michael Müller; Jolanda Ma Boer
Journal:  Am J Clin Nutr       Date:  2010-05-19       Impact factor: 7.045

5.  Erythrocyte membrane phospholipid fatty acids, desaturase activity, and dietary fatty acids in relation to risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study.

Authors:  Janine Kröger; Vera Zietemann; Cornelia Enzenbach; Cornelia Weikert; Eugène Hjm Jansen; Frank Döring; Hans-Georg Joost; Heiner Boeing; Matthias B Schulze
Journal:  Am J Clin Nutr       Date:  2010-10-27       Impact factor: 7.045

6.  FADS genetic variants and omega-6 polyunsaturated fatty acid metabolism in a homogeneous island population.

Authors:  Rasika A Mathias; Candelaria Vergara; Li Gao; Nicholas Rafaels; Tracey Hand; Monica Campbell; Carol Bickel; Priscilla Ivester; Susan Sergeant; Kathleen C Barnes; Floyd H Chilton
Journal:  J Lipid Res       Date:  2010-06-19       Impact factor: 5.922

7.  OMEGA, a randomized, placebo-controlled trial to test the effect of highly purified omega-3 fatty acids on top of modern guideline-adjusted therapy after myocardial infarction.

Authors:  Bernhard Rauch; Rudolf Schiele; Steffen Schneider; Frank Diller; Norbert Victor; Helmut Gohlke; Martin Gottwik; Gerhard Steinbeck; Ulrike Del Castillo; Rudolf Sack; Heinrich Worth; Hugo Katus; Wilhelm Spitzer; Georg Sabin; Jochen Senges
Journal:  Circulation       Date:  2010-11-08       Impact factor: 29.690

Review 8.  Effects on coronary heart disease of increasing polyunsaturated fat in place of saturated fat: a systematic review and meta-analysis of randomized controlled trials.

Authors:  Dariush Mozaffarian; Renata Micha; Sarah Wallace
Journal:  PLoS Med       Date:  2010-03-23       Impact factor: 11.069

9.  Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease.

Authors:  Heribert Schunkert; Inke R König; Sekar Kathiresan; Muredach P Reilly; Themistocles L Assimes; Hilma Holm; Michael Preuss; Alexandre F R Stewart; Maja Barbalic; Christian Gieger; Devin Absher; Zouhair Aherrahrou; Hooman Allayee; David Altshuler; Sonia S Anand; Karl Andersen; Jeffrey L Anderson; Diego Ardissino; Stephen G Ball; Anthony J Balmforth; Timothy A Barnes; Diane M Becker; Lewis C Becker; Klaus Berger; Joshua C Bis; S Matthijs Boekholdt; Eric Boerwinkle; Peter S Braund; Morris J Brown; Mary Susan Burnett; Ian Buysschaert; John F Carlquist; Li Chen; Sven Cichon; Veryan Codd; Robert W Davies; George Dedoussis; Abbas Dehghan; Serkalem Demissie; Joseph M Devaney; Patrick Diemert; Ron Do; Angela Doering; Sandra Eifert; Nour Eddine El Mokhtari; Stephen G Ellis; Roberto Elosua; James C Engert; Stephen E Epstein; Ulf de Faire; Marcus Fischer; Aaron R Folsom; Jennifer Freyer; Bruna Gigante; Domenico Girelli; Solveig Gretarsdottir; Vilmundur Gudnason; Jeffrey R Gulcher; Eran Halperin; Naomi Hammond; Stanley L Hazen; Albert Hofman; Benjamin D Horne; Thomas Illig; Carlos Iribarren; Gregory T Jones; J Wouter Jukema; Michael A Kaiser; Lee M Kaplan; John J P Kastelein; Kay-Tee Khaw; Joshua W Knowles; Genovefa Kolovou; Augustine Kong; Reijo Laaksonen; Diether Lambrechts; Karin Leander; Guillaume Lettre; Mingyao Li; Wolfgang Lieb; Christina Loley; Andrew J Lotery; Pier M Mannucci; Seraya Maouche; Nicola Martinelli; Pascal P McKeown; Christa Meisinger; Thomas Meitinger; Olle Melander; Pier Angelica Merlini; Vincent Mooser; Thomas Morgan; Thomas W Mühleisen; Joseph B Muhlestein; Thomas Münzel; Kiran Musunuru; Janja Nahrstaedt; Christopher P Nelson; Markus M Nöthen; Oliviero Olivieri; Riyaz S Patel; Chris C Patterson; Annette Peters; Flora Peyvandi; Liming Qu; Arshed A Quyyumi; Daniel J Rader; Loukianos S Rallidis; Catherine Rice; Frits R Rosendaal; Diana Rubin; Veikko Salomaa; M Lourdes Sampietro; Manj S Sandhu; Eric Schadt; Arne Schäfer; Arne Schillert; Stefan Schreiber; Jürgen Schrezenmeir; Stephen M Schwartz; David S Siscovick; Mohan Sivananthan; Suthesh Sivapalaratnam; Albert Smith; Tamara B Smith; Jaapjan D Snoep; Nicole Soranzo; John A Spertus; Klaus Stark; Kathy Stirrups; Monika Stoll; W H Wilson Tang; Stephanie Tennstedt; Gudmundur Thorgeirsson; Gudmar Thorleifsson; Maciej Tomaszewski; Andre G Uitterlinden; Andre M van Rij; Benjamin F Voight; Nick J Wareham; George A Wells; H-Erich Wichmann; Philipp S Wild; Christina Willenborg; Jaqueline C M Witteman; Benjamin J Wright; Shu Ye; Tanja Zeller; Andreas Ziegler; Francois Cambien; Alison H Goodall; L Adrienne Cupples; Thomas Quertermous; Winfried März; Christian Hengstenberg; Stefan Blankenberg; Willem H Ouwehand; Alistair S Hall; Panos Deloukas; John R Thompson; Kari Stefansson; Robert Roberts; Unnur Thorsteinsdottir; Christopher J O'Donnell; Ruth McPherson; Jeanette Erdmann; Nilesh J Samani
Journal:  Nat Genet       Date:  2011-03-06       Impact factor: 38.330

10.  Biological, clinical and population relevance of 95 loci for blood lipids.

Authors:  Tanya M Teslovich; Kiran Musunuru; Albert V Smith; Andrew C Edmondson; Ioannis M Stylianou; Masahiro Koseki; James P Pirruccello; Samuli Ripatti; Daniel I Chasman; Cristen J Willer; Christopher T Johansen; Sigrid W Fouchier; Aaron Isaacs; Gina M Peloso; Maja Barbalic; Sally L Ricketts; Joshua C Bis; Yurii S Aulchenko; Gudmar Thorleifsson; Mary F Feitosa; John Chambers; Marju Orho-Melander; Olle Melander; Toby Johnson; Xiaohui Li; Xiuqing Guo; Mingyao Li; Yoon Shin Cho; Min Jin Go; Young Jin Kim; Jong-Young Lee; Taesung Park; Kyunga Kim; Xueling Sim; Rick Twee-Hee Ong; Damien C Croteau-Chonka; Leslie A Lange; Joshua D Smith; Kijoung Song; Jing Hua Zhao; Xin Yuan; Jian'an Luan; Claudia Lamina; Andreas Ziegler; Weihua Zhang; Robert Y L Zee; Alan F Wright; Jacqueline C M Witteman; James F Wilson; Gonneke Willemsen; H-Erich Wichmann; John B Whitfield; Dawn M Waterworth; Nicholas J Wareham; Gérard Waeber; Peter Vollenweider; Benjamin F Voight; Veronique Vitart; Andre G Uitterlinden; Manuela Uda; Jaakko Tuomilehto; John R Thompson; Toshiko Tanaka; Ida Surakka; Heather M Stringham; Tim D Spector; Nicole Soranzo; Johannes H Smit; Juha Sinisalo; Kaisa Silander; Eric J G Sijbrands; Angelo Scuteri; James Scott; David Schlessinger; Serena Sanna; Veikko Salomaa; Juha Saharinen; Chiara Sabatti; Aimo Ruokonen; Igor Rudan; Lynda M Rose; Robert Roberts; Mark Rieder; Bruce M Psaty; Peter P Pramstaller; Irene Pichler; Markus Perola; Brenda W J H Penninx; Nancy L Pedersen; Cristian Pattaro; Alex N Parker; Guillaume Pare; Ben A Oostra; Christopher J O'Donnell; Markku S Nieminen; Deborah A Nickerson; Grant W Montgomery; Thomas Meitinger; Ruth McPherson; Mark I McCarthy; Wendy McArdle; David Masson; Nicholas G Martin; Fabio Marroni; Massimo Mangino; Patrik K E Magnusson; Gavin Lucas; Robert Luben; Ruth J F Loos; Marja-Liisa Lokki; Guillaume Lettre; Claudia Langenberg; Lenore J Launer; Edward G Lakatta; Reijo Laaksonen; Kirsten O Kyvik; Florian Kronenberg; Inke R König; Kay-Tee Khaw; Jaakko Kaprio; Lee M Kaplan; Asa Johansson; Marjo-Riitta Jarvelin; A Cecile J W Janssens; Erik Ingelsson; Wilmar Igl; G Kees Hovingh; Jouke-Jan Hottenga; Albert Hofman; Andrew A Hicks; Christian Hengstenberg; Iris M Heid; Caroline Hayward; Aki S Havulinna; Nicholas D Hastie; Tamara B Harris; Talin Haritunians; Alistair S Hall; Ulf Gyllensten; Candace Guiducci; Leif C Groop; Elena Gonzalez; Christian Gieger; Nelson B Freimer; Luigi Ferrucci; Jeanette Erdmann; Paul Elliott; Kenechi G Ejebe; Angela Döring; Anna F Dominiczak; Serkalem Demissie; Panagiotis Deloukas; Eco J C de Geus; Ulf de Faire; Gabriel Crawford; Francis S Collins; Yii-der I Chen; Mark J Caulfield; Harry Campbell; Noel P Burtt; Lori L Bonnycastle; Dorret I Boomsma; S Matthijs Boekholdt; Richard N Bergman; Inês Barroso; Stefania Bandinelli; Christie M Ballantyne; Themistocles L Assimes; Thomas Quertermous; David Altshuler; Mark Seielstad; Tien Y Wong; E-Shyong Tai; Alan B Feranil; Christopher W Kuzawa; Linda S Adair; Herman A Taylor; Ingrid B Borecki; Stacey B Gabriel; James G Wilson; Hilma Holm; Unnur Thorsteinsdottir; Vilmundur Gudnason; Ronald M Krauss; Karen L Mohlke; Jose M Ordovas; Patricia B Munroe; Jaspal S Kooner; Alan R Tall; Robert A Hegele; John J P Kastelein; Eric E Schadt; Jerome I Rotter; Eric Boerwinkle; David P Strachan; Vincent Mooser; Kari Stefansson; Muredach P Reilly; Nilesh J Samani; Heribert Schunkert; L Adrienne Cupples; Manjinder S Sandhu; Paul M Ridker; Daniel J Rader; Cornelia M van Duijn; Leena Peltonen; Gonçalo R Abecasis; Michael Boehnke; Sekar Kathiresan
Journal:  Nature       Date:  2010-08-05       Impact factor: 49.962

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  25 in total

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

Authors:  Qian Yang; Rui-Xing Yin; Xiao-Li Cao; Dong-Feng Wu; Wu-Xian Chen; Yi-Jiang Zhou
Journal:  Int J Clin Exp Pathol       Date:  2015-06-01

2.  Genetic loci associated with circulating phospholipid trans fatty acids: a meta-analysis of genome-wide association studies from the CHARGE Consortium.

Authors:  Dariush Mozaffarian; Edmond K Kabagambe; Catherine O Johnson; Rozenn N Lemaitre; Ani Manichaikul; Qi Sun; Millennia Foy; Lu Wang; Howard Wiener; Marguerite R Irvin; Stephen S Rich; Hongyu Wu; Majken K Jensen; Daniel I Chasman; Audrey Y Chu; Myriam Fornage; Lyn Steffen; Irena B King; Barbara McKnight; Bruce M Psaty; Luc Djoussé; Ida Y-D Chen; Jason H Y Wu; David S Siscovick; Paul M Ridker; Michael Y Tsai; Eric B Rimm; Frank B Hu; Donna K Arnett
Journal:  Am J Clin Nutr       Date:  2014-12-10       Impact factor: 7.045

3.  Endogenous Production of Long-Chain Polyunsaturated Fatty Acids and Metabolic Disease Risk.

Authors:  Harvey J Murff; Todd L Edwards
Journal:  Curr Cardiovasc Risk Rep       Date:  2014-12-01

4.  Joint effects of fatty acid desaturase 1 polymorphisms and dietary polyunsaturated fatty acid intake on circulating fatty acid proportions.

Authors:  Juan Juan; Hongyan Huang; Xia Jiang; Andres V Ardisson Korat; Mingyang Song; Qi Sun; Walter C Willett; Majken K Jensen; Peter Kraft
Journal:  Am J Clin Nutr       Date:  2018-05-01       Impact factor: 7.045

5.  Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality.

Authors:  Matti Marklund; Jason H Y Wu; Fumiaki Imamura; Liana C Del Gobbo; Amanda Fretts; Janette de Goede; Peilin Shi; Nathan Tintle; Maria Wennberg; Stella Aslibekyan; Tzu-An Chen; Marcia C de Oliveira Otto; Yoichiro Hirakawa; Helle Højmark Eriksen; Janine Kröger; Federica Laguzzi; Maria Lankinen; Rachel A Murphy; Kiesha Prem; Cécilia Samieri; Jyrki Virtanen; Alexis C Wood; Kerry Wong; Wei-Sin Yang; Xia Zhou; Ana Baylin; Jolanda M A Boer; Ingeborg A Brouwer; Hannia Campos; Paulo H M Chaves; Kuo-Liong Chien; Ulf de Faire; Luc Djoussé; Gudny Eiriksdottir; Naglaa El-Abbadi; Nita G Forouhi; J Michael Gaziano; Johanna M Geleijnse; Bruna Gigante; Graham Giles; Eliseo Guallar; Vilmundur Gudnason; Tamara Harris; William S Harris; Catherine Helmer; Mai-Lis Hellenius; Allison Hodge; Frank B Hu; Paul F Jacques; Jan-Håkan Jansson; Anya Kalsbeek; Kay-Tee Khaw; Woon-Puay Koh; Markku Laakso; Karin Leander; Hung-Ju Lin; Lars Lind; Robert Luben; Juhua Luo; Barbara McKnight; Jaakko Mursu; Toshiharu Ninomiya; Kim Overvad; Bruce M Psaty; Eric Rimm; Matthias B Schulze; David Siscovick; Michael Skjelbo Nielsen; Albert V Smith; Brian T Steffen; Lyn Steffen; Qi Sun; Johan Sundström; Michael Y Tsai; Hugh Tunstall-Pedoe; Matti I J Uusitupa; Rob M van Dam; Jenna Veenstra; W M Monique Verschuren; Nick Wareham; Walter Willett; Mark Woodward; Jian-Min Yuan; Renata Micha; Rozenn N Lemaitre; Dariush Mozaffarian; Ulf Risérus
Journal:  Circulation       Date:  2019-05-21       Impact factor: 29.690

Review 6.  Diet-gene interactions and PUFA metabolism: a potential contributor to health disparities and human diseases.

Authors:  Floyd H Chilton; Robert C Murphy; Bryan A Wilson; Susan Sergeant; Hannah Ainsworth; Michael C Seeds; Rasika A Mathias
Journal:  Nutrients       Date:  2014-05-21       Impact factor: 5.717

7.  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.

Authors:  Si-Wei Li; Kun Lin; Pei Ma; Zhen-Lu Zhang; Yi-Dan Zhou; Shuang-Yan Lu; Xin Zhou; Song-Mei Liu
Journal:  PLoS One       Date:  2013-01-31       Impact factor: 3.240

8.  Glycerophospholipid and sphingolipid species and mortality: the Ludwigshafen Risk and Cardiovascular Health (LURIC) study.

Authors:  Alexander Sigruener; Marcus E Kleber; Susanne Heimerl; Gerhard Liebisch; Gerd Schmitz; Winfried Maerz
Journal:  PLoS One       Date:  2014-01-17       Impact factor: 3.240

9.  Genetic variation in FADS1 has little effect on the association between dietary PUFA intake and cardiovascular disease.

Authors:  Sophie Hellstrand; Ulrika Ericson; Bo Gullberg; Bo Hedblad; Marju Orho-Melander; Emily Sonestedt
Journal:  J Nutr       Date:  2014-07-09       Impact factor: 4.798

Review 10.  Effects of oxidative stress on fatty acid- and one-carbon-metabolism in psychiatric and cardiovascular disease comorbidity.

Authors:  J Assies; R J T Mocking; A Lok; H G Ruhé; F Pouwer; A H Schene
Journal:  Acta Psychiatr Scand       Date:  2014-03-21       Impact factor: 6.392

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