Intake levels of dietary long-chain PUFAs modify the association between genetic variation in FADS and LDL-C
2012; Elsevier BV; Volume: 53; Issue: 6 Linguagem: Inglês
10.1194/jlr.p023721
ISSN1539-7262
AutoresSophie Hellstrand, Emily Sonestedt, Ulrika Ericson, B Gullberg, Elisabet Wirfält, B. Hedblad, Marju Orho‐Melander,
Tópico(s)Diet, Metabolism, and Disease
ResumoPolymorphisms of the FA desaturase (FADS) gene cluster have been associated with LDL, HDL, and triglyceride concentrations. Because FADS converts α-linolenic acid (ALA) and linoleic acid into PUFAs, we investigated the interaction between different PUFA intakes and the FADS polymorphism rs174547 (T>C) on fasting blood lipid and lipoprotein concentrations. We included 4,635 individuals (60% females, 45–68 years) from the Swedish population-based Malmö Diet and Cancer cohort. Dietary intakes were assessed by a modified diet history method including 7-day registration of cooked meals. The C-allele of rs174547 was associated with lower LDL concentration (P = 0.03). We observed significant interaction between rs174547 and long-chain ω-3 PUFA intakes on LDL (P = 0.01); the C-allele was only associated with lower LDL among individuals in the lowest tertile of long-chain ω-3 PUFA intakes (P < 0.001). In addition, significant interaction was observed between rs174547 and the ratio of ALA and linoleic FA intakes on HDL (P = 0.03). However, no significant associations between the C-allele and HDL were detected within the intake tertiles of the ratio. Our findings suggest that dietary intake levels of different PUFAs modify the associated effect of genetic variation in FADS on LDL and HDL Polymorphisms of the FA desaturase (FADS) gene cluster have been associated with LDL, HDL, and triglyceride concentrations. Because FADS converts α-linolenic acid (ALA) and linoleic acid into PUFAs, we investigated the interaction between different PUFA intakes and the FADS polymorphism rs174547 (T>C) on fasting blood lipid and lipoprotein concentrations. We included 4,635 individuals (60% females, 45–68 years) from the Swedish population-based Malmö Diet and Cancer cohort. Dietary intakes were assessed by a modified diet history method including 7-day registration of cooked meals. The C-allele of rs174547 was associated with lower LDL concentration (P = 0.03). We observed significant interaction between rs174547 and long-chain ω-3 PUFA intakes on LDL (P = 0.01); the C-allele was only associated with lower LDL among individuals in the lowest tertile of long-chain ω-3 PUFA intakes (P < 0.001). In addition, significant interaction was observed between rs174547 and the ratio of ALA and linoleic FA intakes on HDL (P = 0.03). However, no significant associations between the C-allele and HDL were detected within the intake tertiles of the ratio. Our findings suggest that dietary intake levels of different PUFAs modify the associated effect of genetic variation in FADS on LDL and HDL The blood concentrations of LDL-cholesterol, HDL-cholesterol, and triglycerides have a strong genetic influence (1.Park M.H. Kim N. Lee J.Y. Park H.Y. Genetic loci associated with lipid concentrations and cardiovascular risk factors in a Korean population.J. Med. 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Genet. 2009; 41: 56-65Crossref PubMed Scopus (1089) Google Scholar). More recently, a meta-analysis of >100,000 individuals reported genome-wide significant associations of the FADS locus and LDL, HDL, as well as triglyceride concentrations (5.Teslovich T.M. Musunuru K. Smith A.V. Edmondson A.C. Stylianou I.M. Koseki M. Pirruccello J.P. Ripatti S. Chasman D.I. Willer C.J. et al.Biological, clinical and population relevance of 95 loci for blood lipids.Nature. 2010; 466: 707-713Crossref PubMed Scopus (2791) Google Scholar). FADSs are key enzymes in the endogenous desaturation of α-linolenic acid (ALA, C18:3ω-3) and linoleic acid (LA, C18:2ω-6) into long-chain PUFAs, where FADS1 is a Δ-5 desaturase and FADS2 a Δ-6 desaturase (9.Lattka E. Illig T. Heinrich J. Koletzko B. Do FADS genotypes enhance our knowledge about fatty acid related phenotypes?.Clin. Nutr. 2010; 29: 277-287Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 10.Martinelli N. Girelli D. Malerba G. Guarini P. Illig T. Trabetti E. Sandri M. Friso S. Pizzolo F. Schaeffer L. et al.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: 941-949Crossref PubMed Scopus (264) Google Scholar). Further, SNPs in the FADS locus have been associated with blood concentrations of long-chain PUFAs as well as with cholesterol concentrations (9.Lattka E. Illig T. Heinrich J. Koletzko B. Do FADS genotypes enhance our knowledge about fatty acid related phenotypes?.Clin. Nutr. 2010; 29: 277-287Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 11.Chasman D.I. Pare G. Mora S. Hopewell J.C. Peloso G. Clarke R. Cupples L.A. Hamsten A. Kathiresan S. 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Long-chain PUFAs regulate the fluidity of cell membrane, act as second messengers in intracellular signaling pathways, and regulate transcription (17.Jung U.J. Torrejon C. Tighe A.P. Deckelbaum R.J. n-3 Fatty acids and cardiovascular disease: mechanisms underlying beneficial effects.Am. J. Clin. Nutr. 2008; 87: 2003S-2009SCrossref PubMed Google Scholar). Dietary intakes of the long-chain ω-3 PUFAs docosahexanoic acid (DHA, C22:6ω-3) and eicosapentanoic acid (EPA, C20:5ω-3) have been reported to lower serum triglyceride levels (18.Wijendran V. Hayes K.C. Dietary n-6 and n-3 fatty acid balance and cardiovascular health.Annu. Rev. Nutr. 2004; 24: 597-615Crossref PubMed Scopus (465) Google Scholar), and higher dietary intake of ω-3 was associated with higher HDL and LDL in the Malmö Diet and Cancer (MDC) cohort (19.Sonestedt, E., Wirfalt, E., Wallstrom, P., Gullberg, B., Drake, I., Hlebowicz, J., Nordin Fredrikson, G., Hedblad, B., Nilsson, J., Krauss, R. M. High disaccharide intake associates with atherogenic lipoprotein profile. Br. J. Nutr. Epub ahead of print. October 20, 2011. doi:10.1017/S0007114511003783.Google Scholar). Additionally, long-chain PUFAs, such as arachidonic acid (AA, C20:4ω-6) and EPA, are precursors for inflammatory molecules such as eicosanoids (9.Lattka E. Illig T. Heinrich J. Koletzko B. Do FADS genotypes enhance our knowledge about fatty acid related phenotypes?.Clin. Nutr. 2010; 29: 277-287Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 20.Mathias R.A. Vergara C. Gao L. Rafaels N. Hand T. Campbell M. Bickel C. Ivester P. Sergeant S. Barnes K.C. et al.FADS genetic variants and omega-6 polyunsaturated fatty acid metabolism in a homogeneous island population.J. Lipid Res. 2010; 51: 2766-2774Abstract Full Text Full Text PDF PubMed Scopus (72) Google Scholar), and high long-chain PUFA concentration has been associated with lower prevalence of both metabolic syndrome and cardiovascular disease (9.Lattka E. Illig T. Heinrich J. Koletzko B. Do FADS genotypes enhance our knowledge about fatty acid related phenotypes?.Clin. Nutr. 2010; 29: 277-287Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 10.Martinelli N. Girelli D. Malerba G. Guarini P. Illig T. Trabetti E. Sandri M. Friso S. Pizzolo F. Schaeffer L. et al.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: 941-949Crossref PubMed Scopus (264) Google Scholar). Further, previous studies have suggested that dietary intake levels of different PUFAs interact with FADS1 variation to affect blood lipids (13.Lu Y. Feskens E.J. Dolle M.E. Imholz S. Verschuren W.M. Muller M. Boer J.M. 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: 258-265Crossref PubMed Scopus (82) Google Scholar, 21.Nakayama K. Bayasgalan T. Tazoe F. Yanagisawa Y. Gotoh T. Yamanaka K. Ogawa A. Munkhtulga L. Chimedregze U. Kagawa Y. et al.A single nucleotide polymorphism in the FADS1/FADS2 gene is associated with plasma lipid profiles in two genetically similar Asian ethnic groups with distinctive differences in lifestyle.Hum. Genet. 2010; 127: 685-690Crossref PubMed Scopus (61) Google Scholar). Because FADS are key regulators of ALA and LA desaturation, we examined whether different dietary intake levels of PUFAs modify the association between the rs174547 polymorphism in the FADS locus and blood concentrations of LDL, HDL, and triglycerides. The MDC cohort is a population-based prospective cohort including 28,449 participants, with baseline data collection conducted throughout the years 1991–96 (22.Berglund G. Elmstahl S. Janzon L. Larsson S.A. The Malmo Diet and Cancer Study. Design and feasibility.J. Intern. Med. 1993; 233: 45-51Crossref PubMed Scopus (490) Google Scholar). The study population includes individuals born during 1923–50 (23.Manjer J. Elmstahl S. Janzon L. Berglund G. Invitation to a population-based cohort study: differences between subjects recruited using various strategies.Scand. J. Public Health. 2002; 30: 103-112Crossref PubMed Scopus (115) Google Scholar) and living in Malmö, the third-largest city in Sweden, with about 295,000 citizens. The participation rate was approximately 40% (24.Nilsson P.M. Engstrom G. Hedblad B. The metabolic syndrome and incidence of cardiovascular disease in non-diabetic subjects–a population-based study comparing three different definitions.Diabet. Med. 2007; 24: 464-472Crossref PubMed Scopus (152) Google Scholar). Among MDC participants recruited from November 1991 to February 1994 (n = 12,445), a random 50% was invited to further participate in a carotid artery disease study, the MDC Cardiovascular Cohort. In total, 6,103 individuals underwent a review of their medical history, a physical examination and a laboratory assessment of cardiovascular risk factors (22.Berglund G. Elmstahl S. Janzon L. Larsson S.A. The Malmo Diet and Cancer Study. Design and feasibility.J. Intern. Med. 1993; 233: 45-51Crossref PubMed Scopus (490) Google Scholar, 24.Nilsson P.M. Engstrom G. Hedblad B. The metabolic syndrome and incidence of cardiovascular disease in non-diabetic subjects–a population-based study comparing three different definitions.Diabet. Med. 2007; 24: 464-472Crossref PubMed Scopus (152) Google Scholar, 25.Kathiresan S. Melander O. Anevski D. Guiducci C. Burtt N.P. Roos C. Hirschhorn J.N. Berglund G. Hedblad B. Groop L. et al.Polymorphisms associated with cholesterol and risk of cardiovascular events.N. Engl. J. Med. 2008; 358: 1240-1249Crossref PubMed Scopus (578) Google Scholar). Information on LDL, HDL, and triglyceride fasting blood concentrations was available in 5,363 individuals. Totally, information on diet, FADS genotype, and blood lipids was available in 4,943 individuals. After excluding individuals with diabetes mellitus (self-reported diagnosis or using anti-diabetes medication, n = 123), users of lipid-lowering medication (n = 117), and those with a history of cardiovascular event (coronary event or stroke, n = 117), the study sample included 4,635 individuals (45–68 years, 60.3% female). Information about the history of cardiovascular event (coronary event or stroke) was taken from the national Swedish Hospital Discharge register and the local register of stroke (24.Nilsson P.M. Engstrom G. Hedblad B. The metabolic syndrome and incidence of cardiovascular disease in non-diabetic subjects–a population-based study comparing three different definitions.Diabet. Med. 2007; 24: 464-472Crossref PubMed Scopus (152) Google Scholar). All individuals provided written, informed consent, and the ethics committee of Lund University approved the MDC study protocols. The genotyping of the FADS rs174547 (T/C) was performed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry on the Sequenom Mass-ARRAY platform (San Diego, CA). Genotyping was successful in 5,806 (96%) of the 6,055 individuals with DNA available and the rs174547 was in Hardy-Weinberg equilibrium (P = 0.92). In addition, 5,490 of the 6,055 individuals, of whom we still have DNA available, were additionally genotyped by the TaqMan allelic discrimination on ABI 7900 with a concordance rate for the two methods of 99.2%. Dietary intake was measured by a modified diet history methodology combining a 168 item dietary questionnaire, a 7 day menu book and a 1 h diet history interview, especially designed for the MDC study (26.Callmer E. Riboli E. Saracci R. Akesson B. Lindgarde F. Dietary assessment methods evaluated in the Malmo food study.J. Intern. Med. 1993; 233: 53-57Crossref PubMed Scopus (91) Google Scholar). The 168 item dietary questionnaire covered food items regularly consumed during the past year. The participants were asked to fill in the frequency of food intake and estimate the usual portion sizes using a booklet with photographic aids. The 7 day menu book covered cooked lunch and dinner meals, cold beverages (including alcoholic beverages), medications, natural remedies, and dietary supplements used by the participants. To complete the dietary data, the participants were interviewed, for 1 h about their food choices, food preparation practices, and portion sizes (by using a more-extensive booklet of photos) of the food reported in the menu book. The trained interviewers checked the menu book and questionnaire for very high reported intakes and overlapping information. The average daily food intake (grams per day) was calculated based on the information from the menu book, interview, and questionnaire, and converted into nutrient and energy intakes by using the MDC Food and Nutrient Database, developed from the PC KOST-93 of the Swedish National Food Administration (26.Callmer E. Riboli E. Saracci R. Akesson B. Lindgarde F. Dietary assessment methods evaluated in the Malmo food study.J. Intern. Med. 1993; 233: 53-57Crossref PubMed Scopus (91) Google Scholar). The different PUFA intakes were converted into the percentage contributed by the specific PUFAs to total energy intake (E%). The PUFA dietary variables included in this study were: ALA (C18:3ω-3); long-chain ω-3 PUFA (EPA [C20:5ω-3], docosapentanoic acid [DPA, C22:5ω-3], and DHA [C22:6ω-3]); total ω-3 PUFA (ALA, EPA, DPA, and DHA); total ω-6 PUFA (LA [C18:2ω-6], γ-linolenic acid [C18:3ω-6], and AA [C20:4ω-6]); ALA to LA ratio (ALA/LA); total ω-3 to total ω-6 PUFA ratio (ω-3/ω-6 PUFA). The relative validity of the modified diet history method was examined in 105 women and 101 men. As the reference method, a total of 18 days of weighed food records was collected during 3 consecutive days, every second month for 1 year. The energy-adjusted correlation coefficients between the modified diet history method and the reference method were in men: 0.22 for ALA, 0.23 for LA, 0.55 for AA, 0.24 for EPA, 0.37 for DPA, and 0.20 for DHA. In women, the coefficients were 0.58 for ALA, 0.68 for LA, 0.44 for AA, 0.38 for EPA, 0.40 for DPA, and 0.27 for DHA (27.Riboli E. Elmstahl S. Saracci R. Gullberg B. Lindgarde F. The Malmo Food Study: validity of two dietary assessment methods for measuring nutrient intake.Int. J. Epidemiol. 1997; 26: S161-173Crossref PubMed Google Scholar). HDL, triglyceride, and total cholesterol concentrations were determined in overnight fasting blood samples by standard methods at the department of Clinical Chemistry, University Hospital of Malmö. LDL concentration was calculated by the Friedewald formula: LDL = total cholesterol – HDL – (triglycerides/2.2) (24.Nilsson P.M. Engstrom G. Hedblad B. The metabolic syndrome and incidence of cardiovascular disease in non-diabetic subjects–a population-based study comparing three different definitions.Diabet. Med. 2007; 24: 464-472Crossref PubMed Scopus (152) Google Scholar). For individuals with a triglyceride concentration of more than 400 mg per deciliter (4.5 mmol/l), LDL was defined as missing (25.Kathiresan S. Melander O. Anevski D. Guiducci C. Burtt N.P. Roos C. Hirschhorn J.N. Berglund G. Hedblad B. Groop L. et al.Polymorphisms associated with cholesterol and risk of cardiovascular events.N. Engl. J. Med. 2008; 358: 1240-1249Crossref PubMed Scopus (578) Google Scholar). Body mass index (BMI) was calculated as weight in kilograms divided by square of height in meters (kg/m2). A self-administered questionnaire was used to determine lifestyle factors including cigarette smoking, alcohol intake, and physical activity habits. Three categories of smoking status were used: current (including irregular smoking), former, and never smokers. Alcohol habits were divided into five categories. Individuals reporting no alcohol consumption during the last year in the questionnaire, which also were zero reporters of alcohol in the 7 day menu book, were categorized as zero consumers of alcohol. We divided the other study participants' alcohol consumption (grams per day) into categories with different cutoffs according to gender. The cutoff levels for females were 5, 10, and 20 g of alcohol per day and the cutoff levels for males were 10, 20, and 40 g of alcohol per day. The leisure-time physical activity level (PAL) was calculated from a list of 17 different activities in the questionnaire. The time spent on each activity was multiplied by an intensity factor, creating a leisure-time physical activity score. The leisure-time physical activity score was then divided into quintiles, with the same cutoffs for both genders. Separate categories for smoking, alcohol intake, and leisure-time physical activity were constructed for the subjects with missing data. SPSS, Inc. PASW Statistics 18.0 was used for statistical analysis. Statistical significance was set at P < 0.05, and all P values are 2-sided. All of the covariates, except season, were differentially distributed between tertiles of total ω-3 and ω-6 PUFA intake. Assuming an additive model, associations with the FADS rs174547 (T/C) genotype categories were investigated using the General Linear Model adjusted for age and sex (basic analysis), and thereafter, age, sex, and BMI. Interaction between FADS genotype and tertiles of dietary intake levels on serum lipid concentrations were studied by introducing a multiplicative factor of genotypes and diet tertiles as continuous variables in addition to these main factors as separate variables. The interaction analyses were adjusted for potential confounders: age, sex, BMI, season of diet collection (four categories), cigarette smoking, leisure-time physical activity, alcohol intake, and total energy intake. All continuous variables except age were Ln-transformed to achieve normal distribution when testing for trend across FADS genotype categories and interaction between FADS genotype categories and tertiles of dietary intake levels of PUFA on LDL, HDL, and triglycerides; before transformation, a very small amount (0.001 g) was added to ω-3 PUFA intake to handle zero intakes. In sensitivity analyses, potential misreporters of energy were excluded. Misreporters of energy intake were identified by comparing the individually estimated PAL expressed as the energy expenditure divided by the basal metabolic rate (BMR), with energy intake divided by BMR, further explained elsewhere (28.Mattisson I. Wirfalt E. Aronsson C.A. Wallstrom P. Sonestedt E. Gullberg B. Berglund G. Misreporting of energy: prevalence, characteristics of misreporters and influence on observed risk estimates in the Malmo Diet and Cancer cohort.Br. J. Nutr. 2005; 94: 832-842Crossref PubMed Scopus (87) Google Scholar). Individuals were defined as misreporters when the ratio of the reported energy intake to BMR was outside the 95% confidence limits of the calculated PAL (i.e., under- and over-reporters). Each C-allele of rs174547 associated with 0.05 mmol/l lower LDL concentration (P trend = 0.03, Table 1), but not with HDL or triglyceride concentrations (P trend = 1.00 and P trend = 0.10, respectively) in the basic analysis. BMI was significantly associated with genotype, and when BMI was included as a covariate, a significant association of 0.02 mmol/l higher triglyceride concentration per C-allele was observed (P trend = 0.04). Similar to the basic analysis, the association with LDL concentration remained significant (P trend = 0.047), and no association with HDL concentration was detected (P trend = 0.52) after adjusting for BMI.TABLE 1Characteristics of the Malmö Diet and Cancer cardiovascular cohort individuals by FADS1 rs174547 genotypeCharacteristicsAll(N = 4,635)T/T(N = 2,054)T/C(N = 2,056)C/C(N = 525)P trendaLn transformed. Adjusted for age and sex.Women, N (%)2,795 (60.3)1,227 (59.7)1,240 (60.3)328 (62.5)0.52Age (y)57.7 (52.3–62.6)57.6 (52.2–62.3)57.7 (52.2–62.6)58.0 (52.2–62.7)0.54BMI (kg/m )25.1 (22.8–27.7)25.3 (23.0–27.8)25.0 (22.9–27.3)24.8 (22.7–27.3)0.047Fasting glucose (mmol/l)4.9 (4.6–5.3)4.9 (4.6–5.3)4.9 (4.6–5.3)4.9 (4.6–5.2)0.44LDL cholesterol (mmol/l)4.10 (3.5–4.8)4.10 (3.5–4.8)4.10 (3.5–4.8)4.00 (3.4–4.7)0.03HDL cholesterol (mmol/l)1.35 (1.1–1.6)1.36 (1.1–1.6)1.36 (1.1–1.6)1.36 (1.1–1.6)1.00Triglycerides (mmol/l)1.14 (0.9–1.6)1.13 (0.9–1.5)1.13 (0.9–1.6)1.18 (0.9–1.6)0.10Dietary intakeALA (E%)0.73 (0.6–0.9)0.73 (0.6–0.9)0.72 (0.6–0.9)0.71 (0.6–0.8)0.06Long-chain ω-3 PUFA (E%)0.20 (0.1–0.3)0.20 (0.1–0.3)0.20 (0.1–0.3)0.21 (0.1–0.4)0.41Total ω-3 PUFA (E%)0.97 (0.8–1.2)0.98 (0.8–1.2)0.97 (0.8–1.2)0.96 (0.8–1.2)0.47Total ω-6 PUFA (E%)4.89 (4.0–5.9)4.93 (4.1–5.9)4.87 (4.0–5.9)4.83 (4.0–5.7)0.27ALA/LA (E%)0.15 (0.1–0.2)0.15 (0.1–0.2)0.15 (0.1–0.2)0.15 (0.1–0.2)0.44Total ω-3/ω-6 PUFA (E%)0.19 (0.2–0.2)0.19 (0.2–0.2)0.19 (0.2–0.2)0.19 (0.2–0.2)0.72Data are median (inter-quartile range) or number (%), if not otherwise indicated. ALA, α-linolenic acid; BMI, body mass index; E%, energy percentage of total energy intake; LA, linoleic acid; PUFA, polyunsaturated fatty acid. Sex, age, diet variables, and LDL, HDL, and triglycerides (n = 4,635). BMI (n = 4,633). Fasting glucose (n = 4,624).a Ln transformed. Adjusted for age and sex. Open table in a new tab Data are median (inter-quartile range) or number (%), if not otherwise indicated. ALA, α-linolenic acid; BMI, body mass index; E%, energy percentage of total energy intake; LA, linoleic acid; PUFA, polyunsaturated fatty acid. Sex, age, diet variables, and LDL, HDL, and triglycerides (n = 4,635). BMI (n = 4,633). Fasting glucose (n = 4,624). PUFA intakes did not differ according to FADS genotypes (Table 1). No significant interaction was observed between the FADS genotype categories and intake levels of total ω-3 PUFAs on LDL concentration (Table 2). However, we observed a significant interaction between the FADS genotype categories and long-chain ω-3 PUFA intake on LDL concentration (P = 0.01). The C-allele was significantly associated with lower LDL among individuals within the lowest tertile of long-chain ω-3 PUFA intake (≤0.14 E%, P < 0.001), but not among those in the mid- (0.14–0.28 E%) or highest tertiles (>0.28 E%). When examining within-genotype categories, the high long-chain ω-3 PUFA intake was associated significantly with higher LDL concentration among the CC-genotype (P < 0.001) and TC-genotype carriers (P = 0.04) but not among TT-genotype carriers (P = 0.17) (Fig. 1). In addition, there was a significant interaction between the FADS genotype categories and ALA/LA intakes on HDL concentration (P = 0.03) despite lack of significant associations between the FADS genotypes and HDL concentration in any of the ALA/LA tertiles. However, we observed significant associations between ALA/LA and HDL concentration among CC- (P = 0.046) and TC-genotype carriers (P = 0.02) but not among those with the TT-genotype (Fig. 2). No significant interactions were observed between the FADS genotype categories and any of the different PUFA intake levels on triglyceride concentration (Table 2).TABLE 2Association between rs174547 (T/C) for each additional C-allele and blood lipids in strata of diet intakes among 4,635 individualsLDL CholesterolHDL CholesterolTriglyceridesDiet variables (E%)Effect sizeP-trendaAdjusted for age and sex.P-intbAdjusted for age, sex, season, alcohol intake, cigarette smoking, leisure time physical activity, BMI, and total energy intake.Effect sizeP-trendaAdjusted for age and sex.P-intbAdjusted for age, sex, season, alcohol intake, cigarette smoking, leisure time physical activity, BMI, and total energy intake.Effect sizeP-trendaAdjusted for age and sex.P-intbAdjusted for age, sex, season, alcohol intake, cigarette smoking, leisure time physical activity, BMI, and total energy intake.ALA0.940.550.47Low (≤0.65)−0.0340.39−0.0030.810.0240.37Medium (0.65–0.80)−0.0780.030.0030.980.0280.29High (≥0.80)−0.0210.550.0090.710.0130.89Long-chain ω-3 PUFA0.010.530.70Low (≤0.14)−0.138<0.001−0.0060.430.0250.30Medium (0.14–0.28)0.0010.980.0070.690.0200.53High (≥0.28)−0.0070.860.0040.950.0250.49Total ω-3 PUFA0.380.780.87Low (≤0.86)−0.0710.050.0040.670.0060.91Medium (0.86–1.09)−0.0490.240.0050.930.0370.17High (≥1.09)−0.0130.620.0010.780.0240.55Total ω-6 PUFA0.350.900.90Low (≤4.35)−0.0520.160.0020.890.0130.53Medium (4.35–5.48)−0.0740.040.0040.970.0250.33High (≥5.48)−0.0070.830.0020.860.0300.53ALA/LA0.490.030.15Low (≤0.14)−0.0220.51−0.0200.070.0410.17Medium (0.14–0.16)−0.0550.120.0150.350.0400.25High (≥0.16)−0.0590.120.0140.35−0.0130.78Total ω-3/ω-6 PUFA0.730.260.16Low (≤0.17)−0.0560.11−0.0020.580.0350.30Medium (0.17–0.22)−0.0180.77−0.0070.670.0430.10High (≥0.22)−0.0640.050.0150.38−0.0070.64Effect size (β) = difference in lipid concentration for each additional C-allele. ALA, α-linolenic acid; BMI, body mass index; E%, energy percentage of total energy intake; LA, linoleic acid; PUFA, polyunsaturated fatty acid.a Adjusted for age and sex.b Adjusted for age, sex, season, alcohol intake, cigarette smoking, leisure time physical activity, BMI, and total energy intake. Open table in a new tab Fig. 2Association between ALA/LA and HDL in strata of rs174547 among 4,635 individuals. A high ALA/LA was associated with 0.04 mmol/l and 0.02 mmol/l higher HDL concentration among individuals with CC-genotype (P = 0.046) and TC-genotype (P = 0.02) but not among those with TT-genotype (P = 0.96). There was no association between the CC genotype and HDL in individuals with low, medium, or high ALA/LA (P = 0.0
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