Single nucleotide polymorphisms at the ADIPOQ gene locus interact with age and dietary intake of fat to determine serum adiponectin in subjects at risk of the metabolic syndrome

Background: Adiponectin gene expression is modulated by peroxisome proliferator–activated receptor γ, which is a transcription factor activated by unsaturated fatty acids. Objective: We investigated the effect of the interaction between variants at the ADIPOQ gene locus, age, sex, body mass index (BMI), ethnicity, and the replacement of dietary saturated fatty acids (SFAs) with monounsaturated fatty acids (MUFAs) or carbohydrates on serum adiponectin concentrations. Design: The RISCK (Reading, Imperial, Surrey, Cambridge, and Kings) study is a parallel-design, randomized controlled trial. Serum adiponectin concentrations were measured after a 4-wk high-SFA (HS) diet and a 24-wk intervention with reference (HS), high-MUFA (HM), and low-fat (LF) diets. Single nucleotide polymorphisms at the ADIPOQ locus −11391 G/A (rs17300539), −10066 G/A (rs182052), −7734 A/C (rs16861209), and +276 G/T (rs1501299) were genotyped in 448 participants. Results: In white Europeans, +276 T was associated with higher serum adiponectin concentrations (n = 340; P = 0.006) and −10066 A was associated with lower serum adiponectin concentrations (n = 360; P = 0.03), after adjustment for age, BMI, and sex. After the HM diet, −10066 G/G subjects showed a 3.8% increase (95% CI: −0.1%, 7.7%) and G/A+A/A subjects a 2.6% decrease (95% CI: −5.6%, 0.4%) in serum adiponectin (P = 0.006 for difference after adjustment for the change in BMI, age, and sex). In −10066 G/G homozygotes, serum adiponectin increased with age after the HM diet and decreased after the LF diet. Conclusion: In white −10066 G/G homozygotes, an HM diet may help to increase adiponectin concentrations with advancing age. This trial was registered at clinicaltrials.gov as ISRCTN29111298.

Interaction of PPARG Pro12Ala with dietary fat influences plasma lipids in subjects at cardiometabolic risk

The PPARγ2 gene SNP Pro12Ala has shown variable association with metabolic syndrome traits in healthy subjects. We investigated the effect of interaction between genotype and the ratio of polyunsaturated:saturated (P:S) fatty acid intake on plasma lipids in 367 White subjects aged 30-70 y at increased cardiometabolic risk, in the RISCK study. Interaction was determined after habitual diet at recruitment, at baseline after a 4-week high-SFA (HS) diet and after 24-week reference (HS), high-MUFA (HM) and low-fat (LF) diets. At recruitment, there were no significant associations between genotype and plasma lipids, however, P:S x genotype interaction influenced plasma total cholesterol (TC) (P=0.02), LDL-cholesterol (LDL-C) (P=0.002) and triglyceride (TG) (P=0.02) concentrations. At P:S ratio ≤0.33, mean TC and LDL-C concentrations in Ala12 allele carriers were significantly higher than in non-carriers (respectively P=0.003; P=0.0001). Significant trends in reduction of plasma TC (P=0.02) and TG (P=0.002) concentrations occurred with increasing P:S (respectively ≤0.33 to >0.65 and 0.34 to >0.65) in Ala12 allele carriers. There were no significant differences between carriers and non-carriers after the 4-week HS diet or 24-week interventions. Plasma TC and TG concentrations in PPARG Ala12 allele carriers decrease as P:S increases, but are not dependent on a reduction in SFA intake.

Inequalities in diet and nutrition

The inequality of nutrition and obesity re-focuses concern on who in society is consuming the worst diet. Identification of individuals with the worst of dietary habits permits for targeting interventions to assuage obesity among the population segment where it is most prevalent. We argue that the use of fiscal interventions does not appropriately take into account the economic, social and health circumstances of the intended beneficiaries of the policy. This paper reviews the influence of socio-demographic factors on nutrition and health status and considers the impacts of nutrition policy across the population drawing on methodologies from both public health and welfare economics. The effects of a fat tax on diet are found to be small and while other studies show that fat taxes saves lives, we show that average levels of disease risk do not change much: those consuming particularly bad diets continue to do so. Our results also suggest that the regressivity of the policy increases as the tax becomes focused on products with high saturated fat contents. A fiscally neutral policy that combines the fat tax with a subsidy on fruit and vegetables is actually more regressive because consumption of these foods tends to be concentrated in socially undeserving households. We argue that when inequality is of concern, population-based measures must reflect this and approaches that target vulnerable populations which have a shared propensity to adopt unhealthy behaviours are appropriate.

SATgene dietary model to implement diets of differing fat composition in prospectively genotyped groups (apoE) using commercially available foods

esponse to dietary fat manipulation is highly heterogeneous, yet generic population-based recommendations aimed at reducing the burden of CVD are given. The APOE epsilon genotype has been proposed to be an important determinant of this response. The present study reports on the dietary strategy employed in the SATgenɛ (SATurated fat and gene APOE) study, to assess the impact of altered fat content and composition on the blood lipid profile according to the APOE genotype. A flexible dietary exchange model was developed to implement three isoenergetic diets: a low-fat (LF) diet (target composition: 24 % of energy (%E) as fat, 8 %E SFA and 59 %E carbohydrate), a high-saturated fat (HSF) diet (38 %E fat, 18 %E SFA and 45 %E carbohydrate) and a HSF-DHA diet (HSF diet with 3 g DHA/d). Free-living participants (n 88; n 44 E3/E3 and n 44 E3/E4) followed the diets in a sequential design for 8 weeks, each using commercially available spreads, oils and snacks with specific fatty acid profiles. Dietary compositional targets were broadly met with significantly higher total fat (42·8 %E and 41·0 %E v. 25·1 %E, P ≤ 0·0011) and SFA (19·3 %E and 18·6 %E v. 8·33 %E, P ≤ 0·0011) intakes during the HSF and HSF-DHA diets compared with the LF diet, in addition to significantly higher DHA intake during the HSF-DHA diet (P ≤ 0·0011). Plasma phospholipid fatty acid analysis revealed a 2-fold increase in the proportion of DHA after consumption of the HSF-DHA diet for 8 weeks, which was independent of the APOE genotype. In summary, the dietary strategy was successfully implemented in a free-living population resulting in well-tolerated diets which broadly met the dietary targets set.

PPARγ2 gene Pro12Ala and PPARα gene Leu162Val single nucleotide polymorphisms interact with dietary intake of fat in determination of plasma lipid concentrations

Background/Aims: The peroxisome proliferator-activated receptors (PPARs) are transcriptional regulators of lipid metabolism, activated by unsaturated fatty acids. We investigated independent and interactive effects of PPARγ2 gene PPARG Pro12Ala (rs1801282) andPPARαgene PPARA Leu162Val (rs1800206) genotypes with dietary intake of fatty acids on concentrations of plasma lipids in subjects of whom 47.5% had metabolic syndrome. Methods: The RISCK study is a parallel design, randomised controlled trial. Plasma lipids were quantified at baseline after a 4-week high saturated fatty acids diet and after three parallel 24-week interventions with reference (high saturated fatty acids), high monounsaturated fatty acids and low-fat diets. Single nucleotide polymorphisms were genotyped in 466 subjects. Results: At baseline, the PPARG Ala12allele was associated with increased plasma total cholesterol (n = 378; p = 0.04), LDL cholesterol (p = 0.05) and apoB (p =0.05) after adjustment for age, gender and ethnicity. At baseline, PPARA Leu162Val × PPARG Pro12Ala genotype interaction did not significantly influence plasma lipid concentrations. After dietary intervention, gene-gene interaction significantly influenced LDL cholesterol (p =0.0002) and small dense LDL as a proportion of LDL (p = 0.005) after adjustments. Conclusions: Interaction between PPARG Pro12Ala and PPARA Leu162Valgenotypes may influence plasma LDL cholesterol concentration and the proportion as small dense LDL after a high monounsaturated fatty acids diet.

Greater impact of dietary fat manipulation than apolipoprotein E genotype on ex-vivo cytokine production – insights from the SATgenε study

Apolipoprotein E (APOE) genotype is believed to play an important role in cardiovascular risk. APOE4 carriers have been associated with higher blood lipid levels and a more pro-inflammatory state compared with APOE3/E3 individuals. Although dietary fat composition has been considered to modulate the inflammatory state in humans, very little is known about how APOE genotype can impact on this response. In a follow-up to the main SATgene study, we aimed to explore the effects of APOE genotype, as well as, dietary fat manipulation on ex vivo cytokine production. Blood samples were collected from a subset of SATgene participants (n = 52/88), prospectively recruited according to APOE genotype (n = 26 E3/E3 and n = 26 E3/E4) after low-fat (LF), high saturated fat (HSF) and HSF with 3.45 g docosahexaenoic acid (DHA) dietary periods (each diet eight weeks in duration assigned in the same order) for the measurement of ex vivo cytokine production using whole blood culture (WBC). Concentrations of IL-1beta, IL-6, IL-8, IL-10 and TNF-alpha were measured in WBC supernatant samples after stimulation for 24 h with either 0.05 or 1 lg/ml of bacterial lipopolysaccharide (LPS). Cytokine levels were not influenced by genotype, whereas, dietary fat manipulation had a significant impact on TNF-a and IL-10 production; TNF-a concentration was higher after consumption of the HSF diet compared with baseline and the LF diet (P < 0.05), whereas, IL-10 concentration was higher after the LF diet compared with baseline (P < 0.05). In conclusion, our study has revealed the amount and type of dietary fat can significantly modulate the production of TNF-a and IL-10 by ex vivo LPS-stimulated WBC samples obtained from normolipidaemic subjects.

Diet rich in high glucoraphanin broccoli reduces plasma LDL cholesterol: evidence from randomised controlled trials

Cruciferous-rich diets have been associated with reduction in plasma LDL-cholesterol (LDL-C), which may be due to the action of isothiocyanates derived from glucosinolates that accumulate in these vegetables. This study tests the hypothesis that a diet rich in high glucoraphanin (HG) broccoli will reduce plasma LDL-C. METHODS AND RESULTS: One hundred and thirty volunteers were recruited to two independent double-blind, randomly allocated parallel dietary intervention studies, and were assigned to consume either 400 g standard broccoli or 400 g HG broccoli per week for 12 weeks. Plasma lipids were quantified before and after the intervention. In study 1 (37 volunteers), the HG broccoli diet reduced plasma LDL-C by 7.1% (95% CI: -1.8%, -12.3%, p = 0.011), whereas standard broccoli reduced LDL-C by 1.8% (95% CI +3.9%, -7.5%, ns). In study 2 (93 volunteers), the HG broccoli diet resulted in a reduction of 5.1% (95% CI: -2.1%, -8.1%, p = 0.001), whereas standard broccoli reduced LDL-C by 2.5% (95% CI: +0.8%, -5.7%, ns). When data from the two studies were combined the reduction in LDL-C by the HG broccoli was significantly greater than standard broccoli (p = 0.031). CONCLUSION: Evidence from two independent human studies indicates that consumption of high glucoraphanin broccoli significantly reduces plasma LDL-C

Insulin resistance determines a differential response to changes in dietary fat modification on metabolic syndrome risk factors: the LIPGENE study

Background: Previous data support the benefits of reducing dietary saturated fatty acids (SFAs) on insulin resistance (IR) and other metabolic risk factors. However, whether the IR status of those suffering from metabolic syndrome (MetS) affects this response is not established. OBJECTIVE: Our objective was to determine whether the degree of IR influences the effect of substituting high-saturated fatty acid (HSFA) diets by isoenergetic alterations in the quality and quantity of dietary fat on MetS risk factors. DESIGN: In this single-blind, parallel, controlled, dietary intervention study, MetS subjects (n = 472) from 8 European countries classified by different IR levels according to homeostasis model assessment of insulin resistance (HOMA-IR) were randomly assigned to 4 diets: an HSFA diet; a high-monounsaturated fatty acid (HMUFA) diet; a low-fat, high-complex carbohydrate (LFHCC) diet supplemented with long-chain n-3 polyunsaturated fatty acids (1.2 g/d); or an LFHCC diet supplemented with placebo for 12 wk (control). Anthropometric, lipid, inflammatory, and IR markers were determined. RESULTS: Insulin-resistant MetS subjects with the highest HOMA-IR improved IR, with reduced insulin and HOMA-IR concentrations after consumption of the HMUFA and LFHCC n-3 diets (P < 0.05). In contrast, subjects with lower HOMA-IR showed reduced body mass index and waist circumference after consumption of the LFHCC control and LFHCC n-3 diets and increased HDL cholesterol concentrations after consumption of the HMUFA and HSFA diets (P < 0.05). MetS subjects with a low to medium HOMA-IR exhibited reduced blood pressure, triglyceride, and LDL cholesterol levels after the LFHCC n-3 diet and increased apolipoprotein A-I concentrations after consumption of the HMUFA and HSFA diets (all P < 0.05). CONCLUSIONS: Insulin-resistant MetS subjects with more metabolic complications responded differently to dietary fat modification, being more susceptible to a health effect from the substitution of SFAs in the HMUFA and LFHCC n-3 diets. Conversely, MetS subjects without IR may be more sensitive to the detrimental effects of HSFA intake. The metabolic phenotype of subjects clearly determines response to the quantity and quality of dietary fat on MetS risk factors, which suggests that targeted and personalized dietary therapies may be of value for its different metabolic features.