| 1. |
- Imamura, Fumiaki, et al.
(författare)
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A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes : The EPIC-InterAct case-cohort study
- 2017
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Ingår i: PLoS Medicine. - : Public Library Science. - 1549-1277 .- 1549-1676. ; 14:10
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Tidskriftsartikel (refereegranskat)abstract
- Background Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated.Methods and findings We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested casecohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of.-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding.Conclusions A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors.
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| 2. |
- Zheng, Ju-Sheng, et al.
(författare)
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Association between plasma phospholipid saturated fatty acids and metabolic markers of lipid, hepatic, inflammation and glycaemic pathways in eight European countries : a cross-sectional analysis in the EPIC-InterAct study
- 2017
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Ingår i: BMC Medicine. - : BioMed Central. - 1741-7015. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Accumulating evidence suggests that individual circulating saturated fatty acids (SFAs) are heterogeneous in their associations with cardio-metabolic diseases, but evidence about associations of SFAs with metabolic markers of different pathogenic pathways is limited. We aimed to examine the associations between plasma phospholipid SFAs and the metabolic markers of lipid, hepatic, glycaemic and inflammation pathways. Methods: We measured nine individual plasma phospholipid SFAs and derived three SFA groups (odd-chain: C15:0 + C17:0, even-chain: C14:0 + C16:0 + C18:0, and very-long-chain: C20:0 + C22:0 + C23:0 + C24:0) in individuals from the subcohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study across eight European countries. Using linear regression in 15,919 subcohort members, adjusted for potential confounders and corrected for multiple testing, we examined cross-sectional associations of SFAs with 13 metabolic markers. Multiplicative interactions of the three SFA groups with pre-specified factors, including body mass index (BMI) and alcohol consumption, were tested. Results: Higher levels of odd-chain SFA group were associated with lower levels of major lipids (total cholesterol (TC), triglycerides, apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB)) and hepatic markers (alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT)). Higher even-chain SFA group levels were associated with higher levels of low-density lipoprotein cholesterol (LDL-C), TC/high-density lipoprotein cholesterol (HDL-C) ratio, triglycerides, ApoB, ApoB/A1 ratio, ALT, AST, GGT and CRP, and lower levels of HDL-C and ApoA1. Very-long-chain SFA group levels showed inverse associations with triglycerides, ApoA1 and GGT, and positive associations with TC, LDL-C, TC/HDL-C, ApoB and ApoB/A1. Associations were generally stronger at higher levels of BMI or alcohol consumption. Conclusions: Subtypes of SFAs are associated in a differential way with metabolic markers of lipid metabolism, liver function and chronic inflammation, suggesting that odd-chain SFAs are associated with lower metabolic risk and even-chain SFAs with adverse metabolic risk, whereas mixed findings were obtained for very-long-chain SFAs. The clinical and biochemical implications of these findings may vary by adiposity and alcohol intake.
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| 3. |
- Ward, Heather A., et al.
(författare)
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Measured adiposity in relation to head and neck cancer risk in the European Prospective Investigation into Cancer and Nutrition
- 2017
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Ingår i: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. - : AMER ASSOC CANCER RESEARCH. - 1538-7755 .- 1055-9965. ; 26:6, s. 895-904
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Emerging evidence from cohort studies indicates that adiposity is associated with greater incidence of head and neck cancer (HNC). However, most studies have used self-reported anthropometry which is prone to error.METHODS: Among 363 094 participants in the European Prospective Investigation into Cancer and Nutrition study (EPIC) with measured anthropometry, there were 837 incident cases of HNC. HNC risk was examined in relation to body mass index (BMI) [lean: < 22.5 kg/m2, normal weight (reference): 22.5-24.9 kg/m2, overweight 25-29.9 kg/m2, obese: > 30 kg/m2], waist circumference (WC), hip circumference (HC) and waist to hip ratio (WHR) using Cox proportional hazards models.RESULTS: Among men, a BMI < 22.5 kg/m2 was associated with higher HNC risk [hazard ratio (HR) 1.62, 95% confidence interval (CI) 1.23 - 2.12)]; BMI was not associated with HNC among women. WC and WHR were associated with greater risk of HNC among women, (WC per 5 cm: HR 1.08, 95% CI 1.02 - 1.15; WHR per 0.1 unit: HR 1.64, 95% CI 1.38 - 1.93). After stratification by smoking status, the association for WHR was present only among smokers (p interaction 0.004). Among men, WC and WHR were associated with HNC only upon additional adjustment for BMI (WC per 5 cm: HR 1.16, 95% CI 1.07 - 1.26; WHR per 0.1 unit: HR 1.42, 95% CI 1.21 - 1.65).CONCLUSION: Central adiposity, particularly among women, may have a stronger association with HNC risk than previously estimated.IMPACT: Strategies to reduce obesity may beneficially impact HNC incidence.
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| 4. |
- Fortner, Renee T., et al.
(författare)
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Endometrial cancer risk prediction including serum-based biomarkers : results from the EPIC cohort
- 2017
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 140:6, s. 1317-1323
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Tidskriftsartikel (refereegranskat)abstract
- Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimina-tion. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigat-ed for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selec-tion process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were select-ed into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including eti-ologic markers on independent pathways and genetic markers may further improve discrimination.
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