Inflammation-Related Marker Profiling of Dietary Patterns and All-cause Mortality in the Melbourne Collaborative Cohort Study.

Autor:	Li SX; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.; Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom., Hodge AM; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia., MacInnis RJ; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia., Bassett JK; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia., Ueland PM; Department of Clinical Science, University of Bergen, Bergen, Norway., Midttun Ø; Bevital A/S, Laboratoriebygget, Bergen, Norway., Ulvik A; Bevital A/S, Laboratoriebygget, Bergen, Norway., Rinaldi S; Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France., Meyer K; Bevital A/S, Laboratoriebygget, Bergen, Norway., Navionis AS; Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France., Shivappa N; Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA.; Department of Nutrition, Connecting Health Innovations LLC, Columbia, SC, USA., Hébert JR; Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA.; Department of Nutrition, Connecting Health Innovations LLC, Columbia, SC, USA., Flicker L; WA Centre for Health and Ageing of the University of Western Australia, Crawley, Western Australia, Australia., Severi G; Centre de Recherche en Épidémiologie et Santé des Populations (CESP, Inserm U1018), Université Paris-Saclay, UPS, USQ, Gustave Roussy, Villejuif, France.; Human Genetics Foundation (HuGeF), Turin, Italy., Jayasekara H; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia., English DR; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia., Vineis P; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom., Southey MC; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia., Milne RL; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia., Giles GG; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia., Dugué PA; Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.; Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
Jazyk:	angličtina
Zdroj:	The Journal of nutrition [J Nutr] 2021 Oct 01; Vol. 151 (10), pp. 2908-2916.
DOI:	10.1093/jn/nxab231
Abstrakt:	Background: Nutritional epidemiology research using self-reported dietary intake is prone to measurement error. Objective methods are being explored to overcome this limitation. Objectives: We aimed to examine 1) the association between plasma markers related to inflammation and derive marker scores for dietary patterns [Mediterranean dietary score (MDS), energy-adjusted Dietary Inflammatory Index (E-DIITM), Alternative Healthy Eating Index 2010 (AHEI)] and 2) the associations of these marker scores with mortality. Methods: Weighted marker scores were derived from the cross-sectional association between 30 plasma markers and each dietary score (assessed using food-frequency questionnaires) using linear regression for 770 participants in the Melbourne Collaborative Cohort Study (aged 50-82 y). Prospective associations between marker scores and mortality (n = 249 deaths) were assessed using Cox regression (median follow-up: 14.4 y). Results: The MDS, E-DII, and AHEI were associated (P < 0.05) with 9, 14, and 11 plasma markers, respectively. Healthier diets (higher MDS and AHEI, and lower anti-inflammatory, E-DII) were associated with lower concentrations of kynurenines, neopterin, IFN-γ, cytokines, and C-reactive protein. Five of 6 markers common to the 3 dietary scores were components of the kynurenine pathway. The 3 dietary-based marker scores were highly correlated (Spearman ρ: -0.74, -0.82, and 0.93). Inverse associations (for 1-SD increment) were observed with all-cause mortality for the MDS marker score (HR: 0.84; 95% CI: 0.72-0.98) and the AHEI marker score (HR: 0.76; 95% CI: 0.66-0.89), whereas a positive association was observed with the E-DII marker score (HR: 1.18; 95% CI: 1.01-1.39). The same magnitude of effect was not observed for the respective dietary patterns. Conclusions: Markers involved in inflammation-related processes are associated with dietary quality, including a substantial overlap between markers associated with the MDS, the E-DII, and the AHEI, especially kynurenines. Unfavorable marker scores, reflecting poorer-quality diets, were associated with increased mortality. (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)
Databáze:	MEDLINE
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