Journal
AMERICAN JOURNAL OF CLINICAL NUTRITION
Volume 96, Issue 6, Pages 1354-1361Publisher
AMER SOC NUTRITION-ASN
DOI: 10.3945/ajcn.112.034157
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Funding
- Cancer Research UK
- European Commission
- German Cancer Aid
- German Cancer Research Center
- German Federal Ministry of Education and Research
- Danish Cancer Society
- Health Research Fund of the Spanish Ministry of Health
- Catalan Institute of Oncology
- Medical Research Council, United Kingdom
- Stroke Association, United Kingdom
- Food Standards Agency, United Kingdom
- Hellenic Health Foundation
- Stavros Niarchos Foundation
- Hellenic Ministry of Health and Social Solidarity
- Italian Association for Research on Cancer
- Italian National Research Council
- Dutch Prevention Funds
- World Cancer Research Fund
- Swedish Scientific Council
- Regional Government of Skane, Sweden
- Nordic Centre of Excellence on Systems Biology in controlled dietary interventions and cohort studies, SYSDIET
- regional government of Andalucia, Spain
- British Heart Foundation
- Department of Health, United Kingdom
- Dutch Ministry of Public Health, Welfare and Sports
- Dutch Ministry of Health
- LK Research Funds
- Dutch Zorg Onderzoek Nederland
- Swedish Cancer Society
- regional government of Asturias, Spain
- regional government of Basque Country, Spain
- regional government of Murcia, Spain
- regional government of Navarra, Spain
- Cancer Research UK [14136] Funding Source: researchfish
- Medical Research Council [G1000143, G0401527] Funding Source: researchfish
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Background: Fatty acids in blood may be related to the risk of prostate cancer, but epidemiologic evidence is inconsistent. Blood fatty acids are correlated through shared food sources and common endogenous desaturation and elongation pathways. Studies of individual fatty acids cannot take this into account, but pattern analysis can. Treelet transform (TT) is a novel method that uses data correlation structures to derive sparse factors that explain variation. Objective: The objective was to gain further insight in the association between plasma fatty acids and risk of prostate cancer by applying TT to take data correlations into account. Design: We reanalyzed previously published data from a case-control study of prostate cancer nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. TT was used to derive factors explaining the variation in 26 plasma phospholipid fatty acids of 962 incident prostate cancer cases matched to 1061 controls. Multiple imputation was used to deal with missing data in covariates. ORs of prostate cancer according to factor scores were determined by using multivariable conditional logistic regression. Results: Four simple factors explained 38% of the variation in plasma fatty acids. A high score on a factor reflecting a long-chain n-3 PUFA pattern was associated with greater risk of prostate cancer (OR for highest compared with lowest quintile: 1.36; 95% CI: 0.99, 1.86; P-trend = 0.041). Conclusion: Pattern analyses using TT groupings of correlated fatty acids indicate that intake or metabolism of long-chain n-3 PUFAs may be relevant to prostate cancer etiology. Am J Clin Nutr 2012;96:1354-61.
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