Background: Fatty acids in blood may be related to the risk of prostate cancer, but epidemiologic evidence is inconsistent. Blood fatty acids... » More

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 casecontrol

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

n23 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 n23 PUFAs

may be relevant to prostate cancer etiology.

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