Christina C. Dahm

Fatty acid patterns and risk of prostate cancer in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Christina C Dahm
  • Anders Gorst-Rasmussen
  • Francesca L Crowe
  • ,
  • Nina Roswall, Danish Cancer Society, Denmark
  • Anne Tjønneland, Danish Cancer Society, Denmark
  • Dagmar Drogan
  • ,
  • Heiner Boeing
  • ,
  • Birgit Teucher
  • ,
  • Rudolf Kaaks
  • ,
  • George Adarakis
  • ,
  • Dimosthenes Zylis
  • ,
  • Antonia Trichopoulou
  • ,
  • Veronika Fedirko
  • ,
  • Veronique Chajes
  • ,
  • Mazda Jenab
  • ,
  • Domenico Palli
  • ,
  • Valeria Pala
  • ,
  • Rosario Tumino
  • ,
  • Fulvio Ricceri
  • ,
  • Henk van Kranen
  • ,
  • H Bas Bueno-de-Mesquita
  • ,
  • Jose R Quirós
  • ,
  • María-José Sánchez
  • ,
  • Leila Luján-Barroso
  • ,
  • Nerea Larrañaga
  • ,
  • María-Dolores Chirlaque
  • ,
  • Eva Ardanaz
  • ,
  • Mattias Johansson
  • ,
  • Pär Stattin
  • ,
  • Kay-Tee Khaw
  • ,
  • Nick Wareham
  • ,
  • Petra A Wark
  • ,
  • Teresa Norat
  • ,
  • Elio Riboli
  • ,
  • Tim J Key
  • ,
  • Kim Overvad
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.
Original languageEnglish
JournalAmerican Journal of Clinical Nutrition
Volume96
Issue6
Pages (from-to)1354-61
Number of pages8
ISSN0002-9165
DOIs
Publication statusPublished - Dec 2012

See relations at Aarhus University Citationformats

ID: 50940805