Dokumentenart: | Artikel | ||||
---|---|---|---|---|---|
Titel eines Journals oder einer Zeitschrift: | Cancer Epidemiology Biomarkers & Prevention | ||||
Verlag: | AMER ASSOC CANCER RESEARCH | ||||
Ort der Veröffentlichung: | PHILADELPHIA | ||||
Band: | 27 | ||||
Nummer des Zeitschriftenheftes oder des Kapitels: | 5 | ||||
Seitenbereich: | S. 531-540 | ||||
Datum: | 2018 | ||||
Institutionen: | Medizin > Institut für Epidemiologie und Präventivmedizin | ||||
Identifikationsnummer: |
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Stichwörter / Keywords: | SERUM METABOLITES; AMINO-ACID; CANCER; ALCOHOL; EPIDEMIOLOGY; BIOMARKERS; OBESITY; POPULATION; PLASMA; PHOSPHATIDYLCHOLINE; | ||||
Dewey-Dezimal-Klassifikation: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin | ||||
Status: | Veröffentlicht | ||||
Begutachtet: | Ja, diese Version wurde begutachtet | ||||
An der Universität Regensburg entstanden: | Ja | ||||
Dokumenten-ID: | 47207 |
Zusammenfassung
Background: The "meeting-in-the-middle" (Nirmt) is a principle to identify exposure biornarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (I-ILO variables were related to targeted serum ...
Zusammenfassung
Background: The "meeting-in-the-middle" (Nirmt) is a principle to identify exposure biornarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (I-ILO variables were related to targeted serum metabolites. Methods: Lifestyle and targeted metabolomic data were available from 147 incident 11CC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HU to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk. Results: Exposure-related metabolic signatures were identified, Particularly, the body mass index (BMI)-associated metabolic component was positively related to 0-mantic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1,23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for 13MI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HC-C-with natural indirect effects, respectively, equal to 1.56 (1.24-1,96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100 /0 and 24%. Conclusions: In a refined M ITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk. Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators. Cancer Epiderniol Biomarkers Prey; 27(5); 531-40.(C) 2018 AACR.
Metadaten zuletzt geändert: 28 Jul 2021 17:18