@article{3179634,
    title = "Are Metabolic Signatures Mediating the Relationship between Lifestyle
Factors and Hepatocellular Carcinoma Risk? Results from a Nested
Case-Control Study in EPIC",
    author = "Assi, Nada and Thomas, Duncan C. and Leitzmann, Michael and Stepien, and Magdalena and Chajes, Veronique and Philip, Thierry and Vineis, Paolo and and Bamia, Christina and Boutron-Ruault, Marie-Christine and Sandanger, and Torkjel M. and Molinuevo, Amaia and Boshuizen, Hendriek C. and and Sundkvist, Anneli and Kuehn, Tilman and Travis, Ruth C. and Overvad, Kim and and Riboli, Elio and Gunter, Marc J. and Scalbert, Augustin and Jenab, and Mazda and Ferrari, Pietro and Viallon, Vivian",
    journal = "Cancer Epidemiology, Biomarkers & Prevention",
    year = "2018",
    volume = "27",
    number = "5",
    pages = "531-540",
    publisher = "AMER ASSOC CANCER RESEARCH",
    issn = "1055-9965, 1538-7755",
    doi = "10.1158/1055-9965.EPI-17-0649",
    abstract = "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."
}