TY - JOUR
TI - Are Metabolic Signatures Mediating the Relationship between Lifestyle
Factors and Hepatocellular Carcinoma Risk? Results from a Nested
Case-Control Study in EPIC
AU - Assi, Nada
AU - Thomas, Duncan C.
AU - Leitzmann, Michael
AU - Stepien,
AU - Magdalena
AU - Chajes, Veronique
AU - Philip, Thierry
AU - Vineis, Paolo
AU - and Bamia, Christina
AU - Boutron-Ruault, Marie-Christine
AU - Sandanger,
AU - Torkjel M.
AU - Molinuevo, Amaia
AU - Boshuizen, Hendriek C. and
AU - Sundkvist, Anneli
AU - Kuehn, Tilman
AU - Travis, Ruth C.
AU - Overvad, Kim
AU - and Riboli, Elio
AU - Gunter, Marc J.
AU - Scalbert, Augustin
AU - Jenab,
AU - Mazda
AU - Ferrari, Pietro
AU - Viallon, Vivian
JO - Cancer Epidemiology, Biomarkers & Prevention
PY - 2018
VL - 27
TODO - 5
SP - 531-540
PB - AMER ASSOC CANCER RESEARCH
SN - 1055-9965, 1538-7755
TODO - 10.1158/1055-9965.EPI-17-0649
TODO - null
TODO - 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.
ER -