Grant Details
Grant Number: |
5R03CA223619-02 Interpret this number |
Primary Investigator: |
Giovannucci, Edward |
Organization: |
Harvard School Of Public Health |
Project Title: |
Predicted Lean Body Mass, Fat Mass, and Risk of Lung, Pancreatic, Colorectal, Breast, and Prostate Cancers |
Fiscal Year: |
2019 |
Abstract
Project Summary/Abstract
Our current understanding of obesity and cancer is largely limited to studies that have used body mass index
(BMI) as the sole measure of excess adiposity. However, fat mass and lean body mass, which cannot be
distinguished by BMI, may have distinct effect on cancer. Hence, failure to assess the independent role of fat
mass and lean body mass may dilute or even distort the true relationship between obesity and cancer
endpoints, as exemplified by the `obesity paradox'. Attempts to examine the effect of body composition have
been hampered by infeasibility in using expensive technologies in large scale. We offer a novel approach to
overcome this limitation and explore the association between lean body mass and fat mass and the risk of
major cancers, including lung, pancreatic, colorectal, breast, and prostate cancers. We propose to use
anthropometric prediction models, which were developed in the National Health and Nutrition Examination
Survey and validated using obesity-related biomarkers. The predicted lean body mass and fat mass were
further tested in relation to mortality in the Health Professional Follow-up Study (HPFS) and Nurses' Health
Study (NHS) to ensure the significance and feasibility of the proposed aims. Aim 1 will further build on existing
evidence on the harmful effect of adiposity on cancer development by examining the association between fat
mass and cancer endpoints that is independent of lean body mass. Compared to prior literature using BMI, a
stronger and more linear association may be detected with predicted fat mass. Aim 2 will be the first analysis to
test whether the emerging evidence suggesting beneficial effect of lean body mass on chronic diseases holds
true for the risk of major cancers. If lean body mass, independent of fat mass, has inverse association with
cancer endpoints, then future studies and interventions should emphasize the role of lean body mass, and not
just body weight per se. For Aims 1 and 2, we will leverage the repeated measures over three decades of
follow-up in the HPFS and NHS to explore the latency periods and change in body composition that can
uncover important biological mechanisms underlying cancer development. Aim 3 will perform stratified
analyses by age and smoking status to better understand heterogeneous cancer etiologies. Given that body
composition changes unfavorably with aging, decomposing the effect of lean body mass and fat mass may be
particularly relevant for the older population. Moreover, stratification by smoking can appropriately address
confounding and capture the changes in body composition resulting from smoking. In summary, the proposed
study has great potentials to provide novel insights into the role of lean body mass and fat mass in cancer
incidence that are distinctive from prior studies that have used BMI measure. This study will serve as a
promising step towards development of a clinically feasible method to better characterize future cancer risk,
facilitate research directed to assessing the effect of specific body compartments, and generate new evidence
to inform weight and lifestyle guidelines for cancer prevention.
Publications
Low glycaemic diets alter lipid metabolism to influence tumour growth.
Authors: Lien E.C.
, Westermark A.M.
, Zhang Y.
, Yuan C.
, Li Z.
, Lau A.N.
, Sapp K.M.
, Wolpin B.M.
, Vander Heiden M.G.
.
Source: Nature, 2021 11; 599(7884), p. 302-307.
EPub date: 2021-10-20 00:00:00.0.
PMID: 34671163
Related Citations
Timing of Aspirin Use in Colorectal Cancer Chemoprevention: A Prospective Cohort Study.
Authors: Zhang Y.
, Chan A.T.
, Meyerhardt J.A.
, Giovannucci E.L.
.
Source: Journal Of The National Cancer Institute, 2021-07-01 00:00:00.0; 113(7), p. 841-851.
PMID: 33528007
Related Citations
Predicted lean body mass, fat mass and risk of lung cancer: prospective US cohort study.
Authors: Jeong S.M.
, Lee D.H.
, Giovannucci E.L.
.
Source: European Journal Of Epidemiology, 2019-11-21 00:00:00.0; , .
EPub date: 2019-11-21 00:00:00.0.
PMID: 31754943
Related Citations
Long-term status of predicted body fat percentage, body mass index and other anthropometric factors with risk of colorectal carcinoma: Two large prospective cohort studies in the US.
Authors: Hanyuda A.
, Lee D.H.
, Ogino S.
, Wu K.
, Giovannucci E.L.
.
Source: International Journal Of Cancer, 2019-07-05 00:00:00.0; , .
EPub date: 2019-07-05 00:00:00.0.
PMID: 31276608
Related Citations
Comparison of the association of predicted fat mass, body mass index, and other obesity indicators with type 2 diabetes risk: two large prospective studies in US men and women.
Authors: Lee D.H.
, Keum N.
, Hu F.B.
, Orav E.J.
, Rimm E.B.
, Willett W.C.
, Giovannucci E.L.
.
Source: European Journal Of Epidemiology, 2018-08-16 00:00:00.0; , .
EPub date: 2018-08-16 00:00:00.0.
PMID: 30117031
Related Citations
Predicted lean body mass, fat mass, and all cause and cause specific mortality in men: prospective US cohort study.
Authors: Lee D.H.
, Keum N.
, Hu F.B.
, Orav E.J.
, Rimm E.B.
, Willett W.C.
, Giovannucci E.L.
.
Source: Bmj (clinical Research Ed.), 2018-07-03 00:00:00.0; 362, p. k2575.
EPub date: 2018-07-03 00:00:00.0.
PMID: 29970408
Related Citations