A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study
Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations...
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doaj-580ca562eb854594ae0ec42f12e0d9f42020-11-25T02:57:38ZengMDPI AGMetabolites2218-19892020-03-011039910.3390/metabo10030099metabo10030099A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up StudyBarbra A. Dickerman0Ericka M. Ebot1Brian C. Healy2Kathryn M. Wilson3A. Heather Eliassen4Alberto Ascherio5Claire H. Pernar6Oana A. Zeleznik7Matthew G. Vander Heiden8Clary B. Clish9Edward Giovannucci10Lorelei A. Mucci11Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Neurology, Harvard Medical School, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USAChanning Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USAKoch Institute for Integrative Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USABroad Institute of Massachusetts, Institute of Technology and Harvard, Boston, MA 02142, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USADepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USAObesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations between 165 circulating metabolites and three adiposity measures (BMI, waist circumference, and derived fat mass from a validated prediction equation) to identify adiposity-associated metabolites. We used Lasso to further select metabolites for prediction models of adiposity measures, which we used to calculate metabolic scores representing metabolic obesity. In an independent set of 212 advanced prostate cancer cases (T3b/T4/N1/M1 or lethal during follow-up) and 212 controls, we used logistic regression to evaluate the associations between adiposity measures and metabolic scores with risk of advanced disease. All adiposity measures were associated with higher blood levels of carnitines (Pearson <i>r</i> range, 0.16 to 0.18) and lower levels of glutamine (<i>r</i> = −0.19) and glycine (<i>r,</i> −0.29 to −0.20), in addition to alterations in various lipids. No adiposity measure or metabolic score was associated with risk of advanced prostate cancer (e.g., odds ratio for a 5 kg/m<sup>2</sup> increase in BMI 0.96 (95% CI: 0.73, 1.27) and BMI metabolic score 1.18 (95% CI: 0.57, 2.48)). BMI, waist circumference, and derived fat mass were associated with a broad range of metabolic alterations. Neither adiposity nor metabolic scores were associated with risk of advanced prostate cancer.https://www.mdpi.com/2218-1989/10/3/99adiposityepidemiologyfat massmetabolomicsobesityadvanced prostate cancerwaist circumference |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Barbra A. Dickerman Ericka M. Ebot Brian C. Healy Kathryn M. Wilson A. Heather Eliassen Alberto Ascherio Claire H. Pernar Oana A. Zeleznik Matthew G. Vander Heiden Clary B. Clish Edward Giovannucci Lorelei A. Mucci |
spellingShingle |
Barbra A. Dickerman Ericka M. Ebot Brian C. Healy Kathryn M. Wilson A. Heather Eliassen Alberto Ascherio Claire H. Pernar Oana A. Zeleznik Matthew G. Vander Heiden Clary B. Clish Edward Giovannucci Lorelei A. Mucci A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study Metabolites adiposity epidemiology fat mass metabolomics obesity advanced prostate cancer waist circumference |
author_facet |
Barbra A. Dickerman Ericka M. Ebot Brian C. Healy Kathryn M. Wilson A. Heather Eliassen Alberto Ascherio Claire H. Pernar Oana A. Zeleznik Matthew G. Vander Heiden Clary B. Clish Edward Giovannucci Lorelei A. Mucci |
author_sort |
Barbra A. Dickerman |
title |
A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study |
title_short |
A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study |
title_full |
A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study |
title_fullStr |
A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study |
title_full_unstemmed |
A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study |
title_sort |
metabolomics analysis of adiposity and advanced prostate cancer risk in the health professionals follow-up study |
publisher |
MDPI AG |
series |
Metabolites |
issn |
2218-1989 |
publishDate |
2020-03-01 |
description |
Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations between 165 circulating metabolites and three adiposity measures (BMI, waist circumference, and derived fat mass from a validated prediction equation) to identify adiposity-associated metabolites. We used Lasso to further select metabolites for prediction models of adiposity measures, which we used to calculate metabolic scores representing metabolic obesity. In an independent set of 212 advanced prostate cancer cases (T3b/T4/N1/M1 or lethal during follow-up) and 212 controls, we used logistic regression to evaluate the associations between adiposity measures and metabolic scores with risk of advanced disease. All adiposity measures were associated with higher blood levels of carnitines (Pearson <i>r</i> range, 0.16 to 0.18) and lower levels of glutamine (<i>r</i> = −0.19) and glycine (<i>r,</i> −0.29 to −0.20), in addition to alterations in various lipids. No adiposity measure or metabolic score was associated with risk of advanced prostate cancer (e.g., odds ratio for a 5 kg/m<sup>2</sup> increase in BMI 0.96 (95% CI: 0.73, 1.27) and BMI metabolic score 1.18 (95% CI: 0.57, 2.48)). BMI, waist circumference, and derived fat mass were associated with a broad range of metabolic alterations. Neither adiposity nor metabolic scores were associated with risk of advanced prostate cancer. |
topic |
adiposity epidemiology fat mass metabolomics obesity advanced prostate cancer waist circumference |
url |
https://www.mdpi.com/2218-1989/10/3/99 |
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