Literature DB >> 29325144

A Metabolomics Analysis of Body Mass Index and Postmenopausal Breast Cancer Risk.

Steven C Moore1, Mary C Playdon1, Joshua N Sampson1, Robert N Hoover1, Britton Trabert1, Charles E Matthews1, Regina G Ziegler1.   

Abstract

Background: Elevated body mass index (BMI) is associated with increased risk of postmenopausal breast cancer. The underlying mechanisms, however, remain elusive.
Methods: In a nested case-control study of 621 postmenopausal breast cancer case participants and 621 matched control participants, we measured 617 metabolites in prediagnostic serum. We calculated partial Pearson correlations between metabolites and BMI, and then evaluated BMI-associated metabolites (Bonferroni-corrected α level for 617 statistical tests = P < 8.10 × 10-5) in relation to invasive breast cancer. Odds ratios (ORs) of breast cancer comparing the 90th vs 10th percentile (modeled on a continuous basis) were estimated using conditional logistic regression while controlling for breast cancer risk factors, including BMI. Metabolites with the lowest P values (false discovery rate < 0.2) were mutually adjusted for one another to determine those independently associated with breast cancer risk.
Results: Of 67 BMI-associated metabolites, two were independently associated with invasive breast cancer risk: 16a-hydroxy-DHEA-3-sulfate (OR = 1.65, 95% confidence interval [CI] = 1.22 to 2.22) and 3-methylglutarylcarnitine (OR = 1.67, 95% CI = 1.21 to 2.30). Four metabolites were independently associated with estrogen receptor-positive (ER+) breast cancer risk: 16a-hydroxy-DHEA-3-sulfate (OR = 1.84, 95% CI = 1.27 to 2.67), 3-methylglutarylcarnitine (OR = 1.91, 95% CI = 1.23 to 2.96), allo-isoleucine (OR = 1.76, 95% CI = 1.23 to 2.51), and 2-methylbutyrylcarnitine (OR = 1.89, 95% CI = 1.22 to 2.91). In a model without metabolites, each 5 kg/m2 increase in BMI was associated with a 14% higher risk of breast cancer (OR = 1.14, 95% CI = 1.01 to 1.28), but adding 16a-hydroxy-DHEA-3-sulfate and 3-methylglutarylcarnitine weakened this association (OR = 1.06, 95% CI = 0.93 to 1.20), with the logOR attenuating by 57.6% (95% CI = 21.8% to 100.0+%).
Conclusion: These four metabolites may signal metabolic pathways that contribute to breast carcinogenesis and that underlie the association of BMI with increased postmenopausal breast cancer risk. These findings warrant further replication efforts.

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Year:  2018        PMID: 29325144      PMCID: PMC6279273          DOI: 10.1093/jnci/djx244

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  66 in total

1.  Plasma amino acid levels and insulin secretion in obesity.

Authors:  P Felig; E Marliss; G F Cahill
Journal:  N Engl J Med       Date:  1969-10-09       Impact factor: 91.245

2.  Plasma metabolomic profiles in association with type 2 diabetes risk and prevalence in Chinese adults.

Authors:  Danxia Yu; Steven C Moore; Charles E Matthews; Yong-Bing Xiang; Xianglan Zhang; Yu-Tang Gao; Wei Zheng; Xiao-Ou Shu
Journal:  Metabolomics       Date:  2015-11-07       Impact factor: 4.290

3.  Association of Estrogen Metabolism with Breast Cancer Risk in Different Cohorts of Postmenopausal Women.

Authors:  Joshua N Sampson; Roni T Falk; Catherine Schairer; Steven C Moore; Barbara J Fuhrman; Cher M Dallal; Douglas C Bauer; Joanne F Dorgan; Xiao-Ou Shu; Wei Zheng; Louise A Brinton; Mitchell H Gail; Regina G Ziegler; Xia Xu; Robert N Hoover; Gretchen L Gierach
Journal:  Cancer Res       Date:  2016-12-23       Impact factor: 12.701

4.  Estrogen metabolism and risk of breast cancer in postmenopausal women.

Authors:  Barbara J Fuhrman; Catherine Schairer; Mitchell H Gail; Jennifer Boyd-Morin; Xia Xu; Laura Y Sue; Saundra S Buys; Claudine Isaacs; Larry K Keefer; Timothy D Veenstra; Christine D Berg; Robert N Hoover; Regina G Ziegler
Journal:  J Natl Cancer Inst       Date:  2012-01-09       Impact factor: 13.506

5.  Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies.

Authors:  T Key; P Appleby; I Barnes; G Reeves
Journal:  J Natl Cancer Inst       Date:  2002-04-17       Impact factor: 13.506

6.  A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance.

Authors:  Christopher B Newgard; Jie An; James R Bain; Michael J Muehlbauer; Robert D Stevens; Lillian F Lien; Andrea M Haqq; Svati H Shah; Michelle Arlotto; Cris A Slentz; James Rochon; Dianne Gallup; Olga Ilkayeva; Brett R Wenner; William S Yancy; Howard Eisenson; Gerald Musante; Richard S Surwit; David S Millington; Mark D Butler; Laura P Svetkey
Journal:  Cell Metab       Date:  2009-04       Impact factor: 27.287

7.  On the mechanisms of the formation of L-alloisoleucine and the 2-hydroxy-3-methylvaleric acid stereoisomers from L-isoleucine in maple syrup urine disease patients and in normal humans.

Authors:  O A Mamer; M L Reimer
Journal:  J Biol Chem       Date:  1992-11-05       Impact factor: 5.157

8.  Brain insulin lowers circulating BCAA levels by inducing hepatic BCAA catabolism.

Authors:  Andrew C Shin; Martin Fasshauer; Nika Filatova; Linus A Grundell; Elizabeth Zielinski; Jian-Ying Zhou; Thomas Scherer; Claudia Lindtner; Phillip J White; Amanda L Lapworth; Olga Ilkayeva; Uwe Knippschild; Anna M Wolf; Ludger Scheja; Kevin L Grove; Richard D Smith; Wei-Jun Qian; Christopher J Lynch; Christopher B Newgard; Christoph Buettner
Journal:  Cell Metab       Date:  2014-10-09       Impact factor: 27.287

9.  Alloisoleucine differentiates the branched-chain aminoacidemia of Zucker and dietary obese rats.

Authors:  Kristine C Olson; Gang Chen; Yuping Xu; Andras Hajnal; Christopher J Lynch
Journal:  Obesity (Silver Spring)       Date:  2014-03-17       Impact factor: 5.002

10.  Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change.

Authors:  Peter Würtz; Qin Wang; Antti J Kangas; Rebecca C Richmond; Joni Skarp; Mika Tiainen; Tuulia Tynkkynen; Pasi Soininen; Aki S Havulinna; Marika Kaakinen; Jorma S Viikari; Markku J Savolainen; Mika Kähönen; Terho Lehtimäki; Satu Männistö; Stefan Blankenberg; Tanja Zeller; Jaana Laitinen; Anneli Pouta; Pekka Mäntyselkä; Mauno Vanhala; Paul Elliott; Kirsi H Pietiläinen; Samuli Ripatti; Veikko Salomaa; Olli T Raitakari; Marjo-Riitta Järvelin; George Davey Smith; Mika Ala-Korpela
Journal:  PLoS Med       Date:  2014-12-09       Impact factor: 11.069

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  37 in total

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Journal:  Metabolomics       Date:  2019-01-07       Impact factor: 4.290

2.  Using Metabolomics to Explore the Role of Postmenopausal Adiposity in Breast Cancer Risk.

Authors:  Jessica A Lasky-Su; Oana A Zeleznik; A Heather Eliassen
Journal:  J Natl Cancer Inst       Date:  2018-06-01       Impact factor: 13.506

3.  Breast cancer risk in relation to plasma metabolites among Hispanic and African American women.

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5.  Associations between metabolites and pancreatic cancer risk in a large prospective epidemiological study.

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Journal:  Gut       Date:  2020-02-14       Impact factor: 23.059

6.  A Prospective Analysis of Circulating Plasma Metabolites Associated with Ovarian Cancer Risk.

Authors:  Clary B Clish; Shelley S Tworoger; Oana A Zeleznik; A Heather Eliassen; Peter Kraft; Elizabeth M Poole; Bernard A Rosner; Sarah Jeanfavre; Amy A Deik; Kevin Bullock; Daniel S Hitchcock; Julian Avila-Pacheco
Journal:  Cancer Res       Date:  2020-01-22       Impact factor: 12.701

7.  Validation of plasma metabolites associated with breast cancer risk among Mexican Americans.

Authors:  Hua Zhao; Jie Shen; Yuanqing Ye; Xifeng Wu; Francisco J Esteva; Debasish Tripathy; Wong-Ho Chow
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8.  Serum Metabolomics and Incidence of Atrial Fibrillation (from the Atherosclerosis Risk in Communities Study).

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Journal:  Am J Cardiol       Date:  2019-03-18       Impact factor: 2.778

9.  The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies.

Authors:  Bing Yu; Krista A Zanetti; Marinella Temprosa; Demetrius Albanes; Nathan Appel; Clara Barrios Barrera; Yoav Ben-Shlomo; Eric Boerwinkle; Juan P Casas; Clary Clish; Caroline Dale; Abbas Dehghan; Andriy Derkach; A Heather Eliassen; Paul Elliott; Eoin Fahy; Christian Gieger; Marc J Gunter; Sei Harada; Tamara Harris; Deron R Herr; David Herrington; Joel N Hirschhorn; Elise Hoover; Ann W Hsing; Mattias Johansson; Rachel S Kelly; Chin Meng Khoo; Mika Kivimäki; Bruce S Kristal; Claudia Langenberg; Jessica Lasky-Su; Deborah A Lawlor; Luca A Lotta; Massimo Mangino; Loïc Le Marchand; Ewy Mathé; Charles E Matthews; Cristina Menni; Lorelei A Mucci; Rachel Murphy; Matej Oresic; Eric Orwoll; Jennifer Ose; Alexandre C Pereira; Mary C Playdon; Lucilla Poston; Jackie Price; Qibin Qi; Kathryn Rexrode; Adam Risch; Joshua Sampson; Wei Jie Seow; Howard D Sesso; Svati H Shah; Xiao-Ou Shu; Gordon C S Smith; Ulla Sovio; Victoria L Stevens; Rachael Stolzenberg-Solomon; Toru Takebayashi; Therese Tillin; Ruth Travis; Ioanna Tzoulaki; Cornelia M Ulrich; Ramachandran S Vasan; Mukesh Verma; Ying Wang; Nick J Wareham; Andrew Wong; Naji Younes; Hua Zhao; Wei Zheng; Steven C Moore
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10.  COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia.

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Journal:  Am J Epidemiol       Date:  2022-01-01       Impact factor: 4.897

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