BACKGROUND: Blood adipokines are associated with breast cancer risk; however, blood-breast adipokine correlations and factors that explain variation in adipokines are unknown. METHODS: Plasma (n = 155) and breast (n = 85) leptin and adiponectin were assessed by immunoassays in women with no history of cancer. Multivariable-adjusted regression models were used to determine breast adipokine associations. RESULTS: Through body mass index (BMI)-adjusted analyses, we initially observed positive plasma-breast correlations for leptin (r = 0.41, P = 0.0002) and adiponectin (r = 0.23, P = 0.05). The positive plasma-breast correlation for leptin was strongest among normal weight women (r = 0.62), whereas the correlation for adiponectin was strongest among obese women (r = 0.31). In multivariable models, adjusting for BMI, demographic, reproductive, and lifestyle factors, plasma leptin was not associated with breast leptin, and only the highest quartile of plasma adiponectin was associated with tissue levels. Of the risk factors investigated, those that contributed most to the variation in breast tissue adipokines were BMI and race for leptin, oral contraceptive use and smoking status for adiponectin. CONCLUSIONS: Although we report positive plasma-breast adipokine correlations overall, plasma adipokine concentrations may not be good surrogates for breast concentrations among all women. Predictors of breast adipokines vary, depending on subject characteristics, possibly explaining inconsistent epidemiologic results and they implicate differing pathways toward carcinogenesis. IMPACT: A clearer understanding of the relationships between plasma adipokines and their levels within the target organ is necessary to better understand the impact of these hormones on breast cancer risk. Future studies are needed to identify additional factors associated with breast adipokines in target tissues. 2012 AACR
BACKGROUND: Blood adipokines are associated with breast cancer risk; however, blood-breast adipokine correlations and factors that explain variation in adipokines are unknown. METHODS: Plasma (n = 155) and breast (n = 85) leptin and adiponectin were assessed by immunoassays in women with no history of cancer. Multivariable-adjusted regression models were used to determine breast adipokine associations. RESULTS: Through body mass index (BMI)-adjusted analyses, we initially observed positive plasma-breast correlations for leptin (r = 0.41, P = 0.0002) and adiponectin (r = 0.23, P = 0.05). The positive plasma-breast correlation for leptin was strongest among normal weight women (r = 0.62), whereas the correlation for adiponectin was strongest among obesewomen (r = 0.31). In multivariable models, adjusting for BMI, demographic, reproductive, and lifestyle factors, plasma leptin was not associated with breast leptin, and only the highest quartile of plasma adiponectin was associated with tissue levels. Of the risk factors investigated, those that contributed most to the variation in breast tissue adipokines were BMI and race for leptin, oral contraceptive use and smoking status for adiponectin. CONCLUSIONS: Although we report positive plasma-breast adipokine correlations overall, plasma adipokine concentrations may not be good surrogates for breast concentrations among all women. Predictors of breast adipokines vary, depending on subject characteristics, possibly explaining inconsistent epidemiologic results and they implicate differing pathways toward carcinogenesis. IMPACT: A clearer understanding of the relationships between plasma adipokines and their levels within the target organ is necessary to better understand the impact of these hormones on breast cancer risk. Future studies are needed to identify additional factors associated with breast adipokines in target tissues. 2012 AACR
Authors: Y Arita; S Kihara; N Ouchi; M Takahashi; K Maeda; J Miyagawa; K Hotta; I Shimomura; T Nakamura; K Miyaoka; H Kuriyama; M Nishida; S Yamashita; K Okubo; K Matsubara; M Muraguchi; Y Ohmoto; T Funahashi; Y Matsuzawa Journal: Biochem Biophys Res Commun Date: 1999-04-02 Impact factor: 3.575
Authors: Jun Wang; I-Min Lee; Shelley S Tworoger; Julie E Buring; Paul M Ridker; Bernard Rosner; Susan E Hankinson Journal: Cancer Epidemiol Biomarkers Prev Date: 2015-05-20 Impact factor: 4.254
Authors: Andrew J Pellatt; Abbie Lundgreen; Roger K Wolff; Lisa Hines; Esther M John; Martha L Slattery Journal: Cancer Causes Control Date: 2016-01 Impact factor: 2.506
Authors: Martha L Slattery; Abbie Lundgreen; Lisa Hines; Roger K Wolff; Gabriella Torres-Mejia; Kathy N Baumgartner; Esther M John Journal: Cancer Epidemiol Date: 2015-09-26 Impact factor: 2.984
Authors: Adana A M Llanos; John B Aremu; Ting-Yuan David Cheng; Wenjin Chen; Marina A Chekmareva; Elizabeth M Cespedes Feliciano; Bo Qin; Yong Lin; Coral Omene; Thaer Khoury; Chi-Chen Hong; Song Yao; Christine B Ambrosone; Elisa V Bandera; Kitaw Demissie Journal: Front Endocrinol (Lausanne) Date: 2022-06-29 Impact factor: 6.055
Authors: Adana A Llanos; Theodore M Brasky; Ramona G Dumitrescu; Catalin Marian; Kepher H Makambi; Bhaskar V S Kallakury; Scott L Spear; David J Perry; Rafael J Convit; Mary E Platek; Lucile L Adams-Campbell; Jo L Freudenheim; Peter G Shields Journal: Breast Cancer Res Treat Date: 2013-03-02 Impact factor: 4.872
Authors: Adana A Llanos; Juan Peng; Michael L Pennell; Jessica L Krok; Mara Z Vitolins; Cecilia R Degraffinreid; Electra D Paskett Journal: J Clin Endocrinol Metab Date: 2014-01-01 Impact factor: 5.958
Authors: Nicholas J Ollberding; Yeonju Kim; Yurii B Shvetsov; Lynne R Wilkens; Adrian A Franke; Robert V Cooney; Gertraud Maskarinec; Brenda Y Hernandez; Brian E Henderson; Loïc Le Marchand; Laurence N Kolonel; Marc T Goodman Journal: Cancer Prev Res (Phila) Date: 2013-03