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Background Several anthropometric measures have been associated with hormone-related cancers, and it has been shown that estrogen metabolism in postmenopausal women plays an important role in these relationships. However, little is known about circulating estrogen levels in African women, and the relevance to breast cancer or breast cancer risk factors. To shed further light on the relationship of anthropometric factors and estrogen levels in African women, we examined whether measured body mass index (BMI), waist-to-hip ratio (WHR), height, and self-reported body size were associated with serum estrogens/estrogen metabolites in a cross-sectional analysis among postmenopausal population-based controls of the Ghana Breast Health Study. Methods Fifteen estrogens/estrogen metabolites were quantified using liquid chromatography-tandem mass spectrometry in serum samples collected from postmenopausal female controls enrolled in the Ghana Breast Health Study, a population-based case–control study conducted in Accra and Kumasi. Geometric means (GMs) of estrogens/estrogen metabolites were estimated using linear regression, adjusting for potential confounders. Results Measured BMI (≥ 30 vs. 18.5–24.9 kg/m2) was positively associated with parent estrogens (multivariable adjusted GM for unconjugated estrone: 78.90 (66.57–93.53) vs. 50.89 (43.47–59.59), p-value p-value Conclusions We observed strong associations between measured BMI and parent estrogens and estrogen metabolite patterns that largely mirrored relations that have previously been associated with higher breast cancer risk in postmenopausal White women. The consistency of the BMI-estrogen metabolism associations in our study with those previously noted among White women suggests that estrogens likely explain part of the BMI-postmenopausal breast cancer risk in both groups. These findings merit evaluation in Black women, including prospective studies.

Additional file 1: Supplemental methods. Supplementary Figure 1. Steps of multiple imputation (for more details see Appendix A). Supplementary Table 1. Characteristics of BBD histology and breast cancers among cases by calendar year of BBD and breast cancer diagnoses (N = 514). Supplemental Table 2. Comparison of associations between select patient characteristics and histologic features with breast cancer risk in conditional and unconditional logistic regression models using multiple imputation dataset (N = 1028). Supplemental Table 3. Associations between select patient characteristics and histologic features with breast cancer risk by tumor grade (N = 922). Supplemental Table 4. Associations between select patient characteristics and histologic features with breast cancer risk by tumor size (N = 1013). Supplementary Table 5. Associations between demographic and histologic features with breast cancer risk by BBD calendar year before vs. after 1993 (N = 1028). Appendix A. Distribution of numeric variables before (top) and after (bottom) multiple imputations.

Additional file of Genetic variation in PRL and PRLR, and relationships with serum prolactin levels and breast cancer risk: results from a population-based case-control study in Poland

Authors’ original file for figure 1

Additional file 2: Table S1. Distribution of participants and breast cancer cases in different race subgroups. Table S2. Selected risk factors for hormone therapy use among eligible postmenopausal women in the entire National Institutes of Health-AARP Diet and Health Study cohort in 1996–1997. Table S3. Hormone therapy at baseline and risk of in situ breast cancer and invasive breast cancer by estrogen and progesterone receptor status, among postmenopausal women in the National Institutes of Health-AARP Diet and Health Study cohort (1996/1997–2011). Table S4. Associations of estrogen alone therapy (ET) at baseline with risk of breast cancer, by body mass index (BMI) among postmenopausal women with hysterectomy, the National Institutes of Health-AARP Diet and Health Study cohort (1996/1997–2011). Table S5. Associations of estrogen alone therapy (ET) at baseline with risk of invasive ductal and lobular breast cancer by hormone receptor status, postmenopausal women with hysterectomy, the National Institutes of Health-AARP Diet and Health Study cohort (1996/1997–2011). Table S6. Associations of estrogen plus progestin therapy (EPT) use at baseline with risk of breast cancer, by body mass index (BMI), Postmenopausal women with intact uteri, the National Institutes of Health-AARP Diet and Health Study cohort (1996/1997–2011). Table S7. Associations of estrogen plus progestin therapy (EPT) use at baseline with risk of invasive ductal and lobular breast cancer by hormone receptor status, postmenopausal women with intact uteri, the National Institutes of Health-AARP Diet and Health Study cohort (1996/ 1997–2011).

Additional file 1: Supplementary tables S1-S3. Supplementary table S1. PRLR haplotypes associated with postmenopausal breast cancer in the Polish Breast Cancer Study. Supplementary table S2. Association between PRLR and PRL SNPs and breast cancer risk in the Polish Breast Cancer Study. Supplementary table S3a. Association between PRLR and PRL SNPs and serum prolactin levels among premenopausal controls in the Polish Breast Cancer Study. Supplementary table S3b. Association between PRLR and PRL SNPs and serum prolactin levels among postmenopausal controls in the Polish Breast Cancer Study. (DOC 442 KB)

Additional file 2: Supplementary figure S1. Log-prolactin distribution in postmenopausal controls, by rs849872 genotype. (PDF 75 KB)

Additional file 1: Figure S1. Flow chart of inclusion criteria and study population.

Table S1. Selected characteristics of BREAST Stamp Project participants stratified by menopausal status. Table S2. Correlation among IGF-measures, by menopausal status. Table S3. Distribution of circulating IGF-I and IGFBPs 1–7 (ng/mL) among BREAST Stamp Project participants whose biopsies yielded benign diagnoses, stratified by menopausal status. Table S4. Age- and BMI-adjusted2 linear regression estimates for associations between IGF measures (pg/mL) and mammographic density measures, premenopausal women (N = 193). Table S5. Age- and BMI-adjusted2 linear regression estimates for associations between IGF measures (pg/mL) and mammographic density measures, postmenopausal women (N = 103). Table S6. Factor loadings for IGF analytes, overall, and by menopausal status. Table S7. Age- and BMI-adjusted1 linear regression estimates for the relation of IGF factors (in quintiles) with mammographic density measures. (DOCX 54 kb)

Select patient and clinical characteristics of women included in this study as well as the relationship between the number of CD68-positive macrophages and number of CLS (per unit area of fat) and hormones. (DOCX 25 kb)

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by BMI at age 18Â years in postmenopausal women in the Womenâ s Health Initiative Observational Study. (PDF 94 kb)

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by current BMI (

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by current BMI in postmenopausal women not using menopausal hormone therapy among control subjects only in the Womenâ s Health Initiative Observational Study. (PDF 103 kb)

Percentages of parent estrogens (estradiol and estrone) and child estrogen metabolites (2-, 4-, and 16-hydroxylation pathway metabolites) out of summed estrogens/estrogen metabolites by current BMI among current menopausal hormone therapy users. (PPTX 63 kb)

Percentages of parent estrogens (estradiol and estrone) and child estrogen metabolites (2-, 4-, and 16-hydroxylation pathway metabolites) out of summed estrogens/estrogen metabolites by current BMI among current menopausal hormone therapy users. (PPTX 63 kb)

Percentages of each pathway estrogens/estrogen metabolites (2-catechols, methylated 2-catechols, 4-catechols, methylated 4-catechols, 16-pathway metabolites) out of summed child estrogen metabolites by current BMI among current menopausal hormone therapy users. (PPTX 70 kb)

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by waist-to-hip ratio in postmenopausal women currently using menopausal hormone therapy in the Womenâ s Health Initiative Observational Study. (PDF 95 kb)

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by BMI at age 18Â years in postmenopausal women in the Womenâ s Health Initiative Observational Study. (PDF 94 kb)

Geometric means (pmol/L) and 95% CIs of serum estrogens/estrogen metabolites by waist-to-hip ratio in postmenopausal women currently using menopausal hormone therapy in the Womenâ s Health Initiative Observational Study. (PDF 95 kb)

Estrogen metabolites may have different genotoxic and mitogenic properties yet their relationship with endometrial and ovarian cancer risk remains unclear. Within the Breast and Bone Follow-up to the Fracture Intervention Trial (B ∼ FIT, n = 15,595), we conducted a case-cohort study to evaluate 15 pre-diagnostic serum estrogens and estrogen metabolites with risk of incident endometrial and ovarian cancer among postmenopausal women not on hormone therapy. Participants included 66 endometrial and 67 ovarian cancer cases diagnosed during follow-up (∼ 10 years) and subcohorts of 346 and 416 women, respectively, after relevant exclusions. Serum concentrations were measured by liquid chromatography-tandem mass spectrometry. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazard regression. Exposures were categorized in tertiles (T) and analyzed individually, as metabolic pathways (C-2, -4, or -16) and as ratios to parent estrogens (estradiol, estrone). Estradiol was significantly associated with increased endometrial cancer risk (BMI-adjusted HRT3vsT1 = 4.09, 95% CI 1.70, 9.85; p trend = 0.003). 2-Hydroxyestrone and 16α-hydroxyestrone were not associated with endometrial risk after estradiol adjustment (2-OHE1:HRT3vsT1 = 1.97, 95% CI 0.78, 4.94; 16-OHE1:HRT3vsT1 = 1.50, 95% CI 0.65, 3.46; p trend = 0.16 and 0.36, respectively). Ratios of 2- and 4-pathway catechol-to-methylated estrogens remained positively associated with endometrial cancer after BMI or estradiol adjustment (2-pathway catechols-to-methylated: HRT3vsT1 = 4.02, 95% CI 1.60, 10.1; 4-pathway catechols-to-methylated: HRT3vsT1 = 4.59, 95% CI 1.64, 12.9; p trend = 0.002 for both). Estrogens and estrogen metabolites were not associated with ovarian cancer risk; however, larger studies are needed to better evaluate these relationships. Estrogen metabolism may be important in endometrial carcinogenesis, particularly with less extensive methylation of 2- or 4-pathway catechols associated with elevated endometrial cancer risk.

Associations of IGF levels and TDLU count among women with benign breast disease with mutual adjustment for IGFBP-3 and IGF-I, overall and stratified by menopausal status. (DOC 44 kb)

Association between IGF levels and TDLU count among women with benign breast disease with mutual adjustment for IGFBP-3 and IGF-I, stratified by mammographic density. (DOC 157 kb)

Radiologic and pathologic characteristics of women in the BREAST Stamp Project with benign breast disease, stratified by menopausal status. (PDF 46 kb)

Associations between IGF levels and median category of acini count per TDLU among women with benign breast disease, overall and stratified by menopausal status. (DOC 46 kb)

Correlations between terminal duct lobular unit (TDLU) measures. (PDF 74 kb)

Associations between IGF levels and median TDLU span among women with benign breast disease, overall and stratified by menopausal status. (DOC 48 kb)

Although elevated circulating estrogens are associated with increased postmenopausal breast cancer risk, less is known regarding the role of estrogen metabolism in breast carcinogenesis. We conducted a case-cohort study within the Breast and Bone Follow-up to the Fracture Intervention Trial to assess serum estrogens and estrogen metabolites (EMs) in 407 incident breast cancer cases diagnosed during follow-up and a subcohort of 496 women. In 1992-93, women completed a baseline questionnaire and provided blood samples. Hazard ratios (HRs) and 95% confidence intervals (CIs), adjusted for geography and trial participation status, were estimated using Cox proportional hazard regression. Serum concentrations of EMs were measured by liquid chromatography-tandem mass spectrometry. EMs (quintiles, Q) were analyzed individually, as metabolic pathways (C-2, -4 or -16) and as ratios. Elevated circulating estradiol was associated with increased breast cancer risk (HRQ5vsQ1 = 1.86; 95% CI: 1.19-2.90; P trend = 0.04). An elevated ratio of the 2-hydroxylation pathway (HRQ5vsQ1 = 0.69; 95% CI: 0.46-1.05; P trend = 0.01) and 4-hydroxylation pathway (HRQ5vsQ1 = 0.61; 95% CI: 0.40-0.93; P trend = 0.004) to parent estrogens (estradiol and estrone) was inversely associated with risk. A higher ratio of the 2/16-hydroxylation pathways was associated with reduced risk (HRQ5vsQ1 = 0.60; 95% CI: 0.40-0.90; P trend = 0.002). Increased 2- or 4-hydroxylation of parent estrogens may lower risk of postmenopausal breast cancer. Analyses of metabolic pathways may help elucidate the role of estrogen metabolism in breast carcinogenesis.

Endometrial cancer risk is strongly influenced by obesity, but the mechanisms of action remain unclear. Leptin and adiponectin, secreted from adipose tissue, reportedly play a role in such carcinogenic processes as cell proliferation, angiogenesis, and insulin regulation. In this case-control study, nested within the Breast and Bone Follow-up of the Fracture Intervention Trial (n=15,595), we assessed pre-diagnostic serum leptin, total adiponectin, and high-molecular-weight (HMW) adiponectin in relation to endometrial cancer among postmenopausal women. During the 10-year follow-up, 62 incident endometrial cases were identified and matched to 124 controls on age, geographical site, time of fasting blood draw at baseline (1992-1993), and trial participation status. Adipokines and C-peptide were measured by ELISA. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated via conditional logistic regression, with exposures categorized in tertiles (T). Multivariable models considered C-peptide, BMI (kg/m(2)), and estradiol (E2) as potential confounders. Endometrial cancer risk was significantly associated with higher leptin levels, adjusted for E2 and C-peptide (OR(T3 vs T1)=2.96; 95% CI, 1.21-7.25; P trend

Table S1. Breast cancer incidence and competing mortality rates used for each cohort to estimate absolute risk. Table S2. Descriptive characteristics of invasive + in situ cases and matched controls. Table S3. Descriptive characteristics of invasive breast cancer cases and matched controls, by cohort. Table S4. Descriptive characteristics of invasive plus in situ breast cancer cases and matched controls, by cohort. Table S5. Random-effects meta-analysis relative risk estimates, invasive and in situ. Figure S1. Cohort-specific and random-effects meta-analysis relative risk estimates for Gail model variables, AMH and testosterone (invasive cases only). Figure S2. Cohort-specific and random-effects meta-analysis relative risk estimates for Gail model variables, AMH and testosterone, invasive and in situ. Figure S3. Relative risk estimates by age group, invasive cases only. Figure S4. AUCs by cohort 95% confidence intervals, invasive and in situ. (DOCX 254 kb)

Table S1. Breast cancer incidence and competing mortality rates used for each cohort to estimate absolute risk. Table S2. Descriptive characteristics of invasive + in situ cases and matched controls. Table S3. Descriptive characteristics of invasive breast cancer cases and matched controls, by cohort. Table S4. Descriptive characteristics of invasive plus in situ breast cancer cases and matched controls, by cohort. Table S5. Random-effects meta-analysis relative risk estimates, invasive and in situ. Figure S1. Cohort-specific and random-effects meta-analysis relative risk estimates for Gail model variables, AMH and testosterone (invasive cases only). Figure S2. Cohort-specific and random-effects meta-analysis relative risk estimates for Gail model variables, AMH and testosterone, invasive and in situ. Figure S3. Relative risk estimates by age group, invasive cases only. Figure S4. AUCs by cohort 95% confidence intervals, invasive and in situ. (DOCX 254 kb)