Steroid hormone metabolites and mammographic breast density in premenopausal women.

Background: Steroid hormones influence breast tissue development and play a role in breast carcinogenesis. Their associations with mammographic breast density (MBD), an established risk factor for breast cancer, are less clear. We, therefore, investigated the associations of steroid hormone metabolites with MBD in premenopausal women. Methods: Our study population consists of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. We assessed volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV) using Volpara. We assayed 54 steroid hormone metabolites from fasting blood samples at Metabolon. Linear regression models were used, after adjusting for covariates, to estimate the least square means of VPD, DV, and NDV across tertiles (T) of each metabolite. Sensitivity analysis was performed among the subset of participants with a history of oral contraceptive use (OCP). We used the Benjamini-Hochberg procedure to correct for multiple tests to control the false discovery rate (FDR) at a 5% level. Results: Five androgen metabolites (androstenediol (3beta,17beta) monosulfate 2, androstenediol (3beta,17beta) disulfate 1, 5alpha-androstan-3alpha,17beta-diol monosulfate 2, 5alpha-androstan-3alpha,17beta-diol disulfate, and 5alpha-androstan-3beta,17beta-diol disulfate) and two corticosteroid metabolites (tetrahydrocortisone glucuronide 5, and cortolone glucuronide 1) were inversely associated with VPD. Androstenediol (3beta,17beta) disulfate 1, and 5alpha-androstan-3alpha,17beta-diol disulfate displayed the strongest associations with VPD. The mean VPD decreased across tertiles of androstenediol (3beta,17beta) disulfate 1 from 9.0% in T1 to 8.5% in T2, and 7.5% in T3 (FDR p-value=0.02). Similarly, the mean VPD decreased from 8.8% in T1 to 8.4% in T2, and 7.6% in T3 of 5alpha-androstan-3alpha,17beta-diol disulfate (FDR p-value=0.03). Progestin steroid metabolites appeared to be positively associated with VPD but only 5alpha-pregnan-3beta,20alpha-diol monosulfate 2 was marginally significant after FDR correction (7.5% in T1, 8.3% in T2, and 8.8% in T3; FDR p-value=0.06). Four metabolites (three corticosteroids and one androgenic steroid) were positively associated with NDV. No metabolite was associated with DV. In sensitivity analysis limited to OCP users, mean VPDs were lower but the directions of associations were similar to those observed in the overall analysis. Conclusion: We report novel associations of corticosteroids and androgen metabolites with breast density in premenopausal women. Our findings shed important new insights into hormonal biomarkers and MBD. Citation Format: Kayode A. Matthew, Girish K. Vanapali, Kayla R. Getz, Myung S. Jeon, Chongliang Luo, Xingyi Guo, Jingqin Luo, Adetunji T. Toriola. Steroid hormone metabolites and mammographic breast density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4431.

Introduction: High mammographic breast density (MBD) is a strong risk factor for breast cancer, but the biological mechanisms underlying high MBD are not well understood. We, therefore, comprehensively investigated for the first time the associations of lipid species with volumetric measures of MBD to elucidate potential biological mechanisms of high MBD in premenopausal women. Methods: We performed lipidomic profiling on 705 premenopausal women recruited during their annual screening mammogram at Washington University School of Medicine, St. Louis, MO. Lipidomic profiling for 982 lipid species was completed at Metabolon (Durham, NC®). Lipid species with greater than 300 missing values (N=125) were excluded from the analysis. Using nearest neighbor methods, we imputed the lipid species missing less than 300 values. We used Volpara 1.5 (Volpara Health®) to quantify volumetric measures of MBD - volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV). We investigated the associations of the lipid species with MBD measures using multivariable linear regression models adjusting for age, age at menarche, body shape at age 10, race/ethnicity, body fat %, family history of breast cancer, oral contraceptive use, parity/age at first birth, and alcohol use. MBD measures were log10-transformed, and lipid species were standardized. Linear coefficients were back-transformed to the original scale and considered significant if the Bonferroni corrected p<0.05. Results: In multivariable linear regression models, 34 lipid species were inversely associated with VPD. The lipid species belong to the triacylglycerol (TAG, N=26), diacylglycerol (DAG, N=6), phosphatidylcholine (PC, N=1), and cholesterol ester (N=1) pathways. DAG(16:0/18:2) and TAG54:6-FA20:4 displayed the largest inverse associations with one standard deviation increase in DAG(16:0/18:2), and TAG54:6-FA20:4 corresponding to 9.9% (p=0.002), and 9.6% (p=0.007) decrease in VPD, respectively. Eleven lipid species were significantly associated with NDV, with 10 species (all TAG) having a positive association and 1 inverse association PC(18:1/18:1). The strongest positive association was observed with TAG54:6-FA20:4. One standard deviation increase in TAG54:6-FA20:4 was associated with a 9.8% increase in NDV (p=0.01). Several of the lipid species (N=8, 23.5%) that were associated with VPD were also associated with NDV, but in opposite directions. No lipid species were significantly associated with DV. Conclusions: Our study identified many lipid species, especially in TAG and DAG pathways, that were associated with VPD and NDV and offer new insights into the biological mechanisms underlying high MBD in premenopausal women. Future studies are needed to validate our results and the translational potential. Citation Format: Kayla R. Getz, Myung S. Jeon, Chongliang Luo, Jingqin Luo, Adetunji T. Toriola. Lipidome of mammographic breast density in premenopausal women. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4173.

Background: Higher mammographic breast density is a strong risk factor for breast cancer. Early-life factors may influence breast development and subsequent breast density in adulthood. Although childhood adiposity is inversely associated with breast cancer risk, the association of childhood adiposity with mammographic breast density in premenopausal women has not been adequately studied. This knowledge could provide insight into pathways linking mammographic density and breast cancer risk. We investigated the associations between adiposity at age 10 and mammographic density. Methods: We collected data from 370 premenopausal women during their routine screening mammograms at Washington University in St. Louis, MO from December 2015 to October 2016. Body size at age 10 was self-reported using the Stunkard 9-figure Somatotype pictogram. For these analyses, the Stunkard pictogram was collapsed into 4 groups: (i) body size 1 or 2, (ii) body size 3 or 4, (iii) body size 5, (iv) body size 6 or higher. Body mass index (BMI) at age 10 was imputed using BMI and Stunkard data from the Growing Up Today Study. Trained personnel collected womens' height and weight, which were used to calculate current BMI. We used the Volpara software to evaluate the following volumetric mammographic density measures: volumetric percent density (VPD), dense volume (DV) and non-dense volume (NDV). Age-adjusted Pearson correlations and multivariable linear regression models (adjusted for age, age at each given birth, family history, race, education, oral contraceptive use, and breast feeding history) were used to evaluate the associations between adiposity at age 10 and volumetric mammographic density measures. Results: The mean age at the time of screening mammogram was 47.1 years. The majority of the women (43.8%) reported having body size 1 or 2, followed by body size 3 or 4 (34.9%), body size 5 (13.8%) and body size 6 (7.6%) at age 10. We observed a negative correlation between BMI at age 10 (r= -0.28, p-value<0.001) and VPD, and a positive correlation between BMI at age 10 (r= 0.27, p-value<0.001) and NDV. In multivariable regression models, adiposity at age 10 was significantly inversely associated with VPD, and positively associated with NDV. A 1kg/m2 increase in BMI at age 10 was associated with a 6.3% decrease in VPD (p-value <0.001), and a 6.7% increase in NDV (p-value <0.001). Compared to women whose body sizes were 1 and 2 at age 10, women with body size 3 or 4 had a 17.6% decrease in VPD, and a 28.5% increase in NDV; women with body size 5 had a 32.3% decrease in VPD, and a 58.1% increase in NDV, and women with body sizes ≥6 had a 46.6% decrease in VPD, and a 75.1% increase in NDV (all p-values <0.05). The associations of body size at age 10 and VPD were attenuated, but still statistically significant when we adjusted for current BMI. No statistically significant associations were found between adiposity at age 10 and DV. Conclusions: Our findings of an inverse association between adiposity at age 10 and percent density suggest that adiposity at age 10 could impact breast cancer development via its effect on mammographic density. Mechanistic studies to understand how childhood adiposity reduces mammographic density and breast cancer development in premenopausal women are needed. Citation Format: Alimujiang A, Imm KR, Appleton CM, Colditz GA, Berkey CS, Toriola AT. Adiposity at age 10 and mammographic density among premenopausal women [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-01-01.

Mammographic breast density (MBD) is a strong risk factor and an intermediate phenotype for breast cancer, yet there are limited studies on how environmental pollutants are associated with MBD. We investigated associations of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonate (PFHxS) levels with measures of MBD and evaluated if early life factors modified any associations. Metabolon performed metabolomics analysis using ultrahigh-performance liquid chromatography/tandem accurate mass spectrometry in fasting blood from 705 premenopausal women completing their annual screening mammogram in St. Louis, Missouri. We calculated least square means (LSM) of mammographic volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV) by quartiles (Q) of PFOS, PFOA, and PFHxS from multivariable linear regression modeling overall and stratified by recruitment period, race, age at menarche, and body shape at age 10. Models were adjusted for age, age at menarche, body fat percentage, race, family history of breast cancer, oral contraceptive use, alcohol consumption, parity/age at first birth, and body shape at age 10. PFOS, PFOA, and PFHxS were not significantly associated with VPD or NDV. PFHxS was significantly positively associated with DV (, , , ; ). PFOS was positively associated with DV (, , , ; ) with DV being 8.1%, 12%, and 12.3% higher in Q2, Q3, and Q4 compared to Q1. Among women who were underweight/normal weight at age 10, PFOS was positively associated with VPD (, , , ; ) while there was an inverse association among women who were overweight/obese at age 10 (, , , ; ) (). We report novel associations of PFHxS and PFOS with DV in premenopausal women. PFOS, PFOA, and PFHxS were not associated with VPD and NDV. In addition, body shape at age 10 may modify the associations of PFOS with MBD. Further studies are needed to validate our findings and to evaluate the associations of other per- and polyfluoroalkyl substances (PFAS), as well as mixtures of PFAS, with MBD. https://doi.org/10.1289/EHP14065.

Studies have investigated the associations of coffee and tea with mammographic breast density (MBD) in premenopausal women with inconsistent results. We analyzed data from 375 premenopausal women who attended a screening mammogram at Washington University School of Medicine, St. Louis, MO in 2016, and stratified the analyses by race (non-Hispanic White (NHW) vs. Black/African American). Participants self-reported the number of servings of coffee, caffeinated tea, and decaffeinated tea they consumed. Volpara software was used to determine volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV). We used generalized linear regression models to quantify the associations of coffee and tea intake with MBD measures. Coffee: ≥1 time/day (β = 1.06; 95% CI = 0.93–1.21; p-trend = 0.61) and caffeinated tea: ≥1 time/day (β = 1.01; 95% CI = 0.88–1.17; p-trend = 0.61) were not associated with VPD. Decaffeinated tea (≥1 time/week) was positively associated with VPD in NHW women (β = 1.22; 95% CI = 1.06–1.39) but not in African American women (β = 0.93; 95% CI = 0.73–1.17; p-interaction = 0.02). Coffee (≥1 time/day) was positively associated with DV in African American women (β = 1.52; 95% CI = 1.11–2.07) but not in NHW women (β = 1.10; 95% CI = 0.95–1.29; p-interaction = 0.02). Our findings do not support associations of coffee and caffeinated tea intake with VPD in premenopausal women. Positive associations of decaffeinated tea with VPD, with suggestions of effect modification by race, require confirmation in larger studies with diverse study populations.

BackgroundMammographic breast density (MBD), a strong predictor of breast cancer, is highly influenced by body mass index (BMI) in childhood and early adulthood, but the mechanisms underlying these associations are not fully understood. Our goal is to identify biomarkers that mediate the associations of BMI at ages 10 and 18 with MBD in premenopausal women.MethodsThis study consists of 705 premenopausal women who had their screening mammogram at Washington University in St. Louis, MO, and provided a fasting blood sample. Our comprehensive metabolomic and lipidomic profiling yielded complete data for 828 metabolites and 857 lipid species after imputation. We used Volpara to determine volumetric measures of MBD. We performed high dimensional mediation analysis using the HIMA R package, adjusted for confounders, to determine whether lipid species and metabolites mediate the associations of BMI at 10 and 18 with MBD. We applied a false discovery rate (FDR) p-value < 0.1.ResultsFour metabolites (glutamate, β-cryptoxanthin, cortolone glucuronide (1), phytanate) significantly mediated the association of BMI at 10 with volumetric percent density (VPD), and two (glutamate, β-cryptoxanthin) mediated the association of BMI at 18 with VPD. Glutamate was the strongest mediator across time points. Glutamate mediated 6.7% (FDR p-value = 0.06) and 9.3% (FDR p-value = 0.008) of the association between BMI at age 10 and 18, respectively. Four lipid species (CER(18:0), LCER(14:0), LPC(18:1), PC(18:1/18:1)), mediated the association of BMI at 10 with VPD, while five lipid species (CER(18:0), LCER(14:0), PC(18:1/18:1), TAG56:5-FA22:5, TAG52:2-FA16:0) mediated the association of BMI at 18 with VPD. The strongest mediator was PC(18:1/18:1), which mediated 9.7%, (FDR-p = 0.009) and 7.7%, (FDR-p = 0.04) of the association of BMI at age 10 and 18 with VPD, respectively.ConclusionsMetabolites in amino acid, lipid, cofactor/vitamin, and xenobiotic super-pathways as well as lipid species across the phospholipid, neutral complex lipid and sphingolipid super-pathways mediated the associations of BMI in early-life and MBD in premenopausal women. This study offers insight into the biological mechanisms underlying the link between early-life adiposity and MBD, which can support future research into breast cancer prevention.

Introduction: Mammographic density and family history of breast cancer (FHBC) are independent risk factors for breast cancer. Women with dense breasts have a 4-6-fold increased risk of breast cancer and women with FHBC have a 1.5-3-fold increased risk of breast cancer. However, there is little data on the associations of FHBC with mammographic density, especially in premenopausal women. To address this, we investigated the associations of FHBC in first-degree relatives with mammographic density in premenopausal women. Methods: We used data from 375 cancer-free premenopausal women who were during routine screening mammography at Washington University in St. Louis in 2016. We used Volpara to measure volumetric measures of density including volumetric percent density, dense volume, and non-dense volume. We collected data on first-degree relatives (mother, sister) and numbers of first degree relatives (0, 1, ≥2) with a positive FHBC. We used multivariable linear regression model, adjusted for age, BMI, parity, race, age at menarche, and alcohol consumption, to determine the associations of FHBC and log-transformed volumetric percent density, dense volume, and non-dense volume. Beta coefficients (β) were evaluated and back transformed for easier interpretation. Results: The mean age of participants was 47.5 years (range=32-58). The mean BMI was 30.8 kg/m2 (range =17.9-63.1). Volumetric percent density was 25% (p-value&amp;lt;0.001) higher in women who had a FHBC compared with women who had no FHBC. The associations appeared confined to women with a positive family history in mothers but not those with a positive family history in sisters. Volumetric percent density was 31% higher (p-value&amp;lt;0.001) among women with a positive FHBC in mothers compared to those without a positive FHBC in mothers, but 8% higher (p-value=0.45) among women with a positive FHBC in sisters compared to those without a positive FHBC in sisters. The associations of FHBC with dense volume were similar to those of volumetric percent density in all the analyses. For instance, dense volume was 16% (p-value=0.006) higher in women who had a FHBC compared with women who had no FHBC. Table 1.Associations of family history of breast cancer (FHBC) and volumetric percent density (VPD), and dense volume (DV) in 375 premenopausal women*.FHBCNVPD (%) DV (cm3 ) Beta (95% CI)P-valueBeta (95% CI)P-valueNo275Ref Ref Yes871.25 (1.12,1.41)&amp;lt;0.0011.16 (1.04,1.29)0.007Unknown131.00 (0.76,1.30)0.990.74 (0.58,0.95)0.017*Adjusted for age, BMI, parity, race, age at menarche, and alcohol consumption. Conclusions: Premenopausal women with a first-degree FHBC have higher volumetric percent density. Our findings could help identify high-risk women who may benefit from targeted screening. Citation Format: Han Y, Zong X, Colditz GA, Toriola AT. Family history of breast cancer and mammographic density in premenopausal women [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-10-08.

Family history of breast cancer (FHBC) and mammographic breast density are independent risk factors for breast cancer, but the association of FHBC and mammographic breast density in premenopausal women is not well understood. To investigate the association of FHBC and mammographic breast density in premenopausal women using both quantitative and qualitative measurements. This single-center cohort study examined 2 retrospective cohorts: a discovery set of 375 premenopausal women and a validation set of 14 040 premenopausal women. Data from women in the discovery set was collected between December 2015 and October 2016, whereas data from women in the validation set was collected between June 2010 and December 2015. Data analysis was performed between June 2018 and June 2020. Family history of breast cancer (FHBC). The primary outcomes were mammographic breast density measured quantitatively as volumetric percent density using Volpara (discovery set) and qualitatively using BI-RADS (Breast Imaging Reporting and Data System) breast density (validation set). Multivariable regressions were performed using a log-transformed normal distribution for the discovery set and a logistic distribution for the validation set. Of 14 415 premenopausal women included in the study, the discovery set and validation set had similar characteristics (discovery set with FHBC: mean [SD] age, 47.1 [5.6] years; 15 [17.2%] were Black or African American women and 64 [73.6%] were non-Hispanic White women; discovery set with no FHBC: mean [SD] age, 47.7 [4.5] years; 87 [31.6%] were Black or African American women and 178 [64.7%] were non-Hispanic White women; validation set with FHBC: mean [SD] age, 46.8 [7.3] years; 720 [33.4%] were Black or African American women and 1378 [64.0%] were non-Hispanic White women]; validation set with no FHBC: mean [SD] age, 47.5 [6.1] years; 4572 [38.5%] were Black or African American women and 6632 [55.8%] were non-Hispanic White women]). In the discovery set, participants who had FHBC were more likely to have a higher mean volumetric percent density compared with participants with no FHBC (11.1% vs 9.0%). In the multivariable-adjusted model, volumetric percent density was 25% higher (odds ratio [OR], 1.25 ;95% CI, 1.12-1.41) in women with FHBC compared with women without FHBC; and 24% higher (OR, 1.24; 95% CI, 1.10-1.40) in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives (OR, 1.40; 95% CI, 0.95-2.07) compared with women with no relatives affected. In the validation set, women with a positive FHBC were more likely to have dense breasts (BI-RADS 3-4) compared with women with no FHBC (BI-RADS 3: 41.1% vs 38.8%; BI-RADS 4: 10.5% vs 7.7%). In the multivariable-adjusted model, the odds of having dense breasts (BI-RADS 3-4) were 30% higher (OR, 1.30; 95% CI, 1.17-1.45) in women with FHBC compared with women without FHBC; and 29% higher (OR, 1.29; 95% CI, 1.14-1.45) in women who had 1 affected relative, but not significantly higher in women who had at least 2 affected relatives (OR, 1.38; 95% CI, 0.85-2.23) compared with women with no relatives affected. In this cohort study, having an FHBC was positively associated with mammographic breast density in premenopausal women. Our findings highlight the heritable component of mammographic breast density and underscore the need to begin annual screening early in premenopausal women with a family history of breast cancer.

Associations of Vitamins and Related Cofactor Metabolites with Mammographic Breast Density in Premenopausal Women

Progesterone is a proliferative hormone in the breast but the associations of genetic variations in progesterone-regulated pathways with mammographic breast density (MD) in premenopausal women and whether these associations are mediated through circulating progesterone are not clearly defined. We, therefore, investigated these associations in 364 premenopausal women with a median age of 44 years. We sequenced 179 progesterone receptor (PGR)-related single nucleotide polymorphisms (SNPs). We measured volumetric percent density (VPD) and non-dense volume (NDV) using Volpara. Linear regression models were fit on circulating progesterone or VPD/NDV separately. We performed mediation analysis to evaluate whether the effect of a SNP on VPD/NDV is mediated through circulating progesterone. All analyses were adjusted for confounders, phase of menstrual cycle and the Benjamini–Hochberg false discovery (FDR) adjusted p-value was applied to correct for multiple testing. In multivariable analyses, only PGR rs657516 had a direct effect on VPD (averaged direct effect estimate = − 0.20, 95%CI = − 0.38 ~ − 0.04, p-value = 0.02) but this was not statistically significant after FDR correction and the effect was not mediated by circulating progesterone (mediation effect averaged across the two genotypes = 0.01, 95%CI = − 0.02 ~ 0.03, p-value = 0.70). Five SNPs (PGR rs11571241, rs11571239, rs1824128, rs11571150, PGRMC1 rs41294894) were associated with circulating progesterone but these were not statistically significant after FDR correction. SNPs in PGR-related genes were not associated with VPD, NDV and circulating progesterone did not mediate the associations, suggesting that the effects, if any, of these SNPs on MD are independent of circulating progesterone.

BackgroundHigh mammographic breast density (MBD) is a strong risk factor for breast cancer development, but the biological mechanisms underlying MBD are unclear. Lipids play important roles in cell differentiation, and perturbations in lipid metabolism are implicated in cancer development. Nevertheless, no study has applied untargeted lipidomics to profile the lipidome of MBD. Through this study, our goal is to characterize the lipidome of MBD in premenopausal women.MethodsPremenopausal women were recruited during their annual screening mammogram at the Washington University School of Medicine in St. Louis, MO. Untargeted lipidomic profiling for 982 lipid species was performed at Metabolon (Durham, NC®), and volumetric measures of MBD (volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)) was assessed using Volpara 1.5 (Volpara Health®). We performed multivariable linear regression models to investigate the associations of lipid species with MBD and calculated the covariate-adjusted least square mean of MBD by quartiles of lipid species. MBD measures were log10 transformed, and lipid species were standardized. Linear coefficients of MBD were back-transformed and considered significant if the Bonferroni corrected p-value was < 0.05.ResultsOf the 705 premenopausal women, 72% were non-Hispanic white, and 23% were non-Hispanic black. Mean age, and BMI were 46 years and 30 kg/m2, respectively. Fifty-six lipid species were significantly associated with VPD (52 inversely and 4 positively). The lipid species with positive associations were phosphatidylcholine (PC)(18:1/18:1), lysophosphatidylcholine (LPC)(18:1), lactosylceramide (LCER)(14:0), and phosphatidylinositol (PI)(18:1/18:1). VPD increased across quartiles of PI(18:1/18:1): (Q1 = 7.5%, Q2 = 7.7%, Q3 = 8.4%, Q4 = 9.4%, Bonferroni p-trend = 0.02). The lipid species that were inversely associated with VPD were mostly from the triacylglycerol (N = 43) and diacylglycerol (N = 7) sub-pathways. Lipid species explained some of the variation in VPD. The inclusion of lipid species increased the adjusted R2 from 0.45, for a model that includes known determinants of VPD, to 0.59.ConclusionsWe report novel lipid species that are associated with MBD in premenopausal women. Studies are needed to validate our results and the translational potential.

Studies investigating the associations of self-reported aspirin use and mammographic breast density (MBD) have reported conflicting results. Therefore, we investigated the associations of aspirin metabolites with MBD in premenopausal women. We performed this study on 705 premenopausal women who had a fasting blood draw for metabolomic profiling. We performed covariate-adjusted linear regression models to calculate the least square means of volumetric measures of MBD [volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV)] by quartiles of aspirin metabolites [salicyluric glucuronide, 2-hydroxyhippurate (salicylurate), salicylate, and 2,6-dihydroxybenzoic acid]. Approximately 13% of participants reported taking aspirin in the past 12 months. Aspirin users had higher levels of 2-hydroxyhippurate (salicylurate), salicylate, and salicyluric glucuronide (peak area) than nonusers, but only the mean peak area of salicyluric glucuronide was increased by both dose (1-2 tablets per day = 1,140,663.7 and ≥3 tablets per day = 1,380,476.0) and frequency (days per week: 1 day = 888,129.3, 2-3 days = 1,199,897.9, and ≥4 days = 1,654,637.0). Aspirin metabolites were not monotonically associated with VPD, DV, or NDV. Given the null results, additional research investigating the associations of aspirin metabolites in breast tissue and MBD is necessary. Impact: Elucidating the determinants of MBD, a strong risk factor for breast cancer, can play an important role in breast cancer prevention. Future studies should determine the associations of nonaspirin NSAID metabolites with MBD.

Introduction: Mammographic breast density (MBD), a strong predictor of breast cancer risk, is highly influenced by body mass index (BMI) in childhood and early adulthood, but the mechanisms elucidating this relationship are undetermined. To our knowledge, no study has explored the mediating role of biomarkers on the relationship between early-life adiposity and MBD. The goal of this study is to discover metabolites that mediate the relationship between BMI at ages 10 and 18 with MBD in premenopausal women. Methods: This study includes premenopausal women who had their screening mammogram at Washington University in St. Louis, MO, and provided a fasting blood sample. Metabolon performed untargeted metabolomic profiling, detecting 1,074 metabolites. Metabolites missing &amp;gt;300 observations were excluded, leaving 828 metabolites; the other missing values were imputed using the nearest neighbor method. To mitigate batch effect, we normalized the metabolite peak area data using ComBat. Volumetric percent density (VPD) was calculated in 700 women using Volpara software. BMI at age 10 was estimated using the Stunkard pictogram, and BMI at age 18 was calculated from self-reported weight at 18 and height at study initiation. To assess the mediating role of the 828 metabolites, we performed high dimensional mediation analysis using the hima R package adjusting for potential confounders. Missing values in the covariates and BMI measures included in the mediation analysis were imputed using multivariate imputation by chain equations. Associations were considered significant if FDR p-value &amp;lt;0.1. Results: Four metabolites (glutamate, beta-cryptoxanthin, phytanate, and cortolone glucuronide (1)) mediated the relationship between BMI at age 10 and VPD; and 2 metabolites (glutamate, beta-cryptoxanthin) mediated the relationship between BMI at age 18 and VPD. Glutamate and beta-cryptoxanthin significantly mediated the relationship between both BMI measures and VPD, but glutamate was the strongest mediator across both time points. Glutamate mediated 6.7% (FDR p-value=0.06) and 9.3% (FDR p-value=0.008) of the total effect between BMI at age 10 and 18, respectively, on VPD. Beta-cryptoxanthin mediated 4.1% (FDR p-value=0.06) and 6.3% (FDR p-value=0.04), of the total effect between BMI at age 10 and 18, respectively, on VPD. Additionally, phytanate mediated 2.6% (FDR p-value=0.06) and cortolone glucuronide (1) mediated 2.0% (FDR p-value=0.07) of the total effect between BMI at age 10 and VPD. Conclusion: Amino acid, lipid, cofactor/vitamin, and xenobiotic metabolites mediated the associations of BMI in early-life and VPD in premenopausal women. This innovative study offers insight into the biological mechanisms underlying the link between early-life adiposity and MBD, which can support future research into breast cancer prevention. Citation Format: Kayla R. Getz, Myung Sik Jeon, Lili Liu, Lei Liu, Chongliang Luo, Jingqin Luo, Adetunji T. Toriola. Using metabolomics to identify biomarkers mediating the associations of adiposity in childhood and early adulthood with mammographic breast density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3429.

Multivitamin Use and Mammographic Breast Density.

Although childhood adiposity is inversely associated with breast cancer risk, the association of childhood adiposity with mammographic density in premenopausal women has not been adequately studied. We analyzed data from 365 premenopausal women who came in for screening mammography at Washington University (St. Louis, MO) from 2015 to 2016. Body size at age 10 was self-reported using somatotype pictogram. Body mass index (BMI) at age 10 was imputed using data from Growing Up Today Study. Volpara software was used to evaluate volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV). Adjusted multivariable linear regression models were used to evaluate the associations between adiposity at age 10 and mammographic density measures. Adiposity at age 10 was inversely associated with VPD and positively associated with NDV. A 1 kg/m2 increase in BMI at age 10 was associated with a 6.4% decrease in VPD, and a 6.9% increase in NDV (P < 0.001). Compared with women whose age 10 body size was 1 or 2, women with body size 3 or 4 had a 16.8% decrease in VPD and a 26.6% increase in NDV, women with body size 5 had a 32.2% decrease in VPD and a 58.5% increase in NDV, and women with body sizes ≥6 had a 47.8% decrease in VPD and a 80.9% increase in NDV (P < 0.05). The associations were attenuated, but still significant after adjusting for current BMI. Mechanistic studies to understand how childhood adiposity influences breast development, mammographic density, and breast cancer in premenopausal women are needed. Cancer Prev Res; 11(5); 287-94. ©2018 AACR.