Early Life Body Fatness, Serum Anti-Müllerian Hormone, and Breast Density in Young Adult Women

Abstract

Background Emerging evidence suggests positive associations between serum antimüllerian hormone (AMH), a marker of ovarian function, and breast cancer risk. Body size at young ages may influence AMH levels, but few studies have examined this. Also, no studies have examined the relation of AMH levels with breast density, a strong predictor of breast cancer risk. Methods We examined associations of early life body fatness, AMH concentrations, and breast density among 172 women in the Dietary Intervention Study in Children (DISC). Height and weight were measured at baseline (ages 8–10) and throughout adolescence. Serum AMH concentrations and breast density were assessed at ages 25–29 at the DISC06 Follow-Up visit. We used linear mixed effects models to quantify associations of AMH (dependent variable) with quartiles of age-specific youth body mass index (BMI) Z-scores (independent variable). We assessed cross-sectional associations of breast density (dependent variable) with AMH concentration (independent variable). Results Neither early life BMI nor current adult BMI was associated with AMH concentrations. There were no associations between AMH and percent or absolute dense breast volume. In contrast, women with higher AMH concentrations had significantly lower absolute non-dense breast volume (p-trend <0.01). Conclusions We found no evidence that current or early life BMI influences AMH concentrations in later life. Women with higher concentrations of AMH had similar percent and absolute dense breast volume, but lower non-dense volume. Impact These results suggest that AMH may be associated with lower absolute non-dense breast volume; however, future prospective studies are needed to establish temporality.

Adult adiposity and risk of early menopause

“…Premenopausal obesity is associated with anovulatory infertility, increased androgen production and decreased serum sex hormone binding-globulin level (Pasquali and Gambineri, 2006). In addition, some studies have found lower levels of Anti-Müllerian Hormone (AMH) among obese women compared to normal weight women (Freeman et al, 2007;Steiner et al, 2010), though others report no association (Bertrand et al, 2016;Jung et al, 2017). AMH, produced by granulosa cells in the ovary, is a marker of ovarian reserve highly correlated with antral follicle count (AFC) in older premenopausal women (van Rooij, Ilse et al, 2005;La Marca and Volpe, 2006).…”

Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

“…Forty-one studies did not meet the selection inclusion criteria: no adequate breast density data (n = 20), qualitative analysis (n = 12), editorials (n = 4), conference abstracts (n = 3), post-mortem study (n = 1), and phantom study (n = 1). Finally, 38 studies attained the inclusion criteria [1,2,3,5,11,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57] and were included in the analysis as shown in Table 1.…”

“…Several MRI sequences were used to enable the precise differentiation between adipose and fibroglandular tissues; of these, non-contrast-enhanced T1-weighted was widely used either with 2D spin echo or 3D gradient echo. In fact, 16 studies (41.03%) used non-contrast-enhanced T1-weighted [1,2,26,27,28,29,31,33,35,44,45,48,49,50,51,53], while in 12 studies (30.77%) non-contrast-enhanced images were integrated with contrast-enhanced images [25,36,37,38,39,40,41,42,43,44,47,49]. In terms of breast density segmentation/measurement, the majority of the studies (20 studies; 51.28%) used FCM clustering algorithm [1,2,11,25,26,27,28,29,31,32,33,34,35,36,37,38,39,40,41,42], while 7 studies (17.95%) used FCM and N3 algorithm [45,46,47,48,49,50,51], 4 studies (10.26%) interactive thresholding algorithm [3,5,52,53], 4 studies (10.26%) in-house customized software [29,53,54,55], one study (2.56%) manual software […”

“…Among the thirty-eight studies included in the systematic review and meta-analysis, 21 studies qualified for meta-analysis since they reported the percent breast density using an identical expression of measurement and dispersion [1,3,11,25,26,27,28,29,30,31,32,36,37,38,45,48,49,50,53,54,55] (Table 2). However, for the remaining 17 studies, the percent breast density was reported in different format: in eight of these studies, it was defined as a median and interquartile range (IQR) [2,39,40,41,42,43,44,47], and in the other nine, it was reported either in different measurement unit or the subject’s sets were not independent, due to multiple usage [5,33,34,35,46,51,52,56,57].…”

“…The FCM subgroup consisted of 13 studies, of which, 10 studies reported breast density as a percentage breast density (% BD) [1,11,25,26,27,28,29,30,31,32], whereas 3 studies as a percentage of the dense breast volume (% DBV) [36,37,38]. On one hand, 10 studies with inclusion of 634 patients were included, as Figure 3A shows, there is a wide range of mean values as well as standard deviation (SDs) from those studies, which indicated enormous heterogeneity among study means (Cochran’s Q test: X 2 = 86.93, P < 0.0001).…”