Maturitas 53 (2006) 315–324
Postmenopausal bone mineral density in relation to soy isoflavone-metabolizing phenotypes Cara L. Frankenfeld a,b , Anne McTiernan a,b,c , Wendy K. Thomas a , Kristin LaCroix a , Lynda McVarish a , Victoria L. Holt b,e , Stephen M. Schwartz b,e , Johanna W. Lampe a,b,d,∗ a
e
Cancer Prevention Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., M4-B402, PO Box 19024, Seattle, WA 98109-1024, USA b Department of Epidemiology, University of Washington, Seattle, WA, USA c Department of Medicine, University of Washington, Seattle, WA, USA d Interdisciplinary Program in Nutritional Sciences, University of Washington, Seattle, WA, USA Epidemiology Program, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., M4-B874, Box 19024, Seattle, WA 98109, USA Received 9 February 2005; received in revised form 9 May 2005; accepted 25 May 2005
Abstract Objectives: Intestinal bacterial metabolize the soy isoflavone daidzein to O-desmethylangolensin (O-DMA) or equol. Some individuals do not excrete O-DMA or equol after soy consumption, suggesting they do not harbor bacteria capable of producing these metabolites. The aim of this study was to evaluate bone mineral density (BMD) in relation to presence of these urinary metabolites. Methods: BMD, determined by whole-body dual X-ray absorptiometry scan, was age-adjusted and evaluated in relation to O-DMA-producer and equol-producer phenotypes in 92 postmenopausal women, aged 50–75 years. Women consumed supplemental soy foods (daidzein source) for 3 days and collected a first-void urine sample on the fourth day in order to determine metabolic phenotypes. Results: In O-DMA producers (n = 76) compared to O-DMA non-producers (n = 16), greater total, leg and head BMD (p < 0.05) were observed. Total BMD among the O-DMA producers (geometric mean = 1.04 g/cm2 ) was 6% greater than total BMD among the O-DMA non-producers (geometric mean = 0.98 g/cm2 ). Total and site-specific BMD did not differ between equol producers (n = 24) and non-producers (n = 68) (p > 0.05). In exploratory analyses, among regular soy consumers, spinal BMD was 20% lower among the equol producers than non-producers, whereas, among soy non-consumers, no such difference was observed (pinteraction < 0.05). Among equol producers, circulating estrone and free estradiol concentrations were inversely or not associated with total BMD, whereas, among equol non-producers, these hormones were positively associated (p-interaction < 0.05).
∗
Corresponding author. Tel.: +1 206 667 6580; fax: +1 206 667 7850. E-mail address:
[email protected] (J.W. Lampe).
0378-5122/$ – see front matter © 2005 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.maturitas.2005.05.016
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Conclusions: Our results provide evidence that intestinal bacterial composition may influence BMD in postmenopausal women. Further studies characterizing associations of intestinal bacterial profiles with BMD are warranted. © 2005 Elsevier Ireland Ltd. All rights reserved. Keywords: Bone mineral density; Equol; O-Desmethylangolensin; Intestinal microflora; Daidzein; Soy; Hormones
1. Introduction There is evidence to suggest that intestinal bacterial composition may influence bone mineral density (BMD). Notably, intestinal bacteria metabolize steroid sex hormones, which are involved in the growth, differentiation and function of bone [1]. Evidence from in vitro work suggests that intestinal bacteria isolated from humans metabolize sex hormones in a strainspecific manner [2]; some strains of intestinal bacteria are capable of performing specific metabolic reactions, such as hydroxylation and oxidation, while other strains are not. These observations provide evidence that differences in intestinal bacterial populations may result in different sex hormones and metabolites available for reabsorption, which could influence concentrations of some circulating sex hormones, and thus, influence BMD. There is marked interindividual variability in intestinal bacterial composition among humans. Daidzein, one of the principal isoflavones found in soybeans [3], is metabolized to O-desmethylangolensin (O-DMA) or equol by particular intestinal bacteria [4–6]. Two soy isoflavone-metabolizing phenotypes, the O-DMA-producer and equol-producer phenotypes, are biomarkers of variability of bacteria in the intestine. Although the intestinal bacteria that can metabolize daidzein to O-DMA or to equol have not yet been identified definitively, the presence or absence of these metabolites in urine can serve as markers of particular intestinal bacterial profiles. Studies have shown that the population prevalence of O-DMA producers is approximately 80–90% [7,8] and of equol producers is approximately 30–50% [7–11], and there appears to be little correlation between being an O-DMA producer and being an equol producer [12]. These soy isoflavone-metabolizing phenotypes appear to remain stable within an individual over time [13], suggesting that physiologic effects of these phenotypes could have long-term impact to the human host.
Soy isoflavone-metabolizing phenotypes, irrespective of habitual soy intake, have been associated with hormones and hormone-related outcomes in women. Among premenopausal women, Duncan et al. [14] observed differences in circulating sex hormone concentrations between equol-producing and non-producing women. Based on these observations, we hypothesized that equol producers would have lower BMD than equol non-producers. Because of the relationship between intestinal bacteria and sex hormones, we hypothesized that BMD would also be associated with the O-DMA-producer phenotype, but we did not hypothesize a direction for this association. The objective of this study was to evaluate BMD in relation to soy isoflavone-metabolizing phenotypes in postmenopausal women. 2. Materials and methods 2.1. Subjects and experimental design Participants were recruited from women who participated in the Physical Activity for Total Health Study [15], which was a randomized trial designed to examine the effect of moderate intensity exercise on the reproductive hormone profile in overweight (BMI ≥ 25 or BMI between 24 and 25 if body fat >33%), sedentary (<60 min/week moderate or strenuous exercise), postmenopausal (having no menstrual periods in prior year or FSH >30 mIU/ml for women who had hysterectomy) women, aged 50–75 years. Prior to exercise intervention, demographic and reproductive history data were collected via questionnaire, urine and blood samples were collected, and BMD analysis was performed. More details regarding study procedures and inclusion and exclusion criteria are published elsewhere [15]. From the parent study, 152 women who had indicated willingness to be re-contacted were considered for participation in the current study. Approximately 2–3 years after the completion of the parent study, women were contacted regarding participation in soy
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isoflavone-metabolizing phenotyping. Exclusion criteria for participation in the soy isoflavone-metabolizing phenotyping were known allergy to soy and chronic antibiotic therapy. All women had not used antibiotics in the 3 months prior to phenotyping. Ninety-two women participated in the soy isoflavone-metabolizing phenotyping. 2.2. Study procedures Women were mailed three soy bars and a urine collection kit. For 3 consecutive days, each woman supplemented her usual diet with either one soy bar per day (Revival Soy, Physicians Laboratories, WinstonSalem, NC, ∼83 mg daidzein per day) or one-third of a package of soy nuts per day (GeniSoy, Fairfield, CA, ∼10 mg daidzein per day). Because phenotype determination is based on the presence or absence of O-DMA and equol, the difference in daidzein dose between these two foods does not bias phenotype determination. On the morning of the fourth day, each woman collected a sample of first-void urine (50–80 ml), and mailed the sample to the Fred Hutchinson Cancer Research Center (FHCRC). Urinary ODMA and equol concentrations are stable at room temperature for at least 14 days and the average time for receipt of urine samples in the U.S. is 4 days [16], and no urine samples were received after 14 days in this study. The Institutional Review Board at the FHCRC approved all procedures and informed, written consent was obtained from all participants. 2.3. Bone mineral density Prior to randomization in the parent study, BMD was measured in all women by dual X-ray absorptiometry (DXA) scans performed at the University of Washington, using a Hologic QDR-1500 with body composition software v 7.10D (Hologic Inc., Bedford, MA). Head, right and left legs, right and left arms, trunk, and axial skeleton measurements were taken. 2.4. Serum hormones and urinary estrogen metabolites
317
and stored at −70 ◦ C. Prior to analysis, a serum quality control (QC) pool was created from ineligible subjects (postmenopausal and not taking hormone replacement therapy but ineligible for other reasons). Analysis of circulating hormone concentrations is described elsewhere [17]. A spot urine sample was collected at the same visit as the blood draw in the parent study, and was processed within 1 h of collection. Urinary 2-OH E1 and 16␣-OH E1 were measured using the commercially available EstrametTM 2/16 enzyme immunoassay (EIA) kits (Immunacare Corporation, Bethlehem, PA), as described previously [18]. All kits were from the same lot number, and upon receipt, all components were stored prior to use as recommended by the manufacturer. 2.5. Equol-producer and O-DMA-producer phenotypes Urine samples, frozen and stored at −70 ◦ C until analysis, were ether-extracted, using a variation of the ether extraction method of Heinonen et al. [19], and analyzed for isoflavonoids (O-DMA, equol, daidzein and genistein) by gas chromatography–mass spectrometry as previously described [17]. Urine samples were analyzed in batches of twenty, with two quality control urine samples included in each batch. The mean intra-assay coefficients of variation (CV) for equol and O-DMA in the quality control urine samples, measured in duplicate in each batch, were <7%. Given the sensitivity of the assay, urine concentrations of O-DMA less than 170 nmol/l (44 ng/ml) and of equol less than 182 nmol/l (44 ng/ml) were considered below detectable limit. Women with detectable O-DMA concentrations were classified as O-DMA producers and women with detectable equol concentrations were classified as equol producers. All women had detectable concentrations (>44 ng/ml in urine) of predominant isoflavones found in soy: genistein values were greater than 100 ng/ml and daidzein values were greater than 90 ng/ml, indicating complete compliance with soy consumption. 2.6. Statistical analysis
At the baseline data collection of the parent study, subjects provided a 50-ml sample of blood, after fasting for at least 12 h. Blood was processed into serum within 1 h of collection. Serum was aliquoted into 1.8-ml tubes
Linear regression was used to model differences in BMD in relation to soy isoflavone-metabolizing phenotypes. To evaluate the independence of the
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two soy isoflavone-metabolizing phenotypes from each other and from other characteristics predictive of BMD, three multivariate models were fit: each phenotype, adjusted for (1) age, (2) age and the other soy isoflavone-metabolizing phenotype, and (3) age, anthropometry, history of oral contraceptive use, urinary 2-OH E1 :16␣-OH E1 , and circulating free testosterone and dehydroepiandrosteronesulfate (DHEAS) concentrations. With the exception of the other soy isoflavone-metabolizing phenotype and 2-OH E1 :16␣-OH E1 , other adjustment variables were chosen using a best-fit model procedure. Because effect modification of chronic isoflavone exposure and the equol-producer phenotype on BMD has been proposed by others [20], we explored effect modification of soy intake (greater than one serving per week or one serving or less per week) and equol-producer phenotype on total, spine, and head BMD using an interaction term in linear regression models. Spine and head were chosen because of their metabolic responsiveness (see discussion section for more details). In order to evaluate whether the association of circulating hormones with BMD differs by soy isoflavone-metabolizing phenotypes, we evaluated interactions between each soy isoflavone-metabolizing phenotype and circulating hormone concentrations and urinary 2-OH E1 :16␣OH E1 for total BMD. Data collection for adjustment variables and urinary and circulating hormones is described elsewhere [15,17]. Analyses were performed using Stata 8.0 (Stata Corporation, College Station, TX).
3. Results The prevalence of O-DMA producers in this group was 83% (n = 76). The prevalence of equol producers in this group was 26% (n = 24). No significant association between the two phenotypes was observed; 91% of equol producers and 80% of equol non-producers were O-DMA producers (χ2 = 1.6, p = 0.2). Mean anthropometric characteristics were similar between producers and non-producers of both O-DMA-producer and equol-producer phenotypes (Table 1). No differences were observed in height, weight, body mass index (BMI), or weight history between producers and non-producers within either soy isoflavone-metabolizing phenotype. Most reproductive, dietary and lifestyle characteristics were also similar between producers and non-producers within each soy isoflavone-metabolizing phenotype (Table 2). Approximately twice as many O-DMA and equol producers were former smokers compared to nonproducers within each phenotype (p < 0.05). With the exception of head BMD, specific BMD sites were well correlated with total BMD (r ≥ 0.77) and with each other (r ≥ 0.59). Head BMD was not strongly correlated with total and specific BMD sites (r ≤ 0.47). Age-adjusted total BMD was 6% greater (p = 0.02) in O-DMA producers compared to O-DMA nonproducers (Table 3). O-DMA producers, relative to O-DMA non-producers, had greater leg, spine, rib and head BMD, and no differences in arm or pelvic BMD. Further adjusting for (1) equol-producer phenotype, and (2) current BMI, weight at age 50, weight at age
Table 1 Anthropometric characteristics in 92 postmenopausal women in relation to O-DMA-producer and equol-producer phenotypes Characteristics
Current BMI (kg/m2 ) Current weight (kg) Current height (cm) Weight at age 50 (kg) Weight at age 18 (kg) Maximum adult weight (kg) Minimum adult weight (kg)
O-DMA-producer phenotype
Equol-producer phenotype
Producers (n = 76), mean (S.D.)
Non-producers (n = 16), mean (S.D.)
Producers (n = 24), mean (S.D.)
Non-producers (n = 68), mean (S.D.)
31 (4) 81 (14) 163 (7) 70 (13) 56 (9) 82 (15) 54 (8)
30 (4) 80 (15) 160 (5) 71 (11) 55 (6) 82 (16) 54 (8)
30 (4) 81 (11) 164 (5) 69 (11) 56 (5) 82 (12) 54 (5)
30 (4) 80 (14) 162 (7) 71 (13) 56 (10) 82 (16) 54 (9)
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Table 2 Reproductive, dietary and lifestyle characteristics in 92 postmenopausal women in relation to O-DMA-producer and equol-producer phenotypes Characteristics
Age at first menstrual period (years) 9–11 12–13 14–21 Regular menstrual periods during most of life (vs. no or sometimes) Nulligravid Ever breastfed more than 1 month Menopause occurred naturally (vs. surgical or other) Previous hysterectomy Previous ovariectomy Ever used oral contraceptives Ever used estrogen (non-contraceptive) Ever used herbal estrogen Former smoker Calcium supplement (10–25 years of age) Current calcium intake (tertiles, mg/day) 164–576 604–909 913–1960
O-DMA-producer phenotype
Equol –producer phenotype
Producers (n = 76), n (%)
Non-producers (n = 16), n (%)
Producers (n = 24), n (%)
Non-producers (n = 68), n (%)
13 (17) 46 (61) 17 (22)
2 (13) 11 (69) 3 (19)
3 (13) 15 (62) 6 (25)
12 (18) 42 (62) 14 (21)
63 (83)
13 (81)
21 (88)
55 (81)
10 (13) 45 (59) 60 (79) 16 (21) 6 (8) 48 (63) 34 (44) 6 (8) 43 (57) 9 (12)
2 (13) 10 (63) 14 (88) 1 (6) 2 (13) 9 (56) 8 (50) 0 (0) 4 (25) 0 (0)
5 (21) 14 (58) 20 (83) 3 (13) 3 (13) 17 (71) 14 (58) 2 (8) 17 (71) 2 (8)
7 (10) 41 (60) 54 (79) 14 (21) 5 (7) 40 (59) 28 (41) 4 (6) 30 (44) 4 (11)
23 (30) 25 (33) 28 (37)
8 (50) 5 (31) 3 (19)
5 (21) 9 (38) 10 (42)
26 (38) 21 (31) 21 (31)
7 (9) 1 (1)
3 (21) 0 (0)
1 (4) 0 (0)
9 (14) 1 (2)
Lactose intolerant or avoid dairy Vegetarian diet (10–25 years of age)
18, and oral contraceptive use (ever/never), circulating free testosterone and DHEAS, and urinary 2-OH E1 :16␣-OH E1 did not appreciably alter the association between BMD and O-DMA-producer phenotype.
Age-adjusted total and site-specific BMD did not differ by equol-producer phenotype (Table 4). Further adjusting for (1) O-DMA-producer phenotype, and (2) current BMI, weight at age 50, weight at age 18,
Table 3 Adjusted means (standard errors) for total and site-specific BMD (g/cm2 ) in O-DMA-producing (n = 76) and O-DMA non-producing (n = 16) postmenopausal womena Total
Spine
Rib
Arm
Leg
Pelvis
Head
1.04a (0.01) 0.98 (0.02)
0.94b (0.02) 0.88 (0.03)
0.58b (0.01) 0.55 (0.01)
0.70 (0.01) 0.69 (0.01)
1.13a (0.01) 1.07 (0.03)
1.15 (0.01) 1.11 (0.03)
2.09b (0.05) 1.87 (0.10)
Adjusted for age and equol-producer phenotype 0.94b (0.02) O-DMA producers 1.04a (0.01) O-DMA non-producers 0.98 (0.02) 0.87 (0.03)
0.58b (0.01) 0.55 (0.01)
0.70 (0.01) 0.69 (0.01)
1.13a (0.01) 1.07 (0.03)
1.15 (0.01) 1.11 (0.03)
2.09b (0.05) 1.86 (0.11)
Adjusted for age, anthropometry, oral contraceptive use, urinary 2-OH E1 :16␣-OH E1 , and circulating DHEAS and free Tc O-DMA producers 1.04a (0.01) 0.93 (0.02) 0.57 (0.01) 0.70 (0.01) 1.13a (0.01) 1.15 (0.01) O-DMA non-producers 0.99 (0.02) 0.87 (0.03) 0.55 (0.01) 0.69 (0.01) 1.07 (0.03) 1.10 (0.03)
2.08b (0.05) 1.87 (0.10)
Adjusted for age O-DMA producers O-DMA non-producers
a b c
p ≤ 0.05, difference between producers and non-producers. p ≤ 0.10, difference between producers and non-producers. 2-OH E1 :16␣-OH E1 :2-hydroxyestrone:16␣-hydroxyestrone, DHEAS: dehydroepiandrosterone-sulfate, T: testosterone.
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Table 4 Adjusted means (standard errors) for total and site-specific BMD (g/cm2 ) in equol-producing (n = 24) and equol non-producing (n = 68) postmenopausal womena Total
Spine
Rib
Arm
Leg
Pelvis
Head
1.03 (0.02) 1.03 (0.01)
0.91 (0.03) 0.93 (0.02)
0.57 (0.01) 0.57 (0.01)
0.70 (0.01) 0.70 (0.01)
1.13 (0.02) 1.11 (0.01)
1.15 (0.03) 1.14 (0.02)
2.04 (0.09) 2.06 (0.05)
Adjusted for age and O-DMA-producer phenotype Equol producers 1.03 (0.02) 0.91 (0.03) Equol non-producers 1.03 (0.01) 0.93 (0.02)
0.56 (0.01) 0.58 (0.01)
0.70 (0.01) 0.70 (0.01)
1.13 (0.02) 1.11 (0.01)
1.15 (0.03) 1.14 (0.02)
2.01 (0.09) 2.07 (0.05)
Adjusted for age, anthropometry, oral contraceptive use, urinary 2-OH E1 :16␣-OH E1 , and circulating DHEAS and free Tb Equol producers 1.03 (0.02) 0.91 (0.03) 0.56 (0.01) 0.71 (0.01) 1.14 (0.02) 1.16 (0.03) Equol non-producers 1.03 (0.01) 0.93 (0.02) 0.57 (0.01) 0.70 (0.01) 1.11 (0.01) 1.14 (0.02)
2.05 (0.09) 2.05 (0.05)
Adjusted for age Equol producers Equol non-producers
a b
No statistically significant differences between producers and non-producers. 2-OH E1 :16␣-OH E1 :2-hydroxyestrone:16␣-hydroxyestrone, DHEAS: dehydroepiandrosterone-sulfate, T: testosterone.
and oral contraceptive use (ever/never), circulating free testosterone and DHEAS, and urinary 2-OH E1 :16␣OH E1 did not alter the association between BMD and equol-producer phenotype. Although serum estradiol (p = 0.09) and free estradiol (p = 0.05) were predictors of age-adjusted total BMD, free testosterone (p = 0.01) and DHEAS (p = 0.03) were slightly stronger predictors statistically; thus, because androgens, as well as estrogens, are biologically important for BMD, free testosterone and DHEAS were included in the model. Soy food intake was not prevalent in this population. Only nine women consumed more than one serving of tofu per week and one woman consumed more than one serving of soymilk per week. There was no significant association with soy intake and total, spinal or head BMD. There was a significant interaction between equol-producer phenotype and soy intake in relation to spinal BMD. Among women who consumed more than one serving per week of tofu or soymilk, age-adjusted spinal BMD was 20% lower in equol producers (n = 5, mean BMD = 0.82) than equol non-producers (n = 5, mean BMD = 1.02), whereas among soy non-consumers, spinal BMD was the same in equol producers (n = 19, mean BMD = 0.92) and equol non-producers (n = 62, mean BMD = 0.93) [pinteraction = 0.047). For total and head BMD, there was no difference in mean BMD in relation to equolproducer phenotype among soy non-consumers, but, among soy consumers, equol producers had 10% lower total BMD (p-interaction = 0.099) and 9% lower head BMD (p-interaction = 0.281). No O-DMA nonproducing women were frequent soy consumers, so
interaction between soy intake and O-DMA-producer phenotype in relation to BMD was not evaluated. Age-adjusted total BMD was positively associated with estrogen concentrations in equol producers and was inversely associated in equol non-producers (Table 5). No appreciable differences in the association of total BMD with circulating pro-androgens, androgens or FSH were observed by equol-producer phenotype. No appreciable differences in the association of total BMD with any of hormones were observed by the O-DMA-producer phenotype.
4. Discussion The objective of this study was to evaluate differences in BMD between producers and non-producers for each soy isoflavone-metabolizing phenotype. We observed that O-DMA producers, compared to nonproducers had 0.06 g/cm2 more (6% greater) ageadjusted total BMD and 0.06 g/cm2 more (7% greater) spinal BMD. These differences may represent a substantial difference for postmenopausal women. In 73 postmenopausal women, with BMD measurements taken at least three times over 2–8 years, Slemenda et al. [21] observed that the average rates of bone loss ranged from 0.002 g/cm2 /year in the spine to 0.009 g/cm2 /year in the femoral neck. In relation to breast cancer, Nguyen et al. [22] observed that each 10% increase in spinal BMD and in femoral neck BMD was associated with a two-fold and a one-and-one-half-fold, respectively, increase in breast cancer risk.
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Table 5 Age-adjusted difference (standard errors) in total BMD (g/cm2 ) with a one-standard deviation increase in circulating hormone concentrations and urinary estrogen metabolite ratio in 92 postmenopausal women Hormone or metabolitea
O-DMA-producer phenotype
Equol-producer phenotype Non-producers (n = 68)
Producers (n = 24)
p-interactionb
Non-producers (n = 16)
Producers (n = 76)
p-interactionb
Estrogens E2 Free E2 E1
0.026 (0.011) 0.032 (0.011) 0.027 (0.011)
−0.003 (0.024) −0.007 (0.024) −0.019 (0.024)
0.11 0.05 0.04
0.028 (0.014) 0.029 (0.013) 0.022 (0.016)
0.016 (0.013) 0.025 (0.013) 0.014 (0.012)
0.49 0.69 0.64
Pro-androgens A DHEA DHEAS
0.019 (0.011) 0.018 (0.012) 0.023 (0.011)
0.003 (0.031) 0.028 (0.026) 0.034 (0.028)
0.54 0.87 0.77
0.036 (0.018) 0.029 (0.015) 0.036 (0.013)
0.015 (0.012) 0.018 (0.013) 0.018 (0.013)
0.40 0.32 0.41
Androgens T Free T
0.016 (0.011) 0.029 (0.010)
0.000 (0.032) −0.018 (0.035)
0.86 0.19
0.026 (0.018) 0.025 (0.013)
0.008 (0.012) 0.025 (0.013)
0.93 0.61
−0.008 (0.011)
0.006 (0.027)
0.60
−0.034 (0.032)
−0.008 (0.011)
0.43
Estrogen metabolite ratio 2-OH E1 :16␣-OH E1 −0.008 (0.011)
0.021 (0.032)
0.53
−0.013 (0.017)
−0.005 (0.012)
0.72
Gonadotrophin FSH
a
E2 : estradiol, E1 : estrone, A: androstenedione, DHEA: dehydroepiandrosterone, DHEAS: dehydroepiandrosterone-sulfate, T: testosterone, FSH: follicle stimulating hormone, 2-OH E1 :16␣-OH E1 :2-hydroxyestrone:16␣-hydroxyestrone. b p-value for interaction between soy isoflavone-metabolizing phenotype and hormone/metabolite in relation to total BMD.
In O-DMA producers compared to non-producers, the greatest magnitudes of difference were observed for head (12%) and spinal (7%) BMD, and the least magnitudes of difference for pelvic (4%) and arm (3%). Cortical bone is predominant in the appendicular skeleton (e.g. limbs and pelvis) and a greater proportion of trabecular bone is found in the axial skeleton (e.g. skull, ribs and spine) [23]. Trabecular bone is more metabolically responsive than cortical bone [23] and head BMD is considered to a better marker of endogenous exposures than other sites because head bone is less mechanically stressed [24]; thus, these results provide some support that the O-DMA-producer phenotype may influence BMD through metabolic factors. However, adjusting for metabolic-related factors predictive of BMD, including circulating hormone concentrations, urinary estrogen metabolite ratio, weight history and oral contraceptive use history, did not alter the association of O-DMA-producer phenotype and BMD, suggesting this phenotype may not influence BMD through these particular factors. Because sex hormones, particularly estrogens and androgens, are positively associated with the develop-
ment and maintenance of bone [1], and given the data at the time of this study on hormonal differences between equol phenotypes in premenopausal women [14], we hypothesized that equol producers would have lower BMD than non-producers. Contrary to our hypothesis, we observed no large difference in total or site-specific BMD between equol producers and non-producers in this group of postmenopausal women; however, we observed several effects that warrant further evaluation. To the best of our knowledge, this is the first observational study of the equol-producer phenotype and BMD. There was no suggestion that we were statistically underpowered to detect a difference between equol producers and non-producers. There are several possibilities why we did not observe a difference in BMD in relation to equol-producer phenotype. A first possibility is related to our study population of postmenopausal women. It may be that differences in BMD exist in premenopausal women in relation to equol-producer phenotype, but these differences are not maintained after menopause. A second possibility is that differences in premenopausal or postmenopausal circulating hormone concentrations between equol pro-
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ducers and non-producers observed in previous studies [14,17] are not large enough to translate to appreciable differences in BMD. A third possibility is that soy consumption may be important in the association between equol-producer phenotype and BMD, and because regular soy consumption was low overall, we could not detect differences in this group of women. There are data to suggest that equol-producer phenotype may have role in the relationship between soy consumption and BMD. Lydeking-Olsen et al. [25] present the results of an ancillary analysis to an intervention study of soymilk with or without isoflavones in postmenopausal women; of the women in the isoflavone arm, equol producers (n = 10) had a BMD increase of 2.4% in the lumbar spine, whereas equol non-producers (n = 12) had a 0.6% increase. We observed that equol producers consuming more soy had lower spinal BMD than equol producers consuming less soy, and the converse in equol non-producers. This dissimilarity in our observations from the intervention study may be explained by low soy consumption in our study, limited evaluation of soy consumption in our study, differences in study design, or by soy consumption serving as a marker for other health-related behaviors [26]. Overall, observations from both studies highlight that further observational work with larger sample sizes is needed to determine whether and how the equol-producer phenotype interacts with soy consumption in relation to an association with BMD. We observed, among equol producers, no association between total age-adjusted BMD and circulating estrogen concentrations, whereas we observed a positive association among equol non-producers. These results suggest that circulating estrogens may differentially influence BMD in equol producers compared to equol non-producers. Daidzein is found predominantly in soy, but is also present in minimal levels in other foods [27,28]. Hypothetically, it is possible that low levels of circulating equol in equol producers, resulting from low soy intake or high intake of foods containing nominal levels of daidzein, competes with circulating estrogens for binding to estrogen receptors in bone. In support of this hypothesis, equol binds to estrogen receptor-␣ in vitro, and appears to exert antiestrogenic effects in the human estrogen-sensitive breast cancer cell line MCF-7 [29]. However, these analyses were exploratory, and our findings regarding an interaction between circulating estrogens and equol-producer phe-
notype in relation to BMD may also have been observed by chance. Our study has several limitations. One, given the small sample of women, we were not able to estimate precisely the magnitude of association for the exploratory interactions we evaluated and we also may have failed to identify some true associations. However, we know of no other studies to date that have evaluated the association between BMD and soy isoflavonemetabolizing phenotypes in relation soy intake within an observational study. The soy intake observed in this study is similar to that observed by others in postmenopausal women in the U.S. [26,28]. Thus, although our observations lack the precision of an intervention study, our observations may reflect the association present in the population. Two, the parent study was a randomized trial, and the women were selected for the parent study based on particular selection criteria. All women in our study were postmenopausal and overweight or obese, with an average BMI of 30. In the Women’s Health Initiative observational study, more than half of the women enrolled were overweight or obese [30], suggesting that being overweight or obese is common among postmenopausal women. Thus, while the selection criteria for the parent study may have reduced variability in BMD, and, thus, decreased the power to detect associations in this ancillary study, we believe they do not limit generalizability. Three, our cut-off of 44 ng/ml urinary O-DMA and equol may differ from other studies. The urinary isoflavone cut-off value for assigning soy isoflavone-metabolizing phenotypes has not yet been well-established with validation studies. However, because the cut-off is unlikely to be related to BMD value, any bias introduced would be from non-differential misclassification, and as such, would have reduced the ability to detect an association between soy isoflavone-metabolizing phenotypes and BMD. In this circumstance, our results would be conservative. Another source of potential non-differential misclassification is that phenotyping occurred 2–3 years after BMD was measured. However, in recent work, we observed that, in 92 individuals, the phenotypes are stable in most individuals over a period of 1–3 years (unpublished data); thus, the amount of misclassification introduced would be small. These soy isoflavone-metabolizing phenotypes are markers of the presence of particular bacteria capable of metabolizing daidzein to O-DMA and equol
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(reviewed in [31]). The bacteria responsible for ODMA production and for equol production in humans have not yet been established definitely. Because there are four distinct combined soy isoflavone-metabolizing phenotypes and no significant correlation between phenotypes within an individual [16], it appears that the bacteria that metabolize daidzein to O-DMA are not the same bacteria that metabolize daidzein to equol. Our results suggest that intestinal bacterial profile is associated with BMD independent of several potential confounding factors. The hypothesized mechanisms discussed herein are not mutually exclusive, and intestinal bacteria may influence BMD through several mechanisms. Further work is needed to elucidate the mechanisms by which intestinal bacteria, and in particular the soy-isoflavone metabolizing phenotypes, may influence BMD. Because the O-DMA-producer phenotype appears to be stable in adults over time [32], our results suggest that this phenotype may provide an early marker of osteoporosis risk. Our results should be confirmed in additional studies, and evaluation in other age groups and populations is also warranted.
Acknowledgments This work was supported by National Institutes of Health R03CA097475 and R01CA69334, and Institutional Research Training Grant T32CA009168, Fred Hutchinson Cancer Research Center Institutional Funds, and the National Cancer Institute Cancer Prevention Fellowship. The authors are grateful to Judy Schramm for her work in participant recruitment. Deuterated standards for the analysis of equol and ODMA were prepared and provided by Kristiina W¨ah¨al¨a and Tuija Jokela, Dept. of Chemistry, University of Helsinki. CLF is currently a Cancer Prevention Fellow in the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health.
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