Cancer Causes Control (2014) 25:143–149 DOI 10.1007/s10552-013-0316-8
ORIGINAL PAPER
Plasma amino acid profiles are associated with biomarkers of breast cancer risk in premenopausal Japanese women Chisato Nagata • Keiko Wada • Michiko Tsuji Makoto Hayashi • Noriyuki Takeda • Keigo Yasuda
•
Received: 17 July 2013 / Accepted: 19 October 2013 / Published online: 2 November 2013 Ó Springer Science+Business Media Dordrecht 2013
Abstract Objective Recently, profiles of plasma amino acids have been utilized to detect diseases including breast cancer. However, there is a possibility that the amino acid status may be associated with the risk of breast cancer. We investigated the relationship of plasma levels of amino acids with levels of sex hormones and insulin-like growth factor (IGF)-1, which are relevant to the etiology of premenopausal breast cancer, in normal premenopausal women. Methods Participants were 350 Japanese women who had regular menstrual cycles less than 40-day long. Fasting plasma samples were assayed for estradiol, testosterone, dehydroepiandrosterone sulfate, sex-hormone-binding globulin (SHBG), and IGF-1. A total of 20 amino acids in plasma were quantified by liquid chromatography–mass spectrometry. Information on lifestyle and reproductive factors was obtained using a self-administered questionnaire.
Electronic supplementary material The online version of this article (doi:10.1007/s10552-013-0316-8) contains supplementary material, which is available to authorized users. C. Nagata (&) K. Wada M. Tsuji Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan e-mail: [email protected] M. Tsuji Department of Food and Nutrition, Japan Women’s University, Tokyo, Japan M. Hayashi K. Yasuda Department of Internal Medicine, Matsunami General Hospital, Gifu, Japan N. Takeda Department of Endocrinology and Metabolism, Murakami Memorial Hospital, Asahi University, Gifu, Japan
Results The plasma arginine level was significantly inversely correlated with plasma levels of total and free estradiol and IGF-1 after adjusting for age, body mass index, and phase of the menstrual cycle. Plasma leucine and tyrosine levels were significantly positively correlated with the free testosterone level. The ratio of plasma asparagine to the total amino acids was significantly positively correlated with SHBG level. Conclusions Plasma levels of some specific amino acids, such as arginine, leucine, tyrosine, and asparagine, were associated with the levels of sex hormones, SHBG, or IGF1 in premenopausal women. However, the present crosssectional study cannot provide a cause–effect relation. The implication of amino acids in the etiology of breast cancer needs to be addressed in future studies. Keywords Amino acids Breast cancer Sex hormones IGF-1 Premenopausal
Introduction Recent advances in the metabolomics approach encourage studies that aim at diagnosing and screening diseases [1]. Among metabolites, plasma amino acids are most commonly measured. The use of high-performance liquid chromatography or liquid chromatography–mass spectrometry (LC–MS) facilitates the measurement of about 40 amino acids [2]. Specific abnormalities in amino acid levels have been reported in cases of metabolic diseases and cancers, including breast cancer [3–7]. It is likely that the perturbation of the amino acid profile in patients should be the consequence of disease. However, there may be a possibility that the amino acid status may reflect the risk of disease.
123
144
Amino acids play important roles both as basic metabolites and as metabolic regulators and are considered to be central compounds within metabolic networks [7]. Amino acids have regulatory role in gene expression, nutrient metabolism, oxidative defense, immune function, and cell growth and proliferation [8, 9]. These properties may have influence on the genesis of cancer. Endogenous sex hormones and insulin-like growth factor (IGF)-1 have been associated with the risk of breast cancer in women [10–12]. Evaluating the relationships between amino acids and sex hormones or IGF-1 has the potential to provide etiologic inferences concerning this disease, although we caution that due to the cross-sectional nature of the data, a cause and effect relationship cannot be deduced from this study. We examined the association of plasma levels of amino acids with sex hormones and IGF-1 in healthy premenopausal Japanese women. Previous studies on amino acid levels and sex hormone or IGF-1 in healthy subjects are scarce. In addition, most of them have assessed the shortterm effects of hormone supplementation and have measured a limited number of amino acids [13–15].
Methods A total of 1,545 women who attended a medical health checkup program provided by a general hospital in Gifu, Japan, between October 2003 and March 2006 agreed to join a study designed to assess the relationships among lifestyle, environmental factors, and women’s health [16]. The response proportion was 74.5 percent as 2,073 persons including return visitors to the program during the study were invited. Details of the entire study are described elsewhere [16]. Participants responded to a self-administered questionnaire asking information on demographic characteristics, smoking and drinking habits, diet, exercise, and medical and reproductive histories. Height and weight were measured. On the same day, fasting blood samples were drawn from participants around at 8:00 a.m., and plasma were stored at -80 °C until the assay. The study was approved by the ethical board of the Gifu University Graduate School of Medicine. Written informed consent was obtained from all subjects. Women included in this study were premenopausal women who had regular menstrual cycles of less than 40 days. Detailed information about these women has been described elsewhere [17]. In brief, after excluding women using oral contraceptives, hormone therapy, or steroid (n = 16) at the time of blood draw or those who had cancer, diabetes mellitus, chronic hepatitis, or thyroid disease (n = 22), a total of 436 women who were not pregnant or breastfeeding and had regular menstrual cycles of less than 40 days provided blood samples for sex
123
Cancer Causes Control (2014) 25:143–149
hormone measurements. Since blood volume was insufficient for additional measurement of amino acids for 86 women, remaining 350 women comprised the study population. Among them, the shortest menstrual cycle length was 20 days (n = 2). IGF-1 levels were not measured for 121 women because of insufficient blood volume. Before measurement of amino acids, the EDTA plasma samples were deprotenized using acetonitrile at a final concentration of 80 %. Individual amino acids were determined by LC–MS (LC–MS2020, Shimazu Corp., Kyoto, Japan) using Amino Tag Wako (Wako Pure Chemical Industries, Ltd., Osaka, Japan), followed by precolumn derivatization. Total of 38 amino acids were detected by the analyzer. However, only amino acids that had values of which \25 % were undetected or exceeded 1 % of the total amino acid level were included, with the exception of methionine (Met, 0.85 % of the total amino acids). These were following 20 amino acids: alanine (Ala), arginine (Arg), asparagine (Asn), citrulline (Cit), glutamine (Gln), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), ornithine (Orn), phenylalanine (Phe), proline (Pro), serine (Ser), taurine (Tau), threonine (Thr), tryptophan (Try), tyrosine (Tyr), and valine (Val). The interassay coefficient of variation was B5.0 % for any type of amino acid. Plasma estradiol and testosterone were measured using electro chemiluminescent immunoassay with kits purchased from the Roche Diagnostic Japan, Tokyo, Japan. Plasma dehydroepiandrosterone sulfate (DHEAS) was measured by chemiluminescent enzyme immunoassay using kits purchased from the Beckman Coulter, Tokyo, Japan. Sex-hormone-binding globulin (SHBG) was measured using immunoradiometric assay with kits purchased from Diagnostic Products Corporation, Los Angeles, USA. IGF-1 was measured using immunoradiometric assay with kits purchased from TFB, Inc. Tokyo, Japan. The interassay coefficients of variation were B3.5 % for estradiol, B3.6 % for testosterone, B10.6 % for DHEAS, B7.9 % for SHBG, and B10.0 % for IGF-1. Free estradiol and testosterone were calculated using the measured estradiol, testosterone, albumin, and SHBG levels. This method has been found to have high validity compared with direct measurement [18]. For statistical analysis, plasma levels of amino acids, sex hormones, SHBG, and IGF-1 were logarithmically transformed. The first day of the ongoing menstrual cycle was recorded, but the date of the start of her next menses after blood donation was not obtained. We estimated the date of the start of woman’s next menses after blood donation from the date of her last menses and her reported usual cycle length [17]. The day of the menstrual cycle at blood donation was determined by ‘‘backward dating’’ counted backwards from the estimated date of her next menses. The phase of the
Cancer Causes Control (2014) 25:143–149
145
Table 1 Characteristics of 350 premenopausal women Variables Age (years)
39.6 (5.6)
Height (cm)
158.7 (5.3)
Weight (kg)
52.2 (7.0)
2
20.7 (2.6)
BMI (kg/m ) Education (years)
13.8 (2.0)
Age at menarche (years)
12.8 (1.2)
Age at first birth (years)
26.4 (2.9)
No. of births Exercise (METsh/wk)
1.6 (1.1) 25.1 (32.3)
Current smokers (%)
6.6
Ex-smokers (%)
3.1
Values are means (SD) or percentages BMI body mass index, METs metabolic equivalents
menstrual cycle at blood donation was categorized into the early follicular (days B -21 of the cycle), late follicular (days -20 to -17), peri-ovulatory (days -16 to -13), early luteal (days -12 to -9), midluteal (days -8 to -4), or late luteal (days C -3) phases. The geometric means of amino acids according to the phase of menstrual cycle and the quartiles of hormones were provided using analysis of covariance models. Pearson’s correlation was used to assess the association between plasma levels of amino acids and sex hormones, SHBG, and IGF-1. Age, BMI, and the phase of the menstrual cycle at the time of blood donation were used for adjustment. Given the 25 individual or grouped amino acids according to the metabolic pathways (presented in supplemental Fig. S1), we used a Bonferroni-corrected p value threshold of 0.002 (0.05/25) to account for the number of metabolites analyzed. We also calculated correlation coefficients of the ratios of each amino acid or grouped amino acids the sum of the 20 amino acids (total amino acids) with sex hormone, SHBG, and IGF-1 levels. All the statistical analyses were performed using SAS programs (SAS Institute Inc., Cary, NC, USA).
Results Characteristics of study subjects are shown in Table 1. They were aged 20–54 years and had BMI between 14.7 and 30.9 kg/m2. Most were parous (n = 270, 77.1 %) and \10 % reported being current or ex-smokers. Table 2 shows the means of plasma levels of hormones and amino acids according to the phase of the menstrual cycle. The plasma levels of Thr, Ser, Asn, Gln, Pro, Gly, Ala, Cit, Met, Tyr, Orn, and Lys varied during the subjects’ menstrual cycles, although their varied less compared with levels of total and free estradiol.
Plasma Arg level was significantly inversely correlated with total and free estradiol and IGF-1 levels after controlling for age, BMI, and phase of the menstrual cycle (Table 3). The geometric means of plasma Arg for the lowest to the highest quartiles, respectively, were the following: for total estradiol, 70.7, 62.5, 54.7, and 57.9 nmol/mL; free estradiol, 70.4, 61.7, 54.2, and 59.3 nmol/mL; and IGF-1, 68.8, 66.8, 63.4, and 62.8 nmol/mL. Plasma level of ureagenic amino acids was significantly positively correlated with total estradiol, and the geometric means of them for the lowest to the highest quartiles of total estradiol were 173.4, 159.7, 147.7, and 155.7 nmol/mL, respectively. Plasma levels of Tyr, Leu, and branched-chain amino acids (BCAA) were significantly positively correlated with free testosterone level. The geometric means of plasma Tyr, Leu, and BCAA for the lowest to the highest quartiles of free testosterone, respectively, were the following: Tyr, 53.9, 53.7, 56.2, and 59.1 nmol/mL; Leu, 99.7, 102.4, 102.1, and 108.9 nmol/mL; BCAA, 336.2, 342.3, 344.9, and 363.3 nmol/mL. Plasma levels of Ala, Met, Tyr, Lys, and ketogenic amino acids were significantly inversely correlated with SHBG level. Total testosterone and DHEAS were not significantly correlated with any amino acid level. Regarding ratios, plasma Arg was significantly correlated with total estradiol (r = -0.20, p = 0.0002), free estradiol (r = -0.20, p = 0.0002), and IGF-1 (r = -0.31, p \ 0.0001). The ratio of Tyr to the total amino acids was significantly positively correlated with IGF-1 level (r = 0.22, p = 0.0010). The ratio of Asp to the total amino acids was significantly positively correlated with SHBG level (r = 0.17, p = 0.0019, respectively). BMI was significantly positively correlated with Ala (r = 0.26, p \ 0.0001), Val (0.27, p \ 0.0001), Iso (0.21, p \ 0.0001), Leu (r = 0.19, p = 0.0003), Tyr (r = 0.20, p = 0.0002), ketogenic amino acids (r = 0.22, p \ 0.0001), and BCAA (r = 0.24, p \ 0.0001) and significantly inversely correlated with Cit (r = -022, p \ 0.0001). After excluding BMI from the covariates, plasma levels of Gly (r = 0.19), Val (r = 0.23), Ile (r = 0.19), Leu (r = 0.24), Tyr (r = 0.25), Phe (r = 0.17), and BCAA (r = 0.24) were significantly positively correlated with free testosterone. Plasma levels of Ala (r = -0.26), Val (r = -0.23), Met (r = -0.22), Leu (r = -0.22), Tyr (r = -0.26), Phe (r = -0.17), Lys (r = -0.23), glycogenic amino acids (r = -0.18), ketogenic amino acids (r = -0.26), and BCAA (r = -0.24) were significantly inversely correlated with SHBG. The results concerning the other relations were not altered substantially without adjustment for BMI. Adjustment for age at menarche, parity, age at first birth, and physical activity together with age, BMI, and the phase of menstrual cycle did not alter the results substantially. For example, the correlation coefficients for plasma Alg with total and free estradiol and IGF-1 were -0.20
123
146
Cancer Causes Control (2014) 25:143–149
Table 2 Age-adjusted geometric means of plasma amino acids and hormones by the phase of menstrual cycle at blood draw in premenopausal women Early follicular (n = 74)
Late follicular (n = 48)
Peri-ovulatory (n = 56)
Early luteal (n = 54)
Midluteal (n = 70)
Late luteal (n = 48)
p for homogeneity
Cycle phase-adjusted
Amino acids (nmol/mL) Ala
342.3
351.2
295.5
293.8
295.3
333.8
\0.0001
319.4
Ser Gly
138.2 264.0
135.1 237.3
117.9 204.6
115.7 202.8
118.0 205.1
128.4 220.7
\0.0001 \0.0001
126.4 225.0
Thr
144.3
142.1
115.8
104.4
96.5
120.7
\0.0001
120.8
Trp
51.4
54.1
53.9
52.4
51.7
52.0
0.15
52.4
Asn
47.0
46.6
41.8
40.0
39.4
43.6
\0.0001
43.2
Phe
54.0
53.6
53.6
53.8
54.8
55.9
0.51
54.3
Tyr
57.8
59.1
53.7
53.3
52.5
59.2
\0.0001
55.9
Ile
53.0
52.1
49.8
50.5
51.2
52.8
0.23
51.7
Met
24.4
23.6
20.9
20.9
20.6
23.1
\0.0001
22.4
Val
191.8
191.8
186.9
190.6
187.6
201.8
0.08
191.6
Gln
521.8
520.9
467.6
432.5
430.6
477.0
\0.0001
477.0
Arg
75.8
71.6
57.1
52.6
51.0
62.8
\0.000
62.1
His
77.4
81.0
76.6
77.7
77.9
80.9
0.01
78.4
Pro
130.0
131.1
118.6
111.8
111.8
126.6
0.0005
122.0
Leu
103.2
102.4
99.4
104.1
103.9
106.7
\0.0001
103.3
Lys Orn
177.7 77.3
179.2 78.1
160.5 66.8
153.8 60.6
146.5 62.8
163.1 68.3
\0.0001 \0.0001
163.9 69.3
Cit
29.2
28.1
26.3
24.5
23.8
25.2
\0.0001
26.3
Tau
147.7
137.8
140.8
148.1
150.1
150.9
0.33
146.2
Total
2,742
2,712
2,436
2,375
2,365
2,588
\0.0001
2,548
Total E2 (pg/mL)
62.9
101.9
144.1
138.4
131.2
80.4
\0.0001
100.3
Free E2 (pg/mL)
1.24
2.07
2.82
2.70
2.60
1.58
\0.0001
1.99
Total T (ng/dL)
23.8
23.7
30.8
27.9
26.9
24.8
0.04
26.0
Free T (ng/dL)
0.35
0.36
0.45
0.40
0.40
0.36
0.25
0.40
DHEAS (lg/dL)
121.1
117.6
125.3
124.7
132.2
122.4
0.68
124.0
SHBG (nmol/L)
62.4
58.3
61.8
65.5
61.3
61.8
0.98
61.8
IGF-1 (ng/mL)
179.4
193.0
210.2
216.7
204.8
199.0
0.005
198.0
Ala alanine, Ser serine, Gly glycine, Thr threonine, Trp tryptophan, Asn asparagine, Phe phenylalanine, Tyr tyrosine, Ile isoleucine, Met methionine, Val valine, Gln glutamine, Arg arginine, His histidine, Pro proline, Leu leucine, Lys lysine, Orn ornithine, Cit citrulline, Tau taurine, E2 estradiol, T testosterone, DHEAS dehydroepiandrosterone sulfate, SHBG sex-hormone-binding globulin, IGF-1 insulin-like growth factor-1
(p \ 0.001), -0.19 (p = 0.004), and -0.28 (p \ 0.0001), respectively, after controlling for all these covariates. Insulin resistance affects amino acid and protein metabolism [19]. Adjustment for insulin resistance together with age, BMI, and the phase of the menstrual cycle attenuated the correlation of the ratio of Asp to the total amino acids with SHBG level (r = 0.13, p = 0.03).
Discussion We observed that some amino acids were moderately but significantly associated with endogenous hormone or IGF-1 levels in premenopausal women. In recent years, metabolic profiling of blood plasma has been noted as a promising
123
approach in screening for cancers. To our knowledge, three studies reported the differences in amino acid profiles in plasma or urine between breast cancer patients and healthy controls [4, 6, 7]. Comparisons of the results from these studies with those from the present study would provide biological insights into the role of amino acids in the development of breast cancer. In these studies, differences between breast cancer cases and controls were observed for the levels of Trp, Thr, Ala, Gly, Pro, Ile, Leu, and Val (without replication of any particular amino acid among the three studies) [4, 6, 7]. None of these amino acids except Leu was associated with hormone or IGF-1 levels in our study. The level of Leu was lower in breast cancer patients in one of the three studies [6], whereas plasma Leu level in our study was significantly positively correlated with free testosterone levels.
Cancer Causes Control (2014) 25:143–149
147
Table 3 Partial correlation coefficientsa of plasma amino acids with sex hormones, SHBG, and IGF-1 in premenopausal women Total E2
Free E2
Total T
Free T
DHEAS
SHBG
IGF-1
Ala
-0.09
-0.04
0.04
Ser
-0.11
-0.11
-0.06
0.12
0.01
-0.17*
-0.03
-0.05
-0.06
-0.04
Gly
-0.15
-0.13
-0.05
-0.02
-0.16
-0.04
-0.08
-0.15
Thr
-0.09
-0.07
-0.02
Trp
0.03
0.06
0.08
0.13
-0.10
-0.06
-0.13
0.05
-0.12
Asn
-0.06
-0.07
0.07
0.04
0.05
-0.05
0.01
Phe
-0.05
-0.01
0.09
0.08
0.15
0.08
-0.15
Tyr
-0.06
0.05
-0.007
0.12
0.21**
0.05
-0.20**
Ile
0.10
-0.03
0.02
0.06
0.14
0.06
-0.15
0.002
0.003
Met
-0.08
-0.03
0.008
0.10
-0.03
-0.22**
-0.13
Var Gln
0.02 -0.12
-0.07 -0.11
0.08 0.13
0.16 0.12
-0.10 0.07
-0.14 -0.05
0.06 -0.07
Arg
-0.19**
-0.19*
-0.04
-0.02
-0.06
-0.09
-0.28**
His
-0.09
-0.08
-0.03
-0.004
-0.02
-0.02
0.06 -0.004
Pro
0.06
0.08
0.11
0.13
0.03
-0.06
Leu
-0.05
0.01
0.10
0.19**
0.14
-0.16
Lys
0.14
-0.09
0.02
0.04
-0.18*
-0.06
Orn
-0.05
-0.00
0.08
0.14
0.05
-0.16
-0.08
Cit
-0.09
-0.07
-0.06
-0.02
-0.04
-0.06
-0.09
Tau
-0.02
0.07
0.05
0.06
0.03
Glucogenicb
-0.14
-0.10
0.06
-0.12
Ketogenicc
-0.08
-0.02
0.06
BCAAd
-0.008
-0.14
0.09
Ureagenice
-0.18*
-0.14
0.0003
Total
-0.13
-0.09
0.14
0.07
0.09
0.04
-0.13
0.009
-0.15
-0.07
0.15
0.04
-0.19*
0.18*
0.11
-0.16
0.09
0.06
-0.03
-0.16
-0.26*
0.07
0.03
-0.16
-0.13
0.05
Ala alanine, Ser serine, Gly glycine, Thr threonine, Trp tryptophan, Asn asparagine, Phe phenylalanine, Tyr tyrosine, Ile isoleucine, Met methionine, Val valine, Gln glutamine, Arg arginine, His histidine, Pro proline, Leu leucine, Lys lysine, Orn ornithine, Cit citrulline, Tau taurine, E2 estradiol, T testosterone, DHEAS dehydroepiandrosterone sulfate, SHBG sex-hormone-binding globulin, IGF-1 insulin-like growth factor-1 * Statistically significance after Bonferroni correction p \ 0.0020 ** Statistically significance after Bonferroni correction p \ 0.0004 a
Adjusted for age, BMI, and the phase of the menstrual cycle
b
Sum of Ala, Ser, Gly, Thr, Trp, Asn, Phe, Tyr, Ile, Met, Val, Glu, Arg, His, and Pro Sum of Ile, Leu, Thr, Trp, Lys, Phe, and Tyr
c d
Sum of Ile, Leu, and Val
e
Sum of Arg, Orn, and Cit
Thus, changes in the plasma levels of these amino acids may be the consequence of the breast cancer and would not reflect the risk of breast cancer. One study compared urinary amino acids between ovarian cancer patients and controls and the levels of Leu, Ile, Ala, and Val were lower in the urine of cancer patients [6]. Studies measuring amino acids in prediagnostic plasma are desirable. Among amino acids, only total (not free) cysteine and total homocysteine was measured in some prospective studies [20–22]. No study has prospectively assessed the relationship between the risk of breast cancer and the amino acids given in the present study. We found that a high plasma level of Arg was significantly associated with decreased levels of total and free
estradiol and IGF-1. Arg methylation has been thought to have a regulatory role in estrogen actions [23]. Some studies reported that estrogen reduces asymmetric dimethylarginine (ADMA), an endogenously produced methylated form of Arg [24–26]. In response to estrogen, the catabolism and release of ADMA may be altered, which lead to the decreased circulating ADMA level. Verhoeven et al. [26] observed that ADMA as well as Arg levels in postmenopausal women decreased after intranasal or oral estradiol administration. In our study, total and free estradiol levels were significantly inversely correlated with Arg level, which may reflect their associations with ADMA level. Since IGF-1 and estrogen-mediated signaling
123
148
pathways are cross-linked [27], the inverse correlation may be also observed between Arg level and IGF-1 level. To our knowledge, no study has reported the relationship between plasma Arg and IGF-1 levels. It is likely that significant correlations of ureagenic amino acids with total estradiol and IGF-1 levels reflect those of Arg. We observed that Leu, Tyr, and BCAA levels were significantly correlated with the level of free testosterone. Testosterone has been thought to increase skeletal muscle protein synthesis [28], and Leu has the potential to regulate muscle protein synthesis [29]. Plasma Leu levels are controlled by the rate of use for the anabolic process of protein syntheses, their rate of catabolism, and the rate of protein turnover. The long-term anabolic effects of testosterone may be balanced with increased levels of plasma Leu. Since plasma Tyr levels have been reported to be correlated with plasma levels of Leu and other BCAA [30, 31], it is likely that Tyr showed also a positive correlation with the level of free testosterone. Leu and testosterone also have been associated with obesity and insulin resistance [31, 32]. There is a possibility that insulin or insulin resistance is an intermediate of the observed association between plasma Leu and free testosterone. However, adjustment for insulin resistance did not attenuate the observed associations. Plasma SHBG was significantly inversely correlated with concentrations of Ala, Met, Tyr, and ketogenic acids. Although BMI was included as a covariate, it is possible that these correlations still reflect the inverse association between nutritional status and SHBG. These amino acid levels were closely correlated with plasma total amino acids (r C 0.73); therefore, for the analysis concerning SHBG, it would be informative to give the relationships with individual amino acids in terms of the ratio to the total amino acid level, which may reflect nutritional status, rather than absolute value. We observed that the ratio of Asp to the total amino acid level was significantly positively correlated with SHBG. Interestingly, plasma Asp has been inversely associated with obesity and insulin resistance in some studies [30, 33, 34], and SHBG has been inversely associated with insulin resistance independent of body size [35]. In fact, the adjustment for insulin resistance attenuated the correlations of the ratio of Asp to the total amino acids to SHBG in the present study. Insulin resistance may have implications in the relationships of Asp to SHBG. Several limitations of this study should be noted. Blood samples were obtained at a single point in time without restriction to the day of the cycle, which may have caused large measurement errors for hormone levels and misclassifications of the cycle phase used for adjustments. However, studies with such a restriction regarding the day of a menstrual cycle have limited power. In recent years, some large studies have succeeded in detecting
123
Cancer Causes Control (2014) 25:143–149
associations between potential breast cancer risk factors and sex hormone levels using untimed blood samples [36– 38]. We also confirmed some of these associations in our dataset [17, 39]. A single assessment of amino acids may be subject to measurement error. However, Townsend et al. [40] evaluated the within-person reproducibility of 22 amino acids over 1–2 years and observed acceptable reproducibility (Spearman’s correlation or intraclass correlation coefficients C0.4) for all except His and Lys. All of the amino acids measured in this study were included in their study. Because of the cross-sectional design of the present study, we cannot determine whether sex hormones/ IGF-1 affect the amino acids or the amino acids affect these biomarkers. It is also possible that certain unknown factors may influence hormone and amino acid levels. Our data showed specific amino acids, rather than a large cluster of amino acids, were associated with endogenous sex hormone or IGF-1 levels. Nonetheless, the sample size is not sufficient to detect more associations. Although we partially considered the problem of multiple comparisons, we repeated procedures in analyses, which could have resulted in some associations occurring by chance. In conclusion, the present study showed that plasma levels of some specific amino acids, such as Arg, Leu, Tyr, and Asp, were associated with the endogenous sex hormone, SHBG, or IGF-1 level, established biomarkers of breast cancer risk. Whether these amino acids have implications in the etiology of breast cancer should be investigated in future studies. Acknowledgments This study was supported in part by Grants-inAid for Scientific Research on Innovative Areas (No. 221S0001) from the Japanese Ministry of Education, Culture, Sports, Science, and Technology. Conflict of interest of interest.
The authors declare that they have no conflict
References 1. Chadeau-Hyam M, Ebbels TM, Brown IJ et al (2010) Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification. J Proteome Res 9:4620–4627 2. Becker S, Kortz L, Helmschrodt C, Thiery J, Ceglarek U (2012) LC–MS-based metabolomics in the clinical laboratory. J Chromatogr B 883–884:68–75 3. Nakamura T, Takebe K, Rudoh K et al (1994) Increased plasma gluconeogenic and system A amino acids in patients with pancreatic diabetes due to chronic pancreatitis in comparison with primary diabetes. Tohoku J Exp Med 173:413–420 4. Chen Y, Zhang R, Song Y, He J et al (2009) RRLC–MS/MSbased metabonomics combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer. Analyst 134:2003–2011
Cancer Causes Control (2014) 25:143–149 5. Kamaura M, Nishijima K, Takahashi M, Ando T, Mizushima S, Tochikubo O (2010) Lifestyle modification in metabolic syndrome and associated changes in plasma amino acid profiles. Circ J 74:2434–2440 6. Slupsky CM, Steed H, Wells TH et al (2010) Urine metabolite analysis offers potential early diagnosis of ovarian and breast cancers. Clin Cancer Res 16:5835–5841 7. Miyagi Y, Higashiyama M, Gochi A et al (2011) Plasma free amino acid profiling of five types of cancer patients and its application for early detection. PLoS ONE 6:e24143 8. Wu G (2009) Amino acids: metabolism, functions, and nutrition. Amino Acids 37:1–17 9. Marshall S (2006) Role of insulin, adipocyte hormones, and nutrient-sensing pathways I regulating fuel metabolism and energy homeostasis: a nutritional perspective of diabetes, obesity, and cancer. Sci STKE 346:re7 10. Kaaks R, Berrino F, Key T et al (2005) Serum sex steroids in premenopausal women and breast cancer risk within the European Prospective Investigation into Cancer and Nutrition (EPIC). J Natl Cancer Inst 97:755–765 11. Fortner RT, Eliassen AH, Spiegelman D, Willett WC, Barbieri RL, Hankinson SE (2013) Premenopausal endogenous steroid hormones and breast cancer risk: results from the Nurses’ Health Study II. Breast Cancer Res 15:R19. doi:10.1186/bcr3394 12. The Endogenous Hormones and Breast Cancer Collaborative Group (2010) Insulin-like growth factor 1 (IGF1), IGF-binding protein 3 (IGFBP3), and breast cancer risk: reanalysis of 17 prospective studies. Lancet Oncol 11:530–542 13. Møller SE, Møller-Maach B, Olsen M, Fjalland B (1996) Effects of oral contraceptives on plasma neutral amino acids and cholesterol during a menstrual cycle. Eur J Clin Pharmacol 50:179–184 14. Ferrando AA, Tipton KD, Doyle D, Phillips SM, Cortiella J, Wolfe RR (1998) Testosterone injection stimulates net protein synthesis but not tissue amino acid transport. Am J Physiol 275:E864–E871 15. Hamadeh MJ, Devries MC, Tarnopolsky MA (2005) Estrogen supplementation reduces whole body leucine and carbohydrate oxidation and increases lipid oxidation in men during endurance exercise. J Clin Endocrinol Metab 90:3592–3599 16. Nagata C, Nakamura K, Oba S, Hayashi M, Takeda N, Yasuda K (2009) Association of intakes of fat, dietary fiber, soy isoflavone, and alcohol with uterine fibroids in Japanese women. Br J Nutr 101:1427–1431 17. Nagata C, Wada K, Nakamura K, Hayashi M, Takeda N, Yasuda K (2011) Associations of body size and reproductive factors with circulating levels of sex hormones and prolactin in premenopausal Japanese women. Cancer Cause Control 22:581–588 18. Sodergard R, Backstrom T, Shanbhag V, Carstensen H (1983) Calculation of free and bound fractions of testosterone and estradiol-17b to human plasma proteins at body temperature. J Steroid Biochem 16:801–810 19. Tessari P, Cecchet D, Cosma A et al (2011) Insulin resistance of amino acid and protein metabolism in type 2 diabetes. Clin Nutr 30:267–272 20. Zhang SM, Willett WC, Selhub J et al (2003) Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk of breast cancer. J Natl Cancer Inst 95:373–380 21. Lin J, Lee I-M, Song Y et al (2010) Plasma homocysteine and cysteine and risk of breast cancer in women. Cancer Res 70:2397–2405 22. Zhang SM, Willett WC, Selhub J, Manson JE, Colditz GA, Hankinson SE (2003) A prospective study of plasma total cysteine and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 12:1188–1193
149 23. Teyssier C, Le Romancer M, Sentis S, Jalaquier S, Corbo L, Cavaille´s V (2009) Protein arginine methylation in estrogen signaling and estrogen-related cancers. Trends Endocrinol Metab 21:181–189 24. Holden DP, Cartwright JE, Nussey SS, Whitley GSJ (2003) Estrogen stimulates dimethylarginine dimethylaminohydrolase activity and the metabolism of asymmetric dimethylarginine. Circulation 108:1575–1580 ¨ , Durmusoglu F, Yurdun T, Bilsel AS (2006) 25. C¸evik D, Unay O Plasma markers of NO synthase activity in women after ovarian hyperstimulation: influence of estradiol on ADMA. Vasc Med 11:7–12 26. Verhoeven MO, Hemelaar M, Teerlink T, Kenemans P, Van der Mooren MJ (2007) Effects of intranasal versus oral hormone therapy on asymmetric dimethylarginine in healthy postmenopausal women: a randomized study. Atherosclerosis 195:181–188 27. Hamelers IH, Van Schaik RF, Sussenbach JS, Steenbergh PH (2003) 17 beta-estradiol responsiveness of MCF-7 laboratory strains is dependent on an autocrine signal activating the IGF type I receptor. Cancer Cell Int 3:10 28. Urban RJ (2011) Growth hormone and testosterone: anabolic effects on muscle. Horm Res Paediatr 76(Suppl 1):81–83 29. Garlick PJ (2005) The role of leucine in the regulation of protein metabolism. J Nutr 135:1553S–1556S 30. Tai ES, Tan MLS, Stevens RD et al (2010) Insulin resistance is associated with a metabolic profile of altered protein metabolism in Chinese and Asian-Indian men. Diabetologia 53:757–767 31. Batch BC, Shah SH, Newgard CB et al (2013) Branched chain amino acids are novel biomarkers for discrimination of metabolic wellness. Metabolism. doi: 10.1016/j.metabol.2013.01.007 32. Kelly DM, Jones HT (2013) Testosterone: a metabolic hormone in health and disease. J Endocrinol 217:R25–R45 33. Cory JG, Cory AH (2006) Critical roles of glutamine as nitrogen donors in purine and pyrimidine nucleotide synthesis: asparaginase treatment in childhood acute lymphoblastic leukemia. In vivo 20:587–590 34. Stancˇa´kova´ A, Civelek M, Saleem NK et al (2012) Hyperglycemia and a common variant of GCKR are associated with the levels of eight amino acids in 9,369 Finnish men. Diabetes 61:1895–1902 35. Wallace IR, McKinley MC, Bell PM, Hunter SJ (2013) Sex hormone binding globulin and insulin resistance. Clin Endocrinol (Oxf) 78:321–329 36. Verkasalo PK, Thomas HV, Appleby PN, Davey GK, Key TJ (2011) Circulating levels of sex hormones and their relations to risk factors for breast cancer: a cross-sectional study in 1,092 preand postmenopausal women (United Kingdom). Cancer Causes Control 12:47–59 37. Bezemer ID, Rinaldi S, Dossus L et al (2005) C-peptide, IGF-I, sex-steroid hormones and adiposity: a cross-sectional study in healthy women within the European Prospective Investigation into Cancer and Nutrition (EPIC). Cancer Causes Control 16:561–572 38. Rinaldi S, Peeters PH, Bezemer ID et al (2006) Relationship of alcohol intake and sex steroid concentrations in blood in pre- and post-menopausal women: the European Prospective Investigation into Cancer and Nutrition. Cancer Causes Control 17:1033–1043 39. Tsuji M, Tamai Y, Wada K et al (2012) Associations of intakes of fat, dietary fiber, soy isoflavones, and alcohol with levels of sex hormones and prolactin in premenopausal Japanese women. Cancer Causes Control 23:683–689 40. Townsend MK, Clish CB, Kraft P et al (2013) Reproducibility of metabolomics profiles among men and women in 2 large cohort studies. Clin Chem. doi:10.1373/clinchem.2012.199133
123
ORIGINAL PAPER
Plasma amino acid profiles are associated with biomarkers of breast cancer risk in premenopausal Japanese women Chisato Nagata • Keiko Wada • Michiko Tsuji Makoto Hayashi • Noriyuki Takeda • Keigo Yasuda
•
Received: 17 July 2013 / Accepted: 19 October 2013 / Published online: 2 November 2013 Ó Springer Science+Business Media Dordrecht 2013
Abstract Objective Recently, profiles of plasma amino acids have been utilized to detect diseases including breast cancer. However, there is a possibility that the amino acid status may be associated with the risk of breast cancer. We investigated the relationship of plasma levels of amino acids with levels of sex hormones and insulin-like growth factor (IGF)-1, which are relevant to the etiology of premenopausal breast cancer, in normal premenopausal women. Methods Participants were 350 Japanese women who had regular menstrual cycles less than 40-day long. Fasting plasma samples were assayed for estradiol, testosterone, dehydroepiandrosterone sulfate, sex-hormone-binding globulin (SHBG), and IGF-1. A total of 20 amino acids in plasma were quantified by liquid chromatography–mass spectrometry. Information on lifestyle and reproductive factors was obtained using a self-administered questionnaire.
Electronic supplementary material The online version of this article (doi:10.1007/s10552-013-0316-8) contains supplementary material, which is available to authorized users. C. Nagata (&) K. Wada M. Tsuji Department of Epidemiology and Preventive Medicine, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan e-mail: [email protected] M. Tsuji Department of Food and Nutrition, Japan Women’s University, Tokyo, Japan M. Hayashi K. Yasuda Department of Internal Medicine, Matsunami General Hospital, Gifu, Japan N. Takeda Department of Endocrinology and Metabolism, Murakami Memorial Hospital, Asahi University, Gifu, Japan
Results The plasma arginine level was significantly inversely correlated with plasma levels of total and free estradiol and IGF-1 after adjusting for age, body mass index, and phase of the menstrual cycle. Plasma leucine and tyrosine levels were significantly positively correlated with the free testosterone level. The ratio of plasma asparagine to the total amino acids was significantly positively correlated with SHBG level. Conclusions Plasma levels of some specific amino acids, such as arginine, leucine, tyrosine, and asparagine, were associated with the levels of sex hormones, SHBG, or IGF1 in premenopausal women. However, the present crosssectional study cannot provide a cause–effect relation. The implication of amino acids in the etiology of breast cancer needs to be addressed in future studies. Keywords Amino acids Breast cancer Sex hormones IGF-1 Premenopausal
Introduction Recent advances in the metabolomics approach encourage studies that aim at diagnosing and screening diseases [1]. Among metabolites, plasma amino acids are most commonly measured. The use of high-performance liquid chromatography or liquid chromatography–mass spectrometry (LC–MS) facilitates the measurement of about 40 amino acids [2]. Specific abnormalities in amino acid levels have been reported in cases of metabolic diseases and cancers, including breast cancer [3–7]. It is likely that the perturbation of the amino acid profile in patients should be the consequence of disease. However, there may be a possibility that the amino acid status may reflect the risk of disease.
123
144
Amino acids play important roles both as basic metabolites and as metabolic regulators and are considered to be central compounds within metabolic networks [7]. Amino acids have regulatory role in gene expression, nutrient metabolism, oxidative defense, immune function, and cell growth and proliferation [8, 9]. These properties may have influence on the genesis of cancer. Endogenous sex hormones and insulin-like growth factor (IGF)-1 have been associated with the risk of breast cancer in women [10–12]. Evaluating the relationships between amino acids and sex hormones or IGF-1 has the potential to provide etiologic inferences concerning this disease, although we caution that due to the cross-sectional nature of the data, a cause and effect relationship cannot be deduced from this study. We examined the association of plasma levels of amino acids with sex hormones and IGF-1 in healthy premenopausal Japanese women. Previous studies on amino acid levels and sex hormone or IGF-1 in healthy subjects are scarce. In addition, most of them have assessed the shortterm effects of hormone supplementation and have measured a limited number of amino acids [13–15].
Methods A total of 1,545 women who attended a medical health checkup program provided by a general hospital in Gifu, Japan, between October 2003 and March 2006 agreed to join a study designed to assess the relationships among lifestyle, environmental factors, and women’s health [16]. The response proportion was 74.5 percent as 2,073 persons including return visitors to the program during the study were invited. Details of the entire study are described elsewhere [16]. Participants responded to a self-administered questionnaire asking information on demographic characteristics, smoking and drinking habits, diet, exercise, and medical and reproductive histories. Height and weight were measured. On the same day, fasting blood samples were drawn from participants around at 8:00 a.m., and plasma were stored at -80 °C until the assay. The study was approved by the ethical board of the Gifu University Graduate School of Medicine. Written informed consent was obtained from all subjects. Women included in this study were premenopausal women who had regular menstrual cycles of less than 40 days. Detailed information about these women has been described elsewhere [17]. In brief, after excluding women using oral contraceptives, hormone therapy, or steroid (n = 16) at the time of blood draw or those who had cancer, diabetes mellitus, chronic hepatitis, or thyroid disease (n = 22), a total of 436 women who were not pregnant or breastfeeding and had regular menstrual cycles of less than 40 days provided blood samples for sex
123
Cancer Causes Control (2014) 25:143–149
hormone measurements. Since blood volume was insufficient for additional measurement of amino acids for 86 women, remaining 350 women comprised the study population. Among them, the shortest menstrual cycle length was 20 days (n = 2). IGF-1 levels were not measured for 121 women because of insufficient blood volume. Before measurement of amino acids, the EDTA plasma samples were deprotenized using acetonitrile at a final concentration of 80 %. Individual amino acids were determined by LC–MS (LC–MS2020, Shimazu Corp., Kyoto, Japan) using Amino Tag Wako (Wako Pure Chemical Industries, Ltd., Osaka, Japan), followed by precolumn derivatization. Total of 38 amino acids were detected by the analyzer. However, only amino acids that had values of which \25 % were undetected or exceeded 1 % of the total amino acid level were included, with the exception of methionine (Met, 0.85 % of the total amino acids). These were following 20 amino acids: alanine (Ala), arginine (Arg), asparagine (Asn), citrulline (Cit), glutamine (Gln), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Lys), methionine (Met), ornithine (Orn), phenylalanine (Phe), proline (Pro), serine (Ser), taurine (Tau), threonine (Thr), tryptophan (Try), tyrosine (Tyr), and valine (Val). The interassay coefficient of variation was B5.0 % for any type of amino acid. Plasma estradiol and testosterone were measured using electro chemiluminescent immunoassay with kits purchased from the Roche Diagnostic Japan, Tokyo, Japan. Plasma dehydroepiandrosterone sulfate (DHEAS) was measured by chemiluminescent enzyme immunoassay using kits purchased from the Beckman Coulter, Tokyo, Japan. Sex-hormone-binding globulin (SHBG) was measured using immunoradiometric assay with kits purchased from Diagnostic Products Corporation, Los Angeles, USA. IGF-1 was measured using immunoradiometric assay with kits purchased from TFB, Inc. Tokyo, Japan. The interassay coefficients of variation were B3.5 % for estradiol, B3.6 % for testosterone, B10.6 % for DHEAS, B7.9 % for SHBG, and B10.0 % for IGF-1. Free estradiol and testosterone were calculated using the measured estradiol, testosterone, albumin, and SHBG levels. This method has been found to have high validity compared with direct measurement [18]. For statistical analysis, plasma levels of amino acids, sex hormones, SHBG, and IGF-1 were logarithmically transformed. The first day of the ongoing menstrual cycle was recorded, but the date of the start of her next menses after blood donation was not obtained. We estimated the date of the start of woman’s next menses after blood donation from the date of her last menses and her reported usual cycle length [17]. The day of the menstrual cycle at blood donation was determined by ‘‘backward dating’’ counted backwards from the estimated date of her next menses. The phase of the
Cancer Causes Control (2014) 25:143–149
145
Table 1 Characteristics of 350 premenopausal women Variables Age (years)
39.6 (5.6)
Height (cm)
158.7 (5.3)
Weight (kg)
52.2 (7.0)
2
20.7 (2.6)
BMI (kg/m ) Education (years)
13.8 (2.0)
Age at menarche (years)
12.8 (1.2)
Age at first birth (years)
26.4 (2.9)
No. of births Exercise (METsh/wk)
1.6 (1.1) 25.1 (32.3)
Current smokers (%)
6.6
Ex-smokers (%)
3.1
Values are means (SD) or percentages BMI body mass index, METs metabolic equivalents
menstrual cycle at blood donation was categorized into the early follicular (days B -21 of the cycle), late follicular (days -20 to -17), peri-ovulatory (days -16 to -13), early luteal (days -12 to -9), midluteal (days -8 to -4), or late luteal (days C -3) phases. The geometric means of amino acids according to the phase of menstrual cycle and the quartiles of hormones were provided using analysis of covariance models. Pearson’s correlation was used to assess the association between plasma levels of amino acids and sex hormones, SHBG, and IGF-1. Age, BMI, and the phase of the menstrual cycle at the time of blood donation were used for adjustment. Given the 25 individual or grouped amino acids according to the metabolic pathways (presented in supplemental Fig. S1), we used a Bonferroni-corrected p value threshold of 0.002 (0.05/25) to account for the number of metabolites analyzed. We also calculated correlation coefficients of the ratios of each amino acid or grouped amino acids the sum of the 20 amino acids (total amino acids) with sex hormone, SHBG, and IGF-1 levels. All the statistical analyses were performed using SAS programs (SAS Institute Inc., Cary, NC, USA).
Results Characteristics of study subjects are shown in Table 1. They were aged 20–54 years and had BMI between 14.7 and 30.9 kg/m2. Most were parous (n = 270, 77.1 %) and \10 % reported being current or ex-smokers. Table 2 shows the means of plasma levels of hormones and amino acids according to the phase of the menstrual cycle. The plasma levels of Thr, Ser, Asn, Gln, Pro, Gly, Ala, Cit, Met, Tyr, Orn, and Lys varied during the subjects’ menstrual cycles, although their varied less compared with levels of total and free estradiol.
Plasma Arg level was significantly inversely correlated with total and free estradiol and IGF-1 levels after controlling for age, BMI, and phase of the menstrual cycle (Table 3). The geometric means of plasma Arg for the lowest to the highest quartiles, respectively, were the following: for total estradiol, 70.7, 62.5, 54.7, and 57.9 nmol/mL; free estradiol, 70.4, 61.7, 54.2, and 59.3 nmol/mL; and IGF-1, 68.8, 66.8, 63.4, and 62.8 nmol/mL. Plasma level of ureagenic amino acids was significantly positively correlated with total estradiol, and the geometric means of them for the lowest to the highest quartiles of total estradiol were 173.4, 159.7, 147.7, and 155.7 nmol/mL, respectively. Plasma levels of Tyr, Leu, and branched-chain amino acids (BCAA) were significantly positively correlated with free testosterone level. The geometric means of plasma Tyr, Leu, and BCAA for the lowest to the highest quartiles of free testosterone, respectively, were the following: Tyr, 53.9, 53.7, 56.2, and 59.1 nmol/mL; Leu, 99.7, 102.4, 102.1, and 108.9 nmol/mL; BCAA, 336.2, 342.3, 344.9, and 363.3 nmol/mL. Plasma levels of Ala, Met, Tyr, Lys, and ketogenic amino acids were significantly inversely correlated with SHBG level. Total testosterone and DHEAS were not significantly correlated with any amino acid level. Regarding ratios, plasma Arg was significantly correlated with total estradiol (r = -0.20, p = 0.0002), free estradiol (r = -0.20, p = 0.0002), and IGF-1 (r = -0.31, p \ 0.0001). The ratio of Tyr to the total amino acids was significantly positively correlated with IGF-1 level (r = 0.22, p = 0.0010). The ratio of Asp to the total amino acids was significantly positively correlated with SHBG level (r = 0.17, p = 0.0019, respectively). BMI was significantly positively correlated with Ala (r = 0.26, p \ 0.0001), Val (0.27, p \ 0.0001), Iso (0.21, p \ 0.0001), Leu (r = 0.19, p = 0.0003), Tyr (r = 0.20, p = 0.0002), ketogenic amino acids (r = 0.22, p \ 0.0001), and BCAA (r = 0.24, p \ 0.0001) and significantly inversely correlated with Cit (r = -022, p \ 0.0001). After excluding BMI from the covariates, plasma levels of Gly (r = 0.19), Val (r = 0.23), Ile (r = 0.19), Leu (r = 0.24), Tyr (r = 0.25), Phe (r = 0.17), and BCAA (r = 0.24) were significantly positively correlated with free testosterone. Plasma levels of Ala (r = -0.26), Val (r = -0.23), Met (r = -0.22), Leu (r = -0.22), Tyr (r = -0.26), Phe (r = -0.17), Lys (r = -0.23), glycogenic amino acids (r = -0.18), ketogenic amino acids (r = -0.26), and BCAA (r = -0.24) were significantly inversely correlated with SHBG. The results concerning the other relations were not altered substantially without adjustment for BMI. Adjustment for age at menarche, parity, age at first birth, and physical activity together with age, BMI, and the phase of menstrual cycle did not alter the results substantially. For example, the correlation coefficients for plasma Alg with total and free estradiol and IGF-1 were -0.20
123
146
Cancer Causes Control (2014) 25:143–149
Table 2 Age-adjusted geometric means of plasma amino acids and hormones by the phase of menstrual cycle at blood draw in premenopausal women Early follicular (n = 74)
Late follicular (n = 48)
Peri-ovulatory (n = 56)
Early luteal (n = 54)
Midluteal (n = 70)
Late luteal (n = 48)
p for homogeneity
Cycle phase-adjusted
Amino acids (nmol/mL) Ala
342.3
351.2
295.5
293.8
295.3
333.8
\0.0001
319.4
Ser Gly
138.2 264.0
135.1 237.3
117.9 204.6
115.7 202.8
118.0 205.1
128.4 220.7
\0.0001 \0.0001
126.4 225.0
Thr
144.3
142.1
115.8
104.4
96.5
120.7
\0.0001
120.8
Trp
51.4
54.1
53.9
52.4
51.7
52.0
0.15
52.4
Asn
47.0
46.6
41.8
40.0
39.4
43.6
\0.0001
43.2
Phe
54.0
53.6
53.6
53.8
54.8
55.9
0.51
54.3
Tyr
57.8
59.1
53.7
53.3
52.5
59.2
\0.0001
55.9
Ile
53.0
52.1
49.8
50.5
51.2
52.8
0.23
51.7
Met
24.4
23.6
20.9
20.9
20.6
23.1
\0.0001
22.4
Val
191.8
191.8
186.9
190.6
187.6
201.8
0.08
191.6
Gln
521.8
520.9
467.6
432.5
430.6
477.0
\0.0001
477.0
Arg
75.8
71.6
57.1
52.6
51.0
62.8
\0.000
62.1
His
77.4
81.0
76.6
77.7
77.9
80.9
0.01
78.4
Pro
130.0
131.1
118.6
111.8
111.8
126.6
0.0005
122.0
Leu
103.2
102.4
99.4
104.1
103.9
106.7
\0.0001
103.3
Lys Orn
177.7 77.3
179.2 78.1
160.5 66.8
153.8 60.6
146.5 62.8
163.1 68.3
\0.0001 \0.0001
163.9 69.3
Cit
29.2
28.1
26.3
24.5
23.8
25.2
\0.0001
26.3
Tau
147.7
137.8
140.8
148.1
150.1
150.9
0.33
146.2
Total
2,742
2,712
2,436
2,375
2,365
2,588
\0.0001
2,548
Total E2 (pg/mL)
62.9
101.9
144.1
138.4
131.2
80.4
\0.0001
100.3
Free E2 (pg/mL)
1.24
2.07
2.82
2.70
2.60
1.58
\0.0001
1.99
Total T (ng/dL)
23.8
23.7
30.8
27.9
26.9
24.8
0.04
26.0
Free T (ng/dL)
0.35
0.36
0.45
0.40
0.40
0.36
0.25
0.40
DHEAS (lg/dL)
121.1
117.6
125.3
124.7
132.2
122.4
0.68
124.0
SHBG (nmol/L)
62.4
58.3
61.8
65.5
61.3
61.8
0.98
61.8
IGF-1 (ng/mL)
179.4
193.0
210.2
216.7
204.8
199.0
0.005
198.0
Ala alanine, Ser serine, Gly glycine, Thr threonine, Trp tryptophan, Asn asparagine, Phe phenylalanine, Tyr tyrosine, Ile isoleucine, Met methionine, Val valine, Gln glutamine, Arg arginine, His histidine, Pro proline, Leu leucine, Lys lysine, Orn ornithine, Cit citrulline, Tau taurine, E2 estradiol, T testosterone, DHEAS dehydroepiandrosterone sulfate, SHBG sex-hormone-binding globulin, IGF-1 insulin-like growth factor-1
(p \ 0.001), -0.19 (p = 0.004), and -0.28 (p \ 0.0001), respectively, after controlling for all these covariates. Insulin resistance affects amino acid and protein metabolism [19]. Adjustment for insulin resistance together with age, BMI, and the phase of the menstrual cycle attenuated the correlation of the ratio of Asp to the total amino acids with SHBG level (r = 0.13, p = 0.03).
Discussion We observed that some amino acids were moderately but significantly associated with endogenous hormone or IGF-1 levels in premenopausal women. In recent years, metabolic profiling of blood plasma has been noted as a promising
123
approach in screening for cancers. To our knowledge, three studies reported the differences in amino acid profiles in plasma or urine between breast cancer patients and healthy controls [4, 6, 7]. Comparisons of the results from these studies with those from the present study would provide biological insights into the role of amino acids in the development of breast cancer. In these studies, differences between breast cancer cases and controls were observed for the levels of Trp, Thr, Ala, Gly, Pro, Ile, Leu, and Val (without replication of any particular amino acid among the three studies) [4, 6, 7]. None of these amino acids except Leu was associated with hormone or IGF-1 levels in our study. The level of Leu was lower in breast cancer patients in one of the three studies [6], whereas plasma Leu level in our study was significantly positively correlated with free testosterone levels.
Cancer Causes Control (2014) 25:143–149
147
Table 3 Partial correlation coefficientsa of plasma amino acids with sex hormones, SHBG, and IGF-1 in premenopausal women Total E2
Free E2
Total T
Free T
DHEAS
SHBG
IGF-1
Ala
-0.09
-0.04
0.04
Ser
-0.11
-0.11
-0.06
0.12
0.01
-0.17*
-0.03
-0.05
-0.06
-0.04
Gly
-0.15
-0.13
-0.05
-0.02
-0.16
-0.04
-0.08
-0.15
Thr
-0.09
-0.07
-0.02
Trp
0.03
0.06
0.08
0.13
-0.10
-0.06
-0.13
0.05
-0.12
Asn
-0.06
-0.07
0.07
0.04
0.05
-0.05
0.01
Phe
-0.05
-0.01
0.09
0.08
0.15
0.08
-0.15
Tyr
-0.06
0.05
-0.007
0.12
0.21**
0.05
-0.20**
Ile
0.10
-0.03
0.02
0.06
0.14
0.06
-0.15
0.002
0.003
Met
-0.08
-0.03
0.008
0.10
-0.03
-0.22**
-0.13
Var Gln
0.02 -0.12
-0.07 -0.11
0.08 0.13
0.16 0.12
-0.10 0.07
-0.14 -0.05
0.06 -0.07
Arg
-0.19**
-0.19*
-0.04
-0.02
-0.06
-0.09
-0.28**
His
-0.09
-0.08
-0.03
-0.004
-0.02
-0.02
0.06 -0.004
Pro
0.06
0.08
0.11
0.13
0.03
-0.06
Leu
-0.05
0.01
0.10
0.19**
0.14
-0.16
Lys
0.14
-0.09
0.02
0.04
-0.18*
-0.06
Orn
-0.05
-0.00
0.08
0.14
0.05
-0.16
-0.08
Cit
-0.09
-0.07
-0.06
-0.02
-0.04
-0.06
-0.09
Tau
-0.02
0.07
0.05
0.06
0.03
Glucogenicb
-0.14
-0.10
0.06
-0.12
Ketogenicc
-0.08
-0.02
0.06
BCAAd
-0.008
-0.14
0.09
Ureagenice
-0.18*
-0.14
0.0003
Total
-0.13
-0.09
0.14
0.07
0.09
0.04
-0.13
0.009
-0.15
-0.07
0.15
0.04
-0.19*
0.18*
0.11
-0.16
0.09
0.06
-0.03
-0.16
-0.26*
0.07
0.03
-0.16
-0.13
0.05
Ala alanine, Ser serine, Gly glycine, Thr threonine, Trp tryptophan, Asn asparagine, Phe phenylalanine, Tyr tyrosine, Ile isoleucine, Met methionine, Val valine, Gln glutamine, Arg arginine, His histidine, Pro proline, Leu leucine, Lys lysine, Orn ornithine, Cit citrulline, Tau taurine, E2 estradiol, T testosterone, DHEAS dehydroepiandrosterone sulfate, SHBG sex-hormone-binding globulin, IGF-1 insulin-like growth factor-1 * Statistically significance after Bonferroni correction p \ 0.0020 ** Statistically significance after Bonferroni correction p \ 0.0004 a
Adjusted for age, BMI, and the phase of the menstrual cycle
b
Sum of Ala, Ser, Gly, Thr, Trp, Asn, Phe, Tyr, Ile, Met, Val, Glu, Arg, His, and Pro Sum of Ile, Leu, Thr, Trp, Lys, Phe, and Tyr
c d
Sum of Ile, Leu, and Val
e
Sum of Arg, Orn, and Cit
Thus, changes in the plasma levels of these amino acids may be the consequence of the breast cancer and would not reflect the risk of breast cancer. One study compared urinary amino acids between ovarian cancer patients and controls and the levels of Leu, Ile, Ala, and Val were lower in the urine of cancer patients [6]. Studies measuring amino acids in prediagnostic plasma are desirable. Among amino acids, only total (not free) cysteine and total homocysteine was measured in some prospective studies [20–22]. No study has prospectively assessed the relationship between the risk of breast cancer and the amino acids given in the present study. We found that a high plasma level of Arg was significantly associated with decreased levels of total and free
estradiol and IGF-1. Arg methylation has been thought to have a regulatory role in estrogen actions [23]. Some studies reported that estrogen reduces asymmetric dimethylarginine (ADMA), an endogenously produced methylated form of Arg [24–26]. In response to estrogen, the catabolism and release of ADMA may be altered, which lead to the decreased circulating ADMA level. Verhoeven et al. [26] observed that ADMA as well as Arg levels in postmenopausal women decreased after intranasal or oral estradiol administration. In our study, total and free estradiol levels were significantly inversely correlated with Arg level, which may reflect their associations with ADMA level. Since IGF-1 and estrogen-mediated signaling
123
148
pathways are cross-linked [27], the inverse correlation may be also observed between Arg level and IGF-1 level. To our knowledge, no study has reported the relationship between plasma Arg and IGF-1 levels. It is likely that significant correlations of ureagenic amino acids with total estradiol and IGF-1 levels reflect those of Arg. We observed that Leu, Tyr, and BCAA levels were significantly correlated with the level of free testosterone. Testosterone has been thought to increase skeletal muscle protein synthesis [28], and Leu has the potential to regulate muscle protein synthesis [29]. Plasma Leu levels are controlled by the rate of use for the anabolic process of protein syntheses, their rate of catabolism, and the rate of protein turnover. The long-term anabolic effects of testosterone may be balanced with increased levels of plasma Leu. Since plasma Tyr levels have been reported to be correlated with plasma levels of Leu and other BCAA [30, 31], it is likely that Tyr showed also a positive correlation with the level of free testosterone. Leu and testosterone also have been associated with obesity and insulin resistance [31, 32]. There is a possibility that insulin or insulin resistance is an intermediate of the observed association between plasma Leu and free testosterone. However, adjustment for insulin resistance did not attenuate the observed associations. Plasma SHBG was significantly inversely correlated with concentrations of Ala, Met, Tyr, and ketogenic acids. Although BMI was included as a covariate, it is possible that these correlations still reflect the inverse association between nutritional status and SHBG. These amino acid levels were closely correlated with plasma total amino acids (r C 0.73); therefore, for the analysis concerning SHBG, it would be informative to give the relationships with individual amino acids in terms of the ratio to the total amino acid level, which may reflect nutritional status, rather than absolute value. We observed that the ratio of Asp to the total amino acid level was significantly positively correlated with SHBG. Interestingly, plasma Asp has been inversely associated with obesity and insulin resistance in some studies [30, 33, 34], and SHBG has been inversely associated with insulin resistance independent of body size [35]. In fact, the adjustment for insulin resistance attenuated the correlations of the ratio of Asp to the total amino acids to SHBG in the present study. Insulin resistance may have implications in the relationships of Asp to SHBG. Several limitations of this study should be noted. Blood samples were obtained at a single point in time without restriction to the day of the cycle, which may have caused large measurement errors for hormone levels and misclassifications of the cycle phase used for adjustments. However, studies with such a restriction regarding the day of a menstrual cycle have limited power. In recent years, some large studies have succeeded in detecting
123
Cancer Causes Control (2014) 25:143–149
associations between potential breast cancer risk factors and sex hormone levels using untimed blood samples [36– 38]. We also confirmed some of these associations in our dataset [17, 39]. A single assessment of amino acids may be subject to measurement error. However, Townsend et al. [40] evaluated the within-person reproducibility of 22 amino acids over 1–2 years and observed acceptable reproducibility (Spearman’s correlation or intraclass correlation coefficients C0.4) for all except His and Lys. All of the amino acids measured in this study were included in their study. Because of the cross-sectional design of the present study, we cannot determine whether sex hormones/ IGF-1 affect the amino acids or the amino acids affect these biomarkers. It is also possible that certain unknown factors may influence hormone and amino acid levels. Our data showed specific amino acids, rather than a large cluster of amino acids, were associated with endogenous sex hormone or IGF-1 levels. Nonetheless, the sample size is not sufficient to detect more associations. Although we partially considered the problem of multiple comparisons, we repeated procedures in analyses, which could have resulted in some associations occurring by chance. In conclusion, the present study showed that plasma levels of some specific amino acids, such as Arg, Leu, Tyr, and Asp, were associated with the endogenous sex hormone, SHBG, or IGF-1 level, established biomarkers of breast cancer risk. Whether these amino acids have implications in the etiology of breast cancer should be investigated in future studies. Acknowledgments This study was supported in part by Grants-inAid for Scientific Research on Innovative Areas (No. 221S0001) from the Japanese Ministry of Education, Culture, Sports, Science, and Technology. Conflict of interest of interest.
The authors declare that they have no conflict
References 1. Chadeau-Hyam M, Ebbels TM, Brown IJ et al (2010) Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification. J Proteome Res 9:4620–4627 2. Becker S, Kortz L, Helmschrodt C, Thiery J, Ceglarek U (2012) LC–MS-based metabolomics in the clinical laboratory. J Chromatogr B 883–884:68–75 3. Nakamura T, Takebe K, Rudoh K et al (1994) Increased plasma gluconeogenic and system A amino acids in patients with pancreatic diabetes due to chronic pancreatitis in comparison with primary diabetes. Tohoku J Exp Med 173:413–420 4. Chen Y, Zhang R, Song Y, He J et al (2009) RRLC–MS/MSbased metabonomics combined with in-depth analysis of metabolic correlation network: finding potential biomarkers for breast cancer. Analyst 134:2003–2011
Cancer Causes Control (2014) 25:143–149 5. Kamaura M, Nishijima K, Takahashi M, Ando T, Mizushima S, Tochikubo O (2010) Lifestyle modification in metabolic syndrome and associated changes in plasma amino acid profiles. Circ J 74:2434–2440 6. Slupsky CM, Steed H, Wells TH et al (2010) Urine metabolite analysis offers potential early diagnosis of ovarian and breast cancers. Clin Cancer Res 16:5835–5841 7. Miyagi Y, Higashiyama M, Gochi A et al (2011) Plasma free amino acid profiling of five types of cancer patients and its application for early detection. PLoS ONE 6:e24143 8. Wu G (2009) Amino acids: metabolism, functions, and nutrition. Amino Acids 37:1–17 9. Marshall S (2006) Role of insulin, adipocyte hormones, and nutrient-sensing pathways I regulating fuel metabolism and energy homeostasis: a nutritional perspective of diabetes, obesity, and cancer. Sci STKE 346:re7 10. Kaaks R, Berrino F, Key T et al (2005) Serum sex steroids in premenopausal women and breast cancer risk within the European Prospective Investigation into Cancer and Nutrition (EPIC). J Natl Cancer Inst 97:755–765 11. Fortner RT, Eliassen AH, Spiegelman D, Willett WC, Barbieri RL, Hankinson SE (2013) Premenopausal endogenous steroid hormones and breast cancer risk: results from the Nurses’ Health Study II. Breast Cancer Res 15:R19. doi:10.1186/bcr3394 12. The Endogenous Hormones and Breast Cancer Collaborative Group (2010) Insulin-like growth factor 1 (IGF1), IGF-binding protein 3 (IGFBP3), and breast cancer risk: reanalysis of 17 prospective studies. Lancet Oncol 11:530–542 13. Møller SE, Møller-Maach B, Olsen M, Fjalland B (1996) Effects of oral contraceptives on plasma neutral amino acids and cholesterol during a menstrual cycle. Eur J Clin Pharmacol 50:179–184 14. Ferrando AA, Tipton KD, Doyle D, Phillips SM, Cortiella J, Wolfe RR (1998) Testosterone injection stimulates net protein synthesis but not tissue amino acid transport. Am J Physiol 275:E864–E871 15. Hamadeh MJ, Devries MC, Tarnopolsky MA (2005) Estrogen supplementation reduces whole body leucine and carbohydrate oxidation and increases lipid oxidation in men during endurance exercise. J Clin Endocrinol Metab 90:3592–3599 16. Nagata C, Nakamura K, Oba S, Hayashi M, Takeda N, Yasuda K (2009) Association of intakes of fat, dietary fiber, soy isoflavone, and alcohol with uterine fibroids in Japanese women. Br J Nutr 101:1427–1431 17. Nagata C, Wada K, Nakamura K, Hayashi M, Takeda N, Yasuda K (2011) Associations of body size and reproductive factors with circulating levels of sex hormones and prolactin in premenopausal Japanese women. Cancer Cause Control 22:581–588 18. Sodergard R, Backstrom T, Shanbhag V, Carstensen H (1983) Calculation of free and bound fractions of testosterone and estradiol-17b to human plasma proteins at body temperature. J Steroid Biochem 16:801–810 19. Tessari P, Cecchet D, Cosma A et al (2011) Insulin resistance of amino acid and protein metabolism in type 2 diabetes. Clin Nutr 30:267–272 20. Zhang SM, Willett WC, Selhub J et al (2003) Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk of breast cancer. J Natl Cancer Inst 95:373–380 21. Lin J, Lee I-M, Song Y et al (2010) Plasma homocysteine and cysteine and risk of breast cancer in women. Cancer Res 70:2397–2405 22. Zhang SM, Willett WC, Selhub J, Manson JE, Colditz GA, Hankinson SE (2003) A prospective study of plasma total cysteine and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 12:1188–1193
149 23. Teyssier C, Le Romancer M, Sentis S, Jalaquier S, Corbo L, Cavaille´s V (2009) Protein arginine methylation in estrogen signaling and estrogen-related cancers. Trends Endocrinol Metab 21:181–189 24. Holden DP, Cartwright JE, Nussey SS, Whitley GSJ (2003) Estrogen stimulates dimethylarginine dimethylaminohydrolase activity and the metabolism of asymmetric dimethylarginine. Circulation 108:1575–1580 ¨ , Durmusoglu F, Yurdun T, Bilsel AS (2006) 25. C¸evik D, Unay O Plasma markers of NO synthase activity in women after ovarian hyperstimulation: influence of estradiol on ADMA. Vasc Med 11:7–12 26. Verhoeven MO, Hemelaar M, Teerlink T, Kenemans P, Van der Mooren MJ (2007) Effects of intranasal versus oral hormone therapy on asymmetric dimethylarginine in healthy postmenopausal women: a randomized study. Atherosclerosis 195:181–188 27. Hamelers IH, Van Schaik RF, Sussenbach JS, Steenbergh PH (2003) 17 beta-estradiol responsiveness of MCF-7 laboratory strains is dependent on an autocrine signal activating the IGF type I receptor. Cancer Cell Int 3:10 28. Urban RJ (2011) Growth hormone and testosterone: anabolic effects on muscle. Horm Res Paediatr 76(Suppl 1):81–83 29. Garlick PJ (2005) The role of leucine in the regulation of protein metabolism. J Nutr 135:1553S–1556S 30. Tai ES, Tan MLS, Stevens RD et al (2010) Insulin resistance is associated with a metabolic profile of altered protein metabolism in Chinese and Asian-Indian men. Diabetologia 53:757–767 31. Batch BC, Shah SH, Newgard CB et al (2013) Branched chain amino acids are novel biomarkers for discrimination of metabolic wellness. Metabolism. doi: 10.1016/j.metabol.2013.01.007 32. Kelly DM, Jones HT (2013) Testosterone: a metabolic hormone in health and disease. J Endocrinol 217:R25–R45 33. Cory JG, Cory AH (2006) Critical roles of glutamine as nitrogen donors in purine and pyrimidine nucleotide synthesis: asparaginase treatment in childhood acute lymphoblastic leukemia. In vivo 20:587–590 34. Stancˇa´kova´ A, Civelek M, Saleem NK et al (2012) Hyperglycemia and a common variant of GCKR are associated with the levels of eight amino acids in 9,369 Finnish men. Diabetes 61:1895–1902 35. Wallace IR, McKinley MC, Bell PM, Hunter SJ (2013) Sex hormone binding globulin and insulin resistance. Clin Endocrinol (Oxf) 78:321–329 36. Verkasalo PK, Thomas HV, Appleby PN, Davey GK, Key TJ (2011) Circulating levels of sex hormones and their relations to risk factors for breast cancer: a cross-sectional study in 1,092 preand postmenopausal women (United Kingdom). Cancer Causes Control 12:47–59 37. Bezemer ID, Rinaldi S, Dossus L et al (2005) C-peptide, IGF-I, sex-steroid hormones and adiposity: a cross-sectional study in healthy women within the European Prospective Investigation into Cancer and Nutrition (EPIC). Cancer Causes Control 16:561–572 38. Rinaldi S, Peeters PH, Bezemer ID et al (2006) Relationship of alcohol intake and sex steroid concentrations in blood in pre- and post-menopausal women: the European Prospective Investigation into Cancer and Nutrition. Cancer Causes Control 17:1033–1043 39. Tsuji M, Tamai Y, Wada K et al (2012) Associations of intakes of fat, dietary fiber, soy isoflavones, and alcohol with levels of sex hormones and prolactin in premenopausal Japanese women. Cancer Causes Control 23:683–689 40. Townsend MK, Clish CB, Kraft P et al (2013) Reproducibility of metabolomics profiles among men and women in 2 large cohort studies. Clin Chem. doi:10.1373/clinchem.2012.199133
123
