Hot flushes pose a significant public health concern for several reasons. They are the most common perimenopausal symptom reported by women in the United States and the primary reason that women seek medical care during the menopausal transition.1–3 Frequent and severe hot flushes can significantly affect a woman’s quality of life by causing acute physical discomfort and persistent sleep disturbances leading to fatigue, irritability, and forgetfulness.4,5 In addition, hot flushes may be associated with the development of serious medical conditions, such as depression.6,7
Despite the magnitude of this public health problem, little is known about the cause of hot flushes and the factors that influence their frequency, severity, and duration. Several investigators hypothesize that estrogens play a major role in the pathogenesis of hot flushes by direct or indirect action on the thermoregulatory set point located in the anterior portion of the hypothalamus.8–11 This hypothesis is supported by evidence from animal, epidemiologic, and clinical studies. Animal studies have demonstrated that estrogen alters the firing rate of hypothalamic neurons, stimulates warm and cold neurons in the preoptic area of the brain, and modulates both venous and arterial blood flow.12,13 Epidemiologic studies have shown that there is an inverse association between serum or plasma estrogen levels and hot flushes.14–18 Clinical studies indicate that estrogen therapy effectively ameliorates hot flushes in most women through a decrease in core body temperature.19
Because estrogen is thought to be a primary mediator of hot flushes, genetic polymorphisms that regulate its synthesis and degradation may influence the occurrence, severity, and frequency of hot flushes. To date, several studies have identified genetic polymorphisms in many of the cytochrome P450 (CYP450) enzymes that are involved in the estrogen biosynthesis pathway.20 For example, a specific polymorphism known as CYPc17α MspA1 has been identified in CYPc17α, a gene for the CYP450 enzyme that converts pregnenolone to androstenedione during the early steps of estrogen biosynthesis.20,21 The CYPc17α MspA1 polymorphism results from a single base pair change from T to C in the 5′-untranslated region. This polymorphism is of interest because it is thought to have functional significance due to the addition of a promoter sequence leading to increased expression of CYPc17α mRNA and thus, increased biosynthesis of estradiol (E2) and estrone.20
Studies have also identified polymorphisms in the CYP1B1 and CYP1A1 genes. These 2 genes encode CYP450 enzymes that hydroxylate E2 and estrone to catechol estrogens.20,22–24 The catechol estrogens are then either metabolized by catechol-O-methyltransferase to less active derivatives or oxidized to semiquinones and quinones that can form DNA depurinating adducts.20,25 Although the functional significance of polymorphisms in CYP1A1 and CYP1B1 genes has not been studied in detail, a few studies suggest that a single base pair substitution of leucine for valine at codon 432 of the CYP1B1 gene may increase the conversion of E2 and estrone to catechol estrogens as a result of the production of a variant protein.26–28 In 1 study, lower E2 levels were observed in women homozygous for this polymorphism when compared with women without the polymorphism.29
The goal of this study was to test the hypothesis that specific genetic polymorphisms of the CYPc17α, CYP1A1, and CYP1B1 genes are associated with hot flushes in midlife women. Because polymorphisms in the selected CYP450 enzymes may alter estrogen levels and studies indicate that estrogen levels may be associated with risk of hot flushes, another goal of this study was to test whether the associations between CYPc17α, CYP1A1, and CYP1B1 and hot flush risk can be explained by changes in E2 and estrone levels.
MATERIALS AND METHODS
The Midlife Health Study is a population-based study that was conducted between the years 2000–2004 among women 45 to 54 years of age residing in the Baltimore, Maryland, metropolitan region. Each study participant completed a questionnaire and provided a single blood sample that was stored at −20°C until hormone and genetic analyses. All women gave written informed consent according to procedures approved by the University of Maryland School of Medicine and Johns Hopkins School of Medicine Institutional Review Boards.
The names and addresses of potentially eligible women residing in the Baltimore metropolitan region were obtained from a commercial mailing house that had access to both the Department of Motor Vehicles and Voter Registration lists. In a random order, recruitment letters were mailed to women on the list until recruitment goals were met. Women with and without hot flushes were recruited from the same target population of women.
Women who received the mailings were invited to call the clinic to obtain more information about the study. The study was presented to women as a general study on midlife health, rather than as a study of hot flushes.
Eligibility of the potential participant was determined at the time of the initial call. To be eligible, potential participants had to be between 45 and 54 years of age, have intact ovaries and a uterus, and have had at least 3 menstrual periods in the 12 months before participation. In addition, they had to agree to donate a single sample of approximately 20 mL of blood and complete a questionnaire. Women were ineligible if they were pregnant, currently taking hormone therapy or hormonal contraception, or had a history of cancer of the reproductive organs, because these factors are known to alter endogenous hormone levels and could therefore affect interpretation of the results. Subsequent to their clinic visit, hot flush status was assigned based on the participant’s answer to the question “Have you ever had hot flushes?” Participants who answered “yes” to this question were classified as “women with hot flushes” and those who answered “no” were classified as “women without hot flushes.”
Women were asked to complete a detailed hot flush history. Information was collected on the following: whether the woman had ever experienced hot flushes, whether the woman had a hot flush in the last 30 days, the number of hot flushes experienced within the last 30 days, the severity and frequency of hot flushes, and the length of time each woman experienced hot flushes.
In addition, questions were asked regarding demographic information, reproductive history, hormone therapy use, hormonal contraceptive use, menopausal symptoms, medical and family history, and health behaviors (smoking, alcohol use, vitamin use, and eating habits) (Table 1). Many of the questions that were used were taken from previously validated questionnaires.30–31 However, the hot flush questions were expanded to capture more detail about hot flush severity, frequency, and duration. All questionnaires were pretested before use.
At the completion of the study, 363 women with hot flushes and 259 women without hot flushes were enrolled. For this analysis, 9 women with hot flushes and 1 woman without hot flushes were excluded due to missing information on the date of their last menstrual period.
Genomic DNA was isolated from whole blood using the GenElute Blood Genomic DNA kit (Sigma, St. Louis, MO). Detection of the CYPc17α MspA1 polymorphism was carried out using published methods.32–34 Detection of the CYP1B1 polymorphism was carried out as previously described.35–38 Detection of the CYP1A1 polymorphism was carried out as described by Taioli et al.23 In all genotyping assays, laboratory personnel were blinded to hot flush status, and the polymorphic status of each sample was determined by at least 2 independent investigators. In approximately 98% of the readings, there was complete agreement between the 2 independent investigators. In the rare instances of lack of agreement, the samples were rerun until agreement was reached between the investigators. Each gel contained samples from women with hot flushes and women without hot flushes as well as samples without DNA (negative controls) and samples with known polymorphisms (positive controls).
Serum concentrations of E2 and estrone were measured using enzyme-linked immunosorbent assays. The details of these assays have been previously published (Gallicchio L, Miller SR, Visvanathan K, Lewis LM, Babus J, Zacur H, et al. Cigarette smoking, estrogen levels, and hot flashes in midlife women. Maturitas, in press).39 All samples were run in duplicate in the same laboratory by a single technician who was blinded to hot flush status. Samples from women with and without hot flushes were run in the same assays. The mean values for each participant were used in the analyses.
Sample size and power calculations indicated that a sample size of 181 women with hot flushes and 181 without hot flushes would result in 80% power at an alpha of 0.05 to detect a 2-fold difference in the risk of hot flushes in midlife women. This calculation was based on published literature at the time reporting a prevalence of between 10% and 20% of the selected CYP450 polymorphisms among women without hot flushes.22,33–35 Assuming means and variances in both E2 and estrone levels from published data,14 50 women with hot flushes and 50 without would result in 80% power at an alpha of 0.05 to detect a 12 pg/mL difference in mean E2 levels and a 5 pg/mL difference in mean estrone levels between the 2 groups.
Analyses were conducted to assess the distribution of various covariates between women with hot flushes and women without hot flushes. Wilcoxon rank sum tests or χ2 tests were used to assess statistical significance of continuous and categorical variables, respectively. The CYPc17α, CYP1B1, and CYP1A1 polymorphisms were categorized as wild type (+/+), heterozygous (+/–), or homozygous (–/–). The +/+ group served as the reference group for the homozygous or heterozygous variants. The analyses were completed treating each group separately as well as combining the homozygous and heterozygous variants. Risk ratios and 95% confidence intervals were calculated using modified Poisson models40 to assess the association between specific CYP450 polymorphisms and the occurrence, frequency, duration, and severity of hot flushes. Categories for the outcome variables (occurrence, frequency, duration, and severity of hot flushes) were created based on distributions among participants and clinical relevance. Levels of E2 and estrone were log-transformed because neither hormone was normally distributed. Normality was assessed by examining the distribution of hormone levels among women with and without hot flushes. Geometric means of hormone levels were compared among groups defined by hot flush status, severity, frequency, and duration using generalized linear models.41
The following factors were considered as possible confounders for all the models described above: body mass index (BMI), current smoking, current alcohol use, time since last menstrual period, age, race, and prior hormone therapy or oral contraceptive use. Body mass index was calculated using information on measured weight and height. Women were categorized as having a BMI of less than 24.9 kg/m2, 25.0 to 29.9 kg/m2, 30.0 to 34.9 kg/m2, and more than 35.0 kg/m2. Smoking status was categorized as “ever smoker” or “never smoker.” Current alcohol use was examined as a yes or no variable. Potential confounders were added to the final models if they were significantly associated (P < .1) with CYP450 polymorphisms, estrogen levels, or hot flush status or if they were considered to be confounders of the association between estrogen and hot flushes in the published literature. The final regression models used to evaluate the association between the CYP450 polymorphisms and various hot flush characteristics (Table 2) did not include any confounders. The final generalized linear models assessing the association between plasma E2 and estrone levels and hot flush characteristics (Table 3) were adjusted for age, days since last period, smoking, and BMI.
Differences in the association between E2 and estrone and hot flushes were also evaluated in both premenopausal and postmenopausal women adjusting for time since last menstrual period to account for potential differences in menstrual cycle variability. Perimenopausal women were those who reported experiencing 1) their last menstrual period within the past year, but not within the past 3 months or 2) their last menstrual period within the past 3 months and experiencing 10 or fewer periods within the past year. Premenopausal women were defined as women who reported experiencing their last menstrual period within the past 3 months and experiencing 11 or more periods within the past year. There were no differences in the results obtained by menopausal status, so only the combined results are presented in the results section.
To examine dose–response relationships, a trend test was performed across all levels of exposure by treating ordinal or categorical variables as continuous variables in a logistic regression model.42 A P value of less than .05 was considered to be statistically significant. All analyses were performed using SAS 8.2 (SAS Institute Inc., Cary, NC).
Characteristics of the women with hot flushes and women without hot flushes are presented in Table 1. Women with hot flushes were more likely to be older, current or former smokers, never or former drinkers, and to have a high BMI compared with women without hot flushes. Further, women with hot flushes were more likely to be African American compared with women without hot flushes.
The allele frequencies of the CYPc17α, CYP1B1, and CYP1A1 (–) allele variants among women without hot flushes were 38.6%, 52.1%, and 12.2%, respectively. In the women without hot flushes, all 3 polymorphisms were in Hardy-Weinberg equilibrium, indicating that there was a stable frequency distribution of genotypes in the population of women without hot flushes.
Associations between the CYPc17α, CYP1A1, and CYP1B1 genotypes and hot flushes are shown in Table 2. Women homozygous or heterozygous for the CYP1B1 polymorphism were 16% more likely to report having hot flushes than women without the CYP1B1 polymorphism (risk ratio [RR] 1.16, 95% confidence interval [CI] 0.98–1.37). This result was of borderline statistical significance. Women with the CYP1B1 polymorphism were at a statistically significant greater risk of reporting moderate to severe hot flushes (RR 1.33, 95% CI 1.03–1.70) and hot flushes that persisted for a year or more (RR 1.28, 95% CI 1.00–1.63) compared with women without the CYP1B1 polymorphism. The association between CYP1B1 and hot flushes that occurred at least weekly was of borderline statistical significance (RR 1.32, 95% CI 0.99–1.77).
The association between the selected polymorphism in CYP1A1 and the risk of hot flushes was not statistically significant (RR 1.03, 95% CI 0.88–1.21). Similarly, the risks of reporting hot flushes that were moderate to severe (RR 1.15, 95% CI 0.94–1.42), that occurred at least weekly (RR 1.11, 95% CI 0.86–1.44), or that lasted a year or more (RR 1.05, 95% CI 0.84–1.31) were also not statistically significant in women with the selected CYP1A1 polymorphism.
No significant association was observed between the CYPc17α polymorphism and the occurrence of hot flushes (RR 0.99, 95% CI 0.86–1.14). In addition, there were no significant associations between the CYPc17α polymorphism and the severity of hot flushes (RR 0.96, 95% CI 0.79–1.17), frequency of hot flushes (RR 1.01, 95% CI 0.79–1.28), or occurrence of hot flushes for a year or more (RR 1.02, 95% CI 0.84–1.25).
The combined effect of CYP1B1 and CYP1A1 genotypes resulted in a significant incremental risk of at least weekly hot flushes, moderate to severe hot flushes, and hot flushes that persisted for at least a year related to the number of allelic variants that were present (Table 2). For all genotype analyses, no significant differences were observed when stratified by menopausal status, so only the combined results are presented here.
Smoking and BMI greater than or equal to 35 kg/m2 were significantly associated with hot flushes in this study population (Gallicchio et al, in press) (Table 1).39 Thus, further exploratory analyses were performed to examine the interactions between the CYP450 genotypes, smoking, and BMI with regard to hot flush outcomes. No significant interactions were observed (data not shown).
Table 3 compares the mean levels of E2 and estrone in women with hot flushes and women without hot flushes after adjustment for potential confounders (ie, age, days since last period, smoking status, and BMI). Women who experienced hot flushes within the last 30 days had significantly lower levels of both E2 and estrone compared with women who either had never experienced hot flushes or who had experienced hot flushes before the last 30 days. In addition, women who experienced moderate to severe hot flushes had significantly lower E2 and estrone levels compared with women who never had a hot flush or who reported mild hot flushes. Women reporting daily to weekly hot flushes also had significantly lower levels of E2 and estrone compared with women who experienced monthly hot flushes or who never had hot flushes. Women who experienced hot flushes for less than a year were more likely to have lower levels of E2 and estrone than women reporting hot flushes for a year or more or those who never had hot flushes. There were no differences by menopausal status, so the combined results are presented here.
The mediating effect of E2 on the association between the CYPc17α, CYP1B1, and CYP1A1 polymorphisms and hot flushes is presented in Table 4. There was little difference in the point estimates of any hot flushes, moderate to severe hot flushes, at least weekly hot flushes, and hot flushes that persisted for a year or more when compared with the unadjusted results shown in Table 2. Adjusting for age, days since last period, smoking status, and BMI did not significantly alter the point estimate, and therefore, only data adjusted for E2 alone are shown. Similar results were observed when controlling for estrone (data not shown).
The results of this study suggest that a specific polymorphism in the CYP1B1 gene (ie, a polymorphism that involves a single base pair substitution of leucine for valine at codon 432), but not selected polymorphisms in CYP1A1 and CYPc17α, was significantly associated with increased risk of reporting severe and persistent hot flushes, independent of E2 and estrone levels.
The reason for the association between the selected CYP1B1 polymorphism and hot flushes is unknown. The CYP1B1 gene encodes the CYP1B1 enzyme, which metabolizes E2 and estrone to catechol estrogens, such as 4-hydroxy E2 and 4-hydroxy estrone. Polymorphisms in the CYP1B1 gene have been shown to cause a 2- to 3-fold increase in the catalytic activity of the CYP1B1 enzyme.26–28 Thus, it is biologically possible that polymorphisms in CYP1B1 increase the degradation of E2 and estrone to catechol estrogens. In turn, the increased degradation of E2 and estrone could result in low levels of active estrogens, a scenario that is associated with an increased risk of hot flushes. Our analysis, however, did not support this hypothesis, because controlling for E2 and estrone did not significantly alter the point estimate for the association between the CYP1B1 polymorphism and hot flushes. An alternative explanation for the association between CYP1B1 and hot flushes may be that the CYP1B1 polymorphism increases production of catechol estrogens. In turn, the high levels of catechol estrogens could act directly on the hypothalamus to trigger neurons in the hypothalamus to cause vasodilation and thus, elicit hot flushes.43,44 In this study, we were unable to measure the levels of catechol estrogens because current high-pressure liquid chromatography and enzyme-linked immunosorbent assay techniques are not sensitive enough to detect them in serum, and we did not collect urine samples from participants.
Initially, we were surprised that the selected CYPc17α MspA1 polymorphism was not associated with an increased risk of reporting hot flushes. Because the selected polymorphism has been shown to increase promoter activity in vitro,20 we hypothesized that women with the selected polymorphism would produce more E2 or estrone and, in turn, be less likely to develop hot flushes than women without the polymorphism. Our data do not support this hypothesis, but there are a number of potential explanations for the lack of an observed association between this polymorphism and hot flushes. First, the CYPc17α MspA1 polymorphism may not result in an increase in catalytic activity or estrogen production in healthy midlife women. This possibility is supported by data from this study and other epidemiologic studies that have reported no association between the CYPc17α polymorphism and E2 levels in postmenopausal women.45–47 Second, it is possible that several polymorphisms in CYP450 enzymes need to be present to alter estrogen levels. Third, it is possible that polymorphisms in other genes in the estrogen pathway may be more important determinants of E2 and estrone levels than polymorphisms in CYPc17α. In fact, several recent case–control studies indicate that polymorphisms in the CYP19 gene are important modulators of E2 levels in healthy postmenopausal women.45–47
The lack of statistical significance observed between the CYP1A1 polymorphism and hot flushes may be due in part to sample size limitations. Based on the prevalence of the CYP1A1 genotype in our controls (0.21), we had 80% power to detect a risk ratio of 1.48 at an alpha of 0.05 (2-tailed) between the 2 groups. Alternatively, it is possible that the selected polymorphism in the CYP1A1 gene may not be associated with an increased risk of hot flushes.
Although the current study did not find that any of the selected polymorphisms were associated with E2 and estrone levels, it did find a strong dose–response relation between E2 and estrone and hot flushes. This finding is consistent with the results from several cross-sectional or small case–control studies.14–16 The current study expands on this existing literature by providing detailed information on the association between E2 and estrone levels and the severity, frequency, and persistence of hot flushes in a large population-based study.
In interpreting the results of this study, it is important to consider its strengths and limitations. A major strength of this work is that the study was specifically designed to examine hot flushes in midlife women. Thus, a very detailed hot flush history was obtained from each participant. Another strength is that this study is a novel examination of hot flushes and their association with selected genetic polymorphisms and hormone levels. Another strength involves the steps taken to minimize misclassification of hot flush status as part of the study design. By presenting the study as research into factors related to midlife and not specifically as a study on hot flushes, women who participated in the study may have been less likely to over report hot flushes. The chance of differential misclassification was further minimized by the design of the study, because hot flush status was designated after the clinic visit based on the questionnaire information provided by each participant.
Limitations of the study include those related to study design and sample size. The design of this study does not enable us to determine the temporality of the association between low estrogen levels and the occurrence of hot flushes or the prevalence of hot flushes in the population. We were also limited by having only 1 measurement of E2 or estrone level from the women, given the fluctuation that can occur based on the time of day, the day of her menstrual cycle, body weight, and diet. In an attempt to minimize some of this variability, women were asked to fast before blood collection, all samples were collected in the morning between 8 and 10 am, and in the analysis we adjusted for BMI and time since the beginning of last menstrual period. We elected to perform a cross-sectional analysis because a prospective design requires more resources and effort on the part of the study participants than the cross-sectional design. Although we had adequate sample size to examine the main effects, a larger sample size would have allowed us to explore adequately the gene–gene interactions and gene–environment interactions.
In this study, women had a 30% increased risk of reporting moderate to severe hot flushes and a 28% increase in the risk of reporting persistent hot flushes if they were carriers of the CYP1B1 (Val432Leu) polymorphism. The magnitude of the risk is similar to what has been observed with smoking40 and elevated BMI.43 The associations between the CYP1B1 polymorphism and increased risk of any hot flushes and frequent hot flushes were of borderline significance. These novel results suggest that certain genetic polymorphisms such as those in CYP1B1 may be predictors of subsequent susceptibility to hot flushes in midlife women. This is a new line of investigation with respect to hot flushes that could have future clinical implications. Prospective studies are required to confirm our findings and mechanistic studies are required to understand the functional significance of the CYP1B1 polymorphism.
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