Skip Navigation


Carcinogenesis Advance Access originally published online on December 6, 2005
Carcinogenesis 2006 27(4):758-765; doi:10.1093/carcin/bgi294
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
27/4/758    most recent
bgi294v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (16)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Cleveland, R. J.
Right arrow Articles by Conway, K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cleveland, R. J.
Right arrow Articles by Conway, K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

IGF1 CA repeat polymorphisms, lifestyle factors and breast cancer risk in the Long Island Breast Cancer Study Project

Rebecca J. Cleveland 1, *, Marilie D. Gammon 1, Sharon N. Edmiston 2, Susan L. Teitelbaum 6, Julie A. Britton 6, Mary Beth Terry 3, Sybil M. Eng 7, Alfred I. Neugut 3, 5, Regina M. Santella 4 and Kathleen Conway 1, 2

1 Department of Epidemiology, School of Public Health and 2 Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, NC, USA, 3 Department of Epidemiology and 4 Department of Environmental Health Sciences, Mailman School of Public Health and 5 Department of Medicine, College of Physicians and Surgeons, Columbia University, New York, NY, 6 Department of Community and Preventive Medicine, Mt Sinai School of Medicine, New York, NY and 7 Pfizer, Inc., Global Epidemiology, Safety, and Risk Management, New York, NY

* To whom correspondence should be addressed at: Department of Epidemiology, University of North Carolina, CB# 7435 McGavran-Greenberg Hall, Chapel Hill, NC 27599-7435. Tel: +919 966 7410; Fax: +919 966 2089; Email: becki{at}unc.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Insulin-like growth factor I (IGF-I) is an important regulator of growth and differentiation and is a potent mitogen for human breast cancer cells. Recent investigations suggest an association between cytosine–adenine dinucleotide (CA)n repeat polymorphisms of the IGF1 gene and IGF-I levels and further evidence indicates that genotype may influence breast cancer risk. We assessed the relation between IGF1 (CA)n repeats and breast cancer, and evaluated modification of genotype effects according to traditional breast cancer risk factors in 1028 breast cancer cases and 1086 controls. An increased risk of breast cancer was seen for genotypes that included alleles with fewer than (CA)19 repeats when compared to (CA)19 repeat carriers, an association that was particularly strong among premenopausal women [odds ratio (OR) = 3.31; 95% confidence interval (CI) = 1.47, 7.48]. No significant association was observed between an IGF1 genotype with no (CA)19 repeat compared to (CA)19 repeat genotypes in either pre- or postmenopausal women overall. However, when traditional breast cancer risk factors were considered, premenopausal women with genotypes that lacked a (CA)19 repeat had a nearly 60% increased risk of breast cancer among those who had ever used hormonal birth control, while never users had a significantly reduced risk (Pinteraction = 0.01). Among postmenopausal women, those with genotypes lacking a (CA)19 repeat allele had significantly increased breast cancer risk among subjects with a lower than median body mass index (BMI) (OR = 1.77 95% CI = 1.09, 2.87), while no association for IGF1 genotype was seen among women with a higher than median BMI (Pinteraction = 0.04). Our results demonstrate a role for alleles with fewer than (CA)19 repeats as a risk factor for breast cancer and also suggest that several traditional breast cancer risk factors modify the association of the IGF1 (CA)19 repeat genotype.

Abbreviations: BMI, body mass index; CA, cytosine-adenine repeat; CI, confidence interval; HBC = hormonal birth control; IGF-I, insulin-like growth factor I; LIBCSP = Long Island Breast Cancer Study Project; OR = odds ratio


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Insulin-like growth factor I (IGF-I) is a member of the larger family of insulin-related peptides, which includes insulin and IGF-II, and is one of the most well-characterized growth factors (1,2). IGF-I is an important regulator of cellular growth, differentiation and apoptosis and works in conjunction with growth hormone (GH), insulin and sex steroids (3). GH is the main regulator of IGF-I and the liver is the major source of circulating IGFs, however, there is evidence that IGFs are produced by many tissues, including breast tissue. The actions of IGFs are mediated through the IGF-I receptor (IGF-IR) which is expressed in almost all human cells (4). The bioavailability of IGF-I is regulated not only by the circulating levels of IGF-I, but also by the circulating concentrations and tissue production of six IGF-binding proteins (IGFBP) (5). IGF-I is a potent mitogen and there is increasing biological evidence that IGF-I plays an important role in several cancers including breast, colon and prostate (6–8).

IGF-I levels can vary substantially among individuals and have been shown to be regulated in part by diet, lifestyle and anthropometric indices (9–11). Nutrition and energy balance have an important influence on IGF-I levels which are decreased in energy-restricted diets and transiently increased with intense physical activity (12,13). However, the relationship between body mass index (BMI) and IGF-I has been less consistent and may be due in part to a non-linear association, with one report indicating the highest IGF-I levels occurring in subjects with a BMI between 24 and 26 (11). Orally taken exogenous estrogen has been shown to decrease circulating IGF-I levels, possibly due to suppressed IGF1 gene expression in the liver (9). Although estrogen has also been shown to interact with IGF-I to increase cell proliferation at the tissue level, particularly that of the breast (14), evidence which is supported by results from several epidemiologic studies which have shown positive associations for breast cancer and circulating IGF-I levels, particularly among premenopausal women (7,15,16).

Despite the number of factors that can influence IGF-I levels, it has been estimated that up to 60% of the variability has a genetic basis (17,18). A dinucleotide cytosine–adenine (CA) repeat in the IGF1 gene has been the focus of many recent studies because of its proximity to the promoter, 1kb upstream from the transcription start site (19). The CA repeat is one of the most common forms among the naturally occurring repetitive DNA sequences and studies of other genes have suggested that number of CA repeats in the promoter region is inversely correlated with transcription activity (20,21). Results from a recent cohort study of women may support this hypothesis, reporting a non-significant trend of decreasing IGF-I levels with increasing number of repeats (22).

The examination of genetic markers that influence expression of IGF1 may be a better measurement of lifetime exposure to IGF-I than measuring circulating levels which may be affected by environmental exposures or disease status in case–control studies. Two recent studies have found an association between the number of IGF1 CA repeats and breast cancer risk (23,24), while others have not (22,25). We compared IGF1 genotypes in breast cancer cases and controls to investigate the hypothesis that the number IGF1 CA repeats is associated with breast cancer and evaluate whether other breast cancer risk factors modify the association with IGF1 genotype in the population-based Long Island Breast Cancer Study Project (LIBCSP).


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Study population
Data were collected from participants in the LIBCSP, a population-based case–control study of English-speaking residents of Nassau and Suffolk counties of Long Island, NY (26). Case participants of the study were women with newly diagnosed in situ or invasive breast cancer from August 1, 1996, through July 31, 1997. Cases were identified using a rapid reporting system established by the study investigators specifically for the LIBCSP and were confirmed by the physician and medical records. Controls were women who were residents of the same two counties, frequency matched by 5-year age group to the expected age distribution of cases. Potentially eligible control women were identified by Waksberg's method of random digit dialing (RDD) (27) for those under 65 years of age, and by Health Care Finance Administration (HCFA) rosters for those of 65 years of age and older. The main questionnaire was completed by 1508 cases and 1555 controls, with an overall response rate of 82.1 and 62.7%, respectively.

The main questionnaire was administered in-home by a trained interviewer and took ~2 h to complete. Reproductive and lifestyle information obtained from the main questionnaire includes pregnancy history, menstrual history, lifetime use of exogenous hormones, family history of cancer, body size changes, lifetime physical activity, smoking history, lifetime alcohol use and demographic characteristics. After completing the interview and an additional informed consent form, participants were asked to donate blood samples. From each participant, about 40 cc of blood was obtained (5 EDTA-treated lavender-top tubes). Of the 1102 (73.1%) blood samples collected from case women with a completed main interview, 32% were collected prior to the commencement of any major therapy (no mastectomy, no chemotherapy, no hormones, no radiation) and 77.2% were collected prior to the commencement of chemotherapy. The number of control women with a completed interview who donated a blood sample was 1141 (73.3%). Overall, there were 1038 cases and 1092 controls with available DNA for analysis.

Descriptive characteristics for the entire LIBCSP study have been published previously (26). As reported, an increase in breast cancer among women on Long Island was found to be associated with lower parity, late age at first birth, little or no breastfeeding, a family history of breast cancer, and increasing income and education. However, those providing a blood sample differed from those who did not. White/other race versus black, ever alcohol users, ever hormonal replacement users, those who breast fed ≥6 months and subjects who ever had a mammogram were more likely to provide a blood sample, while smokers and older subjects were less likely to provide a blood sample (26). Reassuringly, risk factors that were found to be associated with breast cancer in the entire study population (19), were also observed in the subset of women who donated blood or for whom DNA was available (data not shown). This study included only women for whom menopausal status was able to be determined (96.7% of all subjects with available DNA), of which 34% were premenopausal [mean age = 44.6; standard deviation (SD) = 6.7] and 66% postmenopausal (mean age = 64.3; SD = 9.5). Ninety-three percent of the study participants were Caucasian.

Genetic analyses
Mononuclear cells were separated by Ficoll (Sigma Chemical Co., St Louis, MO) and washed twice with PBS. Pelleted cells were frozen at –80°C until DNA was isolated by standard phenol and chloroform–isoamyl alcohol extraction and RNase treatment.

Genotyping of the IGF1 gene CA repeats, located 1 kb upstream from the transcription start site, was carried out using previously described methods (19). PCR were carried out in 50 µl volumes with 7.5 ng of genomic DNA using 125 nM of each primer (forward, 5'-GCTAGCCAGCTGGTGTTATT-3' and reverse, 5'-ACCACTCTGGGAGAAGGGTA-3'), 100 µM dNTPs, 1.5 mM MgCl2, and 2.5 U of AmpliTaq Gold polymerase (ABI Applied Biosystems) and the manufacturer's standard buffer. Samples were processed through one cycle of 5 min at 95°C, 30 temperature cycles consisting of 1 min at 94°C (denaturation), 1 min at 64°C (annealing) and 1 min at 72°C (elongation), with the last elongation step lengthened to 10 min. The forward primer was 5'-labeled with HEX fluorescent dye for automated fragment analysis (ABI Applied Biosystems). The PCR amplified products were purified over QIAquick PCR purification columns (Qiagen), and mixed with loading buffer (80% formamide, 5 mM EDTA, 50 µg/µL Blue Dextran) and ROX GeneScan-350 size standard (ABI). After denaturing for 5 min at 95°C, the products were analyzed on 6% polyacrylamide Long Ranger gels in the ABI-377 automated sequencer. GeneScan Analyses 3.1 software (ABI Applied Biosystems) was used to automatically collect and measure the fluorescent products, size and intensity. The amplified fragments ranged in size from 176 to 200 bp, depending on the number of CA repeats within the amplified region.

Representative homozygotes for the (CA)19, (CA)20 and (CA)21 genotypes were sequenced to validate the number of CA repeats. For quality control purposes, laboratory procedures were completed with personnel blinded to case–control status. Positive and negative controls were included in every experiment and results were reviewed routinely by a second reviewer to permit early detection of inconsistent results. In addition, 214 blinded duplicates (10.1%) were repeated to validate procedures used to identify genotype. Concordance for the blinded duplicate samples was 100%. All genotype data results were read and entered twice to check for inconsistencies. There were 10 cases and 6 controls with failed genotype assays resulting in 1028 cases and 1086 controls available for the statistical analyses.

Statistical analyses
We used {chi}2 tests to determine if IGF1 genotypes were in Hardy–Weinberg equilibrium. Genotypes for this study were coded in a variety of ways based on results from previous studies of IGF1 genotype and breast cancer (22–25) and those based on a possible inverse association with transcriptional activity found for CA repeats in the promoter region of other genes, although these gene expression studies for IGF1 have not yet been carried out. Genotypes investigated in other studies have generally been based on combinations with or without the (CA)19 repeat allele. In this study, the IGF1 polymorphism was coded in five ways to provide comparability to other studies and to reflect proposed transcriptional activity dependent on allele length, with the (CA)19 repeat homozygotes or heterozygotes as the referent genotype in most cases (see Table II for comparisons): (1) heterozygotes of the (CA)19 repeat as one group and those with no (CA)19 repeat as another compared to a (CA)19 homozygous referent; (2) as reported in most analyses, having no (CA)19 repeat was compared to those who had at least one (CA)19 repeat; (3) having at least one allele with fewer than (CA)19 repeats and the second allele being any size but (CA)19 compared to those who carried at least one (CA)19 repeat; (4) having at least one allele with greater than (CA)19 repeats and the second allele being any size but (CA)19 compared to those who carried at least one (CA)19 repeat; and (5) total number of repeats on both alleles with cutoffs at <38 total (CA) repeats compared to ≥38 total (CA) repeats.

Odds ratios (ORs) and 95% confidence intervals (CI) were calculated using unconditional logistic regression models (28) using the statistical software package SAS version 8.1 (SAS Institute, Inc., Cary, NC). Logistic regression models were adjusted for the frequency-matching variable age (categorized into 5-year age-groups) and potential confounding variables family history of breast cancer (first degree/no first degree); reproductive factors such as age at menarche (<12 years; 12 years; 13 years; 14+ years), parity status (nulliparous; 1 child; 2 children; 3 children; 4+ children), age at first birth among parous (<22 years; 22–24 years; 25–27 years; 28+ years), and lactation history among parous (never lactated; <2 months; 2–5 months; 6–13 months; 14+ months); BMI (kilograms/meters2) (<18.5; 18.5 to <25; 25 to <30; ≥30) at reference (defined as date of diagnosis for cases and date of identification for controls). Confounders remained in the final models if their inclusion changed the estimate of exposure by >10%. Case–control analyses were conducted by menopausal status. Menopausal status was determined using information provided by the subject about the date of her last menstrual period, prior surgical information on hysterectomy and oophorectomies, cigarette smoking status and use of hormone replacement (26). Postmenopausal status was defined as having a last menstrual period more than 6 months before the reference date or if she had both her ovaries removed before the reference date. For women with unknown menopausal status, women were categorized as postmenopausal based on the 90th percentile for age at menopause in the control population, calculated according to smoking status. A woman was categorized as postmenopausal if her age at reference was ≥54.8 years of age if she was a smoker, and ≥55.4 years if she was a non-smoker. Subjects for whom menopausal status was unable to be determined was 3.2% and were excluded from analyses specific to menopausal status.

Interaction of IGF1 genotypes with known and suspected breast cancer risk factors was evaluated by adding cross-product terms to the logistic regression models and were evaluated using the likelihood ratio test (LRT). Multiplicative interaction was assessed using the LRT by comparing models including the cross-product term to a model containing only the main effects. Effect modification analyses were conducted according to menopausal status. Covariates a priori considered as potential effect modifiers because of their potential link to the IGF pathway (11,29–32), included hormonal birth control (HBC) (ever use of birth control pills, shots or implants versus never), hormone replacement use (HRT) (ever use of estrogen or progestin containing pill, shot or skin patch versus never), BMI at reference (≥ median versus < median), lifetime physical activity levels (≥3 h/week versus <3 h/week), lifetime alcohol use defined as at least one drink a month for 6 months or more (ever versus never), and active cigarette smoking defined as at least one cigarette a day for 6 months or longer (ever versus never). Interaction on the additive scale was evaluated by examining the excess breast cancer risk for the gene-environment interaction by estimating the interaction contrast ratio (ICR) (33). For ease of presentation, IGF1 gene interaction results are shown as stratified models.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Genotype frequencies were in Hardy–Weinberg equilibrium for both pre- and postmenopausal women (P > 0.05).

The distribution of IGF1 alleles is shown in Table I. Alleles ranged in size from (CA)11 to (CA)23. Approximately 65% of the study population carried the (CA)19 repeat allele with 40% carrying two copies of this allele, comparable to allele frequencies reported in other Caucasian populations (9,34). Among premenopausal women, there was an inverse trend for case versus control (CA)n repeat frequency (P for trend = 0.002), where cases had a higher frequency of alleles with fewer than (CA)19 repeats than controls, while controls had a higher frequency of alleles with greater than (CA)19 repeats than cases. There was no association among postmenopausal women according to IGF1 (CA)n repeat polymorphism distribution.


View this table:
[in this window]
[in a new window]
  		Table I. Allelic distribution of IGF1 (CA)n genotype in study populationa

 
Odds ratios and 95% CI for IGF1 genotype groups and breast cancer are shown in Table II. Controlling for other traditional breast cancer risk factors did not appreciably change most estimates and therefore further reported results are adjusted for age only, except where noted. We did not observe any significant association with breast cancer among either pre- or postmenopausal women who did not carry an IGF1 (CA)19 allele when compared to either the IGF1 (CA)19 repeat homozygotes or heterozygotes in IGF1 genotype Groups (1) or (2), nor was any gene-dosage effect observed for decreasing number of the (CA)19 repeat allele. When we evaluated the association for genotypes including at least one allele with <(CA)19 repeats compared to (CA)19 repeat carriers in IGF1 genotype Group (3), we found an increased risk of breast cancer among premenopausal women that was strengthened after adjustment for traditional risk factors (OR = 3.31; 95% CI = 1.47, 7.48). A gene-dosage effect for the ORs with increasing number of the shorter repeat allele was also observed (P = 0.01). The risk of breast cancer remained elevated among premenopausal women who were carriers of at least one <(CA)19 repeat allele when the comparison group was changed from (CA)19 repeat carriers to subjects who did not carry any <(CA)19 repeat alleles (OR = 1.61; 95% CI = 1.06, 2.45) (data not shown). Although the increased association for alleles with <(CA)19 repeats was not statistically significant among postmenopausal women, a modest increase in breast cancer (OR = 1.51; 95% CI = 0.95, 2.40) and a suggested but non-significant gene-dosage effect for increasing number of <(CA)19 repeat alleles were observed (P = 0.08). Conversely, there was no difference between cases and controls for those carrying alleles with >(CA)19 repeats (IGF1 genotype Group 4) in either pre- or postmenopausal women.


View this table:
[in this window]
[in a new window]
  		Table II. Odds ratios (ORs) and 95% confidence intervals (CIs) for IGF1 (CA)n genotype among pre- and postmenopausal women

 
We investigated whether the breast cancer association for IGF1 genotype Groups (1) and (2) differed by exposure to other known and suspected breast cancer risk factors among premenopausal women (Table III). There was little evidence of heterogeneity of effects for most exposures. Although, for IGF1 genotype Group (2) subjects who had ever used HBC experienced about a 60% increase in breast cancer when they lacked a (CA)19 repeat while those who had never used HBC had a significantly reduced risk of breast cancer when they lacked a (CA)19 repeat (P for interaction = 0.01). This association is based on small numbers, however, and should be interpreted with caution. Although not statistically significant, we also observed a several-fold increase in breast cancer among subjects with a family history of breast cancer for IGF1 genotypes that do not include a (CA)19 repeat. When evaluated in a multiplicative model, the association was further strengthened when compared to women with no family history of breast cancer and who carried the common (CA)19 repeat (OR = 4.40; 95% CI = 1.21, 16.1), although the interaction was not statistically significant (LRT P = 0.15).


View this table:
[in this window]
[in a new window]
  		Table III. Breast cancer risk associated with IGF1 (CA)n genotype Groups (1) and (2) among premenopausal women with and without exposure to selected factors

 
Among postmenopausal women, assessing modification of effects for IGF1 genotype with traditional breast cancer risk factors showed significantly increased risk for non-carriers of the (CA)19 repeat among those lacking the risk factor in several characteristics (Table IV). In stratified analyses we found that for women with a lower than median BMI, lacking a (CA)19 repeat was associated with a nearly 80% increase in breast cancer risk (OR = 1.77; 95% CI = 1.06, 2.96), whereas there was no association seen for IGF1 genotype in those with a higher than median BMI. When evaluated on the multiplicative scale, significant interaction was seen between IGF1 genotype and BMI for risk of breast cancer (P for interaction = 0.04). Similar associations were seen among women who had never smoked or had engaged in three or more hours of physical activity per week at baseline, although neither of these interactions were statistically significant. Increased associations were also seen for women who carried only one copy of the (CA)19 repeat when compared to those with two copies among those who never used exogenous hormones and who had ever used alcohol.


View this table:
[in this window]
[in a new window]
  		Table IV. Breast cancer risk associated with IGF1 (CA)n genotype Groups (1) and (2) among postmenopausal women with and without exposure to selected factors

 
Further assessment of effect modification for other IGF1 CA repeat genotypes also using the (CA)19 repeat carriers as the referent showed that breast cancer associations were similar for most genotypes lacking a (CA)19 repeat regardless of whether the genotype included alleles that had primarily <(CA)19 (Group 3) or >(CA)19 (Group 4), observations which were apparent for both pre- and postmenopausal women for most traditional breast cancer risk factors (data not shown). No effect modification was seen for genotype Group 5 (data not shown).

Further analysis of IGF1 genotype according to estrogen receptor (ER) or progesterone receptor (PR) status showed no evidence of association among pre- or postmenopausal women (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
This large population-based case–control study reports on whether the IGF1 promoter CA repeat polymorphism is associated with breast cancer alone or in combination with other breast cancer risk factors. These data support a role for IGF1 genotype in breast cancer occurrence particularly among premenopausal women. We observed evidence of an inverse association between number of CA repeats and breast cancer in premenopausal women, with a significantly increased breast cancer risk in those who carried IGF1 genotypes that included at least one short allele, defined as <(CA)19. There was no significant overall relationship between the IGF1 (CA)n repeat polymorphism and breast cancer in postmenopausal women. These data also provide support for modification of the effects of IGF1 genotype by certain breast cancer risk factors primarily in postmenopausal women.

To date, several epidemiologic studies have examined the association between circulating IGF-I and breast cancer (7,15,35–38). Many of these investigations, including both cohort and case–control studies, have found higher levels of circulating IGF-I in cases than controls, with stronger and more consistent associations among premenopausal women (7,15,35), although not all studies have shown an association (37,38). In vitro studies have suggested that IGF-I is a strong mitogen for breast cancer cell lines (39,40), and there is substantial evidence that IGF-I not only causes proliferation of breast cancer cell lines (41), but also normal breast epithelial tissue (42).

To our knowledge, four published studies have evaluated the association between breast cancer risk and the IGF1 (CA)n repeat polymorphism (22–24,43). Two recent case–control studies found increased breast cancer risk among those who carried the (CA)19 repeat (24,43). It is unknown why results from these studies would be different from ours, although one explanation may be the ethnic composition of the study populations. One study population was primarily African-American (43) and the other was entirely Chinese women (44). IGF1 genotype distribution has been shown to differ according to race and ethnicity, with both African-American and Asian populations carrying a much lower frequency of (CA)19 repeat alleles than Caucasian populations (45). The variation in allelic distributions could result in comparison groups with different genotypic compositions than those of the LIBCSP making a direct comparison of our results difficult to interpret. The Nurses' Health Study and the Caucasian subjects of the Hawaii/Los Angeles Multiethnic Cohort, however, showed similar genotype distributions as that of the LIBCSP and both studies reported no association for the (CA)19 repeat genotype with breast cancer, results which are consistent with our findings (22,23).

Previous investigations of the IGF1 promoter CA repeat polymorphism have generally categorized IGF1 genotype with respect to whether a subject carried a (CA)19 repeat allele or not. The categorization of the IGF1 genotype in this manner has shown inconsistent results for circulating IGF-I levels with reports showing levels being both decreased (9,46) and increased (47,48) among those carrying a (CA)19 repeat allele. The (CA)n repeat is one of the most common forms of naturally occurring repetitive DNA sequences and experimental studies of other genes have reported that these repeats in the promoter region may suppress transcriptional activity (20), and indicate that the length of (CA)n repeats is inversely correlated with transcriptional activity, with up to a 5-fold decrease depending on the number of repeats (21). The inverse association for transcriptional activity with number of (CA)n repeats has not been confirmed for the IGF1 gene, however this effect was suggested recently in results from the Nurses' Health Study which observed a slight, but insignificant trend (P = 0.08) for increasing circulating IGF-I levels with decreasing number of (CA)n repeats (22). The highest levels were detected in those subjects who were heterozygous for the (CA)18/(CA)19 alleles (179 ng/ml) or homozygous for the (CA)19 repeat allele (173 ng/ml), and the lowest levels in those who were homozygous for the (CA)20 repeat allele (149 ng/ml) (22). Similarly, we found a significant inverse association with breast cancer for increasing number of IGF1 (CA)n repeats among premenopausal women (P = 0.002). Further, we found a 3-fold increase in breast cancer risk among premenopausal women who carried at least one <(CA)19 repeat allele compared to those who carried only alleles with ≥(CA)19 repeats (genotype Group 3), findings that are consistent with the hypothesis of a functional relevance for the IGF1 (CA)n repeat promoter polymorphism. We did not, however, see an inverse association for women carrying alleles that were longer than (CA)19 repeats, which may indicate a ceiling effect of IGF-I levels according to genotype or that a functional significance is limited to shorter repeats. Also of interest is that carriers of the <(CA)19 repeat allele genotype in combination with the common (CA)19 repeat allele had breast cancer risks that were attenuated, suggesting that the (CA)19 repeat possibly offers some protection from breast cancer. Meaningful analyses to investigate the impact of individual genotypes that included both alleles with <(CA)19 or with >(CA)19 repeats were not possible in the LIBCSP due to low numbers of subjects with those genotypes. Nor can we confirm whether higher circulating IGF-I levels are associated with shorter (CA)n repeats as IGF-I levels have not been measured in this study.

Although it is estimated that up to 60% of the variation in circulating IGF-I levels may have a genetic basis (17,18), the inter-individual variability may be due in part from exposure to certain environmental or endogenous agents that have the potential to influence expression of IGF1. The effect of oral contraceptives (OC) on breast cancer was reviewed in a recent large meta-analysis consisting of over 50 studies and reported a modest increased association of breast cancer with OC use (49). There is also evidence which suggests that exogenous estrogen use may decrease circulating IGF-I levels in women who take them (50,51) and that this effect may be modified by particular IGF1 genotypes (9). Jernstrom et al. (9) found that in a subgroup of premenopausal women who used OCs circulating IGF-I levels were decreased for those who carried a (CA)19 repeat allele compared to those who did not (264 ng/ml versus 315 ng/ml, P = 0.03), while no difference in IGF-I levels was found according to IGF1 genotype among those who did not use OCs. Our analysis suggests a similar effect showing a modest, though not statistically significant, increased association for women who lack the (CA)19 repeat compared to (CA)19 repeat carriers among premenopausal women who use HBC. We also observed a strong inverse association for (CA)19 repeat allele non-carriers, although the analysis was based on only a few subjects. While these associations among premenopausal women are based on small numbers, the effect shows similarly increased risks among postmenopausal women for both HBC and HRT users. In contrast to premenopausal women, however, postmenopausal women who had never used exogenous hormones were observed to have increased risks for subjects who were non-carriers of a (CA)19 allele, particularly those who had only one copy when compared to homozygous carriers of the (CA)19 allele (Genotype Group 1). These findings suggest a protective effect for the (CA)19 allele among ever users of exogenous hormones possibly through reduction of circulating IGF-I levels, while no protection was seen with this allele among never users.

Postmenopausal obesity is a well-established risk factor for breast cancer, as supported in a recent meta-analysis (52). Some studies have shown that a higher BMI may be associated with reduced circulating IGF-I levels (31,53), possibly due to inhibition of IGFBP-1 and -2 in hyperinsulinemic states that occurs in obesity (54). The reduction of these IGFBPs increase the amount of free IGF-I in circulation, which in turn sends negative feedback on GH-stimulated IGF-I production ultimately resulting in a decrease in total IGF-I levels (55). Our results from stratified analyses, restricted to women with a lower than median BMI, found a significantly increased risk for subjects who lacked a (CA)19 repeat (OR = 1.77; 95% CI = 1.09, 2.87), while no breast cancer association was seen among women with a higher BMI (P for interaction = 0.04). There is evidence, however, to suggest that the association of IGF-I with obesity in postmenopausal women may be non-linear, with the highest levels seen in a recent study among those with a BMI between 24 and 25 (56). When we further evaluated the effect of not carrying a (CA)19 repeat according to quintiles of BMI, we observed similar results with the highest risks among women with a BMI between 22.2 and 24.5 (OR = 3.02; 95% CI = 1.27, 7.18).

In summary, we report that IGF1 genotypes which include alleles with fewer than (CA)19 repeats appear to be associated with an increased risk of breast cancer, particularly among premenopausal women. Our data also indicate that hormonal birth control use in premenopausal women may further increase risk among subjects who have genotypes that lack a (CA)19 repeat. Postmenopausal women with exposures associated with reduced circulating estrogen and higher IGF-I levels may have further increased risks among subjects who carry genotypes that lack a (CA)19 repeat. The suggestion that susceptibility to breast cancer attributed to IGF1 polymorphisms may be modified by other known and suspected risk factors such as obesity further supports the link between IGF-I and breast cancer risk. In light of the strength of the associations and the increased risks found among subjects with exposures that are considered to be low risk for breast cancer, further research is warranted to explore the potential underlying biologic mechanisms involved.


   Acknowledgments
 
We thank Audrey Alexander, Eloise Parrish and Lisa Lindesmith for their laboratory assistance. We would also like to thank the participants of the Long Island Breast Cancer Study Project. For their valuable contributions to the Long Island Breast Cancer Study Project the authors thank: members of the Long Island Breast Cancer Network; the 31 participating institutions on Long Island and in New York City, NY; our National Institutes of Health collaborators, Gwen Colman, Ph.D., National Institutes of Environmental Health Sciences; G. Iris Obrams, M.D., Ph.D. formerly of the National Cancer Institute; members of the External Advisory Committee to the population-based case–control study: Leslie Bernstein, Ph.D., (Committee chair); Gerald Akland, M.S.; Barbara Balaban, MSW; Blake Cady, M.D.; Dale Sandler, Ph.D.; Roy Shore, Ph.D.; and Gerald Wogan, Ph.D.; as well as other collaborators who assisted with various aspects of our data collection efforts including Mary Wolff, Ph.D.; Steven Stellman, Ph.D.; Maureen Hatch, Ph.D.; Gail Garbowski, MPH; Geoff Kabat, Ph.D.; H. Leon Bradlow, Ph.D.; David Camann, B.S.; Martin Trent, B.S.; Jan Beyea, Ph.D.; Ruby Senie, Ph.D.; Carla Maffeo, Ph.D.; Pat Montalvan; Gertrud Berkowitz, Ph.D.; Margaret Kemeny, M.D.; Mark Citron, M.D.; Freya Schnabel, M.D.; Allen Schuss, M.D.; Steven Hajdu, M.D.; and Vincent Vinceguerra, M.D. This work supported by U.S. Army Medical Research and Materiel Command Grant DAMD17-01-1-0348 and in part by the National Cancer Institute and the National Institutes of Environmental Health and Sciences Grant numbers UO1CA/ES66572, UO1CA66572, P50CA55283, P30ES09089, and P30ES10126.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Daughaday,W.H. and Rotwein,P. (1989) Insulin-like growth factors I and II. Peptide, messenger ribonucleic acid and gene structures, serum, and tissue concentrations. Endocr. Rev., 10, 68–91.[Abstract/Free Full Text]
  2. LeRoith,D., Raizada,M.K (ed.). (1993) Proceedings of the 4th International Symposium on Insulin, IGFs, and their Receptors. Woods Hole, Massachusetts, April 20–23, 1993. Adv. Exp. Med. Biol., 343, 1–417.[Medline]
  3. LeRoith,D., Werner,H., Beitner-Johnson,D. and Roberts,C.T.,Jr. (1995) Molecular and cellular aspects of the insulin-like growth factor I receptor. Endocr. Rev., 16, 143–163.[Abstract/Free Full Text]
  4. Jones,J.I. and Clemmons,D.R. (1995) Insulin-like growth factors and their binding proteins: biological actions. Endocr. Rev., 16, 3–34.[Abstract/Free Full Text]
  5. Shimasaki,S. and Ling,N. (1991) Identification and molecular characterization of insulin-like growth factor binding proteins (IGFBP-1, -2, -3, -4, -5 and -6). Prog. Growth Factor Res., 3, 243–266.[CrossRef][Medline]
  6. Chan,J.M., Stampfer,M.J., Giovannucci,E., Gann,P.H., Ma,J., Wilkinson,P., Hennekens,C.H. and Pollak,M. (1998) Plasma insulin-like growth factor-I and prostate cancer risk: a prospective study. Science, 279, 563–566.[Abstract/Free Full Text]
  7. Hankinson,S.E., Willett,W.C., Colditz,G.A., Hunter,D.J., Michaud,D.S., Deroo,B., Rosner,B., Speizer,F.E. and Pollak,M. (1998) Circulating concentrations of insulin-like growth factor-I and risk of breast cancer. Lancet, 351, 1393–1396.[CrossRef][Web of Science][Medline]
  8. Ma,J., Pollak,M.N., Giovannucci,E., Chan,J.M., Tao,Y., Hennekens,C.H. and Stampfer,M.J. (1999) Prospective study of colorectal cancer risk in men and plasma levels of insulin-like growth factor (IGF)-I and IGF-binding protein-3. J. Natl Cancer Inst., 91, 620–625.[Abstract/Free Full Text]
  9. Jernstrom,H., Deal,C., Wilkin,F., Chu,W., Tao,Y., Majeed,N., Hudson,T., Narod,S.A. and Pollak,M. (2001) Genetic and nongenetic factors associated with variation of plasma levels of insulin-like growth factor-I and insulin-like growth factor-binding protein-3 in healthy premenopausal women. Cancer Epidemiol. Biomarkers Prev., 10, 377–384.[Abstract/Free Full Text]
  10. Allen,N.E., Appleby,P.N., Kaaks,R., Rinaldi,S., Davey,G.K. and Key,T.J. (2003) Lifestyle determinants of serum insulin-like growth-factor-I (IGF-I), C-peptide and hormone binding protein levels in British women. Cancer Causes Control, 14, 65–74.[CrossRef][Web of Science][Medline]
  11. Lukanova,A., Soderberg,S., Stattin,P., Palmqvist,R., Lundin,E., Biessy,C., Rinaldi,S., Riboli,E., Hallmans,G. and Kaaks,R. (2002) Nonlinear relationship of insulin-like growth factor (IGF)-I and IGF-I/IGF-binding protein-3 ratio with indices of adiposity and plasma insulin concentrations (Sweden). Cancer Causes Control, 13, 509–516.[CrossRef][Web of Science][Medline]
  12. Roelen,C.A., de Vries,W.R., Koppeschaar,H.P., Vervoorn,C., Thijssen,J.H. and Blankenstein,M.A. (1997) Plasma insulin-like growth factor-I and high affinity growth hormone-binding protein levels increase after two weeks of strenuous physical training. Int. J. Sports Med., 18, 238–241.[Web of Science][Medline]
  13. Thissen,J.P., Ketelslegers,J.M. and Underwood,L.E. (1994) Nutritional regulation of the insulin-like growth factors. Endocr. Rev., 15, 80–101.[Abstract/Free Full Text]
  14. Yee,D. and Lee,A.V. (2000) Crosstalk between the insulin-like growth factors and estrogens in breast cancer. J. Mammary Gland Biol. Neoplasia., 5, 107–115.[CrossRef][Web of Science][Medline]
  15. Toniolo,P., Bruning,P.F., Akhmedkhanov,A., Bonfrer,J.M., Koenig,K.L., Lukanova,A., Shore,R.E. and Zeleniuch-Jacquotte,A. (2000) Serum insulin-like growth factor-I and breast cancer. Int. J. Cancer, 88, 828–832.[CrossRef][Web of Science][Medline]
  16. Muti,P., Quattrin,T., Grant,B.J., Krogh,V., Micheli,A., Schunemann,H.J., Ram,M., Freudenheim,J.L., Sieri,S., Trevisan,M. and Berrino,F. (2002) Fasting glucose is a risk factor for breast cancer: a prospective study. Cancer Epidemiol. Biomarkers Prev., 11, 1361–1368.[Abstract/Free Full Text]
  17. Harrela,M., Koistinen,H., Kaprio,J. et al. (1996) Genetic and environmental components of interindividual variation in circulating levels of IGF-I, IGF-II, IGFBP-1, and IGFBP-3. J. Clin. Invest., 98, 2612–2615.[Web of Science][Medline]
  18. Hong,Y., Pedersen,N.L., Brismar,K., Hall,K. and de Faire,U. (1996) Quantitative genetic analyses of insulin-like growth factor I (IGF-I), IGF-binding protein-1, and insulin levels in middle-aged and elderly twins. J. Clin. Endocrinol. Metab., 81, 1791–1797.[Abstract]
  19. Weber,J.L. and May,P.E. (1989) Abundant class of human DNA polymorphisms which can be typed using the polymerase chain reaction. Am. J. Hum. Genet., 44, 388–396.[Web of Science][Medline]
  20. Tae,H.J., Luo,X. and Kim,K.H. (1994) Roles of CCAAT/enhancer-binding protein and its binding site on repression and derepression of acetyl-CoA carboxylase gene. J. Biol. Chem., 269, 10475–10484.[Abstract/Free Full Text]
  21. Gebhardt,F., Zanker,K.S. and Brandt,B. (1999) Modulation of epidermal growth factor receptor gene transcription by a polymorphic dinucleotide repeat in intron 1. J. Biol. Chem., 274, 13176–13180.[Abstract/Free Full Text]
  22. Missmer,S.A., Haiman,C.A., Hunter,D.J., Willett,W.C., Colditz,G.A., Speizer,F.E., Pollak,M.N. and Hankinson,S.E. (2002) A sequence repeat in the insulin-like growth factor-1 gene and risk of breast cancer. Int. J. Cancer, 100, 332–336.[CrossRef][Web of Science][Medline]
  23. DeLellis,K., Ingles,S., Kolonel,L., McKean-Cowdin,R., Henderson,B., Stanczyk,F. and Probst-Hensch,N.M. (2003) IGF1 genotype, mean plasma level and breast cancer risk in the Hawaii/Los Angeles multiethnic cohort. Br J. Cancer, 88, 277–282.[CrossRef][Web of Science][Medline]
  24. Yu,H., Li,B.D., Smith,M., Shi,R., Berkel,H.J. and Kato,I. (2001) Polymorphic CA repeats in the IGF-I gene and breast cancer. Breast Cancer Res. Treat, 70, 117–122.[CrossRef][Web of Science][Medline]
  25. Figer,A., Karasik,Y.P., Baruch,R.G., Chetrit,A., Papa,M.Z., Sade,R.B., Riezel,S. and Friedman,E. (2002) Insulin-like growth factor I polymorphism and breast cancer risk in Jewish women. Isr. Med. Assoc. J., 4, 759–762.[Web of Science][Medline]
  26. Gammon,M.D., Neugut,A.I., Santella,R.M. et al. (2002) The Long Island Breast Cancer Study Project: description of a multi-institutional collaboration to identify environmental risk factors for breast cancer. Breast Cancer Res. Treat, 74, 235–254.[CrossRef][Web of Science][Medline]
  27. Waksberg,J. (1978) Sampling methods for random digit dialing. J. Amer Statistic Assoc., 73, 40–46.[CrossRef]
  28. Hosmer,D. and Lemeshow,S. (1989) Applied logistic regression. John Wiley & Sons, New York.
  29. Jernstrom,H. and Olsson,H. (1994) Suppression of plasma insulin-like growth factor-1 levels in healthy, nulliparous, young women using low dose oral contraceptives. Gynecol. Obstet. Invest., 38, 261–265.[Web of Science][Medline]
  30. Bellantoni,M.F., Vittone,J., Campfield,A.T., Bass,K.M., Harman,S.M. and Blackman,M.R. (1996) Effects of oral versus transdermal estrogen on the growth hormone/insulin-like growth factor I axis in younger and older postmenopausal women: a clinical research center study. J. Clin. Endocrinol. Metab., 81, 2848–2853.[Abstract/Free Full Text]
  31. Chang,S., Wu,X., Yu,H. and Spitz,M.R. (2002) Plasma concentrations of insulin-like growth factors among healthy adult men and postmenopausal women: associations with body composition, lifestyle, and reproductive factors. Cancer Epidemiol. Biomarkers Prev., 11, 758–766.[Abstract/Free Full Text]
  32. Kaaks,R. and Lukanova,A. (2001) Energy balance and cancer: the role of insulin and insulin-like growth factor-I. Proc Nutr Soc., 60, 91–106.[Web of Science][Medline]
  33. Rothman,K.J., G.S. (1998) Modern Epidemiology. Lippincott-Raven Publishers, Philadelphia, PA.
  34. Frayling,T.M., Hattersley,A.T., McCarthy,A., Holly,J., Mitchell,S.M., Gloyn,A.L., Owen,K., Davies,D., Smith,G.D. and Ben-Shlomo,Y. (2002) A putative functional polymorphism in the IGF-I gene: association studies with type 2 diabetes, adult height, glucose tolerance, and fetal growth in U.K. populations. Diabetes, 51, 2313–2316.[Abstract/Free Full Text]
  35. Bruning,P.F., Van Doorn,J., Bonfrer,J.M., Van Noord,P.A., Korse,C.M., Linders,T.C. and Hart,A.A. (1995) Insulin-like growth-factor-binding protein 3 is decreased in early-stage operable pre-menopausal breast cancer. Int. J. Cancer, 62, 266–270.[Web of Science][Medline]
  36. Kaaks,R., Lundin,E., Rinaldi,S. et al. (2002) Prospective study of IGF-I, IGF-binding proteins, and breast cancer risk, in northern and southern Sweden. Cancer Causes Control, 13, 307–316.[CrossRef][Web of Science][Medline]
  37. Jernstrom,H. and Barrett-Connor,E. (1999) Obesity, weight change, fasting insulin, proinsulin, C-peptide, and insulin-like growth factor-1 levels in women with and without breast cancer: the Rancho Bernardo Study. J. Womens Health Gend Based Med, 8, 1265–1272.[Web of Science][Medline]
  38. Petridou,E., Papadiamantis,Y., Markopoulos,C., Spanos,E., Dessypris,N. and Trichopoulos,D. (2000) Leptin and insulin growth factor I in relation to breast cancer (Greece). Cancer Causes Control, 11, 383–388.[CrossRef][Web of Science][Medline]
  39. Macaulay,V.M. (1992) Insulin-like growth factors and cancer. Br J. Cancer, 65, 311–320.[Web of Science][Medline]
  40. Karey,K.P. and Sirbasku,D.A. (1988) Differential responsiveness of human breast cancer cell lines MCF-7 and T47D to growth factors and 17 beta-estradiol. Cancer Res., 48, 4083–4092.[Abstract/Free Full Text]
  41. Pollak,M., Costantino,J., Polychronakos,C., Blauer,S.A., Guyda,H., Redmond,C., Fisher,B. and Margolese,R. (1990) Effect of tamoxifen on serum insulinlike growth factor I levels in stage I breast cancer patients. J. Natl Cancer Inst., 82, 1693–1697.[Abstract/Free Full Text]
  42. Ng,S.T., Zhou,J., Adesanya,O.O., Wang,J., LeRoith,D. and Bondy,C.A. (1997) Growth hormone treatment induces mammary gland hyperplasia in aging primates. Nat. Med., 3, 1141–1144.[CrossRef][Web of Science][Medline]
  43. Wen,W., Gao,Y.T., Shu,X.O., Yu,H., Cai,Q., Smith,J.R. and Zheng,W. (2005) Insulin-like growth factor-I gene polymorphism and breast cancer risk in Chinese women. Int. J. Cancer, 113, 307–311.[CrossRef][Web of Science][Medline]
  44. Yu,H., Jin,F., Shu,X.O., Li,B.D., Dai,Q., Cheng,J.R., Berkel,H.J. and Zheng,W. (2002) Insulin-like growth factors and breast cancer risk in Chinese women. Cancer Epidemiol. Cancer Epidemiol Biomarkers Prev., 11, 705–712.[Abstract/Free Full Text]
  45. Jernstrom,H., Chu,W., Vesprini,D., Tao,Y., Majeed,N., Deal,C., Pollak,M. and Narod,S.A. (2001) Genetic factors related to racial variation in plasma levels of insulin-like growth factor-1: implications for premenopausal breast cancer risk. Mol. Genet. Metab., 72, 144–54.[CrossRef][Web of Science][Medline]
  46. Rosen,C.J., Kurland,E.S., Vereault,D., Adler,R.A., Rackoff,P.J., Craig,W.Y., Witte,S., Rogers,J. and Bilezikian,J.P. (1998) Association between serum insulin growth factor-I (IGF-I) and a simple sequence repeat in IGF-I gene: implications for genetic studies of bone mineral density. J. Clin. Endocrinol. Metab., 83, 2286–2290.[Abstract/Free Full Text]
  47. Vaessen,N., Heutink,P., Janssen,J.A., Witteman,J.C., Testers,L., Hofman,A., Lamberts,S.W., Oostra,B.A., Pols,H.A. and van Duijn,C.M. (2001) A polymorphism in the gene for IGF-I: functional properties and risk for type 2 diabetes and myocardial infarction. Diabetes, 50, 637–642.[Abstract/Free Full Text]
  48. Rietveld,I., Janssen,J.A., Hofman,A., Pols,H.A., van Duijn,C.M. and Lamberts,S.W. (2003) A polymorphism in the IGF-I gene influences the age-related decline in circulating total IGF-I levels. Eur. J. Endocrinol., 148, 171–175.[Abstract]
  49. Collaborative Group on Hormonal Factors in Breast Cancer. (1996) Breast cancer and hormonal contraceptives: collaborative reanalysis of individual data on 53 297 women with breast cancer and 100 239 women without breast cancer from 54 epidemiological studies. Lancet, 347, 1713–1727.[CrossRef][Web of Science][Medline]
  50. Holmes,M.D., Pollak,M.N. and Hankinson,S.E. (2002) Lifestyle correlates of plasma insulin-like growth factor I and insulin-like growth factor binding protein 3 concentrations. Cancer Epidemiol. Biomarkers Prev., 11, 862–867.[Abstract/Free Full Text]
  51. Goodman-Gruen,D. and Barrett-Connor,E. (1996) Effect of replacement estrogen on insulin-like growth factor-I in postmenopausal women: the Rancho Bernardo Study. J. Clin. Endocrinol. Metab., 81, 4268–4271.[Abstract]
  52. van den Brandt,P.A., Spiegelman,D., Yaun,S.S. et al. (2000) Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Am. J. Epidemiol., 152, 514–527.[Abstract/Free Full Text]
  53. Colletti,R.B., Copeland,K.C., Devlin,J.T., Roberts,J.D. and McAuliffe,T.L. (1991) Effect of obesity on plasma insulin-like growth factor-I in cancer patients. Int. J. Obes., 15, 523–527.[Web of Science][Medline]
  54. Nam,S.Y., Lee,E.J., Kim,K.R., Cha,B.S., Song,Y.D., Lim,S.K., Lee,H.C. and Huh,K.B. (1997) Effect of obesity on total and free insulin-like growth factor (IGF)-1, and their relationship to IGF-binding protein (BP)-1, IGFBP-2, IGFBP-3, insulin, and growth hormone. Int. J. Obes. Relat. Metab. Disord., 21, 355–359.[CrossRef][Web of Science][Medline]
  55. Chapman,I.M., Hartman,M.L., Pieper,K.S., Skiles,E.H., Pezzoli,S.S., Hintz,R.L. and Thorner,M.O. (1998) Recovery of growth hormone release from suppression by exogenous insulin-like growth factor I (IGF-I): evidence for a suppressive action of free rather than bound IGF-I. J. Clin. Endocrinol. Metab., 83, 2836–2842.[Abstract/Free Full Text]
  56. Lukanova,A., Lundin,E., Zeleniuch-Jacquotte,A. et al. (2004) Body mass index, circulating levels of sex-steroid hormones, IGF-I and IGF-binding protein-3: a cross-sectional study in healthy women. Eur. J. Endocrinol., 150, 161–171.[Abstract]
Received September 16, 2005; revised November 14, 2005; accepted November 15, 2005.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
C. Ye, Y.-T. Gao, W. Wen, J. P. Breyer, X. O. Shu, J. R. Smith, W. Zheng, and Q. Cai
Association of Mitochondrial DNA Displacement Loop (CA)n Dinucleotide Repeat Polymorphism with Breast Cancer Risk and Survival among Chinese Women
Cancer Epidemiol. Biomarkers Prev., August 1, 2008; 17(8): 2117 - 2122.
[Abstract] [Full Text] [PDF]

Home page
 Hum Mol GenetHome page
C. Palles, N. Johnson, B. Coupland, C. Taylor, J. Carvajal, J. Holly, I. S. Fentiman, I. dos Santos Silva, A. Ashworth, J. Peto, et al.
Identification of genetic variants that influence circulating IGF1 levels: a targeted search strategy
Hum. Mol. Genet., May 15, 2008; 17(10): 1457 - 1464.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Epidemiol. Biomarkers Prev.Home page
S. L. Deming, Z. Ren, Q. Cai, X.-O. Shu, W. Wen, J.-R. Long, Y.-T. Gao, and W. Zheng
IGF-I and IGF-II Genetic Variation and Breast Cancer Risk in Chinese Women: Results from the Shanghai Breast Cancer Study
Cancer Epidemiol. Biomarkers Prev., January 1, 2008; 17(1): 255 - 257.
[Full Text] [PDF]

Home page
 Physiol. GenomicsHome page
J. Estany, M. Tor, D. Villalba, L. Bosch, D. Gallardo, N. Jimenez, L. Altet, J. L. Noguera, J. Reixach, M. Amills, et al.
Association of CA repeat polymorphism at intron 1 of insulin-like growth factor (IGF-I) gene with circulating IGF-I concentration, growth, and fatness in swine
Physiol Genomics, October 19, 2007; 31(2): 236 - 243.
[Abstract] [Full Text] [PDF]

Home page
 JNCI J Natl Cancer InstHome page
J. P. A. Ioannidis
Common genetic variants for breast cancer: 32 largely refuted candidates and larger prospects.
J Natl Cancer Inst, October 4, 2006; 98(19): 1350 - 1353.
[Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
27/4/758    most recent
bgi294v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (16)
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Cleveland, R. J.
Right arrow Articles by Conway, K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Cleveland, R. J.
Right arrow Articles by Conway, K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?