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Cancer Epidemiology Biomarkers & Prevention Vol. 14, 1394-1401, June 2005
© 2005 American Association for Cancer Research

Variation in Plasma Insulin-Like Growth Factor-1 and Insulin-Like Growth Factor Binding Protein-3: Genetic Factors

Libby M. Morimoto1,2, Polly A. Newcomb1,2,3, Emily White1,2, Jeannette Bigler1 and John D. Potter1,2

1 Public Health Sciences, Fred Hutchinson Cancer Research Center; 2 Department of Epidemiology, University of Washington, Seattle, Washington; and 3 University of Wisconsin, Comprehensive Cancer Center, Madison, Wiscosin

Requests for reprints: Polly Newcomb, 1100 Fairview Avenue North, M4-B402, Seattle, WA 98109. Phone: 206-667-3476; Fax: 206-667-7850. E-mail: pnewcomb{at}fhcrc.org


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Insulin-like growth factors (IGFs) play key roles in cell proliferation and apoptosis. Whereas relatively stable within individuals, IGFs vary substantially between individuals, and a large component of this variation may be determined by genetic factors. Several polymorphisms in IGF genes have been identified, although their functional significance is not clear. We evaluated the association of polymorphisms in IGF-1 and IGFBP-3 and circulating levels of IGF-1 and IGFBP-3 in 323 population-based control subjects enrolled in a case-control study of colorectal cancer from September 1999 through February 2002. Total IGF-1 and IGFBP-3 levels were measured using ELISA assays, and all subjects were genotyped for a microsatellite polymorphism in IGF-1 and a single nucleotide polymorphism in IGFBP-3. Multiple linear regression was used to assess the association of genotype with circulating IGFs. IGF-1 levels were unrelated to either polymorphism. IGFBP-3 was significantly associated with IGFBP-3 genotype, with IGFBP-3 levels increasing from CC (1,895 ng/mL) -> GC (2,029 ng/mL) -> GG (2,182 ng/mL), (p-trend < 0.001). Having an IGF-1 genotype other than homozygous for the 19-repeat allele was associated with higher IGFBP-3 levels (1,945 versus 2,052 ng/mL). Furthermore, both IGF-1 and IGFBP-3 genotypes modified the relationship between postmenopausal hormone use and IGFs. This analysis provides evidence that common variation in IGF genes may contribute to the variation in circulating levels observed between individuals.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Insulin-like growth factor-1 (IGF-1) is an important regulator of cell proliferation, differentiation, and apoptosis. In addition to its anabolic action on protein and carbohydrate metabolism, IGF-1 is a potent mitogen that increases DNA synthesis and promotes cell division by stimulating expression of important cell cycle proteins (1). IGF-1 also prevents cell death by altering the expression of apoptotic proteins Bcl and Bax (2). IGF-1 action is regulated by interaction with several high-affinity IGF-binding proteins (IGFBP), primarily IGFBP-3. IGFBP-3 carries IGF-1 in circulation and directs it to target tissues, protects it from proteolytic degradation, and regulates its interaction with the IGF-1R (3). Additionally, IGFBP-3 has its own IGF-independent apoptotic effects, mediated through a specific cell surface receptor (4).

Prospective observational studies have suggested that circulating levels of IGFs may be related to future risk of prostate (5-7), colorectal (8-11), premenopausal breast (12-18), and possibly lung cancer (19, 20), as well as other chronic diseases (21-26). IGFs in circulation are produced primarily by the liver, yet many other tissues produce IGFs, and it is thought that local bioactivity of IGFs is the most physiologically relevant to these observed neoplastic associations (27). Because endocrine and local expression of IGFs are regulated in parallel, it is believed that circulating IGF levels, in most cases, are likely to correlate with tissue bioactivity and thus may be a useful indicator of IGF exposure (27).

Several studies have evaluated the relationship of personal, lifestyle, and nutritional factors as predictors of circulating IGF-1 and IGFBP-3 (28-42). Twin studies have suggested that heritable factors may account for a substantial proportion of the wide variation in IGF-1 and IGFBP-3 variation between individuals (43, 44). Both IGF-1 and IGFBP-3 genes are polymorphic in human populations (45-47), but the functional relevance of these common variants and how they may interact with known lifestyle and nutritional factors is unclear (48). We conducted a population-based study to investigate the role of a microsatellite polymorphism in IGF-1 and a single nucleotide polymorphism in IGFBP-3 in relation to interindividual variation in circulating IGF-1 and IGFBP-3 and to evaluate whether individuals' genotypes modified the relationship between certain lifestyle factors and IGF levels.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study Population: The Seattle Colon Cancer Family Registry
The Seattle Colon Cancer Family Registry (C-CFR; U01 CA74794) is an ongoing population-based study of incident colorectal cancer cases, relatives, and cancer-free controls and is a resource for studies in colorectal cancer genetics (49). Cases were male and female residents of the metropolitan Seattle area ages 20 to 74 years, who were diagnosed with incident colon or rectal cancer beginning January 1, 1998, identified through the Puget Sound Surveillance Epidemiology and End Results registry (N01-CN-05230), a population registry covering the western Washington counties. Only subjects in the greater Seattle metropolitan area (King, Snohomish, and Pierce counties) were included in this study. Community controls were residents in the Seattle metropolitan area and were randomly selected using Washington State driver's license data for individuals ages 20 to 64 years and Centers for Medicare and Medicare Services files for individuals ages 65 to 74 years. Controls were selected on a monthly basis to represent the age and sex distribution of cases enrolled in the study. Of the 1,889 potential control subjects identified, 38 (2%) had died, 19 (1%) could not be located, and 510 (27%) refused to participate. The final study sample included 1,322 eligible controls (overall response proportion 70%).

Seattle C-CFR: Interview Data
After consent was obtained according to a protocol approved by the Fred Hutchinson Cancer Research Center (FHCRC) Institutional Review Board, trained study interviewers administered the structured C-CFR interview by telephone. Interview data were collected using a computer-assisted telephone interview system (CATI, Ci3, Sawtooth Software, v4.1). The standardized questionnaire elicited information on demographics; anthropometry; physical activity; smoking status; reproductive experiences; medication use, including oral contraceptives, postmenopausal hormones (PMH), and nonsteroidal anti-inflammatory drugs; vitamin and supplement use; alcohol consumption; family history of cancer; and some dietary information. At the conclusion of the telephone interview, permission for a blood specimen by venipuncture was requested; those refusing were asked for a buccal swish sample.

Biospecimen Collection and Processing
Blood samples were collected in the participants' homes, doctors' offices, or the FHCRC clinic and were returned to FHCRC for processing. Whole blood samples were collected in EDTA vacuum tubes to prevent coagulation and were processed within 48 hours of being drawn. White cells, red cells, and plasma were separated according to a standardized protocol. Plasma was aliquoted and stored at –70°C. White cells were stored in appropriate cell culture medium at –70°C for DNA extraction or preparation of cell lines. DNA was extracted from buffy coats or buccal cells at the Specimen Processing Laboratory of the FHCRC using the Qiagen midi kit (Qiagen, Inc., Valencia, CA). DNA was quantified and examined for purity by UV absorption at 260 and 280 nm.

Subjects for Analysis
Subjects for the current analysis consisted of a sequential sample of male and female controls ages 20 to 74 years enrolled in the Seattle C-CFR from September 1999 through January 2002. Of the 1,322 enrolled control subjects, 329 had donated a blood sample at the time this analysis was conducted (participants donating only a buccal sample were excluded). Six subjects were excluded because DNA was of insufficient quantity or quality to perform genotyping for IGF-1 and IGFBP-3 polymorphisms. The current analysis present results for the 323 individuals on whom we had complete genotyping and plasma assay data. Subjects included in the final analysis were similar to those in the total population of eligible controls with respect to age, sex, and race distribution.

IGF-1 and IGFBP-3 Plasma Levels
Circulating levels of plasma total IGF-1 and IGFBP-3 were measured at the FHCRC Cytokine Laboratory by ELISA. Samples were assayed for IGF-1 and IGFBP-3 using ELISA kits from Diagnostic Systems Labs (Webster, TX). The assays used 0.02 mL (for IGF-1) or 0.025 mL (for IGFBP-3) of standard, control, or diluted sample (diluted 1:100 in sample diluent), in duplicate, to the 96-well assay microplate and then 0.05 mL per well of assay buffer was added to all wells. Plates were incubated for 2 hours at room temperature on an orbital shaker. Plates were then washed five times with wash solution provided in the kit and blotted dry on paper towels. An antibody-enzyme conjugate solution (0.1 mL) was added to all wells, and the plates were incubated on an orbital shaker for 1 hour at room temperature. Plates were again washed and blotted dry as before. TMB substrate solution (0.1 mL) was added to each well, and the color development reaction was allowed to proceed at room temperature in the dark for 10 minutes, at which time the reaction was stopped by addition of 0.1 mL per well of stop solution provided in the assay kit. Absorbance at 450 nm was measured on an automatic plate reader and the concentration of unknowns from a given assay plate was calculated by interpolation using a standard curve from the same plate. The mean intra-assay coefficients of variation for IGF-1 and IGFBP-3 were 2.47% and 4.38%, respectively.

Genotyping
Genotyping of the IGF-1 microsatellite polymorphism (cytosine-adenosine, or CA, repeat) was determined by PCR amplification of the polymorphic region (47) followed by rapid fragment length detection using the ABI 3100 DNA Sequencer (Applied Biosystems, Foster City, CA). PCR primers were 5'-GCTAGCCAGCTGGTGTTATT-3' and 5'-ACCACTCTGGGAGAAGGGTA-3'; the forward primer was 5'-labeled with a fluorescent dye (FAM). The PCR reaction contained 10x AmpliTaq buffer (supplied with enzyme, Applied Biosystems), 2.0 mmol/L MgCl2, 200 µmol/L deoxynucleotide triphosphate, 200 nmol/L forward primer, 200 nmol/L reverse primer, 0.5 units of AmpliTaq DNA polymerase (Applied Biosystems), and 40 ng of genomic DNA. Cycling was at 94°C for 5 minutes and 35 cycles of 94°C for 30 seconds, 62°C for 45 seconds, and 72°C for 1 minute followed by 72°C for 5 minutes, using an MJ thermal cycler (MJ Research, Inc., Waltham, MA). The length of amplified fragments was determined relative to GeneScan-500 size standard, using GeneScan and Genotyper Analysis Software (Applied Biosystems). Representative homozygotes (18/18, 19/19, 20/20, and 21/21) were sequenced to determine (CA)n repeat number from base pair length.

Genotyping of the Gly32Ala single nucleotide polymorphism in IGFBP-3 was done by PCR-RFLP. A fragment containing the mutation was amplified using primer 5'-TTCCTGCCTGGATTCCACAGCTT-3' and G5-GGCACTAGCGTTGACGCAGA-3'. The PCR reaction contained 10x AmpliTaq buffer (supplied with enzyme, Applied Biosystems), 2.0 mmol/L MgCl2, 200 µmol/L deoxynucleotide triphosphates, 200 nmol/L forward primer, 200 nmol/L reverse primer, 5% DMSO, 0.5 units AmpliTaq DNA polymerase (Applied Biosystems), and 40 ng of genomic DNA. Cycling was at 96°C for 5 minutes and 35 cycles of 96°C for 30 seconds, 60°C for 45 seconds, and 72°C for 1 minute followed by 72°C for 5 minutes. The amplified fragment was then digested with Ava1 (New England BioLabs, Beverly, MA). The 40-µL reaction contained 20-µL PCR fragment, 10x NEB buffer 4 (NEB, supplied with enzyme), and 2 units of Ava1 enzyme. The products were separated on a 2% NuSieve agarose gel (Bio Whittaker Molecular Applications, Rockland, ME) and stained with ethidium bromide; the fragments were photographed on a UV transilluminator. The fragment sizes were 187 and 263 bp for the G allele and 450 bp for the C allele. Quality control measures for all genotyping included blinded repeat genotyping on 10% of samples; concordance for QC repeats was 100%.

Analyses
For IGF-1 genotype, individuals were first categorized into 10 genotypes based on the four most commonly occurring alleles in our population (307 of our 323 study participants were categorized into 1 of these 10 genotypes), and then individuals were categorized according to whether they had the most common genotype (homozygous for the 19-repeat allele) or had any other IGF-1 genotype (all 323 participants were thus categorized). IGFBP-3 was evaluated as a codominant model, and individuals were categorized as having a CC, GC, or GG genotype.

Age at interview was categorized into four groups (20-49, 50-59, 60-69, and 70-79 years). Body mass index (BMI) was calculated as reported weight (in kg) divided by the square of height (in meters) and dichotomized at the median value separately for men and women. Recent vigorous physical activity [hours per month of physical activity of at least 6.0 metabolic equivalents, or METs (50), over the most recent decade of life] was dichotomized at the median value separately for men and women among those with some reported activity, or categorized as "0" for those who reported no vigorous physical activity. PMH use (never, former, or current) was defined as use of postmenopausal hormones containing estrogen for at least 6 months.

Plasma IGF concentrations were normally distributed and therefore not transformed. In addition to evaluating IGF-1 and IGFBP-3 as dependent outcomes, we assessed the molar ratio of IGF-1/IGFBP-3. This ratio was calculated as:


Data were analyzed using multivariate linear regression to evaluate the association between IGF polymorphisms (independent variables) and circulating IGF-1, IGFBP-3, and the ratio of IGF-1/IGFBP-3 (dependent variables). Age-adjusted mean plasma levels were calculated that were associated with each category of each genotype. For the IGF-1 genotype, we evaluated all genotypes combined compared with the most common genotype (homozygotes for the 19-repeat allele) and evaluated the nine other most common genotypes compared with the most common genotype. For IGFBP-3 genotype, we evaluated individuals with the GC and GG genotype separately, compared with those with the CC genotype. A test for trend was calculated by coding IGFBP-3 as a categorical trend variable.

Effect modification by IGF-1 and IGFBP-3 genotype was also assessed in the relationship of lifestyle factors (physical activity, BMI, and PMH use) with circulating IGF levels. In each stratified analysis, the reference group was assigned as the following: for the BMI analysis, the leanest group with the 19/19 (for IGF-1) or CC (for IGFBP-3) genotype; for the physical activity analysis, the group with 0 hour of vigorous physical activity per month with the 19/19 or CC genotype; for PMH use, the never users with the 19/19 or CC genotype. Each respective strata of genotype and lifestyle factor was compared with this reference group. Pinteraction was calculated as the statistical significance of the multiplicative interaction term of the dichotomous group (IGF-1 genotype) variable and the lifestyle factor coded as a categorical trend variable. The interaction between IGFBP-3 genotype and each lifestyle factor was evaluated using a multiple F test.

All analyses were done using STATA 7.0 for Windows (STATA Corp., College Station, TX) statistical software; all significance tests were two sided.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
There were 129 men and 194 women included in this study. Personal and lifestyle characteristics of the study population are shown in Table 1; these were similar to the characteristics of the complete (n = 1,322) control population (data not shown). Table 2 shows the distribution of more common genotype frequencies in our population, overall and stratified by sex. There were seven different IGF-1 alleles, ranging from 16 to 22 CA repeats. The IGF-1 19-repeat allele was the most common allele in this study population (64%), and the 20-repeat allele was the second most common (19%), followed by the 21-repeat allele (7%) and the 18-repeat allele (7%). No other allele frequency exceeded 5% (data not shown). Overall, the 19r/19r genotype was most common, accounting for 43.0% of our population. Next most common genotypes were 19r/20r (22%), 18r/19r (10%), 19r/21r (8%), and 20r/20r (6%). Although the four most common alleles in our population formed nine additional genotypes (in addition to 19/19), five of these genotypes occurred with a frequency of <5% and were thus excluded from subanalysis. Genotype frequencies stratified by sex were similar in order and magnitude to combined frequencies. For IGFBP-3, the C allele had a frequency of 60% and the G allele 40%. All IGF-1 and IGFBP-3 alleles were in Hardy-Weinberg equilibrium in this population (IGF-1: P = 0.48 and IGFBP-3: P = 0.32).


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  		Table 1. Characteristics of study population

 

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  		Table 2. Mean levels of plasma IGF-1, IGFBP-3 and their molar ratio, by IGF-1 and IGFBP-3 genotype

 
The mean plasma IGF-1 level was 127 ng/mL [SD = 55; 143 ng/mL (SD = 40) among males and 116 ng/mL (SD = 61) among females]; the mean plasma IGFBP-3 level was 2,006 ng/mL [SD = 507; 2034 ng/mL (SD = 489) among males and 1988 ng/mL (SD = 520) among females]; and the mean ratio of IGF-1 to IGFBP-3 was 0.23 [SD = 0.08; 0.26 (SD = 0.06) among males and 0.21 (SD = 0.09) among females]. Table 2 shows the adjusted mean levels of IGF-1, IGFBP-3, and the ratio of IGF-1/IGFBP-3 associated with IGF genotypes. The IGF-1 microsatellite polymorphism was not associated with differences in IGF-1 levels. However, compared with individuals with the most common IGF-1 genotype (19/19), individuals with other genotypes had significantly higher levels of IGFBP-3 (P = 0.05). Specifically, individuals with the 19/20 genotype and the 19/21 genotype had higher IGFBP-3 levels than the 19/19 genotype (108% and 113% higher, respectively). IGF-1 genotype was largely unrelated to the IGF-1/IGFBP-3 ratio, with the exception of the 18/21 genotype, which was associated with a higher molar ratio (P = 0.004). IGFBP-3 genotype was not associated with circulating IGF-1 levels. However, the presence of the IGFBP-3 G allele was positively associated with IGFBP-3 levels; IGFBP-3 levels increased with increasing numbers of G alleles, such that CC < GC < GG (Ptrend < 0.001). The IGFBP-3 polymorphism was also inversely associated with the ratio of IGF-1/IGFBP-3 (P = 0.003). Sex-stratified associations were generally similar to the combined results, although often no longer statistically significant.

Effect Modification by Genotype
IGF-1 genotype modified the relationship between PMH use and circulating IGFBP-3 (Pinteraction = 0.04); PMH use was inversely related to IGFBP-3 levels only among individuals with the 19/19 genotype (Table 3). There was also evidence that the IGFBP-3 genotype modified the relationship of PMH use with the ratio of IGF-1/IGFBP-3 (Pinteraction = 0.05; Table 4). There was no other evidence of effect modification of the relationship between lifestyle factors and IGF levels by either genotype.


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  		Table 3. The association of BMI, physical activity, and PMH use with circulating IGF-1, IGFBP-3, and their molar ratio, stratified by IGF-1 genotype

 

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  		Table 4. The association of body mass index, physical activity, and PMH use with circulating IGF-1, IGFBP-3, and their molar ratio, stratified by IGFBP-3 genotype

 

   Discussion
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
In this cross-sectional analysis of healthy men and women, we observed that IGF-1 concentrations were not affected by IGF-1 or IGFBP-3 genotype but that both genotypes were related to IGFBP-3 levels. Although neither genotype seems a significant modifier of the relationship of physical activity or BMI with circulating IGFs, the IGF-1 genotype modified the relationship of PMH use and circulating IGFBP-3, and the IGFBP-3 genotype modified the relationship between PMH use and the molar ratio of IGF-1/IGFBP-3.

Our null result for the relationship of the IGF-1 microsatellite polymorphism and circulating IGF-1 adds to the diverse literature of this association. In a cross-sectional analysis of 116 Caucasian men and women, homozygosity for the most common allele was associated with significantly lower serum IGF-1 levels than all other genotypes (47). However, subsequent studies found associations in the opposite direction (51), null (52), relations with different alleles (53), or limited to specific subgroups (36, 48). Because both age (28-36, 39, 54) and sex (31, 34, 55, 56) have been related to differences in IGF levels, sex and age distributions of subjects between studies may partly account for these conflicting results, as may differences in racial distributions and therefore allele frequencies.

The IGF-1 dinucleotide repeat polymorphism is located ~1 kb upstream from the transcription start site of the IGF-1 gene, a region that contains specific regulatory elements that influence promotional activity (57). It has been proposed that this polymorphism may be related to differences in IGF-1 expression and protein levels in circulation (47). In addition to its relationship with circulating IGF-1 levels, this polymorphism has been studied in relation to bone density (53, 58, 59), body composition (60), NIDDM (21, 61, 62), and birthweight (63). However, the functional relevance of this microsatellite polymorphism has not been established, and in the absence of any functional assays evaluating the effect of repeat length variation on IGF-1 expression levels, any mechanistic interpretation of this polymorphism is speculative. Furthermore, the microsatellite repeat may be just an informative marker in linkage disequilibrium with an unknown causal allele. Complicating the analysis of this polymorphism is the presence of two promoters for the IGF-1 gene (64, 65); initiation of transcription from these two promoters, as well as alternate splicing (66) and tissue-specific expression (67, 68), results in a variety of mRNA transcripts (69-72). The presence of multiple transcripts is often indicative of the variable response of cells to different stimuli (73-75), suggesting that the influence of genetic and environmental factors may induce different patterns of IGF-1 transcription (2).

We found that IGFBP-3 genotype was related to circulating levels of IGFBP-3 and the ratio of IGF-1/IGFBP-3. To our knowledge, the current analysis is the first to evaluate the relationship of this IGFBP-3 polymorphism with circulating IGFs. The IGFBP-3 protein and its regulation is less well characterized than IGF-1. Although long considered to function mainly as an inhibitor of IGF-1 signaling, recent work has identified cellular actions of IGF-binding proteins that are separate from their IGF-dependent effects, including cell growth inhibition and stimulation and apoptosis (4). IGFBP-3 interacts with several known signaling pathways (4), and it has been shown that IGFBP-3 contributes to the growth-inhibitory effects of several antiproliferative agents, including transforming growth factor (76), retinoic acid (77), antiestrogens (78), and vitamin D (79).

The G -> C transversion in exon 1 of the IGFBP-3 gene results in a nonsynonymous amino acid change, glycine to alanine (46). Although the results of our study suggest that this polymorphism may have an effect on the concentration of circulating IGFBP-3 in cancer-free individuals, the biological mechanisms underlying this relationship are not clear. The amino acid change occurs at residue 32 in the protein structure, a region that has been shown, in fragment analyses, to contain a high-affinity binding region for IGF-1 (80). Furthermore, mutational analyses of the IGFBP-3 protein have suggested that substitution of amino acids at key points within the binding pocket can substantially alter affinity (81, 82). The Gly32Ala polymorphism may modify binding by altering the hydrophobicity in this binding pocket; alanine, although a neutral amino acid, is slightly more hydrophobic than glycine. Because the half-life of IGFBP-3 in circulation is substantially shorter than that of bound (to IGF-1) IGFBP-3, a polymorphism that affects IGF-1 binding may affect the rate of protein degradation and hence the concentration of IGFBP-3 in circulation. Linkage disequilibrium with an as-yet-unknown functional locus provides an alternative explanation for our observation. A single nucleotide polymorphism in the promoter of the IGFBP-3 gene has been reported to be significantly associated with IGFBP-3 levels in previous studies (36, 45, 83), and additional studies examining both polymorphisms within the same population are necessary to evaluate the degree of linkage disequilibrium between these two polymorphisms.

The literature describing the association of BMI and IGF levels has been relatively null (10, 28, 31, 32, 36, 56, 84-88), although our study (in press) and others have observed inverse associations (34, 89, 90). The relationship of IGFs and physical activity is similarly inconsistent, and there was no statistically significant relationship observed in our population (data not shown). However, PMH has been observed to suppress circulating IGF-1 (91-96) and possibly IGFBP-3 (97) in several studies, including our own (data not published). The evaluation of the interaction between IGF genes and lifestyle factors in relation to circulating IGF levels may provide a useful tool to clarifying these associations. Gene-environment interactions can identify subgroups in which lifestyle factors more strongly influence IGF levels, if at all, and may subsequently be modified by changes in lifestyle.

The observation that common variants in the IGF genes can modify the effect of environmental exposures was previously reported by Deal et al. (45). In that study, the authors found that BMI and height were related to IGFBP-3 according to IGFBP-3 genotype. The observed effect modification of PMH use by IGF-1 genotype and by IGFBP-3 genotype in the current study supports a role of gene-environment interactions in circulating IGF determinants. There has been increasing evidence to support cross-talk between estrogen and IGF-1 at several levels (98). Estrogens are also believed to regulate expression of IGFBP-3 and certain IGFBP-3 proteases (99). The gene-environment interaction observed in our study is consistent with both a direct and an indirect relationship of IGFBP-3 in IGF-1/estrogen cross-talk.

Some limitations of this study should be considered. Random degradation of plasma IGF-1 and IGFBP-3 may have introduced nondifferential misclassification in our outcome measure. The half-lives of unbound IGF-1 and IGFBP-3 are relatively short (~10 and 30 minutes, respectively), yet when bound together (along with the acid labile subunit, ~95% of total IGF-1 in circulation exists in this form), half-lives are substantially prolonged. Nonetheless, an earlier study has shown the extended stability of IGF-1 and IGFBP-3 concentrations in samples stored as heparinized whole blood for up to 36 hours before processing (15), and because a large proportion (64%) of our samples were processed within 12 hours after being drawn, we believe it is unlikely that protein degradation substantially biased our estimates.

The specificity of the plasma assays may also have limited the interpretability our results. In its intact form, IGFBP-3 has a molecular weight varying between 40 and 44 kDa (3) and has high affinity for IGF-1. Proteolyzed IGFBP-3 fragments (IGFBP-3 protein fragments remaining after cleavage from IGF-1 by IGFBP proteases) have a lower molecular weight (~30 kDa) and a 20- to 30-fold reduced affinity for IGF-1 (100). The immunoassay used to measure circulating IGFBP-3 did not allow differentiation between these forms. Although some studies have found that IGFBP-3 fragments, even those with little or no demonstrable affinity for IGF-1, may still mediate some of the growth-inhibitory and stimulatory IGF-independent effects (4), dramatic structural and conformation differences between truncated and intact protein might be expected to exhibit substantive differences in vivo, and an assay that measures them in aggregate may not be the best measure. Future studies using more discriminating/specific IGFBP-3 antibody assays may provide more information on the relative frequencies of different isoforms in vivo and their relationship to genetic factors.

In summary, we found that a common single nucleotide polymorphism in exon 1 of the IGFBP-3 gene was significantly associated with variation in circulating IGFBP-3 levels and in the ratio of IGF-1/IGFBP-3 ratio. IGFs are tightly regulated by complex physiologic systems, and single polymorphisms in IGF genes are unlikely to explain the majority of the wide variation in IGF levels observed between individuals. Nonetheless, this does provide evidence that genetic variation is likely one of these influences. Additional studies examining the role of other molecules involved in IGF-1 and IGFBP-3 regulation and signaling, as well as studies evaluating how IGF-1 and IGFBP-3 interact with various modifiable lifestyle factors, may shed more light on the determinants of variation within the reference range. Such information may be important in understanding the etiology and pathogenesis of many common diseases.


   Acknowledgments
 
We thank the Seattle Colorectal Cancer Family Registry (U01 CA074794) for providing data for the analysis and Dr. George McDonald and Rick Lawyer of the FHCRC Cytokine Lab for circulating plasma IGF assays.


   Footnotes
 
Grant support: NIH/National Cancer Institute grant RFA CA-95-011; cooperative agreements with members of the Colon Cancer Family Registry and P.I.s; National Cancer Institute grants U01CA74794, R01CA76366, and R03CA94785; and NIH grant 5-T32-CA09168.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: The content of this article does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CFRs, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government or the CFR.

Received 9/20/04; revised 2/24/05; accepted 3/17/05.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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