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1 University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California; 2 IARC, Lyon, France; and 3 Cancer Research Center of Hawaii, University of Hawaii, Honolulu, Hawaii
Requests for reprints: Katherine A. DeLellis, Department of Preventive Medicine, University of Southern California/Norris Comprehensive Cancer Center, 1441 Eastlake Avenue, MS 44, Room 4411, Los Angeles, CA 90033. Phone: 323-865-3995; Fax: 323-865-0127. E-mail: delellis{at}usc.edu
| Abstract |
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| Introduction |
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Building on previous work on female participants in the Multiethnic Cohort (MEC), which showed that plasma IGF-I levels varied significantly across racial/ethnic groups (15), we did a cross-sectional study on a large, random sample of participants in a population-based cohort study to determine which lifestyle and dietary factors are associated with plasma levels of IGF-I and IGFBP-3 in each sex, whether we could validate an independent racial/ethnic relationship with IGF levels after adjustment for potential confounders, and whether trends in these levels across racial/ethnic groups (African American, Japanese, Native Hawaiian, Latino, and White) lie in parallel with incidence rates of colorectal, breast, and prostate cancers in the underlying cohort.
| Materials and Methods |
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5,000 randomly selected participants after stratification on sex and race/ethnicity. These participants are being used as controls in nested case-control studies. The draw was completed in the morning, typically at the person's home, after informed consent was obtained. Handling of samples was achieved with attention to minimization of time between draw and processing. Ninety percent of samples were processed within 4 hours of the blood draw, and 98% were processed within 24 hours of draw. Sodium heparin was used as an anticoagulant in the blood collection tubes. The participation rate for providing a blood sample was 66% and did not vary greatly across different racial/ethnic groups. Details of the MEC study have been published previously (16). Incident cancer diagnoses are identified through annual linkage of the cohort with files of the Hawaii Tumor Registry and the Cancer Surveillance Program in Los Angeles (both are Surveillance, Epidemiology, and End Results registries and include annual death certificate searches within their respective states for possible missed cases). Linkage is also done annually with the California Tumor Registry and the Hawaii and California death certificate files and periodically with the National Death Index.
We measured plasma IGF-I and IGFBP-3 in a random sample of 1,000 MEC blood subcohort participants [100 for each of 10 sex-racial/ethnic groups with equal representation of each 5-year age group at blood draw (>45 years for men and >55 years for women)]. Women who reported that they were taking estrogen replacement therapy at the time of blood draw were excluded. There were 955 subjects who had complete IGF-I and IGFBP-3 measurements, of whom 926 had complete questionnaire data.
IGF-I and IGFBP-3 Measurements in Plasma
Samples were analyzed blind as to race/ethnicity and sex of the participants. To reduce the effect of laboratory variability, each analytic batch included equal numbers of subjects from each sex-racial/ethnic group. IGF-I and IGFBP-3 were measured by ELISAs from Diagnostic System Laboratories (Webster, TX). IGF-I assays included an acid-ethanol precipitation of IGF-I binding proteins to avoid interference of IGFBPs with the IGF-I assay. The average overall intrabatch coefficients of variation were 6.0% and 5.2% for IGF-I and IGFBP-3, respectively. The average overall interbatch coefficients of variation were 13.9% and 10.6% for IGF-I and IGFBP-3, respectively.
Data Analysis
ANOVA and analysis of covariance were used to test for differences in crude and adjusted mean IGF-related protein levels by sex-racial/ethnic group and covariate level. We assumed homogeneity of effects across racial/ethnic groups and did not correct for differences in the sampling proportion used for each group. The hormone measurements were transformed via the natural log to produce the best approximate normal distribution. These values have been transformed back to normal physiologic levels in the tables for the purpose of presentation. Diet intake data were adjusted for total calorie intake by the calculation of nutrient densities. Nutrient densities were calculated by multiplying the daily diet component intake in grams by the inverse of total daily energy intake in calories (17). Means presented are least-squares means (LS means). Multiple linear regressions were done to determine which covariates were associated with IGF-I, IGFBP-3, and IGF-I-IGFBP-3 molar ratio (IGFMR) levels. We used past reports (18-23) and the known biology about the IGF-I pathway (for review, see refs. 24, 25) to guide the selection of variables to be considered in the models. The R2 selection method was used in conjunction with Mallow's Cp to identify important associated variables. Plots of the Cp statistic, as well as examination of incremental changes in the R2, assisted in the final determination of variables for inclusion in the models. Although the sampling proportions were not equal for each racial/ethnic group, we adjusted the models for this variable and therefore expect the results to be generalizable to the entire cohort. All analyses were done in SAS version 9 (SAS Institute, Cary, NC).
| Results |
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The results of a sex-stratified multiple regression of IGF-I, IGFBP-3, and IGFMR on race/ethnicity, age, height, weight, BMI, parity, age at menarche, age at menopause, physical activity, smoking, and dietary variables indicated that age, race/ethnicity, and BMI were statistically significantly associated with IGF-I and IGFBP-3 among women (Table 3). In addition, alcohol was directly associated with IGFBP-3 in this group. The R2 for the overall model in women was 0.08 for IGF-I and 0.16 for IGFBP-3. Race and BMI only were statistically significantly associated with IGFMR in women.
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We saw some evidence of correlation between LS mean IGF-I levels and colon cancer incidence rates within the MEC by race/ethnicity in both sexes (see Table 4). For example, the African American women have the highest LS mean IGF-I level (160 ng/mL) and the highest colon cancer rate (139 cases per 100,000). White and Latino women rest at the low end of both measures. No other cancer incidence comparison across races/ethnicities seemed to have any clear relationship in this crude analysis.
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| Discussion |
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Several factors have been investigated as potential determinants of the IGF-related proteins. The extensive epidemiologic literature on the determinants of IGF-I and IGFBP-3 has been reviewed recently (24, 25). Dietary findings have pointed to associations between improved nutritional status and increasing circulating IGF-I and IGFBP-3 levels, the exact drivers of these associations remain elusive possibly due to difficulty in deciphering independent effects among highly correlated and inexactly measured covariates. In this analysis, our primary aims were to test in our multiethnic population the reproducibility of our previous racial/ethnic finding and to investigate the cross-sectional relationship between plasma IGF-I and IGFBP-3 with various lifestyle and dietary factors, which had been previously implicated in determining circulating levels of these proteins.
After adjustment for possible confounders, IGF-I and IGFBP-3 levels varied significantly by racial/ethnic group among women in our data. Among men, IGFBP-3 differed strongly across racial/ethnic groups, but IGF-I did not. In a previous article, we reported that race/ethnicity was independently associated with plasma IGF-I levels in women (15). We confirmed that circulating IGF-I levels in postmenopausal women were significantly lower in Latino women compared with African American, Native Hawaiian, and Japanese women. Few past studies had sufficient power to test for differences in IGF levels across race/ethnicity. However, several studies have suggested that Latino neonates, girls, and premenopausal women have lower IGF-I compared with Whites or African Americans (26-28). In contrast to our finding in women of a higher mean IGF-I level for African Americans compared with Whites, Chang et al. (29) have reported no statistically significant difference in mean serum IGF-I between age-matched and weight-matched postmenopausal African American and White women. Chang et al. (29) reported no statistically significant difference in age-adjusted median IGF-I levels in middle-aged Caucasian, Asian, and African American men (224, 208, and 205 ng/mL, respectively; Pdiff = 0.08) but found a statistically significant difference in IGFBP-3 levels across races (3,868, 3,926, and 3,373 ng/mL, respectively; Pdiff = 0.01). These higher IGFBP-3 levels in White men compared with African American men agree with our findings, and the cause of this variation across racial/ethnic groups clearly warrants further investigation as it may shed light on the relationships between IGF proteins and disease incidence.
Our findings were also consistent with the reported relationships of these IGF-related proteins with sex and age. In our data, women had statistically significantly lower plasma IGF-I and higher IGFBP-3 than men independent of race, age, and BMI. IGF-I and IGFBP-3 declined linearly (log-linearly) with age. These findings agree with previous reports (18, 19, 23, 29). In contrast, the association between these proteins and body size seemed to be complex. In our data, IGF-I and IGFBP-3 seemed to have sex-specific relationships with body size. IGF-I seemed to have a direct correlation with BMI in women until some critical BMI point at which IGF-I began to decline, a nonlinear relationship that Lukanova et al. also described in a Swedish cohort (30). However, unlike in the MEC, this pattern was also observed in males in this Swedish cohort. In addition, we found that height is better correlated with IGF-I and IGFBP-3 than BMI in men. The literature on this topic is not consistent possibly because of this nonlinear, sex-dependent relationship (20, 30, 31). Differences in body fat distribution, which may be driven in large part by genetics (32-34), may contribute to differences in hormonal regulation of the IGF system. Further investigation of these relationships may clarify regulatory pathways for IGF and eventually explain inconsistencies in IGF-cancer incidence relationships.
Potential lifestyle determinants of IGF-I and IGFBP-3 include physical activity, smoking, and alcohol, calorie, fat, and protein intakes (24, 35). Among women in our data, the only association found with diet was an inverse one between alcohol and IGFBP-3. In the Rancho Bernardo Study, IGF-I showed a relationship in the opposite direction with alcohol intake among women (18). In men, we found other associations in our data. Fat intake from meat sources and current smoking seemed to be inversely associated with IGF-I levels. Fat intake from meat sources and low-fat milk were also inversely associated with IGFBP-3. In contrast, in a cohort of U.S. men, Ma et al. (36) found a direct association between low-fat milk intake and both IGF-I and IGFBP-3 levels and no association with red meat intake. Thus, the data on diet and IGF proteins are inconsistent. The relationship between smoking and IGF levels is also not clear. In five studies that addressed smoking and IGF-I, two found a positive association, one found an inverse association, as we did in women, and two found no association. The study that addressed smoking and IGFBP-3 reported an inverse association between current smoking and IGFBP-3 levels (24).
The main result from this study was that, overall, our models did not explain much of the variance in plasma IGF-I or IGFBP-3 as indicated by the low R2 values. Previous investigators have reported similarly low R2 values (29), which may be indicative of an as yet ill-defined set of IGF-I and IGFBP-3 determinants. Either we have poorly measured or analyzed the relevant covariates or we have failed to identify the true determinants. Measurement error may have attenuated the relationships under study, although most of the variables measured in the MEC that we included in this analysis have been valid in previous studies (16, 37). Another potential explanation for the low explanatory value of our models is that IGF-I and IGFBP-3 levels are largely driven by factors we have not measured in this study, such as genetic factors. Harrela et al. (38) reported that the proportions of variance in IGF-I and IGFBP-3 attributable to genetic effects were 38% and 60%, respectively. The genetic contribution to interindividual variation in circulating IGF-I and IGFBP-3 levels merits further study. A genetic marker has not yet been confirmed, but inherited variants in the growth hormone gene (39), IGF-I (15, 40), and the gene for IGFBP-3 (41) have been studied for possible association with adult IGF hormone levels.
A potential limitation of our study is that it relied on a single measurement of IGF-I and IGFBP-3 to represent long-term circulating levels. Although many studies have shown measurable interindividual variation in IGF-I and IGFBP-3 (42-45), data from the Rancho Bernardo Study suggest that the intraindividual variation in IGF-I is minimal (45) and that a single measurement may be adequate. It is also possible that adult levels of these peptides are, at least partially, determined early in life. Our finding of an association with height in men suggests that factors (possibly nutritional) during adolescence may have long-lasting effect on IGF-I hormone levels.
If differences in IGF-I and IGFBP-3 levels are related to the risk of breast, prostate, and colon cancers, as has been hypothesized, then one might expect mean levels of these proteins to correlate with racial/ethnicspecific cancer incidence rates in the MEC. The correlation between IGF-I levels and colon cancer incidence rates across racial/ethnic groups shown here provided support for this hypothesis. The cross-sectional nature of the data precluded our drawing conclusions about causation; however, we plan to use future analyses to follow up on these findings. In future work investigating the IGF system and cancer, it will be of value to use the blood samples that are being prospectively collected from the MEC to carry out nested case-control studies.
It is unclear whether the risk factors found here to be associated with IGF-I and IGFBP-3 have confounded previous association studies, leading to the inconsistency in the epidemiologic data on circulating levels of these proteins and cancer risk. However, it would be prudent to adjust for these factors in ongoing and future studies. Because of the relatively weak differences in IGF-I and IGFBP-3 across racial/ethnic groups, it seems unlikely that the identified determinants of these proteins would be a major source of population stratification in studies with significant admixture. However, we intend to further explore racial/ethnic differences in the determinants of IGF-I and IGFBP-3 levels in the MEC as additional data become available.
| Acknowledgments |
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| Footnotes |
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Received 12/10/03; revised 4/ 6/04; accepted 4/26/04.
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