Null Results in Brief IGF-I Genetic Variation and Breast Cancer: the Multiethnic Cohort Veronica Wendy Setiawan, 1 Iona Cheng, 1 Daniel O. Stram, 1 Kathryn L. Penney, 2,3,4,6 Loic Le Marchand, 10 David Altshuler, 2,3,4,6,7 Laurence N. Kolonel, 10 Joel Hirschhorn, 2,3,5,9 Brian E. Henderson, 1 and Matthew L. Freedman 2,3,4,6,8 1 Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California; 2 Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts; Departments of 3 Genetics, 4 Medicine, and 5 Pediatrics, Harvard Medical School; 6 Department of Molecular Biology, 7 Diabetes Unit, and 8 Hematology-Oncology, Massachusetts General Hospital; 9 Division of Genetics and Endocrinology, Children’s Hospital and Department of Pediatrics, Boston, Massachusetts; and 10 Cancer Etiology Program, Cancer Research Center of Hawaii, University of Hawaii, Honolulu, Hawaii Introduction The insulin-like growth factor-I (IGF-I ) signaling pathway regulates both cellular proliferation and apoptosis, thereby making it a compelling candidate gene for cancer pathogen- esis. Epidemiologic studies indicate that high levels of circulating IGF-I are associated with elevated risk of breast cancer in premenopausal women (1, 2). Few studies have investigated the role of genetic variation in IGF-I in relation to breast cancer and have focused solely on the polymorphic dinucleotide repeat (CA ) in the promoter region (3-7). Evidence of an effect of this polymorphism on breast cancer risk remains inconsistent (8). To date, no studies have thoroughly characterized common variation in IGF-I and examined this in relation to breast cancer risk. We character- ized genetic variation across the IGF-I locus using a combination of direct (resequencing) and indirect (haplo- type-based approach) methods and then did a large case- control analysis to assess association between this inherited variation and sporadic breast cancer risk in a multiethnic cohort. Materials and Methods Study Population. Detailed information about the Multi- ethnic Cohort – nested breast cancer case-control study has been reported previously (9). A total of 1,615 incident breast cancer cases (21% African American, 7% Native Hawaiian, 26% Japanese, 21% Latina, and 25% White) and 1,962 controls (22% African American, 15% Native Hawaiian, 21% Japanese, 20% Latina, and 22% White) were included in the present study. Controls were women without breast cancer before the cohort entry and without a diagnosis up to April 2002. Controls were frequency matched to cases by age and ethnicity. IGF-I Characterization. The details of exon resequencing, linkage disequilibrium characterization and tagging single nucleotide polymorphism (tSNP) selection have been de- scribed (10). Briefly, IGF-I exons were sequenced in 95 advanced cases of breast cancer (n = 19 per racial-ethnic group). No missense SNP was identified during this sequenc- ing effort. To characterize the linkage disequilibrium patterns, 64 SNPs (1 SNP/2.4 kb) spanning 156 kb were genotyped in a multiethnic panel of 349 unrelated women with no history of cancer. Haplotype blocks (regions of strong linkage disequi- librium) were defined using the methods of Gabriel et al. (11). Twenty-nine tSNPs were selected to predict the common haplotypes with high probability (average R h 2 = 0.90) and 35 unmeasured SNPs (i.e., SNPs not genotyped in case-control samples). The method of predicting unmeasured SNPs has been described elsewhere (10). Case-Control Genotyping. All SNPs were genotyped by Taqman assay (Applied Biosystems, Foster City, CA). Taqman primers, probes, and conditions for genotyping assays are available upon request. The average genotyping success rate was 97%. All genotyping was done with laboratory personnel blinded to case-control status of the samples, which included quality control samples for validation. Concordance for quality control samples was 99.7%. Statistical Analysis. We used the m 2 test to assess departures of the genotype distribution from Hardy-Weinberg equilibrium among controls in each ethnic group. All tSNPs conformed to Hardy-Weinberg equilibrium at P < 0.01 level. Methods for haplotype estimation and case-control analysis were previously described (9). A likelihood ratio test was done to globally test for haplotype effect in each block. Uncondi- tional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals for haplotype-specific and genotype-specific risks, adjusting for age and ethnicity. We also did multivariate analyses with established breast cancer risk factors included in the models (9). All P s are two sided. SAS version 8.2 (SAS Institute, Cary, NC) was used for all analyses. Results We tested both haplotypes and single tSNPs to maximize the likelihood that we have captured all of the unmeasured variation at the locus. Four regions of strong linkage disequilibrium (haplotype blocks), ranging from 11 to 60 kb, were identified, and 5 to 11 common haplotypes (i.e., frequency z 5%) were observed within each block. The 172 Cancer Epidemiol Biomarkers Prev 2006;15(1). January 2006 Cancer Epidemiol Biomarkers Prev 2005;15(1):172 – 4 Received 8/16/05; revised 10/10/05; accepted 11/8/05. Grant support: National Cancer Institute grants CA54281 and CA63464. 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. Requests for reprints: Matthew L. Freedman, Massachusetts General Hospital, Center for Human Genetic Research, Simches Research Building, 185 Cambridge Street, Boston, MA 02114. E-mail: freedman@broad.mit.edu. Copyright D 2006 American Association for Cancer Research. doi:10.1158/1055-9965.EPI-05-0625 on July 14, 2016. © 2006 American Association for Cancer Research. cebp.aacrjournals.org Downloaded from