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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2013 December 1.
Published in final edited form as:
PMCID: PMC3518741

Variation in genes related to obesity, weight and weight change and risk of contralateral breast cancer in the WECARE Study population



Body mass index (BMI), a known breast cancer risk factor, could influence breast risk through mechanistic pathways related to sex hormones, insulin resistance, chronic inflammation and altered levels of adipose derived hormones. Results from studies of the relationship between BMI and second primary breast cancer have been mixed. To explore the relationship between BMI and asynchronous contralateral breast cancer (CBC), we examined whether variants in genes related to obesity, weight and weight change are associated with CBC risk.


Variants in twenty genes (182 single nucleotide polymorphisms) involved in adipose tissue metabolism, energy balance, insulin resistance and inflammation, as well as those identified through genome-wide association studies of BMI and type II diabetes were evaluated. We examined the association between variants in these genes and the risk of CBC among Caucasian participants (643 cases with CBC and 1,271 controls with unilateral breast cancer) in the population-based Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study using conditional logistic regression.


After adjustment for multiple comparisons, no statistically significant associations between any variant and CBC risk were seen. Stratification by menopausal or estrogen receptor status did not alter these findings.


Among women with early onset disease who survive a first breast cancer diagnosis there was no association between variation in obesity-related genes and risk of CBC.


Genetic variants in genes related to obesity are not likely to strongly influence subsequent risk of developing a second primary breast cancer.

Keywords: genetic variation, obesity, weight, weight change, contralateral breast cancer


Studies examining the relationship between body mass index (BMI) and second primary breast cancer have produced mixed results (1, 2). We recently showed that in a population of women with early onset disease (diagnosed before age 55 years), obese (BMI ≥30kg/m2) postmenopausal women with estrogen receptor (ER)-negative breast cancer had more than 5-fold greater risk of asynchronous contralateral breast cancer risk (CBC) than women of normal weight (BMI <25 kg/m2) with ER-negative first tumors (RR=5.64, 95% CI 1.76, 18.1) (2). BMI could influence CBC risk through mechanistic pathways related to sex hormones, insulin resistance, chronic inflammation and altered levels of adipose derived hormones (3). The impact of variation in obesity-related genes on CBC risk and breast cancer risk in general is not well known. To further explore the relationship between BMI and risk of CBC we examined the association between variants in genes related to obesity (weight, weight change, type 2-diabetes, adipose tissue metabolism) and CBC risk in a population-based study of breast cancer survivors.

Materials and Methods

The Women’s Environmental Cancer and Radiation Epidemiology (WECARE) Study is a multi-center, case-control study where cases are women with asynchronous CBC and controls are women with unilateral breast cancer (UBC). Recruitment, eligibility criteria, data and biospecimen collection, and genotype methods have been described (2, 4).

Eight genes were selected for evaluation based on genome-wide association studies (GWAS) of BMI, weight change, waist circumference and type 2-diabetes (FTO, TCF7L2, TMEM18, NEGR1, MC4R, HHEX, IGF2BP2, PPARG) (57). Twelve candidate genes were selected based on biological plausibility and known involvement with adipose tissue metabolism and obesity (LEP, LEPR, ADIPOQ, ADIPOR1, ADIPOR2, HIF1A, PLAU, PLAUR, SERPINE1, IGF2BP1) (3) or a functional relationship with both obesity and DNA repair (IRS2, FOXO1) (8). SNPs identified from GWAS were genotyped directly, whereas SNPs in candidate genes were selected using a tagSNP approach, supplemented with potentially functionally relevant SNPs from dbSNP (4). A total of 194 SNPs in 20 genes was genotyped.

Of the 2,107 WECARE Study participants, four were excluded because they did not consent to genotyping. We further excluded from analysis 10 SNPs with <95% call rate, one monomorphic SNP, one SNP deviating from Hardy-Weinberg equilibrium (p<0.001) and 20 subjects with >10% missing genotypes. To minimize the potential influence of ancestral differences in genotype frequencies, analyses were restricted to Caucasian women (n=169 excluded). After quality control, analyses were conducted for 182 SNPs in 643 CBC cases and 1,271 UBC controls. Using HapMap Phase II release 24, these remaining variants captured 55% of the SNPs in LEP, 97% in LEPR, 100% in ADIPOQ, 93% in ADIPOR1, 96% in ADIPOR2, 96% in HIF1A, 75% in PLAU, 75% in PLAUR, 72% in SERPINE1, 87% in IGFBP1, 82% in IRS2, and 84% in FOXO1 (r2 > 0.80).

Statistical Analysis

Rate ratios (RR) and 95% confidence intervals (CI) were estimated using conditional logistic regression by fitting a log-additive model, adjusting for age at first breast cancer diagnosis and accounting for the sampling probabilities of the UBC controls (described previously (9)). A conservative Bonferroni correction was used to determine the multiple comparison cut-point (α=0.0003, obtained from (0.05/182 SNPs)), i.e., the value for which results were considered statistically significant. The PACT method of adjusting for multiple comparisons, which takes into account linkage disequilibrium between nearby markers, was also applied (10). We also conducted analyses stratified by menopausal status at first diagnosis, reference date (date of CBC diagnosis in cases and corresponding date in matched controls) and estrogen receptor (ER) status of the first primary tumor.


After adjustment for multiple comparisons, no statistically significant association between any genetic variant and risk of CBC was seen (Table 1). Similarly, no associations were seen in analyses stratified by menopausal status at first diagnosis or at reference date, or ER-status of the first primary breast cancer (results not shown).

Table 1
Association between obesity-related variants and risk of contralateral breast cancer in the WECARE Study


The risk of CBC was not associated with any of the variants of the 20 selected genes involved in adipose tissue metabolism, energy balance, insulin resistance and inflammation or those identified through GWAS of BMI and type 2-diabetes. The primary limitation of the analysis is the limited sample size available for subgroup analyses (e.g., when stratifying by ER-status). We also had limited information on the ER status of second cancers in cases and therefore were unable to take this into account. A tagSNP approach was not taken for the genes identified by GWAS, and the coverage of some candidate genes was reduced after quality control. Thus, it is possible that un-typed variants are associated with risk. Further, other genes in these candidate pathways might be associated with CBC risk. Nonetheless, the results of this study suggest that among women who survive a first breast cancer diagnosed before age 55 years, genetic variation in obesity-related genes is not likely to influence subsequent risk of second primary breast cancer.


Financial support: This research was funded by the National Cancer Institute at the National Institutes of Health (R01CA114236, U01CA083178, R01CA129639).

We thank the women who participated in the WECARE Study.

The WECARE Study Collaborative Group

Memorial Sloan Kettering Cancer Center (New York, NY): Jonine L. Bernstein Ph.D. (WECARE Study P.I.), Colin Begg Ph.D., Jennifer D. Brooks Ph.D., Marinela Capanu Ph.D., Xiaolin Liang M.D., Anne S. Reiner M.P.H., Irene Orlow Ph.D, Robert Klein Ph.D. (Co-investigator), Ken Offit M.D. (Co-investigator); Meghan Woods M.P.H.;

Beckman Research Institute, City of Hope National Medical Center (Duarte, CA): Leslie Bernstein Ph.D. (sub-contract P.I.),

Cancer Prevention Institute of California (Fremont, CA): Esther M. John Ph.D. (Subcontract PI);

Danish Cancer Society (Copenhagen, Denmark): Jørgen H. Olsen M.D. DMSc. (Sub-contract P.I.), Lene Mellemkjær Ph.D.;

Fred Hutchinson Cancer Research Center (Seattle, WA): Kathleen E. Malone Ph.D. (Subcontract P.I.);

International Epidemiology Institute (Rockville, MD) and Vanderbilt University (Nashville, TN): John D. Boice Jr. Sc.D. (Sub-contract P.I.);

National Cancer Institute (Bethesda, MD): Daniela Seminara Ph.D. M.P.H;

New York University (New York, NY): Roy E. Shore Ph.D., Dr.P.H. (Sub-contract P.I.);

Samuel Lunenfeld Research Institute, Mount Sinai Hospital (Toronto, Canada): Julia Knight, Ph.D. (Sub-contract P.I.), Anna Chiarelli Ph.D. (Co-Investigator);

Translational Genomics Research Institute (TGen) (Phoenix, AZ): David Duggan Ph.D. (Sub-contract P.I.);

University of Iowa (Iowa City, IA): Charles F. Lynch M.D., Ph.D. (Sub-contract P.I.), Jeanne DeWall M.A.

University of Southern California (Los Angeles, CA): Robert W. Haile Dr.P.H. (Sub-contract P.I.), Daniel Stram Ph.D.(Co-Investigator), Duncan C. Thomas Ph.D. (Co-Investigator), Anh T. Diep (Co-Investigator), Shanyan Xue M.D., Nianmin Zhou, M.D, Evgenia Ter-Karapetova

University of Texas, M.D. Anderson Cancer Center (Houston, TX): Marilyn Stovall Ph.D. (Sub-contract P.I.), Susan Smith M.P.H. (Co-Investigator);

University of Virginia (Charlottesville, VA): Patrick Concannon, Ph.D. (Sub-contract P.I.), Sharon Teraoka, Ph.D. (Co-Investigator),


Conflicts of Interest: None


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