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. Author manuscript; available in PMC: 2013 Dec 1.
Published in final edited form as: Cancer Epidemiol Biomarkers Prev. 2012 Oct 2;21(12):2261–2267. doi: 10.1158/1055-9965.EPI-12-1036

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

Jennifer D Brooks 1, Leslie Bernstein 2, Sharon N Teraoka 3, Julia A Knight 4, Lene Mellemkjær 5, Esther M John 6, Kathleen E Malone 7, Anne S Reiner 1, Charles F Lynch 8, Patrick Concannon 3, Robert W Haile 9, Jonine L Bernstein 1, for the WECARE Study Collaborative Group
PMCID: PMC3518741  NIHMSID: NIHMS410955  PMID: 23033454

Abstract

Background

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.

Methods

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.

Results

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.

Conclusion

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.

Impact

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

Introduction

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) (5–7). 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.

Results

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

SNP Gene Chr Coordinate Alleles MAFa HWEb RRc 95% CI P value
rs182052 ADIPOQ 3 188043475 G>A 0.35 0.88 1.0 0.8, 1.1 0.59
rs16861205 ADIPOQ 3 188044327 G>A 0.07 0.62 0.9 0.7, 1.2 0.61
rs822391 ADIPOQ 3 188046496 T>C 0.2 0.42 1.0 0.8, 1.2 0.83
rs16861210 ADIPOQ 3 188049191 G>A 0.09 0.16 1.0 0.8, 1.3 0.97
rs822394 ADIPOQ 3 188049421 C>A 0.19 0.35 1.0 0.9, 1.3 0.75
rs12495941 ADIPOQ 3 188050873 G>T 0.34 0.68 1.1 0.9, 1.3 0.16
rs7649121 ADIPOQ 3 188051478 A>T 0.18 0.55 1.0 0.8, 1.2 0.77
rs9877202 ADIPOQ 3 188052300 A>G 0.001 0.97 0.5 0.1, 5.1 0.54
rs17366568 ADIPOQ 3 188053146 G>A 0.13 0.31 0.9 0.7, 1.1 0.39
rs1501299 ADIPOQ 3 188053816 C>A 0.27 0.79 1.1 0.9, 1.3 0.18
rs3821799 ADIPOQ 3 188054179 C>T 0.47 0.56 0.9 0.8, 1.1 0.19
rs3774261 ADIPOQ 3 188054252 G>A 0.4 0.28 1.0 0.9, 1.2 0.80
rs17366743 ADIPOQ 3 188054782 T>C 0.03 0.14 0.8 0.5, 1.2 0.28
rs1063539 ADIPOQ 3 188058085 G>C 0.13 0.24 0.9 0.8, 1.2 0.57
rs7539542 ADIPOR1 1 201176596 C>G 0.33 0.22 1.1 0.9, 1.2 0.51
rs2275735 ADIPOR1 1 201182177 G>A 0.04 0.67 0.8 0.5, 1.2 0.30
rs12045862 ADIPOR1 1 201183428 C>T 0.28 0.34 1.0 0.8, 1.2 0.90
rs12733285 ADIPOR1 1 201188662 C>T 0.3 0.39 1.0 0.9, 1.2 0.90
rs10494839 ADIPOR1 1 201188816 T>C 0.29 0.92 1.0 0.8, 1.1 0.65
rs10753929 ADIPOR1 1 201189800 C>T 0.12 0.70 1.1 0.9, 1.4 0.31
rs12132093 ADIPOR1 1 201192735 G>A 0.009 0.76 1.4 0.7, 3.0 0.34
rs7514221 ADIPOR1 1 201193135 T>C 0.42 0.66 1.1 0.9, 1.3 0.39
rs11061925 ADIPOR2 12 1673494 C>T 0.32 0.49 1.0 0.8, 1.1 0.71
rs11061935 ADIPOR2 12 1684034 A>G 0.15 0.62 1.0 0.8, 1.2 0.69
rs7975600 ADIPOR2 12 1685512 A>T 0.16 0.90 1.0 0.8, 1.2 0.81
rs12826079 ADIPOR2 12 1696816 C>T 0.08 0.57 0.8 0.6, 1.1 0.27
rs11061946 ADIPOR2 12 1698787 C>T 0.07 0.33 1.1 0.8, 1.5 0.54
rs10773984 ADIPOR2 12 1701553 G>A 0.02 0.08 1.2 0.7, 1.9 0.49
rs11612383 ADIPOR2 12 1701615 G>A 0.32 0.91 1.0 0.8, 1.1 0.62
rs1058322 ADIPOR2 12 1707239 C>T 0.33 0.82 1.0 0.9, 1.2 0.95
rs9300298 ADIPOR2 12 1736455 T>A 0.5 0.11 1.0 0.8, 1.1 0.68
rs7967137 ADIPOR2 12 1740785 T>C 0.14 0.46 1.1 0.8, 1.3 0.69
rs12828908 ADIPOR2 12 1749645 A>G 0.33 0.02 1.0 0.8, 1.1 0.52
rs11061979 ADIPOR2 12 1752849 T>G 0.02 0.77 0.7 0.4, 1.1 0.13
rs12829901 ADIPOR2 12 1753638 G>A 0.02 0.47 0.6 0.3, 1.1 0.09
rs4140993 ADIPOR2 12 1759542 A>C 0.006 0.83 0.4 0.1, 1.3 0.14
rs12824519 ADIPOR2 12 1761788 G>A 0.02 0.47 0.6 0.3, 1.1 0.08
rs1044471 ADIPOR2 12 1767216 C>T 0.47 0.00 1.0 0.9, 1.2 0.70
rs9532558 FOXO1 13 40031014 T>C 0.02 0.37 0.5 0.3, 0.9 0.03
rs2755209 FOXO1 13 40035803 A>C 0.39 0.97 1.1 0.9, 1.3 0.33
rs2721068 FOXO1 13 40037711 T>C 0.26 0.82 1.0 0.9, 1.2 0.73
rs2180961 FOXO1 13 40038043 T>A 0.16 0.11 1.1 0.9, 1.3 0.47
rs2755212 FOXO1 13 40041147 T>C 0.01 0.69 1.0 0.5, 2.1 0.98
rs2755213 FOXO1 13 40044300 T>C 0.1 0.31 0.9 0.7, 1.2 0.49
rs2701870 FOXO1 13 40053775 G>C 0.07 0.84 0.9 0.7, 1.3 0.70
rs2951787 FOXO1 13 40059769 C>T 0.4 0.17 0.9 0.8, 1.1 0.46
rs2984121 FOXO1 13 40059978 C>G 0.18 0.74 1.0 0.8, 1.2 0.75
rs4429172 FOXO1 13 40087142 C>A 0.31 0.79 1.0 0.9, 1.2 0.74
rs12876443 FOXO1 13 40094876 T>C 0.1 0.00 1.1 0.9, 1.4 0.48
rs12866643 FOXO1 13 40110731 A>C 0.01 0.60 1.3 0.7, 2.4 0.36
rs12874490 FOXO1 13 40115733 G>C 0.01 0.72 2.1 1.1, 3.8 0.02
rs1334241 FOXO1 13 40121109 G>A 0.21 0.34 1.1 0.9, 1.3 0.44
rs9549248 FOXO1 13 40121395 A>G 0.002 0.93 0.0 0.98
rs9603776 FOXO1 13 40121885 C>T 0.03 0.01 1.1 0.7, 1.8 0.74
rs2297627 FOXO1 13 40131930 T>C 0.31 0.80 1.0 0.9, 1.2 0.63
rs6499640 FTO 16 52327177 A>G 0.41 0.31 0.9 0.8, 1.1 0.24
rs9940646 FTO 16 52358129 C>G 0.42 0.81 1.1 0.9, 1.3 0.34
rs1421085 FTO 16 52358454 T>C 0.39 0.94 1.1 0.9, 1.3 0.31
rs1121980 FTO 16 52366747 C>T 0.42 0.93 1.1 0.9, 1.3 0.35
rs8050136 FTO 16 52373775 C>A 0.39 0.75 1.1 0.9, 1.3 0.33
rs9939609 FTO 16 52378027 T>A 0.39 0.70 1.1 0.9, 1.3 0.31
rs16952624 FTO 16 52480338 C>T 0.004 0.99 0.0 0.98
rs7190492 FTO 16 53828752 G>A 0.37 0.51 1.0 0.9, 1.2 0.94
rs1111875 HHEX 10 94452861 G>A 0.41 0.94 1.0 0.8, 1.1 0.61
rs5015480 HHEX 10 94455538 C>T 0.41 0.99 1.0 0.8, 1.1 0.63
rs1951795 HIF1A 14 61241178 C>A 0.18 0.65 1.0 0.8, 1.2 0.82
rs10135579 HIF1A 14 61242939 A>G 0.05 0.01 0.8 0.6, 1.1 0.21
rs10129270 HIF1A 14 61251706 G>A 0.06 0.17 1.0 0.7, 1.4 0.98
rs4899056 HIF1A 14 61259283 C>T 0.1 0.37 1.0 0.8, 1.2 0.79
rs17099141 HIF1A 14 61263991 G>A 0.02 0.45 0.7 0.4, 1.2 0.23
rs2301111 HIF1A 14 61269953 C>G 0.2 0.54 1.0 0.9, 1.3 0.69
rs966824 HIF1A 14 61270270 C>T 0.04 0.47 1.0 0.7, 1.5 0.98
rs8012370 HIF1A 14 61274047 G>C 0.006 0.83 0.8 0.3, 2.1 0.57
rs10138153 HIF1A 14 61274927 C>T 0.006 0.83 0.8 0.3, 2.1 0.57
rs2301113 HIF1A 14 61276300 A>C 0.22 0.65 1.0 0.8, 1.2 0.99
rs11549465 HIF1A 14 61277309 C>T 0.1 0.63 1.1 0.9, 1.4 0.36
rs7143164 HIF1A 14 62166755 G>C 0.09 0.38 0.9 0.7, 1.2 0.63
rs9912108 IGF2BP1 17 44437242 T>C 0.0004 0.99 1.5 0.1, 26.0 0.76
rs17635703 IGF2BP1 17 44443154 A>C 0.05 0.81 1.0 0.7, 1.3 0.77
rs6504592 IGF2BP1 17 44445296 C>G 0.06 0.01 0.8 0.6, 1.1 0.24
rs9906710 IGF2BP1 17 44446281 C>A 0.36 0.36 1.1 0.9, 1.3 0.34
rs17708997 IGF2BP1 17 44457036 A>G 0.09 0.34 1.2 0.9, 1.6 0.13
rs8073244 IGF2BP1 17 44470036 C>T 0.15 0.68 1.1 0.9, 1.3 0.63
rs11872073 IGF2BP1 17 44474133 G>A 0.03 0.22 0.6 0.4, 1.1 0.10
rs4265867 IGF2BP1 17 44478822 G>A 0.02 0.40 1.2 0.7, 1.9 0.54
rs2969 IGF2BP1 17 44483245 C>T 0.26 0.70 0.9 0.8, 1.1 0.50
rs11655950 IGF2BP1 17 44484119 G>A 0.32 0.98 1.1 0.9, 1.3 0.43
rs3744085 IGF2BP1 17 44486899 T>C 0.49 0.10 1.1 0.9, 1.2 0.45
rs4402960 IGF2BP2 3 186994380 G>T 0.33 0.06 1.0 0.9, 1.2 0.88
rs9515119 IRS2 13 109207336 A>C 0.33 0.08 0.9 0.8, 1.1 0.28
rs7996317 IRS2 13 109207931 A>C 0.0008 0.98 1.0 0.1, 6.4 0.96
rs754204 IRS2 13 109209568 C>T 0.48 0.72 1.0 0.9, 1.2 0.65
rs913949 IRS2 13 109209796 A>G 0.19 0.78 1.1 0.9, 1.3 0.60
rs12583454 IRS2 13 109214505 G>A 0.02 0.59 0.6 0.4, 1.1 0.12
rs2241745 IRS2 13 109220531 A>G 0.14 0.46 1.1 0.9, 1.4 0.43
rs9559648 IRS2 13 109221795 C>T 0.31 0.71 1.0 0.9, 1.2 0.82
rs7323191 IRS2 13 109222075 A>T 0.15 0.07 1.1 0.8, 1.3 0.66
rs7999797 IRS2 13 109224000 A>G 0.46 0.32 1.0 0.8, 1.1 0.69
rs11841502 IRS2 13 109225988 G>A 0.34 0.31 1.0 0.9, 1.2 0.79
rs7997595 IRS2 13 109228768 C>G 0.15 0.55 1.1 0.9, 1.3 0.56
rs11618950 IRS2 13 109232310 G>A 0.17 0.20 1.0 0.8, 1.2 0.88
rs4773092 IRS2 13 109233953 G>A 0.4 0.79 1.1 0.9, 1.3 0.19
rs4731426 LEP 7 127669305 C>G 0.47 0.62 0.9 0.8, 1.1 0.34
rs11763517 LEP 7 127677297 T>C 0.5 0.74 1.0 0.9, 1.2 0.98
rs11760956 LEP 7 127678322 G>A 0.39 0.12 1.0 0.8, 1.1 0.54
rs3828942 LEP 7 127681540 G>A 0.42 0.69 1.0 0.9, 1.15 0.91
rs17151919 LEP 7 127681827 G>A 0.0008 0.98 0.0 0.98
rs12145690 LEPR 1 65659600 A>C 0.45 0.26 1.1 0.9, 1.2 0.54
rs4655802 LEPR 1 65660818 A>G 0.41 0.10 1.0 0.8, 1.1 0.69
rs9436739 LEPR 1 65663286 T>A 0.13 0.79 1.0 0.8, 1.2 0.81
rs9436298 LEPR 1 65663770 T>A 0.007 0.81 0.6 0.2, 1.9 0.41
rs9436740 LEPR 1 65664488 A>T 0.28 0.43 1.1 0.9, 1.3 0.49
rs3790433 LEPR 1 65666929 G>A 0.26 0.48 1.1 0.9, 1.3 0.33
rs9436303 LEPR 1 65669261 A>G 0.25 0.27 1.0 0.8, 1.2 0.94
rs1045895 LEPR 1 65670568 G>A 0.4 0.45 0.8 0.7, 1.0 0.01
rs1536466 LEPR 1 65671559 T>C 0.005 0.85 0.3 0.1, 1.2 0.09
rs10889552 LEPR 1 65678760 C>T 0.05 0.15 1.2 0.9, 1.7 0.25
rs970468 LEPR 1 65679077 T>G 0.36 0.66 1.2 1.0, 1.4 0.07
rs970467 LEPR 1 65679349 G>A 0.12 0.92 1.0 0.8, 1.3 0.73
rs17127652 LEPR 1 65707730 A>G 0.02 0.55 1.4 0.8, 2.4 0.24
rs6704167 LEPR 1 65710467 A>T 0.45 0.62 0.8 0.7, 1.0 0.01
rs7518849 LEPR 1 65721378 T>C 0.07 0.28 1.2 0.9, 1.6 0.17
rs6694528 LEPR 1 65735603 C>T 0.13 0.19 1.1 0.9, 1.4 0.25
rs7537093 LEPR 1 65739151 A>G 0.49 0.28 0.8 0.7, 1.0 0.02
rs6672331 LEPR 1 65748434 G>C 0.03 0.28 1.2 0.7, 1.8 0.54
rs11208659 LEPR 1 65751867 T>C 0.09 0.86 1.2 0.9, 1.5 0.16
rs1627238 LEPR 1 65758666 C>T 0.18 0.95 1.0 0.8, 1.2 0.93
rs1171279 LEPR 1 65761080 C>T 0.27 0.75 1.1 0.9, 1.3 0.43
rs1171267 LEPR 1 65776441 G>T 0.34 0.42 1.2 1.0, 1.4 0.03
rs1137100 LEPR 1 65809028 A>G 0.25 0.59 1.1 1.0, 1.4 0.13
rs3790429 LEPR 1 65809363 A>T 0.18 0.04 1.0 0.8, 1.2 0.70
rs13306519 LEPR 1 65810516 C>G 0.004 0.88 1.4 0.4, 4.3 0.59
rs6588152 LEPR 1 65811585 T>A 0.22 0.76 1.0 0.8, 1.2 0.69
rs6673591 LEPR 1 65820976 G>A 0.52 0.20 0.9 0.8, 1.1 0.21
rs1137101 LEPR 1 65831100 A>G 0.43 0.29 1.1 0.9, 1.3 0.32
rs4655537 LEPR 1 65831388 G>A 0.37 0.01 0.9 0.8, 1.1 0.47
rs3762274 LEPR 1 65836700 A>G 0.38 0.38 1.1 0.9, 1.2 0.56
rs17097193 LEPR 1 65839983 T>C 0.03 0.08 1.1 0.7, 1.7 0.58
rs11585329 LEPR 1 65846401 G>T 0.16 0.01 1.0 0.8, 1.3 0.78
rs8179183 LEPR 1 65848539 G>C 0.18 0.59 1.0 0.8, 1.2 0.68
rs12040007 LEPR 1 65852747 G>A 0.18 0.60 1.1 0.9, 1.3 0.43
rs4655557 LEPR 1 65853374 T>C 0.38 0.12 1.1 0.9, 1.2 0.52
rs17127832 LEPR 1 65869512 T>C 0.19 0.16 1.0 0.8, 1.2 0.91
rs17700144 MC4R 18 55962961 G>A 0.2 0.78 1.1 0.9, 1.3 0.43
rs17782313 MC4R 18 56002076 T>C 0.21 0.40 1.1 0.9, 1.3 0.47
rs12970134 MC4R 18 56035729 G>A 0.24 0.97 1.1 0.9, 1.3 0.51
rs17700633 MC4R 18 56080411 G>A 0.28 0.50 1.0 0.9, 1.2 0.80
rs2229616 MC4R 18 56190255 G>A 0.02 0.07 1.1 0.7, 1.8 0.66
rs8087522 MC4R 18 56191457 G>A 0.31 0.45 1.2 1.0, 1.4 0.03
rs3101336 NEGR1 1 72523772 G>A 0.38 0.48 1.1 0.9, 1.2 0.49
rs2568958 NEGR1 1 72537703 A>G 0.38 0.52 1.1 0.9, 1.2 0.44
rs2815752 NEGR1 1 72585027 T>C 0.38 0.46 1.1 0.9, 1.2 0.49
rs2227562 PLAU 10 75342966 G>A 0.15 0.41 1.2 1.0, 1.5 0.04
rs2227564 PLAU 10 75343106 C>T 0.24 0.53 1.1 0.9, 1.3 0.21
rs4065 PLAU 10 75346469 T>C 0.43 0.53 1.2 1.1, 1.4 0.01
rs344783 PLAUR 19 34997734 C>T 0.48 0.15 1.0 0.9, 1.2 0.93
rs4251938 PLAUR 19 48843460 A>G 0.12 0.04 0.9 0.7, 1.2 0.43
rs2302524 PLAUR 19 48848311 T>C 0.16 0.09 1.0 0.8, 1.2 0.75
rs4251871 PLAUR 19 48853337 G>C 0.05 0.52 1.0 0.7, 1.4 0.96
rs4251864 PLAUR 19 48854072 T>C 0.09 0.94 1.1 0.8, 1.4 0.60
rs2239372 PLAUR 19 48854793 G>A 0.5 0.76 1.0 0.9, 1.1 0.83
rs2283628 PLAUR 19 48854900 T>C 0.18 0.31 1.1 0.9, 1.3 0.32
rs397374 PLAUR 19 48855620 A>T 0.22 0.76 1.1 0.9, 1.3 0.30
rs2283632 PLAUR 19 48856930 G>A 0.11 0.11 1.1 0.8, 1.3 0.68
rs4251831 PLAUR 19 48861577 G>C 0.29 0.96 0.9 0.8, 1.1 0.18
rs2286960 PLAUR 19 48863864 C>T 0.24 0.70 1.0 0.9, 1.2 0.83
rs1801282 PPARG 3 12368124 C>G 0.12 0.13 1.0 0.8, 1.3 0.97
rs6092 SERPINE1 7 100558436 G>A 0.11 0.34 0.9 0.7, 1.2 0.61
rs2227666 SERPINE1 7 100561424 G>A 0.05 0.77 1.3 0.9, 1.8 0.18
rs2227712 SERPINE1 7 100563672 G>A 0.003 0.91 0.8 0.2, 3.1 0.78
rs2070682 SERPINE1 7 100563986 T>C 0.44 0.52 1.0 0.9, 1.2 0.61
rs2227692 SERPINE1 7 100565963 C>T 0.08 0.12 0.8 0.6, 1.1 0.22
rs1050813 SERPINE1 7 100568334 G>A 0.21 0.09 1.0 0.9, 1.2 0.83
rs2227714 SERPINE1 7 100568628 C>T 0.05 0.82 1.1 0.8, 1.6 0.51
rs7903146 TCF7L2 10 114748338 C>T 0.29 0.87 0.9 0.8, 1.1 0.42
rs2867125 TMEM18 2 612826 G>A 0.19 0.81 0.9 0.8, 1.1 0.53
rs6548238 TMEM18 2 624904 C>T 0.19 0.67 1.0 0.8, 1.2 0.83
rs4854344 TMEM18 2 628143 T>G 0.19 0.73 1.0 0.8, 1.2 0.85
rs7561317 TMEM18 2 634952 G>A 0.19 0.81 1.0 0.8, 1.2 0.81
rs10168696 TMEM18 2 662495 T>C 0.14 0.88 1.0 0.8, 1.2 0.76
rs2293084 TMEM18 2 665830 C>A 0.46 0.42 1.1 0.9, 1.2 0.50
rs2293083 TMEM18 2 666176 C>G 0.26 0.44 0.9 0.7, 1.0 0.07
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Abbreviations: SNP=single nucleotide polymorphism; Chr=chromosome; MAF=minor allele frequency; HWE=Hardy-Weinberg equilibrium; RR=rate ratio; 95% CI=95% confidence interval

a

MAF in UBC controls

b

HWE in UBC controls, p<0.001

c

Per allele RR (log-additive model) adjusting for age at diagnosis and the counter-matching offset term

Discussion

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.

Acknowledgments

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),

Footnotes

Conflicts of Interest: None

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