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Effect of Interactions Among Obesity-Related Proteins on Breast Cancer Risk: A Preliminary Study
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摘要:
目的 探讨女性乳腺癌发病过程中肥胖相关蛋白可能存在的交互作用。 方法 采用病例对照研究设计，于2014年4月–2015年5月序贯收集279例原发性女性乳腺癌病例，按年龄频数匹配收集260例同期健康对照。通过文献循证筛选肥胖-乳腺癌病因链上较受关注的蛋白，运用酶联免疫吸附法测定研究对象血浆中相关蛋白水平。按照绝经状态分层后，采用多因素logistic回归和广义多因子降维法（generalized multifactor dimensionality reduction, GMDR）相结合的分析策略，探讨肥胖相关蛋白在乳腺癌发病风险影响中的可能相互作用。 结果 绝经前亚组中，胰岛素样生长因子1（IGF-1）、胰岛素样生长因子结合蛋白3（IGFBP3）、C反应蛋白（CRP）、抵抗素（RETN）、可溶性瘦素受体（sOB-R）、脂联素（ADP）存在边际高阶交互作用（测试集平衡准确度59.01%，交叉验证一致性10/10，置换检验P=0.05）。绝经后亚组中，瘦素（LEP）、sOB-R、ADP、CRP、IGFBP3、内脂素（VF）存在高阶交互作用（测试集平衡准确度67.31%，交叉验证一致性10/10，置换检验P=0.01）。随着肥胖相关蛋白暴露数目的增多，绝经前后乳腺癌发病风险逐渐增大（OR绝经前=2.18，95%CI：1.69~2.82；OR绝经后=2.41，95%CI：1.75~3.32）。 结论 肥胖相关蛋白在对绝经前后乳腺癌发病影响上均存在高阶交互作用，未来的研究应密切关注这些蛋白在联合用作预测因子或构建乳腺癌风险评分时可能存在的交互作用。 Abstract:Objective To explore the potential interactions among obesity-related proteins in the pathogenic process of breast cancer (BC) in women. Methods We conducted a case-control study, enrolling 279 primary breast cancer cases and 260 age-frequency-matched healthy women between April 2014 and May 2015. Based on the evidence of previous published literature on obesity-related proteins and BC risks, we selected proteins that received more attention and measured the plasma levels of these proteins by enzyme-linked immunosorbent assay (ELISA). After stratification of the subjects according to their menopausal status, an analytic strategy combining multivariate logistic regression and generalized multifactor dimensionality reduction (GMDR) was used to explore the effect of the possible interactions of these proteins on BC risk. Results There were marginal high-order interactions among insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), C-reactive protein (CRP), resistin (RETN), soluble leptin receptor (sOB-R), and adiponectin (ADP) in premenopausal women (with the balanced accuracy for the testing set being 59.01%, cross-validation consistency being 10/10, and permutation test P=0.05). There were high-order interactions among leptin (LEP), sOB-R, ADP, CRP, IGFBP3 and visfatin (VF) in postmenopausal women (with the balanced accuracy for the testing set being 67.31%, cross-validation consistency being 10/10, and permutation test P=0.01). Along with an increase in the number of obesity-related proteins to which the subjects were exposed, the risk of developing breast cancer gradually increased in both pre- and postmenopausal women (ORpre=2.18, 95% CI: 1.69-2.82; ORpost=2.41, 95% CI: 1.75-3.32). Conclusions This preliminary study suggested high-order interactions among obesity-related proteins on BC risk in both pre- and postmenopausal women. In future studies, close attention should be given to these potential interactions when these proteins are used jointly as predictors, as well as in developing a comprehensive risk scoring system for BC. -
Key words:
- Breast cancer /
- Obesity /
- Obesity-related proteins /
- Interaction
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表 1 绝经前后乳腺癌组与对照组基本特征以及各蛋白水平的分布与比较
Table 1. Characteristics of pre- and postmenopausal breast cancer cases and controls and the distribution of the obesity-related protein levels
Variable Premenopausal (n=316) Postmenopausal (n=223) Breast cancer
group (n=167)Control group
(n=149)χ2 /Z P Breast cancer
group (n=112)Control group
(n=111)χ2 /Z P Age/yr., median (Q1, Q3) 44 (41, 47) 44 (41, 47) −0.18 0.86 57.5 (53, 62) 56 (52, 62) −1.18 0.24 Residence/case (%) 3.94 0.047 0.36 0.55 Urban 96 (57.49) 69 (46.31) 61 (54.46) 56 (50.45) Rural 71 (42.51) 80 (53.69) 51 (45.54) 55 (49.55) Occupation/case (%) 12.28 0.02 15.91 <0.01 Unemployed 40 (23.95) 23 (15.44) 15 (13.39) 25 (22.52) Government, enterprises, and public institutions 36 (21.56) 50 (33.56) 29 (25.89) 42 (37.84) Manufacturing worker 29 (17.37) 15 (10.07) 19 (16.96) 4 (3.60) Commercial services 44 (26.35) 36 (24.16) 15 (13.39) 10 (9.01) Agriculture 18 (10.78) 25 (16.78) 34 (30.36) 30 (27.03) Total annual household income/case (%) 1.71 0.43 8.53 0.01 <￥30000 66 (39.52) 66 (44.30) 54 (48.21) 46 (41.44) ￥30000-50000 45 (26.95) 31 (20.81) 33 (29.46) 21 (18.92) ≥￥50000 56 (33.53) 52 (34.90) 25 (22.32) 44 (39.64) Menarche age/yr., median (Q1, Q3) 13 (12, 14) 14 (13, 15) 1.98 0.047 15 (13, 16) 14 (13, 16) −1.46 0.14 Number of live birth(s)/case (%) <0.01 <0.01 <0.01 <0.01 0 3 (1.80) 4 (2.68) 4 (3.57) 1 (0.90) 1 112 (67.07) 125 (83.89) 59 (52.68) 81 (72.97) 2 47 (28.14) 19 (12.75) 34 (30.36) 23 (20.72) ≥3 5 (2.99) 1 (0.67) 15 (13.39) 6 (5.41) Family history of cancer/case (%) 0.10 0.75 7.95 <0.01 No 139 (83.23) 122 (81.88) 85 (75.89) 100 (90.09) Yes 28 (16.77) 27 (18.12) 27 (24.11) 11 (9.91) BMI/(kg/m2), $\bar x \pm s $ 23.03±2.93 23.15±3.06 0.14 0.71 23.26±2.70 23.78±2.94 1.91 0.17 E2/(pg/mL), median (Q1, Q3) − − − − 10.95 (8.14, 13.11) 10.09 (6.40, 12.88) −1.35 0.18 RETN/(μg/L), median (Q1, Q3) 20.00 (9.69, 40.42) 12.55 (4.97, 24.30) −3.74 <0.01 53.21 (31.65, 103.78) 44.10 (24.45, 71.45) −2.08 0.04 VF/(μg/L), median (Q1, Q3) 6.76 (3.59, 11.70) 7.72 (4.35, 12.92) 1.27 0.20 5.34 (2.92, 12.77) 6.77 (3.47, 15.02) 1.06 0.29 LEP/(μg/L), median (Q1, Q3) 8.34 (4.00, 14.11) 8.82 (4.68, 14.06) 0.78 0.44 7.98 (4.72, 12.54) 8.22 (4.38, 13.76) 0.05 0.96 sOB-R/(ng/mL), median (Q1, Q3) 24.55 (13.15, 38.80) 30.10 (19.48, 43.80) 2.55 0.01 22.49 (13.42, 34.81) 31.57 (18.40, 41.80) 2.39 0.02 FLI (median [Q1, Q3]) 0.37 (0.23, 0.48) 0.30 (0.21, 0.41) −2.71 <0.01 0.36 (0.23, 0.47) 0.27 (0.18, 0.36) −3.19 <0.01 ADP/(µg/mL), median (Q1, Q3) 10.68 (7.21, 14.90) 13.83 (9.04, 17.66) 3.69 <0.01 12.01 (9.18, 16.61) 19.57 (10.07, 27.57) 4.71 <0.01 CRP/(mg/L), median (Q1, Q3) 2.51 (0.83, 7.02) 1.45 (0.61, 4.04) −2.37 0.02 4.32 (1.72, 10.32) 1.98 (0.77, 5.93) −3.08 <0.01 IGF-1/(ng/mL), median (Q1, Q3) 86.92 (60.67, 171.77) 99.51 (48.10, 199.69) 0.14 0.89 89.60 (60.59, 195.98) 128.91 (61.61, 257.98) 1.28 0.20 IGFBP3/(ng/mL), median (Q1, Q3) 277.45 (161.77, 481.44) 355.15 (230.81, 514.54) 2.42 0.02 316.88 (185.30, 464.73) 330.55 (232.19, 505.60) 1.41 0.16 IGF-1/IGFBP3 ratio (median [Q1, Q3]) 0.34 (0.15, 0.83) 0.30 (0.13, 0.66) −1.08 0.28 0.30 (0.16, 0.67) 0.36 (0.15, 0.80) 0.38 0.70 E2: estradiol; RETN: resistin; VF: visfatin; LEP: leptin; sOB-R: soluble leptin receptor; FLI: free leptin index, i.e., LEP/sOB-R ratio; ADP: adiponectin; CRP: C-reactive protein; IGF-1: insulin-like growth factor 1; IGFBP3: insulin-like growth factor binding protein 3. 
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表 2 肥胖相关蛋白指标与乳腺癌发病风险关联
Table 2. The association between obesity-related proteins and the risk of breast cancer
Premenopausal (n=316) Postmenopausal (n=223) Protein variable Breast cancer cases/Controls OR (95% CI)a Protein variable Breast cancer cases/Controls OR (95% CI)b E2 E2 − − − <10.09 pg/mL 47/57 1.00 − − − ≥10.09 pg/mL 65/54 1.79 (0.98-3.26) IGF-1* IGF-1 <48.10 ng/mL 23/37 1.00 <128.91 ng/mL 69/55 1.00 ≥48.10 ng/mL 144/112 2.38 (1.25-4.55) ≥128.91 ng/mL 43/56 0.66 (0.37-1.19) IGFBP3 IGFBP3* <355.15 ng/mL 105/74 1.00 <232.19 ng/mL 43/27 1.00 ≥355.15 ng/mL 62/75 0.58 (0.35-0.96) ≥232.19 ng/mL 69/84 0.45 (0.23-0.86) IGF-1/IGFBP3 ratio IGF-1/IGFBP3 ratio <0.30 80/74 1.00 <0.36 61/56 1.00 ≥0.30 87/75 0.99 (0.76-1.28) ≥0.36 51/55 0.94 (0.52-1.68) VF VF <7.72 ng/mL 92/74 1.00 <6.77 ng/mL 69/55 1.00 ≥7.72 ng/mL 75/75 0.81 (0.50-1.32) ≥6.77 ng/mL 43/56 0.46 (0.25-0.84) RETN* RETN <4.97 ng/mL 19/36 1.00 <44.10 ng/mL 47/55 1.00 ≥4.97 ng/mL 148/113 3.30 (1.64-6.66) ≥44.10 ng/mL 65/56 1.33 (0.63-2.78) LEP LEP <8.82 ng/mL 88/74 1.00 <8.22 ng/mL 60/55 1.00 ≥8.82 ng/mL 79/75 0.77 (0.47-1.26) ≥8.22 ng/mL 52/56 0.70 (0.38-1.29) sOB-R* sOB-R <19.48 ng/mL 67/37 1.00 <31.57 ng/mL 77/55 1.00 ≥19.48 ng/mL 100/112 0.39 (0.23-0.67) ≥31.57 ng/mL 35/56 0.39 (0.21-0.75) FLI FLI <0.30 63/75 1.00 <0.27 34/56 1.00 ≥0.30 104/74 1.42 (0.86-2.33] ≥0.27 78/55 2.30 (1.21-4.37) ADP ADP <13.83 μg/mL 111/74 1.00 <19.57 μg/mL 96/55 1.00 ≥13.83 μg/mL 56/75 0.47 (0.28-0.78) ≥19.57 μg/mL 16/56 0.14 (0.06-0.29) CRP CRP <1.45 mg/L 61/74 1.00 <1.98 mg/L 36/55 1.00 ≥1.45 mg/L 106/75 1.65 (1.01-2.70) ≥1.98 mg/L 76/56 2.16 (1.17-3.98) The abbreviations are explained in the note to Table 1. a Adjusted for residence, occupation, menarche age, and number of live birth(s); b adjusted for occupation, total annual household income, number of live birth(s), and family history of cancer; * The variables are classified according to the lower quartile of the control, and the rest is classified according to the median of the control.
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表 3 GMDR模型构建的最佳交互作用组合
Table 3. The best interaction models obtained by GMDR
Best model Testing accuracy/% Prediction accuracy/% P for sign test Cross validation Premenopausal (n=316)a IGFBP3, ADP 62.25 57.06 0.17 8/10 sOB-R, RETN, CRP 63.66 56.43 0.17 4/10 sOB-R, RETN, CRP, ADP 66.12 56.34 0.17 5/10 sOB-R, RETN, CRP, ADP, IGF1 68.10 55.69 0.01 5/10 sOB-R, RETN, CRP, ADP, IGF1, IGFBP3 69.83 59.01 0.05 10/10 Postmenopausal (n=223)b sOB-R, ADP 70.70 64.84 0.001 8/10 sOB-R, ADP, CRP 73.19 67.56 0.01 7/10 sOB-R, ADP, LEP, IGFBP3 74.12 64.99 0.001 3/10 sOB-R, ADP, LEP, IGFBP3,VF 76.11 66.43 0.001 6/10 sOB-R, ADP, LEP, IGFBP3,VF,CRP 77.48 67.31 0.01 10/10 The abbreviations are explained in the note to Table 1. a Adjusted for residence, occupation, menarche age, and number of live birth(s); b adjusted for occupation, total annual household income, number of live birth(s), and family history of cancer.
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表 4 GMDR发现的交互项对乳腺癌发生风险的效应估计
Table 4. Estimated effects of obesity-related proteins with interactive effect identified by GMDR on the risk of breast cancer
Number of exposure proteins Premenopausal (n=316) Postmenopausal (n=223) Breast cancer cases/controls OR (95% CI)a Breast cancercases/controls OR (95% CI)b ≤3 48/86 1.00 53/79 1.00 >3 119/63 3.86 (2.29-6.52) 59/32 3.20 (1.69-6.06) Per 1 exposure protein 2.18 (1.69-2.82) 2.41 (1.75-3.32) a Adjusted for residence, occupation, menarche age, and number of live birth(s) for premenopausal models; b adjusted for occupation, total annual household income, number of live birth(s), and family history of cancer for postmenopausal models.
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