Guo Yan, Warren Andersen Shaneda, Shu Xiao-Ou, Michailidou Kyriaki, Bolla Manjeet K, Wang Qin, Garcia-Closas Montserrat, Milne Roger L, Schmidt Marjanka K, Chang-Claude Jenny, Dunning Allison, Bojesen Stig E, Ahsan Habibul, Aittomäki Kristiina, Andrulis Irene L, Anton-Culver Hoda, Arndt Volker, Beckmann Matthias W, Beeghly-Fadiel Alicia, Benitez Javier, Bogdanova Natalia V, Bonanni Bernardo, Børresen-Dale Anne-Lise, Brand Judith, Brauch Hiltrud, Brenner Hermann, Brüning Thomas, Burwinkel Barbara, Casey Graham, Chenevix-Trench Georgia, Couch Fergus J, Cox Angela, Cross Simon S, Czene Kamila, Devilee Peter, Dörk Thilo, Dumont Martine, Fasching Peter A, Figueroa Jonine, Flesch-Janys Dieter, Fletcher Olivia, Flyger Henrik, Fostira Florentia, Gammon Marilie, Giles Graham G, Guénel Pascal, Haiman Christopher A, Hamann Ute, Hooning Maartje J, Hopper John L, Jakubowska Anna, Jasmine Farzana, Jenkins Mark, John Esther M, Johnson Nichola, Jones Michael E, Kabisch Maria, Kibriya Muhammad, Knight Julia A, Koppert Linetta B, Kosma Veli-Matti, Kristensen Vessela, Le Marchand Loic, Lee Eunjung, Li Jingmei, Lindblom Annika, Luben Robert, Lubinski Jan, Malone Kathi E, Mannermaa Arto, Margolin Sara, Marme Frederik, McLean Catriona, Meijers-Heijboer Hanne, Meindl Alfons, Neuhausen Susan L, Nevanlinna Heli, Neven Patrick, Olson Janet E, Perez Jose I A, Perkins Barbara, Peterlongo Paolo, Phillips Kelly-Anne, Pylkäs Katri, Rudolph Anja, Santella Regina, Sawyer Elinor J, Schmutzler Rita K, Seynaeve Caroline, Shah Mitul, Shrubsole Martha J, Southey Melissa C, Swerdlow Anthony J, Toland Amanda E, Tomlinson Ian, Torres Diana, Truong Thérèse, Ursin Giske, Van Der Luijt Rob B, Verhoef Senno, Whittemore Alice S, Winqvist Robert, Zhao Hui, Zhao Shilin, Hall Per, Simard Jacques, Kraft Peter, Pharoah Paul, Hunter David, Easton Douglas F, Zheng Wei
Department of Cancer Biology, Vanderbilt University, Nashville, Tennessee, United States of America.
Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
PLoS Med. 2016 Aug 23;13(8):e1002105. doi: 10.1371/journal.pmed.1002105. eCollection 2016 Aug.
Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors.
We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively.
In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10). The associations were similar for both premenopausal (OR = 0.44, 95% CI:0.31-0.62, p = 9.91 × 10-8) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88 × 10-8). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 × 10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk.
BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.
观察性流行病学研究表明，高体重指数（BMI）与绝经前女性患乳腺癌风险降低相关，但与绝经后女性患癌风险增加相关。目前尚不清楚这种关联是否通过共享的遗传或环境因素介导。
我们应用孟德尔随机化方法，利用来自两个大型乳腺癌联盟的数据评估BMI与乳腺癌发生风险之间的关联。我们创建了一个包含84个与BMI相关的基因变异的加权BMI遗传评分来预测BMI。我们使用来自乳腺癌协会联盟（BCAC）的个体水平数据（病例 = 46325例，对照 = 42482例）评估基因预测的BMI与乳腺癌风险的关联。我们还使用来自乳腺癌遗传变异的发现、生物学和风险（DRIVE）项目的16003例病例和41335例对照的汇总统计数据，进一步评估基因预测的BMI与乳腺癌风险的关联。由于大多数研究在癌症诊断后测量BMI，我们无法进行平行分析来前瞻性地充分评估测量的BMI与乳腺癌风险的关联。
在BCAC数据中，发现基因预测的BMI与乳腺癌风险呈负相关（每增加5kg/m²的优势比[OR] = 0.65，95%置信区间[CI]：0.56 - 0.75，p = 3.32×10⁻¹⁰）。绝经前（OR = 0.44，95%CI：0.31 - 0.62，p = 9.91×10⁻⁸）和绝经后乳腺癌（OR = 0.57，95%CI：0.46 - 0.71，p = 1.88×10⁻⁸）的关联相似。这种关联在DRIVE联盟的数据中得到了重复（OR = 0.72，95%CI：0.60 - 0.84，p = 1.64×10⁻⁷）。单标记分析在p < 0.05时鉴定出84个与BMI相关的单核苷酸多态性（SNP）中的17个与乳腺癌风险相关；其中16个，与BMI升高相关的等位基因与乳腺癌风险降低相关。
通过全基因组关联研究（GWAS）鉴定的变异预测的BMI与绝经前和绝经后乳腺癌风险均呈负相关。本研究中观察到的与基因预测的BMI相关的绝经后乳腺癌风险降低与使用测量的成人BMI的研究所报道的正相关不同。了解这种差异的原因可能会揭示对乳腺癌病因中体重遗传决定因素复杂关系的见解。
Zotero 插件