GWAS on childhood body fatness as an intermediate phenotype of breast cancer

描述(由申请人提供)：身材魁梧的女孩一生中患乳腺癌的风险降低15%-30%。这种关联与出生体重和成人体重指数(BMI)无关，在雌激素受体阴性(ER-)疾病中明显更强。然而，潜在的原因仍然是一个谜，特别是因为年轻时体型较大与青春期较早相关，青春期较早是乳腺癌的已知风险因素。自我报告的儿童期体型是一种表型，在文献中被描述为“儿童期体脂”，是一种高度可遗传的特征。儿童肥胖与成人BMI之间的相关性不大(r=0.24-0.20)，儿童肥胖的遗传率估计为70%-80%，而成人BMI的遗传率为40%-70%。尽管如此，关于儿童体型相关表型的遗传关联的文献非常稀少，到目前为止，还没有研究进行全基因组范围的与儿童体脂相关的基因座搜索。我们在这里提出了一项关于儿童体脂的全基因组关联研究(GWAS)。我们将在护士健康研究(NHS)中使用9000名女性中250万个单核苷酸多态(SNPs)的现有高质量基因分型和推算数据。作为结果，我们将使用通过9级图评估的5岁和10岁以上的平均童年肥胖度。以前的验证研究表明，回忆起来的体脂与测量的BMI之间存在高度相关性(5岁时r=0.60，10岁时r=0.65)，这表明这些数字图提供了对年轻时体型的准确评估。我们将在瑞典1,600名妇女(SASBAC的研究)和包括3,000名非洲裔美国儿童、1,400名西班牙裔儿童和1,600名非西班牙裔白人儿童在内的三个儿童群体中复制最相关的SNPs。确认的变异将使用来自NHS1、NHS2和SASBAC内嵌套病例对照研究的4,000例乳腺癌病例和5,000名对照，以及来自NCI乳腺癌和前列腺癌队列联盟(BPC3)的另外2,100例ER乳腺癌病例的数据来测试与乳腺癌风险的关联。我们还将调查与乳腺癌的关联是否与激素受体状态不同。NHS丰富的资源和已经完成的对16,000人的全基因组扫描提供了极好的统计能力和独特的机会，以极具成本效益的方式研究这些关键问题。识别儿童肥胖的遗传预测因素将为最终影响乳腺癌风险的发育和长期过程提供宝贵的见解。最终，解开乳腺癌的复杂病因将有助于识别高危女性，并为制定预防和治疗策略提供平台。

DESCRIPTION (provided by applicant): Girls with large body size have a 15-30% reduced risk of developing breast cancer throughout life. This association is independent of both birth weight and adult body mass index (BMI) and is significantly stronger for estrogen receptor negative (ER-) disease. However, the underlying causes remain a mystery, especially since large body size at young age is correlated with earlier pubertal timing, a known risk factor for breast cancer. Self-reported childhood body size, a phenotype which is described in the literature as "childhood body fatness", is a highly heritable trait. The correlation between childhood body fatness and adult BMI is only modest (r=0.24-0.20) and the estimated heritability of childhood body fatness is 70-80% compared to 40-70% for adult BMI. Still, the literature on genetic associations in pediatric body size-related phenotypes is very sparse and to date, no study has conducted a genome-wide search for loci associated with childhood body fatness. We here propose a genome-wide association study (GWAS) of childhood body fatness. We will use existing high-quality genotyped and imputed data for 2.5 million single nucleotide polymorphisms (SNPs) in 9,000 women in the Nurses' Health Study (NHS). As outcome, we will use recalled childhood body fatness averaged over ages 5 and 10 as assessed by a 9-level figure drawing. Previous validation studies have showed a high correlation between recalled body fatness and measured BMI (r=0.60 at age 5 and r=0.65 at age 10) indicating that these figure drawings provide an accurate assessment of body size at young ages. We will replicate the strongest associated SNPs in a Swedish population of 1,600 women (the SASBAC study), and three populations of children including 3,000 African-American children, 1,400 Hispanic children and 1,600 White non-Hispanic children. Confirmed variants will be tested for association with breast cancer risk using data from 4,000 breast cancer cases and 5,000 controls from nested case-control studies within NHS1, NHS2 and SASBAC and additional 2,100 ER- breast cancer cases from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We will also investigate if the association with breast cancer differs with hormone receptor status. The rich resources in NHS and already completed genome-wide scans for 16,000 individuals provide excellent statistical power and a unique opportunity to study these critical questions in a highly cost-efficient manner. Identifying genetic predictors of childhood body fatness will provide invaluable insights into developmental and long-term processes that eventually affect breast cancer risk. Ultimately, untangling the complex etiology of breast cancer will help identify women at high risk as well as provide a platform for development of preventive and treatment strategies.