Lipid genotypes, phenotypes, and colorectal adenomas: Elucidating mechanisms

描述（由申请人提供）：流行病学研究的证据表明血脂浓度与结直肠腺瘤之间存在关联。然而，很难确定这种联系是指示因果机制还是癌症和心血管疾病的共同风险因素（如饮食，肥胖，吸烟和缺乏身体活动）的结果。血脂异常是常见的，影响多达三分之一的美国成年人口，并具有很强的遗传成分。一些研究已经确定了已知影响脂质水平的遗传位点与结直肠肿瘤风险之间的关联，包括PCSK 9， ABCG 8和APOE，但这些研究仅限于少数候选基因。近年来，人们对血脂表型进行了多项全基因组关联研究（GWAS），近100个基因座与血脂水平相关。Teslovich等人（2010年）对46项GWAS进行了综合分析，涉及100，000多名个体的血脂测量。他们的分析导致了一组102个单核苷酸多态性（SNP），这些SNP与血液中的总胆固醇（TC）、高密度脂蛋白（HDL）和低密度脂蛋白（LDL）胆固醇以及甘油三酯（TG）水平相关。值得注意的是，这些新识别的变体影响已知对致癌作用重要的途径：炎症、凋亡、血管生成、细胞信号传导、粘附、迁移、激素合成和生长因子调节。在拟议的GWAS后研究中，我们将评估腺瘤发生、脂质表型和脂质基因型之间的关联。我们的孟德尔随机化方法，利用遗传代理观察到的表型，将有助于避免混淆和反向因果关系的问题，阻碍了以前的观察研究这个问题。这种方法已被证明对胆固醇和心血管疾病的研究特别有效。具体来说，我们提出的研究将：1）在我们的研究人群中测试腺瘤与LDL，HDL，TG和TC血液浓度之间的关联; 2）确定腺瘤与102个GWAS鉴定的与血脂相关的SNP之间的关联; 3）评估这些与腺瘤风险的遗传关联是否根据测量的血脂浓度而变化。我们将利用华盛顿州一家大型医疗保健提供商Group Health（GH）的入组者中已完成的结肠镜检查研究的现存生物标本和问卷数据。参与者在1998年至2007年期间在GH接受了任何适应症的结肠镜检查。总共有889例病理学家证实的腺瘤病例和1，037例无息肉结肠镜检查作为对照。新的数据收集包括：1）对提取的DNA进行基因分型; 2）测量来自储存的血浆或来自医疗记录的脂质;以及3）测量来自药房记录的胆固醇药物的使用。将通过逻辑回归估计血脂指标的比值比。变异体将在单SNP分析中考虑，并根据机制途径作为遗传风险评分的一部分。了解脂质基因如何影响腺瘤风险可能会告知致癌机制，最终有助于减轻CRC的负担。

DESCRIPTION (provided by applicant): Evidence from epidemiologic studies shows an association between blood lipid concentrations and colorectal adenomas. It has been difficult, however, to determine if this link is indicative of a causal mechanism or is the consequence of shared risk factors for cancer and cardiovascular disease such as diet, obesity, smoking, and physical inactivity. Dyslipidemia is common, affecting up to one-third of the adult US population, and has a strong hereditary component. Some studies have identified associations between genetic loci known to influence lipid levels and the risk of colorectal neoplasia, including PCSK9, ABCG8, and APOE, but these studies have been limited to only a few candidate genes. Many recent genome-wide association studies (GWASs) have been conducted for lipid phenotypes, and nearly 100 loci have been linked to blood lipid levels. Teslovich at al. (2010) conducted a combined analysis of 46 GWASs involving plasma lipid measurements from over 100,000 individuals. Their analysis resulted in a set of 102 single nucleotide polymorphisms (SNPs) related to blood levels of total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TG). Notably, these newly recognized variants affect pathways known to be important for carcinogenesis: inflammation, apoptosis, angiogenesis, cellular signaling, adhesion, migration, hormone synthesis, and growth factor regulation. In the proposed post-GWAS study, we will evaluate the association between adenoma occurrence, lipid phenotypes, and lipid genotypes. Our Mendelian randomization approach, which exploits genetic proxies for observed phenotypes, will help avoid problems with confounding and reverse causation that have hampered previous observational studies of this question. This method has proved to be especially effective for studies of cholesterol and cardiovascular disease. Specifically, our proposed study will: 1) test the association between adenomas and blood concentrations of LDL, HDL, TG, and TC in our study population; 2) determine the association between adenomas and 102 GWAS-identified SNPs related to blood lipids; and 3) evaluate whether these genetic associations with adenoma risk vary according to measured blood lipid concentrations. We will utilize extant biospecimens and questionnaire data from a completed colonoscopy study among enrollees of Group Health (GH), a large healthcare provider in Washington State. Participants underwent colonoscopy for any indication at GH between 1998 and 2007. In total, there were 889 pathologist-confirmed adenoma cases and 1,037 with a polyp-free colonoscopy that serve as controls. New data collection includes: 1) genotyping extracted DNA; 2) measuring lipids from stored plasma or from medical records; and 3) measuring use of cholesterol medication from pharmacy records. Odds ratios for lipid measures will be estimated from logistic regression. Variants will be considered in both single-SNP analyses and as part of genetic risk scores according to mechanistic pathway. Understanding how lipid genes influence adenoma risk may inform mechanisms of carcinogenesis, ultimately helping to reduce the burden of CRC.