Transcriptome-wide association study to identify susceptibility genes for colorectal cancer

项目总结 遗传因素在结直肠癌的病因中起着重要作用。到目前为止，大约有50个 目前已通过全基因组关联研究确定了结直肠癌的遗传位点。然而，这些 基因座只能解释一小部分遗传性。此外，大多数的靶基因和潜在的机制 这些风险部位仍不清楚。绝大多数是非编码变体，其中许多已经被证明是 调控基因表达。最近的研究表明，大约80%的疾病遗传性可以用 监管变种。然而，这些变异每个都与疾病风险只有很小的变化相关； 因此，它们很难使用GWAs进行识别。最近，一种新的方法，转录组范围的关联 这项研究是为了系统地研究转录组与疾病风险之间的关系而发展起来的。 在TWAS中，使用参考转录组建立模型来预测cis-SNPs的基因表达，然后 将其应用于GWAS数据，以评估它们与疾病风险的关联。在这里，我们建议使用这一创新的 扫描整个转录组以发现新的结直肠癌易感基因并发现可能的 基因座上的致病基因已在以往的遗传多样性分析中发现。在目标1中，我们将在欧洲后裔中进行TWAs。 我们将建立数百个大肠组织中编码基因和非编码RNA的表达预测模型 组织、其他多种组织和交叉组织使用转录组和高密度基因分型数据 基因类型-组织表达(GTEx)项目中的欧洲血统个体。将使用这些模型 使用来自大约27,911例结直肠癌和23,059例结直肠癌的GWAS数据预测基因表达水平 纳入结直肠癌跨学科研究的对照研究(CORECT)和遗传学和流行病学 结直肠癌(GECCO)联盟，然后评估它们与结直肠癌风险的关系。在目标2中，我们将 在东亚后裔中进行一次TWAs。我们将产生转录组数据和高密度基因分型 来自亚洲结直肠癌联盟(ACCC)的400名亚裔结直肠癌患者的数据。我们会 使用这些数据来构建编码基因和非编码RNA的表达预测模型，并执行 来自ACCC的大约18,999例结直肠癌病例和31,269例对照病例。在目标3中，我们将体验- 对目标1和目标2中确定的前30个基因的生物功能进行心理评估。 他们的表达水平和CRC风险之间的方向，我们要么使用CRISPRi抑制表达，要么 使用CRISPRa在多个正常结肠上皮细胞和结直肠癌细胞系中推广它。然后我们将在体外进行 分析和分析生物信息学证据，以检查这些选定基因的生物学功能，并 评估它们在调节已知癌症相关通路方面的潜在作用。我们提议的研究是非常 成本效益高，因为欧洲后代的转录组数据集(GTEx)和Gwas数据都是 已经提供给我们了。这项拟议的研究将为确定结直肠癌易感性提供强有力的证据。 基因，从而促进将我们的发现转化为癌症预防和病人护理。

PROJECT SUMMARY Genetic factors play an important role in the etiology of colorectal cancer (CRC). To date, approximately 50 genetic loci have been identified for CRC through genome-wide association studies (GWAS). However, these loci explain only a small fraction of heritability. Moreover, target genes and underlying mechanisms for most of these risk loci remain unclear. The large majority are noncoding variants, many of which have been shown to regulate gene expression. Recent studies suggest that ~80% of disease heritability can be explained by regulatory variants. However, these variants are each associated with only a small alteration in disease risk; thus they are difficult to identify using GWAS. Recently, a novel approach, the transcriptome-wide association study (TWAS), was developed to systematically investigate the transcriptome's association with disease risk. In TWAS, models are built to predict gene expression with cis-SNPs using a reference transcriptome, and then applied to GWAS data to evaluate their associations with disease risk. Here, we propose to use this innovative approach to scan the whole transcriptome to discover novel CRC susceptibility genes and uncover likely causal genes in loci revealed in previous GWAS. In Aim 1, we will conduct a TWAS in European descendants. We will build expression prediction models for coding genes and non-coding RNAs in hundreds of colorectal tissues, other multiple tissues, and cross tissues using transcriptome and high-density genotyping data from individuals of European ancestry in the Genotype-Tissue Expression (GTEx) project. The models will be used to predict gene expression levels using GWAS data from approximately 27,911 CRC cases and 23,059 controls included in the ColoRectal Transdisciplinary Study (CORECT) and the Genetics and Epidemiology of Colorectal Cancer (GECCO) consortia, and then to evaluate their associations with CRC risk. In Aim 2, we will conduct a TWAS in East-Asian descendants. We will generate transcriptome data and high-density genotyping data from 400 CRC patients of Asian ancestry from the Asia Colorectal Cancer Consortium (ACCC). We will use these data to build expression prediction models for coding genes and non-coding RNAs and perform a TWAS in approximately 18,999 CRC cases and 31,269 controls from the ACCC. In Aim 3, we will experi- mentally evaluate biological function of the top 30 genes identified in Aims 1 and 2. Based on the association direction between their expression levels and CRC risk, we will either suppress expression using CRISPRi or promote it using CRISPRa in multiple normal colon epithelial and CRC cell lines. We will then perform in vitro assays and analyze bioinformatics evidence to examine the biological functions of these selected genes and to assess their potential roles in regulating known cancer-related pathways. Our proposed study is extremely cost-efficient, as both the transcriptome dataset (GTEx) for European descendants and the GWAS data are already available to us. This proposed study will provide strong evidence for pinpointing CRC susceptibility genes, thereby facilitating the translation of our findings to cancer prevention and patient care.