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Integrative functional characterization of genetic loci for cutaneous basal cell carcinoma

皮肤基底细胞癌遗传位点的综合功能特征

基本信息

批准号：
10046682
负责人：
JIALI HAN
金额：
$ 17.35万
依托单位：
INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-07 至 2022-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10046682
关键词：
1p36 Address Affect Animal Model Area Basal cell carcinoma Biological Blood specimen Candidate Disease Gene Clinical Computer software Cutaneous DNA Data Databases Development Diagnosis Elements Enhancers FOXP1 gene Funding Gene Expression Genes Genetic Genetic Risk Genetic Variation Genome Genotype-Tissue Expression Project HLA-B Antigens Human IRF4 gene Individual Intuition Investigation Light Link Linkage Disequilibrium Malignant Neoplasms Metadata Monophenol Monooxygenase Natural regeneration Pathogenesis Pathway interactions Pattern Pigmentation physiologic function Positioning Attribute Prevention Probability Public Health Publishing Quantitative Trait Loci Reporting Review Literature Risk Risk Reduction Series Single Nucleotide Polymorphism Skin Skin Tissue Specific qualifier value Susceptibility Gene TFAP2A gene TP53 gene Telomere Maintenance Therapeutic Intervention Tissue Model Tissue Sample Tissues Validation Variant Work carcinogenesis causal variant epigenome genetic predictors genetic variant genome wide association study genome-wide genomic locus high risk population immunoregulation individualized prevention innovation large datasets metabolomics novel pleiotropism risk prediction model targeted treatment tool transcriptome tumor progression

项目摘要

Cutaneous basal cell carcinoma (BCC) is the most common malignancy diagnosed in the USA and is becoming more frequent in younger individuals. The heavy public health burden associated with BCC underscores the importance of efficient management and prevention efforts directed toward this malignancy, especially targeting the high-risk population. We recently published a large genome-wide association study (GWAS) on BCC with 17,187 cases and 287,054 controls. We yield a list of 31 loci for further investigation to elucidate true causal variants and the specific genes or DNA functional elements through which the genetic variants exert their effects. In this application, we aim to carry out the first well-positioned post-GWAS investigation of BCC to integrate complementary strategies including fine- mapping and transcriptome-wide association study (TWAS), targeting potentially causal variants and functionally relevant genes. We propose the following specific aims: (1) Perform empirical Bayes fine- mapping using the Probabilistic Annotation INTegratOR (PAINTOR) software to predict causal single- nucleotide polymorphisms (SNPs). PAINTOR will summarize GWAS data, information on local linkage disequilibrium (LD) patterns, as well as functional annotations for SNPs from publicly available databases (e.g. ENCODE, Epigenome Roadmap, GTEx, and Metabolomic GWAS Server). (2) Perform TWAS analysis, which integrates current GWAS-meta data on BCC with data from expression quantitative trait loci (eQTL) studies to identify genes whose expression levels are significantly associated with BCC risk. Several novel and emerging robust approaches will be used in our TWAS (including an extension of pleiotropy-robust MR-Egger regression that we have developed) to reduce the risk of false positives due to these confounders. We will conduct a series of TWAS analyses using eQTL data from blood samples and skin tissue samples to distinguish SNPs with skin-specific eQTL effects and those with cross-tissue effects. This study will not only greatly advance our understanding of BCC pathogenesis, but also provide a robust scientific basis for developing clinically useful genetic risk prediction model for precision prevention. Moreover, this proposed study may pinpoint some potential/actionable targets for therapeutic intervention and risk reduction.

皮肤基底细胞癌（BCC）是美国最常见的恶性肿瘤