Copy Number Variation Identification and Association Study on Alzheimer's Disease Whole Genome Sequencing Data

阿尔茨海默病全基因组测序数据拷贝数变异鉴定及关联研究

• 批准号: 10301113
• 负责人: Wan-Ping Lee
• 金额: $ 232.56万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10301113
• 关键词: Address; Affect; Age; Algorithms; Alzheimer' s Disease; Alzheimer' s disease risk; American; Amyloid Beta A4 Precursor Protein; Architecture; Bioconductor; Chromosomes; Code; Cognitive; Collaborations; Copy Number Polymorphism; Data; Data Analyses; Data Collection; Databases; Dementia; Disease; Docking; Down Syndrome; Elderly; Environmental Risk Factor; Ethnic Origin; Ethnic group; Etiology; Frequencies; Gene Dosage; Gene Frequency; Genes; Genetic; Genetic Diseases; Genetic study; Genome; Genomic Segment; Genomics; Genotype; Goals; Hereditary Disease; Heritability; Heterogeneity; Image; Individual; Investigation; Joints; Knowledge; Length; Life Style; Literature; Location; Meta-Analysis; Methods; Molecular; Neurodegenerative Disorders; Not Hispanic or Latino; Nucleotides; Outcome; Pathway interactions; Patients; Pharmaceutical Preparations; Population; Positioning Attribute; Prevention; Public Health; Resolution; Resources; Risk; Role; Sampling; Scientist; Sequence Alignment; Single Nucleotide Polymorphism; Source Code; Standardization; Testing; Therapeutic; Validation; Variant; base; case control; cohort; computational pipelines; disorder risk; dosage; effective intervention; functional genomics; genome sequencing; genome wide association study; genome-wide; innovation; insertion/deletion mutation; insight; multi-ethnic; neuropathology; new therapeutic target; open source; reduce symptoms; risk prediction; risk variant; therapeutic target; trial design; whole genome

SUMMARY Alzheimer's disorder (AD) is a devastating neurodegenerative disease and the most common cause of dementia. There are approximately six million Americans with AD and 29.8 million worldwide, making AD one of the most pressing public health issues as the world's population continues to age. Presently, there is no known effective prevention or cure exists, and current AD medications only alleviate symptoms or slow decline rates. The landscape of AD drug trials is gloomy. One possible reason is that AD is a heterogeneous disorder but trials are designed treating it as a monolithic disease. Although lifestyle and environmental risk factors clearly affect AD, the primacy of genetic influences suggests that categorization by genetic basis should be prioritized in developing effective interventions. Genetics can offer insights on risk prediction, disease mechanism, and new therapeutic targets. Heritability of AD estimates range from 49-79%, but the conventional single nucleotide variants (SNVs) identified to date only account for <50% of AD heritability. Multiple studies have highlighted the roles of copy number variants (CNVs) in AD. We hypothesize that a systematic investigation of genome-wide CNVs at the full spectrum (i.e. small and large in size, common and rare in frequency, and coding and no-coding in genomic regions) from whole-genome sequencing (WGS) can further enhance the knowledge of AD etiology and risk. Leveraging the rich resources from the Alzheimer's Disease Sequencing Project (ADSP), we propose to focus on a large multi-ethnic WGS sample (n>17,000) composed of AD cases and normal healthy elderly controls, and to (1) detect and genotype CNVs from WGS for ADSP case-control samples; (2) perform association analysis to identify genome regions of CNVs contributing to AD; and (3) conduct cross-ethnic association studies to find ethnic-shared or ethnic-unique AD-associated CNVs. Successful completion of our aims will provide (i) the first large-scale CNV investigation of AD genetics using WGS data; (ii) new CNV calling method for WGS based on the current best practices; (iii) new CNV association strategies to address issue of breakpoint non-alignment and enhance association power; (iv) multi-ethnic characterization of shared and unique CNV risk factors for AD; and (v) optimized computational pipelines with open- source code and released standardized images (e.g., Docker images and Bioconductor packages) that are easily deployable in other large-scale WGS association projects.

总结

项目成果

JAX-CNV: A Whole-genome Sequencing-based Algorithm for Copy Number Detection at Clinical Grade Level.

• DOI: 10.1016/j.gpb.2021.06.003
• 发表时间: 2022-12
• 期刊: GENOMICS PROTEOMICS & BIOINFORMATICS
• 影响因子: 9.5
• 作者: Lee, Wan-Ping;Zhu, Qihui;Yang, Xiaofei;Liu, Silvia;Cerveira, Eliza;Ryan, Mallory;Mil-Homens, Adam;Bellfy, Lauren;Ye, Kai;Lee, Charles;Zhang, Chengsheng
• 通讯作者: Zhang, Chengsheng

The prediction of Alzheimer's disease through multi-trait genetic modeling.

• DOI: 10.3389/fnagi.2023.1168638
• 发表时间: 2023
• 期刊: Frontiers in aging neuroscience
• 影响因子: 4.8