This proposal builds on active and productive collaboration between scientists at the University of Michigan and at the University of Pennsylvania. The research team has made several contributions both to our understanding of the genetics of macular degeneration and to the array of statistical methods and analytical tools available for genomic studies of macular degeneration and other disorders. Age-related macular degeneration (AMD) is a progressive neurodegenerative disease and the major cause of blindness among the elderly. Loss of vision caused by macular degeneration is currently irreversible. In the past several years, great progress has been made in our understanding of the molecular mechanisms that lead to macular degeneration through SNP genotyping studies, which focus on an easily accessible class of common DNA sequence variants. Here, we propose to use advances in DNA sequencing and genotyping technology to more systematically evaluate the role of DNA sequence variation in susceptibility to age related macular degeneration. Our research team includes not only clinical expertise and understanding of macular degeneration but also expertise in high-throughput genetics and genomics and in the development and application of cutting edge statistical and computational methods. Through a combination of deep exome resequencing and low pass whole genome sequencing we propose to characterize genetic variation in 3,000 individuals and evaluate the contribution of >20M genetic variants to disease susceptibility, including not only common SNPs, but also rare SNPs, short insertion deletion polymorphisms, and larger copy number variants. Our approach should yield new susceptibility loci for macular degeneration and improve our understanding of the molecular mechanisms that contribute to disease susceptibility in previously implicated loci.

Public Health Relevance

Age-related macular degeneration (AMD) is a progressive neurodegenerative disease and the major cause of blindness among the elderly. Loss of vision caused by macular degeneration is currently irreversible. Previous genetic studies of age-related macular degeneration focused on a class of easily accessible DNA sequence variants. We have assembled a team of experts in the clinical features of age related macular degeneration, in the methods and tools for the analysis of DNA sequence variation, and in associated computational problems and propose to more thoroughly assess the contribution of DNA sequence variation to disease susceptibility. We expect our research will lead to new disease susceptibility variants and better understanding of the molecular changes that lead to disease. This knowledge will facilitate development of new therapies and development of strategies for early diagnosis and prevention of disease.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY022005-03
Application #
8537464
Study Section
Special Emphasis Panel (ZRG1-GGG-C (02))
Program Officer
Shen, Grace L
Project Start
2011-09-01
Project End
2015-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
3
Fiscal Year
2013
Total Cost
$1,121,206
Indirect Cost
$320,443
Name
University of Michigan Ann Arbor
Department
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Yan, Qi; Ding, Ying; Liu, Yi et al. (2018) Genome-wide analysis of disease progression in age-related macular degeneration. Hum Mol Genet 27:929-940
Ding, Ying; Liu, Yi; Yan, Qi et al. (2017) Bivariate Analysis of Age-Related Macular Degeneration Progression Using Genetic Risk Scores. Genetics 206:119-133
Loh, Po-Ru; Danecek, Petr; Palamara, Pier Francesco et al. (2016) Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet 48:1443-1448
Lo, Yancy; Kang, Hyun M; Nelson, Matthew R et al. (2015) Comparing variant calling algorithms for target-exon sequencing in a large sample. BMC Bioinformatics 16:75
Tsoi, Lam C; Elder, James T; Abecasis, Goncalo R (2015) Graphical algorithm for integration of genetic and biological data: proof of principle using psoriasis as a model. Bioinformatics 31:1243-9
Tsoi, Lam C; Iyer, Matthew K; Stuart, Philip E et al. (2015) Analysis of long non-coding RNAs highlights tissue-specific expression patterns and epigenetic profiles in normal and psoriatic skin. Genome Biol 16:24
Liu, Dajiang J; Peloso, Gina M; Zhan, Xiaowei et al. (2014) Meta-analysis of gene-level tests for rare variant association. Nat Genet 46:200-4
Wang, Chaolong; Zhan, Xiaowei; Bragg-Gresham, Jennifer et al. (2014) Ancestry estimation and control of population stratification for sequence-based association studies. Nat Genet 46:409-15
Fritsche, Lars G; Fariss, Robert N; Stambolian, Dwight et al. (2014) Age-related macular degeneration: genetics and biology coming together. Annu Rev Genomics Hum Genet 15:151-71
Zhan, Xiaowei; Larson, David E; Wang, Chaolong et al. (2013) Identification of a rare coding variant in complement 3 associated with age-related macular degeneration. Nat Genet 45:1375-9

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