| Literature DB >> 33848002 |
Qi Yan1, Ying Ding2, Daniel E Weeks2,3, Wei Chen4,5,6.
Abstract
Age-related macular degeneration (AMD) is a multifactorial neurodegenerative disease, which is a leading cause of vision loss among the elderly in the developed countries. As one of the most successful examples of genome-wide association study (GWAS), a large number of genetic studies have been conducted to explore the genetic basis for AMD and its progression, of which over 30 loci were identified and confirmed. In this chapter, we review the recent development and findings of GWAS for AMD risk and progression. Then, we present emerging methods and models for predicting AMD development or its progression using large-scale genetic data. Finally, we discuss a set of novel statistical and analytical methods that were recently developed to tackle the challenges such as analyzing bilateral correlated eye-level outcomes that are subject to censoring with high-dimensional genetic data. Future directions for analytical studies of AMD genetics are also proposed.Entities:
Keywords: AMD genetics; GWAS; Machine learning; Prediction; Progression; Statistical methods
Year: 2021 PMID: 33848002 DOI: 10.1007/978-3-030-66014-7_7
Source DB: PubMed Journal: Adv Exp Med Biol ISSN: 0065-2598 Impact factor: 2.622