AMD Genetics: Methods and Analyses for Association, Progression, and Prediction.
AMD genetics
GWAS
Machine learning
Prediction
Progression
Statistical methods
Journal
Advances in experimental medicine and biology
ISSN: 0065-2598
Titre abrégé: Adv Exp Med Biol
Pays: United States
ID NLM: 0121103
Informations de publication
Date de publication:
2021
2021
Historique:
entrez:
13
4
2021
pubmed:
14
4
2021
medline:
16
4
2021
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 33848002
doi: 10.1007/978-3-030-66014-7_7
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
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