NDLI: Automated discovery and quantification of image-based complex phenotypes: a twin study of drusen phenotypes in age-related macular degeneration.

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Automated discovery and quantification of image-based complex phenotypes: a twin study of drusen phenotypes in age-related macular degeneration.

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Automated discovery and quantification of image-based complex phenotypes: a twin study of drusen phenotypes in age-related macular degeneration.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Quellec, Gwenole Russell, Stephen R. Mahajan, Vinit B. Seddon, Johanna M. Stone, Edwin M. Reynolds, Robyn Scheetz, Todd Abràmoff, Michael D.
Description	Country affiliation: United States Author Affiliation: Quellec G ( Institute for Vision Research, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, IA 52242, USA.)
Abstract	PURPOSE: Determining the relationships between phenotype and genotype of many disorders can improve clinical diagnoses, identify disease mechanisms, and enhance therapy. Most genetic disorders result from interaction of many genes that obscure the discovery of such relationships. The hypothesis for this study was that image analysis has the potential to enable formalized discovery of new visible phenotypes. It was tested in twins affected with age-related macular degeneration (AMD). METHODS: Fundus images from 43 monozygotic (MZ) and 32 dizygotic (DZ) twin pairs with AMD were examined. First, soft and hard drusen were segmented. Then newly defined phenotypes were identified by using drusen distribution statistics that significantly separate MZ from DZ twins. The ACE model was used to identify the contributions of additive genetic (A), common environmental (C), and nonshared environmental (E) effects on drusen distribution phenotypes. RESULTS: Four drusen distribution characteristics significantly separated MZ from DZ twin pairs. One encoded the quantity, and the remaining three encoded the spatial distribution of drusen, achieving a zygosity prediction accuracy of 76%, 74%, 68%, and 68%. Three of the four phenotypes had a 55% to 77% genetic effect in an AE model, and the fourth phenotype showed a nonshared environmental effect (E model). CONCLUSIONS: Computational discovery of genetically determined features can reveal quantifiable AMD phenotypes that are genetically determined without explicitly linking them to specific genes. In addition, it can identify phenotypes that appear to result predominantly from environmental exposure. The approach is rapid and unbiased, suitable for large datasets, and can be used to reveal unknown phenotype-genotype relationships.
ISSN	01460404
e-ISSN	15525783
DOI	10.1167/iovs.10-6793
Journal	Investigative Opthalmology & Visual Science
Issue Number	12
Volume Number	52
Language	English
Publisher	Association for Research in Vision and Ophthalmology
Publisher Date	2011-11-25
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Diseases In Twins Genetics Macular Degeneration Retinal Drusen Twins, Dizygotic Twins, Monozygotic Genetic Predisposition To Disease Genotype Diagnosis Phenotype Registries Research Support, N.i.h., Extramural Research Support, Non-u.s. Gov't Research Support, U.s. Gov't, Non-p.h.s. Twin Study Discipline Ophthalmology
Content Type	Text
Resource Type	Article
Subject	Ophthalmology Sensory Systems Cellular and Molecular Neuroscience

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