Cited by 98

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Genome-wide analysis of disease progression in age-related macular degeneration

Yan, Qi, Ding, Ying, Liu, Yi, Sun, Tao, Fritsche, Lars G, Clemons, Traci, Ratnapriya, Rinki, Klein, Michael L, Cook, Richard J, Liu, Yu, Fan, Ruzong, Wei, Lai, Abecasis, Gonçalo R, Swaroop, Anand, Chew, Emily Y, AREDS2 Research Group, Weeks, Daniel E, Chen, Wei·2018·Human Molecular Genetics

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Crossref · 10.1093/hmg/ddy002

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  • Human genetics point to S2R as a promising therapeutic target for dry AMD, as several large-scale independent genome-wide association studies indicate that a single nucleotide polymorphism in the TMEM-VTN locus confers decreased risk for dry AMD.

    “First, human genetics point to S2R as a promising therapeutic target, as indicated via several large-scale, independent genome-wide association studies. These studies indicate that a single nucleotide polymorphism in the TMEM-VTN locus confers decreased risk for dry AMD [168,169].”

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Research works printed but not linked: 20

  1. Age-Related Eye Disease Study Research, 1999, The age-related eye disease study (AREDS): design implications. AREDS report no. 1, Control. Clin. Trials, 20, 573
  2. Fritsche, 2013, Seven new loci associated with age-related macular degeneration, Nat. Genet, 45, 433
  3. Fritsche, 2016, A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants, Nat. Genet, 48, 134
  4. Chen, 2010, Genetic variants near TIMP3 and high-density lipoprotein-associated loci influence susceptibility to age-related macular degeneration, Proc. Natl. Aacd Sci. U.S.A, 107, 7401
  5. Rivera, 2005, Hypothetical LOC387715 is a second major susceptibility gene for age-related macular degeneration, contributing independently of complement factor H to disease risk, Hum. Mol. Genet, 14, 3227
  6. Seddon, 2011, Risk models for progression to advanced age-related macular degeneration using demographic, environmental, genetic, and ocular factors, Ophthalmology, 118, 2203
  7. Seddon, 2009, Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables, Invest. Ophthalmol. Vis. Sci, 50, 2044
  8. Farwick, 2010, Susceptibility genes and progression in age-related maculopathy: a study of single eyes, Invest. Ophthalmol. Vis. Sci, 51, 731
  9. Klein, 2011, Risk assessment model for development of advanced age-related macular degeneration, Arch. Ophthalmol, 129, 1543
  10. Ding, 2017, Bivariate analysis of age-related macular degeneration progression using genetic risk scores, Genetics, 206, 119
  11. Seddon, 2015, Risk prediction for progression of macular degeneration: 10 common and rare genetic variants, demographic, environmental, and macular covariates, Invest. Ophthalmol. Vis. Sci, 56, 2192
  12. Perlee, 2013, Inclusion of genotype with fundus phenotype improves accuracy of predicting choroidal neovascularization and geographic atrophy, Ophthalmology, 120, 1880
  13. Huang da, 2009, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources, Nat. Protoc, 4, 44
  14. Lambert, 2014, Gene expression pattern of cells from inflamed and normal areas of osteoarthritis synovial membrane, Arthritis Rheum, 66, 960
  15. Hollborn, 2007, Positive feedback regulation between MMP-9 and VEGF in human RPE cells, Invest. Ophthalmol Vis. Sci, 48, 4360
  16. Joachim, 2017, Five-year progression of unilateral age-related macular degeneration to bilateral involvement: the Three Continent AMD Consortium report, Br. J. Ophthalmol, 101, 1185
  17. Sardell, 2016, Progression rate from intermediate to advanced age-related macular degeneration is correlated with the number of risk alleles at the CFH locus, Invest. Ophthalmol. Vis. Sci, 57, 6107
  18. Davis, 2005, The Age-Related Eye Disease Study severity scale for age-related macular degeneration: AREDS Report No. 17, Arch. Ophthalmol, 123, 1484
  19. Zhang, 2002, Cox proportional hazards regression models for survival data in cancer research, Cancer. Treat. Res, 113, 59
  20. Lee, 1992, Survival Analysis, State of the Art, 237

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Metadata

Authors
Yan, Q., Ding, Y., Liu, Y., Sun, T., Fritsche, L. G., Clemons, T., Ratnapriya, R., Klein, M. L., Cook, R. J., Liu, Y., Fan, R., Wei, L., Abecasis, G. R., Swaroop, A., Chew, E. Y., AREDS2 Research Group, Weeks, D. E., & Chen, W.
Affiliations
  • Division of Pulmonary Medicine, Allergy and Immunology, Department of Pediatrics, Children’s Hospital of Pittsburgh of UPMC University of Pittsburgh, Pittsburgh, PA 15224, USA,
  • Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA
  • Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
  • The Emmes Corporation, Rockville, MD 20850, USA
  • Neurobiology Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
  • Casey Eye Institute, Oregon Health & Science University, Portland, OR 97239, USA
  • Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
  • State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong Province 510030, China
  • Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University Medical Center, Washington, DC 20007, USA
  • Division of Epidemiology and Clinical Applications, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
Venue
Human Molecular Genetics
Published
2018-01-15
Volume
27
Issue
5
Pages
929-940
ISSN
  • 0964-6906
  • 1460-2083
Cited by
98
References
4
Language
en
Funders
  • National Institutes of Health (EY024226, EY022005, EY021532)
  • National Eye Institute (EY000474, EY000546)

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