The DOI matches its Crossref record; 143 of the 143 references it cites were found in a registry or an index.
Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks
Open accessAbstract
Background Age-related macular degeneration (AMD) is a leading cause of blindness that affects the central region of the retinal pigmented epithelium (RPE), choroid, and neural retina. Initially characterized by an accumulation of sub-RPE deposits, AMD leads to progressive retinal degeneration, and in advanced cases, irreversible vision loss. Although genetic analysis, animal models, and cell culture systems have yielded important insights into AMD, the molecular pathways underlying AMD's onset and progression remain poorly delineated. We sought to better understand the molecular underpinnings of this devastating disease by performing the first comparative transcriptome analysis of AMD and normal human donor eyes. Methods RPE-choroid and retina tissue samples were obtained from a common cohort of 31 normal, 26 AMD, and 11 potential pre-AMD human donor eyes. Transcriptome profiles were generated for macular and extramacular regions, and statistical and bioinformatic methods were employed to identify disease-associated gene signatures and functionally enriched protein association networks. Selected genes of high significance were validated using an independent donor cohort. Results We identified over 50 annotated genes enriched in cell-mediated immune responses that are globally over-expressed in RPE-choroid AMD phenotypes. Using a machine learning model and a second donor cohort, we show that the top 20 global genes are predictive of AMD clinical diagnosis. We also discovered functionally enriched gene sets in the RPE-choroid that delineate the advanced AMD phenotypes, neovascular AMD and geographic atrophy. Moreover, we identified a graded increase of transcript levels in the retina related to wound response, complement cascade, and neurogenesis that strongly correlates with decreased levels of phototransduction transcripts and increased AMD severity. Based on our findings, we assembled protein-protein interactomes that highlight functional networks likely to be involved in AMD pathogenesis. Conclusions We discovered new global biomarkers and gene expression signatures of AMD. These results are consistent with a model whereby cell-based inflammatory responses represent a central feature of AMD etiology, and depending on genetics, environment, or stochastic factors, may give rise to the advanced AMD phenotypes characterized by angiogenesis and/or cell death. Genes regulating these immunological activities, along with numerous other genes identified here, represent promising new targets for AMD-directed therapeutics and diagnostics. Please see related commentary: http://www.biomedcentral.com/1741-7015/10/21/abstract
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,266
Complement factor H polymorphism in age-related macular degeneration
Klein, R. J., Zeiss, C., Chew, E. Y., Tsai, J.-Y., Sackler, R. S., Haynes, C., Henning, A. K., SanGiovanni, J. P., Mane, S. M., Mayne, S. T., et al. (2005) · Science · doi:10.1126/science.1109557 · Cited by 4,492
Statistical Tables for Biological, Agricultural and Medical Research.
Reed, L. J., Fisher, R. A., & Yates, F. (1944) · Journal of the American Statistical Association · doi:10.2307/2280633 · Cited by 2,998
ToppGene Suite for gene list enrichment analysis and candidate gene prioritization
Chen, J., Bardes, E. E., Aronow, B. J., & Jegga, A. G. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp427 · Cited by 2,952
STRING 8--a global view on proteins and their functional interactions in 630 organisms
Jensen, L. J., Kuhn, M., Stark, M., Chaffron, S., Creevey, C., Muller, J., Doerks, T., Julien, P., Roth, A., Simonovic, M., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn760 · Cited by 2,474
Cited by
Ratnapriya, R., Sosina, O. A., Starostik, M. R., Kwicklis, M., Kapphahn, R. J., Fritsche, L. G., Walton, A., Arvanitis, M., Gieser, L., Pietraszkiewicz, A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0351-9 · Cited by 312
Boyer, D. S., Schmidt-Erfurth, U., van Lookeren Campagne, M., Henry, E. C., & Brittain, C. (2017) · Retina · doi:10.1097/iae.0000000000001392 · Cited by 258
On phagocytes and macular degeneration
Guillonneau, X., Eandi, C. M., Paques, M., Sahel, J.-A., Sapieha, P., & Sennlaub, F. (2017) · Progress in Retinal and Eye Research · doi:10.1016/j.preteyeres.2017.06.002 · Cited by 185
Wang, J., Zibetti, C., Shang, P., Sripathi, S. R., Zhang, P., Cano, M., Hoang, T., Xia, S., Ji, H., Merbs, S. L., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03856-y · Cited by 185
Zou, M., Ke, Q., Nie, Q., Qi, R., Zhu, X., Liu, W., Hu, X., Sun, Q., Fu, J.-L., Tang, X., et al. (2022) · Cell Death & Differentiation · doi:10.1038/s41418-022-00967-4 · Cited by 138
Metadata
- Authors
- Newman, A. M., Gallo, N. B., Hancox, L. S., Miller, N. J., Radeke, C. M., Maloney, M. A., Cooper, J. B., Hageman, G. S., Anderson, D. H., Johnson, L. V., & Radeke, M. J.
- Venue
- Genome Medicine
- Published
- 2012-02-24
- Volume
- 4
- Issue
- 2
- Pages
- 16-16
- ISSN
- 1756-994X (ISSN-L)
- OpenAlex
- W1965031576
- Cited by
- 270
- References
- 143
- FWCI
- 13.95
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks. https://app.cochat.ai/papers/10.1186/gm315
- The paper
- Newman, A. M., Gallo, N. B., Hancox, L. S., Miller, N. J., Radeke, C. M., Maloney, M. A., Cooper, J. B., Hageman, G. S., Anderson, D. H., Johnson, L. V., & Radeke, M. J. (2012). Systems-level analysis of age-related macular degeneration reveals global biomarkers and phenotype-specific functional networks. Genome Medicine. https://doi.org/10.1186/gm315
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.