ArticleScientific reports2017
Simple and complex retinal dystrophies are associated with profoundly different disease networks.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- [Liquid biopsy proteomics in ophthalmology : A clinical and scientific perspective].Die Ophthalmologie · 2026Pooled it
- Identifying genetic determinants of outer retinal function in mice using a large-scale gene-targeted screen.PLoS genetics · 2025Article
- Re-Addressing Dementia by Network Medicine and Mechanism-Based Molecular Endotypes.Journal of Alzheimer's disease : JAD · 2023Article
- Disease-Gene Networks of Skin Pigmentation Disorders and Reconstruction of Protein-Protein Interaction Networks.Bioengineering (Basel, Switzerland) · 2022Article
- Epistatic interactions of genetic loci associated with age-related macular degeneration.Scientific reports · 2021Article
- A transcriptome-wide association study based on 27 tissues identifies 106 genes potentially relevant for disease pathology in age-related macular degeneration.Scientific reports · 2020Article
- Repository of proposed pathways and protein-protein interaction networks in age-related macular degeneration.NPJ aging and mechanisms of disease · 2020Article
- New Technologies to Study Functional Genomics of Age-Related Macular Degeneration.Frontiers in cell and developmental biology · 2020Review
- Network and Systems Medicine: Position Paper of the European Collaboration on Science and Technology Action on Open Multiscale Systems Medicine.Network and systems medicine · 2020Review
- Combining Gene-Disease Associations with Single-Cell Gene Expression Data Provides Anatomy-Specific Subnetworks in Age-Related Macular Degeneration.Network and systems medicine · 2020Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Retinopathies are a group of monogenetic or complex retinal diseases associated with high unmet medical need. Monogenic disorders are caused by rare genetic variation and usually arise early in life. Other diseases, such as age-related macular degeneration (AMD), develop late in life and are considered to be of complex origin as they develop from a combination of genetic, ageing, environmental and lifestyle risk factors. Here, we contrast the underlying disease networks and pathological mechanisms of monogenic as opposed to complex retinopathies, using AMD as an example of the latter. We show that, surprisingly, genes associated with the different forms of retinopathies in general do not overlap despite their overlapping retinal phenotypes. Further, AMD risk genes participate in multiple networks with interaction partners that link to different ubiquitous pathways affecting general tissue integrity and homeostasis. Thus AMD most likely represents an endophenotype with differing underlying pathogenesis in different subjects. Localising these pathomechanisms and processes within and across different retinal anatomical compartments provides a novel representation of AMD that may be extended to complex disease in general. This approach may generate improved treatment options that target multiple processes with the aim of restoring tissue homeostasis and maintaining vision.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.