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A systems biology approach aims to build new research activities on non-neovascular age-related macular degeneration.

Researchers at the Wilmer Eye Institute, Johns Hopkins University, Baltimore and the Boston University Schools of Medicine and Public Health, have provided a review paper on how system biology approaches predict disease onset and progression focused on non-vascular or “dry” form of age-related macular degeneration (AMD).  These research approaches include genomic, proteomic, metabolomic and other pharmacological and clinical data activities using mathematical models to obtain deeper understanding behind the pathobiology and responses of the retina.  Multi-disciplinary expertise from researchers, geneticists, medics, computing engineers, mathematical modellers and statisticians allows to bring together a larger total sum beyond the sum of the individual parts.


As documented, AMD is projected to affect 196 million patients by 2020 globally, through two forms, a non-neovascular (“dry” form) and a neovascular (“wet” form).  When dry AMD progresses in the late stages, geographic atrophy (GA) develops patches of RPE cell loss becoming confluent. This often includes the fovea leading to severe vision loss.  While several experimental treatments have aimed to test a variety of visual cycle inhibitors, sustained release of neurotrophic factors, complement pathway inhibitors and others, to date these GA results have failed in human trials. Systems biology approaches are aimed to combine both genetic and environmental studies including more than 40 genetic variants and environmental factors (diet, lifestyle, light) which can aim to develop individual risk models for AMD.  According to researchers, the integration of heterogeneous factors that influence AMD are now capable to translate and build new knowledge into the prevention, prediction, and treatment for patient clinical management.


Researchers now state that the systems biology outcomes will develop “basic, genomic, preclinical, medical, pharmacological, and clinical data into mathematical models of pathological processes at different stages of dry AMD in order to ask how relevant individual components act together within the living system”.  Most importantly, the practical consequences of these projects have been well identified, showing that researchers “can now link heterologous large data sets to acquire novel information on which to generate new hypotheses, calculate risks on an individual basis, identify drivers of disease manifestation and progression, and turn knowledge into risk assessment and clinical recommendations. The EYE-RISK consortium is an example of how this goal can be achieved. A consortium of participants from different European countries, EYE-RISK ( has been funded by the EU Horizon 2020 program.”