Artikel
Pharmacogenetics in neovascular AMD: useful or useless?
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Veröffentlicht: | 1. Oktober 2015 |
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Gliederung
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Background: Anti-VEGF therapy has become the mainstay of neovascular age-related macular degeneration (AMD) treatment, but large variations in response between patients exist and approximately 10% of patients are considered non-responder. With millions of anti-vascular endothelial growth factor (VEGF) injections administered each year, the need for accurate prognostic tools for response prediction is growing. AMD is known as a multifactorial disease with a substantial genetic component. Consequently, the explanation of the wide range in treatment response has often been sought in genetic factors. We aim to review the current knowledge on pharmacogenetics in neovascular AMD and to discuss its expected impact on clinical practice.
Methods: We reviewed all pharmacogenetic studies in neovascular AMD patients treated with anti-VEGF injections. All response outcomes, functional or anatomical, were considered and taken into review.
Results: Our literature search yielded 39 published papers assessing pharmacogenetic associations. One prediction model for treatment response incorporating genetic factors was identified. Single nucleotide polymorphisms in various known AMD risk loci have been indicated to influence treatment response, as well as variants involved in the VEGF pathway. Large differences between study populations and different outcomes led to inconsistent results. Yet overall, there seems to be considerable evidence suggesting genetic factors play a role in treatment response. However, effect sizes for genotypes were generally small and the prediction model including non-genetic factors implies the overall contribution of genetics to response is limited.
Conclusion: The effect of genetics in pharmacological studies is evident but small and it seems unlikely that response can be completely predicted from genetic factors alone. Accumulation of genetic risk factors may in the future have a part in prediction models for treatment response, but the effect of non-genetic factors such as delay to treatment should not be underestimated.