Julian, T.H. orcid.org/0000-0002-5488-5620, Cooper-Knock, J. orcid.org/0000-0002-0873-8689, MacGregor, S. et al. (5 more authors) (2023) Phenome-wide Mendelian randomisation analysis identifies causal factors for age-related macular degeneration. eLife, 12. ISSN 2050-084X
Abstract
Background: Age-related macular degeneration (AMD) is a leading cause of blindness in the industrialised world and is projected to affect >280 million people worldwide by 2040. Aiming to identify causal factors and potential therapeutic targets for this common condition, we designed and undertook a phenome-wide Mendelian randomisation (MR) study.
Methods: We evaluated the effect of 4591 exposure traits on early AMD using univariable MR. Statistically significant results were explored further using: validation in an advanced AMD cohort; MR Bayesian model averaging (MR-BMA); and multivariable MR.
Results: Overall, 44 traits were found to be putatively causal for early AMD in univariable analysis. Serum proteins that were found to have significant relationships with AMD included S100-A5 (odds ratio [OR] = 1.07, p-value = 6.80E−06), cathepsin F (OR = 1.10, p-value = 7.16E−05), and serine palmitoyltransferase 2 (OR = 0.86, p-value = 1.00E−03). Univariable MR analysis also supported roles for complement and immune cell traits. Although numerous lipid traits were found to be significantly related to AMD, MR-BMA suggested a driving causal role for serum sphingomyelin (marginal inclusion probability [MIP] = 0.76; model-averaged causal estimate [MACE] = 0.29).
Conclusions: The results of this MR study support several putative causal factors for AMD and highlight avenues for future translational research.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023, Julian et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. (https://creativecommons.org/licenses/by/4.0/) |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Neuroscience (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 31 Jan 2023 14:43 |
Last Modified: | 27 Sep 2024 10:55 |
Status: | Published |
Publisher: | eLife Sciences Publications, Ltd |
Refereed: | Yes |
Identification Number: | 10.7554/elife.82546 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195796 |