Metabolomic-derived endotypes of age-related macular degeneration (AMD): A step towards identification of disease subgroups

Authors

Kevin Mendez, Edith Cowan UniversityFollow
Ines Lains
Rachel S. Kelly
João Gil
Rufino Silva
John Miller
Demetrios G. Vavvas
Ivana Kim
Joan Miller
Liming Liang
Jessica A. Lasky-Su
Deeba Husain

Document Type

Journal Article

Publication Title

Scientific Reports

Volume

14

Issue

1

PubMed ID

38802406

Publisher

Nature

School

Centre for Integrative Metabolomics and Computational Biology / School of Science

RAS ID

71187

Funders

Miller Retina Research Fund/Champalimaud Vision Award/National Institutes of Health/Research to Prevent Blindness/Commonwealth Unrestricted Grant for Eye Research

Grant Number

R01EY030088, R01HL123915, R01HL141826

Comments

Mendez, K., Lains, I., Kelly, R. S., Gil, J., Silva, R., Miller, J., ... & Husain, D. (2024). Metabolomic-derived endotypes of age-related macular degeneration (AMD): a step towards identification of disease subgroups. Scientific Reports, 14(1), 12145. https://doi.org/10.1038/s41598-024-59045-z

Abstract

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide, with a complex pathophysiology and phenotypic diversity. Here, we apply Similarity Network Fusion (SNF) to cluster AMD patients into putative metabolomics-derived endotypes. Using a discovery cohort of 163 AMD patients from Boston, US, and a validation cohort of 214 patients from Coimbra, Portugal, we identified four distinct metabolomics-derived endotypes with varying retinal structural and functional characteristics, confirmed across both cohorts. Patients clustered into Endotype 1 exhibited a milder form of AMD and were characterized by low levels of amino acids in specific metabolic pathways. Meanwhile, patients clustered into both Endotype 3 and 4 were associated with more severe AMD and exhibited low levels of fatty acid metabolites and elevated levels of sphingomyelins and fatty acid metabolites, respectively. These preliminary findings indicate that metabolomics-derived endotyping may offer a refined strategy for categorizing AMD patients based on their specific pathophysiological underpinnings, rather than relying solely on traditional observational clinical indicators.

DOI

10.1038/s41598-024-59045-z

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.