Translational Applications of Retinal Biomarkers in Chronic Cardiovascular, Neurological, Metabolic, and Renal Diseases

Imaging the retina is a powerful non-invasive probe of systemic vascular, neurological, metabolic, and renal disease, making it a cornerstone of the new field of systemic oculomics. Advanced retinal imaging techniques like optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) provide detailed imaging of structural and microvascular changes potentially associated with systemic disease. Derived from fundus photography, structural imaging, vascular imaging, and artificial intelligence-based image analysis, retinal biomarkers have been associated with cardiovascular and cerebrovascular disease, neurodegenerative disorders, diabetes, chronic kidney disease, and related clinical outcomes. However, the translational maturity of these biomarkers is variable depending on imaging modality, target disease, intended clinical use, and level of validation. Longitudinally, retinal vascular characteristics have been associated with cardiovascular as well as cerebrovascular outcomes. In addition, optical coherence tomography has provided reproducible measures of neuroaxonal injury in selected neurological conditions. This is especially true for multiple sclerosis. The majority of retinal biomarkers in Alzheimer disease, Parkinson disease, chronic kidney disease, and systemic risk prediction remain experimental because of heterogeneous methodologies, insufficient external validation, and insufficient evidence for incremental clinical utility. Diabetes is the most developed translational model with established retinal screening pathways and validated ocular applications of imaging and artificial intelligence, although these cannot be directly extrapolated to systemic diagnosis or treatment guidance. This narrative review assesses retinal biomarkers for cardiovascular, neurological, metabolic, and renal disease with a focus on analytical validity, clinical validity, incremental value, clinical utility, and implementation. The retina is increasingly accepted as a site for discovery of systemic biomarkers and adjunctive risk assessment, although most applications to systemic disease remain to be standardized, validated independently, and studied prospectively before being suitable for routine clinical use.

Authors

Institutions

Publication Details

Journal
Vision
Published
2026-10-09
DOI
https://doi.org/10.3390/vision10040078
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Translational Applications of Retinal Biomarkers in Chronic Cardiovascular, Neurological, Metabolic, and Renal Diseases

F. Cappellani, Irene Gattazzo, Marco Zeppieri, Caterina Gagliano et al.
Vision
Retinal Imaging and Analysis
article

Translational Applications of Retinal Biomarkers in Chronic Cardiovascular, Neurological, Metabolic, and Renal Diseases

F. Cappellani, Irene Gattazzo, Marco Zeppieri, Caterina Gagliano, N Castellino, Matteo Capobianco, Simonetta Gaia Nicolosi
article en

Abstract

Imaging the retina is a powerful non-invasive probe of systemic vascular, neurological, metabolic, and renal disease, making it a cornerstone of the new field of systemic oculomics. Advanced retinal imaging techniques like optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) provide detailed imaging of structural and microvascular changes potentially associated with systemic disease. Derived from fundus photography, structural imaging, vascular imaging, and artificial intelligence-based image analysis, retinal biomarkers have been associated with cardiovascular and cerebrovascular disease, neurodegenerative disorders, diabetes, chronic kidney disease, and related clinical outcomes. However, the translational maturity of these biomarkers is variable depending on imaging modality, target disease, intended clinical use, and level of validation. Longitudinally, retinal vascular characteristics have been associated with cardiovascular as well as cerebrovascular outcomes. In addition, optical coherence tomography has provided reproducible measures of neuroaxonal injury in selected neurological conditions. This is especially true for multiple sclerosis. The majority of retinal biomarkers in Alzheimer disease, Parkinson disease, chronic kidney disease, and systemic risk prediction remain experimental because of heterogeneous methodologies, insufficient external validation, and insufficient evidence for incremental clinical utility. Diabetes is the most developed translational model with established retinal screening pathways and validated ocular applications of imaging and artificial intelligence, although these cannot be directly extrapolated to systemic diagnosis or treatment guidance. This narrative review assesses retinal biomarkers for cardiovascular, neurological, metabolic, and renal disease with a focus on analytical validity, clinical validity, incremental value, clinical utility, and implementation. The retina is increasingly accepted as a site for discovery of systemic biomarkers and adjunctive risk assessment, although most applications to systemic disease remain to be standardized, validated independently, and studied prospectively before being suitable for routine clinical use.

VisionVol. 10(4)
University of Udine (IT), University of Trieste (IT), Università degli Studi di Enna Kore (IT), University of Catania (IT), Ospedale Sant Antonio (IT), Policlinico Universitario di Catania (IT), Azienda Ospedale - Università Padova (IT)
Openalex Percentile: Top 13%
Retinal Imaging and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.