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Author Spotlight: Ex Vivo OCT-Based Multimodal Imaging of Human Donor Eyes for Research into Age-Related Macular Degeneration
Published on: May 26, 2023
Liver fibrosis and retinal features in an older Mediterranean population: Results from the Salus in Apulia study
Luisa Lampignano1, Alfredo Niro2, Fabio Castellana1
1Unit of Research Methodology and Data Sciences for Population Health, "Salus in Apulia Study", National Institute of Gastroenterology Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) "Saverio de Bellis", Research Hospital, Castellana Grotte, Italy.
Background:
Age is a leading contributor to the liver fibrosis rate and a gradual deterioration of optical function, but this association in older populations is still under-explored. The present study aimed to explore the link between vascular and neural retinal characteristics and the risk of liver fibrosis in 731 older adults from the population-based Salus in Apulia study.
Methods:
Retinal features were obtained using optical coherence tomography (OCT) and OCT-angiography (OCT-A). Liver fibrosis risk was taken as the fibrosis-4 (FIB-4) score. Generalized linear models (logistic regression) were used to estimate the association effect between each unit increase of OCT and OCT-A parameters as independent variables and a FIB-4 ≥ 2.67 score as an outcome. Generalized additive models were used to assess the non-linear association between OCT-A features and the linear FIB-4 score.
Results:
Increased gangliar cell complex (GCC) thickness was inversely associated with a FIB-4 score above the cut-off in both the raw model (OR: 0.98; 95% CI: 0.96-0.99; SE: 0.01) and after adjustment for age, sex, education, hypertension, diabetes, total cholesterol, and triglycerides (OR: 0.98; 95% CI: 0.97-0.99; SE: 0.01).
Conclusion:
Our findings add to the growing volume of scientific literature demonstrating that liver fibrosis is associated with retinal neurodegeneration. This study raises a number of new questions, including whether OCT-A may be used to track the progression of metabolic abnormalities and define exact thresholds for predicting and classifying liver disease.
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