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Liver fibrosis and retinal features in an older Mediterranean population: Results from the Salus in Apulia study

Authors :
Luisa, Lampignano
Alfredo, Niro
Fabio, Castellana
Ilaria, Bortone
Roberta, Zupo
Sarah, Tirelli
Rossella, Tatoli
Chiara, Griseta
Sara, De Nucci
Annamaria, Sila
Giovanni, De Pergola
Caterina, Conte
Giovanni, Alessio
Francesco, Boscia
Giancarlo, Sborgia
Gianluigi, Giannelli
Roberto, Semeraro
Source :
Frontiers in Neuroscience. 16
Publication Year :
2022
Publisher :
Frontiers Media SA, 2022.

Abstract

BackgroundAge 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.MethodsRetinal 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.ResultsIncreased 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).ConclusionOur 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.

Subjects

Subjects :
General Neuroscience

Details

ISSN :
1662453X
Volume :
16
Database :
OpenAIRE
Journal :
Frontiers in Neuroscience
Accession number :
edsair.doi.dedup.....ca03c00a149b83662031129b2ef3b222
Full Text :
https://doi.org/10.3389/fnins.2022.1048375