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. 2020 Mar 24:12:81.
doi: 10.3389/fnagi.2020.00081. eCollection 2020.

Reduced Retinal Thickness Predicts Age-Related Changes in Cognitive Function

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Reduced Retinal Thickness Predicts Age-Related Changes in Cognitive Function

Najiba Mammadova et al. Front Aging Neurosci. .

Abstract

Currently, there is a lack of biomarkers to identify individuals in the early stages of Alzheimer's disease (AD). A preponderance of evidence suggests that neurodegenerative processes that affect the brain, may also affect the retina. Using optical coherence tomography (OCT), a non-invasive approach, many have shown thinning of the retina in AD and the developmental precursor to AD, mild cognitive impairment (MCI). However, the relationship between retinal thickness and cognitive function is not entirely clear. This is likely due to the disparity in diagnostic criteria used to determine MCI that does not fully probe the cognitive domains that are particularly vulnerable to aging. This study used a comprehensive neuropsychological assessment involving multiple domains of cognition to determine if retinal thickness correlates with cognitive performance in a normal aged population. In this study, 20 healthy individuals between 60 and 90 years of age were administered neuropsychological assessments probing various domains of cognitive function, and OCT to measure peripapillary retinal nerve fiber layer (RNFL) thickness. We found that RNFL thickness is correlated with neuropsychological performance in multiple cognitive domains (e.g., working memory, psychomotor speed, and executive function). Our work demonstrates a positive correlation between RNFL thickness and several, but not all, domains of cognitive function in a normative aging population. By determining which cognitive domains retinal thickness can predict, this work can help identify individuals at risk or in preclinical stages of AD and other neurodegenerative diseases.

Keywords: cognitive function; executive function; optical coherence tomograhy; retina; retinal nerve fiber layer.

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