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. 2018 Feb 8;13(2):e0192646.
doi: 10.1371/journal.pone.0192646. eCollection 2018.

Evaluation of inner retinal layers as biomarkers in mild cognitive impairment to moderate Alzheimer's disease

Affiliations

Evaluation of inner retinal layers as biomarkers in mild cognitive impairment to moderate Alzheimer's disease

Eleonora M Lad et al. PLoS One. .

Abstract

Inner retina in Alzheimer's Disease (AD) may experience neuroinflammation resulting in atrophy. The objective of our study was to determine whether retinal GCIPL (ganglion cell-inner plexiform layer) or nerve fiber layer (NFL) thickness may serve as noninvasive biomarkers to diagnose AD. This cross-sectional case-control study enrolled 15 mild cognitive impairment (MCI) patients, 15 mild-moderate AD patients, and 18 cognitively normal adults. NFL and GCIPL thicknesses on optical coherence tomography (OCT) were measured using Duke Optical Coherence Tomography Retinal Analysis Program (DOCTRAP) and Spectralis software. We demonstrated that regional thicknesses of NFL or GCIPL on macular or nerve OCTs did not differ between groups. However, a multi-variate regression analysis identified macular areas with a significant thickening or thinning in NFL and GCIPL in MCI and AD patients. Our primary findings controvert previous reports of thinner NFL in moderate-to-severe AD. The areas of thickening of GCIPL and NFL in the macula adjacent to areas of thinning, as revealed by a more complex statistical model, suggest that NFL and GCIPL may undergo dynamic changes during AD progression.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Results of a multi-variate regression analysis with quasi-least squares, without correction for multiple comparisons.
This analysis identified areas in the macula that were statistically significantly thinner (red) or thicker (green) in NFL and GCIPL in MCI and AD patients as compared to controls, or in AD compared to MCI.
Fig 2
Fig 2. Results of the multi-variate regression analysis with quasi-least squares, adjusted for multiple comparisons.
Fig 3
Fig 3. Distribution of MoCA scores among the three study groups.

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