Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline.
<h4>Background</h4>Alzheimer's disease (AD) pathology precedes symptoms and its detection can identify at-risk individuals who may benefit from early treatment. Since the retinal nerve fiber layer (RNFL) is depleted in established AD, we tested whether its thickness can predict whet...
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doaj-325616b7ffac4b298499a34310d35be52021-04-10T04:31:00ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01155e023278510.1371/journal.pone.0232785Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline.Samuel AsanadMichele FantiniWilliam SultanMarco NassisiChristian M FelixJessica WuRustum KaranjiaFred N Ross-CisnerosAbhay P SagareBerislav V ZlokovicHelena C ChuiJanice M PogodaXianghong ArakakiAlfred N FontehAlfredo A SadunMichael G Harrington<h4>Background</h4>Alzheimer's disease (AD) pathology precedes symptoms and its detection can identify at-risk individuals who may benefit from early treatment. Since the retinal nerve fiber layer (RNFL) is depleted in established AD, we tested whether its thickness can predict whether cognitively healthy (CH) individuals have a normal or pathological cerebrospinal fluid (CSF) Aß42 (A) and tau (T) ratio.<h4>Methods</h4>As part of an ongoing longitudinal study, we enrolled CH individuals, excluding those with cognitive impairment and significant ocular pathology. We classified the CH group into two sub-groups, normal (CH-NAT, n = 16) or pathological (CH-PAT, n = 27), using a logistic regression model from the CSF AT ratio that identified >85% of patients with a clinically probable AD diagnosis. Spectral-domain optical coherence tomography (OCT) was acquired for RNFL, ganglion cell-inner plexiform layer (GC-IPL), and macular thickness. Group differences were tested using mixed model repeated measures and a classification model derived using multiple logistic regression.<h4>Results</h4>Mean age (± standard deviation) in the CH-PAT group (n = 27; 75.2 ± 8.4 years) was similar (p = 0.50) to the CH-NAT group (n = 16; 74.1 ± 7.9 years). Mean RNFL (standard error) was thinner in the CH-PAT group by 9.8 (2.7) μm; p < 0.001. RNFL thickness classified CH-NAT vs. CH-PAT with 87% sensitivity and 56.3% specificity.<h4>Conclusions</h4>Our retinal data predict which individuals have CSF biomarkers of AD pathology before cognitive deficits are detectable with 87% sensitivity. Such results from easy-to-acquire, objective and non-invasive measurements of the RNFL merit further study of OCT technology to monitor or screen for early AD pathology.https://doi.org/10.1371/journal.pone.0232785 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Samuel Asanad Michele Fantini William Sultan Marco Nassisi Christian M Felix Jessica Wu Rustum Karanjia Fred N Ross-Cisneros Abhay P Sagare Berislav V Zlokovic Helena C Chui Janice M Pogoda Xianghong Arakaki Alfred N Fonteh Alfredo A Sadun Michael G Harrington |
spellingShingle |
Samuel Asanad Michele Fantini William Sultan Marco Nassisi Christian M Felix Jessica Wu Rustum Karanjia Fred N Ross-Cisneros Abhay P Sagare Berislav V Zlokovic Helena C Chui Janice M Pogoda Xianghong Arakaki Alfred N Fonteh Alfredo A Sadun Michael G Harrington Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. PLoS ONE |
author_facet |
Samuel Asanad Michele Fantini William Sultan Marco Nassisi Christian M Felix Jessica Wu Rustum Karanjia Fred N Ross-Cisneros Abhay P Sagare Berislav V Zlokovic Helena C Chui Janice M Pogoda Xianghong Arakaki Alfred N Fonteh Alfredo A Sadun Michael G Harrington |
author_sort |
Samuel Asanad |
title |
Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. |
title_short |
Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. |
title_full |
Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. |
title_fullStr |
Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. |
title_full_unstemmed |
Retinal nerve fiber layer thickness predicts CSF amyloid/tau before cognitive decline. |
title_sort |
retinal nerve fiber layer thickness predicts csf amyloid/tau before cognitive decline. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2020-01-01 |
description |
<h4>Background</h4>Alzheimer's disease (AD) pathology precedes symptoms and its detection can identify at-risk individuals who may benefit from early treatment. Since the retinal nerve fiber layer (RNFL) is depleted in established AD, we tested whether its thickness can predict whether cognitively healthy (CH) individuals have a normal or pathological cerebrospinal fluid (CSF) Aß42 (A) and tau (T) ratio.<h4>Methods</h4>As part of an ongoing longitudinal study, we enrolled CH individuals, excluding those with cognitive impairment and significant ocular pathology. We classified the CH group into two sub-groups, normal (CH-NAT, n = 16) or pathological (CH-PAT, n = 27), using a logistic regression model from the CSF AT ratio that identified >85% of patients with a clinically probable AD diagnosis. Spectral-domain optical coherence tomography (OCT) was acquired for RNFL, ganglion cell-inner plexiform layer (GC-IPL), and macular thickness. Group differences were tested using mixed model repeated measures and a classification model derived using multiple logistic regression.<h4>Results</h4>Mean age (± standard deviation) in the CH-PAT group (n = 27; 75.2 ± 8.4 years) was similar (p = 0.50) to the CH-NAT group (n = 16; 74.1 ± 7.9 years). Mean RNFL (standard error) was thinner in the CH-PAT group by 9.8 (2.7) μm; p < 0.001. RNFL thickness classified CH-NAT vs. CH-PAT with 87% sensitivity and 56.3% specificity.<h4>Conclusions</h4>Our retinal data predict which individuals have CSF biomarkers of AD pathology before cognitive deficits are detectable with 87% sensitivity. Such results from easy-to-acquire, objective and non-invasive measurements of the RNFL merit further study of OCT technology to monitor or screen for early AD pathology. |
url |
https://doi.org/10.1371/journal.pone.0232785 |
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