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Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index
To realize an individual-level risk evaluation of progression of early Alzheimer’s disease (AD), we applied an AD resemblance atrophy index (AD-RAI) to differentiate the subjects at risk of progression from normal subjects (NC) to mild cognitive impairment (MCI) and from MCI to AD. We included 183 s...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738429/ https://www.ncbi.nlm.nih.gov/pubmed/31467257 http://dx.doi.org/10.18632/aging.102184 |
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author | Zhao, Lei Luo, Yishan Lew, Darson Liu, Wenyan Au, Lisa Mok, Vincent Shi, Lin |
author_facet | Zhao, Lei Luo, Yishan Lew, Darson Liu, Wenyan Au, Lisa Mok, Vincent Shi, Lin |
author_sort | Zhao, Lei |
collection | PubMed |
description | To realize an individual-level risk evaluation of progression of early Alzheimer’s disease (AD), we applied an AD resemblance atrophy index (AD-RAI) to differentiate the subjects at risk of progression from normal subjects (NC) to mild cognitive impairment (MCI) and from MCI to AD. We included 183 subjects with a two-year follow-up: 50 NC stable (NCs), 23 NC-to-MCI converters (NCc), 50 MCI stable (MCIs), 35 MCI-to-AD converters (MCIc), 25 AD stable (ADs). ANCOVA analyses were used to identify baseline brain atrophy in converters compared with non-converters. To explore the relative merits of AD-RAI over individual regional volumetric measures in prediction of disease progression, we searched for the optimal cutoff for each measure in logistic regressions and plotted the longitudinal trajectories of these brain volumetric measures in converters and non-converters. Baseline AD-RAI performed the best in differentiating NCc from NCs (odds ratio 26.35, AUC 0.740) and MCIc from MCIs (odds ratio 8.91, AUC 0.771). The AD-RAI presented greater increase in the second year for NCc vs. NCs but not for MCIc vs. MCIs. Baseline AD-RAIs were also associated with CSF-based and PET-based AD biomarkers. These results showed the potential of AD-RAI in early risk estimation before progression to MCI/AD at an individual-level. |
format | Online Article Text |
id | pubmed-6738429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-67384292019-09-16 Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index Zhao, Lei Luo, Yishan Lew, Darson Liu, Wenyan Au, Lisa Mok, Vincent Shi, Lin Aging (Albany NY) Research Paper To realize an individual-level risk evaluation of progression of early Alzheimer’s disease (AD), we applied an AD resemblance atrophy index (AD-RAI) to differentiate the subjects at risk of progression from normal subjects (NC) to mild cognitive impairment (MCI) and from MCI to AD. We included 183 subjects with a two-year follow-up: 50 NC stable (NCs), 23 NC-to-MCI converters (NCc), 50 MCI stable (MCIs), 35 MCI-to-AD converters (MCIc), 25 AD stable (ADs). ANCOVA analyses were used to identify baseline brain atrophy in converters compared with non-converters. To explore the relative merits of AD-RAI over individual regional volumetric measures in prediction of disease progression, we searched for the optimal cutoff for each measure in logistic regressions and plotted the longitudinal trajectories of these brain volumetric measures in converters and non-converters. Baseline AD-RAI performed the best in differentiating NCc from NCs (odds ratio 26.35, AUC 0.740) and MCIc from MCIs (odds ratio 8.91, AUC 0.771). The AD-RAI presented greater increase in the second year for NCc vs. NCs but not for MCIc vs. MCIs. Baseline AD-RAIs were also associated with CSF-based and PET-based AD biomarkers. These results showed the potential of AD-RAI in early risk estimation before progression to MCI/AD at an individual-level. Impact Journals 2019-08-29 /pmc/articles/PMC6738429/ /pubmed/31467257 http://dx.doi.org/10.18632/aging.102184 Text en Copyright © 2019 Zhao et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 3.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Zhao, Lei Luo, Yishan Lew, Darson Liu, Wenyan Au, Lisa Mok, Vincent Shi, Lin Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title | Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title_full | Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title_fullStr | Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title_full_unstemmed | Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title_short | Risk estimation before progression to mild cognitive impairment and Alzheimer’s disease: an AD resemblance atrophy index |
title_sort | risk estimation before progression to mild cognitive impairment and alzheimer’s disease: an ad resemblance atrophy index |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738429/ https://www.ncbi.nlm.nih.gov/pubmed/31467257 http://dx.doi.org/10.18632/aging.102184 |
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