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Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments
BACKGROUND: Although amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer’s disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore c...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343354/ https://www.ncbi.nlm.nih.gov/pubmed/30670089 http://dx.doi.org/10.1186/s13195-018-0462-z |
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author | Kim, Yeo Jin Cho, Seong-Kyoung Kim, Hee Jin Lee, Jin San Lee, Juyoun Jang, Young Kyoung Vogel, Jacob W. Na, Duk L. Kim, Changsoo Seo, Sang Won |
author_facet | Kim, Yeo Jin Cho, Seong-Kyoung Kim, Hee Jin Lee, Jin San Lee, Juyoun Jang, Young Kyoung Vogel, Jacob W. Na, Duk L. Kim, Changsoo Seo, Sang Won |
author_sort | Kim, Yeo Jin |
collection | PubMed |
description | BACKGROUND: Although amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer’s disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory. METHODS: We retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB. RESULTS: Trajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group. CONCLUSIONS: Our data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13195-018-0462-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6343354 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63433542019-01-24 Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments Kim, Yeo Jin Cho, Seong-Kyoung Kim, Hee Jin Lee, Jin San Lee, Juyoun Jang, Young Kyoung Vogel, Jacob W. Na, Duk L. Kim, Changsoo Seo, Sang Won Alzheimers Res Ther Research BACKGROUND: Although amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer’s disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory. METHODS: We retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB. RESULTS: Trajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group. CONCLUSIONS: Our data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13195-018-0462-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-22 /pmc/articles/PMC6343354/ /pubmed/30670089 http://dx.doi.org/10.1186/s13195-018-0462-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Kim, Yeo Jin Cho, Seong-Kyoung Kim, Hee Jin Lee, Jin San Lee, Juyoun Jang, Young Kyoung Vogel, Jacob W. Na, Duk L. Kim, Changsoo Seo, Sang Won Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title | Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title_full | Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title_fullStr | Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title_full_unstemmed | Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title_short | Data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
title_sort | data-driven prognostic features of cognitive trajectories in patients with amnestic mild cognitive impairments |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343354/ https://www.ncbi.nlm.nih.gov/pubmed/30670089 http://dx.doi.org/10.1186/s13195-018-0462-z |
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