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Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia

BACKGROUND: Progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by clinical features and a combination of biomarkers may increase the predictive power. In the present study, we investigated whether the combination of olfactory function and plasma neur...

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Autores principales: Zhao, Aonan, Li, Yuanyuan, Yan, Yi, Qiu, Yinghui, Li, Binyin, Xu, Wei, Wang, Ying, Liu, Jun, Deng, Yulei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397685/
https://www.ncbi.nlm.nih.gov/pubmed/32741361
http://dx.doi.org/10.1186/s40035-020-00210-5
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author Zhao, Aonan
Li, Yuanyuan
Yan, Yi
Qiu, Yinghui
Li, Binyin
Xu, Wei
Wang, Ying
Liu, Jun
Deng, Yulei
author_facet Zhao, Aonan
Li, Yuanyuan
Yan, Yi
Qiu, Yinghui
Li, Binyin
Xu, Wei
Wang, Ying
Liu, Jun
Deng, Yulei
author_sort Zhao, Aonan
collection PubMed
description BACKGROUND: Progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by clinical features and a combination of biomarkers may increase the predictive power. In the present study, we investigated whether the combination of olfactory function and plasma neuronal-derived exosome (NDE) Aβ(1–42) can best predict progression to AD dementia. METHODS: 87 MCI patients were enrolled and received the cognitive assessment at 2-year and 3-year follow-up to reevaluate cognition. In the meanwhile, 80 healthy controls and 88 AD dementia patients were enrolled at baseline as well to evaluate the diagnose value in cross-section. Olfactory function was evaluated with the sniffin sticks (SS-16) and Aβ(1–42) levels in NDEs were determined by ELISA. Logistic regression was performed to evaluate the risk factors for cognitive decline in MCI at 2-year and 3-year revisits. RESULTS: In the cross cohort, lower SS-16 scores and higher Aβ(1–42) levels in NDEs were found in MCI and AD dementia compared to healthy controls. For the longitudinal set, 8 MCI individuals developed AD dementia within 2 years, and 16 MCI individuals developed AD dementia within 3 years. The two parameter-combination of SS-16 scores and Aβ(1–42) level in NDEs showed better prediction in the conversion of MCI to AD dementia at 2-year and 3-year revisit. Moreover, after a 3-year follow-up, SS-16 scores also significantly predicted the conversion to AD dementia, where lower scores were associated with a 10-fold increased risk of developing AD dementia (p = 0.006). Similarly, higher Aβ(1–42) levels in NDEs in patients with MCI increased the risk of developing AD dementia by 8.5-fold (p = 0.002). CONCLUSION: A combination of two biomarkers of NDEs (Aβ(1–42)) and SS-16 predicted the conversion of MCI to AD dementia more accurately in combination. These findings have critical implications for understanding the pathophysiology of AD dementia and for developing preventative treatments for cognitive decline.
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spelling pubmed-73976852020-08-06 Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia Zhao, Aonan Li, Yuanyuan Yan, Yi Qiu, Yinghui Li, Binyin Xu, Wei Wang, Ying Liu, Jun Deng, Yulei Transl Neurodegener Research BACKGROUND: Progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by clinical features and a combination of biomarkers may increase the predictive power. In the present study, we investigated whether the combination of olfactory function and plasma neuronal-derived exosome (NDE) Aβ(1–42) can best predict progression to AD dementia. METHODS: 87 MCI patients were enrolled and received the cognitive assessment at 2-year and 3-year follow-up to reevaluate cognition. In the meanwhile, 80 healthy controls and 88 AD dementia patients were enrolled at baseline as well to evaluate the diagnose value in cross-section. Olfactory function was evaluated with the sniffin sticks (SS-16) and Aβ(1–42) levels in NDEs were determined by ELISA. Logistic regression was performed to evaluate the risk factors for cognitive decline in MCI at 2-year and 3-year revisits. RESULTS: In the cross cohort, lower SS-16 scores and higher Aβ(1–42) levels in NDEs were found in MCI and AD dementia compared to healthy controls. For the longitudinal set, 8 MCI individuals developed AD dementia within 2 years, and 16 MCI individuals developed AD dementia within 3 years. The two parameter-combination of SS-16 scores and Aβ(1–42) level in NDEs showed better prediction in the conversion of MCI to AD dementia at 2-year and 3-year revisit. Moreover, after a 3-year follow-up, SS-16 scores also significantly predicted the conversion to AD dementia, where lower scores were associated with a 10-fold increased risk of developing AD dementia (p = 0.006). Similarly, higher Aβ(1–42) levels in NDEs in patients with MCI increased the risk of developing AD dementia by 8.5-fold (p = 0.002). CONCLUSION: A combination of two biomarkers of NDEs (Aβ(1–42)) and SS-16 predicted the conversion of MCI to AD dementia more accurately in combination. These findings have critical implications for understanding the pathophysiology of AD dementia and for developing preventative treatments for cognitive decline. BioMed Central 2020-08-03 /pmc/articles/PMC7397685/ /pubmed/32741361 http://dx.doi.org/10.1186/s40035-020-00210-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research
Zhao, Aonan
Li, Yuanyuan
Yan, Yi
Qiu, Yinghui
Li, Binyin
Xu, Wei
Wang, Ying
Liu, Jun
Deng, Yulei
Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title_full Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title_fullStr Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title_full_unstemmed Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title_short Increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to Alzheimer’s dementia
title_sort increased prediction value of biomarker combinations for the conversion of mild cognitive impairment to alzheimer’s dementia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397685/
https://www.ncbi.nlm.nih.gov/pubmed/32741361
http://dx.doi.org/10.1186/s40035-020-00210-5
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