Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

Abstract To characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with...

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Autores principales:	Soo Hyun Cho, Sookyoung Woo, Changsoo Kim, Hee Jin Kim, Hyemin Jang, Byeong C. Kim, Si Eun Kim, Seung Joo Kim, Jun Pyo Kim, Young Hee Jung, Samuel Lockhart, Rik Ossenkoppele, Susan Landau, Duk L. Na, Michael Weiner, Seonwoo Kim, Sang Won Seo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/239c2d8f3b794272af7686582afa37a6
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spelling	oai:doaj.org-article:239c2d8f3b794272af7686582afa37a62021-12-02T14:04:00ZDisease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia10.1038/s41598-021-83585-32045-2322https://doaj.org/article/239c2d8f3b794272af7686582afa37a62021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83585-3https://doaj.org/toc/2045-2322Abstract To characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.Soo Hyun ChoSookyoung WooChangsoo KimHee Jin KimHyemin JangByeong C. KimSi Eun KimSeung Joo KimJun Pyo KimYoung Hee JungSamuel LockhartRik OssenkoppeleSusan LandauDuk L. NaMichael WeinerSeonwoo KimSang Won SeoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Soo Hyun Cho Sookyoung Woo Changsoo Kim Hee Jin Kim Hyemin Jang Byeong C. Kim Si Eun Kim Seung Joo Kim Jun Pyo Kim Young Hee Jung Samuel Lockhart Rik Ossenkoppele Susan Landau Duk L. Na Michael Weiner Seonwoo Kim Sang Won Seo Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
description	Abstract To characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.
format	article
author	Soo Hyun Cho Sookyoung Woo Changsoo Kim Hee Jin Kim Hyemin Jang Byeong C. Kim Si Eun Kim Seung Joo Kim Jun Pyo Kim Young Hee Jung Samuel Lockhart Rik Ossenkoppele Susan Landau Duk L. Na Michael Weiner Seonwoo Kim Sang Won Seo
author_facet	Soo Hyun Cho Sookyoung Woo Changsoo Kim Hee Jin Kim Hyemin Jang Byeong C. Kim Si Eun Kim Seung Joo Kim Jun Pyo Kim Young Hee Jung Samuel Lockhart Rik Ossenkoppele Susan Landau Duk L. Na Michael Weiner Seonwoo Kim Sang Won Seo
author_sort	Soo Hyun Cho
title	Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
title_short	Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
title_full	Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
title_fullStr	Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
title_full_unstemmed	Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia
title_sort	disease progression modelling from preclinical alzheimer’s disease (ad) to ad dementia
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/239c2d8f3b794272af7686582afa37a6
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Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

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