Differential risk of Alzheimer's disease in MCI subjects with elevated Abeta

People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. The risk classification of AD in MCI was based on se...

Full description

Saved in:
Bibliographic Details
Published inJournal of the neurological sciences Vol. 467; p. 123319
Main Authors Zhou, Bin, Fukushima, Masanori
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier B.V 15.12.2024
Subjects
Online AccessGet full text
ISSN0022-510X
1878-5883
1878-5883
DOI10.1016/j.jns.2024.123319

Cover

Loading…
Abstract People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. The risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol. In total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up. Risk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up. •Using hippocampus volume and cognition test ADAScog13 we created one new parameter Cog_Vol.•The parameter Cog_Vol can detect super high risk group (conversion rate >90%) and low risk group of AD in subjects with Aβ+ MCI•The method simple and practicable in identifying subjects when considering prevention clinical trial design of AD.
AbstractList People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. The risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol. In total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up. Risk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up.
People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. The risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol. In total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up. Risk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up. •Using hippocampus volume and cognition test ADAScog13 we created one new parameter Cog_Vol.•The parameter Cog_Vol can detect super high risk group (conversion rate >90%) and low risk group of AD in subjects with Aβ+ MCI•The method simple and practicable in identifying subjects when considering prevention clinical trial design of AD.
People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease.BACKGROUNDSPeople with elevated beta amyloid have different risk and progress speed to Alzheimer's disease.The research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data.PURPOSEThe research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data.The risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol.METHODSThe risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol.In total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up.RESULTSIn total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up.Risk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up.DISCUSSIONRisk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up.
AbstractBackgroundsPeople with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. PurposeThe research is to validate the risk classification of AD developed in the Shanghai mild cognitive impairment (MCI) cohort study using ADNI data. MethodsThe risk classification of AD in MCI was based on several optimal cut-off points of a novel parameter Cog_Vol. ResultsIn total, 843 subjects with MCI were included, of whom 220 had elevated PET beta amyloid. 273 (32.3 %) and 70 (31.8 %) progressed to AD in all subjects and in those with elevated PET beta amyloid, respectively. The risk of AD in subjects whose Cog_Vol >340 was very low, while the risk for those with Cog_Vol less than 101 indicated a super high within 4 years of follow-up. DiscussionRisk classification using Cog_Vol at an optimal value was able to detect subjects among those with PET-amyloid-elevated MCI were at greater risk of developing AD and were unlikely to develop AD within 4 years of follow-up.
ArticleNumber 123319
Author Zhou, Bin
Fukushima, Masanori
AuthorAffiliation Foundation for Learning Health Society Institute, Nagoya, Aichi 450-0003, Japan
AuthorAffiliation_xml – name: Foundation for Learning Health Society Institute, Nagoya, Aichi 450-0003, Japan
Author_xml – sequence: 1
  givenname: Bin
  surname: Zhou
  fullname: Zhou, Bin
  email: bin.shu928@lhsi.jp
– sequence: 2
  givenname: Masanori
  surname: Fukushima
  fullname: Fukushima, Masanori
BackLink https://www.ncbi.nlm.nih.gov/pubmed/39612639$$D View this record in MEDLINE/PubMed
BookMark eNqFkU1v1DAQhi3Uim4LP4AL8o1esnhsJ7GFhLRaviot4gBI3CzbmahOs06xk6Ly65toCwck2tNcnndG7zOn5CgOEQl5AWwNDKrX3bqLec0Zl2vgQoB-QlagalWUSokjsmKM86IE9uOEnObcMcYqpfRTciJ0BbwSekV270LbYsI4BtvTFPIVHVq66X9fYthjepVpEzLajDRE-nl7QfPkOvRjpr_CeEmxxxs7YkM3Dkf7jBy3ts_4_H6eke8f3n_bfip2Xz5ebDe7wktgY6EaVQrtG_DonGt4xSSzumx5ray2XDjeSgVOSXRS1xzqStY414BWaWhrJc7I-WHvdRp-TphHsw_ZY9_biMOUjQAhZx0Sqhl9eY9Obo-NuU5hb9Ot-WNgBuAA-DTknLD9iwAzi2XTmdmyWSybg-U58-aQwbnkTcBksg8YPTYhzW5MM4QH02__Sfs-xOBtf4W3mLthSnG2Z8Bkbpj5unxxeSKXjMmyXDrp_y945Pgd-wGqGQ
Cites_doi 10.1016/j.jalz.2018.02.018
10.1159/000487852
10.1186/s13024-021-00503-x
10.1155/2020/7029642
10.1016/j.neurobiolaging.2011.02.022
10.1109/JBHI.2020.2984355
10.1186/s13195-021-00900-w
10.1093/braincomms/fcac231
10.1186/s13195-022-01150-0
10.3233/JAD-210092
10.1186/s13024-019-0320-x
10.1016/j.neuroimage.2012.01.021
10.3389/fnagi.2017.00329
10.2174/1567205020666230914161034
10.3390/ijms21228661
10.1007/s00401-014-1269-z
10.3233/JAD-190818
10.1016/S0006-8993(00)03082-1
10.4172/2161-0460.1000224
10.1056/NEJMoa2212948
10.3389/fnagi.2019.00220
10.2967/jnumed.114.148981
10.1038/s41591-021-01348-z
10.2967/jnumed.119.230797
10.3233/JAD-201438
10.1007/s11682-020-00366-8
10.1016/j.neurobiolaging.2021.09.017
10.1001/jamaneurol.2021.4654
10.1016/j.nicl.2020.102387
10.3233/JAD-200906
ContentType Journal Article
Copyright 2024 The Authors
The Authors
Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
Copyright_xml – notice: 2024 The Authors
– notice: The Authors
– notice: Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
CorporateAuthor The Alzheimer's Disease Neuroimaging Initiative
Alzheimer's Disease Neuroimaging Initiative
CorporateAuthor_xml – name: The Alzheimer's Disease Neuroimaging Initiative
– name: Alzheimer's Disease Neuroimaging Initiative
DBID 6I.
AAFTH
AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
DOI 10.1016/j.jns.2024.123319
DatabaseName ScienceDirect Open Access Titles
Elsevier:ScienceDirect:Open Access
CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList MEDLINE


MEDLINE - Academic

Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
EISSN 1878-5883
EndPage 123319
ExternalDocumentID 39612639
10_1016_j_jns_2024_123319
S0022510X24004556
1_s2_0_S0022510X24004556
Genre Journal Article
GeographicLocations China
GeographicLocations_xml – name: China
GroupedDBID ---
--K
--M
.1-
.FO
.~1
0R~
1B1
1P~
1RT
1~.
1~5
4.4
457
4G.
5GY
5RE
5VS
7-5
71M
8P~
9JM
AABNK
AAEDT
AAEDW
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AATTM
AAXKI
AAXLA
AAXUO
AAYWO
ABBQC
ABCQJ
ABFNM
ABFRF
ABGSF
ABIVO
ABJNI
ABLJU
ABMAC
ABMZM
ABTEW
ABUDA
ACDAQ
ACGFO
ACGFS
ACIEU
ACIUM
ACRLP
ACVFH
ADBBV
ADCNI
ADEZE
ADUVX
AEBSH
AEFWE
AEHWI
AEIPS
AEKER
AENEX
AEUPX
AEVXI
AFJKZ
AFPUW
AFRHN
AFTJW
AFXIZ
AGCQF
AGHFR
AGUBO
AGWIK
AGYEJ
AHHHB
AIEXJ
AIGII
AIIUN
AIKHN
AITUG
AJRQY
AJUYK
AKBMS
AKRWK
AKYEP
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
ANKPU
ANZVX
APXCP
AXJTR
BKOJK
BLXMC
BNPGV
CS3
EBS
EFJIC
EFKBS
EO8
EO9
EP2
EP3
F5P
FDB
FIRID
FNPLU
FYGXN
G-Q
GBLVA
IHE
J1W
KOM
L7B
LX8
M29
M2V
M41
MO0
MOBAO
N9A
O-L
O9-
OAUVE
OP~
OZT
P-8
P-9
P2P
PC.
Q38
ROL
RPZ
SAE
SCC
SDF
SDG
SDP
SEL
SES
SEW
SPCBC
SSH
SSN
SSU
SSZ
T5K
Z5R
~G-
.55
.GJ
29L
53G
AACTN
AAQXK
ABWVN
ABXDB
ACRPL
ADMUD
ADNMO
AFCTW
AFKWA
AGRDE
AJOXV
AKRLJ
AMFUW
ASPBG
AVWKF
AZFZN
EJD
FEDTE
FGOYB
G-2
HDW
HMK
HMO
HMQ
HVGLF
HZ~
R2-
RIG
SNS
WUQ
X7M
ZGI
ZXP
6I.
AAFTH
AAYXX
AGQPQ
AGRNS
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
ID FETCH-LOGICAL-c410t-8d8539cd1cebbbd26040a95f278a9a23b2f481b84eb497217647e5101f891f783
IEDL.DBID .~1
ISSN 0022-510X
1878-5883
IngestDate Fri Jul 11 11:07:45 EDT 2025
Wed Feb 19 02:18:00 EST 2025
Tue Jul 01 00:51:33 EDT 2025
Sat Dec 21 16:01:23 EST 2024
Tue Feb 25 20:00:48 EST 2025
Tue Aug 26 16:33:42 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords PET beta amyloid
Mild cognitive impariment
Alzheimer's disease
Risk assessment
Language English
License This is an open access article under the CC BY-NC-ND license.
Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c410t-8d8539cd1cebbbd26040a95f278a9a23b2f481b84eb497217647e5101f891f783
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
OpenAccessLink https://www.sciencedirect.com/science/article/pii/S0022510X24004556
PMID 39612639
PQID 3134331416
PQPubID 23479
PageCount 1
ParticipantIDs proquest_miscellaneous_3134331416
pubmed_primary_39612639
crossref_primary_10_1016_j_jns_2024_123319
elsevier_sciencedirect_doi_10_1016_j_jns_2024_123319
elsevier_clinicalkeyesjournals_1_s2_0_S0022510X24004556
elsevier_clinicalkey_doi_10_1016_j_jns_2024_123319
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2024-12-15
PublicationDateYYYYMMDD 2024-12-15
PublicationDate_xml – month: 12
  year: 2024
  text: 2024-12-15
  day: 15
PublicationDecade 2020
PublicationPlace Netherlands
PublicationPlace_xml – name: Netherlands
PublicationTitle Journal of the neurological sciences
PublicationTitleAlternate J Neurol Sci
PublicationYear 2024
Publisher Elsevier B.V
Publisher_xml – name: Elsevier B.V
References Zhou, Zhao, Kojima, Ding, Fukushima, Hong (bb0080) 2016; 6
Zhou, Fukushima (bb0160) 2020; 21
van Dyck, Swanson, Aisen, Bateman, Chen, Gee, Kanekiyo, Li, Reyderman, Cohen, Froelich, Katayama, Sabbagh, Vellas, Watson, Dhadda, Irizarry, Kramer, Iwatsubo (bb0120) 2023; 388
Nagaraj, Duong (bb0030) 2021; 80
Beyer, Brendel, Scheiwein, Sauerbeck, Hosakawa, Alberts, Shi, Bartenstein, Ishii, Seibyl, Cumming, Rominger (bb0020) 2020; 74
Josephs, Murray, Whitwell, Parisi, Petrucelli, Jack, Petersen, Dickson (bb0125) 2014; 127
Blazhenets, Ma, Sörensen, Schiller, Rücker, Eidelberg, Frings, Meyer (bb0015) 2020; 61
Arai, Yamazaki, Mori, Muramatsu, Asano, Katayama (bb0135) 2001; 888
Shim, Kang, Youn, An, Kim (bb0140) 2022; 14
Twohig, Nielsen (bb0145) 2019; 14
König, Linz, Tröger, Wolters, Alexandersson, Robert (bb0110) 2018; 45
Sarica, Cerasa, Quattrone (bb0065) 2017; 9
Zhou B, Tanabe K, Kojima S, Teramukai S, Fukushima M, Alzheimer Disease Neuroimaging Initiative Alzheimer disease neuroimaging initiative. protective factors modulate the risk of beta amyloid in Alzheimer's disease. Behav. Neurol. (2020):7029642. doi
Platero, Tobar, Alzheimer’s Disease Neuroimaging Initiative (bb0050) 2021; 15
Fristed, Skirrow, Meszaros, Lenain, Meepegama, Papp, Ropacki, Weston (bb0105) 2022; 4
Grueso, Viejo-Sobera (bb0055) 2021; 13
Jack, Bennett, Blennow, Carrillo, Dunn, Haeberlein, Holtzman, Jagust, Jessen, Karlawish, Liu, Molinuevo, Montine, Phelps, Rankin, Rowe, Scheltens, Siemers, Snyder, Sperling, Contributors. (bb0005) 2018; 14
Zhou, Zhao, Kojima, Ding, Higashide, Fukushima, Hong (bb0075) 2023; 20
de Souza, Chupin, Lamari, Jardel, Leclercq, Colliot, Lehéricy, Dubois, Sarazin (bb0150) 2012; 33
Li, Zhang, Riphagen, Yochim, Li, Liu, Salat, Alzheimer’s Disease Neuroimaging Initiative (bb0045) 2020; 28
Fischl (bb0095) 2012; 62
.
Leuzy, Smith, Cullen, Strandberg, Vogel, Binette, Borroni, Janelidze, Ohlsson, Jögi, Ossenkoppele, Palmqvist, Mattsson-Carlgren, Klein, Stomrud, Hansson (bb0025) 2022; 79
ADNI (bb0090) 2024
Prakash, Abdelaziz, Zhang, Strange, Tohka, Alzheimer’s Disease Neuroimaging Initiative (bb0035) 2021; 79
Wisse, Xie, Das, de Flores, Hansson, Habes, Doshi, Davatzikos, Yushkevich, Wolk, Alzheimers Disease Neuroimaging Initiative (bb0155) 2022; 109
Landau, Fero, Baker, Koeppe, Mintun, Chen, Reiman, Jagust (bb0085) 2015; 56
Palmqvist, Tideman, Cullen, Zetterberg, Blennow, Alzheimer’s Disease Neuroimaging Initiative, Dage, Stomrud, Janelidze, Mattsson-Carlgren, Hansson (bb0070) 2021; 27
ADNI4 (bb0115) 2024
Darmanthé, Tabatabaei-Jafari, Cherbuin, Alzheimer’s Disease Neuroimaging Initiative (bb0040) 2021; 82
Jo, Nho, Saykin (bb0060) 2019; 11
Eke, Jammeh, Li, Carroll, Pearson, Ifeachor (bb0100) 2021; 25
Meneses, Koga, O’Leary, Dickson, Bu, Zhao (bb0130) 2021; 16
Shim (10.1016/j.jns.2024.123319_bb0140) 2022; 14
Palmqvist (10.1016/j.jns.2024.123319_bb0070) 2021; 27
Arai (10.1016/j.jns.2024.123319_bb0135) 2001; 888
König (10.1016/j.jns.2024.123319_bb0110) 2018; 45
Platero (10.1016/j.jns.2024.123319_bb0050) 2021; 15
Fristed (10.1016/j.jns.2024.123319_bb0105) 2022; 4
Li (10.1016/j.jns.2024.123319_bb0045) 2020; 28
Zhou (10.1016/j.jns.2024.123319_bb0160) 2020; 21
Meneses (10.1016/j.jns.2024.123319_bb0130) 2021; 16
Sarica (10.1016/j.jns.2024.123319_bb0065) 2017; 9
Zhou (10.1016/j.jns.2024.123319_bb0080) 2016; 6
Grueso (10.1016/j.jns.2024.123319_bb0055) 2021; 13
Wisse (10.1016/j.jns.2024.123319_bb0155) 2022; 109
Eke (10.1016/j.jns.2024.123319_bb0100) 2021; 25
Jack (10.1016/j.jns.2024.123319_bb0005) 2018; 14
Beyer (10.1016/j.jns.2024.123319_bb0020) 2020; 74
Fischl (10.1016/j.jns.2024.123319_bb0095) 2012; 62
Twohig (10.1016/j.jns.2024.123319_bb0145) 2019; 14
ADNI4 (10.1016/j.jns.2024.123319_bb0115)
Josephs (10.1016/j.jns.2024.123319_bb0125) 2014; 127
Darmanthé (10.1016/j.jns.2024.123319_bb0040) 2021; 82
van Dyck (10.1016/j.jns.2024.123319_bb0120) 2023; 388
Nagaraj (10.1016/j.jns.2024.123319_bb0030) 2021; 80
Zhou (10.1016/j.jns.2024.123319_bb0075) 2023; 20
de Souza (10.1016/j.jns.2024.123319_bb0150) 2012; 33
Leuzy (10.1016/j.jns.2024.123319_bb0025) 2022; 79
10.1016/j.jns.2024.123319_bb0010
Jo (10.1016/j.jns.2024.123319_bb0060) 2019; 11
Blazhenets (10.1016/j.jns.2024.123319_bb0015) 2020; 61
Prakash (10.1016/j.jns.2024.123319_bb0035) 2021; 79
Landau (10.1016/j.jns.2024.123319_bb0085) 2015; 56
ADNI (10.1016/j.jns.2024.123319_bb0090)
References_xml – volume: 74
  start-page: 101
  year: 2020
  end-page: 112
  ident: bb0020
  article-title: Alzheimer’s Disease Neuroimaging Initiative improved risk stratification for progression from mild cognitive impairment to Alzheimer’s Disease with a multi-analytical evaluation of amyloid-β positron emission tomography
  publication-title: J. Alzheimers Dis.
– volume: 80
  start-page: 1079
  year: 2021
  end-page: 1090
  ident: bb0030
  article-title: Deep learning and risk score classification of mild cognitive impairment and Alzheimer’s Disease
  publication-title: J. Alzheimers Dis.
– volume: 33
  start-page: 1253
  year: 2012
  end-page: 1257
  ident: bb0150
  article-title: CSF tau markers are correlated with hippocampal volume in Alzheimer’s disease
  publication-title: Neurobiol. Aging
– year: 2024
  ident: bb0090
– volume: 13
  start-page: 162
  year: 2021
  ident: bb0055
  article-title: Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review
  publication-title: Alzheimers Res. Ther.
– volume: 15
  start-page: 1728
  year: 2021
  end-page: 1738
  ident: bb0050
  article-title: Predicting Alzheimer’s conversion in mild cognitive impairment patients using longitudinal neuroimaging and clinical markers
  publication-title: Brain Imaging Behav.
– volume: 56
  start-page: 567
  year: 2015
  end-page: 574
  ident: bb0085
  article-title: Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios
  publication-title: J. Nucl. Med.
– volume: 82
  start-page: 951
  year: 2021
  end-page: 964
  ident: bb0040
  article-title: Combination of plasma Neurofilament light chain and mini-mental state examination score predicts progression from mild cognitive impairment to Alzheimer’s disease within 5 years
  publication-title: J. Alzheimers Dis.
– volume: 61
  start-page: 597
  year: 2020
  end-page: 603
  ident: bb0015
  article-title: Alzheimer disease neuroimaging initiative; predictive value of 18F-Florbetapir and 18F-FDG PET for conversion from mild cognitive impairment to Alzheimer dementia
  publication-title: J. Nucl. Med.
– volume: 20
  start-page: 431
  year: 2023
  end-page: 439
  ident: bb0075
  article-title: Early detection of dementia using risk classification in MCI: outcomes of Shanghai mild cognitive impairment cohort study
  publication-title: Curr. Alzheimer Res.
– reference: ..
– volume: 14
  start-page: 23
  year: 2019
  ident: bb0145
  article-title: Alpha-synuclein in the pathophysiology of Alzheimer’s disease
  publication-title: Mol. Neurodegener.
– volume: 21
  start-page: 8661
  year: 2020
  ident: bb0160
  article-title: Clinical utility of the pathogenesis-related proteins in Alzheimer’s disease
  publication-title: Int. J. Mol. Sci.
– volume: 888
  start-page: 287
  year: 2001
  end-page: 296
  ident: bb0135
  article-title: Alpha-synuclein-positive structures in cases with sporadic Alzheimer’s disease: morphology and its relationship to tau aggregation
  publication-title: Brain Res.
– volume: 109
  start-page: 135
  year: 2022
  end-page: 144
  ident: bb0155
  article-title: Tau pathology mediates age effects on medial temporal lobe structure
  publication-title: Neurobiol. Aging
– volume: 127
  start-page: 811
  year: 2014
  end-page: 824
  ident: bb0125
  article-title: TDP-43 is a key player in the clinical features associated with Alzheimer’s disease
  publication-title: Acta Neuropathol.
– volume: 45
  start-page: 198
  year: 2018
  end-page: 209
  ident: bb0110
  article-title: Fully automatic speech-based analysis of the semantic verbal fluency task
  publication-title: Dement. Geriatr. Cogn. Disord.
– year: 2024
  ident: bb0115
– volume: 27
  start-page: 1034
  year: 2021
  end-page: 1042
  ident: bb0070
  article-title: Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures
  publication-title: Nat. Med.
– volume: 62
  start-page: 774
  year: 2012
  end-page: 781
  ident: bb0095
  article-title: FreeSurfer
  publication-title: Neuroimage
– volume: 388
  start-page: 9
  year: 2023
  end-page: 21
  ident: bb0120
  article-title: Lecanemab in early Alzheimer’s disease
  publication-title: N. Engl. J. Med.
– volume: 9
  start-page: 329
  year: 2017
  ident: bb0065
  article-title: Random forest algorithm for the classification of neuroimaging data in Alzheimer’s disease: a systematic review
  publication-title: Front. Aging Neurosci.
– volume: 25
  start-page: 218
  year: 2021
  end-page: 226
  ident: bb0100
  article-title: Early detection of Alzheimer’s disease with blood plasma proteins using support vector machines
  publication-title: IEEE J. Biomed. Health Inform.
– volume: 79
  start-page: 149
  year: 2022
  end-page: 158
  ident: bb0025
  article-title: Biomarker-based prediction of longitudinal tau positron emission tomography in Alzheimer Disease
  publication-title: JAMA Neurol.
– volume: 79
  start-page: 1533
  year: 2021
  end-page: 1546
  ident: bb0035
  article-title: Quantitative longitudinal predictions of Alzheimer’s disease by multi-modal predictive learning
  publication-title: J. Alzheimers Dis.
– volume: 16
  start-page: 84
  year: 2021
  ident: bb0130
  article-title: TDP-43 pathology in Alzheimer’s disease
  publication-title: Mol. Neurodegener.
– volume: 11
  start-page: 220
  year: 2019
  ident: bb0060
  article-title: Deep learning in Alzheimer’s Disease: diagnostic classification and prognostic prediction using neuroimaging data
  publication-title: Front. Aging Neurosci.
– volume: 4
  year: 2022
  ident: bb0105
  article-title: Leveraging speech and artificial intelligence to screen for early Alzheimer’s disease and amyloid beta positivity
  publication-title: Brain Commun.
– volume: 6
  start-page: 224
  year: 2016
  ident: bb0080
  article-title: Shanghai cohort study on mild cognitive impairment: study design and baseline characteristics
  publication-title: J, Alzheimers Dis. Parkinsonism
– volume: 14
  start-page: 201
  year: 2022
  ident: bb0140
  article-title: Alpha-synuclein: a pathological factor with Aβ and tau and biomarker in Alzheimer’s disease
  publication-title: Alzheimers Res. Ther.
– volume: 28
  year: 2020
  ident: bb0045
  article-title: Prediction of clinical and biomarker conformed Alzheimer’s disease and mild cognitive impairment from multi-feature brain structural MRI using age-correction from a large independent lifespan sample
  publication-title: Neuroimage Clin.
– volume: 14
  start-page: 535
  year: 2018
  end-page: 562
  ident: bb0005
  article-title: NIA-AA research framework: toward a biological definition of Alzheimer’s disease
  publication-title: Alzheimers Dement.
– reference: Zhou B, Tanabe K, Kojima S, Teramukai S, Fukushima M, Alzheimer Disease Neuroimaging Initiative Alzheimer disease neuroimaging initiative. protective factors modulate the risk of beta amyloid in Alzheimer's disease. Behav. Neurol. (2020):7029642. doi:
– volume: 14
  start-page: 535
  issue: 4
  year: 2018
  ident: 10.1016/j.jns.2024.123319_bb0005
  article-title: NIA-AA research framework: toward a biological definition of Alzheimer’s disease
  publication-title: Alzheimers Dement.
  doi: 10.1016/j.jalz.2018.02.018
– volume: 45
  start-page: 198
  issue: 3–4
  year: 2018
  ident: 10.1016/j.jns.2024.123319_bb0110
  article-title: Fully automatic speech-based analysis of the semantic verbal fluency task
  publication-title: Dement. Geriatr. Cogn. Disord.
  doi: 10.1159/000487852
– volume: 16
  start-page: 84
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0130
  article-title: TDP-43 pathology in Alzheimer’s disease
  publication-title: Mol. Neurodegener.
  doi: 10.1186/s13024-021-00503-x
– ident: 10.1016/j.jns.2024.123319_bb0010
  doi: 10.1155/2020/7029642
– volume: 33
  start-page: 1253
  issue: 7
  year: 2012
  ident: 10.1016/j.jns.2024.123319_bb0150
  article-title: CSF tau markers are correlated with hippocampal volume in Alzheimer’s disease
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2011.02.022
– volume: 25
  start-page: 218
  issue: 1
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0100
  article-title: Early detection of Alzheimer’s disease with blood plasma proteins using support vector machines
  publication-title: IEEE J. Biomed. Health Inform.
  doi: 10.1109/JBHI.2020.2984355
– volume: 13
  start-page: 162
  issue: 1
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0055
  article-title: Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review
  publication-title: Alzheimers Res. Ther.
  doi: 10.1186/s13195-021-00900-w
– volume: 4
  issue: 5
  year: 2022
  ident: 10.1016/j.jns.2024.123319_bb0105
  article-title: Leveraging speech and artificial intelligence to screen for early Alzheimer’s disease and amyloid beta positivity
  publication-title: Brain Commun.
  doi: 10.1093/braincomms/fcac231
– volume: 14
  start-page: 201
  issue: 1
  year: 2022
  ident: 10.1016/j.jns.2024.123319_bb0140
  article-title: Alpha-synuclein: a pathological factor with Aβ and tau and biomarker in Alzheimer’s disease
  publication-title: Alzheimers Res. Ther.
  doi: 10.1186/s13195-022-01150-0
– volume: 82
  start-page: 951
  issue: 3
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0040
  article-title: Combination of plasma Neurofilament light chain and mini-mental state examination score predicts progression from mild cognitive impairment to Alzheimer’s disease within 5 years
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-210092
– volume: 14
  start-page: 23
  year: 2019
  ident: 10.1016/j.jns.2024.123319_bb0145
  article-title: Alpha-synuclein in the pathophysiology of Alzheimer’s disease
  publication-title: Mol. Neurodegener.
  doi: 10.1186/s13024-019-0320-x
– volume: 62
  start-page: 774
  issue: 2
  year: 2012
  ident: 10.1016/j.jns.2024.123319_bb0095
  article-title: FreeSurfer
  publication-title: Neuroimage
  doi: 10.1016/j.neuroimage.2012.01.021
– volume: 9
  start-page: 329
  year: 2017
  ident: 10.1016/j.jns.2024.123319_bb0065
  article-title: Random forest algorithm for the classification of neuroimaging data in Alzheimer’s disease: a systematic review
  publication-title: Front. Aging Neurosci.
  doi: 10.3389/fnagi.2017.00329
– volume: 20
  start-page: 431
  issue: 6
  year: 2023
  ident: 10.1016/j.jns.2024.123319_bb0075
  article-title: Early detection of dementia using risk classification in MCI: outcomes of Shanghai mild cognitive impairment cohort study
  publication-title: Curr. Alzheimer Res.
  doi: 10.2174/1567205020666230914161034
– volume: 21
  start-page: 8661
  year: 2020
  ident: 10.1016/j.jns.2024.123319_bb0160
  article-title: Clinical utility of the pathogenesis-related proteins in Alzheimer’s disease
  publication-title: Int. J. Mol. Sci.
  doi: 10.3390/ijms21228661
– volume: 127
  start-page: 811
  issue: 6
  year: 2014
  ident: 10.1016/j.jns.2024.123319_bb0125
  article-title: TDP-43 is a key player in the clinical features associated with Alzheimer’s disease
  publication-title: Acta Neuropathol.
  doi: 10.1007/s00401-014-1269-z
– volume: 74
  start-page: 101
  issue: 1
  year: 2020
  ident: 10.1016/j.jns.2024.123319_bb0020
  article-title: Alzheimer’s Disease Neuroimaging Initiative improved risk stratification for progression from mild cognitive impairment to Alzheimer’s Disease with a multi-analytical evaluation of amyloid-β positron emission tomography
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-190818
– volume: 888
  start-page: 287
  issue: 2
  year: 2001
  ident: 10.1016/j.jns.2024.123319_bb0135
  article-title: Alpha-synuclein-positive structures in cases with sporadic Alzheimer’s disease: morphology and its relationship to tau aggregation
  publication-title: Brain Res.
  doi: 10.1016/S0006-8993(00)03082-1
– volume: 6
  start-page: 224
  year: 2016
  ident: 10.1016/j.jns.2024.123319_bb0080
  article-title: Shanghai cohort study on mild cognitive impairment: study design and baseline characteristics
  publication-title: J, Alzheimers Dis. Parkinsonism
  doi: 10.4172/2161-0460.1000224
– volume: 388
  start-page: 9
  issue: 1
  year: 2023
  ident: 10.1016/j.jns.2024.123319_bb0120
  article-title: Lecanemab in early Alzheimer’s disease
  publication-title: N. Engl. J. Med.
  doi: 10.1056/NEJMoa2212948
– volume: 11
  start-page: 220
  year: 2019
  ident: 10.1016/j.jns.2024.123319_bb0060
  article-title: Deep learning in Alzheimer’s Disease: diagnostic classification and prognostic prediction using neuroimaging data
  publication-title: Front. Aging Neurosci.
  doi: 10.3389/fnagi.2019.00220
– volume: 56
  start-page: 567
  issue: 4
  year: 2015
  ident: 10.1016/j.jns.2024.123319_bb0085
  article-title: Measurement of longitudinal β-amyloid change with 18F-florbetapir PET and standardized uptake value ratios
  publication-title: J. Nucl. Med.
  doi: 10.2967/jnumed.114.148981
– volume: 27
  start-page: 1034
  issue: 6
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0070
  article-title: Prediction of future Alzheimer’s disease dementia using plasma phospho-tau combined with other accessible measures
  publication-title: Nat. Med.
  doi: 10.1038/s41591-021-01348-z
– volume: 61
  start-page: 597
  issue: 4
  year: 2020
  ident: 10.1016/j.jns.2024.123319_bb0015
  article-title: Alzheimer disease neuroimaging initiative; predictive value of 18F-Florbetapir and 18F-FDG PET for conversion from mild cognitive impairment to Alzheimer dementia
  publication-title: J. Nucl. Med.
  doi: 10.2967/jnumed.119.230797
– ident: 10.1016/j.jns.2024.123319_bb0115
– volume: 80
  start-page: 1079
  issue: 3
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0030
  article-title: Deep learning and risk score classification of mild cognitive impairment and Alzheimer’s Disease
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-201438
– volume: 15
  start-page: 1728
  issue: 4
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0050
  article-title: Predicting Alzheimer’s conversion in mild cognitive impairment patients using longitudinal neuroimaging and clinical markers
  publication-title: Brain Imaging Behav.
  doi: 10.1007/s11682-020-00366-8
– volume: 109
  start-page: 135
  year: 2022
  ident: 10.1016/j.jns.2024.123319_bb0155
  article-title: Tau pathology mediates age effects on medial temporal lobe structure
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2021.09.017
– volume: 79
  start-page: 149
  issue: 2
  year: 2022
  ident: 10.1016/j.jns.2024.123319_bb0025
  article-title: Biomarker-based prediction of longitudinal tau positron emission tomography in Alzheimer Disease
  publication-title: JAMA Neurol.
  doi: 10.1001/jamaneurol.2021.4654
– volume: 28
  year: 2020
  ident: 10.1016/j.jns.2024.123319_bb0045
  article-title: Prediction of clinical and biomarker conformed Alzheimer’s disease and mild cognitive impairment from multi-feature brain structural MRI using age-correction from a large independent lifespan sample
  publication-title: Neuroimage Clin.
  doi: 10.1016/j.nicl.2020.102387
– ident: 10.1016/j.jns.2024.123319_bb0090
– volume: 79
  start-page: 1533
  issue: 4
  year: 2021
  ident: 10.1016/j.jns.2024.123319_bb0035
  article-title: Quantitative longitudinal predictions of Alzheimer’s disease by multi-modal predictive learning
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-200906
SSID ssj0006889
Score 2.441612
Snippet People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. The research is to validate the risk classification of AD...
AbstractBackgroundsPeople with elevated beta amyloid have different risk and progress speed to Alzheimer's disease. PurposeThe research is to validate the risk...
People with elevated beta amyloid have different risk and progress speed to Alzheimer's disease.BACKGROUNDSPeople with elevated beta amyloid have different...
SourceID proquest
pubmed
crossref
elsevier
SourceType Aggregation Database
Index Database
Publisher
StartPage 123319
SubjectTerms Aged
Aged, 80 and over
Alzheimer Disease - diagnosis
Alzheimer Disease - epidemiology
Alzheimer's disease
Amyloid beta-Peptides - metabolism
China - epidemiology
Cognitive Dysfunction - diagnosis
Cognitive Dysfunction - epidemiology
Cohort Studies
Disease Progression
Female
Humans
Male
Middle Aged
Mild cognitive impariment
Neurology
PET beta amyloid
Positron-Emission Tomography
Risk assessment
Title Differential risk of Alzheimer's disease in MCI subjects with elevated Abeta
URI https://www.clinicalkey.com/#!/content/1-s2.0-S0022510X24004556
https://www.clinicalkey.es/playcontent/1-s2.0-S0022510X24004556
https://dx.doi.org/10.1016/j.jns.2024.123319
https://www.ncbi.nlm.nih.gov/pubmed/39612639
https://www.proquest.com/docview/3134331416
Volume 467
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3dS9xAEB_EgvRFWrX1_GKFQkE4TbKTj308zsppq08K97bsZjf0RHNi7l764N_uzGVjKfUDfEzIkmS-9rc7v5kF-OYdYiRT0kCFtEApM3KprCj7npYfiSMPw5ZtcZGNrvBsnI6XYNjVwjCtMsT-NqYvonW4cxSkeXQ3mXCNL9liHI2ZBYlpym23uXsd2fThw1-aR1YUqusYzk93mc0Fx-u65o7dCR5S_JbcbOf5uekl7LmYg04-wWoAj2LQft9nWPL1Gqych_T4Ovw6DsedkNveCGaNi2klBjd_fvvJrb__3oiQjxGTWpwPT0Uzt7wP0wjejhVcak7Q04mB9TOzAVcnPy6Ho344LqFfYhzN-oWjqVeVLi69tdbRQgUjo9IqyQujTCItqYNAaoHeIvfsyTPMPbtkVai4ygv5BZbrae03QaCJ0KJVlXMKpa2McTL1qXJ81lFuTQ8OOkHpu7Yrhu7oYteapKpZqrqVag-STpS6K_ekAKUpZr82KH9ukG-CizU61k2iI_2fGfQAn0b-Y0lvvXC_07ImD-O0ian9dN5oGUsuKyPk2oOvrfqffloqQogE8rbe99Jt-MhXTI-J0x1Ynt3P_S6BnJndW1jxHnwYnP4cXTwCDjf31w
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1La9tAEB5SB9peSt9108cWCoWCG0k7euzROA12Y_uUgG_LrnZFHFI5RPYlvz4z1spQkrTQq8Sw0rz2250XwFfvECOZkgQqpANKmZFJZUU58HT8SBxZGLbZFvNsfIa_FuliD0ZdLQynVQbf3_r0rbcOTw4DNw-vlkuu8SVdjKMFZ0FimmaPYJ-7U2EP9oeTk_F855CzolBd03Am6IKb2zSvi5qbdif4g1y45H47929PD8HP7TZ0_ByeBfwohu0nvoA9X7-Ex7MQIX8F06Mw8YQs91Jw4rhYVWJ4eXPul7_99bdGhJCMWNZiNpqIZmP5KqYRfCMruNqc0KcTQ-vX5jWcHf88HY0HYWLCoMQ4Wg8KR7uvKl1cemuto7MKRkalVZIXRplEWpII4dQCvUVu25NnmHu2yqpQcZUX8g306lXt34FAE6FFqyrnFEpbGeNk6lPleNxRbk0fvneM0ldtYwzdZYxdaOKqZq7qlqt9SDpW6q7ik3yUJrf9N6L8PiLfBCtrdKybREf6jib0AXeUfyjTvxb80klZk5Fx5MTUfrVptIwlV5YReO3D21b8u5-WikAi4bz3_7foZ3gyPp1N9XQyPzmAp_yGs2Xi9AP01tcb_5Ewz9p-Cjp9C5GO-og
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Differential+risk+of+Alzheimer%27s+disease+in+MCI+subjects+with+elevated+Abeta&rft.jtitle=Journal+of+the+neurological+sciences&rft.au=Zhou%2C+Bin&rft.au=Fukushima%2C+Masanori&rft.date=2024-12-15&rft.issn=0022-510X&rft.volume=467&rft.spage=123319&rft_id=info:doi/10.1016%2Fj.jns.2024.123319&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_jns_2024_123319
thumbnail_m http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fcdn.clinicalkey.com%2Fck-thumbnails%2F0022510X%2Fcov200h.gif