Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Neuropharmacology
  4. Volume 23, Issue 5
  5. Article
Volume 23, Issue 5
  • ISSN: 1570-159X
  • E-ISSN: 1875-6190
file format pdf download PDF
file format text download EPUB
side by side viewer icon HTML

Abstract

Introduction

The heterogenicity in Alzheimer’s Disease (AD) progression hinders individual prognosis. The present work is an observational 2-year longitudinal study in patients with mild cognitive impairment due to AD (n = 52, with positive CSF biomarkers). The aim of this study is to predict which patients are at risk of fast progression. For this, 3 neuropsychological tests based on different domains (clinical dementia, cognition, delayed memory) and the sum of them were used.

Methods

The tests were performed at diagnosis time (T1) and two years after the diagnosis time (T2). Then, the corresponding progression models were developed using each individual test and their sum as a variable response.

Results

As a result, the model based on cognition status to predict fast decline (differences in the Z score (T2-T1) <1.5 were considered fast declining) provided satisfactory performance (AUC 0.74, 83.3% of sensibility and 70.2% of specificity); the models based on clinical dementia and delayed memory to predict fast declining showed low AUC and sensitivity. Nevertheless, the model based on the sum of the 3 tests showed the highest AUC (0.79), low sensitivity (63.6%), and high specificity.

Conclusion

The developed progression models could provide useful information to clinicians and AD patients regarding their fast/normal decline in general or specific domains.

© 2025 Bentham Science Publishers
© 2025 The Author(s). Published by Bentham Science Publishers. This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode
Loading

Article metrics loading...

/content/journals/cn/10.2174/011570159X332930240925095423
2024-10-28
2025-04-05

  • From This Site

    /content/journals/cn/10.2174/011570159X332930240925095423
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
The full text of this item is not currently available.

References

  1. HodsonR. Alzheimer’s disease.Nature20185597715S1S110.1038/d41586‑018‑05717‑630046078
     [Google Scholar]
  2. 2015 Alzheimer’s disease facts and figures.Alzheimers Dement.201511333238410.1016/j.jalz.2015.02.00325984581
     [Google Scholar]
  3. MattsonM.P. Pathways towards and away from Alzheimer’s disease.Nature2004430700063163910.1038/nature0262115295589
     [Google Scholar]
  4. HymanB.T. PhelpsC.H. BeachT.G. BigioE.H. CairnsN.J. CarrilloM.C. DicksonD.W. DuyckaertsC. FroschM.P. MasliahE. MirraS.S. NelsonP.T. SchneiderJ.A. ThalD.R. ThiesB. TrojanowskiJ.Q. VintersH.V. MontineT.J. National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease.Alzheimers Dement.20128111310.1016/j.jalz.2011.10.00722265587
     [Google Scholar]
  5. LongJ.M. HoltzmanD.M. Alzheimer disease: An update on pathobiology and treatment strategies.Cell2019179231233910.1016/j.cell.2019.09.00131564456
     [Google Scholar]
  6. HanonO. VidalJ.S. LehmannS. BomboisS. AllinquantB. TréluyerJ.M. GeléP. DelmaireC. BlancF. ManginJ.F. BuéeL. TouchonJ. HugonJ. VellasB. GalbrunE. BenetosA. BerrutG. PaillaudE. WallonD. CastelnovoG. Volpe-GillotL. PaccalinM. RobertP.H. GodefroyO. DantoineT. CamusV. BelminJ. VandelP. NovellaJ.L. DuronE. RigaudA.S. Schraen-MaschkeS. GabelleA. Plasma amyloid levels within the Alzheimer’s process and correlations with central biomarkers.Alzheimers Dement.201814785886810.1016/j.jalz.2018.01.00429458036
     [Google Scholar]
  7. ParkJ.C. HanS.H. YiD. ByunM.S. LeeJ.H. JangS. KoK. JeonS.Y. LeeY.S. KimY.K. LeeD.Y. Mook-JungI. Plasma tau/amyloid-β1–42 ratio predicts brain tau deposition and neurodegeneration in Alzheimer’s disease.Brain2019142377178610.1093/brain/awy34730668647
     [Google Scholar]
  8. JinM. ShepardsonN. YangT. ChenG. WalshD. SelkoeD.J. Soluble amyloid β-protein dimers isolated from Alzheimer cortex directly induce Tau hyperphosphorylation and neuritic degeneration.Proc. Natl. Acad. Sci. USA2011108145819582410.1073/pnas.101703310821421841
     [Google Scholar]
  9. PriceJ.L. McKeelD.W.Jr BucklesV.D. RoeC.M. XiongC. GrundmanM. HansenL.A. PetersenR.C. ParisiJ.E. DicksonD.W. SmithC.D. DavisD.G. SchmittF.A. MarkesberyW.R. KayeJ. KurlanR. HuletteC. KurlandB.F. HigdonR. KukullW. MorrisJ.C. Neuropathology of nondemented aging: Presumptive evidence for preclinical Alzheimer disease.Neurobiol. Aging20093071026103610.1016/j.neurobiolaging.2009.04.00219376612
     [Google Scholar]
  10. KnopmanD.S. ParisiJ.E. SalviatiA. Floriach-RobertM. BoeveB.F. IvnikR.J. SmithG.E. DicksonD.W. JohnsonK.A. PetersenL.E. McDonaldW.C. BraakH. PetersenR.C. Neuropathology of cognitively normal elderly.J. Neuropathol. Exp. Neurol.200362111087109510.1093/jnen/62.11.108714656067
     [Google Scholar]
  11. JackC.R.Jr BennettD.A. BlennowK. CarrilloM.C. DunnB. HaeberleinS.B. HoltzmanD.M. JagustW. JessenF. KarlawishJ. LiuE. MolinuevoJ.L. MontineT. PhelpsC. RankinK.P. RoweC.C. ScheltensP. SiemersE. SnyderH.M. SperlingR. ElliottC. MasliahE. RyanL. SilverbergN. NIA‐AA Research Framework: Toward a biological definition of Alzheimer’s disease.Alzheimers Dement.201814453556210.1016/j.jalz.2018.02.01829653606
     [Google Scholar]
  12. OlssonB. LautnerR. AndreassonU. ÖhrfeltA. PorteliusE. BjerkeM. HölttäM. RosénC. OlssonC. StrobelG. WuE. DakinK. PetzoldM. BlennowK. ZetterbergH. CSF and blood biomarkers for the diagnosis of Alzheimer’s disease: A systematic review and meta-analysis.Lancet Neurol.201615767368410.1016/S1474‑4422(16)00070‑327068280
     [Google Scholar]
  13. HanssonO. SeibylJ. StomrudE. ZetterbergH. TrojanowskiJ.Q. BittnerT. LifkeV. CorradiniV. EichenlaubU. BatrlaR. BuckK. ZinkK. RabeC. BlennowK. ShawL.M. CSF biomarkers of Alzheimer’s disease concord with amyloid‐β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts.Alzheimers Dement.201814111470148110.1016/j.jalz.2018.01.01029499171
     [Google Scholar]
  14. ScheltensP. BlennowK. BretelerM.M.B. de StrooperB. FrisoniG.B. SallowayS. Van der FlierW.M. Alzheimer’s disease.Lancet20163881004350551710.1016/S0140‑6736(15)01124‑126921134
     [Google Scholar]
  15. KarikariT.K. PascoalT.A. AshtonN.J. JanelidzeS. BenedetA.L. RodriguezJ.L. ChamounM. SavardM. KangM.S. TherriaultJ. SchöllM. MassarwehG. SoucyJ.P. HöglundK. BrinkmalmG. MattssonN. PalmqvistS. GauthierS. StomrudE. ZetterbergH. HanssonO. Rosa-NetoP. BlennowK. Blood phosphorylated tau 181 as a biomarker for Alzheimer’s disease: A diagnostic performance and prediction modelling study using data from four prospective cohorts.Lancet Neurol.202019542243310.1016/S1474‑4422(20)30071‑532333900
     [Google Scholar]
  16. HardyJ. SelkoeD.J. The amyloid hypothesis of Alzheimer’s disease: Progress and problems on the road to therapeutics.Science2002297558035335610.1126/science.107299412130773
     [Google Scholar]
  17. SelkoeD.J. HardyJ. The amyloid hypothesis of Alzheimer’s disease at 25 years.EMBO Mol. Med.20168659560810.15252/emmm.20160621027025652
     [Google Scholar]
  18. JackC.R.Jr BennettD.A. BlennowK. CarrilloM.C. FeldmanH.H. FrisoniG.B. HampelH. JagustW.J. JohnsonK.A. KnopmanD.S. PetersenR.C. ScheltensP. SperlingR.A. DuboisB. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers.Neurology201687553954710.1212/WNL.000000000000292327371494
     [Google Scholar]
  19. SperlingR.A. RentzD.M. JohnsonK.A. KarlawishJ. DonohueM. SalmonD.P. AisenP. The A4 study: Stopping AD before symptoms begin?Sci. Transl. Med.20146228228fs1310.1126/scitranslmed.300794124648338
     [Google Scholar]
  20. SperlingR.A. AisenP.S. BeckettL.A. BennettD.A. CraftS. FaganA.M. IwatsuboT. JackC.R.Jr KayeJ. MontineT.J. ParkD.C. ReimanE.M. RoweC.C. SiemersE. SternY. YaffeK. CarrilloM.C. ThiesB. Morrison-BogoradM. WagsterM.V. PhelpsC.H. Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging‐Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease.Alzheimers Dement.20117328029210.1016/j.jalz.2011.03.00321514248
     [Google Scholar]
  21. AlbertM.S. DeKoskyS.T. DicksonD. DuboisB. FeldmanH.H. FoxN.C. GamstA. HoltzmanD.M. JagustW.J. PetersenR.C. SnyderP.J. CarrilloM.C. ThiesB. PhelpsC.H. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging‐Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease.Alzheimers Dement.20117327027910.1016/j.jalz.2011.03.00821514249
     [Google Scholar]
  22. DavisM. O’ConnellT. JohnsonS. ClineS. MerikleE. MartenyiF. SimpsonK. Estimating Alzheimer’s disease progression rates from normal cognition through mild cognitive impairment and stages of dementia.Curr. Alzheimer Res.201815877778810.2174/156720501566618011909242729357799
     [Google Scholar]
  23. HampelH. FrankR. BroichK. TeipelS.J. KatzR.G. HardyJ. HerholzK. BokdeA.L.W. JessenF. HoesslerY.C. SanhaiW.R. ZetterbergH. WoodcockJ. BlennowK. Biomarkers for Alzheimer’s disease: Academic, industry and regulatory perspectives.Nat. Rev. Drug Discov.20109756057410.1038/nrd311520592748
     [Google Scholar]
  24. MattssonN. CullenN.C. AndreassonU. ZetterbergH. BlennowK. Association between longitudinal plasma neurofilament light and neurodegeneration in patients with Alzheimer disease.JAMA Neurol.201976779179910.1001/jamaneurol.2019.076531009028
     [Google Scholar]
  25. SoldanA. PettigrewC. CaiQ. WangM.C. MoghekarA.R. O’BrienR.J. SelnesO.A. AlbertM.S. Hypothetical preclinical Alzheimer disease groups and longitudinal cognitive change.JAMA Neurol.201673669870510.1001/jamaneurol.2016.019427064267
     [Google Scholar]
  26. RentzD.M. Parra RodriguezM.A. AmariglioR. SternY. SperlingR. FerrisS. Promising developments in neuropsychological approaches for the detection of preclinical Alzheimer’s disease: A selective review.Alzheimers Res. Ther.2013565810.1186/alzrt22224257331
     [Google Scholar]
  27. ParnettiL. ChipiE. SalvadoriN. D’AndreaK. EusebiP. Prevalence and risk of progression of preclinical Alzheimer’s disease stages: A systematic review and meta-analysis.Alzheimers Res. Ther.2019111710.1186/s13195‑018‑0459‑730646955
     [Google Scholar]
  28. AmariglioR.E. BeckerJ.A. CarmasinJ. WadsworthL.P. LoriusN. SullivanC. MayeJ.E. GidicsinC. PepinL.C. SperlingR.A. JohnsonK.A. RentzD.M. Subjective cognitive complaints and amyloid burden in cognitively normal older individuals.Neuropsychologia201250122880288610.1016/j.neuropsychologia.2012.08.01122940426
     [Google Scholar]
  29. LangbaumJ.B. HendrixS.B. AyutyanontN. ChenK. FleisherA.S. ShahR.C. BarnesL.L. BennettD.A. TariotP.N. ReimanE.M. An empirically derived composite cognitive test score with improved power to track and evaluate treatments for preclinical Alzheimer’s disease.Alzheimers Dement.201410666667410.1016/j.jalz.2014.02.00224751827
     [Google Scholar]
  30. MorrisJ.C. EdlandS. ClarkC. GalaskoD. KossE. MohsR. van BelleG. FillenbaumG. HeymanA. The consortium to establish a registry for Alzheimer’s disease (CERAD). Part IV. Rates of cognitive change in the longitudinal assessment of probable Alzheimer’s disease.Neurology199343122457246510.1212/WNL.43.12.24578255439
     [Google Scholar]
  31. HeymanA. PetersonB. FillenbaumG. PieperC. Predictors of time to institutionalization of patients with Alzheimer’s disease.Neurology19974851304130910.1212/WNL.48.5.13049153462
     [Google Scholar]
  32. BrodatyH. ConnorsM.H. XuJ. WoodwardM. AmesD. Predictors of institutionalization in dementia: A three year longitudinal study.J. Alzheimers Dis.201440122122610.3233/JAD‑13185024448780
     [Google Scholar]
  33. CarcaillonL. PérèsK. PéréJ.J. HelmerC. OrgogozoJ.M. DartiguesJ.F. Fast cognitive decline at the time of dementia diagnosis: a major prognostic factor for survival in the community.Dement. Geriatr. Cogn. Disord.200723643944510.1159/00010201717476100
     [Google Scholar]
  34. BaroccoF. SpallazziM. ConcariL. GardiniS. PelosiA. CaffarraP. The progression of Alzheimer’s disease: Are fast decliners really fast? A four-year follow-up.J. Alzheimers Dis.201757377578610.3233/JAD‑16126428304306
     [Google Scholar]
  35. Peña-BautistaC. Álvarez-SánchezL. PascualR. MorenoM.J. BaqueroM. Cháfer-PericásC. Clinical usefulness of cerebrospinal fluid biomarkers in Alzheimer’s disease.Eur. J. Clin. Invest.2023533e1391010.1111/eci.1391036401799
     [Google Scholar]
  36. O’BryantS.E. LacritzL.H. HallJ. WaringS.C. ChanW. KhodrZ.G. MassmanP.J. HobsonV. CullumC.M. Validation of the new interpretive guidelines for the clinical dementia rating scale sum of boxes score in the national Alzheimer’s coordinating center database.Arch. Neurol.201067674674910.1001/archneurol.2010.11520558394
     [Google Scholar]
  37. HuangH.C. TsengY.M. ChenY.C. ChenP.Y. ChiuH.Y. Diagnostic accuracy of the Clinical Dementia Rating Scale for detecting mild cognitive impairment and dementia: A bivariate meta‐analysis.Int. J. Geriatr. Psychiatry202136223925110.1002/gps.543632955146
     [Google Scholar]
  38. LiY. XiongC. AschenbrennerA.J. ChangC.H. WeinerM.W. NoshenyR.L. MungasD. BatemanR.J. HassenstabJ. MoulderK.L. MorrisJ.C. Item response theory analysis of the clinical dementia rating.Alzheimers Dement.202117353454210.1002/alz.1221033215873
     [Google Scholar]
  39. TsoiK.K.F. ChanJ.Y.C. HiraiH.W. WongS.Y.S. KwokT.C.Y. Cognitive tests to detect dementia.JAMA Intern. Med.201517591450145810.1001/jamainternmed.2015.215226052687
     [Google Scholar]
  40. MitchellA.J. A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment.J. Psychiatr. Res.200943441143110.1016/j.jpsychires.2008.04.01418579155
     [Google Scholar]
  41. Muntal EncinasS. Gramunt-FombuenaN. Badenes GuiaD. Casas HernanzL. Aguilar BarberaM. Spanish translation and adaptation of the repeatable battery for the assessment of neuropsychological status (RBANS) Form A in a pilot sample.Neurologia201227953154610.1016/j.nrl.2011.07.00621906852
     [Google Scholar]
  42. FreilichB.M. HyerL.A. Relation of the repeatable battery for assessment of neuropsychological status to measures of daily functioning in dementia.Psychol. Rep.2007101111912910.2466/pr0.101.1.119‑12917958116
     [Google Scholar]
  43. DuffK. HumphreysclarkJ. ObryantS. MoldJ. SchifferR. SutkerP. Utility of the RBANS in detecting cognitive impairment associated with Alzheimer’s disease: Sensitivity, specificity, and positive and negative predictive powers.Arch. Clin. Neuropsychol.200823560361210.1016/j.acn.2008.06.00418639437
     [Google Scholar]
  44. YinL. RenY. WangX. LiY. HouT. LiuK. CongL. ZhangQ. WangY. JiangZ. DuY. The power of the functional activities questionnaire for screening dementia in rural‐dwelling older adults at high‐risk of cognitive impairment.Psychogeriatrics202020442743610.1111/psyg.1252432092787
     [Google Scholar]
  45. PotashmanM. PangM. TahirM. ShahrazS. DichterS. PerneczkyR. NolteS. Psychometric properties of the Alzheimer’s disease cooperative study - activities of daily living for mild cognitive impairment (ADCS-MCI-ADL) scale: A post hoc analysis of the ADCS ADC-008 trial.BMC Geriatr.202323112410.1186/s12877‑022‑03527‑036879199
     [Google Scholar]
  46. ParmeleeP.A. KatzI.R. Geriatric depression scale; To the editor.J. Am. Geriatr. Soc.19903812137910.1111/j.1532‑5415.1990.tb03461.x.
     [Google Scholar]
  47. ReitzC. MayeuxR. Alzheimer disease: Epidemiology, diagnostic criteria, risk factors and biomarkers.Biochem. Pharmacol.201488464065110.1016/j.bcp.2013.12.02424398425
     [Google Scholar]
  48. KunkleB.W. Grenier-BoleyB. SimsR. BisJ.C. DamotteV. NajA.C. BolandA. VronskayaM. van der LeeS.J. Amlie-WolfA. BellenguezC. FrizattiA. ChourakiV. MartinE.R. SleegersK. BadarinarayanN. JakobsdottirJ. Hamilton-NelsonK.L. Moreno-GrauS. OlasoR. RaybouldR. ChenY. KuzmaA.B. HiltunenM. MorganT. AhmadS. VardarajanB.N. EpelbaumJ. HoffmannP. BoadaM. BeechamG.W. GarnierJ.G. HaroldD. FitzpatrickA.L. ValladaresO. MoutetM.L. GerrishA. SmithA.V. QuL. BacqD. DenningN. JianX. ZhaoY. Del ZompoM. FoxN.C. ChoiS.H. MateoI. HughesJ.T. AdamsH.H. MalamonJ. Sanchez-GarciaF. PatelY. BrodyJ.A. DombroskiB.A. NaranjoM.C.D. DaniilidouM. EiriksdottirG. MukherjeeS. WallonD. UphillJ. AspelundT. CantwellL.B. GarziaF. GalimbertiD. HoferE. ButkiewiczM. FinB. ScarpiniE. SarnowskiC. BushW.S. MeslageS. KornhuberJ. WhiteC.C. SongY. BarberR.C. EngelborghsS. SordonS. VoijnovicD. AdamsP.M. VandenbergheR. MayhausM. CupplesL.A. AlbertM.S. De DeynP.P. GuW. HimaliJ.J. BeeklyD. SquassinaA. HartmannA.M. OrellanaA. BlackerD. Rodriguez-RodriguezE. LovestoneS. GarciaM.E. DoodyR.S. Munoz-FernadezC. SussamsR. LinH. FairchildT.J. BenitoY.A. HolmesC. Karamujić-ČomićH. FroschM.P. ThonbergH. MaierW. RoshchupkinG. GhettiB. GiedraitisV. KawaliaA. LiS. HuebingerR.M. KilanderL. MoebusS. HernándezI. KambohM.I. BrundinR. TurtonJ. YangQ. KatzM.J. ConcariL. LordJ. BeiserA.S. KeeneC.D. HelisalmiS. KloszewskaI. KukullW.A. KoivistoA.M. LynchA. TarragaL. LarsonE.B. HaapasaloA. LawlorB. MosleyT.H. LiptonR.B. SolfrizziV. GillM. LongstrethW.T.Jr MontineT.J. FrisardiV. Diez-FairenM. RivadeneiraF. PetersenR.C. DeramecourtV. AlvarezI. SalaniF. CiaramellaA. BoerwinkleE. ReimanE.M. FievetN. RotterJ.I. ReischJ.S. HanonO. CupidiC. Andre UitterlindenA.G. RoyallD.R. DufouilC. MalettaR.G. de RojasI. SanoM. BriceA. CecchettiR. George-HyslopP.S. RitchieK. TsolakiM. TsuangD.W. DuboisB. CraigD. WuC.K. SoininenH. AvramidouD. AlbinR.L. FratiglioniL. GermanouA. ApostolovaL.G. KellerL. KoutroumaniM. ArnoldS.E. PanzaF. GkatzimaO. AsthanaS. HannequinD. WhiteheadP. AtwoodC.S. CaffarraP. HampelH. QuintelaI. CarracedoÁ. LannfeltL. RubinszteinD.C. BarnesL.L. PasquierF. FrölichL. BarralS. McGuinnessB. BeachT.G. JohnstonJ.A. BeckerJ.T. PassmoreP. BigioE.H. SchottJ.M. BirdT.D. WarrenJ.D. BoeveB.F. LuptonM.K. BowenJ.D. ProitsiP. BoxerA. PowellJ.F. BurkeJ.R. KauweJ.S.K. BurnsJ.M. MancusoM. BuxbaumJ.D. BonuccelliU. CairnsN.J. McQuillinA. CaoC. LivingstonG. CarlsonC.S. BassN.J. CarlssonC.M. HardyJ. CarneyR.M. BrasJ. CarrasquilloM.M. GuerreiroR. AllenM. ChuiH.C. FisherE. MasulloC. CroccoE.A. DeCarliC. BisceglioG. DickM. MaL. DuaraR. Graff-RadfordN.R. EvansD.A. HodgesA. FaberK.M. SchererM. FallonK.B. RiemenschneiderM. FardoD.W. HeunR. FarlowM.R. KölschH. FerrisS. LeberM. ForoudT.M. HeuserI. GalaskoD.R. GieglingI. GearingM. HüllM. GeschwindD.H. GilbertJ.R. MorrisJ. GreenR.C. MayoK. GrowdonJ.H. FeulnerT. HamiltonR.L. HarrellL.E. DrichelD. HonigL.S. CushionT.D. HuentelmanM.J. HollingworthP. HuletteC.M. HymanB.T. MarshallR. JarvikG.P. MeggyA. AbnerE. MenziesG.E. JinL.W. LeonenkoG. RealL.M. JunG.R. BaldwinC.T. GrozevaD. KarydasA. RussoG. KayeJ.A. KimR. JessenF. KowallN.W. VellasB. KramerJ.H. VardyE. LaFerlaF.M. JöckelK.H. LahJ.J. DichgansM. LeverenzJ.B. MannD. LeveyA.I. Pickering-BrownS. LiebermanA.P. KloppN. LunettaK.L. WichmannH.E. LyketsosC.G. MorganK. MarsonD.C. BrownK. MartiniukF. MedwayC. MashD.C. NöthenM.M. MasliahE. HooperN.M. McCormickW.C. DanieleA. McCurryS.M. BayerA. McDavidA.N. GallacherJ. McKeeA.C. van den BusscheH. MesulamM. BrayneC. MillerB.L. Riedel-HellerS. MillerC.A. MillerJ.W. Al-ChalabiA. MorrisJ.C. ShawC.E. MyersA.J. WiltfangJ. O’BryantS. OlichneyJ.M. AlvarezV. ParisiJ.E. SingletonA.B. PaulsonH.L. CollingeJ. PerryW.R. MeadS. PeskindE. CribbsD.H. RossorM. PierceA. RyanN.S. PoonW.W. NacmiasB. PotterH. SorbiS. QuinnJ.F. SacchinelliE. RajA. SpallettaG. RaskindM. CaltagironeC. BossùP. OrfeiM.D. ReisbergB. ClarkeR. ReitzC. SmithA.D. RingmanJ.M. WardenD. RobersonE.D. WilcockG. RogaevaE. BruniA.C. RosenH.J. GalloM. RosenbergR.N. Ben-ShlomoY. SagerM.A. MecocciP. SaykinA.J. PastorP. CuccaroM.L. VanceJ.M. SchneiderJ.A. SchneiderL.S. SliferS. SeeleyW.W. SmithA.G. SonnenJ.A. SpinaS. SternR.A. SwerdlowR.H. TangM. TanziR.E. TrojanowskiJ.Q. TroncosoJ.C. Van DeerlinV.M. Van EldikL.J. VintersH.V. VonsattelJ.P. WeintraubS. Welsh-BohmerK.A. WilhelmsenK.C. WilliamsonJ. WingoT.S. WoltjerR.L. WrightC.B. YuC.E. YuL. SabaY. PilottoA. BullidoM.J. PetersO. CraneP.K. BennettD. BoscoP. CotoE. BoccardiV. De JagerP.L. LleoA. WarnerN. LopezO.L. IngelssonM. DeloukasP. CruchagaC. GraffC. GwilliamR. FornageM. GoateA.M. Sanchez-JuanP. KehoeP.G. AminN. Ertekin-TanerN. BerrC. DebetteS. LoveS. LaunerL.J. YounkinS.G. DartiguesJ.F. CorcoranC. IkramM.A. DicksonD.W. NicolasG. CampionD. TschanzJ. SchmidtH. HakonarsonH. ClarimonJ. MungerR. SchmidtR. FarrerL.A. Van BroeckhovenC. C O’DonovanM. DeStefano, A.L.; Jones, L.; Haines, J.L.; Deleuze, J.F.; Owen, M.J.; Gudnason, V.; Mayeux, R.; Escott-Price, V.; Psaty, B.M.; Ramirez, A.; Wang, L.S.; Ruiz, A.; van Duijn, C.M.; Holmans, P.A.; Seshadri, S.; Williams, J.; Amouyel, P.; Schellenberg, G.D.; Lambert, J.C.; Pericak-Vance, M.A. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.Nat. Genet.201951341443010.1038/s41588‑019‑0358‑230820047
     [Google Scholar]
  49. HamelinL. LagardeJ. DorothéeG. PotierM.C. CorlierF. KuhnastB. CailléF. DuboisB. FillonL. ChupinM. BottlaenderM. SarazinM. Distinct dynamic profiles of microglial activation are associated with progression of Alzheimer’s disease.Brain201814161855187010.1093/brain/awy07929608645
     [Google Scholar]
  50. MonsellS.E. MockC. FardoD.W. BertelsenS. CairnsN.J. RoeC.M. EllingsonS.R. MorrisJ.C. GoateA.M. KukullW.A. Genetic comparison of symptomatic and asymptomatic persons with Alzheimer disease neuropathology.Alzheimer Dis. Assoc. Disord.201731323223810.1097/WAD.000000000000017927849641
     [Google Scholar]
  51. MedinaM. KhachaturianZ.S. RossorM. AvilaJ. Cedazo-MinguezA. Toward common mechanisms for risk factors in Alzheimer’s syndrome.Alzheimers Dement. (N. Y.)20173457157810.1016/j.trci.2017.08.00929124116
     [Google Scholar]
  52. VlassenkoA.G. McCueL. JasielecM.S. SuY. GordonB.A. XiongC. HoltzmanD.M. BenzingerT.L.S. MorrisJ.C. FaganA.M. Imaging and cerebrospinal fluid biomarkers in early preclinical alzheimer disease.Ann. Neurol.201680337938710.1002/ana.2471927398953
     [Google Scholar]
  53. HanseeuwB.J. BetenskyR.A. JacobsH.I.L. SchultzA.P. SepulcreJ. BeckerJ.A. CosioD.M.O. FarrellM. QuirozY.T. MorminoE.C. BuckleyR.F. PappK.V. AmariglioR.A. DewachterI. IvanoiuA. HuijbersW. HeddenT. MarshallG.A. ChhatwalJ.P. RentzD.M. SperlingR.A. JohnsonK. Association of amyloid and tau with cognition in preclinical Alzheimer disease.JAMA Neurol.201976891592410.1001/jamaneurol.2019.142431157827
     [Google Scholar]
  54. FaganA.M. RoeC.M. XiongC. MintunM.A. MorrisJ.C. HoltzmanD.M. Cerebrospinal fluid tau/β-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults.Arch. Neurol.200764334334910.1001/archneur.64.3.noc6012317210801
     [Google Scholar]
  55. RoeC.M. AncesB.M. HeadD. BabulalG.M. StoutS.H. GrantE.A. HassenstabJ. XiongC. HoltzmanD.M. BenzingerT.L.S. SchindlerS.E. FaganA.M. MorrisJ.C. Incident cognitive impairment: Longitudinal changes in molecular, structural and cognitive biomarkers.Brain2018141113233324810.1093/brain/awy24430304397
     [Google Scholar]
  56. VaresiA. CarraraA. PiresV.G. FlorisV. PierellaE. SavioliG. PrasadS. EspositoC. RicevutiG. ChirumboloS. PascaleA. Blood-based biomarkers for Alzheimer’s disease diagnosis and progression: An overview.Cells2022118136710.3390/cells1108136735456047
     [Google Scholar]
  57. BaiB. WangX. LiY. ChenP.C. YuK. DeyK.K. YarbroJ.M. HanX. LutzB.M. RaoS. JiaoY. SiffordJ.M. HanJ. WangM. TanH. ShawT.I. ChoJ.H. ZhouS. WangH. NiuM. MancieriA. MesslerK.A. SunX. WuZ. PagalaV. HighA.A. BiW. ZhangH. ChiH. HaroutunianV. ZhangB. BeachT.G. YuG. PengJ. Deep multilayer brain proteomics identifies molecular networks in Alzheimer’s disease progression.Neuron20201056975991.e710.1016/j.neuron.2019.12.01531926610
     [Google Scholar]
  58. TeunissenC.E. VerberkI.M.W. ThijssenE.H. VermuntL. HanssonO. ZetterbergH. van der FlierW.M. MielkeM.M. del CampoM. Blood-based biomarkers for Alzheimer’s disease: Towards clinical implementation.Lancet Neurol.2022211667710.1016/S1474‑4422(21)00361‑634838239
     [Google Scholar]
  59. HaaksmaM.L. Calderón-LarrañagaA. Olde RikkertM.G.M. MelisR.J.F. LeoutsakosJ.M.S. Cognitive and functional progression in Alzheimer disease: A prediction model of latent classes.Int. J. Geriatr. Psychiatry20183381057106410.1002/gps.489329761569
     [Google Scholar]
  60. McKhannG. DrachmanD. FolsteinM. KatzmanR. PriceD. StadlanE.M. Clinical diagnosis of Alzheimer’s disease.Neurology198434793994410.1212/WNL.34.7.9396610841
     [Google Scholar]
  61. EldholmR.S. BarcaM.L. PerssonK. KnapskogA.B. KerstenH. EngedalK. SelbækG. BrækhusA. SkovlundE. SaltvedtI. Progression of Alzheimer’s disease: A longitudinal study in norwegian memory clinics.J. Alzheimers Dis.20186131221123210.3233/JAD‑17043629254085
     [Google Scholar]
  62. WilkoszP.A. SeltmanH.J. DevlinB. WeamerE.A. LopezO.L. DeKoskyS.T. SweetR.A. Trajectories of cognitive decline in Alzheimer’s disease.Int. Psychogeriatr.201022228129010.1017/S104161020999100119781112
     [Google Scholar]
  63. HanL. ColeM. BellavanceF. McCuskerJ. PrimeauF. Tracking cognitive decline in Alzheimer’s disease using the mini-mental state examination: A meta-analysis.Int. Psychogeriatr.200012223124710.1017/S104161020000635910937543
     [Google Scholar]
  64. TombaughT.N. McIntyreN.J. The mini-mental state examination: A comprehensive review.J. Am. Geriatr. Soc.199240992293510.1111/j.1532‑5415.1992.tb01992.x1512391
     [Google Scholar]
  65. CrumR.M. AnthonyJ.C. BassettS.S. FolsteinM.F. Population-based norms for the Mini-Mental State Examination by age and educational level.JAMA1993269182386239110.1001/jama.1993.035001800780388479064
     [Google Scholar]
  66. MannU.M. MohrE. GearingM. ChaseT.N. Heterogeneity in Alzheimer’s disease: Progression rate segregated by distinct neuropsychological and cerebral metabolic profiles.J. Neurol. Neurosurg. Psychiatry1992551095695910.1136/jnnp.55.10.9561431960
     [Google Scholar]
  67. ThalhauserC.J. KomarovaN.L. Alzheimer’s disease: Rapid and slow progression.J. R. Soc. Interface201296611912610.1098/rsif.2011.013421653567
     [Google Scholar]
  68. SämgårdK. ZetterbergH. BlennowK. HanssonO. MinthonL. LondosE. Cerebrospinal fluid total tau as a marker of Alzheimer’s disease intensity.Int. J. Geriatr. Psychiatry201025440341010.1002/gps.235319650161
     [Google Scholar]
  69. Degerman GunnarssonM. LannfeltL. IngelssonM. BasunH. KilanderL. High tau levels in cerebrospinal fluid predict rapid decline and increased dementia mortality in Alzheimer’s disease.Dement. Geriatr. Cogn. Disord.2014373-419620610.1159/00035555624157938
     [Google Scholar]
  70. Degerman GunnarssonM. IngelssonM. BlennowK. BasunH. LannfeltL. KilanderL. High tau levels in cerebrospinal fluid predict nursing home placement and rapid progression in Alzheimer’s disease.Alzheimers Res. Ther.2016812210.1186/s13195‑016‑0191‑027263933
     [Google Scholar]
  71. López-CuevasR. Baquero-ToledoM. Cuevas-JiménezA. Martín-IbáñezN. Pascual-CostaR. Moreno-MonederoM.J. Cañada-MartínezA. Peña-BautistaC. Ferrer-CairolsI. Álvarez-SánchezL. Cháfer-PericásC. Prognostic value of cerebrospinal fluid biomarkers in mild cognitive impairment due to Alzheimer disease.Neurología (English Edition)202338426226910.1016/j.nrleng.2020.07.02437031800
     [Google Scholar]
  72. KesterM.I. van der VliesA.E. BlankensteinM.A. PijnenburgY.A.L. van ElkE.J. ScheltensP. van der FlierW.M. CSF biomarkers predict rate of cognitive decline in Alzheimer disease.Neurology200973171353135810.1212/WNL.0b013e3181bd827119858456
     [Google Scholar]
  73. WallinÅ.K. BlennowK. ZetterbergH. LondosE. MinthonL. HanssonO. CSF biomarkers predict a more malignant outcome in Alzheimer disease.Neurology201074191531153710.1212/WNL.0b013e3181dd4dd820458070
     [Google Scholar]
  74. QianJ. ZhangY. BetenskyR.A. HymanB.T. Serrano-PozoA. Neuropathology-independent association between APOE genotype and cognitive decline rate in the normal aging-early Alzheimer continuum.Neurol. Genet.202391e20005510.1212/NXG.000000000020005536698453
     [Google Scholar]
  75. DevanandD.P. PeltonG.H. ZamoraD. LiuX. TabertM.H. GoodkindM. ScarmeasN. BraunI. SternY. MayeuxR. Predictive utility of apolipoprotein E genotype for Alzheimer disease in outpatients with mild cognitive impairment.Arch. Neurol.200562697598010.1001/archneur.62.6.97515956169
     [Google Scholar]
  76. LiG. ShoferJ.B. PetrieE.C. YuC.E. WilkinsonC.W. FiglewiczD.P. Shutes-DavidA. ZhangJ. MontineT.J. RaskindM.A. QuinnJ.F. GalaskoD.R. PeskindE.R. Cerebrospinal fluid biomarkers for Alzheimer’s and vascular disease vary by age, gender, and APOE genotype in cognitively normal adults.Alzheimers Res. Ther.2017914810.1186/s13195‑017‑0271‑928673336
     [Google Scholar]
  77. BlomE.S. GiedraitisV. ZetterbergH. FukumotoH. BlennowK. HymanB.T. IrizarryM.C. WahlundL.O. LannfeltL. IngelssonM. Rapid progression from mild cognitive impairment to Alzheimer’s disease in subjects with elevated levels of tau in cerebrospinal fluid and the APOE epsilon4/epsilon4 genotype.Dement. Geriatr. Cogn. Disord.20092745846410.1159/00021684119420940
     [Google Scholar]
/content/journals/cn/10.2174/011570159X332930240925095423
Loading
Fast Declining Prediction in Alzheimer’s Disease from Early Clinical Assessment
Curr. Neuropharmacol. 23, 602 (2025); https://doi.org/10.2174/011570159X332930240925095423
/content/journals/cn/10.2174/011570159X332930240925095423
/content/journals/cn/10.2174/011570159X332930240925095423
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Alzheimer’s disease; biomarker; early assessment; follow-up; neuropsychology; prognostic

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test