Skip to content
2000
  1. Home
  2. A-Z Publications
  3. Current Alzheimer Research
  4. Volume 21, Issue 6
  5. Article
Volume 21, Issue 6
  • ISSN: 1567-2050
  • E-ISSN: 1875-5828

Abstract

Introduction

Distinguishing between frontotemporal dementia (FTD) and Alzheimer’s disease (AD) in their early stages remains a significant clinical challenge. Cerebrospinal fluid (CSF) biomarkers (total Tau, phosphorylated Tau, and beta-amyloid) are promising candidates for identifying early differences between these conditions. This study investigates the relationship between grey matter density and CSF markers in the behavioural variant of frontotemporal dementia (bvFTD) and Alzheimer’s disease (AD).

Methods

CSF and 3D T1-weighted magnetic resonance (MR) images were acquired from 14 bvFTD patients, 15 AD patients, and 13 cognitively normal (CN) matched subjects. The CSF markers and their relative ratios (total Tau/beta-amyloid, phosphorylated Tau/beta-amyloid) were compared across the three groups. Voxel-based morphometry (VBM) was performed to characterize the anatomical changes in bvFTD and AD patients compared to CN subjects. Grey matter density maps were obtained by automatic segmentation of 3.0 Tesla 3D T1-Weighted MR Images, and their correlation with CSF markers and relative ratios was investigated.

Results

Results demonstrated that, as compared to CN subjects, AD patients are characterised by higher CSF total Tau levels and lower beta-amyloid levels; however, beta-amyloid and relative ratios discriminated AD from bvFTD. In addition, AD and bvFTD patients showed different patterns of atrophy, with AD exhibiting more central (temporal areas) and bvFTD more anterior (frontal areas) atrophy. A correlation was found between grey matter density maps and CSF marker concentrations in the AD group, with total Tau and phosphorylated Tau levels showing a high association with low grey matter density in the left superior temporal gyrus.

Conclusion

Overall, while bvFTD lacks a CSF marker profile, CSF beta-amyloid levels are useful for differentiating AD from bvFTD. Furthermore, MR structural imaging can contribute significantly to distinguishing between the two pathologies.

© 2024 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/car/10.2174/0115672050330903240919074725
2024-10-22
2025-04-10

  • From This Site

    /content/journals/car/10.2174/0115672050330903240919074725
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Garre-OlmoJ. Genís BatlleD. del Mar FernándezM. Marquez DanielF. de Eugenio HuélamoR. CasadevallT. Turbau RecioJ. Turon EstradaA. López-PousaS. Registry of Dementia of Girona Study Group (ReDeGi Study Group) Incidence and subtypes of early-onset dementia in a geographically defined general population.Neurology201075141249125510.1212/WNL.0b013e3181f5d4c420810999
     [Google Scholar]
  2. Garre-OlmoJ. Epidemiology of Alzheimer’s disease and other dementias.Rev. Neurol.2018661137738629790571
     [Google Scholar]
  3. RatnavalliE. BrayneC. DawsonK. HodgesJ.R. The prevalence of frontotemporal dementia.Neurology200258111615162110.1212/WNL.58.11.161512058088
     [Google Scholar]
  4. LogroscinoG. PiccininniM. GraffC. HardimanO. LudolphA.C. MorenoF. OttoM. RemesA.M. RoweJ.B. SeelaarH. SoljeE. StefanovaE. TraykovL. JelicV. RydellM.T. PenderN. Anderl-StraubS. BarandiaranM. GabilondoA. KrügerJ. MurleyA.G. RittmanT. van der EndeE.L. van SwietenJ.C. HartikainenP. StojmenovićG.M. MehrabianS. BenussiL. AlbericiA. Dell’AbateM.T. ZeccaC. BorroniB. BelezhanskaD. BianchettiA. BinettiG. CotelliM. CotelliM.S. DreharovaI. FilardiM. FostinelliS. GhidoniR. GnoniV. NachevaG. NovakovićI. PadovaniA. PopivanovI. RaychevaM. StocktonK. StoyanovaK. SuhonenN-M. TaintaM. TonchevaD. UrsoD. ZlatarevaD. ZulaicaM. FRONTIERS group Incidence of syndromes associated with frontotemporal lobar degeneration in 9 european countries.JAMA Neurol.202380327928610.1001/jamaneurol.2022.512836716024
     [Google Scholar]
  5. JosephsKA Frontotemporal lobar degeneration.Neurol. Clin.200725368369610.1016/j.ncl.2007.03.005
     [Google Scholar]
  6. RascovskyK. HodgesJ.R. KnopmanD. MendezM.F. KramerJ.H. NeuhausJ. van SwietenJ.C. SeelaarH. DopperE.G.P. OnyikeC.U. HillisA.E. JosephsK.A. BoeveB.F. KerteszA. SeeleyW.W. RankinK.P. JohnsonJ.K. Gorno-TempiniM.L. RosenH. Prioleau-LathamC.E. LeeA. KippsC.M. LilloP. PiguetO. RohrerJ.D. RossorM.N. WarrenJ.D. FoxN.C. GalaskoD. SalmonD.P. BlackS.E. MesulamM. WeintraubS. DickersonB.C. Diehl-SchmidJ. PasquierF. DeramecourtV. LebertF. PijnenburgY. ChowT.W. ManesF. GrafmanJ. CappaS.F. FreedmanM. GrossmanM. MillerB.L. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia.Brain201113492456247710.1093/brain/awr17921810890
     [Google Scholar]
  7. McKhannG.M. KnopmanD.S. ChertkowH. HymanB.T. JackC.R.Jr KawasC.H. KlunkW.E. KoroshetzW.J. ManlyJ.J. MayeuxR. MohsR.C. MorrisJ.C. RossorM.N. ScheltensP. CarrilloM.C. ThiesB. WeintraubS. PhelpsC.H. The diagnosis of dementia 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.20117326326910.1016/j.jalz.2011.03.00521514250
     [Google Scholar]
  8. ScheltensP. De StrooperB. KivipeltoM. HolstegeH. ChételatG. TeunissenC.E. CummingsJ. van der FlierW.M. Alzheimer’s disease.Lancet2021397102841577159010.1016/S0140‑6736(20)32205‑433667416
     [Google Scholar]
  9. MeyerS. MuellerK. StukeK. BiseniusS. Diehl-SchmidJ. JessenF. KassubekJ. KornhuberJ. LudolphA.C. PrudloJ. SchneiderA. SchuembergK. YakushevI. OttoM. SchroeterM.L. FTLDc Study Group Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI data.Neuroimage Clin.20171465666210.1016/j.nicl.2017.02.00128348957
     [Google Scholar]
  10. IannopolloE. GarciaK. Alzheimer’ Disease Neuroimaging Initiative Enhanced detection of cortical atrophy in Alzheimer’s disease using structural MRI with anatomically constrained longitudinal registration.Hum. Brain Mapp.202142113576359210.1002/hbm.2545533988265
     [Google Scholar]
  11. SeeleyW.W. CrawfordR.K. ZhouJ. MillerB.L. GreiciusM.D. Neurodegenerative diseases target large-scale human brain networks.Neuron2009621425210.1016/j.neuron.2009.03.02419376066
     [Google Scholar]
  12. LooiJ.C.L. LindbergO. ZandbeltB.B. ÖstbergP. AndersenC. BotesL. SvenssonL. WahlundL.O. Caudate nucleus volumes in frontotemporal lobar degeneration: Differential atrophy in subtypes.AJNR Am. J. Neuroradiol.20082981537154310.3174/ajnr.A116818782907
     [Google Scholar]
  13. LooiJ.C.L. SvenssonL. LindbergO. ZandbeltB.B. ÖstbergP. ÖrndahlE. WahlundL.O. Putaminal volume in frontotemporal lobar degeneration and Alzheimer disease: Differential volumes in dementia subtypes and controls.AJNR Am. J. Neuroradiol.20093081552156010.3174/ajnr.A164019497964
     [Google Scholar]
  14. GordonE. RohrerJ.D. KimL.G. OmarR. RossorM.N. FoxN.C. WarrenJ.D. Measuring disease progression in frontotemporal lobar degeneration.Neurology201074866667310.1212/WNL.0b013e3181d1a87920177120
     [Google Scholar]
  15. LuP.H. MendezM.F. LeeG.J. LeowA.D. LeeH.W. ShapiraJ. JimenezE. BoeveB.B. CaselliR.J. Graff-RadfordN.R. JackC.R. KramerJ.H. MillerB.L. BartzokisG. ThompsonP.M. KnopmanD.S. Patterns of brain atrophy in clinical variants of frontotemporal lobar degeneration.Dement. Geriatr. Cogn. Disord.2013351-2345010.1159/00034552323306166
     [Google Scholar]
  16. ReasE.T. ShadrinA. FreiO. MotazediE. McEvoyL. BahramiS. van der MeerD. MakowskiC. LoughnanR. WangX. BroceI. BanksS.J. FominykhV. ChengW. HollandD. SmelandO.B. SeibertT. SelbækG. BrewerJ.B. FanC.C. AndreassenO.A. DaleA.M. Alzheimer’s Disease Neuroimaging Initiative Improved multimodal prediction of progression from MCI to Alzheimer’s disease combining genetics with quantitative brain MRI and cognitive measures.Alzheimers Dement.202319115151515810.1002/alz.1311237132098
     [Google Scholar]
  17. RabinoviciG.D. MillerB.L. Frontotemporal lobar degeneration: Epidemiology, pathophysiology, diagnosis and management.CNS Drugs201024537539810.2165/11533100‑000000000‑0000020369906
     [Google Scholar]
  18. FormanM.S. FarmerJ. JohnsonJ.K. ClarkC.M. ArnoldS.E. CoslettH.B. ChatterjeeA. HurtigH.I. KarlawishJ.H. RosenH.J. Van DeerlinV. LeeV.M.Y. MillerB.L. TrojanowskiJ.Q. GrossmanM. Frontotemporal dementia: Clinicopathological correlations.Ann. Neurol.200659695296210.1002/ana.2087316718704
     [Google Scholar]
  19. Coyle-GilchristI.T.S. DickK.M. PattersonK. Vázquez RodríquezP. WehmannE. WilcoxA. LansdallC.J. DawsonK.E. WigginsJ. MeadS. BrayneC. RoweJ.B. Prevalence, characteristics, and survival of frontotemporal lobar degeneration syndromes.Neurology201686181736174310.1212/WNL.000000000000263827037234
     [Google Scholar]
  20. Gorno-TempiniM.L. HillisA.E. WeintraubS. KerteszA. MendezM. CappaS.F. OgarJ.M. RohrerJ.D. BlackS. BoeveB.F. ManesF. DronkersN.F. VandenbergheR. RascovskyK. PattersonK. MillerB.L. KnopmanD.S. HodgesJ.R. MesulamM.M. GrossmanM. Classification of primary progressive aphasia and its variants.Neurology201176111006101410.1212/WNL.0b013e31821103e621325651
     [Google Scholar]
  21. 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]
  22. PatersonR.W. SlatteryC.F. PooleT. NicholasJ.M. MagdalinouN.K. ToombsJ. ChapmanM.D. LunnM.P. HeslegraveA.J. FoianiM.S. WestonP.S.J. KeshavanA. RohrerJ.D. RossorM.N. WarrenJ.D. MummeryC.J. BlennowK. FoxN.C. ZetterbergH. SchottJ.M. Cerebrospinal fluid in the differential diagnosis of Alzheimer’s disease: Clinical utility of an extended panel of biomarkers in a specialist cognitive clinic.Alzheimers Res. Ther.20181013210.1186/s13195‑018‑0361‑329558979
     [Google Scholar]
  23. OecklP SteinackerP FenebergE OttoM Cerebrospinal fluid proteomics and protein biomarkers in frontotemporal lobar degeneration: Current status and future perspectives.Biochim. Biophys. Acta BBA - Proteins Proteomics201518547757768
     [Google Scholar]
  24. OecklP. SteinackerP. FenebergE. OttoM. Neurochemical biomarkers in the diagnosis of frontotemporal lobar degeneration: An update.J. Neurochem.2016138S1Suppl. 118419210.1111/jnc.1366927186717
     [Google Scholar]
  25. VergalloA. CarlesiC. PagniC. GiorgiF.S. BaldacciF. PetrozziL. CeravoloR. TognoniG. SicilianoG. BonuccelliU. A single center study: Aβ42/p-Tau181 CSF ratio to discriminate AD from FTD in clinical setting.Neurol. Sci.201738101791179710.1007/s10072‑017‑3053‑z28726050
     [Google Scholar]
  26. SchuffN. WoernerN. BoretaL. KornfieldT. ShawL.M. TrojanowskiJ.Q. ThompsonP.M. JackC.R.Jr WeinerM.W. Alzheimer’s Disease Neuroimaging Initiative MRI of hippocampal volume loss in early Alzheimer’s disease in relation to ApoE genotype and biomarkers.Brain2009132Pt 41067107719251758
     [Google Scholar]
  27. ChouY.Y. LeporéN. AvedissianC. MadsenS.K. ParikshakN. HuaX. ShawL.M. TrojanowskiJ.Q. WeinerM.W. TogaA.W. ThompsonP.M. Alzheimer’s Disease Neuroimaging Initiative Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls.Neuroimage200946239441010.1016/j.neuroimage.2009.02.01519236926
     [Google Scholar]
  28. FaganA.M. HeadD. ShahA.R. MarcusD. MintunM. MorrisJ.C. HoltzmanD.M. Decreased cerebrospinal fluid Aβ 42 correlates with brain atrophy in cognitively normal elderly.Ann. Neurol.200965217618310.1002/ana.2155919260027
     [Google Scholar]
  29. ContadorJ. Pérez-MillánA. Tort-MerinoA. BalasaM. FalgàsN. OlivesJ. CastellvíM. Borrego-ÉcijaS. BoschB. Fernández-VillullasG. Ramos-CampoyO. AntonellA. BargallóN. Sanchez-ValleR. Sala-LlonchR. LladóA. Alzheimer’s Disease Neuroimaging Initiative Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer’s disease.Neuroimage Clin.20213210280410.1016/j.nicl.2021.10280434474317
     [Google Scholar]
  30. MiralbellJ. SpulberG. HooshmandB. BesgaA. MataróM. Cedazo-MinguezA. KivipeltoM. WahlundL.O. Grey matter and cognitive patterns in cognitive impaired subjects using CSF biomarker cut-offs.J. Alzheimers Dis.201229474174910.3233/JAD‑2012‑11155322330819
     [Google Scholar]
  31. GrossmanM. FarmerJ. LeightS. WorkM. MooreP. Van DeerlinV. PraticoD. ClarkC.M. CoslettH.B. ChatterjeeA. GeeJ. TrojanowskiJ.Q. LeeV.M.Y. Cerebrospinal fluid profile in frontotemporal dementia and Alzheimer’s disease.Ann. Neurol.200557572172910.1002/ana.2047715852395
     [Google Scholar]
  32. TeunissenC.E. EliasN. Koel-SimmelinkM.J.A. Durieux-LuS. MalekzadehA. PhamT.V. PiersmaS.R. BeccariT. MeeterL.H.H. DopperE.G.P. van SwietenJ.C. JimenezC.R. PijnenburgY.A.L. Novel diagnostic cerebrospinal fluid biomarkers for pathologic subtypes of frontotemporal dementia identified by proteomics.Alzheimers Dement.201621869410.1016/j.dadm.2015.12.00427239539
     [Google Scholar]
  33. MagniE. BinettiG. BianchettiA. RozziniR. TrabucchiM. Mini-mental state examination: A normative study in Italian elderly population.Eur. J. Neurol.19963319820210.1111/j.1468‑1331.1996.tb00423.x21284770
     [Google Scholar]
  34. AppollonioI. LeoneM. IsellaV. PiamartaF. ConsoliT. VillaM.L. ForapaniE. RussoA. NichelliP. The frontal assessment battery (FAB): Normative values in an Italian population sample.Neurol. Sci.200526210811610.1007/s10072‑005‑0443‑415995827
     [Google Scholar]
  35. CaltagironeC. GainottiG. CarlesimoG.A. ParnettiL. FaddaL. GallassiR. Battery for the assessment of Mental Deterioration (part I): Description of a neuropsychological diagnostic instrument.Arch. Psychol. Neurol. Psychiatry1995564461470
     [Google Scholar]
  36. Italian standardization and classification of Neuropsychological tests. The Italian Group on the Neuropsychological Study of Aging.Ital. J. Neurol. Sci.1987Suppl. 81120
     [Google Scholar]
  37. MondiniS. MapelliD. Brief Neuropsychological ExamRaffaello Cortina Publisher2003
     [Google Scholar]
  38. CaffarraP. VezzadiniG. DieciF. ZonatoF. VenneriA. Una versione abbreviata del test di Stroop: dati normativi nella popolazione italiana.Riv. Neurol.2002121115
     [Google Scholar]
  39. Esame Neuropsicologico per l’Afasia: E.N.P.A. - Rita Capasso, Gabriele Miceli - Google Libri.Available from: https://books.google.it/books/about/Esame_Neuropsicologico_per_l_Afasia.html?hl=it&id=4tzVIzJi6uwC&redir_esc=y
  40. D’AgostinoL. Calibration of naming tests for aphasia on normal subjects.Ist. Clin. Neurol. Univ.1985
     [Google Scholar]
  41. CaffarraP. VezzadiniG. DieciF. ZonatoF. VenneriA. Rey-Osterrieth complex figure: Normative values in an Italian population sample.Neurol. Sci.200222644344710.1007/s10072020000311976975
     [Google Scholar]
  42. WarringtonE.K. Visual object and space perception battery.Zenodo1991
     [Google Scholar]
  43. GaleotoG. SansoniJ. ScuccimarriM. BruniV. De SantisR. ColucciM. ValenteD. TofaniM. A psychometric properties evaluation of the italian version of the geriatric depression scale.Depress. Res. Treat.201820181710.1155/2018/179753629686898
     [Google Scholar]
  44. StarksteinS.E. MaybergH.S. PreziosiT.J. AndrezejewskiP. LeiguardaR. RobinsonR.G. Reliability, validity, and clinical correlates of apathy in Parkinson’s disease.J. Neuropsychiatry Clin. Neurosci.19924213413910.1176/jnp.4.2.1341627973
     [Google Scholar]
  45. CummingsJ.L. MegaM. GrayK. Rosenberg-ThompsonS. CarusiD.A. GornbeinJ. The neuropsychiatric inventory: Comprehensive assessment of psychopathology in dementia.Neurology199444122308231410.1212/WNL.44.12.23087991117
     [Google Scholar]
  46. KatzS. FordA.B. MoskowitzR.W. JacksonB.A. JaffeM.W. Studies of illness in the aged.JAMA19631851291491910.1001/jama.1963.0306012002401614044222
     [Google Scholar]
  47. LawtonM.P. BrodyE.M. Assessment of older people: Self-maintaining and instrumental activities of daily living.Gerontologist196993 Part 117918610.1093/geront/9.3_Part_1.1795349366
     [Google Scholar]
  48. AshburnerJ. FristonK.J. Diffeomorphic registration using geodesic shooting and Gauss–Newton optimisation.Neuroimage201155395496710.1016/j.neuroimage.2010.12.04921216294
     [Google Scholar]
  49. GaserC. DahnkeR. ThompsonP.M. KurthF. LudersE. the Alzheimer’s Disease Neuroimaging Initiative CAT: A computational anatomy toolbox for the analysis of structural MRI data.Gigascience202413giae04910.1093/gigascience/giae04939102518
     [Google Scholar]
  50. Tzourio-MazoyerN. LandeauB. PapathanassiouD. CrivelloF. EtardO. DelcroixN. MazoyerB. JoliotM. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.Neuroimage200215127328910.1006/nimg.2001.097811771995
     [Google Scholar]
  51. MagalhãesT.N.C. CassebR.F. GerbelliC.L.B. Pimentel-SivaL.R. NogueiraM.H. TeixeiraC.V.L. CarlettiA.F.M.K. de RezendeT.J.R. JoaquimH.P.G. TalibL.L. ForlenzaO.V. CendesF. BalthazarM.L.F. Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer’s disease.Brain Behav.2023132e286310.1002/brb3.286336601694
     [Google Scholar]
  52. AamodtW.W. WaligorskaT. ShenJ. TropeaT.F. SiderowfA. WeintraubD. GrossmanM. IrwinD. WolkD.A. XieS.X. TrojanowskiJ.Q. ShawL.M. Chen-PlotkinA.S. Neurofilament light chain as a biomarker for cognitive decline in parkinson disease.Mov. Disord.202136122945295010.1002/mds.2877934480363
     [Google Scholar]
  53. ZacàD. HassonU. MinatiL. JovicichJ. Method for retrospective estimation of natural head movement during structural MRI.J. Magn. Reson. Imaging201848492793710.1002/jmri.2595929393987
     [Google Scholar]
  54. SeppäläT.T. NergO. KoivistoA.M. RummukainenJ. PuliL. ZetterbergH. PyykköO.T. HelisalmiS. AlafuzoffI. HiltunenM. JääskeläinenJ.E. RinneJ. SoininenH. LeinonenV. HerukkaS.K. CSF biomarkers for Alzheimer disease correlate with cortical brain biopsy findings.Neurology201278201568157510.1212/WNL.0b013e3182563bd022517093
     [Google Scholar]
  55. ShawL.M. VandersticheleH. Knapik-CzajkaM. ClarkC.M. AisenP.S. PetersenR.C. BlennowK. SoaresH. SimonA. LewczukP. DeanR. SiemersE. PotterW. LeeV.M.Y. TrojanowskiJ.Q. Alzheimer’s Disease Neuroimaging Initiative Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects.Ann. Neurol.200965440341310.1002/ana.2161019296504
     [Google Scholar]
  56. ReijnT.S.M. RikkertM.O. van GeelW.J.A. de JongD. VerbeekM.M. Diagnostic accuracy of ELISA and xMAP technology for analysis of amyloid β(42) and tau proteins.Clin. Chem.200753585986510.1373/clinchem.2006.08167917395712
     [Google Scholar]
  57. BianH. Van SwietenJ.C. LeightS. MassimoL. WoodE. FormanM. MooreP. de KoningI. ClarkC.M. RossoS. TrojanowskiJ. LeeV.M.Y. GrossmanM. CSF biomarkers in frontotemporal lobar degeneration with known pathology.Neurology20087019_part_21827183510.1212/01.wnl.0000311445.21321.fc18458217
     [Google Scholar]
  58. BlennowK. Cerebrospinal fluid protein biomarkers for Alzheimer’s disease.NeuroRx20041221322510.1602/neurorx.1.2.21315717022
     [Google Scholar]
  59. FaganA.M. MintunM.A. MachR.H. LeeS.Y. DenceC.S. ShahA.R. LaRossaG.N. SpinnerM.L. KlunkW.E. MathisC.A. DeKoskyS.T. MorrisJ.C. HoltzmanD.M. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Aβ 42 in humans.Ann. Neurol.200659351251910.1002/ana.2073016372280
     [Google Scholar]
  60. BuergerK. EwersM. PirttiläT. ZinkowskiR. AlafuzoffI. TeipelS.J. DeBernardisJ. KerkmanD. McCullochC. SoininenH. HampelH. CSF phosphorylated tau protein correlates with neocortical neurofibrillary pathology in Alzheimer’s disease.Brain2006129113035304110.1093/brain/awl26917012293
     [Google Scholar]
  61. RiemenschneiderM. WagenpfeilS. DiehlJ. LautenschlagerN. ThemlT. HeldmannB. DrzezgaA. JahnT. FörstlH. KurzA. Tau and Aβ42 protein in CSF of patients with frontotemporal degeneration.Neurology200258111622162810.1212/WNL.58.11.162212058089
     [Google Scholar]
  62. DuA-T. SchuffN. KramerJ.H. RosenH.J. Gorno-TempiniM.L. RankinK. MillerB.L. WeinerM.W. Different regional patterns of cortical thinning in Alzheimer’s disease and frontotemporal dementia.Brain2007130Pt 41159116617353226
     [Google Scholar]
  63. Muñoz-RuizM.Á. HartikainenP. KoikkalainenJ. WolzR. JulkunenV. NiskanenE. HerukkaS.K. KivipeltoM. VanninenR. RueckertD. LiuY. LötjönenJ. SoininenH. Structural MRI in frontotemporal dementia: Comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.PLoS One2012712e5253110.1371/journal.pone.005253123285078
     [Google Scholar]
  64. SusiantiN.A. ProdjohardjonoA. VidyantiA.N. SetyaningsihI. GofirA. SetyaningrumC.T.S. EffendyC. SetyawanN.H. SetyopranotoI. The impact of medial temporal and parietal atrophy on cognitive function in dementia.Sci. Rep.2024141528110.1038/s41598‑024‑56023‑338438548
     [Google Scholar]
  65. MatsudaH. Voxel-based morphometry of brain MRI in normal aging and alzheimer’s disease.Aging Dis.201341293723423504
     [Google Scholar]
  66. ConnorJ.R. TuckerP. JohnsonM. SnyderB. Ceruloplasmin levels in the human superior temporal gyrus in aging and Alzheimer’s disease.Neurosci. Lett.19931591-2889010.1016/0304‑3940(93)90805‑U8264985
     [Google Scholar]
  67. WatsonC.T. RoussosP. GargP. HoD.J. AzamN. KatselP.L. HaroutunianV. SharpA.J. Genome-wide DNA methylation profiling in the superior temporal gyrus reveals epigenetic signatures associated with Alzheimer’s disease.Genome Med.201681510.1186/s13073‑015‑0258‑826803900
     [Google Scholar]
  68. SmithA.R. SmithR.G. CondliffeD. HannonE. SchalkwykL. MillJ. LunnonK. Increased DNA methylation near TREM2 is consistently seen in the superior temporal gyrus in Alzheimer’s disease brain.Neurobiol. Aging201647354010.1016/j.neurobiolaging.2016.07.00827522519
     [Google Scholar]
  69. WoodO.W.G. WalbyJ. YeungJ.H. KeS. PalpagamaT.H. TurnerC. WaldvogelH.J. FaullR.L.M. KwakowskyA. Alzheimer’s disease-associated region-specific decrease of vesicular glutamate transporter immunoreactivity in the medial temporal lobe and superior temporal gyrus.Neuroscience2024546758710.1016/j.neuroscience.2024.03.02738552733
     [Google Scholar]
  70. BloudekL.M. SpackmanD.E. BlankenburgM. SullivanS.D. Review and meta-analysis of biomarkers and diagnostic imaging in Alzheimer’s disease.J. Alzheimers Dis.201126462764510.3233/JAD‑2011‑11045821694448
     [Google Scholar]
  71. WoodwardM. JacovaC. BlackS.E. KerteszA. MackenzieI.R. FeldmanH. ACCORD investigator group Differentiating the frontal variant of Alzheimer’s disease.Int. J. Geriatr. Psychiatry201025773273810.1002/gps.241519823987
     [Google Scholar]
  72. NtymenouS. TsantzaliI. KalamatianosT. VoumvourakisK.I. KapakiE. TsivgoulisG. StranjalisG. ParaskevasG.P. Blood biomarkers in frontotemporal dementia: Review and meta-analysis.Brain Sci.202111224410.3390/brainsci1102024433672008
     [Google Scholar]
  73. SwiftI.J. Sogorb-EsteveA. HellerC. SynofzikM. OttoM. GraffC. GalimbertiD. ToddE. HeslegraveA.J. van der EndeE.L. Van SwietenJ.C. ZetterbergH. RohrerJ.D. Fluid biomarkers in frontotemporal dementia: Past, present and future.J. Neurol. Neurosurg. Psychiatry202192220421510.1136/jnnp‑2020‑32352033188134
     [Google Scholar]
  74. ManippaV. PalmisanoA. FilardiM. VilellaD. NitscheM.A. RivoltaD. LogroscinoG. An update on the use of gamma (multi)sensory stimulation for Alzheimer’s disease treatment.Front. Aging Neurosci.202214109508110.3389/fnagi.2022.109508136589536
     [Google Scholar]
  75. ManippaV. PalmisanoA. NitscheM.A. FilardiM. VilellaD. LogroscinoG. RivoltaD. Cognitive and neuropathophysiological outcomes of gamma-tACS in dementia: A systematic review.Neuropsychol. Rev.202434133836110.1007/s11065‑023‑09589‑036877327
     [Google Scholar]
  76. SrivastavaP. TripathiP.N. SharmaP. RaiS.N. SinghS.P. SrivastavaR.K. ShankarS. ShrivastavaS.K. Design and development of some phenyl benzoxazole derivatives as a potent acetylcholinesterase inhibitor with antioxidant property to enhance learning and memory.Eur. J. Med. Chem.201916311613510.1016/j.ejmech.2018.11.04930503937
     [Google Scholar]
  77. RaiS.N. SinghC. SinghA. SinghM.P. SinghB.K. Mitochondrial dysfunction: A potential therapeutic target to treat alzheimer’s disease.Mol. Neurobiol.20205773075308810.1007/s12035‑020‑01945‑y32462551
     [Google Scholar]
  78. SinghM. AgarwalV. PanchamP. JindalD. AgarwalS. RaiS. SinghS. GuptaV. A comprehensive review and androgen deprivation therapy and its impact on alzheimer’s disease risk in older men with prostate cancer.Degener. Neurol. Neuromuscul. Dis.202414334610.2147/DNND.S44513038774717
     [Google Scholar]
  79. LizioR. LacidognaG. GesualdoL. FerriR. SoricelliA. BabiloniC. Two weeks of a computerized cognitive training may produce beneficial effects in Alzheimer’s disease patients.2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)Bari, Italy, 2019, pp. 1276–1279.10.1109/SMC.2019.8914416
     [Google Scholar]
/content/journals/car/10.2174/0115672050330903240919074725
Loading
Correlations between Cerebrospinal Fluid Biomarkers and Gray Matter Atrophy in Alzheimer's and Behavioural Variant Frontotemporal Dementia
Curr Alzheimer Res 21, 371 (2024); https://doi.org/10.2174/0115672050330903240919074725
/content/journals/car/10.2174/0115672050330903240919074725
/content/journals/car/10.2174/0115672050330903240919074725
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): Alzheimer’s disease; cerebrospinal fluid biomarkers; Frontotemporal dementia; grey matter density; MR structural imaging; voxel-based morphometry

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