2025
Prognostic value of plasma biomarkers for informing clinical trial design in mild-to-moderate Alzheimer’s disease
Qiu Y, Jacobs D, Messer K, Salmon D, Wellington C, Stukas S, Revta C, Brewer J, Léger G, Askew B, Donahue L, Kaplita S, Coric V, Qureshi I, Feldman H. Prognostic value of plasma biomarkers for informing clinical trial design in mild-to-moderate Alzheimer’s disease. Alzheimer's Research & Therapy 2025, 17: 97. PMID: 40317057, PMCID: PMC12046789, DOI: 10.1186/s13195-025-01745-3.Peer-Reviewed Original ResearchConceptsMild to moderate ADADAS-cog11CDR-SBBaseline plasma NfLAlzheimer's diseasePlasma biomarkersMild-to-moderate Alzheimer's diseasePrognostic valueClinical trialsBaseline NfLPlasma NfLPlacebo-controlled trialCortical volumeConcentrations of plasma biomarkersMethodsPost hoc analysisDesign of clinical trialsClinical outcome dataIncreased ventricular volumeTrial participantsVolumetric MRIBaseline concentrationsEarly disease stagesClinical trial designTrial entry criteriaAD trialsSubcellular proteomics and iPSC modeling uncover reversible mechanisms of axonal pathology in Alzheimer’s disease
Cai Y, Kanyo J, Wilson R, Bathla S, Cardozo P, Tong L, Qin S, Fuentes L, Pinheiro-de-Sousa I, Huynh T, Sun L, Mansuri M, Tian Z, Gan H, Braker A, Trinh H, Huttner A, Lam T, Petsalaki E, Brennand K, Nairn A, Grutzendler J. Subcellular proteomics and iPSC modeling uncover reversible mechanisms of axonal pathology in Alzheimer’s disease. Nature Aging 2025, 5: 504-527. PMID: 40065072, PMCID: PMC11922768, DOI: 10.1038/s43587-025-00823-3.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseProximity labeling approachIPSC-derived neuronsSubcellular proteomicsCytoskeleton dynamicsPhosphorylated mTOR levelsDystrophic neuritesLipid transportBiological processesProtein turnoverAD modelHuman induced pluripotent stem cellsAmyloid depositsIPSC modelsProteomicsInduced pluripotent stem cellsPluripotent stem cellsMTOR inhibitionTherapeutic targetAxonal pathologyLabeling approachMTOR levelsMouse brainSpheroid formationAlzheimerPolygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification
D'Aoust T, Clocchiatti‐Tuozzo S, Rivier C, Mishra A, Hachiya T, Grenier‐Boley B, Soumaré A, Duperron M, Le Grand Q, Bouteloup V, Proust‐Lima C, Samieri C, Neuffer J, Sargurupremraj M, Chêne G, Helmer C, Thibault M, Amouyel P, Lambert J, Kamatani Y, Jacqmin‐Gadda H, Tregouët D, Inouye M, Dufouil C, Falcone G, Debette S. Polygenic score integrating neurodegenerative and vascular risk informs dementia risk stratification. Alzheimer's & Dementia 2025, 21: e70014. PMID: 40042447, PMCID: PMC11881617, DOI: 10.1002/alz.70014.Peer-Reviewed Original ResearchConceptsOlder community-dwelling peopleCommunity-dwelling peopleDementia risk stratificationVascular contribution to dementiaAssociated with dementia riskGenetic riskDementia clinical trialsApo E4Polygenic risk scoresGenetic risk groupsHigh-risk individualsDementia riskImprove risk predictionEast Asian ancestryAD-PRSPopulation-basedPolygenic scoresRisk stratificationMemory-clinic patientsPrevention programsClinical risk factorsDementiaClinical participantsRisk scoreAlzheimer's diseaseInhibition of amyloid beta oligomer accumulation by NU-9: A unifying mechanism for the treatment of neurodegenerative diseases
Johnson E, Nowar R, Viola K, Huang W, Zhou S, Bicca M, Zhu W, Kranz D, Klein W, Silverman R. Inhibition of amyloid beta oligomer accumulation by NU-9: A unifying mechanism for the treatment of neurodegenerative diseases. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2402117122. PMID: 40030015, PMCID: PMC11912461, DOI: 10.1073/pnas.2402117122.Peer-Reviewed Original ResearchConceptsProtein aggregationNeurodegenerative diseasesMechanisms of protein aggregationAmyloid-beta oligomersAlzheimer's disease neurodegenerationEndolysosomal traffickingBeta oligomersOligomer accumulationTreatment of neurodegenerative diseasesTDP-43Disease neurodegenerationPeptide aggregationLysosome-dependentCathepsin LProteinHippocampal neuronsPathological accumulationQuantitative assayTraffickingCellular mechanismsCathepsin BBlock neurodegenerationImmunofluorescence imagingPathogenic mechanismsNeurodegenerationS-Nitrosylation of CRTC1 in Alzheimer’s disease impairs CREB-dependent gene expression induced by neuronal activity
Zhang X, Vlkolinsky R, Wu C, Dolatabadi N, Scott H, Prikhodko O, Zhang A, Blanco M, Lang N, Piña-Crespo J, Nakamura T, Roberto M, Lipton S. S-Nitrosylation of CRTC1 in Alzheimer’s disease impairs CREB-dependent gene expression induced by neuronal activity. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2418179122. PMID: 40014571, PMCID: PMC11892585, DOI: 10.1073/pnas.2418179122.Peer-Reviewed Original ResearchConceptsActivity-dependent gene expressionGene expressionAlzheimer's diseaseCREB-dependent gene expressionS-nitrosylationNitric oxide (NO)-related speciesTargets of S-nitrosylationNeuronal activity-dependent gene expressionPathogenesis of ADDecreased neurite lengthIncreased neuronal cell deathNeuronal cell deathSynaptic plasticityTranscriptional pathwaysCell deathCRISPR/Cas9 techniqueTranscription coactivator 1AD modelLong-term memory formationIncreased S-nitrosylationLong-term potentiationTherapeutic targetExpressionNeurite lengthCerebrocortical neuronsDeep learning to quantify the pace of brain aging in relation to neurocognitive changes
Yin C, Imms P, Chowdhury N, Chaudhari N, Ping H, Wang H, Bogdan P, Irimia A, Weiner M, Aisen P, Petersen R, Jack C, Jagust W, Landau S, Rivera-Mindt M, Okonkwo O, Shaw L, Lee E, Toga A, Beckett L, Harvey D, Green R, Saykin A, Nho K, Perrin R, Tosun D, Sachdev P, Green R, Drake E, Montine T, Conti C, Weiner M, Nosheny R, Truran Sacrey D, Fockler J, Miller M, Conti C, Kwang W, Jin C, Diaz A, Ashford M, Flenniken D, Kormos A, Petersen R, Aisen P, Rafii M, Raman R, Jimenez G, Donohue M, Salazar J, Fidell A, Boatwright V, Robison J, Zimmerman C, Cabrera Y, Walter S, Clanton T, Shaffer E, Webb C, Hergesheimer L, Smith S, Ogwang S, Adegoke O, Mahboubi P, Pizzola J, Jenkins C, Beckett L, Harvey D, Donohue M, Saito N, Diaz A, Hussen K, Okonkwo O, Rivera-Mindt M, Amaza H, Thao M, Parkins S, Ayo O, Glittenberg M, Hoang I, Germano K, Strong J, Weisensel T, Magana F, Thomas L, Guzman V, Ajayi A, Di Benedetto J, Talavera S, Jack C, Felmlee J, Fox N, Thompson P, DeCarli C, Forghanian-Arani A, Borowski B, Reyes C, Hedberg C, Ward C, Schwarz C, Reyes D, Gunter J, Moore-Weiss J, Kantarci K, Matoush L, Senjem M, Vemuri P, Reid R, Malone I, Thomopoulos S, Nir T, Jahanshad N, Knaack A, Fletcher E, Harvey D, Tosun-Turgut D, Rossi Chen S, Choe M, Crawford K, Yushkevich P, Das S, Jagust W, Landau S, Koeppe R, Rabinovici G, Villemagne V, LoPresti B, Perrin R, Morris J, Franklin E, Bernhardt H, Cairns N, Taylor-Reinwald L, Shaw L, Lee E, Lee V, Korecka M, Brylska M, Wan Y, Trojanowki J, Toga A, Crawford K, Neu S, Saykin A, Nho K, Foroud T, Jo T, Risacher S, Craft H, Apostolova L, Nudelman K, Faber K, Potter Z, Lacy K, Kaddurah-Daouk R, Shen L, Karlawish J, Erickson C, Grill J, Largent E, Harkins K, Weiner M, Thal L, Kachaturian Z, Frank R, Snyder P, Buckholtz N, Hsiao J, Ryan L, Molchan S, Khachaturian Z, Carrillo M, Potter W, Barnes L, Bernard M, González H, Ho C, Hsiao J, Jackson J, Masliah E, Masterman D, Okonkwo O, Perrin R, Ryan L, Silverberg N, Silbert L, Kaye J, White S, Pierce A, Thomas A, Clay T, Schwartz D, Devereux G, Taylor J, Ryan J, Nguyen M, DeCapo M, Shang Y, Schneider L, Munoz C, Ferman D, Conant C, Martin K, Oleary K, Pawluczyk S, Trejo E, Dagerman K, Teodoro L, Becerra M, Fairooz M, Garrison S, Boudreau J, Avila Y, Brewer J, Jacobson A, Gama A, Kim C, Little E, Frascino J, Ferng N, Trujillo S, Heidebrink J, Koeppe R, MacDonald S, Malyarenko D, Ziolkowski J, O’Connor J, Robert N, Lowe S, Rogers V, Petersen R, Hackenmiller B, Boeve B, Albers C, Kreuger C, Jones D, Knopman D, Botha H, Magnuson J, Graff-Radford J, Crawley K, Schumacher M, McKinzie S, Smith S, Helland T, Lowe V, Ramanan V, Pavlik V, Faircloth J, Bishop J, Nath J, Chaudhary M, Kataki M, Yu M, Pacini N, Barker R, Brooks R, Aggarwal R, Honig L, Stern Y, Mintz A, Cordona J, Hernandez M, Long J, Arnold A, Groves A, Middleton A, Vogler B, McCurry C, Mayo C, Raji C, Amtashar F, Klemp H, Elmore H, Ruszkiewicz J, Kusuran J, Stewart J, Horenkamp J, Greeson J, Wever K, Vo K, Larkin K, Rao L, Schoolcraft L, Gallagher L, Paczynski M, McMillan M, Holt M, Gagliano N, Henson R, LaBarge R, Swarm R, Munie S, Cepeda S, Winterton S, Hegedus S, Wilson T, Harte T, Bonacorsi Z, Geldmacher D, Watkins A, Barger B, Smelser B, Bates C, Stover C, McKinley E, Ikner G, Hendrix H, Cooper H, Mahaffey J, Booth Robbins L, Brown Ashley L, Natelson-Love M, Carter P, Solomon V, Grossman H, Groome A, Ardolino A, Kaplan A, Sheppard F, Burgos-Rivera G, Garcia-Camilo G, Lim J, Neugroschl J, Jackson K, Evans K, Soleimani L, Sano M, Ghesani N, Binder S, Apuango X, Sood A, Troutman A, Blanchard K, Richards A, Nelson G, Hendrickson K, Yurko E, Plenge J, Rufo V, Shah R, Duara R, Lynch B, Chirinos C, Dittrich C, Campbell D, Mejia D, Perez G, Colvee H, Gonzalez J, Gondrez J, Knaack J, Acevedo M, Cereijo M, Greig-Custo M, Villar M, Wishnia M, Detling S, Barker W, Albert M, Moghekar A, Rodzon B, Demsky C, Pontone G, Pekar J, Farrington L, Pomper M, Johnson N, Alo T, Sadowski M, Ulysse A, Masurkar A, Marti B, Mossa D, Geesey E, Petrocca E, Schulze E, Wong J, Boonsiri J, Kenowsky S, Martinez T, Briglall V, Doraiswamy P, Nwosu A, Adhikari A, Hellegers C, Petrella J, James O, Wong T, Hawk T, Vaishnavi S, McCoubrey H, Nasrallah I, Rovere R, Maneval J, Robinson E, Rivera F, Uffelman J, Combs M, O’Donnell P, Manning S, King R, Nieto A, Glueck A, Mandal A, Swain A, Gamble B, Meacham B, Forenback D, Ross D, Cheatham E, Hartman E, Cornell G, Harp J, Ashe L, Goins L, Watts L, Yazell M, Mandal P, Buckler R, Vincent S, Rudd T, Lopez O, Malia A, Chiado C, Zik C, Ruszkiewicz J, Savage K, Fenice L, Oakley M, Tacey P, Berman S, Bowser S, Hegedus S, Saganis X, Porsteinsson A, Mathewson A, Widman A, Holvey B, Clark E, Morales E, Young I, Ruszkiewicz J, Hopkins K, Martin K, Kowalski N, Hunt R, Calzavara R, Kurvach R, D’Ambrosio S, Thai G, Vides B, Lieb B, McAdams-Ortiz C, Toso C, Mares I, Moorlach K, Liu L, Corona M, Nguyen M, Tallakson M, McDonnell M, Rangel M, Basheer N, Place P, Romero R, Tam S, Nguyen T, Thomas A, Frolov A, Khera A, Browning A, Kelley B, Dawson C, Mathews D, Most E, Phillips E, Nguyen L, Nunez M, Miller M, Jones M, Martinez N, Logan R, McColl R, Pham S, Fox T, Moore T, Levey A, Brown A, Kippels A, Ellison A, Lyons C, Hales C, Parry C, Williams C, McCorkle E, Harris G, Rose H, Jooma I, Al-Amin J, Lah J, Webster J, Swiniarski J, Chapman L, Donnelly L, Mariotti L, Locke M, Vaughn P, Penn R, Carpentier S, Yeboah S, Basadre S, Malakauskas S, Lyron S, Villinger T, Burney T, Burns J, Abusalim A, Dahlgren A, Montero A, Arthur A, Dooly H, Kreszyn K, Berner K, Gillen L, Scanlan M, Madison M, Mathis N, Switzer P, Townley R, Fikru S, Sullivan S, Wright E, Beigi M, Daley A, Ko A, Luong B, Nyborg G, Morales J, Durbin K, Garcia L, Parand L, Macias L, Monserratt L, Farchi M, Wu P, Hernandez R, Rodriguez T, Graff-Radford N, Marolt A, Thomas A, Aloszka D, Moncayo E, Westerhold E, Day G, Chrestensen K, Imhansiemhonehi M, McKinzie S, Stephens S, Grant S, Brosch J, Perkins A, Saunders A, Kovac D, Polson H, Mwaura I, Mejia K, Britt K, King K, Nichols K, Lawrence K, Rankin L, Farlow M, Wiesenauer P, Bryant R, Herring S, Lynch S, Wilson S, Day T, Korst W, van Dyck C, Mecca A, Miller A, Brennan A, Khan A, Ruan A, Gunnoud C, Mendonca C, Raynes-Goldfinger D, Salardini E, Hidalgo E, Cooper E, Singh E, Murphy E, May J, Stanhope J, Lam J, Waszak J, Nelsen K, Sacaza K, Hasbani M, Donahue M, Chen M, Barcelos N, Eigenberger P, Bonomi R, O’Dell R, Jefferson S, Khasnavis S, Smilowitz S, DeStefano S, Good S, Camarro T, Clayton V, Cavrel Y, Lu Y, Chertkow H, Bergman H, Hosein C, Black S, Kapadia A, Bhan A, Lam B, Scott C, Gabriel G, Bray J, Zotovic L, Gutierrez M, Masellis M, Farshadi M, Gui M, Mitchell M, Taylor R, Endre R, Taghi-Zada Z, Hsiung R, English C, Kim E, Yau E, Tong H, Barlow L, Jennings L, Assaly M, Nunes P, Marian T, Kertesz A, Rogers J, Trost D, Wint D, Bernick C, Munic D, Grant I, Korkoyah A, Raja A, Lapins A, Ryan C, Pejic J, Basham K, Lukose L, Haddad L, Quinlan L, Houghtaling N, Sadowsky C, Martinez W, Villena T, Reynolds B, Forero A, Ward C, Brennan E, Figueroa E, Esposito G, Mallory J, Johnson K, Turner K, Seidenberg K, McCann K, Bassett M, Chadwick M, Turner R, Bean R, Sharma S, Marshall G, Haviari A, Pietras A, Wallace B, Munro C, Rivera-Delpin G, Hustead H, Levesque I, Ramirez J, Nolan K, Glennon K, Palou M, Erkkinen M, DaSilva N, Friedman P, Silver R, Salazar R, Polleys R, McGinnis S, Gale S, Hall T, Luu T, Chao S, Lin E, Coleman J, Epperson K, Vasanawala M, Atri A, Rangel A, Evans B, Monarrez C, Cline C, Liebsack C, Bandy D, Goldfarb D, Intorcia D, Olgin J, Clark K, King K, York K, Reade M, Callan M, Glass M, Johnson M, Gutierrez M, Goddard M, Trncic N, Choudhury P, Reyes P, Lowery S, Hall S, Olgin S, de Santiago S, Alosco M, Ton A, Jimenez A, Ellison A, Tran A, Anderson B, Carter D, Veronelli D, Lenio S, Steinberg E, Mez J, Weller J, Johns J, Mez J, Harkins J, Puleio A, Hoti I, Mwicigi J, Puleio A, Alosco M, Schultz O, Lauture M, Steinberg E, Denis R, Killiany R, Singh S, Lenio S, Qiu W, Devis Y, Obisesan T, Stone A, Ordor D, Udodong I, Okonkwo I, Khan J, Turner J, Hughes K, Kadiri O, Duffy C, Moss A, Stapleton K, Toth M, Sanders M, Ayres M, Hamski M, Fatica P, Ogrocki P, Ash S, Pot S, Chen D, Soto A, Tanase C, Bissig D, Vanya H, Russell H, Patel H, Zhang H, Wallace K, Ayers K, Gallegos M, Forloines M, Sinn M, Kahulugan Q, Isip R, Calderon S, Hamm T, Borrie M, Lee T, Bartha R, Johnson S, Asthana S, Carlsson C, Perrin A, Tariot P, Fleisher A, Reeder S, Capote H, Emborsky A, Mattle A, Ajtai B, Wagner B, Myers B, Slazyk D, Fragale D, Fransen E, Macnamara H, Falletta J, Hirtreiter J, Mechtler L, King M, Asbach M, Rainka M, Zawislak R, Wisniewski S, O’Malley S, Jimenez-Knight T, Peehler T, Aladeen T, Bates V, Wenner V, Elmalik W, Scharre D, Ramamurthy A, Bouchachi S, Kataki M, Tarawneh R, Kelley B, Celmins D, Leader A, Figueroa C, Bauerle H, Patterson K, Reposa M, Presto S, Ahmed T, Stewart W, Pearlson G, Blank K, Anderson K, Santulli R, Schwartz E, Williamson J, Jessup A, Williams A, Duncan C, O’Connell A, Gagnon K, Zamora E, Bateman J, Crawford F, Thompson D, Walker E, Rowell J, White M, Ledford P, Bohlman S, Henkle S, Bottoms J, Moretz L, Hoover B, Shannon M, Rogers S, Baker W, Harrison W, Wu C, DeMarco A, Stipanovich A, Arcuri D, Clark J, Davis J, Doyon K, Amoyaw M, Acosta M, Bailey R, Warren S, Fogerty T, Sanborn V, Riddle M, Salloway S, Malloy P, Correia S, Windon C, Blackburn M, Rosen H, Miller B, Smith A, Mba I, Echevarria J, Janavs J, Roglaski E, Yong M, Devine R, Okhravi H, Rivera E, Kalowsky T, Smith C, Rosario C, Masdeu J, Le R, Gurung M, Sabbagh M, Garcia A, Ellis Slaughter M, Elayan N, Acothley S, Pomara N, Hernando R, Pomara V, Reichert C, Brawman-Mintzer O, Acree A, Williams A, Long C, Long R, Newhouse P, Hill S, Boegel A, Seshadri S, Saklad A, Jones F, Hu W, Sotelo V, Gonazalez Rojas Y, Mintzer J, Flynn Longmire C, Spicer K. Deep learning to quantify the pace of brain aging in relation to neurocognitive changes. Proceedings Of The National Academy Of Sciences Of The United States Of America 2025, 122: e2413442122. PMID: 39993207, PMCID: PMC11912385, DOI: 10.1073/pnas.2413442122.Peer-Reviewed Original ResearchConceptsCN adultsBrain agingNeuroanatomical agingLongitudinal modelAdverse cognitive changesChronological ageAlzheimer's diseaseNeurocognitive agingCognitive changesNeurocognitive changesCognitive functionNeurocognitive statusAssociated with changesAge trendsLongitudinal MRIAdultsBrainQuantify DNA methylationAD risk assessmentBlood-brain barrierUnbiased CSF Proteomics in Patients With Idiopathic Normal Pressure Hydrocephalus to Identify Molecular Signatures and Candidate Biomarkers
de Geus M, Wu C, Dodge H, Leslie S, Wang W, Lam T, Kahle K, Chan D, Kivisäkk P, Nairn A, Arnold S, Carlyle B. Unbiased CSF Proteomics in Patients With Idiopathic Normal Pressure Hydrocephalus to Identify Molecular Signatures and Candidate Biomarkers. Neurology 2025, 104: e213375. PMID: 39951680, PMCID: PMC11837848, DOI: 10.1212/wnl.0000000000213375.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlzheimer DiseaseBiomarkersFemaleHumansHydrocephalus, Normal PressureMachine LearningMaleMiddle AgedProteomicsConceptsNeuronal pentraxin receptorIdiopathic normal pressure hydrocephalusTranscriptome dataAlzheimer's diseaseDifferential expression of proteinsGene ontology analysisDifferential expression analysisGene set enrichment analysisDownregulation of proteinsDifferentially expressed proteinsNormal pressure hydrocephalusBiological process enrichmentExpression of proteinsPotential disease biomarkersOntology analysisProteomic analysis of CSFPathophysiology of idiopathic normal pressure hydrocephalusProteomic analysisProteomic studiesProcess of immune responseEnrichment analysisExpression analysisPressure hydrocephalusDifferential expressionDiagnosis of idiopathic normal pressure hydrocephalus[18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water.
Fu J, Juttukonda M, Garimella A, Salvatore A, Lois C, Ranasinghe A, Efthimiou N, Sari H, Aye W, Guehl N, El Fakhri G, Johnson K, Dickerson B, Izquierdo-Garcia D, Catana C, Price J. [18F]MK-6240 Radioligand Delivery Indices as Surrogates of Cerebral Perfusion: Bias and Correlation Against [15O]Water. Journal Of Nuclear Medicine 2025, 66: 410-417. PMID: 39947916, PMCID: PMC11876731, DOI: 10.2967/jnumed.124.268701.Peer-Reviewed Original ResearchAlpha rhythm and Alzheimer’s disease: Has Hans Berger’s dream come true?
Babiloni C, Arakaki X, Baez S, Barry R, Benussi A, Blinowska K, Bonanni L, Borroni B, Bayard J, Bruno G, Cacciotti A, Carducci F, Carino J, Carpi M, Conte A, Cruzat J, D'Antonio F, Della Penna S, Del Percio C, De Sanctis P, Escudero J, Fabbrini G, Farina F, Fraga F, Fuhr P, Gschwandtner U, Güntekin B, Guo Y, Hajos M, Hallett M, Hampel H, Hanoğlu L, Haraldsen I, Hassan M, Hatlestad-Hall C, Horváth A, Ibanez A, Infarinato F, Jaramillo-Jimenez A, Jeong J, Jiang Y, Kamiński M, Koch G, Kumar S, Leodori G, Li G, Lizio R, Lopez S, Ferri R, Maestú F, Marra C, Marzetti L, McGeown W, Miraglia F, Moguilner S, Moretti D, Mushtaq F, Noce G, Nucci L, Ochoa J, Onorati P, Padovani A, Pappalettera C, Parra M, Pardini M, Pascual-Marqui R, Paulus W, Pizzella V, Prado P, Rauchs G, Ritter P, Salvatore M, Santamaria-García H, Schirner M, Soricelli A, Taylor J, Tankisi H, Tecchio F, Teipel S, Kodamullil A, Triggiani A, Valdes-Sosa M, Valdes-Sosa P, Vecchio F, Vossel K, Yao D, Yener G, Ziemann U, Kamondi A. Alpha rhythm and Alzheimer’s disease: Has Hans Berger’s dream come true? Clinical Neurophysiology 2025, 172: 33-50. PMID: 39978053, DOI: 10.1016/j.clinph.2025.02.256.Peer-Reviewed Original ResearchConceptsPathological agingAlzheimer's diseaseExpert panelAlpha rhythmAD patient’s qualityQuality of lifeAging-Alzheimer's AssociationCognitive impairmentCognitive declineClinical workupNeuroscience SocietyCortical circuitsAD patientsUS National InstitutesOlder adultsRoutine useSenile dementiaDecades of researchPatients' qualityClinical guidelinesOscillatory synchronizationCause of dementiaClinical applicationNIA-AADementiaHuman and mouse proteomics reveals the shared pathways in Alzheimer’s disease and delayed protein turnover in the amyloidome
Yarbro J, Han X, Dasgupta A, Yang K, Liu D, Shrestha H, Zaman M, Wang Z, Yu K, Lee D, Vanderwall D, Niu M, Sun H, Xie B, Chen P, Jiao Y, Zhang X, Wu Z, Chepyala S, Fu Y, Li Y, Yuan Z, Wang X, Poudel S, Vagnerova B, He Q, Tang A, Ronaldson P, Chang R, Yu G, Liu Y, Peng J. Human and mouse proteomics reveals the shared pathways in Alzheimer’s disease and delayed protein turnover in the amyloidome. Nature Communications 2025, 16: 1533. PMID: 39934151, PMCID: PMC11814087, DOI: 10.1038/s41467-025-56853-3.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseProtein turnoverMouse model of amyloidosisMulti-omics analysisMurine model of Alzheimer's diseaseModel of Alzheimer's diseaseModel of amyloidosisProteome turnoverMouse proteomeGenetic incorporationAD pathwayAmyloid formationBrain proteomeMulti-omicsProteomic strategyAD progressionProteomicsProtein alterationsProteinDisease mechanismsAmyloidPathwayPotential targetMouse brainTurnoverPreliminary Evidence for Perturbation‐Based tACS‐EEG Biomarkers of Gamma Activity in Alzheimer's Disease
Palmisano A, Pezanko L, Cappon D, Tatti E, Macone J, Koch G, Smeralda C, Romanella S, Ruffini G, Rivolta D, Press D, Pascual‐Leone A, El‐Fakhri G, Santarnecchi E. Preliminary Evidence for Perturbation‐Based tACS‐EEG Biomarkers of Gamma Activity in Alzheimer's Disease. International Journal Of Geriatric Psychiatry 2025, 40: e70025. PMID: 39799469, DOI: 10.1002/gps.70025.Peer-Reviewed Original ResearchConceptsPeripheral neuroinflammationIdentification of novel biomarkersResponse to TACPatient's clinical phenotypeSpectral powerGABAergic dysfunctionNo significant correlationPrognostic valueInhibitory circuitryClinical severityClinical phenotypeAnimal modelsCognitive statusNeuroinflammatory markersAlzheimer's diseaseHuman patientsNeuroinflammatory biomarkersNovel biomarkersPatientsDisease severityTherapeutic targetGamma activityBiomarkersMild to moderate dementiaSignificant correlationThe etiology and prevention of early‐stage tau pathology in higher cortical circuits: Insights from aging rhesus macaques
Datta D, Arnsten A. The etiology and prevention of early‐stage tau pathology in higher cortical circuits: Insights from aging rhesus macaques. Alzheimer's & Dementia 2025, 21: e14477. PMID: 39776253, PMCID: PMC11848412, DOI: 10.1002/alz.14477.Peer-Reviewed Original ResearchMeSH KeywordsAgingAlzheimer DiseaseAmyloid beta-PeptidesAnimalsCerebral CortexDisease Models, AnimalHumansMacaca mulattaPhosphorylationtau ProteinsConceptsAged macaquesAged rhesus macaquesP-tauTau hyperphosphorylationCortical circuitsAmyloid-beta generationSoluble phosphorylated tauCognitive deficitsAged monkeysSoluble hyperphosphorylated tauSporadic Alzheimer's diseaseAssociation cortexEarly-stage pathologyRhesus macaquesIncreased ABCalcium dysregulationCalcium regulationToxic to neuronsHyperphosphorylated tauAmyloid-betaCortexInflammatory signalingP-tau217 levelsTau pathologyPhosphorylated tauevoke and evoke+: design of two large-scale, double-blind, placebo-controlled, phase 3 studies evaluating efficacy, safety, and tolerability of semaglutide in early-stage symptomatic Alzheimer’s disease
Cummings J, Atri A, Feldman H, Hansson O, Sano M, Knop F, Johannsen P, León T, Scheltens P. evoke and evoke+: design of two large-scale, double-blind, placebo-controlled, phase 3 studies evaluating efficacy, safety, and tolerability of semaglutide in early-stage symptomatic Alzheimer’s disease. Alzheimer's Research & Therapy 2025, 17: 14. PMID: 39780249, PMCID: PMC11708093, DOI: 10.1186/s13195-024-01666-7.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlzheimer DiseaseDouble-Blind MethodFemaleGlucagon-Like PeptidesHumansMaleMiddle AgedTreatment OutcomeConceptsSymptomatic ADAlzheimer's diseaseDouble-blindGlucagon-like peptide-1 receptor agonist semaglutidePlacebo-controlled phase 3 trialOnce-daily oral semaglutideClinical Dementia RatingMild cognitive impairmentAD-related processesAD biomarkersSafety of semaglutideDose-escalation regimenPhase 3 studyBaseline to weekEffect of semaglutidePhase 3 trialCognitive impairmentPathophysiology of Alzheimer's diseasePotential disease-modifying effectsDementia RatingSymptomatic Alzheimer's diseaseTreatment of type 2 diabetesPlacebo-controlledType 2 diabetesDisease-modifying potentialIn Vivo Head-to-Head Comparison of [18F]GTP1 with [18F]MK-6240 and [18F]PI-2620 in Alzheimer Disease
Olafson E, Tonietto M, Klein G, Teng E, Stephens A, Russell D, Pickthorn K, Bohorquez S. In Vivo Head-to-Head Comparison of [18F]GTP1 with [18F]MK-6240 and [18F]PI-2620 in Alzheimer Disease. Journal Of Nuclear Medicine 2025, 66: jnumed.124.268623. PMID: 39746756, PMCID: PMC11800736, DOI: 10.2967/jnumed.124.268623.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseAccumulation of tau neurofibrillary tanglesTau neurofibrillary tanglesOff-target regionsNeurofibrillary tanglesTau pathologyTau-PET signalTau PET tracersBinding profilesTau-PETMild ADNormal cognitionBraak regionsHead-to-head studiesAD patientsTauMagnitude of uptakeTracer bindingAlzheimerTarget region
2024
Plasma Aβ42/Aβ40 is sensitive to early cerebral amyloid accumulation and predicts risk of cognitive decline across the Alzheimer's disease spectrum
Trelle A, Young C, Vossler H, Benitez J, Cody K, Mendiola J, Swarovski M, Le Guen Y, Feinstein I, Butler R, Channappa D, Romero A, Park J, Shahid‐Besanti M, Corso N, Chau K, Smith A, Skylar‐Scott I, Yutsis M, Fredericks C, Tian L, Younes K, Kerchner G, Deutsch G, Davidzon G, Sha S, Henderson V, Longo F, Greicius M, Wyss‐Coray T, Andreasson K, Poston K, Wagner A, Mormino E, Wilson E. Plasma Aβ42/Aβ40 is sensitive to early cerebral amyloid accumulation and predicts risk of cognitive decline across the Alzheimer's disease spectrum. Alzheimer's & Dementia 2024, 21: e14442. PMID: 39713875, PMCID: PMC11848181, DOI: 10.1002/alz.14442.Peer-Reviewed Original ResearchConceptsAlzheimer's diseaseCognitive declinePositron emission tomographyAmyloid-betaTau accumulationAmyloid positivityHippocampal-dependent memoryAlzheimer's disease spectrumAmyloidAmyloid accumulationTau burdenAb accumulationRisk of cognitive declineSensitive to memoryTau positron emission tomographyAlzheimer's Disease Research CenterPredicting cognitive declineAlzheimerTauScalable biomarkersAD continuumCerebral amyloid accumulationCross-sectional associationsCI individualsAccumulationPhase 2A Proof-of-Concept Double-Blind, Randomized, Placebo-Controlled Trial of Nicotinamide in Early Alzheimer Disease
Grill J, Tam S, Thai G, Vides B, Pierce A, Green K, Gillen D, Teng E, Kremen S, Beigi M, Rissman R, Léger G, Balasubramanian A, Revta C, Morrison R, Jennings R, Pa J, Zhang J, Jin S, Messer K, Feldman H. Phase 2A Proof-of-Concept Double-Blind, Randomized, Placebo-Controlled Trial of Nicotinamide in Early Alzheimer Disease. Neurology 2024, 104: e210152. PMID: 39671543, PMCID: PMC11655133, DOI: 10.1212/wnl.0000000000210152.Peer-Reviewed Original ResearchConceptsTau phosphorylationP-tau<sub>181</sub>Histone deacetylasesCDR-SBAlzheimer's diseaseCSF p-tauPrimary outcomeP-tauDiagnosis of mild cognitive impairmentAlzheimer's Disease Assessment ScaleAlzheimer's Disease Cooperative Study-ActivitiesClass III histone deacetylasePrespecified secondary outcomesCellular oxidation-reduction reactionsDisease Assessment ScaleLevels of tauAD biomarkersHolm-Bonferroni procedureMild cognitive impairmentControl type I errorThreonine 231Histone deacetylase inhibitionAcademic clinical centersAssessment ScaleAdverse eventsPhase separation of microtubule-binding proteins - implications for neuronal function and disease.
Duan D, Koleske A. Phase separation of microtubule-binding proteins - implications for neuronal function and disease. Journal Of Cell Science 2024, 137 PMID: 39679446, PMCID: PMC11795294, DOI: 10.1242/jcs.263470.Peer-Reviewed Original ResearchConceptsMT-binding proteinsLiquid-liquid phase separationRegulation of MT dynamicsProtein liquid-liquid phase separationNeuronal developmentTau neurofibrillary tanglesCytoskeletal regulationMT dynamicsNeurofibrillary tanglesBinding domainMT nucleationBiological functionsDisordered regionsAlzheimer's diseaseNeurodegenerative diseasesIn vivo studiesMaintains homeostasisMicrotubulesNeuronal functionMature neuronsProteinRegulationIn vitroFormation of aggregatesIn vitro studiesDeep learning analysis of fMRI data for predicting Alzheimer’s Disease: A focus on convolutional neural networks and model interpretability
Zhou X, Kedia S, Meng R, Gerstein M. Deep learning analysis of fMRI data for predicting Alzheimer’s Disease: A focus on convolutional neural networks and model interpretability. PLOS ONE 2024, 19: e0312848. PMID: 39630834, PMCID: PMC11616848, DOI: 10.1371/journal.pone.0312848.Peer-Reviewed Original ResearchMeSH KeywordsAgedAged, 80 and overAlzheimer DiseaseBrainDeep LearningFemaleHumansMagnetic Resonance ImagingMaleNeural Networks, ComputerNeuroimagingConceptsConvolutional neural networkNeural networkAlzheimer's diseaseConvolutional neural network modelMultimodal medical datasetsDeep learning methodsPotential of deep learningGenetic risk factorsMedical datasetsAlzheimer's Disease Neuroimaging InitiativeAD predictionDeep learningDeep learning analysisLearning methodsMedical imagesPredicting Alzheimer's diseaseDetection of Alzheimer's diseaseModel interpretationEarly detection of Alzheimer's diseaseAccuracy levelGenetic factorsDatasetEarly detection of ADNetworkDetection of ADThe early-onset Alzheimer’s disease MRI signature: a replication and extension analysis in early-stage AD
Mehta R, Keith C, Teixeira C, Worhunsky P, Phelps H, Ward M, Miller M, Navia R, Pockl S, Rajabalee N, Coleman M, D’Haese P, Rezai A, Wilhelmsen K, Haut M. The early-onset Alzheimer’s disease MRI signature: a replication and extension analysis in early-stage AD. Cerebral Cortex 2024, 34: bhae475. PMID: 39714256, PMCID: PMC11664631, DOI: 10.1093/cercor/bhae475.Peer-Reviewed Original ResearchMeSH KeywordsAge of OnsetAgedAlzheimer DiseaseAtrophyBrainCerebral CortexCohort StudiesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedConceptsEarly-onset Alzheimer's diseaseLate-onset Alzheimer's diseaseNon-AD pathologyCognitively normal individualsManagement of personsCortical atrophyFunctional statusEarly-stage ADRural populationAlzheimer's diseaseDisease stageLongitudinal studyCortical signatureWhole-brainCortical thinningCortical analysisClinical cohortNormal individualsClinical effectsSignature regionsIndividualsPersonsEarly disease stagesMRI signaturesControversies and insights into PTBP1-related astrocyte-neuron transdifferentiation: neuronal regeneration strategies for Parkinson’s and Alzheimer’s disease
McDowall S, Bagda V, Hodgetts S, Mastaglia F, Li D. Controversies and insights into PTBP1-related astrocyte-neuron transdifferentiation: neuronal regeneration strategies for Parkinson’s and Alzheimer’s disease. Translational Neurodegeneration 2024, 13: 59. PMID: 39627843, PMCID: PMC11613593, DOI: 10.1186/s40035-024-00450-9.Peer-Reviewed Original ResearchConceptsPolypyrimidine tract-binding protein 1Expression of polypyrimidine tract-binding protein 1Stem cell transplantationReprogramming of astrocytesCentral nervous system disordersAlzheimer's diseaseNeurodegenerative disordersNervous system disordersCell transplantationReprogram astrocytesTherapeutic strategiesAnimal modelsSystem disordersDisease outcomeRegenerative therapeuticsNeuronal populationsGlial cellsTherapeutic potentialProtein 1NeuronsAstrocyte heterogeneityDiseaseAstrocytesDisordersPublished studies
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