Modeling late-onset Alzheimer’s disease neuropathology via direct neuronal reprogramming
(2024) Science (New York, N.Y.), 385 (6708), p. adl2992.
Sun, Z.a b c , Kwon, J.-S.a d , Ren, Y.a e , Chen, S.a b c , Walker, C.K.a b c , Lu, X.f , Cates, K.a g , Karahan, H.h i , Sviben, S.j , Fitzpatrick, J.A.J.j , Valdez, C.k , Houlden, H.l , Karch, C.M.c f m , Bateman, R.J.n o , Sato, C.n o , Mennerick, S.J.f , Diamond, M.I.k , Kim, J.h i , Tanzi, R.E.p , Holtzman, D.M.c m o , Yoo, A.S.a b c
a Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO 63110, United States
b Center for Regenerative Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
c Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, United States
d Program in Computational and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, United States
e Program in Developmental, Stem Cell Biology, Washington University School of Medicine, St. Louis, MO 63110, United States
f Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
g Program in Molecular Genetics and Genomics, Washington University School of Medicine, St. Louis, MO 63110, United States
h Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN 46202, United States
i Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, United States
j Washington University Center for Cellular Imaging, Washington University School of Medicine, St. Louis, MO 63110, United States
k Center for Alzheimer’s and Neurodegenerative Diseases, Peter O’Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX 75390, United States
l UCL Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
m Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, United States
n Tracy Family SILQ Center for Neurodegenerative Biology, St. Louis, MO 63110, United States
o Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
p Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, United States
Abstract
Late-onset Alzheimer’s disease (LOAD) is the most common form of Alzheimer’s disease (AD). However, modeling sporadic LOAD that endogenously captures hallmark neuronal pathologies such as amyloid-β (Aβ) deposition, tau tangles, and neuronal loss remains an unmet need. We demonstrate that neurons generated by microRNA (miRNA)-based direct reprogramming of fibroblasts from individuals affected by autosomal dominant AD (ADAD) and LOAD in a three-dimensional environment effectively recapitulate key neuropathological features of AD. Reprogrammed LOAD neurons exhibit Aβ-dependent neurodegeneration, and treatment with β- or γ-secretase inhibitors before (but not subsequent to) Aβ deposit formation mitigated neuronal death. Moreover inhibiting age-associated retrotransposable elements in LOAD neurons reduced both Aβ deposition and neurodegeneration. Our study underscores the efficacy of modeling late-onset neuropathology of LOAD through high-efficiency miRNA-based neuronal reprogramming.
Document Type: Article
Publication Stage: Final
Source: Scopus
Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study
(2024) Aging and Disease, 15 (4), pp. 1843-1854. Cited 4 times.
Dolatshahi, M.a , Commean, P.K.a , Rahmani, F.a , Liu, J.b , Lloyd, L.a , Nguyen, C.a , Hantler, N.a , Ly, M.a , Yu, G.a , Ippolito, J.E.a c , Sirlin, C.d , Morris, J.C.e f , Benzinger, T.L.S.a f g , Raji, C.A.a e f
a Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
b Washington University School of Medicine, Division of Public Health Sciences, Department of Surgery, St. Louis, MO, United States
c Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, United States
d Liver Imaging Group, Department of Radiology, University of California, La Jolla, San Diego, CA, United States
e Department of Neurology, Washington University School of Medicine, St Louis, MO, United States
f Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, United States
g Department of Neurosurgery, Washington University School of Medicine, St Louis, MO, United States
Abstract
Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRI-determined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman’s partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology. Copyright: © 2023 Dolatshahi M. et al.
Author Keywords
Alzheimer disease; beta-amyloid; MRI; obesity; PET; visceral adipose tissue
Funding details
Washington University in St. LouisWUSTL
National Institutes of HealthNIH1RF1AG072637-01
National Institutes of HealthNIH
P30AG066444
P01AG026276
P01AG003991
Document Type: Article
Publication Stage: Final
Source: Scopus
Cognition Mediates the Association between Cerebrospinal Fluid Biomarkers of Amyloid and P-Tau and Neuropsychiatric Symptoms
(2024) Journal of Alzheimer’s Disease, 100 (3), pp. 1055-1073.
Frank, B.a b c , Walsh, M.b , Hurley, L.a , Groh, J.b , Blennow, K.d e , Zetterberg, H.d e f g h i , Tripodis, Y.b j , Budson, A.E.a b c , O’Connor, M.K.b c k , Martin, B.b l , Weller, J.b c , McKee, A.b c l m , Qiu, W.b n o , Stein, T.D.b c l m , Stern, R.A.b c p q , Mez, J.b c r , Henson, R.s , Long, J.s , Aschenbrenner, A.J.s , Babulal, G.M.s , Morris, J.C.s , Schindler, S.s , Alosco, M.L.b c
a U.S. Department of Veteran Affairs, VA Boston Healthcare System, Boston, MA, United States
b Boston University Alzheimer’s Disease Research Center, CTE Center, Boston University Chobanian and Avedisian, School of Medicine, Boston, MA, United States
c Department of Neurology, Boston University Chobanian, Avedisian School of Medicine, Boston, MA, United States
d Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
e Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
f Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
g UK Dementia Research Institute at UCL, London, United Kingdom
h Hong Kong Center for Neurodegenerative Diseases, Hong Kong, Hong Kong
i Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
j Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
k VA Bedford Healthcare System, U.S. Department of Veteran Affairs, Bedford, MA, United States
l Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, United States
m Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, United States
n Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
o Department of Pharmacology and Experimental Therapeutics, Boston University School of Medicine, Boston, MA, United States
p Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
q Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
r Framingham Heart Study, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, United States
s Knight Alzheimer Disease Research Center (ADRC), Washington University, St. Louis, MO, United States
Abstract
Background: Neuropsychiatric symptoms (NPS) can be an early manifestation of Alzheimer’s disease (AD). However, the associations among NPS, cognition, and AD biomarkers across the disease spectrum are unclear. Objective: We analyzed cross-sectional mediation pathways between cerebrospinal fluid (CSF) biomarkers of AD (Aβ1-42, p-Tau181), cognitive function, and NPS. Methods: Primary models included 781 participants from the National Alzheimer’s Coordinating Center (NACC) data set who had CSF analyzed for AD biomarkers using Lumipulse. NPS were assessed with the Neuropsychiatric Inventory Questionnaire (NPI-Q). We assessed cognition with the harmonized MMSE/MoCA, as well as neuropsychological tests sensitive to AD pathology: story recall, naming, animal fluency, and Trails B. The Clinical Dementia Rating (CDR®) scale assessed dementia severity. Mediation models were estimated with Kemeny metric covariance in a structural equation model framework, controlling for age, education, sex, and APOE ϵ4. Results: The sample was older adults (M=73.85, SD=6.68; 49.9% male, 390; 27.9% dementia, 218) who were predominantly white (n=688, 88.1%). Higher p-Tau181/Aβ1-42 ratio predicted higher NPI-Q, which was partially mediated by the MMSE/MoCA and, in a second model, story recall. No other pathway was statistically significant. Both the MMSE/MoCA and NPI-Q independently mediated the association between p-Tau181/Aβ1-42 ratio and CDR global impairment. With dementia excluded, p-Tau181/Aβ1-42 ratio was no longer associated with the NPI-Q. Conclusions: NPS may be secondary to cognitive impairment and AD pathology through direct and indirect pathways. NPS independently predict dementia severity in AD. However, AD pathology likely plays less of a role in NPS in samples without dementia. © 2024-IOS Press. All rights reserved.
Author Keywords
Alzheimer’s disease; amyloid; biomarkers; cerebrospinal fluid; cognition; neuropsychiatric symptoms; p-Tau
Funding details
Alzheimer’s AssociationAA
Horizon 2020 Framework ProgrammeH2020
Cure Alzheimer’s FundCAF
U.S. Department of Veterans AffairsVAIK2 CX002065, P30 AG066444, P01AG003991, P01AG026276, I01BX005933
U.S. Department of Veterans AffairsVA
H2020 Marie Skłodowska-Curie ActionsMSCA860197
H2020 Marie Skłodowska-Curie ActionsMSCA
P30 AG066507, P30 AG062421, P20 AG068077, P20 AG068053, P20 AG068024, P30 AG072973, P30 AG072931, P30 AG072979, P30 AG066509, P30 AG066519, P30 AG062422, P30 AG062715, P30 AG066462, P30 AG062677, P30 AG066518, P30 AG066511, P30 AG072947, P30 AG072975, P30 AG072958, P30 AG066468, P30 AG072978, P30 AG079280, P30 AG066514, P30 AG072972, P30 AG066512, P30 AG072959, P30 AG062429, P30 AG066530, P30 AG072976, P30 AG066515, P30 AG066508, P30 AG072977, P30 AG066506, P20 AG068082, P30 AG066546, P30 AG072946
-715986
EU Joint Programme – Neurodegenerative Disease ResearchJPNDJPND2021-00694
EU Joint Programme – Neurodegenerative Disease ResearchJPND
Hjärnfonden#FO2020-0240
Hjärnfonden
1UL1TR001430
National Institutes of HealthNIHP30AG072978, 1R01AG068398-01
National Institutes of HealthNIH
JPND2019-466-236
-71320, 101053962
UK Dementia Research InstituteUK DRI2017-00915, UKDRI-1003, -201809-2016615
UK Dementia Research InstituteUK DRI
2020-00124
#FO2022-0270
Alzheimer’s Drug Discovery FoundationADDF201809-2016862
Alzheimer’s Drug Discovery FoundationADDF
BrightFocus FoundationBFFA2021142 S, -930627
BrightFocus FoundationBFF
U24 AG072122
Alzheimerfonden-0243, -742881
Alzheimerfonden
2022-01018, 2019-02397, 2023-00356
National Institute on AgingNIAR01AG068183, R01AG080469, R01AG067428, R01AG074302
National Institute on AgingNIA
Document Type: Article
Publication Stage: Final
Source: Scopus
Cranioencephalic functional lymphoid units in glioblastoma
(2024) Nature Medicine, .
Dobersalske, C.a b c , Rauschenbach, L.a c d e f , Hua, Y.g , Berliner, C.h , Steinbach, A.a b c , Grüneboom, A.i , Kokkaliaris, K.D.j k l , Heiland, D.H.m n o , Berger, P.a b c , Langer, S.a b c , Tan, C.L.p q r , Stenzel, M.i , Landolsi, S.j k l , Weber, F.i , Darkwah Oppong, M.e f , Werner, R.A.s t u , Gull, H.a c e f , Schröder, T.v , Linsenmann, T.w , Buck, A.K.s , Gunzer, M.i x , Stuschke, M.a d y , Keyvani, K.z , Forsting, M.aa , Glas, M.a d f ab , Kipnis, J.ac ad , Steindler, D.A.ae af , Reinhardt, H.C.a d v ag , Green, E.W.p q r , Platten, M.p q r ah ai aj , Tasdogan, A.a d ag ak , Herrmann, K.a d h , Rambow, F.a g ag , Cima, I.a c , Sure, U.a d e f , Scheffler, B.a b c d ag
a German Cancer Consortium (DKTK), partner site Essen/Düsseldorf, a partnership between DKFZ and University Hospital Essen, University Duisburg–Essen, Essen, Germany
b German Cancer Research Center (DKFZ), Heidelberg, Germany
c DKFZ Division Translational Neurooncology at the WTZ, University Medicine Essen, Essen, Germany
d West German Cancer Center (WTZ), University Hospital Essen, Essen, Germany
e Department of Neurosurgery and Spine Surgery, University Hospital Essen, Essen, Germany
f Center for Translational Neuroscience and Behavioral Science (C-TNBS), University of Duisburg–Essen, Essen, Germany
g Department of Applied Computational Cancer Research, IKIM, University Hospital Essen, Essen, Germany
h Department of Nuclear Medicine, University Hospital Essen, Essen, Germany
i Leibniz-Institut für Analytische Wissenschaften—ISAS—e.V., Dortmund, Germany
j Dr. Senckenberg Institute of Pathology, University Hospital Frankfurt, Frankfurt am Main, Germany
k DKTK, German Cancer Consortium, partner site Frankfurt/Mainz, Quantitative Spatial Cancer Biology Laboratory, University Hospital Frankfurt, Frankfurt am Main, Germany
l Frankfurt Cancer Institute (FCI), Goethe University Frankfurt, Frankfurt am Main, Germany
m DKTK, German Cancer Consortium, partner site Freiburg, Translational Neurosurgery, Microenvironment and Immunology Research Laboratory, University of Freiburg, Freiburg, Germany
n Department of Neurosurgery, University Clinic Erlangen, Erlangen, Germany
o Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
p CCU Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center, Heidelberg, Germany
q DKTK, German Cancer Consortium, Core Center Heidelberg, Heidelberg, Germany
r Department of Neurology, Medical Faculty Mannheim, Mannheim Center for Translational Neuroscience, Heidelberg University, Mannheim, Germany
s Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
t University Hospital Frankfurt, Department of Nuclear Medicine, Clinic for Radiology and Nuclear Medicine, Frankfurt am Main, Germany
u The Russell H. Morgan Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Johns Hopkins University School of Medicine, Baltimore, MD, United States
v Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
w Department of Neurosurgery, University Hospital Würzburg, Würzburg, Germany
x Institute for Experimental Immunology and Imaging, University Hospital, University Duisburg–Essen, Essen, Germany
y Department of Radiation Oncology, University Hospital Essen, Essen, Germany
z Institute of Neuropathology, University Hospital Essen, Essen, Germany
aa Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
ab Department of Neurology, Division of Neurooncology, University Hospital Essen, Essen, Germany
ac Brain Immunology and Glia (BIG) Center, Washington University School of Medicine in St Louis, St Louis, MO, United States
ad Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO, United States
ae Steindler Consulting, Boston, MA, United States
af The Eshelman Institute for Innovation, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
ag Center of Medical Biotechnology (ZMB), University Duisburg–Essen, Essen, Germany
ah Immune Monitoring Unit, National Center for Tumor Diseases, Heidelberg, Germany
ai Helmholtz Institute for Translational Oncology, Mainz, Germany
aj German Cancer Research Center-Hector Cancer Institute at the Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
ak Department of Dermatology, University Hospital Essen, Essen, Germany
Abstract
The ecosystem of brain tumors is considered immunosuppressed, but our current knowledge may be incomplete. Here we analyzed clinical cell and tissue specimens derived from patients presenting with glioblastoma or nonmalignant intracranial disease to report that the cranial bone (CB) marrow, in juxtaposition to treatment-naive glioblastoma tumors, harbors active lymphoid populations at the time of initial diagnosis. Clinical and anatomical imaging, single-cell molecular and immune cell profiling and quantification of tumor reactivity identified CD8+ T cell clonotypes in the CB that were also found in the tumor. These were characterized by acute and durable antitumor response rooted in the entire T cell developmental spectrum. In contrast to distal bone marrow, the CB niche proximal to the tumor showed increased frequencies of tumor-reactive CD8+ effector types expressing the lymphoid egress marker S1PR1. In line with this, cranial enhancement of CXCR4 radiolabel may serve as a surrogate marker indicating focal association with improved progression-free survival. The data of this study advocate preservation and further exploitation of these cranioencephalic units for the clinical care of glioblastoma. © The Author(s) 2024.
Funding details
Else Kröner-Fresenius-StiftungEKFS
Bundesministerium für Bildung und ForschungBMBF
Deutschen Konsortium für Translationale KrebsforschungDKTK
16LW0404
DFG HE 8145/6-1/5-1, SFB1430-A09, SFB1399-A01, RE 2246/13-1, 507803309, SFB1530-A01, 453989101
Nationales Centrum für Tumorerkrankungen HeidelbergNCT Heidelberg01KT2328
Nationales Centrum für Tumorerkrankungen HeidelbergNCT Heidelberg
INST 35/1503-1 FUGG
01ZX1303A, 70113041, 404521405, 394046768, 1117240
2017.148.2
405344257, SCHE656/2-2
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
A genetic and proteomic comparison of key AD biomarkers across tissues
(2024) Alzheimer’s and Dementia, .
Marsh, T.W.a b c , Western, D.a b c , Timsina, J.b c , Gorijala, P.a b , Yang, C.b c , Pastor, P.d , Liu, M.b c , Morris, J.C.e f , Bateman, R.J.f g , Schindler, S.E.f , Sung, Y.J.b c , Cruchaga, C.b c e h i , Dominantly Inherited Alzheimer Networkj
a Division of Biology & Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, United States
b Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
c Neurogenomics and Informatics, Washington University in St. Louis, St. Louis, MO, United States
d Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol and The Germans Trias i Pujol Research Institute (IGTP) Badalona, Barcelona, Spain
e Knight Alzheimer’s Disease Research Center, Washington University in St. Louis, St. Louis, MO, United States
f Department of Neurology, Washington University in St Louis, St Louis, MO, United States
g Dominantly Inherited Alzheimer Network (DIAN), Washington University in St. Louis, St. Louis, MO, United States
h Hope Center for Neurological Diseases, Washington University in St. Louis, St. Louis, MO, United States
i Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
Abstract
INTRODUCTION: Plasma has been proposed as an alternative to cerebrospinal fluid (CSF) for measuring Alzheimer’s disease (AD) biomarkers, but no studies have analyzed in detail which biofluid is more informative for genetics studies of AD. METHOD: Eleven proteins associated with AD (α-synuclein, apolipoprotein E [apoE], CLU, GFAP, GRN, NfL, NRGN, SNAP-25, TREM2, VILIP-1, YKL-40) were assessed in plasma (n = 2317) and CSF (n = 3107). Both plasma and CSF genome-wide association study (GWAS) analyses were performed for each protein, followed by functional annotation. Additional characterization for each biomarker included calculation of correlations and predictive power. RESULTS: Eighteen plasma protein quantitative train loci (pQTLs) associated with 10 proteins and 16 CSF pQTLs associated with 9 proteins were identified. Plasma and CSF shared some genetic loci, but protein levels between tissues correlated weakly. CSF protein levels better associated with AD compared to plasma. DISCUSSION: The present results indicate that CSF is more informative than plasma for genetic studies in AD. Highlights: The identification of novel protein quantitative trait loci (pQTLs) in both plasma and cerebrospinal fluid (CSF). Plasma and CSF levels of neurodegeneration-related proteins correlated weakly. CSF is more informative than plasma for genetic studies of Alzheimer’s disease (AD). Neurofilament light (NfL), triggering receptor expressed on myeloid cells 2 (TREM2), and chitinase-3-like protein 1 (YKL-40) tend to show relatively strong inter-tissue associations. A novel signal in the apolipoprotein E (APOE) region was identified, which is an eQTL for APOC1. © 2024 The Author(s). Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.
Author Keywords
Alzheimer’s disease; biomarkers; CSF; genomics; neurodegenerative disease; plasma; protein quantitative trait loci
Funding details
BioClinica
Deutsches Zentrum für Neurodegenerative ErkrankungenDZNE
Hope Center for Neurological Disorders, Washington University in St. Louis
Fleni
National Multiple Sclerosis SocietyNMSS
Fonds de Recherche du Québec – SantéFRQS
Chan Zuckerberg InitiativeCZI
Fondation Brain Canada
National Institute of Biomedical Imaging and BioengineeringNIBIB
AbbVie
Health~HollandLSH
Japan Agency for Medical Research and DevelopmentAMED
ZonMw
Canadian Institutes of Health ResearchCIHR
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
National Institute on AgingNIA
Alzheimer’s Drug Discovery FoundationADDF
Korea Health Industry Development InstituteKHIDI
Ministerio de Ciencia e InnovaciónMCINPID2020‐115613RA‐I00
Comunidad de Madrid2018‐T2/BMD‐11885
U.S. Department of DefenseDODW81XWH2010849 A
BrightFocus FoundationBFFA2021033S, P01AG03991
European CommissionEC860197, 831434
Selfridges Group FoundationNR170065
Alzheimer’s AssociationAAZEN‐22‐848604, 73305095007
W81XWH‐12‐2‐0012
Alzheimer’s Disease Neuroimaging InitiativeADNIU01 AG024904
BiogenWE.03‐2018‐05
5U19AG032438, P30 AG066444, – SG‐20‐690363, P01AG003991, P01AG026276
U19AG032438
National Institutes of HealthNIHR01AG044546, P01AG003991, U01AG058922, RF1AG074007, RF1AG058501, P30 AG066515, R00AG062723, P01AG026276, P30AG066444, RF1AG053303
Document Type: Article
Publication Stage: Article in Press
Source: Scopus