List of publications for February 18, 2022
Astrocytes deficient in circadian clock gene Bmal1 show enhanced activation responses to amyloid-beta pathology without changing plaque burden
(2022) Scientific Reports, 12 (1), art. no. 1796, .
McKee, C.A.a , Lee, J.a , Cai, Y.a d , Saito, T.b , Saido, T.c , Musiek, E.S.a
a Department of Neurology and Center On Biological Rhythms And Sleep, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
b Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Aichi, Nagoya, Japan
c Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako-shi, Saitama, Japan
d Ann Romney Center for Neurologic Diseases, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
Abstract
An emerging link between circadian clock function and neurodegeneration has indicated a critical role for the molecular clock in brain health. We previously reported that deletion of the core circadian clock gene Bmal1 abrogates clock function and induces cell-autonomous astrocyte activation. Regulation of astrocyte activation has important implications for protein aggregation, inflammation, and neuronal survival in neurodegenerative conditions such as Alzheimer’s disease (AD). Here, we investigated how astrocyte activation induced by Bmal1 deletion regulates astrocyte gene expression, amyloid-beta (Aβ) plaque-associated activation, and plaque deposition. To address these questions, we crossed astrocyte-specific Bmal1 knockout mice (Aldh1l1-CreERT2;Bmal1fl/fl, termed BMAL1 aKO), to the APP/PS1-21 and the APPNL-G-F models of Aβ accumulation. Transcriptomic profiling showed that BMAL1 aKO induced a unique transcriptional profile affecting genes involved in both the generation and elimination of Aβ. BMAL1 aKO mice showed exacerbated astrocyte activation around Aβ plaques and altered gene expression. However, this astrogliosis did not affect plaque accumulation or neuronal dystrophy in either model. Our results demonstrate that the striking astrocyte activation induced by Bmal1 knockout does not influence Aβ deposition, which indicates that the effect of astrocyte activation on plaque pathology in general is highly dependent on the molecular mechanism of activation. © 2022, The Author(s).
Document Type: Article
Publication Stage: Final
Source: Scopus
Selective reduction of astrocyte apoE3 and apoE4 strongly reduces Aβ accumulation and plaque-related pathology in a mouse model of amyloidosis
(2022) Molecular Neurodegeneration, 17 (1), art. no. 13, .
Mahan, T.E., Wang, C., Bao, X., Choudhury, A., Ulrich, J.D., Holtzman, D.M.
Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, United States
Abstract
Background: One of the key pathological hallmarks of Alzheimer disease (AD) is the accumulation of the amyloid-β (Aβ) peptide into amyloid plaques. The apolipoprotein E (APOE) gene is the strongest genetic risk factor for late-onset AD and has been shown to influence the accumulation of Aβ in the brain in an isoform-dependent manner. ApoE can be produced by different cell types in the brain, with astrocytes being the largest producer of apoE, although reactive microglia also express high levels of apoE. While studies have shown that altering apoE levels in the brain can influence the development of Aβ plaque pathology, it is not fully known how apoE produced by specific cell types, such as astrocytes, contributes to amyloid pathology. Methods: We utilized APOE knock-in mice capable of having APOE selectively removed from astrocytes in a tamoxifen-inducible manner and crossed them with the APP/PS1-21 mouse model of amyloidosis. We analyzed the changes to Aβ plaque levels and assessed the impact on cellular responses to Aβ plaques when astrocytic APOE is removed. Results: Tamoxifen administration was capable of strongly reducing apoE levels in the brain by markedly reducing astrocyte apoE, while microglial apoE expression remained. Reduction of astrocytic apoE3 and apoE4 led to a large decrease in Aβ plaque deposition and less compact plaques. While overall Iba1+ microglia were unchanged in the cortex after reducing astrocyte apoE, the expression of the disease-associated microglial markers Clec7a and apoE were lower around amyloid plaques, indicating decreased microglial activation. Additionally, astrocyte GFAP levels are unchanged around amyloid plaques, but overall GFAP levels are reduced in the cortex of female apoE4 mice after a reduction in astrocytic apoE. Finally, while the amount of neuritic dystrophy around remaining individual plaques was increased with the removal of astrocytic apoE, the overall amount of cortical amyloid-associated neuritic dystrophy was significantly decreased. Conclusion: This study reveals an important role of astrocytic apoE3 and apoE4 on the deposition and accumulation of Aβ plaques as well as on certain Aβ-associated downstream effects. © 2022, The Author(s).
Author Keywords
Aldh1l1-Cre; Alzheimer disease; Amyloid; apoE; Apolipoprotein E; Astrocyte; Aβ
Document Type: Article
Publication Stage: Final
Source: Scopus
Radiosynthesis and evaluation of a fluorine-18 radiotracer [18F]FS1P1 for imaging sphingosine-1-phosphate receptor 1
(2022) Organic and Biomolecular Chemistry, 20 (5), pp. 1041-1052.
Qiu, L.a , Jiang, H.a , Yu, Y.a , Gu, J.a , Wang, J.a , Zhao, H.a , Huang, T.a , Gropler, R.J.a , Klein, R.S.b c d , Perlmutter, J.S.c e f , Tu, Z.a
a Department of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, United States
b Department of Medicine, Washington University School of Medicine, Saint Louis, MO 63110, United States
c Departments of Neuroscience, Washington University School of Medicine, Saint Louis, MO 63110, United States
d Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO 63110, United States
e Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110, United States
f Physical Therapy and Occupational Therapy, Washington University School of Medicine, Saint Louis, MO 63110, United States
Abstract
Assessment of sphingosine-1-phosphate receptor 1 (S1PR1) expression could be a unique tool to determine the neuroinflammatory status for central nervous system (CNS) disorders. Our preclinical results indicate that PET imaging with [11C]CS1P1 radiotracer can quantitatively measure S1PR1 expression changes in different animal models of inflammatory diseases. Here we developed a multiple step F-18 labeling strategy to synthesize the radiotracer [18F]FS1P1, sharing the same structure with [11C]CS1P1. We explored a wide range of reaction conditions for the nucleophilic radiofluorination starting with the key ortho-nitrobenzaldehyde precursor 10. The tertiary amine additive TMEDA proved crucial to achieve high radiochemical yield of ortho-[18F]fluorobenzaldehyde [18F]12 starting with a small amount of precursor. Based on [18F]12, a further four-step modification was applied in one-pot to generate the target radiotracer [18F]FS1P1 with 30–50% radiochemical yield, >95% chemical and radiochemical purity, and a high molar activity (37–166.5 GBq μmol−1, decay corrected to end of synthesis, EOS). Subsequently, tissue distribution of [18F]FS1P1 in rats showed a high brain uptake (ID% g−1) of 0.48 ± 0.06 at 5 min, and bone uptake of 0.27 ± 0.03, 0.11 ± 0.02 at 5, and 120 min respectively, suggesting no in vivo defluorination. MicroPET studies showed [18F]FS1P1 has high macaque brain uptake with a standard uptake value (SUV) of ∼2.3 at 120 min. Radiometabolite analysis of macaque plasma samples indicated that [18F]FS1P1 has good metabolic stability, and no major radiometabolite confounded PET measurements of S1PR1 in nonhuman primate brain. Overall, [18F]FS1P1 is a promising F-18 S1PR1 radiotracer worthy of further clinical investigation for human use. This journal is © The Royal Society of Chemistry
Funding details
National Institutes of HealthNIH
National Institute of Neurological Disorders and StrokeNINDSNS0103957, NS103988, NS75527
National Institute of Biomedical Imaging and BioengineeringNIBIBEB025815
Document Type: Article
Publication Stage: Final
Source: Scopus
Using Smartphones to Reduce Research Burden in a Neurodegenerative Population and Assessing Participant Adherence: A Randomized Clinical Trial and Two Observational Studies
(2022) JMIR mHealth and uHealth, 10 (2), art. no. e31877, .
Beukenhorst, A.L.a b , Burke, K.M.c , Scheier, Z.c , Miller, T.M.d , Paganoni, S.c e , Keegan, M.c , Collins, E.c , Connaghan, K.P.f , Tay, A.d , Chan, J.g , Berry, J.D.c , Onnela, J.-P.a
a Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
b Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom
c Neurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, United States
d Department of Neurology, Washington University, Saint Louis, MO, United States
e Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, United States
f MGH Institute of Health Professions, Charlestown, MA, United States
g Biostatistics Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
Abstract
Background: Smartphone studies provide an opportunity to collect frequent data at a low burden on participants. Therefore, smartphones may enable data collection from people with progressive neurodegenerative diseases such as amyotrophic lateral sclerosis at high frequencies for a long duration. However, the progressive decline in patients’ cognitive and functional abilities could also hamper the feasibility of collecting patient-reported outcomes, audio recordings, and location data in the long term. Objective: The aim of this study is to investigate the completeness of survey data, audio recordings, and passively collected location data from 3 smartphone-based studies of people with amyotrophic lateral sclerosis. Methods: We analyzed data completeness in three studies: 2 observational cohort studies (study 1: N=22; duration=12 weeks and study 2: N=49; duration=52 weeks) and 1 clinical trial (study 3: N=49; duration=20 weeks). In these studies, participants were asked to complete weekly surveys; weekly audio recordings; and in the background, the app collected sensor data, including location data. For each of the three studies and each of the three data streams, we estimated time-to-discontinuation using the Kaplan–Meier method. We identified predictors of app discontinuation using Cox proportional hazards regression analysis. We quantified data completeness for both early dropouts and participants who remained engaged for longer. Results: Time-to-discontinuation was shortest in the year-long observational study and longest in the clinical trial. After 3 months in the study, most participants still completed surveys and audio recordings: 77% (17/22) in study 1, 59% (29/49) in study 2, and 96% (22/23) in study 3. After 3 months, passively collected location data were collected for 95% (21/22), 86% (42/49), and 100% (23/23) of the participants. The Cox regression did not provide evidence that demographic characteristics or disease severity at baseline were associated with attrition, although it was somewhat underpowered. The mean data completeness was the highest for passively collected location data. For most participants, data completeness declined over time; mean data completeness was typically lower in the month before participants dropped out. Moreover, data completeness was lower for people who dropped out in the first study month (very few data points) compared with participants who adhered long term (data completeness fluctuating around 75%). Conclusions: These three studies successfully collected smartphone data longitudinally from a neurodegenerative population. Despite patients’ progressive physical and cognitive decline, time-to-discontinuation was higher than in typical smartphone studies. Our study provides an important benchmark for participant engagement in a neurodegenerative population. To increase data completeness, collecting passive data (such as location data) and identifying participants who are likely to adhere during the initial phase of a study can be useful. © 2022 JMIR Publications. All rights reserved.
Author Keywords
Attrition; Digital phenotyping; Mobile health; Mobile phone; Smartphones; Trial
Document Type: Article
Publication Stage: Final
Source: Scopus
Validation of actigraphy for sleep measurement in children with cerebral palsy
(2022) Sleep Medicine, 90, pp. 65-73.
Xue, B.a , Licis, A.b c , Boyd, J.b , Hoyt, C.R.b d , Ju, Y.-E.S.b c e
a School of Engineering, Washington University, Saint Louis, MO, United States
b Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
c Center on Biological Rhythms and Sleep (COBRAS), Washington University, Saint Louis, MO, United States
d Department of Pediatrics, Washington University School of Medicine, Saint Louis, MO, United States
e Hope Center for Neurological Disorders, Saint Louis, MO, United States
Abstract
Objectives: Sleep issues are common in children with cerebral palsy (CP), although there are challenges in obtaining objective data about their sleep patterns. Actigraphs measure movement to quantify sleep but their accuracy in children with CP is unknown. Our goals were to validate actigraphy for sleep assessment in children with CP and to study their sleep patterns in a cross-sectional cohort study. Methods: We recruited children with (N = 13) and without (N = 13) CP aged 2–17 years (mean age 9 y 11mo [SD 4 y 10mo] range 4–17 y; 17 males, 9 females; 54% spastic quadriplegic, 23% spastic diplegic, 15% spastic hemiplegic, 8% unclassified CP). We obtained wrist and forehead actigraphy with concurrent polysomnography for one night, and home wrist actigraphy for one week. We developed actigraphy algorithms and evaluated their accuracy (agreement with polysomnography-determined sleep versus wake staging), sensitivity (sleep detection), and specificity (wake detection). Results: Our actigraphy algorithms had median 72–80% accuracy, 87–91% sensitivity, and 60–71% specificity in children with CP and 86–89% accuracy, 88–92% sensitivity, and 70–75% specificity in children without CP, with similar accuracies in wrist and forehead locations. Our algorithms had increased specificity and accuracy compared to existing algorithms, facilitating detection of sleep disruption. Children with CP showed lower sleep efficiency and duration than children without CP. Conclusions: Actigraphy is a valid tool for sleep assessment in children with CP. Children with CP have worse sleep efficiency and duration. © 2022 The Authors
Author Keywords
Actigraphy; Cerebral palsy; Children; Polysomnography; Validation
Funding details
National Institutes of HealthNIHK23-NS089922, KL2-TR000450, R01-AG059507, UL1RR024992, UL1TR000448, UL1TR002345
National Center for Advancing Translational SciencesNCATS
Institute of Clinical and Translational SciencesICTSCTSA 604
Document Type: Article
Publication Stage: Final
Source: Scopus
Microstructural Periventricular White Matter Injury in Post-hemorrhagic Ventricular Dilatation
(2022) Neurology, 98 (4), pp. E364-E375.
Isaacs, A.M.a b , Neil, J.J.c , McAllister, J.P.d , Dahiya, S.e , Castaneyra-Ruiz, L.d , Merisaari, H.h , Botteron, H.E.d , Alexopoulos, D.c , George, A.h , Sun, P.h , Morales, D.M.d , Shimony, J.S.i , Strahle, J.h , Yan, Y.f , Song, S.-K.h , Limbrick, D.D.d , Smyser, C.D.c g h
a The Department of Neuroscience, Washington University, St. Louis, MO, United States
b Department of Clinical Neurosciences, University of Calgary, Canada
c Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
d Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States
e Department of Pathology, Washington University School of Medicine, St. Louis, MO, United States
f Public Health Sciences, Washington University School of Medicine, St. Louis, MO, United States
g Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
h Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background and Objectives The neurologic deficits of neonatal post-hemorrhagic hydrocephalus (PHH) have been linked to periventricular white matter injury. To improve understanding of PHH-related injury, diffusion basis spectrum imaging (DBSI) was applied in neonates, modeling axonal and myelin integrity, fiber density, and extrafiber pathologies. Objectives included characterizing DBSI measures in periventricular tracts, associating measures with ventricular size, and examining MRI findings in the context of postmortem white matter histology from similar cases. Methods A prospective cohort of infants born very preterm underwent term equivalent MRI, including infants with PHH, high-grade intraventricular hemorrhage without hydrocephalus (IVH), and controls (very preterm [VPT]). DBSI metrics extracted from the corpus callosum, corticospinal tracts, and optic radiations included fiber axial diffusivity, fiber radial diffusivity, fiber fractional anisotropy, fiber fraction (fiber density), restricted fractions (cellular infiltration), and nonrestricted fractions (vasogenic edema). Measures were compared across groups and correlated with ventricular size. Corpus callosum postmortem immunohistochemistry in infants with and without PHH assessed intra- and extrafiber pathologies. Results Ninety-five infants born very preterm were assessed (68 VPT, 15 IVH, 12 PHH). Infants with PHH had the most severe white matter abnormalities and there were no consistent differences in measures between IVH and VPT groups. Key tract-specific white matter injury patterns in PHH included reduced fiber fraction in the setting of axonal or myelin injury, increased cellular infiltration, vasogenic edema, and inflammation. Specifically, measures of axonal injury were highest in the corpus callosum; both axonal and myelin injury were observed in the corticospinal tracts; and axonal and myelin integrity were preserved in the setting of increased extrafiber cellular infiltration and edema in the optic radiations. Increasing ventricular size correlated with worse DBSI metrics across groups. On histology, infants with PHH had high cellularity, variable cytoplasmic vacuolation, and low synaptophysin marker intensity. Discussion PHH was associated with diffuse white matter injury, including tract-specific patterns of axonal and myelin injury, fiber loss, cellular infiltration, and inflammation. Larger ventricular size was associated with greater disruption. Postmortem immunohistochemistry confirmed MRI findings. These results demonstrate DBSI provides an innovative approach extending beyond conventional diffusion MRI for investigating neuropathologic effects of PHH on neonatal brain development. Copyright © 2021 American Academy of Neurology
Funding details
396212
National Institutes of HealthNIHK02 NS089852, K23 MH105179, K23 NS075151, P30 NS098577, R01 HD057098, R01 HD061619, R01 MH113570, R01 NS047592, TR002344, U01 EY025500
Doris Duke Charitable FoundationDDCF
Dana Foundation
Cerebral Palsy International Research FoundationCPIRF
Child Neurology FoundationCNF
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDP50 HD103525
Document Type: Article
Publication Stage: Final
Source: Scopus
Association of BDNF Val66Met with Tau Hyperphosphorylation and Cognition in Dominantly Inherited Alzheimer Disease
(2022) JAMA Neurology, .
Lim, Y.Y.a , Maruff, P.a b , Barthélemy, N.R.c , Goate, A.d , Hassenstab, J.c , Sato, C.c , Fagan, A.M.c , Benzinger, T.L.S.e , Xiong, C.f , Cruchaga, C.g , Levin, J.h i j , Farlow, M.R.k , Graff-Radford, N.R.l , Laske, C.i m , Masters, C.L.n , Salloway, S.o p , Schofield, P.R.q r , Morris, J.C.c , Bateman, R.J.c , McDade, E.c
a Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
b Cogstate Ltd, Melbourne, VIC, Australia
c Department of Neurology, Washington University, School of Medicine in St Louis, St Louis, MO, United States
d Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
e Department of Radiology, Washington University, School of Medicine in St Louis, St Louis, MO, United States
f Division of Biostatistics, Washington University, School of Medicine in St Louis, St Louis, MO, United States
g Department of Psychiatry, Washington University, School of Medicine in St Louis, St Louis, MO, United States
h Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
i German Center for Neurodegenerative Diseases, Munich, Germany
j Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
k Department of Neurology, Indiana University, Indianapolis, United States
l Department of Neurology, Mayo Clinic Jacksonville, Jacksonville, FL, United States
m Section for Dementia Research, Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
n Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
o Butler Hospital, Providence, RI, United States
p Warren Alpert Medical School, Brown University, Providence, RI, United States
q Neuroscience Research Australia, Sydney, NSW, Australia
r School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
Abstract
Importance: Allelic variation in the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism moderates increases in cerebrospinal fluid (CSF) levels of tau and phosphorylated tau 181 (p-tau181), measured using immunoassay, and cognitive decline in presymptomatic dominantly inherited Alzheimer disease (DIAD). Advances in mass spectrometry show that CSF tau phosphorylation occupancy at threonine 181 and 217 (p-tau181/tau181, p-tau217/tau217) increases with initial β-amyloid (Aβ) aggregation, while phosphorylation occupancy at threonine 205 (p-tau205/tau205) and level of total tau increase when brain atrophy and clinical symptoms become evident. Objective: To determine whether site-specific tau phosphorylation occupancy (ratio of phosphorylated to unphosphorylated tau) is associated with BDNF Val66Met in presymptomatic and symptomatic DIAD. Design, Setting, and Participants: This cross-sectional cohort study included participants from the Dominantly Inherited Alzheimer Network (DIAN) and Aβ-positive cognitively normal older adults in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Data were collected from 2009 through 2018 at multicenter clinical sites in the United States, United Kingdom, and Australia, with no follow-up. DIAN participants provided a CSF sample and completed clinical and cognitive assessments. Data analysis was conducted between March 2020 and March 2021. Main Outcomes and Measures: Mass spectrometry analysis was used to determine site-specific tau phosphorylation level; tau levels were also measured using immunoassay. Episodic memory and global cognitive composites were computed. Results: Of 374 study participants, 144 were mutation noncarriers, 156 were presymptomatic mutation carriers, and 74 were symptomatic carriers. Of the 527 participants in the network, 153 were excluded because their CSF sample, BDNF status, or both were unavailable. Also included were 125 Aβ-positive cognitively normal older adults in the ADNI. The mean (SD) age of DIAD participants was 38.7 (10.9) years; 43% were women. The mean (SD) age of participants with preclinical sporadic AD was 74.8 (5.6) years; 52% were women. In presymptomatic mutation carriers, compared with Val66 homozygotes, Met66 carriers showed significantly poorer episodic memory (d = 0.62; 95% CI, 0.28-0.95), lower hippocampal volume (d = 0.40; 95% CI, 0.09-0.71), and higher p-tau217/tau217 (d = 0.64; 95% CI, 0.30-0.97), p-tau181/tau181 (d = 0.65; 95% CI, 0.32-0.99), and mass spectrometry total tau (d = 0.43; 95% CI, 0.10-0.76). In symptomatic mutation carriers, Met66 carriers showed significantly poorer global cognition (d = 1.17; 95% CI, 0.65-1.66) and higher p-tau217/tau217 (d = 0.53; 95% CI, 0.05-1.01), mass spectrometry total tau (d = 0.78; 95% CI, 0.28-1.25), and p-tau205/tau205 (d = 0.97; 95% CI, 0.46-1.45), when compared with Val66 homozygotes. In preclinical sporadic AD, Met66 carriers showed poorer episodic memory (d = 0.39; 95% CI, 0.00-0.77) and higher total tau (d = 0.45; 95% CI, 0.07-0.84) and p-tau181 (d = 0.46; 95% CI, 0.07-0.85). Conclusions and Relevance: In DIAD, clinical disease stage and BDNF Met66 were associated with cognitive impairment and levels of site-specific tau phosphorylation. This suggests that pharmacological strategies designed to increase neurotrophic support in the presymptomatic stages of AD may be beneficial. © 2022 American Medical Association. All rights reserved.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum
(2022) JAMA Neurology, . Cited 1 time.
Jansen, W.J.a b , Janssen, O.a , Tijms, B.M.c , Vos, S.J.B.a , Ossenkoppele, R.c d , Visser, P.J.a c e , Aarsland, D.f g , Alcolea, D.h i , Altomare, D.j k , Von Arnim, C.l m , Baiardi, S.n , Baldeiras, I.o p q , Barthel, H.r , Bateman, R.J.s , Van Berckel, B.t , Binette, A.P.u v , Blennow, K.w , Boada, M.x y , Boecker, H.z , Bottlaender, M.aa , Den Braber, A.ab , Brooks, D.J.ac ad ae , Van Buchem, M.A.af , Camus, V.ag , Carill, J.M.ah , Cerman, J.ai , Chen, K.aj , Chételat, G.ak , Chipi, E.al , Cohen, A.D.am , Daniels, A.an , Delarue, M.ak , Didic, M.ao ap , Drzezga, A.z aq , Dubois, B.ar , Eckerström, M.as , Ekblad, L.L.at , Engelborghs, S.au av , Epelbaum, S.ar , Fagan, A.M.aw , Fan, Y.ax , Fladby, T.ay , Fleisher, A.S.az , Van Der Flier, W.M.ab , Förster, S.ba bb , Fortea, J.h i , Frederiksen, K.S.bc , Freund-Levi, Y.bd be bf , Frings, L.bg , Frisoni, G.B.bh , Fröhlich, L.bi , Gabryelewicz, T.bj , Gertz, H.-J.bk , Gill, K.D.bl , Gkatzima, O.bm , Gómez-Tortosa, E.bn , Grimmer, T.bo , Guedj, E.bp , Habeck, C.G.bq , Hampel, H.br , Handels, R.bs , Hansson, O.bt , Hausner, L.bu , Hellwig, S.bv , Heneka, M.T.bw bx , Herukka, S.-K.by bz , Hildebrandt, H.ca , Hodges, J.cb , Hort, J.ai , Huang, C.-C.cc , Iriondo, A.J.cd , Itoh, Y.ce , Ivanoiu, A.cf , Jagust, W.J.cg ch , Jessen, F.ci cj ck , Johannsen, P.cl , Johnson, K.A.cm , Kandimalla, R.bl cn co cp , Kapaki, E.N.cq , Kern, S.cr , Kilander, L.cs , Klimkowicz-Mrowiec, A.ct , Klunk, W.E.cu cv , Koglin, N.cw , Kornhuber, J.cx , Kramberger, M.G.cy , Kuo, H.-C.cz , Van Laere, K.da db , Landau, S.M.dc , Landeau, B.ak , Lee, D.Y.dd , De Leon, M.de , Leyton, C.E.df , Lin, K.-J.dg dh , Lleó, A.h i , Löwenmark, M.di , Madsen, K.dj , Maier, W.dk , Marcusson, J.dl , Marquié, M.x y , Martinez-Lage, P.dm , Maserejian, N.dn , Mattsson, N.bt , De Mendonça, A.do , Meyer, P.T.bg , Miller, B.L.dp , Minatani, S.ce , Mintun, M.A.dq , Mok, V.C.T.dr ds dt , Molinuevo, J.L.du , Morbelli, S.D.dv dw , Morris, J.C.aw , Mroczko, B.dx dy , Na, D.L.dz ea , Newberg, A.eb , Nobili, F.ec ed , Nordberg, A.a , Olde Rikkert, M.G.M.ee , De Oliveira, C.R.o , Olivieri, P.ef fd , Orellana, A.x y , Paraskevas, G.eg , Parchi, P.eh ei , Pardini, M.ej , Parnetti, L.al , Peters, O.ek , Poirier, J.el , Popp, J.em en , Prabhakar, S.eo , Rabinovici, G.D.ep , Ramakers, I.H.bs , Rami, L.eq , Reiman, E.M.aj , Rinne, J.O.er , Rodrigue, K.M.es , Rodríguez-Rodriguez, E.et , Roe, C.M.aw , Rosa-Neto, P.el , Rosen, H.J.eu , Rot, U.ev , Rowe, C.C.ew ex , Rüther, E.ey , Ruiz, A.x y , Sabri, O.r , Sakhardande, J.ez , Sánchez-Juan, P.fa , Sando, S.B.fb fc , Santana, I.o p q , Sarazin, M.ef fd , Scheltens, P.ab , Schröder, J.fe , Selnes, P.ay , Seo, S.W.ff , Silva, D.fg , Skoog, I.cr , Snyder, P.J.fh , Soininen, H.fi fj , Sollberger, M.fk fl , Sperling, R.A.fm fn , Spiru, L.fo fp , Stern, Y.ez , Stomrud, E.bt , Takeda, A.ce , Teichmann, M.ar fq , Teunissen, C.E.ab , Thompson, L.I.fr , Tomassen, J.ab , Tsolaki, M.fs , Vandenberghe, R.ft fu , Verbeek, M.M.fv , Verhey, F.R.J.bs , Villemagne, V.ew fw , Villeneuve, S.u v fx , Vogelgsang, J.fy , Waldemar, G.bc fz , Wallin, A.cr , Wallin, Å.K.bt , Wiltfang, J.ga gb , Wolk, D.A.gc , Yen, T.-C.gd ge , Zboch, M.gf , Zetterberg, H.cr gg gh gi gj
a Alzheimer Centre Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, PO Box 616, Maastricht, 6200 MD, Netherlands
b Banner Alzheimer’s Institute, Phoenix, AZ, United States
c Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
d Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
e Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
f Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division for Neurogeriatrics, Karolinska Institutet, Huddinge, Sweden
g Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
h Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas, Madrid, Spain
i Memory Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
j Laboratory Alzheimer’s Neuroimaging and Epidemiology, Istituto di Ricovero e Cura A Carattere Scientifico (IRCCS) Fatebenefratelli, Brescia, Italy
k Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
l Division of Geriatrics, University of Goettingen Medical School, Goettingen, Germany
m Clinic for Neurogeriatrics and Neurological Rehabilitation, University and Rehabilitation Hospital Ulm, Ulm, Germany
n Department of Experimental Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Spain
o Center for Neuroscience and Cell Biology (CIBB), University of Coimbra, Coimbra, Portugal
p Neurology Department and Laboratory of Neurochemistry, Centro Hospitalar e Universitário de Coimbra, Praceta Professor Mota Pinto, Coimbra, Portugal
q Faculty of Medicine, University of Coimbra, Azinhaga de Santa Comba, Coimbra, Portugal
r Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
s Department of Neurology and the Alzheimer’s Disease Research Center, Washington University, School of Medicine in St Louis, St Louis, MO, United States
t Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
u Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canada
v Douglas Mental Health University Institute, Montreal, QC, Canada
w Clinical Neurochemistry Laboratory, Department of Neuroscience and Physiology, Sahlgren’s University Hospital, Mölndal, Sweden
x Research Center and Memory Clinic of Fundació, Alzheimer Centre Educacional, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
y CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
z Deutsches Zentrum für Neurodegenerative Erkrankungen E.V. (DZNE), Bonn, Germany
aa Université Paris-Saclay, Service Hospitalier Frédéric Joliot (CEA), French National Centre for Scientific Research (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), BioMaps, Service Hospitalier Frederic Joliot, Orsay, France
ab Department of Neurology, Alzheimer Centre Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
ac Translational and Clinical Research Institute, University of Newcastle Upon Tyne, United Kingdom
ad Department of Nuclear Medicine, Positron Emission Tomography Centre, Aarhus University, Aarhus, Denmark
ae Department of Brain Sciences, Imperial College London, London, United Kingdom
af Department of Neurology, University Hospital Leiden, Leiden, Netherlands
ag Unite Mixte de Recherche, INSERM U930, French National Centre for Scientific Research (CNRS), ERL, Tours, France
ah Nuclear Medicine Department, University Hospital Marqués de Valdecilla, Molecular Imaging, Instituto de Investigación Sanitaria Valdecilla (IDIVAL), University of Cantabria, Santander, Spain
ai Department of Neurology, Second Faculty of Medicine, Charles University, Motol University Hospital, Prague, Czech Republic
aj Banner Alzheimer’s Institute, Phoenix, AZ, United States
ak Normandie University, University of Caen Normandie (UNICAEN), INSERM, U1237, Physiopathology and Imaging of Neurological Disorders (PhIND), Institut Blood and Brain at Caen-Normandie, Cyceron, Caen, France
al Centro Disturbi della Memoria, Laboratorio di Neurochimica Clinica, Clinica Neurologica, Università di Perugia, Perugia, Italy
am Department of Psychiatry, University of Pittsburgh, School of Medicine, Pittsburgh, PA, United States
an Department of Neurology, Washington University, School of Medicine in St Louis, St Louis, MO, United States
ao Assistance Publique Hôpitaux de Marseille (AP-HM), Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
ap Aix Marseille Univ, INSERM, Institut de Neurosciences des Systèmes (INS), Marseille, France
aq Department of Nuclear Medicine, University Hospital of Cologne, Cologne, Germany
ar Department of Neurology, Institut de la Mémoire et de la Maladie d’Alzheimer, Centre de Reference Demences Rares, Hopital de la Pitie-Salpetriere, Assistance Publique-Hôpitaux de Paris (AP-HP), Paris, France
as Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
at Turku PET Centre, University of Turku, Turku, Finland
au Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
av Center for Neurosciences, Vrije Universiteit Brussel, Brussels, Belgium
aw Department of Neurology, The Alzheimer’s Disease Research Center, Washington University, School of Medicine in St Louis, St Louis, MO, United States
ax Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
ay Department of Neurology, Akershus University Hospital, Lorenskog, Norway
az Eli Lilly and Company, Indianapolis, IN, United States
ba Department of Nuclear Medicine, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany
bb Department of Nuclear Medicine, Klinikum Bayreuth, Bayreuth, Germany
bc Danish Dementia Research Center, Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
bd School of Medical Sciences, Örebro University, Örebro, Sweden
be Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Center for Alzheimer Research, Stockholm, Sweden
bf Department of Old Age Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
bg Department of Nuclear Medicine, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
bh Memory Clinic, University Hospitals, University of Geneva, Geneva, Switzerland
bi Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
bj Department of Neurodegenerative Disorders, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
bk Klinik und Poliklinik für Psychiatrie und Psychotherapie, Universitätsklinikum Leipzig, Leipzig, Germany
bl Department of Biochemistry, Postgraduate Institute of Medical Education and Research, Chandigarh, India
bm Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Greece
bn Department of Neurology, Fundación Jiménez Díaz, Madrid, Spain
bo Department of Psychiatry and Psychotherapy, Klinikum Rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany
bp Aix Marseille University, AP-HM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, Centre Européen de Recherche en Imagerie Médicale (CERIMED), Nuclear Medicine Department, Marseille, France
bq Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, Irving Medical Center, New York, NY, United States
br Sorbonne University, Clinical Research Group No. 21, Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
bs Alzheimer Centre Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
bt Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
bu Universität Heidelberg, Abteilung Gerontopsychiatrie, Zentralinstitut für Seelische Gesundheit Mannheim, Mannheim, Germany
bv Department of Psychiatry, Psychotherapy Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
bw Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital of Bonn, Bonn, Germany
bx Division of Infectious Diseases and Immunology, University of Massachusetts Medical School, Worcester, United States
by Institute of Clinical Medicine-Neurology, University of Eastern Finland, Kuopio, Finland
bz Neurocenter, Neurology, Kuopio University Hospital, Kuopio, Finland
ca Klinikum Bremen-Ost, University of Oldenburg, Institute of Psychology, Oldenburg, Germany
cb Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
cc Chang Gung Memorial Foundation-Linkou, Taoyuan, Taiwan
cd Center for Research and Advanced Therapies, Centro de Investigación y Ciencias Avanzadas-Alzheimer Foundation, Donostia-San Sebastian, Spain
ce Department of Neurology, Osaka City University, Graduate School of Medicine, Osaka, Japan
cf Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
cg Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
ch Division of Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
ci Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
cj Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
ck DZNE, Bonn, Germany
cl Memory Disorder Unit, Copenhagen University Hospital, Copenhagen, Denmark
cm Department of Radiology, Massachusetts General Hospital, Boston, United States
cn Department of Radiation Oncology, Emory University, Atlanta, GA, United States
co Applied Biology, Council of Scientific and Industrial Research (CSIR)-Indian Institute of Chemical Technology, Uppal Road, Tarnaka, Telangana State, Hyderabad, India
cp Department of Biochemistry, Kakatiya Medical College, Mahatma Gandhi Memorial Hospital, Telangana State, Warangal, India
cq National and Kapodistrian University of Athens, School of Medicine, 1st Department of Neurology, Eginition Hospital, Athens, Greece
cr Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, The University of Gothenburg, Gothenburg, Sweden
cs Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden
ct Department of Internal Medicine and Gerontology, Faculty of Medicine, Jagiellonian University Medical College, Krakow, Poland
cu Department of Psychiatry, Massachusetts General Hospital, Boston, United States
cv Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
cw Life Molecular Imaging GmbH, Berlin, Germany
cx Department of Psychiatry and Psychotherapy, University Hospital, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
cy Department of Neurology, University Medical Centre Ljubljana, Ljubljana, Slovenia
cz Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Chang Gung University, College of Medicine, Taoyuan, Taiwan
da Division of Nuclear Medicine and Molecular Imaging, University Hospitals Leuven, Leuven, Belgium
db Department of Imaging and Pathology, Katholieke Universiteit Leuven, Leuven, Belgium
dc Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
dd Department of Neuropsychiatry, Seoul National University Hospital, Seoul, South Korea
de Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
df School of Psychology, Faculty of Science, The University of Sydney, Sydney, NSW, Australia
dg Healthy Aging Research Center, Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
dh Department of Nuclear Medicine, Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Guishan, Taoyuan, Taiwan
di Memory Clinic, Department of Geriatrics, Uppsala University Hospital, Uppsala, Sweden
dj Neurobiology Research Unit, Copenhagen University Hospital, Copenhagen, Denmark
dk Department of Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
dl Acute Internal Medicine and Geriatrics, Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
dm Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, Donostia-San Sebastian, Spain
dn Biogen, Cambridge, MA, United States
do Faculty of Medicine, University of Lisboa, Lisboa, Portugal
dp Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, United States
dq Avid Radiopharmaceuticals, Philadelphia, PA, United States
dr Division of Neurology, Department of Medicine and Therapeutics, Prince of Wales Hospital, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
ds Margaret K.L. Cheung Research Centre for Management of Parkinsonism, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
dt BrainNow Research Institute, Guangdong Province, Shenzhen, China
du Alzheimer’s Disease and Other Cognitive Disorders Unit, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Clinic University Hospital, Barcelona, Spain
dv Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
dw Ospedale Policlinico San Martino, IRCCS, Genoa, Italy
dx Department of Neurodegeneration Diagnostics, Medical University of Białystok, Białystok, Poland
dy Department of Biochemical Diagnostics, University Hospital of Białystok, Białystok, Poland
dz Department of Neurology, Samsung Medical Center, Sungkyunkwan University, School of Medicine, Seoul, South Korea
ea Neuroscience Center, Samsung Medical Center, Seoul, South Korea
eb Myrna Brind Center of Integrative Medicine, Thomas Jefferson University and Hospital, Philadelphia, PA, United States
ec Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno-Infantili, University of Genoa, Genoa, Italy
ed Ospedale Policlinico San Martino, IRCCS, Genoa, Italy
ee Radboudumc Alzheimer Centre, Radboud University Medical Center, Nijmegen, Netherlands
ef Department of Neurology of Memory and Language, Groupe Hospitalier Universitaire Paris Psychiatry and Neurosciences, Hôpital Sainte Anne, Paris, F-75014, France
eg National and Kapodistrian University of Athens, School of Medicine, 1st Department of Neurology, Eginition Hospital, Athens, Greece
eh Istituto Delle Scienze Neurologiche di Bologna, IRCCS, Bologna, Italy
ei DIMES, University of Bologna, Bologna, Italy
ej DINOGMI, University of Genoa, Genoa, Italy
ek Klinik für Psychiatrie und Psychotherapie, Charité Universitätsmedizin Berlin-CBF, Berlin, Germany
el Studies on Prevention of Alzheimer’s Disease (StOP-AD) Centre, Montreal, QC, Canada
em Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, University of Zürich, Zürich, Switzerland
en Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, University of Lausanne, Lausanne, Switzerland
eo Department of Neurology, Nehru Hospital, Postgraduate Institute of Medical Education and Research, Chandigarh, India
ep Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, United States
eq Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, IDIBAPS, Barcelona, Spain
er Turku PET Centre, Turku, Finland
es Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, United States
et Neurology Department, Hospital Universitario Marqués de Valdecilla, IDIVAL, Santander, Spain
eu Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, United States
ev Department of Neurology, Medical Center, Zaloska 7, Ljubljana, Slovenia
ew Department of Molecular Imaging, Austin Health, Melbourne, VIC, Australia
ex Florey Department of Neuroscience, University of Melbourne, Melbourne, VIC, Australia
ey Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany, Germany
ez Cognitive Neuroscience Division, Department of Neurology, The Taub Institute, Columbia University, New York, NY, United States
fa Service of Neurology, University Hospital Marqués de Valdecilla-IDIVAL, CIBERNED, Santander, Spain
fb Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway
fc Department of Neurology, University Hospital of Trondheim, Trondheim, Norway
fd Université de Paris, Paris, Université Paris-Saclay, BioMaps, CEA, CNRS, INSERM, Orsay, France
fe Section for Geriatric Psychiatry, University of Heidelberg, Heidelberg, Germany
ff Department of Neurology, Sungkyunkwan University, School of Medicine, Samsung Medical Center, Seoul, South Korea
fg Faculty of Medicine, University of Lisboa, Lisboa, Portugal
fh Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, The University of Rhode Island, Kingston, United States
fi Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland, Finland
fj Neurocenter, Department of Neurology, Kuopio University Hospital, Kuopio, Finland
fk Memory Clinic, University Department of Geriatric Medicine, Felix Platter-Hospital, Basel, Switzerland
fl Department of Neurology, University Hospital Basel, Basel, Switzerland
fm Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
fn Harvard Aging Brain Study, Department of Neurology, Harvard Medical School, Boston, Massachusetts, United States
fo Geriatrics, Gerontology and Old Age Psychiatry Clinical Department, Carol Davila University of Medicine and Pharmacy-Elias, Emergency Clinical Hospital, Bucharest, Romania
fp Memory Clinic and Longevity Medicine, Ana Aslan International Foundation, Bucharest, Romania
fq Centre de Référence Démences Rares, Pitié-Salpêtrière University Hospital, AP-HP, Paris, France
fr Department of Psychiatry and Human Behavior, Alpert Medical School, Brown University, Providence, RI, United States
fs Aristotle University of Thessaloniki, Memory and Dementia Center, 3rd Department of Neurology, George Papanicolau General Hospital of Thessaloniki, Thessaloniki, Greece
ft Laboratory for Cognitive Neurology, Department of Neurosciences, University of Leuven, Leuven, Belgium
fu Neurology Department, University Hospitals Leuven, Leuven, Belgium, Belgium
fv Departments of Neurology and Laboratory Medicine, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Centre, Nijmegen, Netherlands
fw Molecular Biomarkers in Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
fx McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
fy Translational Neuroscience Laboratory, McLean Hospital, Harvard Medical School, Belmont, MA, United States
fz Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
ga Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
gb Center of Neurology, Department of Neurodegeneration, Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
gc Department of Neurology, University of Pennsylvania, Philadelphia, United States
gd Department of Nuclear Medicine, Molecular Imaging Center, Linkou Chang Gung Memorial Hospital, Guishan, Taoyuan, Taiwan
ge Healthy Aging Research Center, Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
gf Research-Scientific-Didactic Centre of Dementia-Related Diseases in Scinawa, Medical University of Wroclaw, Wroclaw, Poland
gg Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
gh Department of Neurodegenerative Disease, University College London (UCL), Queen Square Institute of Neurology, Queen Square, London, United Kingdom
gi UK Dementia Research Institute, London, United Kingdom
gj Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China, Hong Kong
Abstract
Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. Exposures: Alzheimer disease biomarkers detected on PET or in CSF. Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. Results: Among the 19097 participants (mean [SD] age, 69.1 [9.8] years; 10148 women [53.1%]) included, 10139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P =.04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P =.004), subjective cognitive decline (9%; 95% CI, 3%-15%; P =.005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P =.004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P =.18). Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies. © 2022 American Medical Association. All rights reserved.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Two Cases of Wolfram Syndrome Who Were Initially Diagnosed With Type 1 Diabetes
(2022) AACE Clinical Case Reports, .
Silvestri, F.a , Tromba, V.a , Costantino, F.a , Palaniappan, N.b c , Urano, F.b d
a Department of Pediatric Diabetology, “Sapienza” University of Rome, Italy
b Department of Medicine, Division of Endocrinology, Metabolism, and Lipid Research, Washington University School of Medicine, St. Louis, Missouri
c University of Missouri-Kansas City School of Medicine, Kansas City, Missouri
d Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri
Abstract
Objective: Early diagnosis of syndromic monogenic diabetes allows for proper management and can lead to improved quality of life in the long term. This report aimed to describe 2 genetically confirmed cases of Wolfram syndrome, a rare endoplasmic reticulum disorder characterized by insulin-dependent diabetes mellitus, optic nerve atrophy, and progressive neurodegeneration. Case Report: A 16-year-old Caucasian male patient and a 25-year-old Caucasian female patient with a history of diabetes mellitus and optic nerve atrophy presented at our medical center. Both patients were initially diagnosed with type 1 diabetes but negative for islet autoantibodies. Their body mass indexes were under 25 at the diagnosis. Their history and presentation were highly suspicious for Wolfram syndrome. Discussion: The genetic tests revealed a known Wolfram syndrome 1 (WFS1) pathogenic variant (homozygous) in the 16-year-old male patient and 2 known WFS1 pathogenic variants (compound heterozygous) in the 25-year-old female patient with diabetes mellitus and optic nerve atrophy, confirming the diagnosis of Wolfram syndrome. The first patient had a moderate form, and the second patient had a milder form of Wolfram syndrome. Conclusion: Providers should consider monogenic diabetes genetic testing, including WFS1 gene, for patients with early-onset diabetes who are negative for islet autoantibodies and lean. Two patients described in this article could have been diagnosed with Wolfram syndrome before they developed optic nerve atrophy. Genetic testing is a valuable tool for the early detection of Wolfram syndrome, which leads to proper management and improved quality of life in patients with this rare medical condition. © 2022 AACE
Author Keywords
diabetes mellitus; endoplasmic reticulum stress; monogenic diabetes genetic testing; optic nerve atrophy; Wolfram syndrome
Funding details
Eli Lilly and CompanyUS 10,695,324, US 9,891,231
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
BNP facilitates NMB-encoded histaminergic itch via NPRC-NMBR crosstalk
(2021) eLife, 10, .
Meng, Q.-T.a , Liu, X.-Y.a b , Liu, X.-T.a c d , Liu, J.a b , Munanairi, A.a b , Barry, D.M.a b , Liu, B.a b , Jin, H.a b , Sun, Y.a , Yang, Q.a b , Gao, F.a b , Wan, L.a e , Peng, J.a b , Jin, J.-H.a , Shen, K.-F.a , Kim, R.a , Yin, J.a b , Tao, A.d , Chen, Z.-F.a b c d f g
a Center for the Study of Itch and Sensory Disorders, Washington University School of Medicine, St Louis, United States
b Departments of Anesthesiology, Washington University School of Medicine, St Louis, United States
c Developmental Biology, Washington University School of Medicine, St. Louis, United States
d Second Affiliated Hospital, State Key Laboratory of Respiratory Disease, Guangdong Provincial Key Laboratory of Allergy & Clinical Immunology, Guangzhou Medical University, Guangzhou, China
e Department of Pain, Guangzhou Medical University, Guangzhou, China
f Departments of Medicine, Washington University School of Medicine, St. Louis, United States
g Departments of Psychiatry, Washington University School of Medicine, St. Louis, United States
Abstract
Histamine-dependent and -independent itch is conveyed by parallel peripheral neural pathways that express gastrin-releasing peptide (GRP) and neuromedin B (NMB), respectively, to the spinal cord of mice. B-type natriuretic peptide (BNP) has been proposed to transmit both types of itch via its receptor NPRA encoded by Npr1. However, BNP also binds to its cognate receptor, NPRC encoded by Npr3 with equal potency. Moreover, natriuretic peptides (NP) signal through the Gi-couped inhibitory cGMP pathway that is supposed to inhibit neuronal activity, raising the question of how BNP may transmit itch information. Here, we report that Npr3 expression in laminae I-II of the dorsal horn partially overlaps with NMB receptor (NMBR) that transmits histaminergic itch via Gq-couped PLCβ-Ca2+ signaling pathway. Functional studies indicate that NPRC is required for itch evoked by histamine but not chloroquine (CQ), a nonhistaminergic pruritogen. Importantly, BNP significantly facilitates scratching behaviors mediated by NMB, but not GRP. Consistently, BNP evoked Ca2+ responses in NMBR/NPRC HEK 293 cells and NMBR/NPRC dorsal horn neurons. These results reveal a previously unknown mechanism by which BNP facilitates NMB-encoded itch through a novel NPRC-NMBR cross-signaling in mice. Our studies uncover distinct modes of action for neuropeptides in transmission and modulation of itch in mice. © 2021, Meng et al.
An itch is a common sensation that makes us want to scratch. Most short-term itches are caused by histamine, a chemical that is released by immune cells following an infection or in response to an allergic reaction. Chronic itching, on the other hand, is not usually triggered by histamine, and is typically the result of neurological or skin disorders, such as atopic dermatitis. The sensation of itching is generated by signals that travel from the skin to nerve cells in the spinal cord. Studies in mice have shown that the neuropeptides responsible for delivering these signals differ depending on whether or not the itch involves histamine: GRPs (short for gastrin-releasing proteins) convey histamine-independent itches, while NMBs (short for neuromedin B) convey histamine-dependent itches. It has been proposed that another neuropeptide called BNP (short for B-type natriuretic peptide) is able to transmit both types of itch signals to the spinal cord. But it remains unclear how this signaling molecule is able to do this. To investigate, Meng, Liu, Liu, Liu et al. carried out a combination of behavioral, molecular and pharmacological experiments in mice and nerve cells cultured in a laboratory. The experiments showed that BNP alone cannot transmit the sensation of itching, but it can boost itching signals that are triggered by histamine. It is widely believed that BNP activates a receptor protein called NPRA. However, Meng et al. found that the BNP actually binds to another protein which alters the function of the receptor activated by NMBs. These findings suggest that BNP modulates rather than initiates histamine-dependent itching by enhancing the interaction between NMBs and their receptor. Understanding how itch signals travel from the skin to neurons in the spinal cord is crucial for designing new treatments for chronic itching. The work by Meng et al. suggests that treatments targeting NPRA, which was thought to be a key itch receptor, may not be effective against chronic itching, and that other drug targets need to be explored.
Author Keywords
BNP; GRP; itch; mouse; neuroscience; NPRA; NPRC; spinal cord
Document Type: Article
Publication Stage: Final
Source: Scopus
Genome-wide scan of Alzheimer disease cohort identifies genetic loci associated with human brain metabolite levels
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e051756.
Wang, C.a , Farias, F.H.G.a b , Novotny, B.C.c , Yang, C.b c , Wang, F.b c , Fernandez, V.b c , Harari, O.b c d , Cruchaga, C.b e f
a Washington University in St. Louis, St. Louis, MO, USA
b Hope Center for Neurological Disorders, St. Louis, MO, USA
c Washington University School of Medicine, St. Louis, MO, USA
d Washington University, MO, Saint Louis, United States
e Washington University, St. Louis, MO, USA
f Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
Abstract
BACKGROUND: Although metabolome-wide association study (MWAS) has been performed in a wide range of tissue types, such as serum, plasma, urine, saliva, and cerebrospinal fluid (CSF), it has not been conducted on any brain tissue. Here we seek to expand our knowledge on the genetic influence of brain metabolism and on the contribution of metabolism abnormality to AD with the metabolomics approach. We aim to identify metabolite quantitative trait loci (metabQTLs) with the largest AD brain cohort available. METHOD: We performed the first brain MWAS with 460 parietal cortex brains from the Knight-ADRC. 880 metabolites were measured by the powerful non-targeted Metabolon platform (HD4). European individuals were selected, and the analyses were adjusted for age at death, sex, genotype array methods, and genetic components. RESULT: We identified 31 locus-metabolite associations in 30 metabolites with genome-wide significance. 7 associations were significant after study-wide Bonferroni correction. We are performing functional characterization and replication leveraging datasets from ROSMAP brain cohort, WADRC CSF cohort, and other tissues’ cohorts. The strongest locus-metabolite association (p=5.2e-104), found in N6-methyllysine in the discovery phase, was first identified in CSF MWAS (Panyard et al., biorxiv, 2020). CONCLUSION: The first brain metabolome-wide association study discovered the importance of genetic influence on brain metabolite levels. Following expectation, brain metabQTLs can be replicated in the CSF study, implicating that brain and CSF share genetic features in modulating metabolism. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Presence of co-pathology in sporadic early-onset Alzheimer disease versus dominantly inherited Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e055045.
Llibre-Guerra, J.J.a , Li, Y.a , Franklin, E.E.a , Miller, C.A.b , Teich, A.F.c , Kofler, J.d , Dickson, D.W.e , Ghetti, B.F.f , Frosch, M.P.g , Halliday, G.M.h , McLean, C.i , Lashley, T.j , Gordon, B.A.a , Schindler, S.E.k , Chen, C.D.a , Fagan, A.M.a , Benzinger, T.L.S.a , Wang, G.a , Hassenstab, J.a , Morris, J.C.a , Bateman, R.J.a , Perrin, R.J.l , McDade, E.a
a Washington University in St. Louis, St. Louis, MO, USA
b Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
c Columbia University Medical Center, NY, NY, United States
d University of Pittsburgh School of Medicine, PA, Pittsburgh, United States
e Mayo Clinic, FL, Jacksonville, United States
f Indiana University School of Medicine, ININ, United States
g Massachusetts General Hospital, Harvard Medical School, MA, Boston, United States
h Neuroscience Research Australia, Randwick, Australia
i Victorian Brain Bank Network (VBBN), Melbourne, Australia
j University College London, Queen Square Institute of Neurology, London, United Kingdom
k Washington University School of Medicine, MO, Saint Louis, United States
l Washington University in St. Louis School of Medicine, St. Louis, MO, USA
Abstract
BACKGROUND: A small proportion of Alzheimer disease (AD), known as early onset AD (EOAD), has symptomatic age at onset (AAO) before age 65. About 5-10% of EOAD is dominantly inherited (DIAD); the rest is termed to be sporadic (sEOAD). Although DIAD and sEOAD share the hallmark plaques and tangles that define AD neuropathologic change (ADNC), the relative burdens of these lesions and the frequencies of non-AD co-pathologies in sEOAD relative to DIAD remain unknown. METHODS: We compared the neuropathological burden of AD and the frequency of AD and non-AD pathologies in 363 sEOAD cases from the National Alzheimer’s Coordinating Center (NACC) and in 62 DIAD cases (45 from the Dominantly Inherited Alzheimer Network (DIAN); 17 from NACC). Operational criteria for the classification of AD and other co-pathologies followed accepted NACC guidelines. Only cases with AAO under 65 and a primary pathological diagnosis of ‘high ADNC’ were included. RESULTS: DIAD participants [mean AAO = 42.9 ± 8.1 years] had higher CERAD scores than sEOAD cases [mean AAO = 57.1 ±7.2 years] [p=0.03]. Braak stages were similar for both cohorts. The frequency and severity of cerebral amyloid angiopathy (CAA) was higher in DIAD versus sEOAD [CAA: 100% vs 83.7%, p=0.001; severe CAA: 40.3% versus 20.1%, p<0.001, respectively]. The frequency of at least one non-AD/non-CAA pathology was similar between DIAD and sEOAD [63.9% vs 59.7%, p=0.61], but the frequency of multiple pathologies (two or more) was lower in DIAD [3.2%] than in sEOAD [21.0%, p<0.001]. Lewy body disease (LBD) was the most prevalent non-AD/non-CAA pathology in both cohorts [58.1% in DIAD, 51.2% in sEOAD; p=0.39]. Hippocampal sclerosis [14.5%] and argyrophilic grain disease [2.5%], were observed in sEOAD, but were absent from DIAD. CONCLUSIONS: DIAD cases show greater neuritic plaque density and more severe CAA than sEOAD cases, but comparable Braak NFT stages. The similar frequencies of LBD in both cohorts may be linked to severe AD neuropathological change, rather than co-incident age-related pathologies. Future studies should include methodologically uniform assessments of both cohorts to explore age-related and non-age-related mechanisms that may account for differences in the burdens of ADNC lesions and non-AD co-pathologies. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Gearing up for the future: Exploring facilitators and barriers to inform clinical trial design in frontotemporal lobar degeneration
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e052495.
Banga, Y.B.a b , Lai, Y.a b , Kim, P.a b , Boeve, B.F.c , Boxer, A.L.d , Rosen, H.J.d , Forsberg, L.K.c , Heuer, H.W.d , Brushaber, D.c , Appleby, B.e , Biernacka, J.M.c , Bordelon, Y.M.f , Botha, H.c , Bozoki, A.C.g , Brannelly, P.h , Dickerson, B.C.i , Dickinson, S.j , Dickson, D.W.k , Domoto-Reilly, K.l , Faber, K.m , Fagan, A.M.n , Fields, J.A.c , Fishman, A.o , Foroud, T.M.p , Galasko, D.R.q , Gavrilova, R.H.c , Gendron, T.F.k , Geschwind, D.H.r , Ghoshal, N.s , Goldman, J.t , Graff-Radford, J.c , Graff-Radford, N.R.k , Grant, I.u , Grossman, M.v , Hsiung, G.-Y.R.w , Huang, E.J.x , Huey, E.D.y , Irwin, D.J.v , Jones, D.T.c , Kantarci, K.c , Karydas, A.M.d , Kaufer, D.z , Knopman, D.S.c , Kramer, J.H.d , Kremers, W.K.c , Kornak, J.d , Kukull, W.A.aa , Lagone, E.p , Leger, G.C.ab , Litvan, I.ab , Ljubenkov, P.A.d , Lucente, D.E.i , Mackenzie, I.R.ac , Manoochehri, M.y , Masdeu, J.C.ad , McGinnis, S.ae , Mendez, M.F.af , Miller, B.L.ag , Miyagawa, T.c , Nelson, K.M.c , Onyike, C.U.ah , Pantelyat, A.ah , Pascual, B.ad , Pearlman, R.ai , Petrucelli, L.k , Pottier, C.P.k , Rademakers, R.k , Ramos, E.M.aj , Rankin, K.P.ak , Rascovsky, K.al , Rexach, J.E.r , Ritter, A.am , Roberson, E.D.an , Rojas, J.C.d , Sabbagh, M.N.am , Salmon, D.P.ao , Savica, R.c , Seeley, W.W.ak , Staffaroni, A.M.d , Syrjanen, J.A.c , Tartaglia, M.C.ap , Tatton, N.aq , Taylor, J.C.d , Toga, A.W.ar , Weintraub, S.as , Wheaton, D.at , Wong, B.au , Wszolek, Z.k , ALLFTD Consortiumav
a Heritage University, Toppenish, WA, USA
b Pacific Northwest University of Health Sciences, Yakima, WA, USA
c Mayo Clinic, MN, Rochester, United States
d University of California, San Francisco, San Francisco, CA, USA
e Case Western Reserve University, Cleveland, OH, USA
f University of California Los Angeles, Los Angeles, CA, USA
g Michigan State University, MI, East Lansing, United States
h Rainwater Charitable Foundation, TX, Fort Worth, United States
i Massachusetts General Hospital, MA, Boston, United States
j AFTD, PA, King of Prussia, United States
k Mayo Clinic, FL, Jacksonville, United States
l University of Washington, Seattle, WA, USA
m Indiana University School of Medicine, IN, Indianapolis, United States
n Washington University School of Medicine, MO, Saint Louis, United States
o Johns Hopkins University, MD, Baltimore, United States
p Indiana University, IN, Indianapolis, United States
q University of California, San Diego, La Jolla, CA, USA
r University of California, Los Angeles School of Medicine, Los Angeles, CA, USA
s Washington University, St. Louis, MO, USA
t Columbia University, NY, NY, United States
u Northwestern University, Chicago, United States
v Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United States
w Djavad Mowafaghian Centre for Brain Health, University of British Colombia, Vancouver, Canada
x Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
y Gertrude H. Sergievsky Center at Columbia University, NY, NY, United States
z University of North Carolina, Chapel Hill, United States
aa National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA, USA
ab University of California, San Diego, San Diego, CA, USA
ac University of British Columbia, Vancouver, Canada
ad Houston Methodist Neurological Institute, TX, Houston, United States
ae Harvard Medical School, MA, Boston, United States
af David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
ag University of California, San Francisco (UCSF), San Francisco, CA, USA
ah Johns Hopkins University School of Medicine, MD, Baltimore, United States
ai The Bluefield Project to Cure FTD, San Francisco, CA, USA
aj University of California, Los Angeles, Los Angeles, CA, USA
ak Memory and Aging Center, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
al Penn FTD Center, Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United States
am Cleveland Clinic Lou Ruvo Center for Brain Health, NV, Las Vegas, United States
an University of Alabama at Birmingham, Birmingham, AL, USA
ao Shiley-Marcos Alzheimer’s Disease Research Center, La Jolla, CA, United States
ap Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, ON, Toronto, Canada
aq AFTD, PA, Radnor, United States
ar Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
as Northwestern University Feinberg School of Medicine, Chicago, United States
at FTD Disorders Registry, San Francisco, CA, USA
au National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
Abstract
BACKGROUND: Frontotemporal lobar degeneration (FTLD) refers to a group of neurodegenerative conditions, affecting the frontal and/or temporal lobes. Ongoing research has provided insight into developing clinical trials for FTLD and key clinical measures such as structural MRI. To inform clinical trial design and optimize participation, it is imperative to explore facilitators and barriers for potential candidates. OBJECTIVE: The objective of this study is to explore facilitators and barriers to participating in future clinical trials for FTLD. METHODS: Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) are observational studies focused on characterizing FTLD syndromes in preparation for clinical trials. The 584 participants enrolled across 18 research sites in the United States and Canada completed a survey assessing interest in clinical trial participation. RESULTS: 29% of respondents self-reported as patients (63±10 years), 26% self-reported as caregivers answering on behalf of patients (65±10 years), and 45% self-reported as healthy but at risk for FTLD (48±14 years). Travel reimbursement was the most common factor reported to positively influence participation (≧66%), with the healthy but at risk group showing the strongest endorsement (83%). Cost and time involved in travel were possible barriers for about half of the patients (48%) and healthy but at risk respondents (53%). The respondents value receiving feedback on the study findings (≧80%) and being informed of their individual disease progression (≧75%). Particularly, keeping participation confidential was very important for the healthy but at risk group (62%). In regard to research assessments, most participants demonstrated a high interest in physical and neurological exams at a research center (≧87%) whereas only half were interested in doing more invasive procedures such as the lumbar puncture (≧52%). Overall, respondents showed a positive attitude and support for research participation (≧77%) and trusted that their health information would remain confidential in a clinical trial (≧53%). CONCLUSIONS: Favorable attitudes and interest towards medical research exist among participants. To optimize participation, clinical trials should allocate funding for travel and involve participants in feedback about study results and their disease progression. Alternatives to invasive assessments may increase participation. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
The impacts of menopause on a mouse model of co-morbid metabolic syndrome and Alzheimer’s disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e051172.
Abi-Ghanem, C.a , Salinero, A.E.a , Gannon, O.J.a , Riccio, D.a , Mansour, F.a , Kelly, R.D.a , Kordit, D.a , Wang, M.a , Kyaw, N.-R.a , Cirrito, J.R.b , Zuloaga, K.L.a
a Albany Medical College, Albany, NY, USA
b Washington University School of Medicine, MO, Saint Louis, United States
Abstract
BACKGROUND: Alzheimer’s disease (AD) is the leading cause of disability and 5th cause of death in people over 65 years of age. Approximately 2/3 of AD patients are women, most of whom are postmenopausal. Menopause is linked with cognitive changes in women: younger age at menopause is associated with worse cognitive outcomes. Moreover, menopause accelerates mid-life risk factors for dementia, by increasing risk for cardiovascular and cerebrovascular disease and metabolic disease which is by itself a risk factor for dementia. We have previously shown that female 3xTg-AD mice are more greatly impacted cognitively and metabolically by a high fat diet when compared to males. We therefore hypothesized that menopause would exacerbate both metabolic and cognitive impairment and pathology in a mouse model of AD. METHOD: Female App NL-F mice were placed on either low fat (LF; 10% fat) or high fat (HF; 60% fat; metabolic disease model) diet for 7 months. An accelerated ovarian failure model of menopause (4-vinylcyclohexene diepoxide) was used at diet onset and female estrus cycles were monitored to determine menopause onset. Metabolic status was assessed by tracking weight gain and assessing glucose tolerance. Mice were then subjected to a battery of behavioral tests before being euthanized and brains and serum were collected. RESULT: Menopausal mice tended to be more metabolically impaired (worse glucose tolerance) regardless of diet. Cognitive impairment differences between groups were investigated using several behavioral tests. Neither menopause nor HF diet affected anxiety-like behavior (open field testing), however HF diet decreased general activity levels. Novel object recognition testing demonstrated that menopause, regardless of diet, impaired episodic-like memory. Additionally, HF diet, regardless of menopause, impaired spatial learning (assessed via Barnes maze testing). We are currently evaluating the underlying pathology in the brain that could mediate these cognitive deficits (i.e. Amyloid pathology, white matter damage and neuroinflammation). CONCLUSION: We hope that this work will highlight the need to model endocrine aging in animal models of dementia and will contribute to further understanding of the interaction between metabolic disease and menopause in the scope of AD. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
25-Hydroxycholesterol modulates tau-mediated neurodegeneration and microglial chemotaxis and phagocytosis
(2021) Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 17, p. e056404.
Long, J.M.a b c , Tran, A.a , Serrano, J.R.d , Bao, X.d , Wang, C.a , Reznikov, J.a , Cashikar, A.G.a b , Paul, S.M.a b e , Holtzman, D.M.a b f
a Washington University in St. Louis, School of Medicine, St. Louis, MO, USA
b Hope Center for Neurological Disorders, St. Louis, MO, USA
c Knight Alzheimer Disease Research Center, St. Louis, MO, USA
d Washington University in St. Louis, St. Louis, MO, USA
e MA, Boston, United States
f Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
Abstract
BACKGROUND: Immune activation is an important component of Alzheimer disease (AD) pathology, with microglia playing a critical role in driving ApoE-dependent tau-mediated neurodegeneration. The oxysterol 25-hydroxycholesterol (25-HC) is an established potent regulator of peripheral innate immune response, though less is known regarding its role in CNS neuroimmune pathobiology. The enzyme that synthesizes 25-HC, cholesterol 25-hydroxylase (CH25H), is exclusively expressed by microglia in the CNS and is significantly upregulated in human AD brain and in transgenic AD mouse models. We have recently reported pro-inflammatory effects of 25-HC in ApoE4-expressing mouse microglia, including increased microglial IL-1β secretion and inflammasome activation. In this study we explored the role of 25-HC in ApoE-dependent tau-mediated neurodegeneration. METHOD: PS19 tauopathy mice previously crossed with ApoE targeted replacement (TR) mice were subsequently crossed with CH25H KO mice. Hippocampal (HC), entorhinal and pyriform cortical (EC/PC) and ventricular volumes were measured at 9 months of age. In vitro primary cell cultures containing neurons, mixed glia or microglia were utilized to evaluate effects of 25-HC or 7α,25-dihydroxycholesterol (7α,25-diHC), on neurotoxicity, microglial cytokine secretion, chemotaxis and phagocytic activity. RESULT: We found that in female tau mice expressing human ApoE4, genetic deletion of CH25H was protective (increased EC/PC volumes and reduced ventricular volumes). Similar trends were observed in male mice though these were not statistically significant. In a neuronal-glial co-culture model of ApoE4-mediated neurotoxicity, 25-HC protected against neurite loss and neuronal death at low concentrations but was potently neurotoxic at higher concentrations. In primary microglial cultures, 25-HC modulated secretion of a number of chemokines and provoked a potent microglial chemotaxic response that was most robust in microglia derived from CH25H KO, ApoE4-TR or ApoE4-TR-CH25H KO mice. 7α,25-diHC also stimulated chemotaxis but less robustly than 25-HC. Assays testing the effect of 25-HC and 7α,25-diHC on phagocytosis in microglia were also performed, and these data will be presented. CONCLUSION: 25-HC appears to modulate tau-mediated neurodegeneration in an ApoE-dependent manner, especially in female mice, possibly through effects on critical microglial cellular functions. CH25H and 25-HC may be viable therapeutic targets for AD-related neuroimmune activation. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Defining the role of PLD3 in Alzheimer disease pathology
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054611.
Rosene, M.J.a , Hsu, S.b , Martinez, R.c , Norton, J.a b d e , Yan, P.a , Cirrito, J.R.f , Lee, J.-M.a , Cuervo, A.M.g , Goate, A.M.h i , Cruchaga, C.d j k l m , Karch, C.M.c d j k
a Washington University School of Medicine, St. Louis, MO, USA
b Washington University in St. Louis, St. Louis, MO, USA
c Washington University, MO, Saint Louis, United States
d Hope Center for Neurological Disorders, St. Louis, MO, USA
e Knight Alzheimer Disease Research Center, St. Louis, MO, USA
f Washington University School of Medicine, MO, Saint Louis, United States
g Albert Einstein College of Medicine, NY, NY, United States
h Ronald M. Loeb Center for Alzheimer’s Disease, NY, NY, United States
i Icahn School of Medicine at Mount Sinai, NY, NY, United States
j Washington University in St. Louis School of Medicine, St. Louis, MO, USA
k NeuroGenomics and Informatics Center, St. Louis, MO, USA
l Washington University, St. Louis, MO, USA
m Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
Abstract
BACKGROUND: Alzheimer’s disease (AD) is characterized by the accumulation of amyloid-β (Aβ) in the brain. We recently identified coding variants in the phospholipase D3 (PLD3) gene that double the risk for late onset AD. METHOD: We examined the impact of PLD3 risk variants on PLD3 and Aβ metabolism using CRISPR/Cas9 in induced pluripotent stem cells (iPSC). We then modeled the PLD3 expression patterns observed in AD brains in immortalized cell and AD mouse models. Lysosomal function was assessed in human brain tissue. RESULT: PLD3 A442A disrupts a splicing enhancer binding site and reduces PLD3 splicing in human brains. Differentiation of PLD3 A442A and isogenic control iPSCs into cortical neurons produced cells that were morphologically similar. At the molecular level, PLD3 A442A neurons displayed a similar defect in PLD3 splicing as was observed in human brains and a significant increase in Aβ42/Aβ40 compared with isogenic control lines. Thus, PLD3 A442A is sufficient to alter PLD3 splicing and Aβ metabolism. PLD3 expression was significantly lower in AD brains compared with controls, and PLD3 expression was highly correlated with expression of lysosomal genes. Thus, we sought to determine whether PLD3 contributes to Aβ accumulation in AD via disrupted Aβ metabolism. We found that overexpression of PLD3 in immortalized cells decreased Aβ levels while shRNA silencing of PLD3 increased Aβ levels. In an AD mouse model, overexpression of PLD3 in hippocampal neurons produced decreased interstitial fluid (ISF) Aβ levels and accelerated Aβ turnover. Conversely, knocking out PLD3 increased ISF Aβ, reduced Aβ turnover, and increased APP protein levels. Thus, reduced turnover of ISF Aβ along with increase APP substrate may lead to Aβ accumulation. To begin to determine whether PLD3 influences Aβ turnover via the lysosome, we isolated lysosomal fractions from human AD and control brains. PLD3 was enriched in lysosomal subfractions and PLD3 distribution in these subfractions was altered in AD. Furthermore, PLD3 stability in the lysosomal fractions was disrupted in AD brains. CONCLUSION: Together, our findings demonstrate that PLD3 promotes Aβ clearance through pathways involving lysosomal degradation. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Functional exploration of AGFG2, a novel player in the pathology of Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054240.
Fernandez, M.V.a b , Budde, J.P.c d , Eteleeb, A.b , Wang, F.c d , Martinez, R.e , Norton, J.c d , Gentsch, J.c d , Morris, J.C.a f g , Bateman, R.J.c d h , McDade, E.c h , Perrin, R.J.d h i , Harari, O.c d h j , Benitez, B.A.c d j , Karch, C.M.d e , Cruchaga, C.d j k
a Hope Center for Neurological Disorders, MO, Saint Louis, United States
b Washington University School of Medicine, MO, Saint Louis, United States
c Washington University School of Medicine, St. Louis, MO, USA
d Hope Center for Neurological Disorders, St. Louis, MO, USA
e Washington University, MO, Saint Louis, United States
f Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
g Washington University in St. Louis, MO, Saint Louis, United States
h Knight Alzheimer Disease Research Center, St. Louis, MO, USA
i Washington University in St. Louis School of Medicine, St. Louis, MO, USA
j NeuroGenomics and Informatics Center, St. Louis, MO, USA
k Washington University, St. Louis, MO, USA
Abstract
BACKGROUND: There are three main clinical presentations in Alzheimer disease (AD) with diversity in phenotype, onset and progression of clinical symptoms: autosomal dominant (ADAD), early onset (EOAD) and late onset (LOAD). Ultimately, AD is characterized by the deposition of Aβ and ptau protein aggregates in the brain. This work aims to identify and characterize common disrupted pathways across AD etiologies. METHOD: We examined bulk transcriptomic data from brain donors to the DIAN (ADAD, N=19) and Knight-ADRC (EOAD, N=13; LOAD, N=55; controls, N=16). We performed differential gene expression (DGE) analyses using DSeq2 and cross-checked significant signals with known GWAs loci. We replicated our findings in three AMP-AD independent studies. RESULT: DGE analysis identified 57 significantly differentiated genes across ADAD, EOAD or LOAD vs controls. Among those, AGFG2 (p=7×10-4 ) had a higher expression in cases and falls under the AD GWAs signal for NYAP1 (rs1476679). This effect replicated in all independent datasets: Mount Sinai (p=8.63×10-3 ), Mayo (p=5.88×10-12 ), ROSMAP (p=3.96×10-05 ). AGFG2 is expressed primarily in astrocytes and is a member of the HIV-1 Rev binding protein family that mediates the nucleocytoplasmic transfer of proteins and RNAs. AGFG2 has been implicated in APP metabolism, leading to the hypothesis that higher expression of AGFG2 could promote more release of APP to the media. CONCLUSION: Our results suggest that AGFG2 may be a novel player in the etiology of AD. We are currently modifying AGFG2 expression on iPSC-derived astrocytes using CRIPR-Cas9 technology to evaluate AGFG2 role in APP and Tau metabolism. We will present these results at the conference. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
LMNA-mediated nucleoskeleton dysregulation in Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054396.
Rosene, M.J.a , Wen, N.b , Li, Z.a , Brase, L.b , Hsu, S.b , Cruchaga, C.c d e f g , Temple, S.h , Harari, O.a d e i j , Karch, C.M.c d e i
a Washington University School of Medicine, St. Louis, MO, USA
b Washington University in St. Louis, St. Louis, MO, USA
c Washington University in St. Louis School of Medicine, St. Louis, MO, USA
d Hope Center for Neurological Disorders, St. Louis, MO, USA
e NeuroGenomics and Informatics Center, St. Louis, MO, USA
f Washington University, St. Louis, MO, USA
g Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
h Neural Stem Cell Institute, Albany, NY, USA
i Washington University, MO, Saint Louis, United States
j Knight Alzheimer Disease Research Center, St. Louis, MO, USA
Abstract
BACKGROUND: Nucleoskeleton dysfunction has been implicated in Alzheimer disease (AD). Tubular invaginations of the nuclear envelope observed in AD brains are consistent with the accumulation of farnesylated prelamin A (encoded by the LMNA gene) that occurs in Hutchinson-Gilford Progeria Syndrome, a premature aging disorder caused by LMNA mutations. Proper function of the nuclear membrane is required for neuronal survival and for maintenance of genetic architecture. METHOD: To determine whether dysregulated LMNA expression and prelamin A processing are responsible for nucleoskeleton dysfunction in AD, we performed differential gene expression and network analyses in human AD and age-matched control brains. Lamin A protein levels were evaluated in AD and control brains using mass spectrometry. Gene network analyses were carried out using induced pluripotent stem cell-derived neurons transduced with progerin or GFP controls in order to identify molecular pathways influenced by altered LMNA processing. RESULT: In AD brains, we observed a significant increase in LMNA and a significant decrease in ZMPSTE24, resulting in a significant increase Lamin A protein levels, which we observe through mass spectrometry. We replicated these findings in laser capture microdissected neurons from AD brains, suggesting that the effect is neuronally driven. Thus, high levels of LMNA paired with low levels of ZMPSTE24 could result in the accumulation of farnesylated prelamin A and tubular invaginations in the nuclear membrane. LMNA-associated networks were also differentially expressed in AD brains. Genes within the dysregulated LMNA network were enriched in lysosomal and chromatin remodeling pathways. CONCLUSION: Our findings suggest that β-amyloid and tau accumulation disrupts prelamin A processing and downstream changes in the nuclear membrane. Alterations in the nucleoskeleton induce genomic instability, loss of proteostasis, and cellular senescence, which may accelerate AD pathogenesis. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
COVID-19 and preclinical Alzheimer disease: Driving, mobility, activity and experiences of older adults in the United States
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e057692.
Bayat, S.a b , Babulal, G.M.c d , Widener, M.b , Schindler, S.E.c e , Morris, J.C.c d e , Mihailidis, A.a b , Roe, C.M.c d
a KITE – Toronto Rehabilitation Institute, ON, University Health Network, Toronto, Canada
b University of Toronto, ON, Toronto, Canada
c Washington University School of Medicine, St. Louis, MO, USA
d Knight Alzheimer Disease Research Center, St. Louis, MO, USA
e Hope Center for Neurological Disorders, St. Louis, MO, USA
Abstract
BACKGROUND: As the world grapples with the COVID-19 pandemic, there have been widespread disruptions to everyday life due to social distancing. Older adults with Alzheimer disease (AD) are at increased risk of morbidity and mortality from COVID-19. It is unknown how COVID-19 affects the mobility patterns of older adults with preclinical AD. Since before the pandemic, we have been monitoring the driving behaviors of older adults, enabling us to evaluate the impact of the pandemic on individuals with and without preclinical AD. METHOD: We used in-vehicle Global Positioning System (GPS) devices to study driving behaviors of 115 older adults enrolled in the DRIVES study (aged 65+) from 1/1/2019 to 31/12/2020. The cohort included 62 individuals with preclinical AD (PreAD) and 53 without preclinical AD (CTL), as determined by cerebrospinal fluid biomarkers. All participants completed an online survey about their overall experiences during the pandemic. Using the GPS data, we determined the average monthly distance travelled, and the number of visitations to destinations categorized as food shopping, place of worship, restaurant, leisure, or health. All measures were computed monthly. RESULT: oth groups experienced an approximate 40% decline in average monthly distance travelled overall after the start of the pandemic (PreAD: 1287.92 to 783.38 km vs. CTL: 1751.26 to 1053.29 km). Visits to places of worship, restaurants, leisure and health places declined by 70%, 46%, 23%, and 23% for the PreAD group, and by 48%, 31%, 48%, and 22% for the CTL group, respectively. However, the pandemic did not result in a significant decline in Food Shopping among either of the groups. Overall, compared to the CTL group, the PreAD group experienced a higher level of stress in response to the recommendations for socially distancing (p<0.01), more uncertainty about their risk of COVID-19 (p<0.05), more decline in trips for worship (p<0.05) and less decline in trips for leisure (p<0.01). CONCLUSION: Our findings indicate decreased mobility in all older adults during the pandemic, with the preclinical AD group exhibiting more decline in trips to places of worship, less decline in leisure activities, and increased stress and uncertainty in response to COVID-19. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Demographic and psychosocial factors associated with the decision to learn mutation status in familial frontotemporal dementia and the impact of disclosure on mood
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e050692.
Bajorek, L.P.a , Kiekhofer, R.a , Hall, M.a , Taylor, J.a , Lucente, D.E.b , Brushaber, D.c , Appleby, B.d , Coppolla, G.e , Bordelon, Y.M.f , Botha, H.c , Dickerson, B.C.b , Dickson, D.W.g , Domoto-Reilly, K.h , Fagan, A.M.i , Fields, J.A.c , Fong, J.C.j , Foroud, T.M.k , Forsberg, L.K.c , Galasko, D.R.l , Gavrilova, R.H.c , Geschwind, D.H.m , Ghoshal, N.n , Goldman, J.o , Graff-Radford, N.R.g , Graff-Radford, J.c , Grant, I.p , Grossman, M.q , Heuer, H.W.a , Hsiung, G.-Y.R.r , Huang, E.J.s , Huey, E.D.t , Irwin, D.J.u , Jones, D.T.c , Kantarci, K.c , Kornak, J.a , Kremers, W.K.c , Lapid, M.I.c , Leger, G.C.v , Litvan, I.v , Ljubenkov, P.A.a , Mackenzie, I.R.r , Masdeu, J.C.w , McMillan, C.q , Mendez, M.m , Miller, B.L.x , Miyagawa, T.c , Onyike, C.U.y , Pascual, B.w , Pedraza, O.g , Petrucelli, L.g , Rademakers, R.g , Ramos, E.M.m , Rankin, K.P.a , Rascovsky, K.q , Rexach, J.E.m , Ritter, A.z , Roberson, E.D.aa , Savica, R.c , Rojas, J.C.a , Seeley, W.W.ab , Tartaglia, M.C.ac , Toga, A.W.ad , Weintraub, S.ae , Wong, B.af , Wszolek, Z.g , Vandevrede, L.a , Boeve, B.F.c , Boxer, A.L.a , Rosen, H.J.a , Staffaroni, A.M.a , ALLFTD Consortiumag
a University of California, San Francisco, San Francisco, CA, USA
b Massachusetts General Hospital, MA, Boston, United States
c Mayo Clinic, MN, Rochester, United States
d Case Western Reserve University, Cleveland, OH, USA
e University of California, Los Angeles School of Medicine, Los Angeles, CA, USA
f University of California Los Angeles, Los Angeles, CA, USA
g Mayo Clinic, FL, Jacksonville, United States
h University of Washington, Seattle, WA, USA
i Washington University in St. Louis, St. Louis, MO, USA
j Baylor College of Medicine, TX, Houston, United States
k National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD), IN, Indianapolis, United States
l University of California, San Diego, La Jolla, CA, USA
m University of California, Los Angeles, Los Angeles, CA, USA
n Washington University School of Medicine, St. Louis, MO, USA
o Columbia University Medical Center, NY, NY, United States
p Northwestern University, Chicago, United States
q University of Pennsylvania, PA, Philadelphia, United States
r University of British Columbia, Vancouver, Canada
s Department of Pathology, University of California, San Francisco, San Francisco, CA, USA
t Columbia University, NY, NY, United States
u Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United States
v University of California, San Diego, San Diego, CA, USA
w Houston Methodist Neurological Institute, TX, Houston, United States
x University of California, San Francisco (UCSF), San Francisco, CA, USA
y Johns Hopkins University School of Medicine, MD, Baltimore, United States
z Cleveland Clinic Lou Ruvo Center for Brain Health, NV, Las Vegas, United States
aa University of Alabama at Birmingham, Birmingham, AL, USA
ab Weill Institute for Neurosciences and Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
ac University of Toronto, ON, Toronto, Canada
ad University of Southern California, Los Angeles, CA, USA
ae Northwestern University Feinberg School of Medicine, Chicago, United States
af Massachusetts General Hospital/Harvard Medical School, MA, Boston, United States
Abstract
BACKGROUND: Up to 30% of frontotemporal dementia (FTD) cases are due to known pathogenic mutations (f-FTD). Little is known about the factors that predict who will choose to learn their results. Upcoming clinical trials in f-FTD may require disclosure prior to enrollment, even before symptom onset, and thus characterizing this sample is important. Furthermore, understanding the mood impacts of genetic disclosure may guide genetic counseling practice. METHOD: F-FTD participants (n=568) from families with a known pathogenic mutation (MAPT, C9orf72, GRN) were enrolled through the ARTFL/LEFFTDS Longitudinal FTD Study (ALLFTD) and provided the opportunity for disclosure. Independent-sample t-tests compared demographic and psychosocial factors between participants who did and did not receive their results. In participants who were asymptomatic at baseline and follow up (n=199,177 with follow-up), linear mixed effects modeling was used to investigate pre- to post-disclosure changes in the 15-item Geriatric Depression Scale (GDS). RESULT: Of participants from families with a known pathogenic genetic mutation, 47% received genetic disclosure. Of the asymptomatic subset (n=386), 36% know their mutation status. Of these asymptomatic learners, 46% received disclosure through the study, and the remainder learned their genetic status prior to study enrollment. None of the analyzed demographic or psychosocial factors (i.e., sex, age, education, having children) differed between learners and non-learners (p’s > 0.05). In the longitudinal analysis of asymptomatic participants, learners showed a pre- to post-increase of 0.31 GDS points/year (95%CI: -0.08, 0.69, p = 0.12), whereas non-learners showed a slight decline (-0.15 points/year, 95%CI: -0.36, 0.06, p = 0.16). This difference between slopes was statistically significant (0.46, 95%CI: 0.02, 0.89, p=0.04) but represents a small clinical effect. In asymptomatic learners, slopes did not differ based on mutation status (0.28, 95%CI: -0.66, 1.20, p=0.55). Conclusions were based on the estimates and full range of confidence intervals. CONCLUSION: The majority of asymptomatic research participants do not know their genetic status, which will be a consideration for clinical trials that require disclosure. No considered demographic factors were strongly associated with the decision to receive disclosure. The findings suggest that disclosure in asymptomatic participants has minimal impact on depressive symptoms regardless of genetic results. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Identification of genetic modifiers for Alzheimer disease: The Familial Alzheimer Sequencing (FASe) project
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054224.
Neupane, A.a b , Budde, J.P.a b , Bergmann, K.a b , Norton, J.a b , Gentsch, J.a b , Wang, F.a b , Del-Aguila, J.L.a b , Ibanez, L.a b , Morris, J.C.c d , Goate, A.M.e f , Renton, A.E.e , Fernandez, V.a b , Cruchaga, C.b g
a Washington University School of Medicine, St. Louis, MO, USA
b Hope Center for Neurological Disorders, St. Louis, MO, USA
c Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
d Washington University in St. Louis, MO, Saint Louis, United States
e Ronald M. Loeb Center for Alzheimer’s disease, NY, NY, United States
f Icahn School of Medicine at Mount Sinai, NY, NY, United States
g Washington University, St. Louis, MO, USA
Abstract
BACKGROUND: The Familial Alzheimer Sequencing (FASe) project aims to identify rare and high penetrant variants that have strong effect in the etiology of Alzheimer Disease (AD) by using sequencing data from families densely affected by late onset AD (fLOAD). METHOD: We have generated whole genome sequence (WGS) data for 952 samples (758 cases, 194 controls) from the Knight-ADRC at Washington University (WASHU), the NIALOAD and NCRAD repositories. These samples are being added to our current dataset of whole exome (WES) and WGS from 1,235 non-Hispanic white participants (824 cases, 411 controls) across 285 fLOAD families. These samples have no or minimum overlap with the families sequenced by the ADSP consortia which will also be incorporated to our dataset; a total of 440 families and 3,187 samples (average of 5 cases and 2 controls per family) will be analyzed. We are processing all the data using the same bioinformatics pipeline. Briefly, sequence reads are aligned against reference build GRCh38 using BWA; variant calling is restricted to exonic regions following GATK v4.1.2 best practices. Data analysis includes single variant association, segregation, gene-based and pathway analysis. RESULT: We have detected a genetic cross-over between AD, Frontotemporal Dementia and Parkinson disease, and we also identified rare variants in novel candidate genes for AD (PLD3, UNC5C, CPAMD8) highlighting the power of our dataset and the feasibility of our approach. CONCLUSION: We hope to identify novel variants and pathways implicated on AD, which will be followed-up in the case-control ADSP. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Polygenic risk scores for Alzheimer’s disease predict MMSE decline in APOE4 carriers and noncarriers and the impact of sample overlap with GWAS summary statistics
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054622.
Cara, J.a , Collens, J.a , Zhang, H.a , Cruchaga, C.b c d , Hohman, T.J.e
a Vivid Genomics, San Diego, CA, USA
b Washington University in St. Louis School of Medicine, St. Louis, MO, USA
c Washington University, St. Louis, MO, USA
d Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
e Vanderbilt Genetics Institute, Vanderbilt University Medical Center, TN, Nashville, United States
Abstract
BACKGROUND: Heterogeneity in the progression of cognitive impairment, which is common in sporadic Alzheimer’s disease (AD) trials, is especially challenging to predict in pre-symptomatic populations, and has a negative impact on clinical trial power. Heritability of AD extends beyond the APOE genotype, with multiple common genetic variants identified in large genome wide association studies (GWAS). Incorporating APOE and additional genetic variants into models has the potential to improve the prediction of disease progression. The limited volume of genetic cohorts in AD and the sample overlap in GWAS summary statistics poses some concern for polygenic risk score (PRS) overfitting. METHOD: A PRS was calculated using genome-wide association study (GWAS) summary statistics for clinical AD diagnosis. PRS derived from this GWAS study was computed for participants drawn from two aging studies. Logistic regression models assessed the association between PRS and Mini Mental State Exam (MMSE) decline covarying for age, sex, education, APOE-ε4, and baseline MMSE score. Age and sex interactions with PRS were also assessed. Samples assumed to be used in the GWAS calculations were then removed from the test set and the impact to performance was analyzed. RESULT: Participants in the training and test set showed similar baseline ages, years of education and baseline MMSE scores in the whole sample and after stratification by APOE4 carrier status. The PRS model was a significant predictor of MMSE decline, as well as in APOE4 carriers and noncarriers. Model performance was compared to the test set excluding the GWAS overlap samples and no significant difference was observed. CONCLUSION: The proposed model including PRS explains heterogeneity in cognitive decline above and beyond the APOE4 allele. Testing the model in a dataset excluding GWAS overlap samples did not result in a significant difference in performance and potential overfitting does not appear to be an impact. Utilization of demographic and genomic factors beyond APOE in PRS models could enhance clinical trial recruitment and stratification strategies for trial analyses, such that APOE4 carriers are selected for probable cognitive decline, in addition to APOE3 carriers that are high on polygenic risk. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Impact of MAPT mutations on transcriptomic signatures of FTLD brains and patient-derived pluripotent cell models
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054570.
Minaya, M.a , Martinez, R.a , Seeley, W.W.b , Eteleeb, A.M.a , Cruchaga, C.c , Harari, O.a , Karch, C.M.a
a Washington University, MO, Saint Louis, United States
b Weill Institute for Neurosciences and Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
c Washington University, St. Louis, MO, USA
Abstract
BACKGROUND: Mutations in the microtubule-associated protein tau (MAPT) cause heterogeneous forms of frontotemporal lobar dementia with tau inclusions (FTLD-tau). Yet, the pathogenic events linked to disease remain poorly understood. This study was aimed at identifying genes and pathways that drive to FTLD-tau. METHOD: To identify the earliest genes and pathways that are dysregulated in FTLD-tau, we detected differentially expressed genes in RNA-seq data generated from induced pluripotent stem cell (iPSC)-derived cortical neurons carrying MAPT R406W, MAPT P301L, and MAPT IVS10+16 and isogenic, controls and 26 brain tissue samples (3 R406W carriers, 7 IVS10+16, 3 P301L, and 13 unrelated controls). We then identified pathological pathways and drug targets that were enriched among the differentially expressed genes. RESULT: We identified 61 genes that were differentially expressed in iPSC-derived cortical neurons from MAPT R406W carriers compared with isogenic, control neurons and replicated a subset of these genes in brain tissue from MAPT R406W carriers. We identified 15 genes that were differentially expressed in iPSC-derived cortical neurons from MAPT IVS10+16 carriers compared with isogenic, control neurons and replicated a subset of these genes in brain tissue from MAPT IVS10+16 carriers. We identified 37 genes that were differentially expressed in iPSC-derived cortical neurons from MAPT P301L carriers compared with isogenic, control neurons and replicated a subset of these genes in brain tissue from MAPT P301L carriers. Interestingly, there is little overlap among genes differentially expressed for MAPT R406W, MAPT P301L, and MAPT IVS10+16, which suggests that these mutations may lead to tau aggregation and neurodegeneration by different mechanisms. CONCLUSION: The results from this study demonstrate that iPSC-derived neurons capture molecular processes that occur in human brains and can be used to model disease. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Single nuclei RNA-sequencing of GWAS loci variant carriers elucidates cell-types and transcriptional profile alterations associated with Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054402.
Brase, L.a , Del-Aguila, J.L.b , You, S.-F.c , Soriano-Tarraga, C.a d , Farias, F.H.G.e f , Benitez, B.A.b d f g , Karch, C.M.d f h , Cruchaga, C.i j k , Harari, O.b d f g , Dominantly Inherited Alzheimer Networkl
a Washington University in St. Louis, St. Louis, MO, USA
b Washington University School of Medicine, St. Louis, MO, USA
c Washington University, St. Louis, MO, USA
d NeuroGenomics and Informatics Center, St. Louis, MO, USA
e Washington University in St. Louis, School of Medicine, St. Louis, MO, USA
f Hope Center for Neurological Disorders, St. Louis, MO, USA
g Knight Alzheimer Disease Research Center, St. Louis, MO, USA
h Washington University, MO, Saint Louis, United States
i Hope Center for Neurological Disorders, MO, Saint Louis, United States
j Washington University in St. Louis School of Medicine, St. Louis, MO, USA
k Knight Alzheimer Disease Center, MO, Saint Louis, United States
Abstract
BACKGROUND: AD has a substantial genetic, molecular and cellular heterogeneity associated with its etiology. We sought to investigate the glial and neuronal pathways affected by AD at a cell specific resolution. To do so, we generated single-nuclei RNA-seq (snRNA-seq) from the parietal cortex of Mendelian mutation carriers, sporadic AD and neuropath-free donors from the Knight-ADRC and Dominantly Inherited Alzheimer Network banks. METHOD: We generated snRNAseq (10X chemistry v3) for 18 APP and PSEN1 mutation carriers, 36 sporadic AD and 9 controls. After data cleaning and quality control, 336,892 nuclei remained for clustering and downstream analyses (Figure 1). Our analytical approach is based on the identification of cellular states (subclusters), their characterization and identification of genes associated with AD genetic strata. RESULT: We identified a myriad of transcriptional states for the most representative brain cell-types (Figure 1) with distinguishing expression profiles (mean of 600 genes overexpressed; FDR<0.05). We identified that neuronal and glial cells have specific transcriptional states enriched in nuclei from brains with APP and PSEN1 mutations. For example, an astrocyte cell state specific for these brains shows overexpression of genes identified in the Disease Associated Astrocytes (DAA) expression signature. We also noted a microglia cell state enriched for a subset of TREM2 variant carriers showing overexpression of genes related to cell migration and lamellipodium assembly. CONCLUSION: We developed a unique molecular atlas to study the pathways dysregulated in AD. Our analyses indicate that in the backdrop of neuropath free and even sporadic AD brains, ADAD samples have distinctive cell states and altered pathways in neurons and glia. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Heritability analyses show partial genetic overlap between (non-Mendelian) early and late onset Alzheimer disease due to an intriguing APOE effect
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e056143.
da Fonseca, E.L.a , Jean-Francois, M.N.a , Kurup, J.T.b , Slifer, S.H.a , Martin, E.R.a , Kunkle, B.W.a , Schellenberg, G.D.c , Pericak-Vance, M.A.a , Fernandez, V.d , Cruchaga, C.e , Reitz, C.b , Beecham, G.W.a
a University of Miami, Miller School of Medicine, John P. Hussman Institute for Human Genomics, FL, Miami, United States
b Columbia University, Departments of Neurology and Epidemiology, NY, NY, United States
c University of Pennsylvania Perelman School of Medicine, Path & Lab Med, PA, Philadelphia, United States
d Washington University School of Medicine, St. Louis, MO, USA
e Washington University in St. Louis School of Medicine, St. Louis, MO, USA
Abstract
BACKGROUND: Alzheimer disease (AD) is a degenerative brain disease, being the most common cause of progressive dementia and listed as the sixth leading cause of mortality in the USA. It is often described as either early onset (EOAD, age at onset, [AAO] <= 65) or late onset (LOAD, [AAO]>65). Non-Mendelian EOAD (not monogenic; nmEOAD) has irregular inheritance patterns and fluctuating AAO, characteristics also present in LOAD cases. There is still a lack of evidence in the literature depicting the similarities (if any) between nmEOAD and LOAD forms, being unclear how much genetic etiology is shared by the two forms of AD. To shed light to this question, a genome-wide association study (GWAS) and heritability analyses of nmEOAD and LOAD were performed. METHOD: Genetic data on 21,622 individuals from the Alzheimer Disease Genetics Consortium (ADGC) were used: (1,476 nmEOAD, 9,695 LOAD and 10,451 control). Single-variant association analyses were performed using logistic regression under two models: (1) ancestry plus SNP, and (2) ancestry, sex, APOE dosage, and SNP. nmEOAD and LOAD were considered separately. LD score regression was used to estimate the SNP heritability (h2 ) and genetic correlation (rg), considering two additional models: (3) ancestry, sex, and SNP and (4) ancestry, APOE dosage and SNP. RESULT: Several known candidate genes confirmed for LOAD along with novel regions associated with immune and cell-signaling pathways in nmEOAD models. Gene based tests showed significant association for APOE gene (Chr19): nmEOAD (p=3.89×10-16 and p=4.29×10-12 ) and LOAD (p=1.07×10-65 and p=1.12×10-14 ), models (1) and (2) respectively. Heritability analyses showed higher h2 values for EOAD (h2 =0.24, 0.23, 0.25 and 0.24) than LOAD (h2 =0.18, 0.14, 0.18, and 0.14) for models (1) to (4) respectively. Genetic correlation showed moderate genetic overlap between EOAD and LOAD only for models: (2) rg=0.35 (p=0.0283) and (4) rg=0.34 (p=0.0261). CONCLUSION: GWAS and heritability analysis suggest that the genetic etiology of EOAD has a noncomplete genetic overlap with LOAD, with a moderate overlap when APOE dosage is modeled and a minimal overlap otherwise (APOE effect). The results also suggest a stronger polygenic effect in EOAD than LOAD, confirming the need for additional genomics efforts in nmEOAD. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Body mass index predicts lower connectivity in associational fibers of the temporal lobe in older men
(2021) Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 17, p. e052902.
Rahmani, F.a , Raji, C.A.b , Benzinger, T.L.S.a c d
a Mallinckrodt Institute of Radiology, MO, Saint Louis, United States
b Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA
c Washington University in St. Louis School of Medicine, St. Louis, MO, USA
d Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
Abstract
BACKGROUND: Increased body mass index (BMI) is related to changes in white matter (WM) connectivity1 . We investigated whether WM connectivity patterns as a function of BMI varies across sex differences. METHOD: We enrolled 289 individuals (58 CDR=0 & 231 CDR=0.5) from the Knight Alzheimer Disease Research Center (ADRC) (Table 1). Participants were included if they had a physical evaluation within 12 months of a diffusion MRI scan and excluded if they had clinical dementia. Connectome analyses were performed using the DSI Studio software (http://dsi-studio.labsolver.org/). Diffusion data were reconstructed in the MNI space using q-space diffeomorphic reconstruction (QSDR)2 . The quantitative anisotropy was extracted as the local connectome fingerprint. A multi-regression model were used to derive the correlation and a false discovery rate threshold of 0.05 was adopted to select tracts using a deterministic fiber tracking algorithm. RESULT: A positive association between connectivity in the left arcuate fasciculus (AF) and the left middle cerebellar peduncle in men did not survive regression for age (Figure 1-A). Men also showed a statistically significant negative association between connectivity in the bilateral inferior longitudinal fasciculi (ILF), right inferior fronto-occipital fasciculus (IFOF), the frontoparietal and parahippocampal parts of the right cingulum, the tapetum part of the corpus callosum (CC), right fornix and right corticospinal, corticostriatal, and corticopontine tracts. All of these relationships persisted when co-varying for age (Figure 1-B). Results in women revealed a significant positive correlation between connectivity of the right IFOF, right superior longitudinal fasciculus (SLF), right corticopontine, corticospinal tracts, bilateral reticulospinal tracts, and left arcuate fasciculus (AF) (Figure 2-A) even when controlling for age. Connectivity in the bilateral ILF, right IFOF and the tapetum part of the CC showed an inverse correlation with BMI in women (Figure 2-B). CONCLUSION: Increased BMI is related to lower structural connectivity in important associational WM fibers of the temporal lobe, particularly in older men. References: (1) Gupta A, Mayer EA, Sanmiguel CP, et al. Patterns of brain structural connectivity differentiate normal weight from overweight subjects. NeuroImage Clin. 2015;7:506-517. (2) Yeh F-C, Wedeen VJ, Tseng W-YI. Estimation of fiber orientation and spin density distribution by diffusion deconvolution. Neuroimage. 2011;55(3):1054-1062. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Stem cell models of primary tauopathies reveal defects in synaptic function
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054566.
Martinez, R.a , Jiang, S.b , Marsh, J.c , Harari, O.d , Cruchaga, C.e , Goate, A.M.f , Temple, S.g , Karch, C.M.a , Tau Consortium Stem Cell Grouph
a Washington University, Saint Louis, St. Louis, MO, USA
b Washington University School of Medicine, MO, Saint Louis, United States
c Washington University in St. Louis, St. Louis, MO, USA
d Washington University School of Medicine, St. Louis, MO, USA
e Washington University, St. Louis, St. Louis, MO, USA
f Icahn School of Medicine at Mount Sinai, NY, NY, United States
g Neural Stem Cell Institute, Albany, NY, USA
Abstract
BACKGROUND: Primary tauopathies are characterized neuropathologically by inclusions containing abnormal forms of the microtubule-associated protein tau (MAPT) and clinically by diverse neuropsychiatric, cognitive, and motor impairments. Autosomal dominant mutations in the MAPT gene cause heterogeneous forms of frontotemporal lobar degeneration with tauopathy (FTLD-Tau). Common and rare variants in the MAPT gene increase the risk for sporadic FTLD-Tau, including progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). METHOD: We generated a collection of fibroblasts from 140 MAPT mutation/risk variant carriers, PSP, CBD, and cognitively normal controls; 31 induced pluripotent stem cell (iPSC) lines from MAPT mutation carriers, non-carrier family members, and autopsy-confirmed PSP patients; 33 genome engineered iPSCs that were corrected or mutagenized; and forebrain neural progenitor cells (NPCs). RESULT: To begin to identify the genes and pathways that are dysregulated in primary tauopathies, we performed transcriptomic analyses in induced pluripotent stem cell (iPSC)-derived neurons carrying MAPT p.R406W and CRISPR/Cas9-corrected isogenic controls. We found that the expression of the MAPT p.R406W mutation was sufficient to create a significantly different transcriptomic profile compared with that of the isogeneic controls and to cause the differential expression of 328 genes. Sixty-one of these genes were also differentially expressed between MAPT p.R406W carriers and control brains. Twelve of these genes are also differentially expressed between PSP and control brains. Together, these genes are enriched for pathways involved in GABA-mediated signaling and synaptic function, which may contribute to the pathogenesis of FTLD-tau and other primary tauopathies. CONCLUSION: Here, we present a resource of fibroblasts, iPSCs, and NPCs with comprehensive clinical histories that can be accessed by the scientific community for disease modeling and development of novel therapeutics for tauopathies. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Exome sequencing identifies rare damaging variants in the ATB8B4 and ABCA1 genes as novel risk factors for Alzheimer’s disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e055982.
Holstege, H.a , Hulsman, M.a , Charbonnier, C.b , Grenier-Boley, B.c , Quenez, O.d , Grozeva, D.e , van Rooij, J.G.J.f , Sims, R.e , Ahmad, S.f , Amin, N.g , Norsworthy, P.h , Dols-Icardo, O.i , Hummerich, H.h , Kawalia, A.j , Amouyel, P.c , Beecham, G.W.k , Berr, C.l , Bis, J.C.m , Boland, A.n , Bossù, P.o , Bouwman, F.H.p , Bras, J.q , Campion, D.b , Cochran, J.N.r , Daniele, A.s , Dartigues, J.-F.t , Debette, S.t , Deleuze, J.-F.n , Denning, N.e , Destefano, A.L.u , Farrer, L.A.u , Fernandez, V.v , Fox, N.C.h , Galimberti, D.w , Génin, E.x , Gille, H.a , Guen, Y.L.y , Guerreiro, R.q , Haines, J.L.z , Holmes, C.aa , Ikram, M.A.f , Ikram, M.K.f , Jansen, I.E.a , Kraaij, R.f , Lathrop, M.ab , Lemstra, A.W.a , Lleó, A.ac , Luckcuck, L.e , Marshall, R.e , Martin, E.R.ad , Masullo, C.ae , Mayeux, R.af , Mecocci, P.ag , Meggy, A.e , Mol, M.O.f , Morgan, K.ah , Myers, R.M.r , Nacmias, B.ai , Naj, A.C.aj , Napolioni, V.y , Pastor, P.ak , Pericak-Vance, M.A.k , Raybould, R.e , Redon, R.al , Reinders, M.J.am , Richard, A.-C.b , Riedel-Heller, S.G.an , Rivadeneira, F.f , Rousseau, S.b , Ryan, N.S.h , Saad, S.e , Sanchez-Juan, P.ao , Schellenberg, G.D.aj , Scheltens, P.a , Schott, J.M.h , Seripa, D.ap , Sie, D.a , Sistermans, E.a , Sorbi, S.ai , van Spaendonk, R.M.L.a , Spalletta, G.o , Tesi, N.a , Tijms, B.M.a , Van Der Lee, S.J.a , Uitterlinden, A.G.f , Visser, P.J.a , Wagner, M.aq , Wallon, D.d , Wang, L.-S.aj , Zarea, A.d , Clarimón, J.ac , van Swieten, J.C.f , Hardy, J.h , Greicius, M.D.y , Ramirez, A.j , Mead, S.h , Yokoyama, J.S.ar , van der Flier, W.M.a , Cruchaga, C.v , Van Duijn, C.M.g , Williams, J.e , Nicolas, G.d , Bellenguez, C.c , Lambert, J.-C.c
a Amsterdam, Netherlands
b Inserm U1079 / Rouen University, Rouen, France
c Inserm, Institut Pasteur de Lille, Lille, France
d Inserm U1245 / Rouen University Hospital, Rouen, France
e Cardiff University, Cardiff, United Kingdom
f Erasmus MC, Rotterdam, Netherlands
g University of Oxford, Oxford, United Kingdom
h University College London, London, United Kingdom
i Universitat Autònoma de Barcelona, Barcelona, Spain
j University of Bonn, Bonn, Germany
k University of Miami, FL, Miami, United States
l University of Montpellier, Montpellier, France
m University of Washington, Seattle, WA, USA
n Centre National de Génotypage, Institut de Génomique / CEA, Evry, France
o IRCCS Santa Lucia Foundation, Rome, Italy
p Alzheimer Center Amsterdam, Amsterdam, Netherlands
q Van Andel Institute, Grand Rapids, MI, United States
r HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
s Università Cattolica del Sacro Cuore, Rome, Italy
t Bordeaux University Hospital, Bordeaux, France
u Boston University, MA, Boston, United States
v Washington University, St. Louis, MO, USA
w University of Milan, Milan, Italy
x Université Bretagne OccidentaleBrest, France
y Stanford University, Stanford, CA, USA
z Case Western Reserve University School of Medicine, Cleveland, OH, USA
aa University of SouthamptonSouthampton, United Kingdom
ab McGill University and Génome Québec Innovation Centre, QC, Montréal, Canada
ac Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
ad University of Miami Miller School of Medicine, FL, Miami, United States
ae Universitario A. Gemelli, Rome, Italy
af Columbia University, NY, NY, United States
ag University of Perugia, Perugia, Italy
ah University of Nottingham, Nottingham, United Kingdom
ai University of Florence, Florence, Italy
aj University of Pennsylvania, PA, Philadelphia, United States
ak Universidad de Navarra, Pamplona, Spain
al CNRS UMR 6291 / Université de Nantes, Nantes, France
am Delft University of Technology, Delft, Netherlands
an University of Leipzig, Leipzig, Germany
ao CIBERNEDMadrid, Spain
ap IRCCS Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
aq University Hospital Bonn, Bonn, Germany
ar University of California, San Francisco, San Francisco, CA, USA
Abstract
BACKGROUND: Damaging rare variants in the TREM2, SORL1 and ABCA7 genes have been associated with an increased risk of developing Alzheimer’s Disease (AD) with odds ratios that were not observed since the identification of the main AD genetic risk factor, the APOE-ε4 allele. Here, we aimed to identify additional AD-associated genes by investigating the burden of rare damaging variants in the exomes of AD cases and controls. METHOD: On a single server, we analyzed in two stages, the data from 52,270 exome sequences from several independent datasets from Europe and the United States. After comprehensive QC, Stage-1 and Stage-2 datasets comprised in total 16,396 AD cases (5,672 EOAD) and 18,107 controls with European ancestry. All detected non-synonymous and loss-of-function rare variants were prioritized by REVEL and LOFTEE, and analyzed in a per-gene burden analysis. After a Stage-1 discovery analysis, we replicated findings in an independent dataset (Stage-2). We combined the Stage-1 and Stage-2 datasets and determined, for each gene, the features of the variants that drive the burden-associations. RESULTS: We confirmed the AD-association of rare damaging variants SORL1, TREM2, ABCA7, and newly identified a significant AD-association of rare damaging variants in the ATP8B4 and ABCA1 genes. In addition, we find a strong indication for the AD-association of ADAM10 and SRC genes (Stage-2 p<0.05). For most genes, we observed a larger effect size for LOF variants compared to missense variants (Figure-A). High-impact variants in these genes are mostly extremely rare and enriched in AD patients with early ages at onset (Figure-B). CONCLUSION: We identified, for the first time, the AD-association of rare damaging variants in two genes: (i) microglial ATP8B4 which is involved in phospholipid transport, and (ii) ABCA1 which plays a critical role in lipidation of apoE thereby supporting Aβ processing. Further, we found strong evidence for the AD-association of damaging variants in ADAM10 and SRC genes. ADAM10 is involved in the proteolytic processing of APP, while SRC is a Non-Receptor Tyrosine Kinase which binds PTK2B/Pyk2, a known AD risk factor. Together, our study provides further evidence for the role of Aβ and microglia in AD pathophysiology. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Profiling the metabolic landscape of AD
(2021) Alzheimer’s & Dementia : The Journal of the Alzheimer’s Association, 17, p. e050086.
Novotny, B.C.a , Fernandez, V.a b , Budde, J.P.a b , Bergmann, K.a b , Morris, J.C.c d e , Bateman, R.J.a b f , Karch, C.M.b g , Benitez, B.A.a b , Cruchaga, C.b e h , Harari, O.a b , Dominantly Inherited Alzheimer Networki
a Washington University School of Medicine, St. Louis, MO, USA
b Hope Center for Neurological Disorders, St. Louis, MO, USA
c Washington University in St. Louis, St. Louis, MO, USA
d Hope Center for Neurological Disorders, MO, Saint Louis, United States
e Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
f Knight Alzheimer Disease Research Center, St. Louis, MO, USA
g Washington University, MO, Saint Louis, United States
h Washington University, St. Louis, MO, USA
Abstract
BACKGROUND: Metabolic dysfunction, including perturbations in lipid, neurotransmitter, and polyamine metabolism, is an early indicator of cognitive impairment and Alzheimer disease (AD) risk. Further investigation is needed to elucidate the role of genetic heterogeneity in these metabolic disturbances. Here, we interrogate metabolomic signatures in the brains of carriers of pathological mutations in APP, PSEN1, and PSEN2 (Autosomal Dominant AD; ADAD), risk variants in TREM2, non-carrier sporadic AD cases (sAD), individuals with neuropathology but without clinical symptoms (Presymptomatic), and neuropathology-free controls (CO). METHOD: Metabolomic data from parietal brain tissue of donors to the Knight Alzheimer Disease Research Center and the Dominantly Inherited Alzheimer Network (ADAD, n=25; TREM2, n=21; sAD, n=305; Presymptomatic, n=15; CO, n=27) were generated using the Metabolon global metabolomics platform. A total of 627 metabolites passed our QC process. Differential abundance between AD strata and controls was tested using linear regression corrected for sex, age, and post-mortem interval. Age was excluded from ADAD models. Benjamini-Hochberg multiple testing correction was applied, and pathway analysis was performed with MetaboAnalyst and IMPaLA. RESULT: In total, we identified 138 metabolites associated with distinct genetic strata (FDR q-value<0.05). For sAD, these included tryptophan betaine (β=-0.55) and N-acetylputrescine (β=-0.14). Metabolites associated with both sAD and ADAD were ergothioneine (β=-0.22 and -0.26 respectively) and serotonin (β=-0.34 and -0.57). TREM2 and ADAD showed association with α-tocopherol (β=-0.12 and -0.12). β-citrylglutamate abundance decreased in sAD, ADAD, and TREM2 versus controls (β=-0.14; -0.22; and -0.29). Pathways identified included glutamate, vitamin, and antioxidant metabolism. A 16-metabolite subset showed consistent direction of effect among the genetic strata with the magnitude of effect of ADAD greater than that of TREM2, in turn greater than sAD. A representation of these (eigengene) is associated with disease duration in sAD (p=5.65×10-03 ), possibly driven by tau accumulation. Hierarchical clustering identified 41 “early stage” sAD individuals with Braak tau stage similar to Presymptomatic (p=0.35), but lower than other sAD individuals (β=-0.56, p=3.09×10-04 ) (Figure 1). CONCLUSION: Our findings suggest distinct and characteristic metabolic perturbations in ADAD and TREM2 brains. Investigation of these differentially abundant metabolites may lead to greater insight into the metabolic etiology of AD and its impact on clinical presentation. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
TREM2-independent neuroprotection is mediated by monocyte-derived macrophages in a mouse model of Alzheimer’s disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e052775.
Dvir-Szternfeld, R.a , Castellani, G.a , Arad, M.a , Cahalon, L.a , Colaiuta, S.P.a , Keren-Shaul, H.a , Croese, T.a , Ulland, T.K.b , Colonna, M.b , Weiner, A.a , Amit, I.a , Schwartz, M.a
a Weizmann Institute of Science, Rehovot, Israel
b Washington University in St. Louis, St. Louis, MO, USA
Abstract
BACKGROUND: The relative contributions of microglia and infiltrating monocyte-derived macrophages (MDMs) to containing Alzheimer’s disease (AD) are not fully understood. In the 5xFAD animal model of amyloidosis, disease-associated microglia (DAM) expressing the Triggering receptor expressed on myeloid cells 2 (TREM2), are found in close proximity to amyloid beta (Aβ) plaques. Deletion of TREM2 results in the absence of DAM and in an increased Aβ-plaque load. However, the necessity of TREM2 and DAM for resolving AD pathology is still debatable. METHOD: Here, we activated systemic immunity by blocking the programmed cell death protein 1 / ligand (PD-1/PD-L1) pathway in TREM2-/- and TREM2+/+ 5xFAD mice, to decipher the roles of the different myeloid populations in mitigating AD pathology. RESULT: We found that anti-PD-L1 treatment resulted in cognitive improvement in TREM2-/- and TREM2+/+ 5xFAD mice. In addition, in both TREM2-/- 5xFAD and TREM2+/+ 5xFAD, the treatment resulted in a reduction in water soluble-Aβ, while reduction of insoluble-Aβ was observed only in TREM2+/+ 5xFAD mice. Eliminating monocytes using anti-CCR2 antibody fully abrogated the observed effects of anti-PD-L1 treatment in TREM-/- 5xFAD mice, and partially eliminated the effects in the TREM2+/+ 5xFAD. Single-cell RNA-seq of myeloid cells isolated from TREM2-/- 5xFAD brains revealed that MDMs express unique scavenger receptors, previously linked to soluble-Aβ removal, such as Macrophage scavenger receptor 1 (MSR1). CONCLUSION: Overall, our findings highlight a novel TREM2-independent pathway by which cognitive improvement and removal of soluble-Aβ are achieved in an amyloidosis model. Thus, our results support the potential of MDM-harnessing immunotherapy in treating AD patients, irrespective of whether they carry a TREM2 mutation. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
A large-scale, whole genome sequencing study of unexplained early-onset Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e056664.
Beecham, G.W.a , Fonseca, E.L.b , Kurup, J.T.c , Pericak-Vance, M.A.a d , Martin, E.R.d , Schellenberg, G.D.e , Fernandez, V.f , Cruchaga, C.f , Reitz, C.g
a Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, FL, Miami, United States
b University of Miami, Miller School of Medicine, John P. Hussman Institute for Human Genomics, FL, Miami, United States
c Columbia University, Departments of Neurology and Epidemiology, NY, NY, United States
d John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, FL, Miami, United States
e University of Pennsylvania Perelman School of Medicine, PA, Philadelphia, United States
f Washington University, St. Louis, MO, USA
g Columbia University Medical Center, NY, NY, United States
Abstract
BACKGROUND: Genomic studies of Alzheimer disease (AD) have primarily focused on non-Hispanic White (NHW) participants affected by the late-onset form (LOAD; onset age: >65), or the study of early onset AD (EOAD; onset age <=65) cases showing Mendelian inheritance patterns associated with mutations in the APP, PSEN1 and PSEN2 genes. However, mutations in these three genes explain ∼10% of EOAD cases. There are no large-scale efforts to collect and study EOAD cases not explained by these genes, despite this unexplained category accounting for ∼90% of EOAD cases. METHOD: To address this, we aim to identify additional EOAD-associated variants, genes and pathways through a large-scale whole-genome sequencing (WGS) study of unexplained EOAD. We will include cases from several AD cohorts, including the Resource for Early-onset Alzheimer Disease Research (READR), the Knight-ADRC at Washington University, the Alzheimer’s Disease Genetics Consortium (ADGC), and others. Generating and harmonizing a dataset of 200 non-Hispanic White (NHW) and Caribbean Hispanic (CH) multiplex EOAD families, over 5,400 EOAD singletons and over 13,000 unrelated, cognitive controls, all with WGS, this project will yield the largest EOAD genomics dataset to-date, improving statistical power for variant identification and allowing us to assess the impact of specific factors such as APOE genotype, vascular risk factors, and neuropsychiatric comorbidities. The inclusion of a large set of Hispanic families and singletons allows the examination of EOAD risk in a significantly understudied population. Analyses will comprise both linkage and association-based approaches, analyses of polygenic and ancestry effects, and a thorough examination of neurocognitive, neuropsychiatric and cardiovascular endophenotypes. RESULT: When completed this study will point to novel genetic contributors to EOAD, shed light on the mechanisms of AD and facilitate the development of novel prediction models and therapeutics. CONCLUSION: Sampling, phenotyping and sequencing analysis protocols will be complementary to and compatible with the existing LOAD genomics resources, such as the Alzheimer Disease Sequencing Project (ADSP) and related studies. This phenotypic and genomic consistency, together with the use of existing AD infrastructure (NIAGADS), allows for immediate integration with the leading efforts on LOAD, enabling rapid large-scale investigation of a variety of additional critical AD genomics hypotheses. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Defective proteostasis in patient-derived iPSC astrocytes and neurons carrying a MAPT IVS10+16 mutation
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054448.
Mahali, S.a , Martinez, R.b , Hu, M.a , Marsh, J.a , Temple, S.c , Karch, C.M.a d
a Washington University in St. Louis, St. Louis, MO, USA
b Washington University, Saint Louis, St. Louis, MO, USA
c Neural Stem Cell Institute, Albany, NY, USA
d Hope Center for Neurological Disorders, St. Louis, MO, USA
Abstract
BACKGROUND: Impaired proteostasis is associated with normal aging and is accelerated in neurodegeneration. This impairment may lead to the toxic accumulation of protein. In a subset of frontotemporal dementia (FTD) cases, mutations in the microtubule-associated protein tau (MAPT) that alter the relative levels of tau isoforms are sufficient to cause tau inclusions in neurons and astroglia and neurodegeneration without the presence of mutated protein (e.g. MAPTIVS10+16). However, the pathogenic events triggered by the expression of the alternatively spliced tau remain poorly understood. METHOD: To determine whether altered tau splicing induced from MAPT IVS10+16 mutations is sufficient to alter proteostasis in neurons and glia, we used human induced pluripotent stem cell (iPSC)-derived neurons and astrocytes from patients carrying the MAPT IVS10+16 mutation and CRISPR/Cas9, isogenic corrected controls. RESULT: We found that neurons from MAPT IVS10+16 carriers exhibited significantly higher levels of tau containing 4 microtubule binding repeats (4R tau), deficits in lysosomal trafficking, and acidity relative to isogenic-control neurons. Conversely, astrocytes from MAPT IVS10+16 carriers exhibited morphologically an increase in acidic lysosomes compared to isogenic-control astrocytes. Astrocytes from MAPT IVS10+16 carriers were also larger in size, consistent with cellular hypertrophy observed in brains from FTD-tau patients. CONCLUSION: Our findings suggest that altered tau splicing induced by the MAPT IVS10+16 mutation is sufficient to cause impaired lysosomal function and altered proteostasis in a cell-type specific manner. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
DNAJC5 affects the endo-lysosomal pathway, APP processing, and AD pathology in vitro and in vivo
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054177.
Nykanen, N.a , Wang, Z.a b , Davis, T.A.c , Nunez, M.d , O’Dell, K.d , Cirrito, J.R.c , Sands, M.d , Benitez, B.A.e f g h i
a NeuroGenomics and Informatic Center, MO, Saint Louis, United States
b Washington University in Saint Louis, MO, Saint Louis, United States
c Washington University School of Medicine, MO, Saint Louis, United States
d Washington University in Saint Louis, St. Louis, MO, USA
e Hope Center for Neurological Disorders, St. Louis, MO, USA
f Washington University School of Medicine, St. Louis, MO, USA
g Washington University in St. Louis, St. Louis, MO, USA
h NeuroGenomics and Informatics Center, St. Louis, MO, USA
i Knight Alzheimer Disease Research Center, St. Louis, MO, USA
Abstract
BACKGROUND: The DnaJ heat shock protein family member C5 (DNAJC5) gene encodes Cysteine String Protein-alpha (CSPα). CSPα is a key endo-lysosomal element of the misfolding-associated protein secretion (MAPS) machinery. MAPS eliminates misfolded cytosolic proteins, including alpha-synuclein, tau, TDP-43, huntingtin. Mutations in the DNAJC5 gene cause rare early-onset dementia called adult-onset Neuronal ceroid lipofuscinosis (ANCL). Data from CSPα-deficient mice and flies suggest that CSPα is critical for preventing age-dependent neurodegeneration. The endo-lysosome plays an essential role in normal and abnormal Amyloid-beta precursor protein (APP) processing and subsequent β-amyloidogenesis in Alzheimer’s disease (AD). However, the role of CSPα in APP processing, trafficking, and amyloidogenesis is not well understood. METHODS: We used histological staining and whole transcriptome data from ANCL, AD patients, and age-matched pathology-free controls. Differential expression (DE) analysis was performed using DESeq2 software. We performed histological analysis of 5XFAD mouse models crossed with DNAJC5 mice. We used mouse neuroblastoma (N2A) cells stably expressing wild-type human APP695 (N2A695) and human wild-type (WT) and mutant DNAJC5. We used ELISA to quantify Aβ40 and Aβ42 in cell culture media and human brain lysates. RESULTS: CSPα co-localizes with endo-lysosomal and synaptic markers in N2A695 cells. CSPα overexpression affects lysosomal function and SNAP29-mediated exocytosis. Overexpression and knockdown of hCSPα-WT in N2A695 cells significantly affect extracellular Aβ40, Aβ42, full-length APP, and APP C-terminal fragments (CTF). N2A-APP cells expressing a gain-of-function DNAJC5 mutant displayed a significant increase in lysosomal and autophagy (LC3-II and p62) proteins, lysosomal exocytosis, and secreted levels of Aβ40 and Aβ42. ANCL brains showed considerable neuronal Aβ accumulation. ANCL brains exhibit a significant reduction of soluble and insoluble Aβ4 and Aβ42. Transcriptome analysis from ANCL brains shows changes in the mTOR pathway. DNAJC5 transcript levels are significantly reduced in AD cases compared to controls. A mouse AD model exhibits an inverse correlation between DNAJC5 transcript levels and Aβ plaques. 5XFAD mice haploinsufficient for DNAJC5 gene significantly increased the Aβ plaque burden and decreased Aβ plaque latency. CONCLUSIONS: Our results provide evidence of the novel and unexpected role of CSPα in endo-lysosomal function, lysosomal exocytosis, β-amyloidogenesis both in vitro and in vivo. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Genome-wide DNA methylation analysis of autosomal dominantly inherited and sporadic Alzheimer disease brains
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e053502.
Soriano-Tarraga, C.a b , Farias, F.H.G.a c , Budde, J.P.c d , Ebl, C.a , Norton, J.a c , Gentsch, J.c d e , Morris, J.C.a f g , Bateman, R.J.c h i j , Swisher, L.h , McDade, E.a e , Perrin, R.J.c e h , Cruchaga, C.b c g h , Harari, O.b c e i
a Washington University in St. Louis, St. Louis, MO, USA
b NeuroGenomics and Informatics Center, St. Louis, MO, USA
c Hope Center for Neurological Disorders, St. Louis, MO, USA
d Washington University School of Medicine, St. Louis, MO, USA
e Knight Alzheimer Disease Research Center, St. Louis, MO, USA
f Hope Center for Neurological Disorders, MO, Saint Louis, United States
g Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
h Washington University in St. Louis School of Medicine, St. Louis, MO, USA
i Washington University, MO, Saint Louis, United States
j Knight Alzheimer’s Disease Research Center, St. Louis, MO, USA
Abstract
BACKGROUND: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder with many biological processes, and molecular changes. The etiology of AD is complex and not specific to a single genetic factor. Epigenetic changes could help explain the missing heritability not capture in GWAS chips and determine functional variants in genome-wide significant loci. METHOD: Our discovery cohort includes 460 post-mortem brains, 452 AD and 25 controls from Knight-ADRC and Dominantly Inherited Alzheimer Network cohorts. Our study included late-onset (LOAD), but also subjects with Mendelian mutations in APP, PSEN1 and PSEN2 genes (Autosomal Dominant AD; ADAD) and controls. We performed a genome-wide methylation study using DNA from parietal cortex. We used Infinium MethylationEPIC Beadchip arrays (Illumina) to measure DNA methylation. All statistical analyses were adjusted for sex, age at death and neuron proportion. RESULT: Completion of this project will provide an enhanced characterization of the epigenetic factors associated with AD etiology. This study will enhance the understanding of the molecular dynamics underlying the pathophysiology of AD, and may lead to novel clues for its early detection, prevention and treatment. CONCLUSION: Epigenetics of AD brains have been previously studied, but this is the first study to analyze both LOAD and ADAD. These results will be presented in the conference. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Evidence that the gut microbiota regulates progression of neurodegeneration in a mouse model of tauopathy, in a sex- and ApoE isoform-dependent manner
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e049741.
Seo, D.-O.a , Stanley, J.G.a , Shi, Y.a , Wang, C.b , Serrano, J.R.a , Bao, X.a , O’Donnell, D.a , Lelwala-Guruge, J.a , Griffin, N.a , Meier, M.a , Dodiya, H.B.c , Sisodia, S.S.c , Gordon, J.I.a , Holtzman, D.M.a
a Washington University in St. Louis, St. Louis, MO, USA
b Washington University in St. Louis, School of Medicine, St. Louis, MO, USA
c University of Chicago, Chicago, United States
Abstract
BACKGROUND: Alzheimer’s disease (AD) is a fatal progressive neurodegenerative disease. Mounting evidence supports that an unbalanced gut microbiota (GM) is linked to amyloid-β deposition potentially by disrupting neuroinflammation and metabolic homeostasis. However, the contribution of the GM to tau-mediated neurodegeneration is poorly characterized. Furthermore, recent studies have reported that the configuration of the GM is also affected by ApoE isoforms, which is the strongest genetic risk factor for late-onset AD. Here, we explore the hypothesis that the GM regulates tau-mediated neurodegeneration in a sex- and ApoE isoform- dependent manner, using a mouse model of tauopathy. METHOD: Male and female P301S tau transgenic mice were crossed with human ApoE knock-in mice (ApoE3 or ApoE4) or ApoE knockout mice (EKO) to generate P301S::ApoE3/E3, ApoE4/E4, or P301S/EKO mice, termed TE3F, TE4F, and TEKO, respectively. The GM in each group was perturbed by gastric gavage of a combination of antibiotics (ABX) from post-natal day 16-22; controls were gavaged with water (H2O). Mice were housed in a specific pathogen-free facility and fed a standard mouse chow diet ad libitum until they were euthanized at 9 months of age. In addition, a separate group of male and female TE4F mice were housed under germ-free conditions. Collected brains were sectioned, stained with 0.1% Sudan black and used to measure volumes of regions of interest. RESULT: In males, TE3F and TE4F mice treated with H2O showed significant hippocampal atrophy compared to P301S mice lacking a functional ApoE gene (TEKO). However, TE3F mice treated with a short-term ABX showed significantly milder hippocampal atrophy compared to the water-treated group (p < 0.001, t-test). ABX treatment of TE4F animals was also associated with milder atrophy, although the effect did not reach statistical significance (p = 0.09, t-test). There were no effects in TEKO mice treated with ABX. Remarkably, these phenotypic effects of ABX treatment were not observed in females. Moreover, germ-free TE4F mice showed a marked decrease in brain atrophy compared to conventionally-raised animals; this was true for both sexes. CONCLUSION: Our results indicate that tau-mediated neurodegeneration occurs in a ApoE- dependent manner and is influenced by the gut microbiota and gender. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Multi-omics approaches reveal a link between the MS4A gene loci, TREM2, and microglia function
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e054553.
You, S.-F.a , Brase, L.b , Filipello, F.c , Del-Aguila, J.L.d , Mihindukulasuriya, K.A.e , Benitez, B.A.d , Cruchaga, C.a , Harari, O.d , Karch, C.M.f
a Washington University, St. Louis, MO, USA
b Washington University in St. Louis, St. Louis, MO, USA
c Washington University School of Medicine, MO, Saint Louis, United States
d Washington University School of Medicine, St. Louis, MO, USA
e Washington University in St. Louis, School of Medicine, St. Louis, MO, USA
f Washington University, MO, Saint Louis, United States
Abstract
BACKGROUND: Soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) has been associated with Alzheimer’s disease (AD). TREM2 plays a critical role in microglial activation, survival, and phagocytosis; however, the pathophysiological role of sTREM2 in AD is not well understood. Understanding the role of sTREM2 in AD may reveal new pathological mechanisms and lead to the identification of therapeutic targets. We recently identified common variants in the membrane-spanning 4-domains subfamily A (MS4A) gene region that were associated with CSF sTREM2 concentrations. One variant (rs1582763) was associated with increased CSF sTREM2 and reduced AD risk, while a second variant (rs6591561) was associated with reduced CSF sTREM2 and increased AD risk. Using human induced pluripotent stem cell-derived microglia, we found that MS4A4A and TREM2 colocalize on lipid rafts at the plasma membrane. Here, we sought to define the molecular mechanism by which variants in the MS4A gene region impact sTREM2, microglia function and AD risk. METHOD: To define the functional effects of MS4A variants, we used genotype and bulk RNAseq data from 579 human brain samples. We then evaluated microglia specific effects using single nuclei RNAseq data obtained from 64 human brains. RESULT: Leveraging genotypic and transcriptomic data in human brain tissue, we found that rs1582763 and rs6591561 alter distinct molecular pathways. Rs1582763, which confers AD resilience, impacts pathways associated with cholesterol metabolism, while rs6591561, which confers AD risk, impacts pathways associated with chemokine regulation. Using single nuclei RNAseq data in human brain tissue, we found that these variants are associated with MS4A4A expression within microglia. Additionally, these variants modify cellular proportions of a functionally distinct microglia population. CONCLUSION: Together, these findings begin to provide a mechanistic explanation for the original GWAS signal in the MS4A locus for AD risk and indicate that TREM2 may be involved in AD pathogenesis not only in TREM2 risk-variant carriers but also in those with sporadic disease. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus
Multi-omics data integration reveals clinically meaningful molecular profiles of Alzheimer disease
(2021) Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 17, p. e052942.
Eteleeb, A.M.a b , Novotny, B.C.b c , Morris, J.C.c d e , Bateman, R.J.c f g , Perrin, R.J.f g h , Karch, C.M.b f h , Cruchaga, C.b e f h , Benitez, B.A.b c f g , Harari, O.a b f g
a Washington University, MO, Saint Louis, United States
b NeuroGenomics and Informatics Center, St. Louis, MO, USA
c Washington University in St. Louis, St. Louis, MO, USA
d Hope Center for Neurological Disorders, MO, Saint Louis, United States
e Knight Alzheimer Disease Research Center, MO, Saint Louis, United States
f Hope Center for Neurological Disorders, St. Louis, MO, USA
g Knight Alzheimer Disease Research Center, St. Louis, MO, USA
h Washington University in St. Louis School of Medicine, St. Louis, MO, USA
Abstract
BACKGROUND: Alzheimer disease (AD) is a complex polygenic disease in which multiple molecular pathways and biological processes are affected in distinct cell-types of the brain. Increasingly, novel machine learning approaches have been applied in other areas of similarly high complexity (e.g., cancer) to integrate different modalities of “-omics” data and provide novel insights. We sought to apply high-throughput “multi-omics” and machine learning approaches to a large assembly of clinically and neuropathologically well-characterized brain samples to identify genes and biological pathways that may lead to new biomarkers and therapies for AD. METHOD: We analyzed high-throughput transcriptomics, proteomics, metabolomics and lipidomics profiles of postmortem parietal cortex samples from the Knight ADRC (n=328) and the DIAN (n =21) participants including APP, PSEN1 and PSEN2 autosomal dominant AD mutation carriers (ADAD, n=28), sporadic AD (sAD, n=282), presymptomatic AD (preAD, n=14), and controls with minimal neuropathologic changes (n=25). We applied a Bayesian integrative clustering method (iClusterBayes), designed to identify disease subtypes, to cluster sAD samples on the basis of 2,676 transcripts, 1,067 proteins, 350 metabolites, and 277 lipids. RESULT: Our analyses identified four different molecular signatures among sAD cases (Figure 1A). Cluster 4 was associated with higher Clinical Dementia Rating (CDR; p=2.2 x10-20) scores and shorter life span (p=5.6 x10-3, HR=1.6; Figure 1B). In particular, alpha-synuclein (SNCA) transcriptomic and proteomic levels were differentially expressed between samples in cluster 4 and others representing sAD, ADAD, preAD, and controls (Figure 1C) suggesting a unique role for SNCA in sAD cases with unfavorable outcomes. The lower levels of soluble SNCA protein in AD samples may be associated with insoluble aggregated SNCA (Lewy bodies) reported in 50-60% of sAD. CONCLUSION: By applying machine learning approaches to sAD samples with high-throughput multi-omic profiles, we identified novel molecular signatures missed by single layer analyses. These signatures are associated with clinical phenotypes and offer new insights into which molecules may wax or wane as cognition declines. The association of SNCA with poor outcomes suggests that concomitant Lewy bodies may be a negative prognostic factor in sAD. Currently, we are extending these analyses to incorporate replication cohorts and to perform downstream pathway and enrichment analyses. © 2021 the Alzheimer’s Association.
Document Type: Article
Publication Stage: Final
Source: Scopus