17q21.31 sub-haplotypes underlying H1-associated risk for Parkinson’s disease are associated with LRRC37A/2 expression in astrocytes
(2022) Molecular Neurodegeneration, 17 (1), art. no. 48, .
Bowles, K.R.a b , Pugh, D.A.a b , Liu, Y.a b , Patel, T.a b , Renton, A.E.a b , Bandres-Ciga, S.c , Gan-Or, Z.d e f , Heutink, P.g h , Siitonen, A.i j , Bertelsen, S.a b , Cherry, J.D.k l m n , Karch, C.M.o , Frucht, S.J.p , Kopell, B.H.q r , Peter, I.s t , Park, Y.J.q u , Charney, A.a q s u , Raj, T.a b s v , Crary, J.F.a b w , Goate, A.M.a b s v , International Parkinson’s Disease Genomics Consortium (IPDGC)x
a Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
b Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States
c Laboratory of Neurogenetics, National Institute On Aging, National Institutes of Health, Bethesda, MD, United States
d Department of Human Genetics, McGill University, Montréal, QC, Canada
e The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montréal, QC, Canada
f Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
g Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
h German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
i Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland
j Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland
k Alzheimer’s Disease and CTE Center, Boston University, Boston University School of Medicine, Boston, MA, United States
l Department of Neurology, Boston University School of Medicine, Boston, MA, United States
m VA Boston Healthcare System, 150 S. Huntington Avenue, Boston, MA, United States
n Department of Pathology and Laboratory Medicine, Boston University School of Medicine, Boston, MA, United States
o Department of Psychiatry, Washington University in St Louis, St. Louis, MO, United States
p Department of Neurology, Fresco Institute for Parkinson’s and Movement Disorders, New York University Langone, New York, NY, United States
q Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, United States
r Center for Neuromodulation, Icahn School of Medicine at Mount Sinai, New York, NY, United States
s Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
t Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, United States
u Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
v Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
w Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
x IPDGC Authors and Affiliations in Supplementary Material 2, New York, NY, United States
Abstract
Background: Parkinson’s disease (PD) is genetically associated with the H1 haplotype of the MAPT 17q.21.31 locus, although the causal gene and variants underlying this association have not been identified. Methods: To better understand the genetic contribution of this region to PD and to identify novel mechanisms conferring risk for the disease, we fine-mapped the 17q21.31 locus by constructing discrete haplotype blocks from genetic data. We used digital PCR to assess copy number variation associated with PD-associated blocks, and used human brain postmortem RNA-seq data to identify candidate genes that were then further investigated using in vitro models and human brain tissue. Results: We identified three novel H1 sub-haplotype blocks across the 17q21.31 locus associated with PD risk. Protective sub-haplotypes were associated with increased LRRC37A/2 copy number and expression in human brain tissue. We found that LRRC37A/2 is a membrane-associated protein that plays a role in cellular migration, chemotaxis and astroglial inflammation. In human substantia nigra, LRRC37A/2 was primarily expressed in astrocytes, interacted directly with soluble α-synuclein, and co-localized with Lewy bodies in PD brain tissue. Conclusion: These data indicate that a novel candidate gene, LRRC37A/2, contributes to the association between the 17q21.31 locus and PD via its interaction with α-synuclein and its effects on astrocytic function and inflammatory response. These data are the first to associate the genetic association at the 17q21.31 locus with PD pathology, and highlight the importance of variation at the 17q21.31 locus in the regulation of multiple genes other than MAPT and KANSL1, as well as its relevance to non-neuronal cell types. © 2022, The Author(s).
Author Keywords
17q21.31; Astrocytes; Copy number variation; LRRC37A; Parkinson’s disease
Funding details
National Institutes of HealthNIHP01 AG026276
U.S. Department of Health and Human ServicesHHS1ZIA-NS003154, Z01-AG000949-02, Z01-ES101986
National Institute on AgingNIA1ZIAAG000935, 1ZIANS003154
National Institute of Neurological Disorders and StrokeNINDS
National Institute of Environmental Health SciencesNIEHS
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
New York Stem Cell FoundationNYSCF
Association for Frontotemporal DegenerationAFTD
GlaxoSmithKlineGSK
BrightFocus FoundationBFF
CurePSP
McGill UniversityMGU
Consortium canadien en neurodégénérescence associée au vieillissementCCNA
Rainwater Charitable FoundationRCF
Verily Life Sciences
Fonds de Recherche du Québec – SantéFRQS
School of Medicine, CHA University
Parkinson Canada
Canada First Research Excellence FundCFREF
Document Type: Article
Publication Stage: Final
Source: Scopus
Proteinopathy and Longitudinal Cognitive Decline in Parkinson Disease
(2022) Neurology, 99 (1), pp. E66-E76.
Myers, P.S.a , O’Donnell, J.L.a , Jackson, J.J.h , Lessov-Schlaggar, C.N.b , Miller, R.L.a , Foster, E.R.a b c , Cruchaga, C.a b d , Benitez, B.A.b , Kotzbauer, P.T.a , Perlmutter, J.S.c e f g , Campbell, M.C.a
a Department of Neurology, Washington University, St. Louis, MO, United States
b Department of Psychiatry, Washington University, St. Louis, MO, United States
c Program in Occupational Therapy, Washington University, St. Louis, MO, United States
d Department of Genetics, Washington University, St. Louis, MO, United States
e Department of Radiology, Washington University, St. Louis, MO, United States
f Department of Neuroscience, Washington University, St. Louis, MO, United States
g Program in Physical Therapy, Washington University, School of Medicine, St. Louis, MO, United States
h Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, United States
Abstract
Background and ObjectivesPeople with Parkinson disease (PD) commonly experience cognitive decline, which may relate to increased α-synuclein, tau, and β-amyloid accumulation. This study examines whether the different proteins predict longitudinal cognitive decline in PD.MethodsAll participants (PD n = 152, controls n = 52) were part of a longitudinal study and completed a lumbar puncture for CSF protein analysis (α-synuclein, total tau [tau], and β-amyloid42 [β-amyloid]), a β-amyloid PET scan, and/or provided a blood sample for APOE genotype (ϵ4+, ϵ4-), which is a risk factor for β-amyloid accumulation. Participants also had comprehensive, longitudinal clinical assessments of overall cognitive function and dementia status, as well as cognitive testing of attention, language, memory, and visuospatial and executive function. We used hierarchical linear growth models to examine whether the different protein metrics predict cognitive change and multivariate Cox proportional hazard models to predict time to dementia conversion. Akaike information criterion was used to compare models for best fit.ResultsBaseline measures of CSF β-amyloid predicted decline for memory (p = 0.04) and overall cognitive function (p = 0.01). APOE genotypes showed a significant group (ϵ4+, ϵ4-) effect such that ϵ4+ individuals declined faster than ϵ4- individuals in visuospatial function (p = 0.03). Baseline β-amyloid PET significantly predicted decline in all cognitive measures (all p ≤ 0.004). Neither baseline CSF α-synuclein nor tau predicted cognitive decline. All 3 β-amyloid – related metrics (CSF, PET, APOE) also predicted time to dementia. Models with β-amyloid PET as a predictor fit the data the best.DiscussionPresence or risk of β-amyloid accumulation consistently predicted cognitive decline and time to dementia in PD. This suggests that β-amyloid has high potential as a prognostic indicator and biomarker for cognitive changes in PD. © 2022 American Academy of Neurology.
Funding details
National Institute of Neurological Disorders and StrokeNINDSF32NS105365, NS058714, NS075321, NS097437, NS097799, NS118146, NS41509, NS48924, P30 NS048056
National Center for Research ResourcesNCRRUL1RR024992
American Parkinson Disease AssociationAPDA
Foundation for Barnes-Jewish HospitalFBJH
Document Type: Article
Publication Stage: Final
Source: Scopus
Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex
(2022) Cerebral Cortex, 32 (13), pp. 2868-2884.
Gordon, E.M.a , Laumann, T.O.b , Marek, S.b , Newbold, D.J.c , Hampton, J.M.b , Seider, N.A.c , Montez, D.F.c , Nielsen, A.M.d , Van, A.N.e , Zheng, A.c , Miller, R.b c , Siegel, J.S.b , Kay, B.P.c , Snyder, A.Z.a c , Greene, D.J.f , Schlaggar, B.L.g h i , Petersen, S.E.a c j k , Nelson, S.M.l m , Dosenbach, N.U.F.a c g n o
a Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
c Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
d Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL 60611, United States
e Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, United States
f Department of Cognitive Science, University of California San Diego, La JollaCA 92093, United States
g Kennedy Krieger Institute, Baltimore, MD 21205, United States
h Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
i Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, United States
j Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
k Department of Psychological & Brain Sciences, Washington University School of Medicine, St. Louis, MO 63110, United States
l Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, United States
m Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55454, United States
n Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
o Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex – predominately frontal cortex – to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks. © 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved.
Author Keywords
brain networks; fMRI; functional connectivity; individual variability; striatum
Document Type: Article
Publication Stage: Final
Source: Scopus
Automated Measurement of Net Water Uptake From Baseline and Follow-Up CTs in Patients With Large Vessel Occlusion Stroke
(2022) Frontiers in Neurology, 13, art. no. 898728, .
Kumar, A.a , Chen, Y.a , Corbin, A.b , Hamzehloo, A.a , Abedini, A.c , Vardar, Z.d , Carey, G.a , Bhatia, K.a , Heitsch, L.e , Derakhshan, J.J.c , Lee, J.-M.a , Dhar, R.a
a Department of Neurology, Washington University in St. Louis School of Medicine, Saint Louis, MO, United States
b Saint Louis University School of Medicine, Saint Louis, MO, United States
c Department of Radiology, Washington University in St. Louis School of Medicine, Saint Louis, MO, United States
d Department of Radiology, University of Massachusetts Medical School, Worcester, MA, United States
e Department of Emergency Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO, United States
Abstract
Quantifying the extent and evolution of cerebral edema developing after stroke is an important but challenging goal. Lesional net water uptake (NWU) is a promising CT-based biomarker of edema, but its measurement requires manually delineating infarcted tissue and mirrored regions in the contralateral hemisphere. We implement an imaging pipeline capable of automatically segmenting the infarct region and calculating NWU from both baseline and follow-up CTs of large-vessel occlusion (LVO) patients. Infarct core is extracted from CT perfusion images using a deconvolution algorithm while infarcts on follow-up CTs were segmented from non-contrast CT (NCCT) using a deep-learning algorithm. These infarct masks were flipped along the brain midline to generate mirrored regions in the contralateral hemisphere of NCCT; NWU was calculated as one minus the ratio of densities between regions, removing voxels segmented as CSF and with HU outside thresholds of 20–80 (normal hemisphere and baseline CT) and 0–40 (infarct region on follow-up). Automated results were compared with those obtained using manually-drawn infarcts and an ASPECTS region-of-interest based method that samples densities within the infarct and normal hemisphere, using intraclass correlation coefficient (ρ). This was tested on serial CTs from 55 patients with anterior circulation LVO (including 66 follow-up CTs). Baseline NWU using automated core was 4.3% (IQR 2.6–7.3) and correlated with manual measurement (ρ = 0.80, p < 0.0001) and ASPECTS (r = −0.60, p = 0.0001). Automatically segmented infarct volumes (median 110-ml) correlated to manually-drawn volumes (ρ = 0.96, p < 0.0001) with median Dice similarity coefficient of 0.83 (IQR 0.72–0.90). Automated NWU was 24.6% (IQR 20–27) and highly correlated to NWU from manually-drawn infarcts (ρ = 0.98) and the sampling-based method (ρ = 0.68, both p < 0.0001). We conclude that this automated imaging pipeline is able to accurately quantify region of infarction and NWU from serial CTs and could be leveraged to study the evolution and impact of edema in large cohorts of stroke patients. Copyright © 2022 Kumar, Chen, Corbin, Hamzehloo, Abedini, Vardar, Carey, Bhatia, Heitsch, Derakhshan, Lee and Dhar.
Author Keywords
cerebral edema area; computed tomography; image segmentation; machine learning; stroke
Funding details
National Institutes of HealthNIHRR1817, U24NS107230
National Institute of Neurological Disorders and StrokeNINDSK23NS099440, K23NS099487, R01NS085419
Foundation of the American Society of NeuroradiologyFASNR
Document Type: Article
Publication Stage: Final
Source: Scopus
Avoid or Embrace? Practice Effects in Alzheimer’s Disease Prevention Trials
(2022) Frontiers in Aging Neuroscience, 14, art. no. 883131, .
Aschenbrenner, A.J.a , Hassenstab, J.a , Wang, G.a , Li, Y.a , Xiong, C.a , McDade, E.a , Clifford, D.B.a , Salloway, S.b , Farlow, M.c , Yaari, R.d , Cheng, E.Y.J.d , Holdridge, K.C.d , Mummery, C.J.e , Masters, C.L.f , Hsiung, G.-Y.g , Surti, G.h , Day, G.S.i , Weintraub, S.j , Honig, L.S.k , Galvin, J.E.l , Ringman, J.M.m , Brooks, W.S.n , Fox, N.C.o , Snyder, P.J.h , Suzuki, K.p , Shimada, H.q , Gräber, S.r , Bateman, R.J.a , the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU)s
a Washington University in St. Louis School of Medicine, St. Louis, MO, United States
b Warren Alpert Medical School of Brown University, Providence, RI, United States
c Indiana University School of Medicine, Indianapolis, IN, United States
d Eli Lilly and Company, Indianapolis, IN, United States
e University College London, London, United Kingdom
f University of Melbourne, Melbourne, VIC, Australia
g The University of British Columbia, Vancouver, BC, Canada
h The University of Rhode Island, Kingston, RI, United States
i Mayo Clinic, Jacksonville, FL, United States
j Feiniberg School of Medicine, Northwestern University, Chicago, IL, United States
k Columbia University Irving Medical Center, New York, NY, United States
l Miller School of Medicine, University of Miami, Miami, FL, United States
m University of Southern California, Los Angeles, CA, United States
n Neuroscience Research Australia, University of New South Wales Medicine, Randwick, NSW, Australia
o Dementia Research Center, University College London, London, United Kingdom
p The University of Tokyo, Tokyo, Japan
q Osaka City University, Osaka, Japan
r German Center for Neurodegenerative Disease (DZNE), Tübingen, Germany
Abstract
Demonstrating a slowing in the rate of cognitive decline is a common outcome measure in clinical trials in Alzheimer’s disease (AD). Selection of cognitive endpoints typically includes modeling candidate outcome measures in the many, richly phenotyped observational cohort studies available. An important part of choosing cognitive endpoints is a consideration of improvements in performance due to repeated cognitive testing (termed “practice effects”). As primary and secondary AD prevention trials are comprised predominantly of cognitively unimpaired participants, practice effects may be substantial and may have considerable impact on detecting cognitive change. The extent to which practice effects in AD prevention trials are similar to those from observational studies and how these potential differences impact trials is unknown. In the current study, we analyzed data from the recently completed DIAN-TU-001 clinical trial (TU) and the associated DIAN-Observational (OBS) study. Results indicated that asymptomatic mutation carriers in the TU exhibited persistent practice effects on several key outcomes spanning the entire trial duration. Critically, these practice related improvements were larger on certain tests in the TU relative to matched participants from the OBS study. Our results suggest that the magnitude of practice effects may not be captured by modeling potential endpoints in observational studies where assessments are typically less frequent and drug expectancy effects are absent. Using alternate instrument forms (represented in our study by computerized tasks) may partly mitigate practice effects in clinical trials but incorporating practice effects as outcomes may also be viable. Thus, investigators must carefully consider practice effects (either by minimizing them or modeling them directly) when designing cognitive endpoint AD prevention trials by utilizing trial data with similar assessment frequencies. Copyright © 2022 Aschenbrenner, Hassenstab, Wang, Li, Xiong, McDade, Clifford, Salloway, Farlow, Yaari, Cheng, Holdridge, Mummery, Masters, Hsiung, Surti, Day, Weintraub, Honig, Galvin, Ringman, Brooks, Fox, Snyder, Suzuki, Shimada, Gräber and Bateman.
Author Keywords
alternative forms; Alzheimer’s disease; assessment frequency; clinical trials; learning; practice effects
Funding details
K23AG064029
National Institutes of HealthNIHU01AG042791
Foundation for the National Institutes of HealthFNIHDIAN-TU-001, R01AG053267-S1, R1AG046179
National Institute on AgingNIA
Alzheimer’s AssociationAA
Amgen
Bristol-Myers SquibbBMS
Eli Lilly and Company
Roche
Biogen
AbbVie
F. Hoffmann-La Roche
Janssen Pharmaceuticals
American Neurological AssociationANA
GHR FoundationGHR
Canadian Institutes of Health ResearchIRSC
Alzheimer Society
Eisai
Alzheimer Society of B.C.
Document Type: Article
Publication Stage: Final
Source: Scopus
Homotopic contralesional excitation suppresses spontaneous circuit repair and global network reconnections following ischemic stroke
(2022) eLife, 11, art. no. e68852, .
Bice, A.R.a , Xiao, Q.b , Kong, J.c , Yan, P.b , Rosenthal, Z.P.b , Kraft, A.W.b , Smith, K.b , Wieloch, T.f , Lee, J.-M.a b d , Culver, J.P.a d e , Bauer, A.Q.a d
a Departments of Radiology, Washington University in St. Louis, United States
b Departments of Neurology, Washington University in St. Louis, United States
c Departments of Biology and Biomedical Sciences, Washington University in St. Louis, United States
d Departments of Biomedical Engineering, Washington University in St. Louis, United States
e Departments of Physics, Washington University in St. Louis, United States
f Laboratory for Experimental Brain Research, Division of Neurosurgery, Department of Clinical Sciences, Lund University, BMC A13, Lund, 22184, Sweden
Abstract
Understanding circuit-level manipulations that affect the brain’s capacity for plasticity will inform the design of targeted interventions that enhance recovery after stroke. Following stroke, increased contralesional activity (e.g. use of the unaffected limb) can negatively influence recovery, but it is unknown which specific neural connections exert this influence, and to what extent increased contralesional activity affects systems-and molecular-level biomarkers of recovery. Here, we combine optogenetic photostimulation with optical intrinsic signal imaging (OISI) to examine how contralesional excitatory activity affects cortical remodeling after stroke in mice. Following photothrombosis of left primary somatosensory forepaw (S1FP) cortex, mice either recovered spontaneously or received chronic optogenetic excitation of right S1FP over the course of 4 weeks. Contralesional excitation suppressed perilesional S1FP remapping and was associated with abnormal patterns of stimulus-evoked activity in the unaffected limb. This maneuver also prevented the restoration of resting-state functional connectivity (RSFC) within the S1FP network, RSFC in several networks functionally-distinct from somatomotor regions, and resulted in persistent limb-use asymmetry. In stimulated mice, perilesional tissue exhibited transcriptional changes in several genes relevant for recovery. Our results suggest that contralesional excitation impedes local and global circuit reconnection through suppression of cortical activity and several neuroplasticity-related genes after stroke, and highlight the importance of site selection for therapeutic intervention after focal ischemia. © 2022, eLife Sciences Publications Ltd. All rights reserved.
Author Keywords
functional recovery; optogenetics; Plasticity; resting state functional connectivity; stroke
Funding details
National Institutes of HealthNIHF31NS089135, F31NS103275, K25-NS083754, P01NS080675, R01-NS102870, R01NS078223, R01NS084028, R01NS094692, R01NS099429, R37NS110699
Alborada Trust
McDonnell Center for Systems Neuroscience
VetenskapsrådetVR
Document Type: Article
Publication Stage: Final
Source: Scopus
A phase II study repurposing atomoxetine for neuroprotection in mild cognitive impairment
(2022) Brain, 145 (6), pp. 1924-1938. Cited 5 times.
Levey, A.I.a b , Qiu, D.a c , Zhao, L.a d , Hu, W.T.a b , Duong, D.M.e , Higginbotham, L.a b , Dammer, E.B.e , Seyfried, N.T.a e , Wingo, T.S.a b f , Hales, C.M.a b , Tansey, M.G.g , Goldstein, D.S.h , Abrol, A.i , Calhoun, V.D.i , Goldstein, F.C.a b , Hajjar, I.a b , Fagan, A.M.j , Galasko, D.k , Edland, S.D.k , Hanfelt, J.a d , Lah, J.J.a b , Weinshenker, D.a f
a Goizueta Alzheimer’s Disease Research Center, Emory University, Atlanta, GA 30322, United States
b Department of Neurology, Emory University, Atlanta, GA 30322, United States
c Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, United States
d Department of Biostatistics, Emory University, Atlanta, GA 30322, United States
e Department of Biochemistry, Emory University, Atlanta, GA 30322, United States
f Department of Human Genetics, Emory University, Atlanta, GA 30322, United States
g Department of Physiology, Emory University, Atlanta, GA 30322, United States
h NINDS, NIH, Bethesda, MD 20892, United States
i Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303, United States
j Department of Neurology and Knight ADRC, Washington University, St. Louis, MO 630130, United States
k Department of Neurosciences and ADRC, UCSD, San Diego, CA 92093, United States
Abstract
The locus coeruleus is the initial site of Alzheimer’s disease neuropathology, with hyperphosphorylated Tau appearing in early adulthood followed by neurodegeneration in dementia. Locus coeruleus dysfunction contributes to Alzheimer’s pathobiology in experimental models, which can be rescued by increasing norepinephrine transmission. To test norepinephrine augmentation as a potential disease-modifying therapy, we performed a biomarker-driven phase II trial of atomoxetine, a clinically-approved norepinephrine transporter inhibitor, in subjects with mild cognitive impairment due to Alzheimer’s disease. The design was a single-centre, 12-month double-blind crossover trial. Thirty-nine participants with mild cognitive impairment and biomarker evidence of Alzheimer’s disease were randomized to atomoxetine or placebo treatment. Assessments were collected at baseline, 6- (crossover) and 12-months (completer). Target engagement was assessed by CSF and plasma measures of norepinephrine and metabolites. Prespecified primary outcomes were CSF levels of IL1α and TECK. Secondary/exploratory outcomes included clinical measures, CSF analyses of amyloid-β42, Tau, and pTau181, mass spectrometry proteomics and immune-based targeted inflammation-related cytokines, as well as brain imaging with MRI and fluorodeoxyglucose-PET. Baseline demographic and clinical measures were similar across trial arms. Dropout rates were 5.1% for atomoxetine and 2.7% for placebo, with no significant differences in adverse events. Atomoxetine robustly increased plasma and CSF norepinephrine levels. IL-1α and TECK were not measurable in most samples. There were no significant treatment effects on cognition and clinical outcomes, as expected given the short trial duration. Atomoxetine was associated with a significant reduction in CSF Tau and pTau181 compared to placebo, but not associated with change in amyloid-β42. Atomoxetine treatment also significantly altered CSF abundances of protein panels linked to brain pathophysiologies, including synaptic, metabolism and glial immunity, as well as inflammation-related CDCP1, CD244, TWEAK and osteoprotegerin proteins. Treatment was also associated with significantly increased brain-derived neurotrophic factor and reduced triglycerides in plasma. Resting state functional MRI showed significantly increased inter-network connectivity due to atomoxetine between the insula and the hippocampus. Fluorodeoxyglucose-PET showed atomoxetine-associated increased uptake in hippocampus, parahippocampal gyrus, middle temporal pole, inferior temporal gyrus and fusiform gyrus, with carry-over effects 6 months after treatment. In summary, atomoxetine treatment was safe, well tolerated and achieved target engagement in prodromal Alzheimer’s disease. Atomoxetine significantly reduced CSF Tau and pTau, normalized CSF protein biomarker panels linked to synaptic function, brain metabolism and glial immunity, and increased brain activity and metabolism in key temporal lobe circuits. Further study of atomoxetine is warranted for repurposing the drug to slow Alzheimer’s disease progression. © The Author(s) 2022.
Author Keywords
Alzheimer’s disease; atomoxetine; locus coeruleus; mild cognitive impairment; norepinephrine
Document Type: Article
Publication Stage: Final
Source: Scopus
Detection of Brain Tau Pathology in Down Syndrome Using Plasma Biomarkers
(2022) JAMA Neurology, .
Janelidze, S.a , Christian, B.T.b , Price, J.c , Laymon, C.d , Schupf, N.e , Klunk, W.E.d , Lott, I.f , Silverman, W.f , Rosas, H.D.c g , Zaman, S.h , Mapstone, M.i , Lai, F.g , Ances, B.M.j , Handen, B.L.d , Hansson, O.a k
a Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sölvegatan 19, BMC B11, Lund, 221 84, Sweden
b Waisman Center, University of Wisconsin, Madison, United States
c Harvard Medical School, Department of Radiology, Massachusetts General Hospital, Charlestown, United States
d Department of Psychiatry, University of Pittsburgh, 3811 O’Hara St, Pittsburgh, PA 15213, United States
e Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, United States
f School of Medicine, Department of Pediatrics, University of California, Irvine, United States
g Harvard Medical School, Department of Neurology, Massachusetts General Hospital, Charlestown, United States
h School of Clinical Medicine, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
i Department of Neurology, University of California, Irvine, United States
j Washington University, School of Medicine in St Louis, St Louis, MO, United States
k Memory Clinic, Skåne University Hospital, Malmö, Sweden
Abstract
Importance: Novel plasma biomarkers, especially phosphorylated tau (p-tau), can detect brain tau aggregates in Alzheimer disease. Objective: To determine which plasma biomarker combinations can accurately detect tau pathological brain changes in Down syndrome (DS). Design, Setting, and Participants: The cross-sectional, multicenter Alzheimer’s Biomarker Consortium-Down Syndrome study included adults with DS and a control group of siblings without DS. All participants with plasma, positron emission tomography (PET), and cognitive measures available by the time of data freeze 1.0 were included. Participants were enrolled between 2016 and 2019, and data were analyzed from August 2021 to April 2022. Exposures: Plasma p-tau217, glial fibrillary acidic protein (GFAP), amyloid β42/40 (Aβ42/Aβ40), neurofilament light (NfL), and total tau (t-tau); tau positron emission tomography (tau-PET) and Aβ-PET. Main Outcomes and Measures: The primary outcome was tau-PET status. Secondary outcomes included Aβ-PET status and cognitive performance. Results: Among 300 participants with DS and a control group of 37 non-DS siblings, mean (SD) age was 45.0 (10.1) years, and 167 (49.6%) were men. Among participants with DS who all underwent plasma p-tau217 and GFAP analyses, 258 had other plasma biomarker data available and 119, 213, and 288 participants had tau-PET, Aβ-PET, and cognitive assessments, respectively. Plasma p-tau217 and t-tau were significantly increased in Aβ-PET-positive tau-PET-positive (A+T+) DS and A+T-DS compared with A-T-DS while GFAP was only increased in A+T+DS. Plasma p-tau217 levels were also significantly higher in A+T+DS than A+T-DS. In participants with DS, plasma p-tau217 and GFAP (but not other plasma biomarkers) were consistently associated with abnormal tau-PET and Aβ-PET status in models covaried for age (odds ratio range, 1.59 [95% CI, 1.05-2.40] to 2.32 [95% CI, 1.36-3.96]; P <.03). A combination of p-tau217 and age performed best when detecting tau-PET abnormality in temporal and neocortical regions (area under the curve [AUC] range, 0.96-0.99). The most parsimonious model for Aβ-PET status included p-tau217, t-tau, and age (AUC range, 0.93-0.95). In multivariable models, higher p-tau217 levels but not other biomarkers were associated with worse performance on DS Mental Status Examination (β, -0.24, 95% CI, -0.36 to -0.12; P <.001) and Cued Recall Test (β, -0.40; 95% CI, -0.53 to -0.26; P <.001). Conclusions and Relevance: Plasma p-tau217 is a very accurate blood-based biomarker of both tau and Aβ pathological brain changes in DS that could help guide screening and enrichment strategies for inclusion of individuals with DS in future AD clinical trials, especially when it is combined with age as a covariate. © 2022 American Medical Association. All rights reserved.
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Comparative analytical performance of multiple plasma Aβ42 and Aβ40 assays and their ability to predict positron emission tomography amyloid positivity
(2022) Alzheimer’s and Dementia, .
Zicha, S.a , Bateman, R.J.b , Shaw, L.M.c , Zetterberg, H.d e f g , Bannon, A.W.h , Horton, W.A.i , Baratta, M.a , Kolb, H.C.j , Dobler, I.a , Mordashova, Y.k , Saad, Z.S.j , Raunig, D.L.a , Spanakis, E.k , Li, Y.b , Schindler, S.E.b , Ferber, K.l , Rubel, C.E.l , Martone, R.L.l , Weber, C.J.m , Edelmayer, R.M.m , Meyers, E.A.m , Bollinger, J.G.b , Rosenbaugh, E.G.i , Potter, W.Z.n , Alzheimer’s Disease Neuroimaging Initiative (ADNI)o , Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium Plasma Abeta as a Predictor of Amyloid Positivity in Alzheimer’s Disease Project Teamo
a Takeda, Pharmaceutical Company Ltd., Cambridge, MA, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
d Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
e Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
f UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, United Kingdom
g Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom
h AbbVie, North Chicago, IL, United States
i The Foundation for the National Institutes of Health, North Bethesda, MD, United States
j Neuroscience Biomarkers, Janssen Research and Development LLC, La Jolla, CA, United States
k AbbVie Deutschland GmbH & Co KG, Ludwigshafen, Germany
l Biogen, Cambridge, MA, United States
m Alzheimer’s Association, Chicago, IL, United States
Abstract
Introduction: This report details the approach taken to providing a dataset allowing for analyses on the performance of recently developed assays of amyloid beta (Aβ) peptides in plasma and the extent to which they improve the prediction of amyloid positivity. Methods: Alzheimer’s Disease Neuroimaging Initiative plasma samples with corresponding amyloid positron emission tomography (PET) data were run on six plasma Aβ assays. Statistical tests were performed to determine whether the plasma Aβ measures significantly improved the area under the receiver operating characteristic curve for predicting amyloid PET status compared to age and apolipoprotein E (APOE) genotype. Results: The age and APOE genotype model predicted amyloid status with an area under the curve (AUC) of 0.75. Three assays improved AUCs to 0.81, 0.81, and 0.84 (P <.05, uncorrected for multiple comparisons). Discussion: Measurement of Aβ in plasma contributes to addressing the amyloid component of the ATN (amyloid/tau/neurodegeneration) framework and could be a first step before or in place of a PET or cerebrospinal fluid screening study. Highlights: The Foundation of the National Institutes of Health Biomarkers Consortium evaluated six plasma amyloid beta (Aβ) assays using Alzheimer’s Disease Neuroimaging Initiative samples. Three assays improved prediction of amyloid status over age and apolipoprotein E (APOE) genotype. Plasma Aβ42/40 predicted amyloid positron emission tomography status better than Aβ42 or Aβ40 alone. © 2022 The Authors. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.
Author Keywords
Alzheimer’s disease; Alzheimer’s Disease Neuroimaging Initiative; amyloid; amyloid beta 40; amyloid beta 42; amyloid positron emission tomography; amyloid prediction; biomarkers; plasma
Funding details
National Institutes of HealthNIH
U.S. Department of DefenseDODW81XWH‐12‐2‐0012
Foundation for the National Institutes of HealthFNIH
National Institute on AgingNIAP30 AG010124, U19 AG024904
National Institute of Biomedical Imaging and BioengineeringNIBIB
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
Alzheimer’s AssociationAA
Biogen
AbbVie
Alzheimer’s Disease Neuroimaging InitiativeADNI
Takeda Pharmaceuticals U.S.A.TPUSA
BioClinica
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Progressive White Matter Injury in Preclinical Dutch Cerebral Amyloid Angiopathy
(2022) Annals of Neurology, .
Shirzadi, Z.a , Yau, W.-Y.W.a , Schultz, S.A.a , Schultz, A.P.a , Scott, M.R.a , Goubran, M.b , Mojiri-Forooshani, P.b , Joseph-Mathurin, N.c , Kantarci, K.d , Preboske, G.d , Wermer, M.J.H.e , Jack, C.d , Benzinger, T.c , Taddei, K.f , Sohrabi, H.R.g , Sperling, R.A.a , Johnson, K.A.a , Bateman, R.J.c , Martins, R.N.f , Greenberg, S.M.a , Chhatwal, J.P.a , DIAN Investigatorsh
a Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
b Physical Sciences Platform and Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
c Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, United States
d Department of Radiology, Mayo Clinic, Rochester, MN, United States
e Department of Neurology, Leiden University Medical Centre, Leiden, Netherlands
f Centre of Excellence for Alzheimer’s Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
g Centre for Healthy Ageing, Health Future Institute, Murdoch University, Murdoch, WA, Australia
Abstract
Autosomal-dominant, Dutch-type cerebral amyloid angiopathy (D-CAA) offers a unique opportunity to develop biomarkers for pre-symptomatic cerebral amyloid angiopathy (CAA). We hypothesized that neuroimaging measures of white matter injury would be present and progressive in D-CAA prior to hemorrhagic lesions or symptomatic hemorrhage. In a longitudinal cohort of D-CAA carriers and non-carriers, we observed divergence of white matter injury measures between D-CAA carriers and non-carriers prior to the appearance of cerebral microbleeds and >14 years before the average age of first symptomatic hemorrhage. These results indicate that white matter disruption measures may be valuable cross-sectional and longitudinal biomarkers of D-CAA progression. ANN NEUROL 2022. © 2022 American Neurological Association.
Funding details
National Institutes of HealthNIHP41EB015896, S10RR021110, S10RR023043, S10RR023401
National Institute on AgingNIAK23AG049087, P01AG036694, UF1AG032438
National Institute of Neurological Disorders and StrokeNINDSR01NS070834
National Institute of Biomedical Imaging and BioengineeringNIBIB
Massachusetts General HospitalMGH
Alzheimer Society
National Health and Medical Research CouncilNHMRCAPP1129627
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Progression to Loss of Ambulation Among Patients with Autosomal Recessive Limb-girdle Muscular Dystrophy: A Systematic Review
(2022) Journal of Neuromuscular Diseases, 9 (4), pp. 477-492.
Audhya, I.F.a , Cheung, A.b , Szabo, S.M.b , Flint, E.b , Weihl, C.C.c , Gooch, K.L.a
a Sarepta Therapeutics Inc, Cambridge, MA, United States
b Broadstreet Heor, Vancouver, BC V6A 1A4, Canada
c Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background The impact of age at autosomal recessive limb girdle muscular dystrophy (LGMDR) onset on progression to loss of ambulation (LOA) has not been well established, particularly by subtype. Objectives: To describe the characteristics of patients with adult-, late childhood-, and early childhood-onset LGMDR by subtype and characterize the frequency and timing of LOA. Methods: A systematic review was conducted in MEDLINE, Embase and the Cochrane library. Frequency and timing of LOA in patients with LGMDR1, LGMDR2/Miyoshi myopathy (MM), LGMDR3-6, LGMDR9, and LGMDR12 were synthesized from published data. Results: In 195 studies, 695 (43.4%) patients had adult-, 532 (33.2%) had late childhood-, and 376 (23.5%) had early childhood-onset of disease across subtypes among those with a reported age at onset (n = 1,603); distribution of age at onset varied between subtypes. Among patients with LOA (n = 228), adult-onset disease was uncommon in LGMDR3-6 (14%) and frequent in LGMDR2/MM (42%); LGMDR3-6 cases with LOA primarily had early childhood-onset (74%). Mean (standard deviation [SD]) time to LOA varied between subtypes and was shortest for patients with early childhood-onset LGMDR9 (12.0 [4.9] years, n = 19) and LGMDR3-6 (12.3 [10.7], n = 56) and longest for those with late childhood-onset LGMDR2/MM (21.4 [11.5], n = 36). Conclusions: This review illustrated that patients with early childhood-onset disease tend to have faster progression to LOA than those with late childhood-or adult-onset disease, particularly in LGMDR9. These findings provide a greater understanding of progression to LOA by LGMDR subtype, which may help inform clinical trial design and provide a basis for natural history studies. © 2022-The authors. Published by IOS Press.
Author Keywords
age of onset; disease progression; limb-girdle; Muscular dystrophies; systematic review; walking
Funding details
Sarepta TherapeuticsSRPT
Document Type: Review
Publication Stage: Final
Source: Scopus