List of publications for the week of December 17, 2021
Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning
(2022) Journal of Neuroscience Methods, 366, art. no. 109421, .
Zhang, X.a , Landsness, E.C.b , Chen, W.b , Miao, H.b , Tang, M.b , Brier, L.M.c , Culver, J.P.c d e f , Lee, J.-M.b c d , Anastasio, M.A.a
a Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
c Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
d Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO 63130, United States
e Department of Electrical and Systems Engineering, Washington University School of Engineering, St. Louis, MO 63130, United States
f Department of Physics, Washington University School of Arts and Science, St. Louis, MO 63130, United States
Abstract
Background: Wide-field calcium imaging (WFCI) allows for monitoring of cortex-wide neural dynamics in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming and often suffers from low inter- and intra-rater reliability and invasiveness. Therefore, an automated sleep state classification method that operates on WFCI data alone is needed. New method: A hybrid, two-step method is proposed. In the first step, spatial-temporal WFCI data is mapped to multiplex visibility graphs (MVGs). Subsequently, a two-dimensional convolutional neural network (2D CNN) is employed on the MVGs to be classified as wakefulness, NREM and REM. Results: Sleep states were classified with an accuracy of 84% and Cohen’s κ of 0.67. The method was also effectively applied on a binary classification of wakefulness/sleep (accuracy=0.82, κ = 0.62) and a four-class wakefulness/sleep/anesthesia/movement classification (accuracy=0.74, κ = 0.66). Gradient-weighted class activation maps revealed that the CNN focused on short- and long-term temporal connections of MVGs in a sleep state-specific manner. Sleep state classification performance when using individual brain regions was highest for the posterior area of the cortex and when cortex-wide activity was considered. Comparison with existing method: On a 3-hour WFCI recording, the MVG-CNN achieved a κ of 0.65, comparable to a κ of 0.60 corresponding to the human EEG/EMG-based scoring. Conclusions: The hybrid MVG-CNN method accurately classifies sleep states from WFCI data and will enable future sleep-focused studies with WFCI. © 2021 The Authors
Author Keywords
2D CNN; Automated sleep state classification; Deep learning; Local sleep; Multiplex visibility graph; Wide-field calcium imaging
Funding details
National Institute on AgingNIAF30AG061932
National Institute of Neurological Disorders and StrokeNINDSK08NS109292-01A1, R01NS094692, R01NS099429, R37NS110699
American Heart AssociationAHA20CDA35310607
American Academy of Sleep Medicine FoundationAASMF201-BS-19
Document Type: Article
Publication Stage: Final
Source: Scopus
Sonobiopsy for minimally invasive, spatiotemporally-controlled, and sensitive detection of glioblastoma-derived circulating tumor DNA
(2022) Theranostics, 27 (1), pp. 362-378.
Pacia, C.P.a , Yuan, J.a , Yue, Y.a , Xu, L.a , Nazeri, A.b , Desai, R.c d , Gach, H.M.a b e , Wang, X.f g , Talcott, M.R.h , Chaudhuri, A.A.e i j k , Dunn, G.P.c d , Leuthardt, E.C.a c l m , Chen, H.a e
a Department of Biomedical Engineering, Washington University in St. Louis, Saint Louis, MO 63130, United States
b Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO 63110, United States
c Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO 63110, United States
d Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, St. Louis, MO 63110, United States
e Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, MO 63108, United States
f Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL 60612, United States
g University of Illinois Cancer Center, Chicago, IL 60612, United States
h Division of Comparative Medicine, Washington University School of Medicine, Saint Louis, MO 63110, United States
i Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
j Department of Computer Science and Engineering, Washington University in St. Louis, Saint Louis, MO 63130, United States
k Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, United States
l Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO 63110, United States
m Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, Saint Louis, MO 63110, United States
Abstract
Though surgical biopsies provide direct access to tissue for genomic characterization of brain cancer, they are invasive and pose significant clinical risks. Brain cancer management via blood-based liquid biopsies is a minimally invasive alternative; however, the blood-brain barrier (BBB) restricts the release of brain tumor-derived molecular biomarkers necessary for sensitive diagnosis. Methods: A mouse glioblastoma multiforme (GBM) model was used to demonstrate the capability of focused ultrasound (FUS)-enabled liquid biopsy (sonobiopsy) to improve the diagnostic sensitivity of brain tumor-specific genetic mutations compared with conventional blood-based liquid biopsy. Furthermore, a pig GBM model was developed to characterize the translational implications of sonobiopsy in humans. Magnetic resonance imaging (MRI)-guided FUS sonication was performed in mice and pigs to locally enhance the BBB permeability of the GBM tumor. Contrast-enhanced T1-weighted MR images were acquired to evaluate the BBB permeability change. Blood was collected immediately after FUS sonication. Droplet digital PCR was used to quantify the levels of brain tumor-specific genetic mutations in the circulating tumor DNA (ctDNA). Histological staining was performed to evaluate the potential for off-target tissue damage by sonobiopsy. Results: Sonobiopsy improved the detection sensitivity of EGFRvIII from 7.14% to 64.71% and TERT C228T from 14.29% to 45.83% in the mouse GBM model. It also improved the diagnostic sensitivity of EGFRvIII from 28.57% to 100% and TERT C228T from 42.86% to 71.43% in the porcine GBM model. Conclusion: Sonobiopsy disrupts the BBB at the spatially-targeted brain location, releases tumor-derived DNA into the blood circulation, and enables timely collection of ctDNA. Converging evidence from both mouse and pig GBM models strongly supports the clinical translation of sonobiopsy for the minimally invasive, spatiotemporally-controlled, and sensitive molecular characterization of brain cancer. © The author(s).
Author Keywords
Blood-based liquid biopsy; Blood-brain barrier; Droplet digital PCR; Glioblastoma mutation; Image-guided focused ultrasound
Funding details
National Institutes of HealthNIHR01EB027223, R01EB030102, R01MH116981, T32NS115672
Washington University in St. LouisWUSTL
Document Type: Article
Publication Stage: Final
Source: Scopus
Pharmacological and Biophysical Characteristics of Picrotoxin-Resistant, δSubunit-Containing GABAA Receptors
(2021) Frontiers in Synaptic Neuroscience, 13, art. no. 763411, .
Shu, H.-J.a , Lu, X.a , Bracamontes, J.b , Steinbach, J.H.b c , Zorumski, C.F.a c d , Mennerick, S.a c d
a Department of Psychiatry, Washington University in St. Louis, School of Medicine, St. Louis, MO, United States
b Department of Anesthesiology, Washington University in St. Louis, School of Medicine, St. Louis, MO, United States
c Taylor Family Institute for Innovative Psychiatric Research, Washington University in St. Louis, School of Medicine, St. Louis, MO, United States
d Department of Neuroscience, Washington University in St. Louis, School of Medicine, St. Louis, MO, United States
Abstract
GABAA receptors (GABAARs) play a crucial role in inhibition in the central nervous system. GABAARs containing the δ subunit mediate tonic inhibition, have distinctive pharmacological properties and are associated with disorders of the nervous system. To explore this receptor sub-class, we recently developed mice with δ-containing receptors rendered resistant to the common non-competitive antagonist picrotoxin (PTX). Resistance was achieved with a knock-in point mutation (T269Y; T6’Y) in the mouse genome. Here we characterize pharmacological and biophysical features of GABAARs containing the mutated subunit to contextualize results from the KI mice. Recombinant receptors containing δ T6’Y plus WT α4 and WT β2 subunits exhibited 3-fold lower EC50 values for GABA but not THIP. GABA EC50 values in native receptors containing the mutated subunit were in the low micromolar range, in contrast with some published results that have suggested nM sensitivity of recombinant receptors. Rectification properties of δ-containing GABAARs were similar to γ2-containing receptors. Receptors containing δ T6’Y had marginally weaker sensitivity to positive allosteric modulators, likely a secondary consequence of differing GABA sensitivity. Overexpression of δT6’Y in neurons resulted in robust PTX-insensitive IPSCs, suggesting that δ-containing receptors are readily recruited by synaptically released GABA. Overall, our results give context to the use of δ receptors with the T6’Y mutation to explore the roles of δ-containing receptors in inhibition. Copyright © 2021 Shu, Lu, Bracamontes, Steinbach, Zorumski and Mennerick.
Author Keywords
antidepressant; dentate gyrus; ethanol; GABA allosteric modulators; inhibition; neurosteroid
Funding details
National Institutes of HealthNIHAA026753, MH111461, MH114866, MH122379, MH123748
Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine in St. Louis
Document Type: Article
Publication Stage: Final
Source: Scopus
Does Data-Independent Acquisition Data Contain Hidden Gems? A Case Study Related to Alzheimer’s Disease
(2021) Journal of Proteome Research, .
Hubbard, E.E.a , Heil, L.R.b , Merrihew, G.E.b , Chhatwal, J.P.c , Farlow, M.R.d , Mclean, C.A.e , Ghetti, B.f , Newell, K.L.f , Frosch, M.P.g , Bateman, R.J.h , Larson, E.B.i , Keene, C.D.j , Perrin, R.J.l , Montine, T.J.k , Maccoss, M.J.b , Julian, R.R.a
a Department of Chemistry, University of California, Riverside, CA 92521, United States
b Department of Genome Sciences, University of Washington, Seattle, WA 98195, United States
c Massachusetts General Hospital, Department of Neurology, Harvard Medical School, 15 Parkman St, Suite 835, Boston, MA 02114, United States
d Department of Neurology, Indiana University School of Medicine, Indianapolis, IN 46202, United States
e Department of Anatomical Pathology, Alfred Health, Melbourne, VIC 3004, Australia
f Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, United States
g C.S. Kubik Laboratory for Neuropathology, Massachusetts Alzheimer Disease Research Center, Massachusetts General Hospital, Boston, MA 02114, United States
h Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, Missouri 63110, United States
i Kaiser Permanente Washington Health Research Institute, Department of Medicine, University of Washington, Seattle, WA 98195, United States
j Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, United States
k Department of Pathology, Stanford University, Stanford, CA 94305, United States
l Department of Pathology and Immunology, Department of Neurology, Washington University School of Medicine, Saint Louis, Missouri 63110, United States
Abstract
One of the potential benefits of using data-independent acquisition (DIA) proteomics protocols is that information not originally targeted by the study may be present and discovered by subsequent analysis. Herein, we reanalyzed DIA data originally recorded for global proteomic analysis to look for isomerized peptides, which occur as a result of spontaneous chemical modifications to long-lived proteins. Examination of a large set of human brain samples revealed a striking relationship between Alzheimer’s disease (AD) status and isomerization of aspartic acid in a peptide from tau. Relative to controls, a surprising increase in isomer abundance was found in both autosomal dominant and sporadic AD samples. To explore potential mechanisms that might account for these observations, quantitative analysis of proteins related to isomerization repair and autophagy was performed. Differences consistent with reduced autophagic flux in AD-related samples relative to controls were found for numerous proteins, including most notably p62, a recognized indicator of autophagic inhibition. These results suggest, but do not conclusively demonstrate, that lower autophagic flux may be strongly associated with loss of function in AD brains. This study illustrates that DIA data may contain unforeseen results of interest and may be particularly useful for pilot studies investigating new research directions. In this case, a promising target for future investigations into the therapy and prevention of AD has been identified. © 2021 The Authors. Published by American Chemical Society.
Author Keywords
age-related neurodegenerative disease; amyloid; amyloid-beta; aspartic acid; hippocampus; lysosome; neurofibrillary tangle; post-translational modification; proteomics; proteostasis
Funding details
P30 AG062421, U19 AG032438, UF1AG032438
National Institutes of HealthNIHP30 AG066509, R01 AG066626, RF1 AG053959, U01 AG006781
National Institute on AgingNIA
Alzheimer’s Disease Research Center, Emory UniversityADRC
Nancy and Buster Alvord Endowment
Japan Agency for Medical Research and DevelopmentAMED
Korea Health Industry Development InstituteKHIDI
Deutsches Zentrum für Neurodegenerative ErkrankungenDZNE
Fleni
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Different rates of cognitive decline in autosomal dominant and late-onset Alzheimer disease
(2021) Alzheimer’s and Dementia, .
Buckles, V.D.a , Xiong, C.b , Bateman, R.J.a , Hassenstab, J.a , Allegri, R.c , Berman, S.B.d , Chhatwal, J.P.e , Danek, A.f , Fagan, A.M.a , Ghetti, B.g , Goate, A.h , Graff-Radford, N.i , Jucker, M.j , Levin, J.k , Marcus, D.S.l , Masters, C.L.m , McCue, L.b , McDade, E.a , Mori, H.n , Moulder, K.L.a , Noble, J.M.o , Paumier, K.a , Preische, O.p , Ringman, J.M.q , Fox, N.C.r , Salloway, S.s , Schofield, P.R.t , Martins, R.u , Vöglein, J.v , Morris, J.C.a , for the Dominantly Inherited Alzheimer’s Networkw
a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
b Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
c Institute for Neurological Research (FLENI), Buenos Aires, Argentina
d Department of Neurology and Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA, United States
e Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
f Neurologische Klinik und Poliklinik, Klinikum der Universität München, Munich, Germany
g Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, United States
h Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
i Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
j DZNE Tuebingen & Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
k DZNE Munich, Munich Cluster of Systems Neurology (SyNergy) & Ludwig-Maximilians-Universität, Munich, Germany
l Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
m Florey Institute, University of Melbourne, Melbourne, Australia
n Department of Neuroscience, Osaka City University Medical School, Osaka City, Japan
o Department of Neurology, Taub Institute for Research on Aging Brain, Columbia University Irving Medical Center, New York, NY, United States
p DZNE Tuebingen & University of Tuebingen, Tuebingen, Germany
q Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
r Department of Neurodegenerative Disease & UK Dementia Research Institute, Institute of Neurology, London, United Kingdom
s Department of Neurology, Butler Hospital & Alpert Medical School of Brown University, Providence, RI, United States
t Neuroscience Research Australia & School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
u Sir James McCusker Alzheimer’s Disease Research Unit, Edith Cowan University, Nedlands, WA, Australia
v German Center for Neurodegenerative Diseases (DZNE) and Department of Neurology, Ludwig-Maximilians Universität München, Munich, Germany
Abstract
As prevention trials advance with autosomal dominant Alzheimer disease (ADAD) participants, understanding the similarities and differences between ADAD and “sporadic” late-onset AD (LOAD) is critical to determine generalizability of findings between these cohorts. Cognitive trajectories of ADAD mutation carriers (MCs) and autopsy-confirmed LOAD individuals were compared to address this question. Longitudinal rates of change on cognitive measures were compared in ADAD MCs (n = 310) and autopsy-confirmed LOAD participants (n = 163) before and after symptom onset (estimated/observed). LOAD participants declined more rapidly in the presymptomatic (preclinical) period and performed more poorly at symptom onset than ADAD participants on a cognitive composite. After symptom onset, however, the younger ADAD MCs declined more rapidly. The similar but not identical cognitive trajectories (declining but at different rates) for ADAD and LOAD suggest common AD pathologies but with some differences. © 2021 the Alzheimer’s Association
Author Keywords
Alzheimer disease; autosomal dominant Alzheimer disease; cognitive; comorbidities; late-onset Alzheimer disease
Funding details
National Institutes of HealthNIHU24 AG072122
National Institute on AgingNIA
Doris Duke Charitable FoundationDDCF
JPB Foundation
Japan Agency for Medical Research and DevelopmentAMED
Rainwater Charitable FoundationRCF
Medical Research CouncilMRCMR/009076/1, MR/L023784/1
National Health and Medical Research CouncilNHMRC
Deutsches Zentrum für Neurodegenerative ErkrankungenDZNE
UCLH Biomedical Research CentreNIHR BRC
Fleni
Document Type: Article
Publication Stage: Article in Press
Source: Scopus