Fast and slow: Recording neuromodulator dynamics across both transient and chronic time scales
(2024) Science Advances, 10 (8), p. eadi0643.
Ma, P.a b , Chen, P.a c , Tilden, E.I.a b , Aggarwal, S.a , Oldenborg, A.a , Chen, Y.a
a Department of Neuroscience, Washington University, St. Louis, MO 63110, United States
b Ph.D. Program in Neuroscience, Washington University, St. Louis, MO 63110, United States
c Master’s Program in Biomedical Engineering, Washington University, St. Louis, MO 63110, United States
Abstract
Neuromodulators transform animal behaviors. Recent research has demonstrated the importance of both sustained and transient change in neuromodulators, likely due to tonic and phasic neuromodulator release. However, no method could simultaneously record both types of dynamics. Fluorescence lifetime of optical reporters could offer a solution because it allows high temporal resolution and is impervious to sensor expression differences across chronic periods. Nevertheless, no fluorescence lifetime change across the entire classes of neuromodulator sensors was previously known. Unexpectedly, we find that several intensity-based neuromodulator sensors also exhibit fluorescence lifetime responses. Furthermore, we show that lifetime measures in vivo neuromodulator dynamics both with high temporal resolution and with consistency across animals and time. Thus, we report a method that can simultaneously measure neuromodulator change over transient and chronic time scales, promising to reveal the roles of multi-time scale neuromodulator dynamics in diseases, in response to therapies, and across development and aging.
Document Type: Article
Publication Stage: Final
Source: Scopus
Functional parcellation of the neonatal cortical surface
(2024) Cerebral Cortex, 34 (2), art. no. bhae047, .
Myers, M.J.a , Labonte, A.K.a b , Gordon, E.M.c , Laumann, T.O.a , Tu, J.C.b c , Wheelock, M.D.c , Nielsen, A.N.a , Schwarzlose, R.F.a , Camacho, M.C.a , Alexopoulos, D.d , Warner, B.B.e , Raghuraman, N.f , Luby, J.L.a , Barch, D.M.a g , Fair, D.A.h i j , Petersen, S.E.c d , Rogers, C.E.a , Smyser, C.D.c d e , Sylvester, C.M.a c k
a Department of Psychiatry, Washington University in St. Louis, St. Louis, MO 63110, United States
b Neurosciences Graduate Program, Washington University in St. Louis, St. Louis, MO 63110, United States
c Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
d Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
e Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
f Department of Obstetrics and Gynecology, Washington University School of Medicine, St. Louis, MO 63110, United States
g Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO 63110, United States
h Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55414, United States
i Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, United States
j Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, United States
k Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
The cerebral cortex is organized into distinct but interconnected cortical areas, which can be defined by abrupt differences in patterns of resting state functional connectivity (FC) across the cortical surface. Such parcellations of the cortex have been derived in adults and older infants, but there is no widely used surface parcellation available for the neonatal brain. Here, we first demonstrate that existing parcellations, including surface-based parcels derived from older samples as well as volume-based neonatal parcels, are a poor fit for neonatal surface data. We next derive a set of 283 cortical surface parcels from a sample of n = 261 neonates. These parcels have highly homogenous FC patterns and are validated using three external neonatal datasets. The Infomap algorithm is used to assign functional network identities to each parcel, and derived networks are consistent with prior work in neonates. The proposed parcellation may represent neonatal cortical areas and provides a powerful tool for neonatal neuroimaging studies. © The Author(s) 2024. Published by Oxford University Press. All rights reserved.
Author Keywords
cortical areas; fMRI; functional connectivity; neonate; parcellation
Funding details
National Institute of Mental HealthNIMHR01MH122389, R01MH131584
National Institute on Drug AbuseNIDAR01DA046224, U24DA055330
National Institute of Child Health and Human DevelopmentNICHDK99HD109454
Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine in St. LouisIDDRCP50 HD103525
Document Type: Article
Publication Stage: Final
Source: Scopus
Sarm1 knockout prevents type 1 diabetic bone disease in females independent of neuropathy
(2024) JCI insight, 9 (4), .
Brazill, J.M.a , Shen, I.R.a , Craft, C.S.a , Magee, K.L.a , Park, J.S.a , Lorenz, M.a , Strickland, A.b , Wee, N.K.a , Zhang, X.a c , Beeve, A.T.a c , Meyer, G.A.d , Milbrandt, J.b , DiAntonio, A.e , Scheller, E.L.a c e f
a Division of Bone and Mineral Diseases, Department of Medicine
b Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
c Department of Biomedical Engineering, McKelvey School of Engineering, Washington University, St. Louis, MO, United States
d Program in Physical Therapy
e Department of Developmental Biology
f Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Patients with diabetes have a high risk of developing skeletal diseases accompanied by diabetic peripheral neuropathy (DPN). In this study, we isolated the role of DPN in skeletal disease with global and conditional knockout models of sterile-α and TIR-motif-containing protein-1 (Sarm1). SARM1, an NADase highly expressed in the nervous system, regulates axon degeneration upon a range of insults, including DPN. Global knockout of Sarm1 prevented DPN, but not skeletal disease, in male mice with type 1 diabetes (T1D). Female wild-type mice also developed diabetic bone disease but without DPN. Unexpectedly, global Sarm1 knockout completely protected female mice from T1D-associated bone suppression and skeletal fragility despite comparable muscle atrophy and hyperglycemia. Global Sarm1 knockout rescued bone health through sustained osteoblast function with abrogation of local oxidative stress responses. This was independent of the neural actions of SARM1, as beneficial effects on bone were lost with neural conditional Sarm1 knockout. This study demonstrates that the onset of skeletal disease occurs rapidly in both male and female mice with T1D completely independently of DPN. In addition, this reveals that clinical SARM1 inhibitors, currently being developed for treatment of neuropathy, may also have benefits for diabetic bone through actions outside of the nervous system.
Author Keywords
Bone Biology; Bone disease; Diabetes; Endocrinology; Neurodegeneration
Document Type: Article
Publication Stage: Final
Source: Scopus
Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage
(2024) Alzheimer’s and Dementia, .
Joseph-Mathurin, N.a , Feldman, R.L.a , Lu, R.a , Shirzadi, Z.b , Toomer, C.a c , Saint Clair, J.R.a d , Ma, Y.a , McKay, N.S.a , Strain, J.F.a , Kilgore, C.a , Friedrichsen, K.A.a , Chen, C.D.a , Gordon, B.A.a , Chen, G.a , Hornbeck, R.C.a , Massoumzadeh, P.a , McCullough, A.A.a , Wang, Q.a , Li, Y.a , Wang, G.a , Keefe, S.J.a , Schultz, S.A.b , Cruchaga, C.a , Preboske, G.M.e , Jack, C.R., Jr.e , Llibre-Guerra, J.J.a , Allegri, R.F.f , Ances, B.M.a , Berman, S.B.g , Brooks, W.S.h i , Cash, D.M.j , Day, G.S.k , Fox, N.C.j , Fulham, M.l , Ghetti, B.m , Johnson, K.A.b , Jucker, M.n o , Klunk, W.E.g , la Fougère, C.n p , Levin, J.q r s , Niimi, Y.t , Oh, H.u , Perrin, R.J.a , Reischl, G.n p , Ringman, J.M.c , Saykin, A.J.m , Schofield, P.R.h i , Su, Y.v , Supnet-Bell, C.a , Vöglein, J.q r , Yakushev, I.w , Brickman, A.M.x , Morris, J.C.a , McDade, E.a , Xiong, C.a , Bateman, R.J.a , Chhatwal, J.P.b , Benzinger, T.L.S.a , for the Dominantly Inherited Alzheimer Networky
a Washington University School of Medicine in Saint Louis, St. Louis, MO, United States
b Massachusetts General Hospital, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
c Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
d Meharry School of Medicine, Meharry College, Nashville, TN, United States
e Mayo Clinic, Rochester, MN, United States
f Institute for Neurological Research FLENI, Buenos Aires, Montañeses, Argentina
g University of Pittsburgh Medical Center, Pittsburgh, PA, United States
h Neuroscience Research Australia, Sydney, NSW, Australia
i University of New South Wales, Sydney, NSW, Australia
j UK Dementia Research Institute and Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
k Mayo Clinic, Jacksonville, FL, United States
l Royal Prince Alfred Hospital, Camperdown, NSW, Australia
m Indiana University School of Medicine, Indianapolis, IN, United States
n German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
o Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
p University hospital Tübingen, Tübingen, Germany
q German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
r Ludwig Maximilian University of Munich, Munich, Germany
s Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
t The University of Tokyo, Tokyo, Bunkyo City, Japan
u Brown University, Providence, RI, United States
v Banner Alzheimer Institute, Banner Health, Phoenix, AZ, United States
w Department of Nuclear Medicine, Technical University of Munich, Munich, Germany
x Columbia University Medical Center, New York, NY, United States
Abstract
INTRODUCTION: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer’s disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. METHODS: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. RESULTS: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. DISCUSSION: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. Highlights: Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aβ burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage. © 2024 The Authors. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.
Author Keywords
autosomal dominant Alzheimer’s disease (ADAD); cerebral amyloid angiopathy (CAA); codon 200; dominantly inherited Alzheimer’s disease (DIAD); microbleeds; microhemorrhages; peak width of skeletonized mean diffusivity (PSMD); PiB-PET; presenilin-1; PSEN1; small vessel disease (SVD); white matter hyperintensity (WMH)
Funding details
P30AG072980
A2022013F, AARF‐21‐722077, R01AG074909, R03AG072375, RMS2318, T32AG078117‐01
National Institutes of HealthNIH1K01AG080123‐01
National Institute on AgingNIA
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
Alzheimer’s AssociationAA
BrightFocus FoundationBFFA2023001F
Arizona State UniversityASU
Japan Agency for Medical Research and DevelopmentAMED
UK Research and InnovationUKRIMR/V03863X/1
Korea Dementia Research CenterKDRC
Medical Research CouncilMRC
Alzheimer’s Society
Alzheimer’s Research UKARUKARUK‐PG2017‐1946
Ministry of Science, ICT and Future PlanningMSIPHI21C0066
Ministry of Health and WelfareMOHW
Korea Health Industry Development InstituteKHIDI
Instituto de Salud Carlos IIIISCIIIAARFD‐20‐681815
Deutsches Zentrum für Neurodegenerative ErkrankungenDZNE
Fleni
UK Dementia Research InstituteUK DRI
Document Type: Article
Publication Stage: Article in Press
Source: Scopus