Airy-beam holographic sonogenetics for advancing neuromodulation precision and flexibility
(2024) Proceedings of the National Academy of Sciences of the United States of America, 121 (26), pp. e2402200121.
Hu, Z.a , Yang, Y.a , Yang, L.a , Gong, Y.a , Chukwu, C.a , Ye, D.a , Yue, Y.a , Yuan, J.a , Kravitz, A.V.b , Chen, H.a c d
a Department of Biomedical Engineering, Washington University in St. LouisSaint Louis MO 63130, Seychelles
b Department of Psychiatry, Washington University School of MedicineSaint Louis MO 63110, Seychelles
c Department of Neurosurgery, Washington University School of MedicineSaint Louis MO 63110, Seychelles
d Mallinckrodt Institute of Radiology, Washington University School of MedicineSaint Louis MO 63110, Seychelles
Abstract
Advancing our understanding of brain function and developing treatments for neurological diseases hinge on the ability to modulate neuronal groups in specific brain areas without invasive techniques. Here, we introduce Airy-beam holographic sonogenetics (AhSonogenetics) as an implant-free, cell type-specific, spatially precise, and flexible neuromodulation approach in freely moving mice. AhSonogenetics utilizes wearable ultrasound devices manufactured using 3D-printed Airy-beam holographic metasurfaces. These devices are designed to manipulate neurons genetically engineered to express ultrasound-sensitive ion channels, enabling precise modulation of specific neuronal populations. By dynamically steering the focus of Airy beams through ultrasound frequency tuning, AhSonogenetics is capable of modulating neuronal populations within specific subregions of the striatum. One notable feature of AhSonogenetics is its ability to flexibly stimulate either the left or right striatum in a single mouse. This flexibility is achieved by simply switching the acoustic metasurface in the wearable ultrasound device, eliminating the need for multiple implants or interventions. AhSonogentocs also integrates seamlessly with in vivo calcium recording via fiber photometry, showcasing its compatibility with optical modalities without cross talk. Moreover, AhSonogenetics can generate double foci for bilateral stimulation and alleviate motor deficits in Parkinson’s disease mice. This advancement is significant since many neurological disorders, including Parkinson’s disease, involve dysfunction in multiple brain regions. By enabling precise and flexible cell type-specific neuromodulation without invasive procedures, AhSonogenetics provides a powerful tool for investigating intact neural circuits and offers promising interventions for neurological disorders.
Author Keywords
Airy beam; focused ultrasound; hologram; neuromodulation; sonogenetics
Document Type: Article
Publication Stage: Final
Source: Scopus
Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia
(2024) Science Advances, 10 (25), p. eadj9173.
Bhuiyan, S.A.a , Xu, M.a b , Yang, L.a c , Semizoglou, E.a , Bhatia, P.a , Pantaleo, K.I.a , Tochitsky, I.d , Jain, A.d , Erdogan, B.e , Blair, S.e , Cat, V.e , Mwirigi, J.M.f , Sankaranarayanan, I.f , Tavares-Ferreira, D.f , Green, U.g , McIlvried, L.A.c , Copits, B.A.c , Bertels, Z.c , Del Rosario, J.S.c , Widman, A.J.c , Slivicki, R.A.c , Yi, J.c , Sharif-Naeini, R.b , Woolf, C.J.d , Lennerz, J.K.g , Whited, J.L.e , Price, T.J.f , Robert W Gereau Ivc , Renthal, W.a
a Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, United States
b Alan Edwards Center for Research on Pain and Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada
c Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, MO 63110, United States
d F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children’s Hospital and Harvard Medical School, 3 Blackfan Cir., Boston, MA 02115, United States
e Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, United States
f Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX 75080, United States
g Department of Pathology, Center for Integrated Diagnostics, Massachussetts General Hospital and Havard Medical School, Boston, MA 02114, United States
Abstract
Sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli to the central nervous system. Single-cell RNA sequencing has provided insights into the diversity of sensory ganglia cell types in rodents, nonhuman primates, and humans, but it remains difficult to compare cell types across studies and species. We thus constructed harmonized atlases of the DRG and TG that describe and facilitate comparison of 18 neuronal and 11 non-neuronal cell types across six species and 31 datasets. We then performed single-cell/nucleus RNA sequencing of DRG from both human and the highly regenerative axolotl and found that the harmonized atlas also improves cell type annotation, particularly of sparse neuronal subtypes. We observed that the transcriptomes of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The resources presented here can guide future studies in comparative transcriptomics, simplify cell-type nomenclature differences across studies, and help prioritize targets for future analgesic development.
Document Type: Article
Publication Stage: Final
Source: Scopus
An interpretable machine learning-based cerebrospinal fluid proteomics clock for predicting age reveals novel insights into brain aging
(2024) Aging Cell, .
Melendez, J.a b , Sung, Y.J.c d , Orr, M.e , Yoo, A.f , Schindler, S.b , Cruchaga, C.b c , Bateman, R.a b
a Tracy Family SILQ Center, Washington University in St. Louis, St. Louis, MO, United States
b Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
c Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
d Department of Biostatistics, Washington University in St. Louis, St. Louis, MO, United States
e Department of Internal Medicine, Wake Forest School of Medicine Section of Gerontology and Geriatric Medicine Medical Center Boulevard, Winston-Salem, NC, United States
f Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Machine learning can be used to create “biologic clocks” that predict age. However, organs, tissues, and biofluids may age at different rates from the organism as a whole. We sought to understand how cerebrospinal fluid (CSF) changes with age to inform the development of brain aging-related disease mechanisms and identify potential anti-aging therapeutic targets. Several epigenetic clocks exist based on plasma and neuronal tissues; however, plasma may not reflect brain aging specifically and tissue-based clocks require samples that are difficult to obtain from living participants. To address these problems, we developed a machine learning clock that uses CSF proteomics to predict the chronological age of individuals with a 0.79 Pearson correlation and mean estimated error (MAE) of 4.30 years in our validation cohort. Additionally, we analyzed proteins highly weighted by the algorithm to gain insights into changes in CSF and uncover novel insights into brain aging. We also demonstrate a novel method to create a minimal protein clock that uses just 109 protein features from the original clock to achieve a similar accuracy (0.75 correlation, MAE 5.41). Finally, we demonstrate that our clock identifies novel proteins that are highly predictive of age in interactions with other proteins, but do not directly correlate with chronological age themselves. In conclusion, we propose that our CSF protein aging clock can identify novel proteins that influence the rate of aging of the central nervous system (CNS), in a manner that would not be identifiable by examining their individual relationships with age. © 2024 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
Author Keywords
aging; brain aging; cerebrospinal fluid; neurodegeneration; neurodegenerative diseases; proteomics
Funding details
Hope Center for Neurological Disorders, Washington University in St. Louis
Chan Zuckerberg InitiativeCZI
Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. LouisKGAD
University of WashingtonUW
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
National Institutes of HealthNIHR01AG044546, RF1AG058501, RF1AG074007, U01AG058922, RF1AG053303, P30AG066444, P01AG026276, P01AG003991
National Institutes of HealthNIH
Alzheimer’s Disease Neuroimaging InitiativeADNIU19 AG024904
Alzheimer’s Disease Neuroimaging InitiativeADNI
U.S. Department of DefenseDODW81XWH‐12‐2‐0012
U.S. Department of DefenseDOD
Alzheimer’s AssociationAAZEN‐22‐848604
Alzheimer’s AssociationAA
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Statistical considerations when estimating time-saving treatment effects in Alzheimer’s disease clinical trials
(2024) Alzheimer’s and Dementia, .
Wang, G.a b , Cutter, G.c , Oxtoby, N.P.d , Shan, G.e , Wang, W.f , Mangal, B.g , Liao, Y.h , Llibre-Guerra, J.J.a , Li, Y.a , Xiong, C.b , McDade, E.a , Delmar, P.i , Bateman, R.J.a , Schneider, L.j
a Department of Neurology, Division of Biostatistics, School of Medicine, Washington University, St. Louis, MO, United States
b Division of Biostatistics, Washington University, School of Medicine, St. Louis, MO, United States
c Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
d Department of Computer Science, University College London, London, United Kingdom
e Department of Biostatistics, University of Florida, Gainesville, FL, United States
f Tenaya Therapeutics, South San Francisco, CA, United States
g Solara Consulting Corp., North Vancouver, BC, Canada
h Neogene Therapeutics, Inc., Santa Monica, CA, United States
i F. Hoffmann-La Roche Ltd., Basel, Switzerland
j Department of Psychiatry and The Behavioral Sciences, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
Abstract
INTRODUCTION: Estimating treatment effects as time savings in disease progression may be more easily interpretable than assessing the absolute difference or a percentage reduction. In this study, we investigate the statistical considerations of the existing method for estimating time savings and propose alternative complementary methods. METHODS: We propose five alternative methods to estimate the time savings from different perspectives. These methods are applied to simulated clinical trial data that mimic or modify the Clinical Dementia Rating Sum of Boxes progression trajectories observed in the Clarity AD lecanemab trial. RESULTS: Our study demonstrates that the proposed methods can generate more precise estimates by considering two crucial factors: (1) the absolute difference between treatment arms, and (2) the observed progression rate in the treatment arm. DISCUSSION: Quantifying treatment effects as time savings in disease progression offers distinct advantages. To provide comprehensive estimations, it is important to use various methods. Highlights: We explore the statistical considerations of the current method for estimating time savings. We proposed alternative methods that provide time savings estimations based on the observed absolute differences. By using various methods, a more comprehensive estimation of time savings can be achieved. © 2024 The Author(s). Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.
Author Keywords
Alzheimer’s disease; proportional mixed models for repeated measures; semi-real trial data; time savings
Funding details
Alzheimer’s AssociationAA
Avid Radiopharmaceuticals
Biogen
GHR FoundationGHR
Roche Canada
National Institute on AgingNIA
UK Research and InnovationUKRIK01AG073526, AG067505, AARFD‐21‐851415, SG‐20‐690363
UK Research and InnovationUKRI
Foundation for the National Institutes of HealthFNIHR01AG046179, R01AG053267‐S1
Foundation for the National Institutes of HealthFNIH
National Institutes of HealthNIHU01AG042791
National Institutes of HealthNIH
Document Type: Article
Publication Stage: Article in Press
Source: Scopus