Investigating the impact of electroconvulsive therapy on brain networks and sleep: An observational study protocol
(2025) BMJ Open, 15 (3), art. no. e098859, .
Kafashan, M.a b , Lebovitz, L.c , Greenspan, R.a , Zhao, S.d , Kim, T.e , Husain, M.d f , Hershey, T.c e g h , Cristancho, P.c , Hogan, R.E.e , Palanca, B.J.A.a b c i j , Farber, N.B.c
a Department of Anesthesiology, Washington University, School of Medicine in St Louis, St. Louis, MO, United States
b Center on Biological Rhythms and Sleep, Washington University, School of Medicine in St Louis, St. Louis, MO, United States
c Department of Psychiatry, Washington University, School of Medicine in St Louis, St. Louis, MO, United States
d Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
e Department of Neurology, Washington University, School of Medicine in St Louis, St. Louis, MO, United States
f Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
g Department of Radiology, Washington University, School of Medicine in St. Louis, St. Louis, MO, United States
h Department of Psychological and Brain Sciences, Washington University in St Louis, St. Louis, MO, United States
i Division of Biology and Biomedical Sciences, Washington University, School of Medicine in St. Louis, St. Louis, MO, United States
j Department of Biomedical Engineering, Washington University in St Louis, St. Louis, MO, United States
Abstract
Introduction Electroconvulsive therapy (ECT) is a highly effective treatment for refractory depression, but it may also cause cognitive side effects. Despite decades of use, the mechanisms by which ECT exerts both its antidepressant and cognitive effects are still poorly understood, with the latter substantially limiting referral and adherence to therapy. ECT induces changes in correlated neural activity – functional connectivity – across various brain networks, which may underlie both its clinical efficacy and associated cognitive side effects. Electroencephalography (EEG) could address these knowledge gaps by identifying biomarkers that predict therapeutic outcomes or cognitive side effects. Such developments could ultimately improve patient selection and adherence. Such markers likely span large-scale functional brain networks or temporal dynamics of brain activity during sleep. We hypothesise that enhancement in slow wave sleep mediates the relationship between antidepressant effects and changes in functional connectivity throughout the course of ECT. Methods and analysis Disruptions of Brain Networks and Sleep by Electroconvulsive Therapy (DNS-ECT) is an ongoing observational study investigating the impact of ECT on large-scale brain functional networks and their relationships to sleep slow waves, an EEG marker linked to synaptic plasticity. The novelty of this study stems from our focus on the assessment of EEG markers during sleep, wakefulness and ECT-induced seizures over the course of therapy. Graph-based network analyses of high-density EEG signals allow characterisation of functional networks locally in specific subnetworks and globally over large-scale functional networks. Longitudinal assessments of EEG alongside clinical and cognitive outcomes provide a unique opportunity to improve our understanding of the circuit mechanisms underlying the development of cognitive impairments and antidepressant effects incurred during ECT. Ethics and dissemination Recruitment for this 5-year study started in March 2023. Dissemination plans include presentations at scientific conferences and peer-reviewed publications. This study has been registered with ClinicalTrials.gov registry under identifier. © Author(s) (or their employer(s)) 2025.
Author Keywords
Cognition; Depression & mood disorders; Electroencephalography; SLEEP MEDICINE
Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMHK01MH128663, R25MH112473
National Institute of Mental HealthNIMH
Document Type: Article
Publication Stage: Final
Source: Scopus
Proteome-wide assessment of differential missense variant clustering in neurodevelopmental disorders and cancer
(2025) Cell Genomics, art. no. 100807, .
Ng, J.K.a , Chen, Y.b , Akinwe, T.M.a c , Heins, H.B.a , Mehinovic, E.a , Chang, Y.a d , Gutmann, D.H.e , Gurnett, C.A.e f , Payne, Z.L.a c , Manuel, J.G.a , Karchin, R.b g h i , Turner, T.N.a f
a Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
b Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, United States
c Molecular Genetics & Genomics Graduate Program, Washington University School of Medicine, St. Louis, MO 63110, United States
d Human & Statistical Genetics Graduate Program, Washington University School of Medicine, St. Louis, MO 63110, United States
e Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States
f Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO 63110, United States
g Department of Computer Science, Johns Hopkins University, Baltimore, MD 21205, United States
h The Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, United States
i Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21205, United States
Abstract
Prior studies examining genomic variants suggest that some proteins contribute to both neurodevelopmental disorders (NDDs) and cancer. While there are several potential etiologies, here, we hypothesize that missense variation in proteins occurs in different clustering patterns, resulting in distinct phenotypic outcomes. This concept was first explored in 1D protein space and expanded using 3D protein structure models. Missense de novo variants were examined from 39,883 families with NDDs and missense somatic variants from 10,543 sequenced tumors covering five The Cancer Genome Atlas (TCGA) cancer types and two Catalog of Somatic Mutations in Cancer (COSMIC) pan-cancer aggregates of tissue types. We find 18 proteins with differential missense variation clustering in NDDs compared to cancers and 19 in cancers relative to NDDs. These proteins may be important for detailed assessments in thinking of future prognostic and therapeutic applications. We establish a framework for interpreting missense patterns in NDDs and cancer, using advances in 3D protein structure prediction. © 2025 The Author(s)
Author Keywords
3D protein structure models; cancer; clustering algorithm; de novo; missense; neurodevelopmental disorders; protein; somatic; variant interpretation
Funding details
Intellectual and Developmental Disabilities Research CenterIDDRC
McDonnell Center for Cellular and Molecular Neurobiology, Washington University in St. Louis
Intellectual and Developmental Disabilities Research Center, School of Medicine, Washington University in St. LouisIDDRC
Instituto Tecnológico de Costa RicaITCR
Simons FoundationSF734069
Simons FoundationSF
National Institutes of HealthNIHR00MH117165, P50HD103525, R01MH126933
National Institutes of HealthNIH
National Cancer InstituteNCIU24CA258393
National Cancer InstituteNCI
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
In vivo two-photon microscopy imaging of focused ultrasound-mediated glymphatic transport in the mouse brain
(2025) Journal of Cerebral Blood Flow and Metabolism, .
Gong, Y.a , Xu, K.a , Ye, D.a , Yang, Y.a , Miller, M.J.b , Feng, Z.a , Hu, S.a , Chen, H.a c
a Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
b Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
c Department of Neurosurgery, Washington University School of Medicine, St. LouisMO 63110, United States
Abstract
The glymphatic system regulates cerebrospinal fluid (CSF) transport and brain waste clearance. Focused ultrasound combined with microbubbles (FUSMB) has shown feasibility for manipulating glymphatic transport, yet its mechanisms remain poorly understood. In this work, we used in vivo two-photon microscopy to reveal how FUSMB manipulates the CSF tracer transport in the mouse brain. A FUS transducer was confocally aligned with the objective of a two-photon microscope. Fluorescently labeled albumin was infused into the CSF via cisterna magna. FUS sonication was applied following an intravenous injection of microbubbles. Dynamic imaging was performed through a cranial window to record local changes in vessel and tracer dynamics. The fluorescence intensity of the CSF tracer within the treated region decreased rapidly upon FUSMB treatment. Concurrently, vessel deformation was observed, and the fastest diameter changes were observed during FUSMB treatment. A linear correlation was identified between the rate of vessel diameter change and the rate of tracer intensity change. Moreover, given the same rate of vessel diameter change, the tracer intensity changed faster around larger vessels than smaller vessels. These findings offer insight into the potential biophysical mechanism of FUSMB-mediated glymphatic transport. © The Author(s) 2025.
Author Keywords
Brain; focused ultrasound; glymphatic system; microbubbles; two-photon microscopy
Funding details
Focused Ultrasound FoundationFUF
National Institutes of HealthNIHR01EB030102, R01NS128461, UG3MH126861, R01CA276174, R01EB027223
National Institutes of HealthNIH
Document Type: Article
Publication Stage: Article in Press
Source: Scopus