WashU weekly Neuroscience publications | Office of Neuroscience Research

“Circadian neurons in the paraventricular nucleus entrain and sustain daily rhythms in glucocorticoids” (2021) Nature Communications

Circadian neurons in the paraventricular nucleus entrain and sustain daily rhythms in glucocorticoids
(2021) Nature Communications, 12 (1), art. no. 5763, .

Jones, J.R.^a ^b , Chaturvedi, S.^a , Granados-Fuentes, D.^a , Herzog, E.D.^a

^a Department of Biology, Washington University, St. Louis, St. Louis, MO, United States
^b Department of Biology, Texas A&M University, College Station, College Station, TX, United States

Abstract
Signals from the central circadian pacemaker, the suprachiasmatic nucleus (SCN), must be decoded to generate daily rhythms in hormone release. Here, we hypothesized that the SCN entrains rhythms in the paraventricular nucleus (PVN) to time the daily release of corticosterone. In vivo recording revealed a critical circuit from SCN vasoactive intestinal peptide (SCNVIP)-producing neurons to PVN corticotropin-releasing hormone (PVNCRH)-producing neurons. PVNCRH neurons peak in clock gene expression around midday and in calcium activity about three hours later. Loss of the clock gene Bmal1 in CRH neurons results in arrhythmic PVNCRH calcium activity and dramatically reduces the amplitude and precision of daily corticosterone release. SCNVIP activation reduces (and inactivation increases) corticosterone release and PVNCRH calcium activity, and daily SCNVIP activation entrains PVN clock gene rhythms by inhibiting PVNCRH neurons. We conclude that daily corticosterone release depends on coordinated clock gene and neuronal activity rhythms in both SCNVIP and PVNCRH neurons. © 2021, The Author(s).

Funding details
National Institutes of HealthNIH
National Heart, Lung, and Blood InstituteNHLBIF32 HL133772
National Institute of General Medical SciencesNIGMSR01GM131403

Document Type: Article
Publication Stage: Final
Source: Scopus

“A human iPSC-derived inducible neuronal model of Niemann-Pick disease, type C1” (2021) BMC Biology

A human iPSC-derived inducible neuronal model of Niemann-Pick disease, type C1
(2021) BMC Biology, 19 (1), art. no. 218, .

Prabhu, A.V.^a , Kang, I.^a , De Pace, R.^b , Wassif, C.A.^a , Fujiwara, H.^c , Kell, P.^c , Jiang, X.^c , Ory, D.S.^d , Bonifacino, J.S.^b , Ward, M.E.^e , Porter, F.D.^a

^a Division of Translational Medicine, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, DHHS, 10CRC, Rm. 5-2571, 10 Center Dr, Bethesda, MD, United States
^b Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, DHHS, Bethesda, MD 20892, United States
^c Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
^d Diabetic Cardiovascular Disease Center, Washington University School of Medicine, St. Louis, MO 63110, United States
^e National Institute of Neurological Disorders and Stroke, National Institutes of Health, DHHS, Bethesda, MD 20892, United States

Abstract
Background: Niemann-Pick disease, type C (NPC) is a childhood-onset, lethal, neurodegenerative disorder caused by autosomal recessive mutations in the genes NPC1 or NPC2 and characterized by impaired cholesterol homeostasis, a lipid essential for cellular function. Cellular cholesterol levels are tightly regulated, and mutations in either NPC1 or NPC2 lead to deficient transport and accumulation of unesterified cholesterol in the late endosome/lysosome compartment, and progressive neurodegeneration in affected individuals. Previous cell-based studies to understand the NPC cellular pathophysiology and screen for therapeutic agents have mainly used patient fibroblasts. However, these do not allow modeling the neurodegenerative aspect of NPC disease, highlighting the need for an in vitro system that permits understanding the cellular mechanisms underlying neuronal loss and identifying appropriate therapies. This study reports the development of a novel human iPSC-derived, inducible neuronal model of Niemann-Pick disease, type C1 (NPC1). Results: We generated a null i3Neuron (inducible × integrated × isogenic) (NPC1−/− i3Neuron) iPSC-derived neuron model of NPC1. The NPC1−/− and the corresponding isogenic NPC1+/+ i3Neuron cell lines were used to efficiently generate homogenous, synchronized neurons that can be used in high-throughput screens. NPC1−/− i3Neurons recapitulate cardinal cellular NPC1 pathological features including perinuclear endolysosomal storage of unesterified cholesterol, accumulation of GM2 and GM3 gangliosides, mitochondrial dysfunction, and impaired axonal lysosomal transport. Cholesterol storage, mitochondrial dysfunction, and axonal trafficking defects can be ameliorated by treatment with 2-hydroxypropyl-β-cyclodextrin, a drug that has shown efficacy in NPC1 preclinical models and in a phase 1/2a trial. Conclusion: Our data demonstrate the utility of this new cell line in high-throughput drug/chemical screens to identify potential therapeutic agents. The NPC1−/− i3Neuron line will also be a valuable tool for the NPC1 research community to explore the pathological mechanisms contributing to neuronal degeneration. Graphical abstract: [Figure not available: see fulltext.] © 2021, The Author(s).

Author Keywords
Human induced pluripotent stem cells; Human neurons; Lysosomal disease; Neurodegeneration; Niemann-Pick disease, type C1; NPC1

Funding details
National Institutes of HealthNIH
National Heart, Lung, and Blood InstituteNHLBI
National Institute of Biomedical Imaging and BioengineeringNIBIB
Ara Parseghian Medical Research FoundationAPMRF
National Center for Advancing Translational SciencesNCATS
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD

Document Type: Article
Publication Stage: Final
Source: Scopus

“Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group” (2021) Translational Psychiatry

Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group
(2021) Translational Psychiatry, 11 (1), art. no. 502, .

Harrewijn, A.^a , Cardinale, E.M.^a , Groenewold, N.A.^b , Bas-Hoogendam, J.M.^c ^d ^e , Aghajani, M.^f ^g , Hilbert, K.^h , Cardoner, N.ⁱ ^j ^k , Porta-Casteràs, D.ⁱ ^j ^k , Gosnell, S.^l , Salas, R.^l , Jackowski, A.P.^m , Pan, P.M.^m , Salum, G.A.ⁿ , Blair, K.S.^o , Blair, J.R.^o , Hammoud, M.Z.^p , Milad, M.R.^p , Burkhouse, K.L.^q , Phan, K.L.^r , Schroeder, H.K.^s , Strawn, J.R.^s , Beesdo-Baum, K.^t , Jahanshad, N.^u , Thomopoulos, S.I.^u , Buckner, R.^v ^w , Nielsen, J.A.^v ^w ^x , Smoller, J.W.^w , Soares, J.C.^y , Mwangi, B.^y , Wu, M.-J.^y , Zunta-Soares, G.B.^y , Assaf, M.^z ^aa , Diefenbach, G.J.^aa ^ab , Brambilla, P.^ac ^ad , Maggioni, E.^ac , Hofmann, D.^ae , Straube, T.^ae , Andreescu, C.^af , Berta, R.^af , Tamburo, E.^af , Price, R.B.^af ^ag , Manfro, G.G.^ah , Agosta, F.^ai ^aj , Canu, E.^ai , Cividini, C.^ai ^aj , Filippi, M.^ai ^aj ^ak ^al ^am , Kostić, M.^an ^ao , Munjiza Jovanovic, A.^an , Alberton, B.A.V.^ap , Benson, B.^a , Freitag, G.F.^a , Filippi, C.A.^a , Gold, A.L.^aq , Leibenluft, E.^a , Ringlein, G.V.^a , Werwath, K.E.^a , Zwiebel, H.^a , Zugman, A.^a , Grabe, H.J.^ar ^as , Van der Auwera, S.^ar ^as , Wittfeld, K.^ar ^as , Völzke, H.^at , Bülow, R.^au , Balderston, N.L.^av , Ernst, M.^aw , Grillon, C.^aw , Mujica-Parodi, L.R.^ax , van Nieuwenhuizen, H.^ay , Critchley, H.D.^az , Makovac, E.^ba , Mancini, M.^az , Meeten, F.^bb , Ottaviani, C.^bc ^bd , Ball, T.M.^be , Fonzo, G.A.^bf , Paulus, M.P.^bg , Stein, M.B.^bh , Gur, R.E.^bi , Gur, R.C.^bi , Kaczkurkin, A.N.^bi , Larsen, B.^bi , Satterthwaite, T.D.^bi , Harper, J.^bj , Myers, M.^bj , Perino, M.T.^bj , Sylvester, C.M.^bj , Yu, Q.^bj , Lueken, U.^h , Veltman, D.J.^f , Thompson, P.M.^u , Stein, D.J.^bk , Van der Wee, N.J.A.^c ^e , Winkler, A.M.^a , Pine, D.S.^a

^a Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, United States
^b Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
^c Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
^d Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
^e Leiden Institute for Brain and Cognition, Leiden, Netherlands
^f Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam, Netherlands
^g Department of Research & Innovation, GGZ InGeest, Amsterdam, Netherlands
^h Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
ⁱ Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain
^j Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
^k Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
^l Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, United States
^m LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil
ⁿ Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
^o Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, United States
^p Department of Psychiatry, NYU School of Medicine, New York University, New York, NY, United States
^q Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
^r Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, United States
^s Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, United States
^t Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
^u Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
^v Center for Brain Science & Department of Psychology, Harvard University, Cambridge, MA, United States
^w Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
^x Psychology Department & Neuroscience Center, Brigham Young University, Provo, United States
^y Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, United States
^z Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
^aa Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
^ab Anxiety Disorders Center, Institute of Living, Hartford Hospital, Hartford, CT, United States
^ac Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
^ad Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
^ae Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
^af Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
^ag Department Psychology, University of Pittsburgh, Pittsburgh, PA, United States
^ah Anxiety Disorder Program, Hospital de Clínicas de Porto Alegre, Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
^ai Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
^aj Vita-Salute San Raffaele University, Milan, Italy
^ak Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
^al Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
^am Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
^an Institute of Mental Health, University of Belgrade, Belgrade, Serbia
^ao Department of Psychiatry, School of Medicine, University of Belgrade, Belgrade, Serbia
^ap Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do Paraná, Curitiba, Puerto Rico, Brazil
^aq Department of Psychiatry and Human Behavior, Brown University Warren Alpert Medical School, Providence, RI, United States
^ar Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
^as German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
^at Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
^au Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
^av Center for Neuromodulation in Depression and Stress, University of Pennsylvania, Philadelphia, PA, United States
^aw Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, Bethesda, MD, United States
^ax Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
^ay Department of Physics, Stony Brook University, Stony Brook, NY, United States
^az Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom
^ba Centre for Neuroimaging Science, Kings College London, London, United Kingdom
^bb School of Psychology, University of Sussex, Brighton, United Kingdom
^bc Department of Psychology, Sapienza University of Rome, Rome, Italy
^bd IRCCS Santa Lucia Foundation, Rome, Italy
^be Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
^bf Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin Dell Medical School, Austin, TX, United States
^bg Laureate Institute for Brain Research, Tulsa, OK, United States
^bh Department of Psychiatry, School of Medicine and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, United States
^bi Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
^bj Department of Psychiatry, Washington University, St. Louis, MO, United States
^bk South African Medical Research Council Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa

Abstract
The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Funding details
129522
National Science FoundationNSFCBET0954643
National Institutes of HealthNIHK23 MH 086686, R01 MH 108509, R01 MH116147, R01MH101486-04, R01MH101497, R01MH11760, R56 AG058854, T32 MH014654, T32 MH100019, U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U24DA041123, U24DA041147, U54 EB020403
Office of Naval ResearchONRGR-2010-2312442, N000140410051
National Institute of Mental HealthNIMHK23MH109983, K23MH114023, K99MH117274, MH64122, MH65413, ZIA-MH-002782
U.S. Department of Veterans AffairsVAVHA5I01CX000994
Robert and Janice McNair Foundation
Allergan Foundation
Fresenius Medical Care North AmericaFMCNA
European Research CouncilERC
Deutsche ForschungsgemeinschaftDFG44541416 – TRR 58, BE 3809/8-1, R01MH117601
Fundação de Amparo à Pesquisa do Estado de São PauloFAPESP
Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCAPES
Bundesministerium für Bildung und ForschungBMBF01ZZ0103, 01ZZ0403, 01ZZ9603
Ministero della SaluteC06, GR-2018-12367789, K23MH100259, RF-2016-02364582
Nederlandse Organisatie voor Wetenschappelijk OnderzoekNWO019.201SG.022
Conselho Nacional de Desenvolvimento Científico e TecnológicoCNPq304829/2013-7, 475293/2012-6, ZIA-MH-002798
Fundação de Amparo à Pesquisa do Estado do Rio Grande do SulFAPERGS
Agenzia di Ricerca per la Sclerosi Laterale AmiotroficaAriSLA

Document Type: Article
Publication Stage: Final
Source: Scopus

“CHARGE syndrome protein CHD7 regulates epigenomic activation of enhancers in granule cell precursors and gyrification of the cerebellum” (2021) Nature Communications

CHARGE syndrome protein CHD7 regulates epigenomic activation of enhancers in granule cell precursors and gyrification of the cerebellum
(2021) Nature Communications, 12 (1), art. no. 5702, .

Reddy, N.C.^a , Majidi, S.P.^a ^b , Kong, L.^a , Nemera, M.^a , Ferguson, C.J.^a , Moore, M.^a , Goncalves, T.M.^a , Liu, H.-K.^c , Fitzpatrick, J.A.J.^a ^d ^e ^f , Zhao, G.^a , Yamada, T.^a ^g , Bonni, A.^a , Gabel, H.W.^a

^a Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
^b MD-PhD Program, Washington University School of Medicine, St. Louis, MO 63110, United States
^c Division of Molecular Neurogenetics, DKFZ-ZMBH Alliance, German Cancer Research Center Im Neunheimer Feld 280, Heidelberg, 69120, Germany
^d Department of Cell Biology & Physiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^e Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
^f Washington University Center for Cellular Imaging, Washington University School of Medicine, St. Louis, MO 63110, United States
^g Department of Neurobiology, Northwestern University, Evanston, IL 60201, United States

Abstract
Regulation of chromatin plays fundamental roles in the development of the brain. Haploinsufficiency of the chromatin remodeling enzyme CHD7 causes CHARGE syndrome, a genetic disorder that affects the development of the cerebellum. However, how CHD7 controls chromatin states in the cerebellum remains incompletely understood. Using conditional knockout of CHD7 in granule cell precursors in the mouse cerebellum, we find that CHD7 robustly promotes chromatin accessibility, active histone modifications, and RNA polymerase recruitment at enhancers. In vivo profiling of genome architecture reveals that CHD7 concordantly regulates epigenomic modifications associated with enhancer activation and gene expression of topologically-interacting genes. Genome and gene ontology studies show that CHD7-regulated enhancers are associated with genes that control brain tissue morphogenesis. Accordingly, conditional knockout of CHD7 triggers a striking phenotype of cerebellar polymicrogyria, which we have also found in a case of CHARGE syndrome. Finally, we uncover a CHD7-dependent switch in the preferred orientation of granule cell precursor division in the developing cerebellum, providing a potential cellular basis for the cerebellar polymicrogyria phenotype upon loss of CHD7. Collectively, our findings define epigenomic regulation by CHD7 in granule cell precursors and identify abnormal cerebellar patterning upon CHD7 depletion, with potential implications for our understanding of CHARGE syndrome. © 2021, The Author(s).

Funding details
CDI-CORE-2015-505, CDI-CORE-2019-813, OD021694
National Institutes of HealthNIH
National Institute of Neurological Disorders and StrokeNINDSNS041021
G. Harold and Leila Y. Mathers Charitable Foundation

Document Type: Article
Publication Stage: Final
Source: Scopus

“Impact of prenatal exposure characterization on early risk detection: Methodologic insights for the HEALthy Brain and Child Development (HBCD) study” (2021) Neurotoxicology and Teratology

Impact of prenatal exposure characterization on early risk detection: Methodologic insights for the HEALthy Brain and Child Development (HBCD) study
(2021) Neurotoxicology and Teratology, 88, art. no. 107035, .

Massey, S.H.^a ^b ^c , Allen, N.B.^c ^d , Pool, L.R.^c ^d , Miller, E.S.^c ^e , Pouppirt, N.R.^c ^f , Barch, D.M.^g , Luby, J.^h , Perlman, S.B.ⁱ , Rogers, C.E.^h , Smyser, C.D.^j , Wakschlag, L.S.^b ^c

^a Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, 676 North Saint Clair Street, Suite 1000, Chicago, IL 60611, United States
^b Department of Medical Social Sciences, Northwestern University Feinberg School of Medicine, 625 N Michigan Avenue, Suite 2100, Chicago, IL 60611, United States
^c Institute for Innovations in Developmental Sciences, Northwestern University Feinberg School of Medicine, 633 North Saint Clair Street, 19^th floor, Chicago, IL 60611, United States
^d Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 North Lakeshore Drive, Suite 1400, Chicago, IL 60611, United States
^e Department of Obstetrics and Gynecology, Northwestern University Feinberg School of Medicine, 250 East Superior Street, Room 05-2175, Chicago, IL 60611, United States
^f Department of Pediatrics, Division of Neonatology, Ann & Robert H. Lurie Children’s Hospital of Chicago, 225 East Chicago Avenue, Box 45, Chicago, IL 60611, United States
^g Department of Psychological & Brain Sciences, Washington University, Box 1125, One Brookings Drive, St. Louis, MO 63130, United States
^h Department of Psychiatry, Washington University School of Medicine in St. Louis, 660 S. Euclid Box 8511, St. Louis, MO 63110, United States
ⁱ Department of Child and Adolescent Psychiatry, Washington University School of Medicine in St. Louis, 4444 Forest Park Ave, St. Louis, MO 63110, United States
^j Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine in St. Louis, 4525 Scott Avenue, St. Louis, MO 63110, United States

Abstract
Background: A major challenge in prenatal drug exposure research concerns the balance of measurement quality with sample sizes necessary to address confounders. To inform the selection of optimal exposure measures for the HEALthy Brain and Child Development (HBCD) Study, we employed integrated analysis to determine how different methods used to characterize prenatal tobacco exposure influence the detection of exposure-related risk, as reflected in normal variations in birth weight. Methods: Participants were N = 2323 mother-infant dyads derived from 7 independent developmental cohorts harmonized on measures of exposure, outcome (birthweight), and covariates. We compared estimates of PTE-related effects on birthweight derived from linear regression models when PTE was categorized dichotomously based on any fetal exposure (30% exposed; 69% not exposed); versus categorically, based on common patterns of maternal smoking during pregnancy (never smoked 69%; quit smoking 16%; smoked intermittently 2%; smoked persistently 13%). We secondarily explored sex differences in PTE-birthweight associations across these categorization methods. Results: When PTE was categorized dichotomously, exposure was associated with a − 125-g difference in birthweight (95% C.I. -173.7 – −76.6, p < .0001). When PTE was characterized categorically based on maternal smoking patterns, however, exposure was associated with either no difference in birthweight if mothers quit smoking by the end of the first trimester (B = -30.6, 95% C.I. -88.7–27.4, p = .30); or a − 221.8 g difference in birthweight if mothers did not [95% C.I. (−161.7 to −282.0); p < .001]. Qualitative sex differences were also detected though PTE x sex interactions did not reach statistical significance. Maternal smoking cessation during pregnancy was associated with a 239.3 g increase in birthweight for male infants, and a 114.0 g increase in birthweight for females infants (p = .07). Conclusions: Categorization of PTE based on patterns of maternal smoking rather than the presence or absence of exposure alone revealed striking nuances in estimates of exposure-related risk. The described method that captures both between-individual and within-individual variability in prenatal drug exposure is optimal and recommended for future developmental investigations such as the HBCD Study. © 2021

Author Keywords
Birthweight; Infant; Pregnancy; Protective factors; Sex differences; Tobacco

Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMH
National Institute on Drug AbuseNIDAR01MH107652, R01MH113883, R01MH121877

Document Type: Article
Publication Stage: Final
Source: Scopus

“A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex” (2021) Nature

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex
(2021) Nature, 598 (7879), pp. 103-110. Cited 6 times.

Yao, Z.^a , Liu, H.^b , Xie, F.^c , Fischer, S.^d , Adkins, R.S.^e , Aldridge, A.I.^b , Ament, S.A.^e , Bartlett, A.^b , Behrens, M.M.^f , Van den Berge, K.^g ^h , Bertagnolli, D.^a , de Bézieux, H.R.ⁱ , Biancalani, T.^j , Booeshaghi, A.S.^k , Bravo, H.C.^l , Casper, T.^a , Colantuoni, C.^m ⁿ ^o , Crabtree, J.^e , Creasy, H.^e , Crichton, K.^a , Crow, M.^d , Dee, N.^a , Dougherty, E.L.^j , Doyle, W.I.^p , Dudoit, S.^g , Fang, R.^q , Felix, V.^e , Fong, O.^a , Giglio, M.^e , Goldy, J.^a , Hawrylycz, M.^a , Herb, B.R.^e , Hertzano, R.^e ^r , Hou, X.^s , Hu, Q.^t , Kancherla, J.^l , Kroll, M.^a , Lathia, K.^a , Li, Y.E.^u , Lucero, J.D.^f , Luo, C.^b ^v ^w , Mahurkar, A.^e , McMillen, D.^a , Nadaf, N.M.^j , Nery, J.R.^b , Nguyen, T.N.^a , Niu, S.-Y.^b , Ntranos, V.^x , Orvis, J.^e , Osteen, J.K.^f , Pham, T.^a , Pinto-Duarte, A.^f , Poirion, O.^s , Preissl, S.^s , Purdom, E.^g , Rimorin, C.^a , Risso, D.^y , Rivkin, A.C.^w , Smith, K.^a , Street, K.^z , Sulc, J.^a , Svensson, V.^k , Tieu, M.^a , Torkelson, A.^a , Tung, H.^a , Vaishnav, E.D.^j , Vanderburg, C.R.^j , van Velthoven, C.^a , Wang, X.^s ^ae , White, O.R.^e , Huang, Z.J.^aa , Kharchenko, P.V.^t , Pachter, L.^k , Ngai, J.^ab , Regev, A.^j ^ac , Tasic, B.^a , Welch, J.D.^ad , Gillis, J.^d , Macosko, E.Z.^j , Ren, B.^s ^u , Ecker, J.R.^b ^w , Zeng, H.^a , Mukamel, E.A.^p

^a Allen Institute for Brain Science, Seattle, WA, United States
^b Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States
^c Department of Physics, University of California, San Diego, La Jolla, CA, United States
^d Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
^e Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States
^f Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States
^g Department of Statistics, University of California, Berkeley, Berkeley, CA, United States
^h Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Gent, Belgium
ⁱ Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, CA, United States
^j Broad Institute of MIT and Harvard, Cambridge, MA, United States
^k California Institute of Technology, Pasadena, CA, United States
^l Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, United States
^m Johns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, United States
ⁿ Johns Hopkins School of Medicine, Department of Neuroscience, Baltimore, MD, United States
^o University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, United States
^p Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States
^q Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, San Diego, CA, United States
^r Department of Otorhinolaryngology, Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, United States
^s Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, United States
^t Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
^u Ludwig Institute for Cancer Research, La Jolla, CA, United States
^v Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, United States
^w Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, United States
^x University of California, San Francisco, San Francisco, CA, United States
^y Department of Statistical Sciences, University of Padova, Padova, Italy
^z Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, United States
^aa Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
^ab Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, United States
^ac Howard Hughes Medical Institute, Department of Biology, MIT, Cambridge, MA, United States
^ad Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
^ae McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, United States

Abstract
Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis. © 2021, The Author(s).

Funding details
National Institutes of HealthNIHR24MH114788, R24MH114815, U19MH114821, U19MH114830, U19MH121282, U24MH114827
National Institute on Deafness and Other Communication DisordersNIDCDDC013817
National Institute of General Medical SciencesNIGMSGM114267

Document Type: Article
Publication Stage: Final
Source: Scopus

“Comparative cellular analysis of motor cortex in human, marmoset and mouse” (2021) Nature

Comparative cellular analysis of motor cortex in human, marmoset and mouse
(2021) Nature, 598 (7879), pp. 111-119. Cited 3 times.

Bakken, T.E.^a , Jorstad, N.L.^a , Hu, Q.^b , Lake, B.B.^c , Tian, W.^d , Kalmbach, B.E.^a ^e , Crow, M.^f , Hodge, R.D.^a , Krienen, F.M.^g , Sorensen, S.A.^a , Eggermont, J.^h , Yao, Z.^a , Aevermann, B.D.ⁱ , Aldridge, A.I.^j , Bartlett, A.^j , Bertagnolli, D.^a , Casper, T.^a , Castanon, R.G.^j , Crichton, K.^a , Daigle, T.L.^a , Dalley, R.^a , Dee, N.^a , Dembrow, N.^e ^k , Diep, D.^c , Ding, S.-L.^a , Dong, W.^c , Fang, R.^l , Fischer, S.^f , Goldman, M.^g , Goldy, J.^a , Graybuck, L.T.^a , Herb, B.R.^m , Hou, X.ⁿ , Kancherla, J.^o , Kroll, M.^a , Lathia, K.^a , van Lew, B.^h , Li, Y.E.ⁿ ^p , Liu, C.S.^q ^r , Liu, H.^j , Lucero, J.D.^d , Mahurkar, A.^m , McMillen, D.^a , Miller, J.A.^a , Moussa, M.^s , Nery, J.R.^j , Nicovich, P.R.^a , Niu, S.-Y.^j ^t , Orvis, J.^m , Osteen, J.K.^d , Owen, S.^a , Palmer, C.R.^q ^r , Pham, T.^a , Plongthongkum, N.^c , Poirion, O.ⁿ , Reed, N.M.^g , Rimorin, C.^a , Rivkin, A.^d , Romanow, W.J.^q , Sedeño-Cortés, A.E.^a , Siletti, K.^u , Somasundaram, S.^a , Sulc, J.^a , Tieu, M.^a , Torkelson, A.^a , Tung, H.^a , Wang, X.^v , Xie, F.^w , Yanny, A.M.^a , Zhang, R.ⁱ , Ament, S.A.^m , Behrens, M.M.^d , Bravo, H.C.^o , Chun, J.^q , Dobin, A.^x , Gillis, J.^f , Hertzano, R.^y , Hof, P.R.^z , Höllt, T.^aa , Horwitz, G.D.^ab , Keene, C.D.^ac , Kharchenko, P.V.^b , Ko, A.L.^ad ^ae , Lelieveldt, B.P.^h ^af , Luo, C.^ag , Mukamel, E.A.^ah , Pinto-Duarte, A.^d , Preissl, S.ⁿ , Regev, A.^ai , Ren, B.ⁿ ^p , Scheuermann, R.H.ⁱ ^aj ^ak , Smith, K.^a , Spain, W.J.^e ^k , White, O.R.^m , Koch, C.^a , Hawrylycz, M.^a , Tasic, B.^a , Macosko, E.Z.^ai , McCarroll, S.A.^g ^ai , Ting, J.T.^a ^e , Zeng, H.^a , Zhang, K.^c , Feng, G.^al ^am ^an , Ecker, J.R.^j ^ao , Linnarsson, S.^u , Lein, E.S.^a

^a Allen Institute for Brain Science, Seattle, WA, United States
^b Department of Biomedical Informatics, Harvard Medical School, Boston, MA, United States
^c Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
^d The Salk Institute for Biological Studies, La Jolla, CA, United States
^e Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
^f Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
^g Department of Genetics, Harvard Medical School, Boston, MA, United States
^h LKEB, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands
ⁱ J. Craig Venter Institute, La Jolla, CA, United States
^j Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States
^k Epilepsy Center of Excellence, Department of Veterans Affairs Medical Center, Seattle, WA, United States
^l Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, La Jolla, CA, United States
^m Institute for Genomes Sciences, University of Maryland School of Medicine, Baltimore, MD, United States
ⁿ Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, United States
^o Department of Computer Science, University of Maryland College Park, College Park, MD, United States
^p Ludwig Institute for Cancer Research, La Jolla, CA, United States
^q Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, United States
^r Biomedical Sciences Program, School of Medicine, University of California, San Diego, La Jolla, CA, United States
^s University of Connecticut, Storrs, CT, United States
^t Computer Science and Engineering Program, University of California, San Diego, La Jolla, CA, United States
^u Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
^v McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, United States
^w Department of Physics, University of California, San Diego, La Jolla, CA, United States
^x Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States
^y Departments of Otorhinolaryngology, Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, United States
^z Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^aa Computer Graphics and Visualization Group, Delt University of Technology, Delft, Netherlands
^ab Department of Physiology and Biophysics, Washington National Primate Research Center, University of Washington, Seattle, WA, United States
^ac Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
^ad Department of Neurological Surgery, University of Washington School of Medicine, Seattle, WA, United States
^ae Regional Epilepsy Center, Harborview Medical Center, Seattle, WA, United States
^af Pattern Recognition and Bioinformatics group, Delft University of Technology, Delft, Netherlands
^ag Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, United States
^ah Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States
^ai Broad Institute of MIT and Harvard, Cambridge, MA, United States
^aj Department of Pathology, University of California, San Diego, CA, United States
^ak Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA, United States
^al McGovern Institute for Brain Research, MIT, Cambridge, MA, United States
^am Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, United States
^an Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, United States
^ao Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, United States

Abstract
The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations. © 2021, The Author(s).

Funding details
National Science FoundationNSF1846559
National Institutes of HealthNIHU01 MH114812-02
Howard Hughes Medical InstituteHHMI
National Institute of Mental HealthNIMHU19MH121282
National Institute on Drug AbuseNIDAR01DA036909
National Institute of Neurological Disorders and StrokeNINDSR01NS044163
California Institute for Regenerative MedicineCIRMGC1R-06673-B
Silicon Valley Community FoundationSVCF2018–182730
National Center for Advancing Translational SciencesNCATSRF1MH114126
National Alliance for Research on Schizophrenia and DepressionNARSAD
Office of Research Infrastructure Programs, National Institutes of HealthORIP, NIHUL1TR000423
Nederlandse Organisatie voor Wetenschappelijk OnderzoekNWO024.004.012, 17126, P51OD010425

Document Type: Article
Publication Stage: Final
Source: Scopus

“Single-cell epigenomics reveals mechanisms of human cortical development” (2021) Nature

Single-cell epigenomics reveals mechanisms of human cortical development
(2021) Nature, 598 (7879), pp. 205-213.

Ziffra, R.S.^a ^b ^c ^d ^e , Kim, C.N.^a ^b ^c , Ross, J.M.^a ^b ^c , Wilfert, A.^f , Turner, T.N.^g , Haeussler, M.^h , Casella, A.M.ⁱ ^j , Przytycki, P.F.^k , Keough, K.C.^l ^m , Shin, D.^a ^b ^c , Bogdanoff, D.^a ^b ^c , Kreimer, A.^d ^e ⁿ ^o , Pollard, K.S.^k ^l ^p ^q ^r , Ament, S.A.ⁱ ^s , Eichler, E.E.^f ^t , Ahituv, N.^d ^e , Nowakowski, T.J.^a ^b ^c ^r

^a Department of Anatomy, University of California, San Francisco, San Francisco, CA, United States
^b Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
^c Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, United States
^d Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
^e Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, United States
^f Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, United States
^g Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
^h Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, United States
ⁱ Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, United States
^j Medical Scientist Training Program, University of Maryland School of Medicine, Baltimore, MD, United States
^k Gladstone Institutes, San Francisco, CA, United States
^l Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, CA, United States
^m University of California, San Francisco, San Francisco, CA, United States
ⁿ Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States
^o Center for Computational Biology, University of California, Berkeley, Berkeley, CA, United States
^p Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, United States
^q Quantitative Biology Institute, University of California, San Francisco, San Francisco, CA, United States
^r Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, United States
^s Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, United States
^t Howard Hughes Medical Institute, University of Washington, Seattle, WA, United States

Abstract
During mammalian development, differences in chromatin state coincide with cellular differentiation and reflect changes in the gene regulatory landscape1. In the developing brain, cell fate specification and topographic identity are important for defining cell identity2 and confer selective vulnerabilities to neurodevelopmental disorders3. Here, to identify cell-type-specific chromatin accessibility patterns in the developing human brain, we used a single-cell assay for transposase accessibility by sequencing (scATAC-seq) in primary tissue samples from the human forebrain. We applied unbiased analyses to identify genomic loci that undergo extensive cell-type- and brain-region-specific changes in accessibility during neurogenesis, and an integrative analysis to predict cell-type-specific candidate regulatory elements. We found that cerebral organoids recapitulate most putative cell-type-specific enhancer accessibility patterns but lack many cell-type-specific open chromatin regions that are found in vivo. Systematic comparison of chromatin accessibility across brain regions revealed unexpected diversity among neural progenitor cells in the cerebral cortex and implicated retinoic acid signalling in the specification of neuronal lineage identity in the prefrontal cortex. Together, our results reveal the important contribution of chromatin state to the emerging patterns of cell type diversity and cell fate specification and provide a blueprint for evaluating the fidelity and robustness of cerebral organoids as a model for cortical development. © 2021, The Author(s).

Funding details
National Institutes of HealthNIHU01MH114825, U01MH115747, U01MH116438
National Institute of Mental HealthNIMH11874, 1K99MH117165, 5U41HG002371-19, R01 MH101221, R01MH109907
Simons FoundationSFSFARI 491371
Gladstone Institutes
National Alliance for Research on Schizophrenia and DepressionNARSAD
William K. Bowes, Jr. Foundation

Document Type: Article
Publication Stage: Final
Source: Scopus

“Diffusion-Weighted Imaging Reveals Distinct Patterns of Cytotoxic Edema in Patients with Subdural Hematomas” (2021) Journal of Neurotrauma

Diffusion-Weighted Imaging Reveals Distinct Patterns of Cytotoxic Edema in Patients with Subdural Hematomas
(2021) Journal of Neurotrauma, 38 (19), pp. 2677-2685. Cited 1 time.

Robinson, D.^a , Kreitzer, N.^b , Ngwenya, L.B.^c ^d , Adeoye, O.^e , Woo, D.^a , Hartings, J.^c ^d , Foreman, B.^a ^d

^a Department of Neurology and Rehabilitation Medicine, University of Cincinnati, 231 Albert Sabin Way, Room 7101, Cincinnati, OH 45267, United States
^b Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH, United States
^c Department of Neurosurgery, University of Cincinnati, Cincinnati, OH, United States
^d Collaborative for Research on Acute Neurological Injuries, Cincinnati, OH, United States
^e Department of Emergency Medicine, Washington University, St. Louis, MO, United States

Abstract
Subdural hematomas (SDHs) are increasingly common and can cause ischemic brain injury. Previous work has suggested that this is driven largely by vascular compression from herniation, although this work was done before the era of magnetic resonance imaging (MRI). We thus sought to study SDH-related ischemic brain injury by looking at patterns of cytotoxic edema on diffusion-weighted MRI. To do so, we identified all SDH patients at a single institution from 2015 to 2019 who received an MRI within 2 weeks of presentation. We reviewed all MRIs for evidence of restricted diffusion consistent with cytotoxic edema. Cases were excluded if the restricted diffusion could have occurred as a result of alternative etiologies (e.g., cardioembolic stroke or diffuse axonal injury). We identified 450 SDH patients who received an MRI within 2 weeks of presentation. Twenty-nine patients (∼6.5% of all MRIs) had SDH-related cytotoxic edema, which occurred in two distinct patterns. In one pattern (N = 9), patients presented as comatose with severe midline shift and were found to have cytotoxic edema in the vascular territories of the anterior and posterior cerebral artery, consistent with herniation-related vascular compression. In the other pattern (N = 19), patients often presented as awake with less midline shift and developed cytotoxic edema in the cortex adjacent to the SDH outside of typical vascular territories (peri-SDH cytotoxic edema). Both patterns occurred in 1 patient. The peri-SDH cytotoxic edema pattern is a newly described type of secondary injury and may involve direct toxic effects of the SDH, spreading depolarizations, or other mechanisms. © Copyright 2021, Mary Ann Liebert, Inc., publishers 2021.

Author Keywords
ischemia; secondary insult; subdural hematoma

Document Type: Review
Publication Stage: Final
Source: Scopus

“Levels of circulating NS1 impact West Nile virus spread to the brain” (2021) Journal of Virology

Levels of circulating NS1 impact West Nile virus spread to the brain
(2021) Journal of Virology, 95 (20), art. no. e00844-21, .

Wessel, A.W.^a ^b , Dowd, K.A.^c , Biering, S.B.^d , Zhang, P.^e , Edeling, M.A.^a , Nelson, C.A.^a , Funk, K.E.^b , DeMaso, C.R.^c , Klein, R.S.^a ^b ^f ^g , Smith, J.L.^h ⁱ , Cao, T.M.^j ^k , Kuhn, R.J.^j ^k , Fremont, D.H.^a ^l ^m , Harris, E.^d , Pierson, T.C.^c , Diamond, M.S.^a ^b ^l ⁿ

^a Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
^c Viral Pathogenesis Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
^d Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA, United States
^e Department of Immunology, Key Laboratory of Tropical Diseases Control, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
^f Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
^g Center for Neuroimmunology and Neuroinfectious Diseases, Washington University School of Medicine, St. Louis, MO, United States
^h Life Sciences Institute, University of Michigan, Ann Arbor, MI, United States
ⁱ Department of Biological Chemistry, University of Michigan, Ann Arbor, MI, United States
^j Department of Biological Sciences, Purdue University, West Lafayette, IN, United States
^k Purdue Institute of Inflammation, Immunology, and Infectious Disease, Purdue University, West Lafayette, IN, United States
^l Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, United States
^m Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, United States
ⁿ Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Dengue virus (DENV) and West Nile virus (WNV) are arthropod-transmitted flaviviruses that cause systemic vascular leakage and encephalitis syndromes, respectively, in humans. However, the viral factors contributing to these specific clinical disorders are not completely understood. Flavivirus nonstructural protein 1 (NS1) is required for replication, expressed on the cell surface, and secreted as a soluble glycoprotein, reaching high levels in the blood of infected individuals. Extracellular DENV NS1 and WNV NS1 interact with host proteins and cells, have immune evasion functions, and promote endothelial dysfunction in a tissue-specific manner. To characterize how differences in DENV NS1 and WNV NS1 might function in pathogenesis, we generated WNV NS1 variants with substitutions corresponding to residues found in DENV NS1. We discovered that the substitution NS1-P101K led to reduced WNV infectivity in the brain and attenuated lethality in infected mice, although the virus replicated efficiently in cell culture and peripheral organs and bound at wild-type levels to brain endothelial cells and complement components. The P101K substitution resulted in reduced NS1 antigenemia in mice, and this was associated with reduced WNV spread to the brain. Because exogenous administration of NS1 protein rescued WNV brain infectivity in mice, we conclude that circulating WNV NS1 facilitates viral dissemination into the central nervous system and impacts disease outcomes. IMPORTANCE Flavivirus NS1 serves as an essential scaffolding molecule during virus replication but also is expressed on the cell surface and is secreted as a soluble glycoprotein that circulates in the blood of infected individuals. Although extracellular forms of NS1 are implicated in immune modulation and in promoting endothelial dysfunction at blood-tissue barriers, it has been challenging to study specific effects of NS1 on pathogenesis without disrupting its key role in virus replication. Here, we assessed WNV NS1 variants that do not affect virus replication and evaluated their effects on pathogenesis in mice. Our characterization of WNV NS1-P101K suggests that the levels of NS1 in the circulation facilitate WNV dissemination to the brain and affect disease outcomes. Our findings facilitate understanding of the role of NS1 during flavivirus infection and support antiviral strategies for targeting circulating forms of NS1. © 2021 American Society for Microbiology. All Rights Reserved.

Author Keywords
Animal model; Dissemination; Endothelial cells; Flavivirus; Viral pathogenesis; Virology

Funding details
National Institutes of HealthNIH75N93019C00062, HHSN272201400058C, R01 AI073755, R01 AI124493, T32 5T32AI007172-38
National Institute of Allergy and Infectious DiseasesNIAID

Document Type: Article
Publication Stage: Final
Source: Scopus

“Analysis of the effect of intraoperative neuromonitoring during resection of benign nerve sheath tumors on gross-total resection and neurological complications” (2021) Journal of Neurosurgery

Analysis of the effect of intraoperative neuromonitoring during resection of benign nerve sheath tumors on gross-total resection and neurological complications
(2021) Journal of Neurosurgery, 135 (4), pp. 1231-1240.

Wilson, T.J.^a , Hamrick, F.^b , Alzahrani, S.^c , Dibble, C.F.^d , Koduri, S.^e , Pendleton, C.^f , Saleh, S.^e , Ali, Z.S.^g , Mahan, M.A.^b , Midha, R.^c , Ray, W.Z.^d , Yang, L.J.S.^e , Zager, E.L.^g , Spinner, R.J.^f

^a Department of Neurosurgery, Stanford University, Stanford, CA, United States
^b Department of Neurosurgery, University of Utah, Salt Lake City, UT, United States
^c Department of Clinical Neurosciences, University of CalgaryAB, Canada
^d Department of Neurosurgery, Washington University, St. Louis, MO, United States
^e Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States
^f Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
^g Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States

Abstract
OBJECTIVE The aim of this study was to examine the role of intraoperative neuromonitoring (IONM) during resection of benign peripheral nerve sheath tumors in achieving gross-total resection (GTR) and in reducing postoperative neurological complications. METHODS Data from consecutive adult patients who underwent resection of a benign peripheral nerve sheath tumor at 7 participating institutions were combined. Propensity score matching was used to balance covariates. The primary outcomes of interest were the association between IONM and GTR and the association of IONM and the development of a permanent postoperative neurological complication. The secondary outcomes of interest were the association between IONM and GTR and the association between IONM and the development of a permanent postoperative neurological complication in the subgroup of patients with tumors involving a motor or mixed nerve. Univariate and multivariate logistic regression were then performed on the propensity score-matched samples to assess the ability of the independent variables to predict the outcomes of interest. RESULTS A total of 337 patients who underwent resection of benign nerve sheath tumors were included. In multivariate analysis, the use of IONM (OR 0.460, 95% CI 0.199-0.978; p = 0.047) was a significant negative predictor of GTR, whereas none of the variables, including IONM, were associated with the occurrence of a permanent postoperative neurological complication. Within the subgroup of motor/mixed nerve tumors, in the multivariate analysis, IONM (OR 0.263, 95% CI 0.096-0.723; p = 0.010) was a significant negative predictor of a GTR, whereas IONM (OR 3.800, 95% CI 1.925-7.502; p < 0.001) was a significant positive predictor of a permanent postoperative motor deficit. CONCLUSIONS Overall, 12% of the cohort had a permanent neurological complication, with new or worsened paresthesias most common, followed by pain and then weakness. The authors found that formal IONM was associated with a reduced likelihood of GTR and had no association with neurological complications. The authors believe that these data argue against IONM being considered standard of care but do not believe that these data should be used to universally argue against IONM during resection of benign nerve sheath tumors. © AANS 2021.

Author Keywords
Intraoperative neuromonitoring; Nerve sheath tumor; Neurofibroma; Peripheral nerve; Schwannoma

Document Type: Article
Publication Stage: Final
Source: Scopus

“Oromandibular Dystonia: A Clinical Examination of 2,020 Cases” (2021) Frontiers in Neurology

Oromandibular Dystonia: A Clinical Examination of 2,020 Cases
(2021) Frontiers in Neurology, 12, art. no. 700714, .

Scorr, L.M.^a , Factor, S.A.^a , Parra, S.P.^a , Kaye, R.^b , Paniello, R.C.^c , Norris, S.A.^c , Perlmutter, J.S.^c , Bäumer, T.^d , Usnich, T.^d , Berman, B.D.^e , Mailly, M.^f , Roze, E.^g , Vidailhet, M.^g , Jankovic, J.^h , LeDoux, M.S.ⁱ ^j , Barbano, R.^k , Chang, F.C.F.^l , Fung, V.S.C.^l , Pirio Richardson, S.^m , Blitzer, A.ⁿ , Jinnah, H.A.^a , for the Dystonia Coalition Investigators^o

^a Department of Neurology, Emory University, Atlanta, GA, United States
^b Department of Otolaryngology, Rutgers University, Newark, NJ, United States
^c Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^d Department of Neurology, Institute of Systems Motor Science, Universität of Lübeck, Lübeck, Germany
^e Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
^f Department of ENT and Head and Neck Surgery, Fondation Adolphe de Rothschild, Paris, France
^g Department of Neurology, Hôpital de la Pitié Salpétrière, Assistance Publique-Hôpitaux de Paris, Paris, France
^h Baylor St. Luke’s Medical Center, Houston, TX, United States
ⁱ Veracity Neuroscience LLC, Memphis, TN, United States
^j Department of Neurology, University of Memphis, Memphis, TN, United States
^k Department of Neurology, University of Rochester, Rochester, NY, United States
^l Department of Neurology, Westmead Hospital, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
^m Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
ⁿ Head and Neck Surgical Group, New York, NY, United States

Abstract
Objective: The goal of this study is to better characterize the phenotypic heterogeneity of oromandibular dystonia (OMD) for the purpose of facilitating early diagnosis. Methods: First, we provide a comprehensive summary of the literature encompassing 1,121 cases. Next, we describe the clinical features of 727 OMD subjects enrolled by the Dystonia Coalition (DC), an international multicenter cohort. Finally, we summarize clinical features and treatment outcomes from cross-sectional analysis of 172 OMD subjects from two expert centers. Results: In all cohorts, typical age at onset was in the 50s and 70% of cases were female. The Dystonia Coalition cohort revealed perioral musculature was involved most commonly (85%), followed by jaw (61%) and tongue (17%). OMD more commonly appeared as part of a segmental dystonia (43%), and less commonly focal (39%) or generalized (10%). OMD was found to be associated with impaired quality of life, independent of disease severity. On average, social anxiety (LSA score: 33 ± 28) was more common than depression (BDI II score: 9.7 ± 7.8). In the expert center cohorts, botulinum toxin injections improved symptom severity by more than 50% in ~80% of subjects, regardless of etiology. Conclusions: This comprehensive description of OMD cases has revealed novel insights into the most common OMD phenotypes, pattern of dystonia distribution, associated psychiatric disturbances, and effect on QoL. We hope these findings will improve clinical recognition to aid in timely diagnosis and inform treatment strategies. © Copyright © 2021 Scorr, Factor, Parra, Kaye, Paniello, Norris, Perlmutter, Bäumer, Usnich, Berman, Mailly, Roze, Vidailhet, Jankovic, LeDoux, Barbano, Chang, Fung, Pirio Richardson, Blitzer and Jinnah.

Author Keywords
botulinum (neuro)toxin; dystonia; jaw; tongue; treatment

Document Type: Article
Publication Stage: Final
Source: Scopus

“Information content differentiates enhancers from silencers in mouse photoreceptors” (2021) eLife

Information content differentiates enhancers from silencers in mouse photoreceptors
(2021) eLife, 10, art. no. e67403, .

Friedman, R.Z.^a , Granas, D.M.^a , Myers, C.A.^b , Corbo, J.C.^b , Cohen, B.A.^a , White, M.A.^a

^a Edison Family Center for Genome Sciences and Systems Biology, and Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Enhancers and silencers often depend on the same transcription factors (TFs) and are conflated in genomic assays of TF binding or chromatin state. To identify sequence features that distinguish enhancers and silencers, we assayed massively parallel reporter libraries of genomic sequences targeted by the photoreceptor TF CRX in mouse retinas. Both enhancers and silencers contain more TF motifs than inactive sequences, but relative to silencers, enhancers contain motifs from a more diverse collection of TFs. We developed a measure of information content that describes the number and diversity of motifs in a sequence and found that, while both enhancers and silencers depend on CRX motifs, enhancers have higher information content. The ability of information content to distinguish enhancers and silencers targeted by the same TF illustrates how motif context determines the activity of cis-regulatory sequences. © 2021, eLife Sciences Publications Ltd. All rights reserved.

Document Type: Article
Publication Stage: Final
Source: Scopus

“Modelling spinal locomotor circuits for movements in developing zebrafish” (2021) eLife

Modelling spinal locomotor circuits for movements in developing zebrafish
(2021) eLife, 10, art. no. e67453, .

Roussel, Y.^a ^b , Gaudreau, S.F.^a , Kacer, E.R.^a , Sengupta, M.^c , Bui, T.V.^a

^a Brain and Mind Research Institute, Centre for Neural Dynamics, Department of Biology, University of Ottawa, Ottawa, K1N 6N5, Canada
^b Blue Brain Project, École Polytechnique Fédérale de Lausanne, Genève, CH-1202, Switzerland
^c Washington University School of Medicine, Department of Neuroscience, St Louis, MO, United States

Abstract
Many spinal circuits dedicated to locomotor control have been identified in the developing zebrafish. How these circuits operate together to generate the various swimming movements during development remains to be clarified. In this study, we iteratively built models of developing zebrafish spinal circuits coupled to simplified musculoskeletal models that reproduce coiling and swimming movements. The neurons of the models were based upon morphologically or genetically identified populations in the developing zebrafish spinal cord. We simulated intact spinal circuits as well as circuits with silenced neurons or altered synaptic transmission to better understand the role of specific spinal neurons. Analysis of firing patterns and phase relationships helped identify possible mechanisms underlying the locomotor movements of developing zebrafish. Notably, our simulations demonstrated how the site and the operation of rhythm generation could transition between coiling and swimming. The simulations also underlined the importance of contralateral excitation to multiple tail beats. They allowed us to estimate the sensitivity of spinal locomotor networks to motor command amplitude, synaptic weights, length of ascending and descending axons, and firing behaviour. These models will serve as valuable tools to test and further understand the operation of spinal circuits for locomotion. © 2021, eLife Sciences Publications Ltd. All rights reserved.

Funding details
Natural Sciences and Engineering Research Council of CanadaNSERC712210101627, RGPIN-2015–06403

Document Type: Article
Publication Stage: Final
Source: Scopus

“Modelling the functional roles of synaptic and extra-synaptic γ-aminobutyric acid receptor dynamics in circadian timekeeping” (2021) Journal of the Royal Society, Interface

Modelling the functional roles of synaptic and extra-synaptic γ-aminobutyric acid receptor dynamics in circadian timekeeping
(2021) Journal of the Royal Society, Interface, 18 (182), p. 20210454.

Sueviriyapan, N.^a , Granados-Fuentes, D.^b , Simon, T.^b , Herzog, E.D.^b , Henson, M.A.^a

^a Department of Chemical Engineering and the Institute for Applied Life Sciences, University of Massachusetts, MA, Amherst, United States
^b Department of Biology, Washington University in St Louis, MO, Saint Louis, United States

Abstract
In the suprachiasmatic nucleus (SCN), γ-aminobutyric acid (GABA) is a primary neurotransmitter. GABA can signal through two types of GABAA receptor subunits, often referred to as synaptic GABAA (gamma subunit) and extra-synaptic GABAA (delta subunit). To test the functional roles of these distinct GABAA in regulating circadian rhythms, we developed a multicellular SCN model where we could separately compare the effects of manipulating GABA neurotransmitter or receptor dynamics. Our model predicted that blocking GABA signalling modestly increased synchrony among circadian cells, consistent with published SCN pharmacology. Conversely, the model predicted that lowering GABAA receptor density reduced firing rate, circadian cell fraction, amplitude and synchrony among individual neurons. When we tested these predictions, we found that the knockdown of delta GABAA reduced the amplitude and synchrony of clock gene expression among cells in SCN explants. The model further predicted that increasing gamma GABAA densities could enhance synchrony, as opposed to increasing delta GABAA densities. Overall, our model reveals how blocking GABAA receptors can modestly increase synchrony, while increasing the relative density of gamma over delta subunits can dramatically increase synchrony. We hypothesize that increased gamma GABAA density in the winter could underlie the tighter phase relationships among SCN cells.

Author Keywords
circadian rhythms; GABA receptor; mathematical modelling; suprachiasmatic nucleus

Document Type: Article
Publication Stage: Final
Source: Scopus

“Enhancing Cognition in Older Persons with Depression or Anxiety with a Combination of Mindfulness-Based Stress Reduction (MBSR) and Transcranial Direct Current Stimulation (tDCS): Results of a Pilot Randomized Clinical Trial” (2021) Mindfulness

Enhancing Cognition in Older Persons with Depression or Anxiety with a Combination of Mindfulness-Based Stress Reduction (MBSR) and Transcranial Direct Current Stimulation (tDCS): Results of a Pilot Randomized Clinical Trial
(2021) Mindfulness, .

Brooks, H.^a , Oughli, H.A.^b , Kamel, L.^b , Subramanian, S.^b , Morgan, G.^c , Blumberger, D.M.^a , Kloeckner, J.^b , Kumar, S.^a , Mulsant, B.H.^a , Lenze, E.J.^b , Rajji, T.K.^a ^d

^a Centre for Addiction and Mental Health and Department of Psychiatry, University of Toronto, Toronto, ON, Canada
^b Washington University School of Medicine, St. Louis, MO, United States
^c Centre for Mindfulness Studies, Toronto, Canada
^d Toronto Dementia Research Alliance, University of Toronto, Toronto, Canada

Abstract
Objectives: Individuals with subjective memory complaints and symptoms of depression and/or anxiety are at high risk for further cognitive decline, and possible progression to dementia. Low-burden interventions to help slow or prevent cognitive decline in this high-risk group are needed. The objective of this study is to assess the feasibility of combining Mindfulness-Based Stress Reduction (MBSR) with transcranial direct current stimulation (tDCS) to increase putative benefits of MBSR for cognitive function and everyday mindfulness in depressed or anxious older adults with subjective cognitive decline. Methods: We conducted a two-site pilot double-blind randomized sham-controlled trial, combining active MBSR with either active or sham tDCS. The intervention included weekly in-class group sessions at the local university hospital and daily at-home practice. Anodal tDCS was applied for 30 min during MBSR meditative practice, both in-class and at-home. Results: Twenty-six individuals with subjective cognitive complaints and symptoms of depression and/or anxiety were randomized to active (n = 12) or sham tDCS (n = 14). The combination of MBSR and tDCS was safe and well tolerated, though at-home adherence and in-class attendance were variable. While they were not statistically significant, the largest effect sizes for active vs. sham tDCS were for everyday mindfulness (d = 0.6) and social functioning (d = 0.9) (F(1,21) = 3.68, p = 0.07 and F(1,21) = 3.9, p = 0.06, respectively). Conclusions: Our findings suggest that it is feasible and safe to combine tDCS with MBSR in older depressed and anxious adults, including during remote, at-home use. Furthermore, tDCS may enhance MBSR via transferring its meditative learning and practice into increases in everyday mindfulness. Future studies need to improve adherence to MBSR with tDCS. Trial Registration: ClinicalTrials.gov (NCT03653351 and NCT03680664). © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Cognitive function; Late-life anxiety; Late-life depression; MBSR; Mindfulness; Subjective cognitive complaints; tDCS

Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMHR25 MH112473
National Institute on AgingNIA
Brain and Behavior Research FoundationBBRF
Eli Lilly and Company
Patient-Centered Outcomes Research InstitutePCORI
BrightFocus FoundationBFF
Evelyn F. McKnight Brain Research FoundationMBRF
Fondation Brain Canada
Acadia University
National Alliance for Research on Schizophrenia and DepressionNARSAD
Weston Brain InstituteWBI
Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine in St. Louis
Centre for Addiction and Mental Health FoundationCAMH
Takeda Canada
Canadian Institutes of Health ResearchIRSC
Canada Foundation for InnovationCFI
Ontario Ministry of Health and Long-Term CareMOHLTC
Canada Research Chairs950–230879
Ontario Ministry of Research, Innovation and ScienceMRIS
University of TorontoU of T
H. Lundbeck A/S

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

“Early Childhood Socioeconomic Status and Cognitive and Adaptive Outcomes at the Transition to Adulthood: The Mediating Role of Gray Matter Development Across Five Scan Waves” (2021) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

Early Childhood Socioeconomic Status and Cognitive and Adaptive Outcomes at the Transition to Adulthood: The Mediating Role of Gray Matter Development Across Five Scan Waves
(2021) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, .

Barch, D.M.^a ^b ^c , Donohue, M.R.^b , Elsayed, N.M.^a , Gilbert, K.^b , Harms, M.P.^b , Hennefield, L.^b , Herzberg, M.^b , Kandala, S.^b , Karcher, N.R.^b , Jackson, J.J.^a , Luking, K.R.^a , Rappaport, B.I.^a , Sanders, A.^b , Taylor, R.^a , Tillman, R.^b , Vogel, A.C.^b , Whalen, D.^b , Luby, J.L.^b

^a Departments of Psychological & Brain Sciences, Psychiatry, and Radiology, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
^c Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Background: Early low socioeconomic status (SES) is associated with poor outcomes in childhood, many of which endure into adulthood. It is critical to determine how early low SES relates to trajectories of brain development and whether these mediate relationships to poor outcomes. We use data from a unique 17-year longitudinal study with five waves of structural brain imaging to prospectively examine relationships between preschool SES and cognitive, social, academic, and psychiatric outcomes in early adulthood. Methods: Children (n = 216, 50% female, 47.2% non-White) were recruited from a study of early onset depression and followed approximately annually. Family income-to-needs ratios (SES) were assessed when children were ages 3 to 5 years. Volumes of cortical gray and white matter and subcortical gray matter collected across five scan waves were processed using the FreeSurfer Longitudinal pipeline. When youth were ages 16+ years, cognitive function was assessed using the NIH Toolbox, and psychiatric diagnoses, high-risk behaviors, educational function, and social function were assessed using clinician administered and parent/youth report measures. Results: Lower preschool SES related to worse cognitive, high-risk, educational, and social outcomes (|standardized B| = 0.20–0.31, p values <.003). Lower SES was associated with overall lower cortical (standardized B = 0.12, p <.0001) and subcortical gray matter (standardized B = 0.17, p <.0001) volumes, as well as a shallower slope of subcortical gray matter growth over time (standardized B = 0.04, p =.012). Subcortical gray matter mediated the relationship of preschool SES to cognition and high-risk behaviors. Conclusions: These novel longitudinal data underscore the key role of brain development in understanding the long-lasting relations of early low SES to outcomes in children. © 2021 Society of Biological Psychiatry

Author Keywords
Adaptive function; Brain development; Cognition; Risk-taking; Social function; Socioeconomic status

Funding details
National Institute of Mental HealthNIMHK23MH121792, L30 MH120574, R01 MH090786, R01MH064769, T32 MH100019
University of WashingtonUW

Document Type: Article
Publication Stage: Article in Press
Source: Scopus

“Effect of Pain Reprocessing Therapy vs Placebo and Usual Care for Patients with Chronic Back Pain: A Randomized Clinical Trial” (2021) JAMA Psychiatry

Effect of Pain Reprocessing Therapy vs Placebo and Usual Care for Patients with Chronic Back Pain: A Randomized Clinical Trial
(2021) JAMA Psychiatry, .

Ashar, Y.K.^a ^b ^c , Gordon, A.^d , Schubiner, H.^e ^f , Uipi, C.^d , Knight, K.^g , Anderson, Z.^b ^c ^h , Carlisle, J.^b ^c ⁱ , Polisky, L.^b ^c , Geuter, S.^b ^c ^j , Flood, T.F.^k , Kragel, P.A.^b ^c ^l , Dimidjian, S.^b ^m , Lumley, M.A.ⁿ , Wager, T.D.^b ^c ^o

^a Department of Psychiatry, Weill Cornell Medical College, 1300 York Ave, New York, NY 10065, United States
^b Department of Psychology and Neuroscience, University of Colorado, Boulder, United States
^c Institute of Cognitive Science, University of Colorado, Boulder, United States
^d Pain Psychology Center, Los Angeles, CA, United States
^e Ascension Providence Hospital, Southfield, MI, United States
^f Michigan State University College of Human Medicine, East Lansing, United States
^g Panorama Orthopedics and Spine Center, Golden, CO, United States
^h Department of Psychology, Northwestern University, Evanston, IL, United States
ⁱ Department of Philosophy, Washington University in Saint Louis, Saint Louis, MO, United States
^j Johns Hopkins University, Department of Biostatistics, Baltimore, MD, United States
^k Department of Radiology, Brigham and Women’s Hospital, Boston, MA, United States
^l Department of Psychology, Emory University, Atlanta, GA, United States
^m Renée Crown Wellness Institute, University of Colorado, Boulder, United States
ⁿ Department of Psychology, Wayne State University, Detroit, MI, United States
^o Department of Psychological and Brain Sciences, Dartmouth College, 352 Moore Hall, HB 6207, Hanover, NH 03755, United States

Abstract
Importance: Chronic back pain (CBP) is a leading cause of disability, and treatment is often ineffective. Approximately 85% of cases are primary CBP, for which peripheral etiology cannot be identified, and maintenance factors include fear, avoidance, and beliefs that pain indicates injury. Objective: To test whether a psychological treatment (pain reprocessing therapy [PRT]) aiming to shift patients’ beliefs about the causes and threat value of pain provides substantial and durable pain relief from primary CBP and to investigate treatment mechanisms. Design, Setting, and Participants: This randomized clinical trial with longitudinal functional magnetic resonance imaging (fMRI) and 1-year follow-up assessment was conducted in a university research setting from November 2017 to August 2018, with 1-year follow-up completed by November 2019. Clinical and fMRI data were analyzed from January 2019 to August 2020. The study compared PRT with an open-label placebo treatment and with usual care in a community sample. Interventions: Participants randomized to PRT participated in 1 telehealth session with a physician and 8 psychological treatment sessions over 4 weeks. Treatment aimed to help patients reconceptualize their pain as due to nondangerous brain activity rather than peripheral tissue injury, using a combination of cognitive, somatic, and exposure-based techniques. Participants randomized to placebo received an open-label subcutaneous saline injection in the back; participants randomized to usual care continued their routine, ongoing care. Main Outcomes and Measures: One-week mean back pain intensity score (0 to 10) at posttreatment, pain beliefs, and fMRI measures of evoked pain and resting connectivity. Results: At baseline, 151 adults (54% female; mean [SD] age, 41.1 [15.6] years) reported mean (SD) pain of low to moderate severity (mean [SD] pain intensity, 4.10 [1.26] of 10; mean [SD] disability, 23.34 [10.12] of 100) and mean (SD) pain duration of 10.0 (8.9) years. Large group differences in pain were observed at posttreatment, with a mean (SD) pain score of 1.18 (1.24) in the PRT group, 2.84 (1.64) in the placebo group, and 3.13 (1.45) in the usual care group. Hedges g was -1.14 for PRT vs placebo and -1.74 for PRT vs usual care (P <.001). Of 151 total participants, 33 of 50 participants (66%) randomized to PRT were pain-free or nearly pain-free at posttreatment (reporting a pain intensity score of 0 or 1 of 10), compared with 10 of 51 participants (20%) randomized to placebo and 5 of 50 participants (10%) randomized to usual care. Treatment effects were maintained at 1-year follow-up, with a mean (SD) pain score of 1.51 (1.59) in the PRT group, 2.79 (1.78) in the placebo group, and 3.00 (1.77) in the usual care group. Hedges g was -0.70 for PRT vs placebo (P =.001) and -1.05 for PRT vs usual care (P <.001) at 1-year follow-up. Longitudinal fMRI showed (1) reduced responses to evoked back pain in the anterior midcingulate and the anterior prefrontal cortex for PRT vs placebo; (2) reduced responses in the anterior insula for PRT vs usual care; (3) increased resting connectivity from the anterior prefrontal cortex and the anterior insula to the primary somatosensory cortex for PRT vs both control groups; and (4) increased connectivity from the anterior midcingulate to the precuneus for PRT vs usual care. Conclusions and Relevance: Psychological treatment centered on changing patients’ beliefs about the causes and threat value of pain may provide substantial and durable pain relief for people with CBP. Trial Registration: ClinicalTrials.gov Identifier: NCT03294148. © 2021 Ashar YK et al. JAMA Psychiatry.

Document Type: Article
Publication Stage: Article in Press
Source: Scopus