State-level macro-economic factors moderate the association of low income with brain structure and mental health in U.S. children
(2023) Nature Communications, 14 (1), art. no. 2085, .
Weissman, D.G.a , Hatzenbuehler, M.L.a , Cikara, M.a , Barch, D.M.b , McLaughlin, K.A.a
a Department of Psychology, Harvard University, Cambridge, MA, United States
b Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, United States
Abstract
Macrostructural characteristics, such as cost of living and state-level anti-poverty programs relate to the magnitude of socioeconomic disparities in brain development and mental health. In this study we leveraged data from the Adolescent Brain and Cognitive Development (ABCD) study from 10,633 9-11 year old youth (5115 female) across 17 states. Lower income was associated with smaller hippocampal volume and higher internalizing psychopathology. These associations were stronger in states with higher cost of living. However, in high cost of living states that provide more generous cash benefits for low-income families, socioeconomic disparities in hippocampal volume were reduced by 34%, such that the association of family income with hippocampal volume resembled that in the lowest cost of living states. We observed similar patterns for internalizing psychopathology. State-level anti-poverty programs and cost of living may be confounded with other factors related to neurodevelopment and mental health. However, the patterns were robust to controls for numerous state-level social, economic, and political characteristics. These findings suggest that state-level macrostructural characteristics, including the generosity of anti-poverty policies, are potentially relevant for addressing the relationship of low income with brain development and mental health. © 2023, The Author(s).
Document Type: Article
Publication Stage: Final
Source: Scopus
Change in cardiovascular health among adults with current or past major depressive disorder enrolled in intensive smoking cessation treatment
(2023) Journal of Affective Disorders, 333, pp. 527-534.
Carroll, A.J.a , Huffman, M.D.b c e , Wileyto, E.P.d , Khan, S.S.e , Fox, E.e , Smith, J.D.f , Bauer, A.-M.g , Leone, F.T.h , Schnoll, R.A.g , Hitsman, B.e
a Departments of Psychiatry and Behavioral Sciences and Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
b Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
c The George Institute for Global Health, University of New South Wales, Sydney, Australia
d Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States
e Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
f Department of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine at the University of Utah, Salt Lake City, UT, United States
g Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
h Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania, Philadelphia, PA, United States
Abstract
Background: Elevated depressive symptoms and cigarette smoking are independently associated with poorer cardiovascular health (CVH), but it is unknown whether their treatment can synergistically improve CVH. We sought to characterize CVH of adults with comorbid depression and smoking and examine changes in CVH associated with changes in smoking and depression. Methods: Participants (N = 300, 55 % women) were adult smokers (≥ 1 cigarette/day) with lifetime major depressive disorder enrolled in a 12-week intervention trial targeting depression and smoking. Multiple linear regression examined prospective associations between changes in depression (Beck Depression Inventory-II), smoking (past 24-hour cigarettes or smoking abstinence), and modified CVH score (per American Heart Association, excluding smoking: diet, physical activity, body mass index, blood glucose, cholesterol, blood pressure). Results: Baseline mean CVH score was 5.87/12 points (SD = 2.13). No participants met “ideal” on all CVH components (blood glucose: 48 %, cholesterol: 46 %, physical activity: 38 %, body mass index: 24 %, blood pressure: 22 %, diet: 3 %). CVH scores did not change from baseline to end-of-treatment (M = 0.18 points, SD = 1.36, p = .177), nor did change in depression × smoking predict change in CVH (p = .978). However, greater reductions in depression were significantly associated with greater improvements in CVH (β = −0.04, SE = 0.01, p = .015). Limitations: This study was limited by a short follow-up period, missing blood glucose and cholesterol data, and treatment-seeking smokers. Conclusions: Adults with comorbid depression and smoking had poor CVH. Although integrated treatment for depression and smoking improved both conditions, only reductions in depression were associated with improvements in CVH. These findings have implications for integrating psychosocial treatment into CVH promotion efforts. Registration: NCT02378714 (clinicaltrials.gov). © 2023 Elsevier B.V.
Author Keywords
Behavioral activation; Cardiovascular health; Comorbidity; Depression; Smoking; Smoking cessation
Funding details
UL1TR001422
National Heart, Lung, and Blood InstituteNHLBIF31HL129494
National Cancer InstituteNCIR01CA184211
Feinberg School of MedicineUG3HL154297
Document Type: Article
Publication Stage: Final
Source: Scopus
Circadian clock protein BMAL1 broadly influences autophagy and endolysosomal function in astrocytes
(2023) Proceedings of the National Academy of Sciences of the United States of America, 120 (20), pp. e2220551120.
McKee, C.A.a b , Polino, A.J.c , King, M.W.a b , Musiek, E.S.a b
a Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
b Center on Biological Rhythms and Sleep, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
c Department of Cell Biology and Physiology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
Abstract
An emerging role for the circadian clock in autophagy and lysosome function has opened new avenues for exploration in the field of neurodegeneration. The daily rhythms of circadian clock proteins may coordinate gene expression programs involved not only in daily rhythms but in many cellular processes. In the brain, astrocytes are critical for sensing and responding to extracellular cues to support neurons. The core clock protein BMAL1 serves as the primary positive circadian transcriptional regulator and its depletion in astrocytes not only disrupts circadian function but also leads to a unique cell-autonomous activation phenotype. We report here that astrocyte-specific deletion of Bmal1 influences endolysosome function, autophagy, and protein degradation dynamics. In vitro, Bmal1-deficient astrocytes exhibit increased endocytosis, lysosome-dependent protein cleavage, and accumulation of LAMP1- and RAB7-positive organelles. In vivo, astrocyte-specific Bmal1 knockout (aKO) brains show accumulation of autophagosome-like structures within astrocytes by electron microscopy. Transcriptional analysis of isolated astrocytes from young and aged Bmal1 aKO mice indicates broad dysregulation of pathways involved in lysosome function which occur independently of TFEB activation. Since a clear link has been established between neurodegeneration and endolysosome dysfunction over the course of aging, this work implicates BMAL1 as a key regulator of these crucial astrocyte functions in health and disease.
Author Keywords
astrocyte; autophagy; Bmal1; circadian; lysosome
Document Type: Article
Publication Stage: Final
Source: Scopus
Abrogation of MAP4K4 protein function causes congenital anomalies in humans and zebrafish
(2023) Science Advances, 9 (17), p. eade0631.
Patterson, V.a b , Ullah, F.c , Bryant, L.d , Griffin, J.N.e , Sidhu, A.f , Saliganan, S.g , Blaile, M.h , Saenz, M.S.h , Smith, R.i , Ellingwood, S.i , Grange, D.K.j , Hu, X.k , Mireguli, M.l , Luo, Y.l , Shen, Y.m n , Mulhern, M.o , Zackai, E.d , Ritter, A.d , Izumi, K.d , Hoefele, J.p , Wagner, M.p q r , Riedhammer, K.M.p s , Seitz, B.t , Robin, N.H.u , Goodloe, D.u , Mignot, C.v , Keren, B.w , Cox, H.w , Jarvis, J.w , Hempel, M.x , Gibson, C.F.y , Tran Mau-Them, F.z , Vitobello, A.aa ab , Bruel, A.-L.z , Sorlin, A.z , Mehta, S.ac , Raymond, F.L.ad , Gilmore, K.ae , Powell, B.C.af , Weck, K.ag , Li, C.ah , Vulto-van Silfhout, A.T.ai , Giacomini, T.aj , Mancardi, M.M.ak , Accogli, A.al am , Salpietro, V.an , Zara, F.an , Vora, N.L.ae , Davis, E.E.c , Burdine, R.a , Bhoj, E.d
a Princeton University, Princeton, NJ 08544, United States
b Department of Biology, University of York, York, United Kingdom
c Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Departments of Pediatrics and Cell and Developmental Biology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, United States
d Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
e University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, United Kingdom
f Stead Family Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA 52242, United States
g Ambry Genetics, 1 Enterprise, Aliso Viejo, CA 92656, USA
h University of Colorado Anschutz Medical Campus, 13001 E 17th Pl, Aurora, CO 80045, United States
i Maine Medical Center, 22 Bramhall StPortland, United States
j St. Louis Children’s Hospital, Washington University School of Medicine, 660 S Euclid AveMO 63110, United States
k Beijing Key Laboratory for Genetics of Birth Defects, Beijing Pediatric Research Institute, MOE Key Laboratory of Major Diseases in Children, Genetics and Birth Defects Control Center, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s HealthBeijing, China
l First Affiliated Hospital of Xinjiang Medical University, Department of Pediatrics, Xinjiang Uygur Autonomous Region, China
m Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, United States
n Maternal and Child Care Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
o Columbia University Irving Medical Center, 630 W. 168th St, NY, 10032, United States
p Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
q Institute of Neurogenomics, Helmholtz Zentrum München ,Neuherberg, Germany
r Department of Pediatrics, Division of Pediatric Neurology, Developmental Medicine and Social Pediatrics, University Hospital of Munich, Ludwig Maximilians University, Munich, Germany
s Department of Nephrology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
t KfH Pediatric Kidney Center Munich, Munich, Germany
u University of Alabama at Birmingham, 1720 University Blvd, Birmingham, AL 35233, USA
v GH Pitié-Salpêtrière, Paris, France
w Clinical Genetics Unit, Birmingham Women’s and Children’s NHS Foundation Trust, Mindelsohn Way, Birmingham, B15 2TG, United Kingdom
x University Hospital Hamburg-Eppendorf, Martinistraße 52Hamburg 20251, Germany
y Trillium Health Partners, Mississauga, Canada
z University of Bourgogne, Dijon, France
aa UMR1231 GAD, Inserm, Université Bourgogne-Franche-Comté, Dijon, France
ab Unité Fonctionnelle Innovation en Diagnostic génomique des maladies rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
ac Addenbrooke’s Hospital, Cambridge, United Kingdom
ad University of Cambridge, Cambridge, United Kingdom
ae Department of Ob/Gyn, Division of Maternal-Fetal Medicine, University of North Carolina at Chapel Hill, Chapel HillNC 27599, United States
af Department of Genetics, University of North Carolina at Chapel Hill, Chapel HillNC 27599, United States
ag Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel HillNC 27599, United States
ah McMaster University, 1280 Main St WHamilton ON L8S 4L8, Canada
ai Radboudumc Nijmegen, HB Nijmegen, 6500, Netherlands
aj Unit of Child Neuropsychiatry, University of Genova, EpiCARE Network, IRCCS Istituto Giannina Gaslini, Genova, Italy
ak Unit of Child Neuropsychiatry, EpiCARE Network, IRCCS Istituto Giannina Gaslini, Genova, Italy
al Division of Medical Genetics, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
am Department of Human Genetics, McGill University, Montreal, QC, Canada
an Department of Biotechnological and Applied Clinical Science, University of L’Aquila, L’Aquila, 67100, Italy
Abstract
We report 21 families displaying neurodevelopmental differences and multiple congenital anomalies while bearing a series of rare variants in mitogen-activated protein kinase kinase kinase kinase 4 (MAP4K4). MAP4K4 has been implicated in many signaling pathways including c-Jun N-terminal and RAS kinases and is currently under investigation as a druggable target for multiple disorders. Using several zebrafish models, we demonstrate that these human variants are either loss-of-function or dominant-negative alleles and show that decreasing Map4k4 activity causes developmental defects. Furthermore, MAP4K4 can restrain hyperactive RAS signaling in early embryonic stages. Together, our data demonstrate that MAP4K4 negatively regulates RAS signaling in the early embryo and that variants identified in affected humans abrogate its function, establishing MAP4K4 as a causal locus for individuals with syndromic neurodevelopmental differences.
Document Type: Article
Publication Stage: Final
Source: Scopus
Increased Cognitive Effort Costs in Healthy Aging and Preclinical Alzheimer’s Disease
(2023) Psychology and Aging, .
Aschenbrenner, A.J.a , Crawford, J.L.b , Peelle, J.E.c , Fagan, A.M.a , Benzinger, T.L.S.d , Morris, J.C.a , Hassenstab, J.a b , Braver, T.S.b
a Department of Neurology, Washington University, St. Louis, United States
b Department of Psychological and Brain Sciences, Washington University, St. Louis, United States
c Department of Otolaryngology, Washington University, St. Louis, United States
d Department of Radiology, Washington University, St. Louis, United States
Abstract
Life-long engagement in cognitively demanding activities may mitigate against declines in cognitive ability observed in healthy or pathological aging. However, the “mental costs” associated with completing cognitive tasks also increase with age and may be partly attributed to increases in preclinical levels of Alzheimer’s disease (AD) pathology, specifically amyloid. We test whether cognitive effort costs increase in a domaingeneral manner among older adults, and further, whether such age-related increases in cognitive effort costs are associated with working memory (WM) capacity or amyloid burden, a signature pathology of AD. In two experiments, we administered a behavioral measure of cognitive effort costs (cognitive effort discounting) to a sample of older adults recruited from online sources (Experiment 1) or from ongoing longitudinal studies of aging and dementia (Experiment 2). Experiment 1 compared age-related differences in cognitive effort costs across two domains,WMand speech comprehension. Experiment 2 compared cognitive effort costs between a group of participants who were rated positive for amyloid relative to those with no evidence of amyloid. Results showed age-related increases in cognitive effort costs were evident in both domains. Cost estimates were highly correlated between the WM and speech comprehension tasks but did not correlate with WM capacity. In addition, older adults who were amyloid positive had higher cognitive effort costs than those who were amyloid negative. Cognitive effort costs may index a domain-general trait that consistently increases in aging. Differences in cognitive effort costs associatedwith amyloid burden suggest a potential neurobiological mechanism for age-related differences © 2023 American Psychological Association
Author Keywords
aging; Alzheimer’s disease; amyloid; cognitive effort
Funding details
National Institute on AgingNIAP01-AG03991, P01-AG26276, P30-AG066444, P50-AG05681, R21-AG067295
National Institute of Neurological Disorders and StrokeNINDSR24-AG054355, T32-NS115672
Alzheimer’s AssociationAA2019-AARF-643898
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Open-source statistical and data processing tools for wide-field optical imaging data in mice
(2023) Neurophotonics, 10 (1), art. no. 016601, .
Brier, L.M.a , Culver, J.P.a b c d
a Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
b Department of Physics, Washington University School of Arts and Science, St. Louis, MO, United States
c Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO, United States
d Department of Electrical and Systems Engineering, Washington University School of Engineering, St. Louis, MO, United States
Abstract
Significance: Wide-field optical imaging (WOI) can produce concurrent hemodynamic and cell-specific calcium recordings across the entire cerebral cortex in animal models. There have been multiple studies using WOI to image mouse models with various environmental or genetic manipulations to understand various diseases. Despite the utility of pursuing mouse WOI alongside human functional magnetic resonance imaging (fMRI), and the multitude of analysis toolboxes in the fMRI literature, there is not an available open-source, user-friendly data processing and statistical analysis toolbox for WOI data. Aim: To assemble a MATLAB toolbox for processing WOI data, as described and adapted to combine techniques from multiple WOI groups and fMRI. Approach: We outline our MATLAB toolbox on GitHub with multiple data analysis packages and translate a commonly used statistical approach from the fMRI literature to the WOI data. To illustrate the utility of our MATLAB toolbox, we demonstrate the ability of the processing and analysis framework to detect a well-established deficit in a mouse model of stroke and plot activation areas during an electrical paw stimulus experiment. Results: Our processing toolbox and statistical methods isolate a somatosensory-based deficit 3 days following photothrombotic stroke and cleanly localize sensory stimulus activations. Conclusions: The toolbox presented here details an open-source, user-friendly compilation of WOI processing tools with statistical methods to apply to any biological question investigated with WOI techniques. © The Authors.
Author Keywords
calcium imaging; data processing; optical imaging; wide-field imaging
Funding details
National Institutes of HealthNIHR01NS090874, R01NS099429
National Institute on AgingNIAF30AG061932
Document Type: Article
Publication Stage: Final
Source: Scopus
Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium
(2023) Molecular Psychiatry, .
Dwyer, D.B.a b c , Chand, G.B.d e , Pigoni, A.f g , Khuntia, A.a h , Wen, J.d , Antoniades, M.d , Hwang, G.d , Erus, G.d , Doshi, J.d , Srinivasan, D.d , Varol, E.d i , Kahn, R.S.j , Schnack, H.G.k , Meisenzahl, E.l , Wood, S.J.b c m , Zhuo, C.n , Sotiras, A.o , Shinohara, R.T.d p , Shou, H.d p , Fan, Y.d , Schaulfelberger, M.q , Rosa, P.q , Lalousis, P.A.r , Upthegrove, R.r s , Kaczkurkin, A.N.t , Moore, T.M.u , Nelson, B.b c , Gur, R.E.u , Gur, R.C.u , Ritchie, M.D.v , Satterthwaite, T.D.d u w , Murray, R.M.x , Di Forti, M.x , Ciufolini, S.x , Zanetti, M.V.q y , Wolf, D.H.d u , Pantelis, C.z , Crespo-Facorro, B.aa ab ac ad , Busatto, G.F.q , Davatzikos, C.d , Koutsouleris, N.a h x , Dazzan, P.x
a Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
b Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, Australia
c Orygen, Melbourne, VIC, Australia
d Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
e Department of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
f Department of Neurosciences and Mental Health, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
g Social and Affective Neuroscience Group, MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
h Max-Planck Institute of Psychiatry, Munich, Germany
i Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, United States
j Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
k Department of Psychiatry, University Medical Center Utrecht, Utrecht, Netherlands
l LVR-Klinikum Düsseldorf, Kliniken der Heinrich-Heine-Universität, Düsseldorf, Germany
m University of Birmingham, Edgbaston, United Kingdom
n Department of Psychiatric-Neuroimaging-Genetics and Co-morbidity Laboratory (PNGC-Lab), Nankai University Affiliated Tianjin Anding Hospital; Department of Psychiatry, Tianjin Medical University, Tianjin, China
o Department of Radiology and Institute for Informatics, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
p Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
q Institute of Psychiatry, Faculty of Medicine, University of São Paulo, São Paulo, Brazil
r Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, United Kingdom
s Early Intervention Service, Birmingham Women’s and Children’s NHS Foundation Trust, Birmingham, United Kingdom
t Department of Psychology, Vanderbilt University, Nashville, TN, United States
u Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
v Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
w Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, United States
x Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
y Hospital Sírio-Libanês, São Paulo, Brazil
z Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
aa Mental Health Service, Hospital Universitario Virgen del Rocío, Seville, Spain
ab Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III (CIBERSAM), Madrid, Spain
ac Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain
ad Department of Psychiatry, Universidad de Sevilla, Seville, Spain
Abstract
Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups—a ‘lower brain volume’ subgroup (SG1) and an ‘higher striatal volume’ subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership (‘None’), and mixed SG1 + SG2 subgroups (‘Mixed’). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of ‘lower brain volume’ in SG1 and ‘higher striatal volume’ (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature. © 2023, The Author(s).
Funding details
National Institutes of HealthNIHR01MH112070
National Health and Medical Research CouncilNHMRCGA126980, R01M123550, R01MH119219
Lundbeckfonden
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Skeletal muscle delimited myopathy and verapamil toxicity in SUR2 mutant mouse models of AIMS
(2023) EMBO Molecular Medicine, .
McClenaghan, C.a b , Mukadam, M.A.a , Roeglin, J.a , Tryon, R.C.a , Grabner, M.c , Dayal, A.c , Meyer, G.A.d , Nichols, C.G.a
a Center for the Investigation of Membrane Excitability Diseases, and Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, United States
b Center for Advanced Biotechnology and Medicine, and Departments of Pharmacology and Medicine, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, United States
c Department of Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
d Program in Physical Therapy, Departments of Orthopaedic Surgery, Neurology and Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, United States
Abstract
ABCC9-related intellectual disability and myopathy syndrome (AIMS) arises from loss-of-function (LoF) mutations in the ABCC9 gene, which encodes the SUR2 subunit of ATP-sensitive potassium (KATP) channels. KATP channels are found throughout the cardiovascular system and skeletal muscle and couple cellular metabolism to excitability. AIMS individuals show fatigability, muscle spasms, and cardiac dysfunction. We found reduced exercise performance in mouse models of AIMS harboring premature stop codons in ABCC9. Given the roles of KATP channels in all muscles, we sought to determine how myopathy arises using tissue-selective suppression of KATP and found that LoF in skeletal muscle, specifically, underlies myopathy. In isolated muscle, SUR2 LoF results in abnormal generation of unstimulated forces, potentially explaining painful spasms in AIMS. We sought to determine whether excessive Ca2+ influx through CaV1.1 channels was responsible for myopathology but found that the Ca2+ channel blocker verapamil unexpectedly resulted in premature death of AIMS mice and that rendering CaV1.1 channels nonpermeable by mutation failed to reverse pathology; results which caution against the use of calcium channel blockers in AIMS. © 2023 The Authors. Published under the terms of the CC BY 4.0 license.
Author Keywords
ABCC9; AIMS; myopathy; SUR2; verapamil
Funding details
National Institutes of HealthNIHR35 HL140024
American Heart AssociationAHA19POST34380407, K99/R00 HL150277
University of WashingtonUW
Musculoskeletal Research Center, Washington University in St. LouisMRC
Austrian Science FundFWFP23229‐B09, P27392‐B21
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Efficacy and Safety of Viltolarsen in Boys With Duchenne Muscular Dystrophy: Results From the Phase 2, Open-Label, 4-Year Extension Study
(2023) Journal of Neuromuscular Diseases, 10 (3), pp. 439-447.
Clemens, P.R.a b , Rao, V.K.c , Connolly, A.M.d , Harper, A.D.e , Mah, J.K.f , McDonald, C.M.g , Smith, E.C.h , Zaidman, C.M.i , Nakagawa, T.j , Hoffman, E.P.k , CINRG DNHS Investigatorsl
a Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
b Department of Veterans Affairs Medical Center, Pittsburgh, PA, United States
c Division of Neurology, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, United States
d Division of Neurology, Ohio State University College of Medicine, Nationwide Children’s Hospital, Columbus, OH, United States
e Children’s Hospital of Richmond at Virginia Common wealth University, Richmond, VA, United States
f Department of Pediatrics, University of Calgary, Calgary, AB, Canada
g Department of Physical Medicine and Rehabilitation, Department of Pediatrics, UC Davis Health, University of California, Davis, Sacramento, CA, USA
h Department of Pediatrics, Duke University Medical Center, Durham, NC, United States
i Department of Neurology, Washington University at St Louis, St Louis, MO, United States
j NS Pharma, Inc., Paramus, NJ, United States
k Department of Pharmaceutical Sciences, Binghamton University – State University of New York, Binghamton, NY, United States
Abstract
BACKGROUND: Duchenne muscular dystrophy (DMD) is caused by DMD gene mutations, resulting in absence of functional dystrophin protein. Viltolarsen, an exon 53 skipping therapy, significantly increased dystrophin levels in patients with DMD. Presented here are completed study results of > 4 years of functional outcomes in viltolarsen-treated patients compared to a historical control group (Cooperative International Neuromuscular Research Group Duchenne Natural History Study [CINRG DNHS]). OBJECTIVE: To evaluate the efficacy and safety of viltolarsen for an additional 192 weeks in boys with DMD. METHODS: This phase 2, open-label, 192-week long-term extension (LTE) study (NCT03167255) evaluated the efficacy and safety of viltolarsen in participants aged 4 to < 10 years at baseline with DMD amenable to exon 53 skipping. All 16 participants from the initial 24-week study enrolled into this LTE. Timed function tests were compared to the CINRG DNHS group. All participants received glucocorticoid treatment. The primary efficacy outcome was time to stand from supine (TTSTAND). Secondary efficacy outcomes included additional timed function tests. Safety was continuously assessed. RESULTS: For the primary efficacy outcome (TTSTAND), viltolarsen-treated patients showed stabilization of motor function over the first two years and significant slowing of disease progression over the following two years compared with the CINRG DNHS control group which declined. Viltolarsen was well tolerated, with most reported treatment-emergent adverse events being mild or moderate. No participants discontinued drug during the study. CONCLUSIONS: Based on the results of this 4-year LTE, viltolarsen can be an important treatment strategy for DMD patients amenable to exon 53 skipping.
Author Keywords
clinical efficacy; Duchenne muscular dystrophy; dystrophin; exon skipping; viltolarsen
Document Type: Article
Publication Stage: Final
Source: Scopus
Spike-phase coupling patterns reveal laminar identity in primate cortex
(2023) eLife, 12, art. no. e84512, .
Davis, Z.W.a , Dotson, N.M.a , Franken, T.P.a b , Muller, L.c d , Reynolds, J.H.a
a The Salk Institute for Biological Studies, La Jolla, United States
b Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, United States
c Department of Mathematics, Western University, London, Canada
d Brain and Mind Institute, Western University, London, Canada
Abstract
The cortical column is one of the fundamental computational circuits in the brain. In order to understand the role neurons in different layers of this circuit play in cortical function it is necessary to identify the boundaries that separate the laminar compartments. While histological approaches can reveal ground truth they are not a practical means of identifying cortical layers in vivo. The gold standard for identifying laminar compartments in electrophysiological recordings is current-source density (CSD) analysis. However, laminar CSD analysis requires averaging across reliably evoked responses that target the input layer in cortex, which may be difficult to generate in less well-studied cortical regions. Further, the analysis can be susceptible to noise on individual channels resulting in errors in assigning laminar boundaries. Here, we have analyzed linear array recordings in multiple cortical areas in both the common marmoset and the rhesus macaque. We describe a pattern of laminar spike–field phase relationships that reliably identifies the transition between input and deep layers in cortical recordings from multiple cortical areas in two different non-human primate species. This measure corresponds well to estimates of the location of the input layer using CSDs, but does not require averaging or specific evoked activity. Laminar identity can be estimated rapidly with as little as a minute of ongoing data and is invariant to many experimental parameters. This method may serve to validate CSD measurements that might otherwise be unreliable or to esti-mate laminar boundaries when other methods are not practical. © Davis et al.
Funding details
National Science FoundationNSF
National Institutes of HealthNIHK99 EY031795, P30 EY019005, R01-EY028723, T32 EY020503-06
Brain and Behavior Research FoundationBBRF
National Alliance for Research on Schizophrenia and DepressionNARSAD
Canadian Institutes of Health ResearchIRSC2015276
Gatsby Charitable Foundation
Western UniversityUWO
Canada First Research Excellence FundCFREF
Alliance de recherche numérique du Canadal’Alliance
Document Type: Article
Publication Stage: Final
Source: Scopus
Do personality characteristics predict future alcohol problems after considering current demography, substance use, and alcohol response?
(2023) Alcoholism: Clinical and Experimental Research, .
Schuckit, M.A.a , Smith, T.L.b , Danko, G.a , Bucholz, K.K.c , Hesselbrock, V.d , Hesselbrock, M.d , Kuperman, S.e , Kramer, J.f , Nurnberger, J.I.g , Lai, D.h , Chan, G.i , Kamarajan, C.j , Kuo, S.k , Dick, D.M.l , Tear, J.m , Mendoza, L.A.a , Edenberg, H.J.n , Porjesz, B.o
a Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
b University of California, San Diego, La Jolla, CA, United States
c Washington University School of Medicine, Psychiatry, Saint Louis, MO, United States
d Department of Psychiatry, University of Connecticut, Farmington, CT, United States
e Child Psychiatry Clinic, UIHC Department of Psychiatry, The University of Iowa, Iowa City, IA, United States
f Psychiatry, University of Iowa, Iowa City, IA, United States
g Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, United States
h Indiana University School of Medicine, Indianapolis, IN, United States
i Department of Psychiatry, University of Connecticut Health Center, Farmington, CT, United States
j Henri Begleiter Neurodynamics Lab, SUNY Downstate Medical Center, Brooklyn, NY, United States
k VCU Psychology, Virginia Commonwealth University, Richmond, VA, United States
l Psychiatry, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, United States
m Department of Psychiatry, University of California, La Jolla, CA, United States
n Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, United States
o Psychiatry and Behavioral Sciences, State University of New York, Downstate, Brooklyn, NY, United States
Abstract
Background: Several personality traits predict future alcohol problems but also relate to demographic and substance-related variables that themselves correlate with later adverse alcohol outcomes. Few prospective studies have evaluated whether personality measures predict alcohol problems after considering current demographic and substance-related variables. Methods: Data from 414 drinkers without alcohol use disorder (AUD) from the Collaborative Study on the Genetics of Alcoholism (average age 20, 44% male) were followed over an average of 9 years. Time 1 (baseline) demography, AUD family history (FH), substance use and problems, and psychiatric histories were gathered using a standardized interview; the Level of Response (LR) to alcohol was measured by the Self-Report of the Effects of alcohol (SRE) questionnaire; and seven personality dimensions were extracted from the NEO Five-Factor Personality, Barratt, and Zuckerman scales. Analyses involved product–moment correlations of each baseline measure with the highest number of DSM-IV AUD criteria endorsed in any follow-up period, and hierarchical regression analyses evaluated whether the personality domains added significantly to the prediction of the outcome after adjusting for other baseline variables. Results: Significant correlations with the outcome were observed for baseline age, sex, length of follow-up, AUD family history, past cannabis use, and all alcohol-related baseline variables, including SRE-based LR, but not prior mood or anxiety disorders. All personality characteristics except extraversion also correlated with outcomes. A hierarchical regression analysis that included all relevant personality scores together demonstrated significant contributions to the prediction of future alcohol problems for demographics in Step 1; demographics and most baseline alcohol items, including response level, in Step 2; and cannabis use in Step 3; after which demographics, LR, baseline alcohol problems, cannabis use, and higher sensation seeking added significantly in Step 4. Regression for each personality domain separately revealed significant contributions to Step 4 for all personality domains except openness. Lower levels of response to alcohol added significantly to all regression analyses. Conclusions: Most tested personality scores and lower levels of response to alcohol contributed to predictions of later alcohol problems even after considering baseline demographic and substance use measures. © 2023 Research Society on Alcohol.
Author Keywords
alcohol; alcohol response; AUD problems; personality
Funding details
National Institutes of HealthNIHU10 AA008401
National Institute on Drug AbuseNIDA
National Institute on Alcohol Abuse and AlcoholismNIAAA
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Protein kinetics of superoxide dismutase-1 in familial and sporadic amyotrophic lateral sclerosis
(2023) Annals of Clinical and Translational Neurology, .
Ly, C.V.a , Ireland, M.D.a , Self, W.K.a , Bollinger, J.a , Jockel-Balsarotti, J.a , Herzog, H.a , Allred, P.a , Miller, L.b , Doyle, M.b , Anez-Bruzual, I.b , Trikamji, B.a , Hyman, T.a , Kung, T.a , Nicholson, K.b , Bucelli, R.C.a , Patterson, B.W.c , Bateman, R.J.a d e , Miller, T.M.a d
a Department of Neurology, Washington University, Saint Louis, MO, United States
b Sean M. Healey & AMG Center for ALS, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
c Department of Medicine, Washington University, Saint Louis, MO, United States
d Hope Center for Neurological Disorders, Washington University, Saint Louis, MO, United States
e Knight Alzheimer’s Disease Research Center, Washington University, Saint Louis, MO, United States
Abstract
Objective: Accumulation of misfolded superoxide dismutase-1 (SOD1) is a pathological hallmark of SOD1-related amyotrophic lateral sclerosis (ALS) and is observed in sporadic ALS where its role in pathogenesis is controversial. Understanding in vivo protein kinetics may clarify how SOD1 influences neurodegeneration and inform optimal dosing for therapies that lower SOD1 transcripts. Methods: We employed stable isotope labeling paired with mass spectrometry to evaluate in vivo protein kinetics and concentration of soluble SOD1 in cerebrospinal fluid (CSF) of SOD1 mutation carriers, sporadic ALS participants and controls. A deaminated SOD1 peptide, SDGPVKV, that correlates with protein stability was also measured. Results: In participants with heterozygous SOD1A5V mutations, known to cause rapidly progressive ALS, mutant SOD1 protein exhibited ~twofold faster turnover and ~ 16-fold lower concentration compared to wild-type SOD1 protein. SDGPVKV levels were increased in SOD1A5V carriers relative to controls. Thus, SOD1 mutations impact protein kinetics and stability. We applied this approach to sporadic ALS participants and found that SOD1 turnover, concentration, and SDGPVKV levels are not significantly different compared to controls. Interpretation: These results highlight the ability of stable isotope labeling approaches and peptide deamidation to discern the influence of disease mutations on protein kinetics and stability and support implementation of this method to optimize clinical trial design of gene and molecular therapies for neurological disorders. Trial Registration: Clinicaltrials.gov: NCT03449212. © 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.
Funding details
National Institutes of HealthNIHK08 NS107621, P30 DK056341, R01 NS097816
Biogen
Novartis Pharmaceuticals CorporationNPC
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
“Brain age” predicts disability accumulation in multiple sclerosis
(2023) Annals of Clinical and Translational Neurology, .
Brier, M.R.a , Li, Z.a , Ly, M.b c , Karim, H.T.c d , Liang, L.e , Du, W.e , McCarthy, J.E.e , Cross, A.H.a , Benzinger, T.L.S.b , Naismith, R.T.a , Chahin, S.a
a Department of Neurology, Washington University in St. Louis, St Louis, MO, United States
b Mallinckrodt Institute of Radiology, Washington University in St. Louis, St Louis, MO, United States
c Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
d Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
e Department of Mathematics and Statistics, Washington University in St. Louis, St Louis, MO, United States
Abstract
Objective: Neurodegenerative conditions often manifest radiologically with the appearance of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well developed, but measures of neurodegeneration are less well-developed. The appearance of premature aging quantified by machine learning applied to structural MRI assesses neurodegenerative pathology. We assess the explanatory and predictive power of “brain age” analysis on disability in MS using a large, real-world dataset. Methods: Brain age analysis is predicated on the over-estimation of predicted brain age in patients with more advanced pathology. We compared the performance of three brain age algorithms in a large, longitudinal dataset (>13,000 imaging sessions from >6,000 individual MS patients). Effects of MS, MS disease course, disability, lesion burden, and DMT efficacy were assessed using linear mixed effects models. Results: MS was associated with advanced predicted brain age cross-sectionally and accelerated brain aging longitudinally in all techniques. While MS disease course (relapsing vs. progressive) did contribute to advanced brain age, disability was the primary correlate of advanced brain age. We found that advanced brain age at study enrollment predicted more disability accumulation longitudinally. Lastly, a more youthful appearing brain (predicted brain age less than actual age) was associated with decreased disability. Interpretation: Brain age is a technically tractable and clinically relevant biomarker of disease pathology that correlates with and predicts increasing disability in MS. Advanced brain age predicts future disability accumulation. © 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.
Funding details
National Institutes of HealthNIH2R25NS090978‐06, K01MH122741, KL2TR002346
Division of Mathematical SciencesDMS2054199, R01AG052550
Alzheimer’s AssociationAA
Bristol-Myers SquibbBMS
Biogen
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Efficacy and safety of combination behavioral activation for smoking cessation and varenicline for treating tobacco dependence among individuals with current or past major depressive disorder: A 2 × 2 factorial, randomized, placebo-controlled trial
(2023) Addiction, . Cited 1 time.
Hitsman, B.a b d , Papandonatos, G.D.c , Gollan, J.K.d e , Huffman, M.D.a f g , Niaura, R.h , Mohr, D.C.b d , Veluz-Wilkins, A.K.a , Lubitz, S.F.i , Hole, A.i , Leone, F.T.j , Khan, S.S.a , Fox, E.N.a , Bauer, A.-M.i , Wileyto, E.P.i , Bastian, J.i , Schnoll, R.A.i
a Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
b Robert H. Lurie Comprehensive Cancer Center of Northwestern University, United States
c Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, United States
d Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, United States
e Asher Center for the Study and Treatment of Depressive Disorders, Chicago, IL, United States
f John T. Milliken Department of Medicine, Washington University School of Medicine, Washington University in St. Louis, St. Louis, MO, United States
g Cardiovascular Program, The George Institute for Global Health, University of South Wales, Newtown, NSW, Australia
h Department of Epidemiology, School of Global Public Health, New York University, New York, NY, United States
i Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
j Department of Medicine, University of Pennsylvania Perelman School of Medicine, Perelman Center for Advanced Medicine, Philadelphia, PA, United States
Abstract
Background and Aims: Treatment of depression-related psychological factors related to smoking behavior may improve rates of cessation among adults with major depressive disorder (MDD). This study measured the efficacy and safety of 12 weeks of behavioral activation for smoking cessation (BASC), varenicline and their combination. Design, Setting, Participants: This study used a randomized, placebo-controlled, 2 × 2 factorial design comparing BASC versus standard behavioral treatment (ST) and varenicline versus placebo, taking place in research clinics at two urban universities in the United States. Participants comprised 300 hundred adult smokers with current or past MDD. Interventions: BASC integrated behavioral activation therapy and ST to increase engagement in rewarding activities by reducing avoidance, withdrawal and inactivity associated with depression. ST was based on the 2008 PHS Clinical Practice Guideline. Both treatments consisted of eight 45-min sessions delivered between weeks 1 and 12. Varenicline and placebo were administered for 12 weeks between weeks 2 and 14. Measurements: Primary outcomes were bioverified intent-to-treat (ITT) 7-day point-prevalence abstinence at 27 weeks and adverse events (AEs). Findings: No significant interaction was detected between behavioral treatment and pharmacotherapy at 27 weeks (χ2(1) = 0.19, P = 0.67). BASC and ST did not differ (χ2(1) = 0.43, P = 0.51). Significant differences in ITT abstinence rates (χ2(1) = 4.84, P = 0.03) emerged among pharmacotherapy arms (16.2% for varenicline, 7.5% for placebo), with results favoring varenicline over placebo (rate ratio = 2.16, 95% confidence interval = 1.08, 4.30). All significant differences in AE rates after start of medication were higher for placebo than varenicline. Conclusion: A randomized trial in smokers with major depressive disorder found that varenicline improved smoking abstinence versus placebo at 27 weeks without elevating rates of adverse events. Behavioral activation for smoking cessation did not outperform standard behavioral treatment, with or without adjunctive varenicline therapy. © 2023 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.
Author Keywords
adults; behavioral activation therapy; major depressive disorder; smoking cessation treatment; tobacco dependence; varenicline
Document Type: Article
Publication Stage: Article in Press
Source: Scopus