“The CSF in neurosarcoidosis contains consistent clonal expansion of CD8 T cells, but not CD4 T cells” (2022) Journal of Neuroimmunology
The CSF in neurosarcoidosis contains consistent clonal expansion of CD8 T cells, but not CD4 T cells(2022) Journal of Neuroimmunology, 367, art. no. 577860, .
Paley, M.A.a , Baker, B.J.b , Dunham, S.R.b , Linskey, N.a , Cantoni, C.b , Lee, K.b , Hassman, L.M.c , Laurent, J.a , Roberson, E.D.O.a d , Clifford, D.B.b , Yokoyama, W.M.a
a Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, United Statesb Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United Statesc Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, United Statesd Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, United States
AbstractThe tissue-specific drivers of neurosarcoidosis remain poorly defined. To identify cerebrospinal fluid (CSF) specific, antigen-driven T and B cell responses, we performed single-cell RNA sequencing of CSF and blood cells from neurosarcoid participants coupled to T and B cell receptor sequencing. In contrast to pulmonary sarcoidosis, which is driven by CD4 T cells, we found CD8 T cell clonal expansion enriched in the neurosarcoid CSF. These CSF-enriched CD8 T cells were composed of two subsets with differential expression of EBI2, CXCR3, and CXCR4. Lastly, our data suggest that IFNγ signaling may distinguish neurosarcoidosis from other neurological disorders. © 2022
Author KeywordsInterferon; Neurosarcoidosis; Sarcoidosis; Single-cell RNA sequencing; T cells; TCR sequencing
Funding detailsP30-AR073752Arthritis National Research FoundationANRFResearch to Prevent BlindnessRPBRheumatology Research FoundationRRFFoundation for Barnes-Jewish HospitalFBJH
Document Type: ArticlePublication Stage: FinalSource: Scopus
“CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease” (2022) Neurobiology of Disease
CSF Tau phosphorylation at Thr205 is associated with loss of white matter integrity in autosomal dominant Alzheimer disease(2022) Neurobiology of Disease, 168, art. no. 105714, .
Strain, J.F.a , Barthelemy, N.a , Horie, K.a , Gordon, B.A.a c d , Kilgore, C.a , Aschenbrenner, A.a , Cruchaga, C.a , Xiong, C.c h , Joseph-Mathurin, N.b c , Hassenstab, J.a c h , Fagan, A.M.a c , Li, Y.a , Karch, C.M.b , Perrin, R.J.a , Berman, S.B.e , Chhatwal, J.P.f , Graff-Radford, N.R.g , Mori, H.h , Levin, J.i , Noble, J.M.m , Allegri, R.j , Schofield, P.R.k l , Marcus, D.S.c , Holtzman, D.M.a c , Morris, J.C.a c , Benzinger, T.L.S.b c , McDade, E.M.a , Bateman, R.J.a c , Ances, B.M.a b c
a Department of Neurology, Washington University, St. Louis, MO 63110, United Statesb Department of Radiology, Washington University, St. Louis, MO 63110, United Statesc Knight Alzheimer’s Disease Research Center, Washington University, St. Louis, MO 63110, United Statesd Department of Psychological & Brain Sciences, Washington University, St. Louis, MO 63110, United Statese Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, United Statesf Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United Statesg Department of Neurology, Mayo Clinic, Jacksonville, FL 32224, United Statesh Osaka City University School of Medicine Asahimachi, Abenoku, Osaka, 545-8585, Japani German Center for Neurodegenerative Disease (DZNE) Munich, Munich, Germanyj School of Medicine, Universidad de Buenos Aires, Viamonte 430, CABA, C1053, Argentinak Neuroscience Research Australia, Sydney, NSW, Australial Hope Center for Neurological Disorders, Washington University, St. Louis, MO 63100, United Statesm Department of Neurology, Columbia University, New York, NY 100310, United States
AbstractBackground: Hyperphosphorylation of tau leads to conformational changes that destabilize microtubules and hinder axonal transport in Alzheimer’s disease (AD). However, it remains unknown whether white matter (WM) decline due to AD is associated with specific Tau phosphorylation site(s). Methods: In autosomal dominant AD (ADAD) mutation carriers (MC) and non-carriers (NC) we compared cerebrospinal fluid (CSF) phosphorylation at tau sites (pT217, pT181, pS202, and pT205) and total tau with WM measures, as derived from diffusion tensor imaging (DTI), and cognition. A WM composite metric, derived from a principal component analysis, was used to identify spatial decline seen in ADAD. Results: The WM composite explained over 70% of the variance in MC. WM regions that strongly contributed to the spatial topography were located in callosal and cingulate regions. Loss of integrity within the WM composite was strongly associated with AD progression in MC as defined by the estimated years to onset (EYO) and cognitive decline. A linear regression demonstrated that amyloid, gray matter atrophy and phosphorylation at CSF tau site pT205 each uniquely explained a reduction in the WM composite within MC that was independent of vascular changes (white matter hyperintensities), and age. Hyperphosphorylation of CSF tau at other sites and total tau did not significantly predict WM composite loss. Conclusions: We identified a site-specific relationship between CSF phosphorylated tau and WM decline within MC. The presence of both amyloid deposition and Tau phosphorylation at pT205 were associated with WM composite loss. These findings highlight a primary AD-specific mechanism for WM dysfunction that is tightly coupled to symptom manifestation and cognitive decline. © 2022
Author KeywordsADAD; CSF; PCA; Phosphorylated tau; White matter
Funding details1P30NS098577, R01 EB009352National Science FoundationNSFDMS1300280National Institutes of HealthNIHP01AG003991, P01AG026276, P30NS048056, P30NS098577, P50AG05681, R01AG04343404, R01AG052550, R01EB009352, R01NR012657, R01NR012907, R01NR014449, UFAG032438, UL1TR000448National Institute on AgingNIAAlzheimer’s AssociationAAAARFD-20-681815BrightFocus FoundationBFFA2018817FFoundation for Barnes-Jewish HospitalFBJHUniversity of WashingtonUWUF1AG032438Japan Agency for Medical Research and DevelopmentAMEDHope Center for Neurological DisordersMedical Research CouncilMRCMR/009076/1, MR/L023784/1National Institute for Health ResearchNIHRKorea Health Industry Development InstituteKHIDIDeutsches Zentrum für Neurodegenerative ErkrankungenDZNEFleni
Document Type: ArticlePublication Stage: FinalSource: Scopus
“(+)-Catharanthine potentiates the GABAA receptor by binding to a transmembrane site at the β(+)/α(-) interface near the TM2-TM3 loop” (2022) Biochemical Pharmacology
(+)-Catharanthine potentiates the GABAA receptor by binding to a transmembrane site at the β(+)/α(-) interface near the TM2-TM3 loop(2022) Biochemical Pharmacology, 199, art. no. 114993, .
Arias, H.R.a , Borghese, C.M.b , Germann, A.L.c , Pierce, S.R.c , Bonardi, A.e , Nocentini, A.e , Gratteri, P.e , Thodati, T.M.b , Lim, N.J.b , Harris, R.A.b , Akk, G.c d
a Department of Pharmacology and Physiology, Oklahoma State University College of Osteopathic Medicine, Tahlequah, OK, United Statesb Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX, United Statesc Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO, United Statesd Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO, United Statese Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), Section of Pharmaceutical and Nutraceutical Sciences, Laboratory of Molecular Modeling Cheminformatics & QSAR, University of Florence, Florence, Italy
Abstract(+)-Catharanthine, a coronaridine congener, potentiates the γ-aminobutyric acid type A receptor (GABAAR) and induces sedation through a non-benzodiazepine mechanism, but the specific site of action and intrinsic mechanism have not been defined. Here, we describe GABAAR subtype selectivity and location of the putative binding site for (+)-catharanthine using electrophysiological, site-directed mutagenesis, functional competition, and molecular docking experiments. Electrophysiological and in silico experiments showed that (+)-catharanthine potentiates the responses to low, subsaturating GABA at β2/3-containing GABAARs 2.4–3.5 times more efficaciously than at β1-containing GABAARs. The activity of (+)-catharanthine is reduced by the β2(N265S) mutation that decreases GABAAR potentiation by loreclezole, but not by the β3(M286C) or α1(Q241L) mutations that reduce receptor potentiation by R(+)-etomidate or neurosteroids, respectively. Competitive functional experiments indicated that the binding site for (+)-catharanthine overlaps that for loreclezole, but not those for R(+)-etomidate or potentiating neurosteroids. Molecular docking experiments suggested that (+)-catharanthine binds at the β(+)/α(-) intersubunit interface near the TM2-TM3 loop, where it forms H-bonds with β2-D282 (TM3), β2-K279 (TM2-TM3 loop), and β2-N265 and β2-R269 (TM2). Site-directed mutagenesis experiments supported the in silico results, demonstrating that the K279A and D282A substitutions, that lead to a loss of H-bonding ability of the mutated residue, and the N265S mutation, impair the gating efficacy of (+)-catharanthine. We infer that (+)-catharanthine potentiates the GABAAR through several H-bond interactions with a binding site located in the β(+)/α(-) interface in the transmembrane domain, near the TM2-TM3 loop, where it overlaps with loreclezole binding site. © 2022 Elsevier Inc.
Author Keywords(+)-Catharanthine; Coronaridine congeners; Electrophysiology; Molecular docking; Molecular dynamics; Positive allosteric modulators
Funding detailsNational Institutes of HealthNIHR01GM108580, R35GM140947, U24AA025479Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine in St. Louis
Document Type: ArticlePublication Stage: FinalSource: Scopus
“A neural population selective for song in human auditory cortex” (2022) Current Biology
A neural population selective for song in human auditory cortex(2022) Current Biology, 32 (7), pp. 1470-1484.e12. Cited 1 time.
Norman-Haignere, S.V.a b c d e f g , Feather, J.g h i , Boebinger, D.g h j , Brunner, P.k l m , Ritaccio, A.k n , McDermott, J.H.g h i j , Schalk, G.k , Kanwisher, N.g h i
a Zuckerman Institute, Columbia University, New York, NY, United Statesb HHMI Fellow of the Life Sciences Research Foundation, Chevy Chase, MD, United Statesc Laboratoire des Sytèmes Perceptifs, Département d’Études Cognitives, ENS, PSL University, CNRS, Paris, Franced Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY, United Statese Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United Statesf Department of Biomedical Engineering, University of Rochester, Rochester, NY, United Statesg Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United Statesh McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United Statesi Center for Brains, Minds and Machines, Cambridge, MA, United Statesj Program in Speech and Hearing Biosciences and Technology, Harvard University, Cambridge, MA, United Statesk Department of Neurology, Albany Medical College, Albany, NY, United Statesl National Center for Adaptive Neurotechnologies, Albany, NY, United Statesm Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United Statesn Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
AbstractHow is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song. © 2022 Elsevier Inc.
Author Keywordsauditory cortex; component; ECoG; electrocorticography; fMRI; music; natural sounds; song; speech; voice
Funding detailsCCF-1231216National Science FoundationNSFBCS-1634050National Institutes of HealthNIHDP1 HD091947, K99DC018051-01A1, P41-EB018783, P50-MH109429, R01-EB026439, R25-HD088157, U01-NS108916, U24-NS109103Howard Hughes Medical InstituteHHMIArmy Research OfficeAROW911NF-15-1-0440Massachusetts Institute of TechnologyMITLife Sciences Research FoundationLSRF
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Capybara: A computational tool to measure cell identity and fate transitions” (2022) Cell Stem Cell
Capybara: A computational tool to measure cell identity and fate transitions(2022) Cell Stem Cell, 29 (4), pp. 635-649.e11.
Kong, W.a b c , Fu, Y.C.a b c , Holloway, E.M.a b c , Garipler, G.d , Yang, X.a b c , Mazzoni, E.O.d , Morris, S.A.a b c
a Department of Developmental Biology, Washington University School of Medicine in St. Louis, Campus Box 8103, 660 S. Euclid Avenue, St. Louis, MO 63110, United Statesb Department of Genetics, Washington University School of Medicine in St. Louis, Campus Box 8103, 660 S. Euclid Avenue, St. Louis, MO 63110, United Statesc Center of Regenerative Medicine, Washington University School of Medicine in St. Louis, Campus Box 8103, 660 S. Euclid Avenue, St. Louis, MO 63110, United Statesd Department of Biology, New York University, New York, NY 10003, United States
AbstractMeasuring cell identity in development, disease, and reprogramming is challenging as cell types and states are in continual transition. Here, we present Capybara, a computational tool to classify discrete cell identity and intermediate “hybrid” cell states, supporting a metric to quantify cell fate transition dynamics. We validate hybrid cells using experimental lineage tracing data to demonstrate the multi-lineage potential of these intermediate cell states. We apply Capybara to diagnose shortcomings in several cell engineering protocols, identifying hybrid states in cardiac reprogramming and off-target identities in motor neuron programming, which we alleviate by adding exogenous signaling factors. Further, we establish a putative in vivo correlate for induced endoderm progenitors. Together, these results showcase the utility of Capybara to dissect cell identity and fate transitions, prioritizing interventions to enhance the efficiency and fidelity of stem cell engineering. © 2022 Elsevier Inc.
Author Keywordscell differentiation; cell reprogramming; cell-type classification; hybrid cells; single-cell analysis
Funding detailsCDI-CORE-2015-505, CDI-CORE-2019-813National Institutes of HealthNIHNational Heart, Lung, and Blood InstituteNHLBIT32 HL007317-44National Institute of General Medical SciencesNIGMSR01 GM126112Silicon Valley Community FoundationSVCFHCA2-A-1708-02799, R01 GM138876New York Stem Cell FoundationNYSCFFoundation for Barnes-Jewish HospitalFBJH3770, 4642Center for Cellular Imaging, Washington UniversityWUCCI
Document Type: ArticlePublication Stage: FinalSource: Scopus
“SORL1 Polymorphisms in Mexican Patients with Alzheimer’s Disease” (2022) Genes
SORL1 Polymorphisms in Mexican Patients with Alzheimer’s Disease(2022) Genes, 13 (4), art. no. 587, .
Toral-Rios, D.a , Ruiz-Sánchez, E.b , Rodríguez, N.L.M.c , Maury-Rosillo, M.d , Rosas-Carrasco, Ó.e , Becerril-Pérez, F.f , Mena-Barranco, F.g , Carvajal-García, R.h , Silva-Adaya, D.i , Delgado-Namorado, Y.j , Ramos-Palacios, G.k , Sánchez-Torres, C.l , Campos-Peña, V.i
a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United Statesb Laboratorio de Neurotoxicología, Instituto Nacional de Neurología y Neurocirugía, Manuel Velasco Suárez, Ciudad de México, 14269, Mexicoc Unidad de Investigación Epidemiológica en Endocrinología y Nutrición, Hospital Infantil de México Federico Gómez, Ciudad de México, 06720, Mexicod Departamento de la Subdirección de Prevención y Protección a la Salud, Dirección Normativa de Salud, Instituto de Seguridad y Servicios Sociales de los Trabajadores del Estado (ISSSTE), Ciudad de México, 14070, Mexicoe Departamento de Salud, Universidad Iberoamericana, Ciudad de México, 01219, Mexicof Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-BioCenter 1, Vienna, 1030, Austriag Hospital General ISSSTE, La Paz, 23090, Mexicoh Centro Geriátrico SINANK’AY, Jurica, Santiago de Querétaro, 76100, Mexicoi Laboratorio Experimental de Enfermedades Neurodegenerativas, Instituto Nacional de Neurología y Neurocirugía, Ciudad de México, 14269, Mexicoj Molecular Biology Laboratory, National Reference Center “Mexico’s Valley”, Salud Digna, Los Reyes, Tlalnepantla de Baz, Estado de Mexico, 54075, Mexicok Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canadal Departamento de Biomedicina Molecular, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Ciudad de México, 07360, Mexico
AbstractThe present study evaluated the risk effect of 12 Single Nucleotide Polymorphisms in the SORL1 gene in the Mexican population using Late-Onset Alzheimer’s Disease (LOAD) and control subjects. Considering APOE as the strongest genetic risk factor for LOAD, we conducted interaction analyses between single nucleotide polymorphisms (SNPs) and the APOE genotype. Methods: Patients were interviewed during their scheduled visits at neurologic and geriatric clinics from different institutions. The LOAD diagnosis included neurological, geriatric, and psychiatric examinations, as well as the medical history and neuroimaging. Polymorphisms in SORL1 were genotyped by real-time PCR in 156 subjects with LOAD and 221 controls. APOE genotype was determined in each study subject. Allelic, genotypic, and haplotypic frequencies were analyzed; an ancestry analysis was also performed. Results: The A/A genotype in rs1784933 might be associated with an increased LOAD risk. Two blocks with high degree linkage disequilibrium (LD) were identified. The first block composed by the genetic variants rs668387, rs689021 and rs641120 showed a positive interaction (mainly the rs689021) with rs1784933 polymorphism. Moreover, we found a significant association between the APOE ε4 allele carriers and the variant rs2070045 located in the second LD block. Conclusion: The rs1784933 polymorphism is associated with LOAD in Mexican patients. In addition, the presence of APOE ε4 allele and SORL1 variants could represent a genetic interaction effect that favors LOAD risk in the Mexican population. SNPs have been proposed as genetic markers associated with the development of LOAD that can support the clinical diagnosis. Future molecular studies could help understand sporadic Alzheimer’s Disease (AD) among the Mexican population, where currently there is a sub-estimate number in terms of disease frequency and incidence. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Author KeywordsAPOE genotype; AβPP processing; AβPP sorting; polymorphic variants; sortilin 1
Funding details069899, 273182Instituto Mexicano del Seguro SocialIMSS
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Timing and Type of Early Psychopathology Symptoms Predict Longitudinal Change in Cortical Thickness From Middle Childhood Into Early Adolescence” (2022) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
Timing and Type of Early Psychopathology Symptoms Predict Longitudinal Change in Cortical Thickness From Middle Childhood Into Early Adolescence(2022) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 7 (4), pp. 397-405.
Luking, K.R.a , Jirsaraie, R.J.b , Tillman, R.c , Luby, J.L.c , Barch, D.M.a c , Sotiras, A.d
a Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, United Statesb Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, Missouri, United Statesc Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, United Statesd Department of Radiology and Institute for Informatics, Washington University School of Medicine, St. Louis, Missouri, United States
AbstractBackground: Early-life experiences have profound effects on functioning in adulthood. Altered cortical development may be one mechanism through which early-life experiences, including poverty and psychopathology symptoms, affect outcomes. However, there is little prospective research beginning early in development that combines clinician-rated psychopathology symptoms and multiwave magnetic resonance imaging to examine when these relationships emerge. Methods: Children from the Preschool Depression Study who completed diagnostic interviews at three different developmental stages (preschool, school age, early adolescent) and up to three magnetic resonance imaging scans beginning in middle childhood participated in this study (N = 138). Multilevel models were used to calculate intercepts and slopes of cortical thickness within a priori cortical regions of interest. Linear regressions probed how early-life poverty and psychopathology (depression, anxiety, and externalizing symptoms at separate developmental periods) related to intercept/slope. Results: Collectively, experiences during the preschool period predicted reduced cortical thickness, via either reduced intercept or accelerated thinning (slope). Early-life poverty predicted intercepts within sensory and sensory-motor integration regions. Beyond poverty, preschool anxiety symptoms predicted intercepts within the insula, subgenual cingulate, and inferior parietal cortex. Preschool externalizing symptoms predicted accelerated thinning within prefrontal and parietal cortices. Depression and anxiety/externalizing symptoms at later ages were not significant predictors. Conclusions: Early childhood is a critical period of risk; experiences at this developmental stage specifically have the potential for prolonged influence on brain development. Negative early experiences collectively predicted reduced cortical thickness, but the specific neural systems affected aligned with those typically implicated in these individual disorders/experiences. © 2021 Society of Biological Psychiatry
Author KeywordsAdolescent; Anxiety; Cortical thickness; Development; Externalizing; Poverty; Preschool
Funding detailsNational Institutes of HealthNIH2R01 MH064769, R01 AG067103, R01 MH090786
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Association of Multidimensional Poverty with Dementia in Adults Aged 50 Years or Older in South Africa” (2022) JAMA Network Open
Association of Multidimensional Poverty with Dementia in Adults Aged 50 Years or Older in South Africa(2022) JAMA Network Open, 5 (3), p. E224160.
Trani, J.-F.a b c , Moodley, J.b , Maw, M.T.T.d , Babulal, G.M.b e f
a Brown School, Washington University, Goldfarb Hall, One Brookings Drive, Campus Box 1196, St Louis, MO 63130, United Statesb Department of Psychology, Faculty of Humanities, University of Johannesburg, Johannesburg, South Africac Center for Social Development in Africa, University of Johannesburg, Johannesburg, South Africad Department of General Internal Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD, United Statese Department of Neurology, Washington University, School of Medicine, St Louis, MO, United Statesf Department of Clinical Research and Leadership, The George Washington University, School of Medicine and Health Sciences, Washington, DC, United States
AbstractImportance: Limited research exists investigating the association between multidimensional poverty and dementia in low-and middle-income countries (LMICs). Objective: To investigate the association between multidimensional poverty and dementia among adults aged 50 years or older living in South Africa. Design, Setting, and Participants: This cross-sectional study was conducted in Soweto, Johannesburg, South Africa, between November 11, 2019, and February 28, 2020. Participants included 227 adults aged 50 years or older. Data analysis was concluded from August 1 to 30, 2021. Exposures: Multidimensional poverty included 7 dimensions that are central to well-being (education, health, economic activity, living standards, social participation, fair treatment, and psychological well-being) and 11 indicators of deprivation within those dimensions (limited access to education; severe limitation of activity; difficulty functioning; unemployment; deprivation of access to running water, electricity, and a flush toilet; lack of involvement in community groups; discrimination; depression; and decreased self-esteem). Main Outcomes and Measures: The 8-item Interview to Differentiate Aging and Dementia (Assessing Dementia 8 [AD8]) and the Rowland Universal Dementia Assessment Scale (RUDAS) were used to assess dementia. Level and depth of poverty were compared between adults with no dementia and those with a score above the threshold for either the AD8 or the RUDAS, or for both the AD8 and the RUDAS, adjusting for gender, age group, and marital status. Correlation analyses assessed the overlap of dimensions of deprivation. Associations between dementia and multidimensional poverty were investigated using a multivariable logistic regression model. Results: A total of 227 adults (146 women [64.3%]; mean [SD] age, 63.7 [0.5] years) were included in the study; 101 (44.5%) had dementia identified by the AD8, 14 (6.2%) had dementia identified by the RUDAS, and 50 (22.0%) had dementia identified by both the AD8 and the RUDAS. More men than women did not have dementia (26 of 81 [32.1%] vs 36 of 146 [24.7%]), and 33 of 165 adults with dementia (20.0%) compared with 6 of 62 adults (9.7%) without dementia were found to be deprived in 4 dimensions or more. The difference between adults with and adults without dementia in the Multidimensional Poverty Index for deprivation in 4 dimensions was 145.8% for dementia identified by both the AD8 and the RUDAS and 118.2% for dementia identified by either the AD8 or the RUDAS. Education, health, and employment were the main contributors to the adjusted poverty head count ratio. Multidimensional poverty was strongly associated with dementia as measured by the AD8 and the RUDAS (adjusted odds ratio [OR], 2.31; 95% CI, 1.08-4.95), with higher odds for older women (OR, 2.03; 95% CI, 1.00-4.12) or those living in large households (for each additional household member: OR, 1.27; 95% CI, 1.05-1.53). Conclusions and Relevance: This study suggests that the prevalence and depth of poverty were higher among adults with dementia. A lack of education, poor health, and unemployment were major dimensions of poverty that were associated with a higher prevalence of dementia. Long-term interventions beginning early in life may affect social determinants of health through targeted structural policies (eg, access to quality education and health care) and prevent dementia later in life.. © 2022 American Institute of Physics Inc.. All rights reserved.
Funding detailsA2021142S, R01AG056466, R01AG067428, R01AG068183, R01AG074302National Institutes of HealthNIHNational Institute on AgingNIAAlzheimer’s AssociationAAAARG-NTF-21-851241University of WashingtonUW
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Assessing the Relationship of Patient Reported Outcome Measures With Functional Status in Dysferlinopathy: A Rasch Analysis Approach” (2022) Frontiers in Neurology
Assessing the Relationship of Patient Reported Outcome Measures With Functional Status in Dysferlinopathy: A Rasch Analysis Approach(2022) Frontiers in Neurology, 13, art. no. 828525, .
Mayhew, A.G.a , James, M.K.a , Moore, U.a , Sutherland, H.a , Jacobs, M.b c , Feng, J.b , Lowes, L.P.d , Alfano, L.N.d , Muni Lofra, R.a , Rufibach, L.E.e , Rose, K.f , Duong, T.g h , Bello, L.i , Pedrosa-Hernández, I.j , Holsten, S.k , Sakamoto, C.l , Canal, A.m , Sánchez-Aguilera Práxedes, N.n , Thiele, S.o , Siener, C.p , Vandevelde, B.q , DeWolf, B.g , Maron, E.r , Gordish-Dressman, H.b c , Hilsden, H.a , Guglieri, M.a , Hogrel, J.-Y.m , Blamire, A.M.s , Carlier, P.G.t , Spuler, S.u , Day, J.W.v , Jones, K.J.f , Bharucha-Goebel, D.X.w x , Salort-Campana, E.q , Pestronk, A.p , Walter, M.C.o , Paradas, C.y , Stojkovic, T.m , Mori-Yoshimura, M.z , Bravver, E.k , Díaz-Manera, J.aa ab , Pegoraro, E.i , Mendell, J.R.d , Jain COS Consortiumd , Straub, V.a
a The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdomb Center for Translational Science, Division of Biostatistics and Study Methodology, Children’s National Health System, Washington, DC, United Statesc Pediatrics, Epidemiology and Biostatistics, George Washington University, Washington, DC, United Statesd The Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH, United Statese The Jain Foundation, Seattle, WA, United Statesf The Children’s Hospital at Westmead, The University of Sydney, Sydney, NSW, Australiag Cooperative International Neuromuscular Research Group, Children’s National Health System, Washington, DC, United Statesh Lucile Salter Packard Children’s Hospital at Stanford, Neurology, Palo Alto, CA, United Statesi Department of Neuroscience, University of Padova, Padua, Italyj Physical Medicine and Rehabilitation, Hospital de la Santa Creu i Sant Pau, Barcelona, Spaink Neuroscience Institute, Carolinas Neuromuscular/ALS-MDA Center, Carolinas HealthCare System, Charlotte, NC, United Statesl Department of Physical Rehabilitation, National Center Hospital, National Center of Neurology and Psychiatry Tokyo, Tokyo, Japanm Institut de Myologie, AP-HP, GH Pitié-Salpêtrière, Paris, Francen Rehabilitation Hospital Universitario Virgen del Rocío Sevilla, Seville, Spaino Department of Neurology, Friedrich-Baur-Institute, Ludwig-Maximilians-University of Munich, Munich, Germanyp Department of Neurology, Washington University School of Medicine, St. Louis, MO, United Statesq Service des Maladies Neuromusculaire et de la SLA, Hôpital de La Timone, Marseille, Francer ELAN-PHYSIO, Praxis für Physiotherapie Maron, Berlin, Germanys Magnetic Resonance Centre, Institute for Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdomt AIM CEA NMR Laboratory, Institute of Myology, Pitié-Salpêtrière University Hospital, Paris, Franceu Charite Muscle Research Unit, Experimental and Clinical Research Center, A Joint Cooperation of the Charité Medical Faculty and the Max Delbrück Center for Molecular Medicine, Berlin, Germanyv Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United Statesw Department of Neurology Children’s National Health System, Washington, DC, United Statesx National Institutes of Health, Bethesda, MD, United Statesy Neuromuscular Unit, Department of Neurology, Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Sevilla, Spainz Department of Neurology, National Center Hospital, National Center of Neurology and Psychiatry Tokyo, Tokyo, Japanaa Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER, Barcelona, Spainab Neuromuscular Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
AbstractDysferlinopathy is a muscular dystrophy with a highly variable functional disease progression in which the relationship of function to some patient reported outcome measures (PROMs) has not been previously reported. This analysis aims to identify the suitability of PROMs and their association with motor performance.Two-hundred and four patients with dysferlinopathy were identified in the Jain Foundation’s Clinical Outcome Study in Dysferlinopathy from 14 sites in 8 countries. All patients completed the following PROMs: Individualized Neuromuscular Quality of Life Questionnaire (INQoL), International Physical Activity Questionnaire (IPAQ), and activity limitations for patients with upper and/or lower limb impairments (ACTIVLIMs). In addition, nonambulant patients completed the Egen Klassifikation Scale (EK). Assessments were conducted annually at baseline, years 1, 2, 3, and 4. Data were also collected on the North Star Assessment for Limb Girdle Type Muscular Dystrophies (NSAD) and Performance of Upper Limb (PUL) at these time points from year 2. Data were analyzed using descriptive statistics and Rasch analysis was conducted on ACTIVLIM, EK, INQoL. For associations, graphs (NSAD with ACTIVLIM, IPAQ and INQoL and EK with PUL) were generated from generalized estimating equations (GEE). The ACTIVLIM appeared robust psychometrically and was strongly associated with the NSAD total score (Pseudo R2 0.68). The INQoL performed less well and was poorly associated with the NSAD total score (Pseudo R2 0.18). EK scores were strongly associated with PUL (Pseudo R2 0.69). IPAQ was poorly associated with NSAD scores (Pseudo R2 0.09). This study showed that several of the chosen PROMs demonstrated change over time and a good association with functional outcomes. An alternative quality of life measure and method of collecting data on physical activity may need to be selected for assessing dysferlinopathy. Copyright © 2022 Mayhew, James, Moore, Sutherland, Jacobs, Feng, Lowes, Alfano, Muni Lofra, Rufibach, Rose, Duong, Bello, Pedrosa-Hernández, Holsten, Sakamoto, Canal, Sánchez-Aguilera Práxedes, Thiele, Siener, Vandevelde, DeWolf, Maron, Gordish-Dressman, Hilsden, Guglieri, Hogrel, Blamire, Carlier, Spuler, Day, Jones, Bharucha-Goebel, Salort-Campana, Pestronk, Walter, Paradas, Stojkovic, Mori-Yoshimura, Bravver, Díaz-Manera, Pegoraro, Mendell and Straub.
Author Keywordsclinical outcome assessments; dysferlinopathy; limb girdle muscular dystrophy; PROMs; quality of life
Funding detailsMR/K000608/1Jain Foundation
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Hand Transplants, Daily Functioning, and the Human Capacity for Limb Regeneration” (2022) Frontiers in Cell and Developmental Biology
Hand Transplants, Daily Functioning, and the Human Capacity for Limb Regeneration(2022) Frontiers in Cell and Developmental Biology, 10, art. no. 812124, .
Fitzpatrick, S.M.a , Brogan, D.b , Grover, P.c d
a James S. McDonnell Foundation, St. Louis, MO, United Statesb Department of Orthopaedic Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, United Statesc Division of Neurorehabilitation, Orthopaedic Surgery and Neurology, Washington University in St. Louis School of Medicine, St. Louis, MO, United Statesd The Rehabilitation Institute of St Louis, St. Louis, MO, United States
AbstractUnlike some of our invertebrate and vertebrate cousins with the capacity to regenerate limbs after traumatic loss, humans do not have the ability to regrow arms or legs lost to injury or disease. For the millions of people worldwide who have lost a limb after birth, the primary route to regaining function and minimizing future complications is via rehabilitation, prosthetic devices, assistive aids, health system robustness, and social safety net structures. The majority of limbs lost are lower limbs (legs), with diabetes and vascular disorders being significant causal contributors. Upper limbs (arms) are lost primarily because of trauma; digits and hands are the most common levels of loss. Even if much of the arm remains intact, upper limb amputation significantly impacts function, largely due to the loss of the hand. Human hands are marvels of evolution and permit a dexterity that enables a wide variety of function not readily replaced by devices. It is not surprising, therefore, for some individuals, dissatisfaction with available prosthetic options coupled with remarkable advances in hand surgery techniques is resulting in patients undertaking the rigors of a hand transplantation. While not “regeneration” in the sense of the enviable ability with which Axolotls can replace a lost limb, hand transplants do require significant regeneration of tissues and nerves. Regaining sophisticated hand functions also depends on “reconnecting” the donated hand with the areas of the human brain responsible for the sensory and motor processing required for complex actions. Human hand transplants are not without controversy and raise interesting challenges regarding the human regenerative capacity and the status of transplants for enabling function. More investigation is needed to address medical and ethical questions prior to expansion of hand transplants to a wider patient population. Copyright © 2022 Fitzpatrick, Brogan and Grover.
Author Keywordsdelivery of care; functional; hand; microsurgery; prosthesis and implants; regeneration; rehabilitation; transplantation
Document Type: ArticlePublication Stage: FinalSource: Scopus
“Wolframin is a novel regulator of tau pathology and neurodegeneration” (2022) Acta Neuropathologica
Wolframin is a novel regulator of tau pathology and neurodegeneration(2022) Acta Neuropathologica, .
Chen, S.a b , Acosta, D.a , Li, L.a , Liang, J.a , Chang, Y.b c , Wang, C.c , Fitzgerald, J.a , Morrison, C.a , Goulbourne, C.N.d , Nakano, Y.e , Villegas, N.C.H.e f , Venkataraman, L.a g , Brown, C.h , Serrano, G.E.i , Bell, E.j , Wemlinger, T.k , Wu, M.a , Kokiko-Cochran, O.N.a , Popovich, P.a , Flowers, X.E.l , Honig, L.S.l , Vonsattel, J.P.l , Scharre, D.W.j , Beach, T.G.i , Ma, Q.c , Kuret, J.m , Kõks, S.n o , Urano, F.h , Duff, K.E.e p , Fu, H.a q
a Department of Neuroscience, The Ohio State University, Columbus, OH, United Statesb Biomedical Sciences Graduate Program, The Ohio State University, Columbus, OH, United Statesc Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United Statesd Center for Dementia Research, The Nathan S. Kline Institute for Psychiatric Research, New York, NY, United Statese Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, United Statesf Current address: Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United Statesg Center for Gene Therapy, Nationwide Children’s Hospital, Columbus, OH, United Statesh Department of Medicine, Washington University School of Medicine, St. Louis, MO, United Statesi Banner Sun Health Research Institute, Sun City, AZ, United Statesj Department of Neurology, Center for Cognitive and Memory Disorders, Center for Neuromodulation, The Ohio State University, Columbus, OH, United Statesk Clinical Research Center, Clinical Trials Management Organization, The Ohio State University, Columbus, OH, United Statesl Department of Neurology, Columbia University Irving Medical Center, New York, NY, United Statesm Department of Biological Chemistry & Pharmacology, The Ohio State University, Columbus, OH, United Statesn Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, Perth, WA, Australiao Perron Institute for Neurological and Translational Science, Perth, WA, Australiap UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdomq Discovery Theme on Chronic Brain Injury, The Ohio State University, Columbus, OH, United States
AbstractSelective neuronal vulnerability to protein aggregation is found in many neurodegenerative diseases including Alzheimer’s disease (AD). Understanding the molecular origins of this selective vulnerability is, therefore, of fundamental importance. Tau protein aggregates have been found in Wolframin (WFS1)-expressing excitatory neurons in the entorhinal cortex, one of the earliest affected regions in AD. The role of WFS1 in Tauopathies and its levels in tau pathology-associated neurodegeneration, however, is largely unknown. Here we report that WFS1 deficiency is associated with increased tau pathology and neurodegeneration, whereas overexpression of WFS1 reduces those changes. We also find that WFS1 interacts with tau protein and controls the susceptibility to tau pathology. Furthermore, chronic ER stress and autophagy-lysosome pathway (ALP)-associated genes are enriched in WFS1-high excitatory neurons in human AD at early Braak stages. The protein levels of ER stress and autophagy-lysosome pathway (ALP)-associated proteins are changed in tau transgenic mice with WFS1 deficiency, while overexpression of WFS1 reverses those changes. This work demonstrates a possible role for WFS1 in the regulation of tau pathology and neurodegeneration via chronic ER stress and the downstream ALP. Our findings provide insights into mechanisms that underpin selective neuronal vulnerability, and for developing new therapeutics to protect vulnerable neurons in AD. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Author KeywordsAlzheimer’s disease; Autophagy-lysosome pathway; Entorhinal cortex; ER stress; Neurodegeneration; Neuronal vulnerability; Tau pathology; WFS1; Wolframin
Funding detailsP30 CA016058P30AG066462, P50AG008702National Institutes of HealthNIHP30-AG19610, R01-GM131399, U24-NS072026U.S. Department of DefenseDODNational Institute on AgingNIANational Cancer InstituteNCINational Institute of General Medical SciencesNIGMSAARF-17-505009National Institute of Neurological Disorders and StrokeNINDSP30 NS104177, P30NS04578, UL1TR002733Michael J. Fox Foundation for Parkinson’s ResearchMJFFAlzheimer’s AssociationAAW81XWH1910309National Center for Advancing Translational SciencesNCATSOhio State UniversityOSUArizona Department of Health ServicesADHS211002Arizona Biomedical Research CommissionABRC0011, 05-901, 1001, 4001
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Impaired neurogenesis alters brain biomechanics in a neuroprogenitor-based genetic subtype of congenital hydrocephalus” (2022) Nature Neuroscience
Impaired neurogenesis alters brain biomechanics in a neuroprogenitor-based genetic subtype of congenital hydrocephalus(2022) Nature Neuroscience, .
Duy, P.Q.a b c , Weise, S.C.d , Marini, C.e , Li, X.-J.f g , Liang, D.a , Dahl, P.J.h i , Ma, S.a , Spajic, A.a , Dong, W.j , Juusola, J.k , Kiziltug, E.b , Kundishora, A.J.b , Koundal, S.l , Pedram, M.Z.l , Torres-Fernández, L.A.d , Händler, K.m n o , De Domenico, E.m n o , Becker, M.m n o , Ulas, T.m n o , Juranek, S.A.p , Cuevas, E.q , Hao, L.T.b , Jux, B.d , Sousa, A.M.M.a , Liu, F.a , Kim, S.-K.a , Li, M.a , Yang, Y.r , Takeo, Y.b , Duque, A.a , Nelson-Williams, C.s , Ha, Y.t , Selvaganesan, K.t , Robert, S.M.b , Singh, A.K.b , Allington, G.b , Furey, C.G.b , Timberlake, A.T.s , Reeves, B.C.b , Smith, H.b , Dunbar, A.b , DeSpenza, T., Jr.b , Goto, J.u , Marlier, A.b , Moreno-De-Luca, A.v , Yu, X.w , Butler, W.E.w , Carter, B.S.w , Lake, E.M.R.t , Constable, R.T.t , Rakic, P.a , Lin, H.r , Deniz, E.x , Benveniste, H.l , Malvankar, N.S.h i , Estrada-Veras, J.I.y z aa , Walsh, C.A.ab ac ad , Alper, S.L.ad ae , Schultze, J.L.m n o , Paeschke, K.p , Doetzlhofer, A.f g , Wulczyn, F.G.e , Jin, S.C.af , Lifton, R.P.j , Sestan, N.a , Kolanus, W.d , Kahle, K.T.w ab ad ag
a Department of Neuroscience and Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, CT, United Statesb Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, United Statesc Medical Scientist Training Program, Yale University School of Medicine, New Haven, CT, United Statesd Molecular Immunology and Cell Biology, Life & Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germanye Institute for Cell Biology and Neurobiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germanyf Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United Statesg Center for Hearing and Balance, Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, United Statesh Microbial Sciences Institute, Yale University, West Haven, CT, United Statesi Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, United Statesj Laboratory of Human Genetics and Genomics, The Rockefeller University, New York, NY, United Statesk GeneDx, Gaithersburg, MD, United Statesl Department of Anesthesiology, Yale University School of Medicine, New Haven, CT, United Statesm Systems Medicine, Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Bonn, Germanyn Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germanyo Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE). PRECISE Platform for Genomics and Epigenomics at DZNE and University of Bonn, Bonn, Germanyp Department of Oncology, Hematology and Rheumatology, University Hospital Bonn, Bonn, Germanyq Stem Cells and Regenerative Medicine Section, University College London Great Ormond Street Institute of Child Health, London, United Kingdomr Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT, United Statess Department of Genetics, Yale University School of Medicine, New Haven, CT, United Statest Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, United Statesu Division of Pediatric Neurosurgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United Statesv Department of Radiology, Autism & Developmental Medicine Institute, Genomic Medicine Institute, Geisinger, Danville, PA, United Statesw Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United Statesx Department of Pediatrics, Yale University School of Medicine, New Haven, CT, United Statesy Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United Statesz Pediatric Subspecialty Genetics Walter Reed National Military Medical Center, Bethesda, MD, United Statesaa Murtha Cancer Center/Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, United Statesab Division of Genetics and Genomics, Manton Center for Orphan Disease Research, Department of Pediatrics, and Howard Hughes Medical Institute, Boston Children’s Hospital, Boston, MA, United Statesac Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA, United Statesad Broad Institute of MIT and Harvard, Cambridge, MA, United Statesae Division of Nephrology and Vascular Biology Research Center, Beth Israel Deaconess Medical Center and Department of Medicine, Harvard Medical School, Boston, MA, United Statesaf Department of Genetics, Washington University School of Medicine, St. Louis, MO, United Statesag Harvard Center for Hydrocephalus and Neurodevelopmental Disorders, Massachusetts General Hospital, Boston, MA, United States
AbstractHydrocephalus, characterized by cerebral ventricular dilatation, is routinely attributed to primary defects in cerebrospinal fluid (CSF) homeostasis. This fosters CSF shunting as the leading reason for brain surgery in children despite considerable disease heterogeneity. In this study, by integrating human brain transcriptomics with whole-exome sequencing of 483 patients with congenital hydrocephalus (CH), we found convergence of CH risk genes in embryonic neuroepithelial stem cells. Of all CH risk genes, TRIM71/lin-41 harbors the most de novo mutations and is most specifically expressed in neuroepithelial cells. Mice harboring neuroepithelial cell-specific Trim71 deletion or CH-specific Trim71 mutation exhibit prenatal hydrocephalus. CH mutations disrupt TRIM71 binding to its RNA targets, causing premature neuroepithelial cell differentiation and reduced neurogenesis. Cortical hypoplasia leads to a hypercompliant cortex and secondary ventricular enlargement without primary defects in CSF circulation. These data highlight the importance of precisely regulated neuroepithelial cell fate for normal brain–CSF biomechanics and support a clinically relevant neuroprogenitor-based paradigm of CH. © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.
Funding detailsNational Institutes of HealthNIHNational Heart, Lung, and Blood InstituteNHLBICTSA1405, R00HL143036-02Burroughs Wellcome FundBWFHartwell FoundationDA023999, MH113257Children’s Discovery InstituteCDI1DP2AI138259-01, CDI-FR-2021-926Yale Cancer CenterHydrocephalus AssociationHA5R21NS116484-02Deutsche ForschungsgemeinschaftDFGEXC2151–390873048, WU 563/3-1
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Biomarker clustering in autosomal dominant Alzheimer’s disease” (2022) Alzheimer’s and Dementia
Biomarker clustering in autosomal dominant Alzheimer’s disease(2022) Alzheimer’s and Dementia, .
Luckett, P.H.w , Chen, C.w , Gordon, B.A.w , Wisch, J.w , Berman, S.B.a , Chhatwal, J.P.b , Cruchaga, C.w , Fagan, A.M.w , Farlow, M.R.c , Fox, N.C.d , Jucker, M.e f , Levin, J.g h i , Masters, C.L.j , Mori, H.k , Noble, J.M.l , Salloway, S.m , Schofield, P.R.n o , Brickman, A.M.p q , Brooks, W.S.n o , Cash, D.M.d , Fulham, M.J.p q , Ghetti, B.c , Jack, C.R., Jr.r , Vöglein, J.g , Klunk, W.E.a , Koeppe, R.s , Su, Y.t , Weiner, M.u v , Wang, Q.w , Marcus, D.w , Koudelis, D.w , Joseph-Mathurin, N.w , Cash, L.w , Hornbeck, R.w , Xiong, C.w , Perrin, R.J.w , Karch, C.M.w , Hassenstab, J.w , McDade, E.w , Morris, J.C.w , Benzinger, T.L.S.w , Bateman, R.J.w , Ances, B.M.w , for the Dominantly Inherited Alzheimer Network (DIAN)w
a University of Pittsburgh, Pittsburgh, PA, United Statesb Brigham and Women’s Hospital, Massachusetts General Hospital, Boston, MA, United Statesc Indiana University, Bloomington, IN, United Statesd Dementia Research Centre, UCL Queen Square Institute of Neurology, London, United Kingdome German Center for Neurodegenerative Disease, Tübingen, Germanyf Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germanyg Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germanyh German Center for Neurodegenerative Diseases, Munich, Germanyi Munich Cluster for Systems Neurology (SyNergy), Munich, Germanyj Florey Institute, The University of Melbourne, Parkville, VIC, Australiak Osaka City University Medical School, Nagaoka Sutoku University, Osaka, Abenoku, Japanl Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, G.H. Sergievsky Center, and Department of Neurology, Columbia University Irving Medical Center, New York, NY, United Statesm Butler Hospital and Warren Alpert Medical School of Brown University, Providence, RI, United Statesn Neuroscience Research Australia, Randwick, NSW, Australiao School of Medical Sciences, University of New South Wales, Sydney, NSW, Australiap Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, NSW, Australiaq The University of Sydney, SydneyNSW, Australiar Mayo Clinic, Rochester, MN, United Statess University of Michigan, Michigan, Ann Arbor, United Statest Banner Alzheimer Institute, Phoenix, AZ, United Statesu University of California San Francisco, San Francisco, CA, United Statesv San Francisco Veterans Affairs Medical Center, San Francisco, CA, United Statesw Washington University in St. Louis, St. Louis, MO, United States
AbstractINTRODUCTION: As the number of biomarkers used to study Alzheimer’s disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS: We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS: Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION: These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression. © 2022 the Alzheimer’s Association.
Author KeywordsAutosomal dominant Alzheimer’s disease; biomarkers; machine learning
Funding details156243National Institutes of HealthNIHK01AG053474, K23AG046363, P01AG003991, P01AG026276, P30NS098577, P50AG005681, P50AG05131, R01AG052550, R01EB009352, U01AG042791‐S1, UFAG 032438, UL1TR000448U.S. Department of DefenseDODPPRN‐1501‐26817, W81XWH‐13‐1‐0259, W81XWH‐15‐2‐0070Foundation for the National Institutes of HealthFNIHR1AG046179National Institute on AgingNIAMayo Clinic1R01AG053798‐01A1, 1R01AG058676‐01A1, 1RF1AG059009‐01, 1U2CA060426‐01, 5U19AG024904‐14, R01 MH098062Alzheimer’s AssociationAA18–109929, BHR‐16‐459161California Department of Public HealthCDPH16–10054, 174552, 18‐PAF01312, 2015‐A‐011‐NET, 444951–54249BiogenFoundation for Barnes-Jewish HospitalFBJHJapan Agency for Medical Research and DevelopmentAMEDHope Center for Neurological DisordersMedical Research CouncilMRC20‐681815, MR/009076/1, MR/L023784/1National Institute for Health ResearchNIHRDeutsches Zentrum für Neurodegenerative ErkrankungenDZNE
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Germline mosaicism of a missense variant in KCNC2 in a multiplex family with autism and epilepsy characterized by long-read sequencing” (2022) American Journal of Medical Genetics, Part A
Germline mosaicism of a missense variant in KCNC2 in a multiplex family with autism and epilepsy characterized by long-read sequencing(2022) American Journal of Medical Genetics, Part A, .
Mehinovic, E.a , Gray, T.b , Campbell, M.b , Ekholm, J.c , Wenger, A.c , Rowell, W.c , Grudo, A.c , Grimwood, J.d , Korlach, J.c , Gurnett, C.e , Constantino, J.N.b , Turner, T.N.a
a Department of Genetics, Washington University School of Medicine, St. Louis, MO, United Statesb Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United Statesc Pacific Biosciences, Menlo Park, CA, United Statesd HudsonAlpha Institute for Biotechnology, Huntsville, AL, United Statese Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
AbstractCurrently, protein-coding de novo variants and large copy number variants have been identified as important for ~30% of individuals with autism. One approach to identify relevant variation in individuals who lack these types of events is by utilizing newer genomic technologies. In this study, highly accurate PacBio HiFi long-read sequencing was applied to a family with autism, epileptic encephalopathy, cognitive impairment, and mild dysmorphic features (two affected female siblings, unaffected parents, and one unaffected male sibling) with no known clinical variant. From our long-read sequencing data, a de novo missense variant in the KCNC2 gene (encodes Kv3.2) was identified in both affected children. This variant was phased to the paternal chromosome of origin and is likely a germline mosaic. In silico assessment revealed the variant was not in controls, highly conserved, and predicted damaging. This specific missense variant (Val473Ala) has been shown in both an ortholog and paralog of Kv3.2 to accelerate current decay, shift the voltage dependence of activation, and prevent the channel from entering a long-lasting open state. Seven additional missense variants have been identified in other individuals with neurodevelopmental disorders (p = 1.03 × 10−5). KCNC2 is most highly expressed in the brain; in particular, in the thalamus and is enriched in GABAergic neurons. Long-read sequencing was useful in discovering the relevant variant in this family with autism that had remained a mystery for several years and will potentially have great benefits in the clinic once it is widely available. © 2022 The Authors. American Journal of Medical Genetics Part A published by Wiley Periodicals LLC.
Author Keywordsautism; channel; epilepsy; genetics; genomics; long-read sequencing
Funding detailsNational Institutes of HealthNIHP50HD103525, R00MH117165National Institute of Mental HealthNIMHNational Institute on Drug AbuseNIDANational Heart, Lung, and Blood InstituteNHLBINational Human Genome Research InstituteNHGRINational Cancer InstituteNCINational Institute of Neurological Disorders and StrokeNINDS
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy” (2022) Epilepsia
Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy(2022) Epilepsia, .
Luckett, P.H.a , Maccotta, L.b , Lee, J.J.c , Park, K.Y.a , U. F. Dosenbach, N.b , Ances, B.M.b , Hogan, R.E.b , Shimony, J.S.c , Leuthardt, E.C.a
a Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, United Statesb Department of Neurology, Washington University School of Medicine, St Louis, MO, United Statesc Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States
AbstractObjective: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients. Methods: A total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions. Results: The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, and the resting state networks that colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with postsurgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel Class >I compared to Engel Class I. Significance: Noninvasive techniques capable of localizing the seizure onset zone could improve presurgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning. © 2022 International League Against Epilepsy.
Author Keywordsepilepsy; machine learning; resting state functional connectivity
Funding detailsNational Institutes of HealthNIHP01 AG003991, P01 AG026276, P50 HD103525, R01 AG057680, R01 CA203861, R01 DA054009, R01 MH118031, R01 NR014449, R01 NR015738
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Mild hypoxic-ischemic encephalopathy (HIE): timing and pattern of MRI brain injury (2022) Pediatric Research
Mild hypoxic-ischemic encephalopathy (HIE): timing and pattern of MRI brain injury(2022) Pediatric Research, .
Li, Y.a , Wisnowski, J.L.b , Chalak, L.c , Mathur, A.M.d , McKinstry, R.C.e , Licona, G.f , Mayock, D.E.g , Chang, T.h , Van Meurs, K.P.i , Wu, T.-W.j , Ahmad, K.A.k , Cornet, M.-C.l , Rao, R.m , Scheffler, A.n , Wu, Y.W.l o
a Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United Statesb Department of Radiology and Pediatrics, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United Statesc Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, United Statesd Division of Neonatal Perinatal Medicine, Department of Pediatrics, Saint Louis University School of Medicine, St. Louis, MO, United Statese Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United Statesf Division of Neonatology, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, TN, United Statesg Division of Neonatology, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, United Statesh Department of Neurology, Children’s National Hospital, George Washington School of Medicine & Health Sciences, Washington, DC, United Statesi Division of Neonatal and Developmental Medicine, Stanford University School of Medicine, Palo Alto, CA, United Statesj Division of Neonatology, Department of Pediatrics, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern California, Los Angeles, CA, United Statesk Pediatrix Medical Group of San Antonio, San Antonio, TX, United Statesl Department of Pediatrics, University of California San Francisco, San Francisco, CA, United Statesm Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United Statesn Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, United Stateso Department of Neurology, University of California San Francisco, San Francisco, CA, United States
AbstractBackground: Mild hypoxic-ischemic encephalopathy (HIE) is increasingly recognized as a risk factor for neonatal brain injury. We examined the timing and pattern of brain injury in mild HIE. Methods: This retrospective cohort study includes infants with mild HIE treated at 9 hospitals. Neonatal brain MRIs were scored by 2 reviewers using a validated classification system, with discrepancies resolved by consensus. Severity and timing of MRI brain injury (i.e., acute, subacute, chronic) was scored on the subset of MRIs that were performed at or before 8 days of age. Results: Of 142 infants with mild HIE, 87 (61%) had injury on MRI at median age 5 (IQR 4–6) days. Watershed (23%), deep gray (20%) and punctate white matter (18%) injury were most common. Among the 125 (88%) infants who received a brain MRI at ≤8 days, mild (44%) injury was more common than moderate (11%) or severe (4%) injury. Subacute (37%) lesions were more commonly observed than acute (32%) or chronic lesions (1%). Conclusion: Subacute brain injury is common in newborn infants with mild HIE. Novel neuroprotective treatments for mild HIE will ideally target both subacute and acute injury mechanisms. Impact: Almost two-thirds of infants with mild HIE have evidence of brain injury on MRI obtained in the early neonatal period.Subacute brain injury was seen in 37% of infants with mild HIE.Neuroprotective treatments for mild HIE will ideally target both acute and subacute injury mechanisms. © 2022, The Author(s).
Funding detailsRadiological Society of North AmericaRSNA
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Predictors of severe outcome following opioid intoxication in children” (2022) Clinical Toxicology
Predictors of severe outcome following opioid intoxication in children(2022) Clinical Toxicology, .
Cohen, N.a b , Mathew, M.a b , Davis, A.a b , Brent, J.c , Wax, P.d , Schuh, S.a b , Freedman, S.B.e , Froberg, B.f , Schwarz, E.g , Canning, J.h , Tortora, L.h , Hoyte, C.i , Koons, A.L.j , Burns, M.M.k , McFalls, J.l , Wiegand, T.J.m , Hendrickson, R.G.n , Judge, B.o , Quang, L.S.p , Hodgman, M.q , Chenoweth, J.A.r , Algren, D.A.s , Carey, J.t , Caravati, E.M.u , Akpunonu, P.v , Geib, A.-J.w , Seifert, S.A.x , Kazzi, Z.y , Othong, R.z , Greene, S.C.aa , Holstege, C.ab , Tweet, M.S.ac , Vearrier, D.ad , Pizon, A.F.ae , Campleman, S.L.af , Li, S.af , Aldy, K.l , Finkelstein, Y.a b ag , On behalf of ToxIC Pediatric Opioid Exposure Study Groupah
a Division of Paediatric Emergency Medicine, Department of Paediatrics, The Hospital for Sick Children, Toronto, Canadab University of Toronto, Toronto, Canadac Department of Internal Medicine, School of Medicine, University of Colorado, Aurora, CO, United Statesd Southwestern School of Medicine, University of Texas, Dallas, TX, United Statese Department of Paediatrics and Emergency Medicine, Cumming School of Medicine, University of Calgary, Calgary, Canadaf Indiana University School of Medicine, Indianapolis, IN, United Statesg Washington University, St. Louis, MO, United Statesh Banner–University Medical Centre, Phoenix, AZ, United Statesi Rocky Mountain Poison and Drug Center, Denver Health, Denver, CO, United Statesj Lehigh Valley Health Network, USF Morsani College of Medicine, Allentown, PA, United Statesk Boston Children’s Hospital, Boston, MA, United Statesl University of Texas Southwestern Medical Center, Dallas, TX, United Statesm University of Rochester Medical Center, Rochester, NY, United Statesn Oregon Health & Science University, Portland, OR, United Stateso Spectrum Health–Michigan State University, Grand Rapids, MI, United Statesp Arkansas Children’s Hospital/University of Arkansas for Medical Sciences, Little Rock, AR, United Statesq Upstate Medical University, Syracuse, NY, United Statesr University of California at Davis, Sacramento, CA, United Statess University of Missouri-Kansas City School of Medicine, Kansas City, MO, United Statest University of Massachusetts Medical School, Worcester, MA, United Statesu University of Utah School of Medicine, Salt Lake City, UT, United Statesv University of Kentucky, Lexington, KY, United Statesw Atrium Health’s Carolinas Medical Center, Charlotte, NC, United Statesx University of New Mexico, Albuquerque, NM, United Statesy Emory University School of Medicine, Atlanta, GA, United Statesz Vajira Hospital, Navamindradhiraj University, Bangkok, Thailandaa University of Houston College of Medicine, Houston, TX, United Statesab University of Virginia, Charlottesville, VA, United Statesac Toxicon Consortium, Chicago, IL, United Statesad Department of Emergency Medicine, University of Mississippi Medical Center, Jackson, MS, United Statesae University of Pittsburgh School of Medicine, Pittsburgh, PA, United Statesaf American College of Medical Toxicology, Phoenix, AZ, United Statesag Division of Clinical Pharmacology and Toxicology, Department of Paediatrics, The Hospital for Sick Children, Toronto, Canada
AbstractIntroduction: While the opioid crisis has claimed the lives of nearly 500,000 in the U.S. over the past two decades, and pediatric cases of opioid intoxications are increasing, only sparse data exist regarding risk factors for severe outcome in children following an opioid intoxication. We explore predictors of severe outcome (i.e., intensive care unit [ICU] admission or in-hospital death) in children who presented to the Emergency Department with an opioid intoxication. Methods: In this prospective cohort study we collected data on all children (0–18 years) who presented with an opioid intoxication to the 50 medical centers in the US and two international centers affiliated with the Toxicology Investigators Consortium (ToxIC) of the American College of Medical Toxicology, from August 2017 through June 2020, and who received a bedside consultation by a medical toxicologist. We collected relevant demographic, clinical, management, disposition, and outcome data, and we conducted a multivariable logistic regression analysis to explore predictors of severe outcome. The primary outcome was a composite severe outcome endpoint, defined as ICU admission or in-hospital death. Covariates included sociodemographic, exposure and clinical characteristics. Results: Of the 165 (87 females, 52.7%) children with an opioid intoxication, 89 (53.9%) were admitted to ICU or died during hospitalization, and 76 did not meet these criteria. Seventy-four (44.8%) children were exposed to opioids prescribed to family members. Fentanyl exposure (adjusted OR [aOR] = 3.6, 95% CI: 1.0–11.6; p = 0.03) and age ≥10 years (aOR = 2.5, 95% CI: 1.2–4.8; p = 0.01) were independent predictors of severe outcome. Conclusions: Children with an opioid toxicity that have been exposed to fentanyl and those aged ≥10 years had 3.6 and 2.5 higher odds of ICU admission or death, respectively, than those without these characteristics. Prevention efforts should target these risk factors to mitigate poor outcomes in children with an opioid intoxication. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywordschildren; intoxication; Opioids; poisoning
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Functional analysis of a novel de novo variant in PPP5C associated with microcephaly, seizures, and developmental delay” (2022) Molecular Genetics and Metabolism
Functional analysis of a novel de novo variant in PPP5C associated with microcephaly, seizures, and developmental delay(2022) Molecular Genetics and Metabolism, .
Fielder, S.M.a , Rosenfeld, J.A.b , Burrage, L.C.b c , Emrick, L.b c , Lalani, S.b c , Attali, R.d , Bembenek, J.N.e , Hoang, H.a , Baldridge, D.a , Silverman, G.A.a , Schedl, T.f , Pak, S.C.a , Undiagnosed Diseases Networkg
a Department of Pediatrics, Washington University in St Louis School of Medicine, St Louis, MO 63110, United Statesb Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, United Statesc Texas Children’s Hospital, Houston, TX 77030, United Statesd Genomic Research Department, Emedgene Technologies, Tel Aviv, 6744332, Israele Department of Obstetrics and Gynecology, C.S. Mott Center for Human Growth and Development, Wayne State University School of Medicine, Detroit, MI 48201, United Statesf Department of Genetics, Washington University in St Louis School of Medicine, St Louis, MO 63110, United States
AbstractWe describe a proband evaluated through the Undiagnosed Diseases Network (UDN) who presented with microcephaly, developmental delay, and refractory epilepsy with a de novo p.Ala47Thr missense variant in the protein phosphatase gene, PPP5C. This gene has not previously been associated with a Mendelian disease, and based on the population database, gnomAD, the gene has a low tolerance for loss-of-function variants (pLI = 1, o/e = 0.07). We functionally evaluated the PPP5C variant in C. elegans by knocking the variant into the orthologous gene, pph-5, at the corresponding residue, Ala48Thr. We employed assays in three different biological processes where pph-5 was known to function through opposing the activity of genes, mec-15 and sep-1. We demonstrated that, in contrast to control animals, the pph-5 Ala48Thr variant suppresses the neurite growth phenotype and the GABA signaling defects of mec-15 mutants, and the embryonic lethality of sep-1 mutants. The Ala48Thr variant did not display dominance and behaved similarly to the reference pph-5 null, indicating that the variant is likely a strong hypomorph or complete loss-of-function. We conclude that pph-5 Ala48Thr is damaging in C. elegans. By extension in the proband, PPP5C p.Ala47Thr is likely damaging, the de novo dominant presentation is consistent with haplo-insufficiency, and the PPP5C variant is likely responsible for one or more of the proband’s phenotypes. © 2022 The Authors
Author KeywordsC. elegans; Developmental delay; Microcephaly; PPH-5; PPP5C
Funding detailsU01HG007709U54 NS108251National Institutes of HealthNIHP40 OD010440, R01 GM11447Children’s Discovery InstituteCDI
Document Type: ArticlePublication Stage: Article in PressSource: Scopus
“Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder” (2022) Cognitive, Affective and Behavioral Neuroscience
Distinct Neural Profiles of Frontoparietal Networks in Boys with ADHD and Boys with Persistent Depressive Disorder(2022) Cognitive, Affective and Behavioral Neuroscience, .
Vilgis, V.a , Yee, D.b c , Silk, T.J.a d e , Vance, A.a e f
a Department of Paediatrics, University of Melbourne, Melbourne, Australiab Washington University in St. Louis, St. Louis, MO, United Statesc Cognitive, Linguistic & Psychological Sciences, Brown University, Box 182, Metcalf Research Building, 190 Thayer Street, Providence, RI 02912, United Statesd Murdoch Children’s Research Institute, Melbourne, Australiae School of Psychology, Deakin University, Providence, Australiaf Royal Children’s Hospital, Parkville, Australia
AbstractWorking memory deficits are common in attention-deficit/hyperactivity disorder (ADHD) and depression—two common neurodevelopmental disorders with overlapping cognitive profiles but distinct clinical presentation. Multivariate techniques have previously been utilized to understand working memory processes in functional brain networks in healthy adults but have not yet been applied to investigate how working memory processes within the same networks differ within typical and atypical developing populations. We used multivariate pattern analysis (MVPA) to identify whether brain networks discriminated between spatial versus verbal working memory processes in ADHD and Persistent Depressive Disorder (PDD). Thirty-six male clinical participants and 19 typically developing (TD) boys participated in a fMRI scan while completing a verbal and a spatial working memory task. Within a priori functional brain networks (frontoparietal, default mode, salience), the TD group demonstrated differential response patterns to verbal and spatial working memory. The PDD group showed weaker differentiation than TD, with lower classification accuracies observed in primarily the left frontoparietal network. The neural profiles of the ADHD and PDD differed specifically in the SN where the ADHD group’s neural profile suggests significantly less specificity in neural representations of spatial and verbal working memory. We highlight within-group classification as an innovative tool for understanding the neural mechanisms of how cognitive processes may deviate in clinical disorders, an important intermediary step towards improving translational psychiatry. © 2022, The Psychonomic Society, Inc.
Author KeywordsAttention-deficit/hyperactivity disorder; Children; Depression; fMRI; Multivariate pattern analysis; Working memory
Funding detailsNational Institutes of HealthNIHF31-DA042574Murdoch Children’s Research InstituteMCRIRoyal Children’s Hospital FoundationNational Health and Medical Research CouncilNHMRCUniversity of MelbourneUNIMELBState Government of Victoria
Document Type: ArticlePublication Stage: Article in PressSource: Scopus