Scopus list of publications for June 11, 2023
Challenges in studying the interplay of genes and environment. A study of childhood financial distress moderating genetic predisposition for peak smoking
(2023) Journal of Economic Psychology, 98, art. no. 102636, .
Bierut, L.a , Biroli, P.b , Galama, T.J.c d , Thom, K.e
a Washington University School of Medicine, St. Louis, MO, United States
b Department of Economics, University of Bologna, Italy
c University of Southern California, Center for Economic and Social Research (CESR), Los Angeles, United States
d Vrije Universiteit Amsterdam, Amsterdam, Netherlands
e University of Wisconsin, Milwaukee, United States
Abstract
Smoking is one of the leading causes of preventable disease and death in the U.S., and it is strongly influenced both by genetic predisposition and childhood adversity. Using polygenic indices (PGIs) of predisposition to smoking, we evaluate whether childhood financial distress (CFD; a composite measure of financial adversity) moderates genetic risk in explaining peak-cigarette consumption in adulthood. Using the Health and Retirement Study (HRS), we find a substantial reduction in the relationship between genetic risk and peak smoking for those who did not suffer financial adversity in childhood. Among adult smokers who grew up in high-CFD households, a one standard deviation higher PGI is associated with 2.9 more cigarettes smoked per day at peak. By contrast, among smokers who grew up in low-CFD households, this gradient is reduced by 37 percent (or 1.1 fewer). These results are robust to controlling for a host of prime confounders. By contrast, we find no evidence of interactions between the PGI and typical measures of childhood SES such as parental education – a null result that we replicate in the Wisconsin Longitudinal Study (WLS) and the English Longitudinal Study of Aging (ELSA). This suggests the role of childhood financial distress in the relationship with peak smoking is distinct from that of low childhood SES, with high CFD potentially reflecting more acute distress than do measures of low childhood SES. Our evidence also suggests low childhood SES is a weaker proxy for acute distress, providing an alternative explanation for the childhood SES null result. © 2023 Elsevier B.V.
Author Keywords
G×E; Health inequality; Polygenic index; Smoking
Funding details
National Institutes of HealthNIHR01AG078522, R56AG058726, RF1AG055654
National Institute on AgingNIA
Nederlandse Organisatie voor Wetenschappelijk OnderzoekNWO
Document Type: Article
Publication Stage: Final
Source: Scopus
Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness
(2023) NeuroImage, 275, art. no. 120162, .
Luppi, A.I.a b , Cabral, J.c , Cofre, R.d e , Mediano, P.A.M.f g , Rosas, F.E.h i j k , Qureshi, A.Y.l , Kuceyeski, A.m , Tagliazucchi, E.n o , Raimondo, F.p q , Deco, G.r s t u , Shine, J.M.v , Kringelbach, M.L.k w x , Orio, P.y , Ching, S.z , Sanz Perl, Y.r aa ab , Diringer, M.N.ac , Stevens, R.D.ad , Sitt, J.D.aa ae
a Division of Anaesthesia and Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
b Montreal Neurological Institute, McGill University, Montreal, QC, Canada
c Life and Health Sciences Research Institute, University of Minho, Portugal
d CIMFAV-Ingemat, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso, Chile
e Centre National de la Recherche Scientifique (CNRS), Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Gif-sur-Yvette, France
f Department of Computing, Imperial College London, London, United Kingdom
g Department of Psychology, University of Cambridge, Cambridge, United Kingdom
h Department of Informatics, University of Sussex, Brighton, United Kingdom
i Centre for Psychedelic Research, Department of Brain Sciences, Imperial College London, London, United Kingdom
j Centre for Complexity Science, Imperial College London, London, United Kingdom
k Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
l University of Kansas Medical Center, Kansas City, MO, United States
m Department of Radiology, Weill Cornell Medicine, New York, United States
n Departamento de Física (UBA) e Instituto de Fisica de Buenos Aires (CONICET), Buenos Aires, Argentina
o Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
p Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Germany
q Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
r Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
s Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
t Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
u Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
v Brain and Mind Center, The University of Sydney, Sydney, Australia
w Department of Psychiatry, University of Oxford, Oxford, United Kingdom
x Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
y Centro Interdisciplinario de Neurociencia de Valparaíso and Instituto de Neurociencia, Universidad de Valparaíso, Valparaíso, Chile
z Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States
aa Institut du Cerveau et de la Moelle épinière – Paris Brain Institute, ICM, Paris, France
ab National Scientific and Technical Research Council (CONICET), CABA, Godoy Cruz, 2290, Argentina
ac Department of Neurology and Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
ad Departments of Anesthesiology and Critical Care Medicine, Neurology, Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
ae Sorbonne Université, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
Abstract
Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges. © 2023 The Author(s)
Author Keywords
Biophysical models; Computational models; Disorders of consciousness; Generative models; Machine learning; Statistical models
Funding details
FB0008
A20M02
H2020–945539
National Institutes of HealthNIHR01NS102646, RF1MH123232
‘la Caixa’ FoundationLCF/BQ/PR22/11920014
H2020 Marie Skłodowska-Curie ActionsMSCA896354
National Health and Medical Research CouncilNHMRC1193857
Danmarks GrundforskningsfondDNRFDNRF117, R01NS130693
Fondo Nacional de Desarrollo Científico y TecnológicoFONDECYT1211750
Gates Cambridge TrustOPP 1144
Horizon 2020
Agencia Nacional de Investigación y DesarrolloANID
Document Type: Article
Publication Stage: Final
Source: Scopus
Cannabis use, cannabis use disorder and mental health disorders among pregnant and postpartum women in the US: A nationally representative study
(2023) Drug and Alcohol Dependence, 248, art. no. 109940, .
Brown, Q.L.a , Shmulewitz, D.b c , Sarvet, A.L.d , Young-Wolff, K.C.e , Howard, T.f , Hasin, D.S.b c
a School of Social Work, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States
b Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
c New York State Psychiatric Institute, New York, NY, United States
d Department of Mathematics, École polytechnique fédérale de Lausanne, Switzerland
e Kaiser Permanente Northern California, Division of Research, Oakland, CA, United States
f Brown School, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Background: Cannabis use and cannabis use disorder (CUD) are associated with mental health disorders, however the extent of this matter among pregnant and recently postpartum (e.g., new moms) women in the US is unknown. Associations between cannabis use, DSM-5 CUD and DSM-5 mental health disorders (mood, anxiety, personality and post-traumatic stress disorders) were examined among a nationally representative sample of pregnant and postpartum women. Methods: The 2012–2013 National Epidemiologic Survey on Alcohol and Related Conditions–III was used to examine associations between past-year cannabis use, CUD and mental health disorders. Weighted logistic regression models were used to estimate unadjusted and adjusted odds ratios (aORs). The sample (N=1316) included 414 pregnant and 902 postpartum women (pregnant in the past year), aged 18–44 years old. Results: The prevalence of past-year cannabis use and CUD was 9.8% and 3.2%, respectively. The odds of cannabis use (aORs range 2.10–3.87, p-values<0.01) and CUD (aORs range 2.55–10.44, p-values< 0.01) were higher among women with versus without any past-year mood, anxiety or posttraumatic stress disorders or any lifetime personality disorder. aORs for the association of cannabis use with specific mood, anxiety or personality disorders ranged from 1.95 to 6.00 (p-values<0.05). aORs for the association of CUD with specific mood, anxiety or personality disorders ranged from 2.36 to 11.60 (p-values<0.05). Conclusions: From pregnancy up to one year postpartum is a critical period where women may be particularly vulnerable to mental health disorders, cannabis use and CUD. Treatment and prevention are essential. © 2023 Elsevier B.V.
Author Keywords
Anxiety; Anxiety disorders; Cannabis use; Cannabis use disorder; Depression; DSM-5; Epidemiology; Mental health; Mood disorders; Nationally representative; NESARC-III; Personality disorders; Postpartum; Pregnancy; Pregnant; PTSD; US
Funding details
National Institute on Drug AbuseNIDAK01DA043604, R25DA035163
Document Type: Article
Publication Stage: Final
Source: Scopus
DNAJB6 isoform specific knockdown: Therapeutic potential for limb girdle muscular dystrophy D1
(2023) Molecular Therapy – Nucleic Acids, 32, pp. 937-948.
Findlay, A.R.a , Paing, M.M.a , Daw, J.A.a , Haller, M.a , Bengoechea, R.a , Pittman, S.K.a , Li, S.b , Wang, F.b , Miller, T.M.a , True, H.L.c , Chou, T.-F.b , Weihl, C.C.a
a Department of Neurology, Neuromuscular Division, Washington University School of Medicine, Saint Louis, MO 63110, United States
b Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, United States
c Department of Cell Biology and Physiology, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8228, St. Louis, MO 63110, United States
Abstract
Dominant missense mutations in DNAJB6, a co-chaperone of HSP70, cause limb girdle muscular dystrophy (LGMD) D1. No treatments are currently available. Two isoforms exist, DNAJB6a and DNAJB6b, each with distinct localizations in muscle. Mutations reside in both isoforms, yet evidence suggests that DNAJB6b is primarily responsible for disease pathogenesis. Knockdown treatment strategies involving both isoforms carry risk, as DNAJB6 knockout is embryonic lethal. We therefore developed an isoform-specific knockdown approach using morpholinos. Selective reduction of each isoform was achieved in vitro in primary mouse myotubes and human LGMDD1 myoblasts, as well as in vivo in mouse skeletal muscle. To assess isoform specific knockdown in LGMDD1, we created primary myotube cultures from a knockin LGMDD1 mouse model. Using mass spectrometry, we identified an LGMDD1 protein signature related to protein homeostasis and myofibril structure. Selective reduction of DNAJB6b levels in LGMDD1 myotubes corrected much of the proteomic disease signature toward wild type levels. Additional in vivo functional data is required to determine if selective reduction of DNAJB6b is a viable therapeutic target for LGMDD1. © 2023 The Author(s)
Author Keywords
DNAJB6; isoform specific knockdown; limb girdle muscular dystrophy D1 (LGMDD1); morpholino; MT: Oligonucleotides: Therapies and Applications; proteomics
Funding details
17/932,996
MIFR20221004
National Institute of Arthritis and Musculoskeletal and Skin DiseasesNIAMS
Agricultural Research FoundationARFK08AR075894, K24AR073317, R01AR068797, R03AR081395
Document Type: Article
Publication Stage: Final
Source: Scopus
Chromophore supply modulates cone function and survival in retinitis pigmentosa mouse models
(2023) Proceedings of the National Academy of Sciences of the United States of America, 120 (23), pp. e2217885120.
Xue, Y.a b c d , Sun, X.a , Wang, S.K.b c e , Collin, G.B.f , Kefalov, V.J.d , Cepko, C.L.b c e
a Lingang LaboratoryShanghai 200031, China
b Department of Genetics, Harvard Medical School, Boston, MA 02115, United States
c Department of Ophthalmology, Harvard Medical School, Boston, MA 02115, United States
d Department of Ophthalmology & Visual Sciences, Washington University School of Medicine, St. Louis, MO 63110, United States
e HHMI, Boston, MA 02115, United States
f Jackson Laboratory
Abstract
Retinitis pigmentosa (RP) is an ocular disease characterized by the loss of night vision, followed by the loss of daylight vision. Daylight vision is initiated in the retina by cone photoreceptors, which are gradually lost in RP, often as bystanders in a disease process that initiates in their neighboring rod photoreceptors. Using physiological assays, we investigated the timing of cone electroretinogram (ERG) decline in RP mouse models. A correlation between the time of loss of the cone ERG and the loss of rods was found. To investigate a potential role of the visual chromophore supply in this loss, mouse mutants with alterations in the regeneration of the retinal chromophore, 11-cis retinal, were examined. Reducing chromophore supply via mutations in Rlbp1 or Rpe65 resulted in greater cone function and survival in a RP mouse model. Conversely, overexpression of Rpe65 and Lrat, genes that can drive the regeneration of the chromophore, led to greater cone degeneration. These data suggest that abnormally high chromophore supply to cones upon the loss of rods is toxic to cones, and that a potential therapy in at least some forms of RP is to slow the turnover and/or reduce the level of visual chromophore in the retina.
Author Keywords
Alström syndrome; cone photoreceptors; retina; retinitis pigmentosa; visual cycle
Document Type: Article
Publication Stage: Final
Source: Scopus
Sex-dependent effects of acute stress on amyloid-β in male and female mice
(2023) Brain: A Journal of Neurology, 146 (6), pp. 2268-2274.
Edwards, H.M.a , Wallace, C.E.a , Gardiner, W.D.a , Doherty, B.M.a , Harrigan, R.T.a , Yuede, K.M.a , Yuede, C.M.b , Cirrito, J.R.a
a Department of Neurology, Knight Alzheimer’s Disease Research Center, Hope Center for Neurological Disorders, St. Louis, United States
b Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
Abstract
The risk of developing Alzheimer’s disease is mediated by a combination of genetics and environmental factors, such as stress, sleep abnormalities and traumatic brain injury. Women are at a higher risk of developing Alzheimer’s disease than men, even when controlling for differences in lifespan. Women are also more likely to report high levels of stress than men. Sex differences in response to stress may play a role in the increased risk of Alzheimer’s disease in women. In this study, we use in vivo microdialysis to measure levels of Aβ in response to acute stress in male and female mice. We show that Aβ levels are altered differently between female and male mice (APP/PS1 and wild-type) in response to stress, with females showing significantly increased levels of Aβ while most males do not show a significant change. This response is mediated through β-arrestin involvement in Corticotrophin Releasing Factor receptor signalling pathway differences in male and female mice as male mice lacking β-arrestin show increase in Aβ in response to stress similar to females. © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Author Keywords
Alzheimer’s disease; corticotropin releasing factor; sexual dimorphism; stress; β-arrestin
Document Type: Article
Publication Stage: Final
Source: Scopus
PSMC3 proteasome subunit variants are associated with neurodevelopmental delay and type I interferon production
(2023) Science Translational Medicine, 15 (698), p. eabo3189.
Ebstein, F.a , Küry, S.b c , Most, V.d , Rosenfelt, C.e , Scott-Boyer, M.-P.f , van Woerden, G.M.g h i , Besnard, T.b c , Papendorf, J.J.a , Studencka-Turski, M.a , Wang, T.j k l , Hsieh, T.-C.m , Golnik, R.n , Baldridge, D.o , Forster, C.p , de Konink, C.g h , Teurlings, S.M.W.g h , Vignard, V.b c , van Jaarsveld, R.H.q , Ades, L.r s , Cogné, B.b c , Mignot, C.t u , Deb, W.b c , Jongmans, M.C.J.q v , Cole, F.S.o , van den Boogaard, M.-J.H.q , Wambach, J.A.o , Wegner, D.J.o , Yang, S.p , Hannig, V.w , Brault, J.A.w , Zadeh, N.x , Bennetts, B.s y , Keren, B.z , Gélineau, A.-C.z , Powis, Z.aa , Towne, M.aa , Bachman, K.ab , Seeley, A.ab , Beck, A.E.ac , Morrison, J.ad , Westman, R.ae , Averill, K.af , Brunet, T.ag ah , Haasters, J.ai , Carter, M.T.aj ak , Osmond, M.aj , Wheeler, P.G.ad , Forzano, F.al am , Mohammed, S.al am , Trakadis, Y.an , Accogli, A.an , Harrison, R.al ao , Guo, Y.ap aq , Hakonarson, H.ap , Rondeau, S.ar , Baujat, G.ar , Barcia, G.ar , Feichtinger, R.G.as , Mayr, J.A.as , Preisel, M.as , Laumonnier, F.at au , Kallinich, T.av aw , Knaus, A.m , Isidor, B.b c , Krawitz, P.m , Völker, U.ax , Hammer, E.ax , Droit, A.f , Eichler, E.E.j ay , Elgersma, Y.h i , Hildebrand, P.W.d az ba , Bolduc, F.e bb bc , Krüger, E.a , Bézieau, S.b c
a Institut für Medizinische Biochemie und Molekularbiologie (IMBM), Universitätsmedizin Greifswald, Ferdinand-Sauerbruch-Straße, Germany
b CHU Nantes, Service de Génétique Médicale, Nantes, 44000, France
c CHU Nantes, CNRS, INSERM, l’institut du thorax, Nantes, 44000, France
d Institut für Medizinische Physik und Biophysik, Universität Leipzig, Medizinische Fakultät, Härtelstr. 16-18, Leipzig, 04107, Germany
e Department of Pediatrics, University of Alberta, AB CT6G 1C9, Edmonton, Canada
f Research Center of Quebec CHU-Université LavalQuébec, Canada
g Department of Neuroscience, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
h ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
i Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, 3015 CN, Netherlands
j Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA 98195, USA
k Department of Medical Genetics, Center for Medical Genetics, School of Basic Medical Sciences, Peking University Health Science CenterBeijing 100191, China
l Neuroscience Research Institute, Peking University; Key Laboratory for Neuroscience, Ministry of Education of China & National Health Commission of China, Beijing 100191, China
m Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53127, Germany
n Universitätsklinikum Halle (Saale), 06120 Halle (Saale), Germany
o Edward Mallinckrodt Department of Pediatrics, Washington University School of Medicine, United States
p GeneDx, 207 Perry Parkway, Gaithersburg, United States
q Department of Genetics, University Medical Center UtrechtUtrecht 3508 AB, Netherlands
r Department of Clinical Genetics, Children’s Hospital at Westmead, Locked Bag 4001 ,Westmead, Australia
s Disciplines of Genomic Medicine & Child and Adolescent Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
t APHP, Hôpital Pitié-Salpêtrière, Département de Génétique, Centre de Reference Déficience Intellectuelle de Causes Rares, GRC UPMC Déficience Intellectuelle et Autisme, Paris, 75013, France
u Institut du Cerveau et de la Moelle épinière, ICM, Inserm U1127, CNRS UMR 7225, Sorbonne Universités, Paris, 75013, France
v Princess Máxima Center for Pediatric OncologyCS Utrecht 3584, Netherlands
w Department of Medicine, Vanderbilt University Medical Center, Nashville, United States
x Genetics Center and Division of Medical Genetics, Children’s Hospital of Orange County, Orange, CA 92868, USA
y Sydney Genome Diagnostics, Western Sydney Genetics Program, Children’s Hospital at Westmead, NSW, Sydney, 2145, Australia
z Département de Génétique, Centre de Référence des Déficiences Intellectuelles de Causes Rares, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Paris, 75013, France
aa Department of Clinical Research, Ambry Genetics, Aliso Viejo, CA 92656, USA
ab Genomic Medicine Institute, Geisinger, PA 17822, Danville, United States
ac Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital, Seattle, WA 98195-6320, USA
ad Division of Genetics, Arnold Palmer Hospital for Children, Orlando Health, FL 32806, Orlando, United States
ae Division of Genetics, Boise, United States
af Department of Pediatrics, Division of Pediatric Neurology, UT Health Science Center at San Antonio, San Antonio, TX 78229, United States
ag Institute of Human Genetics, Technical University of Munich, School of Medicine, Munich, 81675, Germany
ah Institute of Neurogenomics (ING), German Research Center for Environmental Health, Helmholtz Zentrum München, Germany
ai Klinikum der Universität München, Integriertes Sozialpädiatrisches Zentrum, Munich, 80337, Germany
aj Children’s Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
ak Department of Genetics, Children’s Hospital of Eastern Ontario, Ottawa, Canada
al Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus ,Hinxton, Cambridge, CB10 1SA, United Kingdom
am Clinical Genetics Department, Guy’s and St Thomas’ NHS Foundation Trust, London, SE1 9RT, United Kingdom
an Division of Medical Genetics, McGill University Health Centre, Montreal, Canada
ao Department of Clinical Genetics, Nottingham University Hospitals NHS Trust, City Hospital Campus, the Gables, Gate 3, Hucknall Road, Nottingham NG5 1PB, UK
ap Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, United States
aq Children’s Hospital of Philadelphia, PA 19146, Center for Data Driven Discovery in Biomedicine, Philadelphia, United States
ar Service de Médecine Génomique des Maladies Rares, Hôpital Universitaire Necker-Enfants Malades, Paris, 75743, France
as University Children’s Hospital, Salzburger Landeskliniken (SALK) and Paracelsus Medical University (PMU)Salzburg 5020, Austria
at UMR 1253, Université de Tours, Inserm, Tours, 37032, France
au Centre Hospitalier Régional Universitaire, Service de Génétique, Tours, 37032, France
av Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charité Universitätsmedizin BerlinBerlin 13353, Germany
aw Deutsches Rheumaforschungszentrum, an institute of the Leibniz Association, Berlin and Berlin Institute of HealthBerlin 10117, Germany
ax Universitätsmedizin Greifswald, Interfakultäres Institut für Genetik und Funktionelle Genomforschung, Abteilung für Funktionelle Genomforschung, Germany
ay Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
az Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Medical Physics and BiophysicsBerlin, Germany
ba Berlin Institute of HealthBerlin 10178, Germany
bb Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB T6G 2E1, Canada
bc Department of Medical Genetics, University of Alberta, AB T6G 2H7, Edmonton, Canada
Abstract
A critical step in preserving protein homeostasis is the recognition, binding, unfolding, and translocation of protein substrates by six AAA-ATPase proteasome subunits (ATPase-associated with various cellular activities) termed PSMC1-6, which are required for degradation of proteins by 26S proteasomes. Here, we identified 15 de novo missense variants in the PSMC3 gene encoding the AAA-ATPase proteasome subunit PSMC3/Rpt5 in 23 unrelated heterozygous patients with an autosomal dominant form of neurodevelopmental delay and intellectual disability. Expression of PSMC3 variants in mouse neuronal cultures led to altered dendrite development, and deletion of the PSMC3 fly ortholog Rpt5 impaired reversal learning capabilities in fruit flies. Structural modeling as well as proteomic and transcriptomic analyses of T cells derived from patients with PSMC3 variants implicated the PSMC3 variants in proteasome dysfunction through disruption of substrate translocation, induction of proteotoxic stress, and alterations in proteins controlling developmental and innate immune programs. The proteostatic perturbations in T cells from patients with PSMC3 variants correlated with a dysregulation in type I interferon (IFN) signaling in these T cells, which could be blocked by inhibition of the intracellular stress sensor protein kinase R (PKR). These results suggest that proteotoxic stress activated PKR in patient-derived T cells, resulting in a type I IFN response. The potential relationship among proteosome dysfunction, type I IFN production, and neurodevelopment suggests new directions in our understanding of pathogenesis in some neurodevelopmental disorders.
Document Type: Article
Publication Stage: Final
Source: Scopus
Association of Stages of Objective Memory Impairment With Incident Symptomatic Cognitive Impairment in Cognitively Normal Individuals
(2023) Neurology, 100 (22), pp. E2279-E2289.
Grober, E.a , Petersen, K.K.b , Lipton, R.B.a , Hassenstab, J.a , Morris, J.C.a , Gordon, B.A.a , Ezzati, A.a
a Saul R. Korey, Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background and ObjectivesIncreasing evidence indicates that a subset of cognitively normal individuals has subtle cognitive impairment at baseline. We sought to identify them using the Stages of Objective Memory Impairment (SOMI) system. Symptomatic cognitive impairment was operationalized by a Clinical Dementia Rating (CDR) ≥0.5. We hypothesized that incident impairment would be higher for participants with subtle retrieval impairment (SOMI-1), higher still for those with moderate retrieval impairment (SOMI-2), and highest for those with storage impairment (SOMI-3/4) after adjusting for demographics and APOE ϵ4 status. A secondary objective was to determine whether including biomarkers of β-amyloid, tau pathology, and neurodegeneration in the models affect prediction. We hypothesized that even after adjusting for in vivo biomarkers, SOMI would remain a significant predictor of time to incident symptomatic cognitive impairment.MethodsAmong 969 cognitively normal participants, defined by a CDR = 0, from the Knight Alzheimer Disease Research Center, SOMI stage was determined from their baseline Free and Cued Selective Reminding Test scores, 555 had CSF and structural MRI measures and comprised the biomarker subgroup, and 144 of them were amyloid positive. Cox proportional hazards models tested associations of SOMI stages at baseline and biomarkers with time to incident cognitive impairment defined as the transition to CDR ≥0.5.ResultsAmong all participants, the mean age was 69.35 years, 59.6% were female, and mean follow-up was 6.36 years. Participants in SOMI-1-4 had elevated hazard ratios for the transition from normal to impaired cognition in comparison with those who were SOMI-0 (no memory impairment). Individuals in SOMI-1 (mildly impaired retrieval) and SOMI-2 (moderately impaired retrieval) were at nearly double the risk of clinical progression compared with persons with no memory problems. When memory storage impairment emerges (SOMI-3/4), the hazard ratio for clinical progression increased approximately 3 times. SOMI stage remained an independent predictor of incident cognitive impairment after adjusting for all biomarkers.DiscussionSOMI predicts the transition from normal cognition to incident symptomatic cognitive impairment (CDR ≥0.5). The results support the use of SOMI to identify those cognitively normal participants most likely to develop incident cognitive impairment who can then be referred for biomarker screening. © American Academy of Neurology.
Funding details
P01AG003991, P01AG026276, P30 AG066444, U19 AG024904, U19 AG032438
National Institutes of HealthNIH
National Institute on AgingNIA2PO1 AG003949, K23 AG063993
Alzheimer’s AssociationAA2019-AACSF-641329
Document Type: Article
Publication Stage: Final
Source: Scopus
Age-related differences in resting-state functional connectivity from childhood to adolescence
(2023) Cerebral Cortex (New York, N.Y. : 1991), 33 (11), pp. 6928-6942.
Sanders, A.F.P.a , Harms, M.P.a , Kandala, S.a , Marek, S.b , Somerville, L.H.c , Bookheimer, S.Y.d , Dapretto, M.d , Thomas, K.M.e , Van Essen, D.C.f , Yacoub, E.g , Barch, D.M.a h
a Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, United States
b Department of Radiology, Washington University School of Medicine, St Louis, United States
c Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, United States
d Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
e Institute of Child Development, University of Minnesota, Minneapolis, United States
f Department of Neuroscience, Washington University School of Medicine, St Louis, MO 63110, United States
g Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States
h Department of Psychological and Brain Sciences, Washington University, St Louis, MO 63130, United States
Abstract
The human brain is active at rest, and spontaneous fluctuations in functional MRI BOLD signals reveal an intrinsic functional architecture. During childhood and adolescence, functional networks undergo varying patterns of maturation, and measures of functional connectivity within and between networks differ as a function of age. However, many aspects of these developmental patterns (e.g. trajectory shape and directionality) remain unresolved. In the present study, we characterised age-related differences in within- and between-network resting-state functional connectivity (rsFC) and integration (i.e. participation coefficient, PC) in a large cross-sectional sample of children and adolescents (n = 628) aged 8-21 years from the Lifespan Human Connectome Project in Development. We found evidence for both linear and non-linear differences in cortical, subcortical, and cerebellar rsFC, as well as integration, that varied by age. Additionally, we found that sex moderated the relationship between age and putamen integration where males displayed significant age-related increases in putamen PC compared with females. Taken together, these results provide evidence for complex, non-linear differences in some brain systems during development. © The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Author Keywords
brain development; generalised additive models; participation coefficient; resting-state functional connectivity; sex differences
Document Type: Article
Publication Stage: Final
Source: Scopus
Functional screening of lysosomal storage disorder genes identifies modifiers of alpha-synuclein neurotoxicity
(2023) PLoS Genetics, 19 (5), p. e1010760.
Yu, M.a , Ye, H.b , De-Paula, R.B.c , Mangleburg, C.G.d e , Wu, T.d e , Lee, T.V.b , Li, Y.b , Duong, D.f , Phillips, B.g h , Cruchaga, C.g h , Allen, G.I.i j , Seyfried, N.T.f , Al-Ramahi, I.d j k , Botas, J.c d j k , Shulman, J.M.a k b d j k
a Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
b Department of Neurology, Baylor College of Medicine, Houston, TX, United States
c Quantitative and Computational Biology Program, Baylor College of Medicine, Houston, TX, United States
d Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
e Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
f Departments of Biochemistry and Neurology, Emory University School of Medicine, Atlanta, GA, United States
g Department of Psychiatry, Washington University, St. Louis, MO, United States
h Washington University, St. Louis, MO, United States
i Departments of Electrical and Computer Engineering, Computer Science, Statistics, Rice University, Houston, TX, United States
j Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
k Center for Alzheimer’s and Neurodegenerative Diseases, Baylor College of Medicine, Houston, TX, United States
Abstract
Heterozygous variants in the glucocerebrosidase (GBA) gene are common and potent risk factors for Parkinson’s disease (PD). GBA also causes the autosomal recessive lysosomal storage disorder (LSD), Gaucher disease, and emerging evidence from human genetics implicates many other LSD genes in PD susceptibility. We have systemically tested 86 conserved fly homologs of 37 human LSD genes for requirements in the aging adult Drosophila brain and for potential genetic interactions with neurodegeneration caused by α-synuclein (αSyn), which forms Lewy body pathology in PD. Our screen identifies 15 genetic enhancers of αSyn-induced progressive locomotor dysfunction, including knockdown of fly homologs of GBA and other LSD genes with independent support as PD susceptibility factors from human genetics (SCARB2, SMPD1, CTSD, GNPTAB, SLC17A5). For several genes, results from multiple alleles suggest dose-sensitivity and context-dependent pleiotropy in the presence or absence of αSyn. Homologs of two genes causing cholesterol storage disorders, Npc1a / NPC1 and Lip4 / LIPA, were independently confirmed as loss-of-function enhancers of αSyn-induced retinal degeneration. The enzymes encoded by several modifier genes are upregulated in αSyn transgenic flies, based on unbiased proteomics, revealing a possible, albeit ineffective, compensatory response. Overall, our results reinforce the important role of lysosomal genes in brain health and PD pathogenesis, and implicate several metabolic pathways, including cholesterol homeostasis, in αSyn-mediated neurotoxicity. Copyright: © 2023 Yu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Document Type: Article
Publication Stage: Final
Source: Scopus
Extraction of clinical phenotypes for Alzheimer’s disease dementia from clinical notes using natural language processing
(2023) JAMIA Open, 6 (1), art. no. ooad014, .
Oh, I.Y.a , Schindler, S.E.b , Ghoshal, N.b c , Lai, A.M.a , Payne, P.R.O.a , Gupta, A.a d
a Institute for Informatics, Washington University School of Medicine, St. Louis, MO, United States
b Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
d Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Objectives: There is much interest in utilizing clinical data for developing prediction models for Alzheimer’s disease (AD) risk, progression, and outcomes. Existing studies have mostly utilized curated research registries, image analysis, and structured electronic health record (EHR) data. However, much critical information resides in relatively inaccessible unstructured clinical notes within the EHR. Materials and Methods: We developed a natural language processing (NLP)-based pipeline to extract AD-related clinical phenotypes, documenting strategies for success and assessing the utility of mining unstructured clinical notes. We evaluated the pipeline against gold-standard manual annotations performed by 2 clinical dementia experts for AD-related clinical phenotypes including medical comorbidities, biomarkers, neurobehavioral test scores, behavioral indicators of cognitive decline, family history, and neuroimaging findings. Results: Documentation rates for each phenotype varied in the structured versus unstructured EHR. Interannotator agreement was high (Cohen’s kappa = 0.72-1) and positively correlated with the NLP-based phenotype extraction pipeline’s performance (average F1-score = 0.65-0.99) for each phenotype. Discussion: We developed an automated NLP-based pipeline to extract informative phenotypes that may improve the performance of eventual machine learning predictive models for AD. In the process, we examined documentation practices for each phenotype relevant to the care of AD patients and identified factors for success. Conclusion: Success of our NLP-based phenotype extraction pipeline depended on domain-specific knowledge and focus on a specific clinical domain instead of maximizing generalizability. © 2023 The Author(s). Published by Oxford University Press on behalf of the American Medical Informatics Association.
Author Keywords
Alzheimer’s disease; electronic health records; information retrieval; natural language processing; routinely collected health data
Document Type: Article
Publication Stage: Final
Source: Scopus
Efficacy of laser interstitial thermal therapy for biopsy-proven radiation necrosis in radiographically recurrent brain metastases
(2023) Neuro-Oncology Advances, 5 (1), art. no. vdad031, .
Chan, M.a , Tatter, S.a , Chiang, V.b , Fecci, P.c , Strowd, R.a , Prabhu, S.d , Hadjipanayis, C.e , Kirkpatrick, J.c , Sun, D.f , Sinicrope, K.f , Mohammadi, A.M.g , Sevak, P.f , Abram, S.h , Kim, A.H.i , Leuthardt, E.i , Chao, S.g , Phillips, J.h , Lacroix, M.j , Williams, B.k , Placantonakis, D.l , Silverman, J.l , Baumgartner, J.m , Piccioni, D.n , Laxton, A.a
a Wake Forest Baptist Health, Winston-Salem, NC, United States
b Yale School of Medicine, New Haven, CT, United States
c Duke University Medical Center, Durham, NC, United States
d University of Texas MD Anderson Cancer Center, Houston, TX, United States
e University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
f Norton Neuroscience Institute, Louisville, KY, United States
g Cleveland Clinic Lerner College of Medicine at CWRU, Cleveland, OH, United States
h Ascension St. Thomas Hospital West, Nashville, TN, United States
i Washington University School of Medicine, St. Louis, MO, United States
j Geisinger Medical Center, Danville, PA, United States
k University of Louisville Health, Louisville, KY, United States
l NYU Grossman School of Medicine, New York, NY, United States
m AdventHealth Medical Group, Orlando, FL, United States
n University of California San Diego Health, La JollaCA, United States
Abstract
Background: Laser interstitial thermal therapy (LITT) in the setting of post-SRS radiation necrosis (RN) for patients with brain metastases has growing evidence for efficacy. However, questions remain regarding hospitalization, local control, symptom control, and concurrent use of therapies. Methods: Demographics, intraprocedural data, safety, Karnofsky performance status (KPS), and survival data were prospectively collected and then analyzed on patients who consented between 2016-2020 and who were undergoing LITT for biopsy-proven RN at one of 14 US centers. Data were monitored for accuracy. Statistical analysis included individual variable summaries, multivariable Fine and Gray analysis, and Kaplan-Meier estimated survival. Results: Ninety patients met the inclusion criteria. Four patients underwent 2 ablations on the same day. Median hospitalization time was 32.5 hours. The median time to corticosteroid cessation after LITT was 13.0 days (0.0, 1229.0) and cumulative incidence of lesional progression was 19% at 1 year. Median post-procedure overall survival was 2.55 years [1.66, infinity] and 77.1% at one year as estimated by KaplanMeier. Median KPS remained at 80 through 2-year follow-up. Seizure prevalence was 12% within 1-month post-LITT and 7.9% at 3 months; down from 34.4% within 60-day prior to procedure. Conclusions: LITT for RN was not only again found to be safe with low patient morbidity but was also a highly effective treatment for RN for both local control and symptom management (including seizures). In addition to averting expected neurological death, LITT facilitates ongoing systemic therapy (in particular immunotherapy) by enabling the rapid cessation of steroids, thereby facilitating maximal possible survival for these patients. © 2023 The Author(s). Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
Author Keywords
brain metastasis; Laser interstitial thermal therapy (LITT); radiation necrosis (RN); radiographic progression; stereotactic laser ablation (SLA)
Document Type: Article
Publication Stage: Final
Source: Scopus
Medicaid expansion is associated with increased 1-year survival for primary malignant brain tumors
(2023) Neuro-Oncology Advances, 5 (1), art. no. vdad022, .
Dmukauskas, M.a , Cioffi, G.a b , Neff, C.b c , Price, M.b c , Waite, K.A.a b , Kruchko, C.b , Barnes, J.M.d , Ostrom, Q.T.b c e f , Barnholtz-Sloan, J.S.a b g
a Trans Divisional Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, United States
b Central Brain Tumor Registry of the United States, Hinsdale, IL, United States
c Department of Neurosurgery, Duke University School of Medicine, Durham, NC, United States
d Department of Radiation Oncology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
e Preston Robert Tisch Brain Tumor Center, Duke University School of Medicine, Durham, NC, United States
f Duke Cancer Institute, Duke University Medical Center, Durham, NC, United States
g Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD, United States
Funding details
Centers for Disease Control and PreventionCDC75D30119C06056/Amendment 0002
National Cancer InstituteNCI
American Brain Tumor AssociationABTA
National Brain Tumor SocietyNBTS
Pediatric Brain Tumor FoundationPBTF
Musella Foundation For Brain Tumor Research and Information
Sontag Foundation
Division of Cancer Epidemiology and Genetics, National Cancer InstituteDCEG
Uncle Kory FoundationUKF
Document Type: Article
Publication Stage: Final
Source: Scopus
MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5D hybrid multi-task convolutional neural network
(2023) Neuro-Oncology Advances, 5 (1), art. no. vdad023, .
Chakrabarty, S.a , Lamontagne, P.b , Shimony, J.b , Marcus, D.S.b , Sotiras, A.c
a Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States
b Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
c Mallinckrodt Institute of Radiology, Institute for Informatics, Washington University School of Medicine, St. Louis, United States
Abstract
Background: IDH mutation and 1p/19q codeletion status are important prognostic markers for glioma that are currently determined using invasive procedures. Our goal was to develop artificial intelligence-based methods to noninvasively determine molecular alterations from MRI. Methods: Pre-operative MRI scans of 2648 glioma patients were collected from Washington University School of Medicine (WUSM; n = 835) and publicly available Brain Tumor Segmentation (BraTS; n = 378), LGG 1p/19q (n = 159), Ivy Glioblastoma Atlas Project (Ivy GAP; n = 41), The Cancer Genome Atlas (TCGA; n = 461), and the Erasmus Glioma Database (EGD; n = 774) datasets. A 2.5D hybrid convolutional neural network was proposed to simultaneously localize glioma and classify its molecular status by leveraging MRI imaging features and prior knowledge features from clinical records and tumor location. The models were trained on 223 and 348 cases for IDH and 1p/19q tasks, respectively, and tested on one internal (TCGA) and two external (WUSM and EGD) test sets. Results: For IDH, the best-performing model achieved areas under the receiver operating characteristic (AUROC) of 0.925, 0.874, 0.933 and areas under the precision-recall curves (AUPRC) of 0.899, 0.702, 0.853 on the internal, WUSM, and EGD test sets, respectively. For 1p/19q, the best model achieved AUROCs of 0.782, 0.754, 0.842, and AUPRCs of 0.588, 0.713, 0.782, on those three data-splits, respectively. Conclusions: The high accuracy of the model on unseen data showcases its generalization capabilities and suggests its potential to perform “virtual biopsy”for tailoring treatment planning and overall clinical management of gliomas. © 2023 The Author(s). Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
Author Keywords
1p/19q codeletion; deep learning; glioma; isocitrate dehydrogenase; overall survival
Funding details
National Institutes of HealthNIH1S10OD018091-01, 1S10RR022984-01A1, P30-NS098577, S10OD025200, U24-CA204854, U24-CA258483
Document Type: Article
Publication Stage: Final
Source: Scopus
Structural gray matter alterations in glioblastoma and high-grade glioma – A potential biomarker of survival
(2023) Neuro-Oncology Advances, 5 (1), art. no. vdad034, .
Lamichhane, B.a , Luckett, P.H.a , Dierker, D.b , Yun Park, K.a , Burton, H.c , Olufawo, M.a , Trevino, G.a , Lee, J.J.b , Daniel, A.G.S.d , Hacker, C.D.a , Marcus, D.S.b , Shimony, J.S.b , Leuthardt, E.C.a c d e f g h
a Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States
b Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
c Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
d Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO, United States
e Department of Mechanical Engineering and Materials Science, Washington University, St. Louis, MO, United States
f Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, United States
g Brain Laser Center, Washington University School of Medicine, St. Louis, MO, United States
h Division of Neurotechnology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background: Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients. Methods: We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients’ associated changes in CT as a potential biomarker of overall survival. Results: Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients’ cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%. Conclusions: These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients. © 2023 The Author(s). Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
Author Keywords
biomarker of GBM and HGG; brain tumor; cortical thickness; glioblastoma and high-grade glioma; overall survival
Funding details
National Cancer InstituteNCI
National Institute for Health and Care ResearchNIHRR01CA203861
Document Type: Article
Publication Stage: Final
Source: Scopus
Diffusion basis spectrum imaging as an adjunct to conventional MRI leads to earlier diagnosis of high-grade glioma tumor progression versus treatment effect
(2023) Neuro-Oncology Advances, 5 (1), .
Han, R.H.a , Johanns, T.M.b c , Roberts, K.F.d , Tao, Y.e , Luo, J.e , Ye, Z.f , Sun, P.f , Blum, J.f , Lin, T.-H.f , Song, S.-K.f , Kim, A.H.a c
a Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States
b Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
c Brain Tumor Center, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, United States
d Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
e Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States
f Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Background: Following chemoradiotherapy for high-grade glioma (HGG), it is often challenging to distinguish treatment changes from true tumor progression using conventional MRI. The diffusion basis spectrum imaging (DBSI) hindered fraction is associated with tissue edema or necrosis, which are common treatment-related changes. We hypothesized that DBSI hindered fraction may augment conventional imaging for earlier diagnosis of progression versus treatment effect. Methods: Adult patients were prospectively recruited if they had a known histologic diagnosis of HGG and completed standard-of-care chemoradiotherapy. DBSI and conventional MRI data were acquired longitudinally beginning 4 weeks post-radiation. Conventional MRI and DBSI metrics were compared with respect to their ability to diagnose progression versus treatment effect. Results: Twelve HGG patients were enrolled between August 2019 and February 2020, and 9 were ultimately analyzed (5 progression, 4 treatment effect). Within new or enlarging contrast-enhancing regions, DBSI hindered fraction was significantly higher in the treatment effect group compared to progression group (P =. 0004). Compared to serial conventional MRI alone, inclusion of DBSI would have led to earlier diagnosis of either progression or treatment effect in 6 (66.7%) patients by a median of 7.7 (interquartile range = 0-20.1) weeks. Conclusions: In the first longitudinal prospective study of DBSI in adult HGG patients, we found that in new or enlarging contrast-enhancing regions following therapy, DBSI hindered fraction is elevated in cases of treatment effect compared to those with progression. Hindered fraction map may be a valuable adjunct to conventional MRI to distinguish tumor progression from treatment effect. © 2023 The Author(s). Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
Author Keywords
diffusion basis spectrum imaging; diffusion MRI; glioblastoma; pseudoprogression; radiation necrosis
Funding details
National Institutes of HealthNIHR01NS047592, R01NS116091, R25NS090978, U01EY025500
American Cancer SocietyACSPF-21-149-01-CDP
Alvin J. Siteman Cancer Center
Document Type: Article
Publication Stage: Final
Source: Scopus
Learning slopes in early-onset Alzheimer’s disease
(2023) Alzheimer’s and Dementia, .
Hammers, D.B.a , Nemes, S.a , Diedrich, T.a , Eloyan, A.b , Kirby, K.a , Aisen, P.c , Kramer, J.d , Nudelman, K.e , Foroud, T.e , Rumbaugh, M.e , Atri, A.f , Day, G.S.g , Duara, R.h , Graff-Radford, N.R.g , Honig, L.S.i , Jones, D.T.j k , Masdeu, J.C.l , Mendez, M.F.m , Musiek, E.n , Onyike, C.U.o , Riddle, M.p , Rogalski, E.q , Salloway, S.p , Sha, S.J.r , Turner, R.S.s , Weintraub, S.q , Wingo, T.S.t , Wolk, D.A.u , Wong, B.v , Carrillo, M.C.w , Dickerson, B.C.v , Rabinovici, G.D.d , Apostolova, L.G.a e x , the LEADS Consortiumy
a Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
b Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, RI, United States
c Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, United States
d Department of Neurology, University of California, San Francisco, CA, United States
e Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
f Banner Sun Health Research Institute, Sun City, AZ, United States
g Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
h Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, United States
i Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States
j Department of Radiology, Mayo Clinic, Rochester, MN, United States
k Department of Neurology, Mayo Clinic, Rochester, MN, United States
l Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, TX, United States
m Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
n Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
o Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
p Department of Neurology, Alpert Medical School, Brown University, Providence, RI, United States
q Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer’s Disease, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
r Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, United States
s Department of Neurology, Georgetown University, Washington, DC, United States
t Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, GA, United States
u Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
v Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
w Medical & Scientific Relations Division, Alzheimer’s Association, Chicago, IL, United States
x Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, IN, United States
Abstract
OBJECTIVE: Investigation of learning slopes in early-onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early-onset dementia with and without β-amyloid positivity. METHOD: Data from 310 participants in the Longitudinal Early-Onset Alzheimer’s Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined. RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric—the learning ratio (LR)—outperformed other learning slope calculations across analyses. CONCLUSIONS: Learning slopes appear to be sensitive to early-onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. Highlights: Learning is impaired in amyloid-positive EOAD, beyond cognitive severity scores alone. Amyloid-positive EOAD participants perform worse on learning slopes than amyloid-negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants. © 2023 the Alzheimer’s Association.
Author Keywords
early-onset Alzheimer’s disease; learning slopes; memory
Funding details
R56 AG057195
National Institute on AgingNIAP30 AG010124, P30 AG010133, P30 AG013854, P30 AG062421, P30 AG062422, P30AG066506, P50 AG005146, P50 AG005681, P50 AG008702, P50 AG023501, P50 AG025688, P50AG047366, U01 AG016976, U01AG6057195, U24AG021886
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Local translation in microglial processes is required for efficient phagocytosis
(2023) Nature Neuroscience, .
Vasek, M.J.a b , Mueller, S.M.a b , Fass, S.B.a b , Deajon-Jackson, J.D.a b , Liu, Y.a b , Crosby, H.W.a b , Koester, S.K.a b c , Yi, J.a b c , Li, Q.a d , Dougherty, J.D.a b
a Department of Genetics, Washington University School of Medicine, Saint Louis, MO, United States
b Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, United States
c Division of Biology and Biomedical Sciences, Washington University School of Medicine, Saint Louis, MO, United States
d Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO, United States
Abstract
Neurons, astrocytes and oligodendrocytes locally regulate protein translation within distal processes. Here, we tested whether there is regulated local translation within peripheral microglial processes (PeMPs) from mouse brain. We show that PeMPs contain ribosomes that engage in de novo protein synthesis, and these are associated with transcripts involved in pathogen defense, motility and phagocytosis. Using a live slice preparation, we further show that acute translation blockade impairs the formation of PeMP phagocytic cups, the localization of lysosomal proteins within them, and phagocytosis of apoptotic cells and pathogen-like particles. Finally, PeMPs severed from their somata exhibit and require de novo local protein synthesis to effectively surround pathogen-like particles. Collectively, these data argue for regulated local translation in PeMPs and indicate a need for new translation to support dynamic microglial functions. © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.
Funding details
National Institutes of HealthNIH
National Center for Advancing Translational SciencesNCATS
Center for Cellular Imaging, Washington UniversityWUCCIP30 CA91842, UL1TR002345
Document Type: Article
Publication Stage: Article in Press
Source: Scopus