WashU weekly Neuroscience publications: October 20, 2024

Functional role of myosin-binding protein H in thick filaments of developing vertebrate fast-twitch skeletal muscle
(2024) The Journal of General Physiology, 156 (12), . 

Mead, A.F.^a b , Wood, N.B.^a , Nelson, S.R.^a b , Palmer, B.M.^a b , Yang, L.^c , Previs, S.B.^a b , Ploysangngam, A.^a , Kennedy, G.G.^a , McAdow, J.F.^d , Tremble, S.M.^e , Zimmermann, M.A.^a b , Cipolla, M.J.^e f , Ebert, A.M.^g , Johnson, A.N.^h , Gurnett, C.A.^h , Previs, M.J.^a b , Warshaw, D.M.^a b

^a Department of Molecular Physiology and Biophysics, Larner College of Medicine, University of Vermont, Burlington, VT, United States
^b Cardiovascular Research Institute, University of Vermont, Burlington, VT, United States
^c National Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, United States
^d Department of Neurlogical Sciences, Larner College of Medicine, University of Vermont, Burlington, VT, United States
^e Department of Electrical and Biomedical Engineering, College of Engineering and Mathematical Sciences, University of Vermont, Burlington, VT, United States
^f Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^g Department of Biology, College of Arts and Sciences, University of Vermont, Burlington, VT, United States
^h Department of Developmental Biology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

Abstract
Myosin-binding protein H (MyBP-H) is a component of the vertebrate skeletal muscle sarcomere with sequence and domain homology to myosin-binding protein C (MyBP-C). Whereas skeletal muscle isoforms of MyBP-C (fMyBP-C, sMyBP-C) modulate muscle contractility via interactions with actin thin filaments and myosin motors within the muscle sarcomere “C-zone,” MyBP-H has no known function. This is in part due to MyBP-H having limited expression in adult fast-twitch muscle and no known involvement in muscle disease. Quantitative proteomics reported here reveal that MyBP-H is highly expressed in prenatal rat fast-twitch muscles and larval zebrafish, suggesting a conserved role in muscle development and prompting studies to define its function. We take advantage of the genetic control of the zebrafish model and a combination of structural, functional, and biophysical techniques to interrogate the role of MyBP-H. Transgenic, FLAG-tagged MyBP-H or fMyBP-C both localize to the C-zones in larval myofibers, whereas genetic depletion of endogenous MyBP-H or fMyBP-C leads to increased accumulation of the other, suggesting competition for C-zone binding sites. Does MyBP-H modulate contractility in the C-zone? Globular domains critical to MyBP-C’s modulatory functions are absent from MyBP-H, suggesting that MyBP-H may be functionally silent. However, our results suggest an active role. In vitro motility experiments indicate MyBP-H shares MyBP-C’s capacity as a molecular “brake.” These results provide new insights and raise questions about the role of the C-zone during muscle development. © 2024 Mead et al.

Document Type: Article
Publication Stage: Final
Source: Scopus

The Multiple Sclerosis Prodrome in a Retrospective Pediatric Cohort
(2024) Pediatric Neurology, 161, pp. 144-148. 

Barter, K., Sharayah, S., Mange, U., Gaudioso, C.M., Schanzer, N., Keuchel, C., Zolno, R., Mar, S.

Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, United States

Abstract
Background: Evidence suggests a prodromal phase in multiple sclerosis (MS), with increased health care use preceding the first demyelinating event (FDE). Although prior studies have explored this in adults, limited data exist for pediatric cases. We aimed to analyze health care utilization and prodromal symptoms in the two years before FDE in patients with pediatric-onset MS (POMS). Methods: From 122 patients at the Pediatric Multiple Sclerosis & Demyelinating Diseases Center at Washington University School of Medicine from 2011 to 2021, 37 POMS cases were identified. Of these, 21 with at least two years of records preceding FDE were included. Retrospective analysis covered symptoms and health care utilization in the two-year period before FDE, including ambulatory visits, hospital admissions, and office calls. Results: Patients showed increased health care utilization in the year preceding FDE (period B; 96 interactions) compared with the prior year (period A; 77 interactions) and an increase in the percentage of neurology-related encounters (P < 0.001). There was an increase in all office calls from period A to period B (P = 0.01). Neurological complaints included headaches (28.6%), visual (19.0%), sensory (14.3%), and balance (14.3%) in the two years before FDE, and 28.6% of patients presented for psychiatric complaints. Common non-neurological complaints included infection, dermatologic, and musculoskeletal issues and injury. Conclusions: Our POMS cohort showed increased health care use before FDE, consistent with population-based data. This study emphasizes diverse symptoms in prodromal POMS, with headaches being the most common neurological symptom in the two-year period before FDE. © 2024 Elsevier Inc.

Author Keywords
First demyelinating event;  Multiple sclerosis;  Neuroimmunology;  Pediatric-onset multiple sclerosis;  Prodromal multiple sclerosis

Document Type: Article
Publication Stage: Final
Source: Scopus

Distinct visual processing networks for foveal and peripheral visual fields
(2024) Communications Biology, 7 (1), art. no. 1259, . 

Zhang, J.^a b c , Zhou, H.^b c , Wang, S.^a

^a Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
^b Peng Cheng Laboratory, Shenzhen, 518000, China
^c Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China

Abstract
Foveal and peripheral vision are two distinct modes of visual processing essential for navigating the world. However, it remains unclear if they engage different neural mechanisms and circuits within the visual attentional system. Here, we trained macaques to perform a free-gaze visual search task using natural face and object stimuli and recorded a large number of 14588 visually responsive units from a broadly distributed network of brain regions involved in visual attentional processing. Foveal and peripheral units had substantially different proportions across brain regions and exhibited systematic differences in encoding visual information and visual attention. The spike-local field potential (LFP) coherence of foveal units was more extensively modulated by both attention and visual selectivity, thus indicating differential engagement of the attention and visual coding network compared to peripheral units. Furthermore, we delineated the interaction and coordination between foveal and peripheral processing for spatial attention and saccade selection. Together, the systematic differences between foveal and peripheral processing provide valuable insights into how the brain processes and integrates visual information from different regions of the visual field. © The Author(s) 2024.

Document Type: Article
Publication Stage: Final
Source: Scopus

Machine learning and Bayesian network analyses identifies associations with insomnia in a national sample of 31,285 treatment-seeking college students
(2024) BMC Psychiatry, 24 (1), art. no. 656, . 

Calderon, A.^a , Baik, S.Y.^a , Ng, M.H.S.^b , Fitzsimmons-Craft, E.E.^c , Eisenberg, D.^d , Wilfley, D.E.^c , Taylor, C.B.^e f , Newman, M.G.^a

^a Department of Psychology, The Pennsylvania State University, University Park, PA, United States
^b Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore
^c Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^d Department of Health Policy and Management, University of California-Los Angeles, Los Angeles, CA, United States
^e Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
^f Center for m2Health, Palo Alto University, Los Altos, CA, United States

Abstract
Background: A better understanding of the relationships between insomnia and anxiety, mood, eating, and alcohol-use disorders is needed given its prevalence among young adults. Supervised machine learning provides the ability to evaluate which mental disorder is most associated with heightened insomnia among U.S. college students. Combined with Bayesian network analysis, probable directional relationships between insomnia and interacting symptoms may be illuminated. Methods: The current exploratory analyses utilized a national sample of college students across 26 U.S. colleges and universities collected during population-level screening before entering a randomized controlled trial. We used a 4-step statistical approach: (1) at the disorder level, an elastic net regularization model examined the relative importance of the association between insomnia and 7 mental disorders (major depressive disorder, generalized anxiety disorder, social anxiety disorder, panic disorder, post-traumatic stress disorder, anorexia nervosa, and alcohol use disorder); (2) This model was evaluated within a hold-out sample. (3) at the symptom level, a completed partially directed acyclic graph (CPDAG) was computed via a Bayesian hill-climbing algorithm to estimate potential directionality among insomnia and its most associated disorder [based on SHAP (SHapley Additive exPlanations) values)]; (4) the CPDAG was then tested for generalizability by assessing (in)equality within a hold-out sample using structural hamming distance (SHD). Results: Of 31,285 participants, 20,597 were women (65.8%); mean (standard deviation) age was 22.96 (4.52) years. The elastic net model demonstrated clinical significance in predicting insomnia severity in the training sample [R2 =.44 (.01); RMSE = 5.00 (0.08)], with comparable performance in the hold-out sample (R2 =.33; RMSE = 5.47). SHAP values indicated that the presence of any mental disorder was associated with higher insomnia scores, with major depressive disorder as the most important disorder associated with heightened insomnia (mean |SHAP|= 3.18). The training CPDAG and hold-out CPDAG (SHD = 7) suggested depression symptoms presupposed insomnia with depressed mood, fatigue, and self-esteem as key parent nodes. Conclusion: These findings provide insights into the associations between insomnia and mental disorders among college students and warrant further investigation into the potential direction of causality between insomnia and depression. Trial registration: Trial was registered on the National Institute of Health RePORTER website (R01MH115128 || 23/08/2018). © The Author(s) 2024.

Author Keywords
Bayesian network analysis;  College students;  Comorbidities;  Insomnia;  Machine learning

Document Type: Article
Publication Stage: Final
Source: Scopus

25-hydroxycholesterol promotes brain cytokine production and leukocyte infiltration in a mouse model of lipopolysaccharide-induced neuroinflammation
(2024) Journal of Neuroinflammation, 21 (1), art. no. 251, . 

Romero, J.^a , Toral-Rios, D.^a , Yu, J.^b , Paul, S.M.^a c d , Cashikar, A.G.^a c d

^a Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, United States
^b Department of Genetics & amp; Genome Technology Access Center, Washington University School of Medicine, St Louis, MO 63110, United States
^c Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, United States
^d Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, 425 S Euclid Ave, Campus Box 8134, St Louis, MO 63110, United States

Abstract
Neuroinflammation has been implicated in the pathogenesis of several neurologic and psychiatric disorders. Microglia are key drivers of neuroinflammation and, in response to different inflammatory stimuli, overexpress a proinflammatory signature of genes. Among these, Ch25h is a gene overexpressed in brain tissue from Alzheimer’s disease as well as various mouse models of neuroinflammation. Ch25h encodes cholesterol 25-hydroxylase, an enzyme upregulated in activated microglia under conditions of neuroinflammation, that hydroxylates cholesterol to form 25-hydroxycholesterol (25HC). 25HC can be further metabolized to 7α,25-dihydroxycholesterol, which is a potent chemoattractant of leukocytes. We have previously shown that 25HC increases the production and secretion of the proinflammatory cytokine, IL-1β, by primary mouse microglia treated with lipopolysaccharide (LPS). In the present study, wildtype (WT) and Ch25h-knockout (KO) mice were peripherally administered LPS to induce an inflammatory state in the brain. In LPS-treated WT mice, Ch25h expression and 25HC levels increased in the brain relative to vehicle-treated WT mice. Among LPS-treated WT mice, females produced significantly higher levels of 25HC and showed transcriptomic changes reflecting higher levels of cytokine production and leukocyte migration than WT male mice. However, females were similar to males among LPS-treated KO mice. Ch25h-deficiency coincided with decreased microglial activation in response to systemic LPS. Proinflammatory cytokine production and intra-parenchymal infiltration of leukocytes were significantly lower in KO compared to WT mice. Amounts of IL-1β and IL-6 in the brain strongly correlated with 25HC levels. Our results suggest a proinflammatory role for 25HC in the brain following peripheral administration of LPS. © The Author(s) 2024.

Author Keywords
25-hydroxycholesterol;  Alzheimer’s disease;  Cholesterol-25-hydroxylase;  Cytokines;  Lipopolysaccharide;  Microglial activation;  Neuroinflammation;  Neutrophil infiltration;  Toll-like receptor-4

Document Type: Article
Publication Stage: Final
Source: Scopus

Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer’s disease continuum
(2024) Translational Psychiatry, 14 (1), art. no. 420, . 

Wen, J.^a , Yang, Z.^b , Nasrallah, I.M.^b , Cui, Y.^b , Erus, G.^b , Srinivasan, D.^b , Abdulkadir, A.^b c , Mamourian, E.^b , Hwang, G.^b , Singh, A.^b , Bergman, M.^b , Bao, J.^d , Varol, E.^e , Zhou, Z.^b , Boquet-Pujadas, A.^a , Chen, J.^b , Toga, A.W.^f , Saykin, A.J.^g , Hohman, T.J.^h , Thompson, P.M.ⁱ , Villeneuve, S.^j , Gollub, R.^k , Sotiras, A.^l , Wittfeld, K.^m , Grabe, H.J.^m , Tosun, D.ⁿ , Bilgel, M.^o , An, Y.^o , Marcus, D.S.^p , LaMontagne, P.^p , Benzinger, T.L.^p , Heckbert, S.R.^q , Austin, T.R.^q , Launer, L.J.^r , Espeland, M.^s , Masters, C.L.^t , Maruff, P.^t , Fripp, J.^u , Johnson, S.C.^v , Morris, J.C.^w , Albert, M.S.^x , Bryan, R.N.^y , Resnick, S.M.^o , Ferrucci, L.^z , Fan, Y.^b , Habes, M.^aa , Wolk, D.^b ab , Shen, L.^d , Shou, H.^b ac , Davatzikos, C.^b

^a Laboratory of AI and Biomedical Science (LABS), University of Southern California, Los Angeles, CA, United States
^b Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL), Center for AI and Data Science for Integrated Diagnostics (AI2D), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^c Research Lab in Neuroimaging of the Department of Clinical Neurosciences at Lausanne University Hospital, Lausanne, Switzerland
^d Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^e Department of Statistics, Center for Theoretical Neuroscience, Zuckerman Institute, Columbia University, New York, NY, United States
^f Laboratory of NeuroImaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
^g Radiology and Imaging Sciences, Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana Alzheimer’s Disease Research Center and the Melvin and Bren Simon Cancer Center, Indiana University School of Medicine, Indianapolis, IN, United States
^h Vanderbilt Memory and Alzheimer’s Center, Vanderbilt Genetics Institute, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States
ⁱ Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del ReyCA, United States
^j Douglas Mental Health University Institute, McGill University, Montréal, QC, Canada
^k Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
^l Department of Radiology and Institute for Informatics, Washington University School of Medicine, St. Louis, MO, United States
^m Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
ⁿ Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States
^o Laboratory of Behavioral Neuroscience, National Institute on Aging, NIH, Baltimore, MD, United States
^p Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
^q Cardiovascular Health Research Unit and Department of Epidemiology, University of Washington, Seattle, WA, United States
^r Neuroepidemiology Section, Intramural Research Program, National Institute on Aging, Bethesda, MD, United States
^s Sticht Center for Healthy Aging and Alzheimer’s Prevention, Wake Forest School of Medicine, Winston-Salem, NC, United States
^t Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
^u CSIRO Health and Biosecurity, Australian e-Health Research Centre CSIRO, Brisbane, QLD, Australia
^v Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
^w Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, United States
^x Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
^y Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
^z Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 S. Hanover Street, Baltimore, MD 21225, United States
^aa Glenn Biggs Institute for Alzheimer’s & amp; Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
^ab Department of Neurology and Penn Memory Center, University of Pennsylvania, Philadelphia, PA, United States
^ac Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States

Abstract
Alzheimer’s disease (AD) is associated with heterogeneous atrophy patterns. We employed a semi-supervised representation learning technique known as Surreal-GAN, through which we identified two latent dimensional representations of brain atrophy in symptomatic mild cognitive impairment (MCI) and AD patients: the “diffuse-AD” (R1) dimension shows widespread brain atrophy, and the “MTL-AD” (R2) dimension displays focal medial temporal lobe (MTL) atrophy. Critically, only R2 was associated with widely known sporadic AD genetic risk factors (e.g., APOE ε4) in MCI and AD patients at baseline. We then independently detected the presence of the two dimensions in the early stages by deploying the trained model in the general population and two cognitively unimpaired cohorts of asymptomatic participants. In the general population, genome-wide association studies found 77 genes unrelated to APOE differentially associated with R1 and R2. Functional analyses revealed that these genes were overrepresented in differentially expressed gene sets in organs beyond the brain (R1 and R2), including the heart (R1) and the pituitary gland, muscle, and kidney (R2). These genes were enriched in biological pathways implicated in dendritic cells (R2), macrophage functions (R1), and cancer (R1 and R2). Several of them were “druggable genes” for cancer (R1), inflammation (R1), cardiovascular diseases (R1), and diseases of the nervous system (R2). The longitudinal progression showed that APOEε4, amyloid, and tau were associated with R2 at early asymptomatic stages, but this longitudinal association occurs only at late symptomatic stages in R1. Our findings deepen our understanding of the multifaceted pathogenesis of AD beyond the brain. In early asymptomatic stages, the two dimensions are associated with diverse pathological mechanisms, including cardiovascular diseases, inflammation, and hormonal dysfunction—driven by genes different from APOE—which may collectively contribute to the early pathogenesis of AD. All results are publicly available at https://labs-laboratory.com/medicine/. © The Author(s) 2024.

Document Type: Article
Publication Stage: Final
Source: Scopus

Size and Topography of the Brain’s Functional Networks with Psychotic Experiences, Schizophrenia, and Bipolar Disorder
(2024) Biological Psychiatry Global Open Science, 4 (6), art. no. 100386, . 

Mamah, D.^a , Chen, S.S.^a , Gordon, E.^b , Kandala, S.^a , Barch, D.M.^a c , Harms, M.P.^a

^a Department of Psychiatry, Washington University Medical School, St LouisMissouri, United States
^b Department of Radiology, Washington University Medical School, St LouisMissouri, United States
^c Department of Psychological and Brain Sciences, Washington University Medical School, St LouisMissouri, United States

Abstract
Background: Existing functional connectivity studies of psychosis use population-averaged functional network maps, despite highly variable topographies of these networks across the brain surface. We aimed to define the functional network areas and topographies in the general population and the changes associated with psychotic experiences (PEs) and disorders. Methods: Maps of 8 functional networks were generated using an individual-specific template-matching procedure for each participant from the Human Connectome Project Young Adult cohort (n = 1003) and from a matched case cohort (schizophrenia [SCZ], n = 27; bipolar disorder, n = 35) scanned identically with the same Connectom scanner. In the Human Connectome Project Young Adult cohort, PEs were estimated based on scores from the Achenbach Self-Report Scale. The relationship of symptoms to the probability of network representation at each cortical vertex was assessed using logistic regression. Results: In Human Connectome Project Young Adult participants, PE severity on the Achenbach thought problems scale was predicted by increased language network (LAN) and dorsal attention network (DAN) areas and decreased cingulo-opercular network area (r < 0.12). Significant effects were found in SCZ, with a larger DAN and LAN and a smaller frontoparietal network. Network pattern analysis in SCZ showed an increased probability of LAN in the posterior region of the left superior temporal gyrus and of the visual network in the left insula. Regression analyses in SCZ found that mood dysregulation was related to increased DAN surface area. Conclusions: Those with PEs and SCZ showed abnormal functional network cortical topographies, particularly involving DAN and LAN. Network findings may predict psychosis progression and guide earlier intervention. © 2024 The Authors

Author Keywords
Bipolar disorder;  Functional connectivity;  Human Connectome Project;  Psychotic experiences;  Schizophrenia

Document Type: Article
Publication Stage: Final
Source: Scopus

Cell type–specific epigenetic priming of gene expression in nucleus accumbens by cocaine
(2024) Science Advances, 10 (40), art. no. eado3514, . 

Mews, P.^a , Van der Zee, Y.^a , Gurung, A.^a , Estill, M.^a , Futamura, R.^a , Kronman, H.^a , Ramakrishnan, A.^a , Ryan, M.^a , Reyes, A.A.^a , Garcia, B.A.^b , Browne, C.J.^a , Sidoli, S.^c , Shen, L.^a , Nestler, E.J.^a

^a Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^b Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, United States
^c Department of Biochemistry, Albert Einstein College of Medticine, New York, NY, United States

Abstract
A hallmark of addiction is the ability of drugs of abuse to trigger relapse after periods of prolonged abstinence. Here, we describe an epigenetic mechanism whereby chronic cocaine exposure causes lasting chromatin and downstream transcriptional modifications in the nucleus accumbens (NAc), a critical brain region controlling motivation. We link prolonged withdrawal from cocaine to the depletion of the histone variant H2A.Z, coupled with increased genome accessibility and latent priming of gene transcription, in D1 dopamine receptor–expressing medium spiny neurons (D1 MSNs) that relate to aberrant gene expression upon drug relapse. The histone chaperone ANP32E removes H2A.Z from chromatin, and we demonstrate that D1 MSN–selective Anp32e knockdown prevents cocaine-induced H2A.Z depletion and blocks cocaine’s rewarding actions. By contrast, very different effects of cocaine exposure, withdrawal, and relapse were found for D2 MSNs. These findings establish histone variant exchange as an important mechanism and clinical target engaged by drugs of abuse to corrupt brain function and behavior. Copyright © 2024 The Authors, some rights reserved.

Document Type: Article
Publication Stage: Final
Source: Scopus

The association of dementia risk symptoms and functional activity in adults with Down syndrome
(2024) Alzheimer’s and Dementia: Translational Research and Clinical Interventions, 10 (4), art. no. e70007, . 

Washington, S.E.^a , Bodde, A.E.^b , Helsel, B.C.^c , Bollinger, R.M.^d , Smith, N.^a , Ptomey, L.T.^b , Ances, B.^e , Stark, S.L.^d

^a Department of Occupational Science and Occupational Therapy, Saint Louis University, St. Louis, MO, United States
^b Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, United States
^c Department of Neurology, University of Kansas Alzheimer’s Disease Research Center, University of Kansas Medical Center, Kansas City, KS, United States
^d Program in Occupational Therapy, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^e Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

Abstract
INTRODUCTION: Adults with Down syndrome (DS) have an increased risk of Alzheimer’s disease (AD) dementia, often showing neuropathological indicators by age 40. Physical function and activities of daily living (ADLs) are understudied areas of function that may inform dementia risk. We investigated associations among age, physical function (gait/balance, grip strength, and lower extremity strength), ADLs, and dementia risk symptoms in adults with DS. We hypothesized that compromised physical function and lower independence with ADLs would be associated with an informant/caregiver-reported measure of dementia risk symptoms. METHODS: A secondary analysis for this cross-sectional study was completed using data from two academic research centers with 43 adults with DS (age 30 ± 12 years). We examined the association of dementia risk symptoms, captured through the Dementia Screening Questionnaire for Individuals with Intellectual Disabilities (DSQIID), with physical function (timed up and go [TUG], sit-to-stand [STS], grip strength) and ADLs (Waisman Activities of Daily Living Scale). A linear regression model for the continuous dementia risk measure in the DSQIID used a log transformation of (1 + log(Y + 1)) to account for a high zero count. Wilcoxon rank-sum tests were used to assess differences in the physical function measures, DSQIID questionnaire, and Waisman ADL by dividing mean age categories. RESULTS: Higher DSQIID scores were associated with lower independence with ADLs (β = −0.103, p = 0.008), slower gait times (TUG; β = 0.112, p = 0.034), and impaired lower extremity strength (STS; β = 0.112, p = 0.017) and grip strength (β = −0.039, p = 0.034). DSQIID scores differed significantly between the ≥30 and <30 age groups. Participants ≥30 years of age scored 5 points higher on the DSQIID than participants <30, suggesting that age was associated with greater dementia risk. DISCUSSION: Greater dementia risk symptoms were associated with age, lower physical function scores, and independence with ADLs, suggesting that declines in physical function and ADLs may be early indicators of subsequent dementia risk in adults with DS. Highlights: We explored the association of physical function and activities of daily living (ADLs) in aging adults with DS and their relationship with informant/caregiver report of dementia risk symptoms. Our findings demonstrated a significant relationship between a higher number of dementia risk symptoms observed and lower independence with ADLs, and impaired gait/balance, grip strength, and lower extremity strength. Further research with larger longitudinal studies is necessary to investigate any causative relationships among physical function, ADL function, and dementia risk symptoms. © 2024 The Author(s). Alzheimer’s & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Author Keywords
activities of daily living;  cognition;  dementia;  Down syndrome;  physical function

Funding details
National Institute on AgingNIAR01AG057680‐05S1
National Institute on AgingNIA
K01AG083130-01
R01AG063909-03

Document Type: Article
Publication Stage: Final
Source: Scopus

Linking social determinants of health to mental health, movement behaviors, and cognitive function among U.S. youth
(2024) Mental Health and Physical Activity, 27, art. no. 100639, . 

Liu, Z.^a , Chen, Y.^a b , Herold, F.^c , Cheval, B.^d e , Falck, R.S.^f , Kramer, A.F.^g h i , Gerber, M.^j , Werneck, A.O.^k , An, R.^l , Teychenne, M.^m , Owen, N.^n o , Zou, L.^a

^a Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University518060, China
^b Department of Physical Education, Shanghai Jiao Tong University, Shanghai, China
^c Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, 14476, Germany
^d Department of Sport Sciences and Physical Education, Ecole Normale Supérieure Rennes, Bruz, France
^e Laboratory VIPS2, University of Rennes, Rennes, France
^f Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
^g Center for Cognitive and Brain Health, Northeastern University, Boston, MA, United States
^h Department of Psychology, Northeastern University, Boston, MA 02115, United States
ⁱ Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-ChampaignIL, United States
^j Departement of Sport, Exercise and Health (DSBG), University of Basel, Basel, Switzerland
^k Center for Epidemiological Research in Nutrition and Health, Department of Nutrition, School of Public Health, Universidade de São Paulo, São Paulo, Brazil
^l Brown School and Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, MO 63130, United States
^m Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
ⁿ Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
^o Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia

Abstract
Background: Few studies have focused on a comprehensive view of social determinants of health (SDOH) domains as influences on the health of young people. This study aimed to investigate the associations between the Healthy people 2030 SDOH-related domains (i.e., economic stability, education access and quality, health care access and quality, neighborhood and built environment, and social and community context) with mental health, movement behaviors, and cognitive function among U.S. youth. Methods: This cross-sectional study used nationally representative data from the 2020–2021 National Survey of Children’s Health, covering 54,595 youth aged 6–17 years. The associations of indicators of SDOH-related domains with mental health (depression and anxiety), movement behaviors (physical activity and screen-based sedentary behavior), and cognitive function were estimated using multivariable logistic regression models, adjusting for age, sex, and race. Results: Economic stability, education access and quality, health care access and quality, and social and community context were associated with at least one outcome measure of mental health, movement behaviors, and cognitive function, while neighborhood and built environment was associated with mental health and movement behaviors. The social and community context domain stood out, with friendship difficulty and household-based adverse childhood experiences being associated with poorer outcomes on most health indicators. Conclusion: All five SDOH-related domains are related to aspects of youth health, with the social and community context domain showing the most associations, highlighting the need for interventions to improve social connection and address adverse childhood experiences, which may be more impactful in ameliorating many health-related challenges. © 2024 Elsevier Ltd

Author Keywords
Memory;  Mental health;  Social determinants of health;  Youth

Document Type: Article
Publication Stage: Final
Source: Scopus

Rehabilitation Transition Program to Improve Community Participation Among Stroke Survivors: A Randomized Clinical Trial
(2024) JAMA Network Open, 7 (10), p. e2437758. 

Bollinger, R.M.^a , Krauss, M.J.^a , Somerville, E.K.^a , Holden, B.M.^a , Blenden, G.^a , Hollingsworth, H.^a , Keleman, A.A.^a , Carter, A.^b , McBride, T.D.^c , Barker, A.R.^c , Yan, Y.^d , Stark, S.L.^a

^a Program in Occupational Therapy, Washington University in St Louis School of Medicine, St Louis, MO, United States
^b Division of Neurorehabilitation, Department of Neurology, Washington University in St Louis School of Medicine, St Louis, MO, United States
^c Center for Advancing Health Services, Economics, Policy Research, Institute for Public Health at Washington University in St Louis, St Louis, MO, United States
^d Department of Surgery, Washington University in St Louis School of Medicine, St Louis, MO, United States

Abstract
Importance: Interventions are needed to support the long-term needs of stroke survivors when they transition from inpatient rehabilitation to home, where they face new home and community environmental barriers. Objective: To compare the efficacy of a novel, enhanced rehabilitation transition program with attentional control to improve community participation and activity of daily living (ADL) performance and to reduce environmental barriers in the home and community after stroke. Design, Setting, and Participants: This phase 2b, parallel randomized clinical trial assessed patients 50 years or older who had experienced an acute ischemic stroke or intracerebral hemorrhage, were independent in ADLs before stroke, and planned to be discharged home. Patients were assessed at an inpatient rehabilitation facility in St Louis, Missouri, and their homes from January 9, 2018, to December 20, 2023. Intervention: Community Participation Transition after Stroke (COMPASS), including home modifications and strategy training. Main Outcomes and Measures: The primary outcome was community participation (Reintegration to Normal Living Index). Secondary outcomes were daily activity performance (Stroke Impact Scale ADL domain and the In-Home Occupational Performance Evaluation [I-HOPE] activity, performance, and satisfaction scores) and environmental barriers in the home (I-HOPE environmental barriers score). Results: A total of 185 participants (mean [SD] age, 66.3 [9.0] years; 105 [56.8%] male) were randomized (85 to the COMPASS group and 100 to the control group). The COMPASS and control participants experienced similar improvements in community participation by 12 months, with no significant group (mean difference, 0.3; 95% CI, -4.6 to 5.2; P = .91) or group × time interaction (between-group differences in changes over time, 1.3; 95% CI, -7.1 to 9.6; P = .76) effects. Improvements in I-HOPE performance and satisfaction scores were greater for COMPASS participants than control participants at 12 months (between-group differences in changes for performance: 0.39; 95% CI, 0.01-0.77; P = .046; satisfaction: 0.52; 95% CI, 0.08-0.96; P = .02). The COMPASS participants had greater improvements for I-HOPE environmental barriers than the control participants (P = .003 for interaction), with the largest differences at 6 months (between-group differences in changes: -15.3; 95% CI -24.4 to -6.2). Conclusions and Relevance: In this randomized clinical trial of stroke survivors, participants in both groups experienced improvements in community participation. COMPASS participants had greater improvements in self-rated performance and satisfaction with performing daily activities as well as a greater reduction in environmental barriers than control participants. COMPASS reduced environmental barriers and improved performance of daily activities for stroke survivors as they transitioned from inpatient rehabilitation to home. Trial Registration: ClinicalTrials.gov Identifier: NCT03485820.

Document Type: Article
Publication Stage: Final
Source: Scopus

POLCAM: instant molecular orientation microscopy for the life sciences
(2024) Nature Methods, 21 (10), pp. 1873-1883. 

Bruggeman, E.^a b , Zhang, O.^c , Needham, L.-M.^a d , Körbel, M.^a , Daly, S.^a , Cheetham, M.^a , Peters, R.^e , Wu, T.^c , Klymchenko, A.S.^f , Davis, S.J.^g , Paluch, E.K.^e , Klenerman, D.^a , Lew, M.D.^c , O’Holleran, K.^h , Lee, S.F.^a b

^a Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
^b Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD, United States
^c Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO, United States
^d Department of Chemistry, University of Wisconsin–Madison, Madison, WI, United States
^e Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
^f Laboratoire de Biophotonique et Pharmacologie, Université de Strasbourg, Strasbourg, France
^g MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
^h Cambridge Advanced Imaging Centre, University of Cambridge, Cambridge, United Kingdom

Abstract
Current methods for single-molecule orientation localization microscopy (SMOLM) require optical setups and algorithms that can be prohibitively slow and complex, limiting widespread adoption for biological applications. We present POLCAM, a simplified SMOLM method based on polarized detection using a polarization camera, which can be easily implemented on any wide-field fluorescence microscope. To make polarization cameras compatible with single-molecule detection, we developed theory to minimize field-of-view errors, used simulations to optimize experimental design and developed a fast algorithm based on Stokes parameter estimation that can operate over 1,000-fold faster than the state of the art, enabling near-instant determination of molecular anisotropy. To aid in the adoption of POLCAM, we developed open-source image analysis software and a website detailing hardware installation and software use. To illustrate the potential of POLCAM in the life sciences, we applied our method to study α-synuclein fibrils, the actin cytoskeleton of mammalian cells, fibroblast-like cells and the plasma membrane of live human T cells. © The Author(s) 2024.

Funding details
Aligning Science Across Parkinson’sASAPASAP-000509
Aligning Science Across Parkinson’sASAP
European Research CouncilERC820188-NanoMechShape
European Research CouncilERC

Document Type: Article
Publication Stage: Final
Source: Scopus

Minocycline mitigates sepsis-induced neuroinflammation and promotes recovery in male mice: Insights into neuroprotection and inflammatory modulation
(2024) Physiological Reports, 12 (19), art. no. e70032, . 

Hosseini, M.^a b , Bardaghi, Z.^a c , Askarpour, H.^d , Rajabian, A.^e , Mahmoudabady, M.^b , Shabab, S.^b , Samadi-Noshahr, Z.^f , Salmani, H.^d g

^a Psychiatry and Behavioral Sciences Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
^b Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
^c Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, United States
^d Bioenvironmental Health Hazards Research Center, Jiroft University of Medical Sciences, Jiroft, Iran
^e Neuroscience Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
^f Chabahar Faculty of Medical Sciences, School of Medicine, Iranshahr University of Medical Sciences, Chabahar, Iran
^g Department of Physiology and Pharmacology, Faculty of Medicine, Sabzevar University of Medical Sciences, Mashhad, Iran

Abstract
Sepsis is associated with brain injury and acute brain inflammation, which can potentially transition into chronic inflammation, triggering a cascade of inflammatory responses that may lead to neurological disorders. Minocycline, recognized for its potent anti-inflammatory properties, was investigated in this study for its protective effects against sepsis-induced brain injury. Adult male C57 mice pretreated with minocycline (12.5, 25, and 50 mg/kg) 3 days before sepsis induction. An intraperitoneal injection of 5 mg/kg LPS was used to induce sepsis. Spontaneous locomotor activity (SLA) and weight changes were assessed over several days post-sepsis to monitor the recovery of the mice. The expression of inflammatory mediators and oxidative stress markers was assessed 24 h post sepsis. Septic mice exhibited significant weight loss and impaired SLA. Initially, minocycline did not attenuate the severity of weight loss (1 day) or SLA (4 h post-sepsis), but it significantly accelerated the recovery of the mice in later days. Minocycline dose-dependently mitigated sepsis-induced brain inflammation and oxidative stress. Our findings demonstrate that pretreatment with minocycline has the potential to prevent brain tissue damage and accelerate recovery from sepsis in mice, suggesting that minocycline may serve as a promising therapeutic intervention to protect against sepsis-induced neurological complications. © 2024 The Author(s). Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society.

Author Keywords
brain inflammation;  minocycline;  oxidative stress;  sepsis

Funding details
Jahrom University of Medical SciencesJUMSIR.JMU.AEC.1401.005

Document Type: Article
Publication Stage: Final
Source: Scopus

Gene-Specific Effects on Brain Volume and Cognition of TMEM106B in Frontotemporal Lobar Degeneration
(2024) Neurology, 103 (8), art. no. e209832, . 

Vandebergh, M.^a b , Ramos, E.M.^c , Corriveau-Lecavalier, N.^d e , Ramanan, V.K.^d , Kornak, J.^f , Mester, C.^g , Kolander, T.^d , Brushaber, D.E.^g , Staffaroni, A.M.^h , Geschwind, D.H.ⁱ , Wolf, A.A.^h , Kantarci, K.^d , Gendron, T.^j , Petrucelli, L.^j , Van Den Broeck, M.^a b , Wynants, S.^a b , Baker, M.^j , Borrego-Écija, S.^k , Appleby, B.^l , Barmada, S.^m , Bozoki, A.C.ⁿ , Clark, D.^o , Darby, R.R.^p , Dickerson, B.C.^l , Domoto-Reilly, K.^q , Fields, J.A.^e , Galasko, D.^r , Ghoshal, N.^s , Graff-Radford, N.R.^j , Grant, I.M.^t , Honig, L.S.^u v , Hsiung, G.-Y.R.^w , Huey, E.D.^x , Irwin, D.J.^y , Knopman, D.S.^e , Kwan, J.Y.^z , Léger, G.C.^r , Litvan, I.^r , Masdeu, J.C.^aa , Mendez, M.F.^c , Onyike, C.U.^ab , Pascual, B.^aa , Pressman, P.S.^ac , Ritter, A.^ad , Roberson, E.D.^ae , Snyder, A.^z , Sullivan, A.C.^af , Tartaglia, M.C.^ag , Wint, D.^ad , Heuer, H.W.^ah , Forsberg, L.K.^e , Boxer, A.L.^ah , Rosen, H.J.^ah , Boeve, B.F.^d , Rademakers, R.^a b j

^a The VIB Center for Molecular Neurology, University of Antwerp, Belgium
^b Department of Biomedical Sciences, University of Antwerp, Belgium
^c Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, United States
^d Department of Neurology, Mayo Clinic, Rochester, MN, United States
^e Department of Psychiatry and Psychology, University of California, San Francisco, United States
^f Department of Epidemiology and Biostatistics, University of California, San Francisco, United States
^g Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
^h Department of Neurology, Memory and Aging Center, University of California, San Francisco, Weill Institute for Neurosciences, San Francisco, CA, United States
ⁱ Institute for Precision Health, Departments of Neurology, Psychiatry and Human Genetics, David Geffen School of Medicine, UCLA, United States
^j Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
^k Alzheimer’s Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, Spain
^l Department of Neurology, Case Western Reserve University, Cleveland, OH, United States
^m Department of Neurology, University of Michigan, Ann Arbor, United States
ⁿ Department of Neurology, University of North Carolina, Chapel Hill, United States
^o Department of Neurology, Indiana University, Indianapolis, United States
^p Department of Neurology, Vanderbilt University, Nashville, TN, United States
^q Department of Neurology, University of Washington, Seattle, WA, United States
^r Department of Neurosciences, University of California, La Jolla, San Diego, United States
^s Departments of Neurology and Psychiatry, Washington University School of Medicine, Washington University, St. Louis, MO, United States
^t Department of Psychiatry and Behavioral Sciences, Northwestern Feinberg School of Medicine, Chicago, IL, United States
^u Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, United States
^v Department of Neurology, Columbia University, New York, United States
^w Division of Neurology, University of British Columbia, Vancouver, BC, Canada
^x Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, United States
^y Department of Neurology and Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
^z National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
^aa Department of Neurology, Houston MethodistTX, United States
^ab Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States
^ac Department of Neurology, University of Colorado, Aurora, United States
^ad Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, United States
^ae Department of Neurology, University of Alabama at Birmingham, United States
^af Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, UT Health San Antonio, United States
^ag Tanz Centre for Research in Neurodegenerative Diseases, Division of Neurology, University of TorontoON, Canada
^ah Department of Neurology, Memory and Aging Center, University of California, San Francisco, Weill Institute for Neurosciences, San Francisco, CA, United States

Abstract
Background and Objectives TMEM106B has been proposed as a modifier of disease risk in FTLD-TDP, particularly in GRN pathogenic variant carriers. Furthermore, TMEM106B has been investigated as a disease modifier in the context of healthy aging and across multiple neurodegenerative diseases. The objective of this study was to evaluate and compare the effect of TMEM106B on gray matter volume and cognition in each of the common genetic FTD groups and in patients with sporadic FTD. Methods Participants were enrolled through the ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study, which includes symptomatic and presymptomatic individuals with a pathogenic variant in C9orf72, GRN, MAPT, VCP, TBK1, TARDBP, symptomatic nonpathogenic variant carriers, and noncarrier family controls. All participants were genotyped for the TMEM106B rs1990622 SNP. Cross-sectionally, linear mixed-effects models were fitted to assess an association between TMEM106B and genetic group interaction with each outcome measure (gray matter volume and UDS3-EF for cognition), adjusting for education, age, sex, and CDR+NACC-FTLD sum of boxes. Subsequently, associations between TMEM106B and each outcome measure were investigated within the genetic group. For longitudinal modeling, linear mixed-effects models with time by TMEM106B predictor interactions were fitted. Results The minor allele of TMEM106B rs1990622, linked to a decreased risk of FTD, associated with greater gray matter volume in GRN pathogenic variant carriers under the recessive dosage model (N = 82, beta = 3.25, 95% CI [0.37-6.19], p = 0.034). This was most pronounced in the thalamus in the left hemisphere (beta = 0.03, 95% CI [0.01-0.06], p = 0.006), with a retained association when considering presymptomatic GRN pathogenic variant carriers only (N = 42, beta = 0.03, 95% CI [0.01-0.05], p = 0.003). The minor allele of TMEM106B rs1990622 also associated with greater cognitive scores among all C9orf72 pathogenic variant carriers (N = 229, beta = 0.36, 95% CI [0.05-0.066], p = 0.021) and in presymptomatic C9orf72 pathogenic variant carriers (N = 106, beta = 0.33, 95% CI [0.03-0.63], p = 0.036), under the recessive dosage model. Discussion We identified associations of TMEM106B with gray matter volume and cognition in the presence of GRN and C9orf72 pathogenic variants. The association of TMEM106B with outcomes of interest in presymptomatic GRN and C9orf72 pathogenic variant carriers could additionally reflect TMEM106B’s effect on divergent pathophysiologic changes before the appearance of clinical symptoms. © 2024 American Academy of Neurology.

Document Type: Article
Publication Stage: Final
Source: Scopus

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE)
(2024) Radiology: Artificial Intelligence, 6 (5), art. no. e240076, . Cited 1 time.

Lew, C.O.^a , Calabrese, E.^a , Chen, J.V.^b , Tang, F.^b , Chaudhari, G.^b , Lee, A.^a , Faro, J.^a , Juul, S.^d , Mathur, A.^e , McKinstry, R.C.^f , Wisnowski, J.L.^g , Rauschecker, A.^b , Wu, Y.W.^c , Li, Y.^b

^a Department of Radiology, Duke University Medical Center, 2301 Erwin Rd, Box 3808, Durham, NC 27710, United States
^b Department of Radiology, University of California San Francisco, San Francisco, CA, United States
^c Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
^d Department of Pediatrics, University of Washington, Seattle, WA, United States
^e Department of Pediatrics, Saint Louis University, St Louis, MO, United States
^f Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United States
^g Children’s Hospital Los Angeles, University of Southern California, Los Angeles, CA, United States

Abstract
Purpose: To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical data. Materials and Methods: In this study, MRI data of term neonates with encephalopathy in the High-dose Erythropoietin for Asphyxia and Encephalopathy (HEAL) trial (ClinicalTrials.gov: NCT02811263), who were enrolled from 17 institutions between January 25, 2017, and October 9, 2019, were retrospectively analyzed. The harmonized MRI protocol included T1-weighted, T2-weighted, and diffusion tensor imaging. Deep learning classifiers were trained to predict the primary outcome of the HEAL trial (death or any neurodevelopmental impairment at 2 years) using multisequence MRI and basic clinical variables, including sex and gestational age at birth. Model performance was evaluated on test sets comprising 10% of cases from 15 institutions (in-distribution test set, n = 41) and 10% of cases from two institutions (out-of-distribution test set, n = 41). Model performance in predicting additional secondary outcomes, including death alone, was also assessed. Results: For the 414 neonates (mean gestational age, 39 weeks ± 1.4 [SD]; 232 male, 182 female), in the study cohort, 198 (48%) died or had any neurodevelopmental impairment at 2 years. The deep learning model achieved an area under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.60, 0.86) and 63% accuracy in the in-distribution test set and an AUC of 0.77 (95% CI: 0.63, 0.90) and 78% accuracy in the out-of-distribution test set. Performance was similar or better for predicting secondary outcomes. Conclusion: Deep learning analysis of neonatal brain MRI yielded high performance for predicting 2-year neurodevelopmental outcomes. © RSNA, 2024.

Author Keywords
Brain;  Brain Stem;  Convolutional Neural Network (CNN);  Pediatrics;  Prognosis

Document Type: Article
Publication Stage: Final
Source: Scopus

Protocol to Develop a Core Outcomes Set for Peripheral Nerve Injury
(2024) Journal of Hand Surgery Asian-Pacific Volume, . 

Christopher, J.D.Y.^a , Horowitz, R.S.^a b , Brogan, D.M.^a

^a Department of Orthopaedic Surgery, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Orthopedics, Hadassah Medical Center, Jerusalem, Israel

Abstract
Background: Advances in treatment philosophies and microsurgical techniques for peripheral nerve injuries (PNI) have led to improved outcomes. However, lack of standardisation in the evaluation of clinical outcomes after PNI treatment precludes the ability to compare reconstruction methods, such as nerve transfer, nerve grafting, free functioning muscle transfers and tendon transfers. To this end, our goal is to work collaboratively to establish a core outcome set to evaluate outcomes after PNI. Methods: The protocol for this arc of work, delineated in this manuscript, consists of two phases: (1) conducting a systematic review of how outcomes are currently reported following PNI and (2) a Delphi process to gain consensus on the measures to include in the core outcome set for PNI. In the Delphi process, two online rounds will be used to gather consensus on the importance of each outcome measure. A final round will be conducted in person to discuss and resolve measures for which there is not yet consensus and to finalise the core outcomes set. Conclusions: Through this process, a common standard for reporting outcomes after PNI will be created, facilitating collaboration and future research. © 2024 World Scientific. All rights reserved.

Author Keywords
Delphi;  Nerve injury;  Nerve reconstruction;  Nerve repair;  Outcomes

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

Identifying Gaps and Barriers in Alzheimer’s Disease and Related Dementia Research and Management in Low- and Middle-Income Countries: A Survey of Health Professionals and Researchers
(2024) Journal of Alzheimer’s Disease: JAD, 101 (4), pp. 1307-1320. 

Babulal, G.M.^a b c d , Zha, W.^a , Trani, J.-F.^b c e , Guerra, J.L.^a , Tee, B.L.^f g , Zhu, Y.^h , Chen, Y.ⁱ , Chen, L.^j , Bubu, M.^k , Josephy-Hernandez, S.^l , Wandera, S.^m , Karanja, W.ⁿ , Ellajosyula, R.^o , Caramelli, P.^p , Diversity and Disparity Professional Interest Area, Low-and-Middle-Income Working Group^q

^a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^b Institute of Public Health, Washington University, St. Louis, MO, United States
^c Centre for Social Development in Africa, Faculty of Humanities, University of Johannesburg, Cnr Kingsway & University Roads ,Auckland Park, Johannesburg, South Africa
^d Department of Clinical Research and Leadership, George Washington University School of Medicine and Health SciencesWA, United States
^e National Conservatory of Arts and Crafts, Paris, France
^f Global Brain Health Institute, University of California, San Francisco, CA, United States
^g Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, United States
^h School of Social Work, Adelphi University, Garden City, NY, United States
ⁱ Department of Geriatrics, Univ Lille, Lille Neurosciences & Cognition, Degenerative and Vascular Cognitive Disorders, CHU Lille, Lille, UMR-S1172, France
^j Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
^k Departments of Psychiatry, Neurology, and Population Health, NYU Grossman School of Medicine, New York, NY, USA
^l Department of Neurology, Hospital México, Caja Costarricense de Seguro Social, Torre A – Centro Corporativo InternacionalSan José, Costa Rica
^m Department of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda
ⁿ AKU Brain & Mind Institute, Nairobi, Kenya
^o Cognitive Neurology Clinic, Manipal Hospital & Annasawmy Mudaliar Hospital, Bangalore, India
^p Behavioral and Cognitive Neurology Unit, Faculdade de Medicina, Universidade Federal de Minas Gerais, MG, Belo Horizonte, Brazil

Abstract
Background: The significant increase in Alzheimer’s disease and related dementia prevalence is a global health crisis, acutely impacting low- and lower-middle and upper-middle-income countries (LLMICs/UMICs). Objective: The objective of this study is to identify key barriers and gaps in dementia care and research in LLMICs and UMICs. Methods: We conducted an international, cross-sectional survey among clinicians and healthcare professionals (n = 249 in 34 countries) across LLMICs and UMICs, exploring patient demographics, use of clinical diagnosis, dementia evaluation, screening/evaluation tools, and care and treatment. Results: Significant disparities were found in diagnostic practices, access to assessments, and access to care. On average, clinicians in LLMICs saw more patients, had less time for evaluations, lower use of formal screening and tools, and less access to biomarkers. They were also under-resourced compared to UMICs. Conclusions: The findings provide insights for policymakers, healthcare organizations, and researchers to address the complex challenges associated with dementia care in diverse settings. Addressing these challenges requires a multipronged approach involving local, national, and international stakeholders.

Author Keywords
Alzheimer’s disease;  dementia;  disparity;  low and middle-income countries;  resources;  underserved

Document Type: Article
Publication Stage: Final
Source: Scopus

Dysfunctional Alpha Modulation as a Mechanism of Working Memory Impairment in Serious Mental Illness
(2024) Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, . 

Erickson, M.A.^a , Boudewyn, M.A.^b , Winsler, K.^c , Li, C.^a , Barch, D.M.^d , Carter, C.S.^e , Frank, M.J.^f , Gold, J.M.^g , MacDonald, A.W., III^h , Ragland, J.D.^e , Silverstein, S.M.ⁱ , Yonelinas, A.^c , Luck, S.J.^c

^a Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Chicago, Illinois, United States
^b Department of Psychology, University of California, Santa Cruz, California, United States
^c Center for Mind & Brain, University of California, Davis, Davis, California, United States
^d Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, United States
^e Department of Psychiatry, University of California Davis School of Medicine, Davis, California, United States
^f Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, Rhode Island, United States
^g Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Catonsville, MD, United States
^h Department of Psychology, University of Minnesota, Minneapolis, MN, United States
ⁱ Department of Psychiatry, University of Rochester Medical Center, Rochester, New York, United States

Abstract
Background: People with psychosis and mood disorders experience disruptions in working memory; however, the underlying mechanism remains unknown. We focused on 2 potential mechanisms: first, poor attentional engagement should be associated with elevated levels of prestimulus alpha-band activity within the electroencephalogram (EEG), whereas impaired working memory encoding should be associated with reduced poststimulus alpha suppression. Methods: We collected EEG data from 68 people with schizophrenia, 43 people with bipolar disorder with a history of psychosis, 53 people with major depressive disorder, and 90 healthy comparison subjects while they completed a spatial working memory task. We quantified attention lapsing, memory precision, and memory capacity from the behavioral responses, and we quantified alpha using traditional wavelet analysis as well as a novel approach for isolating oscillatory alpha power from aperiodic elements of the EEG signal. Results: We found that 1) greater prestimulus alpha power estimated using traditional wavelet analysis predicted behavioral errors; 2) poststimulus alpha suppression was reduced in the patient groups; and 3) reduced suppression was associated with a lower likelihood of memory storage. However, we also observed that the prestimulus alpha was larger among healthy control participants than patients, and single-trial analyses showed that it was the aperiodic elements of the prestimulus EEG—not oscillatory alpha—that predicted behavioral errors. Discussion: These results suggest that working memory impairments in serious mental illness primarily reflect an impairment in the poststimulus encoding processes rather than reduced attentional engagement prior to stimulus onset. © 2024 Society of Biological Psychiatry

Author Keywords
Alpha;  Attention;  Electroencephalogram (EEG);  Mood disorders;  Schizophrenia;  Working memory

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

Head-to-head comparison of leading blood tests for Alzheimer’s disease pathology
(2024) Alzheimer’s and Dementia, . 

Schindler, S.E.^a , Petersen, K.K.^a , Saef, B.^a , Tosun, D.^b , Shaw, L.M.^c , Zetterberg, H.^{d e f g h i} , Dage, J.L.^j k , Ferber, K.^l , Triana-Baltzer, G.^m , Du-Cuny, L.ⁿ , Li, Y.^a , Coomaraswamy, J.^o , Baratta, M.^o , Mordashova, Y.ⁿ , Saad, Z.S.^m , Raunig, D.L.^o , Ashton, N.J.^d p q , Meyers, E.A.^r , Rubel, C.E.^l , Rosenbaugh, E.G.^s , Bannon, A.W.^t , Potter, W.Z.^u , Alzheimer’s Disease Neuroimaging Initiative (ADNI) Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium Plasma Abeta and Phosphorylated Tau as Predictors of Amyloid and Tau Positivity in Alzheimer’s Disease Project Team^v

^a Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
^c Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^d Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
^e Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
^f UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, United Kingdom
^g Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
^h Hong Kong Center for Neurodegenerative Diseases, Hong Kong
ⁱ Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
^j Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
^k Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, United States
^l Biogen, Biomarkers Group, Cambridge, MA, United States
^m Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, CA, United States
ⁿ AbbVie, Rheinland-Pfalz, Ludwigshafen am Rhein, Germany
^o Takeda Pharmaceutical Company Ltd., Cambridge, MA, United States
^p Banner Alzheimer’s Institute, Phoenix, AZ, United States
^q Banner Sun Health Research Institute, Sun City, AZ, United States
^r Alzheimer’s Association, Chicago, IL, United States
^s The Foundation for the National Institutes of Health, North Bethesda, MD, United States
^t AbbVie, North Chicago, IL, United States
^u Highly qualified expert, Philadelphia, PA, United States

Abstract
INTRODUCTION: Blood tests have the potential to improve the accuracy of Alzheimer’s disease (AD) clinical diagnosis, which will enable greater access to AD-specific treatments. This study compared leading commercial blood tests for amyloid pathology and other AD-related outcomes. METHODS: Plasma samples from the Alzheimer’s Disease Neuroimaging Initiative were assayed with AD blood tests from C2N Diagnostics, Fujirebio Diagnostics, ALZPath, Janssen, Roche Diagnostics, and Quanterix. Outcomes measures were amyloid positron emission tomography (PET), tau PET, cortical thickness, and dementia severity. Logistic regression models assessed the classification accuracies of individual or combined plasma biomarkers for binarized outcomes, and Spearman correlations evaluated continuous relationships between individual plasma biomarkers and continuous outcomes. RESULTS: Measures of plasma p-tau217, either individually or in combination with other plasma biomarkers, had the strongest relationships with all AD outcomes. DISCUSSION: This study identified the plasma biomarker analytes and assays that most accurately classified amyloid pathology and other AD-related outcomes. Highlights: Plasma p-tau217 measures most accurately classified amyloid and tau status. Plasma Aβ42/Aβ40 had relatively low accuracy in classification of amyloid status. Plasma p-tau217 measures had higher correlations with cortical thickness than NfL. Correlations of plasma biomarkers with dementia symptoms were relatively low. © 2024 The Author(s). Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Author Keywords
A/T/N;  amyloid;  biomarkers;  blood;  glial fibrillary acidic protein;  neurofilament light;  p-tau;  plasma;  tau

Funding details
National Institute on AgingNIA
University of Pennsylvania

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

Outcomes of early-treated infants with spinal muscular atrophy: A multicenter, retrospective cohort study
(2024) Muscle and Nerve, . 

Goedeker, N.L.^a , Rogers, A.^b , Fisher, M.^c , Arya, K.^d , Brandsema, J.F.^e , Farah, H.^e , Farrar, M.A.^f , Felker, M.V.^g , Gibbons, M.^h , Hamid, O.A.ⁱ , Harmelink, M.^j , Herbert, K.^f , Kichula, E.^e , King, K.^k , Lakhotia, A.^b , Lee, B.H.^l , Kuntz, N.L.^k , Parsons, J.^h , Rehborg, R.^j , Veerapaniyan, A.^d , Zaidman, C.M.^a

^a Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^b Department of Pediatrics, Norton Children’s Medical Group, University of Louisville, Louisville, KY, United States
^c Department of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, United States
^d Department of Pediatrics, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital, Little Rock, AR, United States
^e Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^f Sydney Children’s Hospital Network and Discipline of Paediatrics and Child Health, School of Clinical Medicine, UNSW Medicine, UNSW Sydney, Sydney, NSW, Australia
^g Division of Pediatric Neurology, Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
^h Department of Pediatrics Children’s Hospital Colorado, University of Colorado School of Medicine, Aurora, CO, United States
ⁱ Department of Pediatrics, Nemours Children’s Health, Orlando, FL, United States
^j Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
^k Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^l Department of Neurology, University of Rochester, Rochester, NY, United States

Abstract
Introduction/Aims: While prompt identification and treatment of infants with spinal muscular atrophy (SMA) can ameliorate outcomes, variability persists. This study assessed management and outcomes of early-treated infants with SMA. Methods: We analyzed retrospective data at 12 centers on infants with SMA treated at age ≤6 weeks from August 2018 to December 2023. Results: Sixty-six patients, 35 with two SMN2 copies and 31 with ≥3 SMN2 copies, were included. Twenty-five (38%, 22 with two SMN2 copies), had SMA findings before initial treatment which was onasemnogene abeparvovec in 47 (71%) and nusinersen in 19 (29%). Thirty-two received sequential or combination treatments, including 16 adding nusinersen or risdiplam due to SMA findings following onasemnogene abeparvovec. All sat independently. Compared to children with ≥3 SMN2 copies, those with two SMN2 copies were less likely to walk (23/34 [68%] vs. 31/31 [100%], p <.001) and less likely to walk on time (9/34 [26%] vs. 29/31 [94%], p <.001); one non-ambulatory child was <18 months old and was excluded from this analysis. No patients required permanent ventilation or exclusively enteral nutrition; six required nocturnal non-invasive ventilation and four utilized supplemental enteral nutrition, all with two SMN2 copies. Discussion: Early treatment of infants with SMA can improve outcomes as indicated by our cohort, all of whom sat independently and are without permanent ventilation. However, our study demonstrates ongoing disability in most children with two SMN2 copies despite early monotherapy and emphasizes the need for additional research, including earlier monotherapy, initial combination therapy, prenatal treatment, and non-SMN modifying treatments. © 2024 Wiley Periodicals LLC.

Author Keywords
CHOP INTEND;  newborn screening;  nusinersen;  onasemnogene abeparvovec;  spinal muscular atrophy

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