Publications

Hope Center Member Publications

Scopus list of publications for September 17, 2023

Spinal Cord Injury and Assays for Regeneration” (2024) Methods in Molecular Biology (Clifton, N.J.)

Spinal Cord Injury and Assays for Regeneration
(2024) Methods in Molecular Biology (Clifton, N.J.), 2707, pp. 215-222. 

Burris, B.a , Mokalled, M.H.b

a Department of Developmental Biology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
b Center of Regenerative Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

Abstract
Due to their renowned regenerative capacity, adult zebrafish are a premier vertebrate model to interrogate mechanisms of innate spinal cord regeneration. Following complete transection to their spinal cord, zebrafish extend glial and axonal bridges across severed tissue, regenerate neurons proximal to the lesion, and regain swim capacity within 8 weeks of injury. Here, we describe methods to perform complete spinal cord transections and to assess functional and cellular recovery during regeneration. For spinal cord injury, a complete transection is performed 4 mm caudal to the brainstem. Swim endurance is quantified as a central readout of functional spinal cord repair. For swim endurance, zebrafish are subjected to a constantly increasing water current velocity until exhaustion, and time at exhaustion is reported. To assess cellular regeneration, histological examination is performed to analyze the extents of glial and axonal bridging across the lesion. © 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Axon tracing;  Axonal bridging quantification;  Glial bridging quantification;  Spinal cord histology;  Spinal cord injury;  Swim endurance assay

Document Type: Article
Publication Stage: Final
Source: Scopus

Phase separation of protein mixtures is driven by the interplay of homotypic and heterotypic interactions” (2023) Nature Communications

Phase separation of protein mixtures is driven by the interplay of homotypic and heterotypic interactions
(2023) Nature Communications, 14 (1), art. no. 5527, . 

Farag, M.a , Borcherds, W.M.b , Bremer, A.b , Mittag, T.b , Pappu, R.V.a

a Department of Biomedical Engineering and Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO 63130, United States
b Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, United States

Abstract
Prion-like low-complexity domains (PLCDs) are involved in the formation and regulation of distinct biomolecular condensates that form via phase separation coupled to percolation. Intracellular condensates often encompass numerous distinct proteins with PLCDs. Here, we combine simulations and experiments to study mixtures of PLCDs from two RNA-binding proteins, hnRNPA1 and FUS. Using simulations and experiments, we find that 1:1 mixtures of A1-LCD and FUS-LCD undergo phase separation more readily than either of the PLCDs on their own due to complementary electrostatic interactions. Tie line analysis reveals that stoichiometric ratios of different components and their sequence-encoded interactions contribute jointly to the driving forces for condensate formation. Simulations also show that the spatial organization of PLCDs within condensates is governed by relative strengths of homotypic versus heterotypic interactions. We uncover rules for how interaction strengths and sequence lengths modulate conformational preferences of molecules at interfaces of condensates formed by mixtures of proteins. © 2023, Springer Nature Limited.

Funding details
National Institutes of HealthNIHR01NS121114
Air Force Office of Scientific ResearchAFOSRFA9550-20-1-0241

Document Type: Article
Publication Stage: Final
Source: Scopus

Cross-talk between B cells, microglia and macrophages, and implications to central nervous system compartmentalized inflammation and progressive multiple sclerosis” (2023) eBioMedicine

Cross-talk between B cells, microglia and macrophages, and implications to central nervous system compartmentalized inflammation and progressive multiple sclerosis
(2023) eBioMedicine, 96, art. no. 104789, . 

Touil, H.a , Li, R.a , Zuroff, L.a , Moore, C.S.b , Healy, L.c , Cignarella, F.d , Piccio, L.e , Ludwin, S.f , Prat, A.g , Gommerman, J.h , Bennett, F.C.i , Jacobs, D.a , Benjamins, J.A.j , Lisak, R.P.j , Antel, J.P.c , Bar-Or, A.a

a Department of Neurology and Center for Neuroinflammation and Experimental Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
b Division of BioMedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
c Neuroimmunology Unit, Montréal Neurological Institute, McGill University, Canada
d Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, St Louis, MO, United States
e Charles Perkins Centre and School of Medical Sciences, The University of Sydney, Camperdown, NSW, Australia
f Department of Pathology and Molecular Medicine, Queen’s University, Kingston, ON K7L 3N6, Canada
g Université de Montréal Centre de Recherche du CHUM (CRCHUM) and Department of Neuroscience, Université de Montréal, 900 Saint Denis Street, Montréal, QC H2X 0A9, Canada
h Department of Immunology, University of Toronto, Toronto, ON M5S 1A8, Canada
i Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
j Departments of Neurology and Biochemistry, Immunology and Microbiology, Wayne State University School of Medicine, Detroit, MI, United States

Abstract
Background: B cells can be enriched within meningeal immune-cell aggregates of multiple sclerosis (MS) patients, adjacent to subpial cortical demyelinating lesions now recognized as important contributors to progressive disease. This subpial demyelination is notable for a ‘surface-in’ gradient of neuronal loss and microglial activation, potentially reflecting the effects of soluble factors secreted into the CSF. We previously demonstrated that MS B-cell secreted products are toxic to oligodendrocytes and neurons. The potential for B-cell–myeloid cell interactions to propagate progressive MS is of considerable interest. Methods: Secreted products of MS-implicated pro-inflammatory effector B cells or IL-10-expressing B cells with regulatory potential were applied to human brain-derived microglia or monocyte-derived macrophages, with subsequent assessment of myeloid phenotype and function through measurement of their expression of pro-inflammatory, anti-inflammatory and homeostatic/quiescent molecules, and phagocytosis (using flow cytometry, ELISA and fluorescently-labeled myelin). Effects of secreted products of differentially activated microglia on B-cell survival and activation were further studied. Findings: Secreted products of MS-implicated pro-inflammatory B cells (but not IL-10 expressing B cells) substantially induce pro-inflammatory cytokine (IL-12, IL-6, TNFα) expression by both human microglia and macrophage (in a GM-CSF dependent manner), while down-regulating their expression of IL-10 and of quiescence-associated molecules, and suppressing their myelin phagocytosis. In contrast, secreted products of IL-10 expressing B cells upregulate both human microglia and macrophage expression of quiescence-associated molecules and enhance their myelin phagocytosis. Secreted factors from pro-inflammatory microglia enhance B-cell activation. Interpretation: Potential cross-talk between disease-relevant human B-cell subsets and both resident CNS microglia and infiltrating macrophages may propagate CNS-compartmentalized inflammation and injury associated with MS disease progression. These interaction represents an attractive therapeutic target for agents such as Bruton’s tyrosine kinase inhibitors (BTKi) that modulate responses of both B cells and myeloid cells. Funding: Stated in Acknowledgments section of manuscript. © 2023 The Author(s)

Author Keywords
CNS-compartmentalized inflammation;  Human B cells;  Human macrophage;  Human microglia;  Multiple sclerosis

Funding details
National Institutes of HealthNIHAG058501, R21NS118227

Document Type: Article
Publication Stage: Final
Source: Scopus

Differential impacts of road diets on driving behavior among older adults with and without preclinical Alzheimer’s pathology” (2023) Transportation Research Part F: Traffic Psychology and Behaviour

Differential impacts of road diets on driving behavior among older adults with and without preclinical Alzheimer’s pathology
(2023) Transportation Research Part F: Traffic Psychology and Behaviour, 98, pp. 18-28. 

Wisch, J.K.a , Kianfar, J.b , Carr, D.B.a c , Dickerson, A.D.d , Vivoda, J.e , Harmon, A.c , Trani, J.F.f , Johnson, A.M.g , Doherty, J.M.a , Murphy, S.A.a , Domash, H.a , Ashraf, S.a , Aschenbrenner, A.J.a , Schindler, S.E.a h , Benzinger, T.L.S.h i , Morris, J.C.a h , Ances, B.M.a h , Babulal, G.M.a j k

a Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, United States
b Department of Civil Engineering, St. Louis University, St. Louis, MO 63110, United States
c Department of Medicine, Geriatrics and Nutritional Science, Washington University in St. Louis, St. Louis, MO 63110, United States
d Department of Occupational Therapy, East Carolina University, Greenville, NC 27858, United States
e Department of Sociology and Gerontology, Miami University, Oxford, OH 45056, United States
f Brown School of Social Work, Washington University in St. Louis, St. Louis, MO 63110, United States
g Center for Clinical Studies, Washington University in St. Louis, St. Louis, MO 63110, United States
h Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, United States
i Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, United States
j Department of Clinical Research and Leadership, The George Washington University School of Medicine and Health Sciences, Washington, DC, United States
k Department of Psychology, Faculty of Humanities, University of Johannesburg, South Africa

Abstract
The driving populace of the United States is aging. The prevalence of Alzheimer disease (AD) will increase in the coming decades. Road diets (that is, the reallocation of one or more lanes of car traffic to other uses) have been proposed as a modification to increase pedestrian safety, particularly for older adults. In contrast, we considered the impacts of road diets on aging drivers, and on those with early pathological accumulation of AD. We observed naturalistic driving data for 60 cognitively normal older drivers (Age Range = 62–87 years, Median = 75 years) driving across three road segments located in the St. Louis metropolitan area, Missouri, United States. We used neuroimaging and lumbar puncture derived biomarker data to determine which of the drivers had preclinical AD. Since previous AD studies identified a variety of changes in driving behavior among older drivers with preclinical AD, we examined driving speed before and after lane repurposing. We found that drivers with preclinical AD drove at lower speeds compared to those without preclinical AD prior to road diet implementation. After lanes were repurposed, there was no statistical difference in the speed between older drivers with and without preclinical AD. We evaluated cognitive performance and found that attentional control had a mediating effect on driver speed, suggesting that an individual’s ability to focus on a specific task and filter out distractions was associated with faster driving. Driving speed after lane repurposing is not mediated by attentional control, suggesting that road diets are impervious to individual driver capacity. We conclude that lane repurposing has potential as an important mobility infrastructure solution that could enhance older driver safety and facilitate aging in place. © 2023 Elsevier Ltd

Author Keywords
Aging;  Alzheimer disease;  Biomarkers;  Naturalistic driving;  Older adults;  Policy;  Road diets

Funding details
National Institutes of HealthNIHP01AG003991, P01AG026276, P30AG0066444, R01AG067428, R01AG068183, R01AG074302, R01NR012657, R01NR012907, R01NR014449, U19 AG024904, U19 AG032438
Foundation for Barnes-Jewish HospitalFBJH
Institute of Clinical and Translational SciencesICTSUL1 TR000448
Hope Center for Neurological Disorders

Document Type: Article
Publication Stage: Final
Source: Scopus

Tangent functional connectomes uncover more unique phenotypic traits” (2023) iScience

Tangent functional connectomes uncover more unique phenotypic traits
(2023) iScience, 26 (9), art. no. 107624, . 

Abbas, K.a b , Liu, M.a b , Wang, M.a b , Duong-Tran, D.c d , Tipnis, U.e , Amico, E.f g , Kaplan, A.D.e , Dzemidzic, M.h , Kareken, D.h , Ances, B.M.i , Harezlak, J.j , Goñi, J.a b k

a Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, United States
b School of Industrial Engineering, Purdue University, West Lafayette, IN, United States
c Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
d Department of Mathematics, United States Naval Academy, Annapolis, MD, United States
e Lawrence Livermore National Laboratory, Livermore, CA, United States
f Institute of Bioengineering, Center for Neuroprosthetics, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
g Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
h Department of Neurology, Indiana University School of Medicine, Indiana Alcohol Research Center, Indianapolis, IN, United States
i Department of Neurology, Washington University in Saint Louis, School of Medicine, St Louis, MO, United States
j Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, United States
k Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States

Abstract
Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projections, resulting into tangent-FCs. Tangent-FCs have led to more accurate models predicting brain conditions or aging. Motivated by the fact that tangent-FCs seem to be better biomarkers than FCs, we hypothesized that tangent-FCs have also a higher fingerprint. We explored the effects of six factors: fMRI condition, scan length, parcellation granularity, reference matrix, main-diagonal regularization, and distance metric. Our results showed that identification rates are systematically higher when using tangent-FCs across the “fingerprint gradient” (here including test-retest, monozygotic and dizygotic twins). Highest identification rates were achieved when minimally (0.01) regularizing FCs while performing tangent space projection using Riemann reference matrix and using correlation distance to compare the resulting tangent-FCs. Such configuration was validated in a second dataset (resting-state). © 2023 The Author(s)

Author Keywords
Biological sciences;  Phenotyping

Funding details
National Institutes of HealthNIHCTSI CTR EPAR2169, R01 AA029607, R21 AA029614
McDonnell Center for Systems Neuroscience
Indiana Alcohol Research CenterIARCP60AA07611
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungSNFPZ00P2_185716, R01 DA054009, R01 MH118031, R01 NR0112657, R01 NR012907, R01 NR014449, R01 NR015738

Document Type: Article
Publication Stage: Final
Source: Scopus

Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults” (2023) JAMA Neurology

Associations of Sex, Race, and Apolipoprotein E Alleles With Multiple Domains of Cognition Among Older Adults
(2023) JAMA Neurology, 80 (9), pp. 929-939. 

Walters, S.a b , Contreras, A.G.a b , Eissman, J.M.a b , Mukherjee, S.c , Lee, M.L.c , Choi, S.-E.c , Scollard, P.c , Trittschuh, E.H.d e , Mez, J.B.f , Bush, W.S.g , Kunkle, B.W.h , Naj, A.C.i j , Peterson, A.a , Gifford, K.A.a , Cuccaro, M.L.h , Cruchaga, C.k l , Pericak-Vance, M.A.h , Farrer, L.A.f m n , Wang, L.-S.j , Haines, J.L.g , Jefferson, A.L.a , Kukull, W.A.o , Keene, C.D.p , Saykin, A.J.q r , Thompson, P.M.s , Martin, E.R.h , Bennett, D.A.t , Barnes, L.L.t , Schneider, J.A.t , Crane, P.K.c , Hohman, T.J.a b , Dumitrescu, L.a b , Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Genetics Consortium, and Alzheimer’s Disease Sequencing Projectu

a Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, United States
b Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, United States
c Department of Medicine, University of Washington, Seattle, United States
d Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, United States
e Geriatric Research Education and Clinical Center (GRECC), VA Puget Sound Health Care System, Seattle, WA, United States
f Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
g Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
h John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, Puerto Rico
i Department of Biostatistics, Epidemiology, Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
j Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
k Department of Psychiatry, Washington University School of Medicine, St Louis, MO, United States
l NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, United States
m Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
n Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, United States
o Department of Epidemiology, School of Public Health, University of Washington, Seattle, United States
p Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States
q Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis, United States
r Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, United States
s Keck School of Medicine, University of Southern California, Los Angeles, Mexico
t Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States

Abstract
Importance: Sex differences are established in associations between apolipoprotein E (APOE) ε4 and cognitive impairment in Alzheimer disease (AD). However, it is unclear whether sex-specific cognitive consequences of APOE are consistent across races and extend to the APOE ε2 allele. Objective: To investigate whether sex and race modify APOE ε4 and ε2 associations with cognition. Design, Setting, and Participants: This genetic association study included longitudinal cognitive data from 4 AD and cognitive aging cohorts. Participants were older than 60 years and self-identified as non-Hispanic White or non-Hispanic Black (hereafter, White and Black). Data were previously collected across multiple US locations from 1994 to 2018. Secondary analyses began December 2021 and ended September 2022. Main Outcomes and Measures: Harmonized composite scores for memory, executive function, and language were generated using psychometric approaches. Linear regression assessed interactions between APOE ε4 or APOE ε2 and sex on baseline cognitive scores, while linear mixed-effect models assessed interactions on cognitive trajectories. The intersectional effect of race was modeled using an APOE × sex × race interaction term, assessing whether APOE × sex interactions differed by race. Models were adjusted for age at baseline and corrected for multiple comparisons. Results: Of 32 427 participants who met inclusion criteria, there were 19 007 females (59%), 4453 Black individuals (14%), and 27 974 White individuals (86%); the mean (SD) age at baseline was 74 years (7.9). At baseline, 6048 individuals (19%) had AD, 4398 (14%) were APOE ε2 carriers, and 12 538 (38%) were APOE ε4 carriers. Participants missing APOE status were excluded (n = 9266). For APOE ε4, a robust sex interaction was observed on baseline memory (β = -0.071, SE = 0.014; P = 9.6 × 10-7), whereby the APOE ε4 negative effect was stronger in females compared with males and did not significantly differ among races. Contrastingly, despite the large sample size, no APOE ε2 × sex interactions on cognition were observed among all participants. When testing for intersectional effects of sex, APOE ε2, and race, an interaction was revealed on baseline executive function among individuals who were cognitively unimpaired (β = -0.165, SE = 0.066; P = .01), whereby the APOE ε2 protective effect was female-specific among White individuals but male-specific among Black individuals. Conclusions and Relevance: In this study, while race did not modify sex differences in APOE ε4, the APOE ε2 protective effect could vary by race and sex. Although female sex enhanced ε4-associated risk, there was no comparable sex difference in ε2, suggesting biological pathways underlying ε4-associated risk are distinct from ε2 and likely intersect with age-related changes in sex biology.

Document Type: Article
Publication Stage: Final
Source: Scopus

Cognitive deficits and altered functional brain network organization in pediatric brain tumor patients
(2023) Brain Imaging and Behavior

Cognitive deficits and altered functional brain network organization in pediatric brain tumor patients
(2023) Brain Imaging and Behavior, . 

Seitzman, B.A.a , Anandarajah, H.b , Dworetsky, A.c , McMichael, A.d , Coalson, R.S.c d , Agamah, A.M.a , Jiang, C.e , Gu, H.f , Barbour, D.L.e g , Schlaggar, B.L.d h i j , Limbrick, D.D.k , Rubin, J.B.b g , Shimony, J.S.c , Perkins, S.M.a

a Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO, United States
b Department of Pediatrics, St. Louis Children’s Hospital, Washington University School of Medicine, St. Louis, MO, United States
c Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
d Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
e Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, United States
f Department of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States
g Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
h Kennedy Krieger Institute, Baltimore, MD, United States
i Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
j Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, United States
k Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Survivors of pediatric brain tumors experience significant cognitive deficits from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Resting state functional magnetic resonance imaging allows for the study of the spontaneous fluctuations in bulk neural activity, providing insight into brain organization and function. Here, we evaluated cognitive performance and functional network architecture in pediatric brain tumor patients. Forty-nine patients (7–18 years old) with a primary brain tumor diagnosis underwent resting state imaging during regularly scheduled clinical visits. All patients were tested with a battery of cognitive assessments. Extant data from 139 typically developing children were used as controls. We found that obtaining high-quality imaging data during routine clinical scanning was feasible. Functional network organization was significantly altered in patients, with the largest disruptions observed in patients who received propofol sedation. Awake patients demonstrated significant decreases in association network segregation compared to controls. Interestingly, there was no difference in the segregation of sensorimotor networks. With a median follow-up of 3.1 years, patients demonstrated cognitive deficits in multiple domains of executive function. Finally, there was a weak correlation between decreased default mode network segregation and poor picture vocabulary score. Future work with longer follow-up, longitudinal analyses, and a larger cohort will provide further insight into this potential predictor. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Brain networks;  Cognition;  Pediatric brain tumor

Funding details
National Institutes of HealthNIHU54 HD087011
University of WashingtonUW
Children’s Discovery InstituteCDI
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD

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

Toggling between food-seeking and self-preservation behaviors via hypothalamic response networks” (2023) Neuron

Toggling between food-seeking and self-preservation behaviors via hypothalamic response networks
(2023) Neuron, . 

de Araujo Salgado, I.a , Li, C.a , Burnett, C.J.a , Rodriguez Gonzalez, S.a , Becker, J.J.a , Horvath, A.a , Earnest, T.b , Kravitz, A.V.b , Krashes, M.J.a c

a Diabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, United States
b Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, United States
c National Institute on Drug Abuse (NIDA), National Institutes of Health, Baltimore, MD 21224, United States

Abstract
Motivated behaviors are often studied in isolation to assess labeled lines of neural connections underlying innate actions. However, in nature, multiple systems compete for expression of goal-directed behaviors via complex neural networks. Here, we examined flexible survival decisions in animals tasked with food seeking under predation threat. We found that predator exposure rapidly induced physiological, neuronal, and behavioral adaptations in mice highlighted by reduced food seeking and consumption contingent on current threat level. Diminishing conflict via internal state or external environment perturbations shifted feeding strategies. Predator introduction and/or selective manipulation of danger-responsive cholecystokinin (Cck) cells of the dorsal premammilary nucleus (PMd) suppressed hunger-sensitive Agouti-related peptide (AgRP) neurons, providing a mechanism for threat-evoked hypophagia. Increased caloric need enhanced food seeking under duress through AgRP pathways to the bed nucleus of the stria terminalis (BNST) and/or lateral hypothalamus (LH). Our results suggest oscillating interactions between systems underlying self-preservation and food seeking to promote optimal behavior. © 2023

Author Keywords
calcium imaging;  cell-specific perturbation;  chemogenetics;  choice;  conflict behavior;  feeding;  foraging;  in vivo neural activity recordings;  optogenetics;  self-preservation

Funding details
National Institutes of HealthNIH
National Heart, Lung, and Blood InstituteNHLBI
National Institute of Diabetes and Digestive and Kidney DiseasesNIDDKDK075087-06, DK075088
Diabetes Research Center, University of WashingtonDRC, UW
Nutrition Obesity Research Center, University of North CarolinaNORC
Noor Ophthalmology Research CenterNORC

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

Identifying individuals with non-Alzheimer’s disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer’s disease” (2023) Alzheimer’s and Dementia

Identifying individuals with non-Alzheimer’s disease co-pathologies: A precision medicine approach to clinical trials in sporadic Alzheimer’s disease
(2023) Alzheimer’s and Dementia, . 

Tosun, D.a , Yardibi, O.b , Benzinger, T.L.S.c , Kukull, W.A.d , Masters, C.L.e , Perrin, R.J.f g , Weiner, M.W.a , Simen, A.b , Schwarz, A.J.b

a Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States
b Takeda Pharmaceutical Company Ltd, Cambridge, MA, United States
c Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
d Department of Epidemiology, National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA, United States
e The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
f Department of Pathology & Immunology, Washington University in St. Louis, St. Louis, MO, United States
g Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States

Abstract
INTRODUCTION: Biomarkers remain mostly unavailable for non-Alzheimer’s disease neuropathological changes (non-ADNC) such as transactive response DNA-binding protein 43 (TDP-43) proteinopathy, Lewy body disease (LBD), and cerebral amyloid angiopathy (CAA). METHODS: A multilabel non-ADNC classifier using magnetic resonance imaging (MRI) signatures was developed for TDP-43, LBD, and CAA in an autopsy-confirmed cohort (N = 214). RESULTS: A model using demographic, genetic, clinical, MRI, and ADNC variables (amyloid positive [Aβ+] and tau+) in autopsy-confirmed participants showed accuracies of 84% for TDP-43, 81% for LBD, and 81% to 93% for CAA, outperforming reference models without MRI and ADNC biomarkers. In an ADNI cohort (296 cognitively unimpaired, 401 mild cognitive impairment, 188 dementia), Aβ and tau explained 33% to 43% of variance in cognitive decline; imputed non-ADNC explained an additional 16% to 26%. Accounting for non-ADNC decreased the required sample size to detect a 30% effect on cognitive decline by up to 28%. DISCUSSION: Our results lead to a better understanding of the factors that influence cognitive decline and may lead to improvements in AD clinical trial design. © 2023 The Authors. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Author Keywords
Alzheimer’s disease;  CAA;  Lewy body;  TDP-43

Funding details
National Institutes of HealthNIHAG047366, P01 AG003991, P30 AG013854, P30 AG028383, P50 AG005133, P50 AG005681, R01AG058676, U01 AG016976, U01AG068057, U19AG024904, U24AG074855
U.S. Department of DefenseDODW81XWH‐12‐2‐0012
National Institute on AgingNIA
National Institute of Biomedical Imaging and BioengineeringNIBIB
Alzheimer’s AssociationAA
Alzheimer’s Drug Discovery FoundationADDF
Biogen
AbbVie
Alzheimer’s Disease Neuroimaging InitiativeADNI
Takeda Pharmaceuticals U.S.A.TPUSA
BioClinica

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

Personality traits moderate associations between word recall and subjective memory” (2023) Aging, Neuropsychology, and Cognition

Personality traits moderate associations between word recall and subjective memory
(2023) Aging, Neuropsychology, and Cognition, . 

Hill, P.L.a , Pfund, G.N.a b , Cruitt, P.J.c , Spears, I.a , Norton, S.A.a , Bogdan, R.a , Oltmanns, T.F.a

a Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
b Department of Medical Social Sciences, Northwestern University, Evanston, IL, United States
c Minneapolis VA Health Care System, Minneapolis, MN, United States

Abstract
Cognitive gerontology research requires consideration of performance as well as perceptions of performance. While subjective memory is positively associated with memory performance, these correlations typically are modest in magnitude, leading to the need to consider whether certain people may show weaker or stronger linkages between performance and perceptions. The current study leveraged personality (NEO Big Five), memory performance (i.e., word recall), and perceptions of memory ability (i.e., metamemory in adulthood and memory decline) data from the St. Louis Personality and Aging Network (SPAN) study (n = 774, mean age: 71.52 years). Extraversion and conscientiousness held the most consistent associations with the cognitive variables of interest, as both traits were positively associated with metamemory and word recall, but negatively associated with subjective decline. Moreover, extraversion moderated associations between word recall and both memory capacity and complaints, insofar that objective-subjective associations were weaker for those adults higher in extraversion. These findings highlight the need to understand how personality influences the sources of information employed for subjective cognitive beliefs. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Author Keywords
memory decline;  moderation;  Personality;  subjective memory;  word recall

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

Predicting survival in glioblastoma with multimodal neuroimaging and machine learning” (2023) Journal of Neuro-Oncology, . 

Predicting survival in glioblastoma with multimodal neuroimaging and machine learning
(2023) Journal of Neuro-Oncology, . 

Luckett, P.H.a , Olufawo, M.a , Lamichhane, B.a b , Park, K.Y.a c , Dierker, D.d , Verastegui, G.T.a , Yang, P.a , Kim, A.H.a e , Chheda, M.G.e f , Snyder, A.Z.d g , Shimony, J.S.d e , Leuthardt, E.C.a e h i j k l

a Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO 63110, United States
b Center for Health Sciences, Oklahoma State University, Tulsa, OK 74136, United States
c Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
d Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
e Brain Tumor Center at Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, United States
f Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
g Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
h Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO 63130, United States
i Department of Mechanical Engineering and Materials Science, Washington University in Saint Louis, St. Louis, MO 63130, United States
j Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO 63110, United States
k Brain Laser Center, Washington University School of Medicine, St. Louis, MO 63110, United States
l National Center for Adaptive Neurotechnologies, Albany, United States

Abstract
Purpose: Glioblastoma (GBM) is the most common and aggressive malignant glioma, with an overall median survival of less than two years. The ability to predict survival before treatment in GBM patients would lead to improved disease management, clinical trial enrollment, and patient care. Methods: GBM patients (N = 133, mean age 60.8 years, median survival 14.1 months, 57.9% male) were retrospectively recruited from the neurosurgery brain tumor service at Washington University Medical Center. All patients completed structural neuroimaging and resting state functional MRI (RS-fMRI) before surgery. Demographics, measures of cortical thickness (CT), and resting state functional network connectivity (FC) were used to train a deep neural network to classify patients based on survival (< 1y, 1-2y, >2y). Permutation feature importance identified the strongest predictors of survival based on the trained models. Results: The models achieved a combined cross-validation and hold out accuracy of 90.6% in classifying survival (< 1y, 1-2y, >2y). The strongest demographic predictors were age at diagnosis and sex. The strongest CT predictors of survival included the superior temporal sulcus, parahippocampal gyrus, pericalcarine, pars triangularis, and middle temporal regions. The strongest FC features primarily involved dorsal and inferior somatomotor, visual, and cingulo-opercular networks. Conclusion: We demonstrate that machine learning can accurately classify survival in GBM patients based on multimodal neuroimaging before any surgical or medical intervention. These results were achieved without information regarding presentation symptoms, treatments, postsurgical outcomes, or tumor genomic information. Our results suggest GBMs have a global effect on the brain’s structural and functional organization, which is predictive of survival. © 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

Author Keywords
Cortical thickness;  Deep learning;  Functional MRI;  Glioblastoma;  Survival

Funding details
National Cancer InstituteNCIR01CA203861
National Institute of Neurological Disorders and StrokeNINDSU24NS109103
National Institute of Biomedical Imaging and BioengineeringNIBIBP41EB018783, R01EB026439
University of WashingtonUW

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