Multi-scale measurement of stiffness in the developing ferret brain
(2023) Scientific Reports, 13 (1), art. no. 20583, .
Walter, C.a , Balouchzadeh, R.a , Garcia, K.E.b , Kroenke, C.D.c , Pathak, A.a , Bayly, P.V.a
a Mechanical Engineering and Materials Science, Washington University, St. Louis, United States
b Radiology and Imaging Sciences, Indiana University School of Medicine, Evansville, IN, United States
c Advanced Imaging Research Center and Oregon National Primate Research Center Division of Neuroscience, Oregon Health and Science University, Portland, OR, United States
Abstract
Cortical folding is an important process during brain development, and aberrant folding is linked to disorders such as autism and schizophrenia. Changes in cell numbers, size, and morphology have been proposed to exert forces that control the folding process, but these changes may also influence the mechanical properties of developing brain tissue. Currently, the changes in tissue stiffness during brain folding are unknown. Here, we report stiffness in the developing ferret brain across multiple length scales, emphasizing changes in folding cortical tissue. Using rheometry to measure the bulk properties of brain tissue, we found that overall brain stiffness increases with age over the period of cortical folding. Using atomic force microscopy to target the cortical plate, we found that the occipital cortex increases in stiffness as well as stiffness heterogeneity over the course of development and folding. These findings can help to elucidate the mechanics of the cortical folding process by clarifying the concurrent evolution of tissue properties. © 2023, The Author(s).
Funding details
CMMI -154857
National Institutes of HealthNIHR01 NS111948, R35 GM128764, T32 EB028092
Document Type: Article
Publication Stage: Final
Source: Scopus
Molecular Diagnostic Yield of Exome Sequencing in Patients With Congenital Hydrocephalus: A Systematic Review and Meta-Analysis
(2023) JAMA Network Open, 6 (11), p. e2343384.
Greenberg, A.B.W.a , Mehta, N.H.b , Allington, G.a b , Jin, S.C.c d , Moreno-De-Luca, A.e , Kahle, K.T.a f g
a Department of Neurosurgery, Massachusetts General Hospital, Boston, United States
b Department of Pathology, Yale University School of Medicine, New Haven, CT, United States
c Department of Genetics, Washington University School of Medicine, St Louis, MO, United States
d Department of Pediatrics, Washington University School of Medicine, St Louis, MO, United States
e Department of Radiology, Neuroradiology Section, Kingston Health Sciences Centre, Queen’s University Faculty of Health Sciences, Kingston, Ontario, Canada
f Broad Institute of MIT and Harvard, Cambridge, MA, United States
g Harvard Center for Hydrocephalus and Neurodevelopmental Disorders, Massachusetts General Hospital, Boston, United States
Abstract
Importance: Exome sequencing (ES) has been established as the preferred first line of diagnostic testing for certain neurodevelopmental disorders, such as global developmental delay and autism spectrum disorder; however, current recommendations are not specific to or inclusive of congenital hydrocephalus (CH). Objective: To determine the diagnostic yield of ES in CH and whether ES should be considered as a first line diagnostic test for CH. Data Sources: PubMed, Cochrane Library, and Google Scholar were used to identify studies published in English between January 1, 2010, and April 10, 2023. The following search terms were used to identify studies: congenital hydrocephalus, ventriculomegaly, cerebral ventriculomegaly, primary ventriculomegaly, fetal ventriculomegaly, prenatal ventriculomegaly, molecular analysis, genetic cause, genetic etiology, genetic testing, exome sequencing, whole exome sequencing, genome sequencing, microarray, microarray analysis, and copy number variants. Study Selection: Eligible studies included those with at least 10 probands with the defining feature of CH and/or severe cerebral ventriculomegaly that had undergone ES. Studies with fewer than 10 probands, studies of mild or moderate ventriculomegaly, and studies using genetic tests other than ES were excluded. A full-text review of 68 studies was conducted by 2 reviewers. Discrepancies were resolved by consensus. Data Extraction and Synthesis: Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and Meta-Analysis of Observational Studies in Epidemiology guidelines were used by 2 reviewers to extract data. Data were synthesized using a random-effects model of single proportions. Data analysis occurred in April 2023. Main Outcomes and Measures: The primary outcome was pooled diagnostic yield. Additional diagnostic yields were estimated for specific subgroups on the basis of clinical features, syndromic presentation, and parental consanguinity. For each outcome, a 95% CI and estimate of interstudy heterogeneity (I2 statistic) was reported. Results: From 498 deduplicated and screened records, 9 studies with a total of 538 CH probands were selected for final inclusion. The overall diagnostic yield was 37.9% (95% CI, 20.0%-57.4%; I2 = 90.1). The yield was lower for isolated and/or nonsyndromic cases (21.3%; 95% CI, 12.8%-31.0%; I2 = 55.7). The yield was higher for probands with reported consanguinity (76.3%; 95% CI, 65.1%-86.1%; I2 = 0) than those without (16.2%; 95% CI, 12.2%-20.5%; I2 = 0). Conclusions and Relevance: In this systematic review and meta-analysis of the diagnostic yield of ES in CH, the diagnostic yield was concordant with that of previous recommendations for other neurodevelopmental disorders, suggesting that ES should also be recommended as a routine diagnostic adjunct for patients with CH.
Document Type: Article
Publication Stage: Final
Source: Scopus
Skull bone marrow channels as immune gateways to the central nervous system
(2023) Nature Neuroscience, 26 (12), pp. 2052-2062.
Mazzitelli, J.A.a b c d , Pulous, F.E.e f , Smyth, L.C.D.a b , Kaya, Z.e f , Rustenhoven, J.g , Moskowitz, M.A.e f h , Kipnis, J.a b c d , Nahrendorf, M.e f i j
a Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
b Center for Brain Immunology and Glia (BIG), Washington University School of Medicine, St. Louis, MO, United States
c Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO, United States
d Neuroscience Graduate Program, Washington University School of Medicine, St. Louis, MO, United States
e Center for Systems Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
f Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
g Department of Pharmacology and Clinical Pharmacology, The University of Auckland, Auckland, New Zealand
h Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
i Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
j Department of Internal Medicine I, University Hospital Wuerzburg, Wuerzburg, Germany
Abstract
Decades of research have characterized diverse immune cells surveilling the CNS. More recently, the discovery of osseous channels (so-called ‘skull channels’) connecting the meninges with the skull and vertebral bone marrow has revealed a new layer of complexity in our understanding of neuroimmune interactions. Here we discuss our current understanding of skull and vertebral bone marrow anatomy, its contribution of leukocytes to the meninges, and its surveillance of the CNS. We explore the role of this hematopoietic output on CNS health, focusing on the supply of immune cells during health and disease. © 2023, Springer Nature America, Inc.
Funding details
National Institutes of HealthNIHAT010416, HL139598, HL142494, NS096967, NS108419, NS127808
Cure Alzheimer’s FundCAF
Document Type: Article
Publication Stage: Final
Source: Scopus
A global multicohort study to map subcortical brain development and cognition in infancy and early childhood
(2023) Nature Neuroscience, .
Alex, A.M.a , Aguate, F.a b , Botteron, K.c , Buss, C.d e f , Chong, Y.-S.g h , Dager, S.R.i , Donald, K.A.j k , Entringer, S.d e f , Fair, D.A.l , Fortier, M.V.h m , Gaab, N.n , Gilmore, J.H.o , Girault, J.B.o p , Graham, A.M.q , Groenewold, N.A.j r s t , Hazlett, H.p q , Lin, W.u , Meaney, M.J.i , Piven, J.p q , Qiu, A.v w x y z aa , Rasmussen, J.M.e f , Roos, A.j k ab , Schultz, R.T.ac , Skeide, M.A.ad , Stein, D.J.s ab , Styner, M.p ae , Thompson, P.M.af , Turesky, T.K.n , Wadhwa, P.D.e f ag , Zar, H.J.r t , Zöllei, L.ah , de los Campos, G.a b ai , Knickmeyer, R.C.a aj
a Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, United States
b Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, MI, United States
c Mallinickrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
d Department of Medical Psychology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
e Department of Pediatrics, University of California Irvine, Irvine, CA, United States
f Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, United States
g Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
h Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
i Department of Radiology, University of Washington Medical Center, Seattle, WA, United States
j Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, Cape Town, South Africa
k Neuroscience Institute, University of Cape Town, Cape Town, South Africa
l Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, United States
m Department of Diagnostic & Interventional Imaging, KK Women’s and Children’s Hospital, Singapore, Singapore
n Harvard Graduate School of Education, Harvard University, Cambridge, MA, United States
o Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
p Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, United States
q Department of Psychiatry, Oregon Health & Science University, Portland, OR, United States
r South African Medical Research Council (SA-MRC) Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
s Department of Psychiatry, University of Cape Town, Cape Town, South Africa
t Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
u Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
v Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
w NUS (Suzhou) Research Institute, National University of Singapore, Suzhou, China
x The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
y Institute of Data Science, National University of Singapore, Singapore, Singapore
z Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
aa Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, China
ab SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
ac Center for Autism Research, Children’s Hospital of Philadelphia and the University of Pennsylvania, Philadelphia, PA, United States
ad Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
ae Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
af Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, CA, United States
ag Departments of Psychiatry and Human Behavior, Obstetrics & Gynecology, Epidemiology, University of California, Irvine, Irvine, CA, United States
ah A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States
ai Department of Statistics & Probability, Michigan State University, East Lansing, MI, United States
aj Department of Pediatrics and Human Development, Michigan State University, East Lansing, MI, United States
Abstract
The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain–cognition correlations revealed region-specific associations. © 2023, The Author(s).
Funding details
NAF002/1001
U24 AA014811
24467
National Institutes of HealthNIHU54 EB020403
National Institute of Mental HealthNIMHR01MH123716
National Institute on Alcohol Abuse and AlcoholismNIAAAR21AA023887
Carnegie Corporation of New YorkCCNYHD053000, MH064065, MH070890, P30-HD003110, P50 HD103573, R01-HD055741, R33 MH104330, T32-HD040127
Bill and Melinda Gates FoundationBMGFOPP 1017641
Simons FoundationSF140209, K01-MH122779
U.S. Public Health ServiceUSPHSR01 HD-060628, R01 MH-105538, UH3 OD-023349
Harvard University
Harvard Catalyst5UL1RR025758
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHDR01 HD065762-10
European Research CouncilERC5U01MH110274, ERC-Stg 639766, R01 HD065825, R01 MH-091361
National Research FoundationNRF
South African Medical Research CouncilSAMRC
National Medical Research CouncilNMRCNMRC/TCR/004-NUS/2008, NMRC/TCR/012-NUHS/2014
Ministry of Health -SingaporeMOH
National Research Foundation SingaporeNRF
Deutsche ForschungsgemeinschaftDFG433758790
Jacobs Foundation2020136212
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
High-frequency assessment of mood, personality, and cognition in healthy younger, healthy older and adults with cognitive impairment
(2023) Aging, Neuropsychology, and Cognition, .
Aschenbrenner, A.J.a , Jackson, J.J.b
a Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
b Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
Abstract
Increased variability in cognitive scores, mood or personality traits can be indicative of underlying neurological disorders. Whether variability in cognition is due to changes in mood or personality is unknown. A total of 66 younger adults, 51 healthy older adults and 38 participants with cognitive impairment completed 21 daily sessions of attention, working memory, mood, and personality assessment. Group differences in mean performance and variability were examined using Bayesian mixed effects location scale models. Variability in attention decreased from younger to older adults and then increased again in cognitive impairment. Younger adults were more variable in agreeableness, openness and conscientiousness compared to older adults. The clinically impaired group differed from the healthy older adults in terms of variability on attention, openness, and conscientiousness. Healthy aging results in greater stability in personality traits over short intervals yet this stability is not redundant with increased stability in cognitive scores. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords
Aging; attention; personality; variability
Document Type: Article
Publication Stage: Article in Press
Source: Scopus