Bias-free measure of distractor avoidance in visual search
(2025) Cognition, 254, art. no. 106007, .
Ma, X.a b , Abrams, R.A.a
a Department of Psychological & Brain Sciences, Washington University in St. Louis
b Department of Psychological Science, University of Missouri, Columbia
Abstract
Recent findings suggest that it is possible for people to proactively avoid attentional capture by salient distractors during visual search. The results have important implications for understanding the competing influences of top-down and bottom-up factors in visual attention. Nevertheless, questions remain regarding the extent to which apparently ignored distractors are processed. To assess distractor processing, previous experiments have used a probe method in which stimuli are occasionally superimposed on the search display–requiring participants to abort the search and identify the probe stimuli. It has been recently shown that such probe tasks may be vulnerable to decision-level biases, such as a participant’s willingness to report stimuli on to-be-ignored items. We report here results from a new method that is not subject to this limitation. In the new method, the non-target search elements, including the salient distractors, contained features that were either congruent or incongruent with the target. Processing of the non-target elements is inferred from the effects of the compatibility of the shared features on judgments about the target. In four experiments using the technique we show that ignored salient distractors are indeed processed less fully than non-target elements that are not salient, replicating the results of earlier studies using the probe methods. Additionally, the processing of the distractors was found to be reduced at least in part at early perceptual or attentional stages, as assumed by models of attentional suppression. The study confirms the proactive avoidance of capture by salient distractors measured without decision-level biases and provides a new technique for assessing the magnitude of distractor processing. © 2024 The Authors
Author Keywords
Attentional capture; Attentional suppression; Inhibitory control; Visual attention; Visual search
Document Type: Article
Publication Stage: Final
Source: Scopus
Comparing Parent Perception of Neurodevelopment after Primary versus Staged Repair of Neonatal Symptomatic Tetralogy of Fallot
(2025) Journal of Pediatrics, 276, art. no. 114357, .
Zampi, J.D.a , Ilardi, D.L.b c , McCracken, C.E.d , Zhang, Y.e , Glatz, A.C.f , Goldstein, B.H.g , Petit, C.J.e , Qureshi, A.M.h , Goldberg, C.S.a , Law, M.A.i , Meadows, J.J.j , Shahanavaz, S.k , Batlivala, S.P.k , Maskatia, S.A.l , O’Byrne, M.L.m , Ligon, R.A.c , Pettus, J.A.c , Beshish, A.c , Romano, J.C.n , Stack, K.O.m , Khan, H.Q.h , Parekh, S.j , Nicholson, G.T.o
a Division of Cardiology, Department of Pediatrics, C.S. Mott Children’s Hospital, University of Michigan School of Medicine, Ann Arbor, MI, United States
b Pediatric Neurodevelopmental Center, Atlanta, GA, United States
c Children’s Heart Center Cardiology, Department of Pediatrics, Children’s Healthcare of Atlanta, Emory University School of Medicine, Atlanta, GA, United States
d Center for Research and Evaluation, Kaiser Permanente, Atlanta, GA, United States
e Morgan Stanley Children’s Hospital, Columbia University Vagelos College of Physicians & Surgeons, New York, NY, United States
f Division of Cardiology, Department of Pediatrics, Washington University, St Louis, MO, United States
g Department of Pediatrics, Heart Institute, UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
h Lillie Frank Abercrombie Division of Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, TX, United States
i Division of Pediatric Cardiology, Department of Pediatrics, Children’s of Alabama, University of Alabama Birmingham School of Medicine, Birmingham, AL, United States
j Division of Cardiology, Department of Pediatrics, University of California San Francisco School of Medicine, San Francisco, CA, United States
k The Heart Institute, Cincinnati Children’s Hospital Medical Center and Division of Pediatric Cardiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
l Division of Pediatric Cardiology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
m The Cardiac Center at The Children’s Hospital of Philadelphia, Philadelphia, PA, United States
n Division of Congenital Cardiothoracic Surgery, Department of Cardiothoracic Surgery, C.S. Mott Children’s Hospital, University of Michigan School of Medicine, Ann Arbor, MI, United States
o Division of Cardiology, Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, TN, United States
Abstract
Objective: To assess the association between primary and staged repair of neonatal symptomatic tetralogy of Fallot (sTOF) and neurodevelopmental outcomes in preschool through school-age children. Study design: Multicenter cohort (n = 9 sites) study of patients with sTOF who underwent neonatal intervention between 2005 and 2017. The neurodevelopmental outcomes measures included caregivers’ ratings of executive function with the Behavior Rating Inventory of Executive Function, and psychosocial functioning with the Behavior Assessment System for Children – third Edition (BASC-3). Results were compared with normative data and by treatment strategy (primary repair vs staged repair). A parent survey assessed history of disabilities and access to services related to neurodevelopment. Results: Although the majority of patients (median age 8.3 years, IQR 5.7-11.2) had median Behavior Rating Inventory of Executive Function and BASC-3 scores within the normal range, a proportion had clinically elevated (abnormal) scores, especially in the school-age patient subgroup (Behavior Rating Inventory of Executive Function 24%-30% and BASC 20%-37%). There were no statistically significant differences based on treatment strategy for either the Behavior Rating Inventory of Executive Function or BASC-3. However, lower birth weight, genetic syndrome, and medical complexity were significantly associated with worse executive function, and lower maternal education was associated in school-age children with lower executive and psychosocial functioning. Ongoing disabilities were relatively common (learning disability 35%, speech delay 33%, developmental delay 31%), although up to 50% of children were not receiving educational or developmental services. Conclusions: Elevated executive and psychosocial concerns are present in the patient population with sTOF. Although initial treatment strategy appears unrelated to neurodevelopmental outcomes, lower birth weight, genetic syndrome, and medical complexity and lower maternal education are risk factors. Early recognition of neurodevelopmental concerns can facilitate access to appropriate neurodevelopmental services in this high-risk group. © 2024 Elsevier Inc.
Author Keywords
congenital heart disease; executive functioning; neurodevelopment; psychosocial functioning; tetralogy of Fallot
Document Type: Article
Publication Stage: Final
Source: Scopus
Protocol for Xenium spatial transcriptomics studies using fixed frozen mouse brain sections
(2024) STAR Protocols, 5 (4), art. no. 103420, .
Ma, X.a , Chen, P.a , Wei, J.a , Zhang, J.a , Chen, C.a , Zhao, H.c , Ferguson, D.a , McGee, A.W.b , Dai, Z.c d , Qiu, S.a b
a Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States
b Translational Neuroscience Department, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States
c Division of Pulmonary, Critical Care Sleep Medicine, Department of Internal Medicine, University of Arizona College of Medicine-Phoenix, Phoenix, AZ, United States
d Division of Pulmonary, Critical Care Medicine, John T. Milliken Department of Medicine, Washington University School of Medicine in Saint Louis, United States
Abstract
Here, we present a protocol for Xenium spatial transcriptomics studies using fixed frozen mouse brain sections. We describe steps for intracardiac perfusion, cryosectioning, and floating section mounting of brain sections, which enable runs on the Xenium analyzer and data delivery. We demonstrate that, in addition to the 10× Genomics-validated formalin-fixed paraffin-embedded (FFPE) and fresh frozen sections, fixed frozen thin brain sections are compatible with the Xenium platform and provide excellent imaging and quantification results for spatially resolved gene expression. For complete details on the use and execution of this protocol, please refer to Ma et al.1 © 2024
Author Keywords
gene expression; molecular biology; neuroscience; RNA-seq; systems biology
Funding details
Arizona Biomedical Research CommissionABRC
Institute for Mental Health ResearchIMHR
National Institutes of HealthNIHR21AG078700, R01EY035138, R01MH128192
University of ArizonaUAR01HL170096, R01HL158596, R01HL169509, R01HL162794, R01HL62794
Document Type: Article
Publication Stage: Final
Source: Scopus
ECMO Survivors’ Reflections on Their ICU Experience and Recovery
(2024) Pediatrics, 154 (5), .
Hendrickson, E.a b , Mirpuri, K.K.b , Kolmar, A.a b b
a Saint Louis Children’s Hospital, St. Louis, MO, United States
b Washington University School of Medicine, St. Louis, MO, United States
Abstract
OBJECTIVE: As pediatric mortality improves, approaches to pediatric critical care now focus on understanding long-term implications of survivorship on patients and families. We aimed to characterize how patients recall time spent sedated and recovering to identify areas for improvement in patient outcomes. METHODS: We undertook qualitative analysis using semistructured interviews of pediatric patients requiring extra-corporeal support in our intensive care units from 2018 to 2023. All patients were English-speaking, >12 years old at time of hospitalization, and able to communicate at an age-appropriate level. Priority sampling was given to those with more recent hospitalizations to improve recall. Interviews were recorded and transcribed before thematic, inductive analysis. RESULTS: Forty-one patients met inclusion criteria; 14 patients were enrolled before achieving thematic saturation. Several themes emerged, centering on cognitive, physical, and socioemotional experiences during and after hospitalization. Notable findings include profound awareness under sedation, impaired sleep, challenges with communication, physical discomfort, frustration with activities of daily living limitations, and gratitude for provider and family presence. Postdischarge, patients highlighted persistent memory, concentration, sleep, and physical impairments, as well as emotional processing of their illness and mortality. CONCLUSIONS: Our findings describe how pediatric critical illness impacts short and long term cognitive, physical, and socioemotional outcomes for children in the ICU. Future research is necessary to study if there are specific, modifiable factors in patients’ care that impacts their experience of critical illness, such as specific medication choices, diagnoses, communication styles, or physical and speech therapy interventions. Copyright © 2024 by the American Academy of Pediatrics.
Document Type: Article
Publication Stage: Final
Source: Scopus
Genetic Heterogeneity Across Dimensions of Alcohol Use Behaviors
(2024) The American Journal of Psychiatry, 181 (11), pp. 1006-1017.
Savage, J.E., Barr, P.B., Phung, T., Lee, Y.H., Zhang, Y., McCutcheon, V.V., Ge, T., Smoller, J.W., Davis, L.K., Meyers, J., Porjesz, B., Posthuma, D., Mallard, T.T., Sanchez-Roige, S., COGA Investigators
Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam (Savage, Phung, Posthuma); Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, New York (Barr, Meyers, Porjesz); VA New York Harbor Healthcare System, Brooklyn, New York (Barr, Meyers); Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine (Lee, Zhang, Ge, Smoller, Mallard), and Center for Precision Psychiatry (Ge, Smoller), Massachusetts General Hospital, Boston; Department of Psychiatry, Harvard Medical School, Boston (Lee, Ge, Smoller, Mallard); Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge (Lee, Zhang, Ge, Smoller, Mallard); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston (Zhang); Department of Psychiatry, Washington University School of Medicine, St. Louis (McCutcheon); Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville (Davis, Sanchez-Roige); Department of Child and Adolescent Psychology and Psychiatry, section Complex Trait Genetics, VU University Medical Center, Amsterdam (Posthuma); Department of Psychiatry and Institute for Genomic Medicine, University of California San Diego, La Jolla (Sanchez-Roige)
Abstract
OBJECTIVE: Increasingly large samples in genome-wide association studies (GWASs) for alcohol use behaviors (AUBs) have led to an influx of implicated genes, yet the clinical and functional understanding of these associations remains low, in part because most GWASs do not account for the complex and varied manifestations of AUBs. This study applied a multidimensional framework to investigate the latent genetic structure underlying heterogeneous dimensions of AUBs. METHODS: Multimodal assessments (self-report, interview, electronic health records) were obtained from approximately 400,000 UK Biobank participants. GWAS was conducted for 18 distinct AUBs, including consumption, drinking patterns, alcohol problems, and clinical sequelae. Latent genetic factors were identified and carried forward to GWAS using genomic structural equation modeling, followed by functional annotation, genetic correlation, and enrichment analyses to interpret the genetic associations. RESULTS: Four latent factors were identified: Problems, Consumption, BeerPref (declining alcohol consumption with a preference for drinking beer), and AtypicalPref (drinking fortified wine and spirits). The latent factors were moderately correlated (rg values, 0.12-0.57) and had distinct patterns of associations, with BeerPref in particular implicating many novel genomic regions. Patterns of regional and cell type-specific gene expression in the brain also differed between the latent factors. CONCLUSIONS: Deep phenotyping is an important next step to improve understanding of the genetic etiology of AUBs, in addition to increasing sample size. Further effort is required to uncover the genetic heterogeneity underlying AUBs using methods that account for their complex, multidimensional nature.
Author Keywords
Alcohol; Genetics/Genomics; Genomic Structural Equation Modeling; GWAS; Substance-Related and Addictive Disorders
Document Type: Article
Publication Stage: Final
Source: Scopus
Spinal cord metrics derived from diffusion MRI: improvement in prognostication in cervical spondylotic myelopathy compared with conventional MRI
(2024) Journal of Neurosurgery. Spine, 41 (5), pp. 639-647.
Zhang, J.K.a b , Yakdan, S.b , Kaleem, M.I.b , Javeed, S.b , Greenberg, J.K.b , Botterbush, K.S.b , Benedict, B.b , Reis, M.c , Hongsermeier-Graves, N.a , Twitchell, S.a , Sherrod, B.a , Mazur, M.S.a , Mahan, M.A.a , Dailey, A.T.a , Bisson, E.F.a , Song, S.-K.c , Ray, W.Z.b
a Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, United States
b Departments of2Neurosurgery and
c 3Radiology, Washington University School of Medicine, St. Louis, MO, United States
Abstract
OBJECTIVE: A major shortcoming in optimizing care for patients with cervical spondylotic myelopathy (CSM) is the lack of robust quantitative imaging tools offered by conventional MRI. Advanced MRI modalities, such as diffusion MRI (dMRI), including diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help address this limitation by providing granular evaluations of spinal cord microstructure. METHODS: Forty-seven patients with CSM underwent comprehensive clinical assessments and dMRI, followed by DTI and DBSI modeling. Conventional MRI metrics included 10 total qualitative and quantitative assessments of spinal cord compression in both the sagittal and axial planes. The dMRI metrics included 12 unique measures including anisotropic tensors, reflecting axonal diffusion, and isotropic tensors, describing extraaxonal diffusion. The primary outcome was the modified Japanese Orthopaedic Association (mJOA) score measured at 2 years postoperatively. Extreme gradient boosting-supervised classification algorithms were used to classify patients into disease groups and to prognosticate surgical outcomes at 2-year follow-up. RESULTS: Forty-seven patients with CSM, including 24 (51%) with a mild mJOA score, 12 (26%) with a moderate mJOA score, and 11 (23%) with a severe mJOA score, as well as 21 control subjects were included. In the classification task, the traditional MRI metrics correctly assigned patients to healthy control versus mild CSM versus moderate/severe CSM cohorts, with an accuracy of 0.647 (95% CI 0.64-0.65). In comparison, the DTI model performed with an accuracy of 0.52 (95% CI 0.51-0.52) and the DBSI model’s accuracy was 0.81 (95% CI 0.808-0.814). In the prognostication task, the traditional MRI metrics correctly predicted patients with CSM who improved at 2-year follow-up on the basis of change in mJOA, with an accuracy of 0.58 (95% CI 0.57-0.58). In comparison, the DTI model performed with an accuracy of 0.62 (95% CI 0.61-0.62) and the DBSI model had an accuracy of 0.72 (95% CI 0.718-0.73). CONCLUSIONS: Conventional MRI is a powerful tool to assess structural abnormality in CSM but is inherently limited in its ability to characterize spinal cord tissue injury. The results of this study demonstrate that advanced imaging techniques, namely DBSI-derived metrics from dMRI, provide granular assessments of spinal cord microstructure that can offer better diagnostic and prognostic utility.
Author Keywords
cervical spondylotic myelopathy; diffusion MRI; machine learning; magnetic resonance imaging
Document Type: Article
Publication Stage: Final
Source: Scopus
Brain malformations and seizures by impaired chaperonin function of TRiC
(2024) Journal of Bio-X Research, 386 (6721), pp. 516-525.
Kraft, F.a , Rodriguez-Aliaga, P.b , Yuan, W.c , Franken, L.a , Zajt, K.d , Hasan, D.e , Lee, T.-T.b , Flex, E.f , Hentschel, A.g , Innes, A.M.h , Zheng, B.i , Suh, D.S.J.a , Knopp, C.a , Lausberg, E.a , Krause, J.a , Zhang, X.d , Trapane, P.j , Carroll, R.j , McClatchey, M.k l , Fry, A.E.l m , Wang, L.d , Giesselmann, S.a , Hoang, H.c , Baldridge, D.c , Silverman, G.A.c , Radio, F.C.n , Bertini, E.o , Ciolfi, A.n , Blood, K.A.p , de Sainte Agathe, J.-M.q r , Charles, P.q , Bergant, G.s , Čuturilo, G.t u , Peterlin, B.s , Diderich, K.v , Streff, H.w , Robak, L.w , Oegema, R.x , van Binsbergen, E.x , Herriges, J.y z , Saunders, C.J.y z aa , Maier, A.ab ac , Wolking, S.ad , Weber, Y.ad , Lochmüller, H.ae , Meyer, S.ae , Aleman, A.ae , Polavarapu, K.ae af , Nicolas, G.ag ah , Goldenberg, A.ag , Guyant, L.ag , Pope, K.ai aj , Hehmeyer, K.N.aj , Monaghan, K.G.ak , Quade, A.al , Smol, T.am , Caumes, R.am , Duerinckx, S.an , Depondt, C.ao , Van Paesschen, W.ap aq , Rieubland, C.ar , Poloni, C.ar , Guipponi, M.as , Arcioni, S.ar at , Meuwissen, M.au , Jansen, A.C.av , Rosenblum, J.au , Haack, T.B.aw , Bertrand, M.aw , Gerstner, L.aw , Magg, J.ax , Riess, O.aw , Schulz, J.B.ab ac , Wagner, N.ac ay , Wiesmann, M.e , Weis, J.d , Eggermann, T.a , Begemann, M.a , Roos, A.ae az ba , Häusler, M.ac al , Schedl, T.bb , Tartaglia, M.n , Bremer, J.d , Pak, S.C.c , Frydman, J.b , Elbracht, M.a ac , Kurth, I.a ac
a Institute for Human Genetics and Genomic Medicine, Medical Faculty, RWTH Aachen University, Aachen, 52074, Germany
b Department of Biology, Stanford University, Stanford, CA 94305, United States
c Department of Pediatrics, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, United States
d Institute of Neuropathology, RWTH Aachen University Hospital, Aachen, 52074, Germany
e Department for Diagnostic and Interventional Neuroradiology, RWTH Aachen University Hospital, Aachen, 52074, Germany
f Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, 00161, Italy
g Leibniz- Institut für Analytische Wissenschaften -ISAS- e.V., Dortmund, 44139, Germany
h Department of Medical Genetics, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, T2N 1N4, Canada
i Nanjing Key Laboratory of Pediatrics, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, China
j Division of Pediatric Genetics, Department of Pediatrics, University of Florida, College of Medicine-Jacksonville, Jacksonville, FL 32209, United States
k Institute of Medical Genetics, University Hospital of Wales, Cardiff, CF14 4XW, United Kingdom
l Division of Cancer and Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, United Kingdom
m All Wales Medical Genomics Service, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, United Kingdom
n Molecular Genetics and Functional Genomics, Ospedale Pediatrico Bambino Gesù IRCCS, Rome, 00146, Italy
o Neuromuscular Disorders, Ospedale Pediatrico Bambino Gesù IRCCS, Rome, 00146, Italy
p Department of Medical Genetics, University of British Columbia, Vancouver, BC V6T 2A1, Canada
q Department of Medical Genetics, Pitié-Salpêtrière Hospital, AP-HP.Sorbonne University, Paris, 75005, France
r Laboratoire de Médecine Génomique Sorbonne Université, LBM SeqOIA, Paris, 75014, France
s Clinical Institute of Genomic Medicine, University Medical Centre Ljubljana, Ljubljana, 1000, Slovenia
t Faculty of Medicine, University of Belgrade, Belgrade, 11000, Serbia
u University Children’s Hospital, Belgrade, 11000, Serbia
v Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, 3015 GD, Netherlands
w Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, United States
x Department of Genetics, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, Netherlands
y Department of Pathology and Laboratory Medicine, Children’s Mercy-Kansas City, Kansas City, MO 64108, United States
z School of Medicine, University of Missouri Kansas City, Kansas City, MO 64108, United States
aa Genomic Medicine Center, Children’s Mercy Research Institute, Kansas City, MO 64108, United States
ab Department of Neurology, University Hospital, RWTH Aachen University, Aachen, 52074, Germany
ac Center for Rare Diseases Aachen (ZSEA), RWTH Aachen University Hospital, Aachen, 52074, Germany
ad Department of Epileptology and Neurology, Medical Faculty, RWTH Aachen University, Aachen, 52074, Germany
ae Children’s Hospital of Eastern Ontario Research Institute, Division of Neurology, Department of Medicine, The Ottawa Hospital, Brain and Mind Research Institute, University of Ottawa, Ottawa, K1H 8L1, Canada
af Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, 560030, India
ag Univ Rouen Normandie, Normandie univ, Inserm U1245 and CHU Rouen, Department of Genetics and Reference Center for Neurogenetics Diorders, Rouen, F-76000, France
ah Laboratoire multi-sites SeqOIA, Paris, 75014, France
ai University of South Florida, College of Public Health, Tampa, FL 33612, United States
aj Nemours Children’s Health, Department of Pediatrics, Division of Genetics, Orlando, FL 32827, United States
ak GeneDx, Gaithersburg, MD 20877, United States
al Division of Pediatric Neurology and Social Pediatrics, Department of Pediatrics, University Hospital RWTH Aachen, Aachen, 52074, Germany
am Department of Clinical Genetics, Lille University Hospital, CHU Lille, Lille, 59000, France
an Department of Pediatric Neurology, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Université Libre de Bruxelles, Brussels, 1070, Belgium
ao Department of Neurology, Hôpital Universitaire de Bruxelles, Hôpital Erasme, Université Libre de Bruxelles, Brussels, 1070, Belgium
ap Laboratory for Epilepsy Research, KU Leuven, Leuven, 3000, Belgium
aq Department of Neurology, University Hospitals Leuven, Leuven, 3000, Belgium
ar Department of Medical Genetics, Central Institute of the Hospitals, Hospital of the Valais, Sion, 1951, Switzerland
as Department of Genetic Medicine, University Hospitals of Geneva, University of Geneva Medical Faculty, Geneva, 1205, Switzerland
at Division of Medical Genetics, Central Institute of Hospitals, Valais Hospital, Sion, 1951, Switzerland
au Center of Medical Genetics, Antwerp University Hospital, University of Antwerp, Edegem, 2650, Belgium
av Department of Pediatrics, Division of Child Neurology, Antwerp University Hospital, University of Antwerp, Edegem, 2650, Belgium
aw Institute of Medical Genetics and Applied Genomics, University of Tübingen, Tübingen, 72076, Germany
ax Department of Neuropediatrics, Developmental Neurology, Social Pediatrics, University Children’s Hospital, University of Tübingen, Tübingen, 72076, Germany
ay Department of Pediatrics, University Hospital RWTH Aachen, Aachen, 52074, Germany
az Department for Pediatric Neurology, University Medicine Essen, Duisburg-Essen University, Essen, 45147, Germany
ba Institute of Neurology, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, 40225, Germany
bb Department of Genetics, Washington University in St Louis School of Medicine, St Louis, MO 63110, United States
Abstract
Malformations of the brain are common and vary in severity, from negligible to potentially fatal. Their causes have not been fully elucidated. Here, we report pathogenic variants in the core protein-folding machinery TRiC/CCT in individuals with brain malformations, intellectual disability, and seizures. The chaperonin TRiC is an obligate hetero-oligomer, and we identify variants in seven of its eight subunits, all of which impair function or assembly through different mechanisms. Transcriptome and proteome analyses of patient-derived fibroblasts demonstrate the various consequences of TRiC impairment. The results reveal an unexpected and potentially widespread role for protein folding in the development of the central nervous system and define a disease spectrum of “TRiCopathies.” © 2024 American Association for the Advancement of Science. All rights reserved.
Funding details
Gunma University
Medical Research CouncilMRC
Tohoku University
Heart of England NHS Foundation TrustHEFT
Wellcome TrustWT
Cancer Research UKCRUK
Institute for Mental Health ResearchIMHR
Ministerium für Kultur und Wissenschaft des Landes Nordrhein-WestfalenMKW NRW
Children’s Discovery InstituteCDI
Canada Research Chairs
Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum WürzburgIZKF Würzburg
Canada First Research Excellence FundCFREFCFREF-2022-00007
Canada First Research Excellence FundCFREF
PROFILNRW-2020–107-A
National Institute of Child Health and Human DevelopmentNICHDR01 HD110556
National Institute of Child Health and Human DevelopmentNICHD
Horizon 2020 Framework ProgrammeH2020825575
Horizon 2020 Framework ProgrammeH2020
Deutsche ForschungsgemeinschaftDFG418081722, WE 1406/16-1, WE 1406/17-1, 433158657, WO 2385/2-1
Deutsche ForschungsgemeinschaftDFG
OR2-189333, ERT-174211
Canada Foundation for InnovationCFICFI-JELF 38412
Canada Foundation for InnovationCFI
Ministero della SaluteRCR-2022-23682289, PNRR-MR1-2022-12376811
Ministero della Salute
National Institutes of HealthNIHP40 OD010440
National Institutes of HealthNIH
Canadian Institutes of Health ResearchCIHRFDN-167281
Canadian Institutes of Health ResearchCIHR
NFRFG-2022-00033
Hereditary Disease FoundationHDFGM74074, 2019-2023, 499059538, GM56433, INST 222/1458-1 FUGG
Hereditary Disease FoundationHDF
950-232279
European CommissionEC101080249
European CommissionEC
Document Type: Article
Publication Stage: Final
Source: Scopus
West Nile virus triggers intestinal dysmotility via T cell-mediated enteric nervous system injury
(2024) The Journal of Clinical Investigation, 134 (21), .
Janova, H.a , Zhao, F.R.a , Desai, P.a , Mack, M.b , Thackray, L.B.a , Stappenbeck, T.S.c , Diamond, M.S.a d e f
a Department of Medicine, Washington University School of Medicine, Saint Louis, Missouri, USA
b Department of Nephrology, University Hospital Regensburg, Regensburg, Germany
c Department of Inflammation and Immunity, Cleveland Clinic, Cleveland, OH, United States
d Department of Pathology and Immunology
e Department of Molecular Microbiology
f Andrew M. and Jane M. Bursky Center for Human Immunology and Immunotherapy Programs, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Intestinal dysmotility syndromes have been epidemiologically associated with several antecedent bacterial and viral infections. To model this phenotype, we previously infected mice with the neurotropic flavivirus West Nile virus (WNV) and demonstrated intestinal transit defects. Here, we found that within 1 week of WNV infection, enteric neurons and glia became damaged, resulting in sustained reductions of neuronal cells and their networks of connecting fibers. Using cell-depleting antibodies, adoptive transfer experiments, and mice lacking specific immune cells or immune functions, we show that infiltrating WNV-specific CD4+ and CD8+ T cells damaged the enteric nervous system (ENS) and glia, which led to intestinal dysmotility; these T cells used multiple and redundant effector molecules including perforin and Fas ligand. In comparison, WNV-triggered ENS injury and intestinal dysmotility appeared to not require infiltrating monocytes, and damage may have been limited by resident muscularis macrophages. Overall, our experiments support a model in which antigen-specific T cell subsets and their effector molecules responding to WNV infection direct immune pathology against enteric neurons and supporting glia that results in intestinal dysmotility.
Author Keywords
Fas signaling; Gastroenterology; Infectious disease; Neurological disorders; T cells
Document Type: Article
Publication Stage: Final
Source: Scopus
Relationships between abdominal adipose tissue and neuroinflammation with diffusion basis spectrum imaging in midlife obesity
(2024) Obesity, .
Dolatshahi, M.a , Commean, P.K.a , Rahmani, F.a , Xu, Y.b , Liu, J.b , Hosseinzadeh Kassani, S.a , Naghashzadeh, M.a , Lloyd, L.a , Nguyen, C.a , McBee Kemper, A.a , Hantler, N.a , Ly, M.a , Yu, G.a , Flores, S.a c , Ippolito, J.E.a d , Song, S.-K.a , Sirlin, C.B.e , Dai, W.f , Mittendorfer, B.g , Morris, J.C.c h , Benzinger, T.L.S.a c , Raji, C.A.a c h
a Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
b Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, United States
c Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, United States
d Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, United States
e Liver Imaging Group, Department of Radiology, University of California, Los Angeles, CA, United States
f Department of Computer Science, State University of New York at Binghamton, Binghamton, NY, United States
g Departments of Medicine and Nutrition & Exercise Physiology, University of Missouri School of Medicine, Columbia, MO, United States
h Department of Neurology, Washington University School of Medicine, St Louis, MO, United States
Abstract
Objective: This study investigated how obesity, BMI ≥ 30 kg/m2, abdominal adiposity, and systemic inflammation relate to neuroinflammation using diffusion basis spectrum imaging. Methods: We analyzed data from 98 cognitively normal midlife participants (mean age: 49.4 [SD 6.2] years; 34 males [34.7%]; 56 with obesity [57.1%]). Participants underwent brain and abdominal magnetic resonance imaging (MRI), blood tests, and amyloid positron emission tomography (PET) imaging. Abdominal visceral and subcutaneous adipose tissue (VAT and SAT, respectively) was segmented, and Centiloids were calculated. Diffusion basis spectrum imaging parameter maps were created using an in-house script, and tract-based spatial statistics assessed white matter differences in high versus low BMI values, VAT, SAT, insulin resistance, systemic inflammation, and Centiloids, with age and sex as covariates. Results: Obesity, high VAT, and high SAT were linked to lower axial diffusivity, reduced fiber fraction, and increased restricted fraction in white matter. Obesity was additionally associated with higher hindered fraction and lower fractional anisotropy. Also, individuals with high C-reactive protein showed lower axial diffusivity. Higher restricted fraction correlated with continuous BMI and SAT particularly in male individuals, whereas VAT effects were similar in male and female individuals. Conclusions: The findings suggest that, at midlife, obesity and abdominal fat are associated with reduced brain axonal density and increased inflammation, with visceral fat playing a significant role in both sexes. (Figure presented.). © 2024 The Author(s). Obesity published by Wiley Periodicals LLC on behalf of The Obesity Society.
Funding details
1Florida Alzheimer’s Disease Research CenterADRC
National Institute on AgingNIA1RF1AG072637‐01
National Institute on AgingNIA
Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. LouisKGADP30AG066444
Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St. LouisKGAD
P01AG026276
P01AG003991
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Microstructural analysis does not support altered interhemispheric wiring of the human anterior commissure in corpus callosum dysgenesis
(2024) NeuroImage: Clinical, 44, art. no. 103692, .
Edwards, T.J.a b c , Dean, R.J.a d , Robinson, G.A.a e , Knight, J.e , Mandelstam, S.A.f , Richards, L.J.a d g
a Queensland Brain Institute, The University of Queensland, St Lucia, QLD 4072, Australia
b Faculty of Medicine, The University of Queensland, Herston, QLD 4006, Australia
c Metro South Addiction and Mental Health Services, Brisbane, QLD, Australia
d Washington University in St Louis Medical School, Department of Neuroscience, St Louis, MO, United States
e Neuropsychology Research Unit, School of Psychology, The University of Queensland, St Lucia, QLD 4072, Australia
f Departments of Paediatrics and Radiology, The University of Melbourne, Parkville, VIC 3052, Australia
g School of Biomedical Sciences, The University of Queensland, St Lucia, QLD 4072, Australia
Abstract
Background: Individuals with corpus callosum dysgenesis (CCD) lack the clear disconnection syndrome that is characteristic of individuals in whom the corpus callosum has been surgically severed. One potential explanation for this paradox is that the anterior commissure undergoes neuroplastic remodeling in CCD to improve interhemispheric communication between the brain hemispheres. Methods: A cohort of sixteen individuals with CCD (and sixteen sex and age-matched neurotypical controls) underwent multi-shell diffusion magnetic resonance high-field imaging (dMRI) at 7-Tesla to assess the anatomy of the anterior commissure for evidence of neuroplasticity. Results: No significant group-wise differences in midsagittal anterior commissure volumes were detected between the CCD and control cohorts, although there were CCD individuals within the cohort who exhibited volumes that were either substantially larger or smaller than their neurotypical counterparts. Axonal intracellular volume fractions were reduced across the CCD white matter, including regions of the anterior commissure, and tractographic analyses were unable to identify any novel connections projecting through the anterior commissure that were unique to CCD individuals. Finally, variances in the neuroanatomy of the anterior commissure in the CCD cohort did not correlate with performance on neuropsychological tasks that are highly dependent upon interhemispheric communication. Conclusions: The results of this study indicate that there are individuals within the CCD population in whom it is unlikely that the anterior commissure is the primary substrate for interhemispheric communication. Consequently, other, presently unknown, compensatory mechanisms are likely involved in supporting this function. © 2024 The Author(s)
Author Keywords
Agenesis of the corpus callosum; Anterior commissure; Corpus callosum dysgenesis; Diffusion magnetic resonance imaging
Document Type: Article
Publication Stage: Final
Source: Scopus
Exploring the Association Between Pediatric Obstructive Sleep Apnea Severity and Quality of Life
(2024) Laryngoscope, .
Ensing, A.E., Getahun, H., Lin, R.Z., Zhang, A.L., Landes, E.K., Lieu, J.E.C.
Department of Otolaryngology – Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO, United States
Abstract
Objectives: To investigate the relationship between pediatric obstructive sleep apnea (OSA) severity and quality of life (QOL). Study Design: This study was a cross-sectional survey. Methods: Patients aged 2–18 years being evaluated for OSA were recruited from a pediatric otolaryngology clinic and sleep center. Participants completed the Obstructive Sleep Apnea Questionnaire (OSA-18) and the PedsQL™ Multidimensional Fatigue Score (MFS). Results: Responses of 18 control participants without OSA, 26 participants with clinically resolved OSA, 19 with non-obstructive sleep disordered breathing (SDB), 29 with mild OSA, 21 with moderate OSA, and 27 with severe OSA were analyzed. OSA-18 scores for controls were lower (indicating higher QOL) than patients with SDB (mean difference [MD] = −31.1; 95% CI −42.7 to −19.5), mild OSA (MD = −30.4; 95% CI −40.1 to −20.7), moderate OSA (MD = −23.6; 95% CI −34.5 to −12.7), or severe OSA (MD = −40.1; 95% CI −50.0 to −30.2). Participants with resolved OSA also had lower OSA-18 scores than participants in the SDB and OSA groups. Few differences were observed between the SDB, mild OSA, moderate OSA, and severe OSA groups on either the OSA-18 or PedsQL MFS, and these did not demonstrate a clear pattern. Linear regression of apnea hypopnea index (AHI) and OSA-18 or PedsQL MFS scores revealed weak relationships (R2 < 0.1). Conclusion: Using both an OSA-specific measure and generic fatigue measure, no consistent differences in QOL scores were found between children with varying OSA severities. Therefore, disease burden in pediatric patients with mild OSA and SDB should not be underestimated. Level of Evidence: Level 3 Laryngoscope, 2024. © 2024 The American Laryngological, Rhinological and Otological Society, Inc.
Author Keywords
children; fatigue; obstructive sleep apnea; quality of life; sleep disordered breathing
Document Type: Article
Publication Stage: Article in Press
Source: Scopus
Negative effect of treatment with mGluR5 negative allosteric modulator AFQ056 on blood biomarkers in young individuals with Fragile X syndrome
(2024) SAGE Open Medicine, 12, .
Protic, D.a b , Breeze, E.c d , Mendoza, G.e , Zafarullah, M.e , Abbeduto, L.d f , Hagerman, R.d g , Coffey, C.h , Cudkowicz, M.i , Durbin-Johnson, B.j , Ashwood, P.c , Berry-Kravis, E.k , Erickson, C.A.l , Filipink, R.m , Gropman, A.n , Lehwald, L.o , Maxwell-Horn, A.p , Morris, S.q , Bennett, A.P.r , Prock, L.s , Talboy, A.t , Tartaglia, N.u , Veenstra-VanderWeele, J.v w x , Tassone, F.d e
a Faculty of Medicine, Department of Pharmacology, Clinical Pharmacology, and Toxicology, University of Belgrade, Belgrade, Serbia
b Fragile X Clinic, Special Hospital for Cerebral Palsy and Developmental Neurology, Belgrade, Serbia
c Department of Medical Microbiology and Immunology, School of Medicine, University of California Davis, Davis, CA, United States
d MIND Institute, University of California Davis, Sacramento, CA, United States
e Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Sacramento, CA, United States
f Department of Psychiatry and Behavioral Sciences, University of California Davis, Sacramento, CA, United States
g Department of Pediatrics, University of California Davis, Sacramento, CA, United States
h Department of Biostatistics, University of Iowa, Iowa CityIA, United States
i Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
j Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, United States
k Department of Pediatrics, Neurological Sciences, Anatomy, and Cell Biology, Rush University Medical Center, Chicago, IL, United States
l Cincinnati Hospital and Medical Center, Cincinnati, OH, United States
m Children’s Hospital of Pittsburgh, Pittsburgh, PA, United States
n Children’s National Medical Center, Washington, DC, United States
o Nationwide Children’s Hospital, Columbus, OH, United States
p Vanderbilt University Medical Center, Nashville, TN, United States
q Washington University Medical Center, Saint Louis Children’s Hospital, St. Louis, MO, United States
r Children’s Hospital of Philadelphia, Philadelphia, PA, United States
s Boston Children’s Hospital, Boston, MA, United States
t Emory University Medical Center, Atlanta, GA, United States
u Children’s Hospital of Colorado, Denver, CO, United States
v Center for Autism and the Developing Brain, New York-Presbyterian, New York, NY, United States
w Department of Psychiatry, Columbia University, New York, NY, United States
x New York State Psychiatric Institute, New York, NY, United States
Abstract
Background: Fragile X syndrome, with an approximate incidence rate of 1 in 4000 males to 1 in 8000 females, is the most prevalent genetic cause of heritable intellectual disability and the most common monogenic cause of autism spectrum disorder. The full mutation of the Fragile X Messenger Ribonucleoprotein-1 gene, characterized by an expansion of CGG trinucleotide repeats (>200 CGG repeats), leads to fragile X syndrome. Currently, there are no targeted treatments available for fragile X syndrome. In a recent large multi-site trial, FXLEARN, the effects of the mGluR5 negative allosteric modulator, AFQ056 (mavoglurant), were investigated, but did not show a significant impact of AFQ056 on language development in children with fragile X syndrome aged 3–6 years. Objectives: The current analyses from biospecimens collected in the FXLEARN study aimed to determine whether AFQ056 affects the level of potential biomarkers associated with Akt/mTOR and matrix metalloproteinase 9 signaling in young individuals with fragile X syndrome. Previous research has indicated that these biomarkers play crucial roles in the pathophysiology of fragile X syndrome. Design: A double-blind placebo-controlled parallel-group flexible-dose forced titration design. Methods: Blood samples for biomarkers were collected during the FXLEARN at baseline and subsequent visits (1- and 8-month visits). Biomarker analyses included fragile X messenger ribonucleoprotein-1 genotyping by Southern blot and PCR approaches, fragile X messenger ribonucleoprotein-1 mRNA levels determined by PCR, matrix metalloproteinase 9 levels’ detection using a magnetic bead panel, and targets of the Akt/mTOR signaling pathway with their phosphorylation levels detected. Results: This research revealed that administering AFQ056 does not affect the expression levels of the investigated blood biomarkers in young children with fragile X syndrome. Conclusion: Our findings of the lack of association between clinical improvement and biomarkers’ levels in the treatment group are in line with the lack of benefit observed in the FXLEARN study. These findings indicate that AFQ056 does not provide benefits as assessed by primary or secondary endpoints. Registration: ClincalTrials.gov NCT02920892. © The Author(s) 2024.
Author Keywords
AFQ056; biomarkers; Fragile X syndrome; MMP-9; mTOR pathway
Funding details
FRAXA Research FoundationFRF
Azrieli Foundation
Science Fund of the Republic of Serbia
National Institutes of HealthNIHU24NS107198, U24NS107199, U01NS077352, U24NS107168, U01NS077323, U24NS107205, U10NS077368, U24NS107128, P50HD103526, U24NS107209, U01NS077179, U01NS096767, U24NS107183, U24NS107166, U24NS107200, U01NS077366
National Institutes of HealthNIH
NovartisAFQ056X2201T, AFQ056
Novartis
Document Type: Article
Publication Stage: Final
Source: Scopus
Axonal damage and inflammation response are biological correlates of decline in small-world values: a cohort study in autosomal dominant Alzheimer’s disease
(2024) Brain Communications, 6 (5), art. no. fcae357, .
Vermunt, L.a b , Sutphen, C.L.c , Dicks, E.a d , de Leeuw, D.M.a , Allegri, R.F.e , Berman, S.B.f , Cash, D.M.g , Chhatwal, J.P.h , Cruchaga, C.c , Day, G.S.i , Ewers, M.j k , Farlow, M.R.l , Fox, N.C.m n , Ghetti, B.o , Graff-Radford, N.R.i , Hassenstab, J.c , Jucker, M.k o , Karch, C.M.c , Kuhle, J.p , Laske, C.k o , Levin, J.k q , Masters, C.L.r s , McDade, E.c , Mori, H.t , Morris, J.C.c , Perrin, R.J.c , Preische, O.k o , Schofield, P.R.u , Suárez-Calvet, M.v w x , Xiong, C.c , Scheltens, P.a y , Teunissen, C.E.b , Visser, P.J.z , Bateman, R.J.c , Benzinger, T.L.S.c , Fagan, A.M.c , Gordon, B.A.c , Tijms, B.M.a , on behalf of the Dominantly Inherited Alzheimer Networkaa
a Alzheimer center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Programme Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, 1081 HZ, Netherlands
b Neurochemistry Laboratory, Departmentt of Laboratory Medicine, Amsterdam Neuroscience, Programme Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, 1081 HZ, Netherlands
c Washington University, School of Medicine, St. Louis, MO 63110, United States
d Department of Neurology, Mayo Clinic, Rochester, MN 55905, United States
e Instituto de Investigaciones Neurológicas FLENI, Buenos Aires, Argentina
f Department of Neurology, Alzheimer’s Disease Research Center, Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA 15213, United States
g Dementia Research Centre, UCL Queen Square Institute of Neurology, London, WC1N 3AR, United Kingdom
h Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, United States
i Mayo Clinic Florida, Jacksonville, FL 32224, United States
j Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilian-University Munich, Munich, 81377, Germany
k German Center for Neurodegenerative Diseases (DZNE), Göttingen, 37075, Germany
l Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN 46202, United States
m Dementia Research Institute at UCL, University College London, Institute of Neurology, London, W1T 7NF, United Kingdom
n Department of Neurodegenerative Disease, Dementia Research Centre, London, WC1N 3AR, United Kingdom
o Section for Dementia Research, Hertie Institute for Clinical Brain Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, 72076, Germany
p Neurologic Clinic and Policlinic, University Hospital, University Basel, Basel, 4031, Switzerland
q Ludwig-Maximilians-Universität München, München, D-80539, Germany
r Florey Institute, Melbourne, VIC 3052, Australia
s The University of Melbourne, Melbourne, VIC 3052, Australia
t Department of Clinical Neuroscience, Osaka City University Medical School, Osaka, 558-8585, Japan
u Neuroscience Research Australia, School of Medical Sciences, Sydney, Sydney, NSW 2052, Australia
v Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, 08005, Spain
w IMIM (Hospital del Mar Medical Research Institute), Barcelona, 08003, Spain
x Servei de Neurologia, Hospital del Mar, Barcelona, 08003, Spain
y Life Science Partners, Amsterdam, 1071 DV, Netherlands
z Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, 6229 ER, Netherlands
Abstract
The grey matter of the brain develops and declines in coordinated patterns during the lifespan. Such covariation patterns of grey matter structure can be quantified as grey matter networks, which can be measured with magnetic resonance imaging. In Alzheimer’s disease, the global organization of grey matter networks becomes more random, which is captured by a decline in the small-world coefficient. Such decline in the small-world value has been robustly associated with cognitive decline across clinical stages of Alzheimer’s disease. The biological mechanisms causing this decline in small-world values remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and small-world coefficient in mutation carriers (N = 219) and non-carriers (N = 136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Amyloid beta, Tau, synaptic (Synaptosome associated protein-25, Neurogranin) and neuronal calcium-sensor protein (Visinin-like protein-1) preceded loss of small-world coefficient by several years, while increased levels in CSF markers for inflammation (Chitinase-3-like protein 1) and axonal injury (Neurofilament light) co-occurred with decreasing small-world values. This suggests that axonal loss and inflammation play a role in structural grey matter network changes. © The Author(s) 2024.
Author Keywords
autosomal dominant Alzheimer disease; axonal damage; inflammation; neuronal injury; structural covariance network
Funding details
GE Healthcare
Deutsches Zentrum für Neurodegenerative ErkrankungenDZNE
Fleni
National Institute on AgingNIA
Korea Health Industry Development InstituteKHIDI
Foundation for Barnes-Jewish HospitalFBJH1S10OD018091–01, 1S10RR022984–01A1, K01 AG053474
Foundation for Barnes-Jewish HospitalFBJH
Japan Agency for Medical Research and DevelopmentAMED17929884, 16815631
Japan Agency for Medical Research and DevelopmentAMED
National Institutes of HealthNIH1S10RR022984–01A1, 1S10OD018091–01
National Institutes of HealthNIH
Document Type: Article
Publication Stage: Final
Source: Scopus
Leveraging Normative Personality Data and Machine Learning to Examine the Brain Structure Correlates of Obsessive-Compulsive Personality Disorder Traits
(2024) Journal of Psychopathology and Clinical Science, 133 (8), pp. 656-666. Cited 1 time.
Moreau, A.L.a , Gorelik, A.J.a , Knodt, A.b , Barch, D.M.a c d , Hariri, A.R.b , Samuel, D.B.e , Oltmanns, T.F.a , Hatoum, A.S.a , Bogdan, R.a
a Department of Psychological and Brain Sciences, Washington University in St. Louis, United States
b Department of Psychology and Neuroscience, Duke University, United States
c Department of Psychiatry, School of Medicine, Washington University in St. Louis, United States
d Department of Radiology, School of Medicine, Washington University in St. Louis, United States
e Department of Psychological Sciences, Purdue University, United States
Abstract
Brain structure correlates of obsessive-compulsive personality disorder (OCPD) remain poorly understood as limited OCPD assessment has precluded well-powered studies. Here, we tested whether machine learning (ML; elastic net regression, gradient boosting machines, support vector regression with linear and radial kernels) could estimate OCPD scores from personality data and whetherML-predicted scores are associated with indices of brain structure (cortical thickness and surface area and subcortical volumes). Among older adults (ns= 898–1,606) who completed multiple OCPD assessments, ML elastic net regression with Revised NEO Personality Inventory personality items as features best predicted Five-Factor Obsessive-Compulsive Inventory—Short Form (FFOCI-SF) scores, root-mean-squared error (RMSE)/SD= 0.66; performance generalized to a sample of college students (n= 175; RMSE/SD= 0.51). Items from all five-factor model personality traits contributed to predicted FFOCI-SF (p-FFOCI-SF) scores; conscientiousness and openness items were the most influential. In college students (n = 1,253), univariate analyses of cortical thickness, surface area, and subcortical volumes revealed only a positive association between p-FFOCISF and right superior frontal gyrus cortical thickness after adjusting for multiple testing (b = 2.21, p =.0014; all other |b|s,1.04; all other ps..009). Multivariate ML models of brain features predicting FFOCI, conscientiousness, and neuroticism performed poorly (RMSE/SDs.1.00). These data reveal that all five-factor model traits contribute to maladaptive OCPD traits and identify greater right superior frontal gyrus cortical thickness as a promising correlate of OCPD for future study. Broadly, this study highlights the utility of ML to estimate unmeasured psychopathology phenotypes in neuroimaging data sets but that our application of ML to neuroimaging may not resolve unreliable associations and small effects characteristic of univariate psychiatric neuroimaging research. © 2024 American Psychological Association
Author Keywords
brain structure; machine learning; magnetic resonance imaging; neuroimaging; obsessive-compulsive personality disorder
Funding details
201102523
Pro00019095, Pro00014717
National Institutes of HealthNIHR01DA033369, R01AG061162, K01AA030083
Document Type: Article
Publication Stage: Final
Source: Scopus
Three Principles for the Utility of Simple Tasks That Assess Elemental Processes in Parsing Heterogeneity
(2024) Journal of Psychopathology and Clinical Science, 133 (8), pp. 690-696. Cited 1 time.
Moussa-Tooks, A.B.a b c d , Barch, D.M.e , Hetrick, W.P.a b f
a Department of Psychological and Brain Sciences, Indiana University Bloomington, United States
b Program in Neuroscience, Indiana University Bloomington, United States
c Program in Cognitive Science, Indiana University Bloomington, United States
d Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, United States
e Department of Psychological Science, Washington University in St. Louis, United States
f Department of Psychiatry, Indiana University School of Medicine, United States
Abstract
As clinical psychological science and biological psychiatry push to assess, model, and integrate heterogeneity and individual differences, approaches leveraging computational modeling, translational methods, and dimensional approaches to psychopathology are increasingly useful in establishing brain–behavior relationships. The field is ultimately interested in complex human behavior, and disruptions in such behaviors can arise through many different pathways, leading to heterogeneity in etiology for seemingly similar presentations. Parsing this complexity may be enhanced using “simple” tasks—which we define as those assaying elemental processes that are the building blocks to complexity. Using eyeblink conditioning as one illustrative example, we propose that simple tasks assessing elemental processes can be leveraged by and enhance computational psychiatry and dimensional approaches in service of understanding heterogeneity in psychiatry, especially when these tasks meet three principles: (a) an extensively mapped circuit, (b) clear brain–behavior relationships, and (c) relevance to understanding etiological processes and/or treatment. © 2024 American Psychological Association
Author Keywords
brain–behavior relationships; circuits; computational psychiatry; eyeblink conditioning; tasks
Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMHF31 MH119767, T32 MH103213
National Institute of Mental HealthNIMH
National Institute on Drug AbuseNIDAR01 DA048012
National Institute on Drug AbuseNIDA
Indiana Clinical and Translational Sciences InstituteCTSIUL1 TR002529, TL1 TR002531
Indiana Clinical and Translational Sciences InstituteCTSI
Document Type: Article
Publication Stage: Final
Source: Scopus
Using Machine Learning to Derive Neurobiological Subtypes of General Psychopathology in Late Childhood
(2024) Journal of Psychopathology and Clinical Science, 133 (8), pp. 647-655. Cited 1 time.
Reimann, G.E.a , Dupont, R.M.b , Sotiras, A.c , Earnest, T.c , Jeong, H.J.a , Durham, E.L.a , Archer, C.a , Moore, T.M.d , Lahey, B.B.e f , Kaczkurkin, A.N.a
a Department of Psychology, College of Arts and Science, Vanderbilt University, United States
b Department of Psychology, University of Nevada, Las Vegas, United States
c Department of Radiology and Institute for Informatics, Data Science & Biostatistics, Washington University in St. Louis, United States
d Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States
e Department of Public Health Sciences, University of Chicago, United States
f Department of Psychiatry and Behavioral Neuroscience, University of Chicago, United States
Abstract
Traditional mental health diagnoses rely on symptom-based classifications. Yet this approach can oversimplify clinical presentations as diagnoses often do not adequately map onto neurobiological features. Alternatively, our study used structural imaging data and a semisupervised machine learning technique, heterogeneity through discriminative analysis, to identify neurobiological subtypes in 9- to 10-year-olds with high psychopathology endorsements (n =9,027). Our model revealed two stable neurobiological subtypes (adjusted Rand index =0.38). Subtype 1 showed smaller structural properties, elevated conduct problems and attention-deficit/hyperactivity disorder symptoms, and impaired cognitive performance compared to Subtype 2 and typically developing youth. Subtype 2 had larger structural properties, cognitive abilities comparable to typically developing youth, and elevated internalizing symptoms relative to Subtype 1 and typically developing youth. These subtypes remained stable in their neurobiological characteristics, cognitive ability, and associated psychopathology traits over time. Taken together, our data-driven approach uncovered evidence of neural heterogeneity as demonstrated by structural patterns that map onto divergent profiles of psychopathology symptoms and cognitive performance in youth. © 2024 American Psychological Association
Author Keywords
attention-deficit/hyperactivity disorder; conduct problems; general psychopathology; internalizing; machine learning subtypes
Funding details
National Institute of Mental HealthNIMH
Children’s Hospital of PhiladelphiaCHOP
Brain and Behavior Research FoundationBBRF
American Psychological FoundationAPF
National Institute on Drug AbuseNIDAR00MH117274, R01MH098098, R01MH117014, R01AG067103, T32-MH18921
National Institute on Drug AbuseNIDA
National Science FoundationNSF1937963
National Science FoundationNSF
Vanderbilt UniversityVU230704
Vanderbilt UniversityVU
National Institutes of HealthNIHSCR_015769, U01DA041048, U01DA041120, U01DA051039, U01DA041156, U01DA 041025, U01DA041089, U01DA041148, U01DA041028, U01DA041134, U01DA050988, U01DA041093, U01DA041174, U24DA041123, U01DA051038, U01DA 050987, U01DA051018, U01DA051037, U01DA041106, U24DA041147, U01DA050989, U01DA051016, U01DA041022, U01DA041117
National Institutes of HealthNIH
Document Type: Article
Publication Stage: Final
Source: Scopus