Arts & Sciences Brown School McKelvey School of Engineering School of Medicine Weekly Publications

WashU weekly Neuroscience publications

“Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study” (2022) Nature Communications

Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study(2022) Nature Communications, 13 (1), art. no. 2217, . 

Chen, J.a b c d , Tam, A.a b c d , Kebets, V.a b c d , Orban, C.a b c d , Ooi, L.Q.R.a b c d e , Asplund, C.L.b c d f g h , Marek, S.i , Dosenbach, N.U.F.j k l m , Eickhoff, S.B.n o , Bzdok, D.p q , Holmes, A.J.r , Yeo, B.T.T.a b c d e s

a Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singaporeb Centre for Sleep and Cognition, National University of Singapore, Singapore, Singaporec Centre for Translational MR Research, National University of Singapore, Singapore, Singapored N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singaporee Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singaporef Division of Social Sciences, Yale-NUS College, Singapore, Singaporeg Department of Psychology, National University of Singapore, Singapore, Singaporeh Duke-NUS Medical School, Singapore, Singaporei Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United Statesj Department of Neurology, Washington University School of Medicine, St. Louis, MO, United Statesk Department of Radiology, Washington University School of Medicine, St. Louis, MO, United Statesl Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, United Statesm Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United Statesn Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germanyo Institute of Neuroscience and Medicine, Brain & Behaviours (INM-7), Research Center Jülich, Jülich, Germanyp Department of Biomedical Engineering, Montreal Neurological Institute, McGill University, Montreal, QC, Canadaq Mila – Quebec AI Institute, Montreal, QC, Canadar Yale University, Departments of Psychology and Psychiatry, New Haven, CT, United Statess Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

AbstractHow individual differences in brain network organization track behavioral variability is a fundamental question in systems neuroscience. Recent work suggests that resting-state and task-state functional connectivity can predict specific traits at the individual level. However, most studies focus on single behavioral traits, thus not capturing broader relationships across behaviors. In a large sample of 1858 typically developing children from the Adolescent Brain Cognitive Development (ABCD) study, we show that predictive network features are distinct across the domains of cognitive performance, personality scores and mental health assessments. On the other hand, traits within each behavioral domain are predicted by similar network features. Predictive network features and models generalize to other behavioral measures within the same behavioral domain. Although tasks are known to modulate the functional connectome, predictive network features are similar between resting and task states. Overall, our findings reveal shared brain network features that account for individual variation within broad domains of behavior in childhood. © 2022, The Author(s).

Funding detailsNUHSRO/2020/124/TMR/LOANational Institutes of HealthNIHR01MH120080, U01DA041022, U01DA041025, U01DA041028, U01DA041048, U01DA041089, U01DA041093, U01DA041106, U01DA041117, U01DA041120, U01DA041134, U01DA041148, U01DA041156, U01DA041174, U01DA050987, U01DA050988, U01DA050989, U01DA051016, U01DA051018, U01DA051037, U01DA051038, U01DA051039, U24DA041123, U24DA041147National Medical Research CouncilNMRCOFLCG19May-0035, STaR20nov-0003National Research Foundation SingaporeNRFClass of 2017

Document Type: ArticlePublication Stage: FinalSource: Scopus

“PTSD is associated with impaired event processing and memory for everyday events” (2022) Cognitive Research: Principles and Implications

PTSD is associated with impaired event processing and memory for everyday events(2022) Cognitive Research: Principles and Implications, 7 (1), art. no. 35, . 

Pitts, B.L.a , Eisenberg, M.L.b , Bailey, H.R.a , Zacks, J.M.b

a Department of Psychological Sciences, Kansas State University, 942 Bluemont Hall, 1114 Mid-Campus Dr. North, Manhattan, KS 66503, United Statesb Washington University in St. Louis, St. Louis, MO, United States

AbstractCurrent theories of posttraumatic stress disorder (PTSD) propose that memory abnormalities are central to the development and persistence of symptoms. While the most notable memory disturbances in PTSD involve memory for the trauma itself, individuals often have trouble remembering aspects of everyday life. Further, people with PTSD may have difficulty segmenting ongoing activity into discrete units, which is important for our perception and later memory of the activity. The current study investigated whether PTSD diagnosis and symptom severity predicted event segmentation and memory for everyday activities. To do so, 63 people with PTSD and 64 controls with a trauma history watched, segmented, and recalled videos of everyday activities. Viewers with higher PTSD symptom severity showed lower agreement on locations of event boundaries and recalled fewer fine-grained actions than did those with lower symptom severity. These results suggest that PTSD symptoms alter event segmentation, which may contribute to subsequent memory disturbances. © 2022, The Author(s).

Author KeywordsEvent segmentation;  Memory;  Narrative priming;  PTSD;  Symptom severity

Funding detailsNational Institutes of HealthNIHP20GM113109Defense Advanced Research Projects AgencyDARPAD13AP00009

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Sports- and physical activity-related concussion and mental health among adolescents: Findings from the 2017 and 2019 Youth Risk Behavior Survey” (2022) Psychiatry Research

Sports- and physical activity-related concussion and mental health among adolescents: Findings from the 2017 and 2019 Youth Risk Behavior Survey(2022) Psychiatry Research, 312, art. no. 114542, . 

Ziminski, D.a , Szlyk, H.S.a , Baiden, P.b , Okine, L.c , Onyeaka, H.K.d , Muoghalu, C.e f , Cavazos-Rehg, P.g

a Rutgers, The State University of New Jersey, School of Social Work, 120 Albany St, New Brunswick, NJ 08901, United Statesb The University of Texas at Arlington, School of Social Work, 211 S. Cooper St., Box 19129, TX, Arlington, 76019c University of Southern California, USC Suzanne Dworak-Peck School of Social Work, 669 W 34th St, CA, Los Angeles, 90089d Harvard Medical School, Department of Psychiatry, Massachusetts General Hospital/McLean Hospital, Boston, MA 02115, United Statese Plains Regional Medical Center, New Mexico, NM, Clovis, 88101, Mexicof Duke University School of Medicine, Master of Management in Clinical Informatics, NC27710g Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, Box 8134, MO, St. Louis, 63110

AbstractThis study examined the association between self-reported sports- or physical activity-related concussion and symptoms of depression and suicidal behaviors (suicidal ideation, having a suicide plan, and suicide attempts). This study used data from the 2017 and 2019 Youth Risk Behavior Survey (YRBS), a biennial, school-based, nationally representative survey of U.S. students in grade levels 9 to 12 (N = 14,496). Multivariate logistical regression models assessed the association between self-reported sports-or physical activity-related concussions and suicidal behaviors among students, controlling for a range of demographic and psychosocial variables. Altogether, 13.6% of students reported a sports-or physical activity related concussion in the past 12 months. Among youth, sports-or physical activity related concussions were significantly associated with greater odds of symptoms of depression, suicidal ideation, making a suicide plan, and suicide attempts compared to other youth who did not experience sports- or physical activity-related concussion. Findings highlight increased risk for adverse mental health outcomes among students with sports-or physical activity related concussions. Providing resources for students to engage in physical activity and sports teams may help prevent the onset of depression and suicidal behaviors; however, resources must also be available to monitor any concussions related to these activities to provide support for student emotional well-being. © 2022

Author KeywordsAttempted suicide;  Brain concussion;  Depression;  Physical activity;  Suicidal ideation;  Youth

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Co-Use of Opioids and Sedatives Among Retired National Football League Athletes” (2022) Clinical Journal of Sport Medicine: Official Journal of the Canadian Academy of Sport Medicine

Co-Use of Opioids and Sedatives Among Retired National Football League Athletes(2022) Clinical Journal of Sport Medicine: Official Journal of the Canadian Academy of Sport Medicine, 32 (3), pp. 322-328. 

Mannes, Z.L.a b , Hasin, D.S.a b c , Ben Abdallah, A.d , Cottler, L.B.e

a Department of Epidemiology, Mailman School of Public Health, Columbia UniversityNYb New York State Psychiatric InstituteNYc Department of Psychiatry, College of Physicians and Surgeons, Columbia UniversityNYd Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri; ande Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, FL, United States

AbstractOBJECTIVE: Among the general population, co-use of opioids and sedatives is associated with greater risk of overdose compared with opioid use alone. National Football League (NFL) retirees experience higher rates of opioid use than the general population, although little is known about their co-use with sedatives. The aim of this study was to examine the prevalence and risk factors of opioid and sedative co-use among NFL retirees. DESIGN: Retrospective cohort study. SETTING: Professional American football. PARTICIPANTS: NFL retirees (N = 644). INDEPENDENT VARIABLES: Self-reported concussions, pain intensity, heavy alcohol use, physical and mental health impairment, disability status. MAIN OUTCOME MEASURE: Any past 30-day co-use of opioids and sedatives. RESULTS: Approximately 4.9% of the sample reported past 30-day co-use of opioids and sedatives, although nearly 30% of retirees using opioids also used sedatives. Greater pain was associated with co-use of opioids and sedatives (adjusted odds ratios [aOR] = 1.58; 95% confidence interval [CI] = 1.23-1.98), although retirees with moderate/severe mental health impairment (vs none/mild; aOR = 2.47; 95% CI = 1.04-5.91) and disability (vs no disability; aOR = 1.35; 95% CI = 1.05-1.73) demonstrated greater odds of co-use compared with retirees not using either substance. CONCLUSIONS: Given the high rate of sedative use among participants also using opioids, NFL retirees may be susceptible to the negative health consequences associated with co-use. Interventions focused on improving pain and mental health may be especially effective for reducing co-use of these substances among NFL retirees. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“The Effectiveness of Fluoroscopically Guided Genicular Nerve Radiofrequency Ablation for the Treatment of Chronic Knee Pain Due to Osteoarthritis: A Systematic Review” (2022) American Journal of Physical Medicine & Rehabilitation

The Effectiveness of Fluoroscopically Guided Genicular Nerve Radiofrequency Ablation for the Treatment of Chronic Knee Pain Due to Osteoarthritis: A Systematic Review(2022) American Journal of Physical Medicine & Rehabilitation, 101 (5), pp. 482-492. 

Fogarty, A.E., Burnham, T., Kuo, K., Tate, Q., Sperry, B.P., Cheney, C., Walega, D.R., Kohan, L., Cohen, S.P., Cushman, D.M., McCormick, Z.L., Conger, A.

From the Division of Physical Medicine and Rehabilitation, Department of Neurology, Washington University School of Medicine, St Louis, Missouri (AEF); Division of Physical Medicine and Rehabilitation, Department of Orthopedics, University of Utah, Salt Lake City, Utah (TB, KK, QT, CC, DMC, ZLM, AC); University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, California (BPS); Department of Anaesthesiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois (DRW); Division of Pain Management, Department of Anaesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia (LK); Pain Management Division, Department of Anesthesiology and Critical Care Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland (SPC); and Department of Surgery, Walter Reed Army Medical Center, Washington, DC (SPC)

AbstractABSTRACT: The objective was to determine the effectiveness of fluoroscopically guided genicular nerve radiofrequency ablation for painful knee osteoarthritis. Primary outcome measure was improvement in pain after 6 mos. Secondary outcomes included the Oxford Knee Score and Western Ontario and McMaster Universities Osteoarthritis Index. Two reviewers independently assessed publications before October 10, 2020. The Cochrane Risk of Bias Tool and Grades of Recommendation, Assessment, Development, and Evaluation system were used. One hundred ninety-nine publications were screened, and nine were included. Six-month success rates for 50% or greater pain relief after radiofrequency ablation ranged from 49% to 74%. When compared with intra-articular steroid injection, the probability of success was 4.5 times higher for radiofrequency ablation (relative risk = 4.58 [95% confidence interval = 2.61-8.04]). When radiofrequency ablation was compared with hyaluronic acid injection, the probability of treatment success was 1.8 times higher (relative risk = 1.88, 95% confidence interval = 1.38-2.57). The group mean Oxford Knee Score and Western Ontario and McMaster Universities Osteoarthritis Index scores improved in participants receiving genicular radiofrequency ablation compared with intra-articular steroid injection and hyaluronic acid injection. According to Grades of Recommendation, Assessment, Development, and Evaluation, there is moderate-quality evidence that fluoroscopically guided genicular radiofrequency ablation is effective for reducing pain associated with knee osteoarthritis at minimum of 6 mos. Further research is likely to have an important impact on the current understanding of the long-term effectiveness of this treatment. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Cardiac and pulmonary findings in dysferlinopathy: A 3-year, longitudinal study” (2022) Muscle & Nerve

Cardiac and pulmonary findings in dysferlinopathy: A 3-year, longitudinal study(2022) Muscle & Nerve, 65 (5), pp. 531-540. 

Moore, U.a , Fernandez-Torron, R.a b , Jacobs, M.c d , Gordish-Dressman, H.c d , Diaz-Manera, J.e f , James, M.K.a , Mayhew, A.G.a , Harris, E.a , Guglieri, M.a , Rufibach, L.E.g , Feng, J.c , Blamire, A.M.h , Carlier, P.G.i , Spuler, S.j , Day, J.W.k , Jones, K.J.l , Bharucha-Goebel, D.X.m n , Salort-Campana, E.o , Pestronk, A.p , Walter, M.C.q , Paradas, C.r , Stojkovic, T.s , Mori-Yoshimura, M.t , Bravver, E.u , Pegoraro, E.v , Lowes, L.P.w , Mendell, J.R.w , Bushby, K.a , Bourke, J.x , Straub, V.a , Jain COS Consortiumy

a John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdomb Neurology Department, Biodonostia Health Research Institute, Neuromuscular Area, Hospital Donostia, Basque Health Service, Donostia-San Sebastian, Spainc Center for Translational Science, Division of Biostatistics and Study Methodology, Children’s National Health System, Washington, District of Columbia, USAd Pediatrics, Epidemiology and Biostatistics, George Washington University, Washington, District of Columbia, USAe Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), Barcelona, Spainf Neuromuscular Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spaing Jain Foundation, Seattle, WA, United Statesh Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdomi University Paris-Saclay, CEA, DRF, Service Hospitalier Frederic Joliot, Orsay, Francej Charite Muscle Research Unit, Experimental and Clinical Research Center, joint cooperation of the Charité Medical Faculty and the Max Delbrück Center for Molecular MedicineBerlin, Germanyk Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United Statesl Children’s Hospital at Westmead, The University of Sydney, WestmeadNSW, Australiam Department of Neurology Children’s National Health System, Washington, District of Columbia, USAn National Institutes of Health (NINDS), Bethesda, MD, United Stateso Service des maladies neuromusculaire et de la SLA, Hôpital de La Timone, Marseille, Francep Department of Neurology Washington University School of Medicine, St. Louis, MO, United Statesq Friedrich-Baur-Institute, Department of Neurology, Ludwig-Maximilians-University of Munich, Munich, Germanyr Neuromuscular Unit, Department of Neurology, Hospital U. Virgen del Rocío/Instituto de Biomedicina de Sevilla, Seville, Spains Centre de référence des maladies neuromusculaires, Institut de Myologie, AP-HP, Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, Francet Department of Neurology, National Center Hospital, National Center of Neurology and PsychiatryTokyo, Japanu Neuroscience Institute, Carolinas Neuromuscular/ALS-MDA Center, Carolinas HealthCare System, Charlotte, North Carolina, USAv Department of Neuroscience, University of Padova, Padua, Italyw Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH, United Statesx Department of Cardiology, Freeman Hospital, NUTH NHS Hospitals Foundation Trust, Newcastle upon Tyne, United Kingdom

AbstractINTRODUCTION/AIMS: There is debate about whether and to what extent either respiratory or cardiac dysfunction occurs in patients with dysferlinopathy. This study aimed to establish definitively whether dysfunction in either system is part of the dysferlinopathy phenotype. METHODS: As part of the Jain Foundation’s International Clinical Outcome Study (COS) for dysferlinopathy, objective measures of respiratory and cardiac function were collected twice, with a 3-y interval between tests, in 188 genetically confirmed patients aged 11-86 y (53% female). Measures included forced vital capacity (FVC), electrocardiogram (ECG), and echocardiogram (echo). RESULTS: Mean FVC was 90% predicted at baseline, decreasing to 88% at year 3. FVC was less than 80% predicted in 44 patients (24%) at baseline and 48 patients (30%) by year 3, including ambulant participants. ECGs showed P-wave abnormalities indicative of delayed trans-atrial conduction in 58% of patients at baseline, representing a risk for developing atrial flutter or fibrillation. The prevalence of impaired left ventricular function or hypertrophy was comparable to that in the general population. DISCUSSION: These results demonstrate clinically significant respiratory impairment and abnormal atrial conduction in some patients with dysferlinopathy. Therefore, we recommend that annual or biannual follow-up should include FVC measurement, enquiry about arrhythmia symptoms and peripheral pulse palpation to assess cardiac rhythm. However, periodic specialist cardiac review is probably not warranted unless prompted by symptoms or abnormal pulse findings. © 2022 The Authors. Muscle & Nerve published by Wiley Periodicals LLC.

Author Keywordscardiac;  dysferlin;  limb girdle muscular dystrophy R2;  Miyoshi myopathy;  respiratory

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Circadian pacemaker neurons display cophasic rhythms in basal calcium level and in fast calcium fluctuations” (2022) Proceedings of the National Academy of Sciences of the United States of America

Circadian pacemaker neurons display cophasic rhythms in basal calcium level and in fast calcium fluctuations(2022) Proceedings of the National Academy of Sciences of the United States of America, 119 (17), pp. e2109969119. 

Liang, X., Holy, T.E., Taghert, P.H.

Department of Neuroscience, Washington University in St. Louis, St. Louis, MO 63110

AbstractSignificanceDaily rhythms in the molecular clock, in calcium, and in electrical activity all interact to support the functions of circadian pacemaker neurons. However, the regulatory mechanisms that unify these properties are not defined. Here, we utilize the cellular resolution of the Drosophila circadian neural circuit with technological improvements in light-sheet imaging. We report that individual Drosophila pacemakers display two cophasic rhythms of daily calcium fluctuations. We previously described the first: slow changes in intracellular calcium. The second involves high-frequency calcium fluctuations that depend on the function of the T-type calcium channel. We propose that the fast rhythms, emerging sequentially across the 24-h day, correspond to spontaneous electrical activity patterns displayed by different pacemaker groups.

Author Keywordscalcium;  circadian rhythms;  Drosophila;  ITPR;  T-type calcium channel

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Inhibition of the enzyme autotaxin reduces cortical excitability and ameliorates the outcome in stroke” (2022) Science Translational Medicine

Inhibition of the enzyme autotaxin reduces cortical excitability and ameliorates the outcome in stroke(2022) Science Translational Medicine, 14 (641), p. eabk0135. 

Bitar, L.a , Uphaus, T.a , Thalman, C.a , Muthuraman, M.a , Gyr, L.b , Ji, H.a c , Domingues, M.a , Endle, H.a c , Groppa, S.a , Steffen, F.a , Koirala, N.a , Fan, W.d , Ibanez, L.e , Heitsch, L.f , Cruchaga, C.e , Lee, J.-M.g , Kloss, F.b , Bittner, S.a , Nitsch, R.h , Zipp, F.a , Vogt, J.a c

a Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, 55131, Germanyb Transfer Group Anti-Infectives, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knoell Institute, Jena, 07745, Germanyc Department of Molecular and Translational Neuroscience, Cologne Excellence Cluster for Stress Responses in Aging-Associated Diseases (CECAD), Center for Molecular Medicine Cologne (CMMC), University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, 50937, Germanyd Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, 55131, Germanye Department of Psychiatry, Department of Neurology, NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USAf Department of Emergency Medicine, Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USAg Department of Neurology, Radiology, and Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, USAh Institute of Translational Neuroscience, Westfälische Wilhelms-Universität Münster48149 Münster, Germany

AbstractStroke penumbra injury caused by excess glutamate is an important factor in determining stroke outcome; however, several therapeutic approaches aiming to rescue the penumbra have failed, likely due to unspecific targeting and persistent excitotoxicity, which continued far beyond the primary stroke event. Synaptic lipid signaling can modulate glutamatergic transmission via presynaptic lysophosphatidic acid (LPA) 2 receptors modulated by the LPA-synthesizing molecule autotaxin (ATX) present in astrocytic perisynaptic processes. Here, we detected long-lasting increases in brain ATX concentrations after experimental stroke. In humans, cerebrospinal fluid ATX concentration was increased up to 14 days after stroke. Using astrocyte-specific deletion and pharmacological inhibition of ATX at different time points after experimental stroke, we showed that inhibition of LPA-related cortical excitability improved stroke outcome. In transgenic mice and in individuals expressing a single-nucleotide polymorphism that increased LPA-related glutamatergic transmission, we found dysregulated synaptic LPA signaling and subsequent negative stroke outcome. Moreover, ATX inhibition in the animal model ameliorated stroke outcome, suggesting that this approach might have translational potential for improving the outcome after stroke.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Plasma Neurofilament Light Chain Levels Are Elevated in Children and Young Adults With Wolfram Syndrome” (2022) Frontiers in Neuroscience

Plasma Neurofilament Light Chain Levels Are Elevated in Children and Young Adults With Wolfram Syndrome(2022) Frontiers in Neuroscience, 16, art. no. 795317, . 

Eisenstein, S.A.a b , Boodram, R.S.a k , Sutphen, C.L.c l , Lugar, H.M.a , Gordon, B.A.b d , Marshall, B.A.e f , Urano, F.g h i , Fagan, A.M.c d j , Hershey, T.a b c

a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United Statesb Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United Statesc Department of Neurology, Washington University School of Medicine, St. Louis, MO, United Statesd Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, United Statese Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United Statesf Department of Cell Biology, Washington University School of Medicine, St. Louis, MO, United Statesg Department of Medicine, Washington University School of Medicine, St. Louis, MO, United Statesh Division of Endocrinology, Metabolism and Lipid Research, Washington University School of Medicine, St. Louis, MO, United Statesi Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United Statesj Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United Statesk University of Missouri–Columbia, School of Medicine, Columbia, MO, United Statesl Wake Forest School of Medicine, Winston-Salem, NC, United States

AbstractWolfram syndrome is a rare disease caused by pathogenic variants in the WFS1 gene with progressive neurodegeneration. As an easily accessible biomarker of progression of neurodegeneration has not yet been found, accurate tracking of the neurodegenerative process over time requires assessment by costly and time-consuming clinical measures and brain magnetic resonance imaging (MRI). A blood-based measure of neurodegeneration, neurofilament light chain (NfL), is relatively inexpensive and can be repeatedly measured at remote sites, standardized, and measured in individuals with MRI contraindications. To determine whether NfL levels may be of use in disease monitoring and reflect disease activity in Wolfram syndrome, plasma NfL levels were compared between children and young adults with Wolfram syndrome (n = 38) and controls composed of their siblings and parents (n = 35) and related to clinical severity and selected brain region volumes within the Wolfram group. NfL levels were higher in the Wolfram group [median (interquartile range) NfL = 11.3 (7.8–13.9) pg/mL] relative to controls [5.6 (4.5–7.4) pg/mL]. Within the Wolfram group, higher NfL levels related to worse visual acuity, color vision and smell identification, smaller brainstem and thalamic volumes, and faster annual rate of decrease in thalamic volume over time. Our findings suggest that plasma NfL levels can be a powerful tool to non-invasively assess underlying neurodegenerative processes in children, adolescents and young adults with Wolfram syndrome. Copyright © 2022 Eisenstein, Boodram, Sutphen, Lugar, Gordon, Marshall, Urano, Fagan and Hershey.

Author Keywordsaxonal injury;  neurodegeneration;  neurofilament light chain;  thalamus;  WFS1 gene;  Wolfram syndrome

Funding detailsNational Institutes of HealthNIHK01 AG053474, R01 DK112921, R01 HD070855, R21 DK113487, U54 HD087011, UH3 TR002065American Diabetes AssociationADAAlzheimer’s AssociationAAUniversity of WashingtonUWP30 DK020579, UL1 RR024992, UL1 TR000448Institute of Clinical and Translational SciencesICTSUL1 TR002345McDonnell Center for Systems Neuroscience

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Probable Cerebral Amyloid Angiopathy-Related Inflammation Associated With Sitravatinib: A Case Report” (2022) Neurology: Clinical Practice

Probable Cerebral Amyloid Angiopathy-Related Inflammation Associated With Sitravatinib: A Case Report(2022) Neurology: Clinical Practice, 12 (2), pp. E4-E6. 

Ray, C., Dionne, K.

Department of Neurology, Washington University School of Medicine., United States

AbstractBackground and ObjectivesWe present the case of a 67-year-old man who developed encephalopathy, headaches, and seizure activity after initiating treatment with the novel tyrosine kinase inhibitor, sitravatinib.MethodsThe patient was identified in routine clinical practice.ResultsBrain MRI revealed lobar microhemorrhages and bihemispheric vasogenic edema. The patient met the criteria for probable cerebral amyloid angiopathy-related inflammation (CAA-ri) and responded favorably to high-dose methylprednisolone.DiscussionThis report of neurologic autoimmunity in a patient receiving sitravatinib opens new lines of inquiry into the pathophysiology of CAA-ri. We emphasize the importance of early recognition and treatment of CAA-ri among patients receiving immunomodulatory chemotherapy. © American Academy of Neurology.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment” (2022) JAMA Network Open

Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment(2022) JAMA Network Open, 5 (4), p. e228392. 

Hu, Y.a , Kirmess, K.M.a , Meyer, M.R.a , Rabinovici, G.D.b , Gatsonis, C.c , Siegel, B.A.d , Whitmer, R.A.e , Apgar, C.f , Hanna, L.c , Kanekiyo, M.g , Kaplow, J.g , Koyama, A.g , Verbel, D.g , Holubasch, M.S.a , Knapik, S.S.a , Connor, J.h , Contois, J.H.a , Jackson, E.N.a , Harpstrite, S.E.a , Bateman, R.J.i , Holtzman, D.M.i , Verghese, P.B.a , Fogelman, I.a , Braunstein, J.B.a , Yarasheski, K.E.a , West, T.a

a 2 N Diagnostics, St Louis, MO, United Statesb Departments of Neurology, Radiology & Biomedical Imaging, University of California, San Francisco, Mexicoc Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, United Statesd Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO, United Statese Department of Public Health Sciences, University of California, Davis, United Statesf American College of Radiology, Reston, VA, United Statesg Eisai, Woodcliff LakeNJh Miami, FL, United Statesi Department of Neurology, Washington University School of Medicine, St Louis, MO, United States

AbstractImportance: The diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. Objective: To determine the clinical performance associated with a diagnostic algorithm incorporating plasma amyloid-β (Aβ) 42:40 ratio, patient age, and apoE proteotype to identify brain amyloid status. Design, Setting, and Participants: This cohort study includes analysis from 2 independent cross-sectional cohort studies: the discovery cohort of the Plasma Test for Amyloidosis Risk Screening (PARIS) study, a prospective add-on to the Imaging Dementia-Evidence for Amyloid Scanning study, including 249 patients from 2018 to 2019, and MissionAD, a dataset of 437 biobanked patient samples obtained at screenings during 2016 to 2019. Data were analyzed from May to November 2020. Exposures: Amyloid detected in blood and by positron emission tomography (PET) imaging. Main Outcomes and Measures: The main outcome was the diagnostic performance of plasma Aβ42:40 ratio, together with apoE proteotype and age, for identifying amyloid PET status, assessed by accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: All 686 participants (mean [SD] age 73.2 [6.3] years; 368 [53.6%] men; 378 participants [55.1%] with amyloid PET findings) had symptoms of mild cognitive impairment or mild dementia. The AUC of plasma Aβ42:40 ratio for PARIS was 0.79 (95% CI, 0.73-0.85) and 0.86 (95% CI, 0.82-0.89) for MissionAD. Ratio cutoffs for Aβ42:40 based on the Youden index were similar between cohorts (PARIS: 0.089; MissionAD: 0.092). A logistic regression model (LRM) incorporating Aβ42:40 ratio, apoE proteotype, and age improved diagnostic performance within each cohort (PARIS: AUC, 0.86 [95% CI, 0.81-0.91]; MissionAD: AUC, 0.89 [95% CI, 0.86-0.92]), and overall accuracy was 78% (95% CI, 72%-83%) for PARIS and 83% (95% CI, 79%-86%) for MissionAD. The model developed on the prospectively collected samples from PARIS performed well on the MissionAD samples (AUC, 0.88 [95% CI, 0.84-0.91]; accuracy, 78% [95% CI, 74%-82%]). Training the LRM on combined cohorts yielded an AUC of 0.88 (95% CI, 0.85-0.91) and accuracy of 81% (95% CI, 78%-84%). The output of this LRM is the Amyloid Probability Score (APS). For clinical use, 2 APS cutoff values were established yielding 3 categories, with low, intermediate, and high likelihood of brain amyloid plaque pathology. Conclusions and Relevance: These findings suggest that this blood biomarker test could allow for distinguishing individuals with brain amyloid-positive PET findings from individuals with amyloid-negative PET findings and serve as an aid for Alzheimer disease diagnosis.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Laser Interstitial Thermal Therapy in Grade 2/3 IDH1/2 Mutant Gliomas: A Preliminary Report and Literature Review” (2022) Current Oncology

Laser Interstitial Thermal Therapy in Grade 2/3 IDH1/2 Mutant Gliomas: A Preliminary Report and Literature Review(2022) Current Oncology, 29 (4), pp. 2550-2563. 

Johnson, G.W.a , Han, R.H.a , Smyth, M.D.b , Leuthardt, E.C.a c , Kim, A.H.a c

a Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO 63110, United Statesb Department of Neurosurgery, Johns Hopkins All Children’s Hospital, St. Petersburg, FL 33701, United Statesc Brain Tumor Center, Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO 63110, United States

AbstractLaser interstitial thermal therapy (LITT) has become an increasingly utilized alternative to surgical resection for the treatment of glioma in patients. However, treatment outcomes in isocitrate dehydrogenase 1 and 2 (IDH1/2) mutant glioma, specifically, have not been reported. The objective of this study was to characterize a single institution’s cohort of IDH1/2 mutant grade 2/3 glioma patients treated with LITT. We collected data on patient presentation, radiographic features, tumor molecular profile, complications, and outcomes. We calculated progression-free survival (PFS) and tested factors for significant association with longer PFS. Overall, 22.7% of our cohort experienced progression at a median follow up of 1.8 years. The three-and five-year estimates of PFS were 72.5% and 54.4%, respectively. This is the first study to characterize outcomes in patients with IDH1/2 mutant glioma after LITT. Our results suggest that LITT is an effective treatment option for IDH1/2 mutant glioma. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Author Keywordsastrocytoma;  glioma;  IDH1 mutation;  IDH2 mutation;  laser interstitial thermal therapy;  oligodendroglioma

Funding detailsAmerican Cancer SocietyACS

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Brain charts for the human lifespan” (2022) Nature

Brain charts for the human lifespan(2022) Nature, 604 (7906), pp. 525-533. Cited 1 time.

Bethlehem, R.A.I.a b , Seidlitz, J.c d e , White, S.R.f g , Vogel, J.W.c h , Anderson, K.M.i , Adamson, C.j k , Adler, S.l , Alexopoulos, G.S.m , Anagnostou, E.n o , Areces-Gonzalez, A.p q , Astle, D.E.r , Auyeung, B.s t , Ayub, M.u v , Bae, J.w , Ball, G.j x , Baron-Cohen, S.s y , Beare, R.j k , Bedford, S.A.s , Benegal, V.z , Beyer, F.aa , Blangero, J.ab , Blesa Cábez, M.ac , Boardman, J.P.ac , Borzage, M.ad , Bosch-Bayard, J.F.ae af , Bourke, N.ag ah , Calhoun, V.D.ai , Chakravarty, M.M.af aj , Chen, C.ak , Chertavian, C.e , Chetelat, G.al , Chong, Y.S.am an , Cole, J.H.ao ap , Corvin, A.aq , Costantino, M.ar as , Courchesne, E.at au , Crivello, F.av , Cropley, V.L.aw , Crosbie, J.ax , Crossley, N.ay az ba , Delarue, M.al , Delorme, R.bb bc , Desrivieres, S.bd , Devenyi, G.A.be bf , Di Biase, M.A.aw bg , Dolan, R.bh bi , Donald, K.A.bj bk , Donohoe, G.bl , Dunlop, K.bm , Edwards, A.D.bn bo bp , Elison, J.T.bq , Ellis, C.T.i br , Elman, J.A.bs , Eyler, L.bt bu , Fair, D.A.bq , Feczko, E.bq , Fletcher, P.C.bv bw , Fonagy, P.bx by , Franz, C.E.bs , Galan-Garcia, L.bz , Gholipour, A.ca , Giedd, J.cb cc , Gilmore, J.H.cd , Glahn, D.C.ce cf , Goodyer, I.M.f , Grant, P.E.cg , Groenewold, N.A.bk ch , Gunning, F.M.ci , Gur, R.E.c e , Gur, R.C.c e , Hammill, C.F.ax cj , Hansson, O.ck cl , Hedden, T.cm cn , Heinz, A.co , Henson, R.N.f r , Heuer, K.cp cq , Hoare, J.cr , Holla, B.cs ct , Holmes, A.J.cu , Holt, R.s , Huang, H.cv cw , Im, K.ce , Ipser, J.cx , Jack, C.R., Jrcy , Jackowski, A.P.cz da , Jia, T.db dc dd , Johnson, K.A.cf de df dg , Jones, P.B.f bw , Jones, D.T.cy dh , Kahn, R.S.di , Karlsson, H.dj dk , Karlsson, L.dj dk , Kawashima, R.dl , Kelley, E.A.dm , Kern, S.dn do , Kim, K.W.dp dq dr ds , Kitzbichler, M.G.f dt , Kremen, W.S.bs , Lalonde, F.du , Landeau, B.al , Lee, S.dv , Lerch, J.dw dx , Lewis, J.D.dy , Li, J.dz , Liao, W.dz , Liston, C.ea , Lombardo, M.V.s eb , Lv, J.aw ec , Lynch, C.bm , Mallard, T.T.ed , Marcelis, M.ee ef , Markello, R.D.eg , Mathias, S.R.ce , Mazoyer, B.av eh , McGuire, P.az , Meaney, M.J.eh ei , Mechelli, A.ej , Medic, N.f , Misic, B.eg , Morgan, S.E.f ek el , Mothersill, D.em en eo , Nigg, J.ep , Ong, M.Q.W.eq , Ortinau, C.er , Ossenkoppele, R.es et , Ouyang, M.cv , Palaniyappan, L.eu , Paly, L.al , Pan, P.M.ev ew , Pantelis, C.ex ey ez , Park, M.M.fa , Paus, T.fb fc , Pausova, Z.ax fd , Paz-Linares, D.p fe , Pichet Binette, A.ff fg , Pierce, K.at , Qian, X.eq , Qiu, J.fh , Qiu, A.fi , Raznahan, A.du , Rittman, T.fj , Rodrigue, A.ce , Rollins, C.K.fk fl , Romero-Garcia, R.f fm , Ronan, L.f , Rosenberg, M.D.fn , Rowitch, D.H.fo , Salum, G.A.fp fq , Satterthwaite, T.D.c h , Schaare, H.L.fr fs , Schachar, R.J.ax , Schultz, A.P.cf de ft , Schumann, G.fu fv , Schöll, M.fw fx fy , Sharp, D.ag fz , Shinohara, R.T.ak ga , Skoog, I.dn do , Smyser, C.D.gb , Sperling, R.A.cf de df , Stein, D.J.gc , Stolicyn, A.gd , Suckling, J.f bw , Sullivan, G.ac , Taki, Y.dl , Thyreau, B.dl , Toro, R.cq ge , Traut, N.ge gf , Tsvetanov, K.A.fj gg , Turk-Browne, N.B.i gh , Tuulari, J.J.dj gi gj , Tzourio, C.gk , Vachon-Presseau, É.gl , Valdes-Sosa, M.J.bz , Valdes-Sosa, P.A.dz gm , Valk, S.L.gn go , van Amelsvoort, T.gp , Vandekar, S.N.gq , Vasung, L.eg , Victoria, L.W.ci , Villeneuve, S.ff fg gr , Villringer, A.aa gs , Vértes, P.E.f el , Wagstyl, K.bi , Wang, Y.S.gt gu gv gw , Warfield, S.K.ca , Warrier, V.f , Westman, E.gx , Westwater, M.L.f , Whalley, H.C.gd , Witte, A.V.aa gs gy , Yang, N.gt gu gv gw , Yeo, B.gz ha hb , Yun, H.hc , Zalesky, A.aw , Zar, H.J.ch hd , Zettergren, A.dn , Zhou, J.H.eq gz he , Ziauddeen, H.f bw hf , Zugman, A.ew hg hh , Zuo, X.N.gs gt gu gv hi , Bullmore, E.T.f , Alexander-Bloch, A.F.c d e , 3R-BRAINhj , AIBLhk , Alzheimer’s Disease Neuroimaging Initiativehl , Alzheimer’s Disease Repository Without Borders Investigatorshm , CALM Teamhn , Cam-CANho , CCNPhp , COBREhq , cVEDAhr , ENIGMA Developmental Brain Age Working Grouphs , Developing Human Connectome Projectht , FinnBrainhu , Harvard Aging Brain Studyhv , IMAGENhw , KNE96hx , Mayo Clinic Study of Aginghy , NSPNhz , PONDia , PREVENT-AD Research Groupib , VETSAic

a Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdomb Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdomc Department of Psychiatry, University of Pennsylvania, PA, Philadelphia, United Statesd Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, PA, Philadelphia, United Statese Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, PA, Philadelphia, United Statesf Department of Psychiatry, University of Cambridge, Cambridge, United Kingdomg MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdomh Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, PA, Philadelphia, United Statesi Department of Psychology, Yale University, CT, New Haven, United Statesj Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC, Australiak Department of Medicine, Monash University, Melbourne, VIC, Australial UCL Great Ormond Street Institute for Child Health, London, United Kingdomm Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell MedicineNY, United Statesn Department of Pediatrics University of Toronto, Toronto, Canadao Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canadap Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, Chinaq University of Pinar del Río “Hermanos Saiz Montes de Oca”Pinar del Río, Cubar MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdoms Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdomt Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, United Kingdomu Queen’s University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canadav University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, United Kingdomw Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Koreax Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australiay Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdomz Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Indiaaa Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germanyab Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, TX, Edinburg, United Statesac MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, United Kingdomad Fetal and Neonatal Institute, Division of Neonatology, Children’s Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USAae McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, QC, Canadaaf McGill University, Montreal, QC, Canadaag Department of Brain Sciences, Imperial College London, London, United Kingdomah Care Research and Technology Centre, Dementia Research Institute, London, United Kingdomai Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, United Statesaj Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, QC, Canadaak Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, Informatics, Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United Statesal Normandie Univ, UNICAEN, INSERM, PhIND “Physiopathology and Imaging of Neurological Disorders”, Institut Blood and Brain @ Caen-Normandie, Caen, Franceam Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singaporean Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singaporeao Centre for Medical Image Computing (CMIC), University College London, London, United Kingdomap Dementia Research Centre (DRC), University College London, London, United Kingdomaq Department of Psychiatry, Trinity College, Dublin, Irelandar Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canadaas Undergraduate program in Neuroscience, McGill University, Montreal, QC, Canadaat Department of Neuroscience, University of California, San Diego, San Diego, CA, USAau Autism Center of Excellence, University of California, San Diego, San Diego, CA, USAav Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, Franceaw Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, VIC, Australiaax Hospital for Sick Children, Toronto, ON, Canadaay Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de ChileSantiago, Chileaz Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdomba Instituto Milenio Intelligent Healthcare EngineeringSantiago, Chilebb Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, Francebc Human Genetics and Cognitive Functions, Institut Pasteur, Paris, Francebd Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdombe Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, QC, Montreal, Canadabf Department of Psychiatry, McGill University, QC, Montreal, Canadabg Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, MA, Boston, United Statesbh Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdombi Wellcome Centre for Human Neuroimaging, London, United Kingdombj Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, Cape Town, South Africabk Neuroscience Institute, University of Cape Town, Cape Town, South Africabl Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Irelandbm Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, NY, NY, United Statesbn Centre for the Developing Brain, King’s College London, London, United Kingdombo Evelina London Children’s Hospital, London, United Kingdombp MRC Centre for Neurodevelopmental Disorders, London, United Kingdombq Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, MN, Minneapolis, United Statesbr Haskins Laboratories, CT, New Haven, United Statesbs Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USAbt Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USAbu Department of Psychiatry, University of California San Diego, Los Angeles, CA, USAbv Department of Psychiatry, University of Cambridge, Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, United Kingdombw Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdombx Department of Clinical, Educational and Health Psychology, University College London, London, United Kingdomby Anna Freud National Centre for Children and Families, London, United Kingdombz Cuban Center for Neuroscience, La Habana, Cubaca Computational Radiology Laboratory, Boston Children’s Hospital, MA, Boston, United Statescb Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USAcc Department of Psychiatry, University of California San Diego, San Diego, CA, USAcd Department of Psychiatry, University of North Carolina, Chapel Hill, United Statesce Department of Psychiatry, Boston Children’s Hospital and Harvard Medical School, MA, Boston, United Statescf Harvard Medical School, MA, Boston, United Statescg Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, MA, Boston, United Statesch Department of Paediatrics and Child Health, Red Cross War Memorial Children’s Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africaci Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, NY, NY, United Statescj Mouse Imaging Centre, Toronto, ON, Canadack Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Swedencl Memory Clinic, Skåne University Hospital, Malmö, Swedencm Department of Neurology, Icahn School of Medicine at Mount Sinai, NY, NY, United Statescn Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, MA, Boston, United Statesco Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus MitteBerlin, Germanycp Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germanycq Université de Paris, Paris, Francecr Department of Psychiatry, University of Cape Town, Cape Town, South Africacs Department of Integrative Medicine, NIMHANS, Bengaluru, Indiact Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, Indiacu Departments of Psychology and Psychiatry, Yale University, CT, New Haven, United Statescv Radiology Research, Children’s Hospital of Philadelphia, PA, Philadelphia, United Statescw Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United Statescx Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africacy Department of Radiology, Mayo Clinic, MN, Rochester, United Statescz Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazilda National Institute of Developmental PsychiatryBeijing, Chinadb Institute of Science and Technology for Brain-Inspired Intelligence, Fudan UniversityShanghai, Chinadc Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of EducationShanghai, Chinadd Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King’s College London, London, United Kingdomde Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, MA, Boston, United Statesdf Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women’s Hospital, MA, Boston, United Statesdg Department of Radiology, Massachusetts General Hospital, MA, Boston, United Statesdh Department of Neurology, Mayo Clinic, MN, Rochester, United Statesdi Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, United Statesdj Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finlanddk Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finlanddl Institute of Development, Aging and Cancer, Tohoku University, Seiryocho ,Aobaku, Sendai, Japandm Queen’s University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canadadn Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Swedendo Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Region Västra Götaland, Gothenburg, Swedendp Department of Brain and Cognitive Sciences, Seoul National University College of Natural SciencesSeoul, South Koreadq Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Koreadr Department of Psychiatry, Seoul National University College of MedicineSeoul, South Koreads Institute of Human Behavioral Medicine, SNU-MRCSeoul, South Koreadt Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdomdu Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, MD, Bethesda, United Statesdv Department of Brain & Cognitive Sciences, Seoul National University College of Natural SciencesSeoul, South Koreadw Department of Medical Biophysics, University of Toronto, Toronto, ON, Canadadx Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdomdy Montreal Neurological Institute, McGill University, Montreal, QC, Canadadz Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, Chinaea Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, NY, NY, United Stateseb Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italyec School of Biomedical Engineering and Brain and Mind Centre, University of Sydney, Sydney, NSW, Australiaed Department of Psychology, University of Texas, TX, Austin, United Statesee Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, Netherlandsef Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, Netherlandseg McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canadaeh Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, QC, Canadaei Singapore Institute for Clinical Sciences, Singaporeej Bordeaux University Hospital, Bordeaux, Franceek Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdomel Alan Turing Institute, London, United Kingdomem Department of Psychology, School of Business, National College of Ireland, Dublin, Irelanden School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Irelandeo Department of Psychiatry, Trinity College Dublin, Dublin, Irelandep Department of Psychiatry, School of Medicine, Oregon Health and Science University, ORPortland, United Stateseq Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singaporeer Department of Pediatrics, Washington University in St Louis, St Louis, MO, USAes Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam, Netherlandset Lund University, Clinical Memory Research Unit, Lund, Swedeneu Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, ON, Canadaev Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazilew National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazilex Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton SouthVIC, Australiaey Melbourne School of Engineering, University of Melbourne, Parkville, VIC, Australiaez Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australiafa Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canadafb Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canadafc Departments of Psychiatry and Psychology, University of Toronto, Toronto, ON, Canadafd Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canadafe Cuban Neuroscience CenterHavana, Cubaff Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, QC, Canadafg Douglas Mental Health University Institute, Montreal, QC, Canadafh School of Psychology, Southwest UniversityChongqing, Chinafi Department of Biomedical Engineering, N.1 Institute for Health, National University of Singapore, Singaporefj Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdomfk Department of Neurology, Harvard Medical School, MA, Boston, United Statesfl Department of Neurology, Boston Children’s Hospital, MA, Boston, United Statesfm Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spainfn Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, United Statesfo Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdomfp Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazilfq National Institute of Developmental Psychiatry (INPD), São Paulo, Brazilfr Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germanyfs Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germanyft Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, MA, Charlestown, United Statesfu Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan UniversityShanghai, Chinafv Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus MitteBerlin, Germanyfw Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Swedenfx Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Swedenfy Dementia Research Centre, University College London, Queen’s Square Institute of Neurology, London, United Kingdomfz Care Research and Technology Centre, UK Dementia Research Institute, London, United Kingdomga Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, Philadelphia, United Statesgb Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USAgc SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africagd Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdomge Department of Neuroscience, Institut Pasteur, Paris, Francegf Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, Francegg Department of Psychology, University of Cambridge, Cambridge, United Kingdomgh Yale University, CT, New Haven, United Statesgi Department of Clinical Medicine, University of Turku, Turku, Finlandgj Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finlandgk Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, Francegl Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, QC, Canadagm Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, QC, Canadagn Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich ,Jülich, Germanygo Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germanygp Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, Netherlandsgq Department of Biostatistics, Vanderbilt University, TN, Nashville, United Statesgr Department of Biostatistics, Vanderbilt University Medical Center, TN, Nashville, United Statesgs Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germanygt State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal UniversityBeijing, Chinagu Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijing, Chinagv National Basic Science Data CenterBeijing, Chinagw Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of SciencesBeijing, Chinagx Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska InstitutetStockholm, Swedengy Faculty of Medicine, University of Leipzig, Leipzig, Germanygz Department of Electrical and Computer Engineering, National University of Singapore, Singaporeha Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singaporehb N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singaporehc Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singaporehd Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, Australiahe Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singaporehf Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdomhg National Institute of Mental Health (NIMH), National Institutes of Health (NIH), MD, Bethesda, United Stateshh Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazilhi Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China

AbstractOver the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. © 2022. The Author(s).

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Usability and Acceptability of Clinical Decision Support Based on the KIIDS-TBI Tool for Children with Mild Traumatic Brain Injuries and Intracranial Injuries” (2022) Applied Clinical Informatics

a Department of Neurological Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO, United Statesb McKelvey School of Engineering, Washington University School of Medicine in St. Louis, St. Louis, MO, United Statesc Department of Emergency Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, United Statesd Brown School of Social Work, Washington University School of Medicine in St. Louis, St. Louis, MO, United Statese Department of Emergency Medicine, University of California Davis, Davis, CA, United Statesf Institute for Informatics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

AbstractBACKGROUND:  The Kids Intracranial Injury Decision Support tool for Traumatic Brain Injury (KIIDS-TBI) tool is a validated risk prediction model for managing children with mild traumatic brain injuries (mTBI) and intracranial injuries. Electronic clinical decision support (CDS) may facilitate the clinical implementation of this evidence-based guidance. OBJECTIVE:  Our objective was to evaluate the acceptability and usability of an electronic CDS tool for managing children with mTBI and intracranial injuries. METHODS:  Emergency medicine and neurosurgery physicians (10 each) from 10 hospitals in the United States were recruited to participate in usability testing of a novel CDS prototype in a simulated electronic health record environment. Testing included a think-aloud protocol, an acceptability and usability survey, and a semi-structured interview. The prototype was updated twice during testing to reflect user feedback. Usability problems recorded in the videos were categorized using content analysis. Interview transcripts were analyzed using thematic analysis. RESULTS:  Among the 20 participants, most worked at teaching hospitals (80%), freestanding children’s hospitals (95%), and level-1 trauma centers (75%). During the two prototype updates, problems with clarity of terminology and navigating through the CDS interface were identified and corrected. Corresponding to these changes, the number of usability problems decreased from 35 in phase 1 to 8 in phase 3 and the number of mistakes made decreased from 18 (phase 1) to 2 (phase 3). Through the survey, participants found the tool easy to use (90%), useful for determining a patient’s level of care (95%), and likely to improve resource use (90%) and patient safety (79%). Interview themes related to the CDS’s ability to support evidence-based decision-making and improve clinical workflow proposed implementation strategies and potential pitfalls. CONCLUSION:  After iterative evaluation and refinement, the KIIDS-TBI CDS tool was found to be highly usable and useful for aiding the management of children with mTBI and intracranial injuries. Thieme. All rights reserved.

Document Type: ArticlePublication Stage: FinalSource: Scopus

“Investigating the combination of plasma amyloid-beta and geroscience biomarkers on the incidence of clinically meaningful cognitive decline in older adults” (2022) GeroScience

Investigating the combination of plasma amyloid-beta and geroscience biomarkers on the incidence of clinically meaningful cognitive decline in older adults(2022) GeroScience, . 

Lu, W.-H.a b , Giudici, K.V.a , Morley, J.E.c , Guyonnet, S.a b , Parini, A.d , Aggarwal, G.c e , Nguyen, A.D.c e , Li, Y.f g , Bateman, R.J.f , Vellas, B.a b , de Souto Barreto, P.a b , Carrié, I.h , Brigitte, L.h , Faisant, C.h , Lala, F.h , Delrieu, J.h , Villars, H.h , Combrouze, E.h , Badufle, C.h , Zueras, A.h , Andrieu, S.h , Cantet, C.h , Morin, C.h , Abellan Van Kan, G.h , Rolland, Y.h , Dupuy, C.h , Caillaud, C.h , Ousset, P.-J.h , Lala, F.h , Willis, S.h , Belleville, S.h , Gilbert, B.h , Fontaine, F.h , Dartigues, J.-F.h , Marcet, I.h , Delva, F.h , Foubert, A.h , Cerda, S.h , Cuffi, M.-N.h , Costes, C.h , Rouaud, O.h , Manckoundia, P.h , Quipourt, V.h , Marilier, S.h , Franon, E.h , Bories, L.h , Pader, M.-L.h , Basset, M.-F.h , Lapoujade, B.h , Faure, V.h , Tong, M.L.Y.h , Malick-Loiseau, C.h , Cazaban-Campistron, E.h , Desclaux, F.h , Blatge, C.h , Dantoine, T.h , Laubarie-Mouret, C.h , Saulnier, I.h , Clément, J.-P.h , Picat, M.-A.h , Bernard-Bourzeix, L.h , Willebois, S.h , Désormais, I.h , Cardinaud, N.h , Bonnefoy, M.h , Livet, P.h , Rebaudet, P.h , Gédéon, C.h , Burdet, C.h , Terracol, F.h , Pesce, A.h , Roth, S.h , Chaillou, S.h , Louchart, S.h , Sudres, K.h , Lebrun, N.h , Barro-Belaygues, N.h , Touchon, J.h , Bennys, K.h , Gabelle, A.h , Romano, A.h , Touati, L.h , Marelli, C.h , Pays, C.h , Robert, P.h , Le Duff, F.h , Gervais, C.h , Gonfrier, S.h , Gasnier, Y.h , Bordes, S.h , Begorre, D.h , Carpuat, C.h , Khales, K.h , Lefebvre, J.-F.h , Idrissi, S.M.E.h , Skolil, P.h , Salles, J.-P.h , Dufouil, C.h , Lehéricy, S.h , Chupin, M.h , Mangin, J.-F.h , Bouhayia, A.h , Allard, M.h , Ricolfi, F.h , Dubois, D.h , Martel, M.P.B.h , Cotton, F.h , Bonafé, A.h , Chanalet, S.h , Hugon, F.h , Bonneville, F.h , Cognard, C.h , Chollet, F.h , Payoux, P.h , Voisin, T.h , Delrieu, J.h , Peiffer, S.h , Hitzel, A.h , Allard, M.h , Zanca, M.h , Monteil, J.h , Darcourt, J.h , Molinier, L.h , Derumeaux, H.h , Costa, N.h , Perret, B.h , Vinel, C.h , Caspar-Bauguil, S.h , Olivier-Abbal, P.h , Coley, N.h , for the MAPT/DSA Grouph

a Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, 31000, Franceb Inserm CERPOP – UMR1295, University of Toulouse III, Toulouse, 31000, Francec Division of Geriatric Medicine, Saint Louis University School of Medicine, St. Louis, MO, United Statesd Institute of Metabolic and Cardiovascular Diseases (I2MC), Inserm UMR 1048, University of Toulouse, Toulouse, 31400, Francee Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, United Statesf Department of Neurology, Washington University School of Medicine, St. Louis, MO, United Statesg Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States

AbstractWe investigated combining a core AD neuropathology measure (plasma amyloid-beta [Aβ] 42/40) with five plasma markers of inflammation, cellular stress, and neurodegeneration to predict cognitive decline. Among 401 participants free of dementia (median [IQR] age, 76 [73–80] years) from the Multidomain Alzheimer Preventive Trial (MAPT), 28 (7.0%) participants developed dementia, and 137 (34.2%) had worsening of clinical dementia rating (CDR) scale over 4 years. In the models utilizing plasma Aβ alone, a tenfold increased risk of incident dementia (nonsignificant) and a fivefold increased risk of worsening CDR were observed as each nature log unit increased in plasma Aβ levels. Models incorporating Aβ plus multiple plasma biomarkers performed similarly to models included Aβ alone in predicting dementia and CDR progression. However, improving Aβ model performance for composite cognitive score (CCS) decline, a proxy of dementia, was observed after including plasma monocyte chemoattractant protein 1 (MCP1) and growth differentiation factor 15 (GDF15) as covariates. Participants with abnormal Aβ, GDF15, and MCP1 presented higher CCS decline (worsening cognitive function) compared to their normal-biomarker counterparts (adjusted β [95% CI], − 0.21 [− 0.35 to − 0.06], p = 0.005). In conclusion, our study found limited added values of multi-biomarkers beyond the basic Aβ models for predicting clinically meaningful cognitive decline among non-demented older adults. However, a combined assessment of inflammatory and cellular stress status with Aβ pathology through measuring plasma biomarkers may improve the evaluation of cognitive performance. © 2022, The Author(s), under exclusive licence to American Aging Association.

Author KeywordsAging;  Alzheimer’s disease;  Amyloid-beta;  Cognitive decline;  Inflammation;  Neurodegeneration

Funding details1901175National Institutes of HealthNIHR56AG061900National Institute on AgingNIAAvid RadiopharmaceuticalsMinistère des Affaires Sociales et de la SantéCentre Hospitalier Universitaire de ToulouseEuropean Regional Development FundERDFANR-18-EURE-0003, MP0022856

Document Type: ArticlePublication Stage: Article in PressSource: Scopus

“Altered Structural and Functional Connectivity of Salience Network in Patients with Classic Trigeminal Neuralgia” (2022) Journal of Pain

Altered Structural and Functional Connectivity of Salience Network in Patients with Classic Trigeminal Neuralgia(2022) Journal of Pain, . 

Xu, H.a , Seminowicz, D.A.b c , Krimmel, S.R.d , Zhang, M.a , Gao, L.e , Wang, Y.a

a Department of Medical Imaging, the First Affiliated Hospital of Xi’an Jiaotong University, Shaanxi, Xi’an, Chinab Department of Neural and Pain Sciences, School of Dentistry, University of Maryland Baltimore, Maryland, Baltimorec Center to Advance Chronic Pain Research, University of Maryland Baltimore, Maryland, Baltimored Department of Neurology, Washington University School of Medicine, Missouri, St. Louise Department of Mechanical Engineering, Xian Jiaotong University, Shaanxi, Xi’an, China

AbstractClassic trigeminal neuralgia (CTN) is a neuropathic pain disorder displaying spontaneously stabbing or electric shock-like paroxysms in the face. Previous research suggests structural and functional abnormalities in brain regions related to sensory and cognitive-affective dimensions of pain contribute to the pathophysiology of CTN. However, few studies to date have investigated how changes in whole-brain functional networks and white matter connectivity are related to CTN. We performed an independent component analysis to examine abnormalities in resting state functional connectivity of large-scale networks in 48 patients with CTN compared to 46 matched healthy participants. Then, diffusion tensor tractography was performed to test whether these alterations of functional connectivity in intrinsic networks were associated with impairment of the white matter tracts connecting them. Distinct patterns of functional connectivity were detected within default mode network, somatosensory network, and salience network (SN) in the CTN group when compared with healthy controls. Furthermore, abnormality of SN was negatively correlated with pain severity. In support of aberrant functional connectivity within SN, structural disintegration was observed in the white matter tract from left anterior insula (aIns) to left anterior cingulate cortex (ACC) in CTN. These results suggest that altered structural and functional connectivity between aIns and ACC may underpin the aberrant SN in patients with CTN and provide an alternative target for clinical interventions. Perspective: This article presents distinctive abnormalities of functional and structural connectivity from aIns to ACC in the patients with CTN, which is associated with pain ratings. This measure could potentially provide an alternative target for clinicians to alleviate this type of intermittent and refractory pain. © 2022 United States Association for the Study of Pain, Inc.

Author KeywordsClassic trigeminal neuralgia;  Diffusion tensor tractography;  Functional MRI;  Pain intensity;  Salience networks

Funding detailsNational Natural Science Foundation of ChinaNSFC82171909Xi’an Jiaotong UniversityXJTUXJTU1AF-CRF-2020-017Shanxi Provincial Key Research and Development Project2021SF-091

Document Type: ArticlePublication Stage: Article in PressSource: Scopus