WashU weekly Neuroscience publications: August 29, 2022

Precision dynamical mapping using topological data analysis reveals a hub-like transition state at rest
(2022) Nature Communications, 13 (1), art. no. 4791, . 

Saggar, M.^a , Shine, J.M.^b , Liégeois, R.^c d , Dosenbach, N.U.F.^e , Fair, D.^f

^a Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
^b Brain and Mind Center, The University of Sydney, Sydney, NSW, Australia
^c Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
^d Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
^e Departments of Neurology, Radiology, Pediatrics and Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, United States
^f Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, United States

Abstract
In the absence of external stimuli, neural activity continuously evolves from one configuration to another. Whether these transitions or explorations follow some underlying arrangement or lack a predictable ordered plan remains to be determined. Here, using fMRI data from highly sampled individuals (~5 hours of resting-state data per individual), we aimed to reveal the rules that govern transitions in brain activity at rest. Our Topological Data Analysis based Mapper approach characterized a highly visited transition state of the brain that acts as a switch between different neural configurations to organize the spontaneous brain activity. Further, while the transition state was characterized by a uniform representation of canonical resting-state networks (RSNs), the periphery of the landscape was dominated by a subject-specific combination of RSNs. Altogether, we revealed rules or principles that organize spontaneous brain activity using a precision dynamics approach. © 2022, The Author(s).

Funding details
51NF40_180888, DA041148, MH096773, MH115357
National Institutes of HealthNIHDP2, K99/R00, MH104605, MH119735, NS088590
NIH Blueprint for Neuroscience Research1U54MH091657
McDonnell Center for Systems Neuroscience
Stanford Maternal and Child Health Research InstituteMCHRI
Jacobs Foundation2016121703

Document Type: Article
Publication Stage: Final
Source: Scopus

A comparison of methods to harmonize cortical thickness measurements across scanners and sites
(2022) NeuroImage, 261, art. no. 119509, . 

Sun, D.^a b bn , Rakesh, G.^a b , Haswell, C.C.^a b , Logue, M.^c d e f , Baird, C.L.^a b , O’Leary, E.N.^g , Cotton, A.S.^g , Xie, H.^g , Tamburrino, M.^g , Chen, T.^g h , Dennis, E.L.^h i j k , Jahanshad, N.ⁱ , Salminen, L.E.ⁱ , Thomopoulos, S.I.ⁱ , Rashid, F.ⁱ , Ching, C.R.K.ⁱ , Koch, S.B.J.^l m , Frijling, J.L.^l , Nawijn, L.^l n , van Zuiden, M.^l , Zhu, X.^o p , Suarez-Jimenez, B.^o p cb , Sierk, A.^q , Walter, H.^q , Manthey, A.^q , Stevens, J.S.^r , Fani, N.^r , van Rooij, S.J.H.^r , Stein, M.^s , Bomyea, J.^s , Koerte, I.K.^h t , Choi, K.^u , van der Werff, S.J.A.^v w , Vermeiren, R.R.J.M.^v , Herzog, J.^x , Lebois, L.A.M.^y z , Baker, J.T.^aa , Olson, E.A.^y ab , Straube, T.^ac , Korgaonkar, M.S.^ad , Andrew, E.^ae , Zhu, Y.^af ag , Li, G.^af ag , Ipser, J.^ah , Hudson, A.R.^ai , Peverill, M.^aj , Sambrook, K.^ak , Gordon, E.^ca , Baugh, L.^ao ap aq , Forster, G.^ao ap ar , Simons, R.M.^ap as , Simons, J.S.^aq as , Magnotta, V.^at , Maron-Katz, A.^au , du Plessis, S.^av , Disner, S.G.^aw ax , Davenport, N.^aw ax , Grupe, D.W.^ay , Nitschke, J.B.^az , deRoon-Cassini, T.A.^ba , Fitzgerald, J.M.^bb , Krystal, J.H.^bc bd , Levy, I.^bc bd , Olff, M.^l be , Veltman, D.J.^bf , Wang, L.^af ag , Neria, Y.^o p , De Bellis, M.D.^bg , Jovanovic, T.^bh , Daniels, J.K.^bi , Shenton, M.^h bj , van de Wee, N.J.A.^v w , Schmahl, C.^x , Kaufman, M.L.^y bk , Rosso, I.M.^y ab , Sponheim, S.R.^aw ax , Hofmann, D.B.^ac , Bryant, R.A.^bl , Fercho, K.A.^{ao ap aq bm} , Stein, D.J.^ah , Mueller, S.C.^ai , Hosseini, B.^bo , Phan, K.L.^bo bp , McLaughlin, K.A.^bq , Davidson, R.J.^ay az br , Larson, C.L.^bs , May, G.^{al am an bt} , Nelson, S.M.^{al am an bt} , Abdallah, C.G.^bc bd , Gomaa, H.^bu , Etkin, A.^au bv , Seedat, S.^av , Harpaz-Rotem, I.^bc bd , Liberzon, I.^bw , van Erp, T.G.M.^bx by , Quidé, Y.^cc cd , Wang, X.^bz , Thompson, P.M.ⁱ , Morey, R.A.^a b

^a Brain Imaging and Analysis Center, Duke University, Durham, NC, United States
^b Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, United States
^c National Center for PTSD, VA Boston Healthcare System, Boston, MA, United States
^d Department of Psychiatry, Boston University School of Medicine, Boston, MA, United States
^e Biomedical Genetics, Boston University School of Medicine, Boston, MA, United States
^f Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
^g Department of Psychiatry, University of Toledo, Toledo, OH, United States
^h Psychiatry Neuroimaging Laboratory, Brigham & Women’s Hospital, Boston, MA, United States
ⁱ Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, United States
^j Department of Neurology, University of Utah, Salt Lake City, UT, United States
^k Stanford Neurodevelopment, Affect, and Psychopathology Laboratory, Stanford, CA, United States
^l Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
^m Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, Netherlands
ⁿ Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, VU University, Amsterdam, Netherlands
^o Department of Psychiatry, Columbia University Medical Center, New York, NY, United States
^p New York State Psychiatric Institute, New York, NY, United States
^q University Medical Centre Charité, Berlin, Germany
^r Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
^s Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
^t Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
^u Health Services Research Center, University of California, San Diego, La Jolla, CA, United States
^v Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
^w Leiden Institute for Brain and Cognition, Leiden, Netherlands
^x Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
^y Department of Psychiatry, Harvard Medical School, Boston, MA, United States
^z Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, United States
^aa Institute for Technology in Psychiatry, McLean Hospital, Harvard University, Belmont, MA, United States
^ab Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, United States
^ac Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
^ad Brain Dynamics Centre, Westmead Institute of Medical Research, University of Sydney, Westmead, NSW, Australia
^ae Department of Psychology, University of Sydney, Westmead, NSW, Australia
^af Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
^ag Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
^ah SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
^ai Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
^aj Department of Psychology, University of Washington, Seattle, WA, United States
^ak Department of Radiology, University of Washington, Seattle, WA, United States
^al Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, United States
^am Department of Psychology and Neuroscience, Baylor University, Waco, TX, United States
^an Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States
^ao Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, United States
^ap Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, United States
^aq Sioux Falls VA Health Care System, Sioux Falls, SD, United States
^ar Brain Health Research Centre, Department of Anatomy, University of Otago, Dunedin, New Zealand
^as Department of Psychology, University of South Dakota, Vermillion, SD, United States
^at Department of Radiology, Psychiatry, and Biomedical Engineering, University of Iowa, Iowa City, IA, United States
^au Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States
^av Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
^aw Minneapolis VA Health Care System, Minneapolis, MN, United States
^ax Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States
^ay Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
^az Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
^ba Department of Surgery, Division of Trauma and Acute Care Surgery, Medical College of Wisconsin, Milwaukee, WI, United States
^bb Department of Psychology, Marquette University, Milwaukee, WI, United States
^bc Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, United States
^bd Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
^be ARQ National Psychotrauma Centre, Diemen, Netherlands
^bf Department of Psychiatry, Amsterdam University Medical Center, location VUMC, Amsterdam, Netherlands
^bg Healthy Childhood Brain Development Developmental Traumatology Research Program, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
^bh Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
^bi Department of Clinical Psychology, University of Groningen, Groningen, Netherlands
^bj VA Boston Healthcare System, Brockton Division, Brockton, MA, United States
^bk Division of Women’s Mental Health, McLean Hospital, Belmont, MA, United States
^bl School of Psychology, University of New South Wales, Sydney, NSW, Australia
^bm Civil Aerospace Medical Institute, US Federal Aviation Administration, Oklahoma City, OK, United States
^bn Department of Psychology, The Education University of Hong Kong, Hong Kong
^bo Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
^bp Mental Health Service Line, Jesse Brown VA Chicago Health Care System, Chicago, IL, United States
^bq Department of Psychology, Harvard University, Cambridge, MA, United States
^br Department of Psychology, University of Wisconsin-Madison, Madison, WI, United States
^bs Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
^bt Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, United States
^bu Department of Psychiatry and Behavioral Health, Pennsylvania State University, Hershey, PA, United States
^bv VA Palo Alto Health Care System, Palo Alto, CA, United States
^bw Department of Psychiatry and Behavioral Science, Texas A&M University, College Station, TX, United States
^bx Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, United States
^by Center for the Neurobiology of Learning and Memory, University of California, IrvineIrvine, CA, United States
^bz Department of Mathematics and Statistics, University of ToledoToledoOH, United States
^ca Department of Radiology, Washington University, St. Louis, MO, United States
^cb Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
^cc School of Psychology, The University of New South Wales, Sydney, NSW, Australia
^cd Neuroscience Research Australia, Randwick, NSW, Australia

Abstract
Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects. © 2022

Author Keywords
ComBat;  ComBat-GAM;  Cortical Thickness;  Data Harmonization;  General Additive Model;  Linear Mixed-Effects Model;  PTSD;  Scanner Effects;  Site Effects

Funding details
110614, 1R21MH102634, R01MH105535, VA CSR&D 1IK2CX001680
K01 MH118467
CX001600 VA CDA
National Science FoundationNSF
National Institutes of HealthNIH01J05415, F32MH109274, R01 MH106574, R01-MH103291, R01MH105355, R01MH113574
U.S. Department of DefenseDODI01RX000622, W81XWH08-2-0159
National Institute of Mental HealthNIMHR01 AA12479, R01 MH61744, T32-MH018931
National Institute on Alcohol Abuse and AlcoholismNIAAAP50
National Institute of Child Health and Human DevelopmentNICHD10/01/08 – 09/30/13, K23MH112873, L30 MH114379, P30-HD003352
Congressionally Directed Medical Research ProgramsCDMRPW81XWH-08-2-0038
U.S. Department of Veterans AffairsVA
Dana FoundationDF
California Department of Fish and GameDFGC06, C07, HD071982, HD085850, M01RR00039, MH071537, MH098212, MJFF 14848, R01AG059874, R01MH117601, R21MH112956, UL1TR000454
Institute for Clinical and Translational Research, University of Wisconsin, MadisonUW ICTR
National Center for Advancing Translational SciencesNCATS
National Alliance for Research on Schizophrenia and DepressionNARSAD1R01MH110483, 1R21 MH098198, P41 EB015922, R01MH105355-01A, R01MH116147, R56AG058854, U54 EB020403, W81XWH-12-2-0012
National Center for PTSD, U.S. Department of Veterans AffairsNCPTSD
National Health and Medical Research CouncilNHMRC1073041, R01 MH111671
National Research FoundationNRF
South African Medical Research CouncilSAMRCRFA-FSP-01-2013/SHARED ROOTS
Department of Science and Technology, Ministry of Science and Technology, Indiaडीएसटी
Deutsche ForschungsgemeinschaftDFG1K1RX002325, 1K2RX002922, 5U01AA021681-08, DA 1222/4-1, K01 MH118428-01, K01-MH122774, K24 DA028773, K24MH71434, K99NS096116, MH101380, R01 MH63407, R01-MH043454, VA RR&D 1IK2RX000709, WA 1539/8-2
ZonMw40-00812-98-10041
Bundesministerium für Bildung und ForschungBMBFRELEASE 01KR1303A

Document Type: Article
Publication Stage: Final
Source: Scopus

Longitudinal Changes in Vision and Retinal Morphology in Wolfram Syndrome
(2022) American Journal of Ophthalmology, 243, pp. 10-18. 

O’Bryhim, B.E.^a , Samara, A.^b c , Chen, L.^c , Hershey, T.^b d e , Tychsen, L.^a f , Hoekel, J.^a

^a John F. Hardesty Department of Ophthalmology and Visual Science, Washington University School of Medicine, and St. Louis Children’s Hospital, St. Louis, Missouri, United States
^b Department of Psychiatry, Washington University School of Medicine, and St. Louis Children’s Hospital, St. Louis, Missouri, United States
^c Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States
^d Department of Neurology, Washington University School of Medicine, and St. Louis Children’s Hospital, St. Louis, Missouri, United States
^e Department of Radiology, Washington University School of Medicine, and St. Louis Children’s Hospital, St. Louis, Missouri, United States
^f Department of Pediatrics, Washington University School of Medicine, and St. Louis Children’s Hospital, St. Louis, Missouri, United States

Abstract
PURPOSE: To report long-term ophthalmic findings in Wolfram syndrome, including rates of visual decline, macular thinning, retinal nerve fiber layer (RNFL) thinning, and outer plexiform layer (OPL) lamination. DESIGN: Single-center, cohort study. METHODS: A total of 38 participants were studied, who underwent a complete ophthalmic examination as well as optical coherence tomography imaging of the macula and nerve on an annual basis. Linear mixed-effects models for longitudinal data were used to examine both fixed and random effects related to visual acuity and optic nerve quadrants of RNFL and macula thickness. RESULTS: Participants completed a mean of 6.44 years of follow-up (range 2-10 years). Visual acuity declined over time in all participants, with a mean slope of 0.059 logMAR/y (95% CI = 0.07-0.05 logMAR/y), although nearly 25% of participants experienced more rapid visual decline. RNFL thickness decreased in superior, inferior, and nasal quadrants (β = −0.5 µm/y, −0.98 µm/y, −0.28 µm/y, respectively). OPL lamination was noted in 3 study participants, 2 of whom had autosomal dominant mutations. CONCLUSIONS: Our study describes the longest and largest natural history study of visual acuity decline and retinal morphometry in Wolfram syndrome to date. Results suggest that there are slower and faster progressing subgroups and that OPL lamination is present in some individuals with this disease. © 2022 Elsevier Inc.

Funding details
National Institutes of HealthNIH5T32DA007261–29, HD070855, U54 HD087011
American Diabetes AssociationADA
University of WashingtonUWDK020579, UL1 RR024992
McDonnell Center for Systems Neuroscience

Document Type: Article
Publication Stage: Final
Source: Scopus

Facial paresis as the first sign in atypical facioscapulohumeral muscular dystrophy
(2022) Otolaryngology Case Reports, 25, art. no. 100468, . 

Wamkpah, N.S.^a , Chi, J.J.^b

^a Department of Otolaryngology-Head and Neck Surgery, Washington University in St. Louis, 660 S. Euclid Avenue, Campus Box 8115, St Louis, MO 63110, United States
^b Division of Facial Plastic & Reconstructive Surgery, Department of Otolaryngology–Head & Neck Surgery, Washington University in St Louis, 660 S. Euclid Avenue, Campus Box 8115, St Louis, MO 63110, United States

Abstract
Background: Facioscapulohumeral muscular dystrophy (FSHD) is the one of the most common types of muscular dystrophy. We present a retrospective case description of a patient with late-onset, atypical FSHD and provide an overview of the clinical history, physical exam findings, diagnosis and treatment of FSHD. Main findings: A 71-year old male with subjective facial weakness and dysarthria presented initially without physical exam findings of paresis and normal diagnostic lab work. Over time, unilateral incomplete facial paresis appeared on physical exam, as well as mild scapular winging. Conclusion: FSHD classically presents with weakness in muscles of the face, shoulder/upper arms, and proximal lower extremities. Diagnosis is challenging and requires a multidisciplinary approach, due to high variability in clinical presentation and timing of symptoms. A supplementary video is provided, demonstrating unilateral midfacial and lip paresis in a 71-year-old male. © 2022 Elsevier Inc.

Author Keywords
Facial palsy;  Facial weakness;  Facioscapulohumeal muscular dystrophy;  FSHD;  Shoulder weakness;  Winged scapula

Funding details
National Institutes of HealthNIH5T32DC000022-30
National Institute on Deafness and Other Communication DisordersNIDCD

Document Type: Article
Publication Stage: Final
Source: Scopus

Amyloid- β and tau deposition influences cognitive and functional decline in Down syndrome
(2022) Neurobiology of Aging, 119, pp. 36-45. 

Grigorova, M.^a , Mak, E.^a , Brown, S.S.G.^a , Beresford-Webb, J.^a , Hong, Y.T.^b , Fryer, T.D.^b , Coles, J.P.^c , Aigbirhio, F.I.^b , Tudorascu, D.^d , Cohen, A.^d , Christian, B.T.^e , Ances, B.^f , Handen, B.L.^d , Laymon, C.M.^g , Klunk, W.E.^d , Clare, I.C.H.^a , Holland, A.J.^a , Zaman, S.H.^a

^a Cambridge Intellectual and Developmental Disabilities Research Group, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
^b Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
^c Department of Medicine, University of Cambridge, Cambridge, United Kingdom
^d Department of Psychiatry, University of Pittsburgh, Pittsburgh, United States
^e Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
^f Department of Neurology, Washington University at St. Louis, St. Louis, WA, United States
^g Department of Radiology and Bioengineering, University of Pittsburgh, Pittsburgh, United States

Abstract
This study investigates whether tau has (i) an independent effect from amyloid-β on changes in cognitive and functional performance and (ii) a synergistic relationship with amyloid-β in the exacerbation of decline in aging Down syndrome (DS). 105 participants with DS underwent baseline PET [18F]-AV1451 and PET [11C]PiB scans to quantify tau deposition in Braak regions II-VI and the Striatum and amyloid-β status respectively. Linear Mixed Effects models were implemented to assess how tau and amyloid-β deposition are related to change over three time points. Tau was a significant independent predictor of cognitive and functional change. The three-way interaction between time, [11C]PiB status and tau was significant in the models of episodic memory and visuospatial cognition. Baseline tau is a significant predictor of cognitive and functional decline, over and above the effect of amyloid-β status. Results suggest a synergistic relationship between amyloid-β status and tau as predictors of change in memory and visuospatial cognition. © 2022 The Authors

Author Keywords
Alzheimer’s disease;  Amyloid-β;  Down syndrome;  PET [11C]PiB;  PET [18F]-AV1451;  Tau

Funding details
National Institute on AgingNIA
National Institute of Child Health and Human DevelopmentNICHDU01AG051406
Alzheimer’s Society443 JF-18- 017, RG9611
Alzheimer’s Research UKARUKARUK-PG2015-23
NIHR Cambridge Biomedical Research CentreBRC-1215-20014

Document Type: Article
Publication Stage: Final
Source: Scopus

Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants
(2022) Human Genetics and Genomics Advances, 3 (4), art. no. 100131, . 

Mukherjee, S.^a f , Cassini, T.A.^k , Hu, N.^h i , Yang, T.^e , Li, B.^a e f , Shen, W.^h , Moth, C.W.^f , Rinker, D.C.^d f , Sheehan, J.H.^f j , Cogan, J.D.^b , Newman, J.H.^c , Hamid, R.^b , Macdonald, R.L.^e h , Roden, D.M.^e g o , Meiler, J.^{d e f g l m n} , Kuenze, G.^d f l , Phillips, J.A.^b , Capra, J.A.^{a f g o p} , Undiagnosed Diseases Network^q

^a Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, United States
^b Department of Pediatrics, Division of Medical Genetics and Genomic Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232, United States
^c Pulmonary Hypertension Center, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States
^d Department of Chemistry, Vanderbilt University, Nashville, TN 37235, United States
^e Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States
^f Center for Structural Biology, Vanderbilt University, Nashville, TN 37235, United States
^g Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, United States
^h Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, United States
ⁱ Department of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, United States
^j John T. Milliken Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States
^k Department of Internal Medicine, National Institutes of Health Clinical Center, Bethesda, MD 20814, United States
^l Institute for Drug Discovery, Leipzig University Medical School, Leipzig, SAC 04103, Germany
^m Department of Chemistry, Leipzig University, Leipzig, SAC 04109, Germany
ⁿ Department of Computer Science, Leipzig University, Leipzig, SAC 04109, Germany
^o Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, United States
^p Bakar Computational Health Sciences Institute and Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94143, United States

Abstract
Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a “personalized structural biology” (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS. © 2022 The Author(s)

Author Keywords
de novo variant;  DEE;  developmental and epileptic encephalopathy;  electrophysiology;  KCNC2;  molecular dynamics simulations;  personalized structural biology;  rare disease;  Undiagnosed Diseases Network;  variant interpretation

Funding details
National Institutes of HealthNIH
American Heart AssociationAHA
Office of Strategic CoordinationOSCR01GM126249, R01LM013434, U01HG007674, U01HG010215-03S1
Vanderbilt UniversityVU

Document Type: Article
Publication Stage: Final
Source: Scopus

Evaluation of Adenosine A2A receptor gene polymorphisms as risk factors of methamphetamine use disorder susceptibility and predictors of craving degree
(2022) Psychiatry Research, 316, art. no. 114790, . 

Wang, H.^a , Ma, Y.^a , Wang, X.^a , Zhang, W.^a , Han, W.^a , Liu, H.^b , Li, M.^c , Xiao, J.^a , Wei, H.^a , Wang, C.^d , Sindhwani, S.^b , Zhang, T.^b , Guan, F.^a , Rice, J.P.^e

^a Department of Forensic Medicine, School of Medicine & Forensics, Xi’an Jiaotong University, Shaanxi, Xi’an, China
^b Department of Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University, Shaanxi, Xi’an, China
^c Department of Ultrasound, the Second Affiliated Hospital, Xi’an Jiaotong University, Shaanxi, Xi’an, China
^d Department of Health Science, Chang’an Drug Rehabilitation Center, Shaanxi, Xi’an, China
^e Department of Psychiatry, School of Medicine, Washington University in St. Louis, United States

Abstract
The adenosine A2A receptor (ADORA2A) is highly expressed in the central nervous system and plays vital roles in drug addiction. In this study, we aimed to explore the susceptibility of ADORA2A to methamphetamine use disorder (MUD) and the craving degree based on a two-stage association analysis. A total of 3,542 (1,216 patients with MUD and 2,326 controls) and 1,740 participants (580 patients with MUD and 1,160 controls) were recruited in discovery and replication stage, respectively. Significant SNPs identified in the discovery stage were genotyped in the replication samples. Serum levels of ADORA2A were measured using enzyme-linked immunosorbent assay kits. The genetic association signal of each SNP was examined using Plink. A linear model was fitted to investigate the relationship between craving scores and genotypes of significant SNPs. SNP rs5751876 was significantly associated with MUD in the discovery samples and this association signal was then further replicated in the replication samples. Significant associations were also identified between serum levels of ADORA2A and the genotypes of rs5751876 (P = 0.0002). The craving scores in patients with MUD were strongly correlated with rs5751876 genotypes. Our results suggest that polymorphisms of the ADORA2A gene could affect the susceptibility to MUD and its craving degree. © 2022

Author Keywords
Adenosine A2A receptor gene;  Case-control study;  Craving degree;  Genetic polymorphisms;  Methamphetamine use disorder

Funding details
National Natural Science Foundation of ChinaNSFC31,900,407, 82,171,873, 82,222,031

Document Type: Article
Publication Stage: Final
Source: Scopus

Developmental trajectories of cortical thickness by functional brain network: The roles of pubertal timing and socioeconomic status
(2022) Developmental Cognitive Neuroscience, 57, art. no. 101145, . 

Sanders, A.F.P.^a , Baum, G.L.^b , Harms, M.P.^a , Kandala, S.^a , Bookheimer, S.Y.^c , Dapretto, M.^c , Somerville, L.H.^b , Thomas, K.M.^d , Van Essen, D.C.^f , Yacoub, E.^e , Barch, D.M.^a

^a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Department of Psychology, Harvard University, Cambridge, MA 02138, United States
^c Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, United States
^d Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, United States
^e Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, United States
^f Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
The human cerebral cortex undergoes considerable changes during development, with cortical maturation patterns reflecting regional heterogeneity that generally progresses in a posterior-to-anterior fashion. However, the organizing principles that govern cortical development remain unclear. In the current study, we characterized age-related differences in cortical thickness (CT) as a function of sex, pubertal timing, and two dissociable indices of socioeconomic status (i.e., income-to-needs and maternal education) in the context of functional brain network organization, using a cross-sectional sample (n = 789) diverse in race, ethnicity, and socioeconomic status from the Lifespan Human Connectome Project in Development (HCP-D). We found that CT generally followed a linear decline from 5 to 21 years of age, except for three functional networks that displayed nonlinear trajectories. We found no main effect of sex or age by sex interaction for any network. Earlier pubertal timing was associated with reduced mean CT and CT in seven networks. We also found a significant age by maternal education interaction for mean CT across cortex and CT in the dorsal attention network, where higher levels of maternal education were associated with steeper age-related decreases in CT. Taken together, our results suggest that these biological and environmental variations may impact the emerging functional connectome. © 2022

Author Keywords
Brain development;  Brain networks;  Cortical thickness;  HCP;  Puberty;  Socioeconomic status

Funding details
1R24MH122820-01
National Institutes of HealthNIHT32 MH100019
National Institute of Mental HealthNIMH5R24MH108315-05, U01MH109589

Document Type: Article
Publication Stage: Final
Source: Scopus

Natural trajectory of recovery of COVID-19 associated olfactory loss
(2022) American Journal of Otolaryngology – Head and Neck Medicine and Surgery, 43 (5), art. no. 103572, . 

Khan, A.M.^a , Lee, J.^a , Rammaha, T.^a , Gupta, S.^b , Smith, H.^c , Kannampallil, T.^d , Farrell, N.^e , Kallogjeri, D.^a , Piccirillo, J.F.^a

^a Clinical Outcomes Research Office, Department of Otolaryngology-Head and Neck Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^b Medical College of Georgia – Augusta University, Augusta, GA, United States
^c New York Medical College, Valhalla, NY, United States
^d Department of Anesthesiology and Institute for Informatics, Washington University School of Medicine in St. Louis, United States
^e Division of Rhinology, Department of Otolaryngology-Head & Neck Surgery, Washington University School of Medicine in St. Louis, United States

Abstract
Importance: Prevalence of post-viral olfactory loss has increased dramatically due to the frequency and severity of olfactory dysfunction associated with infection by the SARS-CoV-2 virus. Objective: To determine the trajectory of COVID-19 olfactory loss over a six-month period. A key secondary objective is to assess predictive factors associated with the recovery of olfaction. Design: Longitudinal repeated-measures study that enrolled from May 5, 2020 to February 2, 2021, with the last date of data collection on June 15, 2021. Setting: Barnes-Jewish HealthCare/Washington University School of Medicine facilities (Saint Louis, Missouri, USA). Participants: Individuals who tested positive for SARS-CoV-2 by real-time polymerase chain reaction on nasopharyngeal swab and indicated olfactory loss on COVID-19 screening questionnaire. Individuals were excluded if they had previously diagnosed history of olfactory loss, neurodegenerative disorders, <18 years of age, admitted to hospital service, unable to read, write, and understand English, or lacked computer or internet access. Interventions/exposures: Watch and wait for spontaneous recovery. Main outcome(s) and measure(s): Participants completed olfactory assessments every 30 days for six months. Each assessment consisted of the University of Pennsylvania Smell Identification Test (UPSIT), an objective “scratch-and-sniff” test, and Clinical Global Impressions (CGI), a subjective Likert rating scale. Results: The mean age was 41 years old (SD = 16). 39 (80 %) were female and 42 (86 %) white. At baseline assessment of objective olfaction, 18 (36 %) participants had anosmia or severe hyposmia. Subjective, complete recovery at six months was 81 % (95 % CI 74 % to 88 %). Likelihood of recovery was associated with age <50 years (aHR = 8.1 (95 % CI 1.1 to 64.1)) and mild olfactory loss at baseline (UPSIT = 30–33 for males and 31–34 for females) (aHR 6.2 (95 % CI 1.2 to 33.0)). Conclusions and relevance: The trajectory of olfactory recovery among adults with COVID-19 olfactory loss illustrated rapid recovery within 2–3 weeks of infection, and by six months 81 % had recovered based on self-report. Age <50 years old and mild severity of olfactory loss at baseline were associated with increased likelihood of recovery of olfaction. These findings can be used to inform shared decision-making with patients. © 2022 Elsevier Inc.

Author Keywords
Anosmia;  COVID-19;  Hyposmia;  Olfactory loss;  SARS-CoV-2

Funding details
National Institutes of HealthNIHTL1TR002344
National Center for Advancing Translational SciencesNCATS

Document Type: Article
Publication Stage: Final
Source: Scopus

Neurofibromatosis-1 Gene Mutational Profiles Differ Between Syndromic Disease and Sporadic Cancers
(2022) Neurology: Genetics, 8 (4), art. no. e200003, . 

Bewley, A.F.^a , Akinwe, T.M.^b , Turner, T.N.^b , Gutmann, D.H.^c

^a Departments of Medicine, Washington University, St. Louis, MO, United States
^b Genetics, Washington University, St. Louis, MO, United States
^c Neurology, Washington University, St. Louis, MO, United States

Abstract
ObjectivesVariants in the neurofibromatosis type 1 (NF1) gene are not only responsible for the NF1 cancer predisposition syndrome, but also frequently identified in cancers arising in the general population. While germline variants are pathogenic, it is not known whether those that arise in cancer (somatic variants) are passenger or driver variants. To address this question, we sought to define the landscape of NF1 variants in sporadic cancers.MethodsNF1 variants in sporadic cancers were compiled using data curated on the c-Bio database and compared with published germline variants and Genome Aggregation Database data. Pathogenicity was determined using Polyphen and Sorting Intolerant From Tolerant prediction tools.ResultsThe spectrum of NF1 variants in sporadic tumors differ from those most commonly seen in individuals with NF1. In addition, the type and location of the variants in sporadic cancer differ from germline variants, where a high proportion of missense variants were found. Finally, many of the sporadic cancer NF1 variants were not predicted to be pathogenic.DiscussionTaken together, these findings suggest that a significant proportion of NF1 variants in sporadic cancer may be passenger variants or hypomorphic alleles. Further mechanistic studies are warranted to define their unique roles in nonsyndromic cancer pathobiology. © American Academy of Neurology.

Funding details
National Institutes of HealthNIH1-R35-NS07211-01

Document Type: Article
Publication Stage: Final
Source: Scopus

Cochlear ribbon synapse maturation requires Nlgn1 and Nlgn3
(2022) iScience, 25 (8), art. no. 104803, . 

Ramirez, M.A.^a , Ninoyu, Y.^b , Miller, C.^c , Andrade, L.R.^c , Edassery, S.^a , Bomba-Warczak, E.^a , Ortega, B.^b , Manor, U.^c , Rutherford, M.A.^d , Friedman, R.A.^b , Savas, J.N.^a

^a Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
^b Division of Otolaryngology, Department of Surgery, University of California, San Diego, 9500 Gilman Drive, Mail Code 0666, La Jolla, CA 92093, United States
^c Waitt Advanced Biophotonics Core, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, United States
^d Department of Otolaryngology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States

Abstract
Hearing depends on precise synaptic transmission between cochlear inner hair cells and spiral ganglion neurons through afferent ribbon synapses. Neuroligins (Nlgns) facilitate synapse maturation in the brain, but they have gone unstudied in the cochlea. We report Nlgn3 and Nlgn1 knockout (KO) cochleae have fewer ribbon synapses and have impaired hearing. Nlgn3 KO is more vulnerable to noise trauma with limited activity at high frequencies one day after noise. Furthermore, Nlgn3 KO cochleae have a 5-fold reduction in synapse number compared to wild type after two weeks of recovery. Double KO cochlear phenotypes are more prominent than the KOs, for example, 5-fold smaller synapses, 25% reduction in synapse density, and 30% less synaptic output. These observations indicate Nlgn3 and Nlgn1 are essential to cochlear ribbon synapse maturation and function. © 2022 The Author(s)

Author Keywords
cellular neuroscience;  genomics;  neuroscience;  sensory neuroscience

Funding details
National Science FoundationNSF2014862, R21 DC018237
National Institutes of HealthNIHP30 014195
National Cancer InstituteNCI5R01 DC018566, CCSG P30 CA060553, R00 DC-013805, R01 DC014712, T32 MH067564, W81XWH-19-1-0627
Greenwall FoundationGFM.A.R1, M.A.R2
Northwestern UniversityNU
Australian Biological Resources StudyABRS

Document Type: Article
Publication Stage: Final
Source: Scopus

A central alarm system that gates multi-sensory innate threat cues to the amygdala
(2022) Cell Reports, 40 (7), art. no. 111222, . 

Kang, S.J.^a , Liu, S.^a b , Ye, M.^a , Kim, D.-I.^a , Pao, G.M.^c d , Copits, B.A.^e f , Roberts, B.Z.^g , Lee, K.-F.^a , Bruchas, M.R.^h , Han, S.^a b g

^a Peptide Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
^b Department of Neurobiology, School of Biological Sciences, University of California, San Diego, La Jolla, CA 92093, United States
^c Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
^d Okinawa Institute of Science and Technology Graduate University, 1919-1 Tancha, Onna-son, Okinawa 904-0495, Japan
^e Washington University Pain Center, Washington University School of Medicine, St. Louis, MO 63110, United States
^f Department of Anesthesiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^g Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, United States
^h Center of Excellence in the Neurobiology of Addiction, Pain, and Emotion, Departments of Anesthesiology and Pain Medicine, Pharmacology, University of Washington, Seattle, WA 98195, United States

Abstract
Perception of threats is essential for survival. Previous findings suggest that parallel pathways independently relay innate threat signals from different sensory modalities to multiple brain areas, such as the midbrain and hypothalamus, for immediate avoidance. Yet little is known about whether and how multi-sensory innate threat cues are integrated and conveyed from each sensory modality to the amygdala, a critical brain area for threat perception and learning. Here, we report that neurons expressing calcitonin gene-related peptide (CGRP) in the parvocellular subparafascicular nucleus in the thalamus and external lateral parabrachial nucleus in the brainstem respond to multi-sensory threat cues from various sensory modalities and relay negative valence to the lateral and central amygdala, respectively. Both CGRP populations and their amygdala projections are required for multi-sensory threat perception and aversive memory formation. The identification of unified innate threat pathways may provide insights into developing therapeutic candidates for innate fear-related disorders. © 2022 The Author(s)

Author Keywords
central amygdala;  CGRP;  CP: Neuroscience;  innate threats;  lateral amygdala;  lateral parabrachial nucleus;  multi-sensory;  parvocellular subparafascicular nucleus;  PBel;  SPFp;  threat memory

Funding details
1R01MH111520, R01MH112355
National Institute of Mental HealthNIMH
Mary K. Chapman Foundation
Simons Foundation Autism Research InitiativeSFARI388708

Document Type: Article
Publication Stage: Final
Source: Scopus

Dual ontogeny of disease-associated microglia and disease inflammatory macrophages in aging and neurodegeneration
(2022) Immunity, 55 (8), pp. 1448-1465.e6. 

Silvin, A.^a b , Uderhardt, S.^c d e , Piot, C.^a , Da Mesquita, S.^f g , Yang, K.^a , Geirsdottir, L.^h , Mulder, K.^b , Eyal, D.^h , Liu, Z.ⁱ , Bridlance, C.^j , Thion, M.S.^j , Zhang, X.M.^a , Kong, W.T.^a , Deloger, M.^k , Fontes, V.^c d e , Weiner, A.^h , Ee, R.^a , Dress, R.^a , Hang, J.W.^l , Balachander, A.^a , Chakarov, S.^a i , Malleret, B.^a l , Dunsmore, G.^b , Cexus, O.^b m , Chen, J.^a , Garel, S.^j , Dutertre, C.A.^a b , Amit, I.^h , Kipnis, J.^f n , Ginhoux, F.^a b i o

^a Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, 138648, Singapore
^b INSERM U1015, Gustave Roussy Cancer Campus, Villejuif, 94800, France
^c Department of Medicine 3 – Rheumatology and Immunology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, 91054, Germany
^d Deutsches Zentrum für Immuntherapie, FAU, Erlangen, 91054, Germany
^e Exploratory Research Unit, Optical Imaging Centre Erlangen, FAU, Erlangen, 91058, Germany
^f Department of Neuroscience, Center for Brain Immunology and Glia, University of Virginia, Charlottesville, VA 22908, United States
^g Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, United States
^h Department of Immunology, Weizmann Institute of Science, Rehovot, 76100, Israel
ⁱ Shanghai Institute of Immunology, Department of Immunology and Microbiology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
^j Institut de Biologie de l’Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS, INSERM, PSL Research University, Paris, 75005, France
^k INSERM US23, CNRS UMS 3655, Gustave Roussy Cancer Campus, Villejuif, 94800, France
^l Department of Microbiology and Immunology, Immunology Translational Research Programme, Yong Loo Lin School of Medicine, Immunology Programme, Life Sciences Institute, National University of Singapore, Singapore, 117543, Singapore
^m School Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, United Kingdom
ⁿ Center for Brain Immunology and Glia, Department of Pathology and Immunology, School of Medicine, Washington University in St Louis, St Louis, MO 63110, United States
^o Translational Immunology Institute, SingHealth Duke-NUS Academic Medical Centre, Singapore, 169856, Singapore

Abstract
Brain macrophage populations include parenchymal microglia, border-associated macrophages, and recruited monocyte-derived cells; together, they control brain development and homeostasis but are also implicated in aging pathogenesis and neurodegeneration. The phenotypes, localization, and functions of each population in different contexts have yet to be resolved. We generated a murine brain myeloid scRNA-seq integration to systematically delineate brain macrophage populations. We show that the previously identified disease-associated microglia (DAM) population detected in murine Alzheimer’s disease models actually comprises two ontogenetically and functionally distinct cell lineages: embryonically derived triggering receptor expressed on myeloid cells 2 (TREM2)-dependent DAM expressing a neuroprotective signature and monocyte-derived TREM2-expressing disease inflammatory macrophages (DIMs) accumulating in the brain during aging. These two distinct populations appear to also be conserved in the human brain. Herein, we generate an ontogeny-resolved model of brain myeloid cell heterogeneity in development, homeostasis, and disease and identify cellular targets for the treatment of neurodegeneration. © 2022 Elsevier Inc.

Author Keywords
aging;  Alzheimer’s disease;  disease inflammatory macrophages;  disease-associated microglia;  macrophage;  microglia;  neurodegeneration

Funding details
European Molecular Biology OrganizationEMBO
European Research CouncilERC101039438
Agency for Science, Technology and ResearchA*STARNRFI2017-02, NUHSRO/2018/006/SU/01
National University of SingaporeNUS
Deutsche ForschungsgemeinschaftDFG405969122, 448121430, 448121523
Biomedical Research CouncilBMRCH16/99/b0/011, IAF311006

Document Type: Article
Publication Stage: Final
Source: Scopus

Sensitivity of the Social Behavior Observer Checklist to Early Symptoms of Patients With Frontotemporal Dementia
(2022) Neurology, 99 (5), pp. E488-E499. 

Toller, G.^a , Cobigo, Y.^a , Ljubenkov, P.A.^a , Appleby, B.S.^b , Dickerson, B.C.^c , Domoto-Reilly, K.^d , Fong, J.C.^a , Forsberg, L.K.^e , Gavrilova, R.H.^e , Ghoshal, N.^a , Heuer, H.W.^a , Knopman, D.S.^e , Kornak, J.^f , Lapid, M.I.^g , Litvan, I.^h , Lucente, D.E.^c , MacKenzie, I.R.ⁱ , McGinnis, S.M.^c , Miller, B.L.^a , Pedraza, O.^a , Rojas, J.C.^a , Staffaroni, A.M.^a , Wong, B.^c , Wszolek, Z.K.^a , Boeve, B.F.^e , Boxer, A.L.^j , Rosen, H.J.^k , Rankin, K.P.^l

^a Department of Neurology, Memory and Aging Center, University of California, San Francisco, United States
^b Department of Neurology, Case Western Reserve University, Cleveland, OH, United States
^c Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, United States
^d Department of Neurology, University of Washington, Seattle, United States
^e Department of Neurology, Mayo Clinic, Rochester, MN, United States
^f Department of Neurology, Washington University, St. Louis, MO, United States
^g Department of Epidemiology and Biostatistics, University of California, San Francisco, United States
^h Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
ⁱ Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
^j Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
^k Departments of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, United States
^l Neurology, Mayo Clinic, Jacksonville, FL, United States

Abstract
Background and ObjectivesChanges in social behavior are common symptoms of frontotemporal lobar degeneration (FTLD) and Alzheimer disease syndromes. For early identification of individual patients and differential diagnosis, sensitive clinical measures are required that are able to assess patterns of behaviors and detect syndromic differences in both asymptomatic and symptomatic stages. We investigated whether the examiner-based Social Behavior Observer Checklist (SBOCL) is sensitive to early behavior changes and reflects disease severity within and between neurodegenerative syndromes.MethodsAsymptomatic individuals and patients with neurodegenerative disease were selected from the multisite ALLFTD cohort study. In a sample of participants with at least 1 time point of SBOCL data, we investigated whether the Disorganized, Reactive, and Insensitive subscales of the SBOCL change as a function of disease stage within and between these syndromes. In a longitudinal subsample with both SBOCL and neuroimaging data, we examined whether change over time on each subscale corresponds to progressive gray matter atrophy.ResultsA total of 1,082 FTLD pathogenic variant carriers and noncarriers were enrolled (282 asymptomatic, 341 behavioral variant frontotemporal dementia, 114 semantic and 95 nonfluent variant primary progressive aphasia, 137 progressive supranuclear palsy, and 113 Alzheimer disease syndrome). The Disorganized score increased between asymptomatic to very mild (p = 0.016, estimate =-1.10, 95% CI =-1.99 to-0.22), very mild to mild (p = 0.013, estimate =-1.17, 95% CI =-2.08 to-0.26), and mild to moderate/severe (p < 0.001, estimate =-2.00, 95% CI =-2.55 to-1.45) disease stages in behavioral variant frontotemporal dementia regardless of pathogenic variant status. Asymptomatic GRN pathogenic gene variant carriers showed more reactive behaviors (preoccupation with time: p = 0.001, estimate = 1.11, 95% CI = 1.06 to 1.16; self-consciousness: p = 0.003, estimate = 1.77, 95% CI = 1.52 to 2.01) than asymptomatic noncarriers (estimate = 1.01, 95% CI = 0.98 to 1.03; estimate = 1.31, 95% CI = 1.20 to 1.41). The Insensitive score increased to a clinically abnormal level in advanced stages of behavioral variant frontotemporal dementia (p = 0.003, estimate =-0.73, 95% CI =-1.18 to-0.29). Higher scores on each subscale corresponded with higher caregiver burden (p < 0.001). Greater change over time corresponded to greater fronto-subcortical atrophy in the semantic-appraisal and fronto-parietal intrinsically connected networks.DiscussionThe SBOCL is sensitive to early symptoms and reflects disease severity, with some evidence for progression across asymptomatic and symptomatic stages of FTLD syndromes; thus, it may hold promise for early measurement and monitoring of behavioral symptoms in clinical practice and treatment trials.Classification of EvidenceThis study provides Class II evidence that the SBOCL is sensitive to early behavioral changes in FTLD pathogenic variants and early symptomatic individuals in a highly educated patient cohort. © American Academy of Neurology.

Funding details
BHV3241-301, BHV4157-206
National Institutes of HealthNIH
Centers for Disease Control and PreventionCDC
National Institute on AgingNIA
National Institute of Neurological Disorders and StrokeNINDSU54 NS092089
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
Mayo Clinic
Alzheimer’s AssociationAA
Larry L. Hillblom FoundationLLHF
Bristol-Myers SquibbBMS2R01AG038791-06A, 5P50AG005131-33, P20GM109025, R25NS098999, U01NS090259, U01NS100610, U01NS80818, U19 AG063911-1
Association for Frontotemporal DegenerationAFTD
Eli Lilly and Company
Genentech
Novartis
Roche
Biogen
National Center for Advancing Translational SciencesNCATSP300P1_177667, R01AG029577, U01 AG045390
American Parkinson Disease AssociationAPDA
AbbVie
University of California, San DiegoUCSD
Janssen Pharmaceuticals
Sunovion
School of Public Health, University of California BerkeleyUCB
Parkinson’s FoundationPF
Parkinson Study GroupPSG
Avid Radiopharmaceuticals
Applied Genetic Technologies CorporationAGTC
Quest Diagnostics
Sol Goldman Charitable Trust
Rainwater Charitable FoundationRCF
Albertson Parkinson’s Research FoundationAPRF228PD201, M15-562, M15-563
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungSNF
Eisai

Document Type: Article
Publication Stage: Final
Source: Scopus

A multidimensional metabolomics workflow to image biodistribution and evaluate pharmacodynamics in adult zebrafish
(2022) Disease Models & Mechanisms, 15 (8), . 

Jackstadt, M.M.^a b c , Chamberlain, C.A.^a , Doonan, S.R.^a , Shriver, L.P.^a b c , Patti, G.J.^a b c d

^a Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63130, United States
^b Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, United States
^c Center for Metabolomics and Isotope Tracing, Washington University in St. Louis, St. Louis, MO 63130, United States
^d Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110, United States

Abstract
An integrated evaluation of the tissue distribution and pharmacodynamic properties of a therapeutic is essential for successful translation to the clinic. To date, however, cost-effective methods to measure these parameters at the systems level in model organisms are lacking. Here, we introduce a multidimensional workflow to evaluate drug activity that combines mass spectrometry-based imaging, absolute drug quantitation across different biological matrices, in vivo isotope tracing and global metabolome analysis in the adult zebrafish. As a proof of concept, we quantitatively determined the whole-body distribution of the anti-rheumatic agent hydroxychloroquine sulfate (HCQ) and measured the systemic metabolic impacts of drug treatment. We found that HCQ distributed to most organs in the adult zebrafish 24 h after addition of the drug to water, with the highest accumulation of both the drug and its metabolites being in the liver, intestine and kidney. Interestingly, HCQ treatment induced organ-specific alterations in metabolism. In the brain, for example, HCQ uniquely elevated pyruvate carboxylase activity to support increased synthesis of the neuronal metabolite, N-acetylaspartate. Taken together, this work validates a multidimensional metabolomics platform for evaluating the mode of action of a drug and its potential off-target effects in the adult zebrafish. This article has an associated First Person interview with the first author of the paper. © 2022. Published by The Company of Biologists Ltd.

Author Keywords
Drug discovery;  Mass spectrometry imaging;  Metabolomics;  Pharmacodynamics;  Zebrafish

Document Type: Article
Publication Stage: Final
Source: Scopus

Sequential Interventions for Major Depression and Heart Failure Self-Care: A Randomized Clinical Trial
(2022) Circulation: Heart Failure, 15 (8), pp. 745-754. 

Freedland, K.E.^a , Skala, J.A.^a , Carney, R.M.^a , Steinmeyer, B.C.^a , Rubin, E.H.^a , Rich, M.W.^b

^a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^b Cardiovascular Division of the Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Background: Major depression and inadequate self-care are common in patients with heart failure (HF). Little is known about how to intervene when both problems are present. This study examined the efficacy of a sequential approach to treating these problems. Methods: Stepped Care for Depression in HF was a single-site, single-blind, randomized controlled trial of cognitive behavior therapy (CBT) versus usual care (UC) for major depression in patients with HF. The intensive phase of the CBT intervention lasted between 8 and 16 weeks, depending upon the rate of improvement in depression. All participants received a tailored HF self-care intervention that began 8 weeks after randomization. The intensive phase of the self-care intervention ended at 16 weeks post-randomization. The coprimary outcome measures were the Beck Depression Inventory (version 2) and the Maintenance scale of the Self-Care of HF Index (v6.2) at week 16. Results: One hundred thirty-nine patients with HF and major depression were enrolled; 70 were randomized to UC and 69 to CBT. At week 16, the patients in the CBT arm scored 4.0 points ([95% CI, -7.3 to -0.8]; P=0.02) lower on the Beck Depression Inventory, version 2 than those in the usual care arm. Mean scores on the Self-Care of HF Index Maintenance scale were not significantly different between the groups ([95% CI, -6.5 to 1.5]; P=0.22). Conclusions: CBT is more effective than usual care for major depression in patients with HF. However, initiating CBT before starting a tailored HF self-care intervention does not increase the benefit of the self-care intervention. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02997865. © 2022 Lippincott Williams and Wilkins. All rights reserved.

Author Keywords
cognitive behavioral therapy;  depression;  depressive disorder;  heart failure;  self-care;  self-management

Funding details
National Heart, Lung, and Blood InstituteNHLBI

Document Type: Article
Publication Stage: Final
Source: Scopus

Child and Adolescent Abuse Patterns and Incident Obesity Risk in Young Adulthood
(2022) American Journal of Preventive Medicine, . 

Ziobrowski, H.N.^a , Buka, S.L.^b , Austin, S.B.^c d e , Duncan, A.E.^f g , Sullivan, A.J.^h , Horton, N.J.ⁱ , Field, A.E.^b e j

^a Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
^b Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island
^c Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
^d Division of Adolescent/Young Adult Medicine, Boston Children’s Hospital, Boston, Massachusetts
^e Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
^f Brown School, Washington University in St. Louis, St. Louis, Missouri
^g Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
^h Takeda Pharmaceuticals, Cambridge, Massachusetts
ⁱ Department of Mathematics & Statistics, Amherst College, Amherst, Massachusetts
^j Department of Pediatrics, The Warren Alpert Medical School of Brown University, Providence, Rhode Island

Abstract
Introduction: Child abuse is associated with adult obesity. Yet, it is unknown how the developmental timing and combination of abuse types affect this risk. This report examined how distinct child and adolescent abuse patterns were associated with incident obesity in young adulthood. Methods: Data came from 7,273 participants in the Growing Up Today Study, a prospective cohort study in the U.S. with 14 waves from 1996 to 2016 (data were analyzed during 2020–2021). An abuse group variable was empirically derived using latent class analysis with indicators for child (before age 11 years) and adolescent (ages 11–17 years) physical, sexual, and emotional abuse. Risk ratios for obesity developing during ages 18–30 years were estimated using modified Poisson models. Associations of abuse groups with BMI across ages 18–30 years were then examined using mixed-effects models. All models were stratified by sex. Results: Among women, groups characterized by abuse had higher BMIs entering young adulthood and greater changes in BMI per year across young adulthood. Groups characterized by multiple abuse types and abuse sustained across childhood and adolescence had approximately twice the risk of obesity as that of women in a no/low abuse group. Associations were substantially weaker among men, and only a group characterized by physical and emotional abuse in childhood and adolescence had an elevated obesity risk (risk ratio=1.38; 95% CI=1.04, 1.83). Conclusions: Obesity risk in young adulthood varied by distinct abuse groups for women and less strongly for men. Women who experience complex abuse patterns have the greatest risk of developing obesity in young adulthood. © 2022 American Journal of Preventive Medicine

Funding details
National Institutes of HealthNIHDA033974, DK46200, DK59570, HD049889, HD066963, HL68041, MH087786, OH0098003, U01HL145386
Health Resources and Services AdministrationHRSAT76MC00001
Maternal and Child Health BureauMCHB

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

Geotemporal analysis of perinatal care changes and maternal mental health: an example from the COVID-19 pandemic
(2022) Archives of Women’s Mental Health, . 

Hendrix, C.L.^a , Werchan, D.^a , Lenniger, C.^a , Ablow, J.C.^b , Amstadter, A.B.^c , Austin, A.^a , Babineau, V.^d , Bogat, G.A.^e , Cioffredi, L.-A.^f , Conradt, E.^g , Crowell, S.E.^g h i , Dumitriu, D.^j , Elliott, A.J.^k l , Fifer, W.^m , Firestein, M.^m , Gao, W.^n o , Gotlib, I.^p , Graham, A.^q , Gregory, K.D.^r , Gustafsson, H.^q , Havens, K.L.^s , Hockett, C.^k l , Howell, B.R.^t u , Humphreys, K.L.^v , Jallo, N.^w , King, L.S.^p , Kinser, P.A.^w , Levendosky, A.A.^e , Lonstein, J.S.^e , Lucchini, M.^m , Marcus, R.ⁿ , Monk, C.^d m , Moyer, S.^c , Muzik, M.^x , Nuttall, A.K.^y , Potter, A.S.^z , Rogers, C.^aa , Salisbury, A.^w , Shuffrey, L.C.^m , Smith, B.A.^{s ab ac ad} , Smyser, C.D.^ae , Smith, L.^af , Sullivan, E.^q , Zhou, J.^s , Brito, N.H.^ag , Thomason, M.E.^a ah ai

^a Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, NY, United States
^b Department of Psychology, University of Oregon, Eugene, OR, United States
^c Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, United States
^d Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, United States
^e Department of Psychology, Michigan State University, East Lansing, MI, United States
^f Hospital Pediatrics, University of Vermont Medical Center, Burlington, VT, United States
^g Department of Psychology, University of Utah, Salt Lake City, UT, United States
^h Department of Psychiatry, University of Utah Medical School, Salt Lake City, UT, United States
ⁱ Department of Obstetrics and Gynecology, University of Utah Medical School, Salt Lake City, UT, United States
^j Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, United States
^k Department of Pediatrics, University of South Dakota School of Medicine, Vermillion, SD, United States
^l Avera Research Institute, Sioux Falls, SD, United States
^m Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
ⁿ Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, United States
^o Biomedical Imaging Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
^p Department of Psychology, Stanford University, Stanford, CA, United States
^q Department of Psychiatry, Oregon Health & Sciences University, Portland, OR, United States
^r Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
^s Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, United States
^t Fralin Biomedical Research Institute at Virginia Tech Carilion, Roanoke, VA, United States
^u Department of Human Development and Family Science, Virginia Tech University, Blacksburg, VA, United States
^v Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, United States
^w School of Nursing, Virginia Commonwealth University, Richmond, VA, United States
^x Department of Psychiatry, University of Michigan Medical Center, Ann Arbor, VA, United States
^y Human Development and Family Studies, Michigan State University, East Lansing, MI, United States
^z Department of Psychiatry, University of Vermont, Burlington, VT, United States
^aa Department of Psychiatry, Washington University Medical School in Saint Louis, Saint Louis, MO, United States
^ab Developmental Neuroscience and Neurogenetics Program, The Saban Research Institute, Los Angeles, CA, United States
^ac Division of Research On Children, Youth, and Families, Childrens Hospital Los Angeles, Los Angeles, CA, United States
^ad Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
^ae Departments of Neurology, Pediatrics, and Radiology, Washington University Medical School in Saint Louis, Saint Louis, MO, United States
^af The Lundquist Institute, Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, United States
^ag Department of Applied Psychology, New York University, New York, NY, United States
^ah Neuroscience Institute, New York University Medical Center, New York, NY, United States
^ai Department of Population Health, New York University Medical Center, New York, NY, United States

Abstract
Our primary objective was to document COVID-19 induced changes to perinatal care across the USA and examine the implication of these changes for maternal mental health. We performed an observational cross-sectional study with convenience sampling using direct patient reports from 1918 postpartum and 3868 pregnant individuals collected between April 2020 and December 2020 from 10 states across the USA. We leverage a subgroup of these participants who gave birth prior to March 2020 to estimate the pre-pandemic prevalence of specific birthing practices as a comparison. Our primary analyses describe the prevalence and timing of perinatal care changes, compare perinatal care changes depending on when and where individuals gave birth, and assess the linkage between perinatal care alterations and maternal anxiety and depressive symptoms. Seventy-eight percent of pregnant participants and 63% of postpartum participants reported at least one change to their perinatal care between March and August 2020. However, the prevalence and nature of specific perinatal care changes occurred unevenly over time and across geographic locations. The separation of infants and mothers immediately after birth and the cancelation of prenatal visits were associated with worsened depression and anxiety symptoms in mothers after controlling for sociodemographic factors, mental health history, number of pregnancy complications, and general stress about the COVID-19 pandemic. Our analyses reveal widespread changes to perinatal care across the US that fluctuated depending on where and when individuals gave birth. Disruptions to perinatal care may also exacerbate mental health concerns, so focused treatments that can mitigate the negative psychiatric sequelae of interrupted care are warranted. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.

Author Keywords
Coronavirus;  Depression;  Mental health;  Postpartum;  Pregnancy;  Prenatal care

Funding details
R34DA050255, R34DA050255-01S2
National Institutes of HealthNIHKL2TR003016, UL1TR003015
National Center for Advancing Translational SciencesNCATS
Virginia Commonwealth UniversityVCU5R03HD096141-02, R01HD085990, R34DA050283-01S2
Center for Clinical and Translational Science, University of UtahCCTS
Nathaniel Wharton FundNWF
Stanford Institute for Research in the Social SciencesIRiSSR01 DA046224, R01 MH113883, R01MH117177, R01MH119070, R21 HD090493, R21 MH111978, R34 DA050272-01S1, R34DA050291, R37 MH10149, UH3OD023279, UL1TR001881
School of Medicine, Virginia Commonwealth University

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

Development of an acellular nerve cap xenograft for neuroma prevention
(2022) Journal of Biomedical Materials Research – Part A, . 

Faust, A.E.^a , Soletti, L.^a , Cwalina, N.A.^a , Miller, A.D.^b , Wood, M.D.^c , Mahan, M.A.^d , Cheetham, J.^a e f , Brown, B.N.^a f g

^a Renerva, LLC, Pittsburgh, PA, United States
^b Department of Biomedical Sciences, Section of Anatomic Pathology, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States
^c Division of Plastic and Reconstructive Surgery, Department of Surgery, Washington University, St. Louis School of Medicine, St. Louis, MO, United States
^d Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, United States
^e Department of Clinical Sciences, Cornell College of Veterinary Medicine, Cornell University, Ithaca, NY, United States
^f McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
^g Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States

Abstract
Neuroma formation following limb amputation is a prevalent and debilitating condition that can deeply affect quality of life and productivity. Several approaches exist to prevent or treat neuromas; however, no approach is either consistently reliable or surgically facile, with high rates of neuroma occurrence and/or recurrence. The present study describes the development and testing of a xenogeneic nerve cap graft made from decellularized porcine nerve. The grafts were tested in vitro for cellular removal, cytotoxicity, mechanical properties, and morphological characteristics. The grafts were then tested in rat sciatic nerve gap reconstruction and nerve amputation models for 8 weeks. Gross morphology, electrophysiology, and histopathology assessments were performed to determine the ability of the grafts to limit pathologic nerve regrowth. In vitro testing showed well decellularized and demyelinated nerve cap graft structures without any cytotoxicity from residual reagents. The grafts had a proximal socket for the proximal nerve stump and longitudinally oriented internal pores. Mechanical and surgical handling properties suggested suitability for implantation as a nerve graft. Following 8 weeks in vivo, the grafts were well integrated with the proximal and distal nerve segments without evidence of fibrotic adhesions to the surrounding tissues or bulbous outgrowth of the nerve. Electrophysiology revealed absence of nerve conduction within the remodeled nerve cap grafts and significant downstream muscle atrophy. Histologic evaluation showed well organized but limited axonal regrowth within the grafts without fibrous overgrowth or neuromatous hypercellularity. These results provide proof of concept for a novel xenograft-based approach to neuroma prevention. © 2022 Wiley Periodicals LLC.

Author Keywords
acellular;  extracellular matrix;  nerve cap;  neuroma;  xenograft

Funding details
National Science FoundationNSF1913761

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

Return to Learn ECHO: Telementoring for School Personnel to Help Children Return to School and Learning After Mild Traumatic Brain Injury
(2022) Journal of School Health, . 

McAvoy, K.^a , Halstead, M.^b , Radecki, L.^c , Shah, A.^d , Emanuel, A.^e , Domain, S.^e , Daugherty, J.^f , Waltzman, D.^f

^a Brain Injury Educational Consulting Colorado LLC, 631 Peterson Street, Fort Collins, CO 80524, United States
^b Departments of Pediatrics and Orthopedic Surgery, Washington University, 20 Progress Point Parkway, Suite 114, O’Fallon, MO 63368, United States
^c RadeckiResearch LLC, San Diego, CA 92103, United States
^d ECHO Initiatives, American Academy of Pediatrics, 345 Park Blvd, Itasca, IL 60143, United States
^e Child Safety, Health and Wellness, American Academy of Pediatrics, 345 Park Blvd, Itasca, IL 60143, United States
^f Centers for Disease Control and Prevention, 4770 Buford Highway, Atlanta, GA 30341, United States

Abstract
BACKGROUND: Return to learn (RTL) after mild traumatic brain injury (mTBI) presents unique challenges for school professionals. A multidisciplinary team approach is necessary yet training school professionals is logistically difficult. This paper describes an innovative pilot RTL program and its evaluation. METHODS: Utilizing the telehealth/telementoring program Project ECHO® (Extension for Community Healthcare Outcomes), this study utilized a multidisciplinary team of subject matter experts to deliver five 1-hour sessions across 5 cohorts of school-based professionals (total of 133 participants). The evaluation used a mixed-methods approach of post-session and post-program participant surveys and post-program participant focus groups. RESULTS: Participants who completed a post-program survey reported statistically significant improvements in essential aspects of RTL knowledge and self-efficacy. This included improvements in how to manage a student with an mTBI (44.8% to 86.9%), benefits of early return to school for students following mTBI (31.8% to 86.9%), and the importance of written RTL policies/procedures (55.1% to 97.1%). CONCLUSIONS: This study demonstrates that RTL training via a telementoring approach may be a positive and effective way to train school-based professionals and improve knowledge and self-efficacy, especially when attending face-to-face trainings are difficult. This model has the potential to produce programmatic and systematic improvements for RTL education. © 2022 The Authors. Journal of School Health published by Wiley Periodicals LLC on behalf of American School Health Association.

Author Keywords
mild traumatic brain injury;  project ECHO;  return to learn;  return to play;  telementoring

Funding details
Centers for Disease Control and PreventionCDC

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

The Dual Mechanisms of Cognitive Control (DMCC) project: Validation of an online behavioural task battery
(2022) Quarterly Journal of Experimental Psychology, . 

Tang, R.^a , Bugg, J.M.^a , Snijder, J.-P.^b , Conway, A.R.A.^b , Braver, T.S.^a

^a Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States
^b Division of Behavioral and Organizational Sciences, Claremont Graduate University, Claremont, CA, United States

Abstract
Cognitive control serves a crucial role in human higher mental functions. The Dual Mechanisms of Control theoretical framework provides a unifying account that decomposes cognitive control into two qualitatively distinct mechanisms—proactive control and reactive control. Here, we describe the Dual Mechanisms of Cognitive Control (DMCC) task battery, which was developed to probe cognitive control modes in a theoretically targeted manner, along with detailed descriptions of the experimental manipulations used to encourage shifts to proactive or reactive mode in each of four prototypical domains of cognition: selective attention, context processing, multitasking, and working memory. We present results from this task battery, conducted from a large (N > 100), online sample that rigorously evaluates the group effects of these manipulations in primary indices of proactive and reactive control, establishing the validity of the battery in providing dissociable yet convergent measures of the two cognitive control modes. The DMCC battery may be a useful tool for the research community to examine cognitive control in a theoretically targeted manner across different individuals and groups. © Experimental Psychology Society 2022.

Author Keywords
Cognitive control;  context processing;  Stroop;  task-switching;  working memory

Funding details
National Institutes of HealthNIHR37 MH066078
Washington University in St. LouisWUSTL
McDonnell Center for Systems Neuroscience

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

Measurement Properties of Clinical Scales Rating the Severity of Blepharospasm: A Multicenter Observational Study
(2022) Movement Disorders Clinical Practice, . 

Defazio, G.^a , Hallett, M.^b , Berardelli, A.^c d , Perlmutter, J.S.^e , Berman, B.D.^f , Jankovic, J.^g , Bäumer, T.^h , Comella, C.ⁱ , Ercoli, T.^a , Ferrazzano, G.^c , Fox, S.H.^j , Kim, H.-J.^k , Moukheiber, E.S.^l , Pirio Richardson, S.^m , Weissbach, A.^g n , Gigante, A.F.^o , Jinnah, H.A.^p

^a Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
^b Human Motor Control Section, NINDS, NIH, Bethesda, MD, United States
^c Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
^d IRCCS NEUROMED, Pozzilli, Italy
^e Neurology, Radiology, Neuroscience, Physical Therapy, Occupational Therapy, Washington University in St. Louis, St Louis, MO, United States
^f Virginia Commonwealth University, Richmond, VA, United States
^g Parkinson’s Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, TX, United States
^h Institute of Systems Motor Science, University of Luebeck, Luebeck, Germany
ⁱ Rush University Medical Center, New Philadelphia, OH, United States
^j Toronto Western Hospital, Krembil Brain Institute, University of Toronto, Toronto, ON, Canada
^k Department of Neurology and Movement Disorder Centre, Seoul National University Hospital, Seoul, South Korea
^l Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
^m Department of Neurology, University of New Mexico, Albuquerque, NM, United States
ⁿ Institute of Systems Motor Science and Institute of Neurogenetics, University of Lübeck, , Lübeck, Germany
^o Section of Neurology, San Paolo Hospital, Bari, Italy
^p Department of Neurology and Human Genetics, Emory University, Atlanta, GA, United States

Abstract
Background: Several scales have been proposed to clinically evaluate the Motor Severity of Blepharospasm (BSP) but information about their measurement properties as a multicenter instrument is limited. Objective: To compare the measurement properties of four clinical scales in rating the severity of BSP in a large sample of patients from multiple sites. Methods: The Burke–Fahn–Marsden Scale (BFMS), the Global Dystonia Severity Rating Scale (GDRS), the Jankovic Rating Scale (JRS), and the Blepharospasm Severity Rating Scale (BSRS) were administered to 211 patients across 10 sites who were also requested to self-complete the Blepharospasm Disability Index (BDI). Measurement properties to be assessed included inter−/intra-observer agreement, item-to-total correlation, internal consistency, floor and ceiling effect, convergent/discriminant validity, and adherence to the distribution of BDI. Results: The BFMS had unsatisfactory measurement properties, the GDRS had acceptable reliability but other properties could not be completely testable; the JRS had satisfactory measurement properties but the scale did not accurately reflect the distribution of disability parameter (BDI) in the sample, and the BSRS had satisfactory measurement properties and also showed the best adherence to the distribution of BDI in the assessed sample. Conclusion: The comparison of the measurement properties of four rating scales to assess the motor state of the BSP in a large sample of patients from multiple sites showed that the GDRS should be used to simultaneously assess BSP and dystonia in other body parts, while the JRS (easier to use) and BSRS (better to discriminate severity) should be used to assess BSP alone. © 2022 International Parkinson and Movement Disorder Society.

Author Keywords
Blepharospasm;  dystonia;  measurement properties;  rating scale;  severity of illness index

Funding details
National Institutes of HealthNIH
U.S. Department of DefenseDODW81XWH‐19‐CTRR‐CTA
National Institute of Neurological Disorders and StrokeNINDS
National Center for Research ResourcesNCRR
Parkinson’s Disease FoundationPDF
Dystonia Medical Research FoundationDMRF
CHDI FoundationCHDI
National Center for Advancing Translational SciencesNCATSUL1TR001449, UNM CTSC KL21TR001448‐01
Teva Pharmaceutical Industries
AbbVie
Allergan
International Parkinson and Movement Disorder SocietyMDS
Parkinsonfonden
Benign Essential Blepharospasm Research FoundationBEBRF
Sunovion
Toronto General and Western Hospital Foundation
Parkinson’s FoundationPF
National Spasmodic Dysphonia AssociationNSDA
Dystonia CoalitionNS065701, NS116025, TR 001456
Government of South Australia
RevanceRVNC
School of Medicine, Virginia Commonwealth University
Deutsche ForschungsgemeinschaftDFGP20 GM109899, U54 NS116025, WE 5919/2‐1
Else Kröner-Fresenius-StiftungEKFS2018_A55
Parkinson Canada
Institute for Information and Communications Technology PromotionIITP

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

A Data-Driven Approach in an Unbiased Sample Reveals Equivalent Sex Ratio of Autism Spectrum Disorder–Associated Impairment in Early Childhood
(2022) Biological Psychiatry, . Cited 1 time.

Burrows, C.A.^a , Grzadzinski, R.L.^c d , Donovan, K.^g , Stallworthy, I.C.^b , Rutsohn, J.^e , St. John, T.ⁱ , Marrus, N.^l , Parish-Morris, J.^h , MacIntyre, L.^m , Hampton, J.^l , Pandey, J.^h , Shen, M.D.^c d f , Botteron, K.N.^j l , Estes, A.M.^i k , Dager, S.R.^j , Hazlett, H.C.^c d , Pruett, J.R., Jr.^l , Schultz, R.T.^h , Zwaigenbaum, L.ⁿ , Truong, K.N.^e , Piven, J.^c d , Elison, J.T.^a b , IBIS Network^o

^a Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, United States
^b Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN, United States
^c Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^d Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^e Department of Biostatistics, Gillings School of Global PubLic Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^f UNC Neuroscience Center, UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^g Department of Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania
^h Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
ⁱ UW Autism Center, Center on Human Development & Disability, University of Washington, Seattle, WA, United States
^j Department of Radiology, University of Washington Medical Center, Seattle, WA, United States
^k Department of Speech & Hearing Sciences, University of Washington, Seattle, WA, United States
^l Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, Missouri
^m McGill Centre for Integrative Neuroscience, Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada
ⁿ Department of Pediatrics, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AlbertaAB, Canada

Abstract
Background: Sex differences in the prevalence of neurodevelopmental disorders are particularly evident in autism spectrum disorder (ASD). Heterogeneous symptom presentation and the potential of measurement bias hinder early ASD detection in females and may contribute to discrepant prevalence estimates. We examined trajectories of social communication (SC) and restricted and repetitive behaviors (RRBs) in a sample of infant siblings of children with ASD, adjusting for age- and sex-based measurement bias. We hypothesized that leveraging a prospective elevated familial likelihood sample, deriving data-driven behavioral constructs, and accounting for measurement bias would reveal less discrepant sex ratios than are typically seen in ASD. Methods: We conducted direct assessments of ASD symptoms at 6 to 9, 12 to 15, 24, and 36 to 60 months of age (total nobservations = 1254) with infant siblings of children with ASD (n = 377) and a lower ASD-familial-likelihood comparison group (n = 168; nobservations = 527). We established measurement invariance across age and sex for separate models of SC and RRB. We then conducted latent class growth mixture modeling with the longitudinal data and evaluated for sex differences in trajectory membership. Results: We identified 2 latent classes in the SC and RRB models with equal sex ratios in the high-concern cluster for both SC and RRB. Sex differences were also observed in the SC high-concern cluster, indicating that girls classified as having elevated social concerns demonstrated milder symptoms than boys in this group. Conclusions: This novel approach for characterizing ASD symptom progression highlights the utility of assessing and adjusting for sex-related measurement bias and identifying sex-specific patterns of symptom emergence. © 2022 Society of Biological Psychiatry

Author Keywords
Autism spectrum disorder;  Measurement invariance;  Mixture modeling;  Restricted and repetitive behaviors;  Sex differences;  Social communication

Funding details
124:1188–1195
National Institutes of HealthNIHK12-HD055887, P50-HD103573, R01-HD055741, R01-MH118362-01, U54-HD079124, U54-HD086984
Autism SpeaksAS6020
Simons FoundationSF140209
University of MinnesotaUMN
University of North Carolina WilmingtonUNCW
University of WashingtonUW
Johns Hopkins UniversityJHU
Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNICHD3KL2TR002490-03S1
Washington University School of Medicine in St. LouisWUSM
University of AlbertaUofA

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

To BYOD or not: Are device latencies important for bring-your-own-device (BYOD) smartphone cognitive testing?
(2022) Behavior Research Methods, . 

Nicosia, J.^a , Wang, B.^b , Aschenbrenner, A.J.^a , Sliwinski, M.J.^c , Yabiku, S.T.^d , Roque, N.A.^e , Germine, L.T.^f g , Bateman, R.J.^a , Morris, J.C.^a , Hassenstab, J.^a h

^a Charles F. and Joanne Knight Alzheimer Disease Research Center, Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^b Mountain View, United States
^c Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, United States
^d Department of Sociology and Criminology, The Pennsylvania State University, University Park, PA, United States
^e Department of Psychology, University of Central Florida, Orlando, FL, United States
^f Department of Psychiatry, Harvard Medical School, Boston, MA, United States
^g Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, United States
^h Department of Psychological & Brain Sciences, Washington University in St. Louis, St. Louis, MO, United States

Abstract
Studies using remote cognitive testing must make a critical decision: whether to allow participants to use their own devices or to provide participants with a study-specific device. Bring-your-own-device (BYOD) studies have several advantages including increased accessibility, potential for larger sample sizes, and reduced participant burden. However, BYOD studies offer little control over device performance characteristics that could potentially influence results. In particular, response times measured by each device not only include the participant’s true response time, but also latencies of the device itself. The present study investigated two prominent sources of device latencies that pose significant risks to data quality: device display output latency and touchscreen input latency. We comprehensively tested 26 popular smartphones ranging in price from < $100 to $1000+ running either Android or iOS to determine if hardware and operating system differences led to appreciable device latency variability. To accomplish this, a custom-built device called the Latency and Timing Assessment Robot (LaTARbot) measured device display output and capacitive touchscreen input latencies. We found considerable variability across smartphones in display and touch latencies which, if unaccounted for, could be misattributed as individual or group differences in response times. Specifically, total device (sum of display and touch) latencies ranged from 35 to 140 ms. We offer recommendations to researchers to increase the precision of data collection and analysis in the context of remote BYOD studies. © 2022, The Psychonomic Society, Inc.

Author Keywords
Ambulatory assessment;  BYOD;  Remote assessment;  Smartphones

Funding details
National Institutes of HealthNIHP01 AG003991, R01 AG057840, U2C AG060408
BrightFocus FoundationBFFA2018202S

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