WashU weekly Neuroscience publications

Defining the causes of sporadic Parkinson’s disease in the global Parkinson’s genetics program (GP2)
(2023) npj Parkinson’s Disease, 9 (1), art. no. 131, . 

Towns, C.^a , Richer, M.^a , Jasaityte, S.^a , Stafford, E.J.^a b , Joubert, J.^a , Antar, T.^c , Martinez-Carrasco, A.^a b , Makarious, M.B.^a c d , Casey, B.^e f , Vitale, D.^d g h , Levine, K.^g h , Leonard, H.^c g h i , Pantazis, C.B.^d g , Screven, L.A.^g , Hernandez, D.G.^c , Wegel, C.E.^j , Solle, J.^e , Nalls, M.A.^c d g h , Blauwendraat, C.^d g k , Singleton, A.B.^c g l , Tan, M.M.X.^m , Iwaki, H.^c g h , Morris, H.R.^a b , Gatto, E.M.ⁿ , Kauffman, M.^o , Khachatryan, S.^p , Tavadyan, Z.^p , Shepherd, C.E.^q , Hunter, J.^r , Kumar, K.^s , Ellis, M.^t , Rentería, M.E.^u , Koks, S.^v , Zimprich, A.^w , Schumacher-Schuh, A.F.^x , Rieder, C.^y , Awad, P.S.^z , Tumas, V.^aa , Camargos, S.^ab , Fon, E.A.^ac , Monchi, O.^ad , Fon, T.^ae , Galleguillos, B.P.^af , Miranda, M.^ag , Bustamante, M.L.^ah , Olguin, P.^af , Chana, P.^ai , Tang, B.^aj , Shang, H.^ak , Guo, J.^al , Chan, P.^am , Luo, W.^an , Arboleda, G.^ao , Orozco, J.^ap , del Rio, M.J.^aq , Hernandez, A.^ar , Salama, M.^as , Kamel, W.A.^at , Zewde, Y.Z.^au , Brice, A.^av , Corvol, J.-C.^aw , Westenberger, A.^ax , Illarionova, A.^ay , Mollenhauer, B.^az , Klein, C.^ax , Vollstedt, E.-J.^ax , Hopfner, F.^ba , Höglinger, G.^ba , Madoev, H.^ax , Trinh, J.^ax , Junker, J.^ax , Lohmann, K.^ax , Lange, L.M.^bb , Sharma, M.^bc , Groppa, S.^bd , Gasser, T.^bc , Fang, Z.-H.^be , Akpalu, A.^bf , Xiromerisiou, G.^bg , Hadjigorgiou, G.^bg , Dagklis, I.^bh , Tarnanas, I.^bi , Stefanis, L.^bj , Stamelou, M.^bk , Dadiotis, E.^bg , Medina, A.^bl , Chan, G.H.-F.^bm , Ip, N.^bn , Cheung, N.Y.-F.^bm , Chan, P.^bn , Zhou, X.^bn , Kishore, A.^bo , Kp, D.^bp , Pal, P.^bq , Kukkle, P.L.^br , Rajan, R.^bs , Borgohain, R.^bt , Salari, M.^bu , Quattrone, A.^bv , Valente, E.M.^bw , Parnetti, L.^bx , Avenali, M.^bw , Schirinzi, T.^by , Funayama, M.^bz , Hattori, N.^ca , Shiraishi, T.^cb , Karimova, A.^cc , Kaishibayeva, G.^cc , Shambetova, C.^cd , Krüger, R.^ce , Tan, A.H.^cf , Ahmad-Annuar, A.^cf , Norlinah, M.I.^cg , Murad, N.A.A.^ch , Azmin, S.^ci , Lim, S.-Y.^cf , Mohamed, W.^cj , Tay, Y.W.^cf , Martinez-Ramirez, D.^ck , Rodriguez-Violante, M.^cl , Reyes-Pérez, P.^cm , Tserensodnom, B.^cn , Ojha, R.^co , Anderson, T.J.^cp , Pitcher, T.L.^cp , Sanyaolu, A.^cq , Okubadejo, N.^cq , Ojo, O.^cr , Aasly, J.O.^cs , Pihlstrøm, L.^ct , Tan, M.^ct , Ur-Rehman, S.^cu , Cornejo-Olivas, M.^cv , Doquenia, M.L.^cw , Rosales, R.^cw , Vinuela, A.^cx , Iakovenko, E.^cy , Mubarak, B.A.^cz , Umair, M.^da , Tan, E.-K.^db , Foo, J.N.^dc , Amod, F.^dd , Carr, J.^de , Bardien, S.^df , Jeon, B.^dg , Kim, Y.J.^dh , Cubo, E.^di , Alvarez, I.^dj , Hoenicka, J.^dk , Beyer, K.^dl , Periñan, M.T.^dm , Pastor, P.^dn , El-Sadig, S.^do , Zweier, C.^dp , Krack, P.^dp , Lin, C.-H.^dq , Wu, H.-C.^dr , Kung, P.-J.^ds , Wu, R.-M.^dq , Wu, Y.^dr , Amouri, R.^dt , Sassi, S.B.^du , Başak, A.N.^dv , Genc, G.^dw , Çakmak, Ö.Ö.^dv , Ertan, S.^dv , Noyce, A.^dx , Schrag, A.^b , Schapira, A.^b , Carroll, C.^dy , Bale, C.^dz , Grosset, D.^ea , Houlden, H.^b , Hardy, J.^b , Mok, K.Y.^b , Rizig, M.^b , Wood, N.^b , Williams, N.^eb , Okunoye, O.^b , Lewis, P.A.^ec , Kaiyrzhanov, R.^b , Weil, R.^b , Love, S.^ed , Stott, S.^ee , Jasaitye, S.^b , Dey, S.^dx , Obese, V.^b , Espay, A.^ef , O’Grady, A.^f , Sobering, A.K.^eg , Siddiqi, B.^f , Fiske, B.^f , Jonas, C.^eh , Cruchaga, C.^ei , Comart, C.^f , Wegel, C.^ej , Hall, D.^ek , Hernandez, D.^d , Shiamim, E.^el , Riley, E.^em , Faghri, F.^d , Serrano, G.E.^en , Chen, H.^eo , Mata, I.F.^ep , Sarmiento, I.J.K.^eq , Williamson, J.^el , Kim, J.J.^d , Jankovic, J.^er , Shulman, J.^es , Solle, J.C.^f , Murphy, K.^f , Nuytemans, K.^et , Kieburtz, K.^eu , Markopoulou, K.^ev , Marek, K.^ew , Levine, K.S.^h , Chahine, L.M.^ex , Ibanez, L.^ei , Screven, L.^l , Ruffrage, L.^ey , Shulman, L.^ez , Marsili, L.^ef , Kuhl, M.^f , Dean, M.^ey , Koretsky, M.^d , Puckelwartz, M.J.^fa , Inca-Martinez, M.^ep , Louie, N.^f , Mencacci, N.E.^eq , Albin, R.^fb , Alcalay, R.^fc , Walker, R.^fd , Bandres-Ciga, S.^d , Chowdhury, S.^f , Dumanis, S.^fe , Lubbe, S.^fa , Xie, T.^ff , Foroud, T.^fg , Beach, T.^fh , Sherer, T.^f , Song, Y.^d , Nguyen, D.^fi , Nguyen, T.^fi , Atadzhanov, M.^fj

^a Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London, United Kingdom
^b University College London, London, United Kingdom
^c Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
^d National Institutes of Health, Bethesda, MD, United States
^e Department of Clinical Research, Michael J. Fox Foundation for Parkinson’s Research, New York City, NY, United States
^f The Michael J. Fox Foundation for Parkinson’s Research, New York, NY, United States
^g Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
^h Data Tecnica International, Washington, DC, United States
ⁱ National Institute on Aging/National Institutes of Health, Bethesda, MD, United States
^j Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
^k Integrative Genomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
^l National Institute on Aging, Bethesda, MD, United States
^m Department of Neurology, Oslo University Hospital, Oslo, Norway
ⁿ Sanatorio de la Trinidad Mitre- INEBA, Buenos Aires, Argentina
^o Hospital JM Ramos Mejia, Buenos Aires, Argentina
^p Somnus Neurology Clinic, Yerevan, Armenia
^q Neuroscience Research Australia, Sydney, NSW, Australia
^r ANZAC Research Institute, Concord, NSW, Australia
^s Garvan Institute of Medical Research and Concord Repatriation General Hospital, Darlinghurst, NSW, Australia
^t Concord Hospital, Concord, NSW, Australia
^u QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
^v Murdoch University, Perth, Australia
^w Medical University Vienna Austria, Vienna, Austria
^x Universidade Federal do Rio Grande do Sul / Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
^y Federal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil
^z Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
^aa University of São Paulo, São Paulo, Brazil
^ab Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
^ac Montreal Neurological Institute, Montreal, QC, Canada
^ad Institut universitaire de gériatrie de Montréal, Montreal, QC, Canada
^ae McGill University, Montreal, QC, Canada
^af Universidad de Chile, Santiago, Chile
^ag Fundación Diagnosis, Santiago, Chile
^ah Faculty of Medicine Universidad de Chile, Santiago, Chile
^ai CETRAM, Santiago, Chile
^aj Central South University, Changsha, China
^ak West China Hospital Sichuan University, Chengdu, China
^al Xiangya Hospital, Changsha, China
^am Capital Medical University, Beijing, China
^an Zhejiang University, Hangzhou, China
^ao Universidad Nacional de Colombia, Bogotá, Colombia
^ap Fundación Valle del Lili, Santiago De Cali, Colombia
^aq University of Antioquia, Medellin, Colombia
^ar University of Costa Rica, San Jose, Costa Rica
^as The American University in Cairo, Cairo, Egypt
^at Beni-Suef University, Beni Suef, Egypt
^au Addis Ababa University, Addis Ababa, Ethiopia
^av Paris Brain Institute, Paris, France
^aw Sorbonne Université, Paris, France
^ax University of Lübeck, Lübeck, Germany
^ay Deutsches Zentrum für Neurodegenerative Erkrankungen, Göttingen, Germany
^az University Medical Center Göttingen, Göttingen, Germany
^ba Department of Neurology, University Hospital, LMU Munich, Munich, Germany
^bb University of Lübeck and University Medical Center Schleswig-Holstein, Lübeck, Germany
^bc University of Tubingen, Tübingen, Germany
^bd University of Mainz, Mainz, Germany
^be The German Center for Neurodegenerative Diseases, Göttingen, Germany
^bf University of Ghana Medical School, Accra, Ghana
^bg University of Thessaly, Volos, Greece
^bh Aristotle University of Thessaloniki, Thessaloniki, Greece
^bi Ionian University, Corfu, Greece
^bj Biomedical research Foundation of the Academy of Athens, Athens, Greece
^bk Diagnostic and Therapeutic Centre HYGEIA Hospital, Marousi, Greece
^bl Hospital San Felipe, Tegucigalpa, Honduras
^bm Queen Elizabeth Hospital, Kowloon, Hong Kong
^bn The Hong Kong University of Science and Technology, Kowloon, Hong Kong
^bo Aster Medcity, Kochi, India
^bp Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, India
^bq National Institute of Mental Health & Neurosciences, Bengaluru, India
^br Manipal Hospital, Delhi, India
^bs All India Institute of Medical Sciences, Delhi, India
^bt Nizam’s Institute Of Medical Sciences, Hyderabad, India
^bu Shahid Beheshti University of Medical Science, Tehran, Iran
^bv Magna Græcia University of Catanzaro, Catanzaro, Italy
^bw University of Pavia, Pavia, Italy
^bx University of Perugia, Perugia, Italy
^by University of Rome Tor Vergata, Rome, Italy
^bz Juntendo University, Tokyo, Japan
^ca Juntendo University faculty of medicine, Tokyo, Japan
^cb Jikei University School of Medicine, Tokyo, Japan
^cc Institute of Neurology and Neurorehabilitation, Almaty, Kazakhstan
^cd Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan
^ce University of Luxembourg, Luxembourg, Luxembourg
^cf University of Malaya, Kuala Lumpur, Malaysia
^cg Universiti Kebangsaan Malaysia, Selangor, Malaysia
^ch UKM Medical Molecular Biology Institute, Kuala Lumpur, Malaysia
^ci Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
^cj International Islamic University, Kuala Lumpur, Malaysia
^ck Tecnologico de Monterrey, Monterrey, Mexico
^cl Instituto Nacional de Neurologia y Neurocirugia, Mexico City, Mexico
^cm Universidad Nacional Autónoma de México, Mexico City, Mexico
^cn Mongolian National University of Medical Sciences, Ulaanbaatar, Mongolia
^co Tribhuvan University, Kirtipur, Nepal
^cp University of Otago, Dunedin, New Zealand
^cq University of Lagos, Lagos, Nigeria
^cr College of Medicine of the University of Lagos, Lagos, Nigeria
^cs Norwegian University of Science and Technology, Trondheim, Norway
^ct Oslo University Hospital, Oslo, Norway
^cu University of Science and Technology Bannu, Bannu, Pakistan
^cv Universidad Cientifica del Sur, Lima, Peru
^cw Metropolitan Medical Center, Manila, Philippines
^cx University of Puerto Rico, San Juan, Puerto Rico
^cy Research Center of Neurology, Moscow, Russian Federation
^cz King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
^da King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
^db National Neuroscience Institute, Singapore, Singapore
^dc Nanyang Technological University, Singapore, Singapore
^dd University of KwaZulu-Natal, Durban, South Africa
^de University of Stellenbosch, Stellenbosch, South Africa
^df Stellenbosch University, Stellenbosch, South Africa
^dg Seoul National University Hospital, Seoul, South Korea
^dh Yongin Severance Hospital, Seoul, South Korea
^di Hospital Universitario Burgos, Burgos, Spain
^dj University Hospital Mutua Terrassa, Barcelona, Spain
^dk Institut de Recerca Sant Joan de Deu, Barcelona, Spain
^dl Research Institute Germans Trias i Pujol, Barcelona, Spain
^dm Instituto de Biomedicina de Sevilla, Seville, Spain
^dn University Hospital Germans Trias i Pujol, Barcelona, Spain
^do Faculty of medicine university of Khartoum, Khartoum, Sudan
^dp Inselspital Bern, University of Bern, Bern, Switzerland
^dq National Taiwan University Hospital, Taipei City, Taiwan
^dr Chang Gung Memorial Hospital, Taoyuan City, Taiwan
^ds National Taiwan University, Taipei City, Taiwan
^dt National Institute Mongi Ben Hamida of Neurology, Tunis, Tunisia
^du Mongi Ben Hmida National Institute of Neurology, Tunis, Tunisia
^dv Koç University, Istanbul, Turkey
^dw Sisli Etfal Training and Research Hospital, Istanbul, Turkey
^dx Queen Mary University of London, London, United Kingdom
^dy University of Plymouth, Plymouth, United Kingdom
^dz Parkinson’s UK, London, United Kingdom
^ea University of Glasgow, Glasgow, United Kingdom
^eb Cardiff University, Cardiff, United Kingdom
^ec Royal Veterinary College University of London, London, United Kingdom
^ed University of Bristol, Bristol, United Kingdom
^ee Cure Parkinson’s, London, United Kingdom
^ef University of Cincinnati, Cincinnati, OH, United States
^eg Augusta University / University of Georgia Medical Partnership, Augusta, GA, United States
^eh Mid-Atlantic Permanente Medical Group, Bethesda, MD, United States
^ei Washington University, St. Louis, MO, United States
^ej Indiana University, Bloomington, IN, United States
^ek Rush University, Chicago, IL, United States
^el Kaiser Permanente, Oakland, CA, United States
^em Coalition for Aligning Science, Washington, WA, United States
^en Banner Sun Health Research Institute, Sun City, AZ, United States
^eo Michigan State University, East Lansing, MI, United States
^ep Cleveland Clinic, Cleveland, OH, United States
^eq Northwestern University, Evanston, IL, United States
^er Baylor College of Medicine, Houston, TX, United States
^es Baylor College of Medicine, Texas Children’s Hospital, Houston, TX, United States
^et University of Miami Miller School of Medicine, Miami, FL, United States
^eu Beth Israel Deaconess Medical Center, Boston, MA, United States
^ev North Shore University Health System, Chicago, IL, United States
^ew Institute for Neurodegenerative Disorders, New Haven, CT, United States
^ex University of Pittsburgh, Pittsburgh, PA, United States
^ey University of Alabama at Birmingham, Birmingham, AL, United States
^ez University of Maryland, Baltimore, MD, United States
^fa Northwestern University, Chicago, IL, United States
^fb Universit of Michigan, Ann Arbor, MI, United States
^fc Columbia University, New York, NY, United States
^fd James J. Peters Veterans Affairs Medical Center, New York, NY, United States
^fe Aligning Science Across Parkinson’s, Washington, WA, United States
^ff University of Chicago, Chicago, IL, United States
^fg Indiana University School of Medicine, Indianapolis, IN, United States
^fh Sun Health Research Institution, Sun City, AZ, United States
^fi Hue University, Huế, Viet Nam
^fj University of Zambia, Lusaka, Zambia

Abstract
The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia. © 2023, Springer Nature Limited.

Funding details
National Institutes of HealthNIH
U.S. Department of Health and Human ServicesHHSZO1 AG000949
National Institute on AgingNIA
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
International Parkinson and Movement Disorder SocietyMDS
Wellcome TrustWT
PSP AssociationPSPA
Aligning Science Across Parkinson’sASAP
PCB Solutions
Medical Research CouncilMRC
Drake Foundation

Document Type: Article
Publication Stage: Final
Source: Scopus

A Novel Brain PET Radiotracer for Imaging Alpha Synuclein Fibrils in Multiple System Atrophy
(2023) Journal of Medicinal Chemistry, . 

Kim, H.Y.^a , Chia, W.K.^a , Hsieh, C.-J.^a , Saturnino Guarino, D.^a , Graham, T.J.A.^a , Lengyel-Zhand, Z.^a , Schneider, M.^a , Tomita, C.^a , Lougee, M.G.^b , Kim, H.J.^c , Pagar, V.V.^b , Lee, H.^a , Hou, C.^a , Garcia, B.A.^c , Petersson, E.J.^b , O’Shea, J.^d , Kotzbauer, P.T.^d , Mathis, C.A.^e , Lee, V.M.^f , Luk, K.C.^f , Mach, R.H.^a

^a Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 231 S. 34th Street, Philadelphia, PA 19104-6323, United States
^b Department of Chemistry, University of Pennsylvania, Pennsylvania, Philadelphia, 19104-6323, United States
^c Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, Philadelphia, 19104-6303, United States
^d Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110-1010, United States
^e Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, United States
^f Center for Neurodegenerative Disease Research, Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104-2676, United States

Abstract
Abnormal α-synuclein (α-syn) aggregation characterizes α-synucleinopathies, including Parkinson’s disease (PD) and multiple system atrophy (MSA). However, no suitable positron emission tomography (PET) radiotracer for imaging α-syn in PD and MSA exists currently. Our structure-activity relationship studies identified 4-methoxy-N-(4-(3-(pyridin-2-yl)-3,8-diazabicyclo[3.2.1]octan-8-yl)phenyl)benzamide (4i) as a PET radiotracer candidate for imaging α-syn. In vitro assays revealed high binding of 4i to recombinant α-syn fibrils (inhibition constant (Ki) = 6.1 nM) and low affinity for amyloid beta (Aβ) fibrils in Alzheimer’s disease (AD) homogenates. However, [3H]4i also exhibited high specific binding to AD, progressive supranuclear palsy, and corticobasal degeneration tissues as well as PD and MSA tissues, suggesting notable affinity to tau. Nevertheless, the specific binding to pathologic α-syn aggregates in MSA post-mortem brain tissues was significantly higher than in PD tissues. This finding demonstrated the potential use of [11C]4i as a PET tracer for imaging α-syn in MSA patients. Nonhuman primate PET studies confirmed good brain uptake and rapid washout for [11C]4i. © 2023 American Chemical Society.

Funding details
P01AG019724, P30AG062422, U01AG057195, U19AG063911
National Institutes of HealthNIHNS072026, T32-AG000255
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
Rainwater Charitable FoundationRCF

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

High gamma coherence between task-responsive sensory-motor cortical regions in a motor reaction-time task
(2023) Journal of Neurophysiology, 130 (3), pp. 628-639. 

Anand, S.^a , Cho, H.^b c , Adamek, M.^c d , Burton, H.^d , Moran, D.^a b d , Leuthardt, E.^a b c d , Brunner, P.^a b c e

^a Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO, United States
^b Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^c National Center for Adaptive Neurotechnologies, St. Louis, MO, United States
^d Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^e Department of Neurology, Albany Medical College, Albany, NY, United States

Abstract
Electrical activity at high gamma frequencies (70-170 Hz) is thought to reflect the activity of small cortical ensembles. For example, high gamma activity (often quantified by spectral power) can increase in sensory-motor cortex in response to sensory stimuli or movement. On the other hand, synchrony of neural activity between cortical areas (often quantified by coherence) has been hypothesized as an important mechanism for inter-areal communication, thereby serving functional roles in cognition and behavior. Currently, high gamma activity has primarily been studied as a local amplitude phenomenon. We investigated the synchronization of high gamma activity within sensory-motor cortex and the extent to which underlying high gamma activity can explain coherence during motor tasks. We characterized high gamma coherence in sensory-motor networks and the relationship between coherence and power by analyzing electrocorticography (ECoG) data from human subjects as they performed a motor response to sensory cues. We found greatly increased high gamma coherence during the motor response compared with the sensory cue. High gamma power poorly predicted high gamma coherence, but the two shared a similar time course. However, high gamma coherence persisted longer than high gamma power. The results of this study suggest that high gamma coherence is a physiologically distinct phenomenon during a sensory-motor task, the emergence of which may require active task participation.NEW & NOTEWORTHY Motor action after auditory stimulus elicits high gamma responses in sensory-motor and auditory cortex, respectively. We show that high gamma coherence reliably and greatly increased during motor response, but not after auditory stimulus. Underlying high gamma power could not explain high gamma coherence. Our results indicate that high gamma coherence is a physiologically distinct sensory-motor phenomenon that may serve as an indicator of increased synaptic communication on short timescales (∼1 s).

Author Keywords
coherence;  electrocorticography;  high gamma activity;  motor cortex;  sensory cortex

Document Type: Article
Publication Stage: Final
Source: Scopus

Correlating Quantitative MRI-based Apparent Diffusion Coefficient Metrics with 24-month Neurodevelopmental Outcomes in Neonates from the HEAL Trial
(2023) Radiology, 308 (3), p. e223262. 

Calabrese, E., Wu, Y., Scheffler, A.W., Wisnowski, J.L., McKinstry, R.C., Mathur, A., Glass, H.C., Comstock, B.A., Heagerty, P.J., Gillon, S., Juul, S.E., Hess, C.P., Li, Y.

From the Department of Radiology, Duke University Medical Center, Durham, NC (E.C.); Department of Neurology and Weill Institute for Neuroscience (Y.W., H.C.G.), Department of Pediatrics, UCSF Benioff Children’s Hospital (Y.W., H.C.G.), Department of Epidemiology and Biostatistics (A.W.S.), School of Medicine (S.G.), and Neuroradiology Section, Department of Radiology and Biomedical Imaging (C.P.H., Y.L.), University of California, San Francisco, 505 Parnassus Ave, M-391, San Francisco, CA 94143-0628; Department of Radiology, Children’s Hospital of Los Angeles, University of Southern California Keck School of Medicine, Los Angeles, Calif (J.L.W.); Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (R.C.M.); Department of Pediatrics, St Louis University, St Louis, Mo (A.M.); and Departments of Statistics (B.A.C., P.J.H.) and Pediatrics (S.E.J.), University of Washington, Seattle, Wash

Abstract
Background Multiple qualitative scoring systems have been created to capture the imaging severity of hypoxic ischemic brain injury. Purpose To evaluate quantitative volumes of acute brain injury at MRI in neonates with hypoxic ischemic brain injury and correlate these findings with 24-month neurodevelopmental outcomes and qualitative brain injury scoring by radiologists. Materials and Methods In this secondary analysis, brain diffusion-weighted MRI data from neonates in the High-dose Erythropoietin for Asphyxia and Encephalopathy trial, which recruited participants between January 2017 and October 2019, were analyzed. Volume of acute brain injury, defined as brain with apparent diffusion coefficient (ADC) less than 800 × 10-6 mm2/sec, was automatically computed across the whole brain and within the thalami and white matter. Outcomes of death and neurodevelopmental impairment (NDI) were recorded at 24-month follow-up. Associations between the presence and volume (in milliliters) of acute brain injury with 24-month outcomes were evaluated using multiple logistic regression. The correlation between quantitative acute brain injury volume and qualitative MRI scores was assessed using the Kendall tau-b test. Results A total of 416 neonates had available MRI data (mean gestational age, 39.1 weeks ± 1.4 [SD]; 235 male) and 113 (27%) showed evidence of acute brain injury at MRI. Of the 387 participants with 24-month follow-up data, 185 (48%) died or had any NDI. Volume of acute injury greater than 1 mL (odds ratio [OR], 13.9 [95% CI: 5.93, 32.45]; P < .001) and presence of any acute injury in the brain (OR, 4.5 [95% CI: 2.6, 7.8]; P < .001) were associated with increased odds of death or any NDI. Quantitative whole-brain acute injury volume was strongly associated with radiologists’ qualitative scoring of diffusion-weighted images (Kendall tau-b = 0.56; P < .001). Conclusion Automated quantitative volume of brain injury is associated with death, moderate to severe NDI, and cerebral palsy in neonates with hypoxic ischemic encephalopathy and correlated well with qualitative MRI scoring of acute brain injury. Clinical trial registration no. NCT02811263 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Huisman in this issue.

Document Type: Article
Publication Stage: Final
Source: Scopus

Differential genetic associations between dimensions of eating disorders and alcohol involvement in late adolescent twins
(2023) Alcohol: Clinical and Experimental Research, . 

Qi, B.^a , Thornton, L.M.^b , Breiner, C.E.^c , Kuja-Halkola, R.^d , Baker, J.H.^b , Lichtenstein, P.^d , Lundström, S.^e , Agrawal, A.^f , Bulik, C.M.^b d g , Munn-Chernoff, M.A.^b

^a Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^b Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^c Department of Psychology, University at Albany, State University of New York, Albany, NY, United States
^d Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
^e Gillberg Neuropsychiatry Centre, University of Gothenburg, Göteborg, Sweden
^f Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^g Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

Abstract
Background: Twin studies have demonstrated shared genetic and environmental effects between eating disorders and alcohol involvement in adults and middle adolescents. However, fewer studies have focused on late adolescents or investigated a wide range of eating disorder dimensions and alcohol involvement subscales in both sexes. We examined genetic and environmental correlations among three eating disorder dimensions and two alcohol involvement subscale scores in late adolescent twins using bivariate twin models. Methods: Participants were 3568 female and 2526 male same-sex twins aged 18 years old from the Child and Adolescent Twin Study in Sweden. The Eating Disorder Inventory-2 (EDI) assessed the drive for thinness, bulimia, and body dissatisfaction. Alcohol involvement was assessed with the Alcohol Use Disorder Identification Test consumption (AUDIT-C) and problem (AUDIT-P) subscales. Results: Only phenotypic and twin correlations in female twins met our threshold for twin modeling. The proportion of total variance for each trait accounted for by additive genetic factors ranged from 0.50 to 0.64 in female twins, with the rest explained by nonshared environmental factors and measurement error. Shared environmental factors played a minimal role in the variance of each trait. The strongest genetic correlation (ra) emerged between EDI bulimia and AUDIT-P (ra = 0.46, 95% confidence interval: 0.37, 0.55), indicating that the proportion of genetic variance of one trait that was shared with the other trait was 0.21. Nonshared environmental correlations between eating disorder dimensions and alcohol involvement ranged from 0.03 to 0.13. Conclusions: We observed distinct patterns of genetic and environmental effects for co-occurring eating disorder dimensions and alcohol involvement in female vs. male twins, supporting sex-specific treatment strategies for late adolescents with comorbid eating disorders and alcohol use disorder. Our findings emphasize the importance of assessing family history of multiple eating disorder dimensions while treating late adolescents with problematic alcohol use, and vice versa, to improve detection and treatment. © 2023 Research Society on Alcohol.

Author Keywords
alcohol use;  comorbidity;  eating disorders;  twin study;  young adult

Funding details
National Institute of Mental HealthNIMHK01 MH106675
National Institute on Alcohol Abuse and AlcoholismNIAAAK01 AA025113, R01 MH118278, R01 MH119084, R01 MH120170, R01 MH124871
Brain and Behavior Research FoundationBBRF
Lundbeck FoundationR276‐2018‐4581
VetenskapsrådetVR538‐2013‐8864

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

NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data
(2023) Frontiers in Neuroinformatics, 17, art. no. 1215261, . 

Wang, L.^a , Ambite, J.L.^b , Appaji, A.^c , Bijsterbosch, J.^d , Dockes, J.^e , Herrick, R.^d , Kogan, A.^a , Lander, H.^f , Marcus, D.^d , Moore, S.M.^d , Poline, J.-B.^e , Rajasekar, A.^f g , Sahoo, S.S.^h , Turner, M.D.^a , Wang, X.ⁱ , Wang, Y.^g , Turner, J.A.^a

^a Psychiatry and Behavioral Health Department, The Ohio State University Wexner Medical Center, Columbus, OH, United States
^b Information Sciences Institute and Computer Science, University of Southern California, Los Angeles, CA, United States
^c Department of Medical Electronics Engineering, BMS College of Engineering, Bangalore, India
^d Department of Radiology, Washington University in St. Louis, St. Louis, MO, United States
^e Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
^f Renaissance Computing Institute, Chapel Hill, NC, United States
^g School of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
^h Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States
ⁱ College of Information Sciences and Technology, Pennsylvania State University, State College, PA, United States

Abstract
Introduction: Open science initiatives have enabled sharing of large amounts of already collected data. However, significant gaps remain regarding how to find appropriate data, including underutilized data that exist in the long tail of science. We demonstrate the NeuroBridge prototype and its ability to search PubMed Central full-text papers for information relevant to neuroimaging data collected from schizophrenia and addiction studies. Methods: The NeuroBridge architecture contained the following components: (1) Extensible ontology for modeling study metadata: subject population, imaging techniques, and relevant behavioral, cognitive, or clinical data. Details are described in the companion paper in this special issue; (2) A natural-language based document processor that leveraged pre-trained deep-learning models on a small-sample document corpus to establish efficient representations for each article as a collection of machine-recognized ontological terms; (3) Integrated search using ontology-driven similarity to query PubMed Central and NeuroQuery, which provides fMRI activation maps along with PubMed source articles. Results: The NeuroBridge prototype contains a corpus of 356 papers from 2018 to 2021 describing schizophrenia and addiction neuroimaging studies, of which 186 were annotated with the NeuroBridge ontology. The search portal on the NeuroBridge website https://neurobridges.org/ provides an interactive Query Builder, where the user builds queries by selecting NeuroBridge ontology terms to preserve the ontology tree structure. For each return entry, links to the PubMed abstract as well as to the PMC full-text article, if available, are presented. For each of the returned articles, we provide a list of clinical assessments described in the Section “Methods” of the article. Articles returned from NeuroQuery based on the same search are also presented. Conclusion: The NeuroBridge prototype combines ontology-based search with natural-language text-mining approaches to demonstrate that papers relevant to a user’s research question can be identified. The NeuroBridge prototype takes a first step toward identifying potential neuroimaging data described in full-text papers. Toward the overall goal of discovering “enough data of the right kind,” ongoing work includes validating the document processor with a larger corpus, extending the ontology to include detailed imaging data, and extracting information regarding data availability from the returned publications and incorporating XNAT-based neuroimaging databases to enhance data accessibility. Copyright © 2023 Wang, Ambite, Appaji, Bijsterbosch, Dockes, Herrick, Kogan, Lander, Marcus, Moore, Poline, Rajasekar, Sahoo, Turner, Wang, Wang and Turner.

Author Keywords
addiction;  experimental design;  metadata;  MRI;  ontology;  schizophrenia;  text-mining

Funding details
P41 EB019936
R01 MH083320, RF1 MH120021
National Science FoundationNSFOCI-1247602, OCI-1247652, OCI-1247663
National Institutes of HealthNIH
National Institute of Mental HealthNIMH1636893 SP0037646, R01MH096906, U01 MH097435
National Institute on Drug AbuseNIDAR01 DA053028
Division of Information and Intelligent SystemsIIS1649397
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
McGill UniversityMGU
Fondation Brain Canada
Health Canada

Document Type: Article
Publication Stage: Final
Source: Scopus

Interactions between genes involved in physiological dysregulation and axon guidance: role in Alzheimer’s disease
(2023) Frontiers in Genetics, 14, art. no. 1236509, . 

Arbeev, K.G.^a , Ukraintseva, S.^a , Bagley, O.^a , Duan, H.^a , Wu, D.^a , Akushevich, I.^a , Stallard, E.^a , Kulminski, A.^a , Christensen, K.^b , Feitosa, M.F.^c , O’Connell, J.R.^d , Parker, D.^e , Whitson, H.^e f , Yashin, A.I.^a

^a Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, United States
^b Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
^c Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States
^d Division of Endocrinology, Diabetes and Nutrition and Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
^e Duke Center for the Study of Aging and Human Development, Duke University, Durham, NC, United States
^f Durham VA Geriatrics Research Education and Clinical Center, Durham, NC, United States

Abstract
Dysregulation of physiological processes may contribute to Alzheimer’s disease (AD) development. We previously found that an increase in the level of physiological dysregulation (PD) in the aging body is associated with declining resilience and robustness to major diseases. Also, our genome-wide association study found that genes associated with the age-related increase in PD frequently represented pathways implicated in axon guidance and synaptic function, which in turn were linked to AD and related traits (e.g., amyloid, tau, neurodegeneration) in the literature. Here, we tested the hypothesis that genes involved in PD and axon guidance/synapse function may jointly influence onset of AD. We assessed the impact of interactions between SNPs in such genes on AD onset in the Long Life Family Study and sought to replicate the findings in the Health and Retirement Study. We found significant interactions between SNPs in the UNC5C and CNTN6, and PLXNA4 and EPHB2 genes that influenced AD onset in both datasets. Associations with individual SNPs were not statistically significant. Our findings, thus, support a major role of genetic interactions in the heterogeneity of AD and suggest the joint contribution of genes involved in PD and axon guidance/synapse function (essential for the maintenance of complex neural networks) to AD development. Copyright © 2023 Arbeev, Ukraintseva, Bagley, Duan, Wu, Akushevich, Stallard, Kulminski, Christensen, Feitosa, O’Connell, Parker, Whitson and Yashin.

Author Keywords
aging;  Alzheimer’s disease;  axon guidance;  candidate genes;  genetic interactions;  physiological dysregulation;  resilience;  synaptic function

Funding details
National Institutes of HealthNIHR01AG062623, U19AG063893
National Institute on AgingNIA
Alzheimer’s Disease Research Center, University of WashingtonADRC, UWP30AG072958, R01AG063971, RF1AG046860

Document Type: Article
Publication Stage: Final
Source: Scopus