WashU weekly Neuroscience publications: October 30, 2022

Chronic TREM2 activation exacerbates Aβ-associated tau seeding and spreading
(2023) The Journal of Experimental Medicine, 220 (1), . 

Jain, N.^a b c , Lewis, C.A.^a b c , Ulrich, J.D.^a b c , Holtzman, D.M.^a b c

^a Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
^b Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, United States
^c Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Variants in the triggering receptor expressed on myeloid cells 2 (TREM2) gene are associated with increased risk for late-onset AD. Genetic loss of or decreased TREM2 function impairs the microglial response to amyloid-β (Aβ) plaques, resulting in more diffuse Aβ plaques and increased peri-plaque neuritic dystrophy and AD-tau seeding. Thus, microglia and TREM2 are at a critical intersection of Aβ and tau pathologies in AD. Since genetically decreasing TREM2 function increases Aβ-induced tau seeding, we hypothesized that chronically increasing TREM2 signaling would decrease amyloid-induced tau-seeding and spreading. Using a mouse model of amyloidosis in which AD-tau is injected into the brain to induce Aβ-dependent tau seeding/spreading, we found that chronic administration of an activating TREM2 antibody increases peri-plaque microglial activation but surprisingly increases peri-plaque NP-tau pathology and neuritic dystrophy, without altering Aβ plaque burden. Our data suggest that sustained microglial activation through TREM2 that does not result in strong amyloid removal may exacerbate Aβ-induced tau pathology, which may have important clinical implications. © 2022 Jain et al.

Document Type: Article
Publication Stage: Final
Source: Scopus

An analysis-ready and quality controlled resource for pediatric brain white-matter research
(2022) Scientific Data, 9 (1), art. no. 616, . 

Richie-Halford, A.^a b , Cieslak, M.^c d e , Ai, L.^f , Caffarra, S.^a b g , Covitz, S.^c d e , Franco, A.R.^f h , Karipidis, I.I.^b i j k , Kruper, J.^l , Milham, M.^f h , Avelar-Pereira, B.^j , Roy, E.^b , Sydnor, V.J.^c d e , Yeatman, J.D.^a b , Abbott, N.J.ⁿ , Anderson, J.A.E.^o , Gagana, B.^ch , Bleile, M.L.^p , Bloomfield, P.S.^ch , Bottom, V.^q , Bourque, J.^p , Boyle, R.^s , Brynildsen, J.K.^r , Calarco, N.^t , Castrellon, J.J.^u , Chaku, N.^v , Chen, B.^w x , Chopra, S.^ch , Coffey, E.B.J.^y , Colenbier, N.^z , Cox, D.J.^aa , Crippen, J.E.^ch , Crouse, J.J.^ab , David, S.^ac , Leener, B.D.^ad , Delap, G.^ae , Deng, Z.-D.^af , Dugre, J.R.^ag , Eklund, A.^ah , Ellis, K.^ai , Ered, A.^aj , Farmer, H.^ak , Faskowitz, J.^al , Finch, J.E.^am , Flandin, G.^an , Flounders, M.W.^ch , Fonville, L.^ao , Frandsen, S.B.^ap , Garic, D.^aq , Garrido-Vásquez, P.^ar , Gonzalez-Escamilla, G.^as , Grogans, S.E.^at , Grotheer, M.^au , Gruskin, D.C.^av , Guberman, G.I.^aw , Haggerty, E.B.^r , Hahn, Y.^ch , Hall, E.H.^q , Hanson, J.L.^ax , Harel, Y.^ay , Vieira, B.H.^az , Hettwer, M.D.^ba , Hobday, H.^ch , Horien, C.^bb , Huang, F.^ch , Huque, Z.M.^r , James, A.R.^bc , Kahhale, I.^ax , Kamhout, S.L.H.^bd , Keller, A.S.^r , Khera, H.S.^ch , Kiar, G.^be , Kirk, P.A.^an , Kohl, S.H.^bf , Korenic, S.A.^ah , Korponay, C.^bg , Kozlowski, A.K.^bd , Kraljevic, N.^bf , Lazari, A.^bh , Leavitt, M.J.^bi , Li, Z.^bj , Liberati, G.^bk , Lorenc, E.S.^bl , Lossin, A.J.^ch , Lotter, L.D.^bf , Lydon-Staley, D.M.^r , Madan, C.R.^bm , Magielse, N.^bf , Marusak, H.A.^bn , Mayor, J.^bo , McGowan, A.L.^r , Mehta, K.P.^r , Meisler, S.L.^s , Michael, C.^bp , Mitchell, M.E.^aq , Morand-Beaulieu, S.^aw , Newman, B.T.^bq , Nielsen, J.A.^bd , O’Mara, S.M.^br , Ojha, A.^ax , Omary, A.^ch , Özarslan, E.^bs , Parkes, L.^r , Peterson, M.^bd , Pines, A.R.^bt , Pisanu, C.^bu , Rich, R.R.^bp , Sahoo, A.K.^bv , Samara, A.^bj , Sayed, F.^r , Schneider, J.T.^ch , Shaffer, L.S.^bw , Shatalina, E.^ao , Sims, S.A.^bx , Sinclair, S.^ch , Song, J.W.^r , Hogrogian, G.S.^ch , Tooley, U.A.^r , Tripathi, V.^by , Turker, H.B.^bz , Valk, S.L.^ca , Wall, M.B.^ao , Walther, C.K.^bv , Wang, Y.^ch , Wegmann, B.^bs , Welton, T.^cb , Wiesman, A.I.^aw , Wiesman, A.G.^ch , Wiesman, M.^ch , Winters, D.E.^cc , Yuan, R.^ch , Zacharek, S.J.^cd , Zajner, C.^ce , Zakharov, I.^cf , Zammarchi, G.^bu , Zhou, D.^r , Zimmerman, B.^cg , Zoner, K.^ch , Satterthwaite, T.D.^c d e , Rokem, A.^l m , The Fibr Community Science Consortium^ch

^a Stanford University, Division of Developmental and Behavioral Pediatrics, Stanford, CA 94305, United States
^b Stanford University, Graduate School of Education, Stanford, CA 94305, United States
^c Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
^d Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children’s Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, United States
^e Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
^f Child Mind Institute, Center for the Developing Brain, New York City, NY 10022, United States
^g University of Modena and Reggio Emilia, Department of Biomedical, Metabolic and Neural Sciences, Modena, 41125, Italy
^h Nathan Kline Institute for Psychiatric Research, Center for Biomedical Imaging and Neuromodulation, Orangeburg, NY 10962, United States
ⁱ Stanford University, Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford, CA 94305, United States
^j University of Zurich, Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, Zurich, 8032, Switzerland
^k Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, 8057, Switzerland
^l University of Washington, Department of Psychology, Seattle, WA 98195, United States
^m University of Washington, eScience Institute, Seattle, WA 98195, United States
ⁿ Old Dominion University, Norfolk, VA 23529, United States
^o Carleton University, Northfield, MN 55057, United States
^p Southern Methodist University, Dallas, TX 75275, United States
^q University of California-Davis, Davis, CA 95616, United States
^r University of Pennsylvania, Philadelphia, PA 19104, United States
^s Harvard University, Cambridge, MA 2138, United States
^t University of Toronto, Toronto, ON M5T 2S8, Canada
^u Duke University, Durham, NC 27708, United States
^v University of Michigan-Ann Arbor, Ann Arbor, MI 48109, United States
^w San Diego State University, San Diego, CA 92182, United States
^x University of California-San Diego, La JollaCA 92093, United States
^y Concordia University, Montréal, QC H4B 1R6, Canada
^z Katholieke Universiteit Leuven, Leuven, 3000, Belgium
^aa University of Manchester, Manchester, M13 9PL, United Kingdom
^ab University of Sydney, Camperdown, NSW 2006, Australia
^ac University Medical Center Utrecht, Utrecht, 3584 CX, Netherlands
^ad Polytechnique Montreal, Montréal, QC H3T 1J4, Canada
^ae University of Rochester, Rochester, NY 14627, United States
^af National Institute of Mental Health, Bethesda, MD 20892, United States
^ag Centre de Recherche de l’Institut Universitaire en Santé Mentale de Montréal, Montréal, QC H1N 3M5, Canada
^ah Linköping university, Linköping, 581 83, Sweden
^ai Monash University, Clayton, VIC 3800, Australia
^aj Temple University, Philadelphia, PA 19122, United States
^ak University of Greenwich, London, SE10 9LS, United Kingdom
^al Indiana University-Bloomington, Bloomington, IN 47405, United States
^am Georgia State University, Atlanta, GA 30303, United States
^an University College London, London, WC1E 6BT, United Kingdom
^ao Imperial College London, London, SW7 2BX, United Kingdom
^ap Brigham and Women’s Hospital, Boston, MA 02115, United States
^aq University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
^ar University of Concepción, Bio Bio, Concepción, Chile
^as Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Mainz, 55131, Germany
^at University of Maryland-College Park, College Park, MD 20742, United States
^au Philipps-Universität Marburg, Marburg, 35037, Germany
^av Columbia University, New York, NY 10027, United States
^aw McGill University, Montreal, QC H3A 0G4, Canada
^ax University of Pittsburgh, Pittsburgh, PA 15260, United States
^ay University of Montréal, Montreal, QC H3T 1J4, Canada
^az Universidade de São Paulo, Ribeirão Preto, Brazil
^ba Heinrich-Heine University Dusseldorf, Düsseldorf, 40225, Germany
^bb Yale University, New Haven, CT 6520, United States
^bc University of Chicago, Chicago, IL 60637, United States
^bd Brigham Young University, Provo, UT 84602, United States
^be Child Mind Institute, New York, NY 10022, United States
^bf Institute of Neurosciences and Medicine, Forschungszentrum Jülich, Jülich, 52425, Germany
^bg McLean Hospital, Belmont, MA 02478, United States
^bh University of Oxford, Oxford, OX1 2JD, United Kingdom
^bi Auburn University, Auburn, AL 36849, United States
^bj Washington University in St Louis, Saint Louis, MO 63130, United States
^bk Université catholique de Louvain, Ottignies-Louvain-la-Neuve, 1348, Belgium
^bl University of Texas at Austin, Austin, TX 78705, United States
^bm University of Nottingham, Nottingham, NG7 2RD, United Kingdom
^bn Wayne State University, Detroit, MI 48202, United States
^bo University of Oslo, Oslo, 0315, Norway
^bp University of Michigan, Ann Arbor, MI 48109, United States
^bq University of Virginia, Charlottesville, VA 22903, United States
^br Trinity College Dublin, Dublin 2, Ireland
^bs Linköping University, Linköping, 581 83, Sweden
^bt Stanford University, Stanford, CA 94305, United States
^bu University of Cagliari, CA, Cagliari, 09124, Italy
^bv University of Florida, Gainesville, FL 32611, United States
^bw George Mason University, Fairfax, VA 22030, United States
^bx University of Alabama at Birmingham, Birmingham, AL 35294, United States
^by Boston University, Boston, MA 2215, United States
^bz Cornell University, Ithaca, NY 14853, United States
^ca Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04103, Germany
^cb National Neuroscience Institute, Singapore, 308433, Singapore
^cc University of Colorado School of Medicine, Aurora, CO 80045, United States
^cd Massachusetts Institute of Technology, Cambridge, MA 02139, United States
^ce Western Unviersity, London, ON N6A 3K7, Canada
^cf Psychological Institute of Russian Academy of Education, Moscow, 129366, Russian Federation
^cg University of Illinois Urbana-Champaign, Champaign, IL 61820, United States

Abstract
We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets. © 2022, The Author(s).

Funding details
1RF1MH121868-01
National Institute of Mental HealthNIMH1R01EB027585-01
National Institute of Biomedical Imaging and BioengineeringNIBIBR01MH120482

Document Type: Data Paper
Publication Stage: Final
Source: Scopus

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond
(2022) Scientific Reports, 12 (1), art. no. 16873, . 

Gaddis, N.^a , Mathur, R.^a , Marks, J.^a , Zhou, L.^a , Quach, B.^a , Waldrop, A.^a , Levran, O.^b , Agrawal, A.^c , Randesi, M.^b , Adelson, M.^d , Jeffries, P.W.^c , Martin, N.G.^e , Degenhardt, L.^f , Montgomery, G.W.^g , Wetherill, L.^h , Lai, D.^h , Bucholz, K.^c , Foroud, T.^h , Porjesz, B.ⁱ , Runarsdottir, V.^j , Tyrfingsson, T.^j , Einarsson, G.^k , Gudbjartsson, D.F.^k , Webb, B.T.^a , Crist, R.C.^l , Kranzler, H.R.^l , Sherva, R.^aa , Zhou, H.^m , Hulse, G.ⁿ , Wildenauer, D.ⁿ , Kelty, E.^o , Attia, J.^p , Holliday, E.G.^p q , McEvoy, M.^p q , Scott, R.J.^r , Schwab, S.G.^s , Maher, B.S.^t , Gruza, R.^u , Kreek, M.J.^b , Nelson, E.C.^c , Thorgeirsson, T.^k , Stefansson, K.^k v , Berrettini, W.H.^l , Gelernter, J.^w , Edenberg, H.J.^x , Bierut, L.^y , Hancock, D.B.^a , Johnson, E.O.^a z

^a GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, United States
^b The Laboratory of the Biology of Addictive Diseases, The Rockefeller University, New York, NY, United States
^c Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^d Dr. Miriam and Sheldon G. Adelson Clinic for Drug Abuse, Treatment and Research, Las Vegas, NV, United States
^e Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
^f National Drug and Alcohol Research Centre, University of New South Wales, Randwick, NSW, Australia
^g Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
^h Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
ⁱ Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, United States
^j SAA-National Center of Addiction Medicine, Vogur Hospital, Reykjavik, Iceland
^k deCODE Genetics/Amgen, Reykjavik, Iceland
^l Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
^m Department of Psychiatry, Yale University School of Medicine, West Haven, CT, United States
ⁿ School of Psychiatry and Clinical Neurosciences, The University of Western Australia, Perth, WA, Australia
^o School of Population and Global Health, Population and Public Health, The University of Western Australia, Perth, WA, Australia
^p Hunter Medical Research Institute, Newcastle, Australia
^q School of Medicine and Public Health, The University of Newcastle, Callaghan, NSW, Australia
^r School of Biomedical Sciences and Pharmacy College of Health, Medicine and Wellbeing, The University of Newcastle, New Lambton Heights, NSW, Australia
^s Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW, Australia
^t Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
^u Department of Family and Community Medicine, Saint Louis University, Saint Louis, MO, United States
^v Faculty of Medicine, University of Iceland, Reyjavik, Iceland
^w Department of Psychiatry, Genetics, & Neuroscience, Yale University School of Medicine, West Haven, CT, United States
^x Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, United States
^y Department of Psychiatry, Washington University, St. Louis, MO, United States
^z Fellow Program, RTI International, Research Triangle Park, NC, United States
^aa Genome Science Institute, Boston University, Boston, MA, United States

Abstract
Opioid addiction (OA) is moderately heritable, yet only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data together with published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p = 2.56 × 10–9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits. © 2022, The Author(s).

Funding details
National Institutes of HealthNIH
National Institute of Mental HealthNIMH
National Institute on Drug AbuseNIDA
National Heart, Lung, and Blood InstituteNHLBI
National Human Genome Research InstituteNHGRI
National Cancer InstituteNCI
National Institute of Neurological Disorders and StrokeNINDS
California Department of Fish and GameDFG
Dr. Miriam and Sheldon G. Adelson Medical Research FoundationAMRFUL1RR024143
National Center for Advancing Translational SciencesNCATS
Rockefeller University
European CommissionECH2020-2020–848099

Document Type: Article
Publication Stage: Final
Source: Scopus

Spontaneous activity patterns in human motor cortex replay evoked activity patterns for hand movements
(2022) Scientific Reports, 12 (1), art. no. 16867, . 

Livne, T.^a b , Kim, D.H.^b , Metcalf, N.V.^b , Zhang, L.^c d , Pini, L.^c d , Shulman, G.L.^b , Corbetta, M.^b c d

^a Weizmann Institute of Science, Rehovot, 7610001, Israel
^b Washington University in Saint Louis, St. Louis, 63110, United States
^c Department of Neuroscience and Padova Neuroscience Center, University of Padova, Padova, 35131, Italy
^d Venetian Institute of Molecular Medicine (VIMM), Padova, 35129, Italy

Abstract
Spontaneous brain activity, measured with resting state fMRI (R-fMRI), is correlated among regions that are co-activated by behavioral tasks. It is unclear, however, whether spatial patterns of spontaneous activity within a cortical region correspond to spatial patterns of activity evoked by specific stimuli, actions, or mental states. The current study investigated the hypothesis that spontaneous activity in motor cortex represents motor patterns commonly occurring in daily life. To test this hypothesis 15 healthy participants were scanned while performing four different hand movements. Three movements (Grip, Extend, Pinch) were ecological involving grip and grasp hand movements; one control movement involving the rotation of the wrist was not ecological and infrequent (Shake). They were also scanned at rest before and after the execution of the motor tasks (resting-state scans). Using the task data, we identified movement-specific patterns in the primary motor cortex. These task-defined patterns were compared to resting-state patterns in the same motor region. We also performed a control analysis within the primary visual cortex. We found that spontaneous activity patterns in the primary motor cortex were more like task patterns for ecological than control movements. In contrast, there was no difference between ecological and control hand movements in the primary visual area. These findings provide evidence that spontaneous activity in human motor cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life. © 2022, The Author(s).

Funding details
55403
CUP C94I20000420007
869505, H2020-SC5-2019-2
RF-2019-12369300
RF-2008-12366899
MART_ECCELLENZA18_01
Washington University in St. LouisWUSTL
Fondazione Cassa di Risparmio di Padova e Rovigo
Weizmann Institute of ScienceWIS
Ministry of Aliyah and Immigrant Absorption
Ministero dell’Istruzione, dell’Università e della RicercaMIUR
China Scholarship CouncilCSC
Fundação Bial361/18
Horizon 2020

Document Type: Article
Publication Stage: Final
Source: Scopus

A randomized phase 2 clinical trial of phentolamine mesylate eye drops in patients with severe night vision disturbances
(2022) BMC Ophthalmology, 22 (1), art. no. 402, . 

Pepose, J.^a b , Brigell, M.^c , Lazar, E.^d , Heisel, C.^c , Yousif, J.^c , Rahmani, K.^c , Kolli, A.^c , Hwang, M.^c , Mitrano, C.^c , Lazar, A.^c , Charizanis, K.^c , Sooch, M.^c , McDonald, M.^e

^a Pepose Vision Institute, St. Louis, MO, United States
^b Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, St. Louis, MO, United States
^c Ocuphire Pharma, Inc., 37000 Grand River Ave., Suite 120, Farmington Hills, MI 48335, United States
^d elCON Medical, Buffalo, NY, United States
^e Department of Ophthalmology, New York University Langone Medical Center, New York, NY, United States

Abstract
Purpose: Dim light vision disturbances (DLD) comprise a wide range of symptoms affecting the quality of vision at low illumination including glare, halos, and starbursts. This exploratory study investigated 1.0% phentolamine mesylate ophthalmic solution (PMOS) as a treatment to improve vision and image quality for patients with DLD. Methods: In this placebo-controlled, randomized, double-masked clinical trial, 24 adult patients with severe DLD were randomized in a 2:1 ratio to receive either one dose of PMOS or placebo. Subjects were eligible if they reported experiencing severe night vision difficulty that was not eliminated by distance spectacle correction and scored ≥0.3 log units below the normal range of contrast sensitivity assessed under mesopic conditions with glare at ≥2 spatial frequencies. Key efficacy outcomes were change from baseline in pupil diameter, contrast sensitivity, and visual acuity. Safety measures including intraocular pressure, conjunctival hyperemia, and systemic effects were also assessed. Results: Eight subjects were randomized to placebo (63% female; mean age 47 years) and 16 were randomized to PMOS (75% female; mean age 42 years). Mean (SD) pupil diameter of PMOS-treated subjects decreased significantly − 1.3 mm (0 to − 2.8 mm) with p < 0.0001. Mean contrast sensitivity with glare in PMOS-treated subjects improved significantly post-treatment at spatial frequencies 3, 6, 12, and 18 cycles per degree (p ≤ 0.03). PMOS also demonstrated improvements in the numbers of letters read for mesopic and photopic, high- and low-contrast visual acuity (LCVA). Importantly, a statistically greater proportion of PMOS-treated eyes registered mesopic LCVA 5 letter (69% vs. 31%, p = 0.029) and 10 letter (34% vs. 6%, p = 0.04) improvement, with a trend at 15 letters (19% vs. 0%, p = 0.16). PMOS was well tolerated with the only reported side effect being a mild increase in conjunctival hyperemia. Conclusion: PMOS was well tolerated and effectively reduced pupil size with improvements in contrast sensitivity and visual acuity in adults with severe DLD. Future Phase 3 studies should be conducted to further evaluate its potential to treat DLD. Trial registration: The trial registration number is NCT04004507 (02/07/2019). Retrospectively registered. © 2022, The Author(s).

Author Keywords
Dim Light Disturbance;  DLD;  Glare;  Halos;  Night Vision Disturbance;  NVD;  Phentolamine;  Photic Phenomenon;  Starburst

Document Type: Article
Publication Stage: Final
Source: Scopus

Gut-innervating nociceptors regulate the intestinal microbiota to promote tissue protection
(2022) Cell, 185 (22), pp. 4170-4189.e20. Cited 2 times.

Zhang, W.^a , Lyu, M.^a , Bessman, N.J.^a , Xie, Z.^d , Arifuzzaman, M.^a , Yano, H.^a , Parkhurst, C.N.^a , Chu, C.^a , Zhou, L.^a , Putzel, G.G.^a , Li, T.-T.^a , Jin, W.-B.^a , Zhou, J.^a , Hu, H.^d , Tsou, A.M.^a b c , Guo, C.-J.^a b , Artis, D.^a b , JRI Live Cell Bank^e

^a Jill Roberts Institute for Research in Inflammatory Bowel Disease, Joan and Sanford I. Weill Department of Medicine, Department of Microbiology and Immunology, Weill Cornell Medicine, Cornell University, New York, NY 10021, United States
^b Friedman Center for Nutrition and Inflammation, Joan and Sanford I. Weill Department of Medicine, Department of Microbiology and Immunology, Weill Cornell Medicine, Cornell University, New York, NY 10021, United States
^c Division of Pediatric Gastroenterology, Hepatology and Nutrition, Weill Cornell Medical College, New York, NY, United States
^d Department of Anesthesiology, The Center for the Study of Itch, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Nociceptive pain is a hallmark of many chronic inflammatory conditions including inflammatory bowel diseases (IBDs); however, whether pain-sensing neurons influence intestinal inflammation remains poorly defined. Employing chemogenetic silencing, adenoviral-mediated colon-specific silencing, and pharmacological ablation of TRPV1+ nociceptors, we observed more severe inflammation and defective tissue-protective reparative processes in a murine model of intestinal damage and inflammation. Disrupted nociception led to significant alterations in the intestinal microbiota and a transmissible dysbiosis, while mono-colonization of germ-free mice with Gram+ Clostridium spp. promoted intestinal tissue protection through a nociceptor-dependent pathway. Mechanistically, disruption of nociception resulted in decreased levels of substance P, and therapeutic delivery of substance P promoted tissue-protective effects exerted by TRPV1+ nociceptors in a microbiota-dependent manner. Finally, dysregulated nociceptor gene expression was observed in intestinal biopsies from IBD patients. Collectively, these findings indicate an evolutionarily conserved functional link between nociception, the intestinal microbiota, and the restoration of intestinal homeostasis. © 2022 Elsevier Inc.

Author Keywords
IBD;  intestinal damage and inflammation;  intestinal microbiota;  neuron-microbiota crosstalk;  substance P;  tissue protection;  TRPV1+ nociceptor

Funding details
DP2 HD101401-01, F32AI124517
National Institutes of HealthNIHAI095466, AI095608, AI151599, AI172027, AR070116, DK126871, DK132244
W. M. Keck FoundationWMKFAA027065, AR077183, DK103901
CURE Childhood Cancer
Pfizer
AGA Research Foundation
Takeda Pharmaceuticals U.S.A.TPUSA
Kortney Rose FoundationKRF
Crohn’s and Colitis FoundationCCF527125, 901000
LEO Fondet

Document Type: Article
Publication Stage: Final
Source: Scopus

Prenatal exposure to maternal social disadvantage and psychosocial stress and neonatal white matter connectivity at birth
(2022) Proceedings of the National Academy of Sciences of the United States of America, 119 (42), pp. e2204135119. 

Lean, R.E.^a , Smyser, C.D.^b c d , Brady, R.G.^d , Triplett, R.L.^d , Kaplan, S.^d , Kenley, J.K.^d , Shimony, J.S.^c , Smyser, T.A.^a , Miller, J.P.^e , Barch, D.M.^a c f , Luby, J.L.^a , Warner, B.B.^b g , Rogers, C.E.^a b

^a Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
^b Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
^c Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
^d Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
^e Department of Biostatistics, Institute for Informatics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States
^f Department of Psychological and Brain Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO 63130, United States
^g Department of Newborn Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, United States

Abstract
Early life adversity (social disadvantage and psychosocial stressors) is associated with altered microstructure in fronto-limbic pathways important for socioemotional development. Understanding when these associations begin to emerge may inform the timing and design of preventative interventions. In this longitudinal study, 399 mothers were oversampled for low income and completed social background measures during pregnancy. Measures were analyzed with structural equation analysis resulting in two latent factors: social disadvantage (education, insurance status, income-to-needs ratio [INR], neighborhood deprivation, and nutrition) and psychosocial stress (depression, stress, life events, and racial discrimination). At birth, 289 healthy term-born neonates underwent a diffusion MRI (dMRI) scan. Mean diffusivity (MD) and fractional anisotropy (FA) were measured for the dorsal and inferior cingulum bundle (CB), uncinate, and fornix using probabilistic tractography in FSL. Social disadvantage and psychosocial stress were fitted to dMRI parameters using regression models adjusted for infant postmenstrual age at scan and sex. Social disadvantage, but not psychosocial stress, was independently associated with lower MD in the bilateral inferior CB and left uncinate, right fornix, and lower MD and higher FA in the right dorsal CB. Results persisted after accounting for maternal medical morbidities and prenatal drug exposure. In moderation analysis, psychosocial stress was associated with lower MD in the left inferior CB among the lower-to-higher socioeconomic status (SES) (INR ≥ 200%) group, but not the extremely low SES (INR < 200%) group. Increasing access to social welfare programs that reduce the burden of social disadvantage and related psychosocial stressors may be an important target to protect fetal brain development in fronto-limbic pathways.

Author Keywords
depression;  diffusion MRI;  prenatal;  social disadvantage;  stress

Document Type: Article
Publication Stage: Final
Source: Scopus

Neuropsychological Correlates of Changes in Driving Behavior Among Clinically Healthy Older Adults
(2022) The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 77 (10), pp. 1769-1778. 

Aschenbrenner, A.J.^a , Murphy, S.A.^a , Doherty, J.M.^a , Johnson, A.M.^b , Bayat, S.^c d e , Walker, A.^a , Peña, Y.^a , Hassenstab, J.^a , Morris, J.C.^a , Babulal, G.M.^a f g h

^a Department of Neurology, Washington University in St. Louis, St. Louis, MO, United States
^b Center for Clinical Studies, Washington University in St. Louis, St. Louis, MO, United States
^c Department of Biomedical Engineering, University of Calgary, Calgary, AB, Canada
^d Department of Geomatics Engineering, University of Calgary, Calgary, AB, Canada
^e Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
^f Institute of Public Health, Washington University in St. Louis, St. Louis, MO, United States
^g Department of Psychology, Faculty of Humanities, University of Johannesburg, Johannesburg, South Africa
^h Department of Clinical Research and Leadership, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA

Abstract
OBJECTIVES: To determine the extent to which cognitive domain scores moderate change in driving behavior in cognitively healthy older adults using naturalistic (Global Positioning System-based) driving outcomes and to compare against self-reported outcomes using an established driving questionnaire. METHODS: We analyzed longitudinal naturalistic driving behavior from a sample (N = 161, 45% female, mean age = 74.7 years, mean education = 16.5 years) of cognitively healthy, nondemented older adults. Composite driving variables were formed that indexed “driving space” and “driving performance.” All participants completed a baseline comprehensive cognitive assessment that measured multiple domains as well as an annual self-reported driving outcomes questionnaire. RESULTS: Across an average of 24 months of naturalistic driving, our results showed that attentional control, broadly defined as the ability to focus on relevant aspects of the environment and ignore distracting or competing information as measured behaviorally with tasks such as the Stroop color naming test, moderated change in driving space scores over time. Specifically, individuals with lower attentional control scores drove fewer trips per month, drove less at night, visited fewer unique locations, and drove in smaller spaces than those with higher attentional control scores. No cognitive domain predicted driving performance such as hard braking or sudden acceleration. DISCUSSION: Attentional control is a key moderator of change over time in driving space but not driving performance in older adults. We speculate on mechanisms that may relate attentional control ability to modifications of driving behaviors. © The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Author Keywords
Attentional control;  Naturalistic driving;  Self-regulation

Document Type: Article
Publication Stage: Final
Source: Scopus

Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis
(2022) Cancer Research, 82 (19), pp. 3603-3613. Cited 1 time.

Devan, S.P.^a b , Jiang, X.^a c , Luo, G.^d , Xie, J.^a , Quirk, J.D.^e , Engelbach, J.A.^e , Harmsen, H.^f , McKinley, E.T.^g , Cui, J.^a c , Zu, Z.^a c , Attia, A.^d , Garbow, J.R.^e h , Gore, J.C.^a c i j , McKnight, C.D.^c , Kirschner, A.N.^d , Xu, J.^a c i j

^a Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States
^b Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN, United States
^c Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
^d Department of Radiation Oncology, Vanderbilt University Medical Center, Nashville, TN, United States
^e Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, United States
^f Department of Pathology, Microbiology, Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
^g Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN, United States
^h Alvin J. Siteman Cancer Center, Washington University, St. Louis, MO, United States
ⁱ Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
^j Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States

Abstract
Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly. Here, we developed, validated, and evaluated a new MRI technique termed selective size imaging using filters via diffusion times (SSIFT) to differentiate brain tumors from radiotherapy necrosis in the brain. This approach generates a signal filter that leverages diffusion time dependence to establish a cell size-weighted map. Computer simulations in silico, cultured cancer cells in vitro, and animals with brain tumors in vivo were used to comprehensively validate the specificity of SSIFT for detecting typical large cancer cells and the ability to differentiate brain tumors from radiotherapy necrosis. SSIFT was also implemented in patients with metastatic brain cancer and radiotherapy necrosis. SSIFT showed high correlation with mean cell sizes in the relevant range of less than 20 μm. The specificity of SSIFT for brain tumors and reduced contrast in other brain etiologies allowed SSIFT to differentiate brain tumors from peritumoral edema and radiotherapy necrosis. In conclusion, this new, cell size-based MRI method provides a unique contrast to differentiate brain tumors from other pathologies in the brain. SIGNIFICANCE: This work introduces and provides preclinical validation of a new diffusion MRI method that exploits intrinsic differences in cell sizes to distinguish brain tumors and radiotherapy necrosis. ©2022 American Association for Cancer Research.

Document Type: Article
Publication Stage: Final
Source: Scopus

Predictive Value of the Advanced Lipoprotein Profile and Glycated Proteins on Diabetic Retinopathy
(2022) Nutrients, 14 (19), art. no. 3932, . 

Julve, J.^a b , Rossell, J.^a b c , Correig, E.^d , Rojo-Lopez, M.I.^a c , Amigó, N.^e f , Hernández, M.^g , Traveset, A.^h , Carbonell, M.ⁱ , Alonso, N.^b j k , Mauricio, D.^b c l m , Castelblanco, E.^m n

^a Institut d’Investigació Biomèdica Sant Pau (IIB Sant Pau), Barcelona, 08041, Spain
^b CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, 28029, Spain
^c Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, 08025, Spain
^d Department of Biostatistics, Rovira i Virgili University, Reus, 43201, Spain
^e Biosfer Teslab, SL, Reus, 43201, Spain
^f Metabolomics Platform, Institute of Health Research Pere Virgili (IISPV) and Rovira i Virgili University (URV), Reus, 43204, Spain
^g Department of Endocrinology & Nutrition, Arnau de Vilanova University Hospital and Lleida Biomedical Research Institute (IRBLleida), Lleida, 25198, Spain
^h Department of Ophthalmology, Arnau de Vilanova University Hospital and Lleida Biomedical Research Institute (IRBLleida), Lleida, 25198, Spain
ⁱ Department of Ophthalmology, Germans Trias i Pujol University Hospital, Badalona, 08916, Spain
^j Department of Endocrinology & Nutrition, Germans Trias i Pujol University Hospital, Badalona, 08916, Spain
^k Department of Medicine, Autonomous University of Barcelona, Barcelona, 08916, Spain
^l Faculty of Medicine, University of Vic (UVIC/UCC), Vic, 08500, Spain
^m Unitat de Suport a la Recerca Barcelona, Institut Universitari d’Investigació en Atenció Primària Jordi Gol i Gurina (IDIAP Jordi Gol), Barcelona, 08007, Spain
ⁿ Endocrinology, Metabolism and Lipid Research Division, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
This study aimed to assess whether the advanced characteristics of serum lipoprotein subclasses could better predict the risk of developing diabetic retinopathy (DR) and its severity compared to other established risk factors in subjects with type 1 (T1D) and type 2 (T2D) diabetes. This observational, cross-sectional substudy analyzed DR-related data from 309 T1D and 264 T2D subjects. The advanced lipoprotein and glycoprotein profile was determined by nuclear magnetic resonance (NMR) spectroscopy (Liposcale test). NMR analysis of lipoproteins revealed that T1D subjects with DR showed standard non-HDL particles, despite higher IDL lipid concentrations. Notably, IDL lipids were elevated in T1D subjects with worsened DR. VLDL and LDL were smaller, whereas HDL triglycerides were increased in DR compared with non-DR. On the other hand, the T2D subjects with DR showed altered characteristics in the LDL fraction, mainly revealed by a significant decrease in smaller LDL and a reduction in LDL-C. Moreover, the glycoprotein profile did not reveal significant changes among DR groups, regardless of the type of diabetes. However, lipoprotein characteristics and glycoproteins unveiled by NMR analysis did not improve the predictive value of conventional lipids or other traditional, well-established biomarkers of DR in our cohorts. © 2022 by the authors.

Author Keywords
diabetic retinopathy;  glycoproteins;  lipoproteins;  nuclear magnetic resonance spectroscopy;  remnants;  triglycerides;  type 1 diabetes;  type 2 diabetes

Funding details
CB15/00071
Fundació la Marató de TV3201602.30.31, 303/C/2016, CPII18/00004
Federación Española de Enfermedades RarasFEDER
Instituto de Salud Carlos IIIISCIIIPI15/0625, PI17/00232, PI17/01362
Ministerio de Ciencia e InnovaciónMICINN

Document Type: Article
Publication Stage: Final
Source: Scopus

Temporal order of clinical and biomarker changes in familial frontotemporal dementia
(2022) Nature Medicine, 28 (10), pp. 2194-2206. 

Staffaroni, A.M.^a , Quintana, M.^b , Wendelberger, B.^b , Heuer, H.W.^a , Russell, L.L.^c , Cobigo, Y.^a , Wolf, A.^a , Goh, S.-Y.M.^a , Petrucelli, L.^d , Gendron, T.F.^d , Heller, C.^c , Clark, A.L.^a , Taylor, J.C.^a , Wise, A.^a , Ong, E.^a , Forsberg, L.^e , Brushaber, D.^f , Rojas, J.C.^a , VandeVrede, L.^a , Ljubenkov, P.^a , Kramer, J.^a , Casaletto, K.B.^a , Appleby, B.^g , Bordelon, Y.^h , Botha, H.^e , Dickerson, B.C.ⁱ , Domoto-Reilly, K.^j , Fields, J.A.^k , Foroud, T.^l , Gavrilova, R.^e , Geschwind, D.^h m , Ghoshal, N.ⁿ , Goldman, J.^o , Graff-Radford, J.^e , Graff-Radford, N.^p , Grossman, M.^q , Hall, M.G.H.^a , Hsiung, G.-Y.^r , Huey, E.D.^o , Irwin, D.^q , Jones, D.T.^e , Kantarci, K.^e , Kaufer, D.^s , Knopman, D.^e , Kremers, W.^f , Lago, A.L.^a , Lapid, M.I.^k , Litvan, I.^t , Lucente, D.ⁱ , Mackenzie, I.R.^u , Mendez, M.F.^h , Mester, C.^f , Miller, B.L.^a , Onyike, C.U.^v , Rademakers, R.^d w x , Ramanan, V.K.^e , Ramos, E.M.^h , Rao, M.^e , Rascovsky, K.^q , Rankin, K.P.^a , Roberson, E.D.^y , Savica, R.^e , Tartaglia, M.C.^z , Weintraub, S.^aa , Wong, B.ⁱ , Cash, D.M.^c , Bouzigues, A.^c , Swift, I.J.^c , Peakman, G.^c , Bocchetta, M.^c , Todd, E.G.^c , Convery, R.S.^c , Rowe, J.B.^ab , Borroni, B.^ac , Galimberti, D.^ad ae , Tiraboschi, P.^af , Masellis, M.^ag , Finger, E.^ah , van Swieten, J.C.^ai , Seelaar, H.^ai , Jiskoot, L.C.^ai , Sorbi, S.^aj ak , Butler, C.R.^al am , Graff, C.^an ao , Gerhard, A.^ap aq , Langheinrich, T.^ap ar , Laforce, R.^as , Sanchez-Valle, R.^at , de Mendonça, A.^au , Moreno, F.^av aw , Synofzik, M.^ax ay , Vandenberghe, R.^az ba bb , Ducharme, S.^bc bd , Le Ber, I.^be bf bg , Levin, J.^bh bi bj , Danek, A.^bh , Otto, M.^bk , Pasquier, F.^bl bm bn , Santana, I.^bo bp , Kornak, J.^bq , Boeve, B.F.^e , Rosen, H.J.^a , Rohrer, J.D.^c , Boxer, A.L.^a , Frontotemporal Dementia Prevention Initiative (FPI) Investigators^br

^a Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, CA, United States
^b Berry Consultants, Austin, TX, United States
^c Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, United Kingdom
^d Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
^e Department of Neurology, Mayo Clinic, Rochester, MN, United States
^f Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
^g Department of Neurology, Case Western Reserve University, Cleveland, OH, United States
^h Department of Neurology, University of California, Los Angeles, United States
ⁱ Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
^j Department of Neurology, University of Washington, Seattle, WA, United States
^k Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
^l Indiana University School of Medicine, National Centralized Repository for Alzheimer’s, Indianapolis, IN, United States
^m Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, United States
ⁿ Departments of Neurology and Psychiatry, Washington University School of Medicine, Washington University, St. Louis, MO, United States
^o Department of Neurology, Columbia University, New York, NY, USA
^p Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
^q Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
^r Division of Neurology, University of British Columbia, Vancouver, BC, Canada
^s Department of Neurology, University of North Carolina, Chapel HillNC, United States
^t Department of Neurosciences, University of California, La Jolla, San Diego, CA, United States
^u Department of Pathology, University of British Columbia, Vancouver, BC, Canada
^v Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, United States
^w Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
^x Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
^y Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
^z Tanz Centre for Research in Neurodegenerative Diseases, Division of Neurology, University of Toronto, Toronto, ON, Canada
^aa Department of Neurology, Northwestern University, Chicago, IL, United States
^ab Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
^ac Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
^ad Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
^ae Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
^af Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy
^ag Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre; Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
^ah Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
^ai Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
^aj Department of Neurofarba, University of Florence, Florence, Italy
^ak IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
^al Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
^am Department of Brain Sciences, Imperial College London, London, United Kingdom
^an Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Solna, Sweden
^ao Unit for Hereditary Dementias, Karolinska University Hospital, Solna, Sweden
^ap Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of ManchesterManchester, United Kingdom
^aq Departments of Geriatric Medicine and Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, Essen, Germany
^ar Cerebral Function Unit, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, United Kingdom
^as Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, Université Laval, and Faculté de MédecineQuébec CityQuébec, Canada
^at Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d’Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
^au Faculty of Medicine, University of LisbonLisbon, Portugal
^av Cognitive Disorders Unit, Department of Neurology, Donostia University HospitalSan Sebastian, Spain
^aw Neuroscience Area, Biodonostia Health Research InstituteSan Sebastian, Spain
^ax Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
^ay Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
^az Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
^ba Neurology Service, University Hospitals Leuven, Leuven, Belgium
^bb Leuven Brain Institute, KU Leuven, Leuven, Belgium
^bc Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
^bd McConnell Brain Imaging Centre, Montreal Neurological Institute, Department of Neurology & Neurosurgery, McGill University, Montreal, Québec, Canada
^be Sorbonne Université, Paris Brain Institute – Institut du Cerveau – ICM, Inserm U1127, CNRS UMR 7225, AP-HP – Hôpital Pitié-Salpêtrière, Paris, France
^bf Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP – Hôpital Pitié-Salpêtrière, Paris, France
^bg Département de Neurologie, AP-HP – Hôpital Pitié-Salpêtrière, Paris, France
^bh Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
^bi Center for Neurodegenerative Diseases (DZNE), Munich, Germany
^bj Munich Cluster of Systems Neurology, Munich, Germany
^bk Department of Neurology, University of Ulm, Ulm, Germany
^bl University of Lille, Lille, France
^bm Inserm, Lille, France
^bn CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, Lille, France
^bo Neurology Service, Faculty of Medicine, University Hospital of Coimbra (HUC), University of CoimbraCoimbra, Portugal
^bp Center for Neuroscience and Cell Biology, Faculty of Medicine, University of CoimbraCoimbra, Portugal
^bq Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, United States

Abstract
Unlike familial Alzheimer’s disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects. © 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

Document Type: Article
Publication Stage: Final
Source: Scopus

Cellular Sources and Neuroprotective Roles of Interleukin-10 in the Facial Motor Nucleus after Axotomy
(2022) Cells, 11 (19), art. no. 3167, . 

Runge, E.M.^a b c , Setter, D.O.^a b d , Iyer, A.K.^a b e , Regele, E.J.^a b f , Kennedy, F.M.^a b , Sanders, V.M.^g , Jones, K.J.^a b

^a Department of Anatomy, Cell Biology, and Physiology, Indiana University School of Medicine, Indianapolis, IN 46202, United States
^b Research and Development, Richard L. Roudebush VA Medical Center, Indianapolis, IN 46202, United States
^c Department of Physical Medicine and Rehabilitation, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, United States
^d Department of Neurology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905, United States
^e Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, United States
^f Department of Urology, Mayo Clinic College of Medicine and Science, Jacksonville, FL 32224, United States
^g Department of Cancer Biology and Genetics, The Ohio State University, Columbus, OH 43210, United States

Abstract
Facial motoneuron (FMN) survival is mediated by CD4+ T cells in an interleukin-10 (IL-10)-dependent manner after facial nerve axotomy (FNA), but CD4+ T cells themselves are not the source of this neuroprotective IL-10. The aims of this study were to (1) identify the temporal and cell-specific induction of IL-10 expression in the facial motor nucleus and (2) elucidate the neuroprotective capacity of this expression after axotomy. Immunohistochemistry revealed that FMN constitutively produced IL-10, whereas astrocytes were induced to make IL-10 after FNA. Il10 mRNA co-localized with microglia before and after axotomy, but microglial production of IL-10 protein was not detected. To determine whether any single source of IL-10 was critical for FMN survival, Cre/Lox mouse strains were utilized to selectively knock out IL-10 in neurons, astrocytes, and microglia. In agreement with the localization data reflecting concerted IL-10 production by multiple cell types, no single cellular source of IL-10 alone could provide neuroprotection after FNA. These findings suggest that coordinated neuronal and astrocytic IL-10 production is necessary for FMN survival and has roles in neuronal homeostasis, as well as neuroprotective trophism after axotomy. © 2022 by the authors.

Author Keywords
astrocyte;  axotomy;  CD4+ T cell;  facial nerve;  IL-10;  motoneuron;  nerve injury;  neuroprotection

Funding details
National Institutes of HealthNIH
National Institute of Neurological Disorders and StrokeNINDSNS40433

Document Type: Article
Publication Stage: Final
Source: Scopus

Prognostic significance of age within the adolescent and young adult acute ischemic stroke population after mechanical thrombectomy: insights from STAR
(2022) Journal of Neurosurgery: Pediatrics, 30 (4), pp. 448-454. 

Lu, V.M.^a , Luther, E.M.^a , Silva, M.A.^a , Elarjani, T.^a , Abdelsalam, A.^a , Maier, I.^b , Al Kasab, S.^c , Jabbour, P.M.^d , Kim, J.-T.^e , Wolfe, S.Q.^f , Rai, A.T.^g , Psychogios, M.-N.^h , Samaniego, E.A.ⁱ , Arthur, A.S.^j , Yoshimura, S.^k , Grossberg, J.A.^l , Alawieh, A.^l , Fragata, I.^m , Polifka, A.ⁿ , Mascitelli, J.^o , Osbun, J.^p , Park, M.S.^q , Levitt, M.R.^r , Dumont, T.^s , Cuellar, H.^t , Williamson, R.W., Jr.^u , Romano, D.G.^v , Crosa, R.^w , Gory, B.^x , Mokin, M.^y , Moss, M.^z , Limaye, K.^aa , Kan, P.^ab , Yavagal, D.R.^a , Spiotta, A.M.^c , Starke, R.M.^a

^a Department of Neurosurgery, University of Miami, Miami, FL, United States
^b Department of Neurology, University Medical Center Gottingen, Gottingen, Germany
^c Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
^d Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA, United States
^e Department of Neurosurgery, Chonnam National University Hospital, Gwangju, South Korea
^f Department of Neurosurgery, Wake Forest School of Medicine, Winston-Salem, NC, United States
^g Department of Neuroradiology, University of West Virginia, Morgantown, WV, United States
^h Department of Radiology, University Hospital Basel, Basel, Switzerland
ⁱ Department of Neurosurgery, University of Iowa, Iowa City, IA, United States
^j Department of Neurosurgery, Semmes Murphey Neurologic and Spine Clinic, Memphis, TN, United States
^k Department of Neurosurgery, Hyogo College of Medicine, Hyogo, Nishinomiya, Japan
^l Department of Neurosurgery, Emory University, Atlanta, GA, United States
^m Department of Neuroradiology, Hospital Sao Jose Centro Hospitalar Lisboa Central, Lisboa, Portugal
ⁿ Department of Neurosurgery, University of Florida, Gainesville, FL, United States
^o Department of Neurosurgery, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, United States
^p Department of Neurosurgery, Washington University in St. Louis, St. Louis, MO, United States
^q Department of Neurosurgery, University of Virginia, Charlottesville, VA, United States
^r Department of Neurosurgery, University of Washington, Seattle, WA, United States
^s Department of Neurosurgery, University of Arizona, Tucson, AZ, United States
^t Department of Radiology, Louisiana State University Health Shreveport, Shreveport, LA, United States
^u Department of Neurosurgery, Allegheny Health Network, Pittsburgh, PA, United States
^v Department of Neuroradiology, University Hospital San Giovanni di Dio e Ruggi d’Aragona, University of Salerno, Salerno, Italy
^w Department of Neurosurgery, Neurological Endovascular Center, Medica Uruguaya, Montevideo, Uruguay
^x Department of Interventional Neuroradiology, Centre Hospitalier Universitaire de Nancy, Nancy, France
^y Department of Neurosurgery, University of South Florida, Tampa, FL, United States
^z Department of Interventional Neuroradiology, Washington Regional Medical, Fayetteville, AR, United States
^aa Department of Interventional Neuroradiology, Indiana University, Indianapolis, IN, United States
^ab Department of Neurosurgery, University of Texas Medical Branch – Galveston, Galveston, TX, United States

Abstract
OBJECTIVE Although younger adults have been shown to have better functional outcomes after mechanical thrombectomy (MT) for acute ischemic stroke (AIS), the significance of this relationship in the adolescent and young adult (AYA) population is not well defined given its undefined rarity. Correspondingly, the goal of this study was to determine the prognostic significance of age in this specific demographic following MT for large-vessel occlusions. METHODS A prospectively maintained international multi-institutional database, STAR (Stroke Thrombectomy and Aneurysm Registry), was reviewed for all patients aged 12-18 (adolescent) and 19-25 (young adult) years. Parameters were compared using chi-square and t-test analyses, and associations were interrogated using regression analyses. RESULTS Of 7192 patients in the registry, 41 (0.6%) satisfied all criteria, with a mean age of 19.7 ± 3.3 years. The majority were male (59%) and young adults (61%) versus adolescents (39%). The median prestroke modified Rankin Scale (mRS) score was 0 (range 0-2). Strokes were most common in the anterior circulation (88%), with the middle cerebral artery being the most common vessel (59%). The mean onset-to-groin puncture and groin puncture-to-reperfusion times were 327 ± 229 and 52 ± 42 minutes, respectively. The mean number of passes was 2.2 ± 1.2, with 61% of the cohort achieving successful reperfusion. There were only 3 (7%) cases of reocclusion. The median mRS score at 90 days was 2 (range 0-6). Between the adolescent and young adult subgroups, the median mRS score at last follow-up was statistically lower in the adolescent subgroup (1 vs 2, p = 0.03), and older age was significantly associated with a higher mRS at 90 days (coefficient 0.33, p < 0.01). CONCLUSIONS Although rare, MT for AIS in the AYA demographic is both safe and effective. Even within this relatively young demographic, age remains significantly associated with improved functional outcomes. The implication of agedependent stroke outcomes after MT within the AYA demographic needs greater validation to develop effective agespecific protocols for long-term care across both pediatric and adult centers. © AANS 2022.

Author Keywords
adolescent;  Mechanical thrombectomy;  outcome;  pediatric;  stroke;  vascular disorders;  young adult

Document Type: Article
Publication Stage: Final
Source: Scopus

Infantile-onset Pompe disease complicated by sickle cell anemia: Case report and management considerations
(2022) Frontiers in Pediatrics, 10, art. no. 944178, . 

Starosta, R.T.^a , Hou, Y.-C.C.^b , Leestma, K.^a , Singh, P.^a , Viehl, L.^c , Manwaring, L.^a , Granadillo, J.L.^a , Schroeder, M.C.^b , Colombo, J.N.^d , Whitehead, H.^c , Dickson, P.I.^a , Hulbert, M.L.^e , Nguyen, H.T.^a

^a Division of Clinical Genetics and Genomics, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
^c Division of Newborn Medicine, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
^d Division of Pediatric Cardiology, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
^e Division of Pediatric Hematology and Oncology, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Infantile-onset Pompe disease (IOPD) is a rare, severe disorder of lysosomal storage of glycogen that leads to progressive cardiac and skeletal myopathy. IOPD is a fatal disease in childhood unless treated with enzyme replacement therapy (ERT) from an early age. Sickle cell anemia (SCA) is a relatively common hemoglobinopathy caused by a specific variant in the hemoglobin beta-chain. Here we report a case of a male newborn of African ancestry diagnosed and treated for IOPD and SCA. Molecular testing confirmed two GAA variants, NM_000152.5: c.842G&gt;C, p.(Arg281Pro) and NM_000152.5: c.2560C&gt;T, p.(Arg854*) in trans, and homozygosity for the HBB variant causative of SCA, consistent with his diagnosis. An acute neonatal presentation of hypotonia and cardiomyopathy required ERT with alglucosidase alfa infusions preceded by immune tolerance induction (ITI), as well as chronic red blood cell transfusions and penicillin V potassium prophylaxis for treatment of IOPD and SCA. Clinical course was further complicated by multiple respiratory infections. We review the current guidelines and interventions taken to optimize his care and the pitfalls of those guidelines when treating patients with concomitant conditions. To the best of our knowledge, no other case reports of the concomitance of these two disorders was found. This report emphasizes the importance of newborn screening, early intervention, and treatment considerations for this complex patient presentation of IOPD and SCA. Copyright © 2022 Starosta, Hou, Leestma, Singh, Viehl, Manwaring, Granadillo, Schroeder, Colombo, Whitehead, Dickson, Hulbert and Nguyen.

Author Keywords
alpha-glucosidase;  enzyme replacement therapy;  glycogen storage disorder type II;  immune tolerance induction;  methotrexate;  newborn screening;  sickle cell anemia

Funding details
St. Louis Children’s HospitalSLCH

Document Type: Article
Publication Stage: Final
Source: Scopus

Association of Stroke Lesion Pattern and White Matter Hyperintensity Burden With Stroke Severity and Outcome
(2022) Neurology, 99 (13), pp. E1364-E1379. 

Bonkhoff, A.K.^a , Hong, S.^a , Bretzner, M.^a b , Schirmer, M.D.^a c , Regenhardt, R.W.^a , Arsava, E.M.^a , Donahue, K.^a , Nardin, M.^a , Dalca, A.^d e , Giese, A.-K.^f , Etherton, M.R.^a , Hancock, B.L.^e , Mocking, S.J.T.^e , Mcintosh, E.^e , Attia, J.^g , Benavente, O.ⁱ , Cole, J.W.^j , Donatti, A.^k , Griessenauer, C.^l , Heitsch, L.^n o , Holmegaard, L.^p , Jood, K.^p , Jimenez-Conde, J.^q , Kittner, S.^j , Lemmens, R.^y , Levi, C.^y , Mcdonough, C.W.^j , Meschia, J.^s , Phuah, C.-L.^q , Rolfs, A.^r , Ropele, S.^r , Rosand, J.^a e h , Roquer, J.^q , Rundek, T.^t , Sacco, R.L.^u , Schmidt, R.^u , Sharma, P.^d , Slowik, A.^w , Soederholm, M.^w , Sousa, A.^l , Stanne, T.M.^v , Strbian, D.^x , Tatlisumak, T.^p , Thijs, V.^y , Vagal, A.^z ad , Wasselius, J.^ag , Woo, D.^ae , Zand, R.^r , Mcardle, P.^ab af , Worrall, B.B.^u , Jern, C.^aa , Lindgren, A.G.^ac , Maguire, J.^m , Golland, P.^v , Bzdok, D.^ah , Wu, O.^e , Rost, N.S.^a

^a J. Philip Kistler Stroke Research Center, Harvard Medical School, Massachusetts General Hospital, Boston, United States
^b Univ. Lille, Inserm, CHU Lille, U1171-LilNCog (JPARC)-Lille Neurosciences & Cognition, France
^c Clinic for Neuroradiology, University Hospital Bonn, Germany
^d Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Boston, United States
^e Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, United States
^f Department of Neurology, University Medical Center Hamburg-Eppendorf, Germany
^g Hunter Medical Research Institute, Newcastle, Australia
^h School of Medicine and Public Health, University of NewcastleNSW, Australia
ⁱ Department of Medicine, Division of Neurology, University of British Columbia, Vancouver, Canada
^j Department of Neurology, University of Maryland School of Medicine and Veterans Affairs Maryland Health Care System, Baltimore, United States
^k University of Campinas (UNICAMP) and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, SP, Campinas, Brazil
^l Department of Neurosurgery, PA, Danville, United States
^m Department of Neurosurgery, Christian Doppler Clinic, Paracelsus Medical University, Salzburg, Austria
ⁿ Department of Emergency Medicine, Washington University School of Medicine, United States
^o Department of Neurology, Washington University School of Medicine and Barnes-Jewish Hospital, St. Louis, MO, United States
^p Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, Sahlgrenska Academy, Gothenburg, Sweden
^q Neurovascular Research Group (NEUVAS), Department of Neurology, IMIM-Hospital del Mar (Institut Hospital del Mar D’Investigacions M`ediques), Universitat Autonoma de Barcelona, Spain
^r Experimental Neurology and Leuven Research Institute for Neuroscience and Disease (LIND), Department of Neurosciences, KU Leuven-University of Leuven, Belgium
^s Vesalius Research Center, Laboratory of Neurobiology, University Hospitals Leuven, Belgium
^t University of Newcastle, Department of Neurology, School of Medicine and Public Health, John Hunter Hospital, Newcastle, NSW, Australia
^u Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, University of Florida, Gainesville, United States
^v Department of Neurology, Mayo Clinic, Jacksonville, FL, United States
^w Centogene AG, Rostock, Germany
^x Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Austria
^y Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, United States
^z Department of Neurology and Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of MiamiFL, United States
^aa Institute of Cardiovascular Research, Royal Holloway University of London (ICR2UL), UK St Peter’s and Ashford Hospitals, Egham, United Kingdom
^ab Department of Neurology, Jagiellonian University Medical College, Krakow, Poland
^ac Department of Clinical Sciences Malm¨o, Lund University, Sweden
^ad Department of Neurology, Institute of Biomedicine, Skåne University Hospital, the Sahlgrenska Academy, Sweden
^ae Department of Neurology, Helsinki University Hospital and University of Helsinki, Finland
^af Florey Institute of Neuroscience and Mental Health and Department of Neurology, Stroke Division, Austin Health, Heidelberg, Australia
^ag Department of Radiology, University of Cincinnati College of MedicineOH, United States
^ah Department of Clinical Sciences Lund, Lund University, Sweden

Abstract
Background and ObjectivesTo examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways.MethodsMR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age2, sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts.ResultsA total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location.DiscussionHigher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions. © American Academy of Neurology.

Funding details
National Institutes of HealthNIH1R01NS114045-01
National Institute of Neurological Disorders and StrokeNINDSR01 NS100417, R01 NS103824, RF1 NS117643, U01NS100699, U01NS110772
National Institute of Biomedical Imaging and BioengineeringNIBIBNAC P41EB015902
Medtronic
Google
Canadian Institute for Advanced ResearchCIFARR01NS082285, R01NS086905, U19NS115388
Fondation Brain Canada
Health CanadaR01 AG068563A
Canadian Institutes of Health ResearchIRSCCIHR 438531
National Health and Medical Research CouncilNHMRC1023799
Hjärt-Lungfonden
Société Française de RadiologieSFR
Skånes universitetssjukhusSUS
Forschungsfabrik Mikroelektronik DeutschlandFMD

Document Type: Article
Publication Stage: Final
Source: Scopus

Weakly activated core neuroinflammation pathways were identified as a central signaling mechanism contributing to the chronic neurodegeneration in Alzheimer’s disease
(2022) Frontiers in Aging Neuroscience, 14, art. no. 935279, . 

Li, F.^a b c , Eteleeb, A.M.^c d e , Buchser, W.^f , Sohn, C.^c d e , Wang, G.^g , Xiong, C.^g , Payne, P.R.^a , McDade, E.^h , Karch, C.M.^c d e , Harari, O.^c d e , Cruchaga, C.^c d e

^a Institute for Informatics (I2), Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^b Department of Pediatrics, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^c NeuroGenomics and Informatics, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^d Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^e Hope Center for Neurological Disorders, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^f Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^g Division of Biostatistics, Washington University in St. Louis School of Medicine, St. Louis, MO, United States
^h Department of Neurology, Washington University in St. Louis School of Medicine, St. Louis, MO, United States

Abstract
Objectives: Neuroinflammation signaling has been identified as an important hallmark of Alzheimer’s disease (AD) in addition to amyloid β plaques (Aβ) and neurofibrillary tangles (NFTs). However, the molecular mechanisms and biological processes of neuroinflammation remain unclear and have not well delineated using transcriptomics data available. Our objectives are to uncover the core neuroinflammation signaling pathways in AD using integrative network analysis on the transcriptomics data. Materials and methods: From a novel perspective, i.e., investigating weakly activated molecular signals (rather than the strongly activated molecular signals), we developed integrative and systems biology network analysis to uncover potential core neuroinflammation signaling targets and pathways in AD using the two large-scale transcriptomics datasets, i.e., Mayo Clinic (77 controls and 81 AD samples) and ROSMAP (97 controls and 260 AD samples). Results: Our analysis identified interesting core neuroinflammation signaling pathways, which are not systematically reported in the previous studies of AD. Specifically, we identified 7 categories of signaling pathways implicated on AD and related to virus infection: immune response, x-core signaling, apoptosis, lipid dysfunctional, biosynthesis and metabolism, and mineral absorption signaling pathways. More interestingly, most of the genes in the virus infection, immune response, and x-core signaling pathways are associated with inflammation molecular functions. The x-core signaling pathways were defined as a group of 9 signaling proteins: MAPK, Rap1, NF-kappa B, HIF-1, PI3K-Akt, Wnt, TGF-beta, Hippo, and TNF, which indicated the core neuroinflammation signaling pathways responding to the low-level and weakly activated inflammation and hypoxia and leading to the chronic neurodegeneration. It is interesting to investigate the detailed signaling cascades of these weakly activated neuroinflammation signaling pathways causing neurodegeneration in a chronic process, and consequently uncover novel therapeutic targets for effective AD treatment and prevention. Conclusions: The potential core neuroinflammation and associated signaling targets and pathways were identified using integrative network analysis on two large-scale transcriptomics datasets of AD. Copyright © 2022 Li, Eteleeb, Buchser, Sohn, Wang, Xiong, Payne, McDade, Karch, Harari and Cruchaga.

Author Keywords
Alzheimer’s disease;  molecular mechanism;  neuroinflammation;  signaling network;  signaling targets

Funding details
National Institutes of HealthNIHP01AG003991, R01AG044546, RF1AG053303, RF1AG058501, U01AG058922
National Institute on AgingNIAR56AG065352
Biogen
Hope Center for Neurological Disorders
Chan Zuckerberg InitiativeCZI

Document Type: Article
Publication Stage: Final
Source: Scopus

Differences in Motor Features of C9orf72, MAPT, or GRN Variant Carriers With Familial Frontotemporal Lobar Degeneration
(2022) Neurology, 99 (11), pp. e1154-e1167. 

Tipton, P.W., Deutschlaender, A.B., Savica, R., Heckman, M.G., Brushaber, D.E., Dickerson, B.C., Gavrilova, R.H., Geschwind, D.H., Ghoshal, N., Graff-Radford, J., Graff-Radford, N.R., Grossman, M., Hsiung, G.-Y.R., Huey, E.D., Irwin, D.J., Jones, D.T., Knopman, D.S., McGinnis, S.M., Rademakers, R., Ramos, E.M., Forsberg, L.K., Heuer, H.W., Onyike, C., Tartaglia, C., Domoto-Reilly, K., Roberson, E.D., Mendez, M.F., Litvan, I., Appleby, B.S., Grant, I., Kaufer, D., Boxer, A.L., Rosen, H.J., Boeve, B.F., Wszolek, Z.K., ALLFTD Consortium

From the Department of Neurology (P.W.T., A.B.D., N.R.G.-R., Z.K.W.), Mayo Clinic, Jacksonville, FL; Department of Neurology (R.S., D.E.B., R.H.G., J.G.-R., D.T.J., D.S.K., L.K.F., B.F.B.), Mayo Clinic, Rochester, MN; Division of Clinical Trials and Biostatistics (M.G.H.), Mayo Clinic, Jacksonville, FL; Massachusetts General Hospital (B.C.D., S.M.M.), Harvard University, Boston; University of California, Los Angeles (UCLA) (D.H.G., E.M.R., M.F.M.); Washington University (N.G.), St. Louis, MO; University of Pennsylvania (M.G., D.J.I.), Philadelphia; University of British Columbia (G.-Y.R.H.), Vancouver, Canada; Columbia University (E.D.H.), New York; Department of Neuroscience (R.R.), Mayo Clinic, Jacksonville, FL; University of California, San Francisco (UCSF) (H.W.H., A.L.B., H.J.R.); Johns Hopkins University School of Medicine (C.O.), Baltimore, MD; University of Toronto (C.T.), Ontario, Canada; University of Washington (K.D.-R.), Seattle; University of Alabama at Birmingham (E.D.R.); University of California, San Diego (UCSD) (I.L.); Case Western Reserve University (B.S.A.), Cleveland, OH; Northwestern University (I.G.), Evanston, IL; and University of North Carolina (D.K.), Chapel Hill

Abstract
BACKGROUND AND OBJECTIVES: Familial frontotemporal lobar degeneration (f-FTLD) is a phenotypically heterogeneous spectrum of neurodegenerative disorders most often caused by variants within chromosome 9 open reading frame 72 (C9orf72), microtubule-associated protein tau (MAPT), or granulin (GRN). The phenotypic association with each of these genes is incompletely understood. We hypothesized that the frequency of specific clinical features would correspond with different genes. METHODS: We screened the Advancing Research and Treatment in Frontotemporal Lobar Degeneration (ARTFL)/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS)/ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration Consortium for symptomatic carriers of pathogenic variants in C9orf72, MAPT, or GRN. We assessed for clinical differences among these 3 groups based on data recorded as part of a detailed neurologic examination, the Progressive Supranuclear Palsy Rating Scale, Progressive Supranuclear Palsy-Quality of Life Rating Scale, Unified Parkinson’s Disease Rating Scale Part III (motor items), and the Amyotrophic Lateral Sclerosis Functional Rating Scale, revised version. Data were analyzed using Kruskal-Wallis and Wilcoxon rank-sum tests and Fisher exact test. RESULTS: We identified 184 symptomatic participants who had a single pathogenic variant in C9orf72 (n = 88), MAPT (n = 53), or GRN (n = 43). Motor symptom age at onset was earliest in the MAPT participants followed by C9orf72, whereas the GRN pathogenic variant carriers developed symptoms later. C9orf72 participants more often had fasciculations, muscle atrophy, and weakness, whereas parkinsonism was less frequent. Vertical oculomotor abnormalities were more common in the MAPT cohort, whereas apraxia and focal limb dystonia occurred more often in participants with GRN variants. DISCUSSION: We present a large comparative study of motor features in C9orf72, MAPT, and GRN pathogenic variant carriers with symptomatic f-FTLD. Our findings demonstrate characteristic phenotypic differences corresponding with specific gene variants that increase our understanding of the genotype-phenotype relationship in this complex spectrum of neurodegenerative disorders. TRIAL REGISTRATION INFORMATION: NCT02365922, NCT02372773, and NCT04363684. © 2022 American Academy of Neurology.

Document Type: Article
Publication Stage: Final
Source: Scopus

Effectiveness and Minimum Effective Dose of App-Based Mobile Health Interventions for Anxiety and Depression Symptom Reduction: Systematic Review and Meta-Analysis
(2022) JMIR Mental Health, 9 (9), art. no. e39454, . 

Lu, S.-C.^a , Xu, M.^b , Wang, M.^c , Hardi, A.^d , Cheng, A.L.^c e , Chang, S.-H.^c , Yen, P.-Y.^f g

^a Department of Symptom Research, University of Texas MD Anderson Cancer Center, Houston, TX, United States
^b Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
^c Division of Public Health Sciences, Department of Surgery, Washington University in St Louis, St Louis, MO, United States
^d Becker Medical Library, Washington University in St Louis, St Louis, MO, United States
^e Division of Physical Medicine and Rehabilitation, Department of Orthopaedic Surgery, Washington University in St Louis, St Louis, MO, United States
^f Institute for Informatics, Washington University in St Louis, St Louis, MO, United States
^g Goldfarb School of Nursing, Barnes Jewish College, BJC HealthCare, St Louis, MO, United States

Abstract
Background: Mobile health (mHealth) apps offer new opportunities to deliver psychological treatments for mental illness in an accessible, private format. The results of several previous systematic reviews support the use of app-based mHealth interventions for anxiety and depression symptom management. However, it remains unclear how much or how long the minimum treatment “dose” is for an mHealth intervention to be effective. Just-in-time adaptive intervention (JITAI) has been introduced in the mHealth domain to facilitate behavior changes and is positioned to guide the design of mHealth interventions with enhanced adherence and effectiveness. Objective: Inspired by the JITAI framework, we conducted a systematic review and meta-analysis to evaluate the dose effectiveness of app-based mHealth interventions for anxiety and depression symptom reduction. Methods: We conducted a literature search on 7 databases (ie, Ovid MEDLINE, Embase, PsycInfo, Scopus, Cochrane Library (eg, CENTRAL), ScienceDirect, and ClinicalTrials, for publications from January 2012 to April 2020. We included randomized controlled trials (RCTs) evaluating app-based mHealth interventions for anxiety and depression. The study selection and data extraction process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We estimated the pooled effect size using Hedge g and appraised study quality using the revised Cochrane risk-of-bias tool for RCTs. Results: We included 15 studies involving 2627 participants for 18 app-based mHealth interventions. Participants in the intervention groups showed a significant effect on anxiety (Hedge g=–.10, 95% CI –0.14 to –0.06, I2=0%) but not on depression (Hedge g=–.08, 95% CI –0.23 to 0.07, I2=4%). Interventions of at least 7 weeks’ duration had larger effect sizes on anxiety symptom reduction. Conclusions: There is inconclusive evidence for clinical use of app-based mHealth interventions for anxiety and depression at the current stage due to the small to nonsignificant effects of the interventions and study quality concerns. The recommended dose of mHealth interventions and the sustainability of intervention effectiveness remain unclear and require further investigation. © 2022 The Authors. All rights reserved.

Author Keywords
intervention dose effectiveness;  mental health;  meta-analysis;  mobile health;  smartphone apps;  systematic review

Document Type: Review
Publication Stage: Final
Source: Scopus

Extracellular matrix deformations of the porcine recurrent laryngeal nerve in response to hydrostatic pressure
(2022) Acta Biomaterialia, . 

Kollech, H.G.^b , Chao, M.R.^c , Stark, A.C.^d , German, R.Z.^e , Paniello, R.C.^f , Christensen, M.B.^g , Barkmeier-Kraemer, J.M.^h , Vande Geest, J.P.^a i j

^a Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States
^b Computational Modeling and Simulation Program, University of Pittsburgh, Pittsburgh, PA, United States
^c Department of Bioengineering, University of Utah, Salt Lake City, UT, United States
^d National Center for Voice and Speech, University of Utah, Salt Lake City, UT, United States
^e Department of Anatomy and Neurobiology, Northeast Ohio Medical University (NEOMED), Rootstown, OH, United States
^f Department of Otolaryngology – Head and Neck Surgery, Washington University School of Medicine, St. Louis, MO, United States
^g Department of Surgery, University of Utah, Salt Lake City, UT, United States
^h Department of Surgery, Division of Otolaryngology–Head and Neck Surgery, University of UtahUT, United States
ⁱ McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
^j Department of Mechanical Engineering and Material Science, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, United States

Abstract
Damage to the recurrent laryngeal nerve (RLN) caused by supraphysiological compression or tension imposed by adjacent tissue structures, such as the aorta, may contribute to onset of idiopathic unilateral vocal fold paralysis (iUVP) resulting in difficulty speaking, breathing, and swallowing. We previously demonstrated in adolescent pigs that the right RLN epineurium exhibits uniform composition of adipose tissue, with larger quantities along its length within the neck region in contrast to the left RLN that shows greater collagen composition in the thoracic region and greater quantities of adipose tissue in the neck region. In contrast, the epineurium in piglets was primarily composed of collagen tissue that remained uniform along the length of the left and right RLNs. Tensile testing of the left and right RLN in piglets and pigs showed associated differences in strain by RLN side and segment by age. The goal of this study was to investigate how external hydrostatic compression of the RLN affects the nerve’s connective tissue and microstructure. RLN segments were harvested from the distal (cervical/neck) regions and proximal (subclavian for the right RLN, thoracic for the left RLN) regions from eight adolescent pigs and nine piglets. RLN segments were isolated and assessed under fluid compression to test hypotheses regarding epineurium composition and response to applied forces. Second harmonic generation (SHG) imaging of epineurial collagen was conducted at 0, 40, and 80 mmHg of compression. The cartesian strain tensor, principal strain (Eps1), and principal direction of the RLN collagen fibers were determined at each pressure step. Significantly larger values of the 1st principal strain occurred in the proximal segments of the pig left RLN when compared to the same segment in piglets (p = 0.001, pig = 0.0287 [IQR = 0.0161 – 0.0428], piglet = 0.0061 [IQR = 0.0033 – 0.0156]). Additionally, the median transverse strain Eyy) for the second pressure increment was larger in the right proximal segment of pigs compared to piglets (p &lt; 0.001, pig = 0.0122 [IQR = 0.0033 – 0.0171], piglet = 0.0013 [IQR = 0.00001 – 0.0028]). Eyy values were significantly larger in the right proximal RLN versus the left proximal RLNs in pigs but not in piglets (p &lt; 0.001). In contrast to piglets, histological analysis of pig RLN demonstrated increased axial alignment of epineurial and endoneurial collagen in response to compressive pressure. These findings support the hypothesis that the biomechanical response of the RLN to compressive pressure changed from being similar to being different between the right and left RLNs during development in the porcine model. Further investigation of these findings associated with age-related onset of idiopathic UVP may illuminate underlying etiologic mechanisms. Statement of significance: Damage to the recurrent laryngeal nerve (RLN) caused by compression imposed by the aorta may contribute to the onset of left-sided idiopathic unilateral vocal fold paralysis resulting in difficulty speaking, breathing, and swallowing. The goal of this study was to investigate how compression affects the connective tissue and microstructure of the RLN. We quantified the pressure induced deformation of the RLN using multiphoton imaging as a function of both location (proximal versus distal) and age (piglets, adolescent pigs). Our results demonstrate that the biomechanical response of the RLN to compression changes in the right versus left RLN throughout development, providing further evidence that the the left RLN is exposed to increasing dynamic loads with age. © 2022

Funding details
5T32HL076124
National Institute on Deafness and Other Communication DisordersNIDCDR01-DC-011311

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

Association of Bupropion, Naltrexone, and Opioid Agonist Treatment With Stimulant-Related Admissions Among People With Opioid Use Disorder: A Case-Crossover Analysis
(2022) Journal of Clinical Psychiatry, 83 (4), art. no. 21m14112, . 

Xu, K.Y.^a , Mintz, C.M.^a , Presnall, N.^a , Bierut, L.J.^a b , Grucza, R.A.^a c

^a Health and Behavior Research Center, Department of Psychiatry, Washington University, School of Medicine, St Louis, MO, United States
^b Alvin J. Siteman Cancer Center, Barnes Jewish Hospital, Washington University, School of Medicine, St Louis, MO, United States
^c Department of Family and Community Medicine and Health and Outcomes Research, St Louis University, St Louis, MO, United States

Abstract
Background: Stimulant use has substantially increased among people with opioid use disorder (OUD) and is associated with worse treatment outcomes. This study’s objective was to compare risk of stimulant-related emergency department (ED) and hospital admissions associated with exposure to bupropion, OUD medication (buprenorphine, naltrexone, and methadone), and selective serotonin reuptake inhibitors (SSRIs; active comparator) relative to days without active prescriptions for medication. Methods: This recurrent-event, case-crossover study used insurance claims from 51, 084 individuals with OUD enrolled in the IBM MarketScan (2006-2016) Databases who had at least 1 stimulant-related ED or hospital admission. Conditional logistic regression models estimated the risk of admissions between days without active prescriptions and days with prescriptions for bupropion, OUD medication, and SSRIs. Secondary analyses were conducted by stimulant subtype (cocaine; amphetamine) and event subtype (falls, injuries, or poisonings; psychotic events). Results: Compared to days without active prescriptions, days with bupropion treatment were associated with decreased odds of stimulant-related ED or hospital admissions (odds ratio [OR] = 0.77; 95% confidence interval [CI], 0.72-0.82) Among OUD medications, we observed strong protective associations with decreased admissions for buprenorphine (OR = 0.67; 95% CI, 0.64-0.71), naltrexone (OR = 0.65; 95% CI, 0.60-0.70), and methadone (OR = 0.59; 95% CI, 0.51-0.67). The SSRI active comparator group was associated with a small protective association with decreased admissions (OR = 0.90; 95% CI, 0.86-0.93). These effects were sustained in secondary analyses stratifying by stimulant and event subtype. Conclusions: Bupropion and OUD medication, including both naltrexone and opioid agonists, are associated with fewer stimulant-related ED or hospital admissions in patients with OUD. Bupropion may show promise as adjunctive therapy targeting stimulant-specific poisoning risk. © Copyright 2022 Physicians Postgraduate Press, Inc.

Funding details
National Institutes of HealthNIHR24 HS19455
Agency for Healthcare Research and QualityAHRQ
National Center for Advancing Translational SciencesNCATS
Institute of Clinical and Translational SciencesICTSUL1 TR002345

Document Type: Article
Publication Stage: Final
Source: Scopus

Functional neuropathology of neonatal hypoxia-ischemia by single-mouse longitudinal electroencephalography
(2022) Epilepsia, . 

Johnson, K.J., Moy, B., Rensing, N., Robinson, A., Ly, M., Chengalvala, R., Wong, M., Galindo, R.

Department of Neurology, Division of Pediatric & Developmental Neurology, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Objective: Neonatal cerebral hypoxia-ischemia (HI) results in symptomatic seizures and long-term neurodevelopmental disability. The Rice-Vannucci model of rodent neonatal HI has been used extensively to examine and translate the functional consequences of acute and chronic HI-induced encephalopathy. Yet, longitudinal electrophysiological characterization of this brain injury model has been limited by the size of the neonatal mouse’s head and postnatal maternal dependency. We overcome this challenge by employing a novel method of longitudinal single-mouse electroencephalography (EEG) using chronically implanted subcranial electrodes in the term-equivalent mouse pup. We characterize the neurophysiological disturbances occurring during awake and sleep states in the acute and chronic phases following newborn brain injury. Methods: C57BL/6 mice underwent long-term bilateral subcranial EEG and electromyographic electrode placement at postnatal day 9 followed by unilateral carotid cauterization and exposure to 40 minutes of hypoxia the following day. EEG recordings were obtained prior, during, and intermittently after the HI procedure from postnatal day 10 to weaning age. Quantitative EEG and fast Fourier transform analysis were used to evaluate seizures, cortical cerebral dysfunction, and disturbances in vigilance states. Results: We observed neonatal HI-provoked electrographic focal and bilateral seizures during or immediately following global hypoxia and most commonly contralateral to the ischemic injury. Spontaneous chronic seizures were not seen. Injured mice developed long-term asymmetric EEG background attenuation in all frequencies and most prominently during non–rapid eye movement (NREM) sleep. HI mice also showed transient impairments in vigilance state duration and transitions during the first 2 days following injury. Significance: The functional burden of mouse neonatal HI recorded by EEG resembles closely that of the injured human newborn. The use of single-mouse longitudinal EEG in this immature model can advance our understanding of the developmental and pathophysiological mechanisms of neonatal cerebral injury and help translate novel therapeutic strategies against this devastating condition. © 2022 International League Against Epilepsy.

Author Keywords
brain injury;  development;  EEG;  neonatal encephalopathy;  newborn;  seizures;  sleep

Funding details
National Institutes of HealthNIHR01 NS112234

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

The multi-angle extended three-dimensional activities (META) stimulus set: A tool for studying event cognition
(2022) Behavior Research Methods, . 

Bezdek, M.A.^a , Nguyen, T.T.^a , Hall, C.S.^a , Braver, T.S.^a , Bobick, A.F.^b , Zacks, J.M.^a

^a Department of Psychological and Brain Sciences, Washington University in St. Louis, Campus Box 1125, One Brookings Drive, St. Louis, MO 63130-4899, United States
^b Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States

Abstract
To study complex human activity and how it is perceived and remembered, it is valuable to have large-scale, well-characterized stimuli that are representative of such activity. We present the Multi-angle Extended Three-dimensional Activities (META) stimulus set, a structured and highly instrumented set of extended event sequences performed in naturalistic settings. Performances were captured with two color cameras and a Kinect v2 camera with color and depth sensors, allowing the extraction of three-dimensional skeletal joint positions. We tracked the positions and identities of objects for all chapters using a mixture of manual coding and an automated tracking pipeline, and hand-annotated the timings of high-level actions. We also performed an online experiment to collect normative event boundaries for all chapters at a coarse and fine grain of segmentation, which allowed us to quantify event durations and agreement across participants. We share these materials publicly to advance new discoveries in the study of complex naturalistic activity. © 2022, The Psychonomic Society, Inc.

Author Keywords
Action perception;  Event cognition;  Event segmentation;  Naturalistic stimuli;  Norms

Funding details
Office of Naval ResearchONRN00014-17-1

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

Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer’s Disease Neuroimaging Initiative 4
(2022) Alzheimer’s and Dementia, . 

Weiner, M.W.^{a b c d e} , Veitch, D.P.^a f , Miller, M.J.^a f , Aisen, P.S.^g , Albala, B.^h , Beckett, L.A.ⁱ , Green, R.C.^j , Harvey, D.ⁱ , Jack, C.R., Jr.^k , Jagust, W.^l , Landau, S.M.^l , Morris, J.C.^m n o , Nosheny, R.^a d , Okonkwo, O.C.^p , Perrin, R.J.^m n o , Petersen, R.C.^q , Rivera-Mindt, M.^r s , Saykin, A.J.^t u , Shaw, L.M.^v , Toga, A.W.^w , Tosun, D.^a b , Trojanowski, J.Q.^v , Alzheimer’s Disease Neuroimaging Initiative^x

^a Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, United States
^b Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States
^c Department of Medicine, University of California, San Francisco, CA, United States
^d Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, United States
^e Department of Neurology, University of California, San Francisco, CA, United States
^f Northern California Institute for Research and Education (NCIRE), Department of Veterans Affairs Medical Center, San Francisco, CA, United States
^g Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA, United States
^h Department of Neurology, University of California Irvine School of Medicine, Irvine, CA, United States
ⁱ Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, United States
^j Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Broad Institute Ariadne Labs and Harvard Medical School, Boston, MA, United States
^k Department of Radiology, Mayo Clinic, Rochester, MN, United States
^l Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States
^m Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, Saint Louis, MO, United States
ⁿ Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
^o Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO, United States
^p Wisconsin Alzheimer’s Disease Research Center and Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
^q Department of Neurology, Mayo Clinic, Rochester, MN, United States
^r Department of Psychology, Latin American and Latino Studies Institute, & African and African American Studies, Fordham University, New York, NY, United States
^s Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
^t Department of Radiology and Imaging Sciences and the Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, United States
^u Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
^v Department of Pathology and Laboratory Medicine and the PENN Alzheimer’s Disease Research Center, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
^w Laboratory of Neuro Imaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, United States

Abstract
Introduction: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer’s disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50-60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022. Methods: ADNI4 will recruit URPs using community-engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50-60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in-clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials. Results and Discussion: ADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators. © 2022 The Authors. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.

Author Keywords
Alzheimer’s disease;  amyloid;  cerebrovascular disease;  digital biomarkers;  generalizability;  mild cognitive impairment;  plasma biomarkers;  tau;  underrepresented populations

Funding details
G‐89294
National Institutes of HealthNIH1910611‐0, 5U19AG024904, AG034570, AG062542, AG067418, B639943, HD090019, HG008685, HG009922, HL143295, P01AG003991, P01AG026276, P30 AG010133, P30 AG066444, P30 AG072976, P30 AG072979, P30AG072972, P50HD103526, R01 AG019771, R01 AG052550, R01 AG053267, R01 AG057739, R01 AG068193, R01 AG070883, R01 LM013463, R01 NS075321, R01AG051618, R01AG054513, R01AG054567, R01AG062240, R01AG062517, R01AG062689, R01AG064688, R01AG065110‐01A1, R01AG066471‐01A1, R01AG066748, R01AG067541, R01AG068319, R01HD076189, R01HD093654, R01MH117114, R01NS092865, R01NS097799, R13 AG071313‐01, SC3GM141996, T32 AG071444, TR003201, U01 AG068057, U01 AG072177, U19 AG032438, U54NS079202
U.S. Department of DefenseDODW81XWH‐12‐2‐0012, W81XWH‐13‐1‐0259, W81XWH‐14‐1‐0462
Foundation for the National Institutes of HealthFNIH
National Institute on AgingNIA
Division of Information and Intelligent SystemsIIS
Michael J. Fox Foundation for Parkinson’s ResearchMJFF
Mayo Clinic
Alzheimer’s AssociationAA
Merck
Roche
National Institute of JusticeNIJ2014‐R2‐CX‐0012
Biogen
AbbVie
GHR FoundationGHR
Anglo-Israel AssociationAIA
Eisai
Shionogi

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

Parent–child psychotherapy targeting emotion development: unpacking the impact of parental depression on child, parenting and engagement outcomes
(2022) European Child and Adolescent Psychiatry, . 

Schwartz, K.T.G.^a b , Chronis-Tuscano, A.^b , Tillman, R.^c , Whalen, D.^c , Gilbert, K.E.^c , Luby, J.^c

^a Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^b Department of Psychology, University of Maryland, College Park, MD, United States
^c Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Depression in early childhood increases risk of psychopathology and impairment across the lifespan. Parent–Child Interaction Therapy-Emotion Development (PCIT-ED) effectively treats depression and improves functioning in preschoolers. Parental depression has been associated with inconsistent parenting, depression onset and maintenance in offspring, and decreased treatment efficacy for youth. Given the intensity of parent involvement in PCIT-ED, this secondary data analysis aimed to evaluate parental depression severity (i.e., Beck Depression Inventory-II Total Score; BDI-II) as a moderator and predictor of child, parenting, and engagement outcomes, within the context of a randomized trial. Children (N = 229; ages 3–6.11) with early childhood depression and a consenting caregiver were randomly assigned to receive PCIT-ED or Waitlist (WL). Moderation results supported the superiority of PCIT-ED over WL on child and parenting outcomes, independent of parent-reported BDI-II at baseline (p ≥ 0.684 and p ≥ 0.476, respectively). BDI-II did not significantly predict child (p ≥ 0.836), parenting (p ≥ 0.114) or engagement (p ≥ 0.114) outcomes. Finally, BDI-II did not surpass chance in predicting whether children would maintain a depression diagnosis after PCIT-ED (AUC = 0.530) or prematurely terminate treatment (AUC = 0.545). Our results suggest that PCIT-ED is not contraindicated by minimal-to-moderate symptoms of depression in parents. Taken together with previous reports, PCIT-ED may indeed be a particularly beneficial treatment choice for this population. Further research in samples with more severe parental depression is needed. ClinicalTrials.gov identifier: NCT02076425. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.

Author Keywords
Depression;  Moderation;  Parental depression;  Parent–Child Interaction Therapy;  Randomized controlled trial

Funding details
5R01MH098454-04
National Institutes of HealthNIH

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

A gain-of-function GRIA2 variant associated with neurodevelopmental delay and seizures: Functional characterization and targeted treatment
(2022) Epilepsia, . 

Coombs, I.D.^a , Ziobro, J.^b , Krotov, V.^a , Surtees, T.-L.^c , Cull-Candy, S.G.^a , Farrant, M.^a

^a Department of Neuroscience, Physiology, and Pharmacology, University College London, London, United Kingdom
^b Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
^c Department of Neurology, Washington University in St Louis School of Medicine, St Louis, MO, United States

Abstract
α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptors (AMPARs) are ligand-gated cationic channels formed from combinations of GluA1-4 subunits. Pathogenic variants of GRIA1–4 have been described in patients with developmental delay, intellectual disability, autism spectrum disorder, and seizures, with GRIA2 variants typically causing AMPAR loss of function. Here, we identify a novel, heterozygous de novo pathogenic missense mutation in GRIA2 (c.1928 C>T, p.A643V, NM_001083619.1) in a 1-year-old boy with epilepsy, developmental delay, and failure to thrive. We made patch-clamp recordings to compare the functional and pharmacological properties of variant and wild-type receptors expressed in HEK293 cells, with and without the transmembrane AMPAR regulatory protein γ2. This showed GluA2 A643V-containing AMPARs to exhibit a novel gain of function, with greatly slowed deactivation, markedly reduced desensitization, and increased glutamate sensitivity. Perampanel, an antiseizure AMPAR negative allosteric modulator, was able to fully block GluA2 A643V/γ2 currents, suggesting potential therapeutic efficacy. The subsequent introduction of perampanel to the patient’s treatment regimen was associated with a marked reduction in seizure burden, a resolution of failure to thrive, and clear developmental gains. Our study reveals that GRIA2 disorder can be caused by a gain-of-function variant, and both predicts and suggests the therapeutic efficacy of perampanel. Perampanel may prove beneficial for patients with other gain-of-function GRIA variants. © 2022 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.

Author Keywords
AMPA receptor;  epilepsy;  GluA2;  GRIA disorder;  perampanel

Funding details
Medical Research CouncilMRCMR/T002506/1

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

A Feasibility Study of Bilateral Wrist Sensors for Measuring Motor Traits in Children With Autism
(2022) Perceptual and Motor Skills, . 

Konrad, J.^a , Marrus, N.^b , Lang, C.E.^a c d

^a Program in Physical Therapy, Washington University School of Medicine, St. LouisMO, United States
^b Department of Psychiatry, Washington University School of Medicine, St. LouisMO, United States
^c Program in Occupational Therapy, Washington University School of Medicine, St. LouisMO, United States
^d Department of Neurology, Washington University School of Medicine, St. LouisMO, United States

Abstract
Direct, quantitative measures of hyperactivity and motor coordination, two motor characteristics associated with impairment in autism, are limited. Wearable sensors can objectively index real-world movement variables that may relate to these behaviors. Here, we explored the feasibility of bilateral wrist accelerometers for measuring upper limb activity in 3–10-year-olds with autism (n = 22; 19 boys, 3 girls; M age = 5.64, SD = 2.73 years) and without autism (n = 26; 15 boys, 11 girls; M age = 6.26, SD = 2.47 years). We investigated the relationships between movement characteristics related to duration, intensity, complexity, and symmetry on the one hand and parent-reported hyperactivity and motor coordination on the other. Participants with and without autism wore the sensors for 12-hour periods. Sensor variables varied by age but not sex, with movement intensity and complexity moderately related to motor coordination. These findings lend preliminary support to wearable sensors as a means of providing ecologically-valid metrics of motor characteristics that impact adaptive function in children with autism. © The Author(s) 2022.

Author Keywords
accelerometry;  autism;  motor behavior;  movement disorders;  wearable sensors

Funding details
National Institutes of HealthNIHR01MH123723, R01MH723123, T32HD007434
Foundation for Physical TherapyFPT

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