WashU weekly Neuroscience publications | Office of Neuroscience Research

“Correction to: CHD3 helicase domain mutations cause a neurodevelopmental syndrome with macrocephaly and impaired speech and language (Nature Communications, (2018), 9, 1, (4619), 10.1038/s41467-018-06014-6)” (2019) Nature Communications

Correction to: CHD3 helicase domain mutations cause a neurodevelopmental syndrome with macrocephaly and impaired speech and language (Nature Communications, (2018), 9, 1, (4619), 10.1038/s41467-018-06014-6)
(2019) Nature Communications, 10 (1), art. no. 883, .

Blok, L.S.^a ^b ^c , Rousseau, J.^d , Twist, J.^e , Ehresmann, S.^d , Takaku, M.^e , Venselaar, H.^f , Rodan, L.H.^g , Nowak, C.B.^g , Douglas, J.^g , Swoboda, K.J.^h , Steeves, M.A.ⁱ , Sahai, I.ⁱ , Stumpel, C.T.R.M.^j , Stegmann, A.P.A.^j , Wheeler, P.^k , Willing, M.^l , Fiala, E.^l , Kochhar, A.^m , Gibson, W.T.ⁿ ^o , Cohen, A.S.A.ⁿ ^o , Agbahovbe, R.ⁿ ^o , Innes, A.M.^p , Au, P.Y.B.^p , Rankin, J.^q , Anderson, I.J.^r , Skinner, S.A.^s , Louie, R.J.^s , Warren, H.E.^s , Afenjar, A.^t , Keren, B.^u ^v , Nava, C.^u ^v ^w , Buratti, J.^u , Isapof, A.^x , Rodriguez, D.^y , Lewandowski, R.^z , Propst, J.^z , van Essen, T.^aa , Choi, M.^ab , Lee, S.^ab , Chae, J.H.^ac , Price, S.^ad , Schnur, R.E.^ae , Douglas, G.^ae , Wentzensen, I.M.^ae , Zweier, C.^af , Reis, A.^af , Bialer, M.G.^ag , Moore, C.^ag , Koopmans, M.^ah , Brilstra, E.H.^ah , Monroe, G.R.^ah , van Gassen, K.L.I.^ah , van Binsbergen, E.^ah , Newbury-Ecob, R.^ai , Bownass, L.^ai , Bader, I.^aj , Mayr, J.A.^ak , Wortmann, S.B.^ak ^al ^am , Jakielski, K.J.^an , Strand, E.A.^ao , Kloth, K.^ap , Bierhals, T.^ap , McRae, J.F.^av , Clayton, S.^av , Fitzgerald, T.W.^av , Kaplanis, J.^av , Prigmore, E.^av , Rajan, D.^av , Sifrim, A.^av , Aitken, S.^aw , Akawi, N.^av , Alvi, M.^ax , Ambridge, K.^av , Barrett, D.M.^av , Bayzetinova, T.^av , Jones, P.^av , Jones, W.D.^av , King, D.^av , Krishnappa, N.^av , Mason, L.E.^av , Singh, T.^av , Tivey, A.R.^av , Ahmed, M.^ay ^az ^ba , Anjum, U.^bb , Archer, H.^bc ^bd , Armstrong, R.^be , Awada, J.^av , Balasubramanian, M.^bf , Banka, S.^bg , Baralle, D.^ay ^az ^ba , Barnicoat, A.^bh , Batstone, P.^bi , Baty, D.^bj , Bennett, C.^bk , Berg, J.^bj , Bernhard, B.^bl , Bevan, A.P.^av , Bitner-Glindzicz, M.^bh , Blair, E.^bm , Blyth, M.^bk , Bohanna, D.^bn , Bourdon, L.^bl , Bourn, D.^bo , Bradley, L.^bp , Brady, A.^bl , Brent, S.^av , Brewer, C.^bq , Brunstrom, K.^bh , Bunyan, D.J.^ay ^az ^ba , Burn, J.^bo , Canham, N.^bl , Castle, B.^bq , Chandler, K.^bg , Chatzimichali, E.^av , Cilliers, D.^bm , Clarke, A.^bc ^bd , Clasper, S.^bm , Clayton-Smith, J.^bg , Clowes, V.^bl , Coates, A.^bk , Cole, T.^bn , Colgiu, I.^av , Collins, A.^ay ^az ^ba , Collinson, M.N.^ay ^az ^ba , Connell, F.^br , Cooper, N.^bn , Cox, H.^bn , Cresswell, L.^bs , Cross, G.^bt , Clayton-Smith, J.^bg , Clowes, V.^bl , Coates, A.^bk , Cole, T.^bn , Colgiu, I.^av , Collins, A.^ay ^az ^ba , Collinson, M.N.^ay ^az ^ba , Connell, F.^br , Cooper, N.^bn , Cox, H.^bn , Cresswell, L.^bs , Cross, G.^bt , Crow, Y.^bg , D’Alessandro, M.^bi , Dabir, T.^bp , Davidson, R.^bu , Davies, S.^bc ^bd , de Vries, D.^av , Dean, J.^bi , Deshpande, C.^br , Devlin, G.^bq , Dixit, A.^bt , Dobbie, A.^bk , Donaldson, A.^bv , Donnai, D.^bg , Donnelly, D.^bp , Donnelly, C.^bg , Douglas, A.^bw , Douzgou, S.^bg , Duncan, A.^bu , Eason, J.^bt , Ellard, S.^bq , Ellis, I.^bw , Elmslie, F.^bb , Evans, K.^bc ^bd , Everest, S.^bq , Fendick, T.^br , Fisher, R.^bo , Flinter, F.^br , Foulds, N.^ay ^az ^ba , Fry, A.^bc ^bd , Fryer, A.^bw , Gardiner, C.^bu , Gaunt, L.^bg , Ghali, N.^bl , Gibbons, R.^bm , Gill, H.^bx , Goodship, J.^bo , Goudie, D.^bj , Gray, E.^av , Green, A.^bx , Greene, P.^av , Greenhalgh, L.^bw , Gribble, S.^av , Harrison, R.^bt , Harrison, L.^ay ^az ^ba , Harrison, V.^ay ^az ^ba , Hawkins, R.^bv , He, L.^av , Hellens, S.^bo , Henderson, A.^bo , Hewitt, S.^bk , Hildyard, L.^av , Hobson, E.^bk , Holden, S.^be , Holder, M.^bl , Holder, S.^bl , Hollingsworth, G.^bh , Homfray, T.^bb , Humphreys, M.^bp , Hurst, J.^bh , Hutton, B.^av , Ingram, S.^bf , Irving, M.^br , Islam, L.^bn , Jackson, A.^aw , Jarvis, J.^bn , Jenkins, L.^bh , Johnson, D.^bf , Jones, E.^bg , Josifova, D.^br , Joss, S.^bu , Kaemba, B.^bs , Kazembe, S.^bs , Kelsell, R.^av , Kerr, B.^bg , Kingston, H.^bg , Kini, U.^bm , Kinning, E.^bu , Kirby, G.^bn , Kirk, C.^bp , Kivuva, E.^bq , Kraus, A.^bk , Kumar, D.^bc ^bd , Kumar, V.K.A.^bh , Lachlan, K.^ay ^az ^ba , Lam, W.^aw , Lampe, A.^aw , Langman, C.^br , Lees, M.^bh , Lim, D.^bn , Longman, C.^bu , Lowther, G.^bu , Lynch, S.A.^bx , Magee, A.^bp , Maher, E.^aw , Male, A.^bh , Mansour, S.^bb , Marks, K.^bb , Martin, K.^bt , Maye, U.^bw , McCann, E.^by , McConnell, V.^bp , McEntagart, M.^bb , McGowan, R.^bi , McKay, K.^bn , McKee, S.^bp , McMullan, D.J.^bn , McNerlan, S.^bp , McWilliam, C.^bi , Mehta, S.^be , Metcalfe, K.^bg , Middleton, A.^av , Miedzybrodzka, Z.^bi , Miles, E.^bg , Mohammed, S.^br , Montgomery, T.^bo , Moore, D.^aw , Morgan, S.^bc ^bd , Morton, J.^bn , Mugalaasi, H.^bc ^bd , Murday, V.^bu , Murphy, H.^bg , Naik, S.^bn , Nemeth, A.^bm , Nevitt, L.^bf , Norman, A.^bn , O’Shea, R.^bx , Ogilvie, C.^br , Ong, K.-R.^bn , Park, S.-M.^be , Parker, M.J.^bf , Patel, C.^bn , Paterson, J.^be , Payne, S.^bl , Perrett, D.^av , Phipps, J.^bm , Pilz, D.T.^bu , Pollard, M.^av , Pottinger, C.^by , Poulton, J.^bm , Pratt, N.^bj , Prescott, K.^bk , Pridham, A.^bm , Procter, A.^bc ^bd , Purnell, H.^bm , Quarrell, O.^bf , Ragge, N.^bn , Rahbari, R.^av , Randall, J.^av , Raymond, L.^be , Rice, D.^bj , Robert, L.^br , Roberts, E.^bv , Roberts, J.^be , Roberts, P.^bk , Roberts, G.^bw , Ross, A.^bi , Rosser, E.^bh , Saggar, A.^bb , Samant, S.^bi , Sampson, J.^bc ^bd , Sandford, R.^be , Sarkar, A.^bt , Schweiger, S.^bj , Scott, R.^bh , Scurr, I.^bv , Selby, A.^bt , Seller, A.^bm , Sequeira, C.^bl , Shannon, N.^bt , Sharif, S.^bn , Shaw-Smith, C.^bq , Shearing, E.^bf , Shears, D.^bm , Sheridan, E.^bk , Simonic, I.^be , Singzon, R.^bl , Skitt, Z.^bg , Smith, A.^bk , Smith, K.^bf , Smithson, S.^bv , Sneddon, L.^bo , Splitt, M.^bo , Squires, M.^bk , Stewart, F.^bp , Stewart, H.^bm , Straub, V.^bo , Suri, M.^bt , Sutton, V.^bw , Swaminathan, G.J.^av , Sweeney, E.^bw , Tatton-Brown, K.^bb , Taylor, C.^e , Taylor, R.^bb , Tein, M.^bn , Temple, I.K.^ay ^az ^ba , Thomson, J.^bk , Tischkowitz, M.^be , Tomkins, S.^bv , Torokwa, A.^ay ^az ^ba , Treacy, B.^be , Turner, C.^bq , Turnpenny, P.^bq , Tysoe, C.^bq , Vandersteen, A.^bl , Varghese, V.^bc ^bd , Vasudevan, P.^bs , Vijayarangakannan, P.^av , Vogt, J.^bn , Wakeling, E.^bl , Wallwark, S.^be , Waters, J.^bh , Weber, A.^bw , Wellesley, D.^ay ^az ^ba , Whiteford, M.^bu , Widaa, S.^av , Wilcox, S.^be , Wilkinson, E.^av , Williams, D.^bn , Williams, N.^bu , Wilson, L.^bh , Woods, G.^be , Wragg, C.^bv , Wright, M.^bo , Yates, L.^bo , Yau, M.^br , Nellåker, C.^bz ^ca ^cb , Parker, M.^cc , Firth, H.V.^av ^be , Wright, C.F.^av , FitzPatrick, D.R.^av ^aw , Barrett, J.C.^av , Hurles, M.E.^av , Roberts, J.D.^e , Petrovich, R.M.^e , Machida, S.^aq , Kurumizaka, H.^aq , Lelieveld, S.^a , Pfundt, R.^a , Jansen, S.^a ^c , Deriziotis, P.^b , Faivre, L.^ar ^as , Thevenon, J.^ar ^as , Assoum, M.^ar ^as , Shriberg, L.^at , Kleefstra, T.^a ^c , Brunner, H.G.^a ^c ^j , Wade, P.A.^e , Fisher, S.E.^b ^c , Campeau, P.M.^d ^au , The DDD study^cd

^a Department of Human Genetics, Radboud University Medical Center, Nijmegen, 6500HB, Netherlands
^b Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, 6500AH, Netherlands
^c Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6500HE, Netherlands
^d CHU Sainte-Justine Research Center, Montreal, QC H3T 1C5, Canada
^e National Institute of Environmental Health Sciences, Research Triangle Park, NC 27709, United States
^f Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, 6500HB, Netherlands
^g Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, United States
^h Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States
ⁱ Department of Medical Genetics, Massachusetts General Hospital, Boston, MA 02114, United States
^j Department of Clinical Genetics and GROW-School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, 6202AZ, Netherlands
^k Nemours Childrens Clinic, Orlando, FL 32827, United States
^l Division of Genetics and Genomic Medicine, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, United States
^m Valley Children’s Hospital, Madera, CA 93636, United States
ⁿ British Columbia Children’s Hospital Research Institute, Vancouver, BC V5Z 4H4, Canada
^o Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada
^p Department of Medical Genetics and Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
^q Department of Clinical Genetics, Royal Devon and Exeter NHS Foundation Trust (Heavitree), Exeter, EX2 5DW, United Kingdom
^r Division of Genetics, Department of Medicine, University of Tennessee Medical Center, Knoxville, TN 37920, United States
^s Greenwood Genetic Center, Greenwood, SC 29646, United States
^t GRC ConCer-LD, Sorbonne Universités, UPMC Univ Paris ; Department of Medical Genetics and Centre de Référence Malformations et maladies congénitales du cervelet et déficiences intellectuelles de causes rares, Armand Trousseau Hospital, GHUEP, AP-HP, Paris, 75012, France
^u AP-HP, Hôpital de la Pitié-Salpêtrière, Département de Génétique, Paris, 75013, France
^v Groupe de Recherche Clinique (GRC) ‘déficience intellectuelle et autisme’ UPMC, Paris, 75005, France
^w INSERM, U 1127, CNRS UMR 7225, Institut du Cerveau et de la Moelle épinière, ICM, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Paris, 75013, France
^x GRC ConCer-LD, Sorbonne Universités, UPMC Univ Paris 06; Department Child Neurology and Reference Center for Neuromuscular Diseases “Nord/Est/Ile-de-France”, FILNEMUS, Armand Trousseau Hospital, GHUEP, AP-HP, Paris, 75012, France
^y GRC ConCer-LD, Sorbonne Universités, UPMC Univ Paris 06; Department of Child Neurology and National Reference Center for Neurogenetic Disorders, Armand Trousseau Hospital, GHUEP, AP-HP, INSERM U1141, Paris, 75012, France
^z Clinical Genetics Division, Virginia Commonwealth University Health System, Richmond, VA 23298, United States
^aa Clinical Genetics Department, University Medical Center Groningen, Groningen, 9700RB, Netherlands
^ab Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 08826, South Korea
^ac Department of Pediatrics, Seoul National University College of Medicine, Seoul National University Children’s Hospital, Seoul, 08826, South Korea
^ad Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7HE, United Kingdom
^ae GeneDx, Gaithersburg, MD 20877, United States
^af Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, 91054, Germany
^ag Northwell Health, Division of Medical Genetics and Genomics, Great Neck NY, 11021, United States
^ah Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, 3508AB, Netherlands
^ai University Hospitals Bristol, Department of Clinical Genetics, St Michael’s Hospital, Bristol, BS2 8EG, United Kingdom
^aj Department of Clinical Genetics, University Children’s Hospital, Paracelsus Medical University, Salzburg, A-5020, Austria
^ak Department of Pediatrics, Salzburger Landeskliniken and Paracelsus Medical University, Salzburg, A-5020, Austria
^al Institute of Human Genetics, Technische Universität München, Munich, 81675, Germany
^am Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, 85764, Germany
^an Communication Sciences and Disorders, Augustana College, Rock Island, IL 61201, United States
^ao Department of Neurology, Mayo Clinic, Rochester, MN 55905, United States
^ap Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, 20246, Germany
^aq Waseda University, Tokyo, 169-8050, Japan
^ar Equipe Génétique des Anomalies du Développement, Université de Bourgogne- Franche Comté, Dijon, 21070, France
^as Centre de Génétique et Centre de Référence Anomalies du Développement et Syndromes Malformatifs, FHU TRANSLAD, Hôpital d’Enfants, CHU Dijon et Université de Bourgogne, Dijon, 21079, France
^at Waisman Center, Phonology Project, Madison, WI 53705-2280, United States
^au Sainte-Justine Hospital, University of Montreal, Montreal, QC H3T 1C5, Canada
^av Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
^aw MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, United Kingdom
^ax Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, United Kingdom
^ay Wessex Clinical Genetics Service, University Hospital Southampton, Princess Anne Hospital, Coxford Road, Southampton, SO16 5YA, United Kingdom
^az Wessex Regional Genetics Laboratory, Salisbury NHS Foundation Trust, Salisbury District Hospital, Odstock Road, Salisbury, Wiltshire, SP2 8BJ, United Kingdom
^ba Faculty of Medicine, University of Southampton, Building 85, Life Sciences Building, Highfield Campus, Southampton, SO17 1BJ, United Kingdom
^bb South West Thames Regional Genetics Centre, St George’s Healthcare NHS Trust, St George’s, University of London, Cranmer Terrace, London, SW17 0RE, United Kingdom
^bc Institute of Medical Genetics, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, United Kingdom
^bd Department of Clinical Genetics, Block 12, Glan Clwyd Hospital, Rhyl, Denbighshire, LL18 5UJ, United Kingdom
^be East Anglian Medical Genetics Service, Box 134, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom
^bf Sheffield Regional Genetics Services, Sheffield Children’s NHS Trust, Western Bank, Sheffield, S10 2TH, United Kingdom
^bg Manchester Centre for Genomic Medicine, St Mary’s Hospital, Central Manchester University Hospitals NHSFoundation Trust, Manchester Academic Health Science Centre, Manchester, M13 9WL, United Kingdom
^bh North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Foundation Trust, Great Ormond Street Hospital, Great Ormond Street, London, WC1N3JH, United Kingdom
^bi North of Scotland Regional Genetics Service, NHS Grampian, Department of Medical Genetics Medical School, Foresterhill, Aberdeen, AB25 2ZD, United Kingdom
^bj East of Scotland Regional Genetics Service, Human Genetics Unit, Pathology Department, NHS Tayside, Ninewells Hospital, Dundee, DD1 9SY, United Kingdom
^bk Yorkshire Regional Genetics Service, Leeds Teaching Hospitals NHS Trust, Department of Clinical Genetics, Chapel Allerton Hospital, Chapeltown Road, Leeds, LS7 4SA, United Kingdom
^bl North West Thames Regional Genetics Centre, North West London Hospitals NHS Trust, The Kennedy Galton Centre, Northwick Park and St Mark’s NHS Trust Watford Road, Harrow, HA1 3UJ, United Kingdom
^bm Oxford Regional Genetics Service, Oxford Radcliffe Hospitals NHS Trust, The Churchill Old Road, Oxford, OX3 7LJ, United Kingdom
^bn West Midlands Regional Genetics Service, Birmingham Women’s NHS Foundation Trust, Birmingham Women’s Hospital, Edgbaston, Birmingham, B15 2TG, United Kingdom
^bo Northern Genetics Service, Newcastle upon Tyne Hospitals NHS Foundation Trust, Institute of Human Genetics, International Centre for Life, Central Parkway, Newcastle upon Tyne, NE1 3BZ, United Kingdom
^bp Northern Ireland Regional Genetics Centre, Belfast Health and Social Care Trust, Belfast City Hospital, Lisburn Road, Belfast, BT9 7AB, United Kingdom
^bq Peninsula Clinical Genetics Service, Royal Devon and Exeter NHS Foundation Trust, Clinical Genetics Department, Royal Devon & Exeter Hospital (Heavitree), Gladstone Road, Exeter, EX1 2ED, United Kingdom
^br South East Thames Regional Genetics Centre, Guy’s and St Thomas’ NHS Foundation Trust, Guy’s Hospital, Great Maze Pond, London, SE1 9RT, United Kingdom
^bs Leicestershire Genetics Centre, University Hospitals of Leicester NHS Trust, Leicester Royal Infirmary (NHS Trust), Leicester, LE1 5WW, United Kingdom
^bt Nottingham Regional Genetics Service, City Hospital Campus, Nottingham University Hospitals NHS Trust, The Gables, Hucknall Road, Nottingham, NG5 1PB, United Kingdom
^bu West of Scotland Regional Genetics Service, NHS Greater Glasgow and Clyde, Institute of Medical Genetics, Yorkhill Hospital, Glasgow, G3 8SJ, United Kingdom
^bv Bristol Genetics Service (Avon, Somerset, Gloucs and West Wilts), University Hospitals Bristol NHS Foundation Trust, St Michael’s Hospital, St Michael’s Hill, Bristol, BS2 8DT, United Kingdom
^bw Merseyside and Cheshire Genetics Service, Liverpool Women’s NHS Foundation Trust, Department of Clinical Genetics, Royal Liverpool Children’s Hospital Alder Hey, Eaton Road, Liverpool, L12 2AP, United Kingdom
^bx National Centre for Medical Genetics, Our Lady’s Children’s Hospital, Crumlin, Dublin 12, Ireland
^by Department of Clinical Genetics, Block 12, Glan Clwyd Hospital, Rhyl, Denbighshire, Wales, LL18 5UJ, United Kingdom
^bz Nuffield Department of Obstetrics & Gynaecology, University of Oxford, Level 3, Women’s Centre, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom
^ca Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, United Kingdom
^cb Big Data Institute, University of Oxford, Roosevelt drive, Oxford, OX3 7LF, United Kingdom
^cc The Ethox Centre, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Oxford, OX3 7LF, United Kingdom

Abstract
The original version of this Article contained an error in the spelling of the author Laurence Faivre, which was incorrectly given as Laurence Faive. This has now been corrected in both the PDF and HTML versions of the Article. © 2019, The Author(s).

Document Type: Erratum
Publication Stage: Final
Source: Scopus

“Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism” (2019) Translational Psychiatry

Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
(2019) Translational Psychiatry, 9 (1), art. no. 89, .

Kapoor, M.^a , Wang, J.-C.^a , Farris, S.P.^b , Liu, Y.^c , McClintick, J.^c , Gupta, I.^d , Meyers, J.L.^e , Bertelsen, S.^a , Chao, M.^a , Nurnberger, J.^c , Tischfield, J.^f , Harari, O.^g , Zeran, L.^g , Hesselbrock, V.^h , Bauer, L.^h , Raj, T.^a , Porjesz, B.^e , Agrawal, A.^g , Foroud, T.^c , Edenberg, H.J.^c , Mayfield, R.D.^b , Goate, A.^a

^a Department of Neuroscience, Icahn School of Medicine at Mt. Sinai, 1425 Madison Ave, New York, NY, United States
^b The Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX 78712, United States
^c Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
^d Department of Biological Sciences, Indian Institute of Science Education and Research, Bhopal, MP 462066, India
^e Department of Psychiatry, Henri Begleiter Neurodynamics Lab, State University of New York, Downstate Medical Center, Brooklyn, NY, United States
^f Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, United States
^g Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States
^h Department of Psychiatry, University of Connecticut, Farmington, CT, United States

Abstract
Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank’s alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence. © 2019, The Author(s).

Document Type: Article
Publication Stage: Final
Source: Scopus

“Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies” (2019) Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring

Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies
(2019) Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 11, pp. 180-190.

Su, Y.^a , Flores, S.^b , Wang, G.^c ^d , Hornbeck, R.C.^b , Speidel, B.^e , Joseph-Mathurin, N.^b , Vlassenko, A.G.^b ^c , Gordon, B.A.^b ^c , Koeppe, R.A.^f , Klunk, W.E.^g , Jack, C.R., Jr.^h , Farlow, M.R.ⁱ , Salloway, S.^j , Snider, B.J.^c ^k , Berman, S.B.^l , Roberson, E.D.^m , Brosch, J.ⁱ , Jimenez-Velazques, I.ⁿ , van Dyck, C.H.^o , Galasko, D.^p , Yuan, S.H.^p , Jayadev, S.^q , Honig, L.S.^r , Gauthier, S.^s , Hsiung, G.-Y.R.^t , Masellis, M.^u , Brooks, W.S.^v , Fulham, M.^w , Clarnette, R.^x , Masters, C.L.^y , Wallon, D.^z ^aa , Hannequin, D.^z ^aa , Dubois, B.^ab , Pariente, J.^ac , Sanchez-Valle, R.^ad , Mummery, C.^ae , Ringman, J.M.^af , Bottlaender, M.^ag , Klein, G.^ah , Milosavljevic-Ristic, S.^ah , McDade, E.^c ^k , Xiong, C.^c ^d , Morris, J.C.^c ^k , Bateman, R.J.^c ^k , Benzinger, T.L.S.^b ^c

^a Banner Alzheimer’s Institute, Phoenix, AZ, United States
^b Department of Radiology, Washington University School of Medicine, Saint Louis, MO, United States
^c Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, MO, United States
^d Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, United States
^e Department of Neurological Surgery, University of California, San Francisco, CA, United States
^f Department of Radiology, University of Michigan, Ann Arbor, MI, United States
^g Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
^h Department of Radiology, Mayo Clinic, Rochester, MN, United States
ⁱ Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States
^j Butler Hospital, Providence, RI, United States
^k Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
^l Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
^m Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
ⁿ University of Puerto Rico, San Juan, Puerto Rico
^o Yale University School of Medicine, New Haven, CT, United States
^p University of California-San Diego, San Diego, CA, United States
^q University of Washington, Seattle, WA, United States
^r Columbia University, New York, NY, United States
^s McGill Center for Studies in Aging, Douglas Mental Health Research Institute, Montreal, Canada
^t University of British Columbia, Vancouver, British Columbia, Canada
^u Sunnybrook Health Sciences Center, Toronto, Ontario, Canada
^v The University of New South Wales, Sydney, NSW, Australia
^w University of Sydney and Royal Prince Alfred Hospital, Sydney, NSW, Australia
^x University of Western Australia, Crawley, WA, Australia
^y The University of Melbourne and the Florey Institute, Parkville, VIC, Australia
^z Inserm U1245, Department of Neurology and CNR-MAJ, Rouen, France
^aa Normandy Center for Genomic and Personalized Medicine, Rouen, France
^ab University Salpêtrière Hospital in Paris, Paris, France
^ac University of Toulouse, Toulouse, France
^ad Hospital Clínic, Barcelona, Spain
^ae University College London, London, United Kingdom
^af Keck School of Medicine at the University of Southern California, Los Angeles, CA, United States
^ag Service Hospitalier Frédéric Joliot, CEA, Orsay, France
^ah F. Hoffmann-La Roche Ltd., Switzerland

Abstract
Introduction: Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B–based and florbetapir-based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods: Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter-individual variability of the two tracers were compared using multivariate linear models both cross-sectionally and longitudinally. Results: Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion: Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers. © 2019 [Author/Employing Institution]

Author Keywords
Amyloid imaging; Centiloid; Florbetapir; PiB; Positron emission tomography

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

“Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics” (2019) Scientific Reports

Predicting Short-term MCI-to-AD Progression Using Imaging, CSF, Genetic Factors, Cognitive Resilience, and Demographics
(2019) Scientific Reports, 9 (1), art. no. 2235, .

Varatharajah, Y.^a , Ramanan, V.K.^b , Iyer, R.^a , Vemuri, P.^b , Weiner, M.W.^c , Aisen, P.^d , Petersen, R.^b , Jack, C.R.^b , Saykin, A.J.^e , Jagust, W.^f , Trojanowki, J.Q.^g , Toga, A.W.^d , Beckett, L.^h , Green, R.C.ⁱ , Morris, J.^j , Shaw, L.M.^g , Khachaturian, Z.^k , Sorensen, G.^l , Carrillo, M.^m , Kuller, L.ⁿ , Raichle, M.^j , Paul, S.^o , Davies, P.^p , Fillit, H.^q , Hefti, F.^r , Holtzman, D.^j , Mesulam, M.M.^s , Potter, W.^t , Snyder, P.^u , Schwartz, A.^v , Montine, T.^w , Thomas, R.G.^x , Donohue, M.^x , Walter, S.^x , Gessert, D.^x , Sather, T.^x , Jiminez, G.^x , Balasubramanian, A.B.^x , Mason, J.^x , Sim, I.^x , Harvey, D.^h , Bernstein, M.^b , Fox, N.^y , Thompson, P.^z , Schuff, N.^c , DeCArli, C.^h , Borowski, B.^b , Gunter, J.^b , Senjem, M.^b , Jones, D.^b , Kantarci, K.^b , Ward, C.^b , Koeppe, R.A.^aa , Foster, N.^ab , Reiman, E.M.^ac , Chen, K.^ac , Mathis, C.ⁿ , Landau, S.^f , Cairns, N.J.^j , Franklin, E.^j , Taylor-Reinwald, L.^j , Lee, V.^g , Korecka, M.^g , Figurski, M.^g , Crawford, K.^d , Neu, S.^d , Foroud, T.M.^e , Potkin, S.^ad , Faber, K.^e , Kim, S.^e , Nho, K.^e , Thal, L.^x , Buckholtz, N.^ae , Albert, M.^af , Frank, R.^ag , Hsiao, J.^ae , Kaye, J.^ah , Quinn, J.^ah , Silbert, L.^ah , Lind, B.^ah , Carter, R.^ah , Dolen, S.^ah , Schneider, L.S.^d , Pawluczyk, S.^d , Beccera, M.^d , Teodoro, L.^d , Spann, B.M.^d , Brewer, J.^x , Vanderswag, H.^x , Fleisher, A.^x , Heidebrink, J.L.^aa , Lord, J.L.^aa , Mason, S.S.^e , Albers, C.S.^b , Knopman, D.^b , Johnson, K.^b , Doody, R.S.^ai , Villanueva-Meyer, J.^ai , Pavlik, V.^ai , Shibley, V.^ai , Chowdhury, M.^ai , Rountree, S.^ai , Dang, M.^ai , Stern, Y.^aj , Honig, L.S.^aj , Bell, K.L.^aj , Ances, B.^j , Carroll, M.^j , Creech, M.L.^j , Franklin, E.^j , Mintun, M.A.^j , Schneider, S.^j , Oliver, A.^j , Marson, D.^ak , Geldmacher, D.^ak , Love, M.N.^ak , Griffith, R.^ak , Clark, D.^ak , Brockington, J.^ak , Roberson, E.^ak , Grossman, H.^al , Mitsis, E.^al , Shah, R.C.^am , deToledo-Morrell, L.^am , Duara, R.^an , Greig-Custo, M.T.^an , Barker, W.^an , Onyike, C.^af , D’Agostino, D.^af , Kielb, S.^af , Sadowski, M.^ao , Sheikh, M.O.^ao , Ulysse, A.^ao , Gaikwad, M.^ao , Doraiswamy, P.M.^ap , Petrella, J.R.^ap , Borges-Neto, S.^ap , Wong, T.Z.^ap , Coleman, E.^ap , Arnold, S.E.^g , Karlawish, J.H.^g , Wolk, D.A.^g , Clark, C.M.^g , Smith, C.D.^aq , Jicha, G.^aq , Hardy, P.^aq , Sinha, P.^aq , Oates, E.^aq , Conrad, G.^aq , Lopez, O.L.ⁿ , Oakley, M.A.ⁿ , Simpson, D.M.ⁿ , Porsteinsson, A.P.^ar , Goldstein, B.S.^ar , Martin, K.^ar , Makino, K.M.^ar , Ismail, M.S.^ar , Brand, C.^ar , Preda, A.^ad , Nguyen, D.^ad , Womack, K.^as , Mathews, D.^as , Quiceno, M.^as , Levey, A.I.^at , Lah, J.J.^at , Cellar, J.S.^at , Burns, J.M.^au , Swerdlow, R.H.^au , Brooks, W.M.^au , Apostolova, L.^z , Tingus, K.^z , Woo, E.^z , Silverman, D.H.S.^z , Lu, P.H.^z , Bartzokis, G.^z , Graff-Radford, N.R.^av , Parfitt, F.^av , Poki-Walker, K.^av , Farlow, M.R.^e , Hake, A.M.^e , Matthews, B.R.^e , Brosch, J.R.^e , Herring, S.^e , van Dyck, C.H.^aw , Carson, R.E.^aw , MacAvoy, M.G.^aw , Varma, P.^aw , Chertkow, H.^ax , Bergman, H.^ax , Hosein, C.^ax , Black, S.^ay , Stefanovic, B.^ay , Caldwell, C.^ay , Hsiung, G.-Y.R.^az , Mudge, B.^az , Sossi, V.^az , Feldman, H.^az , Assaly, M.^az , Finger, E.^ba , Pasternack, S.^ba , Rachisky, I.^ba , Rogers, J.^ba , Trost, D.^ba , Kertesz, A.^ba , Bernick, C.^bb , Munic, D.^bb , Rogalski, E.^s , Lipowski, K.^s , Weintraub, S.^s , Bonakdarpour, B.^s , Kerwin, D.^s , Wu, C.-K.^s , Johnson, N.^s , Sadowsky, C.^bc , Villena, T.^bc , Turner, R.S.^bd , Johnson, K.^bd , Reynolds, B.^bd , Sperling, R.A.ⁱ , Johnson, K.A.ⁱ , Marshall, G.ⁱ , Yesavage, J.^be , Taylor, J.L.^be , Lane, B.^be , Rosen, A.^be , Tinklenberg, J.^be , Sabbagh, M.N.^bf , Belden, C.M.^bf , Jacobson, S.A.^bf , Sirrel, S.A.^bf , Kowall, N.^bg , Killiany, R.^bg , Budson, A.E.^bg , Norbash, A.^bg , Johnson, P.L.^bg , Obisesan, T.O.^bh , Wolday, S.^bh , Allard, J.^bh , Lerner, A.^bi , Ogrocki, P.^bi , Tatsuoka, C.^bi , Fatica, P.^bi , Fletcher, E.^h , Maillard, P.^h , Olichney, J.^h , DeCarli, C.^h , Carmichael, O.^h , Kittur, S.^bj , Borrie, M.^bk , Lee, T.-Y.^bk , Bartha, R.^bk , Johnson, S.^bl , Asthana, S.^bl , Carlsson, C.M.^bl , Tariot, P.^ac , Burke, A.^ac , Milliken, A.M.^ac , Trncic, N.^ac , Fleisher, A.^ac , Reeder, S.^ac , Bates, V.^bm , Capote, H.^bm , Rainka, M.^bm , Scharre, D.W.^bn , Kataki, M.^bn , Kelly, B.^bn , Zimmerman, E.A.^bo , Celmins, D.^bo , Brown, A.D.^bo , Pearlson, G.D.^bp , Blank, K.^bp , Anderson, K.^bp , Flashman, L.A.^bq , Seltzer, M.^bq , Hynes, M.L.^bq , Santulli, R.B.^bq , Sink, K.M.^br , Gordineer, L.^br , Williamson, J.D.^br , Garg, P.^br , Watkins, F.^br , Ott, B.R.^bs , Tremont, G.^bs , Daiello, L.A.^bs , Salloway, S.^bt , Malloy, P.^bt , Correia, S.^bt , Rosen, H.J.^c , Miller, B.L.^c , Perry, D.^c , Mintzer, J.^bu , Spicer, K.^bu , Bachman, D.^bu , Pomara, N.^bv , Hernando, R.^bv , Sarrael, A.^bv , Schultz, S.K.^bw , Smith, K.E.^bw , Koleva, H.^bw , Nam, K.W.^bw , Shim, H.^bw , Relkin, N.^o , Chaing, G.^o , Lin, M.^o , Ravdin, L.^o , Smith, A.^bx , Raj, B.A.^bx , Fargher, K.^bx , For the Alzheimer’s Disease Neuroimaging Initiative^by

^a Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States
^b Mayo Clinic, Rochester, MN 55905, United States
^c University of California, San Francisco, United States
^d University of Southern California, Los Angeles, United States
^e Indiana University, Bloomington, United States
^f University of California, Berkeley, Berkeley, United States
^g University of Pennsylvania, Philadelphia, United States
^h University of California, Davis, Davis, United States
ⁱ Brigham and Women’s Hospital/Harvard Medical School, Boston, United States
^j Washington University St. Louis, St. Louis, United States
^k Prevent Alzheimer’s Disease, Rockville, 2020, United States
^l Siemens, Munich, Germany
^m Alzheimer’s AssociationIL, United States
ⁿ University of PittsburghPA, United States
^o Cornell UniversityNY, United States
^p Albert Einstein College of Medicine ofYeshiva UniversityNY, United States
^q AD Drug Discovery FoundationNY, United States
^r Acumen PharmaceuticalsCA, United States
^s Northwestern UniversityIL, United States
^t National Institute of Mental HealthMD, United States
^u Brown UniversityRI, United States
^v Eli LillyIN, United States
^w University of WashingtonWA, United States
^x University of California, San Diego, CA, United States
^y University of London, London, United Kingdom
^z University of California, Los Angeles, CA, United States
^aa University of MichiganMI, United States
^ab University of UtahUT, United States
^ac Banner Alzheimer’s InstituteAZ, United States
^ad University of California, IrvineCA, United States
^ae National Institute on AgingMD, United States
^af Johns Hopkins UniversityMD, United States
^ag Richard Frank ConsultingNH, United States
^ah Oregon Health and Science UniversityOR, United States
^ai Baylor College of MedicineTX, United States
^aj Columbia University Medical CenterNY, United States
^ak University of Alabama-BirminghamAL, United States
^al Mount Sinai School of MedicineNY, United States
^am Rush University Medical Center, Rush UniversityIL, United States
^an Wien CenterFL, United States
^ao NewYork UniversityNY, United States
^ap Duke University Medical CenterNC, United States
^aq University of KentuckyKY, United States
^ar University of Rochester Medical CenterNY, United States
^as University of Texas Southwestern Medical SchoolTX, United States
^at Emory UniversityGA, United States
^au University of Kansas, Medical CenterKS, United States
^av Mayo Clinic, Jacksonville, FL, United States
^aw Yale University School of MedicineCT, United States
^ax McGill University, Montreal- Jewish General HospitalQC, Canada
^ay Sunnybrook Health SciencesON, Canada
^az U.B.C. Clinic for AD & Related DisordersBC, Canada
^ba Cognitive Neurology-St. Joseph’sON, Canada
^bb Cleveland Clinic Lou Ruvo Center for Brain HealthOH, United States
^bc Premiere Research Inst (Palm Beach Neurology)FL, United States
^bd Georgetown University Medical Center, Washington, DC, United States
^be Stanford UniversityCA, United States
^bf Banner Sun Health Research InstituteAZ, United States
^bg Boston UniversityMA, United States
^bh Howard University, Washington, DC, United States
^bi Case Western Reserve UniversityOH, United States
^bj Neurological Care of CNYNY, United States
^bk Parkwood HospitalPA, United States
^bl University of WisconsinWI, United States
^bm Dent Neurologic InstituteNY, United States
^bn Ohio State UniversityOH, United States
^bo Albany Medical CollegeNY, United States
^bp Hartford Hospital, Olin Neuropsychiatry Research CenterCT, United States
^bq Dartmouth-Hitchcock Medical CenterNH, United States
^br Wake Forest University Health SciencesNC, United States
^bs Rhode Island HospitalRI, United States
^bt Butler HospitalRI, United States
^bu Medical University South CarolinaNC, United States
^bv Nathan Kline InstituteNY, United States
^bw University of Iowa College of MedicineIA, United States
^bx USF Health Byrd Alzheimer’s Institute, University of South FloridaFL, United States

Abstract
In the Alzheimer’s disease (AD) continuum, the prodromal state of mild cognitive impairment (MCI) precedes AD dementia and identifying MCI individuals at risk of progression is important for clinical management. Our goal was to develop generalizable multivariate models that integrate high-dimensional data (multimodal neuroimaging and cerebrospinal fluid biomarkers, genetic factors, and measures of cognitive resilience) for identification of MCI individuals who progress to AD within 3 years. Our main findings were i) we were able to build generalizable models with clinically relevant accuracy (~93%) for identifying MCI individuals who progress to AD within 3 years; ii) markers of AD pathophysiology (amyloid, tau, neuronal injury) accounted for large shares of the variance in predicting progression; iii) our methodology allowed us to discover that expression of CR1 (complement receptor 1), an AD susceptibility gene involved in immune pathways, uniquely added independent predictive value. This work highlights the value of optimized machine learning approaches for analyzing multimodal patient information for making predictive assessments. © 2019, The Author(s).

Document Type: Article
Publication Stage: Final
Source: Scopus

“Development of context-sensitive pronunciation in reading: The case of ‹c› and ‹g›” (2019) Journal of Experimental Child Psychology

Development of context-sensitive pronunciation in reading: The case of ‹c› and ‹g›
(2019) Journal of Experimental Child Psychology, 182, pp. 114-125.

Treiman, R., Kessler, B.

Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO 63130, United States

Abstract
Writing systems sometimes deviate from one-to-one associations between letters and phonemes, but the deviations are often predictable from sublexical context. For initial ‹c› and ‹g› in English, deviations from the typical /k/ and /g/ pronunciations are influenced by adjacent context (the following vowel, as in center vs. canter) and nonadjacent context (the presence of a Latinate vs. basic suffix, as in gigantic vs. giggling). We conducted two experiments with participants ranging in reading level from early elementary school to university to study the development of context use. Experiment 1 focused on adjacent context, and Experiment 2 also examined nonadjacent context. Use of context developed slowly, and readers at all levels were not as influenced by it as would be expected given the contextual effects in the English vocabulary. We discuss possible reasons for these phenomena and the need to teach children to use context more effectively. © 2019 Elsevier Inc.

Author Keywords
Decoding; Reading; Spelling-to-sound correspondences; Sublexical context

Document Type: Article
Publication Stage: Final
Source: Scopus

“Prenatal lead exposure impacts cross-hemispheric and long-range connectivity in the human fetal brain” (2019) NeuroImage

Prenatal lead exposure impacts cross-hemispheric and long-range connectivity in the human fetal brain
(2019) NeuroImage, 191, pp. 186-192.

Thomason, M.E.^a ^b ^c , Hect, J.L.^d , Rauh, V.A.^e , Trentacosta, C.^d , Wheelock, M.D.^f , Eggebrecht, A.T.^g , Espinoza-Heredia, C.^a , Burt, S.A.^h

^a Department of Child and Adolescent Psychiatry, New York University Medical Center, New York, United States
^b Department of Population Health, New York University Medical Center, New York, NY, United States
^c Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
^d Department of Psychology, Wayne State University, Detroit, MI, United States
^e The Heilbrunn Department of Population & Family Health, Columbia University Medical Center, New York, NY, United States
^f Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States
^g Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
^h Department of Psychology, Michigan State University, East LansingMI, United States

Abstract
Lead represents a highly prevalent metal toxicant with potential to alter human biology in lasting ways. A population segment that is particularly vulnerable to the negative consequences of lead exposure is the human fetus, as exposure events occurring before birth are linked to varied and long-ranging negative health and behavioral outcomes. An area that has yet to be addressed is the potential that lead exposure during pregnancy alters brain development even before an individual is born. Here, we combine prenatal lead exposure information extracted from newborn bloodspots with the human fetal brain functional MRI data to assess whether neural network connectivity differs between lead-exposed and lead-naïve fetuses. We found that neural connectivity patterns differed in lead-exposed and comparison groups such that fetuses that were not exposed demonstrated stronger age-related increases in cross-hemispheric connectivity, while the lead-exposed group demonstrated stronger age-related increases in posterior cingulate cortex (PCC) to lateral prefrontal cortex (PFC) connectivity. These are the first results to demonstrate metal toxicant-related alterations in human fetal neural connectivity. Remarkably, the findings point to alterations in systems that support higher-order cognitive and regulatory functions. Objectives for future work are to replicate these results in larger samples and to test the possibility that these alterations may account for significant variation in future child cognitive and behavioral outcomes. © 2019 Elsevier Inc.

Author Keywords
Brain; Connectivity; Fetal; Lead; MRI; Prenatal; Resting-state

Document Type: Article
Publication Stage: Final
Source: Scopus

“Impact of early diabetic ketoacidosis on the developing brain” (2019) Diabetes Care

Impact of early diabetic ketoacidosis on the developing brain
(2019) Diabetes Care, 42 (3), pp. 443-449.

Aye, T.^a ^j , Mazaika, P.K.^b , Mauras, N.^c , Marzelli, M.J.^b , Shen, H.^b , Hershey, T.^d , Cato, A.^e , Weinzimer, S.A.^f , White, N.H.^g , Tsalikian, E.^h , Jo, B.^b , Reiss, A.L.^b ⁱ

^a Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
^b Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
^c Division of Pediatric Endocrinology, Department of Pediatrics, Nemours Children’s Health System, Jacksonville, FL, United States
^d Departments of Psychiatry and Radiology, Washington University School of Medicine, St. Louis, MO, United States
^e Division of Neurology, Department of Pediatrics, Nemours Children’s Health System, Jacksonville, FL, United States
^f Section of Pediatric Endocrinology, Department of Pediatrics, Yale University, New Haven, CT, United States
^g Division of Endocrinology and Diabetes, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
^h Division of Endocrinology and Diabetes, Stead Family Department of Pediatrics, University of Iowa, Iowa City, IA, United States
ⁱ Departments of Radiology and Pediatrics, Stanford University School of Medicine, Stanford, CA, United States

Abstract
OBJECTIVE This study examined whether a history of diabetic ketoacidosis (DKA) is associated with changes in longitudinal cognitive and brain development in young children with type 1 diabetes. RESEARCH DESIGN AND METHODS Cognitive and brain imaging data were analyzed from 144 children with type 1 diabetes, ages 4 to <10 years, who participated in an observational study of the Diabetes Research in Children Network (DirecNet). Participants were grouped according to history of DKA severity (none/mild or moderate/severe). Each participant had unsedated MRI scans and cognitive testing at baseline and 18 months. RESULTS In 48 of 51 subjects, the DKA event occurred at the time of onset, at an average of 2.9 years before study entry. The moderate/severe DKA group gained more total and regional white and gray matter volume over the observed 18 months compared with the none/mild group. When matched by age at time of enrollment and average HbA 1c during the 18-month interval, participants who had a history of moderate/severe DKA compared with none/mild DKA were observed to have significantly lower Full Scale Intelligence Quotient scores and cognitive performance on the Detectability and Commission subtests of the Conners’ Continuous Performance Test II and the Dot Locations subtest of the Children’s Memory Scale. CONCLUSIONS A single episode of moderate/severe DKA in young children at diagnosis is associated with lower cognitive scores and altered brain growth. Further studies are needed to assess whether earlier diagnosis of type 1 diabetes and prevention of DKA may reduce the long-term effect of ketoacidosis on the developing brain. © 2018 by the American Diabetes Association.

Document Type: Article
Publication Stage: Final
Source: Scopus

“Effect of routing paradigm on patient-centered outcomes in acute ischemic stroke” (2019) Journal of NeuroInterventional Surgery

Effect of routing paradigm on patient-centered outcomes in acute ischemic stroke
(2019) Journal of NeuroInterventional Surgery, 11 (3), pp. 251-256.

Zhou, M.H.^a , Kansagra, A.P.^b ^c ^d

^a School of Medicine, Washington University School of Medicine, St Louis, MO, United States
^b Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, MO 63110, United States
^c Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, United States
^d Department of Neurology, Washington University School of Medicine, St Louis, MO, United States

Abstract
Objective To compare performance of routing paradigms for patients with acute ischemic stroke using clinical outcomes. Methods We simulated different routing paradigms in a system comprising one primary stroke center (PSC) and onecomprehensive stroke center (CSC), separated by distances representative of urban, suburban, and rural environments. In the Nearest Center paradigm, patients are initially sent to the nearest center, while in CSC First, patients are sent to the CSC. In Rhode Island and Distributive paradigms, patients with Field Assessment Stroke Triage for Emergency Destination (FAST-ED) score ≥4 are sent to the CSC, while others are sent to the nearest center or PSC, respectively. Performance and efficiency were compared using rates of good clinical outcome determined by type and timing of treatment using clinical trial data and number needed to bypass (NNB). Results Good clinical outcome was achieved in 43.67% of patients in Nearest Center and 44.62% in CSC First, Rhode Island, and Distributive in an urban setting; 42.79% in Nearest Center and 43.97% in CSC First and Rhode Island in a suburban setting; and 39.76% in Nearest Center, 41.73% in CSC First, and 41.59% in Rhode Island in a rural setting. In all settings, the NNB was considerably higher for CSC First than for Rhode Island or Distributive. Conclusion Routing paradigms that allow bypass of nearer hospitals for thrombectomy-capable centers improve population-level patient outcomes. Differences are more pronounced with increasing distance between hospitals; therefore, the choice of model may have greater effect in rural settings. Selective bypass, as implemented in Rhode Island and Distributive paradigms, improves system efficiency with minimal effect on outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019.

Author Keywords
stroke; thrombectomy

Document Type: Article
Publication Stage: Final
Source: Scopus

“Mechanisms underlying mechanical sensitization induced by complement C5a: the roles of macrophages, TRPV1, and calcitonin gene-related peptide receptors” (2019) Pain

Mechanisms underlying mechanical sensitization induced by complement C5a: the roles of macrophages, TRPV1, and calcitonin gene-related peptide receptors
(2019) Pain, 160 (3), pp. 702-711.

Warwick, C.A.^a , Shutov, L.P.^a , Shepherd, A.J.^b , Mohapatra, D.P.^b , Usachev, Y.M.^a

^a Department of Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, IA, United States
^b Department of Anesthesiology, Washington University Pain Center, Washington University School of Medicine, St. Louis, MO, United States

Abstract
The complement system significantly contributes to the development of inflammatory and neuropathic pain, but the underlying mechanisms are poorly understood. Recently, we identified the signaling pathway responsible for thermal hypersensitivity induced by the complement system component C5a. Here, we examine the mechanisms of another important action of C5a, induction of mechanical hypersensitivity. We found that intraplantar injection of C5a produced a dose-dependent mechanical sensitization and that this effect was blocked by chemogenetic ablation of macrophages in both male and female mice. Knockout of TRPV1 or pretreatment with the TRPV1 antagonists, AMG9810 or 5′-iodoresiniferatoxin (5′-IRTX), significantly reduced C5a-induced mechanical sensitization. Notably, local administration of 5′-IRTX 90 minutes after C5a injection resulted in a slow, but complete, reversal of mechanical sensitization, indicating that TRPV1 activity was required for maintaining C5a-induced mechanical hypersensitivity. This slow reversal suggests that neurogenic inflammation and neuropeptide release may be involved. Indeed, pretreatment with a calcitonin gene-related peptide (CGRP) receptor antagonist (but not an antagonist of the neurokinin 1 receptor) prevented C5a-induced mechanical sensitization. Furthermore, intraplantar injection of CGRP produced significant mechanical sensitization in both wild-type and TRPV1 knockout mice. Taken together, these findings suggest that C5a produces mechanical sensitization by initiating macrophage-to-sensory-neuron signaling cascade that involves activation of TRPV1 and CGRP receptor as critical steps in this process.

Document Type: Article
Publication Stage: Final
Source: Scopus

“Persistent metabolic youth in the aging female brain” (2019) Proceedings of the National Academy of Sciences of the United States of America

Persistent metabolic youth in the aging female brain
(2019) Proceedings of the National Academy of Sciences of the United States of America, 116 (8), pp. 3251-3255.

Goyal, M.S.^a ^b , Blazey, T.M.^a , Su, Y.^a , Couture, L.E.^a , Durbin, T.J.^a , Bateman, R.J.^b , Benzinger, T.L.-S.^a , Morris, J.C.^b , Raichle, M.E.^a ^b , Vlassenko, A.G.^a

^a Neuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (n = 205) to define their metabolic brain age. We find that throughout the adult life span the female brain has a persistently lower metabolic brain age—relative to their chronological age—compared with the male brain. The persistence of relatively younger metabolic brain age in females throughout adulthood suggests that development might in part influence sex differences in brain aging. Our results also demonstrate that trajectories of natural brain aging vary significantly among individuals and provide a method to measure this. © 2019 National Academy of Sciences. All Rights Reserved.

Author Keywords
Brain aging; Brain metabolism; Machine learning; Neoteny; Sex differences

Document Type: Article
Publication Stage: Final
Source: Scopus

“Mural cell-derived laminin-α5 plays a detrimental role in ischemic stroke” (2019) Acta neuropathologica communications

Mural cell-derived laminin-α5 plays a detrimental role in ischemic stroke
(2019) Acta neuropathologica communications, 7 (1), p. 23.

Nirwane, A.^a , Johnson, J.^a , Nguyen, B.^a , Miner, J.H.^b , Yao, Y.^a

^a Department of Pharmaceutical and Biomedical Sciences, University of Georgia, 240 W Green Street, Athens, GA 30602, United States
^b Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States

Abstract
At the blood-brain barrier (BBB), laminin-α5 is predominantly synthesized by endothelial cells and mural cells. Endothelial laminin-α5 is dispensable for BBB maintenance under homeostatic conditions but inhibits inflammatory cell extravasation in pathological conditions. Whether mural cell-derived laminin-α5 is involved in vascular integrity regulation, however, remains unknown. To answer this question, we generated transgenic mice with laminin-α5 deficiency in mural cells (α5-PKO). Under homeostatic conditions, no defects in BBB integrity and cerebral blood flow (CBF) were observed in α5-PKO mice, suggesting that mural cell-derived laminin-α5 is dispensable for BBB maintenance and CBF regulation under homeostatic conditions. After ischemia-reperfusion (MCAO) injury, however, α5-PKO mice displayed less severe neuronal injury, including reduced infarct volume, decreased neuronal death, and improved neurological function. In addition, α5-PKO mice also showed attenuated vascular damage (milder BBB disruption, reduced inflammatory cell infiltration, decreased brain edema, and diminished hemorrhagic transformation). Mechanistic studies revealed less severe tight junction protein (TJP) loss and pericyte coverage reduction in α5-PKO mice after ischemia-reperfusion injury, indicating that the attenuated ischemic injury in α5-PKO mice is possibly due to less severe vascular damage. These findings suggest that mural cell-derived laminin-α5 plays a detrimental role in ischemic stroke and that inhibiting its signaling may have a neuroprotective effect.

Author Keywords
Blood-brain barrier; Ischemic stroke; Laminin; MCAO; Mural cells

Document Type: Article
Publication Stage: Final
Source: Scopus

“Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma” (2019) Acta neuropathologica communications

Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma
(2019) Acta neuropathologica communications, 7 (1), p. 20.

Haage, V.^a , Semtner, M.^a , Vidal, R.O.^a , Hernandez, D.P.^a , Pong, W.W.^b , Chen, Z.^c , Hambardzumyan, D.^c , Magrini, V.^d , Ly, A.^d , Walker, J.^d , Mardis, E.^d , Mertins, P.^a , Sauer, S.^a , Kettenmann, H.^a , Gutmann, D.H.^a ^b

^a Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
^b Department of Neurology, Washington University School of Medicine, Box 8111, 660 S. Euclid Avenue, St. Louis, MO 63110, United States
^c Department of Pediatrics, Emory University, Atlanta, GA, United States
^d McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, United States

Abstract
Monocytes/macrophages have begun to emerge as key cellular modulators of brain homeostasis and central nervous system (CNS) disease. In the healthy brain, resident microglia are the predominant macrophage cell population; however, under conditions of blood-brain barrier leakage, peripheral monocytes/macrophages can infiltrate the brain and participate in CNS disease pathogenesis. Distinguishing these two populations is often challenging, owing to a paucity of universally accepted and reliable markers. To identify discriminatory marker sets for microglia and peripheral monocytes/macrophages, we employed a large meta-analytic approach using five published murine transcriptional datasets. Following hierarchical clustering, we filtered the top differentially expressed genes (DEGs) through a brain cell type-specific sequencing database, which led to the identification of eight microglia and eight peripheral monocyte/macrophage markers. We then validated their differential expression, leveraging a published single cell RNA sequencing dataset and quantitative RT-PCR using freshly isolated microglia and peripheral monocytes/macrophages from two different mouse strains. We further verified the translation of these DEGs at the protein level. As top microglia DEGs, we identified P2ry12, Tmem119, Slc2a5 and Fcrls, whereas Emilin2, Gda, Hp and Sell emerged as the best DEGs for identifying peripheral monocytes/macrophages. Lastly, we evaluated their utility in discriminating monocyte/macrophage populations in the setting of brain pathology (glioma), and found that these DEG sets distinguished glioma-associated microglia from macrophages in both RCAS and GL261 mouse models of glioblastoma. Taken together, this unbiased bioinformatic approach facilitated the discovery of a robust set of microglia and peripheral monocyte/macrophage expression markers to discriminate these monocyte populations in both health and disease.

Author Keywords
CNS; RNA sequencing; Glioma; Macrophages; Microarray; Microglia; Monocytes

Document Type: Article
Publication Stage: Final
Source: Scopus

“The cuticular hydrocarbon profiles of honey bee workers develop via a socially-modulated innate process” (2019) eLife

The cuticular hydrocarbon profiles of honey bee workers develop via a socially-modulated innate process
(2019) eLife, 8, .

Vernier, C.L.^a , Krupp, J.J.^b , Marcus, K.^a , Hefetz, A.^c , Levine, J.D.^b , Ben-Shahar, Y.^a

^a Department of Biology, Washington University in Saint Louis, Saint Louis, United States
^b Department of Biology, University of Toronto Mississauga, Mississauga, Canada
^c Department of Zoology, Tel Aviv UniversityTel Aviv, Israel

Abstract
Large social insect colonies exhibit a remarkable ability for recognizing group members via colony-specific cuticular pheromonal signatures. Previous work suggested that in some ant species, colony-specific pheromonal profiles are generated through a mechanism involving the transfer and homogenization of cuticular hydrocarbons (CHCs) across members of the colony. However, how colony-specific chemical profiles are generated in other social insect clades remains mostly unknown. Here we show that in the honey bee (Apis mellifera), the colony-specific CHC profile completes its maturation in foragers via a sequence of stereotypic age-dependent quantitative and qualitative chemical transitions, which are driven by environmentally-sensitive intrinsic biosynthetic pathways. Therefore, the CHC profiles of individual honey bees are not likely produced through homogenization and transfer mechanisms, but instead mature in association with age-dependent division of labor. Furthermore, non-nestmate rejection behaviors seem to be contextually restricted to behavioral interactions between entering foragers and guards at the hive entrance. © 2019, Vernier et al.

Author Keywords
Apis melifera; ecology; honey bee; social insects

Document Type: Article
Publication Stage: Final
Source: Scopus
Access Type: Open Access

“Reliability and validity of the Japanese version of the Alzheimer’s Disease Knowledge Scale” (2019) Dementia

Reliability and validity of the Japanese version of the Alzheimer’s Disease Knowledge Scale
(2019) Dementia, 18 (2), pp. 599-612.

Amano, T.^a , Yamanaka, K.^b , Carpenter, B.D.^a

^a Washington University, St. Louis, United States
^b University of Tsukuba, Japan

Abstract
Concerned with the importance of prevailing knowledge about dementia in supporting those with dementia, large-scale educational programs have been implemented in some countries. Although Japan is one of those few countries, the experience from Japanese programs has been rarely shared because of the lack of a standardized measurement for assessing knowledge about dementia. This study aims to develop a Japanese version of the Alzheimer’s Disease Knowledge Scale (JADKS) and to examine its reliability and validity. The JADKS was developed through a translation–back-translation process and was distributed to 837 people including university students, community-dwelling older people, health and welfare professionals, and family caregivers. Using data from the 566 participants who fully completed the questionnaire, test–retest reliability, internal consistency, and concurrent validity were evaluated. The results indicate that the JADKS has acceptable psychometric properties. The JADKS may be useful in assessing knowledge about dementia and could help compare effectiveness of educational programs. © The Author(s) 2016.

Author Keywords
Alzheimer’s disease; assessment; dementia; evaluation; knowledge

Document Type: Article
Publication Stage: Final
Source: Scopus

“MP1104, a mixed kappa-delta opioid receptor agonist has anti-cocaine properties with reduced side-effects in rats” (2019) Neuropharmacology

MP1104, a mixed kappa-delta opioid receptor agonist has anti-cocaine properties with reduced side-effects in rats
(2019) Neuropharmacology, .

Atigari, D.V.^a , Uprety, R.^b , Pasternak, G.W.^b , Majumdar, S.^b ^c , Kivell, B.M.^a

^a School of Biological Sciences, Centre for Biodiscovery, Victoria University of Wellington, Wellington, New Zealand
^b Molecular Pharmacology Program and Department of Neurology, Memorial Sloan Kettering Cancer Centre, New York, United States
^c Center for Clinical Pharmacology, St Louis College of Pharmacy and Washington University School of Medicine, St Louis, MO, United States

Abstract
Kappa opioid receptor (KOPr) agonists have preclinical anti-cocaine and antinociceptive effects. However, adverse effects including dysphoria, aversion, sedation, anxiety and depression limit their clinical development. MP1104, an analogue of 3-iodobenzoyl naltrexamine, is a potent dual agonist at KOPr and delta opioid receptor (DOPr), with full agonist efficacy at both these receptors. In this study, we evaluate the ability of MP1104 to modulate cocaine-induced behaviors and side-effects preclinically. In male Sprague-Dawley rats trained to self-administer cocaine, MP1104 (0.3 and 1 mg/kg) reduced cocaine-primed reinstatement of drug-seeking behavior and caused significant downward shift of the dose-response curve in cocaine self-administration tests (0.3 and 0.6 mg/kg). The anti-cocaine effects exerted by MP1104 are in part due to increased dopamine (DA) uptake by the dopamine transporter (DAT) in the dorsal striatum (dStr) and nucleus accumbens (NAc). MP1104 (0.3 and 0.6 mg/kg) showed no significant anxiogenic effects in the elevated plus maze, pro-depressive effects in the forced swim test, or conditioned place aversion. Furthermore, pre-treatment with a DOPr antagonist, led to MP1104 producing aversive effects. This data suggests that the DOPr agonist actions of MP1104 attenuate the KOPr-mediated aversive effects of MP1104. The overall results from this study show that MP1104, modulates DA uptake in the dStr and NAc, and exerts potent anti-cocaine properties in self-administration tests with reduced side-effects compared to pure KOPr agonists. This data supports the therapeutic development of dual KOPr/DOPr agonists to reduce the side-effects of selective KOPr agonists. © 2019 Elsevier Ltd

Author Keywords
Behavioural pharmacology; Cocaine; Conditioned place aversion; Drug-seeking; Elevated plus maze; Self-administration

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

“A multicenter phase II study of temozolomide plus disulfiram and copper for recurrent temozolomide-resistant glioblastoma” (2019) Journal of Neuro-Oncology

A multicenter phase II study of temozolomide plus disulfiram and copper for recurrent temozolomide-resistant glioblastoma
(2019) Journal of Neuro-Oncology, .

Huang, J.^a ⁱ , Chaudhary, R.^b , Cohen, A.L.^c , Fink, K.^d , Goldlust, S.^e , Boockvar, J.^f , Chinnaiyan, P.^g , Wan, L.^a , Marcus, S.^h , Campian, J.L.^a

^a Washington University School of Medicine, St. Louis, MO, United States
^b University of Cincinnati College of Medicine, Cincinnati, OH, United States
^c Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, United States
^d Baylor University Medical Center, Dallas, TX, United States
^e Hackensack University Medical Center, Hackensack, NJ, United States
^f Lenox Hill Hospital, New York, NY, United States
^g Beaumont Health, Royal Oak, MI, United States
^h Cantex Pharmaceuticals, Weston, FL, United States
ⁱ Department of Radiation Oncology, Center for Advanced Medicine, Washington University School of Medicine, 4921 Parkview Place, Campus Box #8224, St. Louis, MO 63110, United States

Abstract
Purpose: Preclinical studies have suggested promising activity for the combination of disulfiram and copper (DSF/Cu) against glioblastoma (GBM) including re-sensitization to temozolomide (TMZ). A previous phase I study demonstrated the safety of combining DSF/Cu with adjuvant TMZ for newly diagnosed GBM. This phase II study aimed to estimate the potential effectiveness of DSF/Cu to re-sensitize recurrent GBM to TMZ. Methods: This open-label, single-arm phase II study treated recurrent TMZ-resistant GBM patients with standard monthly TMZ plus concurrent daily DSF 80 mg PO TID and Cu 1.5 mg PO TID. Eligible patients must have progressed after standard chemoradiotherapy and within 3 months of the last dose of TMZ. Known isocitrate dehydrogenase (IDH) mutant or secondary GBMs were excluded. The primary endpoint was objective response rate (ORR), and the secondary endpoints included progression-free survival (PFS), overall survival (OS), clinical benefit (response or stable disease for at least 6 months), and safety. Results: From March 2017 to January 2018, 23 recurrent TMZ-resistant GBM patients were enrolled across seven centers, and 21 patients were evaluable for response. The median duration of DSF/Cu was 1.6 cycles (range: 0.1–12.0). The ORR was 0%, but 14% had clinical benefit. Median PFS was 1.7 months, and median OS was 7.1 months. Only one patient (4%) had dose-limiting toxicity (grade three elevated alanine transaminase). Conclusions: Addition of DSF/Cu to TMZ for TMZ-resistant IDH-wild type GBM appears well tolerated but has limited activity for unselected population. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Clinical trial; Copper; Disulfiram; Recurrent glioblastoma; Temozolomide

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

“Impact of Baseline Features and Risk Factor Control on Cognitive Function in the Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis Trial” (2019) Cerebrovascular Diseases

Impact of Baseline Features and Risk Factor Control on Cognitive Function in the Stenting and Aggressive Medical Management for Preventing Recurrent Stroke in Intracranial Stenosis Trial
(2019) Cerebrovascular Diseases, pp. 24-31.

Turan, T.N.^a , Al Kasab, S.^b , Smock, A.^a , Cotsonis, G.^c , Bachman, D.^a , Lynn, M.J.^d , Nizam, A.^b , Derdeyn, C.P.^b , Fiorella, D.^e , Janis, S.^f , Lane, B.^b , Montgomery, J.^c , Chimowitz, M.I.^a

^a Medical University of South Carolina, Charleston, SC, United States
^b Department of Neurology, University of Iowa Hospitals and Clinics, 200 Hawkins Dr, Iowa City, IA 52246, United States
^c Department of Public Health, Emory University, Atlanta, GA, United States
^d Washington University, St. Louis, MI, United States
^e Department of Neurosurgery, State University of New York at Stony Brook, Stony Brook, NY, United States
^f National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States

Abstract
Background: Cerebrovascular disease is an important cause of cognitive impairment. The aim of this study is to report the relationship between cognitive function and risk factors at baseline and during follow-up in the Stenting and Aggressive Medical Management for Preventing Recurrent stroke in Intracranial Stenosis (SAMMPRIS) trial. Methods: Subjects in the SAMMPRIS trial were included in this study. In order to have an assessment of cognitive function independent of stroke, patients with a stroke as a qualifying event whose deficits included aphasia or neglect were excluded from these analyses as were those with a cerebrovascular event during follow-up. The Montreal Cognitive Assessment (MoCA) score was used to assess cognitive impairment at baseline, 4 months, 12 months and closeout. Cognitive impairment was defined as MoCA < 26. A multivariate analysis was performed to determine what risk factors were independent predictors of cognitive function at baseline, 12 months and closeout. Among patients randomized to aggressive medical management only, the percentage of patients with cognitive impairment was compared between patients in versus out of target for each risk factor at 12 months and closeout. Results: Of the 451 patients in SAMMPRIS, 371 patients met the inclusion criteria. MoCA < 26 was present in 55% at baseline. Older age and physical inactivity were associated with cognitive impairment at baseline. Older age, non-white race, lower baseline body mass index, and baseline cognitive impairment were associated with cognitive impairment at 12 months. In the aggressive medical management group, at 12 months, physical inactivity during follow-up was the strongest risk factor associated with cognitive impairment. Conclusion: Cognitive impairment is common in patients with severe symptomatic intracranial atherosclerosis. Physical inactivity at baseline and during follow-up is a strong predictor of cognitive impairment. © 2019 S. Karger AG, Basel.

Author Keywords
Cognitive impairment; Intracranial atherosclerosis; Ischemic stroke

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

“Reply to ‘obstructive sleep apnea treatment and amyloid-β in cerebrospinal fluid'” (2019) Annals of Neurology

Reply to “obstructive sleep apnea treatment and amyloid-β in cerebrospinal fluid”
(2019) Annals of Neurology, .

Ju, Y.-E.S.^a ^b , Holtzman, D.M.^a ^b

^a Department of Neurology, Washington University, Saint Louis, MO, United States
^b Hope Center for Neurological Disorders, Washington University, Saint Louis, MO, United States

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

“A 3D Computational Head Model Under Dynamic Head Rotation and Head Extension Validated Using Live Human Brain Data, Including the Falx and the Tentorium” (2019) Annals of Biomedical Engineering

A 3D Computational Head Model Under Dynamic Head Rotation and Head Extension Validated Using Live Human Brain Data, Including the Falx and the Tentorium
(2019) Annals of Biomedical Engineering, .

Lu, Y.-C.^a , Daphalapurkar, N.P.^a ^b , Knutsen, A.K.^e , Glaister, J.^c , Pham, D.L.^e , Butman, J.A.^f , Prince, J.L.^c , Bayly, P.V.^d , Ramesh, K.T.^a ^b

^a Hopkins Extreme Materials Institute, Johns Hopkins University, Baltimore, MD, United States
^b Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, United States
^c Department of Electrical & Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
^d Department of Mechanical Engineering, Washington University in St. Louis, St. Louis, MO, United States
^e Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
^f National Institutes of Health Clinical Center, Bethesda, MD, United States

Abstract
We employ an advanced 3D computational model of the head with high anatomical fidelity, together with measured tissue properties, to assess the consequences of dynamic loading to the head in two distinct modes: head rotation and head extension. We use a subject-specific computational head model, using the material point method, built from T1 magnetic resonance images, and considering the anisotropic properties of the white matter which can predict strains in the brain under large rotational accelerations. The material model now includes the shear anisotropy of the white matter. We validate the model under head rotation and head extension motions using live human data, and advance a prior version of the model to include biofidelic falx and tentorium. We then examine the consequences of incorporating the falx and tentorium in terms of the predictions from the computational head model. © 2019, Biomedical Engineering Society.

Author Keywords
Brain modeling; In vivo experiments; TBI; Validation

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

“An In Vitro Brain Endothelial Model for Studies of Cryptococcal Transmigration into the Central Nervous System” (2019) Current Protocols in Microbiology

An In Vitro Brain Endothelial Model for Studies of Cryptococcal Transmigration into the Central Nervous System
(2019) Current Protocols in Microbiology, art. no. e78, .

Santiago-Tirado, F.H.^a ^c , Klein, R.S.^b , Doering, T.L.^a

^a Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
^c Current address: Department of Biological Sciences, University of Notre Dame, Notre Dame, IN, United States

Abstract
Cryptococcus neoformans is an environmental yeast found worldwide that causes lethal brain infections, particularly in immunocompromised hosts. In 2016, there were 280,000 cases of cryptococcal meningitis in the HIV+ population, two-thirds of them fatal; other immunocompromised patients are also affected. The burden of cryptococcal disease and the limits of current chemotherapy create a pressing need for improved treatment. One hindrance to the development of new therapies is lack of understanding of how this pathogen breaches the barriers protecting the brain. Here we describe a tool for investigating this process. This simple in vitro blood-brain-barrier (BBB) model, based on a human brain endothelial cell line grown on a permeable membrane, may be used to assay the BBB transmigration of C. neoformans or other neurotropic pathogens. © 2019 by John Wiley & Sons, Inc. © 2019 John Wiley & Sons, Inc.

Author Keywords
blood–brain barrier; cryptococcosis; Cryptococcus neoformans; fungal meningitis; hCMEC/D3; transwell permeable supports

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

“Staging biomarkers in preclinical autosomal dominant Alzheimer’s disease by estimated years to symptom onset” (2019) Alzheimer’s and Dementia

Staging biomarkers in preclinical autosomal dominant Alzheimer’s disease by estimated years to symptom onset
(2019) Alzheimer’s and Dementia, .

Wang, G.^a , Coble, D.^a , McDade, E.M.^b , Hassenstab, J.^b , Fagan, A.M.^b , Benzinger, T.L.S.^c , Bateman, R.J.^b , Morris, J.C.^b , Xiong, C.^a , Dominantly Inherited Alzheimer Network (DIAN)^d

^a Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, United States
^b Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
^c Department of Radiology, Washington University School of Medicine, Saint Louis, MO, United States

Abstract
Introduction: Staging preclinical Alzheimer disease (AD) by the expected years to symptom onset (EYO) in autosomal dominant AD (ADAD) through biomarker correlations is important. Methods: We estimated the correlation matrix between EYO/cognition and imaging/CSF biomarkers, and searched for the EYO cutoff where a change in the correlations occurred before and after the cutoff among the asymptomatic mutation carriers of ADAD. We then estimated the longitudinal rate of change for biomarkers/cognition within each preclinical stage defined by the EYO. Results: Based on the change in the correlations, the preclinical ADAD was divided by EYOs −7 and −13 years. Mutation carriers demonstrated a temporal ordering of biomarker/cognition changes across the three preclinical stages. Discussion: Duration of each preclinical stage can be estimated in ADAD, facilitating better planning of prevention trials with the EYO cutoffs under the recently released FDA guidance. The generalization of these results to sporadic AD warrants further investigation. © 2018 the Alzheimer’s Association

Author Keywords
Autosomal dominant Alzheimer disease; Biomarkers; Dominantly inherited Alzheimer Network; Preclinical Alzheimer disease

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

“Boundary conditions for the influence of spatial proximity on context-specific attentional settings” (2019) Attention, Perception, and Psychophysics

Boundary conditions for the influence of spatial proximity on context-specific attentional settings
(2019) Attention, Perception, and Psychophysics, .

Diede, N.T., Bugg, J.M.

Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, United States

Abstract
Flexibility of cognitive control is illustrated by the context-specific proportion compatibility (CSPC) effect, the now well-documented pattern showing that compatibility effects are reduced in mostly incompatible relative to mostly compatible locations. The episodic-retrieval account attributes the CSPC effect to location-specific representations that include the attentional settings formed via experience within a given location (e.g., a “focused” attentional setting becomes bound to a location with frequent conflict, whereas a “relaxed” setting becomes bound to one with infrequent conflict). However, Diede and Bugg (Attention, Perception, & Psychophysics, 78, 1255–1266, 2016) demonstrated that the attentional setting associated with a given location can be based on experiences that accumulate across multiple “grouped” locations—namely, those that are proximal to each other, relative to other (distal) locations. This spatial grouping effect supported the relative-proximity hypothesis, which we further tested in the present study. Experiment 1 replicated the spatial grouping effect and showed that it could be disrupted by a horizontal line dividing the otherwise grouped locations. Experiments 2 through 4 suggested that grouping might be a form of “chunking”—that is, the spatial grouping effect did not occur when the proximal locations were few enough in number (two) to represent independently, but it did occur when there were six locations. When there were eight proximal locations (and ten locations overall), the CSPC effect disappeared entirely. These findings suggest important boundary conditions for the relative-proximity hypothesis and inform our understanding of how past experiences with conflict are organized in the form of episodic representations that enable on-the-fly adjustments in cognitive control. © 2019, The Psychonomic Society, Inc.

Author Keywords
Context-specific cognitive control; Flanker; Proportion congruence; Spatial proximity

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

“Longitudinal evaluation of surrogates of regional cerebral blood flow computed from dynamic amyloid PET imaging” (2019) Journal of Cerebral Blood Flow and Metabolism

Longitudinal evaluation of surrogates of regional cerebral blood flow computed from dynamic amyloid PET imaging
(2019) Journal of Cerebral Blood Flow and Metabolism, .

Bilgel, M.^a , Beason-Held, L.^a , An, Y.^a , Zhou, Y.^b ^c , Wong, D.F.^b ^d ^e ^f , Resnick, S.M.^a

^a Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), Baltimore, United States
^b Department of Radiology and Radiological Science, Johns Hopkins University School (JHU) of Medicine, Baltimore, United States
^c Mallinckrodt Institute of Radiology, Washington University in St. Louis School of Medicine, St. Louis, United States
^d Department of Psychiatry and Behavioral Sciences, JHU School of Medicine, Baltimore, United States
^e Department of Neuroscience, JHU School of Medicine, Baltimore, United States
^f Department of Neurology, JHU School of Medicine, Baltimore, United States

Abstract
Surrogates of neuronal activity, typically measured by regional cerebral blood flow (rCBF) or glucose metabolism, can be estimated from dynamic amyloid PET imaging. Using data for 149 participants (345 visits) from the Baltimore Longitudinal Study of Aging, we assessed whether the average of early amyloid frames (EA) and R 1 computed from dynamic 11 C-Pittsburgh compound B (PiB) PET can serve as surrogates of rCBF computed from 15 O-H 2 O-PET. R 1 had the highest longitudinal test–retest reliability. Interquartile range (IQR) of cross-sectional Pearson correlations with rCBF was 0.60–0.72 for EA and 0.63–0.72 for R 1 . Correlations between rates of change were lower (IQR 0.22–0.50 for EA, 0.25–0.55 for R 1 ). Values in the Alzheimer’s metabolic signature meta-ROI were negatively associated with age and exhibited longitudinal declines for each PET measure. In age-adjusted analyses, meta-ROI rCBF and R 1 were lower among amyloid+ individuals; EA and R 1 were lower among males. Regional PiB-based measures, in particular R 1 , can be suitable surrogates of rCBF. Dynamic PiB-PET may obviate the need for a separate scan to measure neuronal activity, thereby reducing patient burden, radioactivity exposure, and cost. © The Author(s) 2019.

Author Keywords
Amyloid; cerebral blood flow; longitudinal; neurodegeneration; neuronal activity

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

“Involuntary Psychotropic Treatment in the Correctional System: Revisiting the Legal Standards” (2019) Journal of Correctional Health Care

Involuntary Psychotropic Treatment in the Correctional System: Revisiting the Legal Standards
(2019) Journal of Correctional Health Care, 25 (1), pp. 65-69.

Xiong, W.

Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, United States

Abstract
Correctional facilities are obligated to provide psychotropic medications, as part of standard psychiatric care, to inmates with serious mental illness. The right to refuse such medication treatment has become one of the most important and contested areas of legal regulation of correctional mental health. This article will focus on the three cases that have come before the U.S. Supreme Court thus far, as well as their implications for future medicolegal directions in pursuing involuntary treatment. © The Author(s) 2019.

Author Keywords
forensics; involuntary; legal; psychiatry; right to refuse; treatment

Document Type: Article
Publication Stage: Final
Source: Scopus

“De novo variants in HK1 associated with neurodevelopmental abnormalities and visual impairment” (2019) European Journal of Human Genetics

De novo variants in HK1 associated with neurodevelopmental abnormalities and visual impairment
(2019) European Journal of Human Genetics, .

Okur, V.^a , Cho, M.T.^b , van Wijk, R.^c , van Oirschot, B.^c , Picker, J.^d , Coury, S.A.^d , Grange, D.^e , Manwaring, L.^e , Krantz, I.^f , Muraresku, C.C.^f , Hulick, P.J.^g , May, H.^g , Pierce, E.^h , Place, E.^h , Bujakowska, K.^h , Telegrafi, A.^b , Douglas, G.^b , Monaghan, K.G.^b , Begtrup, A.^b , Wilson, A.^a , Retterer, K.^b , Anyane-Yeboa, K.^a , Chung, W.K.^a ⁱ

^a Department of Pediatrics, Columbia University Medical Center, New York, NY, United States
^b GeneDx, Gaithersburg, MD, United States
^c Department of Clinical Chemistry and Hematology, University Medical Center Utrecht, Utrecht, Netherlands
^d Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, United States
^e Department of Pediatrics, Division of Genetics and Genomic Medicine, Washington University School of Medicine, St. Louis, MO, United States
^f Division of Human Genetics, Department of Pediatrics, Individualized Medical Genetics Center, the Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^g Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL, United States
^h Ocular Genomics Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, United States
ⁱ Department of Medicine, Columbia University Medical Center, New York, NY, United States

Abstract
Hexokinase 1 (HK1) phosphorylates glucose to glucose-6-phosphate, the first rate-limiting step in glycolysis. Homozygous and heterozygous variants in HK1 have been shown to cause autosomal recessive non-spherocytic hemolytic anemia, autosomal recessive Russe type hereditary motor and sensory neuropathy, and autosomal dominant retinitis pigmentosa (adRP). We report seven patients from six unrelated families with a neurodevelopmental disorder associated with developmental delay, intellectual disability, structural brain abnormality, and visual impairments in whom we identified four novel, de novo missense variants in the N-terminal half of HK1. Hexokinase activity in red blood cells of two patients was normal, suggesting that the disease mechanism is not due to loss of hexokinase enzymatic activity. © 2019, European Society of Human Genetics.

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

“Continuous epidural infusion in gynecologic oncology patients undergoing exploratory laparotomy: The new standard for decreased postoperative pain and opioid use” (2019) Gynecologic Oncology

Continuous epidural infusion in gynecologic oncology patients undergoing exploratory laparotomy: The new standard for decreased postoperative pain and opioid use
(2019) Gynecologic Oncology, .

Huepenbecker, S.P.^a , Cusworth, S.E.^a , Kuroki, L.M.^b , Lu, P.^c , Samen, C.D.K.^c , Woolfolk, C.^a , Deterding, R.^a , Wan, L.^a , Helsten, D.L.^d , Bottros, M.^d , Mutch, D.G.^b , Powell, M.A.^b , Massad, L.S.^b , Thaker, P.H.^b

^a Department of Obstetrics and Gynecology, Washington University, St. Louis, MO, United States
^b Division of Gynecologic Oncology, Washington University, St. Louis, MO, United States
^c Washington University School of Medicine, St. Louis, MO, United States
^d Department of Anesthesiology, Washington University, St. Louis, MO, United States

Abstract
Objective: To compare the incidence of postoperative complications and opioid pain medication usage in gynecologic oncology patients who did and did not receive an epidural prior to undergoing exploratory laparotomy. Methods: Retrospective cohort study of all patients undergoing exploratory laparotomy with the gynecologic oncology division at Washington University in St Louis between January 2012 and October 2015. Data on demographics, pathology, postoperative pain and opioid use, and incidence of postoperative complications were collected. Results: Five hundred and sixty-one patients underwent laparotomy, 305 with an epidural and 256 without. Patients with an epidural used significantly less hydromorphone in the post-anesthesia care unit (PACU) (p = 0.003) and on postoperative day (POD)#1 (p = 0.05), less total opioids on POD#0 (p < 0.01), and more non-opioid pain medication on POD#1–3 (p < 0.01). Patients with an epidural had lower pain scores in the PACU (p = 0.01), on POD#0 (p < 0.01), POD#1 (p < 0.01), and POD#3 (p = 0.03). Patients with epidurals had shorter hospital length of stay (p < 0.01), no difference in hospital readmission or incidence of venous thromboembolism up to 90 days postoperatively, longer duration of Foley catheter (20.4 vs 10.3 h, p = 0.02) with no difference in postoperative urinary tract infection, higher incidence of postoperative hypotension (63% vs 36.3%, p < 0.01), and lower incidence of wound complications (5% vs 14.1%, p < 0.01). Conclusions: Perioperative epidurals used in patients undergoing major abdominal surgery correlate with decreased postoperative opioid use, increased use of non-opioid pain medications, and improved pain relief postoperatively with acceptable postoperative risks and should be standard of care for these patients. © 2019 Elsevier Inc.

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

“The evolution of the temporoparietal junction and posterior superior temporal sulcus” (2019) Cortex

The evolution of the temporoparietal junction and posterior superior temporal sulcus
(2019) Cortex, .

Patel, G.H.^a ^b , Sestieri, C.^c , Corbetta, M.^d ^e

^a Columbia University, United States
^b New York State Psychiatric Institute, United States
^c University of Chieti, Italy
^d University of Padova, Italy
^e Washington University School of Medicine, United States

Abstract
The scale at which humans can handle complex social situations is massively increased compared to other animals. However, the neural substrates of this scaling remain poorly understood. In this review, we discuss how the expansion and rearrangement of the temporoparietal junction and posterior superior temporal sulcus (TPJ-pSTS) may have played a key role in the growth of human social abilities. Comparing the function and anatomy of the TPJ-pSTS in humans and macaques, which are thought to be separated by 25 million years of evolution, we find that the expansion of this region in humans has shifted the architecture of the dorsal and ventral processing streams. The TPJ-pSTS contains areas related to face-emotion processing, attention, theory of mind operations, and memory; its expansion has allowed for the elaboration and rearrangement of the cortical areas contained within, and potentially the introduction of new cortical areas. Based on the arrangement and the function of these areas in the human, we propose that the TPJ-pSTS is the basis of a third frontoparietal processing stream that underlies the increased social abilities in humans. We then describe a model of how the TPJ-pSTS areas interact as a hub that coordinates the activities of multiple brain networks in the exploration of the complex dynamic social scenes typical of the human social experience. © 2019 Elsevier Ltd

Author Keywords
Default mode network; Dorsal attention network; Face-emotion processing; fMRI; Theory of mind; Ventral attention network

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

“Hypnotic depth and postoperative death: a Bayesian perspective and an Independent Discussion of a clinical trial” (2019) British Journal of Anaesthesia

Hypnotic depth and postoperative death: a Bayesian perspective and an Independent Discussion of a clinical trial
(2019) British Journal of Anaesthesia, .

Vlisides, P.E.^a , Ioannidis, J.P.A.^b , Avidan, M.S.^c

^a University of Michigan Medical School, Department of Anesthesiology, Ann Arbor, MI, United States
^b Stanford University, Meta-Research Innovation Center, Palo Alto, CA, United States
^c Washington University in Saint Louis School of Medicine, Department of Anesthesiology, St. Louis, MO, United States

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