WashU weekly Neuroscience publications

Self-reported sleep disturbance in Crohn’s disease is not confirmed by objective sleep measures
(2020) Scientific Reports, 10 (1), art. no. 1980, . 

Iskandar, H.N.^a , Linan, E.E.^b , Patel, A.^c , Moore, R.^d , Lasanajak, Y.^d , Gyawali, C.P.^b , Sayuk, G.S.^{b e} , Ciorba, M.A.^b

^a Emory University, Department of Medicine, Division of Digestive Diseases, Atlanta, GA, United States
^b Division of Gastroenterology Washington University School of Medicine, St. Louis, MO, United States
^c Duke University, Durham, NC, United States
^d Rollins School of Public Health, Emory University, Atlanta, GA, United States
^e John Cochran Veterans Affairs Medical Center, St. Louis, MO, United States

Abstract
Sleep disturbance and fatigue are commonly reported among patients with Crohn’s disease (CD). In this prospective study, we aimed to define sleep quality in CD patients at various disease activity states and compare to healthy controls using objective and subjective measures. A prospective observational cohort study of CD patients seen at a tertiary academic inflammatory bowel diseases (IBD) clinic was compared to healthy volunteers. CD activity was assessed using the Harvey-Bradshaw Index (HBI). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) and objectively over 1-week using actigraphy (motion-based) and morning urinary melatonin metabolite. 121 subjects (CD patients N = 61; controls N = 60) completed the study. 34 had active CD (HBI > 4). Sleep disturbance was more frequently reported by CD subjects than controls (PSQI: 57% vs. 35%, p = 0.02) and in patients with active CD versus in remission state (PSQI 75.8% vs. 33.3%, p < 0.01; ESS: 45.5% vs. 19%, p = 0.03). Sleep parameters as measured by actigraphy and urine melatonin metabolite did not vary by group. Crohn’s patients report significantly more disturbed sleep than controls. However, poor sleep was not confirmed by objective measures of sleep quality. Excessive daytime sleepiness in CD patients may be driven by factors beyond objectively measured poor sleep. © 2020, The Author(s).

Document Type: Article
Publication Stage: Final
Source: Scopus

Two-stage electro–mechanical coupling of a KV channel in voltage-dependent activation
(2020) Nature Communications, 11 (1), art. no. 676, . 

Hou, P.^a , Kang, P.W.^a , Kongmeneck, A.D.^b , Yang, N.-D.^a , Liu, Y.^a , Shi, J.^a , Xu, X.^c , White, K.M.F.^a , Zaydman, M.A.^d , Kasimova, M.A.^b , Seebohm, G.^e , Zhong, L.^a , Zou, X.^c , Tarek, M.^b , Cui, J.^a

^a Department of Biomedical Engineering, Center for the Investigation of Membrane Excitability Disorders, Cardiac Bioelectricity and Arrhythmia Center, Washington University in St. Louis, St. Louis, MO 63130, United States
^b Université de Lorraine, CNRS, LPCT, Nancy, 53000, France
^c Dalton Cardiovascular Research Center, Department of Physics and Astronomy, Department of Biochemistry, Informatics Institute, University of Missouri – Columbia, Columbia, MO 65211, United States
^d Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, United States
^e Institute for Genetics of Heart Diseases (IfGH), Department of Cardiovascular Medicine, University Hospital Münster, Münster, 48149, Germany

Abstract
In voltage-gated potassium (KV) channels, the voltage-sensing domain (VSD) undergoes sequential activation from the resting state to the intermediate state and activated state to trigger pore opening via electro–mechanical (E–M) coupling. However, the spatial and temporal details underlying E–M coupling remain elusive. Here, utilizing KV7.1’s unique two open states, we report a two-stage E–M coupling mechanism in voltage-dependent gating of KV7.1 as triggered by VSD activations to the intermediate and then activated state. When the S4 segment transitions to the intermediate state, the hand-like C-terminus of the VSD-pore linker (S4-S5L) interacts with the pore in the same subunit. When S4 then proceeds to the fully-activated state, the elbow-like hinge between S4 and S4-S5L engages with the pore of the neighboring subunit to activate conductance. This two-stage hand-and-elbow gating mechanism elucidates distinct tissue-specific modulations, pharmacology, and disease pathogenesis of KV7.1, and likely applies to numerous domain-swapped KV channels. © 2020, The Author(s).

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

Exceptionally low likelihood of Alzheimer’s dementia in APOE2 homozygotes from a 5,000-person neuropathological study
(2020) Nature Communications, 11 (1), art. no. 667, . 

Reiman, E.M.^{a b c d} , Arboleda-Velasquez, J.F.^e , Quiroz, Y.T.^f , Huentelman, M.J.^d , Beach, T.G.^a , Caselli, R.J.^g , Chen, Y.^a , Su, Y.^a , Myers, A.J.^h , Hardy, J.ⁱ , Paul Vonsattel, J.^j , Younkin, S.G.^k , Bennett, D.A.^l , De Jager, P.L.^m , Larson, E.B.ⁿ , Crane, P.K.^o , Keene, C.D.^p , Kamboh, M.I.^q , Kofler, J.K.^r , Duque, L.^s , Gilbert, J.R.^t , Gwirtsman, H.E.^u , Buxbaum, J.D.^v , Dickson, D.W.^w , Frosch, M.P.^x , Ghetti, B.F.^y , Lunetta, K.L.^z , Wang, L.-S.^aa , Hyman, B.T.^ab , Kukull, W.A.^ac , Foroud, T.^ad , Haines, J.L.^ae , Mayeux, R.P.^af , Pericak-Vance, M.A.^t , Schneider, J.A.^l , Trojanowski, J.Q.^aa , Farrer, L.A.^{z ag ah ai} , Schellenberg, G.D.^aa , Beecham, G.W.^t , Montine, T.J.^aj , Jun, G.R.^ag , Abner, E.^ak , Adams, P.M.^al , Albert, M.S.^am , Albin, R.L.^{an ao ap aq ar as at} , Apostolova, L.G.^{aq ar as at au} , Arnold, S.E.^av , Asthana, S.^{aw ax ay} , Atwood, C.S.^{aw ax ay} , Baldwin, C.T.^ag , Barber, R.C.^az , Barnes, L.L.^{l r} , Barral, S.^af , Becker, J.T.^ba , Beekly, D.^bb , Bigio, E.H.^{bc bd} , Bird, T.D.^{be bf} , Blacker, D.^{e bg} , Boeve, B.F.^bh , Bowen, J.D.^bi , Boxer, A.^bj , Burke, J.R.^bk , Burns, J.M.^bl , Cairns, N.J.^bm , Cantwell, L.B.^aa , Cao, C.^bn , Carlson, C.S.^bo , Carlsson, C.M.^{aw ax ay} , Carney, R.M.^h , Carrasquillo, M.M.^w , Chui, H.C.^bp , Cribbs, D.H.^bq , Crocco, E.A.^h , Cruchaga, C.^br , DeCarli, C.^bs , Dick, M.^bt , Doody, R.S.^bu , Duara, R.^bv , Ertekin-Taner, N.^{k w} , Evans, D.A.^bw , Faber, K.M.^au , Fairchild, T.J.^bx , Fallon, K.B.^by , Fardo, D.W.^bz , Farlow, M.R.^ca , Ferris, S.^cb , Galasko, D.R.^cc , Gearing, M.^{cd ce} , Geschwind, D.H.^cf , Ghisays, V.^a , Goate, A.M.^v , Graff-Radford, N.R.^{k w} , Green, R.C.^cg , Growdon, J.H.^ab , Hakonarson, H.^ch , Hamilton, R.L.^r , Hamilton-Nelson, K.L.^t , Harrell, L.E.^ci , Honig, L.S.^af , Huebinger, R.M.^cj , Hulette, C.M.^ck , Jarvik, G.P.^{cl cm} , Jin, L.-W.^cn , Karydas, A.^bj , Katz, M.J.^co , Kauwe, J.S.K.^cp , Kaye, J.A.^{cq cr} , Kim, R.^cs , Kowall, N.W.^{ah ct} , Kramer, J.H.^cu , Kunkle, B.W.^t , Kuzma, A.P.^aa , LaFerla, F.M.^cv , Lah, J.J.^cw , Leung, Y.Y.^aa , Leverenz, J.B.^cx , Levey, A.I.^cw , Li, G.^{bf cy} , Lieberman, A.P.^cz , Lipton, R.B.^co , Lopez, O.L.^q , Lyketsos, C.G.^da , Malamon, J.^aa , Marson, D.C.^ci , Martin, E.R.^t , Martiniuk, F.^db , Mash, D.C.^s , Masliah, E.^{cc dc} , McCormick, W.C.^o , McCurry, S.M.^dd , McDavid, A.N.^bo , McDonough, S.^de , McKee, A.C.^{ah ct} , Mesulam, M.^{bd df} , Miller, B.L.^bj , Miller, C.A.^dg , Miller, J.W.^cn , Morris, J.C.^{bm dh} , Mukherjee, S.^o , Naj, A.C.^aa , O’Bryant, S.^di , Olichney, J.M.^bs , Parisi, J.E.^dj , Paulson, H.L.^dk , Peskind, E.^cy , Petersen, R.C.^bh , Pierce, A.^bq , Poon, W.W.^bt , Potter, H.^dl , Qu, L.^aa , Quinn, J.F.^{cq cr} , Raj, A.^ar , Raskind, M.^cy , Reisberg, B.^{cb dm} , Reisch, J.S.^dn , Reitz, C.^{af do} , Ringman, J.M.^bp , Roberson, E.D.^ci , Rogaeva, E.^dp , Rosen, H.J.^bj , Rosenberg, R.N.^dq , Royall, D.R.^dr , Sager, M.A.^ax , Sano, M.^v , Saykin, A.J.^{aq ar} , Schneider, L.S.^{bp ds} , Seeley, W.W.^bj , Smith, A.G.^bn , Sonnen, J.A.^p , Spina, S.^y , George-Hyslop, P.S.^{dp dt} , Stern, R.A.^ah , Swerdlow, R.H.^bl , Tanzi, R.E.^ab , Troncoso, J.C.^du , Tsuang, D.W.^{bf cy} , Valladares, O.^aa , Van Deerlin, V.M.^aa , Van Eldik, L.J.^dv , Vardarajan, B.N.^af , Vinters, H.V.^{dw dx} , Weintraub, S.^{bc bd} , Welsh-Bohmer, K.A.^{au bk} , Wilhelmsen, K.C.^dy , Williamson, J.^af , Wingo, T.S.^cw , Woltjer, R.L.^dz , Wright, C.B.^ea , Wu, C.-K.^eb , Yu, C.-E.^o , Yu, L.^l , Zhao, Y.^aa , The Alzheimer’s Disease Genetics Consortium^ec

^a Banner Alzheimer’s Institute and Arizona Alzheimer’s Consortium, 901 E Willetta Street, Phoenix, AZ 85006, United States
^b University of Arizona, 714 E Van Buren Street, Phoenix, AZ 85006, United States
^c Arizona State University, 522 N Central Avenue, Phoenix, AZ 85004, United States
^d Neurogenomics Division, Translational Genomics Research Institute and Arizona Alzheimer’s Consortium, 445 N Fifth Street, Phoenix, AZ 85004, United States
^e Schepens Eye Research Institute of Mass Eye and Ear and the Department of Ophthalmology at Harvard Medical School, 20 Staniford Street, Boston, MA 02114, United States
^f Departments of Psychiatry and Neurology, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, United States
^g Mayo Clinic, 13400 E Shea Boulevard, Scottsdale, AZ 85259, United States
^h Department of Psychiatry and Behavioral Science, University of Miami Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, United States
ⁱ Department of Molecular Neuroscience, UCL, Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom
^j New York Brain Bank and Department of Pathology, New York-Presbyterian Hospital at Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, United States
^k Departments of Neuroscience and Neurology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, United States
^l Departments of Neurological Sciences and Pathology (Neuropathology), and Rush Alzheimer’s Disease Center, Rush University Medical Center, 1725 W Harrison Street, Chicago, IL 60612, United States
^m Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University Medical Center, 710 West 168th Street, New York, NY 10032, United States
ⁿ Kaiser Permanente Washington Health Research Institute, 1730 Minor Avenue, Seattle, WA 98101, United States
^o Department of Medicine, University of Washington, 1959 NE Pacific Street, Seattle, WA 98198, United States
^p Department of Pathology, University of Washington, 1959 NE Pacific Street, Seattle, WA 98198, United States
^q Department of Human Genetics, Alzheimer’s Disease Research Center, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, United States
^r Department of Pathology (Neuropathology), University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, United States
^s Department of Neurology, University of Miami, 1120 NW 14th Street, Miami, FL 33136, United States
^t John P. Hussman Institute for Human Genomics, Department of Human Genetics, and Dr. John T. Macdonald Foundation, University of Miami, 1501 NW 10th Avenue, Miami, FL 33136, United States
^u Department of Psychiatry, Vanderbilt University, 1601 23rd Avenue South, Nashville, TN 37212, United States
^v Departments of Psychiatry, Neuroscience and Genetics and Genomic Sciences, Mount Sinai School of Medicine, 1468 Madison Avenue, New York, NY 10029, United States
^w Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, United States
^x C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, 114 16th Street, Charlestown, MA 02129, United States
^y Department of Pathology and Laboratory Medicine, Indiana University, 340 West 10th Street, Indianapolis, IN 46202, United States
^z Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States
^aa Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, 3400 Spruce Street, Philadelphia, PA 19104, United States
^ab Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, United States
^ac Department of Epidemiology, University of Washington, 1959 NE Pacific Street, Seattle, WA 98195, United States
^ad Department of Medical and Molecular Genetics, Indiana University, 410W 10th Street, Indianapolis, IN 46202, United States
^ae Institute for Computational Biology and Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, United States
^af Taub Institute on Alzheimer’s Disease and the Aging Brain, Gertrude H. Sergievsky Center Department of Neurology, Columbia University, 710 West 168th Street, New York, NY 10032, United States
^ag Biomedical Genetics Section, Department of Medicine, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, United States
^ah Department of Neurology, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, United States
^ai Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, United States
^aj Department of Pathology, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, United States
^ak Department of Epidemiology, College of Public Health, Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
^al Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
^am Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
^an Department of Neurology, University of Michigan, Ann Arbor, MI, United States
^ao Geriatric Research, Education and Clinical Center (GRECC), VA Ann Arbor Healthcare System (VAAAHS), Ann Arbor, MI, United States
^ap Michigan Alzheimer Disease Center, Ann Arbor, MI, United States
^aq Department of Radiology, Indiana University, Indianapolis, IA, United States
^ar Department of Medical and Molecular Genetics, Indiana University, Indianapolis, IA, United States
^as Indian Alzheimer’s Disease Center, Indiana University, Indianapolis, IA, United States
^at Department of Neurology, Indiana University, Indianapolis, IA, United States
^au Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
^av Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
^aw Geriatric Research, Education and Clinical Center (GRECC), University of Wisconsin, Madison, WI, United States
^ax Department of Medicine, University of Wisconsin, Madison, WI, United States
^ay Wisconsin Alzheimer’s Disease Research Center, Madison, WI, United States
^az Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX, United States
^ba Departments of Psychiatry, Neurology, and Psychology, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
^bb National Alzheimer’s Coordinating Center, University of Washington, Seattle, WA, United States
^bc Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^bd Cognitive Neurology and Alzheimer’s Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^be Department of Neurology, University of Washington, Seattle, WA, United States
^bf VA Puget Sound Health Care System/GRECC, Seattle, WA, United States
^bg Department of Epidemiology, Harvard School of Public Health, Boston, MA, United States
^bh Department of Neurology, Mayo Clinic, Rochester, MN, United States
^bi Swedish Medical Center, Seattle, WA, United States
^bj Department of Neurology, University of California San Francisco, San Francisco, CA, United States
^bk Department of Medicine, Duke University, Durham, NC, United States
^bl University of Kansas Alzheimer’s Disease Center, University of Kansas Medical Center, Kansas City, KS, United States
^bm Department of Pathology and Immunology, Washington University, St. Louis, MO, United States
^bn USF Health Byrd Alzheimer’s Institute, University of South Florida, Tampa, FL, United States
^bo Fred Hutchinson Cancer Research Center, Seattle, WA, United States
^bp Department of Neurology, University of Southern California, Los Angeles, CA, United States
^bq Department of Neurology, University of California Irvine, Irvine, CA, United States
^br Department of Psychiatry and Hope Center Program on Protein Aggregation and Neurodegeneration, Washington University School of Medicine, St. Louis, MO, United States
^bs Department of Neurology, University of California Davis, Sacramento, CA, United States
^bt Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA, United States
^bu Alzheimer’s Disease and Memory Disorders Center, Baylor College of Medicine, Houston, TX, United States
^bv Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, United States
^bw Department of Internal Medicine, Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, IL, United States
^bx Office of Strategy and Measurement, University of North Texas Health Science Center, Fort Worth, TX, United States
^by Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, United States
^bz Department of Biostatistics, Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, United States
^ca Department of Neurology, Indiana University, Indianapolis, IN, United States
^cb Department of Psychiatry, New York University, New York, NY, United States
^cc Department of Neurosciences, University of California San Diego, La Jolla, CA, United States
^cd Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
^ce Emory Alzheimer’s Disease Center, Emory University, Atlanta, GA, United States
^cf Neurogenetics Program, University of California Los Angeles, Los Angeles, CA, United States
^cg Department of Medicine and Partners Center for Personalized Genetic Medicine, Division of Genetics, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States
^ch Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^ci Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
^cj Department of Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States
^ck Department of Pathology, Duke University, Durham, NC, United States
^cl Department of Genome Sciences, University of Washington, Seattle, WA, United States
^cm Department of Medicine (Medical Genetics), University of Washington, Seattle, WA, United States
^cn Department of Pathology and Laboratory Medicine, University of California Davis, Sacramento, CA, United States
^co Department of Neurology, Albert Einstein College of Medicine, New York, NY, United States
^cp Department of Biology, Brigham Young University, Provo, UT, United States
^cq Department of Neurology, Oregon Health & Science University, Portland, OR, United States
^cr Department of Neurology, Portland Veterans Affairs Medical Center, Portland, OR, United States
^cs Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, CA, United States
^ct Department of Pathology, Boston University, Boston, MA, United States
^cu Department of Neuropsychology, University of California San Francisco, San Francisco, CA, United States
^cv Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, United States
^cw Department of Neurology, Emory University, Atlanta, GA, United States
^cx Cleveland Clinic Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, United States
^cy Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, United States
^cz Department of Pathology, University of Michigan, Ann Arbor, MI, United States
^da Department of Psychiatry, Johns Hopkins University, Baltimore, MD, United States
^db Department of Medicine – Pulmonary, New York University, New York, NY, United States
^dc Department of Pathology, University of California San Diego, La Jolla, CA, United States
^dd School of Nursing Northwest Research Group on Aging, University of Washington, Seattle, WA, United States
^de PharmaTherapeutics Clinical Research, Pfizer Worldwide Research and Development, Cambridge, MA, United States
^df Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
^dg Department of Pathology, University of Southern California, Los Angeles, CA, United States
^dh Department of Neurology, Washington University, St. Louis, MO, United States
^di Internal Medicine, Division of Geriatrics, University of North Texas Health Science Center, Fort Worth, TX, United States
^dj Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
^dk Michigan Alzheimer’s Disease Center, Department of Neurology, University of Michigan, Ann Arbor, MI, United States
^dl Department of Neurology, University of Colorado School of Medicine, Aurora, CO, United States
^dm Alzheimer’s Disease Center, New York University, New York, NY, United States
^dn Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
^do Department of Epidemiology, Columbia University, New York, NY, United States
^dp Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, Toronto, ON, Canada
^dq Department of Neurology, University of Texas Southwestern, Dallas, TX, United States
^dr Departments of Psychiatry, Medicine, Family & Community Medicine, South Texas Veterans Health Administration Geriatric Research Education & Clinical Center (GRECC), UT Health Science Center at San Antonio, San Antonio, TX, United States
^ds Department of Psychiatry, University of Southern California, Los Angeles, CA, United States
^dt Cambridge Institute for Medical Research and Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
^du Department of Pathology, Johns Hopkins University, Baltimore, MD, United States
^dv Sanders-Brown Center on Aging, Department of Anatomy and Neurobiology, University of Kentucky, Lexington, KY, United States
^dw Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States
^dx Department of Pathology and Laboratory Medicine, University of California Los Angeles, Los Angeles, CA, United States
^dy Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, United States
^dz Department of Pathology, Oregon Health and Science University, Portland, OR, United States
^ea Department of Neurology, Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of Miami, Miami, FL, United States
^eb Departments of Neurology, Pharmacology and Neuroscience, Texas Tech University Health Science Center, Lubbock, TX, United States

Abstract
Each additional copy of the apolipoprotein E4 (APOE4) allele is associated with a higher risk of Alzheimer’s dementia, while the APOE2 allele is associated with a lower risk of Alzheimer’s dementia, it is not yet known whether APOE2 homozygotes have a particularly low risk. We generated Alzheimer’s dementia odds ratios and other findings in more than 5,000 clinically characterized and neuropathologically characterized Alzheimer’s dementia cases and controls. APOE2/2 was associated with a low Alzheimer’s dementia odds ratios compared to APOE2/3 and 3/3, and an exceptionally low odds ratio compared to APOE4/4, and the impact of APOE2 and APOE4 gene dose was significantly greater in the neuropathologically confirmed group than in more than 24,000 neuropathologically unconfirmed cases and controls. Finding and targeting the factors by which APOE and its variants influence Alzheimer’s disease could have a major impact on the understanding, treatment and prevention of the disease. © 2020, The Author(s).

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

Tracking regional brain growth up to age 13 in children born term and very preterm
(2020) Nature Communications, 11 (1), art. no. 696, . 

Thompson, D.K.^{a b c d} , Matthews, L.G.^e , Alexander, B.^{a b} , Lee, K.J.^{a c f} , Kelly, C.E.^{a b} , Adamson, C.L.^b , Hunt, R.W.^{a c g} , Cheong, J.L.Y.^{a h i} , Spencer-Smith, M.^{a j} , Neil, J.J.^k , Seal, M.L.^{b c} , Inder, T.E.^{a e} , Doyle, L.W.^{a c h i} , Anderson, P.J.^{a j}

^a Victorian Infant Brain Study (VIBeS), Murdoch Children’s Research Institute, 50 Flemington Road, Parkville, VIC 3052, Australia
^b Developmental Imaging, Murdoch Children’s Research Institute, 50 Flemington Road, Parkville, VIC 3052, Australia
^c Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
^d Florey Institute of Neuroscience and Mental Health, 30 Royal Parade, Parkville, VIC 3052, Australia
^e Department of Pediatric Newborn Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115, United States
^f Clinical Epidemiology and Biostatistics Unit, Murdoch Children’s Research Institute, 50 Flemington Road, Parkville, VIC 3052, Australia
^g Neonatal Medicine, Royal Children’s Hospital, 50 Flemington Road, Parkville, VIC 3052, Australia
^h Royal Women’s Hospital, 20 Flemington Road, Parkville, VIC 3052, Australia
ⁱ Department of Obstetrics and Gynaecology, University of Melbourne, Grattan Street, Parkville, VIC 3010, Australia
^j Turner Institute for Brain and Mental Health, Monash University, Wellington Road, Clayton, VIC 3800, Australia
^k Department of Pediatric Neurology, Washington University School of Medicine, 660 South Euclid Avenue, St. Louis, MO 63110, United States

Abstract
Serial regional brain growth from the newborn period to adolescence has not been described. Here, we measured regional brain growth in 216 very preterm (VP) and 45 full-term (FT) children. Brain MRI was performed at term-equivalent age, 7 and 13 years in 82 regions. Brain volumes increased between term-equivalent and 7 years, with faster growth in the FT than VP group. Perinatal brain abnormality was associated with less increase in brain volume between term-equivalent and 7 years in the VP group. Between 7 and 13 years, volumes were relatively stable, with some subcortical and cortical regions increasing while others reduced. Notably, VP infants continued to lag, with overall brain size generally less than that of FT peers at 13 years. Parieto–frontal growth, mainly between 7 and 13 years in FT children, was associated with higher intelligence at 13 years. This study improves understanding of typical and atypical regional brain growth. © 2020, The Author(s).

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

Validation study of microRNAs previously associated with antidepressant response in older adults treated for late-life depression with venlafaxine
(2020) Progress in Neuro-Psychopharmacology and Biological Psychiatry, 100, art. no. 109867, . 

Marshe, V.S.^{a b} , Islam, F.^{b c} , Maciukiewicz, M.^{b l} , Fiori, L.M.^d , Yerko, V.^d , Yang, J.^d , Turecki, G.^d , Foster, J.A.^{e f} , Kennedy, S.H.^{a e g h} , Blumberger, D.M.^{a b g} , Karp, J.F.^{i j} , Kennedy, J.L.^{a b g} , Mulsant, B.H.^{a b g} , Reynolds, C.F., IIIⁱ , Lenze, E.J.^k , Müller, D.J.^{a b c g}

^a Institute of Medical Science, University of Toronto, Toronto, ON, Canada
^b Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
^c Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
^d McGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Verdun, Quebec, Canada
^e Department of Psychiatry, University Health Network, Toronto, ON, Canada
^f Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, ON, Canada
^g Department of Psychiatry, University of Toronto, Toronto, ON, Canada
^h Keenan Research Centre, St. Michael’s Hospital, Toronto, ON, Canada
ⁱ Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States
^j VA Pittsburgh Health System, Geriatric Research Education and Clinical Center, Pittsburgh, PA, United States
^k Healthy Mind Lab, Department of Psychiatry, Washington University, St. Louis, MO, United States
^l Center of Experimental Rheumatology, Department of Rheumatology, University Hospital Zurich, Switzerland

Abstract
Background: MicroRNAs (miRNAs) are small 22 nucleotides long, non-coding RNAs that are potential biomarkers for antidepressant treatment response. We aimed to replicate previous associations of miRNAs with antidepressant treatment response in a sample of older adults diagnosed with late-life depression. Methods: Our sample included 184 older adults diagnosed with moderately severe depression that received open-label venlafaxine (up to 300 mg/day) for approximately 12 weeks. We quantified miRNA expression levels at baseline and week 12 for miRNAs miR-1202, miR-135a-5p, miR-16-5p, miR-146a-5p, miR-146b-5p, miR-425-3p, and miR-24-3p to explore their association with remission status, response trajectories, and time-to-remission. Results: At T0 and T12, there were no differences in miRNA expression levels between remitters and non-remitters. However, remitters showed a trend toward higher baseline miR-135a-5p (Median = 11.3 [9.9, 15.7], p = .083). Prior to correction, baseline miR-135a-5p expression levels showed an association with remission status (OR = 1.8 [1.0, 3.3], p = .037). Individuals with higher baseline miR-135a-5p showed better response trajectories (F = 4.5, FDR-corrected p = 4.4 × 10−4), particularly at weeks 10 and 12 (p &lt;. 05). In addition, individuals with higher miR-135a-5p expression reached remission faster than those with lower expression (HR = 0.6 [0.4, 0.9], FDR-corrected p = .055). Limitations: Although the sample size was relatively modest, our findings are consistent with the literature suggesting that higher miR-135a-5p levels may be associated with better antidepressant treatment response. Conclusions: However, the miRNA signature of antidepressant response in older adults may be different as compared to younger adults. © 2020

Author Keywords
Late-life depression;  miRNA;  Pharmacogenetics;  Treatment response;  Venlafaxine

Document Type: Article
Publication Stage: Final
Source: Scopus

A review of emerging therapeutic potential of psychedelic drugs in the treatment of psychiatric illnesses
(2020) Journal of the Neurological Sciences, 411, art. no. 116715, . 

Chi, T., Gold, J.A.

Department of Psychiatry, Washington University School of Medicine, United States

Abstract
Though there was initial interest in the use of psychedelic drugs for psychiatric treatment, bad outcomes and subsequent passage of the Substance Act of 1970, which placed psychedelic drugs in the Schedule I category, significantly limited potential progress. More recently, however, there has been renewal in interest and promise of psychedelic research. The purpose of this review is to highlight contemporary human studies on the use of select psychedelic drugs, such as psilocybin, LSD, MDMA and ayahuasca, in the treatment of various psychiatric illnesses, including but not limited to treatment-resistant depression, post-traumatic stress disorder, end-of-life anxiety, and substance use disorders. The safety and efficacy as reported from human and animal studies will also be discussed. Accumulated research to date has suggested the potential for psychedelics to emerge as breakthrough therapies for psychiatric conditions refractory to conventional treatments. However, given the unique history and high potential for misuse with popular distribution, special care and considerations must be undertaken to safeguard their use as viable medical treatments rather than drugs of abuse. © 2020 Elsevier B.V.

Author Keywords
Emergent psychiatric therapy;  LSD;  MDMA;  Psilocybin;  Psychedelic drug research;  Safety

Document Type: Review
Publication Stage: Final
Source: Scopus

Traumatic brain injury and methamphetamine: A double-hit neurological insult
(2020) Journal of the Neurological Sciences, 411, art. no. 116711, . 

El Hayek, S.^a , Allouch, F.^b , Razafsha, M.^c , Talih, F.^a , Gold, M.S.^d , Wang, K.K.^e , Kobeissy, F.^{e f}

^a Department of Psychiatry, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
^b School of Public Health, University of California, Berkeley, United States
^c Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
^d Department of Psychiatry, Washington University School of Medicine, St. Louis, United States
^e Program for Neurotrauma, Neuroproteomics, and Biomarkers Research, Department of Emergency Medicine, University of Florida, Gainesville, FL, United States
^f Department of Biochemistry and Molecular Genetics, Faculty of Medicine, American University of Beirut, Beirut, Lebanon

Abstract
Traumatic brain injury (TBI) is one of the leading causes of morbidity and mortality in the world. TBI causes permanent physical, cognitive, social, and functional impairments. Substance use and intoxication are established risk factors for TBI. Data are emerging that also suggest that brain injury might be a risk factor for substance use. Methamphetamine (METH), a highly addictive psychostimulant, has not been thoroughly investigated in the context of TBI exposure. The interplay between the two has been of interest as their pathophysiology intertwines on many levels. However, the knowledge concerning the association between TBI-METH and the impact of chronic METH use on short and long-term TBI outcomes is equivocal at best. In this review of the literature, we postulate that, when combined, these two conditions synergize to result in more significant neuronal damage. As such, chronic exposure to METH before brain trauma may accentuate the pathophysiological signs of injury, worsening TBI outcomes. Similarly, individuals with a history of TBI would be more vulnerable to METH misuse and harmful effects. We, therefore, review the most recent preclinical and clinical data tackling the significant overlap in the pathophysiology of TBI and METH at three levels: the structural level, the biochemical level, and the cellular level. We also highlight some controversial results of studies investigating the outcomes of the interaction between TBI and METH. © 2020 Elsevier B.V.

Author Keywords
Addiction;  Interplay;  Methamphetamine;  Neurological outcomes;  Traumatic brain injury

Document Type: Review
Publication Stage: Final
Source: Scopus

Effect of Positioning on Intracranial Pressure: Response
(2020) Journal of Neuro-Ophthalmology : The Official Journal of the North American Neuro-Ophthalmology Society, 40 (1), pp. 138-140. 

McClelland, C.M., Van Stavern, G.P., Lee, A.G., Lueck, C.J.

Department of Ophthalmology and Visual Neurosciences, University of Minnesota, Minneapolis, Minnesota Department of Ophthalmology and Visual Sciences, Washington University School of Medicine, Saint Louis, Missouri Department of Ophthalmology, Houston Methodist Hospital, Blanton Eye Institute, Houston, Texas Department of Neurology, Canberra Hospital, Garran, Australia

Document Type: Article
Publication Stage: Final
Source: Scopus

Currently Unstable: Daily Ups and Downs in E-I Balance
(2020) Neuron, 105 (4), pp. 589-591. 

Brunwasser, S.J.^a , Hengen, K.B.^b

^a Washington University Program in Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
^b Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, United States

Abstract
Balance between excitation and inhibition (E-I balance) in neural circuits is believed to be tightly regulated. To the contrary, in this issue of Neuron, Bridi et al. (2020) reveal that inverse oscillations of synaptic inhibition and excitation lead to peaks and valleys in E-I balance across the 24 h day. © 2020 Elsevier Inc.

Balance between excitation and inhibition (E-I balance) in neural circuits is believed to be tightly regulated. To the contrary, in this issue of Neuron, Bridi et al. (2020) reveal that inverse oscillations of synaptic inhibition and excitation lead to peaks and valleys in E-I balance across the 24 h day. © 2020 Elsevier Inc.

Document Type: Article
Publication Stage: Final
Source: Scopus

Why Lungs Keep Time: Circadian Rhythms and Lung Immunity
(2020) Annual Review of Physiology, 82, pp. 391-412. 

Nosal, C.^a , Ehlers, A.^a , Haspel, J.A.^b

^a Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, Missouri 63110, USA; email: jhaspel@wustl.edu
^b Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, Missouri 63110, USA; email:

Abstract
Circadian rhythms are daily cycles in biological function that are ubiquitous in nature. Understood as a means for organisms to anticipate daily environmental changes, circadian rhythms are also important for orchestrating complex biological processes such as immunity. Nowhere is this more evident than in the respiratory system, where circadian rhythms in inflammatory lung disease have been appreciated since ancient times. In this focused review we examine how emerging research on circadian rhythms is being applied to the study of fundamental lung biology and respiratory disease. We begin with a general introduction to circadian rhythms and the molecular circadian clock that underpins them. We then focus on emerging data tying circadian clock function to immunologic activities within the respiratory system. We conclude by considering outstanding questions about biological timing in the lung and how a better command of chronobiology could inform our understanding of complex lung diseases.

Author Keywords
circadian;  clock;  inflammation;  lung;  pulmonary;  rhythm

Document Type: Article
Publication Stage: Final
Source: Scopus

Valence and patterning of aromatic residues determine the phase behavior of prion-like domains
(2020) Science, 367 (6478), pp. 694-699. 

Martin, E.W.^a , Holehouse, A.S.^{b c} , Peran, I.^a , Farag, M.^{b c} , Incicco, J.J.^d , Bremer, A.^a , Grace, C.R.^a , Soranno, A.^{c d} , Pappu, R.V.^{b c} , Mittag, T.^a

^a Department of Structural Biology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, United States
^b Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, United States
^c Center for Science and Engineering of Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO 63130, United States
^d Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, United States

Abstract
Prion-like domains (PLDs) can drive liquid-liquid phase separation (LLPS) in cells. Using an integrative biophysical approach that includes nuclear magnetic resonance spectroscopy, small-angle x-ray scattering, and multiscale simulations, we have uncovered sequence features that determine the overall phase behavior of PLDs. We show that the numbers (valence) of aromatic residues in PLDs determine the extent of temperature-dependent compaction of individual molecules in dilute solutions. The valence of aromatic residues also determines full binodals that quantify concentrations of PLDs within coexisting dilute and dense phases as a function of temperature. We also show that uniform patterning of aromatic residues is a sequence feature that promotes LLPS while inhibiting aggregation. Our findings lead to the development of a numerical stickers-and-spacers model that enables predictions of full binodals of PLDs from their sequences. © 2020 American Association for the Advancement of Science. All rights reserved.

Document Type: Article
Publication Stage: Final
Source: Scopus

2018 Langley Award for Basic Research on Nicotine and Tobacco: Bringing Precision Medicine to Smoking Cessation
(2020) Nicotine & Tobacco Research : Official Journal of the Society for Research on Nicotine and Tobacco, 22 (2), pp. 147-151. 

Bierut, L.J.

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

Abstract
INTRODUCTION: Large segments of the world population use combustible cigarettes, and our society pays a high price for smoking, through increased healthcare expenditures, morbidity and mortality. The development of combustible cigarette smoking requires the initiation of smoking and a subsequent chain of behavioral transitions from experimental use, to established regular use, to the conversion to addiction. Each transition is influenced by both environmental and genetic factors, and our increasing knowledge about genetic contributions to smoking behaviors opens new potential interventions. METHODS: This review describes the journey from genetic discovery to the potential implementation of genetic knowledge for the treatment of tobacco use disorder. RESULTS AND CONCLUSIONS: The field of genetics applied to smoking behaviors has rapidly progressed with the identification of highly validated genetic variants that are associated with different smoking behaviors. The large scale implementation of this genetic knowledge to accelerate smoking cessation represents an important clinical challenge in precision medicine. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.

Document Type: Article
Publication Stage: Final
Source: Scopus

Prevalence and Family-Related Factors Associated With Suicidal Ideation, Suicide Attempts, and Self-injury in Children Aged 9 to 10 Years
(2020) JAMA Network Open, 3 (2), p. e1920956. 

DeVille, D.C.^{a b} , Whalen, D.^{c d e} , Breslin, F.J.^a , Morris, A.S.^{a f} , Khalsa, S.S.^{a g} , Paulus, M.P.^{a g} , Barch, D.M.^{c d e}

^a Laureate Institute for Brain Research, Tulsa, OK, United States
^b Department of Psychology, University of Tulsa, Tulsa, OK, United States
^c Department of Psychological & Brain Sciences, Washington University in St Louis, St Louis, MO, United States
^d Department of Psychiatry, Washington University in St Louis, St Louis, MO, United States
^e Department of Radiology, Washington University in St Louis, St Louis, MO, United States
^f Department of Human Development and Family Science, Oklahoma State University, Tulsa, United States
^g Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States

Abstract
Importance: Although suicide is a leading cause of death for children in the United States, and the rate of suicide in childhood has steadily increased, little is known about suicidal ideation and behaviors in children. Objective: To assess the overall prevalence of suicidal ideation, suicide attempts, and nonsuicidal self-injury, as well as family-related factors associated with suicidality and self-injury among preadolescent children. Design, Setting, and Participants: Cross-sectional study using retrospective analysis of the baseline sample from the Adolescent Brain Cognitive Development (ABCD) study. This multicenter investigation used an epidemiologically informed school-based recruitment strategy, with consideration of the demographic composition of the 21 ABCD sites and the United States as a whole. The sample included children aged 9 to 10 years and their caregivers. Main Outcomes and Measures: Lifetime suicidal ideation, suicide attempts, and nonsuicidal self-injury as reported by children and their caregivers in a computerized version of the Kiddie Schedule for Affective Disorders and Schizophrenia. Results: A total of 11 814 children aged 9 to 10 years (47.8% girls; 52.0% white) and their caregivers were included. After poststratification sociodemographic weighting, the approximate prevalence rates were 6.4% (95% CI, 5.7%-7.3%) for lifetime history of passive suicidal ideation; 4.4% (95% CI, 3.9%-5.0%) for nonspecific active suicidal ideation; 2.4% (95% CI, 2.1%-2.7%) for active ideation with method, intent, or plan; 1.3% (95% CI, 1.0%-1.6%) for suicide attempts; and 9.1% (95% CI, 8.1-10.3) for nonsuicidal self-injury. After covarying by sex, family history, internalizing and externalizing problems, and relevant psychosocial variables, high family conflict was significantly associated with suicidal ideation (odds ratio [OR], 1.12; 95% CI, 1.07-1.16) and nonsuicidal self-injury (OR, 1.09; 95% CI, 1.05-1.14), and low parental monitoring was significantly associated with ideation (OR, 0.97; 95% CI, 0.95-0.98), attempts (OR, 0.91; 95% CI, 0.86-0.97), and nonsuicidal self-injury (OR, 0.95; 95% CI, 0.93-0.98); these findings were consistent after internal replication. Most of children’s reports of suicidality and self-injury were either unknown or not reported by their caregivers. Conclusions and Relevance: This study demonstrates the association of family factors, including high family conflict and low parental monitoring, with suicidality and self-injury in children. Future research and ongoing prevention and intervention efforts may benefit from the examination of family factors.

Document Type: Article
Publication Stage: Final
Source: Scopus

Neuronal Activity in the Primate Amygdala during Economic Choice
(2020) The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 40 (6), pp. 1286-1301. 

Jezzini, A.^a , Padoa-Schioppa, C.^{b c d}

^a Departments of Neuroscience
^b Departments of Neuroscience
^c Economics
^d Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110, United States

Abstract
Multiple lines of evidence link economic choices to the orbitofrontal cortex (OFC), but other brain regions may contribute to the computation and comparison of economic values. A particularly strong candidate is the basolateral amygdala (BLA). Amygdala lesions impair performance in reinforcer devaluation tasks, suggesting that the BLA contributes to value computation. Furthermore, previous studies of the BLA have found neuronal activity consistent with a value representation. Here, we recorded from the BLA of two male rhesus macaques choosing between different juices. Offered quantities varied from trial to trial, and relative values were inferred from choices. Approximately one-third of BLA cells were task-related. Our analyses revealed the presence of three groups of neurons encoding variables offer value, chosen value, and chosen juice In this respect, the BLA appeared similar to the OFC. The two areas differed for the proportion of neurons in each group, as the fraction of chosen value cells was significantly higher in the BLA. Importantly, the activity of these neurons reflected the subjective nature of value. Firing rates in the BLA were sustained throughout the trial and maximal after juice delivery. In contrast, firing rates in the OFC were phasic and maximal shortly after offer presentation. Our results suggest that the BLA supports economic choice and reward expectation.SIGNIFICANCE STATEMENT Economic choices rely on the orbitofrontal cortex (OFC), but other brain regions may contribute to this behavior. A strong candidate is the basolateral amygdala (BLA). Previous results are consistent with a neuronal representation of value, but the role of the BLA in economic decisions remains unclear. Here, we recorded from monkeys choosing between juices. Neurons in the BLA encoded three decision variables: offer value, chosen value, and chosen juice These variables were also identified in the OFC. The two areas differed in the proportion of cells encoding each variable and in the activation timing. In the OFC, firing rates peaked shortly after offer presentation; in the BLA, firing rates were sustained and peaked after juice delivery. These results suggest that the BLA supports choices and reward expectation. Copyright © 2020 the authors.

Author Keywords
decision making;  neuroeconomics;  neurophysiology;  subjective value

Document Type: Article
Publication Stage: Final
Source: Scopus

Quantitative trait variation in ASD probands and toddler sibling outcomes at 24 months
(2020) Journal of Neurodevelopmental Disorders, 12 (1), p. 5. 

Girault, J.B.^a , Swanson, M.R.^b , Meera, S.S.^{a c} , Grzadzinski, R.L.^a , Shen, M.D.^{a d} , Burrows, C.A.^e , Wolff, J.J.^f , Pandey, J.^g , John, T.S.^h , Estes, A.^h , Zwaigenbaum, L.ⁱ , Botteron, K.N.^j , Hazlett, H.C.^{a d} , Dager, S.R.^k , Schultz, R.T.^g , Constantino, J.N.^l , Piven, J.^{a d} , IBIS Network^m

^a Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Campus Box 3376 ,Chapel Hill27599, United States
^b Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, TX, Richardson, United States
^c National Institute of Mental Health and Neurosciences, Bangalore, India
^d Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, United States
^e Department of Pediatrics, University of Minnesota, MN, Minneapolis, United States
^f Department of Educational Psychology, University of Minnesota, MN, Minneapolis, United States
^g Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
^h Department of Speech and Hearing Science, University of Washington, Seattle, WA, USA
ⁱ Department of Pediatrics, University of Alberta, AB, Edmonton, Canada
^j Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
^k Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
^l Division of Child Psychiatry, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA

Abstract
BACKGROUND: Younger siblings of children with autism spectrum disorder (ASD) are at increased likelihood of receiving an ASD diagnosis and exhibiting other developmental concerns. It is unknown how quantitative variation in ASD traits and broader developmental domains in older siblings with ASD (probands) may inform outcomes in their younger siblings. METHODS: Participants included 385 pairs of toddler siblings and probands from the Infant Brain Imaging Study. ASD probands (mean age 5.5 years, range 1.7 to 15.5 years) were phenotyped using the Autism Diagnostic Interview-Revised (ADI-R), the Social Communication Questionnaire (SCQ), and the Vineland Adaptive Behavior Scales, Second Edition (VABS-II). Siblings were assessed using the ADI-R, VABS-II, Mullen Scales of Early Learning (MSEL), and Autism Diagnostic Observation Schedule (ADOS) and received a clinical best estimate diagnosis at 24 months using DSM-IV-TR criteria (n = 89 concordant for ASD; n = 296 discordant). We addressed two aims: (1) to determine whether proband characteristics are predictive of recurrence in siblings and (2) to assess associations between proband traits and sibling dimensional outcomes at 24 months. RESULTS: Regarding recurrence risk, proband SCQ scores were found to significantly predict sibling 24-month diagnostic outcome (OR for a 1-point increase in SCQ = 1.06; 95% CI = 1.01, 1.12). Regarding quantitative trait associations, we found no significant correlations in ASD traits among proband-sibling pairs. However, quantitative variation in proband adaptive behavior, communication, and expressive and receptive language was significantly associated with sibling outcomes in the same domains; proband scores explained 9-18% of the variation in cognition and behavior in siblings with ASD. Receptive language was particularly strongly associated in concordant pairs (ICC = 0.50, p < 0.001). CONCLUSIONS: Proband ASD symptomology, indexed by the SCQ, is a predictor of familial ASD recurrence risk. While quantitative variation in social communication and restricted and repetitive behavior were not associated among sibling pairs, standardized ratings of proband language and communication explained significant variation in the same domains in the sibling at 24 months, especially among toddlers with an ASD diagnosis. These data suggest that proband characteristics can alert clinicians to areas of developmental concern for young children with familial risk for ASD.

Author Keywords
Autism;  Communication;  Development;  Family study;  Infant sibling;  Language

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

APOE genotype regulates pathology and disease progression in synucleinopathy
(2020) Science Translational Medicine, 12 (529), . 

Davis, A.A.^{a b} , Inman, C.E.^{b c} , Wargel, Z.M.^{b c} , Dube, U.^{c d} , Freeberg, B.M.^{b c} , Galluppi, A.^{b c} , Haines, J.N.^{b c} , Dhavale, D.D.^{b c} , Miller, R.^{b c} , Choudhury, F.A.^{b c} , Sullivan, P.M.^e , Cruchaga, C.^{c d} , Perlmutter, J.S.^{b c f} , Ulrich, J.D.^{b c} , Benitez, B.A.^{c d} , Kotzbauer, P.T.^{b c} , Holtzman, D.M.^{b g h}

^a Hope Center for Neurologic Disease, Washington University, St. Louis, MO 63110, USA. holtzman@wustl.edu
^b Department of Neurology, Washington University, St. Louis, MO 63110, USA
^c Hope Center for Neurologic Disease, Washington University, St. Louis, MO 63110, USA
^d Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
^e Department of Medicine, Duke University Medical Center, Durham VAMC and Geriatric Research Clinical Center, Durham, NC 27705, United States
^f Departments of Neuroscience and Radiology, Programs in Physical and Occupational Therapy, Washington University, St. Louis, MO 63110, USA
^g Hope Center for Neurologic Disease, Washington University, St. Louis, MO 63110, USA. albert.a.davis@wustl.edu holtzman@wustl.edu
^h Knight Alzheimer’s Disease Research Center, Washington University, St. Louis, MO 63110, USA

Abstract
Apolipoprotein E (APOE) ε4 genotype is associated with increased risk of dementia in Parkinson’s disease (PD), but the mechanism is not clear, because patients often have a mixture of α-synuclein (αSyn), amyloid-β (Aβ), and tau pathologies. APOE ε4 exacerbates brain Aβ pathology, as well as tau pathology, but it is not clear whether APOE genotype independently regulates αSyn pathology. In this study, we generated A53T αSyn transgenic mice (A53T) on Apoe knockout (A53T/EKO) or human APOE knockin backgrounds (A53T/E2, E3, and E4). At 12 months of age, A53T/E4 mice accumulated higher amounts of brainstem detergent-insoluble phosphorylated αSyn compared to A53T/EKO and A53T/E3; detergent-insoluble αSyn in A53T/E2 mice was undetectable. By immunohistochemistry, A53T/E4 mice displayed a higher burden of phosphorylated αSyn and reactive gliosis compared to A53T/E2 mice. A53T/E2 mice exhibited increased survival and improved motor performance compared to other APOE genotypes. In a complementary model of αSyn spreading, striatal injection of αSyn preformed fibrils induced greater accumulation of αSyn pathology in the substantia nigra of A53T/E4 mice compared to A53T/E2 and A53T/EKO mice. In two separate cohorts of human patients with PD, APOE ε4/ε4 individuals showed the fastest rate of cognitive decline over time. Our results demonstrate that APOE genotype directly regulates αSyn pathology independent of its established effects on Aβ and tau, corroborate the finding that APOE ε4 exacerbates pathology, and suggest that APOE ε2 may protect against αSyn aggregation and neurodegeneration in synucleinopathies. Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Document Type: Article
Publication Stage: Final
Source: Scopus

Cognitive trajectory in mild cognitive impairment due to primary age-related tauopathy
(2020) Brain: A Journal of Neurology, 143 (2), pp. 611-621. 

Teylan, M.^a , Mock, C.^a , Gauthreaux, K.^a , Chen, Y.-C.^a , Chan, K.C.G.^a , Hassenstab, J.^{b c} , Besser, L.M.^d , Kukull, W.A.^a , Crary, J.F.^e

^a National Alzheimer’s Coordinating Center, Department of Epidemiology, University of Washington, Seattle, WA, USA
^b Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
^c Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
^d School of Urban and Regional Planning, Florida Atlantic University, FL, Boca Raton, United States
^e Department of Pathology, Nash Family Department of Neuroscience, Friedman Brain Institute, Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, Neuropathology Brain Bank and Research CoRE, NY, NY, United States

Abstract
Primary age-related tauopathy is increasingly recognized as a separate neuropathological entity different from Alzheimer’s disease. Both share the neuropathological features of tau aggregates and neuronal loss in the temporal lobe, but primary age-related tauopathy lacks the requisite amyloid plaques central to Alzheimer’s disease. While both have similar clinical presentations, individuals with symptomatic primary age-related tauopathy are commonly of more advanced ages with milder cognitive dysfunction. Direct comparison of the neuropsychological trajectories of primary age-related tauopathy and Alzheimer’s disease has not been thoroughly evaluated and thus, our objective was to determine how cognitive decline differs longitudinally between these two conditions after the onset of clinical symptoms. Data were obtained from the National Alzheimer’s Coordinating Center on participants with mild cognitive impairment at baseline and either no neuritic plaques (i.e. primary age-related tauopathy) or moderate to frequent neuritic plaques (i.e. Alzheimer neuropathological change) at subsequent autopsy. For patients with Alzheimer’s disease and primary age-related tauopathy, we compared rates of decline in the sum of boxes score from the CDR® Dementia Staging Instrument and in five cognitive domains (episodic memory, attention/working memory, executive function, language/semantic memory, and global composite) using z-scores for neuropsychological tests that were calculated based on scores for participants with normal cognition. The differences in rates of change were tested using linear mixed-effects models accounting for clinical centre clustering and repeated measures by individual. Models were adjusted for sex, age, education, baseline test score, Braak stage, apolipoprotein ε4 (APOE ε4) carrier status, family history of cognitive impairment, and history of stroke, hypertension, or diabetes. We identified 578 participants with a global CDR of 0.5 (i.e. mild cognitive impairment) at baseline, 126 with primary age-related tauopathy and 452 with Alzheimer’s disease. Examining the difference in rates of change in CDR sum of boxes and in all domain scores, participants with Alzheimer’s disease had a significantly steeper decline after becoming clinically symptomatic than those with primary age-related tauopathy. This remained true after adjusting for covariates. The results of this analysis corroborate previous studies showing that primary age-related tauopathy has slower cognitive decline than Alzheimer’s disease across multiple neuropsychological domains, thus adding to the understanding of the neuropsychological burden in primary age-related tauopathy. The study provides further evidence to support the hypothesis that primary age-related tauopathy has distinct neuropathological and clinical features compared to Alzheimer’s disease. © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Author Keywords
Alzheimer’s disease;  cognitive decline;  neuropathology;  neuropsychology;  primary age-related tauopathy

Document Type: Article
Publication Stage: Final
Source: Scopus

Use of Neuroimaging to Inform Optimal Neurocognitive Criteria for Detecting HIV-Associated Brain Abnormalities
(2020) Journal of the International Neuropsychological Society : JINS, 26 (2), pp. 147-162. 

Campbell, L.M.^{a b} , Fennema-Notestine, C.^{b c} , Saloner, R.^{a b} , Hussain, M.^{a b} , Chen, A.^b , Franklin, D.^b , Umlauf, A.^b , Ellis, R.J.^b , Collier, A.C.^d , Marra, C.M.^e , Clifford, D.B.^f , Gelman, B.B.^g , Sacktor, N.^h , Morgello, S.ⁱ , McCutchan, J.A.^j , Letendre, S.^{b j} , Grant, I.^b , Heaton, R.K.^b , CHARTER Group^k

^a San Diego State University/University of California, San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA 92120, USA
^b Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA
^c Department of Radiology, University of California, San Diego, La Jolla, CA 92093, USA
^d Department of Medicine, University of Washington, Seattle, WA 98195, USA
^e Department of Neurology, University of Washington, Seattle, WA 98195, USA
^f Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
^g Department of Pathology, University of Texas Medical Branch, Galveston, United States
^h Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, United States
ⁱ Department of Neurology, Icahn School of Medicine at Mount Sinai, NY, NY 10029, United States
^j Department of Medicine, University of California, San Diego, La Jolla, CA 92093, USA

Abstract
OBJECTIVE: Frascati international research criteria for HIV-associated neurocognitive disorders (HAND) are controversial; some investigators have argued that Frascati criteria are too liberal, resulting in a high false positive rate. Meyer et al. recommended more conservative revisions to HAND criteria, including exploring other commonly used methodologies for neurocognitive impairment (NCI) in HIV including the global deficit score (GDS). This study compares NCI classifications by Frascati, Meyer, and GDS methods, in relation to neuroimaging markers of brain integrity in HIV. METHOD: Two hundred forty-one people living with HIV (PLWH) without current substance use disorder or severe (confounding) comorbid conditions underwent comprehensive neurocognitive testing and brain structural magnetic resonance imaging and magnetic resonance spectroscopy. Participants were classified using Frascati criteria versus Meyer criteria: concordant unimpaired [Frascati(Un)/Meyer(Un)], concordant impaired [Frascati(Imp)/Meyer(Imp)], or discordant [Frascati(Imp)/Meyer(Un)] which were impaired via Frascati criteria but unimpaired via Meyer criteria. To investigate the GDS versus Meyer criteria, the same groupings were utilized using GDS criteria instead of Frascati criteria. RESULTS: When examining Frascati versus Meyer criteria, discordant Frascati(Imp)/Meyer(Un) individuals had less cortical gray matter, greater sulcal cerebrospinal fluid volume, and greater evidence of neuroinflammation (i.e., choline) than concordant Frascati(Un)/Meyer(Un) individuals. GDS versus Meyer comparisons indicated that discordant GDS(Imp)/Meyer(Un) individuals had less cortical gray matter and lower levels of energy metabolism (i.e., creatine) than concordant GDS(Un)/Meyer(Un) individuals. In both sets of analyses, the discordant group did not differ from the concordant impaired group on any neuroimaging measure. CONCLUSIONS: The Meyer criteria failed to capture a substantial portion of PLWH with brain abnormalities. These findings support continued use of Frascati or GDS criteria to detect HIV-associated CNS dysfunction.

Author Keywords
Cognition;  Frascati criteria;  HIV-associated neurocognitive disorders;  Infectious disease;  Magnetic resonance imaging;  Magnetic resonance spectroscopy

Document Type: Article
Publication Stage: Final
Source: Scopus

Treatment Thresholds in Neurotrauma
(2020) World Neurosurgery, 134, pp. 654-655. 

Hirschi, R.^a , Hawryluk, G.^b

^a Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, United States
^b Section of Neurosurgery, University of Manitoba, GB1 – Health Sciences Centre, Winnipeg, Manitoba, Canada

Document Type: Article
Publication Stage: Final
Source: Scopus

Lack of Neurosteroid Selectivity at δ vs. γ2-Containing GABAA Receptors in Dentate Granule Neurons
(2020) Frontiers in Molecular Neuroscience, 13, art. no. 6, . 

Lu, X.^a , Zorumski, C.F.^{a b c} , Mennerick, S.^{a b c}

^a Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
^b Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, United States
^c Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, MO, United States

Abstract
GABAA receptors mediate a large fraction of inhibitory neurotransmission in the central nervous system. Two major classes of GABAA receptors are γ2-containing receptors and δ-containing receptors, which are largely located synaptically and extrasynaptically, respectively. Neuroactive steroids such as allopregnanolone (3α5αP) and allotetrahydrodeoxycorticosterone (THDOC) are hypothesized to selectively affect δ-containing receptors over γ2-containing receptors. However, the selectivity of neurosteroids on GABAA receptor classes is controversial. In this study, we re-examined this issue using mice with picrotoxin resistance associated with either the δ or γ2 subunit. Our results show that 3α5αP potentiated phasic inhibition of GABAA receptors, and this is mainly through γ2-containing receptors. 3α5αP, with or without exogenous GABA, potentiated tonic inhibition through GABAA receptors. Surprisingly, potentiation arose from both γ2- and δ-containing receptors, even when a δ selective agonist THIP was used to activate current. Although ethanol has been proposed to act through neurosteroids and to act selectively at δ receptors, we found no evidence for ethanol potentiation of GABAA receptor function at 50 mM under our experimental conditions. Finally, we found that the actions of pentobarbital exhibited very similar effects on tonic current as 3α5αP, emphasizing the broad spectrum nature of neurosteroid potentiation. Overall, using chemogenetic analysis, our evidence suggests that in a cell population enriched for δ-containing receptors, neurosteroids act through both δ-containing and non-δ-containing receptors. © Copyright © 2020 Lu, Zorumski and Mennerick.

Author Keywords
allopregnanolone (3α5αP);  GABAA receptor;  hippocampus;  neurosteroid;  phasic inhibition;  tonic inhibition

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

Myelin Oligodendrocyte Glycoprotein Antibody (MOG-IgG)-Positive Optic Perineuritis
(2020) Neuro-Ophthalmology, 44 (1), pp. 1-4. 

Lopez-Chiriboga, A.S.^{a b} , Van Stavern, G.^c , Flanagan, E.P.^{a b d} , Pittock, S.J.^{a b d} , Fryer, J.^{b d} , Bhatti, M.T.^{a e} , Chen, J.J.^{a e}

^a Departments of Neurology, Mayo Clinic, Rochester, MN, United States
^b Center for MS and Autoimmune Neurology, Mayo Clinic, Rochester, MN, United States
^c Department of Ophthalmology and Visual Sciences and Neurology, Washington University School of Medicine, St. Louis, MO, United States
^d Laboratory Medicine, and Pathology, Mayo Clinic, Rochester, MN, United States
^e Ophthalmology, Mayo Clinic, Rochester, MN, United States

Abstract
Optic perineuritis can be a manifestation of infectious and systemic inflammatory disorders, but the majority of cases are idiopathic. Myelin oligodendrocyte glycoprotein (MOG)-IgG-positive optic neuritis has been reported to be associated with optic nerve sheath enhancement. This report describes two MOG-IgG patients with clinical, radiological and therapeutic response consistent with optic perineuritis. MOG-IgG may account for many cases of previously described idiopathic optic perineuritis. Vision loss with optic nerve sheath enhancement on MRI should prompt testing for MOG-IgG. © 2019, © 2019 Taylor & Francis Group, LLC.

Author Keywords
aquaporin-4 (AQP4);  myelin oligodendrocyte glycoprotein (MOG);  optic nerve sheath;  optic neuritis;  Optic perineuritis

Document Type: Article
Publication Stage: Final
Source: Scopus

De novo TBR1 variants cause a neurocognitive phenotype with ID and autistic traits: report of 25 new individuals and review of the literature
(2020) European Journal of Human Genetics, . 

Nambot, S.^{a b c} , Faivre, L.^{a b c} , Mirzaa, G.^{d e} , Thevenon, J.^{a b c f} , Bruel, A.-L.^{a b f} , Mosca-Boidron, A.-L.^{a b f} , Masurel-Paulet, A.^{a c} , Goldenberg, A.^g , Le Meur, N.^g , Charollais, A.^h , Mignot, C.ⁱ , Petit, F.^j , Rossi, M.^k , Metreau, J.^l , Layet, V.^m , Amram, D.ⁿ , Boute-Bénéjean, O.^j , Bhoj, E.^{o p} , Cousin, M.A.^{q r} , Kruisselbrink, T.M.^{q s} , Lanpher, B.C.^{q s} , Klee, E.W.^{q r s} , Fiala, E.^t , Grange, D.K.^u , Meschino, W.S.^v , Hiatt, S.M.^w , Cooper, G.M.^w , Olivié, H.^x , Smith, W.E.^y , Dumas, M.^y , Lehman, A.^aq , Adam, S.^aq , du Souich, C.^aq , Elliott, A.M.^aq , Lehman, A.^aq , Mwenifumbo, J.^aq , Nelson, T.N.^aq , van Karnebeek, C.^aq , Friedman, J.M.^aq , Inglese, C.^aq , Nizon, M.^z , Guerrini, R.^aa , Vetro, A.^aa , Kaplan, E.S.^e , Miramar, D.^ab , Van Gils, J.^ac , Fergelot, P.^ad , Bodamer, O.^ae , Herkert, J.C.^af , Pajusalu, S.^ag , Õunap, K.^ag , Filiano, J.J.^ah , Smol, T.^ai , Piton, A.^aj , Gérard, B.^aj , Chantot-Bastaraud, S.^{i ak} , Bienvenu, T.^al , Li, D.^q , Juusola, J.^am , Devriendt, K.^an , Bilan, F.^ao , Poé, C.^b , Chevarin, M.^b , Jouan, T.^b , Tisserant, E.^b , Rivière, J.-B.^{b c f} , Tran Mau-Them, F.^{b f} , Philippe, C.^{b f} , Duffourd, Y.^{b f} , Dobyns, W.B.^ap , Hevner, R.^ap , Thauvin-Robinet, C.^{a b c f} , CAUSES Study^aq

^a Centre de Génétique et Centre de Référence Maladies Rares (Anomalies du Développement de l’Interrégion Est), Hôpital d’Enfants, CHU Dijon Bourgogne, Dijon, France
^b Inserm UMR 1231 GAD (Génétique des Anomalies du Développement, Université de Bourgogne, Dijon, France
^c Fédération Hospitalo-Universitaire Médecine Translationnelle et Anomalies du Développement (FHU TRANSLAD), CHU Dijon Bourgogne et Université de Bourgogne-Franche Comté, Dijon, France
^d Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, WA, United States
^e Department of Pediatrics, University of Washington, Seattle, WA, United States
^f UF Innovation en diagnostic génomique des maladies rares, CHU Dijon Bourgogne, Dijon, France
^g Service de génétique, CHU de Rouen, Centre Normand de Génomique Médicale et Médecine Personnalisée, Rouen, France
^h Service de Pédiatrie, CHU Rouen Normandie, Rouen, France
ⁱ Service de Génétique et d’Embryologie Médicales, Hôpital Trousseau, Paris, France
^j Clinique de Génétique Guy Fontaine, Pôle de Biologie Pathologie Génétique, Hôpital Jeanne de Flandre, CHU de Lille, Lille, F-59000, France
^k Service de Génétique, Hospices Civils de Lyon, Centre de Recherche en Neurosciences Lyon, INSERM U1028, CNRS UMR5292, GENDEVTeam, Bron, France
^l Service de Neurologie Pédiatrique, Hôpital du Kremlin Bicêtre, Paris, France
^m Service de Génétique, Groupe Hospitalier du Havre, Le Havre, France
ⁿ Unité de Génétique Médicale, CHIC de Créteil, Créteil, France
^o Department of Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^p Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
^q Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, United States
^r Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, United States
^s Department of Clinical Genomics, Mayo Clinic, Rochester, MN 55905, United States
^t Department of Pediatrics, Washington University School of Medicine, Saint Louis, MO, United States
^u Division of Genetics and Genomic Medicine, Department of Pediatrics, Washington University School of Medicine, Saint Louis, MO, United States
^v Genetics Program, North York General Hospital, Toronto, ON, Canada
^w 601 Genome Way, HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
^x Centre for Developmental Disorders, University Hospitals Leuven, Leuven, Belgium
^y Department of Pediatrics, The Barbara Bush Children’s Hospital, Maine Medical Center, Portland, OR, United States
^z Service de Génétique Médicale, CHU de Nantes, Nantes, France
^aa Neuroscience Department, Children’s Hospital Meyer-University of Florence, Florence, Italy
^ab Genetics Unit, Biochemistry Service, Hospital Miguel Servet, Zaragoza, Spain
^ac Service de Génétique Médicale, CHU de Bordeaux, Bordeaux, France
^ad Laboratoire de génétique moléculaire, CHU de Bordeaux, Bordeaux, France
^ae Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA, United States
^af University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, Netherlands
^ag Department of Clinical Genetics, Tartu University Hospital and Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
^ah Departments of Pediatrics and Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, United States
^ai Institut de Génétique Médicale, CHRU de Lille, Lille, France
^aj Laboratoire de diagnostic génétique, Hôpital Civil, CHRU Strasbourg, Strasbourg, France
^ak Service de Génétique et d’Embryologie Médicales, INSERM, Paris, U933, France
^al Service de génétique et biologie moléculaire, Hôpital Cochin, CHU Paris Centre, Paris, France
^am GeneDx, Gaithersburg, MD, United States
^an Center for Human Genetics, University of Leuven, Leuven, Belgium
^ao Laboratoire de Génétique, Service de Génétique, CHU Poitiers, Poitiers, France
^ap Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, WA, United States
^aq Department of Medical Genetics, University of British Columbia, Vancouver, BC V6H 3N1, Canada

Abstract
TBR1, a T-box transcription factor expressed in the cerebral cortex, regulates the expression of several candidate genes for autism spectrum disorders (ASD). Although TBR1 has been reported as a high-confidence risk gene for ASD and intellectual disability (ID) in functional and clinical reports since 2011, TBR1 has only recently been recorded as a human disease gene in the OMIM database. Currently, the neurodevelopmental disorders and structural brain anomalies associated with TBR1 variants are not well characterized. Through international data sharing, we collected data from 25 unreported individuals and compared them with data from the literature. We evaluated structural brain anomalies in seven individuals by analysis of MRI images, and compared these with anomalies observed in TBR1 mutant mice. The phenotype included ID in all individuals, associated to autistic traits in 76% of them. No recognizable facial phenotype could be identified. MRI analysis revealed a reduction of the anterior commissure and suggested new features including dysplastic hippocampus and subtle neocortical dysgenesis. This report supports the role of TBR1 in ID associated with autistic traits and suggests new structural brain malformations in humans. We hope this work will help geneticists to interpret TBR1 variants and diagnose ASD probands. © 2020, The Author(s), under exclusive licence to European Society of Human Genetics.

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

A cross-sectional study of hand function in inclusion body myositis: Implications for functional rating scale
(2020) Neuromuscular Disorders, . 

Lin, A.Y.^{a b} , Clapp, M.^c , Karanja, E.^c , Dooley, K.^d , Weihl, C.C.^c , Wang, L.H.^a

^a Department of Neurology, University of Washington Medical Center, Box 356465, 1959 NE Pacific Street, Seattle, WA 98195-6465, United States
^b Department of Neurology, Stanford Neuroscience Health Center, 213 Quarry Road, M/C 5956, Palo Alto, CA 94305, United States
^c Department of Neurology, Washington University School of Medicine, Campus Box 8111, 660 South Euclid Ave, St. Louis, MO 63110, United States
^d Cure IBM, Davis, CA, United States

Abstract
Inclusion body myositis (IBM) is a slowly progressive and heterogeneous disorder that is a challenge for measuring clinical trial efficacy. The current methods of measuring progression of the disease utilizes the Inclusion Body Myositis Functional Rating Scale, grip strength by dynamometer, and finger flexor strength. One of the hallmarks of the disease is selective deep finger flexor weakness. To date, no adequate data has been available to determine how well the Functional Rating Scale relates to this hallmark physical exam deficit. Our study is the first to investigate the degree of correlation between items pertaining to hand function in the Functional Rating Scale with measured grip and finger flexor strength in IBM patients. We have found a lower than expected correlation with finger flexor strength and even lower with grip strength. The current Functional Rating Scale will benefit from optimization to measure clinical progression more accurately. © 2019 Elsevier B.V.

Author Keywords
Functional rating scale;  Inclusion body myositis

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

Light-Adapted Electroretinogram Differences in Autism Spectrum Disorder
(2020) Journal of Autism and Developmental Disorders, . 

Constable, P.A.^a , Ritvo, E.R.^b , Ritvo, A.R.^c , Lee, I.O.^d , McNair, M.L.^e , Stahl, D.^f , Sowden, J.^g , Quinn, S.^h , Skuse, D.H.^d , Thompson, D.A.^{i j} , McPartland, J.C.^c

^a Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia
^b Professor Emeritus, UCLA, Los Angeles, CA, United States
^c Child Study Center, Yale University School of Medicine, New Haven, CT, United States
^d Behavioural and Brain Sciences Unit, Population Policy and Practice Programme, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
^e Department of Psychology, Stony Brook University, New York, NY, United States
^f School of Medicine, Washington University, St Louis, MO, United States
^g NIHR Great Ormond Street Hospital Biomedical Research Centre, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
^h Department of Statistics, Data Science and Epidemiology, Swinburne University of Technology, Melbourne, Australia
ⁱ The Tony Kriss Visual Electrophysiology Unit, Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom
^j UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom

Abstract
Light-adapted (LA) electroretinograms (ERGs) from 90 individuals with autism spectrum disorder (ASD), mean age (13.0 ± 4.2), were compared to 87 control subjects, mean age (13.8 ± 4.8). LA-ERGs were produced by a random series of nine different Troland based, full-field flash strengths and the ISCEV standard flash at 2/s on a 30 cd m−2 white background. A random effects mixed model analysis showed the ASD group had smaller b- and a-wave amplitudes at high flash strengths (p &lt;.001) and slower b-wave peak times (p &lt;.001). Photopic hill models showed the peaks of the component Gaussian (p =.035) and logistic functions (p =.014) differed significantly between groups. Retinal neurophysiology assessed by LA-ERG provides insight into neural development in ASD. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Author Keywords
Autism spectrum disorder;  b-wave;  Electroretinogram

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

Sleep restores place learning to the adenylyl cyclase mutant rutabaga
(2020) Journal of Neurogenetics, . 

Dissel, S.^{a b} , Morgan, E.^b , Duong, V.^b , Chan, D.^b , van Swinderen, B.^c , Shaw, P.^b , Zars, T.^d

^a School of Biological and Chemical Sciences, University of Missouri-Kansas City, Kansas City, MO, United States
^b Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, United States
^c The Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
^d Division of Biological Sciences, University of Missouri, Columbia, MO, United States

Abstract
Sleep plays an important role in regulating plasticity. In Drosophila, the relationship between sleep and learning and memory has primarily focused on mushroom body dependent operant-learning assays such as aversive phototaxic suppression and courtship conditioning. In this study, sleep was increased in the classic mutant rutabaga (rut2080) and dunce (dnc1) by feeding them the GABA-A agonist gaboxadol (Gab). Performance was evaluated in each mutant in response to social enrichment and place learning, tasks that do not require the mushroom body. Gab-induced sleep did not restore behavioral plasticity to either rut2080 or dnc1 mutants following social enrichment. However, increased sleep restored place learning to rut2080 mutants. These data extend the positive effects of enhanced sleep to place learning and highlight the utility of Gab for elucidating the beneficial effects of sleep on brain functioning. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Author Keywords
learning;  memory;  plasticity;  Sleep

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

The Sociobiology of Brain Tumors
(2020) Advances in Experimental Medicine and Biology, 1225, pp. 115-125. 

Gutmann, D.H.

Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA

Abstract
Brain tumors are complex cellular ecosystems, composed of populations of both neoplastic and non-neoplastic cell types. While the contributions of the cancer cells in low-grade and high-grade gliomas have been extensively studied, there is comparatively less known about the contributions of the non-neoplastic cells in these tumors. As such, a large proportion of the non-neoplastic cells in gliomas are resident brain microglia, infiltrating circulating macrophages, and T lymphocytes. These immune system-like stromal cells are recruited into the evolving tumor through the elaboration of chemokines, and are reprogrammed to adopt new cellular identities critical for glioma formation, maintenance, and progression. In this manner, these populations of tumor-associated microglia and macrophages produce growth factors that support gliomagenesis and continued tumor growth. As we begin to characterize these immune cell contributions, future therapies might emerge as adjuvant approaches to glioma treatment.

Author Keywords
Astrocytoma;  Cancer;  Chemokine;  Ecosystem;  Glioblastoma;  Glioma;  Macrophage;  Microglia;  Neurofibromatosis type 1;  RAS;  T lymphocyte;  Tumor microenvironment;  Tumorigenesis

Document Type: Article
Publication Stage: Final
Source: Scopus

Effects of remote limb ischemic conditioning on muscle strength in healthy young adults: A randomized controlled trial
(2020) PloS One, 15 (2), p. e0227263. 

Surkar, S.M.^a , Bland, M.D.^a , Mattlage, A.E.^a , Chen, L.^b , Gidday, J.M.^c , Lee, J.-M.^d , Hershey, T.^e , Lang, C.E.^{a d f}

^a Program in Physical Therapy, Washington University School of Medicine, St. Louis, MO, United States of America
^b Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
^c Departments of Ophthalmology, Physiology, Neuroscience, Louisiana State University Health Sciences Center, LA, New Orleans, United States
^d Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States of America
^e Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States of America
^f Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO, United States of America

Abstract
Remote limb ischemic conditioning (RLIC) is a clinically feasible method in which brief, sub-lethal bouts of ischemia protects remote organs or tissues from subsequent ischemic injury. A single session of RLIC can improve exercise performance and increase muscle activation. The purpose of this study, therefore, was to assess the effects of a brief, two-week protocol of repeated RLIC combined with strength training on strength gain and neural adaptation in healthy young adults. Participants age 18-40 years were randomized to receive either RLIC plus strength training (n = 15) or sham conditioning plus strength training (n = 15). Participants received RLIC or sham conditioning over 8 visits using a blood pressure cuff on the dominant arm with 5 cycles of 5 minutes each alternating inflation and deflation. Visits 3-8 paired conditioning with wrist extensors strength training on the non-dominant (non-conditioned) arm using standard guidelines. Changes in one repetition maximum (1 RM) and electromyography (EMG) amplitude were compared between groups. Both groups were trained at a similar workload. While both groups gained strength over time (P = 0.001), the RLIC group had greater strength gains (9.38 ± 1.01 lbs) than the sham group (6.3 ± 1.08 lbs, P = 0.035). There was not a significant group x time interaction in EMG amplitude (P = 0.231). The RLIC group had larger percent changes in 1 RM (43.8% vs. 26.1%, P = 0.003) and EMG amplitudes (31.0% vs. 8.6%, P = 0.023) compared to sham conditioning. RLIC holds promise for enhancing muscle strength in healthy young and older adults, as well as clinical populations that could benefit from strength training.

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

The role of screening spinal MRI in children with solitary posterior fossa low-grade glial tumors
(2020) Journal of Neurosurgery: Pediatrics, 25 (2), pp. 106-110. 

Roth, J.^a , Fischer, N.^a , Limbrick, D.D., Jr.^c , CreveCoeur, T.^c , Ben-Sira, L.^b , Constantini, S.^a

^a Department of Pediatric Neurosurgery, Tel-Aviv University, Tel-Aviv, Israel
^b Pediatric Radiology Unit, Dana Children’s Hospital, Tel-Aviv Medical Center, Tel-Aviv University, Tel-Aviv, Israel
^c Department of Pediatric Neurosurgery, St. Louis Children’s Hospital, Washington University, St. Louis, MO, United States

Abstract
OBJECTIVE Solitary posterior fossa low-grade glial tumors (SPFLGT) in children are rarely associated with leptomeningeal dissemination (LMD). To date, there are no clear guidelines regarding the role of screening and surveillance spinal MRI (sMRI) in children with SPFLGT, at diagnosis or during follow-up periods. The current study reviews a cohort of children with SPFLGT, focusing on sMRI findings. METHODS In this binational retrospective study, the authors analyzed 229 patients with SPFLGT treated and followed over 13 years. One hundred twelve children had at least 1 total sMRI screening or surveillance examination. One hundred seventeen had no sMRI, but did not present with clinical spinal signs or symptoms. Collected data included demographics, disease characteristics, radiology, pathology, and clinical follow-up data. RESULTS For the 112 children with at least 1 sMRI, the mean duration from diagnosis to first sMRI was 11.73 ± 28.66 months (range 0–165 months). All sMRI scans were conducted as screening examinations, with no spinal-related symptoms. One patient was found to have a sacral intradural lesion concurrent to the brain tumor diagnosis. Over the course of 180 radiological and 533 clinical follow-up years for the 112 patients with sMRI, and 582 clinical follow-up years for the 117 patients with no sMRI, there were no additional cases with spinal tumor spread. CONCLUSIONS The yield of screening sMRI in the absence of cranial metastasis, or spinal symptoms, is extremely low. Because preoperative sMRI is recommended for medulloblastomas and ependymomas, it may be logical to acquire. During the follow-up period the authors recommend limiting sMRI in patients without symptoms suggesting a spinal lesion, in patients without known cranial metastases, or recurrence or residual SPFLGT. ©AANS 2020,

Author Keywords
Leptomeningeal dissemination;  Low-grade glioma;  Oncology;  Posterior fossa;  Screening;  Spine MRI

Document Type: Article
Publication Stage: Final
Source: Scopus

Time to recovery predicted by the severity of postoperative C5 palsy
(2020) Journal of Neurosurgery: Spine, 32 (2), pp. 191-199. 

Pennington, Z.^a , Lubelski, D.^a , Westbroek, E.M.^a , Ahmed, A.K.^a , Ehresman, J.^a , Goodwin, M.L.^{a b} , Lo, S.-F.^a , Witham, T.F.^a , Bydon, A.^a , Theodore, N.^a , Sciubba, D.M.^a

^a Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
^b Department of Orthopaedics, Washington University, St. Louis, MO, United States

Abstract
OBJECTIVE Postoperative C5 palsy affects 7%–12% of patients who undergo posterior cervical decompression for degenerative cervical spine pathologies. Minimal evidence exists regarding the natural history of expected recovery and variables that affect palsy recovery. The authors investigated pre- and postoperative variables that predict recovery and recovery time among patients with postoperative C5 palsy. METHODS The authors included patients who underwent posterior cervical decompression at a tertiary referral center between 2004 and 2018 and who experienced postoperative C5 palsy. All patients had preoperative MR images and full records, including operative note, postoperative course, and clinical presentation. Kaplan-Meier survival analysis was used to evaluate both times to complete recovery and to new neurological baseline—defined by deltoid strength on manual motor testing of the affected side—as a function of clinical symptoms, surgical maneuvers, and the severity of postoperative deficits. RESULTS Seventy-seven patients were included, with an average age of 64 years. The mean follow-up period was 17.7 months. The mean postoperative C5 strength was grade 2.7/5, and the mean time to first motor examination with documented C5 palsy was 3.5 days. Sixteen patients (21%) had bilateral deficits, and 9 (12%) had new-onset biceps weakness; 36% of patients had undergone C4–5 foraminotomy of the affected root, and 17% had presented with radicular pain in the dermatome of the affected root. On univariable analysis, patients’ reporting of numbness or tingling (p = 0.02) and a baseline deficit (p < 0.001) were the only predictors of time to recovery. Patients with grade 4+/5 weakness had significantly shorter times to recovery than patients with grade 4/5 weakness (p = 0.001) or ≤ grade 3/5 weakness (p < 0.001). There was no difference between those with grade 4/5 weakness and those with ≤ grade 3/5 weakness. Patients with postoperative strength < grade 3/5 had a < 50% chance of achieving complete recovery. CONCLUSIONS The timing and odds of recovery following C5 palsy were best predicted by the magnitude of the postoperative deficit. The use of C4–5 foraminotomy did not predict the time to or likelihood of recovery. ©AANS 2020,

Author Keywords
C5 palsy;  Cervical;  Patient expectations;  Postoperative complications

Document Type: Article
Publication Stage: Final
Source: Scopus

Postural Directionality and Head Tremor in Cervical Dystonia
(2020) Tremor and Other Hyperkinetic Movements (New York, N.Y.), 10, . 

Chen, Q.^a , Vu, J.P.^a , Cisneros, E.^a , Benadof, C.N.^a , Zhang, Z.^a , Barbano, R.L.^b , Goetz, C.G.^c , Jankovic, J.^d , Jinnah, H.A.^e , Perlmutter, J.S.^{f g} , Appelbaum, M.I.^h , Stebbins, G.T.^c , Comella, C.L.^c , Peterson, D.A.^{a i}

^a Institute for Neural Computation, University of California, San Diego, La Jolla, CA, USA
^b Department of Neurology, University of Rochester, Rochester, NY, USA
^c Department of Neurological Sciences, Rush University Medical Center, Chicago, United States
^d Parkinson’s Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, TX, Houston, United States
^e Departments of Neurology and Human Genetics, Emory University, Atlanta, United States
^f Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
^g Departments of Psychiatry, Radiology, Neurobiology, Physical Therapy, and Occupational Therapy, Washington University School of Medicine, St. Louis, MO, USA
^h Department of Psychology, University of California, San Diego, La Jolla, CA, USA
ⁱ Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, United States

Abstract
Background: Although abnormal head and neck postures are defining features of cervical dystonia (CD), head tremor (HT) is also common. However, little is known about the relationship between abnormal postures and HT in CD. Methods: We analyzed clinical data and video recordings from 185 patients enrolled by the Dystonia Coalition. We calculated the likelihood of their HT and HT type (“regular” vs. “jerky”) given directionality of abnormal head postures, disease duration, sex, and age. Results: Patients with retrocollis were more likely to have HT than patients with anterocollis (X2 (1, N = 121) = 7.98, p = 0.005). There was no difference in HT likelihood given left or right turning in laterocollis and rotation. Patients with HT had longer disease duration (t(183) = 2.27, p = 0.024). There was no difference in age between patients with and without HT. In a logistic regression model, anterocollis/retrocollis direction (X2 (1, N = 121) = 6.04, p = 0.014), disease duration (X2 (1, N = 121) = 7.28, p = 0.007), and the interaction term between age and disease duration (X2 (1, N = 121) = 7.77, p = 0.005) collectively contributed to HT likelihood. None of the postural directionality or demographic variables were associated with differential likelihood of having regular versus jerky HT. Discussion: We found that HT is more likely for CD patients with a specific directionality in their predominant posture. Our finding that CD patients with longer disease duration have a higher likelihood of HT also raises the question of whether HT becomes more likely over time in individual patients. © 2020 Chen et al.

Author Keywords
Cervical dystonia;  disease duration;  head tremor;  posture;  tremor type

Document Type: Article
Publication Stage: Final
Source: Scopus

Distinct neural networks associated with obsession and delusion: A connectome-wide association study
(2020) Psychological Medicine, . 

Lee, T.Y.^a , Jung, W.H.^b , Kwak, Y.B.^c , Yoon, Y.B.^d , Lee, J.^a , Kim, M.^a , Kim, E.^a , Kwon, J.S.^{a c}

^a Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
^b Department of Psychology, Daegu University, Gyeongsan, South Korea
^c Department of Brain and Cognitive Science, Seoul National University College of Natural Science, Seoul, South Korea
^d Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, United States

Abstract
BackgroundObsession and delusion are theoretically distinct from each other in terms of reality testing. Despite such phenomenological distinction, no extant studies have examined the identification of common and distinct neural correlates of obsession and delusion by employing biologically grounded methods. Here, we investigated dimensional effects of obsession and delusion spanning across the traditional diagnostic boundaries reflected upon the resting-state functional connectivity (RSFC) using connectome-wide association studies (CWAS).MethodsOur study sample comprised of 96 patients with obsessive-compulsive disorder, 75 patients with schizophrenia, and 65 healthy controls. A connectome-wide analysis was conducted to examine the relationship between obsession and delusion severity and RFSC using multivariate distance-based matrix regression.ResultsObsession was associated with the supplementary motor area, precentral gyrus, and superior parietal lobule, while delusion was associated with the precuneus. Follow-up seed-based RSFC and modularity analyses revealed that obsession was related to aberrant inter-network connectivity strength. Additional inter-network analyses demonstrated the association between obsession severity and inter-network connectivity between the frontoparietal control network and the dorsal attention network.ConclusionsOur CWAS study based on the Research Domain Criteria (RDoC) provides novel evidence for the circuit-level functional dysconnectivity associated with obsession and delusion severity across diagnostic boundaries. Further refinement and accumulation of biomarkers from studies embedded within the RDoC framework would provide useful information in treating individuals who have some obsession or delusion symptoms but cannot be identified by the category of clinical symptoms alone. Copyright © Cambridge University Press 2020.

Author Keywords
Biotypes;  connectome-wide association study (CWAS);  delusion;  obsession;  Research Domain Criteria (RDoC);  resting-state functional connectivity (RSFC)

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

Using a Thin Slice Coding Approach to Assess Preschool Personality Dimensions
(2020) Journal of Personality Assessment, . 

Whalen, D.J.^a , Gilbert, K.E.^a , Jackson, J.J.^b , Barch, D.M.^{a b c d} , Luby, J.L.^a

^a Department of Psychiatry, Washington University in St. Louis, United States
^b Department of Psychological and Brain Sciences, Washington University in St. Louis, United States
^c The Program in Neuroscience, Washington University in St. Louis, United States
^d Department of Radiology, Washington University in St. Louis, United States

Abstract
A large literature assessing personality across the lifespan has used the Big Five as an organizing framework, with evidence that variation along different dimensions predicts aspects of psychopathology. Parent reports indicate that these dimensions emerge as early as preschool, but there is a need for objective, observational measures of personality in young children, as parent report can be confounded by the parents’ own personality and psychopathology. The current study observationally coded personality dimensions in a clinically enriched sample of preschoolers. A heterogeneous group of preschoolers oversampled for depression (N = 299) completed 1–8 structured observational tasks with an experimenter. Big Five personality dimensions of extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience were coded using a “thin slice” technique with 7,820 unique ratings available for analysis. Thin slice ratings of personality dimensions were reliably observed in preschoolers ages 3–6 years. Within and across-task, consistency was also evident, with consistency estimates higher than found in adult samples. Divergent validity was limited, with coders distinguishing between three (extraversion/openness; agreeableness/conscientiousness; and neuroticism) rather than five dimensions. Personality dimensions can be observationally identified in preschool-age children and offer reliable estimates that stand across different observational tasks. Study findings highlight the importance of observational approaches to assessing early personality dimensions, as well as the utility of the thin slice approach for meaningful secondary data analysis. © 2020, © 2020 Taylor & Francis Group, LLC.

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

Sex is an important prognostic factor for glioblastoma but not for nonglioblastoma
(2019) Neuro-Oncology Practice, 6 (6), pp. 451-462. 

Gittleman, H.^{a b c} , Ostrom, Q.T.^{a d} , Stetson, L.C.^b , Waite, K.^{b c} , Hodges, T.R.^{e f} , Wright, C.H.^e , Wright, J.^e , Rubin, J.B.^g , Berens, M.E.^h , Lathia, J.^{b i} , Connor, J.R.^j , Kruchko, C.^a , Sloan, A.E.^{b e f} , Barnholtz-Sloan, J.S.^{a b c}

^a Central Brain Tumor Registry of the United States, Hinsdale, IL, United States
^b Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, United States
^c Department of Population Health and Quantitative Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, United States
^d Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, United States
^e Department of Neurological Surgery, University Hospitals of Cleveland, Case Western University School of MedicineOH, United States
^f Seidman Cancer Center, University Hospitals of ClevelandOH, United States
^g Washington University School of Medicine, St. Louis, MO, United States
^h Translational Genomics Research Institute, Phoenix, AZ, United States
ⁱ Cleveland Clinic, Lerner Research InstituteOH, United States
^j Department of Neurosurgery, Penn State Cancer Institute, Penn State, State College, PA, United States

Abstract
Background. Glioblastoma (GBM) is the most common and most malignant glioma. Nonglioblastoma (non-GBM) gliomas (WHO Grades II and III) are invasive and also often fatal. The goal of this study is to determine whether sex differences exist in glioma survival. Methods. Data were obtained from the National Cancer Database (NCDB) for years 2010 to 2014. GBM (WHO Grade IV; N = 2073) and non-GBM (WHO Grades II and III; N = 2963) were defined using the histology grouping of the Central Brain Tumor Registry of the United States. Non-GBM was divided into oligodendrogliomas/mixed gliomas and astrocytomas. Sex differences in survival were analyzed using Kaplan-Meier and multivariable Cox proportional hazards models adjusted for known prognostic variables. Results. There was a female survival advantage in patients with GBM both in the unadjusted (P = .048) and adjusted (P = .003) models. Unadjusted, median survival was 20.1 months (95% CI: 18.7-21.3 months) for women and 17.8 months (95% CI: 16.9-18.7 months) for men. Adjusted, median survival was 20.4 months (95% CI: 18.9- 21.6 months) for women and 17.5 months (95% CI: 16.7-18.3 months) for men. When stratifying by age group (18-55 vs 56+ years at diagnosis), this female survival advantage appeared only in the older group, adjusting for covariates (P = .017). Women (44.1%) had a higher proportion of methylated MGMT (O6-methylguanine-DNA methyltransferase) than men (38.4%). No sex differences were found for non-GBM. Conclusions. Using the NCDB data, there was a statistically significant female survival advantage in GBM, but not in non-GBM. © The Author(s) 2019.

Author Keywords
Glioblastoma;  Glioma;  NCDB;  Sex differences;  Survival

Document Type: Article
Publication Stage: Final
Source: Scopus

Melanoma in individuals with neurofibromatosis type 1: a retrospective study
(2019) Dermatology Online Journal, 25 (11), . 

Zhang, M., Bhat, T., Gutmann, D.H., Johnson, K.J.

Brown School Master of Public Health Program, Washington University in St. Louis, St. Louis, MO

Abstract
BACKGROUND: Neurofibromatosis type 1 (NF1) is a cancer syndrome associated with many different cancer types. There are limited studies examining melanoma risk in this population. OBJECTIVE: To identify melanoma cases in NF1 patients and compare melanoma incidence rates relative to a general population sample. METHODS: A retrospective single institution case review of 857 NF1 patients (seen from 7/1997 to 7/2017) was conducted. We calculated age- and calendar period-adjusted standardized incidence ratios (SIRs) for white patients &gt;20 years old overall (N=282) and for females (N=156) at their last visit date. We obtained general population melanoma reference rates from the Surveillance, Epidemiology, and End Results (SEER) 9 database. RESULTS: Among 857 patients, 52.2% were female, 54% were &lt;20 (mean±sd=10.9±4.6) years old, and 46% were &gt;20 (40.4±14.9) years old at their last visit date. One white female patient had a malignant melanoma diagnosed at 47 years old. The adjusted SIR was 0.97 (95% CI 0.05-4.78) overall (N=282) and 1.62 (95% CI 0.08-7.98) for females (N=156). CONCLUSIONS: We did not find statistical evidence for an increased melanoma risk in adults with NF1. However, additional large studies are warranted to clarify whether melanoma risk is increased in NF1 patients.

Document Type: Article
Publication Stage: Final
Source: Scopus