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The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project

Research output: Contribution to journalArticle

  • Gabriëlla A M Blokland
  • Elisabetta C Del Re
  • Raquelle I Mesholam-Gately
  • Jorge Jovicich
  • Joey W Trampush
  • Matcheri S Keshavan
  • Lynn E DeLisi
  • James T R Walters
  • Anil K Malhotra
  • Todd Lencz
  • Martha E Shenton
  • Aristotle N Voineskos
  • Dan Rujescu
  • Ina Giegling
  • René S Kahn
  • Joshua L Roffman
  • Daphne J Holt
  • Stefan Ehrlich
  • Zora Kikinis
  • Paola Dazzan
  • Robin M Murray
  • Marta Di Forti
  • Jimmy Lee
  • Kang Sim
  • Max Lam
  • Rick P F Wolthusen
  • Sonja M C de Zwarte
  • Esther Walton
  • Donna Cosgrove
  • Sinead Kelly
  • Nasim Maleki
  • Lisa Osiecki
  • Marco M Picchioni
  • Elvira Bramon
  • Manuela Russo
  • Valeria Mondelli
  • Antje A T S Reinders
  • M Aurora Falcone
  • Annette M Hartmann
  • Bettina Konte
  • Michael Gill
  • Aiden P Corvin
  • Wiepke Cahn
  • New Fei Ho
  • Richard S E Keefe
  • Randy L Gollub
  • Dara S Manoach
  • Vince D Calhoun
  • S Charles Schulz
  • Scott R Sponheim
  • Donald C Goff
  • Stephen L Buka
  • Sara Cherkerzian
  • Heidi W Thermenos
  • Marek Kubicki
  • Paul G Nestor
  • Erin W Dickie
  • Evangelos Vassos
  • Simone Ciufolini
  • Tiago Reis Marques
  • Nicolas A Crossley
  • Shaun M Purcell
  • Jordan W Smoller
  • Neeltje E M van Haren
  • Timothea Toulopoulou
  • Gary Donohoe
  • Jill M Goldstein
  • Larry J Seidman
  • Robert W McCarley
  • Tracey L Petryshen
Original languageEnglish
JournalSchizophrenia Research
Early online date3 Oct 2017
DateAccepted/In press - 20 Sep 2017
DateE-pub ahead of print (current) - 3 Oct 2017


BACKGROUND: Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) Consortium aims to clarify the role of genetic variation in brain abnormalities underlying schizophrenia. This article describes the GENUS Consortium sample collection.

METHODS: We identified existing samples collected for schizophrenia studies consisting of patients, controls, and/or individuals at familial high-risk (FHR) for schizophrenia. Samples had single nucleotide polymorphism (SNP) array data or genomic DNA, clinical and demographic data, and neuropsychological and/or brain magnetic resonance imaging (MRI) data. Data were subjected to quality control procedures at a central site.

RESULTS: Sixteen research groups contributed data from 5199 psychosis patients, 4877 controls, and 725 FHR individuals. All participants have relevant demographic data and all patients have relevant clinical data. The sex ratio is 56.5% male and 43.5% female. Significant differences exist between diagnostic groups for premorbid and current IQ (both p<1×10(-10)). Data from a diversity of neuropsychological tests are available for 92% of participants, and 30% have structural MRI scans (half also have diffusion-weighted MRI scans). SNP data are available for 76% of participants. The ancestry composition is 70% European, 20% East Asian, 7% African, and 3% other.

CONCLUSIONS: The Consortium is investigating the genetic contribution to brain phenotypes in a schizophrenia sample collection of >10,000 participants. The breadth of data across clinical, genetic, neuropsychological, and MRI modalities provides an important opportunity for elucidating the genetic basis of neural processes underlying schizophrenia.

    Research areas

  • Schizophrenia, Neuropsychology, Cognition, Neuroimaging, MRI, Genetics

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    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 468 KB, PDF document


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