Larry J Seidman1, Gerhard Hellemann2, Keith H Nuechterlein3, Tiffany A Greenwood4, David L Braff5, Kristin S Cadenhead4, Monica E Calkins6, Robert Freedman7, Raquel E Gur6, Ruben C Gur6, Laura C Lazzeroni8, Gregory A Light9, Ann Olincy7, Allen D Radant10, Larry J Siever11, Jeremy M Silverman12, Joyce Sprock4, William S Stone13, Catherine Sugar14, Neal R Swerdlow4, Debby W Tsuang10, Ming T Tsuang15, Bruce I Turetsky6, Michael F Green16. 1. Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Harvard Medical School Department of Psychiatry, Boston, MA, United States; Harvard Institute of Psychiatric Epidemiology and Genetic s, Boston, MA, United States. Electronic address: lseidman@bidmc.harvard.edu. 2. Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States. 3. Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States; Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States. 4. Department of Psychiatry, University of California San Diego, La Jolla, CA, United States. 5. Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VA San Diego Healthcare System VISN-22 Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States. Electronic address: dbraff@ucsd.edu. 6. Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States. 7. Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO, United States. 8. Department of Psychiatry and Behavioral Sciences, Stanford University Medical Center, Stanford, CA, United States. 9. Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VA San Diego Healthcare System VISN-22 Mental Illness Research, Education, and Clinical Center (MIRECC), San Diego, CA, United States. 10. Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States; The Department of Veteran Affairs VISN-20 Mental Illness Research, Education, and Clinical Center, Seattle, WA, United States. 11. Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States; James J. Peters VA & VISN3 Mental Illness Research, Education and Clinical Center, Bronx, NY, United States. 12. Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States. 13. Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Harvard Medical School Department of Psychiatry, Boston, MA, United States; Harvard Institute of Psychiatric Epidemiology and Genetic s, Boston, MA, United States. 14. Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States; Department of Biostatistics, University of California Los Angeles, Los Angeles, CA, United States; VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States. 15. Harvard Institute of Psychiatric Epidemiology and Genetic s, Boston, MA, United States; Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; Center for Behavioral Genomics, Department of Psychiatry and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, United States. 16. Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States; VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States.
Abstract
BACKGROUND: Although many endophenotypes for schizophrenia have been studied individually, few studies have examined the extent to which common neurocognitive and neurophysiological measures reflect shared versus unique endophenotypic factors. It may be possible to distill individual endophenotypes into composite measures that reflect dissociable, genetically informative elements. METHODS: The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) is a multisite family study that collected neurocognitive and neurophysiological data between 2003 and 2008. For these analyses, participants included schizophrenia probands (n=83), their nonpsychotic siblings (n=151), and community comparison subjects (n=209) with complete data on a battery of 12 neurocognitive tests (assessing domains of working memory, declarative memory, vigilance, spatial ability, abstract reasoning, facial emotion processing, and motor speed) and 3 neurophysiological tasks reflecting inhibitory processing (P50 gating, prepulse inhibition and antisaccade tasks). Factor analyses were conducted on the measures for each subject group and across the entire sample. Heritability analyses of factors were performed using SOLAR. RESULTS: Analyses yielded 5 distinct factors: 1) Episodic Memory, 2) Working Memory, 3) Perceptual Vigilance, 4) Visual Abstraction, and 5) Inhibitory Processing. Neurophysiological measures had low associations with these factors. The factor structure of endophenotypes was largely comparable across probands, siblings and controls. Significant heritability estimates for the factors ranged from 22% (Episodic Memory) to 39% (Visual Abstraction). CONCLUSIONS: Neurocognitive measures reflect a meaningful amount of shared variance whereas the neurophysiological measures reflect largely unique contributions as endophenotypes for schizophrenia. Composite endophenotype measures may inform our neurobiological and genetic understanding of schizophrenia.
BACKGROUND: Although many endophenotypes for schizophrenia have been studied individually, few studies have examined the extent to which common neurocognitive and neurophysiological measures reflect shared versus unique endophenotypic factors. It may be possible to distill individual endophenotypes into composite measures that reflect dissociable, genetically informative elements. METHODS: The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) is a multisite family study that collected neurocognitive and neurophysiological data between 2003 and 2008. For these analyses, participants included schizophrenia probands (n=83), their nonpsychotic siblings (n=151), and community comparison subjects (n=209) with complete data on a battery of 12 neurocognitive tests (assessing domains of working memory, declarative memory, vigilance, spatial ability, abstract reasoning, facial emotion processing, and motor speed) and 3 neurophysiological tasks reflecting inhibitory processing (P50 gating, prepulse inhibition and antisaccade tasks). Factor analyses were conducted on the measures for each subject group and across the entire sample. Heritability analyses of factors were performed using SOLAR. RESULTS: Analyses yielded 5 distinct factors: 1) Episodic Memory, 2) Working Memory, 3) Perceptual Vigilance, 4) Visual Abstraction, and 5) Inhibitory Processing. Neurophysiological measures had low associations with these factors. The factor structure of endophenotypes was largely comparable across probands, siblings and controls. Significant heritability estimates for the factors ranged from 22% (Episodic Memory) to 39% (Visual Abstraction). CONCLUSIONS: Neurocognitive measures reflect a meaningful amount of shared variance whereas the neurophysiological measures reflect largely unique contributions as endophenotypes for schizophrenia. Composite endophenotype measures may inform our neurobiological and genetic understanding of schizophrenia.
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