Characterization of Neurophysiologic and Neurocognitive Biomarkers for Use in Genomic and Clinical Outcome Studies of Schizophrenia Gregory A. Light 1,2 *, Neal R. Swerdlow 2 , Anthony J. Rissling 2 , Allen Radant 3 , Catherine A. Sugar 4 , Joyce Sprock 1,2 , Marlena Pela 2 , Mark A. Geyer 1,2 , David L. Braff 1,2 1 VISN-22 Mental Illness, Research, Education, and Clinical Center (MIRECC), San Diego VA Health Care System, La Jolla, California, United States of America, 2 Department of Psychiatry, University of California San Diego, La Jolla, California, United States of America, 3 Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Washington, United States of America, 4 Departments of Psychiatry and Biostatistics, University of California Los Angeles, Los Angeles, California, United States of America Abstract Background: Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1) associated with schizophrenia, 2) stable over time, independent of state-related changes, and 3) free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ) and nonpsychiatric comparison subjects (NCS). Stability of clinical and functional measures was also assessed. Methods: Participants (SZ n = 341; NCS n = 205) completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade), neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II). In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF). 223 subjects (SZ n = 163; NCS n = 58) returned for retesting after 1 year. Results: Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS) was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria. Conclusions: The majority of neurophysiological and neurocognitive measures exhibited deficits in patients, stability over a 1-year interval and did not demonstrate practice or time effects supporting their use as endophenotypes in neural substrate and genomic studies. These measures hold promise for informing the ‘‘gene-to-phene gap’’ in schizophrenia research. Citation: Light GA, Swerdlow NR, Rissling AJ, Radant A, Sugar CA, et al. (2012) Characterization of Neurophysiologic and Neurocognitive Biomarkers for Use in Genomic and Clinical Outcome Studies of Schizophrenia. PLoS ONE 7(7): e39434. doi:10.1371/journal.pone.0039434 Editor: Hossein Fatemi, University of Minnesota, United States of America Received February 9, 2012; Accepted May 23, 2012; Published July 3, 2012 This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Funding: This work was supported by grants from National Institute of Mental Health (MH042228, MH079777, and MH065571) and supported by the Department of Veteran Affairs (VISN 22 Mental Illness Research, Education, and Clinical Center). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Dr. Light has received compensation from Astellas for one-time participation in a scientific advisory boad unrelated to this study. Dr. Geyer has received compensation from Abbott, Acadia, Addex, Cerca Insights, Merck, Omeros, and Takeda for work unrelated to this study, and holds an equity interest in San Diego Instruments (San Diego, CA). Dr. Swerdlow has received compensation from Neurocrine for work unrelated to this study. This does not alter the authors’ adherence to all PLoS ONE policies on sharing data and materials. The remaining authors report no financial relationships with commercial interests. * E-mail: glight@ucsd.edu Introduction One prominent strategy for deconstructing complex, heritable neuropsychiatric disorders such as schizophrenia is to examine discrete, genetically determined ‘‘endophenotypes’’ that are part of the illness and detected in the laboratory rather than by ‘‘the naked eye’’ of the clinical interview [1]. Endophenotypes may be useful for deconstructing the complexity of clinical, neural substrate, and genetic underpinnings of the disorder [2,3]. Several criteria for viable endophenotypes have been proposed [1,4–6]. While there is some variability in the criteria, in general, endophenotypes are a subset of biomarkers that: 1) are associated with the illness, i.e., exhibit deficits in patients; 2) are stable over time; 3) are relatively independent of fluctuations in clinical PLoS ONE | www.plosone.org 1 July 2012 | Volume 7 | Issue 7 | e39434