Tiffany A Greenwood1, Laura C Lazzeroni2,3, Adam X Maihofer1, Neal R Swerdlow1, Monica E Calkins4, Robert Freedman5, Michael F Green6,7, Gregory A Light1,8, Caroline M Nievergelt1, Keith H Nuechterlein6, Allen D Radant9,10, Larry J Siever11,12, Jeremy M Silverman11,12, William S Stone13,14, Catherine A Sugar6,15, Debby W Tsuang9,10, Ming T Tsuang1, Bruce I Turetsky4, Ruben C Gur4, Raquel E Gur4, David L Braff1. 1. Department of Psychiatry, University of California, San Diego, La Jolla. 2. Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California. 3. Sierra Pacific Mental Illness Research Education and Clinical Center, Department of Veterans Affairs (VA) Health Care System, Palo Alto, California. 4. Department of Psychiatry, University of Pennsylvania, Philadelphia. 5. Department of Psychiatry, University of Colorado Health Sciences Center, Denver. 6. Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, California. 7. Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles, California. 8. Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California. 9. Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle. 10. Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, Washington. 11. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York. 12. Research & Development, James J. Peters VA Medical Center, New York, New York. 13. Department of Psychiatry, Harvard Medical School, Boston, Massachusetts. 14. Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston. 15. Department of Biostatistics, UCLA School of Public Health.
Abstract
Importance: The Consortium on the Genetics of Schizophrenia (COGS) uses quantitative neurophysiological and neurocognitive endophenotypes with demonstrated deficits in schizophrenia as a platform from which to explore the underlying neural circuitry and genetic architecture. Many of these endophenotypes are associated with poor functional outcome in schizophrenia. Some are also endorsed as potential treatment targets by the US Food and Drug Administration. Objective: To build on prior assessments of heritability, association, and linkage in the COGS phase 1 (COGS-1) families by reporting a genome-wide association study (GWAS) of 11 schizophrenia-related endophenotypes in the independent phase 2 (COGS-2) cohort of patients with schizophrenia and healthy comparison participants (HCPs). Design, Setting, and Participants: A total of 1789 patients with schizophrenia and HCPs of self-reported European or Latino ancestry were recruited through a collaborative effort across the COGS sites and genotyped using the PsychChip. Standard quality control filters were applied, and more than 6.2 million variants with a genotyping call rate of greater than 0.99 were available after imputation. Association was performed for data sets stratified by diagnosis and ancestry using linear regression and adjusting for age, sex, and 5 principal components, with results combined through weighted meta-analysis. Data for COGS-1 were collected from January 6, 2003, to August 6, 2008; data for COGS-2, from June 30, 2010, to February 14, 2014. Data were analyzed from October 28, 2016, to May 4, 2018. Main Outcomes and Measures: A genome-wide association study was performed to evaluate association for 11 neurophysiological and neurocognitive endophenotypes targeting key domains of schizophrenia related to inhibition, attention, vigilance, learning, working memory, executive function, episodic memory, and social cognition. Results: The final sample of 1533 participants included 861 male participants (56.2%), and the mean (SD) age was 41.8 (13.6) years. In total, 7 genome-wide significant regions (P < 5 × 10-8) and 2 nearly significant regions (P < 9 × 10-8) containing several genes of interest, including NRG3 and HCN1, were identified for 7 endophenotypes. For each of the 11 endophenotypes, enrichment analyses performed at the level of P < 10-4 compared favorably with previous association results in the COGS-1 families and showed extensive overlap with regions identified for schizophrenia diagnosis. Conclusions and Relevance: These analyses identified several genomic regions of interest that require further exploration and validation. These data seem to demonstrate the utility of endophenotypes for resolving the genetic architecture of schizophrenia and characterizing the underlying biological dysfunctions. Understanding the molecular basis of these endophenotypes may help to identify novel treatment targets and pave the way for precision-based medicine in schizophrenia and related psychotic disorders.
Importance: The Consortium on the Genetics of Schizophrenia (COGS) uses quantitative neurophysiological and neurocognitive endophenotypes with demonstrated deficits in schizophrenia as a platform from which to explore the underlying neural circuitry and genetic architecture. Many of these endophenotypes are associated with poor functional outcome in schizophrenia. Some are also endorsed as potential treatment targets by the US Food and Drug Administration. Objective: To build on prior assessments of heritability, association, and linkage in the COGS phase 1 (COGS-1) families by reporting a genome-wide association study (GWAS) of 11 schizophrenia-related endophenotypes in the independent phase 2 (COGS-2) cohort of patients with schizophrenia and healthy comparison participants (HCPs). Design, Setting, and Participants: A total of 1789 patients with schizophrenia and HCPs of self-reported European or Latino ancestry were recruited through a collaborative effort across the COGS sites and genotyped using the PsychChip. Standard quality control filters were applied, and more than 6.2 million variants with a genotyping call rate of greater than 0.99 were available after imputation. Association was performed for data sets stratified by diagnosis and ancestry using linear regression and adjusting for age, sex, and 5 principal components, with results combined through weighted meta-analysis. Data for COGS-1 were collected from January 6, 2003, to August 6, 2008; data for COGS-2, from June 30, 2010, to February 14, 2014. Data were analyzed from October 28, 2016, to May 4, 2018. Main Outcomes and Measures: A genome-wide association study was performed to evaluate association for 11 neurophysiological and neurocognitive endophenotypes targeting key domains of schizophrenia related to inhibition, attention, vigilance, learning, working memory, executive function, episodic memory, and social cognition. Results: The final sample of 1533 participants included 861 male participants (56.2%), and the mean (SD) age was 41.8 (13.6) years. In total, 7 genome-wide significant regions (P < 5 × 10-8) and 2 nearly significant regions (P < 9 × 10-8) containing several genes of interest, including NRG3 and HCN1, were identified for 7 endophenotypes. For each of the 11 endophenotypes, enrichment analyses performed at the level of P < 10-4 compared favorably with previous association results in the COGS-1 families and showed extensive overlap with regions identified for schizophrenia diagnosis. Conclusions and Relevance: These analyses identified several genomic regions of interest that require further exploration and validation. These data seem to demonstrate the utility of endophenotypes for resolving the genetic architecture of schizophrenia and characterizing the underlying biological dysfunctions. Understanding the molecular basis of these endophenotypes may help to identify novel treatment targets and pave the way for precision-based medicine in schizophrenia and related psychotic disorders.
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