1
|
Abplanalp SJ, Braff DL, Light GA, Joshi YB, Nuechterlein KH, Green MF. Clarifying directional dependence among measures of early auditory processing and cognition in schizophrenia: leveraging Gaussian graphical models and Bayesian networks. Psychol Med 2024:1-10. [PMID: 38287656 DOI: 10.1017/s0033291724000023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
BACKGROUND Research using latent variable models demonstrates that pre-attentive measures of early auditory processing (EAP) and cognition may initiate a cascading effect on daily functioning in schizophrenia. However, such models fail to account for relationships among individual measures of cognition and EAP, thereby limiting their utility. Hence, EAP and cognition may function as complementary and interacting measures of brain function rather than independent stages of information processing. Here, we apply a data-driven approach to identifying directional relationships among neurophysiologic and cognitive variables. METHODS Using data from the Consortium on the Genetics of Schizophrenia 2, we estimated Gaussian Graphical Models and Bayesian networks to examine undirected and directed connections between measures of EAP, including mismatch negativity and P3a, and cognition in 663 outpatients with schizophrenia and 630 control participants. RESULTS Chain structures emerged among EAP and attention/vigilance measures in schizophrenia and control groups. Concerning differences between the groups, object memory was an influential variable in schizophrenia upon which other cognitive domains depended, and working memory was an influential variable in controls. CONCLUSIONS Measures of EAP and attention/vigilance are conditionally independent of other cognitive domains that were used in this study. Findings also revealed additional causal assumptions among measures of cognition that could help guide statistical control and ultimately help identify early-stage targets or surrogate endpoints in schizophrenia.
Collapse
Affiliation(s)
- Samuel J Abplanalp
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - David L Braff
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Gregory A Light
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Yash B Joshi
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael F Green
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
2
|
Joshi YB, Molina JL, Braff DL, Green MF, Gur RC, Gur RE, Nuechterlein KH, Stone WS, Greenwood TA, Lazzeroni LC, Radant AD, Silverman JM, Sprock J, Sugar CA, Tsuang DW, Tsuang MT, Turetsky BI, Swerdlow NR, Light GA. Sensitivity of Schizophrenia Endophenotype Biomarkers to Anticholinergic Medication Burden. Am J Psychiatry 2023; 180:519-523. [PMID: 37038743 DOI: 10.1176/appi.ajp.20220649] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Affiliation(s)
- Yash B Joshi
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Juan L Molina
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - David L Braff
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Michael F Green
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Ruben C Gur
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Raquel E Gur
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Keith H Nuechterlein
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - William S Stone
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Tiffany A Greenwood
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Laura C Lazzeroni
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Allen D Radant
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Jeremy M Silverman
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Joyce Sprock
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Catherine A Sugar
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Debby W Tsuang
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Ming T Tsuang
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Bruce I Turetsky
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Neal R Swerdlow
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| | - Gregory A Light
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System (Joshi, Molina, Braff, Sprock, Swerdlow, Light); Department of Psychiatry, University of California, San Diego (Joshi, Molina, Braff, Greenwood, Sprock, M. Tsuang, Swerdlow, Light); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Green, Neuchterlein); Desert Pacific Mental Illness Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles (Green, Sugar); Department of Psychiatry, University of Pennsylvania, Philadelphia (Ruben C. Gur, Raquel E. Gur, Turetsky); Department of Psychiatry, Harvard Medical School, Boston (Stone); Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston (Stone); Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford (Lazzeroni); Department of Biomedical Data Science, Stanford University, Stanford (Lazzeroni); Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle (Radant, D. Tsuang); Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle (D. Tsuang); Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York (Silverman); Research & Development, James J. Peters VA Medical Center, New York (Silverman); Department of Biostatistics, UCLA School of Public Health, Los Angeles (Sugar)
| |
Collapse
|
3
|
Abplanalp SJ, Braff DL, Light GA, Nuechterlein KH, Green MF. Understanding Connections and Boundaries Between Positive Symptoms, Negative Symptoms, and Role Functioning Among Individuals With Schizophrenia: A Network Psychometric Approach. JAMA Psychiatry 2022; 79:1014-1022. [PMID: 35976655 PMCID: PMC9386606 DOI: 10.1001/jamapsychiatry.2022.2386] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 06/28/2022] [Indexed: 11/14/2022]
Abstract
Importance Improved understanding of the boundaries and connections between positive symptoms, negative symptoms, and role functioning in schizophrenia is critical, given limited empirical support for clear distinctions among these clinical areas. This study's use of network psychometrics to investigate differential associations and structural overlap between positive symptoms, negative symptoms, and functional domains in schizophrenia may contribute to such understanding. Objective To apply network analysis and community detection methods to examine the interplay and structure of positive symptoms, negative symptoms, and functional domains in individuals with schizophrenia. Design, Setting, and Participants Cross-sectional study in 5 geographically distributed research centers in the US as part of the Consortium on the Genetics of Schizophrenia-2 from July 1, 2010, through January 31, 2014. Data were analyzed from November 2021 to June 2022. Clinically stable outpatients with schizophrenia or schizoaffective disorder were included. Participants were excluded if they had evidence of neurologic or additional Axis I psychiatric disorders. Other exclusion criteria included head injury, stroke, and substance abuse. Of 1415 patients approached, 979 were included in the final analysis. Main Outcomes and Measures Measures included the Scale for the Assessment of Positive Symptoms, the Scale for the Assessment of Negative Symptoms, and the Role Functioning Scale. Main outcomes were expected influence, which assesses the relative importance of items to the network and is defined as the association of an item with all others, and community detection and stability, defined as the presence of statistical clusters and their replicability. Results Participants with complete data included 979 outpatients (mean [SD] age, 46 [11] years; 663 male [67.7%]; 390 participants [40%] self-identified as African American, 30 [3%] as Asian, 7 [0.7%] as Native American, 8 [0.8%] as Pacific Islander, 412 [42.1%] as White, 125 [12.8%] as more than 1 race, and 5 [0.5%] did not identify). Anhedonia had the highest expected influence in the most comprehensive network analysis, showing connections with negative and positive symptoms and functional domains. Positive symptoms had the lowest expected influence. Community detection analyses indicated the presence of 3 clusters corresponding to positive symptoms; negative symptoms and work functioning; functional domains, including independent living, family relationships, and social network; and avolition, anhedonia, and work functioning. Hallucinations and delusions replicated in 1000 bootstrapped samples (100%), while bizarre behavior and thought disorder replicated in 390 (39%) and 570 (57%), respectively. In contrast, negative symptoms and work functioning replicated between 730 (73%) and 770 (77%) samples, respectively, and the remaining functional domains in 940 samples (94%). Conclusions and Relevance The high centrality of anhedonia and its connections with multiple functional domains suggest that it could be a treatment target for global functioning. Interventions for work functioning may benefit from a specialized approach that focuses primarily on avolition.
Collapse
Affiliation(s)
- Samuel J. Abplanalp
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - David L. Braff
- Desert Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego
| | - Gregory A. Light
- Desert Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, California
- Department of Psychiatry, University of California San Diego
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| | - Michael F. Green
- Desert Pacific Mental Illness Research, Education and Clinical Center, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, California
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles
| |
Collapse
|
4
|
Hanks SC, Forer L, Schönherr S, LeFaive J, Martins T, Welch R, Gagliano Taliun SA, Braff D, Johnsen JM, Kenny EE, Konkle BA, Laakso M, Loos RF, McCarroll S, Pato C, Pato MT, Smith AV, Boehnke M, Scott LJ, Fuchsberger C. Extent to which array genotyping and imputation with large reference panels approximate deep whole-genome sequencing. Am J Hum Genet 2022; 109:1653-1666. [PMID: 35981533 PMCID: PMC9502057 DOI: 10.1016/j.ajhg.2022.07.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 07/20/2022] [Indexed: 01/02/2023] Open
Abstract
Understanding the genetic basis of human diseases and traits is dependent on the identification and accurate genotyping of genetic variants. Deep whole-genome sequencing (WGS), the gold standard technology for SNP and indel identification and genotyping, remains very expensive for most large studies. Here, we quantify the extent to which array genotyping followed by genotype imputation can approximate WGS in studies of individuals of African, Hispanic/Latino, and European ancestry in the US and of Finnish ancestry in Finland (a population isolate). For each study, we performed genotype imputation by using the genetic variants present on the Illumina Core, OmniExpress, MEGA, and Omni 2.5M arrays with the 1000G, HRC, and TOPMed imputation reference panels. Using the Omni 2.5M array and the TOPMed panel, ≥90% of bi-allelic single-nucleotide variants (SNVs) are well imputed (r2 > 0.8) down to minor-allele frequencies (MAFs) of 0.14% in African, 0.11% in Hispanic/Latino, 0.35% in European, and 0.85% in Finnish ancestries. There was little difference in TOPMed-based imputation quality among the arrays with >700k variants. Individual-level imputation quality varied widely between and within the three US studies. Imputation quality also varied across genomic regions, producing regions where even common (MAF > 5%) variants were consistently not well imputed across ancestries. The extent to which array genotyping and imputation can approximate WGS therefore depends on reference panel, genotype array, sample ancestry, and genomic location. Imputation quality by variant or genomic region can be queried with our new tool, RsqBrowser, now deployed on the Michigan Imputation Server.
Collapse
Affiliation(s)
- Sarah C. Hanks
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Jonathon LeFaive
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Taylor Martins
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ryan Welch
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Sarah A. Gagliano Taliun
- Department of Medicine and Department of Neurosciences, Université de Montréal, Montreal, QC, Canada,Research Centre, Montreal Heart Institute, Montreal, QC, Canada
| | - David Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jill M. Johnsen
- Research Institute, Bloodworks, Seattle, WA, USA,Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eimear E. Kenny
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Ruth F.J. Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Carlos Pato
- Departments of Psychiatry, Rutgers University, Robert Wood Johnson Medical School and New Jersey Medical School, New Brunswick, NJ, USA
| | - Michele T. Pato
- Departments of Psychiatry, Rutgers University, Robert Wood Johnson Medical School and New Jersey Medical School, New Brunswick, NJ, USA
| | - Albert V. Smith
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | | | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Laura J. Scott
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Christian Fuchsberger
- Institute for Biomedicine (Affiliated with the University of Lübeck), Eurac Research, Bolzano, Italy.
| |
Collapse
|
5
|
Guardiola-Ripoll M, Almodóvar-Payá C, Lubeiro A, Salvador R, Salgado-Pineda P, Gomar JJ, Guerrero-Pedraza A, Sarró S, Maristany T, Fernández-Linsenbarth I, Hernández-García M, Papiol S, Molina V, Pomarol-Clotet E, Fatjó-Vilas M. New insights of the role of the KCNH2 gene in schizophrenia: An fMRI case-control study. Eur Neuropsychopharmacol 2022; 60:38-47. [PMID: 35635995 DOI: 10.1016/j.euroneuro.2022.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 04/14/2022] [Accepted: 04/19/2022] [Indexed: 11/04/2022]
Abstract
The KCNH2 gene, encoding for a subunit of a voltage-gated potassium channel, has been identified as a key element of neuronal excitability and a promising novel therapeutic target for schizophrenia (SZ). Nonetheless, evidence highlighting the role of KCNH2 on cognitive and brain activity phenotypes comes mainly from studies based on healthy controls (HC). Therefore, we aimed to study the role of KCNH2 on the brain functional differences between patients with SZ and HC. The fMRI sample comprised 78 HC and 79 patients with SZ (matched for age, sex and premorbid IQ). We studied the effect of the polymorphism KCNH2-rs3800779 on attention and working memory-related brain activity, evaluated through the N-back task, in regions with detected diagnostic differences (regression model, controlled for age, sex and premorbid IQ, FEAT-FSL). We report a significant diagnosis x KCNH2 interaction on brain activity (1-back vs baseline contrast) at the medial superior prefrontal cortex (Zmax=3.55, p = 0.00861). In this region, patients with SZ carrying the risk genotype (AA) show a deactivation failure, while HC depict the opposite pattern towards deactivation. The brain region with significant diagnosis x KCNH2 interaction has been previously associated with SZ. The results of this study, in which the role of KCNH2 on fMRI response is analysed for the first time in patients, suggest that KCNH2 variability contributes to inefficient brain activity modulation during the N-back task in affected subjects. These data may pave the way to further understand how KCNH2 genetic variability is related to the pathophysiological mechanisms underlying schizophrenia.
Collapse
Affiliation(s)
- Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Alba Lubeiro
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Jesús J Gomar
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; The Litwin-Zucker Alzheimer's Research Center, NY, United States
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; Hospital Benito Menni-CASM, Sant Boi de Llobregat, Barcelona, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain
| | - Teresa Maristany
- Diagnostic Imaging Department, Hospital Sant Joan de Déu Research Foundation, Barcelona, Spain
| | | | - Marta Hernández-García
- Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain
| | - Sergi Papiol
- CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany; Department of Psychiatry, University Hospital, Ludwig Maximilian University, Munich Germany
| | - Vicente Molina
- Psychiatry Department, School of Medicine, University of Valladolid, Valladolid, Spain; Neurosciences Institute of Castilla y León (INCYL), University of Salamanca, Salamanca, Spain; Psychiatry Service, University Hospital of Valladolid, Valladolid, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain.
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, Barcelona, Spain; CIBERSAM (Biomedical Research Network in Mental Health, Instituto de Salud Carlos III), Madrid, Spain; Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona; Barcelona, Spain.
| |
Collapse
|
6
|
Proshin AT. Comparative Analysis of Dopaminergic and Cholinergic Mechanisms of Sensory and Sensorimotor Gating in Healthy Individuals and in Patients With Schizophrenia. Front Behav Neurosci 2022; 16:887312. [PMID: 35846783 PMCID: PMC9282644 DOI: 10.3389/fnbeh.2022.887312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2022] Open
Abstract
Sensory and sensorimotor gating provide the early processing of information under conditions of rapid presentation of multiple stimuli. Gating deficiency is observed in various psychopathologies, in particular, in schizophrenia. However, there is also a significant proportion of people in the general population with low filtration rates who do not show any noticeable cognitive decline. The review article presents a comparative analysis of existing data on the peculiarities of cholinergic and dopaminergic mechanisms associated with lowering gating in healthy individuals and in patients with schizophrenia. The differences in gating mechanisms in cohorts of healthy individuals and those with schizophrenia are discussed.
Collapse
|
7
|
Joshi YB, Thomas ML, Braff DL, Green MF, Gur RC, Gur RE, Nuechterlein KH, Stone WS, Greenwood TA, Lazzeroni LC, MacDonald LR, Molina JL, Nungaray JA, Radant AD, Silverman JM, Sprock J, Sugar CA, Tsuang DW, Tsuang MT, Turetsky BI, Swerdlow NR, Light GA. Anticholinergic Medication Burden-Associated Cognitive Impairment in Schizophrenia. Am J Psychiatry 2021; 178:838-847. [PMID: 33985348 PMCID: PMC8440496 DOI: 10.1176/appi.ajp.2020.20081212] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Many psychotropic medications used to treat schizophrenia have significant anticholinergic properties, which are linked to cognitive impairment and dementia risk in healthy subjects. Clarifying the impact of cognitive impairment attributable to anticholinergic medication burden may help optimize cognitive outcomes in schizophrenia. The aim of this study was to comprehensively characterize how this burden affects functioning across multiple cognitive domains in schizophrenia outpatients. METHODS Cross-sectional data were analyzed using inferential statistics and exploratory structural equation modeling to determine the relationship between anticholinergic medication burden and cognition. Patients with a diagnosis of schizophrenia or schizoaffective disorder (N=1,120) were recruited from the community at five U.S. universities as part of the Consortium on the Genetics of Schizophrenia-2. For each participant, prescribed medications were rated and summed according to a modified Anticholinergic Cognitive Burden (ACB) scale. Cognitive functioning was assessed by performance on domains of the Penn Computerized Neurocognitive Battery (PCNB). RESULTS ACB score was significantly associated with cognitive performance, with higher ACB groups scoring worse than lower ACB groups on all domains tested on the PCNB. Similar effects were seen on other cognitive tests. Effects remained significant after controlling for demographic characteristics and potential proxies of illness severity, including clinical symptoms and chlorpromazine-equivalent antipsychotic dosage. CONCLUSIONS Anticholinergic medication burden in schizophrenia is substantial, common, conferred by multiple medication classes, and associated with cognitive impairments across all cognitive domains. Anticholinergic medication burden from all medication classes-including psychotropics used in usual care-should be considered in treatment decisions and accounted for in studies of cognitive functioning in schizophrenia.
Collapse
Affiliation(s)
- Yash B. Joshi
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| | | | - David L. Braff
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles,Desert Pacific Mental Illness Research, Education, and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia
| | | | - William S. Stone
- Department of Psychiatry, Harvard Medical School, and Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston
| | | | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences and Department of Biomedical Data Science, Stanford University, Stanford, Calif,Sierra Pacific Mental Illness Research, Education, and Clinical Center, VA Health Care System, Palo Alto, Calif
| | - Laura R. MacDonald
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| | - Juan L. Molina
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| | - John A. Nungaray
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle,Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle
| | - Jeremy M. Silverman
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York,Research and Development, James J. Peters VA Medical Center, New York
| | - Joyce Sprock
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles,Department of Biostatistics, UCLA School of Public Health, Los Angeles
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle,Northwest Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla
| | | | - Neal R. Swerdlow
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Gregory A. Light
- Desert Pacific Mental Illness Research, Education, and Clinical Center, VA San Diego Healthcare System, San Diego,Department of Psychiatry, University of California, San Diego, La Jolla
| |
Collapse
|
8
|
Wu Q, He J, Fang S, Zhang P, Luo X, Zhang J, Xiong Y, Luo F, Wang X, Yao S, Wang X. A novel construct of anhedonia revealed in a Chinese sample via the Revised Physical and Social Anhedonia Scales. BMC Psychiatry 2020; 20:529. [PMID: 33167901 PMCID: PMC7650163 DOI: 10.1186/s12888-020-02900-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 09/28/2020] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Anhedonia is a core clinical symptom of mental disorders. The Revised Physical Anhedonia Scale (RPAS) and the Revised Social Anhedonia Scale (RSAS) have been applied in clinical and non-clinical samples since 1980s. However, the construct of a unified RPAS&RSAS for comprehensive measurement of anhedonia has never been explored. Therefore, the purpose of our study was to examine the factor structure of the unified RPAS&RSAS among undergraduates and clinical patients. METHODS A total of 3435 undergraduates from two universities and 294 clinical patients with mental disorders had completed the Chinese version of the RPAS and the RSAS. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were each conducted to reveal the constructs of the RPAS and the RSAS. CFA was used to evaluate first- and second-order models for the unified RPAS&RSAS in undergraduates and clinical patients. The internal consistency and test-retest reliability of the RPAS and the RSAS were also evaluated. RESULTS EFA and CFA indicated 2-factor structures for RPAS and RSAS, with the factors being defined as anticipatory anhedonia and consummatory anhedonia. The second-order model of the unified RPAS&RSAS in the undergraduates and clinical patients both had satisfactory fit index values (Undergraduate sample: CFI = 0.901, TLI = 0.899, RMSEA = 0.055, SRMR = 0.086; Clinical sample: CFI = 0.922, TLI = 0.911, RMSEA = 0.052, SRMR = 0.078). The psychometric robustness of the RPAS&RSAS were confirmed by high internal consistency and test-retest reliability values. CONCLUSIONS The unified RPAS&RSAS with a second-order structure was confirmed in both undergraduates and clinical samples in Chinese. The construct of anhedonia was refreshed as covering physical and social domains, and each of them includes both anticipatory and consummatory components.
Collapse
Affiliation(s)
- Qiongqiong Wu
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China
| | - Jiayue He
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China
| | - Shulin Fang
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China
| | - Panwen Zhang
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China
| | - Xingwei Luo
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China
| | - Jianghua Zhang
- grid.216417.70000 0001 0379 7164Student Affairs Department, Central South University, Changsha, 410083 China
| | - Yan Xiong
- grid.216417.70000 0001 0379 7164Student Affairs Department, Central South University, Changsha, 410083 China
| | - Fusheng Luo
- grid.440660.00000 0004 1761 0083Student Affairs Department, Central South University of Forestry and Technology, Changsha, 410004 China
| | - Xiaosheng Wang
- grid.216417.70000 0001 0379 7164Department of Human Anatomy and Neurobiology, Xiangya School of Medicine, Central South University, Changsha, 410013 China
| | - Shuqiao Yao
- grid.216417.70000 0001 0379 7164Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011 China ,grid.216417.70000 0001 0379 7164Medical Psychological Institute of Central South University, Changsha, 410011 China ,National Clinical Research Center for Mental Disorders, Changsha, 410011 China
| | - Xiang Wang
- Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, 410011, China. .,Medical Psychological Institute of Central South University, Changsha, 410011, China. .,National Clinical Research Center for Mental Disorders, Changsha, 410011, China.
| |
Collapse
|
9
|
Fatjó-Vilas M, Soler J, Ibáñez MI, Moya-Higueras J, Ortet G, Guardiola-Ripoll M, Fañanás L, Arias B. The effect of the AKT1 gene and cannabis use on cognitive performance in healthy subjects. J Psychopharmacol 2020; 34:990-998. [PMID: 32536252 DOI: 10.1177/0269881120928179] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Evidence suggests that the AKT1 gene may modulate the degree to which cannabis use induces cognitive alterations in patients with a psychotic disorder. AIM To examine the interplay between AKT1 and cannabis use in terms of the cognitive performance of the general population. METHODS Our sample consisted of 389 Spanish university students. Sustained attention was measured via the Continuous Performance Test-Identical Pairs, immediate and delayed verbal memory with the Logical Memory subtest of the Wechsler Memory Scale, and working memory with the Wisconsin Card Sorting Test. Lifetime cannabis use frequency was assessed and individuals were classified as cannabis users or non-users. Two single nucleotide polymorphisms of the AKT1 gene were genotyped and, according to previous studies, each subject was defined as a carrier of two, one or no copies of the haplotype (rs2494732(C)-rs1130233(A)). Multiple linear regressions were conducted to test the effect of the genetic variability and cannabis use (and their interaction) on cognitive performance. RESULTS An effect of the AKT1 haplotype was found on attention scores: individuals with two copies of the haplotype performed better (β=0.18, p<0.001 (adjusted for false discovery rate)), while neither cannabis nor the AKT1-cannabis interaction was associated with attention. No effect of AKT1, cannabis or the AKT1-cannabis interaction was found on verbal memory or working memory. CONCLUSIONS Our study provides additional evidence that AKT1 modulates cognitive performance. However, in our non-clinical sample, the previously reported interaction between cannabis use and the AKT1 gene was not replicated.
Collapse
Affiliation(s)
- M Fatjó-Vilas
- FIDMAG Sisters Hospitallers Research Foundation, Barcelona, Spain.,Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Spain.,Biomedicine Institute of the University of Barcelona (IBUB), Spain.,Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - J Soler
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Spain.,Biomedicine Institute of the University of Barcelona (IBUB), Spain
| | - M I Ibáñez
- Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - J Moya-Higueras
- Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Department of Psychology, Faculty of Education, Psychology and Social Work, University of Lleida, Lleida, Spain
| | - G Ortet
- Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain.,Department of Basic and Clinical Psychology and Psychobiology, University Jaume I, Castelló, Spain
| | - M Guardiola-Ripoll
- FIDMAG Sisters Hospitallers Research Foundation, Barcelona, Spain.,Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - L Fañanás
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Spain.,Biomedicine Institute of the University of Barcelona (IBUB), Spain.,Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - B Arias
- Department of Evolutionary Biology, Ecology and Environmental Sciences, Faculty of Biology, University of Barcelona, Spain.,Biomedicine Institute of the University of Barcelona (IBUB), Spain.,Mental Health Networking Biomedical Research Centre (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| |
Collapse
|
10
|
The effects of age and sex on cognitive impairment in schizophrenia: Findings from the Consortium on the Genetics of Schizophrenia (COGS) study. PLoS One 2020; 15:e0232855. [PMID: 32401791 PMCID: PMC7219730 DOI: 10.1371/journal.pone.0232855] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 04/22/2020] [Indexed: 01/05/2023] Open
Abstract
Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.
Collapse
|
11
|
Harvey PD, Sun N, Bigdeli TB, Fanous AH, Aslan M, Malhotra AK, Lu Q, Hu Y, Li B, Chen Q, Mane S, Miller P, Rajeevan N, Sayward F, Cheung KH, Li Y, Greenwood TA, Gur RE, Braff DL, Brophy M, Pyarajan S, O'Leary TJ, Gleason T, Przygodszki R, Muralidhar S, Gaziano JM, Concato J, Zhao H, Siever LJ. Genome-wide association study of cognitive performance in U.S. veterans with schizophrenia or bipolar disorder. Am J Med Genet B Neuropsychiatr Genet 2020; 183:181-194. [PMID: 31872970 DOI: 10.1002/ajmg.b.32775] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 11/22/2019] [Accepted: 12/09/2019] [Indexed: 12/25/2022]
Abstract
Cognitive impairment is a frequent and serious problem in patients with various forms of severe mental illnesses (SMI), including schizophrenia (SZ) and bipolar disorder (BP). Recent research suggests genetic links to several cognitive phenotypes in both SMI and in the general population. Our goal in this study was to identify potential genomic signatures of cognitive functioning in veterans with severe mental illness and compare them to previous findings for cognition across different populations. Veterans Affairs (VA) Cooperative Studies Program (CSP) Study #572 evaluated cognitive and functional capacity measures among SZ and BP patients. In conjunction with the VA Million Veteran Program, 3,959 European American (1,095 SZ, 2,864 BP) and 2,601 African American (1,095 SZ, 2,864 BP) patients were genotyped using a custom Affymetrix Axiom Biobank array. We performed a genome-wide association study of global cognitive functioning, constructed polygenic scores for SZ and cognition in the general population, and examined genetic correlations with 2,626 UK Biobank traits. Although no single locus attained genome-wide significance, observed allelic effects were strongly consistent with previous studies. We observed robust associations between global cognitive functioning and polygenic scores for cognitive performance, intelligence, and SZ risk. We also identified significant genetic correlations with several cognition-related traits in UK Biobank. In a diverse cohort of U.S. veterans with SZ or BP, we demonstrate broad overlap of common genetic effects on cognition in the general population, and find that greater polygenic loading for SZ risk is associated with poorer cognitive performance.
Collapse
Affiliation(s)
- Philip D Harvey
- Research Service, Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, Florida.,Department of Psychiatry and Behavioral Sciences, University of Miami School of Medicine, Miami, Florida
| | - Ning Sun
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Tim B Bigdeli
- Department of Psychiatry, VA New York Harbor Healthcare System, Brooklyn, New York.,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Ayman H Fanous
- Department of Psychiatry, VA New York Harbor Healthcare System, Brooklyn, New York.,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, New York
| | - Mihaela Aslan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, New York.,Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, New York.,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, New York
| | - Qiongshi Lu
- Yale University School of Medicine, New Haven, Connecticut.,Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin
| | - Yiming Hu
- Yale University School of Medicine, New Haven, Connecticut
| | - Boyang Li
- Yale University School of Medicine, New Haven, Connecticut
| | - Quan Chen
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Shrikant Mane
- Yale University School of Medicine, New Haven, Connecticut
| | - Perry Miller
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Kei-Hoi Cheung
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | | | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine and Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,Department of Child & Adolescent Psychiatry and Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine and Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - David L Braff
- Department of Psychiatry, University of California, San Diego, California.,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, California
| | | | - Mary Brophy
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts.,Boston University School of Medicine, Boston, Massachusetts
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts
| | - Timothy J O'Leary
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Ronald Przygodszki
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, District of Columbia
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology Research, and Information Center (MAVERIC), Jamaica Plain, Massachusetts.,Department of Medicine, Harvard University, Boston, Massachusetts
| | - John Concato
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Hongyu Zhao
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, Connecticut.,Yale University School of Medicine, New Haven, Connecticut
| | - Larry J Siever
- James J. Peters Veterans Affairs Medical Center, Bronx, New York.,Department of Psychiatry, Mount Sinai School of Medicine, New York, New York
| |
Collapse
|
12
|
Hochberger WC, Thomas ML, Joshi YB, Swerdlow NR, Braff DL, Gur RE, Gur RC, Light GA. Deviation from expected cognitive ability is a core cognitive feature of schizophrenia related to neurophysiologic, clinical and psychosocial functioning. Schizophr Res 2020; 215:300-307. [PMID: 31744751 DOI: 10.1016/j.schres.2019.10.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 10/03/2019] [Accepted: 10/06/2019] [Indexed: 11/26/2022]
Abstract
Cognitive functioning in schizophrenia is characterized by a generalized impairment in current cognitive ability based on traditional population-based norms. However, these norms assume a normal cognitive trajectory and do not directly account for illness-related declines from expected cognitive potential. Indeed, schizophrenia patients exhibit even greater deviation between their observed and expected cognitive functioning based on expanded norms that leverage premorbid variables resistant to illness-related features. The current study further quantified the extent to which illness-related features account for this deviation from expectation and assessed its relationship to neurophysiologic (mismatch negativity, P3a, theta oscillations), clinical, and psychosocial functioning in schizophrenia patients. Expected cognitive ability (PENN-CNB global cognition) in patients (n = 684) was calculated using healthy comparison subject (n = 660) weighted regression based on premorbid variables resistant to illness-related decline (demographics, single-word reading, parental education). The magnitude of any deviation between current (observed) and regression-predicted (expected) cognitive ability was calculated. Results indicated that 24% (n = 164) of the total patient population exhibited significant (≥-1.96 SD) deviation between observed and expected global cognitive ability. Interestingly, 20% of the total patient population (n = 136) had "normal" range cognitive performance when using traditional population-based norms, but also had significant deviation from expected cognitive ability. The magnitude of this deviation was associated with more severe neurophysiologic abnormalities, longer illness duration, higher levels of negative symptoms, and worse psychosocial functioning. Assessment of cognitive deviation is thus a complementary metric for characterizing the severity of illness-related cognitive declines in patients, while also reflecting the expression and severity of key endophenotypes of schizophrenia.
Collapse
Affiliation(s)
- W C Hochberger
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - M L Thomas
- Department of Psychology, Colorado State University, Fort Collins, CO, USA
| | - Y B Joshi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - N R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - D L Braff
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - G A Light
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
| | | |
Collapse
|
13
|
Hochberger WC, Joshi YB, Zhang W, Thomas ML, Braff DL, Swerdlow NR, Light GA. Decomposing the constituent oscillatory dynamics underlying mismatch negativity generation in schizophrenia: Distinct relationships to clinical and cognitive functioning. Int J Psychophysiol 2019; 145:23-29. [PMID: 30586570 PMCID: PMC7261144 DOI: 10.1016/j.ijpsycho.2018.12.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 12/04/2018] [Accepted: 12/21/2018] [Indexed: 12/31/2022]
Abstract
Abnormalities in early auditory information processing (EAIP) contribute to higher-order deficits in cognition and psychosocial functioning in schizophrenia. A passive auditory oddball paradigm is commonly used to evoke event-related potential (ERP) measures of EAIP reflecting auditory sensory registration and deviance detection, including mismatch negativity (MMN) and P3a responses. MMN and P3a have been extensively studied in healthy subjects and neuropsychiatric patient populations and are increasingly used as translational biomarkers in the development of novel therapeutics. Despite widespread use, relatively few studies have examined the constituent oscillatory elements and the extent to which sensory registration and deviance detection represent distinct or intercorrelated processes. This study aimed to determine the factor structure and clinical correlates of these oscillatory measures in schizophrenia patients (n = 706) and healthy comparison subjects (n = 615) who underwent clinical, cognitive, and functional characterization and EEG testing via their participation in the Consortium of Genomics in Schizophrenia (COGS-2) study. Results revealed significant deficits in theta-band (4-7 Hz) evoked power and phase locking in patients. Exploratory factor analyses of both ERP and oscillatory measures revealed two dissociable factors reflecting sensory registration and deviance detection. While each factor shared a significant correlation with social cognition, the deviance detection factor had a unique relationship to multiple cognitive and clinical domains. Results support the continued advancement of functionally relevant oscillatory measures underlying EAIP in the development of precognitive therapeutics.
Collapse
Affiliation(s)
- W C Hochberger
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States of America; Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
| | - Y B Joshi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
| | - W Zhang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
| | - M L Thomas
- Colorado State University, Department of Psychology, Fort Collins, CO, United States of America
| | - D L Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
| | - N R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America
| | - G A Light
- VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States of America; Department of Psychiatry, University of California San Diego, La Jolla, CA, United States of America.
| |
Collapse
|
14
|
Tsuang DW, Greenwood TA, Jayadev S, Davis M, Shutes-David A, Bird TD. A Genetic Study of Psychosis in Huntington's Disease: Evidence for the Involvement of Glutamate Signaling Pathways. J Huntingtons Dis 2019; 7:51-59. [PMID: 29480208 DOI: 10.3233/jhd-170277] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Psychotic symptoms of delusions and hallucinations occur in about 5% of persons with Huntington's disease (HD). The mechanisms underlying these occurrences are unknown, but the same symptoms also occur in schizophrenia, and thus genetic risk factors for schizophrenia may be relevant to the development of psychosis in HD. OBJECTIVE To investigate the possible role of genes associated with schizophrenia in the occurrence of psychotic symptoms in HD. METHODS DNA from subjects with HD and psychosis (HD+P; n = 47), subjects with HD and no psychosis (HD-P; n = 126), and controls (CTLs; n = 207) was genotyped using the Infinium PsychArray-24 v1.1 BeadChip. The allele frequencies of single-nucleotide polymorphisms (SNPs) that were previously associated with schizophrenia and related psychiatric disorders were compared between these groups. RESULTS Of the 30 candidate genes tested, 10 showed an association with psychosis in HD. The majority of these genes, including CTNNA2, DRD2, ERBB4, GRID2, GRIK4, GRM1, NRG1, PCNT, RELN, and SLC1A2, demonstrate network interactions related to glutamate signaling. CONCLUSIONS This study suggests genetic associations between several previously identified candidate genes for schizophrenia and the occurrence of psychotic symptoms in HD. These data support the potential role of genes related to glutamate signaling in HD psychosis.
Collapse
Affiliation(s)
- Debby W Tsuang
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA.,Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.,Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA
| | - Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Suman Jayadev
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Marie Davis
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA.,Department of Neurology, University of Washington, Seattle, WA, USA
| | - Andrew Shutes-David
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA.,Mental Illness Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA
| | - Thomas D Bird
- Geriatric Research, Education, and Clinical Center, VA Puget Sound Health Care System, Seattle, WA, USA.,Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA.,Department of Neurology, University of Washington, Seattle, WA, USA
| |
Collapse
|
15
|
Alliey-Rodriguez N, Grey TA, Shafee R, Asif H, Lutz O, Bolo NR, Padmanabhan J, Tandon N, Klinger M, Reis K, Spring J, Coppes L, Zeng V, Hegde RR, Hoang DT, Bannai D, Nawaz U, Henson P, Liu S, Gage D, McCarroll S, Bishop JR, Hill S, Reilly JL, Lencer R, Clementz BA, Buckley P, Glahn DC, Meda SA, Narayanan B, Pearlson G, Keshavan MS, Ivleva EI, Tamminga C, Sweeney JA, Curtis D, Badner JA, Keedy S, Rapoport J, Liu C, Gershon ES. NRXN1 is associated with enlargement of the temporal horns of the lateral ventricles in psychosis. Transl Psychiatry 2019; 9:230. [PMID: 31530798 PMCID: PMC6748921 DOI: 10.1038/s41398-019-0564-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 07/11/2019] [Accepted: 07/30/2019] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia, Schizoaffective, and Bipolar disorders share behavioral and phenomenological traits, intermediate phenotypes, and some associated genetic loci with pleiotropic effects. Volumetric abnormalities in brain structures are among the intermediate phenotypes consistently reported associated with these disorders. In order to examine the genetic underpinnings of these structural brain modifications, we performed genome-wide association analyses (GWAS) on 60 quantitative structural brain MRI phenotypes in a sample of 777 subjects (483 cases and 294 controls pooled together). Genotyping was performed with the Illumina PsychChip microarray, followed by imputation to the 1000 genomes multiethnic reference panel. Enlargement of the Temporal Horns of Lateral Ventricles (THLV) is associated with an intronic SNP of the gene NRXN1 (rs12467877, P = 6.76E-10), which accounts for 4.5% of the variance in size. Enlarged THLV is associated with psychosis in this sample, and with reduction of the hippocampus and enlargement of the choroid plexus and caudate. Eight other suggestively significant associations (P < 5.5E-8) were identified with THLV and 5 other brain structures. Although rare deletions of NRXN1 have been previously associated with psychosis, this is the first report of a common SNP variant of NRXN1 associated with enlargement of the THLV in psychosis.
Collapse
Affiliation(s)
- Ney Alliey-Rodriguez
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA.
| | - Tamar A. Grey
- 0000 0001 2341 2786grid.116068.8Massachusetts Institute of Technology, Cambridge, USA
| | - Rebecca Shafee
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Genetics, Boston, USA ,grid.66859.34Stanley Center, Broad Institute of MIT and Harvard, Cambridge, USA
| | - Huma Asif
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Olivia Lutz
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Nicolas R. Bolo
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Jaya Padmanabhan
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Neeraj Tandon
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Madeline Klinger
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Katherine Reis
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Jonathan Spring
- University of Chicago Laboratory for Advanced Computing, Chicago, USA
| | - Lucas Coppes
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Victor Zeng
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Rachal R. Hegde
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Dung T. Hoang
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Deepthi Bannai
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Uzma Nawaz
- 0000 0004 1936 7558grid.189504.1Boston University, Boston, USA
| | - Philip Henson
- 000000041936754Xgrid.38142.3cHarvard University, Cambridge, USA
| | - Siyuan Liu
- 0000 0001 2297 5165grid.94365.3dChild Psychiatry Branch, National Institutes of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Diane Gage
- grid.66859.34Broad Institute of MIT and Harvard, Cambridge, USA
| | | | - Jeffrey R. Bishop
- 0000000419368657grid.17635.36University of Minnesota, Department of Experimental and Clinical Pharmacology and Department of Psychiatry, Minneapolis, USA
| | - Scot Hill
- 0000 0004 0388 7807grid.262641.5Rosalind Franklin University, North Chicago, USA
| | - James L. Reilly
- 0000 0001 2299 3507grid.16753.36Northwestern University, Evanston, USA
| | - Rebekka Lencer
- 0000 0001 2172 9288grid.5949.1University of Muenster, Munster, Germany
| | - Brett A. Clementz
- 0000 0000 9564 9822grid.264978.6Department of Psychology, University of Georgia, Athens, Georgia
| | - Peter Buckley
- 0000 0004 0458 8737grid.224260.0Virginia Commonwealth University, Richmond, USA
| | - David C. Glahn
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Shashwath A. Meda
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Balaji Narayanan
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Godfrey Pearlson
- 0000000419368710grid.47100.32Yale University Departments of Psychiatry & Neuroscience, New Haven, USA
| | - Matcheri S. Keshavan
- 000000041936754Xgrid.38142.3cHarvard Medical School, Department of Psychiatry, Boston, USA
| | - Elena I. Ivleva
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - Carol Tamminga
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - John A. Sweeney
- 0000 0000 9482 7121grid.267313.2University of Texas Southwestern Medical Center, Department of Psychiatry, Dallas, USA
| | - David Curtis
- 0000 0001 2171 1133grid.4868.2University College London and Centre for Psychiatry, Barts and the London School of Medicine and Dentistry, London, UK
| | - Judith A. Badner
- 0000 0001 0705 3621grid.240684.cRush University Medical Center, Chicago, USA
| | - Sarah Keedy
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA
| | - Judith Rapoport
- 0000 0001 2297 5165grid.94365.3dChild Psychiatry Branch, National Institutes of Mental Health, National Institutes of Health, Bethesda, MD USA
| | - Chunyu Liu
- 0000 0000 9159 4457grid.411023.5SUNY Upstate Medical University, Binghamton, USA
| | - Elliot S. Gershon
- University of Chicago, Department of Psychiatry and Behavioral Neurosciences, Chicago, USA ,University of Chicago, Department of Human Genetics, Chicago, USA
| |
Collapse
|
16
|
Hurlimann T, Jaitovich Groisman I, Godard B. Exploring neurologists' perspectives on the return of next generation sequencing results to their patients: a needed step in the development of guidelines. BMC Med Ethics 2018; 19:81. [PMID: 30268121 PMCID: PMC6162934 DOI: 10.1186/s12910-018-0320-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2018] [Accepted: 09/12/2018] [Indexed: 12/12/2022] Open
Abstract
Background The use of Next Generation Sequencing such as Whole Genome Sequencing (WGS) is a promising step towards a better understanding and treatment of neurological diseases. WGS can result into unexpected information (incidental findings, IFs), and information with uncertain clinical significance. In the context of a Genome Canada project on ‘Personalized Medicine in the Treatment of Epilepsy’, we intended to address these challenges surveying neurologists’ opinions about the type of results that should be returned, and their professional responsibility toward recontacting patients regarding new discovered mutations. Methods Potential participants were contacted through professional organizations or direct invitations. Results A total of 204 neurologists were recruited. Fifty nine percent indicated that to be conveyed, WGS results should have a demonstrated clinical utility for diagnosis, prognosis or treatment. Yet, 41% deemed appropriate to return results without clinical utility, when they could impact patients’ reproductive decisions, or on patients’ request. Current use of targeted genetic testing and age of patients influenced respondents’ answers. Respondents stated that analysis of genomics data resulting from WGS should be limited to the genes likely to be relevant for the patient’s specific medical condition (69%), so as to limit IFs. Respondents felt responsible to recontact patients and inform them about newly discovered mutations related to the medical condition that triggered the test (75%) for as long as they are following up on the patient (55%). Finally, 53.5% of the respondents felt responsible to recontact and inform patients of clinically significant, newly discovered IFs. Conclusion Our results show the importance of formulating professional guidelines sensitive to the various – and sometimes opposite – viewpoints that may prevail within a same community of practice, as well as flexible so as to be attuned to the characteristics of the neurological conditions that triggered a WGS.
Collapse
Affiliation(s)
- Thierry Hurlimann
- Institut de recherche en santé publique, Université de Montréal, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada.,Quebec Population Health Research Network, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada
| | - Iris Jaitovich Groisman
- Institut de recherche en santé publique, Université de Montréal, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada
| | - Béatrice Godard
- Institut de recherche en santé publique, Université de Montréal, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada. .,Department of Social and Preventive Medicine, Université de Montréal, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada. .,Quebec Population Health Research Network, PO Box 6128, Station Centre-ville, Montreal, Quebec, H3C 3J7, Canada.
| |
Collapse
|
17
|
Swerdlow NR, Light GA, Thomas ML, Sprock J, Calkins ME, Green MF, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Stone WS, Sugar CA, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL. Deficient prepulse inhibition in schizophrenia in a multi-site cohort: Internal replication and extension. Schizophr Res 2018; 198:6-15. [PMID: 28549722 PMCID: PMC5700873 DOI: 10.1016/j.schres.2017.05.013] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Revised: 05/08/2017] [Accepted: 05/10/2017] [Indexed: 11/29/2022]
Abstract
BACKGROUND The Consortium on the Genetics of Schizophrenia (COGS) collected case-control endophenotype and genetic information from 2457 patients and healthy subjects (HS) across 5 test sites over 3.5 years. Analysis of the first "wave" (W1) of 1400 subjects identified prepulse inhibition (PPI) deficits in patients vs. HS. Data from the second COGS "wave" (W2), and the combined W(1+2), were used to assess: 1) the replicability of PPI deficits in this design; 2) the impact of response criteria on PPI deficits; and 3) PPI in a large cohort of antipsychotic-free patients. METHODS PPI in W2 HS (n=315) and schizophrenia patients (n=326) was compared to findings from W1; planned analyses assessed the impact of diagnosis, "wave" (1 vs. 2), and startle magnitude criteria. Combining waves allowed us to assess PPI in 120 antipsychotic-free patients, including many in the early course of illness. RESULTS ANOVA of all W(1+2) subjects revealed robust PPI deficits in patients across "waves" (p<0.0004). Strict response criteria excluded almost 39% of all subjects, disproportionately impacting specific subgroups; ANOVA in this smaller cohort confirmed no significant effect of "wave" or "wave x diagnosis" interaction, and a significant effect of diagnosis (p<0.002). Antipsychotic-free, early-illness patients had particularly robust PPI deficits. DISCUSSION Schizophrenia-linked PPI deficits were replicable across two multi-site "waves" of subjects collected over 3.5years. Strict response criteria disproportionately excluded older, male, non-Caucasian patients with low-normal hearing acuity. These findings set the stage for genetic analyses of PPI using the combined COGS wave 1 and 2 cohorts.
Collapse
Affiliation(s)
- Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Corresponding Author: Neal R. Swerdlow, M.D., Ph.D., University of California San Diego, Dept. of Psychiatry, 9500 Gilman Drive, La Jolla, CA 92093-0804 619-543-6270 (office); 619-543-2493 (fax);
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN 22, Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Michael L. Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN 22, Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN 22, Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | | | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Laura C. Lazzeroni
- Departments of Psychiatry and Behavioral Sciences and of Pediatrics, Stanford University, Stanford, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA,VISN 22, Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA,Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Institute for Genomic Medicine, University of California San Diego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN 22, Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| |
Collapse
|
18
|
Vora AK, Fisher AM, New AS, Hazlett EA, McNamara M, Yuan Q, Zhou Z, Hodgkinson C, Goldman D, Siever LJ, Roussos P, Perez-Rodriguez MM. Dimensional Traits of Schizotypy Associated With Glycine Receptor GLRA1 Polymorphism: An Exploratory Candidate-Gene Association Study. J Pers Disord 2018; 32:421-432. [PMID: 28758885 PMCID: PMC5856645 DOI: 10.1521/pedi_2017_31_303] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Schizotypy captures the underlying genetic vulnerability to schizophrenia. However, the genetic underpinnings of schizotypy remain unexplored. The authors examined the relationship between single nucleotide poly-morphisms (SNPs) and schizotypy. A sample of 137 subjects (43 healthy controls, 34 subjects with schizotypal personality disorder [SPD], 32 with borderline personality disorder, and 25 with other personality disorders) completed the Schizotypal Personality Questionnaire (SPQ). Subjects were genotyped using a custom array chip. Principal component analysis was used to cluster SPQ variables. Linear regression tested for associations between dimensional schizotypy and SNPs. Logistic regression tested for associations between SNPs and SPD diagnosis. There were significant associations between the minor alleles of three SNPs within the glycine receptor alpha 1 subunit (GLRA1) and the disorganized schizotypy dimension, even after Bonferroni correction. There were no significant associations between any SNPs and the categorical SPD diagnosis. Glycine receptor pathways may have an impact on dimensional traits of psychosis.
Collapse
Affiliation(s)
- Anvi K. Vora
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Amanda M. Fisher
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Antonia S. New
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Erin A. Hazlett
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Margaret McNamara
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Qiaoping Yuan
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD, USA
| | - Zhifeng Zhou
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD, USA
| | - Colin Hodgkinson
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD, USA
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Rockville, MD, USA
| | - Larry J. Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - M. Mercedes Perez-Rodriguez
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA,James J. Peters Veterans Affairs Medical Center, Bronx, NY, USA
| |
Collapse
|
19
|
Neurological soft signs precede the onset of schizophrenia: a study of individuals with schizotypy, ultra-high-risk individuals, and first-onset schizophrenia. Eur Arch Psychiatry Clin Neurosci 2018; 268:49-56. [PMID: 28761988 DOI: 10.1007/s00406-017-0828-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 07/24/2017] [Indexed: 12/13/2022]
Abstract
Neurological soft signs (NSS) are one of the biomarkers for schizophrenia spectrum disorders. However, a few studies have examined the prevalence of NSS across the schizophrenia spectrum. The present study adopted a quasi-longitudinal study design and examined the prevalence of NSS and their associations with clinical and behavioural manifestations in participants in different stages of the illness. The abridged version of the Cambridge Neurological Inventory was administered to 39 patients with the first-episode schizophrenia, 39 individuals with ultra-high risk (UHR) for psychosis, 39 individuals with schizotypy, and 39 healthy controls. Patients with the first-episode schizophrenia had a higher prevalence of NSS in motor coordination than healthy controls as well as individuals with UHR and schizotypy. Individuals with UHR exhibited a higher prevalence of sensory integration items than individuals with schizotypy and healthy controls. Discriminant analysis classified the membership of the individuals correctly across the spectrum with an accuracy of up to 60.9%. In particular, NSS could discriminate individuals with UHR from healthy controls at up to 85.9% accuracy. These findings suggest that NSS are robust biomarkers to detect and discriminate individuals in different stages of the schizophrenia spectrum from healthy controls.
Collapse
|
20
|
DiLalla LF, McCrary M, Diaz E. A review of endophenotypes in schizophrenia and autism: The next phase for understanding genetic etiologies. AMERICAN JOURNAL OF MEDICAL GENETICS PART C-SEMINARS IN MEDICAL GENETICS 2017; 175:354-361. [PMID: 28661580 DOI: 10.1002/ajmg.c.31566] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Revised: 05/17/2017] [Accepted: 05/24/2017] [Indexed: 01/16/2023]
Abstract
Many psychiatric disorders are caused by multiple genes and multiple environmental factors, making the identification of specific genetic risk factors for these disorders difficult. Endophenotypes are behaviors or characteristics that are intermediate between the genotype and a phenotype of interest. Because they are more directly related to the gene action than is the endpoint disorder, they may be useful in the identification of specific genes related to psychiatric disorders and the classification of disorders or traits that share an underlying genetic etiology. We discuss genetic and endophenotype research on schizophrenia and autism spectrum disorder (ASD) in this review. Some of the psychophysiological endophenotypes that have been studied for schizophrenia include prepulse inhibition of the startle response, the antisaccadic task assessing frontal lobe function, inhibition of the P50 event-related potential (ERP), and other auditory ERP measures. Potential ASD endophenotypes include theory of mind, language skills (specifically, age at first spoken word and first spoken phrase), social skills, and certain brain functions, such as asynchronization of neural activity and brain responses to emotional faces. Because the link between genes and specific psychiatric disorders is difficult to determine, identification of endophenotypes is useful for beginning the search to identify specific genes that affect these disorders.
Collapse
Affiliation(s)
| | | | - Emma Diaz
- Southern Illinois University, Carbondale, Illinois
| |
Collapse
|
21
|
Demkow U, Wolańczyk T. Genetic tests in major psychiatric disorders-integrating molecular medicine with clinical psychiatry-why is it so difficult? Transl Psychiatry 2017; 7:e1151. [PMID: 28608853 PMCID: PMC5537634 DOI: 10.1038/tp.2017.106] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Accepted: 03/29/2017] [Indexed: 02/06/2023] Open
Abstract
With the advent of post-genomic era, new technologies create extraordinary possibilities for diagnostics and personalized therapy, transforming todays' medicine. Rooted in both medical genetics and clinical psychiatry, the paper is designed as an integrated source of information of the current and potential future application of emerging genomic technologies as diagnostic tools in psychiatry, moving beyond the classical concept of patient approach. Selected approaches are presented, starting from currently used technologies (next-generation sequencing (NGS) and microarrays), followed by newer options (reverse phenotyping). Next, we describe an old concept in a new light (endophenotypes), subsequently coming up with a sophisticated and complex approach (gene networks) ending by a nascent field (computational psychiatry). The challenges and barriers that exist to translate genomic research to real-world patient assessment are further discussed. We emphasize the view that only a paradigm shift can bring a fundamental change in psychiatric practice, allowing to disentangle the intricacies of mental diseases. All the diagnostic methods, as described, are directed at uncovering the integrity of the system including many types of relations within a complex structure. The integrative system approach offers new opportunity to connect genetic background with specific diseases entities, or concurrently, with symptoms regardless of a diagnosis. To advance the field, we propose concerted cross-disciplinary effort to provide a diagnostic platform operating at the general level of genetic pathogenesis of complex-trait psychiatric disorders rather than at the individual level of a specific disease.
Collapse
Affiliation(s)
- U Demkow
- Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, Warsaw, Poland,Department of Laboratory Diagnostics and Clinical Immunology of Developmental Age, Medical University of Warsaw, Zwirki i Wigury 63a, Warsaw 02-091, Poland. E-mail:
| | - T Wolańczyk
- Department of Child Psychiatry, Medical University of Warsaw, Warsaw, Poland
| |
Collapse
|
22
|
Jaitovich Groisman I, Hurlimann T, Shoham A, Godard B. Practices and views of neurologists regarding the use of whole-genome sequencing in clinical settings: a web-based survey. Eur J Hum Genet 2017; 25:801-808. [PMID: 28488681 DOI: 10.1038/ejhg.2017.64] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 02/28/2017] [Accepted: 03/28/2017] [Indexed: 12/23/2022] Open
Abstract
The use of Whole-Genome Sequencing (WGS) in clinical settings has brought up a number of controversial scientific and ethical issues. The application of WGS is of particular relevance in neurology, as many conditions are difficult to diagnose. We conducted a worldwide, web-based survey to explore neurologists' views on the benefits of, and concerns regarding, the clinical use of WGS, as well as the resources necessary to implement it. Almost half of the 204 neurologists in the study treated mostly adult patients (48%), while the rest mainly children (37.3%), or both (14.7%). Epilepsy (73%) and headaches (57.8%) were the predominant conditions treated. Factor analysis brought out two profiles: neurologists who would offer WGS to their patients, and those who would not, or were not sure in which circumstances it should be offered. Neurologists considering the use of WGS as bringing more benefits than drawbacks currently used targeted genetic testing (P<0.05) or treated mainly children (P<0.05). WGS' benefits were directed towards the patients, while its risks were of a financial and legal nature. Furthermore, there was a correlation between respondents' current use of genetic tests and an anticipation of increased use in the future (P<0.001). However, over half of respondents did not feel sufficiently informed to use WGS in their practice (53.5%). Our results highlight gaps in education, organization, and funding to support the use of WGS in neurology, and draw attention to the need for resources that could strongly contribute to more straightforward diagnoses and possibly better treatment of neurological conditions.
Collapse
Affiliation(s)
- Iris Jaitovich Groisman
- Groupe de recherche Omics-Ethics, Institut de recherche en santé publique, Université de Montréal, Montreal, Quebec, Canada
| | - Thierry Hurlimann
- Groupe de recherche Omics-Ethics, Institut de recherche en santé publique, Université de Montréal, Montreal, Quebec, Canada
| | - Amir Shoham
- Département de psychologie, Faculté des arts et des sciences, Université de Montréal, Montreal, Quebec, Canada
| | - Béatrice Godard
- Groupe de recherche Omics-Ethics, Institut de recherche en santé publique, Université de Montréal, Montreal, Quebec, Canada
| |
Collapse
|
23
|
A Neurophysiological Perspective on a Preventive Treatment against Schizophrenia Using Transcranial Electric Stimulation of the Corticothalamic Pathway. Brain Sci 2017; 7:brainsci7040034. [PMID: 28350371 PMCID: PMC5406691 DOI: 10.3390/brainsci7040034] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 03/11/2017] [Accepted: 03/24/2017] [Indexed: 12/16/2022] Open
Abstract
Schizophrenia patients are waiting for a treatment free of detrimental effects. Psychotic disorders are devastating mental illnesses associated with dysfunctional brain networks. Ongoing brain network gamma frequency (30–80 Hz) oscillations, naturally implicated in integrative function, are excessively amplified during hallucinations, in at-risk mental states for psychosis and first-episode psychosis. So, gamma oscillations represent a bioelectrical marker for cerebral network disorders with prognostic and therapeutic potential. They accompany sensorimotor and cognitive deficits already present in prodromal schizophrenia. Abnormally amplified gamma oscillations are reproduced in the corticothalamic systems of healthy humans and rodents after a single systemic administration, at a psychotomimetic dose, of the glutamate N-methyl-d-aspartate receptor antagonist ketamine. These translational ketamine models of prodromal schizophrenia are thus promising to work out a preventive noninvasive treatment against first-episode psychosis and chronic schizophrenia. In the present essay, transcranial electric stimulation (TES) is considered an appropriate preventive therapeutic modality because it can influence cognitive performance and neural oscillations. Here, I highlight clinical and experimental findings showing that, together, the corticothalamic pathway, the thalamus, and the glutamatergic synaptic transmission form an etiopathophysiological backbone for schizophrenia and represent a potential therapeutic target for preventive TES of dysfunctional brain networks in at-risk mental state patients against psychotic disorders.
Collapse
|
24
|
Iacono WG, Malone SM, Vrieze SI. Endophenotype best practices. Int J Psychophysiol 2017; 111:115-144. [PMID: 27473600 PMCID: PMC5219856 DOI: 10.1016/j.ijpsycho.2016.07.516] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/21/2016] [Accepted: 07/24/2016] [Indexed: 01/19/2023]
Abstract
This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.
Collapse
|
25
|
Thomas ML, Green MF, Hellemann G, Sugar CA, Tarasenko M, Calkins ME, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Radant AD, Seidman LJ, Shiluk AL, Siever LJ, Silverman JM, Sprock J, Stone WS, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL, Light GA. Modeling Deficits From Early Auditory Information Processing to Psychosocial Functioning in Schizophrenia. JAMA Psychiatry 2017; 74:37-46. [PMID: 27926742 PMCID: PMC5453308 DOI: 10.1001/jamapsychiatry.2016.2980] [Citation(s) in RCA: 149] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
IMPORTANCE Neurophysiologic measures of early auditory information processing (EAP) are used as endophenotypes in genomic studies and biomarkers in clinical intervention studies. Research in schizophrenia has established correlations among measures of EAP, cognition, clinical symptoms, and functional outcome. Clarifying these associations by determining the pathways through which deficits in EAP affect functioning would suggest when and where to therapeutically intervene. OBJECTIVES To characterize the pathways from EAP to outcome and to estimate the extent to which enhancement of basic information processing might improve cognition and psychosocial functioning in schizophrenia. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional data were analyzed using structural equation modeling to examine the associations among EAP, cognition, negative symptoms, and functional outcome. Participants were recruited from the community at 5 geographically distributed laboratories as part of the Consortium on the Genetics of Schizophrenia 2 from July 1, 2010, through January 31, 2014. This well-characterized cohort of 1415 patients with schizophrenia underwent EAP, cognitive, and thorough clinical and functional assessment. MAIN OUTCOME AND MEASURES Mismatch negativity, P3a, and reorienting negativity were used to measure EAP. Cognition was measured by the Letter Number Span test and scales from the California Verbal Learning Test-Second Edition, the Wechsler Memory Scale-Third Edition, and the Penn Computerized Neurocognitive Battery. Negative symptoms were measured by the Scale for the Assessment of Negative Symptoms. Functional outcome was measured by the Role Functioning Scale. RESULTS Participants included 1415 unrelated outpatients diagnosed with schizophrenia or schizoaffective disorder (mean [SD] age, 46 [11] years; 979 males [69.2%] and 619 white [43.7%]). Early auditory information processing had a direct effect on cognition (β = 0.37, P < .001), cognition had a direct effect on negative symptoms (β = -0.16, P < .001), and both cognition (β = 0.26, P < .001) and experiential negative symptoms (β = -0.75, P < .001) had direct effects on functional outcome. The indirect effect of EAP on functional outcome was significant as well (β = 0.14, P < .001). Overall, EAP had a fully mediated effect on functional outcome, engaging general rather than modality-specific cognition, with separate pathways that involved or bypassed negative symptoms. CONCLUSIONS AND RELEVANCE The data support a model in which EAP deficits lead to poor functional outcome via impaired cognition and increased negative symptoms. Results can be used to help guide mechanistically informed, personalized treatments and support the strategy of using EAP measures as surrogate end points in early-stage procognitive intervention studies.
Collapse
Affiliation(s)
- Michael L. Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Gerhard Hellemann
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA
| | - Melissa Tarasenko
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | | | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | | | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Center for Behavioral Genomics, and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| |
Collapse
|
26
|
Fatjó-Vilas M, Prats C, Pomarol-Clotet E, Lázaro L, Moreno C, González-Ortega I, Lera-Miguel S, Miret S, Muñoz MJ, Ibáñez I, Campanera S, Giralt-López M, Cuesta MJ, Peralta V, Ortet G, Parellada M, González-Pinto A, McKenna PJ, Fañanás L. Involvement of NRN1 gene in schizophrenia-spectrum and bipolar disorders and its impact on age at onset and cognitive functioning. World J Biol Psychiatry 2016; 17:129-39. [PMID: 26700405 DOI: 10.3109/15622975.2015.1093658] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Neuritin 1 gene (NRN1) is involved in neurodevelopment processes and synaptic plasticity and its expression is regulated by brain-derived neurotrophic factor (BDNF). We aimed to investigate the association of NRN1 with schizophrenia-spectrum disorders (SSD) and bipolar disorders (BPD), to explore its role in age at onset and cognitive functioning, and to test the epistasis between NRN1 and BDNF. METHODS The study was developed in a sample of 954 SSD/BPD patients and 668 healthy subjects. Genotyping analyses included 11 SNPs in NRN1 and one functional SNP in BDNF. RESULTS The frequency of the haplotype C-C (rs645649-rs582262) was significantly increased in patients compared to controls (P = 0.0043), while the haplotype T-C-C-T-C-A (rs3763180-rs10484320-rs4960155-rs9379002-rs9405890-rs1475157) was more frequent in controls (P = 3.1 × 10(-5)). The variability at NRN1 was nominally related to changes in age at onset and to differences in intelligence quotient, in SSD patients. Epistasis between NRN1 and BDNF was significantly associated with the risk for SSD/BPD (P = 0.005). CONCLUSIONS Results suggest that: (i) NRN1 variability is a shared risk factor for both SSD and BPD, (ii) NRN1 may have a selective impact on age at onset and intelligence in SSD, and (iii) the role of NRN1 seems to be not independent of BDNF.
Collapse
Affiliation(s)
- Mar Fatjó-Vilas
- a Departament de Biologia Animal, Facultat de Biologia, Universitat de Barcelona , Barcelona , Spain ; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Spain;,b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain
| | - Claudia Prats
- a Departament de Biologia Animal, Facultat de Biologia, Universitat de Barcelona , Barcelona , Spain ; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Spain;,b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain
| | - Edith Pomarol-Clotet
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,c FIDMAG Germanes Hospitalàries, Research Foundation , Barcelona , Spain
| | - Luisa Lázaro
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,d Servei de Psiquiatria i Psicologia Infantil i Juvenil, Hospital Clínic de Barcelona , Barcelona , Spain ;,e Institut d'investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Barcelona, Spain; Departament de Psiquiatria i Psicobiologia Clínica, Facultat de Medicina, Universitat de Barcelona , Barcelona , Spain
| | - Carmen Moreno
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,f Servicio de Psiquiatría del Niño y del Adolescente , Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM); Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense , Madrid , Spain
| | - Itxaso González-Ortega
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,g Psychiatry Service, University Hospital of Alava-Santiago, EMBREC, EHU/UPV University of the Basque Country, Kronikgune , Vitoria , Spain
| | - Sara Lera-Miguel
- d Servei de Psiquiatria i Psicologia Infantil i Juvenil, Hospital Clínic de Barcelona , Barcelona , Spain
| | - Salvador Miret
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,h Centre de Salut Mental d'Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida , Lleida , Spain
| | - Ma José Muñoz
- i Àrea d'Adolescents, Complex Assistencial en Salut Mental Benito Menni, Sant Boi De Llobregat , Spain
| | - Ignacio Ibáñez
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,j Departament de Psicologia Bàsica , Clínica i Psicobiologia, Facultat de Ciències de la Salut, Universitat Jaume I , Castelló , Spain
| | - Sílvia Campanera
- h Centre de Salut Mental d'Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida , Lleida , Spain
| | - Maria Giralt-López
- i Àrea d'Adolescents, Complex Assistencial en Salut Mental Benito Menni, Sant Boi De Llobregat , Spain
| | - Manuel J Cuesta
- k Servicio de Psiquiatría, Complejo Hospitalario de Navarra, Pamplona Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA) , Pamplona , Spain
| | - Victor Peralta
- k Servicio de Psiquiatría, Complejo Hospitalario de Navarra, Pamplona Spain; Instituto de Investigación Sanitaria de Navarra (IdiSNA) , Pamplona , Spain
| | - Generós Ortet
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,j Departament de Psicologia Bàsica , Clínica i Psicobiologia, Facultat de Ciències de la Salut, Universitat Jaume I , Castelló , Spain
| | - Mara Parellada
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,f Servicio de Psiquiatría del Niño y del Adolescente , Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM); Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense , Madrid , Spain
| | - Ana González-Pinto
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,g Psychiatry Service, University Hospital of Alava-Santiago, EMBREC, EHU/UPV University of the Basque Country, Kronikgune , Vitoria , Spain
| | - Peter J McKenna
- b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain ;,c FIDMAG Germanes Hospitalàries, Research Foundation , Barcelona , Spain
| | - Lourdes Fañanás
- a Departament de Biologia Animal, Facultat de Biologia, Universitat de Barcelona , Barcelona , Spain ; Institut de Biomedicina de la Universitat de Barcelona (IBUB), Spain;,b Instituto De Salud Carlos III, Centro De Investigación Biomédica En Red De Salud Mental (CIBERSAM) , Madrid , Spain
| |
Collapse
|
27
|
Schmitt A, Rujescu D, Gawlik M, Hasan A, Hashimoto K, Iceta S, Jarema M, Kambeitz J, Kasper S, Keeser D, Kornhuber J, Koutsouleris N, Lanzenberger R, Malchow B, Saoud M, Spies M, Stöber G, Thibaut F, Riederer P, Falkai P. Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part II: Cognition, neuroimaging and genetics. World J Biol Psychiatry 2016; 17:406-28. [PMID: 27311987 DOI: 10.1080/15622975.2016.1183043] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVES Schizophrenia is a group of severe psychiatric disorders with high heritability but only low odds ratios of risk genes. Despite progress in the identification of pathophysiological processes, valid biomarkers of the disease are still lacking. METHODS This comprehensive review summarises recent efforts to identify genetic underpinnings, clinical and cognitive endophenotypes and symptom dimensions of schizophrenia and presents findings from neuroimaging studies with structural, functional and spectroscopy magnetic resonance imaging and positron emission tomography. The potential of findings to be biomarkers of schizophrenia is discussed. RESULTS Recent findings have not resulted in clear biomarkers for schizophrenia. However, we identified several biomarkers that are potential candidates for future research. Among them, copy number variations and links between genetic polymorphisms derived from genome-wide analysis studies, clinical or cognitive phenotypes, multimodal neuroimaging findings including positron emission tomography and magnetic resonance imaging, and the application of multivariate pattern analyses are promising. CONCLUSIONS Future studies should address the effects of treatment and stage of the disease more precisely and apply combinations of biomarker candidates. Although biomarkers for schizophrenia await validation, knowledge on candidate genomic and neuroimaging biomarkers is growing rapidly and research on this topic has the potential to identify psychiatric endophenotypes and in the future increase insight on individual treatment response in schizophrenia.
Collapse
Affiliation(s)
- Andrea Schmitt
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany ;,b Laboratory of Neuroscience (LIM27), Institute of Psychiatry , University of Sao Paulo , Sao Paulo , Brazil
| | - Dan Rujescu
- c Department of Psychiatry, Psychotherapy and Psychosomatics , University of Halle , Germany
| | - Micha Gawlik
- d Department of Psychiatry, Psychotherapy and Psychosomatics , University of Würzburg , Germany
| | - Alkomiet Hasan
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Kenji Hashimoto
- e Division of Clinical Neuroscience , Chiba University Center for Forensic Mental Health , Chiba , Japan
| | - Sylvain Iceta
- f INSERM, U1028; CNRS, UMR5292; Lyon Neuroscience Research Center, PsyR2 Team , Lyon , F-69000 , France ; Hospices Civils De Lyon, France
| | - Marek Jarema
- g Department of Psychiatry , Institute of Psychiatry and Neurology , Warsaw , Poland
| | - Joseph Kambeitz
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Siegfried Kasper
- h Department of Psychiatry and Psychotherapy , Medical University of Vienna , Austria
| | - Daniel Keeser
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Johannes Kornhuber
- i Department of Psychiatry and Psychotherapy , Friedrich-Alexander-University Erlangen-Nuremberg , Erlangen , Germany
| | | | - Rupert Lanzenberger
- h Department of Psychiatry and Psychotherapy , Medical University of Vienna , Austria
| | - Berend Malchow
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | - Mohamed Saoud
- f INSERM, U1028; CNRS, UMR5292; Lyon Neuroscience Research Center, PsyR2 Team , Lyon , F-69000 , France ; Hospices Civils De Lyon, France
| | - Marie Spies
- h Department of Psychiatry and Psychotherapy , Medical University of Vienna , Austria
| | - Gerald Stöber
- d Department of Psychiatry, Psychotherapy and Psychosomatics , University of Würzburg , Germany
| | - Florence Thibaut
- j Department of Psychiatry , University Hospital Cochin (Site Tarnier), University of Paris-Descartes, INSERM U 894 Centre Psychiatry and Neurosciences , Paris , France
| | - Peter Riederer
- k Center of Psychic Health; Clinic and Policlinic for Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Wuerzburg , Germany
| | - Peter Falkai
- a Department of Psychiatry and Psychotherapy , LMU Munich , Germany
| | | |
Collapse
|
28
|
Prioritizing schizophrenia endophenotypes for future genetic studies: An example using data from the COGS-1 family study. Schizophr Res 2016; 174:1-9. [PMID: 27132484 PMCID: PMC4912929 DOI: 10.1016/j.schres.2016.04.011] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Revised: 04/06/2016] [Accepted: 04/11/2016] [Indexed: 11/20/2022]
Abstract
Past studies describe numerous endophenotypes associated with schizophrenia (SZ), but many endophenotypes may overlap in information they provide, and few studies have investigated the utility of a multivariate index to improve discrimination between SZ and healthy community comparison subjects (CCS). We investigated 16 endophenotypes from the first phase of the Consortium on the Genetics of Schizophrenia, a large, multi-site family study, to determine whether a subset could distinguish SZ probands and CCS just as well as using all 16. Participants included 345 SZ probands and 517 CCS with a valid measure for at least one endophenotype. We used both logistic regression and random forest models to choose a subset of endophenotypes, adjusting for age, gender, smoking status, site, parent education, and the reading subtest of the Wide Range Achievement Test. As a sensitivity analysis, we re-fit models using multiple imputations to determine the effect of missing values. We identified four important endophenotypes: antisaccade, Continuous Performance Test-Identical Pairs 3-digit version, California Verbal Learning Test, and emotion identification. The logistic regression model that used just these four endophenotypes produced essentially the same results as the model that used all 16 (84% vs. 85% accuracy). While a subset of endophenotypes cannot replace clinical diagnosis nor encompass the complexity of the disease, it can aid in the design of future endophenotypic and genetic studies by reducing study cost and subject burden, simplifying sample enrichment, and improving the statistical power of locating those genetic regions associated with schizophrenia that may be the easiest to identify initially.
Collapse
|
29
|
Loos M, Schetters D, Hoogeland M, Spijker S, de Vries TJ, Pattij T. Prefrontal cortical neuregulin-ErbB modulation of inhibitory control in rats. Eur J Pharmacol 2016; 781:157-63. [DOI: 10.1016/j.ejphar.2016.04.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2016] [Revised: 04/07/2016] [Accepted: 04/11/2016] [Indexed: 12/13/2022]
|
30
|
Morris SE, Vaidyanathan U, Cuthbert BN. Changing the Diagnostic Concept of Schizophrenia: The NIMH Research Domain Criteria Initiative. NEBRASKA SYMPOSIUM ON MOTIVATION. NEBRASKA SYMPOSIUM ON MOTIVATION 2016; 63:225-52. [PMID: 27627829 DOI: 10.1007/978-3-319-30596-7_8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
|
31
|
Liu C, Saffen D, Schulze TG, Burmeister M, Sham PC, Yao YG, Kuo PH, Chen C, An Y, Dai J, Yue W, Li MX, Xue H, Su B, Chen L, Shi Y, Qiao M, Liu T, Xia K, Chan RCK. Psychiatric genetics in China: achievements and challenges. Mol Psychiatry 2016; 21:4-9. [PMID: 26481319 PMCID: PMC4830695 DOI: 10.1038/mp.2015.95] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
To coordinate research efforts in psychiatric genetics in China, a group of Chinese and foreign investigators have established an annual “Summit on Chinese Psychiatric Genetics” to present their latest research and discuss the current state and future directions of this field. To date, two Summits have been held, the first in Changsha in April, 2014, and the second in Kunming in April, 2015. The consensus of roundtable discussions held at these meetings is that psychiatric genetics in China is in need of new policies to promote collaborations aimed at creating a framework for genetic research appropriate for the Chinese population: relying solely on Caucasian population-based studies may result in missed opportunities to diagnose and treat psychiatric disorders. In addition, participants agree on the importance of promoting collaborations and data sharing in areas where China has especially strong resources, such as advanced facilities for non-human primate studies and traditional Chinese medicine: areas that may also provide overseas investigators with unique research opportunities. In this paper, we present an overview of the current state of psychiatric genetics research in China, with emphasis on genome-level studies, and describe challenges and opportunities for future advances, particularly at the dawn of “precision medicine.” Together, we call on administrative bodies, funding agencies, the research community, and the public at large for increased support for research on the genetic basis of psychiatric disorders in the Chinese population. In our opinion, increased public awareness and effective collaborative research hold the keys to the future of psychiatric genetics in China.
Collapse
Affiliation(s)
- Chunyu Liu
- State Key Laboratory of Medical Genetics of China, Central South University, Changsha, China
- Department of Psychiatry, University of Illinois at Chicago, Chicago, United States of America
| | - David Saffen
- Depatement of Cellular and Genetic Medicine, Fudan University, Shanghai, China
| | - Thomas G Schulze
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August-Universität, Göttingen, Germany
- Institute of Psychiatric Phenomics and Genomics, Ludwig Maximilians-University, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health Mannheim, University Medical Center Mannheim, University of Heidelberg, Mannheim, Germany
| | - Margit Burmeister
- Molecular and Behavioral Neuroscience Institute, Departments of Psychiatry, Human Genetics and Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Pak Chung Sham
- Department of Psychiatry, University of Hong Kong, Pokfulam, Hong Kong
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Kunming, China
| | - Po-Hsiu Kuo
- Department of Public Health and Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Chao Chen
- State Key Laboratory of Medical Genetics of China, Central South University, Changsha, China
| | - Yu An
- Institute of Biomedical Sciences and MOE Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China
| | - Jiapei Dai
- Wuhan Institute for Neuroscience and Neuroengineering, South-Central University for Nationalities, Wuhan, China
| | - Weihua Yue
- Key Laboratory of Mental Health, Ministry of Health, Institute of Mental Health, The Sixth Hospital, Peking University, Beijing, China
| | - Miao Xin Li
- Department of Psychiatry, University of Hong Kong, Pokfulam, Hong Kong
| | - Hong Xue
- Division of Life Science and Applied Genomics Center, The Hong Kong University of Science & Technology, Hong Kong, China
| | - Bing Su
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology and Kunming Primate Research Centre, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Li Chen
- Depatement of Cellular and Genetic Medicine, Fudan University, Shanghai, China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Mingqi Qiao
- Institute of Traditional Chinese Medicine theory, School of Basic Medicine, Shandong University of Traditional Chinese Medicine, Jinan 250014, China
| | - Tiebang Liu
- Shenzhen Kang Ning Hospital, No.1080, Cuizhu Street, Luohu District, Shenzhen, Guangdong, 518020, China
| | - Kun Xia
- State Key Laboratory of Medical Genetics of China, Central South University, Changsha, China
- School of Life Sciences, Central South University, Changsha, China
| | - Raymond C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences
| |
Collapse
|
32
|
Xu T, Wang Y, Li Z, Huang J, Lui SSY, Tan SP, Yu X, Cheung EFC, He MG, Ott J, Gur RE, Gur RC, Chan RCK. Heritability and familiality of neurological soft signs: evidence from healthy twins, patients with schizophrenia and non-psychotic first-degree relatives. Psychol Med 2016; 46:117-123. [PMID: 26347209 DOI: 10.1017/s0033291715001580] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Neurological soft signs (NSS) have long been considered potential endophenotypes for schizophrenia. However, few studies have investigated the heritability and familiality of NSS. The present study examined the heritability and familiality of NSS in healthy twins and patient-relative pairs. METHOD The abridged version of the Cambridge Neurological Inventory was administered to 267 pairs of monozygotic twins, 124 pairs of dizygotic twins, and 75 pairs of patients with schizophrenia and their non-psychotic first-degree relatives. RESULTS NSS were found to have moderate but significant heritability in the healthy twin sample. Moreover, patients with schizophrenia correlated closely with their first-degree relatives on NSS. CONCLUSIONS Taken together, the findings provide evidence on the heritability and familiality of NSS in the Han Chinese population.
Collapse
Affiliation(s)
- T Xu
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - Y Wang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - Z Li
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - J Huang
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - S S Y Lui
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - S-P Tan
- Beijing Huilongguan Hospital,Beijing,People's Republic of China
| | - X Yu
- Peking University Sixth Hospital,Beijing,People's Republic of China
| | - E F C Cheung
- Castle Peak Hospital,Hong Kong Special Administrative Region,People's Republic of China
| | - M-G He
- State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,People's Republic of China
| | - J Ott
- Statistical Genetics Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| | - R E Gur
- Department of Psychiatry,Perelman School of Medicine,University of Pennsylvania,and the Philadelphia Veterans Administration Medical Center,Philadelphia,PA,USA
| | - R C Gur
- Department of Psychiatry,Perelman School of Medicine,University of Pennsylvania,and the Philadelphia Veterans Administration Medical Center,Philadelphia,PA,USA
| | - R C K Chan
- Neuropsychology and Applied Cognitive Neuroscience Laboratory,Key Laboratory of Mental Health,Institute of Psychology,Chinese Academy of Sciences,Beijing,People's Republic of China
| |
Collapse
|
33
|
Solanki RK, Kumar A, Satija Y, Gupta S, Singh P. An Indian experience of neurocognitive endophenotypic markers in unaffected first-degree relatives of schizophrenia patients. Indian J Psychiatry 2016; 58:20-6. [PMID: 26985100 PMCID: PMC4776576 DOI: 10.4103/0019-5545.174356] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
CONTEXT Multiple vulnerability genes interact with environmental factors to develop a range of phenotypes in the schizophrenia spectrum. Endophenotypes can help characterize the impact of risk genes by providing genetically relevant traits that are more complaisant than the behavioral symptoms that classify mental illness. AIMS We aimed to investigate the neurocognitive endophenotypic markers for schizophrenia in Indian population. SETTINGS AND DESIGN In a cross-sectional study, we assessed neurocognitive functioning in 40 unaffected first-degree relatives (FDR) of schizophrenia patients with an equal number of healthy controls. MATERIALS AND METHODS FDR schizophrenia group was compared with the control group on measures of short-term memory, verbal working memory, auditory verbal memory on indices of immediate recall and recognition, visuospatial working memory, visual attention, and executive functions. RESULTS The study found that FDR schizophrenia scored poorly on all tested measures of neurocognition except visual attention. On calculating composite score, we found that composite neurocognitive score better discriminated the FDR schizophrenia from the control group. CONCLUSIONS Neurocognitive measures of short-term memory, verbal working memory, auditory verbal memory, visuospatial working memory, and executive functions significantly differentiate FDR of patients with schizophrenia from controls and can be considered as endophenotypic markers of schizophrenia in non-Caucasian population. The exactitude of this approach can be increased by calculating a composite neurocognitive score which combines various neurocognitive measures.
Collapse
Affiliation(s)
- Ram Kumar Solanki
- Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Ashok Kumar
- Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Yogesh Satija
- Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Suresh Gupta
- Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| | - Paramjeet Singh
- Department of Psychiatry, Sawai Man Singh Medical College, Jaipur, Rajasthan, India
| |
Collapse
|
34
|
Affiliation(s)
- Paul S. Appelbaum
- Department of Psychiatry, Columbia University, New York, NY,*To whom correspondence should be addressed; Department of Psychiatry, Columbia University, New York State Psychiatric Institute, 1051 Riverside Drive, Unit 122, New York, NY 10032, US; tel: 646-774-8630, fax: 646-774-8633, e-mail:
| |
Collapse
|
35
|
Stone WS, Mesholam-Gately RI, Braff DL, Calkins ME, Freedman R, Green MF, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Light GA, Nuechterlein KH, Olincy A, Radant AD, Siever LJ, Silverman JM, Sprock J, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Seidman LJ. California Verbal Learning Test-II performance in schizophrenia as a function of ascertainment strategy: comparing the first and second phases of the Consortium on the Genetics of Schizophrenia (COGS). Schizophr Res 2015; 163:32-7. [PMID: 25497440 PMCID: PMC5954831 DOI: 10.1016/j.schres.2014.10.029] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 10/16/2014] [Accepted: 10/19/2014] [Indexed: 12/21/2022]
Abstract
The first phase of the Consortium on the Genetics of Schizophrenia (COGS-1) showed performance deficits in learning and memory on the California Verbal Learning Test, Second Edition (CVLT-II) in individuals with schizophrenia (SZ), compared to healthy comparison subjects (HCS). A question is whether the COGS-1 study, which used a family study design (i.e. studying relatively intact families), yielded "milder" SZ phenotypes than those acquired subsequently in the COGS-2 case-control design that did not recruit unaffected family members. CVLT-II performance was compared for the COGS-1 and COGS-2 samples. Analyses focused on learning, recall and recognition variables, with age, gender and education as covariates. Analyses of COGS-2 data explored effects of additional covariates and moderating factors in CVLT-II performance. 324 SZ subjects and 510 HCS had complete CVLT-II and covariate data in COGS-1, while 1356 SZ and 1036 HCS had complete data in COGS-2. Except for recognition memory, analysis of covariance showed significantly worse performance in COGS-2 on all CVLT-II variables for SZ and HCS, and remained significant in the presence of the covariates. Performance in each of the 5 learning trials differed significantly. However, effect sizes comparing cases and controls were comparable across the two studies. COGS-2 analyses confirmed SZ performance deficits despite effects of multiple significant covariates and moderating factors. CVLT-II performance was worse in COGS-2 than in COGS-1 for both the SZ and the HCS in this large cohort, likely due to cohort effects. Demographically corrected data yield a consistent pattern of performance across the two studies in SZ.
Collapse
Affiliation(s)
- William S Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States.
| | - Raquelle I Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - David L Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States
| | - Monica E Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO, United States
| | - Michael F Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Tiffany A Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, United States; Department of Pediatrics, Stanford University, Stanford, CA, United States
| | - Gregory A Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States
| | - Keith H Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Health Sciences Center, Denver, CO, United States
| | - Allen D Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States; VA Puget Sound Health Care System, Seattle, WA, United States
| | - Larry J Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States; James J. Peters VA Medical Center, New York, NY, United States
| | - Jeremy M Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States; James J. Peters VA Medical Center, New York, NY, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Catherine A Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA, United States
| | - Neal R Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Debby W Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, United States; VA Puget Sound Health Care System, Seattle, WA, United States
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States; Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA, United States; VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, United States; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, United States
| | - Bruce I Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, United States
| | - Larry J Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| |
Collapse
|
36
|
The importance of endophenotypes in schizophrenia research. Schizophr Res 2015; 163:1-8. [PMID: 25795083 DOI: 10.1016/j.schres.2015.02.007] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2014] [Revised: 02/06/2015] [Accepted: 02/06/2015] [Indexed: 11/21/2022]
Abstract
Endophenotypes provide a powerful neurobiological platform from which we can understand the genomic and neural substrates of schizophrenia and other common complex neuropsychiatric disorders. The Consortium on the Genetics of Schizophrenia (COGS) has conducted multisite studies on carefully selected key neurocognitive and neurophysiological endophenotypes in 300 families (COGS-1) and then in a follow up multisite case-control study of 2471 subjects (COGS-2). Endophenotypes are neurobiologically informed quantitative measures that show deficits in probands and their first degree relatives. They are more amenable to statistical analysis than are "fuzzy" qualitative clinical traits or confoundingly heterogeneous diagnostic categories. Endophenotypes are also viewed as uniquely informative in traditional diagnosis-based as well as emerging NIMH Research Domain (RDoC) contexts, offering a bridge between the two approaches to psychopathology classification and research. Endo- or intermediate phenotypes are heritable, and in the COGS-1 cohort their level of heritability is in the same range as is the heritability of schizophrenia itself, using the same statistical methods and subjects to assess both. Because we can demonstrate endophenotypes link to both gene networks and neural circuits on the one hand and also to real-life function, endophenotypes provide a critically important bridge for "connecting the dots" between genes, cells, circuits, information processing, neurocognition and functional impairment and personalized treatment selection in schizophrenia patients. By connecting schizophrenia risk genes with neurobiologically informed endophenotypes, and via the use of association, linkage, sequencing, stem cell and other strategies, we can provide our field with new neurobiologically informed information in our efforts to understand and treat schizophrenia. Evolving views, data and new analytic strategies about schizophrenia risk, pathology and treatment are described in this Viewpoint and in the accompanying Special Issue reports.
Collapse
|
37
|
Light GA, Swerdlow NR, Thomas ML, Calkins ME, Green MF, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Pela M, Radant AD, Seidman LJ, Sharp RF, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Tsuang DW, Tsuang MT, Braff DL, Turetsky BI. Validation of mismatch negativity and P3a for use in multi-site studies of schizophrenia: characterization of demographic, clinical, cognitive, and functional correlates in COGS-2. Schizophr Res 2015; 163:63-72. [PMID: 25449710 PMCID: PMC4382452 DOI: 10.1016/j.schres.2014.09.042] [Citation(s) in RCA: 136] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 09/16/2014] [Accepted: 09/18/2014] [Indexed: 12/30/2022]
Abstract
Mismatch negativity (MMN) and P3a are auditory event-related potential (ERP) components that show robust deficits in schizophrenia (SZ) patients and exhibit qualities of endophenotypes, including substantial heritability, test-retest reliability, and trait-like stability. These measures also fulfill criteria for use as cognition and function-linked biomarkers in outcome studies, but have not yet been validated for use in large-scale multi-site clinical studies. This study tested the feasibility of adding MMN and P3a to the ongoing Consortium on the Genetics of Schizophrenia (COGS) study. The extent to which demographic, clinical, cognitive, and functional characteristics contribute to variability in MMN and P3a amplitudes was also examined. Participants (HCS n=824, SZ n=966) underwent testing at 5 geographically distributed COGS laboratories. Valid ERP recordings were obtained from 91% of HCS and 91% of SZ patients. Highly significant MMN (d=0.96) and P3a (d=0.93) amplitude reductions were observed in SZ patients, comparable in magnitude to those observed in single-lab studies with no appreciable differences across laboratories. Demographic characteristics accounted for 26% and 18% of the variance in MMN and P3a amplitudes, respectively. Significant relationships were observed among demographically-adjusted MMN and P3a measures and medication status as well as several clinical, cognitive, and functional characteristics of the SZ patients. This study demonstrates that MMN and P3a ERP biomarkers can be feasibly used in multi-site clinical studies. As with many clinical tests of brain function, demographic factors contribute to MMN and P3a amplitudes and should be carefully considered in future biomarker-informed clinical studies.
Collapse
Affiliation(s)
- Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Michael L. Thomas
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | | | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA
| | - Marlena Pela
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Richard F. Sharp
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY,James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles School of Public Health, Los Angeles, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA,Center for Behavioral Genomics, and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston, MA
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
| |
Collapse
|
38
|
Nuechterlein KH, Green MF, Calkins ME, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Light GA, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL. Attention/vigilance in schizophrenia: performance results from a large multi-site study of the Consortium on the Genetics of Schizophrenia (COGS). Schizophr Res 2015; 163:38-46. [PMID: 25749017 PMCID: PMC4382444 DOI: 10.1016/j.schres.2015.01.017] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2014] [Revised: 01/07/2015] [Accepted: 01/09/2015] [Indexed: 12/31/2022]
Abstract
Attention/vigilance impairments are present in individuals with schizophrenia across psychotic and remitted states and in their first-degree relatives. An important question is whether deficits in attention/vigilance can be consistently and reliably measured across sites varying in many participant demographic, clinical, and functional characteristics, as needed for large-scale genetic studies of endophenotypes. We examined Continuous Performance Test (CPT) data from phase 2 of the Consortium on the Genetics of Schizophrenia (COGS-2), the largest-scale assessment of cognitive and psychophysiological endophenotypes relevant to schizophrenia. The CPT data from 2251 participants from five sites were examined. A perceptual-load vigilance task (the Degraded Stimulus CPT or DS-CPT) and a memory-load vigilance task (CPT-Identical Pairs or CPT-IP) were utilized. Schizophrenia patients performed more poorly than healthy comparison subjects (HCS) across sites, despite significant site differences in participant age, sex, education, and racial distribution. Patient-HCS differences in signal/noise discrimination (d') in the DS-CPT varied significantly across sites, but averaged a medium effect size. CPT-IP performance showed large patient-HCS differences across sites. Poor CPT performance was independent of or weakly correlated with symptom severity, but was significantly associated with lower educational achievement and functional capacity. Current smoking was associated with poorer CPT-IP d'. Patients taking both atypical and typical antipsychotic medication performed more poorly than those on no or atypical antipsychotic medications, likely reflecting their greater severity of illness. We conclude that CPT deficits in schizophrenia can be reliably detected across sites, are relatively independent of current symptom severity, and are related to functional capacity.
Collapse
Affiliation(s)
- Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States,Corresponding author: Keith H. Nuechterlein, Department of Psychiatry and Biobehavioral Science, David Geffen School of Medicine at UCLA, 300 UCLA Medical Plaza, Room 2240, Los Angeles, CA 90095-6968.
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States, VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Tiffany A. Greenwood
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA United States, Department of Pediatrics, Stanford University, Stanford, CA, United States
| | - Gregory A. Light
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States, VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States, Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States, James J. Peters VA Medical Center, New York, NY, United States
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States, James J. Peters VA Medical Center, New York, NY, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States, Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California, Los Angeles, CA, United States, VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States, Department of Biostatistics, University of California, Los Angeles, CA, United States
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States, VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Ming T. Tsuang
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, Institute for Genomic Medicine, University of California, San Diego, CA, United States,The Center for Behavioral Genomics, Department of Psychiatry, University of California, San Diego, CA, United States, Harvard Institute of Psychiatry Epidemiology and Genetics, Boston, MA, United States
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - David L. Braff
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States, VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| |
Collapse
|
39
|
Turetsky BI, Dress EM, Braff DL, Calkins ME, Green MF, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Nuechterlein KH, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Light G. The utility of P300 as a schizophrenia endophenotype and predictive biomarker: clinical and socio-demographic modulators in COGS-2. Schizophr Res 2015; 163:53-62. [PMID: 25306203 PMCID: PMC4382423 DOI: 10.1016/j.schres.2014.09.024] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 09/09/2014] [Accepted: 09/11/2014] [Indexed: 10/24/2022]
Abstract
Reduced auditory P300 amplitude is a robust schizophrenia deficit exhibiting the qualities of a viable genetic endophenotype. These include heritability, test-retest reliability, and trait-like stability. Recent evidence suggests that P300 may also serve as a predictive biomarker for transition to psychosis during the schizophrenia prodrome. Historically, the utility of the P300 has been limited by its clinical nonspecificity, cross-site measurement variability, and required EEG expertise. The Consortium on the Genetics of Schizophrenia (COGS-2) study provided an opportunity to examine the consistency of the measure across multiple sites with varying degrees of EEG experience, and to identify important modulating factors that contribute to measurement variability. Auditory P300 was acquired from 649 controls and 587 patients at 5 sites. An overall patient deficit was observed with effect size 0.62. Each site independently observed a significant patient deficit, but site differences also existed. In patients, site differences reflected clinical differences in positive symptomatology and functional capacity. In controls, site differences reflected differences in racial stratification, smoking and substance use history. These factors differentially suppressed the P300 response, but only in control subjects. This led to an attenuated patient-control difference among smokers and among African Americans with history of substance use. These findings indicate that the P300 can be adequately assessed quantitatively, across sites, without substantial EEG expertise. Measurements are suitable for both genetic endophenotype analyses and studies of psychosis risk and conversion. However, careful attention must be given to selection of appropriate comparison samples to avoid misleading false negative results.
Collapse
Affiliation(s)
- Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia,
PA
| | - Erich M. Dress
- Department of Psychiatry, University of Pennsylvania, Philadelphia,
PA
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La
Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia,
PA
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen School
of Medicine, University of California Los Angeles, Los Angeles, CA,VA Greater Los Angeles Healthcare System, Los Angeles, CA
| | | | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia,
PA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia,
PA
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford
University, Palo Alto, CA
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen School
of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences, University of
Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the
Beth Israel Deaconess Medical Center, Boston, MA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New
York, NY,James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New
York, NY,James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La
Jolla, CA
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA,Massachusetts Mental Health Center Public Psychiatry Division of the
Beth Israel Deaconess Medical Center, Boston, MA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los Angeles
School of Public Health, Los Angeles, CA
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La
Jolla, CA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences, University of
Washington, Seattle, WA,VA Puget Sound Health Care System, Seattle, WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La
Jolla, CA,Center for Behavioral Genomics, and Institute for Genomic Medicine,
University of California SanDiego, La Jolla, CA,Harvard Institute of Psychiatric Epidemiology and Genetics, Boston,
MA
| | - Gregory Light
- Department of Psychiatry, University of California San Diego, La
Jolla, CA,VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| |
Collapse
|
40
|
Factor structure and heritability of endophenotypes in schizophrenia: findings from the Consortium on the Genetics of Schizophrenia (COGS-1). Schizophr Res 2015; 163:73-9. [PMID: 25682549 PMCID: PMC5944296 DOI: 10.1016/j.schres.2015.01.027] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Revised: 01/14/2015] [Accepted: 01/17/2015] [Indexed: 11/23/2022]
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.
Collapse
|
41
|
Gur RC, Braff DL, Calkins ME, Dobie DJ, Freedman R, Green MF, Greenwood TA, Lazzeroni LC, Light GA, Nuechterlein KH, Olincy A, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Gur RE. Neurocognitive performance in family-based and case-control studies of schizophrenia. Schizophr Res 2015; 163:17-23. [PMID: 25432636 PMCID: PMC4441547 DOI: 10.1016/j.schres.2014.10.049] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2014] [Revised: 10/19/2014] [Accepted: 10/21/2014] [Indexed: 11/19/2022]
Abstract
BACKGROUND Neurocognitive deficits in schizophrenia (SZ) are established and the Consortium on the Genetics of Schizophrenia (COGS) investigated such measures as endophenotypes in family-based (COGS-1) and case-control (COGS-2) studies. By requiring family participation, family-based sampling may result in samples that vary demographically and perform better on neurocognitive measures. METHODS The Penn computerized neurocognitive battery (CNB) evaluates accuracy and speed of performance for several domains and was administered across sites in COGS-1 and COGS-2. Most tests were included in both studies. COGS-1 included 328 patients with SZ and 497 healthy comparison subjects (HCS) and COGS-2 included 1195 patients and 1009 HCS. RESULTS Demographically, COGS-1 participants were younger, more educated, with more educated parents and higher estimated IQ compared to COGS-2 participants. After controlling for demographics, the two samples produced very similar performance profiles compared to their respective controls. As expected, performance was better and with smaller effect sizes compared to controls in COGS-1 relative to COGS-2. Better performance was most pronounced for spatial processing while emotion identification had large effect sizes for both accuracy and speed in both samples. Performance was positively correlated with functioning and negatively with negative and positive symptoms in both samples, but correlations were attenuated in COGS-2, especially with positive symptoms. CONCLUSIONS Patients ascertained through family-based design have more favorable demographics and better performance on some neurocognitive domains. Thus, studies that use case-control ascertainment may tap into populations with more severe forms of illness that are exposed to less favorable factors compared to those ascertained with family-based designs.
Collapse
Affiliation(s)
- Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - David L. Braff
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - Dorcas J. Dobie
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Robert Freedman
- Department of Psychiatry, University of Colorado Denver,
Aurora, CO
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Sciences, Geffen
School of Medicine, University of California Los Angeles, Los Angeles, CA; VA
Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Tiffany A. Greenwood
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | | | - Gregory A. Light
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Sciences, Geffen
School of Medicine, University of California Los Angeles, Los Angeles, CA; VA
Greater Los Angeles Healthcare System, Los Angeles, CA
| | - Ann Olincy
- Department of Psychiatry, University of Colorado Denver,
Aurora, CO
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston,
MA; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel
Deaconess Medical Center, Boston, MA
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of
Medicine, New York, NY; 13James J. Peters VA Medical Center, New York, NY
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of
Medicine, New York, NY; 13James J. Peters VA Medical Center, New York, NY
| | - Joyce Sprock
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston,
MA; Massachusetts Mental Health Center Public Psychiatry Division of the Beth Israel
Deaconess Medical Center, Boston, MA
| | - Catherine A. Sugar
- Department of Biostatistics, University of California Los
Angeles School of Public Health, Los Angeles, CA
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Sciences,
University of Washington, Seattle, WA; VA Puget Sound Health Care System, Seattle,
WA
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San
Diego, La Jolla, CA; VISN-22 Mental Illness, Research, Education and Clinical Center
(MIRECC), VA San Diego Healthcare System
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania,
Philadelphia, PA
| |
Collapse
|
42
|
Lee J, Green MF, Calkins ME, Greenwood TA, Gur RE, Gur RC, Lazzeroni LC, Light GA, Nuechterlein KH, Radant AD, Seidman LJ, Siever LJ, Silverman JM, Sprock J, Stone WS, Sugar CA, Swerdlow NR, Tsuang DW, Tsuang MT, Turetsky BI, Braff DL. Verbal working memory in schizophrenia from the Consortium on the Genetics of Schizophrenia (COGS) study: the moderating role of smoking status and antipsychotic medications. Schizophr Res 2015; 163:24-31. [PMID: 25248939 PMCID: PMC4368500 DOI: 10.1016/j.schres.2014.08.014] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Revised: 08/03/2014] [Accepted: 08/06/2014] [Indexed: 10/24/2022]
Abstract
OBJECTIVES Working memory impairment has been extensively studied in schizophrenia, but less is known about moderators of the impairment. Using the Consortium on the Genetics of Schizophrenia case-control study (COGS-2), we examined smoking status, types of antipsychotic medication, and history of substance as moderators for working memory impairment in schizophrenia. METHODS From 5 sites, 1377 patients with schizophrenia or schizoaffective, depressed type and 1037 healthy controls completed the letter-number span (LNS) task. The LNS uses intermixed letter and digit stimuli that increase from 2 up to 8 stimuli. In the forward condition, participants repeated the letters and numbers in the order they were presented. In the reorder condition, participants repeated the digits in ascending order followed by letters in alphabetical order. RESULTS Schizophrenia patients performed more poorly than controls, with a larger difference on reorder than forward conditions. Deficits were associated with symptoms, functional capacity, and functional outcome. Patients who smoked showed larger impairment than nonsmoking patients, primarily due to deficits on the reorder condition. The impairing association of smoking was more pronounced among patients taking first-generation than those taking second-generation antipsychotic medications. Correlations between working memory and community functioning were stronger for nonsmokers. History of substance use did not moderate working memory impairment. CONCLUSIONS Results confirm the working memory impairment in schizophrenia, and indicate smoking status as an important moderator for these deficits. The greater impairment in smokers may reflect added burden of smoking on general health or that patients with greater deficits are more likely to smoke.
Collapse
Affiliation(s)
- Junghee Lee
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California Los Angeles, CA, United States; VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States.
| | - Michael F. Green
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California Los Angeles, CA, United States
,VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Tiffany A. Greenwood
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - Laura C. Lazzeroni
- Department of Psychiatry and Behavioral Science, Stanford University, Stanford, CA United States
,Department of Pediatrics, Stanford University, Stanford, CA, United States
| | - Gregory A. Light
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
,VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - Keith H. Nuechterlein
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California Los Angeles, CA, United States
| | - Allen D. Radant
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States
,VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Larry J. Seidman
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
,Massachusetts Mental Health Center Public Psychiatry Devision of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Larry J. Siever
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States
,James J. Peters VA Medical Center, New York, NY, United States
| | - Jeremy M. Silverman
- Department of Psychiatry, The Mount Sinai School of Medicine, New York, NY, United States
,James J. Peters VA Medical Center, New York, NY, United States
| | - Joyce Sprock
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
,VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| | - William S. Stone
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States
,Massachusetts Mental Health Center Public Psychiatry Devision of the Beth Israel Deaconess Medical Center, Boston, MA, United States
| | - Catherine A. Sugar
- Department of Psychiatry and Biobehavioral Science, Geffen School of Medicine, University of California Los Angeles, CA, United States
,VA Greater Los Angeles Healthcare System, Los Angeles, CA, United States
,Department of Biostatistics, University of California Los Angeles, CA, United States
| | - Neal R. Swerdlow
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral Science, University of Washington, Seattle, WA, United States
,VA Puget Sound Healthcare System, Seattle, WA, United States
| | - Ming T. Tsuang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
,Institute for Genomic Medicine, University of California, San Diego, CA, United States
,Harvard Institute of Psychiatry Epidemiology and Genetics, Boston, MA, United States
| | - Bruce I. Turetsky
- Department of Psychiatry, University of Pennsylvania, Philadelphia, United States
| | - David L. Braff
- Department of Psychiatry, University of California San Diego, La Jolla, CA, United States
,VISN22, Mental Illness Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA, United States
| |
Collapse
|