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Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study

Molecular Psychiatry volume 27, pages 3719–3730 (2022)Cite this article

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Abstract

Cognitive deficits are among the best predictors of real-world functioning in schizophrenia. However, our understanding of how cognitive deficits relate to neuropathology and clinical presentation over the disease lifespan is limited. Here, we combine multi-site, harmonized cognitive, imaging, demographic, and clinical data from over 900 individuals to characterize a) cognitive deficits across the schizophrenia lifespan and b) the association between cognitive deficits, clinical presentation, and white matter (WM) microstructure. Multimodal harmonization was accomplished using T-scores for cognitive data, previously reported standardization methods for demographic and clinical data, and an established harmonization method for imaging data. We applied t-tests and correlation analysis to describe cognitive deficits in individuals with schizophrenia. We then calculated whole-brain WM fractional anisotropy (FA) and utilized regression-mediation analyses to model the association between diagnosis, FA, and cognitive deficits. We observed pronounced cognitive deficits in individuals with schizophrenia (p < 0.006), associated with more positive symptoms and medication dosage. Regression-mediation analyses showed that WM microstructure mediated the association between schizophrenia and language/processing speed/working memory/non-verbal memory. In addition, processing speed mediated the influence of diagnosis and WM microstructure on the other cognitive domains. Our study highlights the critical role of cognitive deficits in schizophrenia. We further show that WM is crucial when trying to understand the role of cognitive deficits, given that it explains the association between schizophrenia and cognitive deficits (directly and via processing speed).

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Fig. 1: Mediation analyses utilized in the present study.
Fig. 2: Group comparisons between individuals with schizophrenia (SCZ) and healthy individuals for the eight cognitive domains investigated in the present study.

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Acknowledgements

We gratefully acknowledge funding provided by the following National Institutes of Health (NIH) grants: R01MH102377, K24MH110807 (PI: MK), R01MH119222 (PI: YR), R03 MH110745, K01 MH115247–01A1 (PI: AEL), VA Merit Award and U01 MH109977 (PI: MES), R01MH108574 (PI: OP), MRC G0500092 (PI: AJ), R01MH076995 (PI: PS), P50MH080173 (PI: AKM), 1R01 MH102318-01A1 (PI: RWB), R01MH092440, MH078113 (PI: MK), MH077851 (PI: CT), MH077945 (PI: GP), MH077862 (PI: JS), 1R01MH102324-01A1 (PI: AV). We also acknowledge funding provided by the Swiss National Science Foundation (SNF) grant 152619 (PI: SW), National Research Foundation of Korea (NRF) grant NRF-2012R1A1A1006514 (PI: JL), the University of Cincinnati Schizophrenia Research Fund (JAS), BWH Program for Interdisciplinary Neuroscience (through a gift from Lawrence and Tina Rand (PI: SC-K), the Harvard Medical School Livingston Fellowship Award (PI: JS-H), and BBRF NARSAD Young Investigator grants (PI: SC-K, PI: Dr. AEL, PI: JS-H [funded by Mary and John Osterhaus and the Brain & Behavior Research Foundation]).

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Authors and Affiliations

  1. Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Johanna Seitz-Holland, Suheyla Cetin-Karayumak, Amanda E. Lyall, Ofer Pasternak, Yogesh Rathi, Sinead Kelly, Martha E. Shenton & Marek Kubicki

  2. Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Johanna Seitz-Holland, Amanda E. Lyall, Yogesh Rathi, Martha E. Shenton & Marek Kubicki

  3. Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Harvard Medical School, Boston, MA, USA

    Joanne D. Wojcik, Sinead Kelly, Matcheri S. Keshavan & Raquelle I. Mesholam-Gately

  4. Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Yogesh Rathi, Martha E. Shenton & Marek Kubicki

  5. Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Mark Vangel

  6. Department of Psychiatry, Yale University, New Haven, CT, USA

    Godfrey Pearlson

  7. Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA

    Carol Tamminga

  8. Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA

    John A. Sweeney

  9. Department of Psychology and Neuroscience, Bio-Imaging Research Center, University of Georgia, Athens, GA, USA

    Brett A. Clementz

  10. Department of Psychiatry and Behavioral Sciences, Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD, USA

    David A. Schretlen

  11. University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland

    Petra Verena Viher, Katharina Stegmayer & Sebastian Walther

  12. Department of Psychiatry, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea

    Jungsun Lee

  13. Department of Psychiatry, SANE POWIC, Warneford Hospital, University of Oxford, Oxford, UK

    Tim Crow & Anthony James

  14. Center for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, ON, Canada

    Aristotle Voineskos

  15. Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA

    Robert W. Buchanan

  16. Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Philip R. Szeszko

  17. Mental Illness Research, Education and Clinical Center, James J. Peters VA Medical Center, Bronx, New York, NY, USA

    Philip R. Szeszko

  18. The Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA

    Anil K. Malhotra

Authors
  1. Johanna Seitz-Holland
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Contributions

JS-H: study design, data analysis and interpretation, visualization, writing original draft; JDW: data curation, methodology, data interpretation, writing original draft; SC-K: data curation, methodology, data interpretation, visualization, writing original draft; AEL: data interpretation, writing review and editing; OP: data interpretation, writing review and editing; YR: data curation, methodology, data interpretation, writing review and editing; MV: statistical supervision, writing review and editing; GP: funding acquisition original study, data collection, writing review and editing; CT: funding acquisition original study, data collection, writing review and editing; JAS: funding acquisition original study, data collection, writing review and editing; BAC: data collection, writing review and editing; DAS: data collection, writing review and editing; PVV: data collection, writing review and editing; KS: data collection, writing review and editing; SW: funding acquisition original study, data collection, writing review and editing; JL: funding acquisition original study, data collection, writing review and editing; TC: data collection, writing review and editing; AJ: funding acquisition original study, data collection, writing review and editing; AV: funding acquisition original study, data collection, writing review and editing; RWB: funding acquisition original study, data collection, writing review and editing; PRS: funding acquisition original study, data collection, writing review and editing; AKM: funding acquisition original study, data collection, writing review and editing; SK: data interpretation, writing review and editing; MES: funding acquisition original study, data collection, data interpretation, writing review and editing, MSK: funding acquisition original study, data collection, data interpretation, writing review and editing; RIMG: study design, methodology, data interpretation, writing original draft; MK: funding acquisition, study design, data interpretation, writing original draft

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Correspondence to Johanna Seitz-Holland.

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JAS consults to VeraSci. The other authors declare no competing interests.

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Seitz-Holland, J., Wojcik, J.D., Cetin-Karayumak, S. et al. Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study. Mol Psychiatry 27, 3719–3730 (2022). https://doi.org/10.1038/s41380-022-01731-3

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