Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Baseline brain structural and functional predictors of clinical outcome in the early course of schizophrenia

Abstract

Although schizophrenia is considered a brain disorder, the role of brain organization for symptomatic improvement remains inadequately defined. We investigated the relationship between baseline brain morphology, resting-state network connectivity and clinical response after 24-weeks of antipsychotic treatment in patients with schizophrenia (n = 95) using integrated multivariate analyses. There was no significant association between clinical response and measures of cortical thickness (r = 0.37, p = 0.98) and subcortical volume (r = 0.56, p = 0.15). By contrast, we identified a strong mode of covariation linking functional network connectivity to clinical response (r = 0.70; p = 0.04), and particularly to improvement in positive (weight = 0.62) and anxious/depressive symptoms (weight = 0.49). Higher internal cohesiveness of the default mode network was the single most important positive predictor. Key negative predictors involved the functional cohesiveness of central executive subnetworks anchored in the frontoparietal cortices and subcortical regions (including the thalamus and striatum) and the inter-network integration between the default mode and sensorimotor networks. The present findings establish links between clinical response and the functional organization of brain networks involved both in perception and in spontaneous and goal-directed cognition, thereby advancing our understanding of the pathophysiology of schizophrenia.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Murray CJ, Vos T, Lozano R, Naghavi M, Flaxman AD, Michaud, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2197–223.

    PubMed  Google Scholar 

  2. Hafner H, an der Heiden W. The course of schizophrenia in the light of modern follow-up studies: the ABC and WHO studies. Eur Arch Psychiatry Clin Neurosci. 1999;249(Suppl 4):14–26.

    PubMed  Google Scholar 

  3. Rosenbaum B, Valbak K, Harder S, Knudsen P, Koster A, Lajer M, et al. Treatment of patients with first-episode psychosis: 2-year outcome data from the Danish National Schizophrenia Project. World Psychiatry. 2006;5:100–3.

    PubMed  PubMed Central  Google Scholar 

  4. Harvey PD, Heaton RK, Carpenter WT Jr., Green MF, Gold JM, et al. Functional impairment in people with schizophrenia: focus on employability and eligibility for disability compensation. Schizophr Res. 2012;140:1–8.

    PubMed  PubMed Central  Google Scholar 

  5. Rosenheck RA, Estroff SE, Sint K, Lin H, Mueser KT, Robinson DG, et al. Incomes and outcomes: social security disability benefits in first-episode psychosis. Am J Psychiatry. 2017;174:886–94.

    PubMed  Google Scholar 

  6. Hayes JF, Marston L, Walters K, King MB, Osborn DPJ. Mortality gap for people with bipolar disorder and schizophrenia: UK-based cohort study 2000-14. Br J Psychiatry J Ment Sci. 2017;211:175–81.

    Google Scholar 

  7. Saha S, Chant D, McGrath J. A systematic review of mortality in schizophrenia: is the differential mortality gap worsening over time? Arch Gen Psychiatry. 2007;64:1123–31.

    PubMed  Google Scholar 

  8. Davidson L, McGlashan TH. The varied outcomes of schizophrenia. Can J Psychiatry. 1997;42:34–43.

    CAS  PubMed  Google Scholar 

  9. Heilbronner U, Samara M, Leucht S, Falkai P, Schulze TG. The longitudinal course of schizophrenia across the lifespan: clinical, cognitive, and neurobiological aspects. Harv Rev Psychiatry. 2016;24:118–28.

    PubMed  PubMed Central  Google Scholar 

  10. Conus P, Cotton S, Schimmelmann BG, McGorry PD, Lambert M. Rates and predictors of 18-months remission in an epidemiological cohort of 661 patients with first-episode psychosis. Soc Psychiatry Psychiatr Epidemiol. 2017;52:1089–99.

    PubMed  Google Scholar 

  11. Koutsouleris N, Kahn RS, Chekroud AM, Leucht S, Falkai P, Wobrock T, et al. Multisite prediction of 4 and 52-week treatment outcomes in patients with first-episode psychosis: a machine learning approach. Lancet Psychiatry. 2016;3:935–46.

    PubMed  Google Scholar 

  12. Menezes NM, Arenovich T, Zipursky RB. A systematic review of longitudinal outcome studies of first-episode psychosis. Psychol Med. 2006;36:1349–62.

    CAS  PubMed  Google Scholar 

  13. Samara MT, Leucht C, Leeflang MM, Anghelescu IG, Chung YC, Crespo-Facorro B, et al. Early improvement as a predictor of later response to antipsychotics in schizophrenia: a diagnostic test review. Am J Psychiatry. 2015;172:617–29.

    PubMed  Google Scholar 

  14. Birur B, Kraguljac NV, Shelton RC, Lahti AC. Brain structure, function, and neurochemistry in schizophrenia and bipolar disorder-a systematic review of the magnetic resonance neuroimaging literature. NPJ Schizophr. 2017;3:15.

    PubMed  PubMed Central  Google Scholar 

  15. van Erp TG, Hibar DP, Rasmussen JM, Glahn DC, Pearlson GD, Andreassen OA, et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol Psychiatry. 2016;21:585.

    PubMed  Google Scholar 

  16. Van Erp TG, Walton E, Hibar DP, Schmaal L, Jiang W, Glahn DC et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 controls via the ENIGMA consortium. Biol Psychiatry. 2018. https://doi.org/10.1016/j.biopsych.2018.04.023. (paper in press- no volume or page available yet)

  17. Dong D, Wang Y, Chang X, Luo C, Yao D. Dysfunction of large-scale brain networks in schizophrenia: a meta-analysis of resting-state functional connectivity. Schizophr Bull. 2018;44:168–81.

    PubMed  Google Scholar 

  18. Lee WH, Doucet GE, Leibu E, Frangou S. Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia. Schizophr Res. 2018;pii: S0920-9964(18)30242-1.

  19. Doucet G, Rider R, Taylor N, Skidmore C, Sharan A, Sperling M et al. Pre-surgery resting-state local graph-theory measures predict neurocognitive outcomes after brain surgery in temporal lobe epilepsy. Epilepsia. 2015;56:517–26.

  20. Willette AA, Calhoun VD, Egan JM, Kapogiannis D, Alzheimers Disease Neuroimaging I. Prognostic classification of mild cognitive impairment and Alzheimer’s disease: MRI independent component analysis. Psychiatry Res. 2014;224:81–88.

    PubMed  PubMed Central  Google Scholar 

  21. Lieberman J, Chakos M, Wu H, Alvir J, Hoffman E, Robinson D, et al. Longitudinal study of brain morphology in first episode schizophrenia. Biol Psychiatry. 2001;49:487–99.

    CAS  PubMed  Google Scholar 

  22. Lieberman J, Jody D, Geisler S, Alvir J, Loebel A, Szymanski S, et al. Time course and biologic correlates of treatment response in first-episode schizophrenia. Arch Gen Psychiatry. 1993;50:369–76.

    CAS  PubMed  Google Scholar 

  23. Molina V, Reig S, Sarramea F, Sanz J, Francisco Artaloytia J, Luque R, et al. Anatomical and functional brain variables associated with clozapine response in treatment-resistant schizophrenia. Psychiatry Res. 2003;124:153–61.

    CAS  PubMed  Google Scholar 

  24. Nieuwenhuis M, Schnack HG, van Haren NE, Lappin J, Morgan C, Reinders AA, et al. Multi-center MRI prediction models: predicting sex and illness course in first episode psychosis patients. Neuroimage. 2017;145(Pt B):246–53.

    PubMed  PubMed Central  Google Scholar 

  25. Palaniyappan L, Marques TR, Taylor H, Handley R, Mondelli V, Bonaccorso S, et al. Cortical folding defects as markers of poor treatment response in first-episode psychosis. JAMA Psychiatry. 2013;70:1031–40.

    PubMed  Google Scholar 

  26. Cahn W, van Haren NE, Hulshoff Pol HE, Schnack HG, Caspers E, Laponder DA, et al. Brain volume changes in the first year of illness and 5-year outcome of schizophrenia. Br J Psychiatry J Ment Sci. 2006;189:381–2.

    CAS  Google Scholar 

  27. Prasad KM, Sahni SD, Rohm BR, Keshavan MS. Dorsolateral prefrontal cortex morphology and short-term outcome in first-episode schizophrenia. Psychiatry Res. 2005;140:147–55.

    PubMed  Google Scholar 

  28. Milev P, Ho BC, Arndt S, Nopoulos P, Andreasen NC. Initial magnetic resonance imaging volumetric brain measurements and outcome in schizophrenia: a prospective longitudinal study with 5-year follow-up. Biol Psychiatry. 2003;54:608–15.

    PubMed  Google Scholar 

  29. Bodnar M, Harvey PO, Malla AK, Joober R, Lepage M. The parahippocampal gyrus as a neural marker of early remission in first-episode psychosis: a voxel-based morphometry study. Clin Schizophr Relat Psychoses. 2011;4:217–28.

    PubMed  Google Scholar 

  30. Bodnar M, Malla AK, Joober R, Lord C, Smith E, Pruessner J, et al. Neural markers of early remission in first-episode schizophrenia: a volumetric neuroimaging study of the parahippocampus. Psychiatry Res. 2012;201:40–47.

    PubMed  Google Scholar 

  31. Molina V, Martin C, Ballesteros A, de Herrera AG, Hernandez-Tamames JA. Optimized voxel brain morphometry: association between brain volumes and the response to atypical antipsychotics. Eur Arch Psychiatry Clin Neurosci. 2011;261:407–16.

    PubMed  Google Scholar 

  32. Nejad AB, Madsen KH, Ebdrup BH, Siebner HR, Rasmussen H, Aggernaes B, et al. Neural markers of negative symptom outcomes in distributed working memory brain activity of antipsychotic-naive schizophrenia patients. Int J Neuropsychopharmacol. 2013;16:1195–204.

    CAS  PubMed  Google Scholar 

  33. Kraguljac NV, White DM, Hadley N, Hadley JA, Ver Hoef L, Davis E, et al. Aberrant hippocampal connectivity in unmedicated patients with schizophrenia and effects of antipsychotic medication: a longitudinal resting state functional MRI study. Schizophr Bull. 2016;42:1046–55.

    PubMed  PubMed Central  Google Scholar 

  34. Sarpal DK, Argyelan M, Robinson DG, Szeszko PR, Karlsgodt KH, John M, et al. Baseline striatal functional connectivity as a predictor of response to antipsychotic drug treatment. Am J Psychiatry. 2016;173:69–77.

    PubMed  Google Scholar 

  35. Andreasen NC, Carpenter WT Jr., Kane JM, Lasser RA, Marder SR, et al. Remission in schizophrenia: proposed criteria and rationale for consensus. Am J Psychiatry. 2005;162:441–9.

    PubMed  Google Scholar 

  36. Karow A, Naber D, Lambert M, Moritz S, Initiative E. Remission as perceived by people with schizophrenia, family members and psychiatrists. Eur Psychiatry. 2012;27:426–31.

    CAS  PubMed  Google Scholar 

  37. Russo M, Levine SZ, Demjaha A, Di Forti M, Bonaccorso S, Fearon P, et al. Association between symptom dimensions and categorical diagnoses of psychosis: a cross-sectional and longitudinal investigation. Schizophr Bull. 2014;40:111–9.

    PubMed  Google Scholar 

  38. Esteghamati A, Khalilzadeh O, Anvari M, Ahadi MS, Abbasi M, Rashidi A. Metabolic syndrome and insulin resistance significantly correlate with body mass index. Arch Med Res. 2008;39:803–8.

    CAS  PubMed  Google Scholar 

  39. Johnson W, Bouchard TJ Jr., Krueger RF, McGue M, Gottesman II. Just one g: consistent results from three test batteries. Intelligence. 2004;32:95–107.

    Google Scholar 

  40. Plomin R, Deary IJ. Genetics and intelligence differences: five special findings. Mol Psychiatry. 2015;20:98–108.

    CAS  PubMed  Google Scholar 

  41. Moser DA, Doucet GE, Lee WH, Rasgon A, Krinsky H, Leibu E, et al. Multivariate associations among behavioral, clinical and multimodal imaging phenotypes in psychosis. JAMA Psychiatry. 2018;75:386–95.

    PubMed  PubMed Central  Google Scholar 

  42. Hermes E, Nasrallah H, Davis V, Meyer J, McEvoy J, Goff D, et al. The association between weight change and symptom reduction in the CATIE schizophrenia trial. Schizophr Res. 2011;128:166–70.

    PubMed  PubMed Central  Google Scholar 

  43. Ventura J, Subotnik KL, Guzik LH, Hellemann GS, Gitlin MJ, Wood RC, et al. Remission and recovery during the first outpatient year of the early course of schizophrenia. Schizophr Res. 2011;132:18–23.

    PubMed  PubMed Central  Google Scholar 

  44. Witten DM, Tibshirani R, Hastie T. A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis. Biostatistics. 2009;10:515–34.

    PubMed  PubMed Central  Google Scholar 

  45. Breiman L, Friedman JH. Predicting multivariate responses in multiple linear regression. J R Stat Soc Ser B Stat Methodol. 1997;59:3–54.

    Google Scholar 

  46. Klami A, Virtanen S, Kaski S. Bayesian canonical correlation analysis. J Mac Learn Res. 2013;14:965–1003.

    Google Scholar 

  47. Association AP. Diagnostic and statistical manual of mental disorders. Arlington, VA: American Psychiatric Publishing; 2013.

    Google Scholar 

  48. First MB, Williams JBW, Karg RS, Spitzer RL. Structured clinical interview for DSM-5, research version. American Psychiatric Association, Arlington, VA; 2015.

  49. Wechsler D. Wechsler Abbreviated Scale of Intelligence. 2nd ed. San Antonio, TX: NCS Pearson; 2011.

    Google Scholar 

  50. Wells R, Swaminathan V, Sundram S, Weinberg D, Bruggemann J, Jacomb I, et al. The impact of premorbid and current intellect in schizophrenia: cognitive, symptom, and functional outcomes. NPJ Schizophr. 2015;1:15043.

    PubMed  PubMed Central  Google Scholar 

  51. Ventura J, Green MF, Shaner A, Liberman RP. Training and quality assurance with the Brief Psychiatric Rating Scale. Int J Methods Psychiatr Res. 1993;3:221–44.

    Google Scholar 

  52. Kopelowicz A, Ventura J, Liberman RP, Mintz J. Consistency of Brief Psychiatric Rating Scale factor structure across a broad spectrum of schizophrenia patients. Psychopathology. 2008;41:77–84.

    PubMed  Google Scholar 

  53. Gardner DM, Murphy AL, O’Donnell H, Centorrino F, Baldessarini RJ. International consensus study of antipsychotic dosing. Am J Psychiatry. 2010;167:686–93.

    PubMed  Google Scholar 

  54. Leucht S, Cipriani A, Spineli L, Mavridis D, Orey D, Richter F, et al. Comparative efficacy and tolerability of 15 antipsychotic drugs in schizophrenia: a multiple-treatments meta-analysis. Lancet. 2013;382:951–62.

    CAS  PubMed  Google Scholar 

  55. Tiihonen J, Wahlbeck K, Lonnqvist J, Klaukka T, Ioannidis JP, Volavka J, et al. Effectiveness of antipsychotic treatments in a nationwide cohort of patients in community care after first hospitalisation due to schizophrenia and schizoaffective disorder: observational follow-up study. BMJ. 2006;333:224.

    PubMed  PubMed Central  Google Scholar 

  56. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–80.

    PubMed  Google Scholar 

  57. Doucet GE, Rasgon N, McEwen BS, Micali N, Frangou S. Elevated body mass index is associated with increased integration and reduced cohesion of sensory-driven and internally guided resting-state functional brain networks. Cereb Cortex. 2018;28:988–97.

    PubMed  Google Scholar 

  58. Gu S, Satterthwaite TD, Medaglia JD, Yang M, Gur RE, Gur RC, et al. Emergence of system roles in normative neurodevelopment. Proc Natl Acad Sci USA. 2015;112:13681–6.

    CAS  PubMed  Google Scholar 

  59. Zalesky A, Fornito A, Harding IH, Cocchi L, Yucel M, Pantelis C, et al. Whole-brain anatomical networks: does the choice of nodes matter? Neuroimage. 2010;50:970–83.

    PubMed  Google Scholar 

  60. Crossley NA, Mechelli A, Vertes PE, Winton-Brown TT, Patel AX, Ginestet CE, et al. Cognitive relevance of the community structure of the human brain functional coactivation network. Proc Natl Acad Sci USA. 2013;110:11583–8.

    CAS  PubMed  Google Scholar 

  61. Moser DA, Doucet GE, Ing A, Dima D, Schumann G, Bilder RM et al. An integrated brain-behavior model for working memory. Mol Psychiatry. 2017. https://doi.org/10.1038/mp.2017.247. (paper in press- no volume or page available yet)

  62. Lambert M, Karow A, Leucht S, Schimmelmann BG, Naber D. Remission in schizophrenia: validity, frequency, predictors, and patients’ perspective 5 years later. Dialog Clin Neurosci. 2010;12:393–407.

    Google Scholar 

  63. Corbetta M, Kincade JM, Shulman GL. Neural systems for visual orienting and their relationships to spatial working memory. J Cogn Neurosci. 2002;14:508–23.

    PubMed  Google Scholar 

  64. Doucet G, Naveau M, Petit L, Delcroix N, Zago L, Crivello F, et al. Brain activity at rest: a multiscale hierarchical functional organization. J Neurophysiol. 2011;105:2753–63.

    PubMed  Google Scholar 

  65. Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA. 2005;102:9673–8.

    CAS  PubMed  Google Scholar 

  66. Raichle ME. The brain’s default mode network. Annu Rev Neurosci. 2015;38:433–47.

    CAS  PubMed  Google Scholar 

  67. Fair DA, Cohen AL, Dosenbach NU, Church JA, Miezin FM, Barch DM, et al. The maturing architecture of the brain’s default network. Proc Natl Acad Sci USA. 2008;105:4028–32.

    CAS  PubMed  Google Scholar 

  68. Andrews-Hanna JR. The brain’s default network and its adaptive role in internal mentation. Neuroscience. 2012;18:251–70.

    Google Scholar 

  69. Whitfield-Gabrieli S, Thermenos HW, Milanovic S, Tsuang MT, Faraone SV, McCarley RW, et al. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci USA. 2009;106:1279–84.

    CAS  PubMed  Google Scholar 

  70. Krishnadas R, Ryali S, Chen T, Uddin LQ, Supekar K, Palaniyappan L, et al. Resting state functional hyperconnectivity within a triple network model in paranoid schizophrenia. Lancet. 2014;383:S65.

    Google Scholar 

  71. Abel KM, Drake R, Goldstein JM. Sex differences in schizophrenia. Int Rev Psychiatry. 2010;22:417–28.

    PubMed  Google Scholar 

  72. Haynes VS, Zhu B, Stauffer VL, Kinon BJ, Stensland MD, Xu L, et al. Long-term healthcare costs and functional outcomes associated with lack of remission in schizophrenia: a post-hoc analysis of a prospective observational study. BMC Psychiatry. 2012;12:222.

    PubMed  PubMed Central  Google Scholar 

  73. Anticevic A, Gancsos M, Murray JD, Repovs G, Driesen NR, Ennis DJ, et al. NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia. Proc Natl Acad Sci USA. 2012;109:16720–5.

    CAS  PubMed  Google Scholar 

  74. Lewis DA, Moghaddam B. Cognitive dysfunction in schizophrenia: convergence of gamma-aminobutyric acid and glutamate alterations. Arch Neurol. 2006;63:1372–6.

    PubMed  Google Scholar 

  75. Keshavan MS, Vinogradov S, Rumsey J, Sherrill J, Wagner A. Cognitive training in mental disorders: update and future directions. Am J Psychiatry. 2014;171:510–22.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Dr. Frangou received support from the National Institutes of Health (R01 MH104284-01A1) and European Unit FP7 program (IMAGEMEND 602450; IMAging GEnetics for MENtal Disorders) projects. Dr. Moser received support from the Swiss National Science Foundation (P300PB_171584).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sophia Frangou.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Doucet, G.E., Moser, D.A., Luber, M.J. et al. Baseline brain structural and functional predictors of clinical outcome in the early course of schizophrenia. Mol Psychiatry 25, 863–872 (2020). https://doi.org/10.1038/s41380-018-0269-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-018-0269-0

This article is cited by

Search

Quick links