Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-19T11:50:11.177Z Has data issue: false hasContentIssue false
  • English
  • Français

White-matter markers for psychosis in a prospective ultra-high-risk cohort

Published online by Cambridge University Press:  09 November 2009

O. J. N. Bloemen ,
M. B. de Koning ,
N. Schmitz ,
D. H. Nieman ,
H. E. Becker ,
L. de Haan ,
P. Dingemans ,
D. H. Linszen  and
T. A. M. J. van Amelsvoort
O. J. N. Bloemen*
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
M. B. de Koning
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
N. Schmitz
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
D. H. Nieman
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
H. E. Becker
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
L. de Haan
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
P. Dingemans
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
D. H. Linszen
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
T. A. M. J. van Amelsvoort
Affiliation:
Academic Medical Centre, Department of Psychiatry, Amsterdam, The Netherlands
*
*Address for correspondence: Dr O. J. N. Bloemen, Department of Psychiatry, Academic Medical Centre, Amsterdam, The Netherlands (Email: o.j.n.bloemen@amc.nl)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Subjects at ‘ultra high risk’ (UHR) for developing psychosis have differences in white matter (WM) compared with healthy controls. WM integrity has not yet been investigated in UHR subjects in relation to the development of subsequent psychosis. Hence, we investigated a prospective cohort of UHR subjects comparing whole brain fractional anisotropy (FA) of those later developing psychosis (UHR-P) to those who did not (UHR-NP).

Method

We recruited 37 subjects fulfilling UHR criteria and 10 healthy controls. Baseline 3 Tesla magnetic resonance imaging (MRI) scans and Positive and Negative Syndrome Scale (PANSS) ratings were obtained. UHR subjects were assessed at 9, 18 and 24 months for development of frank psychosis. We compared baseline FA of UHR-P to controls and UHR-NP subjects. Furthermore, we related clinical data to MRI outcome in the patient population.

Results

Of the 37 UHR subjects, 10 had transition to psychosis. UHR-P subjects showed significantly lower FA values than control subjects in medial frontal lobes bilaterally. UHR-P subjects had lower FA values than UHR-NP subjects, lateral to the right putamen and in the left superior temporal lobe. UHR-P subjects showed higher FA values, compared with UHR-NP, in the left medial temporal lobe. In UHR-P, positive PANSS negatively correlated to FA in the left middle temporal lobe. In the total UHR group positive PANSS negatively correlated to FA in the right superior temporal lobe.

Conclusions

UHR subjects who later develop psychosis have differences in WM integrity, compared with UHR subjects who do not develop psychosis and to healthy controls, in brain areas associated with schizophrenia.

Keywords

DT-MRIFAschizophreniatransitionUHRwhite matter
Type
Original Articles
Information
Psychological Medicine , Volume 40 , Issue 8 , August 2010 , pp. 1297 - 1304
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antonova, E, Sharma, T, Morris, R, Kumari, V (2004). The relationship between brain structure and neurocognition in schizophrenia: a selective review. Schizophrenia Research 70, 117–145.CrossRefGoogle ScholarPubMed
Ashburner, J, Friston, KJ (2000). Voxel-based morphometry – the methods. Neuroimage 11, 805–821.CrossRefGoogle ScholarPubMed
Ashburner, J, Friston, KJ (2001). Why voxel-based morphometry should be used. Neuroimage 14, 1238–1243.CrossRefGoogle ScholarPubMed
Basser, PJ (1995). Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR in Biomedicine 8, 333–344.CrossRefGoogle ScholarPubMed
Basser, PJ, Mattiello, J, LeBihan, D (1994). MR diffusion tensor spectroscopy and imaging. Biophysical Journal 66, 259–267.CrossRefGoogle ScholarPubMed
Beaulieu, C (2002). The basis of anisotropic water diffusion in the nervous system – a technical review. NMR in Biomedicine 15, 435–455.CrossRefGoogle ScholarPubMed
Buchsbaum, MS, Tang, CY, Peled, S, Gudbjartsson, H, Lu, D, Hazlett, EA, Downhill, J, Haznedar, M, Fallon, JH, Atlas, SW (1998). MRI white matter diffusion anisotropy and PET metabolic rate in schizophrenia. Neuroreport 9, 425–430.CrossRefGoogle ScholarPubMed
de Koning, MB, Bloemen, OJ, van Amelsvoort, TA, Becker, HE, Nieman, DH, van der Gaag, M, Linszen, DH (2009). Early intervention in patients at ultra high risk of psychosis: benefits and risks. Acta Psychiatrica Scandinavica 119, 426–442.CrossRefGoogle ScholarPubMed
Ellison-Wright, I, Bullmore, E (2009). Meta-analysis of diffusion tensor imaging studies in schizophrenia. Schizophrenia Research 108, 3–10.CrossRefGoogle ScholarPubMed
Friedman, JI, Tang, C, Carpenter, D, Buchsbaum, M, Schmeidler, J, Flanagan, L, Golembo, S, Kanellopoulou, I, Ng, J, Hof, PR, Harvey, PD, Tsopelas, ND, Stewart, D, Davis, KL (2008). Diffusion tensor imaging findings in first-episode and chronic schizophrenia patients. American Journal of Psychiatry 165, 1024–1032.CrossRefGoogle ScholarPubMed
Hoptman, MJ, Nierenberg, J, Bertisch, HC, Catalano, D, Ardekani, BA, Branch, CA, Delisi, LE (2008). A DTI study of white matter microstructure in individuals at high genetic risk for schizophrenia. Schizophrenia Research 106, 115–124.CrossRefGoogle ScholarPubMed
Howes, OD, Montgomery, AJ, Asselin, MC, Murray, RM, Valli, I, Tabraham, P, Bramon-Bosch, E, Valmaggia, L, Johns, L, Broome, M, McGuire, PK, Grasby, PM (2009). Elevated striatal dopamine function linked to prodromal signs of schizophrenia. Archives of General Psychiatry 66, 13–20.CrossRefGoogle ScholarPubMed
Jones, DK, Symms, MR, Cercignani, M, Howard, RJ (2005). The effect of filter size on VBM analyses of DT-MRI data. Neuroimage 26, 546–554.CrossRefGoogle ScholarPubMed
Kay, SR, Fiszbein, A, Opler, LA (1987). The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin 13, 261–276.CrossRefGoogle ScholarPubMed
Kircher, TT, Liddle, PF, Brammer, MJ, Williams, SC, Murray, RM, McGuire, PK (2001). Neural correlates of formal thought disorder in schizophrenia: preliminary findings from a functional magnetic resonance imaging study. Archives of General Psychiatry 58, 769–774.CrossRefGoogle ScholarPubMed
Konrad, A, Winterer, G (2008). Disturbed structural connectivity in schizophrenia primary factor in pathology or epiphenomenon? Schizophrenia Bulletin 34, 72–92.CrossRefGoogle ScholarPubMed
Lappin, JM, Dazzan, P, Morgan, K, Morgan, C, Chitnis, X, Suckling, J, Fearon, P, Jones, PB, Leff, J, Murray, RM, McGuire, PK (2007). Duration of prodromal phase and severity of volumetric abnormalities in first-episode psychosis. British Journal of Psychiatry Supplement 51, s123–s127.CrossRefGoogle ScholarPubMed
Miller, TJ, McGlashan, TH, Rosen, JL, Cadenhead, K, Cannon, T, Ventura, J, McFarlane, W, Perkins, DO, Pearlson, GD, Woods, SW (2003). Prodromal assessment with the structured interview for prodromal syndromes and the scale of prodromal symptoms: predictive validity, interrater reliability, and training to reliability. Schizophrenia Bulletin 29, 703–715.CrossRefGoogle ScholarPubMed
Mori, S, Wakana, S, Nagae-Poetscher, L, van Zijl, P (2005). MRI Atlas of Human White Matter. Elsevier: Amsterdam.Google Scholar
Muñoz Maniega, S, Lymer, GK, Bastin, ME, Marjoram, D, Job, DE, Moorhead, TW, Owens, DG, Johnstone, EC, McIntosh, AM, Lawrie, SM (2008). A diffusion tensor MRI study of white matter integrity in subjects at high genetic risk of schizophrenia. Schizophrenia Research 106, 132–139.CrossRefGoogle ScholarPubMed
Olsen, KA, Rosenbaum, B (2006). Prospective investigations of the prodromal state of schizophrenia: review of studies. Acta Psychiatrica Scandinavica 113, 247–272.CrossRefGoogle ScholarPubMed
Peters, BD, de Haan, L, Dekker, N, Blaas, J, Becker, HE, Dingemans, PM, Akkerman, EM, Majoie, CB, van Amelsvoort, T, den Heeten, GJ, Linszen, DH (2008). White matter fibertracking in first-episode schizophrenia, schizoaffective patients and subjects at ultra-high risk of psychosis. Neuropsychobiology 58, 19–28.CrossRefGoogle ScholarPubMed
Peters, BD, Schmitz, N, Dingemans, PM, van Amelsvoort, TA, Linszen, DH, de Haan, L, Majoie, CB, den Heeten, GJ (2009). Preliminary evidence for reduced frontal white matter integrity in subjects at ultra-high-risk for psychosis. Schizophrenia Research 111, 192–193. Published online: 15 April 2009. doi: 10.1016/j.schres.2009.03.018.CrossRefGoogle ScholarPubMed
Pierpaoli, C, Basser, PJ (1996). Toward a quantitative assessment of diffusion anisotropy. Magnetic Resonance in Medicine 36, 893–906.CrossRefGoogle Scholar
Schmand, B, Bakker, D, Saan, R, Louman, J (1991). [The Dutch Reading Test for Adults: a measure of premorbid intelligence level]. Tijdschrift voor Gerontologie en Geriatrie 22, 15–19.Google ScholarPubMed
Shenton, ME, Dickey, CC, Frumin, M, McCarley, RW (2001). A review of MRI findings in schizophrenia. Schizophrenia Research 49, 1–52.CrossRefGoogle ScholarPubMed
Spitzer, RL, Williams, JB, Gibbon, M, First, MB (1992). The Structured Clinical Interview for DSM-III-R (SCID). I: History, rationale, and description. Archives of General Psychiatry 49, 624–629.CrossRefGoogle ScholarPubMed
Talairach, J, Tournoux, P (1988). Co-planar Stereotaxic Atlas of the Human Brain. Thieme: New York.Google Scholar
Tamagaki, C, Sedvall, GC, Jonsson, EG, Okugawa, G, Hall, H, Pauli, S, Agartz, I (2005). Altered white matter/gray matter proportions in the striatum of patients with schizophrenia: a volumetric MRI study. American Journal of Psychiatry 162, 2315–2321.CrossRefGoogle ScholarPubMed
Walterfang, M, McGuire, PK, Yung, AR, Phillips, LJ, Velakoulis, D, Wood, SJ, Suckling, J, Bullmore, ET, Brewer, W, Soulsby, B, Desmond, P, McGorry, PD, Pantelis, C (2008 a). White matter volume changes in people who develop psychosis. British Journal of Psychiatry 193, 210–215.CrossRefGoogle ScholarPubMed
Walterfang, M, Yung, A, Wood, AG, Reutens, DC, Phillips, L, Wood, SJ, Chen, J, Velakoulis, D, McGorry, PD, Pantelis, C (2008 b). Corpus callosum shape alterations in individuals prior to the onset of psychosis. Schizophrenia Research 103, 1–10.CrossRefGoogle Scholar
Whalley, HC, Gountouna, VE, Hall, J, McIntosh, A, Whyte, MC, Simonotto, E, Job, DE, Owens, DG, Johnstone, EC, Lawrie, SM (2007). Correlations between fMRI activation and individual psychotic symptoms in un-medicated subjects at high genetic risk of schizophrenia. BMC Psychiatry 7, 61.CrossRefGoogle ScholarPubMed
WHO (1993). Composite International Diagnostic Interview – Version 1.1. World Health Organization: Geneva.Google Scholar
Witthaus, H, Brune, M, Kaufmann, C, Bohner, G, Ozgurdal, S, Gudlowski, Y, Heinz, A, Klingebiel, R, Juckel, G (2008). White matter abnormalities in subjects at ultra high-risk for schizophrenia and first-episode schizophrenic patients. Schizophrenia Research 102, 141–149.CrossRefGoogle ScholarPubMed
Woods, SW (2003). Chlorpromazine equivalent doses for the newer atypical antipsychotics. Journal of Clinical Psychiatry 64, 663–667.CrossRefGoogle ScholarPubMed
Yung, AR, Phillips, LJ, Yuen, HP, Francey, SM, McFarlane, CA, Hallgren, M, McGorry, PD (2003). Psychosis prediction: 12-month follow up of a high-risk (‘prodromal’) group. Schizophrenia Research 60, 21–32.CrossRefGoogle ScholarPubMed