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Do premorbid and post-onset cognitive functioning differ between schizophrenia and bipolar disorder? A systematic review and meta-analysis

Published online by Cambridge University Press:  23 June 2014

A. Trotta ,
R. M. Murray  and
J. H. MacCabe
A. Trotta*
Affiliation:
Psychosis Studies, Institute of Psychiatry, King's College London, UK
R. M. Murray
Affiliation:
Psychosis Studies, Institute of Psychiatry, King's College London, UK
J. H. MacCabe
Affiliation:
Psychosis Studies, Institute of Psychiatry, King's College London, UK
*
*Address for correspondence: Dr A. Trotta, PO52 Psychosis Studies, Institute of Psychiatry, King's College London, De Crespigny Park, London SE5 8AF, UK. (Email: antonella.a.trotta@kcl.ac.uk)
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Abstract

Background

Schizophrenia (SZ) is characterized by a broad global cognitive impairment that precedes the onset of the disease. By contrast, some studies suggest that premorbid deficits are absent, or even reversed, in bipolar disorder (BD). However, studies have shown impairments in cognitive functioning after the illness onset in both disorders. The aim of this study was to systematically review and meta-analyze those studies that compared premorbid and/or post-onset global cognitive function between SZ and BD.

Method

We searched Medline (PubMed), EMBASE and PsycINFO for studies where information on cognitive functioning was collected in both SZ and BD within the same study or using the same methods.

Results

Compared to healthy comparison groups, SZ patients showed a significant premorbid cognitive impairment [standardized mean difference (SMD) −0.597, 95% confidence interval (CI) −0.707 to −0.487, p < 0.0001] and a large post-onset impairment (SMD −1.369, 95% CI −1.578 to −1.160, p < 0.0001). We found small significant deficits in premorbid intellectual function in the BD group when this was assessed retrospectively (−0.147, 95% CI −0.238 to −0.056, p = 0.001) but not prospectively (−0.029, 95% CI −0.199 to + 0.142, p = 0.744), and moderate cognitive impairment after onset (SMD −0.623, 95% CI −0.717 to −0.529, p < 0.0001).

Conclusions

SZ is characterized by significant deficits in premorbid intellectual function but the evidence regarding premorbid function in BD is equivocal. After illness onset, patients with both disorders seem to suffer a further decline in cognitive function but the magnitude of the impairment remains greater in SZ than in BD.

Keywords

Bipolar disordercognitive functionfirst episodeintelligencemeta-analysispre- and post-onsetschizophreniasystematic review
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 2 , January 2015 , pp. 381 - 394
Copyright
Copyright © Cambridge University Press 2014 

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References

APA (2013). Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. DSM-5. American Psychiatric Association: Washington, DC.Google Scholar
Aylward, E, Walker, E, Bettes, B (1984). Intelligence in schizophrenia: meta-analysis of the research. Schizophrenia Bulletin 10, 430–459.Google Scholar
Bergen, SE, O'Dushlaine, CT, Ripke, S, Lee, PH, Ruderfer, DM, Akterin, S, Moran, JL, Chambert, KD, Handsaker, RE, Backlund, L, Ösby, U, McCarroll, S, Landen, M, Scolnick, EM, Magnusson, PK, Lichtenstein, P, Hultman, CM, Purcell, SM, Sklar, P, Sullivan, PF (2012). Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder. Molecular Psychiatry 17, 880–886.Google Scholar
Booker, BH, Cyr, JJ (1986). Tables for clinicians to use to convert WAIS-R short forms. Journal of Clinical Psychology 42, 982–986.Google Scholar
Canavan, AGM, Dunn, G, McMillan, TM (1986). Principal components of the WAIS-R. British Journal of Clinical Psychology 25, 81–85.Google Scholar
Cohen, J (1969). Statistical Power Analysis for the Behavioral Sciences. Academic Press: New York, NY.Google Scholar
Craddock, N, Owen, MJ (2005). The beginning of the end for the Kraepelinian dichotomy. British Journal of Psychiatry 186, 364–366.CrossRefGoogle ScholarPubMed
Crow, TJ (2008). Craddock & Owen vs Kraepelin: 85 years late, mesmerised by ‘polygenes’. Schizophrenia Research 103, 156–160.CrossRefGoogle Scholar
Cyr, JJ, Booker, BH (1984). Use of appropriate formulas for selecting WAIS-R short forms. Journal of Consulting and Clinical Psychology 52, 903–905.CrossRefGoogle Scholar
Deary, IJ, Strand, P, Smith, P, Fernandes, C (2007). Intelligence and educational achievement. Intelligence 35, 13–21.Google Scholar
Demjaha, A, MacCabe, JH, Murray, RM (2012). How genes and environmental factors determine the different neurodevelopmental trajectories of schizophrenia and bipolar disorder. Schizophrenia Bulletin 38, 209–214.CrossRefGoogle ScholarPubMed
DerSimonian, R, Laird, N (1986). Meta-analysis in clinical trials. Controlled Clinical Trials 7, 177–188.Google Scholar
Egger, M, Davey Smith, G, Schneider, M, Minder, C (1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal 315, 629–634.Google Scholar
Fromer, M, Pocklington, AJ, Kavanagh, DH, Williams, HJ, Dwyer, S, Gormley, P, Georgieva, L, Rees, E, Palta, P, Ruderfer, DM, Carrera, N, Humphreys, I, Johnson, JS, Roussos, P, Barker, DD, Banks, E, Milanova, V, Grant, SG, Hannon, E, Rose, SA, Chambert, K, Mahajan, M, Scolnick, EM, Moran, JL, Kirov, G, Palotie, A, McCarroll, SA, Holmans, P, Sklar, P, Owen, MJ, Purcell, SM, O'Donovan, MC (2014). De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184.Google Scholar
Harvey, PD, Wingo, AP, Burdick, KE, Baldessarini, RJ (2010). Cognition and disability in bipolar disorder: lessons from schizophrenia research. Bipolar Disorders 12, 364–375.Google Scholar
Higgins, JPT, Thompson, SG, Deeks, JJ, Altman, DG (2003). Measuring inconsistency in meta-analyses. British Medical Journal 327, 557–560.Google Scholar
Jastak, S, Wilkinson, G (1984). Wide Range Achievement Test: Manual of Instructions. Jastak Associates: Wilmington, DE.Google Scholar
Koenen, KC, Moffitt, TE, Roberts, AL, Martin, LT, Kubzansky, L, Harrington, H, Poulton, R, Caspi, A (2009). Childhood IQ and adult mental disorders: a test of the cognitive reserve hypothesis. American Journal of Psychiatry 166, 50–57.Google Scholar
Lett, TA, Zai, CC, Tiwari, AK, Shaikh, SA, Likhodi, O, Kennedy, JL, Müller, DJ (2011). ANK3, CACNA1C and ZNF804A gene variants in bipolar disorders and psychosis subphenotype. World Journal of Biological Psychiatry 12, 392–397.Google Scholar
Lichtenstein, P, Yip, BH, Björk, C, Pawitan, Y, Cannon, TD, Sullivan, PF, Hultman, CM (2009). Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study. Lancet 373, 234–239.Google Scholar
Lodge, DJ, Grace, AA (2011). Developmental pathology, dopamine, stress and schizophrenia. International Journal of Developmental Neuroscience 29, 207–213.CrossRefGoogle ScholarPubMed
MacCabe, JH (2008). Population-based cohort studies on premorbid cognitive function in schizophrenia. Epidemiologic Reviews 30, 77–83.CrossRefGoogle ScholarPubMed
MacCabe, JH, Lambe, MP, Cnattingius, S, Sham, PC, David, AS, Reichenberg, A, Murray, RM, Hultman, CM (2010). Excellent school performance at age 16 and risk of adult bipolar disorder: national cohort study. British Journal of Psychiatry 196, 109–115.Google Scholar
MacCabe, JH, Lambe, MP, Cnattingius, S, Torrång, A, Björk, C, Sham, PC, David, AS, Murray, RM, Hultman, CM (2008). Scholastic achievement at age 16 and risk of schizophrenia and other psychoses: a national cohort study. Psychological Medicine 38, 1133–1140.Google Scholar
Martino, DJ, Strejilevich, SA, Scapola, M, Igoa, A, Marengo, E, Ais, ED, Perinot, L (2008). Heterogeneity in cognitive functioning among patients with bipolar disorder. Journal of Affective Disorders 109, 149–156.CrossRefGoogle ScholarPubMed
Murray, RM, Sham, P, van Os, J, Zanelli, J, Cannon, M, McDonald, C (2004). A developmental model for similarities and dissimilarities between schizophrenia and bipolar disorder. Schizophrenia Research 71, 405–416.Google Scholar
Nelson, HE (1982). National Adult Reading Test (NART): Test Manual. NFER-Nelson: Windsor.Google Scholar
Nelson, HE, McKenna, P (1975). The use of current reading ability in the assessment of dementia. British Journal of Social and Clinical Psychology 14, 259–267.Google Scholar
Rees, E, Walters, JT, Georgieva, L, Isles, AR, Chambert, KD, Richards, AL, Mahoney-Davies, G, Legge, SE, Moran, JL, McCarroll, SA, O'Donovan, MC, Owen, MJ, Kirov, G (2014). Analysis of copy number variations at 15 schizophrenia-associated loci. British Journal of Psychiatry 204, 108–114.Google Scholar
Schretlen, DJ, Cascella, NG, Meyer, SM, Kingery, LR, Testa, SM, Munro, CA, Pulver, AE, Rivkin, P, Rao, VA, Diaz-Asper, CM, Dickerson, FB, Yolken, RH, Pearlson, GD (2007). Neuropsychological functioning in bipolar disorder and schizophrenia. Biological Psychiatry 62, 179–186.Google Scholar
Schumacher, J, Jamra, RA, Freudenberg, J, Becker, T, Ohlraun, S, Otte, AC, Tullius, M, Kovalenko, S, Bogaert, AV, Maier, W, Rietschel, M, Propping, P, Nöthen, MM, Cichon, S (2004). Examination of G72 and D-amino-acid oxidase as genetic risk factors for schizophrenia and bipolar affective disorder. Molecular Psychiatry 9, 203–207.CrossRefGoogle ScholarPubMed
Shifman, S, Bronstein, M, Sternfeld, M, Pisanté, A, Weizman, A, Reznik, I, Spivak, B, Grisaru, N, Karp, L, Schiffer, R, Kotler, M, Strous, RD, Swartz-Vanetik, M, Knobler, HY, Shinar, E, Yakir, B, Zak, NB, Darvasi, A (2004). COMT: a common susceptibility gene in bipolar disorder and schizophrenia. American Journal of Medical Genetics. Part B, Neuropsychiatric Genetics 128, 61–64.CrossRefGoogle Scholar
Stefanopoulou, E, Manoharan, A, Landau, S, Geddes, JR, Goodwin, G, Frangou, S (2009). Cognitive functioning in patients with affective disorders and schizophrenia: a meta-analysis. International Review of Psychiatry 21, 336–356.Google Scholar
Stroup, DF, Berlin, JA, Morton, SC, Olkin, I, Williamson, GD, Rennie, D, Moher, D, Becker, BJ, Sipe, TA, Thacker, SB (2000). Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. Journal of the American Medical Association 283, 2008–2012.Google Scholar
Wechsler, D (2007). Wechsler Memory Scale – Third Edition (WMS-III). Norwegian Manual. Pearson Assessment: Stockholm.Google Scholar
WHO (1992). The ICD-10 Classification of Mental and Behavioral Disorders: Clinical Descriptions and Diagnostic Guidelines. World Health Organization: Geneva.Google Scholar
Woodberry, KA, Giuliano, AJ, Seidman, LJ (2008). Premorbid IQ in schizophrenia: a meta-analytic review. American Journal of Psychiatry 165, 579–587.Google Scholar
Zipursky, RB, Reilly, TJ, Murray, RM (2012). The myth of schizophrenia as a progressive brain disease. Schizophrenia Bulletin 39, 1363–1372.Google Scholar
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