James A Karantonis1, Susan L Rossell2, Sean P Carruthers1, Philip Sumner3, Matthew Hughes3, Melissa J Green4, Christos Pantelis5, Katherine E Burdick6, Vanessa Cropley1, Tamsyn E Van Rheenen7. 1. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia. 2. Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia; St Vincent's Mental Health, St Vincent's Hospital, VIC, Australia. 3. Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia. 4. School of Psychiatry, University of New South Wales (UNSW), Sydney, NSW, Australia; Neuroscience Research Australia, Randwick, NSW, Australia. 5. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Department of Electrical and Electronic Engineering, University of Melbourne, VIC, Australia; Centre for Neuropsychiatric Schizophrenia Research (CNSR) and Centre for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS), Mental Health Centre Glostrup, Glostrup, Denmark. 6. Harvard Medical School, Department of Psychiatry, Boston, MA, United States; Brigham and Women's Hospital, Boston, MA, United States. 7. Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Australia. Electronic address: tamsyn.van@unimelb.edu.au.
Abstract
BACKGROUND: Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. METHOD: Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. RESULTS: A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. LIMITATIONS: For clustering analysis, sample size was relatively small. CONCLUSIONS: The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
BACKGROUND: Cognitive heterogeneity in schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) has been explored using clustering analyses. However, the resulting subgroups have not been cognitively validated beyond measures used as clustering variables themselves. We compared the emergent cross-diagnostic subgroups of SSD and BD patients on measures used to classify them, and also across a range of alternative cognitive measures assessing some of the same constructs. METHOD: Domain scores from the Matrics Consensus Cognitive Battery were used in a cross-diagnostic clustering analysis of 86 patients with SSD (n = 45) and BD (n = 41). The emergent subgroups were then compared to each other and healthy controls (n = 76) on these and alternative measures of these domains, as well as on premorbid IQ, global cognition and a proxy of cognitive decline. RESULTS: A three-cluster solution was most appropriate, with subgroups labelled as Globally Impaired, Selectively Impaired, and Superior/Near-Normal relative to controls. With the exception of processing speed performance, the subgroups were generally differentiated on the cognitive domain scores used as clustering variables. Differences in cognitive performance among these subgroups were not always statistically significant when compared on the alternative cognitive measures. There was evidence of global cognitive impairment and putative cognitive decline in the two cognitively impaired subgroups. LIMITATIONS: For clustering analysis, sample size was relatively small. CONCLUSIONS: The overall pattern of findings tentatively suggest that emergent cross-diagnostic cognitive subgroups are not artefacts of the measures used to define them, but may represent the outcome of different cognitive trajectories.
Authors: Elysha Ringin; David W Dunstan; Roger S McIntyre; Michael Berk; Neville Owen; Susan L Rossell; Tamsyn E Van Rheenen Journal: Neuropsychopharmacology Date: 2022-10-15 Impact factor: 8.294
Authors: Gaelle E Doucet; Dongdong Lin; Yuhui Du; Zening Fu; David C Glahn; Vincent D Calhoun; Jessica Turner; Sophia Frangou Journal: NPJ Schizophr Date: 2020-12-04
Authors: Nikolaos Koutsouleris; Lana Kambeitz-Ilankovic; Julian Wenzel; Shalaila S Haas; Dominic B Dwyer; Anne Ruef; Oemer Faruk Oeztuerk; Linda A Antonucci; Sebastian von Saldern; Carolina Bonivento; Marco Garzitto; Adele Ferro; Marco Paolini; Janusch Blautzik; Stefan Borgwardt; Paolo Brambilla; Eva Meisenzahl; Raimo K R Salokangas; Rachel Upthegrove; Stephen J Wood; Joseph Kambeitz Journal: Neuropsychopharmacology Date: 2021-03-15 Impact factor: 7.853
Authors: James A Karantonis; Sean P Carruthers; Susan L Rossell; Christos Pantelis; Matthew Hughes; Cassandra Wannan; Vanessa Cropley; Tamsyn E Van Rheenen Journal: Schizophr Bull Date: 2021-10-21 Impact factor: 7.348