Neuropsychological Clustering in Bipolar and Major Depressive Disorder

• Published in: Journal of the International Neuropsychological Society Vol. 23; no. 7; pp. 584 - 593
• Main Authors: Cotrena, Charles, Damiani Branco, Laura, Ponsoni, André, Milman Shansis, Flávio, Paz Fonseca, Rochele
• Format: Journal Article
• Language: English
• Published: New York, USA Cambridge University Press 01.08.2017
• Subjects: Adult; Adults; Behavior disorders; Bipolar disorder; Bipolar Disorder - complications; Bipolar Disorder - physiopathology; Cluster Analysis; Clustering; Cognition & reasoning; Cognitive ability; Cognitive Dysfunction - classification; Cognitive Dysfunction - etiology; Cognitive Dysfunction - physiopathology; Dementia; Depressive Disorder, Major - complications; Depressive Disorder, Major - physiopathology; Female; Humans; Male; Mental depression; Middle Aged; Mood; Motor task performance; Neuropsychology; Psychiatry; Psychosis; Schizophrenia; Studies; Cluster analysis; Mood disorders; Executive function; Cognition; Cognition disorders; Neuropsychology
• ISSN: 1355-6177; 1469-7661; 1469-7661
• DOI: 10.1017/S1355617717000418

Objectives: Cognitive dysfunction is a key feature of major depressive (MDD) and bipolar (BD) disorders. However, rather than a single cognitive profile corresponding to each diagnostic categories, recent studies have identified significant intra- and cross-diagnostic variability in patterns of cognitive impairment. The goal of this study was to contribute to the literature on cognitive heterogeneity in mood disorders by identifying cognitive subprofiles in a population of patients with MDD, BD type I, BD type II, and healthy adults. Methods: Participants completed a neuropsychological battery; scores were converted into Z-scores using normative data and submitted to hierarchical cluster analysis. Results: Three distinct neuropsychological clusters were identified: (1) a large cluster containing mostly control participants, as well as some patients with BD and MDD, who performed at above-average levels on all neuropsychological domains; (2) a cluster containing some patients from all diagnostic groups, as well as healthy controls, who performed worse than cluster 1 on most tasks, and showed impairments in motor inhibition and verbal fluency; (3) a cluster containing mostly patients with mood disorders with severe impairments in verbal inhibition and cognitive flexibility. Conclusions: These findings revealed multiple cognitive profiles within diagnostic categories, as well as significant cross-diagnostic overlap, highlighting the importance of developing more specific treatment approaches which consider patients’ demographic and cognitive profiles in addition to their diagnosis. (JINS, 2017, 23, 584–593)