Premorbid adjustment trajectories in schizophrenia and bipolar disorder: A transdiagnostic cluster analysis

Abstract

Despite the overlap between schizophrenia and bipolar disorder, neurodevelopmental abnormalities are thought to be associated primarily with schizophrenia. Transdiagnostic and empirical identification of subgroups based on premorbid adjustment (PMA) may enhance understanding of illness trajectories. 160 patients with bipolar I or II disorder (BD; n = 104) or schizophrenia or schizoaffective disorder (SZ; n = 56) were assessed on PMA course from childhood to late adolescence and current symptoms and functioning. A hierarchical cluster analysis was performed using social and academic PMA scores, resulting in three optimal clusters. Cluster 1 (n = 28 SZ, 65 BD) had normal social and academic PMA, the most education, and mildest current symptoms. Cluster 2 (n = 15 SZ, 24 BD) had normal social PMA but an impaireddeclining academic course and had a greater proportion of males than Cluster 1. Cluster 3 (n = 13 SZ, 15 BD) had an impaired-stable social PMA and an impaired-declining academic course and the most severe current negative symptoms and childhood trauma. The proportions of SZ and BD diagnoses, current neurocognition, and functioning did not differ between clusters. These findings suggest shared neurodevelopmental abnormalities between SZ and BD, with subgroups exhibiting distinct PMA trajectories that cut across disorders.

Current understandings of the trajectory and emerging correlates of cognitive impairment in bipolar disorder: An overview of evidence

“…Importantly, there may be substantial heterogeneity of premorbid intellectual functioning in BD, as has been demonstrated in post‐onset patients where some score lower on proxy measures of premorbid cognitive dysfunction and others do not . A recent cross‐diagnostic clustering study also indicated the presence of at least one subgroup comprising ~53% patients with BD and ~47% with SZ that demonstrated poor premorbid academic adjustment relative to controls . Heterogeneity in premorbid factors may have complex implications for BD risk.…”

“…5,63,64 A recent cross-diagnostic clustering study also indicated the presence of at least one subgroup comprising ~53% patients with BD and ~47% | 17 VAN RHEENEN Et Al. with SZ that demonstrated poor premorbid academic adjustment relative to controls. 65 Heterogeneity in premorbid factors may have complex implications for BD risk. For example, Parellada et al 16 In so much as the evidence for cognitive impairment as progressive or stable is mixed, it is strikingly clear that much of the findings that speak to the evolution of cognitive impairment in BD is derived from cross-sectional studies that to date, have only considered BD as a single entity and have thus analysed cognitive performance at the group level.…”

Plasma Metabolite Profiles in First Episode Psychosis: Exploring Symptoms Heterogeneity/Severity in Schizophrenia and Bipolar Disorder Cohorts

“…Although the symptoms are more evident in SCZ than in BD, studies suggest that these effects lack diagnostic specificity (8,39,(43)(44)(45). Recently, Chan et al (46) performed a cluster analysis based on premorbid adjustment trajectories. All clusters had SCZ and BD, corroborating that clinical differentiation is not specific.…”

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

“…Transdiagnostic clustering supports the existence of diagnostically mixed subtypes across two [4, 29–31] or more disorders [32–35]. However, previous transdiagnostic clustering studies were limited by small samples and analyzed few disorders or variables [36, 37].…”

“…The wealth of available data and advances in machine learning intensified efforts to redefine disorder categories using data-driven methods. Previous studies stratified psychiatric disorders mostly by clustering single domains (e.g., psychometry [4][5][6][7][8], neuroimaging [9][10][11][12][13][14], biochemical markers [15], or genetics [16,17]) or disorders (e.g., major depressive disorder (MDD) [5,9,16,[18][19][20] or schizophrenia (SCZ) [21][22][23][24][25][26]). However, these analyses could not unravel shared neurobiological mechanisms, overlapping genetic profiles, and a transdiagnostic symptom continuum [27,28].…”