Abstract
The ability to classify patients with bipolar disorder (BD) is restricted by their heterogeneity, which limits the understanding of their neuropathology. Therefore, we aimed to investigate clinically discernible and neurobiologically distinguishable BD subtypes. T1-weighted and resting-state functional magnetic resonance images of 112 patients with BD were obtained, and patients were segregated according to diagnostic subtype (i.e., types I and II) and clinical patterns, including the number of episodes and hospitalizations and history of suicide and psychosis. For each clinical pattern, fewer and more occurrences subgroups and types I and II were classified through nested cross-validation for robust performance, with minimum redundancy and maximum relevance, in feature selection. To assess the proportion of variance in cognitive performance explained by the neurobiological markers, multiple linear regression between verbal memory and the selected features was conducted. Satisfactory performance (mean accuracy, 73.60%) in classifying patients with a high or low number of episodes was attained through functional connectivity, mostly from default-mode and motor networks. Moreover, these neurobiological markers explained 62% of the variance in verbal memory. The number of episodes is a potentially critical aspect of the neuropathology of BD. Neurobiological markers can help identify BD neuroprogression.
Highlights
The ability to classify patients with bipolar disorder (BD) is restricted by their heterogeneity, which limits the understanding of their neuropathology
Because studies on both precise phenotypic delineation of BD and the neurobiological representation of subtypes are underway, this study aimed to investigate the differentiated subtypes through multimodal neuroimaging, including the analysis of overall brain morphology and functional connectivity, and the essential markers for BD subtypes categorized by clinical dimensions, including the number of episodes and hospitalizations and the history of suicide and psychosis
Demographic characteristics of the BD subgroups based on clinical patterns and diagnostic subtypes
Summary
The ability to classify patients with bipolar disorder (BD) is restricted by their heterogeneity, which limits the understanding of their neuropathology. Satisfactory performance (mean accuracy, 73.60%) in classifying patients with a high or low number of episodes was attained through functional connectivity, mostly from default-mode and motor networks These neurobiological markers explained 62% of the variance in verbal memory. Approaches to identify patient subtypes include the assessment of overall brain morphology[6,9], brain region activation[10], functional connectivity[11], and white-matter integrity[12] These neuroimaging approaches have been suggested as the intermediate phenotype between two psychiatric disorders or patient–control p airs[13,14,15]. Categorization of patients into predefined subtypes based on clinical features served as a potential approach to improve classification performance and better understand the neuropathology of B D20, especially the precise neurobiological basis of a BD subtype. The extent to which patients with BD can be classified on the basis of neuroimaging abnormalities remains unclear, likely due to the heterogeneity among such patients and some redundant predictors in their abnormalities
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