Episode-specific and common intrinsic functional network patterns in bipolar

Understanding the alterations in brain function across different episodes of bipolar disorder (BD), including manic (BipM), depressive (BipD), and remission states (rBD), poses a significant challenge. In our cross-sectional study, we collected resting-state functional magnetic resonance imaging data from 117 BD patients (BipM: 38, BipD: 42, rBD: 37) and 35 healthy controls. Our aim was to delineate functional connections associated with episode dynamics, delineate common and specific patterns, validate them as biomarkers, and elucidate their biological underpinnings. Initially, we identified a common altered pattern within the subregions of the ventral-attention network, alongside specific patterns observed in the default mode network for BipM, the prefrontal network for BipD, and the limbic network for rBD. Using large-sample data from the Human Connectome Project, we further identified that these connectivity patterns exhibit relatively high reliability and heritability. Also, these distinct patterns accurately characterized the diverse episodes of BD and effectively predicted the corresponding clinical symptoms linked with each episode type. Importantly, using out of sample data to decode possible neurobiological mechanisms underlying these patterns, we found that regions of particular interest were enriched in multiple receptors, including MOR, NMDA, and H3 for specific alterations, and A4B2, 5HTT, and 5HT1a for common alterations. Moreover, both episode-specific and common patterns demonstrated a high enrichment for cell types such as L5ET, Micro/PVM,oligodendrites and Chandelier. Our study offers novel insights concerning episode dynamics in BD, paving the way for personalized medicine approaches tailored to address the various episodes.