Distinct static functional patterns and dynamic patterns between depressed bipolar disorder and major depressive disorder: integrating neuroimaging, cognitive, and transcriptomic evidence

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Bipolar disorder (BD) and major depressive disorder (MDD) pose diagnostic challenges due to overlapping symptoms, leading to misdiagnosis and suboptimal treatment. While neuroimaging studies have explored brain alterations in these disorders, a comprehensive understanding integrating static and dynamic functional connectomes with cognitive and transcriptomic evidence remains incompletely characterized. This study addresses this gap by providing a unique, multi-modal investigation to identify novel neurobiological markers and underlying genetic mechanisms that can differentiate these disorders. We enrolled 315 participants, including 94 with depressed BD, 94 with MDD, and 127 healthy controls, all of whom were treatment-naïve. Static functional connectivity was assessed using the Dosenbach 160-node functional brain atlas with the DPABI toolbox. Dynamic resting-state functional connectivity was analyzed with a sliding-window approach using the DynamicBC toolbox. Cognitive assessments were performed, and transcriptomic analyses using the Allen Human Brain Atlas were integrated to explore possible genetic mechanisms. Static functional connectomics revealed distinct patterns in depressed BD, characterized by heightened intra-network connectivity in the default mode network (DMN), frontoparietal network (FPN), sensorimotor network (SMN), and ventral attention network (VAN), while MDD exhibited reduced connectivity within these networks. Dynamic functional connectivity analyses showed no significant differences between BD and MDD. Transcriptomic analysis identified genes associated with altered connectivity patterns, including those involved in synaptic signaling and MAPK cascade regulation. Validation analyses supported the robustness of findings. Our study offers a comprehensive exploration of intrinsic functional architecture disparities in resting-state activity between depressed BD and MDD, delving into both static and dynamic functional connectivity. Findings highlight reduced intra/inter-network connectivity in the DMN, FPN, VAN, and SMN in MDD, contrasting with heightened connectivity in depressed BD within these networks. This striking directional contrast suggests distinct underlying pathophysiological mechanisms. Furthermore, by integrating neuroimaging data with transcription analysis to unveil potential genetic factors influencing functional differences, our study contributes a valuable piece to the evolving puzzle of mood disorders, potentially paving new avenues for more precise diagnosis and targeted treatment strategies. Not applicable.