From Cell to Circuit: Altered Functional Network Topology in iPSC-derived Neuronal Circuits in Major Depressive Disorder.

The functional organization of brain networks relies on a delicate balance between segregation and integration, which supports both localized neural processing and global information exchange. While numerous whole-brain imaging studies have linked disruptions in this balanced topology to Major Depressive Disorder (MDD), it remains unclear whether such macroscale alterations are reflected in neuronal circuit dynamics at the cellular level. In this study, we investigated whether neuronal networks derived from human induced pluripotent stem cells (hiPSCs) of nine MDD patients display a distinct functional topology compared to nine matched controls. We obtained skin biopsies from all participants, cultivated fibroblasts, and reprogrammed these into hiPSCs. We then differentiated hiPSCs into neural progenitor cells (NPCs), which we later developed into neurons. We recorded spontaneous activity in the derived neuronal networks using calcium imaging, and applied graph theory analysis to quantify differences in functional topology between groups. We observed a significant decrease in the clustering coefficient and average node degree in MDD-derived neural networks. Furthermore, global efficiency showed a downward trend across varying thresholds and network sizes in patient-derived lines. Together, these findings demonstrate diminished segregation and reduced overall nodal connectivity in MDD-derived neural networks. This suggests that a predisposition for less efficient functional topology exists in depression at the microscale, highlighting the utility of hiPSC technology in modeling cellular disease mechanisms and exploring potential cellular correlates of network-level phenomena reported in depression.