Increasing variance of rich-club nodes distribution in early onset depression according to dynamic network

Early onset depression (EOD) and late onset depression (LOD) are thought to have different pathogeneses, but lack of pathological evidence. In the current study we describe the dynamic rich-club properties of patients with EOD and LOD to address this question indirectly. We recruited 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. Memory, executive function and processing speed were measured, and resting-stage functional MRI was performed with all participants. We constructed a dynamic functional connectivity network and carried out rich-club and modularity analyses. Normalized mutual information (NMI) was applied to describe the variance in rich-club nodes distribution and partitioning. The NMI coefficient of rich club nodes distribution among the three groups was the lowest in the EOD patients (F = 4.298; P = 0.0151, FDR = 0.0231), which was positively correlated with rich-club connectivity (R = 0.886, P < 0.001) and negatively correlated with memory (R = -0.347, P = 0.038) in the EOD group. In the LOD patients, non-rich-club connectivity was positively correlated with memory (R = 0.353, P = 0.030 and R = 0.420, P = 0.009). Furthermore, local connectivity was positively correlated with processing speed in the LOD patients (R = 0.374, P = 0.021). The modular partition was different between the EOD patients and the HCs (P = 0.0013 < 0.05/3). The temporal instability of rich-club nodes was found in the EOD patients, but not the LOD patients, supporting the hypothesis that EOD and LOD result from different pathogenesis, and showing that the instability of the rich-club nodes across time might disrupt rich-club connectivity.