Novel Antidepressant-Like Properties of the Iron Chelator Deferiprone in a Mouse Model of Depression

Abstract

Depressed individuals who carry the short allele for the serotonin-transporter-linked promotor region of the gene are more vulnerable to stress and have reduced response to first-line antidepressants such as selective serotonin reuptake inhibitors. Since depression severity has been reported to correlate with brain iron levels, the present study aimed to characterise the potential antidepressant properties of the iron chelator deferiprone. Using the serotonin transporter knock-out (5-HTT KO) mouse model, we assessed the behavioural effects of acute deferiprone on the Porsolt swim test (PST) and novelty-suppressed feeding test (NSFT). Brain and blood iron levels were also measured following acute deferiprone. To determine the relevant brain regions activated by deferiprone, we then measured c-Fos expression and applied network-based analyses. We found that deferiprone reduced immobility time in the PST in 5-HTT KO mice and reduced latency to feed in the NSFT in both genotypes, suggesting potential antidepressant-like effects. There was no effect on brain or blood iron levels following deferiprone treatment, potentially indicating an acute iron-independent mechanism. Deferiprone reversed the increase in c-Fos expression induced by swim stress in 5-HTT KO mice in the lateral amygdala. Functional network analyses suggest that hub regions of activity in mice treated with deferiprone include the caudate putamen and prefrontal cortex. The PST-induced increase in network modularity in wild-type mice was not observed in 5-HTT KO mice. Altogether, our data show that the antidepressant-like effects of deferiprone could be acting via an iron-independent mechanism and that these therapeutic effects are underpinned by changes in neuronal activity in the lateral amygdala.

Keywords: Antidepressant; Functional network; Iron; Stress.

Fig. 1

Effect of acute deferiprone on depression-related behaviours and locomotor activity. Effect of deferiprone on the Porsolt swim test at 1 hour (a) and 24 hours (b) post-injection (2-way ANOVA; Bonferroni post hoc). c Effect of deferiprone on the novelty-suppressed feeding test (Cox-regression test). d Locomotor activity in the 60 minutes following deferiprone injection (3-way repeated measure ANOVA; Bonferroni post hoc). a, b Data are expressed as median with interquartile range; whiskers represent min to max values. d Data are expressed as mean ± SEM. a n = 15–21; b, d n = 10–13; c n = 13–14. ***p < 0.001 KO vehicle vs. KO deferiprone, $p < 0.05 WT vs. KO, #p < 0.05; ##p < 0.01; ###p < 0.001 vehicle vs. deferiprone. WT = wild-type; KO = knock-out

Fig. 2

Levels of iron in brain regions and blood following acute deferiprone treatment. Effect of acute deferiprone treatment on the a prefrontal cortex, b striatum, c brainstem and d blood. Two-way ANOVA. Data are expressed as median with interquartile range; whiskers represent min to max values. n = 9–14. $p < 0.05 WT vs. KO overall effect. WT = wild-type; KO = knock-out

Fig. 3

Acute deferiprone and swim stress exposure on c-Fos expression in various brain regions. Effect of deferiprone and swim stress exposure on c-Fos expression in subnuclei of the a lateral amygdala, b dorsal raphe and c lateral septum. d Representative photomicrographs of deferiprone treatment on behaviourally naive WT and 5-HTT KO mice in the basolateral, basomedial and lateral amygdala. Three-way ANOVA; Bonferroni post hoc. Data are expressed as median with interquartile range; whiskers represent min to max values. Black bar represents 100 μm. a n = 6–9, b n = 5–9, c n = 5–8. ^^p < 0.01 KO naive vs. KO PST, + p < 0.05; +  + p < 0.01 KO vehicle vs. KO deferiprone, † WT deferiprone vs. KO deferiprone, ##p < 0.01 vehicle vs. deferiprone. WT = wild-type; KO = knock-out; BNST = bed nucleus of the stria terminalis; PST = Porsolt swim test; LaDL = lateral amygdala−dorsolateral; LaVL = lateral amygdala−ventrolateral; LaVM = lateral amygdala−ventromedial; BLP = basolateral amygdala−posterior; BLA = basolateral amygdala−anterior; BMP = basomedial amygdala−posterior

Fig. 4

Functional connectivity network and hub regions following deferiprone treatment in WT and 5-HTT KO mice. a Connectivity matrix for inter-regional correlation following deferiprone treatment in both WT and 5-HTT KO mice was created using Pearson’s correlation. b The functional connectivity network in each group was created using the strongest (Pearson’s r ≥ 0.83) correlation between regions. The size of nodes is proportional to the number of significant inter-regional correlation while the lines depict the edge between two nodes. c Hubs for the functional connectome in WT and KO mice treated with deferiprone. Hubs are central regions of information integration, and were identified in bold by determining if they were in the 80th percentile for number of nodes in the low (grey) r ≥ 0.78, primary (orange) r ≥ 0.83 and high (red) r ≥ 0.87 correlation network as well as the 80th percentile for betweenness centrality. WT = wild-type; KO = knock-out; BNST = bed nucleus of the stria terminalis

Fig. 5

Functional connectivity network and hub regions following deferiprone treatment and swim stress in WT and 5-HTT KO mice. a Connectivity matrix for inter-regional correlation following deferiprone treatment and swim stress in both WT and 5-HTT KO mice was created using Pearson’s correlation. b The functional connectivity network in each group was created using the strongest (Pearson’s r ≥ 0.83) correlation between regions. The size of nodes is proportional to the number of significant inter-regional correlation while the lines depict the edge between two nodes. c Hubs for the functional connectome in WT and KO mice exposed to swim stress and deferiprone treatment. Hubs are central regions of information integration, and were identified in bold by determining if they were in the 80th percentile for number of nodes in the low (grey) r ≥ 0.78, primary (orange) r ≥ 0.83 and high (red) r ≥ 0.87 correlation network as well as the 80th percentile for betweenness centrality. WT = wild-type; KO = knock-out; BNST = bed nucleus of the stria terminalis; PST = Porsolt swim test

Fig. 6

Functional negative correlation network following deferiprone treatment and swim-stress exposure in WT controls and 5-HTT KO mice. The functional negative correlation network was characterised in behaviourally naive (a) and following swim-stress exposure (b). The negative correlation network for each group was created using the strongest negative (Pearson’s r ≤  −0.87) between regions. The size of nodes is proportional to the number of significant inter-regional negative correlation while the lines depict the edge between two nodes

Fig. 7

Community detection and hierarchical clustering on behaviourally naive and swim stress–exposed WT mice. a Graph-theory based community detection analysis of the functional network following deferiprone treatment and swim-stress exposure. An arbitrary Pearson’s r > 0.6 was used for visualisation purposes. Different colours around each node represent respective modules of activity. Regions in bold include the lateral, basolateral and basomedial amygdala. b Hierarchical clustering of the Euclidean distance following deferiprone treatment and swim stress exposure. Dendrogram was cut at 70% height for clustering visualisation. c Number of modules of each treatment group at various tree cuts of the hierarchical clustering dendrogram. WT = wild-type

Fig. 8

Community detection and hierarchical clustering on behaviourally naive and stress–exposed 5-HTT KO mice. a Graph-theory based community detection analysis of the functional network following deferiprone treatment and swim-stress exposure. An arbitrary Pearson’s r > 0.6 was used for visualisation purposes. Different colours around each node represent respective modules of activity. Regions in bold include the lateral, basolateral and basomedial amygdala. b Hierarchical clustering of the Euclidean distance following deferiprone treatment and swim-stress exposure. Dendrogram was cut at 70% height for clustering visualisation. c Number of modules of each treatment group at various tree cuts of the hierarchical clustering dendrogram. KO = knock-out