Mouse repeated electroconvulsive seizure (ECS) does not reverse social stress effects but does induce behavioral and hippocampal changes relevant to electroconvulsive therapy (ECT) side-effects in the treatment of depression

Electroconvulsive therapy (ECT) is an effective treatment for depression, but can have negative side effects including amnesia. The mechanisms of action underlying both the antidepressant and side effects of ECT are not well understood. An equivalent manipulation that is conducted in experimental animals is electroconvulsive seizure (ECS). Rodent studies have provided valuable insights into potential mechanisms underlying the antidepressant and side effects of ECT. However, relatively few studies have investigated the effects of ECS in animal models with a depression-relevant manipulation such as chronic stress. In the present study, mice were first exposed to chronic social stress (CSS) or a control procedure for 15 days followed by ECS or a sham procedure for 10 days. Behavioral effects were investigated using an auditory fear conditioning (learning) and expression (memory) test and a treadmill-running fatigue test. Thereafter, immunohistochemistry was conducted on brain material using the microglial marker Iba-1 and the cholinergic fibre marker ChAT. CSS did not increase fear learning and memory in the present experimental design; in both the control and CSS mice ECS reduced fear learning and fear memory expression. CSS induced the expected fatigue-like effect in the treadmill-running test; ECS induced increased fatigue in CSS and control mice. In CSS and control mice ECS induced inflammation in hippocampus in terms of increased expression of Iba-1 in radiatum of CA1 and CA3. CSS and ECS both reduced acetylcholine function in hippocampus as indicated by decreased expression of ChAT in several hippocampal sub-regions. Therefore, CSS increased fatigue and reduced hippocampal ChAT activity and, rather than reversing these effects, a repeated ECS regimen resulted in impaired fear learning-memory, increased fatigue, increased hippocampal Iba-1 expression, and decreased hippocampal ChAT expression. As such, the current model does not provide insights into the mechanism of ECT antidepressant function but does provide evidence for pathophysiological mechanisms that might contribute to important ECT side-effects.</p

Assignment of Students from Mexico

Major depressive disorder is a heterogeneous disorder, mostly diagnosed on the basis of symptomatic criteria alone. It would be of great help when specific biomarkers for various subtypes and symptom clusters of depression become available to assist in diagnosis and subtyping of depression, and to enable monitoring and prognosis of treatment response. However, currently known biomarkers do not reach sufficient sensitivity and specificity, and often the relation to underlying pathophysiology is unclear. In this review, we evaluate various biomarker approaches in terms of scientific merit and clinical applicability. Finally, we discuss how combined biomarker approaches in both preclinical and clinical studies can help to make the connection between the clinical manifestations of depression and the underlying pathophysiology

Hot plate test: latency to first display a pain-related behavior.

<p>There was no significant effect of CSS or ECS.</p

Microglia cell body:total coverage ratio based on Iba-1 immunohistochemistry.

<p>Microglia cell body:total coverage ratio based on Iba-1 immunohistochemistry.</p

Comparison of body weight in CSS (n = 22) and control (n = 22) mice prior to and during ECS.

<p>A: Average body weight (g) in 5-day blocks prior to (block 1) and throughout the 15-day CSS procedure (block 2–4). B: Percentage average daily absolute (increase or decrease) body weight delta during the same period. (C): Average body weight during the final 5 days of CSS (block 4) and throughout the 10-day ECS procedure (block 5–6). Data presented as mean + sem. *p<0.05; ***p<0.001; two-way ANOVA with Bonferroni post hoc test.</p

Iba-1 immunohistochemistry for the calculation of microglial activity: representative images of the hippocampal CA1 radiatum, CA3 radiatum and hippocampal hilus regions from control-sham, control ECS, CSS-sham, CSS-ECS mice.

<p>Iba-1 immunohistochemistry for the calculation of microglial activity: representative images of the hippocampal CA1 radiatum, CA3 radiatum and hippocampal hilus regions from control-sham, control ECS, CSS-sham, CSS-ECS mice.</p

ChAT immunohistochemistry: representative images of the hippocampal CA1, CA3, and dentate gyrus (DG) regions from control-sham, control ECS, CSS-sham, CSS-ECS mice.

<p>ChAT immunohistochemistry: representative images of the hippocampal CA1, CA3, and dentate gyrus (DG) regions from control-sham, control ECS, CSS-sham, CSS-ECS mice.</p

Hippocampal cholinergic fibre density based on area covered by ChAT using immunohistochemistry.

<p>Hippocampal cholinergic fibre density based on area covered by ChAT using immunohistochemistry.</p

Effects of CSS and ECS on tone-shock (CS-US) fear conditioning and expression, measured as % time spent freezing.

<p>A + B: Fear conditioning stage; (A) Inter-trial intervals between CS-US pairings, (B) During CS of CS-US trials. C + D: Fear expression stage; (C) Inter-trial intervals between CS, (D) During CS trials. Data presented as mean + sem. In (A), significant treatment x trial interaction and significant trial-specific treatment effects in post hoc tests # p<0.05, ### p<0.001. In (B), significant main effect of trial ^ p<0.05, and significant main effect of treatment # p<0.05. In (C) and (D), significant main effect of treatment #### p<0.0001.</p

Major depressive disorder is associated with changes in a cluster of serum and urine biomarkers

Major Depressive Disorder (MDD) is a heterogeneous disorder with a considerable symptomatic overlap with other psychiatric and somatic disorders. This study aims at providing evidence for association of a set of serum and urine biomarkers with MDD. We analyzed urine and serum samples of 40 MDD patients and 47 age- and sex-matched controls using 40 potential MDD biomarkers (21 serum biomarkers and 19 urine biomarkers). All participants were of Caucasian origin. We developed an algorithm to combine the heterogeneity at biomarker level. This method enabled the identification of correlating biomarkers based on differences in variation and distribution between groups, combined the outcome of the selected biomarkers, and calculated depression probability scores (the “bio depression score”). Phenotype permutation analysis showed a significant discrimination between MDD and euthymic (control) subjects for biomarkers in urine (P <.001), in serum (P =.02) and in the combined serum plus urine result (P <.001). Based on this algorithm, a combination of 8 urine biomarkers and 9 serum biomarkers were identified to correlate with MDD, enabling an area under the curve (AUC) of 0.955 in a Receiver Operating Characteristic (ROC) analysis. Selection of either urine biomarkers or serum biomarkers resulted in AUC values of 0.907 and 0.853, respectively. Internal cross-validation (5-fold) confirmed the association of this set of biomarkers with MDD