Background
Major depressive disorder (MDD) affects 20% of the population and is characterized by an array of behavioral, emotional, and cognitive symptoms [
1]. Cognitive symptoms of MDD, such as negative cognitive bias, persist in individuals in remission from MDD and are associated with increased relapse rates in these individuals [
2‐
4]. Current treatments are not effective in reducing negative cognitive bias in MDD [
5,
6] and the presence of negative cognitive bias can predict the efficacy of antidepressants in MDD [
7,
8]. Thus, there is a need to develop novel therapeutics to treat MDD and attenuate negative cognitive bias in MDD. Human females are more likely to present with MDD and display cognitive symptoms of MDD compared to human males [
9,
10]. Discovering the underlying mechanisms of negative cognitive bias with a focus on sex will aid in the discovery of precision treatments for negative cognitive bias in MDD.
Pattern separation, the ability to distinguish between highly similar inputs, is impaired in MDD [
11‐
13], is involved in cognitive bias [
14,
15], and relies on hippocampal neurogenesis [
16‐
21]. Neurogenesis in the hippocampus declines with MDD and age in humans and in rodent models [
22‐
30]. Further, treatment with antidepressants, such as selective serotonin reuptake inhibitors (SSRIs), is linked to increased neurogenesis in MDD and in rodent models with some suggestion of sex differences [
23,
31,
32]. Intriguingly, there are sex differences in pattern separation and neurogenesis in response to pattern separation [
33,
34]. However, the association between hippocampal neurogenesis and cognitive bias has not been examined.
Meta-analyses indicate that peripheral cytokines (including interleukin (IL)-1β, IL-6, and tumour necrosis factor (TNF)-α) and hippocampal inflammation are increased in individuals with MDD [
35‐
38], indicating inflammation as potential biomarker for MDD. Indeed, levels of cytokines are associated with poor treatment response in individuals with MDD, indicating they may play a role in remission [
39]. Moreover, there are sex and age differences in proinflammatory cytokine production with higher levels in young and middle-aged females compared to males at baseline and in response to a challenge [
40‐
42]. However, sex differences are seldom examined in studies of inflammation in MDD, even though females may be more susceptible than males to the effects of inflammation on depressed mood [
40].
Both inflammation and neurogenesis in the hippocampus influences cognition, including pattern separation [
16‐
21,
43], indicating that both may be involved in cognitive bias. The basolateral amygdala, which is associated with mood regulation, modulates negative affect and depressive-like behavior after immune challenge [
44‐
47] and interacts with the hippocampus to regulate neurogenesis [
48]. Further, projections between the ventral hippocampus and the basolateral amygdala are required for fear memory, anxiety, and pattern separation [
49‐
51], but sex differences have not been analyzed. Previously we found greater neural activity in dorsal and ventral hippocampal subregions (CA1, CA3, dentate gyrus) and amygdala subregions (basolateral, lateral, central) of young adult females compared to young adult males in response to a similar cognitive bias, indicating a sex difference in the role of these regions to negative cognitive bias [
52]. Sex differences in the association between inflammation in the hippocampus and amygdala, neurogenesis in the hippocampus, and negative cognitive bias have yet to be examined.
In the present study, we examined sex and age differences in hippocampal neurogenesis and inflammatory cytokine (interferon gamma (IFN-γ), IL-1β, IL-4, IL-5, IL-6, IL-10, IL-13, TNF-α) and chemokine (C-X-C motif ligand 1; CXCL1) levels in the basolateral amygdala and ventral hippocampus after cognitive bias testing in rats. We hypothesized that there would be sex differences in the associations of inflammation and neurogenesis with cognitive bias. As cognitive bias changes with age, we examined adolescent, young adult, and middle-aged rats, and hypothesized that the association between cognitive bias, inflammation, and neurogenesis would differ by age.
Methods
Animals
Male and female Sprague–Dawley rats (N = 91) were bred in house from animals obtained from Charles River (Québec, Canada). Only 1 male and 1 female rat per litter was assigned to each age group and each condition to avoid litter confounding effects. Males and females were housed (2–3 per cage) in separate colony rooms. Rats were maintained under a 12 h light–dark cycle, with lights on at 07:00 h. Rats were housed in opaque polyurethane bins (48 × 27 × 20 cm) with aspen chip bedding and ad libitum access to autoclaved tap water and rat chow (Jamieson’s Pet Food Distributors Ltd, Delta, BC, Canada). Rats were left undisturbed, apart from weekly cage changing, until they reached the correct age for testing. All experimental procedures were approved by the University of British Columbia Animal Care Committee and in accordance with the Canadian Council on Animal Care guidelines.
Cognitive bias task procedure
Cognitive bias procedure and tissue collection methods are previously described in Hodges et al. ([
52]). Briefly, male and female rats were randomly assigned to be tested in adolescence (postnatal day (PD) 40,
n = 29), young adulthood (PD 100,
n = 30), or middle-aged adulthood (PD 210,
n = 36) and then to one of the two groups—test rats (adolescents: male
n = 8, female
n = 9; young adults:
n = 9 per sex; middle-aged adults:
n = 12 per sex), or no-shock controls (
n = 6 per sex and age). Rats were placed in a shock-paired context (Context A) and in a no-shock-paired context (Context B) for 5 min each daily for 16 consecutive days, one context in the morning (8:30 h – 11:00 h) and the other context in the afternoon (13:00 h – 15:30 h). After 16 days of training, rats were placed in an ambiguous context (Context C) for 5 min with no footshock on Test Day (Day 18). Context C partially resembled both Contexts A and B in terms of transport (duration and method), illumination (two lights), one lever out, and an intermediate pattern of lines on the walls (7 mm between lines). No-shock controls did not receive a footshock in any context. Time spent freezing (no head or body movement besides breathing; [
99]) during the first 3 min of entering each context was measured on each day and percentage freezing was computed. Further, a difference score was created by subtracting percentage freezing in Context C on Day 18 from percentage freezing in Context B (no footshock-paired) on Day 16 and used to index negative cognitive bias scores (high freezing = negative cognitive bias; low freezing = neutral/positive cognitive bias; adapted from [
100,
101]).
These behavioral data were published previously [
52]. We found that adolescent rats had a more positive cognitive bias compared to a greater negative cognitive bias in adults and middle-aged males had a greater negative cognitive bias than middle-aged females (see supplementary Fig. S
2). Regardless of age and sex, test rats had higher freezing than no-shock controls in the ambiguous context. Ninety min after exposure to Context C on day 18, test rats were euthanized by decapitation. Brains were removed from the skull and cut in equal halves along the sagittal plane. The left hemisphere was used for DCX immunohistochemistry and the right hemisphere was used for electrochemiluminescence (described below).
DCX Immunohistochemistry
We examined hippocampal neurogenesis using a marker of immature neurons and microtubule-associated protein, doublecortin (DCX; [
102]) in both the cognitive bias and no-shock controls. The left hemisphere was placed into a 4% paraformaldehyde solution for 24 h, and subsequently placed into a 30% sucrose in 0.1 M phosphate buffered saline (PBS; pH 7.4) for another 24 h and then until sliced. Coronal Sects. (30 µm) were sliced on a microtome and collected from approximately bregma 3.72 mm to -6.96 mm [
103]. Sections were stored in an antifreeze solution (30% ethylene glycol, 20% glycerol in 0.1 M phosphate buffer (PB; pH 7.4)) at -20 °C until immunohistochemistry assays were conducted.
Coronal sections were successively washed 3 × in PBS for 10 min per wash and incubated at room temperature in a 0.6% hydrogen peroxide (H2O2; H1009, Sigma-Alrich, St. Louis, MO, USA) in distilled water (dH2O) for 30 min. Sections were then washed another 3 × in 0.1 M PBS for 10 min per wash, and then incubated at 4 °C in DCX primary antibody (1:1000 goat Anti-DCX pAb; SC-8066; Santa Cruz Biotechnology, Dallas, TX, USA), 3% normal rabbit serum (VECTS5000, Vector Laboratories, Inc, Burlingame, CA), and 4% Triton-X in PBS for 24 h. The next day, sections were washed 5 × in 0.1 M PBS for 10 min per wash and incubated overnight at 4 °C in secondary antibody (biotinylated rabbit anti-goat IgG; 1:500; Vector Laboratories, Inc, Burlingame, CA). The last day, after another series of 5 washes in 0.1 M PBS for 10 min per wash, sections were incubated in an avidin–biotin horseradish peroxidase solution (PK-4000, Vector Laboratories, Inc, Burlingame, CA) for 4 h at room temperature. Sections were washed 3 × in 0.1 M PBS for 10 min per wash and horseradish peroxidase was visualized using 3,3’ diaminobenzidine (DAB) in a 3 M sodium acetate buffer containing 2.5% nickel sulfate and 0.05% H2O2 (SK-4100, Vector Laboratories, Inc, Burlingame, CA) for 3 min. Sections were washed another 3 × in 0.1 M PBS for 10 min per wash and then mounted on Superfrost Plus slides (Fisher Scientific, Inc., Hampton, NH) and let dry. Sections were then dehydrated using increasing concentrations of ethanol (50%, 70%, 95%, 100% for 2, 2, 2, and 10 min respectively), and then cleared with xylene for 10 min and coverslipped using Permount mounting medium (Fisher Scientific, Inc., Hampton, NH).
DCX protein immunostained brain sections were analyzed using a Nikon Eclipse 80i microscope in the dorsal hippocampus (within bregma -2.64 mm and -4.56 mm) and ventral hippocampus (within bregma -5.76 mm and -6.36 mm). Photomicrographs were taken using a slidescanner (ZEISS Axioscan 7 Slide Scanner, Germany) and used to trace outline of each subregion of interest to calculate the area of each region using ImageJ software (Image J, 2020). Cell counts of DCX expressing cells were conducted by experimenters’ blind to experimental condition and averaged across 2 sections per animal hippocampal region using a 40 × objective. DCX expressing cells for each subregion of interest was calculated by dividing the cell count by the corresponding area in mm2 for each animal.
Multiplex cytokine electrochemiluminescence
Electrochemiluminescence was done in accordance with previous protocols [
104]. The right hemisphere of the brain was rapidly frozen and coronally sliced at 300 µm. The BLA (within bregma 1.92 mm and 0.96 mm) and the vHPC (within -5.76 mm and -6.36 mm) were identified and dissected out using tissue punching tools (0.75 mm, 1.20 mm, and 2 mm in diameter; Harris Uni-Core, Sigma-Alrich) and placed directly into tubes containing beads (1.4 mm ceramic spheres, Lysing Matrix D, MP Biomedicals™, Santa Ana, CA, USA) on dry ice. Tissue was homogenized in complete lysis buffer using the Omni Bead Ruptor 24 (Omni International. Kennesaw, GA, USA). After homogenization, samples were centrifuged at 4°C at 1000 g for 10 min and supernatant was collected and stored at -80°C until cytokine analysis.
Cytokine levels were quantified in samples using a multiplex electrochemiluminescence immunoassay kit (V-PLEX Proinflammatory Panel 2, Rat) from Meso Scale Discovery (Rockville, MD, USA). The following 8 cytokines and 1 chemokine were quantified in each sample: interferon gamma (IFN- γ), interleukin (IL)-1β, IL-4, IL-5, IL-6, IL-10, IL-13, tumor necrosis factor (TNF)-α, and the chemokine C-X-C motif ligand 1 (CXCL1). Samples were run in duplicates and plates were read using a Sector Imager 2400 (Meso Scale Discovery) and analyzed using the Discovery Workbench 4.0 software (Meso Scale Discovery). The lower limits of detection (LLOD) were as follows for each individual plate (4 plates total) in pg/mL: IFN- γ: 0.674, 1.776, 1.62, 2.652; IL-1β: 1.995, 3.745, 3.616, 8.118; IL-4: 1.64, 4.613, 2.062, 5.75; IL-5: 0.552, 1.563, 0.541, 0.999; IL-6: 2.18, 4.09, 2.462, 3.718; IL-10: 0.789, 1.99, 1.744; 5.574; IL-13: 0.168, 0.698, 0.143, 0.252; TNF-α: 0.385, 0.97, 0.298, 0.399; and CXCL1: 0.99, 0.406, 0.967, 0.558. Inter-assay coefficient of variation was < 23% for all cytokines between plates.
Data analyses
General linear mixed model ANOVAs for levels of each cytokine/chemokine in the basolateral amygdala and ventral hippocampus were run with sex (male, female) and age (adolescence, young adulthood, middle-aged adulthood) as between-subjects factors. A repeated measures ANOVA using the same between-subjects factors as above and condition (no-shock controls, test rats) as an additional between-subjects factor was performed on the dorsal and ventral hippocampus DCX data. Pearson’s correlations were conducted between BLA or vHPC cytokine/chemokine levels, dorsal or ventral hippocampal DCX, and freezing in the ambiguous context or negative cognitive bias score. Principal component analyses were performed using DCX data and inflammation data in each brain region in test rats only. Missing values, due to outliers (two standard deviations below or above the mean), which accounted for 1.65% of the data, were replaced by the mean for PCA analyses. One middle-aged male was completely removed from PCA analyses because they were missing 78% of cytokine/chemokine data in the ventral hippocampus due to cytokine levels two standard deviations above the mean. Post-hoc tests used Newman-Keuls comparisons. Any a priori comparisons examining sex differences were subjected to Bonferroni comparisons. Significance level of p < 0.05 was used. All statistical analyses were performed using Statistica software (v. 9, StatSoft, Inc., Tulsa, OK, USA).
Four test rats were excluded from the following analyses due to their inability to distinguish between the shock- and no-shock-paired contexts on Day 16 of training (2 middle-aged males, 1 middle-aged female, 1 young adult male).
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