Abstract
Objective: After an intense and repeated stress some rats become vulnerable to depression. This state is characterized by persistent low serum BDNF concentration. Our objective was to determine whether electrophysiological markers can sign vulnerability to depression.Methods: Forty-three Sprague Dawley rats were recorded with supradural electrodes above hippocampus and connected to wireless EEG transmitters. Twenty-nine animals experienced four daily social defeats (SD) followed by 1 month recovery. After SD, 14 rats had persistent low serum BDNF level and were considered as vulnerable (V) while the 15 others were considered as non-vulnerable (NV). EEG signals were analyzed during active waking before SD (Baseline), just after SD (Post-Stress) and 1 month after SD (Recovery).Results: We found that V animals are characterized by higher high θ and α spectral relative powers and lower β2 main peak frequency before SD. These differences are maintained at Post-Stress and Recovery for α spectral relative powers and β2 main peak frequency. Using ROC analysis, we show that low β2 main peak frequency assessed during Baseline is a good predictor of the future state of vulnerability to depression.Conclusion: Given the straightforwardness of EEG recordings, these results open the way to prospective studies in humans aiming to identify population at-risk for depression.
Highlights
Depression is thought to be the result of interaction effects between the individual and the environment (Harro, 2013)
One month after social defeats (SD), we identified vulnerable (V, n = 14) and non-vulnerable animals (NV, n = 15) using a k-mean method based on their serum Brain Derived Neurotrophic Factor (sBDNF) levels during Baseline and Recovery (Figure 2)
The time course of sBDNF was different in NV and V rats (Figure 3; Supplementary Table 2, Group∗Time effect: p < 0.001): sBDNF decreased after SD to return to Baseline values 1 month later in the NV group, but remained low in the V group
Summary
Depression is thought to be the result of interaction effects between the individual and the environment (Harro, 2013). The diathesis-stress model provides a conceptual framework to understand the occurrence of depression. The diathesis represents the vulnerability of a given individual (Bernard, 2016). Such vulnerability includes numerous factors, such as genetic (Sullivan et al, 2000) and environmental ones (Lueboonthavatchai, 2009). Prevention of depression requires an early detection of vulnerable subjects, i.e., individuals presenting a high risk to develop depression when exposed to a stressful event. Finding biomarkers of vulnerability to depression is a key issue to identify high risk subjects, who do not present clinical signs, in order to open the way to preventive treatment
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