Background Stress is widely known to alter behavioral responses to rewards and punishments. It is believed that stress may precipitate these changes through modulation of corticostriatal circuitry involved in reinforcement learning and motivation, although the intervening mechanisms remain unclear. One candidate is inflammation, which can rapidly increase following stress, and can disrupt dopamine-dependent reward pathways. Methods Here, in a sample of 88 healthy female participants, we first assessed the effect of an acute laboratory stress paradigm on levels of plasma interleukin-6 (IL-6), a cytokine known to be both responsive to stress and elevated in depression. In a second laboratory session, we examined the effects of a second laboratory stress paradigm on reward prediction error (RPE) signaling in the ventral striatum. Results We show that individual differences in stress-induced increases in IL-6 (session 1) were associated with decreased ventral striatal RPE signaling during reinforcement learning (session 2), though there was no main effect of stress on RPE. Further, changes in IL-6 following stress predicted intra-individual variability in perceived stress during a 4-month follow-up period. Conclusions Taken together, these data identify a novel link between IL-6 and striatal reward prediction errors during reinforcement learning in the context of acute psychological stress, as well as future appraisal of stressful life events.
The development of robust laboratory procedures for acute stress induction over the last decades has greatly advanced our understanding of stress responses in humans and their underlying neurobiological mechanisms. Nevertheless, attempts to uncover linear relationships among endocrine, neural, and affective responses to stress have generally yielded inconsistent results. Here, 79 healthy females completed a well established laboratory procedure of acute stress induction that was modified to prolong its effect. Endocrinological and subjective affect assessments revealed stress-induced increases in cortisol release and negative affect that persisted 65 and 100 min after stress onset, respectively, confirming a relatively prolonged acute stress induction. Applying latent class linear mixed modeling on individuals' patterns of cortisol responses identified three distinct trajectories of cortisol response: the hyper-response ( = 10), moderate-response ( = 21), and mild-response ( = 48) groups. Notably, whereas all three groups exhibited a significant stress-induced increase in cortisol release and negative affect, the hyper-response and mild-response groups both reported more negative affect relative to the moderate-response group. Structural MRI revealed no group differences in hippocampal and amygdala volumes, yet a continuous measure of cortisol response (area under the curve) showed that high and low levels of stress-induced cortisol release were associated with less hippocampal gray matter volume compared with moderate cortisol release. Together, these results suggest that distinct trajectories of cortisol response to prolonged acute stress among healthy females may not be captured by conventional linear analyses; instead, quadratic relations may better describe links between cortisol response to stress and affective responses, as well as hippocampal structural variability. Despite substantial research, it is unclear whether and how individual neuroendocrine stress response patterns are linked to affective responses to stress and structural variability in neuroendocrine regulatory brain regions. By applying latent class linear mixed modeling on individuals' patterns of cortisol responses to a prolonged acute stressor, we identified three distinct trajectories of cortisol response. Relative to the group showing a moderate cortisol response, groups characterized by hyper and mild cortisol response were both associated with more negative affect. Moreover, a continuous measure of cortisol response showed that high and low levels of stress-induced cortisol release correlated with reduced hippocampal gray matter volume. Given that neuroendocrine stress responses are conceptualized as biomarkers of stress susceptibility, these insights may have clinical implications.
BackgroundPreclinical and human studies suggest an association between chronic inflammation and the development of depressive behaviors. This is proposed to occur through downstream effects of inflammatory cytokines on neuroplasticity, neurogenesis and neurotransmitter function, although the neural correlates remain poorly understood in humans.MethodsIn Study 1, structural magnetic resonance imaging and serum inflammatory cytokine data were analyzed from 53 psychiatrically healthy female participants. Correlational analyses were conducted between interleukin-6 (IL-6) and volume in a priori regions implicated in the pathophysiology of major depressive disorder (MDD). In Study 2, medical data [including serum inflammatory acute phase reactants (C-reactive protein)] were analyzed for 12 589 participants. Participants were classified as having (n = 2541) v. not having (n = 10 048) probable lifetime MDD using phenotypes derived using machine-learning approaches. Non-parametric analyses compared inflammation between groups, whereas regression analyses probed whether inflammation predicted probable MDD classification while accounting for other variables.ResultsIn Study 1, significant negative correlations emerged between IL-6 and hippocampal, caudate, putamen and amygdalar volume. In Study 2, the MDD group showed a higher probability of elevated inflammation than the non-MDD group. Moreover, elevated inflammation was a significant predictor of probable MDD classification.ConclusionsFindings indicate that inflammation is cross-sectionally related to reduced volume in brain regions implicated in MDD phenotypes among a sample of psychiatrically healthy women, and is associated with the presence of probable MDD in a large clinical dataset. Future investigations may identify specific inflammatory markers predicting first MDD onset.
Investigations of pathophysiological mechanisms implicated in vulnerability to depression have been negatively impacted by the significant heterogeneity characteristic of psychiatric syndromes. Such challenges are also reflected in numerous null findings emerging from genome-wide association studies (GWAS) of depression. Bolstered by increasing sample sizes, recent GWAS studies have identified genetics variants linked to MDD. Among them, Okbay and colleagues (Nat. Genet. 2016 Jun;48(6):624–33) identified genetic variants associated with three well-validated depression-related phenotypes: subjective well-being, depressive symptoms, and neuroticism. Despite this progress, little is known about psychopathological and neurobiological mechanisms underlying such risk. To fill this gap, a genetic risk score (GRS) was computed from the Okbay’s study for a sample of 88 psychiatrically healthy females. Across two sessions, participants underwent two well-validated psychosocial stressors, and performed two separate tasks probing reward learning both before and after stress. Analyses tested whether GRS scores predicted anhedonia-related phenotypes across three units of analyses: self-report (Snaith Hamilton Pleasure Scale), behavior (stress-induced changes in reward learning), and circuits (stress-induced changes in striatal reward prediction error; striatal volume). GRS scores were negatively associated with anhedonia-related phenotypes across all units of analyses but only circuit-level variables were significant. In addition, the amount of explained variance was systematically larger as variables were putatively closer to the effects of genes (self-report < behavior < neural circuitry). Collectively, findings implicate anhedonia-related phenotypes and neurobiological mechanisms in increased depression vulnerability, and highlight the value of focusing on fundamental dimensions of functioning across different units of analyses.
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