Distinct profiles of anhedonia and reward processing and their prospective associations with quality of life among individuals with mood disorders

Abstract

Leading professional health bodies have called for the wider adoption of Patient Reported Outcome Measures, such as quality of life, in research and clinical practice as a means for understanding why the global burden of depression continues to climb despite increased rates of treatment use. Here, we examined whether anhedonia-an often recalcitrant and impairing symptom of depression-along with its neural correlates, was associated with longitudinal changes in patient-reported quality of life among individuals seeking treatment for mood disorders. We recruited 112 participants, including n = 80 individuals with mood disorders (58 unipolar, 22 bipolar) and n = 32 healthy controls (63.4% female). We assessed anhedonia severity along with two electroencephalographic markers of neural reward responsiveness (scalp-level 'Reward Positivity' amplitude and source-localized reward-related activation in the dorsal anterior cingulate cortex), and assessed quality of life at baseline, 3- and 6-month follow-up. Anhedonia emerged as a robust correlate of quality of life cross-sectionally and longitudinally among individuals with mood disorders. Furthermore, increased neural reward responsiveness at baseline was associated with greater improvements in quality of life over time, and this improvement was mediated by longitudinal improvements in anhedonia severity. Finally, differences in quality of life observed between individuals with unipolar and bipolar mood disorders were mediated by differences in anhedonia severity. Our findings indicate that anhedonia and its reward-related neural correlates are linked to variability in quality of life over time in individuals with mood disorders. Treatments capable of improving anhedonia and normalizing brain reward function may be necessary for improving broader health outcomes for individuals seeking treatment for depression.ClinicalTrials.gov identifier: NCT01976975.

Figure 1.

The waveform on the left shows results of the principal component analysis (PCA). The two red lines show the waveforms for the RewP components (TF8/SF2) for the rich (higher amplitude) and lean (lower amplitude) conditions. The black dotted line shows the waveform resulting from adding the RewP and other key components together, and closely resembles the raw ERP waveform (other components shown in Fig. S1). The results of the source localization analysis (shown on the right) indicated that the scalp recorded RewP component was associated with current source density (CSD) in a cluster of voxels in the dorsal anterior cingulate cortex (dACC), shown in red.

Figure 2.

Bivariate correlations between symptom severity, reward markers, and quality of life (a), ranked correlates of life enjoyment and satisfaction (b), ranked correlates of mental health-related quality of life (c), and ranked correlates of physical health-related quality of life (d). Correlations reflect associations among the patient group only. Color scale reflects Pearson’s r values with uncorrected p-values shown in parentheses in panel a. Asterisks on panels b, c and d indicate significant correlations (*p < 0.05; **p < 0.01; ***p < 0.001); all remain significant after Benjamini-Hochberg correction for multiple correlations. Note. QLES=Total scores on the Q-LES-Q; MCS=Mental health-related quality of life subscale of the SF-36; PCS=Physical health-related quality of life subscale of the SF-36; AD=Anhedonic Depression subscale of the MASQ; GDD=General Distress due to Depression subscale of the MASQ; GDA=General Distress due to Anxiety subscale of the MASQ; AA=Anxious arousal subscale of the MASQ; RewP=ΔRewP amplitude; dACC=ΔRewP-related current source density in the dorsal anterior cingulate cortex.

Figure 3.

Schematic showing the potential pathways via which brain reward function may be linked to patient’s overall quality of life. Domains of functioning (denoted by dashed borders) were not directly evaluated in this study, so have been inferred from prior research. This schematic was informed by Wilson & Cleary’s (1995) Conceptual Model of Patient Outcomes, which shows the pathways through which biological/physiological measures may influence patient quality of life via symptoms, functioning and health perceptions.