Negative biases in emotional processing are central to cognitive models of Major Depressive Disorder (MDD), yet it remains unclear whether negatively biased valence attribution covaries with depressive symptoms or represents a more stable vulnerability. In this longitudinal study, we examined emotional valence ratings during a subliminal affective priming task in n = 232 MDD patients and n = 496 healthy controls (HC's) across multiple follow-up assessments, yielding 1395 observations. Multilevel models tested effects of depressive symptom severity, diagnostic group (MDD vs. HC), affective prime (happy, sad, neutral), and their interactions. To separate within-person fluctuations from between-person differences, depressive symptom severity was decomposed (Mundlak within-between specification). Exploratory analyses examined whether long-term symptom trajectory clusters were associated with emotional bias. Greater depressive symptom severity was associated with more negative valence ratings. Within-between analyses indicated that this association was primarily driven by within-person symptom fluctuations, indicating more negative ratings when symptom severity exceeded individual average. In contrast, diagnostic group, prime condition, and symptom severity × prime interactions did not significantly predict valence ratings, and no group differences emerged between HC's and remitted MDD patients. Exploratory trajectory analyses suggested that patients with recurrent symptom patterns may show more negative valence ratings, although cluster stability was limited and findings should be interpreted cautiously. Overall, the results suggest that negative valence attribution in MDD is more closely linked to current depressive symptom severity than to diagnostic status alone. Longitudinal approaches separating within- and between-person processes may help clarify when negative biases emerge and persist during depression progression.