Sleep fragmentation and heightened inflammation: A latent profile subtype predicting nine-year major depressive...

Cross-sectional and standard approaches to examining proinflammatory activity and sleep disturbances separately hinder understanding of their additive, long-term impacts on major depressive disorder (MDD). The current study used latent profile analysis (LPA) to identify multimodal neuroimmune profiles and to investigate whether subtypes predicted 9-year MDD severity in a community-dwelling adult sample.

Community adults (N = 306) completed psychiatric interviews to measure MDD symptoms at baseline and 9-year follow-up. The Pittsburgh Sleep Quality Index and eight-day actigraphy captured subjective and objective sleep disturbances, respectively. Nine log-transformed inflammatory markers-including C-reactive protein, E-selectin, intercellular adhesion molecule-1, fibrinogen, interleukin-6, interleukin-8, interleukin-10, and tumor necrosis factor-α-were assayed. An LPA with an interpretable 13-variable core set was conducted, with model selection based on various metrics, including split-sample Adjusted Rand Index (ARI) stability.

The two-profile solution provided the best fit (ARI = 0.948). Profile 1 (n = 212) was marked by adequate sleep and low inflammation; Profile 2 (n = 94) by insufficient sleep and high inflammation. Profile 2 membership was a strong predictor of greater 9-year MDD severity (Cohen's d = 0.244, p = .039) after controlling for baseline demographics and MDD severity. This effect remained practically significant in the completely adjusted model (d = 0.208). LPA had superior performance than variable-centered approaches on parsimony-based model fit.

A neuroimmune profile characterized by proinflammatory activity and insufficient, fragmented sleep functioned as a distal risk factor of MDD symptoms. A person-centered, multimodal risk stratification approach may enhance targeted prevention of long-term MDD.