Prognostic prediction of subjective cognitive decline in major depressive disorder based on immune biomarkers: a prospective observational study

[摘要] ObjectiveSubjective cognitive decline (SCD) is highlighted in patients with major depressive disorder (MDD), which impairs objective cognitive performance and worsens the clinical outcomes. Immune dysregulation is supposed to be the potential mechanism of cognitive impairment. However, the peripheral immune biomarkers in patients troubled with MDD and SCD are not conventionally described.MethodsA prospective-observational study was conducted for 8 weeks. Subjective cognitive function was measured using the Chinese version of the 20-item perceived deficits questionnaire-depression (PDQ-D) and depression symptoms were evaluated with Hamilton Depression Rating Scale-17 (HDRS-17). Luminex assays were used to measure 48 immune cytokines in plasma at baseline. Integrating these results and clinicopathological features, a logistic regression model was used to develop a prognostic prediction.ResultsTotally, 114 patients were enrolled in this study. Among the patients who completed follow-up, 56% (N = 50) had residual subjective cognitive decline, and 44% (N = 50) did not. The plasma levels of FGF basic, INF-γ, IL-1β, MCP-1, M-CSF and SCF were increased and the levels of IL-9, RANTES and PDGF-BB were decreased in the SCD group. Additionally, Basic FGF, IFN-γ, IL-1β, and SCF were positively correlated and IL-9, RANTES, and PDGF-BB were negatively correlated with the PDQ-D scores after treatment. Notably, combinations of cytokines (SCF and PDGF-BB) and PDQ-D scores at baseline showed good performance (The area under the receiver operating characteristic curve = 0.818) in the prediction of subjective cognitive decline.ConclusionA prognostic model based on protein concentrations of SCF, PDGF-BB, and scores of PDQ-D showed considerable accuracy in predicting residual subjective cognitive decline in depression.

[发布日期] 2022-12-30

[关键词] Major depressive disorder;Subjective cognitive decline;Immune biomarkers;Predictive model