Differentiating MCI from depression through verbal memory scores

The present study aims to assess the differences between major depressive disorder (MDD) and mild cognitive impairment (MCI) in terms of verbal learning profile together with structural changes in the brain on magnetic resonance imaging (MRI) and to reveal predictive factors for MCI.

Fifty-six patients with MDD and 31 MCI subjects were assessed using the Turkish Verbal Memory Processes Test (VMPT). Brain MRI was used to evaluate sulcal atrophy (SA), ventricular atrophy, periventricular white matter hyperintensity (WMH), subcortical WMH, basal ganglia infarct, medial temporal lobe atrophy, and infratentorial infarct scores based on the Modified Visual MRI Rating Scale (MVMRS). The symptoms of depression were evaluated with the Beck Depression Inventory in both groups. Demographic factors, VMPT scores, and MVMRS scores between MDD and MCI groups were compared. Also, potential predictors of MCI were analyzed by binary logistic regression analyses.

The total scores of VMPT and the scores of VMPT subgroups, including immediate memory, highest learning, total learning, and delayed recall, were significantly higher in the MDD groups compared to MCI patients (Mann-Whitney U, Student's t-test, p < 0.05), indicating that higher scores were associated with better memory. The total MVMRS score and a subgroup of MVMRS, the SA score, were significantly higher in MCI patients compared to the MDD group, suggesting more atrophic changes and a higher burden of infarction in MCI patients. In our statistical analyses, impaired immediate memory (p < 0.001; OR = 6.002; 95% CI: 1.996-18.042), increased SA (p = 0.008; OR = 1.522; 95% CI: 1.118-2.073), and education (p = 0.028; OR = 0.84; 95% CI: 0.719-0.981) were significant predictive values obtained through backward Wald elimination in the binary logistic regression model for detecting MCI.

Our findings suggest that VMPT may potentially represent a novel neuropsychiatric test that might be combined with MRI-based morphometric evaluation methods, such as MVMRS.