Identifying Mild Cognitive Impairment in Healthy Aging: The Role of Subjective Complaints and Blood Biomarkers

Background: Mild Cognitive Impairment (MCI) is described as an intermediate nosological entity between healthy aging and dementia, characterized by objective cognitive impairment, subjective cognitive decline (SCD) and preserved activities of daily living (Winblad et al., 2004). Even though there is sufficient consensus across literature on its diagnostic features, research and clinical settings still lack a gold standard instrument and defined thresholds for the assessment of SCD. In this framework, a recently developed scale, the Multidimensional Assessment of Subjective Cognitive Decline (MASCoD), may play a critical role in evaluating SCD. Likewise, blood-based biomarkers of Alzheimer’s disease (AD) have undergone significant advancements in recent years, resulting in the development of feasible blood tests for tau pathology and other underlying pathological mechanisms. Considering that AD neuropathology is known to begin up to 20 years prior to symptom onset, blood biomarkers may help predict future progression to dementia during the prodromal stages of AD (Alawode et al., 2022). Methods: Seventy-four older adults were enrolled in the study and classified as cognitively unimpaired (CU) individuals or as having MCI. This distinction was determined through a neuropsychological assessment (evaluating 6 cognitive domains) and reports of SCD, measured through the MASCoD scale. This procedure was in accordance with the updated MCI criteria (Dunne et al., 2021). In addition, blood samples were collected to measure the concentrations of AD-related plasma biomarkers such as p-tau217, p-tau181, GFAP, NfL, and Aβ42/40 ratio. Results: No difference in MASCoD scores emerged between CU and MCI participants, whereas levels of p-tau217, p-tau181, GFAP, and NfL appeared to be higher in individuals with MCI. In MCI participants, SCD correlated positively with plasma p-tau217 levels, explaining 21.2% of MASCoD variance. In the MCI group, no significant correlation was found between SCD and cognitive performance. Although, when controlling for potentially confounding demographic variables (i.e., age, education, cognitive reserve), a negative correlation emerged between SCD and language performance. Across CU individuals, MASCoD variance was better explained by attentive domain and depressive symptoms (as assessed by BDI-II). Specifically, SCD had a negative correlation with performance in the attention domain, while the correlation with depressive symptoms was found to be positive. Conclusion: Even though MASCoD scores did not differentiate MCI from cognitively unimpaired participants, findings suggest that in individuals with MCI, SCD may be associated to underlying neuropathological changes, as indicated by the correlation with plasma p-tau217 (marker of AD-pathology). Clinically, this underscores how SCD assessment can improve diagnostic accuracy when subtle objective cognitive impairment is present, as it may help identify subjects at higher risk for cognitive decline. Age, education level and cognitive reserve seem to act as confounding factors, masking MCI individuals’ awareness for difficulties in the language domain. In CU individuals, the role of SCD appears to be different, as the perception of cognitive changes was mainly associated with attentional difficulties and mood symptoms such as depression.