Cognitive tests distinguish biomarker-verified early Alzheimer's disease from other patients.

BACKGROUND: The diagnosis of Alzheimer’s disease (AD) is based on the presence of characteristic biomarkers and the presence of a clinical AD phenotype. Since pathological changes typically begin years before a formal diagnosis, early detection is an important objective in AD research. Literature suggests that especially cognitive tests for assessing relational memory and memory tests requiring discrimination between previously learned and similar novel stimuli, are indicative of early AD-related cognitive impairment. METHODS: 288 memory clinic patients were divided into three Mini-Mental State Examination (MMSE) groups: Group A (MMSE 27–30), Group B (MMSE 23–26), Group C (MMSE 18–22). Logistic regression analyses were conducted to evaluate the ability of seven neuropsychological tests, selected for their clinical relevance in diagnosing AD and distinguishing it from differential diagnoses, to predict whether a patient has AD according to their cerebrospinal fluid profile (AD+) or another neurodegenerative disease/ another dementia syndrome (AD-), for the three MMSE groups separately. RESULTS: The model’s classification accuracy decreased from 83.78% in Group A to 72.92% in Group B and 75.81% in Group C. In Group A, significant predictors included Paired-Associate Learning (PAL), with AD+ patients performing worse; Phonemic Fluency (PhonoWF) and Beck’s Depression Inventory (BDI). PhonoWF and BDI are related to impairments of the AD- group: AD- patients showed a poorer test performance and more depressive symptoms. CONCLUSIONS: Predictive value of neuropsychological tests varies with the stage of cognitive impairment. Integrating relational memory tasks, such as PAL, enhances the utility of neuropsychological assessments in early identification of clinical AD phenotypes.