Early Detection of Alzheimer’s Disease: Biomarkers and Cognitive Screening Tools

Abstract

Early detection of Alzheimer’s disease (AD) is essential for timely intervention, disease management, and improved quality of life. This study investigates the diagnostic accuracy of combining cognitive screening tools—Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA)—with blood-based biomarkers, including amyloid-beta 42/40 ratio (Aβ42/40) and phosphorylated tau (p-tau181), for early identification of AD. A total of 180 participants categorized as cognitively normal (CN), mild cognitive impairment (MCI), or early-stage AD were assessed. Descriptive and inferential statistics, including ANOVA, Pearson correlation, t-tests, multiple linear regression, and ROC curve analysis, were conducted using IBM SPSS and GraphPad Prism. Results revealed significant differences across diagnostic groups in both cognitive scores and biomarker levels. MoCA and p-tau181 demonstrated the highest diagnostic accuracy with AUC values of 0.947 and 0.936, respectively. Regression analysis confirmed all four indicators as significant predictors of AD diagnosis (p < 0.001). Strong correlations were observed between cognitive decline and biomarker abnormalities. These findings support a multidimensional approach that integrates cognitive and biological assessments for early Alzheimer’s detection. The use of non-invasive, scalable biomarker testing alongside cognitive tools enhances diagnostic precision and holds significant potential for implementation in clinical and community settings.