Journal of Dementia and Alzheimer's Disease

Background: Performance of daily activities (Activities of Daily Living [ADLs] and Instrumental ADLs [IADLs]) is key to independent functioning in dementia, and greater I/ADL dependence contributes to burden in caregivers. We investigated how domains of daily living activities predict previously defined factors of the Zarit Burden Interview (ZBI). Methods: Caregiver and care recipient data for 389 dyads were extracted from outpatient memory clinic records. Results: Four previously defined factors of the ZBI (‘Impact on Life’, ‘Guilt/Uncertainty’, ‘Embarrassment/Frustration’, ‘Overwhelm’) were used in regression analyses, which demonstrated that ADLs predicted Impact on Life and Embarrassment/Frustration while IADLs predicted only Embarrassment/Frustration. Conclusions: Areas of decline in daily performance may differentially contribute to facets of dementia caregiver burden, with ADLs potentially having greater impact than IADLs.

Background: Early diagnosis of Alzheimer’s disease (AD) is constrained by invasive and costly tests. Aggregation of $\beta$-amyloid and the A$\beta$42/A$\beta$40 ratio in cerebrospinal fluid (CSF) and blood are key biomarkers. Fluorescent probes can report aggregate states, and artificial intelligence (AI) can extract subtle patterns from spectral and blood data. This review synthesizes how probes and AI can identify aggregates and assess the A$\beta$42/A$\beta$40 ratio in body fluids to facilitate earlier AD diagnosis. Methods: PRISMA-compliant searches were conducted in Scopus, PubMed, Web of Science, and IEEE Xplore. Results: Twenty-eight studies met inclusion criteria. Plasma A$\beta$42/A$\beta$40 was lower in PET-positive individuals by ∼7–18%, with higher performance for mass spectrometry (mean AUC ≈ 0.80) than immunoassays (AUC ≈ 0.71). CSF A$\beta$42/A$\beta$40 showed larger group differences (∼50% reductions in PET+) and stronger PET concordance, outperforming plasma. Fluorescent probes—including AN-SP and CRANAD-28—were sensitive to early aggregates and showed in vivo imaging potential, but evidence is largely preclinical or from small cohorts. AI/ML approaches frequently achieved within-study accuracies >90% (e.g., 94–100% in spectral tasks), yet external validation and head-to-head tests of ratio alone versus ratio + AI remain scarce. Conclusions: Plasma A$\beta$42/40 —particularly by mass spectrometry—currently provides the most reproducible fluid approximation to amyloid PET (mean AUC ≈ 0.80). Fluorescent probes sensitively detect oligomeric A$\beta$ species and show in vivo potential, but evidence remains largely preclinical or from small cohorts. AI/ML methods can extract additional signal from spectral and multivariate blood data, yet consistent incremental gains over optimized Aβ42/40 assays have not been demonstrated due to limited external validation and head-to-head comparisons.

Alzheimer’s disease accounts for approximately 50% to 80% of all causes of dementia. Co-existence of AD with other diseases causing dementia poses a diagnostic challenge, as we are still far from diagnosing AD accurately in order to manage it appropriately. Neuroimaging techniques, not only help diagnose AD but also consistently feature in diagnostic and research criteria for AD as biomarkers. Molecular biomarkers including positron emission tomography (PET) and single-photon emission computed tomography (SPECT), and structural biomarkers including magnetic resonance imaging (MRI), have been used in various therapeutic and prognostic studies in AD. This review highlights the recent advances in neuroimaging biomarkers, including molecular biomarkers (PET and SPECT tracers) and structural biomarkers (MRI), for AD. For the purpose of this review, molecular biomarkers have been further subcategorized into non-specific radiotracers (FDG-PET and blood flow SPECT) and specific amyloid- and tau-related radiotracers. The aim of this review is to discuss the recent advances and evidence of molecular and structural biomarkers of AD.