Qihao Guo

Alzheimer's disease (AD) is a neurodegenerative disorder. Irreversible pathological alterations are already present when clinical symptoms emerge. Therefore, early diagnosis and intervention are crucial for improving patient outcomes and reducing the social and healthcare burden. With its advantages of minimal invasiveness, convenience, affordability, and high accessibility, blood‐based testing has overcome the limitations of conventional methods, becoming a major focus of research in early AD diagnosis in recent years. Based on the key domestic and international research findings in recent years, this paper systematically reviews the types, mechanisms of action, and relevant detection technologies of blood‐based biomarkers for AD.

Background: Late-life depressive symptoms accompany cognitive and functional impairment, but overall burden can obscure clinically and biologically relevant symptom differences. Methods: We analysed cross-sectional data from 2977 Chinese Preclinical Alzheimer’s Disease Study participants spanning normal cognition to dementia. We examined data-derived Inventory of Depressive Symptomatology–Self-Report (IDS-SR) dimensions and person-centred profiles against function, cognition, plasma biomarkers, amyloid PET, dorsal attention network connectivity, and cognitive status. Findings: Five dimensions showed distinct associations. Psychomotor disturbance had the broadest clinical and plasma associations; per-SD odds ratios were 1·700 (95% CI 1·436–2·011) for mild cognitive impairment and 2·932 (2·432–3·535) for dementia versus normal cognition. Other dimensions showed selective, stage-dependent patterns. No dimension-level amyloid-PET or dorsal attention network association survived false-discovery-rate correction. Five profiles primarily reflected severity. After adjustment for overall burden, a post-hoc comparison showed poorer cognition, higher phosphorylated tau 217 and 181, glial fibrillary acidic protein, and amyloid burden, and greater dementia odds in the psychomotor-relative than insomnia-relative low-burden profile. The IDS-SR psychomotor-disturbance subscore (IDS-SR-PM), comprising the four psychomotor-dimension items—concentration or decision making, general interest, capacity for pleasure or enjoyment, and feeling slowed down—retained clinical and biomarker associations and showed slightly stronger plasma associations than IDS total. Interpretation: Depressive symptom dimensions and configurations reveal distinct clinical and biological patterns beyond overall burden, improving phenotypic resolution. Brief psychomotor assessment is a candidate for longitudinal validation.

Background: Late-life depressive symptoms are associated with cognitive and functional impairment and dementia, yet assessing overall burden can obscure clinically and biologically informative differences in symptom composition.Methods: We analysed cross-sectional baseline data from 2977 Chinese Preclinical Alzheimer’s Disease Study participants spanning normal cognition, subjective cognitive decline, mild cognitive impairment, and dementia. Five data-derived dimensions of the Inventory of Depressive Symptomatology–Self-Report (IDS-SR) were jointly examined against function, cognition, plasma biomarkers, florbetapir standardised uptake value ratio, dorsal attention network connectivity, and cognitive status; person-centred analysis identified symptom profiles. There was no formal lived-experience involvement.Outcomes: Five partly separable dimensions and five profiles were identified, capturing symptom patterns beyond overall burden. Psychomotor disturbance had the broadest associations, encompassing all functional and cognitive outcomes, all five plasma biomarkers, and all non-normal cognitive groups; per-SD odds ratios were 1·700 (95% CI 1·436–2·011) for mild cognitive impairment and 2·932 (2·432–3·535) for dementia versus normal cognition. Other dimensions had selective and stage-dependent patterns. No dimension-level amyloid-PET or dorsal attention network association passed false-discovery-rate correction. Profiles were largely ordered by severity, but psychomotor-relative and insomnia-relative low-burden profiles differed in cognition, pTau217, pTau181, glial fibrillary acidic protein, amyloid-PET burden, and dementia odds after adjustment for overall burden. The IDS-SR psychomotor-disturbance subscore (IDS-SR-PM), formed from the four psychomotor-dimension items—concentration or decision making, general interest, capacity for pleasure or enjoyment, and feeling slowed down—retained broad clinical and biomarker associations and showed stronger plasma-biomarker associations than IDS total.Interpretation: Depressive symptom dimensions and within-person configurations revealed distinct clinical and biological patterns beyond overall burden across the cognitive continuum. This framework improves phenotypic resolution across dimensions and profiles. Psychomotor disturbance was the most informative focused phenotype, and the brief IDS-SR-PM is a practical candidate for longitudinal and treatment-response validation.

Background: This study aims to validate the suitability of the Inventory of Depressive Symptomatology Self-Report (IDS-SR) for evaluating mood disorders in older adults with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). Methods: A total of 1670 participants aged ≥ 50 years were included (531 males; mean age 65.79 ± 7.39 years). Construct validity of the IDS-SR was evaluated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Criterion validity was examined using Pearson correlation analyses between IDS-SR scores and scores on the Hamilton Depression Scale (HAMD) and the Hamilton Anxiety Scale (HAMA). Receiver operating characteristic (ROC) curve analysis was conducted to determine the ability of the IDS-SR and its subscales to distinguish mood disorders in SCD and MCI. Cronbach’s α and the intraclass correlation coefficient (ICC) were employed to assess the reliability of the scale. Results: The EFA demonstrated that the major factors explained 47.722% of the total variance. The CFA confirmed a three-factor model of the IDS-SR and indicated good construct validity. The fit indices were as follows: chi-square/degree of freedom ( χ ² / df ) = 3.316, root mean square error of approximation (RMSEA) = 0.054, goodness of fit index (GFI) = 0.945, adjusted goodness-of-fit index (AGFI) = 0.928, comparative fit index (CFI) = 0.921, incremental fit index (IFI) = 0.922, and Tucker-Lewis index (TLI) = 0.908. The total Cronbach’s α was 0.839. The ICC for the total scale was 0.952. Conclusions: The IDS-SR scale is a reliable and valid screening tool for detecting mood disorders in older adults with SCD and MCI. This study provides the first validation of the scale in this population.

The association between cerebral amyloid-β (Aβ) burden and cognitive performance in cognitively normal (CN) older adults remains uncertain. This