Emerging blood exosome-based biomarkers for preclinical and clinical Alzheimer’s disease: a meta-analysis and systematic review
Bibliographic record
Abstract
Blood exosomes, which are extracellular vesicles secreted by living cells into the circulating blood, are regarded as a relatively noninvasive novel tool for monitoring brain physiology and disease states. An increasing number of blood cargo-loaded exosomes are emerging as potential biomarkers for preclinical and clinical Alzheimer’s disease. Therefore, we conducted a meta-analysis and systematic review of molecular biomarkers derived from blood exosomes to comprehensively analyze their diagnostic performance in preclinical Alzheimer’s disease, mild cognitive impairment, and Alzheimer’s disease. We performed a literature search in PubMed, Web of Science, Embase, and Cochrane Library from their inception to August 15, 2020. The research subjects mainly included Alzheimer’s disease, mild cognitive impairment, and preclinical Alzheimer’s disease. We identified 34 observational studies, of which 15 were included in the quantitative analysis (Newcastle-Ottawa Scale score 5.87 points) and 19 were used in the qualitative analysis. The meta-analysis results showed that core biomarkers including Aβ1–42, P-T181-tau, P-S396-tau, and T-tau were increased in blood neuron-derived exosomes of preclinical Alzheimer’s disease, mild cognitive impairment, and Alzheimer’s disease patients. Molecules related to additional risk factors that are involved in neuroinflammation (C1q), metabolism disorder (P-S312-IRS-1), neurotrophic deficiency (HGF), vascular injury (VEGF-D), and autophagy-lysosomal system dysfunction (cathepsin D) were also increased. At the gene level, the differential expression of transcription-related factors (REST) and microRNAs (miR-132) also affects RNA splicing, transport, and translation. These pathological changes contribute to neural loss and synaptic dysfunction. The data confirm that the above-mentioned core molecules and additional risk-related factors in blood exosomes can serve as candidate biomarkers for preclinical and clinical Alzheimer’s disease. These findings support further development of exosome biomarkers for a clinical blood test for Alzheimer’s disease. This meta-analysis was registered at the International Prospective Register of Systematic Reviews (Registration No. CRD4200173498, 28/04/2020).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".