Investigating Salivary Extracellular Vesicles as Biomarkers for Alzheimer's Disease: ExosomeAD Study Design and Baseline Characteristics
Bibliographic record
Abstract
Abstract Background Brain‐derived salivary extracellular vesicles (EVs) contain mRNA, miRNA, and protein species which have the potential to be used for molecular characterization of brain health. Prior analysis of salivary EV mRNA identified Alzheimer's disease (AD)‐ and inflammation‐related biomarkers that may be diagnostically useful in this regard, however EV analysis is still in its infancy. The primary objective of this study is to identify a novel biomarker signature for AD using salivary EVs. Method ExosomeAD is a 60‐month longitudinal cohort study enrolling older adults with normal cognition (CN; n = 150) and mild cognitive impairment (MCI; n = 50) at the Rhode Island Hospital Alzheimer's Disease and Memory Disorders Center. Baseline evaluation includes neuropsychological testing, self‐report inventories (mood, subjective cognitive impairment, daily functioning), vital signs, and collection of saliva and blood samples. Salivary EVs are being analyzed for mRNA, miRNA, and protein composition and compared with plasma biomarkers of AD risk assessed by PrecivityAD (C2N Diagnostics) testing (plasma Aß42‐40 ratio, APOE proteotype, and the Amyloid Probability Score (APS)). Participants complete up to 4 annual follow up visits (cognitive testing, surveys, and saliva/blood sample collection). Result Currently, 183 participants (CN=163; MCI=20) have been enrolled. Participants in both groups to‐date are predominately female (CN, n = 115 (71%); MCI, n = 13 (65%). On average, participants with MCI (M age =77.7, standard deviation (SD)=5.6) are older than the CN group (M age =72.1 (5.1)). The group mean Montreal Cognitive Assessment total score in the current sample is lower among those with MCI (M=20.1 (4.1)) vs CN (M=27 (2.2)). MCI participants are more likely to be APOE4 carriers (71.4% vs CN, 31.1%), and have higher median APS (MCI APS =81.5; CN APS =17). More than half of participants endorsed family history positive for dementia (CN=60%; MCI=65%). Conclusion Salivary EVs contain important information about brain health and may be a useful biomarker for AD. However, AD‐specific signatures in EVs have not yet been characterized. If successful, the Exosome Study will be first to demonstrate that salivary EV RNA and protein can be used to detect AD and facilitate the development of an inexpensive and noninvasive screening method for use in specialty and primary care settings.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".