Neurodegenerative fluid biomarkers are enriched in human cervical lymph nodes
Bibliographic record
Abstract
In animal models, brain neurodegeneration biomarkers drain into cervical lymph nodes (CLNs), and this drainage function is reduced with ageing. If this occurred in humans, CLNs may provide a readily accessible measure of this aspect of protein clearance. We tested this hypothesis in people using ultrasound-guided fine needle aspiration. We measured amyloid-beta 40 and 42, phosphorylated tau 181 (pTau181), glial fibrillary acidic protein and neurofilament light using single molecule array in CLN aspirates and plasma from: (i) a discovery cohort of 25 autoimmune patients; and (ii) plasma, CLNs and capillary blood in four healthy volunteers, an optimization cohort. Ultrasound-guided fine needle aspiration was well-tolerated by all participants. In both cohorts, all biomarkers were detected in all plasma and CLN samples, other than neurofilament light (8/17 of discovery cohort). CLN biomarker concentrations were significantly greater than plasma concentrations for all except neurofilament light, most markedly for pTau181 (266-fold; P < 0.02), whose CLN concentrations decreased with age (Spearman r = -0.66, P = 0.001). This study presents the first evidence that neurodegenerative biomarkers are detectable in human CLNs. Raised CLN:plasma biomarker ratios suggest their concentration in CLNs may offer a distinct compartment for minimally-invasive measurement of brain clearance and lymphatic drainage, with potential applicability to study of ageing and future clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".