Plasma levels of phosphorylated tau and neurofilament light chain as potential biomarkers for Alzheimer’s disease: A biochemical analysis in Pakistani population
Bibliographic record
Abstract
The National Institute on Aging-Alzheimer's Association's research framework in 2018 proposed a molecular construct for the diagnosis of Alzheimer’s disease (AD). Nonetheless, the clinical exclusionary strategy is still the mainstay of AD diagnosis in Pakistan. We looked at the plasma levels of amyloid beta-42 (Aβ-42), phosphorylated tau (P-tau), and neurofilament light (NFL) in patients with Alzheimer's clinical syndrome (ACS) and healthy controls (HC) from the Pakistani population to keep pace with the global efforts towards establishing accessible and affordable biochemical diagnostic markers for AD in Pakistan. Consultant neurologists screened patients who presented with cognitive impairment to three large tertiary care hospitals in Karachi, and after receiving informed consent, recruited participants with ACS and HC from the same facilities. We collected 5cc of blood in EDTA tubes along with demographic and lifestyle information of the subjects. Plasma aliquots were stored at −80°C after centrifugation. For analysis it was thawed at 4℃ and levels of the three proteins were measured through ELISA. Data from 28 ACS patients and 28 age matched healthy controls were evaluated. Among demographic factors, education and depression were related with health status (p = 0.03 and 0.003, respectively). NFL and P-tau mean values demonstrated a significant difference between the ACS and control groups (p = 0.003 and 0.006), however Aβ42 did not (p = 0.114). ROC analysis showed that plasma P-tau and NFL, with AUCs of 0.717 and 0.735, respectively, could substantially distinguish ACS from the HC group (p = 0.007 and 0.003, respectively). Both plasma P-tau (r = −0.389; p = 0.004) and NFL (r = −0.424; p = 0.001) levels were significantly and negatively correlated with individuals' MMSE scores. NFL and plasma P-tau show promise in differentiating AD patients from healthy individuals. However, similar larger studies are needed to validate our findings.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".