Molecular biomarkers quantified using the Single Molecule Array in Brazilian patients with mild Alzheimer’s disease and mild cognitive impairment
Bibliographic record
Abstract
Abstract Background The clinically diagnosed late‐onset Alzheimer’s disease (AD) cases has the most heterogeneous pathology. The development of more sensitive biomarkers is essential to perform an early diagnosis, especially in the prodromal phase, mild cognitive impairment (MCI). Biomarkers such as glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) have emerged as potential markers of the pathophysiological process of AD. The objective of this study was to evaluate the concentrations of GFAP and NfL in blood serum and CSF of patients with MCI and mild AD in a Brazilian sample, never quantified using the Single Molecule Array technology (Simoa). Method We used samples (blood serum and cerebrospinal fluid (CSF)) from 91 participants to perform molecular analyzes. These participants were recruited in the outpatient service of the UNICAMP Clinic Hospital. All participants underwent blood collection and only the patients, lumbar puncture, to analyze GFAP and NfL levels. All patients had pathophysiological evidence of AD (low Aβ1‐42 concentrations < 540pg/mL) and was considered Tau alteration: p‐Tau > 36.7 pg/mL and t‐Tau > 76.7 pg/mL. Result Statistical analyzes were performed using SPSS software (version 25). We performed a multivariate analysis of covariance (MANCOVA) to compare the biomarkers levels between the groups. To compare CSF levels (Aβ42, t‐Tau, p‐Tau, GFAP and NfL) we used T‐test analyses and to correlate GFAP and NfL with CSF proteins we use partial correlations. We did not find statistical differences between the groups regarding GFAP and NfL levels, but we did find differences between Aβ1‐42 protein between MCI and mild AD (p = 0.003). We also found moderate correlations between t‐Tau, GFAP and NfL CSF levels (r = .625, p = 0.0; r = .508, p = 0.005, respectively), and p‐Tau with GFAP CSF levels (r = .373, p = 0.046). Conclusion GFAP and NfL reflect neuro‐axonal damage and recent studies have demonstrated its effectiveness in tracking disease progression (5). Although we did not find differences between individuals in relation to GFAP and NfL markers, we were able to observe correlations between these markers at the CSF level and the proteins classically related to the pathological process of the disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".