Levels of plasma ADAM10 and cognitive performance in older adults with and without Alzheimer’s dementia from a middle‐income country
Bibliographic record
Abstract
Abstract Background Alzheimer’s Disease (AD) is the most prevalent dementia, and its underdiagnosis rates are still challenging, especially in low and middle‐income countries (LMIC) (Pelegrini et al., 2019). Research suggests the potential benefits of blood‐based biomarkers for accurate diagnosis, and ADAM10 is an example (Oliveira et al., 2020). However, more evidence from LMIC, such as Brazil and other Latin American countries, is necessary (Parra et al., 2022). Aim To compare the plasma ADAM10 levels and cognitive performance between healthy older adults and individuals with AD in a Latin American country. Methods This is a cross‐sectional study in which healthy older adults (n = 31) and participants with AD (n = 51) had their cognitive performance assessed through MMSE. In addition, a blood sample was collected, and the plasma ADAM10 levels were obtained through SDS‐PAGE and Western‐Blotting analyses. Comparison of means, correlation, and binomial logistic regression analyses were conducted at a significance level of p<0.05. Results Most participants were female (61%), whose average age was 76.1 (8.3). The mean years of education and MMSE scores were, respectively, 4.6 (4.1) and 18.8 (8.2). The AD group was older (U = 363.5; p<0.001); had a lower score on MMSE (U = 129; p<0.001), and had higher plasma ADAM10 levels (U = 429; p = 0.001). Correlation analysis revealed a relationship between MMSE score and ADAM10 levels (r = ‐0.225; p = 0.04); age and cognitive performance (r = ‐0.353; p = 0.001); as well as between age and ADAM10 levels (r = 0.324; p = 0.004). Finally, our results suggested that those individuals with higher plasma ADAM10 levels have approximately eleven times more chances of being diagnosed with AD (B = 2.36; S.E. = 0.74; p = 0.001; Exp(B) = 10.63; 95%CI [2.48 – 45.69]). Conclusion This study showed that levels of ADAM10 are different between healthy older adults and individuals with AD. Specifically, participants with AD have higher plasma ADAM10 levels. Also, low MMSE scores were correlated with higher ADAM10 plasma levels. Finally, people with higher plasma ADAM10 levels have more chances of being diagnosed with AD.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".