Peripheral inflammatory biomarkers and risk factors of dementia in the Chilean GERO cohort
Bibliographic record
Abstract
Abstract Background Dementia is one of the mean causes of disability in elderly. Peripheral inflammatory biomarkers and ApoE‐ε4 allele have been described as important biological risk factors of dementia in Caucasian population. Currently, there is scarce information about the specific age‐related and predisposition factors to develop dementia in Latino populations. The aim of this study is to investigate these biological risks factors in Chilean elderly with healthy and pathological brain ageing. Method We evaluated and quantified plasma samples obtained from the GERO cohort (114 elderly subjects, >70 years, classified in 51 subjects with subjective cognitive complaint (SCC) and 63 with mild cognitive impairment (MCI)), in addition to 36 healthy brain controls (HBC) and 31 subjects with Alzheimer’s disease dementia (ADD). Genotyping of ApoE gene was analyzed by qPCR. We analyzed inflammatory biomarkers using Luminex technique including IL‐2, IL‐6, IL‐10, TNF‐α, CRP and SAP proteins. All subjects receive a clinical and neuropsychological assessment. Result CRP protein was found significant decrease expression in SCC and ADD groups compared to MCI and HBC (p=0.048). In SAP protein was found a significant decrease in expression in the SSC (p=0.04) and MCI (p=0.0178) groups compared to HBC. It was observed a positive correlation in the SCC, MCI and ADD groups with the IL‐6 and TNFα, and, SAP and CRP. A negative correlation between IL‐2, IL‐6 and IL‐10 cytokines was found with Direct Span Digit test, which assess attentional capacity. Also was identified a negative correlation between SAP protein and the Free and Cued Selective Reminding Test (FCSRT), which assess verbal episodic memory, and IL‐10 cytokine and Montreal Cognitive Assessment (MoCA), which assess global cognition. Finally, a positive correlation was found in CRP protein with Pfeffer Functional Activity Questionnaire. Frequency of the ApoE‐ε4 allele, was significantly higher in ADD (52%) and SCC (27%) patients than controls and MCI (p=1x10‐4). Conclusion The results shown correlations between the different inflammatory proteins and performance in neuropsychological test suggesting that inflammatory biomarkers are associated with pathological brain ageing. The correlations in SCC and MCI are not being reported previously. Additionally, the frequency of ApoE‐ε4 allele in ADD group is higher than worldwide populations.
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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 | 0.000 | 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) | 0.002 | 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".