Differential roles of ApoE isoforms in regulation of inflammatory cytokine expression
Bibliographic record
Abstract
Abstract Background ApoE Ɛ4 has long been known as a top genetic risk factor in the development of late‐onset Alzheimer’s disease (LOAD). More recently the genetic variants of the innate immune receptor TREM2 such as R47H, which confers a similar risk as ApoE4 in LOAD, have been identified as genetic risk factors in the development of many neurodegenerative diseases with dysregulated neuroinflammation. TREM2 is expressed highly on microglia and macrophages and plays key roles in inflammation regulation. Our previous study (Dorey et al. 2017) has shown that ApoE isoforms play differential roles in Aβ‐induced inflammatory response. Atagi et al (2015) identified that ApoE is a ligand for TREM2. Given the physiological relationship between ApoE and TREM2 while also considering the three isoforms of ApoE, it is crucial to investigate and understand the mechanisms underlying the possibility differential ApoE isoform signaling through TREM2 surface receptor. Method THP‐1 (human monocytic leukemia cell line) cells were differentiated into macrophages (M0) using PMA and subsequently polarized to M1 and M2 using IFN‐γ/LPS and IL‐4/IL‐13, respectively. Following differentiation, 3uM of ApoE2, E3, or E4 was added to polarization media. RNA was extracted following 2 day polarization and used for RT‐qPCR in relative gene expression quantification. Result ApoE2 strongly stimulated the expression of anti‐inflammatory cytokines IL‐10 and TARC/CCL17 in M1 and M2 macrophages as compared to control, ApoE3 and ApoE4. While ApoE4 showed a massive reduction in these same transcripts in M0 and M2 macrophages. In contrast, ApoE4 strongly promoted the expression of pro‐inflammatory cytokines IL‐1β and TNF‐α in M0, M1, and M2 macrophages as compared to control, ApoE3 and ApoE2. Conclusion The ability for ApoE2 to promote the expression of anti‐inflammatory cytokines in macrophages, suggests that ApoE2 may play a neuroprotective role; while ApoE4’s ability to promote inflammatory cytokine expression indicates its pro‐inflammatory role. Both ApoE2 and ApoE4 may play their roles via interacting with TREM2.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".