A human iPSC‐derived neurosphere model to study functional and transcriptomic properties of microglial neuroprotection in AD
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease is characterized by the accumulation of Aβ plaques in the brain, but the pathways leading from early Aβ deposits to eventual neurodegeneration are not fully understood. The specific role of microglia in AD is controversial, with microglial activation to be protective or detrimental depending on disease progression. We developed a 3D human iPSC-derived neurosphere model to better characterize how microglia respond to Aβ pathology. METHOD: Neurospheres were grown from iPSC-derived neuronal progenitor cells and cultured for 60 days. iPSC-derived microglia were added separately to assess their functional impact. Continuous synthetic oligomeric Aβ treatment was used to model amyloidosis. Genetically encoded sensors roGFP1 and GCaMP6f allowed to monitor neuronal oxidative stress and calcium activity, respectively. Single nuclei RNA sequencing (snRNA-seq) was performed to examine transcriptomic differences induced by Aβ and microglia. RESULT: Neurospheres grew to consist of a complex network of healthy mature neurons and astrocytes. The added microglia readily infiltrate the 3D tissue. Chronic Aβ treatment resulted in the formation of plaque-like aggregates and subsequently led to severe oxidative stress and loss of neuronal activity. Microglia were able to prevent these neurotoxic effects in neurospheres that received mild 3 weeks Aβ treatment, but failed to do so after severe 5 weeks treatment. snRNA-seq revealed that, after 3 weeks treatment, microglia induced upregulation of genes linked to oxidative regulation in astrocytes. After 5 week treatment, microglia more noticeably drove the expression of many AD-associated genes, such as APOE, CLU, and FTL, in astrocytes and neurons. Microglia also appear to have enhanced ability for Aβ clearance after treatment with anti-Aβ antibodies. CONCLUSION: We developed a human 3D neurosphere model to study microglial responses to Aβ pathology. In this model, microglia acquire a neuroprotective phenotype which may be enhanced by anti-Aβ antibodies. Microglia are essential for driving the transcriptomic profile linked to AD after severe Aβ treatment. By mimicking critical AD pathological features, this model offers a platform to identify therapeutic targets with translational relevance.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".