RNA sequencing reveals MMP2 and TGFB1 downregulation in LRRK2 G2019S Parkinson's iPSC-derived astrocytes
Bibliographic record
Abstract
Non-neuronal cell types such as astrocytes can contribute to Parkinson's disease (PD) pathology. The G2019S mutation in leucine-rich repeat kinase 2 (LRRK2) is one of the most common known causes of familial PD. To characterize its effect on astrocytes, we developed a protocol to produce midbrain-patterned astrocytes from human induced pluripotent stem cells (iPSCs) derived from PD LRRK2 G2019S patients and healthy controls. RNA sequencing analysis revealed the downregulation of genes involved in the extracellular matrix in PD cases. In particular, transforming growth factor beta 1 (TGFB1), which has been shown to inhibit microglial inflammatory response in a rat model of PD, and matrix metallopeptidase 2 (MMP2), which has been shown to degrade α-synuclein aggregates, were found to be down-regulated in LRRK2 G2019S astrocytes. Our findings suggest that midbrain astrocytes carrying the LRRK2 G2019S mutation may have reduced neuroprotective capacity and may contribute to the development of PD pathology.
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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".