MerTK is a mediator of alpha-synuclein fibril uptake by human microglia
Bibliographic record
Abstract
Mer tyrosine kinase (MerTK) is a receptor tyrosine kinase that mediates non-inflammatory, homeostatic phagocytosis of diverse types of cellular debris. Highly expressed on the surface of microglial cells, MerTK is of importance in brain development, homeostasis, plasticity and disease. Yet, involvement of this receptor in the clearance of protein aggregates that accumulate with ageing and in neurodegenerative diseases has yet to be defined. The current study explored the function of MerTK in the microglial uptake of alpha-synuclein fibrils which play a causative role in the pathobiology of synucleinopathies. Using human primary and induced pluripotent stem cell-derived microglia, the MerTK-dependence of alpha-synuclein fibril internalization was investigated in vitro. Relevance of this pathway in synucleinopathies was assessed through burden analysis of MERTK variants and analysis of MerTK expression in patient-derived cells and tissues. Pharmacological inhibition of MerTK and siRNA-mediated MERTK knockdown both caused a decreased rate of alpha-synuclein fibril internalization by human microglia. Consistent with the non-inflammatory nature of MerTK-mediated phagocytosis, alpha-synuclein fibril internalization was not observed to induce secretion of pro-inflammatory cytokines such as IL-6 or TNF, and downmodulated IL-1β secretion from microglia. Burden analysis in two independent patient cohorts revealed a significant association between rare functionally deleterious MERTK variants and Parkinson's disease in one of the cohorts (P = 0.002). Despite a small upregulation in MERTK mRNA expression in nigral microglia from Parkinson's disease/Lewy body dementia patients compared to those from non-neurological control donors in a single-nuclei RNA-sequencing dataset (P = 5.08 × 10-21), no significant upregulation in MerTK protein expression was observed in human cortex and substantia nigra lysates from Lewy body dementia patients compared to controls. Taken together, our findings define a novel role for MerTK in mediating the uptake of alpha-synuclein fibrils by human microglia, with possible involvement in limiting alpha-synuclein spread in synucleinopathies such as Parkinson's disease. Upregulation of this pathway in synucleinopathies could have therapeutic values in enhancing alpha-synuclein fibril clearance in the brain.
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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".