CSF sTREM2 is elevated in a subset in GRN-related frontotemporal dementia
Bibliographic record
Abstract
Excessive microglial activation might be a central pathological process in GRN-related frontotemporal dementia (FTD-GRN). We measured soluble triggering receptor expressed on myeloid cells 2 (sTREM2), which is shed from disease-associated microglia following cleavage of TREM2, in cerebrospinal fluid of 34 presymptomatic and 35 symptomatic GRN mutation carriers, 6 presymptomatic and 32 symptomatic C9orf72 mutation carriers and 67 healthy noncarriers by ELISA. Although no group differences in sTREM2 levels were observed (GRN: symptomatic (median 5.2 ng/mL, interquartile range [3.9-9.2]) vs. presymptomatic (4.3 ng/mL [2.6-6.1]) vs. noncarriers (4.2 ng/mL [2.6-5.5]): p = 0.059; C9orf72: symptomatic (4.3 [2.9-7.0]) vs. presymptomatic (3.2 [2.2-4.2]) vs. noncarriers: p = 0.294), high levels were seen in a subset of GRN, but not C9orf72, mutation carriers, which might reflect differential TREM2-related microglial activation. Interestingly, 2 presymptomatic carriers with low sTREM2 levels developed symptoms after 1 year, whereas 2 with high levels became symptomatic after >5 years. While sTREM2 is not a promising diagnostic biomarker for FTD-GRN or FTD-C9orf72, further research might elucidate its potential to monitor microglial activity and predict disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".