Developing a mass spectrometric assay to measure granulin peptides in CSF for progranulin‐associated frontotemporal dementia
Bibliographic record
Abstract
Abstract Background Pathogenic mutations in the progranulin gene (GRN) are a key cause of frontotemporal dementia (FTD), inducing a reduced biofluid concentration of the progranulin protein (PGRN). PGRN is a cysteine‐rich glycoprotein with essential roles in inflammation and lysosomal function, made up of 7 granulin peptides and 1 paragranulin. The role of these peptides is unclear, but existing data suggests they may have contradictory roles to full‐length PGRN. With the development of numerous clinical trials aiming to treat progranulin‐associated FTD (FTD‐GRN) by increasing full‐length PGRN, it is important to establish effective outcome measures to assess treatment success and further our understanding of PGRN’s biology. Here, we aimed to develop an assay to quantify granulin peptides in cerebrospinal fluid (CSF) and determine whether they contribute to the pathology of FTD‐GRN. Method Based on previously published explorative data of endogenous CSF peptides, 12 peptides spanning the progranulin sequence, were selected for the development of targeted assays using a quadrupole Orbitrap hybrid mass spectrometer (Fusion Tribrid, Thermo). An analytical protocol was optimised involving reduction, alkylation, molecular weight cut‐off filtration and solid phase extraction, and using isotope labelled heavy standards for quantification. Additionally, tandem mass tag (TMT) proteomics was used to analyse tryptic peptides spanning granulin and paragranulin sequence regions in 248 CSF samples from the Genetic FTD initiative (GENFI) including 56 GRN mutation carriers and 76 mutation‐negative controls. Result Preliminary results reveal the presence of three endogenous peptides in CSF, which based on sequence matching, likely represent granulin 6 and 7 alongside the paragranulin peptide. TMT results showed significantly reduced relative peptide intensity across the granulin regions in GRN carriers CSF compared to controls (p<0.0001), but no significant difference in the paragranulin region (p>0.33). Conclusion These findings indicate that two granulins and paragranulin are quantifiable in CSF and may have key roles in progranulin biology and potentially FTD pathology. This is supported by TMT results of differential CSF paragranulin levels compared to granulins. Continuing work will quantify CSF granulin concentrations in the GENFI cohort to assess whether these peptides have key roles in FTD‐GRN’s underlying biology and as potential outcome measures in trials.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".