FLNA-filaminopathy skeletal phenotypes are not due to an osteoblast autonomous loss-of-function
Bibliographic record
Abstract
Mutations in FLNA, which encodes the cytoskeletal protein FLNA, cause a spectrum of sclerosing skeletal dysplasias. Although many of these genetic variants are recurrent and cluster within the gene, the pathogenic mechanism that underpins the development of these skeletal phenotypes is unknown. To determine if the skeletal dysplasia in FLNA-related conditions is due to a cell-autonomous loss-of-function localising to osteoblasts and/or osteocytes, we utilised mouse models to conditionally remove Flna from this cellular lineage. Flna was conditionally knocked out from mature osteocytes using the Dmp1-promoter driven Cre-recombinase expressing mouse, as well as the committed osteoblast lineage using the Osx-Cre or Col1a1-Cre expressing lines. We measured skeletal parameters with μCT and histological methods, as well as gene expression in the mineralised skeleton. We found no measureable differences between the conditional Flna knockout mice, and their control littermate counterparts. Moreover, all of the conditional Flna knockout mice, developed and aged normally. From this we concluded that the skeletal dysplasia phenotype associated with pathogenic variants in FLNA is not caused by a cell-autonomous loss-of-function in the osteoblast-osteocyte lineage, adding more evidence to the hypothesis that these phenotypes are due to gain-of-function in FLNA.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".