Defects in the IFT-B Component IFT172 Cause Jeune and Mainzer-Saldino Syndromes in Humans
Bibliographic record
Abstract
Intraflagellar transport (IFT) depends on two evolutionarily conserved modules, subcomplexes A (IFT-A) and B (IFT-B), to drive ciliary assembly and maintenance. All six IFT-A components and their motor protein, DYNC2H1, have been linked to human skeletal ciliopathies, including asphyxiating thoracic dystrophy (ATD; also known as Jeune syndrome), Sensenbrenner syndrome, and Mainzer-Saldino syndrome (MZSDS). Conversely, the 14 subunits in the IFT-B module, with the exception of IFT80, have unknown roles in human disease. To identify additional IFT-B components defective in ciliopathies, we independently performed different mutation analyses: candidate-based sequencing of all IFT-B-encoding genes in 1,467 individuals with a nephronophthisis-related ciliopathy or whole-exome resequencing in 63 individuals with ATD. We thereby detected biallelic mutations in the IFT-B-encoding gene IFT172 in 12 families. All affected individuals displayed abnormalities of the thorax and/or long bones, as well as renal, hepatic, or retinal involvement, consistent with the diagnosis of ATD or MZSDS. Additionally, cerebellar aplasia or hypoplasia characteristic of Joubert syndrome was present in 2 out of 12 families. Fibroblasts from affected individuals showed disturbed ciliary composition, suggesting alteration of ciliary transport and signaling. Knockdown of ift172 in zebrafish recapitulated the human phenotype and demonstrated a genetic interaction between ift172 and ift80. In summary, we have identified defects in IFT172 as a cause of complex ATD and MZSDS. Our findings link the group of skeletal ciliopathies to an additional IFT-B component, IFT172, similar to what has been shown for IFT-A.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".