Bi-allelic loss-of-function variants in TMEM147 cause moderate to profound intellectual disability with facial dysmorphism and pseudo-Pelger-Huët anomaly
Bibliographic record
Abstract
The transmembrane protein TMEM147 has a dual function: first at the nuclear envelope, where it anchors lamin B receptor (LBR) to the inner membrane, and second at the endoplasmic reticulum (ER), where it facilitates the translation of nascent polypeptides within the ribosome-bound TMCO1 translocon complex. Through international data sharing, we identified 23 individuals from 15 unrelated families with bi-allelic TMEM147 loss-of-function variants, including splice-site, nonsense, frameshift, and missense variants. These affected children displayed congruent clinical features including coarse facies, developmental delay, intellectual disability, and behavioral problems. In silico structural analyses predicted disruptive consequences of the identified amino acid substitutions on translocon complex assembly and/or function, and in vitro analyses documented accelerated protein degradation via the autophagy-lysosomal-mediated pathway. Furthermore, TMEM147-deficient cells showed CKAP4 (CLIMP-63) and RTN4 (NOGO) upregulation with a concomitant reorientation of the ER, which was also witnessed in primary fibroblast cell culture. LBR mislocalization and nuclear segmentation was observed in primary fibroblast cells. Abnormal nuclear segmentation and chromatin compaction were also observed in approximately 20% of neutrophils, indicating the presence of a pseudo-Pelger-Huët anomaly. Finally, co-expression analysis revealed significant correlation with neurodevelopmental genes in the brain, further supporting a role of TMEM147 in neurodevelopment. Our findings provide clinical, genetic, and functional evidence that bi-allelic loss-of-function variants in TMEM147 cause syndromic intellectual disability due to ER-translocon and nuclear organization dysfunction.
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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 | 0.000 |
| 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) | 0.001 | 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".