Pathogenic variants in MAEA disrupt DNA replication fork stability and are associated with developmental abnormalities in humans
Bibliographic record
Abstract
Replication stress (RS) poses a threat to genome stability and drives genomic rearrangements. The homologous recombination (HR) pathway repairs stalled replication forks (RFs) and prevents such instability. Through an E3 ubiquitin ligase screen aimed at identifying regulators of RAD51, we identified macrophage erythroblast attacher (MAEA), a core component of C-terminal to Lish (CTLH) E3 ubiquitin ligase complex, as a regulator of the HR pathway. Loss of MAEA impairs RAD51 recruitment at stalled RFs, leading to increased sensitivity to RS-inducing agents and excessive degradation of nascent DNA strands. Mechanistically, MAEA associates with and mediates the ubiquitylation of Ku80, enabling its removal from RF ends and facilitating the loading of RAD51. Notably, MAEA deficiency is associated with a developmental disorder involving microcephaly, craniofacial abnormalities, ocular defects, and heart malformations. Functional assays show that disease-linked MAEA variants (R34C, E349G, Y394D, and M396R) are defective in RS response. These findings establish MAEA as an essential factor in RF protection and genome integrity.
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".