Expanding Clinical Presentations Due to Variations in THOC2 mRNA Nuclear Export Factor
Bibliographic record
Abstract
Multiple TREX mRNA export complex subunits (e.g., THOC1, THOC5, THOC7, THOC6) have now been implicated in neurodevelopmental disorders (NDDs), neurodegeneration and cancer. We previously implicated missense and splicing-defective THOC2 variants in NDDs and a broad range of other clinical features. Here we report 10 individuals from 9 families with rare missense THOC2 variants including the first case of a recurrent variant (p.Arg77Cys), and an additional individual with an intragenic THOC2 microdeletion (Del-Ex37-38). Ex vivo missense variant testing and patient-derived cell line data from current and published studies show 9 of the 14 missense THOC2 variants result in reduced protein stability. The splicing-defective and deletion variants result in a loss of small regions of the C-terminal THOC2 RNA binding domain. Interestingly, reduced stability of THOC2 variant proteins has a flow on effect on the stability of the multiprotein TREX complex and specifically the other NDD-associated THOC subunits. Our current, expanded cohort refines the core phenotype of THOC2 NDDs to language disorder and/or ID, with a variable severity, and disorders of growth. A subset of affected individuals' have severe-profound ID, persistent hypotonia and respiratory abnormalities. Further investigations to elucidate the pathophysiological basis for this severe phenotype are warranted.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".