De novo missense variants in <i>LMBRD2</i> are associated with developmental and motor delays, brain structure abnormalities and dysmorphic features
Bibliographic record
Abstract
Objective To determine the potential disease association between variants in LMBRD2 and complex multisystem neurological and developmental delay phenotypes. Methods Here we describe a series of de novo missense variants in LMBRD2 in 10 unrelated individuals with overlapping features. Exome sequencing or genome sequencing was performed on all individuals, and the cohort was assembled through GeneMatcher. Results LMBRD2 encodes an evolutionary ancient and widely expressed transmembrane protein with no known disease association, although two paralogues are involved in developmental and metabolic disorders. Exome or genome sequencing revealed rare de novo LMBRD2 missense variants in 10 individuals with developmental delay, intellectual disability, thin corpus callosum, microcephaly and seizures. We identified five unique variants and two recurrent variants, c.1448G>A (p.Arg483His) in three cases and c.367T>C (p.Trp123Arg) in two cases. All variants are absent from population allele frequency databases, and most are predicted to be deleterious by multiple in silico damage-prediction algorithms. Conclusion These findings indicate that rare de novo variants in LMBRD2 can lead to a previously unrecognised early-onset neurodevelopmental disorder. Further investigation of individuals harbouring LMBRD2 variants may lead to a better understanding of the function of this ubiquitously expressed gene.
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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) | 0.003 | 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".