Clinical spectrum of <i>KIAA2022</i> pathogenic variants in males: Case report of two boys with <i>KIAA2022</i> pathogenic variants and review of the literature
Bibliographic record
Abstract
KIAA2022 is an X-linked intellectual disability (XLID) syndrome affecting males more severely than females. Few males with KIAA2022 variants and XLID have been reported. We present a clinical report of two unrelated males, with two nonsense KIAA2022 pathogenic variants, with profound intellectual disabilities, limited language development, strikingly similar autistic behavior, delay in motor milestones, and postnatal growth restriction. Patient 1, 19-years-old, has long ears, deeply set eyes with keratoconus, strabismus, a narrow forehead, anteverted nares, café-au-lait spots, macroglossia, thick vermilion of the upper and lower lips, and prognathism. He has gastroesophageal reflux, constipation with delayed rectosigmoid colonic transit time, difficulty regulating temperature, several musculoskeletal issues, and a history of one grand mal seizure. Patient 2, 10-years-old, has mild dysmorphic features, therapy resistant vomiting with diminished motility of the stomach, mild constipation, cortical visual impairment with intermittent strabismus, axial hypotonia, difficulty regulating temperature, and cutaneous mastocytosis. Genetic testing identified KIAA2022 variant c.652C > T(p.Arg218*) in Patient 1, and a novel nonsense de novo variant c.2707G > T(p.Glu903*) in Patient 2. We also summarized features of all reported males with KIAA2022 variants to date. This report not only adds knowledge of a novel pathogenic variant to the KIAA2022 variant database, but also likely extends the spectrum by describing novel dysmorphic features and medical conditions including macroglossia, café-au-lait spots, keratoconus, severe cutaneous mastocytosis, and motility problems of the GI tract, which may help physicians involved in the care of patients with this syndrome. Lastly, we describe the power of social media in bringing families with rare medical conditions together.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".