Woodhouse-Sakati syndrome: genotype–phenotype review and case of intra-familial heterogeneity
Bibliographic record
Abstract
Abstract Woodhouse-Sakati syndrome (WSS) is a rare eponymous disease described by Drs. Woodhouse and Sakati in 1983 as a syndrome of hypogonadism, alopecia, diabetes mellitus, intellectual disability, and ECG abnormalities. A couple of years later, a variant in the gene DCAF17 (DDB1 and CUL4-associated factor 17) was labeled as the founder mutation in most cases of WSS in the Arabian Peninsula and the Middle East. Reports around the world started to emerge on variable presentations of the syndrome, expanding its phenotypic spectrum. In addition, the discovery of new variants in the same gene grew our understanding of this multi-systemic syndrome. Genotype and phenotype expansion is increasing with the growing number of diagnosed cases owing to the availability and advances in clinical genetic testing. This review describes the current understanding of the DCAF17 gene with its molecular implication in WSS. We also provide an extensive analysis of the documented genetic changes associated with the syndrome, describing the geographical prevalence of these genetic variations. Additionally, we examine the disorder’s extensive manifestations and clinical presentations and describe a case of intra-familial phenotypic heterogeneity.
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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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".