Molecular and clinical analysis of <i>ALPL</i> in a cohort of patients with suspicion of Hypophosphatasia
Bibliographic record
Abstract
Hypophosphatasia (HPP) is a rare autosomal dominant or recessive metabolic disorder caused by mutations in the tissue nonspecific alkaline phosphatase gene (ALPL). To date, over 300 different mutations in ALPL have been identified. Disease severity is widely variable with severe forms usually manifesting during perinatal and/or infantile periods while mild forms are sometimes only diagnosed in adulthood or remain undiagnosed. Common clinical features of HPP are defects in bone and tooth mineralization along with the biochemical hallmark of decreased serum alkaline phosphatase activity. The incidence of severe HPP is approximately 1 in 300,000 in Europe and 1 in 100,000 in Canada. We present the clinical and molecular findings of 83 probands and 28 family members, referred for genetic analysis due to a clinical and biochemical suspicion of HPP. Patient referrals included those with isolated low alkaline phosphatase levels and without any additional clinical features, to those with a severe skeletal dysplasia. Thirty-six (43.3%) probands were found to have pathogenic ALPL mutations. Eleven previously unreported mutations were identified, thus adding to the ever increasing list of ALPL mutations. Seven of these eleven were inherited in an autosomal dominant manner while the remaining four were observed in the homozygous state. Thus, this study includes a large number of well-characterized patients with hypophosphatasemia which has permitted us to study the genotype:phenotype correlation. Accurate diagnosis of patients with a clinical suspicion of HPP is crucial as not only is the disease life-threatening but the patients may be offered bone targeted enzymatic replacement therapy. © 2017 Wiley Periodicals, Inc.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".