Family mapping of previously identified patients with pathogenic or likely pathogenic ALPL variants using predictive genotyping and detailed phenotyping approach: the FAME case-control study
Bibliographic record
Abstract
Hypophosphatasia (HPP) is an inborn error of metabolism caused by loss-of-function variants in the ALPL gene, which encodes the tissue nonspecific isozyme of alkaline phosphatase (ALP). There is no typical phenotype in adults. We used a genotyping first approach to determine whether ALPL pathogenic variants were associated with musculoskeletal symptoms, mineral metabolism abnormalities, and an impact on quality of life. We recruited individuals with a pathogenic (or likely pathogenic) variant in ALPL gene (n = 26) and their relatives (n = 44). We performed genetic tests and compared the relatives with positive (n = 20) and negative (n = 24) genetic test. We applied standard questionnaires and physical tests (Brief Pain Inventory [BPI]; Western Ontario and McMaster Universities Arthritis [WOMAC]; Modified Hypophosphatasia Impact Patient Survey; Short Form of 36 Survey [SF-36]; and the Short Physical Performance Battery). In fasting blood samples, we measured creatinine, calcium, phosphate (P), parathyroid hormone (PTH), ALP, bone ALP, 25OHD-, 1,25(OH)2D, CTX, type 1 procollagen N-terminal peptide (PINP), osteocalcin, and tartrate-resistant acid phosphatase5b (TRACP5b). Relatives with positive genetic test had lower ALP (IU/L) [32.5(12.8) vs 87.8(32.6) p < .001], bone ALP (ng/mL) [6.3(4.3, 9.8) vs 17.5 (13.12-25.7) p < .001], PTH (pg/L) [28.6(20.6, 38.1) vs 40.05(25.7, 52.3) p = .03], and higher PLP(nmol/L) [162.0 (91.75, 337.5) vs 37.5 (18.25, 60.5) p < .001] and P(mmol/L) [1.36 (0.18) vs 1.05 (0.2) p < .001]. We did not find significant differences in fractures or musculoskeletal features between the groups. Greater pain scores were observed on BPI in relatives with positive genetic tests, and bone and muscle pain were more often reported by this group, but statistical tests were not significant. No differences were found in physical performance or quality of life. In conclusion, we assessed relatives of individuals with pathogenic or likely pathogenic variants in the ALPL gene regardless of the presence of signs and symptoms. Biochemical abnormalities were more common in gene-positive relatives, but the prevalence of musculoskeletal symptoms was comparable in relatives with positive and negative genetic tests.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".