Functional analysis of mutations in the ATP loop of the Wilson disease copper transporter, ATP7B
Bibliographic record
Abstract
Wilson disease (WND) is an autosomal recessive disorder resulting from mutation of ATP7B. Transport of copper by ATP7B from the trans-Golgi of hepatocytes into apical membrane-trafficked vesicles for excretion in the bile is the major means of copper elimination from the body. Although copper is an essential nutrient, homeostasis must be carefully maintained. If homeostasis is disrupted, copper can accumulate within the liver, kidney, cornea, and/or brain. The range of organs affected leads to clinical heterogeneity and difficulty in WND diagnosis. Sequencing of ATP7B is an important adjunct for diagnosis but has led to the discovery of many novel missense variants. Although prediction programs are available, functional characterization is essential for determining the consequence of novel variants. We have tested 12 missense variants localized to the ATP loop of ATP7B and compared three predictive programs (SIFT, PolyPhen, and Align-GVGD). We found p.L1043P, p.G1000R, p.G1101R, p.I1102T, p.V1239G, and p.D1267V deleterious; p.G1176E and p.G1287S intermediate; p.E1173G temperature sensitive; p.T991M and p.I1148T mild; and p.R1228T functioning as wild type. We found that SIFT most often agreed with functional data (92%), compared with PolyPhen (83%) and Align-GVGD (67%). We conclude that variants found to negatively affect function likely contribute to the WND phenotype in patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.001 | 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".