Inherited glycophosphatidylinositol deficiency variant database and analysis of pathogenic variants
Bibliographic record
Abstract
BACKGROUND: Glycophosphatidylinositol-anchored proteins (GPI-APs) mediate several physiological processes such as embryogenesis and neurogenesis. Germline variants in genes involved in their synthesis can disrupt normal development and result in a variety of clinical phenotypes. With the advent of new sequencing technologies, more cases are identified, leading to a rapidly growing number of reported genetic variants. With this number expected to rise with increased accessibility to molecular tests, an accurate and up-to-date database is needed to keep track of the information and help interpret results. METHODS: We therefore developed an online resource (www.gpibiosynthesis.org) which compiles all published pathogenic variants in GPI biosynthesis genes which are deposited in the LOVD database. It contains 276 individuals and 192 unique public variants; 92% of which are predicted as damaging by bioinformatics tools. RESULTS: A significant proportion of recorded variants was substitution variants (81%) and resulted mainly in missense and frameshift alterations. Interestingly, five patients (2%) had deleterious mutations in untranslated regions. CADD score analysis placed 97% of variants in the top 1% of deleterious variants in the human genome. In genome aggregation database, the gene with the highest frequency of reported pathogenic variants is PIGL, with a carrier rate of 1/937. CONCLUSION: We thus present the GPI biosynthesis database and review the molecular genetics of published variants in GPI-anchor biosynthesis genes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".