A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase
Bibliographic record
Abstract
Abstract Success in precision medicine depends on our ability to determine which rare human genetic variants have functional effects. Classical homocystinuria—characterized by elevated homocyst(e)ine in plasma and urine—is caused by primarily-rare variants in the cystathionine beta-synthase ( CBS ) gene. About half of patients respond to vitamin B 6 therapy. With early detection in newborns, existing therapies are highly effective. Functional CBS variants, especially those that respond to vitamin B 6 , can be detected based on their ability to restore growth in yeast cells lacking CYS4 ( the yeast ortholog of CBS ). This assay has previously been carried out only ‘reactively’ after first observation of a variant in patients. Here we describe a ‘proactive’ comprehensive missense variant effect map for human CBS. Together, saturation codon-replacement mutagenesis, en masse growth selection at different vitamin B 6 levels, and sequencing yielded a ‘look-up table’ for CBS missense variant function and vitamin B 6 -remediability in yeast. The CBS variant effect map identified disease variants and predicted both disease severity ( r = 0.82) and human clinical response to vitamin B 6 ( r = 0.89). Thus, highly-multiplexed cell-based assays can yield proactive maps of variant function and patient response to therapy, even for rare variants not previously seen in the clinic.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".