Pathogenicity predictions for 71 million human missense variants
An AlphaFold-derived model classified 89% of all 71 million possible human missense variants as likely benign or likely pathogenic, against the roughly 0.1% that carry a clinical classification today.
- Model
- AlphaMissense
- Field
- Medicine
- Date
- 2023-09-19
What was found
AlphaMissense fine-tunes AlphaFold's structural representation on human and primate variant frequency data, so it learns which substitutions natural selection tolerates without being trained on clinical labels. Applied across 19,233 canonical human proteins it scored every possible single amino-acid change, calling 57% likely benign and 32% likely pathogenic. The full catalogue and the model code were released publicly. Published in Science.
Novelty check
Variant-effect predictors are a crowded field (SIFT, PolyPhen-2, EVE, CADD). The contribution is proteome-wide coverage at state-of-the-art benchmark accuracy without training on clinical annotations, which is what makes the predictions usable where no clinical data exists.
Caveats and known objections
These are predictions, not diagnoses, and DeepMind says so: ACMG/AMP guidance treats computational evidence as supporting rather than standalone. Benchmarks have been criticised for circularity, since the model trains on population frequency and is evaluated partly against datasets encoding related signals. Calibration varies by gene, and a "likely pathogenic" call on a variant nobody has seen in a patient remains a hypothesis.
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Entry history (1 event)
- AddedEntered the registry graded Peer reviewed and AI-led.
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Cite this entry
whataifound.org. (2023). Pathogenicity predictions for 71 million human missense variants. whataifound.org: A Registry of AI Scientific and Mathematical Discoveries. https://whataifound.org/finding/2023-09-19-alphamissenseBibTeX
@misc{whataifound-googledeepmind-2023-alphamissense,
title = {Pathogenicity predictions for 71 million human missense variants},
author = {{whataifound.org}},
year = {2023},
howpublished = {whataifound.org: A Registry of AI Scientific and Mathematical Discoveries},
note = {Result by Google DeepMind. Verification: Peer reviewed. Autonomy: AI-led.},
url = {https://whataifound.org/finding/2023-09-19-alphamissense}
}