Evaluating potential drug targets through human loss-of-function genetic variation
Eric Vallabh Minikel,
Konrad J Karczewski,
Hilary C. Martin,
Beryl B. Cummings,
Richard C. Trembath,
David A van Heel,
Mark J. Daly,
Genome Aggregation Database Production Team,
Genome Aggregation Database Consortium,
Stuart L Schreiber,
Daniel G. MacArthur
Posted 28 Jan 2019
bioRxiv DOI: 10.1101/530881
Posted 28 Jan 2019
Naturally occurring human genetic variants predicted to cause loss of function of protein-coding genes provide an in vivo model of human gene inactivation that complements cell and model organism knockout studies. Here we investigate the application of human loss-of-function variants to assess genes as candidate drug targets, with three key findings. First, even essential genes, where loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous “knockout” humans will await sample sizes ~1,000 times those available at present. Third, automated variant annotation and filtering are powerful, but manual curation remains critical for removing artifacts and making biological inferences, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human “knockout” studies and should guide interpretation of loss-of-function variants in drug development.
- Downloaded 4,054 times
- Download rankings, all-time:
- Site-wide: 993 out of 83,433
- In genomics: 221 out of 5,384
- Year to date:
- Site-wide: 3,038 out of 83,433
- Since beginning of last month:
- Site-wide: 4,063 out of 83,433
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!