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Evaluating drug targets through human loss-of-function genetic variation

Vallabh Minikel, Eric and MacArthur, Daniel G (2020) In Nature 581. p.459-464
Abstract
Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which 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 that are approximately 1,000 times those presently available, unless recruitment... (More)
Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which 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 that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development. (Less)
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author
and
contributor
LU ; Haiman, Christopher ; LU and LU
author collaboration
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
automation, cell, drug, genetic variation, genotype
in
Nature
volume
581
pages
6 pages
publisher
Nature Publishing Group
external identifiers
  • scopus:85085564434
  • pmid:32461653
ISSN
0028-0836
DOI
10.1038/s41586-020-2267-z
language
English
LU publication?
yes
id
b6b6e8e1-e1ce-47be-ba79-abe72c95af87
date added to LUP
2020-06-16 09:49:23
date last changed
2020-09-23 08:11:58
@article{b6b6e8e1-e1ce-47be-ba79-abe72c95af87,
  abstract     = {Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which 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 that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development. },
  author       = {Vallabh Minikel, Eric  and MacArthur, Daniel G},
  issn         = {0028-0836},
  language     = {eng},
  month        = {05},
  pages        = {459--464},
  publisher    = {Nature Publishing Group},
  series       = {Nature},
  title        = {Evaluating drug targets through human loss-of-function genetic variation},
  url          = {http://dx.doi.org/10.1038/s41586-020-2267-z},
  doi          = {10.1038/s41586-020-2267-z},
  volume       = {581},
  year         = {2020},
}