Academic Journal
Identification of PCSK9-like human gene knockouts using metabolomics, proteomics, and whole-genome sequencing in a consanguineous population
| Title: | Identification of PCSK9-like human gene knockouts using metabolomics, proteomics, and whole-genome sequencing in a consanguineous population |
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| Authors: | Aziz Belkadi, Gaurav Thareja, Fatemeh Abbaszadeh, Ramin Badii, Eric Fauman, Omar M.E. Albagha, Karsten Suhre |
| Source: | Cell Genomics, Vol 3, Iss 1, Pp 100218- (2023) |
| Publisher Information: | Elsevier, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Genetics LCC:Internal medicine |
| Subject Terms: | human gene knockouts, metabolomics, proteomics, whole-genome sequencing, consanguineous population, drug target validation, drug target identification, Genetics, QH426-470, Internal medicine, RC31-1245 |
| More Details: | Summary: Natural human knockouts of genes associated with desirable outcomes, such as PCSK9 with low levels of LDL-cholesterol, can lead to the discovery of new drug targets and treatments. Rare loss-of-function variants are more likely to be found in the homozygous state in consanguineous populations, and deep molecular phenotyping of blood samples from homozygous carriers can help to discriminate between silent and functional variants. Here, we combined whole-genome sequencing with proteomics and metabolomics for 2,935 individuals from the Qatar Biobank (QBB) to evaluate the power of this approach for finding genes of clinical and pharmaceutical interest. As proof-of-concept, we identified a homozygous carrier of a very rare PCSK9 variant with extremely low circulating PCSK9 levels and low LDL. Our study demonstrates that the chances of finding such variants are about 168 times higher in QBB compared with GnomAD and emphasizes the potential of consanguineous populations for drug discovery. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2666-979X |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2666979X22001719; https://doaj.org/toc/2666-979X |
| DOI: | 10.1016/j.xgen.2022.100218 |
| Access URL: | https://doaj.org/article/e1770f153d584d008d88b05b5bb7250b |
| Accession Number: | edsdoj.1770f153d584d008d88b05b5bb7250b |
| Database: | Directory of Open Access Journals |
| ISSN: | 2666979X |
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| DOI: | 10.1016/j.xgen.2022.100218 |
| Published in: | Cell Genomics |
| Language: | English |