Your browser doesn't support javascript.
loading
Identification of PCSK9-like human gene knockouts using metabolomics, proteomics, and whole-genome sequencing in a consanguineous population.
Belkadi, Aziz; Thareja, Gaurav; Abbaszadeh, Fatemeh; Badii, Ramin; Fauman, Eric; Albagha, Omar M E; Suhre, Karsten.
Afiliação
  • Belkadi A; Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha 24144, Qatar.
  • Thareja G; Department of Biophysics and Physiology, Weill Cornell Medicine, New York, NY, USA.
  • Abbaszadeh F; Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, Doha 24144, Qatar.
  • Badii R; Department of Biophysics and Physiology, Weill Cornell Medicine, New York, NY, USA.
  • Fauman E; Hamada Medical Corporation, Doha, Qatar.
  • Albagha OME; Hamada Medical Corporation, Doha, Qatar.
  • Suhre K; College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar.
Cell Genom ; 3(1): 100218, 2023 Jan 11.
Article em En | MEDLINE | ID: mdl-36777185
ABSTRACT
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.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article