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Proteome-wide association study using cis and trans variants and applied to blood cell and lipid-related traits in the Women's Health Initiative study.
Chen, Brian D; Lee, Chanhwa; Tapia, Amanda L; Reiner, Alexander P; Tang, Hua; Kooperberg, Charles; Manson, JoAnn E; Li, Yun; Raffield, Laura M.
Afiliación
  • Chen BD; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Lee C; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Tapia AL; Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Reiner AP; Department of Epidemiology, University of Washington, Seattle, Washington, USA.
  • Tang H; Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.
  • Kooperberg C; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, Washington, USA.
  • Manson JE; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
  • Li Y; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Raffield LM; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Genet Epidemiol ; 2024 Jun 28.
Article en En | MEDLINE | ID: mdl-38940271
ABSTRACT
In most Proteome-Wide Association Studies (PWAS), variants near the protein-coding gene (±1 Mb), also known as cis single nucleotide polymorphisms (SNPs), are used to predict protein levels, which are then tested for association with phenotypes. However, proteins can be regulated through variants outside of the cis region. An intermediate GWAS step to identify protein quantitative trait loci (pQTL) allows for the inclusion of trans SNPs outside the cis region in protein-level prediction models. Here, we assess the prediction of 540 proteins in 1002 individuals from the Women's Health Initiative (WHI), split equally into a GWAS set, an elastic net training set, and a testing set. We compared the testing r2 between measured and predicted protein levels using this proposed approach, to the testing r2 using only cis SNPs. The two methods usually resulted in similar testing r2, but some proteins showed a significant increase in testing r2 with our method. For example, for cartilage acidic protein 1, the testing r2 increased from 0.101 to 0.351. We also demonstrate reproducible findings for predicted protein association with lipid and blood cell traits in WHI participants without proteomics data and in UK Biobank utilizing our PWAS weights.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Genet Epidemiol Asunto de la revista: EPIDEMIOLOGIA / GENETICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Genet Epidemiol Asunto de la revista: EPIDEMIOLOGIA / GENETICA MEDICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos