Royal College of Surgeons in Ireland
Browse
Pharmacogenetic meta-analysis of genome-wide association studies.pdf (667.16 kB)

Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins.

Download (667.16 kB)
Version 2 2021-12-21, 12:20
Version 1 2019-11-22, 16:24
journal contribution
posted on 2019-11-22, 16:24 authored by Iris Postmus, Stella Trompet, Harshal A Deshmukh, Michael R Barnes, Xiaohui Li, Helen R Warren, Daniel I Chasman, Kaixin Zhou, Benoit J Arsenault, Louise A Donnelly, Kerri L Wiggins, Christy L Avery, Paula Griffin, QiPing Feng, Kent D Taylor, Guo Li, Daniel S Evans, Albert V Smith, Catherine E de Keyser, Andrew D Johnson, Anton J M de Craen, David J Stott, Brendan M Buckley, Ian Ford, Rudi G J Westendorp, P Eline Slagboom, Naveed Sattar, Patricia B Munroe, Peter Sever, Neil Poulter, Alice Stanton, Denis C Shields, Eoin O'Brien, Sue Shaw-Hawkins, Y-D Ida Chen, Deborah A Nickerson, Joshua D Smith, Marie Pierre Dubé, S Matthijs Boekholdt, G Kees Hovingh, John J P Kastelein, Paul M McKeigue, John Betteridge, Andrew Neil, Paul N Durrington, Alex Doney, Fiona Carr, Andrew Morris, Mark I McCarthy, Leif Groop, Emma Ahlqvist, Joshua C Bis, Kenneth Rice, Nicholas L Smith, Thomas Lumley, Eric A Whitsel, Til Stürmer, Eric Boerwinkle, Julius S Ngwa, Christopher J O'Donnell, Ramachandran S Vasan, Wei-Qi Wei, Russell A Wilke, Ching-Ti Liu, Fangui Sun, Xiuqing Guo, Susan R Heckbert, Wendy Post, Nona Sotoodehnia, Alice M Arnold, Jeanette M Stafford, Jingzhong Ding, David M Herrington, Stephen B Kritchevsky, Gudny Eiriksdottir, Leonore J Launer, Tamara B Harris, Audrey Y Chu, Franco Giulianini, Jean G MacFadyen, Bryan J Barratt, Fredrik Nyberg, Bruno H Stricker, André G Uitterlinden, Albert Hofman, Fernando Rivadeneira, Valur Emilsson, Oscar H Franco, Paul M Ridker, Vilmundur Gudnason, Yongmei Liu, Joshua C Denny, Christie M Ballantyne, Jerome I Rotter, L Adrienne Cupples, Bruce M Psaty, Colin N A Palmer, Jean-Claude Tardif, Helen M Colhoun, Graham Hitman, Ronald M Krauss, J Wouter Jukema, Mark J Caulfield

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

Funding

Competing financial interests: B.M.P. serves on the Data and Safety Monitoring Board of a clinical trial funded by the device manufacturer (Zoll LifeCor). N.P. and A.S. received funding from Pfizer for the extended follow-up of the ASCOT UK participants. D.I.C. and P.M.R. received research support for independent genetic analysis in JUPITER from AstraZeneca. F.N. and B.J.B. have employment, stock and stock options in AstraZeneca, a for-profit company engaged in the discovery, development, manufacture and marketing of proprietary therapeutics such as rosuvastatin, but do not consider that this creates any conflict of interest with the subject–matter of this publication. R.M.K. serves on the Merck Global Atherosclerosis Advisory Board. The remaining authors declare no competing financial interests.

History

Comments

This article is also available at http://www.nature.com/ncomms/2014/141028/ncomms6068/pdf/ncomms6068.pdf

Published Citation

Postmus, I. et al. Pharmacogenetic meta-analysis of genomewide association studies of LDL cholesterol response to statins. Nature Communications. 2014;5:5068

Publication Date

2014-01-01

Publisher

Macmillan Publishers Limited

PubMed ID

25350695

Usage metrics

    Royal College of Surgeons in Ireland

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC