Author
Listed:
- Clint L. Miller
(Stanford University School of Medicine)
- Milos Pjanic
(Stanford University School of Medicine)
- Ting Wang
(Stanford University School of Medicine)
- Trieu Nguyen
(Stanford University School of Medicine)
- Ariella Cohain
(Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai)
- Jonathan D. Lee
(Stanford University School of Medicine
Stanford University School of Medicine)
- Ljubica Perisic
(Karolinska Institutet)
- Ulf Hedin
(Karolinska Institutet)
- Ramendra K. Kundu
(Stanford University School of Medicine)
- Deshna Majmudar
(Stanford University School of Medicine)
- Juyong B. Kim
(Stanford University School of Medicine)
- Oliver Wang
(Stanford University School of Medicine)
- Christer Betsholtz
(Genetics and Pathology, Rudbeck Laboratory, Uppsala University
Vascular Biology Unit, Karolinska Institutet)
- Arno Ruusalepp
(Tartu University Hospital
Clinical Gene Networks AB)
- Oscar Franzén
(Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Clinical Gene Networks AB)
- Themistocles L. Assimes
(Stanford University School of Medicine)
- Stephen B. Montgomery
(Stanford University School of Medicine
Stanford University School of Medicine)
- Eric E. Schadt
(Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai)
- Johan L.M. Björkegren
(Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai
Vascular Biology Unit, Karolinska Institutet
Institute of Biomedicine and Translation Medicine, University of Tartu)
- Thomas Quertermous
(Stanford University School of Medicine)
Abstract
Coronary artery disease (CAD) is the leading cause of mortality and morbidity, driven by both genetic and environmental risk factors. Meta-analyses of genome-wide association studies have identified >150 loci associated with CAD and myocardial infarction susceptibility in humans. A majority of these variants reside in non-coding regions and are co-inherited with hundreds of candidate regulatory variants, presenting a challenge to elucidate their functions. Herein, we use integrative genomic, epigenomic and transcriptomic profiling of perturbed human coronary artery smooth muscle cells and tissues to begin to identify causal regulatory variation and mechanisms responsible for CAD associations. Using these genome-wide maps, we prioritize 64 candidate variants and perform allele-specific binding and expression analyses at seven top candidate loci: 9p21.3, SMAD3, PDGFD, IL6R, BMP1, CCDC97/TGFB1 and LMOD1. We validate our findings in expression quantitative trait loci cohorts, which together reveal new links between CAD associations and regulatory function in the appropriate disease context.
Suggested Citation
Clint L. Miller & Milos Pjanic & Ting Wang & Trieu Nguyen & Ariella Cohain & Jonathan D. Lee & Ljubica Perisic & Ulf Hedin & Ramendra K. Kundu & Deshna Majmudar & Juyong B. Kim & Oliver Wang & Christe, 2016.
"Integrative functional genomics identifies regulatory mechanisms at coronary artery disease loci,"
Nature Communications, Nature, vol. 7(1), pages 1-16, November.
Handle:
RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12092
DOI: 10.1038/ncomms12092
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Cited by:
- Abolfazl Doostparast Torshizi & Dongnhu T. Truong & Liping Hou & Bart Smets & Christopher D. Whelan & Shuwei Li, 2024.
"Proteogenomic network analysis reveals dysregulated mechanisms and potential mediators in Parkinson’s disease,"
Nature Communications, Nature, vol. 15(1), pages 1-16, December.
- Lucia Trastulla & Georgii Dolgalev & Sylvain Moser & Laura T. Jiménez-Barrón & Till F. M. Andlauer & Moritz Scheidt & Monika Budde & Urs Heilbronner & Sergi Papiol & Alexander Teumer & Georg Homuth & , 2024.
"Distinct genetic liability profiles define clinically relevant patient strata across common diseases,"
Nature Communications, Nature, vol. 15(1), pages 1-28, December.
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