Regulatory Variants Modulate Protein Kinase C α (PRKCA) Gene Expression in Human Heart
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Protein kinase C α (PRKCA) is involved in multiple functions and has been implicated in heart failure risks and treatment outcomes. This study aims to identify regulatory variants affecting PRKCA expression in human heart, and evaluate attributable risk of heart disease.
mRNA expression quantitative trait loci (eQTLs) were extracted from the Genotype and Tissue Expression Project (GTEx). Allelic mRNA ratios were measured in 51 human heart tissues to identify cis-acting regulatory variants. Potential regulatory regions were tested with luciferase reporter gene assays and further evaluated in GTEx and genome-wide association studies.
Located in a region with robust enhancer activity in luciferase reporter assays, rs9909004 (T > C, minor allele frequency =0.47) resides in a haplotype displaying strong eQTLs for PRKCA in heart (p = 1.2 × 10−23). The minor C allele is associated with both decreased PRKCA mRNA expression and decreased risk of phenotypes characteristic of heart failure in GWAS analyses (QT interval p = 3.0 × 10−14). While rs9909004 is the likely regulatory variant, other variants in high linkage disequilibrium cannot be excluded. Distinct regulatory variants appear to affect expression in other tissues.
The haplotype carrying rs9909004 influences PRKCA expression in the heart and is associated with traits linked to heart failure, potentially affecting therapy of heart failure.
KEY WORDSassociation gene expression genetic variant heart failure polymorphism protein kinase C α (PRKCA)
beta-1 adrenergic receptor
Allelic expression imbalance
Expression quantitative trait loci
Genome-wide association studies
Minor allele frequency
Protein kinase C α subunit
Sarcoplasmic reticulum Ca2+ ATPase-2
Single nucleotide polymorphisms
Acknowledgments and Disclosures
We thank Rosanna Asselta for giving us the primer sequences and PCR condition of rs35476409/rs61762387 and 15 × GCC microsatellite. This study was supported by National Institutes of Health Pharmacogenetics Research Network grant U01 GM092655 (WS), U01-GM074492 (JAJ), the National Institute of Health grant R01HL126969 (DW), and partially by a grant from the National Center for Research Resources (UL1RR025755). We also acknowledge support from the Ohio Supercomputer Center (grant #PAS0885). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Center for Research Resources. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health. Additional funds were provided by the NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. Donors were enrolled at Biospecimen Source Sites funded by NCI\SAIC-Frederick, Inc. (SAIC-F) subcontracts to the National Disease Research Interchange (10XS170), Roswell Park Cancer Institute (10XS171), and Science Care, Inc. (X10S172). The Laboratory, Data Analysis, and Coordinating Center (LDACC) was funded through a contract (HHSN268201000029C) to The Broad Institute, Inc. Biorepository operations were funded through an SAIC-F subcontract to Van Andel Institute (10ST1035). Additional data repository and project management were provided by SAIC-F (HHSN261200800001E). The Brain Bank was supported by a supplement to University of Miami grants DA006227 & DA033684 and to contract N01MH000028. Statistical Methods development grants were made to the University of Geneva (MH090941 & MH101814), the University of Chicago (MH090951, MH090937, MH101820, MH101825), the University of North Carolina - Chapel Hill (MH090936 & MH101819), Harvard University (MH090948), Stanford University (MH101782), Washington University St Louis (MH101810), and the University of Pennsylvania (MH101822). The data used for the analyses described in this manuscript were obtained from GTEx Analysis Release V6p, dbGaP Accession phs000424.v6.p1. Disclosures None.
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