Genome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery

Objectives Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common...

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Published inBMJ open Vol. 5; no. 5; p. e006920
Main Authors Kertai, Miklos D, Li, Yi-Ju, Li, Yen-Wei, Ji, Yunqi, Alexander, John, Newman, Mark F, Smith, Peter K, Joseph, Diane, Mathew, Joseph P, Podgoreanu, Mihai V
Format Journal Article
LanguageEnglish
Published England BMJ Publishing Group LTD 06.05.2015
BMJ Publishing Group
Subjects
Adult
Aged
Biomarkers - metabolism
Coronary Artery Bypass - adverse effects
Coronary Artery Bypass - methods
Coronary vessels
Creatine Kinase - metabolism
Datasets
Female
Genes
Genetics
Genetics and Genomics
Genome-Wide Association Study
Genomes
Heart surgery
Humans
Integrated approach
Intraoperative Complications - diagnosis
Male
Methods
Middle Aged
Monitoring, Physiologic
Mortality
Myocardial Infarction - diagnosis
Myocardial Infarction - etiology
Myocardial Infarction - metabolism
Myocardium - metabolism
Prognosis
Quality control
Studies
SURGERY
GENETICS
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Abstract Objectives Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. Setting 107 secondary and tertiary cardiac surgery centres across the USA. Participants We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. Primary and secondary outcome measures The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. Results Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10−5 in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10−3 for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10−6 for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. Conclusions Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
AbstractList Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. 107 secondary and tertiary cardiac surgery centres across the USA. We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology.OBJECTIVESIdentification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology.107 secondary and tertiary cardiac surgery centres across the USA.SETTING107 secondary and tertiary cardiac surgery centres across the USA.We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included.PARTICIPANTSWe conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included.The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution.PRIMARY AND SECONDARY OUTCOME MEASURESThe primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution.Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation.RESULTSFollowing quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation.Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.CONCLUSIONSUsing a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
Objectives Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. Setting 107 secondary and tertiary cardiac surgery centres across the USA. Participants We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. Primary and secondary outcome measures The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. Results Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10−5 in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10−3 for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10−6 for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. Conclusions Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
ObjectivesIdentification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology.Setting107 secondary and tertiary cardiac surgery centres across the USA.ParticipantsWe conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included.Primary and secondary outcome measuresThe primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution.ResultsFollowing quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10−5 in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10−3 for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10−6 for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation.ConclusionsUsing a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI.
Author Newman, Mark F
Kertai, Miklos D
Joseph, Diane
Mathew, Joseph P
Li, Yi-Ju
Li, Yen-Wei
Ji, Yunqi
Podgoreanu, Mihai V
Smith, Peter K
Alexander, John
AuthorAffiliation 6 Cardiac Surgery; Duke University , Durham, North Carolina , USA
2 Department of Biostatistics and Bioinformatics , Duke University , Durham, North Carolina , USA
3 Duke Molecular Physiology Institute; Duke University , Durham, North Carolina , USA
5 Duke Clinical Research Institute; Duke University , Durham, North Carolina , USA
4 Division of Cardiology , Duke University , Durham, North Carolina , USA
1 Division of Cardiothoracic Anesthesiology , Duke University , Durham, North Carolina , USA
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/25948407$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
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Glower, D D
Swaminathan, M
Jones, R
Podgoreanu, M V
Willard, H F
Li, Y J
Smith, P K
Milano, C A
Smith, M P
Mathew, J P
White, W D
Goldstein, D B
Davis, R D
Allen, A S
Newman, M F
Welsby, I J
Moretti, E W
Phillips-Bute, B
Hauser, E
Hall, R L
Laskowitz, D T
Grichnik, K P
Gaca, J G
Funk, B
Kertai, M D
Stafford-Smith, M
Lodge, A J
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Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions 2015
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– notice: Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
– notice: Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions 2015 This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
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CorporateAuthor Duke Perioperative Genetics and Safety Outcomes (PEGASUS) Investigative Team
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Snippet Objectives Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic...
Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective...
ObjectivesIdentification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic...
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Enrichment Source
Publisher
StartPage e006920
SubjectTerms Adult
Aged
Biomarkers - metabolism
Coronary Artery Bypass - adverse effects
Coronary Artery Bypass - methods
Coronary vessels
Creatine Kinase - metabolism
Datasets
Female
Genes
Genetics
Genetics and Genomics
Genome-Wide Association Study
Genomes
Heart surgery
Humans
Integrated approach
Intraoperative Complications - diagnosis
Male
Methods
Middle Aged
Monitoring, Physiologic
Mortality
Myocardial Infarction - diagnosis
Myocardial Infarction - etiology
Myocardial Infarction - metabolism
Myocardium - metabolism
Prognosis
Quality control
Studies
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Title Genome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery
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Volume 5
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