About CardiOmics.net



CardiOmics is a website of the Interventional & Translational Cardiology (ITC) research group of the University Medical Center Groningen. This group is headed by Prof. Pim van der Harst.

The ITC groups has had the great fortune of working on some truly inspiring projects while collaborating with many influential and creative individuals and research groups along the way. We believe in the power of working together to create a whole that is greater than the sum of its parts.

We have worked on multiple cardiovascular traits and are interested in multiple type of 'omics' data, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, radiomics and the microbiome.

We have published on the genomics of multiple electrocardiographic traits, including the P-wave, PR-segment, QRS duration, QRS voltages, and QT time. We have studied vital cardiovascular signs; heart rate and blood pressure (systolic, diastolic, mean arterial pressure and pulse pressure). Summary and references of our key findings can be found below.


Student Research Internships:
For more information about the ICT group and opportunities to work with us, get in touch today. We are always looking for ambitious new talent!


Summary of selected

Published Work


Coronary Artery Disease

Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease.


Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. Ninety-seven genetic risk loci have been identified to date, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD.


To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD.


We performed a genome-wide association study in 34 541 CAD cases and 261 984 controls of UK Biobank resource followed by replication in 88 192 cases and 162 544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant (P<5×10-8) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci, we identified all promising (P<0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK Biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance (P<5×10-8) in meta-analysis. Finally, we performed a genome-wide meta-analysis of all available data revealing 30 additional novel loci (P<5×10-8) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene sets from 4.2% to 13.9% of all gene sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure, and death.


We identified 64 novel genetic risk loci for CAD and performed fine mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene sets argues in favor of an expanded omnigenic model view on the genetic architecture of CAD.

Link: Pubmed

Data download:

          CAD GWAS in UK Biobank: http://dx.doi.org/10.17632/2zdd47c94h.1

          CAD meta-analysis: http://dx.doi.org/10.17632/gbbsrpx6bs.1

Publication: Van der Harst P, Verweij N. Identification of 64 Novel Genetic Loci Provides an Expanded View on the Genetic Architecture of Coronary Artery Disease. Circ Res. 2018 Feb 2;122(3):433-443.

doi: 10.1161/CIRCRESAHA.117.312086. Epub 2017 Dec 6.

FREE FULL TEXT: download

Identification of 15 novel risk loci for coronary artery disease and genetic risk of recurrent events, atrial fibrillation and heart failure


Coronary artery disease (CAD) is the major cause of morbidity and mortality in the world. Identification of novel genetic determinants may provide new opportunities for developing innovative strategies to predict, prevent and treat CAD. Therefore, we meta-analyzed independent genetic variants passing P <× 10-5 in CARDIoGRAMplusC4D with novel data made available by UK Biobank. Of the 161 genetic variants studied, 71 reached genome wide significance (p < 5 × 10-8) including 15 novel loci. These novel loci include multiple genes that are involved in angiogenesis (TGFB1, ITGB5, CDH13 and RHOA) and 2 independent variants in the TGFB1 locus. We also identified SGEF as a candidate gene in one of the novel CAD loci. SGEF was previously suggested as a therapeutic target based on mouse studies. The genetic risk score of CAD predicted recurrent CAD events and cardiovascular mortality. We also identified significant genetic correlations between CAD and other cardiovascular conditions, including heart failure and atrial fibrillation. In conclusion, we substantially increased the number of loci convincingly associated with CAD and provide additional biological and clinical insights.

Link: Pubmed


Verweij N, Eppinga RN, Hagemeijer Y, van der Harst P. Identification of 15 novel risk loci for coronary artery disease and genetic risk of recurrent events, atrial fibrillation and heart failure.
Sci Rep. 2017 Jun 5;7(1):2761. doi: 10.1038/s41598-017-03062-8.

FREE FULL TEXT: download


GWAS heart rate CardiOmics Pim van der Harst

Heart Rate Omics (RR-interval)

Resting heart rate is a heritable trait correlated with lifespan. Little is known about the genetic contribution of resting heart rate and its relationship with mortality.


To further our understanding of the genetic basis of resting heart rate we performed a genome-wide association analysis of 19.9 million genetic variants in 134,251 individuals from UK Biobank and a further replication analyses in 130,795 individuals from 4 independent populations. We then used the identified genetic variants as an instrument to study the association between resting heart rate, cardiovascular risk factors and all-cause mortality.



Genome-wide association analysis identified 64 loci associated with resting heart rate (P<5×10-8), 46 of these were novel. An increase in genetically predicted resting heart rate of 5 beats per minute was associated with a 20% increased mortality risk (hazard ratio 1.20, 95% CI of 1.11-1.28, P=8.20×10-7) translating to a 2.9 years reduction in life expectancy for males and 2.6 years for females. Genetically predicted resting heart rate was found to be associated with higher body-mass index, systolic and diastolic blood pressure, hypertension, smoking, supraventricular tachycardia, and device implantation (all P<0.05). However, we did not identify such factors as mediators on the causal pathway between resting heart rate and all-cause mortality. Candidate gene and pathway analyses provide strong support for a dominant role of cardiac development and structure.



We discovered 46 novel loci for resting heart rate. These provide evidence for shared genetic predictors of resting heart rate and all-cause mortality.

Link: Pubmed

Data Download


​​​​​Ruben N. Eppinga, Yanick Hagemeijer, Stephen Burgess, David A. Hinds, Kari Stefansson, Daniel F. Gudbjartsson, Dirk J. van Veldhuisen, Patricia B. Munroe, Niek Verweij, and Pim van der Harst. Identification of genomic loci associated with resting heart rate and shared genetic predictors with all-cause mortality Nat Genet. 2016 Oct 31. doi: 10.1038/ng.3708. [Epub ahead of print]


Den Hoed M, Eijgelsheim M, Esko T, ....Snieder H, Samani NJ, Loos RJ. Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders.
Nat Genet. 2013;45:621-31.

FREE FULL TEXT: download

GWAS ECG QRS PR QRS PP ST CardiOmics Pim van der Harst


P-wave and PR Segment

The PR interval on the ECG reflects atrial depolarization and atrioventricular nodal delay which can be partially differentiated by P wave duration and PR segment, respectively. We show that known genetic associations of PR interval seem to be mainly driven by genetic determinants of the PR segment. We also identified 5 novel loci by a genome-wide analysis on P wave duration and PR segment, seperatetly. SNPs in KCND3 (P=8.3×10(-11)) and FADS2 (P=2.7×10(-8)) were associated with P wave duration. SNPs near IL17D (P=2.3×10(-8)), in EFHA1 (P=3.3×10(-10)), and in LRCH1 (P=2.1×10(-8)) were associated with PR segment.

Publication: Verweij N, Mateo Leach I, van den Boogaard M, van Veldhuisen DJ, Christoffels VM; LifeLines Cohort Study, Hillege HL, van Gilst WH, Barnett P, de Boer RA, van der Harst P. Genetic determinants of P wave duration and PR segment. Circ Cardiovasc Genet. 2014;7:475-81. PubMed PMID: 24850809.


QRS amplitudes and duration

QRS amplitudes and duration are measures reflecting myocardial mass, a key determinant of cardiac muscle function and hypertrophy. These measures are associated with clinical and pre-clinical cardiac conditions, including left ventricular hypertrophy, heart failure and various cardiomyopathies. To understand the genetic factors influencing the QRS complex, we have carried out a GWAS disocvery and replication study of 4 closely related traits; Sokolow-Lyon, Cornell, and 12-lead-voltage duration products (12-leadsum), and QRS duration. We identified 52 loci and used multiple strategies to follow-up on these findings.



van der Harst P, van Setten J, Verweij N, ...., Isaacs A, Samani NJ, de Bakker PI.  52 Genetic Loci Influencing Myocardial Mass. J Am Coll Cardiol. 2016;68:1435-48.

FREE FULL TEXT: download

Sotoodehnia N, Isaacs A, de Bakker PI, Dörr M, Newton-Cheh C, Nolte IM, van der Harst P, ..., Jamshidi Y, Stricker BH, Samani NJ, Kääb S, Arking DE. Common variants in 22 loci are associated with QRS duration and cardiac ventricular conduction. Nat Genet. 2010;42:1068-76.

FREE FULL TEXT: download












QT interval

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization.

Publication: Arking DE, Pulit SL, Crotti L, van der Harst P, Munroe PB,.... Chakravarti A, Ackerman MJ, Pfeufer A, de Bakker PI, Newton-Cheh C. Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization. Nat Genet. 2014;46:826-36.

FREE FULL TEXT: download

ST-T wave amplitudes

The ST-T wave, as measured on the electrocardiogram, reflects cardiac repolarization. Changes and abnormalities of these parameters have been linked to ventricular arrhythmias and sudden cardiac death. We performed a genome wide meta-analysis on quantitative measures of the ST-T wave amplitudes in up to 37,977 individuals. Here we identified 28 genome wide associated loci which includes genes with established roles in the cardiac repolarization phase (SCN5A/SCN10A, KCND3, KCNB1, NOS1AP and HEY2) and others with as yet undefined cardiac function. Our findings may provide insights in the spatiotemporal contribution of genetic variation influencing cardiac repolarization.

Publication: Verweij N, Mateo Leach I, ....  Van Der Harst P. Twenty-eight genetic loci associated with ST-T-wave amplitudes of the electrocardiogram Hum Mol Genet. 2016;25:2093-2103.
FREE FULL TEXT: download

GWAS blood pressure SBP DBP PP MAP CardiOmics Pim van der Harst

Blood Pressure

By trans-ancestry genome-wide association among 320,251 individuals of East Asian, European and South Asian ancestry, we identified 12 new loci to be associated with blood pressure phenotypes. In addition, we observed that genetic variants are enriched for associations with nearby CpG sites, suggesting that DNA methylation may lie on the regulatory pathway between the genetic variants and blood pressure. The 12 new loci point include genes known to be involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal function (ARHGAP24, OSR1, SLC22A7 and TBX2) .


Surendran P, Drenos F, Young R, ..., Butterworth AS, Howson JM, Munroe PB. Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension. Nat Genet. 2016;48:1151-61.

Kato N, Loh M, Takeuchi F, Verweij N, .....  Tai ES, van der Harst P, Kooner JS, Chambers JC Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation. Nat Genet. 2015;47:1282-93.
FREE FULL TEXT: download.

International Consortium for Blood Pressure Genome-Wide Association Studies. Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature. 2011;478:103-9.

FREE FULL TEXT: download.

Newton-Cheh C, Johnson T, Gateva V, ..., Abecasis GR, Caulfield M, Munroe PB. Genome-wide association study identifies eight loci associated with blood pressure. Nat Genet. 2009;41:666-76.

FREE FULL TEXT: download.

GWAS Blood Biomarkers telomere galectin-3 renin aldosterone CardiOmics Pim van der Harst

Blood Biomarkers

Telomere length



Codd V, Nelson CP, Albrecht E,...Spector TD, van der Harst P, Samani NJ. Identification of seven loci affecting mean telomere length and their association with disease. Nat Genet. 2013;45:422-7.

FREE FULL TEXT: download

Codd V, Mangino M, van der Harst P, ..., Thompson JR, Spector T, Samani NJ. Common variants near TERC are associated with mean telomere length. Nat Genet. 2010;42:197-9.

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Circulating Galectin-3, a lecting, has been associated with various disease, including cardiovascular disease and mortality. We performed a genomet wide assocation study of Galectin-3, identying the LGALS3 gene (rs2274273; P = 2.35 × 10(-188)) and the ABO gene (rs644234; P = 3.65 × 10(-47)).A genome-wide association study of circulating galectin-3.

de Boer RA, Verweij N, van Veldhuisen DJ, Westra HJ, Bakker SJ, Gansevoort RT, Muller Kobold AC, van Gilst WH, Franke L, Mateo Leach I, van der Harst P. A genome-wide association study of circulating galectin-3. PLoS One 2012;7:e47385

FREE FULL TEXT: download

Plasma Renin and Aldosterone



Lieb W, Chen MH, Teumer A, de Boer RA, ..., van der Harst P, Reincke M, Vasan RS. Genome-wide meta-analyses of plasma renin activity and concentration reveal association with the kininogen 1 and prekallikrein genes. Circ Cardiovasc Genet. 2015;8:131-40.
FREE FULL TEXT: download

​​Red blood cells


Cvejic A, Haer-Wigman L, Stephens JC, ...., van der Harst P, van der Schoot CE, Ouwehand WH, Albers CA. SMIM1 underlies the Vel blood group and influences red blood cell traits. Nat Genet. 2013;45:542-5.

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van der Harst P, Zhang W, Mateo Leach I, ..., Ouwehand WH, Soranzo N, Chambers JC. Seventy-five genetic loci influencing the human red blood cell. Nature. 2012;492:369-75.

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​Liver enzymes



Chambers JC, Zhang W, Sehmi J, Li X, Wass MN, Van der Harst P, ...., Scott J, Järvelin MR, Elliott P, Kooner JS. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nat Genet. 2011;43:1131-8.

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​​​Creatine and kidney function



Chambers JC, Zhang W, Lord GM, van der Harst P, ..., Navis G, Elliott P, Kooner JS. Genetic loci influencing kidney function and chronic kidney disease. Nat Genet. 2010;42:373-5.

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