GENetics and the Electrocardiogram for predicting Scd rISk

Project Information

GENESIS

Grant agreement ID: 786833

DOI

10.3030/786833

Project closed

EC signature date 19 March 2018

Start date 18 March 2019

End date 17 March 2021

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost

€ 183 454,80

EU contribution

€ 183 454,80

Coordinated by

QUEEN MARY UNIVERSITY OF LONDON
United Kingdom

Periodic Reporting for period 1 - GENESIS (GENetics and the Electrocardiogram for predicting Scd rISk)

Reporting period: 2019-03-18 to 2021-03-17

Summary of the context and overall objectives of the project

Sudden cardiac death (SCD) is a common and devastating event, often occurring in the prime of life and having profound consequences for surviving members of the individual’s family . Prospective studies reported annual SCD rates ranging from 40-100 per 100,000 in the general population in the United States, Europe and Asia . Consequently, enhancement of methods for prediction and prevention of SCD are critically important. The main objective of this project is to establish and test a novel effective approach to prevent SCD based on the combination of information derived from cardiac electrophysiological indices and genetic predisposition.

The main scientific objective of GENESIS was to establish and test a novel effective approach to prevent SCD based on the combination of information derived from cardiac electrophysiological indices and genetic predisposition.
The specific tasks were:
• Aim 1: Propose and test the SCD predictive value of a novel ECG risk marker based on the adaptation of 3D T-wave morphological variations to heart rate changes.
• Aim 2: Provide a mechanistic interpretation of non-invasive ECG indices based on comparison with intra-cardiac electrophysiological indices simultaneously measured during electrophysiological studies.
• Aim 3: Generate personalized risk scores combining genetics, ECG indices and clinical variables to optimize SCD prediction.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In Aim 1, I proposed and developed the TMT index, quantifying T-wave morphology deviations in time from a normal reference from standard ECG recordings at rest, which are widely available at the clinical practice and ambulatory settings. I extracted T-wave morphology references from standard 12-lead ECGs from ~24,000 participants in the UK Biobank (UKB). I, then, obtained average T-wave morphologies from ~52,000 independent participants in UKB, and from ~2,000 patients with coronary artery disease in the ARTEMIS study. Next, I quantified the difference between these average T-wave morphologies and their corresponding references using time‐warping metrics. Results showed that TMT was the only ECG risk marker significantly associated with ventricular arrhythmias in UKB and SCD risk in ARTEMIS.

Regarding Aim 2, first, we derived measures of QT dynamics in ~57,000 individuals from UKB. We identified 20 loci, of which 4 included genes implicated in Mendelian long-QT syndrome. We did not observe associations of QT dynamics with cardiovascular events. Second, we conducted GWASs for resting Tpe and Tpe dynamics in ∼72,000 individuals from UKB. We identified 32 loci for resting Tpe, and 6 for Tpe dynamics modulating ventricular repolarization, cardiac conduction and contraction. In addition,we investigated the causal effect of heart rate (HR) dynamics during exercise and recovery on cardiovascular (CV) risk, all-cause mortality (ACM), atrial fibrillation (AF), coronary artery disease (CAD) and ischemic stroke (IS) using Mendelian Randomisation. Inverse-variance weighted method (IVW) showed a nominally significant effect of HRI on CV events and on CAD and AF. Regarding HRR, IVW was not significant for any outcome. The IVW method indicated statistically significant associations of resting HR with AF, and a nominally significant association with IS.

Under Aim 3, we first assessed the risk stratification improvement of including genetic risk scores (GRSs) for multiple cardiovascular traits into a score integrating traditional risk factors and a GRS for CAD in ~380,000 participants in the UKB without known cardiovascular conditions for CAD and major adverse cardiovascular events (MACE). For both CAD and MACE, adding the GRSs for multiple cardiovascular traits increased the AUC, the hazard ratio for individuals in the top versus bottom 20% of the distribution and the net reclassification index. I, secondly, co-led a project performing fine-mapping on blood pressure (BP) loci. We mapped variants to 253 functional and regulatory annotations. Joint modelling revealed significant global enrichment for signals mapping to protein coding exons in heart and adrenal tissues.

In total, GENESIS funding has led to 11 journal, 2 editorial and 9 conference peer-reviewed publications. In addition, I have presented results from GENESIS at 8 international conferences and 6 invited talks at specialised seminars. Moreover, I have been part of the organising committee of a special session at an international conference where I disseminated research from GENESIS. I have also disseminated my results and research activities in the project's website, and by posting in social media (@Ju_Ra_Ga). Finally, I have taken part in the ‘I am a scientist, get me out of here’ event, where school students interact with scientists and in the ‘Let’s Talk Hearts’ event, to educate patient groups and clinicians on the research of GENESIS.

Finally, regarding training, thanks to GENESIS I have broadened my collaboration skills, I have improved my presentation and communication skills, I have received direct feedback and scientific training from Prof Munroe and collaborators, I have received intense training in mentoring and supervision of students and in developing and writing grants.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

With Aim 1, and as indicated above, I have contributed with the creation and development of a novel non-invasive ECG marker of SCD risk that can be measured from standard 10-s 12-lead ECGs, which are widely available at clinical practices and ambulatory scenarios. The results on its predictive value support that our simplified alternative, TMT, is able to capture increased dispersion of ventricular repolarization than traditional T-wave indices form easily acquired ECG recordings, identifying a high-risk substrate for malignant VAs that could lead to SCD.

Regarding Aim 2, we discovered new responsible loci for variations in the QT and Tpe dynamics by modulating ventricular repolarization, as well as cardiac conduction and contraction. Regarding the second project, our findings suggested no strong evidence of an association between HRI and HRR and any outcome and confirm prior work reporting a highly significant effect of resting HR on AF. Thus, we informed the scientific community about our negative results of any causal link between HR dynamics during exercise and recovery and cardiovascular risk, as opposed to what was originally believed.

Regarding Aim 3, we showed that, in individuals without known cardiovascular disease, adding GRSs for multiple cardiovascular risk factors to a score integrating traditional risk factors and GRS for CAD improves risk stratification In addition, our findings on the BP project suggested mechanistic hypotheses that can be targeted for large-scale empirical validation at both variant and candidate effector gene level.

Findings from GENESIS include the identification of basic mechanisms underlying the cause of electrical dysfunction and its progression to malignant ventricular arrhythmias, providing new biomarkers (genetic and ECG), thus significantly decreasing its human and socioeconomic burden in the European community. Results from GENESIS specifically have an impact on European society since the ECG and genetic data analysed in this project are mainly acquired from European individuals. In addition, my findings have had a gender impact, I have stratified all analyses by gender and I have found an interaction between gender, the studied ECG markers and the lead genetic variants in predicting SCD.

GENESIS Overview