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.
