After four years, the project has been completed successfully and the major outcomes will create a platform for continued work by the members of the consortium.
The project provided one of the largest atrial tissue collections analysed so far.
An automated analysis of the hallmarks of atrial structural remodelling was developed. Validation to manual annotation showed that detection of cardiomyocytes occurred with precision (95,4 ± 4,5%), while maintaining sensitivity (93,9 ± 5.5%). A comparison between samples from patient with and without atrial fibrillation and/or heart failure indicate that endomysial fibrosis is driven by rhythm status, whereas increasing cardiomyocyte diameters occur predominantly in heart failure patients.
It was found that the atrial epicardium is a source of fibroblasts that can invade the neighboring myocardium. These epicardial-derived fibroblasts arise from the epithelial-to-mesenchymal transition and differentiation of a subset of resident epicardial progenitors, a process regulated by distinct signaling pathways and peptides. These results have already started impacting AF risk assessment, preventive strategies, and therapeutic stratifications through successful dissemination efforts at meetings and through publications relating to circulating microRNA, telomere length analysis, ECG based analyses with respect to AF complexity and P wave signals, assessment of atrial fibrosis, and endurance training. These dissemination efforts impacted the wider awareness for AF and set the stage for the planned novel AF classification evolving from CATCH ME.
Models including only clinical variables have been developed to predict recurrent and prevalent AF. These models demonstrated to be accurate and to overperform other commonly used scores such as CHADS, APPLE, HATCH and ATLAS.
Seven hypotheses had been designed a priori focusing on the association between some health modifiers and therapies, and AF prevalence or recurrence risk. These hypotheses have been tested in the CATCHME cohort.
A database has been created with a contribution from the majority of the consortium will be used for further analyses by the partners. The database will also be made available for further analyses to other researchers upon request.
Two apps have been developed for both Apple and android devices. These can be downloaded by searching for My AF (patients) or AF Manager (clinicians). These are being successfully used and the patient app has been translated into German, Dutch, French, Spanish Italian, Polish and Portuguese.
More than 30 new biomarker opportunities have been identified, where investigations and validations are still ongoing. One of the first important outcomes showed that the fibrotic pathway (FGF23) plays an important role in AFib. The markers showed good performance to predict recurrence of AFib and also diagnostic use. In analogy, the marker NT-proBNP was confirmed. This work will carry on post project.
We have contributed to academic as well as non-academic events, engaged via social media, press releases and websites. Fifty papers have been published in high impact journals and the consortium expect this number to increase. Details can be found on our web site www.catch-me.info
A short summary of the CATCH ME outcomes has been put into a booklet. This booklet has been made publicly available on the CATCH ME website
http://www.catch-me.info/sites/default/files/docs/CATCH%20ME_Key%20work_final.pdf(öffnet in neuem Fenster)
