Transcription factor protein interactomes reveal genetic determinants in heart disease

With broadening availability of next-generation sequencing technologies, patients are increasingly undergoing genetic testing for cardiovascular diseases. Aetiologic genetic diagnosis of complex diseases such as congenital heart disease (CHD) is extremely challenging, especially due to remarkable genetic heterogeneity. In a recent issue of Cell, Gonzales -Teran et al. show very exciting results of a novel “combination” strategy using proteomics, genomics and computation biology to identify novel candidate genes (1).

Rather than starting from straightforward genetic sequencing, the Authors analysed in human induced pluripotent stem cell-derived cardiac progenitors the protein-protein interactomes of two transcription factors whose mutations have been consistently involved in CHD: GATA4 and TBX5. Resulting data were integrated with human whole-exome-sequencing data to map novel potential CHD-associated variants, identifying GLYR1, an ubiquitously expressed epigenetic reader co-binding and co-regulating with GATA4 a set of genes involved in cardiac development. A GLYR1 missense variant associated with CHD disrupted interaction with GATA4 and impaired cardiomyocyte differentiation and in vivo cardiogenesis.

The use of tissue-specific factors allowed the Authors to identify a candidate gene with potential tissue-specific effects, even if rare. Thus, an articulated scoring method was required to predict the likelihood that identified variants would actually be involved in CHD. However, whether GLYR1 might be associated to CHD in other populations is still unknown and will need further studies. Despite these limitations, the possible scientific implications of this integrated multi-omics approach are wide and might potentially involve in the future other cardiovascular diseases with heterogenous genetic basis, such as many cardiomyopathies. As shown by this paper and several other multi-omics studies, intense collaboration between cardiovascular and bioinformatic research groups as well as cardiovascular scientists with strong bioinformatic expertise – a profile difficult to find - are now crucial in cardiovascular research, since extensive computational biology capability and bioinformatic analysis already represent essential tools in the discovery/diagnosis toolbox of cardiovascular diseases.