Periodic Reporting for period 4 - STEMCARDIORISK (Stem Cells for Cardiac Arrhythmia Risk Assessment)
Okres sprawozdawczy: 2020-05-01 do 2021-04-30
Cardiovascular disease is a major cause of morbidity and mortality in Europe. Genetic studies have been pivotal in identifying the genetic basis of many inherited cardiac diseases such as primary electric disorders, where potentially lethal arrhythmias arise from abnormalities in the electrical function of the heart. However a complicating factor for clinicians in predicting patients at risk of these disorders is that they are clinically characterised by a broad spectrum of phenotypic expression, even within families. This variability in severity can be due to the type and position of the rare genetic mutations, as well as the influence of more commonly occurring variants. Understanding these genetic contributions has been hampered by the lack of suitable model systems to perform such studies.
Previously we showed that cardiomyocytes generated from human pluripotent stem cell (hPSC) lines derived from patients with arrhythmogenic diseases exhibit the characteristic electrophysiological features of the respective disorders. However it remained unclear how well these models reflected the genotype-phenotype relationship. Therefore the overall objective of STEMCARDIORISK was to establish whether these models could replicate in vitro the variable disease severity and incomplete penetrance commonly observed in patients, and be used to pinpoint and assess the pathogenicity of individual mutations.
To achieve this we aimed:
- to develop gene editing tools to enable the rapid generation of cell lines containing different individual genetic mutations
- to establish strategies to detect subtle phenotypic differences in the resulting isogenic cardiomyocytes that could be directly attributable to either the primary mutation or the influence of additional modifying variants
- to use these resulting models to identify mutation-specific drug response differences.
Overall, the methods and models we developed within STEMCARDIORISK will be of important value in the areas of drug safety and personalised medicine, particularly with regards to improved individual risk stratification and patient-specific pharmacotherapy.
Previously we showed that cardiomyocytes generated from human pluripotent stem cell (hPSC) lines derived from patients with arrhythmogenic diseases exhibit the characteristic electrophysiological features of the respective disorders. However it remained unclear how well these models reflected the genotype-phenotype relationship. Therefore the overall objective of STEMCARDIORISK was to establish whether these models could replicate in vitro the variable disease severity and incomplete penetrance commonly observed in patients, and be used to pinpoint and assess the pathogenicity of individual mutations.
To achieve this we aimed:
- to develop gene editing tools to enable the rapid generation of cell lines containing different individual genetic mutations
- to establish strategies to detect subtle phenotypic differences in the resulting isogenic cardiomyocytes that could be directly attributable to either the primary mutation or the influence of additional modifying variants
- to use these resulting models to identify mutation-specific drug response differences.
Overall, the methods and models we developed within STEMCARDIORISK will be of important value in the areas of drug safety and personalised medicine, particularly with regards to improved individual risk stratification and patient-specific pharmacotherapy.
Within STEMCARDIORISK it was key to initially establish how sensitive the hPSC models were for investigating genotype-phenotype relationships. This is achieved by using genetically-matched cell lines in which the cardiac disease-linked genetic variant is the sole modified variable. In our first iteration we used CRISPR/Cas9 to introduce specific heterozygous ion channel mutations into a wild-type hPSC line. In patients it is known that the region of the ion channel containing the mutation influences the risk of an arrhythmic event occurring. In our genetically matched hPSC models we also detected such changes in the cardiomyocyte’s electrophysiology.
We subsequently expanded on this and determined that we could also use these hPSC disease models that we generated to detect differences in disease severity caused by the presence of commonly occurring modifying variants. We believe that by performing these investigations in very tight genetically controlled conditions we can address some of the discordant results in literature of whether some of these variants exacerbate or reduce the severity of the disease in patients.
To be able to address these questions we have needed to reduce heterogeneity by refining our cardiomyocyte differentiation strategy to improve yield and purity. This has also involved establishing a panel of cardiac markers to ensure that the resulting populations for comparison between the different lines are equivalent, and developing cryopreservation protocols so that the same stock of cardiomyocytes can be used over multiple assays. These developments have clearly reduced the level of variability we observe in our measurements thereby also improving the sensitivity of our models to detect subtle functional differences.
Concurrently we also developed a novel allele replacement strategy that enabled the rapid and simultaneous generation of cell lines containing different individual genetic mutations while maintaining the correct genomic context. Where once it would have taken us more than one year to generate 12 lines of different targeted genetic mutations, we can now do this in less than 2 months. Not only can we use this to generate a range of different models of known mutations with different phenotypes, but this approach can also potentially be used to classify the pathogenicity of variants identified in patients for which their clinical relevance is currently unknown. We are now investigating further how this could be employed diagnostically.
Finally, we have also demonstrated that we can use the hPSC disease models we have developed to detect mutation-specific drug response differences. Overall, the methods and models we have developed within STEMCARDIORISK will be of important value in the areas of drug safety and personalised medicine, particularly with regards to improved individual risk stratification and patient-specific pharmacotherapy.
The project has also resulted in 14 publications to date, along with ~16 poster and (invited) oral presentations at ~15 conferences, and a submitted patent. Members of the group employed on this project have subsequently found employment within the same field in both academia and industry, as well as successfully obtaining their own independent funding. Results from STEMCARDIORISK have also formed the basis for several new proposal for funding, including successful applications to Health~Holland and the Dutch Research Council.
We subsequently expanded on this and determined that we could also use these hPSC disease models that we generated to detect differences in disease severity caused by the presence of commonly occurring modifying variants. We believe that by performing these investigations in very tight genetically controlled conditions we can address some of the discordant results in literature of whether some of these variants exacerbate or reduce the severity of the disease in patients.
To be able to address these questions we have needed to reduce heterogeneity by refining our cardiomyocyte differentiation strategy to improve yield and purity. This has also involved establishing a panel of cardiac markers to ensure that the resulting populations for comparison between the different lines are equivalent, and developing cryopreservation protocols so that the same stock of cardiomyocytes can be used over multiple assays. These developments have clearly reduced the level of variability we observe in our measurements thereby also improving the sensitivity of our models to detect subtle functional differences.
Concurrently we also developed a novel allele replacement strategy that enabled the rapid and simultaneous generation of cell lines containing different individual genetic mutations while maintaining the correct genomic context. Where once it would have taken us more than one year to generate 12 lines of different targeted genetic mutations, we can now do this in less than 2 months. Not only can we use this to generate a range of different models of known mutations with different phenotypes, but this approach can also potentially be used to classify the pathogenicity of variants identified in patients for which their clinical relevance is currently unknown. We are now investigating further how this could be employed diagnostically.
Finally, we have also demonstrated that we can use the hPSC disease models we have developed to detect mutation-specific drug response differences. Overall, the methods and models we have developed within STEMCARDIORISK will be of important value in the areas of drug safety and personalised medicine, particularly with regards to improved individual risk stratification and patient-specific pharmacotherapy.
The project has also resulted in 14 publications to date, along with ~16 poster and (invited) oral presentations at ~15 conferences, and a submitted patent. Members of the group employed on this project have subsequently found employment within the same field in both academia and industry, as well as successfully obtaining their own independent funding. Results from STEMCARDIORISK have also formed the basis for several new proposal for funding, including successful applications to Health~Holland and the Dutch Research Council.
A key development from STEMCARDIORISK was the allele replacement strategy that enabled the rapid generation of panels of isogenic hPSC lines differing exclusively at candidate genetic variants thought to be associated with inherited or acquired cardiac arrhythmias. Testing of this method indicated that we could target ~50kb genetic fragments into the hPSCs with >80% efficiency, and could even extend the approach to introduce up to 170 kb genomic regions. This technology simplifies the procedure for generating panels of lines with a wider range and combination of genetic variants while maintaining control of the allele being modified. The approach is expected to help advance the field of precision medicine, both in terms of assessing whether a rare mutation is likely to be disease-causing, as well as providing panels of cell lines that can be used to test the efficacy of pharmacological compounds against individual mutations.