First person – Anaïs Kervadec and James Kezos

Anaïs Kervadec

How would you explain the main findings of your paper to non-scientific family and friends?

AK/JK: Atrial fibrillation (AF) is the most common form of sustained cardiac arrhythmia in humans that can lead to various heart-related complications, including stroke and heart failure. Genetics, ageing and other risk factors contribute to this disease, which presently affects ∼33 million individuals worldwide, and this number is estimated to rise significantly in the upcoming years. Unfortunately, existing treatments and medications have proven inadequately effective, making research on AF a topic of high interest. While progress has been made over the past two decades in identifying AF-associated genes, no direct links to disease-causing mechanisms have been established, likely due to the multifactorial nature of the disease. To address this issue, we have developed a multimodel platform that enables us to directly correlate gene function with the onset or maintenance of AF, thereby advancing drug discovery efforts. Our approach integrates three high-throughput model systems: a human atrial-like cell model system, a fruit fly cardiac model system providing whole-organ and ageing relevance, and a predictive computer modeling system. Our platforms all identified phospholamban (PLN) as a gene that caused robust irregular heart rhythm patterns in our models. The addition of external stressors, such as adrenaline or ageing, in combination with reduced PLN activity, resulted in significant signs of arrhythmia. Furthermore, our predictive computer modeling model identified other genes that could potentially rescue or worsen AF. We validated these predictions in the cell and fly systems and showed that reduced PLN activity, coupled with diminished NCX activity, intensified arrhythmicity, and, conversely, we were able to rescue this arrhythmia with specific medications, such as verapamil. Our platform thus represents an effective approach to investigating gene interactions underlying cardiac arrhythmia and holds promise for identifying therapeutic targets to treat AF.

What are the potential implications of these results for your field of research?

AK/JK: The findings and insights presented in our paper highlight the power of utilising a multimodel system approach to unravel the mechanisms underlying various diseases and disorders, extending beyond AF. A fundamental perspective that emerges from our work is that most diseases are either oligogenic or polygenic in nature. Consequently, in order to discover treatments and disease prevention strategies, it becomes imperative to understand how multiple genetic, ageing and environmental factors synergistically contribute to pathogenic mechanisms. This is practically very hard to do with strategies that focus on a single cell type or model organism. We hope that our research inspires and encourages other laboratories to incorporate additional model systems into their experimental designs, thus improving the predictive power and validity of their investigations.

What are the main advantages and drawbacks of the experimental system you have used as it relates to the disease you are investigating?

AK/JK: Each of our model systems have their own respective advantages and drawbacks. Regarding the fruit fly model, there are many genetic and molecular pathways associated with cardiac development and function that are conserved between flies and humans. Many of the genes important in human heart development and function were first found or studied in fruit flies. In addition, the fruit fly model ages rapidly, allowing us to examine the effects of age on heart function in a few weeks, not years. However, the simple tube-like structure of the Drosophila heart cannot be directly compared to the four-chambered heart, closed-circulatory system of humans. The induced atrial-like cardiomyocyte model allows us to conduct high-throughput experiments with multiple gene knockdowns and measure various rhythmicity parameters in thousands of cells within a short timeframe. We can easily introduce extra factors such as isoproterenol, fibroblast co-culture, as well as drug treatments to assess their impact on the cell rhythmicity. However, it is important to note that this system primarily assesses the effects of genes at the single-cellular level, rather than providing a comprehensive assessment of adult heart function. Additionally, the cell model represents a relatively immature state of human adult atrial myocytes and does not permit us to examine the effects of ageing. This is where our computational model system becomes instrumental, allowing us to incorporate a population of models of human adult atrial myocytes to bridge the gaps and account for physiological diversity. This computational model facilitates both the validation of our findings and the generation of hypotheses, thereby enhancing the overall power and robustness of our research. However, it is important to note that while the model considers physiological variability, it may not capture the complete complexity of the entire population.

What has surprised you the most while conducting your research?

AK/JK: We were surprised at the lack of robust arrhythmicity occurring when we tested individual candidate genes identified in human AF patients. To induce significant levels of arrhythmia in the flies, we either had to co-knock down two AF candidate genes, or wait until the flies became old and/or pharmacologically stress the hearts with cardioactive hormones. Similarly, in the atrial-like cardiomyocytes, isoproterenol and fibroblast co-culture stressors were necessary in addition to gene knockdown to induce robust arrhythmicity. This shows once again the complexity underlying AF disease-causing mechanisms and emphasises the difficulty in finding effective treatment targets. However, it challenged us and pushed us to think beyond our individual research efforts and combine forces to make a meaningful impact in the field of AF research.

What do you think is the most significant challenge impacting your research at this time and how will this be addressed over the next 10 years?

AK/JK: There are two significant challenges that we must acknowledge and attempt to address. First, there is an ever-growing list of candidate genes for AF; however, there are many studies that demonstrate conflicting results when investigating these genes, which hinders the establishment of a clear understanding. Second, there is no quick, effective vertebrate model system to study age-related disorders such as AF, which makes it challenging to test more than 300 AF candidate genes in more relevant model systems to identify mechanisms. These two challenges are related to each other, and emphasise the necessity for embracing novel, innovative, and unconventional model systems, as we have done. By combining these cutting-edge methodologies, we can discover new gene networks associated with AF and advance the development of effective therapies for this disease.

What changes do you think could improve the professional lives of scientists?

AK/JK: As we grow from graduate students to postdoctoral associates and eventually principal investigators, more emphasis needs to be placed on the development and training of skills associated with experimental design, statistics, bioinformatics, and other traits involved with research reproducibility and efficiency. Second, access to resources to better develop skills associated with grant writing, networking and communication, and leadership/mentorship would be effective in building a stronger research and science community, as well as personal growth.

AK: I am currently working as a scientist at Avidity Biosciences, a biotech company that utilises a new class of targeted RNA therapeutics called antibody oligonucleotide conjugates to tackle the root cause of genetically inherited diseases. We rely heavily on published data, mainly coming from academic research, to understand disease-causing mechanisms to develop new therapies. I think more support should be given to academic labs, particularly in terms of funding, to nurture their contributions to scientific knowledge. Encouraging collaborations should also be emphasised, as the power of our research lies in creating networks of experts who share a common goal: deciphering disease mechanisms to advance the development of therapies that will impact patients' lives. By actively promoting and supporting these collaborative efforts, we can propel scientific advancements and accelerate the translation of research findings into tangible benefits for patients.

What's next for you?

AK: While my doctoral and postdoctoral trainings were focused on the cardiac muscle field, I have transitioned into the skeletal muscle field in my current role at Avidity Biosciences. I am now working on developing therapies to address the unmet medical needs of patients affected with rare muscular dystrophies. The translational aspect of this work inspires me, knowing that I have the opportunity to contribute to the development of novel and innovative therapies that have the potential to make a significant impact on patients' lives. With this goal in mind, I am dedicated to making a meaningful contribution to advancing muscular disorders research and treatment that have the potential to transform the lives of patients affected by these debilitating disorders.

JK: I am currently conducting postdoctoral research on candidate AF genes identified in AF patients using our cardiac-ageing fruit fly model system. Within the next year or two, I plan to make the transition to the assistant professor level, where I can lead my own research lab studying AF and other cardiac rhythm diseases.