Reviews
Recent Technological Innovations to Promote Cardiovascular Research
2022 年 86 巻 6 号 p. 919-922
詳細
2022 年 86 巻 6 号 p. 919-922
Cardiovascular disease (CVD) is a major global health concern. Several therapeutic strategies for CVDs are available, such as medicine, cardiac assist devices, and heart transplantation. However, they are insufficient for the treatment of severe CVD. To develop novel, innovative treatment approaches for CVDs, it is imperative to understand the underlying pathophysiology and to undertake basic research on this facet. The generation of induced pluripotent stem (iPS) cells has opened avenues for developing new strategies for disease analysis and drug development. This technology has made it possible to obtain pluripotent stem cells from patients with genetic disorders, model the disease in a dish, and use such cells for future regeneration therapy. Meanwhile, artificial intelligence (AI), which is widely used for big data analysis in basic research, has potential in various applications in medicine. New tools such as iPS cells and AI can provide much needed novel insights into CVDs. This review focuses on the recent progress in cardiovascular research using these new technologies.
Cardiovascular disease (CVD) is a leading cause of death worldwide.1 Several types of drugs have been developed to improve the quality of life and decrease mortality in patients with CVD. However, therapeutic options are limited for severe CVDs, and their effects remain insufficient.2 Therefore, innovative developments are highly desirable. In other areas of medicine, such as cancer, autoimmune diseases, and neurological disorders, many innovative therapeutic options have been developed in recent decades. These include immunotherapy, drugs with specific molecular targets, and genome-based therapy. The pathology of CVDs is complex and poorly understood. To develop innovative therapies for CVDs, it is essential to first fully elucidate the underlying pathogenesis. Different types of cells in the cardiovascular organs, including the heart and arteries, control the homeostasis of the cardiovascular system. Dysfunction of these cells can cause cardiovascular dysfunction and diseases. Traditionally, cardiovascular research involves in vitro experiments, ex vivo experiments, animal model studies, and human genome research. Technological innovations for basic research provide exciting opportunities for new analyses to further understand the disease and develop effective treatment strategies. In recent years, breakthroughs such as induced pluripotent stem (iPS) cells, single-cell analysis, multi-omics analysis, genome editing, and artificial intelligence (AI) have been integrated in ongoing research in various medical fields, including cardiovascular research. In this review, updates on the status of applications of iPS cells and AI in CVD research are provided.
The successful generation of iPS cells was first reported in 2006, and their potential was heralded with considerable enthusiasm.3 iPS cells have several advantages over established stem cells and embryonic stem (ES) cells. Importantly, there are ethical concerns regarding the generation and use of human ES cells because of the need for human fertilized eggs. It is impossible to generate ES cells from a patient’s tissues. The use of iPS cells overcomes this limitation because these cells can be generated from a patient’s somatic cells. Since the initial report on the generation of iPS cells, there have been continuous, marked, improvements in technologies for the generation of human iPS cells,4–10 enabling the easy and efficient generation of iPS cells in any laboratory. iPS cells have the definitive characteristics of stem cells, including self-renewal ability and multipotency. iPS cells have been used in a wide variety of applications, such as regenerative medicine, disease modeling, and drug screening.11–15
Cardiomyocytes are the main focus of CVDs because these cells are unique to the heart. To obtain cardiomyocytes from iPS cells, cardiomyocytes need to be differentiated from iPS cells. Many studies have been conducted to develop cardiomyocyte differentiation methods, and sophisticated methods have been developed.16–19 After differentiation, iPS cell-derived cardiomyocytes can be observed among several types of cells in cell culture dishes, which makes it difficult to use cardiomyocytes generated in this manner. Contamination with other cell types increases the risks associated with regeneration therapy and decreases the accuracy of disease analysis. This limitation has been overcome by the development of cardiomyocyte purification methods, which enable the use of pure cardiomyocytes for research and regenerative medicine.20–22
Heart transplantation is the only effective therapy for end-stage heart failure, but the number of organ donors is limited. The need for regenerative therapy for severe heart failure is widely acknowledged. Single cardiomyocyte transplantation is not ideal because of cell fragility and runoff, warranting tissue engineering technology. Accordingly, cell sheet technology and spheroid formation technology have been developed.20,23 These methods have been examined in large animal (e.g., non-human primates and swine) studies.24–26 One of the unique iPS cell research areas is disease modeling, in which human genetic disorders can be modeled by patient-derived iPS cells.27–30 These iPS cells differentiate into disease-causing cell types, including cardiomyocytes. These cardiomyocytes can express the patient phenotype in a dish. Numerous studies have shown that these models recapitulate disease phenotypes similar to those seen in patients.31–35 These systems help clarify the disease mechanisms and can guide the development of drug screening systems for the disease. Initially, iPS cell-derived cardiomyocytes were the main focus in disease research, but a recent study showed that several types of cells can interact with each other in vitro and that these interactions can induce complex disease phenotypes.36
Genome editing is a well-known innovative technology. Several types of genome-editing tools have been developed, such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9).37 These tools, when used in concert with iPS cell studies, have manifold applications. For example, mutations in patients can be corrected, and new mutations can be inserted in iPS cells. Gene modifications enable us to understand the role of mutations in diseased cells. Organoid technology also benefits from iPS cell studies. Cardiac organoids resemble the native heart and can be used to understand complex disease phenotypes.38
iPS cells have several potential uses, such as in regenerative medicine,14,15,39 drug screening,40,41 disease modeling,11,33,42–44 and precision medicine.45 However, several issues remain to be resolved to realize breakthrough technologies for medicine. Recent progress in AI has had a considerable impact on several aspects of society, including medicine. Among several types of AI, machine learning is an algorithm for learning pattern formation and classification from large datasets. Deep learning is a form of machine learning that learns data features using a multilayered neural network mimicking the structure of the human neural circuit. Machine learning technology has been used for big data analysis in cardiovascular research, such as genomic and RNA sequencing data analysis.46 Recent advances in machine learning algorithms and computational power have enabled the use of AI in a wide variety of research and clinical applications.
Image recognition systems based on convolutional neural network (CNN) have also improved considerably. The accuracy of image classification by CNN has been found to exceed that of humans in specific tasks.47 Image recognition systems have been widely used in the real world, such as facial recognition and self-driving cars. It is expected that CNN will also have a considerable impact on basic research into CVD.48 iPS cells can differentiate into numerous types of cells in vitro and in vivo. To use these cells for any purposes, the cell type needs to be initially identified by specific molecular techniques, such as immunostaining with specific antibodies. Each cell type has unique characteristics and cell type-specific gene expression patterns, indicating that each cell type will exhibit distinct morphological characteristics. Although, the cell type cannot be identified by phase-contrast microscopic observations alone, a morphology-based identification system using CNN successfully identified cell types from phase-contrast microscope images, and can serve as an alternative molecular detection technique.49 Cell types can be identified by machine learning technology, which raises the possibility that machine learning technology can identify cell status in terms of a healthy or diseased cell.
Cardiomyocytes are one of the main cell types in the heart. Cardiomyocyte dysfunction definitely induces several types of heart disease, such as heart failure and arrhythmic disorders. Diseased organs encompass many types of cells with various cellular conditions, including healthy and diseased states. Diseased cells underlie disease and can induce a disease state. To understand the mechanism of disease, the diseased cellular state is usually identified using molecular techniques. Diseased cells possess many aspects of pathological phenotypes and display unique morphological features. We have focused on senescent endothelial cells among the many types of diseased cells, because such cells induce aging-related changes and aging-related diseases. We developed a method to identify senescent endothelial cells by CNN using phase-contrast microscope images.50 Diseased cells can be a potential therapeutic target in these diseases.51,52 A screening system to identify potential drugs that can directly affect the cellular disease phenotype may uncover promising therapeutic options. We have developed a novel drug screening system using a morphology-based CNN system, through which we identified potential anti-aging drugs that could diminish the aging phenotypes of endothelial cells.50 These systems can be applied to other cellular conditions and other cell types, such as those of the cardiovascular system.
New technologies pave the way for new knowledge in research and medicine (Figure). It is essential to understand how new technologies can be incorporated into conventional research. Here, iPS cells and AI technologies in basic cardiovascular research were discussed, in addition to how these technologies are revolutionizing research at the cellular level. Looking ahead, one must consider numerous new technologies, such as cryoelectron microscopy and mRNA vaccines, which should also be integrated into CVD research. Basic cardiovascular research calls for the rigorous and sustainable use of emerging technologies to realize innovative therapies.
New technology for cardiovascular research. New technologies pave the way for disease analysis, mechanism elucidation, and drug discovery in cardiovascular research. Induced pluripotent stem (iPS) cell technology facilitates the development of regeneration therapy, disease modeling, and drug discovery. Artificial intelligence technology is applied to big data analysis, automation, and drug discovery.
The author thanks his laboratory members for their assistance. The author’s research reported herein was supported by JSPS KAKENHI (Grant no. 20H3678, 20K8193, 20K8461, 19H3622), Keio University Academic Development Funds for Individual Research, and the SENSHIN Medical Research Foundation. Research funds were also provided by Alchemedicine, Inc.
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