The Moonshot R&D Project started in 2020 with the aim of creating disruptive innovations originating in Japan. A total of four interviews were conducted to introduce the project. In the second installment, we will introduce Goal 2 "Realization of ultra-early disease prediction and intervention by 2050." The key to the program is the "whole body network simulator" to predict health instability. By clarifying the complex networks between organs and tissues in the body and making full use of mathematical models and sensors, it will be possible to predict diseases and "treat" them before patients become ill. Takuro Teramura, a science communicator at the National Museum of Emerging Science and Innovation, interviewed the Program Director, Gen Sobue, Chairperson of Aichi Medical University.


Detecting abnormalities in the body’s network in diseases such as cancer and diabetes

Teramura: Goal 2 aims to achieve ultra-early prediction and prevention of disease, focusing on four areas of refractory cancer, diabetes, dementia, and viral infections. Why were these chosen?

Sobue: Cancer accounts for about a quarter of all deaths in Japan. The number of diabetic patients has reached about 20 million, including the preliminary group, and the number of patients with dementia, which is common among the elderly, is about 6 million. Infectious diseases, such as COVID-19, appear suddenly and are a threat to the health of many people. Because of this, early diagnosis, prevention, and treatment are strongly desired, and we have selected diseases that should be resolved in order of priority to extend healthy life expectancy.

Teramura: The importance of early detection of illness has indeed been pointed out so far.

Sobue: For some illnesses, it takes time for symptoms to appear. For example, in dementia, it is known that the progression of the disease begins nearly 30 years before the onset of symptoms. However, until now, the process leading up to the onset has not been clarified, so treatment was performed after onset. In Goal 2, we aim to discover diseases before patients become sick, and to establish treatments that can return patients to their pre-disease state.

Teramura: Genetic testing and other tests have also shown the risk of disease.

Sobue: Certainly, diseases caused by genetic mutations are easier to predict. However, even when a particular causative gene carries a mutation, this does not mean that the associated disease develops immediately. The body is very complex and contains multiple mechanisms that always try to keep it in a constant state of health. When something goes wrong with an organ, another function occurs to compensate and tries to restore it to its original state.

Teramura: How are abnormalities in the body shared with other organs?

Sobue: Networks are formed between organs and share information by various means such as hormones and neurotransmitters. These networks also exist at the cellular and molecular levels. Conversely, because of these networks, if something goes wrong somewhere, you are more likely to develop the disease elsewhere. That is why it is important to detect abnormalities as soon as possible and to return to a healthy state as soon as possible. This means that it is necessary to comprehensively grasp the phenomena occurring in the body and clarify the body’s associated networks.

Measuring the huge amount of information going back and forth in the body daily and utilizing it for analysis

Teramura: Are there any diseases that can already be predicted from biological information?

Sobue: In the case of animals, when we analyzed model mice that develop metabolic syndrome in about 8 weeks, we identified unusual fluctuations in the expression of more than 100 genes 2-3 weeks before onset. From this, it is thought that if we can grasp the fluctuation of gene expression, we can grasp the state change before the onset.

Teramura: Do we know anything similar for humans?

Sobue: Some illnesses have been found to be correlated, but we still lack sufficient knowledge in this area. In the case of mice, we can continuously observe them, from full health until they become sick, but we cannot do the same for humans. Even if data is obtained, it is necessary to carefully analyze which abnormality correlates with what disease from the vast amount of biometric information exchanged in the body.

Teramura: That means the first step is to collect accurate biological information while a person is healthy right?

Sobue: In Japan, there is a cohort study that collects information on the medical check-ups of tens of thousands of people. Through these efforts, we receive data from the same people every year, allowing us to collect valuable information over time.

Teramura: Nowadays, wearable devices such as watches can be used to measure blood pressure and body temperature.

Sobue: If you use them, you can get more biometric information. These could be used to detect abnormalities and facilitate very early prediction of illness. We would like to clarify the relationship between the internal network and illness and realize a "whole body network simulator" that can predict and prevent illness from biological information that can be measured daily.

Teramura: How accurate can these predictions be?

Sobue: In older weather forecasts, there was little observation data, and the prediction accuracy was low. However, the accuracy has improved dramatically based on mathematical analysis using abundantly available data. The "whole body network simulator" that we are aiming for will gradually accumulate data, and eventually it should be possible to predict many diseases with high accuracy.


Teramura: What kind of system will the research proceed in?

Sobue: It is divided into four disease-specific teams and a mathematical analysis team that cuts across all of them. Professor Shigeo Ohno of Juntendo University is studying intractable cancer, and Professor Hideki Katagiri of Tohoku University is studying diabetes. Professor Ryosuke Takahashi of Kyoto University is studying dementia, and Professor Yoshiharu Matsuura of Osaka University is studying infectious diseases. Professor Kazuyuki Aihara, of University of Tokyo is working on mathematical analysis across these four studies.

Citizen cooperation and understanding is indispensable/Addressing ethical issues

Teramura: What are the rules for handling clinical data?

Sobue: In Japan, there are some institutions that collect clinical data, and the usage and management methods of said data is strongly restricted by law. However, without those data, we cannot carry out our research. This is where informed consent comes into play. When we ask patients to provide us with their data, first we explain what we intend to do with it, and how it will be used. Only after the patient has agreed to these aims do they provide us with their data. After this, we researchers work with institutions that specialize in handling clinical data as we move proceed with our research.

Teramura: I take it that the cooperation of us citizens that provide data is therefore indispensable. On the other hand, there are many people who want to cooperate in research but are worried about the handling of personal information.

Sobue: Clinical data includes both data that can be used to identify individuals, and data from which an individual’s identity cannot be identified. For example, while genomic information can identify an individual, gene expression information differs depending on the situation, so it is difficult to use for identification. In the past, there was a tendency to believe that even information that was difficult to use for identification should not be handled. However, in order to confront the threat of illness, it is necessary to establish a mechanism of safely handling biological information and utilize it for research. Therefore, this project will also include a team of experts dealing with ethical, legal, and social issues, and will proceed while discussing various topics.

Teramura: Ah, so it is important to create a practical system that firmly grasps the risks and usefulness. Finally, what do you want us to pay attention to in this project in the future?

Sobue: Until now, the main idea in medical care has been to overcome illness after getting sick. In the future, however, we would like to slowly shift to the awareness that many diseases are linked, and that prediction and prevention prior to onset is important. We would like for not only researchers, but also citizens, like our readers, to pay attention to research advancements. If this change can happen, we believe that the nature of care itself can also slowly change. We also hope that everyone will help support a future in which ultra-early prediction and prevention of illness will be possible by 2050.