The future of cardiovascular prevention: between fiction and reality

The coronavirus disease (COVID)-19 pandemic has exacerbated the flow of ‘health’ care systems worldwide, which, actually, are ‘sick’ care systems, activated only when somebody is not well. One of the lessons learnt is that, in the future, a real ‘health’ care system has to care for the maintenance of individuals’ wellbeing and reduce the number of times individuals become patients.1 This needs an improvement in the delivery of prevention and it is the focus of this editorial. The issue is particularly true for cardiovascular diseases (CVDs), a pathology that can be effectively prevented. Mendelian randomization clinical trials have helped us to understand that the negative effects of risk factors, such as high blood pressure and LDL-cholesterol levels, are determined by both the magnitude and the duration of the exposure.2,3 Thus, for these risk factors not only ‘the lower’ but also ‘the earlier’ is the best! This concept is supported by the finding that long-term reduction of blood pressure and LDL-cholesterol results in independent and additive reduction of risk for CVD.2 In the future, the world is likely to be confronted with multiple risk factors difficult to capture and integrate with the usual score systems.4 This is the bad news. The good news is that, as shown in Figure 1, technology [through advanced imaging, genetics, mobile- and sensor-derived biometrics, metabolomics, proteomics, artificial intelligence (AI), deep learning machines, etc.] may help to capture and analyse the multiplicity of data, thus allowing a real and precocious personalized risk prediction. Let’s analyse possible future changes related to CVD prevention. Future vision of how prevention could develop Sensors will help population to continuously collect data related to classic risk factors but also to the new ones, such as those from the exposome, pollution, genetics, etc. The data will be transformed into deep learning's and artificial intelligence's regulated algorithms and stored in a medical control power station. This last, is in continuous contact with the individuals' general practicioners and/or dedicated experts. Every time an alert is generated, either automatically or through general practicioners, individuals will be contacted, alerted, counselled for the maintenance of their own wellbeing. Already a useful tool to detect CVD, will produce new images: those of the human cell atlas, the so-called ‘cartography’.5 This massive programme has already mapped every cell of the heart: not only myocytes, smooth muscle, or endothelial cells of the coronaries but also immune cells, fibroblasts, pericytes, myeloid, lymphoid, adipocytes, neuronal cells, etc. Single-cell genomic analysis linked to AI will detect which genes are switched ‘on’ or ‘off’ in every single cell, thus providing ‘ultra-personalized cardiac prevention’ at a cellular level. There are millions of variants with thousands of disease-associated genes describing a ‘genetic risk’. Such enormous possibilities of combinations will generate a massive amount of data, unsuitable to be analysed by the human brain but not for AI models, which will be able to integrate genetics with all of the other individual and environmental risks. This will not happen overnight but sooner than we imagine. Actually, genomics has already allowed the development of polygenic risk scores, including the cumulative impact of several common variants, linked to the risks of cardiovascular (CV) events.6 Polygenic tests for CVD are commercially available at different prices (ranging from 200 to 1000 euros) and their use is slightly increasing in the Western world although the real benefits are still unknown. A new wording, meaning exposure to several subliminal environmental risk factors. Industrialization, urbanization, and mega cities are meant to produce wealth and wellbeing but, ironically, are also sources of diseases, including CVD.6 The measurement of the exposome is complex. It means grading and connecting the still poorly understood environmental risk factors to produce a complex network of influencers, all contributing to CV and other diseases.6 Today, the determination of individual exposome is unrealistic, but not in the near future, once again thanks to the use of technologies, such as sensors and biodetectors connected to AI and machine learning models. The measurement of the exposome will allow us to move forward from the old concept ‘one exposure-one disease-one outcome’ to a more ‘omic’ risk estimation. Although prevention should be targeted for all people from childhood to the elderly, usually it is for relatively young and middle-aged subjects and is based on hard endpoints. In recent years, thanks to the progresses in treatments of CV and other diseases, life expectancy has constantly increased in several parts of the world but without a parallel increase of a ‘healthy’ lifespan. The degree of late-life wellbeing can be improved as ageing is mouldable, but problems need to be spotted well before occurring. Disability and sickness, at end of life, will be another target for prevention: not just prevention of an outcome, but also estimation of its cost for the community.7 The actual ‘health’ or ‘sick’ care system, although successful so far, has demonstrated several limits during the COVID-19 pandemic, mainly in terms of territorial and preventive medicine. Consequently, national governments and the European Union (EU) are asking for urgent improvements. Maintenance of people’s wellbeing will be one of the goals of medicine, requiring a different approach to prevention, which can no longer be just a list of what to do and not to do.8 As illustrated in Figure 1, individuals must become proactive for their own wellbeing.9 Technology might help. Soon, people will be able to continuously monitor themselves and particularly their heart function. The output of sensors could be transmitted to an AI model able to integrate and elaborate all of the incoming data which might be stored in a remote server or ‘medical control power station’. The process could be available 24 h a day (H24) throughout a lifespan! This will be a great help for the actual general practitioners. He/she could establish a partnership with people, specialists, and medical or social allied figures all liaising with the ‘medical control power station’ in a multidisciplinary way to find out the ideal time to intervene and correct, modify or even eliminate each relevant risk factor exceeding a security level. In so doing, he/she will contribute to the maintenance of wellbeing of the population which will be treated (when necessary) at a very early stage or addressed to counselling or engaged in social networks until ‘clear’ from risks. The advantages of this system are numerous: (i) the establishment of life longer contact vs. a sporadic one at a time estimation of the risks; (ii) the capability to react immediately; (iii) the link of the population with the digital transformation; and (iv) individuals will be encouraged to share their data, sensations, problems, etc. for population-based research, thus feeling part of the new progress. Probably, a bit of both. On one hand, it seems that treatment of CVD will soon reach a plateau; on the other hand, the cost of progress might affect human health, the COVID-19 pandemic being just one example. In the near future, human health is at risk of being threatened by a multiplicity of risk factors and science will reveal some others, particularly in the area of genetics. It is on such a diversity and volume of risks that prevention can drive the future. The idea of a ‘medical control power station’ liaising with the classical ‘white coat’ doctor might be considered fiction but it could more realistic than one might think. It needs just few interventions: (i) more funding allocated to prevention; (ii) more coordinated and collective actions for the planet and its population; (iii) more alliances between academies, big pharma, and technologic industry to accomplish a global public health projects; and (iv) more focus on maintaining wellbeing. Today, at least, we have the imagination (fiction); tomorrow we will need to make it real. The authors thank Silvia Felloni and Juliet Verri for their professional assistance with this manuscript. This work was supported by a grant from Fondazione Anna Maria Sechi per il Cuore (FASC). No new data were generated or analysed in support of this research.