Can predictive genomics make our healthcare systems more sustainable?




Can predictive genomics make our healthcare systems more sustainable?





















predictive genomics, healthcare systems
© Catalin Iliescu

Dr Zisis Kozlakidis with Francesco Florindi, discuss predictive genomics and ask if it can help make our healthcare systems more sustainable

Many healthcare systems across the world are perilously approaching the no-return in terms of sustainability. Aging, resulting in increasing patient numbers with multiple conditions, sedentary lifestyles and changing nutritional profiles are driving the rising prevalence of non-communicable diseases (NCDs) such as cancer, cardiovascular diseases and diabetes.

At the same time, the young healthy and productive population (which should shoulder the socio-economic burden of older generations) is anticipated to continue shouldering the increased healthcare costs. The result is a potentially catastrophic sustainability pressure for healthcare systems’ functioning, which can further expand inequalities, especially in Low- and Middle- Income (LMIC) settings, where there is high competition for resource access and prioritization.

Thus, healthcare systems and policy-makers have a responsibility to comprehensively evaluate new ways to predict and prevent NCDs, providing citizens with the tools to change their lifestyles and, at the same time, supporting public health professionals with the most innovative tools available to allocate dwindling resources effectively. Here we will focus on predictive genomics and how such methods might influence sustainability.

Harnessing genetic information

The genetic material, organized into genes, provides the operating template for all our biological processes, and in some cases, sequence variations in the genetic material have been linked to conferring genetic disadvantages, for example, higher risks of developing certain types of cancer. (1)

Predictive genomics is the capacity to harness the power of this genetic information and interpret it in a clinically actionable manner to help prevent disease and / or managing a healthy lifestyle. For most common diseases, such as coronary artery disease and type 2 diabetes, polygenic inheritance, involving many common genetic variants of small effect, plays a greater role than much rarer mutations in single genes.

In cancer for example, while rare mutations in genes such as BRCA1 and BRCA2 confer high risks of developing breast cancer, these account for only a small proportion of breast cancer cases in the general population. On the other hand, a more common situation includes variants that confer a small risk individually, but their combined effect, when summarized as a polygenic risk score, can be substantial. This polygenic inheritance might also be distinct between different individuals as well as different population groups.

As such, the capacity to understand the risk of developing disease (s) might constitute a critical component in future healthcare provision. Predictive genomics has the potential to transition healthcare systems from an emergency-based response, taking care of those who get sick, to helping everyone stay as healthy as possible for as long as possible.

This could be achieved at the individual level by promoting lifestyle choices and / or providing the most effective medication based on each personal genome; and at the public level by increasing the accuracy of targeted public health screening programs and treatments. Thus, using tools such as genomics, a more preventative outlook for the healthcare systems is anticipated to eventually emerge and widen the time window at which lifestyle changes or interventions can be recommended to avert the development of preventable disease.

predictive genomics
© Luchschen

Opportunities and barriers

Governments have demonstrated their interest in the potential of genomics in making healthcare systems more sustainable. For example, all large European economies have launched genomic initiatives in the last five years (UK, France, Germany, Italy, Spain and others), however these are mainly focused on diagnostics (with a shorter market implementation horizon) rather than a longer- term prevention. Furthermore, the emergence of pan-European initiatives, such as the 1+ Million Genomes (2), Beyond 1+ Million Genomes and the Million Veteran Program in the USA – to name but a few – demonstrate the governments’ collective appetite for genomics.

However, only a few countries (Finland, UK, Estonia) have specifically invested in predictive genomics. One of the reasons for doing so, is that predictive genomics can raise practical, ethical and legal considerations. For example, predictive genomics are data-intensive approaches to improve diagnosis and develop new treatments for major diseases, however this increased sharing of personal information raises concerns about data privacy, commercialization, and public trust.

Thus, the time is ripe for the following three conversations to happen on the role (s) predictive genomics can play in creating sustainable healthcare systems. Firstly, a discussion on the allocation of clinical attention and resources across individuals with different levels of genetic risk and the ways in which the integration of predictive genomics will be implemented into routine healthcare practice. (3) Secondly, a health economic conversation to evaluate more precisely the financial impact of predictive genomics as part of such routine healthcare planning and provision. Thirdly, a wider public and political conversation to strike a new balance between the benefits of predictive genomics, the potential ethical / legal risks, and how to mitigate them.

Importantly, new technologies such as predictive genomics should be viewed and leveraged as opportunities for LMICs to leapfrog into a more sustainable healthcare provision model for NCD patient populations within their regions. However, achieving this would require new technologies to become LMIC-friendly by design, allowing for their successful implementation and long-term routine operation in the field. If for example the reliance of high-cost digital equipment and skilled technical expertise remains an inflexible requirement for predictive genomics, then the risk emerges of the latter becoming an improvement applicable to a small number of resource abundant settings only.

Opportunity to improve healthcare

Predictive genomics are fast emerging as a promising opportunity for healthcare systems to improve disease prevention and survival, through targeted screening, preventative strategies or other interventions addressed to those individuals most likely to benefit. However, risk communication will require serious consideration. For example, while predictive genomics may allow for relative risks to be calculated at birth for all common diseases, the usefulness of knowledge and the potential harms to the individual may vary with the disease and stage of life.

Thus, while research progresses at a rapid pace, it will be important to consider how predictive genomics will be integrated into the core of healthcare services and how to communicate any identified risks to best serve each patient. The considerable investments by many countries in the field of predictive genomics, by helping to promote the future integration of genetic testing in healthcare delivery and clinical decision making, is anticipated to advance precision medicine and improve the healthcare of the general population.

REFERENCE

  1. Kalimutho M, Nones K, Srihari S, Duijf PH, Waddell N, Khanna KK. Patterns of genomic instability in breast cancer. Trends in pharmacological sciences. 2019 Mar 1; 40 (3): 198-211.
  2. 2020-2022 Roadmap of the 1 + Million Genomes Initiative, European Commission. https://digitalhealtheurope.eu/wp- content / uploads / 2020/10 / 1MillionGenomesRoadmap2020-2022.pdf 3. Minari J, Brothers KB, Morrison M. Tensions in ethics and policy created by National Precision Medicine Programs. Human genomics. 2018 Dec; 12 (1): 1-0.

Editor’s Recommended Articles