Biomarkers as an Essential Component in Precision Medicine

The approach to healthcare is evolving once again. Healthcare initially started as bedside medicine in the 18th century, in which care was directly delivered to patients in a holistic approach. Physicians and healthcare workers would evaluate the entirety of the patient’s wellbeing in order to provide treatment. Healthcare providers often did not know the etiology of diseases, and therefore, treatments often did not have any scientific backing. Healthcare then transitioned into hospital medicine in the 19th century. In this phase of healthcare, hospitals became the site medical knowledge and training. Physicians held all the medical knowledge and patients were largely left out of medical decisions. The next phase of healthcare was the laboratory phase, which started in the late 19th century. With the invention of the microscope, much of medical knowledge and treatment was based on laboratory test and pathology. In these eras of medicine, treatments are based on methods that an average amount of people will respond positively. This strategy for treatment does not take into account individual differences and may result in people receiving ineffective treatment. Furthermore, these therapeutic treatments can result in adverse responses in the patient. Presently, there is an emphasis on shifting healthcare system to an era of precision, or personalized, medicine. Jameson and Longo (2015) define precision medicine as “treatments targeted to the needs of individual patients on the basis of genetic, biomarker, phenotypic, or psychological characteristics that distinguish a given patient from another patient with similar clinical presentations.” Transitioning to a precision medicine approach in healthcare can increase the efficacy of treatments for patients and decrease the number of adverse side effects that are attributed to treatments. Furthermore, precision medicine provides the opportunity for healthcare to be more proactive. Healthcare often takes a reactive approach, in which interventions are offered only after the disease occurs, but precision medicine can provide better assessment of an individual’s risk of developing a disease.

An essential component for the development precision medicine is the incorporation of biomarkers. Biomarkers are defined characteristics that have the ability to identify normal or abnormal biological functions. Biomarkers can have the ability to diagnose disease, monitor disease progression, identify those at risk for developing disease, and assess the safety of treatments. Biomarkers can be obtained from molecules in the body tissues and fluids, physiological characteristics, or imaging of tissues. Biomarkers should be as objective as possible to remove any potential bias from interpretation. Therefore, biomarkers do not measure how a person is feeling. In precision medicine, biomarkers can be used to identify individual characteristics of a person which can direct healthcare and treatment specific for the individual. Biomarkers associated with the genomics have been of particular interest in precision medicine. However, other omics approaches, such as transcriptomics, proteomics, and metabolomics can also be great benefit. Furthermore, wearable technology that has the capabilities to continuously monitor biomarkers in an individual and detect changes. This can also help to direct precision medicine, and can contribute to heath databases. Health databases can be used to monitor the health of an individual throughout their lifetime, and can be a valuable asset for research. While there are countless benefits associated with precision medicine, there are also many issues and concerns that need to be addressed before precision medicine can be fully implemented in healthcare systems. For precision medicine to be most effective, adjustments need to be made in all aspects of healthcare and biomarker development. This includes making changes to practices and education of patients, healthcare providers, academia, industry, regulatory bodies, and policy makers.

Ever since the Human Genome Project was able to map the entire genome, there has been great interest in the roles that DNA and RNA play in disease processes. With the advent of better, more sensitive technology, genetic testing can be used to diagnose diseases, predict individuals with increased susceptibility of developing a disease and predict the success of a particular treatment or response to a drug. Genetic biomarkers look for variations in DNA and RNA sequences, as well as the overall RNA expression. Differential variations and expressions of genetic material can have an significant impact on how an individual will develop disease and react to treatments. These differences are the targets of biomarkers. However, despite the many possible applications of genomic biomarkers, there are concerns that there is too much emphasis being placed on genomic biomarker development. Firstly, while DNA sequences are able to show variations in the genome, but DNA sequences do not correlate with the amount of proteins that are actually produced. Therefore, sequences may not be able to be used to prove causality. Secondly, the knowledge of genetic sequences and the functions then encode for may be incomplete. Many genome wide association studies (GWAS) have reported associations between variations in genetic sequences and diseases. However, many of these studies had small sample sizes, and the results are not reproducible. Thirdly, genetic biomarkers are very effective in diagnosing diseases like Cystic Fibrosis, that are a result of a single gene mutation. However, when it comes to more complex chronic conditions, such as cancer and obesity, genetic biomarkers have a limited ability to predict disease. In chronic diseases, multiple alleles contribute to the development of disease. As a result, the impact of single genetic variations on disease development is very small, and is not an effective method of identifying causes of chronic conditions. Furthermore, there is evidence to demonstrate that environmental and behavioural factors have a greater impact on disease development.

Integrating genomic approaches with other omics approaches can help to resolve these problems. Transcriptomics, proteomics, metabolomics, and an understanding of the immune response can supplement the results from genomic tests to provide more reliable disease associations. Overall, the combination of multiple approaches can contribute to the production of biomarkers with greater validity. A combined approach is demonstrated in integrative personal omics profiles (iPOP). Profiles of the genome, transcriptome, metabolome, and autoantibodies are generated and combined to create the iPOP. The iPOPs that are generated can be used to monitor healthy individuals and detect abnormalities associated with diseases. Specifically, iPOPs have been found to be effective in monitoring and identifying diabetes and viral infections. iPOPs are valuable in the development of precision medicine, as they can greatly contribute to the monitoring and diagnosis of diseases in individuals.

Digital biomarkers and wearable technology also have great potential to impact precision medicine. Presently, wearable technology is mostly used in the context of fitness monitoring, but there are many possibilities for wearable technology to be incorporated into healthcare. Wearable technology has the ability to take continuous measurements of biomarkers that are normally limited by the lack of portability of measuring tools. Biomarkers that can measured with wearable technology include heart rate, respiration rate and pulmonary function, blood pressure, temperature, and sweat. Heart rate, respiration rate, blood pressure and temperature are common measures of health, and are checked at routine doctor’s visits. As a biomarker, sweat can be used to measure stress, electrolyte metabolism disorders, and cystic fibrosis. Wearable technology for healthcare is not readily available to the public. One reason for this is that not many wearable devices for health monitoring have been approved. Furthermore, it is difficult to produce devices that can accurately measure biomarkers, easy to use, and comfortable to wear. A major concern associated with wearable technology has to do with the production and maintenance of large data sets. Especially with devices that take continuous measurements, large datasets will quickly be generated and will perpetually continue to grow. For epidemiological purposes, these large datasets are of great benefit. However, issues may arise when trying to maintain the security of the data, and there will need to be rigourous protocols in place to ensure that the rights of the individuals in the dataset are not violated. Furthermore, inaccurate data from wearable technology can result in researchers finding associations between biomarkers and disease that do not actually exist.

Overall, the development of sophisticated and validated biomarkers has been essential for the transition into precision medicine. However, there are still many obstacles that need to be overcome before precision medicine can be fully implemented into healthcare practice. Precision medicine implementation can be limited by every person involved in healthcare, including the patients, clinicians, academia, industry, regulatory bodies, and policy makes. From the patient perspective, social and cultural issues, including lack of access to reliable healthcare, will determine how effective precision medicine approaches will be. Furthermore, patients need to be able to trust and act on the results they receive from biomarker tests. Currently, genetic testing can give patients information about their risk of developing a specific disease. However, there has been evidence to show that even with this knowledge, patients are not likely to make any lifestyle or behavioural changes in response. Also, for the development of effective biomarkers to continue, patients need to be willing to participate in clinical trials. From the perspective of the clinician, there needs to be adaptations to how medicine is taught and practiced. Clinicians need to continuously be updating their knowledge on available biomarkers. Furthermore, clinicians need to be able to interpret biomarker test results and accurately communicate the results to patients. Continuous education may be difficult for some clinicians to maintain, especially in areas with shortages in healthcare workers. From an academia perspective, research needs to be able to filter out biomarkers that will be the most effective in clinical practice. For every different disease, there are many different possible biomarkers that can be explored. Pursuing biomarkers that have low probability of being clinically effective is a waste of the funding and resources. Furthermore, conducting studies with good experimental designs will produce data of better quality. Better quality data can allow researchers to make more accurate conclusions about the validity of the biomarker. From the perspective of industries, having an increased knowledge of biomarkers and their applications can greatly decrease production costs. This knowledge can allow drugs to be used for purposes other than the intended one. Currently, compared to the incentive to create more pharmaceuticals, incentive to create new biomarkers is very limited. Biomarkers are beginning to receive more approval from regulatory agencies, which could be a good opportunity for industries to capitalize on. From the perspective of regulatory bodies, a greater reliance on independent validation agencies could result in the reduced incidence of false claims. Increased funding to these types of regulatory agencies could allow them more power to enforce regulatory standards and better implement tools to educate researchers on these standards. From the perspective of policy makers, public health policies and practices need to adapt to match the objectives of precision medicine. Better assessment of disease prevalence and susceptibility can inform public health policies on health targets that will have the most positive impact on the population on a whole. On the other hand, a major goal for public health is to address that social determinants of health within a population and try to reduce the negative impact they may have on health. With the right policies in place, public health can direct precision medicine to focus not just on individuals who are sick, but towards the general wellbeing of the entire population.

In conclusion, biomarkers are an essential component in the introduction of precision medicine into healthcare. Genomics and digital biomarkers are key examples of how biomarkers can contribute to the tailoring of healthcare to individuals. These biomarkers are particularly useful in identifying individuals susceptible to certain diseases, directing treatments, and monitoring health over long periods of time. These biomarkers are not perfect, but there is continuous research into making biomarkers as effective as possible. Despite the influx of biomarker innovations, there are still barriers in the way of fully implementing precision medicine into healthcare systems. Each individual and entity that has contact with the healthcare system will have to make adjustments, so all people can receive maximum benefit from precision medicine.