Precision medicine is the practice of tailoring medical management to each patient's unique traits - genetics, lifestyle, environment, and medical history. Over the last decade, the field of precision medicine has grown in tandem with advances in genetic research, data analytics, and cognitive computing in the health information technology sector.
Precision medicine is a new method of preventing and treating disease that considers the individual characteristics of each patient, such as their genetics, lifestyle, environment, and medical history. As described by the President's Council of Advisors on Science and Technology: "[...] the tailoring of medical treatment to the individual characteristics of each patient, the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment […]". With this approach, medical professionals and researchers can predict more accurately which disease-specific treatments and preventative measures will benefit specific populations, potentially sparing expenses and side effects.
Precision medicine comprises healthcare providers, patients, laboratories, and researchers. They collaborate to form a healthcare delivery model that strongly relies on a combination of patient data, specific analysis, and multifactorial research to prevent and treat diseases. Collections of genomic data from biospecimens create a strong ecosystem that may aid in disseminating information to other healthcare specialties.
Even though "precision medicine" is relatively new, the idea has long been present in healthcare, initially focusing on cancer and pharmacotherapy from its inception in the early 2000s to its explosion recently with the progression of data analytic techniques and artificial intelligence. The use of precision medicine in day-to-day clinical practice is limited, but it will spread to a wide range of health and healthcare in the coming years.
Precision medicine has several uses that benefit patient care throughout their lifetime. Next-generation sequencing allows for rapid and accurate analysis of an individual's genetic code. This information can then be used to identify specific genetic mutations or variations that may influence a person's risk of developing certain diseases and their response to different treatments. In the current era, genetic screening is utilized before pregnancy to determine the likelihood of transferring congenital abnormalities to future generations. A pregnant woman can undergo whole genome sequencing of the baby or genetic testing to detect chromosomal abnormalities of the fetus between 8 and 12 weeks of pregnancy. Sequencing at birth can quickly identify severe diseases for which there may be treatable remedies that lower morbidity and death. Early concepts of precision medicine have also been applied with artificial intelligence to study pregnancy and its effect on the cardiovascular system, finding that AI-based electrocardiograms may help predict post-partum heart failure.
The evolution of advanced precision medicine in cardiology has led to the discovery of a broad range of novel biomarkers associated with the progression of cardiovascular disease. These biomarkers may improve risk assessment, decrease cardiovascular morbidity and mortality, and are important diagnostic tools in clinical practice. For example, ST2 cardiac biomarker (also known as soluble interleukin 1 receptor-like 1 with transmembrane) has been suggested as a potential tool to assess for allograft rejection in heart transplant recipients. Soluble ST2 (sST2) is a biomarker of inflammation and fibrosis. Elevated sST2 levels (35 ng/mL) are linked to worse outcomes in heart failure patients. Troponin T and I molecules have amino acid sequences unique to cardiac tissue, making their assays extremely specific for detecting cardiac tissue injury. While troponin tests have improved in analytical sensitivity and precision over time, they offer a substantial advance in laboratory testing. They will help providers quickly diagnose patients with suspected acute coronary syndromes when appropriately applied.
In patients with advanced heart failure and more acute needs, the field of transplant medicine has grown to incorporate precision medicine to help patients survive longer, fuller lives. Gene expression profiling (GEP) is a key technology that has enabled the development of precision medicine in heart transplantation. GEP has evolved from tissue analysis to blood sample testing.
This information can help providers determine if the transplanted organ is at risk of rejection or if the patient is at risk of developing complications such as future coronary artery disease in the transplanted organ – a unique process that, once it begins, is difficult to control. Temporal monitoring of serial GEP samples allows providers to optimize medical regimens and other aspects of care – such as diabetic status, lipid management, and optimization of cardiopulmonary rehabilitation. This pluripotent effect of GEP is an example of the broad-reaching implications of using precision medicine.
Precision medicine in heart transplantation is also being applied to selecting donor hearts. Donor hearts that are well-matched to the recipient regarding blood type and tissue compatibility are more likely to be successful. However, genetic differences between the donor and recipient can also play a role in the transplant's success. Gene expression profiling and other molecular techniques can help identify donor hearts that are a good match for the recipient at the genetic level, improving the likelihood of a successful transplant.
Using molecular imaging techniques in diagnostic imaging, such as strain pattern mapping in echocardiography, is a promising method that enables providers to assess the heart muscle's health precisely and repeatedly. Strain pattern mapping can thoroughly evaluate heart muscle function by measuring the strain, or distortion, as it contracts and relaxes. The method builds a map of the strain patterns in the heart muscle by analyzing the echocardiographic images using specialized software. Heart failure, ischemic heart disease, and valvular heart disease are just a few cardiovascular disorders that can be diagnosed and tracked using this data.
For instance, strain pattern mapping can detect early heart muscle alterations in people more likely to experience adverse cardiovascular events, including heart attacks and heart failure. Providers can intervene with lifestyle changes, medications, or other treatments to avoid or delay the beginning of these events. In using this technique to identify patients with early indications of cardiovascular disease, with the ability to track them over time, both prevention and response are capable – with specificity to the individual patient.
A plethora of technology is in the pipeline and continues to be innovated upon. Ultimately, the future of healthcare is very promising because of advanced precision medicine. We can increase the accuracy of diagnoses, maximize treatment results, and ultimately improve our patients' overall health and well-being by customizing treatments to each patient's particular characteristics. We may anticipate even more fascinating developments in precision medicine as the industry develops innovative technology.
References:
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4. Goswami, Rohan. “The current state of artificial intelligence in cardiac transplantation.” Current opinion in organ transplantation vol. 26,3 (2021): 296-301. doi:10.1097/MOT.0000000000000875
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6. Grupper, Avishay, et al. “Elevated ST2 Levels Are Associated with Antibody-Mediated Rejection in Heart Transplant Recipients.” Clinical Transplantation, vol. 32, no. 9, 2018, doi:10.1111/ctr.13349
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Dr. Desai was born in Gujarat, India, and raised in Troy, Michigan. She is a graduate of the Surat Municipal Institute of Medical Education and Research. She is currently a Research Fellow at the Mayo Clinic in Jacksonville Florida’s Division of Advanced heart failure and Transplantation. She looks forward to a promising career as a cardiologist in the future as she hopes to begin her Residency training in internal medicine in 2023.
Dr. Goswami is a Transplant Cardiologist practicing at Mayo Clinic in Florida. He is a graduate of the American University of the Caribbean School of Medicine and completed his internal medicine residency at Columbia University College of Physicians and Surgeons – Stamford Hospital, a cardiology fellowship at The University of Tennessee Memphis, and a Transplant Fellowship in 2017 at Mayo Clinic in Florida. He has a keen interest in clinically focused artificial intelligence research to improve outcomes in patients with advanced heart failure. He has published articles in the field of both heart transplantation and artificial intelligence, as well as presented at Ai4 in 2020 on the future impact of AI in healthcare and invited lectures at the International Society of Heart and Lung Transplantation in both 2021 and 2022. He looks forward to one day utilizing AI integration to prevent organ failure.
Smit Paghdar, M.B.B.S. is an Advanced Heart Failure and Transplant Cardiology division Research Fellow at the Mayo Clinic in Jacksonville, Florida. Dr. Paghdar was born in Gujarat, India, and received his medical degree from the Surat Municipal Institute of Medical Education and Research (SMIMER). He looks forward to a promising career as a cardiologist in the future as he hopes to begin his Residency training in internal medicine in 2023.
