N. Tidbury, J. Preston, W. Ding, J. Rivera‐Caravaca, F. Marín, G. Lip
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Utilizing biomarkers associated with cardiovascular events in atrial fibrillation: informing a precision medicine response
ABSTRACT Introduction Atrial fibrillation is the most common sustained cardiac rhythm disorder, which currently affects 1–2% of the global population. Furthermore, the incidence and prevalence of atrial fibrillation is rising. Biomarkers have the potential to improve clinical management of patients and therefore reduce the burden on health systems in the future. Areas covered A variety of pathways and mechanisms have been associated with atrial fibrillation. This paper provides an overview of a range of blood-based, imaging and genetic biomarkers that are associated with mechanisms and outcomes in atrial fibrillation and their potential use in a clinical setting. Expert commentary Atrial fibrillation is becoming increasingly prevalent. Current biomarkers associated with atrial fibrillation such as those involved in myocardial stress, inflammation, hemostasis and fibrosis do not currently provide much additional practical value beyond recommended scores based only on clinical risk factors.
期刊介绍:
Expert Review of Precision Medicine and Drug Development publishes primarily review articles covering the development and clinical application of medicine to be used in a personalized therapy setting; in addition, the journal also publishes original research and commentary-style articles. In an era where medicine is recognizing that a one-size-fits-all approach is not always appropriate, it has become necessary to identify patients responsive to treatments and treat patient populations using a tailored approach. Areas covered include: Development and application of drugs targeted to specific genotypes and populations, as well as advanced diagnostic technologies and significant biomarkers that aid in this. Clinical trials and case studies within personalized therapy and drug development. Screening, prediction and prevention of disease, prediction of adverse events, treatment monitoring, effects of metabolomics and microbiomics on treatment. Secondary population research, genome-wide association studies, disease–gene association studies, personal genome technologies. Ethical and cost–benefit issues, the impact to healthcare and business infrastructure, and regulatory issues.