Measuring the Turnover Rate of Clinically Important Plasma Proteins using an Automated SISCAPA Workflow

To the Editor:Today, the term “personalized medicine” is most frequently used to refer to performing “static tests” (e.g., genetic testing) to categorize patients into subgroups and to deliver tailored treatment(s). Although this approach has been effective where genetic mutations are linked to specific diseases, a more comprehensive personalization strategy is required when DNA analysis is not informative. This would entail establishing personal baseline levels for clinically important biomolecules (e.g., proteins) so that dynamic changes can be tracked over time, thus allowing personal health monitoring. We recently published a study in which 27 protein biomarkers were longitudinally monitored in dried blood specimens collected from individuals over 1 to 5 years (1). For some proteins, personalized baselines could be established using relatively infrequent sampling (weekly collections), whereas for others (e.g., C-reactive protein), determining accurate intraindividual biological variations required dense sampling. Although frequent sampling is currently impractical for most clinical uses, at a research level, it is important to explore whether frequent measurement of proteins and establishment of personal baselines would have diagnostic advantages over the conventional, population-based methods currently in practice. To conduct such research, the fundamental question becomes “What is the appropriate frequency …