Identifying Low-Abundance Biomarkers

B iomarkers are clinical, molecular, or image-based measurable parameters that can characterize an individual’s specific biological state, whether normal, pathological, or in response to treatment. A biomarker is considered of clinically valuable if (1) it can be measured repeatedly with accuracy and relatively rapid clinical turnaround, (2) it provides unique, superior information on patient status, and (3) it aids in clinical decision making with high precision.1 High-quality biomarkers can critically inform clinical diagnosis (eg, high-sensitivity troponin for acute myocardial infarction) and guide therapy (eg, CYP2C19 status for clopidogrel therapy). The ideal biomarkers can further reveal underlying biological processes, inform therapeutic deployment, and pave the way for true personalized precision medicine. In this issue of Circulation, Ngo et al2 demonstrate the use of a developing proteomics technology to rapidly screen for protein biomarkers in patients with planned and spontaneous myocardial infarcts. How valuable are new, additional biomarkers in cardiovascular medicine? The current medical literature is replete with publications on biomarkers in cardiovascular medicine. A search of the PubMed database revealed 6421 articles on biomarkers and cardiovascular disease in 2015 alone. Unfortunately, despite the wealth of publications, truly high-value biomarkers that are etiologically specific, reproducibly validated in multiple populations, and informative in decision making, and that can be implemented in clinical care are very few indeed. As highlighted in the most recent guidance on personalized medicine for cardiovascular disease from the Food and Drug Administration, the need for high-value, validated biomarkers to guide treatment development is now more urgent than ever.3 Advances in systems biology over the past decade have provided more opportunities for innovative discovery of biomarkers than ever before. These advances range from identifying disease-causing genes using deep genome sequencing, the characterization of mRNA, microRNA, and noncoding RNAs through RNA-Seq, and profiling the expressed proteins and their modified states through deep proteomics. For common conditions such as hypertension, coronary disease, or heart failure, the individual genetic influences are relatively small. Analysis of the expressed genome, integrating environmental imprint and influence, such as RNA or proteins, will likely be more fruitful. By using an integrated approach, one can begin to understand the precise interactions of susceptibility, environmental epigenetic regulation, and functional protein production and turnover, which can be potentially detected as a biomarker, to relate to the individual’s phenome and ultimately disease outcome.4 Proteomics, however, is perhaps the most challenging of the different systems biology approaches, given the complexity of the human proteome. For each expressed gene, there can be tens to hundreds of expressed protein variations, and, with posttranslational modifications, there is another order of magnitude of complexity. Many important signaling or regulatory proteins have concentrations in the Identifying Low-Abundance Biomarkers