In the past century, the broad use of routine diagnostic assays in the clinical laboratory was a major advance that remains a core element of contemporary patient care. As quantitative, objective measurements, these routine clinical tests often provide unequivocal evidence for a diagnosis or help frame a therapeutic strategy. The development of specific laboratory tests is generally predicated on a plausible biological hypothesis grounded in (pre)clinical experimentation. As a result, the majority of routine laboratory tests are limited in number and sufficiently well understood by practitioners to be clinically useful. In the past few years, the biomedical community has witnessed an increasing number of reports of associations between a wide range of newer molecular markers and disease phenotypes (pathophenotypes) or outcomes. These biomarkers—here broadly defined as molecular indicators of the presence of a disease, outcome, or response to therapy—include conventional laboratory measurements of proteins or enzymes, recently identified genetic polymorphisms (either singly [single nucleotide polymorphisms, or SNPs] or in combinations [haplotypes]), and plasma metabolites, peptides, or proteins, many with as yet unknown function. In contrast to the earlier era of biochemical testing, these contemporary biomarkers are generally not identified by hypothesis-driven, preclinical experimentation and the application of rational, reductionist principles; rather, they reflect the output of the brute-force forms of discovery science, viz , comparative total genome scanning, global proteomic analysis, and comprehensive metabolomic testing between populations with and without a well-defined disease phenotype. With the use of technically sophisticated molecular methods, the entire human genome or the plasma proteome, for example, is analyzed in some detail to identify changes in gene sequence or protein patterns, respectively, that are more or less prevalent in those with disease than in those without disease. The magnitude of the observed difference in prevalence of the biomarker between the 2 populations defines the strength …