A biomarker, in the most general sense, is an indicator or predictor of a biological state. For research purposes, it must be readily measurable, sensitive but not too sensitive—the high-sensitivity C-Reactive Protein (hsCRP) can literally be elevated if a patient stubs his toe hard—and capable of reliably representing something about the character of a factor, i.e., a nutrient, a physiologic process, or a disease prognosis that has known implications for health and/or disease variables.
There are many biomarkers that may be pertinent to diet and disease. They have three basic functions: indicate the biological plausibility of a diet–disease relationship, improve the assessment of relative risk, and serve as surrogate end-points (Schatzkin, 2006). Often-used biomarkers include various plasma lipoproteins, folic acid and homocysteine, blood pressure, various microorganisms (e.g., Helicobacter pylori, human papillomavirus infection, or the Iraqi genotype Acinetobacter baumanni), oxidative stress variables (e.g., nitric oxide and other reactive oxygen species), intima-media thickness of the carotid wall, elasticity of the radial artery, or a vast array of proteomic compounds (e.g., cytokines involved in inflammatory and anti-inflammatory responses).
To illustrate the anatomy of a biomarker, let us consider diabetes. With the well-intentioned single assessment, the distinct identifi cation of type I and type II diabetes has blurred. The assessment of hyperglycemia using traditional but inadequate biomarkers (serum glucose, hemoglobin A1C, and serum triglycerides) has highlighted the critical need for markers that distinguish the clinically meaningful stages of what may well be a spectrum of diabetes pathology, one that encompasses many more subtypes of the disease with far-more-involved etiologies and trajectories than the simplistic model of only two broad themes.
The food industry, in its effort to provide more-healthful choices in the functional foods arena, must consider more-illuminating biomarkers that punctuate the much larger and exquisitely complex constellation of factors representing our emerging knowledge of the progression of disease states.
As we examine the mechanisms of disease progression and the role of diet in augmenting health, it becomes paramount that we realize fundamental processes. For example, if up-regulation of inflammatory or pro-inflammatory cytokine production offers targets in and of themselves while simultaneously allowing a readily assay-able means of tracking the pathological process and the response to intervention, then a powerful and multidimensional concept has been identified. This may indeed embody the famous “paradigm shift” postulated by Kuhn (1996)—a shift in thinking, vocabulary, and method which can transform an entire field of health evaluation and disease assessment.
If we produce and standardize what we believe are health-related nutrients that can be incorporated into food, then our task will be ideally to select a biomarker that serves both as intervention target and as “barometer” of intervention efficacy and health status or of disease progression.
Next, let us consider the food industry’s inexorable shift to a “medical–industrial complex.” From functional foods to performance nutrition, the fight against obesity, digestive health, heart health, diabetes, women’s health, men’s health, and aging, we are engaging a clear priority on health promotion and disease risk reduction.
Along with this movement is the absolute ethical and legal requirement that we scientifically support any health claims we make for our products. How is this to be accomplished in the context of generic products and processes far more biologically complex than pharmaceuticals and medical devices?
The answer is that we define and apply what may turn out to be a new generation of biomarkers. We embed the appropriate biomarker in experimental design, methodology, and data analysis tailored to food and nutrition and the associated likely character of health impacts.Naturally, when specifying a biomarker, it is important to understand how it fits with nutritional exposure or intake, time frame, sampling, specimen collection, storage, the model system under study (i.e., human, other primate, rodent, or dogfish), laboratory/instrument error, biologic variation, and the analytic quality control.
by Roger Clemens , Dr.P.H.,
Special Projects Advisor, ETHorn, La Mirada, Calif.
Peter Pressman, M.D.,
Attending Staff, Internal Medicine, Cedars-Sinai Medical Center, Los Angeles, Calif.
Kuhn, T.S. 1996. “The Structure of Scientific Revolutions,” 3rd ed. University of Chicago Press, Chicago.
Schatzkin, A. 2006. Promises and perils of validating biomarkers for cancer risk. J. Nutr. 136: 2671S-72S.