Exploring a Cancer Biomarker: The Example of C-Reactive Protein

Abstract

An elevated plasma level of C-reactive protein (CRP) is an established biomarker of increased risk of cardiovascular diseases and diabetes ( 1 , 2 ). An association has also been suggested between plasma CRP level and the risk of cancer, particularly lung and colon cancers; however, the evidence is inconclusive because of the lack of large-scale prospective studies in which CRP levels were measured in healthy individuals before the onset of the disease ( 3 ). One explanation for why CRP may identify individuals at increased risk of disease lies in its association with chronic — mostly subclinical — inflammation. There is also some evidence that CRP may act as active contributor to inflammation, and this activity may depend on the conformation of the protein ( 4 ). Whether CRP is only a biomarker or an active player in inflammation might have important clinical implications. The study by Allin et al. ( 5 ) in this issue of the Journal addresses precisely the role of CRP as a biomarker vs as a contributor to carcinogenesis. The study is an elegant example of how genetic variants that have a functional impact can be used to explore associations between environmental factors and disease, and specifi cally to identify and control for confounding factors, based on the approach that has become known as Mendelian randomization, a term fi rst used by Gray and Wheatley in 1991 in the context of treatment of childhood leukemia ( 6 ). The basic principle of Mendelian randomization is that if a genetic variant infl uences a nongenetic (ie, environmental) factor that is relevant to disease risk, and if the same variant has no other associations with the same disease, then the variant predicts disease risk through its infl uence on the risk factor. Therefore, genetic variants with well-characterized functions (or that are in linkage disequilibrium with other variants with a well-characterized function) can be used to characterize associations between environmental factors and disease risk ( 7 ). Furthermore, using genetic variants instead of their environmental counterparts ensures protection from confounding and reverse causality and — at least in some cases — allows one to assess the effect of long-term exposures. The requirements for Mendelian randomization to be useful (strong functional signifi cance of the variant and the absence of an effect on other pathways) are demanding and are not often fulfi lled. There are examples, however, in which the analysis of genetic variants has helped to elucidate the role of environmental exposures, such as polymorphisms in genes encoding alcoholmetabolizing enzymes that explain the possible protective role of alcohol intake in cardiovascular disease as well as its detrimental role in pregnancy outcomes ( 8 , 9 ). The Mendelian randomization approach would be particularly valuable in the case of environmental factors that are not easily measurable.