title: Inter-individual variation in expression: a missing link in biomarker biology?
abstract: The past decade has seen an explosion of variation data demonstrating that diversity of both protein-coding sequences and of regulatory elements of protein-coding genes is common and of functional importance. In this article, we argue that genetic diversity can no longer be ignored in studies of human biology, even research projects without explicit genetic experimental design, and that this knowledge can, and must, inform research. By way of illustration, we focus on the potential role of genetic data in case-control studies to identify and validate cancer protein biomarkers. We argue that a consideration of genetics, in conjunction with proteomic biomarker discovery projects, should improve the proportion of biomarkers that can accurately classify patients.
authors.affiliation: University Hall, National University of Singapore, 119077 Singapore. Peter.Little@nus.edu.sg
authors.forename: Peter F R
authors.initials: PF
authors.lastname: Little
authors.forename: Rohan B H
authors.initials: RB
authors.lastname: Williams
authors.forename: Marc R
authors.initials: MR
authors.lastname: Wilkins
mesh_terms: D001695:Biology / Q000639:trends*; D019143:Evolution, Molecular; D015870:Gene Expression / Q000235:genetics*; D005786:Gene Expression Regulation / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics*; D014644:Genetic Variation / Q000235:genetics*; D020543:Proteome / Q000235:genetics*
chemical_list: D005819:Genetic Markers; D020543:Proteome