title: System-wide peripheral biomarker discovery using information theory.
abstract: The identification of reliable peripheral biomarkers for clinical diagnosis, patient prognosis, and biological functional studies would allow for access to biological information currently available only through invasive methods. Traditional approaches have so far considered aspects of tissues and biofluid markers independently. Here we introduce an information theoretic framework for biomarker discovery, integrating biofluid and tissue information. This allows us to identify tissue information in peripheral biofluids. We treat tissue-biofluid interactions as an information channel through functional space using 26 proteomes from 45 different sources to determine quantitatively the correspondence of each biofluid for specific tissues via relative entropy calculation of proteomes mapped onto phenotype, function, and drug space. Next, we identify candidate biofluids and biomarkers responsible for functional information transfer (p < 0.01). A total of 851 unique candidate biomarkers proxies were identified. The biomarkers were found to be significant functional tissue proxies compared to random proteins (p < 0.001). This proxy link is found to be further enhanced by filtering the biofluid proteins to include only significant tissue-biofluid information channels and is further validated by gene expression. Furthermore, many of the candidate biomarkers are novel and have yet to be explored. In addition to characterizing proteins and their interactions with a systemic perspective, our work can be used as a roadmap to guide biomedical investigation, from suggesting biofluids for study to constraining the search for biomarkers. This work has applications in disease screening, diagnosis, and protein function studies.
authors.affiliation: Division of Health Sciences and Technology, Harvard University/Massachusetts Institute of Technology, Cambridge, MA, USA.
authors.forename: Gil
authors.initials: G
authors.lastname: Alterovitz
authors.forename: Michael
authors.initials: M
authors.lastname: Xiang
authors.forename: Jonathan
authors.initials: J
authors.lastname: Liu
authors.forename: Amelia
authors.initials: A
authors.lastname: Chang
authors.forename: Marco F
authors.initials: MF
authors.lastname: Ramoni
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D001826:Body Fluids / Q000737:chemistry; D019295:Computational Biology; D005260:Female; D006801:Humans; D007257:Information Theory; D008297:Male; D015233:Models, Statistical; D011247:Pregnancy; D040901:Proteomics / Q000706:statistics & numerical data; D014018:Tissue Distribution
chemical_list: D015415:Biomarkers