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Theory of signs and statistical approach to big data in assessing the relevance of clinical biomarkers of inflammation and oxidative stress

Abstract:
Biomarkers are widely used not only as prognostic or diagnostic indicators, or as surrogate markers of disease in clinical trials, but also to formulate theories of pathogenesis. We identify two problems in the use of biomarkers in mechanistic studies. The first problem arises in the case of multifactorial diseases, where different combinations of multiple causes result in patient heterogeneity. The second problem arises when a pathogenic mediator is difficult to measure. This is the case of the oxidative stress (OS) theory of disease, where the causal components are reactive oxygen species (ROS) that have very short half-lives. In this case, it is usual to measure the traces left by the reaction of ROS with biological molecules, rather than the ROS themselves. Borrowing from the philosophical theories of signs, we look at the different facets of biomarkers and discuss their different value and meaning in multifactorial diseases and system medicine to inform their use in patient stratification in personalized medicine.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1073/pnas.1719807115

Authors


More by this author
Role:
Author
ORCID:
0000-0003-0911-8358
More by this author
Role:
Author
ORCID:
0000-0001-7790-3003
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Oxford Internet Institute
Role:
Author
ORCID:
0000-0002-5444-2280


Publisher:
National Academy of Sciences
Journal:
Proceedings of the National Academy of Sciences More from this journal
Volume:
115
Issue:
10
Pages:
2473-2477
Publication date:
2018-02-20
Acceptance date:
2018-01-24
DOI:
EISSN:
1091-6490
ISSN:
0027-8424
Pmid:
29463702


Language:
English
Keywords:
Pubs id:
pubs:826664
UUID:
uuid:46c603fc-67e3-4896-ab53-e4b392b83d92
Local pid:
pubs:826664
Source identifiers:
826664
Deposit date:
2018-08-27

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