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Review
. 2017 Aug;24(3):229-239.
doi: 10.1016/j.spen.2017.08.001. Epub 2017 Aug 12.

Promise, Progress, and Pitfalls in the Search for Central Nervous System Biomarkers in Neuroimmunological Diseases: A Role for Cerebrospinal Fluid Immunophenotyping

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Review

Promise, Progress, and Pitfalls in the Search for Central Nervous System Biomarkers in Neuroimmunological Diseases: A Role for Cerebrospinal Fluid Immunophenotyping

Bibiana Bielekova et al. Semin Pediatr Neurol. 2017 Aug.

Abstract

Biomarkers are central to the translational medicine strategic focus, though strict criteria need to be applied to their designation and utility. They are one of the most promising areas of medical research, but the "biomarker life-cycle" must be understood to avoid false-positive and false-negative results. Molecular biomarkers will revolutionize the treatment of neurological diseases, but the rate of progress depends on a bold, visionary stance by neurologists, as well as scientists, biotech and pharmaceutical industries, funding agencies, and regulators. One important tool in studying cell-specific biomarkers is multiparameter flow cytometry. Cerebrospinal fluid immunophenotyping, or immune phenotypic subsets, captures the biology of intrathecal inflammatory processes, and has the potential to guide personalized immunotherapeutic selection and monitor treatment efficacy. Though data exist for some disorders, they are surprisingly lacking in many others, identifying a serious deficit to be overcome. Flow cytometric immunophenotyping provides a valuable, available, and feasible "window" into both adaptive and innate components of neuroinflammation that is currently underutilized.

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Conflict of interest statement

Disclosure of interests: B.B. is co-inventor on the U.S. Patent Application No. 62/038,530: Biomarkers for Diagnosis and Management of Neuroimmunological Diseases, but received no financial gains from this patent. M.P. has no commercial, proprietary, or financial interest in any products or companies described in this article.

Figures

Figure 1
Figure 1
Understanding a biomarker life-cycle
Figure 2
Figure 2
Adjustment of biomarker levels based on mechanistic understanding of its lifecycle

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