Literature DB >> 20155362

Is the word 'biomarker' being properly used by proteomics research in neuroscience?

Daniel Martins-de-Souza.   

Abstract

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Year:  2010        PMID: 20155362      PMCID: PMC2953633          DOI: 10.1007/s00406-010-0105-2

Source DB:  PubMed          Journal:  Eur Arch Psychiatry Clin Neurosci        ISSN: 0940-1334            Impact factor:   5.270


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Lately, when researchers see an article with the word “biomarker”, they feel, at least, suspicious. Sometimes, even scared and such feeling of distrust occurs mostly because the majority of the published articles in the field of global proteome analysis are revealing, for instance, differentially expressed proteins in pathologic conditions and claiming that biomarkers are being discovered. In addition to transform a differentially expressed protein in a biomarker, a long road has to be travelled. Biomarker is defined by the United States Food and Drug Administration (FDA) as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic or pathogenic processes or pharmacological responses to a therapeutic intervention” [1]. Such definition is, indeed, quite specific and very different from a differentially expressed protein discovered as potentially related to some disease in a small set of sample. Therefore, researchers are totally correct regarding their suspicions. Searching at PubMed database (31 Dec 2009), the word “biomarker” returns 477,273 different articles that have exponentially increased in the recent years (Fig. 1a). If the words “biomarker and proteomics (or proteome)” are searched, we can also realize a massive number of articles in the past 13 years (30,719 articles), and an exponential increase in the number of lately published articles (Fig. 1b). Searching the word “biomarker” from 1996 to 2009 (1996 was when the first article of proteomics (or proteome) and biomarker was published), we can find 342,751 articles, which means that proteomics research have published 8.96% of the articles which contains “biomarker” as keyword. This huge number of articles is very far to be at same proportion to the number of the recently discovered biomarkers that are useful to disease diagnosis, indicators of disease status, or targets to monitor and predict response to therapeutics or disease outcome and such data show us that a better definition for differentially expressed proteins with potential to be biomarkers has to be implemented, to leave the word “biomarker” to its own and well-defined meaning, avoiding the misuse of the term.
Fig. 1

a "Biomarker" b "Proteomic or proteomics or proteome and biomarker" on PubMed 

a "Biomarker" b "Proteomic or proteomics or proteome and biomarker" on PubMed Recently, researchers have been used safer terms such as “potential biomarker” or “biomarker candidate” for proteins differentially expressed in diseased conditions that might have a potential as biomarker. I would propose that the correct term for most of developed research regarding biomarker discover based on the most of published articles not only for proteomics, but also in transcriptome and association studies, would be “potential biomarker candidate” (PBC). Why such name? Considering a differential proteome analysis comparing healthy and diseased tissue, differentially expressed protein will be found by high throughput and semi-automatic proteomics methods. At this point, I would say we would have a simple “biomarker candidate”, which means something far, at least two levels away from a real biomarker. The biomarker candidates need to be validated in a greater and statistically significant universe of individual samples using distinct methodologies such as Western blot, ELISA or single and multiple reaction monitoring (SRM or MRM). If such proteins are indeed validated as differentially expressed, then we would have a second level of candidate, which I would call PBC. And we are clearly aware that for a PBC reach the “biomarker” level, many other steps must be climbed, using different parameters and technologies, studying different sets of samples, considering potential confounding factors. A good review for that can be found at Mischak et al. [2] and its references. Sets of adequate standards to proteomics studies for biomarker discovery have been already proposed, applied in proteome research [2] and required by proteomics journals. Now, we need to define to “potential biomarkers” or “biomarker candidates” a better and clearer term or name that could really be distinct from “biomarker”, that has its own and well-defined meaning. For most of clinical proteomics studies, I believe that PBC would be a considerable suggestion. This way, it would be possible to clearly separate PBC from biomarker, two entities that have very different concepts and distinct values. Moreover, an adequate nomenclature would facilitate the judgment of the researchers and reviewers, who may feel more comfortable to read PBC instead biomarker in clinical proteomics studies.
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1.  Clinical proteomics: A need to define the field and to begin to set adequate standards.

Authors:  Harald Mischak; Rolf Apweiler; Rosamonde E Banks; Mark Conaway; Joshua Coon; Anna Dominiczak; Jochen H H Ehrich; Danilo Fliser; Mark Girolami; Henning Hermjakob; Denis Hochstrasser; Joachim Jankowski; Bruce A Julian; Walter Kolch; Ziad A Massy; Christian Neusuess; Jan Novak; Karlheinz Peter; Kasper Rossing; Joost Schanstra; O John Semmes; Dan Theodorescu; Visith Thongboonkerd; Eva M Weissinger; Jennifer E Van Eyk; Tadashi Yamamoto
Journal:  Proteomics Clin Appl       Date:  2007-01-22       Impact factor: 3.494

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Authors:  Nenad Vasic; Bernhard J Connemann; Robert C Wolf; Hayrettin Tumani; Johannes Brettschneider
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Authors:  Erich Castro-Dias; André S Vieira; Claudio C Werneck; Francesco Langone; José C Novello; Daniel Martins-de-Souza
Journal:  J Neural Transm (Vienna)       Date:  2010-04-13       Impact factor: 3.575

Review 3.  Proteomic approaches to predict bioavailability of fatty acids and their influence on cancer and chronic disease prevention.

Authors:  Baukje de Roos; Donato F Romagnolo
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4.  Cerebrospinal fluid diagnostics in first-episode schizophrenia.

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Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2012-08-30       Impact factor: 5.270

6.  Proteomics as a tool for understanding schizophrenia.

Authors:  Daniel Martins-de-Souza
Journal:  Clin Psychopharmacol Neurosci       Date:  2011-12-31       Impact factor: 2.582

Review 7.  The potential of biomarkers in psychiatry: focus on proteomics.

Authors:  Izabela Sokolowska; Armand G Ngounou Wetie; Kelly Wormwood; Johannes Thome; Costel C Darie; Alisa G Woods
Journal:  J Neural Transm (Vienna)       Date:  2013-12-20       Impact factor: 3.575

8.  Biomarkers, population-based studies and a proof of principle investigation in pharmacotherapy.

Authors:  P Falkai; H-J Möller
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2010-10       Impact factor: 5.270

9.  Mapping CSF biomarker profiles onto NIA-AA guidelines for Alzheimer's disease.

Authors:  Panagiotis Alexopoulos; Jennifer Roesler; Nathalie Thierjung; Lukas Werle; Dorothea Buck; Igor Yakushev; Lena Gleixner; Simone Kagerbauer; Marion Ortner; Timo Grimmer; Hubert Kübler; Jan Martin; Nikolaos Laskaris; Alexander Kurz; Robert Perneczky
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2015-08-08       Impact factor: 5.270

10.  Heart-type fatty acid binding protein and vascular endothelial growth factor: cerebrospinal fluid biomarker candidates for Alzheimer's disease.

Authors:  Liang-Hao Guo; Panagiotis Alexopoulos; Robert Perneczky
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2013-04-17       Impact factor: 5.270

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