Evidence map›Paper›PMID 36380380›Full record

ReviewBiomarker research2022

Bioinformatics tools and data resources for assay development of fluid protein biomarkers.

Katharina Waury, Eline A J Willemse, Eugeen Vanmechelen, Henrik Zetterberg, Charlotte E Teunissen, Sanne Abeln

Abstract readReview
In one paragraph

Review in Biomarker research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Data-driven evaluation of suitable immunogens for improved antibody selection.Protein science : a publication of the Protein Society · 2025
    Article
  3. Review
  4. Decision Tree for Protein Biomarker Selection for Clinical Applications.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Katharina WauryIBIVU - Center for Integrative Bioinformatics, Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-8570-7640
Eline A J WillemseDepartments of Biomedicine and Neurology, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0001-9140-4243
Eugeen VanmechelenADx NeuroSciences, Ghent, Belgium.ORCID http://orcid.org/0000-0002-9466-5366
Henrik ZetterbergDepartment of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.ORCID http://orcid.org/0000-0003-3930-4354
Charlotte E TeunissenDepartment of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands.ORCID http://orcid.org/0000-0002-4061-0837
Sanne AbelnIBIVU - Center for Integrative Bioinformatics, Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. s.abeln@vu.nl.ORCID http://orcid.org/0000-0002-2779-7174

Funding

European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 860197
6 · The paper itself

Abstract

Fluid protein biomarkers are important tools in clinical research and health care to support diagnosis and to monitor patients. Especially within the field of dementia, novel biomarkers could address the current challenges of providing an early diagnosis and of selecting trial participants. While the great potential of fluid biomarkers is recognized, their implementation in routine clinical use has been slow. One major obstacle is the often unsuccessful translation of biomarker candidates from explorative high-throughput techniques to sensitive antibody-based immunoassays. In this review, we propose the incorporation of bioinformatics into the workflow of novel immunoassay development to overcome this bottleneck and thus facilitate the development of novel biomarkers towards clinical laboratory practice. Due to the rapid progress within the field of bioinformatics many freely available and easy-to-use tools and data resources exist which can aid the researcher at various stages. Current prediction methods and databases can support the selection of suitable biomarker candidates, as well as the choice of appropriate commercial affinity reagents. Additionally, we examine methods that can determine or predict the epitope - an antibody's binding region on its antigen - and can help to make an informed choice on the immunogenic peptide used for novel antibody production. Selected use cases for biomarker candidates help illustrate the application and interpretation of the introduced tools.

Indexed as

AntibodyBioinformaticsBiomarkerDementiaImmunoassay

Identifiers

PMID36380380
PMCPMC9667682

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.