Evidence map›Paper›PMID 30115926›Full record

ReviewTranslational psychiatry2018

Proteomics for blood biomarker exploration of severe mental illness: pitfalls of the past and potential for the future.

Ashley L Comes, Sergi Papiol, Thorsten Mueller, Philipp E Geyer, Matthias Mann, Thomas G Schulze

Abstract readReview
In one paragraph

Review in Translational psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 5 pooled it
–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

49 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Plasma proteomic profile of inflammatory depressive symptoms.Brain, behavior, & immunity - health · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Review
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.

Ashley L ComesInstitute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336, Munich, Germany. Ashley.Comes@med.uni-muenchen.de.ORCID http://orcid.org/0000-0001-6745-9834
Sergi PapiolInstitute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336, Munich, Germany.
Thorsten MuellerInstitute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336, Munich, Germany.
Philipp E GeyerDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Matthias MannDepartment of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany.
Thomas G SchulzeInstitute of Psychiatric Phenomics and Genomics (IPPG), University Hospital Munich, LMU, 80336, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent improvements in high-throughput proteomic approaches are likely to constitute an essential advance in biomarker discovery, holding promise for improved personalized care and drug development. These methodologies have been applied to study multivariate protein patterns and provide valuable data of peripheral tissues. To highlight findings of the last decade for three of the most common psychiatric disorders, namely schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), we queried PubMed. Here we delve into the findings from thirty studies, which used proteomics and multiplex immunoassay approaches for peripheral blood biomarker exploration. In an explorative approach, we ran enrichment analyses in peripheral blood according to these results and ascertained the overlap between proteomic findings and genetic loci identified in genome-wide association studies (GWAS). The studies we appraised demonstrate that proteomics for psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results constraining the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges for the implementation of proteomic signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of proteomics in mental disease diagnostics, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Indexed as

BiomarkersBiomedical ResearchGenetic LociGenome-Wide Association StudyHumansMental DisordersProteomicsBiomarkers

Identifiers

PMID30115926
PMCPMC6095863

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.