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

Journal

TRANSLATIONAL PSYCHIATRY
Volume 8, Issue -, Pages -

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/s41398-018-0219-2

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Funding

  1. Max Planck Society
  2. European Union's Horizon 2020 research and innovation program [686547]
  3. Novo Nordisk Foundation [NNF15CC0001]
  4. Deutsche Forschungsgemeinschaft (DFG) [SCHU 1603/4-1,, SCHU 1603/5-1, SCHU 1603/7-1]
  5. German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders), under the e:Med Programme [01ZX1614K]
  6. German Federal Ministry of Education and Research (BMBF) [01EE1404H]
  7. 2016 NARSAD Young Investigator Grant from the Brain and Behavior Research Foundation [25015]
  8. DFG [MU 3525/3-1]
  9. Mercur [Pr-2016-0010]

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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.

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