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Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia

Overview of attention for article published in Journal of Neural Transmission, May 2014
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Title
Multiplatform metabolome and proteome profiling identifies serum metabolite and protein signatures as prospective biomarkers for schizophrenia
Published in
Journal of Neural Transmission, May 2014
DOI 10.1007/s00702-014-1224-0
Pubmed ID
Authors

Khaled Al Awam, Ida Sibylle Haußleiter, Ed Dudley, Rossen Donev, Martin Brüne, Georg Juckel, Johannes Thome

Abstract

Schizophrenia is a severe mental illness with a biological basis. However, the search for reliable biomarkers suitable for clinical routine has been futile so far. Accordingly, there is a need for innovative approaches such as genomics and proteomics to achieve this goal. In the present study, we compared metabolomic and proteomic data from 26 schizophrenia patients as well as from unaffected controls carefully matched for age and gender in a multi-platform approach. The combined analysis identified many signatures with initially good biomarker characteristics. After statistical analysis and comparison of these identified serum metabolites (analysed by Gas Chromatography Mass Spectrometry) and hydrophobic serum proteins (analysed by matrix-assisted laser desorption ionisation mass spectrometry), several markers (e.g., 2-piperidinec carboxylic acid, 6-deoxy-mannofuranose, galactoseoxime and a serum peptide of m/z 3177) were determined as having the best discriminating value between the groups. Our findings represent a proof of principle indicating that metabolomic and proteomic approaches can be successfully used in psychiatric biomarker research, even though the results should be regarded as preliminary with a need for replication in larger samples.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 297 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Poland 1 <1%
Germany 1 <1%
Unknown 295 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 193 65%
Student > Master 16 5%
Other 13 4%
Researcher 10 3%
Student > Ph. D. Student 10 3%
Other 16 5%
Unknown 39 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 19%
Chemistry 41 14%
Biochemistry, Genetics and Molecular Biology 36 12%
Medicine and Dentistry 21 7%
Engineering 21 7%
Other 72 24%
Unknown 49 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 April 2016.
All research outputs
#20,166,456
of 25,654,806 outputs
Outputs from Journal of Neural Transmission
#1,435
of 1,868 outputs
Outputs of similar age
#170,314
of 242,798 outputs
Outputs of similar age from Journal of Neural Transmission
#13
of 23 outputs
Altmetric has tracked 25,654,806 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,868 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.