Identification of targeted analyte clusters for studies of schizophrenia


The search for biomarkers to diagnose psychiatric disorders such as schizophrenia has been underway for decades. Many molecular profiling studies in this field have focused on identifying individual marker signals that show significant differences in expression between patients and the normal population. However, signals for multiple analyte combinations that exhibit patterned behaviors have been less exploited. Here, we present a novel approach for identifying biomarkers of schizophrenia using expression of serum analytes from first onset, drug-naïve patients and normal controls. The strength of patterned signals was amplified by analyzing data in reproducing kernel spaces. This resulted in the identification of small sets of analytes referred to as targeted clusters that have discriminative power specifically for schizophrenia in both human and rat models. These clusters were associated with specific molecular signaling pathways and less strongly related to other neuropsychiatric disorders such as major depressive disorder and bipolar disorder. These results shed new light concerning how complex neuropsychiatric diseases behave at the pathway level and demonstrate the power of this approach in identification of disease-specific biomarkers and potential novel therapeutic strategies.

Publication DOI:
Divisions: College of Health & Life Sciences > Aston Medical School
Additional Information: © 2010 ASBMB. Currently published by Elsevier Inc; originally published by American Society for Biochemistry and Molecular Biology.. Creative Commons Attribution (CC BY 4.0)
Uncontrolled Keywords: Analytical Chemistry,Biochemistry,Molecular Biology
Publication ISSN: 1535-9484
Last Modified: 08 Jul 2024 08:05
Date Deposited: 16 Jun 2021 14:10
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.mcp ... 0829-X/fulltext (Publisher URL)
PURE Output Type: Article
Published Date: 2010-03
Authors: Cheng, Tammy M.K.
Lu, Yu En
Guest, Paul C.
Rahmoune, Hassan
Harris, Laura W.
Wang, Lan
Ma, Dan (ORCID Profile 0000-0001-8628-8954)
Stelzhammer, Victoria
Umrania, Yagnesh
Wayland, Matt T.
Lió, Pietro
Bahn, Sabine



Version: Published Version

License: Creative Commons Attribution

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