title: The Utility of Multiplex Assays for Identification of Proteomic Signatures in Psychiatry.
abstract: As substantial efforts are being made to identify biological markers of psychiatric illnesses, it is becoming clear that clinically useful accuracy will require larger sets of readouts that potentially span different technological platforms. For discovery of proteomic biomarkers, simultaneous measurement of analytes in small sample quantities has developed into a widely used technology of similar quality as the respective single-plex assays. Multiplex assay systems therefore hold promise for biomarker discovery and development in many complex disease areas including psychiatry. However, analysis of the derived data is subject to substantial challenges that may impede the possibility of obtaining meaningful findings. This chapter discusses potential applications of multiplexed assay technologies during biomarker development and highlights potential challenges for machine learning analysis of derived data.
authors.affiliation: Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
authors.forename: Junfang
authors.initials: J
authors.lastname: Chen
authors.affiliation: Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Rua Monteiro Lobato 255 F/01, Cidade Universitária Zeferino Vaz, 13083-862, Campinas, Brazil.
authors.forename: Paul C
authors.initials: PC
authors.lastname: Guest
authors.affiliation: Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. emanuel.schwarz@zi-mannheim.de.
authors.forename: Emanuel
authors.initials: E
authors.lastname: Schwarz
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D006801:Humans; D000069550:Machine Learning; D001523:Mental Disorders / Q000175:diagnosis / Q000378:metabolism*; D009419:Nerve Tissue Proteins / Q000032:analysis; D040901:Proteomics / Q000379:methods*; D012107:Research Design
chemical_list: D015415:Biomarkers; D009419:Nerve Tissue Proteins
keywords: Bias; Biomarker discovery; Confounding factors; Machine learning; Multiplex; Proteomics; Psychiatric disorders