Translational bioinformatics in mental health: open access data sources and computational biomarker discovery

Abstract Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities ari...

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Bibliographic Details
Published in:Briefings in bioinformatics 2019-05, Vol.20 (3), p.842-856
Main Authors: Tenenbaum, Jessica D, Bhuvaneshwar, Krithika, Gagliardi, Jane P, Fultz Hollis, Kate, Jia, Peilin, Ma, Liang, Nagarajan, Radhakrishnan, Rakesh, Gopalkumar, Subbian, Vignesh, Visweswaran, Shyam, Zhao, Zhongming, Rozenblit, Leon
Format: Article
Language:English
Subjects:
Bioinformatics
Biomarkers
Biomarkers - metabolism
Computational Biology
Consortia
Datasets
Gene expression
Genomics
Genotypes
Humans
Medical imaging
Mental disorders
Mental Health
Metabolomics
Phenotypes
Proteomics
Schizophrenia
Transcriptomics
Translational Research, Biomedical
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Summary:Abstract Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.
ISSN:1477-4054
1467-5463
1477-4054
DOI:10.1093/bib/bbx157