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Identifying blood biomarkers for mood disorders using convergent functional genomics

Molecular Psychiatry volume 14, pages 156–174 (2009)Cite this article

A Corrigendum to this article was published on 18 November 2009

Abstract

There are to date no objective clinical laboratory blood tests for mood disorders. The current reliance on patient self-report of symptom severity and on the clinicians’ impression is a rate-limiting step in effective treatment and new drug development. We propose, and provide proof of principle for, an approach to help identify blood biomarkers for mood state. We measured whole-genome gene expression differences in blood samples from subjects with bipolar disorder that had low mood vs those that had high mood at the time of the blood draw, and separately, changes in gene expression in brain and blood of a mouse pharmacogenomic model. We then integrated our human blood gene expression data with animal model gene expression data, human genetic linkage/association data and human postmortem brain data, an approach called convergent functional genomics, as a Bayesian strategy for cross-validating and prioritizing findings. Topping our list of candidate blood biomarker genes we have five genes involved in myelination (Mbp, Edg2, Mag, Pmp22 and Ugt8), and six genes involved in growth factor signaling (Fgfr1, Fzd3, Erbb3, Igfbp4, Igfbp6 and Ptprm). All of these genes have prior evidence of differential expression in human postmortem brains from mood disorder subjects. A predictive score developed based on a panel of 10 top candidate biomarkers (five for high mood and five for low mood) shows sensitivity and specificity for high mood and low mood states, in two independent cohorts. Our studies suggest that blood biomarkers may offer an unexpectedly informative window into brain functioning and disease state.

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Acknowledgements

This work was supported by funds from INGEN (Indiana Genomics Initiative of Indiana University) and INBRAIN (Indiana Center for Biomarker Research In Neuropsychiatry) to ABN, as well as NIMH R01 MH071912-01 to MTT and ABN. ABN is a NARSAD Mogens Schou Young Investigator. ABN thanks Drs Christian Felder and George Sandusky of Lilly Research Laboratories for help with establishing INBRAIN, Dr Matthew McFarland for help with sample repository organization and Dr Nicholas Schork from Scripps for insightful discussions and advice. We thank Sudharani Mamidipalli and Dr Meghana Bhat for their precise work with database maintenance and data analysis, Dr Paul Lysaker for advice on neuropsychological testing and help with subject recruitment, as well as David Bertram and Jeremy Davis for help with subject testing. Last but not least, we thank the subjects who participated in these studies. Without their generous participation, such work to advance the understanding of mental illness would not be possible.

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Authors and Affiliations

  1. Department of Psychiatry, Laboratory of Neurophenomics, Indiana University School of Medicine, Indianapolis, IN, USA

    H Le-Niculescu, N Yehyawi, C Dike, S D Patel & A B Niculescu

  2. Department of Psychiatry, INBRAIN, Indiana University School of Medicine, Indianapolis, IN, USA

    H Le-Niculescu & A B Niculescu

  3. Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, IN, USA

    H Le-Niculescu, S D Patel, J I Nurnberger Jr & A B Niculescu

  4. Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA, USA

    S M Kurian & D R Salomon

  5. Indianapolis VA Medical Center, Indianapolis, IN, USA

    N Yehyawi, C Dike & A B Niculescu

  6. Department of Biochemistry and Molecular Biology,

    H J Edenberg

  7. , Indiana University School of Medicine, Indianapolis, IN, USA

    H J Edenberg

  8. Department of Psychiatry, University of California at San Diego, La Jolla, CA, USA

    M T Tsuang

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  1. H Le-Niculescu
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Le-Niculescu, H., Kurian, S., Yehyawi, N. et al. Identifying blood biomarkers for mood disorders using convergent functional genomics. Mol Psychiatry 14, 156–174 (2009). https://doi.org/10.1038/mp.2008.11

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