Research

Molecular


Platform Leadership

Gustavo Turecki, MD, PhD
Jane Foster, PhD

Active Sites

The Molecular Platform operates at the following research sites:

  • Centre for Addiction and Mental Health (Toronto, Ontario)
  • McGill University (Montreal, Quebec)
  • St. Joseph’s Healthcare Hamilton (Hamilton, Ontario)
  • St. Michael’s Hospital (Toronto, Ontario)
  • University Health Network (Toronto, Ontario)

Collaborating Research Institutions:

  • Imperial College London (London, UK)

Platform Overview

The Molecular Platform investigates biological samples (e.g. blood and urine samples) that are collected through CAN-BIND’s clinical studies. Biological samples allow researchers to explore molecular factors, such as DNA, RNA, or protein levels, and their role in predicting response to depression treatments. These changes could be used to develop simple blood or urine tests to objectively monitor treatment outcomes. The Molecular Platform studies genomics, inflammatory markers, metabolic phenotyping, and targeted genetic analysis associated with depression, antidepressant response and remission.

 

Resources and Publications

CAN-BIND and H Lundbeck A/S formed an innovative academic-industry partnership based on the shared goals of identifying clinically relevant biomarkers to personalize treatment selection and stratifying patients in clinical trials to improve drug development for depression. Through this partnership, CAN-BIND researchers were able to investigate miRNAs, mRNAs, gene variants, and proteins in peripheral samples from placebo-controlled Lundbeck clinical trials using a comparator drug duloxetine. This served as a proof-of-concept for the current CAN-BIND platform, and multiple publications resulted from this work, which can be found below.

GWAS-based Machine Learning Approach to Predict Duloxetine Response in Major Depressive Disorder
Maciukiewicz, M., V.S. Marshe, A.C. Hauschild, J.A. Foster, S. Rotzinger, J.L. Kennedy, S.H. Kennedy, D.J. Mueller, and J. Geraci. (2018). GWAS-based machine learning approach to predict duloxetine response in major depressive disorder. J Psychiatr Res 99:62-68.

miRNAs in MDD and Antidepressant Response

Fiori, L. M., Lopez, J. P., Richard-Devantoy, S., Berlim, M., Chachamovich, E., Jollant, F., Foster J., Rotzinger  S., Kennedy S.H., Turecki, G. (2017). Investigation of miR-1202, miR-135a, and miR-16 in Major Depressive Disorder and Antidepressant Response. International Journal of Neuropsychopharmacology, 20(8), 619-623. doi:10.1093/ijnp/pyx034

GWAS of Placebo and Duloxetine Response

Maciukiewicz, M., Marshe, V. S., Tiwari, A. K., Fonseka, T. M., Freeman, N., Kennedy, J. L., Rotzinger S, Foster J.A., Kennedy S.H., Müller, D.J. (2017). Genome-wide association studies of placebo and duloxetine response in major depressive disorder. The Pharmacogenomics Journal. doi:10.1038/tpj.2017.29

MicroRNA Markers of Antidepressant Response

Lopez, J. P., Fiori, L. M., Cruceanu, C., Lin, R., Labonte, B., Cates, H. M., Heller, E.A., Vialou, V., Ku, S.M., Gerald, C., Han, M.H., Foster, J., Frey, B.N., Soares, C.N., Mueller, D.J., Farzan, F., Leri, F., MacQueen, G.M., Feilotter, H., Tyryshkin, K., Evans, K.R., Giacobbe, P., Blier, P., Lam, R.W., Milev, R., Parihk, S.V., Rotzinger, S., Strother, S.C., Lewis, C.M., Aitchison, K. J., Wittenberg, G.M., Mechawar, N., Nestler, E.J., Uher, R., Kennedy, S.H., Turecki, G. (2017). MicroRNAs 146a/b-5 and 425-3p and 24-3p are markers of antidepressant response and regulate MAPK/Wnt-system genes. Nature Communications, 8, 15497. doi:10.1038/ncomms15497

Genetic Variants Associated with Response to Duloxetine

Maciukiewicz M, Marshe, V.S., Tiwari, A.K., Fonseka, T.M., Freeman, N., Rotzinger, S., Foster, J.A., Kennedy, J.L., Kennedy, S.H., Mueller, D.J. (2015). Genetic variation in IL-1beta, IL-2, IL-6, TSPO and BDNF and response to duloxetine or placebo treatment in major depressive disorder. Pharmacogenomics. 16(17):1919-29. doi: 10.2217/pgs.15.136

 

Reviews and Commentaries

microRNAs as Peripheral Biomarkers (Perspective)

Lopez, J. P., Kos, A., & Turecki, G. (2017). Major depression and its treatment: microRNAs as peripheral biomarkers of diagnosis and treatment response. Current Opinion in Psychiatry, 1. doi:10.1097/yco.0000000000000379

Microbiome and Mental Health (Commentary)

Foster, J. A. (2017). Targeting the Microbiome for Mental Health: Hype or Hope? Biological Psychiatry, 82(7), 456-457. doi:10.1016/j.biopsych.2017.08.002

Transcriptomic and Epigenomic Biomarkers (Review)

Belzeaux, R., Lin, R., Ju, C., Chay, M., Fiori, L. M., Lutz, P., & Turecki, G. (2017). Transcriptomic and epigenomic biomarkers of antidepressant response. Journal of Affective Disorders. doi:10.1016/j.jad.2017.08.087

Noncoding RNAs in Depression (Review)

Turecki G, Lin R. (2017). Noncoding RNAs in Depression. Advances in Experimental Medicine and Biology. 978:197-210. doi: 10.1007/978-3-319-53889-1_11.

Using MicroRNA to Monitor Antidepressant Response (Review)

Belzeaux R, Lin R, Turecki G. (2017). Potential Use of MicroRNA for Monitoring Therapeutic Response to Antidepressants. CNS Drugs. Apr;31(4):253-262. doi: 10.1007/s40263-017-0418-z.