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Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report

Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report
Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual’s biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

2399-3642
903
Caspani, Giorgia
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Turecki, Gustavo
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Lam, Raymond W.
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Milev, Roumen V.
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Frey, Benicio N.
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MacQueen, Glenda M.
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Müller, Daniel J.
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Rotzinger, Susan
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Kennedy, Sidney H.
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Foster, Jane A.
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Swann, Jonathan R.
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Caspani, Giorgia
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Turecki, Gustavo
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Lam, Raymond W.
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Milev, Roumen V.
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Frey, Benicio N.
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MacQueen, Glenda M.
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Müller, Daniel J.
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Rotzinger, Susan
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Kennedy, Sidney H.
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Foster, Jane A.
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Swann, Jonathan R.
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Caspani, Giorgia, Turecki, Gustavo, Lam, Raymond W., Milev, Roumen V., Frey, Benicio N., MacQueen, Glenda M., Müller, Daniel J., Rotzinger, Susan, Kennedy, Sidney H., Foster, Jane A. and Swann, Jonathan R. (2021) Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report. Communications Biology, 4 (1), 903, [903]. (doi:10.1038/s42003-021-02421-6).

Record type: Article

Abstract

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual’s biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

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Accepted/In Press date: 7 June 2021
Published date: 22 July 2021
Additional Information: Funding Information: CAN-BIND is an Integrated Discovery Program carried out in partnership with, and financial support from, the Ontario Brain Institute, an independent non-profit corporation, funded partially by the Ontario government. The opinions, results and conclusions are those of the authors and no endorsement by the Ontario Brain Institute is intended or should be inferred. Additional funding is provided by the Canadian Institutes of Health Research (CIHR), Lundbeck, Bristol-Myers Squibb, Pfizer, and Servier. Funding and/or in kind support is also provided by the investigators’ universities and academic institutions. All study medications are independently purchased at wholesale market values. This work was also supported by the Medical Research Council and National Institute for Health Research [grant number MC_PC_12025] and infrastructure support was provided by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). G.C. is supported by the MRC (grant number MR/N014103/1). Funding Information: R.W.L. has received honoraria for ad hoc speaking or advising/consulting, or received research funds, from: Allergan, Asia-Pacific Economic Cooperation, BC Leading Edge Foundation, Canadian Institutes of Health Research, Canadian Network for Mood and Anxiety Treatments, Canadian Psychiatric Association, Hansoh, Healthy Minds Canada, Janssen, Lundbeck, Lundbeck Institute, Michael Smith Foundation for Health Research, MITACS, Myriad Neuroscience, Ontario Brain Institute, Otsuka, Pfizer, St. Jude Medical, University Health Network Foundation, and VGH-UBCH Foundation. R.V.M. has received consulting and speaking honoraria from Allergan, Janssen, KYE, Lundbeck, Otsuka, and Sunovion, and research grants from CAN-BIND, CIHR, Janssen, Lallemand, Lundbeck, Nubiyota, OBI and OMHF. B.N.F. received a research grant from Pfizer. SHK has received research funding or honoraria from the following sources: Abbott, Alkermes, Allergan, Boehringer-Ingelheim, Brain Canada, Canadian Institutes of Health Research (CIHR), Janssen, Lundbeck, Lundbeck Institute, Ontario Mental Health Foundation (OMHF), Ontario Brain Institute, Ontario Research Fund (ORF), Otsuka, Pfizer, Sanofi, Servier, St. Jude Medical, Sun Pharmaceuticals, and Sunovion. The remaining authors declare that there is no competing interests. Funding Information: The data produced and used in this study are supported by The Canadian Biomarker Integration Network in Depression (CAN-BIND, https://canbind.ca/), which is an Integrative Discovery Program funded by the Ontario Brain Institute (OBI, https:// braininstitute.ca/). In accordance with the Research Activity Agreements between CAN-BIND and OBI, data produced in this study must be submitted to Brain-CODE (https:// www.braincode.ca/), an informatic platform created by the OBI to facilitate open-access of data generated from research funded by the OBI. Researchers requesting Data will provide OBI with written documentation of the proposed use of the Data in the form of an Research Ethics Board (REB) approval package which includes the full REB submission package and REB approval letter from their local Institutional REB. Should the REB determine that ethics review is not required, an exemption letter from the REB will be required. If the External Researcher is from an Institution that does not have a local REB, OBI will work with the External Researcher to identify a mutually acceptable REB for review. All documents not in English or French will require a certified translation copy. For detailed data access policy and procedure, please refer https://www. braininstitute.ca/research-data-sharing/brain-code or contact help@braincode.ca. Otherwise, data points underlying Figs. 2b, 3b, and 4b are presented in Supplementary Data 5–7. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

Identifiers

Local EPrints ID: 453473
URI: http://eprints.soton.ac.uk/id/eprint/453473
ISSN: 2399-3642
PURE UUID: be7b5525-1993-43e1-b407-28c6ef3499ea
ORCID for Jonathan R. Swann: ORCID iD orcid.org/0000-0002-6485-4529

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Date deposited: 18 Jan 2022 17:37
Last modified: 18 Mar 2024 03:56

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Contributors

Author: Giorgia Caspani
Author: Gustavo Turecki
Author: Raymond W. Lam
Author: Roumen V. Milev
Author: Benicio N. Frey
Author: Glenda M. MacQueen
Author: Daniel J. Müller
Author: Susan Rotzinger
Author: Sidney H. Kennedy
Author: Jane A. Foster

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