A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

Chiara Fabbri; Siegfried Kasper; Alexander Kautzky; Joseph Zohar; Daniel Souery; Stuart Montgomery; Diego Albani; Gianluigi Forloni; Panagiotis Ferentinos; Dan Rujescu; Julien Mendlewicz; Rudolf Uher; Cathryn M. Lewis; Alessandro Serretti

doi:10.1038/s41398-020-0738-5

A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

Chiara Fabbri, Siegfried Kasper, Alexander Kautzky, Joseph Zohar, Daniel Souery, Stuart Montgomery, Diego Albani, Gianluigi Forloni, Panagiotis Ferentinos, Dan Rujescu, Julien Mendlewicz, Rudolf Uher, Cathryn M. Lewis, Alessandro Serretti

Medicine

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34 Citations (Scopus)

Résumé

Treatment-resistant depression (TRD) occurs in ~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.

Langue d'origine	English
Numéro d'article	50
Journal	Translational Psychiatry
Volume	10
Numéro de publication	1
DOI	https://doi.org/10.1038/s41398-020-0738-5
Statut de publication	Published - déc. 1 2020

Note bibliographique

Funding Information:
We thank the NIMH for having had the possibility of analyzing their data on the STAR*D sample. We also thank the authors of previous publications in this dataset, and foremost, we thank the patients and their families who accepted to be enrolled in the study. Data and biomaterials were obtained from the limited access datasets distributed from the NIH-supported “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D). The study was supported by NIMH Contract No. N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528. The GENDEP project was supported by a European Commission Framework 6 grant (contract reference: LSHB-CT-2003-503428). The Medical Research Council, United Kingdom, and GlaxoSmithKline (G0701420) provided support for genotyping. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). We thank Intomics (Copenhagen, Denmark) for genotype calling and contribution to quality control of exome sequence data in the GSRD sample. C.F. is supported by a Marie Skłodowska-Curie Actions Individual Fellowship funded by the European Community (EC Grant agreement number: 793526; project title: Exome Sequencing in stages of Treatment Resistance to Antidepressants— ESTREA). C.M.L. is part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. R.U. is supported by the Canada Research Chairs Program. This study was supported by an unrestricted grant from Lundbeck for the Group for the Study of Resistant Depression (GSRD). Lundbeck had no further role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. All authors were actively involved in the design of the study, the analytical method of the study, the selection, and review of all scientific content. All authors had full editorial control during the writing of the manuscript and approved it.

Publisher Copyright:
© 2020, The Author(s).

ASJC Scopus Subject Areas

Psychiatry and Mental health
Cellular and Molecular Neuroscience
Biological Psychiatry

ODD de l’ONU

Cette action contribue à la réalisation des objectifs de développement durable suivants

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10.1038/s41398-020-0738-5

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Fabbri, C., Kasper, S., Kautzky, A., Zohar, J., Souery, D., Montgomery, S., Albani, D., Forloni, G., Ferentinos, P., Rujescu, D., Mendlewicz, J., Uher, R., Lewis, C. M., & Serretti, A. (2020). A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. Translational Psychiatry, 10(1), Article 50. https://doi.org/10.1038/s41398-020-0738-5

Fabbri, C, Kasper, S, Kautzky, A, Zohar, J, Souery, D, Montgomery, S, Albani, D, Forloni, G, Ferentinos, P, Rujescu, D, Mendlewicz, J, Uher, R, Lewis, CM & Serretti, A 2020, 'A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping', Translational Psychiatry, vol. 10, n° 1, 50. https://doi.org/10.1038/s41398-020-0738-5

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abstract = "Treatment-resistant depression (TRD) occurs in ~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.",

author = "Chiara Fabbri and Siegfried Kasper and Alexander Kautzky and Joseph Zohar and Daniel Souery and Stuart Montgomery and Diego Albani and Gianluigi Forloni and Panagiotis Ferentinos and Dan Rujescu and Julien Mendlewicz and Rudolf Uher and Lewis, {Cathryn M.} and Alessandro Serretti",

note = "Funding Information: We thank the NIMH for having had the possibility of analyzing their data on the STAR*D sample. We also thank the authors of previous publications in this dataset, and foremost, we thank the patients and their families who accepted to be enrolled in the study. Data and biomaterials were obtained from the limited access datasets distributed from the NIH-supported “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D). The study was supported by NIMH Contract No. N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528. The GENDEP project was supported by a European Commission Framework 6 grant (contract reference: LSHB-CT-2003-503428). The Medical Research Council, United Kingdom, and GlaxoSmithKline (G0701420) provided support for genotyping. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). We thank Intomics (Copenhagen, Denmark) for genotype calling and contribution to quality control of exome sequence data in the GSRD sample. C.F. is supported by a Marie Sk{\l}odowska-Curie Actions Individual Fellowship funded by the European Community (EC Grant agreement number: 793526; project title: Exome Sequencing in stages of Treatment Resistance to Antidepressants— ESTREA). C.M.L. is part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King{\textquoteright}s College London. R.U. is supported by the Canada Research Chairs Program. This study was supported by an unrestricted grant from Lundbeck for the Group for the Study of Resistant Depression (GSRD). Lundbeck had no further role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. All authors were actively involved in the design of the study, the analytical method of the study, the selection, and review of all scientific content. All authors had full editorial control during the writing of the manuscript and approved it. Publisher Copyright: {\textcopyright} 2020, The Author(s).",

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doi = "10.1038/s41398-020-0738-5",

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AU - Fabbri, Chiara

AU - Kasper, Siegfried

AU - Kautzky, Alexander

AU - Zohar, Joseph

AU - Souery, Daniel

AU - Montgomery, Stuart

AU - Albani, Diego

AU - Forloni, Gianluigi

AU - Ferentinos, Panagiotis

AU - Rujescu, Dan

AU - Mendlewicz, Julien

AU - Uher, Rudolf

AU - Lewis, Cathryn M.

AU - Serretti, Alessandro

N1 - Funding Information: We thank the NIMH for having had the possibility of analyzing their data on the STAR*D sample. We also thank the authors of previous publications in this dataset, and foremost, we thank the patients and their families who accepted to be enrolled in the study. Data and biomaterials were obtained from the limited access datasets distributed from the NIH-supported “Sequenced Treatment Alternatives to Relieve Depression” (STAR*D). The study was supported by NIMH Contract No. N01MH90003 to the University of Texas Southwestern Medical Center. The ClinicalTrials.gov identifier is NCT00021528. The GENDEP project was supported by a European Commission Framework 6 grant (contract reference: LSHB-CT-2003-503428). The Medical Research Council, United Kingdom, and GlaxoSmithKline (G0701420) provided support for genotyping. This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. High performance computing facilities were funded with capital equipment grants from the GSTT Charity (TR130505) and Maudsley Charity (980). We thank Intomics (Copenhagen, Denmark) for genotype calling and contribution to quality control of exome sequence data in the GSRD sample. C.F. is supported by a Marie Skłodowska-Curie Actions Individual Fellowship funded by the European Community (EC Grant agreement number: 793526; project title: Exome Sequencing in stages of Treatment Resistance to Antidepressants— ESTREA). C.M.L. is part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. R.U. is supported by the Canada Research Chairs Program. This study was supported by an unrestricted grant from Lundbeck for the Group for the Study of Resistant Depression (GSRD). Lundbeck had no further role in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the paper for publication. All authors were actively involved in the design of the study, the analytical method of the study, the selection, and review of all scientific content. All authors had full editorial control during the writing of the manuscript and approved it. Publisher Copyright: © 2020, The Author(s).

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Y1 - 2020/12/1

N2 - Treatment-resistant depression (TRD) occurs in ~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.

AB - Treatment-resistant depression (TRD) occurs in ~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.

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A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

Résumé

Note bibliographique

ASJC Scopus Subject Areas

ODD de l’ONU

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