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

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A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. / Fabbri, Chiara; Kasper, Siegfried; Kautzky, Alexander; Zohar, Joseph; Souery, Daniel; Montgomery, Stuart; Albani, Diego; Forloni, Gianluigi; Ferentinos, Panagiotis; Rujescu, Dan; Mendlewicz, Julien; Uher, Rudolf; Lewis, Cathryn M; Serretti, Alessandro.

In: Translational psychiatry, Vol. 10, No. 1, 50, 03.02.2020.

Research output: Contribution to journalArticle

Harvard

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, no. 1, 50. https://doi.org/10.1038/s41398-020-0738-5

APA

Fabbri, C., Kasper, S., Kautzky, A., Zohar, J., Souery, D., Montgomery, S., ... Serretti, A. (2020). A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. Translational psychiatry, 10(1), [50]. https://doi.org/10.1038/s41398-020-0738-5

Vancouver

Fabbri C, Kasper S, Kautzky A, Zohar J, Souery D, Montgomery S et al. A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. Translational psychiatry. 2020 Feb 3;10(1). 50. https://doi.org/10.1038/s41398-020-0738-5

Author

Fabbri, Chiara ; Kasper, Siegfried ; Kautzky, Alexander ; Zohar, Joseph ; Souery, Daniel ; Montgomery, Stuart ; Albani, Diego ; Forloni, Gianluigi ; Ferentinos, Panagiotis ; Rujescu, Dan ; Mendlewicz, Julien ; Uher, Rudolf ; Lewis, Cathryn M ; Serretti, Alessandro. / A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping. In: Translational psychiatry. 2020 ; Vol. 10, No. 1.

Bibtex Download

@article{4e7083e05a0149bda3c5ebefeb896602,
title = "A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping",
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.",
keywords = "TREATMENT-RESISTANT DEPRESSION, Exome sequencing, Genome-wide association study, Antidepressant, polygenic prediction",
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",
year = "2020",
month = "2",
day = "3",
doi = "10.1038/s41398-020-0738-5",
language = "English",
volume = "10",
journal = "Translational psychiatry",
issn = "2158-3188",
publisher = "Nature Publishing Group",
number = "1",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

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

PY - 2020/2/3

Y1 - 2020/2/3

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.

KW - TREATMENT-RESISTANT DEPRESSION

KW - Exome sequencing

KW - Genome-wide association study

KW - Antidepressant

KW - polygenic prediction

UR - http://www.scopus.com/inward/record.url?scp=85079677527&partnerID=8YFLogxK

U2 - 10.1038/s41398-020-0738-5

DO - 10.1038/s41398-020-0738-5

M3 - Article

VL - 10

JO - Translational psychiatry

JF - Translational psychiatry

SN - 2158-3188

IS - 1

M1 - 50

ER -

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