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A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping
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 co...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026437/ https://www.ncbi.nlm.nih.gov/pubmed/32066715 http://dx.doi.org/10.1038/s41398-020-0738-5 |
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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 |
author_facet | 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 |
author_sort | Fabbri, Chiara |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7026437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70264372020-03-03 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 Transl Psychiatry Article 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. Nature Publishing Group UK 2020-02-03 /pmc/articles/PMC7026437/ /pubmed/32066715 http://dx.doi.org/10.1038/s41398-020-0738-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article 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 |
title | A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
title_full | A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
title_fullStr | A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
title_full_unstemmed | A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
title_short | A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
title_sort | polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026437/ https://www.ncbi.nlm.nih.gov/pubmed/32066715 http://dx.doi.org/10.1038/s41398-020-0738-5 |
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