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

Translational psychiatry | 2020

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.

Pubmed ID: 32066715 RIS Download

Associated grants

  • Agency: NIMH NIH HHS, United States
    Id: N01MH90003
  • Agency: European Commission (EC), International
    Id: 793526

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This is a list of tools and resources that we have found mentioned in this publication.


PLINK (tool)

RRID:SCR_001757

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

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Psychiatric Genomics Consortium (tool)

RRID:SCR_004495

Consortium conducting meta-analyses of genome-wide genetic data for psychiatric disease. Focused on autism, attention-deficit hyperactivity disorder, bipolar disorder, major depressive disorder, schizophrenia, anorexia nervosa (AN), Tourette syndrome (TS), and obsessive-compulsive disorder (OCD). Used to investigate common single nucleotide polymorphisms (SNPs) genotyped on commercial arrays, structural variation (copy number variation) and uncommon or rare genetic variation. To participate you are asked to upload data from your study to central computer used by this consortium. Genetic Cluster Computer serves as data warehouse and analytical platform for this study . When data from your study have been incorporated, account will be provided on central server and access to all GWAS genotypes, phenotypes, and meta-analytic results relevant to deposited data and participation aims. NHGRI GWAS Catalog contains updated information about all GWAS in biomedicine, and is usually excellent starting point to find comprehensive list of studies. Files can be obtained by any PGC member for any disease to which they contributed data. These files can also be obtained by application to NIMH Genetics Repository. Individual-level genotype and phenotype data requires application, material transfer agreement, and informed consent consideration. Some datasets are also in controlled-access dbGaP and Wellcome Trust Case-Control Consortium repositories. PGC members can also receive back cleaned and imputed data and results for samples they contributed to PGC analyses.

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Sequenced Treatment Alternatives to Relieve Depression Study (tool)

RRID:SCR_008051

A nationwide public health clinical trial conducted to determine the effectiveness of different treatments for people with major depression, in both primary and specialty care settings, who have not responded to initial treatment with an antidepressant. This is the largest and longest study ever done to evaluate depression treatment. The study is completed and no longer recruiting participants. Each of the four levels of the study tested a different medication or medication combination. The primary goal of each level was to determine if the treatment used during that level could adequately treat participants����?? major depressive disorder (MDD). Those who did not become symptom-free could proceed to the next level of treatment. The design of the STAR*D study reflects what is done in clinical practice because it allowed study participants to choose certain treatment strategies most acceptable to them and limited the randomization of each participant only to his/her range of acceptable treatment strategies. No prior studies have evaluated the different treatment strategies in broadly defined participant groups treated in diverse care settings. Over a seven-year period, the study enrolled 4,041 outpatients, ages 18-75 years, from 41 clinical sites around the country, which included both specialty care settings and primary medical care settings. Participants represented a broad range of ethnic and socioeconomic groups. All participants were diagnosed with MDD, were already seeking care at one of these sites, and were referred to the trial by their doctors. * STAR*D Study Medications: Citalopram (Celexa), Sertraline (Zoloft), Bupropion SR (Wellbutrin SR), Venlafaxine XR (Effexor XR), Buspirone (BuSpar), Mirtazapine (Remeron), Triiodothyronine (T3) (Cytomel), Nortriptyline (Pamelor, Aventyl), Tranylcypromine (Parnate), Lithium (Eskalith, Lithobid) *STAR*D Talk Therapy:Cognitive Therapy

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SIFT (tool)

RRID:SCR_012813

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

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NIMH Repository and Genomics Resources (tool)

RRID:SCR_016318

Collaborative venture between the National Institute of Mental Health (NIMH) and several academic institutions. Repository facilitates psychiatric genetic research by providing patient and control samples and phenotypic data for wide-range of mental disorders and Stem Cells.Stores biosamples, genetic, pedigree and clinical data collected in designated NIMH-funded human subject studies. RGR database likewise links to other repositories holding data from same subjects, including dbGAP, GEO and NDAR. Allows to access these data and biospecimens (e.g., lymphoblastoid cell lines, induced pluripotent cell lines, fibroblasts) and further expand genetic and molecular characterization of patient populations with severe mental illness.

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NIMH Repository and Genomics Resources (tool)

RRID:SCR_006698

Collaborative venture between the National Institute of Mental Health (NIMH) and several academic institutions. Repository facilitates psychiatric genetic research by providing patient and control samples and phenotypic data for wide-range of mental disorders and Stem Cells.Stores biosamples, genetic, pedigree and clinical data collected in designated NIMH-funded human subject studies. RGR database likewise links to other repositories holding data from same subjects, including dbGAP, GEO and NDAR. Allows to access these data and biospecimens (e.g., lymphoblastoid cell lines, induced pluripotent cell lines, fibroblasts) and further expand genetic and molecular characterization of patient populations with severe mental illness.

View all literature mentions