Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics
Abstract Background Genome-wide association studies (GWAS) have significantly contributed to the association of many clinical conditions and phenotypic characteristics with genomic variants. The majority of these genomic findings have been deposited to the GWAS catalog. So far, findings uncovering a...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2020-01-01
|
Series: | Human Genomics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40246-019-0254-y |
id |
doaj-b152fb948e8c47d4ab9c3c3fb869f6ae |
---|---|
record_format |
Article |
spelling |
doaj-b152fb948e8c47d4ab9c3c3fb869f6ae2021-01-17T12:58:04ZengBMCHuman Genomics1479-73642020-01-0114111010.1186/s40246-019-0254-yDelineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomicsMaria Koromina0Stefania Koutsilieri1George P. Patrinos2Laboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of PatrasLaboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of PatrasLaboratory of Pharmacogenomics and Individualized Therapy, Department of Pharmacy, School of Health Sciences, University of PatrasAbstract Background Genome-wide association studies (GWAS) have significantly contributed to the association of many clinical conditions and phenotypic characteristics with genomic variants. The majority of these genomic findings have been deposited to the GWAS catalog. So far, findings uncovering associations of single nucleotide polymorphisms (SNPs) with treatment efficacy in mood disorders are encouraging, but not adequate. Methods Statistical, genomic, and literature information was retrieved from EBI’s GWAS catalog, while we also searched for potential clinical information/clinical guidelines in well-established pharmacogenomics databases regarding the assessed drug-SNP correlations of the present study. Results Here, we provide an overview of significant genome-wide associations of SNPs with the response to commonly prescribed antipsychotics and antidepressants. Up to date, this is the first study providing novel insight in previously reported pharmacogenomics associations for antipsychotic/antidepressant treatment. We also show that although there are published CPIC guidelines for antidepressant agents, as well as the FDA labels include genome-based drug prescription information for both antipsychotic and antidepressant treatments, there are no specific clinical guidelines for the assessed drug-SNP correlations of this study. Conclusions Our present findings suggest that more effort should be implemented towards identifying GWA-significant antipsychotic and antidepressant pharmacogenomics correlations. Moreover, additional functional studies are required in order to characterise the potential role of the assessed SNPs as biomarkers for the response of patients to antipsychotic/antidepressant treatment.https://doi.org/10.1186/s40246-019-0254-yAntipsychoticsAntidepressantsPharmacogenomicsStatistical assessmentGWAS catalogGWAS findings |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maria Koromina Stefania Koutsilieri George P. Patrinos |
spellingShingle |
Maria Koromina Stefania Koutsilieri George P. Patrinos Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics Human Genomics Antipsychotics Antidepressants Pharmacogenomics Statistical assessment GWAS catalog GWAS findings |
author_facet |
Maria Koromina Stefania Koutsilieri George P. Patrinos |
author_sort |
Maria Koromina |
title |
Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
title_short |
Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
title_full |
Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
title_fullStr |
Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
title_full_unstemmed |
Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
title_sort |
delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics |
publisher |
BMC |
series |
Human Genomics |
issn |
1479-7364 |
publishDate |
2020-01-01 |
description |
Abstract Background Genome-wide association studies (GWAS) have significantly contributed to the association of many clinical conditions and phenotypic characteristics with genomic variants. The majority of these genomic findings have been deposited to the GWAS catalog. So far, findings uncovering associations of single nucleotide polymorphisms (SNPs) with treatment efficacy in mood disorders are encouraging, but not adequate. Methods Statistical, genomic, and literature information was retrieved from EBI’s GWAS catalog, while we also searched for potential clinical information/clinical guidelines in well-established pharmacogenomics databases regarding the assessed drug-SNP correlations of the present study. Results Here, we provide an overview of significant genome-wide associations of SNPs with the response to commonly prescribed antipsychotics and antidepressants. Up to date, this is the first study providing novel insight in previously reported pharmacogenomics associations for antipsychotic/antidepressant treatment. We also show that although there are published CPIC guidelines for antidepressant agents, as well as the FDA labels include genome-based drug prescription information for both antipsychotic and antidepressant treatments, there are no specific clinical guidelines for the assessed drug-SNP correlations of this study. Conclusions Our present findings suggest that more effort should be implemented towards identifying GWA-significant antipsychotic and antidepressant pharmacogenomics correlations. Moreover, additional functional studies are required in order to characterise the potential role of the assessed SNPs as biomarkers for the response of patients to antipsychotic/antidepressant treatment. |
topic |
Antipsychotics Antidepressants Pharmacogenomics Statistical assessment GWAS catalog GWAS findings |
url |
https://doi.org/10.1186/s40246-019-0254-y |
work_keys_str_mv |
AT mariakoromina delineatingsignificantgenomewideassociationsofvariantswithantipsychoticandantidepressanttreatmentresponseimplicationsforclinicalpharmacogenomics AT stefaniakoutsilieri delineatingsignificantgenomewideassociationsofvariantswithantipsychoticandantidepressanttreatmentresponseimplicationsforclinicalpharmacogenomics AT georgeppatrinos delineatingsignificantgenomewideassociationsofvariantswithantipsychoticandantidepressanttreatmentresponseimplicationsforclinicalpharmacogenomics |
_version_ |
1724334189833093120 |