Translating Pharmacogenetics and Pharmacogenomics: The Last 60 Years and the Rise of Collective Innovation as a Force Multiplier for Personalized Medicine

Cheng, Yuanda; He, Yijing; Tang, Jie; Zhou, Hong-Hao

doi:10.2174/1875692111666131223235548

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The United States Food and Drug Administration (FDA; http://www.fda.gov) started incorporating pharmacogenomics information on its labels especially after 2005 and the completion of the Human Genome Project ("www.fda.gov", [11]). Almost 15 years later, more than 200 drug labels are accompanied by pharmacogenomics information highlighting the progressive acknowledgment of the major regulatory body regarding this field of precision medicine [12]. Such information is gathered and represented in detail in the FDA's Table of Pharmacogenomics Biomarkers in Drug Labels [13] bearing variable levels of significance, from informational to necessary guidance.…”

Section: Introductionmentioning

confidence: 99%

Delineating significant genome-wide associations of variants with antipsychotic and antidepressant treatment response: implications for clinical pharmacogenomics

Koromina¹,

Koutsilieri²,

Patrinos³

2020

Hum Genomics

View full text Add to dashboard Cite

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 GWAsignificant 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.

show abstract

Section: Introductionmentioning

confidence: 99%