Genome-wide association studies in pharmacogenomics of antidepressants

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Date: Apr. 2015
From: Pharmacogenomics(Vol. 16, Issue 5)
Publisher: Future Medicine Ltd.
Document Type: Report
Length: 8,056 words
Lexile Measure: 2370L

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Author(s): Eugene Lin aff1 aff2 , Hsien-Yuan Lane [*] aff1 aff3

Keywords:

antidepressants; genome-wide association study; major depressive disorder; pharmacogenomics; single nucleotide polymorphisms

Major depressive disorder (MDD) is a serious health concern worldwide and is estimated to be the second leading cause of disability by 2030 [1 ]. Antidepressants are currently the first line of medication for lifting MDD. However, doctors can only take a trial and error approach to prescribe antidepressants because the effectiveness of medical treatments for MDD in an individual patient is unpredictable beforehand. In clinical association studies, SNPs can be employed to determine the contribution of genes to drug efficacy because accumulating evidence suggests that the combined effects of a number of genetic variants such as SNPs contribute about 50% or more to antidepressants response [2-4 ]. Although further findings in support of this hypothesis are needed, more and more genetic variants are being discovered to be associated with antidepressant response [2-4 ]. In this paper, we reviewed the pharmacogenomics of the drug efficacy and side effects of antidepressants in MDD.

With the Human Genome Project completed, a new era of scientific research is set to produce revolutionary technologies such as the genome-wide association study (GWAS), which is an alternative to the candidate-gene approach [ 5 ]. The GWAS is different from the candidate-gene approach because there is no a priori hypothesis about the relevant genes in the GWAS, which employs high-throughput genotyping technologies to analyze common SNPs across the entire human genome (about 500,000 to 2 million SNPs in cases and controls) as well as to find genetic associations with observable traits [6,7 ]. A typical GWAS usually has four parts including: selection of participants with the particular trait of interest and a suitable comparison group (controls); DNA isolation, genotyping platforms and data review to ensure high quality of data; statistical tests for associations between SNPs and the particular trait of interest; and experimental studies of functional indications or replication studies of identified associations in independent populations [8 ]. This GWAS approach faces several challenges, such as how to account for the issue of multiple comparisons as well as differences in the prevalence of SNPs due to ethnicity [9,10 ]. When multiple statistical tests are considered simultaneously, the situation of multiple comparisons occurs so that SNP frequencies in cases and controls would differ simply because chance increases naturally [ 11,12 ].

First, we surveyed the SNPs and genes that were discovered as genetic markers and were associated with the drug efficacy of antidepressants in the GWAS studies for MDD patients. Furthermore, we investigated some potential candidate genes that were assessed in GWAS studies and were shown to be correlated with adverse drug reactions for antidepressant medications. In addition, we reviewed the genetic markers examined in GWAS studies that may distinguish patients who have an increased risk of suicidal ideation. Finally, we summarized the limitations and future perspectives with respect to the pharmacogenomics studies in the GWAS studies. Future replication studies in large and independent samples are needed to confirm the...

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Gale Document Number: GALE|A411315282