Research Highlights

Abstract

Personalized MedicineVol. 7, No. 1 News & ViewsFree AccessResearch HighlightsAlexandra SchosserAlexandra SchosserInstitute of Psychiatry, King’s College London, PO Box 82, De Crespigny Park, Denkmark Hill, London, SE5 8AF, UK and, Department of Psychiatry & Physiotherapy, Medical University of Vienna, Vienna, Austria. Search for more papers by this authorEmail the corresponding author at alexandra.schosser@kcl.ac.ukPublished Online:21 Dec 2009https://doi.org/10.2217/pme.09.72AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInRedditEmail Evaluation of: Ising M, Lucae S, Binder EB et al.: A genome-wide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch. Gen. Psychiatry 66(9), 966–975 (2009).It is widely believed that genetic factors play a major role in both the variation of treatment response and the incidence of adverse effects to medication. So far, several polymorphisms in candidate genes have been associated with antidepressant response [1,2]. However, as the understanding of the mechanism of action of antidepressants is incomplete, important genes and regulatory intergenic sequences may have been missed in candidate gene studies. Hypotheses-free genome-wide association studies (GWAS) have the potential to detect further variants that may help us to understand the biology of antidepressant action and to predict individual response to a specific antidepressant. The study by Ising et al. is among the first GWAS of antidepressant treatment outcome in depression [3]. Ising et al. investigated 339 depressed inpatients of the Munich Antidepressant Response Signature (MARS) project, two replication samples that included 361 depressed inpatients from a German replication sample and 832 outpatients with major depression from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) project. As antidepressant outcome phenotypes, they evaluated early partial response (Hamilton Depression Rating Scale [HAM-D] score reduction ≥ 25%) after 2 weeks, and response (HAM-D score reduction ≥ 50%) and remission (HAM-D score < 10) after 5 weeks. Genotyping of the MARS sample was performed using the Sentrix® Human-1 (109,000 loci) and HumanHap300 (317,000 loci) BeadChips (Illumina Inc., CA, USA), which together covered almost 410,000 nonoverlapping SNPs from the entire human genome. Three pairs of DNA pools of the German replication sample were created, and genome-wide allele frequencies were determined in triplicate using the HumanHap300 (317,000 loci) BeadChip. The ‘best’ 300 SNPs from the HumanHap300 chip that demonstrated concordant associations with treatment outcome in both genome-wide samples with the lowest combined p-values (geometric mean of the respective p-values), and 38 SNPs from the Sentrix Human-1 chip associated with treatment outcome in the MARS sample (p = 1 × 10-4), were selected for replication in the STAR*D sample. Of these 338 SNPs, 328 were successfully genotyped using a GoldenGate® custom assay (Illumina Inc.), and 46 SNPs were associated at the nominal level of significance but not withstanding multiple testing correction. The predominance of negative findings can be owing to the limited power to detect weak-to-moderate associations. Meta-analysis with other genome-wide pharmacogenetic studies of antidepressant response (e.g., [4]) will be needed to provide further insights into the pharmacogenetics of response to antidepressants.Financial & competing interests disclosureThe author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.References1 Horstmann S, Binder EB: Pharmacogenomics of antidepressant drugs. Pharmacol. Ther.124(1),57–73 (2009).Crossref, Medline, CAS, Google Scholar2 Kato M, Serretti A: Review and meta-analysis of antidepressant pharmacogenetic findings in major depressive disorder. Mol. Psychiatry (2008) (Epub ahead of print).Google Scholar3 Ising M, Lucae S, Binder EB et al.: A genome-wide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch. Gen. Psychiatry66(9),966–975 (2009).Crossref, Medline, CAS, Google Scholar4 Uher R, Perroud N, Ng MYM et al.: Genome-wide pharmacogenetics of antidepressant response in the GENDEP project. Am. J. Psychiatry (2009) (In press)Google ScholarEvaluation of: Laje G, Allen AS, Akla N, Manji H, Rush AJ, McMahon FJ: Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients. Pharmacogenet. Genomics 19, 666–674 (2009).Suicidal ideation is among the most serious adverse events of antidepressant treatments. A genetic contribution to suicidal behavior has long been established [1,2], although the genetic determinants of suicidality are only beginning to emerge, for example associations with variants in the serotonin transporter gene (5-HTT) [3], the tryptophan hydroxylase 1 gene (TPH1) [4], brain-derived neurotrophic factor (BDNF) and its receptor neurotrophic tyrosine kinase receptor type 2 (NTRK2) [5], cAMP response element-binding protein 1 (CREB1) [6] and the glutamate receptor genes GRIK2 and GRIA3[7].Hypothesis-free GWAS have recently become possible using SNP microarrays [8,9]. The study by Laje et al.[10] is the first study published so far, investigating treatment-emergent suicidal ideation (TESI) at a genome-wide level in a sample of nonpsychotic, major depressive disorder patients treated with the selective serotonin reuptake inhibitor citalopram, from the STAR*D cohort [11]. They investigated all of the 90 white (including Hispanic) participants of the STAR*D cohort who developed TESI and 90 sex-matched, race-matched and ethnicity-matched treated participants who denied having any history of suicide attempts or suicidal ideas during their citalopram treatment. Subjects were genotyped using the Human-1 BeadChip, which analyzed 109,365 SNPs. Only two SNPs attained p-values of less than 5 × 10-6, suggesting evidence of association with suicidal behavior – one SNP was found to be located approximately 50 bp from exon 13 in the proteoglycan-like sulphated glycoprotein gene (PALPLN) on chromosome 14q24.2, and one SNP was within the 3´-untranslated region of the IL28RA gene (which encodes for a protein in the class II cytokine receptor family) on chromosome 1p36.11. One additional marker in PAPLN and four additional markers in IL28RA were associated with TESI. Replication of these findings will require large samples, owing to the relatively low frequency of TESI in major depressive disorder. In addition, investigation of other antidepressants is required to clarify if these findings extend to other antidepressants.References1 McGuffin P, Marusic A, Farmer A: What can psychiatric genetics offer suicidology? Crisis22,61–65 (2001).Crossref, Medline, CAS, Google Scholar2 Brent DA, Mann JJ: Family genetic studies, suicide, and suicidal behaviour. Am. J. Med. Genet. C Semin. Med. Genet.133C,13–24 (2005).Crossref, Medline, Google Scholar3 Li D, He L: Meta-analysis supports association between serotonin transporter (5-HTT) and suicidal behavior. Mol. Psychiatry12(1),47–54 (2007).Crossref, Medline, Google Scholar4 Bellivier F, Chaste P, Malafosse A: Association between the TPH gene A218C polymorphism and suicidal behavior: a meta-analysis. Am. J. Med. Genet. B Neuropsychiatr. Genet.124B(1),87–91 (2004).Crossref, Medline, Google Scholar5 Perroud N, Uher R, Marusic A et al.: Suicidal ideation during treatment of depression with escitalopram and nortriptyline in genome-based therapeutic drugs for depression (GENDEP): a clinical trial. BMC Med.7,60 (2008).Crossref, Google Scholar6 Perlis RH, Purcell S, Fava M et al.: Association between treatment-emergent suicidal ideation with citalopram and polymorphisms near cyclic adenosine monophosphate response element binding protein in the STAR*D study. Arch. Gen. Psychiatry64,689–697 (2007).Crossref, Medline, CAS, Google Scholar7 Laje G, Paddock S, Manji H et al.: Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am. J. Psychiatry164,1530–1538 (2007).Crossref, Medline, Google Scholar8 Craig DW, Stephan DA: Applications of whole-genome high-density SNP genotyping. Expert Rev. Mol. Diagn.5,159–170 (2005).Crossref, Medline, CAS, Google Scholar9 Hirschhorn JN, Daly MJ: Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet.4,45–61 (2005).Google Scholar10 Laje G, Allen AS, Akla N, Manji H, Rush AJ, McMahon FJ: Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients. Pharmacogenet. Genomics19,666–674 (2009).Crossref, Medline, CAS, Google Scholar11 Rush AJ, Fava M, Wisniewski SR et al.: Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design. Control Clin. Trials25,119–142 (2004).Crossref, Medline, Google ScholarEvaluation of: McClay JL, Adkins DE, Aberg K et al.: Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics. Mol. Psychiatry (2009) (Epub ahead of print).Genetic factors are believed to have a major role in the variation of treatment response and in the incidence of drug-induced adverse effects [1]. So far, most pharmacogenetic studies on antipsychotic drug response have used the candidate gene approach [2,3]. A major limitation of candidate gene-association studies is that the selection of candidate genes is restricted to the current knowledge with regard to the mechanisms of drug action. Hypothesis-free GWAS using large samples have recently become possible, and the systematic screen of the whole genome for association with drug response likely represents a superior strategy for discovering relevant genetic variation.McClay et al. used a genome-wide approach to detect genetic variation underlying individual differences in response to antipsychotic treatment with olanzapine, quetiapine, risperidone, ziprasidone and perphenazine [4]. They investigated 738 subjects of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study [5,6] with a Diagnostic and Statistical Manual of Mental Disorders 4th Edition (DSM-IV) diagnosis of schizophrenia. Treatment outcome was measured using the Positive and Negative Syndrome Scale (PANSS). Whole-genome genotyping was performed using the Affymetrix (CA, USA) 500K genotyping platform as well as a custom 164 K chip, resulting in anaylsis of a total of 492,900 SNPs after stringent quality control. A GWAS of treatment response was only performed for the first antipsychotic drug prescribed (CATIE, Phase I) in order to avoid potential difficulties arising from drug switching and also to increase the power to find SNPs affecting common drug pathways. They prespecified a threshold allowing for 10% false discoveries, and one SNP on chromosome 4p15 hit this threshold, mediating the effect of ziprasidone on positive symptoms. An adjacent SNP also reached significance with the same phenotype, making it unlikely that the finding was caused by a genotyping error. Several other SNPs were close to the preselected significance threshold, three of them being located in genes expressed in the brain: ANKS1B (a tyrosine kinase signal transduction gene, CNTNAP5 (which belongs to a subgroup of the neurexin family of multidomain transmembrane proteins that are involved in cell adhesion and intercellular communication in the central nervous system) and transient receptor potential cation channel, subfamily M, member 1 (TRPM1). Investigating 2032 SNPs in 33 candidate genes for drug effects demonstrated that the most significant association was with a SNP located 120 kb from the serotonin 5-HT-2A receptor (HTR2A), which mediated the effects of quetiapine on negative symptoms. Some possibly relevant genetic variation in candidate genes might have been missed, since there were some notable gaps in genome-wide coverage whereby specific candidate genes were not assayed (e.g., some of the cytochrome P450 genes). Although this study, among others, demonstrates the potential of GWAS for discovering novel genes associated with treatment response, replication and functional validation are required in order to move towards predictive testing for treatment response, outcome and side effects of antipsychotic drug treatments.References1 Basu A, Tsapakis E, Aitchison KJ: Pharmacogenetics and psychiatry. Curr. Psychiatry Rep.6,134–142 (2004).Crossref, Medline, Google Scholar2 Kirchheiner J, Nickchen K, Bauer M: Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response. Mol. Psychiatry9(5),442–473 (2004).Crossref, Medline, CAS, Google Scholar3 Arranz MJ, de Leon J: Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research. Mol. Psychiatry12(8),707–747 (2007).Crossref, Medline, CAS, Google Scholar4 McClay JL, Adkins DE, Aberg K et al.: Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics. Mol. Psychiatry (2009) (Epub ahead of print).Medline, Google Scholar5 Stroup TS, McEvoy JP, Swartz MS et al.: The National Institute of Mental Health Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) project: schizophrenia trial design and protocol development. Schizophr. Bull.29,15–31 (2003).Crossref, Medline, Google Scholar6 Lieberman JA, Stroup TS, McEvoy JP et al.: Effectiveness of antipsychotic drugs in patients with chronic schizophrenia. N. Engl. J. Med.353,1209–1223 (2005).Crossref, Medline, CAS, Google ScholarEvaluation of: Vegt R, Bertoli-Avella AM, Tulen JHM et al.: Genome-wide linkage analysis in a Dutch multigenerational family with attention deficit hyperactivity disorder. Eur. J. Hum. Genet. (2009) (Epub ahead of print).Attention deficit hyperactivity disorder (ADHD) is one of the most common childhood behavioral disorders, characterized by the early onset of age-inappropriate hyperactivity, impulsivity and inattentiveness [1]. Heritability estimates range from 60 to 90% [2], and significant associations were identified for several candidate genes, including genes involved in the dopaminergic pathways, adrenergic pathways and serotonergic pathways [3]. However, novel genes are still to be discovered through hypothesis-free genome-wide linkage and association studies. Several genome-wide linkage analyses have been performed so far; however, no chromosome region has been consistently identified across the studies. This is likely to be owing to a lack of power of individual studies to identify genes of small-to-moderate effects that contribute to complex traits such as ADHD, whereas meta-analyses of multiple genome-wide linkage scans (e.g., [4]) provide more power to detect true linkage signals.In a recent genome-wide linkage study, Vegt et al. investigated a Dutch family consisting of 37 individuals in three generations of which 24 (ten females and 14 males) participated in the study [5]. A total of eight out of 24 family members (33%) were diagnosed as DSM-IV ADHD, ‘definitely affected’, and four members (17%) were diagnosed as being ‘possibly affected’. Genotyping of 382 markers was performed using the ABI PRISM® MD-10 Linkage versus 2.5 Mapping Set (Applied Biosystems, CA, USA), and for fine mapping of ‘positive’ regions, additional markers from the Marshfield integrated genetic map (Marshfield Clinic, WI, USA) were genotyped. Parametric and nonparametric linkage analyses were performed for all autosomes, using the ‘affected only’ design. Two regions on chromosomes 7 and 14 demonstrated an excess of allele sharing among the definitely affected members of the family, with suggestive logarithm of the odds scores of 2.1 and 2.08, and maximum nonparametric logarithm of the odds scores of 2.92 and 2.56. They refined the regions on chromosomes 7 and 14, and found that all eight patients shared the same haplotype at 7p15.1-q31.33 and had a common haplotype at 14q11.2-q22.3. Linkage of these regions had been reported previously – for example, a meta-analysis of seven genome-wide linkage scans in ADHD [4] identified an overlapping region with nominal linkage signals on chromosome 7. Converging genome-wide linkage and genome-wide association data, a recent study [6] identified several overlapping candidate loci, including 14q11.2–12. While in genome-wide linkage studies the identified regions are generally large and not easily limitable, GWAS are suitable for the identification of disease risk genes that have a considerably smaller effect. Recently, the first GWAS of ADHD have become available [7] and will provide further insight into genetic association with ADHD.References1 Asherson P: Attention-deficit hyperactivity disorder in the post-genomic era. Eur. Child Adolesc. Psychiatry13(Suppl. 1),I50–I70 (2004).Crossref, Medline, Google Scholar2 Waldman I, Rhee SL: Behavioral and molecular genetic studies. In: Hyperactivity and Attention Disorders of Childhood (2nd Edition). Sandberg S (Ed.). Wiley, NY, USA 290–335 (2002).Google Scholar3 Gizer IR, Ficks C, Waldman ID: Candidate gene studies of ADHD: a meta-analytic review. Hum. Genet.126,51–90 (2009).Crossref, Medline, CAS, Google Scholar4 Zhou K, Dempfle A, Arcos-Burgos M et al.: Meta-analysis of genome-wide linkage scans of attention deficit hyperactivity disorder. Am. J. Med. Genet. B Neuropsychiatr. Genet.147B(8),1392–1398 (2008).Crossref, Medline, CAS, Google Scholar5 Vegt R, Bertoli-Avella AM, Tulen JHM et al.: Genome-wide linkage analysis in a Dutch multigenerational family with attention deficit hyperactivity disorder. Eur. J. Hum. Genet. (2009) (Epub ahead of print).Medline, Google Scholar6 Lesch KP, Timmesfeld N, Renner TJ et al.: Molecular genetics of adult ADHD: converging evidence from genome-wide association and extended pedigree linkage studies. J. Neural Transm.115,1573–1585 (2008).Crossref, Medline, CAS, Google Scholar7 Franke B, Neale BM, Faraone SV: Genome-wide association studies in ADHD. Hum. Genet.126,13–50 (2009).Crossref, Medline, CAS, Google ScholarFiguresReferencesRelatedDetails Vol. 7, No. 1 Follow us on social media for the latest updates Metrics Downloaded 472 times History Published online 21 December 2009 Published in print January 2010 Information© Future Medicine LtdPDF download