Skip to main content Accessibility help
×
Home
Hostname: page-component-564cf476b6-44467 Total loading time: 0.244 Render date: 2021-06-20T07:03:34.422Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true }

Pharmacogenetics of mood disorders: what clinicians need to know

Published online by Cambridge University Press:  20 September 2013

Gonzalo Laje
Affiliation:
Washington Behavioral Medicine Associates, LLC, and Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, Maryland, USA
Corresponding
E-mail address:

Abstract

Pharmacogenetics brought the promise of matching individuals with treatments that would be efficacious while minimizing adverse events. This has been long needed in psychiatry, where treatment options have been empirical and treatment choices have been made largely based on clinical judgment. The efficacy and tolerability of antidepressants, the most common drugs used in mood disorders, have been widely studied in pharmacogenetics. Genetic association studies have been reported for pharmacokinetic genes such as the CYP450 isoenzymes or MDR1, and pharmacodynamic genes such as the serotonin transporter (SLC6A4) or the serotonin 2A receptor (HTR2A). However, despite the large number of reports, clinically useful predictors are still scarce for antidepressant monotherapy. Pharmacogenetic predictors of efficacy for mood stabilizers such as lithium and anticonvulsants have not had a dissimilar fate, and clinically meaningful markers are yet to emerge. The lack of consistent results may be in part due to small samples of heterogeneous populations and lack of consensus on phenotype definitions. Current pharmacogenetic recommendations include testing for HLA-B*1502 when using carbamazepine in Asian ancestry populations to prevent Stevens–Johnson syndrome, CYP2D6 genotypes when using pimozide, and CYP2D6 in polypharmacy to minimize drug interactions. This review, which is aimed at clinicians, lays the basis for understanding strengths and weaknesses of pharmacogenetic studies and outlines current clinical uses of these biomarkers.

Type
Review Articles
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below.

Footnotes

I would like to express my deepest gratitude to Drs. McMahon and Zarate for their mentorship and support over the past several years.

References

1.Schlesser, MA, Altshuler, KZ. The genetics of affective disorder: data, theory, and clinical applications. Hosp Community Psychiatry. 1983; 34(5): 415422.Google ScholarPubMed
2.Angst, J. A clinical analysis of the effects of tofranil in depression: longitudinal and follow-up studies: treatment of blood-relations. Psychopharmacologia. 1961; 2: 381407.CrossRefGoogle ScholarPubMed
3.Pare, CM, Mack, JW. Differentiation of two genetically specific types of depression by the response to antidepressant drugs. J Med Genet. 1971; 8(3): 306309.CrossRefGoogle ScholarPubMed
4.Wadelius, M, Chen, LY, Downes, K, etal. Common VKORC1 and GGCX polymorphisms associated with warfarin dose. Pharmacogenomics J. 2005; 5(4): 262270.CrossRefGoogle ScholarPubMed
5.Duman, RS, Newton, SS. Epigenetic marking and neuronal plasticity. Biol Psychiatry. 2007; 62(1): 13.CrossRefGoogle ScholarPubMed
6.Kang, HJ, Kawasawa, YI, Cheng, F, etal. Spatio-temporal transcriptome of the human brain. Nature. 2011; 478(7370): 483489.CrossRefGoogle ScholarPubMed
7.Laje, G, Cannon, DM, Allen, AS, etal. Genetic variation in HTR2A influences serotonin transporter binding potential as measured using PET and [11C]DASB. Int J Neuropsychopharmacol. 2010; 13(6): 715724.CrossRefGoogle Scholar
8.Hu, XZ, Rush, AJ, Charney, D, etal. Association between a functional serotonin transporter promoter polymorphism and citalopram treatment in adult outpatients with major depression. Arch Gen Psychiatry. 2007; 64(7): 783792.CrossRefGoogle ScholarPubMed
9.Lesser, IM, Castro, DB, Gaynes, BN, etal. Ethnicity/race and outcome in the treatment of depression: results from STAR*D. Med Care. 2007; 45(11): 10431051.CrossRefGoogle ScholarPubMed
10.Laje, G, Perlis, RH, Rush, AJ, McMahon, FJ. Pharmacogenetics studies in STAR*D: strengths, limitations, and results. Psychiatr Serv. 2009; 60(11): 14461457.CrossRefGoogle ScholarPubMed
11.Khan, A, Detke, M, Khan, SR, Mallinckrodt, C. Placebo response and antidepressant clinical trial outcome. J Nerv Ment Dis. 2003; 191(4): 211218.CrossRefGoogle ScholarPubMed
12.Fournier, JC, DeRubeis, RJ, Hollon, SD, etal. Antidepressant drug effects and depression severity: a patient-level meta-analysis. JAMA. 2010 ; 303(1): 4753.CrossRefGoogle ScholarPubMed
13.Trivedi, MH, Rush, AJ, Wisniewski, SR, etal. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006; 163(1): 2840.CrossRefGoogle Scholar
14.Serretti, A, Kato, M, Kennedy, JL. Pharmacogenetic studies in depression: a proposal for methodologic guidelines. Pharmacogenomics J. 2008; 8(2): 90100.CrossRefGoogle Scholar
15.McMahon, FJ, Buervenich, S, Charney, D, etal. Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet. 2006; 78(5): 804814.CrossRefGoogle ScholarPubMed
16.Peters, EJ, Slager, SL, Kraft, JB, etal. Pharmacokinetic genes do not influence response or tolerance to citalopram in the STAR*D sample. PLoS One. 2008; 3(4): e1872.CrossRefGoogle ScholarPubMed
17.Mrazek, DA, Rush, AJ, Biernacka, JM, etal. SLC6A4 variation and citalopram response. Am J Med Genet B Neuropsychiatr Genet. 2009; 150B(3): 341351.CrossRefGoogle ScholarPubMed
18.GENDEP Investigators, MARS Investigators, STAR*D Investigators. Common genetic variation and antidepressant efficacy in major depressive disorder: a meta-analysis of three genome-wide pharmacogenetic studies. Am J Psychiatry. 2013; 170(2): 207217.CrossRefGoogle Scholar
19.Rasmussen, HB, Werge, TM. Novel procedure for genotyping of the human serotonin transporter gene-linked polymorphic region (5-HTTLPR)—a region with a high level of allele diversity. Psychiatr Genet. 2007; 17(5): 287291.CrossRefGoogle ScholarPubMed
20.Serretti, A, Kato, M, De, RD, Kinoshita, T. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients. Mol Psychiatry. 2007; 12(3): 247257.CrossRefGoogle ScholarPubMed
21.Taylor, MJ, Sen, S, Bhagwagar, Z. Antidepressant response and the serotonin transporter gene-linked polymorphic region. Biol Psychiatry. 2010; 68(6): 536543.CrossRefGoogle ScholarPubMed
22.Murphy, GM Jr, Hollander, SB, Rodrigues, HE, Kremer, C, Schatzberg, AF. Effects of the serotonin transporter gene promoter polymorphism on mirtazapine and paroxetine efficacy and adverse events in geriatric major depression. Arch Gen Psychiatry. 2004; 61(11): 11631169.CrossRefGoogle ScholarPubMed
23.Hu, XZ, Rush, AJ, Charney, D, etal. Association between a functional serotonin transporter promoter polymorphism and citalopram treatment in adult outpatients with major depression. Arch Gen Psychiatry. 2007 July64(7): 783792.CrossRefGoogle ScholarPubMed
24.Kraft, JB, Peters, EJ, Slager, SL, etal. Analysis of association between the serotonin transporter and antidepressant response in a large clinical sample. Biol Psychiatry. 2007; 61(6): 734742.CrossRefGoogle Scholar
25.Paddock, S, Laje, G, Charney, D, etal. Association of GRIK4 with outcome of antidepressant treatment in the STAR*D cohort. Am J Psychiatry. 2007; 164(8): 11811188.CrossRefGoogle ScholarPubMed
26.Horstmann, S, Lucae, S, Menke, A, etal. Polymorphisms in GRIK4, HTR2A, and FKBP5 show interactive effects in predicting remission to antidepressant treatment. Neuropsychopharmacology. 2010; 35(3): 727740.CrossRefGoogle ScholarPubMed
27.Green, E, Craddock, N. Brain-derived neurotrophic factor as a potential risk locus for bipolar disorder: evidence, limitations, and implications. Curr Psychiatry Rep. 2003; 5(6): 469476.CrossRefGoogle ScholarPubMed
28.Saarelainen, T, Hendolin, P, Lucas, G, etal. Activation of the TrkB neurotrophin receptor is induced by antidepressant drugs and is required for antidepressant-induced behavioral effects. J Neurosci. 2003; 23(1): 349357.CrossRefGoogle ScholarPubMed
29.Egan, MF, Kojima, M, Callicott, JH, etal. The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell. 2003; 112(2): 257269.CrossRefGoogle ScholarPubMed
30.Ventriglia, M, Bocchio Chiavetto, L, Benussi, L, etal. Association between the BDNF 196 A/G polymorphism and sporadic Alzheimer's disease. Mol Psychiatry. 2002; 7(2): 136137.CrossRefGoogle ScholarPubMed
31.Hwang, JP, Tsai, SJ, Hong, CJ, etal. The Val66Met polymorphism of the brain-derived neurotrophic-factor gene is associated with geriatric depression. Neurobiology Aging. 2006; 27(12): 18341837.CrossRefGoogle ScholarPubMed
32.Ribeiro, L, Busnello, JV, Cantor, RM, etal. The brain-derived neurotrophic factor rs6265 (Val66Met) polymorphism and depression in Mexican-Americans. Neuroreport. 2007; 18(12): 12911293.CrossRefGoogle ScholarPubMed
33.Schumacher, J, Jamra, RA, Becker, T, etal. Evidence for a relationship between genetic variants at the brain-derived neurotrophic factor (BDNF) locus and major depression. Biol Psychiatry. 2005; 58(4): 307314.CrossRefGoogle ScholarPubMed
34.Hong, CJ, Huo, SJ, Yen, FC, etal. Association study of a brain-derived neurotrophic-factor genetic polymorphism and mood disorders, age of onset and suicidal behavior. Neuropsychobiology. 2003; 48(4): 186189.CrossRefGoogle ScholarPubMed
35.Tsai, SJ, Cheng, CY, Yu, YW, Chen, TJ, Hong, CJ. Association study of a brain-derived neurotrophic-factor genetic polymorphism and major depressive disorders, symptomatology, and antidepressant response. Am J Med Genet B Neuropsychiatr Genet. 2003; 123(1): 1922.CrossRefGoogle Scholar
36.Chen, L, Lawlor, DA, Lewis, SJ, etal. Genetic association study of BDNF in depression: finding from two cohort studies and a meta-analysis. Am J Med Genet B Neuropsychiatr Genet. 2008; 147B(6): 814821.CrossRefGoogle ScholarPubMed
37.Choi, MJ, Kang, RH, Lim, SW, Oh, KS, Lee, MS. Brain-derived neurotrophic factor gene polymorphism (Val66Met) and citalopram response in major depressive disorder. Brain Res. 2006; 1118(1): 176182.CrossRefGoogle ScholarPubMed
38.Anttila, S, Huuhka, K, Huuhka, M, etal. Interaction between 5-HT1A and BDNF genotypes increases the risk of treatment-resistant depression. J Neural Transm. 2007; 114(8): 10651068.CrossRefGoogle ScholarPubMed
39.Domschke, K, Lawford, B, Laje, G, etal. Brain-derived neurotrophic factor (BDNF) gene: no major impact on antidepressant treatment response. Int J Neuropsychopharmacol. 2010; 13(1): 93101.CrossRefGoogle ScholarPubMed
40.Zarate, CA Jr., Singh, JB, Carlson, PJ, etal. A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry. 2006; 63(8): 856864.CrossRefGoogle ScholarPubMed
41.Liu, RJ, Lee, FS, Li, XY, etal. Brain-derived neurotrophic factor Val66Metallele impairs basal and ketamine-stimulated synaptogenesis in prefrontal cortex. Biol Psychiatry. 2012; 71(11): 9961005.CrossRefGoogle ScholarPubMed
42.Laje, G, Lally, N, Mathews, D, etal. Brain-derived neurotrophic factor Val66Met polymorphism and antidepressant efficacy of ketamine in depressed patients. Biol Psychiatry. 2012; 72(11): e27e28.CrossRefGoogle ScholarPubMed
43.Garriock, HA, Kraft, JB, Shyn, SI, etal. A genomewide association study of citalopram response in major depressive disorder. Biol Psychiatry. 2010; 67(2): 133138.CrossRefGoogle ScholarPubMed
44.Ising, M, Lucae, S, Binder, EB, etal. A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch Gen Psychiatry. 2009; 66(9): 966975.CrossRefGoogle ScholarPubMed
45.Uher, R, Perroud, N, Ng, MY, etal. Genome-wide pharmacogenetics of antidepressant response in the GENDEP project. Am J Psychiatry. 2010; 167(5): 555564.CrossRefGoogle ScholarPubMed
46.Laje, G, McMahon, FJ. Genome-wide association studies of antidepressant outcome: a brief review. Prog Neuropsychopharmacol Biol Psychiatry. 2011; 35(7): 15531557.CrossRefGoogle ScholarPubMed
47.Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. Recommendations from the EGAPP Working Group: testing for cytochrome P450 polymorphisms in adults with nonpsychotic depression treated with selective serotonin reuptake inhibitors. Genet Med. 2007; 9(12): 819825.CrossRefGoogle Scholar
48.Huezo-Diaz, P, Perroud, N, Spencer, EP, etal. CYP2C19 genotype predicts steady state escitalopram concentration in GENDEP. J Psychopharmacol. 2012; 26(3): 398407.CrossRefGoogle ScholarPubMed
49.Food and Drug Administration. Antidepressant Use in Children, Adolescents and Adults. http://www.fda.gov/cder/drug/antidepressants/default.htm. Accessed February 5, 2006.Google Scholar
50.Perlis, RH, Purcell, S, Fava, M, etal. 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 Psychiatry. 2007; 64(6): 689697.CrossRefGoogle ScholarPubMed
51.Laje, G, Paddock, S, Manji, H, etal. Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am J Psychiatry. 2007; 164(10): 15301538.CrossRefGoogle ScholarPubMed
52.Menke, A, Lucae, S, Kloiber, S, etal. Genetic markers within glutamate receptors associated with antidepressant treatment-emergent suicidal ideation. Am J Psychiatry. 2008; 165(7): 917918.CrossRefGoogle ScholarPubMed
53.Laje, G, Allen, AS, Akula, N, etal. Genome-wide Association Study of Suicidal Ideation Emerging During Citalopram Treatment of Depressed Outpatients. Pharmacogenet Genomics. 2009; 19(9): 666674.CrossRefGoogle ScholarPubMed
54.Menke, A, Domschke, K, Czamara, D, etal. Genome-wide association study of antidepressant treatment-emergent suicidal ideation. Neuropsychopharmacology. 2012; 37(3): 797807.CrossRefGoogle ScholarPubMed
55.Perroud, N, Uher, R, Ng, MY, etal. Genome-wide association study of increasing suicidal ideation during antidepressant treatment in the GENDEP project. Pharmacogenomics J. 2012; 12(1): 6877.CrossRefGoogle ScholarPubMed
56.Perroud, N, Aitchison, KJ, Uher, R, etal. Genetic predictors of increase in suicidal ideation during antidepressant treatment in the GENDEP project. Neuropsychopharmacology. 2009; 34(12): 25172528.CrossRefGoogle ScholarPubMed
57.Grof, P, Duffy, A, Cavazzoni, P, etal. Is response to prophylactic lithium a familial trait? J Clin Psychiatry. 2002; 63(10): 942947.CrossRefGoogle ScholarPubMed
58.McCarthy, MJ, Leckband, SG, Kelsoe, JR. Pharmacogenetics of lithium response in bipolar disorder. Pharmacogenomics. 2010; 11(10): 14391465.CrossRefGoogle ScholarPubMed
59.Brandish, PE, Su, M, Holder, DJ, etal. Regulation of gene expression by lithium and depletion of inositol in slices of adult rat cortex. Neuron. 2005; 45(6): 861872.CrossRefGoogle ScholarPubMed
60.Popkie, AP, Zeidner, LC, Albrecht, AM, etal. Phosphatidylinositol 3-kinase (PI3 K) signaling via glycogen synthase kinase-3 (Gsk-3) regulates DNA methylation of imprinted loci. J Biol Chem. 2010; 285(53): 4133741347.CrossRefGoogle Scholar
61.Yu, Z, Ono, C, Sora, I, Tomita, H. Effect of chronic lithium treatment on gene expression profile in mouse microglia and brain dendritic cells. Nihon Shinkei Seishin Yakurigaku Zasshi. 2011; 31(2): 101102.Google ScholarPubMed
62.Perlis, RH, Dennehy, EB, Miklowitz, DJ, etal. Retrospective age at onset of bipolar disorder and outcome during two-year follow-up: results from the STEP-BD study. Bipolar Disord. 2009; 11(4): 391400.CrossRefGoogle ScholarPubMed
63.Squassina, A, Manchia, M, Borg, J, etal. Evidence for association of an ACCN1 gene variant with response to lithium treatment in Sardinian patients with bipolar disorder. Pharmacogenomics. 2011; 12(11): 15591569.CrossRefGoogle ScholarPubMed
64.Schulze, TG, Alda, M, Adli, M, etal. The International Consortium on Lithium Genetics (ConLiGen): an initiative by the NIMH and IGSLI to study the genetic basis of response to lithium treatment. Neuropsychobiology. 2010; 62(1): 7278.CrossRefGoogle Scholar
65.Chung, WH, Hung, SI, Hong, HS, etal. Medical genetics: a marker for Stevens-Johnson syndrome. Nature. 2004; 428(6982): 486.CrossRefGoogle ScholarPubMed
66.McCormack, M, Alfirevic, A, Bourgeois, S, etal. HLA-A*3101 and carbamazepine-induced hypersensitivity reactions in Europeans. N Engl J Med. 2011; 364(12): 11341143.CrossRefGoogle ScholarPubMed
6
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Pharmacogenetics of mood disorders: what clinicians need to know
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Pharmacogenetics of mood disorders: what clinicians need to know
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Pharmacogenetics of mood disorders: what clinicians need to know
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *