Abstract
The standard of care for antidepressant treatment in major depressive disorder (MDD) is a trial-and-error approach. Patients often have to undergo multiple medication trials for weeks to months before finding an effective treatment. Clinical factors such as severity of baseline symptoms and the presence of specific individual (anhedonia or insomnia) or cluster (atypical, melancholic, or anxious) of symptoms are commonly used without any evidence of their utility in selecting among currently available antidepressants. Genomic and proteomic biomarker have gained recent attention for their potential in informing antidepressant medication selection. In this report, we have reviewed some of the major pharmacogenomics studies along with individual genetic and proteomic biomarker of antidepressant response. Additionally, we have reviewed the blood-based protein biomarkers that can inform selection of one antidepressant over another. Among all currently available biomarkers, C-reactive protein (CRP) appears to be the most promising and pragmatic choice. Low CRP (<1 mg/L) in patients with MDD predicts better response to escitalopram while higher levels are associated with better response to noradrenergic/dopaminergic antidepressants. Future studies are needed to demonstrate the superiority of a CRP-based treatment assignment over high-quality measurement-based care in real-world clinical practices.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Altar CA, Hornberger J, Shewade A, Cruz V, Garrison J, Mrazek D (2013) Clinical validity of cytochrome P450 metabolism and serotonin gene variants in psychiatric pharmacotherapy. Int Rev Psychiatry 25:509–533
Altar CA, Carhart J, Allen JD, Hall-Flavin D, Winner J, Dechairo B (2015) Clinical utility of combinatorial pharmacogenomics-guided antidepressant therapy: evidence from three clinical studies. Mol Neuropsychiatry 1:145–155
Anttila S, Huuhka K, Huuhka M, Illi A, Rontu R, Leinonen E, Lehtimäki T (2008) Catechol-O-methyltransferase (COMT) polymorphisms predict treatment response in electroconvulsive therapy. Pharmacogenomics J 8:113
Arnow BA, Blasey C, Williams LM, Palmer DM, Rekshan W, Schatzberg AF, Etkin A, Kulkarni J, Luther JF, Rush AJ (2015) Depression subtypes in predicting antidepressant response: a report from the iSPOT-D trial. Am J Psychiatr 172:743–750
Baune BT, Hohoff C, Berger K, Neumann A, Mortensen S, Roehrs T, Deckert J, Arolt V, Domschke K (2007) Association of the COMT val158met variant with antidepressant treatment response in major depression. Neuropsychopharmacology 33:924
Beurel E, Harrington LE, Jope RS (2013) Inflammatory T helper 17 cells promote depression-like behavior in mice. Biol Psychiatry 73:622–630
Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, Altman RB, Arolt V, Brockmoller J, Chen CH, Domschke K, Hall-Flavin DK, Hong CJ, Illi A, Ji Y, Kampman O, Kinoshita T, Leinonen E, Liou YJ, Mushiroda T, Nonen S, Skime MK, Wang L, Baune BT, Kato M, Liu YL, Praphanphoj V, Stingl JC, Tsai SJ, Kubo M, Klein TE, Weinshilboum R (2015) The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry 5:e553
Binder EB, Salyakina D, Lichtner P, Wochnik GM, Ising M, Putz B, Papiol S, Seaman S, Lucae S, Kohli MA, Nickel T, Kunzel HE, Fuchs B, Majer M, Pfennig A, Kern N, Brunner J, Modell S, Baghai T, Deiml T, Zill P, Bondy B, Rupprecht R, Messer T, Kohnlein O, Dabitz H, Bruckl T, Muller N, Pfister H, Lieb R, Mueller JC, Lohmussaar E, Strom TM, Bettecken T, Meitinger T, Uhr M, Rein T, Holsboer F, Muller-Myhsok B (2004) Polymorphisms in FKBP5 are associated with increased recurrence of depressive episodes and rapid response to antidepressant treatment. Nat Genet 36:1319–1325
Bobo WV, Chen H, Trivedi MH, Stewart JW, Nierenberg AA, Fava M, Kurian BT, Warden D, Morris DW, Luther JF (2011) Randomized comparison of selective serotonin reuptake inhibitor (escitalopram) monotherapy and antidepressant combination pharmacotherapy for major depressive disorder with melancholic features: a CO-MED report. J Affect Disord 133:467–476
Chen J, Lipska BK, Halim N, Ma QD, Matsumoto M, Melhem S, Kolachana BS, Hyde TM, Herman MM, Apud J (2004) Functional analysis of genetic variation in catechol-O-methyltransferase (COMT): effects on mRNA, protein, and enzyme activity in postmortem human brain. Am J Hum Genet 75:807–821
Cheng Y, Desse S, Martinez A, Worthen RJ, Jope RS, Beurel E (2018) TNF alpha disrupts blood brain barrier integrity to maintain prolonged depressive-like behavior in mice. Brain Behav Immun 69:556–567
Dong C, Wong M-L, Licinio J (2009) Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: association with major depression and antidepressant response in Mexican-Americans. Mol Psychiatry 14:1105
Ellsworth KA, Moon I, Eckloff BW, Fridley BL, Jenkins GD, Batzler A, Biernacka JM, Abo R, Brisbin A, Ji Y, Hebbring S, Wieben ED, Mrazek DA, Weinshilboum RM, Wang L (2013) FKBP5 genetic variation: association with selective serotonin reuptake inhibitor treatment outcomes in major depressive disorder. Pharmacogenet Genomics 23:156–166
Friedman ES, Davis LL, Zisook S, Wisniewski SR, Trivedi MH, Fava M, Rush AJ, Team C-MS (2012) Baseline depression severity as a predictor of single and combination antidepressant treatment outcome: results from the CO-MED trial. Eur Neuropsychopharmacol 22:183–199
Gadad BS, Jha MK, Czysz A, Furman JL, Mayes TL, Emslie MP, Trivedi MH (2018a) Peripheral biomarkers of major depression and antidepressant treatment response: current knowledge and future outlooks. J Affect Disord 233:3–14
Gadad BS, Raj P, Jha MK, Carmody T, Dozmorov I, Mayes TL, Wakeland EK, Trivedi MH (2018b) Association of novel ALX4 gene polymorphisms with antidepressant treatment response: findings from the CO-MED trial. Mol Neuropsychiatry 4:7–19
Gartlehner G, Hansen RA, Morgan LC, Thaler K, Lux L, Van Noord M, Mager U, Thieda P, Gaynes BN, Wilkins T (2011) Comparative benefits and harms of second-generation antidepressants for treating major depressive disorder: an updated meta-analysis. Ann Intern Med 155:772–785
Gelenberg AJ, Freeman MP, Markowitz JC, Rosenbaum JF, Thase ME, Trivedi MH, Van Rhoads RS, Reus VI, Raymond DePaulo J Jr, Fawcett JA (2010) Practice guideline for the treatment of patients with major depressive disorder third edition. Am J Psychiatry 167:1
Gex-Fabry M, Eap CB, Oneda B, Gervasoni N, Aubry J-M, Bondolfi G, Bertschy G (2008) CYP2D6 and ABCB1 genetic variability: influence on paroxetine plasma level and therapeutic response. Ther Drug Monit 30:474–482
Green E, Goldstein-Piekarski AN, Schatzberg AF, Rush AJ, Ma J, Williams L (2017) Personalizing antidepressant choice by sex, body mass index, and symptom profile: an iSPOT-D report. Personalized Med Psychiatry 1:65–73
Hennings JM, Owashi T, Binder EB, Horstmann S, Menke A, Kloiber S, Dose T, Wollweber B, Spieler D, Messer T, Lutz R, Kunzel H, Bierner T, Pollmacher T, Pfister H, Nickel T, Sonntag A, Uhr M, Ising M, Holsboer F, Lucae S (2009) Clinical characteristics and treatment outcome in a representative sample of depressed inpatients - findings from the Munich Antidepressant Response Signature (MARS) project. J Psychiatr Res 43:215–229
Hennings JM, Kohli MA, Czamara D, Giese M, Eckert A, Wolf C, Heck A, Domschke K, Arolt V, Baune BT, Horstmann S, Bruckl T, Klengel T, Menke A, Muller-Myhsok B, Ising M, Uhr M, Lucae S (2013) Possible associations of NTRK2 polymorphisms with antidepressant treatment outcome: findings from an extended tag SNP approach. PLoS One 8:e64947
Hodgson K, Tansey KE, Uher R, Dernovšek MZ, Mors O, Hauser J, Souery D, Maier W, Henigsberg N, Rietschel M (2015) Exploring the role of drug-metabolising enzymes in antidepressant side effects. Psychopharmacology 232:2609–2617
Holsboer F (2001) Antidepressant drug discovery in the postgenomic era. World J Biol Psychiatry 2:165–177
Hong C, Chen T, Yu YW, Tsai S (2006) Response to fluoxetine and serotonin 1A receptor (C-1019G) polymorphism in Taiwan Chinese major depressive disorder. Pharmacogenomics J 6:27
Horstmann S, Lucae S, Menke A, Hennings JM, Ising M, Roeske D, Müller-Myhsok B, Holsboer F, Binder EB (2010) Polymorphisms in GRIK4, HTR2A, and FKBP5 show interactive effects in predicting remission to antidepressant treatment. Neuropsychopharmacology 35:727
Investigators G, Investigators M, Investigators SD (2013) Common genetic variation and antidepressant efficacy in major depressive disorder: a meta-analysis of three genome-wide pharmacogenetic studies. Am J Psychiatr 170:207–217
Jha MK, Trivedi MH (2018) Personalized antidepressant selection and pathway to novel treatments: clinical utility of targeting inflammation. Int J Mol Sci 19
Jha MK, Minhajuddin A, Gadad BS, Greer T, Grannemann B, Soyombo A, Mayes TL, Rush AJ, Trivedi MH (2017a) Can C-reactive protein inform antidepressant medication selection in depressed outpatients? Findings from the CO-MED trial. Psychoneuroendocrinology 78:105–113
Jha MK, Minhajuddin A, Gadad BS, Greer TL, Mayes TL, Trivedi MH (2017b) Interleukin 17 selectively predicts better outcomes with bupropion-SSRI combination: novel T cell biomarker for antidepressant medication selection. Brain Behav Immun 66:103–110
Jha MK, Minhajuddin A, Gadad BS, Trivedi MH (2017c) Platelet-derived growth factor as an antidepressant treatment selection biomarker: higher levels selectively predict better outcomes with bupropion-SSRI combination. Int J Neuropsychopharmacol 20:919–927
Jha MK, Wakhlu S, Dronamraju N, Minhajuddin A, Greer TL, Trivedi MH (2018a) Validating pre-treatment body mass index as moderator of antidepressant treatment outcomes: findings from CO-MED trial. J Affect Disord 234:34–37
Jha MK, Miller AH, Minhajuddin A, Trivedi MH (2018b) Association of T and non-T cell cytokines with anhedonia: role of gender differences. Psychoneuroendocrinology 95:1–7
Jha M, Minhajuddin A, Gadad B, Trivedi M (2018c) 68. Blood brain barrier dysfunction selectively predicts poorer outcomes with SSRI monotherapy vs. antidepressant combinations: clinical utility of novel astrocytic marker. Biol Psychiatry 83:S28
Ji Y, Schaid DJ, Desta Z, Kubo M, Batzler AJ, Snyder K, Mushiroda T, Kamatani N, Ogburn E, Hall-Flavin D, Flockhart D, Nakamura Y, Mrazek DA, Weinshilboum RM (2014) Citalopram and escitalopram plasma drug and metabolite concentrations: genome-wide associations. Br J Clin Pharmacol 78:373–383
Katharina D, Maxim Z, Julia D, Sarina N, Christa H, Baune TB, Juergen D, Volker A, Peter Z (2010) COMT val158met influence on electroconvulsive therapy response in major depression. Am J Med Genet B Neuropsychiatr Genet 153B:286–290
Kato M, Fukuda T, Serretti A, Wakeno M, Okugawa G, Ikenaga Y, Hosoi Y, Takekita Y, Mandelli L, Azuma J (2008) ABCB1 (MDR1) gene polymorphisms are associated with the clinical response to paroxetine in patients with major depressive disorder. Prog Neuro-Psychopharmacol Biol Psychiatry 32:398–404
Kraft JB, Peters EJ, Slager SL, Jenkins GD, Reinalda MS, McGrath PJ, Hamilton SP (2007) Analysis of association between the serotonin transporter and antidepressant response in a large clinical sample. Biol Psychiatry 61:734–742
Laika B, Leucht S, Steimer W (2006) ABCB1 (P-glycoprotein/MDR1) gene G2677T/a sequence variation (polymorphism): lack of association with side effects and therapeutic response in depressed inpatients treated with amitriptyline. Clin Chem 52:893–895
Laje G, Perlis RH, Rush AJ, McMahon FJ (2009) Pharmacogenetics studies in STAR(*)D: strengths, limitations, and results. Psychiatr Serv 60:1446–1457
Lucae S, Ising M, Horstmann S, Baune BT, Arolt V, Müller-Myhsok B, Holsboer F, Domschke K (2010) HTR2A gene variation is involved in antidepressant treatment response. Eur Neuropsychopharmacol 20:65–68
Maron E, Tammiste A, Kallassalu K, Eller T, Vasar V, Nutt DJ, Metspalu A (2009) Serotonin transporter promoter region polymorphisms do not influence treatment response to escitalopram in patients with major depression. Eur Neuropsychopharmacol 19:451–456
McMahon FJ, Buervenich S, Charney D, Lipsky R, Rush AJ, Wilson AF, Sorant AJ, Papanicolaou GJ, Laje G, Fava M (2006) Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet 78:804–814
Miller AH, Trivedi MH, Jha MK (2017) Is C-reactive protein ready for prime time in the selection of antidepressant medications? Psychoneuroendocrinology 84:206
Mrazek D, Rush A, Biernacka J, O’Kane D, Cunningham J, Wieben E, Schaid D, Drews M, Courson V, Snyder K (2009) SLC6A4 variation and citalopram response. Am J Med Genet B Neuropsychiatr Genet 150:341–351
Mrazek DA, Biernacka JM, McAlpine DE, Benitez J, Karpyak VM, Williams MD, Hall-Flavin DK, Netzel PJ, Passov V, Rohland BM, Shinozaki G, Hoberg AA, Snyder KA, Drews MS, Skime MK, Sagen JA, Schaid DJ, Weinshilboum R, Katzelnick DJ (2014) Treatment outcomes of depression: the pharmacogenomic research network antidepressant medication pharmacogenomic study. J Clin Psychopharmacol 34:313–317
Nikisch G, Eap CB, Baumann P (2008) Citalopram enantiomers in plasma and cerebrospinal fluid of ABCB1 genotyped depressive patients and clinical response: a pilot study. Pharmacol Res 58:344–347
O’Connell CP, Goldstein-Piekarski AN, Nemeroff CB, Schatzberg AF, Debattista C, Carrillo-Roa T, Binder EB, Dunlop BW, Edward Craighead W, Mayberg HS, Williams LM (2018a) Antidepressant outcomes predicted by genetic variation in corticotropin-releasing hormone binding protein. Am J Psychiatry 175:251–261
O’Connell CP, Goldstein-Piekarski AN, Nemeroff CB, Schatzberg AF, Debattista C, Carrillo-Roa T, Binder EB, Dunlop BW, Craighead WE, Mayberg HS, Williams LM (2018b) Antidepressant outcomes predicted by genetic variation in Corticotropin-releasing hormone binding protein. Am J Psychiatry 175:251–261
Paddock S, Laje G, Charney D, Rush AJ, Wilson AF, Sorant AJ, Lipsky R, Wisniewski SR, Manji H, McMahon FJ (2007) Association of GRIK4 with outcome of antidepressant treatment in the STAR* D cohort. Am J Psychiatr 164:1181–1188
Peles AM, Bozina N, Sagud M, Kuzman MR, Lovric M (2008) MDR1 gene polymorphism: therapeutic response to paroxetine among patients with major depression. Prog Neuro-Psychopharmacol Biol Psychiatry 32:1439–1444
Perlis RH, Fijal B, Dharia S, Heinloth AN, Houston JP (2010) Failure to replicate genetic associations with antidepressant treatment response in duloxetine-treated patients. Biol Psychiatry 67:1110–1113
Perroud N, Aitchison KJ, Uher R, Smith R, Huezo-Diaz P, Marusic A, Maier W, Mors O, Placentino A, Henigsberg N, Rietschel M, Hauser J, Souery D, Kapelski P, Bonvicini C, Zobel A, Jorgensen L, Petrovic A, Kalember P, Schulze TG, Gupta B, Gray J, Lewis CM, Farmer AE, McGuffin P, Craig I (2009) Genetic predictors of increase in suicidal ideation during antidepressant treatment in the GENDEP project. Neuropsychopharmacology 34:2517–2528
Peters EJ, Slager SL, McGrath PJ, Knowles JA, Hamilton SP (2004) Investigation of serotonin-related genes in antidepressant response. Mol Psychiatry 9:879–889
Peters EJ, Slager SL, Kraft JB, Jenkins GD, Reinalda MS, McGrath PJ, Hamilton SP (2008) Pharmacokinetic genes do not influence response or tolerance to citalopram in the STAR* D sample. PLoS One 3:e1872
Peters EJ, Slager SL, Jenkins GD, Reinalda MS, Garriock HA, Shyn SI, Kraft JB, McGrath PJ, Hamilton SP (2009) Resequencing of serotonin-related genes and association of tagging SNPs to citalopram response. Pharmacogenet Genomics 19:1
Porcelli S, Drago A, Fabbri C, Gibiino S, Calati R, Serretti A (2011) Pharmacogenetics of antidepressant response. J Psychiatry Neurosci 36:87
Porcelli S, Fabbri C, Serretti A (2012) Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with antidepressant efficacy. Eur Neuropsychopharmacol 22:239–258
Pu M, Zhang Z, Xu Z, Shi Y, Geng L, Yuan Y, Zhang X, Reynolds GP (2013) Influence of genetic polymorphisms in the glutamatergic and GABAergic systems and their interactions with environmental stressors on antidepressant response. Pharmacogenomics 14:277–288
Schatzberg AF, DeBattista C, Lazzeroni LC, Etkin A, Murphy GM Jr, Williams LM (2015) ABCB1 genetic effects on antidepressant outcomes: a report from the iSPOT-D trial. Am J Psychiatr 172:751–759
Serretti A, Chiesa A, Crisafulli C, Massat I, Linotte S, Calati R, Kasper S, Bailer U, Lecrubier Y, Fink M (2012) Failure to replicate influence of GRIK4 and GNB3 polymorphisms on treatment outcome in major depression. Neuropsychobiology 65:70–75
Shelton RC, Falola M, Li L, Zajecka J, Fava M, Papakostas GI (2015) The pro-inflammatory profile of depressed patients is (partly) related to obesity. J Psychiatr Res 70:91–97
Strimbu K, Tavel JA (2010) What are biomarkers? Curr Opin HIV AIDS 5:463–466
Sung SC, Haley CL, Wisniewski SR, Fava M, Nierenberg AA, Warden D, Morris DW, Kurian BT, Trivedi MH, Rush AJ (2012) The impact of chronic depression on acute and long-term outcomes in a randomized trial comparing selective serotonin reuptake inhibitor monotherapy versus each of 2 different antidepressant medication combinations. J Clin Psychiatry 73:967–976
Sung S, Wisniewski S, Balasubramani G, Zisook S, Kurian B, Warden D, Trivedi M, Rush A (2013) Does early-onset chronic or recurrent major depression impact outcomes with antidepressant medications? A CO-MED trial report. Psychol Med 43:945–960
Sung SC, Wisniewski SR, Luther JF, Trivedi MH, Rush AJ, Team CS (2015) Pre-treatment insomnia as a predictor of single and combination antidepressant outcomes: a CO-MED report. J Affect Disord 174:157–164
Tadić A, Müller MJ, Rujescu D, Kohnen R, Stassen HH, Dahmen N, Szegedi A (2007) The MAOA T941G polymorphism and short-term treatment response to mirtazapine and paroxetine in major depression. Am J Med Genet B Neuropsychiatr Genet 144B:325–331
Tiwari AK, Zai CC, Sajeev G, Arenovich T, Müller DJ, Kennedy JL (2013) Analysis of 34 candidate genes in bupropion and placebo remission. Int J Neuropsychopharmacol 16:771–781
Trivedi MH (2016) Right patient, right treatment, right time: biosignatures and precision medicine in depression. World Psychiatry 15:237–238
Uher R, Huezo-Diaz P, Perroud N, Smith R, Rietschel M, Mors O, Hauser J, Maier W, Kozel D, Henigsberg N, Barreto M, Placentino A, Dernovsek MZ, Schulze TG, Kalember P, Zobel A, Czerski PM, Larsen ER, Souery D, Giovannini C, Gray JM, Lewis CM, Farmer A, Aitchison KJ, McGuffin P, Craig I (2009) Genetic predictors of response to antidepressants in the GENDEP project. Pharmacogenomics J 9:225–233
Uher R, Tansey KE, Dew T, Maier W, Mors O, Hauser J, Dernovsek MZ, Henigsberg N, Souery D, Farmer A, McGuffin P (2014) An inflammatory biomarker as a differential predictor of outcome of depression treatment with escitalopram and nortriptyline. Am J Psychiatry 171:1278–1286
Uhr M, Tontsch A, Namendorf C, Ripke S, Lucae S, Ising M, Dose T, Ebinger M, Rosenhagen M, Kohli M (2008) Polymorphisms in the drug transporter gene ABCB1 predict antidepressant treatment response in depression. Neuron 57:203–209
Zeier Z, Carpenter LL, Kalin NH, Rodriguez CI, McDonald WM, Widge AS, Nemeroff CB (2018) Clinical implementation of pharmacogenetic decision support tools for antidepressant drug prescribing. Am J Psychiatry. https://doi.org/10.1176/appi.ajp.2018.17111282
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Jha, M.K., Trivedi, M.H. (2018). Pharmacogenomics and Biomarkers of Depression. In: Macaluso, M., Preskorn, S. (eds) Antidepressants. Handbook of Experimental Pharmacology, vol 250. Springer, Cham. https://doi.org/10.1007/164_2018_171
Download citation
DOI: https://doi.org/10.1007/164_2018_171
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-10948-6
Online ISBN: 978-3-030-10949-3
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)