Genome-wide association study of antidepressant response: involvement of the inorganic cation transmembrane transporter activity pathway

Enrico Cocchi, Chiara Fabbri, Changsu Han, Soo-Jung Lee, Ashwin A Patkar, Prakash S Masand, Chi-Un Pae, Alessandro Serretti, Enrico Cocchi, Chiara Fabbri, Changsu Han, Soo-Jung Lee, Ashwin A Patkar, Prakash S Masand, Chi-Un Pae, Alessandro Serretti

Abstract

Background: Genome-wide association studies (GWAS) represent the current frontier in pharmacogenomics. Thousands of subjects of Caucasian ancestry have been included in previous GWAS investigating antidepressant response. GWAS focused on this phenotype are lacking in Asian populations.

Methods: A sample of 109 major depressive disorder (MDD) patients of Korean origin in antidepressant treatment was collected. Phenotypes were response and remission according to the Hamilton Rating Scale for Depression (HRSD). Genome-wide genotyping was performed using the Illumina Human Omni2.5-8 platform. The same phenotypes were used in the STAR*D level 1 (n = 1677) for independent replication. In order to corroborate findings and increase the comparability between the two datasets, three levels of analysis (SNPs, genes and pathways) were carried out. Bonferroni correction, permutations, and replication across samples were used to reduce the risk of false positives.

Results: Among the genes replicated across the two samples (permutated p < 0.05 in both of them), CTNNA3 appeared promising. The inorganic cation transmembrane transporter activity pathway (GO:0022890) was associated with antidepressant response in both samples (p = 2.9e-5 and p = 0.001 in the Korean and STAR*D samples, respectively) and this pathway included CACNA1A, CACNA1C, and CACNB2 genes.

Conclusions: The present study supported the involvement of genes coding for subunits of L-type voltage-gated calcium channel in antidepressant efficacy across different ethnicities but replication of findings is required before any definitive statement.

Trial registration: ClinicalTrials.gov NCT00021528.

Keywords: Antidepressant; Calcium channel; Cation transmembrane transporter; GWAS; Gene; Major depression; Pathway; Pharmacogenomics.

References

    1. Tansey KE, Guipponi M, Hu X, Domenici E, Lewis G, Malafosse A, Wendland JR, Lewis CM, McGuffin P, Uher R. Contribution of common genetic variants to antidepressant response. Biol Psychiatry. 2013;73:679–82. doi: 10.1016/j.biopsych.2012.10.030.
    1. Garriock HA, Kraft JB, Shyn SI, Peters EJ, Yokoyama JS, Jenkins GD, Reinalda MS, Slager SL, McGrath PJ, Hamilton SP. A genomewide association study of citalopram response in major depressive disorder. Biol Psychiatry. 2010;67:133–8. doi: 10.1016/j.biopsych.2009.08.029.
    1. Uher R, Perroud N, Ng MY, Hauser J, Henigsberg N, Maier W, Mors O, Placentino A, Rietschel M, Souery D, et al. Genome-wide pharmacogenetics of antidepressant response in the GENDEP project. Am J Psychiatry. 2010;167:555–64. doi: 10.1176/appi.ajp.2009.09070932.
    1. Ising M, Lucae S, Binder EB, Bettecken T, Uhr M, Ripke S, Kohli MA, Hennings JM, Horstmann S, Kloiber S, et al. A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch Gen Psychiatry. 2009;66:966–75. doi: 10.1001/archgenpsychiatry.2009.95.
    1. Hunter AM, Leuchter AF, Power RA, Muthen B, McGrath PJ, Lewis CM, Cook IA, Garriock HA, McGuffin P, Uher R, et al. A genome-wide association study of a sustained pattern of antidepressant response. J Psychiatr Res. 2013;47:1157–65. doi: 10.1016/j.jpsychires.2013.05.002.
    1. Tansey KE, Guipponi M, Perroud N, Bondolfi G, Domenici E, Evans D, Hall SK, Hauser J, Henigsberg N, Hu X, et al. Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis. PLoS Med. 2012;9:e1001326. doi: 10.1371/journal.pmed.1001326.
    1. GENDEP, MARS, 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;170:207–17. doi: 10.1176/appi.ajp.2012.12020237.
    1. Sasayama D, Hiraishi A, Tatsumi M, Kamijima K, Ikeda M, Umene-Nakano W, Yoshimura R, Nakamura J, Iwata N, Kunugi H. Possible association of CUX1 gene polymorphisms with antidepressant response in major depressive disorder. Pharmacogen J. 2013;13:354–8. doi: 10.1038/tpj.2012.18.
    1. Myung W, Kim J, Lim SW, Shim S, Won HH, Kim S, Lee MS, Chang HS, Kim JW, Carroll BJ, et al. A genome-wide association study of antidepressant response in Koreans. Translat Psychiatry. 2015;5:e633. doi: 10.1038/tp.2015.127.
    1. Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, Altman RB, Arolt V, Brockmoller J, Chen CH, et al. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Translat Psychiatry. 2015;5:e553. doi: 10.1038/tp.2015.47.
    1. Jin L, Zuo XY, Su WY, Zhao XL, Yuan MQ, Han LZ, Zhao X, Chen YD, Rao SQ. Pathway-based Analysis Tools for Complex Diseases: A Review. Genomics Proteomics Bioinformatics. 2014;12:210–20. doi: 10.1016/j.gpb.2014.10.002.
    1. Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, Franz M, Grouios C, Kazi F, Lopes CT, et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010;38:W214–20. doi: 10.1093/nar/gkq537.
    1. Segre AV, Consortium D, investigators M, Groop L, Mootha VK, Daly MJ, Altshuler D. Common inherited variation in mitochondrial genes is not enriched for associations with type 2 diabetes or related glycemic traits. PLoS Genet. 2010;6(8). doi:10.1371/journal.pgen.1001058.
    1. Lee PH, O'Dushlaine C, Thomas B, Purcell SM. INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics. 2012;28:1797–9. doi: 10.1093/bioinformatics/bts191.
    1. Holmans P, Green EK, Pahwa JS, Ferreira MA, Purcell SM, Sklar P, Wellcome Trust Case-Control C, Owen MJ, O'Donovan MC, Craddock N. Gene ontology analysis of GWA study data sets provides insights into the biology of bipolar disorder. Am J Hum Genet. 2009;85:13–24.
    1. Nam D, Kim J, Kim SY, Kim S. GSA-SNP: a general approach for gene set analysis of polymorphisms. Nucleic Acids Res. 2010;38:W749–54. doi: 10.1093/nar/gkq428.
    1. Fabbri C, Serretti A. Genetics of long-term treatment outcome in bipolar disorder. Prog Neuro-Psychopharmacol Biol Psychiatry. 2015;65:17–24. doi: 10.1016/j.pnpbp.2015.08.008.
    1. First MB, Spitzer RL, Gibbon M, Williams JBW. Structured Clinical Interview for DSM-IV-TR Axis I Disorders, Research Version, Patient Edition. (SCID-I/P) New York: Biometrics Research: New York State Psychiatric Institute; 2002.
    1. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56–62. doi: 10.1136/jnnp.23.1.56.
    1. Howland RH. Sequenced Treatment Alternatives to Relieve Depression (STAR*D). Part 1: study design. J Psychosoc Nurs Ment Health Serv. 2008;46:21–4. doi: 10.3928/02793695-20080901-06.
    1. Trivedi MH, Rush AJ, Ibrahim HM, Carmody TJ, Biggs MM, Suppes T, Crismon ML, Shores-Wilson K, Toprac MG, Dennehy EB, et al. The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol Med. 2004;34:73–82. doi: 10.1017/S0033291703001107.
    1. Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, Norquist G, Howland RH, Lebowitz B, McGrath PJ, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:28–40. doi: 10.1176/appi.ajp.163.1.28.
    1. Anderson CA, Pettersson FH, Clarke GM, Cardon LR, Morris AP, Zondervan KT. Data quality control in genetic case-control association studies. Nat Protoc. 2010;5:1564–73. doi: 10.1038/nprot.2010.116.
    1. Shyn SI, Shi J, Kraft JB, Potash JB, Knowles JA, Weissman MM, Garriock HA, Yokoyama JS, McGrath PJ, Peters EJ, et al. Novel loci for major depression identified by genome-wide association study of Sequenced Treatment Alternatives to Relieve Depression and meta-analysis of three studies. Mol Psychiatry. 2011;16:202–15. doi: 10.1038/mp.2009.125.
    1. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75. doi: 10.1086/519795.
    1. Fabbri C, Di Girolamo G, Serretti A. Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research. Am J Med Genet B Neuropsychiatr Genet. 2013;162B:487–520. doi: 10.1002/ajmg.b.32184.
    1. Cline MS, Smoot M, Cerami E, Kuchinsky A, Landys N, Workman C, Christmas R, Avila-Campilo I, Creech M, Gross B, et al. Integration of biological networks and gene expression data using Cytoscape. Nat Protoc. 2007;2:2366–82. doi: 10.1038/nprot.2007.324.
    1. Montojo J, Zuberi K, Rodriguez H, Kazi F, Wright G, Donaldson SL, Morris Q, Bader GD. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics. 2010;26:2927–8. doi: 10.1093/bioinformatics/btq562.
    1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9. doi: 10.1038/75556.
    1. Drago A, Cocchi E, Crisafulli C, Serretti A. A molecular pathway analysis of the glutamatergic-monoaminergic interplay serves to investigate the number of depressive records during citalopram treatment. J Neural Transm (Vienna). 2015;122(3):465–75.
    1. Abatangelo L, Maglietta R, Distaso A, D'Addabbo A, Creanza TM, Mukherjee S, Ancona N. Comparative study of gene set enrichment methods. BMC Bioinformatics. 2009;10:275. doi: 10.1186/1471-2105-10-275.
    1. Fridley BL, Jenkins GD, Biernacka JM. Self-contained gene-set analysis of expression data: an evaluation of existing and novel methods. PLoS One. 2010;5:e12693. doi: 10.1371/journal.pone.0012693.
    1. Purcell S, Cherny SS, Sham PC. Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics. 2003;19:149–50. doi: 10.1093/bioinformatics/19.1.149.
    1. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91. doi: 10.3758/BF03193146.
    1. Lauks J, Klemmer P, Farzana F, Karupothula R, Zalm R, Cooke NE, Li KW, Smit AB, Toonen R, Verhage M. Synapse associated protein 102 (SAP102) binds the C-terminal part of the scaffolding protein neurobeachin. PLoS One. 2012;7:e39420. doi: 10.1371/journal.pone.0039420.
    1. Nair R, Lauks J, Jung S, Cooke NE, de Wit H, Brose N, Kilimann MW, Verhage M, Rhee J. Neurobeachin regulates neurotransmitter receptor trafficking to synapses. J Cell Biol. 2013;200:61–80. doi: 10.1083/jcb.201207113.
    1. Drago A, Crisafulli C, Sidoti A, Serretti A. The molecular interaction between the glutamatergic, noradrenergic, dopaminergic and serotoninergic systems informs a detailed genetic perspective on depressive phenotypes. Prog Neurobiol. 2011;94:418–60. doi: 10.1016/j.pneurobio.2011.05.009.
    1. Rogowski K, van Dijk J, Magiera MM, Bosc C, Deloulme JC, Bosson A, Peris L, Gold ND, Lacroix B, Bosch Grau M, et al. A family of protein-deglutamylating enzymes associated with neurodegeneration. Cell. 2010;143:564–78. doi: 10.1016/j.cell.2010.10.014.
    1. Budziszewska B, Jaworska-Feil L, Tetich M, Basta-Kaim A, Kubera M, Leskiewicz M, Lason W. Regulation of the human corticotropin-releasing-hormone gene promoter activity by antidepressant drugs in Neuro-2A and AtT-20 cells. Neuropsychopharmacology. 2004;29:785–94. doi: 10.1038/sj.npp.1300379.
    1. Kirchheiner J, Nickchen K, Sasse J, Bauer M, Roots I, Brockmoller J. A 40-basepair VNTR polymorphism in the dopamine transporter (DAT1) gene and the rapid response to antidepressant treatment. Pharmacogen J. 2007;7:48–55. doi: 10.1038/sj.tpj.6500398.
    1. Tiwari AK, Zai CC, Sajeev G, Arenovich T, Muller DJ, Kennedy JL. Analysis of 34 candidate genes in bupropion and placebo remission. Int J Neuropsychopharmacol. 2013;16:771–81. doi: 10.1017/S1461145712000843.
    1. Cross-Disorder, Group, of, the, Psychiatric, Genomics, Consortium Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371–9. doi: 10.1016/S0140-6736(12)62129-1.
    1. Wang N, Zhang GF, Liu XY, Sun HL, Wang XM, Qiu LL, Yang C, Yang JJ. Downregulation of neuregulin 1-ErbB4 signaling in parvalbumin interneurons in the rat brain may contribute to the antidepressant properties of ketamine. J Mol Neurosci. 2014;54:211–8. doi: 10.1007/s12031-014-0277-8.
    1. Borglum AD, Demontis D, Grove J, Pallesen J, Hollegaard MV, Pedersen CB, Hedemand A, Mattheisen M, Uitterlinden A, Nyegaard M, et al. Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci. Mol Psychiatry. 2014;19:325–33. doi: 10.1038/mp.2013.2.
    1. Mostany R, Valdizan EM, Pazos A. A role for nuclear beta-catenin in SNRI antidepressant-induced hippocampal cell proliferation. Neuropharmacology. 2008;55:18–26. doi: 10.1016/j.neuropharm.2008.04.012.
    1. Fabbri C, Marsano A, Albani D, Chierchia A, Calati R, Drago A, Crisafulli C, Calabro M, Kasper S, Lanzenberger R, et al. PPP3CC gene: a putative modulator of antidepressant response through the B-cell receptor signaling pathway. Pharmacogen J. 2014;14:463–72. doi: 10.1038/tpj.2014.15.
    1. Lin JY, Jiang MY, Kan ZM, Chu Y. Influence of 5-HTR2A genetic polymorphisms on the efficacy of antidepressants in the treatment of major depressive disorder: a meta-analysis. J Affect Disord. 2014;168:430–8. doi: 10.1016/j.jad.2014.06.012.
    1. Hu Y, Xing J, Wang L, Huang M, Guo X, Chen L, Lin M, Zhou Y, Liu Z, Zhou Z, et al. RGS22, a novel cancer/testis antigen, inhibits epithelial cell invasion and metastasis. Clin Exp Metastasis. 2011;28:541–9. doi: 10.1007/s10585-011-9390-z.
    1. Habuchi H, Tanaka M, Habuchi O, Yoshida K, Suzuki H, Ban K, Kimata K. The occurrence of three isoforms of heparan sulfate 6-O-sulfotransferase having different specificities for hexuronic acid adjacent to the targeted N-sulfoglucosamine. J Biol Chem. 2000;275:2859–68. doi: 10.1074/jbc.275.4.2859.
    1. Giovannetti E, Wang Q, Avan A, Funel N, Lagerweij T, Lee JH, Caretti V, van der Velde A, Boggi U, Wang Y, et al. Role of CYB5A in pancreatic cancer prognosis and autophagy modulation. J Natl Cancer Inst. 2014;106:djt346. doi: 10.1093/jnci/djt346.
    1. Elakovic I, Djordjevic A, Adzic M, Djordjevic J, Radojcic M, Matic G. Gender-specific response of brain corticosteroid receptors to stress and fluoxetine. Brain Res. 2011;1384:61–8. doi: 10.1016/j.brainres.2011.01.078.
    1. Heydendael W, Jacobson L. Differential effects of imipramine and phenelzine on corticosteroid receptor gene expression in mouse brain: potential relevance to antidepressant response. Brain Res. 2008;1238:93–107. doi: 10.1016/j.brainres.2008.08.018.
    1. Malki K, Campbell J, Davies M, Keers R, Uher R, Ward M, Paya-Cano J, Aitchinson KJ, Binder E, Sluyter F, et al. Pharmacoproteomic investigation into antidepressant response in two mouse inbred strains. Proteomics. 2012;12:2355–65. doi: 10.1002/pmic.201100306.
    1. Dao DT, Mahon PB, Cai X, Kovacsics CE, Blackwell RA, Arad M, Shi J, Zandi PP, O'Donnell P, Bipolar Genome Study C, et al. Mood disorder susceptibility gene CACNA1C modifies mood-related behaviors in mice and interacts with sex to influence behavior in mice and diagnosis in humans. Biol Psychiatry. 2010;68:801–10. doi: 10.1016/j.biopsych.2010.06.019.
    1. Bhat S, Dao DT, Terrillion CE, Arad M, Smith RJ, Soldatov NM, Gould TD. CACNA1C (Cav1.2) in the pathophysiology of psychiatric disease. Prog Neurobiol. 2012;99:1–14. doi: 10.1016/j.pneurobio.2012.06.001.
    1. Koncz I, Szasz BK, Szabo SI, Kiss JP, Mike A, Lendvai B, Sylvester Vizi E, Zelles T. The tricyclic antidepressant desipramine inhibited the neurotoxic, kainate-induced [Ca(2+)]i increases in CA1 pyramidal cells in acute hippocampal slices. Brain Res Bull. 2014;104:42–51. doi: 10.1016/j.brainresbull.2014.04.003.
    1. Zhang W, Meehan J, Su Z, Ng HW, Shu M, Luo H, Ge W, Perkins R, Tong W, Hong H. Whole genome sequencing of 35 individuals provides insights into the genetic architecture of Korean population. BMC Bioinformatics. 2014;15 Suppl 11:S6. doi: 10.1186/1471-2105-15-S11-S6.
    1. Lin P, Hartz SM, Zhang Z, Saccone SF, Wang J, Tischfield JA, Edenberg HJ, Kramer JR, A MG, Bierut LJ, et al. A new statistic to evaluate imputation reliability. PLoS One. 2010;5:e9697.
    1. Ortega VE, Meyers DA. Pharmacogenetics: implications of race and ethnicity on defining genetic profiles for personalized medicine. J Allergy Clin Immunol. 2014;133:16–26. doi: 10.1016/j.jaci.2013.10.040.
    1. Jiang L, Yin J, Ye L, Yang J, Hemani G, Liu AJ, Zou H, He D, Sun L, Zeng X, et al. Novel risk loci for rheumatoid arthritis in Han Chinese and congruence with risk variants in Europeans. Arthritis Rheumatol. 2014;66:1121–32. doi: 10.1002/art.38353.
    1. Niitsu T, Fabbri C, Bentini F, Serretti A. Pharmacogenetics in major depression: a comprehensive meta-analysis. Prog Neuro-Psychopharmacol Biol Psychiatry. 2013;45:183–94. doi: 10.1016/j.pnpbp.2013.05.011.

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