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BMC Psychiatry
Published in: BMC Psychiatry 1/2016

Open Access 01-12-2016 | Research article

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

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

Published in: BMC Psychiatry | Issue 1/2016

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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.
Appendix
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Literature
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.CrossRefPubMed
2.
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.CrossRefPubMedPubMedCentral
3.
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.CrossRefPubMed
4.
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.CrossRefPubMedPubMedCentral
5.
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.CrossRefPubMedPubMedCentral
6.
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.CrossRefPubMedPubMedCentral
7.
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.CrossRef
8.
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.CrossRef
9.
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.CrossRef
10.
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.CrossRef
11.
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.CrossRefPubMedPubMedCentral
12.
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.CrossRefPubMedPubMedCentral
13.
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.
14.
Lee PH, O'Dushlaine C, Thomas B, Purcell SM. INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics. 2012;28:1797–9.CrossRefPubMedPubMedCentral
15.
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.
16.
17.
Fabbri C, Serretti A. Genetics of long-term treatment outcome in bipolar disorder. Prog Neuro-Psychopharmacol Biol Psychiatry. 2015;65:17–24.CrossRef
18.
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.
19.
20.
Howland RH. Sequenced Treatment Alternatives to Relieve Depression (STAR*D). Part 1: study design. J Psychosoc Nurs Ment Health Serv. 2008;46:21–4.CrossRef
21.
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.CrossRefPubMed
22.
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.CrossRefPubMed
23.
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.CrossRefPubMedPubMedCentral
24.
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.CrossRefPubMedPubMedCentral
25.
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.CrossRefPubMedPubMedCentral
26.
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.CrossRefPubMed
27.
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.CrossRefPubMedPubMedCentral
28.
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.CrossRefPubMedPubMedCentral
29.
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.CrossRefPubMedPubMedCentral
30.
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.
31.
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.CrossRefPubMedPubMedCentral
32.
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.CrossRefPubMedPubMedCentral
33.
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.CrossRefPubMed
34.
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.CrossRefPubMed
35.
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.CrossRefPubMedPubMedCentral
36.
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.CrossRefPubMedPubMedCentral
37.
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.CrossRefPubMed
38.
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.CrossRefPubMed
39.
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.CrossRefPubMed
40.
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.CrossRef
41.
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.CrossRefPubMed
42.
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.CrossRef
43.
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.CrossRefPubMed
44.
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.CrossRefPubMedPubMedCentral
45.
Mostany R, Valdizan EM, Pazos A. A role for nuclear beta-catenin in SNRI antidepressant-induced hippocampal cell proliferation. Neuropharmacology. 2008;55:18–26.CrossRefPubMed
46.
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.CrossRef
47.
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.CrossRefPubMed
48.
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.CrossRefPubMed
49.
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.CrossRefPubMed
50.
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.CrossRefPubMedPubMedCentral
51.
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.CrossRefPubMed
52.
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.CrossRefPubMed
53.
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.CrossRefPubMed
54.
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.CrossRefPubMedPubMedCentral
55.
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.CrossRefPubMedPubMedCentral
56.
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.CrossRefPubMed
57.
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.CrossRefPubMed
58.
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.
59.
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.CrossRefPubMedPubMedCentral
60.
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.CrossRefPubMed
61.
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.CrossRef
Metadata
Title
Genome-wide association study of antidepressant response: involvement of the inorganic cation transmembrane transporter activity pathway
Authors
Enrico Cocchi
Chiara Fabbri
Changsu Han
Soo-Jung Lee
Ashwin A. Patkar
Prakash S. Masand
Chi-Un Pae
Alessandro Serretti
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Psychiatry / Issue 1/2016
Electronic ISSN: 1471-244X
DOI
https://doi.org/10.1186/s12888-016-0813-x

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