Skip to main content

Advertisement

SpringerLink
Log in

Genome-Wide Pathway Analysis in Major Depressive Disorder

  • Published:
Journal of Molecular Neuroscience Aims and scope Submit manuscript

Abstract

The aims of this study were: (1) to identify candidate single-nucleotide polymorphisms (SNPs) and mechanisms of major depressive disorder (MDD) and (2) to generate SNP-to-gene-to-pathway hypotheses. An MDD genome-wide association study (GWAS) data set that included 365,419 SNPs in 1,821 MDD cases and 1,822 controls of European descent was used in this study. Identify Candidate Causal SNPs and Pathway (ICSNPathway) analysis was applied to the GWAS dataset. ICSNPathway analysis identified 21 candidate SNPs, 16 genes, and 5 pathways, which provided 16 hypothetical biological mechanisms. The strongest hypothetical biological mechanism was that rs3213764 alters the role of ATF7IP in the context of the pathways of negative regulation of transcription, negative regulation of nucleobase, nucleoside, nucleotide, and nucleic acid metabolic processes and negative regulation of gene expression (nominal p < 0.001, FDR = 0.043, 0.044, and 0.046, respectively). Five of 16 candidate genes are known to be associated with inflammatory or immune response that may be associated with MDD: ANPEP, PRDM1, ZBTB32, MMP8, and ENPEP. By applying the ICSNPathway analysis to the MDD GWAS data, 21 candidate SNPs, 16 genes that included ATF7IP, ANPEP, PRDM1, ZBTB32, MMP8, and ENPEP, and 5 pathways that involved negative regulation of transcription and nucleic acid metabolism were identified that may contribute to MDD susceptibility.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  • Arakawa R, Bagashev A, Song L, Maurer K, Sullivan KE (2010) Characterization of LRRFIP1. Biochem Cell Biol 88:899–906

    Article  PubMed  CAS  Google Scholar 

  • Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29

    Article  PubMed  CAS  Google Scholar 

  • Boomsma DI, Willemsen G, Sullivan PF, Heutink P, Meijer P, Sondervan D, Kluft C, Smit G, Nolen WA, Zitman FG, Smit JH, Hoogendijk WJ, van Dyck R, de Geus EJ, Penninx BW (2008) Genome-wide association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects. Eur J Hum Genet 16:335–342

    Article  PubMed  CAS  Google Scholar 

  • Dantzer R, O’Connor JC, Freund GG, Johnson RW, Kelley KW (2008) From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 9:46–56

    Article  PubMed  CAS  Google Scholar 

  • Elbers CC, van Eijk KR, Franke L, Mulder F, van der Schouw YT, Wijmenga C, Onland-Moret NC (2009) Using genome-wide pathway analysis to unravel the etiology of complex diseases. Genet Epidemiol 33:419–431

    Article  PubMed  Google Scholar 

  • Fridley BL, Biernacka JM (2011) Gene set analysis of SNP data: benefits, challenges, and future directions. Eur J Hum Genet 19:837–843

    Article  PubMed  CAS  Google Scholar 

  • International HapMap, C, Altshuler DM, Gibbs RA, Peltonen L, Altshuler DM, Gibbs RA, Peltonen L, Dermitzakis E, Schaffner SF, Yu F, Peltonen L, Dermitzakis E, Bonnen PE, Altshuler DM, Gibbs RA, de Bakker PI, Deloukas P, Gabriel SB, Gwilliam R, Hunt S, Inouye M, Jia X, Palotie A, Parkin M, Whittaker P, Yu F, Chang K, Hawes A, Lewis LR, Ren Y, Wheeler D, Gibbs RA, Muzny DM, Barnes C, Darvishi K, Hurles M, Korn JM, Kristiansson K, Lee C, McCarrol SA, Nemesh J, Dermitzakis E, Keinan A, Montgomery SB, Pollack S, Price AL, Soranzo N, Bonnen PE, Gibbs RA, Gonzaga-Jauregui C, Keinan A, Price AL, Yu F, Anttila V, Brodeur W, Daly MJ, Leslie S, McVean G, Moutsianas L, Nguyen H, Schaffner SF, Zhang Q, Ghori MJ, McGinnis R, McLaren W, Pollack S, Price AL, Schaffner SF, Takeuchi F, Grossman SR, Shlyakhter I, Hostetter EB, Sabeti PC, Adebamowo CA, Foster MW, Gordon DR, Licinio J, Manca MC, Marshall PA, Matsuda I, Ngare D, Wang VO, Reddy D, Rotimi CN, Royal CD, Sharp RR, Zeng C, Brooks LD, McEwen JE (2010) Integrating common and rare genetic variation in diverse human populations. Nature 467:52–58

    Article  PubMed  CAS  Google Scholar 

  • Johnson AD, O’Donnell CJ (2009) An open access database of genome-wide association results. BMC Med Genet 10:6

    Article  PubMed  Google Scholar 

  • Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O’Donnell CJ, de Bakker PI (2008) SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24:2938–2939

    Article  PubMed  CAS  Google Scholar 

  • Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M (2010) KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 38:D355–D360

    Article  PubMed  CAS  Google Scholar 

  • Kim HR, Park MK, Cho ML, Kim KW, Oh HJ, Park JS, Heo YM, Lee SH, Kim HY, Park SH (2010) Induction of macrophage migration inhibitory factor in ConA-stimulated rheumatoid arthritis synovial fibroblasts through the P38 map kinase-dependent signaling pathway. Korean J Intern Med 25:317–326

    Google Scholar 

  • Lai A, Ghaffari A, Li Y, Ghahary A (2012) Microarray-based identification of aminopeptidase N target genes in keratinocyte conditioned medium-stimulated dermal fibroblasts. J Cell Biochem 113:1061–1068

    Article  PubMed  CAS  Google Scholar 

  • Lee YH, Song GG (2012) Pathway analysis of genome-wide association studies on uric acid concentrations. Hum Immunol 73:805–810

    Article  PubMed  CAS  Google Scholar 

  • Liu L, Ishihara K, Ichimura T, Fujita N, Hino S, Tomita S, Watanabe S, Saitoh N, Ito T, Nakao M (2009) MCAF1/AM is involved in Sp1-mediated maintenance of cancer-associated telomerase activity. J Biol Chem 284:5165–5174

    Article  PubMed  CAS  Google Scholar 

  • Manolio TA (2010) Genomewide association studies and assessment of the risk of disease. N Engl J Med 363:166–176

    Article  PubMed  CAS  Google Scholar 

  • Pardo CA, Vargas DL, Zimmerman AW (2005) Immunity, neuroglia and neuroinflammation in autism. Int Rev Psychiatry 17:485–495

    Article  PubMed  Google Scholar 

  • Pedroso I, Breen G (2011) Gene set analysis and network analysis for genome-wide association studies. Cold Spring Harb Protoc 2011(9), pdb.top065581

  • Sullivan PF, Neale MC, Kendler KS (2000) Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry 157:1552–1562

    Article  PubMed  CAS  Google Scholar 

  • Verbeek EC, Bakker IM, Bevova MR, Bochdanovits Z, Rizzu P, Sondervan D, Willemsen G, de Geus EJ, Smit JH, Penninx BW, Boomsma DI, Hoogendijk WJ, Heutink P (2012) A fine-mapping study of 7 top scoring genes from a GWAS for major depressive disorder. PLoS One 7:e37384

    Article  PubMed  CAS  Google Scholar 

  • Wang K, Li M, Hakonarson H (2010) Analysing biological pathways in genome-wide association studies. Nat Rev Genet 11:843–854

    Article  PubMed  CAS  Google Scholar 

  • Zeggini E, Ioannidis JP (2009) Meta-analysis in genome-wide association studies. Pharmacogenomics 10:191–201

    Article  PubMed  Google Scholar 

  • Zhang Y, Huang Q, Cheng JC, Nishi Y, Yanase T, Huang HF, Leung PC (2010) Homeobox A7 increases cell proliferation by up-regulation of epidermal growth factor receptor expression in human granulosa cells. Reprod Biol Endocrinol 8:61

    Article  PubMed  Google Scholar 

  • Zhang K, Chang S, Cui S, Guo L, Zhang L, Wang J (2011) ICSNPathway: identify candidate causal SNPs and pathways from genome-wide association study by one analytical framework. Nucleic Acids Res 39:W437–W443

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge investigators for sharing their valuable GWAS data.

Conflict of interest statement

The authors declare that they have no vested interest that could be construed to have inappropriately influenced this study.

Author information

Authors and Affiliations

  1. Division of Rheumatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea

    Gwan Gyu Song, Jae-Hoon Kim & Young Ho Lee

  2. Division of Rheumatology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, 126-1 5 ga, Anam-dong, Seongbuk-gu, Seoul, 136-705, Korea

    Young Ho Lee

Authors
  1. Gwan Gyu Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jae-Hoon Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Young Ho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Young Ho Lee.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Song, G.G., Kim, JH. & Lee, Y.H. Genome-Wide Pathway Analysis in Major Depressive Disorder. J Mol Neurosci 51, 428–436 (2013). https://doi.org/10.1007/s12031-013-0047-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12031-013-0047-z

Keywords

Search

Navigation