An enhanced understanding of the pathophysiology of depression would facilitate the discovery of new efficacious medications. To this end, we examined hippocampal transcriptional changes in rat models of disease and in humans to identify common disease signatures by using a new algorithm for signature-based clustering of expression profiles. The tool identified a transcriptomic signature comprising 70 probesets able to discriminate depression models from controls in both Flinders Sensitive Line and Learned Helplessness animals. To identify disease-relevant pathways, we constructed an expanded protein network based on signature gene products and performed functional annotation analysis. We applied the same workflow to transcriptomic profiles of depressed patients. Remarkably, a 171-probesets transcriptional signature which discriminated depressed from healthy subjects was identified. Rat and human signatures shared the SCARA5 gene, while the respective networks derived from protein-based significant interactions with signature genes contained 25 overlapping genes. The comparison between the most enriched pathways in the rat and human signature networks identified a highly significant overlap (p-value: 3.85 × 10–6) of 67 terms including ErbB, neurotrophin, FGF, IGF, and VEGF signaling, immune responses and insulin and leptin signaling. In conclusion, this study allowed the identification of a hippocampal transcriptional signature of resilient or susceptible responses in rat MDD models which overlapped with gene expression alterations observed in depressed patients. These findings are consistent with a loss of hippocampal neural plasticity mediated by altered levels of growth factors and increased inflammatory responses causing metabolic impairments as crucial factors in the pathophysiology of MDD.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Additional information

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Mrazek Da, Hornberger JC, Altar CA, Degtiar I. A review of the clinical, economic, and societal burden of treatment-resistant depression: 1996–2013. Psychiatr Serv. 2014;65:977–87.

  2. 2.

    McEwen BS. Neurobiological and systemic effects of chronic stress. Chronic Stress. 2017;1:247054701769232.

  3. 3.

    CONVERGE consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature. 2015;523:588–91.

  4. 4.

    Flint J, Kendler KS. The genetics of major depression. Neuron. 2014;81:484–503.

  5. 5.

    Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Ripke S, Wray NR, Lewis CM, Hamilton SP, Weissman MM, et al. A mega-analysis of genome-wide association studies for major depressive disorder. Mol Psychiatry. 2013;18:497–511.

  6. 6.

    Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016;48:1–9.

  7. 7.

    Overstreet DH, Friedman E, Mathé AA, Yadid G. The Flinders Sensitive Line rat: a selectively bred putative animal model of depression. Neurosci Biobehav Rev. 2005;29:739–59.

  8. 8.

    Vollmayr B, Gass P. Learned helplessness: unique features and translational value of a cognitive depression model. Cell Tissue Res. 2013;354:171–8.

  9. 9.

    Piubelli C, Carboni L, Becchi S, Mathé AA, Domenici E. Regulation of cytoskeleton machinery, neurogenesis and energy metabolism pathways in a rat gene-environment model of depression revealed by proteomic analysis. Neuroscience. 2011;176:349–80.

  10. 10.

    Buwalda B, Kole MHP, Veenema AH, Huininga M, Boer SF, de, Korte SM, et al. Long-term effects of social stress on brain and behavior: a focus on hippocampal functioning. Neurosci Biobehav Rev. 2005;29:83–97.

  11. 11.

    Akil H, Gordon J, Hen R, Javitch J, Mayberg H, McEwen B, et al. Treatment resistant depression: a multi-scale, systems biology approach. Neurosci Biobehav Rev. 2018;84:272–88.

  12. 12.

    Hervé M, Bergon A, Guisquet A-MLe, Leman S, Consoloni J-L, Fernandez-Nunez N, et al. Translational identification of transcriptional signatures of major depression and antidepressant response. Front Mol Neurosci. 2017;10:248.

  13. 13.

    Labonté B, Engmann O, Purushothaman I, Menard C, Wang J, Tan C, et al. Sex-specific transcriptional signatures in human depression. Nat Med. 2017;23:1102–11.

  14. 14.

    Wingo AP, Velasco ER, Florido A, Lori A, Choi DC, Jovanovic T, et al. Expression of the PPM1F gene is regulated by stress and associated with anxiety and depression. Biol Psychiatry. 2018;83:284–95.

  15. 15.

    Sheline YI, Mittler BL, Mintun MA. The hippocampus and depression. Eur Psychiatry. 2002;17:300–5.

  16. 16.

    McEwen BS, Bowles NP, Gray JD, Hill MN, Hunter RG, Karatsoreos IN, et al. Mechanisms of stress in the brain. Nat Neurosci. 2015;18:1353–63.

  17. 17.

    Blaveri E, Kelly F, Mallei A, Harris K, Taylor A, Reid J, et al. Expression profiling of a genetic animal model of depression reveals novel molecular pathways underlying depressive-like behaviours. PLoS One. 2010;5:e12596.

  18. 18.

    Carboni L, Piubelli C, Pozzato C, Astner H, Arban R, Righetti PGG, et al. Proteomic analysis of rat hippocampus after repeated psychosocial stress. Neuroscience. 2006;137:1237–46.

  19. 19.

    Luoni A, Macchi F, Papp M, Molteni R, Riva MA. Lurasidone exerts antidepressant properties in the chronic mild stress model through the regulation of synaptic and neuroplastic mechanisms in the rat prefrontal cortex. Int J Neuropsychopharmacol. 2015;18:1–12.

  20. 20.

    Lauria M. Rank-based transcriptional signatures. Syst Biomed. 2013;1:228–39.

  21. 21.

    Lauria M, Moyseos P, Priami C. SCUDO: a tool for signature-based clustering of expression profiles. Nucleic Acids Res. 2015;43:W188–92.

  22. 22.

    Clark RA, Shoaib M, Hewitt KN, Stanford SC, Bate ST. A comparison of InVivoStat with other statistical software packages for analysis of data generated from animal experiments. J Psychopharmacol. 2012;26:1136–42.

  23. 23.

    Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.

  24. 24.

    Krishnan V, Han M-HH, Graham DL, Berton O, Renthal W, Russo SJ, et al. Molecular adaptations underlying susceptibility and resistance to social defeat in brain reward regions. Cell. 2007;131:391–404.

  25. 25.

    Bagot RCC, Cates HMM, Purushothaman I, Lorsch ZSS, Walker DMM, Wang J, et al. Circuit-wide transcriptional profiling reveals brain region-specific gene networks regulating depression susceptibility. Neuron. 2016;90:969–83.

  26. 26.

    Ojala JRM, Pikkarainen T, Elmberger G, Tryggvason K. Progressive reactive lymphoid connective tissue disease and development of autoantibodies in scavenger receptor A5-deficient mice. Am J Pathol. 2013;182:1681–95.

  27. 27.

    Stuart MJ, Baune BT. Depression and type 2 diabetes: inflammatory mechanisms of a psychoneuroendocrine co-morbidity. Neurosci Biobehav Rev. 2012;36:658–76.

  28. 28.

    Xu C, Aragam N, Li X, Villla EC, Wang L, Briones D, et al. (2013). BCL9 and C9orf5 are associated with negative symptoms in schizophrenia: meta-analysis of two genome-wide association studies. PLoS One 8. e51674

  29. 29.

    Rincón-Cortés M, Barr GA, Mouly AM, Shionoya K, Nuñez BS, Sullivan RM. Enduring good memories of infant trauma: rescue of adult neurobehavioral deficits via amygdala serotonin and corticosterone interaction. Proc Natl Acad Sci. 2015;112:881–6.

  30. 30.

    Garbett K, Ebert PJ, Mitchell A, Lintas C, Manzi B, Mirnics K, et al. Immune transcriptome alterations in the temporal cortex of subjects with autism. Neurobiol Dis. 2008;30:303–11.

  31. 31.

    Cornejo F, Vruwink M, Metz C, Muñoz P, Salgado N, Poblete J, et al. (2017). Scavenger receptor-A deficiency impairs immune response of microglia and astrocytes potentiating Alzheimer’s disease pathophysiology. Brain Behav. Immun. https://doi.org/10.1016/j.bbi.2017.12.007.

  32. 32.

    Frenkel D, Wilkinson K, Zhao L, Hickman SE, Means TK, Puckett L, et al. Scara1 deficiency impairs clearance of soluble amyloid-β by mononuclear phagocytes and accelerates Alzheimer’s-like disease progression. Nat Commun. 2013;4:1–9.

  33. 33.

    Brites D, Fernandes A. Neuroinflammation and depression: microglia activation, extracellular microvesicles and microRNA dysregulation. Front Cell Neurosci. 2015;9:1–20.

  34. 34.

    Mei L, Nave KA. Neuregulin-ERBB signaling in the nervous system and neuropsychiatric diseases. Neuron. 2014;83:27–49.

  35. 35.

    Bousman CA, Potiriadis M, Everall IP, Gunn JM. Effects of neuregulin-1 genetic variation and depression symptom severity on longitudinal patterns of psychotic symptoms in primary care attendees. Am J Med Genet Part B Neuropsychiatr Genet. 2014;165:62–67.

  36. 36.

    Aston C, Jiang L, Sokolov BP. Transcriptional profiling reveals evidence for signaling and oligodendroglial abnormalities in the temporal cortex from patients with major depressive disorder. Mol Psychiatry. 2005;10:309–22.

  37. 37.

    Milanesi E, Minelli A, Cattane N, Cattaneo A, Mora C, Barbon A, et al. ErbB3 mRNA leukocyte levels as a biomarker for major depressive disorder. BMC Psychiatry. 2012;12:145.

  38. 38.

    Wang N, Zhang GF, Liu XY, Sun HL, Wang XM, Qiu LL, et al. 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.

  39. 39.

    Biernacka JM, Sangkuhl K, Jenkins G, Whaley RM, Barman P, Batzler A, et al. The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry. 2015;5:e553.

  40. 40.

    Dang R, Cai H, Zhang L, Liang D, Lv C, Guo Y, et al. Dysregulation of Neuregulin-1/ErbB signaling in the prefrontal cortex and hippocampus of rats exposed to chronic unpredictable mild stress. Physiol Behav. 2015;154:145–50.

  41. 41.

    Molendijk ML, Spinhoven P, Polak M, Bus BAA, Penninx BWJH, Elzinga BM. Serum BDNF concentrations as peripheral manifestations of depression: evidence from a systematic review and meta-analyses on 179 associations (N = 9484). Mol Psychiatry. 2014;19:791–800.

  42. 42.

    Hosang GM, Shiles C, Tansey KE, McGuffin P, Uher R. Interaction between stress and the BDNF Val66Met polymorphism in depression: a systematic review and meta-analysis. BMC Med. 2014;12:7.

  43. 43.

    Björkholm C, Monteggia LM. BDNF—a key transducer of antidepressant effects. Neuropharmacology. 2016;102:72–9.

  44. 44.

    Gray JD, Milner TA, McEwen BS. Dynamic plasticity: the role of glucocorticoids, brain-derived neurotrophic factor and other trophic factors. Neuroscience. 2013;239:214–27.

  45. 45.

    Autry AE, Monteggia LM. Brain-derived neurotrophic factor and neuropsychiatric disorders. Pharmacol Rev. 2012;64:238–58.

  46. 46.

    Sharma AN, Costa E, Silva BFB, Da, Soares JC, Carvalho AF, Quevedo J. Role of trophic factors GDNF, IGF-1 and VEGF in major depressive disorder: a comprehensive review of human studies. J Affect Disord. 2016;197:9–20.

  47. 47.

    Turner CA, Eren-Koçak E, Inui EG, Watson SJ, Akil H. Dysregulated fibroblast growth factor (FGF) signaling in neurological and psychiatric disorders. Semin Cell Dev Biol. 2016;53:136–43.

  48. 48.

    Aurbach EL, Inui EG, Turner CA, Hagenauer MH, Prater KE, Li JZ, et al. Fibroblast growth factor 9 is a novel modulator of negative affect. Proc Natl Acad Sci. 2015;112:11953–8.

  49. 49.

    Wu C, Tseng P, Chen Y, Tu K, Lin P. Significantly higher peripheral fibroblast growth factor-2 levels in patients with major depressive disorder: a preliminary meta-analysis under MOOSE guidelines. Medicine. 2016;95:e4563.

  50. 50.

    Burgdorf J, Zhang X, Colechio EM, Ghoreishi-Haack N, Gross A, Kroes RA, et al. Insulin-like growth factor I produces an antidepressant-like effect and elicits N-methyl-D-aspartate receptor independent long-term potentiation of synaptic transmission in medial prefrontal cortex and hippocampus. Int J Neuropsychopharmacol. 2016;19:pyv101.

  51. 51.

    Fournier NM, Duman RS. Role of vascular endothelial growth factor in adult hippocampal neurogenesis: implications for the pathophysiology and treatment of depression. Behav Brain Res. 2012;227:440–9.

  52. 52.

    Carvalho AF, Köhler CA, McIntyre RS, Knöchel C, Brunoni AR, Thase ME, et al. Peripheral vascular endothelial growth factor as a novel depression biomarker: a meta-analysis. Psychoneuroendocrinology. 2015;62:18–26.

  53. 53.

    Nasca C, Xenos D, Barone Y, Caruso A, Scaccianoce S, Matrisciano F, et al. L-acetylcarnitine causes rapid antidepressant effects through the epigenetic induction of mGlu2 receptors. Proc Natl Acad Sci. 2013;110:4804–9.

  54. 54.

    Bigio B, Mathé AAA, Sousa VCC, Zelli D, Svenningsson P, McEwen BSS, et al. Epigenetics and energetics in ventral hippocampus mediate rapid antidepressant action: implications for treatment resistance. Proc Natl Acad Sci. 2016;113:7906–11.

  55. 55.

    Domenici E, Willé DR, Tozzi F, Prokopenko I, Miller S, McKeown A, et al. Plasma protein biomarkers for depression and schizophrenia by multi analyte profiling of case-control collections. PLoS One. 2010;5:e9166.

  56. 56.

    Lamers F, Bot M, Jansen R, Chan M, Cooper J, Bahn S, et al. (2016). Serum proteomic profiles of depressive subtypes. Nat Publ Gr. 6. e51674

  57. 57.

    Kemp DE, Ismail-Beigi F, Ganocy SJ, Conroy C, Gao K, Obral S, et al. Use of insulin sensitizers for the treatment of major depressive disorder: a pilot study of pioglitazone for major depression accompanied by abdominal obesity. J Affect Disord. 2012;136:1164–73.

  58. 58.

    Grillo CA, Piroli GG, Kaigler KF, Wilson SP, Wilson MA, Reagan LP. Downregulation of hypothalamic insulin receptor expression elicits depressive-like behaviors in rats. Behav Brain Res. 2011;222:230–5.

  59. 59.

    Stieg MR, Sievers C, Farr O, Stalla GK, Mantzoros CS. Leptin: A hormone linking activation of neuroendocrine axes with neuropathology. Psychoneuroendocrinology. 2015;51:47–57.

  60. 60.

    Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Publ Gr. 2016. https://doi.org/10.1038/nm.4246.

Download references


We thank Dr. Stewart A. Bates for help with gene expression experiments and for critical reading of the manuscript and Dr. Roberto Arban for help with the SD experiments and helpful discussions.


This work was part of a project funded by the European Commission that combined large-scale clinical pharmacogenomic studies on depressed patients with preclinical investigations on animal models of disease, focusing on treatment with pro-serotonergic and pro-noradrenergic antidepressants, called ‘Genome-based therapeutic drugs for depression (GENDEP)’, contract number LSHB-CT-2003-503428. The work was also supported by the University of Bologna (RFO 2014) to L. Carboni and the Swedish Medical Research Council to AAM (10414). The funding bodies had no role in the design of the study, collection and analysis of data and decision to publish. L. Carboni, MR, ED, and L. Caberlotto were GlaxoSmithKline employees when this work was started. During the past year, Dr Malki received income from and has been an employee and stockholder of Eli Lilly and UCB Celltech. The authors declare no conflicts of interests.

Author information

Author notes

  1. These authors contributed equally: Laura Caberlotto, Aleksander A. Mathé.


  1. Department of Pharmacy and Biotechnology, Alma Mater Studiorum University of Bologna, Bologna, Italy

    • Lucia Carboni
  2. The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Rovereto, Trento, Italy

    • Luca Marchetti
    • , Mario Lauria
    • , Enrico Domenici
    •  & Laura Caberlotto
  3. Department of Mathematics, University of Trento, Povo, Trento, Italy

    • Mario Lauria
  4. RG Animal Models in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany

    • Peter Gass
    •  & Barbara Vollmayr
  5. MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK

    • Amanda Redfern
    •  & Lesley Jones
  6. Department of Integrative Biology and Physiology University of Minnesota, 2231 6th Street SE, Minneapolis, USA

    • Maria Razzoli
  7. King’s College London, at the Institute of Psychiatry, Psychology and Neuroscience (IOPPN), London, UK

    • Karim Malki
  8. Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, Italy

    • Veronica Begni
    •  & Marco A. Riva
  9. Laboratory of Neurogenomic Biomarkers, Centre for Integrative Biology (CIBIO), University of Trento, Povo, Trento, Italy

    • Enrico Domenici
  10. The Aptuit Center for Drug Discovery & Development, Via Fleming, 4, 37135, Verona, Italy

    • Laura Caberlotto
  11. Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden

    • Aleksander A. Mathé


  1. Search for Lucia Carboni in:

  2. Search for Luca Marchetti in:

  3. Search for Mario Lauria in:

  4. Search for Peter Gass in:

  5. Search for Barbara Vollmayr in:

  6. Search for Amanda Redfern in:

  7. Search for Lesley Jones in:

  8. Search for Maria Razzoli in:

  9. Search for Karim Malki in:

  10. Search for Veronica Begni in:

  11. Search for Marco A. Riva in:

  12. Search for Enrico Domenici in:

  13. Search for Laura Caberlotto in:

  14. Search for Aleksander A. Mathé in:

Corresponding author

Correspondence to Lucia Carboni.

Electronic supplementary material

About this article

Publication history