Sex-specific transcriptional signatures in human depression

  • A Corrigendum to this article was published on 01 April 2018

Abstract

Major depressive disorder (MDD) is a leading cause of disease burden worldwide. While the incidence, symptoms and treatment of MDD all point toward major sex differences, the molecular mechanisms underlying this sexual dimorphism remain largely unknown. Here, combining differential expression and gene coexpression network analyses, we provide a comprehensive characterization of male and female transcriptional profiles associated with MDD across six brain regions. We overlap our human profiles with those from a mouse model, chronic variable stress, and capitalize on converging pathways to define molecular and physiological mechanisms underlying the expression of stress susceptibility in males and females. Our results show a major rearrangement of transcriptional patterns in MDD, with limited overlap between males and females, an effect seen in both depressed humans and stressed mice. We identify key regulators of sex-specific gene networks underlying MDD and confirm their sex-specific impact as mediators of stress susceptibility. For example, downregulation of the female-specific hub gene Dusp6 in mouse prefrontal cortex mimicked stress susceptibility in females, but not males, by increasing ERK signaling and pyramidal neuron excitability. Such Dusp6 downregulation also recapitulated the transcriptional remodeling that occurs in prefrontal cortex of depressed females. Together our findings reveal marked sexual dimorphism at the transcriptional level in MDD and highlight the importance of studying sex-specific treatments for this disorder.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Differential expression profiles in humans with MDD reveal distinct sex-specific transcriptional signatures across brain regions.
Figure 2: Gene coexpression modules in males and females with MDD are enriched for DEGs across brain regions.
Figure 3: CVS induces an equivalent depressive-like behavioral phenotype in male and female mice.
Figure 4: Dusp6 and Emx1 in vmPFC control sex-specific depressive-like phenotypes in mice.
Figure 5: Cell-type specific increase in phospho-ERK1/2 (pERK) in females with MDD and stressed female mice.
Figure 6: Dusp6 downregulation and Emx1 overexpression alter the physiological properties of vmPFC pyramidal neurons in a sex-specific fashion.

Accession codes

Primary accessions

Gene Expression Omnibus

Referenced accessions

Gene Expression Omnibus

Change history

  • 07 March 2018

    In the version of this article initially published, the last name of author Andrew Kasarskis was misspelled as "Kazarskis". The error has been corrected in the PDF and HTML versions of the article.

References

  1. 1

    World Health Organization. The Global Burden of Disease 2004 Update (World Health Organization, 2008).

  2. 2

    Kessler, R.C., Chiu, W.T., Demler, O., Merikangas, K.R. & Walters, E.E. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch. Gen. Psychiatry 62, 617–627 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3

    Kessler, R.C., McGonagle, K.A., Swartz, M., Blazer, D.G. & Nelson, C.B. Sex and depression in the National Comorbidity Survey. I: Lifetime prevalence, chronicity and recurrence. J. Affect. Disord. 29, 85–96 (1993).

    Article  CAS  PubMed  Google Scholar 

  4. 4

    Kornstein, S.G. et al. Gender differences in chronic major and double depression. J. Affect. Disord. 60, 1–11 (2000).

    Article  CAS  PubMed  Google Scholar 

  5. 5

    Kornstein, S.G. et al. Gender differences in treatment response to sertraline versus imipramine in chronic depression. Am. J. Psychiatry 157, 1445–1452 (2000).

    Article  CAS  PubMed  Google Scholar 

  6. 6

    Khan, A., Brodhead, A.E., Schwartz, K.A., Kolts, R.L. & Brown, W.A. Sex differences in antidepressant response in recent antidepressant clinical trials. J. Clin. Psychopharmacol. 25, 318–324 (2005).

    Article  PubMed  Google Scholar 

  7. 7

    Hastings, R.S., Parsey, R.V., Oquendo, M.A., Arango, V. & Mann, J.J. Volumetric analysis of the prefrontal cortex, amygdala, and hippocampus in major depression. Neuropsychopharmacology 29, 952–959 (2004).

    Article  PubMed  Google Scholar 

  8. 8

    Kong, L. et al. Sex differences of gray matter morphology in cortico-limbic-striatal neural system in major depressive disorder. J. Psychiatr. Res. 47, 733–739 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  9. 9

    Frey, B.N., Skelin, I., Sakai, Y., Nishikawa, M. & Diksic, M. Gender differences in α-[11C]MTrp brain trapping, an index of serotonin synthesis, in medication-free individuals with major depressive disorder: a positron emission tomography study. Psychiatry Res. 183, 157–166 (2010).

    Article  CAS  PubMed  Google Scholar 

  10. 10

    Kaufman, J. et al. Quantification of the serotonin 1A receptor using PET: identification of a potential biomarker of major depression in males. Neuropsychopharmacology 40, 1692–1699 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. 11

    Underwood, M.D. et al. Neuron density and serotonin receptor binding in prefrontal cortex in suicide. Int. J. Neuropsychopharmacol. 15, 435–447 (2012).

    Article  CAS  PubMed  Google Scholar 

  12. 12

    Bangasser, D.A. & Valentino, R.J. Sex differences in stress-related psychiatric disorders: neurobiological perspectives. Front. Neuroendocrinol. 35, 303–319 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13

    Chopra, K.K. et al. Sex differences in hormonal responses to a social stressor in chronic major depression. Psychoneuroendocrinology 34, 1235–1241 (2009).

    Article  CAS  PubMed  Google Scholar 

  14. 14

    Gallucci, W.T. et al. Sex differences in sensitivity of the hypothalamic-pituitary-adrenal axis. Health Psychol. 12, 420–425 (1993).

    Article  CAS  PubMed  Google Scholar 

  15. 15

    Kunugi, H. et al. Assessment of the dexamethasone/CRH test as a state-dependent marker for hypothalamic-pituitary-adrenal (HPA) axis abnormalities in major depressive episode: a multicenter study. Neuropsychopharmacology 31, 212–220 (2006).

    Article  CAS  PubMed  Google Scholar 

  16. 16

    Mehta, D., Menke, A. & Binder, E.B. Gene expression studies in major depression. Curr. Psychiatry Rep. 12, 135–144 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  17. 17

    Sequeira, A. et al. Patterns of gene expression in the limbic system of suicides with and without major depression. Mol. Psychiatry 12, 640–655 (2007).

    Article  CAS  PubMed  Google Scholar 

  18. 18

    Sequeira, A. et al. Global brain gene expression analysis links glutamatergic and GABAergic alterations to suicide and major depression. PLoS One 4, e6585 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 19

    Sequeira, A. et al. Gene expression changes in the prefrontal cortex, anterior cingulate cortex and nucleus accumbens of mood disorders subjects that committed suicide. PLoS One 7, e35367 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. 20

    Evans, S.J. et al. Dysregulation of the fibroblast growth factor system in major depression. Proc. Natl. Acad. Sci. USA 101, 15506–15511 (2004).

    Article  CAS  PubMed  Google Scholar 

  21. 21

    Kang, H.J. et al. Gene expression profiling in postmortem prefrontal cortex of major depressive disorder. J. Neurosci. 27, 13329–13340 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. 22

    Klempan, T.A. et al. Altered expression of genes involved in ATP biosynthesis and GABAergic neurotransmission in the ventral prefrontal cortex of suicides with and without major depression. Mol. Psychiatry 14, 175–189 (2009).

    Article  CAS  Google Scholar 

  23. 23

    Lalovic, A., Klempan, T., Sequeira, A., Luheshi, G. & Turecki, G. Altered expression of lipid metabolism and immune response genes in the frontal cortex of suicide completers. J. Affect. Disord. 120, 24–31 (2010).

    Article  CAS  PubMed  Google Scholar 

  24. 24

    Wang, S.S., Kamphuis, W., Huitinga, I., Zhou, J.N. & Swaab, D.F. Gene expression analysis in the human hypothalamus in depression by laser microdissection and real-time PCR: the presence of multiple receptor imbalances. Mol. Psychiatry 13, 786–799 (2008).

    Article  CAS  PubMed  Google Scholar 

  25. 25

    Li, J.Z. et al. Circadian patterns of gene expression in the human brain and disruption in major depressive disorder. Proc. Natl. Acad. Sci. USA 110, 9950–9955 (2013).

    Article  PubMed  Google Scholar 

  26. 26

    Iwamoto, K., Kakiuchi, C., Bundo, M., Ikeda, K. & Kato, T. Molecular characterization of bipolar disorder by comparing gene expression profiles of postmortem brains of major mental disorders. Mol. Psychiatry 9, 406–416 (2004).

    Article  CAS  PubMed  Google Scholar 

  27. 27

    Malki, K. et al. Pervasive and opposing effects of Unpredictable Chronic Mild Stress (UCMS) on hippocampal gene expression in BALB/cJ and C57BL/6J mouse strains. BMC Genomics 16, 262 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. 28

    Tripp, A. et al. Brain-derived neurotrophic factor signaling and subgenual anterior cingulate cortex dysfunction in major depressive disorder. Am. J. Psychiatry 169, 1194–1202 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  29. 29

    Guilloux, J.P. et al. Molecular evidence for BDNF- and GABA-related dysfunctions in the amygdala of female subjects with major depression. Mol. Psychiatry 17, 1130–1142 (2012).

    Article  CAS  PubMed  Google Scholar 

  30. 30

    Gray, A.L., Hyde, T.M., Deep-Soboslay, A., Kleinman, J.E. & Sodhi, M.S. Sex differences in glutamate receptor gene expression in major depression and suicide. Mol. Psychiatry 20, 1139 (2015).

    Article  CAS  PubMed  Google Scholar 

  31. 31

    Goswami, D.B., May, W.L., Stockmeier, C.A. & Austin, M.C. Transcriptional expression of serotonergic regulators in laser-captured microdissected dorsal raphe neurons of subjects with major depressive disorder: sex-specific differences. J. Neurochem. 112, 397–409 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. 32

    Szewczyk, B. et al. Gender-specific decrease in NUDR and 5-HT1A receptor proteins in the prefrontal cortex of subjects with major depressive disorder. Int. J. Neuropsychopharmacol. 12, 155–168 (2009).

    Article  CAS  PubMed  Google Scholar 

  33. 33

    Seney, M.L., Tripp, A., McCune, S., Lewis, D.A. & Sibille, E. Laminar and cellular analyses of reduced somatostatin gene expression in the subgenual anterior cingulate cortex in major depression. Neurobiol. Dis. 73, 213–219 (2015).

    Article  CAS  PubMed  Google Scholar 

  34. 34

    Lin, L.C., Lewis, D.A. & Sibille, E. A human-mouse conserved sex bias in amygdala gene expression related to circadian clock and energy metabolism. Mol. Brain 4, 18 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. 35

    Krishnan, V. et al. Molecular adaptations underlying susceptibility and resistance to social defeat in brain reward regions. Cell 131, 391–404 (2007).

    Article  CAS  Google Scholar 

  36. 36

    Lisowski, P. et al. Effect of chronic mild stress on hippocampal transcriptome in mice selected for high and low stress-induced analgesia and displaying different emotional behaviors. Eur. Neuropsychopharmacol. 21, 45–62 (2011).

    Article  CAS  PubMed  Google Scholar 

  37. 37

    Seney, M.L. et al. The role of genetic sex in affect regulation and expression of GABA-related genes across species. Front. Psychiatry 4, 104 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  38. 38

    Lin, L.C. & Sibille, E. Somatostatin, neuronal vulnerability and behavioral emotionality. Mol. Psychiatry 20, 377–387 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. 39

    Hodes, G.E. et al. Sex differences in nucleus accumbens transcriptome profiles associated with susceptibility versus resilience to subchronic variable stress. J. Neurosci. 35, 16362–16376 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. 40

    Flint, J. & Kendler, K.S. The genetics of major depression. Neuron 81, 484–503 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Hyde, C.L. et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat. Genet. 48, 1031–1036 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. 42

    Jiang, P. et al. A systems approach identifies networks and genes linking sleep and stress: implications for neuropsychiatric disorders. Cell Reports 11, 835–848 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. 43

    Parikshak, N.N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Zhang, B. et al. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell 153, 707–720 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. 45

    Bagot, R.C. et al. Circuit-wide transcriptional profiling reveals brain region-specific gene networks regulating depression susceptibility. Neuron 90, 969–983 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Vialou, V., Feng, J., Robison, A.J. & Nestler, E.J. Epigenetic mechanisms of depression and antidepressant action. Annu. Rev. Pharmacol. Toxicol. 53, 59–87 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. 47

    Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, 17 (2005).

    Article  Google Scholar 

  48. 48

    Horvath, S. Weighted Network Analysis: Applications in Genomics and Systems Biology (Springer, 2011).

  49. 49

    Russo, S.J. & Nestler, E.J. The brain reward circuitry in mood disorders. Nat. Rev. Neurosci. 14, 609–625 (2013).

    Article  CAS  Google Scholar 

  50. 50

    Muda, M. et al. The dual specificity phosphatases M3/6 and MKP-3 are highly selective for inactivation of distinct mitogen-activated protein kinases. J. Biol. Chem. 271, 27205–27208 (1996).

    Article  CAS  PubMed  Google Scholar 

  51. 51

    Schuurmans, C. & Guillemot, F. Molecular mechanisms underlying cell fate specification in the developing telencephalon. Curr. Opin. Neurobiol. 12, 26–34 (2002).

    Article  CAS  PubMed  Google Scholar 

  52. 52

    Mazzucchelli, C. & Brambilla, R. Ras-related and MAPK signalling in neuronal plasticity and memory formation. Cell. Mol. Life Sci. 57, 604–611 (2000).

    Article  CAS  PubMed  Google Scholar 

  53. 53

    Rush, A.J. The varied clinical presentations of major depressive disorder. J. Clin. Psychiatry 68 (Suppl. 8), 4–10 (2007).

    PubMed  Google Scholar 

  54. 54

    Covington, H.E. III et al. Antidepressant effect of optogenetic stimulation of the medial prefrontal cortex. J. Neurosci. 30, 16082–16090 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Mailliet, F. et al. Protection of stress-induced impairment of hippocampal/prefrontal LTP through blockade of glucocorticoid receptors: implication of MEK signaling. Exp. Neurol. 211, 593–596 (2008).

    Article  CAS  PubMed  Google Scholar 

  56. 56

    Quan, M.N., Zhang, N., Wang, Y.Y., Zhang, T. & Yang, Z. Possible antidepressant effects and mechanisms of memantine in behaviors and synaptic plasticity of a depression rat model. Neuroscience 182, 88–97 (2011).

    Article  CAS  PubMed  Google Scholar 

  57. 57

    Mayberg, H.S. et al. Deep brain stimulation for treatment-resistant depression. Neuron 45, 651–660 (2005).

    Article  CAS  PubMed  Google Scholar 

  58. 58

    Piper, M. et al. Emx and Nfi genes regulate cortical development and axon guidance in the telencephalon. Novartis Foundation Symposium 288, 230–242 (2007).

    CAS  PubMed  Google Scholar 

  59. 59

    CONVERGE Consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature 523, 588–591 (2015).

  60. 60

    Labuda, M. et al. Linkage disequilibrium analysis in young populations: pseudo-vitamin D-deficiency rickets and the founder effect in French Canadians. Am. J. Hum. Genet. 59, 633–643 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Haines, D. Neuroanatomy: An Atlas of Structures, Sections, and Systems 5th edn. (Lippincott Williams & Wilkins, 2000).

  62. 62

    Nolte, J. The Human Brain: An Introduction to Its Functional Neuroanatomy 5th edn. (Mosby-Year Book Inc., 2002).

  63. 63

    Dumais, A. et al. Risk factors for suicide completion in major depression: a case-control study of impulsive and aggressive behaviors in men. Am. J. Psychiatry 162, 2116–2124 (2005).

    Article  CAS  PubMed  Google Scholar 

  64. 64

    McGirr, A. et al. Risk factors for completed suicide in schizophrenia and other chronic psychotic disorders: a case-control study. Schizophr. Res. 84, 132–143 (2006).

    Article  CAS  PubMed  Google Scholar 

  65. 65

    American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders 4th edn. (American Psychiatric Publishing, 1994).

  66. 66

    Spitzer, R.L., Williams, J.B., Gibbon, M. & First, M.B. The Structured Clinical Interview for DSM-III-R (SCID). I: History, rationale, and description. Arch. Gen. Psychiatry 49, 624–629 (1992).

    Article  CAS  PubMed  Google Scholar 

  67. 67

    LaPlant, Q. et al. Role of nuclear factor κB in ovarian hormone-mediated stress hypersensitivity in female mice. Biol. Psychiatry 65, 874–880 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. 68

    Yang, C.R., Seamans, J.K. & Gorelova, N. Electrophysiological and morphological properties of layers V–VI principal pyramidal cells in rat prefrontal cortex in vitro. J. Neurosci. 16, 1904–1921 (1996).

    Article  CAS  PubMed  Google Scholar 

  69. 69

    Lovén, J. et al. Revisiting global gene expression analysis. Cell 151, 476–482 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. 70

    Akula, N. et al. RNA-sequencing of the brain transcriptome implicates dysregulation of neuroplasticity, circadian rhythms and GTPase binding in bipolar disorder. Mol. Psychiatry 19, 1179–1185 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. 71

    Smyth, G.K. in Bioinformatics and Computational Biology Solutions using R and Bioconductor Vol. 1 (eds. Carey, V. et al.) 397–420 (Springer, 2005).

  72. 72

    Chen, L.S. & Storey, J.D. Eigen-R2 for dissecting variation in high-dimensional studies. Bioinformatics 24, 2260–2262 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. 73

    Risso, D., Ngai, J., Speed, T.P. & Dudoit, S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat. Biotechnol. 32, 896–902 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Gautier, L., Cope, L., Bolstad, B.M. & Irizarry, R.A. affy—analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20, 307–315 (2004).

    Article  CAS  Google Scholar 

  75. 75

    Plaisier, S.B., Taschereau, R., Wong, J.A. & Graeber, T.G. Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic Acids Res. 38, e169 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. 76

    Stein, J.L. et al. A quantitative framework to evaluate modeling of cortical development by neural stem cells. Neuron 83, 69–86 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. 77

    Huang, W., Sherman, B.T. & Lempicki, R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009).

    Article  CAS  Google Scholar 

  78. 78

    Margolin, A.A. et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7 (Suppl. 1), S7 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. 79

    Zhang, Y. et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. 80

    Langfelder, P., Luo, R., Oldham, M.C. & Horvath, S. Is my network module preserved and reproducible? PLOS Comput. Biol. 7, e1001057 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank V. Vialou for his in vivo expertise, K. Gleason at The University of Texas Southwestern Medical Center and Josée Prud'homme and Danielle Cecyre at the Douglas Bell-Canada Brain Bank for their help with procuring human brain samples, and O. Jabado for his expert advice on RNA-seq. This work was funded by National Institute of Mental Health (NIMH) grants P50MH096890 and R01MH051399 and by the Hope for Depression Research Foundation (HDRF) to E.J.N. B.L. was supported by a Frederick Banting and Charles Best postdoctoral fellowship from the Canadian Institute for Health Research (CIHR) and now by a Research Chair in Molecular Neurobiology of Mood Disorders and a Fond de Recherche du Québec-Santé (FRQ-S) Junior 1 award.

Author information

Affiliations

Authors

Contributions

B.L. and E.J.N. conceived the project, designed the experiments and wrote the manuscript. B.L. also generated and analyzed all of the data. B.Z. and L.S. oversaw all bioinformatics analyses. A.K., Y.D., C. Tamminga, S.R., N.M. and G.T. also contributed to the study design. O.E., G.M., Z.S.L., P.J.H., E.S.C., O.I., H.K. and A.L.J.O. contributed to the cloning, in vivo surgeries and behavioral experiments. G.E.H. M.P., G.M. and A.L.J.O. contributed to the behavioral experiments. C.M., C. Tan, G.M. and M.C. helped with the protein and IHC experiments. J.W. and Y.D. generated the electrophysiological data. I.P., J.R.S., Z.S.L. and Y.-H.E.L. contributed to the differential expression and network analyses. R.L.N. packaged the viruses. C. Tamminga, N.M. and G.T. contributed brain samples. All authors contributed to the preparation of the manuscript.

Corresponding author

Correspondence to Eric J Nestler.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Tables 1, 5, 6 and 12. (PDF 2465 kb)

Life Sciences Reporting Checklist (PDF 192 kb)

Supplementary Table 2

List of genes differentially expressed across brain regions in MDD versus control males. (XLSX 851 kb)

Supplementary Table 3

List of genes differentially expressed across brain regions in MDD versus control females. (XLSX 870 kb)

Supplementary Table 4

NanoString validation data in males and females. (XLSX 17 kb)

Supplementary Table 7

Statistics from the inter-region overlap analysis (Fisher's exact test) in human males with and without MDD. (XLSX 36 kb)

Supplementary Table 8

Statistics from the inter-region overlap analysis (Fisher's exact test) in human females with and without MDD. (XLSX 38 kb)

Supplementary Table 9

Summary statistics from Fisher's exact test overlap analyses. (XLSX 15 kb)

Supplementary Table 10

Summary of the gene ontology overlap analyses performed in males and females. (XLSX 398 kb)

Supplementary Table 11

List of genes differentially expressed between males and females at baseline (controls only). (XLSX 10698 kb)

Supplementary Table 13

Summary table of the gene network analysis results in male MDD. (XLSX 42 kb)

Supplementary Table 14

Summary table of the gene network analysis results in female MDD. (XLSX 47 kb)

Supplementary Table 15

Male MDD preservation analysis summary. (XLSX 25 kb)

Supplementary Table 16

Female MDD preservation analysis summary. (XLSX 31 kb)

Supplementary Table 17

List of genes differentially expressed across brain regions in stressed versus control males. (XLSX 398 kb)

Supplementary Table 18

List of genes differentially expressed across brain regions in stressed versus control females. (XLSX 508 kb)

Supplementary Table 19

Inter-species overlap analysis summary for gene differentially expressed in males and females. (XLSX 17 kb)

Supplementary Table 20

Inter-species overlap analysis summary for gene ontology terms enriched in males and females with MDD or stress. (XLSX 140 kb)

Supplementary Table 21

Gene ontology analysis summary for terms associated with MDD in humans (males and females) and stress in mice (males and females). (XLSX 17 kb)

Supplementary Table 22

Summary table for the correlation values of the top three covariates' principal components. (XLSX 8 kb)

Supplementary Table 23

List of gene differentially expressed across brain regions in males and females with MDD from the publicly available microarray validation cohort. (XLSX 14 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Labonté, B., Engmann, O., Purushothaman, I. et al. Sex-specific transcriptional signatures in human depression. Nat Med 23, 1102–1111 (2017). https://doi.org/10.1038/nm.4386

Download citation

Further reading

Search

Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing