Blood plasma/IgG N-glycome biosignatures associated with major depressive disorder symptom severity and the antidepressant response

Scientific Reports

Volumn 8, Issue 1, 2018, Pages

  Park, Dong Ik ^a   Štambuk, Jerko ^b   Razdorov, Genadij ^b   Pučić Baković, Maja ^b   Martins De Souza, Daniel ^c   Lauc, Gordan ^b,d   Turck, Christoph W ^a  

^a MAX PLANCK INSTITUTE OF PSYCHIATRY   (Germany)

^b GENOS GLYCOSCIENCE RESEARCH LABORATORY   (Croatia)

^c UNIVERSITY OF CAMPINAS   (Brazil)

^d UNIVERSITY OF ZAGREB   (Croatia)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIDEPRESSANT AGENT; BIOLOGICAL MARKER; IMMUNOGLOBULIN G; POLYSACCHARIDE;

ADULT; AGED; BLOOD; FEMALE; GLYCOSYLATION; HUMAN; MAJOR DEPRESSION; MALE; METABOLISM; MIDDLE AGED; MONOCYTE; PROTEIN PROCESSING;

ADULT; AGED; ANTIDEPRESSIVE AGENTS; BIOMARKERS; DEPRESSIVE DISORDER, MAJOR; FEMALE; GLYCOSYLATION; HUMANS; IMMUNOGLOBULIN G; MALE; MIDDLE AGED; MONOCYTES; POLYSACCHARIDES; PROTEIN PROCESSING, POST-TRANSLATIONAL;

EID: 85040619991     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/s41598-017-17500-0     Document Type: Article

References (60)

1. Gu, J. et al. Potential roles of N-glycosylation in cell adhesion. Glycoconj J 29, 599-607, https://doi. org/10. 1007/s10719-012-9386-1 (2012).
2. Watson, F. L., Porcionatto, M. A., Bhattacharyya, A., Stiles, C. D. & Segal, R. A. TrkA glycosylation regulates receptor localization and activity. J Neurobiol 39, 323-336 (1999).
3. Xu, C. & Ng, D. T. Glycosylation-directed quality control of protein folding. Nat Rev Mol Cell Biol 16, 742-752, https://doi. org/10. 1038/nrm4073 (2015).
4. Anthony, R. M. & Ravetch, J. V. A novel role for the IgG Fc glycan: The anti-inflammatory activity of sialylated IgG Fcs. J Clin Immunol 30(Suppl 1), S9-14, https://doi. org/10. 1007/s10875-010-9405-6 (2010).
5. Rademacher, T. W., Williams, P. & Dwek, R. A. Agalactosyl glycoforms of IgG autoantibodies are pathogenic. Proceedings of the National Academy of Sciences of the United States of America 91, 6123-6127 (1994).
6. Wuhrer, M. et al. Pro-inflammatory pattern of IgG1 Fc glycosylation in multiple sclerosis cerebrospinal fluid. J Neuroinflammation 12, 235, https://doi. org/10. 1186/s12974-015-0450-1 (2015).
7. Zorrilla, E. P. et al. The relationship of depression and stressors to immunological assays: A meta-analytic review. Brain Behav Immun 15, 199-226, https://doi. org/10. 1006/brbi. 2000. 0597 (2001).
8. Blume, J., Douglas, S. D. & Evans, D. L. Immune suppression and immune activation in depression. Brain Behav Immun 25, 221-229, https://doi. org/10. 1016/j. bbi. 2010. 10. 008 (2011).
9. Besedovsky, H. O. et al. Cytokines as modulators of the hypothalamus-pituitary-adrenal axis. J Steroid Biochem Mol Biol 40, 613-618 (1991).
10. Miller, A. H., Maletic, V. & Raison, C. L. Inflammation and its discontents: The role of cytokines in the pathophysiology of major depression. Biol Psychiatry 65, 732-741, https://doi. org/10. 1016/j. biopsych. 2008. 11. 029 (2009).
11. Moreno-Villanueva, M. et al. N-glycosylation profiling of plasma provides evidence for accelerated physiological aging in posttraumatic stress disorder. Translational Psychiatry 3, e320, https://doi. org/10. 1038/tp. 2013. 93 (2013).
12. Bauer, D., Haroutunian, V., Meador-Woodruff, J. H. & McCullumsmith, R. E. Abnormal glycosylation of EAAT1 and EAAT2 in prefrontal cortex of elderly patients with schizophrenia. Schizophr Res 117, 92-98, https://doi. org/10. 1016/j. schres. 2009. 07. 025 (2010).
13. Narayan, S., Head, S. R., Gilmartin, T. J., Dean, B. & Thomas, E. A. Evidence for disruption of sphingolipid metabolism in schizophrenia. J Neurosci Res 87, 278-288, https://doi. org/10. 1002/jnr. 21822 (2009).
14. Maguire, T. M., Thakore, J., Dinan, T. G., Hopwood, S. & Breen, K. C. Plasma sialyltransferase levels in psychiatric disorders as a possible indicator of HPA axis function. Biol Psychiatry 41, 1131-1136, https://doi. org/10. 1016/s0006-3223(96)00223-5 (1997).
15. Maguire, T. M., Coughlan, C. M., Seckl, J. R. & Breen, K. C. The effect of corticosteroids on serum sialyltransferase enzyme activities in the rat. Biochim Biophys Acta 1379, 23-28 (1998).
16. Wang, X. C., O'Hanlon, T. P. & Lau, J. T. Regulation of beta-galactoside alpha 2, 6-sialyltransferase gene expression by dexamethasone. J Biol Chem 264, 1854-1859 (1989).
17. Dempster, E. L. et al. Disease-associated epigenetic changes in monozygotic twins discordant for schizophrenia and bipolar disorder. Hum Mol Genet 20, 4786-4796, https://doi. org/10. 1093/hmg/ddr416 (2011).
18. McAuley, E. Z. et al. Identification of sialyltransferase 8B as a generalized susceptibility gene for psychotic and mood disorders on chromosome 15q25-26. PLoS ONE 7, e38172, https://doi. org/10. 1371/journal. pone. 0038172 (2012).
19. Baysal, B. E. et al. A mannosyltransferase gene at 11q23 is disrupted by a translocation breakpoint that co-segregates with bipolar affective disorder in a small family. Neurogenetics 4, 43-53 (2002).
20. Hamshere, M. L. et al. Genetic utility of broadly defined bipolar schizoaffective disorder as a diagnostic concept. The British journal of psychiatry: The journal of mental science 195, 23-29, https://doi. org/10. 1192/bjp. bp. 108. 061424 (2009).
21. Beasley, C. L. et al. Proteomic analysis of the anterior cingulate cortex in the major psychiatric disorders: Evidence for diseaseassociated changes. Proteomics 6, 3414-3425, https://doi. org/10. 1002/pmic. 200500069 (2006).
22. Gottschalk, M. G., Wesseling, H., Guest, P. C. & Bahn, S. Proteomic enrichment analysis of psychotic and affective disorders reveals common signatures in presynaptic glutamatergic signaling and energy metabolism. The international journal of neuropsychopharmacology 18, https://doi. org/10. 1093/ijnp/pyu019 (2014).
23. Johnston-Wilson, N. L. et al. Disease-specific alterations in frontal cortex brain proteins in schizophrenia, bipolar disorder, and major depressive disorder. The Stanley Neuropathology Consortium. Molecular psychiatry 5, 142-149 (2000).
24. Martins-de-Souza, D. et al. Identification of proteomic signatures associated with depression and psychotic depression in postmortem brains from major depression patients. Translational Psychiatry 2, e87-, https://doi. org/10. 1038/tp. 2012. 13 (2012).
25. Park, D. I. et al. Delineation of molecular pathway activities of the chronic antidepressant treatment response suggests important roles for glutamatergic and ubiquitin-proteasome systems. Translational Psychiatry 7, e1078, https://doi. org/10. 1038/tp. 2017. 39 (2017).
26. Park, D. I. et al. Purine and pyrimidine metabolism: Convergent evidence on chronic antidepressant treatment response in mice and humans. Scientific reports 6, 35317, https://doi. org/10. 1038/srep35317 (2016).
27. Webhofer, C. et al. Proteomic and metabolomic profiling reveals time-dependent changes in hippocampal metabolism upon paroxetine treatment and biomarker candidates. Journal of psychiatric research 47, 289-298, https://doi. org/10. 1016/j. jpsychires. 2012. 11. 003 (2013).
28. Croft, D. et al. The Reactome pathway knowledgebase. Nucleic Acids Res 42, D472-477, https://doi. org/10. 1093/nar/gkt1102 (2014).
29. Milacic, M. et al. Annotating cancer variants and anti-cancer therapeutics in reactome. Cancers (Basel) 4, 1180-1211, https://doi. org/10. 3390/cancers4041180 (2012).
30. Hori, H. et al. Blood-based gene expression signatures of medication-free outpatients with major depressive disorder: integrative genome-wide and candidate gene analyses. Scientific reports 6, 18776, https://doi. org/10. 1038/srep18776 (2016).
31. Jansen, R. et al. Gene expression in major depressive disorder. Molecular psychiatry 21, 339-347, https://doi. org/10. 1038/mp. 2015. 57 (2016).
32. Martins-de-Souza, D. et al. Blood mononuclear cell proteome suggests integrin and Ras signaling as critical pathways for antidepressant treatment response. Biol Psychiatry 76, e15-17, https://doi. org/10. 1016/j. biopsych. 2014. 01. 022 (2014).
33. Yamagata, H. et al. Altered plasma protein glycosylation in a mouse model of depression and in patients with major depression. Journal of affective disorders, https://doi. org/10. 1016/j. jad. 2017. 08. 057 (2017).
34. Ding, X. et al. The Potential Biomarker Panels for Identification of Major Depressive Disorder (MDD) Patients with and without Early Life Stress (ELS) by Metabonomic Analysis. PLoS ONE 9, https://doi. org/10. 1371/journal. pone. 0097479 (2014).
35. D'Souza-Schorey, C. & Chavrier, P. ARF proteins: roles in membrane traffic and beyond. Nat Rev Mol Cell Biol 7, 347-358, https:// doi. org/10. 1038/nrm1910 (2006).
36. Fisher, P. & Ungar, D. Bridging the Gap between Glycosylation and VesicleTraffic. Front Cell Dev Bio l4, 15, https://doi. org/10. 3389/ fcell. 2016. 00015 (2016).
37. Martins-de-Souza, D. et al. Plasma fibrinogen: now also an antidepressant response marker Translational Psychiatry 4, e352, https:// doi. org/10. 1038/tp. 2013. 129 (2014).
38. Lefkovits, J., Plow, E. F. & Topol, E. J. Platelet glycoprotein IIb/IIIa receptors in cardiovascular medicine. N Engl J Med 332, 1553-1559, https://doi. org/10. 1056/nejm199506083322306 (1995).
39. Crook, M. Sialic Acid: its importance to platelet function in health and disease. Platelets 2, 1-10, https://doi. org/10. 3109/09537109109005496 (1991).
40. Yun, S. H., Sim, E. H., Goh, R. Y., Park, J. I. & Han, J. Y. Platelet Activation: The Mechanisms and Potential Biomarkers. Biomed Res Int 2016, 9060143, https://doi. org/10. 1155/2016/9060143 (2016).
41. Kelm, S. & Schauer, R. Sialic acids in molecular and cellular interactions. International review of cytology 175, 137-240 (1997).
42. Mercado, C. P. et al. A serotonin-induced N-glycan switch regulates platelet aggregation. Scientific reports 3, https://doi. org/10. 1038/ srep02795 (2013).
43. Lopez-Vilchez, I., Diaz-Ricart, M., White, J. G., Escolar, G. & Galan, A. M. Serotonin enhances platelet procoagulant properties and their activation induced during platelet tissue factor uptake. Cardiovasc Res 84, 309-316, https://doi. org/10. 1093/cvr/cvp205 (2009).
44. Morrell, C. N. et al. Glutamate mediates platelet activation through the AMPA receptor. J Exp Med 205, 575-584, https://doi. org/10. 1084/jem. 20071474 (2008).
45. Hannestad, J., DellaGioia, N. & Bloch, M. The effect of antidepressant medication treatment on serum levels of inflammatory cytokines: A meta-analysis. Neuropsychopharmacology 36, 2452-2459, https://doi. org/10. 1038/npp. 2011. 132 (2011).
46. Hashioka, S., McGeer, P. L., Monji, A. & Kanba, S. Anti-inflammatory effects of antidepressants: possibilities for preventives against Alzheimer's disease. Cent Nerv Syst Agents Med Chem 9, 12-19 (2009).
47. Dimitrov, J. D., Bayry, J., Siberil, S. & Kaveri, S. V. Sialylated therapeutic IgG: A sweet remedy for inflammatory diseases Nephrol Dial Transplant 22, 1301-1304, https://doi. org/10. 1093/ndt/gfl847 (2007).
48. Shin, T. The pleiotropic effects of galectin-3 in neuroinflammation: A review. Acta histochemica 115, 407-411, https://doi. org/10. 1016/j. Acthis. 2012. 11. 010 (2013).
49. Starossom, S. C. et al. Galectin-1 deactivates classically activated microglia and protects from inflammation-induced neurodegeneration. Immunity 37, 249-263, https://doi. org/10. 1016/j. immuni. 2012. 05. 023 (2012).
50. Mazalouskas, M. et al. Integrin 3 Haploinsufficiency Modulates Serotonin Transport and Antidepressant-Sensitive Behavior in Mice. Neuropsychopharmacology 40, 2015-2024, https://doi. org/10. 1038/npp. 2015. 51 (2015).
51. Svenningsson, P., Kim, Y., Warner-Schmidt, J., Oh, Y.-S. & Greengard, P. p11 and its role in depression and therapeutic responses to antidepressants. Nat Rev Neurosci 14, 673-680, https://doi. org/10. 1038/nrn3564 (2013).
52. Knezevic, A. et al. Effects of aging, body mass index, plasma lipid profiles, and smoking on human plasma N-glycans. Glycobiology 20, 959-969, https://doi. org/10. 1093/glycob/cwq051 (2010).
53. Opel, N. et al. Obesity and major depression: Body-mass index (BMI) is associated with a severe course of disease and specific neurostructural alterations. Psychoneuroendocrinology 51, 219-226, https://doi. org/10. 1016/j. psyneuen. 2014. 10. 001 (2015).
54. Parekh, A., Smeeth, D., Milner, Y. & Thuret, S. The Role of Lipid Biomarkers in MajorDepression. Healthcare 5, https://doi. org/10. 3390/healthcare5010005 (2017).
55. Pasco, J. A. et al. Tobacco smoking as a risk factor for major depressive disorder: population-based study. The British journal of psychiatry: The journal of mental science 193, 322-326, https://doi. org/10. 1192/bjp. bp. 107. 046706 (2008).
56. Akmacic, I. T. et al. High-throughput glycomics: optimization of sample preparation. Biochemistry. Biokhimiia 80, 934-942, https:// doi. org/10. 1134/s0006297915070123 (2015).
57. Pucic, M. et al. High throughput isolation and glycosylation analysis of IgG-variability and heritability of the IgG glycome in three isolated human populations. Mol Cell Proteomics 10(M111), 010090, https://doi. org/10. 1074/mcp. M111. 010090 (2011).
58. Pezer, M. et al. Effects of allergic diseases and age on the composition of serum IgG glycome in children. Scientific reports 6, 33198, https://doi. org/10. 1038/srep33198 (2016).
59. Selman, M. H. et al. Fc specific IgG glycosylation profiling by robust nano-reverse phase HPLC-MS using a sheath-flow ESI sprayer interface. J Proteomics 75, 1318-1329, https://doi. org/10. 1016/j. jprot. 2011. 11. 003 (2012).
60. Balbin, M., Grubb, A., de Lange, G. G. & Grubb, R. DNA sequences specific for Caucasian G3m(b) and (g) allotypes: Allotyping at the genomic level. Immunogenetics 39, 187-193 (1994).