The Neurobiology of Suicide: Claudin-5 is a Novel Biomarker of Suicide Pathogenesis

ISBN: 979-8-89480-845-1


Every forty seconds, suicide steals a life, yet no biomarkers exist for suicide. Suicide has largely been investigated from a psychological lens, and therefore the pathogenesis remains unclear. This study investigated blood-brain barrier (BBB) claudin-5 breakdown, the most enriched BBB tight junction, as a biomarker for suicide. Human de-identified postmortem brain tissue (n=20) was stratified based on suicidality. ELISAs assessed cytokine and claudin-5 levels and an immunolabeling solvent-cleared organs protocol determined claudin-5 localization. RNA-sequencing data from publicly-available repositories was aligned to perform pathway enrichment and differential expression analyses. Molecular docking software PyRx determined whether current medications to treat suicide and anti-inflammatory compounds dock with claudin-5. IL-6 and IL-8 were higher in suicide cases (p < 0.05) indicating neuroinflammation and claudin-5 was increased in the brain of suicide cases (p < 0.05). Photomicrographs indicated claudin-5 mislocalization in neurons and brain microvessels of suicides. Inflammatory and neurodegenerative pathways modulating claudin-5 degradation were identified. Matrix metalloproteinase-1 (MMP-1) was upregulated (log2F2 = 4.10, p < 0.001), and aquaporin-1 (AQP1) was downregulated (log2F2 = -1.58; p < 0.001) in suicide. Molecular docking indicated a weak affinity of antidepressants for claudin-5, but a strong affinity for medications targeting MMP-1 and AQP1. High claudin-5 levels could serve as pre-markers for suicide. Future in vitro assessments should evaluate the novel therapeutics promoting claudin-5 for suicide risk prevention. 

References

  1. World Health Organization. (2019, September 9). Suicide: One person dies every 40 seconds. World Health Organization. Retrieved June 25, 2022, from https://www.who.int/news/item/09-09-2019-suicide-one-person-dies-every-40-seconds.
  2. Sliwa, J. (2016). After decades of research, science is no better able to predict suicidal behaviors. American Psychological Association. https://doi.org/10.1037/e515562016-001.
  3. Franklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., Musacchio, K. M., Jaroszewski, A. C., Chang, B. P., & Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research. Psychological Bulletin, 143(2), 187–232. https://doi.org/10.1037/bul0000084.
  4. National Action Alliance for Suicide Prevention: Research Prioritization Task Force. (2014). A prioritized research agenda for suicide prevention: An action plan to save lives. Rockville, MD: National Institute of Mental Health and the Research Prioritization Task Force.
  5. Stovall, J., & Domino, F. J. (2003). Approaching the suicidal patient. American Family Physician, 68(9), 1814–1818.
  6. Simon, G. E., Yarborough, B. J., Rossom, R. C., Lawrence, J. M., Lynch, F. L., Waitzfelder, B. E., & Shortreed, S. M. (2019). Self-reported suicidal ideation as a predictor of suicidal behavior among outpatients with diagnoses of psychotic disorders. Psychiatric Services, 70(3), 176–183. doi:10.1176/appi.ps.201800381.
  7. Friedlander, A., Nazem, S., Fiske, A., Nadorff, M. R., & Smith, M. D. (2012). Self-concealment and suicidal behaviors. Suicide and Life-Threatening Behavior, 42(3), 332–340. doi:10.1111/j.1943-278X.2012.00094.x.
  8. Franklin, J. C., Ribeiro, J. D., Fox, K. R., Bentley, K. H., Kleiman, E. M., Huang, X., Musacchio, K. M., Jaroszewski, A. C., Chang, B. P., & Nock, M. K. (2017). Risk factors for suicidal thoughts and behaviors: A meta-analysis of 50 years of research.
  9. Nock, M. K. (2016). Recent and needed advances in the understanding, prediction, and prevention of suicidal behavior. Depression and Anxiety, 33(6), 460–463. https://doi.org/10.1002/da.22528.
  10. Niciu, M. J., Mathews, D. C., Ionescu, D. F., Richards, E. M., Furey, M. L., Yuan, P., Nugent, A. C., Henter, I. D., Machado-Vieira, R., & Zarate, C. A. Jr. (2014). Biomarkers in mood disorders research: Developing new and improved therapeutics. Revista de Psiquiatria Clinica, 41, 131–134.
  11. Johnston, J. N., Campbell, D., Caruncho, H. J., Henter, I. D., Ballard, E. D., & Zarate, C. A. Jr. (2022). Suicide biomarkers to predict risk, classify diagnostic subtypes, and identify novel therapeutic targets: 5 years of promising research. International Journal of Neuropsychopharmacology, 25(3), 197–214. https://doi.org/10.1093/ijnp/pyab083.
  12. Interian, A., Myers, C. E., Chesin, M. S., Kline, A., Hill, L. S., King, A. R., Miller, R., Latorre, M., Gara, M. A., Stanley, B. H., & Keilp, J. G. (2020). Towards the objective assessment of suicidal states: Some neurocognitive deficits may be temporally related to suicide attempt. Psychiatry Research, 287, 112624. https://doi.org/10.1016/j.psychres.2019.112624.
  13. Rajalin, M., Hirvikoski, T., Renberg, E. S., Åsberg, M., & Jokinen, J. (2020). Exposure to early life adversity and interpersonal functioning in attempted suicide. Frontiers in Psychiatry, 11, 552514. doi:10.3389/fpsyt.2020.552514. PMID: 33093835; PMCID: PMC7527599.
  14. Duffy, K. A., McLaughlin, K. A., & Green, P. A. (2018). Early life adversity and health-risk behaviors: Proposed psychological and neural mechanisms. Annals of the New York Academy of Sciences, 1428(1), 151–169. doi:10.1111/nyas.13928. PMID: 30011075; PMCID: PMC6158062.
  15. Mann, J. J., & Rizk, M. M. (2020). A brain-centric model of suicidal behavior. The American Journal of Psychiatry, 177(10), 902–916. https://doi.org/10.1176/appi.ajp.2020.20081224.
  16. Cunningham, K., Mengelkoch, S., Gassen, J., & Hill, S. E. (2022). Early life adversity, inflammation, and immune function: An initial test of adaptive response models of immunological programming. Development and Psychopathology, 34(2), 539–555.
  17. Shalev, I., Hastings, W. J., Etzel, L., Israel, S., Russell, M. A., Hendrick, K. A., et al. (2020). Investigating the impact of early-life adversity on physiological, immune, and gene expression responses to acute stress: A pilot feasibility study. PLOS ONE, 15(4), e0221310.
  18. Andersen, S. L. (2022). Neuroinflammation, early-life adversity, and brain development. Harvard Review of Psychiatry, 30(1), 24–39. https://doi.org/10.1097/HRP.0000000000000325.
  19. Dich, N., Hansen, Å. M., Avlund, K., Lund, R., Mortensen, E. L., Bruunsgaard, H., & Rod, N. H. (2015). Early life adversity potentiates the effects of later life stress on cumulative physiological dysregulation. Anxiety, Stress, & Coping, 28(4), 372–390. https://doi.org/10.1080/10615806.2014.969720.
  20. Horn, S. R., Leve, L. D., Levitt, P., & Fisher, P. A. (2019). Childhood adversity, mental health, and oxidative stress: A pilot study. PLOS ONE, 14(4), e0215085. doi:10.1371/journal.pone.0215085. PMID: 31026258; PMCID: PMC6485615.
  21. Wolkow, A., Aisbett, B., Reynolds, J., Ferguson, S. A., & Main, L. C. (2015). Relationships between inflammatory cytokine and cortisol responses in firefighters exposed to simulated wildfire suppression work and sleep restriction. Physiological Reports, 3(11), e12604. doi:10.14814/phy2.12604. PMID: 26603450; PMCID: PMC4673634.
  22. Kim, Y. K., Na, K. S., Myint, A. M., & Leonard, B. E. (2016). The role of pro-inflammatory cytokines in neuroinflammation, neurogenesis and the neuroendocrine system in major depression. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 64, 277–284. https://doi.org/10.1016/j.pnpbp.2015.06.008.
  23. Daneman, R., & Prat, A. (2015). The blood-brain barrier. Cold Spring Harbor Perspectives in Biology, 7(1), a020412. doi:10.1101/cshperspect.a020412. PMID: 25561720; PMCID: PMC4292164.
  24. Kadry, H., Noorani, B., & Cucullo, L. (2020). A blood–brain barrier overview on structure, function, impairment, and biomarkers of integrity. Fluids and Barriers of the CNS, 17, 69. https://doi.org/10.1186/s12987-020-00230-3.
  25. Rochfort, K. D., Collins, L. E., Murphy, R. P., & Cummins, P. M. (2014). Downregulation of blood-brain barrier phenotype by proinflammatory cytokines involves NADPH oxidase-dependent ROS generation: Consequences for interendothelial adherens and tight junctions. PLOS ONE, 9(7), e101815.