Advertisement

Futuristic Methods for Treatment of HIV in the Nervous System

  • Allison NavisEmail author
  • Jessica Robinson-Papp
Chapter

Abstract

While many pathogens can seed the central nervous system (CNS) and cause severe morbidity and mortality, HIV presents a unique challenge. HIV is known to cross into the CNS early on in infection, and long-term infection leads to neurocognitive impairment. Antiretrovirals (ARVs) have decreased the complications related to HIV, and extended the lifespan for those living with the virus; however, they haven’t lowered the overall prevalence of neurocognitive disorders. One theory is due to compartmentalization of the virus in the CNS, leading to low level viremia and inflammation. ARVs have variable penetrance into the brain, which may explain the compartmentalization. Many new techniques are being used to tackle this problem such as nanotechnology. Nanotechnology offers a means of modifying existing ARVs and increasing their CNS penetration as well as sustaining CNS concentrations by conjugating them with liposomes, or ligands that can bind to receptors on the surface of the blood-brain barrier. Further, techniques such as machine learning can help in understanding the pathogenesis of cognitive disorders by using computer algorithms to sort through hundreds of variables and determine pathological HIV genes or proteins that can be used to develop medications in the future. While these applications are still in the early-stages, they offer hope in tackling a longstanding problem.

Keywords

Human immunodeficiency virus Anti-retrovirals Central nervous system Blood-brain barrier Nanotechnology Machine learning 

Notes

Acknowledgments

The authors would like to acknowledge the Neuro-AIDS Division at Icahn School of Medicine at Mount Sinai Hospital, including David Simpson MD and Susan Morgello MD for their support in this work.

References

  1. 1.
    Nair S, Diamond MS. Innate immune interactions within the central nervous system modulate pathogenesis of viral infections. Curr Opin Immunol. 2015;36:47–53.PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    Ransohoff RM, Brown MA. Innate immunity in the CNS. J Clin Invest. 2012;122:1164–71.  https://doi.org/10.1172/JCI58644.CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Berlin LE, Rorabaugh ML, Heldrich F, et al. Aseptic meningitis in infants <2 years of age: diagnosis and etiology. J Infect Dis. 1993;168(4):888–92.PubMedCrossRefGoogle Scholar
  4. 4.
    Teoh HL, Mohammad SS, Britton PN, et al. Clinical characteristics and functional motor outcomes of enterovirus 71 neurological disease in children. JAMA Neurol. 2016;73(3):300–7.PubMedCrossRefPubMedCentralGoogle Scholar
  5. 5.
    Frederickson BL. The neuroimmune response to West Nile virus. J Neurovirol. 2014;20(2):113–21.CrossRefGoogle Scholar
  6. 6.
    Shih C, Liao CC, Chang YS, et al. Immunocompetent and immunodeficient mouse models for enterovirus 71 pathogenesis and therapy. Viruses. 2018;10(12):674.  https://doi.org/10.3390/v10120674.CrossRefPubMedCentralGoogle Scholar
  7. 7.
    Whitley RJ, Alford CA, Hirsch MS, et al. Vidarabine versus acyclovir therapy in herpes simplex encephalitis. N Engl J Med. 1986;314(3):144–9.PubMedCrossRefPubMedCentralGoogle Scholar
  8. 8.
    Caniglia EC, Phillips A, Porter K, et al. Commonly prescribed antiretroviral therapy regimens and incidence of AIDS-defining neurological conditions. J Acquir Immune Defic Syndr. 2018;77(1):102–9.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Joseph J, Colosi DA, Rao VR. HIV-1 induced CNS dysfunction: current overview and research priorities. Curr HIV Res. 2016;14(5):389–99.PubMedCrossRefPubMedCentralGoogle Scholar
  10. 10.
    Gartner S, Liu Y. HIV neuroinvasion. In: Shapshak P, Levine AJ, Foley BT, Somboonwit C, Singer E, Chiappelli F, Sinnott JT, editors. Global virology II-HIV and NeuroAIDS. New York: Springer; 2017. p. 111–42.Google Scholar
  11. 11.
    Spudich S, Gisslen M, Hagberg L, et al. Central nervous system immune activation characterizes primary human immunodeficiency virus 1 infection even in participants with minimal cerebrospinal fluid viral burden. J Infect Dis. 2012;206(2):275–82.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Fischer-Smoth T, Bell C, Croul S, et al. Monocyte/macrophage trafficking in acquired immunodeficiency syndrome encephalitis: lessons from human and nonhuman primate studies. J Neurovirol. 2008;14(4):318–32.CrossRefGoogle Scholar
  13. 13.
    Siminoi S, Cavassini M, Annoni JM, et al. Cognitive dysfunction in HIV patients despite long-standing suppression of viremia. AIDS. 2010;24(9):1243–50.Google Scholar
  14. 14.
    Heaton RK, Clifford DB, Franklin DR, et al. HIV-associated neurocognitive disorders persist in the era of potent antiretroviral therapy; a Charter Study. Neurology. 2010;75:2087–96.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Antinori A, Arendt G, Becker JT, et al. Updated research nosology for HIV-associated neurocognitive disorders. Neurology. 2007;69(18):1789–99.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    de Almeida SM, Rotta I, Ribeiro CE, Smith D, HNRC Group, et al. Blood-CSF barrier and compartmentalization of CNS cellular immune response in HIV infection. J Neuroimmunol. 2016;301:41–8.PubMedPubMedCentralCrossRefGoogle Scholar
  17. 17.
    Rawson T, Muir D, Mackie NE, et al. Factors associated with cerebrospinal fluid HIV RNA in HIV infected subjects undergoing lumbar puncture examination in a clinical setting. J Infect. 2012;65:239–45.PubMedCrossRefPubMedCentralGoogle Scholar
  18. 18.
    Eden A, Fuchs D, Hagberg L, et al. HIV-1 viral escape in cerebrospinal fluid of subjects on suppressive antiretroviral treatment. J Infect Dis. 2010;202:1819–25.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Peluso MJ, Ferretti F, Peterson J, et al. Cerebrospinal fluid HIV escape associated with progressive neurologic dysfunction in patients on antiretroviral therapy with well controlled plasma viral load. AIDS. 2012;26:1765–74.PubMedCrossRefPubMedCentralGoogle Scholar
  20. 20.
    Nightingale S, Geretti AM, Beloukas A, et al. Discordant CSF/plasmaHIV-1 RNA in patients with unexplained low-level viraemia. J Neurovirol. 2016;22:852–60.PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Anderson AM, Munoz-Moreno JA, McClernon D, et al. Prevalence andcorrelates of persistent HIV-1 RNA in cerebrospinalfluid duringantiretroviral therapy. J Infect Dis. 2016;215:105–13.PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Mukerji SS, Misra V, Lorenz D, et al. Temporal patterns and drug resistance in CSF viral escape among ART experienced HIV-1 infected adults. J Acquir Immune Defic Syndr. 2017;75(2):246–55.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Letendre S, Marquie-Beck J, Capparelli E, CHARTER GROUP, et al. Validation of the CNS penetration-effectiveness rank for quantifying antiretroviral penetration into the central nervous system. Arch Neurol. 2008;65(1):65–70.PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Antinori A, Lorenzini P, Giancola ML et al. Antiretroviral CNS Penetration-Effectiveness (CPE) 2010 ranking predicts CSF Viral Suppression Only in Patients with an Undetectable HIV-1 RNA in Plasma. 2011. Conference on retroviruses and opportunistic infections, Boston MA. http://www.natap.org/2011/CROI/croi_139.htm.
  25. 25.
    Smurzynski M, Wu K, Letendre S. Effects of central nervous system antiretroviral penetration on cognitive functioning in the ALLRT cohort. AIDS. 2011;25(3):357–65.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Bonet I. Machine learning for prediction of HIV drug resistance: a review. Curr Bioinforma. 2015;10(5):579–85.  https://doi.org/10.2174/1574893610666151008011731.CrossRefGoogle Scholar
  27. 27.
    Reynolds JL, Mahato RI. Nanomedicines for the treatment of CNS diseases. J Neuroimmune Pharmacol. 2017;12:1–5.PubMedCrossRefPubMedCentralGoogle Scholar
  28. 28.
    Teleanu DM, Chircov C, Grumezescu AM, et al. Blood-brain delivery methods using nanotechnology. Pharmaceutics. 2018;10(4):269.CrossRefGoogle Scholar
  29. 29.
    Mehnert W, Mader K. Solid lipid nanoparticles: production, characterization and applications. Adv Drug Deliv Rev. 2001;47(2–3):165–96.PubMedCrossRefPubMedCentralGoogle Scholar
  30. 30.
    Fiandra L, Capetti A, Sorrentino L, Corsi F. Nanoformulated antiretrovirals for pentration of the central nervous system: state of the art. J Neuroimmune Pharmacol. 2017;12:17–30.PubMedCrossRefGoogle Scholar
  31. 31.
    Gupta S, Kesarla R, Chotai N, Misra A, Omri A. Systematic approach for the formulation and optimization of solid lipid nanoparticles of Efavirenz by high pressure homogenization using design of experiments for brain targeting and enhanced bioavailability. Biomed Res Int. 2017;2017:5984014.PubMedPubMedCentralGoogle Scholar
  32. 32.
    Torchilin VP. Recent advances with liposomes as pharmaceutical carriers. Nat Rev Drug Discov. 2005;4(2):145–60.PubMedCrossRefGoogle Scholar
  33. 33.
    Saiyed ZM, Gandhi NH, Nair MPN. Magnetic nanoformulation of azidothymidine 5′-triphosphate for targeted delivery across the blood-brain barrier. Int J Nanomedicine. 2010;5:157–66.PubMedPubMedCentralGoogle Scholar
  34. 34.
    Bollam S, Kandadi P, Apte SS, Veerabrahma K. Development of indinavir submicron lipid emulsions loaded with lipoamino acids- in vivo pharmacokinetics and brain-specific delivery. AAPS PharmSciTech. 2011;12(1):422–30.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Kuo YC, Ko HF. Targeting delivery of saquinavir to the brain using 83-14 monoclonal antibody-grafted solid lipid nanoparticles. Biomaterials. 2013;34(20):4818–30.PubMedCrossRefGoogle Scholar
  36. 36.
    Polli JW, Jarrett JL, Studenberg SD, et al. Role of P-glycoprotein on the CNS disposition of amprenavir (141W94), an HIV protease inhibitor. Pharm Res. 1999;16(8):1206–12.PubMedCrossRefGoogle Scholar
  37. 37.
    Van der Sandt IC, Vos CM, Nabulsi L, et al. Assessment of active transport of HIV protease inhibitor in various cell lines and the in vitro blood-brain barrier. AIDS. 2001;15(4):483–91.PubMedCrossRefGoogle Scholar
  38. 38.
    Rao KS, Reddy MK, Horning JL, Labhasetwar V. TAT-conjugated nanoparticles for the CNS delivery of ani-HIV drugs. Biomaterials. 2008;29(33):4429–38.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Borgmann K, Rao KS, Labhasetwar V, Ghorpade A. Efficacy of TAT-conjugated ritonavir-loaded nanoparticles in reducing HIV-1 replication in monocyte derived macrophages and cytocompatibility with macrophages and human neurons. AIDS Res Hum Retrovir. 2011;27(8):853–62.PubMedCrossRefGoogle Scholar
  40. 40.
    Kuo YC, Su FL. Transport of stavudine, delavirdine, and saquinavir across the blood-brain barrier by polybutylcyanoacrylate, methylmethacrylate-sulfopropylmethacrylate, and solid lipid nanoparticles. Int J Pharm. 2007;340(1–2):143–52.PubMedCrossRefPubMedCentralGoogle Scholar
  41. 41.
    Kuo YC, Kuo CY. Electromagnetic interference in the permeability of saquinavir across the blood-brain barrier using nanoparticulate carriers. Int J Pharm. 2008;351(1–2):271–81.PubMedCrossRefPubMedCentralGoogle Scholar
  42. 42.
    Fire A, Xu S, Montgomery MK, Kostas SA, Driver SE, Mello CC. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature. 1998;391(6669):806–11.PubMedCrossRefPubMedCentralGoogle Scholar
  43. 43.
    Scarborough RJ, Gatignol A. RNA interference therapies for an HIV-1 functional cure. Viruses. 2018;10(1):8.CrossRefGoogle Scholar
  44. 44.
    Bobbin M, Burnett JC, Rossi JJ. RNA interference approaches for treatment of HIV-1 infection. Genome Med. 2015;7(1):50.PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Long L, Thelen JP, Furgason M, et al. The U4/U6 recycling factor SART3 has histone chaperone activity and associates with USP15 to regulate H2B deubiquitination. J Biol Chem. 2014;289:8916–30.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Chiu YL, Cao H, Jacque JM, Stevenson M, Rana TM. Inhibition of human immunodeficiency virus type 1 replication by RNA interference directed against human transcription elongation factor P-TEFb (CDK9/cyclinT1). J Virol. 2004;78:2517–29.PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Gu J, Al-Bayati K, Ho EA. Development of antibody-modified chitosan nanoparticles for the targeted delivery of siRNA across the blood-brain barrier as a strategy for inhibiting HIV replication in astrocytes. Drug Deliv Transl Res. 2017;7(4):497–506.PubMedCrossRefPubMedCentralGoogle Scholar
  48. 48.
    Zhang L, Tan J, Han D, Zhu H. From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discov Today. 2017;22(11):1680–5.PubMedCrossRefPubMedCentralGoogle Scholar
  49. 49.
    Libbrecht MW. Machine learning in genetics and genomics. Nat Rev Genet. 2015;16(6):321–32.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Holman AG, Gabuzda D. A machine learning approach for identifying amino acid signatures in the HIV env gene predictive of dementia. PLoS One. 2012;7(11):e49538.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Ogishi M, Yotsuyanagi H. Prediction of HIV-associated neurocognitive disorder (HAND) from three genetic features of envelope pg120 glycoprotein. Retrovirology. 2018;15:12.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Pillai SK, Kosakovsky Pond SL, Liu Y, et al. Genetic attributes of cerebrospinal fluid-derived HIV-1 env. Brain. 2006;129(7):1872–83.PubMedCrossRefPubMedCentralGoogle Scholar
  53. 53.
    Underwood J, Cole JH, Leech R, et al. Multivariate pattern analysis of volumetric neuroimaging data and its relationship with cognitive function in treated HIV disease. J Acquir Immune Defic Syndr. 2018;78(4):429–36.PubMedPubMedCentralCrossRefGoogle Scholar
  54. 54.
    Dsouza AM, Abidin AZ, Leistritz L, Wismuller A. Identifying HIV associated neurocognitive disorder using large-scale granger causality analysis on resting-state functional MRI. Proc SPIE Int Opt Eng. 2017;10133:101330M.CrossRefGoogle Scholar
  55. 55.
    Dsouza AM, Abidin AZ, Wismuller A. Investigating changes in resting-state connectivity from functional MRI data in patients with HIV associated neurocognitive disorder using MCA and machine learning. Proc SPIE Int Soc Opt Eng. 2017;10137:101371C.PubMedPubMedCentralGoogle Scholar
  56. 56.
    Wright EJ, Grund B, Robertson K, et al. Cardiovascular risk factors associated with lower baseline cognitive performance in HIV-positive persons. Neurology. 2010;75(10):864–73.PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Robertson K, Liner J, Meeker RB. Antiretroviral neurotoxicity. J Neurovirol. 2012;18(5):388–99.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Neuro-AIDS Division, Department of NeurologyIcahn School of Medicine at Mount Sinai, One Gustave L. Levy PlaceNew YorkUSA

Personalised recommendations