Journal of NeuroVirology

, Volume 23, Issue 2, pp 319–328 | Cite as

Neuroimaging abnormalities in clade C HIV are independent of Tat genetic diversity

  • Robert H. PaulEmail author
  • Sarah Phillips
  • Jacqueline Hoare
  • David H. Laidlaw
  • Ryan Cabeen
  • Gayla R. Olbricht
  • Yuqing Su
  • Dan J. Stein
  • Susan Engelbrecht
  • Soraya Seedat
  • Lauren E. Salminen
  • Laurie M. Baker
  • Jodi Heaps
  • John Joska


Controversy remains regarding the neurotoxicity of clade C human immunodeficiency virus (HIV-C). When examined in preclinical studies, a cysteine to serine substitution in the C31 dicysteine motif of the HIV-C Tat protein (C31S) results in less severe brain injury compared to other viral clades. By contrast, patient cohort studies identify significant neuropsychological impairment among HIV-C individuals independent of Tat variability. The present study clarified this discrepancy by examining neuroimaging markers of brain integrity among HIV-C individuals with and without the Tat substitution. Thirty-seven HIV-C individuals with the Tat C31S substitution, 109 HIV-C individuals without the Tat substitution (C31C), and 34 HIV− controls underwent 3T structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Volumes were determined for the caudate, putamen, thalamus, corpus callosum, total gray matter, and total white matter. DTI metrics included fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). Tracts of interest included the anterior thalamic radiation (ATR), cingulum bundle (CING), uncinate fasciculus (UNC), and corpus callosum (CC). HIV+ individuals exhibited smaller volumes in subcortical gray matter, total gray matter and total white matter compared to HIV− controls. HIV+ individuals also exhibited DTI abnormalities across multiple tracts compared to HIV− controls. By contrast, neither volumetric nor diffusion indices differed significantly between the Tat C31S and C31C groups. Tat C31S status is not a sufficient biomarker of HIV-related brain integrity in patient populations. Clinical attention directed at brain health is warranted for all HIV+ individuals, independent of Tat C31S or clade C status.


HIV Clade C C30C31 dicysteine motif Tat C31S Neuroimaging 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest. This work was supported by a NIH grant (MH085604).


  1. Ackermann C, Andronikou S, Laughton B, Kidd M, Dobbels E, Innes S et al (2014) White matter signal abnormalities in children with suspected HIV-related neurologic disease on early combination antiretroviral therapy. Pediatr Infect Dis J 33:e207–e212CrossRefPubMedPubMedCentralGoogle Scholar
  2. Ananworanich J, Sacdalan CP, Pinyakorn S, Chomont N, de Souza M, Luekasemsuk T et al (2016) Virological and immunological characteristics of HIV-infected individuals at the earliest stage of infection. Journal of virus eradication 2:43–48PubMedPubMedCentralGoogle Scholar
  3. Ances BM, Ortega M, Vaida F, Heaps J, Paul R (2012) Independent effects of HIV, aging, and HAART on brain volumetric measures. Journal of acquired immune deficiency syndromes (1999) 59:469–477CrossRefGoogle Scholar
  4. Boivin MJ, Ruel TD, Boal HE, Bangirana P, Cao H, Eller LA et al (2010) HIV-subtype A is associated with poorer neuropsychological performance compared with subtype D in antiretroviral therapy-naive Ugandan children. AIDS 24:1163–1170CrossRefPubMedPubMedCentralGoogle Scholar
  5. Catani M, de Schotten MT (2012) Atlas of human brain connections Google Scholar
  6. Chan PA, Reitsma MB, DeLong A, Boucek B, Nunn A, Salemi M et al (2014) Phylogenetic and geospatial evaluation of HIV-1 subtype diversity at the largest HIV center in Rhode Island. Infect Genet Evol 28:358–366CrossRefPubMedPubMedCentralGoogle Scholar
  7. Chen Y, An H, Zhu H, Stone T, Smith KJ, Hall C et al (2009) White matter abnormalities revealed by diffusion tensor imaging in non-demented and demented HIV+ patients. NeuroImage 47:1154–1162CrossRefPubMedPubMedCentralGoogle Scholar
  8. Cohen RA, Harezlak J, Schifitto G, Hana G, Clark U, Gongvatana A et al (2010) Effects of nadir CD4 count and duration of human immunodeficiency virus infection on brain volumes in the highly active antiretroviral therapy era. J Neurovirol 16:25–32CrossRefPubMedPubMedCentralGoogle Scholar
  9. Constantino AA, Huang Y, Zhang H, Wood C, Zheng JC (2011) HIV-1 clade B and C isolates exhibit differential replication: relevance to macrophage-mediated neurotoxicity. Neurotox Res 20:277–288CrossRefPubMedPubMedCentralGoogle Scholar
  10. Correia S, Lee SY, Voorn T, Tate DF, Paul RH, Zhang S et al (2008) Quantitative tractography metrics of white matter integrity in diffusion-tensor MRI. NeuroImage 42:568–581CrossRefPubMedPubMedCentralGoogle Scholar
  11. de Almeida S, Ribeiro C, de Pereira A, Badiee J, Cherner M, Smith D et al (2013) Neurocognitive impairment in HIV-1 clade C- versus B-infected individuals in Southern Brazil. Journal of NeuroVirology 19:550–556CrossRefPubMedPubMedCentralGoogle Scholar
  12. Desikan RS, Segonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31:968–980CrossRefPubMedGoogle Scholar
  13. Filippi CG, Ulug AM, Ryan E, Ferrando SJ, van Gorp W (2001) Diffusion tensor imaging of patients with HIV and normal-appearing white matter on MR images of the brain. AJNR Am J Neuroradiol 22:277–283PubMedGoogle Scholar
  14. Fischl B, Dale AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci U S A 97:11050–11055CrossRefPubMedPubMedCentralGoogle Scholar
  15. Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C et al (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33:341–355CrossRefPubMedGoogle Scholar
  16. Gamaldo CE, Gamaldo A, Creighton J, Salas RE, Selnes OA, David PM et al (2013) Evaluating sleep and cognition in HIV. J Acquir Immune Defic Syndr 63:609–616CrossRefPubMedGoogle Scholar
  17. Gandhi N, Saiyed Z, Thangavel S, Rodriguez J, Rao KV, Nair MP (2009) Differential effects of HIV type 1 clade B and clade C Tat protein on expression of proinflammatory and antiinflammatory cytokines by primary monocytes. AIDS Res Hum Retrovir 25:691–699CrossRefPubMedPubMedCentralGoogle Scholar
  18. Ghate M, Narkhede H, Rahane G, Nirmalkar A, Gaikwad N, Kadam D (2014) Cognitive function among HIV infected children in Pune. Indian J Pediatr 82:515–518CrossRefPubMedGoogle Scholar
  19. Gongvatana A, Schweinsburg BC, Taylor MJ, Theilmann RJ, Letendre SL, Alhassoon OM et al (2009) White matter tract injury and cognitive impairment in human immunodeficiency virus–infected individuals. Journal of Neurovirology 15:187–195CrossRefPubMedPubMedCentralGoogle Scholar
  20. Gupta JD, Satishchandra P, Gopukumar K, Wilkie F, Waldrop-Valverde D, Ellis R et al (2007) Neuropsychological deficits in human immunodeficiency virus type 1 clade C-seropositive adults from South India. J Neurovirol 13:195–202CrossRefPubMedGoogle Scholar
  21. Hawkins CP, McLaughlin JE, Kendall BE, McDonald WI (1993) Pathological findings correlated with MRI in HIV infection. Neuroradiology 35:264–268CrossRefPubMedGoogle Scholar
  22. He JGJ, Mui K, Aminipour S, Kim J, Fuller R, Rataj E, Lentz M, Sehgal P, Westmoreland S, de Crespigny A, Gonzalex R (2003) Diffusion MR detection of early white matter changes in the SIV primate model of neuroaids. Intl Soc Mag Reson Med:2536Google Scholar
  23. Heaps JM, Joska J, Hoare J, Ortega M, Agrawal A, Seedat S et al (2012) Neuroimaging markers of human immunodeficiency virus infection in South Africa. Journal of NeuroVirology 18:151–156CrossRefPubMedPubMedCentralGoogle Scholar
  24. Heaps JM, Sithinamsuwan P, Paul R, Lerdlum S, Pothisri M, Clifford D et al (2015) Association between brain volumes and HAND in cART-naïve HIV+ individuals from Thailand. Journal of NeuroVirology 21:105–112CrossRefPubMedPubMedCentralGoogle Scholar
  25. Hemelaar J, Gouws E, Ghys PD, Osmanov S (2011) Isolation W-UNfH, characterisation. Global trends in molecular epidemiology of HIV-1 during 2000–2007. AIDS 25:679–689CrossRefPubMedPubMedCentralGoogle Scholar
  26. Hoare J, Fouche J-P, Spottiswoode B, Sorsdahl K, Combrinck M, Stein DJ et al (2011) White-matter damage in clade C HIV-positive subjects: a diffusion tensor imaging study. The Journal of Neuropsychiatry and Clinical Neurosciences 23:308315CrossRefGoogle Scholar
  27. Hoare J, Fouche JP, Spottiswoode B, Donald K, Philipps N, Bezuidenhout H et al (2012) A diffusion tensor imaging and neurocognitive study of HIV-positive children who are HAART-naive “slow progressors”. J Neurovirol 18:205–212CrossRefPubMedGoogle Scholar
  28. Hoare J, Fouche J-P, Phillips N, Joska JA, Donald KA, Thomas K et al (2015a) Clinical associations of white matter damage in cART-treated HIV-positive children in South Africa. Journal of NeuroVirology 21:120–128CrossRefPubMedGoogle Scholar
  29. Hoare J, Fouche J-P, Phillips N, Joska JA, Paul R, Donald KA, et al. (2015b) White matter micro-structural changes in ART-naive and ART-treated children and adolescents infected with HIV in South Africa. AIDS, Publish Ahead of PrintGoogle Scholar
  30. Huang W, Eshleman SH, Toma J, Fransen S, Stawiski E, Paxinos EE et al (2007) Coreceptor tropism in human immunodeficiency virus type 1 subtype D: high prevalence of CXCR4 tropism and heterogeneous composition of viral populations. J Virol 81:7885–7893CrossRefPubMedPubMedCentralGoogle Scholar
  31. Jenkinson M, Smith S (2001) A global optimisation method for robust affine registration of brain images. Med Image Anal 5:143–156CrossRefPubMedGoogle Scholar
  32. Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM (2012) FSL. NeuroImage 62:782–790CrossRefPubMedGoogle Scholar
  33. Jernigan TL, Archibald SL, Fennema-Notestine C, Taylor MJ, Theilmann RJ, Julaton MD et al (2011) Clinical factors related to brain structure in HIV: the CHARTER study. J Neurovirol 17:248–257CrossRefPubMedPubMedCentralGoogle Scholar
  34. Joska JA, Westgarth-Taylor J, Myer L, Hoare J, Thomas KGF, Combrinck M et al (2011) Characterization of HIV-associated neurocognitive disorders among individuals starting antiretroviral therapy in South Africa. AIDS Behav 15:1197–1203CrossRefPubMedGoogle Scholar
  35. Kaleebu P, French N, Mahe C, Yirrell D, Watera C, Lyagoba F et al (2002) Effect of human immunodeficiency virus (HIV) type 1 envelope subtypes A and D on disease progression in a large cohort of HIV-1-positive persons in Uganda. The Journal of infectious diseases 185:1244–1250CrossRefPubMedGoogle Scholar
  36. Kaleebu P, Nankya IL, Yirrell DL, Shafer LA, Kyosiimire-Lugemwa J, Lule DB et al (2007) Relation between chemokine receptor use, disease stage, and HIV-1 subtypes A and D: results from a rural Ugandan cohort. Journal of acquired immune deficiency syndromes (1999) 45:28–33CrossRefGoogle Scholar
  37. Kallianpur KJ, Shikuma C, Kirk GR, Shiramizu B, Valcour V, Chow D et al (2013) Peripheral blood HIV DNA is associated with atrophy of cerebellar and subcortical gray matter. Neurology 80:1792–1799CrossRefPubMedPubMedCentralGoogle Scholar
  38. Kallianpur KJC, Donn Jahanshad, Neda Fletcher, James L Ananworanich, Jintanat Clifford, Katherine Benjapornpong, Khunthalee Adams, Collin Spudich, Serena S. Valcour (2016) Victor. for the The RV254/SEARCH010 Study Group. Brain Volumetric Changes After 2 Years of ART Initiated During Acute HIV Infection | CROI Conference. In: CROI. Boston, MAGoogle Scholar
  39. Kiwanuka N, Laeyendecker O, Robb M, Kigozi G, Arroyo M, McCutchan F et al (2008) Effect of human immunodeficiency virus Type 1 (HIV-1) subtype on disease progression in persons from Rakai, Uganda, with incident HIV-1 infection. The Journal of infectious diseases 197:707–713CrossRefPubMedGoogle Scholar
  40. Kiwanuka N, Robb M, Laeyendecker O, Kigozi G, Wabwire-Mangen F, Makumbi FE et al (2010) HIV-1 viral subtype differences in the rate of CD4+ T-cell decline among HIV seroincident antiretroviral naive persons in Rakai district, Uganda. J Acquir Immune Defic Syndr 54:180–184PubMedPubMedCentralGoogle Scholar
  41. Leemans A, Jones DK (2009) The B-matrix must be rotated when correcting for subject motion in DTI data. Magn Reson Med 61:1336–1349CrossRefPubMedGoogle Scholar
  42. Leite SCB, Corrêa DG, Doring TM, Kubo TTA, Netto TM, Ferracini R et al (2013) Diffusion tensor MRI evaluation of the corona radiata, cingulate gyri, and corpus callosum in HIV patients. Journal of magnetic resonance imaging: JMRI 38:1488–1493CrossRefPubMedGoogle Scholar
  43. Mbugua KK, Holmes MJ, Cotton MF, Ratai EM, Little F, Hess AT, et al. (2016) HIV-associated CD4/8 depletion in infancy is associated with neurometabolic reductions in the basal ganglia at age 5 years despite early antiretroviral therapy. AidsGoogle Scholar
  44. McCutchan FE (2006) Global epidemiology of HIV. J Med Virol 78(Suppl 1):S7–s12CrossRefPubMedGoogle Scholar
  45. Mishra M, Vetrivel S, Siddappa NB, Ranga U, Seth P (2008) Clade-specific differences in neurotoxicity of human immunodeficiency virus-1 B and C Tat of human neurons: significance of dicysteine C30C31 motif. Ann Neurol 63:366–376CrossRefPubMedGoogle Scholar
  46. Mori S, van Zijl PC (2002) Fiber tracking: principles and strategies—a technical review. Biomedicine 15:468–480Google Scholar
  47. Oishi K, Faria AV, van Zijl PC, Mori S (2010) MRI atlas of human white matter.: Academic PressGoogle Scholar
  48. Ortega M, Heaps JM, Joska J, Vaida F, Seedat S, Stein DJ et al (2013) HIV clades B and C are associated with reduced brain volumetrics. Journal of NeuroVirology 19:479–487CrossRefPubMedGoogle Scholar
  49. Osmanov S, Pattou C, Walker N, Schwardlander B, Esparza J, Isolation W-UNH et al (2002) Estimated global distribution and regional spread of HIV-1 genetic subtypes in the year 2000. J Acquir Immune Defic Syndr 29:184–190CrossRefPubMedGoogle Scholar
  50. Ostrosky-Solis F, Ramirez M, Ardila A (2004) Effects of culture and education on neuropsychological testing: a preliminary study with indigenous and nonindigenous population. Appl Neuropsychol 11:188–195CrossRefPubMedGoogle Scholar
  51. Paul R, Cohen R, Navia B, Tashima K (2002) Relationships between cognition and structural neuroimaging findings in adults with human immunodeficiency virus type-1. Neurosci Biobehav Rev 26:353–359CrossRefPubMedGoogle Scholar
  52. Paul RH, Ernst T, Brickman AM, Yiannoutsos CT, Tate DF, Cohen RA et al (2008) Relative sensitivity of magnetic resonance spectroscopy and quantitative magnetic resonance imaging to cognitive function among nondemented individuals infected with HIV. J Int Neuropsychol Soc 14:725–733CrossRefPubMedGoogle Scholar
  53. Paul RH, Joska JA, Woods C, Seedat S, Engelbrecht S, Hoare J et al (2014) Impact of the HIV Tat C30C31S dicysteine substitution on neuropsychological function in patients with clade C disease. Journal of NeuroVirology 20:627–635CrossRefPubMedPubMedCentralGoogle Scholar
  54. Radloff LS (1977) The CES-D scale: a self report depression scale for research in the general population. Applied Psychological Measurements 1:385–401CrossRefGoogle Scholar
  55. Ranga U, Shankarappa R, Siddappa NB, Ramakrishna L, Nagendran R, Mahalingam M et al (2004) Tat protein of human immunodeficiency virus type 1 subtype C strains is a defective chemokine. J Virol 78:2586–2590CrossRefPubMedPubMedCentralGoogle Scholar
  56. Rao VR, Sas AR, Eugenin EA, Siddappa NB, Bimonte-Nelson H, Berman JW et al (2008) HIV-1 clade-specific differences in the induction of neuropathogenesis. J Neurosci 28:10010–10016CrossRefPubMedPubMedCentralGoogle Scholar
  57. Rao VR, Neogi U, Talboom JS, Padilla L, Rahman M, Fritz-French C et al (2013) Clade C HIV-1 isolates circulating in Southern Africa exhibit a greater frequency of dicysteine motif-containing Tat variants than those in Southeast Asia and cause increased neurovirulence. Retrovirology 10:61CrossRefPubMedPubMedCentralGoogle Scholar
  58. Rosselli M, Ardila A (2003) The impact of culture and education on non-verbal neuropsychological measurements: a critical review. Brain Cogn 52:326–333CrossRefPubMedGoogle Scholar
  59. Sacktor N, Nakasujja N, Skolasky RL, Rezapour M, Robertson K, Musisi S et al (2009) HIV subtype D is associated with dementia, compared with subtype A, in immunosuppressed individuals at risk of cognitive impairment in Kampala, Uganda. Clin Infect Dis 49:780–786CrossRefPubMedPubMedCentralGoogle Scholar
  60. Sacktor N, Nakasujja N, Redd AD, Manucci J, Laeyendecker O, Wendel SK et al (2014) HIV subtype is not associated with dementia among individuals with moderate and advanced immunosuppression in Kampala, Uganda. Metab Brain Dis 29:261–268CrossRefPubMedPubMedCentralGoogle Scholar
  61. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E et al (1998) The mini-international neuropsychiatric interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of clinical psychiatry 59(Suppl 20):22PubMedGoogle Scholar
  62. Smith SM (2002) Fast robust automated brain extraction. Hum Brain Mapp 17:143–155CrossRefPubMedGoogle Scholar
  63. Stern RA, Silva SG, Chaisson N, Evans DL (1996) Influence of cognitive reserve on neuropsychological functioning in asymptomatic human immunodeficiency virus-1 infection. Arch Neurol 53:148–153CrossRefPubMedGoogle Scholar
  64. Valcour V, Chalermchai T, Sailasuta N, Marovich M, Lerdlum S, Suttichom D et al (2012) Central nervous system viral invasion and inflammation during acute HIV infection. J Infect Dis 206:275–282CrossRefPubMedPubMedCentralGoogle Scholar
  65. Vasan A, Renjifo B, Hertzmark E, Chaplin B, Msamanga G, Essex M et al (2006) Different rates of disease progression of HIV type 1 infection in Tanzania based on infecting subtype. Clin Infect Dis 42:843–852CrossRefPubMedGoogle Scholar
  66. Yepthomi T, Paul R, Vallabhaneni S, Kumarasamy N, Tate DF, Solomon S et al (2006) Neurocognitive consequences of HIV in southern India: a preliminary study of clade C virus. J Int Neuropsychol Soc 12:424–430CrossRefPubMedGoogle Scholar
  67. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC et al (2006) User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31:1116–1128CrossRefPubMedGoogle Scholar
  68. Zhang SDC, Laidlaw DH (2003) Visualizing diffusion tensor MR images using streamtubes and streamsurfaces. IEEE Trans Vis Comput Graph 9:454–462CrossRefGoogle Scholar
  69. Zhang H, Yushkevich PA, Alexander DC, Gee JC (2006) Deformable registration of diffusion tensor MR images with explicit orientation optimization. Med Image Anal 10:764–785CrossRefPubMedGoogle Scholar
  70. Zhang H, Avants BB, Yushkevich PA, Woo JH, Wang S, McCluskey LF et al (2007) High-dimensional spatial normalization of diffusion tensor images improves the detection of white matter differences: an example study using amyotrophic lateral sclerosis. IEEE Trans Med Imaging 26:1585–1597CrossRefPubMedGoogle Scholar

Copyright information

© Journal of NeuroVirology, Inc. 2016

Authors and Affiliations

  • Robert H. Paul
    • 1
    Email author
  • Sarah Phillips
    • 1
  • Jacqueline Hoare
    • 2
  • David H. Laidlaw
    • 3
  • Ryan Cabeen
    • 3
  • Gayla R. Olbricht
    • 4
  • Yuqing Su
    • 4
  • Dan J. Stein
    • 2
  • Susan Engelbrecht
    • 5
  • Soraya Seedat
    • 6
  • Lauren E. Salminen
    • 7
  • Laurie M. Baker
    • 1
  • Jodi Heaps
    • 1
  • John Joska
    • 2
  1. 1.Missouri Institute of Mental HealthUniversity of MissouriSt. LouisUSA
  2. 2.Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
  3. 3.Department of Computer ScienceBrown UniversityProvidenceUSA
  4. 4.Department of Mathematics and StatisticsMissouri University of Science and TechnologyRollaUSA
  5. 5.Division of Medical VirologyStellenbosch University and National Health Laboratory Services (NHLS)Cape TownSouth Africa
  6. 6.MRC Unit on Anxiety and Stress Disorders, Department of PsychiatryUniversity of StellenboschStellenboschSouth Africa
  7. 7.Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesUSA

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