HIV subtype determination in the env region was possible for 54 (52%), with total subtype defined for 70 (68%) children (Table 1). Taken together, children with any subtype determination did not differ from those in whom subtype was indeterminate, demographically or by weight adjusted for age z-scores (WAZ) (based on Epi Info CDC 2000 norms). No children had signs of symptoms of central nervous system (CNS) infection on the day of testing or within 3 months before or after the testing date. No child had been diagnosed with pulmonary tuberculosis with 120 days of testing and only one child had been diagnosed with malaria within 60 days of testing. Subtype A and D infected children had comparable WHO staging  (Table 2). Although a medical history of malnutrition for the child was not directly measured in the SES or HOME surveys, the SES provided a measure of the most locally important influence on nutritional status, financial resources and our clinical data on weight/height ratios provide one measure of the physical consequences of malnutrition. For either of these variables, there was no significant difference between groups infected with subtype A HIV and those infected with subtype D (by either definition).
There were no differences in CD4 cell count or percentage, comparing by env A, to D/indeterminate or A, to D/recombinant/indeterminate when using total subtype. However, children with subtype A had higher viral load levels than those with indeterminate or D when defining subtype by env (Table 1). When using total subtype, those with A had significantly higher viral loads that those with indeterminate subtype and higher (but not reaching statistical significance) compared with those with subtype D.
Mean and standard deviation raw score performance totals were compared for children infected with each of the subtypes with subtype being a composite of two or more gene regions (Table 3). Subtype A-infected children (n = 37) performed more poorly than those with subtype D infection (n = 24) on KABC-2 Simultaneous Processing (visual–spatial analysis and problem solving) and Learning using raw score totals adjusted for age, sex, weight-for-age z-score, and HOME quality in an ANCOVA analysis. On KABC-2 performance, the recombinant (5 A/D, 2 A/C, 1 C/D) children (n = 9) resembled the subtype A children in level of performance. When log viral load was included as a covariate in the ANCOVA comparison between subtypes A and D, KABC-2 differences did not remain significant.
Of the viral genes assessed for subtype determination, env harbors the most direct determinants of co-receptor usage (CXCR4 versus CCR5) and cellular/tissue tropism . Because this could influence the efficiency of viral replication in the CNS, we used subtype determination from this particular gene region as the basis for comparing neuropsychological performance of children with infection by subtypes A (n = 37) and D (n = 16). For the unadjusted t score comparison between subtypes A and D in Table 4, we used performance measures standardized by age using a non-HIV control group at Mulago Hospital (n = 104). For the adjusted t score, ANCOVA means and standard errors were computed from global raw scores using age, sex, weight-for-age z-score, HOME total score, and viral load as covariates.
On the KABC-2 measures standardized by age, subtype A-infected children performed significantly more poorly than those with subtype D. There were significant differences on KABC-2 Sequential Processing (P = 0.01), Simultaneous Processing (P = 0.005), and Learning (P = 0.02) (Table 4). The subtype A group also performed more poorly on the TOVA D prime signal detection measure of attention (P = 0.04). After adjusting for viral load along with the other covariates, K-ABC-2 Sequential (P = 0.05) and Simultaneous Processing (P = 0.007) remained significant. Simultaneous Processing was the only ANCOVA cognitive performance that remained statistically significant after adjusting for the number of comparisons for the KABC-2 performance measures.
The only evaluative basis for diagnosing behavioral or learning disability for our study children is to use our present neuropsychological and cognitive assessments. As normative data do not exist for Ugandan children for our tests, we can define impairment for a study child as any score that is 2 or more SDs below the mean for the non-HIV-infected control children for that age. Using this criterion, seven of the subtype A children (19%) based on tot were impaired on at least one of the global neurocognitive domains listed in Table 3, compared with four subtype D children (17%) and one subtype C child (100%). The proportion of children with at least one domain of impairment did not differ significantly between subtypes A and D.
The impact of the viral genetic complexity that characterizes the HIV epidemic in sub-Saharan Africa on the disease course of individual patients is not well understood. In the current work, we found evidence that HIV-subtype influences neurocognitive disability in HIV-infected Ugandan children. Whether we used a combination of gene regions (tot) or just the env region to determine subtype, children with subtype A did more poorly on cognitive ability and visual attention than those with subtype D. The differences were especially pronounced on KABC-2 Simultaneous Processing (visual-spatial analysis and problem solving). It should also be noted that Simultaneous Processing was the K-ABC performance domain where ART-naive HIV-positive children have shown the most significant deficits compared with HIV-negative children, both in DR Congo  and Uganda . Simultaneous Processing remained significantly lower for the subtype A children after adjusting for the higher viral load apparent for subtype A children as determined by the env region.
In contrast to our findings, Sacktor et al. concluded that Ugandan adults with subtype D infection had a greater level of neurocognitive deficits than those with subtype A infection. This stark difference in subtype association may partly be due to the fact that the adults in that study were at a more advanced disease stage and qualified for initiation of ART. Subtype D is associated with greater immunovirulence in east African adults and the immunocompromise associated with this aspect of subtype D disease may have contributed to the higher prevalence of HAND among Ugandan adults (although CD4 cell counts were not different between groups). Our children were ART-naive because they were at an earlier stage of disease with lesser degrees of laboratory and clinically defined immunodeficiency.
In preliminary study, we have not observed a higher mortality in children infected with subtype D in our cohort. It should also be noted that in the study by Sacktor et al., infection with subtype D was shown to be associated with an increased risk of HIV dementia when subtype was defined by the gp41 envelope gene. In the study by Sacktor et al., the same statistical association of subtype D and HIV dementia was not evident in the gag gene. These results suggest that determinants within the env region may be more critical for conferring an increased risk of HIV dementia compared with the gag gene in HIV-infected individuals with subtype D. In fact, use of the env gene for our subtype determination resulted in more robust neuropsychological differences favoring subtype D children in our study. Sacktor et al. also suggest that neuropsychological differences among subtypes D and A may depend on differences in coreceptor usage and syncytium inducibility mediating differences in neurovirulence.
Immunologically asymptomatic HIV disease is thought to be associated with more encephalopathy in children than in adults . Coupled with the impact of the virus on developing neural networks in children during sensitive periods of development , the neurocognitive effects of HIV subtype may fundamentally differ in children from that in adults. Subtype A HIV may be more directly encephalopathogenic than HIV subtype D in children, whereas in adults, infection with subtype D HIV could result in a greater degree of neuropsychological impairment related to heightened immunopathology associated with HIV subtype D infection.
There are several well defined virologic differences between HIV subtypes A and D. Subtype D strains have an increased number of positively charged amino acid substitutions in the envelope region . Studies suggest an increased prevalence of CXCR4 tropism in subtype D isolates. In one such study of Ugandan adults who had not yet developed AIDS, a surprisingly high percentage [44% (12/27)] of those with subtype D harbored CXCR4 tropic virus, compared with only 17% (4/23) with subtype A . There is a need to determine CXCR4 tropism of isolates from children in the cohort and determine whether subtype D is associated with an increased prevalence of CXCR4 tropism.
Higher degrees of CCR5 tropism associated with subtype A isolates of treatment-naive individuals could confer an advantage in infecting macrophages, the principal cells of transport of the virus through the blood–brain barrier into the CNS  and microglia, the other major target cell for HIV in the CNS. This could result in CCR5 tropic strains being more ‘encephalopathogenic’, particularly during sensitive periods of brain development in early childhood. In contrast, CXCR4 tropic strains may be more immunopathogenic over the long term, because they infect a wider range of target cells in lymphoid tissue but, at the same time, may replicate less efficiently in the CNS.
However, the relationship between HIV subtype and neuropathogenesis is likely to be more complex than this simple association and involve other factors. Although HIV subtype D may be predisposed to CXCR4 tropism, subtype A strains can also acquire this phenotype in advanced disease. What is more, many potential target cell types express both CCR5 and CXCR4 coreceptors . In HIV subtype C infection, the viral regulatory gene product Tat has been implicated as another variable affecting the development of HAND [27,28].
In a murine model, HIV-1 Tat mediates differences in monocyte recruitment between subtype C-infected and subtype B-infected macrophages resulting in attenuation of astrogliosis and relative preservation of neuronal network integrity during infection with subtype C . In this same study, HIV subtype B was associated with greater memory impairment. In vitro, subtype C Tat induces apoptosis in primary human neurons to a lesser degree than subtype B Tat. The determinants of this difference in subtype C neurotoxicity were mapped to the dicysteine motif in the 5′ first exon of Tat . Such comparisons between subtype A and D tat should be done.
Additional studies of the neuropsychological associations of HIV subtypes in younger infants and children in Uganda are warranted. There is also a need to further validate subtype associations with independent markers of neuroinflammation (e.g., monocyte chemotactic protein-1 or MCP-1) and the neurocognitive deficits associated with subtype A infection in Ugandan children. In addition, given recent reports of a high prevalence of neurocognitive impairment in western adult populations  and pediatric populations despite HAART , there is a need to determine how HAART differentially affects neurocognitive responses in children with subtype A and D.
In contrast to adults, children with HIV subtype A demonstrated poorer neurocognitive performance than those with subtype D in this cross-sectional study. Some of this effect may be the result of higher viral loads, but likely also reflects subtype-specific and age-specific differences in the neuropathogenesis of HIV. These findings support the need to monitor the long-term developmental effects of HIV infection of different subtypes in children through longitudinal follow-up to define a neurodevelopmental trajectory.
Although the current data are not sufficient to alter clinical practice, they strongly point to a need for such additional study. If future studies confirm that HIV subtype A is more neuropathogenic for children in the long-term, such findings could have more direct clinical implications. For example, they might suggest that HIV subtype should be considered in deciding the timing of ART initiation and that the encephalopathic risk of a given subtype should be considered in selecting antiretroviral drugs with varying CNS penetration characteristics . At a time when universal treatment remains highly controversial [34,35], it is important to develop more precise tools to stratify the risk of HIV-infected children for both immunological and nonimmunological harm from deferred treatment.
We thank Dr Francine McCutchan of the Bill & Melinda Gates Foundation developed the multiregion hybridization assay (MHA) used for subtype determination in our study; Dr Pim Brouwers of the NIMH for encouragement and support at the inception of the study; Dr Michael Eller of the Makerere University – Walter Reed Project supervised the clinical and immunological analyses. Ivan Muwanguzi, Clare Ahabwe, Joseylee Kasule, and Paul Oloya completed neuropsychological and home assessments of our study children and we are grateful for their excellent efforts.
We acknowledge funding support from the National Institutes of Health: R21 MH083573 (J.K.W., M.J.B., T.D.R.); NIH/NCRR/OD UCSF-CTSI Grant Number TL1 RR024129 and the Doris Duke Charitable Foundation (H.E.B.); Michigan State University Department of Neurology faculty start-up funding (M.J.B.); and support from R01 NS051132, U01 AI052142, U01 AI062677, and P30 AI027763. The funding agencies had no role in the analysis, interpretation, or communication of our study findings.
M.J.B. designed the assessment portion of the study, completed the analyses, and wrote the paper.
T.D.R. helped organize the subtype and clinical laboratory tests and data management of these assessments and contributed to the writing of the paper.
H.E.B. helped supervise study recruitment, consent, neuropsychological assessment, data management, and contributed to the writing of the paper.
P.B. supervised study consent, neuropsychological assessment, data management, data analysis, formulation of tables, and contributed to the writing of the paper.
H.C. directed immunophenotyping assays for T cell activation and laboratory interpretation.
L.A.E. assisted in the immunological and clinical assays for T-cell activation and laboratory interpretation.
E.C. helped with patient selection and recruitment, provided statistical and data management support and contributed to the writing of the paper.
D.H. assisted in patient selection and recruitment and clinical coordination and contributed to the conceptualization of the study.
M.K. contributed to study design, patient selection and recruitment, and clinical coordination and contributed to the writing of the paper.
J.A. contributed to patient selection and recruitment and clinical coordination.
C.A. contributed to patient selection and recruitment and clinical coordination.
J.K.W. developed the overall design of the study, helped organize and interpret the subtype and clinical laboratory tests, contributed to the interpretation of the study findings, helped write the manuscript, and was principal investigator on the NIMH R21 grant that provided the principal support for this work.
1. McCutchan FE. Map: HIV-1 global distribution
. PBS; 2006.
2. Ball SC, Abraha A, Collins KR, Marozsan AJ, Baird H, Quinones-Mateu ME, et al
. Comparing the ex vivo fitness of CCR5-tropic human immunodeficiency virus type 1 isolates of subtypes B and C. J Virol 2003; 77:1021–1038.
3. Senkaali D, Muwonge R, Morgan D, Yirrell D, Whitworth J, Kaleebu P. The relationship between HIV type 1 disease progression and V3 serotype in a rural Ugandan cohort. AIDS Res Hum Retroviruses 2004; 20:932–937.
4. Kaleebu P, French N, Mahe C, Yirrell D, Watera C, Lyagoba F, et al
. 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. J Infect Dis 2002; 185:1244–1250.
5. Robertson K, Kopnisky K, Hakim J, Merry C, Nakasujja N, Hall C, et al
. Second assessment of NeuroAIDS in Africa. J Neurovirol 2008; 14:87–101.
6. Sacktor N, Nakasujja N, Skolasky RL, Rezapour M, Robertson K, Musisi S, et al
. 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 2009; 49:780–786.
7. Gray L, Roche M, Churchill MJ, Sterjovski J, Ellett A, Poumbourios P, et al
. Tissue-specific sequence alterations in the human immunodeficiency virus type 1 envelope favoring CCR5 usage contribute to persistence of dual-tropic virus in the brain. J Virol 2009; 83:5430–5441.
8. Kamya MR, Gasasira AF, Achan J, Mebrahtu T, Ruel T, Kekitiinwa A, et al
. Effects of trimethoprim-sulfamethoxazole and insecticide-treated bednets on malaria among HIV-infected Ugandan children. AIDS 2007; 21:2059–2066.
9. Boivin M, Bangirana P, Byarugaba J, Opoka O, Idro R, John CC. Cognitive sequelae of cerebral malaria in children: a prospective study
10. Boivin MJ, Green SD, Davies AG, Giordani B, Mokili JK, Cutting WA. A preliminary evaluation of the cognitive and motor effects of pediatric HIV infection in Zairian children. Health Psychol 1995; 14:13–21.
11. Bagenda D, Nassali A, Kalyesubula I, Sherman B, Drotar D, Boivin MJ, Olness K. Health, neurologic, and cognitive status of HIV-infected, long-surviving, and antiretroviral-naive Ugandan children. Pediatrics 2006; 117:729–740.
12. Bangirana P, Musisi S, Allebeck P, Giordani B, John CC, Opoka OR, et al
. A preliminary examination of the construct validity of the KABC-II in Ugandan children with a history of cerebral malaria. Afr Health Sci 2009; 9:188–192.
13. Belman AL, Diamond G, Dickson D, Horoupian D, Llena J, Lantos G, Rubinstein A. Pediatric acquired immunodeficiency syndrome. Neurologic syndromes. Am J Dis Child 1988; 142:29–35.
14. Diamond GW, Kaufman J, Belman AL, Cohen L, Cohen HJ, Rubinstein A. Characterization of cognitive functioning in a subgroup of children with congenital HIV infection. Arch Clin Neuropsychol 1987; 2:245–256.
15. John CC, Bangirana P, Byarugaba J, Opoka RO, Idro R, Jurek AM, et al
. Cerebral malaria in children is associated with long-term cognitive impairment. Pediatrics 2008; 122:e92–e99.
16. Van Rie A, Mupuala A, Dow A. Impact of the HIV/AIDS epidemic on the neurodevelopment of preschool-aged children in Kinshasa, Democratic Republic of the Congo. Pediatrics 2008; 122:e123–e128.
17. Caldwell BM, Bradley RH. Home observation for measurement of the environment. Little Rock, Arkansas: University of Arkansas Press; 1979.
18. Hoelscher M, Dowling WE, Sanders-Buell E, Carr JK, Harris ME, Thomschke A, et al
. Detection of HIV-1 subtypes, recombinants, and dual infections in east Africa by a multiregion hybridization assay. AIDS 2002; 16:2055–2064.
19. Arroyo MA, Hoelscher M, Sateren W, Samky E, Maboko L, Hoffmann O, et al
. HIV-1 diversity and prevalence differ between urban and rural areas in the Mbeya region of Tanzania. AIDS 2005; 19:1517–1524.
20. Barry SM, Johnson MA, Janossy G. Increased proportions of activated and proliferating memory CD8+ T lymphocytes in both blood and lung are associated with blood HIV viral load. J Acquir Immune Defic Syndr 2003; 34:351–357.
21. Duncombe CJ, Crowley S. Antiretroviral therapy for children with HIV infection in resource-limited settings. Part 1: Initiating and changing therapy
. HIV/AIDS Antriretroviral Newsletter
. Geneva: World Health Organization; July 2005.
22. Bisiacchi PS, Suppiej A, Laverda A. Neuropsychological evaluation of neurologically asymptomatic HIV-infected children. Brain Cogn 2000; 43:49–52.
23. Okamoto S-I, Kang Y-J, Brechtel CW, Siviglia E, Russo R, Clemente A, et al
. HIV/gp120 decreases adult neural progenitor cell proliferation via checkpoint kinase-mediated cell-cycle withdrawal and G1 arrest. Cell Stem Cell 2007; 1:230–236.
24. De Wolf F, Hogervorst E, Goudsmit J, Fenyo EM, Rubsamen-Waigmann H, Holmes H, et al
. Syncytium-inducing and nonsyncytium-inducing capacity of human immunodeficiency virus type 1 subtypes other than B: phenotypic and genotypic characteristics. WHO Network for HIV Isolation and Characterization. AIDS Res Hum Retroviruses 1994; 10:1387–1400.
25. Kaleebu P, Nankya IL, Yirrell DL, Shafer LA, Kyosiimire-Lugemwa J, Lule DB, et al
. Relation between chemokine receptor use, disease stage, and HIV-1 subtypes A and D: results from a rural Ugandan cohort. J Acquir Immune Defic Syndr 2007; 45:28–33.
26. Huang W, Eshleman SH, Toma J, Fransen S, Stawiski E, Paxinos EE, et al
. Coreceptor tropism in human immunodeficiency virus type 1 subtype D: high prevalence of CXCR4 tropism and heterogeneous composition of viral populations. J Virol 2007; 81:7885–7893.
27. Li W, Li G, Steiner J, Nath A. Role of Tat protein in HIV neuropathogenesis. Neurotox Res 2009; 16:205–220.
28. Ranga U, Shankarappa R, Siddappa NB, Ramakrishna L, Nagendran R, Mahalingam M, et al
. Tat protein of human immunodeficiency virus type 1 subtype C strains is a defective chemokine. J Virol 2004; 78:2586–2590.
29. Rao VR, Sas AR, Eugenin EA, Siddappa NB, Bimonte-Nelson H, Berman JW, et al
. HIV-1 clade-specific differences in the induction of neuropathogenesis. J Neurosci 2008; 28:10010–10016.
30. Mishra M, Vetrivel S, Siddappa NB, Ranga U, Seth P. Clade-specific differences in neurotoxicity of human immunodeficiency virus-1 B and C Tat of human neurons: significance of dicysteine C30C31 motif. Ann Neurol 2008; 63:366–376.
31. Cysique LA, Vaida F, Letendre S, Gibson S, Cherner M, Woods SP, et al
. Dynamics of cognitive change in impaired HIV-positive patients initiating antiretroviral therapy. Neurology 2009; 73:342–348.
32. Jeremy RJ, Kim S, Nozyce M, Nachman S, McIntosh K, Pelton SI, et al
. Neuropsychological functioning and viral load in stable antiretroviral therapy-experienced HIV-infected children. Pediatrics 2005; 115:380–387.
33. Letendre S, Marquie-Beck J, Capparelli E, Best B, Clifford D, Collier AC, et al
. Validation of the CNS penetration-effectiveness rank for quantifying antiretroviral penetration into the central nervous system. Arch Neurol 2008; 65:65–70.
34. Granich RM, Gilks CF, Dye C, De Cock KM, Williams BG. Universal voluntary HIV testing with immediate antiretroviral therapy as a strategy for elimination of HIV transmission: a mathematical model. Lancet 2009; 373:48–57.
35. Smith RJ, Okano JT, Kahn JS, Bodine EN, Blower S. Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco. Science 2010; 327:697–701.
Keywords:© 2010 Lippincott Williams & Wilkins, Inc.
attention; CD activation; children; cognitive ability; encephalopathy; HIV clades; home environment; memory; motor; viral load