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HIV-subtype A is associated with poorer neuropsychological performance compared with subtype D in antiretroviral therapy-naive Ugandan children

Boivin, Michael Ja; Ruel, Theodore Db; Boal, Hannah Ec; Bangirana, Pauld; Cao, Huyene; Eller, Leigh Af; Charlebois, Edwing; Havlir, Diane Vh; Kamya, Moses Ri; Achan, Janej; Akello, Carolynei; Wong, Joseph Kk

doi: 10.1097/QAD.0b013e3283389dcc
Clinical Science

Background: HIV-subtype D is associated with more rapid disease progression and higher rates of dementia in Ugandan adults compared with HIV-subtype A. There are no data comparing neuropsychological function by HIV subtype in Ugandan children.

Design: One hundred and two HIV-infected antiretroviral therapy (ART) naive Ugandan children 6–12 years old (mean 8.9) completed the Kaufman Assessment Battery for Children, second edition (KABC-2), the Test of Variables of Attention (TOVA), and the Bruininks–Oseretsky Test for Motor Proficiency, second edition (BOT-2). Using a PCR-based multiregion assay with probe hybridization in five different regions (gag, pol, vpu, env, gp-41), HIV subtype was defined by hybridization in env and by total using two or more regions. Analysis of covariance was used for multivariate comparison.

Results: The env subtype was determined in 54 (37 A, 16 D, 1 C) children. Subtype A and D groups were comparable by demographics, CD4 status, and WHO stage. Subtype A infections had higher log viral loads (median 5.0 vs. 4.6, P = 0.02). Children with A performed more poorly than those with D on all measures, especially on KABC-2 Sequential Processing (memory) (P = 0.01), Simultaneous Processing (visual–spatial analysis) (P = 0.005), Learning (P = 0.02), and TOVA visual attention (P = 0.04). When adjusted for viral load, Sequential and Simultaneous Processing remained significantly different. Results were similar comparing by total HIV subtype.

Conclusion: HIV subtype A children demonstrated poorer neurocognitive performance than those with HIV subtype D. Subtype-specific neurocognitive deficits may reflect age-related differences in the neuropathogenesis of HIV. This may have important implications for when to initiate ART and the selection of drugs with greater central nervous system penetration.

aInternational Neurologic and Psychiatric Epidemiology Program Michigan State University, East Lansing, Michigan, USA

bDivision of Infectious Disease, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA

cDepartment of Pediatrics, University of Washington Seattle Children's Hospital, Seattle, Washington, USA

dDepartment of Psychiatry, Makerere University School of Medicine, Kampala, Uganda

eCalifornia Department of Public Health, Viral and Rickettsial Disease Laboratory, Richmond, California, USA

fMakerere University–Walter Reed Program, Kampala, Uganda

gDepartment of Medicine, University of California, San Francisco, USA

hPositive Health Program, Department of Medicine, University of California, San Francisco, San Francisco General Hospital, San Francisco, California, USA

iDepartment of Medicine, Makerere University School of Medicine, Uganda

jDepartment of Paediatrics and Child Health, Makerere University School of Medicine, Kampala, Uganda

kSection of Infectious Diseases, Department of Medicine, University of California, San Francisco, San Francisco, California, USA.

Received 29 November, 2009

Revised 8 February, 2010

Accepted 10 February, 2010

Correspondence to Michael J. Boivin, PhD, 324 West Fee Hall, East Lansing, MI 48824-1315, USA. Tel: +1 517 884 0281; fax: +1 517 884 0275; e-mail:

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HIV-subtype B is the predominant HIV subtype in the United States, Latin America, Europe, and Australia. In East Africa, subtypes A, C, and D are predominant, whereas C is predominant in India and much of Asia [1]. Subtype-specific differences in coreceptor tropism and viral fitness may underlie the differential impact on HIV disease progression [2]. Studies of HIV-infected adults in East Africa have suggested that subtype D is associated with more rapid CD4 decline, greater rise in viral load, and more rapid progression to AIDS or death [3,4]. Differences in neurovirulence among HIV subtypes have also been postulated because of markedly different prevalence rates of HIV-associated neurocognitive disorders (HANDs) in various parts of the world [5]. However, disease prevalence between geographically distinct regions may also be explained by differences in host genetics and available healthcare resources.

Sacktor et al. [6] examined the relationship between HIV subtype and the severity of HIV-associated cognitive impairment among HIV-infected adults initiating antiretroviral therapy in a single clinic in Uganda. Using subtype assignments that were generated by sequence analysis of the gag and gp41 regions, eight of nine (89%) HIV-infected adults with subtype D had dementia, compared with seven of 33 (24%) HIV-infected adults with subtype A (P = 0.004). They concluded that HIV dementia may be more common among adults with subtype D than in those with subtype A, providing the first evidence that HIV subtypes may differ in terms of neurocognitive pathogenesis. However, there has been no study investigating potential differences in the impact of HIV by subtype in children and in the context of ongoing neurocognitive development. In Uganda, where HIV subtypes A and D are in co-circulation, there is a unique opportunity to investigate the neuropsychological impact of these different subtypes in children.

The purpose of the present study is to compare the neurocognitive impact between HIV subtypes A and D in a cohort of HIV-infected antiretroviral therapy (ART) naive Ugandan children. Because env is the region of the virus important to co-receptor usage and cellular/tissue tropism [7], we hypothesized that children with HIV subtype D in the envelope region will exhibit greater impairment of neurocognitive function.

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One hundred and two ART-naive children 6–12 years old (64 girls, 38 boys; mean 8.9 years) were enrolled from an ongoing prospective cohort of HIV-infected Ugandan children based in Kampala, Uganda [8]. Neuropsychological assessments were conducted in a private room in a wing of the patient ward that afforded quietness and privacy. Assessments were conducted in the local language of the children (Luganda) by native speakers. Assessors were unaware of the HIV subtype or clinical status of the children.

Clinical and socioeconomic data were obtained from the cohort study database. Socioeconomic status and quality of home environment was assessed upon enrollment. All children received comprehensive care, including CD4 measures, HIV RNA levels, and complete blood counts every 12 weeks. Children had access to medical care 7 days a week and all symptoms are evaluated using standardized protocols and diagnostic codes. ART was initiated per Uganda country guidelines. Children selected for this analysis were ART-naive at the time of neurocognitive testing.

Informed written consent was obtained from the child's parent and assent from older children (age >7 years). IRB approval for this study was obtained from Makerere University, University of California, San Francisco, and Michigan State University.

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Kaufman Assessment Battery for Children (second edition)

The Kaufman Assessment Battery for Children, second edition (KABC-2) has been used by Boivin with Ugandan pediatric cerebral malaria survivors [9], HIV-positive Congolese (Zairian) children[10], and Ugandan school-age HIV survivors [11]. The KABC-2 maintains its factor structure with Ugandan cerebral malaria survivors [12]. The K-ABC has been used as well with HIV-infected American children [13,14]. The primary outcome variables were the global scores of Sequential Processing (memory), Simultaneous Processing (visual–spatial processing and problem solving), Learning (immediate and delayed memory), and Planning (executive reasoning). We did not administer the Knowledge (crystallized intelligence) portion of this test because of problems in cultural suitability.

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Test of Variables of Attention

Both the auditory and visual versions of the Test of Variables of Attention (TOVA) were administered. The TOVA is a visual continuous performance test used in the diagnosis and monitoring of children and adults with attention deficit disorders. In our prior use of this computerized assessment, the TOVA provided the most sensitive measures of the persisting neurocognitive effects of cerebral malaria in Ugandan children [15]. Following instructions and practice trials, the Auditory and Visual TOVA each take about 22 min to administer. We began our neurocognitive assessment sessions with the TOVA so that vision and hearing deficits for any of our study children would immediately become evident, allowing us to exclude the child from further study participation. In the present analysis, we used TOVA D prime signal-detection measure (signal-detection sensitivity) for overall attention performance.

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Bruininks–Oseretsky Test for Motor Proficiency (second edition)

This is regarded as one of the most comprehensive and sensitive instruments for motor assessment. Testing involves game-like tasks that hold the child's interest and are not verbally complex. Composite scores include fine manual control, manual coordination, body coordination, strength and agility and total composite score. Its use in this study is particularly relevant because of the pronounced motor impairment that seems to accompany HIV-related neurocognitive delay compared with impairment from severe malaria [10,16].

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Home Observation for the Measurement of the Environment

The middle childhood version of the Caldwell Home Observation for the Measurement of the Environment (HOME) [17] was used to assess the stimulation and learning opportunities offered by the child's home environment. It is important to control for this measure when evaluating the impact of HIV subtype on neurodevelopmental and psychosocial outcomes. This is especially true when assessing such outcomes in African children developmentally at risk for a number of factors related to poverty. Along with the HOME, we also used a socioeconomic evaluation scale of physical quality of the home environment [socioeconomic status (SES) score] previously used with Ugandan children.

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Subtype assignment

HIV subtype was determined by application of the multiregion hybridization assay from plasma HIV RNA (MHA) [18]. The MHA is particularly useful for identifying recombinant forms, as five different targets dispersed across the HIV genome are simultaneously assessed [19]. This protocol generates five short amplicons in gag, pol, vpu, env (gp120), and gp41 by PCR using pan-subtype primers. Each amplicon is then distributed to separate second-round Taqman (Applied Biosystems, Foster City, California, USA) kinetic PCR reactions, employing subtype-specific Taqman probes. The assay was originally developed for use with DNA from peripheral blood mononuclear cells, but it has also been used with RT-PCR amplifying RNA in plasma [18]. The second generation of this assay has 90% sensitivity and 98% specificity when compared with the ‘gold standard’ of full genome sequencing [19]. Because of variability in performance, this assay does not generate a subtype in every region for every strain. Therefore, subtype was defined for this analysis in two ways: env defined by hybridization in the envelope region and total using the subtype assignment determined in two or more gene regions (may or may not include env); if subtypes differed by region within a stain, it was considered recombinant.

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CD4+ T-cell counts, immune activation, and viral load testing

CD4 measures were available within a median (mean, range) of 28 (32, 0–212) days from the time of neuropsychological assessment. HIV viral load data were available within a median (mean, range) 30 (54, 0–245) days. CD4 T-cell and CD8 T-cell activation level testing was performed on EDTA anticoagulated whole blood using a fresh lyse-no wash flow cytometry procedure. Blood was incubated with monoclonal antibodies including CD3, CD8, CD4, CD38, and HLA DR, then processed and acquired on a multilaser bench top flow cytometer. For each run of patient samples, a separate sample of stabilized blood product (CD-Chex; Streck Laboratories, Omaha, Nebraska, USA) was processed. CD4 T-cell and CD8 T-cell activation levels were defined as percentage of CD38 and HLA-DR co-expression [20].

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Statistical analyses

Children were grouped by env and total subtype (A, C, D, recombinant) and compared on all demographic and clinical measures using the Student's t-test for two independent samples from SPSS Base program v17.0 (Table 1). Because the testing modules can vary as a result of cultural specific factors, z-scores were generated using age-adjusted norms from a cohort of 122 non-HIV children from a separate study in the greater Kampala area. Subtype A and D children were then compared on all global performance measures for the KABC-2, TOVA, and BOT-2 (Table 2), again first by env subtype and then by total subtype. Age, sex, weight-for-age z-scores (CDC2000, Epi Info), HOME total score, and viral load were used as covariates for analysis of covariance (ANCOVA) comparisons between A and D on our principal neurocognitive outcomes.

Table 1

Table 1

Table 2

Table 2

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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 [21] (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.

Table 3

Table 3

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 [7]. 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.

Table 4

Table 4

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.

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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 [10] and Uganda [11]. 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 [22]. Coupled with the impact of the virus on developing neural networks in children during sensitive periods of development [23], 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 [24]. 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 [25]. 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 [7] 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 [26]. 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 [29]. 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 [30]. 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 [31] and pediatric populations despite HAART [32], there is a need to determine how HAART differentially affects neurocognitive responses in children with subtype A and D.

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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 [33]. 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.

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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.

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attention; CD activation; children; cognitive ability; encephalopathy; HIV clades; home environment; memory; motor; viral load

© 2010 Lippincott Williams & Wilkins, Inc.