Central nervous system (CNS) dysfunction is a common characteristic of HIV infection. The underlying neuropathology is largely related to the indirect consequence of disrupted glial function because HIV does not substantially infect neurons. Instead, brain macrophages, microglia, and multinucleated giant cells become infected and instigate a reactive astrocytosis.1 Subsequent brain injury likely ensues from both toxic HIV particles and toxins from activated macrophages and astrocytes resulting in cognitive impairment as evidenced by neuropsychological testing abnormalities. Even in the era of combination antiretroviral therapy (cART), the prevalence of HIV-associated neurocognitive disorders (HAND) remains substantial.2–4 Whether these chronic deficits are due to the same mechanisms as seen in untreated HIV is incompletely understood and may be informed by noninvasive measures of glial function and CNS inflammation, as is possible with proton magnetic resonance spectroscopy (MRS).
Abnormal brain chemical concentrations in the basal ganglia (BG), frontal white matter (FWM), frontal gray matter (FGM) and the posterior cingulate gyrus (PCG) regions have been described in HIV.5–8 Clinical studies demonstrate abnormal axonal and neuronal markers in HIV-infected individuals with cognitive impairment and other neurological symptoms.9–11 Our earlier prospective study of the same cART-naive, chronically HIV-infected, Thai subjects examined in the current work, revealed associations between reservoir levels of HIV DNA in peripheral blood mononuclear cells enriched with those having the CD14+ cell surface marker (monocytes) and MRS abnormalities.12 In this study, we examine MRS abnormalities associated with HIV in cART-naive subjects and those associated with HAND. We also examined changes in MRS that were associated with cART initiation over 12 months in order to assess if MRS abnormalities could be identified in association with continued HAND despite 12 months of continuous cART.
MATERIALS AND METHODS
HIV-infected adults were enrolled at the SEARCH clinic of the Thai Red Cross AIDS Research Center in Bangkok, Thailand (protocol SEARCH 011, www.ClinicalTrials.gov NCT00782808); details are previously described.12 All participants met Thai Ministry Public Health criteria for initiating cART (CD4 count < 350 cells/mm3 or symptomatic disease). We enrolled participants using a stratified scheme for peripheral blood mononuclear cells HIV DNA (>/<1000 copies of HIV DNA/106 cells) and age (>/<35 years), based on a predetermined blinded randomization scheme.13 HIV-uninfected adults were recruited in a separate normative imaging study (SEARCH 009) capturing one-time MRS data on 28 controls. HIV-infected individuals (n = 59) received baseline, 6 months, and 12 months MRS, of whom 51 completed all 3 visits. All provided written consent approved by the institutional review boards at the Chulalongkorn University in Bangkok and the University of California, San Francisco.
HIV-infected participants completed a 60-minute battery of neuropsychological tests that included the WHO-UCLA auditory verbal learning task, color trails 1 and 2, Digit Symbol Modalities Test, block design tasks, Grooved Pegboard for both hands, finger tapping for both hands, Timed Gait, 2 verbal fluency tasks (first names and animals), and the trail making test A.14 We conducted consensus conferences with 2 of the authors (V.V. and R.P.) and a US neurologist to assign HAND diagnoses using 2007 Frascati criteria.15 We calculated a composite neuropsychological testing score (NPZ-global) as the arithmetic mean of age- and education-adjusted z-scores for performance on individual tests using normative data from over 500 Thai controls.16
Brain Proton MRS
All the participants completed axial 3D T1-weighted spoiled gradient echo magnetic resonance imaging (MRI) (TE = 7 ms, TR = 11.2 ms, 1 mm resolution) on the same 1.5T GE MRI scanner (Signa, GEHealthCare, Milwaukee, WI) using the same software throughout the study duration (software version 12.0; GE Healthcare); where TE is the echo time and TR is the repetition time. An 8-channel head coil and standard body coil was used. Eight cubic centimeter voxels were placed in the normal appearing brain regions in the right BG and FWM, midline FGM, and PCG using a double spin echo data acquisition (Probe-p) (TE/TR = 35/1500, number of excitations of 128 for FWM, FGM and PCG and 192 for BG).
Voxels were carefully placed by an experienced technologist (M.P.) by visual inspection of the MRI screen shot of the prescription as closely monitored by our physicist (N.S.). The average voxel placement was consistent throughout the study with approximately 4.0 ± 0.5 mm differences between baseline, 6, and 12-month follow-up. We employed commercially available time domain fitting software (LCModel version 6.2.2, www.s-provencher.com, Ontario, Canada) to quantify brain metabolites.17 An estimate of the variance associated (Cramer-Rao lower bounds) with time domain fitting provided by the software was used to determine reliability of the fitting, and value of less than 15% was used to accept the fitting results for n-acetyl aspartate (NAA), creatine (CR), choline (CHO), and less than 25% is accepted for glutamate (GLU).18 Brain chemical concentrations are reported in mM uncorrected for T1, T2 relaxation times and contribution of gray and white matters in each voxel. In each voxel, we measured total CHO, myo-inositol (MI), GLU, CR, and NAA. The same MRS head phantom measurements were acquired at the end of each examination. The quantitative results of the MRS phantom were consistent and reproducible throughout the 12-month period.
The statistical analysis was conducted by first assessing the descriptive statistics for all MRS measures, at all study time points, by subject's HIV status (HIV-infected vs. uninfected healthy controls). Two-sample t test was used to assess the mean differences of MRS measures between healthy controls and HIV-positive subjects. Paired t test was used to examine the mean differences of MRS measures between baseline and each of the subsequent follow-up visits. The statistical tests were not corrected for multiple comparisons.
A mixed effect model was used to examine how the MRS measures change over time after initiation of treatment. Multivariate analyses of variances were performed by adding age, gender, years of education, and time-varying (CD4, plasma VL) as covariates in the mixed models. Pearson correlation coefficients were used to examine the correlation between MRS and clinical measures. The level of significance was P < 0.05. Data were analyzed using SAS version 9.2 and SPSS version 17.0 (SPSS for Windows, SPSS Inc., Chicago, IL).
The HIV-infected and uninfected participants were similar in sex and age with mean ages of 35 and 34 years, respectively. Among HIV-infected participants, baseline mean CD4 T-lymphocyte count was 233 cells per cubic millimeter and the mean log10 plasma HIV RNA was 4.83 copies per milliliter before cART. After 6 and 12 months of treatment, the mean CD4 T-lymphocyte count increased to 371 and 412 cells per cubic millimeter, respectively, whereas the log10 plasma HIV RNA levels decreased to 1.84 and 1.70, respectively (Table 1). All but 3 cases were undetectable (lower level of detection 50 copies/mL) at 12 months (log10 plasma HIV RNA of 2.22, 2.45, and 2.10 reduced from baseline log10 plasma HIV RNA levels of 5.64, 5.34, and 4.93, respectively). At baseline, 27 of the 59 HIV-infected participants were diagnosed with HAND (46%), including 5 with HIV-associated dementia (HAD), 8 with mild neurocognitive disorder and 14 with asymptomatic neurocognitive impairment. All but one of the 59 HIV-infected participants were started on a nonnucleoside reverse transcriptase inhibitor-based regimen, with the latter starting a protease inhibitor-based regimen. During the first year of treatment, 12 subjects switched to an alternative regimen owing to adverse drug reactions, resistance, pregnancy, or co-enrollment in another study.
Cross-Sectional Baseline Brain Metabolites Before Treatment
We observed group difference between HIV-infected and uninfected participants in the FWM, with HIV-infected participants having a higher MI (P = 0.040) and CHO (P = 0.002) in the BG and PCG (P = 0.022) relative to HIV-uninfected participants. We also noted lower NAA in the PCG (weakly significant with P = 0.051) and higher NAA in the BG (P = 0.047) in the HIV-infected group (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A723).
Effects of cART on Brain Metabolites
Longitudinal brain metabolite changes from pre-cART through 6 months and 12 months after the initiation of cART treatment were measured (Fig. 1). We observed a pattern of reduced inflammatory markers after 6 months of cART in the BG with statistical significance reached for decreased CR (P = 0.001), CHO (P = 0.001), and MI (P = 0.012). After 12 months of treatment, further reduction of CR (P = 0.001), CHO (P = 0.004), and MI (P = 0.026) was observed in the BG compared to baseline. Additionally, CR significantly decreased after 6 months of treatment in the FWM (P = 0.014). There were no significant changes in NAA. Compared with uninfected controls, only CR (P = 0.012) and GLU (P = 0.012) were significantly lower among HIV-infected participants at 12 months. No other metabolite/voxel pairs differed at 12 months compared with controls.
Further analysis using a multivariate mixed effect model revealed changes in brain metabolites between baseline and 6 months after cART treatment (estimated coefficient), including decreased NAA (estimated coefficient = −0.94, P = 0.031) in the FWM and CR in the PCG (estimated coefficient = −0.73, P = 0.026). We noted an increase in MI from the FGM between baseline and 6 months (estimated coefficient = 0.39, P = 0.022) and 12 months (estimated coefficient = 0.40, P = 0.021). We also noted an increase in BG MI at 12 months compared with baseline (estimated coefficient. = 0.99, P = 0.038) (see Table S2, Supplemental Digital Content, http://links.lww.com/QAI/A723).
Effects of Clinical Measures on Brain Metabolites
At baseline, there were direct correlations between plasma HIV RNA and MI in the BG (r = 0.358, P = 0.005) and the FGM (r = 0.282, P = 0.031). There were modest indirect correlations to the FWM NAA (r = −0.261, P = 0.046). The pre-cART CD4 T-lymphocyte count indirectly correlated modestly with MI in the BG (r = −0.322, P = 0.013) and FWM (r = −0.263, P = 0.044). In separate analysis, a diagnosis of HAD at baseline (n = 5) had a strong positive statistically significant correlation with BG CR (r = 0.972, P = 0.006) and CHO (r = 0.889, P = 0.043). Further comparison among HIV-infected participants with normal cognition and those with HAND, revealed increased MI in the FGM (P = 0.014) at baseline. At 12 months, participants who remained cognitively impaired showed increased CHO in the PCG (P = 0.018) and decreased GLU in the FWM (P = 0.027) and BG (P = 0.013) (Table 2).
Correlation between changes in NPZ-global score and changes in brain metabolites revealed that decreased BG CHO from baseline to 12 months was correlated with improvement on the NPZ-global score (r = −0.32, P = 0.023). A decrease in MI also correlated with improved NPZ-global score in the FWM (r = −0.43, P = 0.002) and BG (r = −0.42, P = 0.002) (see Table S3, Supplemental Digital Content, http://links.lww.com/QAI/A723). There were no significant correlations between changes in NPZ-global score and changes in brain metabolites from baseline to 6 months.
Several studies, including our recent studies, have demonstrated persistent and continued neuronal injury in treated HIV patients using proton MRS and MRI.12,19–21 Risk factors associated with neuronal injury and cognitive impairment includes plasma HIV DNA and pre-cART CD4 T-lymphocyte cell counts. There remain large gaps in our understanding of the underlying mechanism that contribute to the persistent injury despite cART.
This study identified brain chemical differences between pre-cART HIV-infected subjects and controls, and between HIV-infected subjects with and without HAND post-cART. The most robust baseline associations were with clinical parameters of plasma HIV RNA and CD4 T-lymphocyte cell counts at baseline. The elevated CHO noted at baseline in HIV-infected compared with uninfected subjects is consistent with expectations, supporting an inflammatory phenotype with untreated chronic HIV. In a preclinical study, elevated CHO/CR was observed in the frontal brain of simian immunodeficiency virus macaques at the time of peak viremia, indicating early neuroinflammatory process.22 In human studies, elevated CHO/CR has been documented in international settings21,23–25 and in the US populations.26–29 However, in similar but smaller studies, Suwanwelaa et al30 observed no statistical difference of CHO/CR in asymptomatic HIV-infected participants, whereas Winston et al31 observed lower CHO/CR in HIV-infected participants before cART treatment compared with healthy volunteers. One possible reason for this discrepancy, is the assumption that CR is stable in HIV, an assumption that is not supported by our current and past data.
A pattern of improved CHO was observed across multiple voxels, and seemed to occur as early as 6 months, demonstrating more rapid recovery, which is consistent with findings from a recently reported multicenter study that identified normalization of CHO over 2 years.32 At 12 months, we noted no evidence of continued elevation of CHO, with levels that were similar to controls across all voxels.
Creatine, a combination of creatine and phosphocreatine measured with proton MRS, is a metabolite associated with cell energy metabolism. It is widely considered to be unchanged in numerous brain pathologies and is often used as an internal reference with metabolites, which are reported as a ratio to the presumed stable CR.33,34 We observed a decrease in CR in multiple brain regions over time in these participants who initiated cART. Chang et al35 reported a similar finding in the frontal cortex of HIV-infected participants. The level of CR in the brain is in equilibrium with phosphocreatine via the creatine kinase enzymes activity.36 Our patients were treated with nonnucleoside reverse transcriptase inhibitors that has been linked to reduced creatine kinase activity, raising concerns that they impact MRS CR; thus, it should not be considered to remain stable in this scenario.37,38 Alternatively, it has been hypothesized that changes in total CR levels are associated with intense neuronal activity and failure of energy production.39 High energy demands of infected monocytes during the early stage of HIV infection could persist in chronic HIV infection.40
Myo-inositol is present mainly in glial cells and considered to be an important brain osmolyte.41 It is only observable at a short echo time MRS, as used in our study. Elevated MI has been reported at various stages of HIV infection.10,42 In this study, elevated MI in the FWM and slightly elevated MI in the BG at baseline reflected microglial activation during the early stage of HIV infection and tend to normalize after 12 months of treatment. This normalization suggests reduced inflammation and improved brain repair mechanisms after cART.
Unsettled issues remain around cognitive impairment in cART treated subjects, with increasing evidence of contributions from non–HIV-related comorbidity and HIV. In this study, we demonstrated improved neuropsychological testing performance with cART, and associations between HAND and MRS parameters. This provides further evidence of inflammatory pathogenesis to HAND. Among those who continued to have impairment at 12 months, we continued to see elevated CHO at PCG, providing evidence that, at least among a subset of subjects, inflammation is incompletely resolved with cART.
Glutamatergic neurotransmission has been associated with the pathophysiology of cognitive dysfunction in several brain conditions including HAND.43–46 Glutaminase is the enzyme that catalyzes the conversion of glutamine (GLN) to GLU, and its activity has been shown to inhibit GLU production in HIV.47 Reduced GLU may reflect mitochondria damage,38,48 enhanced synthesis of anti-oxidant49,50 or glial injury.47,51 In the longitudinal component of our study, we observed lower GLU in FWM and BG among impaired, compared with unimpaired subjects at 12 months. It is important to point out that several studies exist documenting the difficulty in sorting out GLU signal without contamination of the overlapped GLN signal at 1.5T scanner field strength.8,52,53 Using short echo time proton MRS, the unresolved GLU and GLN resonances are readily reported as GLX, a combination of GLU and GLN. Previous studies reported decreased GLX in FWM in cognitively impaired HIV-infected subjects,54 whereas increased GLX was observed in the BG in HIV participants who were on stable cART.55 There are several factors that contribute to this discrepancy, which may include the scanner field strength (1.5T vs. 3T). Mohamed et al argued that changes in GLX might be due to dysfunction in the glutamate-glutamine cycle; therefore it is uncertain that increased GLX is a direct result of increased GLU or both GLU and GLN. Using a more rigorous MRS approach to measure the uncontaminated GLU signal at 3T scanner field strength, reduced GLU was also observed in the FWM of cognitively normal HIV-infected participants.8
In this study, the standard deviation for the GLU metabolite quantification using the LCModel analysis was >20% (range 9%–24%) in 8% of our results at 12 months. Therefore, we adopted criteria to include results in the final analysis of <25%, which is higher than generally accepted (<20%).18 This practice is not unusual and has been used in several MRS studies.56–58 We also noted that, by not having follow-up examinations in the uninfected participants, we might have missed some inherent variability in our measurement. However, there were no significant changes observed in MRS phantom measurements acquired at the end of each examination.
In summary, we identified evidence of CNS inflammation in HIV before cART and among those who fail to improve cognitively at 12 months. MRS inflammatory markers are linked to important clinical measures pre-cART including plasma HIV RNA, and neuropsychological testing improvement is associated with improvement in these MRS markers.
The authors thank our study participants and the SEARCH 011 study group particularly the following members from Thailand: Pradit Chaisit, Yothin Chinvarun, Phayao Thongkramjaroen, Sumit Thongmuang, Sirichai Jarupittaya, Prapian Khongtia, Pornpen Methajittiphun, Pravit Mingkwanrungruang, Nittaya Phanuphak, Eugene Kroon, Nipat Terratakulpisarn, Nitiya Chomchey, Duanghathai Suttichom, Somprartthana Rattanamanee, Michittra Boonchan, Ratchapong Kanaprach and from UCSF: Elijah Mun, Nicholas Hutchings, Katherine Clifford, and Lauren Wendelken. The authors also thank Isabel Allen and Jiahong Xu for statistical assistance.
1. Gonzalez-Scarano F, Martin-Garcia J. The neuropathogenesis of AIDS. Nat Rev Immunol. 2005;5:69–81.
2. Garvey L, Winston A, Walsh J, et al.. HIV
-associated central nervous system diseases in the recent combination antiretroviral therapy era. Eur J Neurol. 2011;18:527–534.
3. Tozzi V, Balestra P, Bellagamba R, et al.. Persistence of neuropsychologic deficits despite long-term highly active antiretroviral therapy in patients with HIV
-related neurocognitive impairment: prevalence and risk factors. J Acquir Immune Defic Syndr. 2007;45:174–182.
4. Heaton RK, Clifford DB, Franklin DR Jr, et al.. HIV
-associated neurocognitive disorders persist in the era of potent antiretroviral therapy: CHARTER Study. Neurology. 2010;75:2087–2096.
5. Barker PB, Lee RR, McArthur JC. AIDS dementia complex: evaluation with proton MR spectroscopic imaging. Radiology. 1995;195:58–64.
6. Chang L, Lee PL, Yiannoutsos CT, et al.. A multicenter in vivo proton-MRS study of HIV
-associated dementia and its relationship to age. Neuroimage. 2004;23:1336–1347.
7. Lentz MR, Kim WK, Kim H, et al.. Alterations in brain metabolism during the first year of HIV
infection. J Neurovirol. 2011;17:220–229.
8. Sailasuta N, Shriner K, Ross B. Evidence of reduced glutamate in the frontal lobe of HIV
-seropositive patients. NMR Biomed. 2009;22:326–331.
9. Menon DK, Baudouin CJ, Tomlinson D, et al.. Proton MR spectroscopy and imaging of the brain in AIDS: evidence of neuronal loss in regions that appear normal with imaging. J Comput Assist Tomogr. 1990;14:882–885.
10. Laubenberger J, Haussinger D, Bayer S, et al.. HIV
-related metabolic abnormalities in the brain: depiction with proton MR spectroscopy with short echo times. Radiology. 1996;199:805–810.
11. Tracey I, Carr CA, Guimaraes AR, et al.. Brain choline-containing compounds are elevated in HIV
-positive patients before the onset of AIDS dementia complex: a proton magnetic resonance spectroscopic study. Neurology. 1996;46:783–788.
12. Valcour VG, Ananworanich J, Agsalda M, et al.. HIV
DNA reservoir increases risk for cognitive disorders
in cART-naive patients. PLoS One. 2013;8:e70164.
13. Sungkanuparph S, Techasathit W, Utaipiboon C, et al.. Thai national guidelines for antiretroviral therapy in HIV
-1 infected adults and adolescents 2010. Asian Biomed. 2010;4:515–528.
14. Valcour VG, Sithinamsuwan P, Nidhinandana S, et al.. Neuropsychological abnormalities in patients with dementia in CRF 01_AE HIV
-1 infection. Neurology. 2007;68:525–527.
15. Antinori A, Arendt G, Becker JT, et al.. Updated research nosology for HIV
-associated neurocognitive disorders. Neurology. 2007;69:1789–1799.
16. Heaps J, Valcour V, Chalermchai T, et al.. Development of normative neuropsychological performance in Thailand for the assessment of HIV
-associated neurocognitive disorders. J Clin Exp Neuropsychol. 2013;35:1–8.
17. Provencher SW. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR Biomed. 2001;14:260–264.
18. Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med. 1993;30:672–679.
19. Sailasuta N, Ross W, Ananworanich J, et al.. Change in brain magnetic resonance spectroscopy
after treatment during acute HIV
infection. PLoS One. 2012;7:e49272.
20. Cohen RA, Harezlak J, Gongvatana A, et al.. Cerebral metabolite abnormalities in human immunodeficiency virus are associated with cortical and subcortical volumes. J Neurovirol. 2010;16:435–444.
21. Cysique LA, Moffat K, Moore DM, et al.. HIV
, vascular and aging injuries in the brain of clinically stable HIV
-infected adults: a (1)H MRS study. PLoS One. 2013;8:e61738.
22. Fuller RA, Westmoreland SV, Ratai E, et al.. A prospective longitudinal in vivo 1H MR spectroscopy study of the SIV/macaque model of neuroAIDS. BMC Neurosci. 2004;5:10.
23. Salvan AM, Vion-Dury J, Confort-Gouny S, et al.. Brain proton magnetic resonance spectroscopy
-related encephalopathy: identification of evolving metabolic patterns in relation to dementia and therapy. AIDS Res Hum Retroviruses. 1997;13:1055–1066.
24. Paley M, Cozzone PJ, Alonso J, et al.. A multicenter proton magnetic resonance spectroscopy
study of neurological complications of AIDS. AIDS Res Hum Retroviruses. 1996;12:213–222.
25. Bladowska J, Zimny A, Koltowska A, et al.. Evaluation of metabolic changes within the normal appearing gray and white matters in neurologically asymptomatic HIV
-1-positive and HCV-positive patients: magnetic resonance spectroscopy
and immunologic correlation. Eur J Radiol. 2013;82:686–692.
26. Chang L, Ernst T, Witt MD, et al.. Relationships among brain metabolites, cognitive function, and viral loads in antiretroviral-naive HIV
patients. Neuroimage. 2002;17:1638–1648.
27. Harezlak J, Buchthal S, Taylor M, et al.. Persistence of HIV
-associated cognitive impairment, inflammation, and neuronal injury in era of highly active antiretroviral treatment. AIDS. 2011;25:625–633.
28. Meyerhoff DJ, Bloomer C, Cardenas V, et al.. Elevated subcortical choline metabolites in cognitively and clinically asymptomatic HIV
+ patients. Neurology. 1999;52:995–1003.
29. Young AC, Yiannoutsos CT, Hegde M, et al.. Cerebral metabolite changes prior to and after antiretroviral therapy in primary HIV
infection. Neurology. 2014;83:1592–1600.
30. Suwanwelaa N, Phanuphak P, Phanthumchinda K, et al.. Magnetic resonance spectroscopy
of the brain in neurologically asymptomatic HIV
-infected patients. Magn Reson Imaging. 2000;18:859–865.
31. Winston A, Duncombe C, Li PC, et al.. Two patterns of cerebral metabolite abnormalities are detected on proton magnetic resonance spectroscopy
-infected subjects commencing antiretroviral therapy. Neuroradiology. 2012;54:1331–1339.
32. Gongvatana A, Harezlak J, Buchthal S, et al.. Progressive cerebral injury in the setting of chronic HIV
infection and antiretroviral therapy. J Neurovirol. 2013;19:209–218.
33. Danielson E, Ross B. Magnetic Resonance Spectroscopy
Diagnosis of Neurological Diseases. New York, NY: Marcel Dekker; 1999.
34. Lin A, Ross BD, Harris K, et al.. Efficacy of proton magnetic resonance spectroscopy
in neurological diagnosis and neurotherapeutic decision making. NeuroRx. 2005;2:197–214.
35. Chang L, Ernst T, Speck O, et al.. Additive effects of HIV
and chronic methamphetamine use on brain metabolite abnormalities. Am J Psychiatry. 2005;162:361–369.
36. Berg J, Tymoczko J, Stryer L. Biochemistry. 6th ed. New York, NY: WH Freeman & Company; 2007.
37. Streck EL, Scaini G, Rezin GT, et al.. Effects of the HIV
treatment drugs nevirapine and efavirenz on brain creatine kinase activity. Metab Brain Dis. 2008;23:485–492.
38. Schweinsburg BC, Taylor MJ, Alhassoon OM, et al.. Brain mitochondrial injury in human immunodeficiency virus-seropositive (HIV
+) individuals taking nucleoside reverse transcriptase inhibitors. J Neurovirol. 2005;11:356–364.
39. Ratai EM, Annamalai L, Burdo T, et al.. Brain creatine elevation and n-acetylaspartate reduction indicates neuronal dysfunction in the setting of enhanced glial energy metabolism in a macaque model of neuroAIDS. Magn Reson Med. 2011;66:625–634.
40. Williams KC, Hickey WF. Central nervous system damage, monocytes and macrophages, and neurological disorders in AIDS. Annu Rev Neurosci. 2002;25:537–562.
41. Brand A, Richter-Landsberg C, Leibfritz D. Multinuclear NMR studies on the energy metabolism of glial and neuronal cells. Dev Neurosci. 1993;15:289–298.
42. Lopez-Villegas D, Lenkinski RE, Frank I. Biochemical changes in the frontal lobe of HIV
-infected individuals detected by magnetic resonance spectroscopy
. Proc Natl Acad Sci U S A. 1997;94:9854–9859.
43. Lyoo IK, Yoon SJ, Musen G, et al.. Altered prefrontal glutamate-glutamine-gamma-aminobutyric acid levels and relation to low cognitive performance and depressive symptoms in type 1 diabetes mellitus. Arch Gen Psychiatry. 2009;66:878–887.
44. Moghaddam B, Adams B, Verma A, et al.. Activation of glutamatergic neurotransmission by ketamine: a novel step in the pathway from NMDA receptor blockade to dopaminergic and cognitive disruptions associated with the prefrontal cortex. J Neurosci. 1997;17:2921–2927.
45. Lewis DA, Moghaddam B. Cognitive dysfunction in schizophrenia: convergence of gamma-aminobutyric acid and glutamate alterations. Arch Neurol. 2006;63:1372–1376.
46. Potter MC, Figuera-Losada M, Rojas C, et al.. Targeting the glutamatergic system for the treatment of HIV
-associated neurocognitive disorders. J Neuroimmune Pharmacol. 2013;8:594–607.
47. Erdmann N, Zhao J, Lopez AL, et al.. Glutamate production by HIV
-1 infected human macrophage is blocked by the inhibition of glutaminase. J Neurochem. 2007;102:539–549.
48. Valcour V, Shiramizu B. HIV
-associated dementia, mitochondrial dysfunction, and oxidative stress. Mitochondrion. 2004;4:119–129.
49. Mialocq P, Oiry J, Puy JY, et al.. Oxidative metabolism of HIV
-infected macrophages: the role of glutathione and a pharmacologic approach [in French]. Pathol Biol (Paris). 2001;49:567–571.
50. Rimaniol AC, Mialocq P, Clayette P, et al.. Role of glutamate transporters in the regulation of glutathione levels in human macrophages. Am J Physiol Cell Physiol. 2001;281:C1964–C1970.
51. Ernst T, Chang L, Arnold S. Increased glial metabolites predict increased working memory network activation in HIV
brain injury. Neuroimage. 2003;19:1686–1693.
52. Hurd R, Sailasuta N, Srinivasan R, et al.. Measurement of brain glutamate using TE-averaged PRESS at 3T. Magn Reson Med. 2004;51:435–440.
53. Hancu I, Zimmerman EA, Sailasuta N, et al.. 1H MR spectroscopy using TE averaged PRESS: a more sensitive technique to detect neurodegeneration associated with Alzheimer's disease. Magn Reson Med. 2005;53:777–782.
54. Mohamed MA, Lentz MR, Lee V, et al.. Factor analysis of proton MR spectroscopic imaging data in HIV
infection: metabolite-derived factors help identify infection and dementia. Radiology. 2010;254:577–586.
55. Hua X, Boyle CP, Harezlak J, et al.. Disrupted cerebral metabolite levels and lower nadir CD4 + counts are linked to brain volume deficits in 210 HIV
-infected patients on stable treatment. Neuroimage Clin. 2013;3:132–142.
56. Kim H, Catana C, Ratai EM, et al.. Serial magnetic resonance spectroscopy
reveals a direct metabolic effect of cediranib in glioblastoma. Cancer Res. 2011;71:3745–3752.
57. Lin Y, Stephenson MC, Xin L, et al.. Investigating the metabolic changes due to visual stimulation using functional proton magnetic resonance spectroscopy
at 7 T. J Cereb Blood Flow Metab. 2012;32:1484–1495.
58. Dydak U, Jiang YM, Long LL, et al.. In vivo measurement of brain GABA concentrations by magnetic resonance spectroscopy
in smelters occupationally exposed to manganese. Environ Health Perspect. 2011;119:219–224.