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. 2015 Mar;10(1):111-21.
doi: 10.1007/s11481-014-9581-x. Epub 2015 Jan 10.

Independent and co-morbid HIV infection and Meth use disorders on oxidative stress markers in the cerebrospinal fluid and depressive symptoms

Affiliations

Independent and co-morbid HIV infection and Meth use disorders on oxidative stress markers in the cerebrospinal fluid and depressive symptoms

Jun Panee et al. J Neuroimmune Pharmacol. 2015 Mar.

Abstract

Both HIV infection and Methamphetamine (Meth) use disorders are associated with greater depressive symptoms and oxidative stress; whether the two conditions would show additive or interactive effects on the severity of depressive symptoms, and whether this is related to the level of oxidative stress in the CNS is unknown. 123 participants were evaluated, which included 41 HIV-seronegative subjects without substance use disorders (Control), 25 with recent (<6 months) moderate to severe Meth use disorders (Meth), 34 HIV-seropositive subjects without substance use disorders (HIV) and 23 HIV+Meth subjects. Depressive symptoms were assessed with the Center for Epidemiologic Studies-Depression Scale (CES-D), and oxidative stress markers were evaluated with glutathione (GSH), 4-hydroxynonenal (HNE), and activities of gamma-glutamyltransferase (GGT) and glutathione peroxidase (GPx) in the cerebrospinal fluid (CSF). Compared with Controls, HIV subjects had higher levels of HNE (+350%) and GGT (+27%), and lower level of GSH (-34%), while Meth users had higher levels of GPx activity (+23%) and GSH (+30 %). GGT correlated with GPx, and with age, across all subjects (p < 0.0001). CES-D scores correlated with CSF HNE levels only in Control and HIV groups, but not in Meth and HIV+Meth groups. HIV and Meth use had an interactive effects on depressive symptoms, but did not show additive or interactive effects on oxidative stress. The differential relationship between depressive symptoms and oxidative stress response amongst the four groups suggest that depressive symptoms in these groups are mediated through different mechanisms which are not always related to oxidative stress.

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Conflict of interest statement

Conflict of Interest The authors declare that there are no conflicts of interest.

Figures

Fig. 1
Fig. 1
Glutathione metabolism pathway in the cytoplasm and in extracelluar space. Black arrows, glutathione catabolism; green arrows, antioxidant function of glutathione; red arrows, glutathione de novo synthesis. * Rate-limiting components. Abbreviation: Cys cysteine; DPEP dipeptidase; EAAC1 excitatory amino acid carrier 1; EAAT excitatory amino acid transporters; GCS glutamylcysteine synthetase; GGT glutamyl transferase; Glu glutamate; Gly glycine; GPx glutathione peroxidase; GS glutathione synthetase; GSH glutathione; GSSG oxidized glutathione; HNE 4-hydroxynonenal; HNE-GSH 4-hydroxynonenal-glutathione adduct; MRP multidrug resistance proteins
Fig. 2
Fig. 2
CES-D score, HNE concentration in the CSF, and their correlations with each other and with Karnofsky scale and Meth use. a Square root-transformed CES-D score of subjects in the Control (n=41), HIV (n=34), Meth (n=25) and HIV+ Meth (n=23) groups. b Log transformed HNE concentration in the CSF of the 4 groups. c Correlations between CES-D and HNE in Meth- (i.e. Control and HIV) and Meth+ (i.e., Meth and HIV+Meth) subjects. d Correlation of CES-D vs. Karnofsky scale in HIV-positive subjects (i.e. HIV and HIV+Meth). e Correlation of CES-D vs. duration of Meth use in recent Meth users (i.e., Meth and HIV+Meth). f Correlation of Log HIV dementia scale vs. Log HNE. The p values were calculated from Pearson correlations. In panels a and b, the p values were calculated from two-way ANCOVA. **p<0.01; ***p<0.0001, Bonferroni post hoc test. In panels cf, the p-values were calculated from Pearson or Spearman correlations
Fig. 3
Fig. 3
GSH concentration and GPx activity in the CSF and their correlations with HNE and Meth use. a Log transformed GSH concentration in the CSF of subjects in the Control (n=41), HIV (n=34), Meth (n=25) and HIV+Meth (n=23) groups. b Different correlations between GSH and HNE in HIV+ (i.e., HIV and HIV+Meth) and HIV- (i.e., Control and Meth) subjects. c–e Correlations between GSH and total Meth use, daily meth use, and duration of Meth abstinence in recent Meth users (i.e., Meth and HIV+Meth). f GPx activity in the CSF of the 4 groups. g Different correlations between GPx and HNE in the HIV+ (i.e., HIV and HIV+Meth) and HIV- (i.e., Control and Meth) subjects. In panels a and f, the p value was calculated from two-way ANCOVA. *p<0.05, **p<0.01, Bonferroni post hoc test. In the other panels, the p values were calculated from Pearson correlations
Fig. 4
Fig. 4
GGT activity in the CSF and its correlations with GSH, GPx, and age. a GPx activity in the CSF of subjects in the Control (n=41), HIV (n=34), Meth (n=25) and HIV+Meth (n=23) groups. b Correlations between GGT and GSH. c Correlations between GGT and GPx. d Correlations between GGT and age. In panel a, the p value was calculated from two-way ANCOVA. ***p<0.001, Bonferroni multiple comparison test. In panels bd, the p values were calculated from Pearson correlations. n.s. non-significant

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