Amyloid beta-42 (Aβ-42), neprilysin and cytokine levels. A pilot study in patients with HIV related cognitive impairments

Journal of Neuroimmunology 282 (2015) 73–79

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Amyloid beta-42 (Aβ-42), neprilysin and cytokine levels. A pilot study in patients with HIV related cognitive impairments K.M. Mothapo a,⁎, F. Stelma b, M. Janssen c, R. Kessels c, S. Miners f, M.M. Verbeek d,e, P. Koopmans a, A. van der Ven a a

Department of Internal Medicine and Nijmegen Institute for Infection, Inflammation and Immunity, Radboud University Medical Center, The Netherlands Department of Virology, Radboud University Nijmegen Medical Center, The Netherlands Department of Medical Psychology, Radboud University Nijmegen Medical Center, The Netherlands d Department of Neurology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands e Department of Laboratory Medicine, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands f Dementia Research Group, University of Bristol, Institute of Clinical Neurosciences, Level 1, Learning and Research, Southmead Hospital, Bristol, UK b c

a r t i c l e

i n f o

Article history: Received 2 February 2015 Received in revised form 18 March 2015 Accepted 20 March 2015 Keywords: Amyloid beta-42 Neprilysin Pro-inflammatory cytokines Anti-inflammatory cytokines HIV associated neurocognitive disorders HIV related cognitive impairments

a b s t r a c t HIV-associated dementia (HAD) is associated with amyloid-beta (Aβ) deposition. This study measured CSF and plasma amyloid beta-42 (Aβ-42), neprilysin (NEP) and cytokine levels in HIV-related cognitive impairments (HCI), HIV normal cognitive functioning (NF) and non-HIV controls. Our data showed a trend towards detectable plasma Aβ-42 levels more frequently in HCI (67%), when compared to NF (29%) and controls (10%). We showed elevated IL-8 levels in CSF of HCI compared to NF, although not significant values. The data from this pilot study indicates that CSF IL-8 and plasma Aβ-42 may be interesting biomarkers for the presence of HCI. © 2015 Published by Elsevier B.V.

1. Introduction HIV-associated dementia (HAD) is rarely seen in patients treated with combination antiretroviral therapy (cART) (Mirza and Rathore, 2012), but more mildly neurocognitive disorders have been observed in 15–50% of patients that are successfully treated with cART (Cysique et al., 2004; Schouten et al., 2011; Simioni et al., 2010). Specific neuropsychometric performance tests can be used to identify and monitor patients with more subtle HIV-associated neurocognitive disorders (HAND) (Clifford and Ances, 2013; Overton et al., 2011); however, these tests acquire specific trained personnel and are labor intensive. Many scientists have therefore been searching for easy accessible biomarkers for HAND, but no reliable markers have yet been found (Price et al., 2013). Amyloid-β (Aβ) protein isoforms are candidates as biomarkers for HAND. Aβ deposition has been found in brain tissues of HIV infected patients (Achim et al., 2009; Andras and Toborek, 2013; Esiri et al., 1998; Mirza and Rathore, 2012; Rempel and Pulliam, 2005; Soontornniyomkij et al., 2012) and in those with Alzheimer's disease ⁎ Corresponding author at: Department of Internal Medicine, Radboud University Medical Center, PO Box 9101, 6500 HB Nijmegen, The Netherlands. E-mail address: [email protected] (K.M. Mothapo).

http://dx.doi.org/10.1016/j.jneuroim.2015.03.017 0165-5728/© 2015 Published by Elsevier B.V.

(AD) (van Duinen et al., 1987; Yamada et al., 1988). There are two major soluble Aβ protein isoforms, Aβ-42 and Aβ-40 (Iversen et al., 1995; Iwatsubo et al., 1994), with Aβ-42 being the most neurotoxic compared to Aβ-40 (Klein et al., 1999). Reduced cerebrospinal fluid (CSF) Aβ-42 levels have been found in patients with HAND/AIDS dementia and AD (Brew et al., 2005; Clifford et al., 2009; Hampel et al., 2004), which may be explained by an increased deposition of Aβ-42 (Fagan et al., 2006) or increased ingestion by activated microglial cells (Spies et al., 2012). Plasma Aβ-42 levels were found to be elevated in AD patients with mild cognitive impairment (Cammarata et al., 2009); however, plasma Aβ-42 did not differentiate between AD patients and their age matched controls in other studies (Koyama et al., 2012; Sedaghat et al., 2009). In the normal brain, Aβ is rapidly degraded by a zinc metalloendopeptidase, referred to as neprilysin (NEP) (Farris et al., 2003; Wang et al., 2006). In AD transgenic Mice it was shown that recombinant soluble neprilysin reduces Aβ accumulation and improves memory impairment in AD transgenic mice (Marr et al., 2003). NEP is inhibited by HIV tat protein, a HIV replicative factor which may explain the accumulation of Aβ in the brains of certain HIV infected patients (Rempel and Pulliam, 2005). Recently it has been demonstrated that HIV tat protein is driving T cell activation and inflammation, also in the central nervous system (Johnson et al., 2013). In AD animal models, pro-

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inflammatory cytokines, especially IL-6 and TNF-alpha were shown to play a key role in neuroinflammation that has a relevance to neurodegeneration (Lin et al., 2014; Tweedie et al., 2012), while different mice studies showed that blocking inflammation attenuates Aβ deposition in the brain (DaSilva et al., 2006; Kiyota et al., 2010). The general consensus is that elevated CSF pro-inflammatory cytokines (Kamat et al., 2012; Yuan et al., 2013) promote cognitive deficits and antiinflammatory cytokines do not show such distinction (Airoldi et al., 2012; Nolting et al., 2009). Different mechanisms may therefore contribute to the development of HAND and/or HAD whereby either HIV tat can down-regulate NEP, influence cerebral cytokine levels and predispose to brain amyloid deposition. Therefore we hypothesize that decreased NEP activity will result in increased inflammation and Aβ deposition and decreased CSF Aβ-42 levels in HIV-related cognitive impairments (HCI) patients. The present study aimed to investigate the role of Aβ-42, NEP, proand anti-inflammatory cytokines as biomarkers for HCI in CSF and plasma. 2. Materials and methods

substrate, Mca-RPPGFSAFK(Dnp)-OH (20 μM) (R&D systems, Minneapolis, MN, USA) in the presence of thiorphan (2 μM) (Sigma Aldrich, Dorset, UK) adapted from the immunocapture-based assay published by Miners et al. (Miners et al., 2008). Concentrations of IL-6, IL-8, IL-10, IL-18, IFN-γ, IL-17 and IL-22 were quantified by Multiplex Fluorescent Bead Immunoassays (Milliplex MAP kit, Millipore, Billerica, MA, USA) according to the manufacturer's instructions. Bio-plex microbead analyzer (Luminex, TX, USA) was used to read the plate according to the manufacturer's protocol. All CSF and plasma samples were analyzed in one batch. 2.3.3. Statistical analysis Data analysis was performed using the SPSS statistical package (SPSS 20, Inc. Chicago, Illinois, USA). Spearman's correlation was used to determine correlation coefficient between Aβ-42 levels, NEP activity and cytokine levels. Aβ-42 levels, NEP activity and cytokine levels were compared between HCI and NF, HCI and control, NF and control groups pairwise by Mann–Whitney U-test. Proportions were compared using Chi-square statistics. All data are expressed as medians.

2.1. Study population

3. Results

This study included 32 patients, among which 22 HIV seropositive patients (19 were on cART) and 10 HIV seronegative controls. HIV positive patients were included if a neuropsychological assessment was available and paired CSF and plasma sample could be retrieved. The 22 HIV positive patients underwent an extensive neuropsychological assessment and then were grouped into 15 patients with significant neurocognitive disorders according to the Frascati criteria (Antinori et al., 2007) and 7 patients with normal neurocognitive functioning. Paired CSF and plasma samples were retrieved from all 32 individuals. The 10 HIV negative controls consisted of samples from patients suspected for neuroborreliosis, all of them tested negative. No intrathecal inflammation as defined by the absence of pleiocytosis or abnormal Q albumin or both was observed in 9 control patients, while 1 control patient had a leukocyte count of 12 cells/mm3. All patients were recruited from the HIV outpatient clinic at the Radboud University Medical Center (Radboudumc, Nijmegen, The Netherlands). The study protocol was reviewed and approved by the Medical Ethical Committee of the Radboud University Nijmegen Medical Center.

3.1. Baseline characteristics (Table 1)

2.2. Neuropsychological evaluation A trained neuropsychologist, using validated tasks, performed the neuropsychological evaluation. The assessment covered the following domains; abstract reasoning, working memory, episodic memory, psychomotor speed, visuoconstruction, executive functioning, attention and information processing speed (Janssen et al., 2013). A continuous score was obtained for all 8 domains in HCI and Normal cognitive functioning (NF) groups. HIV patients were defined into two categories 1) HCI and 2) NF, by Frascati criteria (Antinori et al., 2007). 2.3. Laboratory methods 2.3.1. HIV viral load measurement HIV viral loads in both CSF and plasma compartments were measured by COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, version 2.0, following the manufacturer's instructions (Roche Molecular Systems Inc., USA), with the lower detection limit of 20 copies/ml. 2.3.2. Amyloid beta-42 and neprilysin and cytokines quantification Aβ-42 concentration in CSF and plasma were quantified by High Sensitivity Human Amyloid beta-42 ELISA (Millipore, Billerica, MA, USA) according to the manufacturer's instructions. NEP activity in CSF and plasma samples was measured using the fluorogenic peptide

Almost all HIV patients (16/18) and all controls showed normal Qalbumin (~brain–barrier-function) ratio of no higher than 8.9 indicating normal blood–brain barrier function. Two patients in the HCI group showed high Q-albumin ratios and for four patients no Q-albumin data were available. HIV viral loads were measured in 22 HIV positive patients in both CSF and plasma. Nine patients had detectable viral loads in CSF, 6 of the 9 had viral loads N200 copies/ml. Five of the 9 patients had higher viral load in CSF than in plasma. Nineteen of 22 HIV positive patients were on cART, 2 of 3 patients not on cART were in the HCI group. The median age did not differ between the groups, 44, 49 and 45 years in the HCI, NF and control groups respectively. 3.2. Amyloid beta-42 levels and NEP activity in patients with different cognitive functioning The CSF levels of Aβ-42 and NEP did not show significant difference between HCI, NF and control groups. Plasma Aβ-42 levels were detectable in 67% (10/15) of HCI patients, but in only 29% (2/7) and 10% (1/10) of NF and control groups respectively (Fig. 1). Plasma Aβ-42 concentrations were significantly different between HCI and controls (25 pg/ml and 16 pg/ml respectively, p = 0,01). There was no difference in plasma Aβ-42 concentrations between HCI and NF (p = 0.28). Positivity rates of plasma Aβ-42 were equal between HCI and NF groups (67% versus 29%, p = 0.17), NF and control groups (29% versus 10%, p = 0.53), but showed a significant difference between HCI and controls (67% versus 10%, p = 0.005). Median plasma NEP activity was elevated in HIV positive patients as compared to HIV negative controls (120 ng/ml versus 88 ng/ml; p = 0.036). 3.3. Cytokine production in patients with different cognitive functioning Most cytokine concentrations in plasma did not differ significantly between HCI and NF groups (Fig. 2a to g). However, plasma IL-10 and IL-22 levels were slightly elevated in HCI patients. Several cytokines (IL-10, IL-17, IL-18, IL-22, IFN-γ) were not detectable or rarely measured (IL-6) in CSF. Remarkably IL-8 showed higher concentrations in CSF when compared to the plasma concentrations (Fig. 2b). Patients with HCI appeared to have higher IL-8 levels in CSF compared to patients with NF (37 pg/ml and 22 pg/ml respectively, p = 0.057) and controls (37 pg/ml and 24 pg/ml respectively, p = 0.11) (Fig. 2b).

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Table 1 Clinical characteristics for the study population. No

Cognitive function

Age (Years)

HIV viral load CSF (copies/ml)

HIV viral load plasma (copies/ml)

HAART

Q-albumin ratio

CD4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI HCI NF NF NF NF NF NF NF Control Control Control Control Control Control Control Control Control Control

43 56 59 50 57 51 41 42 60 62 28 46 44 45 56 54 51 30 42 51 43 37 60 28 55 55 50 22 50 58 27 51

800* Undetectable Undetectable 70* Undetectable 90 Undetectable Undetectable 200* Undetectable Undetectable 1000 Undetectable Undetectable 1000* 200 Undetectable Undetectable 2000 Undetectable 80* Undetectable – – – – – – – – – –

Undetectable Undetectable Undetectable Undetectable Undetectable 5000 Undetectable Undetectable Undetectable 300 Undetectable 90000 Undetectable Undetectable 200 10000 Undetectable 30 70000 Undetectable 30 Undetectable – – – – – – – – – –

ABC/3TC/IND/RIT TFV/3TC/NEV AZT/3TC/NEV/IND TFV/FTC/RIT/ATZ ABC/AZT/3TC TFV/FTC/EFV TFV/FTC/RIT/ATZ TFV/FTC/EFV TFV/FTC/RIT/ATZ ABC/3TC/RAL TFV/FTC/EFV No HAART TFV/FTC/RAL TFV/FTC/RIT/DAR TFV/RAL/RIT/DAR No HAART TFV/RAL/RIT/DAR AZT/3TC/RIT/LOP ABC/AZT/3TC TFV/FTC/NEV No HAART TFV/FTC/EFV Not applicable Not applicable Not applicable Not applicable Not applicable Not applicable Not applicable Not applicable Not applicable Not applicable

No data 6.0 No data 8.8 9.3 4.3 5.0 5.2 5.0 6.4 2.9 8.2 9.5 6.5 4.8 5.9 No data No data 6.1 5.0 5.0 5.4 4.4 4.0 7.0 6.8 4.4 4.5 7.2 8.8 5.3 6.8

150 1000 720 230 320 530 800 510 550 170 300 390 210 620 650 1340 1060 220 670 360 300 410

HCI (=patients with HIV-related cognitive impairments), NF (=HIV patients with normal cognitive function) and controls (=patients without HIV and cognitive disturbances). HAART = highly active antiretroviral therapy; ABC = abacavir; ATZ = zidovudine; AZT = azidothymidine; D4T = stavudine; DAR = darunavir; EFV = efavirenz; IND = indinavir; RIT = ritonavir; 3TC = lamivudine; LPV = lopinavir; TFV = tenofovir; NEV = nevirapine; FTC = emtricitabine; RAL = raltegravir; LOP = lopinavir.

correlation with Aβ-42 or NEP. CSF IL-8 and CSF HIV load also did not show any correlation (r = 0.21, p = 0.36).

3.4. Correlation between Aβ-42 and NEP and cytokines and HIV load CSF Aβ-42 levels showed a positive correlation with CSF NEP activity in all studied groups (r = 0.46, p = 0.01), (Fig. 3). Plasma and CSF NEP activity showed a positive correlation (r = 0.49, p = 0.004), while no correlation was observed between plasma and CSF Aβ-42 levels (r = − 0.07, p = 0.72). CSF and plasma cytokines did not show any

4. Discussion Our preliminary findings show that plasma Aβ-42 was detectable in 67% of HCI patients compared to 29% in NF and 10% in control groups

a) CSF and plasma Amyloid beta-42

b) CSF and plasma Neprilysin

p=0.97 p=0.74

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Fig. 1. CSF and plasma Aβ-42 concentration and neprilysin activity in HCI (=patients with HIV-related cognitive impairments), NF (=HIV patients with normal cognitive function) and controls (=patients without HIV and cognitive disturbances). The horizontal lines represent the median values. Mann–Whitney U-test was used to compare between two sets of data.

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a) IL-6 CSF and plasma

b) IL-8 CSF and plasma

p=0.004 p=0.28

p=0.008

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150

p=0.03

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c) IL-10 CSF and plasma 44 42 40 38 36

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Fig. 2. CSF and plasma cytokine concentrations in HCI (=patients with HIV-related cognitive impairments), NF (=HIV patients with normal cognitive function) and controls (=patients without HIV and cognitive disturbances). The horizontal lines represent the median values. Mann–Whitney U-test was used to compare between two sets of data.

K.M. Mothapo et al. / Journal of Neuroimmunology 282 (2015) 73–79

a) CSF NEP and A

b) Plasma NEP and A

-42 correlations

-42 correlations

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Plasma NEP activity (ng/ml)

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Fig. 3. Correlation between CSF (a) or plasma (b) Aβ-42 and neprilysin (NEP) in the combined study groups (HCI, NF and controls). Spearman's correlation was used for the analysis.

and therefore might be used as an indicator of HAND. CSF Aβ-42 levels and NEP activity were not different between HCI, NF patients and controls, and do not appear to be useful markers for HAND according to our study. Finally, a trend for elevated CSF IL-8 levels was observed in HIV-infected patients with cognitive impairments compared to HIVinfected patients with normal functioning. The small sample size of our study has hampered statistical analysis and we could only show sound differences in plasma Aβ-42 levels between HCI and controls. Different cells in the body produce Aβ. However, in spite of what could be expected our data did not show a correlation between Aβ-42 levels in plasma and CSF. It is important to note that blood–brain barrier was intact in most of our studied patients, indicating that the Aβ-42 levels observed in plasma and CSF are locally produced. Higher plasma Aβ-42 levels have been observed in non-HIV infected persons with mild amnestic cognitive impairment, compared to healthy controls (Cammarata et al., 2009) and was therefore regarded an early marker Alzheimer's dementia. We found undetectable plasma Aβ-42 levels in NF and control groups and therefore concluded that Aβ-42 levels in plasma also can be used as an early marker for HAND. No previous studies reported plasma Aβ-42 levels in HCI or HAND, in contrast to CSF Aβ-42 levels. Peluso et al. (Peluso et al., 2013) also found increased CSF Aβ-42 levels in HIV infected patients; however, they could not associate this finding to disturbed cognitive functioning. There have been reports of reduced CSF Aβ-42 levels in HAND/AIDS dementia (Brew et al., 2005; Clifford et al., 2009) as well as in AD (Hampel et al., 2004). Our study confirms the observation of Peluso & colleagues as neither positive nor negative correlation was found between CSF Aβ-42 and HAND. In our study we did not find any significant association between the plasma cytokines IL-6, IL-8, IL-17, IL-18, and IFN-γ levels and HCI. However, in HCI patients IL-10 and IL-22 plasma levels showed slight elevated levels. IL-22 is a member of a group of cytokines called the IL-10 family (Pestka et al., 2004). IL-22 like IL-10, are both anti-inflammatory cytokines protecting many cells from pro-inflammatory responses (Moore et al., 2001). In our study plasma IL-22 or IL-10 did not correlate with Aβ-42; this suggests that Aβ-42 does not lead to plasma antiinflammatory response in HAND. Only the cytokine IL-8 was detectable in the CSF. IL-8 is a potent neutrophil chemotactic factor, a crucial mediator in neutrophil-dependent acute inflammation (Lynch et al., 1992). Numerous observations have demonstrated that various types of brain cells can produce a large amount of IL-8, including astrocytes and microglia cells (Choi et al., 2014; Ehrlich et al., 1998). In our study CSF IL-8 appeared elevated especially in the HCI group as compared to NF and control group. These data are in line with other studies that showed significant elevation in CSF IL8 levels in HCI patients (Cassol et al., 2014; Yuan et al., 2013) and can be explained by activation of microglial cells. Interestingly IL-8 levels have been shown to be elevated in AD patients (McLarnon, 2012). This was explained by activation of microglia

by Aβ release leading to IL-8 production by these cells (Franciosi et al., 2005; McLarnon, 2012). However our data did not show a positive correlation between IL-8 and Aβ-42 to substantiate this hypothesis. It is possible that the Aβ pathway in CNS of HIV infected patients differs from AD patients and stimulation of this pathway. In our study it is difficult to investigate this further as our study group was very heterogeneous with respect to HIV viremia, detectable CFS RNA levels and response to treatment. All these factors are known to affect intrathecal inflammation (Dore et al., 2003; Zhao et al., 2015) thereby hampering the associations we could possibly observe in our study. Further, we did not observe any relationship between CSF IL-8 and CSF HIV load the HIV treatment. In both AD and HIV infected patients, NEP appears to be the predominant protease that degrades Aβ in the brain (Pulliam, 2009; Wang et al., 2006). So far there are no studies that correlated NEP activity and Aβ-42 level in CSF of HCI or HAND patients and their controls. There are few studies that correlated CSF NEP and Aβ-42, in patients with AD, Lewy body disease, frontotemporal dementia (FTD), Creutzfeldt–Jakob disease and depression (Maetzler et al., 2010; Sorensen et al., 2013). In Lewy body disease and FTD patients, CSF NEP activity and Aβ–42 levels correlated positively (Maetzler et al., 2010; Sorensen et al., 2013). We found a positive correlation between Aβ-42 levels and NEP activity in CSF, supporting the observations made by Maetzler, Sorensen & colleagues (Maetzler et al., 2010; Sorensen et al., 2013). Apart from NEP, insulin-degrading enzyme (IDE), and endothelinconverting enzyme (ECE-1) are also known Aβ-degrading enzymes (Farris et al., 2003). A study in AD patients indicated however, that NEP is the major protease involved in Aβ degradation while neither IDE nor ECE-1 correlated with Aβ or clinical diagnosis (Wang et al., 2010). Our study could not substantiate these observations as we did not observe a correlation between NEP and Aβ-42 in plasma. It is, however important to note that plasma Aβ-42 was mainly undetectable in NF and controls groups. This does not rule out that Aβ degradation in plasma may occur via other Aβ degrading enzymes, such as IDE nor ECE-1. As mentioned earlier, limitation of our study is the small samples size and the cross-sectional design which hampers the search for associations between markers. Further, multiple comparisons were made during our statistical analysis; consequently our results should be interpreted with caution. In conclusion, the data from this pilot study indicate that CSF IL-8 and plasma Aβ-42 may be interesting biomarkers for the presence of HCI. Our data also indicate a possible role for NEP in the CNS for the regulation of Aβ-42. Further larger studies are needed to confirm these preliminary findings. Conflict of interest No competing financial interests exist.

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