# Disease-Induced Alterations in Brain Drug Transporters in Animal Models of Alzheimer's Disease

Kati-Sisko Vellonen, Jouni Ihalainen, Marie-Christine Boucau, Fabien Gosselet, Théo Picardat, Mikko Gynther, Katja Kanninen, Anthony White, Tarja Malm, Jari Koistinaho, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Kati-Sisko Vellonen, Jouni Ihalainen, Marie-Christine Boucau, Fabien Gosselet, Théo Picardat, et al. Disease-Induced Alterations in Brain Drug Transporters in Animal Models of Alzheimer's Disease. Pharmaceutical Research, 2017, 34 (12), pp.2652-2662. 10.1007/s11095-017-2263-7. hal-02506588

HAL Id: hal-02506588

https://univ-artois.hal.science/hal-02506588

Submitted on 23 Jul 2021

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Disease-Induced Alterations in Brain Drug Transporters in Animal Models of Alzheimer's Disease

**Theme: Drug Discovery, Development and Delivery in Alzheimer's Disease**

**Guest Editor: Davide Brambilla**

Kati-Sisko Vellonen<fnref n="1" /> • Jouni Ihalainen<fnref n="1" /> • Marie-Christine Boucau<fnref n="2" /> • Fabien Gosselet<fnref n="2" /> • Théo Picardat<fnref n="1" /> • Mikko Gynther<fnref n="1" /> • Katja M. Kanninen<fnref n="3" /> • Anthony R. White<fnref n="4" /> • Tarja Malm<fnref n="3" /> • Jari Koistinaho<fnref n="3" /> • Markus M. Forsberg<fnref n="1" /> • Marika Ruponen<fnref n="1" />

Received: 20 June 2017 / Accepted: 12 September 2017 / Published online: 26 September 2017
© Springer Science+Business Media, LLC 2017

## ABSTRACT

**Purpose** Alzheimer's disease (AD) may disturb functions of the blood-brain barrier and change the disposition of drugs to the brain. This study assessed the disease-induced changes in drug transporters in the brain capillaries of transgenic AD mice.

**Methods** Eighteen drug transporters and four tight junction-associated proteins were analyzed by RT-qPCR in cortex, hippocampus and cerebellum tissue samples of 12–16-month-old APdE9, Tg2576 and APP/PS1 transgenic mice and their healthy age-matched controls. In addition, microvessel fractions enriched from 1-3-month-old APdE9 mice were analyzed using RT-qPCR and Western blotting. Brain transport of methotrexate in APdE9 mice was assessed by in vivo microdialysis.

**Results** The expression profiles of studied genes were similar in brain tissues of AD and control mice. Instead, in the microvessel fraction in APdE9 mice, >2-fold alterations were detected in the expressions of 11 genes but none at the protein level. In control mice strains, >5-fold changes between different brain regions were identified for Slc15a2, Slc22a3 and

occludin. Methotrexate distribution into hippocampus of APdE9 mice was faster than in controls.

**Conclusions** The expression profile of mice carrying presenilin and amyloid precursor protein mutations is comparable to controls, but clear regional differences exist in the expression of drug transporters in brain.

**KEY WORDS** APdE9 · blood-brain barrier · brain disposition · brain microdialysis · CNS exposure · pharmacokinetics

## ABBREVIATIONS

<table><tr><td>AD</td><td>Alzheimer's disease</td></tr><tr><td>amyloid-β</td><td>Αβ</td></tr><tr><td>BBB</td><td>Blood-brain barrier</td></tr><tr><td>CB</td><td>Cerebellum</td></tr><tr><td>CX</td><td>Cortex</td></tr><tr><td>HC</td><td>Hippocampus</td></tr><tr><td>wt</td><td>Wild type</td></tr></table>

## INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia; it is associated with accumulation of senile plaques and neurofibrillary tangles in the brain (1). The extracellular senile plaques are mainly formed by aggregating amyloid-β (Aβ) peptides in the brain parenchyma, whereas hyperphosphorylated and misfolded tau proteins are the main constituent of the intraneuronal neurofibrillary tangles.

The distribution of drug molecules from the systemic circulation to the brain is controlled and limited by the blood-brain barrier (BBB). The BBB is formed by capillary endothelial cells and supported by the end feet of astrocytes and pericytes around brain capillaries. Dysfunction of the BBB has been

**Electronic supplementary material** The online version of this article (https://doi.org/10.1007/s11095-017-2263-7) contains supplementary material, which is available to authorized users.

<figure><img src="image_4.png" /></figure>

Kati-Sisko Vellonen
Kati-Sisko.Vellonen@uef.fi

<footnote n="1">¹ School of Pharmacy, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, FI, Finland</footnote>

<footnote n="2">² Laboratoire de la barrière hémato-encéphalique (LBHE), University Artois, Lens, France</footnote>

<footnote n="3">³ A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland</footnote>

<footnote n="4">⁴ QIMR Berghofer Medical Research Institute, Herston, QLD, Australia</footnote>
associated with neurodegeneration, although the importance of
BBB alterations solely attributable to AD, without the presence
of additional vascular diseases, is still unclear (2). A dysfunction-
al BBB may alter the access of AD drugs to their site of action; it
may either increase the drug exposure to the brain, potentially
causing unwanted effects, or decrease drug access and lead to
an insufficient response. AD patients are generally over 65 years
old, and in addition to AD drugs, they often have medication
for several other chronic diseases. Therefore, BBB dysfunction
can also either increase or decrease the brain distribution of
other concomitant medications and possibly increase their ad-
verse effects on the central nervous system.

The BBB is enriched with several transporter proteins be-
longing to the ATP binding cassette (ABC) and solute carrier
(SLC) gene families; these are responsible for ensuring the
supply of dietary components into the brain and the disposal
of metabolic products from the brain, as well as preventing
noxious agents accessing the brain from the circulation (3).
Transporters have also a significant role in the pharmacoki-
netics of many drugs. For instance, L-dopa, which is used to
treat Parkinson's disease, crosses the BBB via the influx carrier
L-type amino acid transporter (LAT1). Furthermore, the ef-
flux transporter Multidrug resistance protein 1 (MDR1, P-
glycoprotein) is known to diminish the central access of various
drug molecules. In addition, high levels of efflux transporters
including Breast cancer resistance protein (BCRP, ABCG2)
and Multidrug resistance-associated protein 4 (MRP4,
ABCC4) are expressed by the endothelial cells in the BBB (4).
Other transporters, relevant also as drug carriers, such as
MRP proteins (MRP1, MRP5), monocarboxylate (MCT1),
nucleoside (ENT1) and organic cation (OCT3) and anion
(OAT3) transporters, organic anion transporting polypeptides
(OATPs) and multidrug and toxin extrusion protein 1
(MATE1) have been localized in the endothelial cells of hu-
man and mouse brain capillaries (3-7).

The influence of AD on the expression and functionality of
some BBB drug transporters has been studied both in post-
mortem AD patient samples and animal models of AD.
MDR1 has been the most widely studied efflux protein in
AD and in addition to a wide variety of drug molecules it
has been shown to also transport Aβ (8). Downregulation of
MDR1 expression in brain capillaries in close proximity to Aβ
deposits of AD patients has been observed by several groups
(9-13). In addition to expression, a positron emission tomog-
raphy study investigated MDR1 function in the BBB of AD
patients with MDR1 substrate (R)-[11C]verapamil and found
evidence of decreased efflux function (14). The findings relat-
ed to the impact of AD on BCRP expression have revealed
minor and also partly conflicting alterations (10,12,13,15) and
a slight upregulation of MRP4 expression at both RNA and
protein levels has been detected in the hippocampus of AD
patients (10). There are even fewer studies examining disease-
induced changes in drug transporter expression in AD mouse

models. With respect to Mdr1, both up- and down-regulation
have been reported, whereas increase in expression levels of
Bcrp have been detected (8,16,17). However, there are many
transporters whose expression and functionality in AD remain
obscure i.e. no comprehensive comparative data is available.

Transgenic mouse models of AD, which have mutations in
amyloid precursor protein (APP), such as Tg2576, or in both
APP and presenilin (PSEN1) genes, such as APdE9 and APP/
PS1 mouse models, can provide useful information on AD
pathogenesis and disease mechanisms. APdE9 mice exhibit
an increase in the parenchymal Aβ load, with the appearance
of Aβ plaques starting from the age of four months; APP/PS1
mice develop Aβ deposits around 9 months of age, and
Tg2576 mice around 10 months of age. In addition, signs of
gliosis can be seen concurrently. Disease models are important
tools for drug development. For example, the pharmacokinetic
properties of novel AD drug candidates can be studied in
models having similar disease-induced alterations as AD pa-
tients. Before these AD models can be better exploited in pre-
clinical drug development, it would be important to acquire a
more detailed characterization of the drug transporters.

This study aimed to characterize the expression of drug
transporters and tight junction-associated proteins in three
mouse models of AD, the APdE9, APP/PS1 and Tg2576
mice, and to investigate the regional expression differences
in the brain. In order to assess the effect of AD pathology on
drug transport into the brain in vivo, we applied a pharmaco-
kinetic microdialysis method to measure the unbound extra-
cellular drug levels in the hippocampus after systemic admin-
istration of methotrexate.

## MATERIALS AND METHODS

### Animals

All procedures were made in compliance with the European
Communities Council Directive (86/609/EEC) and
Principles of laboratory Animal Care, and studies were ap-
proved by the National Animal Experiment Board. The ani-
mals were kept in a controlled environment with 12 h light/
dark cycle and food and water freely available. Brain tissue
samples were collected from male APP/PS1dE9 (APdE9)
mice (C57BL/6 J strain) (18) at the age of 16 months (n = 3-
4), female APP/PS1 mice (C57BL/6 J strain) (19) at the age of
12-15 months (n = 3-4) and female Tg2576 mice (C57BL/
6JxSJL strain) (20) at the age of 12-15 months (n = 4). All mice
groups had age-matched wildtype (wt) controls (n = 3-5).
During sample collection, the mice were anesthetized with
250 mg/kg Avertin and perfused 3 min transcardially with
heparinized (2500 IU/l) saline at a flow rate of 20 ml/min.
The cortical (CX), hippocampal (HC) and cerebellar (CB)
samples were dissected and snap frozen in liquid nitrogen.
Aβ accumulates mainly in CX and HC, whereas CB remains devoid of Ab deposits and was therefore considered as unaffected control tissue.

## Mechanical Isolation of Brain Capillaries

The microvessel enriched fraction was isolated from 5–12 weeks old female APdE9 mice as previously described by Coisne *et al.* (21). Briefly, ten cortices, from APdE9 or wt mice were isolated by removing cerebellum and brain white matter. Outer vessels and meninges were also removed. Preparations were pooled and ground using a Dounce homogenizer (first with the loose clearance pestle: 25–80 µm, then with the tight clearance pestle: 5–25 µm) in HBSS 1x containing 10 mM HEPES and 0.1% BSA. The resulting homogenate was mixed with 30% dextran (v/v, molecular weight 100,000–200,000) in HBSS 1x supplemented with 10 mM HEPES and 0.1% BSA. This suspension was centrifuged at 3000 g for 25 min at 4°C. The neural component and the dextran layer were discarded and the pellet containing the vascular component was washed twice in cold PBS CMF and then separated into two equal parts by centrifugation at 1000 g for 7 min at 4°C. The resulting pellets were resuspended either in RLT lysis buffer for RNA extraction or in RIPA lysis buffer for protein extraction.

## Quantitative RT-PCR

RNA expression of drug transporter and tight junction-associated genes was studied in brain tissues of 12–16 months old mice modelling AD and their healthy age-matched controls. Total RNA was extracted from HC, CX and CB tissue samples with TRI Reagent (Sigma). From microvessel samples, the RNA was extracted by RNeasy Mini Kit (Qiagen). After RNA extraction, the procedure was similar for both tissue and microvessel samples. Possible DNA residues were removed with DNA-free™ kit (Ambion). RNA concentration was measured with Nanodrop 1000 (Thermo Fisher Scientific) or NanoVue (GE Healthcare) spectrophotometer and 500 ng (brain tissues) or 200 ng (microvessels) of RNA was reverse-transcribed using random primers and M-MuLV enzyme (Fermentas, Hanover, MD). In the quantitative real-time PCR, the ABI Prism 7500 instrument with TaqMan® Gene expression assays (Supplementary Table I) or SYBR Green chemistry and primers designed for each gene (Supplementary Table II) were used. Normalized expression was calculated with the QGene application (22) using beta-actin as the reference gene. In the microvessel enriched fraction, a 2-fold difference was used as a threshold value and when a > 2-fold difference was determined with the first batch, the results were confirmed with a second batch. Efficiency was calculated for each primer pair and a melting curve analysis was performed after amplification cycles, in order to check the specificity/purity of each amplification.

## Western Blotting

After the capillary isolation procedure, the pellet was washed twice with cold PBS-CMF and then homogenized (polytron homogeniser: 2 times for 15 s at 11000 r/min on ice) in cold RIPA lysis buffer (Millipore, containing 0.5 M Tris-HCl, pH 7.4, 1.5 M NaCl, 2.5% deoxycholic acid, 10% NP-40 and 10 mM EDTA, supplemented with phosphatase and protease inhibitor cocktails (Sigma-Aldrich)). The protein concentration in each sample was determined by the method of Bradford (Bio-Rad). Then, 5–40 µg of proteins were electrophoresed on 4–15% Criterion XT sodium dodecyl sulphate (SDS)-polyacrylamide gel (P-gp/Abcb1, Rage, Lrp1) or 4–20% Mini-Protean TGX Gel (Mrp4) (Bio-Rad) and subsequently electrotransferred to nitrocellulose membranes. Unspecific binding was blocked with 5% skimmed milk in TBS, 0.1% Tween 20 and then incubated with primary antibody using following dilutions: Rage (Abcam) 1:2000, P-gp/Abcb1 (C219) (Genetex) 1:400, Lrp (5A6) (Santa Cruz) 1:200, Mrp4 (M41–10) (Santa Cruz) 1:200, β-actin (AC-15) (Sigma-Aldrich) 1:20,000, α-tubulin (B-5-1-2) (Sigma-Aldrich) 1:8000 and β-tubulin (9F3) (Cell Signaling) 1:1000. Immunoreactivity was detected with HRP conjugated secondary antibodies (Goat anti-rat IgG (Santa Cruz) (1: 10,000), Goat anti-rabbit IgG (Dako) (1:2000) and Goat anti-mouse IgG (1:2000 for Dako and 1:7500 for Santa Cruz) and enhanced chemiluminescence (ECL) system.

## Pharmacokinetic In Vivo Microdialysis

Microdialysis experiments were performed with 16–18 months old male APdE9 mice. To implant the guide cannulae (Brainlink B.V., the Netherlands) 2–3 days before the microdialysis experiment, the mice were anesthetized with 1–2% isoflurane in 70% N₂O and 30% O₂ (flow 300 ml/min, induction 5% isoflurane). Lidocaine (10 mg/mL; Orion Corporation, Oulu, Finland) was used as a local anesthetic. Anesthetized mice were placed in a Kopf stereotaxic frame equipped with a DKI 921 mouse adapter (David Kopf Instr., Tujunga, CA, USA). The guide cannula was implanted into the right HC using following coordinates: A: -3.1 mm, L: -2.7 mm, V: -1.3 mm and secured with cranial screws and dental cement. Carprofen (5 mg/kg s.c.; Vericore Ltd., Dundee, UK) and buprenorphine (0.12 mg/kg, s.c.; Schering-Plough, Belgium) were used for postoperative pain relief. Saline (0.6 mL i.p.) was injected after surgery to maintain fluid balance.

Three hours before the start of the microdialysis experiment, the mice were transferred into microdialysis bowls (CMA120, CMA microdialysis, Solna, Sweden), and the microdialysis probe (membrane length 3 mm, regenerated cellulose; cut-off 18 kDa; Brainlink B.V., the Netherlands) was inserted into the right HC through the guide cannula. The probe was connected to a rotating liquid swivel (375/D/
22QM, Instech Laboratories, Plymouth Meeting, PA, USA) and was perfused with Ringer fluid (147 mM NaCl, 3 mM KCl, 1.2 mM CaCl₂, 1.2 mM MgCl₂) at a flow rate of 1.5 µl/min. After a 120-min wash-out period, a 20 min baseline sample was collected and methotrexate (50 mg/kg in a volume of 2.5 ml/kg; Metoject, medac GmbH) was given intravenously. Dialysate was collected for 240 min (12 samples), and the samples were frozen in liquid nitrogen and stored at -70°C. Terminal blood samples were collected by cardiac puncture and plasma was separated by centrifugation (2000 × g for 10 min at 4°C), immediately fresh frozen on liquid nitrogen and stored at -70°C.

*In vivo* recovery was determined to estimate the true methotrexate concentration in the brain extracellular fluid in a separate experiment (wt *n* = 3 and APdE9 *n* = 3, 13 months) by using the retrodialysis method to calibrate the microdialysis probe. The basic procedure of *in vivo* microdialysis was performed as described above. After a 120-min wash-out period, a 20 min baseline sample was collected and then the Ringer solution was switched to a Ringer containing 200 ng/mL methotrexate. The microdialysis sample collection was continued for 120 min (6 samples). The *in vivo* recovery for methotrexate was calculated from the last three samples with the eq. C = (Cin-Cout)/Cin, where R is *in vivo* recovery of methotrexate, Cin is concentration of methotrexate in the perfusate and Cout is concentration of methotrexate in the dialysate. *In vivo* recovery values of 8 ± 3% for APdE9 mice and 18 ± 7% for WT mice were used to correct the dialysate concentrations.

## LC-MS/MS Analysis

The microdialysis samples were analyzed for MTX concentration with an Agilent 1200 series liquid chromatograph and an Agilent 6410 Triple Quadrupole Mass Spectrometer with electrospray ionization. The column was a Poroshell 120 EC-C18 (50 mm × 2.1 mm, 2.7 µm; Agilent Technologies, Santa Clara, CA) maintained at 40°C and a Rapid Resolution LC in-line filter (2 mm, 0.2 mm; Agilent Technologies) was used for protecting the analytical column from possible contaminants. A binary mobile phase with a gradient elution was used. Solvent A was milliQ water with 0.1% formic acid (eluent additive for LC-MS, Fluka) and solvent B was acetonitrile (Sigma-Aldrich) with 0.1% formic acid. The gradient was performed as following: 5% B kept constant for 1 min, increased to 90% for 5 min, decreased to 5% B for 0.1 min, and kept constant for 2.9 min. Under these conditions, the total run time was 8 min. The flow rate was 0.3 ml/min and the injection volume of Ringer fluid samples was 20 µl. The source parameters were: capillary voltage 3 kV, nebuliser 40 psi, gas temperature 300°C, gas flow 8 l/min. Data acquisition was done in the positive ion MRM mode using transitions 455.1 → 308 for MTX and 458.1 → 311 for the internal standard (deuterated MTX). Fragmentor voltages used for

MTX and the internal standard were 200 V and 160 V, respectively. The collision energies were 38 V and 16 V for MTX and the internal standard, respectively. Agilent MassHunter Workstation Acquisition software (Data Acquisition for Triple Quadrupole Mass Spectrometer, version B.03.01) was used for data acquisition, whereas Quantitative Analysis (B.04.00) software was used for the data processing and analysis. The lower limit of quantification (LLOQ) was 0.05 ng/ml for Ringer fluid samples and 5 ng/ml for plasma samples. The linearity of the calibration curve was evaluated by a quadratic regression analysis and the method was found to be selective, accurate, and precise over the calibration range. The calibration range of 0.05–500 ng/ml was used for Ringer fluid samples and 5–1000 ng/ml for plasma samples. Within-run accuracy and precision were calculated from the results of the quality control samples at the three concentrations. The accuracies and precisions for quality control concentrations of 20% were considered acceptable.

## Data Analysis

To evaluate differences in gene expression between brain tissues the statistical significance was tested with Kruskal-Wallis one way analysis of variance on Ranks followed by Dunn's Method for pairwise comparison (SigmaPlot 13.0).

The area under the concentration curve (AUC) values were determined using Phoenix™ WinNonlin® (Pharsight, Certara L.P., USA). In the statistical analysis of differences between AUC values, two-tailed t-test (SigmaPlot 13.0) was used.

# RESULTS

## Gene Expression Profile of Drug Transporters and Tight Junction-Associated Proteins in Brain of AD Mouse Models

### *Efflux Transporters*

The expressions of 8 ABC efflux transporters (Abcb1a, Abcb1b, Abcc1-Abcc5, Abcg2) were compared between AD mouse models APdE9, Tg2576 and APP/PS1 (12–16 months old mice) and their healthy age-matched wt controls using brain samples comprising of brain parenchyma and BBB. In the APdE9 model, the greatest difference was detected for Abcb1b gene, which had a 1.4-fold higher expression level in AD CX and HC tissues when compared to wt (Fig. 1a). In Tg2576 mice, the differences between AD tissues and controls were ≤1.4-fold (Fig. 1b) and in the APP/PS1 model, the differences were even smaller (≤ 1.3-fold) (Fig. 1c), if Abcc2 was not taken into account. With respect to Abcc2, up to 2-fold differences were detected, but statistical significance was not reached because of the high variation in Abcc2 expression
<figure><img src="image_5.png" /><figcaption>**Fig. 1** Gene expression of Abc efflux transporters in the CX, HC and CB of male APdE9 (a), female Tg2576 (b) and female APP/PS1 (c) mouse models expressed as relative to wt control mice (AD/wt) (mean ± sd, n = 3–5). The gene expression was normalized against the beta-actin house-keeping gene. The dotted line depicts 1.5-fold down- or up-regulation.</figcaption></figure>

due to its very low expression levels. Overall, the gene expres-
sion profile of efflux transporters between these three AD
models was similar. Differences between AD and wt were
minor (≤ 1.4 fold) with the exception of Abcc2.

Influx Transporters

Gene expression of SLC influx transporters including L-type
amino acid transporter (Slc7a5), peptide transporter
(Slc15a2), organic anion and cation transporters (Slc22a2,
Slc22a3, Slc22a5 and Slc22a8), Multidrug and toxin extru-
sion protein (Slc47a1) and organic anion transporting poly-
peptides (Slco1a4, Slco2b1 and Slco1c1) was studied in the
three AD mouse models (Fig. 2). More than 2-fold lower ex-
pression in AD samples compared to wt controls was observed
for four transporters, namely Slc22a2 (HC of APdE9 and
Tg2576), Slc22a3 (CB of Tg2576), Slc22a8 (HC of Tg2576)
and Slc47a1 (HC of APdE9 and Tg2576). The highest differ-
ence was seen for Slc22a2, the expression of which in HC of
Tg2576 mice was approximately one fifth of that in control
and a similar trend was also seen in APdE9 (less than half than
in controls). The Slc22a8 expression level in the HC of
Tg2576 mice was one third of the control and similarly in
APdE9, almost half of the control. In APP/PS1 brains, the
differences between AD and control were in all cases <1.5
fold. Slc22a2 was expressed at a low level in all studied brain
samples; likewise, the levels of Slc22a3 and Slc47a1 were low

in certain tissues, thereby introducing high variability into the
results for those genes.

Tight Junction-Associated Proteins and Cell Markers

Four genes (Ocln, Cldn3, Cldn5, Jam1) related to tight junc-
tions were included in the study. Cldn3 expression in HC of
Tg2576 and APdE9 mice was lower (0.43 ± 0.14 and
0.61 ± 0.30, respectively) compared to wt control and similar-
ly Jam1 in HC of Tg2576 (0.61 ± 0.11), but in other brain
regions and animal models, the differences were smaller (Fig. 3).
For the other tight junction-associated genes (Ocln,
Cldn5), only minor differences were seen between AD
and wt controls. However, with regard to the cell
markers analyzed (Pecam1, Aif1, Rbfox3, Gfap), a clear
upregulation of the astrocyte marker Gfap was detected.
In the CX of APdE9, Tg2576 and APP/PS1 mice, the
expression of Gfap was 3.5 ± 0.2-fold (p = 0.037),
2.27 ± 1.13-fold and 4.4 ± 0.2-fold (p = 0.029) higher,
respectively, than in wt controls. In addition, in HC, the
AD/wt ratio was elevated, i.e. it was 2.4 ± 0.4 in APP/
PS1 and 2.3 ± 0.2 in APdE9. The microglial marker
Aif1 expression was upregulated only in APdE9 mice,
with 1.6-fold and 1.5-fold higher expressions in HC and
CX, respectively.

When the expression levels of 26 genes were compared
between brain regions (CX, HC and CB) of wt control mice,
the differences were more prominent (Table I) and more than

<figure><img src="image_6.png" /><figcaption>**Fig. 2** Gene expression of Slc influx transporters in the CX, HC and CB of male APdE9 (a), female Tg2576 (b) and female APP/PS1 (c) mouse models expressed as relative to wt control mice (AD/wt) (mean ± sd, n = 3–5). The gene expression was normalized against the beta-actin house-keeping gene. The dotted line depicts 1.5-fold down- or up-regulation.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 3** Gene expression of tight junction-associated proteins and cell markers in CX, HC and CB of male APdE9 (a), female Tg2576 (b) and female APP/PS1 (c) AD models expressed as relative to wt control mice (AD/wt) (mean ± sd, n = 3–5). The gene expression was normalized against the beta-actin house-keeping gene. The dotted line depicts 1.5-fold down- or up-regulation. \* indicates significant difference between AD and wt (p < 0.05).</figcaption></figure>

2-fold differences were observed for 20 genes. Only Slc1c1 was equally expressed in all three brain regions. Ocln expression was 5–7-fold higher in CB than in CX, whereas in CX, the expression of Slc22a3 was ≥5-fold higher than in CB and HC. Interestingly, the expression of Abcc1, Slc7a5, Slc22a5, Slc47a1, Cldn5 and Jam1 was higher (>2-fold) in CB than in CX.

The differences between brain regions were rather similar among all three wt control strains. Since only minor differences were detected between AD and wt mice, these results are mostly comparable also in AD mice models.

## Gene and Protein Expression Profile in Brain Microvessel Enriched Fraction of APdE9 Mice

The expression of 35 genes was studied in enriched fraction of microvessels isolated from the cortices of 5–12 weeks old APdE9 mice and age-matched controls. In the case of 11 genes, there was a more than 2-fold difference in the expression level between AD and wt (Table II). Only one gene, Slc2a1, was upregulated by 2-fold in AD; for 10 genes, the AD/wt ratio was <0.5. For the endothelial markers Pecam1 and Cdh5, the ratio was in the range 0.31–0.36. Efflux transporters Abcb1a, Abcc4 and Abcg2

<table><caption>**Table I** Comparison of gene expression between brain regions in three wt strains (healthy control of each AD mice model i.e. male APdE9, female Tg2576 and female APP/PS1)</caption><thead><tr><th></th><th>HC/CX<br>APdE9</th><th>HC/CX<br>Tg2576</th><th>HC/CX<br>APP/PS1</th><th>CB/CX<br>APdE9</th><th>CB/CX<br>Tg2576</th><th>CB/CX<br>APP/PS1</th><th>CB/HC<br>APdE9</th><th>CB/HC<br>Tg2576</th><th>CB/HC<br>APP/PS1</th></tr></thead><tbody><tr><td>Abcb1a</td><td>0.88 ± 0.22</td><td>0.86 ± 0.20</td><td>0.73 ± 0.15</td><td>1.72 ± 0.14</td><td>1.67 ± 0.29</td><td>1.74 ± 0.10</td><td>1.94 ± 0.16</td><td>1.95 ± 0.34</td><td>2.37 ± 0.13</td></tr><tr><td>Abcb1b</td><td>1.05 ± 0.20</td><td>0.91 ± 0.18</td><td>1.13 ± 0.19</td><td>0.78 ± 0.11</td><td>0.48 ± 0.12*</td><td>0.69 ± 0.07</td><td>0.75 ± 0.11</td><td>0.53 ± 0.13</td><td>0.61 ± 0.06</td></tr><tr><td>Abcc1</td><td>0.95 ± 0.05</td><td>0.81 ± 0.18</td><td>0.81 ± 0.01</td><td>2.37 ± 0.46</td><td>2.16 ± 0.22</td><td>2.3 ± 0.18</td><td>2.5 ± 0.48</td><td>2.65 ± 0.27</td><td>2.86 ± 0.22</td></tr><tr><td>Abcc2</td><td>1.12 ± 0.66</td><td>0.36 ± 0.16</td><td>0.50 ± 0.17</td><td>1.15 ± 0.84</td><td>0.52 ± 0.59</td><td>0.63 ± 0.58</td><td>1.03 ± 0.75</td><td>1.46 ± 1.65</td><td>1.26 ± 1.16</td></tr><tr><td>Abcc3</td><td>0.90 ± 0.09</td><td>0.63 ± 0.13</td><td>0.76 ± 0.04</td><td>0.61 ± 0.06</td><td>0.47 ± 0.27</td><td>0.65 ± 0.05</td><td>0.68 ± 0.07</td><td>0.74 ± 0.43</td><td>0.85 ± 0.06</td></tr><tr><td>Abcc4</td><td>1.13 ± 0.13</td><td>0.97 ± 0.21</td><td>0.94 ± 0.09</td><td>1.97 ± 0.05</td><td>1.69 ± 0.31</td><td>1.93 ± 0.27</td><td>1.75 ± 0.04</td><td>1.75 ± 0.32</td><td>2.06 ± 0.29</td></tr><tr><td>Abcc5</td><td>0.68 ± 0.06</td><td>0.72 ± 0.05</td><td>0.74 ± 0.05</td><td>1.37 ± 0.15</td><td>1.60 ± 0.21</td><td>1.46 ± 0.05</td><td>2.01 ± 0.23</td><td>2.22 ± 0.30</td><td>1.97 ± 0.06</td></tr><tr><td>Abcg2</td><td>0.87 ± 0.15</td><td>0.81 ± 0.2</td><td>0.89 ± 0.09</td><td>1.31 ± 0.12</td><td>1.09 ± 0.17</td><td>1.35 ± 0.27</td><td>1.52 ± 0.14</td><td>1.35 ± 0.21</td><td>1.51 ± 0.30</td></tr><tr><td>Slc7a5</td><td>0.85 ± 0.15</td><td>0.79 ± 0.17</td><td>0.78 ± 0.09</td><td>2.21 ± 0.17</td><td>2.01 ± 0.41</td><td>2.05 ± 0.16</td><td>2.58 ± 0.20</td><td>2.55 ± 0.52</td><td>2.64 ± 0.21</td></tr><tr><td>Slc15a2</td><td>0.93 ± 0.08</td><td>0.96 ± 0.31</td><td>1.09 ± 0.18</td><td>1.98 ± 0.10</td><td>1.66 ± 0.83</td><td>5.54 ± 0.82</td><td>2.14 ± 0.11</td><td>1.74 ± 0.86</td><td>5.09 ± 0.75</td></tr><tr><td>Slc22a2</td><td>1.60 ± 1.09</td><td>1.80 ± 1.26</td><td>0.97 ± 0.41</td><td>1.01 ± 0.26</td><td>0.71 ± 0.30</td><td>0.88 ± 0.16</td><td>0.63 ± 0.16</td><td>0.40 ± 0.17</td><td>0.90 ± 0.17</td></tr><tr><td>Slc22a3</td><td>0.15 ± 0.09</td><td>0.19 ± 0.05</td><td>0.12 ± 0.05</td><td>0.18 ± 0.16</td><td>0.11 ± 0.01</td><td>0.06 ± 0.05*</td><td>1.21 ± 1.06</td><td>0.61 ± 0.07</td><td>0.52 ± 0.40</td></tr><tr><td>Slc22a5</td><td>0.91 ± 0.11</td><td>1.14 ± 0.23</td><td>1.00 ± 0.11</td><td>2.09 ± 0.16</td><td>2.46 ± 0.50</td><td>2.27 ± 0.20</td><td>2.29 ± 0.18</td><td>2.16 ± 0.44</td><td>2.28 ± 0.20</td></tr><tr><td>Slc22a8</td><td>1.54 ± 0.78</td><td>1.27 ± 0.69</td><td>0.92 ± 0.46</td><td>1.92 ± 0.30</td><td>1.77 ± 0.20</td><td>1.20 ± 0.13</td><td>1.24 ± 0.19</td><td>1.40 ± 0.15</td><td>1.30 ± 0.14</td></tr><tr><td>Slc47a1</td><td>0.90 ± 0.77</td><td>1.29 ± 0.79</td><td>0.85 ± 0.64</td><td>2.70 ± 0.84</td><td>2.34 ± 1.28</td><td>2.10 ± 0.30</td><td>3.00 ± 0.94</td><td>1.82 ± 1.00</td><td>2.48 ± 0.36</td></tr><tr><td>Slco1a4</td><td>1.12 ± 0.17</td><td>0.95 ± 0.43</td><td>0.92 ± 0.12</td><td>2.09 ± 0.10</td><td>1.48 ± 0.36</td><td>1.95 ± 0.13</td><td>1.86 ± 0.09</td><td>1.55 ± 0.38</td><td>2.12 ± 0.14</td></tr><tr><td>Slco2b1</td><td>0.93 ± 0.08</td><td>0.82 ± 0.19</td><td>0.93 ± 0.18</td><td>0.89 ± 0.13</td><td>0.45 ± 0.19</td><td>1.00 ± 0.05</td><td>0.96 ± 0.14</td><td>0.55 ± 0.23</td><td>1.07 ± 0.05</td></tr><tr><td>Slco1c1</td><td>0.89 ± 0.16</td><td>0.78 ± 0.11</td><td>0.83 ± 0.09</td><td>1.17 ± 0.21</td><td>1.14 ± 0.12</td><td>1.08 ± 0.19</td><td>1.33 ± 0.23</td><td>1.45 ± 0.29</td><td>1.30 ± 0.23</td></tr><tr><td>Ocln</td><td>1.76 ± 0.15</td><td>2.55 ± 0.62</td><td>1.74 ± 0.15</td><td>5.64 ± 0.16</td><td>7.25 ± 0.75*</td><td>5.37 ± 0.40</td><td>3.20 ± 0.09</td><td>2.84 ± 0.30</td><td>3.09 ± 0.23</td></tr><tr><td>Cldn3</td><td>1.30 ± 1.04</td><td>1.87 ± 1.94</td><td>1.09 ± 0.16</td><td>1.49 ± 0.80</td><td>0.89 ± 0.50</td><td>1.39 ± 0.94</td><td>1.14 ± 0.62</td><td>0.47 ± 0.27</td><td>1.28 ± 0.87</td></tr><tr><td>Cldn5</td><td>1.24 ± 0.25</td><td>1.14 ± 0.30</td><td>0.88 ± 0.33</td><td>1.88 ± 0.17</td><td>2.12 ± 0.84</td><td>1.43 ± 0.28</td><td>1.51 ± 0.13</td><td>1.86 ± 0.74</td><td>1.62 ± 0.32</td></tr><tr><td>Jam1</td><td>1.05 ± 0.18</td><td>1.30 ± 0.96</td><td>0.99 ± 0.27</td><td>2.38 ± 0.25*</td><td>3.78 ± 1.54</td><td>1.65 ± 0.29</td><td>2.27 ± 0.24</td><td>2.91 ± 1.19</td><td>1.67 ± 0.30</td></tr><tr><td>Pecam1</td><td>1.11 ± 0.29</td><td>1.06 ± 0.35</td><td>0.99 ± 0.27</td><td>1.86 ± 0.09</td><td>1.44 ± 0.44</td><td>1.73 ± 0.17</td><td>1.67 ± 0.08</td><td>1.36 ± 0.42</td><td>1.74 ± 0.17</td></tr><tr><td>Aif1</td><td>0.76 ± 0.08</td><td>0.72 ± 0.14</td><td>0.84 ± 0.11</td><td>0.80 ± 0.14</td><td>0.53 ± 0.18</td><td>0.51 ± 0.02</td><td>1.06 ± 0.18</td><td>0.74 ± 0.25</td><td>0.60 ± 0.02</td></tr><tr><td>Rbfox3</td><td>0.63 ± 0.08</td><td>0.73 ± 0.02</td><td>0.75 ± 0.02</td><td>1.59 ± 0.30</td><td>2.18 ± 0.16</td><td>2.09 ± 0.23</td><td>2.54 ± 0.48</td><td>2.97 ± 0.22</td><td>2.80 ± 0.30</td></tr><tr><td>Gfap</td><td>2.18 ± 0.29</td><td>2.23 ± 0.50*</td><td>2.38 ± 0.25</td><td>1.68 ± 0.16</td><td>1.85 ± 0.22</td><td>2.67 ± 0.45</td><td>0.77 ± 0.07</td><td>0.83 ± 0.10</td><td>1.12 ± 0.19</td></tr></tbody></table>

Results are expressed HC/CX, CB/CX OR CB/HC ratio (mean ± sd, n = 3–5). Yellow color indicates ≥1.5-fold and green color ≥2-fold differences between brain regions. \* = p < 0.05
had 73%, 60% and 55% lower expression levels, respectively, in AD than in wt. A similar trend was observed in case of the expression of the influx transporters Slc22a8 (55%) and Slco1a4 (61%), beta-amyloid peptide receptor Ager (Rage) (65%) and tight junction-associated genes occludin (60%) and claudin 5 (64%).

Results were normalized against beta-actin, which showed stable expression between AD and wt samples. Since the amount of RNA was limited, the replicate measurements were focused on genes with moderate or high expression and/or where a difference between AD and wt was detected in the first measurement.

The microvessel enriched fraction was used also to study the protein expression of the main receptors for amyloid-beta peptide, Rage and Lrp1, with the efflux transporters Mdr1 and Mrp4 showing lower gene expression in AD than in wt mice. According to the results of immunoblotting, the expression of these proteins did not differ significantly (≤ 1.5-fold) between AD and wt samples (Fig. 4).

Distribution of Methotrexate into Brain in APdE9 Mice

To assess the effect of AD pathology on efflux transporter function *in vivo*, methotrexate was selected as a model drug for the

<table><caption>**Table II** Comparison of Gene Expression Levels between Brain Microvessels Isolated from Cortices of Female AD Mice (APdE9) and their wt Controls</caption><thead><tr><th colspan="3">ATP-binding cassette (ABC) transporters</th></tr></thead><tbody><tr><td><strong>Gene</strong></td><td><strong>Protein</strong></td><td><strong>Ratio of AD/wt<sup>a</sup></strong></td></tr><tr><td>Abcb1a</td><td>Multidrug resistance protein 1a (Mdr1a)</td><td>0.258–0.283</td></tr><tr><td>Abcb1b</td><td>Multidrug resistance protein 1b (Mdr1b)</td><td>0.537</td></tr><tr><td>Abcc1</td><td>Multidrug resistance-associated protein 1 (Mrp1)</td><td>0.758</td></tr><tr><td>Abcc2</td><td>Multidrug resistance-associated protein 2 (Mrp2)</td><td>0.677</td></tr><tr><td>Abcc3</td><td>Multidrug resistance-associated protein 3 (Mrp3)</td><td>1.011</td></tr><tr><td>Abcc4</td><td>Multidrug resistance-associated protein 4 (Mrp4)</td><td>0.3971–0.3973</td></tr><tr><td>Abcc5</td><td>Multidrug resistance-associated protein 5 (Mrp5)</td><td>0.588–0.668</td></tr><tr><td>Abcg2</td><td>Breast cancer resistance protein (Bcrp)</td><td>0.436–0.457</td></tr><tr><td><strong>Solute carriers (SLCs)</strong></td><td></td><td></td></tr><tr><td>Slc2a1</td><td>Glucose transporter 1 (Glut1)</td><td>1.803–2.230</td></tr><tr><td>Slc5a7</td><td>High affinity choline transporter 1 (Cht1)</td><td>1.173–1.653</td></tr><tr><td>Slc7a5</td><td>L-type amino acid transporter 1 (Lat1)</td><td>0.696–0.943</td></tr><tr><td>Slc15a2</td><td>Peptide transporter 2 (Pept2)</td><td>0.766–0.913</td></tr><tr><td>Slc16a1</td><td>Monocarboxylate transporter 1 (Mct1)</td><td>0.620–0.657</td></tr><tr><td>Slc22a2</td><td>Organic cation transporter 2 (Oct2)</td><td>1.161</td></tr><tr><td>Slc22a3</td><td>Organic cation transporter 3 (Oct3)</td><td>0.990</td></tr><tr><td>Slc22a5</td><td>Organic cation/camitine transporter 2 (Octn2)</td><td>0.626</td></tr><tr><td>Slc22a8</td><td>Organic anion transporter 3 (Oat3)</td><td>0.414–0.495</td></tr><tr><td>Slc29a1</td><td>Equilibrative transporter 1 (Ent1)</td><td>0.941–1.03</td></tr><tr><td>Slc47a1</td><td>Multidrug and toxin extrusion protein 1 (Mate1)</td><td>0.543</td></tr><tr><td>Slco1a4</td><td>Organic anion transporting polypeptide 1a4 (Oatp1a4)</td><td>0.369–0.405</td></tr><tr><td>Slco2b1</td><td>Organic anion transporting polypeptide 2b1 (Oatp2b1)</td><td>0.714–0.726</td></tr><tr><td>Slco1c1</td><td>Organic anion transporting polypeptide 1c1 (Oatp1c1)</td><td>0.525–0.563</td></tr><tr><td><strong>Transport of beta-amyloid</strong></td><td></td><td></td></tr><tr><td>Lrp1</td><td>Full name<br/>Low density lipoprotein receptor-related protein 1</td><td>0.960–0.964</td></tr><tr><td>Ager</td><td>Advanced glycation end product-specific receptor (Rage)</td><td>0.300–0.400</td></tr><tr><td><strong>Tight junction-associated proteins</strong></td><td></td><td></td></tr><tr><td>Odn</td><td>Occludin</td><td>0.362–0.431</td></tr><tr><td>Cldn1</td><td>Claudin1</td><td>1.079–1.334</td></tr><tr><td>Cldn3</td><td>Claudin 3</td><td>1.052</td></tr><tr><td>Cldn5</td><td>Claudin 5</td><td>0.308–0.410</td></tr><tr><td>Tjp1</td><td>Tight junction protein ZO-1</td><td>0.555–0.646</td></tr><tr><td>F11r</td><td>Junctional adhesion molecule A (Jam-A)</td><td>0.591–0.666</td></tr><tr><td><strong>Cell markers</strong></td><td></td><td></td></tr><tr><td>Pecam1</td><td>Full name/Cell type<br/>Platelet/endothelial cell adhesion molecule 1/Endothelial</td><td>0.324–0.363</td></tr><tr><td>Cdh5</td><td>Cadherin-5/Endothelial</td><td>0.306–0.354</td></tr><tr><td>Aif1</td><td>Allograft inflammatory factor 1/Microglial</td><td>0.826–0.898</td></tr><tr><td>Gfap</td><td>Glial fibrillary acidic protein/Astrocytic</td><td>1.07–1.09</td></tr><tr><td>Rbfox3</td><td>RNA binding protein, fox-1 homolog (C. elegans) 3/Neuronal</td><td>1.243</td></tr></tbody></table>

<footnote><sup>a</sup>When results are expressed as range, two replicate samples were used. Otherwise the results are based on one sample of isolated microvessels. Each sample is a pool from brain microvessels of 5 mice</footnote>
brain microdialysis studies since it has been previously shown to be effluxed by both Mrp4 and Bcrp in a similar study conducted in Mrp4 and Bcrp knock-out mice (23). Unbound extracellular methotrexate levels in hippocampus were 9-fold higher in APdE9 mouse than the corresponding values in wt in the 20 min fraction after drug administration (Fig. 5), but the difference diminished later. The brain methotrexate exposure (AUC₀-∞) was 2.7-fold higher in APdE9 than in wt (p = 0.013) mice and the difference was even greater, 2.9-fold (p = 0.006), within the first 60 min (AUC₀-60) (Table III). Total plasma concentration was measured after intravenous injection of methotrexate from separate mice (wt n = 6 and APdE9 n = 5–6, 17 months). The plasma concentrations at 10, 30 and 60 min were 52.7 ± 7, 14.0 ± 7.2 and 5.9 ± 1.1 µg/ml (mean ± sd) in APdE9 and 58.4 ± 16, 14.1 ± 4.5 and 6.6 ± 2.6 µg/ml in wt mice, respectively.

DISCUSSION

Transporters and tight junctions of the BBB are crucial for the maintenance of brain homeostasis. Neurodegenerative diseases, such as AD, alter the function of the BBB and are therefore likely to change drug distribution into the brain (24). In this study, the expression of Abc and Slc transporters relevant in pharmacokinetics and tight junction-associated proteins in the brains of three AD mouse models, APdE9, Tg2576 and APP/PS1 were investigated. We focused on genes that are known to be expressed in brain/BBB. Brain samples were dissected from >12 months old animals having clear pathological signs of the disease in their brain i.e. amyloid beta plaques and gliosis. We used APP and APP/PS1 mutant mouse lines considered to be AD models of Aβ pathology rather than AD models fully addressing the clinical presentation of AD. The expression levels of the studied genes in AD models were close to their healthy age-matched controls and the observed differences were minor

<table><thead><tr><th></th><th>wt</th><th>AD</th><th>Mean fold change<br>AD/wt</th></tr></thead><tbody><tr><td>Rage</td><td></td><td>42 kDa</td><td rowspan="2">0.97±0.27</td></tr><tr><td>β-Tubulin</td><td></td><td>55 kDa</td></tr><tr><td>Lrp1</td><td></td><td>75 kDa (expected 84 kDa)</td><td rowspan="2">0.92±0.03</td></tr><tr><td>β-Actin</td><td></td><td>42 kDa</td></tr><tr><td>Mdr1</td><td></td><td>141 kDa</td><td rowspan="2">0.92±0.07</td></tr><tr><td>β-Actin</td><td></td><td>42 kDa</td></tr><tr><td>Mrp4</td><td></td><td>159 kDa</td><td rowspan="2">1.5±0.36</td></tr><tr><td>α-Tubulin</td><td></td><td>42 kDa</td></tr></tbody></table>

**Fig. 4** Expression of Rage, Lrp1, Mdr1 and Mrp4 proteins in microvessel enriched fraction isolated from cortices of female APdE9 (AD) and wt mouse and detected by Western blotting. For Rage, Lrp1 and Abcb1, 40 µg of total protein were used, the corresponding value for Mrp4 was 5 µg. Mean fold change ± SEM (AD/wt) was calculated based on three replicate blots

<figure><img src="image_8.png" /></figure>

**Fig. 5** Unbound extracellular methotrexate levels in the hippocampus of male APdE9 mice (AD) (n = 7) and wt controls (n = 8) after i.v. injection at 50 mg/kg. Microdialysis samples were collected as 20 min fractions. LLOQ was 0.05 ng/ml

(mostly less than 1.5-fold change) with the exception of the astrocyte cell marker, Gfap. This was expected since upregulation of Gfap due to an increase in the numbers of reactive astrocytes is an early and common sign in various models of neurodegeneration and brain diseases, and is also observed in transgenic AD mice (25). Furthermore, the expression of the microglial activation marker, Aif1, was elevated (about 1.5-fold) in APdE9 mice in line with extensive data revealing neuroinflammation as a characteristic of AD.

Comparison of gene expression of transporters and tight junction-associated proteins between brain regions showed more than 2-fold differences for 21 genes in wt mice. For 14 genes, a higher expression level was observed in CB in comparison to CX or HC. We detected a > 5-fold difference between brain regions in gene expression of organic cation transporter Slc22a3 and the tight junction-associated protein, occludin. Such large differences in gene expression should reflect protein expression and functionality. In the literature, the data regarding regional variability of brain drug transporters is sparse and scattered. The highest Mdr1 activity has been proposed for CB by a combinatory mapping approach and PET studies in rats (26,27). These observations are in accordance with our data as Abcb1a is the major form in brain. However, in another study, Mdr1 mediated efflux activity of loperamide was highest in cerebral CX and mid-brain regions when assessed by *in situ* brain perfusion in mice (28). Kannan *et al.* stated that there was equal BCRP density

<table><caption>**Table III** Brain Exposure to Methotrexate in Male APdE9 Mice (AD) and their wt Controls After i.v. Injection at 50 mg/kg, AUC Calculated from Whole Concentration-Time Curve (AUC₀-∞) and First 60 min (AUC₀-60) are Presented (mean ± SEM, n = 7–8)</caption><thead><tr><th></th><th>AD</th><th>wt control</th></tr></thead><tbody><tr><td>AUC₀-∞ (ng x min/ml)</td><td>40178 ± 7587*</td><td>15107 ± 4765</td></tr><tr><td>AUC₀-60 (ng x min/ml)</td><td>27485 ± 4167**</td><td>9507 ± 3604</td></tr></tbody></table>

<footnote>*p < 0.05 vs. wt control value</footnote>

<footnote>**p < 0.01 vs. wt control value</footnote>
between brain regions, which is also in line with our results (13). The high regional variability in transporter expression may perhaps be explained by the higher capillary density in certain brain region or the variation in the relative amount of each cell type. Previously, brain capillary density has been determined with the vascular volume marker, inulin, with a 3.7-fold difference being observed between brain regions (28). This high variation between brain areas can affect the regional distribution of drugs in brain, but more information about transporter expression at the cell type level will be needed to estimate the effect of regional variability on brain pharmacokinetics and access of drugs to their target site.

The endothelial cells of the BBB and tight junctions expressed between these cells form the physical barrier for brain distribution of drugs. Since the brain microvessels comprise only 0.1% of brain weight and brain tissue contains many cell types (endothelial cells, astrocytes, microglial cells, neurons and pericytes), the alterations in gene and protein expression occurring solely in the microvessel endothelial cells can be interfered by other cell types. Therefore, further studies to reveal AD-induced changes in BBB protein expression were conducted by using brain microvessels isolated from APdE9 mice. The isolation of a microvessel enriched fraction is feasible only in young mice (≤12 weeks), whose brain pathology of AD is still developing. The normalized expressions of endothelial markers, Pecam1 and Cdh5, were about 3-fold lower in APdE9 compared to their healthy control mice, suggesting that APP and PSEN1 mutations may considerably affect the brain vasculature already during development or in young adulthood. Both increased and decreased vascular densities have been reported in AD (29).

The gene expression of Abcb1a was downregulated in the microvessel enriched fraction which is in line with the earlier reports from AD patients and animal models (8,10). Furthermore, Abcc4 and Abcg2 were downregulated. In order to assess the effect of AD pathology on efflux transporter function, MTX was selected as a model drug, because it has been previously demonstrated to cross the BBB via Mrp4 and Bcrp in a brain microdialysis study conducted in Mrp4 and Bcrp knock-out mice (23). Methotrexate is also a substrate for MDR1, OAT and OATP transporters (30–34). Since Abcb1a (Mrdr1a), Slac22a8 (Oat3) and Slco1a4 (Oatp1a4) were also downregulated in the microvessel enriched fraction, it is possible that these transporters participate in the distribution of methotrexate into the brain. As far as we are aware, this is the first study where AD-induced changes in brain unbound extracellular drug concentrations have been studied by pharmacokinetic microdialysis in the context of transporter function.

Brain microdialysis revealed that methotrexate gained faster access into the brain in 16–18 months old APdE9 mice after drug administration but the difference vs. wt controls diminished later. This finding may reflect alterations in the active transport in BBB or otherwise compromised BBB. Identification of functionally

altered transporter(s) is challenging due to overlapping substrate specificities and would require experiments with inhibitors. The consequences of BBB disruption, even when local or transient, can be harmful for the homeostasis of brain. Aβ has been reported to compromise BBB tight junction proteins and thus BBB integrity in human amyloid precursor protein transgenic mice (35) and human apoE4 transgenic mice (36). Generally, in tumor-bearing rats, a compromised BBB has been shown to increase brain extracellular MTX levels shortly after drug administration (37). However, Bien-Ly et al. (2015) reported recently that brain access of antibodies and radiotracers was not significantly altered in AD mouse models (38). Cheng et al. (2010) also reported that brain penetration of some small-molecule drugs was unaltered in AD-related animal models and Mehta et al. (2013) even found decreased brain uptake of transcellular permeability markers (diazepam and propranolol) in the 3xTg model possibly due to thickening of the basement membrane (16,39). Furthermore, imaging studies with AD patients have not found convincing evidence that AD alone, without a vascular component, causes BBB disruption (2). These discrepancies both in experimental models of AD and patients may partly be due to variation in the degree of AD pathology and the characteristics of the model drugs. Accumulation of Aβ plaques within the extracellular space, severe shrinkage of cerebral cortex and hippocampus, and an increase in the size of the ventricles in AD brains may affect the distribution of drugs in brain tissue. For a hydrophilic drug like methotrexate (LogD<sub>pH7.4</sub>-5.22, Chemspider, predicted using ACD/Labs), a smaller volume of extracellular fluid can lead to higher initial drug concentration in AD mice after a single systemic dose.

No significant differences were detected between <3 month old APdE9 mice and their controls at the protein level in the expression of Mdr1, Mrp4, Rage and Lrp1 in the microvessel enriched fraction. Earlier, Hartz et al. (2010) demonstrated that Mdr1 expression was decreased by approximately 60% and efflux of Mdr1 substrate NBD-CSA was reduced by 70% in brain capillaries of Tg2576 mice (8). Recently, Do et al. (2016) stated that Abcb1 and Abcg2 expressions in the brain capillary fraction of another AD model, 3xTg-AD were upregulated by 1.7-fold at 18 months of age, although younger mice (3 and 6 months) did not display significant changes (17). With the same AD model, Mehta et al. reported that cortical or hippocampal uptake of three Mdr1 substrates, digoxin, loperamide and verapamil, was not significantly altered in 18–20 month old 3xTg-AD mice (16). However, Mdr1 expression showed variability between replicates, ranging from a 42% reduction to no difference in 3xTg-AD compared to wt controls. These results demonstrate that alterations in efflux proteins, induced by AD-causing mutations, are minor in animal models but comparable to those encountered in human studies.

The expression level of transporters affects the maximum velocity of transport ($V_{max}$) and therefore, it can be assumed to reflect in transport function. A decrease in the transporter
expression is comparable to the inhibition kinetics of active
transport, where the degree of inhibition increases with inhib-
itor concentration (40). Should efflux transporter expression
decrease by 50%, this would cause at maximum a 2-fold in-
crease in the steady state drug concentration in the brain,
assuming that the drug passes through the BBB exclusively
via this specific transporter. Similarly, a 67% decline in ex-
pression would cause at maximum a 3-fold and an 80% de-
cline would evoke a maximum of a 5-fold increase in brain
drug concentration at steady state. If we consider the clinical
relevance of alterations detected in AD patients, mostly 2-fold
or smaller alterations for MDR1 have been observed. For
instance, when the activity of MDR1 was studied with PET
imaging, the binding potential of verapamil was found to be
modestly increased in AD patients (2.18 ± 0.25) compared to
healthy controls (1.77 ± 0.41) (14). In addition, the expression
of MDR1 was 25% lower in the blood vessels of AD patients
than age-matched controls when hippocampal sections were
studied by immunofluorescence (10). Accordingly, when
Kannan et al. recently studied transporter density in the vas-
cular space, they found that MDR1 global density was 53%
lower in the temporal CX of AD patients as compared to
controls, and in capillaries near to Aβ deposits, the MDR1
density was locally decreased by 35% (13). Our present results
with AD models are in line with these observations.
Therefore, in order that a detected approximately 2-fold
change in expression level should be clinically significant, the
drug should have an extremely narrow therapeutic level and
adverse effects in brain should be the dose-limiting factor, an
extremely rare situation for clinically used drugs (40). It should
be kept in mind that in addition to the expression level, trans-
porter functionality is also dependent on other factors such as
post-translational modifications and changes in membrane
composition, which may change in Alzheimer's disease and
affect binding affinity and transport activity. Furthermore,
binding to plasma proteins is an important factor influencing
drug distribution into the brain since only unbound drug is
able to cross the endothelial cell barrier. Disease states can
change the plasma protein binding, but thus far, no significant
changes in plasma protein content have been observed in AD
patients. In addition to the influence of disease, other factors
such as age and sex may affect transporter expression (41, 42).
However, in this study, we used age-matched controls of the
same gender in order to assess the effect of AD on drug
transporters.

In conclusion, transporter expression varied significantly
between brain areas in both transgenic AD mice and wt mice.
However, disease-induced alterations in transporter expres-
sion were low in all studied transgenic AD mouse models,
which accords with the current knowledge on disease-
induced changes in AD patients. Decreased expression of
some transporters and tight junction-associated proteins in
brain microvessel fraction of APdE9 mice as well as more

rapid brain access of MTX in APdE9 mice indicate that AD
pathology may contribute to the BBB functionality to some
extent.

ACKNOWLEDGMENTS AND DISCLOSURES

This study was funded by Academy of Finland (Grant number
257386). Finnish Cultural Foundation is also acknowledged
for financial support. KMK and TM acknowledges the
funding from the Academy of Finland and Sigrid Juselius
Foundation. We thank Dr. Aaro Jalkanen for advice in de-
signing microdialysis experiment, Prof. Seppo Auriola for
consultation in LC-MS/MS analysis and Lecturer Veli-
Pekka Ranta for advice regarding pharmacokinetics. Mrs.
Jaana Leskinen, Mrs. Leena Pietilä and Mrs. Lea Pirskanen
are acknowledged for technical assistance. The authors de-
clare that they have no conflict of interest. All applicable in-
ternational, national and institutional guidelines for the care
and use of animals were followed. All procedures performed
in studies involving animals were in accordance with the eth-
ical standards of the University of Eastern Finland or practice
at which the studies were conducted. This article does not
contain any studies with human participants performed by
any of the authors.

REFERENCES

1. Ballard C, Gauthier S, Corbett A, Brayne C, Aarsland D, Jones E. Alzheimer's disease. Lancet. 2011;377(9770):1019-31.

2. Erickson MA, Banks WA. Blood-brain barrier dysfunction as a cause and consequence of Alzheimer's disease. J Cereb Blood Flow Metab. 2013;33(10):1500-13.

3. Stieger B, Gao B. Drug transporters in the central nervous system. Clin Pharmacokinet. 2015;54(3):225-42.

4. Uchida Y, Ohtsuki S, Katsukura Y, Ikeda C, Suzuki T, Kamiie J, et al. Quantitative targeted absolute proteomics of human blood-brain barrier transporters and receptors. J Neurochem. 2011;117(2):333-45.

5. Agarwal S, Uchida Y, Mittapalli RK, Sane R, Terasaki T, Elmquist WF. Quantitative proteomics of transporter expression in brain capillary endothelial cells isolated from P-glycoprotein (P-gp), breast cancer resistance protein (Bcrp), and P-gp/Bcrp knock-out mice. Drug Metab Dispos. 2012;40(6):1164-9.

6. Geier EG, Chen EC, Webb A, Papp AC, Yee SW, Sadee W, et al. Profiling solute carrier transporters in the human blood-brain barrier. Clin Pharmacol Ther. 2013;94(6):636-9.

7. Nies AT, Jedlitschky G, Konig J, Herold-Mende C, Steiner HH, Schmitt HP, et al. Expression and immunolocalization of the multidrug resistance proteins, MRP1-MRP6 (ABCC1-ABCC6), in human brain. Neuroscience. 2004;129(2):349-60.

8. Hartz AM, Miller DS, Bauer B. Restoring blood-brain barrier P-glycoprotein reduces brain amyloid-beta in a mouse model of Alzheimer's disease. Mol Pharmacol. 2010;77(5):715-23.

9. Vogelgesang S, Cascorbi I, Schroeder E, Pahnke J, Kroemer HK, Siegmund W, et al. Deposition of Alzheimer's beta-amyloid is inversely correlated with P-glycoprotein expression in the brains of elderly non-demented humans. Pharmacogenetics. 2002;12(7):535-41.
10. Wijesuriya HC, Bullock JY, Faull RL, Hladky SB, Barrand MA. ABC efflux transporters in brain vasculature of Alzheimer's subjects. Brain Res. 2010;1358:228-38.

11. Jeynes B, Provias J. An investigation into the role of P-glycoprotein in Alzheimer's disease lesion pathogenesis. Neurosci Lett. 2011;487(3):389-93.

12. Carrano A, Snkhchyan H, Kooij G, van der Pol S, van Horssen J, Veerhuis R, et al. ATP-binding cassette transporters P-glycoprotein and breast cancer related protein are reduced in capillary cerebral amyloid angiopathy. Neurobiol Aging. 2014;35(3):565-75.

13. Kannan P, Schain M, Kretzschmar WW, Weidner L, Mitsios N, Gulyas B, et al. An automated method measures variability in P-glycoprotein and ABCG2 densities across brain regions and brain matter. J Cereb Blood Flow Metab. 2016;01:271678X16660984.

14. van Assema DM, Lubberink M, Bauer M, van der Flier WM, Schuit RC, Windhorst AD, et al. Blood-brain barrier P-glycoprotein function in Alzheimer's disease. Brain. 2012;135(Pt 1):181-9.

15. Xiong H, Callaghan D, Jones A, Bai J, Rasquinha I, Smith C, et al. ABCG2 is upregulated in Alzheimer's brain with cerebral amyloid angiopathy and may act as a gatekeeper at the blood-brain barrier for Abeta(1-40) peptides. J Neurosci. 2009;29(17):5463-75.

16. Mehta DC, Short JL, Nicolazzo JA. Altered brain uptake of therapeutics in a triple transgenic mouse model of Alzheimer's disease. Pharm Res. 2013;30(11):2868-79.

17. Do TM, Dodack A, Alata W, Calon F, Nicolic S, Scherrmann JM, et al. Age-dependent regulation of the blood-brain barrier influx/efflux equilibrium of amyloid-beta peptide in a mouse model of Alzheimer's disease (3xTg-AD). J Alzheimers Dis. 2016;49(2):287-300.

18. Jankowsky JL, Fadale DJ, Anderson J, Xu GM, Gonzales V, Jenkins NA, et al. Mutant presenilins specifically elevate the levels of the 42 residue beta-amyloid peptide in vivo: evidence for augmentation of a 42-specific gamma secretase. Hum Mol Genet. 2004;13(2):159-70.

19. Jankowsky JL, Slunt HH, Ratovitski T, Jenkins NA, Copeland NG, Borchelt DR. Co-expression of multiple transgenes in mouse CNS: a comparison of strategies. Biomol Eng. 2001;17(6):157-65.

20. Hsiao K, Chapman P, Nilsen S, Eckman C, Harigaya Y, Younkin S, et al. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science. 1996;274(5284):99-102.

21. Coisne C, Dehouck L, Faveeuw C, Delplace Y, Miller F, Landry C, et al. Mouse syngenic in vitro blood-brain barrier model: a new tool to examine inflammatory events in cerebral endothelium. Lab Investig. 2005;85(6):734-46.

22. Muller PY, Janovjak H, Miserez AR, Dobbie Z. Processing of gene expression data generated by quantitative real-time RT-PCR. BioTechniques. 2002;32(6):1372. -4, 1376, 1378-9

23. Sane R, Wu SP, Zhang R, Gallo JM. The effect of ABCG2 and ABCC4 on the pharmacokinetics of methotrexate in the brain. Drug Metab Dispos. 2014;42(4):537-40.

24. Pahnke J, Langer O, Krohn M. Alzheimer's and ABC transporters–new opportunities for diagnostics and treatment. Neurobiol Dis. 2014;72(Pt A):54-60.

25. Middeldorp J, Hol EM. GFAP in health and disease. Prog Neurobiol. 2011;93(3):421-43.

26. Loryan I, Melander E, Svensson M, Payan M, Konig F, Jansson B, et al. In-depth neuropharmacokinetic analysis of antipsychotics based on a novel approach to estimate unbound target-site concentration in CNS regions: link to spatial receptor occupancy. Mol Psychiatry. 2016;21(11):1527-36.

27. Kuntner C, Bankstahl JP, Bankstahl M, Stanek J, Wanek T, Stundner G, et al. Dose-response assessment of tariquidar and

elacridar and regional quantification of P-glycoprotein inhibition at the rat blood-brain barrier using (R)-[(11)G]verapamil PET. Eur J Nucl Med Mol Imaging. 2010;37(5):942-53.

28. Zhao R, Pollack GM. Regional differences in capillary density, perfusion rate, and P-glycoprotein activity: a quantitative analysis of regional drug exposure in the brain. Biochem Pharmacol. 2009;78(8):1052-9.

29. Brown WR, Thore CR. Review: cerebral microvascular pathology in ageing and neurodegeneration. Neuropathol Appl Neurobiol. 2011;37(1):56-74.

30. van de Steeg E, van der Kruijssen CM, Wagenaar E, Burggraaff JE, Mesman E, Kenworthy KE, et al. Methotrexate pharmacokinetics in transgenic mice with liver-specific expression of human organic anion-transporting polypeptide 1B1 (SLCO1B1). Drug Metab Dispos. 2009;37(2):277-81.

31. Badagnani I, Castro RA, Taylor TR, Brett CM, Huang CC, Stryke D, et al. Interaction of methotrexate with organic-anion transporting polypeptide 1A2 and its genetic variants. J Pharmacol Exp Ther. 2006;318(2):521-9.

32. Zhu Y, Meng Q, Wang C, Liu Q, Huo X, Zhang A, et al. Methotrexate-bestatin interaction: involvement of P-glycoprotein and organic anion transporters in rats. Int J Pharm. 2014;465(1-2):368-77.

33. Kanamitsu K, Kusuhara H, Schuetz JD, Takeuchi K, Sugiyama Y. Investigation of the importance of multidrug resistance-associated protein 4 (Mrp4/Abcc4) in the active efflux of anionic drugs across the blood-brain barrier. J Pharm Sci. 2017;106(9):2566-75.

34. Takeda M, Khamdang S, Narikawa S, Kimura H, Hosoyamada M, Cha SH, et al. Characterization of methotrexate transport and its drug interactions with human organic anion transporters. J Pharmacol Exp Ther. 2002;302(2):666-71.

35. Hartz AM, Khaer B, Soldner EL, Wolf A, Boy S, Backhaus R, et al. Amyloid-beta contributes to blood-brain barrier leakage in transgenic human amyloid precursor protein mice and in humans with cerebral amyloid angiopathy. Stroke. 2012;43(2):514-23.

36. Bell RD, Winkler EA, Singh I, Sagare AP, Deane R, Wu Z, et al. Apolipoprotein E controls cerebrovascular integrity via cyclophilin A. Nature. 2012;485(7399):512-6.

37. de Lange EC, de Vries JD, Zurcher C, Danhof M, de Boer AG, Breimer DD. The use of intracerebral microdialysis for the determination of pharmacokinetic profiles of anticancer drugs in tumor-bearing rat brain. Pharm Res. 1995;12(12):1924-31.

38. Bien-Ly N, Boswell CA, Jeet S, Beach TG, Hoyte K, Luk W, et al. Lack of widespread BBB disruption in Alzheimer's disease models: Focus on therapeutic antibodies. Neuron. 2015;88(2):289-97.

39. Cheng Z, Zhang J, Liu H, Li Y, Zhao Y, Yang E. Central nervous system penetration for small molecule therapeutic agents does not increase in multiple sclerosis- and Alzheimer's disease-related animal models despite reported blood-brain barrier disruption. Drug Metab Dispos. 2010;38(8):1355-61.

40. Kalvass JC, Polli JW, Bourdet DL, Feng B, Huang SM, Liu X, et al. Why clinical modulation of efflux transport at the human blood-brain barrier is unlikely: the ITC evidence-based position. Clin Pharmacol Ther. 2013;94(1):80-94.

41. Kelly SD, Harrell CS, Neigh GN. Chronic stress modulates regional cerebral glucose transporter expression in an age-specific and sexually-dimorphic manner. Physiol Behav. 2014;126:39-49.

42. Flores K, Manautou JE, Renfro JL. Gender-specific expression of ATP-binding cassette (Abc) transporters and cytoprotective genes in mouse choroid plexus. Toxicology. 2017;386:84-92.