Age, Inflammation, Blood Brain Barrier Permeability and Single...

Age, Inflammation, Blood Brain Barrier Permeability and Single Nucleotide

Polymorphisms in Transporters May Influence Cerebrospinal Fluid Antiretrovirals’

Concentrations

Calcagno A, Cusato J, Scarvaglieri E, Audagnotto S, De Nicolò A, Imperiale D, Mighetto L, D’Avolio A, Di Perri G, Bonora S.

19th International Workshop on Clinical Pharmacology of Antiviral Therapy, 22 - 24 May 2018, Baltimore, Maryland, USA

Potential relevance of CNS exposure of ARVs

Nightingale S, et al. Lancet Neurol 2014; Estes J, et al. Nature Med 2017

What did we learn in the past two years?


Curley P et al, AAC 2017; Thompson CG, et al. AAC 2015; Srinivas et al, IAS 2017, Abstract WEAB0105; Fletcher

CV, et al. PNAS 2014

1. Cerebrospinal fluid is a poor predictor of brain concentrations of different drugs• EFV Brain PK 3.7-12.7 times higher than plasma in a

macaque• EFV Brain PK to plasma ratios 9.5 (rodents) - 15.8 (PBPK

modelling) 2. CSF concentrations correlate with brain concentrations

• Individual PK in macaques3. Inflammation is associated with the induction of several

transporters involved in drug distribution• SIV infected animals have higher expression of P-gp and

BCRP4. Methods matter

• Tissue homogenate vs. mononuclear cells











AcknowledgementsWe acknowledge the following funding sources: RO1 GM66940, RO1GM09697, AFPE pre-doctoral fellowship and the Royster Society ofFellows

SHIV Infection and Drug Transporters Influences Brain Tissue Concentrations of EfavirenzN. Srinivas1, J. Fallon1, C. Sykes1, N. White1, A. Schauer1, Michelle Matthews1, L. Adamson2, P. Luciw2, P. Smith1, A.D.M. Kashuba1

1University of North Carolina, Chapel Hill, United States, 2University of California at Davis, Davis, United States,

• Despite antiretroviral (ARV) therapy, there is a high prevalenceof HIV-associated neurocognitive disorder (HAND) in HIV-infected individuals1.

• It has been theorized that inadequate ARV concentrations maycontribute to the persistence of HAND2. However, there is noconclusive relationship between ARV concentration in the CSFand HAND3,4. Concentration of ARVs in the brain may be amore accurate pharmacokinetic measure but the data on braintissue concentrations is sparse.

• This study compared the concentration of ARVs in four regionsof brain tissue with CSF in uninfected and SHIV-infected rhesusmacaques and investigated the effect of drug transporters oninfluencing ARV concentrations in brain tissue

Background

MethodsConcentration of ARVs in brain tissue and CSF• In 12 male macaques (6 uninfected and 6 SHIV-infected) dosed

to steady-state, concentrations of 6 ARVs –tenofovir (TFV),emtricitabine (FTC), efavirenz (EFV), raltegravir (RAL), maraviroc(MVC) and atazanavir (ATZ) were measured by LC-MS/MS in theCSF, where LLOQ was 0.5 ng/mL and in the frontal cortex,cerebellum, basal ganglia and parietal cortex regions of the brainwhere LLOQ of homogenate ranged from 0.002-0.01 ng/mL.

• Tissue concentrations were converted to ng/g using density of1.06.

Concentration of BCRP and P-gp in brain tissue• To assess the influence of drug transporters on ARV

concentration, protein was extracted from the brain tissue andanalyzed for Pgp and BCRP efflux transporter concentration byLCMS/MS proteomics method called Quantitative TargetedAbsolute Proteomics (QTAP)5. The LLOQ was 0.1 pMol/mgprotein).

Data Analysis• Statistical analysis was performed by Kruskal-Wallis test using

Sigmaplot®

Results

Conclusions and future directions

• Antiretroviral concentrations in brain tissue were significantly greater than CSF for TFV, FTC and EFV (Figure 1): ranging from 5-times (FTC)to 769-times (EFV) higher. Brain tissue concentration of EFV was 4.1 times higher in uninfected animals. Brain tissue concentrations ofefavirenz correlated with CSF over a range of concentrations (Figure 2).

• BCRP concentration (Figure 3) was 1.7 times higher in infected animals (p=0.02) while Pgp concentration did not differ with infection status(p=0.06). There was a trend noted for correlation between concentration of BCRP transporter and efavirenz in brain tissue (Figure 4).

• CSF concentrations need to be interpreted cautiously as surrogate for brain tissue concentration for several ARVs. Further, increase in BCRPconcentration may lead to lower EFV concentration in infected rhesus macaques.

• In future analyses, additional animals will be evaluated, and unbound concentration of EFV in brain tissue will be quantified since EFVexhibits a high degree of non-specific binding (>99.5%) in the brain tissue. Further investigations are needed to determine the influence ofbrain tissue concentrations on HAND

References1. Marra CM. HIV-associated neurocognitive disorders and central nervous system drug penetration: what next? AntivirTher. 2015. doi:10.3851/IMP2951.

2. Decloedt EH, Rosenkranz B, Maartens G, Joska J. Central Nervous System Penetration of Antiretroviral Drugs:Pharmacokinetic, Phharmacodynamic and Pharmacogenomic Considerations. Clin Pharmacokinet. 2015 Jun;54(6):581-98

3. Caniglia EC, Cain LE, Justice A, et al. Antiretroviral penetration into the CNS and incidence of AIDS-defining neurologicconditions. Neurology. 2014;83(2):134-141.

4. Scott Lentendre. Randomized Clinical Trial of Antiretroviral Therapy for Prevention of Hand (Oral Presentation). In: CROI2015..

5. Uchida Y et al. A study protocol for quantitative targeted absolute proteomics (QTAP) by LC-MS/MS: application forinter-strain differences in protein expression levels of transporters, receptors, claudin-5, and marker proteins at theblood–brain barrier in ddY, FVB, and C57BL/6J mice. Fluids Barriers CNS. 2013; 10: 21

Figure 1. Concentrations of Tenofovir, Emtricitabine, Efavirenz, Raltegravir,

Maraviroc and Atazanavir in brain tissue and CSF of rhesus macaquesFigure 3. Concentration of BCRP and P-gp transporter

proteins in brain tissue of rhesus macaques by QTAP

Figure 4.

Correlation

analysis between

brain tissue

concentration of

antiretroviral and

concentration of

BCRP transporter

protein in rhesus

macaques

Figure 2. Correlation between brain tissue and CSF

concentrations of Antiretrovirals

















Background







Sigmaplot®

Results














Figure 4.

Correlation

analysis between

brain tissue

concentration of

antiretroviral and

concentration of

BCRP transporter

protein in rhesus

macaques









Background







Sigmaplot®

Results














Figure 4.

Correlation

analysis between

brain tissue

concentration of

antiretroviral and

concentration of

BCRP transporter

protein in rhesus

macaques









Background







Sigmaplot®

Results














Figure 4.

Correlation

analysis between

brain tissue

concentration of

antiretroviral and

concentration of

BCRP transporter

protein in rhesus

macaques













Brain tissue homogenate Mononuclear cells extracted from tissues

Brain distribution is not homogeneous

Bumpus N, et al. CROI 2015 #436; Srinivas et al, CROI 2018 #472

nOverall

Mean

WM

(mean)

GP

(mean)

CGM

(mean)

Concentrations Similar to Historical CSF Concentrations

Atazanavir

(ATV)2 < 25 < 25 < 25 < 25

Efavirenz

(EFV)2 38.6 45.2 34.8 35.9

Emtricitabine

(FTC)4 181.3 230.4 173.2 140.3

Lamivudine

(3TC)3 196.9 205.5 209.8 175.4

Concentrations in White Matter Higher than Historical CSF

Concentrations

Lopinavir

(LPV)4 153.3 410.6 < 25 < 25

Concentrations Higher than Historical CSF Concentrations

Tenofovir

(TDF)6 206.0 220.0 212.1 185.8

WM = White Matter; GP = Globus Pallidus (Deep Gray Matter);

CGM = Cortical Gray Matter

Background

Despite ongoing antiretroviral (ARV) therapy, HIV inflammation continues to cause

issues in the central nervous system (CNS), as demonstrated by HIV-associated

neurocognitive disorder.1

HIV persistence in the brain may be due to inadequate drug exposure in HIV-target cells;

however, there is little information on brain distribution of ARVs.

In this study, we have quantified the concentration of 4 ARVs in brain tissue by liquid

chromatography mass spectroscopy (LC-MS/MS) and infrared matrix-assisted laser

desorption electrospray ionization (IR-MALDESI) while mapping their distribution

relative to expression of CD4+ T-cells and CD11b+ microglia.

Methods

Concentration of ARVsin cerebellum by LC-MS/MS

• Four male rhesus macaques were dosed to steady-state with a combination of 4

ARVs –tenofovir (TFV), emtricitabine (FTC), efavirenz (EFV) and raltegravir

(RAL). Two animals were left uninfected and two were infected with SHIV for 4

weeks prior to ARV dosing. Concentrations of the ARVs were measured by LC-

MS/MS2 in a 10 μm thick section of the cerebellum region of the brain tissue where

LLOQ of homogenate ranged from 0.002-0.01 ng/mL.

• Tissue concentrations were converted to ng/g using density of 1.06.

Massspectrometry imaging (MSI)

• 10 μm thick frozen slices of discrete cerebellum regions were thaw-mounted onto a

glass slide, covered with an ice layer and ablated with 2 mid-IR laser pulses with a

100 μm spot-to-spot distance.3,4 Ablated molecules were ionized by electrospray

and sampled into a Thermo Q-Exactive Plus mass spectrometer.

• Raw data from each volumetric pixel were converted to the imzMl format to

evaluate using MSiReader.5 Quantification of ARV concentration was achieved by

spotting calibration standards of known concentration onto a non-dosed tissue slice.

Immunohistochemistry (IHC) staining

• IHC staining of CD11b+ microglia and CD4+ T-cells was performed on contiguous

slices.

Imageanalysis

• Analysis of co-registered MSI and down-sampled IHC images was performed in

MATLAB®.

Conclusion and Future Directions

Figure 1. Cholesterol and efavirenz MSI in cerebellar

brain tissue in a) uninfected and b) RT-SHIV-infected

animals

Figure 2. Overlay between efavirenz MSI and CD11b+ cell distribution in the

cerebellum tissue in a) uninfected and b) RT-SHIV-infected animals

Distribution of EFV and CD11b+ cells in the cerebellum and the overlay of

distribution are shown in a) uninfected and b) RT-SHIV-infected animals.

Fractional coverage of the CD11b+ cells with EFV (FrC) was higher in the

uninfected animals compared to the RT-SHIV infected animals.

• EFV accumulation was 12- to 60-fold greater in brain tissue compared to other ARVs in RT-SHIV+ animals but only 14% to 59% of CD11b+ and CD4+ brain cells in these animals were colocalized with

detectable EFV.

• This low fractional coverage suggests that ARV exposure may be incomplete for cell populations that harbor, or can become infected, with HIV.

• This approach has the potential to provide ARV concentration-effect relationships in the brain at the cellular level with improvements in the spatial resolution of the MSI.

• TFV, FTC, and RAL were not detected by

MALDESI and were <100 ng/g by LC-MS/MS

(range of concentrations were 9.4-61.2 ng/g).

• EFV concentrations by IR-MALDESI had a

standard deviation of 663 ng/g for all samples and

was 86% lower in RT-SHIV-infected than

uninfected brain tissue (median = 1596 and 723

ng/g, respectively).

• EFV concentrations were up to 3-fold higher in the

white matter versus gray matter (Figure 1).

• The fractional coverage of CD11b+ cells co-

localized with EFV (FrC) differed based on

infection status: for CD11b+ cells FrC was 22-59%

(RT-SHIV+) and 76-81% (RT-SHIV-) and for

CD4+ T-cells FrC was 14-59% (RT-SHIV+) and

73-77% (SHIV-). However, FrC of total CD11b+

cells exposed to EFV concentrations above the

upper limit of the in-vitro IC50 reported from the

literature (0.5 ng/g) was considerably smaller: 0-

3.3%, regardless of infection status (Figure 2).

• Overlay results between the EFV concentration

above the IC50 and CD4+ T-cell distribution

showed a similarly low FrC.

1.Marra CM. Antivir. Ther., 2015; 20(4): 365-367.

2.Srinivas N, Fallon JK, Sykes C, White N, et al. 9th International AIDS Society Conference on HIV Sciences 23-26 July 2017: Abstract WEAB0105.

3.Barry JA, Robichaud G, Bokhart MT, Thompson C, Sykes C, Kashuba AD et al. J. Am. Soc. Mass Spectrom., 2014; 25(12): 2038–2047.

4.Thompson CG, Bokhart MT, Sykes C, Adamson L, Fedoriw Y, Luciw PA, Muddiman DC, et al. Antimicrob. Agents Chemother., 2015; 59(5): 2944–2948.

5.Robichaud G, Garrard KP, Barry JA, and Muddiman DC, J. Am. Soc. Mass Spectrom., 2013; 24(5):718–721.

Acknowledgements

We acknowledge the following funding sources: the National Institutes of Health

under grants: RO1 AI111891, S10 RR024595, RO1 GM66940, RO1 GM09697,

the UNC center for AIDS research under grant: P30 AI50410, AFPE pre-doctoral

fellowship and the Royster Society of Fellows, UNC Chapel Hill.

Mapping the Distribution of Efavirenz Relative to Brain CellsN. Srinivas1, E. P. Rosen1, G. De La Cruz1, C. Sykes1, A. Schauer1, L. Adamson2, P. Luciw2, A.D.M. Kashuba1

1University of North Carolina, Chapel Hill, United States. 2University of California at Davis, Davis, United States.

Results

Ion maps of cholesterol (left) indicate distinction between

white matter (WM) and gray matter (GM) in the brain tissue.

The EFV heat maps (right) show the amount of efavirenz per

voxel based on accompanying scale bar. (a) In the uninfected

animals, clear preferential distribution of efavirenz was noted

in the WM compared to the GM (b) In RT-SHIV-infected

animals, efavirenz concentrations were 86% lower.

References

Poster Number 472

Background










Methods



















slices.

Image analysis


MATLAB®.




animals








detectable EFV.































Acknowledgements







Results








References

Poster Number 472

EFV up to 3-fold higher in the WM vs. GM

22-59 of CD11b+

microglialcells with EFV and only 3.3

with EFV>0.5

ng/g

Background










Methods



















slices.

Image analysis


MATLAB®.




animals








detectable EFV.































Acknowledgements







Results








References

Poster Number 472

Background










Methods



















slices.

Image analysis


MATLAB®.




animals








detectable EFV.































Acknowledgements







Results








References

Poster Number 472

Aim of the study

• To characterize ARVs’ cerebrospinal fluid concentrations according to patients’ demographic, treatment and genetic features

• HIV-positive patients receiving lumbar punctures for clinical reasons and participating to specific study protocols were included after signing a written informed consent.

• CSF and plasma were withdrawn less than 15 minutes apart and analyzed using validated HPLC/MS-MS methods.

• BBB permeability was estimated using Reibergrams(CSAR) and CSF neopterin trough ELISA methods.

• Multivariate linear regression analysis were performed including age, CSAR, CSF neopterin and plasma concentrations besides SNPs with univariate p values <0.20.

Material and Methods

BBB impairment

Intrathecalproduction of IgGs

• Genomic DNA was extracted using QIAamp whole blood mini kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s instructions. Genotyping was conducted by real time-based allelic discrimination

• including the following SNPs:– ABCB1 (rs1045642, rs1128503,

rs2032582),– ABCC2 (rs717620), – SLC22A6 (rs4149170), – SLCO1A2 (rs10841795, rs11568563), – ABCG2 (rs2231142, rs13120400), – HNF4α (rs1884613).

Material and Methods (PG)

abundantly expressed in the kidney, with only modest or low expression in the liver. In

contrast, OCTN2 (SLC22A5) and OAT2 (SLC22A7) were highly expressed in both kidney

and liver. OCT1 (SLC22A1) was most strongly expressed in the liver and OCT3

(SLC22A3) in the prostate, salivary gland and skeletal muscle. Expression of the

concentrative and equilibrative nucleoside transporters (CNTs, ENTs) was ubiquitous,

with the exception of CNT3 (SLC28A3), which was restricted to pancreas and skin, with

lower levels detected in mammary gland, jejunum and foetal liver.

ABCB1 (MDR1)ABCB4 (MDR3)

ABCB11 (BSEP)ABCC1 (MRP1)ABCC2 (MRP2)ABCC3 (MRP3)ABCC4 (MRP4)ABCC5 (MRP5)ABCC6 (MRP6)

ABCC10 (MRP7)ABCC11 (MRP8)ABCC12 (MRP9)ABCG2 (BCRP)

OSTalphaSLC10A1 (NTCP)SLC10A2 (ASBT)

SLC15A1 (PEPT1)SLC15A2 (PEPT2)SLC16A1 (MCT1)SLC16A7 (MCT2)SLC17A1 (NaPi1)SLC22A1 (OCT1)SLC22A2 (OCT2)SLC22A3 (OCT3)

SLC22A4 (OCTN1)SLC22A5 (OCTN2)

SLC22A6 (OAT1)SLC22A7 (OAT2)SLC22A8 (OAT3)

SLC22A11 (OAT4)SLC22A12 (URAT1)

SLC28A1 (CNT1)SLC28A2 (CNT2)SLC28A3 (CNT3)SLC29A1 (ENT1)SLC29A2 (ENT2)SLC29A3 (ENT3)SLC29A4 (ENT4)

SLC6A14 (ATB(0+))SLCO1A2 (OATP-A)SLCO1B1 (OATP-C)SLCO1B3 (OATP-8)SLCO1C1 (OATP-F)

SLCO2A1 (PGT)SLCO2B1 (OATP-B)SLCO3A1 (OATP-D)SLCO4A1 (OATP-E)SLCO4C1 (OATP-H)SLCO5A1 (OATP-J)SLCO6A1 (OATP-I)

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Figure 1. Average absolute gene-expression intensity of multiple probes for human xenobiotictransporter genes. White represents missing data due to erroneous measurements. Percentiles arebased on a reference set of intensities of 19 000 genes in over 100 tissues.

Tissue distribution of transporter genes 971

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abundantly expressed in the kidney, with only modest or low expression in the liver. In

contrast, OCTN2 (SLC22A5) and OAT2 (SLC22A7) were highly expressed in both kidney

and liver. OCT1 (SLC22A1) was most strongly expressed in the liver and OCT3

(SLC22A3) in the prostate, salivary gland and skeletal muscle. Expression of the

concentrative and equilibrative nucleoside transporters (CNTs, ENTs) was ubiquitous,

with the exception of CNT3 (SLC28A3), which was restricted to pancreas and skin, with

lower levels detected in mammary gland, jejunum and foetal liver.

ABCB1 (MDR1)ABCB4 (MDR3)

ABCB11 (BSEP)ABCC1 (MRP1)ABCC2 (MRP2)ABCC3 (MRP3)ABCC4 (MRP4)ABCC5 (MRP5)ABCC6 (MRP6)

ABCC10 (MRP7)ABCC11 (MRP8)ABCC12 (MRP9)ABCG2 (BCRP)

OSTalphaSLC10A1 (NTCP)SLC10A2 (ASBT)

SLC15A1 (PEPT1)SLC15A2 (PEPT2)SLC16A1 (MCT1)SLC16A7 (MCT2)SLC17A1 (NaPi1)SLC22A1 (OCT1)SLC22A2 (OCT2)SLC22A3 (OCT3)

SLC22A4 (OCTN1)SLC22A5 (OCTN2)

SLC22A6 (OAT1)SLC22A7 (OAT2)SLC22A8 (OAT3)

SLC22A11 (OAT4)SLC22A12 (URAT1)

SLC28A1 (CNT1)SLC28A2 (CNT2)SLC28A3 (CNT3)SLC29A1 (ENT1)SLC29A2 (ENT2)SLC29A3 (ENT3)SLC29A4 (ENT4)

SLC6A14 (ATB(0+))SLCO1A2 (OATP-A)SLCO1B1 (OATP-C)SLCO1B3 (OATP-8)SLCO1C1 (OATP-F)

SLCO2A1 (PGT)SLCO2B1 (OATP-B)SLCO3A1 (OATP-D)SLCO4A1 (OATP-E)SLCO4C1 (OATP-H)SLCO5A1 (OATP-J)SLCO6A1 (OATP-I)

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Figure 1. Average absolute gene-expression intensity of multiple probes for human xenobiotictransporter genes. White represents missing data due to erroneous measurements. Percentiles arebased on a reference set of intensities of 19 000 genes in over 100 tissues.

Tissue distribution of transporter genes 971

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Results

• 259 patients providing 405 paired CSF/plasma samples

• Asymptomatic (29.6%), HAND (21.5%), CNS Opportunistic infections or neoplasms (17.8%) or White matter hyperintensities (4.2%)

• Altered BBB (<6.5 if age <=40, <8 if >40) in 21.5%

• High CSF neopterin (>1.5 ng/mL) in 24.4%

N or median

or IQR

Male 185 71.4

European Ancestry

194 74.9

Age 48 41-55

BMI 22.4 20.1-24.6

CD4 321 145-549

Nadir CD4 97 24-208

Plasma VL<50 267 68.8

CSF VL<50 228 60.5

Results (2)

n 57 34 12 107 104 9 14 14 6 28 78 31 116 4 21 80 4 12

Q1 75 18 6,8 0 57 269 25 5,4 1 13 14 1,9 0 2,3 0,41 19 2,6 3,3

Med 122 88 15 5 103 1062 41 17 2 25 29 7,2 0,36 6,5 2,2 30 3,9 6,5

Q3 162 234 35 10 155 3051 82 23 3 49 47 22 0,90 7,8 5,5 57 5,7 11

3TC

ABC

AZT

TFVFTC

NVP

EFVETV

RPV

LPVDRV

ATV

RTV

CO

BM

VCRAL

EVG

DTG

1

10

100

1000

10000

CS

F c

on

ce

ntr

atio

ns

(L

og

10 n

g/m

L)

CSF concentrations below the LOD were observed

in patients receiving

TDF31.8%

AZT16.8%

ATV12.9%

RTV28.4%

n 54 33 12 99 102 9 13 14 6 28 77 31 112 4 19 64 4 11

Q1 (%) 18 38 4,6 0 16 4 0,8 0,8 1 0,1 0,4 0,5 0 0,6 0,4 2,2 0,4 0,3

Med (%) 37 92 97 7,7 39 45 1,5 2,7 1,3 0,3 0,7 1,3 0,1 8,9 2,4 12 0,4 0,6

Q3 (%) 58 200 150 20 54 51 2,8 3,6 1,7 0,8 1,1 1,4 0,3 28 5,8 27 0,4 1

Results (3)

3TC

ABC

AZT

TFVFTC

NVP

EFVETV

RPV

LPVDRV

ATV

RTV

CO

BM

VCRAL

EVGDTG

0.001

0.010

0.100

1

10

CS

F to

pla

sm

a r

atio

s

CSF to plasma correlations

0 500 1000 15000

1000

2000

3000

4000

5000

NRTIs

CSF concentrations

Pla

sm

a c

on

ce

ntra

tio

ns

0 50 100 150 2000

5000

10000

15000

20000

25000

PIs

CSF concentrations

0 1000 2000 3000 4000 50000

2000

4000

6000

8000

10000

NNRTIs

CSF concentrations

Pla

sm

a c

on

ce

ntra

tion

s

0 100 200 3000

5000

10000

15000

20000

25000

CSF concentrations

INSTIs

Rho=0.78P<0.001

Rho=0.72P<0.001

Rho=0.18P=0.115

Rho=0.52P<0.001

A

g

e

NNRTIsNRTIs

INSTIsPIs

BBB and inflammationrho= 0.178, p=0.002

NRTIs

p=0.003

INSTIs

p=0.012

PIs

p=0.088

rho= 0.235, p=0.034

Single nucleotide polymorphisms

NRTIs PIs INSTIs

CSF CPR CSF CPR CSF CPR

ABCB1

rs1045642

rs1128503

rs2032582

ABCC2 rs717620 0.043

SLC22A6 rs4149170 0.065

SLCO1A2rs10841795

rs11568563

ABCG2rs2231142

rs13120400

HNF4α rs1884613 0.020

p value set at 0.005

CSF NRTIs CSF PIs CSF INSTIs

Model1

R2=0.297

p<0.001

Model2

R2=0.353

p<0.001

Model1

R2=0.333

p<0.001

Model2

R2=0.341

p<0.001

Model1

R2=0.450

p<0.001

Model2

R2=0.173

P=0.029

Age

1 year increase0.018 0.003 0.108 0.099 0.913 0.968

CSAR

1 unit increase0.068 0.046 0.998 - 0.350 0.437

Neopterin

1 ng/mL increase0.661 0.771 <0.001 <0.001 0.757 -

Plasma conc.

1 ng/mL increase<0.001 <0.001 0.001 0.001 <0.001 0.020

PI coadministration

yes vs. no0.778 0.397 - - - -

SLCO1A2 516

AC vs. AA- 0.052 - - - -

ABCG2 421

CA/AA vs. CC- 0.014 - - - -

ABCC2 -24

AA/AC vs. CC- - - - - 0.056

Multivariate Linear Regression Analysis

Conclusions

• Several limitations including heterogeneous time after dosing (however mostly “flat” CSF PK), a limited number of samples (NNRTIs and EVG) and different drugs within the same class

• A significant variability in CSF concentrations was explained by plasma concentrations, age/BBB permeability (NRTIs) and CSF immune activation (PIs)

Conclusions and Discussion

• The effect of SNPs in transporters was small but including ABCG2 (BCRP) improved the model performance for NRTIs

• The effect of immune activation, BBB permeability and SNPs needs to be considered when modelling antiretrovirals’ exposure in the CNS

Acknowledgements

Prof. G Di PerriProf. S BonoraLaura TrentiniCristina TettoniRoberto BertucciSabrina AudagnottoLetizia MarinaroIlaria MottaAlice TrentalangeElisabetta ScarvaglieriElisa ScabiniChiara Cardellino

Antonio D’AvolioJessica CusatoMarco SimieleAmedeo de Nicolò

Daniele ImperialeCristiana AtzoriDaniela VaiAlessandra Romito

Prof. P CassoniLuca Bertero Consuelo Valentini

Prof. R SwanstromSarah B JosephLaura P Kincer

Enrica AmasioSebastiano Catera

Valeria GhisettiTiziano Allice

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