W Heuer

M Stiesch

Dr Wolf-Rainer R Abraham
email: rainer.abraham@helmholtz-hzi.de

Microbial diversity of supra-and subgingival biofilms on freshly colonized titanium implant abutments in the human mouth

Keywords: Oral implants, single strand conformation polymorphism, microbial diversity, implant abutments, biofilm, microbial communities

Microbial diversity of supra-and subgingival biofilms on

freshly colonized titanium implant abutments in the human mouth

Introduction:

The clinical success of osseointegrated oral implants led to extended application. Today many conventionally prosthetic treatments have been replaced by implant supported prosthetic supraconstructions.

From a clinical viewpoint this fact is supported by multitudinous studies which analyzed structural and functional improvements of the implant surface. While the problem of primary osseointegration is solved in a high quality manner, inflammation of peri-implant tissues by the presence of bacterial biofilms is considered currently as one of the principle problems in oral implantation and, therefore, responsible for early implant failure. This early implant failures are clinically characterized by inflammation of the peri-implantary mucosa (Figure 1a) and a subsequent destruction of the peri-implantary bone (Figure 1b).

The early processes of biofilm formation, like generation of an acquired pellicle by salivary biopolymers or enzymes and adherence of initial microorganisms, is described as is the relationship between biofilm formation and periodontitis or periimplantitis. For example, Streptococcus mitis, S. sanguinis and S. oralis are known to create the pre-conditions for the accumulation of gram-negative anaerobic bacteria [START_REF] Slots | The predominant cultivable microflora of advanced periodontitis[END_REF][START_REF] Loe | Experimental gingivitis in man[END_REF][START_REF] Quirynen | Clinical relevance of surface characteristics on the formation of plaque on teeth and implants[END_REF][START_REF] Hannig | Transmission electron microscopic study of in vivo pellicle formation on dental restorative materials[END_REF][START_REF] Slots | Microflora in the healthy gingival sulcus in man[END_REF].

Several studies were able to indicate, that during periimplant biofilm formation the microbial composition shifted towards a higher proportion of such gram-negative anaerobic microbiota [START_REF] Berglundh | Enhanced gingivitis in the deciduous and permanent dentition. An experimental study in the dog[END_REF][START_REF] Berglundh | Soft tissue reaction to de novo plaque formation on implants and teeth. An experimental study in the dog[END_REF][START_REF] Leonhardt | Putative periodontal pathogens on titanium implants and teeth in experimental gingivitis and periodontitis in beagle dogs[END_REF][START_REF] Ericsson | Long-standing plaque and gingivitis at implants and teeth in the dog[END_REF][START_REF] Abrahamsson | Soft tissue response to plaque formation at different implant systems. A comparative study in the dog[END_REF]. However, these previously studies of microorganisms associated with diseases relied heavily upon cultivation or DNA checkerboard hybridization methods. The applied techniques are associated with the main disadvantages of a specific bacterial identification or time-consuming and fault-prone cultivation [START_REF] Lau | Quantitative real-time polymerase chain reaction versus culture: a comparison between two methods for the detection and quantification of Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis and Tannerella forsythensis in subgingival plaque samples[END_REF]. This led to the identification of several species as putative periodontopathogens based on frequency of their isolation in lesion sites. Among these are Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Prevotella intermedia, Bacteroides forsythus, Treponema denticola, Fusobacterium nucleatum, Parvimonas micra, Campylobacter rectus, Eikenella corrodens and Selenomonas sputigena [START_REF] Slots | New views on periodontal microbiota in special patient categories[END_REF][START_REF] Socransky | The bacterial etiology of destructive periodontal disease: current concepts[END_REF][START_REF] Wolff | Bacteria as risk markers for periodontitis[END_REF][START_REF] Socransky | Microbial complexes in subgingival plaque[END_REF]. However, concentrating only on those bacteria which can currently be cultivated and ignoring particularly those which cultivation fails to capture [START_REF] Li | Survey of oral microbial diversity using PCR-based denaturing gradient gel electrophoresis[END_REF] will not give a complete picture of infections leading to periodontitis or periimplantitis [START_REF] Kroes | Bacterial diversity within the human subgingival crevice[END_REF]. Because of these limitations, it is also difficult to acquire a complete understanding of the dynamic changes of oral microbes as dental biofilms turn from harmless ones into detrimental microbial communities. Answers to this challenge are cultureindependent methods to monitor microbial communities over space and time.

Therefore, the objective of the present study was to assess the diversity of microbial communities, by culture-independent methods, of initial periimplant biofilms in supra-and subgingival areas, to compare them with those of the sulcus fluid and to identify microbial communities posing potential problems for infections. In addition, a sample of sulcusfluid was taken at one remaining tooth in the same jaw to evaluate cross-infections between implants and teeth in the initial phase of biofilm formation.

Material and methods:

Subjects:

The present study was approved by the ethics committee of Hannover Medical School (No. 3791). The examination was performed with the understanding and written consent of each patient.

Qualitative analysis was based on 10 healing abutments which were inserted for 14 days into 10 patients, 6 women and 4 men, aged between 60 and 83 years (mean 70 years ± 6.7 years). Patients were selected to fulfil the following inclusion criteria: no systemic illness, no smoking, no pregnancy, no active periodontitis (probing pocket depth ≤ 4 mm), no pharmacological treatment or antibiotic therapy during or up to four months before the study. At the day of abutment insertion all patients received dental hygiene instructions but no professional tooth cleaning was performed during the observation period.

All patients were partially edentulous and had at least one oral two-piece implant made of titanium (Astra Tech, Mölndal, Sweden), which had been inserted three months before investigation. Two weeks after abutment surgery, the previously existing abutments were removed and new sterile healing abutments (Astra Tech, Mölndal, Sweden) for the analysis were inserted (Figure 2). Thereby no trimming of surrounding gingiva was performed.

Sampling:

Two weeks after insertion of the new sterile healing abutments, samples of adherent biofilm and crevicular fluid were taken. The periimplant saliva was removed by use of an air spray and cotton rolls. First, samples of crevicular fluid were taken with sterile paper points at abutments and remaining teeth. Afterwards, samples of adherent supragingival biofilm on the abutments were taken with sterile sponges. The samples of adherent subgingival biofilm could be collected after abutment removal. All samples were stored in sample tubes (Eppendorf AG) at -80 °C.

DNA analysis:

DNA was extracted using the Fast-DNA-Spin-Kit for soil (Bio 101, CA, USA) following the instructions of the manufacturer. The primers chosen for the amplification of bacterial 16S rRNA genes were forward primer Com1 (5'CAGCAGCCGCGGTAATAC3') and reverse primer Com2-Ph

(5'CCGTCAATTCCTTTGAGTTT3' with 5'-terminal phosphate group) as published by Schwieger and Tebbe [START_REF] Schwieger | A new approach to utilize PCR-single-strand-conformation polymorphism for 16S rRNA gene-based microbial community analysis[END_REF]. To obtain single-stranded DNA the phosphorylated strand of the PCR products was digested by lambda exonuclease (New England Biolabs, Schwalbach, Germany) following the protocol of Schwieger and Tebbe, and further purified using the Mini-elute-Kit (Qiagen, Hilden, Germany) as recommended by the manufacturer, and the remaining single stranded DNA was dried under vacuum. The DNA was then resuspended in denaturating SSCP loading buffer (47.5 % formamide, 5 mM sodium hydroxide, 0.12 % bromophenol blue and 0.12 % xylene cyanol), incubated at 95°C for 2 min and immediately cooled on ice. After 5 min, samples were loaded onto the gels and subjected to electrophoresis. The samples were electrophoresed in a MDE gel (9 ml 2x MDE (FMC Bioproducts, Rockland, Maine), 3 ml 10x TBE buffer, 18 ml bidest. water, 10% APS 120 µl and 12 µl TEMED).

Gels (21 cm) were cast (spacers of 0.5 mm) and run with 1x TBE buffer. Gels were run at 400 V for 16 h at 20°C in a Macrophor electrophoresis unit (LKB Bromma, Sweden) and subsequently silver stained [START_REF] Bassam | Fast and sensitive silver staining of DNA in polyacrylamide gels[END_REF].

Sequence analysis:

Single bands were excised from the gels and eluted in extraction-buffer (10 mM Tris-buffer, 5 mM KCl, 1.5 mM MgCl2 x 6 H2O, 0.1 % Triton X 100, pH 9.0) at 95°C for 15 min. Extracts were centrifuged (12000 x g, 1 min) and the DNA in the supernatant fluid was used for PCR with the primers described above. The PCRproduct was cleaned (Mini-elute-Kit, Qiagen, Hilden, Germany) and sequenced with a sequencing kit (DYEnamic ET Terminator cycle sequencing kit by Amersham Biosciences, Freiburg, Germany) and both primers. The product was cleaned with the Dye Ex Spin Kit (Qiagen, Hilden, Germany) and the sequence analyzed on an ABI PRISMTM 337 DNA-Sequencer and 3100 Genetic Analyser. Comparisons of the sequences were performed using the BLAST program and the databases of EMBL [START_REF] Cochrane | Nucleic aids research database issue and online database collection: a community of data resources[END_REF] and GenBank [START_REF] Benson | GenBank[END_REF]. The phylogenetic analysis was done using the MUSCLE version 3.6 software for sequence alignments [START_REF] Edgar | MUSCLE: multiple sequence alignment with high accuracy and high throughput[END_REF]. Tree topologies were reconstructed with neighbour-joining algorithm (complete deletion of gaps/missing data, maximum composite likelihood model, bootstrap: 1000 replicates) (Figure 3) with the software MEGA 4 [START_REF] Kumar | MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences[END_REF].

All reference sequences used in the tree are from validated bacterial species: each has been cultured, characterized, deposited with at least two recognized culture collections, and named under the procedure described in the International Bacteriological Code of Nomenclature (ICNB), 1990 revision [START_REF] Sneath | International code of nomenclature of bacteria: bacteriological code, 1990 revision[END_REF].The sequences of the oral rDNA bands obtained from patients 1 to 10 (31 sequences, indicated in Figure 3) have been deposited

in the GenBank database under accession numbers FN870024-FN870053 and FR666873.

Statistics:

Statistical analyses were done using the STATISTICA 6 software. For correlation analysis and discriminate analysis the presence/absence of a species was used. Discriminant analysis was performed applying the forward stepwise method setting the tolerance to minimum (10 -10 ).

Results

All samples showed a large number of SSCP-bands and, hence, possess a high diversity of bacteria varying between patients and within one patient with location (Figure 4). Sequence analyses of 101 SSCP-bands led to the identification of 31 different bacterial taxa belonging to 5 different bacterial phyla (Firmicutes, Actinobacteria, Proteobacteria (Beta-, Gamma-and Epsilon-), Bacteroidetes and Fusobacteria). Remarkable were the diversity of Veillonella, Streptococcus, Parvimonas, Fusobaterium and Neisseria species detected.

Species have only been identified down to the species level if they matched exactly with the sequence of the type strain (Figure 3). In the genus Veillonella gene sequences matching those of Veillonella parvula (Veillonella which is known to have many interactions with other bacteria in dental plaques, but we found only a significant correlation between its occurrences with the two Campylobacter species.

We addressed the question whether the microbial communities are controlled by the individual host or the environment controls the composition of the community. To achieve this goal we used the bacteria detected in a sample to discern between the different types of samples. Discriminant analysis is used to find a combination of features (here bacteria species) which characterize or separate classes of objects (here sampling sites or patients). The resulting combination can be used to reduce the dimensionality. We applied discriminant analyses to identify such correlations and could not find microbial communities specific for the individual patients (data not shown). However, discriminant analyses identified occurrences of Lactobacillus delbrueckii Neisseria mucosa 133-2 were characteristic for the supragingival microbial communities, while those of the sulcusfluid from the abutments were characterized by the presence of Burkholderia sp. 113-1 (Figure 5a). In figure 5b the contribution of every discriminative strain to the plot shown in figure 5a was plotted for the first two coefficients factors. This presentation allows the fast identification of strains to a given sample set, e. g.

Parvimonas micra 52-1 and Neisseria mucosa 133-2 contributed most to supragingival biofilms while Parvimonas sp. 72-1 was characteristic for subgingival biofilms. For the sulcusfluid from the residual teeth no discriminative bacteria could be identified as expected from the central position of this group in figure 5a.

Comparing the sulcusfluid around the abutments and around the residual teeth only small differences in the microbial diversity was seen. One remarkable difference, however, was the higher diversity and the much higher frequency of Streptococcus sequences found in the sulcusfluid around the abutments compared to that from residual teeth.

Discussion

The use of healing abutments to study the microbial diversity of initial biofilms on oral implant abutments using an unspecific molecular biological detection method allows an in-vivo analysis of biofilms in supra and subgingival areas along oxic-anoxic gradients. The anaerobic environment enables realistic formation of the same biofilm as during development of mucositis or periimplantitis. The advantage to remove healing abutments atraumatically for sampling adherent bacteria in subgingival areas without contaminating the sample with supragingival microbiota was an important precondition for a realistic comparison of supra-and subgingival biofilm compositions. In the present study a short term investigation of biofilm formation on healing abutments was performed over a period of 14 days. The analysis was performed over this specific period to display the realistic and typical microorganisms in the initial phase of biofilm formation. Furthermore previous investigations approved microbiota around implants to remain unchanged for six months after a comparable period [START_REF] Boever | Early colonization of non-submerged dental implants in patients with a history of advanced aggressive periodontitis[END_REF]. In recent studies, a similar method directed to the typical periodontal pathogens Aggregatibacter actinomycetemcomitans or Porphyromonas gingivalis in the periimplant crevicular fluid was used [START_REF] Elter | Supraand subgingival biofilm formation on implant abutments with different surface characteristics[END_REF][START_REF] Heuer | Analysis of early biofilm formation on oral implants in man[END_REF].

However, structural differences between healing abutments and implant retained prostheses have to be considered while interpreting the results. Implant anchored prostheses like crowns or bridges exhibit an anatomic form with typical plaque retentive sites. Furthermore, a gap between the definitive abutments and the dental prostheses can boost the biofilm formation because of their modular configuration. However, an analysis of initial adherent biofilms along oxic-anoxic gradients is not possible with implant retained dental prostheses because sampling of adherent bacteria in subgingival areas without removal of the construction is leading to a contamination with supragingival microbiota in the majority of cases.

In the present study several species of the genera Veillonella, Streptococcus, Parvimonas, Fusobaterium and Neisseria were detected all of them well known from dental plaques. Not all of them fitted to the 16S rRNA gene sequences reported from the type strains of accepted species. However, the identification of the Veillonella species is complicated as it has been reported that as least some Veillonella species have a rather high intrachromosomal heterogeneity between their four rRNA gene copies [START_REF] Marchandin | Intra-chromosomal heterogeneity between the four 16S rRNA gene copies in the genus Veillonella: implications for phylogeny and taxonomy[END_REF]. No Streptococcus mutans sequences were found, however, the essential role of Streptococcus mutans in the caries process has been questioned [START_REF] Beighton | The complex oral microflora of high-risk individuals and groups and its role in the caries process[END_REF] as some strains of Streptococcus oralis exhibited levels of caries induction in rats that were close to those of Streptococcus mutans [START_REF] Willcox | Relative cariogenicity and in-vivo plaque-forming ability of the bacterium Streptococcus oralis in gnotobiotic WAG/RIJ rats[END_REF]. Streptococci are the principal group of the early colonizing bacteria showing interactions with a number of other bacteria. One example is a metabolic interaction with Veillonella species, which coaggregate with Streptococci [START_REF] Hughes | Characterization of Veillonella atypica PK1910 adhesin-mediated coaggregation with oral Streptococcus spp[END_REF]. In this food chain Veillonella uses lactic acid produced by the Streptococci as an end product of carbohydrate fermentation [START_REF] Mikx | Symbiosis of Streptococcus mutans and Veillonella alcalescens in mixed continuous cultures[END_REF]. Streptococcus species were detected in 75%

and Veillonella species in 50% of the patients. Only in one patient no Streptococcus but Veillonella parvula could be found.

Species of the genus Fusobacterium are obligate anaerobes and implicated in the pathogenesis of periodontal disease. However, this organism has also been frequently identified in high numbers in healthy adults. Consequently it was found in six out ten patients. The diversity of Fusobacterium species between the different patients and also between the different locations was high. Such diversity has also been observed at the clonal level of F. nucleatum isolates [START_REF] Suchett-Kaye | Clonal analysis by ribotyping of Fusobacterium nucleatum isolates obtained from healthy young adults with optimal plaque control[END_REF]. Interestingly, in this study also a large dynamic between the clones could be shown. Furthermore, it is known from F. nucleatum that is a typically middle colonizer of dental surfaces showing many interactions with the surrounding bacteria cells [START_REF] Periasamy | Central role of early colonizer Veillonella sp. in establishing multispecies biofilm communities with initial, middle and late colonizers of enamel[END_REF]. Both observations can explain the diversity observed in our study but not the absence of Fusobacterium strains in some patients. This finding points to alternative routes to anaerobic communities and plaque formation not involving Fusobacterium.

Well known primary colonizers are species of the genus Neisseria and found in the majority of the patients but in two out of ten patients they could not be detected. Again it is reasonably to assume that Neisseria is not essential for the primary colonization of dental implants and can be substituted by other species. In addition to Neisseria many of the bacteria identified in this study including the Burkholderia species were also reported from the initial colonization of enamel [START_REF] Diaz | Molecular characterization of subject-specific oral microflora during initial colonization of enamel[END_REF], childhood caries [START_REF] Becker | Molecular analysis of bacterial species associated with childhood caries[END_REF] and in periodontal pockets [START_REF] Paster | Bacterial diversity in human subgingival plaque[END_REF].

Interestingly, no Prevotella or Rothia species was detected which were reported to be rather abundant in a recent study on the oral microbiota of 10 individuals with healthy oral tissues [START_REF] Bik | Bacterial diversity in the oral cavity of 10 healthy individuals[END_REF]. It is tempting to speculate that these bacteria appear late in the oral biofilm formation and were, therefore, not observed in our two-weeks-study. Such an information can only obtained with methods which are at least "semiquantitative" but are hard to deduce from a metagenomic approach [START_REF] Zaura | Defining the healthy "core microbiome" of oral microbial communities[END_REF]. A further advantage of the culture-independent approach applied here is the detection of novel species, e. g. Oribacterium sp. 54-3. According to the gene databases such strain has never been detected before and judging from its remote relatedness to Oribacterium sinus it may well belong to a still undescribed genus.

Having assessed the microbial diversity of young biofilms in the human mouth it is interesting to compare the findings with detrimental biofilms reported in the literature [START_REF] Zijnge | Denaturing gradient gel electrophoresis analysis to study bacterial community structure in pockets of periodontitis patients[END_REF]. Socransky and coworkers assessed the microbial diversity of a large number of plaque samples and correlated it with the clinical assessment [START_REF] Socransky | Microbial complexes in subgingival plaque[END_REF].

Multivariate analyses revealed five groups of bacteria increasingly related to periodontitis. We compared this finding with our results and found that none of the species in the group strikingly related to periodontal disease was detected in our study. This indicates no forms of gingivitis or periodontitis. Beside pathogens related to dental diseases other pathogens were found in a few samples, e. g. Neisseria mucosa, Actinomyces israelii or Haemophilus parainfluenzae. The detection of Haemophilus parainfluenzae fits to the suggestion that typical respiratory pathogens may colonize the teeth of hospitalized intensive care and nursing home patients [START_REF] Scannapieco | Role of oral bacteria in respiratory infection[END_REF].

The occurrences of some bacteria were found to be discriminative for some sites. Streptococcus mitis and Lactobacillus delbrueckii contributed together with Parvimonas sp. 72-1 to the discrimination of subgingival biofilm communties while Neisseria mucosa and Parvimonas micra where mainly contributing to the discrimination of supragingival biofilms. This also confirms their role as primary colonizers. Our results confirmed earlier findings [START_REF] Paster | The breadth of bacterial diversity in the human periodontal pocket and other oral sites[END_REF] but extended the number of site specific bacteria considerably. We also showed that Prevotella and Rothia species, abundant in the oral cavity of healthy individuals, are not members of the young biofilm communities. Concerning the experimental set-up used our results show as well that healing abutments can be used as a convenient model to study initial colonization of implants under natural conditions in humans.

2 ,

 2 parvula 54-5) and Veillonella atypica (Veillonella atypica 133-5) could be identified. A third sequence (Veillonella sp. 112-3) was closer related to Veillonella dispar. As has been expected, many biofilm bacteria fell into the genus Streptococcus. Here Streptococcus mitis 42-1 and Streptococcus intermedius 63-1 could be identified together with two unknown Streptococcus species which were related to Streptococcus intermedius and Streptococcus constellatus (Streptococcus sp. 41-2 and 113-3). No sequence belonging to Streptococcus mutans was found. The genus Fusobacterium comprises strictly anaerobic bacteria and species of this genus are well known from the human mouth. The species Fusobacterium naviforme 72-3 and Fusobacterium canifelinum 113-8 were identified from the corresponding SSCP amplicons together with a third Fusobacterium sequence (Fusobacterium sp. 63-3) which was related to Fusobacterium naviforme. As for the former two species of the genus Neisseria have been reported as common members of dental biofilms in humans and Neisseria mucosa 133-2 was found together with the unknown Neisseria species 71-2 related to Neisseria polysaccharea. Parvimonas micra, widely distributed in human dental biofilms, was also detected in this study (Parvimonas micra 52-1). From one patient however, two distinct Parvimonas sequences have been identified (Parvimonas sp. 72-1 and 72-3) belonging to two undescribed Parvimonas species (Figure 3). To detect interdependencies between bacteria species we correlated the occurrence of all species identified. Significant correlations were found between Veillonella species 112-3 and Neisseria species 71-Haemophilus parainfluenzae 112-5 and Campylobacter sp. 113-6, between Veillonella parvula 54-5 and Oribacterium species 54-3 and Centipeda periodontii 54-1 and between Veillonella sp. 133-5 and Campylobacter gracilis 54-7 and Selenomonas noxia 134-1. Streptococcus mitis 42-1 was significantly associated with Lautropia mirabilis 74-1, while the occurrence of Streptococcus intermedius 63-1 correlated with that of Campylobacter sp. 113-6. Fusobacterium canifelinum is closely related to Fusobacterium nucleatum

92- 2 ,

 2 Parvimonas sp. 72-1, Haemophilus parainfluenzae 112-5 and Streptococcus mitis 42-1 as discriminative between the subgingival bacteria and the other samples. The occurrences of Parvimonas micra 52-1 and

Figure 1 :

 1 Figure 1: Clinical signs of periimplantitis with an inflammation of the peri-implantary mucosa (arrows) (a) and a subsequent destruction of the peri-implantary bone with the typical signs of radiographic bone loss around the dental implant (arrows) (b).

Figure 2 :

 2 Figure 2: New sterile Healing abutment (regio 12) in situ.

Figure 3 :

 3 Figure 3: Unrooted phylogentic tree based on 16S rRNA gene sequences obtained by sequencing SSCP bands and the nearest type strain using neighbour joining. Bootstraps values are shown at the branching points; only values above 50% are shown. Only sequences with more than 350 unambiguously determined base pairs were included. Numbers in bold stand for sequences of SSCP bands deposited at GenBank. Scale bar represents 5 nucleotide substitutions per 100 bases.

Figure 4 : 3 = 2 , 7 = 1 , 15 = 19 =

 432711519 Figure 4: SSCP samples from 5 patients; sp = supragingival, sb = subgingival, ab = sulcusfluid from abutment, rt = sulcusfluid from residual teeth. Numbered bands are 1 = Neisseria mucosa, 2 = Veillonella parvula, 3 = Burkholderia sp. 113-1, 4 = Marinobacter santoriniensis, 5 = Parvimonas micra, 6 = Corynebacterium sp. 51-2, 7 = Leptotrichia sp. 51-3, 8 = Klingella sp. 112-2, 9 = Campylobacter gracilis, 10 = Centipeda periodontii, 11 = Oribacterium sp. 54-3, 12 = Fusobacterium nucleatum, 13 = Fusobacterium sp. 63-3, 14 = Parvimonas sp. 72-1, 15 = Parvimonas sp. 72-2, 16 = Fusobacterium naviforme, 17 = Lautropia mirabilis, 18 = Neisseria sp. 71-2, 19 = Streptococcus mitis, 20 = Lactobacillus delbrueckii, 21 = Streptococcus intermedius, 22 = Capnocytophaga sputigena.

Figure 5 :

 5 Figure 5: Discriminant analysis between the four sampling sites and the presence/absence of their bacteria. Only roots 1 and 2 are shown. 5a (left): Plot of the four different sample types; circle: supragingival biofilms (solid ellipse), square: subgingival biofilms (dashed ellipse), rhomb: sulcusfluids of the abutments (mixed dashed ellipse), triangle: sulcusfluids of the residual teeth (solid ellipse). 5b (right): factor loadings of the bacteria discriminating the four groups.

Figures:Figure 1 a

 1 Figures: Figure 1 a/b:

Figure 2 :

 2 Figure 2:

Figure 3

 3 Figure 3:

Figure 4 : 18

 418 Figure 4:

Figure 5

 5 Figure 5:

Acknowledgements

We are indebted to Jennifer Knaak for her excellent technical assistance. This work was supported by a grant from the German Federal Ministry for Science, Education and Research (Project No. 01 KI 07 96) and by the German Research Foundation (DFG-SFB Collaborative Research Center 599).


Laura Magliulo

Marja-Liisa Dahl

Grazia Lombardi

Silvia Fallarini

Laura Maria Villa

Aldo Biolcati

Dr Maria Gabriella Scordo
email: gabriella.scordo@medsci.uu.se

Do CYP3A and ABCB1 genotypes influence the plasma concentration and clinical outcome of donepezil treatment?

Keywords: Donepezil, CYP3A4, CYP3A5, ABCB1, polymorphisms, Alzheimer's disease, Pharmacogenetics

Purpose: Aim of our study was to evaluate the impact of CYP3A4, CYP3A5 and ABCB1 polymorphisms on donepezil disposition and clinical outcome.

Methods: Fifty-four Italian patients diagnosed with probable mild to moderate Alzheimer's disease, treated with donepezil (37 patients 5 mg/day, 17 patients 10 mg/day) were genotyped for CYP3A4 (*1B, *3 and *4), CYP3A5 (*2, *3 and *6) and ABCB1 (3435C>T, 2677G>T/A and 1236C>T) polymorphisms. All patients were evaluated for the degree of cognitive impairment with Mini Mental State Examination (MMSE) screening test at baseline (before treatment) and after at least three months of donepezil treatment at stable dose, when the drug plasma levels were measured.

Results: Three patients carried one detrimental CYP3A4 allelic variant, and 12 one functional CYP3A5*1 allele. No statistically significant association was found between CYP3A4 or CYP3A5 genotypes and plasma donepezil concentrations, or between genotypes and clinical response (as measured by change in MMSE score). Nine ABCB1 haplotypes were observed, the most common being 1236C/2677G/3435C (46%) and 1236T/2677T/3435T (41%). Patients homozygous for the T/T/T haplotype had slightly though not significantly lower plasma donepezil concentration to dose ratios than those carrying other genotypes (median (95% CI) 0.18 (0.13-0.45) vs 0.31 (0.30-0.44) mg/l/mg/kg respectively). These patients also showed a slightly better clinical response (as measured by change in MMSE score) than the other genotype groups (median (95% CI) 0 (-1.3-3.3) vs -1.0 (-2.1-0.0), respectively).

Conclusions:

Our data suggest that the CYP3A4 and CYP3A5 polymorphisms are unlikely to influence donepezil metabolism and/or clinical outcome. On the other hand the ABCB1 polymorphisms may play a role in donepezil disposition and clinical outcome.

Introduction

Acetylcholinesterase (AChE) inhibitors, such as donepezil, are the current pharmacological class indicated for the symptomatic treatment of moderate to mild Alzheimer's disease (AD) [START_REF] Scarpini | Treatment of Alzheimer's disease: current status and new perspectives[END_REF]. There is a large variability in the clinical response to donepezil, partially related to inter-individual differences in its pharmacokinetics, caused by factors such as age, concomitant diseases and drugdrug interactions. A role may also be played by genetic polymorphisms affecting drug disposition. Donepezil is metabolized mainly by the cytochrome P450 enzymes CYP2D6 and 3A [START_REF] Barner | Donepezil use in Alzheimer's disease[END_REF]. The CYP2D6 gene is highly polymorphic (http://www.imm.ki.se/CYPalleles/cyp2d6.htm) and the population can be divided into phenotypes with deficient (poor metabolizers, PM), normal (extensive metabolizers, EM), or increased (ultrarapid metabolizers, UM) enzymatic activity.

Varsaldi et al. [START_REF] Varsaldi | Impact of the CYP2D6 polymorphism on steady-state plasma concentrations and clinical outcome of donepezil in Alzheimer's disease patients[END_REF] observed a large inter-individual variability in the plasma concentration to dose (C/D) ratios of donepezil among AD patients. This variability was associated with the CYP2D6 genotype, suggesting a role for this polymorphic enzyme in donepezil kinetics and clinical outcome.

Co-administration of substrates or inhibitors of CYP3A (i.e. cimetidine, ketokonazole) has been shown to cause changes in the plasma concentrations of donepezil [START_REF] Tiseo | Concurrent administration of donepezil HCL and cimetidine: assessment of pharmacokinetic changes following single and multiple doses[END_REF][START_REF] Tiseo | Concurrent administration of donepezil HCL and ketoconazole: assessment of pharmacokinetic changes following single and multiple doses[END_REF], indicating a role for these enzymes in donepezil metabolism as well. A number of allelic variants have been described for the genes encoding CYP3A4 and CYP3A5 (http://www.imm.ki.se/CYPalleles/cyp3a.htm). Three CYP3A4 variants (CYP3A4*1B, CYP3A4*3 and CYP3A4*4) have been reported to alter enzyme activity and to affect the in vivo metabolism of commonly used drugs such as simvastatin, tacrolimus and cyclosporine [START_REF] Wang | Ile118Val genetic polymorphism of CYP3A4 and its effects on lipid-lowering efficacy of simvastatin in Chinese hyperlipidemic patients[END_REF][START_REF] Hesselink | Genetic polymorphisms of the CYP3A4, CYP3A5, and MDR-1 genes and pharmacokinetics of the calcineurin inhibitors cyclosporine and tacrolimus[END_REF][START_REF] Hesselink | Population pharmacokinetics of cyclosporine in kidney and heart transplant recipients and the influence of ethnicity and genetic polymorphisms in the MDR-1, CYP3A4, and CYP3A5 genes[END_REF]. Only subjects carrying at least one CYP3A5*1 allele (about 10% of the population) express the CYP3A5 enzyme [START_REF] Hustert | The genetic determinants of the CYP3A5 polymorphism[END_REF]. The main cause of the absence of CYP3A5 among a majority of Caucasians is the CYP3A5*3 allele [START_REF] Hustert | The genetic determinants of the CYP3A5 polymorphism[END_REF][START_REF] Van Schaik | CYP3A5 variant allele frequencies in Dutch Caucasians[END_REF]. CYP3A5*6 and CYP3A5*2 are more rare variants coding for a non-functional protein [START_REF] Van Schaik | CYP3A5 variant allele frequencies in Dutch Caucasians[END_REF].

P-glycoprotein (P-gp) has been recently recognized as an important determinant for the disposition of donepezil, influencing its efflux from the brain to the blood at the blood brain barrier level [START_REF] Ishiwata | In vivo evaluation of P-glycoprotein modulation of 8 PET radioligands used clinically[END_REF].

The gene encoding this protein (ABCB1) is highly polymorphic [START_REF] Kroetz | Sequence diversity and haplotype structure in the human ABCB1 (MDR1, multidrug resistance transporter) gene[END_REF][START_REF] Ito | Polymorphism of the ABC transporter genes, MDR1, MRP1 and MRP2/Cmoat, in healthy Japanese subjects[END_REF]. Three polymorphisms, 1236C>T, 2677G>T/A and 3435C>T, that are in linkage disequilibrium [START_REF] Horinouchi | Significant genetic linkage of MDR1 polymorphisms at position 3435 and 2677: functional rilevance to pharmacokinetics of digoxin[END_REF][START_REF] Johne | Modulation of steadystate kinetics of digoxin by haplotypes of the P-glycoprotein MDR1 gene[END_REF], have been studied extensively with respect to their effects on P-gp function and clinical relevance.

3435C>T is a silent SNP in exon 26, associated with a lower expression and function of the protein [START_REF] Hoffmeyer | Functional polymorphisms of the human multidrug resistance gene: multiple sequence variations and correlation of one allele with Pglycoprotein expression and activity in vivo[END_REF]. 2677G>T/A is a tri-allelic polymorphism in exon 21. Both variant alleles (A or T) result in an amino acid change, Ala893Thr and Ala893Ser, respectively, which alter expression and activity of P-gp [START_REF] Verstuyft | Digoxin pharmacokinetics and MDR1 genetic polymorphisms[END_REF][START_REF] Morita | MDR1 genotype related duodenal absorption rate of digoxin in healthy Japanese subjects[END_REF]. The studies that have evaluated the role of the 1236C>T SNP, a silent polymorphism in exon 12, in the pharmacokinetics of drugs such as fexofenadine, have produced discordant results [START_REF] Johne | Modulation of steadystate kinetics of digoxin by haplotypes of the P-glycoprotein MDR1 gene[END_REF][START_REF] Illmer | MDR1 gene polymorphisms affect therapy outcome in acute myeloid leukemia patients[END_REF][START_REF] Kim | Identification of functionally variant MDR1 alleles among European Americans and African Americans[END_REF][START_REF] Mathijssen | Irinotecan pathway genotype analysis to predict pharmacokinetics[END_REF]. The frequencies of these three ABCB1 SNPs have also been shown to vary between ethnic groups [START_REF] Ozawa | Ethnic differences in genetic polymorphisms of CYP2D6, CYP2C19, CYP3As and MDR1/ABCB1[END_REF].

The aim of this study was to evaluate the impact of CYP3A4, CYP3A5 and ABCB1 polymorphisms on the steady-state plasma concentrations and therapeutic outcome of donepezil in a population of AD patients, taking CYP2D6 genotype status into account.

Methods

Study design and population

Fifty-four Italian AD out-patients of Caucasian ethnicity were enrolled in the study at the Geriatric Clinical Unit "Unità Operativa Autonoma" (UOA), "Ospedale Maggiore della Carità", Novara, Italy. Most patients (n=42) had participated in a previous study designed to assess the impact of CYP2D6 polymorphisms on donepezil kinetics and therapeutic outcome [START_REF] Varsaldi | Impact of the CYP2D6 polymorphism on steady-state plasma concentrations and clinical outcome of donepezil in Alzheimer's disease patients[END_REF]. The demographic and clinical characteristics of the patients are shown in Table 1. All participants had been diagnosed with probable mild to moderate AD according to the NINCDS-ADRDA Work Group Criteria for AD diagnosis [START_REF] Mckhann | Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer's disease[END_REF]. They were evaluated for the degree of functional and cognitive impairment with the Mini-Mental State Examination (MMSE) screening test [START_REF] Folstein | Mini-Mental State". A practical method for grading the cognitive state of patients for the clinician[END_REF] and for daily living with the Clinical Dementia Rating Scale (CDR), the Instrumental Activity of Daily Living (ADL) and the Clinician's Interview Based Impression of Change-Plus (CIBIC-Plus) scales. The MMSE test is a psychometric test designed to quantitatively estimate the severity of cognitive impairment and to serially document cognitive changes in domains such as memory, orientation, language and praxis [START_REF] Folstein | Mini-Mental State". A practical method for grading the cognitive state of patients for the clinician[END_REF]. Its score ranges from 0 to 30, subjects with a score of 24 or more classified as cognitively normal. A negative change in the score reflects a worsening in the cognitive status. The MMSE score was corrected by age and educational level. Physical health, other concomitant drug therapies and adverse effects to donepezil were also recorded. Subjects with cardiac or hepatic impaired functions were excluded from the study. Tests to assess the liver function were performed at baseline (inclusion point) and repeated at the time of the second clinical evaluation. Fifteen patients received concomitant therapies with one or more substrates or weak inhibitors of CYP3A or P-gp (Table 1). The clinical evaluations were performed at baseline, once the patients were diagnosed with AD, before donepezil treatment (first assessment), and at the time of blood sampling for the donepezil concentration measurement (second assessment). All patients started donepezil therapy at 5 mg/day. After 4 weeks of treatment, the treating physicians decided whether maintaining the same dose (37 patients) or increasing it to 10 mg/day (17 patients), based on clinical evaluations. At the second assessment the patients had been treated with a stable dose of donepezil for at least 3 months. The mean treatment time before the second assessment was 9 months (range 3-40 months).

The protocol was approved by the Research Ethics Committee at the "Ospedale Maggiore della Carità" of Novara (Italy). Prior to inclusion in the study all patients, or their legal tutors, gave their written informed consent.

Control group

In order to estimate whether the genotype and allele frequencies among the AD patients were consistent with those in the general population, 285 Italian healthy volunteers (Table 1) were also included in the study and genotyped for CYP3A4, CYP3A5 and ABCB1.

Determination of donepezil plasma concentrations

Twelve to 15 hours after the last drug administration (i.e. at 8-10 a.m.), a 5 ml blood sample was collected in heparinized tubes. Plasma was separated and stored at -20°C until analysis. Donepezil plasma concentrations were determined by high-performance liquid chromatography (HPLC) with UV absorbance detection, according to Yasui-Furukori et al. [START_REF] Yasui-Furukori | Determination of donepezil, an acetylcholinesterase inhibitor, in human plasma by high-perfomance liquid chromatography with ultraviolet absorbance detection[END_REF] with slight modifications, as described by Varsaldi et al. [START_REF] Varsaldi | Impact of the CYP2D6 polymorphism on steady-state plasma concentrations and clinical outcome of donepezil in Alzheimer's disease patients[END_REF]. Mean recoveries were 85-96%, and the intra-and inter-day coefficient of variation were below 4.2 and 5.1%, respectively, at concentrations ranging between 1 and 100 mg/l. The lowest limit of quantification was 1.3 ng/l. No interfering peaks were observed despite the fact that various other drugs were coadministered with donepezil.

Genotyping methods

Genomic DNA was isolated from peripheral leukocytes using the QIAamp DNA Blood Mini kit (Qiagen, Hilden, Germany) according to the guidelines of the manufacturer. [START_REF] Mirghani | CYP3A5 genotype has significant effect on quintine 3-hydroxilation in Tanzanians, who have lower total CYP3A activity compared to a Swedish population[END_REF]. The CYP3A4*1B (-290A>G) was analysed by allele-specific PCR followed by digestion with restriction enzyme according to van Schaik et al. [START_REF] Van Schaik | CYP3A4-V Polimorphism detection by PCR-Restriction Fragment Length Polymorphism Analysis and its allelic frequency among 199 Dutch Caucasians[END_REF].

The CYP2D6 genotype was available for most patients from the previous study [START_REF] Varsaldi | Impact of the CYP2D6 polymorphism on steady-state plasma concentrations and clinical outcome of donepezil in Alzheimer's disease patients[END_REF]. The newly included patients were genotyped with the same methods.

Statistical analysis

Data were analyzed by Kruskal-Wallis non-parametric rank analysis of variance to establish an overall difference between the genotypes, and by the Mann-Whitney T-test for comparisons of two groups. When allele and genotype frequencies between AD patients and controls were compared, the Chi-square test was used. Statistical analysis was performed using the GraphPad Prism 4 software (San Diego, CA, U.S.A). A p value of 0.05 or lower was regarded as statistically significant. 2). The allele and genotype frequencies among both volunteers and patients were in equilibrium with the Hardy-Weinberg equation.

Results

Genotypes

The allele frequencies of individual ABCB1 polymorphisms are given in Table 2. Nine haplotypes for ABCB1 were observed. The most common ABCB1 haplotypes among AD patients and volunteers were 1236C/2677G/3435C (with frequencies of 46% and 45% respectively) and 1236T/2677T/3435T (41% and 42%, respectively, Table 3).

Donepezil concentrations and the CYP3A4/3A5/ABCB1 genotypes

The plasma concentrations of donepezil ranged from 0.078 to 0.654 mg/l among patients receiving a donepezil dose of 5 mg/day and from 0.024 to 0.537 mg/l among those receiving 10 mg/day. Since the pharmacokinetics of donepezil is linear [START_REF] Rogers | Pharmacokinetic and pharmacodynamic profile of donepezil HCl following single oral doses[END_REF][START_REF] Rogers | Pharmacokinetic and pharmacodynamic profile of donepezil HCl following multiple oral doses[END_REF], and there was a large variation in body weight (39-90 kg), the measured plasma concentrations were corrected for the dose and the body weight (C/D).

The C/D ratios were not associated with the CYP3A4 or CYP3A5 genotypes (p>0.05), and a considerable overlap was observed in C/D ratios between subjects homozygous and heterozygous for both CYP3A4*1 and CYP3A5*3. The median C/D ratio among the 15 patients receiving concomitant CYP3A4 and/or P-gp substrates/weak inhibitors was slightly, not significantly (p=0.21), higher than that among patients not receiving any CYP3A4-or P-gp-interacting drugs (median 0.41 (95% CI 0.29-0.51) (range 0.17-0.91) vs 0.28 (95% CI 0.26-0.42) (range 0.02-0.95) mg/l/mg/kg, respectively). Donepezil C/D was not significantly influenced by ABCB1 polymorphisms (p>0.05) (Table 4). On the other hand, there was a trend for subjects homozygous for the T-variants at all three sites to have lower donepezil C/Ds compared to other genotype groups (Table 4). Consistently, subjects homozygous for the haplotype 1236T/2677T/3435T had slightly, though not significantly (p=0.176), lower plasma C/D of donepezil (median 0.18 (95% CI 0.13-0.45) (range 0.07-0.85) mg/l/mg/kg) compared to the other genotypes (median 0.31 (95% CI 0.30-0.44) (range 0.02-0.95) mg/l/mg/kg) (Fig. 1).

Clinical Outcome and the CYP3A4/3A5 and ABCB1 genotypes

No statistically significant association was found between CYP3A4 or CYP3A5 genotypes and clinical response, as measured by the CIBIC-plus score or change in the MMSE score. However, patients carrying one CYP3A5*1 allele showed a slightly worse clinical response, measured as MMSE change from the first to the second assessment, compared to the CYP3A5*3/*3 group (median -1.8 (95% CI -3.9 -1.8) (range -8.0 -8.4) vs -0.05 (-1.5 -0.5) (-8.6 -6.0) respectively, p=0.519). No impact of concomitant CYP3A4 and/or P-gp substrates/weak inhibitors was seen on the clinical outcome, as measured by in the change in MMSE score (data not shown).

Subjects with ABCB1 T/T genotypes showed a trend towards a better clinical response, as measured by the change in the MMSE score, compared with other genotypes (Table 4). Consistently, the median change in MMSE score among patients homozygous for the ABCB1 1236T/2677T/3435T haplotype was 0 (95% CI -1.3 -3.3) (range -3.0 -8.4) compared to -1.0 (95% CI -2.1 -0.0) (range -8.6 -6.0) among those with other genotypes (p=0.138) (Fig. 2).

CYP2D6 genotype, donepezil plasma concentrations and clinical outcome

The median C/D ratios of donepezil in UMs, homozygous EMs, heterozygous EMs and PMs were 0.13 (95% CI -0.57 -0.82) (range 0.07-0.18), 0.31 (95% CI 0.29 -0.43) (range 0.07-0.91), 0.30 (95% CI 0.21 -0.49) (range 0.02-0.85) and 0.51 (95% CI -5.1 -6.1) (range 0.07-0.95) mg/l/mg/kg, respectively. The heterozygous EM showed a significantly better clinical response to the therapy than homozygous EM as measured by change in the MMSE score (median 1.20 vs -1.00, respectively; p=0.03). The two UMs and the two PMs were among the subjects who experienced a most marked worsening in their cognitive functions (UMs change in MMSE score -4.4 and -2.0, PMs change in MMSE score -3.3 and -1.8, respectively).

Discussion

To our knowledge this is the first study to evaluate the impact of CYP3A4 and ABCB1 genotypes on the clinical outcome in donepezil therapy. The frequencies of CYP3A4, CYP3A5 and ABCB1 allelic variants detected in this study were similar among the two groups studied and consistent with earlier data on Caucasian populations (Table 2). No statistically significant differences in allele or genotype frequencies were detected between AD patients and volunteers, suggesting that CYP3A4/3A5 and ABCB1 polymorphisms are unlikely to represent a risk factor for susceptibility to Alzheimer's disease. No AD patient or volunteer carried the CYP3A4*4 allele, indicating that this variant has a frequency <0.5%, and could therefore represent a rare single gene defect, rather than an actual polymorphism. Consistently, so far there are no data regarding this allele's frequency in Caucasians. The CYP3A5*2 allele was detected in a previous study with a frequency of 1% [START_REF] Van Schaik | CYP3A5 variant allele frequencies in Dutch Caucasians[END_REF],

but in our study it was not found either among AD patients or volunteers, suggesting that this is also a very rare variant among Italians. Kuehl et al. [START_REF] Kuehl | Sequence diversity in CYP3A4 promoters and characterization of the genetic basis of polymorphic CYP3A5 expression[END_REF] have reported that the CYP3A4*1B and CYP3A5*1 alleles are in linkage disequilibrium in African Americans, and suggested that this linkage disequilibrium might influence CYP3A activity towards exogenous and endogenous compounds. Since the frequency of CYP3A4*1B is lower in Caucasians than in African Americans, larger populations would be required to demonstrate whether CYP3A4*1B and CYP3A5*1 are in linkage disequilibrium in Caucasians [START_REF] Lamba | Genetic contribution to variable human CYP3A-mediated metabolism[END_REF]. Furthermore, Ingelman-Sundberg et al. [START_REF] Ingelman-Sundberg | Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetics, pharmacoepigenetic and clinical aspects[END_REF] suggested that the presence of a CYP3A5*1 allele, leading to expression of CYP3A5, could compensate for the reduction in CYP3A4 activity caused by the CYP3A4*1B allele (that causes decreased transcription [START_REF] Rodriguez-Antona | Phenotype-genotype variability in the human CYP3A locus as assessed by the probe drug quinine and analyses of variant CYP3A4 alleles[END_REF]) and result in total CYP3A activity similar to that of CYP3A4*1A/CYP3A5*3 carriers. Previous studies in Germans [START_REF] Dally | Genotype relationship in the CYP3A locus in Caucasians[END_REF] and Spaniards [START_REF] Sinues | CYP3A5*3 AND CYP3A4*1B allele distribution and genotype combinations: differences between Spaniards and Central Americans[END_REF] reported frequencies of 4% and 5.4%, respectively, for the CYP3A4*1B/CYP3A5*1 allele combination. Consistently, in the present study, we found the allele combination CYP3A4*1B/CYP3A5*1 with a frequency of 3.7% among AD patients and 4.9% among volunteers (two out of two AD patients and fourteen out of twenty volunteers with CYP3A4*1B also carried CYP3A5*1).

Varsaldi et al. [START_REF] Varsaldi | Impact of the CYP2D6 polymorphism on steady-state plasma concentrations and clinical outcome of donepezil in Alzheimer's disease patients[END_REF] showed that CYP2D6 polymorphism does influence donepezil kinetics and therapeutic outcome. In the present study we confirmed these results in a somewhat larger population. Heterozygous EM had a better clinical response than homozygous EM as measured by change in the MMSE score (p=0.03). UM subjects had the lowest median C/D ratio and PMs had the highest. However, only two patients with these genotypes were included in the study, and the data are thus very uncertain with respect to these groups.

In accordance with previous interaction studies [START_REF] Tiseo | Concurrent administration of donepezil HCL and cimetidine: assessment of pharmacokinetic changes following single and multiple doses[END_REF][START_REF] Tiseo | Concurrent administration of donepezil HCL and ketoconazole: assessment of pharmacokinetic changes following single and multiple doses[END_REF][START_REF] Nagy | Concurrent administration of donepezil HCl and sertraline HCl in healthy volunteers : assessment of pharmacokinetic changes and safety following single and multiple oral doses[END_REF], the concurrent administration of CYP3A4 and/or P-gp substrates and/or weak inhibitors was found to be associated with slightly, but not significantly, higher C/D ratios compared with patients with no concomitant interacting therapies.

The large inter-individual variability in the C/D ratio of donepezil among AD patients was not related to the CYP3A genotype and a considerable overlap was observed in C/D ratios between subjects homo-and heterozygous for both CYP3A4*1 and CYP3A5*3. Furthermore, the low frequency of CYP3A4 allelic variants in the Italian population suggests that polymorphisms in this gene are unlikely to play a fundamental role for donepezil.

In previous studies, reduced P-gp activity and higher exposure levels of drug substrates such as digoxin were associated with homozygosity for the three variant alleles of ABCB1, 3435T, 2677T and 1236T [START_REF] Johne | Modulation of steadystate kinetics of digoxin by haplotypes of the P-glycoprotein MDR1 gene[END_REF][START_REF] Chowbay | Genetic polymorphisms in MDR1 and CYP3A4 genes in Asians and the influence of MDR1 haplotypes on cyclosporine disposition in heart transplant recipients[END_REF][START_REF] Kurata | Role of human MDR1 gene polymorphism in bioavaliability and interaction of digoxin, a substrate of P-glycoprotein[END_REF]. Accordingly in our study, AD patients homozygous for the haplotype 1236T/2677T/3435T showed a tendency towards a better clinical response, measured by change in MMSE score, although the results did not reach statistical significance. Concurrently, these patients had slightly lower C/Ds of donepezil. The same trend was also seen when the three SNPs were analysed separately (Table 4), so suggesting that this haplotype might play a certain role in the clinical outcome and plasma levels of donepezil.

The low C/D in patients with tendency for better response, in T/T/T homozygous subjects was somewhat surprising. However, Lamba et al. [START_REF] Lamba | MDR1 genotype is associated with hepatic cytochrome P450 3A4 basal and induction phenotype[END_REF] showed that subjects homozygous for the ABCB1 2677T allele had higher CYP3A4 expression than subjects homozygous for the 2677G allele, suggesting a link between ABCB1 and CYP3A4 regulation. This would be in agreement with our findings of low C/Ds of donepezil among T/T/T homozygous subjects. Furthermore, these patients showed a tendency towards a better clinical response. A possible explanation could be that the SNPs in the ABCB1 gene, associated with decreased P-gp activity, may lead to increased donepezil CNS levels due to a reduced efflux of the drug from the CNS to the blood compartment. Such a phenomenon has been earlier suggested for other P-gp substrates such as risperidone [START_REF] Gunes | ABCB1 polymorphisms influence steadystate plasma levels of 9-hydroxyrisperidone and risperidone active moiety[END_REF].

Limitations of this study are the small number of patients and the lack of a placebo control-group. Thus, larger and preferably prospective studies are necessary to clarify the clinical relevance of the CYP3A4, CYP3A5, and ABCB1 genotypes on donepezil plasma concentrations and clinical outcome among AD patients.

Conclusions

Our results suggest that the CYP3A4 and CYP3A5 allele variants considered in the present study do not play a pivotal role in the variability in donepezil metabolism. Conversely, ABCB1 polymorphisms may contribute to the variability in donepezil disposition and clinical outcome.

CYP3A4* 3 ,

 3 CYP3A4*4, CYP3A5*2, CYP3A5*6 and ABCB1 polymorphisms were identified by real time PCR with TaqMan kits purchased from Applied Biosystems (Warrington, UK), according to the guidelines of the manufacturer (for CYP3A4*3, Assay ID: C__27535825_20, for CYP3A4*4, Assay ID: C__30634211_30, for CYP3A5*2, Assay ID: C__30633862_10, for CYP3A5*6, Assay ID: C__30203950_10; for ABCB1 1236C>T, Assay ID: C__7586662_10, for ABCB1 3435C>T, Assay ID: C__7586657_1_, and for ABCB1 2677G>A/T, Forward Primer GTA AGC AGT AGG GAG TAA CAA AAT AAC ACT, Reverse Primer GAC AAG CAC TGA AAG ATA AGA AAG AAC T, 2677G probe VIC-CCT TCC CAG CAC CT, 2677A probe FAM-CTT CCC AGT ACC TTC, 2677T probe FAM-CTT CCC AGA ACC TT). The CYP3A5*3 was identified by real time PCR according to Mirghani et al.

  Three AD patients (5.6%) and twenty-four (8.4%) volunteers carried one detrimental CYP3A4 allele (AD patients: CYP3A4*1/*1B n=2 and CYP3A4*1/*3 n=1; Volunteers: CYP3A4*1/*1B n=20, and CYP3A4*1/*3 n=4). Twelve AD patients (22.2%) were heterozygous for CYP3A5*1, while all the others (77.8%) were homozygous for the CYP3A5*3 allele. Among volunteers, 246 (86.3%) were homozygous for CYP3A5*3 and four (1.4%) carried the CYP3A5*3/*6 genotype. Five volunteers (1.7%) were homozygous and thirty (10.5%) were heterozygous for CYP3A5*1. No AD patient or volunteer carried CYP3A4*4 or CYP3A5*2 alleles. The frequencies of the allelic variants of CYP3A4 and CYP3A5 did not differ between patients and volunteers, and were similar to those reported in other Caucasian populations (Table

Fourteen ( 25 . 2 ( 3 .

 2523 9%) AD patients could be classified as heterozygous CYP2D6 EM (CYP2D6*1/*3 n=2, CYP2D6*1/*4 n=10, CYP2D6*1/*5 n=1, CYP2D6*1/*6 n=1). Two (3.7%) patients carried two detrimental alleles (CYP2D6*3/*6 n=1, CYP2D6*5/*5 n=1) and were classified as PM, while 7%) were found to carry extra copies of a functional CYP2D6 allele and were thus classified as UM.

Figure 1 .

 1 Figure 1. Relationship between the ABCB1 genotypes and plasma concentration-to-dose (C/D) ratio of donepezil. Horizontal bars represent median values.

Figure 2 .

 2 Figure 2. Relationship between the ABCB1 genotypes and change in Mini-Mental State Examination (MMSE) screening test score. Horizontal bars represent median values.

Figure 1 .

 1 Figure 1.

Table 1 .

 1 Demographic and clinical characteristics of patients with Alzheimer's disease (AD) and

	volunteers
		AD patients (n=54)	Volunteers (n=285)
	Age a (years)	61-93 (79±6)	19-52 (30±9)
	Male/Female	14/40	155/130
	Body weight a (kg)	39-90 (63±12)
	Smokers/No-Smokers	1 (less than 10 cig per day)/53
	MMSE at the baseline b	19.1 (3-28.3)
	MMSE at the steady-state b	18.5 (7.7-30)
	MMSE change	-0.6 (-8.6-8.4)
	Co-administered drugs	Alprazolam (2), risperidone (2), trazodone (4),
		atorvastatin (1) , simvastatin (4),
		felodipine (1), lecarnidipine (1), nicardipine (1),
		verapamil (2), amiodarone (1)

a Data are expressed as range (mean± SD) b Data are expressed as median (range)

Table 2 .

 2 CYP3A and ABCB1 allele frequencies in patients with Alzheimer's disease (AD) and in volunteers

	Allelic Variant	Allele frequencies	95% Confidence interval a	χ 2	Allele frequencies in other Caucasian populations
		AD patients Volunteers
	CYP3A4*1B (rs 2740574)	0.019	0.036	0.021-0.051	ns	0.045 [41]
	CYP3A4*3 (rs 4986910)	0.009	0.007	0.007-0.021	ns	0.011 [42]
	CYP3A4*4	Not detected Not detected	-	-	No data
	CYP3A5*3 (rs 776746)	0.889	0.933	0.912-0.954	ns	0.90 [10]
	CYP3A5*6 (rs 10264272)	Not detected	0.007	0.000-0.014	-	0.001 [10]
	CYP3A5*2 (rs 28365083)	Not detected Not detected	-	-	0.01 [10]
	ABCB1 1236T	0.472	0.458	0.417-0.499	ns	0.41 [43]
	ABCB1 3435T	0.481	0.502	0.461-0.543	ns	0.539 [43]
	ABCB1 2677T	0.435	0.458	0.417-0.499	ns	0.416 [43]
	ABCB1 2677A	0.009	0.024	0.011-0.037	ns	0.019 [43]

a Based on volunteer frequencies

Table 3 .

 3 ABCB1 haplotype frequencies among patients with Alzheimer's disease (AD) and

	volunteers (%)
	C1236T	G2677T/A	C3435T	AD patients	Volunteers
	C	G	C	46	45
	T	T	T	41	42
	C	G	T	5	6
	T	T	C	2	2
	T	G	C	4	1
	C	T	T	0.9	1
	T	G	T	0.9	0
	C	A	T	0.9	0.2
	C	A	C	0	2

Acknowledgements

This work was supported by grants from the Swedish Society of Medicine, the Swedish Research Council, and the "Piedmont County Grants for Research" (2008, Turin, Italy). We thank Dr. Norio Yasui-Furukori (Hirosaki University, School of Medicine, Japan) for the generous gift of donepezil.

The study protocol was approved by the Research Ethics Committee at the "Ospedale Maggiore della Carità" of Novara (Italy) in accordance with the ethical standards laid down in the Declaration of Helsinki.


Jessica Amadio

Cormac D Murphy
email: cormac.d.murphy@ucd.ie

Production of human metabolites of the anti-cancer drug flutamide via biotransformation in Cunninghamella species

Keywords: Biotransformation, cytochrome P450, fluorine-19 NMR, sulfotransferase

Fungi belonging to the genus Cunninghamella have enzymes similar to those employed by mammals for the detoxification of xenobiotics, thus they are useful as models of mammalian drug metabolism, and as a source for drug metabolites. We report the transformation of the anti-cancer drug flutamide in Cunninghamella spp. The most predominant phase I metabolites present in the plasma of humans, 2-hydroxyflutamide and 4-nitro-3-(trifluoromethyl)aniline, were also produced in Cunninghamella cultures. Other phase I and phase II metabolites were also detected using a combination of HPLC, GC-MS and 19 F-NMR.

Introduction

Flutamide (2-methyl-N-[4-nitro-3-(trifluoromethyl)phenyl]propanamide is a non steroidal antiandrogen drug primarily used to treat prostate cancer and, like an increasing number of anti-cancer agents, it is fluorinated [START_REF] Isanbor | Fluorine in medicinal chemistry: A review of anticancer agents[END_REF].

In medicinal chemistry, the substitution of a fluorine atom is used to improve metabolic stability, bioavailability and interaction with the biological target [START_REF] Purser | Fluorine in medicinal chemistry[END_REF]. In particular the trifluoromethyl group, which is part of flutamide, is the most used fluorinated moiety in pharmaceuticals and agrochemicals. It is among the most lipophilic of all substituents and it is known to retard metabolic degradation by blocking cytochrome P450 enzymes [START_REF] Park | Metabolism of fluorine-containing drugs[END_REF]. Some microorganisms have enzymes that are synonymous to those involved in xenobiotic detoxification in mammals [START_REF] Prior | Identification and characterization of a bacterial cytochrome p450 for the metabolism of diclofenac[END_REF][START_REF] Zhang | Phase I and phase II enzymes produced by Cunninghamella elegans for the metabolism of xenobiotics[END_REF] and, as such, are useful models of drug metabolism [START_REF] Smith | Microbial models of mammalian metabolism -aromatic hydroxylation[END_REF] and in the production of drug metabolites [START_REF] Osorio-Lozada | Biosynthesis of drug metabolites using microbes in hollow fiber cartridge reactors: Case study of diclofenac metabolism by Actinoplanes species[END_REF]. Few studies have been published on the metabolism of fluorinated drugs by microorganisms despite the significance of this class of compounds. There are a few studies on the degradation of trifluoromethyl-containing xenobiotics, for example, [START_REF] Engesser | Bacterial metabolism of side-chain fluorinated aromatics -co-metabolism of 3-trifluoromethyl(tfm)-benzoate by Pseudomonas putida (arvilla) mt-2 and Rhodococcus rubropertinctus n657[END_REF][START_REF] Engesser | Bacterial metabolism of side-chainfluorinated aromatics -unproductive meta-cleavage of 3trifluoromethylcatechol[END_REF] reported the metabolism of 3-and 4-trifluoromethyl benzoate in Pseudomonas putida, via the corresponding catechols, to 2-hydroxy-6-oxo-7,7,7-trifluoro-hepta-2,4dienoate. [START_REF] Herath | Microbial metabolism. Part 11. Metabolites of flutamide[END_REF] examined the biotransformation of flutamide in 40 microorganisms, and demonstrated the production of three metabolites also found in mammals, which arose via nitroreduction, hydrolysis and acetylation. However, 2hydroxyflutamide, which is a major metabolite in human plasma [START_REF] Aizawa | Flutamide-induced hepatic dysfunction in relation to steady-state plasma concentrations of flutamide and its metabolites[END_REF] was not observed in these fungal cultures, presumably because the enzyme required, cytochrome P450 (CYP1A2), was not produced by the fungi investigated.

In the present study, we investigated the biotransformation of flutamide in Cunninghamella species, which have been previously shown to be very effective models of mammalian drug metabolism (Amadio et al. 2010;[START_REF] Asha | Cunninghamella -a microbial model for drug metabolism studies -a review[END_REF], since they have cytochrome P450 activity and conjugation enzymes (Zhang et al. 2010).

Materials and Methods

Materials

Flutamide, 2-hydroxyflutamide, 4-nitro-3-(trifluoromethyl)aniline, N-methyl-N-(trimethyl-silyl)trifluoroacetamide, sulfatase (from Helix pomatia type H-1), βglucoronidase (from Escherichia coli) and β-glucosidase (from almonds) were purchased from Sigma.

Culture conditions

Cunninghamella elegans (strains DSM 1908, DSM 8217, DSM 63299), C. echinulata DSM 1905 andC. blakesleeana DSM 1906 (DSMZ, Germany) were selected for biotransformation of flutamide. Fungi were grown on Sabouraud dextrose/agar plates for 5 days at 26 °C before being aseptically homogenized into 100 ml of sterile saline solution. The homogenate (10 % v/v) was used to inoculate 50 ml of Sabouraud dextrose/broth in 250 ml Erlenmeyer flasks, which were incubated at 28°C with shaking at 150 rpm. Control experiments were conducted in either the absence of flutamide or fungi. After 72 h, 5 mg flutamide dissolved in 20 μl dimethylformamide was added to the cultures and incubated for up to eight days. The entire cultures (supernatant and cells) were sonicated on ice (Sonicator U200S control, IKA Labortechnik) for 5 min at 50 % amplitude, with intervals of 30 sec after each minute to prevent overheating. Sonicates were centrifuged and the supernatant extracted with 50 ml ethyl acetate, and the extracts evaporated to dryness. Organic extracts were finally dissolved in 1 ml methanol and aqueous fractions were lyophilized and then reconstituted in 1 ml D 2 O prior to NMR analysis.

Analysis of fluorometabolites

Organic extracts in methanol were analysed by reversed phase HPLC using a Microsorb MV-100.5 C8 250 4.6 mm column. The eluate was monitored at 250 nm.

Compounds were eluted with a gradient of acetonitrile/water (10-90 % v/v acetonitrile) over 30 min (1 ml min -1 flow). The fluorometabolites were isolated by preparative reversed phase HPLC using a Zorbax SB-C18 9.4 mm x 25 cm column (Agilent Technologies) and a gradient of acetonitrile/water (20-60 % v/v acetonitrile) over 30 min (3.5 ml min -1 flow).

GC-MS analysis was conducted on per-trimethylsilylated extracts and nonderivatised culture extracts that were dissolved in 1 ml ethyl acetate. Silylation was performed on 1 ml lyophilised extracts by adding 50 l N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA) and heating at 100 °C for 1 h. Derivatised samples (1 µl) were injected in the splitless mode onto a HP-1 column (12 m x 0.25 mm x 0.33 µm) and the oven was held at 120 ºC for 2 min then raised to 300 ºC at 10 ºC min -1 .

Non-derivatized (1 µl) samples were injected in the splitless mode and the oven temperature held at 70 ºC for 3 min then raised to 250 ºC at 10 ºC min -1 . The mass spectrometer was operated in the scan mode.

Fluorine-19 NMR ( 19 F-NMR) spectroscopy was performed using a Varian 400 MHz spectrometer. Organic and aqueous extracts were dissolved in 800 µl of CDCl 3 or D 2 O, respectively, to provide a lock signal.

Results

Analysis of phase I metabolites

The microbial biotransformation of flutamide was investigated in selected Organic extracts analyzed by 19 F-NMR showed the presence of four fluorometabolites (Supplementary Figure 1) with resonances at -60.22 (2hydroxyflutamide), -60.21 (flutamide), -60.47 and -62.95 ppm (all singlets). Signals of flutamide and 2-hydroxyflutamide were assigned by comparison with authentic standards. The most predominant metabolite was the 2-hydroxyflutamide that it is also known to be the major pharmacologically active metabolite in mammals [START_REF] Kostrubsky | Transport, metabolism, and hepatotoxicity of flutamide, drug-drug interaction with acetaminophen involving phase I and phase II metabolites[END_REF]. HPLC analysis of the organic extracts (Fig. 1) showed that approx. 50% of flutamide was degraded to a variety of more polar metabolites by Cunninghamella species over eight days. No metabolite peaks were found in the control experiments and no disappearance of flutamide was observed in uninoculated control flasks. Flutamide had a retention time (t R ) of 27.5 min and was metabolised to four major metabolites with t R 20.8, 20, 19.5 and 17.7 min (peaks M1, M2, M3, M4, respectively). The chromatographic profile was comparable to that reported by [START_REF] Kang | Bioactivation of flutamide metabolites by human liver microsomes[END_REF]) using human liver microsomes, and the t R of M1 and M2 were identical to those of 2-hydroxyflutamide and 4-nitro-3-(trifluoromethyl)aniline standards, respectively. In an attempt to increase the degree of biotransformation, a longer period of incubation (up to 14 days) and different flutamide starting concentrations (0.01-1mg/ml) were investigated; in each case there was no difference in the extent of flutamide biotransformation (data not shown).

Peaks M1 and M2 had the same retention times as 2-hydroxyflutamide and 4nitro-3-(trifluoromethyl)aniline, respectively, by comparison with authentic standards.

To identify the other compounds the metabolites were isolated by preparative reversed phase HPLC and then re-analyzed by HPLC to confirm their retention times.

Owing to the small amounts recovered the metabolites were analysed by GC-MS (Table 1). The fractions containing the compounds M1 and M2 had mass spectra identical to the authentic standards of 2-hydroxyflutamide and 4-nitro-3-(trifluoromethyl)aniline, respectively, as anticipated from the HPLC analyses. The compounds M3 and M4 required silylation prior to GC-MS analysis; M3 had a similar mass spectrum to 2-hydroxyflutamide, thus is probably another mono-hydroxylated metabolite, and the molecular ion of M4 was identical to silylated 2-methyl-N-[4amino-3-(trifluoromethyl)phenyl]propanamide. In the recent study by [START_REF] Herath | Microbial metabolism. Part 11. Metabolites of flutamide[END_REF], the yeast Rhodotorula mucilaginosa (and other fungi that they investigated) produced two of the same metabolites that were identified here, M2 and M4, and these authors suggested that fungal metabolism of flutamide occurs

Analysis of phase II metabolites

Several flutamide conjugates such as sulfate, glucuronide and glutathione-related adducts have been recovered in urine from rats and humans [START_REF] Tevell | Flutamide metabolism in four different species in vitro and identification of flutamide metabolites in human patient urine by high performance liquid chromatography/tandem mass spectrometry[END_REF]). In our study, examination of aqueous extracts by 19 F-NMR showed six signals (Fig. 3A) with resonances at -50. 16, -59.99, -60.05, 60.72, -60.78 and -75.43 ppm. C. elegans has the ability to form conjugates with aromatic hydrocarbons [START_REF] Cerniglia | Glucuronide and sulfate conjugation in the fungal metabolism of aromatic-hydrocarbons[END_REF] and possible these are possibly phase II metabolites. The aqueous fraction was treated with the sequential addition of deconjugation enzymes (added in the order: sulfatase, β-glucuronidase and β-glucosidase) and the reactions monitored by 19 F-NMR spectroscopy between each addition, demonstrating that a sulfated metabolite was present (Fig. 3B). Subsequent treatment with other deconjugative enzymes did not result in any further changes to the spectrum. HPLC analysis of the aqueous extract revealed the presence of flutamide and 2-hydroxyflutamide, which were not completely removed by ethyl acetate extraction. It was not possible to determine the identity of the other compounds present, although other conjugation reactions, e.g. glutathione-S-transferase and glucuronsyl transferase, are known in C. elegans [START_REF] Zhang | Phase I and phase II enzymes produced by Cunninghamella elegans for the metabolism of xenobiotics[END_REF].

Fig 3 Discussion

We have determined the major biotransformation products of the anticancer drug flutamide in the fungus C. elegans. The work demonstrates for the first time using microorganisms that 2-hydroxyflutamide is the most predominant metabolite, which is similar to previous in vivo and in vitro studies conducted in mammals. The results support the potential of using the fungus Cunninghamella, which can transform a broad range of xenobiotic compounds in an analogous fashion to mammals and is therefore a model of mammalian drug metabolism to generate primary and conjugated metabolites of flutamide. Considering that promoting alternatives to animal testing is one of the objectives of the recent European Union legislation governing the testing and evaluation of chemicals, REACH (Regulation, Evaluation, Authorisation and Restriction of Chemicals), and the US Food and Drug Administration's guidelines for testing drug metabolites [START_REF] Guengerich | Introduction: Human Metabolites in Safety Testing (MIST) Issue[END_REF], the use of microbial systems is becoming an important tool for testing drugs and for production of valuable drug metabolites.

  Cunnighamella species previously shown to transform xenobiotics[START_REF] Asha | Cunninghamella -a microbial model for drug metabolism studies -a review[END_REF]. Morphological growth as dispersed mycelia of Cunninghamella species in liquid cultures is a crucial condition for biotransformation(Amadio and Murphy 2010). C. elegans DSM 8217, DSM 63299 and C. echinulata DSM 1905 grew forming clumps which resulted in negligible biotransformation. Interestingly, when the three species were mixed together as single inoculum the most favourable growth morphology of substrate was achieved, but it was not possible to determine the predominant species involved in the metabolic process. C. elegans DSM 1908 and C. blakesleeana DSM 1906 both had reproducible morphological growth as homogeneously dispersed mycelia and biotransformed flutamide to the same type of metabolites and with comparable yield. For the purpose of this study C. elegans 1908 strain was chosen for more detailed investigation.

Fig 1

 1 Fig 1

  bond cleavage. Here, we have shown that in Cunninghamella spp. the main pathway of biotransformation is oxidation to hydroxyflutamide, presumably via cytochrome P450 activity (Fig 2). Shet et al. (1997) demonstrated that the inhibition of flutamide metabolism in humans is caused by its own main metabolite, 2-hydroxyflutamide, which possibly accounts for the incomplete catabolism of flutamide in C. elegans.

Fig. 1 .

 1 Fig. 1. HPLC chromatogram of organic extracts from C. elegans cultures incubated

Fig. 2 .

 2 Fig. 2. Metabolism of flutamide by C. elegans and Rhodotorula mucilaginosa.

Fig. 3 .

 3 Fig. 3. 19 F NMR analysis of C. elegans aqueous extracts before (a) and after treatment

  Figure 1

Table 1 .

 1 GC-MS analysis of purified organically extractable metabolites of flutamide from C. elegans DSM1908

	Compound	t R (min)	m/z of M + (relative intensity)	m/z of fragment ions (relative intensity)
	Flutamide	6.72	348(29)	333(46), 259(13), 213(13),
				171(16), 144(24), 73 (100)
	M1	9.24	436(0.3)	421(2), 243(3), 147(6), 131(100),
				73(71)
	M2 a	10.53	278(59)	263(100), 216(16), 167(24),
				109(14), 77(67)
	M3 b	9.23	436(5)	421(23), 180(19), 165(14),
				143(12), 73(100)
	M4 b	6.44	390(32)	375(31), 301(14), 260(11),
				163(6), 73(100)
	a Analysis of this metabolite was performed using HP-5MS column.

b Silylated compound

Acknowledgments

The authors acknowledge financial assistance from the Environmental Protection Agency STRIVE Programme.


Tiina Karonen

Pertti J Neuvonen

MD Janne T Backman
email: janne.backman@hus.fi

The CYP2C8 inhibitor gemfibrozil does not affect the pharmacokinetics of zafirlukast

Keywords: gemfibrozil, zafirlukast, CYP2C8, drug interaction, pharmacokinetics

Purpose: Gemfibrozil, a strong inhibitor of cytochrome P450 (CYP) 2C8 in vivo, was recently found to markedly increase the plasma concentrations of montelukast in humans. Like montelukast, zafirlukast is a substrate of CYP2C9 and CYP3A4 and a potent inhibitor of CYP2C8 in vitro. To investigate the contribution of CYP2C8 to the metabolism of zafirlukast in vivo, we studied the effect of gemfibrozil on the pharmacokinetics of zafirlukast. Methods: Ten healthy subjects took in a randomized cross-over study gemfibrozil 600 mg or placebo twice daily for 5 days, and on day 3, a single oral dose of 20 mg zafirlukast. The plasma concentrations of zafirlukast were measured for 72 hours postdose.

Results:

The mean total area under the plasma concentration-time curve of zafirlukast during the gemfibrozil phase was 102% (geometric mean ratio; 95% confidence interval 89-116%) of that during the placebo phase. Furthermore, there were no statistically significant differences in the peak plasma concentration, time of peak concentration or elimination half-life of zafirlukast between the phases.

Conclusions: Gemfibrozil has no effect on the pharmacokinetics of zafirlukast, indicating that CYP2C8 does not play a significant role in the elimination of zafirlukast.

Introduction

Zafirlukast and montelukast are cysteinyl leukotriene receptor antagonists used in the treatment of asthma [START_REF] Calhoun | Summary of clinical trials with zafirlukast[END_REF][START_REF] Kelloway | Zafirlukast: the first leukotriene-receptor antagonist approved for the treatment of asthma[END_REF][START_REF] Lipworth | Leukotriene-receptor antagonists[END_REF]. The strong cytochrome P450 (CYP) 2C8 inhibitor gemfibrozil was recently shown to increase the area under the plasma concentration-time curve (AUC) of montelukast about 5-fold, markedly reducing the formation of its main metabolites [START_REF] Karonen | Gemfibrozil markedly increases the plasma concentrations of montelukast: a previously unrecognized role for CYP2C8 in the metabolism of montelukast[END_REF]. These findings indicate that CYP2C8 plays a major role in the metabolism of montelukast, and diverge from the product information of Singulair , which gives CYP2A6, 2C9 and 3A4 as the enzymes involved in montelukast metabolism. However, the role of CYP2C8 in the metabolism of the structurally related leukotriene receptor antagonist zafirlukast is not known.

The absolute oral bioavailability of zafirlukast is unknown, but food reduces its absorption by 30-60% [5]. The peak plasma concentrations of zafirlukast are observed at about 3 hours after a single oral dose, and the plasma concentrations decline in a biphasic manner, with a terminal elimination half-life of about 10 hours [5,[START_REF] Dekhuijzen | Pharmacokinetic profile of zafirlukast[END_REF]. Zafirlukast is highly bound to plasma proteins (99.7-99.9%) and is extensively metabolised [5,7]. According to preclinical in vitro studies, at least CYP2C9 and CYP3A4 can contribute to its hepatic microsomal metabolism [7][START_REF] Savidge | Metabolism and excretion of zafirlukast in dogs, rats, and mice[END_REF][START_REF] Kassahun | Zafirlukast metabolism by cytochrome P450 3A4 produces an electrophilic alpha,betaunsaturated iminium species that results in the selective mechanism-based inactivation of the enzyme[END_REF]. Like montelukast, also zafirlukast is a CYP2C8 inhibitor in vitro, with an IC 50 value of 0.6 µM [START_REF] Walsky | Examination of 209 drugs for inhibition of cytochrome P450 2C8[END_REF]. This is at least an order of magnitude lower than its IC 50 value for CYP2C9 or any other CYP isoform, consistent with a relatively selective inhibitory effect on CYP2C8 [START_REF] Walsky | Examination of 209 drugs for inhibition of cytochrome P450 2C8[END_REF][11][START_REF] Jaakkola | Pioglitazone is metabolised by CYP2C8 and CYP3A4 in vitro: potential for interactions with CYP2C8 inhibitors[END_REF][13]. In vivo, however, neither montelukast nor zafirlukast affected the pharmacokinetics of the CYP2C8 substrate pioglitazone [START_REF] Jaakkola | Montelukast and zafirlukast do not affect the pharmacokinetics of the CYP2C8 substrate pioglitazone[END_REF], indicating that despite their high affinity for CYP2C8, their free concentrations in vivo are not sufficient to cause inhibition of CYP2C8.

The major metabolite of gemfibrozil, gemfibrozil 1-O-β glucuronide, is a potent and selective mechanism-based inhibitor of CYP2C8, which explains the strong and long-lasting CYP2C8 inhibitory effect of gemfibrozil in vivo [START_REF] Shitara | Gemfibrozil and its glucuronide inhibit the organic anion transporting polypeptide 2 (OATP2/OATP1B1:SLC21A6)-mediated hepatic uptake and CYP2C8-mediated metabolism of cerivastatin: analysis of the mechanism of the clinically relevant drug-drug interaction between cerivastatin and gemfibrozil[END_REF][START_REF] Ogilvie | Glucuronidation converts gemfibrozil to a potent, metabolism-dependent inhibitor of CYP2C8: implications for drug-drug interactions[END_REF][START_REF] Baer | Benzylic oxidation of gemfibrozil-1-O-beta-glucuronide by P450 2C8 leads to heme alkylation and irreversible inhibition[END_REF][18][19]. In addition to increasing the concentrations of montelukast, gemfibrozil has increased the concentrations of several CYP2C8 substrates, e.g. the AUC of repaglinide 8-fold, that of cerivastatin 6-fold and that of pioglitazone 3-fold [START_REF] Backman | Gemfibrozil greatly increases plasma concentrations of cerivastatin[END_REF][START_REF] Jaakkola | Effects of gemfibrozil, itraconazole, and their combination on the pharmacokinetics of pioglitazone[END_REF][START_REF] Niemi | Effects of gemfibrozil, itraconazole, and their combination on the pharmacokinetics and pharmacodynamics of repaglinide: potentially hazardous interaction between gemfibrozil and repaglinide[END_REF][START_REF] Deng | Effect of gemfibrozil on the pharmacokinetics of pioglitazone[END_REF]. Gemfibrozil itself is also a relatively potent inhibitor of CYP2C9 in vitro, while its inhibitory effects on other CYP enzymes are weaker [START_REF] Wen | Gemfibrozil is a potent inhibitor of human cytochrome P450 2C9[END_REF][START_REF] Wang | Gemfibrozil inhibits CYP2C8-mediated cerivastatin metabolism in human liver microsomes[END_REF]. In vivo, however, it has not inhibited the CYP2C9-mediated metabolism of warfarin [START_REF] Lilja | Effect of gemfibrozil on the pharmacokinetics and pharmacodynamics of racemic warfarin in healthy subjects[END_REF], and is therefore unlikely to have any significant inhibitory effects on CYP enzymes other than CYP2C8.

In this study, we investigated the possible effects of gemfibrozil on the pharmacokinetics of zafirlukast in healthy subjects, in order to find out whether CYP2C8 is involved in the metabolism of zafirlukast in humans, similarly as it was recently found to participate in the metabolism of montelukast.

Methods

Subjects

Ten healthy volunteers (7 men, 3 women; age 20-27 years; weight 57-93 kg) participated in the study after each gave a written informed consent and were ascertained to be healthy by medical history, clinical examination, and routine laboratory tests. None received continuous medication or used hormonal contraception or was a tobacco smoker. The study protocol was approved by the Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District and by the Finnish Medicines Agency.

Study design

A randomized, placebo-controlled, 2-phase crossover study with a washout period of 4 weeks between the phases was carried out. Each subject took either 600 mg gemfibrozil (Lopid 600 mg tablets, Gödecke, Freiburg, Germany), or unmatched placebo (University Pharmacy Placebo-tablets, University Pharmacy, Helsinki, Finland) twice daily at 0900 and 2100 hours for 5 days. On day 3, the morning dose of these medications was taken at 0800 hours, and 1 h later, a single dose of 20 mg zafirlukast (Accolate 20 mg, Astra Zeneca UK Ltd., Macclesfield, UK) was administered orally with 150 ml water.

The subjects had fasted for 9 hours before zafirlukast intake and received a standardised meal 3 h and standardised light meals 7 h and 11 h after zafirlukast intake.

Blood sampling and determination of plasma drug concentrations

On days of zafirlukast administration, timed blood samples (5 or 10 ml) were drawn from a cannulated forearm vein before and 0.5, 1, 2, 3, 4, 5, 7, 9, 12, 24, 48 and 72 h after administration of zafirlukast.

Blood samples were collected into tubes containing ethylenediaminetetraacetic acid (EDTA). Plasma was separated immediately and stored at -70°C until analysis.

Plasma samples (0.5 ml) were spiked with internal standard (IS; valdecoxib), and zafirlukast concentrations were measured by use of SCIEX API 2000 liquid chromatography-tandem mass spectrometry system (Sciex Division of MDS Inc, Toronto, ON, Canada) after extraction from plasma with ethyl acetate, as described earlier [START_REF] Bharathi | Development and validation of a sensitive LC-MS/MS method with electrospray ionization for quantitation of zafirlukast, a selective leukotriene antagonist in human plasma: application to a clinical pharmacokinetic study[END_REF]. Chromatography was performed on a Symmetry C8 reversed phase column (2.1x150 mm; Waters Corporation, Milford Mass, USA) using gradient elution, as described [START_REF] Bharathi | Development and validation of a sensitive LC-MS/MS method with electrospray ionization for quantitation of zafirlukast, a selective leukotriene antagonist in human plasma: application to a clinical pharmacokinetic study[END_REF]. The limit of quantification for zafirlukast was 0.5 ng/ml. The between-day coefficient of variation (CV) for zafirlukast was 5.1% at 3.5 ng/ml, 11.1% at 35 ng/ml and 6.2% at 350 ng/ml. Gemfibrozil and its glucuronide did not interfere with the assay.

The plasma concentrations of gemfibrozil and gemfibrozil 1-O-β glucuronide in samples taken before and at 1, 3, 5, 9 and 12 hours after zafirlukast administration were determined by use of Applied Biosystems API 2000 Q Trap liquid chromatography-tandem mass spectrometry system (Sciex Division of MDS) as described before [19]. The limits of quantification for gemfibrozil and gemfibrozil 1-O-β glucuronide were 0.0025 µg/ml and the between-day CVs were 3.1-4.6% and 2.8-8.0% at relevant concentrations, respectively.

Pharmacokinetics

The pharmacokinetics of zafirlukast were characterised by peak plasma concentration (C max ), time of peak plasma concentration (t max ), elimination half-life (t ½ ), and AUC from 0 to 72 hours or infinity (AUC 0-72, 0-∞ ). The C max and t max values were taken directly from the original data. The terminal loglinear part of each plasma concentration-time curve was identified visually, and the elimination rate constant (k e ) was determined by linear regression analysis of the log-linear part of the concentrationtime curve. The t ½ was calculated by the equation t ½ = ln2/k e . The AUC values were calculated by the linear trapezoidal rule for the rising phase and the log-linear trapezoidal rule for the descending phase, with extrapolation to infinity by division of the last measured concentration by k e . The pharmacokinetics of gemfibrozil and gemfibrozil 1-O-β glucuronide were characterised by peak plasma concentration (C max ), time of peak plasma concentration (t max ), and AUC from 0 to 13 hours after the morning dose of gemfibrozil on day 3 (AUC 0-13 ). The pharmacokinetic calculations were performed with MK-Model, version 5.0 (Biosoft, Cambridge, UK).

Statistical analysis

The pharmacokinetic variables between the two phases were compared with the paired t-test, or, in the case of t max , with the Wilcoxon signed-rank test. Logarithmic transformation of C max and AUC values was performed before statistical analysis, and 95% confidence intervals were calculated for the geometric mean ratios of these variables. The level of statistical significance was P<0.05. The analysis was performed with SPSS for Windows version 17.0 (SPSS Inc, Chicago, IL, USA).

Results

Zafirlukast pharmacokinetics

Gemfibrozil 600 mg twice daily had no significant effects on any of the pharmacokinetic variables of zafirlukast (Fig. 1, Table 1). The mean AUC (0-∞) of zafirlukast in the gemfibrozil phase, expressed as the geometric mean ratio, was 102% (range 72-137%, 95% confidence interval 89-116%, P=0.79) of the control (placebo values). The mean (C max ) of zafirlukast was 102% (range 65-134%, 95% confidence interval 87-120%, P=0.72), and its mean elimination half-life (t ½ ) was 104% (range 85-131%, 95% confidence interval 91-117%, P=0.50) of the control. The t max of zafrlukast was not changed significantly by gemfibrozil.

Gemfibrozil and gemfibrozil 1-O-glucuronide

During the gemfibrozil phase on day 3 (i.e. when zafirlukast was administered), the mean standard deviation (SD) C max of gemfibrozil was 23.4 6.9 µg/ml and its AUC 0-13 was 98.9 42.2 µg h/ml (Fig. 1). The mean C max of gemfibrozil 1-O-glucuronide was 18.8 4.1 µg/ml and its AUC 0-13 was 111.3 38.4µg h/ml. The mean SD predose morning concentrations of gemfibrozil and gemfibrozil 1-Oglucuronide were 1.8 1.7 and 2.1 1.9 µg/ml on day 3, 1.6 0.9 and 2.2 1.5 µg/ml on day 4, 1.2 0.6 and 1.7 1.0 µg/ml on day 5 and 1.5 0.6 and 2.0 1.1 µg/ml on day 6, respectively. The individual concentrations were consistent with good compliance by all subjects.

Discussion

Zafirlukast has been shown to be a potent and relatively selective inhibitor of CYP2C8 in vitro, yet having no inhibitory effect on the metabolism of the CYP2C8 substrate pioglitazone in vivo [START_REF] Walsky | Examination of 209 drugs for inhibition of cytochrome P450 2C8[END_REF][START_REF] Jaakkola | Pioglitazone is metabolised by CYP2C8 and CYP3A4 in vitro: potential for interactions with CYP2C8 inhibitors[END_REF][START_REF] Jaakkola | Montelukast and zafirlukast do not affect the pharmacokinetics of the CYP2C8 substrate pioglitazone[END_REF]. In this and other regards zafirlukast is very similar to montelukast, whose concentrations are markedly increased by gemfibrozil [START_REF] Karonen | Gemfibrozil markedly increases the plasma concentrations of montelukast: a previously unrecognized role for CYP2C8 in the metabolism of montelukast[END_REF]. This led us to investigate the effect of gemfibrozil on the pharmacokinetics of zafirlukast in healthy subjects, in order to compare the interaction susceptibility of zafirlukast to that of montelukast and to evaluate the role of CYP2C8 in the metabolism of zafirlukast in humans.

In the present study, which had a similar design compared with our previous gemfibrozilmontelukast study [START_REF] Karonen | Gemfibrozil markedly increases the plasma concentrations of montelukast: a previously unrecognized role for CYP2C8 in the metabolism of montelukast[END_REF], the usual therapeutic dose of gemfibrozil (600 mg twice daily) did not affect the pharmacokinetic variables of zafirlukast in humans. The AUC, C max , and t ½ of zafirlukast remained practically unchanged compared to placebo, as demonstrated by the narrow 95% CIs of their gemfibrozil/placebo geometric mean ratios. Based on individual plasma concentrations of gemfibrozil, the compliance in taking the gemfibrozil doses was excellent. Also, as the strong CYP2C8 inhibitory effect of gemfibrozil persists even after its concentrations have declined to less than 1% of its maximum concentration [19], the lack of interaction observed in the present study cannot be explained by the decline in plasma concentrations of gemfibrozil and gemfibrozil 1-O-glucuronide between gemfibrozil doses. Accordingly, our findings demonstrate with confidence that CYP2C8 does not contribute significantly to the elimination of zafirlukast in humans.

According to preclinical in vitro studies, which included evaluation of most major CYP enzymes (excluding CYP2C8), CYP2C9 and CYP3A4 are involved in the metabolism of zafirlukast in vitro [START_REF] Kassahun | Zafirlukast metabolism by cytochrome P450 3A4 produces an electrophilic alpha,betaunsaturated iminium species that results in the selective mechanism-based inactivation of the enzyme[END_REF]. In asthma patients, the CYP3A4 inhibitor erythromycin did not increase the concentrations of zafirlukast [7]. Thus, the contribution of CYP3A4 to the total metabolism of zafirlukast seems to very small in vivo. Furthermore, as the present findings indicate lack of contribution by CYP2C8, CYP2C9 may be the major enzyme involved in the metabolism of zafirlukast in vivo. However, further studies are needed to resolve this question.

Like montelukast, zafirlukast has a high molecular weight (575.7, vs 608.2 for montelukast), its primary metabolic routes involve hydroxylation at multiple sites, and both CYP2C9 and CYP3A4 can catalyse its hydroxylations in vitro [START_REF] Savidge | Metabolism and excretion of zafirlukast in dogs, rats, and mice[END_REF][START_REF] Kassahun | Zafirlukast metabolism by cytochrome P450 3A4 produces an electrophilic alpha,betaunsaturated iminium species that results in the selective mechanism-based inactivation of the enzyme[END_REF]. Furthermore, like montelukast, zafirlukast is a potent competitive inhibitor of CYP2C8 in vitro, with an IC 50 value of 0.4 µM [START_REF] Walsky | Examination of 209 drugs for inhibition of cytochrome P450 2C8[END_REF], but due to extensive protein binding and very low unbound plasma concentrations (peak < 10 nM) it has no inhibitory effects on CYP2C8 in vivo [START_REF] Jaakkola | Montelukast and zafirlukast do not affect the pharmacokinetics of the CYP2C8 substrate pioglitazone[END_REF]. In addition, the in vitro affinity of zafirlukast towards CYP2C8 is much higher than that towards CYP2C9 and CYP3A4 (IC 50 7.0 µM and 20.9 µM, respectively) or other CYP forms [11]. Yet, the present findings indicate that montelukast and zafirlukast differ from each other with respect to the contribution of CYP2C8 to their metabolism. A possible explanation for this finding is that despite the high affinity of zafirlukast for CYP2C8, the capacity (and intrinsic clearance) of CYP2C8 to metabolise zafirlukast is much lower than its capacity to metabolise montelukast.

The clinical implication of the present findings is that although montelukast concentrations are increased several fold by the strong CYP2C8 inhibitor gemfibrozil, the pharmacokinetics of zafirlukast are not affected by gemfibrozil. Thus, these structurally related cysteinyl leukotriene receptor antagonists clearly differ in the susceptibility to interact with gemfibrozil and probably also with other inhibitors of CYP2C8. Although both montelukast and zafirlukast are relatively safe drugs and the clinical significance of the gemfibrozil-montelukast interaction is probably limited, zafirlukast can be a preferable choice for patients requiring a leukotriene receptor antagonist, when using concomitantly gemfibrozil or another therapeutic drug inhibiting CYP2C8.

In conclusion, normal therapeutic doses of the fibric acid derivative gemfibrozil have no effect on the pharmacokinetics of zafirlukast in humans. These findings indicate that CYP2C8 does not contribute significantly to the metabolic elimination of zafirlukast in vivo. Moreover, unlike montelukast, zafirlukast is not susceptible to interactions involving the CYP2C8 enzyme, which makes it a preferable choice, compared to montelukast, in patients taking concomitantly CYP2C8 inhibiting drugs like gemfibrozil.

Figure 1 Mean

 1 Figure 1

Table 1

 1 Pharmacokinetic variables of zafirlukast in 10 healthy volunteers after a single oral dose of 20 mg zafirlukast on day 3 of a 5-day treatment with 600 mg gemfibrozil twice daily or placebo.Data are mean ± SD; t max data are given as median with range. C max , observed peak plasma concentration; t max , time to reach C max ; t ½ , elimination half-life; AUC 0-∞ , area under the plasma concentration versus time curve.

	Variable	Placebo phase	Gemfibrozil phase Percentage of control	P-value
		(control)		(95% CI)
	C max (ng/ml)	648±277	664±267	102% (87-120%)	0.8
	% of control (range)	100%	102% (65-134%)
	t max (h)	1.5 (1-4)	2 (1-3)		0.3
	t ½ (h)	9.3±3.3	9.7±3.3	104% (91-117%)	0.5
	% of control (range)	100%	104% (85-131%)
	AUC 0-∞ (ng•h/ml)	2087±1064	2088±920	102% (89-116%)	0.8
	% of control (range)	100%	100% (72-137%)

Acknowledgments

We would like to thank Mrs Eija Mäkinen-Pulli, Mrs Lisbet Partanen and Mr Jouko Laitila for skilful technical assistance. This study was supported by grants from the Helsinki University Central Hospital Research Fund, and the Sigrid Jusélius Foundation, Finland. None of the authors has any financial or personal relationships that could be perceived as influencing the research described.

The experiments comply with the current laws of Finland, and the study protocol was approved by the Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District and by the Finnish Medicines Agency.