# Patent

## Title
Polymorphisms in ABCB1 associated with a lack of clinical response to medicaments

## Abstract

The present invention relates to methods, compositions, kits and reagents for determining the prognosis of a clinical response in a human patient to a medicament which acts in the central nervous system (CNS) and which is a substrate of the ABCB1 protein. Further, the invention relates to a combination of medicaments for the treatment of human patients having specific polymorphisms in the ABCB1 gene.

## Background
This application is a divisional of U.S. Ser. No. 12/663,997 filed Dec. 10, 2009, which is a 35 U.S.C. 371 National Phase Entry Application from PCT/EP2008/004737, filed Jun. 12, 2008, which claims the benefit of U.S. Ser. No. 60/943,335 filed on Jun. 12, 2007, the disclosures of which are incorporated herein in their entirety by reference.


DESCRIPTION
The present invention relates to methods, compositions, kits and reagents for determining the prognosis of a clinical response in a human patient to a medicament which acts in the central nervous system (CNS) and which is a substrate of the ABCB1 protein. Further, the invention relates to a combination of medicaments for the treatment of human patients having specific polymorphisms in the ABCB1 gene.
Major depression constitutes one of the greatest disease burdens world-wide and is anticipated to be the second leading global disease burden by the year 2020 trailing only cardiovascular disease (Murray and Lopez, 1996). Antidepressants are the first line treatment of major depression, but their overall clinical efficacy is unsatisfactory as remission, i.e. full resolution of depressive symptoms, occurs in only about half of the patients after a trial with an adequately dosed single drug. Remission rates even decline following successive treatment failures (Trivedi et al., 2006)).
One of the possible reasons for poor antidepressant response is their inadequate penetration into the central nervous system, which depends on the drug's ability to pass the blood-brain barrier (BBB). This barrier includes active transporters that are expressed at the luminal membrane of the endothelial cells lining the small blood capillaries that form the blood-brain barrier. These molecules actively transport their substrates against a concentration gradient out of the cells back into the blood circulation, thus potentially keeping brain drug concentrations low. One of the best-studied transporter molecules is P-glycoprotein (P-gp) (Cordon-Cardo et al., 1989; Thiebaut et al., 1987). P-gp is a member of the highly conserved super-family of ATP-binding cassette (ABC) transporter proteins (Ambudkar et al., 1999). In humans, this 170-kDa glycoprotein is encoded on chromosome 7 by the ABCB1 gene, also known as the multidrug resistance 1 (MDR1) gene (Callen et al., 1987; Chin et al., 1989). P-gp acts as an active efflux pump for a wide range of compounds including a number of drugs and steroid hormones (Schinkel et al., 1996; Uhr et al., 2000, 2002, 2004, 2005). P-gp at the BBB thus regulates intracerebral concentrations and, by extension, may affect the clinical response of CNS-targeting drugs that are substrates of this transporter.
It was speculated that inter-individual differences in the activity of the ABCB1 gene can account in part for the great variation in clinical response to antidepressants in psychiatric patients, even at comparable plasma levels (Uhr and Grauner, 2003). A further study showed different enhancement of penetration of the antidepressants doxepin, venlafaxine and paroxetine in the brain of mice with an ABCB1ab knockout mutation (Uhr, Grauer and Holsboer, 2003).
Numerous papers describe polymorphisms in ABCB1 (Kioka et al., 1989; Stein et al., 1994; Mickley et al., 1998; Hoffmeyer et al., 2000; Kim et al., 2001; Ito et al., 2001; Cascorbi et al., 2001; Tanabe et al., 2001; Eichelbaum et al., 2004), and a multitude of single nucleotide polymorphisms (SNPs) are listed in public SNP databases.
WO 01/09183 discloses polymorphisms in the human ABCB1 gene for the use in diagnostic tests to improve therapy of established drugs and help to correlate genotypes with drug activity and side effect.
WO 2005/108605 relates to polymorphisms in the ABCB1 gene which are associated with an insufficient clinical response to a CNS active medicament which is a substrate of the ABCB1 protein. Seven single nucleotide polymorphisms (SNPs) in the ABCB1 gene are described, which are associated with clinical response to antidepressant drugs. However, there is no evidence in this document that beside the specific polymorphisms disclosed any further polymorphisms in the ABCB1 gene might be associated with a clinical response to CNS-active medicaments.
Thus, there is still a need for identifying polymorphisms of the ABCB1 gene involved in regulating intracerebral concentrations of CNS-active medicaments. It was the object of the present invention to determine new single nucleotide polymorphisms in the ABCB1 gene which are predictive for treatment course and outcome of CNS-active medicaments, which are ABCB1 transporter substrates.
In the studies on which the present application is based the inventors surprisingly were able to identify several new polymorphisms in the ABCB1 gene, which have a clear and statistically relevant association with an insufficient clinical response to CNS-active medicaments. The inventors succeeded in identifying the SNPs rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067 as particularly responsible for this association. The presence of these particular SNPs proved highly predictive for treatment course and outcome of CNS-active medicaments.
A first aspect of the invention relates to a method for determining the prognosis of a clinical response in a human patient to a central nervous system (CNS)-active medicament which is a substrate of the ABCB1 protein wherein the presence of at least one first polymorphism in the ABCB1 gene of said patient is determined, wherein said first polymorphism is selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067 and combinations thereof.
A further aspect of the invention relates to a diagnostic composition or kit for the prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein, comprising at least one primer or probe for determining at least one first polymorphism in the ABCB1 gene in said patient, wherein said first polymorphism is selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420, rs12720067 and combinations thereof.
A still further aspect of the invention relates to a microarray for the prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein comprising a carrier having immobilized thereto at least one probe for determining at least one first polymorphism in the ABCB1 gene in said patient, wherein said first polymorphism is selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420, rs12720067 and combinations thereof.
Still a further aspect of the invention relates to a primer or probe for the prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein comprising a carrier having immobilized thereto at least one probe for determining at least one first polymorphism in the ABCB1 gene in said patient, wherein said polymorphism is selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420, rs12720067 and combinations thereof.
Finally, a further aspect of the invention relates to a therapeutic composition or kit comprising:

    (a) a CNS-active medicament which is a substrate of the ABCB1 protein;
    (b) a further medicament which is an inhibitor of the ABCB1 protein for treating a human patient having at least one polymorphism in the ABCB1 gene, wherein said polymorphism is selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420, rs12720067 and combinations thereof.


The polymorphisms in the human ABCB1 gene disclosed in the present application have a statistically significant association with a delayed, partial sub-optimal or lacking clinical response to medicaments which act in the central nervous system and which are substrates of the ABCB1 protein. A statistically significant association is preferably p<0.05, more preferably p<0.01 and most preferably p<0.001. The determination of significance may be carried out by a polymorphism/haplotype analysis of a sufficient number, e.g. of at least 40, preferably of at least 80, more preferably of at least 100 normal cases. More preferably the determination of significance may be carried out as described in the Example section.
The polymorphisms of the invention are single nucleotide polymorphisms (SNPs). Preferred SNPs are selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067. Surprisingly it was found that the polymorphisms highly associated with the response to CNS-active medicaments are located in a single haplotype block (FIG. 4). The SNPs rs2235067, rs4188740, rs2032583, rs4148739, rs11983225, rs2235040, rs12720067 as well as the SNPs rs7787082 and rs10248420 exhibited an r-square of >0.8 with each other. All highly associated SNPs are located in introns and with a D′ of more than 90% in linkage disequilibrium (LD) with the best examined exon SNPs rs1045642 (C3435T), rs2032582 (G2677T) and rs1128503 (C1236T).
The sequence of the human ABCB1 gene including the introns is described in the human reference sequence of the National Center for Biotechnolgy Information (NCBI). The sequence is accessible in gene databases such of NCBI, or Genomics Browser (UCSC) using the reg. sep #=ONM.000927 or the gene ID ABCB1. With regard to the nomenclature of the polymorphisms it is referred to ABCB1 at chr7:8670884-87180500-(NM_000927) ATP-binding cassette, sub-family B (MDR/TAP), NM #=Reference Sequence Number, Localisation on genome according to the May 2004 human reference sequence (UCSC version hg17) based on NCBI Build 33. All polymorphisms have been selected from the public SNP database of SNP. The location of the SNPs within ABCB, is according to the May 2004 human reference sequence (UCSC version mg 17).
The CNS-active medicaments are preferably selected from the group consisting of antidepressants, anxiolytics, hypnotics, cognitive enhancers, antipsychotics, neuroprotective agents, antiemetics, antiepileptics, antibiotics, anticancer agents, antimycetics, antiparkinson agents, antiviral agents, glucocorticoids, immunosuppressants, statins, neuroleptics, and opioids. A preferred class of medicaments are antidepressants. Examples of CNS-active medicaments are described in Schatzberg and Nemeroff, “The American Psychiatric Publishing Textbook of Psychopharmacology”, Amer Psychiatric Pr, 2004.
A preferred class of medicaments are antidepressants. Examples of antidepressants are imipramine, amitriptyline, amitriptylinoxid, bupropion, citalopram, clomipramine, doxepine, desipramine, flesinoxan, fluoxetine, fluvoxamine, maprotiline, mirtazepine, mianserin, moclobemide, nefazodone, nortriptyline, paroxetine, selegiline, sertraline, tranylcypromine, trazodon, trimipramine and, venlafaxine. Preferred examples of antidepressants which are substrate of the ABCB1 protein are amitriptyline, citalopram, doxepine, flesinoxan, nortriptyline, paroxetine, trimipramine, and venlafaxine. Especially preferred examples of antidepressants are citalopram, venlafaxine, amitriptyline or paroxetine.
Further preferred CNS-medicaments are anxiolytics, hypnotics, cognitive enhancers and, antipsychotics. Examples of anxiolytics include but are not limited to alprazolam, bromazepam, clonazepam, diazepam, iorazepam, halazepam, chlordiazepoxide, buspirone, azapirone, pagoclone, prazosin, biperiden and, kava kava. Examples of hypnotics are secobarbital, pentobarbital, methaqualone, ethchlorvynol, chloral hydrate, mebrobamate. Examples of cognitive enhancers are acetyl L-carnitine (ALCAR), adrafinil, aniracetam, deprenyl, galantamine, hydergine, idebenone, modafinil, picamilon, piracetam, pyritinol, vasopressin and, vinpocetine. Examples of antipsychotics are aripiprazol, risperidon, olanzapine, quetiapine and, ziprasidone, chlorpromazine, fluphenazine, trifluoperazine, perphenazine, thioridazine, holoperidol, thiothixene, molindone, loxapine, clozapine, olanzapine, quetiapine, risperidone, sertindole, ziprasidone, amisulpid, aripriprazol, benperidol, chlorpromazine, chlorprothixen, flupentixol, fluspirilen, levomepromazin, benperidol, melperon, perazin, perphenazin, pimozid, pipamperon, sulpirid, triflupromazin, zotepin, zuclopenthixol.
Further preferred examples of substrates of the ABCB1 protein are antiemetics such as domperidone or ondansetron, antiepileptics such as carbamazepine, felbamate, lamotrigin, phenobarbita and phenytoin, antiparkinson agents such as budipin or L-Dopa, neuroleptics such as olanzapine, quetiapine, risperidone and sulpiride, or opioids such as fentanyl or morphine.
The patients to be tested are human patients suffering from a disorder which may be treated with a CNS-active medicament, e.g. a psychiatric disorder. Particularly, the patients have a depressive disorder, dysthymia and/or a bipolar disorder.
The present invention relates to the determination of the prognosis of a clinical response in a human patient. The term “a clinical response” in the present application with regard to antidepressants relates to a remission status after four to six weeks of treatment. Methods of assessing a remission status are well known in the art. For example, remission can be evaluated according to the Hamilton Depression Rating Scale (HAM-D; Hamilton, Br. J. Soc. Clin. Psychol. 6 (1967) 278-296). A HAM-D score of 10 or below is regarded as remission of the depressive symptoms. Remission can also be assessed according to a normalisation of the hypothalamic-pituitary-adrenocortical (HPA) axis. The development and course of depression is causally linked to impairments in the central regulation of the HPA axis. Abnormalities in the HPA axis can be measured using the dexamethasone-suppression test (DST) or the combined dexamethasone/corticotropin-releasing hormone (Dex/CRH) test. Changes in cortisol and/or adrenocorticotropic hormone (ACTH) measurements during the DST or Dex/CRH test are indicative of HPA dysfunction while normalisation of cortisol and or ATCH is indicative of remission (Heuser et al, J. Psychiat. Res. 28 (1994) 341-356; Rybakowski and Twardowska, J. Psychiat. Res. 33 (1999) 363-370; Zobel et al, J. Psychiat. Res. 35 (2001) 83-94; Künzel et al, Neuropsychopharmacology 28 (2003) 2169-2178). Methods and conditions for performing the DST and Dex/CRH test are well known in the art, see for example Heuser et al, J. Psychiat. Res. 28 (1994) 341-356; Künzel et al, Neuropsychopharmacology 28 (2003) 2169-2178. Briefly, individuals may be pre-treated at 23:00 with an oral administration of 1.5 mg dexamethasone. For the DST test, a blood sample may be drawn at 8:00 prior to dexamethasone administration (i.e. pre-dexamethasone) and at 8:00 the morning following dexamethasone administration (i.e. post-dexamethasone). For the Dex/CRH test, a venous catheter may be inserted at 14:30 the day following dexamethasone administration and blood may be collected at 15:00, 15:30, 15:45, 16:00, and 16:15 into tubes containing EDTA and trasylol (Bayer Inc., Germany). At 15:02, 100 mg of human CRH (Ferring Inc., Germany) may be administered intravenously. Measurement of plasma cortisol concentrations may be done according to known methods, e.g. using a commercial radioimmunoassay kit (ICN Biomedicals, USA). Plasma ACTH concentrations may also be measured according to known methods, e.g. using a commercial immunometric assay (Nichols Institute, USA). With regard to other classes of medicaments, the term “clinical response” may be defined as a reduction of the severity of symptoms by over 50% from the severity of symptoms at the beginning of treatment.
The presence of a polymorphism associated with a delayed, partial, sub-optimal or lacking clinical response to a medicament is preferably determined by a genotyping analysis of the human patient. According to the invention, (a) at least one polymorphism selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067 is determined. In a preferred embodiment of the invention, at least one additional polymorphism (b) being in linkage disequilibrium with at least one of the polymorphisms of (a) is determined. The polymorphisms of (b) being in linkage disequilibrium with the polymorphisms of (a) are preferably selected from the group consisting of rs2235067, rs2032583, rs2235040, and rs2235015.
The genotyping analysis frequently comprises the use of polymorphism-specific primers and/or probes capable of hybridizing with the human ABCB1 gene and allowing a discrimination between polymorphisms, particularly SNPs at a predetermined position. For example, the genotyping analysis may comprise a primer elongation reaction using polymorphism-specific primers as described in the examples. The determination of individual polymorphisms may be carried out by mass-spectrometric analysis as described in the examples. A further preferred embodiment comprises a microarray analysis which is particularly suitable for the parallel determination of several polymorphisms. Suitable microarray devices are commercially available.
According to a further embodiment of the invention the prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein can also be determined by detecting a change in the function of the ABCB1 gene. The determination of the transporting activity of the ABCB1 gene product at the blood-brain barrier can be used as an indicator for the clinical response in a human patient to a CNS-active medicament. An assay for detecting a change in the function of the ABCB1 gene may comprise imaging techniques like positron emission tomography (PET) and MR-spectroscopy.
According to a particularly preferred embodiment of the invention, the assay of the transporting activity is accomplished in addition to the determination of the at least one specific polymorphism of the invention described above. Based on the results of polymorphism determination a prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein can be made. Thus, on the one hand, if the patient to be tested does not have a polymorphism which is associated with an insufficient clinical response to the medicament, a favourable prognosis for a clinical response can be given and the medicament for obtaining the clinical response may be manufactured, prescribed and administered in a standard dose whereby a sufficient clinical response may be expected with high probability. On the other hand, the patient to be tested may have one or a plurality of polymorphisms which are associated with an unfavourable prognosis for a clinical response of the medicament. If such an unfavourable prognosis for a clinical response is given, a modified therapeutic regimen for the patient may be used. For example, the medicament may be administered in a dose which is higher than the standard dose, e.g. by increasing the dose strength and/or the number of doses to be administered per time interval. Further, the formulation of the medicament may be manufactured and adminstered which shows an increased permeation through the blood-brain barrier, e.g. by including a blood-brain barrier permeation aid such as those indicated in Table 1.
Further, the manufacture and administration of the medicament may be combined with the manufacture and administration of a further medicament which is an inhibitor of the ABCB1 protein. Suitable inhibitors of the ABCB1 protein are known and for example described in US 2003/0073713 A1 which is herein incorporated by reference. Further ABCB1 inhibitors are described in Marzolini C, et al (2004), Clin Pharmacol Ther. 2004 January; 75(1):13-33 which is herein incorporated by reference.
As outlined above, the present invention also relates to diagnostic compositions and kits for the prognosis of a clinical response in a human patient to a CNS-active medicament which is a substrate of the ABCB1 protein. A diagnostic composition or kit preferably comprises (a) at least one primer and/or probe for determining at least one polymorphism selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067. In a preferred embodiment, the diagnostic composition or kit further comprises at least one additional primer and/or probe for determining at least one polymorphism (b) being in linkage disequilibrium with said polymorphism of (a). The additional primer and/or probe is preferably for determining at least one polymorphism selected from the group consisting of rs2235067, rs2032583, rs2235040, and rs2235015. The primers and/or probes may be nucleic acid molecules such as a DNA, an RNA or nucleic acid analogues such as peptide nucleic acids (PNA) or a locked nucleic acids (LNA). The primer and/or probes are selected such that they can discriminate between polymorphisms at the position to be analyzed. Usually, the primers and probes have a length of at least 10, preferably at least 15 up to 50, preferably up to 30 nucleic acid building blocks, e.g. nucleotides. In a preferred embodiment, the composition or kit comprises at least one primer which hybridizes to the human ABCB1 gene under predetermined conditions, e.g. of temperature, buffer, strength and/or concentration of organic solvent, and which allows a specific determination of the polymorphism to be tested.
The composition or kit preferably further comprises an enzyme for primer elongation such as a DNA polymerase, nucleotides, e.g. chain elongation nucleotides such as deoxide nucleoside triphosphates (dNTPs) or chain termination nucleotides such as didesoxynucleoside triphosphates (ddNTPs) and/or labelling groups, e.g. fluorescent or chromogenic labelling groups.
A microarray for the prognosis of a clinical response to a CNS-active medicament comprises a carrier, e.g. a planar carrier or a microchannel device, having immobilized thereto at least one probe which allows a determination of a polymorphism to be tested. Preferably, the microarray carrier has immobilized thereto a plurality of different probes located at different areas on the carrier which are designed such that they can bind nucleic acid molecules, e.g. RNA molecules or DNA molecules, amplification products, primer elongation products, etc. containing the sequence in which the polymorphism to be tested is located. Thus, an identification of the polymorphism to be analyzed by detection of a site-specific binding events of the nucleic acid sample molecule to the probe immobilized on the carrier may be accomplished.
Finally, the present invention relates to a therapeutic composition or kit comprising a CNS-active medicament which is a substrate of the ABCB1 protein in a therapeutically effective dose and a further medicament which is an inhibitor of the ABCB1 protein in a therapeutically effective dose for treating a human patient having at least one polymorphism in the ABCB1 gene associated with a lack of clinical response to said CNS-active medicament. According to the invention, the polymorphism is at least one polymorphism selected from the group consisting of rs4148740, rs10280101, rs7787082, rs4148739, rs11983225, rs10248420 and rs12720067, optionally in combination with at least one additional polymorphism being in linkage disequilibrium with said polymorphism. The additional polymorphism is preferably selected from the group consisting of rs2235067, rs4148740, rs10280101, rs7787082, rs2032583, rs4148739, rs11983225, rs10248420, rs2235040, rs12720067 and rs2235015. The medicaments may be present as a single formulation or as separate formulations, if desired. Pharmaceutically acceptable carriers, diluents or adjuvants may be included. The composition or kit may be administered by any suitable route, e.g. by oral or parenteral administration or any other suitable means.
The schedule of administration and dose of a CNS-active medicament such as, for example an antidepressant drug can vary between patients and are well know in the medical art, see, for example Benkert and Hippius, “Kompendium der Psychiatrischen Pharmakotherapie”, Springer Verlag Publishing, 2000; Albers, “Handbook of Psychiatric Drugs: 2001-2002 Edition”, Current Clinical Strategies Publishing, 2000. For antidepressants, there are three therapeutic possibilities for individuals that have been genotyped with SNPs in the ABCB1 gene.
1. The dosage of an antidepressant that is a substrate of ABCB1 would be increased. Examples of such antidepressants are, between 10 mg and 100 mg per day, preferably 40 mg, citalopram; between 10 mg and 80 mg per day, preferably 20 mg, paroxetine; between 50 mg and 500 mg per day, preferably 150 mg, venlafaxine; between 25 mg and 300 mg per day, preferably 75 mg, amitriptyline; between 25 mg and 400 mg per day, preferably 75 mg, nortriptyline; between 50 mg and 400 mg per day, preferably 200 mg, fluvoxamine; between 2 mg and 15 mg per day, preferably 10 mg, reboxetine.
2. An alternative antidepressant that is not a substrate of ABCB1 would be administered. Preferred examples include between 15 mg and 100 mg per day, preferably 30 mg, mirtazapine; between 5 mg and 80 mg per day, preferably 20 mg, fluoxetine.
3. An antidepressant that is a substrate of ABCB1 would be combined with an inhibitor or modulator of ABCB1. Examples of inhibitors or modulators of ABCB1 are disclosed in Table 1 and the dosage would be determined according to the manufactured recommendations.
Furthermore, the present invention shall be explained by the following Tables and Figures as well as Examples:



FIGURES
FIGS. 1A-D Blood-organ barrier function for antidepressant drugs
Organ/plasma ratios of drug concentration in abcb1ab(−/−) mice compared to wild-type controls after subcutaneous administration of citalopram FIG. 1(A), mirtazapine FIG. 1(B) or venlafaxine FIGS. 1. (C and D) for 11 days via osmotic pumps. The organ/plasma ratios for citalopram FIG. 1 (A), mirtazapine FIG. 1(B), venlafaxine FIG. 1 (C) and desmethyl-venlafaxine FIG. 1(D) are shown as % of the control. An asterisk indicates a significant difference between the knockout mutants and the control mice (univariate F-tests in MANOVA, p-values <0.05). Cerebrum (cer), spleen (spl), kidney (kid), liver (liv), testes (tes) and lung (lun) were investigated. Values are shown as means±SEM.
FIGS. 2 A-B Distribution of rs2032583 genotypes
Percentage of rs2032583 genotypes in the groups “non-remitters” and “remitters” for patients treated with substrates of P-gp FIG. 2 (A) (amitriptyline, citalopram, paroxetine or venlafaxine) and those treated with non-P-gp substrates FIG. 2 (B) (mirtazapine).
FIGS. 3 A-F Cox regression analysis for rs2032583 and rs2235015
A Cox regression analysis for remission was performed for the SNPs 2032583 FIGS. 3 (A, B, C) and rs2235015 FIGS. 3(D1 E, F) dependant from the genetic feature “C-carrier” (rs2032583) or “T-carrier” (rs2235015). The Figure shows the time course of non-remitters, i.e. depressed patients. It depicts the examination of all patients FIGS. 3 (A, D) and the two subgroups of patients receiving substrates of P-gp FIGS. 3 (B, E) and those receiving non-P-gp substrates FIGS. 3 (C, F).
FIGS. 4A-R Linkage disequilibrium mapping
Representation of linkage disequilibrium (LD) and block structure in ABCB1 using D′ as a measure for LD strength by means of HAPLOVIEW.



1. METHODS
1.1. Experiments Using Transgenic Animals
Materials.
Venlafaxine and O-desmethyl venlafaxine (d-venlafaxine) were obtained from Wyeth-Pharma GmbH (Munster, Germany). Mirtazapine was obtained from Thiemann Arzneimittel GmbH (Waltrop, Germany) and citalopram from Lundbeck (Copenhagen, Denmark). Protriptyline was purchased from Research Biochemical International, Natick, Mass. (USA). All other chemicals were obtained in the purest grade available from Merck (Darmstadt, Germany).
Animals.
All animal experiments were conducted in accordance with the Guide for the Care and Use of Laboratory Animals of the Government of Bavaria, Germany.
Male abcb1ab(−/−) mice and FVB/N wild-type mice were housed individually and maintained on a 12:12 h light/dark cycle (lights on at 07:00), with food and water ad libitum. Abcb1ab double knockout mice, originally created by A. Schinkel by sequential gene targeting in 129/Ola E14 embryonic stem cells (Schinkel et al., 1997) and backcrossed seven times (N7) to FVB/N from the C57BL/6×129 chimera, and FVB/N wild-type mice were obtained from Taconic (Germantown, N.Y., USA; FVB/Tac-[KO]Pgy2 N7). A homozygous colony is maintained at the Max Planck Institute of Psychiatry on the N7 FVB/N background through intercrossing of homozygous mice. Age, weight and group size of the mice used are shown in Table 9.
Experimental and Extraction Procedures.
Experimental and extraction procedures were performed as described before (Uhr et al., 2003; Uhr and Grauer, 2003). Citalopram, mirtazapine and venlafaxine dissolved in 0.9 percent sodium chloride and 0.5 percent ethanol were administered subcutaneously in the nape of the neck through surgically implanted osmotic infusion pumps (Alzet® micro-osmotic pump, Alza Corporation, Palo Alto, Calif., USA), which continuously delivered the drugs at the scheduled concentrations (citalopram and mirtazapine 60 μg/d; venlafaxine 300 μg/d). After 11 days, the mice were anesthetized and sacrificed. The dissected organs were homogenized and a liquid-liquid extraction procedure was performed with n-hexane/isoamyl alcohol in step 1 (see Table 9) and phosphoric acid in step 2. The extraction recoveries were greater than 90 percent for citalopram, mirtazapine and venlafaxine and 36 percent for d-venlafaxine.
High-performance liquid chromatography (HPLC) measurements were performed as described before (van de Vrie et al., 1998; Uhr et al., 2003). A Beckman gradient pump, an autoinjector, a UV detector and a Merck fluorescence detector were used for the HPLC analysis. Separations were made on a reversed phase Luna 5μ C18(2) 250×4.6 mm column (Phenomenex, Torrance, Calif., USA) at 60° C., with a mobile phase flow of 1 ml/min. A mobile phase gradient with acetonitrile was used for chromatographic analysis (see Table 9). The substances were determined by UV absorption and fluorescence.
Statistics.
Statistical analysis was performed using the statistic package software SPSS Release 14.0 for Windows (Chicago, Ill., USA). Significance was tested by one-factorial multivariate analyses of variance (MANOVAs). Univariate F-tests followed to identify the variables the differences of which between the two groups contributed significantly to the global group effect. As a nominal level of significance α=0.05 was accepted and corrected (reduced according to the Bonferroni procedure) for all a posteriori tests (univariate F-tests) to keep the type I error less than or equal to 0.05.
1.2. Human Genetic Studies
Description of Patients.
The study included 443 in-patients with depressive disorder who were treated at the Max Planck Institute of Psychiatry (MPI), Munich/Germany. Patients were included in this study within 1-3 days of admission and diagnosed by trained psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders (DSM) IV criteria. Patients with depressive disorder due to a medical or neurological condition were excluded. Ethnicity was recorded using a self-report sheet for nationality, native language and ethnicity of the subject and of all 4 grandparents. The study was approved by the local ethics committee and written informed consent obtained from all subjects.
The study was designed as a naturalistic pharmacogenetic study (Munich Antidepressant Response Signature (MARS) project) (Künzel et al., 2003; Binder et al. 2004) designed to discover biomarkers and genotypes predictive of clinical outcome; all patients were treated according to doctor's choice of antidepressant drugs within a few days after admission. The antidepressant plasma concentration was monitored to assure clinically efficient drug levels.
The total group of patients was divided in two subgroups that differed from each other by the fact that the patients of both subgroups received drugs that were or were not substrates of P-glycoprotein in the animal model. In the group of patients taking antidepressants that are substrates of P-gp patients were taking amitriptyline, paroxetine, venlafaxine or citalopram for at least 4 weeks within the first 5 weeks of treatment. In addition, they were not allowed to take other antidepressants for more than 3 weeks (with the exception of trimipramine that was allowed in a daily dose of up to 100 mg for sleep promotion purposes). In the group of patients taking antidepressants that are not substrates of P-gp in the animal model patients had to take mirtazapine for at least 4 weeks within the first 5 weeks of treatment and were not allowed to take other antidepressants. If a patient was dismissed prior to week 5, he had to take the respective drugs for 3 weeks when hospitalized for 4 weeks and for 2 weeks in the case of a 3-week hospitalization. The group characteristics number of patients (% women), age, Hamilton Depression Rating Scale (HAM-D) at inclusion, age at onset, illness duration in years, number of previous episodes, number of former hospitalizations, duration of actual episode, ethnicity, co-medication and diagnosis are shown in Table 6 and Table 8, for the representative SNPs rs2032583 and rs2235015 depending on the genotype.
Not all patients finished the weekly psychopathology ratings until week 4 after being included in the study. After weeks 4, 5 and 6 the data of only 366 (83%), 324 (73%) and 297 (67%) patients were available for evaluation. This attrition was due to the patients' rapid recovery, discharge against their doctor's advice and relocation or refusal of further participation.
Psychopathology and Definition of Response to Antidepressant Drug Treatment.
Trained raters using the 21-item Hamilton Depression Rating Scale (HAM-D) assessed the severity of psychopathology at admission. Patients fulfilling the criteria for at least one moderate depressive episode (HAM-D>=14) entered the analysis. Ratings were performed within 3 days of admission and then weekly until discharge.
We defined response as a reduction of at least 50% in the HAM-D scores at admission. Remission was defined as reaching a total HAM-D score of less than 10. The 4 to 6 week time period was chosen because this duration of treatment is considered necessary for an antidepressant drug to display its clinical efficacy.
DNA Preparation, SNP Selection and Genotyping.
At the time of enrollment in the study, 40 ml of EDTA blood was drawn from each patient and DNA was extracted from fresh blood using the Puregene® whole blood DNA extraction kit (Gentra Systems, Minneapolis, Minn., USA). Ninety-five ABCB1 (NM_000927) SNPs were genotyped. SNPs were selected from dbSNP or part of the Illumina Sentrix Human-1 100 k BeadChips.
Genotyping was performed on a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometer (MassArray® system) employing the Spectrodesigner software (Sequenom®; San Diego, Calif., USA) for primer selection and multiplexing and the homogeneous mass extension (hMe) process for producing primer extension products. Cleaned extension products were analyzed by means of a mass spectrometer (Bruker Daltronik) and the peaks identified using the SpectroTYPER software (Sequenom). Only if the call rate of the plates tested was more than 90%, the results were used for evaluation.
SNPs that could not be examined by means of the Sequenom technology were tested by pyrosequencing (Biotage, Uppsala, Sweden).
rs7779562, rs4148738, rs2235033, rs10264856, rs10267099, rs7796247 and rs10275625 were performed on Sentrix Human-1 Genotyping BeadChips (Illumina Inc., San Diego, USA) according to the manufacturer's standard protocols. The SNPs rs2235048, rs1045642, rs2032583, rs2235046, rs1202169, rs2235015 and rs1202172 were performed using both the Sequenom and Illumina technology. The measuring results were congruent in more than 99%.
The tetra-allelic SNP rs2032582 was measured in the light-cycler using allele-specific hybridization probes. All primer sequences are available upon request.
Linkage Disequilibrium in ABCB1.
For the linkage disequilibrium (LD) structure examination D′ and r2 measures were used (Hill and Robertson, 1968). Analysis of measures was performed using HAPLOVIEW Version 3.32. Blocks were defined using the confidence interval method described by Gabriel et al. (2002).
Statistics.
Exact tests to detect deviations from Hardy Weinberg equilibrium (HWE) (Wigginton et al., 2005) were performed for all SNPs (Table 2).
To calculate whether there exists a significant association between phenotype variables and genetic variability in the ABCB1 gene, the multivariate Fisher's product method (FPM) was employed. Phenotype variables were corrected for the effects of age and gender by calculating linear regression residuals with the statistic package software SPSS Release 14.0.0 (Chicago, Ill., USA). Bivariate associations between SNP genotyping data and phenotypes were tested in an ANOVA analysis (Analysis of Variance). Empiric p-values were calculated by applying 106 permutations (phenotypes randomly redistributed over the genotypes). Fisher's product method (FPM) (Fisher, 1932) includes the residuals of the phenotype variables remission after 4 weeks, remission after 5 weeks, remission after 6 weeks, and the genotype variables from all polymorphic SNPs. P-value correction for multiple comparisons was done by re-sampling (106 permutations).
To correct for multiple testing, the permutation method by Westfall and Young (1993) was applied to take advantage of the dependence structure between the SNPs and the phenotypes. We performed the entire analysis scan 106 times using phenotypes randomly redistributed over the genotypes. Finally, a Cox regression survival analysis was carried out with the statistic package software SPSS Release 14.0.0 (Chicago, Ill., USA), examining remission incidence (HAM-D<10) during the first 6 weeks of treatment, with age and sex as covariates.
Results
Experiments Using Abcb1a and Abcb1 b Double Knockout Mice
Since P-gp function is only critical for drugs that are substrates of P-gp in humans, an in vivo assay was developed using mouse mutants lacking the homologues of the human ABCB1 gene, i.e. abcb1ab knockout mice. After treatment for 11 days with subcutaneously implanted osmotic infusion pumps it was observed that the intracerebral concentrations of the antidepressants citalopram (F7,8=35.4; p<0.001), venlafaxine (F7,8=30.7; p<0.001) and its active metabolite d-venlafaxine (F7,8=4.5; p=0.022) are regulated by P-gp. The brain concentrations of citalopram, venlafaxine and d-venlafaxine were 3.0, 1.7 and 4.1 times higher in the mutant mice compared to their wild-type littermates (Table 2). This was not the case for mirtazapine, another frequently used antidepressant (F8,9=3.0; p=0.58). No differences in plasma levels were found between abcb1ab (−/−) mutants and their wild-type littermates for any of the drugs and metabolites investigated (Table 2).
The blood-organ barrier function is represented in FIG. 1 as an organ/plasma concentration ratio. In the animals lacking P-gp, the penetration into the brain of citalopram, venlafaxine and d-venlafaxine is 3.7, 1.8 and 3.6 times higher than that found in the control animals. Beside differences in brain/plasma ratios smaller but still significant differences were found for citalopram, venlafaxine and d-venlafaxine, but not mirtazapine, in the testes, another organ with a blood-organ barrier.
Human SNP Association Study
If a patient is treated with a substrate of P-pg, functionally relevant genetic variants in the ABCB1 transporter could influence intracerebral drug concentrations and thereby clinical response. To test this hypothesis, the association of single nucleotide polymorphisms (SNPs) in the ABCB1 gene with the time until remission under antidepressant treatment was analysed in patients with depressive disorders.
To that aim 95 SNPs in ABCB1 were investigated, 74 of which were polymorphic. Information on chromosome position, function, HWE, minor allele frequencies (MAF) and the number of patients genotyped are presented in Table 7. The average intermarker distance of informative SNPs was 3.5 kb over the 262 kb long ABCB1 region on chromosome 7 including all tagging SNPs of the HapMap project.
Since P-g does not influence cerebral penetration of ail antidepressants, patients were divided in two subgroups, one group including patients treated with substrates of P-gp (citalopram, paroxetine, amitriptyline and venlafaxine), the other one including patients treated with non-substrates (mirtazapine) (Uhr et al., 2000, 2003, 2007; Uhr and Grauer, 2003; Grauer and Uhr, 2004).
All polymorphic SNPs were tested for genotypic association with the phenotypes remission after 4 weeks, remission after 5 weeks or remission after 6 weeks.
Table 3 shows the empiric p-values of the ANOVA analysis determined by applying 106 permutations and corrected for age and sex for both the entire group and the two subgroups.
An association with p-values of <0.001 was found only in the subgroup including patients who received drugs that were substrates of P-gp. The SNPs concerned were rs2235067, rs4148740, rs10280101, rs7787082, rs2032583, rs4148739, rs11983225, rs10248420, rs2235040, rs12720067 and rs2235015.
This association analysis for all polymorphic SNPs and phenotypes was conducted according to Fisher's product method (FPM) (Fisher, 1932) for the genotypic and allelic models. Correction for multiple testing was performed using the minimum P method of Westfall and Young (1993). Table 4 shows the p-values of FPM over all SNPs, sorted by phenotypes and models, as well as over all SNPs and all phenotypes, sorted by model and the Westfall-Young corrected p-values. In the group of patients taking substrates of P-gp there exist highly significant associations between the genetic variability of the SNPs tested and both the remission of depressive symptoms in weeks 4, 5 and 6 and the combination of these remission variables. In this group of patients the Westfall and Young corrected p-values over all SNPs and phenotypes was 0.00040 and 0.00016 for the genotypic and allelic analysis. In the group of patients taking drugs that are not substrates of P-gp there was no significant association.
This is illustrated in FIG. 2, which presents the genotype distribution of the SNP rs2032583 for patients who remitted after 4 weeks and those who did not. In the group of patients receiving antidepressants that are substrates of P-gp there are clear differences in the genotype distribution between remitters and non-remitters (FIG. 2A). While in the group of non-remitted to patients carrying the C-allele made up 9.5%, their percentage in the group of remitted patients was 45%. The 2×3 table Cochran-Armitage test yielded a chi-square of 15.8, p=0.00007 for patients receiving the P-gp substrates and a chi-square of 0.004, p=0.945 for patients receiving a non-P-gp substrate. If C-carriers are treated with drugs that are substrates of P-gp, they have a clearly higher approx. relative risk for remission after 4 weeks. The odds ratio (approx. relative risk) was 7.72 (95% confidence interval limits 2.80 and 21.32) with p=0.000065 in the 2×2 table Fisher's exact test. For any particular negative test result (non-carrier), the probability that it was true-negative (non-remission) was 81.5%.
For patients receiving non-P-gp substrates there are no differences in the genotype distribution between remitters and non-remitters (FIG. 2B). The odds ratio was 1.12 (95% confidence interval limits 0.38 and 3.37) with p=1 in Fisher's exact test.
For a better presentation of the remission development up to week 6 a survival analysis (Cox regression) was performed. FIG. 3 shows the decrease in non-remitters, i.e. patients who are still ill, for all patients and the two subgroups during the first 6 weeks depending on their genotype. For rs2032583 a distinction was made between C-carriers and non-carriers; for rs 2235015 we distinguished between T carriers and non-carriers. The group of patients treated with a substrate of P-gp shows clear differences depending on the genotype. For instance, after 6 weeks, 62% of the patients who are non-C-carriers of the SNP rs2032583 had not remitted, while this was the case in only 25% of the C-carriers.
For all SNPs showing a highly significant association between genotype and remission in the FPM a Cox regression was performed; the values of the Wald statistics and p-values are shown in Table 5. In the group of patients who had received drugs that are substrates of P-gp there was a significant difference for all SNPs tested (p-values <0.0025). The subgroup of patients taking an antidepressant where its brain concentrations are not influenced by P-gp did not show any differences.
Linkage Disequilibrium in ABM
In an attempt to narrow down the region of ABCB1 containing the causal variant, the linkage disequilibrium (LD) structure of ABCB1 was analyzed using HAPLOVIEW. This analysis included all patients. Applying the method of Gabriel et al. (2002) for the delineation of haplotype blocks, a total of 7 blocks were identified (FIG. 4).
The 11 SNPs that showed a highly significant association between genotype and remission in the FPM are marked with an arrow. The linked SNPs rs2235067, rs4148740, rs2032583, rs4148739, rs11983225, s2235040, rs12720067 as well as the SNPs rs7787082 and rs10248420 exhibited an r-square of >0.8. The SNPs rs10280101 and rs2235015 were not included in any tagging bin with an r-square of >0.8.
Genotype, Plasma Antidepressant Levels and Dosage
To exclude the possibility that the observed effect is based solely on differences in the administered drug dose or intestinal uptake, and to support the hypothesis that genotype-related differences in treatment response are linked to differences in intracerebral drug concentrations, we examined whether there were significant differences in the doses and plasma levels of amitriptyline, citalopram, paroxetine, venlafaxine and mirtazapine between the genotypes of significant SNPs.
To this end, we created the residuals of linear regression with the dependent variable drug dose or plasma concentration and the independent variables age and gender. These residuals and SNP genotyping data were tested in an ANOVA analysis for statistical differences between the genotypes. Empiric p-values were calculated by applying 106 permutations (residuals randomly redistributed over the genotypes). Fisher's product method (FPM) includes the residuals of the dose or plasma concentration variables and the genotype variables from the SNPs rs2235067, rs4148740, rs2032583, rs4148739, rs11983225, rs2235040, rs12720067, rs7787082, rs10248420, rs10280101 and rs2235015.
We neither found significant differences in the doses of amitriptyline, citalopram, paroxetine, venlafaxine and mirtazapine between the SNP genotypes studied nor genotype-dependent differences in the plasma levels of patients receiving amitriptyline, paroxetine, venlafaxine or mirtazapine. However, a small significant difference could be detected for citalopram plasma levels. Although Fisher's product over all SNPs and phenotypes was p=0.023 for the genotypes, the plasma levels of patients showing less treatment success was higher.
Case-Control Association
A control group of 362 subjects was genotyped for rs2032583 and rs2235015, the representative SNPs in the haplotype blocks 3 and 5 in the LD map (FIG. 4). Subjects were randomly selected from a Munich-based community sample and were negative for lifetime psychiatric axis I disorders (M-CIDI) and severe somatic diseases. Controls did not differ from the patient sample regarding gender distribution (p=0.603), age (p=0.322) or ethnicity (100% Caucasians in both samples, p=1). Genotype tests were performed using Fisher's exact test on a 2×3 table. We observed no significant case-control association for rs2032583 and rs2235015 (Fisher's exact test, p=0.669 and 0.351).
DISCUSSION
The present results provide for the first time evidence that genetic variants in the ABCB1 gene account for differences in the clinical efficacy of antidepressants most likely by influencing their access to the brain. Here it is reported that antidepressant-induced remission of depressive symptoms is predicted by SNPs in the ABCB1 gene among those depressed patients who were treated with drugs that are substrates of the ABCB1-encoded P-glycoprotein. To identify whether or not the antidepressants administered to patients are substrates of the P-glycoprotein, mouse mutants lacking the mouse homologues of the ABCB1 gene were studied. Whereas P-gp is encoded by a single gene in humans (ABCB1), there are two homologues in mice, the abcb1a and abcb1b genes (Devault and Gros, 1990). Although abcb1a and abcb1b are not always expressed in the same organs, the overall distribution of these genes in mouse tissue coincides with that of the single ABCB1 gene in humans, indicating that abcb1a and abcb1b together function in the same manner in mice as human ABCB1 (Meijer et al., 1998; van de Vrie et al., 1998). It has yet not been possible to predict the affinity of a substrate to P-glycoprotein from its chemical structure, hydrophobicity, lipophilicity or charge. Using this mouse model, it could already be shown in earlier studies that citalopram, venlafaxine, paroxetine and amitriptyline, after single administration, were substrates of P-gp at the blood-brain barrier, while mirtazapine and fluoxetin were not (Uhr et al., 2000, 2003, 2007; Uhr and Grauer, 2003; Grauer and Uhr, 2004).
In this study, the drugs were administered over an extended time period to investigate the time-dependent interaction of the drug and P-gp. It is shown that two structurally different antidepressants citalopram (a selective serotonin reuptake inhibitor) and venlafaxine (a combined serotonin and norepinephrine reuptake inhibitor) were both substrates of P-gp at the BBB as the brain drug concentration in mutants not carrying the genes coding for P-gp was increased (Table 2, FIG. 1). In contrast, the penetration of mirtazapine (targeting serotonin2C and alpha2A-adrenergic receptors) into the brain is not influenced by P-gp. The important role of P-gp was further supported by the fact that drug and metabolite organ concentrations and organ/plasma ratios of all antidepressants investigated did not differ between mutant and wild-type littermates in those organs that either lack P-gp completely or in which P-gp is not expressed in endothelial cells, such as the spleen, kidney, liver and lung. These results shows that some but not all antidepressants are substrates of P-gp in mice. In this study the antidepressants were administered for 11 days and it was found that the substrate specificity is similar to that observed after acute administration (Uhr et al., 2000, 2003; Uhr and Grauer, 2003), indicating that P-gp substrate specificity or activity does not change over time.
To answer the question whether differences in the access of antidepressants into the brain might influence the course of treatment and outcome, a clinical study was conducted in which the genetic variability of the ABCB1 gene of 443 in-patients with depressive disorder receiving antidepressants was investigated. Patients were divided in two groups, those receiving drugs that had proved to be substrates of P-gp at the BBB (amitriptyline, citalopram, paroxetine and venlafaxine) and those receiving mirtazapine, which is not a substrate.
Numerous papers describe polymorphisms in ABCB1 (Kioka et al., 1989; Stein et al., 1994; Mickley et al., 1998; Hoffmeyer et al., 2000; Kim et al., 2001; Ito et al., 2001; Cascorbi et al., 2001; Tanabe et al., 2001; Eichelbaum et al., 2004), and a multitude of single nucleotide polymorphisms (SNPs) are listed in public SNP databases.
The inventors investigated 95 SNPs, 74 of which were polymorphic (average intermarker distance: 3.5 kb) and thus included in the statistical evaluation. The genetic variability of all polymorphic SNPs and the recovery from depressive symptoms were examined in a summarizing model using Fisher's product method. After correction for multiple testing a highly significant association was found between the genotypes or allele frequencies of the ABCB1 gene and the remission in weeks 4, 5 and 6 only in patients receiving substrates of P-gp (Table 3). For a better presentation of the clinical course and involvement of the entire period up to week 6 including all patients enrolled in the study a Cox regression survival analysis was performed. As demonstrated in FIG. 3 and Table 4, only the patients receiving substrates of P-gp showed genotype-dependent, highly significant target parameter differences during the clinical course, achieving a remission with a score of <10 on the HAM-D (FIG. 3, Table 4).
Mainly responsible for this association were the SNPs rs2235067, rs4148740, rs10280101, rs7787082, rs2032583, rs4148739, rs11983225, rs10248420, rs2235040, rs12720067 and rs2235015, showing p-values of <0.001 in the ANOVA analysis (Table 3). In an attempt to narrow down the region of ABCB1 possibly causing differential response, the linkage disequilibrium (LD) structure of ABCB1 was analyzed using HAPLOVIEW. With the exception of rs2235015 all highly associated SNPs were located in a single haplotype block (FIG. 4), and the SNPs rs2235067, rs4148740, rs2032583, rs4148739, rs11983225, s2235040, rs12720067 as well as the SNPs rs7787082 and rs10248420 exhibited an r-square of >0.8 with each other. All highly associated SNPs are located in introns and with a D′ of more than 90% in linkage disequilibrium (LD) with the best examined exon SNPs rs1045642 (C3435T), rs2032582 (G2677T) and rs1128503 (C1236T). In both the synonymous SNPs rs2032582 (exon 21) and rs1128503 (exon 12) and the non-synonymous SNP rs1045642 (exon 26) the known genetic variabilities result in different P-gp functions (Kimchi-Sarfaty et al., 2007). However, the r-square values are comparatively low (in the range of 15%) and there is no significant association between these SNPs in the exons and the remission.
As exemplified in FIG. 2 for the SNP rs2232583 the genotype distribution differs between the patient group with remission versus the group without remission among patients treated for 4 weeks with a P-gp substrate (Cochran-Armitage test, p=0.00007). The probability of being remitted from depression after 4 weeks is increased for C-carriers treated with substrates of P-gp (odds ratio: 7.72, p=0.000065). In contrast, it was predictable that patients carrying the TT genotype will not be remitted after a 4-week treatment period. In the group of patients receiving the non-substrate mirtazapine there was no difference found between the genotypes of remitters and non-remitters. The group characteristics for the representative SNP rs2032583, depending on the genotype, did not differ between the two subgroups “patients treated with P-gp substrates” and “patients treated with non-P-gp substrates” (Table 6).
The Cox regression analysis did not reveal any significant differences for remission (HAM-R<10) in the first 6 weeks (Wald value=0.125; sig=0.72) between the subgroup of patients receiving drugs that are substrates of P-pg and the subgroup of patients receiving drugs that are not substrates of P-gp, allowing to reject the possibility that differences in drug efficacy accounts for our different findings. In fact, the drugs used here proved to be especially effective according to large comparative studies required for approval. It is only the combined consideration of both the patient's ABCB1 genotype and the medication's P-gp substrate status that identifies a group of patients who exhibit a clearly better remission rate than patient populations assembled on the basis of the patient's genotype or the medication's P-gp substrate status alone.
SNPs in ABCB1 have been reported to influence intestinal uptake and thus plasma levels of drugs (Hoffmeyer et al., 2000; Brinkmann, 2002; Sakaeda et al., 2003). However, the various genotype-dependant remission rates found in this study were not due to different doses or plasma drug levels, which underscores that monitoring plasma antidepressant levels is not reliable to predict adequacy of treatment.
Recently, McMahon et al. (2006) reported that African-Americans responded less well to an established antidepressant than Caucasians. They accounted this difference to the global higher frequency of the A-allele in a specific SNP in the serotonin 2 A receptor gene. In this context it is noteworthy that also in the ABCB1 gene and particularly in the SNPs it was reported that in the prediction of treatment outcome considerable ethnic variability occurs (Kim, 2002; Tang et al., 2002, 2004; Kroetz et al., 2003). Thus, the current finding indicates that variant ABCB1 genotypes contribute to differences in treatment outcome across ethnic groups and further encourage studies to elucidate the clinical implications of these differences across ethnic groups.
The general conclusion to be drawn is that any drug administered to treat CNS diseases should be analyzed for its P-gp substrate status, which can be determined by using abcb1ab knockout mice. From a clinical point of view, the findings warrant that patients receiving a drug that is a P-gp substrate for the treatment of brain diseases are genotyped to exclude the possibility that a patient receives a drug that fails to enter the CNS to an extent required for efficacy. The combination of therapeutic drug monitoring (TDM) involving enteral drug intake and cytochrome P450 drug metabolism and P-gp genotyping for detecting the drug's bioavailability in the brain may predict the response of an individual patient to a certain drug. Finally, the interdependence of P-gp substrate capacity and ABCB1 genotype needs to be considered in future CNS development, because drugs that differ in their P-gp substrate capacity need to be evaluated in clinical trials where study populations are stratified according to the ABCB1 genotype.
TABLES







TABLE 1







Inhibitors and Modulators of ABCB1












Substance
Substrate
Inhibitor
Inducer







Antiacids






Cimetidine
x



Lansoprazole
x
x



Omeprazol

x



Pantoprazole

x



Ranitidine
x



Antiarrhythmics



Amiloride
x
x



Amiodarone

x



Barnidipine

x



Benidipine

x



Bepridil

x



Digitoxin
x



Digoxin
x



Efonidipine

x



Manidipine



Niguldipine

x



Nilvadipine

x



Propafenone

x



Propranolol

x



Quinidine
x
x



Verapamil
x
x



Antibiotics



Amoxicillin
x



Ceftriaxone

x



Ciprofloxacin
x



Clarithromycin

x



Enoxacin
x



Erythromycin
x
x



Fucidine

x



Josamycin

x



Levofloxacin
x



Ofloxacin
(x)
x



Rifampin
x

x



Sparfloxacin
x



Tetracycline
x



Anticancer agents



Actinomycin D
x



Adriamycin
x



Azidopine
x
x



Daunorubicin
x



Docetaxel
x



Doxorubicin
x

x



Epirubicin
x



Etoposide
x



Gramicidine

x



Imatinib
x



Irinotecan
x



Mitomycin C
x
(x)



Mitoxantrone
x



Paclitaxel
x
x



Quercetin

x



Teniposide
x



Topotecan
x



Valinomycin

x



Vinblastine
x



Vincristine
x



Vindesine
x



Vinorelbine
x



Antidepressants



Amitriptyline
x



Citalopram
x
x



Desipramine

x



Doxepine
x



Flesinoxan
x



Fluoxetine

x



Fluvoxamine

x



Imipramine

x



Maprotiline

x



Nefazodone

x
(x)



Nortriptyline
x



Paroxetine

x



Reboxetine

x



Sertraline

x



St John's wort


x



Trazodone


(x)



Trimipramine
x
x



Venlafaxine
x
x



Antiemetics



Domperidone
x



Ondansetron
x



Antiepileptics



Carbamazepine
x



Felbamate
x



Lamotrigin
x



Phenobarbital
x



Phenytoin
x



Antihypertensive agents



Carvedilol

x



Celiprolol
x



Diltiazem
x



Doxazosin

x



Felodipine

x



Losartan
x



Mibefradil
x
x



Nifedipine

x



Nicardipine

x



Nitrendipine

x



Prazosin


x



Reserpine

x



Talinolol
x



Antimycotics



Fluconazole



Itraconazole
x
x



Ketoconazole

x



Antiparkinson



Amantadine



Budipin
x



L-Dopa
x



Antiviral agents



Amprenavir
x

x



Indinavir
x
x
x



Lopinavir

x
x



Nelfinavir
x
x
x



Ritonavir
x
x
x



Saquinavir
x
x
x



Glucocorticoids



Aldosterone
x



Cortisol
x



Dexamethasone
x

x



Hydrocortisone
x



Methylprednisolone
x



Immunosuppressants



Cyclosporine
x
x



FK 506

x



Methotrexat



Rapamycin
x
x



Sirolimus
x
x



Tacrolimus
x
x



Tamoxifen

x



Valspodar (PSC833)
x
x



Vinblastine

x



Statins



Atorvastatin
x
x



Lovastatin

x



Simvastatin

x



Neuroleptics



Chloropromazine

x



Clozapine



Droperidol

x



Flupenthixol

x



Fluphenazine

x



Haloperidol

(x)



Melperon



Olanzapine
(x)



Phenothiazine

x
x



Pimozide

x



Prochlorpemazine

x



Promethazine

x



Quetiapine
x



Risperidone
x



Sulpiride
x



Thioridazine

x



Trifluoperazine

x



Triflupromazine

x



Opioids



Alfentanil

x



Fentanyl
x
x



Methadone

x



Morphine
x

x



Pentazocine

x



Sufentanil

x



Surfactants



Cremophor EL

x



Triton X-100

x



Tween 80

x



Others



Albendazole



Anti-CD19 antibody

x



Azelastine

x



Bilirubin
x



Bisantrene
x



Bromocriptine

x



Bunitrolol
x



Celiprolol
x



Chloroquine

(x)



Chlorpheniramine



Cholesterol
x
x



Colchicine
x



Cortexolone



Cyproheptadin

x



Debrisoquine
x



Dihydrotestosterone
x



Dipyridamole

x



DM27



DM40



E6

x



Emetine

x



EP 51389

x



Estradiol
x



Fexofenadine
x



Flavinoids

x



Flunitrazepam



Garlic

x



GF120918

x



Ginsenoide

x



Grapefruit

x
(x)



Green Tea

x
x



H2O2


x



Ivermectin
x



Lidocaine

x



Lonafarnib (SCH66336)

x



Loperamide
x



Loratadine
(x)
(x)



Mefloquine
x
x



Midazolam
x
(x)



Nobilitin

x



orange juice-Seville

x



Pipeline

x



Probenecid

x



Progesterone

x



Quinacrine

x



Quinine

x



Retinoic acid


x



Rhodamine 123
x



RU 486

x



Spironolactone

x



Sumatriptan



Terfenadine
x
x



1,2,3,4-
x



tetrahydroisoquinoline



Tetrandrine

x



Thyroid Hormones
x
x



TNF alpha

x



Unconjugated Bilirubin
x

x



Vandate

x



Vecuronium
x



Vitamin A


x



XR9576

x



Yohimbin

x



Zosuquidar•3HCl

x



Elacridar (GF120918)

x



LY335979

x



Tariquidar (XR9576)

x

















TABLE 2





Organ concentrations of antidepressant drugs and their metabolites


after 11 days of subcutaneous administration via osmotic pumps.







Citalopram [ng/g or ml]


















ratio




abcb1ab



(−/−)/
Signifi-



(−/−)
SEM
control
SEM
(+/+)
cance





plasma
89.37
8.65
106.71
7.60
0.8
ns


cerebrum
480.93
27.39
158.27
15.84
3.0
*


spleen
468.29
42.16
446.96
46.93
1.0
ns


kidney
795.74
50.39
962.29
87.92
0.8
ns


liver
240.33
16.40
238.02
18.46
1.0
ns


lung
1238.47
124.86
1238.71
105.37
1.0
ns


testes
687.92
28.30
428.19
35.05
1.6
*










Group effect: F(7, 8) = 35.4; significance of F < 0.001


Venlafaxine [ng/g or ml]


















ratio




abcb1ab



(−/−)/
Signifi-



(−/−)
SEM
control
SEM
(+/+)
cance





plasma
70.57
4.22
71.37
3.34
1.0
ns


cerebrum
456.32
19.76
261.14
9.54
1.7
*


spleen
564.20
23.00
581.95
11.31
1.0
ns


kidney
1054.88
37.58
1035.27
23.67
1.0
ns


liver
323.22
17.09
314.59
22.03
1.0
ns


lung
672.59
36.14
747.38
36.16
0.9
ns


testes
842.61
9.88
715.92
21.29
1.2
*










Group effect: F(7, 8) = 30.7; significance of F < 0.001


D-Venlafaxine [ng/g or ml]


















ratio




abcb1ab



(−/−)/
Signifi-



(−/−)
SEM
control
SEM
(+/+)
cance





plasma
5.98
0.70
5.50
1.12
1.1
ns


cerebrum
36.99
4.86
8.97
2.57
4.1
*


spleen
33.80
3.42
29.42
3.76
1.1
ns


kidney
127.32
22.51
107.88
12.72
1.2
ns


liver
88.22
10.60
83.15
8.15
1.1
ns


lung
44.91
3.85
50.63
7.09
0.9
ns


testes
39.19
2.64
30.18
4.01
1.3
ns










Group effect: F(7, 8) = 4.8; significance of F = 0.022


Mirtazapine [ng/g or ml]


















ratio




abcb1ab



(−/−)/
signifi-



(−/−)
SEM
control
SEM
(+/+)
cance





plasma
11.17
1.19
7.66
1.59
1.5
ns


cerebrum
51.31
4.84
34.90
6.20
1.5
ns


spleen
86.19
10.75
67.54
14.27
1.3
ns


kidney
91.22
9.75
70.93
13.29
1.3
ns


liver
20.59
2.14
12.39
2.43
1.7
ns


lung
105.36
9.64
61.47
11.75
1.7
ns


testes
110.29
12.14
61.22
11.59
1.8
ns


intestine
24.58
2.61
19.96
3.33
1.2
ns










Group effect: F(8, 9) = 3.0; significance of F = 0.58


* = significant difference; ns = not significant













TABLE 3







ANOVA analysis of the association between remission and SNPs Empiric p-values of the ANOVA


analysis determined by applying 106 permutations and corrected for age and sex for both


the entire group (all patients) and the two subgroups of patients receiving amitriptyline,


citaiopram, paroxetine or venlafaxine (substrates of P-gp) or mirtazapine (non-P-gp-substrate).











All patients
Substrates of P-gp
Non-substrates of P-gp



Remission (HDRS < 10)
Remission (HDRS < 10)
Remission (HDRS < 10)



















dbSNP ID
N
Week 4
Week 5
Week 6
N
Week 4
Week 5
Week 6
N
Week 4
Week 5
Week 6






















rs4148809
267
0.199
0.466
0.313
93
0.477
0.344
0.803
70
0.582
0.156
0.574


rs2888611
268
0.980
0.907
0.826
94
0.671
0.114
0.179
70
0.777
0.925
0.658


rs6979325
268
0.282
0.134
0.355
94
0.020
0.045
0.037
70
1.000
1.000
1.000


rs2178658
268
0.760
0.687
0.870
94
0.754
0.856
0.938
70
0.498
0.091
0.662


rs7789645
269
0.919
0.864
0.755
94
0.779
0.156
0.242
70
0.777
0.926
0.658


rs7793196
268
0.929
0.872
0.827
94
0.779
0.156
0.242
70
0.779
0.924
0.944


rs1055302
270
0.181
0.374
0.400
96
0.531
0.513
0.529
70
0.658
0.445
0.568


rs17064
215
0.362
0.901
0.377
79
0.132
0.516
0.227
59
0.837
0.310
0.423


rs2235048
353
0.427
0.010
0.482
112
0.280
0.108
0.164
85
0.861
0.477
0.331


rs1045642
351
0.316
0.044
0.483
112
0.240
0.204
0.119
85
0.860
0.473
0.268


rs6949448
268
0.593
0.046
0.594
94
0.239
0.188
0.224
70
0.196
0.048
0.728


rs7779562
344
0.423
0.406
0.277
110
0.434
0.866
0.482
84
0.325
1.000
1.000


rs2235067
272
0.047
0.0085
0.978
97
0.000075
0.0033
0.030
70
0.902
0.0024
0.927


rs4148744
229
0.465
0.577
0.967
84
0.368
0.879
0.485
62
0.475
1.000
1.000


rs4148743
228
0.351
0.046
0.500
84
0.387
0.437
0.174
61
0.770
0.362
0.510


rs4148740
267
0.123
0.030
0.756
93
0.000031
0.0048
0.011
70
0.442
0.017
0.759


rs10280101
264
0.217
0.052
0.770
92
0.000056
0.013
0.0053
69
0.444
0.018
0.732


rs7787082
265
0.035
0.011
0.497
91
0.000048
0.00011
0.0052
70
0.526
0.069
0.807


rs2032583
355
0.049
0.0038
0.221
114
0.000034
0.0035
0.016
86
0.658
0.003
0.931


rs2032582
268
0.294
0.171
0.956
94
0.251
0.450
0.276
68
0.538
0.197
0.837


rs4148739
268
0.118
0.028
0.756
93
0.000031
0.0048
0.011
71
0.460
0.016
0.759


rs11983225
265
0.111
0.031
0.742
91
0.000036
0.0061
0.012
70
0.442
0.017
0.844


rs4148738
344
0.287
0.023
0.890
110
0.212
0.059
0.125
84
0.095
0.109
0.771


rs10248420
264
0.039
0.010
0.566
91
0.00010
0.00021
0.010
69
0.596
0.046
0.807


rs2235040
266
0.019
0.038
0.846
93
0.0000070
0.0016
0.012
67
0.983
0.012
0.934


rs12720067
211
0.124
0.029
0.719
92
0.000021
0.0059
0.0023
71
0.460
0.016
0.759


rs1922242
228
0.487
0.844
0.821
82
0.252
0.725
0.859
61
0.052
0.741
0.708


rs2235046
355
0.132
0.041
0.941
113
0.137
0.063
0.072
86
0.177
0.124
0.816


rs2235013
268
0.381
0.023
0.400
93
0.057
0.147
0.280
71
0.566
0.056
0.324


rs2235035
249
0.877
0.672
0.252
87
0.564
0.602
0.399
64
0.446
0.433
0.355


rs2235033
344
0.135
0.043
0.830
110
0.087
0.104
0.312
84
0.209
0.042
0.374


rs2032588
227
0.562
0.654
0.046
82
0.352
0.854
0.356
60
0.351
0.290
0.135


rs1128503
270
0.252
0.033
0.446
94
0.144
0.129
0.140
71
0.263
0.045
0.605


rs2229109
262
0.545
0.277
0.084
93
0.560
0.468
1.000
63





rs10276036
269
0.246
0.031
0.426
94
0.144
0.129
0.140
71
0.263
0.045
0.605


rs1922240
269
0.939
0.203
0.163
94
0.645
0.262
0.323
71
0.259
0.856
0.190


rs2235023
269
0.399
0.798
0.470
94
0.763
0.452
0.273
68
0.818
0.768
0.503


rs1202169
355
0.170
0.062
0.816
113
0.185
0.090
0.109
86
0.411
0.088
0.692


rs1202168
270
0.383
0.100
0.799
94
0.200
0.163
0.177
68
0.565
0.170
0.831


rs1202167
227
0.557
0.030
0.502
83
0.264
0.191
0.179
62
0.860
0.278
0.882


rs2235019
228
0.496
0.406
0.067
84



62





rs2235017
229
0.685
0.596
0.448
84



62





rs2235015
350
0.155
0.0043
0.029
113
0.0015
0.0013
0.00026
85
0.810
0.051
0.520


rs6950978
267
0.728
0.902
0.141
93
0.354
0.956
0.492
70
0.566
0.499
0.417


rs10256836
268
0.815
0.892
0.126
94
0.475
0.942
0.460
70
0.556
0.540
0.359


rs10264990
265
0.758
0.881
0.112
91
0.676
0.646
0.224
70
0.685
0.341
0.988


rs1202179
272
0.393
0.085
0.250
97
0.115
0.214
0.039
70
0.362
0.030
0.083


rs1989831
228
0.413
0.049
0.057
83
0.096
0.249
0.028
62
0.507
0.062
0.160


rs1202172
355
0.555
0.127
0.285
114
0.074
0.033
0.0071
86
0.192
0.040
0.083


rs1202171
271
0.412
0.092
0.266
96
0.125
0.240
0.046
70
0.362
0.029
0.083


rs17327442
267
0.921
0.442
0.227
93
0.805
0.449
0.451
70
0.414
0.727
0.201


rs4148733
227
0.786
0.468
0.103
82
0.610
0.376
0.548
62
0.396
0.724
0.223


rs1202186
225
0.420
0.061
0.076
82
0.209
0.152
0.014
62
0.507
0.062
0.160


rs1202185
228
0.413
0.049
0.057
83
0.096
0.249
0.028
62
0.507
0.062
0.160


rs1202182
228
0.413
0.050
0.057
83
0.096
0.249
0.028
62
0.499
0.061
0.158


rs1202181
200
0.722
0.031
0.080
77
0.087
0.085
0.0049
51
0.358
0.045
0.686


rs2188525
269
0.854
0.955
0.509
94
0.903
0.405
0.584
71
1.000
1.000
1.000


rs2235074
226
0.551
0.553
0.991
81
0.337
0.677
0.524
60
1.000
1.000
1.000


rs2214102
202
0.226
0.237
0.247
75
0.151
0.263
0.261
54
0.447
0.366
1.000


rs4728709
237
0.261
0.742
0.661
91
0.475
0.637
0.862
70
0.777
0.343
0.462


rs4148731
227
0.136
0.560
0.782
83



61





rs4148730
226
0.132
0.698
0.700
80



62





rs13233308
267
0.146
0.968
0.453
93
0.308
0.604
0.585
70
0.256
0.173
0.138


rs4148729
229
0.133
0.560
0.782
84



62





rs10264856
339
0.097
0.595
0.672
110
0.265
0.380
0.853
83
0.754
1.000
1.000


rs2157926
228
0.369
0.633
0.772
81
0.171
0.535
0.836
63
0.782
1.000
1.000


rs10245878
269
0.761
0.237
0.583
94
0.520
0.975
0.869
71
0.744
0.019
0.047


rs10267099
344
0.813
0.483
0.922
110
0.365
0.647
0.791
84
0.634
0.109
0.314


rs7796247
344
0.068
0.487
0.954
110



84





rs2188529
221
0.160
0.794
0.548
81



59





rs4148727
220
0.133
0.560
0.782
80



62





rs10275625
333
0.068
0.487
0.954
110



84
















TABLE 4







Fisher's product and Westfall/Young analysis


An analysis of all polymorphic SNPs and phenotypes was conducted according to


Fisher's product method (FPM) for the genotypic und allelic models. For FPM,


as a single statistic is formed, no further correction for multiple testing is


necessary. We also give result for the minimum P of Westfall and Young, which


is a more conventional method controlling the family-wise error rate.











All patients
Substrates of P-gp
Non-substrates of P-gp
















Fisher's
Westfall/
Fisher's
Westfall/
Fisher's
Westfall/


Remission

product
Young
product
Young
product
Young










Fisher's product and Westfall/Young correction over all SNPs














4 weeks
Genotypic
0.191
0.466
0.00034
0.00011
0.775
0.712


4 weeks
Allelic
0.136
0.678
0.00039
0.000048
0.565
0.829


5 weeks
Genotypic
0.015
0.132
0.0084
0.0042
0.014
0.056


5 weeks
Allelic
0.005
0.039
0.0019
0.0021
0.160
0.137


6 weeks
Genotypic
0.513
0.615
0.0071
0.013
0.644
0.621


6 weeks
Allelic
0.327
0.233
0.0012
0.00049
0.904
0.856







Fisher's product and Westfall/Young correction over all SNPs and over all Phenotypes















Genotypic
0.068
0.309
0.00036
0.00040
0.160
0.136



Allelic
0.024
0.099
0.000094
0.00016
0.557
0.340
















TABLE 5







Cox regression analysis of genotype-dependant remission


For all SNPs showing a highly significant association between


genotype and remission in the FPM a Cox regression was


performed and the Wald values and p-values shown. testing


carriers of the rarer allele versus non-carriers.











All patients
Substrates of P-gp
Non-substrates of P-gP















p-

p-

p-


SNP
Wald
value
Wald
value
Wald
value
















rs2235067
1.902
0.168
10.586
0.0011
0.214
0.644


rs4148740
1.938
0.164
14.424
0.00015
0.157
0.692


rs10280101
1.493
0.222
13.119
0.00029
0.115
0.734


rs7787082
3.126
0.077
9.115
0.0025
0.454
0.500


rs2032583
3.218
0.073
13.277
0.00027
0.758
0.384


rs4148739
1.991
0.158
14.424
0.00015
0.175
0.675


rs11983225
2.486
0.115
13.636
0.00022
0.440
0.507


rs10248420
3.374
0.066
9.115
0.0025
0.566
0.452


rs2235040
2.285
0.131
10.109
0.0015
0.353
0.552


rs12720067
2.624
0.105
15.289
0.000092
0.175
0.675


rs2235015
2.970
0.085
9.197
0.0024
0.008
0.931
















TABLE 6







Genotype-dependent group characteristics for rs2032583


The group characteristics number of patients (% women), age, HDRS at


inclusion, age at onset, illness duration in years, previous episodes,


number of previous hospitalizations, duration of actual episode,


ethnicity, co-medication and diagnosis are shown for each genotype. It


was investigated in an ANOVA analysis whether there are significant


differences between the CC, CT and TT groups (Sig). The Table shows


the results of all patients, patients receiving substrates of P-gps


and patients receiving non-P-gp-substrates.












CC
CT
TT
Sig.











All patients











N (% women)
7 (57.1%)
84 (55.9%)
344 (57.2%)
0.97


Age
 48 ± 4.3
48.6 ± 1.4
48.3 ± 0.8
0.98


HAM-D at
30.7 ± 2.8 
26.5 ± 0.7
26.4 ± 0.3
0.22


inclusion


Age at onset
40.8 ± 6.8 
 38 ± 1.6
 36 ± 0.8
0.44


Illness duration
7.1 ± 3.3
10.7 ± 1.2
12.3 ± 0.7
0.36


(years)


Previous episodes
1.1 ± 0.5
  3 ± 0.6
 2.6 ± 0.2
0.58


Previous
0.7 ± 0.4
 1.2 ± 0.2
 1.7 ± 0.3
0.71


hospitalization


Duration of actual
41.5 ± 8.5 
38.4 ± 7.3
38.1 ± 3.7
0.99


Caucasian
100% 
 100%
 100%


German origin
100% 
83.5%
85.5%
0.87


Neuroleptics
57.1%  
10.7%
  18%
0.01


Mood stabilizers
14.2%  
16.6%
17.4%
1.00


Lithium
0%
 9.5%
 6.7%
0.62


Benzodiazepines
14.2%  
28.5%
31.1%
0.67


Single episode
42.8%  
28.5%
31.9%
0.61


Recurrent
57.1%  
57.1%
52.7%
0.77


depression


Bipolar II
0%
  13%
12.3%
0.88


Dysthymia
0%
 1.1%
 0.5%
0.51


Schizoaffective
0%
  0%
 1.4%
0.62


disorder


Adjustment
0%
  0%
 0.8%
1.00


disorder







Substrates of P-gp











N (% women)
2 (50%)  
21 (61.9%)
110 (59%)  
1.00


Age
44.5 ± 9.5 
48.2 ± 3 
 45 ± 1.4
0.66


HAM-D at
29 ± 1 
25.1 ± 1.5
26.7 ± 0.6
0.57


inclusion


Age at onset
43.5 ± 9.5 
36.9 ± 3.2
33.3 ± 1.4
0.43


Illness duration
1 ± 0
12.1 ± 2.2
11.6 ± 1.1
0.41


(years)


Previous episodes
0.5 ± 0.5
 1.6 ± 0.5
 2.7 ± 0.5
0.64


Previous
0.5 ± 0.5
 1.2 ± 0.4
 1.1 ± 0.1
0.82


hospitalization


Duration of actual
20 ± 4 
32.2 ± 8.2
 38 ± 6.3
0.86


Caucasian
100% 
 100%
 100%


German origin
100% 
89.4%
84.6%
0.80


Neuroleptics
0%
  19%
16.3%
0.83


Mood stabilizers
0%
14.2%
13.6%
1.00


Lithium
0%
14.2%
 7.3%
0.48


Benzodiazepines
0%
23.8%
23.6%
1.00


Single episode
50% 
33.3%
28.4%
0.64


Recurrent
50% 
47.6%
56.8%
0.74


depression


Bipolar II
0%
14.2%
11.9%
0.79


Dysthymia
0%
 4.7%
  0%
0.17


Schizoaffective
0%
  0%
 1.8%
1.00


disorder


Adjustment
0%
  0%
 0.9%
1.00


disorder







Non-substrates of P-gp











N (% women)
3 (100%) 
23 (52.1%)
 72 (52.7%)
0.36


Age
 45 ± 6.4
46.7 ± 2.9
50.4 ± 1.7
0.49


HAM-D at
35.6 ± 5.3 
27.1 ± 1.3
26.6 ± 0.7
0.07


inclusion


Age at onset
31.3 ± 12.5
39.3 ± 2.9
37.4 ± 1.7
0.66


Illness duration
13.6 ± 6.3 
 7.1 ± 1.5
12.9 ± 1.8
0.23


(years)


Previous episodes
1 ± 1
 1.7 ± 0.2
 2.3 ± 0.4
0.62


Previous
0 ± 0
 0.6 ± 0.2
 2.7 ± 1.3
0.64


hospitalization


Duration of actual
46.3 ± 15 
 23 ± 4.1
42.8 ± 9.1
0.49


Caucasian
100% 
 100%
 100%


German origin
100% 
89.4%
  83%
0.80


Neuroleptics
66.6%  
  0%
22.2%
0.002


Mood stabilizers
0%
 4.3%
11.1%
0.59


Lithium
0%
  0%
 4.1%
1.00


Benzodiazepines
33.3%  
30.4%
30.5%
1.00


Single episode
66.6%  
  26%
40.8%
0.20


Recurrent
33.3%  
69.5%
  45%
0.09


depression


Bipolar II
0%
 4.3%
  14%
0.50


Dysthymia
0%
  0%
  0%


Schizoaffective
0%
  0%
  0%


disorder


Adjustment
0%
  0%
  0%


disorder
















TABLE 7







Information on genotyped SNPs. Position according to Human Reference


Sequence. SNP-Information was retrieved from dbSNP.



















HWE-p-

%


SNP ID
Position
Gene
Function
Alleles
value
MAF
genotyped

















rs4148809
86747914
ABCB4
intron
A/G
0.82
0.411
71.2


rs2888611
86748321
ABCB4
intron
C/G
0.70
0.172
71.4


rs1922239
86751465
ABCB4
untranslated
C/G

not
66.4








polymorph



rs6979325
86751910
ABCB4
locus
A/C
0.46
0.044
71.4


rs10280466
86751997
ABCB4
locus
G/T

not
70.5








polymorph



rs2178658
86766673

unknown
G/T
0.76
0.233
71.4


rs7789645
86767254

unknown
C/G
1.00
0.175
71.6


rs7793196
86767498

unknown
A/G
1.00
0.175
71.4


rs1055305
86777342

locus
A/C

not
61.9








polymorph



rs1055302
86777567

locus
A/G
0.34
0.133
76.4


rs17064
86778121
ABCB1
untranslated
A/T
0.57
0.055
61.3


rs2235048
86783162
ABCB1
intron
C/T
0.32
0.451
94.6


rs1045642
86783296
ABCB1
coding-non- and
A/C/G/T
0.63
0.446
97.5





synon






rs6949448
86786465
ABCB1
intron
C/T
0.04
0.446
71.4


rs7779562
86789467
ABCB1
intron
C/G
1.00
0.030
89.6


rs2235044
86790476
ABCB1
coding-synon
A/G

not
57








polymorph



rs2235067
86794573
ABCB1
intron
A/G
0.56
0.106
76.6


rs4148744
86795425
ABCB1
intron
C/T
1.00
0.038
64.9


rs4148743
86795741
ABCB1
intron
A/G
0.12
0.479
64.6


rs4148740
86796754
ABCB1
intron
C/T
0.28
0.116
71.2


rs10280101
86798236
ABCB1
intron
A/C
0.56
0.111
70.3


rs7787082
86801702
ABCB1
intron
A/G
0.05
0.152
70.3


rs2032583
86805212
ABCB1
intron
C/T
0.47
0.113
98


rs2032582
86805269
ABCB1
coding-
A/C/G/T
0.37
0.444
74.5





nonsynon






rs9282563
86805296
ABCB1
coding-synon
C/T
1.00
0.002
69.6


rs4148739
86805700
ABCB1
intron
A/G
0.28
0.115
71.4


rs11983225
86806171
ABCB1
intron
C/T
0.40
0.117
70.3


rs4148738
86807700
ABCB1
intron
A/G
0.19
0.448
89.4


rs10248420
86809637
ABCB1
intron
A/G
0.07
0.150
70


rs2235040
86810401
ABCB1
intron
A/G
0.16
0.113
73.6


rs12720067
86814007
ABCB1
intron
A/G
0.25
0.111
71.2


rs1922242
86818318
ABCB1
intron
A/T
0.18
0.439
63.1


rs2235046
86818717
ABCB1
intron
A/G
0.08
0.444
95


re2235036
86819922
ABCB1
coding-
A/G

not
71.8





nonsynon


polymorph



rs2235013
86823277
ABCB1
intron
A/G
0.26
0.500
71.4


rs2235012
86823378
ABCB1
coding-synon
C/G

not
71.6








polymorph



rs2235035
86823737
ABCB1
intron
C/T
0.53
0.345
70.3


rs2235033
86823794
ABCB1
intron
C/T
0.09
0.499
89.6


rs2235032
86824033
ABCB1
intron
G/T

not
70.5








polymorph



rs2032588
86824094
ABCB1
intron
C/T
1.00
0.054
62.8


rs1128503
86824252
ABCB1
coding-synon
C/T
0.57
0.435
71.4


rs2229109
86824460
ABCB1
coding-
A/G
0.38
0.038
73.4





nonsynon






rs2235030
86824577
ABCB1
intron
C/T

not
64.2








polymorph



rs2235029
86824586
ABCB1
intron
G/T

not
64.4








polymorph



rs10276036
86824849
ABCB1
intron
C/T
0.57
0.435
71.2


rs1922240
86828005
ABCB1
intron
C/T
0.54
0.351
71.2


rs2235023
86835103
ABCB1
intron
A/G
1.00
0.066
74.8


rs17407959
86840184
ABCB1
coding-synon
A/T

not
71.6








polymorph



rs17407952
86840185
ABCB1
coding-
G/T

not
71.6





nonsynon


polymorph



rs1202169
86840501
ABCB1
intron
A/G
0.20
0.429
95


rs1202168
86840613
ABCB1
intron
C/T
0.74
0.441
75


rs1202167
86841710
ABCB1
intron
A/G
0.55
0.431
64


rs2235019
86843954
ABCB1
intron
G/T
1.00
0.012
64.6


rs2235018
86844016
ABCB1
intron
A/G
1.00
0.002
64.9


rs2235017
86844024
ABCB1
intron
C/T
1.00
0.012
64.9


rs2235016
86844063
ABCB1
intron
G/T

not
63.3








polymorph



rs2235015
86844215
ABCB1
intron
G/T
0.60
0.168
92.6


rs2235014
86844266
ABCB1
intron
C/T

not
64.9








polymorph



rs6950978
86845118
ABCB1
intron
A/T
0.61
0.333
70.9


rs10256836
86845424
ABCB1
intron
C/G
0.80
0.331
71.4


rs10264990
86847266
ABCB1
intron
C/T
0.90
0.351
70.3


rs1202179
86848930
ABCB1
intron
A/G
0.90
0.334
77.3


rs1989831
86850130
ABCB1
intron
A/T
0.79
0.338
64.6


rs1202172
86855625
ABCB1
intron
G/T
0.75
0.334
98.2


rs1202171
86855696
ABCB1
intron
A/T
0.90
0.335
76.6


rs17327442
86857641
ABCB1
intron
A/T
0.37
0.149
71.2


rs4148733
86857883
ABCB1
intron
C/T
0.23
0.147
64.2


rs1202186
86857909
ABCB1
intron
A/G
1.00
0.329
64


rs1202185
86858035
ABCB1
intron
A/G
0.79
0.338
64.6


rs1202182
86859955
ABCB1
intron
C/T
0.60
0.340
64.6


rs1202181
86860801
ABCB1
intron
C/T
0.66
0.327
55.4


rs2188525
86869423
ABCB1
intron
G/T
1.00
0.035
71.6


rs2235074
86869697
ABCB1
intron
C/T
1.00
0.038
62.8


rs2214102
86874152
ABCB1
untranslated
A/G
0.15
0.103
55.9


rs3213619
86874844
ABCB1
untranslated
C/T

not
62.8








polymorph



rs2188524
86875086
ABCB1
untranslated
A/G

not
64.6








polymorph



rs4728709
86878253
ABCB1
untranslated
A/G
1.00
0.056
70.3


rs4148731
86883980
ABCB1
untranslated
C/T
1.00
0.021
64.4


rs4148730
86884002
ABCB1
untranslated
C/T
1.00
0.019
64.2


rs13233308
86889611
ABCB1
untranslated
C/T
0.43
0.489
71.2


rs4604363
86898847
ABCB1
untranslated
A/G

not
64.6








polymorph



rs2157928
86903055
ABCB1
untranslated.intron
C/T

not
64.4








polymorph



rs4148729
86907037
ABCB1
untranslated.intron
A/C
0.15
0.024
64.9


rs10264856
86907232
ABCB1
untranslated.intron
A/G
1.00
0.050
88.3


rs2157926
86915151
ABCB1
untranslated.intron
A/T
1.00
0.054
64.4


rs4148728
86915468
ABCB1
untranslated.intron
A/C

not
64.4








polymorph



rs10246878
86920292
ABCB1
untranslated.intron
A/G
0.54
0.239
71.2


rs10267099
86923411
ABCB1
untranslated.intron
A/G
0.21
0.237
89.6


rs7796247
86969037
ABCB1
untranslated.intron
A/G
0.13
0.019
89.6


rs916715
86971580
ABCB1
untranslated.intron
C/T

not
64








polymorph



rs2188529
86977122
ABCB1
untranslated.intron
A/T
1.00
0.018
62.4


rs3747802
86987237

locus.intron
C/T

not
60.4








polymorph



rs4148727
86987417

locus.intron
C/T
0.15
0.024
64.9


rs10227683
86987607

locus.intron
C/T

not
71.2








polymorph



rs10275625
87009899

intron
C/T
0.13
0.019
89.6
















TABLE 8







Genotype-dependent group characteristics for rs2235015


The group characteristics number of patients (% women), age, HDRS at


inclusion, age at onset, illness duration in years, previous episodes,


number of previous hospitaiizations, duration of actual episode,


ethnicity, co-medication and diagnosis are shown for each genotype. It


was investigated in an ANOVA analysis whether there are significant


differences between the CC, CT and TT groups (Sig). The Table shows


the results of all patients, patients receiving substrates of P-gps


and patients receiving non-P-gp-substrates.












GG
GT
TT
Sig.











All patients











N (% women)
286 (58.7%) 
112 (52.6%) 
13 (61.5%)
0.51


Age
 49 ± 0.8
46.9 ± 1.3
48.6 ± 3.5 
0.44


HAM-D at
26.6 ± 0.3
26.3 ± 0.6
27.7 ± 2.1 
0.75


inclusion


Age at onset
36.9 ± 0.9
35.7 ± 1.4
41.9 ± 5.2 
0.38


Illness duration
12.1 ± 0.7
11.3 ± 1 
6.7 ± 2.4
0.30


(years)


Previous episodes
 2.4 ± 0.3
  3 ± 0.5
1.3 ± 0.4
0.36


Previous
 1.7 ± 0.3
 1.3 ± 0.2
0.8 ± 0.2
0.68


hospitalization


Duration of actual
39.5 ± 4.2
40.1 ± 6.5
41.3 ± 11.7
0.99


Caucasian
 100%
 100%
100% 


German origin
87.4%
79.5%
100% 
0.10


Neuroleptics
18.5%
13.3%
38.4%  
0.07


Mood stabilizers
18.8%
  16%
7.6%  
0.60


Lithium
 7.3%
 7.2%
0%
0.93


Benzodiazepines
30.7%
30.3%
30.7%  
1.00


Single episode
34.9%
26.7%
38.4%  
0.25


Recurrent
51.5%
58.9%
53.8%  
0.42


depression


Bipolar II
11.3%
13.3%
7.6%  
0.86


Dysthymia
 0.3%
 0.8%
0%
0.52


Schizoaffective
 0.7%
  0%
0%
1.00


disorder


Adjustment
  1%
  0%
0%
0.60


disorder







Substrates of P-gp











N (% women)
96 (62.5%)
33 (51.5%)
 3 (33.3%)
0.36


Age
45.8 ± 1.5
43.4 ± 2.4
48.3 ± 6.6 
0.68


HAM-D at
26.7 ± 0.6
25.9 ± 1.4
28.3 ± 0.8 
0.76


inclusion


Age at onset
34.1 ± 1.5
33.4 ± 2.6
47.6 ± 6.8 
0.30


Illness duration
11.7 ± 1.1
10.3 ± 1.4
0.6 ± 0.3
0.19


(years)


Previous episodes
 2.9 ± 0.6
 1.4 ± 0.2
0.3 ± 0.3
0.29


Previous
 1.2 ± 0.1
 0.7 ± 0.2
0.3 ± 0.3
0.13


hospitalization


Duration of actual
38.9 ± 7.1
 33 ± 7.4
29.3 ± 9.6 
0.88


Caucasian
 100%
 100%
100% 


German origin
84.5%
  88%
100% 
1.00


Neuroleptics
14.5%
24.2%
0%
0.38


Mood stabilizers
16.6%
  6%
0%
0.26


Lithium
 9.4%
  6%
0%
0.79


Benzodiazepines
21.8%
24.2%
33.3%  
0.75


Single episode
30.5%
24.2%
66.6%  
0.29


Recurrent
  52%
66.6%
33.3%  
0.29


depression


Bipolar II
13.6%
  6%
0%
0.55


Dysthymia
  0%
  3%
0%
0.27


Schizoaffective
 2.1%
  0%
0%
1.00


disorder


Adjustment
  1%
  0%
0%
1.00


disorder







Non-substrates of P-gp











N (% women)
62 (51.6%)
30 (53.3%)
 4 (100%)
0.22


Age
49.7 ± 1.8
49.9 ± 2.6
41.7 ± 8.1 
0.55


HAM-D at
27.1 ± 0.8
26.4 ± 1.1
30.7 ± 5.7 
0.48


inclusion


Age at onset
37.7 ± 1.9
38.5 ± 2.6
33.2 ± 10.2
0.80


Illness duration
11.9 ± 1.9
11.3 ± 2.2
8.5 ± 4 
0.89


(years)


Previous episodes
 1.6 ± 0.3
 3.2 ± 0.9
1.5 ± 0.9
0.13


Previous
 2.6 ± 1.5
 1.5 ± 0.4
0 ± 0
0.80


hospitalization


Duration of actual
40 ± 9
 36.8 ± 12.9
30.7 ± 15.3
0.95


Caucasian
 100%
 100%
100% 


German origin
88.2%
  76%
100% 
0.42


Neuroleptics
20.9%
  10%
50% 
0.11


Mood stabilizers
11.2%
 6.6%
0%
0.81


Lithium
 4.8%
  0%
0%
0.60


Benzodiazepines
25.8%
43.3%
25% 
0.23


Single episode
44.2%
26.6%
50% 
0.22


Recurrent
42.6%
66.6%
25% 
0.049


depression


Bipolar II
13.1%
 6.6%
25% 
0.33


Dysthymia
  0%
  0%
0%


Schizoaffective
  0%
  0%
0%


disorder


Adjustment
  0%
  0%
0%


disorder
















TABLE 9







Details with respect to animals, experimental and extraction


procedures, and high-performance liquid chromatography.











Citalopram
Mirtazapine
Venlafaxine














Animals





Gender
male
male
male


Group size [n]
8
9
8


Age [weeks]
16-24
15-17
12-15


Weight abcb1ab(−/−)
31.2 ± 0.6
28.6 ± 0.3
30.6 ± 0.5


Weight abcb1ab(+/+)
29.8 ± 1.0
28.3 ± 0.6
29.9 ± 1.0


Experimental procedure


s.c. administration via osmotic


pumps
60 μg/day
60 μg/day
300 μg/day


Extraction procedures


Isoamyl alcohol (plasma
0%
0%
0.5%


extraction)


Isoamy alcohol (organ
0%
0%
0.5%


extraction)


High-performance liquid


chromatography


Mobile phase gradient [% B]
 5-25
 0-25
 0-30


Detection UV [nm]
214 
214 
214 


Detection fluorescence ex/em
230/300
295/370
225/305


[nm]





B, acetonitrile;


ex, extinction;


em, emission






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## Claims

1. A method for detecting the minor C allele of the rs4148740 polymorphism in a patient, comprising:
a) obtaining a blood sample from a patient suffering from depressive disorder, dysthymia, or bipolar disorder;
b) extracting DNA from the blood sample to provide a DNA sample;
c) contacting the DNA sample with at least one probe or primer capable of hybridizing with ABCB1 gene polymorphism rs4148740, and
d) carrying out genotyping analysis to detect the minor C allele of the rs4148740 polymorphism.

2. The method according to claim 1, further comprising contacting the DNA sample with at least one additional probe or primer capable of determining the presence of a ABCB1 gene polymorphism in linkage disequilibrium with polymorphism rs4148740, wherein said ABCB1 gene polymorphism in linkage disequilibrium with polymorphism rs4148740 is selected from the group consisting of rs2235067, rs2032583, rs4148739, rs11983225, rs2235040, rs12720067, rs7787082, rs10248420, and combinations thereof.

3. The method of claim 1, wherein the genotyping analysis comprises the use of polymorphism-specific primers and/or probes.

4. The method of claim 1, wherein the genotyping analysis comprises a primer extension reaction.

5. The method of claim 1, wherein the genotyping analysis comprises a microarray analysis.

6. The method of claim 1, wherein the genotyping analysis comprises a mass-spectrometric analysis.

7. The method of claim 1, further comprising detecting a change in the function of the ABCB1 gene.

8. The method of claim 7, wherein detecting a change in the function of the ABCB1 gene comprises detecting the transport of specific substances at the blood-brain barrier.