Magnus Altman

Ingelman-Sundberg

Sarah C Sim
email: sarah.sim@ki.se

Russ B Altman

Magnus Ingelman-Sundberg

Databases in the area of Pharmacogenetics

Keywords: Pharmacogenetics, database, personalized medicine, adverse drug reaction, cytochrome P450, transporter, polymorphism Pharmacogenetics, database, personalized medicine, adverse drug reaction, cytochrome P450, transporter, polymorphism Pharmacogenetics, database, personalized medicine, adverse drug reaction, cytochrome P450, transporter, polymorphism

  L'archive ouverte pluridisciplinaire

Introduction

There is a rapid development in genetic analyses and functional genomics covering next generation sequencing methods and versatile arrays that rapidly analyze the most important mutations and gene copy number variations in the genome. Based on this progress, it becomes increasingly evident that much but not all of the drug therapy can be individualized based on genome sequence variation. These efforts can result in pharmacogenomic drug labels that advise the physician to use a genetic test prior to drug prescription. This test can be mandatory, recommended or for information purposes only (see (Sim and Ingelman-Sundberg, 2011) for a review). The genetic variation of interest mainly concerns genes encoding drug metabolizing enzymes, drug transporters, drug targets and human leukocyte antigens (HLA). Only 30-60 % of patients respond to common drug therapy using e.g. antidepressants, statins, and antipsychotics (Spear et al., 2001). Furthermore, adverse drug reactions (ADRs) are an increasing problem (Moore et al., 2007) and apparently cost society as much as the drug therapy itself (cf. Eichelbaum et al., 2006). In addition, meta-analyses by Lazarou et al. (1998) revealed consequences of more than 100,000 deaths annually caused by ADRs in the US, and Davies et al. (2009) have documented an increased length of hospitalization for more than 25% of patients experiencing ADRs in the UK. Also, ADRs are shown to occur in 16 % of hospitalized patients, frequently with severe consequences (Davies et al., 2009), and ADRs have in several studies been shown to be responsible for about 7 % of hospitalizations in the average population (Lazarou et al., 1998;Davies et al., 2009), 20 % of readmissions to the hospital F o r P e e r R e v i e w (Davies et al., 2010) and more than 30 % among elderly (Paul et al., 2008). These data emphasize the need of updated databases that can provide fruitful guidance to both scientists, physicians, regulatory agencies and industries to cope with this major problem in human health.

The Pharmacogenomics Knowledge Base (PharmGKB)

The Pharmacogenomics Knowledgebase (PharmGKB, http://www.pharmgkb.org/) was established in 2000 and strives to provide information on how human genetic variation impacts drug response. Stable government-funded efforts such as Genbank, Gene Expression Omnibus, and dbGAP from the National Center for Biomedical Information (NCBI) at the National Institutes of Health (NIH) in the US are the preferred databases for archiving data, whereas curation of genes (or groups of related homologous genes) and their variations are best handled by locus-specific databases (LSDBs) such as the Human Cytochrome P450 (CYP) Allele Nomenclature Website (see section 3), and others focusing on transporters, receptors, and kinases. In contrast, PharmGKB focuses on four main activities: (1) curation of published literature in respect to relationships between genes, their variations, and drug response phenotypes, (2) creation of "Very Important Pharmacogene" (VIP gene) summaries that highlight specific pharmacogenomic significance of genes that are very important for drug response, (3) creation of pathway diagrams focusing on drug response (pharmacodynamics, PD) and drug metabolism (pharmacokinetics, PK) pathways, and finally (4) assistance to organize and lead data-sharing consortia within pharmacogenomics where multiple centers combine data and expertise to answer questions that cannot be answered by any center alone (usually because of statistical power and smaller data sets). The core activity of PharmGKB curators is to survey the literature and capture reports of human genetic variation that impacts drug response phenotypes. These phenotypes may occur at the molecular (e.g. binding), cellular (e.g. expression), tissue (e.g. drug transformation) or organismal level (e.g. disease, symptoms), and all annotations are encoded with respect to these categories to assist in searches. The PharmGKB has a list of journals publishing pharmacogenomics observations, and also broadly searches the literature on a weekly basis to find associations between genes, their variations, drugs, and phenotypes. The PharmGKB uses the Human Genome Nomenclature Committee recommendations for genes and variations. Also, they use a combination of the RcNorm drug list with some modifications for drug, and Medical Subject Headings (MeSH) and Unified Medical Language System (UMLS) to encode phenotypes.

The result of this curation activity is currently about 2500 annotations that associate particular human variations (mostly SNPs, but also including insertions or deletions (indels), copy number variations, structural changes, and haplotypes) with drug-related phenotypes. These annotations were recently used to create a "pharmacogenomic annotation" of a complete human genome sequence (Ashley et al., 2010). Interestingly, there were nearly 100 drugs for which risks or benefits could be predicted for this individual. Many of them were "low confidence" based on the level of published evidence, but several of them would have some clinical utility. The application of the PharmGKB annotations to this genome was manual, and so current efforts are aimed at representing the basic variant annotations and their potential clinical consequences in a more structured manner that will allow more automated application to individual genomes.

Writing VIP gene summaries

As the PharmGKB curators accumulate individual variant annotations, the genes may appear as either (1) repeatedly involved in drug response because of their role in general drug pharmacokinetics (e.g. cytochrome P450s, transporters, transferases) or (2) having an important role in the action of a single drug or class of drugs (e.g. pharmacodynamic drug targets). When the amount of information for these genes reaches a level that the curators find to be sufficiently large, they can designate these genes as VIP genes 1 . The PharmGKB curators prioritize these genes for short written summary reviews of their role in drug response, and the key variations in these genes that have been shown to modulate drug response. These reviews are re-examined every two years or more frequently if the pace of new knowledge generation is rapid, and are written in a templated manner that includes names and alternate names, introductory information, key publications, key pathways, known drugs/substrates, associated phenotypes/diseases and summaries of key variants with their associated effects. There are currently 43 VIP genes on the PharmGKB website, and their summaries are published regularly in a cooperative venture with the Pharmacogenetics & Genomics journal in order to draw attention to them and to provide a citation for their usage (Eichelbaum et al., 2009;Mi et al., 2010). In addition to the VIP gene summaries, curators also create annotated graphical pathways depicting the relationships of genes and drugs. These pathways are the most popular feature at PharmGKB. Each pathway is the result of a PharmGKB curator gathering all information available for the drug of interest (for example, by collecting the basic annotations and genedrug relationships discussed above), and assembling a pathway summary. These pathways are often created collaboratively with experts working on these systems and they include a downloadable graphical depiction that is linked to the individual genes and small molecules depicted.

Creating pathways of drug response and metabolism

It also includes supporting data and references upon which the pathway is based. As with the VIP genes, the pathways are also published regularly in the Pharmacogenetics & Genomics journal (Eichelbaum et al., 2009;Sangkuhl et al., 2010). In addition to PharmGKB-generated pathways, PharmGKB links to pathways from external resources, and they are made available to augment the PharmGKB pathways.

Data sharing consortia

A somewhat unexpected activity for PharmGKB has been the convening of data sharing consortia. The mission of PharmGKB is to promote the creation and sharing of data about pharmacogenomics, and as a trusted third party, PharmGKB is in a good position to bring together groups of investigators interested in common scientific questions. After signing a memorandum of understanding that outlines the responsibilities and privileges of joining the consortium (and protects the rights of data generators to publish, as well as the rights of the consortium members to see data and participate in its analysis), the PharmGKB accepts data sets, brings them into a common format, and then participates in the statistical analysis to answer one or more shared scientific questions. The first example of a PharmGKB consortium was the International Warfarin Pharmacogenetics Consortium (IWPC) which brought together 21 groups internationally to create a globally-relevant warfarin dosing algorithm, as well as an analysis of inter-ethnicity differences in warfarin dosing (Klein et al., 2009;Limdi et al., 2010).

Other consortia have subsequently been established addressing the discovery of new genetic variations relevant to warfarin, the role of CYP2D6 variations in tamoxifen response, and the role of CYP2D6 in selective serotonin reuptake inhibitor (SSRI) response. A list of consortia and their members are available on the "Contributors" tab of PharmGKB.

The PharmGKB website and other activities

In addition to a global search capability, users of PharmGKB are able to search for particular kinds of information in five more focused search boxes: genes, variants, pathways, drugs, and diseases. These search boxes can accept any text, but will only return results of one of these 5 specific types. In addition, the home page provides the PharmGKB curators "Favorite Papers" that are updated every two weeks, and are available as an archive over the last four years. The home page also offers an automatically created pharmacogenomics news feed, access to tutorial information, introductions to pharmacogenetics, and access to tools.

Current new efforts at PharmGKB focus on:

• The development of automated natural language parsing tools to extract annotation information from the literature automatically (Coulet et al., 2010;Garten and Altman 2010;Garten and Altman 2009). • The addition of chemoinformatics, such as drug structure similarity metrics to help predicting new gene-drug interactions (Garten et al., 2010;Hansen et al., 2009).

• The creation of systems biology methods to look at drug response with a more networkbased view of the genes involved in producing complex drug responses (Hansen et al., 2009;Tatonetti et al., 2009).

The Human Cytochrome P450 (CYP) Allele Nomenclature Website

Cytochrome P450 enzymes are responsible for 75-80 % of all phase I-dependent metabolism, resulting in more polar metabolites that can be further conjugated in Phase II metabolism, and for 65-70 % of the clearance of clinically used drugs (Bertz and Granneman 1997;Evans and Relling 1999). CYP enzymes are encoded by 57 CYP genes and divided into families, of which 1-3 (CYP1-3) are generally involved in the metabolism of exogenous substances including drugs, whereas members of other families mainly are involved in metabolism of endogenous compounds. Variation in CYP genes results in four different phenotypes classically defined as ultrarapid, extensive, intermediate and poor metabolizers.

Characterization of the genetic polymorphism of CYP enzymes provides a basis for personalized medicine composing drug dose adjustment and selection of drug type (Ingelman-Sundberg 2004;Ingelman-Sundberg et al., 2007;Kirchheiner et al., 2004;[START_REF] Pirmohamed | Genetic susceptibility to adverse drug reactions[END_REF]Weinshilboum 2003) To unite and summarize efforts focusing on the characterization of CYP polymorphism, the Human Cytochrome P450 Allele (CYP-allele) Nomenclature Committee was established in 1999, and the efforts resulted in agreed CYP nomenclature guidelines and the launching of the CYP- At present, 29 polymorphic CYPs are included on the CYP-allele website, with the addition in 2008 of NADPH cytochrome P450 reductase (POR) (Sim et al., 2009) due to its elementary function as electron donor to CYP enzymes. Every gene has its own webpage, listing the associated alleles and their consequences on the genetic, molecular, in vitro and in vivo levels, all together with relevant references and links to the NCBI dbSNP database.

The nomenclature system designates numbers (such as CYP2B6*4) for alleles that have been thoroughly sequenced and well characterized in terms of linkage of the functionally relevant SNP with other polymorphic sites. Functionally relevant in this aspect is regarded as a variation causing measurable consequences such as amino acid substitutions, translation terminations or splice defects. At a minimum, the open reading frame must have been sequenced. All sequence variations are numbered based on A in the translation initiation codon as the reference nucleotide (+1). Additional letter-designated sub-alleles of the same number (such as CYP2B6*4B) contain the same functional SNP but additional sequence variations not causing functional effects. A combination of functionally relevant variants are designated a new allele number due to the potential of combinatorial effects, unless one of the variant is deleterious and thus defines the allele name. As an example, CYP2C19*2 carries a SNP causing a splice defect of the transcribed RNA that is detrimental for enzyme function. This splice defect

Deleted: full coding region

Deleted: be Deleted: , although flanking regions and introns would preferentially be covered as well, especially when a gene has shown to carry important variations in these regions.

Deleted: with

Deleted: contains non-causative Deleted: in addition to the causative one that defines the allele. Such suballeles are named when they have been characterized together with the mother allele (e.g. CYP2B6*4A), but are Deleted: designated thereafter due to the uncertainty whether they compose new alleles or just additional coverage by the sequencing method.

Deleted: causative

Deleted: that can also be found alone Deleted: whereby the combination allele will be designated a sub-allele name. attained much focus since CYP2C19 is responsible for bioactivation of the drug. A recent metaanalysis of 9 studies and almost 10,000 patients showed a significantly increased risk of adverse cardiovascular events in carriers of defective (mainly CYP2C19*2) alleles due to impaired bioactivation of clopidogrel, especially in patients having undergone percutaneous intervention, and in particular for stent thrombosis as the major cardiovascular event (Mega et al., 2010).

Computer-inferred haplotypes are generally avoided, although some predicted alleles have been assigned and included on the CYP-allele website. Alleles published in the early beginning of the CYP-allele era do not fully comply with the current standard.

Submission of new alleles is achieved by contacting the Webmaster of the CYP-allele website, whereby the data characterizing the allele is reviewed for potential allele name designation (see inclusion criteria at http://www.cypalleles.ki.se/criteria.htm). All information is kept confidential and a manuscript in preparation can often serve as a good basis for review and discussion between the author and the Webmaster. Designation of allele names outside the CYP-allele nomenclature committee is not advised, due to the apparent risk of confusion in the literature. Submissions with respect to additional functional in vivo and in vitro characterization of alleles listed are also highly relevant, and aids in keeping the CYP-allele website up to date. structures and these enzymes were early described in terms of pharmacogenetic variation, resulting in slow and rapid acetylation phenotypes that may impact the risk of drug-induced toxicity (Sim et al., 2008). There are two active genes in the NAT locus, NAT1 and NAT2 and in 1995, a nomenclature system was published (Vatsis et al., 1995). However, a systematic procedure for naming new alleles was not in use at once and resulted in problems such as dual assignments. From 1998, further discussions resulted in the formation of the Human Arylamine N-Acetyltransferase (NAT) Gene Nomenclature Committee with the aim to reach a nomenclature consensus for NAT alleles (Hein et al., 2008;Hein et al., 2000). A website was launched for maintenance of the renewed system and to provide an update on NAT alleles (http://n-acetyltransferasenomenclature.louisville.edu/). New allele submissions are sent to the NAT Nomenclature Committee for review, and the NAT allele website covers alleles of the NAT1 and NAT2 genes. The NAT allele nomenclature follows the star system (e.g. NAT*5) with special focus on functionally relevant sequence variations, whereby sub-alleles defined by an extra letter may contain additional variants that are functionally not relevant compared to the SNP causing the major effect. For example, alleles of the NAT2*5 series (NAT2*5A-P) all contain a SNP causing the I114T amino acid substitution that in turn causes slow acetylation, which is associated with an increased risk of drug-induced liver injury in isoniazid-treated tuberculosis patients (Daly, 2010). The NAT website also contains NAT allele information in the pdf format reporting nucleotide changes, amino acid changes, phenotypes (slow or rapid acetylation), NCBI dbSNP numbers and relevant references, as well as information on allele inclusion criteria for designation of new alleles.

As opposed to other nomenclature systems, the "wild type" allele is not designated NAT*1 due to historical reasons. Thus, the reference allele for NAT nomenclature is NAT*4 for both NAT genes. As a result of this, NAT alleles with numbers between *1 and *3 are excluded from the nomenclature system. At present, 29 alleles are presented for NAT1 and 21 for NAT2.

The Pharmacogenetics of Membrane Transporters (PMT) database

The Pharmacogenetics of Membrane Transporters (PMT) database (http://pharmacogenetics.ucsf.edu/) (Kroetz et al., 2010) is part of the PharmGKB (see section 2) with as focus on drug response in relation to genetic variation in membrane transporters.

Since membrane transporters are involved in the transport of drugs, genetic variation affecting transport function may impact drug therapy in terms of both response and ADRs. The PMT project was initiated in 2000 and focuses on the two superfamilies of solute carrier (SLC) transporters (n= 366) and ATP binding cassette (ABC) transporters (n=46). The database covers coding and non-coding variations as well as both SNPs and indels, but does not provide allele or haplotype information. The list of transporter proteins contains the OMIM phenotype, nucleotide and protein reference sequences, Entrez hits, and number of isoforms (splice variants) for every gene. The whole list is composed of 430 genes, although not all are transporter proteins since for some unknown reason genes such as monoamine oxidase A Deleted: . The NAT nomenclature pdf files also contain Deleted: and the risk of confusion with renaming of alleles. (MAOA), pregnane X receptor (PXR) and POR are also included in this list. Most genes are extensively presented on their own web page, containing information such as main tissue expression sites, substrates, gene structure, and genetic variation. The genetic variants are reported by their genomic, transcript and coding position, together with amino acid effects, array availability, PubMed and dbSNP links, and the frequency observed in different populations. Also, a secondary structure transmembrane prediction shows the position of amino acid substitutions, insertions or deletions within the transporter protein. Additionally, the PMT database provides a search tool to access gene expression data with respect to a single gene in multiple tissues (Gene Plot), selected genes in selected tissues (Mixed Plot) and multiple genes in a single tissue (Tissue Plot).

Transporter database (TP-search)

On the Transporter Database TP-search website (http://www.tp-search.jp/) (Ozawa et al., 2004), transporters are summarized under the respective species and the human section contains 33 transporter proteins together with information such as the driving force used (e.g. ATP, Na + ), the presence of SNPs, protein length, direction of transport and association with disease. In addition, searches can be performed by transporter name, compound name, drugdrug interaction, pathophysiology, genetic polymorphisms, and tissue name. Additional web pages include gender differences, animal models, and genetic diseases. The Transporter Name search includes the choice of human, mouse and/or rat species, and substrate, inhibitor and/or inducer substances. The Transporter Name search outcome includes parameters associated with the requested transporter, i.e. substance name and chemical structure, interaction type, Deleted: The PMT database's POR web page contains additional apparent noncoding variants, but do not provide any additional causative variants, as compared to the official POR allele nomenclature present at the CYP-allele website, neither does it provide with allele or haplotype information. Of the 430 genes presented, 366 encode SLC transporters and 46 encode ABC transporters.

Deleted: with its

UGT Alleles Nomenclature Page

UGT enzymes (Phase II metabolism) link glycosyl groups to endogenous and exogenous substrates including drugs, to yield more hydrophilic products that can be more easily excreted from the body (Mackenzie et al., 2005). The UDP-glucuronosyltransferase (UGT) Allele TA repeats causes reduced UGT1A1 gene transcription and the common reduced activity UGT1A1*28 allele associates with reduced clearance of SN-38 (Schulz 2009 PMID: 19770637).

Due to the increased risk of neutropenia in UGT1A1*28/*28 subjects, the Food and Drug Administration in the US recommends a lower starting dose of irinotecan in such patients.

PharmaADME

PharmaADME (http://www.pharmaadme.org/) is a database initiated by academic and industrial interests. The aim of this database is to compile lists of genes and genetic variation affecting Absorption, Distribution, Metabolism and Excretion (ADME) of drugs. The PharmaADME's main aim is to aid in selection of genotyping assays for product development and clinical trials. PharmaADME provides three gene lists, the ADME Gene List, the Core Marker Gene List and the Related Gene List. The ADME Gene Lists contain genes associated with drug metabolism, either sorted under the more important Core List of 32 genes or under the Extended ADME Gene List of 267 genes. The ADME Gene Lists contains the gene symbol, full gene name and the protein class, but no other information and no links to information on which the qualifications are based or which drugs the gene product is affecting. The Related Gene List contains 74 genes that are related to, but not involved in, drug metabolism such as drug targets and receptors. The Core Marker Gene List is composed of 184 genotypes in 32 genes, of which 11 are CYPs, 9 are transporters and 9 are transferases, which by PharmaADME have been selected as most important. This list comprises the gene symbol, the primary name (e.g. CYP2D6*5) and the NCBI dbSNP number.

Conclusions

The area of pharmacogenomics is rapidly developing. It is anticipated that novel, cheaper and more efficient high throughput techniques for genomic analyses as well as the discovery of interindividual variation in epigenomic control of gene expression and the identification of additional types of snRNA molecules, will result in a rapid expansion of the area. Consequently, the number of useful biomarkers for predicting drug response will rapidly increase in quantity and quality. Thus, existing and future databases, which are developed in a user-friendly manner, will provide relevant information on drugs and gene variants for physicians, scientists, regulatory agencies and industry, and constitute very important tools for the possibility to improve drug treatment and settle the basis for personalized medicine in society. (Sim and Ingelman-Sundberg, 2011) for a review). The genetic variation of interest mainly concerns genes encoding drug metabolizing enzymes, drug transporters, drug targets and human leukocyte antigens (HLA). Only 30-60 % of patients respond to common drug therapy using e.g. antidepressants, statins, and antipsychotics (Spear et al., 2001). Furthermore, adverse drug reactions (ADRs) are an increasing problem (Moore et al., 2007) and apparently cost society as much as the drug therapy itself (cf. Eichelbaum et al., 2006). In addition, meta-analyses by Lazarou et al. (1998) revealed consequences of more than 100,000 deaths annually caused by ADRs in the US, and Davies et al. (2009) have documented an increased length of hospitalization for more than 25% of patients experiencing ADRs in the UK. Also, ADRs are shown to occur in 16 % of hospitalized patients, frequently with severe consequences (Davies et al., 2009), and ADRs have in several studies been shown to be responsible for about 7 % of hospitalizations in the average population (Lazarou et al., 1998;Davies et al., 2009), 20 % of readmissions to the hospital (Davies et al., 2010) and more than 30 % among elderly (Paul et al., 2008). These data emphasize the need of updated databases that can provide fruitful guidance to both scientists, physicians, regulatory agencies and industries to cope with this major problem in human health.

The Pharmacogenomics Knowledge Base (PharmGKB)

The Pharmacogenomics Knowledgebase (PharmGKB, http://www.pharmgkb.org/) was established in 2000 and strives to provide information on how human genetic variation impacts drug response. Stable government-funded efforts such as Genbank, Gene Expression Omnibus, and dbGAP from the National Center for Biomedical Information (NCBI) at the National Institutes of Health (NIH) in the US are the preferred databases for archiving data, whereas curation of genes (or groups of related homologous genes) and their variations are best handled by locus-specific databases (LSDBs) such as the Human Cytochrome P450 (CYP) Allele Nomenclature Website (see section 3), and others focusing on transporters, receptors, and kinases. In contrast, PharmGKB focuses on four main activities: (1) curation of published literature in respect to relationships between genes, their variations, and drug response phenotypes, (2) creation of "Very Important Pharmacogene" (VIP gene) summaries that highlight specific pharmacogenomic significance of genes that are very important for drug response, (3) creation of pathway diagrams focusing on drug response (pharmacodynamics, PD)

and drug metabolism (pharmacokinetics, PK) pathways, and finally (4) assistance to organize and lead data-sharing consortia within pharmacogenomics where multiple centers combine data and expertise to answer questions that cannot be answered by any center alone (usually because of statistical power and smaller data sets). The core activity of PharmGKB curators is to survey the literature and capture reports of human genetic variation that impacts drug response phenotypes. These phenotypes may occur at the molecular (e.g. binding), cellular (e.g. expression), tissue (e.g. drug transformation) or organismal level (e.g. disease, symptoms), and all annotations are encoded with respect to these categories to assist in searches. The PharmGKB has a list of journals publishing pharmacogenomics observations, and also broadly searches the literature on a weekly basis to find associations between genes, their variations, drugs, and phenotypes. The PharmGKB uses the Human Genome Nomenclature Committee recommendations for genes and variations. Also, they use a combination of the RcNorm drug list with some modifications for drug, and Medical Subject Headings (MeSH) and Unified Medical Language System (UMLS) to encode phenotypes.

Curation of published literature

The result of this curation activity is currently about 2500 annotations that associate particular human variations (mostly SNPs, but also including insertions or deletions (indels), copy number variations, structural changes, and haplotypes) with drug-related phenotypes. These annotations were recently used to create a "pharmacogenomic annotation" of a complete human genome sequence (Ashley et al., 2010). Interestingly, there were nearly 100 drugs for which risks or benefits could be predicted for this individual. Many of them were "low confidence" based on the level of published evidence, but several of them would have some clinical utility. The application of the PharmGKB annotations to this genome was manual, and so current efforts are aimed at representing the basic variant annotations and their potential clinical consequences in a more structured manner that will allow more automated application to individual genomes.

Writing VIP gene summaries

As the PharmGKB curators accumulate individual variant annotations, the genes may appear as either (1) repeatedly involved in drug response because of their role in general drug pharmacokinetics (e.g. cytochrome P450s, transporters, transferases) or ( 2) having an important role in the action of a single drug or class of drugs (e.g. pharmacodynamic drug targets). When the amount of information for these genes reaches a level that the curators find to be sufficiently large, they can designate these genes as VIP genes 1 . The PharmGKB curators prioritize these genes for short written summary reviews of their role in drug response, and the key variations in these genes that have been shown to modulate drug response. These reviews are re-examined every two years or more frequently if the pace of new knowledge generation is rapid, and are written in a templated manner that includes names and alternate names, introductory information, key publications, key pathways, known drugs/substrates, associated phenotypes/diseases and summaries of key variants with their associated effects. There are currently 43 VIP genes on the PharmGKB website, and their summaries are published regularly in a cooperative venture with the Pharmacogenetics & Genomics journal in order to draw attention to them and to provide a citation for their usage (Eichelbaum et al., 2009;Mi et al., 2010).

Creating pathways of drug response and metabolism

1 Very Important Pharmacogene (VIP gene) denotes genes that have a documented role in modulating the response to one or more drugs In addition to the VIP gene summaries, curators also create annotated graphical pathways depicting the relationships of genes and drugs. These pathways are the most popular feature at PharmGKB. Each pathway is the result of a PharmGKB curator gathering all information available for the drug of interest (for example, by collecting the basic annotations and genedrug relationships discussed above), and assembling a pathway summary. These pathways are often created collaboratively with experts working on these systems and they include a downloadable graphical depiction that is linked to the individual genes and small molecules depicted.

It also includes supporting data and references upon which the pathway is based. As with the VIP genes, the pathways are also published regularly in the Pharmacogenetics & Genomics journal (Eichelbaum et al., 2009;Sangkuhl et al., 2010). In addition to PharmGKB-generated pathways, PharmGKB links to pathways from external resources, and they are made available to augment the PharmGKB pathways.

Data sharing consortia

A somewhat unexpected activity for PharmGKB has been the convening of data sharing consortia. The mission of PharmGKB is to promote the creation and sharing of data about pharmacogenomics, and as a trusted third party, PharmGKB is in a good position to bring together groups of investigators interested in common scientific questions. After signing a memorandum of understanding that outlines the responsibilities and privileges of joining the consortium (and protects the rights of data generators to publish, as well as the rights of the consortium members to see data and participate in its analysis), the PharmGKB accepts data sets, brings them into a common format, and then participates in the statistical analysis to answer one or more shared scientific questions. The first example of a PharmGKB consortium was the International Warfarin Pharmacogenetics Consortium (IWPC) which brought together 21 groups internationally to create a globally-relevant warfarin dosing algorithm, as well as an analysis of inter-ethnicity differences in warfarin dosing (Klein et al., 2009;Limdi et al., 2010).

Other consortia have subsequently been established addressing the discovery of new genetic variations relevant to warfarin, the role of CYP2D6 variations in tamoxifen response, and the role of CYP2D6 in selective serotonin reuptake inhibitor (SSRI) response. A list of consortia and their members are available on the "Contributors" tab of PharmGKB.

The PharmGKB website and other activities

In addition to a global search capability, users of PharmGKB are able to search for particular kinds of information in five more focused search boxes: genes, variants, pathways, drugs, and diseases. These search boxes can accept any text, but will only return results of one of these 5 specific types. In addition, the home page provides the PharmGKB curators "Favorite Papers" that are updated every two weeks, and are available as an archive over the last four years. The home page also offers an automatically created pharmacogenomics news feed, access to tutorial information, introductions to pharmacogenetics, and access to tools.

Current new efforts at PharmGKB focus on:

• The development of automated natural language parsing tools to extract annotation information from the literature automatically (Coulet et al., 2010;Garten and Altman 2010;Garten and Altman 2009). • The addition of chemoinformatics, such as drug structure similarity metrics to help predicting new gene-drug interactions (Garten et al., 2010;Hansen et al., 2009).

• The creation of systems biology methods to look at drug response with a more networkbased view of the genes involved in producing complex drug responses (Hansen et al., 2009;Tatonetti et al., 2009). At present, 29 polymorphic CYPs are included on the CYP-allele website, with the addition in 2008 of NADPH cytochrome P450 reductase (POR) (Sim et al., 2009) due to its elementary function as electron donor to CYP enzymes. Every gene has its own webpage, listing the associated alleles and their consequences on the genetic, molecular, in vitro and in vivo levels, all together with relevant references and links to the NCBI dbSNP database.

The Human

The nomenclature system designates numbers (such as CYP2B6*4) for alleles that have been and in particular for stent thrombosis as the major cardiovascular event (Mega et al., 2010).

Computer-inferred haplotypes are generally avoided, although some predicted alleles have been assigned and included on the CYP-allele website. Alleles published in the early beginning of the CYP-allele era do not fully comply with the current standard.

Submission of new alleles is achieved by contacting the Webmaster of the CYP-allele website, whereby the data characterizing the allele is reviewed for potential allele name designation (see inclusion criteria at http://www.cypalleles.ki.se/criteria.htm). All information is kept confidential and a manuscript in preparation can often serve as a good basis for review and discussion between the author and the Webmaster. Designation of allele names outside the CYP-allele nomenclature committee is not advised, due to the apparent risk of confusion in the literature. Submissions with respect to additional functional in vivo and in vitro characterization of alleles listed are also highly relevant, and aids in keeping the CYP-allele website up to date. structures and these enzymes were early described in terms of pharmacogenetic variation, resulting in slow and rapid acetylation phenotypes that may impact the risk of drug-induced toxicity (Sim et al., 2008). There are two active genes in the NAT locus, NAT1 and NAT2 and in 1995, a nomenclature system was published (Vatsis et al., 1995). However, a systematic procedure for naming new alleles was not in use at once and resulted in problems such as dual assignments. From 1998, further discussions resulted in the formation of the Human Arylamine N-Acetyltransferase (NAT) Gene Nomenclature Committee with the aim to reach a nomenclature consensus for NAT alleles (Hein et al., 2008;Hein et al., 2000). A website was launched for maintenance of the renewed system and to provide an update on NAT alleles (http://n-acetyltransferasenomenclature.louisville.edu/). New allele submissions are sent to the NAT Nomenclature Committee for review, and the NAT allele website covers alleles of the NAT1 and NAT2 genes. The NAT allele nomenclature follows the star system (e.g. NAT*5) with special focus on functionally relevant sequence variations, whereby sub-alleles defined by an extra letter may contain additional variants that are functionally not relevant compared to the SNP causing the major effect. For example, alleles of the NAT2*5 series (NAT2*5A-P) all contain a SNP causing the I114T amino acid substitution that in turn causes slow acetylation, which is associated with an increased risk of drug-induced liver injury in isoniazid-treated tuberculosis patients (Daly, 2010). The NAT website also contains NAT allele information in the pdf format reporting nucleotide changes, amino acid changes, phenotypes (slow or rapid acetylation), NCBI dbSNP numbers and relevant references, as well as information on allele inclusion criteria for designation of new alleles.

As opposed to other nomenclature systems, the "wild type" allele is not designated NAT*1 due to historical reasons. Thus, the reference allele for NAT nomenclature is NAT*4 for both NAT genes. As a result of this, NAT alleles with numbers between *1 and *3 are excluded from the nomenclature system. At present, 29 alleles are presented for NAT1 and 21 for NAT2.

The Pharmacogenetics of Membrane Transporters (PMT) database

The Pharmacogenetics of Membrane Transporters (PMT) database (http://pharmacogenetics.ucsf.edu/) (Kroetz et al., 2010) is part of the PharmGKB (see section

2) with as focus on drug response in relation to genetic variation in membrane transporters.

Since membrane transporters are involved in the transport of drugs, genetic variation affecting transport function may impact drug therapy in terms of both response and ADRs. The PMT project was initiated in 2000 and focuses on the two superfamilies of solute carrier (SLC) transporters (n= 366) and ATP binding cassette (ABC) transporters (n=46). The database covers coding and non-coding variations as well as both SNPs and indels, but does not provide allele or haplotype information. The list of transporter proteins contains the OMIM phenotype, nucleotide and protein reference sequences, Entrez hits, and number of isoforms (splice variants) for every gene. The whole list is composed of 430 genes, although not all are transporter proteins since for some unknown reason genes such as monoamine oxidase A

Transporter database (TP-search)

On the Transporter Database TP-search website (http://www.tp-search.jp/) (Ozawa et al., 2004), transporters are summarized under the respective species and the human section contains 33 transporter proteins together with information such as the driving force used (e.g.

ATP, Na + ), the presence of SNPs, protein length, direction of transport and association with disease. In addition, searches can be performed by transporter name, compound name, drugdrug interaction, pathophysiology, genetic polymorphisms, and tissue name. Additional web pages include gender differences, animal models, and genetic diseases.

UGT Alleles Nomenclature Page

UGT enzymes (Phase II metabolism) link glycosyl groups to endogenous and exogenous substrates including drugs, to yield more hydrophilic products that can be more easily excreted from the body (Mackenzie et al., 2005). The UDP-glucuronosyltransferase (UGT) Allele TA repeats causes reduced UGT1A1 gene transcription and the common reduced activity UGT1A1*28 allele associates with reduced clearance of SN-38 (Schulz 2009 PMID: 19770637).

Due to the increased risk of neutropenia in UGT1A1*28/*28 subjects, the Food and Drug Administration in the US recommends a lower starting dose of irinotecan in such patients.

PharmaADME

Conclusions

The area of pharmacogenomics is rapidly developing. It is anticipated that novel, cheaper and more efficient high throughput techniques for genomic analyses as well as the discovery of interindividual variation in epigenomic control of gene expression and the identification of additional types of snRNA molecules, will result in a rapid expansion of the area. Consequently, the number of useful biomarkers for predicting drug response will rapidly increase in quantity and quality. Thus, existing and future databases, which are developed in a user-friendly manner, will provide relevant information on drugs and gene variants for physicians, scientists, regulatory agencies and industry, and constitute very important tools for the possibility to improve drug treatment and settle the basis for personalized medicine in society.

F

  Deleted: and provide "one stop shopping" for users interested in drugrelated pathways.Deleted: the curators have outstanding skills at data organization, representation, aggregation and integration. As Deleted: that are difficult to answer individually because of small sample sizes.

  http://www.cypalleles.ki.se/). The main purpose of the CYP-allele website is the management of new allele designations based on recognized nomenclature guidelines, facilitation of rapid publication, as well as providing a readily available summary of alleles and their associated effects (Ingelman-Sundberg and Oscarson 2002; Oscarson and Ingelman-Sundberg 2002; Sim and Ingelman-Sundberg 2006; Sim and Ingelman-Sundberg 2010).

Formatted

  exists in different combinations with other SNPs causing amino acid substitutions and the combination alleles have thus received allele names CYP2C19*2A-D. The effect of CYP2C19 genotype on clopidogrel (Plavix  ) antiplatelet treatment of cardiovascular disease has

  Human Arylamine N-Acetyltransferase (NAT) Gene Nomenclature Committee Arylamine N-acetyltransferases (NATs) conjugate drugs and xenobiotics containing arylamine

  K i values, experimental setup used for producing the data and references to publications. Similar searches can be done with the Compound Name, where a list of transporters interacting with the substance is provided. The Drug-Drug Interaction search involves in vivo data, and displays drug-drug interactions involving the searched compound, together with its effects on parameters such as clearance, C max and area under plasma concentration curve (AUC). Also, the interaction site where the effects are believed to occur is presented. The Tissue Distribution search provides schematic figures of the transporters present in intestine, kidney or liver. In addition, a tissue distribution table lists the tissue and localization of the transporters, together with the experimental method used and the corresponding references. The Genetic Polymorphism search of functionality yields in vivo information on the respective transporter SNPs (but not alleles or haplotypes) with respect to nucleotide changes, protein changes, drug involved, type of drug administration, number and ethnicity of the study sample, in vivo parameters (such as AUC or plasma concentration), and the relationship between the different genotypes. A similar Genetic search with respect to frequency yields the distribution of the polymorphisms in different populations. A reference sequence with respect to the nucleotide change is however not provided and the TP-search database has not been updated since 2007.

  Nomenclature Page (http://www.pharmacogenomics.pha.ulaval.ca/sgc/ugt_alleles) contains UGT enzymes of subfamily UGT1A (9 enzyme web pages) and UGT2B (5 active web pages). The inclusion criteria are based on the CYP-allele nomenclature system, and thus alleles designated by the Webmaster contains an asterisk and a number where the *1 allele (e.g. UGT1A1*1) is considered the wild type allele. Similarly to CYP-alleles, the UGT Alleles Nomenclature Page focus on nucleotide changes that cause functional effects such as amino acid substitutions, splice defects and frameshifts, and thus alleles with additional variations not causing any effects receives a sub (letter) allele name. Every enzyme has a "Haplotype" page and a "SNP" page, where the former contains a list of all alleles and their changes whereas the latter contain a list of all SNPs together with their rs numbers and the reference sequence used. As an example, the UGT1A1 Haplotype web page contains 113 different alleles that are presented with their allelic names, nucleotide changes, protein effects, exon numbers affected, consequences (e.g. frameshift), phenotypes with respect to causation of Crigler-Najjar syndrome or Gilbert's syndrome, enzyme activity in vitro and in vivo, and the respective references. The rare Crigler-Najjar syndrome is caused by a complete inability to glucuronize bilirubin due to UGT1A1 mutations that consequently causes jaundice and potential brain injury, whereas reduced but not depleted UGT1A1-mediated glucuronidation of bilirubin lead to the less severe phenotype Gilbert's syndrome. UGT1A1 is also involved in the metabolism of the anti-cancer drug irinotecan, since the active metabolite SN-38 is glucuronidated and inactivated by UGT1A1.Excessive levels of SN-38 can cause neutropenia, the risk of which is affected by UGT1A1 genotype. The wild-type allele UGT1A1*1 carries a 6-repeat TATA box, (A(TA) 6 TAA) whereas UGT1A1*36 has 5, UGT1A1*28 has 7 and UGT1A1*37 has 8 repeats. An increased number of

Formatted:

  Level 1, Keep with next, Tabs: 113.4 pt, Left + 177.2 pt, Left + 191.4 pt, Left + 269.35 pt, Left + 361.5 pt, Left + 375.65 pt,

  Cytochrome P450 (CYP) Allele Nomenclature Website Cytochrome P450 enzymes are responsible for 75-80 % of all phase I-dependent metabolism, resulting in more polar metabolites that can be further conjugated in Phase II metabolism, and for 65-70 % of the clearance of clinically used drugs (Bertz and Granneman 1997; Evans and Relling 1999). CYP enzymes are encoded by 57 CYP genes and divided into families, of which 1-3 (CYP1-3) are generally involved in the metabolism of exogenous substances including drugs, whereas members of other families mainly are involved in metabolism of endogenous compounds. Variation in CYP genes results in four different phenotypes classically defined as ultrarapid, extensive, intermediate and poor metabolizers. Characterization of the genetic polymorphism of CYP enzymes provides a basis for personalized medicine composing drug dose adjustment and selection of drug type (Ingelman-Sundberg 2004; Ingelman-Sundberg et al., 2007; Kirchheiner et al., 2004; Pirmohamed and Park 2001; Weinshilboum 2003) To unite and summarize efforts focusing on the characterization of CYP polymorphism, the Human Cytochrome P450 Allele (CYP-allele) Nomenclature Committee was established in 1999, and the efforts resulted in agreed CYP nomenclature guidelines and the launching of the CYP-http://www.cypalleles.ki.se/). The main purpose of the CYP-allele website is the management of new allele designations based on recognized nomenclature guidelines, facilitation of rapid publication, as well as providing a readily available summary of alleles and their associated effects (Ingelman-Sundberg and Oscarson 2002; Oscarson and Ingelman-Sundberg 2002; Sim and Ingelman-Sundberg 2006; Sim and Ingelman-Sundberg 2010).

  thoroughly sequenced and well characterized in terms of linkage of the functionally relevant SNP with other polymorphic sites. Functionally relevant in this aspect is regarded as a variation causing measurable consequences such as amino acid substitutions, translation terminations or splice defects. At a minimum, the open reading frame must have been sequenced. All sequence variations are numbered based on A in the translation initiation codon as the reference nucleotide (+1). Additional letter-designated sub-alleles of the same number (such as CYP2B6*4B) contain the same functional SNP but additional sequence variations not causing functional effects. A combination of functionally relevant variants are designated a new allele number due to the potential of combinatorial effects, unless one of the variant is deleterious and thus defines the allele name. As an example, CYP2C19*2 carries a SNP causing a splice defect of the transcribed RNA that is detrimental for enzyme function. This splice defect exists in different combinations with other SNPs causing amino acid substitutions and the combination alleles have thus received allele names CYP2C19*2A-D. The effect of CYP2C19 genotype on clopidogrel (Plavix  ) antiplatelet treatment of cardiovascular disease has attained much focus since CYP2C19 is responsible for bioactivation of the drug. A recent metaanalysis of 9 studies and almost 10,000 patients showed a significantly increased risk of adverse cardiovascular events in carriers of defective (mainly CYP2C19*2) alleles due to impaired bioactivation of clopidogrel, especially in patients having undergone percutaneous intervention,

  acetyltransferases (NATs) conjugate drugs and xenobiotics containing arylamine

  Nomenclature Page (http://www.pharmacogenomics.pha.ulaval.ca/sgc/ugt_alleles) contains UGT enzymes of subfamily UGT1A (9 enzyme web pages) and UGT2B (5 active web pages). The inclusion criteria are based on the CYP-allele nomenclature system, and thus alleles designated by the Webmaster contains an asterisk and a number where the *1 allele (e.g. UGT1A1*1) is considered the wild type allele. Similarly to CYP-alleles, the UGT Alleles Nomenclature Page focus on nucleotide changes that cause functional effects such as amino acid substitutions, splice defects and frameshifts, and thus alleles with additional variations not causing any effects receives a sub (letter) allele name. Every enzyme has a "Haplotype" page and a "SNP" page, where the former contains a list of all alleles and their changes whereas the latter contain a list of all SNPs together with their rs numbers and the reference sequence used. As an example, the UGT1A1 Haplotype web page contains 113 different alleles that are presented with their allelic names, nucleotide changes, protein effects, exon numbers affected, consequences (e.g. frameshift), phenotypes with respect to causation of Crigler-Najjar syndrome or Gilbert's syndrome, enzyme activity in vitro and in vivo, and the respective references. The rare Crigler-Najjar syndrome is caused by a complete inability to glucuronize bilirubin due to UGT1A1 mutations that consequently causes jaundice and potential brain injury, whereas reduced but not depleted UGT1A1-mediated glucuronidation of bilirubin lead to the less severe phenotype Gilbert's syndrome. UGT1A1 is also involved in the metabolism of the anti-cancer drug irinotecan, since the active metabolite SN-38 is glucuronidated and inactivated by UGT1A1.Excessive levels of SN-38 can cause neutropenia, the risk of which is affected by UGT1A1 genotype. The wild-type allele UGT1A1*1 carries a 6-repeat TATA box, (A(TA) 6 TAA) whereas UGT1A1*36 has 5, UGT1A1*28 has 7 and UGT1A1*37 has 8 repeats. An increased number of

  PharmaADME (http://www.pharmaadme.org/) is a database initiated by academic and industrial interests. The aim of this database is to compile lists of genes and genetic variation affecting Absorption, Distribution, Metabolism and Excretion (ADME) of drugs. The PharmaADME's main aim is to aid in selection of genotyping assays for product development and clinical trials. PharmaADME provides three gene lists, the ADME Gene List, the Core Marker Gene List and the Related Gene List. The ADME Gene Lists contain genes associated with drug metabolism, either sorted under the more important Core List of 32 genes or under the Extended ADME Gene List of 267 genes. The ADME Gene Lists contains the gene symbol, full gene name and the protein class, but no other information and no links to information on which the qualifications are based or which drugs the gene product is affecting. The Related Gene List contains 74 genes that are related to, but not involved in, drug metabolism such as drug targets and receptors. The Core Marker Gene List is composed of 184 genotypes in 32 genes, of which 11 are CYPs, 9 are transporters and 9 are transferases, which by PharmaADME have been selected as most important. This list comprises the gene symbol, the primary name (e.g. CYP2D6*5) and the NCBI dbSNP number.

Table 1 .

 1 Pharmacogenetic databases.

	Database	Organisation	Activities	Web address	Content
	PharmGKB	The	Curation of	http://www.pharmgkb.	Genotype and
		Pharmacogenomics	pharmacogenetic	org/	phenotype of ADME
		Knowledgebase	effects, creation of		genes and drug target
			gene and drug		genes
			summaries, data
			sharing consortia
	CYP-allele	The Human	Reviewing and	http://www.cypalleles.k	CYP nomenclature and
	database	Cytochrome P450	designation of CYP	i.se/	CYP allele
		(CYP) Allele	alleles		characteristics
		Nomenclature
		Website
	NAT-allele	The Human	Reviewing and	http://n-	NAT nomenclature
	database	Arylamine N-	designation of NAT	acetyltransferasenomen	and NAT allele
		Acetyltransferase	alleles	clature.louisville.edu/	characteristics
		(NAT) Gene
		Nomenclature
		Committee
	PMT database The	Compilation of	http://pharmacogenetic	Genetic variation in
		Pharmacogenetics of	sequence variation	s.ucsf.edu/	SLC and ABCC
		Membrane	in transporter genes		transporters
		Transporters (PMT)	(no alleles or
		database (part of	haplotypes)
		PharmGKB)
	TP-search	The Transporter	Summaries of	http://www.tp-	Genotype and
	database	database	transporters and	search.jp/	phenotype of SLC and
			their genetic		ABCC transporters
			variations (no alleles
			or haplotypes)
	UGT-allele	The UDP-	Reviewing and	http://www.pharmacog	UGT nomenclature
	databse	glucuronosyltransfer	designation of UGT	enomics.pha.ulaval.ca/s	and UGT allele
		ase (UGT) Allele	alleles	gc/ugt_alleles	characteristics
		Nomenclature Page
	PharmaADME Pharmacogenetics of	Compilation of	http://www.pharmaad	Polymorphic ADME
		Absorption,	ADME gene lists	me.org/	genes ranked in order
		Distribution,			of significance for
		Metabolism and			causing variability in
		Excretion genes			drug response
					Formatted: English (U.S.)

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  (MAOA), pregnane X receptor (PXR) and POR are also included in this list. Most genes are extensively presented on their own web page, containing information such as main tissue expression sites, substrates, gene structure, and genetic variation. The genetic variants are reported by their genomic, transcript and coding position, together with amino acid effects, array availability, PubMed and dbSNP links, and the frequency observed in different populations. Also, a secondary structure transmembrane prediction shows the position of amino acid substitutions, insertions or deletions within the transporter protein. Additionally, the PMT database provides a search tool to access gene expression data with respect to a single gene in multiple tissues (Gene Plot), selected genes in selected tissues (Mixed Plot) and multiple genes in a single tissue (Tissue Plot).

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  The Transporter Name search includes the choice of human, mouse and/or rat species, and substrate, inhibitor and/or inducer substances. The Transporter Name search outcome includes parameters associated with the requested transporter, i.e. substance name and chemical structure, interaction type, K m and K i values, experimental setup used for producing the data and references to publications. Similar searches can be done with the Compound Name, where a list of transporters interacting with the substance is provided. The Drug-Drug Interaction search involves in vivo data, and displays drug-drug interactions involving the searched compound, together with its effects on parameters such as clearance, C max and area under plasma concentration curve (AUC). Also, the interaction site where the effects are believed to occur is presented. The Tissue Distribution search provides schematic figures of the transporters present in intestine, kidney or liver. In addition, a tissue distribution table lists the tissue and localization of the transporters, together with the experimental method used and the corresponding

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references. The Genetic Polymorphism search of functionality yields in vivo information on the respective transporter SNPs (but not alleles or haplotypes) with respect to nucleotide changes, protein changes, drug involved, type of drug administration, number and ethnicity of the study sample, in vivo parameters (such as AUC or plasma concentration), and the relationship between the different genotypes. A similar Genetic search with respect to frequency yields the distribution of the polymorphisms in different populations. A reference sequence with respect to the nucleotide change is however not provided and the TP-search database has not been updated since 2007.

Table 1 .

 1 Pharmacogenetic databases.

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Acknowledgements

The research at the laboratories of the authors is supported by grants from The Swedish Research Council, The Swedish Brain Foundation, The Swedish cancer Fund and from NIH GM61374.

Acknowledgements

The research at the laboratories of the authors is supported by grants from The Swedish Research Council, The Swedish Brain Foundation, The Swedish cancer Fund and from NIH GM61374.


Tomasz Hetmański

Marcin Bocheński
email: m.bochenski@wnb.uz.zgora.pl

Piotr Tryjanowski
email: piotr.tryjanowski@gmail.com

Piotr Skórka

C Gortázar

The effect of habitat and number of inhabitants on the population sizes of feral pigeons around towns in northern Poland

Keywords: Columba livia, Distribution, Colonization, Foraging strategy, Urban ecology

Most studies on factors influencing density of the feral pigeons Columba livia var. domestica were carried out in large cities and agglomerations. However, also in small towns, pigeons are important epidemiological and sanitary problem. In our studies, feral pigeons were censused in 33 towns located in the Pomeranian Province (northern Poland) during 2006-2008. These birds occurred in 19 (57.6%) towns. The number of pigeons was positively correlated with the area of the town, and it was significantly higher in towns localized in agricultural landscape than in towns surrounded by forests. We also found a significant effect of interactions between type of a landscape surrounding a town and residual number of inhabitants on the abundance of pigeons. In the largest towns of the Pomeranian Province, feral pigeons were concentrated mainly in central quarters. In smaller towns, they were noted in central parts or in areas with blocks of flats and even the suburbs. The obtained results suggest that food conditions in small and middle towns may be not sufficient for colonization by pigeons.

Introduction

Feral pigeons are a great challenge for municipal authorities because they must take care of the health of the people and also of keeping the town clean. These birds, which are abundant in large towns, can be vectors of many diseases of humans and domestic animals. They often naturally infected people of viruses, bacteria, fungi and pathogenic protozoans [START_REF] Bassi | The role of pigeon excrement in stone biodeterioration[END_REF][START_REF] Haag-Wackernagel | Health hazards posed by feral pigeons[END_REF][START_REF] Vlahović | Campylobacter, Salmonella and Chlamydia in free-living birds of Croatia[END_REF]). Moreover, in large towns, they are a source of ornithosis in human by infection of Chlamydophila psittaci [START_REF] Magnino | Chlamydial infections in feral pigeons in Europe: review of data and focus on public health implications[END_REF]. The major problem is the harmful effect of pigeon faeces floating in the air as dust that can be breathed in [START_REF] Haag-Wackernagel | Health hazards posed by feral pigeons[END_REF]. Thus, it is obvious that the places where pigeons occur in high densities are dangerous to the health of people. To prevent local concentration of pigeons, pigeon-deterring devices can be used, such as nets or spikes put on buildings [START_REF] Haag-Wackernagel | Behavioural responses of the feral pigeon (Columbidae) to deterring systems[END_REF].

Failure of control programs to capture pigeons is caused by immigration of individuals from nearby populations [START_REF] Sol | Urban pigeon populations: stability, home range, and the effect of removing individuals[END_REF]. According to [START_REF] Haag-Wackernagel | Street pigeons in Basel[END_REF], the effective long-term elimination procedure is the limitation of food supplied by "pigeon lovers". For a successful culling of surplus pigeons, it is necessary to understand all factors promoting their reproduction. One of the most important factors is food resources. [START_REF] Barbieri | Indagine sulla presenza die colombi (Columba livia forma domestica) nel centro storico di Pavia e nell'Oltrepò[END_REF] found that the population size of feral pigeons depends on the size of a town, but [START_REF] Jokimäki | Distribution and habitat selection of wintering birds in urban environments[END_REF] showed that it also depends on the density of human population. It is well evidenced that urban areas and people living there provide abundant food resources for birds [START_REF] Jokimäki | Distribution and habitat selection of wintering birds in urban environments[END_REF][START_REF] Jokimäki | Spatial similarity of urban bird communities: a multiscale approach[END_REF][START_REF] Marzluff | Avian ecology and conservation in urbanizing world[END_REF][START_REF] Fuller | Garden bird feeding predicts the structure of urban avian assemblages[END_REF][START_REF] Robb | Winter feeding of birds increases productivity in the subsequent breeding season[END_REF]. However, both size of a town and density of human population are often strongly correlated, making it difficult to separate both effects. According to [START_REF] Speirs | Populations of birds in urban habitats, Ontario County[END_REF], the abundance of pigeons does not necessarily depend on the size of human population, and it may be also influenced by the history of the town. Frequent foraging strategy of feral pigeon is to look for food within the town, but urban pigeons can fly longer distances and forage in farmland [START_REF] Janiga | Seasonal aspects of intensity and course of daily translocations of pigeons (Columba livia f. domestica) for food from Bratislava to its surroundings[END_REF]Rose et al. 2006a). The same foraging strategy is used by rock pigeons Columba livia, which are progenitors of feral pigeons [START_REF] Baldaccini | Foraging flights of wild rock doves (Columba L. livia): a spatio-temporal analysis[END_REF]. In some big cities, pigeons foraging outside of the city areas may constitute a small fraction of the total population, as it was found in Basel where this foraging strategy was demonstrated for ca. 6% of population (Rose et al. 2006a), but in Milan, it was just up to 46% [START_REF] Sacchi | Effects of building features on density and flock distribution on feral pigeons Columba livia var. domestica in an urban environment[END_REF]. Therefore, foraging in farmland can largely influence population size in towns. If the population size of the feral pigeon depends on availability of the farmland area in the vicinity of the town, then it should be independent of human population size in the town. Otherwise, if the landscape in the vicinity of towns is dominated by forests or wetlands, then population size of the feral pigeons should be strongly dependent on size of human population in towns, as birds may forage only on human-related food resources. In other words, we expect significant interaction between landscape type surrounding the town and number of human inhabitants, i.e. in forested/water landscape, we expect stronger relationship between number of human inhabitants and number of pigeons than in towns surrounded by farmland.

The main aim of this paper was to determine the influence of different parameters such as size of a town, number of human inhabitants and landscape type surrounding towns on numbers of feral pigeons in towns of Pomerania Province (northern Poland). We examined the following predictions: (1) population size of the feral pigeons is positively correlated with the human population size in towns, but (2) population size of the feral pigeons is much more linked with human population size in towns surrounded by forests and water than in towns surrounded by farmland. We also expected (3) that number of pigeons is positively related to the town area.

Materials and methods

Study area

The distribution and abundance of feral pigeons were examined in 33 towns of northern Poland in the autumn of 2006 and 2008. The study area is presented in Fig. 1. The Pomeranian Province is situated along the southwest seaside on the Gulf of Gdańsk (southern Baltic Sea), and it is crossed by the lower Vistula River catchment area. The Pomeranian Province is highly diversified in terms of the relief, soil quality and forest cover. The area to the left of the Vistula River is part of the East Pomeranian Lakeland and, to a smaller extent, of the West Pomeranian Lakeland [START_REF] Kondracki | Geografia regionalna Polski[END_REF]). The region is characterised by the glacial landscape with numerous moraines and lakes. Forests cover a significant part of the land, even up to 75%. Soils are dominated by light podzolic soils and by higher quality brown soils. Agricultural areas are small and punctuated with wasteland, hay meadows and pastures. In this part of the province, as many as 25 towns with human population between 3,800 and 460,000 inhabitants were studied.

Remaining towns were located east of the Vistula River in the area of Żuławy. The region is characterised by a depression with fertile soils supporting farmlands. Żuławy is located in the delta of the Vistula River at the mouth of the Baltic Sea. This area depression is small and constitutes about 2,460 km 2 . The Żuławy was formed from alluvial deposits accumulated during the recent 5,000 years, and forests cover a very small area ranging from 0% to 15%. Fertile soils of Żuławy supply the production of cereals and rape [START_REF] Kondracki | Geografia regionalna Polski[END_REF]. In this part of the Pomeranian Province, there are many facilities for production, storing and processing of cereals, rape and root crops. Moreover, establishments involved in production of animal fodder are located in the region, contributing even further to its agricultural importance. In Żuławy and adjacent areas east of the Vistula River, eight towns were under study. Their population ranged from 3,900 in Nowy Staw to 40,000 inhabitants in Malbork.

In our research, we divided towns into two groups according to the dominating landscape type in the vicinity of towns. The groups were (1) towns localized among farmland and (2) towns localized in forested and water landscape (when cover by forests and water bodies was over 70%).

Pigeons counting

Counts of pigeons were carried out during autumn from the beginning of October through December. This is the best period for the inventory of feral pigeons, as only few of them breed at that time [START_REF] Hetmański | Timing of breeding in the feral pigeon Columba livia f. domestica in Słupsk (NW Poland)[END_REF]. During these months, birds are outside the lofts, as they have to refill fat reserves (Rose et al. 2006a). Another reason why pigeons spend more time outside the loft during autumn is the limited access to the food resources in conjunction with the shortest foraging time [START_REF] Hetmański | Timing of breeding in the feral pigeon Columba livia f. domestica in Słupsk (NW Poland)[END_REF]); thus, they gather around feeding grounds (Murton et al. 1972a, b). Moreover, Murton et al. (1972a) as well as [START_REF] Hetmański | Wyniki badań ankietowych struktury ludności dokarmiającej gołębie miejskie Columba livia w miastach Pomorza (Results of survey on structure of people feeding feral pigeons Columba livia in the towns of Pomerania)[END_REF] showed that the tourists increase the food availability for pigeons in spring and summer but not during autumn.

Counts of pigeons were conducted from the morning until noon. We noticed that during the morning, the pigeons gathered at the feeding grounds and waited for food brought by humans. [START_REF] Giunchi | Distance sampling as an effective method for monitoring feral pigeon (Columba livia f. domestica) urban populations[END_REF] also conducted bird counts during the morning hours, and they have found that during this time period, most pigeons remained within the city.

We used a simple method of estimating the abundance of pigeons, which consisted primarily of counting birds attracted to the food [START_REF] Sacchi | Effects of building features on density and flock distribution on feral pigeons Columba livia var. domestica in an urban environment[END_REF] and counting birds departing to search for food over surrounding agricultural areas. Counters provided food at feeding sites where pigeons gathered. They used fine-grained cereals to extend the foraging time of pigeons arriving from the closest surroundings. In case the number of birds stabilized and no new birds arrived, the pigeons were counted three times. Several observers counted pigeons simultaneously in different places of the selected quarter of the town. They used bicycles to count pigeons in specified streets, courtyards, parks and squares. The census sites were randomly chosen, and survey effort was proportionally higher in larger towns. We surveyed 25% of the town's area. Birds moving to farmland were counted from dawn, before the birds foraging in the town were counted.

We did not apply the correction factor which some researchers used to incorporate in order to estimate the true population size of feral pigeons [START_REF] Senar | Censo de Palomas Columba livia var. de la ciudad de Barcelona: aplicación del muestreo estratificado con factor de corrección[END_REF][START_REF] Senar | Bird census techniques for the urban habitat: a review[END_REF]. Their correction factor was determined on the basis of the number of undetected marked birds in the surveyed area. They recommended multiplying the results of every quadrate count by 3.5. [START_REF] Giunchi | Distance sampling as an effective method for monitoring feral pigeon (Columba livia f. domestica) urban populations[END_REF] demonstrated, however, that detectability of feral pigeons differed in January and November; therefore, using a consistent correction factor of 3.5 is not an accurate solution for every time period.

Feral pigeons could be confounded with domestic pigeons, but longer observations and information from local inhabitants made it possible to determine the origin of birds and to notice the difference between domestic and feral pigeons.

We tested efficiency of used method, and to check how repeatable and comparable the results were, we used repeatability analysis. In 54 randomly selected parts of towns in the study area, pigeons were counted twice (with a gap of 10-14 days between counts). Repeatability of counts between sites was highly significant (F 1,53 =161.847, R 2 = 0.975, P<0.0001).

Statistical analysis

The first analytical aim of the research was to describe the spatial aggregation in the abundance of the species by means of Moran's I correlograms. A correlogram is a graph in which spatial autocorrelation values of a given parameter are plotted on the ordinate against distance classes among sampling points [START_REF] Legendre | Spatial autocorrelation: trouble or new paradigm?[END_REF][START_REF] Legendre | Numerical ecology[END_REF]. The spatial autocorrelation value at a given distance class indicates how predictable (positively or negatively) is the abundance of birds in a given point of the sampling framework. This probability is expressed as a function of the abundance of birds in a sampling point (town) located at the distance to x. Autocorrelation Moran's index typically varies between -1 and +1 with no significant values close to zero. Taking into account our sampling design, we considered eight distance classes chosen so that the number of towns' pairs was equal in each interval. We also manipulated with the distance classes and intervals in various ways, changing the distance from 10 to 40 km as well as altering the number of intervals, but this had no impact on the final results. To test the significance of the autocorrelation, we applied P values based on the proportion of 500 Monte Carlo simulations performed in SAM statistical software (Rangel et al. 2006).

As we did not find evidence for spatial autocorrelation (see "Results" section), we used ordinary generalized linear model [START_REF] Crawley | GLIM for ecologists[END_REF] with Poisson error distribution and log-link functions for testing which factors significantly influenced number of pigeons living in the studied areas. This method is recommended for counts data [START_REF] Nally | Regression and model-building in conservation biology, biogeography and ecology: the distinction betweenand reconciliation of-'predictive' and 'explanatory' models[END_REF]. Function parameters were estimated by Firth adjusted maximum likelihood method [START_REF] Firth | Bias reduction of maximum likelihood estimates[END_REF][START_REF] Jowaheer | Estimating regression effects in com Poisson generalized model[END_REF] and corrected for over-dispersion. The explanatory variables were as follows: (1) landscape cover around the town (coded as binary variable: 0, forest and water habitats; 1, farmland), (2) town area (square kilometre) and (3) number of inhabitants (log-transformed). Town area and number of inhabitants were highly positively correlated (R adj 2 =0.62, P<0.001) and caused a problem of multicollinearity. To remove this effect, we performed simple regression between number of inhabitants and town area. Subsequently, we used the residual number of town inhabitants not explained by the town area in the later analyzes. Additionally, we introduced an interaction term between categorical variable (landscape type) and continuous explanatory variables (town area and residual number of inhabitants). The fit of the model was assessed by the corrected R 2 value [START_REF] Mittlbock | Pseudo R-squared measures for generalized linear models[END_REF]) and the corrected Akaike information criterion AICc [START_REF] Hurvich | Regression and time series model selection in small samples[END_REF]. We used JMP 8 statistical software during GLM analyses. As the distribution of number of pigeons in towns was highly skewed, the means given in text are corrected by logarithmical transformation.

Results

Feral pigeons were observed in 19 out of 33 (57.6%) towns under study. More than 1,000 individuals were noted only in Gdańsk, Gdynia and Słupsk. Typically, feral pigeons were not present in smaller towns (less than 1,000 inhabitants), but they were also absent in Rumia with 40,000 inhabitants and in Starogard Gdański with 50,000 inhabitants; only 25 individuals were noted.

In the largest towns of the Pomeranian Province, feral pigeons were concentrated mainly in central quarters. In smaller towns, they were noted in central parts or in areas with blocks of flats and, surprisingly, in the suburbs. For example, in Nowy Staw, pigeons concentrated in the old market square. In Tczew and Kwidzyn, flocks were more abundant in areas with blocks of flats than in the centre. In Władysławowo, the only colony inhabited a tower at the edge of the town.

We did not find any evidence for spatial autocorrelation in abundance of the species in studied towns (Fig. 2). Moran's I coefficients were always close to zero at all distance intervals (Fig. 2).

The statistical analysis indicated that the best-suited model contained all the effects (AICs = 3,893.3) and explained 86% of variance. All models with reduced number of explanatory variables had higher AICc. The number of pigeons was positively correlated with the area of the town (Table 1 and Fig. 3a), and it was significantly higher in towns localized in agricultural landscape (mean ± SE, 338.7±1.3) than in towns surrounded by forests (mean ± SE, 11.2±1.9; mostly because in a few latter towns, pigeons were absent). We found significant effect of interactions between type of a landscape surrounding a town and residual number of inhabitants on the abundance of pigeons (Table 1). In towns surrounded by forests and waters, the number of inhabitants was positively correlated with the number of pigeons, whereas in towns surrounded by the agricultural land, the relationship was absent (significant difference in the regression slopes, Fig. 3b).

Discussion

After World War II, the population of feral pigeons increased in towns where they were previously observed.

In the same time, they colonised new towns in Europe [START_REF] Johnston | Feral pigeon[END_REF]. Some studies conducted in towns of northern Poland showed that three towns were colonised in the 1970s: Koszalin [START_REF] Górski | Quantitative investigations on the breeding avifauna of Poznań and Koszalin in 1972[END_REF], Słupsk [START_REF] Górski | The breeding birds of Słupsk and its suburban areas[END_REF] and Olsztyn (Okulewicz 1971). The densities of birds recorded at that time were very low, approximately on the level of one pair/10 ha. Currently, pigeon populations in these towns comprise more than 1,000 individuals (personal observation). In some larger towns of Europe, pigeon populations began to stabilize already in the 1980s [START_REF] Konstantinov | Recent changes in the avifauna of cities in European Russia and Eastern Polandresults of a questionnaire[END_REF]. The present study in 33 towns of the Pomeranian Province shows that the colonisation of towns by pigeons advances and constitutes a part of a long-term process. The lack of spatial autocorrelation indicates that each town with pigeons may be considered as an independent local population. Since pigeons are rather reluctant to leave their natal area [START_REF] Hetmański | Dispersion asymmetry within a feral pigeon Columba livia population[END_REF], it is possible that the local factors (e.g. availability of refuse or landscape around to the natal town) maybe a key factor affecting local population dynamics [START_REF] Hetmański | Breeding parameters and recruitment in feral pigeons Columba livia f. domestica[END_REF].

Our results suggest that number of inhabitants and type of habitats surrounding towns (i.e. food resources for pigeons) are important factors limiting the local population size of pigeons in towns. Towns surrounded by farmland had significantly higher numbers of feral pigeons than towns surrounded mostly by forests and lakes. This implies that food resources in small and medium towns surrounded by forests or lakes are insufficient to be colonised by pigeons. For instance, in Starogard Gdański (localized in an arboreal landscape) with 50,000 inhabitants, local population of pigeons comprised only 25 individuals. In Lębork (35,000 inhabitants), pigeon population was established as late as in 2003 as a result of the introduction of pigeons from Słupsk by pigeon-fanciers from Lębork. The present population in Lębork consists of over 110 birds, as compared with 25 individuals in 2003. The increase in this population was possible due to abundant supplemental feeding in the centre of the town. However, the above explanation should be treated with caution because we did not quantify directly food resources within towns. It could be extremely difficult as the food resources are patchily distributed and often changes location (depending on people leaving food or refuse), and it was impossible to collect this information in this study. Further study should quantify such resources and estimate their role in shaping local pigeons densities within towns.

The study conducted in northern Poland shows that feral pigeons can use food resources not only in urbanised areas but also in their surroundings. Some birds chose to forage in the streets and yards [START_REF] Hetmański | Plumage polymorphism and breeding parameters of various feral pigeon (Columba livia Gm.) morphs in urban area (Gdańsk, N Poland)[END_REF][START_REF] Hetmański | Wyniki badań ankietowych struktury ludności dokarmiającej gołębie miejskie Columba livia w miastach Pomorza (Results of survey on structure of people feeding feral pigeons Columba livia in the towns of Pomerania)[END_REF], whereas others rely on the recourses outside towns [START_REF] Janiga | Seasonal aspects of intensity and course of daily translocations of pigeons (Columba livia f. domestica) for food from Bratislava to its surroundings[END_REF]. Rose et al. (2006a, b) used the GPS method that allowed them to record and follow commuting flights to the arable fields. They found that pigeons used different individual foraging strategies even within the same population. Females commuted further than males, and the foraging activity depended on the breeding state and season. Birds are flexible enough to adapt to different urban environments. Consequently, when attempting to manage pigeon populations in towns, the habitats surrounding these towns should be considered, as shown for corvids (Jerzak et al. 2005). The corvids are also the best reference points showing importance of agricultural land around towns for foraging.

Another explanation for strong relationship between number of pigeons and number of humans in towns surrounded by forest as well as lower number of pigeons in these towns is that pigeons may be reluctant to forage in forested landscape. Forests are inhabited by many predators, as e.g. goshawk Accipiter gentilis that frequently prey upon different species of pigeons. It does not necessary mean that predation rate is high in towns localized in forested landscape, but even the presence of predators may change behaviour of the potential prey (non-lethal effect of predators; [START_REF] Lima | Predators and the breeding bird: behavioral and reproductive flexibility under the risk of predation[END_REF]. What is more, forests may constitute a behavioural barrier for pigeons by increasing the cost of finding food as was shown for other species [START_REF] Skórka | The use of optimal foraging and metapopulation theories to predict animal movement and foraging decisions in mobile animals in heterogeneous landscapes[END_REF].

In our study, we found that abundance of pigeons was positively related to town's area and independent from the surrounding landscape type. The area-population abundance relationship is a well-documented ecological phenomenon in many taxa [START_REF] Prugh | Effect of habitat area and isolation on fragmented animal populations[END_REF]). This has important practical consequence, indicating that the greatest number of humanpigeons conflicts arises in larger towns. Simultaneously, in small towns, controlling number of pigeons seems to be much easier.

Obviously, in our study, we did not include other factors potentially affecting pigeon abundance in towns. One of such variable may be the age and building structure of a town. [START_REF] Speirs | Populations of birds in urban habitats, Ontario County[END_REF] found that pigeon populations can be larger in smaller but older towns than in larger and younger towns. The present results partially confirm this observation as no pigeons were found in towns without a distinct centre with old buildings, such as Rumia and Reda, where residential architecture predominates. Buildings of this kind with allotments gardens are not readily colonised by pigeons [START_REF] Luniak | Birds of allotment gardens in Warsaw[END_REF]. Instead, pigeons showed preference for central parts of towns mainly with old buildings mostly those built before the war [START_REF] Sacchi | Effects of building features on density and flock distribution on feral pigeons Columba livia var. domestica in an urban environment[END_REF]. In large towns in our study area, such as Słupsk and Gdynia, pigeons concentrated mainly in their centres where old buildings can be found. However, in small towns, this was not the rule. For example, in Tczew, more birds were observed in the area with blocks of flats than in the old town. A similar situation was noted in Olsztyn, where the highest densities of pigeons were found in the quarter with blocks of flats, rather than in the centre of the town [START_REF] Nowakowski | Birds of Olsztyn. ElSet, Olsztyn Okulewicz J (1971) Birds of Olsztyn and its victinity[END_REF]. In Starogard Gdański, on the contrary, pigeons occurred in the centre of the town, and they were absent from blocks of flats. Thus, it seems that there is no general pattern in occupation of various parts of towns by pigeons.

Availability of nesting sites is the other factor that could affect population size of the feral pigeons but was not included in this study. However, we think that nesting sites cannot be a limiting factor for this species. Feral pigeon is a species of remarkable nest site choice plasticity. It breeds in cavities, bridges, on balconies, windowsills and many others places. Even in areas of high pigeon density, we often found many potential breeding sites for this species, but not occupied (unpublished observations).

Moreover, it must be admitted that our model explained considerable part of the variation in the dataset, which indicates that we included in our study all key factors affecting local population sizes of the feral pigeons in northern Poland.

Management recommendations

Our study showed that both town area and number of human inhabitants positively influence population sizes of the feral pigeons. [START_REF] Haag-Wackernagel | Street pigeons in Basel[END_REF] stated that population size of pigeons foraging within the city limits can be quite easily controlled by reducing food resources delivered by humans. We think it is the case mostly in towns surrounded by forests and wetlands. In these towns, reduction of the abundance of food resources may be the most effective way to control pigeon abundance because the birds cannot find alternative food sources.

We think that future studies should focus on methods of effective removal of pigeons from the parts of towns where they cause the largest problems. Moreover, more studies on habitat selection and (micro)habitat use within towns by the species are crucial. Rangel TFLVB, Diniz-Filho JAF, Bini LM (2006) Towards an integrated computational tool for spatial analysis in macroecology and biogeography. Global Ecol Biogeogr 15:321-327

Fig. 1

 1 Fig. 1 Study area

Fig. 2

 2 Fig. 2 Spatial correlogram of abundance of pigeons in towns. The dashed line indicates the expected values under the null hypothesis of absence of autocorrelation

Fig. 3

 3 Fig. 3 Effect of a town area and b number of inhabitants on number of feral pigeon Columba livia var. domestica in towns of northern Poland surrounded by forested (white circles and dotted line) and agricultural landscape (black circles and solid line). Logarithmic function is fitted

Table 1

 1 Results of GLM model with Poisson error and log-link function

	Effect	df	χ 2	P
	Town area	1	18.730	<0.001
	Number of inhabitants	1	2.168	0.141
	Landscape type	1	13.338	<0.001
	Landscape type × town area	1	2.493	0.114
	Landscape type × number of inhabitants	1	5.091	0.024

Eur J Wildl Res (2011) 57:421-428

Eur J Wildl Res (2011) 57:421-428

Acknowledgements The final analysis of the data was supported by a small grant project from the City of Poznań (RoM. III/3420-56/10). We thank Tim H. Sparks for linguistic corrections.

Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.