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10 Pharmacogenetics 2003, Vol 13 No 1Table 2.(continued)Gene nameand acronymLow density lipoprotein receptorLDLRLipase hepaticLIPCLipoprotein lipaseLPLOtherCalcium sensing receptorCASREndothelin 2ET2Glucocorticoid receptorGRLLecithin-cholesterol acyltransferaseLCATNeuropeptide YNPYOsteoprotegerinOPGParathyroid hormonePTHPeroxisome proliferator activatedreceptor ÆPPARAPeroxisome proliferator activatedreceptor gammaPPARGSuperoxide dismutaseSODVitamin D receptorVDRAccessionnumberaSNP nameb,cdbSNP IDdAmino 3895––AF050163–––CETP G338ACETP G571ACETP A311G(CETP G2132T)(CETP T1511G)LDLR C16730TLDLR T20001CLIPC G89ALIPC A110G(LIPC C873T)(LIPC A1075C)(LIPC C1221T)LPL C9040GLPL G7315CLPL A7344GLPL R C3031GCASR G2956T(CASR G2968A)(ET2 T461C)(ET2 G577A)(GRL (LCAT G2233A)NAArg/HisK01911(NPY 1(OPG T950C)(OPG C1217T)(OPG G1181C)(PTH T164C)(PTH T179C)PPARA /ArgSer/ProVal/AlaL40904–PPARG G1043APPARG (SOD C386T)(SOD C2734T)(SOD C5775G)(VDR raAccession number of GenBank entry. b SNP name composed of acronym, nucleotide variation and nucleotide position.Alternative SNP name in parentheses. c SNPs marked with parentheses were excluded from genotyping panel. d dbSNP IDnumber; NA, not available.100 l of PCR reaction buffer supplied with the enzyme. The multiplex PCR reactions had been optimized with respect to MgCl2 , enzyme and primerconcentrations. The success of the PCR was evaluatedon 8% polyacrylamide gels.Preparation of microarraysThe minisequencing primers were covalently immobilized on CodeLinkTM Activated slides (previously 3DLink slides, Motorola, Northbrook, Illinois, USA) bymediation of a 59-NH2 group [17]. The NH2 -modifiedprimers were applied to the slides at a 25 mol/lconcentration in 400 mmol/l sodium bicarbonate buffer,pH 9.0, by contact printing using a ProSys 5510Aspotter (Cartesian Technologies Inc., Irvine, California,USA) equipped with four Stealth Micro Spotting Pins(SMP3; TeleChem International Inc., Sunnyvale, Cali-fornia, USA) resulting in spots with a diameter of160 m. The oligonucleotides were printed in duplicatespots with a centre-to-centre distance of 200 m in an‘array of arrays’ format with the same spacing as thewells of a 384-well microtitre plate [14] with fourcolumns and 14 rows on each slide. A fluorescentlylabelled oligonucleotide was included as control for theimmobilization process and for scanning of the arrays.Microarray minisequencing reactionsThe multiplex PCR products from each sample werecombined, precipitated with ethanol and the DNApellet was resuspended in 46 l of water. After denaturation of the DNA at 95 8C for 2 min, 14 l of abuffer containing 4.5 mmol/l NaCl, 50 mmol/l TrisHCl, pH 8.0, 5 mmol/l Na2 -EDTA was added, and15 l of the DNA solution was used in four parallelCopyright Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

Minisequencing for pharmacogenetic profiling Liljedahl et al. 11reaction wells on the slides. A custom made siliconrubber grid placed on top of each microscope slide wasused to form 56 separate reaction chambers [14]. Aheated aluminium block holding three microscopeslides was used for the reactions. After incubation for40 min at 37 8C, the slides were briefly rinsed in asolution containing 5 mmol/l Tris-HCl pH 8.0, 0.5mmol/l Na2 -EDTA, 100 mmol/l NaCl, 0.1% Triton X100 followed by rinsing with water. The minisequencing reaction mixtures contained one of the fourTAMRA-labelled ddNTPs (ddATP NEL474, ddCTPNEL473, ddGTP NEL475 or ddUTP NEL472 PerkinElmer Life Sciences, Boston, Massachusetts, USA) andthe other three ddNTPs unlabelled at a concentrationof 0.5 mol, 0.75 U of DynaSeq DNA polymerase (giftfrom Finnzymes OY, Helsinki, Finland) or ThermoSequenase DNA Polymerase (Amersham Biosciences,Uppsala, Sweden) in 26 mmol/l Tris-HCl pH 9.5,6.5 mmol/l MgCl2 , 0.1% Triton X-100. Fifteen l ofreaction mixture was added to the reaction wells on theslides preheated to 55 8C, followed by incubation for15 min. The slides were then briefly rinsed in waterfollowed by washing for 2 min with 50 mmol/l NaOH,and twice for 5 min with 3 mmol/l sodium citrate,30 mmol/l NaCl, 0.1% SDS, pH 7.0 at 65 8C and finallybriefly rinsed with water. The slides were allowed todry at room temperature before fluorescence scanning.Fluorescence scanning and data interpretationThe fluorescence signals were detected using an arrayscanner (ScanArray 5000, Perkin-Elmer Life Sciences,Boston, Massachusetts, USA). The fluorescence intensity values were extracted with the QuantArray software supplied with the scanner. Using an algorithm,the mean values of the signals from the duplicate spotswere corrected for the average background measuredbeneath each ‘subarray’. The ratio between the fluorescence signal from one of the alleles and the sum of thefluorescence signals from both possible alleles at eachSNP site was calculated to assign the genotypes.Minisequencing in microtitre platesSolid-phase minisequencing in microtitre plates with3H-labelled dNTPs was used to determine the allelefrequencies of the SNPs in pooled DNA samplesessentially as described previously [12,18], with theexception that a biotin residue for immobilization ofthe PCR products in the streptavidin-coated microtitrewell was incorporated in a secondary PCR reaction witha biotinylated primer complementary to the universalsequence on the specific PCR primer. The ratio between the 3 H-dNTPs incorporated was normalizedagainst the ratio in a heterozygous sample. If noheterozygous reference sample was available, the specific activities of the tritium labelled nucleotides (3 HdATP TRK633 69 Ci/mmol, 3 H-dCTP TRK625 46 Ci/mmol, 3 H-dGTP TRK627 41 Ci/mmol, 3 H-dTTPTRK576 124 Ci/mmol, Amersham Biosciences) wereused for normalization. Solid-phase minisequencingalso served as reference method [12].Statistical analysisFor the SNPs with a frequency over 5% for the minorallele, Hardy–Weinberg equilibrium was assessed bycomparison of the observed and expected genotypefrequencies using the chi-square test with one degreeof freedom. The Genepop web program (http://wbiomed.curtin.edu.au/genepop) [19] was used to calculatepairwise linkage disequilibrium (LD). Haplotypes weredesignated using the expectation maximization algorithm in the Haplo program (http://info.med.yale.edu/genetics/kkidd) [20]. Subsets of SNPs required fordistinguishing between haplotypes [21] were identifiedby visual inspection of the haplotypes.The relationship between genotypes and change inblood pressure was first analysed using factorial oneway ANOVA (Statview 5, SAS Institute Inc., Cary,North Carolina, USA) to evaluate which of the genotypes of the 74 SNPs were related to the changes inSBP or DBP in the irbesartan and atenolol groupseparately. Four univariate analyses were performed foreach of the individual SNPs. SNPs demonstrating aP , 0.10 were entered as independent variables inforward stepwise multiple regression models with oneof the four possible combinations of SBP/DBP andirbesartan/atenolol as a dependent variable. In thesemodels, P , 0.01 was set for retention of the independent variables in the models in order to reduce theeffect of multiple testing by reducing the P-valueaccepted. Two-tailed significance levels were used. Noformal correction for multiple testing was applied.ResultsThe candidate genes were chosen based on their function in the renin–angiotensin–aldosterone, adrenergicand endothelial systems, and the lipid metabolism,respectively. A panel of 98 genetic variants in thesegenes was assembled for prediction of individual responses to treatment with antihypertensive drugs(Table 2). This panel comprised a small number ofSNPs that had been shown or suggested to be involvedin blood pressure regulation in the published literature.Most of the SNPs in the panel were located in codingor regulatory regions of the candidate genes, but also afew SNPs in non-coding regions close to the genes(, 1.5 kb) were included. When possible, SNPs withpublished allele frequencies from 10% to 90% wereselected. The allele frequencies in the Swedish population of the initially selected SNPs were determinedby quantitative minisequencing analysis [12,18] of apooled sample containing DNA from 150 healthyindividuals of Swedish origin. Based on this analysis, 24SNPs were excluded from the panel for SNP profilingCopyright Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

12 Pharmacogenetics 2003, Vol 13 No 1because they had a minor allele frequency of less than1% in the Swedish population (16 SNPs) or due toPCR failure (8 SNPs). Over one-half of the SNPs,especially those with even allele distribution, hadsimilar frequencies in Sweden as in the populationwhere they had been identified (Table 3). Seventy-fourSNPs with allele frequencies ranging from 1% to 50%for their minor allele were included in the panel togenotype the DNA samples from hypertensive patients.Figure 1 presents a fluorescence scan image of amicroarray where the SNPs included in the panel havebeen genotyped by minisequencing in samples from 12of the patients. After fluorescence scanning of thearrays, the results are interpreted with the aid of analgorithm that extracts the signals from the microarray,and assigns the genotypes according to the ratio of thefluorescence signal from one of the alleles to the sumof the fluorescence signals from both alleles at eachSNP site. As shown in Fig. 2, the signal ratios for eachSNP fall within one of three distinct, non-overlappingclusters that define the three possible genotypes unequivocally. Although the limits for the clusters ofratios vary depending on the sequence context of theSNPs, the ratios defining the genotype of the SNPsdiffer from each other on average by 0.32.Using the microarray-based system, the panel of SNPswas genotyped in DNA samples from the 97 hypertensive patients participating in the study. As a consequence of the stringent criteria applied for definingthe genotypes, approximately 20% of the genotypeswere assigned after repeating the microarray-basedanalysis with a primer of the opposite polarity, or byverification of individual genotypes in the microtitreplate format of the minisequencing method. As a resultof this strategy, a genotype was assigned for each SNPin every patient, and thus almost 7200 genotypes weregenerated. The genotypes of four SNPs (CYP11B2T267C, AGTR1 A50058C, ADRB1 A145G, ADRB2T1217C) were also determined individually by thereference method in all of the study samples. Inaddition, 200 randomly selected genotypes (8%) wereredetermined by the reference method. Fully concordant genotyping results were obtained by the individualanalysis and by the multiplex microarray-based genotyping, evidencing for the accuracy of the microarraysystem. The assigned genotypes conformed to Hardy–Weinberg expectations with the exception of the threeSNPs in the AT2 receptor gene, the C1165G SNP inthe 1 -adrenergic receptor gene and the G134A SNP inthe renin gene (P , 0.001).The allele frequencies for the panel of SNPs calculatedfrom the individual patient samples are shown in Table3. With the exception of the SNPs REN G134A,Allele frequency of the single nucleotide polymorphismsincluded in the panelTable 3.Allele frequencySNPLiteratureaSwedenStudy subjectsNANA65/35 6/3485/1580/20 ��angiotensin–aldosteronesystemCYP11B2 T267C57/43ACE C10514T59/41ACE T10527C86/14ACE A10578G86/14ACE G12257A41/59ACE G14480C59/41ACE C14488A41/59ACE A14521G59/41AGT C1015T88/12AGT T1198C59/41AGT A1237GNAAGT A1204C90/10AGT G1218A30/70AGTR1 A49954G75/25 AGTR1 A50058C50/50 AGTR1 T4955A82/18AGTR1 T5052G83/17AGTR1 C5245T64/36AGTR2 G1675A56/44AGTR2 G4297T60/40AGTR2 A4303G30/70MLR C1825TNAREN T1456G55/45 REN A1442G95/5 REN G134AREN T164GREN A279CAdrenergic systemADRA1A T1441CADRA2A C787GADRA2A G1817AADRA2A G278TADRB1 C1165GADRB1 A145GADRB2 T1217CADRB2 T1244CADRB2 G1309AADRB2 G1342CADRB3 T827CADRB3 C3246TEndothelial systemEDNRA T89CEDNRA G125AEDNRB G40AENOS G7002TENOS A2000TENOS G9767AENOS A498GENOS G20455TENOS G2996ALipid metabolismAPOA A1449GAPOB G10108AAPOB C711TAPOE T3932CAPOE C4070TCETP A128CCETP C146ACETP C147ACETP A1300GCETP G1335ACETP G338ACETP G571ACETP A311GLDLR C16730TLDLR T20001CLIPC G89ALIPC ht Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.

Minisequencing for pharmacogenetic profiling Liljedahl et al. 13Table 3.(continued)Allele frequencySNPLPL C9040GLPL G7315CLPL A7344GLPL G7360AOtherCASR C3031GCASR G2956TPPARA T39067CPPARG G1043APPARG C1575TLiteratureaSwedenStudy 93/790/10100/0100/0100/0aAllele frequency in a European population except for a few from Zimbabwemarked with an asterisk. NA, frequency not available. b Deviation from Hardy–Weinberg equilibrium, P , 0.001.gene is in complete LD with the ACE I/D polymorphism, which was shown to predict the reduction in bloodpressure in the same patients treated with irbesartan inour previous study [10]. In both treatment groups, theSNPs in the endothelin type B receptor (G40A) andthe endothelial nitric oxide synthase (eNOS) (A498G)genes were predictors of SBP reduction. Of the SNPsin genes encoding components of lipid metabolism, thesame SNP in the apolipoprotein A gene (A1449G)emerged as predictor of both SBP and DBP response toirbesartan. The SNP in the hepatic lipase gene(A110G) showed opposite effects on DBP response inthe irbesartan and atenolol groups. In both treatmentgroups, the combined SNP genotype profiles explain asmuch as 44% to 56% of the reduction in SBP and DBP.DiscussionADRB1 C1165G, ADRB2 G1342C and LPL G7360A,the allele frequencies identified in the hypertensivepatients were identical to those in the pooled samplerepresenting healthy blood donors.The most probable haplotypes were determined usingthe expectation maximization algorithm based on thegenotypes of the SNPs in eight of the candidate genes(Fig. 3). This analysis revealed that the allelic diversityof these genes is explained by three to six majorhaplotypes with a frequency of more than 5%. Thisanalysis also shows that only two or three SNPs pergene define the haplotypes in 73% to 95% of theindividuals analysed.Of the 97 individuals with hypertension included in thestudy, one-half had been treated with atenolol and halfwith irbesartan. There was no difference in the basiccharacteristics between the two treatment groups, andboth groups showed a similar reduction in SBP andDBP at three months of treatment (Table 1). Becausethe reduction in blood pressure was unrelated to thedoses of the two drugs, the doses were not evaluated asconfounders in the statistical analysis. Those SNPs thatwere related to a change in blood pressure by univariateanalysis were subjected to stepwise multiple regressionanalyses relating the genotypes of the SNPs to changesin blood pressure. This analysis revealed profiles of fouror five SNPs that appeared as significant predictors ofthe reduction in SBP and DBP (Table 4).According to the calculation of pairwise linkage disequilibrium by the Genepop program, the two SNPs inthe adrenergic receptor Æ2 in the group treated withatenolol, as well as the two SNPs in the ADRB2-genethat predicted both the SBP and DBP responses, are inLD, respectively. In the irbesartan-treated group, SNPsin the genes encoding angiotensinogen, ACE and aldosterone synthase were significant predictors of bloodpressure reduction. The SNP G12257A in the ACEIn this study, we have established a robust microarraybased minisequencing system for genotyping a panel of74 SNPs in 25 genes encoding proteins that potentiallydetermine the pharmacodynamics of individual responses to antihypertensive treatment. The systemproved to be robust and allowed accurate genotyping ofall SNPs in every sample. Using this genotypingsystem, we were able to identify combinations of a fewSNPs that predicted approximately 50% of the variationin the individual drug responses in two groups ofhypertensive patients that had been subjected to monotherapy with one of two different antihypertensivedrugs, a 1 -AR blocker or an AT1 -receptor blocker. Thenumber of s

aDepartment of Medical Sciences, Uppsala University, Uppsala, bAstra Zeneca R&D, . SNPs in the coding regions of genes may alter the function or the structure of the encoded proteins. While most of the SNPs are . Endothelial nitric oxide synthase D26607 eNOS G7002T rs1799983 Asp/Glu ENOS AF032908 eNOS A2000T rs1800783