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Kerwin & Dr. Maria J. Arranz Clinical Neuropharmacology, Institute of Psychiatry, London, UK"r2@,+ &l!Variability in treatment response""$2 million patients/year present adverse reactions in US hospitals (Norton, 2001) 100,000 deaths/year caused by adverse reactions (US data, Lazarou et al., 1998) 10% of schizophrenia patients commit suicide (Pickar & Rubinew, 2001) 30-50 % treatment failure in common complex diseases (i.e. rheumatism and schizophrenia) Failure to find appropriate treatment has detrimental effects on prognosis 2.6 billion/year approximate cost of schizophrenia in the UK (Knapp, 1997) f  =    ` &   M m0Variability in response to psychiatric treatment11nCauses of treatment variability  o*Drugs targeted by Pharmacogenetic research++$.    Expensive drugs with a heterogeneous response profile: CLOZAPINE STATINS CHOLINESTERASE INHIBITORS INTERFERON LEUKO TRIENE INHIBITORSP7O7ffO pCurrent status of research$ .Mutations in metabolic enzymes (CYPs) influence absorption & elimination of drugs. Alterations in drug targets contribute to treatment outcome Current findings Asthma: mutations in b-adrenergic receptors affect treatment. ADHD : DAT1 polymorphisms associated to methylphenidate response. Cancer : Several genes identified related to treatment variation. Alzheimer s: APOE, PS1 & PS2 genetic variants influential in treatment outcome. Antipsychotics: response-related mutations detected in metabolic enzymes and in targeted receptors. Z!Z Zw Zfff(ff9f      f  5 = ;  E U qCase Study: Schizophrenia Common, Lifelong, Expensive: Care costs: 1,8 billion (UK data) 0% remission rate 70% partially successful (40-60% develop EPS) 30% failure 5-10% of total drug costs Improved treatment trials (helped by pharmacogenetics) can potentially have massive impact on total costsjjfj  f.  4 r1Genetic prediction (5-HT2A, 5-HT2C, 5-HT6, 5-HTT)2} sDiscussion points$ Ethical dilemmas (so called) : Pharmacogenetic profile (not disease profile) investigated Pharmacogenetics is a prescription (not a diagnostic) tool Ethnic differences in response should be considered for safer treatment What if there is no choice? At what level of accuracy do we deny patients a chance? What are the real economics? The gain might be relatively small Pharmacogenetic applications: overoptimistic? Complex traits (i.e. treatment response) are difficult to define and/or predictf Z Z!Z Z8 Z!Z Z# Z!Z. ZP Zffff8f  f  f#  ff.fPfb  ,     n IPharmacogenetics in psychiatryValidation of targets Identification of novel targets Identification of genes related to disease Selection of most beneficial treatment according to genetic profilefZZ ZZ+ZZDZfR >Pharmacogenetics of antipsychotics: Epidemiological evidence. ?>$$No systematic family or twin-study Familial concordance of fluvoxamine response (67% 1st degree). (Francini et al., 1998) Monozygotic twins concordant for clozapine-induced agranulocytosis. (Horaceck et al., 2001) Monozygotic twins concordant for response to clozapine. (Vojvoda et al., Lancet, 1996) Monozygotic twins concordant for response to olanzapine (Mata et al., Br.J.Psychiatry, 2001) Z$ZZWZZ\ZZWZZ]ZZXff fffDff7fff f8f%ff= 1  = E 'XQ!Pharmacogenetic studies: strategy""(Collection of clinical sample Selection of candidate gene (biological information) Mutation screening (dHPLC, automated sequencing, databanks) Association studies Combination of information for prediction tests Investigation of functionality of response related mutationsZfgW!Pharmacogenomic studies: strategy""(Large clinical samples Large number of genes investigated (Functional information or differential expression) Large scale mutation screening (arrays) High-throughput techniques (automated genotyping) Large investment Results in 5-10 years?@%Genetic factors and clinical response&&$A"Candidate genes: Metabolic enzymes##$Antipsychotics Bromperidol CYP3A4 Ziprasidone CYP3A4 Clozapine CYP1A2, CYP3A4 Olanzapine CYP1A2, CYP2D6 Risperidone CYP2D6, CYP3A4 Chlorpromazine CYP2D6, CYP3A4 Haloperidol CYP2D6,CYP3A4 Sertindole CYP2D6, CYP3A4 Zotepine CYP3A4, CYP1A, CYP2D6Zff     H  Antidepressants Paroxetine CYP2D6 Clomipramine CYP2D6 Desipramine CYP2D6 Doxepin CYP2D6 Mirtazepine CYP2D6,CYP3A4 Trazodone CYP3A4 Amitryptiline CYP2C19,CYP3A4Zff      ?#Associations with metabolic enzymes$$$No clear evidence of association with therapeutic efficacy: CYP2D6 PM & UM not associated with clozapine response (Arranz et al., 1995; Aitchison et al., 1999; Detlling et al., 2000; Mihara et al., 2000) Associations with side effects/adverse reactions: with drug-induced abnormal movements (Ellingrod et al., 1999) CYP2D6 and TD (Kapitany et al., 1998) CYP1A2 and TD (Basile et al., 2000) CYP1A2 PM more susceptible to side effects (Aitchison et al., 2000)<ZZZ2ZZ<fff2fft_ 8h SC(Candidate genes: drug-targeted receptors)) T"Dopaminergic receptors  Involved in pathogenesis of psychiatric disorders Dopamine receptors may be associated with positive symptoms Targeted by antipsychotic drugs Genetic associations reported between DR variants and schizophrenia x2ZZ<ZZ ZZEZffU#(Polymorphisms in Dopamine receptor genes))$D1 : - 48 -A/G, 198-G/A,1263-G/A D2 : -141 DC, Taq I, Pro310Ser, Ser311Cys D3 : -712-G/C, -205-A/G, Ser9Gly, Ala38Thr D4 : 48bp repeat in 3rd loop, 12bp in exon 1 D5 : (TC)13 in promoter, Leu88Phe, Asn351Asp x"+,..ff"ff fffff,ff.ff,fff,2n7fPolymorphisms in D3 gene$X&=D3 Ser 9Gly and clozapine response Frequencies of allele Gly9>=  %aASummary of significant associations.I: dopaminergic polymorphismsBB'&'  D2  141-C Ins/Del early response to clozapine (Malhotra et al.,1999) D2 Taq I short-term response to haloperidol (Schafer et al., 2001) D2 Taq I nemonapride (Suzuki et al., 2000) D3 Ser9Gly response to clozapine (Scharfetter et al., 1998) D3 Ser9Gly neuroleptic (Krebs et al., 1998) D3 Ser9Gly drug-induced movement disorders (Lerer et al., 2002) D3 Ser9Gly & 205-GA improvement of positive symptoms (Staddon et al., 2002) D4 48bp repeat neuroleptic (Hwu et al., 1998; Cohen et al., 1999)LZZZFZCZ !2&0> $( C 1   DK     # [)5-HT receptors$Lower blood 5-HT and CSF 5-HIAA, increased density of 5-HT2A associated with suicidal behaviour (Rao et al., 1998; Asberg et al., 1997). Increased serotonergic function associated with depressive symptoms (Abel et al., 1997). High occupancy of 5-HT2 receptors by clozapine, risperidone and olanzapine (Travis et al., 1998, 1999; Kapur et al. 1998; Farde et al., 1994, 1995) 5-HT2A occupancy associated with improvement in negative symptoms and cognition (Kapur et al., 1998; Meltzer, 1999) ZZZZZZZtZZ;ffff}fftfffb j   h gj75-HT2A (102-T/C) META-ANALYSIS Frequencies of C102/C10248 1 _. Other neurotransmitter receptorsYH1and H2 polymorphisms not associated with clozapine response (Mancama et al., 2000) Novel polymorphisms detected in muscarinic receptors (M1,M2,M3,M4,M5) not associated with response Polymorphisms in prometer region of adrenergic receptors not associated with antipsychotic response (Bolonna et al., 2000) Minor influence on treatment outcome?03&Zfb+  / JL6bBSummary of significant associations.II: serotonergic polymorphismsCC'&(  5-HT2A 102-C poor response to antipsychotics in Caucasians (Arranz et al., 1998) 5-HT2A 102-C more frequent in Chinese responders (Lin et al., 1999; Lane et al., 2002) 5-HT2A His452Tyr clozapine response (Arranz et al., 1996,8; Masellis et al., 1998) 5-HT2C Cys23Ser clozapine response (Sodhi et al., 1995) 5-HT2C Cys23Ser drug-induced tardive dyskinesia (Segman et al., 2000) 5-HT2C  759-C/T drug-induced weight gain (Reynolds et al., 2002) 5-HTT LPR l/l & s/l better response to fluvoxamine in Europeans (Smeraldi et al., 1998) 5-HTT LPR s/s better response to fluvoxamine in Asians (Kim et al., 2000; Yoshida et al., 2002)VZZZZZ=ff4f#f'f.f&ff3ff,ffff2ff;f&ffw    , z 1 3 k"Sample size (O.R.= 2-2.5, p= 0.05)0# ($(i; Pharmacogenetic association studies: Influencing factors <;$,WSample size Type and duration of treatment Assessment methods Ethnic origin: 5-HT2A 102-T/C: C/C genotype associated with poor response in Europeans (Arranz et al., 1998) and with improved symptoms in Chinese (Lin et al., 1999; Lane et al., 2002) 5-HTT LPR: 5-HTT LPR l/l & l/s genotypes associated with better response in Europeans (Smeraldi et al., 1998) and s/s genotype with better response in Asians (Kim et al., 2000; Yoshida et al., 2002) Age: Influences associations with AIMs (Segman et al., 2002) Investigations on extreme phenotypes can help to compare results from different studies bMZsZZZ8ZZXZZMfIf f)f# f[ff3f&fff  f#  f  f  fZ  fPih#Time of first response to clozapine$#$ E35-HT2A (102-T/C) META-ANALYSIS: EXTREME RESPONDERS>4i - x<4Can antipsychotic response be genetically predicted?54!Individual associations have no real clinical value Combination of genetic information in key genes may prove useful Can response variability be predicted using genetic information? Logistic/Linear regression combining genetic information in key genes (5-HTs, Ds, Hs, Ms, transporters) 4ZZAZZAZZhZZ!ffw;!Prediction of clozapine response"!$  Clozapine treated patients with schizophrenia (N=200, retrospective clinical data, GAF) Combination of polymorphisms in 4 genes: 5-HT2A: -1438-G/A (102-T/C), His452Tyr 5-HT2C: VNTR in PR 5-HTT: VNTR in intron and 5-HTTLPR H2: -1018-G/A *XZZ)Z(^}Zffff%ff1f  f  f  f$ $F!Prediction of response: Clozapine "!$ _`!Prediction of olanzapine response""(&    de[Prediction of risperidone response: Influence of dopaminergic & serotonergic polymorphisms \Z $J     Y'SAntipsychotic prediction tests $oClozapine prediction test based on a combination of genotypes: correct prediction in nearly 80% of cases Currently undergoing validation Results available in 2 days Under development: prediction tests for response to olanzapine, risperidone and haloperidol Future: prediction of side effects (agranulocytosis, weight gain, tardive diskynesia) and symptom improvement.npfl   6 ~?7Individualisation of psychiatric treatment : the futureOAnalysis of specific symptoms/ adverse reactions: TD (Lerer et al., 2002) Associations with positive/negative symptoms Investigation of factors influencing short/long-term response Combination of pharmacokinetic and pharmacodynamic information : metabolic activity and site of action Prediction tests for individuals/type of drug? 3ZEZZ>ZZgZZ/ZZ3fEff  f,7f/Ja{  P$  ` 3ff3f3` MMMe3f` ___` 3f3ff33` f3ff33f3` ̙ff3ff3f33>?" dP@,?nZd@  d vK@ d` n?" dd@   @@``PR    @ ` `p>> % \T ( P P   Hd?" " nZ }xv # "~B  N8c?}v~B  N)?}xvx  Zgֳgֳ ?"t`  T Click to edit Master title style! !<  HTgֳgֳ ?"h0  RClick to edit Master text styles Second Level Third Level Fourth Level Fifth Level!     S   Nbgֳgֳ ?"0   \*   Tpgֳgֳ ?"@  \*   NEgֳgֳ ?"  Z*f  Nd޽h @? ? 3f3f &Project Post-Mortem  % wo@  (   F   "f   6d?T@ }v   }v ~B   N8c?} v ~B   N)?}vl   <d?@  Zgֳgֳ ?"p  T Click to edit Master title style! !  H8~gֳgֳ ?" `    W#Click to edit Master subtitle style$ $  Ngֳgֳ ?"0   \*  T<gֳgֳ ?"@  \*  Nlgֳgֳ ?"  Z*f  Nd޽h @? ? 3f3f 0 `(  ` ` 000 "P    ^*   ` 03 "    `*  r ` c $ ?"  $ ` 0@ " @  RClick to edit Master text styles Second level Third level Fourth level Fifth level!     S ` 6 "`P   ^*   ` 6| "`   `*  H ` 0޽h ? ̙3380___PPT10.~ vnh( )pM h h 0H/  "    `*   h 6Hb  "M    `*   h 6  "FRQ   `*  H h 0޽h ? ̙3380___PPT10.~  % 0X$(  Xr X S L p  r X S n     H X 0޽h ? 3f3fy___PPT10Y+D=' = @B +  % P0(  x  c $``0   x  c $D0p  H  0޽h ? ̙33y___PPT10Y+D=' = @B +  % `(  x  c $``   l  0A U??oq  U  0 ``  >50-60% 2  0ܫ  >30-45% 2  0z  >20-30% 2T  <޽h ? ̙33y___PPT10Y+D=' = @B +/$  % B#:#pZZ"(  x  c $z@  z R  s *0R  s *0R  s *00R  s *0`pR  s *ppR2  s * 0R   s *0R   s *0`0R   s *0R   s *pR   s *0pR2  s * 0R  s *P @R  s *@ PR  s *@R  s *PR  s *P R2  s * PR  s *Pp@R  s *@pR  s *@R  s *P0R  s *P@pR2  s *pPR  s *P`@R  s *@`R  s *@R  s *P R  s *P0`R2   s *`PX ! 0PR " s *PR # s *R $ s *pX % 0PPR & s *PPR ' s *PR ( s *PpX ) 0 R * s * R + s *R , s *3@X - 0 R . s * R / s *R 0 s *3@X 1 0 R 2 s * X 3 0R 4 s *@R 5 s *pR 6 s *p@R 7 s *@R 8 s *0R 9 s *@pX : 0@X ; 0@p@X < 0@X = 0X > 0@X ? 0 0 X @ 0 @ X A 0 0@ X B 0 0` X C 0 p X D 0  X E 0  @ X F 0 P@ X G 0  X H 0  R I s * 0 R J s * 0`@ R K s * @ R L s *  R M s * 0 R2 N s *0 0 ^ O 61p   P 0d,z  8 USmoking Food Plasma levels Doses Concomitant treatment Age Initial symptoms GenderV0F2V Q 01z   HDRUG TREATMENT 2 R 045z0 d.Mutations in Metabolic enzymes & Drug targets/ 2/X S 00@ T 0 9z @ =GENES 2 U 03z  G  BRESPONSE 2  V 0\z p0 0  C ENVIRONMENT 2  W 0@z   9& 2X X 00 0 X Y 00  R2 Z s *0pH  0޽h ? ̙33y___PPT10Y+D=' = @B +  % <(     0sz`  z x  c $4tzPp z H  0޽h ? ̙33y___PPT10Y+D=' = @B +  % 0(  x  c $$z``  z x  c $z  z H  0޽h ? ̙33y___PPT10Y+D=' = @B +y  0(  x  c $z``  z x  c $XzP z H  0޽h ? ̙33y___PPT10Y+D=' = @B +z ZK0 (  x  c $z`0  z  0 HA V?a V z   ` z1?`  JN= 200(   Z z1?@ P  IN= 50( 2  Zz1?p IN= 30( 2-  ZPz1? CResponse prediction: 78% (p= 0.001) 76% (ns) 86% (p= 0.02)DD 2f+ffH  0޽h ? y___PPT10Y+D=' = @B + ZK0 0(  x  c $z  z x  c $z ` z H  0޽h ? ̙33y___PPT10Y+D=' = @B + ZK0  $(  r  S z`  z r  S zp z H  0޽h ? 3f3fy___PPT10Y+D=' = @B + ZK0  6(   ~   s * z`  z x   c $z   z H   0޽h ? f̙y___PPT10Y+D=' = @B + ZK0   L0 (  L L s *IzP@ p `Pharmacogenetics 2 L s * KzPP p `Pharmacogenomics 2 L s *SzP $ p0Candidate genes (biological information) $1 2/ L 0,Wz$ d.Large number of genes (Functional information)/ 2/ L 0|Zz  t  _Identification of single genes $ 2 L 0^z P0F  Y%Standard molecular genetic techniques& 2& L 0bz F  ['High-throughput techniques (DNA arrays)( 2(  L 0ez Pt  V Identification of multiple genes! 2!  L 0iz  _-Prediction tests based on genetic information. 2.  L s *pI`p HTailored treatment 2XB  L 0DԔXB L 0DԔ@ XB L 0DԔp 0XB L 0DԔPPXB L 0DԔ@PP RB L s *DԔ p XB L 0DԔ  L 0LN  b(Identification of response related genes) 2) H L 0޽h ? 3f3fy___PPT10Y+D=' = @B + ZK0 $$(  $r $ S LyH   r $ S dh0  H $ 0޽h ? 3f3fy___PPT10Y+D=' = @B + ZK0 <$(  <r < S  H   r < S < @  H < 0޽h ? 3f3fy___PPT10Y+D=' = @B +5  ZK0 D< (  x  c $       fP`1?  M drug, 2ff   f\1?  Bresponse 2 f   f1?P  metabolic enzymes (CYP)R 2 ffff   f1?P   `Dose toxic effect20 22ff#   fZ1?0 !  1Site of action symptom improvement/ side effects@0 22 2 0 222fB   fD>?0 Z   S  ??0  b  Z1?` p r  Z1? 0 p  H  0޽h ? y___PPT10Y+D=' = @B + ZK0 & (  ~  s *`H   x  c $[ P   x  c $1 P  H  0޽h ? w&UGGGy___PPT10Y+D=' = @B + ZK0 00(  x  c $$w   x  c $w   H  0޽h ? y___PPT10Y+D=' = @B + ZK0 @F(  ~  s *``    0 <A ?pW  H  0޽h ? y___PPT10Y+D=' = @B + ZK0 P6(  ~  s * |H   x  c $p  H  0޽h ? y___PPT10Y+D=' = @B +~ ZK0 `(  x  c $    ~  s *h00d    Z 1?p`0 UWong et al., 2000( 2H  0޽h ? y___PPT10Y+D=' = @B +  ZK0   pJ (  x  c $4`x      f 1?  @  H     f#1? P@  H     `&1?   oPromoter region Coding region6 2 B   `Do?p B   `Do?`     f+1?@@z L-712-G/C( 2    fP1?  F 2    3 r 1?p j  >-205-A/G  B   ZDo?     fT 1?  QSer9Gly. 2B   ZDo?@ @    f 1? P  PAla38Thr, 2H  0޽h ? f̙y___PPT10Y+D=' = @B +U ZK0 d\$(  $ $ C x` xaxa1 ?P     $  `A 0?1?@aX 0$ 0d 0H $ 0޽h ? a(y___PPT10Y+D=' = @B + ZK0 p0(  px p c $X `0   x p c $ p   H p 0޽h ? f3y___PPT10Y+D=' = @B + ZK0 40(  4x 4 c $ `P   x 4 c $ `   H 4 0޽h ? y___PPT10Y+D=' = @B +3ZK0 B: (    s *O    _ 5-HT2A gene8 ( ((   f1?@ pp   Z1?@ p`p B  # lDԔ? pp B  # lDԔ?     f 2 H  0޽h ? y___PPT10Y+D=' = @B +v  ZK0 }(    C x xaxa1 ?P       `A >?1?!X >$ 0d 0  Z 1?` ADifferences: treatment duration, response assessment, sample size2B 2AffH  0޽h ? a(y___PPT10Y+D=' = @B + ZK0 T6(  T~ T s *W t`   x T c $    H T 0޽h ? y___PPT10Y+D=' = @B + ZK0 t0(  tx t c $L    x t c $     H t 0޽h ? f3y___PPT10Y+D=' = @B + ZK0 O(  x  c $ `0p0   b   f@ 1? Allele frequency 0.10 0.20 0.30 0.40 Sample size (N) 600 80-95% 95-99% >95-99% >98% 400 60-80% 80-95% 90-99% >90-99% 300 45-70% 70-90% 80-95% 80-97% 200 40-55% 50-80% 60-85% 65-86% >0 P20 n2 2=fffff"ff!ff"fB   fDԔ?B   fDԔ?    fa 1?t ksamples= 50% cases/50% controls0 2ffH  0޽h ? ffy___PPT10Y+D=' = @B + ZK0 $(  r  S j    r  S |k     H  0޽h ? 3f3fy___PPT10Y+D=' = @B + ZK0   (  x  c $     0 HA ;?0Ct ;     f 1?p `@j  G46%( 2   f 1?` Z  ;71% 2   fD 1?p ` j  I77%* 2   fL 1? I91%* 2   f 1? <100% 2    f 1?`` JMeltzer et al., 1992 2H  0޽h ? fffy___PPT10Y+D=' = @B +A ZK0 PH (    C x xaxa1 ?@`    0 TA ?1 ?h/ 0h $ 0d 0   0 TA ?1 ?h 0h $ 0d 0    3 r  1?F_W JArranz et al. (1998) H  0޽h ? a(y___PPT10Y+D=' = @B + ZK0 00(  x  c $|'@   x  c $X'p ' H  0޽h ? y___PPT10Y+D=' = @B +y  @0(  x  c $ '``00  ' x  c $p'@`` ' H  0޽h ? y___PPT10Y+D=' = @B + B .Institute of Psychiatry Pg(  x  c $D'`  '  0 HA ?X|  '2   fd'1?0``* >PPV= 0.80 NPV= 0.73 Sensitivity= 90.3% Specificity= 53%B? 2 1  Z'1? 0 _Arranz et al., 20000 2  Z'1?@@` ^$78.2% correct prediction (p< 0.0001)% 2%H  0޽h ? y___PPT10Y+D=' = @B +( ZK0 7 / `h (  h4 h T'?@+` ,Polymorphism difGAF PANSS PPANS NPANS PGPANS:-  &  | h T'? D2 -141-C Ins/Del .53 .26 .27 .66 .22 D2 Taq I .80 .81 .68 .98 .83 D3  205-G/A .80 .62 .51 .86 .54 D3  7685-G/C .46 .06 .08 .21 .09 D3 Ser9Gly .18 .007 .03 .06 .01 D4 521-C/T .86 .35 .48 .10 .07 5-HT2A His452Tyr .47 .72 .76 .77 .43 5-HT2A  1438-G/A .69 .83 .68 .59 .90 5-HT2A 102-T/C .23 .38 .58 .24 .57 5-HT2C  759-C/T .31 .92 .66 .82 .99 5-HT2C  995-G/A .46 .95 .61 .54 .92 5-HT2C Cys23Ser .91 .95 .10 .28 .58 5-HT2C VNTR .21 .26 .54 .29 .26 5-HT6 267-C/T .06 .03 .02 .78 .03 5-HTT VNTR .25 .07 .20 .75 .02 5-HTT LPR .57 .88 .71 .21 .53 M1  12064-T/C .67 .74 .60 .32 .34Iw33383333B&*  h H9'?P D 2   h H '?0 3Olanzapine response: Analysis of variance p values *4 22 *H h 0޽h ? f3y___PPT10Y+D=' = @B +  p l[(  lx l c $' `p  '  l0 <A :?   : '^ l HL'? 0 ~Logistic regression : bimodal response Level prediction= 78% (p= 0.05) PPV= 0.77 NPV= 0.77 Sensitivity= 80% Specificity= 75%0 2'X~ p l H? @0p l N\'? `e _ Predicted 2    l ZT'? pu  ^Observed 2  p l Hf3? P@p  l H_'?` L p$Predictor variables: D3  205-G/A & Ser9Gly 5-HT2C -759-C/T, -995-G/A, Cys23Ser & VNTR 5-HT2A His452Tyr & 102-T/C 5-HT6 267-C/T 5-HTT VNTR & LPR 0 2~H l 0޽h ? f3y___PPT10Y+D=' = @B + ZK0   |Q (  |4 | Tj'?@` ,Polymorphism difGAF PANSS PPANS NPANS PGPANS:-  &   | Tr'? T@D2 -141-C Ins/Del .86 .94 .87 .59 .84 D2 Taq I .09 .04 .15 .51 .07 D3  205-G/A .67 .67 .78 .01 .81 D3  7685-G/C .27 .33 .20 .19 .99 D3 Ser9Gly .67 .61 .77 .23 .24 D4 521-C/T .35 .93 .16 .07 .94 5-HT2A His452Tyr .55 .37 .07 .37 .41 5-HT2A  1438-G/A .20 .30 .88 .24 .28 5-HT2A 102-T/C .05 .07 .40 .18 .09 5-HT2C  759-C/T .29 .40 .28 .05 .58 5-HT2C  995-G/A .42 .30 .23 .03 .69 5-HT2C Cys23Ser .22 .28 .35 .70 .45 5-HT2C VNTR .31 .31 .55 .11 .08 5-HTT VNTR .25 .07 .20 .75 .02 5-HTT LPR .57 .88 .71 .21 .53 Combined .08 .02 .07 .15 .01!  ^< E  &*  | 0u'  5Risperidone response: Analysis of variance p values 26 23 +H | 0޽h ? f3y___PPT10Y+D=' = @B + ZK0  (  x  c $+'  '  0 <A 4?   4 '  H-'?p` b mN= 8700P2 M  H\'? 0  Logistic regression : bimodal response Level prediction= 87% (p= 0.003) PPV= 0.88 NPV= 0.86 Sensitivity= 88% Specificity= 87% 2 p  H?0  Z'?p05j _ Predicted 2     Zī'?p  j ^Observed 2  p   H?0   0D' 0  d.Predictor genes: 5-HT2A, 5-HT2C, 5-HTT, D2, D4/ 2/3H  0޽h ? f3y___PPT10Y+D=' = @B +ZK0 ,$(  ,l , 0A 1??   ( 1 , 00' p QGenotype Gly/- allele Gly response vs PANSS: F= 3.352, p= 0.07 response vs PPANSS: F= 11.46, p= 0.002 response vs NPANSS: F= 0.005, p= 0.94 20 F2|b  &( , 0\  0D3 Ser9Gly and response to olanzapine in Basques1 21   , Z8 1?0p  AN= 47  2H , 0޽h ? ̙33y___PPT10Y+D=' = @B + ZK0 ,6(  ,~ , s *$R    x , c $R     H , 0޽h ? y___PPT10Y+D=' = @B + ZK0 $(  r  S N lH   r  S X      H  0޽h ? 3f3fy___PPT10Y+D=' = @B + 0 8(  d c $    s *X5  @   " H  0޽h ? ̙33`& 0  ((  ( ( N1 ?    (C xy xaxa1 ? @   " H ( 0޽h ? a(; 0 08(  d c $    s *`  @   " H  0޽h ? ̙33g 0 8(  d c $    s * %  @   " H  0޽h ? ̙33`j 0   (    N1 ?    C x xaxa1 ? @   " H  0޽h ? a([ 0 p (  X  C `     S ]` @   " H  0޽h ? ̙3380___PPT10.txUO(QffY6=I8!)m\(Ueݴ[r$GW7'řF͑%̛$rofy~7gW;kC74dBh @ilzSx%>_\OH"^c})YlU~lƮTu'&>? #oy T })yUC#y X{CUD sr/Pl+ҿC Dľ[~0񮫚o/j, ",!K2/_ӊmvjxND|& Ţ =z2?EeTѱI)O~!?v,~Wd.:MWOybTjh 51@&F1BwbĘ&&ۦ|n-qW1&58^TTq]PwbUu/{|x pU_H B!p03@8:I&d0 D+V׫Ew] %Vqy,@,]]K ,^g:3d2?u}^}bIGXrS 3t@xt"IQ7irMO Y!a6X@ X'M=A/$+A_rHS 40` `)ʏFjc8d!9 X0NI@ng^c,&JU6x*hS|vbt~;=Y}l]>;%}`?;ԦZ0>HDY~NHit6E} Eq$Mi*]%*"r]4OWyyުԉ w_N>tP$mSrټ7iK}ҥ4-gƃ$*b^u\o9+ujj0>gqw6ǂsR|i Lc;b?L YL{t. MatN;W!>w'mA;W~QfAzi~MF%o5I]u^ySmo6\zFCu{#]Bu薅ѝwnCD}6