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TODAY…. trials and errors diagnosis effective treatment TOMORROW…. tailor made Pharmacogenetics • Hypothesis Variability in response, toxicity and adverse effects following drug treatment is influenced by genetic variation • Advantages Genotyping can be done any time Not influenced by current treatment Can be measured very reliably Genome fully sequenced Easy to do – peripheral blood sample Heritability – a starting point • FHx of response or side effects Poor man’s pharmacogenetics? • Antidepressants 38 family pairs concordant for response to Imipramine (Angst, 1964) 12/12 and 10/12 concordance of first degree relatives (Pare et al. 1962; Pare & Mack, 1971) Retrospective study in 4 families who responded to tranylcypromine but not other ADs (O’Reilly et al. 1994) 67% of 1° rels of fluvoxamine responders responded (Franchini et al. 1998) • Antipsychotics Afro-Caribbean greater acute response than Caucasians (Emsley et al. 2002) Little other supportive data Definition of some terms • Pharmacogenetics The study of candidate genes that may influence drug effects and metabolism • Pharmacogenomics The study of all genes (and their expression) in the genome that may influence drug effects and metabolism Non-hypothesis based Needs large-scale high-through put techniques to screen the genome Genetic Variation • Polymorphism Genetic variation that occurs with a frequency ≥ 1% in the population Various types • SNPs (Single nucleotide polymorphisms) • Repetitive DNA sequences Must be functional (?) • Alter the expression levels or conformation of a drug-related protein Single Nucleotide Polymorphism (SNP) in the Coding Region of a Gene SNP results in alteration of the amino acid sequence of the corresponding protein • arginine (Arg) substituted for glycine (Gly) • Distinct protein structures could result in phenotypic differences between the subjects, such as variation in response to medication. Taken from Malhotra et al. 2004 Am.J.Psych. Pharmacogenetic tree Absorption/ Excretion Pharmacokinetics study of availability of therapeutic in body Pharmacogenetics Metabolism Distribution study of correlation between genetic traits and response to therapeutics (efficacy and adverse effects) Receptors Pharmacodynamics Pharmacodynamics study Study of drug of drug andand target interaction target interactions Transporters /Channels Enzymes CYP450: • 76% of ADRs are dose dependent • CYP450 is one of the best characterized metabolic protein complexes CYP 450 and metabolism of TCAs • Marked genetic variation in hepatic metabolism Up to 30-fold variation in plasma concentrations between individuals • N.B. cardiac arrhythmias occur at concentrations just 10fold higher than monoamine uptake blockade • Main rate limiting step in TCA metabolism is mediated by CYP2D6 isoenzyme 7% of Caucasians have a functional impairment of this enzyme which can lead to toxic levels occurring Drug Concentrations by Genotype Metabolizer Status Genotype Ultrarapid Response to average daily dose Conc. Time Extensive Intermediate Poor normal activity reduced activity no activity = Adverse Events = Therapeutic Window Regional distribution of ultrarapid metabolisers Ingelman-Sundberg (2001) Journal of Internal Medicine 250: 186 CYP2D6 and dosing of antidepressants Source: Kirchheiner et al., Mol Psychiatry 9: 442-47392 CYP2D6 and dosing of antipsychotics Source: Kirchheiner et al., Mol Psychiatry 9: 442-47392 CYP450 Polymorphism Findings • No confirmed association between CYP450 polymorphisms and response to antipsychotics or antidepressants identified to date (see Vetti et al. 2010) • CYP2D6 and CYP1A2 associated with increased side effects of antipsychotics (TD and PSx)(Basile et al. 2000; Lam et al. 2001) • CYP2D6 and CYP2C19 associated with increased side effects with sertraline (Wang et al. 2001) N.B. wide therapeutic index with SSRIs P-glycoproteins and antidepressant response • P-glucoproteins (P-gp) are transport proteins that occur around the body, including in the BBB Includes the MDR1 (ABCBB1) protein Can influence the entry of drugs into the brain 15 Organ/plasma ration of antidepressants in ABCB1 mutant mice Uhr, M. et al. 2008 Neuron 57: 203-209 16 P-gp polymorphisms and response to antidepressants • 362 patients treated with P-gp substrates (amitriptyline, citalopram, paroxetine, venlafaxine) or non-substrate (mirtazepine) • 9.5% non-remitters carried C allele vs 45% of remitters • C-carriers treated with P-gp substrate significant increased risk of remission Uhr, M. et al. 2008 Neuron 57: 203-209 17 18 Pharmacodynamics • The interaction of a drug with a target molecule Receptors, enzymes, transporters, ion channels • Leads to therapeutic effects • Can lead to side effects 5-HTT/SERT 5HTTLPR polymorphism Serotonin transport gene polymorphisms • The brain serotonin transporter (5HTT) is the principal site of action of many antidepressants.1 Transcriptional activity of the 5HTT gene is modulated by a gene linked polymorphic region (5HTTLPR).2 The short (s) allele is associated with lower transcriptional efficiency than the long (l) allele.2 • • 1. 2. 3. Serretti A et al. Prog Neuro Psychopharmacol Biol Psychiatry 2005;29:1074-1084 Lesch KP et al. Science 1996 ;274:1527-1531 Diagram from Canli T & Lesch KP. Nat Neurosci 2007;10:1103-1109 Genetic (5-HTTLPR polymorphism) influence on response to stress Trier Social Stress Test in healthy subjects2 Association of stressful life events aged 2126yrs and depression outcome aged 26 as a function of 5HTT geneotype.1 Meta analysis demonstrates greater amygdala activity in s allele carriers when shown pictures of fearful faces.3 1. Caspi A et al. Science 2003; 301:386-389 3. Munafo MR et al. Biol Psychiatry 2008;63:852-857 2. Way BM & Taylor SE. Biol Psychiatry 2010;67:487-492 SSRIs and 5-HTT/SERT (from Schosser & Kasper, 2009) 22 5-HTTLPR effects may be mediated via complex and indirect effects 5-HT Receptors and antidepressants • 5-HT1A polymorphism Functional Associated with alterations in expression of 5-HT1A receptors (Lemonde et al. 2003) Associated with response to TCAs and SSRIs (Serretti et al. 2004; Lemonde et al. 2004) • 5-HT2A polymorphism Association found in largest pharmacogenetics study (n = 1953, 768 SNPs examined) 79.9% vs 62.4% response rates for homozygous patients (McMahon et al. 2006) Antidepressants and other polymorphisms • Glutamate receptor polymorphism associated with response to citalopram (Paddock et al. 2007) GRIK4 • Glutamate receptor polymorphism associated with treatment emergent suicidal ideation with citalopram (Laje et al. 2007; Menke et al. 2008) GRIK2 (kainate-sensitive ionotropic glut receptor – GluR6) GRIA3 (ionotropic glut receptor – AMPA3) • CREB1 (cAMP response element binding protein 1) associated with treatment emergent suicidality in men (Perlis et al. 2007) • NET polymorphisms and response to nortriptyline Uher et al. 2009) • GR polymorphisms associated with response to escitalopram and nortriptyline (Uher et al. 2009) 28 CLOCK gene – multiple effects • CLOCK 3111T/C Polymorphism Associated with “eveningness” (healthy subjects) Associated with a higher recurrence of episodes (BP) Associated with lifetime insomnia (BP+UP) CLOCK gene variants and insomnia during SSRI treatment HAMD insomnia score p=0.0443 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 p=0.0379 p=0.0195 p=0.0050 TT TC CC T0 T1 T2 T3 T4 T5 T6 Weeks of treatment 33 Zang & Malhotra (2011) - summary • Most pharmacogenetic studies of antipsychotic drugs have used a candidate gene approach, focusing on polymorphisms in genes coding for receptors in the dopamine and 5-HT systems, as well as genes coding for enzymes that metabolize drugs, such as COMT and CYP2D6. 34 Zang & Malhotra (2011) - summary • Regarding genetic variants predicting antipsychotic drug efficacy, previous studies have produced promising results for a few polymorphisms including the -141C Ins/Del in DRD2, Ser9Gly in DRD3, -1438G/A in HTR2A, 5-HTTLPR and Val108Met in COMT. • Studies with larger samples and better designs are needed to validate these findings. 35 Zang & Malhotra (2011) - summary • Regarding genetic variants predicting antipsychotic-induced side effects, different studies have been inconsistent. • For tardive dyskinesia, the Taq1A in DRD2, the Ser9Gly in DRD3, the T102C SNP (single nucleotide polymorphism) in HTR2A and the loss of functional variants in CYP2D6 may warrant further research. 36 Pharmacogenetics of antipsychotic induced weight gain (Lett et al. 2011 Mol Psychiatry) • Replicated data for leptin and 5-HT2C genes • Also evidence for: DRD2, TNF, SNAP-25 and MC4R genes • Preliminary evidence for: CNR1, MDR1, ADRA1A and INSIG2 37 Combinations of genes • Combining information from key response-related genes Can constantly refine predictions by adding additional genes Will need adjustments for ethnic mix • Examples: DRD3 and 5-HT2C polymorphisms have additive effects on risk of TD (Segman & Lerer 2002) DRD3 and CYP1A2 polymorphisms additive effects on risk of TD (Basile et al. 2000) Response in Alzheimers predicted by combination of polymorphisms of APOE, PS1 and PS2 (Cacabelos et al. 2000) • Problems What statistical methods should be used? Effects additive or synergistic? Genes investigated in the short term response to antidepressants • • • • • • • • • 5-HTTLPR SERT-STin2 5HT1A C-1019G 5-HT1B 5HT2A T102C 5HT2A G1438A 5HT2C 5HT6 C267T TPH1 A218C TPH2 • NET T-182C • • • • • • • • • • COMT • MAOA • DRD2 S311C • DRD4 VNTR • ACE I/D • polymorphism • G-protein beta3 • C825T • ADRB1 G1165C • CRHR1 • NOS C276T • IL-1beta C511T • CRHR1 DTNBP1 FKBP5 CLOCK BDNF DTNBP1 nNOS IL-1beta APOE MDR1P-gp A-161T Dysbindin Genes investigated in the short term response to antidepressants • • • • • • • • • 5-HTTLPR SERT-STin2 5HT1A C-1019G 5-HT1B 5HT2A T102C 5HT2A G1438A 5HT2C 5HT6 C267T TPH1 A218C TPH2 • NET T-182C • • • • • • • • • • COMT • MAOA • DRD2 S311C • DRD4 VNTR • ACE I/D • polymorphism • G-protein beta3 • C825T • ADRB1 G1165C • CRHR1 • NOS C276T • IL-1beta C511T • CRHR1 DTNBP1 FKBP5 CLOCK BDNF DTNBP1 nNOS IL-1beta APOE MDR1P-gp A-161T Dysbindin 41 1. Number of episodes 2. Side effects (yes/no) 3. Delusional features (yes/no) 4. Baseline HAM-D 5. Length of current episode 6. Lithium augmentation (yes/no) 7. Current medical condition (y/n) 8. Personality disorders (yes/no) 9. Sex (female/male) 10. Age at onset 11. Polarity (UP/BP) 12. Plasma level 13. Baseline VAS HAMD improvement 1. Number of episodes 2. Side effects (yes/no) 3. Delusional features (yes/no) 4. Baseline HAM-D 5. Length of current episode 6. Lithium augmentation (yes/no) 7. Current medical condition (y/n) 8. Personality disorders (yes/no) 9. Sex (female/male) 10. Age at onset 11. Polarity (UP/BP) 12. Plasma level 13. Baseline VAS HAMD improvement 21% Variance explained Genes investigated in the short term response to antidepressants • • • • • • • • • 5-HTTLPR SERT-STin2 5HT1A C-1019G 5-HT1B 5HT2A T102C 5HT2A G1438A 5HT2C 5HT6 C267T TPH1 A218C TPH2 • NET T-182C • • • • • • • • • • COMT • MAOA • DRD2 S311C • DRD4 VNTR • ACE I/D • polymorphism • G-protein beta3 • C825T • ADRB1 G1165C • CRHR1 • NOS C276T • IL-1beta C511T • CRHR1 DTNBP1 FKBP5 CLOCK BDNF DTNBP1 nNOS IL-1beta APOE MDR1P-gp A-161T Dysbindin Prediction of Clozapine response (Arranz et al. 2000) • 200 schizophrenia patients (all white Caucasians of British origin) treated with clozapine (133 responded) • 19 polymorphisms analysed • 6 with strongest association with response (5HT2A X 2, 5-HT2C X 2, 5-HTT, H2) combined PPV: 0.76 ± 0.08 NPV: 0.82 ± 0.16 Sensitivity 95.9% ± 0.04% (for identifying “satisfactory” responders) Specificity 38.3 % ± 0.14% (for identifying poor responders) • Utility? N.B. Ethical, Legal and Social Implications • Use of genetic information by insurers, employers... • Who should have access to personal genetic information, and how will it be used? • Privacy and confidentiality. • Who owns and controls genetic information? • Stigmatization. • How does personal genetic information affect an individual and society's perceptions of that individual? • More information at http://www.royalsoc.ac.uk/displaypagedoc.asp?id=17570 48 Pharmacogenetics Conclusions Pharmacogenetics: Any relevance to clinical practice? Possibly…. • CYP450 chip technology may be helpful for a minority of patients • Use of pharmacogenetics for efficacy predictions (e.g. for clozapine) less clear • The future (5-10 years) does potentially look very interesting