Post on 17-Apr-2015
Dúvidas
denucci@gdenucci.com
Arquivo
Farmacogenômica
Site
www.gdenucci.com
Dúvidas
denucci@gdenucci.com
Arquivo
Farmacogenômica
Site
www.gdenucci.com
Pacientes com o mesmo diagnóstico
Resposta preditiva boa
para o medicamento
Resposta preditiva ruim ou ausente
Use outro medicamento
Risco de toxicidade alto
Diminuir a dose ou usar outro
medicamento
Ensaio DrogaEventos (%)
Benefício/100 Ausência de Benefício/100Placebo Tratad
Hope
APTC
FTT
4S
EPIC
CURE
Ramipril
Aspirina
Trombolíticos
Simvastatina
Abciximab
Clopidogrel
17.8
14
11.5
28
12.8
11.5
14
10
9.6
19
8.3
9.3
3.8
4
1.9
9
4.5
2.2
96.2
96
98.1
91
95.5
97.8
Tratamentos estabelecidos com alta eficácia e % dos pacientes beneficiados e não beneficiados com o
tratamento
Alvos do medicamento
Transporta-dores
Enzimas metabolisadoras
Farmacodinâmica Farmacocinética
Variabilidade na eficácia ou toxicidade
Farmacogenética
FarmacogenômicaFarmacogenômica
Afinidade do receptor Afinidade do receptor pela drogapela droga
Afinidade do receptor Afinidade do receptor pela drogapela droga
Droga atuando em produtos gênicosDroga atuando em produtos gênicosDroga atuando em produtos gênicosDroga atuando em produtos gênicos
ExcreçãoExcreçãoExcreçãoExcreçãoDistribuiçãoDistribuiçãoDistribuiçãoDistribuição
AbsorçãoAbsorçãoAbsorçãoAbsorção
Farmagenômica
Curr Probl Cardiol, May 2003
The concept of pharmacogenetics.
Pharmacogenomics: Challenges and Opportunities - © 2006 American College of Physicians - Ann Intern Med. 2006;145:749-757.
Two types of variability in drug action.
Pharmacogenomics: Challenges and Opportunities - © 2006 American College of Physicians - Ann Intern Med. 2006;145:749-757.
PD and PK pathways of HMGCo A reductase inhibitors (Statins).
Cholesterol and lipoprotein transport: genes involved in mediating statin effects on hepatic cholesterol metabolism and consequent effects on plasma lipoprotein transport. Statins inhibit endogenous cholesterol production by competitive inhibition of HMG-CoA reductase (HMGCR), the enzyme that catalyzes conversion of HMG-CoA to mevalonate, an early rate-limiting step in cholesterol synthesis. This pathway delineates genes involved in statin pharmacogenomics, including genes involved in mediating the PD effects of statins on plasma lipoprotein metabolism and those involved in the PKs effects of the drug transport and metabolism. Note the effects of inhibition of HMG-CoA reductase on major aspects of hepatic cholesterol metabolism and selected gene products that can modulate the effects of statins on metabolism and transport of plasma lipoproteins.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
PD and PK pathways of HMGCo A reductase inhibitors (Statins).
PKs of Statins: representation of the superset of all genes involved in the transport, metabolism, and clearance of statin class drugs. This figure depicts a generalized view of the PKs of statins, representing the superset of all genes with a reported influence on statin transport and metabolism. Statins are dosed orally and enter the systemic circulation through intestinal cells both passively and by active transport via the ABC and SLC gene family transporters. The major organs of metabolism and elimination include the liver and, to a lesser extent, the kidney. Metabolism is catalyzed by enzymes of the CYP and UGT gene family. The main pathway of elimination is ABC-transporter-mediated biliary excretion. The more hydrophilic compounds (e.g., pravastatin) require active transport into the liver, are less metabolized by the CYP family, and exhibit more pronounced active renal excretion, whereas the less hydrophilic compounds are transported by passive diffusion and are better substrates for both CYP enzymes and transporters involved in biliaryexcretion.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
The home page of PharmGKB provides a straightforward schema for understanding pharmacogenomics.
Diastolic blood pressure response to metoprolol in hypertensive patients is predicted by ADRB1 diplotype.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
Flow chart for the functional evaluation of genes with replicated associations.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
Whole-genome approach to identify genes that predict survival.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
Impact of germline TPMT genotype on incidence of toxicity (upper).
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
The path of phenytoin and imidapril after ingestion.
This figure shows the paths that are taken by the anti-epileptic drug phenytoin and the angiotensin-converting enzyme (ACE) inhibitor imidapril in the human body. Phenytoin is absorbed into the bloodstream at the gut and circulated through the liver to the brain. It crosses the blood–brain barrier where it binds and inhibits its target, neuronal sodium channels. It is pumped back out across the blood–brain barrier into the bloodstream by multidrug resistance protein 1 (MDR1, also known as ABCB1) efflux pumps. Note that MDR1 efflux pumps are also active in the gut, where they promote drug excretion (not shown). At the liver, phenytoin is metabolized by the cytochrome P450 enzymes CYP2C9 and CYP2C19, and it is eliminated through the kidneys. Imidapril is a PRO-DRUG. After its absorption from the gut into the bloodstream it is hydroxylated in the liver to the active metabolite imidaprilat. Imidaprilat binds and inhibits ACE in the plasma. Imidaprilat is also eliminated through the kidneys.
PHARMACOGENETICS GOES GENOMIC - NATURE REVIEWS -GENETICS VOLUME 4 - DECEMBER 2003
Alelos da apo
• apo 2
• apo 3
• apo 4
Kaplan-Meier em pctes com e sem o alelo apo4
Dias após Randomização Tratamento com Placebo
~Pro
por
ção
Viv
oSemSem N=312N=312
--PortadoresPortadoresN=166N=166
Curr Probl Cardiol, May 2003
1.00
0.95
0.90
0.85
0.800 500 1000 1500 2000 2500
Tratamento com simvastatina reduz mortalidade em
• 13% em pacientes não apo 4
• 50% em pacientes apo 4
Kaplan-Meier em pctes com e sem o alelo apo4
Dias após randomizaçãoTratamento com Simvastatina
Pro
por
ção
Viv
oSem N=301
4-PortadoresN=187
Curr Probl Cardiol, May 2003
1.00
0.95
0.90
0.85
0.800 500 1000 1500 2000 2500
Alelos da ACE (modulam níveis da ACE em plasma)
• Alelo DD – níveis 2x
• Alelo II – níveis x
• Alelo ID – níveis >x e <2x
Kaplan-Meier e genótipo da ACE
Seguimento em Meses
Sob
revi
vên
cia
de
tran
spla
nta
dos
ACE II (N=69)ACE ID (N=154)ACE DD (N=105)
p = 0.04p = 0.04
Curr Probl Cardiol, May 2003
1.00
0.80
0.60
0.40
0.20
0.000 6 12 18 24 30
Kaplan-Maier em ACE DD e uso de betabloqueadores
Seguimento em Meses
Sob
revi
vên
cia
de
Tra
nsp
lan
tad
os
Beta Bloqueador (N=154)Sem Beta Bloqueador (N=105)
p = 0.007p = 0.007
Curr Probl Cardiol, May 2003
1.00
0.80
0.60
0.40
0.20
0.000 6 12 18 24 30
0 100 200 300 400 500 600 700 800 900 1000
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Tre-164
Ile-164
Ajustado RR = 4.81, p < 0.001
Dias após entrada no estudo
Pro
por
ção
de
sob
revi
ven
tes
Receptor adrenérgico AR - pacientes com ICC
0 6 12 18 24 30 36 42 48 54
Seguimento em meses
% s
em e
ven
tos
1.00
0.80
0.60
0.40
0.20
0.00
Sintase de óxido nítrico endotelial - ICC
Asp=298
Glu-Glu
Adenosina monofosfato deaminase
ATP
ADP
IMP AMP Adenosina
AMPdeaminase
Tempo (anos)0 5 10 15
1.0
0.8
0.6
0.4
0.2
0
Pro
bab
ilid
ade
de
sob
revi
vên
cia
sem
tra
nsp
lan
te
AMPD1 (+/-)/(-/-)
AMPD1 (+/+)
Adenosina monofosfato deaminase - ICC
Tiopurina Metiltransferase
• Polimorfismo TPMT
• Metila mercaptopurina – reduz F
• Leucemia linfocítica aguda
• 10% intermediária – maior toxicidade
• 0.3% não tem TMPT – fatal
• Genotipagem essencial
UDP-glucoronosiltransferase 1A1
• Irinotecan – câncer de cólon, pulmão
• Forma ativa inativada por glucoronidação
• Aumento de 4x a toxicidade
• Genotipagem alelo UGT1a1*28
Gene da colinesterase plasmática
• Apnéia prolongada após succinilcolina
• 1 em 187 em Valencia
• 1 em 3460 europeus
• 1 em 25 x 106 asiáticos
• Complicação facilmente tratada, não há necessidade de genotipagem
Leucemia mielóide crônica
• Translocação no cromossoma Filadelfia• Alterou localização dos genes bcr e abl • bcr-abl tirosina quinase fica ativa• Imatinib bloqueia especificamente• Imatinib 88% resposta positiva em pctes
Câncer de mama
• Herceptin – ab citotóxico contra Her-2/neu.
• Her-2/neu aumentada em 25% pctes
• Herceptina funciona somente nestes pacientes
Substratos para citocromo P4502D6
• -bloqueadores – alprenolol, carvedilol, propranolol
• Anti-arrítmicos – flecainida, mexiletina, propafenona
• Neurolépticos – haloperidol, clozapina, olanzapina, risperidona
• Antidepresssivos – amitriptilina, clomipramina, paroxetina
• Antieméticos – ondansetrona, tropisetrona
• Outros – anfetamina, codeína, debrisoquina, dextrometorfano
Inibidores do citocromo P4502D6
• Neurolépticos – clomipramina, levopromazina, haloperidol
• Antidepressivos – fluoxetina, paroxetina, sertralina
• Antieméticos - metoclopramida
• Anti-histamínicos – clorfeniramina, cimetidina, clemastina, difenilhidramina
• Outros – ritonavir, quinidina, amiodarona
Genótipo do citocromo P4502D6
• Metabolisadores ultrarápidos
• Metabolisadores rápidos
• Metabolisadores lentos
Genótipo do citocromo P4502D6
• Metabolisadores ultrarápidos – muito baixa em orientais (<<1%), baixa em europeus do norte (<1%), 7% em espanhóis, 29% em etíopes
• Metabolisadores rápidos
• Metabolisadores lentos – muito baixa em orientais
Tratamento de náusea e vômito in quimioterapia - Tropisetron
• 42 pacientes, 30% tiveram náusea e vômito
• CitP4502D6 – maior frequência dos demais pacientes
• Genotipagem recomendável – evitaria emese severe em 1/50 pacientes.
Polimorfismo genético (acetiladores rápidos e lentos)
Polimorfismo genético (acetiladores rápidos e lentos)
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20202020
15151515
10101010
5555
0000
0 1 2 3 4 5 6 7 8 9 10 11 120 1 2 3 4 5 6 7 8 9 10 11 120 1 2 3 4 5 6 7 8 9 10 11 120 1 2 3 4 5 6 7 8 9 10 11 12
Concentração Concentração isoniazidaisoniazida ( (g/mL)g/mL)Concentração Concentração isoniazidaisoniazida ( (g/mL)g/mL)
Fre
qu
eên
cia
(nF
req
ueê
nci
a (n
o de
ind
ivíd
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) d
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div
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Fre
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(nF
req
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nci
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o de
ind
ivíd
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) d
e in
div
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Isoenzima Substrato típico Comentários
CYP1A CYP2A CYP2B CYP2C CYP2D CYP2E CYP3A CYP4
Teofilina Testestorona Numerosos Numerosos Debrisoquina Nitrosaminas Nifedipina/ciclosporina Ácidos graxos
Induzida por tabagismo Induzida por tabagismo
Induzido por fenobarbital Apresenta polimorfismo genético Apresenta polimorfismo genético Induzida por álcool Induzida por carbamazepina Induzida por clofibrato
A superfamília do citocromo P450A superfamília do citocromo P450
Diferenças Farmacogenéticas das Enzimas que metabolizam medicamentos
Pseudocolinesterase plasmática
Desidrogenase alcoólica
CYP2C19
CYP2D6
CYP2C?
Acetil-N-transferase
Metiltransferase
Pseudocolinesterase plasmática
Desidrogenase alcoólica
CYP2C19
CYP2D6
CYP2C?
Acetil-N-transferase
Metiltransferase
1 in 30005-10% (approx. 90% em Asiáticos)
5% (approx. 20% em Asiáticos)
5 - 10%
Muito raro
Approx. 60% (approx. 5% em japoneses)
0.5 %
1 in 30005-10% (approx. 90% em Asiáticos)
5% (approx. 20% em Asiáticos)
5 - 10%
Muito raro
Approx. 60% (approx. 5% em japoneses)
0.5 %
Suxametônio (succinilcolina)
Etanol
S-Mefenitoína, omeprazole
Debrisoquina, espartina, metoprolol, dextrometorfan
Fenitoína
Isoniazida, hidralazina, procainamida
6-Mercaptopurina
Suxametônio (succinilcolina)
Etanol
S-Mefenitoína, omeprazole
Debrisoquina, espartina, metoprolol, dextrometorfan
Fenitoína
Isoniazida, hidralazina, procainamida
6-Mercaptopurina
EnzEnzimaimaIncidência de deficiência Incidência de deficiência ou metabolizadores lentosou metabolizadores lentosaa Substratos típicosSubstratos típicos
aa Para caucasianosPara caucasianosaa Para caucasianosPara caucasianos
Metabolism (Biotransformation) of Drugs
Conjugation Reaction
Endogenous Conjugant
Intracellular Sites
Common Substrates
Drug Examples
Acetylation Acetyl-CoA Cytosol -OH, -COOH, -NH2, -NR2, -SH
Clonazepam, dapsone, isoniazid, sulfonamides, valproate
Glutathione conjugation
Reduced form of γ-Glu-Cys-Gly (the most common intracellular thiol)
Cytosol and microsomes
Electrophilic benzyl halides, aliphatic nitrate esters, epoxides, and quinines
Acetaminophen, ethacrynic acid
Gly (amino acid) conjugation
Gly, Glu, others Mitochondria -COOH Benzoic and salicylic acid
Glucoronidation UDPGA (uridine-5’- diphospho-α-D-glucuronic acid
Microsomes Hydroxyl, amino, or sulfhydryl groups
Acetaminophen, codeine, diazepam, disulfiram, ethinyl estradiol, fentanyl galantamine, lorazepam, modafinil, morphine, propanolol, paroxetine, sulfonamides
Methyllation (N-, O-, and S-)
CH3 from S-adeno sylmethionine (SAM)
Cytosol (eg, COMT)
-OH, -NH2, -SH Oxprenolol (N-), clomethiazole and isoproterenol (O-), captopril (S-)
Sulfate conjugation
3’-Phosphoadenosine 5’-phosphosulfate (PAPS)
Cytosol -OH, -NH2, Acetaminophen, ethinyl estradiol, methyldopa, paoxetine, steroids, triamterene
Netter’s Iluustrated Pharmacology – Chapter 1 – Fig. 1.29
CYP3A50%
5%
5%
CYP2C915%
CYPD625%
Other
CYP1A2
Cytochrome P-450
Ribbon model of CYP2C9 isozyme
Netter’s Iluustrated Pharmacology – Chapter 1 – Fig. 1.30
Cytochrome P-450
CYP Substrate1A2 Acetaminophen, antipyrine, caffeine, clomipramine, olanzapine, ondansetron,
phenacetin, rilozole, ropinirole, tamoxifen, theophylline, warfarin
2A6 Coumarin
2B6 Artemisinin, buproprion, cyclophosphamide, S-mephobarbital, S-mephenytoin, (N-demethylation to nirvanol), propofol, selegiline, sertraline
2C8 Pioglitazone
2C9 Carvedilol, celecoxib, fluvastatin, glimepiride, hexobarbital, ibuprofen, losartan, mefenamic, meloxicam, montelukast, nateglinide, phenytoin, tolbutamide, trimethadone, sulfaphenazole, warfarin, ticrynafen, zafirlukast
2C19 Citalopram, diazepan, escitalopram, esomeprazole (S9 isomer of omeprazole), irbesartan, S-mephenytoin, naproxen, nirvanol, omeprazole, pantoprazole, proguanil, propranolol
2D6 Almotriptan, bufuralol, bupranolol, carvedilol, clomipramine, clozapine, codeine, debrisoquin, dextromethorphan, dolasetron, fluxetine (S-norfluoxetine), formoterol, galantamine, guanoxan, haloperidol, hydrocodone, 4-methoxy-amphetamine, metoprolol, mexiletine, olanzapine, oxycodone, paroxetine, phenformin, phenothiazine, propoxyphene, selegiline, (deprenyl), sparteine, thioridazine, timolol, tolterodine, tramadol, tricyclic antidepressants, type 1C antiarrhythmics (eg. encainide, flecainide, propafenone), venlafaxina
Netter’s Iluustrated Pharmacology – Chapter 1 – Fig. 1.30
Cytochrome P-450 (cont.)
CYP Substrate2E1 Acetaminophen, Chlorzoxazone, enflurane, halothane, ethanol (minor pathway)
3A4 Acetaminophen, alfentanil, almotriptan, amiodarone, astemizole, beclomethasone, bexarotene, budesonide, S-bupivacaine, carbamazepine, citalopram, cocaine, cortisol, cyclosporine, dapsone, delavirdine, diazepam, dihydroergotamine, dihydropyridines, dihydropyridines, diltiazem, escitalopram, ethinyl estradiol, fentanyl, finasteride, fluticasone, galantamine, gestodone, imatinab, indinavir, itraconazole, letrozole, lidocaine, loratadine, losartan, lovastatin, macrolides, methadone, miconazole, midazolam, mifepristone (RU-486), montelukast, oxybutynin, paclitaxel, pimecrolimus, pimozide, pioglitazone, progesterone, quinidine, rabeprazole, rapamycin, repamycin, repaglinide, ritonavir, saquinavir, spironolactone, sulfamethoxazole, sufentanil, tacrolimus, tamoxifen, terfenadine, testosterone, tetrahydrocannabinol, tiagabine, triazolam, troleandomycin, verapamil, vinca alkaloids, ziprasidone, zonisamide
27 Doxercalciferol (activated)
No / minimal involvement
Abacavir, acyclovir, alendronate, amiloride, benazepril, cabergoline, digoxin, disoproxil, hydrochlorothiazide, linezolid, lisinopril, olmesartan, oxaliplatin, metformim, moxifloxacin, raloxifene, ribavirin, risedronate, telmisartan, tenofovir, tiludronic acid, valacyclovir, valsartan, zoledronic acid
Netter’s Iluustrated Pharmacology – Chapter 1 – Fig. 1.30
Challenges in Pharmacogenomics
Pharmacogenomics: Challenges and Opportunities - © 2006 American College of Physicians - Ann Intern Med. 2006;145:749-757.
Examples of Associations between Drug Response and Genetic Variants*
Pharmacogenomics: Challenges and Opportunities - © 2006 American College of Physicians - Ann Intern Med. 2006;145:749-757.
Browsing function in PharmGKB. PharmGKB allows users to browse the major classes of data (genetic variation in pharmacogenes, curated literature, drugs associated with genotype, phenotype, pathway or other information, pathways, diseases, and phenotype data files). The number of data objects in each category is displayed, and there is a full-text search capability to allow more focused searching.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
Example of the PharmGKB gene variant browser: nitric oxide synthetase 3 (NOS3).
is involved in the angiotensin and vascular endothelial growth factor (agents inhibiting the vascular endothelial growth factor signaling pathway have been developed as a new class of anticancer agents) pathways and the response to a number of drugs. The genomic DNA is the thick bar, with exons marked in brown. SNPs in PharmGKB are shown above the genomic DNA with a graphical indication of minor allele frequency. The location of SNPs in dbSNP and jSNP are shown below the genomic DNA. The table shows the chromosomal position, with links to the Golden Path genome browser, dbSNP, and with links to detailed information about the alleles, assays, frequencies, and individual-level data.
The Pharmacogenetics Research Network: From SNP Discovery to Clinical Drug Response - VOLUME 81 NUMBER 3 - MARCH 2007
Illustration of tagging SNPs.
The diagram shows five haplotypes. Twelve single nucleotide polymorphisms (SNPs) are localized in order along the chromosome. The letters on the top indicate groups of SNPs that have perfect pairwise linkage disequilibrium (LD) with one another, and the numbers on the bottom indicate each of the 12 SNPs. SNP 9 is the causal variant, which in this simple example determines drug response: allele C results in a therapeutic response, whereas allele G results in an adverse reaction. In this example, the selection of just one SNP from each of the groups A–E would be sufficient to fully represent all of the haplotype diversity. Each haplotype can be identified by just five tagging SNPs (tSNPs), and the causal variant would be tagged even if it were not itself typed (in fact, multi-marker approaches to tSNP selection would reduce the set of tags to fewer than five, but this is ignored for simplicity). So, tSNP profiles that are highlighted predict an adverse reaction to the medicine. Normally, LD patterns are not so clear-cut and statistical methods are required to select appropriate sets of tSNPs. P
HA
RM
AC
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EN
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ICS
GO
ES
GE
NO
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- N
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EV
IEW
S -
GE
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S V
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UM
E 4
- D
EC
EM
BE
R 2
003
Illustration of tagging SNPs.
The diagram depicts the same 12 SNPs, but with different associations among them, as might happen in a different population group. Because patterns of LD are different, some patients would be misclassified if the same five tSNPs were used and interpreted in the same way; that is, using the same SNP profiles as defined in population A, haplotype profiles 1, 2 and 3 are predicted to have allele C at the causal SNP 9 (a therapeutic response), whereas haplotype profiles 4 and 5 are predicted to have na adverse response. However, because the pattern of association has changed, the new haplotypes 6 and 7 are misclassified as haplotype patterns 6 and 7 in population B.
PH
AR
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