Genetica umana - farmacogenetica

Genetics and Drug Efficacy

GENETICS RESPONDERS GENETICSVARIABILITY ImprovingChoosing Better PredictingEarlythe Best Understanding Efficacy andDecisionTargets of Our Targets SafetyMaking.Goal: use geneticsto broaden drug’stherapeutic indexEfficacy: % patients cured at a given doseToxicity: % patients exhibiting side effectsat a given doseTherapeutic index: Dose range at whichdrug shows highest efficacy and lowtoxicity

Drug Efficacy in anIndividual Patient

Drug Efficacy in PatientPopulation

Drug Toxicity forIndividual Patient

Drug Toxicity in PatientPopulation

Unsafe drug: small window

Therapeutic window

genetic info to enhance the therapeutic index (TI)

Dose (mg/kg) 0 1 2 3 4 5 6 7 8 9

TI without pharmacogenomics

Patient 1

Patient 2

Patient 3

Patient 4

Patient 5

Patient 6

TI with pharmacogenomics

What are the steps for translating pharmacogenomic information from research into practice?

Step 1. Identify SNPs in genes relevant to drug efficacy or toxicity

Human Genome: 2,900,000,000 billion total base pairs

10,000,000 total single nucleotide polymorphisms (SNP)

300,000 variant haplotypes

10,000 haplotypes in pharmacologically-relevant genes

Step 2. Retrospectively, find SNPs associated with response

SNP: single nucleotide polymorphism

ATGCTTCCCTTTTAAA

Patient 1 Good response

No response ATTGTTCCCTTTTAAA

Patient 2 No response

ATTGTTGCCTTTTAAA

Patient 3 Good response

Good response ATGGTTGCCTTTTAAA

Patient 4 No response

ATAGTTGCCTTTTAAT

Patient 5 No response

ATAGTTGCCTTTTAAT

Patient 6 Good response

Good response ATGATTGCCTTTTAAA

Patient 7 Good response

Good response ATGATTGGCTTTTAAA

Patient 8 Good response

Good response

ATGTTTCGCTTTTAAAPatient 9 Good response

ATGTTTTGCTTTTAAAGood responsePatient 10 No response

ATTTTTTGCTTTTAAAPatient 11 No response

ATCTTTTGCTTTTAAAPatient 12 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Step 3. Prospectively, determine if those SNPs affect therapeutic outcome

GG GG GGGGGGGGGGGG Treat

GG GGGGGGGG25% cure 50% cure

Determine statistical significance (the probability that such a difference is due to random chance)

Clinical significance of DME polymorphism (1)

Plasma concentrations in the different CYP2C19 genotype after omeprazole 20 mg dosing Clin Pharmacol Ther 1999;65:552-561.

Omeprazole is mainly metabolized by CYP2C19. Distinct differences in plasma concentration are observed between CYP2C19 genotypes.

DME: drug metabolizing enzyme; EM: extensive metabolizers; PM: poor metabolizers

Clinical significance of DME polymorphism (2)

Median data on 24-hour intragastric pH profiles in the different CYP2C19 genotype after omeprazole 20 mg dosing

PK difference between CYP2C19 genotype

PD difference

Pharmacol Ther 1999;65:552-561.

Genotype is required to rationalize the dosing

PK: pharmacokinetics, PD: pharmacodynamics

Ideal flow considering PK-related polymorphism

No No necessity

Non-clinical Suggested genetically variability in PK to consider genotype large small

Clin Pharm PK comparison

Studies between genotypes Genotype data Δsmall Δlarge collection as

Exploratory Dosage regimen demographics & by genotype, etc.

Confirmatory Studies Population PK/PD: genotype

To confirm Genotyping as covariate utility of is useful? genotyping Yes No No necessity

•Product Dosage regimen by genotype to consider Launch

•Pharmacogenomics-oriented TDM genotype

Polymorphic drug metabolizing enzymes

Drug metabolizing enzymes for β-blocker

Drug metabolizing β-blocker enzymes metoprolol CYP2D6

bisoprolol CYP2D6/3A4/1A2

carvedilol

Effect of CYP2D6*10 allele on PK of S-metoprolol

500 (nM) CYP2D6* 10/ * 10

400 plasma

300 in Concentration

200

100 2D6* 1/ * 10 0 2 4 6 8 10 12 14 Time (hr)

Clin Pharmacol Ther 1999;

65 : 402-407

Chronic Heart Failure (CHF) β blocker responder non-responder

CAUSES:

Plasma Concentration Polymorphisms of β blocker Drug Metabolizing Enzyme

Function of Target Polymorphisms Molecules of β blocker Adrenergic Receptor (AR) and Target Molecules

β AR Ser49Gly and Risk in CHF

1 △Ser49 homozygotes without β-blockers (n=63)

▲Gly49 variant without β-blockers (n=28)

☆Ser49 homozygotes with β-blockers (n=59)

60 ★Gly49 variant with β-blockers (n=33)

△β-blocker is more effective％)( in Patients with Gly allele p = 0.12 end-point

40 ☆▲ p = 0.016 of 20 Risk ★0 0 2 53 41 Follow-up (years)

Eur Heart J 2000;21:1853-8.

β Adrenergic Receptor 2 polymorphism Ratio of Responders

Gln/Gln 26%

Gln/Glu Glu/Glu 62%

Gln27Glu is a potential determinant for the response to carvedilol in heart failure

Kaye DM et al. (2003) Pharmacogenetics 13: 379-382

Scientific Basis for Using Pharmacogenomics to Rationalize Dosing

• Top 27 drugs more frequently cited in

reports– 59% (16/27) metabolized by at least one enzyme having poor metabolizer (PM) genotype– 38% (11/27) metabolized by CYP 2D6• mainly drugs acting on central nervous and cardiovascular systems

Phillips et al. (2001) JAMA, 286 (18): 2270-2279

Summary of CYP2D6 activity

Genetica della malattia cardiovascolare

Dati in parte della British Heart Foundation

Heart disease statistics

• Leading cause of premature death in UK– Deaths under 75, 39% of men, 30% of women
• 270,000 heart attacks per year– 43% fatal within 28 days, 32% within 24 hours

350 UK00 300,0 Germany0 250

Sweden USA0/1 200sth Italy150ae France100D Japan500

Mortality from CVD and CHD in selected countries

Rate per 100,000 population (Men aged 35 –74 years)

CVD deaths CHD deaths

1500 1000 500

Russia Poland Finland New England/ USA Italy Spain Japan

Zealand Wales (Adapted from 1998 World Health Statistics)

Genetics of CVD

• Positive Family History– 7-fold increase in mortality in first degree relatives of CAD patients compared with control subjects
• Families share environment as well as genes
• CAD is not a monogenic trait– rare exceptions involving mutation of genes e.g. LDL receptor, apolipoprotein B

Sibling recurrence rate (λ ) for CVDs

• CHD (MI<55yr) =4
• Hypertension = 2.5
• TEXTBOOKIDDM = 15
• Cystic fibrosis = 500
• λ = 2 to 12 (premature CHD)
• RANGE IN LITERATURE sλ = 3 (fatal CHD <65yr)
• DZTλ TWINS
• Male = 7 ; Female = 15 (fatal CHD <65yr)
• MZT (Marenberg NEJM 1994) Female > Male

HERITABILITY Early > Late disease

What is a heart attack?

Blockage of the

Coronary arteries, preventing bloodflow and hence oxygen delivery to heart muscle

Atherosclerosis in vivo

Angiogram

What causes a heart attack ?

Atherosclerosis - slow build up of cholesterol, smooth muscle1. cells and macrophages in cells of arterial walls, may eventually cause ANGINA

Plaque rupture - plaque weakens and tears

Thrombosis - clot forms on the exposed surface of ruptured plaque, repairs damage or...

Clot blocks the already narrowed artery, blood cannot flow, noO delivery to tissue, ischemia - heart attack/stroke/thrombosis2

Clinical manifestations of atherosclerosis

Coronary heart disease

- Angina pectoris, myocardial infarction, sudden cardiac death

Cerebrovascular disease

- Transient ischaemic attacks, stroke

Peripheral arterial disease

- Intermittent claudication, gangrene

Factors contributing to heart disease

Diabetes

Obesity

Inflammation

Infection

Atherosclerosis

Dyslipidemia

Vessel wall Plaque

integrity Thrombosis and rupture