1. e-PGA: an integrated electronic Pharmacogenomics Assistant for Personalized Medicine
K. Lakiotaki1, E. Kartsaki1, A. Kanterakis1, T. Katsila2, G. P. Patrinos2, G. Potamias1
1Institute of Computer Science, Foundation for Research & Technology – Hellas, Heraklion, Crete
2Department of Pharmacy, University of Patras, Hellas
The Clinical Problem
eMoDiA: electronic Molecular Diagnostic Assistant
Pharmacogenomics (PGx) holds promise to personalize medical interventions by determining genetic influence in drug response and enabling tailor-made drug prescription according to an individual’s genetic makeup.
I am about to prescribe fluoropyrimidine to a patient who is Poor Metabolizer of this drug. Are there any recommendations?
Integrates heterogeneous PGx information from several valid PGx resources (PharmGKB, Ensembl …)
Offers automated personalized PGx translation (genotype-to- phenotype) services
Provides a user friendly interface for submitting newly discovered PGx related gene- variants and alleles
Motivations. Drug response varies among individuals, ranging from expected beneficial effects to adverse reactions and sometimes to even fatal events Different populations carry different profiles of rare and common genetic variants.
Towards Population Pharmacogenomics (PPGx):
What do SNPs tell us about drug response?
In this work we study how 65 pharmacogenes - genes enabled in the absorption, distribution, metabolism, excretion and toxicity (ADMET) of drugs - and their variants (508 SNP biomarkers) vary among 2504 genomes across 26 populations.
Start with at least a 50% reduction in starting dose followed by titration of dose based on toxicity or pharmacokinetic test
Patient
eMoDiA: From Genotype to Phenotype to Recommendations
eMoDiA: Translation Service
eMoDiA: Explore Service
Methodology. We developed a genotype to phenotype translation algorithm, which infers metabolizer phenotypes from individual genetic (SNP) profiles. For each pharmacogene, and based on available (PharmGKB) haplotype/allele tables, an individual’s genotype-profile is matched against the available gene-alleles. Next, each inferred allele is assigned to a metabolizer phenotype, according to available “look up” tables. [the algorithm was verified with the Affymetrix© DMET Plus respective translation results]
PGx Variation among 1kG Populations
ABCB1
ABCC2
South Asian Ancestry (SAS): 19%
African Ancestry (AFR): 26%
European Ancestry (EUR): 20%
Americas Ancestry (AMR): 19%
East Asian Ancestry (EAS): 20%
65 pharmacogenes, 508 SNPs, 328 haplotypes found in 1kG samples
22 core PharmADME genes (4 Transporters, 12 Phase I, 6 Phase II), 26 extended PharmADME genes (1 Transporter, 2 Modifiers, 9 Phase I, 14 Phase II)
15/65 included in FDA’s Pharmacogenomic Biomarkers in Drug Labeling
ACB
GWD
ESN
MSL
YRI
LWK
ASW
CHS
CDX
KHV
CHB
JPT
PJL
BEB
STU
ITU
GIH
GBR
FIN
IBS
CEU
TSI
PUR
CLM
PEL
MXL
The 1000 Genomes (1kG) Project aims to provide a deep characterization of human genome sequence variation.
2504 individuals from 26 populations
Total variant sites ~80M
Chr: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 X
phGenes
phGenes matched to heterozygous or homozygous variant haplotypes
AFR
AMR
EAS
EUR
SAS
SLC25A27
UGT1A10
UGT2B15
CHRNA5
CYP2A13
CYP2C19
CYP3A43
CYP4A22
SLC22A1
SLCO1B1
SULT1A2
SULT1C2
SULT2A1
SULT4A1
CYP1A1
CYP2W1
ADRB1
CYP1A2
CYP1B1
CYP2A6
UGT1A8
UGT1A9
ADRB2
CYP2B6
CYP2C8
CYP2C9
CYP2D6
CYP2E1
CYP2F1
CYP2R1
CYP2S1
CYP3A4
CYP3A5
CYP3A7
CYP4B1
CYP4F2
HMGCR
P2RY12
SCNN1B
UGT1A1
UGT1A3
UGT1A4
UGT1A5
UGT1A6
UGT1A7
VKORC1
ABCB1
ABCC2
IGFBP3
PIK3CA
BRCA1
COMT
HTR2C
SCN1A
SCN5A
APOE
DPYD
CFTR
G6PD
NAT1
NAT2
TPMT
CDA
DDC
LDLR
Potential abnormal metabolism in most phGenes
CYP2D6
CYP2C19
NAT2
CYP2B6
: statistically significant phenotypic difference among populations in 29 genes
CYP2C19-a liver enzyme that acts on 10-15% of drugs in current clinical use, including the antiplatelet clopidogrel (Plavix)-haplotypes, are matched to only 5 individuals assigning a V/V phenotype (although phSNP coverage is 78%). Same holds for 2 individuals in NAT2, a gene encoding an enzyme that functions to both activate and deactivate arylamine and hydrazine drugs and carcinogens (phSNP coverage is 63%).
R/R: combination of 2 wild type haplotypes =>normal metabolic status
R/V: a combination of 1 wild type and 1 variant haplotype =>intermediate metabolic status
V/V: a combination of 2 variant haplotypes=>poor or ultra-rapid metabolic status
Abnormal metabolism
Population Pharmacogenomics Analysis
Conclusions
We adequately (sample coverage>90%) assigned PGx phenotypes in 33 out of 65 pharmacogenes.
We found statistically significant phenotypic difference among 1kG populations in 29 pharmacogenes
EAS
AFR
EUR
AMR
PEL
SAS
PharmacoSNP allele frequencies reflect population structures
The PEL population diverges from its relevant ancestral region (AMR)
Population of African Ancestry, South and East Asian Ancestry can be accurately clustered
Populations of Americas Ancestry are not easily differentiated from European Ancestry populations
GBR
IBS
PCA
IBS
FIN
TSI
PUR
PJL
GIH
Component 2
CLM
ACB
ASW
ITU
STU
CHB
GWD
JPT
LWK
MXL
BEB
CDX
MSL
YRI
ESN
CHS
KHV
PEL
Component 1
The reported work was funded by the eMoDiA (electronic Molecular Diagnostics Assistant) project (11SYN_10_145)
under the "Competitiveness and Entrepreneurship» (OPCE ΙΙ; Greek-EU) operational program
Contact:
George Potamias