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Sequence Polymorphisms   & Personalized Medicine Unit 6

Sequence Polymorphisms   & Personalized Medicine Unit 6. BIOL221T : Advanced Bioinformatics for Biotechnology. Irene Gabashvili, PhD igabashvili@yahoo.com. Pharmacogenomics - Study of genetic variation underlying differential response to drugs.

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Sequence Polymorphisms   & Personalized Medicine Unit 6

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  1. Sequence Polymorphisms   & Personalized MedicineUnit 6 BIOL221T: Advanced Bioinformatics for Biotechnology Irene Gabashvili, PhD igabashvili@yahoo.com

  2. Pharmacogenomics - Study of genetic variation underlying differential response to drugs

  3. Complexity of Finding Gene Variations that affect drug responses • SNP (single nucleotide polymorphism) are common DNA sequence variations that occur when a single nucleotide (A,T,C,or G) in the genome sequence is altered, at 1% or higher frequency in the population. • Millions of SNPs must be identified and analyzed to determine their involvement (if any) in drug response. • Multi-gene interactions • Gene-environment interactions • Further complicating the process is our limited knowledge of which genes are involved with each drug response.

  4. Limited Drug Benefits • 5 to 10 percent of people from Mediterranean and African ancestry lack the glucose-6-phosphate dehydrogenase enzyme and thus risk breakdown of red blood cells from more than 200 drugs. • Less than 5 percent of patients in breast cancer and Alzheimer’s are caused by genetic burden. • Only ~10% of NSC lung cancer patients (15-30) will benefit from NSCLC drugs Tarceva and IRESSA • No population group is homogeneous. • Even if drugs are developed, few people benefit.

  5. Genetic Variation • Few genotypes predict patients drug handling with high fidelity. • Rare variants (frequency of less than 1%) cannot account for high proportion of frequently occurring ADRs • The presence of a polymorphism associated with altered drug handling is usually not a powerful predictor of the outcome. • Example, the genetic test for exon 26 of the MDR gene is not a powerful predictor for low activity of the membrane p-glycoprotein. (Because sometimes these genes will give the same amino acid sequence)

  6. Environmental factors • Differences in the function of enzymes or proteins that affect drug handling may result from non genetic modification which might be influenced by other drugs or other exogenous factors • Example, cholesterol level is affected by diet and exercise. • Cholesterol is also high during pregnancy. Women should wait at least six weeks after the baby is born to have cholesterol measured. • Genetic or environmental……?

  7. False (+) or False (-) • Giving therapy when not needed based on genetic testing revealing false tests • Unless genetic variant is highly predictive of altered drug handling, the test for variance will not have clinical significance • Even for well established risk of polyneuritis in isoniazid users who are slow acetylators, the predictive value of testing is rather weak • Breast cancer therapy, false positives and false negatives

  8. Gene-Gene Interaction • Some mutations will not alter drug handling unless mutations in genes at other loci are simultaneously present. • “Black or white” • No quality ranking, either have it or don’t • Hard to base therapy…

  9. Research in large populations • Many of the trials would recruit only patients with favorable pharmacogentic profile in order to make the trials smaller and faster. • Problem: You do not get a full range of results for people who do not have “ideal” genetic profiles. • In phase III testing there is even more reduction of sample size so less adverse reactions observed. • Opposed to large populations where highly variable population so almost all adverse drug reactions observed • BIG BIAS !!!!

  10. www.pharmgkb.org

  11. PGx Flow

  12. PharmGKB, in brief. • Mission: aggregate, integrate & annotate PGxdata and knowledge • Main resources: (Statistics as of Fall-2006) • 232 genes with detailed genotypes • 1600+ published gene-drug associations • 37 Annotated PGx Pathways • 16 “VIP Gene & variant” summaries • 44K unique IP visitors in 10/06 • Google referrals predominantly drugs (30%) • Referred from drug resources (15%) • Referred from gene resources (10%) • Direct links (30%) • Misc (15%)

  13. Core contents

  14. Whole Genome Data

  15. Literature annotations & Publication Links • Literature Annotations • PharmGKB curators create data entries that associate genes with drugs and phenotypes, based on an interpretation of the literature. They encode with controlled vocabularies. • Publication Links • Scientists can upload phenotype files (all formats) at the time of submission of publications • PharmGKB ID numbers provided in advance to cite in manuscripts

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