An Introduction to Genomics, Pharmacogenomics, and Personalized Medicine Michael D. Kane, PhD Associate Professor, University Faculty Scholar, Graduate Education Chair Department of Computer and Information Technology College of Technology & Lead Genomic Scientist, Bindley Bioscience Center at Discovery Park Purdue University West Lafayette, Indiana Bioinformatics.tech.purdue.edu

DNA is Information Storage Introduction to Genomics

“Zipped Files” Decompression “Executable Files”

CAGGACCATGGAACTCAGCGTCCTCCTCTTCCTTGCACTCCTCACAGGACTCTTGCTACT CCTGGTTCAGCGCCACCCTAACACCCATGACCGCCTCCCACCAGGGCCCCGCCCTCTG CCCCTTTTGGGAAACCTTCTGCAGATGGATAGAAGAGGCCTACTCAAATCCTTTCTGAG GTTCCGAGAGAAATATGGGGACGTCTTCACGGTACACCTGGGACCGAGGCCCGTGGTC ATGCTGTGTGGAGTAGAGGCCATACGGGAGGCCCTTGTGGACAAGGCTGAGGCCTTCT CTGGCCGGGGAAAAATCGCCATGGTCGACCCATTCTTCCGGGGATATGGTGTGATCTTT GCCAATGGAAACCGCTGGAAGGTGCTTCGGCGATTCTCTGTGACCACTATGAGGGACTT CGGGATGGGAAAGCGGAGTGTGGAGGAGCGGATTCAGGAGGAGGCTCAGTGTCTGAT AGAGGAGCTTCGGAAATCCAAGGGGGCCCTCATGGACCCCACCTTCCTCTTCCAGTCC ATTACCGCCAACATCATCTGCTCCATCGTCTTTGGAAAACGATTCCACTACCAAGATCAA GAGTTCCTGAAGATGCTGAACTTGTTCTACCAGACTTTTTCACTCATCAGCTCTGTATTCG GCCAGCTGTTTGAGCTCTTCTCTGGCTTCTTGAAATACTTTCCTGGGGCACACAGGCAA GTTTACAAAAACCTGCAGGAAATCAATGCTTACATTGGCCACAGTGTGGAGAAGCACCG TGAAACCCTGGACCCCAGCGCCCCCAAGGACCTCATCGACACCTACCTGCTCCACATG GAAAAAGAGAAATCCAACGCACACAGTGAATTCAGCCACCAGAACCTCAACCTCAACA CGCTCTCGCTCTTCTTTGCTGGCACTGAGACCACCAGCACCACTCTCCGCTACGGCTTC CTGCTCATGCTCAAATACCCTCATGTTGCAGAGAGAGTCTACAGGGAGATTGAACAGGT GATTGGCCCACATCGCCCTCCAGAGCTTCATGACCGAGCCAAAATGCCATACACAGAGG CAGTCATCTATGAGATTCAGAGATTTTCCGACCTTCTCCCCATGGGTGTGCCCCACATTG TCACCCAACACACCAGCTTCCGAGGGTACATCATCCCCAAGGACACAGAAGTATTTCTC ATCCTGAGCACTGCTCTCCATGACCCACACTA

THEREDCAT_HSDKLSD_WASNOTHOTBUT_WKKNASDN KSAOJ.ASDNALKS_WASWET_ASDFLKSDOFIJEIJKNAW DFN_ANDMAD_WERN.JSNDFJN_YETSAD_MNSFDGPOIJ D_BUTTHEFOX_SDKMFIDSJIR.JER_GOTWET_JSN.DFOI AMNJNER_ANDATEHIM.

Start with a thin 2 x 4 lego block… Add a 2 x 2 lego block… Add a 2 x 3 lego block… Add a 2 x 4 lego block…

organismestimated size estimated gene number average gene density chromo -some number Homo sapiens (human) 3200 million bases~30,0001 gene per 100,000 bases46 Rattus norvegicus (rat) 2750 million bases~30,0001 gene per 100,000 bases42 Mus musculus (mouse) 2500 million bases~30,0001 gene per 100,000 bases40 Drosophila melanogaster (fruit fly) 180 million bases13,6001 gene per 9,000 bases8 Arabidopsis thaliana (plant) 125 million bases25,5001 gene per 4000 bases5 Caenorhabditis elegans (roundworm) 97 million bases19,1001 gene per 5000 bases6 Saccharomyces cerevisiae (yeast) 12 million bases63001 gene per 2000 bases16 Escherichia coli (bacteria) 4.7 million bases32001 gene per 1400 bases1 H. influenzae (bacteria) 1.8 million bases17001 gene per 1000 bases1 The onion genome is 6-times bigger that the human genome The lily genome is 30-times bigger that the human genome

GenBank Data YearBase PairsSequences , ,274,0292, ,368,7654, ,204,4205, ,615,3719, ,514,77614, ,800,00020, ,762,58528, ,179,28539, ,947,42655, ,008,48678, ,152,442143, ,102,462215, ,939,485555, ,972,9841,021, ,160,300,6871,765, ,008,761,7842,837, ,841,163,0114,864, ,101,066,28810,106, ,849,921,43814,976, ,507,990,16622,318, ,553,368,48530,968, ,575,745,17640,604, ,037,734,46252,016, ,019,290,70564,893, ,874,179,73080,388, ,116,431,94298,868,465 In 2008 a new gene sequence was uncovered every 1.7 seconds! …equivalent to 483 DNA base pairs every second of every day!

DNA contains “Genes” (i.e. “blueprint for living systems on earth) “Genes” are the ‘coding’ information to make “Proteins” Proteins are the functional units of life…enzymes, structures, etc., etc., etc.,… (i.e. the bricks, mortar, steel, hinges, cables, motors, etc.) ( )( )( )( ) gene Example: Hemoglobin

Single Nucleotide Polymorphisms (SNPs) are simple changes (or differences) in the DNA sequence that appear to have little or no impact on human health. They represent 90% of all human genetic variations. Genetically similar to a mutation, but distinct in that a SNP is not causal to a clinical disease or disorder (or at least not yet causally linked, and not really applicable to ages >40 yrs old). Across the human genome we average approximately 1 SNP for every 300 base pairs of DNA (over one million known SNPs that occur at a frequency of 1% or higher in the world population). Important Consideration: Inheritance The appearance of deleterious mutations during evolution tend to NOT be inherited for obvious reasons, at least those that affect growth, reproduction and viability. …and our modern existence is the result of millions of years of tolerated (and occasionally beneficial) changes in our genome, which is most often evident in what we can and cannot eat or consume (think: evolutionary pressure & natural selection) Monomethyl Hydrazine (in “False” Morel Mushrooms)Tylenol: Acetaminophen (Cats?) (many examples of “toxins” in nature, many of them are presumably synthesized to prevent consumption or predation of the host plant or organism) Introduction to PharmacoGenomics Modern drug discovery & development falls outside the tolerances & toxicity that have resulted from evolution, because most of these compounds have NEVER been seen in nature.

Introduction to PharmacoGenomics When you ingest a drug, the drug is absorbed into the circulatory system and is distributed throughout the body. The drug is then available to carry out its intended ‘mechanism of action’ (MOA). In the case of WARFARIN, it inhibits Vitamin K Epoxide Reductase Complex 1 (VKORC1), and reduces blood clotting. It is the largest selling anticoagulant in the world, and the leading case in support of Personalized Medicine”. Subsequently, the body has the ability to eliminate the drug from the body through “drug metabolism”, which is primarily carried out in the liver. WARFARIN is metabolized primarily by the oxidative liver enzyme CYP2C9, which basically adds an oxygen group to the WARFARIN structure thereby inactivating its MOA and increasing its likelihood of elimination from the body via the kidneys (urine). For this reason, drug tests that utilize urine a sample source often look for the “metabolite” of the drug in the urine, rather than the ingested drug. IMPORTANT: If you are prescribed WARFARIN, you have a condition that generates potentially life-threatening blood clots. If you are dosed with too much WARFARIN you could die from complications due to internal bleeding, yet if you are dosed with too little WARFARIN you may be in danger of serious consequences due to circulating embolism.

The “ideal” dosing curve for WARFARIN Drug Plasma Concentration vs. Time Minimum effective plasma concentration Minimum toxic plasma concentration

WARFARIN MOA: VKORC1 - Inhibition to prevent blood clotting METABOLISM:CYP2C9 – Removable from the body What would happen if there was a SNP in the gene for VKORC1 that (1) did NOT affect the clotting cascade, yet altered the protein enough to prevent WARFARIN binding and inhibition? The drug is present in the patient, but NOT effective in patients that have this specific SNP! RESULT: Excessive blood clotting and circulating emboli. It is estimated that SNPs in VKORC1 are responsible for 15-30% of variability in WARFARIN therapy.

WARFARIN MOA: VKORC1 - Inhibition to prevent blood clotting METABOLISM:CYP2C9 – Removable from the body What would happen if there was a SNP in CYP2C9 that reduced the rate of drug metabolism and elimination of WARFARIN? The drug dosing curve would be elevated due to decreased metabolism and clearance of the drug from the body. RESULT: Increased risk of complications due to internal bleeding, associated with WARFARIN overdosing. There are 2 different SNPs in CYP2C9 that decrease WARRAFIN metabolism, occurring in 7% and 11% of the population, respectively.

Introduction to Personalized Medicine It is estimated that up to 50% of variability in WARFARIN therapeutics and effectiveness are due to the presence of genetic variations (SNPs) in the genome. This is certainly true for most other prescription drugs on the market, in light of variability that we all are familiar, such as decreased compliance, drug-drug interactions, certain drugs are more effective in some people, etc. PERSONALIZED MEDICINE: using clinical genotyping to identify which drugs (and drug doses) are most safe and most effective in an individual, by identifying which SNPs that patient harbors (if any) that can be used to predict the patient’s response to a prescribed drug. Missense mutations with functional effects mapped in the crystal structure of human CYP2C9 protein bound with warfarin (PDB: 10G5). S-warfarin and heme are shown in the skeleton model with pink and red, respectively. Amino acid residues are shown in the sphere mode with colors.

Introduction to Personalized Medicine APPLIED GENOMICS: Personalized Medicine vs. Diagnostics/Prognostics Modern healthcare can utilize the DNA testing as a means to determine an individual’s risk for developing certain diseases (i.e. Diagnostics and Prognostics), but this use of clinical genotyping is associated with serious legal, ethical and business hindrances. GINA: The Genetic Information Non-discrimination Act (passed into law May 21, 2008, effective Nov 21 st, 2009). Personalized Medicine applies the methods of clinical genotyping ONLY to genetic markers associated with drug safety and drug efficacy, these markers are NOT associated with disease. Furthermore, the practice of personalized medicine will significantly decrease adverse drug responses in the population (one of the top ten causes of death in the US), thereby making pharmacotherapeutics safer, and prevent the removal of beneficial drugs from the market. Therefore personalized medicine is supported by a viable ‘value proposition’ to benefit pharmaceutical companies, healthcare insurers, and healthcare consumers.