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Personalized Medicine - Genomics Maria Judit Molnar 2014.

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1 Personalized Medicine - Genomics Maria Judit Molnar 2014

2 The Personal Genome Project is a long term, large cohort study Aims to sequence and publicize the complete genomes and medical records of 100,000 volunteers, in order to enable research into personal genomics and personalized medicine.personal genomicspersonalized medicine It was initiated by Harvard University in 2005.Harvard University

3 Personal Genome Project The individuals agree to make their genome and their health records public. „volunteers… willing to share their genome sequence and many types of personal information with the research community and the general public, Aim: to understand genetic and environmental contributions to human traits.”

4 The project publish the genotype (the full DNA sequence), genotypeDNA sequence phenotype: medical records, various measurements, MRI images, etc. phenotypeMRI all data are within the public domainpublic domain made available over the Internet so that researchers can test various hypotheses about the relationships among genotype, environment and phenotype.Internetgenotypeenvironmentphenotype

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7 Risks Curiosity may be just suspicion co-opted by endorphins. I had no idea what I was blundering into. But I figured I could start learning now about privacy and public good, research and entrepreneurship, risk and susceptibility – all the dangers of knowing the full story – or I could bump up against them later, along with the rest of unwitting humanity. Richard Powers

8 Dealing with bad news We know what happens to people who do get the worst news. They don’t sink into despair or throw themselves off bridges; they handle it perfectly well. Most of us cope using some combination of denial resignation and religion. Steven Pinker

9 Genotype and phenotype When the connection between the ACTN3 gene and muscle type was discovered, parents and coaches started swabbing the cheeks of children so they could steer the ones with the fast-twitch variant into sprinting and football. Steven Pinker

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11 Some variants predicting severe effects in the PGP-10 Participant VariantPutative effect PGP5 (hu9385BA)PKD1-R4276WAutosomal dominant polycystic kidney disease PGP6 (hu04FD18)MYL2-A13THypertrophic cardiomyopathy PGP9 (hu034DB1)SCN5A-G615ELong QT syndrome PGP10 (hu604D39)PKD2-S804NAutosomal dominant polycystic kidney disease PGP10 (hu604D39)RHO-G51AAutosomal dominant retinitis pigmentosa

12 PGP Canada PGP UK PGP Harward

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14 Risk-Benefit Ratio

15 The roots „ It’s far more important to know what person the disease has than what disease the person has.” Hippocrates (BC. 400)

16 The paradigm of the classic treatments Symptom Diagnosis Treatment Dosage Non specific Non selectiv Uniformized Phenotype Trial and error Does not evaluate the different therapeutic response - the blockbuster concept

17 The medicine in the XX. century „One fits to all” The target is the disease Evidence based medicine – statistical approach using the rule of large numbers, resulting in statistically meaningful conclusions

18 Paracelsus ( ) “The dose makes the poison.” But differently for genetically different individuals The revolution of the molecular biology: Right Disease Right Patient Right Drug Right Time

19 Ineffective therapies – waste money Hypertension Drugs 10-30% ACE Inhibitors $390 million – $1.2 billion Heart Failure Drugs 15-25% Beta Blockers $345 million – $575 million Anti Depressants 20-50% SSRIs $2.3 billion – $5.8 billion Cholesterol Drugs 30-70% Statins $3.8 billion – $8.8 billion Asthma Drugs 40-70% Beta-2-agonists $560 million – $1.0 billion

20 The results in 2013 The most drugs are not or partially effective in the 60% of the treated patients Side effects are responsible for – 100,000 death – 2 million hospitalisations – 100 billion USD cost for healthcare in USA – 50%- of the cases is related genetics

21 Personalized Medicine: The Answer? Definition The use of information and data from a patient’s genotype and phenotype (level of gene expression and/or clinical information) to: – stratify disease – select a medication – provide a therapy – initiate a preventative measure that is particularly suited to that patient at the time of administration

22 Personalized Medicine is an emerging practice of medicine that uses an individual's genetic profile to guide decisions made in regard to the prevention, diagnosis, and treatment of disease Focus on the clinical needs! “Bench to Bedside” “Bedside to Bench to Bedside” However genomic determinate the potential biological and physiological reactions of the individual, we can not miss the analysis of the environmental effects. The bigest weakness of the clinic nowadays is the lack of the exact diagnosis and the inapropriate determination of the stadium of the disease.

23 The classical therapy: Uniformisation ObservationTreatment Uncertain respond Observation Testing (Biomarker) Treatment Predicted respond Targeted therapy: Differenciate, diagnostics and drug co-development Independently from the heterogeneity of the population try to get in large cohorts positiv results/risk ratio with the treatment (clinical utility) Targeted therapies help by identificatioon of the patients with the best respond and less side effects Biomarkers are such diagnostic tools, wich may predict the therapeutic respond to a certain drug

24 Healthcare pressure: Risk / benefit ratio Economical pressure: Cost / benefit ratio New Technologies: Expanding possibilities Needs of highly differentiated healthcare, which effects the health of the person and society Only the really innovative medicine is justified Innovative ~ Personalized, Differentiated The key drivers of the paradigm change in the healthcare

25 The Power of Information - Moore’s law Computer processing power is doubling every 18 months Amount of data is doubling every 18 months Power of technology

26 Technological improvement Genomic revolution of the end of the 20.th century – Completing the Human Genom Project (2000) „Only” 25 thousand genes – vs 100 thousand – Computed genotyping, DNA microarray – „$1000 Genom” „Nobody expected”: – 25thousand genes – 9 million SNP – The function of 30% of the genes is uncleared – The role of deletions, duplications, CNVs – Microsatellite polymorphisms – Epigenetic Forrás: Jose de Leon, Pharm Res 59 (2009) alapján

27 PM impacts diagnostic categories

28 A new era in genomics medicine? Human genome project Direct-to-consumer genomics Intellectual property disputes – Catalona – Myriad Genetics – Henrietta Lacks Personal Genome Project

29 Drug discovery paradigm shift: a problem or an opportunity? Ever increasing demand for safer medicine Stark realization that drug discovery is expensive and slow – shrinking budgets, consolidation, outsourcing Current drug inventory is large, diverse and possibly has a lot more to offer than was initially thought Increasing availability of genomic data and tools to use/understand it

30 Genomic data in the patient care

31 Monogenic vs Complex Disorders

32 Monogenic Disorders: Success story

33 Complex disorders: limited success rate Age related macula degeneration

34 Apolipoprotein E Genotype and Alzheimer Disease Metaanalysis of 40 study patient and control

35 A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline and Alzheimer Disease Thorlakur JonssonThorlakur Jonsson et al. Nature 2012; 488, 96–99 (02 August 2012) doi: /nature11283 A coding mutation (A673T) in the APP gene protects against Alzheimer’s disease This substitution results in an approximately 40% reduction in the formation of amyloidogenic peptides in vitro.

36 The change of disease concept Traditional: reductionist, one single factor Causal factor Disease Basic risk Environmental factors Preclinical progression Disease onset Disease progression Irreversible changes New conception: multifactorial

37 Egészségregyakorolthatás SNP combinations Other SNPsEnvironment Köztes fenotípus Effect on the health Intermedier phenotype Complex, polygenic, multifactorial disease Egészségregyakorolthatás Mutation Other SNPsEnvironment intermediate phenotype Effect on the health Intermedier phenotype Monogenic disease New Disease Concept

38 The old paradigm: Treatment of the disease Diagnosis Select drug Switch drug Switch drug again Time Reactive medical care Disease severity

39 To effective health management ScreeningPredisposition Diagnosis/Prognosis Right Drug Time Efficient medical care Disease severity Monitoring

40 Social expectations Cheaper, more effective drug development Forrás: Business Insights: Expanding Applications of Personalized Medicine, 2009

41 Social expectations

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44 Scruples Healthpolitical questions Regulatory issues Financing aspects Insurance consequence – USA: Genetic Information Nondiscrimination Act (2008) Ethical questions – How to sell the test laymens?

45 FDA prohibited to sell the test

46 What will likely happen?? Personalized medicine will involve pharmacogenomic treatment approaches that transcend the „one-size-fits-all” approach Personalized medicine will focus on keeping people well and treating disease at its earliest stages! Laboratory medicine will lead the way! „Disease signatures” comprised of hundreds or thousands of data point will be the biomarkers of the future Drug companies will develope their markets around interventional treatments for „disease signatures”!!

47 The POTENTIAL for Personalized Medicine A „Wellness” Vision A new comprehensive and integrated approach to wellness – prevention of chronic disease, early detection of disease risk and individualized treatment plans Predictive toxicology for new drug candidates – ability to predict which individuals will benefit and those who might be most at risk for experiencing serious side-effects HealthyPre-diseaseDiseasedRecovering Routine Comprehensive Health Status Monitoring New diagnostics Disease prediction Preventative therapies Earlier disease detection New interventional therapies New diagnostics Accurate disease diagnosis Personalized treatment Informed treatment decisions Real-time Disease Reoccurrence Monitoring People adopting healthier lifestyles Timely testing of environmental exposures Improved economics of disease screening Reduced occupational exposures Timely medical interventions Reduced hospitalizations More timely therapy Reduced unnecessary referrals More efficient treatment plans Improved outcomes

48 The POTENTIAL for Personalized Medicine Increased Healthcare Quality and Reduced Costs (?) Predict and prevent chronic diseases Keep people out of the hospital Eliminate adverse drug events Improve drug development Create new markets

49 The POTENTIAL for Personalized Medicine Transform Healthcare Markets Today HC markets on numbers of sick people might be treated with a new drug Metric Morbidity and mortality rates Outcome People suffer and die from chronic and preventable diseases with multiple hospitalizations Tomorrow HC markets based on numbers of people with preventable diseases Metric Number of people positive for valid predictive biomarkers Outcome New era of interventional therapeutics People will live healthier, pain- free lives and die of old age or trauma with minimal hospitalizations Multiplex biomarkers to predict and guide treatment of early chronic Dz

50 We Can’t do This Now!!

51 Current Personalized Medicine Approaches Limited To: Pharmacogenomics Electronic Health Records Great Start – But does not yet address the all technologies required for prediction and prevention

52 State of the Art in HC Measurement Technologies Despite Major Progress over the Last 25 Years, Healthcare Measurement Technological Capabilities is Limited to: Digitalizing medical records Measuring a few serum biomarkers Identifying simple genetic defects/differences Imaging gross anatomical features and detect major changes Imaging some disease-associated molecular mechanism Comparing mRNA expression patterns between healthy and diseased cells Statistical analysis of research for evidence-based medicine

53 The Personalized Medicine Gap The lack of adequate measurement technology limits the vision for personalized medicine We simply do not have the tools to measure the biochemical details of the human body with the resolution needed to fully-realize the amazing potential of personalized medicine

54 Need to Know the Root Cause of Chronic Disease But… Human Cells are Extremly Complex

55 Diseases are the result of perturbations in complex biomolecular networks

56 Prevention BRCA1/2 - Breast and ovarian tu. prophyilactic tamoxifen and surgery Effectivity Oncology Herceptin – breast cancer Cetuximab – colon tumor Rare disease: cystic fibrosis Ivacaftor G551D mutation in CFTR gene Safety VKOR/CYP2C9 – warfarin dosing PM in the clinical practice

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58 Multiplex Tests are Already Starting to Have an Impact OncoType DX Analyzes by qPCR, mRNA expression of a panel of 21 genes within a tumor to determine a Recurrence Score MammaPrint Microarray-based prognostic breast cancer mRNA expression profiling test of 70 genes AlloMap qPCR-based expression profile of 11 genes to assist physicians in managing heart transplant patients for potential organ rejection Tissue of Origin Microarray technology considers 15 common malignant tumor types, including bladder, breast,and colorectal tumors based on mRNA expression on 1,550 genes

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60 A kihivások

61 New Technologies for Determination of „Disease Signatures ” Changes in biomolecular networks indicative of the onset or progression of disease Normal Human System 100 trillion cells 6 billion basepairs 30,000 genes 10 million different proteins 100,000’s of molecular events 50 organs and organ systems ABNORMALITIES Multiplex Measurements Computer Integration Cell- or Tissue- specific Disease Probablity Score Increased Drug Pipeline Improved Diagnostics New Predictive Biomarkers Decrease Adverse Events Improve Clinical Outcome Fewer Errors & Misdiagnoses Predict Disease Onset Prevent Disease Reduce Health Care Costs Discovery Decisions Clinical Decisions

62 Changes due to P4 Medicine More innovative, patient-centered, proactive medicine that will be predictive, preventive, personalized and participatory rather than reactive The role of physician is changing Patients increasingly need „coaches” to help them dealing with complexity of „data clouds”, monitor their health and wellness Broadening the definition of patient (not only limited to thick persons) Social media and e-health will influence the healthcare

63 Fears from the P4 Payer: increasing expenses? Physician: decreasing margin? Patient: certain drugs are inaccessible? Authorities: how to deal the complex situation? Diagnostic lab: more test with bed financing? Industry: – Narrowing market? – New financing strategy? ?

64 Too soon for conclusions New ideas about self, privacy, medicine, and freedom Ethics

65 Conclusion We tend to overestimate the effect of technology in the short run and underestimate the effect in the long run Amara’s Law Figuring out how to use that information to improve your medical care is personalized medicine's next great challenge

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