Personalized medicine lecture biochem2013Presentation Transcript
Personalized Medicine Personal Omics Profiling forMapping Healthy and Disease States Hanan H. Fouad Professor of Medical BiochemistryFaculty of Medicine Cairo University
Personalized medicine exploits thebenefit from the combination of genomicinformation with the global monitoring ofmolecular components andphysiological states.
Integrated Personal Omics Profiling (iPOP)analysis, integrate genomic, transcriptomicproteomic, metabolomic, autoantibodyomic information.These fields require in-depth knowledge in BIOINFORMATICS longitudinal personal omics profiling can relate genomic information to globalfunctional omics activity for physiological and medical interpretation of healthy and disease states
Positive Effect on Healthcare• Stratify patients for proper management strategy• Predict the risk of developing a disease at the genetic level• Predict the risk of recurrence of a disease• Understanding the pathophysiology help to develop proper preventive strategy protocols
• Better diagnoses and earlier interventions. Molecular analysis could determine precisely which variant of a disease a person has,• Or whether an individual is susceptible to drug toxicities, to help guide treatment choices
• Molecular analysis could also help select patients for inclusion in, or exclusion from, late stage clinical trials.• Better understanding of genetic variations could help scientists identify new disease subgroups or their associated molecular pathways, and design efficient drugs that target them
With the advancement of many new technologies,it is now possible to analyze upward of 105molecular constituents.• DNA microarrays have allowed the subcategorization of lymphomas and gliomas• RNA sequencing (RNA-Seq) has identified breast cancer transcript isoforms• Transcriptome and RNA splicing profiling are powerful, when combined with genomic, proteomic, and metabolomic data provide a much deeper understanding of normal and diseased states
serpin peptidase inhibitor, clade A (alpha-1antiproteinase, antitrypsin), member , SERPINA1mutation leads to emphysema and liver disease• Damaging mutation in TERT, associated with acquired aplastic anemia, telomerase reverse transcriptase• GCKR glucokinase (hexokinase 4) regulator mutation leads to susceptibility to MODY form of DM• KCNJ11, potassium inwardly-rectifying channel, subfamily J, member , Defects in this gene may also contribute to autosomal dominant non-insulin- dependent diabetes mellitus type II (NIDDM), transient neonatal diabetes mellitus type 3 (TNDM3), and permanent neonatal diabetes mellitus (PNDM).
SLC22A1 solute carrier family 22(organic cation transporter), member 1VKORC1 – vitamin K epoxide reductase complex, subunit 1
Pharmacogenomics and pharmacometabolomics• Pharmacogenetics (also termed pharmacogenomics ) is the field of study that examines the impact of genetic variation on the response to medications.• This approach is aimed at tailoring drug therapy at a dosage that is most appropriate for an individual patient,• Pre-dose metabolic profiles from urine can be used to predict drug metabolism
• Genotyping for SNPs in genes involved in metabolism of warfarin (coumarin). Genetic variants in the gene encoding Cytochrome P450 enzyme CYP2C9, which metabolizes warfarin and the Vitamin K epoxide reductase gene (VKORC1), a target of coumarins, have led to efficient testing for accurate dosing.• Genotyping variants in genes encoding Cytochrome P450 enzymes (CYP2D6, CYP2C19, and CYP2C9), which metabolize neuroleptic medications, to improve drug response and reduce side effects
Applications of Metabolomic and Genomic Profiling in Diabetic Clinical Medicine• Metabolic markers of type 2 diabetes• HbA1c , glucose and insulin• γ-glutamyl transferase and incident type 2 DM• The hepatic component of metabolic syndrome, studies have associated raised ALT with metabolic syndrome and type 2 DM.
• Ferritin: The mechanisms involve insulin resistance, free radical damage accumulation of iron in hepatocytes• Pancreatic polypeptide is proposaed as a marker of β-cell failure• Fetuin-A, a hepatic secretory protein binds the insulin receptor and inhibits insulin action• In a recent study of 31 novel biomarkers, demonstrated an association between clinically incident diabetes and insulin receptor, creatine kinase-MB, MR-Pro atrial natriuretic peptide, NT-Pro B-type natriuretic peptide, and B-type natriuretic peptide.
• Lipid-related markers of type 2 diabetes• Adiponectin increases insulin sensitivity, regulates glucose and lipid metabolism enhances insulin action in the liver• Leptin is already a marker of percentage fat mass in healthy individuals and regulates body weight by effects on food intake and metabolism.• Endothelial and inflammatory markers of type 2 diabetes• IL-18, IL-6, IL-1 receptor antagonist, IL-1ra, IL-2ra
• Circulating levels of several other inflammatory endothelial-derived factors such as cell adhesion molecules, tissue-plasminogen activator antigen, neopterin, and von Willebrand factor have been linked to diabetes risk
Drivers of Personalized Medicine• Technology – Significant new opportunities over the past 5 years• Patient financial burden – When you are paying more, you want more say• Less personal care – Who will be my doctor today?• Cost of care – Even the USA cant afford treating 100% to benefit 20%
Preemptive action is a clinical major weapon• Drug interactions• Renal dysfunction• Age• Vaccination• Antimalarial• TB• Mammography• colonoscopy
The clinical problem •Multiple active regimens for the treatment of most diseases •Variation in response to therapy •Unpredictable toxicity $$$$$$$$$$$ With choice comes decision
Correlative science: business as usual Phase I Phase II Phase III In vivo Biomarker BiomarkerMechanism assessment validation
Prediction of disease recurrence after surgery in Stage II colon cancer 1.0 N = 20 Good prognosis 0.8Distant Relapse-free Survival 0.6 N = 16 0.4 Poor prognosis 0.2 P-value = 0.0001 0.0 0 20 40 60 80 Time (months)