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Genomic Medicine and Prevention. Paul Kruszka , M.D., M.P.H. Commander, USPHS National Human Genome Research Institute (NHGRI). National Institutes of Health Bethesda, MD USA. NHGRI PHS PHYSICIANS CDR Paul Kruszka, Clinical Fellow CDR Melissa Meredith, Staff Clinician
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Genomic Medicine and Prevention Paul Kruszka, M.D., M.P.H. Commander, USPHS National Human Genome Research Institute (NHGRI)
NHGRI PHS PHYSICIANS CDR Paul Kruszka, Clinical Fellow CDR Melissa Meredith, Staff Clinician CAPT David Ng, Staff Clinician CAPT Ellen Sidransky, Senior Investigator
Objectives • Case presentation and its application to Genomic Medicine and Prevention • A (very) basic understanding of: • Single Nucleotide Polymorphisms • Microarray Technology • Single Gene (Mendelian) vs. Complex Disorders • Genome Wide Associate Studies (GWAS) • Next Generation Sequencing (NGS) • Our future with Genomics
What is Genomic Medicine? Genetic Medicine Genomic Medicine Is based on understanding the impact of our entire genome and environmental factors on disease and health… • Is based on understanding the impact of single genes on disease…
CASE Italian Italian 65y CAD 50y 45y MI 42y CAD 46y 21y 17y
Old Ideas; New Paradigm • “The doctor does not treat ‘man’ except accidentally; he treats Callius or Socrates or someone else described in this way, who is accidentally ‘man’…and thus knows the universal without knowing the individuals contained in it, he will often fail in his treatment; for it is the individual who has to be treated.”– Aristotle
Individual/Genomic/Personalized Medicine • “At it’s most basic, personalized medicine refers to using information about a person’s genetic makeup to tailor strategies for the detection, treatment or prevention of disease” Francis Collins (Boston Globe 2005)
What has changed to help our patient? 1990 Initiation of HGP • Completion of HGP Draft • International HapMap Project begins • Next generation sequencing (Illumina) 2007 GWAS explosion (100 new studies) • Initiation of 1000 Genomes Project 2010 More than 17 million SNPs in human genome catalogue SNP Database
The Human Genome Project • 3 billion base pairs (3,000 Mb) • Genes (protein coding) = 22,000 • Known Function 75% • The “exome” 50 Mb (1.5%)
The Genomic Era • Birth date: 14 April 2003, completion of the Human Genome Project • 49 years and 354 days after Watson and Crick’s description of the DNA double helix
The Central Dogma The Increasing Complexity of the Central Dogma of Molecular Biology Feero W et al. N Engl J Med 2010;362:2001-2011
The Human Genome • Only ,1.5% of the human genome encodes protein sequence • Comparative analysis with the mouse, rat and dog genomes showed that at least 5% is under purifying selection and thus probably functional • 3.5% consists of non-coding elements with probable regulatory roles. 4 7 6 | N AT U R E | VO L 4 7 8 | 2 7 O C T O B E R 2 0 1 1
? Genomic Medicine
What has changed to help our patient? 1990 Initiation of HGP • Completion of HGP Draft • International HapMap Project begins • Next generation sequencing (Illumina) 2007 GWAS explosion (100 new studies) • Initiation of 1000 Genomes Project 2010 More than 17 million SNPs in human genome catalogue SNP Database
HapMap • Validated millions of SNPs • Characterized linkage disequilibrium in populations of European, Asian, and African ancestry
SINGLE NUCLEOTIDE POLYMORPHISM (SNP) http://learn.genetics.utah.edu/content/health/pharma/snips/
LINKAGE DISEQUILIBRIUM http://learn.genetics.utah.edu/content/health/pharma/snips/
Microarray Technologies Microarray Technology Feero W et al. N Engl J Med 2010;362:2001-2011
What has changed to help our patient? 1990 Initiation of HGP • Completion of HGP Draft • International HapMap Project begins • Next generation sequencing (Illumina) 2007 GWAS explosion (100 new studies) • Initiation of 1000 Genomes Project 2010 More than 17 million SNPs in human genome catalogue SNP Database
Examples Mendelian (monogenic) Common/Complex (polygenic) Hypertension Coronary artery disease Hyperlipidemia Diabetes Autism Spectrum Disorders • Familial Hypercholesterolemia • Cystic fibrosis • Sickle cell anemia • Huntington disease • Tay-Sachs disease • Duchene Muscular dystrophy
Published Genome-Wide Associations through 06/2011, 1,449 published GWA at p≤5x10-8 for 237 traits NHGRI GWA Catalog www.genome.gov/GWAStudies
July 1, 2009, 5:10 pmHoopla, and Disappointment, in Schizophrenia Research By NICHOLAS WADE …more of a historic defeat, a Pearl Harbor of schizophrenia research…. The principal news from the three studies is that schizophrenia is caused by a very large number of errant genes, not a manageable and meaningful handful. http://tierneylab.blogs.nytimes.com/2009/07/01/hoopla-and-disappointment-in-schizophrenia-research/?em
The Missing Heritability of Complex Diseases… • Copy Number Variations (CNV) • Rare (lower frequency) SNPs • Insertion and deletions (indels) • Structural variations
What has changed to help our patient? 1990 Initiation of HGP • Completion of HGP Draft • International HapMap Project begins • Next generation sequencing (Illumina) 2007 GWAS explosion (100 new studies) • Initiation of 1000 Genomes Project 2010 More than 17 million SNPs in human genome catalogue SNP Database
The Beginning of “the Next Generation” in sequencing Science 2005, 309:1728-1732 Nature 2005, 437:376-380
g Technologies Next-Generation Sequencing Feero W et al. N Engl J Med 2010;362:2001-2011
What has changed to help our patient? 1990 Initiation of HGP • Completion of HGP Draft • International HapMap Project begins • Next generation sequencing (Illumina) 2007 GWAS explosion (100 new studies) • Initiation of 1000 Genomes Project 2010 More than 17 million SNPs in human genome catalogue SNP Database
1000 Genomes Project • Goal: sequencing at least 1000 genomes around world • Provide a comprehensive map of genetic variation for future disease association studies
http://www.sciencemag.org/content/early/recent / 17 May 2012/ Page 1/ 10.1126/science.1219240
“PC2-Z will systematically review, evaluate, and summarize medical evidence regarding genomic associations that are clinically actionable for application in clinic settings and develop and enhance existing AFMS information technology systems to capture and analyze genetic information for enhanced clinical decisionmaking.”