Goldschmidt1
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Goldschmidt1
- 1. Pascal J. Goldschmidt, MD, FACC, FAHA Edward Orgain Professor of Cardiology Chairman, Department of Medicine Duke University Durham, North Carolina AEHA 2006 Summit Designer Genes: From Plaque to Attack
- 2. Presenter Disclosure Information FINANCIAL DISCLOSURE: None <Pascal J. Goldschmidt, MD, FACC, FAHA> <Gene Expression Studies of Atherosclerosis> UNLABELED/UNAPPROVED USES DISCLOSURE: None
- 3. Healing hearts Changing lives Department of MedicinePg 3 Vascular Progenitor Cell Senescence and Plaque Instability CK, GF VPC Recruitment Injury InflammationRepair Competent Marrow Senescent Marrow VPC Recruitment Injury InflammationAtherosclerosis CK, GF - + Dong, Crawford, Goldschmidt, JACC May 3 ‘05
- 4. Healing hearts Changing lives Department of MedicinePg 4 Can we identify a molecular signature that corresponds to arterial repair by progenitor cells? Gene expression profiling Healing hearts Changing lives Department of MedicinePg 4
- 5. Healing hearts Changing lives Department of MedicinePg 5 Stages of Atherosclerosis Karra, Goldschmidt, Seo, In Press, PNAS
- 6. Healing hearts Changing lives Department of MedicinePg 6 Patterns of Disease Stages Karra, Goldschmidt, Seo, In Press, PNAS
- 7. Healing hearts Changing lives Department of MedicinePg 7 *P<0.05 vs Young ApoE -/- cells IV. † P<0.05 vs No cells and WT cells IP. Effect of Age on Arterial Repair Capacity: Quantitative a) Old ApoE -/- cells IV (n=6) b) Young ApoE -/- cells IV (n=6) c) No cells (n=6) d) WT cells IP (n=6) e) WT cells IV, stroma-enriched (n=6) f) WT cells IV, hematopoietic-enriched (n=6) Treatments * † 0 10 20 30 Abdominal Aorta Percent Karra, Goldschmidt, Seo, In Press, PNAS Rauscher et al. Circulation. 2003;108:457 Goldschmidt and Peterson. Science. 2003 (SAGE-KE) farnesyl diphosphate farnesyl transferase 1 zinc finger RNA binding protein RAB1, member RAS oncogene family TGFB inducible early growth response 1 Fas (TNFRSF6)-associated via death domain neurotrophic tyrosine kinase, receptor, type 3 protein tyrosine phosphatase, receptor type, M wingless-related MMTV integration site 5B snail homolog 2 (Drosophila)
- 8. Healing hearts Changing lives Department of MedicinePg 8 Functional Genomics Karra, Goldschmidt, Seo, In Press, PNAS
- 9. Healing hearts Changing lives Department of MedicinePg 9 Human Arteries: Tissue Procurement
- 10. Healing hearts Changing lives Department of MedicinePg 10 Orthologous Expression Patterns Karra et al. Submitted, 2004
- 11. Healing hearts Changing lives Department of MedicinePg 11 Over time, the capacity of the marrow to produce competent stem cells capable of arterial repair becomes exhausted. Cause of plaque destabilization? Healing hearts Changing lives Department of MedicinePg 11
- 12. Healing hearts Changing lives Department of MedicinePg 12 Predictive Modeling of Coronary Artery Disease Based on Simultaneous Expression Pattern of 8 Genes (t1- Scores) Granger et al. (Duke/GeneProt/Novartis) Hypothesis: As circulating cells (progenitor and inflammatory cells) contribute to arterial repair/plaque destabilization, Can we array nucleated blood cells to assess severity of coronary artery disease?
- 13. Healing hearts Changing lives Department of MedicinePg 13 Previous Study Identified Susceptibility Region on 3q13 for Coronary Artery Disease (CAD) LOD score = 3.5, one LOD-unit down region: >20 Mb 3q13 Hauser ER. et al., AJHG, 2004 Sep;75(3):436-47 Chr 3 “A Genomewide Scan for Early-Onset Coronary Artery Disease in 438 Families: The GENECARD Study”
- 14. Healing hearts Changing lives Department of MedicinePg 14 Genomic Convergence: Synergy between Genome-wide scan and expression genomics Aorta SNPs: Expression analysis and association results 0.0 1.0 2.0 3.0 4.0 0 500 1000 1500 2000 2500 3000 Map position (cM) -log10(p-value) PVALUE_GENOTYPE A1_GPVAL A1_APVAL A2_GPVAL A2_APVAL A3_GPVAL A3_APVAL 21 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 5 16 17 18 19 20 22 Chromosome #: pvalue=.05
- 15. Healing hearts Changing lives Department of MedicinePg 15 Novel Gene That Predicts Left Main Disease: Limbic System Associated Membrane Protein (LSAMP) Known: 1. LSAMP mediates cell-cell adhesion in neurons. Pimenta et al., Neuron 1995; 15(2):287-297 2. Overexpression of LSAMP inhibits renal cancer cell proliferation. Chen et al., Cancer Cell 2003; 4:405-413 Unknown: 1. Is LSAMP involved in the pathogenesis of CAD? 2. Can LSAMP SNPs predict LM disease AHA 2005: Liyong Wang, Ph.D. Center for Human Genetics Duke University Medical Center
- 16. Healing hearts Changing lives Department of MedicinePg 16 Prediction of LM-Disease by LSAMP SNPs P=0.003 P=0.132 P=0.002 rs1676232_a_rs4404477_a LM Control Set 1 102 149 Set 2 151 229
- 17. Healing hearts Changing lives Department of MedicinePg 17 Expression of LSAMP_1a Is Downregulated in Aortas with Severe Atherosclerosis Burden Atherosclerosis Burden (N=sample size) 0 3 6 9 12 mRNALevel (relativevalue) P<0.001 * * mild/moderate moderate/severe (N=3) Severe (N=7)(N=27)
- 18. Healing hearts Changing lives Department of MedicinePg 18 Conclusions • Genomics has transformed our ability to predict atherosclerosis, CAD, instability • Genomic techniques are utmost useful to discover disease mechanisms • Early testing to predict plaque rupture and other features of CAD via genomic advances will become affordable during the next five years
- 19. Healing hearts Changing lives Department of MedicinePg 19Pg 19 Collaborators Duke: IGSP Department of Medicine Joe Nevins DCRI Mike West Chunming Dong Geoff Kunz Center for David Seo Demographic Studies Shoukang Zhu Julia Kravtchenko Xialin Liu Ken Manton Lisa Satterwhite Ken land Fred Rauscher Eric Stallart Sreek Vemulapalli Department of Surgery Ryan Schulties Carmello Milano Ravi Karra Center for Human Genetics Eric Peterson Beth Hauser Grace Liang Department of Radiology Olujimi Ajijola Bennett Chin Department of Pediatrics Joanne Kurtzberg
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- To achieve different levels of disease, we used mice. Mice with no disease are WT, 6wk chow Mice with ealry disease are ApoE, 6 wk chow Mice with intermediate disease are ApoE, 12 wk High Fat Mice with moderate disease are ApoE, 16 wk High Fat Disease extent characterized for each group of mice using Oil Red O staining and calculating the affected area Can see by graph clear difference in lesion burden among groups Composite pictures show that the major difference is actually at the aortic arch
- We compared the expression profiles for aortas of different disease stages We built a model with 197 genes to distinguish samples without disease from samples with early disease The model distinguishing samples with early disease from intermediate disease used 146 genes The model distinguishing samples with interemdiate disease from moderate disease uses 110 genes The model distinguishing samples with no disease from moderate disease uses 650 genes To verify that these patterns are indeed robust, we used cross-validation. All the models are able to cross-validate &gt; 96% of the samples. At this point, we were a little befuddled in how to describe our list of genes. Therefore, we turned to Gene Ontology. Gene Ontology terms allow for broad descriptions to be applied to a genes based on their inferred Biological process We found an over-representation of genes for metabolism, inflammation, tissue remodeling, and once again inflammation