David Geffen School of Medicine at UCLA
Department of Human Genetics

Speaker Series - Winter Quarter 2007

Mondays, 11am - 12pm, Gonda Building First Floor Conference Room, 1357

Mon, Jan 22
Aberrant gene silencing, the cancer epigenome, and stem cells
Stephen B. Baylin, MD, Virginia and D.K. Ludwig Professor for Cancer Research, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine
Contact & Intro: Guoping Fan
  1. A stem cell–like chromatin pattern may predispose tumor suppressor genes to DNA hypermethylation and heritable silencing. Ohm JE, McGarvey KM, Yu X, Cheng L, Schuebel KE, Cope L, Mohammad HP, Chen W, Daniel VC, Yu W, Berman DM, Jenuwein T, Pruitt K, Sharkis SJ, Watkins DN, Herman JG, Baylin SB. Nature Genetics 39: 1-6 (2007).
  2. Epigenetic gene silencing in cancer – a mechanism for early oncogenic pathway addiction? Baylin SB, Ohm, JE. Nature Reviews 6: 107-116 (2006).
  3. The cancer epigenome—components and functional correlates. Ting AH, McGarvey KM, Baylin SB. Genes & Development 20: 3215-3231 (2006).
Mon, Jan 29
Genetic etiology of human obesity
Ruth McPherson, MD, PhD, FRCP(C), Director, Lipid Research Laboratory, Professor, Departments of Medicine & Biochemistry, Division of Cardiology, University of Ottawa Heart Institute
Contact & Intro: Jake Lusis
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ABSTRACT: Dr. McPherson's laboratory research is centered in two major areas. These include the regulation and cellular function of HDL receptors, specifically SR-BI and CETP. She also directs a new collaborative program directed at developing a comprehensive and integrated understanding of the genetic and molecular etiology of two complex phenotypes, obesity and coronary artery disease, by simultaneous application of a number of methodologies.

Genetic Etiology of Human Obesity

Twin, adoption, and family studies have indicated that 40 to 70% of inter-individual variation in body mass index is heritable. Nonetheless, the genetic origins of human obesity remain obscure in part due to the multiple pathways involved in the regulation of food intake, energy expenditure and energy storage. We have recruited and extensively phenotyped a population of over 1000 very obese and over 1000 age and sex matched very lean individuals. Approaches include: definition of obese and lean sub-phenotypes, skeletal muscle gene expression and cellular function, re-sequencing of multiple candidate genes (in collaboration with Dr. Len Pennacchio) and SNP genotyping. Preliminary Results: Obese subjects can be further categorized on the basis of ability to lose weight in response to a precise caloric restriction. Slow weight losers (energy conservers) demonstrate differences in skeletal muscle gene expression profile as compared to fast weight losers (energy burners), implicating a set of genes involved in insulin signaling, mitochondrial function and oxidative metabolism. Rare sequence variants in genes associated with monogenic forms of obesity in mice (e.g. MC4R, PYY) make a small but significant contribution to human obesity. A novel mutation (R225W) in human PRKAG3, associated with increased basal and stimulated AMPK activity, an important regulator of cellular energy homeostasis, will also be discussed.

  1. A PYY Q62P variant linked to human obesity. Ahituv N, Kavaslar N, Schackwitz W, Ustaszewska A, Collier JM, Hebert S, Doelle H, Dent R, Pennacchio LA, McPherson R. Human Molecular Genetics 15: 387–391 (2006).
  2. Lack of MEF2A mutations in coronary artery disease. Weng L, Kavaslar N, Ustaszewska A, Doelle H, Schackwitz W, Hébert S, Cohen JC, McPherson R, Pennacchio LA. The Journal of Clinical Investigation 115: 1016-1020 (2005).
  3. Decreased mitochondrial proton leak and reduced expression of uncoupling protein 3 in skeletal muscle of obese diet-resistant women. Harper ME, Dent R, Monemdjou S, Bézaire V, Van Wyck L, Wells G, Kavaslar GN, Gauthier A, Tesson F, McPherson R. Diabetes 51: 2459-2466 (2002).
Mon, Feb 05
Talk scheduled 11:30am - 12:30pm
Lupus: its complex genetics
John B. Harley, MD, PhD, Member and Program Head, Arthritis and Immunology Research Program, Oklahoma Medical Research Foundation
Contact & Intro: Jake Lusis
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ABSTRACT: Purpose: Progress against deadly and complicated diseases is hindered by not understanding basic etiology and causation. Systemic lupus erythematosus (SLE) is such a disease, the basic autoimmune nature of which is revealed by the detection of relatively SLE-specific autoantibodies that precede clinical onset by years. We apply modern technologies to define the genetic basis of this disorder.

Methods: We have assembled almost 8000 subjects from pedigrees containing a proband with SLE and unrelated controls. Genotyping using various technologies has generated an enormous and growing marker dataset. Standard genetic linkage and association methods have been applied to identify genetic effects.

Results: For SLE 15 linkages and 7 secure genetic associations are present in our data. The linkages with SLE include 1q23, 1q41-42, 2q37, 4p16, 11p13, 12q24, & 16q12-13 and in subset analyses include 2q34 (nephritis in blacks), 3p21 (smokers, anti-La), 5p15 (multiplex alleged rheumatoid arthritis in whites), 5q14 (autoimmune thyroid disease in whites), 11q14 (hemolytic anemia in blacks), 17p13 (vitiligo in whites), and 19p13 (anti-double stranded DNA in whites). The more convincing genetic associations include PTPN22, FCRL3, FGR2A, FGR3A, PDCD1, multiple HLA-region genes, and IRF5. These genes and many others work together in, at present, unknown combinations with the environmental factors to generate SLE. In addition, the female predominance of SLE is complemented by the discovery of a 14-fold increased frequency of 47,XXY males in men with SLE.

Conclusion: New technologies provide important new approaches to identify the origins of complex diseases, such as SLE. The quantity of data in this and many other genetic problems is almost overwhelming.

  1. Arbuckle MR, McClain MT, Rubertone MV, Scofield RH, Dennis GJ, James JA, Harley JB. Development of autoantibodies before the clinical onset of systemic lupus erythematosus. New England Journal of Medicine 349:1526-33 (2003).
  2. McClain MT, Heinlen LD, Dennis GJ, Roebuck J, Harley JB, James JA. Early events in lupus humoral autoimmunity suggest initiation through molecular mimicry. Nature Medicine 11: 85-9 (2005). Epub 2004 Dec 26 [PMID: 15619631]
  3. Sestak AL, Nath SK, Harley JB. Genetics of systemic lupus erythematosus: how far have we come? Rheumatic Disease Clinics of North America 31: 223-44 (2005)[PMID: 15922143]
  4. McClain MT, Poole BD, Bruner BF, Kaufman KM, Harley JB, James JA. An altered immune response to Epstein-Barr nuclear antigen 1 in pediatric systemic lupus erythematosus. Arthritis and Rheumatism 54: 360-8 (2006). [PMID: 16385527]
Fri, Feb 09
All talks will be presented at the Institute for Pure and Applied Mathematics
Computational genetics: a perspective
Invited speakers, Michael Boehnke, Ruzong Fan, David Hunter, Laura Lazzeroni, Neil Risch, Eric Schadt, Eric Sobel, Daniel Weeks
Contact & Intro: Chiara Sabatti
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ABSTRACT: Schedule

Mon, Feb 12
Genomewide association testing for family-based tests of association
Nan M. Laird, PhD, Professor of Biostatistics, Harvard School of Public Health
Contact & Intro: Chiara Sabatti
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ABSTRACT: Genomewide association studies are currently receiving much attention as a new means for locating genes for complex disease. Family-based association tests are popular because of their robustness to population structure, but are sometimes criticized for ignoring information in the data. I will discuss a general approach to incorporate extra information into the analysis of family data which greatly enhances their utility in the setting of genomewide testing. An example involving BMI in the Framingham Heart study will be discussed.

  1. Family-based designs in the age of large-scale gene-association studies. Laird NM, Lange C. Nature Reviews | Genetics 7: 385-394 (2006).
  2. A Common Genetic Variant Is Associated with Adult and Childhood Obesity. Herbert A, Gerry NP, McQueen MB, Heid IM, Pfeufer A, Illig T, Wichmann HE, Meitinger T, Hunter D, Hu FB, Colditz G, Hinney A, Hebebrand J, Koberwitz K, Zhu X, Cooper R, Ardlie K, Lyon H, Hirschhorn JN, Laird NM, Lenburg ME, Lange C, Christman, MF. Science 312: 279-283 (2006).
  3. Genomic screening and replication in one data set in family-based association testing. Van Steen K, McQueen MB, Herbert A, Raby B, Lyon H, DeMeo DL, Murphy A, Su J, Datta S, Rosenow C, Christman M, Silverman EK, Laird NM, Weiss ST, Lange C. Nature Genetics Advance Online Publication 1-11. http://www.nature.com/naturegenetics/
Mon, Feb 26
Type 2 diabetes susceptibility genes on chromosome 1q
Sandy Hasstedt, PhD, Associate Professor, Department of Human Genetics, University of Utah
Contact & Intro: Chiara Sabatti
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ABSTRACT: Type 2 diabetes (T2D) susceptibility has been localized to chromosome 1q21-24 in multiple populations, including a Utah pedigree sample. The 1q region contains numerous T2D candidate genes; nineteen variants in six chromosome 1q candidate genes have been genotyped in a sample of 63 Utah pedigrees. Each variant was tested individually and in combinations for an effect on T2D risk using a logistic regression model that accounted for gender, age, and BMI and attributed residual genetic effects to a polygenic component. The findings and interpretation of the analysis will be discussed.

  1. Linkage and association mapping of a chromosome 1q21-q24 type 2 diabetes susceptibility locus in northern European Caucasians. Das SK, Hasstedt SJ, Zhang Z, Elbein SC. Diabetes 53: 492-499 (2004).
  2. Polymorphisms in the glucokinase-associated, dual specificity phosphatase 12 (DUSP12) gene under chromosome 1q21 linkage peak are associated with type 2 diabetes. Das SK, Chu WS, Hale TC, Wang X, Craig RL, Wand H, Shuldiner AR, Froguel P, Deloukas P, McCarthy MI, Zeggini E, Hasstedt SJ, Elbein SC. Diabetes 55: 2631-2639 (2006).
Mon, Mar 05
The genomes of recombinant inbred lines
Karl W. Broman, PhD, Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University
Contact & Intro: Chiara Sabatti
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ABSTRACT: Recombinant inbred lines (RILs) are formed by crossing two inbred strains (e.g., of mice), followed by repeated sibling mating (or, in some plants, selfing) to produce a new inbred line whose genome is a mosaic of the genomes of the initial strains. RILs can be powerful tools for genetic mapping. Recently, members of the Complex Trait Consortium have begun the development of a large panel of eight-way RILs in the mouse, derived from eight genetically diverse parental strains. The use of such 8-way RILs will require a detailed understanding of the relationship between alleles at linked loci on an RI chromosome. We have extended the work of Haldane and Waddington (1931) on two-way RILs and describe the map expansion, clustering of breakpoints, and other features of the genomes of multi-way RILs as a function of the level of crossover interference in meiosis. The problem concerns the absorption probabilities of a Markov chain with a very large number of states.

  1. The genomes of recombinant inbred lines. Broman KW. Genetics 169: 1133-1146 (2005).
  2. The Collaborative Cross, a community resource for the genetic analysis of complex traits. The Complex Trait Consortium (2004). Nature Genetics 36: 1133-1137 (2004).
  3. Inbreeding and linkage. Haldane JBS, Waddington CH. Genetics 16: 357-374 (1931).
Mon, Mar 12
Talk scheduled 2:30pm-3:30pm
Mapping lipid genes
Gail Jarvik, MD, PhD, Professor of Medicine, Division of Medical Genetics, University of Washington Medical Center
Contact & Intro: Paivi Pajukanta
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ABSTRACT: Heart disease remains the leading cause of death in the US. Our goal is the identification of genes that increase athersclerosis risk through unfavorable lipid profiles. One challange is the genetic and non-genetic variation, heterogeneity, that complicates gene localizaton. To address this we are working primarily with 4 large families with familial combined hyperlipidemia. Lipid phenotypes of interest are low density lipoprotein size, high density lipoprotein level, and apolipoprotein B levels. A tagSNP approach is used to follow-up regional candidates.

  1. LDL particle size loci in familial combined hyperlipidemia: Evidence of multiple loci from a genome scan. Badzioch M, Igo RP, Gagnon F, Brunzell JD, Krauss RM, Motulsky AG, Wijsman EM, Jarvik GP. Arteriosclerosis, Thrombosis, and Vascular Biology 24: 1942-1950 (2004).
  2. TagSNP evaluation for the association of 42 inflammation loci and vascular disease: Evidence of IL6, FGB, ALOX5, NFKBIA, and IL4R loci effects. Carlson CS, Heagerty PJ, Nord AS, Pritchard DK, Ranchalis J, Boguch JM, Duan H, Hatsukami TS, Schwartz SM, Rieder MJ, Nickerson DA, Jarvik GP. Human Genetics (2006), epub ahead of print.

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