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158 results on '"Kristin G. Ardlie"'

151. A Missense Single-Nucleotide Polymorphism in a Gene Encoding a Protein Tyrosine Phosphatase (PTPN22) Is Associated with Rheumatoid Arthritis

Author

Annette Lee, Randall K. Saiki, Veronica Garcia, Christopher I. Amos, Monica Chang, Franak Batliwalla, Michael F. Seldin, Kristin G. Ardlie, Lee Honigberg, Marion T. Conn, Peter K. Gregersen, Douglas A. Jeffery, Daniel L. Kastner, Steven J. Schrodi, Ann B. Begovich, Lindsey A. Criswell, Victoria E.H. Carlton, John J. Sninsky, Sheng Yung P Chang, Ashley M. Smith, Joseph J. Catanese, Anand P. Chokkalingam, Elaine F. Remmers, Jill M. Spoerke, Linda B. McAllister, Heather C. Alexander, Qiqing Huang, and Diane U. Leong

Subjects
Population, Molecular Sequence Data, Mutation, Missense, Single-nucleotide polymorphism, Protein tyrosine phosphatase, Biology, Polymorphism, Single Nucleotide, PTPN22, Arthritis, Rheumatoid, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, Report, Genetics, Missense mutation, Humans, Genetics(clinical), RNA, Messenger, Allele, education, Genetics (clinical), 030304 developmental biology, Protein Tyrosine Phosphatase, Non-Receptor Type 1, 0303 health sciences, education.field_of_study, 3. Good health, Minor allele frequency, Organ Specificity, PADI4, Immunology, Protein Tyrosine Phosphatases, 030215 immunology
Abstract

Rheumatoid arthritis (RA) is the most common systemic autoimmune disease, affecting approximately 1% of the adult population worldwide, with an estimated heritability of 60%. To identify genes involved in RA susceptibility, we investigated the association between putative functional single-nucleotide polymorphisms (SNPs) and RA among white individuals by use of a case-control study design; a second sample was tested for replication. Here we report the association of RA susceptibility with the minor allele of a missense SNP in PTPN22 (discovery-study allelic P=6.6 x 10(-4); replication-study allelic P=5.6 x 10(-8)), which encodes a hematopoietic-specific protein tyrosine phosphatase also known as "Lyp." We show that the risk allele, which is present in approximately 17% of white individuals from the general population and in approximately 28% of white individuals with RA, disrupts the P1 proline-rich motif that is important for interaction with Csk, potentially altering these proteins' normal function as negative regulators of T-cell activation. The minor allele of this SNP recently was implicated in type 1 diabetes, suggesting that the variant phosphatase may increase overall reactivity of the immune system and may heighten an individual carrier's risk for autoimmune disease.

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152. Evaluation of Clinical Colon Carcinoma Using Activity-Based Proteomic Profiling

Author

Kristin G. Ardlie, Emme C. K. Lin, Melissa C. Zhang, and Jiangyue Wu

Subjects
Serine protease, Proteomic Profiling, Clinical Biochemistry, Cancer, Serine hydrolase, General Medicine, Biology, medicine.disease, Proteomics, Molecular biology, Fibroblast activation protein, alpha, Targeted drug delivery, Tumor progression, medicine, biology.protein, Molecular Medicine, Molecular Biology
Abstract

The evaluation of clinical tumor tissues is a valuable approach to discovering novel drug targets because of the direct relevance of human samples. We used activity-based proteomic profiling (ABPP) to study the differences in serine hydrolase activities from 12 matched pairs of clinical normal and tumor colon tissues. Unlike traditional proteomics or measures of mRNA abundance, ABPP actually quantifies enzymatic activities, a characteristic crucial for drug targeting. Several serine hydrolases were differentially active in tumor vs normal tissues, despite a lack of obvious corresponding alterations in protein expression. We identified one tumor-specific activity by mass spectrometry to be fibroblast activation protein (FAP), an integral membrane serine protease that has been reported to be present only in tumor stroma or during wound healing and absent in normal tissues. FAP activity was further found to be approximately twofold higher in stage III relative to stage II colon cancer, suggestive of a role in tumor progression. We were also able to identify other proteins, some of which had not been previously linked to cancer, which had higher activity in tumors. Our results demonstrate the applicability of ABPP for the efficient identification of multiple clinical disease targets.

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153. Testing for Population Subdivision and Association in Four Case-Control Studies

Author

Kathryn L. Lunetta, Kristin G. Ardlie, and Mark Seielstad

Subjects
education.field_of_study, Population, Case-control study, Sample (statistics), Biology, Sample size determination, Polymorphism (computer science), Genetics, Genetics(clinical), education, Allele frequency, Genetics (clinical), Negroid, Demography, Genetic association
Abstract

Population structure has been presumed to cause many of the unreplicated disease-marker associations reported in the literature, yet few actual case-control studies have been evaluated for the presence of structure. Here, we examine four moderate case-control samples, comprising 3,472 individuals, to determine if detectable population subdivision is present. The four population samples include: 500 U.S. whites and 236 African Americans with hypertension; and 500 U.S. whites and 500 Polish whites with type 2 diabetes, all with matched control subjects. Both diabetes populations were typed for the PPARg Pro12Ala polymorphism, to replicate this well-supported association (Altshuler et al. 2000). In each of the four samples, we tested for structure, using the sum of the case-control allele frequency χ2 statistics for 9 STR and 35 SNP markers (Pritchard and Rosenberg 1999). We found weak evidence for population structure in the African American sample only, but further refinement of the sample, to include only individuals with U.S.-born parents and grandparents, eliminated the stratification. Our examples provide insight into the factors affecting the replication of association studies and suggest that carefully matched, moderate-sized case-control samples in cosmopolitan U.S. and European populations are unlikely to contain levels of structure that would result in significantly inflated numbers of false-positive associations. We explore the role that extreme differences in power among studies, due to sample size and risk-allele frequency differences, may play in the replication problem.

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154. Punctuated Evolution of Prostate Cancer Genomes

Author

Yotam Drier, Daniel Auclair, Andrey Sivachenko, Ashutosh K. Tewari, Gordon Saksena, Michelle Cipicchio, Gad Getz, Levi A. Garraway, Scott L. Carter, Philip W. Kantoff, Robert C. Onofrio, Gregory V. Kryukov, Theresa Y. MacDonald, Himisha Beltran, Jean-Philippe Theurillat, David Soong, Alessandro Romanel, Kristian Cibulskis, Kristin G. Ardlie, Eliezer M. Van Allen, Todd R. Golub, Francesca Demichelis, Matthew Meyerson, Candace Guiducci, Christopher E. Barbieri, Alex H. Ramos, Douglas Voet, Elizabeth Nickerson, Mark A. Rubin, Wendy Winckler, Sylvan C. Baca, Gunther Boysen, Mahmoud Ghandi, Davide Prandi, Olivier Elemento, Naoki Kitabayashi, Andrea Sboner, Eric S. Lander, Kyung Park, Michael S. Lawrence, Stacey Gabriel, Juan Miguel Mosquera, Michael F. Berger, Massachusetts Institute of Technology. Department of Biology, Whitehead Institute for Biomedical Research, and Lander, Eric S.

Subjects
Male, Biology, SPOP, Adenocarcinoma, medicine.disease_cause, Genome, Article, General Biochemistry, Genetics and Molecular Biology, Cohort Studies, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Prostate, medicine, Humans, 030304 developmental biology, Genetics, Chromosome Aberrations, 0303 health sciences, Chromothripsis, Biochemistry, Genetics and Molecular Biology(all), Genome, Human, Prostatic Neoplasms, Chromoplexy, medicine.disease, 3. Good health, Gene Expression Regulation, Neoplastic, Neuroendocrine Tumors, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Human genome, Carcinogenesis, Genome-Wide Association Study
Abstract

The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term “chromoplexy,” frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis., National Human Genome Research Institute (U.S.). Large Scale Sequencing Program (U54 HG003067)

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155. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Author

Barbara E. Engelhardt, Sarah Kim-Hellmuth, Sarah Urbut, Ashis Saha, Gen Li, Jessica Halow, Panagiotis Papasaikas, Simona Volpi, Alvaro N. Barbeira, Jared L. Nedzel, Meng Wang, Nikolaos I Panousis, Benedict Paten, Lori E. Brigham, Gao Wang, Mary Barcus, Anthony Payne, Xiaoquan Wen, Nicola J. Rinaldi, Hua Tang, Seva Kashin, Casey Martin, Steven Hunter, Yi-Hui Zhou, Kristen Lee, Ian C. McDowell, Jason M. Torres, Alexandra J. Scott, Kane Hadley, Duyen T. Nguyen, Leslie H. Sobin, Jiamao Zheng, Paul Flicek, Casandra A. Trowbridge, Anjené M. Addington, Omer Basha, Brandon L. Pierce, Pejman Mohammadi, Xiao Li, Halit Ongen, Ki Sung Um, John T. Lonsdale, Alexis Battle, Takunda Matose, Kathryn Demanelis, Yuan He, Bernadette Mestichelli, Kasper D. Hansen, Marcus Hunter, Shin Lin, Richard Hasz, Thomas Juettemann, Ellen Karasik, Taru Tukiainen, Lin Chen, Fred A. Wright, Martijn van de Bunt, Meritxell Oliva, Fidencio J. Neri, François Aguet, Todd L. Edwards, Judith B. Zaugg, Michael Snyder, Gary Walters, Yongjin Park, Mary Goldman, Michael Sammeth, Kristin G. Ardlie, A. Roger Little, Reza Sodaei, Stephen J. Trevanion, Kevin S. Smith, Stephen B. Montgomery, Katherine H. Huang, John A. Stamatoyannopoulos, David E. Tabor, Gene Kopen, Melina Claussnitzer, Nancy Roche, Rodrigo Bonazzola, Deborah C. Mash, Helen M. Moore, Anne Ndungu, Lihua Jiang, Konrad J. Karczewski, Marian S. Fernando, Liqun Qi, Princy Parsana, Ping Guan, Eleazar Eskin, Kate R. Rosenbloom, Jason Bridge, Maria M. Tomaszewski, David A. Davis, Joseph Wheeler, Sarah E. Gould, Morgan Diegel, Eric S. Torstenson, Nancy J. Cox, Daniel R. Zerbino, Joshua M. Akey, Kimberly M. Valentino, Brunilda Balliu, Jingchun Zhu, Joe R. Davis, Nicholas Van Wittenberghe, Michael F. Salvatore, Susan E. Koester, Barbara A. Foster, Andrey A. Shabalin, Ira M. Hall, John Vivian, Eun Yong Kang, Nathan S. Abell, Laure Fresard, Lindsay F. Rizzardi, Ayellet V. Segrè, Dan Sheppard, Rajinder Kaul, Jeffrey McLean, Michael Washington, Joanne Chan, Mark Miklos, Benoit Molinie, Christopher Johns, Laura M. Huckins, Monkol Lek, Christopher D. Brown, Laura A. Siminoff, Alisa McDonald, Abhi Rao, Jean Monlong, Jie Quan, Diego Garrido-Martín, Barbara E. Stranger, Donald F. Conrad, Farhan N. Damani, Cédric Howald, Buhm Han, Michael S. Noble, Caroline Linke, Daniel C. Rohrer, Jimmie B. Vaught, Hae Kyung Im, Audra K. Johnson, Rui Zhang, Muhammad G. Kibriya, Matthew Stephens, Chiara Sabatti, Brian Roe, Latarsha J. Carithers, Robert E. Handsaker, Pushpa Hariharan, Boxiang Liu, Manolis Kellis, YoSon Park, Manuel Muñoz-Aguirre, Lei Hou, Matthew T. Maurano, Ariel D. H. Gewirtz, Ruth Barshir, Michael J. Gloudemans, Li Wang, Gireesh K. Bogu, Christopher Lee, Anita H. Undale, Genna Gliner, Sandra Linder, Serghei Mangul, Andrew A. Brown, Tzintzuni Garcia, Eric Haugen, Michael T. Moser, Jessica Lin, Andrew B. Nobel, Richard Sandstrom, Emmanouil T. Dermitzakis, Kieron Taylor, Brian Jo, Rachna Kumar, Laura Barker, Magali Ruffier, Ferran Reverter, Saboor Shad, Jin Billy Li, Eli A. Stahl, Mark I. McCarthy, William F. Leinweber, Gad Getz, Karna Robinson, Xin Li, Esti Yeger-Lotem, Jemma Nelson, Negin Vatanian, Scott P. Dickinson, Colby Chiang, Jeffrey A. Thomas, Kaanan P. Shah, Maximilian Haeussler, Heather M. Traino, Concepcion R. Nierras, Fan Wu, Hualin S. Xi, Yaping Liu, Daniel Bates, Peter Hickey, Eric R. Gamazon, Jennifer A. Doherty, Ellen Gelfand, Jae Hoon Sul, Jeffery P. Struewing, Beryl B. Cummings, W. James Kent, John Palowitch, Brian Craft, Anna M. Smith, Pedro G. Ferreira, Emily K. Tsang, Andrew P. Feinberg, Nicole C. Lockart, Ruiqi Jian, Robert G. Montroy, Dan L. Nicolae, Yungil Kim, Kevin Myer, Christine B. Peterson, Benjamin J. Strober, Andrew D. Skol, Qin Li, Bryan Gillard, Dana R. Valley, Zachary Zappala, Philip A. Branton, Stephane E. Castel, Daniel G. MacArthur, Mark H. Johnson, Olivier Delaneau, Maghboeba Mosavel, Roderic Guigó, Farzana Jasmine, Scott D. Jewell, Shilpi Singh, Tuuli Lappalainen, Farhad Hormozdiari, and Heather E. Wheeler

Subjects
0301 basic medicine, Science, Quantitative Trait Loci, Gene Expression, General Physics and Astronomy, Genome-wide association study, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Genome-wide association studies, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Meta-Analysis as Topic, Genetic variation, Humans, Computer Simulation, lcsh:Science, Gene, Genetics, Multidisciplinary, Models, Genetic, Chromosome Mapping, Genetic Variation, Tissue-Specific Gene Expression, Robustness (evolution), General Chemistry, Phenotype, 030104 developmental biology, Organ Specificity, Trait, lcsh:Q, Data integration, Genome-Wide Association Study
Abstract

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes., Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.

156. Comprehensive molecular portraits of human breast tumours

Author

Julie M. Gastier-Foster, Nguyen Van Bang, Christopher Szeto, Daoud Meerzaman, Nguyen Viet Tien, Richard K. Wilson, Jennifer Brown, Singer Ma, Andrew H. Beck, Sam Ng, Phillip H. Lai, Peter J. Park, Khurram Z. Khan, Gordon B. Mills, Joel S. Parker, Li Ding, Ying Hu, Jill P. Mesirov, Rebecca Carlsen, Kevin P. White, Benjamin P. Berman, Michael C. Adams, Laura A.L. Dillon, Jake Lin, Giovanni Ciriello, Simeen Malik, Moiz S. Bootwalla, Sheila Reynolds, Petar Stojanov, B. Arman Aksoy, Jerry Usary, Mei Huang, Andrzej Mackiewicz, Prachi Kothiyal, Keith A. Baggerly, Hann Hsiang Chao, Timo Erkkilä, Elaine R. Mardis, Nils Gehlenborg, Bradley M. Broom, Tara M. Lichtenberg, Jeff Gentry, Payal Sipahimalani, Chris Wakefield, Zhining Wang, Anna Chu, Konstanty Korski, Michael S. Noble, Lawrence A. Donehower, Pavana Anur, Janita Thusberg, Rohit Bhargava, Chris Sander, Lori Boice, Juok Cho, Charles Saller, Sophie C. Egea, Marc Danie Nazaire, Heather Schmidt, Bui Duc Phu, Hye Jung E. Chun, Bradley A. Ozenberger, Robert S. Fulton, Carrie Hirst, Stephen B. Baylin, Miruna Balasundaram, Peter White, Fergus J. Couch, Saianand Balu, Christina Yau, Yevgeniy Antipin, Jacek J. Brzeziński, Rehan Akbani, Todd Pihl, Ari B. Kahn, Nianxiang Zhang, Sean P. Barletta, Mary Iacocca, Kelly Daily, Wiam Bshara, Marc Ladanyi, Michael D. Topal, Huy Nguyen, Theodore C. Goldstein, Tari A. King, Bernard Kohl, Jingchun Zhu, Wiktoria Maria Suchorska, Xuan Van Le, Wei Zhang, Yan Shi, Marta Bogusz-Czerniewicz, Barry S. Taylor, Li-Wei Chang, Matthew C. Nicholls, Julien Baboud, Honorata Tatka, Doug Voet, Vesteinn Thorsson, Richard W. Park, Aaron D. Black, Pawel Murawa, Leonid Kvecher, Raju Kucherlapati, Colleen Mitchell, Wei Zhao, Leigh B. Thorne, Artem Sokolov, Modesto Patangan, Yidi J. Turman, Teresa R. Tabler, Kyle Ellrott, Yaron S.N. Butterfield, Gordon Saksena, Ronglai Shen, Yaqin Chen, Olga Voronina, Candace Carter, Yiling Lu, Cynthia McAllister, Thomas Stricker, Chunqing Luo, Dominique L. Berton, Thomas Barr, Robert A. Holt, Christopher Wilks, David Van Den Berg, Robert Sfeir, Ilya Shmulevich, Ranabir Guin, Nilsa C. Ramirez, Hollie A. Harper, John A. Demchok, Matthew J. Ellis, David Haussler, Katherine A. Hoadley, Eric Chuah, Richard J. Mural, Charles M. Perou, Timothy J. Triche, Steven J.M. Jones, Mark A. Jensen, Jeffrey R. Marks, Hanna Perz, Rashmi N. Sanbhadti, Robin J.N. Coope, Brian Craft, Andy Chu, Peter W. Laird, Eric E. Snyder, Chunhua Yan, Martin L. Ferguson, Junyuan Wu, Richard Varhol, Daniel J. Weisenberger, Yongjun Zhao, Ewa Leporowska, Ashley Hill, Katie Tarvin, M. Teresiak, David Pot, Nguyen Phi Hung, Helga Thorvaldsdottir, Erik Zmuda, Spring Yingchun Liu, Melissa Hart-Kothari, Joshua M. Stuart, Caroline Larson, Erin Pleasance, Nikolaus Schultz, Matthew Ibbs, Hubert Stoppler, Joelle Kalicki-Veizer, Andrey Sivachenko, Christopher C. Benz, Dawid Murawa, Swapna Mahurkar, Nicholas J. Petrelli, Lynda Chin, Juinhua Zhang, Pei Lin, Michael Mayo, Wilma L. Lingle, Julian Malicki, Robin Brookens, Ethan Cerami, Angela Tam, Shelley Alonso, Carmelo Gaudioso, Dominik Stoll, Anders Jacobsen, Stephen C. Benz, Mark S. Guyer, Wendy Winckler, Roel R.G. Verhaak, Chang-Jiun Wu, Raktim Sinha, Xiaping He, Nina Thiessen, Craig D. Shriver, Kenna R. Mills Shaw, Heidi J. Sofia, Martin Hirst, Stuart R. Jefferys, Robert Penny, Adam Brufsky, Kristen M. Leraas, Joshua F. McMichael, Brenda Rabeno, Inanc Birol, David J. Dooling, Peggy Yena, Richard A. Moore, Andrew D. Cherniack, Lucinda Fulton, Jessica K. Booker, Lihua Zou, Rileen Sinha, Michael D. Iglesia, Dennis T. Maglinte, Rohini Raman, Evan O. Paull, Rameen Beroukhim, Oleg Dolzhansky, Grace O. Silva, Jiashan Zhang, Witold Kycler, Janae V. Simons, Anisha Gulabani, Michael S. Lawrence, Peter Fielding, Huynh Quyet Thang, Peter A. Kigonya, Myra M. George, Jay Bowen, Haiyan I. Li, Robert E. Pyatt, Margi Sheth, Stacey Gabriel, Ana M. Gonzalez-Angulo, Hui Shen, Andrew J. Mungall, Carmen Gomez-Fernandez, Liming Yang, Hai Hu, Radoslaw Łaźniak, Olufunmilayo I. Olopade, Christine Czerwinski, Richard A. Hajek, Michael D. McLellan, Arash Shafiei, Matthew Meyerson, Gad Getz, Stanley Girshik, Cheng Fan, Shuying Liu, Olga Potapova, Alan P. Hoyle, Mia Grifford, Daniel C. Koboldt, Jacqueline D. Palchik, Jessica Walton, Greg Eley, Jamie Leigh Campbell, Thomas Zeng, Mikhail Abramov, Benjamin Gross, Brenda Deyarmin, Maciej Wiznerowicz, Natasja Wye, Ron Bose, Darlene Lee, Carl Morrison, Albert J. Kovatich, Andrew Crenshaw, Jessica Frick, John N. Weinstein, Adrian Ally, Nam H. Pho, Brady Bernard, Scott L. Carter, Gary K. Scott, Steven E. Schumacher, Barbara Tabak, D. Neil Hayes, Robert C. Onofrio, Sean D. Mooney, Mary D. Dyer, Mark Gerken, Erin Curley, Rajiv Dhir, Anna K. Unruh, Noreen Dhalla, Candace Shelton, Kevin R. Coombes, Richard Thorp, George E. Sandusky, A. Gordon Robertson, Marco A. Marra, Roy Tarnuzzer, Mark Backus, Aleix Prat, Kristin G. Ardlie, Daniel Di Cara, Richard Kreisberg, Kenneth H. Buetow, Jacqueline E. Schein, J. Todd Auman, Jianjiong Gao, Lisa Wise, Ling Li, James A. Robinson, Jonathan S. Berg, Tod D. Casasent, James N. Ingle, Brenda Ayala, Xiaolong Meng, Boris Reva, Rui Jing, Mark D. Pegram, Arkadiusz Spychała, Joan Pontius, Jeffrey A. Hooke, Daniel E. Carlin, Nils Weinhold, Jared R. Slobodan, Tom Bodenheimer, Wenbin Liu, Christopher K. Wong, W. Kimryn Rathmell, David Mallery, Paul T. Spellman, Hailei Zhang, Ryan Bressler, Deepak Srinivasan, Lisle E. Mose, Bryan Hernandez, Stella Somiari, Chad J. Creighton, Howard H. Sussman, Frederic Waldman, Matthew G. Soloway, and Universitat de Barcelona

Subjects
Proteomics, Oncologia, DNA Mutational Analysis, Genes, BRCA1, Retinoblastoma Protein, Phosphatidylinositol 3-Kinases, 0302 clinical medicine, Breast cancer, Exome, RNA, Neoplasm, Exome sequencing, Oligonucleotide Array Sequence Analysis, Ovarian Neoplasms, Genetics, 0303 health sciences, Multidisciplinary, Triple Negative Breast Neoplasms, Genomics, 3. Good health, Gene Expression Regulation, Neoplastic, Receptors, Estrogen, Oncology, 030220 oncology & carcinogenesis, Female, DNA Copy Number Variations, Class I Phosphatidylinositol 3-Kinases, Protein Array Analysis, MAP Kinase Kinase Kinase 1, Breast Neoplasms, GATA3 Transcription Factor, Biology, Article, Càncer de mama, Genetic Heterogeneity, 03 medical and health sciences, medicine, Humans, RNA, Messenger, 030304 developmental biology, MicroRNA sequencing, Genome, Human, Genetic heterogeneity, Gene Expression Profiling, Cancer, DNA Methylation, Genes, erbB-2, Genes, p53, medicine.disease, Claudin-Low, Expressió gènica, MicroRNAs, Genòmica, Mutation, Gene expression, Genes, Neoplasm
Abstract

We analysed primary breast cancers by genomic DNA copy number arrays, DNA methylation, exome sequencing, messenger RNA arrays, microRNA sequencing and reverse-phase protein arrays. Our ability to integrate information across platforms provided key insights into previously defined gene expression subtypes and demonstrated the existence of four main breast cancer classes when combining data from five platforms, each of which shows significant molecular heterogeneity. Somatic mutations in only three genes (TP53, PIK3CA and GATA3) occurred at >10% incidence across all breast cancers; however, there were numerous subtype-associated and novel gene mutations including the enrichment of specific mutations in GATA3, PIK3CA and MAP3K1 with the luminal A subtype. We identified two novel protein-expression-defined subgroups, possibly produced by stromal/microenvironmental elements, and integrated analyses identified specific signalling pathways dominant in each molecular subtype including a HER2/phosphorylated HER2/EGFR/phosphorylated EGFR signature within the HER2-enriched expression subtype. Comparison of basal-like breast tumours with high-grade serous ovarian tumours showed many molecular commonalities, indicating a related aetiology and similar therapeutic opportunities. The biological finding of the four main breast cancer subtypes caused by different subsets of genetic and epigenetic abnormalities raises the hypothesis that much of the clinically observable plasticity and heterogeneity occurs within, and not across, these major biological subtypes of breast cancer.

157. Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes

Author

Ulf Lindblad, Maria Sun, Noël P. Burtt, Joel N. Hirschhorn, Steve Schayer, Tiinamaija Tuomi, Marketa Sjögren, Jose C. Florez, Daniel Gaudet, Leif Groop, Thomas J. Hudson, David Altshuler, Peter Almgren, Kristin G. Ardlie, Marju Orho-Melander, and Mark J. Daly

Subjects
medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Type 2 diabetes, Scandinavian and Nordic Countries, Biology, Polymorphism, Single Nucleotide, White People, Insulin resistance, Polymorphism (computer science), Internal medicine, Insulin receptor substrate, Internal Medicine, medicine, Humans, Allele, Siblings, Insulin, Odds ratio, Phosphoproteins, medicine.disease, IRS1, Phenotype, Endocrinology, Amino Acid Substitution, Diabetes Mellitus, Type 2, Insulin Receptor Substrate Proteins
Abstract

The insulin receptor substrate (IRS)-1 is an important component of the insulin signal transduction cascade. Several reports suggest that a Gly→Arg change in codon 972 is associated with type 2 diabetes and related traits, and a recent meta-analysis reported a modest but nominally significant association with type 2 diabetes (odds ratio [OR] 1.25 in favor of carriers of the Arg allele [95% CI 1.05–1.48). To test the reproducibility of the model in a recent meta-analysis, we examined genotype-phenotype correlation in three large Caucasian samples (not previously reported for this variant) totaling 9,000 individuals (estimated to have >95% power to obtain a P < 0.05 for the OR of 1.25 estimated in the meta-analysis). In our combined sample, comprising 4,279 case and 3,532 control subjects, as well as 1,189 siblings discordant for type 2 diabetes, G972R was not associated with type 2 diabetes (OR 0.96 [0.84–1.10], P = 0.60). Genotype at G972R had no significant effect on various measures of insulin secretion or insulin resistance in a set of Scandinavian samples in whom we had detailed phenotypic data. In contrast, the well-documented associations of peroxisome proliferator-activated receptor γ P12A and Kir6.2 E23K with type 2 diabetes are both robustly observed in these 9,000 subjects, including an additional (previously unpublished) confirmation of Kir6.2 E23K and type 2 diabetes in the Polish and North American samples (combined OR 1.15 [1.05–1.26], P = 0.001). Despite genotyping 9,000 people and >95% power to reproduce the estimated OR from the recent meta-analysis, we were unable to replicate the association of the IRS-1 G972R polymorphism with type 2 diabetes.

158. A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2.

Author

Monica Chang, Charles M Rowland, Veronica E Garcia, Steven J Schrodi, Joseph J Catanese, Annette H M van der Helm-van Mil, Kristin G Ardlie, Christopher I Amos, Lindsey A Criswell, Daniel L Kastner, Peter K Gregersen, Fina A S Kurreeman, Rene E M Toes, Tom W J Huizinga, Michael F Seldin, and Ann B Begovich

Subjects
Genetics, QH426-470
Abstract

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (OR(common) = 1.28, trend P(comb) = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (P(comb) 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential.

Published
2008
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