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6 results on '"McCabe, Cristin"'

1. Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Author

Int Multiple Sclerosis Genetics, Mitrovic, Mitja, Patsopoulos, Nikoloas, Beecham, Ashley, Dankowski, Theresa, Goris, An, Dubois, Bénédicte, D'hooghe, Marie B, Lemmens, Robin, Van Damme, Philip, Bach Sondergaard, Helle, Sellebjerg, Finn, Soelberg Sorensen, Per, Ullum, Henrik, Thorner, Lise W, Werge, Thomas, Saarela, Janna, Cournu-Rebeix, Isabelle, Damotte, Vincent, Fontaine, Bertrand, Guillot-Noel, Lena, Lathrop, Mark, Vukusik, Sandra, Gourraud, Pierre-Antoine, Andlauer, Till FM, Pongratz, Viola, Buck, Dorothea, Gasperi, Christiane, Bayas, Antonios, Heesen, Christoph, Kümpfel, Tania, Linker, Ralf, Friedemann, Paul, Stangel, Martin, Tackenberg, Björn, Then Bergh, Florian, Warnke, Clemens, Wiendl, Heinz, Wildemann, Brigitte, Zettl, Uwe, Ziemann, Ulf, Tumani, Hayrettin, Gold, Ralf, Grummel, Verena, Hemmer, Bernhard, Knier, Benjamin, Lill, Christina, Luessi, Felix, Dardiotis, Efthimios, Agliardi, Cristina, Barizzone, Nadia, Mascia, Elisabetta, Bernardinelli, Luisa, Comi, Giancarlo, Cusi, Daniele, Esposito, Federica, Ferrè, Laura, Comi, Cristoforo, Galimberti, Daniela, Leone, Maurizio A, Sorosina, Melissa, Mescheriakova, Julia, Hintzen, Rogier, van Duijn, Cornelia, Theunissen, Charlotte E, Bos, Steffan D, Myhr, Kjell-Morten, Celius, Elisabeth G, Lie, Benedicte A, Spurkland, Anne, Comabella, Manuel, Montalban, Xavier, Alfredsson, Lars, Stridh, Pernilla, Hillert, Jan, Jagodic, Maja, Piehl, Fredrik, Jelcic, Ilijas, Martin, Roland, Sospedra, Mireia, Ban, Maria, Hawkins, Clive, Hysi, Pirro, Kalra, Seema, Karpe, Fredrik, Khadake, Jyoti, Lachance, Genevieve, Neville, Matthew, Santaniello, Adam, Caillier, Stacy J, Calavresi, Peter A, Cree, Bruce AC, Cross, Anne, Davis, Mary F, Haines, Jonathan L, de Bakker, Paul IW, Delgado, Silvia, Dembele, Marieme, Edwards, Keith, Fitzgerald, Kathryn C, Hakonarson, Hakon, Konidari, Ioanna, Lathi, Ellen, Manrique, Clara P, Pericak-Vance, Margaret A, Piccio, Laura, Schaefer, Cathy, McCabe, Cristin, Weiner, Howard, Goldstein, Jacqueline, Olsson, Tomas, Hadjigeorgiou, Georgios, Taylor, Bruce, Tajouri, Lotti, Charlesworth, Jac, Booth, David R, HArbo, Hanne F, Ivinson, Adrian J, Hauser, Stephen L, Compston, Alistair, Stewart, Graeme, Zipp, Frauke, Barcellos, Lisa F, Baranzini, Sergio E, Martinelli-Boneschi, Filippo, D'Alfonso, Sandra, Ziegler, Andreas, Oturai, Annette, McCauley, Jacob L, Sawcer, Stephen J, Oksenberg, Jorge R, De Jager, Philip L, Kockum, Ingrid, Hafler, David A, and Cotsapas, Chris

Subjects
Biochemistry & Molecular Biology, Science & Technology, REPLICATION, LINKAGE, Cell Biology, GENETIC RISK, GENOME-WIDE ASSOCIATION, VARIANTS, Life Sciences & Biomedicine, METAANALYSIS, POPULATION
Abstract

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS. ispartof: CELL vol:175 issue:6 pages:1679-1695 ispartof: location:United States status: published

Published
2018

2. Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Author

Mitrovič, Mitja, Patsopoulos, Nikolaos, Beecham, Ashley, Dankowski, Theresa, Goris, An, Dubois, Bénédicte, D’hooghe, Marie, Lemmens, Robin, Van Damme, Philip, Søndergaard, Helle Bach, Sellebjerg, Finn, Sorensen, Per Soelberg, Ullum, Henrik, Thørner, Lise, Werge, Thomas, Saarela, Janna, Cournu-Rebeix, Isabelle, Damotte, Vincent, Fontaine, Bertrand, Guillot-Noel, Lena, Lathrop, Mark, Vukusik, Sandra, Gourraud, Pierre-Antoine, Andlauer, Till F.M., Pongratz, Viola, Buck, Dorothea, Gasperi, Christiane, Bayas, Antonios, Heesen, Christoph, Kümpfel, Tania, Linker, Ralf, Paul, Friedemann, Stangel, Martin, Tackenberg, Björn, Bergh, Florian Then, Warnke, Clemens, Wiendl, Heinz, Wildemann, Brigitte, Zettl, Uwe, Ziemann, Ulf, Tumani, Hayrettin, Gold, Ralf, Grummel, Verena, Hemmer, Bernhard, Knier, Benjamin, Lill, Christina, Luessi, Felix, Dardiotis, Efthimios, Agliardi, Cristina, Barizzone, Nadia, Mascia, Elisabetta, Bernardinelli, Luisa, Comi, Giancarlo, Cusi, Daniele, Esposito, Federica, Ferrè, Laura, Comi, Cristoforo, Galimberti, Daniela, Leone, Maurizio, Sorosina, Melissa, Mescheriakova, Julia, Hintzen, Rogier, Van Duijn, Cornelia, Teunissen, Charlotte, Bos, Steffan, Myhr, Kjell-Morten, Celius, Elisabeth, Lie, Benedicte, Spurkland, Anne, Comabella, Manuel, Montalban, Xavier, Alfredsson, Lars, Stridh, Pernilla, Hillert, Jan, Jagodic, Maja, Piehl, Fredrik, Jelčić, Ilijas, Martin, Roland, Sospedra, Mireia, Ban, Maria, Hawkins, Clive, Hysi, Pirro, Kalra, Seema, Karpe, Fredrik, Khadake, Jyoti, Lachance, Genevieve, Neville, Matthew, Santaniello, Adam, Caillier, Stacy, Calabresi, Peter, Cree, Bruce A.C., Cross, Anne, Davis, Mary, Haines, Jonathan, de Bakker, Paul I.W., Delgado, Silvia, Dembele, Marieme, Edwards, Keith, Fitzgerald, Kathryn, Hakonarson, Hakon, Konidari, Ioanna, Lathi, Ellen, Manrique, Clara, Pericak-Vance, Margaret, Piccio, Laura, Schaefer, Cathy, McCabe, Cristin, Weiner, Howard, Goldstein, Jacqueline, Olsson, Tomas, Hadjigeorgiou, Georgios, Taylor, Bruce, Tajouri, Lotti, Charlesworth, Jac, Booth, David, Harbo, Hanne, Ivinson, Adrian, Hauser, Stephen, Compston, Alastair, Stewart, Graeme, Zipp, Frauke, Barcellos, Lisa, Baranzini, Sergio, Martinelli-Boneschi, Filippo, D’Alfonso, Sandra, Ziegler, Andreas, Oturai, Annette, McCauley, Jacob, Sawcer, Stephen, Oksenberg, Jorge, De Jager, Philip, Kockum, Ingrid, Hafler, David, Cotsapas, Chris, Søndergaard, Helle, Sorensen, Per, Andlauer, Till, Bergh, Florian, Cree, Bruce, De Bakker, Paul, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Centre de recherche en Myologie – U974 SU-INSERM, Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), and Centre de Recherche en Myologie

Subjects
[SDV.MHEP.AHA]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO]
Abstract

International audience; Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

Published
2018

3. Additional file 1: Table S1. of Dissecting the role of non-coding RNAs in the accumulation of amyloid and tau neuropathologies in Alzheimerâ s disease

Author

Patrick, Ellis, Sathyapriya Rajagopal, Hon-Kit Wong, McCabe, Cristin, Jishu Xu, Tang, Anna, Imboywa, Selina, Schneider, Julie, Pochet, Nathalie, Krichevsky, Anna, Chibnik, Lori, Bennett, David, and Jager, Philip De

Abstract

Demographic information. Table S3. A table of the correlations between each of the pertinent covariates, Study, Age, Sex, NNLS, PMI, RIN, NP, NFT and AD. Figure S1. Behavior of miRNAs implicated in other experiments. Figure S2. Differentially expressed miRNAs and lincRNAs. Figure S3. Validation of RIN association. (DOCX 483 kb)

Published
2017
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4. GEMS Project: A Platform to Investigate Multiple Sclerosis Risk

Author

Xia, Zongqi, White, Charles C., Owen, Emily K., Von Korff, Alina, Clarkson, Sarah R., McCabe, Cristin A., Cimpean, Maria, Winn, Phoebe A., Hoesing, Ashley, Steele, Sonya U., Cortese, Irene C. M., Chitnis, Tanuja, Weiner, Howard L., Reich, Daniel S., Chibnik, Lori B., and De Jager, Philip L.

Subjects
Adult, Male, Multiple Sclerosis, Incidence, Environment, Middle Aged, Polymorphism, Single Nucleotide, Risk Assessment, Article, United States, Risk Factors, Humans, Family, Female, Genetic Predisposition to Disease, Longitudinal Studies
Abstract

The Genes and Environment in Multiple Sclerosis project establishes a platform to investigate the events leading to multiple sclerosis (MS) in at-risk individuals. It has recruited 2,632 first-degree relatives from across the USA. Using an integrated genetic and environmental risk score, we identified subjects with twice the MS risk when compared to the average family member, and we report an initial incidence rate in these subjects that is 30 times greater than that of sporadic MS. We discuss the feasibility of large-scale studies of asymptomatic at-risk subjects that leverage modern tools of subject recruitment to execute collaborative projects.

Published
2015

5. Intersection of population variation and autoimmunity genetics in human T cell activation

Author

Ye, Chun Jimmie, Feng, Ting, Kwon, Ho-Keun, Raj, Towfique, Wilson, Michael T, Asinovski, Natasha, McCabe, Cristin, Lee, Michelle H, Frohlich, Irene, Paik, Hyun-il, Zaitlen, Noah, Hacohen, Nir, Stranger, Barbara, De Jager, Philip, Mathis, Diane, Regev, Aviv, and Benoist, Christophe

Subjects
CD4-Positive T-Lymphocytes, General Science & Technology, Quantitative Trait Loci, Black People, Autoimmunity, Lymphocyte Activation, Autoimmune Disease, White People, Asian People, Clinical Research, Genetics, Humans, 2.1 Biological and endogenous factors, Aetiology, Whites, Inflammatory and immune system, Human Genome, Genetic Variation, Blacks, Asians, Gene Expression Regulation, Multigene Family, Cytokines, Th17 Cells, Genome-Wide Association Study, Biotechnology
Abstract

T lymphocyte activation by antigen conditions adaptive immune responses and immunopathologies, but we know little about its variation in humans and its genetic or environmental roots. We analyzed gene expression in CD4(+) T cells during unbiased activation or in T helper 17 (T(H)17) conditions from 348 healthy participants representing European, Asian, and African ancestries. We observed interindividual variability, most marked for cytokine transcripts, with clear biases on the basis of ancestry, and following patterns more complex than simple T(H)1/2/17 partitions. We identified 39 genetic loci specifically associated in cis with activated gene expression. We further fine-mapped and validated a single-base variant that modulates YY1 binding and the activity of an enhancer element controlling the autoimmune-associated IL2RA gene, affecting its activity in activated but not regulatory T cells. Thus, interindividual variability affects the fundamental immunologic process of T helper activation, with important connections to autoimmune disease.

Published
2014

6. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci

Author

Srivastava, Gyan, Lunnon, Katie, Burgess, Jeremy, Yu, Lei, Ernst, Jason, McCabe, Cristin, Tang, Anna, Raj, Towfique, Replogle, Joseph, Brodeur, Wendy, Gabriel, Stacey, Younkin, Curtis, Zou, Fanggeng, Szyf, Moshe, Meissner, Alexander, Ertekin-Taner, Nilufer, Kellis, Manolis, Mill, Jonathan, De Jager, Philip L., Schalkwyk, Leonard C., Eaton, Matthew Lucas, Eaton, Matthew L., Keenan, Brendan T., Chai, High S., Younkin, Steven G., Epstein, Charles B., Schneider, Julie A., Bernstein, Bradley E., Chibnik, Lori B., Bennett, David A., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Eaton, Matthew Lucas, Ernst, Jason, Meissner, Alexander, and Kellis, Manolis

Subjects
Male, Aging, Genome-wide association study, Neurodegenerative, Alzheimer's Disease, 80 and over, 2.1 Biological and endogenous factors, Psychology, Protein Interaction Maps, Aetiology, Epigenomics, Genetics, Aged, 80 and over, General Neuroscience, Intracellular Signaling Peptides and Proteins, Brain, Adaptor Proteins, Nuclear Proteins, Methylation, Amyloidosis, Middle Aged, 3. Good health, CpG site, Neurological, DNA methylation, Female, Cognitive Sciences, Alzheimer's disease, Ankyrins, and over, Biology, Article, Alzheimer Disease, Acquired Cognitive Impairment, medicine, Humans, Genetic Predisposition to Disease, Gene, Adaptor Proteins, Signal Transducing, Aged, Neurology & Neurosurgery, Tumor Suppressor Proteins, Human Genome, Signal Transducing, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), DNA Methylation, medicine.disease, Brain Disorders, Differentially methylated regions, Dementia, CpG Islands, Carrier Proteins, Genome-Wide Association Study
Abstract

We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network., National Institutes of Health (U.S.) (Grant R01 AG036042), National Institutes of Health (U.S.) (Grant R01AG036836), National Institutes of Health (U.S.) (Grant R01 AG17917), National Institutes of Health (U.S.) (Grant R01AG15819), National Institutes of Health (U.S.) (Grant R01 AG032990), National Institutes of Health (U.S.) (Grant R01 AG18023), National Institutes of Health (U.S.) (Grant RC2 AG036547), National Institutes of Health (U.S.) (Grant P30 AG10161), National Institutes of Health (U.S.) (Grant P50 AG016574), National Institutes of Health (U.S.) (Grant U01 ES017155), National Institutes of Health (U.S.) (Grant KL2 RR024151), National Institutes of Health (U.S.) (Grant K25 AG041906-01)

Published
2014

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