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Find video protocols related to scientific articles indexed in Pubmed.
A polygenic burden of rare disruptive mutations in schizophrenia.
Nature
PUBLISHED: 01-22-2014
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Schizophrenia is a common disease with a complex aetiology, probably involving multiple and heterogeneous genetic factors. Here, by analysing the exome sequences of 2,536 schizophrenia cases and 2,543 controls, we demonstrate a polygenic burden primarily arising from rare (less than 1 in 10,000), disruptive mutations distributed across many genes. Particularly enriched gene sets include the voltage-gated calcium ion channel and the signalling complex formed by the activity-regulated cytoskeleton-associated scaffold protein (ARC) of the postsynaptic density, sets previously implicated by genome-wide association and copy-number variation studies. Similar to reports in autism, targets of the fragile X mental retardation protein (FMRP, product of FMR1) are enriched for case mutations. No individual gene-based test achieves significance after correction for multiple testing and we do not detect any alleles of moderately low frequency (approximately 0.5 to 1 per cent) and moderately large effect. Taken together, these data suggest that population-based exome sequencing can discover risk alleles and complements established gene-mapping paradigms in neuropsychiatric disease.
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Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol.
Leslie A Lange, Youna Hu, He Zhang, Chenyi Xue, Ellen M Schmidt, Zheng-zheng Tang, Chris Bizon, Ethan M Lange, Joshua D Smith, Emily H Turner, Goo Jun, Hyun Min Kang, Gina Peloso, Paul Auer, Kuo-Ping Li, Jason Flannick, Ji Zhang, Christian Fuchsberger, Kyle Gaulton, Cecilia Lindgren, Adam Locke, Alisa Manning, Xueling Sim, Manuel A Rivas, Oddgeir L Holmen, Omri Gottesman, Yingchang Lu, Douglas Ruderfer, Eli A Stahl, Qing Duan, Yun Li, Peter Durda, Shuo Jiao, Aaron Isaacs, Albert Hofman, Joshua C Bis, Adolfo Correa, Michael E Griswold, Johanna Jakobsdottir, Albert V Smith, Pamela J Schreiner, Mary F Feitosa, Qunyuan Zhang, Jennifer E Huffman, Jacy Crosby, Christina L Wassel, Ron Do, Nora Franceschini, Lisa W Martin, Jennifer G Robinson, Themistocles L Assimes, David R Crosslin, Elisabeth A Rosenthal, Michael Tsai, Mark J Rieder, Deborah N Farlow, Aaron R Folsom, Thomas Lumley, Ervin R Fox, Christopher S Carlson, Ulrike Peters, Rebecca D Jackson, Cornelia M van Duijn, André G Uitterlinden, Daniel Levy, Jerome I Rotter, Herman A Taylor, Vilmundur Gudnason, David S Siscovick, Myriam Fornage, Ingrid B Borecki, Caroline Hayward, Igor Rudan, Y Eugene Chen, Erwin P Bottinger, Ruth J F Loos, Pål Sætrom, Kristian Hveem, Michael Boehnke, Leif Groop, Mark McCarthy, Thomas Meitinger, Christie M Ballantyne, Stacey B Gabriel, Christopher J O'Donnell, Wendy S Post, Kari E North, Alexander P Reiner, Eric Boerwinkle, Bruce M Psaty, David Altshuler, Sekar Kathiresan, Dan-Yu Lin, Gail P Jarvik, L Adrienne Cupples, Charles Kooperberg, James G Wilson, Deborah A Nickerson, Gonçalo R Abecasis, Stephen S Rich, Russell P Tracy, Cristen J Willer, .
Am. J. Hum. Genet.
PUBLISHED: 01-14-2014
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Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.
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Genetics of rheumatoid arthritis contributes to biology and drug discovery.
Yukinori Okada, Di Wu, Gosia Trynka, Towfique Raj, Chikashi Terao, Katsunori Ikari, Yuta Kochi, Koichiro Ohmura, Akari Suzuki, Shinji Yoshida, Robert R Graham, Arun Manoharan, Ward Ortmann, Tushar Bhangale, Joshua C Denny, Robert J Carroll, Anne E Eyler, Jeffrey D Greenberg, Joel M Kremer, Dimitrios A Pappas, Lei Jiang, Jian Yin, Lingying Ye, Ding-Feng Su, Jian Yang, Gang Xie, Ed Keystone, Harm-Jan Westra, Tonu Esko, Andres Metspalu, Xuezhong Zhou, Namrata Gupta, Daniel Mirel, Eli A Stahl, Dorothée Diogo, Jing Cui, Katherine Liao, Michael H Guo, Keiko Myouzen, Takahisa Kawaguchi, Marieke J H Coenen, Piet L C M van Riel, Mart A F J van de Laar, Henk-Jan Guchelaar, Tom W J Huizinga, Philippe Dieudé, Xavier Mariette, S Louis Bridges, Alexandra Zhernakova, René E M Toes, Paul P Tak, Corinne Miceli-Richard, So-Young Bang, Hye-Soon Lee, Javier Martín, Miguel A González-Gay, Luis Rodriguez-Rodriguez, Solbritt Rantapää-Dahlqvist, Lisbeth Arlestig, Hyon K Choi, Yoichiro Kamatani, Pilar Galán, Mark Lathrop, , Steve Eyre, John Bowes, Anne Barton, Niek de Vries, Larry W Moreland, Lindsey A Criswell, Elizabeth W Karlson, Atsuo Taniguchi, Ryo Yamada, Michiaki Kubo, Jun S Liu, Sang-Cheol Bae, Jane Worthington, Leonid Padyukov, Lars Klareskog, Peter K Gregersen, Soumya Raychaudhuri, Barbara E Stranger, Philip L De Jager, Lude Franke, Peter M Visscher, Matthew A Brown, Hisashi Yamanaka, Tsuneyo Mimori, Atsushi Takahashi, Huji Xu, Timothy W Behrens, Katherine A Siminovitch, Shigeki Momohara, Fumihiko Matsuda, Kazuhiko Yamamoto, Robert M Plenge.
Nature
PUBLISHED: 01-07-2014
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A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ?10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
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Allele-specific methylation occurs at genetic variants associated with complex disease.
PLoS ONE
PUBLISHED: 01-01-2014
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We hypothesize that the phenomenon of allele-specific methylation (ASM) may underlie the phenotypic effects of multiple variants identified by Genome-Wide Association studies (GWAS). We evaluate ASM in a human population and document its genome-wide patterns in an initial screen at up to 380,678 sites within the genome, or up to 5% of the total genomic CpGs. We show that while substantial inter-individual variation exists, 5% of assessed sites show evidence of ASM in at least six samples; the majority of these events (81%) are under genetic influence. Many of these cis-regulated ASM variants are also eQTLs in peripheral blood mononuclear cells and monocytes and/or in high linkage-disequilibrium with variants linked to complex disease. Finally, focusing on autoimmune phenotypes, we extend this initial screen to confirm the association of cis-regulated ASM with multiple complex disease-associated variants in an independent population using next-generation bisulfite sequencing. These four variants are implicated in complex phenotypes such as ulcerative colitis and AIDS progression disease (rs10491434), Celiac disease (rs2762051), Crohn's disease, IgA nephropathy and early-onset inflammatory bowel disease (rs713875) and height (rs6569648). Our results suggest cis-regulated ASM may provide a mechanistic link between the non-coding genetic changes and phenotypic variation observed in these diseases and further suggests a route to integrating DNA methylation status with GWAS results.
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Integration of sequence data from a Consanguineous family with genetic data from an outbred population identifies PLB1 as a candidate rheumatoid arthritis risk gene.
PLoS ONE
PUBLISHED: 01-01-2014
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Integrating genetic data from families with highly penetrant forms of disease together with genetic data from outbred populations represents a promising strategy to uncover the complete frequency spectrum of risk alleles for complex traits such as rheumatoid arthritis (RA). Here, we demonstrate that rare, low-frequency and common alleles at one gene locus, phospholipase B1 (PLB1), might contribute to risk of RA in a 4-generation consanguineous pedigree (Middle Eastern ancestry) and also in unrelated individuals from the general population (European ancestry). Through identity-by-descent (IBD) mapping and whole-exome sequencing, we identified a non-synonymous c.2263G>C (p.G755R) mutation at the PLB1 gene on 2q23, which significantly co-segregated with RA in family members with a dominant mode of inheritance (P = 0.009). We further evaluated PLB1 variants and risk of RA using a GWAS meta-analysis of 8,875 RA cases and 29,367 controls of European ancestry. We identified significant contributions of two independent non-coding variants near PLB1 with risk of RA (rs116018341 [MAF = 0.042] and rs116541814 [MAF = 0.021], combined P = 3.2 × 10(-6)). Finally, we performed deep exon sequencing of PLB1 in 1,088 RA cases and 1,088 controls (European ancestry), and identified suggestive dispersion of rare protein-coding variant frequencies between cases and controls (P = 0.049 for C-alpha test and P = 0.055 for SKAT). Together, these data suggest that PLB1 is a candidate risk gene for RA. Future studies to characterize the full spectrum of genetic risk in the PLB1 genetic locus are warranted.
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Quantifying Missing Heritability at Known GWAS Loci.
PLoS Genet.
PUBLISHED: 12-01-2013
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Recent work has shown that much of the missing heritability of complex traits can be resolved by estimates of heritability explained by all genotyped SNPs. However, it is currently unknown how much heritability is missing due to poor tagging or additional causal variants at known GWAS loci. Here, we use variance components to quantify the heritability explained by all SNPs at known GWAS loci in nine diseases from WTCCC1 and WTCCC2. After accounting for expectation, we observed all SNPs at known GWAS loci to explain [Formula: see text] more heritability than GWAS-associated SNPs on average ([Formula: see text]). For some diseases, this increase was individually significant: [Formula: see text] for Multiple Sclerosis (MS) ([Formula: see text]) and [Formula: see text] for Crohns Disease (CD) ([Formula: see text]); all analyses of autoimmune diseases excluded the well-studied MHC region. Additionally, we found that GWAS loci from other related traits also explained significant heritability. The union of all autoimmune disease loci explained [Formula: see text] more MS heritability than known MS SNPs ([Formula: see text]) and [Formula: see text] more CD heritability than known CD SNPs ([Formula: see text]), with an analogous increase for all autoimmune diseases analyzed. We also observed significant increases in an analysis of [Formula: see text] Rheumatoid Arthritis (RA) samples typed on ImmunoChip, with [Formula: see text] more heritability from all SNPs at GWAS loci ([Formula: see text]) and [Formula: see text] more heritability from all autoimmune disease loci ([Formula: see text]) compared to known RA SNPs (including those identified in this cohort). Our methods adjust for LD between SNPs, which can bias standard estimates of heritability from SNPs even if all causal variants are typed. By comparing adjusted estimates, we hypothesize that the genome-wide distribution of causal variants is enriched for low-frequency alleles, but that causal variants at known GWAS loci are skewed towards common alleles. These findings have important ramifications for fine-mapping study design and our understanding of complex disease architecture.
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Genome-wide association analysis identifies 13 new risk loci for schizophrenia.
Stephan Ripke, Colm O'Dushlaine, Kimberly Chambert, Jennifer L Moran, Anna K Kähler, Susanne Akterin, Sarah E Bergen, Ann L Collins, James J Crowley, Menachem Fromer, Yunjung Kim, Sang Hong Lee, Patrik K E Magnusson, Nick Sanchez, Eli A Stahl, Stephanie Williams, Naomi R Wray, Kai Xia, Francesco Bettella, Anders D Borglum, Brendan K Bulik-Sullivan, Paul Cormican, Nick Craddock, Christiaan de Leeuw, Naser Durmishi, Michael Gill, Vera Golimbet, Marian L Hamshere, Peter Holmans, David M Hougaard, Kenneth S Kendler, Kuang Lin, Derek W Morris, Ole Mors, Preben B Mortensen, Benjamin M Neale, Francis A O'Neill, Michael J Owen, Milica Pejović Milovančević, Danielle Posthuma, John Powell, Alexander L Richards, Brien P Riley, Douglas Ruderfer, Dan Rujescu, Engilbert Sigurdsson, Teimuraz Silagadze, August B Smit, Hreinn Stefansson, Stacy Steinberg, Jaana Suvisaari, Sarah Tosato, Matthijs Verhage, James T Walters, , Douglas F Levinson, Pablo V Gejman, Claudine Laurent, Bryan J Mowry, Michael C O'Donovan, Ann E Pulver, Sibylle G Schwab, Dieter B Wildenauer, Frank Dudbridge, Jianxin Shi, Margot Albus, Madeline Alexander, Dominique Campion, David Cohen, Dimitris Dikeos, Jubao Duan, Peter Eichhammer, Stephanie Godard, Mark Hansen, F Bernard Lerer, Kung-Yee Liang, Wolfgang Maier, Jacques Mallet, Deborah A Nertney, Gerald Nestadt, Nadine Norton, George N Papadimitriou, Robert Ribble, Alan R Sanders, Jeremy M Silverman, Dermot Walsh, Nigel M Williams, Brandon Wormley, Maria J Arranz, Steven Bakker, Stephan Bender, Elvira Bramon, David Collier, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Assen Jablensky, René S Kahn, Luba Kalaydjieva, Stephen Lawrie, Cathryn M Lewis, Don H Linszen, Ignacio Mata, Andrew McIntosh, Robin M Murray, Roel A Ophoff, Jim van Os, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Peter Donnelly, Inês Barroso, Jenefer M Blackwell, Matthew A Brown, Juan P Casas, Aiden P Corvin, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S Markus, Christopher G Mathew, Colin N A Palmer, Robert Plomin, Anna Rautanen, Stephen J Sawcer, Richard C Trembath, Ananth C Viswanathan, Nicholas W Wood, Chris C A Spencer, Gavin Band, Celine Bellenguez, Colin Freeman, Garrett Hellenthal, Eleni Giannoulatou, Matti Pirinen, Richard D Pearson, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Sarah E Hunt, Sarah Edkins, Rhian Gwilliam, Hannah Blackburn, Suzannah J Bumpstead, Serge Dronov, Matthew Gillman, Emma Gray, Naomi Hammond, Alagurevathi Jayakumar, Owen T McCann, Jennifer Liddle, Simon C Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew J Waller, Paul Weston, Sara Widaa, Pamela Whittaker, Mark I McCarthy, Kari Stefansson, Edward Scolnick, Shaun Purcell, Steven A McCarroll, Pamela Sklar, Christina M Hultman, Patrick F Sullivan.
Nat. Genet.
PUBLISHED: 08-01-2013
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Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.
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Human genetics in rheumatoid arthritis guides a high-throughput drug screen of the CD40 signaling pathway.
PLoS Genet.
PUBLISHED: 05-01-2013
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Although genetic and non-genetic studies in mouse and human implicate the CD40 pathway in rheumatoid arthritis (RA), there are no approved drugs that inhibit CD40 signaling for clinical care in RA or any other disease. Here, we sought to understand the biological consequences of a CD40 risk variant in RA discovered by a previous genome-wide association study (GWAS) and to perform a high-throughput drug screen for modulators of CD40 signaling based on human genetic findings. First, we fine-map the CD40 risk locus in 7,222 seropositive RA patients and 15,870 controls, together with deep sequencing of CD40 coding exons in 500 RA cases and 650 controls, to identify a single SNP that explains the entire signal of association (rs4810485, P?=?1.4×10(-9)). Second, we demonstrate that subjects homozygous for the RA risk allele have ?33% more CD40 on the surface of primary human CD19+ B lymphocytes than subjects homozygous for the non-risk allele (P?=?10(-9)), a finding corroborated by expression quantitative trait loci (eQTL) analysis in peripheral blood mononuclear cells from 1,469 healthy control individuals. Third, we use retroviral shRNA infection to perturb the amount of CD40 on the surface of a human B lymphocyte cell line (BL2) and observe a direct correlation between amount of CD40 protein and phosphorylation of RelA (p65), a subunit of the NF-?B transcription factor. Finally, we develop a high-throughput NF-?B luciferase reporter assay in BL2 cells activated with trimerized CD40 ligand (tCD40L) and conduct an HTS of 1,982 chemical compounds and FDA-approved drugs. After a series of counter-screens and testing in primary human CD19+ B cells, we identify 2 novel chemical inhibitors not previously implicated in inflammation or CD40-mediated NF-?B signaling. Our study demonstrates proof-of-concept that human genetics can be used to guide the development of phenotype-based, high-throughput small-molecule screens to identify potential novel therapies in complex traits such as RA.
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Polygenic heritability estimates in pharmacogenetics: focus on asthma and related phenotypes.
Pharmacogenet. Genomics
PUBLISHED: 03-28-2013
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Although accurate measures of heritability are required to understand the pharmacogenetic basis of drug treatment response, these are generally not available, as it is unfeasible to give medications to individuals for which treatment is not indicated. Using a polygenic linear mixed modeling approach, we estimated lower bounds on the heritability of asthma and the heritability of two related drug-response phenotypes, bronchodilator response and airway hyperreactivity, using genome-wide single nucleotide polymorphism (SNP) data from existing asthma cohorts. Our estimate of the heritability for bronchodilator response is 28.5% (SE 16%, P=0.043) and airway hyperresponsiveness is 51.1% (SE 34%, P=0.064), whereas we estimate asthma genetic liability at 61.5% (SE 16%, P<0.001). Our results agree with the previously published estimates of the heritability of these traits, suggesting that the linear mixed modeling method is useful for computing the heritability of other pharmacogenetic traits. Furthermore, our results indicate that multiple SNP main effects, including SNPs as yet unidentified by genome-wide association study methods, together explain a sizable portion of the heritability of these traits.
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Genome-wide association study and gene expression analysis identifies CD84 as a predictor of response to etanercept therapy in rheumatoid arthritis.
PLoS Genet.
PUBLISHED: 01-13-2013
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Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (?DAS) in the etanercept subset of patients (P = 8 × 10(-8)), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3 UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1 × 10(-11) in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ?DAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry.
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Integrating autoimmune risk loci with gene-expression data identifies specific pathogenic immune cell subsets.
Am. J. Hum. Genet.
PUBLISHED: 07-25-2011
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Although genome-wide association studies have implicated many individual loci in complex diseases, identifying the exact causal alleles and the cell types within which they act remains greatly challenging. To ultimately understand disease mechanism, researchers must carefully conceive functional studies in relevant pathogenic cell types to demonstrate the cellular impact of disease-associated genetic variants. This challenge is highlighted in autoimmune diseases, such as rheumatoid arthritis, where any of a broad range of immunological cell types might potentially be impacted by genetic variation to cause disease. To this end, we developed a statistical approach to identify potentially pathogenic cell types in autoimmune diseases by using a gene-expression data set of 223 murine-sorted immune cells from the Immunological Genome Consortium. We found enrichment of transitional B cell genes in systemic lupus erythematosus (p = 5.9 × 10(-6)) and epithelial-associated stimulated dendritic cell genes in Crohn disease (p = 1.6 × 10(-5)). Finally, we demonstrated enrichment of CD4+ effector memory T cell genes within rheumatoid arthritis loci (p < 10(-6)). To further validate the role of CD4+ effector memory T cells within rheumatoid arthritis, we identified 436 loci that were not yet known to be associated with the disease but that had a statistically suggestive association in a recent genome-wide association study (GWAS) meta-analysis (p(GWAS) < 0.001). Even among these putative loci, we noted a significant enrichment for genes specifically expressed in CD4+ effector memory T cells (p = 1.25 × 10(-4)). These cell types are primary candidates for future functional studies to reveal the role of risk alleles in autoimmunity. Our approach has application in other phenotypes, outside of autoimmunity, where many loci have been discovered and high-quality cell-type-specific gene expression is available.
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Meta-analysis of genome-wide association studies in celiac disease and rheumatoid arthritis identifies fourteen non-HLA shared loci.
PLoS Genet.
PUBLISHED: 02-24-2011
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Epidemiology and candidate gene studies indicate a shared genetic basis for celiac disease (CD) and rheumatoid arthritis (RA), but the extent of this sharing has not been systematically explored. Previous studies demonstrate that 6 of the established non-HLA CD and RA risk loci (out of 26 loci for each disease) are shared between both diseases. We hypothesized that there are additional shared risk alleles and that combining genome-wide association study (GWAS) data from each disease would increase power to identify these shared risk alleles. We performed a meta-analysis of two published GWAS on CD (4,533 cases and 10,750 controls) and RA (5,539 cases and 17,231 controls). After genotyping the top associated SNPs in 2,169 CD cases and 2,255 controls, and 2,845 RA cases and 4,944 controls, 8 additional SNPs demonstrated P<5 × 10(-8) in a combined analysis of all 50,266 samples, including four SNPs that have not been previously confirmed in either disease: rs10892279 near the DDX6 gene (P(combined)?=? 1.2 × 10(-12)), rs864537 near CD247 (P(combined)?=? 2.2 × 10(-11)), rs2298428 near UBE2L3 (P(combined)?=? 2.5 × 10(-10)), and rs11203203 near UBASH3A (P(combined)?=? 1.1 × 10(-8)). We also confirmed that 4 gene loci previously established in either CD or RA are associated with the other autoimmune disease at combined P<5 × 10(-8) (SH2B3, 8q24, STAT4, and TRAF1-C5). From the 14 shared gene loci, 7 SNPs showed a genome-wide significant effect on expression of one or more transcripts in the linkage disequilibrium (LD) block around the SNP. These associations implicate antigen presentation and T-cell activation as a shared mechanism of disease pathogenesis and underscore the utility of cross-disease meta-analysis for identification of genetic risk factors with pleiotropic effects between two clinically distinct diseases.
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Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records.
Am. J. Hum. Genet.
PUBLISHED: 01-08-2011
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Discovering and following up on genetic associations with complex phenotypes require large patient cohorts. This is particularly true for patient cohorts of diverse ancestry and clinically relevant subsets of disease. The ability to mine the electronic health records (EHRs) of patients followed as part of routine clinical care provides a potential opportunity to efficiently identify affected cases and unaffected controls for appropriate-sized genetic studies. Here, we demonstrate proof-of-concept that it is possible to use EHR data linked with biospecimens to establish a multi-ethnic case-control cohort for genetic research of a complex disease, rheumatoid arthritis (RA). In 1,515 EHR-derived RA cases and 1,480 controls matched for both genetic ancestry and disease-specific autoantibodies (anti-citrullinated protein antibodies [ACPA]), we demonstrate that the odds ratios and aggregate genetic risk score (GRS) of known RA risk alleles measured in individuals of European ancestry within our EHR cohort are nearly identical to those derived from a genome-wide association study (GWAS) of 5,539 autoantibody-positive RA cases and 20,169 controls. We extend this approach to other ethnic groups and identify a large overlap in the GRS among individuals of European, African, East Asian, and Hispanic ancestry. We also demonstrate that the distribution of a GRS based on 28 non-HLA risk alleles in ACPA+ cases partially overlaps with ACPA- subgroup of RA cases. Our study demonstrates that the genetic basis of rheumatoid arthritis risk is similar among cases of diverse ancestry divided into subsets based on ACPA status and emphasizes the utility of linking EHR clinical data with biospecimens for genetic studies.
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Progress and promise of genome-wide association studies for human complex trait genetics.
Genetics
PUBLISHED: 11-29-2010
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Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.
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Exploring genetic and expression differences between physiologically extreme ecotypes: comparative genomic hybridization and gene expression studies of Kas-1 and Tsu-1 accessions of Arabidopsis thaliana.
Plant Cell Environ.
PUBLISHED: 03-18-2010
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Recent studies have documented remarkable genetic variation among Arabidopsis thaliana accessions collected from diverse habitats. Of particular interest are accessions with putatively locally adapted phenotypes - that is, accessions with attributes that are likely adaptive at their sites of origin. These genotypes may provide insight into the genetic basis of adaptive evolution as well as allow the discovery of genes of ecological importance. We studied the physiology, genome content and gene expression of two physiologically extreme accessions (Tsu-1 from Tsushima, Japan and Kas-1 from Kashmir, India). Our study was conducted under two levels of soil moisture and accompanied by physiological measurements to characterize early responses to soil drying. Genomic hybridizations identified 42,503 single feature polymorphisms (SFP) between accessions, providing an initial screen for genetic differences. Transcript profiling identified a large number (5996) of genes exhibiting constitutive differences in expression including genes involved in many biological pathways. Mild soil drying resulted in only subtle physiological responses but resulted in gene expression changes in hundreds of transcripts, including 352 genes exhibiting differential responses between accessions. Our results highlight the value of genomic studies of natural accessions as well as identify a number of candidate genes underlying physiological differences between Tsu-1 and Kas-1.
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Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci.
Nat. Genet.
PUBLISHED: 02-25-2010
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To identify new genetic risk factors for rheumatoid arthritis, we conducted a genome-wide association study meta-analysis of 5,539 autoantibody-positive individuals with rheumatoid arthritis (cases) and 20,169 controls of European descent, followed by replication in an independent set of 6,768 rheumatoid arthritis cases and 8,806 controls. Of 34 SNPs selected for replication, 7 new rheumatoid arthritis risk alleles were identified at genome-wide significance (P < 5 x 10(-8)) in an analysis of all 41,282 samples. The associated SNPs are near genes of known immune function, including IL6ST, SPRED2, RBPJ, CCR6, IRF5 and PXK. We also refined associations at two established rheumatoid arthritis risk loci (IL2RA and CCL21) and confirmed the association at AFF3. These new associations bring the total number of confirmed rheumatoid arthritis risk loci to 31 among individuals of European ancestry. An additional 11 SNPs replicated at P < 0.05, many of which are validated autoimmune risk alleles, suggesting that most represent genuine rheumatoid arthritis risk alleles.
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Genetic variants at CD28, PRDM1 and CD2/CD58 are associated with rheumatoid arthritis risk.
Nat. Genet.
PUBLISHED: 05-13-2009
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To discover new rheumatoid arthritis (RA) risk loci, we systematically examined 370 SNPs from 179 independent loci with P < 0.001 in a published meta-analysis of RA genome-wide association studies (GWAS) of 3,393 cases and 12,462 controls. We used Gene Relationships Across Implicated Loci (GRAIL), a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three were convincingly validated: CD2-CD58 (rs11586238, P = 1 x 10(-6) replication, P = 1 x 10(-9) overall), CD28 (rs1980422, P = 5 x 10(-6) replication, P = 1 x 10(-9) overall) and PRDM1 (rs548234, P = 1 x 10(-5) replication, P = 2 x 10(-8) overall). An additional four were replicated (P < 0.0023): TAGAP (rs394581, P = 0.0002 replication, P = 4 x 10(-7) overall), PTPRC (rs10919563, P = 0.0003 replication, P = 7 x 10(-7) overall), TRAF6-RAG1 (rs540386, P = 0.0008 replication, P = 4 x 10(-6) overall) and FCGR2A (rs12746613, P = 0.0022 replication, P = 2 x 10(-5) overall). Many of these loci are also associated to other immunologic diseases.
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Recent speciation associated with the evolution of selfing in Capsella.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 02-19-2009
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The evolution from outcrossing to predominant self-fertilization represents one of the most common transitions in flowering plant evolution. This shift in mating system is almost universally associated with the "selfing syndrome," characterized by marked reduction in flower size and a breakdown of the morphological and genetic mechanisms that prevent self-fertilization. In general, the timescale in which these transitions occur, and the evolutionary dynamics associated with the evolution of the selfing syndrome are poorly known. We investigated the origin and evolution of selfing in the annual plant Capsella rubella from its self-incompatible, outcrossing progenitor Capsella grandiflora by characterizing multilocus patterns of DNA sequence variation at nuclear genes. We estimate that the transition to selfing and subsequent geographic expansion have taken place during the past 20,000 years. This transition was probably associated with a shift from stable equilibrium toward a near-complete population bottleneck causing a major reduction in effective population size. The timing and severe founder event support the hypothesis that selfing was favored during colonization as new habitats emerged after the last glaciation and the expansion of agriculture. These results suggest that natural selection for reproductive assurance can lead to major morphological evolution and speciation on relatively short evolutionary timescales.
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Rare, low-frequency, and common variants in the protein-coding sequence of biological candidate genes from GWASs contribute to risk of rheumatoid arthritis.
Am. J. Hum. Genet.
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The extent to which variants in the protein-coding sequence of genes contribute to risk of rheumatoid arthritis (RA) is unknown. In this study, we addressed this issue by deep exon sequencing and large-scale genotyping of 25 biological candidate genes located within RA risk loci discovered by genome-wide association studies (GWASs). First, we assessed the contribution of rare coding variants in the 25 genes to the risk of RA in a pooled sequencing study of 500 RA cases and 650 controls of European ancestry. We observed an accumulation of rare nonsynonymous variants exclusive to RA cases in IL2RA and IL2RB (burden test: p = 0.007 and p = 0.018, respectively). Next, we assessed the aggregate contribution of low-frequency and common coding variants to the risk of RA by dense genotyping of the 25 gene loci in 10,609 RA cases and 35,605 controls. We observed a strong enrichment of coding variants with a nominal signal of association with RA (p < 0.05) after adjusting for the best signal of association at the loci (p(enrichment) = 6.4 × 10(-4)). For one locus containing CD2, we found that a missense variant, rs699738 (c.798C>A [p.His266Gln]), and a noncoding variant, rs624988, reside on distinct haplotypes and independently contribute to the risk of RA (p = 4.6 × 10(-6)). Overall, our results indicate that variants (distributed across the allele-frequency spectrum) within the protein-coding portion of a subset of biological candidate genes identified by GWASs contribute to the risk of RA. Further, we have demonstrated that very large sample sizes will be required for comprehensively identifying the independent alleles contributing to the missing heritability of RA.
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Genome-wide association analysis of anti-TNF drug response in patients with rheumatoid arthritis.
Ann. Rheum. Dis.
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Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach.
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High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.
Nat. Genet.
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Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.
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Rheumatoid arthritis. Evidence for a genetic component to disease severity in RA.
Nat Rev Rheumatol
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Rheumatoid arthritis (RA) is partly heritable; genetic and serological markers are known to confer risk of developing pathology. But given clinical heterogeneity in RA, can we predict who will develop severe disease? Substantial heritability of erosive progression rates has now been identified, but better prognostic biomarkers remain wanting.
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Meta-analysis identifies nine new loci associated with rheumatoid arthritis in the Japanese population.
Nat. Genet.
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Rheumatoid arthritis is a common autoimmune disease characterized by chronic inflammation. We report a meta-analysis of genome-wide association studies (GWAS) in a Japanese population including 4,074 individuals with rheumatoid arthritis (cases) and 16,891 controls, followed by a replication in 5,277 rheumatoid arthritis cases and 21,684 controls. Our study identified nine loci newly associated with rheumatoid arthritis at a threshold of P < 5.0 × 10(-8), including B3GNT2, ANXA3, CSF2, CD83, NFKBIE, ARID5B, PDE2A-ARAP1, PLD4 and PTPN2. ANXA3 was also associated with susceptibility to systemic lupus erythematosus (P = 0.0040), and B3GNT2 and ARID5B were associated with Graves disease (P = 3.5 × 10(-4) and 2.9 × 10(-4), respectively). We conducted a multi-ancestry comparative analysis with a previous meta-analysis in individuals of European descent (5,539 rheumatoid arthritis cases and 20,169 controls). This provided evidence of shared genetic risks of rheumatoid arthritis between the populations.
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Bayesian inference analyses of the polygenic architecture of rheumatoid arthritis.
Nat. Genet.
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The genetic architectures of common, complex diseases are largely uncharacterized. We modeled the genetic architecture underlying genome-wide association study (GWAS) data for rheumatoid arthritis and developed a new method using polygenic risk-score analyses to infer the total liability-scale variance explained by associated GWAS SNPs. Using this method, we estimated that, together, thousands of SNPs from rheumatoid arthritis GWAS explain an additional 20% of disease risk (excluding known associated loci). We further tested this method on datasets for three additional diseases and obtained comparable estimates for celiac disease (43% excluding the major histocompatibility complex), myocardial infarction and coronary artery disease (48%) and type 2 diabetes (49%). Our results are consistent with simulated genetic models in which hundreds of associated loci harbor common causal variants and a smaller number of loci harbor multiple rare causal variants. These analyses suggest that GWAS will continue to be highly productive for the discovery of additional susceptibility loci for common diseases.
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Use of a multiethnic approach to identify rheumatoid- arthritis-susceptibility loci, 1p36 and 17q12.
Am. J. Hum. Genet.
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We have previously shown that rheumatoid arthritis (RA) risk alleles overlap between different ethnic groups. Here, we utilize a multiethnic approach to show that we can effectively discover RA risk alleles. Thirteen putatively associated SNPs that had not yet exceeded genome-wide significance (p < 5 × 10(-8)) in our previous RA genome-wide association study (GWAS) were analyzed in independent sample sets consisting of 4,366 cases and 17,765 controls of European, African American, and East Asian ancestry. Additionally, we conducted an overall association test across all 65,833 samples (a GWAS meta-analysis plus the replication samples). Of the 13 SNPs investigated, four were significantly below the study-wide Bonferroni corrected p value threshold (p < 0.0038) in the replication samples. Two SNPs (rs3890745 at the 1p36 locus [p = 2.3 × 10(-12)] and rs2872507 at the 17q12 locus [p = 1.7 × 10(-9)]) surpassed genome-wide significance in all 16,659 RA cases and 49,174 controls combined. We used available GWAS data to fine map these two loci in Europeans and East Asians, and we found that the same allele conferred risk in both ethnic groups. A series of bioinformatic analyses identified TNFRSF14-MMEL1 at the 1p36 locus and IKZF3-ORMDL3-GSDMB at the 17q12 locus as the genes most likely associated with RA. These findings demonstrate empirically that a multiethnic approach is an effective strategy for discovering RA risk loci, and they suggest that combining GWASs across ethnic groups represents an efficient strategy for gaining statistical power.
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Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis.
Nat. Genet.
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The genetic association of the major histocompatibility complex (MHC) to rheumatoid arthritis risk has commonly been attributed to alleles in HLA-DRB1. However, debate persists about the identity of the causal variants in HLA-DRB1 and the presence of independent effects elsewhere in the MHC. Using existing genome-wide SNP data in 5,018 individuals with seropositive rheumatoid arthritis (cases) and 14,974 unaffected controls, we imputed and tested classical alleles and amino acid polymorphisms in HLA-A, HLA-B, HLA-C, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1 and HLA-DRB1, as well as 3,117 SNPs across the MHC. Conditional and haplotype analyses identified that three amino acid positions (11, 71 and 74) in HLA-DR?1 and single-amino-acid polymorphisms in HLA-B (at position 9) and HLA-DP?1 (at position 9), which are all located in peptide-binding grooves, almost completely explain the MHC association to rheumatoid arthritis risk. This study shows how imputation of functional variation from large reference panels can help fine map association signals in the MHC.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.