THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease
Background Genome-wide association studies (GWASs) have been successfully used to identify novel common genetic variants that contribute to susceptibility to complex diseases, but individual GWASs are limited in terms of identifying new loci. Thus, pathway-based analysis is required to identify furt...
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description | Background Genome-wide association studies (GWASs) have been successfully used to identify novel common genetic variants that contribute to susceptibility to complex diseases, but individual GWASs are limited in terms of identifying new loci. Thus, pathway-based analysis is required to identify further new loci that contribute to susceptibility to complex diseases. Objectives The aim of this study was to explore candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms of psoriasis and Behcets’s disease (BD) and to generate an SNP à gene à pathway hypothesis, using pathway analysis. Methods A psoriasis GWAS dataset that included 436,192 SNPs in 1,409 psoriasis cases and 1,436 controls of European descent and a BD GWAS dataset that contained 310,324 SNPs in 1,215 BD cases and 1,278 controls were used in this study. Pathway-based analysis using ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the GWAS datasets. Results ICSNPathway analysis identified 15 candidate SNPs and 28 candidate causal pathways. The top 5 candidate causal SNPs were rs1063478 (P =1.45E-10), rs8084 (P =2.20E-08), rs7192 (P =5.18E-08), rs20541 (P =5.30E-06), and rs1130838 (P =5.65E-06), which with the exception of rs20541 (interleukin [IL]-13) are at HLA loci. These candidate SNPs and pathways provided ten hypothetical biological mechanisms. The most strongly associated pathway concerned human leukocyte antigen (HLA). When HLA loci were excluded, ICSNPathway analysis provided one hypothetical biological mechanism. rs20541 (non_synonymous_coding) à IL-13 à dendritic cell involvement in the regulation of Th1 and Th2 development, and the GATA3 pathway. ICSNPathway analysis identified four candidate causal SNPs, eleven candidate causal pathways, and three hypothetical biological mechanisms. One of them was as follows; rs2072895 (non_synonymous_coding & splice_site)) and rs2735059 (non_synonymous_coding) à HLA-F à Type I diabetes mellitus, antigen processing and presentation, and autoimmune thyroid disease. Conclusions The application of ICSNPathway analysis to GWAS datasets of psoriasis and BD resulted in the identification of candidate SNPs and candidate pathways that might contribute to psoriasis susceptibility. Disclosure of Interest None Declared |
doi_str_mv | 10.1136/annrheumdis-2012-eular.1984 |
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fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1777973275</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4008640071</sourcerecordid><originalsourceid>FETCH-LOGICAL-b1655-26534660425e6504add1e551a032b59008a5b5a21f9f3c9edc9aa9e8113dfb343</originalsourceid><addsrcrecordid>eNqVkLFu2zAQhomgBeKmeQcBmZWSokiK6FQYtVPAaIHCyZCFOEmnmI4luTwJibcsfYi8np8kdF0EWTMR5H0_7-5j7ELwSyGk_gJdF1Y4trWnNOMiS3HcQLgUtshP2ETkuojPmn9gE865THOrzSn7RLSOV16IYsLa5dU158Lun_7OsetbTB98jckWhtUD7BLoYLMjT0nfJHdv6kDUVx4G33cJDWPtMSJdsqU-eDjw0NVJiasKh_3TMyVxQATCz-xjAxvC8__nGbuefV9Or9LFr_mP6bdFWgqtVJppJXOteZ4p1IrnUNcClRLAZVYqG0cHVSrIRGMbWVmsKwtgsYhO6qaUuTxjF8d_t6H_MyINbt2PIe5CThhjrJGZUZH6eqSq0BMFbNw2-BbCzgnuDn7dG7_u4Nf98-sOfmM6PaY9Dfj4GoVw77SRRrmfN1M3uymEuf2du2Xk9ZEv2_W7Gr0AILOYIA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1777973275</pqid></control><display><type>article</type><title>THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease</title><source>BMJ Journals - NESLi2</source><creator>Lee, Y.H.</creator><creatorcontrib>Lee, Y.H.</creatorcontrib><description>Background Genome-wide association studies (GWASs) have been successfully used to identify novel common genetic variants that contribute to susceptibility to complex diseases, but individual GWASs are limited in terms of identifying new loci. Thus, pathway-based analysis is required to identify further new loci that contribute to susceptibility to complex diseases. Objectives The aim of this study was to explore candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms of psoriasis and Behcets’s disease (BD) and to generate an SNP à gene à pathway hypothesis, using pathway analysis. Methods A psoriasis GWAS dataset that included 436,192 SNPs in 1,409 psoriasis cases and 1,436 controls of European descent and a BD GWAS dataset that contained 310,324 SNPs in 1,215 BD cases and 1,278 controls were used in this study. Pathway-based analysis using ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the GWAS datasets. Results ICSNPathway analysis identified 15 candidate SNPs and 28 candidate causal pathways. The top 5 candidate causal SNPs were rs1063478 (P =1.45E-10), rs8084 (P =2.20E-08), rs7192 (P =5.18E-08), rs20541 (P =5.30E-06), and rs1130838 (P =5.65E-06), which with the exception of rs20541 (interleukin [IL]-13) are at HLA loci. These candidate SNPs and pathways provided ten hypothetical biological mechanisms. The most strongly associated pathway concerned human leukocyte antigen (HLA). When HLA loci were excluded, ICSNPathway analysis provided one hypothetical biological mechanism. rs20541 (non_synonymous_coding) à IL-13 à dendritic cell involvement in the regulation of Th1 and Th2 development, and the GATA3 pathway. ICSNPathway analysis identified four candidate causal SNPs, eleven candidate causal pathways, and three hypothetical biological mechanisms. One of them was as follows; rs2072895 (non_synonymous_coding & splice_site)) and rs2735059 (non_synonymous_coding) à HLA-F à Type I diabetes mellitus, antigen processing and presentation, and autoimmune thyroid disease. Conclusions The application of ICSNPathway analysis to GWAS datasets of psoriasis and BD resulted in the identification of candidate SNPs and candidate pathways that might contribute to psoriasis susceptibility. Disclosure of Interest None Declared</description><identifier>ISSN: 0003-4967</identifier><identifier>EISSN: 1468-2060</identifier><identifier>DOI: 10.1136/annrheumdis-2012-eular.1984</identifier><identifier>CODEN: ARDIAO</identifier><language>eng</language><publisher>London: BMJ Publishing Group Ltd and European League Against Rheumatism</publisher><ispartof>Annals of the rheumatic diseases, 2013-06, Vol.71 (Suppl 3), p.160-160</ispartof><rights>2013, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><rights>Copyright: 2013 (c) 2013, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttp://ard.bmj.com/content/71/Suppl_3/160.1.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttp://ard.bmj.com/content/71/Suppl_3/160.1.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>114,115,315,782,786,3198,23578,27931,27932,77608,77639</link.rule.ids></links><search><creatorcontrib>Lee, Y.H.</creatorcontrib><title>THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease</title><title>Annals of the rheumatic diseases</title><addtitle>Ann Rheum Dis</addtitle><description>Background Genome-wide association studies (GWASs) have been successfully used to identify novel common genetic variants that contribute to susceptibility to complex diseases, but individual GWASs are limited in terms of identifying new loci. Thus, pathway-based analysis is required to identify further new loci that contribute to susceptibility to complex diseases. Objectives The aim of this study was to explore candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms of psoriasis and Behcets’s disease (BD) and to generate an SNP à gene à pathway hypothesis, using pathway analysis. Methods A psoriasis GWAS dataset that included 436,192 SNPs in 1,409 psoriasis cases and 1,436 controls of European descent and a BD GWAS dataset that contained 310,324 SNPs in 1,215 BD cases and 1,278 controls were used in this study. Pathway-based analysis using ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the GWAS datasets. Results ICSNPathway analysis identified 15 candidate SNPs and 28 candidate causal pathways. The top 5 candidate causal SNPs were rs1063478 (P =1.45E-10), rs8084 (P =2.20E-08), rs7192 (P =5.18E-08), rs20541 (P =5.30E-06), and rs1130838 (P =5.65E-06), which with the exception of rs20541 (interleukin [IL]-13) are at HLA loci. These candidate SNPs and pathways provided ten hypothetical biological mechanisms. The most strongly associated pathway concerned human leukocyte antigen (HLA). When HLA loci were excluded, ICSNPathway analysis provided one hypothetical biological mechanism. rs20541 (non_synonymous_coding) à IL-13 à dendritic cell involvement in the regulation of Th1 and Th2 development, and the GATA3 pathway. ICSNPathway analysis identified four candidate causal SNPs, eleven candidate causal pathways, and three hypothetical biological mechanisms. One of them was as follows; rs2072895 (non_synonymous_coding & splice_site)) and rs2735059 (non_synonymous_coding) à HLA-F à Type I diabetes mellitus, antigen processing and presentation, and autoimmune thyroid disease. Conclusions The application of ICSNPathway analysis to GWAS datasets of psoriasis and BD resulted in the identification of candidate SNPs and candidate pathways that might contribute to psoriasis susceptibility. Disclosure of Interest None Declared</description><issn>0003-4967</issn><issn>1468-2060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqVkLFu2zAQhomgBeKmeQcBmZWSokiK6FQYtVPAaIHCyZCFOEmnmI4luTwJibcsfYi8np8kdF0EWTMR5H0_7-5j7ELwSyGk_gJdF1Y4trWnNOMiS3HcQLgUtshP2ETkuojPmn9gE865THOrzSn7RLSOV16IYsLa5dU158Lun_7OsetbTB98jckWhtUD7BLoYLMjT0nfJHdv6kDUVx4G33cJDWPtMSJdsqU-eDjw0NVJiasKh_3TMyVxQATCz-xjAxvC8__nGbuefV9Or9LFr_mP6bdFWgqtVJppJXOteZ4p1IrnUNcClRLAZVYqG0cHVSrIRGMbWVmsKwtgsYhO6qaUuTxjF8d_t6H_MyINbt2PIe5CThhjrJGZUZH6eqSq0BMFbNw2-BbCzgnuDn7dG7_u4Nf98-sOfmM6PaY9Dfj4GoVw77SRRrmfN1M3uymEuf2du2Xk9ZEv2_W7Gr0AILOYIA</recordid><startdate>201306</startdate><enddate>201306</enddate><creator>Lee, Y.H.</creator><general>BMJ Publishing Group Ltd and European League Against Rheumatism</general><general>BMJ Publishing Group LTD</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8AF</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>201306</creationdate><title>THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease</title><author>Lee, Y.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b1655-26534660425e6504add1e551a032b59008a5b5a21f9f3c9edc9aa9e8113dfb343</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Y.H.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Annals of the rheumatic diseases</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Y.H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease</atitle><jtitle>Annals of the rheumatic diseases</jtitle><addtitle>Ann Rheum Dis</addtitle><date>2013-06</date><risdate>2013</risdate><volume>71</volume><issue>Suppl 3</issue><spage>160</spage><epage>160</epage><pages>160-160</pages><issn>0003-4967</issn><eissn>1468-2060</eissn><coden>ARDIAO</coden><abstract>Background Genome-wide association studies (GWASs) have been successfully used to identify novel common genetic variants that contribute to susceptibility to complex diseases, but individual GWASs are limited in terms of identifying new loci. Thus, pathway-based analysis is required to identify further new loci that contribute to susceptibility to complex diseases. Objectives The aim of this study was to explore candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms of psoriasis and Behcets’s disease (BD) and to generate an SNP à gene à pathway hypothesis, using pathway analysis. Methods A psoriasis GWAS dataset that included 436,192 SNPs in 1,409 psoriasis cases and 1,436 controls of European descent and a BD GWAS dataset that contained 310,324 SNPs in 1,215 BD cases and 1,278 controls were used in this study. Pathway-based analysis using ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the GWAS datasets. Results ICSNPathway analysis identified 15 candidate SNPs and 28 candidate causal pathways. The top 5 candidate causal SNPs were rs1063478 (P =1.45E-10), rs8084 (P =2.20E-08), rs7192 (P =5.18E-08), rs20541 (P =5.30E-06), and rs1130838 (P =5.65E-06), which with the exception of rs20541 (interleukin [IL]-13) are at HLA loci. These candidate SNPs and pathways provided ten hypothetical biological mechanisms. The most strongly associated pathway concerned human leukocyte antigen (HLA). When HLA loci were excluded, ICSNPathway analysis provided one hypothetical biological mechanism. rs20541 (non_synonymous_coding) à IL-13 à dendritic cell involvement in the regulation of Th1 and Th2 development, and the GATA3 pathway. ICSNPathway analysis identified four candidate causal SNPs, eleven candidate causal pathways, and three hypothetical biological mechanisms. One of them was as follows; rs2072895 (non_synonymous_coding & splice_site)) and rs2735059 (non_synonymous_coding) à HLA-F à Type I diabetes mellitus, antigen processing and presentation, and autoimmune thyroid disease. Conclusions The application of ICSNPathway analysis to GWAS datasets of psoriasis and BD resulted in the identification of candidate SNPs and candidate pathways that might contribute to psoriasis susceptibility. Disclosure of Interest None Declared</abstract><cop>London</cop><pub>BMJ Publishing Group Ltd and European League Against Rheumatism</pub><doi>10.1136/annrheumdis-2012-eular.1984</doi><tpages>1</tpages></addata></record> |
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title | THU0019 Genome-wide pathway analysis of genome-wide association studies on psoriasis and behcet’s disease |
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