Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction
Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate...
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| Veröffentlicht in: | Scientific reports 2017-03, Vol.7 (1), p.43709-43709, Article 43709 |
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| creator | Wu, Yiming Jing, Runyu Dong, Yongcheng Kuang, Qifan Li, Yan Huang, Ziyan Gan, Wei Xue, Yue Li, Yizhou Li, Menglong |
| description | Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate for the hundreds of SNPs, most of which reside in non-coding regions. Here we provide a comprehensive annotation of 65 known T2D related SNPs and inspect putative functional SNPs probably causing protein dysfunction, response element disruptions of known transcription factors related to T2D genes and regulatory response element disruption of four histone marks in pancreas and pancreas islet. In new identified risk SNPs, some of them were reported as T2D related SNPs in recent studies. Further, we found that accumulation of modest effects of single sites markedly enhanced the risk prediction based on 1989 T2D samples and 3000 healthy controls. The A
ROC
value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals. |
| doi_str_mv | 10.1038/srep43709 |
| format | Article |
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ROC
value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/srep43709</identifier><identifier>PMID: 28262806</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/114/1305 ; 631/114/2404 ; Diabetes ; Diabetes mellitus ; Genome-wide association studies ; Genomes ; Health risks ; Humanities and Social Sciences ; multidisciplinary ; Pancreas ; Polymorphism ; Reclassification ; Science ; Single-nucleotide polymorphism ; Transcription factors</subject><ispartof>Scientific reports, 2017-03, Vol.7 (1), p.43709-43709, Article 43709</ispartof><rights>The Author(s) 2017</rights><rights>Copyright Nature Publishing Group Mar 2017</rights><rights>Copyright © 2017, The Author(s) 2017 The Author(s)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-3611114b64acebda3ba68d78abff74d8df9958f0d415192406a1288ddbd6ef523</citedby><cites>FETCH-LOGICAL-c438t-3611114b64acebda3ba68d78abff74d8df9958f0d415192406a1288ddbd6ef523</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337961/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5337961/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27923,27924,41119,42188,51575,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28262806$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Yiming</creatorcontrib><creatorcontrib>Jing, Runyu</creatorcontrib><creatorcontrib>Dong, Yongcheng</creatorcontrib><creatorcontrib>Kuang, Qifan</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Huang, Ziyan</creatorcontrib><creatorcontrib>Gan, Wei</creatorcontrib><creatorcontrib>Xue, Yue</creatorcontrib><creatorcontrib>Li, Yizhou</creatorcontrib><creatorcontrib>Li, Menglong</creatorcontrib><title>Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate for the hundreds of SNPs, most of which reside in non-coding regions. Here we provide a comprehensive annotation of 65 known T2D related SNPs and inspect putative functional SNPs probably causing protein dysfunction, response element disruptions of known transcription factors related to T2D genes and regulatory response element disruption of four histone marks in pancreas and pancreas islet. In new identified risk SNPs, some of them were reported as T2D related SNPs in recent studies. Further, we found that accumulation of modest effects of single sites markedly enhanced the risk prediction based on 1989 T2D samples and 3000 healthy controls. The A
ROC
value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals.</description><subject>631/114/1305</subject><subject>631/114/2404</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Genome-wide association studies</subject><subject>Genomes</subject><subject>Health risks</subject><subject>Humanities and Social Sciences</subject><subject>multidisciplinary</subject><subject>Pancreas</subject><subject>Polymorphism</subject><subject>Reclassification</subject><subject>Science</subject><subject>Single-nucleotide polymorphism</subject><subject>Transcription factors</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNplkd9LHDEQx4NYPLn60H9AFvpihW3za7PZF0GkpwVpC22fQ3aTaM69ZJtkxfvvzbl6nDovM2E-880wXwA-IfgVQcK_xaAHSmrY7IFDDGlVYoLx_k49A0cxLmGOCjcUNQdghjlmmEN2CNRidF2y3sm-kM75JDePwpsi2oe0Lo2910VaD7rEhbKy1UnHIth4V_z5-TvmEVXYlPMw9LabZq2bgCFoZZ-0P4IPRvZRHz3nOfi3-P734qq8_nX54-L8uuwo4akkDOWgLaOy062SpJWMq5rL1piaKq5M01TcQEVRhRpMIZMIc65Uq5g2FSZzcDbpDmO70qrTLgXZiyHYlQxr4aUVrzvO3oobfy8qQuqGoSxw8iwQ_P9RxyRWNna676XTfowC8ZrWvGZ0g35-gy79GPIZM9VAQhiuKMvUl4nqgo_ZKbNdBkGxsU9s7cvs8e72W_LFrAycTkDMLXejw86X79QeASA7pW8</recordid><startdate>20170306</startdate><enddate>20170306</enddate><creator>Wu, Yiming</creator><creator>Jing, Runyu</creator><creator>Dong, Yongcheng</creator><creator>Kuang, Qifan</creator><creator>Li, Yan</creator><creator>Huang, Ziyan</creator><creator>Gan, Wei</creator><creator>Xue, Yue</creator><creator>Li, Yizhou</creator><creator>Li, Menglong</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20170306</creationdate><title>Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction</title><author>Wu, Yiming ; Jing, Runyu ; Dong, Yongcheng ; Kuang, Qifan ; Li, Yan ; Huang, Ziyan ; Gan, Wei ; Xue, Yue ; Li, Yizhou ; Li, Menglong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-3611114b64acebda3ba68d78abff74d8df9958f0d415192406a1288ddbd6ef523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>631/114/1305</topic><topic>631/114/2404</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Genome-wide association studies</topic><topic>Genomes</topic><topic>Health risks</topic><topic>Humanities and Social Sciences</topic><topic>multidisciplinary</topic><topic>Pancreas</topic><topic>Polymorphism</topic><topic>Reclassification</topic><topic>Science</topic><topic>Single-nucleotide polymorphism</topic><topic>Transcription factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wu, Yiming</creatorcontrib><creatorcontrib>Jing, Runyu</creatorcontrib><creatorcontrib>Dong, Yongcheng</creatorcontrib><creatorcontrib>Kuang, Qifan</creatorcontrib><creatorcontrib>Li, Yan</creatorcontrib><creatorcontrib>Huang, Ziyan</creatorcontrib><creatorcontrib>Gan, Wei</creatorcontrib><creatorcontrib>Xue, Yue</creatorcontrib><creatorcontrib>Li, Yizhou</creatorcontrib><creatorcontrib>Li, Menglong</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</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 One Sustainability</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>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>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Publicly Available Content 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 Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wu, Yiming</au><au>Jing, Runyu</au><au>Dong, Yongcheng</au><au>Kuang, Qifan</au><au>Li, Yan</au><au>Huang, Ziyan</au><au>Gan, Wei</au><au>Xue, Yue</au><au>Li, Yizhou</au><au>Li, Menglong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2017-03-06</date><risdate>2017</risdate><volume>7</volume><issue>1</issue><spage>43709</spage><epage>43709</epage><pages>43709-43709</pages><artnum>43709</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Genome-wide association studies (GWAS) have identified more than sixty single nucleotide polymorphisms (SNPs) associated with increased risk for type 2 diabetes (T2D). However, the identification of causal risk SNPs for T2D pathogenesis was complicated by the factor that each risk SNP is a surrogate for the hundreds of SNPs, most of which reside in non-coding regions. Here we provide a comprehensive annotation of 65 known T2D related SNPs and inspect putative functional SNPs probably causing protein dysfunction, response element disruptions of known transcription factors related to T2D genes and regulatory response element disruption of four histone marks in pancreas and pancreas islet. In new identified risk SNPs, some of them were reported as T2D related SNPs in recent studies. Further, we found that accumulation of modest effects of single sites markedly enhanced the risk prediction based on 1989 T2D samples and 3000 healthy controls. The A
ROC
value increased from 0.58 to 0.62 by only using genotype score when putative risk SNPs were added. Besides, the net reclassification improvement is 10.03% on the addition of new risk SNPs. Taken together, functional annotation could provide a list of prioritized potential risk SNPs for the further estimation on the T2D susceptibility of individuals.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>28262806</pmid><doi>10.1038/srep43709</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | 631/114/1305 631/114/2404 Diabetes Diabetes mellitus Genome-wide association studies Genomes Health risks Humanities and Social Sciences multidisciplinary Pancreas Polymorphism Reclassification Science Single-nucleotide polymorphism Transcription factors |
| title | Functional annotation of sixty-five type-2 diabetes risk SNPs and its application in risk prediction |
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