Validating, augmenting and refining genome-wide association signals
Key Points Genome-wide association studies have yielded a large number of association signals with robust statistical support, but these are only markers of the true functional variants. Reliable identification of the true functional variants can be notoriously difficult, but a series of methods cou...
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description | Key Points
Genome-wide association studies have yielded a large number of association signals with robust statistical support, but these are only markers of the true functional variants.
Reliable identification of the true functional variants can be notoriously difficult, but a series of methods could be helpful in this regard.
Large-scale exact replication to achieve robust statistical credibility of a marker should precede efforts at finding the causative variants.
Fine mapping and resequencing might help to identify more informative markers and multiple independent informative loci.
Functional information could fine tune the credibility of different variants for being the causative variant.
Additional insights might be obtained by more extensive phenotype mapping of proposed variants.
Genome-wide association studies have identified many promising links between genetic variants and human traits. However, the steps from the initial identification of associated markers to the reliable validation of the causal variant are long and tortuous, as the authors describe.
Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive. |
doi_str_mv | 10.1038/nrg2544 |
format | Article |
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Genome-wide association studies have yielded a large number of association signals with robust statistical support, but these are only markers of the true functional variants.
Reliable identification of the true functional variants can be notoriously difficult, but a series of methods could be helpful in this regard.
Large-scale exact replication to achieve robust statistical credibility of a marker should precede efforts at finding the causative variants.
Fine mapping and resequencing might help to identify more informative markers and multiple independent informative loci.
Functional information could fine tune the credibility of different variants for being the causative variant.
Additional insights might be obtained by more extensive phenotype mapping of proposed variants.
Genome-wide association studies have identified many promising links between genetic variants and human traits. However, the steps from the initial identification of associated markers to the reliable validation of the causal variant are long and tortuous, as the authors describe.
Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive.</description><identifier>ISSN: 1471-0056</identifier><identifier>EISSN: 1471-0064</identifier><identifier>DOI: 10.1038/nrg2544</identifier><identifier>PMID: 19373277</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>Agriculture ; Animal Genetics and Genomics ; Animals ; Biological and medical sciences ; Biomedical and Life Sciences ; Biomedicine ; Cancer Research ; Chromosome mapping ; Classical genetics, quantitative genetics, hybrids ; Consortia ; Datasets ; Diabetes ; Disease ; Epidemiology ; Fundamental and applied biological sciences. Psychology ; Gene Function ; Genetic aspects ; Genetic Heterogeneity ; Genetic Linkage ; Genetic markers ; Genetic variation ; Genetics of eukaryotes. Biological and molecular evolution ; Genome ; Genome-Wide Association Study - methods ; Genomes ; Human ; Human Genetics ; Humans ; Methods ; Phenotype ; Reproducibility of Results ; review-article ; Risk factors ; Systemic lupus erythematosus</subject><ispartof>Nature reviews. Genetics, 2009-05, Vol.10 (5), p.318-329</ispartof><rights>Springer Nature Limited 2009</rights><rights>2009 INIST-CNRS</rights><rights>COPYRIGHT 2009 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group May 2009</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4624-521de41c4ac41e18024223d7d17c660971b8d88c57cdd4e78c0d469c32ce67c73</citedby><cites>FETCH-LOGICAL-c4624-521de41c4ac41e18024223d7d17c660971b8d88c57cdd4e78c0d469c32ce67c73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/nrg2544$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/nrg2544$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21348487$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/19373277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ioannidis, John P. A.</creatorcontrib><creatorcontrib>Thomas, Gilles</creatorcontrib><creatorcontrib>Daly, Mark J.</creatorcontrib><title>Validating, augmenting and refining genome-wide association signals</title><title>Nature reviews. Genetics</title><addtitle>Nat Rev Genet</addtitle><addtitle>Nat Rev Genet</addtitle><description>Key Points
Genome-wide association studies have yielded a large number of association signals with robust statistical support, but these are only markers of the true functional variants.
Reliable identification of the true functional variants can be notoriously difficult, but a series of methods could be helpful in this regard.
Large-scale exact replication to achieve robust statistical credibility of a marker should precede efforts at finding the causative variants.
Fine mapping and resequencing might help to identify more informative markers and multiple independent informative loci.
Functional information could fine tune the credibility of different variants for being the causative variant.
Additional insights might be obtained by more extensive phenotype mapping of proposed variants.
Genome-wide association studies have identified many promising links between genetic variants and human traits. However, the steps from the initial identification of associated markers to the reliable validation of the causal variant are long and tortuous, as the authors describe.
Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive.</description><subject>Agriculture</subject><subject>Animal Genetics and Genomics</subject><subject>Animals</subject><subject>Biological and medical sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Cancer Research</subject><subject>Chromosome mapping</subject><subject>Classical genetics, quantitative genetics, hybrids</subject><subject>Consortia</subject><subject>Datasets</subject><subject>Diabetes</subject><subject>Disease</subject><subject>Epidemiology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene Function</subject><subject>Genetic aspects</subject><subject>Genetic Heterogeneity</subject><subject>Genetic Linkage</subject><subject>Genetic markers</subject><subject>Genetic variation</subject><subject>Genetics of eukaryotes. Biological and molecular evolution</subject><subject>Genome</subject><subject>Genome-Wide Association Study - methods</subject><subject>Genomes</subject><subject>Human</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Methods</subject><subject>Phenotype</subject><subject>Reproducibility of Results</subject><subject>review-article</subject><subject>Risk factors</subject><subject>Systemic lupus erythematosus</subject><issn>1471-0056</issn><issn>1471-0064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkk1v1DAQhiNERUtB_AMUgfg4EPDYjse5VKpWUJAqcQGulmt7s64Su9ibIv49Dhvt0l44zVjzeD7emap6BuQ9ECY_hNTTlvMH1QlwhIYQwR_u_VYcV49zviYEBCB7VB1Dx5BRxJNq9UMP3uqtD_27Wk_96MLs1zrYOrm1D_OjdyGOrvnlrat1ztH48iGGOvs-6CE_qY7Wxbiniz2tvn_6-G31ubn8evFldX7ZGC4ob1oK1nEwXBsODiShnFJm0QIaIUiHcCWtlKZFYy13KA2xXHSGUeMEGmSn1dku7810NTprSqtJD-om-VGn3ypqr-5Ggt-oPt4qlIhtS0uC10uCFH9OLm_V6LNxw6CDi1NWAoGB4PhfkBKJRfaugC_ugddxSrMoqsyGvGUwQy93UK8Hp3xYx9KdmTOqc-ikJLKT4lDzL7VxethuchymWel8F3yzA02KOZcl7RUAouZrUMs1FPL5v4IduGX9BXi1ADobPayTDsbnPUeBccnlzL3dcbmEQu_SYcz7Nf8AEUDH1A</recordid><startdate>200905</startdate><enddate>200905</enddate><creator>Ioannidis, John P. A.</creator><creator>Thomas, Gilles</creator><creator>Daly, Mark J.</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7QR</scope><scope>7RV</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</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>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PJZUB</scope><scope>PKEHL</scope><scope>PPXIY</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>200905</creationdate><title>Validating, augmenting and refining genome-wide association signals</title><author>Ioannidis, John P. A. ; Thomas, Gilles ; Daly, Mark J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4624-521de41c4ac41e18024223d7d17c660971b8d88c57cdd4e78c0d469c32ce67c73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Agriculture</topic><topic>Animal Genetics and Genomics</topic><topic>Animals</topic><topic>Biological and medical sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Cancer Research</topic><topic>Chromosome mapping</topic><topic>Classical genetics, quantitative genetics, hybrids</topic><topic>Consortia</topic><topic>Datasets</topic><topic>Diabetes</topic><topic>Disease</topic><topic>Epidemiology</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene Function</topic><topic>Genetic aspects</topic><topic>Genetic Heterogeneity</topic><topic>Genetic Linkage</topic><topic>Genetic markers</topic><topic>Genetic variation</topic><topic>Genetics of eukaryotes. Biological and molecular evolution</topic><topic>Genome</topic><topic>Genome-Wide Association Study - methods</topic><topic>Genomes</topic><topic>Human</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Methods</topic><topic>Phenotype</topic><topic>Reproducibility of Results</topic><topic>review-article</topic><topic>Risk factors</topic><topic>Systemic lupus erythematosus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ioannidis, John P. A.</creatorcontrib><creatorcontrib>Thomas, Gilles</creatorcontrib><creatorcontrib>Daly, Mark J.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</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>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research 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>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</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>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest Health & Medical Research Collection</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Health & Nursing</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nature reviews. Genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ioannidis, John P. A.</au><au>Thomas, Gilles</au><au>Daly, Mark J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Validating, augmenting and refining genome-wide association signals</atitle><jtitle>Nature reviews. Genetics</jtitle><stitle>Nat Rev Genet</stitle><addtitle>Nat Rev Genet</addtitle><date>2009-05</date><risdate>2009</risdate><volume>10</volume><issue>5</issue><spage>318</spage><epage>329</epage><pages>318-329</pages><issn>1471-0056</issn><eissn>1471-0064</eissn><abstract>Key Points
Genome-wide association studies have yielded a large number of association signals with robust statistical support, but these are only markers of the true functional variants.
Reliable identification of the true functional variants can be notoriously difficult, but a series of methods could be helpful in this regard.
Large-scale exact replication to achieve robust statistical credibility of a marker should precede efforts at finding the causative variants.
Fine mapping and resequencing might help to identify more informative markers and multiple independent informative loci.
Functional information could fine tune the credibility of different variants for being the causative variant.
Additional insights might be obtained by more extensive phenotype mapping of proposed variants.
Genome-wide association studies have identified many promising links between genetic variants and human traits. However, the steps from the initial identification of associated markers to the reliable validation of the causal variant are long and tortuous, as the authors describe.
Studies using genome-wide platforms have yielded an unprecedented number of promising signals of association between genomic variants and human traits. This Review addresses the steps required to validate, augment and refine such signals to identify underlying causal variants for well-defined phenotypes. These steps include: large-scale exact replication across both similar and diverse populations; fine mapping and resequencing; determination of the most informative markers and multiple independent informative loci; incorporation of functional information; and improved phenotype mapping of the implicated genetic effects. Even in cases for which replication proves that an effect exists, confident localization of the causal variant often remains elusive.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>19373277</pmid><doi>10.1038/nrg2544</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Agriculture Animal Genetics and Genomics Animals Biological and medical sciences Biomedical and Life Sciences Biomedicine Cancer Research Chromosome mapping Classical genetics, quantitative genetics, hybrids Consortia Datasets Diabetes Disease Epidemiology Fundamental and applied biological sciences. Psychology Gene Function Genetic aspects Genetic Heterogeneity Genetic Linkage Genetic markers Genetic variation Genetics of eukaryotes. Biological and molecular evolution Genome Genome-Wide Association Study - methods Genomes Human Human Genetics Humans Methods Phenotype Reproducibility of Results review-article Risk factors Systemic lupus erythematosus |
title | Validating, augmenting and refining genome-wide association signals |
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