dc.contributor.author
Soria Fernández, José Manuel
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Morange, Pierre-Emmanuel
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Vila, Joan
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Souto, Juan Carlos
dc.contributor.author
Moyano, Manel
dc.contributor.author
Trégouët, David-Alexandre
dc.contributor.author
Mateo, José
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Saut, Noémi
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Salas, Eduardo
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Elosua, Roberto
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Universitat Autònoma de Barcelona
dc.identifier
https://ddd.uab.cat/record/302436
dc.identifier
urn:10.1161/JAHA.114.001060
dc.identifier
urn:oai:ddd.uab.cat:302436
dc.identifier
urn:scopus_id:84922931517
dc.identifier
urn:articleid:20479980v3n5e001060
dc.identifier
urn:pmid:25341889
dc.identifier
urn:pmc-uid:4323784
dc.identifier
urn:pmcid:PMC4323784
dc.identifier
urn:oai:pubmedcentral.nih.gov:4323784
dc.description.abstract
Background-Genetics plays an important role in venous thromboembolism (VTE). Factor V Leiden (FVL or rs6025) and prothrombin gene G20210A (PT or rs1799963) are the genetic variants currently tested for VTE risk assessment. We hypothesized that primary VTE risk assessment can be improved by using genetic risk scores with more genetic markers than just FVL-rs6025 and prothrombin gene PT-rs1799963. To this end, we have designed a new genetic risk score called Thrombo inCode (TiC). Methods and Results-TiC was evaluated in terms of discrimination (Δ of the area under the receiver operating characteristic curve) and reclassification (integrated discrimination improvement and net reclassification improvement). This evaluation was performed using 2 age- and sex-matched case-control populations: SANTPAU (248 cases, 249 controls) and the Marseille Thrombosis Association study (MARTHA; 477 cases, 477 controls). TiC was compared with other literature-based genetic risk scores. TiC including F5 rs6025/rs118203906/rs118203905, F2 rs1799963, F12 rs1801020, F13 rs5985, SERPINC1 rs121909548, and SERPINA10 rs2232698 plus the A1 blood group (rs8176719, rs7853989, rs8176743, rs8176750) improved the area under the curve compared with a model based only on F5-rs6025 and F2-rs1799963 in SANTPAU (0.677 versus 0.575, P<0.001) and MARTHA (0.605 versus 0.576, P=0.008). TiC showed good integrated discrimination improvement of 5.49 (P<0.001) for SANTPAU and 0.96 (P=0.045) for MARTHA. Among the genetic risk scores evaluated, the proportion of VTE risk variance explained by TiC was the highest. Conclusions-We conclude that TiC greatly improves prediction of VTE risk compared with other genetic risk scores. TiC should improve prevention, diagnosis, and treatment of VTE.
dc.format
application/pdf
dc.relation
Ministerio de Economía y Competitividad RD12/0042/0032
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Ministerio de Economía y Competitividad RD12/0042/0061
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Ministerio de Economía y Competitividad FI12/00322
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Journal of the American Heart Association. Cardiovascular and cerebrovascular disease ; Vol. 3 Núm. 5 (2014), p. e001060
dc.rights
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original.
dc.rights
https://creativecommons.org/licenses/by-nc/4.0/
dc.title
Multilocus genetic risk scores for venous thromboembolism risk assessment