Additional value of a combined genetic risk score to standard cardiovascular stratification
Main Author: | |
---|---|
Publication Date: | 2018 |
Other Authors: | , , , , , , , , , , , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.13/2971 |
Summary: | The utility of genetic risk scores (GRS) as independent risk predictors remains inconclusive. Here, we evaluate the additive value of a multi-locus GRS to the Framingham risk score (FRS) in coronary artery disease (CAD) risk prediction. A total of 2888 individuals (1566 coronary patients and 1322 controls) were divided into three subgroups according to FRS. Multiplicative GRS was determined for 32 genetic variants associated to CAD. Logistic Regression and Area Under the Curve (AUC) were determined first, using the TRF for each FRS subgroup, and secondly, adding GRS. Different models (TRF, TRF+GRS) were used to classify the subjects into risk categories for the FRS 10-year predicted risk. The improvement offered by GRS was expressed as Net Reclassification Index and Integrated Discrimination Improvement. Multivariate analysis showed that GRS was an independent predictor for CAD (OR = 1.87; p<0.0001). Diabetes, arterial hypertension, dyslipidemia and smoking status were also independent CAD predictors (p<0.05). GRS added predictive value to TRF across all risk subgroups. NRI showed a significant improvement in all categories. In conclusion, GRS provided a better incremental value in intermediate subgroup. In this subgroup, inclusion of genotyping may be considered to better stratify cardiovascular risk. |
id |
RCAP_1c1df36a6714923b99814a002a3ef0f5 |
---|---|
oai_identifier_str |
oai:digituma.uma.pt:10400.13/2971 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
Additional value of a combined genetic risk score to standard cardiovascular stratificationCoronary artery diseaseGenetic risk scoreFramingham scoreRisk predictionRisk factors.Faculdade de Ciências da VidaThe utility of genetic risk scores (GRS) as independent risk predictors remains inconclusive. Here, we evaluate the additive value of a multi-locus GRS to the Framingham risk score (FRS) in coronary artery disease (CAD) risk prediction. A total of 2888 individuals (1566 coronary patients and 1322 controls) were divided into three subgroups according to FRS. Multiplicative GRS was determined for 32 genetic variants associated to CAD. Logistic Regression and Area Under the Curve (AUC) were determined first, using the TRF for each FRS subgroup, and secondly, adding GRS. Different models (TRF, TRF+GRS) were used to classify the subjects into risk categories for the FRS 10-year predicted risk. The improvement offered by GRS was expressed as Net Reclassification Index and Integrated Discrimination Improvement. Multivariate analysis showed that GRS was an independent predictor for CAD (OR = 1.87; p<0.0001). Diabetes, arterial hypertension, dyslipidemia and smoking status were also independent CAD predictors (p<0.05). GRS added predictive value to TRF across all risk subgroups. NRI showed a significant improvement in all categories. In conclusion, GRS provided a better incremental value in intermediate subgroup. In this subgroup, inclusion of genotyping may be considered to better stratify cardiovascular risk.Sociedade Brasileira de GenéticaDigitUMaPereira, AndreiaMendonca, Maria IsabelBorges, SofiaSousa, Ana CéliaFreitas, SóniaHenriques, EvaRodrigues, MarianaFreitas, Ana IsabelGuerra, GraçaFreitas, CarolinaPereira, DécioBrehm, AntónioReis, Roberto Palma dos2020-11-12T15:38:43Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.13/2971eng10.1590/1678-4685-GMB-2017-0173info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-24T16:59:52Zoai:digituma.uma.pt:10400.13/2971Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:45:22.552359Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
title |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
spellingShingle |
Additional value of a combined genetic risk score to standard cardiovascular stratification Pereira, Andreia Coronary artery disease Genetic risk score Framingham score Risk prediction Risk factors . Faculdade de Ciências da Vida |
title_short |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
title_full |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
title_fullStr |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
title_full_unstemmed |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
title_sort |
Additional value of a combined genetic risk score to standard cardiovascular stratification |
author |
Pereira, Andreia |
author_facet |
Pereira, Andreia Mendonca, Maria Isabel Borges, Sofia Sousa, Ana Célia Freitas, Sónia Henriques, Eva Rodrigues, Mariana Freitas, Ana Isabel Guerra, Graça Freitas, Carolina Pereira, Décio Brehm, António Reis, Roberto Palma dos |
author_role |
author |
author2 |
Mendonca, Maria Isabel Borges, Sofia Sousa, Ana Célia Freitas, Sónia Henriques, Eva Rodrigues, Mariana Freitas, Ana Isabel Guerra, Graça Freitas, Carolina Pereira, Décio Brehm, António Reis, Roberto Palma dos |
author2_role |
author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
DigitUMa |
dc.contributor.author.fl_str_mv |
Pereira, Andreia Mendonca, Maria Isabel Borges, Sofia Sousa, Ana Célia Freitas, Sónia Henriques, Eva Rodrigues, Mariana Freitas, Ana Isabel Guerra, Graça Freitas, Carolina Pereira, Décio Brehm, António Reis, Roberto Palma dos |
dc.subject.por.fl_str_mv |
Coronary artery disease Genetic risk score Framingham score Risk prediction Risk factors . Faculdade de Ciências da Vida |
topic |
Coronary artery disease Genetic risk score Framingham score Risk prediction Risk factors . Faculdade de Ciências da Vida |
description |
The utility of genetic risk scores (GRS) as independent risk predictors remains inconclusive. Here, we evaluate the additive value of a multi-locus GRS to the Framingham risk score (FRS) in coronary artery disease (CAD) risk prediction. A total of 2888 individuals (1566 coronary patients and 1322 controls) were divided into three subgroups according to FRS. Multiplicative GRS was determined for 32 genetic variants associated to CAD. Logistic Regression and Area Under the Curve (AUC) were determined first, using the TRF for each FRS subgroup, and secondly, adding GRS. Different models (TRF, TRF+GRS) were used to classify the subjects into risk categories for the FRS 10-year predicted risk. The improvement offered by GRS was expressed as Net Reclassification Index and Integrated Discrimination Improvement. Multivariate analysis showed that GRS was an independent predictor for CAD (OR = 1.87; p<0.0001). Diabetes, arterial hypertension, dyslipidemia and smoking status were also independent CAD predictors (p<0.05). GRS added predictive value to TRF across all risk subgroups. NRI showed a significant improvement in all categories. In conclusion, GRS provided a better incremental value in intermediate subgroup. In this subgroup, inclusion of genotyping may be considered to better stratify cardiovascular risk. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018 2018-01-01T00:00:00Z 2020-11-12T15:38:43Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.13/2971 |
url |
http://hdl.handle.net/10400.13/2971 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-4685-GMB-2017-0173 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833598841033588736 |