Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts.
<h4>Background</h4>More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain mo...
Guardado en:
| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Public Library of Science (PLoS)
2012
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/93aa9ce69c34452b95c91a1125596ec4 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:93aa9ce69c34452b95c91a1125596ec4 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:93aa9ce69c34452b95c91a1125596ec42021-11-18T07:11:12ZGenetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts.1932-620310.1371/journal.pone.0040922https://doaj.org/article/93aa9ce69c34452b95c91a1125596ec42012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22848412/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.<h4>Methods</h4>Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.<h4>Results</h4>Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.<h4>Conclusions</h4>Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.Maria F HughesOlli SaarelaJan StritzkeFrank KeeKaisa SilanderNorman KloppJukka KonttoJuha KarvanenChristina WillenborgVeikko SalomaaJarmo VirtamoPhillippe AmouyelDominique ArveilerJean FerrièresPer-Gunner WiklundJens BaumertBarbara ThorandPatrick DiemertDavid-Alexandre TrégouëtChristian HengstenbergAnnette PetersAlun EvansWolfgang KoenigJeanette ErdmannNilesh J SamaniKari KuulasmaaHeribert SchunkertPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 7, p e40922 (2012) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Medicine R Science Q |
| spellingShingle |
Medicine R Science Q Maria F Hughes Olli Saarela Jan Stritzke Frank Kee Kaisa Silander Norman Klopp Jukka Kontto Juha Karvanen Christina Willenborg Veikko Salomaa Jarmo Virtamo Phillippe Amouyel Dominique Arveiler Jean Ferrières Per-Gunner Wiklund Jens Baumert Barbara Thorand Patrick Diemert David-Alexandre Trégouët Christian Hengstenberg Annette Peters Alun Evans Wolfgang Koenig Jeanette Erdmann Nilesh J Samani Kari Kuulasmaa Heribert Schunkert Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| description |
<h4>Background</h4>More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.<h4>Methods</h4>Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.<h4>Results</h4>Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.<h4>Conclusions</h4>Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men. |
| format |
article |
| author |
Maria F Hughes Olli Saarela Jan Stritzke Frank Kee Kaisa Silander Norman Klopp Jukka Kontto Juha Karvanen Christina Willenborg Veikko Salomaa Jarmo Virtamo Phillippe Amouyel Dominique Arveiler Jean Ferrières Per-Gunner Wiklund Jens Baumert Barbara Thorand Patrick Diemert David-Alexandre Trégouët Christian Hengstenberg Annette Peters Alun Evans Wolfgang Koenig Jeanette Erdmann Nilesh J Samani Kari Kuulasmaa Heribert Schunkert |
| author_facet |
Maria F Hughes Olli Saarela Jan Stritzke Frank Kee Kaisa Silander Norman Klopp Jukka Kontto Juha Karvanen Christina Willenborg Veikko Salomaa Jarmo Virtamo Phillippe Amouyel Dominique Arveiler Jean Ferrières Per-Gunner Wiklund Jens Baumert Barbara Thorand Patrick Diemert David-Alexandre Trégouët Christian Hengstenberg Annette Peters Alun Evans Wolfgang Koenig Jeanette Erdmann Nilesh J Samani Kari Kuulasmaa Heribert Schunkert |
| author_sort |
Maria F Hughes |
| title |
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| title_short |
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| title_full |
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| title_fullStr |
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| title_full_unstemmed |
Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts. |
| title_sort |
genetic markers enhance coronary risk prediction in men: the morgam prospective cohorts. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2012 |
| url |
https://doaj.org/article/93aa9ce69c34452b95c91a1125596ec4 |
| work_keys_str_mv |
AT mariafhughes geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT ollisaarela geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT janstritzke geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT frankkee geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT kaisasilander geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT normanklopp geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT jukkakontto geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT juhakarvanen geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT christinawillenborg geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT veikkosalomaa geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT jarmovirtamo geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT phillippeamouyel geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT dominiquearveiler geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT jeanferrieres geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT pergunnerwiklund geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT jensbaumert geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT barbarathorand geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT patrickdiemert geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT davidalexandretregouet geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT christianhengstenberg geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT annettepeters geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT alunevans geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT wolfgangkoenig geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT jeanetteerdmann geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT nileshjsamani geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT karikuulasmaa geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts AT heribertschunkert geneticmarkersenhancecoronaryriskpredictioninmenthemorgamprospectivecohorts |
| _version_ |
1718423804159459328 |