Evidence map›Paper›PMID 22521901›Full record

SynthesisAtherosclerosis2012

Assessment of the value of a genetic risk score in improving the estimation of coronary risk.

Carla Lluis-Ganella, Isaac Subirana, Gavin Lucas, Marta Tomás, Daniel Muñoz, Mariano Sentí, Eduardo Salas, Joan Sala, Rafel Ramos, Jose M Ordovas and 2 more

Open access · greenAbstract readMeta-Analysis
In one paragraph

Synthesis in Atherosclerosis, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
6.0field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Cohort Profile: The Girona Heart Registry.International journal of epidemiology · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Genetic Risk Score for Coronary Heart Disease: Review.Journal of personalized medicine · 2020
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 5 institutions in 2 countries.

Carla Lluis-GanellaCardiovascular Epidemiology and Genetics, IMIM, Barcelona, Spain.
Isaac Subirana
Gavin Lucas
Marta Tomás
Daniel Muñoz
Mariano Sentí
Eduardo Salas
Joan Sala
Rafel Ramos
Jose M Ordovas
Jaume Marrugat
Roberto Elosua
Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública · ESHospital Universitari de Girona Doctor Josep Trueta · ESPompeu Fabra University · ESTufts University · USUniversity of Girona · ES

Funding

GENE/DIET EFFECTS ON PLASMA LIPOPROTEIN LEVELSR01HL054776 · NHLBI · TUFTS UNIVERSITY BOSTON · PI ORDOVAS, JOSE M. · 1996 to 2010
$2.6M
PAT PROTEINS: GENE-DIET INTERACTIONS OBESITY RISK AND HEALTHR01DK075030 · NIDDK · TUFTS UNIVERSITY BOSTON · PI ORDOVAS, JOSE M. · 2007 to 2009
$989k
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS HL-54776NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01-HC-25195NHLBI NIH HHS N02 HL064278NHLBI NIH HHS R01 HL054776NIDDK NIH HHS DK075030NIDDK NIH HHS R01 DK075030
6 · The paper itself

Abstract

backgroundThe American Heart Association has established criteria for the evaluation of novel markers of cardiovascular risk. In accordance with these criteria, we assessed the association between a multi-locus genetic risk score (GRS) and incident coronary heart disease (CHD), and evaluated whether this GRS improves the predictive capacity of the Framingham risk function. METHODS AND

resultsUsing eight genetic variants associated with CHD but not with classical cardiovascular risk factors (CVRFs), we generated a multi-locus GRS, and found it to be linearly associated with CHD in two population based cohorts: The REGICOR Study (n=2351) and The Framingham Heart Study (n=3537) (meta-analyzed HR [95%CI]: ~1.13 [1.01-1.27], per unit). Inclusion of the GRS in the Framingham risk function improved its discriminative capacity in the Framingham sample (c-statistic: 72.81 vs.72.37, p=0.042) but not in the REGICOR sample. According to both the net reclassification improvement (NRI) index and the integrated discrimination index (IDI), the GRS improved re-classification among individuals with intermediate coronary risk (meta-analysis NRI [95%CI]: 17.44 [8.04; 26.83]), but not overall.

conclusionsA multi-locus GRS based on genetic variants unrelated to CVRFs was associated with a linear increase in risk of CHD events in two distinct populations. This GRS improves risk reclassification particularly in the population at intermediate coronary risk. These results indicate the potential value of the inclusion of genetic information in classical functions for risk assessment in the intermediate risk population group.

Indexed as

Genetic VariationMultilocus Sequence TypingAdultAgedBiomarkersBlood PressureCoronary DiseaseDiscriminant AnalysisFemaleGenetic Predisposition to DiseaseGenetic TestingHumansIncidenceKaplan-Meier EstimateLinear ModelsMaleBiomarkers

Identifiers

PMID22521901
PMCPMC3697002
OpenAlexW2058328790

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.