title: Multilocus genetic risk scores for coronary heart disease prediction.
abstract: OBJECTIVE
  Current guidelines do not support the use of genetic profiles in risk assessment of coronary heart disease (CHD). However, new single nucleotide polymorphisms associated with CHD and intermediate cardiovascular traits have recently been discovered. We aimed to compare several multilocus genetic risk score (MGRS) in terms of association with CHD and to evaluate clinical use.
  
  
  RESULTS
  We investigated 6 Swedish prospective cohort studies with 10 612 participants free of CHD at baseline. We developed 1 overall MGRS based on 395 single nucleotide polymorphisms reported as being associated with cardiovascular traits, 1 CHD-specific MGRS, including 46 single nucleotide polymorphisms, and 6 trait-specific MGRS for each established CHD risk factors. Both the overall and the CHD-specific MGRS were significantly associated with CHD risk (781 incident events; hazard ratios for fourth versus first quartile, 1.54 and 1.52; P<0.001) and improved risk classification beyond established risk factors (net reclassification improvement, 4.2% and 4.9%; P=0.006 and 0.017). Discrimination improvement was modest (C-index improvement, 0.004). A polygene MGRS performed worse than the CHD-specific MGRS. We estimate that 1 additional CHD event for every 318 people screened at intermediate risk could be saved by measuring the CHD-specific genetic score in addition to the established risk factors.
  
  
  CONCLUSIONS
  Our results indicate that genetic information could be of some clinical value for prediction of CHD, although further studies are needed to address aspects, such as feasibility, ethics, and cost efficiency of genetic profiling in the primary prevention setting.
authors.affiliation: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
authors.forename: Andrea
authors.initials: A
authors.lastname: Ganna
authors.forename: Patrik K E
authors.initials: PK
authors.lastname: Magnusson
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Pedersen
authors.forename: Ulf
authors.initials: U
authors.lastname: de Faire
authors.forename: Marie
authors.initials: M
authors.lastname: Reilly
authors.forename: Johan
authors.initials: J
authors.lastname: Arnlöv
authors.forename: Johan
authors.initials: J
authors.lastname: Sundström
authors.forename: Anders
authors.initials: A
authors.lastname: Hamsten
authors.forename: Erik
authors.initials: E
authors.lastname: Ingelsson
mesh_terms: D000368:Aged; D003327:Coronary Disease / Q000175:diagnosis* / Q000453:epidemiology / Q000235:genetics*; D016002:Discriminant Analysis; D018572:Disease-Free Survival; D005260:Female; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing; D040941:Heredity; D006801:Humans; D015994:Incidence; D016014:Linear Models; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D017720:Molecular Epidemiology; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D013548:Sweden / Q000453:epidemiology; D013997:Time Factors
keywords: association studies; genetics; risk assessment; risk prediction; risk score