title: Literature-based genetic risk scores for coronary heart disease: the Cardiovascular Registry Maastricht (CAREMA) prospective cohort study.
abstract: BACKGROUND
  Genome-wide association studies (GWAS) have identified many single-nucleotide polymorphisms (SNPs) associated with coronary heart disease (CHD) or CHD risk factors (RF). Using a case-cohort study within the prospective Cardiovascular Registry Maastricht (CAREMA) cohort, we tested if genetic risk scores (GRS) based on GWAS-identified SNPs are associated with and predictive for future CHD.
  
  
  RESULTS
  Incident cases (n=742), that is, participants who developed CHD during a median follow-up of 12.1 years (range, 0.0-16.9 years), were compared with a randomly selected subcohort of 2221 participants selected from the total cohort (n=21 148). We genotyped 179 SNPs previously associated with CHD or CHD RF in GWAS as published up to May 2, 2011. The allele-count GRS, composed of all SNPs, the 153 RF SNPs, or the 29 CHD SNPs were not associated with CHD independent of CHD RF. The weighted 29 CHD SNP GRS, with weights obtained from GWAS for every SNP, were associated with CHD independent of CHD RF (hazard ratio, 1.12 per weighted risk allele; 95% confidence interval, 1.04-1.21) and improved risk reclassification with 2.8% (P=0.031). As an exploratory approach to achieve weighting, we performed least absolute shrinkage and selection operator (LASSO) regression analysis on all SNPs and the CHD SNPs. The CHD LASSO GRS performed equal to the weighted CHD GRS, whereas the Overall LASSO GRS performed slightly better than the weighted CHD GRS.
  
  
  CONCLUSIONS
  A GRS composed of CHD SNPs improves risk prediction when adjusted for the effect sizes of the SNPs. Alternatively LASSO regression analysis may be used to achieve weighting; however, validation in independent populations is required.
authors.affiliation: Molecular Epidemiology Section, Leiden University Medical Center, Leiden, The Netherlands. a.a.m.vaarhorst@lumc.nl
authors.forename: Anika A M
authors.initials: AA
authors.lastname: Vaarhorst
authors.forename: Yingchang
authors.initials: Y
authors.lastname: Lu
authors.forename: Bastiaan T
authors.initials: BT
authors.lastname: Heijmans
authors.forename: Martijn E T
authors.initials: ME
authors.lastname: Dollé
authors.forename: Stefan
authors.initials: S
authors.lastname: Böhringer
authors.forename: Hein
authors.initials: H
authors.lastname: Putter
authors.forename: Sandra
authors.initials: S
authors.lastname: Imholz
authors.forename: Audrey H H
authors.initials: AH
authors.lastname: Merry
authors.forename: Marleen M
authors.initials: MM
authors.lastname: van Greevenbroek
authors.forename: J Wouter
authors.initials: JW
authors.lastname: Jukema
authors.forename: Anton P M
authors.initials: AP
authors.lastname: Gorgels
authors.forename: Piet A
authors.initials: PA
authors.lastname: van den Brandt
authors.forename: Michael
authors.initials: M
authors.lastname: Müller
authors.forename: Leo J
authors.initials: LJ
authors.lastname: Schouten
authors.forename: Edith J M
authors.initials: EJ
authors.lastname: Feskens
authors.forename: Jolanda M A
authors.initials: JM
authors.lastname: Boer
authors.forename: P Eline
authors.initials: PE
authors.lastname: Slagboom
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000235:genetics*; D005260:Female; D005500:Follow-Up Studies; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D011446:Prospective Studies; D012042:Registries; D012307:Risk Factors; D055815:Young Adult