Table 1.

Overview of population-based gene-mapping study designs and sentinel publications

Type of Study	Noteworthy papers	Comments
Candidate gene studies	Brown et al. (1986)1 (established LDLR as a driver of cholesterol homeostasis) Cohen et al. (2005)3 (identified mutations in PCSK9 associated with LDL levels) Ioannidis et al. (2001)44 (critique of candidate gene studies and lack of replication)	Generally under-powered; hypothesis driven; often susceptible to false positives
Genome-wide association studies	Deloukas et al. (2013)28 (recent large-scale GWAS on coronary artery diseases) Willer et al. (2013)45 (recent large-scale GWAS on lipids) Stitziel et al. (2016)38 (large-scale exome based study of coronary disease)	Moderately-powered for common variants; hypothesis generating; low false positive rate; genome wide coverage of common variants
Whole-exome sequencing	Do et al. (2015)46 (exome-sequencing study on myocardial infarction) Lange et al. (2015)47 (exome-sequencing study on lipids)	Under-powered; hypothesis generating; low false positive rate; coverage of common and rare protein coding variants
Whole-genome sequencing	The UK10K project48 (whole-genome sequencing of 3,781 individuals to find rare-variants associated complex disease) The GoNL project49 (whole-genome sequencing of 250 Dutch parent-offspring families) The SardiNIA project50 (whole-genome sequencing of 2,500 Sardinians to find variants associated with longevity and related traits).	Currently under-powered; hypothesis generating; low false positive rate; genome wide coverage of common and rare variants